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PurposeMedical equipment’s supply chains play a vital role in performance of national 1healthcare systems. This supply chain is confronted with different internal and external risks. The purpose of this study is to investigate and find the key factors affecting the resilience of the supply chain of medical equipment and to examine the dynamic relations among these factors.Design/methodology/approachA hybrid methodology is used for meeting the purpose of this study. First, the Delphi method is extended by using hesitant fuzzy linguistic term sets to identify the key factors of supply chain resilience. At the second phase, using the system dynamic methodology, the dynamic relations among identified resilience factors are analyzed.FindingsUsing the Delphi method, agility, collaboration among actors, sharing of information, trust among actors, explicitness of supply chain, risk management culture, adaptability, structure, funding and environment conditions are identified as ten major factors affecting medical equipment’s supply chain resilience. Also, four scenarios are simulated along with their impacts on the system.Originality/valueThe main contribution of this study is extending a hesitant fuzzy linguistic term sets-based Delphi and applying it along a system dynamic analysis to identify the key factors affecting resilience of medical equipment’s supply chain for the first time.

PurposeThis paper aims to recognise and identify fears of failure in the international entrepreneurship ecosystem and find the effects of these fears on each other to reduce these increasing effects and minimise the mental barriers for potential entrepreneurs. Therefore, this research is beneficial to strengthen international entrepreneurial personality and to reduce the shadows of fears on entrepreneurs’ minds. To address this purpose the international tourism industry has been investigated in the emerging economy of Iran.Design/methodology/approachThis paper is organised based on experts' opinions, and then factors are identified by literature review and are finalised through the Delphi method with a panel of practical and academic experts. These fears are categorised using a questionnaire and factor analysis (FA) technique. The respondents were entrepreneurship students and tourism entrepreneurs. Subsequently, the effect and importance of fears of failure are scored and ranked by some experts. These fears were analysed through decision-making trial and evaluation laboratory (DEMATEL) method. The results presented the effects of fears of failure in the international entrepreneurial in the tourism industry and the relationship amongst them.FindingsThe first two fears are respectively “fears of future” which are caused by the unclear situation; and “fear of losing credit” that is due to the importance of “personal relationships” in Iranians culture. As pointed out by results, “fear of future” is the most effective group of factors that may lead to other fears too. This fear seems important in the international entrepreneurial tourism industry because of future ambiguity.Originality/valueThis study indicates the relations between groups of fears and offers some practical and applicable solutions to reduce these effects. To the best knowledge of the authors, analysing the relationship between fears amongst the entrepreneurs has not been investigated previously.

The COVID-19 pandemic outbreak deeply impressed supply chains in different aspects. In response to this unexpected situation, supply chain managers have decided to recover and reinforce their supply chains. Considering the expanse of these decisions, project management principle and tools seems inevitable to successfully manage the transformation from before pandemic to post-pandemic supply chains (SCs). In this study, the problem of time–cost tradeoff is extended to time, cost, and risk tradeoff. The risk factor is considered to convey the uncertainty arising from the COVID-19 pandemic situation. Since projects are affected by the level of pandemic expansion and different countries ruled out various quarantine policies (isolation, quarantine, social distancing, and lock-down), the tradeoff problem is influenced accordingly. Therefore, a scenario-based robust optimization model is proposed to deal with time, cost, and risk tradeoff problems to reflect the effects of the global pandemic of COVID-19 on managing projects in supply chains. In addition, various quarantine policies (isolation, quarantine, social distancing, and lock-down) as a prevalent response to the pandemic have been investigated separately. To illustrate the model, a real-world case study in the emerging economy of Iran is examined using the proposed approach. The results indicated that supply chain managers can use the designed model and approach as a tool for a flexible and adaptable decision-making framework dealing with a global pandemic such as COVID-19.

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. This paper proposes a novel approach for identifying the best implementation situation for each activity in a project by optimizing and balancing time, cost, quality, and risk criteria under uncertain circumstances. A hesitant fuzzy linguistic term set (HFLTS) approach is proposed to determine the status of project activities in the presence of quality and risk criteria alongside time and cost. Afterwards, a multi-objective linear programming (MOLP) model is formulated for time, cost, quality, and risk trade-off (TCQRT). To validate the model, a research and development project in the food industry is investigated. The results indicate that the project's time compared to the deterministic approach was reduced by 20%. Completing the R&D project earlier than other competitors brings a higher profit for the company than trade-off expenses, even without considering the quality and risk trade-off benefits of the proposed approach. Considering uncertainty in the risk and quality of activities in a project via HFLTSs and optimizing all four elements of time, cost, quality, and risk simultaneously are the main values of this research. The proposed approach can be employed by managers to adopt and optimize project planning and scheduling while optimizing the trade-offs among TCQR factors in uncertain circumstances.

