Factors Influencing the Adoption of Social Media in ... - IDEALS @ Illinois

Factors Influencing the Adoption of Social Media in the Perspective of Information Needs Youngseek Kim

Minjae Kim

Kyungseek Kim

Syracuse University School of Information Studies 221 Hinds Hall Syracuse, NY 13244



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[email protected]

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ABSTRACT This study focuses on the factors which affect individual users’ adoption of social media in the perspective of their information needs. Social media are the emerging digital communication channels which provide information sharing grounds by helping users distribute and consume information. We introduced both adoption and gratification approaches of IT/IS adoption research by considering individual users and their information needs. For this empirical study, we reviewed previous literatures and their theoretical frameworks in regards to individual users’ adoption of IT/IS. Then, we developed the social media adoption model by including significant constructs including perceived usefulness, perceived ease of use, perceived enjoyment, and intention to use from TAM and its extended models. In addition, we also included two more constructs including social influence and personal innovativeness as moderating factors. Finally, we will empirically test our model by using a survey method in order to understand individual users’ adoption of social media.

Keywords Social Media, IT/IS Adoption, Information Needs, Gratification Approach, TAM, Innovation Diffusion Theory

1. INTRODUCTION Social media are the emerging digital communication channels which create a user-oriented information sharing ground where any people can generate or subscribe information content as both information provider and consumer. Social media have steadily increased among adult American Internet-users according to Pew Internet Research [6]. And they have become an important source of information for online users. Agichtein and his colleagues found that social media provide a rich variety of information sources: in addition to the content itself, there is a wide array of non-content information available [2]. The social media can be considered as an information system Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. iConference’2010, February 3–6, 2010, University of Illinois at UrbanaChampaign, Illinois, USA. Copyright 2010 iConference

which users distribute and consume information. In the Information Systems (IS) field, individual users’ IT/IS adoption has been studied in organizational contexts. Also, researchers already have empirically examined the determinants of IT/IS usage [5, 7, 9, 10]. However, there are just few studies why individual users adopt social media for their own usage, especially to satisfy their information needs. This study is interested in individual users’ adoption of social media in the perspective of their information needs. As a starting point of this research, relevant literatures including theoretical background were reviewed. Based on the review of existing literature, we developed a research framework to guide a survey study, which will be used to collect data for the research questions. Following the research framework, the survey questionnaire will be developed and tested with pilot study sample. Then, actual data will be collected through an online and offline survey of the general Internet users. Factor analysis and multiple regression analysis will be conducted based on the collected data. Finally, we will interpret and discuss about the data analysis based on our research framework.

2. THEORETICAL BACKGROUND OF IT/IS ADOPTION There are various theoretical models which explain individuals’ IT/IS adoption. According to Verkasalo, the adoption research can generally be divided into four categories including diffusion research (market focus), adoption approach (individual user focus), gratification research (needs of users focus), and domestication research (consequence of adoption focus) [12]. In this study, we will focus on both gratification research and adoption approach by considering individual users and their information needs. The Theory of Reasoned Action (TRA) and Theory of Planed Behavior (TPB) provide the basic theoretical framework for understanding users’ innovation adoption [3, 4]. The TRA and TPB have influenced the Technology Acceptance Model (TAM) and its extended models. Davis presented the TAM to explain the determinants of user acceptance of a wide range of end-user computing technologies [5]. In the TAM, both perceived usefulness and perceived ease of use affect the intention to use, which eventually influences the real usage behavior. Later, the TAM model has been developed by adding determinants which affect perceived usefulness and perceived ease of use.

Venkatesh and Davis enhanced the TAM to TAM2, which provides a detailed account of the key forces underlying judgments of perceived usefulness [10]. TAM2 was expanded to include the impacts of three interrelated social forces including subjective norm, voluntariness, and image as determinants of perceived usefulness. Later, the Unified Theory of Acceptance and Use of Technology model (UTAUT) was developed by Venkatesh and colleagues [11]. UTAUT provides a refined view of how the determinants of intention and behavior evolve over time and assumes that there are three direct determinants of intention to use (performance expectancy, effort expectancy, and social influence) and two direct determinants of usage behavior (intention and facilitating conditions) [11]. For this study, we introduce the innovation diffusion theory to explain individual’s social media adoption behavior [8]. Drawing upon Rogers’ theory of the diffusion of innovations, Agarwal and Prasad described personal innovativeness as the willingness of an individual to try out any new information technology [1]. They added this individual difference variable as a new construct to Davis’s original TAM model and hypothesized that individuals with higher levels of personal innovativeness are expected to develop more positive perceptions about the innovation in terms of advantage, ease of use, compatibility, etc. and have more positive intentions toward use of a new IT/IS [1].

