| 研究生: |
陶品岑 Tao, Pin-Cen |
|---|---|
| 論文名稱: |
公務人員使用人力招募網站意圖 與滿意度之影響因素研究 -以「事求人機關徵才系統」為例 A Study of the Factors Affecting Civil Servants’ Intentions to Use and Satisfaction with an Online Recruitment Platforms: Using the Job Seeker Government Recruitment System as an Example |
| 指導教授: | 陳敦源 |
| 口試委員: |
董祥開
李仲彬 |
| 學位類別: |
碩士
Master |
| 系所名稱: |
社會科學學院 - 行政管理碩士學程 Master for Eminent Public Administrators |
| 論文出版年: | 2025 |
| 畢業學年度: | 114 |
| 語文別: | 中文 |
| 論文頁數: | 182 |
| 中文關鍵詞: | 事求人機關徵才系統 、公務人員 、UTAUT 模型 、E-S-QUAL 模型 、使用者滿意度 、持續使用意圖 |
| 外文關鍵詞: | Job-Opening Recruitment System, Civil Servants, UTAUT, E-S-QUAL, User Satisfaction, Continuance Intention |
| 相關次數: | 點閱:14 下載:0 |
| 分享至: |
| 查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
本研究以行政院人事行政總處建置之「事求人機關徵才系統」(簡稱事求人系統)為研究對象,探討影響公務人員使用該人力招募網站之持續使用意圖與使用者滿意度的關鍵因素。由於「事求人系統」具任務導向與階段性使用特性,且使用行為多受行政流程與職務需求所驅動,使用自主性相對有限,與民間求職平台之市場導向與自主操作情境存在本質差異。為更全面呈現影響機制,本研究整合科技接受與使用理論(Unified Theory of Acceptance and Use of Technology, UTAUT 模型)與 E-S-QUAL 模型(Electronic Service Quality Model),建構以持續使用意圖為核心依變項之研究架構,並將使用者滿意度作為中介變項。
本研究以曾使用「事求人系統」之公務人員為對象,採問卷調查法蒐集資料,經語意前測與預試分析後正式施測。研究結果顯示:
一、「績效期望」、「努力期望」、「社會影響」及「系統可用性」對持續使用意圖具有顯著正向影響。
二、「績效期望」、「促成條件」與「安全隱私性」對使用者滿意度具顯著正向影響。
三、「績效期望」與「促成條件」透過「使用者滿意度」對「持續使用意圖」產生顯著中介效果,其中前者為部分中介,後者為完全中介。
四、控制變項整體未呈顯著影響,顯示公務人員之性別、年齡、官等、服務年資及使用經驗等個人屬性,對持續使用意圖與使用者滿意度皆未產生顯著差異。
綜合分析結果,績效期望在所有構面中展現最高影響力,顯示系統效能與任務支援是驅動持續使用意圖與提升滿意度的核心因素。對於持續使用意圖而言,努力期望、社會影響與系統可用性亦呈顯著正向效果,反映操作便利性、組織氛圍及同儕影響均會推動公務人員使用該制度性平台。滿意度方面,促成條件與安全隱私性為關鍵來源,代表行政支援、技術協助與資訊安全均會提升整體使用評價;而促成條件與績效期望並透過滿意度進一步影響持續使用意圖,展現明確的中介路徑。整體而言,事求人系統之使用行為同時受到動機面(UTAUT)與品質面(E-S-QUAL)因素共同影響。研究建議主管機關可強化任務支援功能、提升資訊安全、簡化操作流程並完善行政與技術支援,以全面提升公務人員之使用體驗、滿意度及後續使用意願。
This study examines the key factors influencing civil servants’ continuance intention to use and user satisfaction with the “Job-Opening Recruitment System for Agencies” (hereafter, the Job-Opening System), an online recruitment platform developed by the Directorate-General of Personnel Administration, Executive Yuan. The Job-Opening System is characterized by task-oriented and stage-based usage, where user behavior is largely driven by administrative procedures and job requirements. As a result, users’ autonomy is relatively limited, which fundamentally distinguishes this institutional platform from the market-driven and self-directed usage context of private job-search websites. To more comprehensively capture the underlying mechanisms, this study integrates the Unified Theory of Acceptance and Use of Technology (UTAUT) with the Electronic Service Quality Model (E-S-QUAL), and develops a research framework that takes continuance intention as the core dependent variable while incorporating user satisfaction as a mediating variable.
The research targets civil servants who have used the Job-Opening System and employs a questionnaire survey to collect data. Following semantic pretesting and pilot analysis, the formal survey was administered. The empirical findings show that:
(1) Performance expectancy, effort expectancy, social influence, and system usability all exert significant positive effects on continuance intention.
(2) Performance expectancy, facilitating conditions, and security and privacy have significant positive effects on user satisfaction.
