製造執行系統(Manufacturing Execution System, MES)在整合度高的現代製造業自動化工廠裡擁有非常重要的地位，因為其扮演了銜接企業和工廠的核心角色，所有工廠的資訊都透過這個系統傳遞給企業管理階層以支援決策，而管理階層的指示也藉由此系統傳達給工廠。
目前所見大部分對製造執行系統的討論都是以企業整體或生產作業為考量觀點，然而一個資訊系統存在的價值是在於其使用的價值，使用者才是資訊系統能否有效發揮其功能的關鍵。而製造執行系統涵蓋的使用者階層很廣，唯有能夠支援所有使用者才能成功的完全發揮製造執行系統的價值與效益，並使得所有使用者都滿意。
因此本研究旨在以資訊系統使用領域廣受肯定，並且不論是在學術研究或管理實務方面都極具解釋能力的科技接受度模型(Technology Acceptance Model, TAM)、任務與科技配適度模型(Task-Technology Fit model, TTF)和使用者滿意度等研究方法為基礎，來發展出適合本研究議題之研究模型，以期透過使用者的角度來瞭解製造執行系統的使用者接受度和滿意度。
本研究發放問卷之對象為台灣在全球居於產業領導地位之某高科技大廠員工，而研究結果發現，感受有用性和感受易用性對使用者滿意度有較強的影響效用，顯示對於製造執行系統這樣一個龐大的現場控制系統之使用者而言，使用者對系統的感受有用性和感受易用性會比系統的任務與科技配適度來得重要，因此在系統設計與支援方面，應該著重在其對使用者而言是否容易操作以及能否實質提升使用者對達成工作目標的管控。

The manufacturing execution system possesses a very important status in the modern manufacturing industry because it acts a core role to engage enterprise and the factory. Information from the factory via this system is to support the decision-making for the business manager, and the instructions from them also go through by the system.
At present, the discussion about the information system is all about the enterprise or the production work and the relative technology aspect. However, an information system’s truly value lies in its use, and the user is the key to effectively perform the system function. The range of users for the system is quite broad and only if the system supports all its user can it successfully display its true value.
Our research model is based on widely used technology acceptance model and task-technology fit model to figure out the user acceptance and satisfaction for the manufacturing execution system. Data were collected from a leading enterprise in the world, and the findings discovered that the perceived usefulness and the perceived ease of use have the strong effect on the user satisfaction. It also shows that such a huge scene control system as manufacturing execution system, the perceived usefulness and perceived ease of use about the system is much important than the task-technology fit of the system. Therefore, one should emphasize on whether it is easy to operate and can promote the job control for the users on the system design and the support aspect.

中文部分
山口俊之 著，林怡君 譯(2000)。工作支援與資訊系統的關聯─電腦化現場管理。台北市：中衛發展中心。
卜運忠(2002)。生產新利器-MES系統的實戰成果。工業自動化電子化，8，35-37。
吳德常(2002)。工廠營運管制系統的真義。工業自動化電子化，8，27-30。
吳紹穎(2002)。建置提升整體生產體質的MES系統。工業自動化電子化，8，31-34。
陳姿君(2005)。MES是正新輪胎的資訊中樞神經。工業自動化電子化，11，8-11。
陳順宇(2004)。多變量分析。台北市：華泰書局。
陳順宇(2007)。結構方程模式。台北市：心理出版社。
王立志(2006)。系統化運籌與供應鏈管理-企業營運新典範。臺中市：滄海書局。

英文部分
Adams, D. A., Nelson, R. R., & Todd, P. A. (1992). Perceived Usefulness, Ease of Use, and Usage of Information Technology: A Replication. MIS Quarterly, 16(2), 227-247.
Alder, D. J., Herkamp, J., Henricks, D., & Moss, R. (1995). Does a Manufacuring Execution System reduce the cost of production for bulk pharmaceuticals? ISA Transactions, 34(4), 343-347.
Amoako-Gyampah, K., & Salam, A. F. (2004). An extension of the technology acceptance model in an ERP implementation environment. Information & Management, 41(6), 731-745.
Bailey, J. E., & Pearson, S. W. (1983). Development of a tool for measuring and analyzing computer user satisfaction. Management Science, 29(5), 530–545.
