بررسی مقایسه‌ای ویژگی‌های ساختاری شرکت‌های شبکه تامین صنعت خودرو ایران (رویکرد تحلیل شبکه اجتماعی)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری، مدیریت صنعتی، دانشگاه تربیت مدرس، تهران، ایران.

2 دانشیار، دانشکده مدیریت و اقتصاد، دانشگاه تربیت مدرس، تهران، ایران.

3 استادیار، دانشکده مدیریت و اقتصاد، دانشگاه تربیت مدرس، تهران، ایران.

چکیده

به دلیل ورود کسب‌و‌کارها به زمینه رقابت بین شبکه‌ای، موفقیت نهایی آن‌ها به توانایی مدیریت برای هماهنگ کردن شبکه در هم پیچیده شده روابط بین شرکتی بستگی دارد. این کار با شناسایی ویژگی‌های ساختاری شبکه‌‌ها، برای مدیریت بهتر، آن‌ها را ضروری ساخته است. رویکردهای تحلیل و مدل‌سازی سنتی بیشتر روابط شرکت‌‌های تأمین کننده-خریدار را در نظر می‌‌گیرند؛ از‌ این‌رو، در بررسی اثرهای نظام‌ند ناشی از جنبه‌‌های ذاتی پیچیده ریخت‌شناسی و رفتاری در شبکۀ روابط، شکست می‌خورند. با اینکه‌ شبکه‌های تأمین از نظر اقتصادی اهمیت زیادی دارند؛ امّا تنوع آن‌‌ها از نظر ساختاری کمتر شناخته شده است. از این رو بسیاری از پژوهشگران به استفاده از تحلیل شبکه اجتماعی به عنوان ابزاری برای تحلیل ریخت شناسی شبکه‌‌های تأمین، تأکید کرده‌‌اند. این مطالعه به مقایسه ویژگی‌‌های ساختاری شبکه تأمین بین شرکتی در صنعت خودرو ایران و شرکت‌‌های برتر در این زمینه با استفاده از تحلیل شبکه‌‌های اجتماعی با هدف شناخت تفاوت ساختاری آن‌‌ها پرداخته است. نتیجه‌های این پژوهش نشان می‌دهد؛ که شرکت‌‌های با عملکرد برتر در این صنعت، پیکربندی مناسبی برای پاسخ‌گویی به نیازهای بازار را نداشته و سرعت کمی در این زمینه دارند. همچنین آن‌‌ها از قدرت نفوذ بیشتر، دسترسی سریع‌تر به منبع‌ها و قدرت رابطه‌‌ای بالاتری نسبت به سایر شرکت‌‌ها را دارند؛ و روابط خود را به گونه‌‌ای مدیریت می‌‌کنند که اشتراک گذاری، انتقال دانش و یادگیری را برای آن‌‌ها آسان کند.

کلیدواژه‌ها


عنوان مقاله [English]

Comparative analysis of the structural attributes of supply network firms in auto industry (social network analysis approach)

نویسندگان [English]

  • mahin sabet sarvestani 1
  • abbas moghbel baarz 2
  • Amir Afsar 3
1 phd student, industrial management, tarbiat modares university
2 Associate Professor of management , Tarbiat Modares University
3 Assistant Professor at Tarbiat Modares University
چکیده [English]

Due to the entry of companies into the competition among the networks the ultimate success of companies depends on the ability of management to integrate the interconnected network of interfirm relationships. Hence, this has required the identification of the structural characteristics of the networks for their better management. Traditional modeling and analysis approaches focus on individual firms or use a dyadic lens. This approach, however, fails to account for the systemic effects resulting from the complex topological and behavioral aspects inherent in supply networks (SNs). In spite of economic importance, little is known about diversification in the structural shape or topology of SNs. Therefore, many researchers have emphasized the use of social network analysis as a tool for morphological analysis of SNs. In this regard, this study examines the structural characteristics of the supply network in the Iran automotive industry for understanding the structural difference between the high-performing companies and the others in their network. The results showed that high-performing companies are not properly configured to respond to market requirnments and have little agility in this regard. Also, they exhibit significant relational power, more timely access to resources, greater levels of knowledge sharing and learning among SN members. In other words, they manage their relationships in a way that facilitates sharing of knowledge and learning.

کلیدواژه‌ها [English]

