Abstract

It is imperative for residents to have access to safe facilities after an earthquake. This ensures the safety and well-being of individuals while minimizing the risks posed by aftershocks. This research has used multi-criteria decision-making (MCDM) and network-based analysis to select and allocate emergency shelters (ESs). Several ESs are initially chosen as potential candidates. A weighting process is then used to evaluate various criteria, including proximity to the fault, fire stations, hospitals, main roads, the area of the ESs, and the population’s vulnerability. The centers are evaluated and ranked using the CRiteria Importance Through Intercriteria Correlation (CRITIC) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods. The Maximized Weighted Capacitated Coverage with a Radius (MWCCR) problem is used to address location and allocation issues for varying ESs using option rankings. The findings showed that increasing the number of centers does not always lead to a higher level of service delivery, assuming a consistent service delivery radius. The distribution of the centers is more crucial. Additionally, line density analysis is used to evaluate traffic conditions in the study area, assisting in finding areas with heavy traffic flow. When the radius of access for ESs is assumed to be small, the main roads bear less additional traffic, and with the increase of the radius, the amount of traffic on the main roads gradually increases. This is valuable information for emergency services following an earthquake.

Introduction

Earthquakes, as natural disasters, can cause extensive damage. Due to their potential to cause widespread damage to critical urban infrastructure, they are a significant challenge for large cities. Therefore, organizing crisis planning, including implementing policies that govern urban decisions, is very important to respond effectively to earthquakes [1], [2]. After an earthquake, one of the priorities is to quickly and safely evacuate citizens to protect them from potential hazards such as earthquakes, fires, and the spread of infectious diseases [3]. Emergency shelters (ESs) are safe places with necessary services for evacuating citizens during earthquakes [4]. Therefore, it is crucial to construct secure and appropriately located emergency evacuation facilities to mitigate risks following an earthquake. These facilities should have sufficient resources to support affected citizens [5]. Researchers face challenges in selecting the appropriate location for emergency evacuation due to multiple criteria. The city officials should allocate a budget to adapt the facilities and create a wide range of services in these centers. Therefore, it is crucial to determine the optimal location and quantity of ESs to minimize costs. Selecting these centers’ locations involves a location–allocation problem with two components. A positioning component determines the placement of ESs and outlines how these centers serve the population in the allocation section [6], [7]. Therefore, to determine appropriate locations for ESs, a solution must be selected to address the location allocation problem.

Various approaches have been used in studies on location allocation for ES planning. Some approaches have focused on allocating ESs to citizens in a single-objective manner, considering only one criterion, such as time or distance. Many studies commonly use single-objective techniques such as p-median, p-center, and maximum coverage. Multi-objective and hierarchical models have been used in some studies. Additionally, geographic information systems (GIS) methods, such as the Voronoi diagram, can be used [8], [9].

Conclusion

ESs are essential for promoting peace and ensuring the safety of individuals during earthquakes and potential aftershocks. These centers’ locating and coverage areas should be optimized to prioritize citizen safety and maximize accessibility. This study aimed to identify and allocate ESs in a part of Tehran’s 12th district. Potential ESs were initially selected based on specific criteria, including their proximity to fault lines, fire stations, hospitals, main roads, ES areas, and population vulnerability. The criteria were weighted, and the centers were ranked using the CRITIC and TOPSIS methods.

According to the results obtained using the CRITIC method, the criteria of distance from the hospital and fire department had the highest weight (0.19). In contrast, the area criteria had the lowest weight (0.12). The TOPSIS method has been used to rank the ESs by assigning weights to the criteria. The ranked centers were utilized to address the issue of location and allocation. In the location problem, priority was given to centers with higher ratings. The location and allocation issues have been resolved for different numbers of ESs. Based on the results, the service delivery radius is assumed to remain constant. Simply increasing the number of centers does not guarantee better service delivery. The distribution is crucial. When the coverage radius was set to 500 m, increasing the number of ESs decreased the occupancy percentage of the centers. This indicates that the centers were not fully utilized because they were more than 500 meters away from the residents. If the coverage radius is small, the distribution of centers becomes more significant. This requires considering multiple centers in different locations. In cases where the radius was set at 1000 and 1500 m, there was an increase in the percentage of service delivery and occupancy of ESs. The service coverage percentage within a 1500-meter radius was only about 60%, well below the desired value of 80%. It is possible to expand the distance to increase this case’s coverage. It is important to note that as the distance from centers increases, quick and easy access becomes more complex, which is crucial during times of crisis.

Abstract

     This research takes a novel approach to analyzing impact and benefit agreements (IBA) using multiple-criteria decision making (MCDM) and game theory. Local communities, which are often Indigenous communities, face with difficult decisions regarding the trade-offs of impacts vs. benefits from mineral resource development. Analyses of IBAs typically focus on their economic benefits but fail to consider environmental, socio-cultural, and other sustainability criteria. By not considering these criteria, current methods struggle to predict if an IBA is adequate or if it will be accepted. This research develops a model with MCDM that balances complex sustainability trade-offs for communities during mineral development negotiations. Bargaining positions of companies or impacted communities are also an essential, yet understudied factor in IBA analyses. Game theory is employed to show how bargaining positions can affect the compensation included in an IBA. In all, this research develops a model that can consider different criteria, value systems, and the implications of cooperation or competition to predict if an IBA will be accepted. This study provides recommendations, which can be applied other resource development projects which impact communities. The model shows the importance of flexibility in design, power dynamics in bargaining, cooperation, and knowledge sharing.

