本研究旨在探討臺灣偏鄉地區居民對無人機物流服務之偏好行為，並以隨訂隨送（On-demand Delivery）、預約方案（Reservation Delivery）及維持現況（Status Quo）三種方案作為研究情境。本研究問卷採用顯示性偏好法（Stated Preference, SP）進行資料蒐集，以分析不同配送服務屬性在各偏鄉地區及社經特性族群間之接受程度差異。為同時考量受訪者可觀察特徵與不可觀察心理因素對選擇行為之影響，本研究建構整合異質一般化選擇潛在變數模型（Integrated Heteroskedastic Generalized Choice and Latent Variable Model, IHGLV），以深入探討效用結構與替代方案相關性中之偏好異質性。
研究結果顯示，偏鄉民眾對無人機物流服務之偏好具有顯著的異質性。相較於隨訂隨送方案，受訪者普遍認為預約方案具有更高的穩定性及可預測性，因此展現較高的接受意願。此外，本研究將隱私性（Privacy Concerns）、個人創新性（Personal Innovativeness）及創新障礙（Innovation Barriers）等潛在心理構面納入模型，能夠更有效的解釋不同受訪者間接受程度之差異，結果顯示心理態度在無人機物流的使用意願中扮演重要角色。研究結果亦證實，IHGLV模型相較於傳統離散選擇模型具有較佳之解釋能力，可同時捕捉服務屬性、社經變數與潛在心理因素對選擇行為之影響，以進一步的解釋影響無人機物流接受程度之影響因素。
本研究之結果顯示出在需求預測與無人機物流規劃中，同時考量可觀察與不可觀察異質性的重要性。此外，預約配送相較於其他替選方案，更適合作為偏鄉地區無人機物流之初期導入方案，尤其對於風險感知較高或隱私顧慮較強之使用者將更具吸引力。並且透過有效的宣導措施及試辦計畫，有助於降低民眾對新興技術之創新障礙，進而提升接受意願。在研究方法之部分，IHGLV模型能夠同時捕捉效用異質性、潛在心理態度及替代方案間之偏好，為需求預測與政策評估提供更有效之分析架構。本研究結果可作為相關政府部門及未來無人機物流業者規劃偏鄉無人機物流服務之重要參考依據，以提升服務之可靠性、接受度及未來長期發展之機會。

This study explores rural residents’ preferences toward drone delivery services in Taiwan, focusing on three alternatives: on-demand delivery, reservation delivery, and the status quo. A stated preference survey was conducted to evaluate how users respond to different delivery configurations across geographic and demographic segments. To capture both observed characteristics and unobserved psychological factors, an Integrated Heterogeneous Generalized Nested Logit model with Latent Variables (IHGLV) was employed, allowing a comprehensive investigation of preference heterogeneity in both utility structure and substitution patterns.
The results demonstrate that individual preferences toward drone delivery are far from uniform. While on-demand delivery was often perceived as uncertain, reservation-based services were better received due to their structured and predictable nature. More importantly, including latent constructs: Privacy concerns, Personal Innovativeness, and Innovation Barriers revealed significant attitudinal heterogeneity that helped explain variation in acceptance levels across individuals. The IHGLV model outperformed conventional models by uncovering how underlying attitudes interact with delivery attributes and socioeconomic traits, offering a deeper understanding of the psychological mechanisms driving choice behavior.
This study underscores the value of accounting for both observed and latent sources of heterogeneity in demand forecasting and service design. From a service-design perspective, reservation-based drone delivery represents a more viable initial deployment pathway, particularly for users with higher perceived risk or stronger privacy concerns, while targeted communication and trial operations may be necessary to reduce innovation barriers. Methodologically, the IHGLV approach provides a robust basis for demand forecasting by capturing simultaneous heterogeneity in utilities, latent attitudes, and substitution structures dimensions that conventional discrete choice models often fail to represent. These insights offer actionable implications for policymakers and operators seeking to design reliable, acceptable, and scalable drone logistics in underserved rural regions.

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