Knowledge Transfer at Saudi Aramco Dissertation

Introduction and Background

Knowledge is considered a critical success factor for service-oriented and manufacturing-based organizations and economies (Brčić & Mihelič, 2015). Indeed, today, many organizations understand the importance of intellectual capital as a strategic resource for modern-day economies. Thus, a company’s ability to generate, share and preserve intellectual capital is deemed an area of strategic competitive advantage (Francesca, 2017; Argote, 2012). To capitalize on the strengths and importance of knowledge to modern societies, companies need to ensure it is freely shared through knowledge sharing.

Knowledge exchange is an independent discipline that falls under the concept of intellectual capital management (Brčić & Mihelič, 2015). Such systems exist because intellectual capital is commonly confined within specialized domains. Different researchers have unique conceptions of the concept; however, most of them agree that it refers to the provision or receipt of information relating to a specific organizational task (Argote, 2012; Brčić & Mihelič, 2015). Others say it refers to the sharing of information relating to organizational expertise, or the generation and use of feedback pertaining to a specific product or service (Francesca, 2017; Argote, 2012).

Simar and Rahmanseresht (2017) say that companies, which have managed to narrow their knowledge gaps are able to deliver superior value to their customers, while those that are unable to do so constantly have to recruit and train new talents – a process which leads to significant cost increments, lack of innovation, and poor service delivery. Thus, the ability of organizations to thrive in the wake of a highly competitive “knowledge industry” comes from their ability to use traditional resources in new ways (Simar & Rahmanseresht, 2017). Relative to this discussion, knowledge resources empower organizations to boost their key competencies in ways that they would otherwise be unable to, had they lost the vital resource. The same knowledge reservoir allows them to improve their competitive position in the marketplace by maximizing the value of their resources. Based on these discussions, the management of an organization’s intellectual capital is largely intended to improve its competitive position. Such an advantage would enhance an organization’s strategic position and maximize its resource capabilities as well (Simar & Rahmanseresht, 2017).

The need for intellectual capital management, as a key organizational process, partly comes from the understanding that in today’s information-centered and global economy, traditional factors of production are equally important as what employees know (Argote, 2012; Brčić & Mihelič, 2015). In other words, resource capabilities should be understood to have the same power as knowledge capabilities. Thus, prosperous companies in the 21^st century are not only those which have the best access to land, factories and similar resources, but also those that are able to organize their knowledge management systems effectively.

Simar and Rahmanseresht (2017) support this fact by saying that some organizations have failed to attain their goals not because of their inability to access natural resources, but because of their inability to acquire, organize and transfer knowledge. Furthermore, based on the same assessment, it has been established that most companies, which are successful at managing their knowledge platforms have a higher probability of outwitting their competitors through the adoption of superior operational practices (Meier-Comte, 2012). This statement is further augured with the success of some organizations, which have adopted total quality management (TQM) concept, which postulates that all employees of an organization should always maintain a high standard of operation for their activities. TQM is often safeguarded through succinct knowledge management processes that sometimes involve sharing the same resource. Collective learning processes and system engineering techniques are also aimed at improving organizational activities because they are often hinged on knowledge-based resource systems that generate enviable competitive advantages for companies (Simar & Rahmanseresht, 2017). However, it is equally important to point out that some firms prefer to use centralized knowledge management systems as opposed to shared ones. For example, those that are associated with sensitive matters prefer this system to the shared one.

There are different types of knowledge shared across various organizational platforms. However, as Fawzy (2013) points out, the information shared is either explicit or tactical. Regardless of the typologies mentioned, managers are starting to acknowledge the need for knowledge sharing as a key organizational process because they say it is critical in transforming individual data into organizational resources (Fawzy, 2013). This fact is supported by several studies, which show that knowledge sharing leads to intellectual capital creation and idea generation (innovation) (Fawzy, 2013; Francesca, 2017; Argote, 2012). Other studies have shown that it leads to improved problem solving (Argote, 2012; Brčić & Mihelič, 2015). These findings have prompted many observers to contend that the process of sharing intellectual capital resources is a key ingredient in achieving innovation within different organizational departments (Fawzy, 2013). Other studies have associated it with team creativity and ultimately, improved organizational performance (Brčić & Mihelič, 2015).

Managing an organization that has different groups of employees may lead to conflicts and disagreements that would eventually hinder organizational productivity. In some firms, knowledge gaps are linked with knowledge-based complexities that hinder the decision-making process, making it slower and inefficient (Saleh, 2012; Shaw, 2013). However, in others, there is a conscious decision not to share information because of the nature of operations, or any other issue relating to their performance. For example, knowledge gaps in the army are deliberately created. Therefore, discretion is often applied when managing knowledge in such contexts. It is also common to find these kinds of problems occurring simultaneously in environments characterized by significant knowledge gaps.

In extreme situations, this problem could lead to the failure of organizations to distinguish between interpretive failures and information shortcomings associated with decision-making procedures and company processes (Simar & Rahmanseresht, 2017). Here, knowledge sharing emerges as a dynamic process that requires vibrant interactions among different cadres of employees. Based on this understanding, it is important to understand the main drivers of this process and the influence of micro-level constructs of intellectual knowledge resource management on organizational outcomes.

The focus on micro-level constructs of knowledge management is deliberately selected as the premise for this paper because past research studies have often concentrated on macro-level constructs, such as dynamic capabilities and absorptive capacities, when investigating knowledge management. These macro-level attributes are often executed at a firm level and could be argued to be “out-of-touch” with some subtle aspects of operational performance, such as how employees interact with each other. Indeed, it is further argued by some observers that macro-level constructs are not firmly entrenched in micro-foundations of knowledge management (Francesca, 2017).

As mentioned earlier, micro-level foundations largely refer to the actions and interactions among individuals in an organization. They may include team-building efforts, the nature of employee relations with their supervisors, decision-making procedures, and worker appraisal processes among others (Francesca, 2017). These micro-level processes often underpin the knowledge management process. The failure of past researchers to pay attention to this important area of study in knowledge management has led many of them to question their origins and foundations. Therefore, the focus on micro-level constructs for understanding knowledge management is a different approach for investigating knowledge sharing and outlines the basis for which this study is premised on. Based on the understanding that micro-level constructs of knowledge management place workers at the center of knowledge management, differences between unique cadres of workers become central to understanding how knowledge is shared.

One of the most notable challenge organizations experience today when trying to understand knowledge sharing is comprehending the knowledge gap that exists between older and younger employees (Saleh, 2012). These two groups of workers denote the differences in intellectual capital between different generational cohorts. Indeed, researchers have observed that the seamless transfer of knowledge between different generations of workers is important in the realization of organizational success (Saleh, 2012). Pieces of evidence that support the above assertion point out to the possibility of cross-generational conflicts that could limit knowledge transfer (Shaw, 2013). Such conflicts could emerge from differences in beliefs, values, and attitudes about life (between the young and the old) that could ultimately influence how they carry out their work, or interact.

Indeed, although many organizations spend a lot of time and resources in trying to realize diversity within their workforce, with most attempts (at fostering diversity) being focused on realizing ethnic and gender differences, generational diversity has been relatively unexplored. Indeed, as Shaw (2013) points out, most organizations are struggling to balance the different needs and working styles associated with varied cohorts of employees. Contrary to the general expectation that managers should try to align the needs of these groups of employees with an organization’s needs, most of them have left workers to figure out this problem by themselves. Although most observers regard differences in inter-generational styles as a serious issue, they tend to hinder team performance, thereby leading to frustration, conflict and poor performance (Saleh, 2012; Shaw, 2013).

Underlying the problem is a general understanding of how younger and older employees think. Many studies have tried to investigate these differences with three main ideologies representing groups of workers dominating most literatures. The first group of workers is the baby boomer population, which includes employees who were born between 1946 and 1964 (Acton, 2012). This population is often pitted against generation X, which is comprised of employees who were born in the 1965s and 1980s. The last group of workers is the millennials (or generation Y), which is comprised of employees born between 1980 and 1999. Research has pointed out that these groups of employees have different work practices that could be analyzed differently, based on their views, beliefs and values about work (Liebowitz & Frank, 2016).

Although the differences among these groups of workers will be further explored in the next chapter, Saleh (2012) says one argument touted by the “baby boomer” population against “Generation X” is the failure of the latter to use time-tested strategies because of their perceived lack of patience. Another belief about “Generation X,” cited in some literatures, is that they are often self-absorbed and too “spoilt” to appreciate what is around them (Liebowitz & Frank, 2016). Comparatively, the “Generation X” see the “Baby boomers” as being too rigid to change (Saleh, 2012; Shaw, 2013). In other words, some of them say that the latter are “out of touch” with reality, because they are set in their ways too much to notice that they could do things in a better and more efficient way (Saleh, 2012; Shaw, 2013).

An abundance of evidence shows how different generational cohorts have varied experiences and knowledge about organizational processes (Saleh, 2012; Shaw, 2013). These knowledge gaps are detrimental to organizational sustainability because they could cause several problems, such as poor communication between different levels of employees and poor work coordination (just to mention a few) (Saleh, 2012; Shaw, 2013). These problems often arise because of divergent views and intellectual misinterpretations that could occur when different cadres of employees analyze the same sources of information (Simar & Rahmanseresht, 2017).

This study takes a keen look at how individual factors influence knowledge sharing in one organization – Saudi Aramco. Saudi Aramco is an energy company in Saudi Arabia. Its operations are mostly concentrated in the energy sector, with some literatures showing that its key focus is in the petroleum industry (IBP, Inc., 2015). A few of the main initiatives of the firm include optimizing the organization’s processes, building its capabilities, growing the business, and engaging the kingdom (Saudi Aramco Inc., 2015). Saudi Aramco has not had a long history of knowledge management; in fact, it only recently adopted the operational excellence management system in 2013 (Saudi Aramco Inc., 2015). After this process, all subsidiaries of the organization are supposed to operate under this banner. The company specifically operates operational excellence 12.7, which relates directly to knowledge transfer (IBP, Inc., 2015). However, this platform has not solved the knowledge gap problem between the young and older workers. This is an issue for the organization because it seeks continuity for all its workers. Details about this problem are explained in the section below.

Research Problem

After the Second World War, oil was discovered in Saudi Arabia. At the time, an American company known as Chevron dominated the global oil exploration business (OBG, 2013). This company partnered with Texaco to form what is known today as Saudi Aramco (OBG, 2013). The company’s name was simply an acronym for the Arabian American Oil Corporation. When there was a global trend to nationalize companies in the 1980s, the Saudi Arabian government bought the company’s assets and eventually controlled its majority shares (OBG, 2013). However, most of the organization’s employees were maintained from the traditional organizational structure (OBG, 2013). For more than three decades, there has not been any substantial change of key workers in the organization. This is a problem because most of the original employees are due for retirement. Based on this issue, Saudi Aramco, has experienced many challenges in its operations, including (but not limited to) poor trust in business, sustainability challenges, corporate brand and reputation issues, geopolitical/economic risk management, customer relation problems, inadequate innovation, operational excellence challenges and human capital problems (Saudi Aramco Inc., 2015).

Although the aforementioned factors affect the company’s operations, human capital problems emerge as the top concern for the firm because there is a growing body of ageing workers who do not interact openly with their younger counterparts (OBG, 2013). This concern has inhibited the realization of one of the main objectives of Saudi Aramco, which is to develop a reliable workforce that could meet the evolving technical and technological needs of its petroleum engineering processes (OBG, 2013). This is also a problem shared by most petroleum and gas companies in the kingdom because the Saudi Arabia Oil and Gas (2017) says many of such firms experience a looming problem in their human resource strategies because they lose well-trained, technically experienced, and skilled personnel because of retirement.

Many employees who work in Saudi Aramco were employed after a successful hiring campaign in the 1980s that saw many of them secure lucrative employment opportunities in the organization when the prices of oil was high (USA International Business Publications, 2015). The impending retirement of most of these workers from the workforce has made it imperative to develop a knowledge transfer program that would see older workers transfer useful technical information to the younger workers.

The knowledge gap present at Saudi Aramco is mostly characterized by the presence of a significant knowledge gap between employees who have worked for more than 23 years and those who have worked for less than a decade. Those who have worked for more than 23 years have a significantly higher level of knowledge compared to those who have worked for less than ten years.

The main problem experienced at Saudi Aramco is the lack of a knowledge transfer mechanism that would allow the organization to function properly in the event that many of its experienced employees retire at once. This issue could be problematic for the organization because it would signify a loss in knowledge that could impede the organization’s operations (OBG, 2013). This issue highlights the need for the oil company to preserve the intellectual capital resources of the organization because its operational practices require technical expertise that rests with those who have worked in the organization for a long time.

Underlying this problem is the risk that most employees who will leave the organization will take vital knowledge with them (USA International Business Publications, 2015). This risk could come at a huge cost to the firm because it has spent a lot of time and resources nurturing and teaching existing employees how to conduct critical knowledge processes in the company. To meet the challenges that bedevil the organization, there needs to be a sound plan of knowledge transfer between older and younger workers.

Purpose of Research

This study is designed to understand the predictors of knowledge sharing in Saudi Aramco and to emphasize the relevance of knowledge sharing across different employee groups that work in the oil company. Indeed, knowledge sharing could happen across different employee groups that could be divided along team lines, age differences, roles, responsibilities and other measures of organizational functions. The focus of this study will solely be on intra-organizational knowledge sharing and will emphasize on understanding the individual factors that influence knowledge sharing in the organization. This study would also strive to understand the level of employee satisfaction regarding the quality and quantity of information being transferred from older employees to the younger ones. Getting such information from workers could allow the organization to improve its formal knowledge transfer programs, such as the virtual reality tool, which allows younger workers to learn and understand the company’s plants (Saudi Aramco Oil Co., 2017).

Importance of Study

As mentioned in this paper, knowledge is increasingly emerging as an important resource for most organizations. In fact, some of the research studies reviewed in this document show that it constitutes among the most critical tools for improving an organization’s competitive advantage (Simar & Rahmanseresht, 2017; Argote, 2012; Brčić & Mihelič, 2015). Although its importance is rarely disputed, unless knowledge is shared freely among employees, organizations would be limited by their inability to exploit their potential for maximizing their intellectual capital. Of particular importance to this study is the need to understand how knowledge is shared across different generational cohorts at Saudi Aramco. This view is vital to the sustainability of the company because older employees are supposed to share their intellectual resources with their younger counterparts.

This study would take a keen look at how individual factors influence knowledge sharing in the organization. The individual factors include willingness to share information, motivation to share data, the quality of knowledge people are willing to share, and the level of collaboration people foster when doing so. Part of the study would also seek to understand the perceptions of the quality and quantity of information shared across cross-generational relationships. Therefore, the study would help in preserving the institutional memory of long-term employees and help transfer the same knowledge to newer workers. This analysis would help Saudi Aramco to store or preserve the knowledge held by their most experienced employees before they leave the organization.

The need to fill the knowledge gap in the Saudi-based oil company has been supported by many researchers, such as Francesca (2017), who say that the failure to do so is akin to dismantling an organization’s knowledge and intellectual assets. Here, knowledge is not conceived to be a product that could be packed and distributed, but a resource that should be shared. The transfer of current knowledge to new employees and the process of generating new ones are derived from the interaction between older and younger workers in the organization. If left unaddressed, the differences between both sets of employees could significantly affect how the organization operates (Simar & Rahmanseresht, 2017). Concisely, similar to how organizations have improved ethnic and gender diversity in their workplaces to increase their productivity, filling the gap that exists between the aforementioned groups of employees could yield the same outcomes.

Research Statement

The aim of this research is to bridge the knowledge gap at Saudi Aramco. The research goals are as described below.

Research Goals

• To provide an inventory and catalogue of Saudi Aramco’s critical activities
• To determine the risk of loss of critical knowledge, skills and behaviors at Saudi Aramco
• To prepare Saudi Aramco to minimize its knowledge gaps
• To establish knowledge transfer relationships between knowledge providers and knowledge recipients at Saudi Aramco
• To develop knowledge transfer plans for identifying at risk knowledge at Saudi Aramco

The aforementioned goals are attached to specific objectives, which are to be pursued in the study. The objectives appear below.

Research Objectives

• To identify at-risk critical activities (knowledge)
• To identify employees who have knowledge and experience of value (knowledge providers)
• To transfer knowledge as efficiently and as effectively as possible to those who need it (knowledge recipients)

Guiding the research will be a set of questions that appear below.

Research Questions

• What are Saudi Aramco’s critical activities?
• Which employees of Saudi Aramco have the knowledge and experience of value?
• What is the nature of knowledge transfer relationships between knowledge providers and knowledge recipients at Saudi Aramco?
• How could Saudi Aramco bridge the knowledge gap between the older and younger employees?