Introduction

     The mining industry is at a crossroads. Society’s growing demand for minerals continues to push for more mines, but many projects struggle to secure permits due to opposition from impacted Indigenous communities and other stakeholders. The continued growth of the mining industry impacts communities on countless socio-environmental levels, which are not easily accounted for during project evaluation. Impact and benefit agreements (IBAs) were developed to create collaborative solutions to balance the impacts and benefits of mineral development for communities. IBAs are contracts between impacted groups and project proponents that typically outline the benefits the community will receive, in terms of compensation and economic opportunities, as well as the strategies for impact mitigation (Gibson and O’Faircheallaigh, 2015). IBAs formalize a company-community partnership with the goal of reducing project delays and disruptions from protests, blockades, or legal opposition (Ali, 2003). The issue is that it is not well understood what exactly should be included in IBAs to balance the impacts vs. benefits of a project (Cascadden et al., 2021). There are several guidelines created for IBAs, e.g., Gibson and O’Faircheallaigh (2015), but there is a critical lack of formalized methods that can incorporate community values and predict if IBAs will be accepted and successful. The main questions of this research are: How can we predict if an IBA will be accepted? What are the main factors for a successful IBA? How can IBAs be better aligned to the wants, needs, and values of communities? And, what are the sustainability challenges with IBAs for mineral development projects? To better understand these questions, this research’s goal is to create a new method to analyze IBAs.

Conclusion and recommendations

     To summarize, the following list provides several key recommendations uncovered from this research for individuals looking to develop IBAs or predict if it will be accepted:

A project which provides alternatives which can trade-off between all important criteria, can make a project more likely to be accepted.

Before negotiations, bargaining factors should be analyzed to understand which group will potentially be at an advantage. The main factors–patience, knowledge, uncertainty, and power to make proposals–should be discussed and mediated.

Mineral policies should require proponents to provide flexible alternatives for all important criteria to communities.

Abstract

     The similarity measure in this paper is verified for Pythagorean fuzzy sets (PFSs). We point out that a similar measure for two PFSs is a Pythagorean fuzzy value (PFV). To calculate the similarity measure of two PFSs, it is logical that their similarity should be vague. Therefore, we introduce for the first time, as far as we know, the similarity measures for two PVFs is the same as PFV. For calculating PFV of similar measure, we first present the method for calculating Pythagorean similar measure for two PFV by using T-norm and S-norm and then extend it to calculate similar measure for two PFSs. Finally, a numerical example is provided to illustrate the validity and applicability of the presented decision-making method.

Introduction

     In many multi-criteria decision making (MCDM) problems, the decision maker has to use vague (qualitative) values to decide. In the face of qualitative values, for the first time, Bellman and his associates introduced the theory of fuzzy sets (FSs) using mathematical modeling. In making decision with fuzzy sets, the decision maker considers only the degree of correctness of the option and cannot take into account the degree of incorrectness. Continuing this trend, Atanassov in [1] introduced the intuitionistic fuzzy sets (IFSs) theory which is a generalization from FSs which included both the degrees of membership and non-membership.

     Atanassov and Gargov [2] presented an interval valued IFS (IVIFS) as a generalization and an intuitionist fuzzy sets (IFS) that makes use of interval value instead of a real number.

Conclusion

     We have successfully introduced a new definition for similarity measure for Pythagorean collections, which is also a PFV. We define the similarity measure of the two PFVs with a PFV, using T-norm, and S-norm and we generalized it to PFS. This method is used for decision making with Pythagoras value, using similarity measure. The advantages of this method include:

     Calculating the similarity size in the form of PFSs takes more information into decision making, and we lose a lot of information, if converted to a real number.

Abstract

     The weight and reliability of an individual assessment are two important concepts considered in the evidential reasoning (ER) approach. Through analyzing the existing studies on the combination of individual assessments with both their weights and reliabilities considered in the ER context, their deficiencies are identified in accordance with two principles. One principle is developed in the situation where a specific individual assessment is fully unreliable and the other is developed in the situation where all individual assessments are fully reliable. To address the deficiencies, this paper proposes a new method. In the method, a combination process that takes into account both the weights and reliabilities of individual assessments simultaneously is developed to generate the overall assessment. It is theoretically proven that the combination process satisfies the two principles. Three ways are designed to help a decision maker to flexibly provide individual assessments and determine their reliabilities. A strategic project evaluation problem for an enterprise located in Changzhou, Jiangsu, China is analyzed using the proposed method as a case study to demonstrate its validity and applicability. These are highlighted by its comparison with two existing methods.

Introduction

     When facing real world problems or challenges, people usually need to take into account multiple diverse or conflicting perspectives to make satisfactory decisions. To facilitate the analysis of problems, multiple criteria decision making (MCDM) methods have been applied (Hafezalkotob et al., 2019; Liao et al., 2020; Ma et al., 2018). Representative applications include the selection of sustainable suppliers (Girubha et al., 2016), the evaluation of new product pricing strategies (Baykaso ˘glu et al., 2017), the selection of socially responsible investments (Bilbao-Terol et al., 2016), the evaluation of logistics performance in hospitals (Longaray et al., 2018), and the evaluation of photovoltaic cells (García-Cascales et al., 2012). In studies on MCDM, criterion weights are commonly considered although their meanings may be different. They are generally used to make trade-offs among criteria (Butler et al., 1997, 2001).

