بررسی نقش توانمندسازها برای دستیابی به چابکی سازمانی با استفاده از رگرسیون چندگانه
محورهای موضوعی : مدیریت و توسعه پایدار
رضا احتشام راثی
1
(دانشیار، گروه مدیریت صنعتی، واحد قزوین، دانشگاه آزاد اسلامی، قزوین، ایران.)
امید مهری نمک آورانی
2
(دانشجوی دکتری حسابداری، گروه حسابداری، واحد قزوین، دانشگاه آزاد اسلامی، قزوین، ایران.)
کلید واژه: چابکی سازمانی, چابکی, رگرسیون چندگانه, توانمندسازها, قابلیت‌های چابکی,
چکیده مقاله :
پژوهش حاضر در صدد بررسی نقش توانمندسازهای چابکی برای دستیابی به چابکی در شرکت لبنیات پگاه تهران با استفاده از رگرسیون چندگانه می‌باشد. در این پژوهش برای دستیابی به سطح ایده آل چابکی و برای تحلیل اثر شاخص‌ها و همچنین ارائه مسیری بهینه برای دستیابی به چابکی از مدل رگرسیون استفاده شده است. به این منظور 96 پرسش‌نامه بین مدیران شرکت لبنیات پگاه تهران توزیع شد و آزمون‌های پژوهش حاضر به کمک نرم افزارهای SPSS و Smart-PLS انجام شده است. آزمون‌های روایی استفاده شده در این پژوهش آزمون متوسط واریانس استخراجی و آزمون لاوشه می‌باشد که ضرایب آن‌ها برای متغیرهای پژوهش به ترتیب بیش از 5/0 و 8/0 می‌باشد. در واقع، ضرایب حاصل، بیانگر این است که پرسش‌نامه مورد بررسی دارای اعتبار کافی است. برای سنجش پایایی پرسش‌نامه نیز از آزمون آلفای کرونباخ استفاده شده است که ضریب آن برای تمامی ابعاد پرسش‌نامه بیش از 7/0 می‌باشد که بیانگر قابل اعتماد بودن پرسش‌نامه می‌باشد. نتایج نشان داد که بیشترین تاثیر را به ترتیب متغیرهای اتوماسیون و کارکنان داشته و کمترین اثر را متغیر فناوری داشته است. همچنین برای آنکه بتوانیم به سطح قابل قبولی از هر یک از ابعاد قابلیت‌های چابکی دست پیدا کنیم باید متغیر یا متغیرهای کلیدی که از تحلیل‌های این پژوهش استخراج شده‌اند را شناسایی و با تغییراتی در آن‌ها به نتایج مطلوب دست پیدا کنیم. در این صورت می‌توانیم با حداقل زمان و هزینه به حداکثر کارایی و ارتقاء سطح چابکی دست یابیم.
The current study is aimed at investigating the role of agile enablers to achieve agility in Pegah Tehran Dairy Co. using multiple regression. In this study, a regression model was employed to achieve the ideal agility level, as well as analyze the effect of indicators and provide an optimal path to achieve agility. To this end, 96 questionnaires were distributed among the managers of Pegah Tehran Dairy Co., and the research tests were carried out by means of SPSS and Smart PLS software. The validity tests used in this research were average variance extracted (AVE) and the Lawshe test, respectively, with coefficients more than 0.5 and 0.8 for research variables. In fact, the resulting coefficients indicate the sufficient validity of the investigated questionnaire. Moreover, Cronbach’s alpha test was utilized to measure its reliability, with a coefficient of more than 0.7 for all dimensions of the questionnaire, exhibiting its reliability. The results revealed that the variables of automation and employees had the most effect, and the technology variable had the least one. Besides, to achieve an acceptable level of each of the dimensions of agility attributes, the key variable(s) extracted from the analysis of this research should be identified, and the desired results would be achieved by making changes to them. In this case, maximum efficiency can be achieved, and the agility level can be improved with minimum time and cost.
Abbasian, S., Yousefi, B., Zardoshtian, S., & Eydi, H. (2018). The Effect of Organizational Agility on Performance of Employees with the Intermediate role of Intellectual Capital (Case Study: Staff of Sports and Youth Departments of West Provinces of Iran). Scientific Journal Of Organizational Behavior Management in Sport Studies, 5(3), 91-104. (In Persian)
Ashrafi, A., Ravasan, A. Z., Tarkma, P., & Afshari, S. (2019). The role of business analytics capabilities in bolstering firms’ agility and performance International journal of information management, 47, 1-15.
