Responsive image
博碩士論文 etd-0612122-152217 詳細資訊
Title page for etd-0612122-152217
論文名稱
Title
個人認知負荷對員工之任務科技適配程度之影響 —以任務科技適配理論為核心來探討
The Effect of Individual Cognitive Load on Employee’s Task-Technology Fit -Based on Task-Technology Fit Theory
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
76
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2022-06-27
繳交日期
Date of Submission
2022-07-12
關鍵字
Keywords
認知負荷理論、任務特徵、科技特徵、任務科技適配理論、過程滿意度、結果滿意度
Cognitive Load Theory, Task characteristics, Technology characteristics, Task-Technology Fit, Satisfaction of process, Satisfaction of outcome
統計
Statistics
本論文已被瀏覽 314 次,被下載 148
The thesis/dissertation has been browsed 314 times, has been downloaded 148 times.
中文摘要
隨著網路的無遠弗屆,及科技高速的發展之下,數位能力儼然已成為企業競爭的基礎能力,企業不斷的增加對於新興科技系統的投資,然而科技的使用或許能帶來更高任務成果效益,但同時也可能造成員工更大的心理壓力。先前相關研究多著重於科技如何協助任務的執行,本研究加入了個人心理因素來探討工作場域上影響任務與科技,以更完整的角度探討影響任務與科技適配之因素與其如何影響任務結果滿意度。
本研究結合了認知負荷理論、任務科技適配理論以及過去文獻中提及的架構來探討個人認知負荷對於任務結果滿意度之影響因素。任務科技適配受任務特徵、科技特徵所影響,本研究歸納出四項影響任務特徵之性質、與三項影響科技特徵之性質,並加入三項認知負荷因素來探討其對於任務科技適配程度之影響程度,而任務科技適配則影響任務執行過程滿意度,進而影響結果滿意度。
本研究回收了385份有效問卷,驗證任務特徵、科技特徵、認知負荷對於任務科技適配之影響,結果顯示時間壓力對於任務特徵無顯著影響,並表示支持個人認知負荷過載時對於任務科技適配的程度有負向影響,任務科技適配對於任務過程滿意度有顯著正向影響。本研究有別於以往任務科技適配之研究,結合認知心理學與架構來驗證影響任務適配之變數,可以提供給企業作為未來在科技評估或是流程改良之參考。
Abstract

