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Managing supply chains (SCs) for sustainability often results in conflicting demands, which can be conceptualized as sustainability tensions. This paper studies sustainability tensions in electronics SC contexts and the related management responses by applying a paradox perspective.

A single case study on the electronics SC is conducted with companies and third-party organizations as embedded units of analysis, using semi-structured interviews that are triangulated with publicly available data.

The study identifies tension elements (learning, belonging, organizing and economic performing) conflicting with general social–ecological objectives in the electronics SC. The results indicate a hierarchal structure among the sustainability tensions in SC contexts. The management responses of contextualization and resolution are assigned to the identified tensions.

Framing social–ecological objectives with their conflicting elements as paradoxical tensions enables organizations and SCs to develop better strategies for responding to complex sustainability issues in SC contexts.

The study contributes toward filling the gap on paradoxical sustainability tensions in SCs. Empirical insights are gained from different actors in the electronics SC. The level of emergence and interconnectedness of sustainability tensions in a larger SC context is explored through an outside-in perspective.

The Middle East and North Africa (MENA) region is known for its extreme weather conditions during Summer. A major determinant of the sustainability of the design of a building is its fenestrations. The purpose of this paper is to explore the problem of designing and locating windows on building facades such that a number of relevant criteria to the MENA region are optimised, including solar heat gain, privacy, daylighting and cost of installation.

A multi-objective optimisation problem is proposed with the focus on capturing the requirements of residential dwellings in the MENA region. Since the problem contains conflicting objectives that need to be optimised, a lexicographic approach is adopted. In order to display the Pareto curve, a bi-objective analysis based on the ε-constraint method is utilised.

The conflicting nature of the proposed problem is indicated via the Pareto optimal solutions yielded. Depending on the preference of criteria adopted in lexicographic optimisation, the location of the windows on the building façade tends to change. The bi-objective analysis indicates the importance of balancing out the daylight factor against each of privacy, solar heat gain and installation cost criteria. Furthermore, an analysis conducted in three major cities in the MENA region highlights the discrepancy in design alternatives generated depending on the local climatic condition.

This work proposes a novel mathematical optimisation model which focuses on producing a sustainable design and layout for windows on the facades of residential dwellings located in the MENA region. The proposed model provides designers with guidance through an automated support tool that yields optimised window designs and layout to ensure the sustainability of their designed buildings.

The purpose of this paper is to investigate the economic feasibility of a three-echelon Halal Meat Supply Chain (HMSC) network that is monitored by a proposed radio frequency identification (RFID)-based management system for enhancing the integrity traceability of Halal meat products and to maximize the average integrity number of Halal meat products, maximize the return of investment (ROI), maximize the capacity utilization of facilities and minimize the total investment cost of the proposed RFID-monitoring system. The location-allocation problem of facilities needs also to be resolved in conjunction with the quantity flow of Halal meat products from farms to abattoirs and from abattoirs to retailers.

First, a deterministic multi-objective mixed integer linear programming model was developed and used for optimizing the proposed RFID-based HMSC network toward a comprised solution based on four conflicting objectives as described above. Second, a stochastic programming model was developed and used for examining the impact on the number of Halal meat products by altering the value of integrity percentage. The ε-constraint approach and the modified weighted sum approach were proposed for acquisition of non-inferior solutions obtained from the developed models. Furthermore, the Max-Min approach was used for selecting the best solution among them.

The research outcome shows the applicability of the developed models using a real case study. Based on the computational results, a reasonable ROI can be achievable by implementing RFID into the HMSC network.

This work addresses interesting avenues for further research on exploring the HMSC network design under different types of uncertainties and transportation means. Also, environmentalism has been becoming increasingly a significant global problem in the present century. Thus, the presented model could be extended to include the environmental aspects as an objective function.

The model can be utilized for food supply chain designers. Also, it could be applied to realistic problems in the field of supply chain management.

Although there were a few studies focusing on the configuration of a number of HMSC networks, this area is overlooked by researchers. The study shows the developed methodology can be a useful tool for designers to determine a cost-effective design of food supply chain networks.

The purpose of this paper is to investigate the influence of conflict and intuition on explorative new products and performance in small- and medium-sized enterprises (SMEs).