Bustelo, V., D., Avella, L., & Fernández, E. (2007). Agility drivers, enablers and outcomes: empirical test of an integrated agile manufacturing model. International Journal of Operations & Production Management, 27(12), 1303-1332.
Chen, W. H., & Chiang, A. H. (2011). Network agility as a trigger for enhancing firm performance: a case study of a high-tech firm implementing the mixed channel strategy. Industrial Marketing Management, 40(4), 43-51.
Dahmardeh, N., & Pourshahabi, V. (2011). Agility evaluation in public sector using fuzzy logic. Iranian Journal of Fuzzy Systems, 8(3), 95-111. https://doi.org/10.22111/ijfs.2011.289
Esmaelian, M., & Molavi, B. (2014). Prioritization and Selection Agility Capability Using Fuzzy TOPSIS and Fuzzy DEA Approach. Journal of Production and Operations Management, 5(2), 145-160. (In Persian)
Gunasekaran, A. (1998). Agile Manufacturing: enablers and in implementation framework. International Journal of Production Research, 36(5), 1247-1223.
Hamidi, N., Hasanpour, A., Kiaei, M., & Mousavi, S. (2009). The role of human resources management in organizational agility. J Manag Syst 8, 111–128 (In Persian)
Heeager, L. T. (2012). Introducing agile practices in a documentation-driven software development practice: A case study. Journal of Information Technology Case and Application Research, 14, 3–24.
Hornby, A. S. (2000). Oxford advanced learner’s dictionary of current English (6 ed.). oxford university press.
Karbasian, M., Khayambashi, B., Nilipour, A., & Javanmardi, M. (2014). Identification and ranking of fuzzy AHP method of enablers agility industry segment group. J Manag Syst 29, 39–54. (In Persian)
Karre, H., Hammer, M., & Ramsauer, C. (2019). Building capabilities for agility in a learning factory setting. Procedia Manufacturing, 31, 60-65.
Mahdeyan, A., Forozandeh Dehkordi, L., Mir Hosseini Zavareh, M., & Hamidi Zadeh, M. (2013). Assessment indicators and strategies for agility, alignment and right sizing of the administrative structure of the country. Strateg Vis, 1(4), 150–187. (In Persian)
McCullen, P., & Towill, D. (2001). Achieving lean supply through agile manufacturing. Integrated Manufacturing Systems, 12(7), 524-533
Patanakul, P., & McCarron, R. R. (2018). Transitioning to agile software development: Lessons learned from a government-contracted program. Journal of High Technology Management Research, 29(2), 1-12.
Ren, J., Yusuf, Y. Y., & Burns, D. (2003). The effects of agile attributes on competitive priorities: a neural network approach. Integrated Manufacturing Systems, 14(6), 489-497.
Richter, J., & Basten, D. (2013). How do service-oriented architectures influence organizational agility? Proceedings of the Nineteenth Americas Conference on Information Systems, Chicago, Illinois.
Seyedhosseini, S., Rajabzade Ghatari, A., Alborzi, M., Razavi, S., & Ramezni, A. (2012). Identify and Rank the Factors Affecting the Formation of the Agility Capabilities (Case study: The Automobile Trading Companies). Industrial Management Journal, 4(1), 15-36. (In Persian)
Shoul, A., & Sadeghi, S. (2017). Presenting an interpretive structural modeling approach of agility criteria (Case Study: Fajr Jam Gas Refinery). J Manag Syst, 40, 63–80. (In Persian)
Shukla, S., K., & Sushil, A. (2020). Evaluating the Practices of Flexibility Maturity for the Software Product and Service of Organizations. International journal of information management, 50, 71-89.
Tseng, Y.-H., & Lin, C.-T. (2011). Enhancing enterprise agility by deploying agile drivers, capabilities and providers. Information Sciences, 181(17), 3693-3708.
Zhou, J., Mavondo, F. T., & Saunders, S. G. (2018). The relationship between marketing agility and financial performance under different levels of market turbulence. Industrial Marketing Management, 1-11.