Research Hypotheses

• H1: Critical activities have an effect on knowledge transfer.

Ho: Critical activities do not affect knowledge transfer

• H2: Risk of loss has an effect on knowledge transfer.

Ho: Risk of loss has no effect on knowledge transfer

• H3: Communication skills have an effect on knowledge transfer.

Ho: Communication skills have no effect on knowledge transfer

• H4: Culture has an effect on knowledge transfer.

Ho: Culture has no effect on knowledge transfer

• H5: The demographic information (gender, age, nationality, educational level, work field, work experience, job position, and training) have statistically significant differences on Knowledge Transfer.

Ho: The demographic information has no effect on knowledge transfer

Expected Outcomes

The expected outcomes of the research are as follows:

• To create a cost-effective process to develop and retain talent at Saudi Aramco
• To preserve the institutional memory of long-time employees and transfer that knowledge to younger workers
• To store and transfer the lessons learned from experienced workers before they leave employment

Dimensions That Would Be Explored In the Research (Scope of Research)

Some key dimensions of knowledge management that would be explored in this study include the nature of relationships between older workers and newer employees at Saudi Aramco, knowledge transfer structures in the organization, and critical activities that are susceptible to the loss of vital knowledge in the company. These dimensions of research will address the main tenets of intellectual capital resource management in the organization, as proposed by Argote (2012).

This study will be different from many others that have investigated knowledge sharing in organizations because the above dimensions of study focus on micro-level constructs of the same issue, as opposed to macro-level constructs which have been highlighted in other studies. Four micro-level constructs will guide the researcher – willingness to share information, communication structures for sharing information, motivation to share data, and collaboration among employees when sharing knowledge. These four concepts of individual interactions define the scope of this study because they are the main catalysts of knowledge sharing in organizations (Francesca, 2017; Argote, 2012). The scope of this study would also be limited to intergenerational knowledge transfer in one organization – Saudi Aramco.

Significance of the Research

The findings of this study will be important to the prosperity of Saudi Aramco because they could create an emphasis on employee development in the organization. Similarly, the knowledge that will be derived from this study will be instrumental in creating cost-effective processes to develop or retain talent. This way, Saudi Aramco will be better placed to preserve its institutional memory. At the same time, it will be in a position to transfer the same knowledge to newer workers effectively. Thus, it would be possible for the company to store and transfer the knowledge held by their most experienced employees before they leave the organization.

The findings of this study will not only be useful in minimizing the knowledge gap that exists in the organization, but also align individual and company goals. This way, there will be a greater focus on job-specific development and a preservation of the critical knowledge present in the organizations. Moreover, through the process, there would be a greater facilitation of efficient and effective job-specific development in the firm.

By adopting some of the recommendations outlined in this study, Saudi Aramco could also meet its short-term and long-term goals. The short-term goals include an improvement in the speed and ease through which it could undertake knowledge transfer, and an increased level of efficiency for improving existing communication styles and network operations. Other short-term goals that could be experienced by the company include improving work effectiveness in the organization (such as improved problem solving), encouraging more innovative and out-of-the-box thinking and the prevention of a “re-invention of the wheel” because younger employees would be learning from the older ones. Some long–term goals that could be enjoyed by the organization include inculcating knowledge transfer in the company’s culture and allowing knowledge management to constitute an organization’s key functions.

Definition of Terms and Key Concepts

• Knowledge – employee skills and experiences
• Knowledge Gap – The difference between what an organization can do and what it is required to do, relative to knowledge management
• Knowledge Management – The art of managing knowledge
• Knowledge Transfer – The art of exchanging knowledge among different groups of workers
• Generational Cohort – A group of workers defined by an age group
• Intellectual Capital – The intangible operational resources of an organization

Literature Review

This chapter contains a review of what other researchers have written about the research issue. In this section of the document, evidence would be provided to show how specific theories and models of knowledge management apply to the research topic and how they align with the research goals. The conceptual framework of these discussions appears below.

Conceptual Framework

Recent studies have departed from the conventional definitions of knowledge and focused on the relational nature of the concept. According to the latter view, knowledge should not only be transferred from a selected group of employees to another, but also be used to create value in an organization (Jasimuddin, 2012). In this regard, intellectual capital management emerges as a process of wanting to know more (Jasimuddin, 2012). This reasoning is regarded as the occupational community perspective and has been widely used in understanding the social and situational context of knowledge management (Abbott, 2016; King & Lawley, 2016). Within the same framework, social interaction within communities could be widely perceived as the main context, or platform, through which knowledge sharing takes place.

The occupational community perspective does not only regard intellectual capital management as a process that occurs at a social and actionable level, but also at a personal level. The focus on the micro-level interactions gives us an in-depth insight into the knowledge processes that characterize the relationships people or organizations build within this system. As Simar and Rahmanseresht (2017) observe, the focus on alliance building as a unique level of knowledge management system tends to focus on knowledge management at organizational levels. Nonetheless, this analysis has also included the role of interpersonal relationships within the wider structure of knowledge management. While different studies have shown that knowledge management occurs at organizational levels, knowledge sharing tends to be more profound at an interpersonal level (Simar & Rahmanseresht, 2017). Haider and Mariotti (2017) support this assertion by saying that informal contacts were instrumental in gaining access to information that would otherwise not be available in the public domain. Haider and Mariotti (2017) also add that the exchange of information across different organizations mostly occurs through informal contacts.

The conceptual framework for this study will be based on the processual approach of knowledge management to understand how to fill knowledge gaps between different groups of employees. Jasimuddin (2012) defines process as that which involves the spread of information sharing activities over a specific period. Abbott (2016) takes a different stand on the issue and says that process refers to a specific focus on complex organizational activities that occur over a specific time. Organizational phenomena categorized this way include (but are not limited to) cultural exchanges, decision-making processes, and structural change processes (Jasimuddin, 2012). Many research studies have evaluated this conceptual framework by paying a close attention to the nature of interactions among different stakeholders as a measure of how they exchange knowledge and interact with each other (Abbott, 2016; King & Lawley, 2016). Although many processual analyses use time as the main unit of analysis, the process does not only stop at this point of analysis; instead, it extends to the conceptualization, analysis, and description of events or activities in an organization that fall within the context of knowledge management. The basic nature of the processual approach of knowledge management is the understanding that social interactions and knowledge management often occur across a specified time. Here, the period taken for knowledge exchange to occur and context, which this process occurs, are at the center of all social interactions that lead to knowledge exchanges (King & Lawley, 2016). The uniqueness of this approach is temporality, which makes it unique from other frameworks of analysis.

The driving assumption behind this conceptual framework is the understanding that social interactions often occur dynamically and not necessarily in a steady manner. From an organizational perspective, this conceptual framework recognizes the duality of agency and context when investigating knowledge transfer issues. This analysis shows that contexts have always shaped the nature of knowledge transfer, while actors are often producers of the same process. This same analysis shows that actions are the main drivers of the processes that lead to knowledge exchange. However, at the same time, the entire chain cannot only be explained by the actions of one individual. Within this analysis, people’s actions are viewed within varied, but specific, contexts that ultimately limit the kinds of information that could be exchanged. The insight and influence of information processing are also limited by the same context. The social interaction that occurs between agents and their operational context is often analyzed through a cumulative process. Although the field of processual analysis is still young and the boundaries of analysis not clearly defined, the case study approach has been commonly accepted in current research analysis because it focuses on issues and events that are integral to the understanding of a research phenomenon. This approach is also adopted in this study.

What Is Knowledge?

The historical understanding of knowledge is shaped by the work of different scholars, poets, and academicians. For example, Ferdowsi and Francis Bacon, who are well-known poets, have explained knowledge in artistic contexts, such as poems, songs and other diverse literary works (Simar & Rahmanseresht, 2017). Some literatures also point out that there was a time people were often defined by the kind of knowledge they had (Schiedat, 2012; Ray, 2013). Simar and Rahmanseresht (2017) investigated the concept of knowledge and said that it has undergone a metamorphosis that is characterized by three evolutionary phases.

The first phase is one that took place before 1700 A.D. During this period, there was a general attitude among managers that meant that knowledge should be substituted for wisdom and enlightenment should be pursued at all times (Simar & Rahmanseresht, 2017). The second phase occurred between 1700 and 1800 A.D (Simar & Rahmanseresht, 2017). This era heralded a period where technology was pursued as the main basis of knowledge creation. This phase also heralded a stage in knowledge development where there was the systematic organization of knowledge and a resurge in the importance of setting goals to guide the process (Schiedat, 2012; Ray, 2013). The third phase of understanding knowledge happened in 1800 A.D where some researchers used scientific management principles to improve the discipline (Schiedat, 2012; Ray, 2013). These principles were meant to consolidate employee skills and experiences.

Before the post-modernist era of managing intellectual capital, managing knowledge was a concept mainly sourced from the tangible assets of an organization, such as cars, inventory, machinery and equipment (just to mention a few) (Schiedat, 2012). Most researchers termed these sources, associated with the generation of intellectual capital, as having structure and tangibility. They were also synonymously referred to as hard capital (Simar & Rahmanseresht, 2017). However, in today’s economy, the intangibility of a resource is as important as the need for having tangible resources (Ivey, 2014). Such intangible resources include organizational culture, process systems, effective teamwork, and innovative networks (Ivey, 2014). Nonetheless, researchers agree that the concept of knowledge management stems from three key resources. The first one is religion and philosophy, which helps to comprehend the nature and role of knowledge. The second origin of the concept comes from psychology, which has helped to understand the role of knowledge in organizational behavior. The third root of the concept is economics and social sciences, which have helped researchers to understand the role of knowledge in the workplace (Simar & Rahmanseresht, 2017).

Types of Knowledge

There are two main types of knowledge highlighted by several research studies, which have explored knowledge gaps in organizations – explicit and tacit knowledge. They are discussed below:

Explicit Knowledge: Explicit knowledge is both qualitative and quantitative, in the sense that it can be described both numerically and using words. Explicit knowledge can also be easily shared across several platforms and in different forms, including files and videos (Simar & Rahmanseresht, 2017; Argote, 2012).

Tacit Knowledge: Tacit knowledge differs from explicit knowledge because information is often acquired through employee experiences. Such information is often not freely available for transfer because it is still held by individuals and has not been recorded or documented. Some forms of tacit knowledge that could manifest in organizations include information that is obtained from having good competence, decision-making skills, work ethics, social networks, and values (Simar & Rahmanseresht, 2017; Argote, 2012).

Knowledge Management Gaps

According to Allen and Beech (2013), knowledge gaps refer to “demarcate absences” (p. 56). Generally, they yield to adverse organizational outcomes, which signal a weakness on the part of the knowers and, by extension, a lack of ideas, practices and networks within an organization that lead to the negative outcomes in the first place. Since ideas, practices and knowledge are among the main constituents of an effective knowledge system, the lack of these attributes means certain domains would be inaccessible. The actor-network theory affirms this assertion through a statement shared by Allen and Beech (2013) which says, “Knowledge gaps are domains unpopulated by different actors, where enrollment becomes a practical impossibility because there is nothing or no one to enroll” (p. 13). The social network theory is also applicable here because it shows that knowledge gaps are symbols of structural holes in the organization (Brčić & Mihelič, 2015). In other words, they delineate paths of greatest resistance and by virtue of doing so; they divert an organization’s resources to paths that have the least resistance. This statement means that institutional arrangements are reinforced and the status quo prevails, or questions about what could be of an organization left unanswered. Based on this assertion, knowledge gaps emerge as latent structures of different organizations. On one hand, they facilitate knowledge exchange in specific company domains and on the other hand, they foreclose possibilities in other organizations (Allen & Beech, 2013).

Based on the above assertions, knowledge gaps appear as social products that have a profound social effect on the society. In principle, both of these effects are measurable and identifiable. Nonetheless, as Allen and Beech (2013) point out, knowledge gaps are also social processes. In other words, they are shaped by human practices and interactions. Organizational practices and institutional pressures also affect the same gaps. Although these elements are variable, they are not evenly distributed in different social contexts. Therefore, in addition to describing the social features of these knowledge gaps, as highlighted by the social exchange theory, it is equally important to explain their distribution across knowledge systems, relative to the processes that lead to their creation.

Generally, knowledge management gaps often exist when there is a difference between what organizations can do and what knowledge management systems help them to achieve. Different studies have come up to explain the concept. The most notable one is by Simar and Rahmanseresht (2017), which defines the knowledge gap as what a company should do and can do with respect to knowledge management.

Some studies point out that the main types of knowledge gaps are socioeconomic and socio-specific. Tofanelli (2012) says some of the intellectual capital gaps seen in today’s organizations result from infrastructural gaps. Additionally, he says that the main effect of these infrastructural gaps is the inability for organizations to develop effective systems for managing knowledge (Tofanelli, 2012). King and Lawley (2016) add to this conversation by saying that knowledge gaps often suffice when organizations do not understand how to bridge the gap that exists between the processing and demand for current knowledge. Simar and Rahmanseresht (2017) also adopt the same approach by saying that this gap exists as the qualitative and quantitative difference between existing and required knowledge.

Although the above-mentioned researchers have different conceptualizations of what knowledge gaps entail, they generally agree that the gaps stem from four areas of operational management – strategy, planning, implementation, and perception. Cumulatively, the researchers point out that the failure to recognize these knowledge gaps could have significant consequences for organizations because they would be engaging in a process that is flawed, relative to the problems they will experience in the implementation stage (Simar & Rahmanseresht, 2017). Therefore, it is important to engage in different knowledge management processes, such as a requirement analysis and a risk management process, before designing or implementing knowledge management systems.

Types of Knowledge Gaps

Discussions about existing types of knowledge gaps have arisen from studies that have tried to explain how employees interact with one another (socially) to acquire new knowledge or retain existing ones. Nonetheless, it is important to understand these intellectual capital gaps because studies have shown that they are vital to the sustainability of organizations (King & Lawley, 2016; Tofanelli, 2012). A study done by Kriesi (2012) to identify the main types of intellectual capital gaps through a succinct processual review, established that there were five main types of knowledge gaps. These gaps address different intellectual capital management requirements that are central to this analysis. They are further explored below.

Physical Capital Knowledge Gaps:Physical capital gaps stem from knowledge types that are related to managing capital resources, such as the traditional factors of capital (Kriesi, 2012). Within this analytical scope, Kriesi (2012) says this knowledge gap could occur if some employees do not understand how to operate machinery, how to draw operational plans, or how to make use of existing tests required in their operational plans.

Intellectual Capital Knowledge Gaps: This category of knowledge gap refers to organizational skills that are needed to implement specific aspects of a company’s management strategy (Kriesi, 2012). Handzic and Bassi (2017) add that this type of gap emerges when there is a lack of operational skills to support management expertise. Some aspects of organizational plans that could be affected by the lack of proper organizational skills include how to manage operations, how to make decisions, and how to solve problems (Handzic & Bassi, 2017). The most important aspect of intellectual capital knowledge gap is the realization that the knowledge gap exists in the first place (Kriesi, 2012).

Relationship Management Knowledge Gap: This type of knowledge gap often exists in organizations that are service-oriented because research shows that organizations that treat their customers poorly often suffer from this type of knowledge gap (Handzic & Bassi, 2017). Poor relationships within markets, contractors and subcontractors are also other symptoms of the existence of the knowledge gap. Simar and Rahmanseresht (2017) add that this gap does not only affect how organizations maintain existing relationships with their clients, but also how they could forge new ones with others.

Social Capital Knowledge Gap: This type of knowledge gap often thrives when organizations do not have a proper understanding of how to develop trust or trustworthiness with their business partners or customers (Ngeloo, 2017). How organizations treat their partners, the kinds of roles and responsibilities they assign them and the kind of independence they give them to carry out these duties partly contribute to the creation of these knowledge gaps (Simar & Rahmanseresht, 2017). Based on the key areas which this knowledge gap affects, organizations which tend to rely on successful partnerships for their success tend to be most affected (Ngeloo, 2017). One interesting angle to this analysis is that the knowledge gap also relates to the need for organizations to manage their intellectual capital management challenges by understanding their localized employee relationships. Simar and Rahmanseresht (2017) have also included this gap in their research by saying that organizations often learn from their experiences with other organizations when forging new relationships with others. This way, the social capital gap decreases.

Cultural Gap: As its name suggests, the cultural gap often arises when organizations fail to understand how to navigate through a multicultural business environment (Meier-Comte, 2012). In this regard, there is a problem associated with the improvement of work practices, especially in environments where organizations want to change their culture. This gap is likely to affect different management techniques applied in organizations, such as teamwork and problem solving initiatives. According to Simar and Rahmanseresht (2017), different organizations fill the above knowledge gaps by undertaking unique knowledge processes. Some of them include collaborating with other firms, improving internal knowledge management systems, and disseminating knowledge to concerned parties (Simar & Rahmanseresht, 2017).

