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عنوان URL للمقالة


رقم المقالة : IMJ-2008-1420 (R1) زيارة : 165 الصفحة: 175 - 196

نوع المخطوط: ابحاث

تاب آوری زنجیره تأمین در حمل ونقل پستی با رویکرد تحلیل عاملی

الموضوعات :

Mansour Jangizehi 1 , Mohammad Reza Maleki 2

1 - PhD candidate in Industrial Engineering, Eyvanekey University, Semnan, Iran
2 - Department of Industrial Engineering, Golpayegan University of Technology, Golpayegan, Iran

تاريخ الإرسال : 12 الأحد , ذو الحجة, 1441 تاريخ التأكيد : 01 الأربعاء , جمادى الأولى, 1442 تاريخ الإصدار : 09 الأحد , رجب, 1442

الکلمات المفتاحية: حمل و نقل پستی, تاب آوری, تحلیل عاملی, تحلیل شبکه ای, زنجبره تامین,

ملخص المقالة :

هدف این پژوهش، بررسی وضعیت تاب آوری زنجیره تامین در حمل و نقل کالا توسط شرکتهای پستی در شرایط بحرانی است. برای این منظور پس از بررسی ادبیات و پیشینه تحقیق و مصاحبه با خبرگان، 14 شاخص تاب آوری استخراج و پرسشنامه بین 98 نفر از مشتریان پستی توزیع و جمع آوری شد. بررسی و تحلیل اولیه داده ها از طریق نرم افزار spss و روش تحلیل مولفه های اصلی و تحلیل عاملی اکتشافی انجام شد. پس از چرخش واریماکس، متغیرهایی که دارای مقادیر ویژه بزرگتر از یک و بارهای عاملی بزرگتر از 55/0 بودند و بیشترین همبستگی و واریانس را تبیین می کردند، مشخص شدند. درنهایت شش عامل پنهان بدست آمد. همچنین بمنظور بدست آوردن ارتباط بین شاخص ها و عامل ها و ارتباط درونی بین شاخص ها، از طریق نرم افزار متلب تمام محاسبات سوپر ماتریس، ماتریس های موزون و ماتریس حدی از روش فرآیند تحلیل شبکه ای انجام شده است. در پایان، ارزش اهمیت هر عامل و اهمیت ضریب نسبی هر شاخص محاسبه شده ، که بیمه بودن کالا، مهمترین عامل و تحویل به موقع کالا، به عنوان مهمترین شاخص بدست آمده است.

المصادر:


