@article { author = {Bouayad, Hakim and Benabbou, Loubna and Berrado, Abdelaziz}, title = {A Multi-Criteria Decision Analysis Approach for Aligning IT and Supply Chain Strategies}, journal = {International Journal of Supply and Operations Management}, volume = {9}, number = {2}, pages = {126-148}, year = {2022}, publisher = {Kharazmi University}, issn = {23831359}, eissn = {23832525}, doi = {10.22034/ijsom.2021.109042.2147}, abstract = {As a component of Information Technology Governance, Business-Information Technology Alignment (BITA) is more and more critical to the survival of enterprises. It ensures that Information Technology (IT) strategy is aligned and supports the business strategy, unleashing the potential of IT an avoiding loss of resources. The strategic alignment is a multi-criteria situation with a certain level of uncertainty for the Decision Makers (DM). There is a gap in the literature for IT alignment in a Supply Chain (SC) context with multi-criteria decision methods. This paper introduces a MCDM approach to align the IT and SC strategies. Furthermore, it provides a comparison between the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) and a hybrid Fuzzy Analytic Hierarchy Process (FAHP) FTOPSIS approach in aligning the IT strategy to the SC strategy. The approach introduced herein is illustrated for the case of a public pharmaceutical SC in Morocco. The results have shown the advantages of the fuzzy character of the methods at the strategic level and the differences between them for the prioritisation of the IT strategy.}, keywords = {Multiple-criteria decision method (MCDM),IT alignment,Supply Chain Management,Fuzzy,COBIT 2019,SCOR 12.0}, url = {http://www.ijsom.com/article_2876.html}, eprint = {http://www.ijsom.com/article_2876_7dc2389efb08a22af2a7e9594be1a1d4.pdf} } @article { author = {Forghani, Athena and Sadjadi, Seyed Jafar and Farhang Moghadam, Babak}, title = {Supplier Selection Models for Complementary, Substitutable, and Conditional Products}, journal = {International Journal of Supply and Operations Management}, volume = {9}, number = {2}, pages = {149-161}, year = {2022}, publisher = {Kharazmi University}, issn = {23831359}, eissn = {23832525}, doi = {10.22034/ijsom.2021.108506.1745}, abstract = {The supplier selection process, as one of the components of the supply chain management (SCM), refers to evaluating and selecting suitable suppliers based on relevant criteria. This study presents two supplier selection models to supply complementary, substitutable, and conditional products. For this purpose, two multi-objective mixed-integer non-linear programming (MOMINLP) models are formulated to select the suppliers with the highest scores, the lowest total cost, and the highest quality. To identify the criteria weights and to score the suppliers, first, one of the effective multiple criteria decision-making (MCDM) methods, called the Best-Worst Method (BWM), is employed. Then, the weighted relative deviations from the ideal values of the criteria are minimized to solve the multi-objective models. Finally, two case studies are represented to show the practical application of the proposed methodology in the decision-making process.}, keywords = {Supplier Selection,Supply Chain Management,BWM,Complementary Products,Substitutable Products,Conditional Products}, url = {http://www.ijsom.com/article_2867.html}, eprint = {http://www.ijsom.com/article_2867_3e65082c56c9b275ac8938e763501ef5.pdf} } @article { author = {Srivastava, Abhay and Kumar, Surender and Chauhan, Ankur and Tripathi, Prasoon}, title = {A Technology Enabled Framework for Mitigating Risk during Supply chain disruptions in a pandemic scenario}, journal = {International Journal of Supply and Operations Management}, volume = {9}, number = {2}, pages = {162-174}, year = {2022}, publisher = {Kharazmi University}, issn = {23831359}, eissn = {23832525}, doi = {10.22034/ijsom.2021.108966.2093}, abstract = {At present supply chains are dynamic and interactive in nature which integrates suppliers, manufacturers, distributors, and consumers. An important objective of supply chain management is to ensure that each supply chain partner is in the coordination with others so that supply chain potential and enhanced surplus can be realized in sales. In general, this coordination breaks due to distrust, misinformation, poor logistics and transportation infrastructure; however, in specific cases like Covid-19, it