Acceptance of Smartphone‐Based Mobile Shopping: Mobile Benefits, Customer Characteristics, Perceived Risks, and the Impact of Application Context

Abstract

Despite their generally increasing use, the adoption of mobile shopping applications often differs across purchase contexts. In order to advance our understanding of smartphonebased mobile shopping acceptance, this study integrates and extends existing approaches from technology acceptance literature by examining two previously underexplored aspects. Firstly, the study examines the impact of different mobile and personal benefits (instant connectivity, contextual value and hedonic motivation), customer characteristics (habit) and risk facets (financial, performance, and security risk) as antecedents of mobile shopping acceptance. Secondly, it is assumed that several acceptance drivers differ in relevance subject to the perception of three mobile shopping characteristics (location sensitivity, time criticality, and extent of control), while other drivers are assumed to matter independent of the context. Based on a dataset of 410 smartphone shoppers, empirical results demonstrate that several acceptance predictors are associated with ease of use and usefulness, which in turn affect intentional and behavioral outcomes. Furthermore, the extent to which risks and benefits impact ease of use and usefulness is influenced by the three contextual characteristics. From a managerial perspective, results show which factors to consider in the development of mobile shopping applications and in which different application contexts they matter.

Tourists’ Risk Perception and the Use of Mobile Devices in Beach Tourism Destinations

“…According to Beinat [58], privacy risk issues involve the ability to collect, store, use and disclose users' locations. Other literature identifies various aspects that characterise privacy risk (improper access to and the collection and unauthorised secondary use of personal information), which were taken into account when designing the issues surveyed in this study [8,45,53,[59][60][61]. Subsequently, several questions were included in order to obtain information on privacy risk perception: "It bothers me that when I use mobile devices I can be observed by other people or they can know my exact position"; "It upsets me if my personal data is used to offer me customised services and products"; "I like to receive messages about personalised services and product offers on my mobile device when I'm on holiday"; and "I like to post personal comments and photographs on social media, despite the fact that someone may recognise me or figure out where I am".…”

Under the sway of a mobile device during an in‐store shopping experience

“…Potential opportunity exists for retailers to employ mobile technology to engage customers when they undertake search effort (Hubert et al., ; Rippé et al., ). In a shopping context, search effort is limited by the amount of time and energy available to process information and respond to cues (Vermeir & Patrick Van, ).…”

“…With increasing consumer preference for mobile devices for both hedonic and utilitarian reasons (Ha & Park, 2013;Hubert, Blut, Brock, Backhaus, & Eberhardt, 2017) and avoidance of the retail salesperson, this study seeks to contribute to the under-researched areas of consumer mobile shopping behavior and the retail salesperson's ability to sell to this mobile shopper in today's omni-channel world (Holmes, Byrne, & Rowley, 2013;Rapp et al, 2015;Shankar, Venkatesh, Hofacker, & Naik, 2010). This investigation explores the consumer's information search behavior vis-à-vis the salesperson's selling behavior so as to enhance understanding of how retail salespeople can influence mobile-dependent shoppers.…”

Take it Personally – The Role of Consumers’ Perceived Value of Personalization on Cross-Category Use in a Smart Home Ecosystem

“…To establish the use of smart home technologies across categories, the habit of using a single technology already [2,18,24,35] often not only leads to repeated use of this specific device, but also to cross-category use of additional technologies [12]. Thus, we hypothesize a spillover effect from the habit of using a single connected home device to the intention to use as well as to the actual use of smart devices across categories.…”

“…Third, participants had to own a smart home device/technology. Within the main questionnaire, participants had to answer questions with regard to (1) the different UTAUT dimensions: (a) performance expectancy (PE, 4 items; "I find the services provided by a connected/smart home device useful", "A connected/smart home device increases my chances of achieving things that are important to me", "A connected/smart home device helps me accomplish things more quickly", "A connected/smart home device increases my productivity"); (b) effort expectancy (EE, 4 items, "Learning how to use a connected/smart home device is easy for me", "My interaction with a connected/smart home device is clear and understandable", "I find a connected/smart home device easy to use", "It is easy for me to become skillful at using a connected/smart home device"); (c) enjoyment (ENJ, 2 items, "When using smart home technology, I primarily want to have fun", "When using smart home technology, I primarily want to relieve boredom"); (d) facilitating conditions (FC, 4 items, "I have the resources necessary to use a connected/smart home", "I have the knowledge necessary to use a connected/smart home", "A connected/smart home is compatible with other technologies I use", "I can get help from others when I have difficulties using a connected/smart home"); and (e) price value (PV, 3 items, "A connected/smart home device is reasonably priced", "A connected/smart home device is a good value for the money", "At the current price, a connected/smart home device provides good value") [12,35]; (2) their perceived value for personalization (CVP, 3 items, "I value smart home technology that is personalized for the device that I use", "I value smart home technology that is personalized for my usage experience preferences", "I value smart home technology that acquires my personal preferences and personalizes the services and products themselves") The scale originally consisted of six items. However, we have chosen only those three which point to personalized data without limitations (e.g., anonymity).…”