识别covid-19期间消费者对移动支付的抵制:一种解释结构建模(ism)方法

IF 0.9 Q4 BUSINESS
N. Singh, Pragati Singh
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引用次数: 2

摘要

目的——由于2019冠状病毒病期间全国范围的封锁和各邦范围的宵禁,人们在印度购物期间无法进行线下支付(即现金支付)。因此,人们正在将他们的支付行为从线下模式转变为线上模式。但是,根据央行的报告,通过移动支付的采用率仍然很慢。本文的重点是确定移动支付系统(mps)在印度采用的关键障碍。创新阻力理论(IRT)已被用作障碍的基本模型,尽管在mps背景下可选择的障碍范围很广。此外,本文还纳入了三个外部变量,这些变量不在IRT结构的更广泛覆盖范围内。另一方面,本研究从理论角度补充了mps参考框架下的创新阻力理论。利用解释结构模型(ISM)和MICMAC分析来分析障碍之间的直接和间接关系。研究方法- ISM方法已被用于通过文献和专家意见建立八个(08)确定的障碍之间的关系。在MICMAC分析的帮助下,确定了高驱动功率的关键障碍。结果显示,价值障碍(b2)、图像障碍(b5)和可见度障碍(b7)是最重要的变量。有趣的是,文献中irt的风险壁垒(b3)和隐私壁垒(b6)在ISM模型中处于最低水平。大多数障碍位于MICMAC分析的第三象限,表明具有较高的驱动和依赖能力。▽研究局限性=开发的ISM模型是基于5(05)名专家的观点,这可能会有偏见,并影响结构模型的最终输出。由于新冠肺炎疫情,数据采集采用在线视频会议方式,如果采用线下或面对面采访方式采集数据,可能会有所不同。提出的模型的主要发现旨在帮助解释MPS采用过程中存在的障碍。原创性/价值-本研究首次尝试将ISM方法与IRT结合使用,以检测mps内部的障碍。本文的研究结果将指导和激励研究者利用IRT分析更多的关键障碍,为理论发展做出贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
IDENTIFYING CONSUMER RESISTANCE OF MOBILE PAYMENT DURING COVID-19: AN INTERPRETIVE STRUCTURAL MODELING (ISM) APPROACH
Purpose – Due to country-wise lockdown and state-wise curfews in COVID-19, people were not able to make offline payments (i.e. cash payments) during purchases in India. So, people are switching their payment behavior from offline to online mode. But, as per the central bank report, the rate of adoption through mobile payments is still slow. The paper focuses on identifying critical barriers to mobile payment systems (MPSs) adoption in India. Innovation resistance theory (IRT) has been used as a base model for barriers, despite the wide range of choices of barriers available in the MPSs context. Additionally, three external variables which are out of the wider coverage of IRT constructs were incorporated in this paper. The study, on the other hand, adds to innovation resistance theory in the frame of reference of MPSs from a theoretical perspective. Interpretive structural modeling (ISM), together with MICMAC analysis is brought into play to analyse the direct and indirect relationship amongst the barriers. Research methodology – ISM approach has been used to establish the relationship among the eight (08) identified barriers, through literature and expert opinions. The key barriers to high driving power are then identified with the help of MICMAC analysis. Findings – The results reveal that value barrier (b2), image barrier (b5) and visibility barrier (b7) are the most significant variables. Interestingly, IRTs’ risk barrier (b3) and privacy barrier (b6) from the literature fall in the lowest level of the ISM model. The majority of the barriers fall under quadrant III of MICMAC analysis, indicating the high driving and dependence power. Research limitations – The developed ISM model is based on the sentiments of five (05) experts, which could be biased and influence the structural model’s final output. Due to COVID-19, data has been collected through online video conferencing mode, this may vary if data will be collected through an offline or face-to-face interview. The proposed model’s key findings aim to assist in explaining the barriers that exist during MPS adoption. Originality/Value – This study is the first attempt to use the ISM approach in conjunction with IRT to detect barriers within MPSs. The result of this paper will guide and motivate the researcher to analyse more critical barriers with IRT to contribute to the theoretical development.
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来源期刊
CiteScore
3.20
自引率
0.00%
发文量
14
审稿时长
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