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The effects of the spread of COVID-19 across the world are devastating, both from a health and an economic perspective. However, we also see encouraging examples of collaborative and innovative initiatives, in society and in organizations. The purpose of this paper is to focus on initiatives related to digital business model innovation. The authors explore how organizational characteristics provide a variety of opportunities for digital responses to the COVID-19 pandemic and discuss the potential consequences for the speed of digital transformation in organizations and society.

In this paper, the authors analyze how organizations attempt to mitigate the negative effects of fighting COVID-19 using digital business model responses. The authors draw on a qualitative study where they have collected data from the retail and service industries. They have analyzed the data in relation to theory to better understand this ongoing phenomenon.

The authors have identified four categories of organizations (crisispreneurs, accelerators, endurers and thrivers). Each category faces different challenges and shows a different intensity in their digital transformation. The authors propose that the rapid turn toward digital business models will have enduring effects, as organizations have gained transformational capabilities that will remain, and that the digital trajectory has, as a result, changed forever.

The findings in this paper point toward new challenges for leaders and policymakers in terms of how to support initiatives and meet the needs of different categories of organizations while simultaneously being conscious of the potential societal effects of this rapid digital shift. The authors hope that this paper can be of value for managing this shock and learning how to adapt for the future taking certain aspects of current business models as the departure point.

Although the challenges associated with big data are increasing, the question of the most suitable big data analytics (BDA) platform in libraries is always significant. The purpose of this study is to propose a solution to this problem.

The current study identifies relevant literature and provides a review of big data adoption in libraries. It also presents a step-by-step guide for the development of a BDA platform using the Apache Hadoop Ecosystem. To test the system, an analysis of library big data using Apache Pig, which is a tool from the Apache Hadoop Ecosystem, was performed. It establishes the effectiveness of Apache Hadoop Ecosystem as a powerful BDA solution in libraries.

It can be inferred from the literature that libraries and librarians have not taken the possibility of big data services in libraries very seriously. Also, the literature suggests that there is no significant effort made to establish any BDA architecture in libraries. This study establishes the Apache Hadoop Ecosystem as a possible solution for delivering BDA services in libraries.

The present work suggests adapting the idea of providing various big data services in a library by developing a BDA platform, for instance, providing assistance to the researchers in understanding the big data, cleaning and curation of big data by skilled and experienced data managers and providing the infrastructural support to store, process, manage, analyze and visualize the big data.

The study concludes that Apache Hadoops’ Hadoop Distributed File System and MapReduce components significantly reduce the complexities of big data storage and processing, respectively, and Apache Pig, using Pig Latin scripting language, is very efficient in processing big data and responding to queries with a quick response time.

According to the study, there are significantly fewer efforts made to analyze big data from libraries. Furthermore, it has been discovered that acceptance of the Apache Hadoop Ecosystem as a solution to big data problems in libraries are not widely discussed in the literature, although Apache Hadoop is regarded as one of the best frameworks for big data handling.

This paper aims to explore the past and future impacts of automation on family businesses, with a focus on the opportunities for human capital empowerment.

This paper draws upon a contemporary literature search to examine a range of scholarly and practitioner perspectives of the challenges and benefits of automation, exploring the evolvement towards hyperautomation and the empowerment of human capital in family businesses.

Automation, transforming to hyperautomation, general purpose artificial intelligence (AI) and beyond has the possibility of radically improving productivity. Fear of job obsolescence has been present since the birth of modern automation, and whilst some jobs are at risk of redundancy, a net gain towards higher-skilled labour is already evident. Family business leaders must be prepared to react appropriately to the accelerating war for talent by implementing a strategy for human capital empowerment.

This unique paper synthesises developments in automation and proposes a future perspective centred upon the empowerment of human capital in family businesses.

This bibliometric study aims to analyze the latest trends and patterns of big data applications in librarianship from 2000 to 2022. By conducting a comprehensive examination of the existing literature, this study aims to provide valuable insights into the emerging field of big data in librarianship and its potential impact on the future of libraries.

This study employed a rigorous four-stage process of identification, screening, eligibility and inclusion to filter and select the most relevant documents for analysis. The Scopus database was utilized to retrieve pertinent data related to big data applications in librarianship. The dataset comprised 430 documents, including journal articles, conference papers, book chapters, reviews and books. Through bibliometric analysis, the study examined the effectiveness of different publication types and identified the main topics and themes within the field.

