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This study aims to propose strategies to address the identified major barriers for giving the public open access to government data. The study adopts fuzzy analytical hierarchy process and technique for order performance by similarity to ideal solution (AHP-TOPSIS) to weigh the barriers and strategies, and it subsequently involves experts to identify and weigh the barriers and strategies. A case of Indonesia is used to contextualize the study.

The data were collected using fuzzy AHP-TOPSIS-based questionnaires given to several government representatives who had been working with data and information. The respondents were given sets of pairwise comparisons of which they were asked to compare the level of importance using one to nine fuzzy numbers between barriers and strategies. The data were then calculated using the fuzzy AHP-TOPSIS formula to obtain each weight of the barriers and strategies. The weight is used to prioritize the barrier and strategies.

In total, five barrier categories in the order of importance, namely, legal and privacy; government culture; social; technical; and economic, were identified from 27 barriers. In total, ten strategies of open government data (OGD) adoption were identified and ranked in the order of importance, and they can be grouped into five priorities. Priority 1 is to involve stakeholders in OGD planning and establish an OGD competence center. Priority 2 is to develop a legal compliance framework. Priority 3 is to adopt OGD gradually. Priority 4 is to create a collaboration feature on the portal for stakeholder communication and raise public awareness of OGD. Priority 5, finally, is to conduct training for government officials, develop standard operating practice for OGD management, use standard data formats and provide metadata.

This study provides a perspective from the government’s view. One suggestion for future research is to conduct a study from the public’s perspective to formulate strategies based on the identified citizens’ barriers in using OGD. In addition, cross-country (of different characteristics) studies were required to generalize the findings.

The first strategy of the first priority implies that government institutions should be able to develop a preliminary plan to involve relevant stakeholders in OGD planning, which includes identifying relevant stakeholders and continuously engaging them to participate in the planning phase of OGD. The second strategy in the first priority entails that government institutions should realize an OGD competence center by creating a virtual team whose members are from various backgrounds and who are very knowledgeable about OGD and how to manage OGD in government institutions.

This research provides key strategies to address the main barriers to giving the public open access to government data.

Collaborative networked organisations (CNO) are a means of ensuring longevity and business continuity in the face of a global crisis such as COVID-19. This paper aims to present a multi-criteria decision-making method for sustainable partner selection based on the three sustainability pillars and risk.

A combined analytic hierarchy process (AHP) and fuzzy AHP (F-AHP) with Technique for Order of Preference by Similarity to Ideal Solution approach is the methodology used to evaluate and rank potential partners based on known conditions and predicted conditions at a future time based on uncertainty to support sustainable partner selection.

It is integral to include risk criteria as an addition to the three sustainability pillars: economic, environmental and social, to build a robust and sustainable CNO. One must combine the AHP and F-AHP weightings to ensure the most appropriate sustainable partner selection for the current as well as predicted future period.

The approach proposed in this paper is intended to support existing CNO, as well as individual firms wanting to create a CNO, to build a more robust and sustainable partner selection process in the context of a force majeure such as COVID-19.

This paper presents a novel approach to the partner selection process for a sustainable CNO under current known conditions and future uncertain conditions, highlighting the risk of a force majeure occurring such as COVID-19.

The purpose of this paper is to introduce an integrated approach using failure modes and effects analysis (FMEA), multiple-criteria decision making (MCDM), mathematical modeling and quality function deployment (QFD) techniques, for risk assessment and service quality enhancement in coronary artery bypass grafting (CABG) as a treatment for cardiovascular diseases (CVDs).

First, the disruptions in the CABG process are identified and prioritized following FMEA instructions, using two MCDM techniques, called analytic hierarchy process (AHP) and TOPSIS. Consequently, several corrective activities are identified and weighted on the basis of QFD. Finally, a mathematical model is established to determine the most cost-effective activities for implementation. The approach is developed in a fuzzy environment to reflect the uncertainty and ambiguity of human reasoning.

