Abstract

The environmental footprint of courier, express, and parcel (CEP) logistics is significant and growing, owing to increased e-commerce. Consumer willingness to participate in the green logistics of CEPs, however, has been understudied. This study addresses this knowledge gap by surveying 155 Chinese consumers about their willingness to participate in CEP green logistics. Additionally, this research identifies some technical issues with previous survey research. Three main factors were extracted after the data were tested for reliability and validity using exploratory factor analysis with principal axis factor extraction and confirmatory factor analysis with diagonally weighted least squares. Consumer willingness is positively correlated with economic (8 items), operational (3 items), and social (3 items) factors, with a statistical significance of p < 0.001. Of all the factors, the strongest correlation, 0.67 (95% CI = 0.57, 0.75; p < 0.001; N = 155), exists between economic factors and consumer willingness. The results of a multinomial logistic regression analysis suggest that all consumers are highly unlikely to participate in economic factors, while they are highly likely to positively commit to operational and social factors. Therefore, it is recommended that the government provides monetary incentives to CEP companies to adopt green logistics, such as tax reductions and subsidies, to reduce the costs of green logistics. Meanwhile, the CEP industry could provide some direct and indirect incentives to consumers to re-use, recycle, and share materials, and to spend time learning about express enterprises’ green logistics, to increase consumer participation in economic factors.

Highlights

  • Logistics operations have a significant impact on greenhouse gas emissions [1]

  • This study addresses this knowledge gap by surveying 155 Chinese consumers about their willingness to participate in CEP green logistics

  • Zhao et al found that environmental knowledge had a significant impact on the green consumer behaviour of Chinese consumers [6]. We considered this fact, and conjectured that the time spent by customers learning about green logistics was positively related to CWPGL

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Summary

Methods

To minimise the risk of making a Type I error, a lower significance level (α) can be used, while the risk of making a Type II error can be minimised by ensuring that an experiment has higher statistical power [39]. To minimise the possibility of making a Type I error during the directional hypothesis testing (which is performed later via correlation analysis), the significance level is set to the popular α = 0.05; the null hypothesis is not rejected above this value. The statistical power of this study is 100% (1.00), which means that, at a significance level of α = 0.05, there is no likelihood of encountering a Type II error. The hypotheses and their selection criteria follow below

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