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This paper is to contribute to addressing the knowledge gap on the roles of rural cooperatives in disaster risk reduction and management (DRRM).

This study adopts a mixed-methods approach highlighting indigenous strategies of community engagement – the pantatabtaval/tong tongan (brainstorming and dialogs), pan-iestorya/dad-at (storytelling session) and field observations with 50 village-level cooperatives in Benguet, Philippines to understand their contributions to local DRRM.

Rural cooperatives in Benguet have evolved on their context of service from mere rural development to now include DRRM donations and aid for disaster-affected families, credit and loans are the most common services of these rural cooperative extended to their members to deal with risks of disasters.

Most research on cooperatives focuses on their contribution to socio-economic development and only few dealt with DRRM. This paper explores the link of these rural organizations with DRRM drawing evidence from cooperatives in the rural communities of Benguet, Philippines.

The purpose is to assess Industry 4.0 (I4.0) readiness index using fuzzy logic and multi-grade fuzzy approaches in an automotive component manufacturing organization.

I4.0 implies fourth industrial revolution that necessitates vital challenges to be dealt with. In this viewpoint, this article presents the evaluation of I4.0 Readiness Index. The evaluation includes two levels with appropriate criteria and factors. Fuzzy logic approach is used for assessment. Furthermore, the results obtained from fuzzy logic have been benchmarked with multi-grade fuzzy approach.

The proposed assessment model has successfully utilized fuzzy logic approach for assessment of I4.0 readiness index of automotive component manufacturing organization. Based on fuzzy logic approach, readiness index of I4.0 has been found to be (4.74, 6.26, 7.80) which is further benchmarked using multi-grade fuzzy approach. Industry 4.0 readiness index obtained from multi-grade fuzzy approach is 6.258 and thus, validated. Furthermore, 20 weaker areas have been identified and improvement suggestions are provided.

The assessment module include two levels (Six Criteria and 50 Factors). The assessment model could be expanded based on advancements in industrial developments. Therefore, future researchers could utilize findings of the readiness model to further develop multi-level assessment module for Industry 4.0 readiness in organization. The developed readiness model helped researchers in understanding the methodology to assess I4.0 readiness of organization.

The model has been tested with reference to automotive component manufacturing organization and hence the inferences derived have practical relevance. Furthermore, the benchmarking strategy adopted in the present study is simple to understand that makes the model unique and could be applied to other organizations. The results obtained from the study reveal that fuzzy logic-based readiness model is efficient to assess I4.0 readiness of industry.

The development of model for I4.0 readiness assessment and further analysis is the original contribution of the authors. The developed fuzzy logic based I4.0 readiness model indicated the readiness level of an organization using I4RI. Also, the model provided weaker areas based on FPII values which is essential to improve the readiness of organization that already began with the adoption of I4.0 concepts. Further modification in the readiness model would help in enhancing I4.0 readiness of organization. Moreover, the benchmarking strategy adopted in the study i.e. MGF would help to validate the computed I4.0 readiness.

The purpose of this paper is to analyse performance (on efficiency) of agricultural cooperatives in Mpumalanga province, South Africa, using Data Envelopment Analysis (DEA). The empirical investigation is motivated by the dearth of empirical literature on agricultural cooperatives’ performance measurement and its correlates.

The study employed DEA and applied the input minimisation constraint. The authors used the data from 19 agricultural cooperatives which had complied with reporting on their annual financial statements (AFS) in the financial year 2014/2015. The input variables were total assets and total expenses, and the output variables were revenue and profit.

The average technical efficiency was found to be 72 per cent efficient indicating the presence of 28 per cent resource wastages. Of the 19 decision-making units, only 5 (26 per cent) were 100 per cent efficient. It should be noted that the 26 per cent that were technically efficient were also operating at constant returns to scale (optimal resource allocation).

Data limitation was with regard to 19 cooperatives, which means that if more agricultural cooperatives could be analysed, the results will be different.

There are more than 60 agricultural cooperatives in the province, and yet only 19 could report on their AFS. This is an indication that there is a gap in governance, and policy makers and government need to revisit support, over and above funding, and issues of governance have to be strengthened.

Agricultural cooperatives are created as vehicles that can stimulate the economy and contribute towards job creation. If the cooperatives do not perform or are not sustainable, the socio-economic conditions of the communities in which they operate will never realise the economic gains.

The study was necessitated by the continued focus on government based on the cooperatives, as there is a dearth of empirical literature separating managers’ reports and empirically proven studies/results.

The aim of this study is to analyze workforce attributes related to Industry 4.0 using fuzzy decision-making trial and evaluation laboratory (DEMATEL) and fuzzy combinative distance-based assessment (CODAS).

