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Achieving a zero-carbon city requires a long-term strategic perspective. The authors propose a decision-making model which would take into account the economic, environmental and social impacts for prioritizing the zero-carbon measures for sustainable urban transportation.

An integrated intuitionistic fuzzy gained and lost dominance score (IF-GLDS) model is introduced based on intuitionistic fuzzy Yager weighted aggregation (IFYWA) operators and proposed weight-determining IF-SPC procedure. In addition, a weighting tool is presented to obtain the weights of decision experts. Further, the feasibility and efficacy of developed IF-SPC-GLDS model is implemented on a multi-criteria investment company selection problem under IFS context.

The results of the developed model, “introducing zero-emission zones” should be considered as the first measure to implement. The preference of this initiative offers sustainable transport in India to achieve a zero-carbon transport by having the greatest impact on the modal shift from cars to sustainable mobility modes with a lower operational and implementation cost as well as having greater public support. The developed model utilized can be relocated to other smart cities which aim to achieve a zero-carbon transport. Sensitivity and comparative analyses are discussed to reveal the robustness of obtained result. The outcomes show the feasibility of the developed methodology which yields second company as the suitable choice, when compared to and validated using the other MCDA methods from the literature, including TOPSIS, COPRAS, WASPAS and CoCoSo with intuitionistic fuzzy information.

A new intuitionistic fuzzy symmetry point of criterion (IF-SPC) approach is presented to find weights of criteria under IFSs setting. Then, an IF-GLDS model is introduced using IFYWA operators to rank the options in the realistic multi-criteria decision analysis (MCDA) procedure. For this purpose, the IFYWA operators and their properties are developed to combine the IFNs. These operators can offer a flexible way to deal with the realistic MCDA problems with IFS context.

The reemergence of immersive virtual technology (IVR) provides both opportunities and challenges for workplace learning (WPL). The purpose of this study is to explore and develop knowledge about how gamification influences the WPL experience by addressing two research questions: RQ1. What characterizes a gamified immersive safety training experience with IVR technology? and RQ2. How does gamified immersive safety training with IVR technology impact the WPL experience?

The study adopted a mixed methods approach by combining a systematic literature review with a case study on an empirical project about immersive fire safety training for train operators that are used at the Swedish train operating company SJ. The case study included data from semistructured interviews, Web survey and observation studies. The data was analyzed in two stages combining inductive and deductive data analysis for identifying themes and categories.

The findings of the study are twofold: (1) themes that conceptualize the gamified immersive safety training experience based on outputs from both the literature review and the first round of data analysis; and (2) a framework with three overarching categories that are mapped with the identified themes, and which were deduced throughout the second round of data analysis.

The originality of the findings stresses the implications of how a body of knowledge that synthesizes gamification concepts with immersive safety training, can inform the design of WPL experiences that are facilitated with IVR technology. As such, the implications of the findings are targeted toward both the advancement of the IVR discourse in the WPL field, but also toward practical considerations for design of immersive learning experiences that enrich WPL practices and culture.

The purpose of this study is to establish a synthetic group decision framework based on the Pythagorean fuzzy (PF) set to select the optimal medicine cold chain logistics provider (MCCLP). Fierce market competition makes enterprises must constantly improve every link in the process of enterprise sustainable development. The evaluation of MCCLP in pharmaceutical enterprises is an important link to enhance the comprehensive competitiveness. Because of the fuzziness of expert cognition and the complexity of the decision procedure, PF set can effectively handle the uncertainty and ambiguity in the process of multi-criteria group decision decision-making (MCGDM).

This paper develops an integrated group decision framework through combining the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique and combined compromise solution (CoCoSo) approach to select a satisfactory MCCLP within PF circumstances. First, the PF set is used to process the ambiguity and uncertainty of the cognition ability of experts. Second, a novel PF knowledge measure is propounded to measure the vagueness of the PF set. Third, a comprehensive criterion weight determination technique is developed through aggregating subjective weights attained utilizing the PF DEMATEL approach and objective weight deduced by knowledge measure method. Furthermore, an integrated MCGDM approach based on synthetic weight and CoCoSo method is constructed.

The outcomes of sensibility analysis and comparison investigation show that the suggested decision framework can help decision experts to choose a satisfactory MCCLP scientifically and reasonably. Accordingly, the propounded comprehensive decision framework can be recommended to enterprises and organizations to assess the MCCLP for their improvement of core competitiveness.

MCCLP selection is not only momentous for pharmaceutical enterprises to improve transportation quality and ensure medicine safety but also provides a strong guarantee for enterprises to improve their core competitiveness. Nevertheless, enterprises face certain challenges due to the uncertainty of the assessment environment as well as human cognition in the process of choosing a satisfactory MCCLP. PF set possesses a formidable capability to address the uncertainty and imprecision information in the process of MCGDM. Therefore, pharmaceutical enterprises can implement the proposed method to evaluate the suppliers to further improve the comprehensive profit of enterprises.