The study proposes a theoretical model that was tested using two survey instruments: one instrument was administered to the owners of 150 SMEs within the United Arab Emirates (UAE) and the second was administered to senior managers within the same SMEs.

The results show that within the decision-making process both objective and personal conflicts drive decision makers to the use of intuition, with high levels of market turbulence strengthening the effect of objective conflict on the use of intuition. Furthermore, the use of intuition was found to have an adverse effect on explorative new products, negating the positive effectiveness of explorative new products on SME performance.

The study’s conceptual model may not completely represent the perspective it aims to elucidate. An alternative model with equally well-conceived explanatory variables could provide further interesting results.

Drawing on the perspective of the decision-making process, an interpretation of the model results and some practical implications are discussed.

The primary contribution of this study is the introduction of a model investigating the influence of conflict on the use of intuition in strategic decisions. Furthermore, the study collected empirical evidence from SMEs operating in the dynamic economy of the UAE, which is a less studied setting.

Multi-objective is a complex problem that appears in real life while these objectives are conflicting. The swarm intelligence algorithm is often used to solve such multi-objective problems. Due to its strong search ability and convergence ability, particle swarm optimization algorithm is proposed, and the multi-objective particle swarm optimization algorithm is used to solve multi-objective optimization problems. However, the particles of particle swarm optimization algorithm are easy to fall into local optimization because of their fast convergence. Uneven distribution and poor diversity are the two key drawbacks of the Pareto front of multi-objective particle swarm optimization algorithm. Therefore, this paper aims to propose an improved multi-objective particle swarm optimization algorithm using adaptive Cauchy mutation and improved crowding distance.

In this paper, the proposed algorithm uses adaptive Cauchy mutation and improved crowding distance to perturb the particles in the population in a dynamic way in order to help the particles trapped in the local optimization jump out of it which improves the convergence performance consequently.

In order to solve the problems of uneven distribution and poor diversity in the Pareto front of multi-objective particle swarm optimization algorithm, this paper uses adaptive Cauchy mutation and improved crowding distance to help the particles trapped in the local optimization jump out of the local optimization. Experimental results show that the proposed algorithm has obvious advantages in convergence performance for nine benchmark functions compared with other multi-objective optimization algorithms.

In order to help the particles trapped in the local optimization jump out of the local optimization which improves the convergence performance consequently, this paper proposes an improved multi-objective particle swarm optimization algorithm using adaptive Cauchy mutation and improved crowding distance.

Companies with multiple roles, as both a profit generator and public service provider, have specific characteristics that differentiate them from single-role companies. However, literature suggests that no performance measurement framework exists to fully suit the characteristics of such companies. This study aims to develop a novel performance-measuring framework to manage logistics performance in multiple-role companies.

The framework is developed by combining a literature review and a case study approach as applied to a company with multiple roles. The case study is conducted to identify the characteristics of multiple-role companies, the factors that potentially affect such companies’ logistics performance and criteria for a new framework. The literature review identifies the concepts, performance attributes and indicators from existing frameworks with the potential for incorporation and synthesis in the new framework.

This study identified several characteristics, performance drivers and criteria for a logistics performance-measuring framework for multiple-role companies. Additionally, this study successfully developed a new logistics performance-measuring framework that consists of eight performance management stages and an aggregated index to measure overall logistics performance.

The proposed logistics performance-measuring methodology provides useful guidance for stakeholders of multiple-role companies to plan, organize, execute and evaluate logistics performance.

This research fills a theoretical gap by explaining the characteristics of logistics systems in multiple-role companies, as well as the factors that may affect such companies’ logistics performance. Further, the proposed framework contributes to academia by integrating performance attributes from several available frameworks to manage objective conflicts, dynamism issues and the inconsistent performance evaluations that exist in companies with multiple roles.

This paper develops a framework for selecting the most efficient and effective preventive maintenance policy using multiple-criteria decision making and multi-objective optimization.

The critical component is identified with a list of maintenance policies, and then its failure data are collected and the optimization objective functions are defined. Fuzzy AHP is used to prioritize each objective based on the experts' questionnaire. Weighted comprehensive criterion method is used to solve the multi-objective models for each policy. Finally, the effectiveness and efficiency are calculated to select the best maintenance policy.

