技术接受模型
背景(考古学)
独创性
多级模型
结构方程建模
营销
可用性
心理学
食物运送
感知
计划行为理论
业务
知识管理
计算机科学
社会心理学
地理
考古
人机交互
机器学习
神经科学
创造力
控制(管理)
人工智能
作者
Meenal Arora,Jaya Gupta,Amit Mittal
出处
期刊:Global knowledge, memory and communication
[Emerald (MCB UP)]
日期:2023-04-20
被引量:10
标识
DOI:10.1108/gkmc-01-2023-0005
摘要
Purpose This study aims to provide insight into consumer behavior regarding the use of food delivery apps when making purchases. To investigate the primary elements affecting users' intentions to use meal delivery applications, this study suggests an extension to the technology acceptance model through some contextual variable such as “various food choices (VFC),” “trust (TRR),” “perception of COVID-19-related risks (PCR)” and “convenience (CONV)” during the pandemic. Design/methodology/approach A cross-sectional data of 407 was collected in the Indian context. This research adopts the covariance-based structural modeling approach to test the hypotheses along with hierarchical regression to predict the efficiency of constructs. Findings Considering the outcomes, “perceived usefulness (PU)” was positively influenced by “perceived ease of use (PEOU),” “VFC” and “CONV.” In addition, the attitude (ATT) was positively impacted by “PU,” “TRR” and “PEOU.” Nevertheless, “PCR” negatively influenced ATT. In additional, this research illustrates the positive impact of ATT and PU on behavioral intention to use. Originality/value By confirming the technology acceptance model's capacity for explanation in relation to food delivery apps, this study adds to the body of knowledge. The primary focus of this study is on determining the direct impact of the identified determinants on the adoption of food delivery applications within the context of a pandemic situation in developing countries.
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