Arezoo Gazori-Nishabori, Kaveh Khalili-Damghani and Ashkan Hafezalkotob
A Nash bargaining game data envelopment analysis (NBG-DEA) model is proposed to measure the efficiency of dynamic multi-period network structures. This paper aims to propose…
Abstract
Purpose
A Nash bargaining game data envelopment analysis (NBG-DEA) model is proposed to measure the efficiency of dynamic multi-period network structures. This paper aims to propose NBG-DEA model to measure the performance of decision-making units with complicated network structures.
Design/methodology/approach
As the proposed NBG-DEA model is a non-linear mathematical programming, finding its global optimum solution is hard. Therefore, meta-heuristic algorithms are used to solve non-linear optimization problems. Fortunately, the NBG-DEA model optimizes the well-formed problem, so that it can be solved by different non-linear methods including meta-heuristic algorithms. Hence, a meta-heuristic algorithm, called particle swarm optimization (PSO) is proposed to solve the NBG-DEA model in this paper. The case study is Industrial Management Institute (IMI), which is a leading organization in providing consulting management, publication and educational services in Iran. The sub-processes of IMI are considered as players where their pay-off is defined as the efficiency of sub-processes. The network structure of IMI is studied during multiple periods.
Findings
The proposed NBG-DEA model is applied to measure the efficiency scores in the IMI case study. The solution found by the PSO algorithm, which is implemented in MATLAB software, is compared with that generated by a classic non-linear method called gradient descent implemented in LINGO software.
Originality/value
The experiments proved that suitable and feasible solutions could be found by solving the NBG-DEA model and shows that PSO algorithm solves this model in reasonable central process unit time.
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Raziyeh Reza-Gharehbagh, Ashkan Hafezalkotob, Ahmad Makui and Mohammad Kazem Sayadi
This study aims to analyze the competition of two financial chains (FCs) when the government intervenes in the financial market to prohibit the excessively high-interest rate by…
Abstract
Purpose
This study aims to analyze the competition of two financial chains (FCs) when the government intervenes in the financial market to prohibit the excessively high-interest rate by minimizing the arbitrages caused by speculative transactions. Each FC comprises an investor and one intermediary, attempts to finance the capital-constrained firms in financing needs.
Design/methodology/approach
Using a Stackelberg game theoretic framework and formulating two- and three-level optimization problems for six possible scenarios, the authors establish an integrative framework to evaluate the scenarios through the lens of the two main decision-making structures of the FCs (i.e. centralized and decentralized) and three policies of the government (i.e. speculation minimizing, revenue gaining and utility maximizing).
Findings
Solving the problem results in optimal values for tariffs, which guarantee a stable competitive market. Consequently, policymaking by the government influences the decision variables, which is shown in a numerical study. The authors find that the government can orchestrate the FCs in the competitive market by imposing tariffs and prohibiting high-interest rates via regulating the speculation impacts, which guarantees a stable market and facilitates the financing of capital-constrained firms.
Research limitations/implications
This paper aids the financial markets and governments to control the interest rate by minimizing the speculation level.
Originality/value
This paper investigates the impact of government intervention policies – as a leading player – on the competition of FCs – as followers – in providing financial services and making profits. The government imposes tariffs on the interest rate to stabilize the market by limiting speculative transactions. The paper presents the mathematical models of the optimization problems through the game-theoretic framework and comparison of the scenarios through a numerical experiment.
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Mojtaba Moradi, Ashkan Hafezalkotob and Vahidreza Ghezavati
This study considers a project scheduling model to assess the project risks and the impacts on project sustainability when subcontractors collaborate under uncertainty. Moreover…
Abstract
Purpose
This study considers a project scheduling model to assess the project risks and the impacts on project sustainability when subcontractors collaborate under uncertainty. Moreover, some allocation methods are applied for fair allocating utility of the project and supper-additivity, stability and satisfaction level of each coalition. Finally, sustainability concept is considered in risk assessment in all coalitions.