For a fleet of buses in hot climate environment where coolant pump is identified as the most critical component, it was found that block-GAN policy is the most efficient and effective one with a 10.24% of cost saving and 0.34 expected number of failures per cycle compared to age policy and block-BAO policy.

Only three maintenance policies are compared and studied. Other maintenance policies can also be considered in future.

The proposed methodology is implemented in UAE for selecting a maintenance scheme for a critical component in a fleet of buses. It can be validated later in other Gulf countries.

This research lays a solid foundation for selecting the most efficient and effective preventive maintenance policy for different applications and sectors using MCDM and multi-objective optimization to improve reliability and avoid economic loss.

Supplier selection problem is the key process in decision making of supply chain management. An effective selection of vendors is heavily responsible for the success of any organization. Vendor selection problem (VSP) reflects a more practical view when the decision makers involved in the problem are present on different levels. Moreover, vendor selection consists of various random parameters to be dealt with in real life. The purpose of this paper is to present a decentralized bi-level VSP where demand and supply are normal random variables and objectives are fuzzy in nature. Decision makers are present at two levels and are called as leader and follower. As the next purpose, this paper extends and presents a solution approach for fuzzy bi-level multi-objective decision-making model with stochastic constraints. Different scenarios have been developed within a real-life case study based on different sets of controlling factors under the control of leader.

This study uses chance-constrained programming and fuzzy set theory to generate the results. Stochastic constraints are converted into deterministic constraints using chance-constrained programming. Decision variables in the bi-level VSP are partitioned between the two levels and considered as controlling factors. Membership functions based on fuzzy set theory are created for the goals and controlling factors and are used to obtain the overall satisfactory solutions. The model is tested on a real-life case study of a textile industry and different scenarios are constructed based on the choice of leader’s controlling factors.

Results showed that the approach is quite helpful as it generates efficient results producing a good level of satisfaction for the decision makers of both the levels. Results showed that on choosing the vendors that are associated with worst values in terms of associated costs, vendor ratings and quota flexibilities as controlling factors by the leaders, the level of satisfaction achieved is highest. The level of satisfaction of solution is lowest for the scenario when the leader chooses to control the decision variables associated with vendors that are profiled with minimum vendor ratings. Results also showed that higher availability of materials and budget with vendors proved helpful in obtaining quota allocations. Different scenarios generate different results along with different values of satisfaction degrees and objective values which shows the flexible feature of the approach based on leader’s choice of controlling factors. Numerical results showed that the leader’s control can be effectively incorporated maintaining satisfaction levels of the followers under various scenarios or conditions.

The paper makes a certain contribution toward the study of vendor selection existing in a hierarchical manner under uncertain environment. A wide set of data of different factors is needed which can be seen as a limitation when the available time is short for the supplier selection process.

VSP which is generally adopted by most of the large organizations is characterized with hierarchical decision making. Moreover, dealing with the real-life concern, the data available for some of the parameters are not complete, representing an uncertainty of parameters. This study is quite helpful for decentralized VSP under uncertain environment to reduce the costs, improve profit margins and to create long-term relationships with selected vendors. The proposed model also provides an avenue to explore the decision making when the leader has control over some of the decision variables.

Reviewing the literature available, this is the first attempt to present a multi-objective VSP where the decision makers are at hierarchical levels considering uncertain parameters such as demand and supply as per the best knowledge of authors. This research further provides an approach to construct scenarios or different cases based on the choice of leader’s choice of controlling factors.

Today’s dynamic markets are forcing firms to design increasingly complex channel strategies involving multiple channels of distribution. As the complexity of these systems increases, so too does the opportunity for conflict between individual channel coalitions within the firm. Whereas this hybrid channel conflict can reduce channel performance, it can also serve as a mechanism forcing internal channel coalitions to work harder and smarter to serve their markets. In this paper, we develop and test six hypotheses related to hybrid channel conflict. The findings indicate that hybrid channel conflict is an important determinant of both channel performance and satisfaction. The results suggest further that the relationship between hybrid channel conflict and channel performance is moderated by the lifecycle stage. Moreover, our data support the view that the frequency of conflict, but not its intensity, has a negative effect on channel system performance. We conclude with a discussion of the theoretical and managerial implications of this study.