With the far-reaching characteristics of Internet, and the rapid development of technology, digital capabilities have become the foundation of enterprise competitiveness. Therefore, enterprises are constantly increasing their investment in emerging information system. However, while powerful technologies may bring higher task performances, it may cause serious psychological stress to employees at the same time. Previous studies have focused on how technology can be adapted to the task to achieve higher benefits. This study adds individual psychological factors to examine how these factors affect the degree of task and technology in the workspace.
This study combines Cognitive Load Theory, Task-Technology Fit Theory and the framework proposed in past literature to discuss the influence of cognitive load on task-technology fit. This study summarizes four task characteristics and three technology characteristics that affect task-technology fit. In addition, three cognitive load factors were added to the discussion. Task-technology fit affects the satisfaction of task process, which in turn affects the satisfaction of task outcome.
This study collected 385 valid samples. The results showed that time pressure didn’t have a significant effect on task characteristics, and indicated that cognitive overload had a significant negative effect on task-technology fit. This research differs from previous research by combining cognitive psychology to verify the variables affecting task-technology fit, which can be used as a reference for companies evaluate technology and improve process in the future.
目次 Table of Contents
論文審定書.....................................................................................................................i 摘要................................................................................................................................ii Abstract ........................................................................................................................ iii 目錄...............................................................................................................................iv 圖次..............................................................................................................................vii 表次............................................................................................................................ viii 第一章 緒論................................................................................................................ 1
第一節 研究背景.................................................................................................... 1 第二節 研究動機.................................................................................................... 2 第三節 研究目的與問題........................................................................................ 4 第四節 研究流程.................................................................................................... 4
第二章 文獻探討........................................................................................................ 6
第一節 任務科技適配理論(Task-Technology Fit Theory)...................................6 第二節 過去任務科技適配相關文獻.................................................................... 9 第三節 認知負荷理論(Cognitive Load Theory) .................................................11 第四節 認知負荷對滿意度之影響...................................................................... 15
第三章 研究方法...................................................................................................... 17
第一節 研究模型.................................................................................................. 17 第二節 假說研究.................................................................................................. 18 一、 任務構面(Task) .......................................................................................18 二、 科技構面(Technology)............................................................................19
三、 認知負荷構面(Cognitive Load) .............................................................. 20 四、 任務科技適配(Task-Technology Fit Theory).........................................22 五、 滿意度(Satisfaction) ................................................................................ 23
第三節 操作型定義.............................................................................................. 25 第四節 研究設計.................................................................................................. 26 一、 研究對象.................................................................................................. 26 二、 問卷設計.................................................................................................. 26 三、 資料搜集.................................................................................................. 31
第四章 資料分析...................................................................................................... 32
第一節 敘述性統計(Descriptive Statistics) ......................................................... 32 第二節 衡量模型(Measurement Model)..............................................................35 一、 共同方法偏誤(Common Methods Bias).................................................35 二、 信度(Reliability) ...................................................................................... 37 三、 收斂效度(Convergent Validity) ..............................................................38 四、 區別效度(Discriminant V alidity) ............................................................ 40 五、 共線性(Multivollinearity)........................................................................ 41 第三節 結構模型與假說檢定(Structural Model and Hypothesis Testing).........42 第四節 討論(Disscusion) ..................................................................................... 44 一、 任務特徵對任務科技適配之影響.......................................................... 44 二、 科技特徵之影響...................................................................................... 45 三、 認知負荷.................................................................................................. 46 四、 任務科技適配對過程滿意度之影響...................................................... 46 五、 過程滿意度對結果滿意度之影響.......................................................... 46
第五章 結論.............................................................................................................. 48
第一節 結論.......................................................................................................... 48
第二節 學術貢獻與實務貢獻(Academic And Practical Implications)...............49 第三節 研究限制與未來研究方向(Limitations And Suggestions For Future Study) .................................................................................................................. 50
參考文獻...................................................................................................................... 51 附件.............................................................................................................................. 61
參考文獻 References
Awad, H. A. H. (2020). Investigating employee performance impact with integration of task technology fit and technology acceptance model: the moderating role of self-efficacy. International Journal of Business Excellence, 21(2), 231-249.
Ayres, P. (2006). Impact of reducing intrinsic cognitive load on learning in a mathematical domain. Applied Cognitive Psychology: The Official Journal of the Society for Applied Research in Memory and Cognition, 20(3), 287-298.
Banken, V., Seeber, I., & Maier, R. (2019). Comparing pineapples with lilikois: an experimental analysis of the effects of idea similarity on evaluation performance in innovation contests.
Bannert, M. (2002). Managing cognitive load—recent trends in cognitive load theory. Learning and instruction, 12(1), 139-146.
Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation- confirmation model. MIS quarterly, 351-370.
Boskovic-Pavkovic, I., Seeber, I., & Maier, R. (2019). How digital nudges affect consideration set size and perceived cognitive effort in idea convergence of open innovation Contests. Proceedings of the 52nd Hawaii International Conference on System Sciences,
Bradford, G. R. (2011). A relationship study of student satisfaction with learning online and cognitive load: Initial results. The Internet and Higher Education, 14(4), 217-226.
Briggs, R. O., Kolfschoten, G. L., de Vreede, G.-J., Lukosch, S., & Albrecht, C. C. (2013). Facilitator-in-a-box: process support applications to help practitioners realize the potential of collaboration technology. Journal of Management Information Systems, 29(4), 159-194.
Brunken, R., Plass, J. L., & Leutner, D. (2003). Direct measurement of cognitive load in
51
multimedia learning. Educational psychologist, 38(1), 53-61.
Cameron, A. F., & Webster, J. (2005). Unintended consequences of emerging communication
technologies: Instant messaging in the workplace. Computers in Human behavior,
21(1), 85-103.
Chatterjee, S., & Wernerfelt, B. (1991). The link between resources and type of
diversification: Theory and evidence. Strategic management journal, 12(1), 33-48. Chen, S. (2017). The construct of cognitive load in interpreting and its measurement.
Perspectives, 25(4), 640-657.
Chen, S. (2017). The construct of cognitive load in interpreting and its measurement.
Perspectives, 25(4), 640-657.
Cheng, Y.-M. (2018). A hybrid model for exploring the antecedents of cloud ERP
continuance: Roles of quality determinants and task-technology fit. International
Journal of Web Information Systems.
Cheng, X., Fu, S., De Vreede, T., De Vreede, G.-J., Seeber, I., Maier, R., & Weber, B.
(2020). Idea convergence quality in open innovation crowdsourcing: a cognitive load
perspective. Journal of Management Information Systems, 37(2), 349-376.
Chin, W. W. (1998). Commentary: Issues and opinion on structural equation modeling. In
(pp. vii-xvi): JSTOR.
Cho, V., Cheng, T. E., & Lai, W. J. (2009). The role of perceived user-interface design in
continued usage intention of self-paced e-learning tools. Computers & Education,
53(2), 216-227.
Chow, T., & Cao, D.-B. (2008). A survey study of critical success factors in agile software
projects. Journal of systems and software, 81(6), 961-971.
Daim, T. U., Ha, A., Reutiman, S., Hughes, B., Pathak, U., Bynum, W., & Bhatla, A. (2012).
Exploring the communication breakdown in global virtual teams. International
Journal of Project Management, 30(2), 199-212. 52