Knowledge Gap Model

The knowledge gap model adds to our understanding of knowledge as a critical organizational resource. It presupposes that knowledge is a type of wealth, which is unevenly distributed among people of higher and lower socioeconomic status (Sloan, 2014). In other words, it argues that as information slowly diffuses to the society through different modes (such as mass media and word of mouth communication), people of higher socioeconomic status tend to acquire it faster than people of lower socioeconomic status do (Sloan, 2014). Thus, the knowledge gap between these two segments of the population tends to increase (Ray, 2013).

The same phenomenon also happens in organizations because studies show that cohorts of employees acquire and process knowledge differently (Ray, 2013). If we use the above example, we find that managers are the same as people of higher socioeconomic status who tend to acquire knowledge faster than people of lower socioeconomic status (who could be likened to lower level employee groups). This knowledge gap model was introduced in the 1970s, and it has been implicitly used throughout mass communication literature (Brčić & Mihelič, 2015).

In the mid-1970s, there were attempts aimed at refining this model because different researchers, such as Donohue, Tichenor, and Olien, were interested in understanding how to eliminate this knowledge gap, or even to attenuate it (Ray, 2013). To this extent of interest, they started investigating national data related to understanding how to weaken knowledge gaps. Their investigation pointed out that three ways could be used to eliminate the knowledge gap and they include an increased awareness of the intellectual capital gap, decreased levels of social conflict brought about by the issue, and the level of homogeneity in a community (Ray, 2013). From these findings came the developments of the knowledge transfer triad, which is comprised of three main actors – knowledge provider, knowledge recipient, and knowledge supervisor (Brčić & Mihelič, 2015). The knowledge supervisor is always at the center of the knowledge triad because he moderates the interaction between the knowledge provider and recipient. Knowledge is often shared among the three players.

Knowledge Management

Different scholars have described the process of managing knowledge as an initiative by organizations to create, protect and preserve their intellectual property. For example, Simar and Rahmanseresht (2017) say knowledge management involves the creation of information pertaining to an organization with the goal of making it readily available to other employees in an organization. The same authors describe the same concept differently by saying knowledge management involves the design of organizational structures to effectively use its intellectual capital (Simar & Rahmanseresht, 2017).

The principle of knowledge management systems largely stems from the field of “undone science” (Allen & Beech, 2013). This conception situates the production of knowledge within three realms of analysis, which are found within the institutional matrix of the state, organization, and social movements. These social movements are often used by researchers to draw attention to the undeveloped areas of research, which strive to present knowledge gaps as a tenet of “undone science.”

Researchers have pointed out that effective intellectual capital management is not only useful in creating a competitive advantage among organizations, but also in creating a competitive advantage among different countries (Ray, 2013). The opposite is also true because nations that often suffer from lower levels of economic, social, and political development standards often suffer from poor knowledge management standards (Ray, 2013). Figure 2.1 below affirms this situation because it shows that the most developed countries often have a high number of knowledge products.

The table above measured the development or advancement of different economies using the growth and development index, which is a measure of the economic macro-environment in different nations (Simar & Rahmanseresht, 2017). How these countries undertake their public governance processes and their levels of technological development were also other measures involved in the analysis of national development. Similarly, total quality management was used as another index to predict the efficiency of how different countries managed their knowledge.

In the organizational context, the efficiency of knowledge management often increases when managers are experiencing the need to know their competitors’ actions and how they are formulating, designing or implementing their business strategies (Meier-Comte, 2012). Contextualized studies have shown the effect of knowledge management systems around the globe. For example, in Iran, researchers contended that the main problem associated with its organizations is a weak knowledge management system (Simar & Rahmanseresht, 2017).

They also argued that these problems have led to the failure of these organizations to manage their knowledge effectively and extract the most value from it (Simar & Rahmanseresht, 2017). Indeed, as Simar and Rahmanseresht (2017) posit, organizations that fail to realize the importance of having this effective strategy for managing their knowledge suffer a high possibility of experiencing serious gaps, based on the creation of knowledge gaps that would occur from their inaction. Relative to this assertion, Simar and Rahmanseresht (2017) add that such organizations could suffer different negative outcomes such as a decline in quality of operations, operational redundancies, and the occurrence of mistakes and errors in the provision of goods and services. The failure to develop proper knowledge management systems also creates the likelihood that an organization’s knowledge resource would be depleted and the time and money involved in creating it would go to waste.

Knowledge Management Approaches

As shown in this chapter, many literatures have highlighted the need for knowledge sharing, and emphasized its importance in the context of today’s complex, and dispersed knowledge environment. Edwards (2016) adds that, in today’s fast –paced society, it is difficult for organizations to rely on their internal competencies or knowledge. Thus, they need to forge alliances with other organizations to maintain their competencies (Edwards, 2016).

Researchers have pointed out that pools of information (or knowledge) often allow the participating organizations to improve their competencies, skills and strategies (Francesca, 2017; Argote, 2012). Here, different studies point out that knowledge is not only accessed, but also internalized by organizations and stored to achieve the aforementioned goals (Francesca, 2017; Argote, 2012). This process is multifaceted. Besides creating a common pool for accessing the knowledge, North and Kumta (2014) say that forging new alliances between companies could also help to foster the generation of new intellectual capital in them. While many studies often highlight the need for knowledge exchange to occur between knowledge providers and knowledge recipients, they may have as well presented knowledge as a tangible resource, such as land, because their analyses mirror this analogy (Francesca, 2017; Argote, 2012). These discussions have happened within the context of understanding knowledge management approaches.

Varied research studies show four types of knowledge management approaches. The first and second ones are the mechanistic and systematic approaches. The last two are the core competency and cultural approaches (Simar & Rahmanseresht, 2017). They are discussed below.

Cultural Approach: The cultural approach to knowledge management traces its origins in the field of change management (Ivey, 2014). This approach looks at knowledge as a management issue. Although technological management is treated as a useful tool for managing this resource, proponents of the cultural approach do not view it as the only instrument for doing so. Instead, they focus more on innovation and creativity (Simar & Rahmanseresht, 2017). Thus, they do not necessarily believe in manipulating explicit resources to manage knowledge effectively.

Knowledge sharing often occurs within an institution or a company because these setups often accommodate employees who work together and share their experiences within the same settings (Ivey, 2014). As Simar and Rahmanseresht (2017) point out, such setups help organizations to share intelligence (freely) among their key employees. There are two key assumptions underlying the cultural approach. One of them is that organizations, which pursue them, are often willing to shake up their organizational cultures to improve employee behaviors. Another one is that organizational behaviors are often changed whenever businesses have exhausted the limits of their technological innovations (Meier-Comte, 2012).

Core Competency Approach: Proponents of the core competency approach say that effective knowledge management systems are often developed when intellectual capital is deemed as a key resource for organizational prosperity (Meier-Comte, 2012). However, in this context, it is pertinent to note a distinction between the ability of organizations to improve their performance and their ability to improve their knowledge management systems. This is not to deny their complementary nature because studies have also shown that they are critical tenets of organizational identities as well (Ivey, 2014). Generally, the core competency approach is a technique for using an organization’s vital knowledge to develop superior goods and services. These core competencies could also include the efficiency through which companies or organizations deliver goods or services to the market and the efficiency through which they do so as well (Simar & Rahmanseresht, 2017). The same competencies allow organizations to develop customized goods/services and optimize their logistics, at the same time. The process of employing qualified employees and disseminating a succinct vision for the organization are also other attributes or organizational efficiency that are attributed to organizational success (Simar & Rahmanseresht, 2017).

The Systematic Approach: The systematic approach involves using predetermined systematic procedures to disseminate information among a selected group of employees. The goal of the systematic approach is to achieve desirable outcomes for an organization and not necessarily to certify or approve the processes involved. This approach comes from the philosophy that considers it impossible to retrieve value from a resource if it is not modeled well enough (Francesca, 2017). Part of this philosophy is reinforced by a belief that most knowledge resources could be explicitly modeled to provide value to organizations and that solutions could be easily found through such a process. Another assumption lies in the possibility of investigating the nature of knowledge management and solving associated problems by simply applying traditional methods of decision-making (Simar & Rahmanseresht, 2017). Although cultural issues are critical in the same analysis, it is vital to appreciate the importance of systematic thinking. Therefore, while changes may occur among employees, organizational policies also need to support the same changes. One last assumption of this model is that technology is useful in solving knowledge management issues (Simar & Rahmanseresht, 2017).

The Mechanistic Approach: The mechanistic approach to knowledge management is enshrined in the philosophy that more could be done using appropriate tools or technology (Bharadwaj, 2015). In other words, more of the same could be done better than is currently done. Underlying this fact is the assumption that access to information is vital to the process of managing intellectual capital and enhances methods of accessing and using information in an organization (Bharadwaj, 2015).

Knowledge Management Models

According to Simar and Rahmanseresht (2017), two models generally represent knowledge management in organizations. They are described below.

First model: The first model highlights the difference in knowledge acquisition between people of a higher and lower socioeconomic status. The general understanding is that people who hail from a lower socioeconomic status often exhibit signs of a poor understanding of policy-relevant information (Simar & Rahmanseresht, 2017). They also show signs of poorly understanding the importance of increasing public knowledge through mass media channels. Figure 2.2 below shows the model of knowledge management gap, as described by Simar and Rahmanseresht (2017).

Two types of explanations could apply to the aforementioned knowledge gap model. One of them is trans-situational, in the sense that the knowledge gap could be merely created from conditions associated with lower socioeconomic levels. One issue that could be associated with this analysis is the probable poor communication skills associated with people of lower socioeconomic status (Jasimuddin, 2012). A situation-specific theory has also been used to explain the same knowledge gap by demonstrating that the gap could exist if people of lower socioeconomic status do not understand the need to acquire incremental information because they deem it as irrelevant or non-functional to their lives (Jasimuddin, 2012). These two schools of thought have been historically used to explain people’s propensity to hold and seek information.

Second model: This model of knowledge management is hinged on establishing a chain of knowledge management. It has been systematically used to explain why some organizations experience management gaps when implementing knowledge management systems. These gaps have been explained in four ways, as described below:

• Strategic Perspective: The strategic perspective argues for the need for organizations (or managers) to scan their environments and seek opportunities for development, or improve their competitive advantages (Simar & Rahmanseresht, 2017). The failure to do so creates gaps that explain why some of them are unable to keep up with their competition. These gaps are best explained by the difference in knowledge management and top management outcomes.
• Perception Perspectives: The perception perspective often points out the probability that top managers may fail to identify the knowledge required to improve their organizational competitiveness. In this regard, a gap forms between the structures present in an organization to manage its intellectual resources and the knowledge management structures that are actually desired (Birkman International, 2017). This difference may also emerge within an organization’s management structure because some employees may have different perceptions about what the organization needs to do, in terms of its knowledge management systems. The same variance may also emerge from the difference in the perception of managers and employees regarding the need to acquire, or retain, specific knowledge in the organization (Birkman International, 2017).
• Planning Perspective: Most managers often plan their organization’s processes, depending on how they understand the company’s internal and external environments. When these managers experience difficulties trying to apply the findings they get from this analysis to the organization, a knowledge management gap emerges (Simar & Rahmanseresht, 2017). The same is true if employees fail to translate this information into tangible value for the organization, especially when they fail to understand the importance of such an analysis.
• Implementation Perspective: It is vital for organizations to align their knowledge management systems with their goals. The failure to do so often results in knowledge management gaps. Within this understanding, it is essential for employees to gain the right perceptions and appreciate why such knowledge is good for the organization. Failure to do so would also create knowledge management gaps. Based on the two models defined above, we find that six knowledge gaps emerge. They are highlighted in table 2.1 below.

Table 2.1. Knowledge Gaps

Infrastructure Capabilities to Fill Knowledge Gaps

Filling the knowledge gaps that emerge in different organizations is an art that managers need to learn when designing a strong infrastructure to aid the process. There are three types of infrastructure commonly applied in knowledge management – information technology, knowledge structure, and knowledge culture. These elements of knowledge management interact through dynamic processes that include acquisition process, storage process, dissemination process, and application process. Both the infrastructural and process capabilities lead to organizational knowledge effectiveness. The elements interact as described in Figure 2.3 below.

Information technology: As shown from the diagram above, technology is a key infrastructural component of knowledge management. According to Bharadwaj (2015) technology is an important tool for mobilizing the social capital needed to make knowledge sharing systems work. This tool is superior to many others that will be discussed in this paper because it is able to transcend the barriers of space and time that often limit the other types of knowledge sharing platforms. Technology is also superior to other forms of knowledge management infrastructure because it acts as a repository for information (Bharadwaj, 2015). In this way, knowledge can be reliably stored and retrieved at any time. Thus, technology is a tangible resource for knowledge management and has been used by different organizations to support knowledge management initiatives. Bharadwaj (2015) also say that technology has many aspects to it, which include the hardware, software, middle ware and protocols. These elements of technology often facilitate encoding and information exchange in organizations.

Some of the information technology resources available in knowledge management include knowledge-oriented technologies, functional-oriented technologies, specialty-oriented technologies, and social networking technologies (Ray, 2013; Ngeloo, 2017). The most common knowledge-oriented technologies include groupware and web browsers. These resources help companies to process their knowledge management issues and, by extension, improve how they manage their intellectual capital resources (Aanestad & Bratteteig, 2013). Function-oriented technologies could include robotics, desktop computing technologies and such like tools of knowledge management (Aanestad & Bratteteig, 2013). They are mostly aimed at improving operational level practices. Such practices may include production, service delivery, and data processing. Specialty-oriented technologies are often for advanced operational processes in organizations because they are associated with facilitating specialized organizational functions (Bharadwaj, 2015). Typically, such organizations require a high level of knowhow (Ngeloo, 2017). Some of these technologies include computer-aided designs and expert systems software. Lastly, social networking technologies for knowledge management include platforms, such as web 2.0. They are important in facilitating collaborations between team members or enhancing information dissemination within the organization (Aanestad & Bratteteig, 2013).

Most technological tools applied in knowledge management today tend to use one or more tools, such as groupware web browsers, data mining tools and group decision support (among others). However, knowledge portals are the most commonly used tools in different organizations around the world because they have been proved to significantly improve knowledge management systems (Aanestad & Bratteteig, 2013). Groupware is often used to foster collaboration between different knowledge centers in an organization. According to Bharadwaj (2015), information technology tools that foster collaboration include databases and performance management systems. An integrated performance support system and knowledge platforms are other areas of knowledge sharing where collaboration can be fostered (Aanestad & Bratteteig, 2013). Bharadwaj (2015) believe that information technology tools play four key roles that include seeking and identifying related contents, flexibility that help express the contents of the various backgrounds where knowledge is utilized and defining and storing data (among many others).

Based on the above findings, technology emerges as the main resource for developing knowledge management solutions. Indeed, as Bharadwaj (2015) point out, technology acts as the repositories for unstructured information or knowledge exchange. It is also the platform for storing structured data using different tools such as data warehousing and management. Although technology has been touted as being the most useful resource for knowledge management, other researchers have shown that having an effective knowledge structure is also a critical part of developing a reliable infrastructure for knowledge sharing.

Knowledge structure: Bharadwaj (2015) says knowledge structure involves different elements of design that characterize the knowledge management system. They include how organizations have designed their structures of reporting, articulated their communication policies and devised their incentive provision systems (Bharadwaj, 2015). Based on this analysis, the knowledge structure consists of dynamic processes that outline how knowledge should be shared in an organization. Most organizations often have cultures that define the kind of knowledge structures exist in an organization (Kriesi, 2012). For example, most companies categorize their employees into different groups that are defined by their experiences, skills, time, output, or types of clients served (Meier-Comte, 2012). Some of these structural elements of organizational processes are often highlighted to be responsible for poor collaboration within knowledge management teams (Bharadwaj, 2015). For example, bureaucratic processes that exist within organizations often lead to slow decision-making processes and the failure of people to interact freely. Based on such outcomes, knowledge structures form a critical part of the infrastructure needed for knowledge sharing. Studies have also shown that having a supportive knowledge culture also contributes to the quest by organizations to develop strong infrastructures for managing their intellectual capital resources.

Knowledge culture: Knowledge culture is not different from organizational culture, except that it mostly focuses on knowledge as a key strategic resource. Relative to this assertion, Bharadwaj (2015) says that an organizational culture could be used to leverage knowledge management. Similar to the dual nature of organizational culture, a knowledge culture could inhibit or facilitate knowledge sharing within an organization. Indeed, as Bharadwaj (2015) points out, culture often has a significant influence on organizations because it affects the efficiency of knowledge management systems. Its power in doing so mostly stems from the ability of culture to define the values and norms that dictate employee behaviors and practices (Ray, 2013; Ngeloo, 2017). Concisely, the presence of an effective knowledge culture is integral to the success of many organizations that want to excel in knowledge management because it signals the commitment of management to knowledge sharing initiatives (Ray, 2013). In this regard, organizations benefit from a superior decision-making structure.

