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Within a religious tourism destination, the study of business networks can be used to improve understanding of the interactions taking place within or among businesses, by exploring the informal and formal connections linking them together. Hence, the purpose of this study is to map and analyze strategic business networks operating in a religious destination.

This research explores the networks of stakeholders associated with a religious context in an intensive single case study on Al-Atabat Al-Aliyat in Iraq through qualitative analysis. Multiple methods of data collection were used to build strategic networks promoting religious tourism in the Middle-East region. Key analysis practices include content analysis and social network analysis (SNA). The identified interrelationships between stakeholders were analyzed by using UCINet, an SNA tool.

The study reveals three different types of cooperation networks in the case of Al-Atabat Al-Aliyat, namely, a 67-actor continuous network, a 69-actor non-Arbaeen network and an 89-actor Arbaeen network. The results also pinpoint the need for more collaborative activities on the different levels of cooperation in the networks.

This paper provides important guidelines on how to manage the interrelationships within tourism networks in a religious destination such as Iraq. The findings highlight the acute need for establishing strategic and effective networks of stakeholders in Al-Atabat Al-Aliyat. Non-tangible, long-term and quantitative benefits can be found for tourism businesses investing time and money in religious networks in Iraq.

The research contributes to religious tourism literature, filling the gaps about how the interrelationships among the actors involved in a business network can evolve over time and influence the success of a certain religious destination.

The purpose of this paper is to introduce and discuss 11 strategies and 11 sets of tools to provide a knowledge background on how native people of Iran have come up with innovative solutions to create a sustainable and comfortable living environment within the confinement of their homes, in harsh environment of Iran’s hot-arid and hot-humid regions.

These strategies include density, building orientation, introversion, design for four seasons, using local materials, using the ground’s thermal capacity, natural wind induced ventilation, using walls’ thickness and porosity, Panãm (insulation), using special native additive elements and integration of water and plants into the building. Discussed tools include water, courtyard, Showãdãn, Bahãr-khãb, roof, korsi room, ratio and Pãyãb, Sardãb and Howz-khãneh, Shanãshil, Bãdgir and Eivãn.

In conclusion, interrelations between these strategies and tools are illustrated in order to provide a collection of guidelines and inspirations for those involved in the building industry in Iran and Middle East to come up with innovative solutions for creating a sustainable and comfortable living environment in this region’s climates.

This paper provides a collection of guidelines and inspirations for those involved in the building industry in Iran and Middle East to come up with innovative solutions for creating a sustainable and comfortable living environment in this region’s climates.

This study aims to review the existing literature on corporate-level strategy to develop a conceptual framework of the headquarters’ roles as well as situational factors influencing them.

The systematic review is conducted. Accordingly, 598 studies (published from 1962–2018) were extracted from three databases (ProQuest, EBSCO and Web of Science). Then, after screening and ensuring the quality by the TAPUPAS checklist, 53 articles were systematically analyzed by manual coding method.

In total, 31 interventions in the form of four roles, namely, “value creation,” “value reduction,” “portfolio management“ and “loss prevent“ were identified for headquarters (HQ). Furthermore, four influencing situational factors distinguish “business characteristics,” “headquarters characteristics,” “corporate company characteristics” and “characteristic of the HQ-subsidiary relationships.”

The value of this research can be outlined as: mapping the cutting edge on the topic and systematizes the current knowledge; presenting an integrative, unique conceptual framework of HQs’ roles and influences, and particularly, of situational factors that determine the consequents of the interventions; and producing practical insights for corporate parent managers considering the situational factors influencing HQs’ roles and influences in managing their business portfolio successfully.

Religious tourism is a form of tourism where people of a particular faith travel to visit places of religious significance in their faith. Previous research into the various aspects of religious and spiritual tourism (RST) has been noticeably extended. The purpose of this study is to perform systematic mapping to provide trends and classification regarding the recent publications in the area of RST.

This study collected 181 papers from five scientific databases, from which 122 were selected to be classified according to six properties: research type, research focus, research method, investigated religion, publication type and time.

The analysis of these data resulted in a map of the research field, which was presented under three perspectives: the distribution and trends over time of each classification property and the relationship between them. Besides the visual map, the full list of classified papers is available. The results showed that the number of publications is increasing every year, which shows a growing interest in this field. Moreover, the primary research focuses were destination, demand and marketing. Top three journals were found to be International Journal of Tourism Research, Tourism Recreation Research and Journal of Heritage Tourism. Furthermore, evaluation research, solution proposals and opinion papers were the main research types in the area. In addition, the majority of studies focused on Christianity and Islam. Finally, survey, discussion paper, interview and case study were the predominantly used research methods.

