A multi-attribute framework for the selection of high-performance work systems: the hybrid DEMATEL-MABAC model

Research in strategic human resource management indicates that high performance work systems (HPWS) have a positive impact on the overall performance of an organization as a result of better human resource (HR) outcomes. Regarding the multi-dimensional and complex nature of these factors, common statistical models are not useful for examining the performance of HPWS. Using the capabilities of multi-attribute decision-making (MADM) methods to deal with various criteria that may be contradictory, this study proposes a MADM-based framework that provides the opportunity to prioritize HR practices. Based on this framework, high-performance HR practices and their related HR outcomes were identified after studying the theoretical literature and ascertaining the views of decision-makers and HR experts. Then, after looking at the interactions among HR outcomes, the weights of the criteria were calculated using the method of the decision making trial and evaluation laboratory (DEMATEL). Then, the alternatives were ranked using the multi-attributive border approximation area comparison (MABAC) method. Finally, the designed framework was implemented in an organization active in the banking industry. This framework can be used to improve employees’ performance and, consequently, the performance of the organization. Accordingly, taking into account the resource constraints organizations face, the priorities presented can be helpful in budgeting human-resource-management (HRM) improvement projects and making an appropriate resource allocation for this

Identifying and prioritizing cost reduction solutions in the supply chain by integrating value engineering and gray multi-criteria decision-making

Value engineering is an appropriate policy for creating and improving value, which reduces unnecessary costs and maintains core functionality. Despite the mentioned benefits, this approach has so far received little attention in the area of supply chain management. Although this approach is highly structured, limitations such as overemphasizing the cost criterion and failure to meet other criteria, utilizing team members’ votes to rank solutions, ignoring inherent uncertainty and ultimately disagreement between value engineering team members have reduced the effectiveness of this approach. The present study aims to provide a coherent framework for utilizing a value engineering approach to supply chain cost management and overcome the aforementioned limitations by utilizing gray multi-criteria decision-making. In this regard, in the first phase, the initial list of improvement solutions is determined, the criteria extracted from the literature are localized using value engineering team members’ opinion. These criteria are weighted using the gray stepwise weight assessment ratio analysis (SWARA-Gray) method. Then, the score of each solution is calculated by the value engineering team based on the list of criteria as a gray number. The scores are aggregated using the gray evaluation based on distance from average solution (EDAS-Gray) method, and the solutions are prioritized. Finally, the application of the proposed framework is investigated in a real case study in a power plant in Iran. The results of the research show that the final rankings of the solutions rarely changed for different methods; so the model used in this study has acceptable stability. First published online 24 September 202

Big data analytics recommender system for housing health and safety

The dissertation analyses issues arising in the management of safe and healthy housing. The research focuses on the management of safe and healthy housing in micro, meso and macro environment in order to keep it safe and healthy, according to the needs of stakeholder groups. The aim of the dissertation is to develop an integrated big data analytics recommender system for housing health and safety that will allow to manage safe and healthy house for the stakeholder groups

A novel performance evaluation framework for new service development in the healthcare industry using hybrid ISM and ANP

Today, the innovative activities of companies in new service development (NSD) have an undeniable contribution to the economic development of countries. Given the recent advances in the healthcare industry, the issue of NSD and performance management of firms operating in this industry has received special attention of researchers and decision makers. A review of previous research shows that on the one hand there is no agreement among experts on NSD performance measurement criteria and on the other hand there has been no systematic framework that can measure and manage firm performance in this area. The proposed framework should allow for interaction between different decision makers, considering multiple and sometimes conflicting criteria. In this regard, this paper aimed to provide a framework to assess the NSD performance in healthcare industry using multiple-criteria-decision-making methods. The proposed model consists of 17 different criteria that have been identified and finalized based on previous studies as well as experts’ opinions. Then, the indicators are classified with the help of experts in the form of a balanced scorecard model and presented as an initial model. Due to internal relationships between criteria, this model was evaluated using interpretive structural modelling and modelled at 5 different levels. Then, the analytic network process approach was applied to determine criteria weights. Finally, new service development performance in Moheb hospital was evaluated through the framework proposed here

Assessment of Progress towards Achieving Sustainable Development Goals of the “Agenda 2030” by Using the CoCoSo and the Shannon Entropy Methods: The Case of the EU Countries

The United Nations Member States adopted the “Agenda 2030” which contains 17 sustainable development goals (SDG) that involve a certain number of targets and indicators. Although the indicators are helpful in defining the position of the current country relative to the goals’ achievement, it is very complex to determine its position relative to other countries, because this requires an extensive analysis. Therefore, in this paper, the application of the multiple-criteria decision-making approach (MCDM) in defining the position of the EU (Europe Union) countries relative to the SDGs is proposed. The MCDM model is based on the Combined Compromise Solution (CoCoSo) and the Shannon Entropy methods. The final results highlight Sweden as the country that best implemented the set SD goals and has the best outputs relative to them, while Romania is in last place. The main reason for these kinds of results could be that the countries on the bottom of the list are relatively new EU members and have not been made to properly implement SDGs yet. The conclusion is that the obtained results are fully objective and rational, and that the applied model is applicable for performing this kind of analysis.This article belongs to the Special Issue Sustainability as a Multi-criteria Concept: New Developments and Application

Multiple Criteria Evaluation of the EU Country Sustainable Construction Industry Lifecycles

This article looks at the trends and success of the sustainable construction industries in the EU member states, the UK and Norway. The research, covering the past three decades, revealed that different quality of life, macroeconomic, human development, construction and well-being factors define the sustainable construction industries in the EU member states, the UK and Norway. A multiple criteria decision matrix was created and analysed to look at the EU member countries, the UK and Norway from the perspective of their macro level environment and construction industries. Assessments of the sustainable construction industries were completed by using the COmplex PRoportional Assessment (COPRAS) and Degree of Project Utility and Investment Value Assessments (INVAR), two analysis methods. A look was taken at the dependencies linking the indicators related to the construction industries and macro level in the EU member countries, the UK and Norway. Then, the multiple criteria analysis of the construction industry’s utility degree and performances were completed, and recommendations were generated. A country’s perceived image and success can influence the economic behaviour of consumers. By and large, advanced and successful countries rarely become associated with a negative national image and their products and services rarely suffer negative consequences due to such association. This research, then, offers findings that can assist potential buyers in more rational decision-making when choosing of products and services based on a country of origin.This article belongs to the Special Issue Probabilistic and Fuzzy Approaches for Estimating the Life Cycle Costs of BuildingsThis project received funding from European Regional Development Fund (project No 01.2.2-LMT-K-718-01-0073) under grant agreement with the Research Council of Lithuania (LMTLT). The sponsor had no involvement in the study design, the collection, analysis and interpretation of data, or the preparation of the article