The study found that the field of big data in librarianship is growing rapidly, with a significant increase in publications and citations over the past few years. China is the leading country in terms of publication output, followed by the United States of America. The most influential journals in the field are Library Hi Tech and the ACM International Conference Proceeding Series. The top authors in the field are Minami T, Wu J, Fox EA and Giles CL. The most common keywords in the literature are big data, librarianship, data mining, information retrieval, machine learning and webometrics.

This bibliometric study contributes to the existing body of literature by comprehensively analyzing the latest trends and patterns in big data applications within librarianship. It offers a systematic approach to understanding the state of the field and highlights the unique contributions made by various types of publications. The study’s findings and insights contribute to the originality of this research, providing a foundation for further exploration and advancement in the field of big data in librarianship.

This article aims to systematically review the literature published in recognized journals focused on cognitive heuristic-driven biases and their effect on investment management activities and market efficiency. It also includes some of the research work on the origins and foundations of behavioral finance, and how this has grown substantially to become an established and particular subject of study in its own right. The study also aims to provide future direction to the researchers working in this field.

For doing research synthesis, a systematic literature review (SLR) approach was applied considering research studies published within the time period, i.e. 1970–2021. This study attempted to accomplish a critical review of 176 studies out of 256 studies identified, which were published in reputable journals to synthesize the existing literature in the behavioral finance domain-related explicitly to cognitive heuristic-driven biases and their effect on investment management activities and market efficiency as well as on the origins and foundations of behavioral finance.

This review reveals that investors often use cognitive heuristics to reduce the risk of losses in uncertain situations, but that leads to errors in judgment; as a result, investors make irrational decisions, which may cause the market to overreact or underreact – in both situations, the market becomes inefficient. Overall, the literature demonstrates that there is currently no consensus on the usefulness of cognitive heuristics in the context of investment management activities and market efficiency. Therefore, a lack of consensus about this topic suggests that further studies may bring relevant contributions to the literature. Based on the gaps analysis, three major categories of gaps, namely theoretical and methodological gaps, and contextual gaps, are found, where research is needed.

The skillful understanding and knowledge of the cognitive heuristic-driven biases will help the investors, financial institutions and policymakers to overcome the adverse effect of these behavioral biases in the stock market. This article provides a detailed explanation of cognitive heuristic-driven biases and their influence on investment management activities and market efficiency, which could be very useful for finance practitioners, such as an investor who plays at the stock exchange, a portfolio manager, a financial strategist/advisor in an investment firm, a financial planner, an investment banker, a trader/broker at the stock exchange or a financial analyst. But most importantly, the term also includes all those persons who manage corporate entities and are responsible for making their financial management strategies.

Currently, no recent study exists, which reviews and evaluates the empirical research on cognitive heuristic-driven biases displayed by investors. The current study is original in discussing the role of cognitive heuristic-driven biases in investment management activities and market efficiency as well as the history and foundations of behavioral finance by means of research synthesis. This paper is useful to researchers, academicians, policymakers and those working in the area of behavioral finance in understanding the role that cognitive heuristic plays in investment management activities and market efficiency.

By working through the case and assignment questions, students will be able to conduct a marketing environmental analysis to aid strategic decisions; analyse the first-mover advantages of a retail firm and how these can be sustained; comprehend online retail business models and the challenges therein; understand the trade-offs of online/offline retail experiences specific to an emerging market’s beauty and personal care sector; conceptualize and formulate actionable growth strategies that balance the individual and collective requirements of brick and mortar and retail e-commerce environments.

The case is set in 2022, right after Nykaa – the pioneer of beauty and wellness e-commerce platforms in India makes a blockbuster stock market debut in 2021. Starting in 2012 with a disruptive online model for selling beauty and wellness products online in India, Nykaa had come a long way with expansions in physical retail and other segments such as fashion. The firm, which initially aimed to be a virtual store, is now thinking of aggressively expanding in the brick-and-mortar retail space as it opens its 85th retail outlet.

Falguni S. Nayar, founder and CEO of Nykaa, wanted to roll out 300 physical stores targeting 100 cities in India in the next couple of years. She aspired to establish Nykaa as a category leader as the “Indian Sephora” in the beauty and personal care market. Nykaa’s first-mover advantage in the online beauty and personal care marketplace worked well to establish it as a brand with positive endorsements by digital shoppers that enhanced the investment potential with potential financiers. However, the pandemic had brought every physical retailer to the online platform. Most e-commerce platforms dealing in grocery to lifestyle had added personal care products to their existing merchandise.

