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Academic research is critical to finding answers to a problem. A study’s methodological approach depends on the research question, which is fundamentally a hypothesis framed as a query. In the quantitative paradigm, observed trends are investigated objectively to clarify or predict trends in phenomena. It is utilized to find solutions to a problem based on specific variables. This paper discusses the suitable quantitative methods for resolving research questions (RQs) claimed by an author of a dissertation and describes relevant data for addressing the RQs.
The dissertation investigates the dynamics of social capital stimulation in organizations. Specifically, it examines the connection between the structure of social relations in companies and employee performance. This problem is reduced to two research questions for inquiry: “how do people use the social resources accessible to them under their position in the structure? And what organizational interventions can help people forge valuable new connections in the workplace?” (Srivastava 2012, p. 1). An abstract concept examined by the study is social capital. Employees develop network ties that can be tapped into to bolster performance, especially during organizational change.
Suitable Quantitative Research Methods
Quantitative measurement of social capital in firms and how people utilize interrelations and resources in organizations can be problematic given its abstract nature and context-specificity. One appropriate method for investigating the above RQs is a correlational study design. In this approach, no variable is experimentally altered. It entails empirical measurement and determination of the relationship between the dimensions of social capital. Thus, validated instruments can be used to measure social resources available to staff and the effect of firm interventions on workplace connections.
In empirical studies, a social capital scale comprising Likert-type rated items is utilized to collect quantitative data. Adams, Harris, and Lindsey (2017) used a pretested social capital scale to evaluate aspects of social capital, such as trust and reciprocity, in organized networks (sports clubs). Based on the instrument, it was possible to assess the impact of social policies. A similar approach could be used to identify organizational initiatives that support the formation of new relations consistent with the second RQ.
Correlation analysis would help establish the relationship between social resource utilization and position in the organization. Additionally, multiple regression analysis could be used to determine how each social capital dimension affects the formation of new connections by the subjects.
A second suitable quantitative method is longitudinal or panel study. It allows the measurement of repeated observations over a period to determine changes in behavior. Despite being an observational/qualitative approach, a longitudinal design would be appropriate for investigating the development of new workplace relations over time as a specific outcome of organizational interventions (Wang & Hou 2015).
Repeated measurements would allow long-term tracking of the same subjects. Srivastava (2012) utilized a large panel of archived data to measure how individuals in organizations mobilize social resources at a personal level. A repeated measures design could give a high statistical power because it relies on a longitudinal (administrative) dataset or census records on motivation or other personality characteristics (Kim 2018). Thus, it would be useful in assessing changes in the patterns of use of social resources at different organizational levels over time.
Analysis of longitudinal data would require the analysis of variance (ANOVA). In this approach, group differences at two points are assessed. The method is valid here as the second RQ requires an evaluation of changes in workplace connections due to an organizational intervention over time. Thus, repeated measures are treated as variables. A limitation of this approach lies in the assumption that the outcomes exhibit equal variances. However, it gives subject-specific trends that can be used to gauge the influences of organizational interventions on the formation of new workplace relations.
A third most appropriate quantitative method is a multi-source cross-sectional design. This approach requires that data collection occurs at a specified period. A cohort of employees from multiple organizations can rate individual utilization frequency of the available social resources as at that time using ordered categories. Subsequently, the researcher can use the data to determine if there is an association between employee position and usage levels.
Indicators of utilization can be used to estimate this link. Loch et al. (2015) found an association between a low overall social capital score and low leisure-time activity in adult workers. Their study also established that social capital reduces risky behaviors. Thus, a cross-sectional design would help identify organizational policies or initiatives that promote the formation of new connections in workplace settings.
The main downside to the cross-sectional design is its low statistical power compared to longitudinal studies. It does not involve repeat measures. Therefore, changes in the utilization of social resources accessible to the subjects occupying various positions in the organization may not be uncovered (Agyapong, Agyapong & Poku 2017). Cross-sectional data can be analyzed using cross-tabulation to compare measures between different organizations. Descriptive analysis can also show the relationship between how individuals use social capital and position.