The concept of sustainable product design (SPD) is gaining significant attention in recent research. However, due to inherent uncertainties associated with new product development and incorporation of multiple qualitative and quantitative criteria; SPD is a complex and challenging task. The purpose of this paper is to introduce a novel approach by integrating quality function deployment (QFD), multi-criteria decision making (MCDM) technique and Six Sigma evaluation for facilitating SPD in the context of Industry 4.0.

The customer requirements are evaluated through the neutrosophic-decision-making trial and evaluation laboratory-analytic network process (DEMATEL-ANP)-based approach followed by utilizing QFD matrix to estimate the weights of the engineering characteristics (EC). The Six Sigma method is then employed to evaluate the alternatives’ design based on the ECs’ values.

The effectiveness of the suggested approach is illustrated through an example. The result indicates that utilization of the neutrosophic MCDM technique with integration of Six Sigma methodology provides a simple, effective and computationally inexpensive method for SPD.

The proposed approach is helpful in upstream evaluation of the product design with limited experimental/numerical data, maintaining a strong competitive position in the market and enhancing customer satisfaction.

This work provides a novel approach to objectively quantify performance of SPD under the paradigm of Industry 4.0 using the integration of QFD-based hybrid MCDM with Six Sigma method.

The purpose of this study is to identify Offshore Wind Energy (OWE) as a key technology that could drive countries toward achieving climate goals. However, there are multiple challenges that this sector faces.

This study aims to identify the challenges faced by the sector globally by systematically reviewing the existing literature in global context and portraying it in the Indian context. Factors are identified using content analysis.

Results suggest high levelized cost of energy as the most discussed challenge for the growth of OWE. Insufficient financial support and policy, initial capital and inadequate technology formed the second, third and fourth most discussed challenges respectively.

To reduce the cost of OWE, the distribution companies in India could adopt feed-in tariffs (FiTs) in the early stages of development and make OWE procurement mandatory. The renewable purchase obligation (RPO) in India is specific to solar and non-solar; policy should accommodate offshore wind-specific RPO targets for each state to reach the 2030 target of 30 GW from OWE.

To the best of the authors’ knowledge, this is the first attempt to study the challenges of OWE development from a global perspective and portray these major challenges in the Indian context and uses content analysis from the existing literature to ascertain the major roadblocks for the development of OWE.

The study identifies the unexplored gap in literature that includes futuristic challenges for OWE from climate change. Future studies can explore the possibilities of forecasting based on climate change scenarios and rank the challenges based on their relevance caused by possible damages.

Research on the underlying mechanisms that transfer the effects of performance appraisal (PA) on employees’ behaviors and intentions remains scarce. The social exchange view of performance appraisal can be a source of deeper understanding about these underlying mechanisms. This study aims to investigate how psychological empowerment (PE) and organizational commitment (OC) explain the link between performance appraisal and three important distal outcomes: voice behavior (VB), organizational citizenship behavior (OCB), and turnover intentions (TOI).

The current study utilizes two wave – two source data from a sample of 250 employees and their supervisors from private organizations in Pakistan and tested the mediation model using SMART-PLS.

Results demonstrated that organizational commitment mediated the effects of performance appraisal on VB, OCB, and TOI, whereas psychological empowerment mediated the effects of performance appraisal on VB and OCB. These results have significant implications for theory and practice.

This study adopts the social exchange perspective to examine the mediation mechanisms linking PA with the three distal outcomes: VB, OCB and TOI. The paper identifies two novel mediators of PA – outcome relationship, i.e., psychological empowerment and organizational commitment.

The paper aims to examine the effect of justice perceptions of performance appraisal (JPPA) practices (i.e. distributive, procedural, informational and interpersonal justice) on organizational citizenship behavior (OCB) and affective commitment (AC) and the effect of AC on OCB. Further, it investigates the mediating role of AC in the relationship between JPPA practices and OCB. Moreover, this study examines the moderating effect of job level on the relationship between JPPA practices and OCB.

The data were collected using a self-reported structured questionnaire. A total of 650 questionnaires were distributed among the employees of 50 information technology (IT) companies in India, and 503 samples were obtained. The conceptual framework was tested using the partial least squares structural equation modeling (PLS-SEM) method, and the moderating effect was tested using process macro.

The findings of this study reveal that the JPPA practices positively affect OCB and AC and AC affects OCB. Further, AC partially mediates this relationship between JPPA practices and OCB. Furthermore, the direct effect of JPPA practices on OCB happens to be strengthened when the job level decreases, thus confirming the moderating role of job level.