A sound knowledge culture should support the formal and informal sharing of knowledge. Other researchers add that an effective knowledge management culture should provide a vision that supports knowledge sharing (Ivey, 2014; Bharadwaj, 2015). For example, Bharadwaj (2015) defines an organizational culture that mandates older workers to share their knowledge with younger and less experienced ones. Nonetheless, to realize the benefits of this type of culture, there should be sound leadership at various levels of management (Ivey, 2014). Such leadership acumen should include a strong willingness of management to empower and involve employees at different levels of decision-making. Middle and front level managers have a more important role to play in nurturing such a culture because they are the points of contact between employees and management (Ivey, 2014). Nonetheless, as Bharadwaj (2015) point out, “Leadership is required to develop a desired culture and, ultimately, to develop a knowledge culture as well” (p. 423).

Mechanisms to Fill Knowledge Gaps

Haider and Mariotti (2017) conducted a case study to understand how companies manage their knowledge systems. They established that managers often interacted with technical workers, such as engineers, to fill their knowledge gaps (Haider & Mariotti, 2017). One of the methods used to do so was on-the-job training. Training courses and lectures, plus plant visits and in-house training, were also other methods used by the employees to reduce their knowledge gaps (Haider & Mariotti, 2017). The main salient features that attracted the organization to these methods of knowledge exchange was that they allowed the managers to acquire knowledge that they would have otherwise not have gotten. The arguments made for these unique types of knowledge exchange forums are explained below.

On-the-job training: It was established that employees who were on the job training were better placed in acquiring new knowledge if they worked with more experienced employees through on-the-job training processes (Haider & Mariotti, 2017). Through such a platform, it was easy to learn new information about organizational processes, such as simple information relating to machine operations. Complex processes, such as how to improve organizational practices could also be learned this way. Research studies undertaken by Haider and Mariotti (2017) also showed that this method of knowledge acquisition was the most widely accepted and used by most organizations. In most cases, on the job training often started with a three-month course that was first focused on a language course. It was mainly used in multicultural contexts. Evidence of its application exists in organizations that had both Japanese and English-speaking employees (Haider & Mariotti, 2017). Such a course was not only aimed at imparting language skills, but also educating the employees about the values, philosophies and cultures of each group of workers. In most of these sessions, workers spent time with their colleagues on the factory floor. In one of the assertions made by an employee, it was established that new workers learnt a lot from on-the-job-training because it was happening in real-time, as the job was being done.

In one session that involved training new workers in a heat treatment shop, it was established that the first step of on the job training was educating the workers about all the processes involved (Haider & Mariotti, 2017). In order of processing, employees learnt about each process systematically. For example, if the first process involved jig setting, such was done first. Later, the trainees learnt about how to operate machines, in the order of importance. Generally, the process involved on-the-spot practical training for all the workers. No classes were involved, but new employees often jotted down some notes regarding what they learned. Comprehensively, this example shows that on-the-job training is one practical way organizations have used to fill knowledge gaps. Another one is plant visits and observation, discussed below.

Plant visits and observations: Plant visits involve employees being taken to a company’s plant to observe how operations are being undertaken. These visits could involve a trip to a factory plant or to another company (Aanestad & Bratteteig, 2013). Haider and Mariotti (2017) provide us with another example of how it worked in their organization. Their training process involved understanding how their employees implemented different systems and understood how the processes were relevant to their training course. The main goal of doing so was to make sure the employees understood how operations were being carried out in their respective companies (Haider & Mariotti, 2017).

Other case studies have been cited in several multinational organizations, including Massey Fergusson and AHl which undertake case studies of their own to understand how other organizations perform their organizational processes (Schiedat, 2012). One employee at AHL said that the exercise involved evaluating quality control procedures between the organization and several others (Schiedat, 2012). Comprehensively, this attempt shows how different organizations evaluate their operational processes using a strategy that closely resembles the benchmarking process.

In-house on-the-job training: As insinuated in the name of the concept, the in-house on the job training method involves educating employees about how work is done within the confines of their organization. Therefore, unlike other training methods that include external parties, this method only involves the concerned organization (Haider & Mariotti, 2017). This reason justifies why it is called “in-house training.” However, some literatures present an opposing view to this narrative because they say that knowledge transfer could also involve external stakeholders since outside parties could come to an organization and educate their employees about operational procedures (Haider & Mariotti, 2017). This observation has been reported in an organization called MTL where engineers from another organization (Massey Ferguson) came to share their knowledge about operations processes with employees working for the company (Haider & Mariotti, 2017). Nonetheless, this method does not differ much from the other methods highlighted in this review, in the sense that training and knowledge transfer occurs on-the-job.

In-house training school: Corporations that want to internalize knowledge transfers by developing training schools within an organization have adopted this method (Haider & Mariotti, 2017). Usually, these schools involve the development of curriculums that are solely designed for a specific group of employees or department. Within this internalized knowledge transfer system, it is possible to find selected organizations inviting people from outside the organization to share their knowledge regarding a specific knowledge area (Sloan, 2014). Generally, based on the above assertions, we find that different modes of sharing information within organizations outline different forms of social interaction and knowledge exchange.

There are several cases where organizations have sought the input of third parties in intellectual capital management and in so doing have found enough supporting information to satisfy the needs of all their stakeholders (Haider & Mariotti, 2017). However, there are instances where such knowledge has been transformed to eliminate gaps in intellectual capital management experienced by specific organizations. This outcome was often visible in cases where the knowledge obtained from the external parties was deemed inapplicable to the local context. Usually, when such exchanges and transformation occur, innovation and knowledge creation also suffice. Although the knowledge transformation process happens to fit the knowledge gaps identified in specific organizational processes, it was established that the transformation occurred because employees were the first to note the need for the transformation, relative to the gaps present in their organizations (Haider & Mariotti, 2017).

The inability to transfer knowledge from the partners to the concerned organizations largely arose from differences in working environments. For instance, in the example highlighted above, pitting Japanese and English employees, Haider and Mariotti (2017) found that Japanese products and processes helped to create products that were not directly applicable to the English markets because of several demographic and environmental variations. Therefore, there was a need to introduce changes in the product specification standards. The changes to be made created some sort of knowledge gap in the organizations concerned. Although companies often deliberate on such gaps before engaging in knowledge transfer with other companies, researchers established that employees who were engaged in on-the-job-training often filled such gaps by brainstorming with their counterparts on the work floor (Haider & Mariotti, 2017).

Benefits of Knowledge Sharing

Knowledge sharing has many benefits that accrue at individual and group levels. At an individual level, different benefits of knowledge sharing include (but are not limited to) improved employee attitude, ability to meet deadlines, consistent performance and proactivity (Francesca, 2017). At a group level, there are different benefits associated with knowledge sharing, such as the ability to work well in groups, increased contribution to organizational activities, improved employee attitudes, and increased participation at different levels of organizational performance (Francesca, 2017). These benefits notwithstanding, different researchers have pointed out that knowledge sharing activities can be monitored across different levels of participation, including group discussions, interest groups, learning activities, seminars and conferences (Meier-Comte, 2012).

Factors Influencing Knowledge Sharing in Organizations

Although many factors affect how organizations share knowledge in the workplace environment, researchers have narrowed down these reasons into two main ones – intrapersonal and interpersonal factors (Argote & Fahrenkopf, 2016). To understand the role of these two factors in knowledge sharing, it is first important to understand that knowledge sharing is majorly an interpersonal matter. In other words, an employee’s willingness to share knowledge with another worker is mainly motivated by his or her willingness to do so. At the same time, for knowledge sharing to occur seamlessly, a series of interpersonal actions occurs to determine the level at which knowledge sharing should occur. Alternatively, the employees should have some sort of relationship if knowledge sharing is to happen (Argote & Fahrenkopf, 2016).

In one study undertaken by Edwards (2016), knowledge management systems were evaluated based on their relational and process-based nature. This approach consistently views knowledge as an outcome of people-based interactions. It argues that knowledge is not only created through instructions or demonstration, but through people’s interaction with one another. Indeed, as Horaguchi (2014) points out, knowledge is created this way through a socialization process or through an interactive process with “old timers.” Some researchers refer to this process as the “legitimate peripheral participation” (Argote, 2012). It argues that knowledge management occurs within a context whereby new employees learn about an organization’s processes by interacting with older employees. By doing so, a transition occurs, where newcomers (employees) move from a stage of peripheral state to a new one where they are full participants of the “community.”

In a recent work by Styhre (2013), the concept of participation has been investigated in-depth. Researchers have viewed it as more than only participating in occupational community, but also a process that easily generates new intellectual resources (Argote, 2012). Face-to-face interactions are usually the only mode of communication that leads to the development of new intellectual capital resources. Relative to this discussion, Styhre (2013) says, by communicating with different people, there is an opportunity to create a common sense of understanding regarding what should be done, relative to the need for knowledge management. Though this statement, Styhre (2013) also says that knowledge may be shared through different forms such as storytelling, where older employees teach new ones how they have been doing their jobs. Evidence exists of how this method has been used in different organizations, including Xerox, where older employees shared knowledge with newer employers about their jobs. Relative to such an example, Jasimuddin (2012) says that such social interactions often provide a fertile ground for the creation of a common identity within an organization. This common identity could also be regarded as a tool, which further motivates employees to share experiences. Styhre (2013) reported this advantage in Xerox where most of the technicians shared a strong work context that nurtured a common understanding among them that allowed them to share knowledge freely. Jasimuddin (2012) argues that this sense of community if nurtured well within the organizational context easily creates a high sense of trust among the members. Furthermore, Jasimuddin (2012) adds that it creates shared behavioral norms, reciprocity and mutual respect among most levels of employee hierarchies.

Organizations that are positioned to achieve this level of success are able to create a high social capital that researchers have linked to effective social management systems. In line with this reasoning, recent studies have reorganized the social nature of knowledge by pointing out that the management of intellectual capital is an ongoing process that involves different actors and that could adopt a provisional or virtual nature, depending on the kind of knowledge management systems adopted by a company (Styhre, 2013). Based on the above statement, researchers understand knowledge to be better informed by action more than anything else. Similarly, they point out that the concept should be conceived in terms of knowing.

At a dyadic level, knowledge sharing should occur when two factors are present – communication and collaboration (Ray, 2013). The main assumption underlying this statement is that the closer two employees are, or the stronger their working relationship, the more likely knowledge sharing would occur. Again, two predictors are considered to be important in determining the success of knowledge sharing initiatives – willingness and motivation to share intellectual capital resources. Experts highlight the importance of understanding them in detail, as discussed below.

Willingness: Many research studies have highlighted one significant assumption in knowledge sharing that is associated with the willingness to share information. This assumption states, “The willingness to share information has a positive impact on knowledge sharing” (Simar & Rahmanseresht, 2017, p. 3). The willingness of employees to share information could be loosely deemed to refer to the preparedness of an employee to grant another access to their intellectual capital. This willingness would suffice in contexts where employees have a positive attitude towards one another (Argote & Fahrenkopf, 2016). Based on this finding, knowledge sharing appears to be a significantly individualistic factor. According to Argote (2012), organizations should understand the importance of an employee’s will to share information because this basis helps them to increase the efficiency of knowledge sharing.

Motivation: As highlighted in this chapter, intergenerational differences in the workplace have made it increasingly difficult for managers to maintain high levels of motivation among their workers. According to Ray (2013), trust is central in motivating employees to share information. Given the importance of knowledge sharing, it is not surprising that many observers agree that the motivation to share information significantly affects the efficiency of the process (Argote, 2012). Extrinsic and intrinsic factors are important in maintaining the desired level of motivation to support effective knowledge sharing initiatives. Extrinsic factors refer to the understanding by some employees that the realization of some independent factor would boost their motivation to share knowledge. Comparatively, intrinsic factors refer to the self-determination of employees to gain knowledge, relative to any external factors, as one of the greatest influences of the motivation to share knowledge. In this regard, intrinsic factors are bound to boost knowledge sharing activities. Here, motivation also emerges as a moderating variable that would affect the relationship between network positioning and the knowledge sharing process (Ray, 2013).

Limitations of Organizational Capability to Manage Intellectual Capital Resources

Most organizations that implement knowledge management systems often experience gaps in their implementation strategies that stem from the failure of existing management systems to align with existing organizational cultures and policies (Meier-Comte, 2012). The problems they encounter are diverse, but Simar and Rahmanseresht (2017) say one of the most common ones is the differences in perception between those who design the knowledge management systems and those who are supposed to follow or protect them. Simar and Rahmanseresht (2017) observe this issue as a common problem by saying that the isolationist way in which knowledge management designers conducts their work makes it difficult for them to be objective because they tend to design them according to personal beliefs and perceptions. Another problem reported by some observers is the tendency of these knowledge management systems to be annoying and upsetting to most users, based on their designs, which are often regarded as having unrealistic capabilities (Aanestad & Bratteteig, 2013). Simar and Rahmanseresht (2017) say another limitation of knowledge management systems is the failure to align the same with business needs. This problem makes it difficult for the knowledge management systems to create value for the associated organizations.

Lastly, researchers have also pointed out that one weakness of knowledge management systems is the failure of organizations to allocate the right resources to the systems and to assign the right number of employees to implement the system (Aanestad & Bratteteig, 2013). Despite these challenges, organizations have not shied away from giving knowledge management systems the importance they deserve because they understand that in today’s knowledge-centered global economy, the success of organizations depends on the implementation of effective knowledge management systems (Aanestad & Bratteteig, 2013). This fact is further reinforced by studies done by Simar and Rahmanseresht (2017) in 25 multinational organizations, which showed that most senior managers acknowledged the loss of credible and reliable organizational processes because of a poor management of their intellectual capital.

Common Barriers to Knowledge Transfer

Some of the most common barriers to knowledge transfer include inadequate awareness, inadequate transfer capacity, inadequate pre-existing relationships, and inadequate innovation (Schiedat, 2012). The lack of awareness regarding intellectual capital exchange is highlighted by researchers, such as the ITM Platform (2017), who point out that if employees do not understand the need for the same in the first place, they would similarly be unaware of their need to transfer the same knowledge to other employees. Awareness also includes identifying knowledge providers and their recipients and later matching them up to identify how they need to pair up. Such links could be identified using knowledge maps and such like tools.

Researchers point out that using such tools is pertinent for the efficient formulation of knowledge transfer programs and the increase of people’s awareness regarding the same because they help organizations to could help provide an efficient and effective approach to addressing complex knowledge management problems (Aanestad & Bratteteig, 2013). The failure to have such tools simply means that organizations would have trouble finding a solution to a given problem or conflict associated with knowledge transfer. Such problems often occur because knowledge transfer roles would be assigned to people who do not understand the process, or are unaware about how to conduct such an exercise. Theorists who have investigated this issue have argued that organizations could be more effective if they increase employee awareness regarding the need for knowledge transfers because this is the first step towards the integration of knowledge in the organization (ITM Platform, 2017).

Inadequate pre-existing relationships between knowledge providers and knowledge recipients has also been voiced as another challenge affecting knowledge transfer because such relationships act as the vein through which knowledge flows in the organization (ITM Platform, 2017). Without such an infrastructure, it is difficult for knowledge transfer to occur. This barrier is closely associated with an inadequate capacity to transfer knowledge within organizations because it also points to the need to have a proper infrastructure for knowledge transfer (Francesca, 2017). The lack of a proper infrastructure could easily lead to the loss of knowledge between different phases of firm operations. For example, studies have shown that most organizations, which depend on critical organizational processes for sustenance often, experience knowledge losses if they do not have a proper infrastructure for the same because their current designs and uses of equipment often depend on the passage of knowledge across different operational phases (ITM Platform, 2017). Thus, intellectual capital losses occur when knowledge is transmitted inadequately.