The mapping study delivers the first systematic summary of RST research.

One of the practical issues in the area of location and allocation is the location of the hub. In recent years, exchange rates have fluctuated sharply for a number of reasons such as sanctions against the country. Natural disasters that have occurred in recent years caused delays in hub servicing. The purpose of this study is to develop a mathematical programming model to minimize costs, maximize social responsibility and minimize fuel consumption so that in the event of a disruption in the main hub, the flow of materials can be directed to its backup hub to prevent delays in flow between nodes and disruptions in hubs.

A multi-objective mathematical programming model is developed considering uncertainty in some parameters, especially cost as fuzzy numbers. In addition, backup hubs are selected for each primary hub to deal with disruption and natural disasters and prevent delays. Then, a robust possibilistic method is proposed to deal with uncertainty. As the hub location-allocation problem is considered as NP-Hard problems so that exact methods cannot solve them in large sizes, two metaheuristic algorithms including a non-dominated sorting genetic algorithm non-dominated sorting genetic algorithm (NSGA-II) and multi-objective particle swarm optimization (MOPSO) are applied to tackle the problem.

Numerical results show the proposed model is valid. Also, they demonstrate that the NSGA-II algorithm outperforms the MOPSO algorithm.

The proposed model was implemented in one of the largest food companies in Iran, which has numerous products manufactured in different cities, to seek the hub locations. Also, due to several reasons such as road traffic and route type the difference in the rate of fuel consumption between nodes, this model helps managers and decision-makers to choose the best locations to have the least fuel consumption. Moreover, as the hub set up increases the employment rate in that city and has social benefits as it requires hiring some staff.

This paper investigates the hub location problem considering backup hubs with multiple objective functions to deal with disruption and uncertainty. Also, this study examines how non-hub nodes are assigned to hub nodes.

This study aims at characterizing and identifying the existing research on tourism business networks.

The authors conducted a systematic mapping study to identify and analyze related literature. They identified 225 primary studies, dated from 1997-2016, and classified them with respect to research focus, types of research and contribution.

Seventy four studies were identified and mapped, synthesizing the available evidence on tourism business networks. “Business networks” with 27 articles is the dominant research focus and “Network configuration” with 22 articles is the next dominant one. Regarding the research type, “Solution proposal” is the most frequently used research type. “Interview” and “Case study”, respectively, were the most used research methods. However, “Agent-based modeling”, “Delphi study” and “Non-linear time series analysis” were used less often. “Philosophical paper” was the most common research type between 1997 and 2002, and after that “Solution proposal” was the dominant research paper type. Further, the number of publications has declined between 2012 and 2014.

This mapping study provides the first systematic exploration of the state-of-art on tourism business networks research. The existing body of knowledge is limited to a few high quality studies.

The purpose of this study was to address waste management in the food supply chain (FSC) through the integration of inspection processes in production and distribution centers under uncertain conditions, aiming to enhance sustainability across environmental, economic and social dimensions. The study introduces a sustainable forward and reverse FSC network using a closed-loop supply chain network approach to prevent the transfer of spoiled products, ultimately providing competitive advantages to stakeholders.

A robust multi-objective mathematical programming model is proposed, incorporating inspection processes to manage perishable products effectively. The model is solved using the Augmented Epsilon Constraint technique implemented in GAMS software, providing Pareto-optimal solutions tailored to decision-makers’ preferences. Furthermore, the methodology is applied in a real-world case study and solved with the Benders Decomposition algorithm to validate its practicality and effectiveness.

The proposed methodology effectively minimizes waste and enhances sustainability in the FSC by optimizing decision-making processes under uncertainty. The illustrative examples and real case study demonstrate the efficiency of the model and solution approach, highlighting the significant role of inspection in improving all three dimensions of sustainability.

The study offers valuable insights into and tools for food industry managers to make informed strategic and tactical decisions. By addressing waste management through advanced supply chain modeling, the research helps organizations reduce costs, improve sustainability and gain a competitive edge in the market.