Bhattacherjee, A. (2001). Understanding Information Systems Continuace: An Expectation-Confirmation Model. MIS Quarterly, 25(3), 351-370.
Benbasat, I., Dexter, A. S., & Todd, P. (1986). An Experimental Program Investigating Color-Enhanced and Graphical Information Presentation: An Integration of the Findings. Communications of the ACM, 29(11), 1094-1105.
Chakraborty, S., & Tah, D. (2006). Real time statistical process advisor for effective quality control. Decision Support Systems, 42(2), 700–711.
Chen, L. -d., Gillenson, M. L., & Sherrell, D. L. (2002). Enticing online consumers: an extended technology acceptance perspective. Information & Management, 39(8), 705-719.
Cooper, R. B., & Zmud, R. W. (1990). Information Technology Implementation Research: A Technological Diffusion Approach. Management Science, 36(2), 123-139.
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technologie. MIS Quarterly, 13(3), 319–340.
Davis, F. D. (1993). User acceptance of information technology: system characteristics, user perceptions, and behavioral impacts. International Journal of Man-Machine Studies, 38(3), 475–487.
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.
DeLone, W. H., & McLean, E. R. (1992). Information Systems Success: The Quest for the Dependent Variable. Information Systems Research, 3(1), 60-95.
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.
Dishaw, M. T., & Strong, D. M. (1999). Extending the technology acceptance model with task-technology fit constructs. Information & Management, 36(1), 9-21.
Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention and Behavior：Introduction to Theory and Research. MA: Addison-Wesley.
Gelderman, M. (1998). The relation between user satisfaction, usage of information systems and performance. Information & Management, 34(1), 11-18.
Goodhue, D. L. (1995). Understanding User Evaluations of Information Systems. Management Science, 41(12), 1827-1844.
Goodhue, D. (1997). The Model Underlying the Measurement of the Impacts of the IIC on the End-Users. Journal of the American Society for Information Science, 48(5), 449-453.
Goodhue, D. L. (1998). Development and Measurement Validity of a Task-Technology Fit Instrument for User Evaluations of Information Systems. Decision Sciences, 29(1), 105-138.
Goodhue, D. L., & Thompson, R. L. (1995). Task-Technology Fit and Individual Performance. MIS Quarterly, 19(2), 213-236.
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (2006). Multivariate Data
Analysis. New Jersey: Pearson Education.
Harrington, J. (1973). Computer Integrated Manufacturing. New York: Industrial Press, Inc.
Hu, J., Chau, Y. K., Liu, R., & Tam, K. Y. (1999). Examining the Technology Acceptance Model Using Physician Acceptance of Telemedicine Technology. Journal of Management Information Systems, 16(2), 91–112.
Igbaria, M., & Tan, M. (1997). The consequences of information technology acceptance on subsequent individual performance. Information & Management, 32(3), 113-121.
Igbaria, M., Zinatelli, N., Cragg, P., & Cavaye, A. (1997). Personal Computing Acceptance Factors in Small Firms: A Structural Equation Model. MIS Quarterly, 21(3), 279–305.
ISA. (1995). ANSI/ISA-88.01-1995, Batch Control Part 1: Models and Terminology. Retrieved from
http://www.isa.org/Content/Microsites165/SP18,_Instrument_Signals_and_Alarms/Home163/ISA_Standards_for_Committee_Use/S_8801.PDF
Ives, B., Olson, M., & Baroudi, J. (1983). The Measurement of User Information Satisfaction. Communications of the ACM, 26(10), 785-793.
Karahanna, E., & Straub, D. W. (1999). The psychological origins of perceived usefulness and ease-of-use. Information & Management, 35(4), 237-250.
Klopping, I. M., & Mckinney, E. (2004). Extending the Technology Acceptance Model and the Task-Technology Fit Model to Consumer E-Commerce. Information Technology, Learning, and Performance Journal, 22(1), 35-48.
Konradt, U., Christophersen, T., & Schaeffer-Kuelz, U. (2006). Predicting user satisfaction, strain and system usage of employee self-services. International Journal of Human-Computer Studies, 64(11), 1141–1153.
Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information & Management, 40(3), 191-204.
Liu, L., & Ma, Q. (2005). The impact of service level on the acceptance of application service oriented medical records. Information & Management, 42(8), 1121-1135.
