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Small and Medium-Size Enterprises’ IT Solutions Essay


Introduction

The Internet of Things (Internet of Things) will grow over the next years in application and adoption. As it grows, its associated technologies will also have to undergo major advancements to accommodate customization and scaling needs of the Internet of Things.

For example, privacy, security and semantic interoperability are all features that need further attention. In addition, other IT advancements like cloud technologies and big data, as well as future networks like in the case of proposed 5G will also have to be considered when contemplating the adoption of the Internet of Things now and in the medium-term.

For Small and Medium Enterprises (SMEs), the IT solutions combined with the Internet of Things, promise to enhance competitiveness and to make the daily running of businesses easy. Enhancement will come through better customer relationships, better supply chain management and relationships, as well as the provision of an affordable innovative avenue that translates to better services and products.

However, the uptake of cloud computing, big data analytics, the Internet of Things, among other features faces the hurdle of overcoming sceptical thoughts about the advancements and their actual need for SMEs (Ruggieri & Nikookar 2013).

This paper will review academic literature whose focus is on factors that drive emerging information technology uptake among SMEs. In evaluating literature for inclusion in the various discussions that follow, the author will be keen on evaluating factors that affect uptake, characteristics of the uptake, and emerging trends about uptake in both SMEs and bigger organizations.

However, a review of bigger organizations is only done to form a comparison basis, without steering away from the topic of the paper. The first part of the paper explains the methods used to gather information that forms a part of the discussion. The methodology section also explains the reasons for picking the given method over other research methods that are available.

The next part covers theoretical literature that explains why SMEs would adopt the various technologies and expected consequences by SMEs that would influence the uptake. Here, the paper concentrates on the categorization of technology needs, the theory of planned behaviour and the task-technology fit theory.

The theoretical framework forms the basis of presenting the results of the secondary review used as the main data collection method for the research. In the findings section, the paper systematically reveals the impact of adopting major emerging information technologies on SMEs. It breaks down specifics about the four mentioned technologies.

It also refers to the contextual environment facing SMEs when they take on these technologies. The impact is considered in terms of the objectives achieved due to the technologies and associated costs.

In pursuing the topic of this paper, the critical section offers explanations of the findings to link them to theory and provide the reader with a basis for understanding the overall impact of the technologies to SMEs. A critical scrutiny section helps to reconciles various divergent thoughts expressed in the introduction and the findings section.

Research mythology

The findings of this research come from a secondary literature review guided by the paper’s title. The researcher relied on internet sources for publications that discuss the present and past features of SMEs adoption of the novel IT features. The search also covered published research findings from other scholars to make deductions and to inform the analysis part of the paper.

Application of theory/methods

This paper will rely on the theories about diffusion as they apply to technology adoption in reviewing the various research reports and industry reports on the use of technologies. The various states of technology adoption are awareness, interest, evaluation, trial, and adoption. The provided states allow practitioners to categorize a country, institution, or sector according to its stage of adoption.

Alternatively, adoption could be categorized in the form of two categories; the innovators and the imitators. This would apply to the users of the technology and its creators. SMEs that are innovators would be those that base their decision to embrace the solution independently. Meanwhile, the imitators would be the ones that are influenced by other firms and industry trends to adopt the given technologies.

According to the theory of planned behaviour (TPB), behavioural intentions rely on the attitude about the likelihood that a given behaviour will lead to an expected outcome. At the same time, it will depend on the subjective review of associated risks of the behaviour and the benefits of the outcomes.

In this respect, when looking at an SME as a social entity, its behaviour of adoption will depend on its attitude or the known features of adopting, as well as the expected outcomes and the risk associated with the uptake compared to its benefits (Al-Qirim (ed.) 2004).

The use of the TPB is informed in part by the fact that in SMEs, the business owners mostly behave like individual decision-makers. At the same time, the secondary literature available shows that new technology adoption, behaviour of SMEs is similar to a person’s processing of adopting technologies.