The findings of this study augment the social exchange theory (SET) by suggesting that individuals perceiving justice or fairness in performance appraisal practices are likely to have a greater AC that ultimately engages employees in OCB.

This study will be helpful for human resource practitioners in IT companies who are responsible for the fairness of performance appraisal practices and expect their employees to be emotionally attached to the organization and engaged in OCB.

The study adds to the body of knowledge of how justice in performance appraisal practices links to OCB through AC and moderates by job level in an emerging economy in Asia.

The All India Institute of Medical Sciences (AIIMS) is a premier medical institution in India that has significantly contributed to cancer research. This study aims to highlight the cancer research productivity of AIIMS by assessing the impact and reach of the institution’s research output.

The study was based on 2,078 published papers on cancer of AIIMS indexed in the Web of Science (WoS) database from 1989 to 2021. A combination of tools such as Microsoft Excel, Biblioshiny, BibExcel and VOSviewer was used to evaluate and visualize the selected data.

The analysis revealed the interdisciplinary nature of research outputs, which have collaborative contributions from various fields such as oncology, pathology, radiology and surgery. The most productive research area within cancer was found to be breast cancer. In terms of international collaboration, the analysis revealed that AIIMS has a strong presence in the global cancer research community, with collaborations with researchers from more than 50 countries.

This study has some limitations. First, the study is limited to using only the WoS Core Collection database. Other databases, such as Scopus and PubMed, were excluded. Second, there is ambiguity in author names and nonuniformity in the institutions’ names, which can significantly affect the study’s outcomes.

Identifying research productivity in cancer at AIIMS aids resource allocation, collaboration and strategic planning, enhancing India’s overall cancer research impact and patient outcomes.

To the best of the authors’ knowledge, this study is to use scientometric indicators to evaluate AIIMS’s research productivity with particular reference to cancer for the first time. This detailed analysis provides a deeper understanding of AIIMS’s contribution to cancer research and its potential implications.

The purpose of this article is to study the link between mean shift and inflation coefficient when the underlying null hypothesis is rejected in the analysis of variance (ANOVA) application after the preliminary test on the model specification.

A new approach is proposed to study the link between mean shift and inflation coefficient when the underlying null hypothesis is rejected in the ANOVA application. First, we determine this relationship from the general perspective of Six Sigma methodology under the normality assumption. Then, the approach is extended to a balanced two-stage nested design with a random effects model in which a preliminary test is used to fix the main test statistic.

The features of mean-shifted and inflated (but centred) processes with the same specification limits from the perspective of Six Sigma are studied. The shift and inflation coefficients are derived for the two-stage balanced ANOVA model. We obtained good predictions for the process shift, given the inflation coefficient, which has been demonstrated using numerical results and applied to case studies. It is understood that the proposed method may be used as a tool to obtain an efficient variance estimator under mean shift.

In this work, as a new research approach, we studied the link between mean shift and inflation coefficients when the underlying null hypothesis is rejected in the ANOVA. Derivations for these coefficients are presented. The results when the null hypothesis is accepted are also studied. This needs the help of preliminary tests to decide on the model assumptions, and hence the researchers are expected to be familiar with the application of preliminary tests.

After studying the proposed approach with extensive numerical results, we have provided two practical examples that demonstrate the significance of the approach for real-time practitioners. The practitioners are expected to take additional care before deciding on the model assumptions by applying preliminary tests.

The proposed approach is original in the sense that there have been no similar approaches existing in the literature that combine Six Sigma and preliminary tests in ANOVA applications.

This study aims to examine the impacts of global geopolitical risks (GPRs) and COVID-19 pandemic stringency on the size of Sukuk issuance in Malaysia.

To examine the issue, this paper collected yearly data for the Sukuk issuance from the DataStream, and the rest of the variables, including the control variables from the World Bank, were from 2018 to 2022. Several econometric approaches have been used, that is, ordinary least square (OLS), two-stage least squares (2SLS) and generalized method of moment (GMM) with fixed effects and random effects in examining the impacts.

The results demonstrate that global GPRs negatively impact the size of Sukuk issuance due to the investment risk during the high global geopolitical conflicts, war and rampant terrorism. Besides, the COVID-19 pandemic-related stringency also similarly affects the country's Sukuk issuance market because of the long-time lockdown measures, border closures, travel restrictions and low access to the market. The control variables also demonstrate similar results except for the gross domestic products, which shows positive and significant impacts on the Sukuk market of Malaysia.

The study's policy implications for Sukuk investors and issuers stress the importance of disclosing risk mitigation procedures, strengthening the regulatory framework and raising investor knowledge to attract and protect investors in the Sukuk sector.