A methodologically sound survey of Chinese consumers’ willingness to participate in courier, express, and parcel companies’ green logistics

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.

Identifying contributing factors to China’s declining share of renewable energy consumption: no silver bullet to decarbonisation

“…A hypothesis is an assumption based on prior studies or existing information about a subject (John A. Dutton e-Education Institute 2014 ). A clearly defined and specific research topic and hypothesis will almost certainly aid in guiding the direction and breadth of the study, as well as how data is collected (Farrugia et al 2010 ; Sajid et al 2021 ). We have relied on the previously published literature, economic theory, and intuition to develop high-quality hypotheses.…”

“…Researchers frequently use the correlation coefficient to determine the direction of a relationship between two variables (Schober et al 2018 ). PCC and SRCC are commonly used in hypothesis testing to determine the directionality of a relationship between dependent and independent variables (Sajid et al 2021 ). The PCC is widely used for normally distributed continuous data, whereas the SRCC can be used for ordinal and non-normal distributions.…”

“…The PCC is widely used for normally distributed continuous data, whereas the SRCC can be used for ordinal and non-normal distributions. The estimates for the SPSS-based skewness and kurtosis tests for normality should be between + 1 and − 1 (Sajid et al 2021 ). Furthermore, one-tailed significance is preferable to traditional two-tailed significance for directional hypothesis testing (Sajid et al 2021 ).…”

“…The estimates for the SPSS-based skewness and kurtosis tests for normality should be between + 1 and − 1 (Sajid et al 2021 ). Furthermore, one-tailed significance is preferable to traditional two-tailed significance for directional hypothesis testing (Sajid et al 2021 ).…”

“…Coal consumption accounts for nearly 58% of this energy requirement (U.S. EIA 2021 ). This excessive reliance on unclean fossil fuels made China the world’s largest carbon emitter (Sajid et al 2020 , 2021 ; Sajid 2021 ; Sajid and Gonzalez 2021 ). Despite this significant contribution to global carbon emissions, China was the world leader in renewable energy production capacity in 2020 (Jaganmohan 2021a ).…”