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_||_

  1. Barad, M. and Sapir, D.E. (2003). Flexibility in logistic systems-modelling and performance evaluation. International Journal of Production Economics, 85 (2): 155–170.
    2.
  2. Carvalho, H., A. P. Barroso, V. H. Machado, S. Azevedo, and V. Cruz-Machodo. (2012). Supply chain Redesign for Resilience Using Simulation. Computers and Industrial Engineering 62 (1): 329–341.
    3.
  3. Chang, S.E. and Nojima, N. (2001). Measuring post-disaster transportation system performance: the 1995 Kobe earthquake in comparative perspective. Transportation Research Part A: Policy and Practice, 35 (6): 475–494.
    4.
  4. Chopra, S. and Meindl, P. (2004). Supply chain management strategy. planning and operation. 7th ed. Upper Saddle River, NJ: Prentice Hall.
    5.
  5. Chopra, S., and M. Sodhi. (2004). Managing Risk to Avoid Supply Chain Breakdown. MIT Sloan Management Review 46 (1): 53–62.
    6.
  6. Christopher, M. and Peck, H. (2004). Building the resilient supply chain. The International Journal of Logistics Management, 15 (2): 1–14.
    7.
  7. Christopher, M. and Lee, H. (2004). Mitigating supply chain risk through improved confidence. International Journal of Physical Distribution & Logistics Management, 34(5): 388-396.
    8.
  8. Cowles, J. (2012). Logistics Management, World Tehnologies, New Delhi.Daniel, H. and Fredrik, N. (2011), Logistics-driven packaging innovation: a case study at IKEA. International Journal of Retail & Distribution Management, 39(9): 638-657
    9.
  9. Davis, T. (1993). Effective supply chain management. Sloan Management Review, 34(4) 35-46.
    10.
  10. Day, G.S. (1994). The capabilities of market driven organisations.Journal of Marketing, 58(4): 37-52.
    11.
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    22.
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    23.
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    24.
  24. Lee, H. L. (2004). The Triple-A Supply Chain. Harvard Business Review, 82 (10): 102–112.
    25.
  25. Lu, C.-S. and Yang, C. C. (2010). Logistics service capabilities and firmperformance of international distribution center operators.The Service Industries Journal, 30(2): 281-298.
    26.
  26. Major, J. A. (2002). Advanced Techniques for Modeling Terrorism Risk. white paper. www.guycarp.com.
    27.
  27. Mark, S. and Martin, S. (2007). Flexibility from a supply chain perspective: definition and review.  International Journal of Operations & Production Management, 27(7): 685-713.
    28.
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    30.
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    40.
  40. Sedighpour, A., Zandieh, M., AlamTabriz, A.,and DoriNokourani, B. (2018). Design and Explanation of Resilient Supply Chain Model in Iranian Pharmaceutical Industry, Quarterly Journal of Industrial Management Studies, Year, 16(15): 106-55.
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  43. Simangunsong, E., Hendry, L.C. and Stevenson, M. (2012). Supply-chain uncertainty: a review and theoretical foundation for future research. International Journal of Production Research, 50(16): 4493-4523.
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  44. Soni, S., Gupta, R., and Pirkul, H. (1999). Survivable network design: the state of the art. Information Systems Frontiers,1 (3): 303–315.
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  45. Svensson, G. (2002). Dyadic vulnerability in companies’ inbound and outbound logistics flows. International Journal of Logistics: Research and Applications, 5 (1): 13–43.
    46.
  46. Tang, O. and Nurmaya Musa, S. (2011). Identifying risk issues and research advancements in supply chain risk management. International Journal of Production Economics, 133(1): 25-34.
    47.
  47. Tse, Y. K., and K. H. Tan. (2012). Managing Product Quality Risk and Visibility in Multi-layer Supply Chain. International Journal of Production Economics, 139 (1): 49–57.
    48.
  48. Tukamuhabwa, B. R., M. Stevenson, J. Busby, and M. Zorzini. (2015). Supply Chain Resilience: Definition, Review and Theoretical Foundations for Further Study. International Journal of Production Research, 53 (18): 5592–5623.
    49.
  49. Van der Vegt, G. S., P. Essens, M. Wahlstrom, and G. George. (2015). From the Editors: Managing Risk and Resilience. Academy of Management Journal, 58 (4): 971–980.
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  50. Wang, Z. (2005). Business intelligence. Taiwan: DrMaster Culture Limited Company.
    51.
  51. Waters, D. (2011). Supply Chain Risk Management Vulnerability and Resilience in Logistics.2nd ed., Kogan Page, London.
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  52. Wernerfelt, B. (1984). A resource based view of the firm. Strategic Management Journal, 5(2): 171-180.
    53.
  53. Wilson, M.C. (2007). The impact of transportation disruptions on supply chain performance. Transportation Research Part E: Logistics and Transportation Review, 43 (4): 295–320.
    54.
  54. Xia, D., and B. Chen. (2011). A Comprehensive Decision Making Model for Risk Management of Supply Chain.Expert Systems with Applications, 38 (5): 4957–4966.
    55.
  55. Zebardast, E. (2014). Application of F'ANP in Urban Planning, Journal of Fine Arts (Architecture and Urban Planning), 19(2): 38-23.
    56.
  56. Zebardast, E. (2013). Constructing a Social Vulnerability Index to Earthquake Hazards using a Hybrid Factor Analysis and Analytic Network Process (F’ANP) Model. Natural Hazards, 65(1): 1331-1359.
    57.
  57. Zhang, Q.,Vonderembse, M., and Lim, J. (2005). Logistics flexibility and its impact on customer satisfaction. International Journal of Logistics Management, 16 (1): 71–95.
    58.
  58. Zhao, M., Dröge, C. and Stank, T.P. (2001). The effects of logitsics capabilities on firm performance: customer-focused versus informati,on-focused capabilities. Journal of Business Logistics, 22(2): 91-107.
    59.

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