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The incompatibility of natural fibers with polymer matrices is one of the key obstacles restricting their use in polymer composites. The interfacial connection between the fibers and the matrix was weak resulting in a lack of mechanical properties in the composites. Chemical treatments are often used to change the surface features of plant fibers, yet these treatments have significant drawbacks such as using substantial amounts of liquid and chemicals. Plasma modification has recently become very popular as a viable option as it is easy, dry, ecologically friendly, time-saving and reduces energy consumption. This paper aims to explore plasma treatment for improving the surface adhesion characteristics of sisal fibers (SFs) without compromising the mechanical attributes of the fiber.

A cold glow discharge plasma (CGDP) modification using N₂ gas at varied power densities of 80 W and 120 W for 0.5 h was conducted to improve the surface morphology and interfacial compatibility of SF. The mechanical characteristics of unmodified and CGDP-modified SF-reinforced epoxy composite (SFREC) were examined as per the American Society for Testing and Materials standards.

The cold glow discharge nitrogen plasma treatment of SF at 120 W (30 min) enhanced the SFREC by nearly 122.75% superior interlaminar shear strength, 71.09% greater flexural strength, 84.22% higher tensile strength and 109.74% higher elongation. The combination of improved surface roughness and more effective lignocellulosic exposure has been responsible for the increase in the mechanical characteristics of treated composites. The development of hydrophobicity in the SF had been induced by CGDP N₂ modification and enhanced the size of crystals and crystalline structure by removing some unwanted constituents of the SF and etching the smooth lignin-rich surface layer of the SF particularly revealed via FTIR and XRD.

Chemical and physical treatments have been identified as the most efficient ways of treating the fiber surface. However, the huge amounts of liquids and chemicals needed in chemical methods and their exorbitant performance in terms of energy expenditure have limited their applicability in the past decades. The use of appropriate cohesion in addition to stimulating the biopolymer texture without changing its bulk polymer properties leads to the formation and establishment of plasma surface treatments that offer a unified, repeatable, cost-effective and environmentally benign replacement.

The authors are sure that this technology will be adopted by the polymer industry, aerospace, automotive and related sectors in the future.

This paper aims to examine the traditional business communities and family businesses of India, their emergence and sustained growth.

The authors analyze the role of business communities in family businesses of India and identify business communities that have still sustained and marked a global presence.

Business communities such as Marwaris have the knack for business activities and are leaders of family businesses in India today, who have sustained their past success and continue to create new histories. Other traditional business communities such as Parsis, Sindhis, Chettiars and Gujarati banias have not been able to sustain much. Possible reasons were switching to white-collar jobs, taking up diplomacy and other professions, inter caste marriages, international migration in search of business and Indian government policies.

This study provides a useful source of information for academics, policy-makers and economists.

Traditional business communities populate the list of family businesses that have marked their global presence. This paper identifies various factors that are responsible for the growth and sustainability of these business communities.

The study clarifies the role of business communities in domestic economic development.

The paper explored traditional business communities of India and assessed their role in family businesses of India that currently mark a global presence.

This study aims to highlight the importance of brand equity dimensions which act as a mediator between online reviews and consumer’s purchase intention. In particular, the present study tries to determine which the Aaker’s (1991) brand equity dimensions have the mediating roles between source credible online reviews and purchase intention.

Data were collected from select e-commerce site’s brand community on Facebook social media platform through Google form application. The present study first determines the reliability of the variables. To check the unidimensionality of the variables, exploratory factor analysis has been performed. This study makes use of structural equation modeling bootstrapping method to examine the mediating effects of brand equity dimensions between source credible online reviews and purchase intention.

Data analysis reveals that marketers should concentrate more on brand awareness and perceived value, which ultimately influence the purchase intention of the consumers.

This paper is one of the first that examines the mediating effects of consumer-based brand equity dimensions between source credible online reviews and consumer’s purchase intention. Further, the present study integrates source credibility theory and attribution theory to develop the research model.

As Covid-19 became a pandemic, numerous people were forced to stay at home, leading to increased intimate partner violence (IPV) in many countries, particularly in developing and least-developed ones. This paper aims to highlight the IPV based on 15 different cases formed from the practical evidence of five developing countries.

The authors interviewed 15 women from five countries who were the victims of IPV during the early periods of Covid-19 outbreak. Due to geographical remoteness, the authors conducted informal telephone interviews to collect the participants' personal experiences. The conversations were recorded with participants' permission; afterwards, the authors summarized participants’ experiences into 15 different cases without revealing their original identities (instead, disguised names were used).