  • supply network
  • structural characteristics
  • social network analysis
  • network structure
  • auto industry
[1]    Scavarda, M., H. Seok, and S.Y. Nof, The constrained-collaboration algorithm for intelligent resource distribution in supply networks. Computers & Industrial Engineering, 113, 2017, 803-818.
[2]    Long, Q., A novel research methodology for supply network collaboration management. Information Sciences, 331, 2016, 67-85.
[3]    Bellamy, M.A. and R.C. Basole, Network analysis of supply chain systems: A systematic review and future research. Systems Engineering, 16(2), 2013, 235-249.
[4]    Kim, Y., et al., Structural investigation of supply networks: A social network analysis approach. Journal of Operations Management, 29(3), 2011, 194-211.
[5]    Barratt, M., Exploring Supply Chain Relationships and Information Exchange in UK Grocery Supply Chains: Some Preliminary Findings, in Developments in Logistics and Supply Chain Management: Past, Present and Future, K.S. Pawar, et al., Editors. 2016, Palgrave Macmillan UK: London. p. 181-188.
[6]    Borgatti, S.P. and X. Li, On social network analysis in a supply chain context. Journal of Supply Chain Management, 45(2), 2009, 5-22.
[7]    DiMaggio, P. and H. Louch, Socially embedded consumer transactions: For what kinds of purchases do people most often use networks? American sociological review, 1998, 619-637.
[8]    Basole, R.C., Topological analysis and visualization of interfirm collaboration networks in the electronics industry. Decision Support Systems, 83, 2016, 22-31.
[9]    Long, Q., A framework for data-driven computational experiments of inter-organizational collaborations in supply chain networks. Information Sciences, 399, 2017, 43-63.
[10]  Min, H. and G. Zhou, Supply chain modeling: past, present and future. Computers & Industrial Engineering, 43(1), 2002, 231-249.
[11]  Rodewald, J., et al., Using information-theoretic principles to analyze and evaluate complex adaptive supply network architectures. Procedia Computer Science, 61, 2015, 147-152.
[12]  Pathak, S.D., et al., Complexity and Adaptivity in Supply Networks: Building Supply Network Theory Using a Complex Adaptive Systems Perspective. Decision Sciences, 38(4), 2007, 547-580.
[13]  Taklimi, S.Z.R., The Effect of Industrial Concentration on Employment
in Iran. 2016, Masters Degree in Field Economics, University of Mazandaran.
[14]  Villa, A., Managing Cooperation in Supply Network Structures and Small or Medium-sized Enterprises: Main Criteria and Tools for Managers. 2011: Springer London.
[15]  Lamming, R., et al., An initial classification of supply networks. International Journal of Operations & Production Management, 20(6), 2000, 675-691.
[16]  Klein, R. and A. Rai, Interfirm strategic information flows in logistics supply chain relationships. Mis Quarterly, 2009, 735-762.
[17]  Pathak, S.D., D.M. Dilts, and S. Mahadevan, Investigating Population and Topological Evolution in a Complex Adaptive Supply Network*. Journal of Supply Chain Management, 45(3), 2009, 54-57.
[18]  Nair, A. and J.M. Vidal, Supply network topology and robustness against disruptions–an investigation using multi-agent model. International Journal of Production Research, 49(5), 2011, 1391-1404.
[19]  Basole, R.C. and W.B. Rouse, Complexity of service value networks: Conceptualization and empirical investigation. IBM systems journal, 47(1), 2008, 53-70.
[20]  Kim, K.K., et al., Inter-organizational cooperation in buyer–supplier relationships: Both perspectives. Journal of Business Research, 63(8), 2010, 863-869.
[21]  Wang, E.T.G. and H.-L. Wei, Interorganizational Governance Value Creation: Coordinating for Information Visibility and Flexibility in Supply Chains*. Decision Sciences, 38(4), 2007, 647-674.
[22]  Jarillo, J.C., On Strategic Networks. Strategic Management Journal, 9(1), 1988, 31-41.
[23]  Williamson, O.E., The Economic Institutions of Capitalism: Firms, Markets, Relational Contracting. 1985: Free Press.
[24]  Collaborative inter-organizational relationship model to improve supply chain performance in Iranian machine-woven carpet industry. Iranian journal of management sciences, 6(22), 2012, 1-27.
[25]  Nason, R.S. and J. Wiklund, An assessment of resource-based theorizing on firm growth and suggestions for the future. Journal of Management, 2015, 0149206315610635.
[26]  Barney, J., Firm resources and sustained competitive advantage. Journal of management, 17(1), 1991, 99-120.
[27]  Knudsen, D., Aligning corporate strategy, procurement strategy and e-procurement tools. International Journal of Physical Distribution & Logistics Management, 33(8), 2003, 720-734.
[28]  Wang, E.T. and H.L. Wei, Interorganizational governance value creation: coordinating for information visibility and flexibility in supply chains. Decision Sciences, 38(4), 2007, 647-674.
[29]  Barringer, B.R. and J.S. Harrison, Walking a Tightrope: Creating Value Through Interorganizational Relationships. Journal of Management, 26(3), 2000, 367-403.
[30]  Rodríguez, R.R. and R.D. Leon, Social network analysis and supply chain management. International Journal of Production Management and Engineering, 4(1), 2016, 35-40.
[31]  Monaghan, S., J. Lavelle, and P. Gunnigle, Mapping networks: Exploring the utility of social network analysis in management research and practice. Journal of Business Research, 76, 2017, 136-144.
[32]  Hollenbeck, J.R. and B.B. Jamieson, Human capital, social capital, and social network analysis: Implications for strategic human resource management. The Academy of Management Perspectives, 29(3), 2015, 370-385.
[33]  Carpenter, M.A., M. Li, and H. Jiang, Social network research in organizational contexts: A systematic review of methodological issues and choices. Journal of Management, 38(4), 2012, 1328-1361.
[34]  Chan, K. and J. Liebowitz, The synergy of social network analysis and knowledge mapping: a case study. International journal of management and decision making, 7(1), 2005, 19-35.
[35]  Basole, R.C., et al., Models of Complex Enterprise Networks. Journal of Enterprise Transformation, 1(3), 2011, 208-230.
[36]  Kao, T.-W.D., et al., Relating supply network structure to productive efficiency: A multi-stage empirical investigation. European Journal of Operational Research, 259(2), 2017, 469-485.
[37]  Bellamy, M.A., S. Ghosh, and M. Hora, The influence of supply network structure on firm innovation. Journal of Operations Management, 32(6), 2014, 357-373.
[38]  Mahmodzadeh, M. and A. Laleh, Evaluating Supply Network Efficiency by Using Social Networks Analysis (Case Study: Tractor Motor Manufacturing Company). Scientific Journal Management System, 8(3(30)), 2014, 135-152.