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Investigating retailing customers' adoption of augmented reality apps: integrating the unified theory of acceptance and use of technology (UTAUT2) and task-technology fit (TTF)
Marketing Intelligence & Planning ( IF 4.338 ) Pub Date : 2023-07-03 , DOI: 10.1108/mip-03-2023-0112
Mohamed A. Khashan , Mohamed M. Elsotouhy , Thamir Hamad Alasker , Mohamed A. Ghonim

Purpose

Since 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/approach

The present research uses variance-based partial least squares structural equation modeling (PLS-SEM) using WarpPLS.7 to examine 398 responses from Egyptian retail consumers.

Findings

TTF, 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/value

The 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.



中文翻译:

调查零售客户对增强现实应用程序的采用情况:整合技术接受和使用统一理论 (UTAUT2) 和任务技术契合度 (TTF)

目的

自增强现实(AR)技术出现以来,“智慧零售”已成为零售领域的主导商业模式。因此,如果零售商想要成功地鼓励客户接受这种极其创新的技术形式,那么了解 AR 采用的动态至关重要。因此,作者提出并评估了一个更全面的模型,由任务技术匹配(TTF)模型和技术接受和使用统一理论(UTUAT2)模型组成,供低收入国家使用。

设计/方法论/途径

本研究使用基于方差的偏最小二乘结构方程模型 (PLS-SEM),使用 WarpPLS.7 来检查来自埃及零售消费者的 398 份回复。

发现

TTF、绩效预期 (PE)、努力预期 (EE)、社会影响力 (SI)、促进条件 (FC)、享乐动机 (HM) 和客户创新性 (CI) 对购物者采用 AR 应用的行为意图 (BI) 产生积极影响在零售业,感知风险 (PR) 对 BI 产生负面影响。

原创性/价值

当前的研究首次使用 UTAUT2 和 TTF 模型调查零售环境中购物者 BI 对 AR 应用采用的决定因素。

更新日期:2023-07-06
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