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To meet energy demand and tackle the challenges posed by global warming, Bagasse-based Cogeneration Power Generation (BCPG) plant in sugar mills have tremendous potential due to large-scale supply of renewable fuel called bagasse. To meet this goal, an integrated framework has been proposed for analyzing performance issues of BCPG.

Intuitionistic Fuzzy Lambda-Tau (IFLT) approach was implemented to compute various reliability parameters. Intuitionistic Fuzzy Failure Mode and Effect Analysis (IF-FMEA) approach has been implemented for studying risk issues results in decrease in plant's availability. Moreover, IF- Technique for Order Performance by Similarity to Ideal Solution (IF-TOPSIS) is implemented to verify accuracy of IF-FMEA approach.

For membership and non-membership functions, availability decreases to 0.0006% and 0.0020% respectively for spread ±15% to ±30%, and further decreases to 0.0127% and 0.0221% for spread ±30% to ±45%. Under risk assessment failure causes namely Storage tank (ST3), Valve (VL6), Transfer pump (TF8), Deaerator tank (DT11), High pressure heater and economiser (HP15), Boiler drum and super heater (BS22), Forced draft and Secondary air fan (FS25), Air preheater (AH29) and Furnace (FR31) with Intuitionistic Fuzzy Hybrid Weighted Euclidean Distance (IFHWED) based output scores – 0.8988, 0.9752, 0.9400, 0.8988, 0.9267, 1.1131, 1.0039, 0.8185, 1.0604 were identified as the most critical failure causes.

Reliability and risk analysis results derived from IFLT and IF-FMEA approaches respectively, to address the performance issues of BCPG is based on the quantitative and qualitative data collected from the industrial experts and maintenance log book. Moreover, to take care of hesitation in expert's knowledge, IF theory-based concept is incorporated so as to achieve more accuracy in analysis results. Reliability and risk analysis results together will be helpful in analyzing the performance characteristics and diagnosis of critical failure causes, which will minimize frequent failure in BCPG.

The framework will help plant managers to frame optimal maintenance policy in order to enhance the operational aspects of the considered unit. Moreover, the accurate and early detection of failure causes will also help managers to take prudent decision for smooth operation of plant.

The results obtained ensure continuous operation of plant by utilizing the bagasse as fuel in boiler and also mitigate the wastages of fuel. If this bagasse (green fuel) is not properly utilized, there remains a dependency on coal-based power plants to meet the power demand. The results obtained are useful for decreasing dependency on coal, and promoting bagasse as the green, and alternative fuel, the emission by burning of these fuels are not harmful for environment and thereby contribute in preventing the environment from harmful effect of GHGs gases.

IFLT approach has been implemented to develop reliability modeling equations of the BCPG unit, and furthermore to compute various reliability parameters for both membership and non-membership function. The ranking results of IF-FMEA are compared to IF-TOPSIS approach. Sensitivity analysis is done to check stability of proposed framework.

This study aims to focus on assessing the psychometric properties necessary to validate the internal structure of the TOURQUAL scale.

A quantitative research study was conducted in collaboration with the Brazilian Network of Tourism Observatories, comprising 927 respondents surveyed between October 2021 and May 2022. The data analysis involved the application of descriptive statistics and exploratory factor analysis, in alignment with the principles outlined in the Standards for Educational and Psychological Testing 2014 to validate the scale.

The findings of this study validate the TOURQUAL scale as a robust tool for assessing the perceived quality of tourist services, with results demonstrating one-dimensionality and replicability.

To the best of the authors’ knowledge, this study is the first to assess the psychometric properties for validating the internal structure of the TOURQUAL scale.

This study investigates the validity of Ferreira et al.’s (2020) Organizational Bullshit Perception Scale by examining its distinctiveness from similar constructs (perceptions of organizational politics, organizational cynicism, procedural justice) and its predictive validity through its relations with important organizational attitudes (organizational identification) and behaviors (counterproductive work behavior and organizational citizenship behavior). This study also examines the moderating effects of honesty–humility on the relations between organizational bullshit perception and the outcomes of counterproductive work behavior, organizational citizenship behavior and organizational identification. Finally, this study examines the incremental validity of organizational bullshit perception in predicting counterproductive work behavior, organizational citizenship behavior and organizational identification above and beyond similar constructs in an exploratory fashion.

Survey data were collected from a sample of working adults online via Amazon’s Mechanical Turk platform across two waves (final N = 323 for wave 1 and 174 for wave 2), one month apart.