(3) Performance expectancy and facilitating conditions have significant mediating effects on continuance intention through user satisfaction, with the former exhibiting partial mediation and the latter full mediation.
(4) Overall, the control variables do not show significant effects, indicating that civil servants’ individual attributes—such as gender, age, rank, tenure, and system usage experience—do not produce significant differences in either continuance intention or user satisfaction.
Taken together, the results indicate that performance expectancy has the strongest influence among all constructs, suggesting that system effectiveness and task support are the core drivers of both continuance intention and user satisfaction. With respect to continuance intention, effort expectancy, social influence, and system usability also demonstrate significant positive effects, reflecting that ease of use, organizational climate, and peer influence all help encourage civil servants to use this institutional platform. In terms of satisfaction, facilitating conditions and security and privacy are the key sources, implying that administrative support, technical assistance, and information security all enhance overall evaluations of system use. Moreover, facilitating conditions and performance expectancy further influence continuance intention through user satisfaction, forming clear mediating pathways. Overall, usage behavior on the Job-Opening System is jointly shaped by motivational factors (UTAUT) and service quality factors (E-S-QUAL). The study recommends that system administrators strengthen task-support functions, enhance information security, simplify operational procedures, and improve administrative and technical support in order to comprehensively enhance user experience, user satisfaction, and subsequent willingness to continue using the system.
摘要 I
Abstract III
目次 V
表目錄 VII
圖目錄 IX
第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的與問題 5
第三節 研究流程 7
第二章 文獻探討 11
第一節 政府內部人力市場與「事求人系統」 11
第二節 UTAUT模型 24
第三節 E-S-QUAL網站服務品質模型 33
第四節 使用者滿意度 38
第五節 理論整合架構與研究變項關係之綜合分析 42
第三章 研究方法 53
第一節 研究架構與研究假設 53
第二節 研究變數之操作型定義 56
第三節 研究設計 64
第四節 問卷前測與信效度分析 70
第四章 資料分析 76
第一節 問卷發放情形與樣本結構分析 76
第二節 各變項構面之描述性統計與信效度分析 83
第三節 PLS-SEM分析 92
第四節 使用者滿意度與使用行為之補充分析 102
第五節 事求人系統與民間求職平台之情境差異 108
第五章 研究結論 114
第一節 研究成果 114
第二節 研究建議 122
第三節 研究限制與未來研究方向 128
參考文獻 131
附錄一 前測與正式問卷 139
附錄二 本研究補充分析統計表 151
附錄三 修正建議與紀錄 153
壹、中文文獻
李淑萍、李暐珣、詹雅慧(2007)。人力銀行服務品質之研究:Kano二維品質及IPA整合模式之應用。績效與策略研究,4(2),1-17。
邱皓政(2009)。量化研究與統計分析:使用SPSS為例。五南圖書出版公司。
林曉伶(2018)。求職者使用就業網站之意向研究-以勞動部台灣就業通網站為例(未出版之碩士論文)。南臺科技大學企業管理學系人力資源管理研究所。
邱昱綺(2021)。人力招募網站行動裝置應用程式之使用意願影響因素研究-以104人力銀行為例(未出版之碩士論文)。國立政治大學企業管理研究所。
施能傑(2003)。公務人員考選制度的評估。臺灣政治學刊,7(1),157-205。
孫思源、羅月秀、趙珮如(2008)。人力資源招募網站使用意向影響因素之探討。人力資源管理學報,8(3),1-23。
郭麗文(2012)。公務人員導入資訊系統之使用者滿意度相關研究(以某直轄市政府及其所屬機關為例)(未出版之碩士論文)。國立高雄師範大學人力與知識管理研究所。
張瓊文(2012)。高雄市政府導入WEBITR差勤電子表單系統使用者滿意度之研究(未出版之碩士論文)。國立高雄師範大學人力與知識管理研究所。
游子正、董祥開(2020)。公務人員單位離職傾向之影響因素分析。文官制度季刊》,12(4),1–38。
陳揚中、陳敦源、張鎧如、董祥開(2018)。探索臺灣公務人員追求職涯成功「為官之道」的認知:Q方法論之研究。行政暨政策學報,11(1),1–66。
陳敦源、張鎧如、董祥開、陳揚中(2016)。從循證人力資源管理建構激勵導向的公共服務:公務人員職涯發展模式初探與規劃。(未出版之考試院專題研究計畫)。
陳岳陽(2019)。智慧型穿戴式裝置創新感知特徵對使用者滿意度與持續使用意圖影響之研究(未出版碩士論文)。國立中央大學資訊管理學系。
蘇偉業(2017)。我國行政機關內部人力市場人力流動之空間分析(第2年)。(未出版之科技部專題研究計畫,計畫編號:MOST 104-2410-H-004-095-MY2)。
蘇偉業(2018)。我國政府內部人力市場行為之初探:個人利益與組織利益之權衡。文官制度季刊,10(1),21-58。
蘇偉業、賴怡樺、王貿(2019)。我國行政機關公務人力流動之初探:以跨職系流動為焦點。行政暨政策學報,69,49-84。
貳、西文文獻
Alam, M. Z., Hoque, M. R., Hu, W., & Barua, Z. (2020a). Factors Influencing the Adoption of mHealth Services in a Developing Country: A Patient-Centric Study. International Journal of Information Management, 50, 128–143.
