Exploring Asymmetric Gender-Based Satisfaction of Delivery Riders in Real-Time Crowdsourcing Logistics Platforms DOI Creative Commons
Dan Li, Yi Zhang

Symmetry, Год журнала: 2024, Номер 16(11), С. 1499 - 1499

Опубликована: Ноя. 8, 2024

This study investigates gender-based differences in the satisfaction ranking of riders on real-time crowdsourcing logistics platforms, using online reviews from Ele.me platform. Quantitative methods, including frequency ratio-based Analytic Hierarchy Process (AHP), probabilistic linguistic term sets (PLTS), and fuzzy comprehensive evaluation (FCE), were applied to analyze between men women riders. The findings reveal an asymmetric pattern preferences: place more emphasis perceived value, while prioritize service quality. Although both groups rank platform image, product quality, rider expectations similarly, importance these factors varies significantly, indicating underlying asymmetry their values. Women express higher with expectations, showing largest difference. Additionally, multi-criteria decision-making methods used this offer insights for optimizing performance particularly handling uncertainty enhancing system adaptability through sets. These provide a basis developing gender-specific strategies aimed at satisfaction, minimizing turnover, improving adaptability—contributing inclusive sustainable supply chain.

Язык: Английский

Dynamic prediction of product competitive position: A multisource data-driven competitive analysis framework from a multi-competitor perspective DOI

Yanlai Li,

Hee-Wan Yu, Zifan Shen

и другие.

Journal of Retailing and Consumer Services, Год журнала: 2025, Номер 85, С. 104289 - 104289

Опубликована: Март 21, 2025

Язык: Английский

Процитировано

0
Dynamic product quality improvement using social media data and competitor-based Kano model DOI
Zheng Lu, Lin Sun, Zhen He

и другие.

International Journal of Production Economics, Год журнала: 2025, Номер unknown, С. 109645 - 109645

Опубликована: Апрель 1, 2025

Процитировано

0
Exploring Asymmetric Gender-Based Satisfaction of Delivery Riders in Real-Time Crowdsourcing Logistics Platforms DOI Creative Commons
Dan Li, Yi Zhang

Symmetry, Год журнала: 2024, Номер 16(11), С. 1499 - 1499

Опубликована: Ноя. 8, 2024

This study investigates gender-based differences in the satisfaction ranking of riders on real-time crowdsourcing logistics platforms, using online reviews from Ele.me platform. Quantitative methods, including frequency ratio-based Analytic Hierarchy Process (AHP), probabilistic linguistic term sets (PLTS), and fuzzy comprehensive evaluation (FCE), were applied to analyze between men women riders. The findings reveal an asymmetric pattern preferences: place more emphasis perceived value, while prioritize service quality. Although both groups rank platform image, product quality, rider expectations similarly, importance these factors varies significantly, indicating underlying asymmetry their values. Women express higher with expectations, showing largest difference. Additionally, multi-criteria decision-making methods used this offer insights for optimizing performance particularly handling uncertainty enhancing system adaptability through sets. These provide a basis developing gender-specific strategies aimed at satisfaction, minimizing turnover, improving adaptability—contributing inclusive sustainable supply chain.

Язык: Английский

Процитировано

0