Technological trends stipulate various revolution in industries. Industry 4.0 is a vital challenge for modern manufacturing industries. Workforce adoption to such challenge is gaining vital importance. Therefore, such workforce-related attributes need to be identified for enhancing their performance in Industry 4.0 environment. In this context, this article highlights the analysis of 20 workforce attributes for Industry 4.0. Relevant criteria are prioritized using fuzzy DEMATEL. Workforce attributes are prioritized using fuzzy CODAS.

The key attributes are “Skills/training in decision-making (WA2)”, “Competences in complex system modelling and simulation (WA1)” and “Coding skills (WA20)”.

In the present study, 20 workforce attributes are being considered. In future, additional workforce attributes could be considered.

The study has been conducted based on inputs from industry experts. Hence, the inferences have practical relevance.

The analysis of workforce attributes for Industry 4.0 using MCDM methods is the original contribution of the authors.

This study aims to carry out the deposition of zinc sulfide (ZnS) thick films on glass and silicon (100) substrates using radio frequency (RF) magnetron sputtering method at different powers. Film structure has been analyzed by X-ray diffraction (XRD); the patterns showed that the films possesses a cubic structure with (111) preferred orientation. Photoluminance (PL) intensity of the films has been related to the crystallinity, which is varied with the power.

Scanning electron microscope (SEM) images have been used to discover the films’ morphology. The stoichiometry has been confirmed by energy dispersive X-ray spectroscopy (EDX) analysis. MicroRaman spectroscopy has been used to validate the film structure. Gas-sensing studies were carried out by means of a static gas chamber to sense acetone, ethanol, methanol, H₂O and NH₃ vapor in air ambient.

ZnS has a stoichiometric and cubic structure. The band gaps and photoluminance intensity of the films are correlated with the crystallinity, which is varied with the power. The EDX analysis approved the stoichiometry of the prepared films. Acetone, ethanol, humidity (H₂O), methanol and NH₃ vapor gases were used to justify the sensing properties at 25°C of the thickest ZnS film.

High-quality ZnS films have been obtained at different powers without annealing. Gases sensing properties at 25°C are justified for deposited ZnS films using acetone, ethanol, humidity (H₂O), methanol and NH₃ vapor gases. It reveals good response for NH₃ and humidity vapors at room temperature; the sensing functioning at this temperature was attractive in recent research.

This paper investigated the possibilities of implementing inclusive education in the tertiary-level language classrooms and suggests new teaching methodologies adhering to the guidelines of multicultural education (MCE) framework. It explored how Indian teachers fostered social inclusivity in ESP (English for Specific Purposes) classrooms and documented the methods used by the language teachers to sustain a socially inclusive environment in the classroom.

This qualitative study undertaken with 17 faculty members using online interviews and surveys as tools revealed the challenges faced by the teachers.

The results have implications towards teacher training as there is a clear dearth of teacher strategies to foster an equitable and inclusive learning environment inside the classroom.

Classrooms are the sources of values and perspectives, and teachers are responsible for providing equal opportunities to students who are otherwise marginalised in society.

Inclusive education aims at providing equal opportunities to people despite the differences in terms of race, class, caste, region, religion, gender, sexuality, ethnicity and disabilities. India being a multilingual and multicultural country, inculcating values in students to enable them to reflect beyond these differences becomes important.

Farmers producer organisations (FPOs) play the most crucial role in the agriculture supply chain system, aiming to redress the balance between farming and marketing activities of agricultural produce. The purpose of this study is to assess the performance of FPOs using data envelopment analysis (usually referred to as DEA) on 34 FPO units selected from the state of Rajasthan.

One of the most commonly used techniques to examine business performance is the application of DEA. The application of DEA requires the selection of inputs and outputs. This study takes three inputs and three outputs based on the insights drawn from the field survey. While the input variables consist of total assets, paid-up capital and the number of economic activities, the three output variables are turnover, net profit and number of members benefitted. Broadly, these variables encapsulate the operational performance of the business units.

This study’s findings reveal that the estimated relative efficiency score of the input-oriented CCR (Charnes, Cooper, and Rhodes) model ranges from 0.06 to 1. Interestingly, only one FPO has reported a relative efficiency (RE) score of one, whereas the remaining FPOs fall below the efficiency frontier. However, 15 FPOs report an RE score of one in the output-oriented CCR approach. Considering the estimates obtained in the input- and output-oriented BCC (Banker, Charnes and Cooper) models, this study found that about 20% of the FPOs report an efficiency score greater than 0.80. Moreover, three FPOs are on the frontier line. An examination of the scale efficiency score in the input-oriented model, 45% of the FPOs have an efficiency score greater than 0.80, whereas almost all FPOs achieve a scale efficiency score greater than 0.80 in the output-oriented model. Overall, the results imply that the FPOs should place greater emphasis on the efficient utilisation of the inputs to enhance the overall business performance and productivity.