PurposeBased on the emerging view of supply chains as complex adaptive systems, this paper aims to build and test an analytical model for resilience assessment surrounding supply chain risks at the level of the supply chain system and its individual tiers.Design/methodology/approachTo address the purpose of this study, a multimethod research approach is adopted as follows: first, data envelopment analysis (DEA) modelling and fuzzy set theory are used to build a fuzzy network DEA model to assess risk resilience of the overall supply chains and their individual tiers; next, the proposed model is tested using a survey of 150 middle- and top-level managers representing nine industry sectors in Iran.FindingsThe survey results show a substantial variation in resilience ratings between the overall supply chains characterizing nine industry sectors in Iran and their individual tiers (upstream, downstream and organizational processes). The findings indicate that the system-wide characteristic of resilience of the overall supply chain is not necessarily indicative of the resilience of its individual tiers.Practical implicationsHigh efficiency scores of a number of tiers forming a supply chain are shown to have only a limited effect on the overall efficiency score of the resulting supply chain. Overall, our research findings confirm the necessity of adopting both the system-wide and tier-specific approach by analysts and decision makers when assessing supply chain resilience. Integrated as part of risk response and mitigation process, the information obtained through such analytical approach ensures timely identification and mitigation of major sources of risk in the supply chains.Originality/valueSupply chain resilience assessment models rarely consider resilience to risks at the level of individual supply chain tiers, focusing instead on the system-wide characteristics of supply chain resilience. The proposed analytical model allows for the assessment of supply chain resilience among individual tiers for a wide range of supply chain risks categorized as upstream, downstream, organizational, network and external.

open access article Decision makers usually prefer to express their preferences by linguistic variables. Classic fuzzy sets allowed expressing these preferences using a single linguistic value. Considering inevitable hesitancy of decision makers, hesitant fuzzy linguistic term sets allowed them to express individual evaluation using several linguistic values. Therefore, these sets improve the ability of humans to determine believes using their own language. Considering this feature, in this paper a method upon linear assignment method is proposed to solve group decision making problems using this kind of information, when criteria weights are known or unknown. The performance of the proposed method is illustrated in a numerical example and the results are compared with other methods to delineate the models efficiency. Following a logical and well-known mathematical logic along with simplicity of execution are the main advantages of the proposed method.

Public transport is a critical part of civilization in this decade. The amount of money invested and the criticality of transferring people in an acceptable time and without any conflict made it a challenging problem for managers, especially in metropolises. Absolutely, making effective decisions in this area requires considering different aspects. Waiting time is a key criterion in apprising quality of public transport. In this paper, a real world case study of ranking causes of delay in Tehran (Iran) metro system is solved by developing multi attribute group decision-making VIšeKriterijumska Optimizacija I KOmpromisno Rešenje (in Serbian, VIKOR) method under uncertainty, where this uncertainty is captured by Fuzzy Belief Structures (FBS). The obtained results are then compared with a previously proposed Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method with FBSs. The results show that human related issues, along with the problems related to line and transportation system are the most important causes of delay. The obtained results of the problem seem acceptable for decision makers.

The aim of this paper is to discuss success criteria of oil, gas and petrochemical projects and developing a pattern for evaluation of these projects. It is conducted following a case study approach in which the projects of Arya Petro Gas Co. are examined. The methodological framework of this research includes a literature review for identifying the original success criteria and the factor analysis method is applied on gathered data to develop the considered pattern. Also, the reliability and validity of research tool is examined. Applying the research methodology on gathered data, the developed model showed that the absolute factors for success of oil, gas and petrochemical projects include mutual cooperation of all individuals involved in the project, fulfilling projects’ goals, paving the path for future, having clarity of rules and contractors’ capability to manage the project.The extended success criteria pattern for oil, gas and petrochemical projects can play a guiding role for managers of project-based companies in this area. These pattern also can be worthy for outsourcing decisions in this field.Identifying success factors provides a critical tool for managers to concentrate their decisions on these factors. Each type of projects in different fields has their own characteristics which made their success factors to be different. Considering this cognitive nature of critical success factors, the main achievement of this study is to extend a pattern of success factors in oil, gas and petrochemical projects for contractor companies. Keywords-function of project; paving the path for future; success criteria of oil, gas and petrochemical projects; Clarity of rules

A project is a series of related activities which are organized to reach a defined goal or satisfy a certain need. Project management plays an important role in different fields of human life. The amount of resources spent on a project renders management of these resources a sensitive task. Determinant factors’ influencing the payoffs of a project mainly encompasses time, cost, quality and also the risk of each activity. Therefore, a critical path method is presented to find the longest path of a project completion time in order to draw managers’ attention to the critical activities. Critical path method is a well-known and widely accepted method to find the critical activities of a project and to concentrate on them for accomplishment of the project without any deviation. Classical critical path methods usually consider only a time factor, but growing complexity and importance of projects entail cost, quality and risk as the critical factors to be considered in project management. Due to the unavailability of certain information relating each factor of each activity, considering a novel approach to deal with such vague and unstable situations is really a controversial issue. Thus, another challenge of the project management contains uncertainty for approximating time, cost, quality, and risk factors of the project activities. Taking into account these two challenges, a grey multi-objective critical path model is proposed in this paper, where parameters of the activities are evaluated as grey numbers, dealing with their uncertainty. Meanwhile, a goal programming based method is illustrated to solve the problem of critical path identification, considering four considerable criteria including time, cost, quality, and risk. Eventually, a numerical example is represented to address applicability of the proposed method.

