نوع مقاله : مقاله پژوهشی

نویسندگان

1 استادیار، گروه لجستیک، دانشگاه امام حسن(ع)، تهران، ایران

2 دانشیار، گروه پیشگیری، دانشگاه علوم انتظامی امین، تهران، ایران

چکیده

این پژوهش ازنظر هدف کاربردی-توسعه ای و از نوع توصیفی- تحلیلی است. جامعه پژوهش عبارت است از مدیران و فرماندهان خبره نیروی انتظامی مرتبط با فرماندهی عملیاتی در حوزه پلیسی و اساتید خبره دانشگاهی لجستیک پلیس و مدیران خبره لجستیکی که دارای مدرک حداقل کارشناسی و حداقل 15 سال مدیریت در سطوح عالی پلیسی و آمادوپشتیبانی می‌باشند. ابزار گردآوری اطلاعات پژوهش مصاحبه نیمه‌ساختاریافته با استفاده از نظرات 22 نفر از خبرگان جامعه موردبررسی به روش قضاوتی هدفمند است. روش تجزیه­وتحلیل اطلاعات نیز روش تحلیل تماتیک است. یافته‌های حاصل از پژوهش در طراحی مدل حاکی از آن است که مدل لجستیک چابک و تاب آور پلیس دربرگیرنده 178 شاخص، 30 مؤلفه و 6 بعد اساسی ازجمله سازمان و مدیریت، فناوری، اقدامات لجستیکی، تأمین و توزیع، قابلیت­های چابکی و قابلیت­های تاب‌آوری است. مدل لجستیک چابک و تاب آور در یک رویکرد یکپارچه که در این پژوهش موردنظر بوده است، دارای هم­پوشانی­هایی میان دو مفهوم چابکی و تاب‌آوری در یک نگاه مجزا است اما بر اساس مبانی نظری این دو رویکرد دارای زمینه‌های مشترکی هستند. درواقع چنانچه چابکی را پیش­زمینه نظری ازنظر تقدم و تأخر تاریخی در نظر بگیریم، به‌نوعی تاب‌آوری اگرچه پس از مفهوم چابکی ارائه گردید، اما عملاً رویکرد تاب‌آوری که بازگشتی به حالت اولیه و یا مطلوب­تر از آن در نظر گرفته می­شود، بدون توجه به عناصر چابکی امکان­پذیر نیست. با توجه به ماهیت و حساسیت مأموریت سازمان­های پلیسی، استفاده از رویکردهای توانمندساز لجستیک در جهت حرکت سریع و چابک و از طرف دیگر، بازیابی لجستیک در شرایط بحران و در صورت بروز اختلال و شکست، از مهم‌ترین ارکان کلیدی در مدیریت لجستیک سازمان­های پلیسی است. ازاین‌رو، هدف از این پژوهش ارائه مدلی ترکیبی برای لجستیک چابک و تاب‌آور در سازمان­های پلیسی است.

کلیدواژه‌ها

عنوان مقاله [English]

A Hybrid Model of Agile and Resilient Logistics in Police Organizations Using the Thematic Analysis Method

نویسندگان [English]

  • milad aghaee 1
  • Alireza Jazini 2

1 Assistant Professor, Department of Logistics, Imam Hassan University, Tehran, Iran

2 Associate Professor, Department of Prevention, Amin University of Police Sciences, Tehran, Iran

چکیده [English]

Today, the geographical distribution of crime, particularly in Tehran, is so unpredictable that accurately predicting its location and timing has become impossible. Consequently, the utilization of proactive and retrospective models has become essential for the prevention police, ensuring their ability to maintain maximum proactive and reactive operational power. In this context, logistics serves as a pivotal element supporting police missions and operations, thereby playing a significant role in enhancing the overall performance of the preventive police and establishing sustainable security. Given the nature and sensitivity of the prevention police mission, it is inevitable to encounter insecure factors that frequently manifest as sudden and unexpected disruptions. These disruptions can range from natural disasters, fires, and cyberattacks to economic shocks, illegal gatherings, violent crimes, and drug-related incidents. Consequently, there is a pressing need for the preventive police logistics system to embrace novel approaches and strategies in order to effectively adapt to the dynamic and varied nature of the police mission environment. Due to the nature and sensitivity of police organizations' missions, the utilization of logistics-based approaches that facilitate fast and agile movement, as well as logistics recovery during crises and disruptions, is crucial for effective logistics management in these organizations. Therefore, the objective of this research is to propose a hybrid model for agile and resilient logistics in police organizations.
 