The findings of this study provide vital insights into the specific inputs and outputs that determine the performance efficiency of FPOs and identify the potential areas for improving the existing inefficient FPOs.

This study contributes to the repository of the existing empirical studies in three distinct ways. First, the authors hardly found any previous studies that quantitatively assess the business performance of FPOs using the DEA technique. Second, the effort to identify the slacks associated with each input and output variable in input- and output-oriented models gives insights on improvable areas for inefficient FPOs. Third, the authors attempt to demystify the empirical obfuscations by highlighting the major challenges FPOs face in the state of Rajasthan.

Additive manufacturing (AM) technologies have tremendous applications in industries owing to their unique advantages. Sustainable AM (SAM) is gaining significance because of lightweight structures, lattice geometries and customized parts for industrial applications. To facilitate design for SAM, design guidelines from AM and environment viewpoints are to be analyzed. In this context, this paper aims to present the analysis of SAM guidelines.

This work divides 26 identified SAM guidelines into four categories. Grey axiomatic design was used to calculate the weights of guidelines categories. Further, the grey technique for order preference by similarity to ideal solution was used as a solution methodology to prioritize the SAM guidelines.

The top identified guidelines are “Design for reusability” and “Optimize part orientation for build time and roughness.” Implementing proper design guidelines leads to many sustainable benefits such as minimum material consumption, energy consumption and emissions.

This study would facilitate Am product designers to deploy prioritized guidelines for enhancing the effectiveness of the additively manufactured product with sustainability benefits. The prioritized guidelines would guide the AM product designers to take maximum advantage of the AM process by deploying design for AM and design for environment guidelines. This study contributed a structured approach for design engineers and practitioners to deploy guidelines during the early stages of product design to ensure AM feasibility with minimal environmental impact.

The present study aimed to assess performance of Industry 4.0 (I4.0) in case organization by considering potential performance measures and analysis using scoring approach.

50 performance measures grouped into five dimensions namely manufacturing management, manufacturing economics, manufacturing strategy, manufacturing technology and workforce were considered for the analysis. The study had been done with relevance to automotive component manufacturing organization. Further, questionnaire for each performance measure was developed to gather expert inputs regarding different performance aspects of I4.0 in case organization. Reliability of the expert responses towards questionnaire was assessed by computing Cronbach's alpha (a) using Statistical Package for the Social Sciences (SPSS) software.

Findings of the study revealed overall I4.0 performance index (OIPI) of 0.71, i.e. 71% signifying improvement scope of 29% pertaining to I4.0 adoption. Gap analysis was performed across dimensions and performance measures to realize the weaker areas. Gap analysis revealed workforce dimension with highest gap and manufacturing management with lowest gap. The gaps that obstruct performance of I4.0 are being recognized and proposals for improvement were provided to the industrial practitioners. Based on further analysis, dimensions and performance measures found to be weaker.

The study helped industrial practitioners and managers to create the foundation for evaluating performance of I4.0-focused organization. Industry practitioners can employ the study to understand different performance measures with respect to different dimensions and realize the significance of I4.0 adoption.

The identification of performance dimensions and measures for I4.0 performance measurement and assessment using scoring approach is the original contribution of the authors.

The manufacturing domain presently focusing on Industry 4.0 (I4.0). One such domain is the automotive sector. The purpose of this study is to analyse the I4.0 research studies with a focus on the automotive sector using a systematic literature review (SLR).

This paper presents a SLR of previous studies on I4.0 characteristics from its inception to performance measures focusing on the automotive sector. A total of 90 papers published in reputed journals during 2014–2020 were collected from major publishers, namely, Elsevier, Springer, Taylor and Francis, Emerald, Institute of Electrical and Electronics, MDPI, etc.

The findings of the study provided vital insights on various perspectives of I4.0 in an automotive organization. Moreover, this systematic analysis would help the automotive industry policymakers in implementing I4.0 in an organization. Based on the SLR, a conceptual framework is established to guide industry practitioners towards I4.0 implementation. The review findings could be used to carry out future studies in assessing the readiness of I4.0 in the organization with the help of a survey.

The limitation of the study is in the adoption of the sampling approach. In the present study, conference papers and refereed journals have been considered based on the relevance of I4.0 in the automotive industry. As I4.0 is a growing concept, non-refereed articles, book chapters and white papers may cover practical aspects regarding I4.0 implementation that need to be considered for depth analysis. Moreover, the framework needs to be validated with various automotive industries for ensuring practical validity.

The unique contribution of the study is the SLR of I4.0 in manufacturing with a focus on the automotive sector.