It was revealed that the women were the primary victims of such violence, particularly from their intimate partners (husbands). In most cases, such IPV, as reported by the interviewees, originated or increased after the pandemic when they were forced to stay at home, losing their partners’ jobs or income sources.

The authors summarized the causes of IPV and put forward a few action recommendations based on the interviewees’ practical experience and existing literature. This paper will open a new window for research investigations on IPV during emergencies such as Covid-19 outbreak.

The paper develops a model for enhancing R&D productivity for Indian public funded laboratories. The paper utilizes the productivity data of five Council of Scientific and Industrial Research (CSIR) laboratories for analysis and to form the constructs of the model.

The weighted average method was employed for analyzing the rankings of survey respondents pertaining to the significant measures enhancing R&D involvement of researchers and significant non-R&D jobs. The authors have proposed a model of productivity. Various individual, organizational and environmental constructs related to the researchers working in the CSIR laboratories have been outlined that can enhance R&D productivity of researchers in Indian R&D laboratories. Partial Least Squares-Structural Equation Modeling (PLS-SEM) was used to find the predictability of the productivity model.

The organizational factors have a crucial role in enhancing the R&D outputs of CSIR laboratories. The R&D productivity of researchers can be improved through implementing the constructs of the proposed model of productivity.

The R&D productivity model can be adapted by the R&D laboratories to enhance researchers’ R&D involvement, increased R&D outputs and achieving self-sustenance in long run.

The R&D laboratories can initiate exercises to explore the most relevant factors and measures to enhance R&D productivity of their researchers. The constructs of the model can function as a guideline to introduce the most preferable research policies in the laboratory for overall mutual growth of laboratory and the researchers.

Hardly any studies have been found that have focused on finding the measures of enhancing R&D involvement of researchers and the influence of significant time-intensive jobs on researchers’ productivity.

The learning outcomes are as follows: understand the mechanism of sourcing and allocation of funds in the Indian banking industry; compare financial indicators of Yes bank with the industry average and interpret the hidden stress; understand the role of NPAs in the banking industry and analyze Yes bank’s performance; and identify the possible red signals in the business model of Yes bank.

The case narrated the story of Yes bank which was considered as one of the most promising and rising banks of India. The stock of Yes bank had been the preferred investment choice for many investors because of its outstanding performance in almost all the important parameters of the industry since 2005. Since its inception, investors favored the stock with an assumption that this new generation bank had a unique as well as a sustainable banking model. However, after the year 2016, Reserve Bank of India (Indian central bank and banking regulator) found huge under-reporting of non-performing assets (NPAs) in the three (i.e. 2015–16, 2016–17 and 2018–19) out of its four annual regulatory inspections, casting doubt in the way Yes bank functioned. Risk and aggression seemed to be the two most important aspects of Yes bank’s culture and this case tried to narrate the same through various financial indicators. The ratio comparison with the industry average indicated the possible gray areas of Yes bank, which was once considered as the most promising bank of India. Unfortunately, even the change of guard at the helm of Yes bank did not change the fate of the bank.

MBA/PGDBA/Executive MBA.

Teaching Notes are available for educators only.

CSS 1: Accounting and Finance.

In this study, an integrated decision-making model consisting of decision-making trial and evaluation laboratory (DEMATEL), best worst method (BWM) and a modified version of evaluation based on distance from average solution (EDAS) methods is proposed for supplier selection problem in a public procurement system considering sustainable development goals.

DEMATEL and BWM methods are used to determine weights of the criteria that are defined for the supplier selection problem. Weight aggregation method is applied to combine the weights obtained from these two methods. A modified version of EDAS method is then used in order to rank the alternative suppliers.

The proposed decision-making model is investigated for a supplier selection problem for a hospital in Spain. The validity of the results is checked using comparison with other decision-making methods and several performance analysis tests.

The proposed multi-criteria decision-making (MCDM) model contributes to the healthcare supply chain management (SCM) and aims to lead the policy makers in selecting the best supplier.

There is no such study that combines DEMATEL and BWM together for weight generation. The application of the modified EDAS method is also new. In real time situations, the decision experts may confront to the difficulty of using BWM while identifying the best and the worst criteria choices. The idea of using DEMATEL is to aid the experts to make them enable in distinguishing between the best/worst criteria and handle BWM easily.

