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This paper aims to propose a process optimization approach showing how organizations are able to achieve sustainable and efficient process optimization, based on integrated process-risk analysis using several criteria to a better decision-making.

Several approaches are used (functional/dysfunctional) to analyze how processes work and how to deal with risks forming multi-criteria decision-making. In addition, a risk factor is integrated into the structured analysis and design techniques (SADT) method forming a novel graphical view SADT-RISK; it identifies process’s failures using the traditional failure modes, effects and criticality analysis (FMECA) and economic consideration “failure mode and effect, criticality analysis-cost FMECA-C” making a multi-criterion matrix for better decision-making. Subsequently, some recommendations are proposed to overcome the failure.

This paper illustrates a methodology with a case study in a company, which has a leading brand in the market in Algeria. The authors are integrating a varied portfolio of approaches linking with each other to analyze, improve and optimize the processes in terms of reliability and safety to deal with risks; reduce the complexity of the systems; increase the performance; and achieve a safer process. However, the proposed method can be readily used in practice.

The paper provides a new approach based on integrated management using new elements as an innovative contribution, forming a novel graphical view SADT-RISK; it identifies process’s failures using the traditional FMECA and economic consideration “a new multi-criterion matrix for better decision-making and using the SWOT analysis – Strengths, Weaknesses, Opportunities, Threats – as a balance to decide about the process improvement”. The authors conclude that this methodology is oriented and applicable to different types of companies such as financial, health and industrial as illustrated by this case study.

Improvement maintenance’s aim is identifying and implementing improvement action on equipment in service. The purpose of this paper is to propose an approach based on downtime’s analysis to raise up equipment’s performance, such as reliability, maintainability, availability, and safety. Steps of this approach will be illustrated by industrial applications.

Furthermore, it proposes an approach based on a combination of several methods (FMECA, cause and effect diagrams, ABC analysis, 5W, RCA method, etc.). This approach is based on the downtime analysis and lead to improve maintenance’s performance and equipment’s reliability, maintainability, availability and safety. Those objectives have a strong correlation with the downtime.

This approach led to apply easily improvement maintenance by using known methods. In the industrial application, this approach helps the authors to choose the good solution with the better life durance.

After following the steps simulated by the proposed approach, actions and concrete measures will be deducted and illustrated by the industrial’s application.

At present, there is not an explicit improvement maintenance, to lead to specific maintenance actions on equipment in service, in order to improve the maintenance function goals.

This paper aims to evaluate the market concentration and competition in the European Banking Sector using an integrated multi-criteria decision-making approach under the fuzzy environment.

The hybrid model combining fuzzy decision-making trial and evaluation laboratory (DEMATEL), fuzzy analytic network process (ANP) and fuzzy VIKOR methods is applied to measure the market competition and concentration in the European Banking Sector. For this purpose, two academicians and one expert from banking sector with at least five-year experiences are selected to evaluate the dimensions, criteria and alternatives. The academicians are also appointed to define the decision-making problem and determine the dimensions and the criteria on the basis of related literature. The implementation of the model has been constructed in three main phases. The first phase consists of the fuzzy DEMATEL technique for understanding the impact-relation map among the dimensions. The second phase includes the fuzzy ANP method for measuring the relative importance of the criteria. The last phase comprises the fuzzy VIKOR approach to rank the alternatives with the values of the Herfindahl–Hirschman Index (HHI).

Turkey, France, England and Germany are placed in the competitive market structure of the European Banking Sector respectively. Additionally, the comparative results of the study confirm the market shares and the competitive policies of the European and Turkish Banking Sector.

The novelty of the paper is to construct a hybrid multi-criteria decision-making model with the proposed HHI scales under the fuzzy environment and defined competition dimensions and criteria based on the literature for the European Banking Industry.

The purpose of this paper is twofold: the selection of project portfolios through hybrid artificial neural network algorithms, feature selection based on grey relational analysis, decision tree and regression; and the identification of the features affecting project portfolio selection using the artificial neural network algorithm, decision tree and regression. The authors also aim to classify the available options using the decision tree algorithm.

In order to achieve the research goals, a project-oriented organization was selected and studied. In all, 49 project management indicators were chosen from A Guide to the Project Management Body of Knowledge (PMBOK Guide), and the most important indicators were identified using a feature selection algorithm and decision tree. After the extraction of rules, decision rule-based multi-criteria decision making matrices were produced. Each matrix was ranked through grey relational analysis, similarity to ideal solution method and multi-criteria optimization. Finally, a model for choosing the best ranking method was designed and implemented using the genetic algorithm. To analyze the responses, stability of the classes was investigated.