Lastly, inadequate innovation has also been highlighted as another knowledge transfer barrier in some organizations (Meier-Comte, 2012). This barrier often leads to inadequate knowledge integration, which could lead to the inability of organizations to solve knowledge transfer problems that could incapacitate a company’s operations (ITM Platform, 2017). This problem also limits an organization’s capacity to transform its intellectual capital resources into something greater than the value it would ordinarily create for the organization (because innovation would aid managers to correctly couple different pieces of information for something greater) (Argote, 2012). As the ITM Platform (2017) points out, many organizations often lack that one key that would appropriately fit with diverse centers of knowledge. Thus, there is always a risk that one piece of a puzzle would fit incorrectly and interfere with the general knowledge transfer objective. Through this analysis, researchers have always highlighted the importance of fostering innovation in the organization to better manage and exploit multifunctional knowledge (Meier-Comte, 2012).

failure to align knowledge gaps with strategy. One of the most notable challenges organizations have faced when trying to fill their knowledge gaps is the difficulty of matching the knowledge gap with the organization’s attributes. Soliman (2015) identifies this problem in his book titled “From Knowledge Management to Learning Organization to Innovation” which presupposes that, although knowledge is transferable, the process should be cognizant of the fact that it needs to align with an organization’s attributes. However, doing so has been problematic for most companies that pride themselves on being innovative. Part of the problem is specific risks, which make it difficult for organizations to realize how knowledge gaps could impede or facilitate their organizational processes. As Horaguchi (2014) observes, some of these risks could be emerging from the failure of organizations to identify knowledge mismatches. Soliman (2015), who says the higher the level of involvement of individuals and functional units in the knowledge transfer process, the higher the possibility that a mismatch would occur further compounds this risk.

Brčić and Mihelič (2015) further explored the link between knowledge and strategy by saying that creating an alignment between the two is often a difficult and complex process. However, this process is critical to the success of organizations that want to extract value from their knowledge management systems. This finding may have triggered a greater interest in understanding how unassessed intellectual capital could aid companies to improve their strategic management systems Relative to this assertion, Soliman (2015) purported that, by virtue of trying to align their knowledge management systems with their business strategies; companies were overlooking existing knowledge management gaps. By extension, this action also meant that they were overlooking existing strategic gaps. Soliman (2015) failed to note that adverse organizational outcomes were directly linked to this problem. Although several authors have highlighted the need to assess intellectual capital when developing or implementing business strategies, the process may be inhibited by the existence of defective knowledge, or knowledge that cannot be directly applied to organizational processes (Brčić & Mihelič, 2015).

History is littered with several organizations and institutions that faced imminent collapse because of their failure to understand or appreciate the importance and meaning of knowledge transfers. These examples cut across different fields, including finance, manufacturing, banking and the likes. For example, in one case cited by the Chartered Management Institute (2017), Barings Bank (based in London) reported a significant decline in its performance because of knowledge gaps within its employee pool. The bank mostly suffered from a cultural problem that made it difficult for the organization to detect knowledge gaps in its operations (Chartered Management Institute, 2017). This mistake was further compounded by strategic weaknesses in the organization’s operational plans because it suffered from overconfidence and the lack of a timely system that would relay information to managers, in real time, regarding the bank’s activities (Chartered Management Institute, 2017).

Two groups of traders operated at Barings Bank. One of them was a group from Barings Securities and another one was from Barings Brothers. Both sets of employees had significant cultural differences (Chartered Management Institute, 2017). One effect that emerged from this difference was the focus by some of the managers in the organization to protect their departmental operations, as opposed to making sure there was synergy in the organization that would allow the bank to work as a whole. In 1993, this clash came to a simmering end when there were several employee transfers in the organization that left some departmental operations significantly understaffed (Chartered Management Institute, 2017). This problem was highlighted in an article by “Euromoney,” which showed that significant derivative knowledge was lost in the organization, which significantly affected the operations of derivative trading that mostly sustained most of its Asian operations (Chartered Management Institute, 2017). To explain this problem further, the Chartered Management Institute (2017) said that the bank’s management abdicated its duty to oversee the quality of actions being taken in the institution and, by extension, created a fertile ground for the bank to collapse.

Kidder Peabody is a trading company that failed to notice its knowledge gaps and suffered a similar fate as Barings Bank. One of the company’s employees (Joe Jett) significantly inflated the company’s profits by up to $350 million, over a period of two years (Tofanelli, 2012). However, the issue was undetected by the company’s management because there was an existing knowledge transfer structure that would have shown that the employee had a string of failures prior to joining the organization. The company’s management made more mistakes by allocating more capital to Jeff without understanding how he made his profits (Tofanelli, 2012). An audit on the issue showed that Kidder Peabody was not keen on testing some of the knowledge used by Jeff because they were blinded by his success (Tofanelli, 2012). The knowledge gap in the organization manifested the need for employees to share information because as it was, Jeff was unwilling to do so. This example highlighted one flawed mistake in many trading firms that emphasized individual performance at the expense of group performance.

Although the above-mentioned examples are robust and explain the effects of knowledge management failures in organizations, there is a gap in literature that has failed to show the effects of generational differences on knowledge management. This gap exists despite the fact that many examples of knowledge sharing gaps today occur within the context of appreciating the contribution of different groups of employees and their roles in the organization (which is the same as the case highlighted in this study). The section below outlines different generational cohorts in the workplace that are responsible for these gaps.

Generational Cohorts in the Workplace

Generational cohorts in an organization refer to the categorization of employees into different groups, based on when they were born and the kind of historical events associated with their upbringing. Typically, these experiences would influence the beliefs and values that would affect their values and beliefs about work (Shaw, 2013). A variety of factors could contribute to these beliefs and values. Some of them include influences from the media, social and economic events, parental influences, and peer influences (Saleh, 2012; Shaw, 2013). Based on the collective factors, each employee group often manifests different behaviors in the workplace. Their differences translate to knowledge gaps. As Saleh (2012) points out, the general reason for the knowledge gap that exists in many organizations is that different cohorts of employees have acquired different types of knowledge, depending on their life and organizational experiences. It is difficult to delink employee experience and age because the older the employees, the more experience they gather at work.

The Strauss-Howe generational theory is perhaps the most vivid theoretical points of reference to explain intergenerational issues associated with knowledge transfer and management. The theory posits that generational cohorts in the workplace are brought about by four different events (“turnings”) (Lyons, 2012). The events are “the high,” “the awakening,” “the crisis” and “the unraveling.” These four turning points are briefly discussed below.

The High: This turning refers to periods where individualistic attitudes are suppressed by the greater and collective effort by employees to subscribe to a higher purpose of the organization’s goals. In other words, employees are often clear about the direction they would take as a collective group and are motivated to do so (Lyons, 2012).

The Awakening: This turning simply refers to a period where people feel the need to uphold personal and spiritual autonomy over anything else in the organization. It is often heralded by a sense of social tire where the drive for self-awareness supersedes all other aspirations of workers (Lyons, 2012).

The Unraveling: This turning point is synonymously associated with a period of low confidence in organizations because they are often deemed weak. Instances where the unraveling occurs are also characterized by a high sense of individualism by employees. However, it often later crystallizes to the atomization of an organization’s purpose (Lyons, 2012).

The Crisis: This last turning stage is often associated with war, which is permitted through people’s resolve to manage a crisis. Afterwards, restructuring can take place when people build the organization again (Lyons, 2012). Although the above turnings have largely been used to explain organization phenomena, it is important to point out that the development of the Strauss-Howe generational theory has borrowed heavily from the American organizational experience. Nonetheless, by virtue of understanding the value systems of different employee groups, universally, researchers have said there are three main types of employee groups– baby boomers, Millennials, and generation X. They are assumed to symbolize three blocks of employees that characterize most knowledge gaps in current organizations around the world. They are further explored below.

Baby Boomers: The baby boomer generation was typically born between 1945 and 1965. Their upbringing was ordinarily associated with economic prosperity and suburban affluence (Saleh, 2012; Shaw, 2013). Studies also show that they grew up in strong nuclear families and valued traditional family values (Birkman International, 2017). For example, most of their mothers were stay-at-home mums and worked hard to be homemakers, as opposed to becoming breadwinners. Currently, people in this generation are considered leaders in the workplace. The youngest employee within this generational group is estimated to be 52 years old (Birkman International, 2017).

Generation X: This generation was born between 1965 and 1980 (Tofanelli, 2012). Most of those who grew up within this generation group were latch-kids and their mothers often went out to look for work, as opposed to being homemakers and depending on their husbands (Tofanelli, 2012). Consequently, they were exposed to parents who were resilient and independent. It is similarly common to find most children who grew up in such sort of setups to value independence. In some literatures, this generation is often overlooked because they are sandwiched between two large generations – baby boomers and millennials (Levitt, 2012).

Millennials: Millennials are an employee generation birthed from the early 1980s to late 1990s. In some circles, they are also known as “Generation Y” (Birkman International, 2017). This group of employees is regarded as having grown up in the most child-centric times of human history (Birkman International, 2017). Consequently, they tend to appear more confident and at times cockier than their older counterparts do. This attribute may have stemmed from the high expectations put on them by their parents. Some studies point out that this group of employees is the largest in the global workforce and its dominance is still growing (Tofanelli, 2012).

The above classifications of employee generations are important to the study of knowledge management because each group of workers has different behaviors and values that affect how they perform their duties in the workplace. For example, different research studies have pointed out how the baby boomer generation is unique from the other types of employee groups highlighted above because they tend to value work relationships more than anything else (Levitt, 2012). Comparatively, generation X and the millennials tend to value the work environment more than any other factor of production (Birkman International, 2017). Conversely, some key attributes that would influence their job satisfaction levels include decision-making opportunities, career development opportunities, autonomy at work and such like job-related factors (Tofanelli, 2012). Although each generation has its unique strengths, some of the main issues associated with their weaknesses include discontentment and disrespect at work (Levitt, 2012). These problems often occur because of misunderstandings and the failure of one employee cohort to understand the point of view of another. For example, the millennial group may fail to understand the intense work regimen that the baby boomer generation is accustomed to. Similarly, a top-down hierarchical organizational structure (which is preferred by the baby boomer generation) may irritate most generation X workers (Tofanelli, 2012). Independent of these factors, Shaw (2013) adds that different generations also have their unique communication styles that affect team cohesion in the workplace. Although there are many stereotypes about millennials in the workforce, the collective personality that defines them is more similar to baby boomers than previously thought (Simar & Rahmanseresht, 2017). However, accepting such facts has been difficult for managers and researchers alike. Nonetheless, managers that bother to understand these perceived differences and create an environment where they are able to nurture the skills and competencies of both cohorts of employees are likely to succeed through organizational success, compared to those who do not (Simar & Rahmanseresht, 2017).

Generally, the main message that researchers convey from this analysis is that workplaces are becoming more diverse by the day and the possibility of an older employee reporting to a younger one is as real as the possibility that an older employee would have to look up to a younger colleague to gain knowledge regarding a particular operational process. Argote & Fahrenkopf (2016) say that companies need to develop effective knowledge management systems that would allow older employees to transfer their knowledge to younger workers if they want to remain truly competitive. A greater point of concern for most organizations is the immense wealth of knowledge held by the baby boomer generation who are now retiring from the workplace (Saleh, 2012; Shaw, 2013). Companies that recognize this problem are shifting their strategies to support a framework that allows intergeneration knowledge transfers. While different organizations are starting to embrace the importance of developing effective knowledge management strategies, many researchers agree that these management systems should appeal to the need to have a multigenerational workforce.

Why all the Talk about Generations Anyway?

Although researchers have pointed out significant differences between how generations think, work and the challenges that these two sets of ideologies have on the organizational performance, this issue is more than a trendy topic. As the Birkman International (2017) points out, it has a significant impact on organizational and team performance. This is why organizations, which have an effective knowledge management system, seem to tower over their competitors (Tofanelli, 2012). Understanding the secrets that keep older and younger employees engaged in the workplace is among the most sought after skills. Indeed, the cost of having disengaged employees is dire to organizations because research points out that, companies lose up to $550 billion annually because of this problem (Tofanelli, 2012). Having engaged employees in the workplace has been largely associated with financial stability and high levels of employee motivation (Spiegel, 2013). A high level of employee satisfaction has also been associated with the same outcome because research studies point out that when employees feel they have an equal opportunity to succeed, they tend to be more motivated to do their work (Spiegel, 2013). Additionally, the importance of understanding how different cohorts of employees could work together is critical in today’s society because studies report that 1 out of 3 employees in the global workforce today are millennials (Simar & Rahmanseresht, 2017). At the beginning of 2015, researchers estimated that this population group surpassed the number of baby boomer workers in the global workforce (Levitt, 2012). In America, millennials are considered the most diverse employee group yet (Levitt, 2012). This finding stems from evidence that shows that up to 44% of this employee group are minorities (Levitt, 2012). This rate of diversity not only highlights the importance of appreciating or acknowledging the need to motivate employees, but also forces us to appreciate the diversity that exists in the global workforce today.

Summary

Although the findings highlighted in this literature review explain the main concepts of knowledge management and its antecedents, a gap in literature has emerged and it has failed to show the effects of generational differences on knowledge management. This gap exists despite the fact that many knowledge-sharing gaps today occur because of generational differences in the workplace (which is the same as the case highlighted in this study). This study would contribute towards the development of this literature through the Saudi Aramco case study.

Research Methodology

Introduction

This chapter outlines the research strategies that were used in meeting not only the research objectives, but also answering the research questions after evaluating factors that affect knowledge transfer performance in Saudi Aramco. Key aspects of the strategies that would be explored in this paper include the research approach, research design, data collection strategy, data analysis strategy, and ethical considerations. The quantitative approach was used in developing the questionnaire as a tool based on 5-points Likert-scale to test the conceptual model, by allowing the research participants to give a range of views about the research questions, stretching from “strongly agree,” “agree,” “neutral,” “disagree,” to “strongly disagree.”. To collect information from the respondents, a simple questionnaire was issued to the respondents to collect information about the research issue as highlighted in appendix 1. Moreover, this chapter presents the research method, research strategy, research framework, research variables, research hypotheses, research instruments, research population and sample, data collection, validity and reliability of instruments, statistical analysis tools, and the summary.

Research Method

There are three main research techniques in academic studies. They include the mono method, mixed method and multimethod (Crowther & Lancaster, 2012). The mono-method typically involves the use of only one research choice – either qualitative or quantitative. Comparatively, the mixed methods approach combines both the qualitative and quantitative techniques. Lastly, the multi-method approach uses two qualitative research choices (Crowther & Lancaster, 2012). This study adopts the mixed-method approach because it is centered on the use of the qualitative and quantitative research methods. The mixed methods approach is applicable to this study because it allows researchers to get comprehensive data that could be analyzed using graphs, narratives and even pictures (Crowther & Lancaster, 2012). By using the mixed methods technique, it would also be possible to get insights about the research issues that could otherwise have been missed if only one method was used.

Research Strategy

Crowther and Lancaster (2012) say there are three main types of research strategies, which include exploratory, descriptive, and explanatory studies. The exploratory study seeks to gather new insights regarding a research phenomenon. In other words, it is used to assess a new topic in a new light. Exploratory researches are usually conducted in three major ways that include searching the academic literature, interviewing experts in the subject, and conducting interviews (McNabb, 2015). Comparatively, descriptive research is used to describe a phenomenon, event or situation. The most common way of conducting descriptive research are sampling, interviews, reanalysis of secondary data, and questionnaire surveys (Crowther & Lancaster, 2012).

The exploratory technique is selected for this study. An explanatory review often involves an analysis of an event or research problem with the goal of explaining different variables that underlie the same investigation (Crowther & Lancaster 2012). Some of the most common methods used in exploratory research include case studies, observation, historical analysis, attitude surveys, and statistical surveys (Crowther & Lancaster, 2012).

The questionnaire was designed with the following considerations:

• The survey had to be simple to make the employees comprehend what information was sought from them
• They have to be easy to fill so that the process does not take a long time because employees would be taking time off their work schedules to complete them
• The surveys would have to be completed by different groups of employees and from different age groups and works stations to make the responses inclusive
• The survey questions have to be written in easy language to make all the employees understand the questions.

Research Framework

The research framework consists of a conceptual model that strives to understand the relationship between the independent variables and dependent variables. The main dimensions analyzed include, critical activities, risk of loss, communications skills, culture, and demographic information (gender, age, nationality, educational level, work field, work experience, job position, and training). They have been added to this model to investigate the effect of that information on the knowledge transfer. In addition, this is in detail shown in Figure 3.1

Research Variables

The variables of the study are classified into two types: dependent and independent. The only dependent variable of the conceptual model is knowledge transfer and the independent variables are: critical activities risk of loss, communication skills, culture, and demographic information (gender, age, nationality, educational level, work field, work experience, job position, and training).

Research Hypotheses

Based on the research questions of this study the hypotheses were formulated as listed below:

• H₁: Critical activities have an effect on Knowledge Transfer.
• H₂: Risk of loss has an effect on Knowledge Transfer.
• H_3: Communication skills have an effect on Knowledge Transfer.
• H₄: Culture has an effect on Knowledge Transfer
• H₅: Demographic information affects knowledge transfer

Research Instruments

The current study depends on the conceptual model that informs the development of the questionnaire as a tool which allows the research participants to give a range of views about the research questions, stretching from “strongly agree,” “agree,” “neutral,” “disagree,” to “strongly disagree.” To collect information from the respondents, a simple questionnaire will be issued to collect information about the research issue as highlighted in appendix 1. The questionnaire contains demographic information and number of statements that have been formulated according to the study objectives. Table (3.1) lists the dimension names and the number of statements for each dimension.