Mathieson, K., & Keil, M. (1998). Beyond the interface: Ease of use and task/technology fit. Information & Management, 34(4), 221-230.
McClellan, M. (1997). Applying manufacturing execution systems. Boca Raton, Florida: St. Lucie Press.
MESA International. (1997a). MESA White Paper #06: MES Explained: A High Level Vision for Executives. Retrieved from
https://services.mesa.org/ResourceLibrary/ShowResource/334444c5-388f-4360-beb4-3c86dc0f4de4
MESA International. (1997b). MESA White Paper #05: Execution-Driven Manufacturing Management for Competitive Advantage. Retrieved from
https://services.mesa.org/ResourceLibrary/ShowResource/d92d377a-3a5f-4fee-b093-673a6c640b77
MESA International. (1997c). MESA White Paper #02: MES Functionalities and MRP to MES Data Flow Possibilities. Retrieved from
https://services.mesa.org/ResourceLibrary/ShowResource/2cedfe75-daed-4b9c-b187-f421cf90fdd2
Miller, J., & Doyle, B. A. (1987). Measuring the Effectiveness of Computer-Based Information Systems in the Financial Services Sector. MIS Quarterly, 11(1), 107-124.
Morris, M. G., & Dillon, A. (1997). How User Perceptions Influence Software Use. IEEE Software, 14(4), 58-65.
Neuman, W. L. (2000). Social research methods: qualitative and quantitative approaches. MA: Allyn and Bacon Needham Heights.
Pagani, M. (2006). Determinants of adoption of High Speed Data Services in the business market: Evidence for a combined technology acceptance model with task technology fit model. Information & Management, 43(7), 847-860.
Robbins, S. P. (1994). Management. Englewood Cliffs, N. J.: Prentice Hall.
Schumann, A. (1997). SAP-R/3 in process industries: expectations, experiences and outlooks. ISA Transactions, 36(3), 161-166.
Snoeij, J., & Visser, R. (2004). MES Product Survey. Retrieved from
https://services.mesa.org/ResourceLibrary/ShowResource/be12bc6d-badc-4365-a4e7-6230ebc5e333
Sun, Y. M., Tsai, C. H., Li, R. K., & Chang, C. L. (2008). Research on Application of Computer Integrated Manufacturing System for Semiconductor Equipment Management. Proceedings of 2008 MIICS Mechatronic and Industry Interact Cross Strait Conference, Novenber 12, Hsinchu, Taiwan.
Tjahjono, B. (2009). Supporting shop floor workers with a multimedia task-oriented information system. Computers in Industry, 60(4), 257–265.
van der Heijden, H. (2003). Factors influencing the usage of websites: the case of a generic portal in The Netherlands. Information & Management, 40(6), 541–549.
Venkatesh, V., & Davis, F. D. (1996). A Model of the Antecedents of Perceived Ease of Use: Development and Test. Decision Sciences, 27(3), 451-481.
Venkatesh, V., & Davis, F. D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46(2), 186-204.
Vessey, I. (1991). Cognitive Fit: A Theory-Based Analysis of the Graphs Versus Tables Literature. Decision Sciences, 22(2), 219-240.
Vessey, I., & Galleta, D. (1991). Cognitive Fit: An Empirical Study of Information Acquisition. Information Systems Research, 2(1), 63-84.
Wang, T. Y., & Pan, H. C. (2008). Integrating OEE into cost model for semiconductor assembly and testing industry. IEEE Transactions on Electronics Packaging Manufacturing, accepted.
Weygandt, S. (1996). Getting the MES model—methods for system analysis. ISA Transactions, 35(2), 95-103.
Woodroof, J., & Burg, W. (2003). Satisfaction/dissatisfaction: are users predisposed? Information & Management, 40(4), 317-324.
Young, S. L. (1995). Technology…The enabler for tomorrow’s agile enterprise. ISA Transactions, 34(4), 335-341.
Zhang, D. Z., Anosike, A. I., Lim, M. K., & Akanle, O. M. (2006). An agent-based approach for e-manufacturing and supply chain integration. Computers & Industrial Engineering, 51(2), 343–360.

參考網站
http://www.mesa.org/
http://www.isa-95.com/
http://www.ninety-five.com/