Methodology
This research is applied-developmental and descriptive-analytical in nature. The research population consists of managers, expert commanders of the police force in operational command, expert university professors specializing in police logistics, and experienced logistics managers with at least a bachelor's degree and a minimum of 15 years of management experience at high levels within the police and military support. Data collection is conducted through semi-structured interviews, with the input of 22 experts selected using a purposeful judgmental method. The thematic analysis method is employed for data analysis. Additionally, in this research, the reliability of the findings was confirmed through the method of audit by a referee. This involved sending the coding to a referee who possesses knowledge in the research subject. At each stage of implementing the thematic analysis method, the referee's opinions were obtained and incorporated. The Attride-Stirling methodology was employed, which encompassed the identification of basic, constructive, and comprehensive themes. To ensure internal validity, a combination of triangulation methods, member checks, paired checks, and bias elimination techniques were employed. Additionally, several strategies were implemented to safeguard accurate performance and ensure external validity, including collecting data from multiple information sources, consistently comparing data during analysis, preventing initial assumptions from influencing conclusions, and avoiding hasty judgments.
 
Findings
The research findings, in terms of model design, reveal that the police agile and resilient logistics model encompasses 178 indicators, 30 components, and 6 fundamental dimensions, which include organization and management, technology, logistics measures, supply and distribution, agility capabilities, and capabilities. A total of 89 basic themes related to agility and 58 basic themes related to resilience were extracted from the conducted interviews and analyzed using the thematic analysis method. These findings led to the identification of six main dimensions in the police agile and resilient logistics model: organization and management, technology, logistics measures, supply and distribution, agility capabilities, and resilience capabilities.
 
Conclusion
We are currently residing in an era where organizational managers, particularly logistics managers in police organizations, strive to deliver timely and suitable logistics services to fulfill their requirements. This enables them to consistently enhance their performance and improve customer satisfaction within their operational units. In this context, agility and resilience approaches emerge as crucial strategies that can play a highly functional role in empowering logistics as an effective tool towards achieving this objective. The integrated approach of the agile and resilient logistics model, as intended in this research, highlights the overlap between the two concepts of agility and resilience. Although agility has a historical precedence over resilience, the theoretical foundations of these two approaches demonstrate common ground. In fact, resilience, as an approach, considers a return to the initial state or an even better state, which is not achievable without taking into account the elements of agility. The hybrid model of agile and resilient logistics, based on the research findings, combines managerial and technical elements. It not only encompasses indicators from theoretical foundations and previous research but also addresses indicators specific to the operational environment of the police, particularly their activities within cities. Providing logistics services to police operations within urban areas, especially in large cities with distinct traffic patterns, diverse populations, various types of crimes, and ethnic and cultural characteristics, poses significant logistical challenges for police organizations.

کلیدواژه‌ها [English]