Dang, Y., Zhang, Y., Chen, H., Brown, S. A., Hu, P. J.-H., & Nunamaker, J. F. (2012). Theory-informed design and evaluation of an advanced search and knowledge mapping system in nanotechnology. Journal of Management Information Systems, 28(4), 99-128.
De Jong, T. (2010). Cognitive load theory, educational research, and instructional design: Some food for thought. Instructional science, 38(2), 105-134.
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.
DeVellis, R. (2016). Scale development: theory and applications. Sage Publications. In: Inc. Dijkstra, T. K., & Henseler, J. (2015). Consistent partial least squares path modeling. MIS
quarterly, 39(2), 297-316.
Fong Boh, W., Slaughter, S. A., & Espinosa, J. A. (2007). Learning from experience in
software development: A multilevel analysis. Management science, 53(8), 1315-1331. Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables
and measurement error: Algebra and statistics. In: Sage Publications Sage CA: Los
Angeles, CA.
Fox, C. R., & Tversky, A. (1995). Ambiguity aversion and comparative ignorance. The
quarterly journal of economics, 110(3), 585-603.
Fritz, M. B. W., Narasimhan, S., & Rhee, H.-S. (1998). Communication and coordination in
the virtual office. Journal of Management Information Systems, 14(4), 7-28.
Fu, S., de Vreede, G.-J., Cheng, X., Seeber, I., Maier, R., & Weber, B. (2017). Convergence
of Crowdsourcing Ideas: A Cognitive Load perspective. ICIS,
Gerjets, P., & Scheiter, K. (2003). Goal configurations and processing strategies as moderators between instructional design and cognitive load: Evidence from
hypertext-based instruction. Educational psychologist, 38(1), 33-41. 53

Girotra, K., Terwiesch, C., & Ulrich, K. T. (2010). Idea generation and the quality of the best idea. Management science, 56(4), 591-605.
Glynn, S. M., Brickman, P., Armstrong, N., & Taasoobshirazi, G. (2011). Science motivation questionnaire II: Validation with science majors and nonscience majors. Journal of research in science teaching, 48(10), 1159-1176.
Golden, T. D., Veiga, J. F., & Dino, R. N. (2008). The impact of professional isolation on teleworker job performance and turnover intentions: does time spent teleworking, interacting face-to-face, or having access to communication-enhancing technology matter? Journal of Applied Psychology, 93(6), 1412.
Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual performance. MIS quarterly, 213-236.
Gorla, N., Somers, T. M., & Wong, B. (2010). Organizational impact of system quality, information quality, and service quality. The Journal of Strategic Information Systems, 19(3), 207-228.
Griffin, J. G., & Broniarczyk, S. M. (2010). The slippery slope: The impact of feature alignability on search and satisfaction. Journal of Marketing Research, 47(2), 323- 334.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing theory and Practice, 19(2), 139-152.
Hender, J. M., Dean, D. L., Rodgers, T. L., & Nunamaker Jr, J. F. (2002). An examination of the impact of stimuli type and GSS structure on creativity: Brainstorming versus non- brainstorming techniques in a GSS environment. Journal of Management Information Systems, 18(4), 59-85.
Henseler, J., Dijkstra, T. K., Sarstedt, M., Ringle, C. M., Diamantopoulos, A., Straub, D. W.,
Ketchen Jr, D. J., Hair, J. F., Hult, G. T. M., & Calantone, R. J. (2014). Common
beliefs and reality about PLS: Comments on Rönkkö and Evermann (2013).
54

