Exploring positive and negative effects of social media platforms: focus on promotion and phubbing behavior

Abstract

Social media and smartphones have changed and continue to change significant aspects of our lives. This thesis aims to present two studies evidence that digital technology may influence human social life in both negative and positive ways. The first part of the dissertation investigates the influence of users' generated content (UGC) on the business performance evidence from two social media platforms widely used in the hospitality industry: Instagram and OpenTable. Using the data-driven approach, we provide scholars and practitioners a conceptual model that demonstrates all steps from data collection to data analysis to understand the latter. Additionally, we examine how UGC about business across two channels interact in a complex set of feedback loops known as “echo verse." Moreover, the study offers advice for managers in navigating this new complex media world. The dissertation displayed a methodological contribution using a series of data analysis techniques: sentiment analysis, text mining, fixed-effect, and panel-vector-autoregression. Technology is here to stay, but it is always morphing and expanding. As each new technology enters the scene, it has the potential to shape our relationships, personal lives, and sense of self. However, with the significant increasing smartphone use trends, this will erode social interaction and face to face communication in alarming ways. The phenomenon is known as Phubbing behavior, defined as ignoring his/her companion and paying only attention to his/her smartphone. The latter is predominant in the restaurant context, where an average restaurant will see 36 cases of phubbing per dinner session. Plenty of studies introduced addiction in all its forms, such as phone, social media, games, and the internet, to explain the phubbing behavior.However, some studies could not confirm common concerns that excessive screen time is linked to the latter. There is increasing consensus that research, public policies, and interventions need to focus on the user and not the extent of technology usage. The present paper aims to examine phubbing behavior based on self-discrepancy, which may expand current research on the understanding of phone-snubbing and further validating a theoretical foundation. To conduct this research, we collect 409 valid responses through an on-line survey for two months, and we deployed partial least squares based on structural equation modeling (PLS-SEM) to test the research model. The last chapter of the dissertation summarizes the findings of two studies and provides several valuable contributions for academicians and practitioners.