However, in the business case, social influence would translate to influences happening in the competitive environment, such as the need to grow competitiveness or to catch up with the competition (Dahnil et al. 2014).

Lastly, the Task-Technology Fit Theory is also useful in explaining the adoption of technologies. According to the theory, the task and technology characteristic will affect its suitability and performance when used by humans and compatibility affects adoption (Dahnil et al. 2014).

Findings

Infrastructural factors that contribute to technology uptake by SMEs

A requirement of cloud computing is that the infrastructure must have access to data anywhere, anytime, and on any devices at a level that meets the minimum threshold of quality service.

In many European countries and in North America, a high number of individuals have access to broadband and almost all corporate entities are hooked to broadband internet services. The existence of a network of connected individuals and companies provides the market requirement for cloud computing and offers demand for the service (Kloch, Petersen & Madsen 2011).

For cloud computing to make sense, it has to be combined with broadband and for SMEs; the inclusion of e-commerce makes the uptake more exiting in the business sense.

According to Kloch, Petersen and Madsen (2011), there is a huge number of SMEs that still apply manual billing systems, like the use of Excel-like systems. Such SMEs are also ill equipped in their respective IT departments, such that they are unable to embrace advances in the automation of their systems. As a result, they spend most of their human resources on their manual system.

For the society, which includes businesses of all sizes, to benefit from the possibilities of Information and Communication Technologies (ICT), the applied processes must be efficient. In this regard, there is a need for ease of maintenance, flexibility, and scalability to a worldwide platform.

A possible solution has been to remove the hardware limitations caused by the geographical and physical needs of hardware for computing. Instead, solutions are offered by cloud computing, which serves as the necessary infrastructure upon which other normal business system services lay (Kloch, Petersen & Madsen 2011).

In Hong Kong, the existence of an excellent and affordable ICT infrastructure that supports the delivery of secure e-services and the development of the local ICT industry has been instrumental in facilitating the update of cloud computing, big data analytics, and the Internet of Things (So 2013). In addition, market liberalisation has allowed internet access to penetrate throughout the population at an affordable price.

In such a geographically small area, in comparison to the mainland China, the broadband penetration is 85 per cent (So 2013). On the other hand, Hong Kong enjoys a mobile penetration rate of 231 per cent, which makes it one of the highest in the world. Typical speeds for users are about 10 Mbps, while peak speeds reach more than 60 Mbps (So 2013).

Consequences of taking up emerging information technologies

Now and then, SMEs have to deal with the fact that technology comes along in a way that is so profound, powerful, and universal, such that it changes the way of doing business totally (Ramsey et al. 2003). In theory, the top performing SMEs are the ones that embrace ICT in all their operations.

The reason for this theory is that the services and systems under ICT provide a business with competitive advantages, which are distinctive in the first instance, but they become common after wide adoption.

Even then, the businesses that are left out of the ICT bandwagon cannot match efficiencies and scalability enjoyed by their counterparts that are already seeking more robust ICT features to improve their production processes and service delivery, as well as customer and supply chain relations (Ramsey et al. 2003).

In 2003, according to research by Ramsey et al. (2003), most SMEs in European countries were not using ICTs, such as the Internet for commercial transactions. They were missing out on the benefits of e-business and the upstream or downstream application.

In North Ireland, 83 per cent of business respondents mentioned that they had no strategy for including the Internet or ICT in general as part of their marketing strategy (Ramsey et al. 2003).

On the other hand, overwhelming evidence also presented by Ramsey et al. (2003) shows that despite the numerous possibilities of ICT and the different levels of maturity for e-commerce usages, most SMEs have low-level requirements and they follow non-linear path.

Unfortunately, at the time, available models were weak in theoretical underpinning, even though they obliged to the principles of e-business. Nevertheless, most SMEs were subjected to heavy usage of their scarce resources on these models (Ramsey et al. 2003).

Zhuge (2011) helps to link human intelligence and control to the advancement of intelligent information processing technologies and their various uses. The research notes that unlike humans, machines can only process pre-designed algorithms and data structures in the cyber space. They cannot move beyond the cyberspace to learn thinking rules or know the effect of linking.