Ajzen, I. (1991). The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes, 50, 179–211.
Al-Khaldi, M. A., & Wallace, R. S. O. (1999). The Influence of Attitudes on Personal Computer Utilization Among Knowledge Workers: The Case of Saudi Arabia. Information & Management, 36(4), 185–204.
Bandura, A. (1986). Social Foundations of Thought and Action: A Social Cognitive Theory. Englewood Cliffs, NJ: Prentice-Hall.
Bhattacherjee, A. (2001). Understanding Information Systems Continuance: An Expectation-Confirmation Model. MIS Quarterly, 25(3), 351–370.
Bhattacherjee, A., & Premkumar, G. (2004). Understanding Changes in Belief and Attitude Toward Information Technology Usage: A Theoretical Model and Longitudinal Test. MIS Quarterly, 28(2), 229–254.
Baroudi, J. J., & Orlikowski, W. J. (1988). A Short-Form Measure of User Information Satisfaction: A Psychometric Evaluation and Notes on Use. Journal of Management Information Systems, 4(4), 44–59.
Bagozzi, R. P., & Yi, Y. (1988). On the Evaluation of Structural Equation Models. Journal of the Academy of Marketing Science, 16(1), 74–94.
Chao, C. M. (2019). Factors Determining the Behavioral Intention to Use Mobile Learning: An Application and Extension of the UTAUT Model. Frontiers in Psychology, 10(1652), 1–14.
Cyert, R. M., & March, J. G. (1963). A Behavioral Theory of the Firm. Englewood Cliffs, NJ: Prentice-Hall.
Chow, A., & Legowo, R. (2023). Measuring User Satisfaction of the Peduli Lindungi Application Using PLS-SEM. Journal of System and Management Sciences, 13(2), 170–184.
Cristobal, E., Flavián, C., & Guinalíu, M. (2007). Perceived E-Service Quality: Measurement Validation and Effects on Consumer Satisfaction and Website Loyalty. Managing Service Quality, 17(3), 317–340.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35(8), 982–1003.
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319–340.
DeLone, W. H., & McLean, E. R. (1992). Information Systems Success: The Quest for the Dependent Variable. Information Systems Research, 3(1), 60–95.
Doll, W. J., & Torkzadeh, G. (1988). The Measurement of End-User Computing Satisfaction. MIS Quarterly, 12(2), 259–274.
DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean Model of Information Systems Success: A Ten-Year Update. Journal of Management Information Systems, 19(4), 9–30.
Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39–50.
Fornell, C. (1992). A National Customer Satisfaction Barometer: The Swedish Experience. Journal of Marketing, 56(1), 6–21.
Faizal, A. (2020). The Influential Factors in the Modified Unified Theory of the Acceptance and Use of Technology on Customer Satisfaction for Adopting BJB Digi. In Proceedings of the 5th Global Conference on Business, Management and Entrepreneurship (GCBME 2020) (pp. 429–433). Atlantis Press.
Field, A. (2018). Discovering Statistics Using IBM SPSS Statistics (5th ed.). SAGE Publications.
Hurley, R. F., & Estelami, H. (1998). Alternative Indexes for Monitoring Customer Perceptions of Service Quality: A Comparative Evaluation in a Retail Context. Academy of Marketing Science, 36(3), 209–221.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (2nd ed.). SAGE Publications.
Hair, J. F., Babin, B. J., Anderson, R. E., & Black, W. C. (2019). Multivariate Data Analysis (8th ed.). Pearson.
Hu, L. T., & Bentler, P. M. (1999). Cutoff Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria Versus New Alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55.
Ives, B., Olson, M. H., & Baroudi, J. J. (1983). The Measurement of User Information Satisfaction. Communications of the ACM, 26(10), 785–793.
Khalil, O. E. M., & Elkordy, M. M. (1999). The Relationship Between User Satisfaction and Systems Usage. Journal of End User Computing, 11(2), 21–28.
Melone, N. P. (1990). A Theoretical Assessment of the User-Satisfaction Construct in Information Systems Research. Management Science, 36(1), 76–91.
Moore, G. C., & Benbasat, I. (1991). Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation. Information Systems Research, 2(3), 191–222.