Organizational research methods, 17(2), 182-209.
Hong, W., Thong, J. Y., & Tam, K. Y. (2004). The effects of information format and
shopping task on consumers' online shopping behavior: A cognitive fit perspective.
Journal of Management Information Systems, 21(3), 149-184.
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.
Isaac, O., Abdullah, Z., Ramayah, T., & Mutahar, A. M. (2017). Internet usage, user
satisfaction, task-technology fit, and performance impact among public sector employees in Yemen. The International Journal of Information and Learning Technology.
Jensen, M. L., Lowry, P. B., Burgoon, J. K., & Nunamaker, J. F. (2010). Technology dominance in complex decision making: The case of aided credibility assessment. Journal of Management Information Systems, 27(1), 175-202.
Keith, M., Demirkan, H., & Goul, M. (2017). The role of task uncertainty in IT project team advice networks. Decision Sciences, 48(2), 207-247.
Kirschner, F., Paas, F., & Kirschner, P. A. (2009). A cognitive load approach to collaborative learning: United brains for complex tasks. Educational psychology review, 21(1), 31- 42.
Kolfschoten, G. L., de Vreede, G.-J., & Pietron, L. R. (2011). A training approach for the transition of repeatable collaboration processes to practitioners. Group Decision and Negotiation, 20(3), 347-371.
Kompier, M. A., Cooper, C. L., & Geurts, S. A. (2000). A multiple case study approach to work stress prevention in Europe. European Journal of Work and Organizational Psychology, 9(3), 371-400.
Kositanurit, B., Ngwenyama, O., & Osei-Bryson, K.-M. (2006). An exploration of factors
55

that impact individual performance in an ERP environment: an analysis using multiple analytical techniques. European Journal of Information Systems, 15(6), 556- 568.
Koslowsky, M., Kluger, A. N., & Reich, M. (2013). Commuting stress: Causes, effects, and methods of coping. Springer Science & Business Media.
Kude, T., Mithas, S., Schmidt, C. T., & Heinzl, A. (2019). How pair programming influences team performance: The role of backup behavior, shared mental models, and task novelty. Information systems research, 30(4), 1145-1163.
Liu, P., & Li, Z. (2012). Task complexity: A review and conceptualization framework. International Journal of Industrial Ergonomics, 42(6), 553-568.
Mahmood, M. A., Burn, J. M., Gemoets, L. A., & Jacquez, C. (2000). Variables affecting information technology end-user satisfaction: a meta-analysis of the empirical literature. International Journal of Human-Computer Studies, 52(4), 751-771.
Mălăescu, I., & Sutton, S. G. (2015). The effects of decision aid structural restrictiveness on cognitive load, perceived usefulness, and reuse intentions. International Journal of Accounting Information Systems, 17, 16-36.
McGill, T. J., & Klobas, J. E. (2009). A task–technology fit view of learning management system impact. Computers & Education, 52(2), 496-508.
Miranda, S. M., & Bostrom, R. P. (1999). Meeting facilitation: process versus content interventions. Journal of Management Information Systems, 15(4), 89-114.
Olson, M. H. (1983). Remote office work: changing work patterns in space and time. Communications of the ACM, 26(3), 182-187.
Paas, F., Renkl, A., & Sweller, J. (2004). Cognitive load theory: Instructional implications of the interaction between information structures and cognitive architecture. Instructional science, 32(1/2), 1-8.
Panetta, K. (2021). CIO Agenda 2021:Prepare for Increased Digital Innovation. Retrieved 56

from https://www.gartner.com/smarterwithgartner/cio-agenda-2021-prepare-for-
increased-digital-innovation
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method
biases in behavioral research: a critical review of the literature and recommended
remedies. Journal of Applied Psychology, 88(5), 879.
Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of method bias in
social science research and recommendations on how to control it. Annual review of
psychology, 63(1), 539-569.
Podsakoff, P. M., & Organ, D. W. (1986). Self-reports in organizational research: Problems
and prospects. Journal of management, 12(4), 531-544.
Podsakoff, P. M., Todor, W. D., Grover, R. A., & Huber, V. L. (1984). Situational
moderators of leader reward and punishment behaviors: Fact or fiction?
Organizational behavior and human performance, 34(1), 21-63.
Porter, C. O., Webb, J. W., & Gogus, C. I. (2010). When goal orientations collide: Effects of
learning and performance orientation on team adaptability in response to workload
imbalance. Journal of Applied Psychology, 95(5), 935.
Rai, R. S., & Selnes, F. (2019). Conceptualizing task-technology fit and the effect on
adoption–A case study of a digital textbook service. Information & Management,
56(8), 103161.
Raman, P., Wittmann, C. M., & Rauseo, N. A. (2006). Leveraging CRM for sales: the role of
organizational capabilities in successful CRM implementation. Journal of Personal
Selling & Sales Management, 26(1), 39-53.
Ramadan, Z. B., Abosag, I., & Zabkar, V. (2018). All in the value. European Journal of
Marketing, 52(7/8), 1704-1726. https://doi.org/10.1108/EJM-03-2017-0189
Reinig, B. A. (2003). Toward an understanding of satisfaction with the process and outcomes
of teamwork. Journal of Management Information Systems, 19(4), 65-83. 57