Design/methodology/approach
The proposed mathematical programming model evaluates project risks when the subcontractors cooperate with each other by sharing their limited resources. Then, some cooperative game theory methods are applied for fair allocation of net present value, of the cooperation and finally sustainability aspects (economic, social and environmental) are investigated in risk assessment for each possible coalition.
Finding
The results of the proposed model indicate that the subcontractors can increase their profit by 10 per cent ($14,028,450 thousand) and save the equilibrium between sustainability aspects especially in grand coalition. It means that subcontractors do not have incentive to leave the coalition and the supper-additive property is feasible. Furthermore, risk assessment shows that project risks have less impact on subcontractor profits when they cooperate with each other.
Originality/value
Sustainability aspects may be investigated in project management in previous studies, but the authors study sustainability indicators when subcontractors form a coalition and share their resources in response to the risks of availability to resources and delay in completing the project under uncertainty.
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Somaye Fathalikhani, Ashkan Hafezalkotob and Roya Soltani
In the past two decades, the growth in the number and severity of disasters causes a rapid increase in the presence of NGOs for more effective response and efficient management of…
Abstract
Purpose
In the past two decades, the growth in the number and severity of disasters causes a rapid increase in the presence of NGOs for more effective response and efficient management of disasters. The NGOs must spend part of their resources on attracting funds to fulfill their humanitarian goals. However, limited number of donors and received contributions leads to a competition among NGOs for fundraising. Therefore, managing the relationship between these organizations and donors is very important. This paper aims to examine the competitive and coopetitive behavior of NGOs to model the interaction.
Design/methodology/approach
To achieve this purpose, by using game theory, two mathematical programing models are presented to examine the two inter-organizational interactions among NGOs.
Findings
The results show that if the NGOs work together, all the organizations, donors and affected people will benefit, and the accrued disaster will be managed more efficiently.
Practical implications
The expressed benefits of coopetition of NGOs can be an incentive for them to work together to manage disasters effectively.
Originality/value
To the best of authors’ knowledge, no research has considered the impact of the coopetition of NGOs in achieving their social mission successfully. Therefore, this paper can be seen as a valuable resource in this field.
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Seyedehanahita Mousavi, Ashkan Hafezalkotob, Vahidreza Ghezavati and Farshid Abdi
This study aims to identify and accurately assess the risk factors of competitors’ cooperation in the NPD project.
Abstract
Purpose
This study aims to identify and accurately assess the risk factors of competitors’ cooperation in the NPD project.
Design/methodology/approach
New product development (NPD) is essential to the survival of companies and surpassing other competitors. A key prerequisite for the success of an NPD project is the timing of new product delivery to the market. The main challenge faced by many project managers is the delay in execution and completion phases due to the complex nature and uncertainty of these projects. Rival companies' cooperation reduces the time spent on an NPD project which is an excellent way to reduce the risk of losing the market, but it increases other risk factors.
Findings
Based on the results, the security and confidentiality of innovation, the competitors attracting human resources and the company’s brand credibility factors were ranked higher than other factors and should be predicted and managed before cooperating with competitors.
Originality/value
This paper proposed a new model to assess risk factors in cooperation with rival companies in NPD projects. This model takes into account new parameters, for example, negative and positive risks, negative and positive passable risks and risk-based multi-objective optimization by ratio analysis plus full multiplicative form methodology for the rival companies cooperation in NPD projects. To evaluate the efficiency of the proposed model, a real case of the R&D unit of Iran Khodro Company was studied.
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Mohammad Khalilzadeh, Rose Balafshan and Ashkan Hafezalkotob
The purpose of this study is to provide a comprehensive framework for analyzing risk factors in oil and gas projects.
Abstract
Purpose
The purpose of this study is to provide a comprehensive framework for analyzing risk factors in oil and gas projects.