     There is another important concept associated with each criterion as implied in the work of Yang and Xu (2013), which is reliability. Reliability is a very common concept usually associated with specific meanings in different contexts. For example, in the context of system, reliability is evaluated to improve system performance or safety (Wang et al., 2011); while in the context of underground structures, reliability is measured by the probability that the structures have been safe over a period of time (Wang & Fang, 2018). Differently, in the context of MCDM, the reliability of a criterion means the reliability of the individual assessment on the criterion. When all data are available and the judgments of a decision maker are not explicitly required, most MCDM methods can find a solution by comprehensively considering all data. However, when the judgments of a decision maker are necessary, many MCDM methods may be able to generate a solution that is consistent with what is anticipated by the decision maker. This paper focuses on the second type of situations. In such cases, the reliability of an individual assessment should be explicitly considered in the analysis of the MCDM problems. Unfortunately, in existing studies, criterion weights are usually considered to make tradeoffs among criteria under the assumption that all individual assessments are fully reliable and thus reliabilities of criteria are not explicitly considered in MCDM processes. This assumption may not be valid in many practical cases and may result in a solution that is not satisfactory or acceptable to a decision maker. An example of breast cancer screening is provided to demonstrate this.

Conclusions

     To focus on MCDM problems modeled by belief functions with the consideration of the weights and reliabilities of individual assessments, the deficiencies of existing studies in two extreme situations and general situations are analyzed. To overcome the deficiencies, a new MCDM method with belief functions is proposed. In the method, a new process is designed to combine individual assessments with their weights and reliabilities. The process is theoretically proven to be correct in two extreme situations and is numerically demonstrated to be correct in general situations. To make the new process applicable, three ways are designed to help a decision maker flexibly provide individual assessments and correspondingly obtain their reliabilities. The generation of a solution is then presented. The proposed method is applied to solve the SPE problem for an enterprise that primarily provides high-quality gear boxes for high-speed trains. Through the data in the SPE problem, the main contributions of the proposed method are highlighted by its comparison with existing studies.

Abstract

     In the last decades, the art and science of multi-attribute decision-making (MADM) have witnessed significant developments and have found applications in many active areas. A lot of research has demonstrated the ability of cognitive techniques in dealing with complex and uncertain decision information. The purpose of representing human cognition in the decision-making process encourages the integration of cognitive psychology and multi-attribute decision-making theory. Due to the emergence of research on cognitively inspired MADM methods, we make a comprehensive overview of published papers in this field and their applications. This paper has been grouped into five parts: we first conduct some statistical analyses of academic papers from two angles: the development trends and the distribution of related publications. To illustrate the basic process of cognitively inspired MADM methods, we present some underlying ideas and the systematic structure of this kind of method. Then, we make a review of cognitively inspired MADM methods from different perspectives. Applications of these methods are further reviewed. Finally, some challenges and future trends are summarized. This paper highlights the benefits of the synergistic approach that is developed based on cognitive techniques and MADM methods and identifies the frontiers in this field.

Introduction

     Real-world decision-making problems are often too complex to be considered through a single criterion. In order to solve problems with multiple attributes, multi-attribute decision-making (MADM) methods are developed, which signifcantly enhance the ability of decision-making methods. As a cognitive process, MADM refers to selecting the optimal solution by evaluating alternatives in the presence of multiple attributes. The number of alternatives for MADM problems is predetermined and limited. Basically, MADM methods can be roughly grouped into two categories [1]: (1) Outranking techniques. The outranking methods are based on pairwise comparison of alternatives, like ELECTRE (Elimination et Choix Traduisant la Realité in French, Elimination and Choice Expressing the Reality) [2] and PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluations) [3]. (2) Multi-attribute utility and value theories. This kind of method usually assigns a utility to each alternative and includes UTA (utility additives) [5], AHP (analytic hierarchy process) [6], ANP (analytic network process) [7], MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique) [8], etc. There is a growing body of literature that recognizes the importance of MADM methods in many fields of human life, such as healthcare [9, 10], transportation [11–14], manufacturing [15–18], and business [20, 21].

Conclusions

     The emergence of cognitively inspired MADM methods enriches the theoretical framework in MADM and greatly promotes the development of intelligent decision-making. It presents excellent modeling ability in processing complex information, which makes it of signifcant importance to MADM both from theoretical and practical points of view.

     In this paper, we have gone through the recent contributions about cognitively inspired MADM methods and attempted to provide a comprehensive review in this feld. Firstly, some statistical analyses of published papers regarding cognitively inspired MADM have been unfolded from two aspects: the development trend and the distribution of related publications. We have seen a steady increase in the number of academic papers in this feld. As to this fact, more investors have their sights on the cognitively inspired MADM methods in recent years. After that, the system architecture of cognitively inspired MADM has been illustrated. Then, a comprehensive overview of diferent types of cognitively inspired MADM approaches has been provided, which concludes the contributions of these methods to modern decisionmaking. After analyzing the theoretical knowledge, practical applications have also been summarized, which concludes that cognitively inspired MADM methods make great efects on practical applications. We have ended by discussing some challenges and future trends in this feld.