Schmidt, H. K., Rothgangel, M., & Grube, D. (2015). Prior knowledge in recalling arguments in bioethical dilemmas. Frontiers in psychology, 6, 1292.
Seeber, I., De Vreede, G.-J., Maier, R., & Weber, B. (2017). Beyond brainstorming: Exploring convergence in teams. Journal of Management Information Systems, 34(4), 939-969.
Seppälä, P., Mauno, S., Feldt, T., Hakanen, J., Kinnunen, U., Tolvanen, A., & Schaufeli, W. (2009). The construct validity of the Utrecht Work Engagement Scale: Multisample and longitudinal evidence. Journal of Happiness studies, 10(4), 459-481.
Sinha, A. P., & Vessey, I. (1992). Cognitive fit: an empirical study of recursion and iteration. IEEE Transactions on Software Engineering, 18(5), 368.
Staples, D. S., Hulland, J. S., & Higgins, C. A. (1999). A self-efficacy theory explanation for the management of remote workers in virtual organizations. Organization Science, 10(6), 758-776.
Stock, G. N., & Tatikonda, M. V. (2004). External technology integration in product and process development. International Journal of Operations & Production Management.
Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive science, 12(2), 257-285.
Sweller, J. (1994). Cognitive load theory, learning difficulty, and instructional design. Learning and instruction, 4(4), 295-312.
Sweller, J., Ayres, P. L., Kalyuga, S., & Chandler, P. (2003). The expertise reversal effect. Sweller, J., & Chandler, P. (1994). Why some material is difficult to learn. Cognition and
instruction, 12(3), 185-233.
Sweller, J., Van Merrienboer, J. J., & Paas, F. G. (1998). Cognitive architecture and
instructional design. Educational psychology review, 10(3), 251-296.
Teo, T. S., & Men, B. (2008). Knowledge portals in Chinese consulting firms: a task–
58

technology fit perspective. European Journal of Information Systems, 17(6), 557-574. Valcke, M. (2002). Cognitive load: updating the theory? Learning and instruction, 12(1),
147-154.
Vessey, I., & Galletta, D. (1991). Cognitive fit: An empirical study of information
acquisition. Information systems research, 2(1), 63-84.
Vijayasarathy, L. R., & Irwin Casterella, G. (2016). The effects of information request
language and template usage on query formulation. Journal of the Association for
Information Systems, 17(10), 2.
Wang, Q., Yang, S., Liu, M., Cao, Z., & Ma, Q. (2014). An eye-tracking study of website
complexity from cognitive load perspective. Decision support systems, 62, 1-10. Warkentin, M., & Beranek, P. M. (1999). Training to improve virtual team communication.
Information systems journal, 9(4), 271-289.
Xu, J. D. (2016). Retaining customers by utilizing technology-facilitated chat: Mitigating
website anxiety and task complexity. Information & Management, 53(5), 554-569. Xu, K. M., Koorn, P., De Koning, B., Skuballa, I. T., Lin, L., Henderikx, M., Marsh, H. W.,
Sweller, J., & Paas, F. (2021). A growth mindset lowers perceived cognitive load and improves learning: Integrating motivation to cognitive load. Journal of Educational Psychology, 113(6), 1177.
Xu, K. M., Koorn, P., De Koning, B., Skuballa, I. T., Lin, L., Henderikx, M., Marsh, H. W., Sweller, J., & Paas, F. (2021). A growth mindset lowers perceived cognitive load and improves learning: Integrating motivation to cognitive load. Journal of Educational Psychology, 113(6), 1177.
Zhu, B., & Watts, S. A. (2010). Visualization of network concepts: The impact of working memory capacity differences. Information systems research, 21(2), 327-344.
Chang, T.(2021)。 2021 台灣企業數位轉型報告, Goolge。 檢自
https://www.thinkwithgoogle.com/intl/zh-tw/future-of-marketing/digital-
59

transformation/2021-台灣-企業數位轉型關鍵報告/
電子全文 Fulltext
本電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。
論文使用權限 Thesis access permission:校內校外完全公開 unrestricted
開放時間 Available:
校內 Campus: 已公開 available
校外 Off-campus: 已公開 available


紙本論文 Printed copies
紙本論文的公開資訊在102學年度以後相對較為完整。如果需要查詢101學年度以前的紙本論文公開資訊,請聯繫圖資處紙本論文服務櫃台。如有不便之處敬請見諒。
開放時間 available 已公開 available

QR Code