  • Agile logistics
  • Resiliente logistic
  • Logistics performance
  • Prevention police
  1. Aguila, J.O., ElMaraghy, W. (2019). Supply chain resilience and structure: an evaluation framework. Procedia manufacturing, 28, 43-50.
  2. Attride-Stirling, J. (2001). Thematic Networks: An Analytic Tool for Qualitative Research. Qualitative Research, 1(3), 385-405.
  3. Dubey, R., Ali, S. S., Aital, P., & Venkatesh, V. (2014). Mechanics of humanitarian supply chain agility and resilience and its empirical validation. International Journal of Services and Operations Management, 17(4), 367–384.
  4. Hasan, M.M., Jiang, D., Sharif Ullah, A.M.M., & Noor-E-Alam, Md. (2020). Resilient supplier selection in logistics 4.0 with heterogeneous information. Expert systems with applications, 139, 1-24.
  5. Kim, H., Moon, S., & Moon, H. (2019). Parallel military supply chain for resilience. International Journal of Advanced Logistics, 6(2), 80-87.
  6. Koot, M. (2019). Towards a Framework for Smart Resilient Logistics. IEEE 23rd International Enterprise Distributed Object Computing Workshop (EDOCW), https://orcid.org/0000-0001-9143-8531.
  7. Lam, C.Y. (2016). Resilience of Logistics Network: Analysis and Design. World Congress on Industrial Control Systems Security (WCICSS-2016).
  8. Liu, C.L., Shang, K. Ch., Lirn, T. Ch., Lai, K.H., & Lun, Y.H.V. (2017). Supply chain resilience, firm performance, and management policies in liner shipping industry. Transportation research Part A, 1-18, http://dx.doi.org/10.1016/j.tra.2017.02.004.
  9. Mandal, S. (2014). Supply chain resilience: a state-of-the-art review and research directions. International Journal of Disaster Resilience in the Built Environment, 5(4), 427-453
  10. Mills, John, Johannes Schmitz, and Gerry Frizell (2004). A strategic review of supply networks. International Journal of Operations & Production Management, 24 (10), 1012 -1036.
  11. Pfohl, H. Ch., Köhler, H., & Thomas, David. (2010). State of the art in supply chain risk management research: empirical and conceptual findings and a roadmap for the implementation in practice. Logistics Research, 2(1), 33-44.
  12. Soni, U., Jain, V., & Kumar, S. (2014). Measuring supply chain resilience using a deterministic modeling approach. Computers &Industrial Engineering, 74, 11-25.
  13. Stachowiak, A., & Oleskow-Szlapka, J. (2018). Agility capability Maturity Framwork. Procedia Manufacturing, 17, 603-610.
  14. Swieboda, J., & Zajac, M. (2015). Synthesis of issue pertaining to the resilience of logistics systems. Safety and Reliability of Complex Engineered Systems – Podofillini et al. (Eds) Taylor & Francis Group, London, ISBN 978-1-138-02879-1.
  15. Wu C., Barnes D. (2010). Formulating partner selection criteria for agile supply chains: A Dempster - Shafer belief acceptability optimization approach. International Journal of Production Economics, 125, 284–293.
  16. Aghaei, A., & Aghaei, M. (2013). Naja Agile Supply Chain Model. Tehran: The 4th International Conference on Logistics and Supply Chain. [in Persian]
  17. Aghaei, A., Sedqiani, J., Ghorbanzadeh, Vajiho Allah., Mikaili, F., & Aghaei, M. (2014). Naja Agile Supply Chain Model, Quarterly Journal of Resource Management in Police Force, 2(2), 51-72. [in Persian]
  18. Bagheri Jamkhane, A., & Salehi, M. (2015). The effect of organizational commitment components on improving the performance of the Mazandaran police force. Mazandaran Police Science Quarterly, 7(26), 1-20. [in Persian]
  19. Jafaranejad, A. Safari, H., and Mohseni, M. (2014). Analyzing the relationships between the actions of supply chain management paradigms and performance criteria with an interpretive structural modeling approach. Industrial Management Perspectives Quarterly, 18, 9-31. [in Persian]
  20. Jahani, M., Azar, A., and Muqebel Baara', A. (2016). Designing an interpretative-structural model of factors affecting supply chain resilience. Organizational Resource Management Research Quarterly, 7(4), 1-27. [in Persian]
  21. Rahimi Sheikh, H. A., Sharifi, M., & Shahriari, M. R. (2016). Designing a resilient supply chain model (case study: the country's welfare organization). Industrial Management Perspectives Quarterly, 27, 127-150. [in Persian]
  22. Rahimi, A., Rad, A., Alam Tabriz, A., & Motmani, A. (2017). Presenting an interpretative structural model of resilient supply chain in Iran's defense industries. Military Management Quarterly, 18(3), 31-70. [in Persian]
  23. Salari, G., Shahraki, M. R, & Sharifi, A. (2018). Agile supply chain network design with forbidden search algorithm. Technology Growth Quarterly, 15(58), 23-29. [in Persian]
  24. Shoghi, M. (2011). ready support (2). Tehran: Naja Deputy Education Publications. [in Persian]
  25. Sediqpour, A. R., Zandieh, M., Alam Tabriz, A., & Dari Noukrani, B. (2017). Designing and explaining the resilient supply chain model in Iran's pharmaceutical industry. Industrial Management Studies Quarterly, 16(51), 55-106. [in Persian]
  26. Qorani, S. F., Amiri, M., Alfat, L., & Kezazi, A. (2014). Designing a model for supply chain agility and investigating the effects of its dimensions on supply chain performance. Industrial Management Perspectives Quarterly, 20, 9-39. [in Persian]
  27. Kiaroudi, M. (2015). Agile supply chain evaluation model in Rayan Andish Avat company. Industrial Engineering Master's Thesis (System Orientation and Productivity), Faculty of Industrial Engineering, Ivanki University. [in Persian]