Mohamed, N., Hussein, R., Zamzuri, N. H. A., & Haghshenas, H. (2014). Insights Into Individual’s Online Shopping Continuance Intention. Industrial Management & Data Systems, 114(9), 1453–1476.
Mokhtar, S. A., Katan, H., & Hidayat ur Rehman, I. (2017). Mobile Banking Adoption: The Impacts of Social Influence, Ubiquitous Finance Control and Perceived Trust on Customers’ Loyalty. Scientific International (Lahore), 29(4), 829–836.
Nunnally, J. C. (1978). Psychometric Theory (2nd ed.). McGraw-Hill.
Oliver, R. L. (1980). A Cognitive Model of the Antecedents and Consequences of Satisfaction. Journal of Marketing Research, 17(4), 460–469.
Oliver, R. L. (1981). Measurement and Evaluation of Satisfaction Processes in Retailing Setting. Journal of Retailing, 57(3), 25–48.
Oliver, R. L. (1997). Satisfaction: A Behavioral Perspective on the Consumer. McGraw-Hill.
Parasuraman, A., Zeithaml, V. A., & Malhotra, A. (2005). E-S-QUAL: A Multiple-Item Scale for Assessing Electronic Service Quality. Journal of Service Research, 7(3), 213–233.
Pappu, R., & Quester, P. (2006). Does Customer Satisfaction Lead to Improved Brand Equity: An Empirical Examination of Two Categories of Retail Brands. The Journal of Product and Brand Management, 15(1), 4–14.
Putra, N. P., & Retnowardhani, A. (2024). Unlocking User Satisfaction: A DeLone & McLean IS Success Model Approach to IT Helpdesk Ticketing System Adoption. Journal of Applied Engineering and Technological Science, 6(1), 610–625.
Rehman, I. H. U., Ahmad, A., Akhter, F., & Aljarallah, A. (2021). A Dual-Stage SEM-ANN Analysis to Explore Consumer Adoption of Smart Wearable Healthcare Devices. Journal of Global Information Management (JGIM), 29(6), 1–30.
Rogers, E. M. (2003). Diffusion of Innovations (5th ed.). Free Press.
Rai, A., Lang, S. S., & Welker, R. B. (2002). Assessing the Validity of IS Success Models: An Empirical Test and Theoretical Analysis. Information Systems Research, 13(1), 50–69.
Rafiq, M., Lu, X., & Fulford, H. (2012). Measuring Internet Retail Service Quality Using E-S-QUAL. Journal of Marketing Management, 28(9–10), 1189–1208.
Salimon, M. G., Sanuri, S. M. M., Aliyu, O. A., Perumal, S., & Yusr, M. M. (2021). E-Learning Satisfaction and Retention: A Concurrent Perspective of Cognitive Absorption, Perceived Social Presence and Technology Acceptance Model. Journal of Systems and Information Technology, 23(1), 98–117.
Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal Computing: Toward a Conceptual Model of Utilization. MIS Quarterly, 15(1), 125–143.
Taylor, S., & Todd, P. (1995). Assessing IT Usage: The Role of Prior Experience. MIS Quarterly, 19(4), 561–570.
Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal Computing: Toward a Conceptual Model of Utilization. MIS Quarterly, 15(1), 125–143.
Tawafak, R. M., Romli, A. B., Arshah, R. B. A., & Malik, S. I. (2020). Framework Design of University Communication Model (UCOM) to Enhance Continuous Intentions in Teaching and E-Learning Process. Education and Information Technologies, 25, 817–843.
Venkatesh, V., & Davis, F. D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46(2), 186–204.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425–478.
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 36(1), 157–178.
Voorhees, C. M., Brady, M. K., Calantone, R., & Ramirez, E. (2016). Discriminant Validity Testing in Marketing: An Analysis, Causes for Concern, and Proposed Remedies. Journal of the Academy of Marketing Science, 44(1), 119–134.
Woodside, A. G., Frey, L. L., & Daly, R. T. (1989). Linking Service Quality, Customer Satisfaction, and Behavioral Intention. Journal of Health Care Marketing, 9(4), 5–17.
Wixom, B. H., & Todd, P. A. (2005). A Theoretical Integration of User Satisfaction and Technology Acceptance. Information Systems Research, 16(1), 85–102.
Zeithaml, V. A., Berry, L. L., & Parasuraman, A. (1988). Communication and Control Processes in the Delivery of Service Quality. Journal of Marketing, 52(2), 35–48.
Zeithaml, V. A., Parasuraman, A., & Malhotra, A. (2002). Service Quality Delivery Through Web Sites: A Critical Review of Extant Knowledge. Journal of the Academy of Marketing Science, 30(4), 362–375.
Zeithaml, V. A., & Bitner, M. J. (2000). Services Marketing: Integrating Customer Focus Across the Firm (3rd ed.). Upper Saddle River, NJ: McGraw-Hill.
全文公開日期 2027/02/08