群眾物流餐飲外送平台之消費者行為與服務屬性

Consumer Behavior and Service Attributes for Food Delivery via Crowd Logistics Platforms

溫裕弘(Yuh-Horng Wen) ； 游欣妤(Hsin-Yu You)

《運輸學刊》 33卷3期 (2021/09) Pp. 333-360

https://doi.org/10.6383/JCIT.202109_33(3).0004

摘要

本研究以服務體驗工程為架構結合服務體驗洞察與方法目的鏈及消費者行為模型方法，探討群眾物流餐飲外送平台之消費者服務體驗過程之服務屬性與使用行為特性。研究歸納消費者服務體驗之使用行為流程，得出5類服務失效點、13項重要服務屬性、6條主要認知路徑並彙整服務體驗需求表。並由消費者行為模型調查分析，探討有、無使用經驗者之行為特性。透過集群分析，將有使用經驗者分為3個集群，以滿意度易受平台服務項目影響之「平台服務導向型」占比最多；無使用經驗者則分為2個集群，以選定平台前先進行評估之「平台評估型」占比最多。本研究以顧客導向提出使用者偏好之服務屬性，可供業者發展創新商業模式參考，進而提升平台營運的發展性。

關鍵字

服務體驗工程 ； 群眾物流 ； 餐飲外送平台 ； 服務屬性

並列摘要

This study applies the service experience engineering (SEE) as the research structure, the approach integrated with the contextual inquiry and means-end chains (MEC) and Engel-Kollat-Blackwell (EKB) model explores the user experience, the motivation, target value and behavior characteristics in the consumer service experience process towards crowd logistics food delivery platforms. The results of qualitative research highlighted five types of service failure points, thirteen important service attributes, and six main cognitive paths. The results of EKB model deduced important service attributes for those with/without usage experience of food delivery platforms. According to the cluster analysis, three clusters of the experienced group were identified, with the largest sample number of ＂platform service-oriented＂ cluster, who are more likely to be affected their satisfaction by platform service items. On the other hand, two clusters of those without experience were identified, with the largest sample number of ＂platform-evaluated＂ cluster, who will conduct evaluation before selecting a platform. The results contribute to identifying user-oriented service attributes from the consumer preference which can be used to improve the development of innovative business models for platform operators.

並列關鍵字

Service experience engineering ； Crowd logistics ； Food delivery platform ； Service attributes

參考文獻

財團法人資訊工業策進會 (2008)，服務體驗工程方法指引，臺北：經濟部技術處。

財團法人資訊工業策進會 (2011)，服務體驗工程方法：藍圖、工具、案例，臺北：經濟部技術處。

國家發展委員會 (2018)，107 年持有手機民眾數位機會調查報告。

Boomsma, A. (1983), On the Robustness of LISREL (Maximum Likelihood Estimation) Against Small Sample Size and Non-normality, Ph.D. Thesis, University of Groningen, Sociometric Foundation, Amsterdam.

Rai, H. B., Verlinde, S., Merckx, J., and Macharis, C. (2017), “Crowd Logistics: An Opportunity for More Sustainable Urban Freight Transport?” European Transport Research Review, Vol. 9, No. 39, pp. 9-39.