Design/methodology/approach
This paper consists of several sections. In the first section, 19 common potential risks in the projects of Pars Oil and Gas Company were finalized in six groups using the Lawshe validation method. These factors were identified through previous literature review and interviews with experts. Then, using the “best-worst multi-criteria decision-making” method, the study measured the weights associated with the performance evaluation indicators of each risk. Consequently, failure mode and effects analysis (FMEA) and the grey relational analysis (GRA)-VIKOR mixed method were used to rank and determine the critical risks. Finally, to assign response strategies to each critical risk, a zero-one multi-objective mathematical programming model was proposed and developed Epsilon-constraint method was used to solve it.
Findings
Given the typical constraints of projects which are time, cost and quality, of the projects that companies are often faced with, this study presents the identified risks of oil and gas projects to the managers of the oil and gas company in accordance with the priority given in the present research and the response to each risk is also suggested to be used by managers based on their organizational circumstances.
Originality/value
This study aims at qualitative management of cost risks of oil and gas projects (case study of Pars Oil and Gas Company) by combining FMEA, best worst and GRA-VIKOR methods under fuzzy environment and Epsilon constraints. According to studies carried out in previous studies, the simultaneous management of quantitative and qualitative cost of risk of oil and gas projects in Iran has not been carried out and the combination of these methods has also been innovated.
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Ashkan Hafezalkotob, Reza Mahmoudi, Elham Hajisami and Hui Ming Wee
Nowadays, uncertainty in market demand poses considerable risk to the retailers that supply the market. On the other hand, the risk-averse behaviors of retailers toward risk may…
Abstract
Purpose
Nowadays, uncertainty in market demand poses considerable risk to the retailers that supply the market. On the other hand, the risk-averse behaviors of retailers toward risk may have evolved over time. Considering a supply chain including a manufacturer and a population of retailers, the authors intend to investigate how the population of retailers tends to evolve toward risk-averse behavior. Moreover, this study aims to evaluate the effects of wholesale-retail price of manufacturer on evolutionary stable strategy (ESS) of the retailers.
Design/methodology/approach
Due to market uncertainty, a supply chain with a population of risk-averse and risk-neutral retailers was investigated. The wholesale pricing strategy is determined by a manufacturer acting as a leader, while retailers who make order quantity decisions act as followers. An integrated Cournot duopoly equilibrium and evolutionary game theory (EGT) approach has been used to model this situation.
Findings
A numerical real-world case study using Iran Khodro Company is analyzed by applying the proposed EGT approach. The study provides managerial insights to the manufacturer as well as retailers in developing their strategies. Results showed that risk behavior of retailers significantly affects optimal wholesale/retail price, profits and ESS. In the long term, the retailers tend to have a risk-neutral behavior to gain more profit. In the short term, if a retailer choses risk-averse strategy, in the long term, it will change its strategy to obtain more profit and remain in the competitive market.
Originality/value
The contributions in this research are fourfold. First, ESS concept to investigate the risk-averse or risk-neutral attitudes of the retailers was used. Second, the uncertain risk behavior of the competing retailers was considered. Third, the effect of varying wholesale pricing was investigated. Fourth, the equilibrium wholesale and retail prices have been obtained by considering uncertainty demand and risk.
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Ehsan Rashidzadeh, Seyyed Mohammad Hadji Molana, Roya Soltani and Ashkan Hafezalkotob
Delivery management of perishable products such as blood in a supply chain is a considerable issue such that the last-mile delivery, which refers to deliver goods to the end user…
Abstract
Purpose
Delivery management of perishable products such as blood in a supply chain is a considerable issue such that the last-mile delivery, which refers to deliver goods to the end user as fast as possible takes into account as one of the most important, expensive and, polluting segments in the entire supply chain. Regardless of economic challenges, the last-mile delivery faces social and environmental barriers to continuing operations while complying with environmental and social standards, therefore incorporating sustainability into last-mile logistic strategy is no longer an option but rather a necessity. Accordingly, the purpose of this paper is to consider a last-mile delivery in a blood supply chain in terms of using appropriate technologies such as drones to assess sustainability.