Table 3.1: The questionnaires dimensions and the number of statements

The questionnaire consists of two parts. The first part is investigates employees’ demographic information (gender, age, nationality, educational level, work field, work experience, job position, and training). The informants were asked seven general questions, Which skills have they used in knowledge transfer (KT) activities during the past 12 months, do they have an experience in knowledge transfers or not, does their organization experience KT methods, have they practiced KT processes with regard to the job they are working at, do they know who can help in solving problems in the organization, is their mentor performing his duties in a proper way, and do they go to their supervisor whenever they face a problem. The second part of the questionnaire consist of (25) statements distributed on five dimensions, and they are; critical activities (which includes (5) statements), risk of loss (which includes (3) statements), communication skills (which includes (6) statements), culture (which includes (6) statements), and knowledge transfer (which includes (5) statements). Five intervals of scale were used to interpret the respondents’ degree of agreement. The following formula was used to calculate the score interval;

Score interval = (Maximum score – Minimum score) / Number of levels

= 5 – 1 / 5 = 0.8

The following rating scale was used to measure the degree of agreement:

Table 3.2: Rating scale

The correlation between the dimensions was calculated to measure the direction degree of relation that ranged between -1 and +1. The positive values mean positive relationship, while the negative values mean a negative relationship. According to Gertsman (2003), the scale that measures the strength of correlation is as highlighted in Table 3.3 below.

Table 3.3: Strength of correlation scale

Research Population and Sample

A sampling method refers to how employees would be recruited to participate in the study. The simple random sampling method was used to recruit the research participants. The method works by giving respondents an equal chance of participating in the study. The simple random sampling method was in the study because the researcher wanted to get unbiased and random opinions from the employees of Saudi Aramco regarding their knowledge transfer methods. The population of three departments in Aramco such as Accounting, Marketing, and HR are 700 (Saudi Aramco Inc., 2015). The sample size were calculated with a confidence level of 0.95 and a marginal error 0.05 by using (www.raosoft.com/samplesize). Here, the minimum recommended sample size is (249).

Data Collection

Data collection refers to the important step of gathering and analyzing the required information (Gupta, 2013). The survey highlighted in this study involved the collection of data from a group of respondents in a structured manner. The data may be collected using different techniques, or data collection methods, including questionnaires, structured interviews, or semi-structured interviews. As mentioned in chapter 1, the statistical surveys approach was used in this study. This research technique is intended to provide adequate insights regarding knowledge transfer in a real-life organizational setting.

Table (3.4) below shows the respondent rate for the questionnaire. The data collection tool was distributed virtually to the intended responses at Saudi Aramco in three main departments, accounting, marketing, and HR. They were also distributed randomly in each of the three departments. The number of responses received was 370 questionnaires which have been analyzed and the correct respondents’ rate is 91.6% as highlighted in Table 3.4 below.

Table 3.4: Respondent rate for the questionnaire

Validity and Reliability of Instruments

The ethical considerations that could affect this study largely refer to practices of good conduct by the researcher. Some of the main ethical issues that were relevant to the study are discussed below:

• Informed Consent: All the respondents who participated in the study did so voluntarily. This means that they were not coerced or paid to participate in the study.
• Privacy and Confidentiality: The identity of the research participants was not revealed in the research. This stipulation means that there were no names of the respondents attached to their views (Wiles, 2012). The aim of doing so was to protect the privacy of the respondents.
• Data Management: All the findings obtained from the research participants were safely stored in a computer and secured with a password. Only the researcher had permission to access the data. After completing the study, the information would be destroyed.

The questionnaire was evaluated and reviewed by qualified employees and supervisors who are in-charge of the knowledge transfer mechanism in Saudi Aramco to determine the validity as outlined in the appendix (B). To test the reliability of the questionnaire, Cronbach’s alpha were used. Table (3.5) shows the result of testing the reliability by Cronbach’s alpha.

Table 3.5: Cronbach’s alpha test for study Dimensions

The table shows the output of alpha coefficient for the questionnaire dimensions, according to Wang (2007), the dimension with alpha coefficients values of 0.6 and above are considered reliable. The values are all above 0.6, which indicate that the internal consistencies of the items have good internal reliability. The Cronbach’s alpha was ranging from 0.619 to 0.917 with overall reliability of 0.937. This means that the reliability of the questionnaire is acceptable for analysis.

Statistical Analysis Tools

Google form was used to present, manipulate, and process the data. The pieces of information obtained from the surveys were also analyzed by using the SPSS technique – version 23. This software is a window-based method that was used to analyze the quantitative findings that would be obtained from the respondents using different tools available in it. The SPSS technique was chosen for this study because the research process involved the analysis of large amounts of data that were otherwise difficult to analyze manually. Additionally, the data collected were analyzed using Microsoft Excel 2013. Descriptive statistical methods, such as tables and graphs were employed. Additionally, statistical data were calculated in several measures such as averages, standard of deviation, frequencies and percentages, and the degree of agreement. Pearson, Spearman, and liner regression were also used to measure the correlations between dimensions. Moreover, T-test and one-way ANOVA techniques were used to verify the effect of demographic variables on the declared dimensions.

Data Analysis and Discussion

This chapter contains information pertaining to the analysis of findings about how to bridge the knowledge gap at Saudi Aramco. It contains a section that discusses the statistical findings for the knowledge management practices in the organization and the demographic data relating to the informants. The data collected from the surveys are also analyzed here to test the hypotheses and present information that will be used in the analysis of the research questions in subsequent chapters. However, before reviewing the findings of the research questions, it is important to analyze first the demographic data characterizing the research respondents below.

Demographic Data

Gender

Gender was the first demographic variable investigated in the research data. In total, 370 respondents took part in the study. About 79.5% of them were male, while 20.5% of them were female. These statistics are highlighted in Table 4.1 below.

Table 4.1. Gender Distribution

The same findings depicted above are reflected in the pie chart below as Figure 4.1. It shows that there were more male respondents compared to female participants who took part in the study by a factor of 4.

These respondents were also classified according to age as depicted below.

Age

The respondents’ ages were highlighted as the second demographic variable in the analysis. According to Table 3.2 below, there were four categories of age. The first one was comprised of employees who were below 30 years, the second one was constituted of people who were between 30 and 40 years, the third one included employees who were between 40 and 50 years and lastly those who were between 50 and 60 years. A majority of respondents belonged to the first group (less than 30 years). This cluster of employees comprised 42.2% of the respondents. The second largest age group was made up of employees who were between 30 and 40 years (37.6%), followed by those who were between 40 and 50 years (13.8%) and lastly those who were between 50 and 60 years (6.5%). This analysis shows that most of the employees were young as opposed to old. Table 4.2 below summarizes this data.

Table 4.2. Age Distribution

The same findings highlighted above are also reflected in the pie chart below, which appears as Figure 4.2.

After the analysis of age, nationality was the third demographic variable evaluated. The findings appear below.

Nationality

The nationality variable was categorized into four key segments: Saudi, North American/Europe, Arabic and “others.” The majority of the respondents were Saudi nationals. They comprised 98.1% of the sample. The other nationalities were less than 1% of the population. These findings are summarized in Table 4.3 below.

Table 4.3. Distribution of Nationalities

The above findings are also reflected in the pie chart below, which appears as Figure 4.3.

The fourth demographic variable analyzed in this paper was education level and the findings are highlighted below.

Education level

The respondents were categorized into four education groups: high school (or less), diploma, bachelor, and graduate studies. Most of the respondents who took part in the study had a bachelor’s degree. Comparatively, the second largest group of respondents had finished their graduate studies and they comprised 18.1% of the total sample. Informants who had high school (or less) and diploma education levels were both 17% of the total sample. Table 4.4 below summarizes the findings.

Table 4.4. Education Levels

The statistics mentioned above are also graphically represented in the pie chart below, which is hereby highlighted as Figure 4.4.

After evaluating the education levels of the informants, the other demographic variable investigated in the study was “work field” and the results are depicted below.

Work field

The fifth demographic variable analyzed in the study was “work field.” This characteristic had three tenets: job group, work experience, and work field. Under the work field category, the respondents indicated that they worked in eight fields, which included accounting, management, economics, marketing, finance, MIS/IT, HR training and “others.” Most of the employees sampled worked in the marketing department. They accounted for about 49.5% of the total sample. The smallest groups of informants worked either in the economics department or in the “others” category. Table 4.5 below summarizes the findings.

Table 4.5. Work Field Distribution

The above findings are also reflected in the pie chart below, which appears as Figure 4.5.

Work experience

The employees who participated in the study were also asked to state their work experience. They were provided with five options, which included less than 1 year, 1 to less than 5 years, 5 to less than 10 years, 10 to less than 15 years, and 15 years and above. Employees who had accumulated between 5 and 10 years of work experience formed the largest group of employees (27.8%). The second biggest group of informants had accumulated 15 years (or more) in work experience and they comprised 25.9% of the total sample. The third and fourth largest informant groups constituted 22.4% and 19.5% of the total sample and they were of employees who had accumulated “1 to 5 years” of work experience and “10 to less than 15 years” of work experience. Table 4.6 below summarizes the findings.

Table 4.6. Work Field Distribution

The same data depicted above is replicated graphically in Figure 4.6 below.

Job position

Job position was also assessed as another demographic variable in the study. It was categorized into four segments which were “grade code 3-10,” “grade code 11-14,” “grade code 15-17,” and “grade code 18+.” Most of the respondents sampled were within the grade code 11-14. They comprised 45.5% of the total sample. The second largest group of respondents was associated with the grade code 3-10 and they comprised 45.4% of the respondents. The smallest group of respondents was only 7.8% of the total sample and they were within the grade code 15-17. Figure 4.7 below outlines the distribution.

An analysis of the respondents’ training was reviewed relative to the number of training courses they have enrolled in the company within the last five years. Based on this criterion, it was established that most of the respondents had participated in five or more training courses within the past five years. This group of respondents comprised 65.4% of the total sample. Those who had attended the same training course four times were 10% of the population. A third group of respondents who had attended the training sessions at least three times closely followed them. Those who had attended the same sessions two times were 8.9% of the total population, while employees who had attended training one time were about 4% of the total sample. Some employees also said that they had not attended any type of training sessions in the organization. They comprised about 1% of the total sample. Figure 4.7 below summarizes the findings.

Besides the above demographic data, the relationship between the dependent and independent variables were also explored and the findings appear below.

Findings of the Relationship between the Independent and Dependent Variables

As highlighted in the third chapter of this paper, the second part of the questionnaire investigated five dimensions of knowledge management. The first one was critical activities; the second one risk of loss; third one was communication skills; fourth one was culture and the fifth one was knowledge transfer. The findings for the first aspect of critical activities is highlighted below.

Critical activities (1^st dimension)

Table 4.8 below shows the results of critical activities as the first dimension of analysis in the questionnaire completed by the informants.

Table 4.7. Critical Activity (1^st Dimension) Findings

According to the table above, the highest response was S5, “KT is a key resource for my organization.” It had a mean of 3.192 and a standard of deviation of 1.1600. The second highest response rate was related to statement S1, which says, “Top management recognizes KT as a critical activity.” Its mean and standard of deviation were 3.251 and 1.1412, respectively. The third highest response was S4, which says, “KT is fostered and encouraged in my organization.” Its mean and standard of deviation were 3.282 and 1.0853, respectively. The fourth highest response rate was attributed to statement S2, which stated, “Adequate organizational resources are dedicated to knowledge sharing.” Its mean and standard of deviation were 3.222 and 1.0385, respectively. Conversely, the least response rate was highlighted in statement S3, which stated, “Intellectual assets are valued and appreciated in our organization.” It had a mean of 3.275 and a standard of deviation of 1.0196. The general results for this dimension of analysis are outlined below.

Result Analysis: In sum, the result showed that the mean of the first dimension of analysis (critical activities) was 3.24 with a standard of deviation of 1.088 and an “agree” degree of response. This result shows that the employees of Saudi Aramco agreed to the fact that knowledge management was a critical activity in the firm. The second dimension investigated in the review sought to find out if the risk of loss affected knowledge transfer. The results are depicted below.

Risk of loss

The second dimension investigated in the study was about the risk of loss. Table 4.9 below shows the results of this analysis in the questionnaire completed by the informants.

Table 4.8: Risk of Loss (2^nd Dimension) Findings

The highest response was observed in statement S8, which stated, “Younger workers need more training to carry out their processes.” It had a mean of 4.112 and a standard of deviation of 1.070. The second highest response was associated with statement S9, which stated, “Younger employees need supervision.” Lastly, the statement with the least response was S6 and it stated that, “My operations will be affected by the retirement of older workers.” Both S9 and S6 had mean figures of 3.877 and 3.261, respectively. Their standards of deviation were also 1.125 and 1.211, respectively. The general results for this dimension of analysis are outlined below.

Result Analysis: In sum, the results depicted above show that the mean of the second dimension of analysis (risk of loss) was 3.75 with a standard of deviation of 1.135 and an “agree” degree of response. These results showed that the employees of Saudi Aramco affirmed that the risk of loss has an effect on knowledge transfer. The third dimension investigated in the study sought to find out if communication skills had an effect on knowledge transfer and the findings are outlined below.

Communication skills (3^rd dimension)

The third dimension investigated in the questionnaire was communication skills. Table 4.10 below shows the results of the evaluation.

Table 4.9: Descriptive statistic of the Communication Skills, 3^rd dimension

According to the table above, the statement with the highest response was S12, which says, “KT is effective between older and younger employees.” It had a mean of 3.73 and a standard of deviation of 1.067. Statement S13, which says, “In my organization, seeking external help or advice is valued and encouraged” had the second highest response rate. It had a mean of 3.46 and a standard of deviation of 1.028. The fourth highest response rate was reported in statement S11 – “I am willing to share knowledge with employees.” The mean was 4.35 and the standard of deviation was 0.999. The statement with the fifth highest response rate was S10 – “Older and younger workers share a pleasant working relationship.” Its mean and standard of deviation were 3.59 and 0.997, respectively. The question with the least response was S10 – “Older and younger workers share a pleasant working relationship.” Its mean and standard of deviation were 3.58 and 0.996, respectively. The general results for this dimension of analysis are outlined below.

Result Analysis: In sum, the results depicted above show that the mean of the third dimension of analysis was 3.75 with a standard of deviation of 1.135 and an “agree” degree of response. This result showed that the employees of Saudi Aramco agreed to the fact that communication skills have a significant effect on knowledge transfer in the firm. The fourth dimension examined in the study sought to find out the effect of culture on knowledge transfer. Its findings are highlighted below.

Culture (4^th dimension)

The fourth dimension investigated in the questionnaire was culture. Table 4.11 below shows the results of the evaluation.

Table 4.10. Descriptive statistic of Culture, 4^th dimension

According to the table above, the statement with the highest response was S25, which stated that, “My organization supports KT culture.” It had a mean of 3.90 and a standard of deviation of 0.895. The second highest response rate was statement S26, which stated that, “My organization tends to share knowledge.” It had a mean of 3.79 and a standard of deviation of 0.865. The statement with the third highest response rate was S30 and it stated that, “My organization has the ability to value KT.” Its mean and standard of deviation were 3.50 and 0.994 respectively. The fourth highest response rate was in statement S29, which stated that, “KT is valued by my organization performance management program system.” It had a mean of 3.44 and a standard of deviation of 1.134. The statement with the least response was S28 – “KT is considered as a strength and not a weakness to employee performance.” Its mean and standard of deviation were 3.39 and 1.060, respectively. The general results for this dimension of analysis are outlined below.

Result Analysis: In sum, the results depicted above show that the mean of the fourth dimension of analysis was 3.55 with a standard of deviation of 1.002 and an “agree” degree of response. This results showed that the employees of Saudi Aramco agreed to the fact that culture has a significant effect on knowledge transfer. The fifth dimension analyzed in the study was knowledge transfer and its results are highlighted below.

Knowledge transfer (5^th dimension)

The fifth dimension investigated in the questionnaire was knowledge transfer. Table 4.12 below shows the results of the evaluation.

Table 4.11. Descriptive statistic of knowledge transfer, 5^th dimension

According to the table above, the statement with the highest response was S20, which says, “The value created by the KT is considered good.” It had a mean of 4.23 and a standard of deviation of 0.868. Statement S23, which says, “There is effort to train young employees about the organizational processes” had the second highest response rate. It had a mean of 4.05 and a standard of deviation of 1.154. The statement with the third highest response rate was S19 and it stated, “My organization’s policy and structure supports KT.” It had a mean of 3.93 and a standard of deviation of 0.961. Comparatively, statement S22 had the fourth highest response rate and it stated that, “Older employees should take a proactive effort to teach younger workers about organizational processes.” It had a mean of 3.88 and a standard of deviation of 0.931. The question with the least response was S21 and it stated that, “In my organization, it is easy to justify the resources spent on assimilating the transferred knowledge.” Its mean and standard of deviation were 3.74 and 1.071, respectively. The general results for this dimension of analysis are outlined below.

