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Proposing an improved model for evaluating criticality of non-value added (waste) in operation is necessary for realizing sustainable manufacturing practices. The purpose of this paper is concerning on improvement of the decision support model for evaluating risk criticality lean waste occurrence by considering the weight of modified FMEA indices and the influence of waste-worsening factors causing the escalation of waste risk magnitude.

Integration of entropy and Taguchi loss function into decision support model of modified FMEA is presented to rectify the limitation of previous risk reprioritization models in modified FMEA studies. The weight of the probability components and loss components are quantified using entropy. A case study from industry is used to test the applicability of the integration model in practical situation.

The proposed model enables to overcome the limitations of using subjective determination on the weight of modified FMEA indices. The inclusion of the waste-worsening factors and Taguchi loss functions enables the FMEA team to articulate the severity level of waste consequences appropriately over the use of ordinal scale in ranking the risk of lean waste in modified FMEA references.

When appraising the risk of lean waste criticality, ignorance on weighting of FMEA indices may be inappropriate for an accurate risk-based decision-making. This paper provides insights to scholars and practitioners and others concerned with the lean operation to understand the significance of considering the impact of FMEA indices and waste-worsening factors in evaluating criticality of lean waste risks.

The method adopted is for quantifying the criticality of lean waste and inclusion of weighting of FMEA indices in modified FMEA provides insight and exemplar on tackling the risk of lean waste and determining the most critical waste affecting performability of company operations.

Integration of the entropy and Taguchi loss function for appraising the criticality of lean waste in modified FMEA is the first in the lean management discipline. These findings will be highly useful for professionals wishing to implement the lean waste reduction strategy.

The purpose of this paper is to introduce the integrated model of the Preference Selection Index (PSI) and the prospect theory as new means to appraise the impact of supply chain sustainability risks based on five pillars of sustainability. Research has shown that sustainability risk assessment has a strong positive impact on improving the performance of enterprises.

This study adopts a new decision support model for assessing supply chain sustainability risk based on additional failure mode and effect analysis parameters and its integration with PSI methodology and prospect theory. A case example of the supply chain small and medium enterprise (SME) producing fashion have been used in this study.

The result of this study reveals some critical supply chain sustainability risks affecting the sustainability of enterprises under study.

The use of a limited sample is often associated as a limitation in the research studies and this study is based on findings from SMEs in the fashion retail supply chain. This preliminary study provides academics and practitioners an exemplar of supply chain sustainability risk assessment using integration of the PSI method and prospect theory.

The result of this study is beneficial for practitioners, particularly owner–managers of SMEs who can use this study as guidance on how to consider risk behavior to identify and select the critical sustainability risks and plan mitigating strategies accordingly.

Scientific studies on using the PSI and its integration with prospect theory as means to assess the criticality of supply chain sustainability risks is very rare. To the best of the authors’ knowledge, this is the first paper that presents the integrated model of the PSI and prospect theory to rank supply chain sustainability risks based on five pillars of sustainability.

This study proposes a new model for assessing supply chain sustainability risk integrating subjectivity and objectivity of decision-maker. Research has shown the vacancy of study in dealing with the above issue. To fill this research gap, a new decision support model considering the subjectivity and objectivity of decision-makers in assigning the weight of the supply chain risk reprioritization criteria is presented and demonstrated using a case example.

This study adopts a new decision support model for assessing supply chain sustainability risk based on additional failure mode and effect analysis (FMEA) parameters and its integration with preference selection index (PSI) methodology and the Shannon entropy. A case example of the supply chain small and medium enterprise (SME) producing handy crafts has been used in this study.

The result of the study reveals critical sustainability risk dimensions and their risk elements demanding management attention to support realization to a more sustainable business operation.

The use of a single case study is often associated as a limitation in the research studies, and this study is based on findings from SMEs in the handy craft sector in a developing country. Nonetheless, future studies may focus on replicating this study using more samples. This preliminary study provides academics and practitioners with an exemplar of supply chain sustainability risk assessment from the SME in a developing country.

The result of this study is beneficial for practitioners, particularly owner-managers of SMEs who can use this study as guidance on how to identify and select the critical sustainability risks and plan mitigating strategies accordingly.

Scientific effort on appraising criticality of supply chain sustainability risks considering subjectivity and objectivity of decision-maker simultaneously is missing in earlier studies. To the best of the author’s knowledge, this is the first paper applying the PSI and Shannon entropy method and using it for evaluating the impact of supply chain risk based on five sustainability pillars. The findings and suggestions for future research initiatives will provide new insights for scholars and practitioners in managing SME supply chain sustainability risks.

In the present study, the thermal performance of engine radiator using conventional coolant and nanofluid is determined experimentally for the different flow rates. Further, the study implemented the Integrated Taguchi-GRA-PCA for optimising the heat transfer performance.

Nanofluids were prepared by taking ethylene glycol and water (25:75 by volume) with volume fraction of 0.01, 0.03 and 0.05% of TiO₂ nanopowder. Experimental Data were collected based on the design of experiments (DOE) L9 orthogonal array using Taguchi method. Statistical analysis via Grey relation analysis (GRA) and principal component analysis (PCA) were done to determine the role of experimental parameters on heat transfer coefficient and rate of heat transfer. Impact of three control factors, vol. % of TiO₂ concentration (φ), flow rate (LPH), and sonication time (min) on the performance characteristics on heat transfer coefficient and ratio of heat transfer rate is analysed to get the best combination of the parameters involved.

