Chapter 1: Introduction
1.1. Research Problem
Social networking websites were created with a simple idea in mind – to help users share their experiences and communicate with each other in an easy yet engaging manner (Erdogmus & Tatar, 2015, 189). Over the years, however, business entities have revealed that social media can be a powerful marketing tool. Among other benefits, social media allows for creating more favourable conditions for business essentials, such as time, costs, consumers, and relationships (Lai, 2017, 21). As a result, the concept of social commerce, wherein social media users are engaged in social interaction conductive to commercial activities, has emerged (Han, Xu & Chen, 2018, 38).
Business and marketing studies demonstrate that social commerce generates exposure, drives awareness and loyalty, and increases traffic to the organisations (Lu, Papagiannidis & Alamanos, 2019, 153). At the same time, there is limited empirical evidence on how companies establish social commerce engagement with consumers and what factors affect this relationship (Taherdoost, 2018, 960). This dissertation narrows down this literature gap by proposing a research framework that addresses the impacts of technology attractiveness and acceptance on social commerce engagement. Since interactions in the social media context are usually encouraged by users’ common interests in consumption activities (Yahia, Al-Neama & Kerbache, 2018, 11), the researcher further investigates the moderating role of personal interest in the link between social commerce engagement and technology attractiveness.
1.2. Thesis Background
Social commerce is a relatively new wave of e-commerce that implies the mediation of the traditional e-commerce by social media (Alalwan, 2018, 65). This relationship allows organisations to promote product- and service-related information, shopping process, and online transactions (Erdogmus & Tatar, 2015, 189). Therefore, companies engaged into social commerce can effectively stimulate consumer behaviour and the decision-making process. However, the success of this type of e-commerce depends on strong brand loyalty and commitment from social media users (Lai, 2017, 21). Thus, the issue of consumer engagement plays a crucial role in the effectiveness and successfulness of firms’ social commerce initiatives and strategies. In accordance with Han et al. (2018, 38), highly engaged consumers more actively participate in promotional and advertising activities in the online environment as compared to those consumers whose level of engagement is low. Nonetheless, community involvement is another factor that influences the degree to which social media users are engaged in social commerce activities (Braojos, Benitez & Llorens, 2018, 1)
The technology acceptance model (TAM) introduced by Fred Davis is 1986, which depicts individuals’ technology acceptance process, is presented as follows.
The TAM implies that perceived usefulness and perceived ease of use are the key factors that determine the extent to which consumers intend to and actually use a technology (Lu et al., 2019, 153). According to this framework, individuals are more likely to use a technology if they anticipate no effort to be required by this technology; and if it is expected to upsurge their performance (Tajvidi, Richard, Wang & Hajli, 2018, 1). Therefore, the TAM allows for explaining users’ attitudes towards social media in general and social commerce in particular. By contrast, the relative simplicity of the TAM as well as the lack of factors that affect consumers’ behaviour in relation to technology acceptance limits its practical application in the marketing field (Huang & Benyoucef, 2017, 40). Nonetheless, this model forms the basis for the conceptual framework of this doctorate project and contributes to the achievement of its main aim.
1.3. Rationale for the Study
Social commerce is becoming increasingly popular across industries in the business-to-consumer (B2C) platforms, making it a highly important topic for research (Taherdoost, 2018, 960). By exploring the relationship between technology acceptance and social commerce engagement as well as the moderating factors that influence this link, it is possible to make a significant contribution to the existing marketing literature (Lai, 2017, 21). In addition, based on the empirical findings, the researcher can generate important practical and theoretical implications as how companies operating in the social media context can more effectively involve consumers in their social commerce activities (Wang & Herrando, 2019, 164). The moderating role of consumers’ personal characteristics in this link is also worth investigating. Alalwan (2018, 65) noted that such individual characteristic as personal interest facilitates the impact of marketing stimuli on consumer behaviour. Thus, personal characteristics are expected to moderate the relationship between technology acceptance and social media engagement. Outcomes emerged from this project will add to the understanding of what forms social commerce engagement and will help marketers improve the effectiveness of their company’s social media strategy.
1.4. Main Purpose
Drawing on the interpersonal attraction theory and the relationship management perspective, this doctorate project explores the role of individual consumer characteristics in the relationship between technology acceptance and social commerce engagement.
RO1: To explore why and how consumers engage in social commerce.
RO2: To identify what types of social media content create consumer engagement.
RO3: To examine the extent to which users’ acceptance of social media influences their social commerce engagement level.
RO4: To assess the moderating power of individual consumer characteristics in the link between technology acceptance and social commerce engagement.
RO5: To recommend how marketers could more actively engage social media users in their social commerce activities.
1.6. Methodological Choices
In this project, the researcher follows a mixed method approach to data collection and analysis. During the first phase, 137 social media users provided primary qualitative data via self-administered, close-ended questionnaires based on the existing literature on social commerce engagement and technology acceptance factors (Easterby-Smith, Thorpe & Jackson, 2012, 142; Tajvidi et al., 2018, 1). During the next stage, the researcher obtained primary qualitative data from 19 managers of product and service companies operating in the social media environment and having social commerce engagement activities in place. The analysis of the obtained data involved the employment of graphical and statistical methods of analysis, such as descriptive statistics, linear regression, and Pearson correlation (Daniel & Harland, 2017, 98; Fisher, 2010, 48).
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