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The purpose of this paper is to consider one of the recent and practical extensions of the resource-constrained project scheduling problem (RCPSP) termed as the multi-skill resource-constrained project scheduling problem (MSRCPSP) for investigation. The objective is the minimization of the makespan or total project duration.

To solve this complex problem, the authors propose a teaching–learning-based optimization (TLBO) algorithm in which self-study and examination have been used as additional features to enhance its exploration and exploitation capabilities. An activity list-based encoding scheme has been modified to include the resource assignment information because of the multi-skill nature of the algorithm. In addition, a genetic algorithm (GA) is also developed in this work for the purpose of comparisons. The computational experiments are performed on 216 test instances with varying complexity and characteristics generated for the purpose.

The results obtained after computations show that the TLBO has performed significantly better than GA in terms of average percentage deviation from the critical path-based lower bound for different combinations of three parameters, namely, skill factor, network complexity and modified resource strength.

The modified TLBO proposed in this paper can be conveniently applied to any product or service organization wherein human resources are involved in executing project activities.

The developed model can suitably handle resource allocation problems faced in real-life large-sized projects usually administered in software development companies, consultancy firms, R&D-based organizations, maintenance firms, big construction houses, etc. wherein human resources are involved.

The current work aims to propose an effective metaheuristic for a more realistic version of MSRCPSP, in which resource requirements of activities may be more than one. Moreover, to enhance the exploration and exploitation capabilities of the original TLBO, the authors use two additional concepts, namely, self-study and examination in the search process.

The purpose of this paper is to stir the deliberation on understanding grassroots innovation (GI) phenomenon through the lived experience approach and attempt to address the existing void in current literature.

This paper outlines a human science research approach for studying the subjective reality embedded in the GI phenomenon. Such an approach provides a better and more bottom-up understanding of the underlying individual and interpersonal dynamics shaping the GI.

This study provides a richer understanding of the underlying individual and interpersonal dynamics shaping the GI phenomena. This may serve as an aid for future research on scaling, managing GI and developing entrepreneurial capabilities of the grassroots innovators (GIrs). The study also confirms that no single unilateral theory can fully explain the lived experiences of the GIrs at the ideation, opportunity recognition, prototyping and scaling stage of GI. Rather, it is quintessential to have an integrated holistic perspective for understanding GI. This study also highlights the importance of hermeneutic phenomenology in pro-poor innovation research and practice in the near future.

This paper’s main limitation is whether the findings can be generalized in a wider context. The authors acknowledge this limitation. However, the purpose of this study is not to generalize the findings but rather provide a contextual understanding of what constitutes the lived experiences of GI. The authors recommend that a future study covering greater number of GIrs across India be undertaken to gain a better appreciation of the bigger picture.

Systematic approaches for tapping into GI are conspicuously non-existent and hence a contextual understanding through the proposed holistic lens will assist in thriving of the GI phenomena in South Asian countries such as India.

In the Indian system of medicine – Ayurveda, Musa paradisiaca has been mentioned as a remedy for various diseases and ailments. Based on the folkloric use, the purpose of this paper is to verify and compare the hypoglycemic potential of unripe, ripe and overripe fruit extract of Musa paradisiaca.

Hypoglycemic activity of fruit extracts has been evaluated using various in vitro methods, namely, determination of glucose adsorption capacity, glucose uptake in yeast cells, amylolysis kinetics and glucose diffusion.

The extracts of unripe, ripe and overripe fruits of Musa paradisiaca adsorbed glucose, and the adsorption of glucose increased remarkably with an increase in glucose concentration. In the amylolysis kinetic experimental model, the rate of glucose diffusion was found to increase with time, and all the extracts of unripe, ripe and overripe fruits of Musa paradisiaca demonstrated significant inhibitory effects on the movement of glucose into external solution across the dialysis membrane as compared to the control. The extracts under study also promoted glucose uptake by the yeast cells in all the five glucose concentrations used in the study.

Here, the authors have verified and compared the hypoglycemic potential of Musa paradisiaca, its unripe fruit extract was found to show a better activity than ripe and overripe fruit extracts.

Banana, being an all season readily available fruit, is widely consumed due to its ready availability and low cost. It acts as a complete food for even low socio-economic classes of society, owing to its rich nutritional values. Even in a processed and unprocessed manner, it is an important constituent of diet. The research suggests that instead of consuming ripe and overripe fruit, the unripe fruit will help in management of diabetes.

Industry 4.0 is regarded as a modern industrial phase wherein convergence between horizontal and vertical production systems, along with their interactions, would enable industries to obtain excellent industrial efficiency. This research thus explores the barriers relevant to Industry 4.0 and their cause and effect relations using the decision-making trial and evaluation laboratory (DEMATEL) technique, and this will assist in the implementation of Industry 4.0 in manufacturing industries.

A comprehensive literature review is carried out to outline the barriers for the Industry 4.0 implementation. The investigative techniques used in this research were conducted utilizing a questionnaire as an instrument for collecting data. The data collected were analysed using the method DEMATEL.

The findings indicate that key barriers to implementing Industry 4.0 include their cause and effect relationships. Reported “implementation costs” have been a critical barrier for Industry 4.0 implementation. Prioritization of barriers and their cause and effect relationships was achieved so that decision-makers could concentrate on overcoming such barriers for Industry 4.0 implementation.

The research is intended to assist executives in recognizing the barriers to Industry 4.0 implementation in their manufacturing industries. Furthermore, the strong functional and empirical importance of emerging and digital manufacturing technologies ensures that understanding the necessary barriers to implementation is important.

This is one of the first few empirical studies in the field of Indian manufacturing industries that uses the DEMATEL method framework as a foundation for recognizing cause-effect interactions among the barriers that affect Industry 4.0.

Delivering vaccines to the children who need them requires a supply chain that is efficient and effective. In most of the developing countries, however, the unknown and unresolved supply chain issues are causing inefficiencies in distributing vaccines. There is, therefore, a great need in such countries to recognize the issues that cause delays in vaccine delivery. With this purpose, the present study aims to identify and analyze the key issues in the supply chain of basic vaccines required to immunize children in developing countries.

Based on a field survey of three states of India, in-depth review of relevant literature and experts’ opinions, 25 key issues were recognized as factors of the vaccine supply chain (VSC) and categorized into five main domains. Using integrated interpretive structural modeling and fuzzy analytic network process approaches, the issues have been prioritized to determine their relative importance in the VSC. In addition, a sensitivity analysis has been performed to investigate the priority stability of the issues.

The results of the analysis show that among the five domains of VSC issues, the economic domain with a weight of 0.4262 is the most important domain, followed by the management (0.2672), operational (0.2222), environmental (0.0532) and social (0.0312).

This study focuses on the prioritization of VSC issues; therefore, the results of the present study can provide direction to the decision-makers of immunization programs of developing countries in driving their efforts and resources on eliminating the most important obstacles to design successful vaccination programs.

To the authors’ knowledge, this paper is first to provide a direction to the decision-makers in identifying and managing important issues through the use of an analytical approach.