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Trade Finance, International Trade, International Business, Emerging Markets, Textile Industry.

This case has been designed for the students studying courses on International Business during their graduation/post-graduation. Students are expected to have basic knowledge of International Trade and are also expected to study the different ways of financing the foreign trade to appreciate the case.

The case describes the various ways of financing of foreign trade. The case has been designed in the context of an Indian Textile Exporter who has grown steadily over the past years. As business has increased, simultaneously the requirement of funds for the exporter has also increased. Through the medium of conversations, the different ways of financing the foreign trade have been explained in detail. Equipped with this knowledge, students are required to discuss the pros and cons of the different ways of financing the foreign trade. The case also discusses the dilemma of foreign currency hedging. This is a common dilemma faced by importers and exporters as they grow over a period of time.

This case has been designed to: understand the various ways of financing the foreign trade and understand their merits and demerits; understand the difference between factoring and forfeiting understand how the Exim Bank of India plays an important role in supporting exporters and importers in India; and understand the various ways of hedging the foreign currency risk.

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Technology has been witnessing a rapid growth. The advent of artificial intelligence has further enhanced the satisfaction level of consumers, which makes it even more vital in the current scenario. This paper aims to explore the factors affecting practical implacability of artificial intelligence and its impact on consumers’ online purchase intention.

This paper has used a technology-based model as the base to explore the different factors affecting consumers’ purchase intention towards e-retailing. This study has formulated a model that demonstrates the integration of artificial intelligence in retailing by the business organizations so as to understand the needs of customers and help them accept technology. This study has further explored faith, subjective norms and consciousness as constructs which enhance the implacability of artificial intelligence.

This study shows that artificial intelligence positively influences consumers’ buying behaviour. This study through a model also shows that integration of artificial intelligence enhances consumers’ purchase intention.

The study has been focusing on a portion of target population. So there is scope to include the whole set of the population to get closer-to-accurate results.

The study offers useful inputs for academicians as well as marketers for predicting buying behaviour of consumers. Marketing managers can use artificial intelligence–embedded technology to enhance online purchase intention.

The study shows that an increase in consciousness towards e-retailing has made consumers keenly analyse and purchase products on the basis of merit and usefulness of the products.

The contribution has been made with the best of knowledge in formulating an integrated artificial intelligence model for consumers’ purchase intention in e-retailing.

The study aims to estimate the impact of the vigilant board independence (BIND) dimension that potentially neutralises the unfair influence of chief executive officer duality (CEODU) on Indian public banks' performance.

The study takes into account the fixed-effects model to investigate the potential moderating effect of BIND in the relationship between CEODU and Indian bank performance. The econometric model is also robust against heteroscedasticity, serial correlation and cross-section dependence issues to ensure that the model is free from such biases. The study also addresses the major issue of endogeneity via vector autoregression and performs the analysis by considering one period lag of the explanatory variables.

The findings demonstrate that CEODU does not always lead to a negative outcome on the performance until or unless the board is monitored by the effective presence of outside directors.

The regulatory bodies consider the results to strengthen board capital where CEODU can benefit a business entity if vigilance BIND is present at or above a threshold point.

The study evaluated an under-researched role of BIND as a moderator that undermines the negative influence of CEODU on the performance of Indian banks. The study also establishes that the CEO's contribution to performance increases when the number of outside directors is at or above a certain threshold.

The paper aims to craft a non-parametric composite value for the board quality of Indian banks where the weights can be assigned endogenously.

The study employed a non-parametric data envelopment analysis (DEA)-based novel extension known as the benefit of doubt approach. To measure the strength of the Indian bank corporate board in terms of board efficiency (BEF), the study used a mixed approach, i.e. first, the study calculates the percentile ranks of the five attributes that the study assumes are the characteristics of the strong board including board size, number of outside directors, frequency of meetings, non-duality leadership and board gender diversity. Thereafter, the study performs the benefit-to-doubt approach to finally measure the efficiency of the board.

The findings of the study establish that the methodological framework present in the study to measure the strength of the board in terms of BEF has been a much superior method over the other weighted and non-weighted linear average methods.

This methodology aids the shareholders, investors and regulatory bodies in rating the Indian banks based on their strength in terms of better monitoring boards and ensuring a smooth agent–owner relationship.

The benefit of doubt approach has been a unique and novel methodology to craft the composite value for any multidimensional phenomenon. One of the major benefits of using this approach is that it assigns the weights endogenously to each dimension and thereafter collectively determines the efficiency of such a phenomenon.

Sustainable development goals (SDGs) are gaining significant importance in the current environment. Many businesses are keen to adopt SDGs to get a competitive edge. There are certain challenges in realigning the present working scenario for sustainable development, which is a primary concern for society. Various firms are adopting sustainable engineering (SE) practices to tackle such issues. Artificial intelligence (AI) is an emerging technology that can help the ineffective adoption of sustainable practices in an uncertain environment. In this regard, there is a need to review the current research practices in the field of SE in AI. The purpose of the present study is to comprehensive review the research trend in the field of SE in AI.

This work presents a review of AI applications in SE for decision-making in an uncertain environment. SCOPUS database was considered for shortlisting the articles. Specific keywords on AI, SE and decision-making were given, and a total of 127 articles were shortlisted after implying inclusion and exclusion criteria.

Bibliometric study and network analyses were performed to analyse the current research trends and to see the research collaboration between researchers and countries. Emerging research themes were identified by using structural topic modelling (STM) and were discussed further.

Research propositions corresponding to each research theme were presented for future research directions. Finally, the implications of the study were discussed.

This work presents a systematic review of articles in the field of AI applications in SE with the help of bibliometric study, network analyses and STM.

Grassroots innovations, developed by local people using locally available resources, have shown the potential to provide low-cost technological solutions to the problems faced by underserved consumers in the global south. This paper aims to link the concept of grassroots innovations to energy use in the context of India.

The paper takes three case studies from the list of technologies scouted and nurtured by the National Innovation Foundation to critically discuss the potential of grassroots innovations for the dissemination and diffusion of urban sustainable energy uses. The data for this study has been collected from various secondary sources. It discusses the opportunities and challenges in promoting grassroots innovations for sustainable energy uses in urban settings.

The paper discusses the opportunities and challenges in promoting grassroots innovations for sustainable energy uses in urban settings.

Although the concept and understanding of grassroots innovations have well developed, its linkages with sustainable energy use in urban settings have received scarce or no attention in the literature.