The results showed that projects ranked based on neural network weights by the grey relational analysis method prove to be better options for the selection of a project portfolio. The process of identification of the features affecting project portfolio selection resulted in the following factors: scope management, project charter, project management plan, stakeholders and risk.

This study presents the most effective features affecting project portfolio selection which is highly impressive in organizational decision making and must be considered seriously. Deploying sensitivity analysis, which is an innovation in such studies, played a constructive role in examining the accuracy and reliability of the proposed models, and it can be firmly argued that the results have had an important role in validating the findings of this study.

This study is centered on the identification of the most appropriate Technology Adoption (TA) model for investigating the adoption of Industry 4.0 technologies within pharmaceutical and related enterprises. The aim is to facilitate a smooth transition to advanced technologies while concurrently achieving environmental sustainability.

Selection of a suitable TA theory is carried out using a hybrid multi-criteria decision-making (MCDM) approach incorporating PIvot Pairwise RElative Criteria Importance Assessment (PIPRECIA) and Fuzzy Measurement of alternatives and ranking according to Compromise solution (F-MARCOS) methods. A group of three experts is formulated for the ranking of criteria and alternatives based on those criteria.

The results indicate that out of all six TA models considered unified theory of acceptance and use of technology (UTAUT) model gets the highest utility function value, followed by the technical adoption model (TAM). Further, sensitivity analysis is conducted to confirm the validity of the MCDM model employed.

Challenging times like COVID-19 pointed out the importance of technology in the pharmaceutical and healthcare sectors. TA studies in this area can help in the identification of critical factors that can assist pharmaceutical firms in their efforts to embrace emerging technologies, enhance their outputs and increase their efficiency.

The novelty of this research lies in the fact that the utilization of a TA theory prior to its implementation has not been witnessed in existing scholarly literature. The utilization of a TA theory, specifically within the pharmaceutical industry, can assist enterprises in directing their attention toward pertinent factors when contemplating the implementation of emerging technologies and achieving sustainable development.

This study is to develop an accurate assessment tool to identify the factors that may influence determining the appropriate use for historic buildings.

The research method in this study is qualitative. The integrated MCDM (multi-criteria decision-making) method is used to determine the most appropriate use for historic buildings, which ultimately led to the development of the MAU (most appropriate use) model.

The results of this study show that, in terms of preserving identity and cultural heritage, the role intangible criteria have to play is seemingly more important than that of tangible criteria. Also, weighted criteria in the matrix relating the “use” options demonstrate cultural-social, commercial and educational uses being apparently more important than other uses.

The novelty of this research is in providing a framework to facilitate contribution to determine the most suitable use for historic buildings with the ability to set criteria and separate weights for each building aiming to increase the useful life to the maximum extent and delaying the need for a subsequent major overhaul.

The aim of this paper is to introduce a newly developed multi-criteria analysis for the comparison of two grid expansion alternatives, conventional and voltage-regulated distribution transformer. The case study comprises environmental, economic, technical and social aspects.

The newly developed method decision condition Preference Ranking Organization METHod for Enrichment Evaluation (DC-PROMETHEE) combines scenario planning with the multi-attribute decision-making method PROMETHEE. DC-PROMETHEE supports the decision-maker to evaluate the total potential of an alternative considering a large number of decision conditions. The calculated performance indicator supports the decision-maker to select the best alternative.

The voltage-regulated distribution transformer shows a high overall potential in the present case study. This leads to the recommendation to the investigated distribution system operator to include the voltage-regulated distribution transformers as a grid expansion measure.

The DC-PROMETHEE can be applied to other distribution system operators by considering their individual grid topology and preferences. Other fields of application are infrastructure investments in the service area, in which expansion alternatives are evaluated in a large number of decision conditions. Examples include telecommunication, gas supply, water supply, sewage and rail networks.

This paper develops the DC-PROMETHEE approach. The DC-PROMETHEE enables the multi-criteria evaluation of a few alternatives in a large number of decision conditions.

Robot selection is basically a task of choosing appropriate robot among available alternatives with respect to some evaluation criteria. The task becomes much more complicated since apart from objective criteria a number of subjective criteria need to be evaluated simultaneously. Plenty of decision support systems have been well documented in existing literature which considers either objective or subjective data set; however, decision support module with simultaneous consideration of objective as well as subjective data has rarely been attempted before. The paper aims to discuss these issues.

