A Multi-Criteria Decision Analysis Approach for Aligning IT and Supply Chain Strategies Hakim Bouayad AMIPS Team (System and Process Analysis, Modeling and Integration), Ecole Mohammadia d’Ingénieurs (EMI), Mohammed V University, Rabat, Morocco author Loubna Benabbou Department of Management Sciences, Université du Québec à Rimouski (UQAR), Campus de Lévis, Québec, Canada author Abdelaziz Berrado AMIPS Team (System and Process Analysis, Modeling and Integration), Ecole Mohammadia d’Ingénieurs (EMI), Mohammed V University, Rabat, Morocco author text article 2022 eng 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. International Journal of Supply and Operations Management Kharazmi University 23831359 9 v. 2 no. 2022 126 148 http://www.ijsom.com/article_2876_7dc2389efb08a22af2a7e9594be1a1d4.pdf dx.doi.org/10.22034/ijsom.2021.109042.2147 Supplier Selection Models for Complementary, Substitutable, and Conditional Products Athena Forghani Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran author Seyed Jafar Sadjadi Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran author Babak Farhang Moghadam Institute for Management and Planning Studies, Tehran, Iran author text article 2022 eng 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. International Journal of Supply and Operations Management Kharazmi University 23831359 9 v. 2 no. 2022 149 161 http://www.ijsom.com/article_2867_3e65082c56c9b275ac8938e763501ef5.pdf dx.doi.org/10.22034/ijsom.2021.108506.1745 A Technology Enabled Framework for Mitigating Risk during Supply chain disruptions in a pandemic scenario Abhay Srivastava IPE Hyderabad, Telagana, India author Surender Kumar Jaipuria Institute of Management, Noida, India author Ankur Chauhan Jaipuria Institute of Management, Noida, India author Prasoon Tripathi Jaipuria Institute of Management, Jaipur, India author text article 2022 eng 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. International Journal of Supply and Operations Management Kharazmi University 23831359 9 v. 2 no. 2022 162 174 http://www.ijsom.com/article_2871_3a270b4b9e317c2efebfbe1951eb2bef.pdf dx.doi.org/10.22034/ijsom.2021.108966.2093 A Bi-objective Integrated Production-distribution Planning Problem Considering Intermodal Transportation: An Application to a Textile and Apparel Company Taycir Ben Abid Mechanics, Modelling and Production Research Laboratory (LA2MP), University of Sfax, Sfax, Tunisia author Omar AYADI Mechanics, Modelling and Production Research Laboratory (LA2MP), University of Sfax, Sfax, Tunisia author Faouzi Masmoudi Mechanics, Modelling and Production Research Laboratory (LA2MP), University of Sfax, Sfax, Tunisia author text article 2022 eng 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. International Journal of Supply and Operations Management Kharazmi University 23831359 9 v. 2 no. 2022 175 194 http://www.ijsom.com/article_2875_0fc63a29c8f93beb4bc524b02fe5e9f0.pdf dx.doi.org/10.22034/ijsom.2021.109193.2235 A Mathematical Model to Evaluate Time, Cost and Customer Satisfaction in Omni-Channel Distribution Hamid Esmaili Department of Industrial Engineering, North Tehran Branch, Islamic Azad University, Tehran, Iran author Ahad Hosseinzadeh Department of Industrial Engineering, North Tehran Branch, Islamic Azad University, Tehran, Iran author Roya Soltani Department of Industrial Engineering, Khatam University, Tehran, Iran author text article 2022 eng 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. International Journal of Supply and Operations Management Kharazmi University 23831359 9 v. 2 no. 2022 195 211 http://www.ijsom.com/article_2868_2abbc935b804f654ce743cf2002b7041.pdf dx.doi.org/10.22034/ijsom.2021.108835.1981 Multimodal Container Ttransportation Ttraceability and Supply Chain Risk Management: A Review of Methods and Solutions Cheik Ouedraogo Department of Industrial engineering, IMT Mines Albi-Carmaux , Toulouse University, IMT Mines Albi, Albi, France author Aurelie Montarnal Department of Industrial engineering, IMT Mines Albi-Carmaux , Toulouse University, IMT Mines Albi, Albi, France author Didier Gourc Department of Industrial engineering, IMT Mines Albi-Carmaux , Toulouse University, IMT Mines Albi, Albi, France author text article 2022 eng 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. International Journal of Supply and Operations Management Kharazmi University 23831359 9 v. 2 no. 2022 212 234 http://www.ijsom.com/article_2880_abbeab65ba8bb2407e38188269b4e34c.pdf dx.doi.org/10.22034/ijsom.2022.109139.2201 Optimization of the Stochastic Home Health Care Routing and Scheduling Problem with Multiple Hard Time Windows Mohammad Bazirha SI2M Laboratory INSEA, Rabat, Morocco author Abdeslam Kadrani SI2M Laboratory INSEA, Rabat, Morocco author Rachid Benmansour SI2M Laboratory INSEA, Rabat, Morocco author text article 2022 eng 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. International Journal of Supply and Operations Management Kharazmi University 23831359 9 v. 2 no. 2022 235 250 http://www.ijsom.com/article_2874_7a05146854253f5d84599032d738b794.pdf dx.doi.org/10.22034/ijsom.2021.109079.2170