Result Analysis: In sum, the results depicted above show that the mean of the fifth dimension of analysis was 3.96 with a standard of deviation of 0.997 and an “agree” degree of response. This finding means that the employees of Saudi Aramco agreed to the fact that knowledge transfer was a critical process in the organization’s operations. The findings for the group statistics and variances appear below.

Group Statistics and Variances

Table 4.12 below explains the results of the group statistics.

Table 4.12. Group Statistics

An analysis of the effect of job position on knowledge transfer practices of Saudi Aramco was done using the Anova method and the results appear in Table 4.14 below.

Table 4.13. Anova (Job Position Effect on Knowledge Transfer)

According to the statistics shown above, the significance value of the relationship between job position and knowledge transfer is indicated as 0.028 indicating that the two factors are significantly related. The sum of squares also supports the same narrative because the findings between groups was 5.600 and within groups, it was 205.190. Generally, the results of the data analysis shows that the effect of job position on KT is.028, which indicates that it has a significant effect on knowledge transfer. Table 4.14 below also alludes to the same view.

Table 4.14. Job Position and Knowledge Transfer findings ANOVA

An analysis of the correlation among the five dimensions highlighted in this paper revealed the following outcomes in Table 4.15 below.

Table 4.15: Correlation among Variables

According to Table 4.15 above, all the five dimensions investigated in the paper were correlated. This fact is based on the 0.000 significance value attributed to them. They symbolize correlation because such an outcome is significant at the level 0.01 for a 2-tailed analysis. Although significance was established among the variables, the highest correlation emerged between dimensions five and four (knowledge transfer and culture). The second highest correlation was established between the fourth (culture) and first (critical activities) dimensions. This is because the variables had the second highest correlation value of.749^**. Lastly, two dimensions that had the weakest correlations were one (critical activities) and two (risk of loss).

The findings developed in this section of analysis have shown that all the five dimensions investigated in the study were correlated. This outcome was established because the Pearson’s correlation coefficient had a significance value of 0.000 for all the five dimensions explored. Generally, this finding shows that critical activities relate with risk of loss, communication skills, culture, and knowledge transfer. However, the strongest correlations were observed between dimensions five and four (knowledge transfer and culture). This finding aligns with the views of several research studies, which have shown the power of culture in influencing organizational outcomes (Bolisani & Scarso, 2014). For example, the study by Torabia and El-Den (2017) showed that the main aspects of organizational culture, which affected knowledge transfer, are artifacts, norms and shared beliefs.

Culture is central to bridging the knowledge gaps at Saudi Aramco because it innately describes what employees in the organization should do to inculcate new knowledge to younger employees. It also helps the younger employees to understand what they need to do to receive the knowledge from older workers. This way, the company’s institutional memory is preserved and the process is accomplished in a sustainable manner. Stated differently, when a culture of knowledge transfer is established in the organization, employees do not need a reminder (or external input from third parties) to improve their work practices. Here, culture acts as the binding force between older and younger employees to the extent that it would be difficult to notice generational differences among the employees. The role of culture in this context directly appeals to the research gap identified in the literature review section of this paper and the first chapter of this report because it was established that many organizations today experience knowledge gaps because of generational differences. The establishment of a strong culture of knowledge transfer ensures that such gaps do not exist because all employees are encouraged to work as one unit.

The least correlation observed in the study was between risk of loss and critical activities. Perhaps this finding could have been a result of the ambiguity associated with the concept of risk of loss for the organization because it could possibly be unclear how the risk of loss affects critical activities in the organization. Here, the lack of clarity could partly stem from the fact that both risk of loss and critical activities are tools for promoting or inhibiting knowledge transfer practices. Therefore, the workers did not properly establish a cause and effect relationship.

Hypotheses Testing

The simple linear regression was used to test the four hypotheses (highlighted as H1, H2, H3, and H4) in the study. As a recap, the project hypotheses are listed below.

• H1: Critical activities have an effect on KT performance.
• H2: Risk of losing critical knowledge has an effect on KT performance.
• H3: Communication skills between older and younger workers have an effect on KT performance.
• H4: Organizational Culture has an effect on KT performance.

Table 4.16 below highlights the outcomes for the hypotheses test.

Table 4.16: Hypotheses Test Findings

According to the table above, we find that critical activities had an effect on the performance of Saudi Aramco’s knowledge transfer program. This view is established because the significance is.000, which according to Kotur and Anbazhagan (2014) affirms a significant relationship between the variables measured. At the same time, the r-square value is 0.476, which signifies the same outcome. Based on these findings, hypothesis 1 (H1) “Critical activities have an effect on KT performance” is affirmed.

Based on the table above, we find that the loss of critical knowledge has an effect on the performance of Saudi Aramco’s knowledge transfer program. This view is established because the significance value of H2 is.000, which according to Gholami, Asli, Nazari-Shirkouhi, & Noruzy (2013) affirm a strong relationship. At the same time, the r-square value is 0.217, which signifies the same outcome. Based on these findings, hypothesis 1 (H2) “Risk of losing critical knowledge has an effect on KT performance” is also affirmed.

The above table also shows that communication skills between older and younger workers have an effect on the KT performance at Saudi Aramco. This view is established because the significance value of H3 is.000, which according to Ekore (2014) affirms a significant relationship. At the same time, the r-square value is 0.442, which signifies the same outcome. Based on these findings, hypothesis 1 (H3) “Communication skills between older and younger workers have an effect on KT performance” is affirmed. Lastly, the same outcome is true for H4 because the hypothesis “Organizational Culture has an effect on KT performance” is affirmed by the significance value of 0.000, which is depicted in the table above. The r square of.685 also supports a similar narrative. The results of the linear regression test for the hypotheses also affirm the above findings and they appear below.

Simple linear regression tests

The Results of the Simple Linear Regression Test for the Hypothesis H₁ appears in Table 4.17 below.

Table 4.17. Variables Analysis

The model summary in Table 4.18 below shows that the standard of error of the estimate was 0.57011 and the R-square was 0.476.

Table 4.18. Model Summary

A review of the results for the ANOVA test appears in Table 4.19 below.

Table. 4.19: ANOVA Test Findings

According to the table above, H1 is accepted because the significance value is 0.000, which is less than 0.05. The results for the second hypothesis test also appear in Table 4.20 below.

Table 4.20. Variables Entered For Testing H2

The r-square and standard of error of the estimates above were 0.217 and 0.69688 as shown in Table 4.21 below.

Table 4.21. Model Summary

The results for the ANOVA test are highlighted in Table 4.22 below.

Table 4.22. ANOVA Results for H2

Based on the findings highlighted above, H2 is accepted because the significance value is 0.000.

The results for the H3 testing appears in Table 4.23 below.

Table 4.23: Variables for H3 Testing

According to the table above, the variable entered when testing H3 were communication skills (D3) and knowledge transfer (D5). The model summary in Table 4.24 below shows that the standard of error of the estimate was 0.58818, while the adjusted r-square was 0.440.

Table 4.24. Model Summary for H3

The results of the ANOVA test are highlighted in Table 4.25 below.

Table 4.25. ANOVA Results for H3

According to the table above, H3 is accepted because the significance value is 0.000. The results of H4 testing also appear in Table 4.26 below.

Table 4.26. Variables Entered and Removed for H4

According to the table above, the variables entered when testing hypothesis H4 were culture (D4) and knowledge transfer (D5). The model summary highlighted in Table 4.27 below shows that the standard of error of the estimates were 0.44222, while the adjusted r-square was 0.684.

Table 4.27. Model Summary for H4

The findings of the ANOVA test appear in Table 4.28 below.

Table 4.28. ANOVA Test Results for H4

According to the findings highlighted above, H4 is accepted because the significance value is 0.000. Collectively, these tests show that all the four hypotheses were accepted. A discussion of these findings together with the results depicted in this chapter are discussed in chapter 5 below.

Conclusion and Recommendations

This chapter provides a detailed analysis of the findings highlighted in chapter 4. It is aimed at making sense of the statistical results by reviewing how the information presented in the findings section relates with different aspects of the research process and respondents’ characteristics. However, before delving into this analysis, it is important to understand that this study was guided by four research questions. They sought to establish Saudi Aramco’s critical activities, investigate which employees have knowledge and experience of value, explore the nature of knowledge transfer relationships between knowledge providers and recipients in the workplace as well as establish how Saudi Aramco could bridge the knowledge gap between the older and younger employees. The subsequent sections below analyze these research areas sequentially.

Saudi Aramco’s Critical Activities

The first research question investigated in this study was centered on understanding whether knowledge transfer was a critical activity at Saudi Aramco, or not. In chapter four, it was established that the top management of the organization considers knowledge transfer as a critical activity in the firm. At the same time, the employees of the company posited that the organization allocated adequate resources to this function. This finding shows that intellectual assets are valued and appreciated at Saudi Aramco. Therefore, knowledge transfer is a key resource for the organization. Based on the appreciation for the critical role played by knowledge transfer at Saudi Aramco, the need to ensure that there is no knowledge gap between older and younger workers is emphasized.

The realization that knowledge transfer is a critical tenet of organization activities draws attention to the core competency approach, which was highlighted in the second chapter of this paper. Proponents of this approach say that effective knowledge management systems are often developed when intellectual capital is deemed as a key resource for organizational prosperity (Meier-Comte, 2012). However, in the context of this study, it is pertinent to note a distinction between the ability of Saudi Aramco to improve its performance and its ability to improve its knowledge management systems. This is not to deny the complementary nature of the different elements of analysis because studies have also shown that they are critical tenets of organizational identities as well (Ivey, 2014).

Generally, the core competency approach demonstrate that when firms recognize KT as a critical resource, they achieve new heights of success. This core competency approach could also include the efficiency through which companies or organizations deliver goods or services to the market and the efficiency through which they do so as well (Simar & Rahmanseresht, 2017). The same competencies have allowed organizations to develop customized goods/services and optimize their logistics (Simar & Rahmanseresht, 2017). The process of employing qualified employees and disseminating a succinct vision for the organization are also other attributes or organizational efficiency that are attributed to the core competency approach (Simar & Rahmanseresht, 2017).

By understanding that KT is a critical activity in the organization, Saudi Aramco could enjoy many benefits that accrue at individual and group levels. Some of these benefits have been highlighted in the literature review section of this paper and they posit that, at an individual level, the firm could enjoy different benefits of knowledge sharing, including (but are not limited to) improved employee attitude, ability to meet deadlines, consistent performance and enhanced proactivity. At a group level, Saudi Aramco will benefit from the ability of its employees to work well in groups, increased contribution to organizational activities, improved employee attitudes, and increased participation at different levels of organizational performance (Francesca, 2017). These benefits notwithstanding, different researchers have also pointed out that knowledge sharing activities can be monitored across different levels of participation, including group discussions, interest groups, learning activities, seminars and conferences (Meier-Comte, 2012).

Consequently, by recognizing that knowledge management is a critical activity, Saudi Aramco needs to bridge the gap between its older and younger employees. The need to bridge this gap is partly highlighted by the second research question of the study, which is addressed below.

Which Employees At Saudi Aramco Have The Knowledge and Experience Of Value?

One of the key areas of focus for the research questions investigated in this study is the determination of which group of employees have the knowledge and experience of value. Based on the responses received from the research participants, older employees emerged as being the custodians of the company’s knowledge. This is because this group of employees have worked in the organization for a long time and are more familiar with its processes compared to their younger counterparts. However, this finding seems to contradict some of the demographic variables that emerged in the study (and which will be explored in subsequent sections of tis chapter) because it was established that most of the employees had more than 15 years of work experience in the organization. This finding means that most of the young employees in the company (who form a majority of the research informants) have worked for a long time in the firm without properly acquiring the skills needed to propel the organization further (in the absence of their older counterparts). Based on this analysis, the research problem, which was highlighted in the first section of this paper, is emphasized because there has been no proper knowledge transfer mechanism to help newer employees acquire the knowledge needed to undertake their functions. In this regard, older employees at the firms emerged as the custodians of the company’s most valuable intellectual capital.

Time should be considered a core tenet of Saudi Aramco’s effort to bridge the knowledge gap between younger and older employees. As highlighted in the literature review section of this report, the processual approach should be adopted in such situations because it helps managers to understand how to fill knowledge gaps between different groups of employees. In other words, this technique is useful in understanding how to undertake information sharing activities over a specific period. The adoption of the processual approach helps to understand how some of the dimensions highlighted in chapter four would fit within the wider context of knowledge exchange in the workplace. This is because this technique explains how cultural exchanges, decision-making processes, and structural change processes influence KT (Jasimuddin, 2012).

Many research studies have evaluated how the processual approach could be applied in KT settings by paying a close attention to the nature of interactions among different stakeholders as a measure of how they exchange knowledge and interact with each other (Abbott, 2016; King & Lawley, 2016). Although many processual analyses use time as the main unit of analysis, the process does not only stop at this point of analysis; instead, it extends to the conceptualization, analysis, and description of events or activities in an organization that fall within the context of knowledge management. The basic context of applying this technique in the knowledge management setting of Saudi Aramco is the understanding that social interactions and knowledge management in the firm often occur across a specified time. Here, the period taken for knowledge exchange to occur (and context, which this process occurs) are at the center of all social interactions that lead to knowledge exchanges. The uniqueness of this approach is temporality, which makes it different from other frameworks of analysis highlighted in this study.

The driving factors which influence how KT should occur between knowledge providers and recipients is the understanding that social interactions often occur dynamically and not necessarily in a steady manner. From an organizational perspective, the KT processes at Saudi Aramco could be representing the duality of agency and context of the relationship between knowledge providers and recipients. This analysis shows that contexts have always shaped the nature of interaction between older and younger employees, while knowledge providers are often the main protagonists of the same process. This same analysis shows that knowledge providers are the main drivers of the processes that lead to knowledge exchange. However, at the same time, the entire chain of knowledge transfer cannot only be explained by the actions of one group of workers. Thus, the actions of both knowledge providers and recipients should be viewed within varied, but specific, contexts that ultimately limit the kinds of information that could be exchanged. The insight and influence of information processing that should be happening between knowledge providers and recipients in Saudi Aramco could be limited by the same context. Here, the social interaction that should occur between knowledge providers and recipients should be analyzed through a cumulative process that recognizes the nature of knowledge transfer relationships between knowledge providers and recipients in the firm. This element of analysis is discussed below.

Nature of Knowledge Transfer Relationships between Knowledge Providers and Recipients in the Firm

The third research question investigated in this study involved understanding the nature of knowledge transfer relationships between knowledge providers and knowledge recipients at Saudi Aramco. Although this chapter shows that there is a significant gap between the older and younger employees of Saudi Aramco, most of the workers sampled said both sets of employees shared a pleasant working relationship. They also said they were willing to share knowledge among themselves. This expression of willingness indicates that the management of the company could enjoy employee buy-in when they develop a model for transferring knowledge from the older workers to the younger ones.

Relative to the above analysis, most of the employees believed that knowledge transfer between older and younger employees would be effective if properly adopted. A majority of them also emphasized the need to conduct training sessions between both cadres of employees as one way of improving the synergy between both sets of workers. The company’s management needs to exploit this opportunity for the advancement of KT because, as explained by the workers, the company is in a position to acquire the necessary resources to make this happen, including empowering the workers to communicate effectively. This view aligns with the fact that Saudi Aramco has traditionally embraced the need to seek external advice in improving its operational processes. This effort has mostly been aligned with its quest to improve its competitive position

According to Meier-Comte (2012), the efficiency of knowledge management often increases when managers are experiencing the need to know their competitors’ actions and how they are formulating, designing or implementing their business strategies. As mentioned in the literature review section of this paper, contextualized studies have shown the effect of knowledge management systems around the globe. Particularly, they have shown that the failure to nurture good relationships between knowledge providers and recipients have led to the failure of many organizations to manage their knowledge effectively and extract the most value from it (Simar & Rahmanseresht, 2017). Indeed, as Simar and Rahmanseresht (2017) posit, organizations that fail to realize the importance of having this effective strategy for managing good relationships in the workplace suffer a high possibility of experiencing serious gaps, based on the creation of knowledge gaps that would occur from their inaction. Relative to this assertion, Simar and Rahmanseresht (2017) add that such organizations could suffer different negative outcomes, such as a decline in quality of operations, operational redundancies, and the occurrence of mistakes and errors in organizational processes. The failure to understand the nature of relationships between knowledge providers and recipients also creates the likelihood that an organization’s knowledge resource would be depleted and the time and money involved in creating it would go to waste.