Abstract

     Access to healthy drinking water is vital to human health and development. Bottled water consumption has been on the rise in recent years. As several chemical and bacteriological parameters affect bottled water quality, it is difficult to choose the highest-quality bottled water. Numerous studies have proposed the use of multiple-criteria decision-making (MCDM) methods to overcome this problem. Herein, the two-stage fuzzy analytic hierarchy process (FAHP) and technique for order preference by similarity to ideal solution (TOPSIS) method were adopted to rank different brands of bottled water. The FAHP approach allows working at the intervals of judgment rather than absolute values. TOPSIS is a technique for ordering performance based on its similarity to the ideal solution. An expert panel selected and classified the criteria and sub-criteria. A pairwise comparison questionnaire was then developed, and the weights of the criteria and sub-criteria were assigned by water quality experts. The data on the quality of different brands of water were collected from the Iranian bottled water database. The final data analysis and weight determination of each parameter were performed in Excel and R software Programs. Finally, the CCi (value of closeness coefficient) and rank of 71 bottled water brands were calculated, and the best brand was introduced. Among the selected criteria, carcinogenic chemical compounds with the weight of 0.368 were the most important compound in ranking bottled water brands, followed by bacteriologic, pathogenic chemical compounds, chemical compounds important in terms of toxicity, nutritious chemical compounds with a low toxicity level, chemical compounds related to esthetic effects, and chemical compounds without health effects, respectively.

Introduction

     A challenge currently faced by developing countries is the lack of access to healthy drinking water (Abuzerr et al. 2019; Cobbina et al. 2015). Based on the World Health Organization’s (WHO) report, about 663 million people worldwide do not have access to healthy drinking water (WHO 2017). The increased population growth, a lack of healthy drinking water, and the public opinion about good taste, health, and appropriate quality have increased bottled water consumption. This rise has been considered in the past three decades, with the highest consumption being reported in developing countries of Asia and South Africa (Hu et al. 2011). The bottled water sale rate was $198.50 billion in 2017, a value which is estimated to reach $307.2 billion by 2024 (Doria 2006). Therefore, access to healthy drinking water is vital to human health and development (Fisher et al. 2015).

     Natural processes (erosion) and anthropogenic activities (electroplating, metal smelting, and chemical industries) are the main sources of pollutant entrance into the water. Although a few heavy metals are essential to human health, their excess amount can have negative efects such as anemia, renal dysfunction, cancer, and brain damage (Chowdhury et al. 2016; Gharibi et al. 2012; Qu et al. 2020; Qu et al. 2021a, b; Rezaee et al. 2015; Zhang et al. 2021). The existence of numerous parameters afecting water quality complicates bottled water quality assessment and ranking and decisionmaking about the purchase of the best and highest-quality brand. Therefore, there is a dire need for precise and logical techniques for accurate and scientifc decision-making. To this end, studies have proposed various methods for choosing the best option and making the decision, among which MCDM methods have received considerable attention owing to their numerous advantages (Kou et al. 2014; Mulliner et al. 2016).

Conclusion

     The quality assessment and selection of the best bottled water brand are difcult due to the efect of various physical (temperature and turbidity), chemical (heavy metals, anions, and cations), and bacteriological (Pseudomonas and coliforms) parameters on water quality and the existence of numerous brands in the market. Herein, by using the MCDM method (FAHP-TOPSIS), the quality of 71 bottled water brands in the Iranian market was ranked. The application of MCDM approaches in various sciences indicates these methods’ strong capability in evaluating problems that possess multiple criteria. These methods accurately assess bottled water quality and aid the customer in selecting a higher-quality brand. They can, therefore, be adopted to create competition among manufacturers to produce higher-quality products. In this study, the grouping and weighting of elements were based on the opinions of Iranian experts and by taking into account the local conditions of Iran. For global applications, a comprehensive model can be proposed for water quality assessment by considering other chemical and bacteriological parameters afecting water quality and with the participation of international experts from other countries.

Abstract

     The rate at which buildings are renovated across Europe is expected to increase in the upcoming years. However, selecting renovation solutions for residential buildings is still a challenging task due to the participation of multiple stakeholders, lack of clear decision-making procedures, and diverse effects resulting from the renovation alternatives. Most of the existing approaches do not consider multiple stakeholders and focus mainly on weighting criteria and performing simulations to quantify alternatives’ performance. Therefore, this paper presents a more complete Multi-criteria decision-making (MCDM) framework to support the decision-making process in renovation. To illustrate and validate the framework, it is implemented in two case studies based on a five-story building located in Spain. Each case includes five stakeholders. Two weighting settings are analysed to study the robustness and sensitivity of the proposed approach. The main contributions correspond to: 1) an MCDM enabling the participation of multiple stakeholders using the Pairwise comparison method; supporting the setting of objectives and criteria, promoting a comprehensive evaluation of the alternatives; and facilitating the integration of criteria weights and alternatives’ performance through the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method; and 2) the validation of the proposed framework, especially the implementation of TOPSIS to evaluate renovation alternatives. Promoting the setting of objectives and criteria can enable discussions and encourage a broader and more complete analysis of renovation alternatives. In the two case studies, stakeholders included social aspects and assigned in total weights around 20% to this category. The Pairwise comparison and TOPSIS methods integrated the perspectives of stakeholders with different interests and the alternatives’ performance to obtain a shared view of the renovation and a final ranking of the alternatives to differentiate them accordingly and make a better-informed decision.