Neither can they explain what happens when computing results are added to physical, psychological, and social laws. Nevertheless, researchers, developers, and practitioners are advancing their knowledge and applications that link various spaces to create a complex space, where cyber space is only a part of it. A consequence of such integration is the development of cyber-physical-psychological-socio-mental environment (Zhuge 2011).

Indeed, Zhuge (2011) points out the possibilities of linking various spaces to realize a human-machine environment uniting society, cyberspace, and nature. Here, patterns of social individuals’ movements are collected and analysed to reflect the status of the individual or a society. With these patterns, it is possible to provide appropriate services to users and to make the right decisions to change a given status.

Thus, the application of the interconnections is helpful to both organizations delivering goods and services and consumers of the goods and services, as it increases understandings of entire systems of components of the system.

According to Mui (2012), SMEs adopt business intelligence products and services for growth, differentiation, and agility. They are able to understand their businesses and make better decisions, which should lead to more sustainable growth together with differentiating pursuits and agility. This is what Zhuge (2010) theoretically presumed when contemplating the effect of super networked spaces.

Cloud technologies that incorporate in-memory computing allow businesses to obtain immediate answers through a remarkable increase in the speed of analytics. They also get real-time access and deeper insight as they can interrogate a large scope of granular data. Moreover, the solutions are simpler and more cost-effective because the IT complexity burden is low (Mui 2012).

With big data analytics, it is possible to employ in-database, predictive algorithms to obtain various insights into internal and external business trends. At the same time, SMEs can access open source algorithms that directly integrate into their big data analytics systems, such that they would not have to incur additional programming and customization costs.

Moreover, it is possible to embed specific or entire components of the big data analytics framework to existing business platforms and extend the obtained business intelligence into company reports, with delivery options of the information happening real-time to companywide communication channels, such as alerts to smartphones (Mui 2012).

The European Commission (2013a) evaluated the current adoption, plans of adoption, and drivers or barriers of big data usage by EU companies. The report shows that big data include hardware and software integration, organization, management, and analysis with the presentation of data that is massive in volume of data and is varied in the breadth of data sources and formats (European Commission 2013a).

In addition, there is a velocity characterized by a high speed at which information arrival, analysis and delivery happen, and value characterized by cost of technology and utility (European Commission 2013a).

Why SMEs are forced to adopt additional technologies after stepping into the ICT bandwagon

When considering adoption of big data, SMEs have to invest in the following features either as services provided by intermediary companies or as an in-house solution. They need the infrastructure, which includes storage systems, servers, and data centre networking. They also need software to manage and organize data, software to analyse and discover, as well as decision support and automation software.

Other than that, companies implementing big data technologies need business consulting services, business process outsources, and other outsourcing services for IT and IT project based. They may also demand support and training services for big data implementations (European Commission 2013a).

According to Miller and Mork (2013), SMEs require a plan that considers the entire continuum of big data application from the begging of data collection to the final decision based on the data collected. Thus, the biggest benefit arises when all stakeholders in the continuum integrate big data solutions.

After a decade of the Ramsey et al. (2003) research that reported limited uptake of ICT by SMEs, the European Commission (2013b) report quotes a 29 per cent figure for European companies that are ready for big data uptake. At the same time, a majority of business included in the survey content that they need to re-asses their current information management processes to meet the challenges of data growth.

Nevertheless, big data adoption is still in its infancy at 6.2 per cent for SMEs, with 10 to 250 employees (European Commission 2013b). However, from the same survey, trends show that adoption among SMEs will increase significantly due to vertical integration along the supply chain and in particular industries, such as financial, oil and gas, telecom, computers, and electronics where data processing needs are high.

Drivers of adoption include the data explosion witnessed in recent years. In fact, compared to 2003 when Ramsey et al. (2003) made their report, 2013 witnessed an extraordinary increase in internet usage and data transfers. The world now creates about 2.5 quintillion bytes of data daily (Xia et al. 2012).

