营销
顾客满意度
客户的声音
业务
清晰
客户情报
客户保留
客户宣传
客户体验
客户对客户
比例(比率)
顾客惊喜
服务质量
服务(商务)
物理
化学
量子力学
生物化学
作者
Arvind Sahay,Amit Kumar,Som Sekhar Bhattacharyya,Arunaditya Sahay
出处
期刊:Asia Pacific Journal of Marketing and Logistics
[Emerald Publishing Limited]
日期:2025-08-11
卷期号:: 1-31
标识
DOI:10.1108/apjml-08-2024-1099
摘要
Purpose Firm deployment of technology breadth and depth (TBD) throughout the pre-purchase, purchase and post-purchase stages is critical for customer experience management. A significant gap in customer–technology interactions in the customer journey is the absence of a reliable measurement for TBD. This paper addresses conceptual clarity on TBD in the customer journey, grounded on expectation confirmation theory. Next, scales for technology breadth in the customer journey (TBCJ) and technology depth in the customer journey (TDCJ) are developed and validated. Design/methodology/approach This research followed a mixed-methods design and comprised five different studies. The data were collected from online retail Generation Z and Millennial customers for item generation, purification and validation. The TBCJ and TDCJ predictive validity were examined for their effects on customer satisfaction and repurchase intention for high-involvement (HI) and low-involvement (LI) products. Findings The results establish the validity of TBCJ and TDCJ as second-order constructs based on customer expectations and confirmations in the pre-purchase, purchase and post-purchase stages. Furthermore, TBCJ had higher effects than TDCJ on customer satisfaction and re-purchase intention for LI products. TDCJ had higher effects on customer satisfaction and repurchase intention for HI products than TBCJ. Research limitations/implications This research is the first robust effort toward developing and validating a scale for TBD in the customer journey. Practical implications TBCJ and TDCJ measurements offer managerial utility in deciding on the suitable mix for technology deployment to enhance the customer experience. Originality/value This research is the first robust effort toward developing and validating a scale for TBD in the customer journey.
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