Introduction

     In Europe, building renovation rates are expected to increase due to the large number of existing buildings that require to be renovated. Around 75% of existing buildings are considered inefficient according to current standards [1]. 85–95% of the existing building stock will still be standing in 2050 [2]. Typically, in residential renovation projects, complex governance and ownership structures, legal structures, and other challenges impact the initiation and execution of the renovation activities [3]. Some of these aspects lead towards complex decision-making processes to select the final renovation solution. Strategies and tools need to be developed to support stakeholders to overcome these barriers.

     In the building renovation field, there is a lack of consensus regarding the main criteria, applicable renovation methodologies, and tools to support the decision-making process [4]. Despite the involvement of multiple stakeholders in such projects, most of the existing approaches are limited to cases where the decision is made by a single stakeholder. Nevertheless, in these projects, additional stakeholders such as tenants and building managers may get involved [5], influencing the decision-making process. Around 49% of the housing stock in Europe corresponds to multi-family units, and the average share of rented units is 30%, reaching levels around 70% in countries such as Germany [3]. Therefore, a decision-making strategy in the context of residential renovation should support the participation of multiple and diverse stakeholders, which may have different rights and obligations [6].

Conclusion

     Residential renovation projects encounter different scenarios and particularities that require a better-structured decision-making approach to select suitable renovation solutions that fulfil the requirements of the project and stakeholders involved. This paper presented an approach that enables the participation of multiple stakeholders through the Pairwise comparison method, supports the objectives and criteria setting based on a predefined comprehensive decision tree and complementary activities, and integrates the criteria weights and alternatives’ performance through the TOPSIS method. Firstly, the implementation of the Pairwise comparison allows gathering the preferences of stakeholders with different interests to obtain a gathered perspective of the problem. The first weighting setting showed that following the perspective of only one of the stakeholders can lead to different results in the ranking of the renovation alternatives. Secondly, promoting the setting of objectives and criteria can enable discussions and encourage a broader and more complete analysis of renovation alternatives, including social-related issues. In the two case studies, besides economic and environmental aspects, stakeholders selected social and technical elements to evaluate the renovation alternatives, assigning in total weights around 20% to this category. Since each renovation project encounters specific requirements, the flexibility of the proposed framework to include new goals and criteria in the decision tree proved to be relevant. Stakeholders included new criteria according to their requirements. Thirdly, the inclusion of the TOPSIS method enabled the integration of the stakeholders’ perspective and alternatives’ performance to make a better-informed decision, especially in complex cases where the effects resulting from the different renovation alternatives are not easy to differentiate. Different weighting settings showed that TOPSIS allows considering the importance of the criteria in combination with the alternatives’ performance to differentiate renovation alternatives and rank them accordingly to facilitate the analysis by the stakeholders involved. Finally, even though the proposed approach was implemented in two specific cases, it can be applied in other scenarios including single or multiple stakeholders, playing different roles in the decision-making process.

Abstract

     To succeed, a firm essentially needs to take the right amount of risk. Thus, the great significance of risk management has attracted many researchers to focus on how to implement enterprise risk management (ERM) systems most effectively. Generally, smaller entrepreneurial firms have to cope with this challenge more informally. Most manufacturing small and medium-sized enterprises (SMEs) are family companies; as a result, family dynamics greatly impact how such companies do business. The q-rung orthopair fuzzy set (q-ROFS) provides a wide window for the preference elicitation of decision-makers (DMs). Inspired by the advantages of the q-ROFS, in the current paper, a novel decision framework, the q-ROF-entropy-rank sum (RS)-additive ratio assessment (ARAS), called the “q-ROF-entropy-RS-ARAS” approach, is developed. The q-ROF-entropy-RS approach is applied to compute the weights of critical success factors (CSFs) for dynamic ERM in SMEs, and the q-ROF-ARAS model is used to assess enterprise preferences. An empirical case study is conducted to evaluate the CSFs for dynamic enterprise risk management in SMEs. Additionally, the comparison and sensitivity investigation are carried out to show the superiority of the developed framework.

Introduction

     In the current world, which is becoming increasingly digital, companies face several challenges in establishing and/or sustaining a competitive advantage in the market (Ganju et al., 2016; Rocha et al., 2016). Compared with conventional firms, responsive firms operate differently. Such companies are normally acquainted with dynamic, exponential, and disruptive thinking; through these experiences, they are made ready to adopt exponential growth (Ismail et al., 2014). How a company is structured and operates demonstrates its “Enterprise Risk Management (ERM)” system. As a result, to effectively manage risks, there is a need for constant alignment between the enterprise and its risk function (Knight, 1921), which could be achieved by incorporating ERM into the firm’s decision-support processes. ERM, as a decision support tool, could be effectively used by every company (with a focus on organizational processes) to manage the risks that may arise during business operations in the real environment (ISO, 2018). ERM is defined as a “process that combines the organization’s entire risk management activities in one integrated, holistic framework to achieve a comprehensive corporate perspective” (ISO, 2018). Currently, many firms use different ERM frameworks. Two popular risk frameworks are the ISO31000 and the “Committee of Sponsoring Organizations of the Treadway Commission (COSO)”. The COSO helps firms enhance the quality of their model in the management of risks well to satisfy the demand of an evolving business environment. By adopting the COSO, companies would be capable of further understanding the risks that affect the outcome of their business strategies and goals. ISO3100 is presently used as a best practice in risk management; it also incorporates the best practices of the COSO (ISO, 2018).

