Investigating retailing customers' adoption of augmented reality apps: integrating the unified theory of acceptance and use of technology (UTAUT2) and task-technology fit (TTF)

M. A. Khashan, Mohamed M. Elsotouhy, Thamir Hamad Alasker, Mohamed A. Ghonim
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Abstract

PurposeSince the advent of augmented reality (AR) technology, “Smart Retailing” has become the dominant business model in the retail sector. Therefore, comprehending the dynamics of AR adoption is essential if retailers are to successfully encourage customers to embrace this extremely innovative form of technology. As a result, the authors propose and evaluate a more comprehensive model, consisting of the task-technology fit (TTF) and unified theory of acceptance and use of technology (UTUAT2) models, for use in low-income countries.Design/methodology/approachThe present research uses variance-based partial least squares structural equation modeling (PLS-SEM) using WarpPLS.7 to examine 398 responses from Egyptian retail consumers.FindingsTTF, performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating condition (FC), hedonic motivation (HM) and customer innovativeness (CI) positively affect shoppers' behavioral intentions (BI) to adopt AR Apps in retail, while perceived risk (PR) negatively affects BI.Originality/valueThe current study is the first to investigate the determinants of shoppers' BI toward AR Apps adoption in the retail context using UTAUT2 and TTF models.
调查零售客户对增强现实应用的采用:整合技术接受和使用统一理论(UTAUT2)和任务-技术契合度(TTF)
自增强现实(AR)技术出现以来,“智能零售”已成为零售业的主导商业模式。因此,如果零售商要成功地鼓励顾客接受这种极具创新性的技术形式,了解AR采用的动态是至关重要的。因此,作者提出并评估了一个更全面的模型,包括任务-技术契合(TTF)和技术接受和使用统一理论(UTUAT2)模型,供低收入国家使用。设计/方法/方法本研究使用基于方差的偏最小二乘结构方程模型(PLS-SEM)。调查了398份来自埃及零售消费者的回复。结果发现,绩效预期(PE)、努力预期(EE)、社会影响(SI)、促进条件(FC)、享乐动机(HM)和顾客创新(CI)正向影响购物者在零售中采用AR应用程序的行为意图(BI),而感知风险(PR)负向影响BI。目前的研究首次使用UTAUT2和TTF模型调查了零售环境中购物者对AR应用采用的BI决定因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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