The purpose of this paper is to study the status and trend of intellectual capital disclosures by selected companies in India. Three categories of intellectual capital disclosures across six industry groups were measured. The relation of the three categories of disclosures, i.e. human capital, relational capital and structural capital disclosures with the measures of organisational performance such as sales, R&D, R&D intensity, net profit and export intensity has also been studied.

Based on National Industrial Classification 2008, six sectors, namely pharmaceutical, basic metals, industrial manufacturing, energy, financial services and information technology were included in the study and 20 companies were selected from each sector based on the availability of data from 2004-2005 to 2013-2014, thus, making a sample of 1,200 firm-years. For collecting the data, a list of keywords related to various dimensions of intellectual capital was prepared and the count of keywords was searched in the annual reports of the companies.

Significant and positive trend coefficients were found in the majority of the sectors. Analysis revealed that trend coefficients differed across various sectors indicating the presence of sector specificity. Results of trend analysis reveal that structural capital-related disclosures have stagnated in case of pharmaceutical sector after hitting the peak. Significant variations were found across sectors in terms of all three types of intellectual capital disclosures. Results of study empirically support the fact that intellectual capital disclosures tend to increase with size of the organisation.

As data have been collected from annual reports of the companies, the accuracy of the findings is limited to the accuracy of the reported data.

The study is an original piece of work. This study provides an insight into the disclosure trend of intellectual capital in an emerging economy.

The textile sector is one of the sectors where competition is intense and requires the production of high-value-added products. This study aims to conduct patent analysis to find the technology status, recent trends, applications and technological evaluations of protective textile technologies in practice.

More than 36,840 patent documents related to protective textile technologies are available for researchers, patent examiners and patent researchers. Patent analysis is conducted to report the technology status, recent trends and applications of protective textile technologies. This analysis provides insights into the possible future directions of protective textile technologies in practice. Additionally, association rule mining (ARM) is performed to find the hidden patterns among protective textile technologies.

The development of protective textile technologies is revealed by the technology evaluation in this study. In addition, the sub-technology classes affecting protective textile technologies are examined using the cooperative patent classification (CPC) codes of the patent documents. Technology status and recent trends of protective textile technologies are provided in detail. The results of this study show that (1) protective textile technologies are constantly being developed, (2) the working areas of medical protective textiles are increasing, (3) there are frequent studies on fabric structures for saving lives within the framework of human needs and (4) there are four technology classes, namely A41D, Y10T, B32B and A62B impacting the other technology classes related to textile technologies such as D10B, Y10T, F41H, A62D, D04H, Y10S and D10B.

To have a competitive advantage in the marketplace, evaluation of textile technologies is critical in developing “functionalized” and “technologized” textile products. In particular, evaluating technologies in developing protective textile products is extremely important to meet customer demands and present competitive products in the market. Examining these patents for technology developers, decision-makers and policymakers is an urgent and necessary job. However, studies examining the development of protective textile technologies with patent analysis are very limited in the literature. To fill this gap, technology status, recent trends and applications of protective textile technologies are reported based on patent analysis and ARM in this study.

The purpose of this paper is to explore the most significant determinants of capital structure of manufacturing firms in India and to investigate whether the capital structure models derived from foreign research provide convincing explanations for capital structure decisions of Indian firms by using multiple regression model.

Different conditional theories of capital structure like trade off theory, pecking order theory and agency theory are reviewed to formulate testable propositions concerning determinants of capital structure of manufacturing firms. Multiple regression model and correlation matrix have been used as statistical tools to investigate the most significant determinants of capital structure of manufacturing firms in India with the help of SPSS Software for a sample of top 100 manufacturing firms listed in BSE.

The results suggest that variables like asset composition, business risk and return on assets are positively related to debt ratio whereas firm size and debt service capacity are negatively related to debt ratio. The asset composition, business risk and return on assets appear to be significant determinants of capital structure, while firm size and debt service capacity are insignificant determinants.

The findings of this study are consistent with predictions of trade off, pecking order and agency theory of finance which helps in understanding financing behaviour of firms in India.

This study has laid some ground work to explore the determinants of capital structure of Indian firms upon which a more detailed evaluation could be based. Furthermore, empirical findings should help corporate managers to make optimal capital structure decisions.

To the authors’ knowledge, this study is the first that explores the most significant determinants of capital structure of manufacturing firms in India by using the most recent data. Moreover, this study also confirms that same factors affect the capital structure decisions of firms in developing countries as identified for firms in developed economies.