Conclusions

     Business communities and scholars working in this domain have become increasingly interested in ERM. Some previously-conducted studies have reported that despite the fact that ERM has received positive attention, it has not been extensively implemented yet. The literature still lacks research into the determinants of ERM and ERM CSFs. Most past studies have concentrated on issues related to large enterprises and ignored SMEs. Accordingly, the current study proposes an inclusive framework for the CSFs of ERM adoption in manufacturing SMEs. To analyze, rank, and evaluate the CSFs for dynamic ERM in SMEs, this study introduced an integrated q-ROF-entropy-RS-ARAS. To rank critical success factors for dynamic ERM in SMEs, the q-ROF-entropy-RS is utilized for determining the integrated weight values. Afterward, the q-ROF-ARAS is used to prioritize different enterprises with the CSFs for dynamic ERM in SMEs in this process. To show the usefulness of the presented method, a case study is discussed on the critical success factors identified to be effective in applying dynamic ERM in SMEs. The outcome of the assessment shows that the enterprise-IV (O4) with a utility degree of 0.7675 is the optimal choice for evaluating the CSFs for dynamic ERM in SMEs. To validation of the results of this study, a comparison is discussed between the performance of the presented approach and that of extant models. Finally, sensitivity analysis and comparison with some extant models have been presented to validate the robustness and stability of the obtained outcomes.

Abstract

     A tolerance framework is developed to address a group multiple criteria ranking problem with indirect preference information, which is referred to as the interaction, importance and tolerance of criteria as well as pairwise comparisons among alternatives and criteria. Choquet integral preference model is employed to capture the interaction, importance and tolerance of criteria, all of which are specific to decision makers (DMs). Some mandatory/sufficient requirements concerning criteria which are global or local, also called the tolerance attitudes of DMs, are quantified as tolerability constraints. Preference disaggregation analysis is extended to solve this type of tolerability constraints for preference elicitation. Confronted with the inconsistency issue (the feasibility of the whole preference constraints translated from indirect preference information), cause oriented strategy and consequence oriented strategy are established by regression-based mixed 0–1 integer linear programs with the objectives of the most credible minimal inconsistent preference constraints and the most credible maximal preference constraints in the context of group decision making. Considering a wide range of the minimal unsatisfied subsets of preference constraints responsible for the inconsistency and the maximum satisfied subsets of preference constraints as a consistent result, to reach a robust decision, stochastic multicriteria acceptability analysis (SMAA)-like simulation analysis is generated to examine the whole instances of compatible preference models in the modified feasible preference polyhedron and compute the result in a probabilistic form. Simulation experiment is conducted to investigate the influence of global tolerance attitudes of DMs on preference elicitation in conservative and radical scenarios. Finally, the application of the proposed approach to a credit ranking of small and medium-sized enterprises (SMEs) and the comparison analysis with objective methods are presented and discussed for the effectiveness of the proposed tolerance framework.

Introduction

     Many real-world decision problems in different fields can be formulated as multiple criteria decision making (MCDM) as the performance of alternatives can be decomposed as the evaluation of alternatives on considered criteria and ranked by the comprehensive score which is a straightforward intuition for decision makers (DMs) to comprehend. The preference model in MCDM would be paid more attention to the property that is consistent with observable properties of human decision process (i.e., intuitive reasoning, common sense, and expert knowledge), otherwise it would deteriorate a justifiable decision. The theory of fuzzy measures and integrals Liginlal and Ow (2006) has emerged to characterize the preference of DMs with the realistic hypothesis about preferential dependence among criteria and give the opportunity to represent and interpret the typical human decision process, which is such a predominant character that can address numerous practical preference modelling.

     The DMs have distinguished aggregation behaviors in context of group MCDM, also called the tolerance attitudes of DMs in some literatures. From a mathematical perspective, the tolerance attitudes of DMs are equivalent to the tolerance (or intolerance) of criteria represented by the aggregation operator (Li, Yao, Sun, & Wu, 2018). In a strategic investment decision problem, when searching for most qualified candidates among prospective alternatives, every candidate failing at most k criteria would be rejected. It implies k-intolerance attitudes of the DMs which can be perceived as a selection policy. In the field of fuzzy aggregation operator field, ordered weighted averaging (OWA) operator was studied which used the global tolerance of criteria to measure the optimism degree of DMs (Kim and Ahn, 2018, Zeng et al., 2018). Based on the k-tolerance (or k-intolerance) properties of the Bonferroni mean aggregation operator (Beliakov & James, 2013), Dutta, Figueira, and Das (2019) studied orness measure to define the or‐like degree of the Bonferroni mean and its variants. Considering non-additive value function, previous researchers constructed the optimization model using fuzzy measure to capture tolerance attitudes required from DMs without any post optimality analysis (Li et al., 2018, Yao et al., 2018). It is doubted that the decision from the inferred preference model is robust in case of the existence of the multiple feasible near-optimal solutions. As noted by Dujmović and Larsen (2007), the requirements (or expectations) on criteria combining by preference model cannot be neglected during preference aggregation. Subsequently, concise mathematical formulas for them (Hudec and Mesiar, 2020, Marichal, 2004) were defined to express a global or local tolerance degree of the DMs.

