Productivity Management Studies

Designing the pattern of the information system in the warehouse with the approach of implementing WMS software using the SSM method

Document Type : Original Article

Authors

1 , Professor of Department of Business Management, Faculty of Economics, Management and Administrative Sciences, University of Semnan, Semnan, Iran.

2 Associate Prof of Department of Industrial Management, Faculty of Economics, Management and Administrative Sciences, University of Semnan, Semnan, Iran.

3 Professor of Department of Business Management, Faculty of Economics, Management and Administrative Sciences, University of Semnan, Semnan, Iran.

4 Ph.D. Student of Industrial Management, Faculty of Economics, Management and Administrative Sciences, University of Semnan, Semnan, Iran

Abstract

The astonishing progress of science, the introduction of new technologies in all areas, especially in supply chains, the competitive market, and the staggering increase in customer demands, have caused the warehouse, as one of the main parts of the organization, to be in the center of attention and the optimal performance of the warehouse plays an undeniable role in increasing organizational productivity. In the meantime, the correct design and implementation of an information system is of great importance due to its impact on the accurate and error-free performance of a warehouse. In the current research, using soft systems methodology, an appropriate information system model has been designed for the implementation of specialized warehouse software. Accordingly, after identifying and understanding the problem conditions, an illustrative picture of the warehouse information system conditions was drawn and then the fundamental definition and development of root definitions related to the defined problem according to CATWOE, a conceptual model of the information system pattern was created. In the next step, to compare the model with the real world, the opinions of 28 experts in this industry, who were selected using the snowball method, were obtained using an open questionnaire and expert method. Based on this, in the next stage, the desired changes in the designed model were applied. Finally, the conceptual model of the information system pattern and the steps for implementing the optimal information system were presented. The results of current research, by providing a clear picture of the various aspects of warehouse processes, facilitate the deployment of the required software using a comprehensive and improvable information system mode