This research is novel in its focus on integrating inspection into the FSC network and addressing uncertainty through robust mathematical modeling. It contributes to the existing literature by demonstrating the impact of inspection on sustainability in FSCs and providing practical solutions for real-world implementation.

Integrating project scheduling and material ordering problems is vital in realistically estimating project cost and duration. Also, the quality level of materials is important as one of the key project success factors.

In this paper, a three-objective mathematical model is presented for green project scheduling with materials ordering problems considering rental resources. The first objective is to minimize the total cost of the project site and logistics. The second objective is to minimize the environmental impacts of producing materials and the third objective is to maximize the total quality of materials. Since costs trigger several challenges in projects, cost constraints are considered in this model for the first time and also the cost of delay in supplying of materials by the suppliers has been deducted from the project costs. Subsequently, the model was implemented in a real case and solved by the Lagrangian Relaxation algorithm as an exact method on GAMS software for model validation.

Based on sensitivity analysis of some parameters, the findings indicate that the cost constraint and lead time have considerable effects on the project duration. Also, integrating project scheduling and material ordering improves the robustness of the project schedule.

The primary contributions of the present research can be stated as follows: considering the cost constraints in the project scheduling with material ordering problem, incorporating the rental resources and taking the quality levels of materials as well as the environmental impacts into account.

Untimely responses to emergency situations in urban areas contribute to a rising mortality rate and impact society's primary capital. The efficient dispatch and relocation of ambulances pose operational and momentary challenges, necessitating an optimal policy based on the system's real-time status. While previous studies have addressed these concerns, limited attention has been given to the optimal allocation of technicians to respond to emergency situation and minimize overall system costs.

In this paper, a bi-objective mathematical model is proposed to maximize system coverage and enable flexible movement across bases for location, dispatch and relocation of ambulances. Ambulances relocation involves two key decisions: (1) allocating ambulances to bases after completing services and (2) deciding to change the current ambulance location among existing bases to potentially improve response times to future emergencies. The model also considers the varying capabilities of technicians for proper allocation in emergency situations.

The Augmented Epsilon-Constrained (AEC) method is employed to solve the proposed model for small-sized problem. Due to the NP-Hardness of the model, the NSGA-II and MOPSO metaheuristic algorithms are utilized to obtain efficient solutions for large-sized problems. The findings demonstrate the superiority of the MOPSO algorithm.

This study can be useful for emergency medical centers and healthcare companies in providing more effective responses to emergency situations by sending technicians and ambulances.

In this study, a two-objective mathematical model is developed for ambulance location and dispatch and solved by using the AEC method as well as the NSGA-II and MOPSO metaheuristic algorithms. The mathematical model encompasses three primary types of decision-making: (1) Allocating ambulances to bases after completing their service, (2) deciding to relocate the current ambulance among existing bases to potentially enhance response times to future emergencies and (3) considering the diverse abilities of technicians for accurate allocation to emergency situations.

This paper aims to study the hub transportation system in supply chain networks which would contribute to reducing costs and environmental pollution, as well as to economic development and social responsibility. As not all customers tend to buy green products, several customer groups should be considered in terms of need type.

In this paper, a multi-objective hub location problem is developed for designing a sustainable supply chain network based on customer segmentation. It deals with the aspects of economic (cost reduction), environment (minimizing greenhouse gas emissions by the transport sector) and social responsibility (creating employment and community development). The epsilon-constraint method and augmented epsilon-constraint (AEC) method are used to solve the small-sized instances of this multi-objective problem. Due to the non-deterministic polynomial-time hardness of this problem, two non-dominated sorting genetic algorithm-II (NSGA-II) and multi-objective grey wolf optimizer (MOGWO) metaheuristic algorithms are also applied to tackle the large-sized instances of this problem.

As expected, the AEC method is able to provide better Pareto solutions according to the goals of the decision-makers. The Taguchi method was used for setting the parameters of the two metaheuristic algorithms. Considering the meaningful difference, the MOGWO algorithm outperforms the NSGA-II algorithm according to the rate of achievement to two objectives simultaneously and the spread of non-dominance solutions indexes. Regarding the other indexes, there was no meaningful difference between the performance of the two algorithms.

The model of this research provides a comprehensive solution for supply chain companies that want to achieve a rational balance between the three aspects of sustainability.

The importance of considering customer diversity on the one hand and saving on hub transportation costs, on the other hand, triggered us to propose a hub location model for designing a sustainable supply chain network based on customer segmentation.