Most Suitable Quantitative Research Method
A correlational design would be the most appropriate approach to resolving the two research questions. The first RQ has two variables: use of social resources and rank. Correlation research would help evaluate the association between them without the need for experimental manipulation. Similar studies have examined this relationship from different angles. Meng, Clausen, and Borg (2018) explored the correlation between social capital and job engagement.
Their findings indicate a positive relationship between the two variables. Thus, a correlational design would be critical to linking the use of social resources by staff and position in the organization. In this regard, the rank would be a crucial explanatory variable for the difference in how people use social capital.
Another more compelling reason for using a correlational design as opposed to a longitudinal or cross-sectional method is that not all organizational initiatives may be associated with improved new workplace connections. Therefore, though the association may not be a causal one, a correlation design would help delineate useful firm interventions or policies. Unni (2014) found a strong positive correlation between social capital and employee citizenship behavior. This association was attributed to specific organizational practices, such as advocacy and staff engagement, which encourage staff to create good relations among themselves as a way of improving individual performance.
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The relationship between the variables considered in the research questions is not a causal one. Based on this premise, a job position might not produce specific utilization patterns of social resources. Neither variable can be viewed as causing the other. For this reason, a correlational design is the most appropriate quantitative research method for finding solutions to the research questions. Even if there is a causal link, manipulation of one of the variables may impossible or impractical (Tantardini & Kroll 2015).
For example, an organizational initiative can be thought of as a possible trigger of new workplace connections. However, manipulating this variable may impractical or unethical due to the requirement of a control group. Thus, a more practical approach would be measuring identified indicators of new relations as outcomes of organizational interventions through various instruments.
A correlational design allows a researcher to use validated scales to measure variables. Tulin, Lancee, and Volker (2018) used a validated 5-item instrument – the Big Five – to assess personality dimensions that affect social capital. They found a relationship between extraversion and utilization of social resources. Thus, with a correlational design, instruments can be developed to measure how employees utilize social resources and relate that to organizational rank (Nam 2014). Additionally, social capital scales can indicate valuable new connections resulting from an implemented corporate initiative.
Data for Studying the Chosen Research Question
Social capital (SC) and its dimensions are intangible resources. Studying the association between how staff utilizes these assets and job rank (the first research question) would require survey data obtained using semi-structured questionnaires. In their research, Ben-Hador and Eckhaus (2018) surveyed Enron employee emails to assess the different effects of individual SC (ISC) and intra-organizational SC (IOSC) on staff vigor and success. After removing redundant emails, they extracted data and categorized the responses based on personnel occupation status. Correlation analysis found a positive relationship between ISC and staff vigor/success. The problem with such retrospective studies is the high rate of missing information or data.
The selected research question has two measurable constructs: the use of available social resources and job position/rank. They can be described as the dependent and independent variables, respectively. The relationship between the two constructs can be determined based on survey data obtained from employees working in one or more organizations. The utilization of social assets will be operationalized as “information, influence, and support” (Srivastava 2012, p. 21). The questionnaire will also capture the rank or job title of the respondents (senior managers, supervisors, and subordinates). Validated Likert-type items will be used to measure the variables. Validity (a pilot study) and reliability analysis – test/retest – will be conducted before administering the instrument to a larger sample.
The questionnaire will be administered using two modes: online and paper-based formats. The aim is to reduce the non-response rate. The respondents will rate items, such as how often they utilize social resources in the presence and absence of a crisis, on a scale. Correlation analysis will be used to determine the statistical relationship between social resource utilization score and job position, which is an independent variable. It is hypothesized that senior managers will use social capital more than subordinates do because they have greater access to this asset.
Quantitative research tackles a problem by posing a hypothesis or question. The aim is to collect and analyze data that would indicate relationships between variables. The dissertation’s research questions focus on how social resource use relates to the job position and the organizational initiatives that can spur new workplace connections. Three quantitative designs are considered appropriate for the RQs, namely, correlational, longitudinal/panel, and multi-source cross-sectional. Of the three, the correlational design that uses survey data is selected as the most suitable for resolving the RQs.
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