3. RESEARCH FRAMEWORK Based on the theoretical background and literature review, we can identify major constructs which may affect individual users’ intention to adopt social media to satisfy their information needs. We developed individuals’ social media adoption model by including significant elements from TAM model. If users believe that social media are complicated to use for their information purposes, they may not want to use the social media in order to distribute or acquire information. People may want to use social media if they believe the social media are useful by satisfying users’ information needs. Also, since the social media provide various entertainment-related functions through their information ground, the enjoyment of social media would be a good reason why people want to adopt social media for their information related entertainment purposes. In addition to the direct factors to the intention of individuals’ adoption of social media including perceived usefulness, perceived ease of use, and perceived enjoyment, there are moderating factors which affect the individuals’ intention to adopt social media. These moderating factors include social influences and personal innovativeness. In this study, social influence refers to perceived pressures from other people and media to make or not to make a certain behavioral decision. Social influence can play a significant role in affecting users’ adoption of social media for their information sharing behaviors. Also, Personal innovativeness is included in this research since it has been expected to influence individuals’ intention to adopt social media. Personal innovativeness is defined as the willingness of an individual to try out any new information systems [1]. We believe that these moderating factors would directly affect the intention to use social media, and also they would indirectly affect the intention to use social media services by influencing the direct factors including perceived usefulness, perceived ease of use, and perceived enjoyment.

4. RESEARCH DESIGN & METHOD We will use a survey method to conduct this research. To examine the conceptual constructs and hypothesized relationships, the survey questionnaire will be developed for the adoption of social media in the perspective of information needs. The survey items will be brought from previous studies and modified for this research. Then, we will create an actual survey questionnaire by adjusting the measures of the constructs according to the interviews with actual social media users. For the questionnaire, all the items from previous studies will be modified to make them relevant to the social media usage under the information behavior context. The survey data will be collected through online survey. The population in this study focuses on the Internet users in the U.S., and the sample population which we will collect is targeted 250 participants. The sample would be collected by using a commercial survey response website. Since college students are more the early adopters in IT/IS adoption, it would be appropriate not to use the college students in this survey. Later, we can generalize the results of this research to the population of the general Internet users. The empirical data will be gathered to test our research model. The questionnaire will consist of research introduction and purpose, specific questions to measure the constructs, and respondents’ demographic information. Each measurement for the constructs including perceived usefulness, perceived ease of use, perceived enjoyment, social influence, personal innovativeness, and intention to use the social media will be collected. After we get the final data set, we will clean the survey data set by removing invalid data. The descriptive data analysis will show some demographic information about the respondents. In regard to statistical analyses, factor analysis and multiple regression analysis will be conducted based on the collected data. For the measurements of six different variables, Principal Factor Analysis can be used with VARIMAX rotation (if needed). Correlation analysis will be used to see the relationships among all the research variables.

5. CONCLUSION The purpose of this study is to understand the factors which influence individuals’ adoption of social media in the perspective of their information needs. We focus on both gratification research and adoption approach to answer our research questions. In regards to the possible results of this research, first, we believe that perceived usefulness, perceived enjoyment, and social influence are the important determinants of the social media adoption. Second, we also believe that perceived enjoyment rather than perceived usefulness and perceived ease of use may have a greater impact on individual users’ intention to adopt social media. Third, we think that individual users’ perception of usefulness, ease of use, and enjoyment may be significantly attributed to social influence from users’ social network. Lastly, individual users’ perception of usefulness, ease of use, and enjoyment may be significantly attributed to personal innovativeness. The analysis of the survey results will help us validate the new model and understand individual users’ adoption of social media.

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http://www.pewinternet.org/Reports/2009/Twitter-andstatus-updating.aspx [7] Moore, G.C., and Benbasat, I. “Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation,” Information Systems Research (2:3) 1991, pp 192-222. [8] Rogers, E.M. Diffusion of Innovations (5th Edition) The Free Press, New York, NY, 2003. [9] Taylor, S., and Todd, P.A. “Understanding Information Technology Usage: A Test of Competing Models,” Information Systems Research (6:2) 1995, pp 144-176. [10] Venkatesh, V., and Davis, F.D. “A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies,” Management Science (46:2) 2000, pp 186-204. [11] Venkatesh, V., Morris, M.G., Davis, G.B., and Davis, F.D. “User Acceptance of Information Technology: Toward a Unified View,” MIS Quarterly (27:3) 2003, pp 425-478. [12] Verkasalo, H. “Dynamics of Mobile Service Adoption,” International Journal of E-Business Research (4:3) 2008, pp 40-63.