Journal of Multi-Criteria Decision Analysis最新文献

The decision-making process in healthcare systems, especially in the area of surgical management is generally considered to have a low level of transparency; hence, effective decision-making plays a vital role in the case sector. Non-union of a fracture is dependent on many critical causative factors and in the past healthcare management studies, several research activities highlighted the influence of various causative factors on non-union. However, none of the studies neither tried to prioritise the factors nor identified the interrelationship between them. In the present research, through literature review and opinions of seven surgeons' 10 causative factors of non-union were shortlisted and they were analysed and modelled by a multi-criteria decision-making tool. The total interpretive structural modelling (TISM) methodology was used for identifying the mutual relationships among the causative factors and for developing a hierarchical structure. Also, the MICMAC approach was employed to identify the significant/dominant factors. The results of the TISM approach and MICMAC analysis revealed that ‘Alcohol abuse’ was found to be the most significant causative factor followed by ‘use of tobacco’, and ‘inappropriate dynamisation’ was found to be the least important. This study intends to guide the medical practitioners and healthcare managers in understanding the mutual influence of the causative factors and prioritisation of the same. Further, it helps them to carry out the surgical management effectively.

A primary reason for the failure of renewal plans for the heritage of urban areas is ignorance of the risk factors of tourism. Urban heritage sites are valuable tourism resources and focus on tourism activities. These sites are affected by risks and negative events. Assessing tourism risks requires an in-depth knowledge of the current situation. Thus, in order to reduce the risk of tourism on urban heritage, it is necessary to assess the risk of tourist destinations. This study assesses the urban heritage of central districts in Tehran with an emphasis on tourism risk as a real case study. This study provides an in-depth review of the dimensions and criteria for evaluating tourism risks from the perspectives of social culture, environment, finance, safety and security. Fourteen criteria developed on the basis of the fuzzy decision-making trial and evaluation laboratory (FDEMATEL) method are adopted for this assessment to construct the fuzzy influential network relation map and find the fuzzy influential weights; this is known as the DEMATEL-based analysis network process (called DANP). The hybrid modified fuzzy VIKOR method is adopted to evaluate and reduce the tourism risk towards for closing the gap zero. Finally, an empirical case of Tehran city illustrates the availability and effectiveness of the proposed methods. The results revealed that safety and security risks have the greatest influence. The remaining dimensions are sociocultural, financial, and environmental risks. According to the model and the results of the risk assessment in tourism, this method is a reasonable solution for the assessment and risk analysis in real-world problems. The proposed method can be a useful tool for managers in tourism and urban planning.

Various multicriteria sorting methods have been proposed in the literature to assign the feasible alternatives into predefined categories. We consider here problems involving a set of totally ordered categories representing different achievement levels in the satisfaction of criteria. As in many existing methods, the assignment rule of an alternative to a category is based on the comparison of its performance vector to reference profiles defining lower bounds of the categories. Within this standard setting we address a new problem that consists in finding how to modify a given solution, within a combinatorial set of alternatives, to upgrade it in the upper category (or higher) at minimum cost. We also consider the problem of identifying the sequence of solutions that minimize the total cost while satisfying some budget constraint at every step, and the problem of determining how to modify the current solution to save money while staying in the same category. We first propose a general approach based on mixed integer (linear or quadratic) programming to solve these problems. Then, we implement this approach on various multiobjective combinatorial problems, such as multi-agent assignment problems and multiobjective knapsack problems. Numerical tests are provided to establish the feasibility of the approach on instances of different sizes.

Growing concerns about sustainability lead decision-makers to include in the supply chain network design, environmental and social impacts as well as economic objectives, which requires a balanced multi-criteria approach. In this paper, a multi-objective mixed integer model for a regional supply chain network of a fish processing industry is developed. The model and decision-making process is analysed using approximation and visualization of Pareto frontier in criteria space in the form of Interactive Decision Maps. For test purposes, the data of the network of tilapia fillet processing in West Paraná, Brazil, are used. A reasonable strategy is formulated, representing a compromise between different conflicting criteria in the supply chain — profit, carbon dioxide emissions, number of suppliers, number of hired workers, costs and revenue.

Implementing Enterprise Resource Planning (ERP) systems is currently recognized as a best practice with wide associated possibilities of business improvement for companies. Integrating these kinds of systems with business processes in the most efficient way requires to endeavour as much as possible simplifications for final users, which can be pursued by optimizing crucial software characteristics. The present article proposes a novel Multi-Criteria Decision-Making (MCDM) approach to deal with such an issue. Specifically, the ELECTRE (ELimination Et Choix Traduisant la REalité) TRI technique is suggested to assign ERP modules into predefined and ordered categories according to maintainability and usability, which are useful drivers in evaluating which module of an ERP software should be enhanced with priority. The results prove to have whole beneficial impact on system performance with relation to a case study: improvement evaluations will be identified based on the classes the ERP modules are assigned to by the method.