_||_Abbasian, S., Yousefi, B., Zardoshtian, S., & Eydi, H. (2018). The Effect of Organizational Agility on Performance of Employees with the Intermediate role of Intellectual Capital (Case Study: Staff of Sports and Youth Departments of West Provinces of Iran). Scientific Journal Of Organizational Behavior Management in Sport Studies, 5(3), 91-104. (In Persian)
Ashrafi, A., Ravasan, A. Z., Tarkma, P., & Afshari, S. (2019). The role of business analytics capabilities in bolstering firms’ agility and performance International journal of information management, 47, 1-15.
Bustelo, V., D., Avella, L., & Fernández, E. (2007). Agility drivers, enablers and outcomes: empirical test of an integrated agile manufacturing model. International Journal of Operations & Production Management, 27(12), 1303-1332.
Chen, W. H., & Chiang, A. H. (2011). Network agility as a trigger for enhancing firm performance: a case study of a high-tech firm implementing the mixed channel strategy. Industrial Marketing Management, 40(4), 43-51.
Dahmardeh, N., & Pourshahabi, V. (2011). Agility evaluation in public sector using fuzzy logic. Iranian Journal of Fuzzy Systems, 8(3), 95-111. https://doi.org/10.22111/ijfs.2011.289
Esmaelian, M., & Molavi, B. (2014). Prioritization and Selection Agility Capability Using Fuzzy TOPSIS and Fuzzy DEA Approach. Journal of Production and Operations Management, 5(2), 145-160. (In Persian)
Gunasekaran, A. (1998). Agile Manufacturing: enablers and in implementation framework. International Journal of Production Research, 36(5), 1247-1223.
Hamidi, N., Hasanpour, A., Kiaei, M., & Mousavi, S. (2009). The role of human resources management in organizational agility. J Manag Syst 8, 111–128 (In Persian)
Heeager, L. T. (2012). Introducing agile practices in a documentation-driven software development practice: A case study. Journal of Information Technology Case and Application Research, 14, 3–24.
Hornby, A. S. (2000). Oxford advanced learner’s dictionary of current English (6 ed.). oxford university press.
Karbasian, M., Khayambashi, B., Nilipour, A., & Javanmardi, M. (2014). Identification and ranking of fuzzy AHP method of enablers agility industry segment group. J Manag Syst 29, 39–54. (In Persian)
Karre, H., Hammer, M., & Ramsauer, C. (2019). Building capabilities for agility in a learning factory setting. Procedia Manufacturing, 31, 60-65.
Mahdeyan, A., Forozandeh Dehkordi, L., Mir Hosseini Zavareh, M., & Hamidi Zadeh, M. (2013). Assessment indicators and strategies for agility, alignment and right sizing of the administrative structure of the country. Strateg Vis, 1(4), 150–187. (In Persian)
McCullen, P., & Towill, D. (2001). Achieving lean supply through agile manufacturing. Integrated Manufacturing Systems, 12(7), 524-533
Patanakul, P., & McCarron, R. R. (2018). Transitioning to agile software development: Lessons learned from a government-contracted program. Journal of High Technology Management Research, 29(2), 1-12.
Ren, J., Yusuf, Y. Y., & Burns, D. (2003). The effects of agile attributes on competitive priorities: a neural network approach. Integrated Manufacturing Systems, 14(6), 489-497.
Richter, J., & Basten, D. (2013). How do service-oriented architectures influence organizational agility? Proceedings of the Nineteenth Americas Conference on Information Systems, Chicago, Illinois.
Seyedhosseini, S., Rajabzade Ghatari, A., Alborzi, M., Razavi, S., & Ramezni, A. (2012). Identify and Rank the Factors Affecting the Formation of the Agility Capabilities (Case study: The Automobile Trading Companies). Industrial Management Journal, 4(1), 15-36. (In Persian)
Shoul, A., & Sadeghi, S. (2017). Presenting an interpretive structural modeling approach of agility criteria (Case Study: Fajr Jam Gas Refinery). J Manag Syst, 40, 63–80. (In Persian)
Shukla, S., K., & Sushil, A. (2020). Evaluating the Practices of Flexibility Maturity for the Software Product and Service of Organizations. International journal of information management, 50, 71-89.
Tseng, Y.-H., & Lin, C.-T. (2011). Enhancing enterprise agility by deploying agile drivers, capabilities and providers. Information Sciences, 181(17), 3693-3708.
Zhou, J., Mavondo, F. T., & Saunders, S. G. (2018). The relationship between marketing agility and financial performance under different levels of market turbulence. Industrial Marketing Management, 1-11.