Conclusion

     In this paper, under a robust perspective, we present a tolerance framework to address a group multiple criteria ranking problem with indirect preference information such as the interaction, importance and tolerance of criteria as well as pairwise comparison among alternatives and criteria. Based on indirect preference information, Choquet integral preference model is elicited to capture the interaction, importance and tolerance of criteria for the final decision. With respect to the tolerance attitudes of DMs such as the mandatory/sufficient requirements on criteria for specific alternatives, they are quantified as tolerability constraints for preference elicitation. Once inconsistency issue (the feasibility of the whole preference constraints) in preference constructive learning process occurs, in the tolerance framework, two developed strategies including cause oriented strategy and consequence oriented strategy are applied. Then identify the minimal unsatisfied subsets of preference constraints responsible for the inconsistency or the maximum satisfied subsets of preference constraints as a specific set of consistent preference information by regression-based mixed 0-1 integer linear programs. By following the idea of treating all possible sets of preference parameters in line with indirect preference information, SMAA-like simulation algorithm is constructed to generate the rank result in the probabilistic form, which is used to generate a solution considered by exploring the whole instances of the compatible preference model. The proposed method can deal with indirect preference information involved with not only less cognitive effort but also the tolerance attitudes on criteria for the DMs, which has been paid insufficient attention in the literatures. From the illustration and application, it suggested that the proposed unified framework for MCDA has two characteristics: expressiveness of the underlying preference model which can reconstruct indirect preference information provided by the DMs and robustness of the final result which address uncertainties and imprecision observed in the actual decision support processes.

Abstract

1 Introduction

2 Literature review

3 Methodology used in research

4 Problem formulation

5 Proposed research methodology

6 Case study on ERP consultant selection problem

7 Sensitivity analysis

8 Discussion and conclusions

Declarations

References

Abstract

Enterprise Resource Planning (ERP) projects are risk prone due to software complexity, budget overruns, long duration, poor project delivery and a broad range of organization transformation processes. Companies are hiring experienced external consultants to achieve successful implementation of ERP system. Proper selection of ERP consultant is challenging task for any top management of organization because consultant fees accounts a major portion of project cost and this problem may be considered as Multi criteria decision-making problem. This article presents the hybrid approach of Fuzzy Analytical hierarchy process (F-AHP) and COPRAS-G in selection process of ERP consultants. F-AHP is used to obtain the weight of selection criteria and COPRAS-G is used to get the final ranking of consultants based on utility degree. The proposed model is illustrated with a numerical example whose data has been collected from survey in Indian industries. Finally, sensitivity analysis was performed to determine the robustness of the approached. The result of F- AHP highlights that reputation, ERP project experience and partner of ERP vendor and cost is an important selection criterion for selecting consultant and rank reversal problem has been greatly reduced by COPRAS-G. This proposed hybrid technique is quite flexible and provides efficient decision making in the selection of an ERP consultant.

1 Introduction
Companies are investing huge amount in information technology systems so as to meet the challenges of business organizations and smooth flow of information in the industries. ERP is an advanced information technology tool which supports business functions and information flow of an organization in a single software system. Shadi et al. (2019) has defined ERP is an Information Technology (IT) business solution which enables Organizations and their Stakeholders for management of project effectively & efficiently throughout the lifecycle of project. Thus, ERP system is amalgamation of business, technology and human resource. Implementation of ERP system has been considered among the most challenging investment projects due to the high costs involved, complexity and higher duration (Yusuf et al. 2004). Continuous high failure rates of ERP projects are major concern in recent years. Aloini et al. (2007)

Green marketing strategy has increasingly become a sustainable business operation goal, and Green Marketing Audit (GMA) is an effective measurement tool. In order to satisfy the green marketing quality assurance, the tight integration of green marketing missions, competition, stakeholders’ requirements, and business activities are necessary. This study focuses on the establishment of green marketing audit criteria and priority sequence, using Multiple Criteria Decision Analysis (MCDA) to combine the Analytic hierarchy process (AHP) and Decision Making Trial and Evaluation Laboratory (DEMATEL) techniques. The major contributions of this study are as follows: (1) the proposed model provides a new practical architecture of GMA, which incorporates the experience and judgment of professional experts, and satisfies the needs of existing internal auditing operations; and (2) the GMA evaluation shows that linking the green marketing activities and firm performance contributes to the development of green marketing strategy management in Taiwan.

Introduction

Sustainable city development is an increasingly important focus of government policy, where the alignment of climate change and low-carbon strategy implementation are the key challenges (Mi et al., 2019). In the complex business world, traditional business operation strategies are insufficient to face increasingly strict environmental policies, stakeholder requirements, and the competition for innovation products/services. Implementing internal green practices and introducing monitoring mechanisms into firm operational processes can contribute to environment performance (Li et al., 2018). Regarding internal green marketing actions, Papadas et al. (2018) indicated that strategic green marketing and internal green marketing actions have positive influence on competitive advantage. The success of green marketing strategy depends on the effective implementation of green marketing activities. Although many approaches and checklists of marketing audit have been proposed (Herhausen, Egger and Oral, 2014; Morgan, Clark and Gooner, 2002), the main focus is limited to the audits of sales and collection (Taghian and Shaw, 2008). Given the impact of growing consumption on the environment, the number of companies developing green products has been rapidly increasing, and consumers have shown an increasing interest in these green products (Dangelico and Vocalelli, 2017).