arises due to uncertainties caused by various types of risks such as delays and disruptions. During pandemic Covid-19 global supply chains have been distorted badly due to multiple lockdowns and country specific decisions to contain the spread of coronavirus. For dealing with such pandemic situation in future, we have learned and proposed some of the strategies from literature and practice that a supply chain manager can think of to minimize supply chain disruptions during a pandemic. These supply chain strategies include Resilience, Outsourcing/Offshoring, Agility, and Digitalization. For helping in decision making to the practitioners, we have applied Best Worst Method (BWM) to evaluate these strategies during pandemic times and found that Digitalization strategy (0.574) has been most differentiating among the proposed four strategies in a pandemic scenario; whereas, Outsourcing/Offshoring strategy is most hampered/ineffective during such times.}, keywords = {Supply Chain Management,Pandemic,Disruption,Risk Mitigation,Multi-Criteria Decision Making}, url = {http://www.ijsom.com/article_2871.html}, eprint = {http://www.ijsom.com/article_2871_3a270b4b9e317c2efebfbe1951eb2bef.pdf} } @article { author = {Ben Abid, Taycir and AYADI, Omar and Masmoudi, Faouzi}, title = {A Bi-objective Integrated Production-distribution Planning Problem Considering Intermodal Transportation: An Application to a Textile and Apparel Company}, journal = {International Journal of Supply and Operations Management}, volume = {9}, number = {2}, pages = {175-194}, year = {2022}, publisher = {Kharazmi University}, issn = {23831359}, eissn = {23832525}, doi = {10.22034/ijsom.2021.109193.2235}, abstract = {This paper addresses a bi-objective tactical integrated production-distribution planning problem for a multi-stage, multi-site, multi-product and multi-period Supply Chain network. The proposed model considers sea-air intermodal transportation network in order to enhance the responsiveness and flexibility of the distribution planning. This framework aims at making the trade-off between two conflicting goals. The first objective function considers the minimization of the overall costs associated with production, distribution, inventory and backorders. The second goal is to enhance the customers’ service level by maximizing the on-time deliveries over a tactical time horizon. Therefore, to solve the bi-objective model, the ɛ-constraint method is applied to generate efficient Pareto set of optimal solutions. In fact, the obtained Integer Linear Programming model (ILP), solved using LINGO 18.0 software optimization tool. Computational results are based on a real-life case study from a textile and apparel industry. From a practical point of view, the obtained results prove the pertinence of the proposed model in terms of responsiveness and efficiency of the supply chain to handle peaks demand.}, keywords = {Supply chain,Intermodal transportation,integrated production-distribution,textile and apparel industry}, url = {http://www.ijsom.com/article_2875.html}, eprint = {http://www.ijsom.com/article_2875_0fc63a29c8f93beb4bc524b02fe5e9f0.pdf} } @article { author = {Esmaili, Hamid and Hosseinzadeh, Ahad and Soltani, Roya}, title = {A Mathematical Model to Evaluate Time, Cost and Customer Satisfaction in Omni-Channel Distribution}, journal = {International Journal of Supply and Operations Management}, volume = {9}, number = {2}, pages = {195-211}, year = {2022}, publisher = {Kharazmi University}, issn = {23831359}, eissn = {23832525}, doi = {10.22034/ijsom.2021.108835.1981}, abstract = {Today, upon the higher internet usage and the Covid-19 pandemic, the use of omni-channel distribution has experienced significant growth. The shopping experience in omni-channel distributions is influenced by the physical environment of the buyer, delivery time, and the cost of production to distribution of the goods which have a significant impact on customer loyalty and customer satisfaction. The lack of comprehensive studies in this field, and the number of constant variables in most of the available studies in the literature, especially uncertainty-laden demand, illustrate the significance of this study. After a related literature review and experts’ interviews, based on omni-channel Approach, all important factors influencing time, cost, and customer satisfaction have been included within a multi-objective mathematical model. Thus, defining constraints and decision variables, the objective functions have been solved within two new meta-heuristic algorithms, namely MOGWO and NSGA-II. Besides, these algorithms have been validated using NPS, DM, MID, and SNS indices. Upon comparing the outputs of these two algorithms and inserting 30 numerical instances, it has been shown that the MOGWO method has a stronger Pareto frontier and organized scattering for Pareto solutions. However, averagely, the NSGA-II algorithm produces fewer and more values compared with the first and second objectives, respectively.