Regarding the CABG process disruption, a total of 30 failure modes in four main categories were identified and prioritized. Moreover, eight corrective activities were devised and ranked according to their impact on the failure modes. Finally, considering a limited amount of budget, a sensitivity analysis on the mathematical model’s objective function indicated that using 30 percent of the total budget, required to implement all corrective activities, was enough to cover more than 70 percent of the effects of corrective activities on the failure modes.

This paper contributes to the quality risk assessment knowledge by introducing an integrated approach to evaluate and improve healthcare services quality. Also, the case study conducted on the CABG process has not been done by other related studies in the literature.

Resilience is a fundamental component of healthcare supply chains, as the quality and endurance of human life are dependent on them. However, there are numerous resilience-building measures, and there is a need for prioritization of those strategies. This research study aims to prioritize resilience strategies for healthcare supply chains while considering the risks that most severe, probable to occur and have the lengthiest periods of recovery.

This research study has used multi-criteria decision-making (MCDM) techniques for analysis. Initially, the criteria for prioritization of risks, i.e. severity, probability of occurrence and recovery time were assigned with importance weights through the fuzzy analytical hierarchy process (AHP). Then, these weights were used in the fuzzy technique for order preference by similarity to ideal solution (TOPIS) analysis for prioritization of risks. Subsequently, the identified risks were used for highlighting the appropriate resilience strategies through the fuzzy quality function deployment (QFD) technique.

Results indicate that Industry 4.0, multiple sourcing, risk awareness, agility and global diversification of suppliers, markets and operations are the most significant resilience strategies.

This study's limitation is that it is conducted in a general perspective, rather than reducing the context to a developing or developed country. Different areas have variable market factors, due to which potential risks occur in a different form. Moreover, resilience strategies work differently in different environments. Therefore, for future endeavors, the studies should be carried out in a limited context.

This research study proposes a novel MCDM-based approach for ranking resilience strategies, in light of the most probable, severe and long-lasting risks. In addition, this approach has been employed for the enhancement of resilience in healthcare supply chains.

Nowadays, the increase in the capacity of batteries has laid the foundations for a broader diffusion of electric mobility. However, electric mobility is causing a growing electricity demand as well as the need to increase the diffusion of suitable charging stations. Within these last challenges, drawing on the recent literature, this chapter provides a critical and wide-ranging review of papers dealing with the formulation of the problem of the localisation of electric vehicle (EV) charging points. This problem is approached considering the electric charging infrastructure technologies, localisation criteria and related methodologies. This review shows how the ‘electric mobility revolution’ applies the technological innovations provided by the energy supply systems, and the location of these systems within the urban contexts. Since the technological innovations have different options, achieving an international standard of charging systems is still far away. Moreover, as there are several criteria, parameters and methodologies, and some analytical approaches for the localisation of electric vehicle charging points, the formulation of the ‘localisation’ problem should require the application of multi-criteria analysis to be addressed. Finally, the results show that there is no consensus on technologies, criteria, and methodologies to be adopted. Therefore, this wide-ranging analysis of the literature would be useful to support possible benchmarking and systematisation accordingly.

Various networked organizational forms already exist in the market today, however, all of them share the same problem – lack of fast and objective procedures for partners’ selection when addressing a particular project. The purpose of this paper is to solve such problems by offering an alternative to the existing global market layout, dominated by large corporations.

This research belongs to the category “fuzzy decision making and multi-attributive decision making,” since it is using methodologies such as the analytical hierarchy process (AHP), the fuzzy-AHP approach, and the Technique for Order of Preference by Similarity to Ideal Solution.

The authors defend that appropriate partner selection is a vital success factor in any collaboration.

The authors have designed a sustainable partner network solution for the field of machinery. Nevertheless, the proposed approach is adaptable to other fields also, whereas the focal player or project owner selects the best partner based on a set of criteria.

The paper includes a feasibility case study for the approval of findings, where several small and medium enterprises (SMEs) from the field of machining collaborate to achieve a common goal.