The linear programming technique for multidimensional analysis of preference, known as LINMAP is one of the existing well-known ideal seeking methods for multi attribute decision making problems. This method originally is proposed under crisp and deterministic circumstances. However, uncertainty is an indubitable property of decision making problems. In this paper, a new version of LINMAP-G is proposed where the decision maker's judgments are expressed as grey numbers. Like original LINMAP method, the grey ideal solution and attributes weight vector is determined and alternatives are ranked according to their weighted distance from determined ideal point. Application of the proposed method is illustrated in two numerical examples.

Aggregate planning is a medium-range capacity planning that suggests the production strategies in order to meet the forecasted demand considering the capacity constraints. As the period of planning length increases, the uncertainty of information will grow. Regarding this point, in this paper, a multi-objective model is proposed for aggregate planning problem in which the parameters of the model are expressed in the form of grey numbers. The suggested grey multi-objective model is solved based on a goal programming problem with fuzzy aspiration levels. The model is applied in a real-world problem, and its results are illustrated. The obtained results give a range for decision variables, and decision makers can handle the inevitable uncertainty of information by using these ranges.

Project management (PM) is one of the prominent fields in business and industry. Every task of an organization can be imagined as a project, being a coordinated set of activities toward a common goal. One important aspect of PM is analysing the information related to the optimum balance among the project’s objectives. Each project is a combination of different activities, being connected to each other and having several success criteria, among which the time, cost and quality of the project completion are more significant, due to their significant effect on obtained results. Accordingly, the time might lead to delay and penalty which means more cost; and cost may be underestimated than real required funds. They both will lead to failure in project management. On the other hand, quality is the final key which confirms the success. The aim of a time-cost-quality trade-off problem (TCQTP) is to select a set of activities and an appropriate execution mode for each activity; the cost and time of the project is minimized while the project quality is maximized. The purpose of this paper is to present a model for TCQTP in which these parameters are approximated by grey numbers. Since there are various modes to accomplish each activity, the trade-off problem is formulated based upon a multi-objective integer grey programming model. Afterwards, a goal programming- based approach is designed to solve this model. The model's results provide a framework for the project manager to manage his/ her project successfully, in acceptable time, with the lowest cost and the highest quality. The main originality of the proposed model is the approximation of time, cost and quality parameters of activities mode with grey numbers and the development of a two phase goal programming- based approach to solve this problem. Ultimately, the proposed model is applied in two different cases and results are illustrated to clarify the outstanding capabilities of the model. DOI: http://dx.doi.org/10.5755/j01.ee.26.1.9930

Multiple criteria decision making methods have received different extensions under the uncertain environment in recent years. The aim of the current research is to extend the application of the MULTIMOORA method (Multiobjective Optimization by Ratio Analysis plus Full Multiplicative Form) for group decision making in the uncertain environment. Taking into account the advantages of IVIFS (interval-valued intuitionistic fuzzy sets) in handling the problem of uncertainty, the development of the interval-valued intuitionistic fuzzy MULTIMOORA (IVIF-MULTIMOORA) method for group decision making is considered in the paper. Two numerical examples of real-world civil engineering problems are presented, and ranking of the alternatives based on the suggested method is described. The results are then compared to the rankings yielded by some other methods of decision making with IVIF information. The comparison has shown the conformity of the proposed IVIF-MULTIMOORA method with other approaches. The proposed algorithm is favorable because of the abilities of IVIFS to be used for imagination of uncertainty and the MULTIMOORA method to consider three different viewpoints in analyzing engineering decision alternatives.

Real-world decision-making problems often consist in considering multiple and antithetic objectives. Therefore, multi-objective decision making (MODM) is a practical framework in implicational areas. In this paper, a fuzzy MODM problem is considered, where all of its parameters are defined fuzzily, and a solution inspired by multi-attribute VIKOR method is proposed. The proposed method tries to find fuzzy efficient solution for a problem by minimizing its combinational distance from an ideal and anti-ideal solution. This method can reveal the efficient frontier of the problem. Applicability of the proposed method is shown in an illustrative example and its application is summarized in an investment problem. Both examples show applicability of the proposed method.

The purpose of this paper is to develop current mathematical models of cost, time, and quality tradeoffs in conditions that parameters of project activities are estimated uncertainly by grey numbers. In some projects like construction projects, activities can be done within a much shorter time by increasing in the resources, while project's cost may rise at the same time. In such situations, managers are usually required to determine the best combination of cost, time, and quality parameters of the activities, although their information regarding these parameters is limited and rather incomplete. The greyness of these parameters in the proposed method can aid managers to deal with these conditions. The most important aspect of the proposed model is that it considers uncertainty of the project planning data in the form of grey numbers. A combination of fuzzy goal programming and grey linear programming is also developed to solve the proposed model. Finally, this model will provide the managers with a stronger ability to face with uncertainty in project management and planning. The application of this model is examined in a numerical example. As its major finding, the model determines an optimal range in which the project managers can respond to intrinsic changes that may occur in the parameters during a project.