Today, sources of data include social media, digital imaging and video, smart meters, non-traditional networked smart devices, and machine to machine communication in factories. IT vendors are also producing tools for collection, storage, and analysis to meet the emerging needs of dealing with the data. Consumers and customers are also becoming more connected and demand access and availability of ready-to-use information.

As consumers demand personalization, they are ceding more privacy to enterprises. Now data and personalization is not only happening in traditional environments like call centres and mobile applications, but also on cars and domestic appliances in the Internet of Things.

But, as hinted earlier, resistance to share personal and proprietary data and information will remain hindrances for the adoption and full utilization of cloud computing, big data, social media, and the Internet of Things. For SMEs, the lack of time and resources to study trends and opportunities and threats serves as a barrier for uptake of the IT innovations.

Language differences make data analysis complex, just like differences in national regulations on privacy and data usage also complicate matters for SMEs seeking to fully utilize the novelty of the various technologies.

According to Duhnil et al. (2014), social media is among the most popular novel IT technologies embraced by SMEs across the world. Social media has become a fresh tool for marketing communication. It fits well with the need to deploy rapid and dynamic campaigns for businesses that are already using other forms of electronic media.

Its adoption is helped by the social uptake of the technology and service, which now make it relevant for both businesses and customers (Michaelidou, Siamagka & Christodoulides 2011).

Social media marketing is now a subset of marketing, where the marketing practices, information, and ideas spread through social media online. Nevertheless, social media marketing and usage are not social marketing. The latter is the bigger environment within which the former falls into (Dahnil et al. 2014).

End users remain a major factor in influencing the adoption of social media by SMEs; a second influencing factor is the technological orientation of the SMEs, which determines just how compatible the intended adoption will be. A third reason is the management when looked at from the business environment perspective (Durkin, McGowan & McKeown 2013).

Critical analysis

The uptake of cloud computing, big data analytics, and the Internet of Things among SMEs globally has not been very successful in the past decade, as it would be expected. Part of the reason, as elaborated in the findings of this paper, is the misalignment of risk and costs with the expected benefits of the technologies.

As the European Commission (2013a) report stated, the uptake was more in bigger companies than in SMEs, which would be partly attributed to the accessibility of technology.

The findings have also shown that SMEs have discontinued systems that would benefit most SMEs in integration, but the integration would be too costly. In this respect, it is not surprising to see that there are many research reports on SME adoption of social media compared to the Internet of Things, Big Data analytics, and Cloud Computing.

During the research, this researcher encountered many pointers to social media usage by SMEs, especially in their marketing efforts. It explains why the other features of IT developments have not caught up with business owners.

The reason is that they do not directly affect the customer as much as social media does. Most help in the backend, thus they are not readily considered as revenue generating opportunities for the small and medium firms. As Mui (2012) and Zhuge (2011) showed, the uptake of networked based implementation, such as big data analytics and the Internet of Things depend more on the level of vertical integration.

Thus, when one compares firms operating in highly integrated industries, such as the financial sectors, one is most likely to find SMEs that embrace cloud technologies and big data, while those in manufacturing chains may not have deep linkages with vertical partners other than basic business process relations (Schwertner 2013).

The limited uptake among SMEs of the mentioned technologies is changing rapidly because the cost of not catching up to the competition is rising. The demand for efficient and usable systems for handling data will also increase among all business sizes, thus SMEs are not spared.

As the report by So (2013) on Hong Kong highlighted, and as Zhuge (2011) also contemplated, the future will see the connection of various spaces to realize a multi-networked environment where data gathering and analysis will be key to survival and understanding. Thus, SMEs will undoubtedly have to adopt at a faster rate than they currently do.

Limitation and implications

This research was restricted in scope by relying on secondary literature. It does not provide new information other than the analysis due to the lack of primary data sources as part of its limitation. Another limitation of the research would be the existence of errors in the researches and reports consulted for the study, or biases exist in the scholars’ analysis of their findings.

