Management Information Management Speed Management in Manufacturing Industries

Document Type : Review article


1 Malek Ashtar University of Technology

2 Student in MBA at Malek Ashtar University of Technology - Faculty of Management and Industrial Engineering


The concept of speed in today›s volatile market was formed after concepts such as lean manufacturing, mass production, and flexibility, in fact evolving from previous concepts, which were not responsive. In fact, this concept adds momentum to previous concepts. In todays competitive world, it is no longer the competition of the organization with the organization but the suppliers that compete with each other, merging these two concepts together creates the concept of speed in the supply of resources. This study investigates this issue and the impact of information management variable on optimal rate of resource supply. The present study is applied in terms of purpose and descriptive-correlational. The research instrument was a questionnaire with a reliability of 87%. The population and statistical sample were experts in supply chain, management information system and questionnaire tools were distributed among 25 managers of different departments of LISREL software. 5 Used to conduct route analysis with all validity dimensions. Finally, path analysis was used to examine the simultaneous impact of variables, which revealed that information management had no significant effect on the speed of supply. Pearson correlation test showed a significant and positive correlation between all variables.


Ana-Maria, S., Bîzoi, M & Filip, f. (2010 .(Audit for Information Systems Security. Journal of information economic, 48-43.
Christopher, M). 2000). The agile supply chain: Competing in volatile markets. Industrial Marketing Management,44-37.
Christopher, M & Towill , D.(2001). An Integrated Model for The Design of Agile Supply Chains. International Journal of Physical Distribution & Logistics Management, 246-235.
Gunasekaran, A., Patel, C & Tirtiroglu , E.(2001). Performance measure and metrics in supply chain environment. International Journal of Operations & Production Management, 78-71.
Hazen, B., Skipper, J., Boone, C & Hill, R. (2016). Back in business: Operations research in support of big data analytics for operations and supply chain management. Annals of Operations Research, 211-201.
Ivanov, D., Dolgui, A & Sokolov, B. (2019). The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics. International Journal of Production Research, 846-829.
Klein, F., Mello, R., Cordes, A & Hellingrath, B. (2018). Big data for demand forecasting in supply chain management. Paper presented at the The UI Annual Nofoma Conference.
Kwon, S., Jang, S., Lee, J & Kim, S. (2007). Common Defects in Information Management System of Korean Companies. The Journal of Systems & Software, 1638-1631.
Lin, C.-T., Chiu, H & Chu, P.-Y. (2006). Agility index in the supply chain. International Journal of Production Economics, 299-285.
Loukis, E & Spinellis, D. (2001). Information System in the Greek Public Sector. Information Management & Computer Security, 30-21.
Mishra, D., Gunasekaran, A., Papadopoulos, T & Childe, S. (2018). Big Data and supply chain management: a review and bibliometric analysis. Annals of Operations Research, 336-313.
Motadel, M., Toloie-Eshlaghy, A & Halvachi-Zadeh, D. (2011). Assessment of Supply Chain Agility in the Automotive Industry of Tehran. European Journal of Scientific Research, 229-210.
Pal, K. (2019). Quality Assurance Issues for Big Data Applications in Supply Chain Management in Predictive Intelligence Using Big Data and the Internet of Things. IGI Globa.
Power, D., Sohal, A & Rahman, S.‐U. (2001). Critical Success Factors in Agile Supply Chain Management: An Empirical Study. International Journal of Physical Distribution & Logistics Management, 265-247.
Scheibe, K & Blackhurst, J. (2018). Supply chain disruption propagation: a systemic risk and normal accident theory perspective. International Journal of Production Research, 59-43.
Srinivasan, R & Swink, M. (2018). An investigation of visibility and flexibility as complements to supply chain analytics: An organizational information processing theory perspective. Production and Operations Management, 1867-1849.
Swafford, P., Ghosh, S & Murthy, N. (2006). The antecedents of supply chain agility of a firm: Scale development and model Testing. Journal of Operations Management, 188-170.
Tipton, H & Krause. (2003). Information Management Handbook. Boca Raton: CRC Press LCC.
Tiwari, S., Wee, H & Daryanto, Y. (2018). Big data analytics in supply chain management between 2010 and 2016: Insights to industries. Computers & Industrial Engineering,330-319.
van Hoek, R., Harrison, A & Christopher , M. (2001). Measuring agile capabilities in the supply chain. International Journal of Operations & Production Management, 147-126.
الوانی, س. وخسروی, م. (1384). نقش سیستم های اطلاعاتی مدیریت در تصمیم گیری. مطالعات مدیریت بهبود و تحول, 81-98.
قزل, ع., رمضان, م. و زاهدی, م. (1392). ارائه چارچوب مفهومی برای اندازه گیری سرمایه ساختاری در دانشگاه. رشد و فناوری.
صنایعی، علی، فیض پور، محمدعلی، نادری بنی، محمود(1391)،  تاثیر فناوری اطلاعات بر زنجیره ارزش شرکت های نمونه صادراتی ایران، فصلنامه علمی - پژوهشی تحقیقات بازاریابی نوین سال دوم ، شماره چهارم صفحه 43-22.
مطلبی ورکانی, ا., تقی پور, ا. و علی محمدپور, ع. (1396). سیستم اطلاعات مدیریت (Management Information Systems). مدیریت بهرهوری, 61-79.
مولوی, مهران؛ عبدالرحمان ابراهیمی و سیروس عزیزاکرم، ۱۳۹۵، بررسی تاثیر سیستم های اطلاعاتی مدیریت بر بهبود فرآیند تصمیم گیری، فصلنامه مطالعات مهندسی صنایع و مدیریت تولید 2 (1)،
نوری, س., ابراهیمی, م., زاهدی, م. و رمضانی ویشکی, ف. (1386). مطالعه ارزش، رویکردی سریع و مطمئن در راستای ارتقای بهره وری. مدیریت فردا, 113-121.