Public acceptance of crowdsourced delivery from a customer perspective

Yi-Jia Wang, Yue Wang, George Q. Huang and Ciyun Lin

European Journal of Operational Research, 2024, vol. 317, issue 3, 793-805

Abstract: The goals of crowdsourced delivery are to enable customers to be served efficiently and flexibly by occasional deliverymen. It could also be considered pro-social behavior by utilizing available human resources as deliverymen. The successful implementation of crowdsourced delivery highly depends on customers' willingness to adopt the crowdsourced delivery service considering its characteristics. This study develops a novel theoretical acceptance model of crowdsourced delivery service, integrating the technology acceptance model and norm activation model with the considerations of trust, social influence, and loss of privacy. The proposed model is tested based on the empirical data captured by a cross-sectional survey administered to 2333 participants in China through partial least squares structural equation modeling. Multiple group analyses are conducted to test whether the results were different or identical among various factors. The results indicate the proposed acceptance model interprets 84.5% of the variance in the behavioral intention of using the crowdsourced delivery service. The influences of predictors from the technology acceptance model are greater than those of predictors from the norm activation model, while social influence and trust are revealed to contribute most to explaining whether customers would accept crowdsourced delivery services. In contrast, loss of privacy negatively affects behavioral intention. Age, usage experience, and experience of being occasional deliverymen also moderate the path coefficients between antecedent factors and behavioral intention to use crowdsourced delivery services. We also provide theoretical findings and practical suggestions for developing crowdsourced delivery services based on the results and our analysis.

Keywords: Logistics; Crowdsourced delivery; Acceptance modeling; Trust; Social influence (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:317:y:2024:i:3:p:793-805

DOI: 10.1016/j.ejor.2023.03.028

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