انعطاف‌پذیری زنجیره تأمین و ارتباط آن با عملکرد در شرکت‌های تولیدی(مورد مطالعه: صنعت پوشاک)
محورهای موضوعی :
مدیریت صنعتی
Morteza Abbasi
1
(
Assistance Professor, Malek Ashtar University of Technology
)
Jafar Gheidar-Kheljani
2
(
Assistance Professor, Malek Ashtar University of Technology
)
Reza Aghasi
3
(
M.S. Industrial Engineering, Malek Ashtar University of Technology
)
تاریخ دریافت : 1394/11/11
تاریخ پذیرش : 1395/04/28
تاریخ انتشار : 1395/06/04
کلید واژه:
Supply Chain,
performance,
عملکرد,
Flexibility,
معادلات ساختاری,
انعطاف‌پذیری,
زنجیره تأمین,
structural equation modeling,
چکیده مقاله :
محیط کسب‌وکار کنونی به‌شدت نامطمئن و غیرقابل‌پیش‌بینی شده است، سازمان‌ها برای مواجه با این عدم قطعیت‌ها باید سیستم‌های انعطاف‌پذیری داشته باشند. برای دست‌یابی به این هدف، انعطاف‌پذیری زنجیره تأمین از اهمیت زیادی برخوردار است. هدف این مقاله مطالعه تجربی ارتباط بین انعطاف‌پذیری زنجیره تأمین و عملکرد شرکت‌های فعال صنعت پوشاک در تهران و حومه است.اطلاعات اولیه با استفاده از پرسشنامه جمع‌آوری شده و سپس به کمک مدل‌سازی معادلات ساختاری در دو بخش مدل اندازه‌گیری و ساختاری مورد تجزیه‌وتحلیل قرار گرفته است. انعطاف‌پذیری زنجیره تأمین شامل ابعاد منبع یابی، عملیات، اطلاعات، توزیع و منابع انسانی است. نتایج پژوهش نشان می‌دهد که انعطاف‌پذیری منبع یابی، اطلاعات و توزیع، تأثیر مثبت و معنادار بر عملکرد دارند درحالی‌که انعطاف‌پذیری عملیات و منابع انسانی، تأثیر مثبت ولی ناچیز بر عملکرد دارند.
چکیده انگلیسی:
The business environment has now become uncertain and unpredictable. It is needed to have flexible systems to face with these uncertainties. The flexibility of supply chain is important to reach this objective. The purpose of this article is an empirical study of the relationship between supply chain flexibility (SCF) and firm’s performance in Tehran’s clothing industry. The Initial data are collected from experts were asked to fill in a questionnaire and then analyzed by structural equation modeling (SEM) method in two section: measurement model and structural model. Supply chain flexibility dimensions are sourcing flexibility, operation system flexibility, information system flexibility, distribution flexibility and human resource flexibility. The results show sourcing, information system, and distribution flexibility have a positive and significant impact on performance, while operation system and human resource flexibility have a positive and insignificant impact on performance.
منابع و مأخذ:
Barclay,D., Higgins, C., & Thompson, R. (1995). The partial least squares (PLS) approach to causal modeling: Personal Computer Use as an Illustration. Technology studies, 2(2), 285-309.
Bhattacharya, M., Gibson, D. E., & Doty, D. H. (2005). The effects of flexibility in employee skills, employee behaviors, and human resource practices on firm performance. Journal of Management, 31(4), 622-640.
Calantone, R., & Dröge, C. (1999). Supply chain flexibility: an empirical study. Journal of Supply Chain Management, 35(2), 16-24.
Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern methods for business research, 295(2), 295-336.
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. psychometrical, 16(3), 297-334.
Davari, A; Reza Zadeh, A. (2013). Modeling structural equation with PLS. Tehran: Jahad collegiate press.
Dess, G. G., & Beard, D. W. (1984). Dimensions of organizational task environments. Administrative science quarterly, 52-73.
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Fredericks, E. (2005). Infusing flexibility into business-to-business firms: A contingency theory and resource-based view perspective and practical implications. Industrial Marketing Management, 34(6), 555-565.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 39-50.
Gupta, Y. P., & Somers, T. M. (1992). The measurement of manufacturing flexibility. European Journal of Operational Research, 60(2), 166-182.
Hatum, A., & Pettigrew, A. M. (2006). Determinants of organizational flexibility: a study in an emerging economy. British journal of management, 17(2), 115-137.
Hulland, J., & Richard Ivey School of Business. (1999). Use of partial least squares (PLS) in strategic management research: A review of four recent studies. Strategic management journal, 20(2), 195-204.
Koste, L. L., Malhotra, M. K., & Sharma, S. (2004). Measuring dimensions of manufacturing flexibility. Journal of Operations Management, 22(2), 171-196.
