CCE Theses and Dissertations

Date of Award

2021

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

College of Computing and Engineering

Advisor

Timothy J. Ellis

Committee Member

Martha M. Snyder

Committee Member

Ling Wang

Abstract

Knowledge sharing (KS) has been determined by many researchers as an important tool for problem-solving experiences and achieving success. Recent studies have explained KS as an activity in which knowledge is exchanged through individuals or between organizations. KS can help facilitate decision-making capabilities, stimulate cultural change, and create innovation. Through KS, individuals and organizations can capture explicit and tacit knowledge to save time and money. Previous studies have indicated a lack of research in how perceived shared cultural values impact KS through a social media application.

The purpose of this research was to add new information to the body of knowledge in regard to identifying perceived shared cultural values as measured by demographic factors such as age, race, religion, language, and socio-economic status to understand how these characteristics impacted an individual’s ability to share knowledge through social media applications. The goal was to fill the gap in the literature by explaining the effect of perceived shared cultural values on knowledge creation and sharing through the usage of social media applications.

The results showed potential generalizability in identifying the type of KS (tacit and explicit) that will occur. Previous studies that focused on KS, culture, social media, and barriers are discussed regarding how these features impact an individual’s ability to share knowledge. Perceived shared cultural values were identified to gain an insight into how these perceived values correlated with actual knowledge being exchanged through social media applications.

To test the hypotheses, data were collected based on the analysis of social media postings. A total of 42 participants took the survey. The survey specifically collected the participants’ age, race, religion, language, and socioeconomic status. A total of 113 postings were collected, 30 of which contained no exchange of knowledge. The remaining 83 were analyzed independently by three subject matter experts. The postings of the knowledge being shared between the participants based on their perceived shared cultural values was analyzed and placed into two categories: tacit and explicit KS. The structural equation modeling technique was used to analyze the relationships between the different perceived shared cultural values. The tacit and explicit models were not supported. All ten hypotheses were not supported due to the p-values that were calculated through bootstrapping. The strength of the relationships was calculated and displayed by using SmartPLS. The data collected from the postings and the demographics collected through a survey were an attempt to test the 10 hypotheses.

The results indicated that all the hypotheses were not supported due to their significance levels. Several limitations existed in this study, such as sample size, diverse population, amount of knowledge being shared through the social media application, instructional method, and remote nature of teacher involvement. Implications regarding how this study differed from previous studies’ results were provided. Future research suggestions were made to extend the body of knowledge.

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