Based on the above findings, Saudi Aramco should not exclusively rely on its internal competencies or knowledge. Instead, its needs to borrow best practice standards from experts to maintain its key competencies. By doing so, it will tap into pools of information (or knowledge) that will allow it to improve its competencies, skills and strategies. Relative to this assertion, researchers have said that knowledge is not only accessed, but also internalized by organizations and stored to meet corporate goals (Francesca, 2017; Argote, 2012). This process is multifaceted.

Besides creating a common pool for accessing the knowledge, North and Kumta (2014) say that forging new relationships between different cadres of workers could also help to foster the generation of new intellectual capital. While many studies often highlight the need for knowledge exchange to occur between knowledge providers and knowledge recipients, they may have as well presented knowledge as a tangible resource, such as land, because their analyses mirror this analogy (Francesca, 2017; Argote, 2012). These discussions have happened within the context of understanding knowledge management approaches.

This analysis reflects some of the findings highlighted in the second chapter of this report, which showed that four types of knowledge management approaches could be used to repair relationships between different groups of workers. The first and second ones are the mechanistic and systematic approaches. The last two are the core competency and cultural approaches (Simar & Rahmanseresht, 2017). Based on the findings of this study, the cultural approach emerges as being the most relevant to this study because most of the informants’ responses emphasized the need to have a strong culture of KT.

The cultural approach to knowledge management traces its origins in the field of change management and looks at knowledge as a management issue (Ivey, 2014). Although technological management is treated as a useful tool for managing this resource, proponents of the cultural approach do not view it as the only instrument for doing so. Instead, they focus more on innovation and creativity (Simar & Rahmanseresht, 2017). Thus, they do not necessarily believe in manipulating explicit resources to manage knowledge.

In the context of the responses gathered in this paper knowledge sharing will happen within an institutional context because such a setup accommodates employees who work together and share their experiences within the same settings (Ivey, 2014). As Simar and Rahmanseresht (2017) point out, such setups help employees to share intelligence (freely) among their colleagues. There are two key assumptions underlying this cultural approach. One of them is that organizations, which pursue them, are often willing to shake up their organizational cultures to improve employee behaviors. Another one is that organizational behaviors are often changed whenever businesses have exhausted the limits of their technological innovations (Meier-Comte, 2012). These assumptions could help to provide clarity regarding the third research question, which is examining the nature of knowledge transfer relationships between knowledge providers and knowledge recipients at Saudi Aramco.

Which Employees Have the Knowledge and Experience of Value?

The third research question that was investigated in this study centered on exploring the kind of relationships that employees have at Saudi Aramco. According to Wambui, Wangombe, and Muthura (2013), such relationships could strongly predict the synergy among employees in the organization. This view has been supported by several researchers such as Óskarsdóttir and Oddsson (2017) who have highlighted the importance of improving employee relationships (especially between higher and lower ranking employees) because teamwork is a significant predictor of organizational success.

When the participants sampled in this study were asked to respondent to statements that alluded to understanding the kind of relationships they shared with their colleagues, most of them said that they shared a good working relationship with their bosses and with themselves. The problem with this kind of interaction has been the inability for both sets of workers to engage in meaningful conversations that would spur knowledge transfer. This view closely aligns with the concept of culture, which has been highlighted severally in this paper. The concept has a huge role to play in determining how employees are going to relate because the power distance between older and younger workers or high ranking and lower cadre employees shape how different sets of workers relate in the organization.

Relative to this analysis, when the respondents were asked to explain their views about the role played by different types of workers in the organization and how their operations would affect the overall firm performance, most of them said that the retirement of workers would significantly dent the organization’s operations. This view aligns with the findings highlighted earlier, which showed that older workers were the main custodians of the company’s most valuable information. In other words, a majority of the employees believed that if these employees retired from the organization, the firm’s performance would significantly be affected. In this regard, it is also important to point out that some of them felt that management was not making enough effort to address the needs of knowledge transfer in the organization. This view partly informs the assertion by some informants who believed that younger workers needed more training to carry out their duties and responsibilities. At the same time, most of the employees also said younger workers need more supervision when undertaking their duties. This positive view reported in this chapter could have acted as a prompter for most of the employees to regard it as a platform for sharing information. In other words, most of them believed that when younger employees could acquire the knowledge required in carrying out their functions if their older counterparts mentored them. At the same time, doing so would inadvertently make them at par with their older colleagues.

How Saudi Aramco Bridges the Knowledge Gap between Older and Younger Employees

The last research question explored in this study strived to investigate how Saudi Aramco’s employees could bridge the knowledge gap between younger and older employees. Based on the findings highlighted in chapter 4 about knowledge transfer as one dimension of study, this element of analysis indicates that Saudi Aramco should be encouraged to uphold its existing polices and structures because it is perceived not to support knowledge transfer. This perception could outline the cause of the knowledge transfer gaps in the corporation because its employees appear not to understand how the company’s policies and structures support intellectual capital growth. The company’s management needs to work on this problem because as explained in the works of Akhavan and Pezeshkan (2014), companies should not only implement robust knowledge transfer policies and practices but also make the employees aware that it is trying to do so. This view is supported by many human resource studies that have highlighted the importance of involving employees in organizational change processes (Óskarsdóttir & Oddsson, 2017; Wambui et al., 2013).

The value of actively involving employees in knowledge transfer is high because most of them already understand that the process is good for accomplishing organizational goals and promoting their career. At the same time, there seems to be an existing goodwill from most of the employees in the organization about intellectual capital growth because a majority of them said that the organization could easily justify the kind of resources it has spent on knowledge transfer. This view draws attention to the fact that although they recognize that there are still many loopholes in the implementation of the knowledge transfer system in the firm, the organization is striving to make a change in this regard. Here, it is also essential to note that most of the employees believed that older employees should take a proactive role in teaching the younger workers about what they have learnt on the job. This reason partly explains why most of the workers believed that there were not enough effort made within the organization to train young workers about the organization’s processes.

Culture emerged as an important dimension that relates with the research question that focused on exploring ways to bridge the knowledge gap between younger and older workers because it had the strongest correlation with knowledge transfer. However, opinion was divided among the employees regarding whether Saudi Aramco supports a strong knowledge management culture. However, it is difficult to ignore the fact that a majority of the respondents did not approve of this statement. In other words, they seemed to support the view that the organization supported a culture of knowledge management. This is one area of growing importance in the organization and it will form the basis for some of the recommendations that will be outlined at the end of this report. Stated differently, the need for the culture of Saudi Aramco to be changed to accommodate knowledge transfer practices in the firm should be a priority. This way, the organization will have a better understanding of how it could share knowledge through the creation of a new platform for doing so (Óskarsdóttir & Oddsson, 2017; Wambui et al., 2013).

Based on the respondent’s views, Saudi Aramco seems to be faring well in providing adequate details about its performance measures. However, it is failing in safeguarding the foundation of their success (the institutional memory of the corporation), which is currently in the hands of the older workers. Therefore, the oil company should find new ways of transferring the same knowledge to new workers to protect its success. Culture provides a mechanism for doing so. Within its framework, the importance of presenting knowledge management as a strength and not a weakness should be emphasized. In other words, older workers should be made to feel that transferring knowledge to their younger counterparts is a strength and not a weakness on their part. Here, they should not be made to feel that doing so would make them weaker than their younger peers. By doing so, knowledge transfer would be increasingly seen as a key tenet of the company’s performance measure record. These views largely explain why most of the employees believe that Saudi Aramco has the ability to value knowledge transfer.

Based on the research questions highlighted above and on the dimensions investigated in the study, critical activities emerged to have a significant effect on the knowledge transfer practices of Saudi Aramco. The risk of loss also had the same influence on the firm’s knowledge transfer practices and were moderated by communication skills, which similarly influences knowledge transfer practices (Óskarsdóttir & Oddsson, 2017; Wambui et al., 2013). A broader analysis of the effects of culture on the company’s knowledge management practices also showed that it influenced how the organization managed its intellectual capital. These findings fit well with the conceptual framework for this study because in the literature review section, it was predicted that critical activities, risk of loss, communication skills, culture and demographic variables would significantly affect knowledge transfer. These elements of the analysis were presented as the independent variables and knowledge transfer was the dependent variable. Thus, based on these different elements of the conceptual framework, it is plausible to argue that all the independent variables presented in the study shared a positive correlation with the dependent variable – knowledge transfer.

A deeper analysis of these findings showed that the five independent variables were explored as the five dimensions of knowledge transfer. Although, it was established that all the five dimensions shared a positive correlation with the process, respondents were asked varied number of questions to understand the effect of each dimension on knowledge transfer activities in the organization. The third and fourth dimensions had the highest number of statements attributed to knowledge transfer practices because each one of them had six dimensions analyzed. Risk of loss had the least number of statements because the respondents were only asked three questions. The high number of statements attributed to the third and fourth dimensions of analysis could largely be attributed to the broad nature of communication skills and culture as influential elements of knowledge transfer. For example, different researchers such as Chen, Hsiao, and Chu, (2014) and Chin-Hui (2015) have explored the influence of culture on knowledge transfer. They say it is a broad determinant of firm performance, which has its roots spread in knowledge transfer, dispute resolution, firm accountability, leadership practices, and human resource performance (among others). Therefore, its influence on knowledge transfer is only a small aspect of its effects on firm performance. However, this attribute should be regarded as a contextualized understanding of the effects of culture on human resource practices. Broadly, these views fit within a wider framework of characteristics attributed to the respondents who provided them. A detailed analysis of the demographic information is explained below.

Analysis of Saudi Aramco Employees’ Demographic Information

Based on an analysis of the demographic data, a statistically significant difference in knowledge transfer caused by changes in demographic information (gender, age, nationality, educational level, work field, work experience, job position, and training) occurred. For example, it is possible to deduce that most of the information or views presented in the study were largely representative of men who formed the majority of the respondents (79%). Although it could be argued that this percentage is largely biased towards presenting the findings outlined in this study through a male perspective, it is also important to point out that the gender distribution reported in this study is largely representative of the gender disparities that exist in Saudi Aramco. More importantly, it is essential to note that these disparities do not affect the quality of information presented in this review because it is an accurate reflection of the true characteristics of Saudi Aramco employees.

Based on the general age of the participants who took part in the study, it is also important to point out that the views highlighted in the study were largely representative of the younger workforce at Saudi Aramco because a majority of the respondents (42%) was less than 30 years. In addition, 37% of them were between the ages of 30 years and 40 years, meaning that about 80% of the employees who gave their views in this study were below the age of 40. Therefore, it could be argued that the findings of this review were largely representative of the opinions of a mostly young workforce in the organization.

The analysis of demographic data based on nationality showed that 98% of the employees who took part in the study were Saudi. This was not surprising because Saudi Aramco is a Saudi Arabian oil company and it is natural that most of the employees would be of the same nationality. Nonetheless, it is essential to point out that most of the views expressed in this paper are of an educated workforce because close to half of the respondents who took part in the study had a bachelor’s degree. Only 17% of them had high school (or lower) education level. These statistics imply that the majority of the employees were educated. Therefore, the information given provided by the respondents was mostly provided from an educated point of view. It is also essential to note that a majority of these respondents worked in the marketing department and with a work experience of 15 years or more. This analysis means that the views provided in this analysis could be understood to be from seasoned employees at the firm because the smallest group of employees (evaluated in terms of work experience) had worked for less than one year.

The hypotheses sampled were all accepted as per the findings of the simple linear regression tests. To recap, the analysis showed H1, which suggested that critical activities have an effect on Knowledge Transfer, was accepted. The same was true for H2, H3, and H4 because the statistical results also accepted that the risk of loss has an effect on knowledge transfer, communication skills have an effect on knowledge transfer, and culture has an effect on knowledge transfer.

Broadly, the findings of this study are instrumental in promoting employee development programs at Saudi Aramco because it improves their capacity to manage the organization’s problems (Law & Kamoche, 2015). Through the appreciation of the need to inculcate a culture that promotes knowledge sharing, the findings of this study are also instrumental in aligning individual goals with company objectives, thereby establishing a synchrony of purpose for the organization and the employees. More importantly, the workers of Saudi Aramco are in a position to benefit from the enhancement of job specific development. In comparison to the achievement of organizational goals, the managers of Saudi Aramco should take pride in the fact that the promotion of a culture of knowledge transfer would help in improving communication between older and younger workers, as well as increase the level of efficiency in the organization, including the improvement of work effectiveness. This benefit aligns with the improved correlation between the attainment of organizational goals and the expected human resource outcomes for the workers. Broadly, these outcomes set the stage for the formulation of list of recommendations for Saudi Aramco’s review.

Recommendations

• Saudi Aramco should strive to develop a robust infrastructure that fills some of the knowledge gaps that exist between older and younger employees by infusing the five dimensions of analysis (critical activities, risk of loss, communication skills, culture, and knowledge transfer) in the organization’s human resource framework.
• The firm should align its knowledge management practices with the overall organizational strategy to create good synergy between employee activities and operational strategies. Doing so will ensure that all employees “read from the same script,” thereby providing a common ground for different cadres of workers to interact and share knowledge freely (for the fulfillment of organizational goals).
• Saudi Aramco should nurture a culture that is not only cost-effective in developing and retaining talent, but also proficient in preserving its institutional memory and storing or transferring the lessons learnt. These elements of analysis should be the checklists for the new culture.
• Saudi Aramco should work to promote the development of trust among employees. More importantly, it should leverage a new culture that promotes trust between older workers and new employees. From this framework, there should be an established framework, which will act as a control mechanism where the organization’s implicit and explicit rules of engagement are properly defined. This recommendation is based on the understanding that most of the knowledge available at Saudi Aramco is implicit (if it was explicit, there would be no need for fostering knowledge transfer). Since the firm’s intellectual capital is tacit, there is a need to promote trust between younger and older employees.
• Saudi Aramco’s processes for creation and transfer of knowledge in the organization need to transcend the micro process of organizational performance and accommodate aspects of its macro-environment. Stated differently, the process should also accommodate change management aspects of organizational performance by including “soft issues” about knowledge transfer.
• Changes to the organization’s knowledge transfer processes should include both individual and organizational KT goals. Here, there needs to be a basis for forging a mutual understanding between senders and receivers of knowledge transfer.

Future Works

This study was developed from the backdrop of a gap in knowledge transfer between older and younger employees in Saudi Aramco. Emphasis was made to highlight the differences between the technical knowledge held by older employees, vis-à-vis those held by younger ones. Data was collected using surveys as the primary information collection technique. The aim of collecting data this way was to meet five main research goals of this paper. They included providing an inventory and catalogue of Saudi Aramco’s critical activities, determining the risk of loss of critical knowledge, skills and behaviors at the firm, preparing the organization to minimize knowledge gaps, establishing knowledge transfer relationships between knowledge providers and knowledge recipients, and developing knowledge transfer plans for identifying at risk knowledge. This study specifically focused on Saudi Aramco because, as highlighted in the first chapter of this study, the firm has a huge pool of employees waiting to retire. By focusing on this organization, findings that would enable Saudi Aramco to prepare for knowledge transfer were generated.

The findings of this study would enable Saudi Aramco to prepare for knowledge transfer, while the focus on this area of research will allow the organization to fill its knowledge gaps and skills. Collectively, the focus on KT presents an opportunity for the Saudi-based oil corporation to develop an infrastructure of knowledge transfer for its future posterity. Similarly, by adopting some of the recommendations outlined above, the company will be able to develop the skills of individuals for targeted or critical jobs. By doing so, Saudi Aramco will be in a position to improve its productivity and business performance. Similarly, using the findings of the study, the firm will be able to develop and train individuals for targeted or critical jobs. By doing so, it will be in a position to improve its productivity and business performance. However, future research should focus on the areas highlighted below.

• Understanding the key attributes of older and younger workers, which often creates gaps in the attainment of operational synergy. Here, efforts should be attuned to understand the attitudinal differences, adaptation dynamics, and differences in belief patterns or values that make older and younger employees disjointed in their approach to work processes.
• Increase the number of statements respondents are asked to find out whether the findings depicted in this study will remain true after the change. This recommendation stems from the fact that only 25 statements were used to explore the respondents’ views about the five dimensions of analysis. Thus, the informants could be asked more statements to find out whether they would still have the same views highlighted in this paper.
• Knowledge management has emerged to be a dynamic topic that has multiple levels of assessment. Future research should also focus on understanding some of the “soft issues” surrounding knowledge transfer that would affect Saudi Aramco. This recommendation is stems from the fact that this paper largely relied on a quantitative assessment of the respondents’ views. In future, a study that mostly relies on subjective issues regarding knowledge transfer could be undertaken.

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