Mobile social media and social media: advancing our understanding of value creation, use behavior, and competitive intelligence
Authors:   , Ju Xingting 
Published: June 2022

The combination of social media and mobile technology has revolutionized the ways customers and firms create value. The purpose of this thesis is to better understand the role of mobile social media and social media in value creation. The thesis comprises three chapters. The first chapter provides a systematic literature review about mobile social media and value creation to illustrate how firms and customers apply mobile social media to create and co-create value. The second chapter focuses on individuals’ mobile social media use behavior. The study firstly examines the determinants that drive individuals to use mobile social media. Furthermore, the study detects unobserved heterogeneity among individual users and includes an international microsegmentation based on individuals’ behavioral patterns. The third chapter aims to investigate how the gained competitive intelligence from social media data can be used to predict customer engagement and support decisions. To achieve the purpose of the thesis, I applied different research methods in the three chapters. In the first chapter, the literature was collected using academic databases and manual cross-referencing. Then, the thematic analysis method was used to extract the specific value creation and exchange paths between firms and customers. In the second chapter, I proposed a model that integrated the technology acceptance model, motivation theory, and social influence theory to explore the determinants of individuals’ mobile social media use behavior. The data was collected using the survey method in China and the United States. For the data analysis, I firstly applied Partial Least Squares Structural Equation Modeling (PLS-SEM) to estimate the correlations amongst variables. Then, I applied the REBUS-PLS algorithm to detect the unobserved heterogeneity and conduct the post hoc segmentation. As for the third chapter, I extended the existing social media competitive intelligence frameworks by integrating the influence of the external environment and the phase to predict customer engagement. I conducted a case study to illustrate how to implement the framework. I collected tweets generated by the leading American catering brands using Application Programming Interface (API) before and during the COVID-19 pandemic. In the first phase, I used Amazon comprehend and Latent Dirichlet allocation (LDA) to analyze sentiments and topics behind the unstructured text data. In the second phase, I trained the classifiers using six machine learning algorithms to predict customer engagement behaviors in social media. The findings of the three chapters reveal that mobile and social media are effective value creation tools in modern marketing. Firms that conduct business through mobile social media can apply digital technology to create value for customers. They can also capture value from customers in return. Besides, customers co-create value for firms. Mobile social media use behavior is a premise in value creation. Specifically, individuals’ attitude towards the applications is a key factor that bridges the motivational and social factors and actual use behavior. At the same time, global mobile social media users are not homogeneous. They can be segmented into different groups which are significantly different in terms of their behavioral patterns, cultural values, and demographic characteristics. Apart from that, firms can also make use of competitive intelligence extracted from social media data to predict customer engagement behaviors and support decisions under different environments. The results show that the neutral sentiment predominates in the firm-generated content, and the number of topics raises in the pandemic situation. Moreover, the influence of the predictors on customer engagement is different before and during the pandemic. This thesis makes several contributions to the social media literature. First, after summarizing current knowledge on mobile social media, the thesis provides a conceptual framework on value creation in mobile social media and presents a list of future research guidelines. Second, the thesis deepens our understanding of mobile social media use behavior at the individual level by demonstrating that motivation theory has more explanatory power than social influence theory. In addition, by detecting the unobserved heterogeneity in mobile social media users, the thesis highlights the importance of incorporating international microsegmentation in marketing strategy. Third, the thesis also highlights the roles of social media data and firms in value creation. By proposing a refined social media competitive intelligence framework, the thesis demonstrates that competitive intelligence gained from social media data empowers customer engagement prediction and decision support, especially during times of high environmental uncertainty.