In this work we present a method for risk-informed decision-making in the physical asset management context whereby risk evaluation and cost-benefit analysis are considered in a common framework. The methodology uses quantitative risk measures to prioritize projects based on a combination of risk tolerance criteria, cost-benefit analysis and uncertainty reduction metrics. There is a need in the risk and asset management literature for a unified framework through which quantitative risk can be evaluated against tolerability criteria and trade-off decisions can be made between risk treatment options. The methodology uses quantitative risk measures for loss of life, loss of production and loss of property. A risk matrix is used to classify risk as intolerable, As Low As Reasonably Practicable (ALARP) or broadly tolerable. Risks in the intolerable and ALARP region require risk treatment, and risk treatment options are generated. Risk reduction benefit of the treatment options is quantified, and costbenefit analysis is performed using discounted cashflow analysis. The Analytic Hierarchy Process is used to derive weights for prioritization criteria based on decision-maker preferences. The weights, along with prioritization criteria for risk reduction, tolerance criteria and project cost, are used to prioritize projects using the Technique for Order Preference by Similarity to Ideal Solution. The usefulness of the methodology for improved decision-making is illustrated using a numerical example.

Introduction

In the last decade, the management of physical assets has emerged as a crucial business function for companies operating in asset intensive industries. Furthermore, the complex nature of modern engineered systems has led to the need for physical asset management as a discipline (Hastings 2015). Complex systems, composed of many interacting and interdependent components are increasing the likelihood of extreme, rare and disruptive events (Komljenovic, et al. 2016). As such, it comes as no surprise that the ISO 55000 Asset Management series of standards emphasize the need for risk-informed decisions (International Standards Organization 2014). Risk assessment in the asset management context requires the identification of what can go wrong (e.g. unexpected asset failures), characterization of the likelihood and consequence of such events, and comparison of the likelihood and consequence against risk tolerability criteria to determine risk treatment options (International Standards Organization 2018). Treatment options give rise to potential asset investments that must be prioritized while taking into consideration several factors (e.g. cost, return on investment, risk tolerability, etc.). In this work we present a framework and methodology for quantitative prioritization of risk-informed asset management projects using multi-criteria decision analysis. Several methodologies exist in the literature for multi-criteria decision making (MCDM), sometimes referred to as multicriteria decision aiding or multi-criteria decision analysis (MCDA). We use the acronym MCDM/A to consider both.

1- Introduction

2- Literature review

3- Methodology

4- MCDM for boxboard production

5- Sensitivity analysis

6- Conclusion

References

Abstract

Papermaking is a capital-intensive industry that requires a high consumption of plant fibers, energy, and water. Previous sustainability assessments of papermaking industry primarily focused on separate evaluations for multiple criteria without the integration for criteria and could not compare the overall priority of the production alternatives. The life cycle sustainability for the most representative boxboard production is analyzed as a case study in this work. Life cycle water consumption, energy consumption, greenhouse gas emissions, and internal costs are selected as the assessment criteria. The two multi-criteria decision-making methods are applied to integrate the above criteria to obtain the sustainability sequence under different production pathways. When the papermaking enterprises are regarded as decision-makers, the alternative using waste paper as raw material to manufacture boxboard is the most sustainable, following by mixed fiber. The sustainability sequence of the alternatives using wood and straw as raw materials is controversial due to the different calculation models. Changing the proportion of raw materials and the criteria weights might adjust sustainability sequence of the alternatives.

Introduction

Papermaking is a capital-intensive industry with a long industrial chain, it contributes to about 3% of global end uses of energy (Ma et al., 2018), 2% of global industrial carbon emissions (Bajpai, 2016), and 40% of global industrial wastewater (Ashrafi et al., 2015). In China, the rapid development of papermaking industry brings extensive energy demand and high emission generation, the sustainable development of papermaking industry has received widespread attention (Ingwersen et al., 2016; Wang et al., 2016; Corcelli et al., 2018). As the largest paper producer around the world, the papermaking industry in China is surrounded by several challenges: the energy structure dominated by coal leads to significant emissions of greenhouse gases (GHG) (Wang et al., 2016); the technology level varies greatly and too much capital is invested for unit product in some enterprises; low forest cover (Zhu et al., 2017) and policies on restricting deforestation prompt that papermaking industry has to import large quantities of wood and pulp board, resulting in increased cost and material replacement. Therefore, in order to achieve sustainable development of the papermaking industry, it needs to overcome environmental, economic and social obstacles. Since 2007, the production of boxboard has headed the list in China’s papermaking industry for 11 years and it accounted for 21.4% of the total paper production in 2017. Boxboard papermaking industry is still in a rising state with the development of packaging and logistics industries (CPA, 2017). The boxboard papermaking enterprises are widely distributed in every province in China, most of them use recycled waste paper to produce non-deinked pulp to manufacture boxboard, some sorts of high-grade boxboard are manufactured by using natural wood pulp cooked from wood chips or using natural straw pulp, the latter is mostly distributed in the major straw-producing area in north China. Besides, mixing virgin pulp and waste paper pulp as a raw material is also a common solution for the production of boxboard. Variety of production pathways have a different effect on the sustainability criteria for papermaking industry. The industrial process assessment (Wen et al., 2016; Li et al., 2015) and life cycle analysis (Man et al., 2018a; Ewijk et al., 2018) of papermaking industry analyzed environmental and economic criteria from different boundaries.