Nevertheless, the paper serves as an important contribution that brings together the analysis of big data, the Internet of Things, cloud computing and social media in one report. Thus, practitioners will be able to get insights at a glance. Lastly, the recommendation to SME owners is that they should embrace these technologies as a matter of survival.

Conclusion

The adoption of cloud computing, big data, the Internet of things, among emerging technology has only recently peaked among SMEs. This paper revealed, in the findings and critical discussion sections, details of the uptake and its impact on SMEs. The main points are that in the past, most ICT solutions demanded considerable capital investment, even after the initial adoption.

Moreover, there were still challenges of matching returns and costs of investment. Prior to the development of necessary infrastructure for adoption of emerging technologies, the impact on SMEs adoption was limited to early adopters. However, adoption has become a process of gaining competitive advantage and no SME wishes to remain behind.

Nevertheless, factors such as industry type and capital demands for adoption still affect the ability of SMEs to fully integrate their systems with upcoming technologies. Better market information intelligence gathering has been an observable result in the areas where integration has been successful, such as social media and cloud computing.

The development of nationwide data infrastructures cut the cost of implementing ICT solutions and an increase in the Internet of things and other data usage creates a market demand for SMEs to adopt emerging technologies.

Therefore, the overall present impact of adopting technologies is the increased catch-up ability to competition, better provision of services to match changing market needs and substantial reduction in costs or an increase in innovativeness to drive competitive abilities of SMEs in some cases.

Reference List

Al-Qirim, N (ed.) 2004, Electronic commerce in small to medium-sized enterprises, Idea Group Publishing, Hershey.

Dahnil, MI, Marzuki, KM, Langgat, J & Fabeil, NF 2014, ‘Factors influencing SMEs adoption of social media marketing’, Procedia – Social and Behavioral Science, vol 148, pp. 119-126.

Durkin, M, McGowan, P & McKeown, N 2013, ‘Exploring social media adoption in small to medium-sized enterprises in Ireland’, Journal of Small Business and Enterprise Development, vol 20, no. 4, pp. 716-734.

European Commission 2013a, ‘Business opportunities: Big data’, Report, EC.

European Commission 2013b, . Web.

Kloch, C, Petersen, EB & Madsen, OB 2011, ‘Cloud based infrastructure, the new business possibilities and barriers’, Wireless Personal Communications, vol 58, no. 1, pp. 17-30.

Michaelidou, N, Siamagka, NT & Christodoulides, G 2011, ‘Usage, barriers and measurement of social media marketing: An exploratory investigation of small and medium B2B brands’, Industrial Marketing Management, vol 40, no. 7, pp. 1153-1159.

Miller, HG & Mork, P 2013, ‘From data to decisions: A value chain for big data’, IT Professional, Jan-Feb 2013, pp. 57-59.

Mui, E 2012, ‘Do small businesses have big data needs?’, Ecosystem & Channels Product Marketing at SAP, SAP AG.

Ramsey, E, Ibbotson, P, Bell, J & Gray, B 2003, ‘E-opportunities of service sector SMEs: an Irish cross-border study’, Journal of Small Business and Enterprise Development, vol 10, no. 3, p. 250.

Ruggieri, M & Nikookar, H 2013, Internet of things: Converging technologies for smart environments and integrated ecosystems, River Publishers, Aalborg.

Schwertner, K 2013, ‘Modern Information Technology (IT): Factor for business efficiency and business driver’, Journal of Modern Accounting and Auditing, vol 9, no. 8, pp. 1131-1139.

So, G 2013, ‘Public consultation on 2014 digital 21 strategy’, Commerce and Economic Development Bureau, Hong Kong.

Xia, F, Yang, LT, Wang, L & Vinel, A 2012, ‘Internet of Things’, International Journal of Communication Systems, vol 25, no. 9, pp. 1101-1102.

Zhuge, H 2011, ‘Semantic linking through spaces for cyber-physical-socio intelligence: A methodolgy’, Artificial Intelligence, vol 5, no. 6, pp. 988-1019.

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