Kumar, P., Shankar, R., & Yadav, S. S. (2008). Flexibility in global supply chain: modeling the enablers. Journal of Modelling in Management, 3(3), 277-297.
Lee, H.L. (2000). Creating value through supply chain integration. Supply Chain Management Review, 4 (4), 30–36.
Lee, H. L., & Whang, S. (2000). Information sharing in a supply chain. International Journal of Manufacturing Technology and Management, 1(1), 79-93.
Lin, F. R., & Shaw, M. J. (1998). Reengineering the order fulfillment process in supply chain networks. International Journal of Flexible Manufacturing Systems, 10(3), 197-229.
Lummus, R. R., Duclos, L. K., & Vokurka, R. J. (2003). Supply chain flexibility: building a new model. Global Journal of Flexible Systems Management, 4(4), 1.
Martínez Sánchez, A., & Pérez Pérez, M. (2005). Supply chain flexibility and firm performance: a conceptual model and empirical study in the automotive industry. International Journal of Operations & Production Management, 25(7), 681-700.
Merschmann, U., & Thonemann, U. W. (2011). Supply chain flexibility, uncertainty and firm performance: an empirical analysis of German manufacturing firms. International Journal of Production Economics, 130(1), 43-53.
Moon, K. K. L., Yi, C. Y., & Ngai, E. W. T. (2012). An instrument for measuring supply chain flexibility for the textile and clothing companies. European Journal of Operational Research, 222(2), 191-203.
Nunally, Jum C. (1978). Psychometric theory, 2nd Edn. New York: McGraw-Hill.
Pagell, M., & Krause, D. R. (1999). A multiple-method study of environmental uncertainty and manufacturing flexibility. Journal of Operations Management, 17(3), 307-325.
Rice, J. B., & Hoppe, R. M. (2001). Supply chain vs. supply chain: the hype and the reality. Supply chain management review, 5(5), 46-54.
Rivard, S., & Huff, S. L. (1988). Factors of success for end-user computing. Communications of the ACM, 31(5), 552-561.
Sarmad Z., Hejazi E., Bazargan A., (2016). Research methods in behavioral science. Tehran: Agah Publication.
Sawhney, R. (2006). Interplay between uncertainty and flexibility across the value-chain: towards a transformation model of manufacturing flexibility. Journal of Operations Management, 24(5), 476-493.
Sethi, A. K., & Sethi, S. P. (1990). Flexibility in manufacturing: a survey. International journal of flexible manufacturing systems, 2(4), 289-328.
Stevenson, M., & Spring, M. (2007). Flexibility from a supply chain perspective: definition and review. International Journal of Operations & Production Management, 27(7), 685-713.
Swafford, P. M., Ghosh, S., & Murthy, N. (2006). The antecedents of supply chain agility of a firm: scale development and model testing. Journal of Operations Management, 24(2), 170-188.
Tachizawa, E. M., & Gimenez, C. (2009). Assessing the effectiveness of supply flexibility sources: An empirical research. International Journal of Production Research, 47(20), 5791-5809.
Tenenhaus, M., Amato, S., & Esposito Vinzi, V. (2004, June). A global goodness-of-fit index for PLS structural equation modelling. In Proceedings of the XLII SIS scientific meeting (Vol. 1, pp. 739-742).
Werts, C. E., Linn, R. L., & Jöreskog, K. G. (1974). Intraclass reliability estimates: Testing structural assumptions. Educational and Psychological measurement, 34(1), 25-33.
Wetzels, M., Odekerken-Schröder, G., & Van Oppen, C. (2009). Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS quarterly, 177-195.
Wheelwright, S. C. (2010). Managing new product and process development: text cases. Simon and Schuster.
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Barclay,D., Higgins, C., & Thompson, R. (1995). The partial least squares (PLS) approach to causal modeling: Personal Computer Use as an Illustration. Technology studies, 2(2), 285-309.
Bhattacharya, M., Gibson, D. E., & Doty, D. H. (2005). The effects of flexibility in employee skills, employee behaviors, and human resource practices on firm performance. Journal of Management, 31(4), 622-640.
Calantone, R., & Dröge, C. (1999). Supply chain flexibility: an empirical study. Journal of Supply Chain Management, 35(2), 16-24.
Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern methods for business research, 295(2), 295-336.
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. psychometrical, 16(3), 297-334.
Davari, A; Reza Zadeh, A. (2013). Modeling structural equation with PLS. Tehran: Jahad collegiate press.
Dess, G. G., & Beard, D. W. (1984). Dimensions of organizational task environments. Administrative science quarterly, 52-73.
Duclos, L. K., Vokurka, R. J., & Lummus, R. R. (2003). A conceptual model of supply chain flexibility. Industrial Management & Data Systems, 103(6), 446-456.