Motivated by this, present work exhibits application potential of preference ranking organization method for enrichment evaluations (extended to operate under fuzzy environment) to solve decision-making problems which encounter both objective as well as subjective evaluation data.

An empirical case study has been demonstrated in the context of robot selection problem. Finally, a sensitivity analysis has been performed to make the robot selection process more robust. A trade-off between objective criteria measure and subjective criteria measure has been shown using sensitivity analysis.

Robot selection has long been viewed as an important decision-making scenario in the industrial context. Appropriate robot selection helps in enhancing value of the product and thereby, results in increased profitability for the manufacturing industries. The proposed decision support system considering simultaneous exploration of subjective as well as objective database is rarely attempted before.

The US Government adopted the base realignment and closure (BRAC) to resolve the military, economic and political issue of excess base capacity. There have been five rounds of BRAC since 1988, and more are expected to come in the years ahead. The complexity of the closure and realignment decisions and the plethora of factors that are often involved necessitate the need for a sound theoretical framework to structure and model the decision‐making process. This paper aims to address the issues.

The paper presents a multiple criteria benchmarking system that integrates the employment, environmental, financial, strategic, and tactical impacts of the closure and realignment decisions into a weighted‐sum measure called the “survivability index.” The proposed index is used to determine whether the returns generated by each military base on the Department of Defense (DoD) hit list meet a sufficient target benchmark.

There is a significant amount of evidence that intuitive decision making is far from optimal and it deteriorates exponentially with problem complexity. The benchmarking system presented in this study helps decision makers (DMs) crystallize their thoughts and reduce the environmental complexities inherent in the BRAC decisions. The presented model is intended to create an even playing field for benchmarking and pursuing consensus not to imply a deterministic approach to BRAC decisions.

An iterative process is used to consistently analyze the objective and subjective judgments of multiple DMs within a structured framework based on the analytic network process and fuzzy logic. This iterative and interactive preference modeling procedure is the basic distinguishing feature of the presented model as opposed to statistical and optimization decision‐making approaches.

The purpose of this paper is to determine compatibility groups of different fruits and vegetables that can be stored and transported together based upon their requirements for temperature, relative humidity, odour and ethylene production. Pre-cooling which is necessary to prepare the commodity for subsequent shipping and safe storage is also discussed.

The methodology used in this journal is an attempt to form clusters/groups of storing together 43 identified fruits and vegetables based on four important parameters, namely, temperature, relative humidity, odour and ethylene production. An agglomerative hierarchical clustering algorithm is used to build a cluster hierarchy that is commonly displayed as a tree diagram called dendrogram. The same is further analyzed using K-means clustering to find clusters of comparable spatial extent. The results obtained from the analytics are compared with the available data of grouping fruits and vegetables.

This study investigates the usefulness and efficacy of the proposed clustering approach for storage and transportation of different fruits and vegetables that will eventually save huge investment made in terms of developing infrastructure components and energy consumption. This will enable the investors to adopt it for using the space more effectively and also reducing food wastage.

Due to limited research and development (R&D) data pertaining to storage parameters of different fruits and vegetables on the basis of temperature, relative humidity, ethylene production/sensitivity, odour and pre-cooling, information from different available sources have been utilized. India needs to develop its own crop specific R&D data, since the conditions for soil, water and environment vary when compared to other countries. Due to the limited availability of the research data, various multi-criteria approaches used in other areas have been applied to this paper. Future studies might be interested in considering other relevant variables depending upon R&D and data availability.

With the increase in population, the demand for food is also increasing. To meet such growing demand and provide quality and nutritional food, it is important to have a clear methodology in terms of compatibility grouping for utilizing the available storage space for multi-commodity produce and during transportation. The methodology used shall enable the practitioners to understand the importance of temperature, humidity, odour and ethylene sensitivity for storage and transportation of perishables.

This approach shall be useful for decision making by farmers, Farmer Producer Organization, cold-storage owners, practicing managers, policy makers and researchers in the areas of cold-chain management and will provide an opportunity to use the available space in the cold storage for storing different fruits and vegetables, thereby facilitating optimum use of infrastructure and resources. This will enable the investors to utilize the space more effectively and also reduce food wastage. It shall also facilitate organizations to manage their logistic activities to gain competitive advantage.

The proposed model would help decision makers to resolve the issues related to the selection of storing different perishable commodities together. From the secondary research, not much research papers have been found where such a multi-criteria clustering approach has been applied for the storage of fruits and vegetables incorporating four important parameters relevant for storage and transportation.