In recent years, the Quebec government has highlighted the importance of making decisions that are both sustainable and robust under climate change uncertainties. This paper aims to answer the following question: How to sort the alternatives according to their degree of sustainability achievement while evaluations are uncertain and temporal? The general objective of the paper is to propose a first temporal sorting method under stochastic uncertainty. The proposed method, called TSMAA-Tri, will assign each alternative to a predefined category based on a generalization of SMAA-Tri to a temporal context (multi-period evaluation of alternatives) where alternative evaluations are stochastic. The method starts performing Monte Carlo simulations to generate stochastic evaluation values. Each simulation (scenario of uncertainty) will generate a specific value for each criterion using the corresponding probability distribution. Then, aggregation consists in applying SMAA Tri at each period and performing a triple aggregation: (a) uncertainty aggregation; (b) multi-criteria aggregation; and (c) temporal aggregation. Multi-criteria aggregation consists in applying the SMAA-TRI method at each period. Then, two ways of temporal aggregation are proposed, based either on acceptability index or on outranking index of boundary profile. The proposed method is illustrated for sustainable forest management to show its applicability.

Since project management is inevitably a social effort involving all relevant actors, social aspects have to be emphasized when considering collaborative project management. Social innovation focuses on reacting to social demands and developing innovative solutions to overcome various social issues. Therefore, determining the social innovation potential in the project management process is very important. The main purpose of this study is to propose a Fuzzy Analytic Network Process (FANP) and Fuzzy VIKOR (FVIKOR)-based decision model to determine the social innovation potential of technological projects. The results of FANP revealed that the most important criteria for determining social innovation potential of projects are financial resources, technological developments and social capital. Furthermore, FVIKOR was used for ranking social innovation potential of the selected technological projects. There are several managerial implications of this study. First, we suggest that practitioners should integrate the proposed model into their project evaluation processes. Second, they can also use this model to define the social innovation factors during project selection. Lastly, the proposed model can be employed to prioritize the social innovation factors that enable managers to allocate the appropriate resources to project management process.

In this article, there is established a reverse logistics (RL) system to collect unwanted medications (UMs) in households. A reverse supply chain (RSC) is proposed in a decentralized state including manufacturer, and retailer involving a strategic consumer. The novelty of this article is that the model is investigated from the consumer's perspective, whereas in the previous studies, the proposed models were from other upstream members' perspectives such as manufacturer and retailer. Furthermore, inducement and advertising strategies are proposed for stimulating consumers to engage more in an RSC. To analyse the effect of these two strategies, the three-person RSC game-theoretical approach is used. A three-person supply chain consists of a pharmaceutical manufacturer and a retailer who will interact with a strategic consumer in several non-cooperative Stackelberg games. Three Stackelberg games are established and, each member takes a turn as a leadership role and the other two players assume the role of the follower.

Structured decision-making in the presence of conflicting goals is difficult, and even more so when accounting for uncertainties in the goals or constraints. In this article, we propose a new approach to multi-criteria decision-making that extends the deterministic preemptive goal programming approach to account for such uncertainties. The uncertainties may be characterized in various ways including a Bayesian network or extensive Monte Carlo multi-variate output. We contend the proposed stochastic preemptive goal programming approach is particularly applicable when better goal achievement increases uncertainty or induces risk to other goals. Resulting solutions tend to be a balance of the goals' achievements and robust to minor changes to the goals or constraints. We demonstrate the approach using three illustrative examples: a univariate example, a bivariate example, and a stock portfolio optimization example along with an application to determine military requests for absence. Our preliminary results suggest that a stochastic preemptive goal programming approach represents an effective means of analysing multi-criteria decision-making problems under uncertainty.

The theory of public finance suggests that public sector intervention in the economy primarily concerns the efficient allocation of resources, equal distribution of wealth, and stabilization of economic activity throughout the operating cycle. Given that prisons are a public investment, this study identified the criteria involved in selecting the location of prisons in Turkey, a topic that has not been discussed before. The criteria for locating these establishments were analysed using an analytical network process in which the weight of each criterion in the total was determined by conducting a face-to-face survey with officials in the justice system who are difficult to access. The results show that political factors (50.89%) had the biggest influence on the location selection of a prison, and the positive impact on economic development of the selected region was only 13.56%. In contrast to the existing literature, location selection in Turkey does not follow the theory of public finance: the economic impacts are not considered, and decisions are taken politically.