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This piece is a performative keynote address delivered at the 2016 International Congress of Qualitative Inquiry, University of Illinois Champaign-Urbana. ¹ The keynote showed clips from films on education that triggered critical memories of the author’s own educational experience as teacher/scholar/administrator. The keynote was thus a performative film autocritography. The title “Black Man/White Tower” serves as a trope of tensiveness and transgression at the nexus of thick intersectionalities in higher education.

Purpose: This chapter aims to unveil the challenges of adopting and using banking chatbots in India and identify the challenges of Chat Generative Pre-trained Transformer (ChatGPT) for future banking.

Need for the study: Unveiling the challenges of chatbots and ChatGPT in the banking industry in India is crucial to understand the limitations and areas of improvement to enhance customer experience, ensure data security, and maintain regulatory compliance.

Methodology: The researchers conducted a narrative review systematically summarising and analysing existing literature on chatbots and ChatGPT, providing a comprehensive overview of the challenges faced in the industry.

Findings: The authors identify perceived risk, platform quality, connectivity and infrastructure, data privacy and security, user education and acceptance, existing legacy systems, and regulatory guidelines as the challenges of adopting chatbots. Additionally, the findings reveal that the challenges posed by ChatGPT in future banking include the potential reduction of traditional banking jobs, linguistic diversity, data privacy and security, ethical considerations and bias mitigation, explainability and accountability, integration with existing banking systems, and user trust and acceptance. However, implementing these new technologies also presents opportunities for individuals with unique human skills, such as critical thinking, empathy, and creativity, which are difficult to replace with technology.

Practical implications: By minimising the challenges of ChatGPT and chatbots, the banking industry could achieve improved customer service, cost efficiency, automation of routine tasks, and 24/7 availability, leading to enhanced customer satisfaction and operational efficiency in the banking industry. Additionally, these artificial intelligence (AI) tools enable data-driven insights, personalised experiences, scalability, and efficient handling of large customer volumes, contributing to better decision-making and enhanced customer engagement.

A pandemic causes abrupt and unanticipated disruptions in many facets of society. A lot of authorities have quickly turned to online teaching methods. The best methods for online teaching have become a hot topic of discussion due to this urgent fast transmission. It was difficult to teach physiology to medical and paramedical students online because of concerns about how to give the students an effective interactive online teaching practice and how to guarantee successful outcomes. Therefore, three approaches have been individually applied to medical and nursing students for the first time in the physiology department of the Faculty of Medicine in Rabigh, King Abdulaziz University. Through online lectures and assignments, the strategies attempted to capture the students’ interest and interaction. The second-year nursing students were given a mind map project to complete after the lecture. The third-year medical students used a crossword puzzle game to test the students’ understanding. The third-year medical students were presented with short stories to better comprehend the physiological processes covered in the lectures. Overall, the three instructional strategies received positive feedback from the students. Incorporating such cutting-edge and imaginative educational approaches, in conclusion, could significantly aid in managing the pressures that arise during pandemics.

The concept and practice of e-services has become essential in business transactions. Yet there are still many organizations that have not developed e-services optimally. This is especially relevant in the context of Indonesian Airline companies. Therefore, many airline customers in Indonesia are still in doubt about it, or even do not use it. To fill this gap, this study attempts to develop a model for e-services adoption and empirically examines the factors influencing the airlines customers in Indonesia in using e-services offered by the Indonesian airline companies. Taking six Indonesian airline companies as a case example, the study investigated the antecedents of e-services usage of Indonesian airlines. This study further examined the impacts of motivation on customers in using e-services in the Indonesian context. Another important aim of this study was to investigate how ages, experiences and geographical areas moderate effects of e-services usage.

The study adopts a positivist research paradigm with a two-phase sequential mixed method design involving qualitative and quantitative approaches. An initial research model was first developed based on an extensive literature review, by combining acceptance and use of information technology theories, expectancy theory and the inter-organizational system motivation models. A qualitative field study via semi-structured interviews was then conducted to explore the present state among 15 respondents. The results of the interviews were analysed using content analysis yielding the final model of e-services usage. Eighteen antecedent factors hypotheses and three moderating factors hypotheses and 52-item questionnaire were developed. A focus group discussion of five respondents and a pilot study of 59 respondents resulted in final version of the questionnaire.

In the second phase, the main survey was conducted nationally to collect the research data among Indonesian airline customers who had already used Indonesian airline e-services. A total of 819 valid questionnaires were obtained. The data was then analysed using a partial least square (PLS) based structural equation modelling (SEM) technique to produce the contributions of links in the e-services model (22% of all the variances in e-services usage, 37.8% in intention to use, 46.6% in motivation, 39.2% in outcome expectancy, and 37.7% in effort expectancy). Meanwhile, path coefficients and t-values demonstrated various different influences of antecedent factors towards e-services usage. Additionally, a multi-group analysis based on PLS is employed with mixed results. In the final findings, 14 hypotheses were supported and 7 hypotheses were not supported.

The major findings of this study have confirmed that motivation has the strongest contribution in e-services usage. In addition, motivation affects e-services usage both directly and indirectly through intention-to-use. This study provides contributions to the existing knowledge of e-services models, and practical applications of IT usage. Most importantly, an understanding of antecedents of e-services adoption will provide guidelines for stakeholders in developing better e-services and strategies in order to promote and encourage more customers to use e-services. Finally, the accomplishment of this study can be expanded through possible adaptations in other industries and other geographical contexts.

The contribution of the Indian Automobile industry in the economic growth of the country is significantly high. Besides catering to a large domestic market, the automobile industry in India has also captured market shares in many foreign countries successfully in the last few decades. Not only is it an important export-oriented industry of the nation but also the fourth largest exporter of automobiles in Asia. However, in the recent years (2018–2019), it has faced an unprecedented slump. This chapter captures this fact by calculating the growth of car selling for the four quarters of the period 2018–2019 across the Indian states. It primarily tries to find out whether the variation in income and tax levied on petrol and diesel has an impact on the variation in the car selling across the states for the abovementioned time period. It has been proven from our study that higher income of a state has a positive impact, whereas higher tax on petrol and diesel which varies across the states has a negative impact on car selling. Apart from this, this study then distinctively tries to find out whether there exists any neighborhood impact on growth rate of car selling and different tax rate on petrol and diesel on the basis of Moran's Index. It is witnessed that there exists a high level of spatial autocorrelation among the different states in case of growth of a car selling and tax imposition on diesel as well as on petrol. This fact necessitates some degree of regional orientation in formulating an effective policy to revive the automobile industry on the part of the Government.