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Higher education institutions must keep up to date with the changing needs and situations of students, addressing societal issues affecting young people’s lives and learning. Among the crises that higher education institutions in South Korea are facing, population decline and a lack of sustainable development present a significant threat to these institutions’ existence as well as student satisfaction and learning experience. By relying on a review of relevant literature, this chapter will discuss each of these challenges and potential solutions. We hope that our discussion of the challenges in South Korea will also highlight that many of the ‘crises’ for higher education and ways to tackle them can be both localised and globally applicable. What is significant here is that higher education has a key role to play in preparing the young generation of Koreans to embrace sustainability and to foster resilience in them – for preparedness for future crises. We propose that a focus on community identity strength and education for sustainable development (ESD) can work as a solution for improving students’ learning and global citizenship in these areas. Furthermore, we argue that this is especially important for preserving local and regional strengths and, ultimately, mutual development between the region and universities. Sustainable development depends on building a stronger and positive personal and collective identity, and students’ active participation in sustainable development transcends the localised challenges. Such outcomes are also important for the sustainable future of higher education in South Korea and continuous development in the higher education scholarship.

This study aims to operationalize consumer decision-making styles as higher-order constructs and investigates the influence of two distinct subdimensions of consumer vanity – namely, appearance vanity and achievement vanity – on consumer decision-making orientations (CDMO).

Using data from an online survey of 319 young adults, the authors construct a higher-order structural model capturing the following three orientations: social/conspicuous, utilitarian and undesirable. The partial least squares structural equation modeling approach was used to test the validity of the higher-order structural model and the hypothesized relationships.

Results, confirming the higher-order structure of consumer decision-making styles, highlight the distinctive impacts of the vanity dimensions on different CDMOs. Specifically, appearance vanity predominantly affects social and undesirable orientations, and achievement vanity influences utilitarian orientation.

While several theoretical classifications of consumer decision-making styles have been proposed in the past, none of the earlier studies leveraged those classifications as higher-order models. Addressing this literature gap, this study provides empirical evidence associating CDMOs with a specific consumer trait – vanity – thereby validating the higher-order nature of consumer decision-making styles.

Different age groups display different shopping patterns in terms of how and where consumers buy products. During times of crisis, such behavioural differences become even more striking yet remain under-researched with respect to elderly consumers. This paper investigates the impact of age on retail-related behavioural changes and behavioural stability of elderly shoppers (in comparison to younger consumers) during a crisis.

The authors surveyed 643 Austrian consumers to assess the impact of perceived threat on behavioural change and the moderating effect of age groups. Based on findings from this survey, they subsequently conducted 51 semi-structured interviews to understand the causes of behavioural change and behavioural stability during a crisis.

Elderly shoppers display more stable shopping behaviour during a crisis compared to younger consumers, which is influenced by perceived threat related to the crisis. Such findings indicate that elderly shoppers reinforce their learnt and embedded shopping patterns. The causes of change and stability in behaviour include environmental and inter-personal factors.

Through the lens of social cognitive theory, protection motivation theory and dual process theory, this research contributes to an improved understanding of changes in shopping behaviour of elderly consumers, its antecedents and consequences during a time of crisis. The authors reveal reasons that lead to behavioural stability, hence the absence of change, in terms of shopping during a crisis. They further outline implications for retailers that might wish to better respond to shopping behaviours of the elderly.

The purpose of this study is to comprehensively explore the impact of digitalization on healthcare supply chains (HcSCs). It seeks to understand how digital technologies enhance efficiency, transparency and responsiveness within these complex logistical systems. The study aims to provide a holistic view of the transformative potential of digitalization in the healthcare sector, with a particular focus on improving patient care and streamlining operational processes.

This research employs a systematic review methodology, carefully curating a selection of 45 relevant articles from 66 articles rigorously screened using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to provide a holistic view. It follows established systematic review protocols, incorporating a meticulous search strategy and precise keyword selection. The chosen research design enables a comprehensive examination of the existing body of knowledge concerning digital platforms, real-time tracking technologies, transparency and responsiveness in the context of HcSCs.

The findings of this study emphasize the pivotal role of digital technologies in reshaping HcSCs. Digital platforms, real-time tracking systems and technological integrations substantially enhance efficiency, transparency and responsiveness. Data-driven decision-making, improved communication and agile responses to dynamic demands are key aspects. These findings underscore the transformative impact of digitalization on healthcare logistics, emphasizing the potential for streamlined operations, enhanced patient care and more efficient resource allocation.

Despite the systematic methodology, this study is subject to certain limitations. It relies on existing literature, which may not cover the most recent developments in the rapidly evolving field of digital HcSCs. Furthermore, the study may be influenced by publication bias. The implications suggest the need for continued research to explore emerging digital technologies and their effects on healthcare logistics, ensuring that supply chains remain agile and responsive.

The practical implications of this research are significant for HcSC managers with insights into digital technologies to enhance transparency and collaboration and improve resource visibility. The integration of data analytics can lead to more effective inventory management and demand forecasting. Blockchain (BC) technology can ensure transparent and secure transactions, fostering trust among stakeholders. For practitioners, this research offers actionable guidance for navigating the digital age, promoting operational efficiency and ensuring a consistent supply of essential medical products. Researchers can use these insights as a foundation for further exploration into the potential of digitalization in HcSCs.