Keywords

Main Subjects

Abdul Rahman, N. S. F., Karim, N. H., Md Hanafiah, R., Abdul Hamid, S., & Mohammed, A. (2023). Decision analysis of warehouse productivity performance indicators to enhance logistics operational efficiency. International Journal of Productivity and Performance Management, 72(4), 962-985. [persian].
Adeitan, A. D., Aigbavboa, C., & Bamisaye, O. S. (2021). Influence of information flow on logistics management in the industry 4.0 era. International Journal of Supply and Operations Management, 8(1), 29-38.
Andiyappillai, N. (2020). Factors influencing the successful implementation of the warehouse management system (WMS). International Journal of Computer Applications, 177(32), 21-25.
Aravindaraj, K., & Chinna, P. R. (2022). A systematic literature review of integration of industry 4.0 and warehouse management to achieve Sustainable Development Goals (SDGs). Cleaner logistics and supply chain, 100072.
Asadi, S. (2020). Soft systems methodology approach to IS change management. International Journal of Industrial Engineering and Management Science, 7(1), 66-80.[persian]
Bahr, W., Mavrogenis, V., & Sweeney, E. (2022). Gamification of warehousing: exploring perspectives of warehouse managers in the UK. International Journal of Logistics Research and Applications, 25(3), 247-259.
Bayram, D. E. D. E., & Çengel, Ö. (2020). Efficient warehouse management analysis in logistics services. İstanbul Ticaret Üniversitesi Sosyal Bilimler Dergisi, 19(37), 341-352.
Bélanger, M. J., Pellerin, R., & Lamouri, S. (2023). A Literature Review on Digital Twins in Warehouses. Procedia Computer Science, 219, 370-377.
Brunaud, B., Bassett, M. H., Agarwal, A., Wassick, J. M., & Grossmann, I. E. (2018). Efficient formulations for dynamic warehouse location under discrete transportation costs. Computers & Chemical Engineering, 111, 311-323.
Burganova, N., Grznar, P., Gregor, M., & Mozol, Š. (2021). Optimalisation of internal logistics transport time through warehouse management: Case study. Transportation Research Procedia, 55, 553-560.
Custodio, L., & Machado, R. (2020). Flexible automated warehouse: a literature review and an innovative framework. The International Journal of Advanced Manufacturing Technology, 106, 533-558.
Eghbalian, ali., Azar,. Adel., (2016). Macro level design of Islamic culture management system with soft systems methodology approach (SSM), Strategic Management Thought, 10(1), 151-180. [Persian].
Golshahi, B., Rastegar, A.A., Feiz, D., Zarei, A. (2018). The Architecture of Talent Identifying Process at National Elite Foundation: CM and SSM Hybrid Algorithm. Industrial Management Journal, 10(3), 387- 406. [Persian].
Hamdy, W., Al-Awamry, A., & Mostafa, N. (2022). Warehousing 4.0: A proposed system of using node-red for applying internet of things in warehousing. Sustainable Futures, 4, 100069.
Hanafizadeh, P., Mehrabioun, M., & Mostasharirad, A. (2021). The necessary and sufficient conditions for the solution of soft systems methodology. Philosophy of Management, 20, 135-166. [Persian].
Hao, J., Shi, H., Shi, V., & Yang, C. (2020). Adoption of automatic warehousing systems in logistics firms: A technology–organization–environment framework. Sustainability, 12(12), 5185.
Istiqomah, N. A., Sansabilla, P. F., Himawan, D., & Rifni, M. (2020, July). The implementation of barcode on warehouse management system for warehouse efficiency. In Journal of Physics: Conference Series (Vol. 1573, No. 1, p. 012038). IOP Publishing.
Kembro, J., & Norrman, A. (2022). The transformation from manual to smart warehousing: an exploratory study with Swedish retailers. The International Journal of Logistics Management, 33(5), 107-135.
Khan, M. G., Huda, N. U., & Zaman, U. K. U. (2022). Smart warehouse management system: Architecture, real-time implementation and prototype design. Machines, 10(2), 150.
Martins, R., Pereira, M. T., Ferreira, L. P., Sá, J. C., & Silva, F. J. G. (2020). Warehouse operations logistics improvement in a cork stopper factory. Procedia Manufacturing, 51, 1723-1729.
Marziali, M., Rossit, D. A., & Toncovich, A. (2021). Warehouse Management Problem and a KPI Approach: a Case Study. Management and Production Engineering Review.
Mehregan, M., Abooyee Ardakan, M., & Soltan Mohammadi, N,. (2012). Identify Key Factors in the Data Envelopment Analysis (DEA) for Evaluating University Departments by Using Soft System Methodology (SSM). Journal of Industrial Management,4(8), 129-146. [Persian].
Sadeghi Moghadam, A., Khatami Firozabadi, A., & Rabbani, Y. (2012). Using Combined Method of SD and SSM for Solving Unstructured Social Problems. Journal of Industrial Management, 3(7), 55. [Persian].
Sadeghpour, H., Zarei, A., Feiz, D., & Rastgar, A. (2020). Pathology of Management System of Electricity Dispatching Centers: Soft Systems Methodology. Quarterly Journal of Energy Policy and Planning Research, 6 (1):109-147.[Persian]
Saderova, J., Rosova, A., Sofranko, M., & Kacmary, P. (2021). Example of warehouse system design based on the principle of logistics. Sustainability, 13(8), 4492.
Rebelo, C. G. S., Pereira, M. T., Silva, F. J., Ferreira, L. P., & Sá, J. C. (2021). The relevance of space analysis in warehouse management. Procedia Manufacturing, 55, 471-478.
Rosenhead, Jonathan., Mingers, John., (2013). Rational analysis for a problematic world revisted:problem structuring (Soft modeling in management), translated by: Azar, Adel., Anvari, Ali.Tehran, Negah Danesh pub,. First Edition.
Tejesh, B. S. S., & Neeraja, S. J. A. E. J. (2018). Warehouse inventory management system using IoT and open source framework. Alexandria engineering journal, 57(4), 3817-3823.
Torabizadeh, M., Yusof, N. M., Ma’aram, A., & Shaharoun, A. M. (2020). Identifying sustainable warehouse management system indicators and proposing new weighting method. Journal of Cleaner Production, 248, 119190. [Persian]
van Geest, M., Tekinerdogan, B., & Catal, C. (2021). Smart warehouses: Rationale, challenges and solution directions. Applied sciences, 12(1), 219.
Yang, D., Wu, Y., & Ma, W. (2021). Optimization of storage location assignment in automated warehouse. Microprocessors and Microsystems, 80, 103356.
Zaman, S. I., Khan, S., Zaman, S. A. A., & Khan, S. A. (2023). A grey decision-making trial and evaluation laboratory model for digital warehouse management in supply chain networks. Decision Analytics Journal, 100293.
Zhang, D., Pee, L. G., & Cui, L. (2021). Artificial intelligence in E-commerce fulfillment: A case study of resource orchestration at Alibaba’s Smart Warehouse. International Journal of Information Management, 57, 102304.
Zhen, L., & Li, H. (2022). A literature review of smart warehouse operations management. Frontiers of Engineering Management, 9(1), 31-55.
Žunić, E., Delalić, S., Hodžić, K., Beširević, A., & Hindija, H. (2018). Smart warehouse management system concept with implementation. In 2018 14th Symposium on Neural Networks and Applications (NEUREL) (1-5). IEEE.
Productivity Management Studies
Volume 1, Issue 1
January 1404
Pages 39-56