}, keywords = {Omni-Channel,Supply chain,Mathematical programming,Optimization,NSGA-II,MOGWO}, url = {http://www.ijsom.com/article_2868.html}, eprint = {http://www.ijsom.com/article_2868_2abbc935b804f654ce743cf2002b7041.pdf} } @article { author = {Ouedraogo, Cheik and Montarnal, Aurelie and Gourc, Didier}, title = {Multimodal Container Ttransportation Ttraceability and Supply Chain Risk Management: A Review of Methods and Solutions}, journal = {International Journal of Supply and Operations Management}, volume = {9}, number = {2}, pages = {212-234}, year = {2022}, publisher = {Kharazmi University}, issn = {23831359}, eissn = {23832525}, doi = {10.22034/ijsom.2022.109139.2201}, abstract = {Containerization has revolutionized international freight transport. It makes possible to optimize port handling operations and offers multimodality. In addition, the construction of increasingly large container vessels allows economies of scale while smart logistics thanks to the development of the Internet of Things, increase companies’ flexibility and responsiveness. However, international multimodal transportation is subject to random events (risks) and suffers from lack of visibility which severely impacts the entire supply chain. In order to deal with these problems, research has been carried out in the field of supply chain risk management and the literature has been widely populated. This work deals with multimodal container supply chain risk management using traceability and visibility Data. The main objective of this paper is to analyze proposed solutions to improve the supply chains efficiency by acting on risk management in containers transportation, highlighting literature gaps and providing future research directions. Finally, a specific approach for real-time management of shipments by taking into account random events is proposed.}, keywords = {Smart Container,Traceability,Risk management,Container multimodal transportation}, url = {http://www.ijsom.com/article_2880.html}, eprint = {http://www.ijsom.com/article_2880_abbeab65ba8bb2407e38188269b4e34c.pdf} } @article { author = {Bazirha, Mohammad and Kadrani, Abdeslam and Benmansour, Rachid}, title = {Optimization of the Stochastic Home Health Care Routing and Scheduling Problem with Multiple Hard Time Windows}, journal = {International Journal of Supply and Operations Management}, volume = {9}, number = {2}, pages = {235-250}, year = {2022}, publisher = {Kharazmi University}, issn = {23831359}, eissn = {23832525}, doi = {10.22034/ijsom.2021.109079.2170}, abstract = {Home health care (HHC) aims to assist patients at home and to help them to live with greater independence, avoiding hospitalization or admission to care institutions. The patients should be visited within their availability periods. Unfortunately, the uncertainties related to the traveling and caring times would sometimes violate these time windows constraints, which will qualify the service as poor or even risky. This work addresses the home health care routing and scheduling problem (HHCRSP) with multiple hard/fixed time windows as well as stochastic travel and service times. A two-stage stochastic programming model recourse (SPR model) is proposed to deal with the uncertainty. The recourse is to skip patients if their availability periods will be violated. The objective is to minimize caregivers’ traveling cost and the average number of unvisited patients. Monte Carlo simulation is embedded into the genetic algorithm (GA) to solve the SPR model. The results highlight the efficiency of the GA, show the complexity of the SPR model, and indicate the advantage of using multiple time windows.}, keywords = {Genetic Algorithm,Simulation,Stochastic Programming Recourse Model,Multiple Time Windows}, url = {http://www.ijsom.com/article_2874.html}, eprint = {http://www.ijsom.com/article_2874_7a05146854253f5d84599032d738b794.pdf} }