Design/methodology/approach
The authors discuss the impact of drone technology on last-mile delivery and its importance in achieving sustainability. They focus on the effect of using drones on CO2 emission, costs and social benefits by proposing a multi-objective mathematical model to assess sustainability in the last-mile delivery. A preemptive fuzzy goal programming approach to solve the model and measure the achievement degree of sustainability is conducted by using a numerical example to show the capability and usefulness of the suggested model, solution approach and, impact of drone technology in achieving all three aspects of sustainability.
Findings
The findings illustrate the achievement degree of sustainability in the delivery of blood based on locating distribution centers and allocating drones. Moreover, a comparison between drones and conventional vehicles is carried out to show the preference of using drones in reaching sustainability. A sensitivity analysis on aspects of sustainability and specifications of drone technology is conducted for validating the obtained results and distinguishing the most dominant aspect and parameters in enhancing the achievement degree of sustainability.
Originality/value
To the best of the authors’ knowledge, no research has considered the assessment of sustainability in the last-mile delivery of blood supply chain with a focus on drone technology.
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Jafar Razmi, Anis Hassani and Ashkan Hafezalkotob
Over the past two decades, in developed countries a trend towards the liberalization and restructuring of the gas market has been observed. Today, restructuring is an ongoing…
Abstract
Purpose
Over the past two decades, in developed countries a trend towards the liberalization and restructuring of the gas market has been observed. Today, restructuring is an ongoing process. In this study, a restructured natural gas market has been considered in which several regional distribution companies have ownership of the network and are competing against each other to gain more benefits. The main purpose of this study is to achieve efficiency and economic rationality in such a market through horizontal cooperation.
Design/methodology/approach
A restructured natural gas distribution network is modeled as a cooperative game to estimate the potential cost savings for various collaboration scenarios. In addition, the cost savings’ allocation among collaborating companies is evaluated using the cooperative game theory.
Findings
The results reveal validity and efficiency of the solution of the proposed model and capabilities of the cooperative game theory for reduction in gas distribution costs and improvement in the service level.
Research limitations/implications
This study is limited to natural gas in one region of Yazd City in Iran. Moreover, one segment of the natural gas network (i.e. distribution network) is modeled. Moreover, long-term cooperation between companies relies on fair distribution of cooperation benefits to the participants.
Practical implications
For the purpose of comparison and to get an insight into properties of the cost savings game, the real case study of one region of Yazd city in Iran is implemented.
Originality/value
This study contributes to the competitive models in the restructured gas market, particularly, in gas distribution network. The main contribution is to provide potential benefits for the participants via the horizontal cooperation.
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Jaber Valizadeh, Peyman Mozafari and Ashkan Hafezalkotob
Waste production and related environmental problems have caused urban services management many problems in collecting, transporting and disposal of waste. The purpose of this…
Abstract
Purpose
Waste production and related environmental problems have caused urban services management many problems in collecting, transporting and disposal of waste. The purpose of this study is to design a new model for municipal waste collection vehicle routing problems with time windows and energy generating from waste. To this purpose, a bi-objective model is presented with the objectives of increasing the income of waste recycles and energy generation from waste and reducing emissions from environmental pollutants.
Design/methodology/approach
A bi-objective model is presented with the objectives of increasing income of recycles trade and energy generation and reducing emissions from environmental pollutants. Concerning the complexity of the model and its inability to solve large-scale problems, non-dominated sorting genetic algorithms and multi-objective particle swarm optimization algorithms are applied.
Findings
In this research, an integrated approach to urban waste collection modeling that coordinates the various activities of waste management in the city of Kermanshah and energy generation from waste are provided. Besides, this study calculates the criteria that show the environmental effects of municipal waste. The proposed model helps to collect municipal wastes in the shortest possible time in addition to reducing the total cost, revenues from the sale of recycled materials and energy production.
Originality/value
The proposed model boosts the current understanding of the waste management and energy generation of waste. The paper adds additional value by unveiling some key future research directions. This guidance may demonstrate possible existing and unexplored gaps so that researchers can direct future research to develop new processes.