The research focuses on production enterprises (especially for SMEs) and is intended to improve their competitiveness. Small enterprises combining into a network makes it possible to compete with large corporations and helps to decrease project initiation time and project realization risks.

The main idea is to collect information about the available resources of SMEs into a new temporary entity and to utilize those resources for the realization of the tasks of a particularly large project, while meeting customer expectations. In addition, this work also suggests a calculation tool for faster partner evaluation (assessment) based on various criteria for each particular project.

The food industry is crucial in delivering healthy products for life saving of the society. The identification of key barriers of knowledge management (KM) is desired to enhance the sustainability of the industry. KM has been seen as a part of sustainable development by reducing the bullwhip effect in the entire supply chain. The core objective of the existing research is to prioritize the essential factors of KM adoption in sustainable supply chain (SSC) based on fuzzy analytical hierarchy process (FAHP) method.

In order to fulfill objectives of this study, an extensive review of literature and a questionnaire-based field visits were conducted. A total of five major barriers categories and 22 sub-barriers categories were identified in food sector of Pakistan using experts' inputs. This study employed fuzzy analytical hierarchy process (FAHP).

Managerial barriers, innovation and technological barriers categories are found to be highly prioritized among others. Further, the sensitivity analysis is applied to check the incremental changes of ranked barriers. This prioritization of barriers and incremental changes in them is expected to serve food sector for long-term sustainability and competitive advantage for importers and exporters. Finally, the findings of this research are very helpful for industrial experts, practitioners, consultants and government officials in effectively developing policies regarding KM adoption in line with sustainable goals.

The present work is conducted in the Pakistani context; however, the benchmark model may be tested and applied to other developing countries to compare the outcomes. For further research, the identified barriers may also be evaluated to establish their inter-relationships, using ISM, DEMATEL, ANP, etc. Similarly, the results of this study can also be compared with that of other fuzzy multi-criteria techniques like fuzzy TOPSIS, fuzzy VIKOR, fuzzy ELECTRE, fuzzy PROMETHEE, or fuzzy VIKOR.

This research study can facilitate policymakers, government bodies, stakeholders and supply chain professionals to recognize the key barriers they may encounter in adopting KM practices in their SSC. Additionally, this work helps managers to evaluate the identified barriers by computing their relative importance in adopting KM practices at managerial levels like strategically, tactically and operationally activities in business. This study also facilitates industrial management in formulating policies and action plans in case of implementation, eliminating the barriers in adoption of KM, and SSC successfully.

Few research studies were conducted on KM adoption in industries of China, India, Turkey, Saudi Arabia and Malaysia, but due to workforce diversity these industries have dissimilar views of experts about KM adoption. This study significantly contributed to fill the existing literature gap for prioritization of key barriers against KM implementation in Pakistani context.

In this paper, two popular multiple-criteria decision-making (MCDM) methods with hesitant fuzzy logic approach; hesitant fuzzy analytic hierarchy process (hesitant F-AHP) and hesitant fuzzy the technique for order preference by similarity to ideal solution (HF-TOPSIS) are integrated as HF-AHP-TOPSIS to evaluating a set of enterprise resource planning (ERP) alternatives and rank them by weight to reach to the ultimate one that satisfies the needs and expectations of a company.

Selecting the best ERP software package among the rising number of the options in market has been a critical problem for most companies for a long time because of the reason that an improper ERP software package might lead to many issues (i.e. time loss, increased costs and a loss of market share). On the other hand, finding the best ERP alternative is a comprehensive MCDM problem in the presence of a set of alternatives and several potentially competing quantitative and qualitative criteria.

In this integrated approach, the hesitant F-AHP is used to determine the criteria weights, as the hesitant F-TOPSIS is utilized to rank ERP package alternatives. The proposed approach was also validated in a numerical example that has five ERP package alternatives and 12 criteria by three decision-makers in order to show its applicability to potential readers and practitioners.

If the number of the alternatives and criteria are dramatically increased beyond reasonable numbers, the reaching to final solution will be so difficult because of the great deal of fuzzy based calculations. Therefore, the number of criteria and alternatives should be at reasonable numbers.