The results indicate that organizational bullshit perception, as measured by Ferreira et al.’s (2020) scale, represents a distinct construct that has statistically significant relations with counterproductive work behavior, organizational citizenship behavior and organizational identification, even after controlling for procedural justice, organizational cynicism and perceptions of organizational politics. The results, however, showed no support for honesty–humility as a moderator.

These findings suggest that organizations can benefit from assessing and working to alleviate their employees’ perceptions of organizational bullshit. This construct predicts behaviors and attitudes important for organizational functioning.

This study adds to Ferreira et al.’s (2020) original work by demonstrating organizational bullshit perception’s distinctiveness from existing constructs in the literature and its implications for organizations and their employees.

Scholarly literature on the Internationalization of Education has generated important theories, debates, and insights supporting in-depth understandings of the field, yet we lack comprehensive reviews exploring the design, implementation, and impact of practical approaches. The present review addresses this gap, mapping the literature on international curriculum design, identifying trends and themes across approaches and pedagogies while revealing limitations and lack of attention to issues that inhibit practice in the field. It highlights the privileging of “instrumental,” or quantifiable skills-based curricula, over “transformative” internationalization dedicated to social justice and equity, and observes important disconnects between theory and practice: publications in the field offer critical conceptualizations of what internationalized curricula should achieve and why but with little attention to specific content and teaching practice that would lead to achieving these objectives. The review further analyzes such disconnect in the literature dedicated to decolonial internationalizing pedagogies, while simultaneously illuminating how prevailing decolonial theories of international education erase and ignore parts of the world. It concludes by contending that approaches to the internationalization of curriculum would benefit from increased practical frameworks that could guide educators, practitioners, and students in crucial conversations at the intersections of social justice and International Education.

This chapter argues that the concept of ‘mass supervision’, and indeed the concept of ‘mass incarceration’ from which it derives, is both quantitatively and qualitatively indeterminate when applied outside of the context of the US. However, the qualitative indeterminacy of mass supervision only holds so long as one treats the word ‘mass’ as being an analogy to mass consumption. This chapter therefore considers an alternative construction of ‘mass’ punishment in terms of mass production. Comparing the philosophies of production associated with Henry Ford and William Morris with the scholarship of Michel Foucault and Fergus McNeill reveals that mass supervision can authentically claim to be qualitatively ‘massive’, given the bespoke and one-on-one nature of traditional supervision. It is thus possible to speak coherently of ‘mass supervision’ in an international context, although this negative conception of a problem invites questions about the best solution that it generally leaves open.

The purpose of this study is to develop a method to assess social performance. Traditionally, environment, social and governance (ESG) rating providers use subjectively weighted arithmetic averages to combine a set of social performance (SP) indicators into one single rating. To overcome this problem, this study investigates the preconditions for a new methodology for rating the SP component of the ESG by applying machine learning (ML) and artificial intelligence (AI) anchored to social controversies.

This study proposes the use of a data-driven rating methodology that derives the relative importance of SP features from their contribution to the prediction of social controversies. The authors use the proposed methodology to solve the weighting problem with overall ESG ratings and further investigate whether prediction is possible.

The authors find that ML models are able to predict controversies with high predictive performance and validity. The findings indicate that the weighting problem with the ESG ratings can be addressed with a data-driven approach. The decisive prerequisite, however, for the proposed rating methodology is that social controversies are predicted by a broad set of SP indicators. The results also suggest that predictively valid ratings can be developed with this ML-based AI method.

This study offers practical solutions to ESG rating problems that have implications for investors, ESG raters and socially responsible investments.

The proposed ML-based AI method can help to achieve better ESG ratings, which will in turn help to improve SP, which has implications for organizations and societies through sustainable development.

To the best of the authors’ knowledge, this research is one of the first studies that offers a unique method to address the ESG rating problem and improve sustainability by focusing on SP indicators.

Sources highlight that insufficient skills of site supervisors considerably influence the progress of many construction projects in numerous countries. This study intends to identify the crucial supervisory competencies that influence the effectiveness of building project operations in the context of developing countries.

The crucial construction site supervisory competencies were qualitatively identified through a comprehensive literature survey and a series of expert interviews with the use of thematic analysis approaches. A questionnaire survey was then carried out among 154 building project firms to quantify the impacts of the competencies on the effectiveness of project tasks with the use of the relative importance index approach. Additionally, industry-consultative meetings were held using problem-focused communication strategies to scrutinise the necessary actions.