Englehardt , C. S. and P. R .Simmons (2002). "Organizational Flexibility for a changing world," Leadership & Organization Developing Journal, Vol. 3/4,NO 23,pp 113-121.
Fredericks, E. (2005). Infusing flexibility into business-to-business firms: A contingency theory and resource-based view perspective and practical implications. Industrial Marketing Management, 34(6), 555-565.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 39-50.
Gupta, Y. P., & Somers, T. M. (1992). The measurement of manufacturing flexibility. European Journal of Operational Research, 60(2), 166-182.
Hatum, A., & Pettigrew, A. M. (2006). Determinants of organizational flexibility: a study in an emerging economy. British journal of management, 17(2), 115-137.
Hulland, J., & Richard Ivey School of Business. (1999). Use of partial least squares (PLS) in strategic management research: A review of four recent studies. Strategic management journal, 20(2), 195-204.
Koste, L. L., Malhotra, M. K., & Sharma, S. (2004). Measuring dimensions of manufacturing flexibility. Journal of Operations Management, 22(2), 171-196.
Kumar, P., Shankar, R., & Yadav, S. S. (2008). Flexibility in global supply chain: modeling the enablers. Journal of Modelling in Management, 3(3), 277-297.
Lee, H.L. (2000). Creating value through supply chain integration. Supply Chain Management Review, 4 (4), 30–36.
Lee, H. L., & Whang, S. (2000). Information sharing in a supply chain. International Journal of Manufacturing Technology and Management, 1(1), 79-93.
Lin, F. R., & Shaw, M. J. (1998). Reengineering the order fulfillment process in supply chain networks. International Journal of Flexible Manufacturing Systems, 10(3), 197-229.
Lummus, R. R., Duclos, L. K., & Vokurka, R. J. (2003). Supply chain flexibility: building a new model. Global Journal of Flexible Systems Management, 4(4), 1.
Martínez Sánchez, A., & Pérez Pérez, M. (2005). Supply chain flexibility and firm performance: a conceptual model and empirical study in the automotive industry. International Journal of Operations & Production Management, 25(7), 681-700.
Merschmann, U., & Thonemann, U. W. (2011). Supply chain flexibility, uncertainty and firm performance: an empirical analysis of German manufacturing firms. International Journal of Production Economics, 130(1), 43-53.
Moon, K. K. L., Yi, C. Y., & Ngai, E. W. T. (2012). An instrument for measuring supply chain flexibility for the textile and clothing companies. European Journal of Operational Research, 222(2), 191-203.
Nunally, Jum C. (1978). Psychometric theory, 2nd Edn. New York: McGraw-Hill.
Pagell, M., & Krause, D. R. (1999). A multiple-method study of environmental uncertainty and manufacturing flexibility. Journal of Operations Management, 17(3), 307-325.
Rice, J. B., & Hoppe, R. M. (2001). Supply chain vs. supply chain: the hype and the reality. Supply chain management review, 5(5), 46-54.
Rivard, S., & Huff, S. L. (1988). Factors of success for end-user computing. Communications of the ACM, 31(5), 552-561.
Sarmad Z., Hejazi E., Bazargan A., (2016). Research methods in behavioral science. Tehran: Agah Publication.
Sawhney, R. (2006). Interplay between uncertainty and flexibility across the value-chain: towards a transformation model of manufacturing flexibility. Journal of Operations Management, 24(5), 476-493.
Sethi, A. K., & Sethi, S. P. (1990). Flexibility in manufacturing: a survey. International journal of flexible manufacturing systems, 2(4), 289-328.
Stevenson, M., & Spring, M. (2007). Flexibility from a supply chain perspective: definition and review. International Journal of Operations & Production Management, 27(7), 685-713.
Swafford, P. M., Ghosh, S., & Murthy, N. (2006). The antecedents of supply chain agility of a firm: scale development and model testing. Journal of Operations Management, 24(2), 170-188.
Tachizawa, E. M., & Gimenez, C. (2009). Assessing the effectiveness of supply flexibility sources: An empirical research. International Journal of Production Research, 47(20), 5791-5809.
Tenenhaus, M., Amato, S., & Esposito Vinzi, V. (2004, June). A global goodness-of-fit index for PLS structural equation modelling. In Proceedings of the XLII SIS scientific meeting (Vol. 1, pp. 739-742).
Werts, C. E., Linn, R. L., & Jöreskog, K. G. (1974). Intraclass reliability estimates: Testing structural assumptions. Educational and Psychological measurement, 34(1), 25-33.
Wetzels, M., Odekerken-Schröder, G., & Van Oppen, C. (2009). Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS quarterly, 177-195.
Wheelwright, S. C. (2010). Managing new product and process development: text cases. Simon and Schuster.