Analysis revealed the importance of parameters on heat transfer coefficient and can be sorted in terms of contributions from higher to lower degree. Finally, ANOVA test has been conducted to validate the effect of process parameters. The major controllable parameter is φ (concentration), contributing about 32.74%, then flow rate contributing 32.5% and finally sonication time showing small contribution of 18.57%.

A grey relational analysis integrated with principal component analyses (PCA) are implemented to get the optimum heat transfer coefficient and ratio of heat transfer rate. The novelty of the work is to adopt and implement the Integrated Taguchi-GRA-PCA first time for the purpose of thermal performance analysis of engine nano-coolant for radiator.

The regular occurrence of natural disasters elevates the need for an effective method to measure organizational preparedness in responding to the adverse impact of disasters. In this context, this paper presents a new decision support model to assess organizational disaster preparedness using both subjective and objective disaster preparedness criteria in a multi-criteria decision-making context.

The statistical variance method is integrated with the proximity value index (PVI) technique to determine priority scores in order to rank organizational disaster readiness.

The results of applying the integrated model developed herein enable decision-makers to make informed decisions for assigning priority ranking of organizational disaster preparedness in a simpler and more efficient way.

Human resource is the most impacting criterion affecting hospital preparedness in undertaking action to cure disaster victims.

This paper offers an exemplar of a simple and efficient decision-making process considering the subjectivity associated with decision-making as well as the objectivity of data used for determining the priority ranking of organizational disaster preparedness.

Integrating statistical variance method with the PVI technique is novel and it has not been presented in previous studies. In fact, this study is the first to integrate both methods for selecting the priority ranking of organizational disaster preparedness.

Beyond the rhetoric of Nigeria's policymakers, there are multifaceted challenges threatening sustainable development (SD) in Nigeria under climate change (CC). To strengthen theory and practice, this chapter discusses SD under CC in Nigeria using SWOT analysis. The exploratory focus of this chapter made the qualitative research method, an interpretivist research paradigm, most appropriate. Data sourced from scholarly articles and other secondary resources were reviewed, integrated and synthesised using SWOT analysis. At the end of the SWOT analysis, four insights emerged. The strengths and opportunities of SD under CC include increased awareness and growing access to climate-friendly technologies, sustainable finance, climate-friendly agriculture, solar technologies and renewable energy solutions, among others. The weaknesses and threats include deforestation, unabated gas flaring, rising carbon emissions and exorbitant cost of climate-friendly technologies, among others. The chapter explicates the need for policymakers and regulatory agencies in Nigeria to consolidate the strengths, correct all weaknesses, harness opportunities and avert the looming threats of CC. The chapter contributes to the three themes of SD by affirming that CC comes with devastating consequences that evidently pose existential risks and threats to people, profits and the planet. Consequently, policymakers need to mobilise sufficient resources and capabilities for CC adaptation and mitigation to achieve SD in Nigeria.

This study aims to assess the effect of knowledge management (KM) development and emotional intelligence (EI) on the productivity of librarians regarding the mediating role of job motivation (JM) and job feedback (JF).

This study was carried out in two phases. First, the variables affecting the productivity of librarians were identified and selected through an explorative study and by surveying their opinions. Then, the theoretically designed model was administered to 312 librarians at Iranian public libraries. A questionnaire was used to collect data, and the structural equation modelling technique was used to analyse data.

The results of this study showed that KM and EI, mediated by JM and JF, had a positive and significant effect on developing the librarians’ productivity. The results also revealed that JF had a positive effect on JM and that JF was more effective on productivity than JM. This study marginally proved the direct effect of KM and EI on productivity where KM was more effective than EI on productivity. Knowing the effects of organizational and individual factors on the higher productivity of librarians in public libraries will help library managers make more efficient use of those factors in developing the capabilities of librarians and enhancing productivity.

This study is one of the few studies of its kind that facilitates the perception of the concept of productivity in public libraries and also the assessment of the effects of organizational and individual factors on the librarians’ productivity.

This study aims to investigate the influence of Muslim tourist perceived value (MTPV) on Muslim millennials’ intention to revisit Bandung (Indonesia) with customer satisfaction as an intervening variable.

Using quantitative methods, this study analyzed responses to a questionnaire distributed to 250 respondents from all over Indonesia. To test the hypothesis, the data were analyzed through Path Analysis using SPSS 24.I software.

The results suggest that MTPV has a significant effect on revisit intention to the city. This finding affirms that Islamic values and customer satisfaction are very important in encouraging millennial Muslims to revisit Bandung (Indonesia).

To increase Muslim millennials’ intention to revisit Bandung (Indonesia), tourist perceived value and satisfaction are central factors. The government's role is central in promoting halal tourism through various platforms, such as social media, seminars, workshops inter alia to increase MTPV and satisfaction rate toward the city. In addition, stakeholders in tourism sector should raise the awareness to support and encourage halal tourism through certifications of halal products and tourism services, and view halal tourism as a promising sector of tourism.

This study is the first to study the effects of Muslim tourists perceived value on revisit intention of millennial Muslims to Bandung (Indonesia) with customer satisfaction as an intervening variable. This study reveals the strengths and weaknesses of the perceived value of Muslim tourists in influencing millennial Muslims to revisit the city.