Overall, 22 cognitive elements and 24 skills/abilities of supervisors were determined as being critical according to their impact values, where the site supervisors cognitive domains in construction planning and construction materials were determined as the top-ranking competencies in the list, with their manual skills/abilities in labour management and labour performance evaluation. Accordingly, a group of key competency outcomes were produced for the considerations in developing new site supervisory training components. Relevant statistical analysis results and the industry consultative outcomes substantiated the validity and dependability of the overall results.

Although the study's focus was to site supervision procedures used in Sri Lankan building construction projects, the overall findings/outcomes might be put to the test in related situations in other emerging industries in other countries.

The study has constructed a base that shows how the significant site supervisory competencies influence the effectiveness of building construction operations, contributing to making a big difference in the methods of reskilling/upskilling in the industry associated with construction labour, supervision, efficiency management and productivity enhancement.

In response to environmental uncertainty, organizations rely on independent, empowered teams to increase their responsiveness to change. The purpose of this paper is to analyze how objectives and key results (OKRs) can contribute to creating a shared vision which keeps the different, empowered teams aligned.

Through a qualitative study, this paper develops a conceptual model of how OKRs lead to a shared vision. The authors interview professionals in nine organizations differing in size and industry who recently introduced agile, focusing on the main hurdles encountered and benefits obtained from the methodology.

The findings confirm that OKRs are an effective goal-setting methodology and suggest that their successful implementation builds on the new ways of organizing introduced by the agile methods. Moreover, the findings suggest that OKRs contribute to developing a shared vision and increase the alignment: first, the organizational vision becomes clear and its definition is participatory; second at the team level, individuals align around a shared team vision through participative definition of objectives.

The contribution of the paper is two-fold: this study provide an overview on the methodology, which is diffused from a practice perspective, but has not yet been addressed from a theoretical point of view. And this study connects OKRs to extant theory on goal-setting and vision development. This study shows they act as a coupling mechanism which helps empowered and independent teams together.

This study aims to determine the impact of innovation conviction, innovation mindset and innovation creed on the need for achievement and the success of women entrepreneurs. The study also investigates the impact of entrepreneurial education in moderating the relationship between the need for achievement and women’s entrepreneurial success.

The study used a structured questionnaire and a quantitative research design. Data were gathered from 304 women entrepreneurs in South Africa’s Gauteng province. The data were analysed using smart partial least squares.

The results showed that innovation conviction, innovation mindset and innovation creed have positive and significant impacts on the need for achievement. It was also discovered that the need for achievement and entrepreneurial education have a positive and significant impact on women's entrepreneurial success. Moreover, the results showed that entrepreneurial education had a positive and significant moderating effect on the nexus between the need for achievement and women's entrepreneurial success.

By comprehensively examining the impact of innovation conviction, innovation mindset and innovation creed on the need for achievement and women's entrepreneurial success, this study has valuable implications for academics.

This research will add to the corpus of information on women's entrepreneurship and small business management in Africa, which is generally overlooked by academics in developing countries.

The COVID-19 pandemic has showcased the lack of resilience found in the global value chains (GVCs) of multinational enterprises (MNEs). Existing evidence shows that MNEs have only recently and slowly started recovering and attempting to rebuild the resilience of their GVCs. This paper analyzes the challenges/inhibitors faced by MNEs in building their resilience through their GVCs.

A four-stage hybrid model was used to identify the interrelationship among the identified inhibitors and to distinguish the most critical ones by ranking them. In the first stage, we employed a modified total interpretive structural modeling (m-TISM) approach to determine the inter-relationship among the inhibitors. Additionally, we identified the inhibitors' driving power and dependency by performing a matrix multiplication applied to classification (MICMAC) analysis. In the second stage, we employed the Pythagorean fuzzy analytic hierarchy process (PF-AHP) method to determine the weight of the criteria. The next stage followed, in which we used the Pythagorean fuzzy combined compromise solution (PF-CoCoSo) method to rank the inhibitors. Finally, we performed a sensitivity analysis to determine the robustness of the framework we had built based on the criteria and inhibitors.

We find business sustainability to have the highest importance and managerial governance as the most critical inhibitor hindering the path to resilience. Based on these insights, we derive four research propositions aimed at strengthening the resilience of such GVCs, followed by their implications for theory and practice.

Our findings contribute to the extant literature by uncovering key inhibitors that act as barriers to MNEs. We link out our findings with a number of propositions that we derive, which may be considered for implementation by MNEs and could help them endow their GVCs with resilience.