The Influence of IT-Related Beliefs on Emotional Trust for a Smartphone and Smartphone Continuance Usage: An Empirical Study

The Influence of IT-Related Beliefs on Emotional Trust for a Smartphone and Smartphone Continuance Usage: An Empirical Study

Efosa C. Idemudia, Mahesh S. Raisinghani, Olusola Samuel-Ojo
Copyright: © 2013 |Pages: 18
DOI: 10.4018/jtd.2013040103
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Abstract

Companies and municipalities worldwide are encouraging bring your own devices (BYOD) such as smartphones to the work environment to enhance communication among all employees, job performance, system quality, product quality, and service quality. Thus, understanding factors that have direct and indirect influence on smartphone continuance usage is helpful to companies worldwide that are investing heavily on BYOD. To date, there are no published studies that have investigated both the influence of external variables (i.e. cognitive factors) and emotional trust on smartphone continuance usage. To fill this gap in the literature, the authors develop their research model. This study indicates that emotional trust in a smartphone has a positive and significant effect on smartphone continuance usage. This finding strongly supports both the theory of reasoned action and the technology acceptance model. Familiarity with a smartphone, satisfaction with a smartphone, usefulness of a smartphone’s apps/features, and smartphone functionality have a significant positive effect on emotional trust on a smartphone. The authors’ findings strongly indicate that the continuance usage of a smartphone in their daily activities and tasks involve emotion, cognition, and mental processes.
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Introduction

The use of mobile technology in society has grown tremendously in recent years. Society has become very dependent upon mobile technology in every aspect of life including business, healthcare, education and the private sector among other sectors. In today’s era of mobile commerce, technology is rapidly changing to fit the needs of the fast paced business world and society. For example, using mobile technology becomes important in monitoring chronically ill patients diagnosed with diabetes, kidney failure, chronic obstructive pulmonary disease and arteriosclerosis. Medical parameters such as weight, blood pressure, blood sugar and peak air flow are being augmented by technology that monitors the patient compliance with drug regimens, to ensure that they enjoy maximal quality of life with minimal disruptive impact (Kirsch et al., 2007).

Developers are constantly creating networks that have faster connectivity, enhanced performance, capacity and coverage. As the mobile technology industry grows, consumers grow more and more dependent on this industry as it integrates into our daily lives. As the world continues to advance, we can expect technological devices such as the smartphone (e.g., Apple’s iPhone, Samsung’s Galaxy, BlackBerry, and so forth) to become smaller, faster, more energy efficient, and more mobile. Thus, our study investigates the influence of IT-related beliefs and emotional trust on smartphone continuance usage.

Mobile technology is visible in nearly all geographic areas. Mobile phones are used by consumers to make phone calls, send text messages, utilize global positioning system (GPS) navigation to find restaurants, download podcasts, snap photographs, shop online, or check email. The terminology involved in the wireless phone industry today is quite perplexing. There are Personal Digital Assistants (PDAs), cell phones, feature phones and smartphones. Some of the smartphone vendors include Apple, Blackberry, Nokia, Mitsubishi, HTC, Sharp, Palm, Dell, Hewlett Packard, Samsung, Sony Ericsson, and recently Google. The converging technology of smartphones combine nearly all of the capabilities of a PDA, which keeps track of calendar information; a regular cell phone that makes voice calls with limited games; and a feature phone, which may have a camera, video and mp3 player. Some of the previous research reviewed assessed smartphones based on value chain analyses, cluster analyses, layer models, and business ecosystems.

Innovation diffusion theory (IDT) attempts to explain which factors will influence the adoption of information technology (IT). According to the study conducted to examine if consumers will accept multimedia message service (MMS) technology, the results concluded that the consumers were drawn to the MMS technology and that they were more likely to use it and to continue use. To investigate the use and acceptance of smartphone, Park and Chen (2007) argue that many articles have used the technology acceptance model (TAM) and the innovation diffusion theory (IDT) as the theoretical background for their research models. Some researchers have combined both TAM and IDT to develop their models (Cheong and Park 2005; Mao et al., 2005). Park and Chen (2007) investigate how human motivation affects the adoption decision for smartphone among medical doctors and nurses. Prior studies have been very helpful and these studies focus on behavioral intention to use smartphone instead of smartphone continuance usage. The literature review for our study reveals that no studies have investigated the influence of both external variables (i.e., cognitive factors) and emotional trust on smartphone continuance usage. Furthermore, of the current body of knowledge on business models and value creation is not as advanced as required to contribute sound modeling of phenomena, deriving theoretical explanations or provide guidance concerning smartphone continuance usage. Thus to overcome this lack/dearth of understanding and to fill the identified gap in the literature, we develop our research model based on the theory of reasoned action.

The following section presents the theoretical background and research model. This is followed by the research model which discusses participants and data collection procedures; and the operationalization of constructs and measurement scales. This is followed by data analysis that presents scale validation and measurement model; and hypotheses testing and structural model. Finally, the conclusion summaries the discussion of key findings, practical and research implications, and summarized the research.

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