Additionally, several start-ups had ventured into the online marketplace. Online was a cluttered marketplace with little to no differentiation. In this bloodbath, would the first-mover advantage for Nykaa in the online space still count as a competitive advantage? Nayar was all set to expand Nykaa’s physical presence aggressively. The concern was that the beauty and personal care segment had also moved online as a function of long stay-at-home periods. In the post-pandemic times, would the customer indeed revert to brick and mortar once again? Nykaa was also into product formulations, but so was every big and small player in the space. What was the differentiated winning formula for the consumer’s heart and mind?

The case can be effectively used in foundation courses in marketing and a wide range of specialized courses on marketing management (core/foundation course), retail marketing and e-commerce/digital marketing and e-commerce for B-school learners. The complex decision points faced by an innovative e-commerce start-up firm on its road to market expansion make the case suitable for niche courses such as Marketing for Start-ups. Moreover, learners in executive MBA programs with considerable experience can benefit from the case analysis that balances a growing retail company’s long- and short-run objectives.

Teaching notes are available for educators only.

CSS 8: Marketing.

Homelessness and psychoactive substance (PS) use are both determinants of physical and mental ill health, with the homeless population using, and dying of PSs more frequently than the general population. However, there is a gap in research on the real-world implications psychoactive substance use (PSU) has on the homeless population. This study aims to explore the experiences of PSU from the perspective of homeless users.

Purposive sampling was adopted to recruit participants and semi-structured interviews collected data from participants, with interpretive phenomenological analysis (IPA) generating common themes from the data gathered.

Four participants were interviewed. The themes generated were family and close relationships; cyclical patterns; mistrust in people and services; and low self-worth.

This study is limited by potential bias from researchers who built relationships with participants through the data collection process. Despite efforts to remove this bias, through reflexivity throughout data collection and analysis, some bias may be still present. The researchers saw the participants as vulnerable people who were striving to overcome adversity. Such conception of the participants is reflective of how the participants portrayed themselves. The small sample is suitable for IPA purposes. Of course, it could have been possible that if different participants had been recruited or more participants had been recruited, then there could have been different themes and findings. IPA prides itself on its idiographic focus.

More research is needed on a wider scale to assess the extent and cause of these issues. Increased education and dissemination of research such as this is required to break down stigma within the public and guide policy change in professional services.

This paper interpretatively presents themes generated by semi-structured interviews with four homeless PSUs. As such, these individuals are vulnerable and have faced adversity throughout life from both society and the services they use. Their vulnerability leads to a cycle of substance use and a feeling of low self-worth, which is perpetuated by the perceived views of those around them.

The aim of the study presented in this paper is to investigate the interrelationships among technologies in retail, webrooming and showrooming purchase intentions and customer experience.

The study was conducted in the fashion industry in three fashion groups: LPP, CCC and Inditex, which declare to use omnichannel solutions in their supply chains. The study focusses on 825 customers drawn from the emerging market in Poland. The research follows the partial least squares path model procedure.

Based on the study, it was concluded that out-store technologies are positively associated with omnichannel purchase intentions and also positively associated with cognitive and affective customer experience. This study proves that the boundary between traditional and online stores is beginning to blur, and thanks to new technologies, customers can experience traditional shopping resembling online shopping, and vice-versa.

Although the results provide several major contributions to theory and implications for practitioners, the study still demonstrates some methodological constraints. More specifically, although the study employs a relatively large research sample of 825 shoppers, it still focusses only on a selected group of customers in three fashion groups, LPP, CCC and Inditex, and is limited to investigating a particular type of customer experience solely in the fashion industry.

The results of this study not only verify the theoretical concepts and assumptions of technologies supporting omnichannel retail but also offer a practical roadmap for creating omnichannel solutions providing the best customer experience.

This paper aims to study the relationship between working while studying in college/university and education mismatch among employed youth in the Zambian labour market.

The study uses data from the 2014 School-to-Work Transition Survey and a multinomial logit model to examine three education-mismatch categories: undereducated, matched and overeducated. The paper also examines heterogeneities by education level and gender and uses empirical and subjective approaches of education mismatch.

The evidence shows that employed youth who worked while studying have a higher likelihood of having well-matched jobs. The subgroup analysis by education level reveals no significant relationship between working while studying among employed youth with higher education (secondary and above). However, employed youth with lower education (primary and lower) are less likely to be mismatched for the job. The linkage between the education system and the labour market needs to be strengthened to support a smoother school-to-work transition for youth. Additional support to enable exposure to the right type of work during youth's college or university studies could increase job match and reduce labour market inefficiencies.

The paper provides insights into a significant challenge faced by youth in developing countries, i.e. finding a suitable job for youth's level of education.