The proposed approach was also validated in a illustrated example with the five ERP package options and 12 criteria by the three decision-makers in order to show its applicability to potential readers and practitioners.

Furthermore, in literature, to the best of our knowledge, the authors did not come cross any work that integrates the HF-AHP with the HF-TOPSIS for ERP software package selection problem.

Many developed countries have been using environmental taxes in their economic systems for many years. These taxes have a great impact on reducing the environmental damages of companies and individuals in society. But many developing countries have not used this tool effectively yet, and some countries face barriers to the effective implementation of environmental taxes that make it difficult and unsuccessful. To increase the effectiveness of the implementation of environmental taxes, governments must prioritize barriers and solutions to overcome its barriers. The identified knowledge gap of the pre-literature review is that an overview of the identification which completely considers all barriers and solutions of environmental taxes implementation does not exist. In response to this knowledge gap, this study aims to identify and prioritize the barriers and solutions of environmental taxes implementation.

Ranking the barriers and solutions is a complicated multi-criteria decision making (MCDM) problem that requires consideration of multiple feasible alternatives and conflicting tangible and intangible criteria. This study addresses the prioritization of solutions of Environmental Taxes implementation by proposing hybrid MCDM methods based on the Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) and the Fuzzy Technique for order preference by similarity to an ideal solution (Fuzzy-TOPSIS) under fuzzy environment. Fuzzy AHP is used to determine the weight of each barrier using a pairwise comparison, and fuzzy TOPSIS is used to finalize the ranking of solutions for more effective implementation of environmental taxes.

The results showed that environmental tax reform (ETR) (S3) has the highest value among the solutions for more effective implementation of environmental taxes. The result of the proposed model is validated by performing sensitivity analysis.

This study could foster research on the discussion of these barriers and precise ways of implementing solutions to pay more attention to environmental taxes.

Ratings of solutions can be a guide and help governments to improve the implementation of environmental taxes or even develop this policy by being aware of the ranking of barriers and solutions.

This paper creates a new perspective on the effective implementation of environmental taxes, which is closely related to improving environmental performance and increasing social welfare through improving the tax system.

For the first time, this study comprehensively identifies barriers and solutions for more effective implementation of environmental taxes and ranks them using two MCDM techniques.

The implementation of lean production in small manufacturing enterprises (SMEs) harbors a great deal of barriers on practical, theoretical, financial and organizational sides. In view of this, the purpose of this paper is to explore and prioritize the solutions to overcome these barriers and pitfalls in order to identify a list of the most feasible and efficient solutions on which SMEs must focus to success their lean journey.

First, a review of the published articles along with the interview of some lean experts have allowed to identify 20 barriers grouped into five categories along with 17 solutions proposed to overcome these barriers. Afterwards, an integrated fuzzy Analytic Hierarchy Process-Technique for Order Preference by Similarity to Ideal Solution (AHP-TOPSIS) was proposed to evaluate and rank the solutions of lean implementation in SMEs and overcome its barriers. The AHP is used to determine weights of the barriers as criteria, and the fuzzy TOPSIS method is used to determine the final ranking of the solutions of lean adoption in SMEs.

The top five barriers of lean implementation in SMEs were found to be: lack of management involvement, lack of adapted methodology of lean implementation, short-term vision, fear and resistance to change and lack of understanding of lean. Moreover, the top five solutions to overcome the barriers of lean adoption in SMEs are as follows: commitment and participation of management, adoption of simple measurement and KPIs, development of organizational learning culture, early deployment of lean culture through training and allocation of sufficient time and resources for change.

The findings of this study can provide a basis for researchers and practitioners in order to understand the real reasons of lean failure in SMEs and develop improvement plans to increase its success rate. Moreover, it proposes a more reliable, robust and systematic decision support tool for stepwise implementation of the solutions of lean adoption in SMEs since they lack sufficient resources to address all the solutions simultaneously.