在當今快速變化的市場環境中，柔性化技術服務已成為企業競爭的關鍵因
素之一。特別是對於大客戶來說，他們往往需要更加個性化和靈活的服務來滿
足其獨特需求。研究柔性化技術服務對大客戶購買行為的影響具有重要的理論
和實踐意義。本研究首先通過文獻綜述，對柔性化技術服務的定義和特點進行
了深入探討，並回顧了現有研究中關於大客戶購買行為的相關理論和模型。在
此基礎上，本研究構建了一個理論框架，其中包括柔性化技術服務的影響因素，
如技術服務的特性、客戶需求、服務交付過程和技術服務的價值主張，以及大
客戶購買行為的影響因素，如大客戶決策過程、購買動機、風險和回報。為了
驗證柔性化技術服務與大客戶購買行為之間的關係，本研究採用了實證研究方
法。通過精心設計的問卷調查和深入的訪談，收集了大量的大客戶購買行為數
據，並運用統計分析方法對數據進行了深入分析。研究結果表明，柔性化技術
服務對大客戶的購買行為具有顯著影響，能夠提高客戶的購買滿意度和忠誠度。
根據研究結果，本研究提出了一系列針對性的管理實踐和建議，以幫助企業優
化其柔性化技術服務，更好地滿足大客戶的需求。
關鍵字：柔性化技術服務；大客戶購買行為；影響因素；購買滿意度

In today's rapidly changing market environment, flexible technology service has
become one of the key factors of enterprise competition. Especially for big customers,
they often need more personalized and flexible services to meet their unique needs. It
is of great theoretical and practical significance to study the influence of flexible
technology service on the purchasing behavior of big customers. Firstly, the definition
and characteristics of flexible technology services are deeply explored through the
literature review, and the relevant theories and models about the purchase behavior of
large customers in the existing studies are reviewed. Based on this, this study constructs
a theoretical framework, including the influencing factors of flexible technical services,
such as the characteristics of technical services, customer demand, service delivery
process and the value proposition of technical services, as well as the influencing
factors of big customer purchasing behavior, such as big customer decision-making
process, purchasing motivation, risk and return. To try to verify the relationship
between flexible technology services and key customer purchasing behavior, empirical
research methods were used in this study. Through carefully designed questionnaire
survey and in-depth interview, a large number of purchasing behavior data of key
customers were collected, and the data were deeply analyzed by statistical analysis
methods. The research results show that flexible technology services have a significant
impact on the purchasing behavior of large customers, and can improve their purchasing
satisfaction and loyalty. According to the research results, this study puts forward a
series of targeted management practices and suggestions to help enterprises optimize
their flexible technology services to better meet the needs of big customers.
Keywords: Flexible technology service; purchasing behavior of key customers;
influencing factors; purchase satisfaction

中文文獻
王大飛、張旭梅、掌曙光、官子力、但斌（2022）。考慮消費者策略行為的產
品服務供應鏈動態定價與服務品質決策。管理評論，34 (01)，155-167。
王子君（2023）。我國成品油大客戶購買行為研究（未出版碩士論文）。中國:
北京石油化工學院。
李玉翠、韋淞文、周清萍（2023）。繼任CEO 身分差異與家族企業創新投入研
究—基於合法性的視角。廣西民族師範學院學報，40(1)，44-52。
李茜（2023）。進口跨境電商直播服務品質對購買意願的影響研究（未出版碩
士論文）。中國: 杭州師範大學。
杜姍（2023）。縣郵政企業農產品直播的消費者購買意願提升策略研究（未出
版碩士論文）。中國：南京郵電大學。
沈志禹（2023）。HT 證券公募基金產品客戶購買行為研究（未出版碩士論
文）。中國:中國礦業大學。
侯正毅、王崇彩（2022）。生鮮農產品電商服務品質對顧客行為影響實證研
究。山西農經，24，135-137。
程新鳳（2023）。T 公司服務運營管理優化研究（未出版碩士論文）。中國: 哈
爾濱工程大學。
齊雨萱（2022）。電商消費環境下消費者的購買行為研究。商展經濟，3， 69-
71。
51
英文文獻
Feng, Y., Song, D., Li, D., & Xie, Y. (2022). Service fairness and value of customer
information for the stochastic container relocation problem under flexible service
policy. Transportation Research Part E: Logistics and Transportation
Review, 167, 102921.
Hasumoto, K., & Goto, M. (2022). Correction to: Predicting customer churn for
platform businesses: using latent variables of variational autoencoder as
consumers’ purchasing behavior. Neural Computing and Applications, 34(21),
18543-18544.
Liu Yang. (2022). Thoughts on Library Flexible Service and Readers' Psychological
Environment [J]. Psychiatria Danubina, ,34 (S5): 257-257.
Nakamura, A., Naito, K., & Yamazato, T. (2022). Proposal of flexible service
deployment environment for the edge processing system. IEICE
Communications Express, 11(8), 503-508.
Tabianan, K., Velu, S., & Ravi, V. (2022). K-means clustering approach for intelligent
customer segmentation using customer purchase behavior data. Sustainability,
14(12), 7243.
Wu, Y., Wu, Y., Cimen, H., Vasquez, J. C., & Guerrero, J. M. (2022). P2P energy
trading: Blockchain-enabled P2P energy society with multi-scale flexibility
services. Energy Reports, 8, 3614-3628.
Yang, T., Kumoi, G., Yamashita, H., & Goto, M. (2022). Transfer Learning Based on
Probabilistic Latent Semantic Analysis for Analyzing Purchase Behavior
Considering Customers' Membership Stages. Journal of Japan Industrial
Management Association, 73(2), 160-175.
Zhang, Y., Guo, W., Negenborn, R. R., & Atasoy, B. (2022). Synchromodal transport
planning with flexible services: Mathematical model and heuristic algorithm.
Transportation Research Part C: Emerging Technologies, 140, 103711.