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Articles

Revisiting a model of customer engagement cycle: a systematic review

重新审视客户参与周期模型:系统回顾

ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon
Pages 579-617 | Received 06 Aug 2022, Accepted 07 Apr 2023, Published online: 11 May 2023
 

ABSTRACT

The purpose of this paper is to consolidate published research on customer engagement (CE), and building on that, to further develop a set of integrated CE elements that fit the online context, based on Sashi’s [Customer engagement, buyer-seller relationships, and social media. Management Decision, 50(2), 253–272]. CE cycle model. Thus, we develop a systematic alignment of CE concepts and propose additional themes – including Experience, Organizational and Environmental Context, Customer Participation, Employee Participation, and Trust – and solidify the model with theoretical propositions for each theme. This paper’s originality comes from being the pioneer study to systematically examine each CE activity through the lens of an online-dominant context, while contributing to the CE literature. Recommendations for future research are provided for researchers of the CE field, calling for deeper investigation of existing theory, more attention to the areas in which e-commerce is developing rapidly, and additional prospective propositions for the CE cycle model to adapt to a post-pandemic world.

本文的目的是整合已发表的关于客户参与 (CE) 的研究,并以此为基础,基于 Sashi [Customer engagement, buyer-seller relationships, and social media. Management Decision, 50(2), 253–272] 的 CE 循环模型,进一步开发一套适合在线环境的集成 CE 元素。 因此,我们开发了 CE 概念的系统调整,并提出了额外的主题 – – 包括经验、组织和环境背景、客户参与、员工参与和信任 – – 并用每个主题的理论命题巩固模型。 本文的独创性来自于作为先驱研究,通过在线主导环境的镜头系统地检查每个 CE 活动,同时为 CE 文献做出贡献。 为 CE 领域的研究人员提供了未来研究的建议,呼吁对现有理论进行更深入的研究,更多地关注电子商务快速发展的领域,并为 CE 循环模型适应后时代提出额外的前瞻性命题。 大流行世界。

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was funded by Fundação para a Ciência e a Tecnologia (UIDB/00124/2020, UIDP/00124/2020 and Social Sciences DataLab - PINFRA/22209/2016), POR Lisboa and POR Norte (Social Sciences DataLab, PINFRA/22209/2016).

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