Examining Location-Based Services Usage from the Perspectives of Unified Theory of Acceptance and Use of Technology and Privacy Risk

By Zhou, Tao | Journal of Electronic Commerce Research, May 1, 2012 | Go to article overview

Examining Location-Based Services Usage from the Perspectives of Unified Theory of Acceptance and Use of Technology and Privacy Risk


Zhou, Tao, Journal of Electronic Commerce Research


ABSTRACT

As an emerging service, location-based services (LBS) have not received wide adoption among users. Drawing on both perspectives of Unified Theory of Acceptance and Use of Technology (UTAUT) and privacy risk, this research examined user adoption of LBS. We conducted data analysis with structural equation modeling. The results indicated that usage intention is affected by both enablers such as performance expectancy and inhibitors such as perceived risk. This implies that service providers need to concern both perspectives of technological perceptions and privacy risk in order to facilitate user adoption of LBS.

Keywords: location-based services; UTAUT; privacy concern; trust

1. Introduction

Mobile internet has been developing rapidly around the world. Especially, the application of third generation (3G) communication technologies triggers mobile internet development. According to a report issued by China Internet Network Information Center (CNNIC) in January 2012, the number of mobile internet users in China has exceeded 356 million, accounting for 69% of its internet population (513 million) [CNNIC 2012]. Attracted by the great market, service providers have released a variety of mobile services, such as mobile instant messaging (IM), location-based services (LBS), mobile games and mobile payment. Among them, a few services such as mobile IM have been widely adopted by users. However, many services such as LBS have not received wide adoption among users. Mobile service providers need to understand the factors affecting user behavior. Then they can take measures to facilitate user adoption and usage of these services.

LBS mean that mobile service providers present context-related information to users based on their location and preferences [Dhar and Varshney 2011]. This personalized service delivers a better experience to users. Due to this advantage, LBS are called the killer application of mobile business [Junglas and Watson 2008]. Typical LBS include location-based advertisement, navigation, emergency evacuation and location check-in services. LBS can bring great value to users and this may promote their usage behavior. However, LBS need to utilize users' location information. This may incur users' privacy concern and increase their perceived risk. Users feel that they are tracked by service providers. Their concern on privacy risk will negatively affect their usage of LBS.

The objective of this research is to identify the factors affecting user adoption of LBS from both perspectives of technological perceptions and privacy risk. On one hand, LBS represent a new technological application. Thus we may apply information technology theories such as the unified theory of acceptance and use of technology (UTAUT) to explain user behavior. UTAUT is mainly concerned with the effect of enablers such as performance expectancy and effort expectancy on usage behavior. On the other hand, LBS user behavior may be also affected by inhibitors such as privacy risk. If users have high privacy concern, they may perceive great risk and have low trust in service providers. Thus it is necessary to integrate both perspectives of enablers such as performance expectancy and inhibitors such as privacy risk to examine LBS user behavior. Extant research has focused on the single effect of privacy risk on user adoption of LBS [Junglas et al. 2008b; Xu et al. 2011], and has seldom combined both perspectives of enablers and inhibitors to explain user behavior. This research tries to fill the gap. The results support our hypotheses.

The rest of this paper is organized as follows. We review related literature in the next section. Then we develop research model and hypotheses in section three. Section four reports instrument development and data collection. Section five presents results and section six discusses these results. We present theoretical and managerial implications in section seven. …

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