The social implications of digitalization in HcSCs are far-reaching. They encompass improved patient care, as digital technologies enhance the efficiency, transparency and responsiveness of supply chains. This translates to better access to critical medical supplies, potentially reducing healthcare disparities and benefiting underserved populations. Enhanced patient safety is a significant social outcome, as transparent and secure transactions enabled by technologies like BC mitigate the risks associated with counterfeit medications. Furthermore, digitalization builds trust among stakeholders, promotes accountability and fosters resilient healthcare systems, which are capable of responding effectively to crises. It also has the potential to make healthcare more affordable, contributing to increased healthcare access and transparency in decision-making.

The originality and value of this study lie in its comprehensive synthesis of diverse findings related to digitalization in HcSCs. While prior studies have examined isolated facets of digital technology adoption, this research provides a comprehensive overview. It contributes to a deeper understanding of the transformative potential of digitalization within the healthcare sector, offering practical approaches to enhance patient care and streamline operations.

Artificial intelligence (AI) carries the risk of widening gender inequalities due to the digital divide, while simultaneously promising to equalise the situation for women through the gender digital dividend. The conflicting findings from previous studies justify the need to investigate the gendered aspects of Artificial Intelligence (AI) diffusion. Specifically, the aim of this chapter is to understand the relationship between female entrepreneurship and the adoption of AI technologies within business contexts at the macroeconomic level. To achieve this, cluster analyses are conducted for the European Union (EU) countries. The results indicate an inverted U-shaped pattern in the relationship between the level of female entrepreneurship and the diffusion of AI technology in business. In the EU countries belonging to clusters with the highest level of AI diffusion, female entrepreneurship is at a moderate level, while in the EU countries with the lowest level of intelligent transformation, both extremes are observed: the highest and the lowest levels of female entrepreneurship. The variety of patterns in female entrepreneurship and AI technology spread in the EU countries implies the complex and multidimensional nature of the interrelationship, and, thus, it indicates the need for diverse, country-specific policies and practices to reach the intelligent transformation with respect to more equal society.

Current developments in the FinTech payment industry have shown a rapid revolution in Industry 4.0, and understanding the factors affecting individual acceptance of facial recognition payment (FRP) is crucial. Hence, this study aims to evaluate the benefits and risks of FRP system adoption in Malaysia.

The perceived risks and benefits framework is adopted as the foundation in this study to examine the various risks and benefits that users perceive, along with the trust factor, to study the relationships between these variables. Data were collected via an online questionnaire, and the hypotheses were tested using Partial Least Squares analysis on 277 responses.

The results revealed that perceived risk is a significant predictor of users' intention to use the FRP system. Privacy risk and financial risk significantly influence perceived risks, while security risk does not. Although convenience, perceived ease of use and perceived trust positively influence perceived benefits, perceived benefits do not significantly influence adoption intention. Moreover, perceived trust negatively affects perceived risks while positively affecting both perceived benefits and adoption intention. Additionally, personal innovativeness moderates the relationship between perceived risks and the intention to use the FRP system.

This study helps policymakers and service providers understand individuals’ concerns and expectations regarding FRP systems. It aids practitioners in developing strategies to build trust, address innovativeness differences and mitigate risks, serving as a roadmap for integrating these systems into Malaysia's financial landscape.

This study distinguishes itself from prior research by evaluating FRP system adoption in Malaysia through the lens of perceived risks and benefits framework. It also explores personal innovativeness as a moderator, examining its impact on the relationship between usage intention and perceived risks and benefits. Additionally, it highlights perceived trust as a crucial factor influencing individuals' intention to adopt FRPs.

This study aims to examine whether companies adopt digital platforms for corporate whistleblowing systems (CWSs), as more substantive corporate social responsibility (CSR) initiatives, by following the existing practices of their industry peers (competitive pressure) and/or geographical location peers (legitimacy pressure).

This study identifies 446 focal companies in the European Economic Area that introduced new CWSs during 2017–2021. Then, the peers are defined as companies with existing CWS practices that are similar in size to each focal company. Using a quantitative approach, this study uses a logistic regression model.

This study finds that companies are more likely to adopt digital CWS if their country peers (not, industry peers) have done so, especially the ones operated in countries where governments build CSR partnerships with companies through cooperative consensus. However, the role of country peers is less prominent when companies have CSR committees.

This study shows the importance of country norms over competitive pressure in CSR. Nevertheless, the results offer additional insights for policy-makers by showing that country regulations mandating CWSs are not significant in promoting the adoption of digital CWS nor reducing the role of country peers.

Providing CWSs with digital platforms may show corporate commitment to better preventing social misconduct and improving social responsibility.

While most literature focuses on the role of industry peers and/or community peers in a single-country setting, this study examines the role of country peers specifically on digitalization regarding CSR and governance.

This study aims to expand understanding of the diversity of virtual influencer forms by investigating their nonhuman-like, animal and graphic or cartoon variations.

A three-year multisite longitudinal netnography studied 174 virtual influencers and spanned ten social media platforms. Typological categories were constructed from the data set, focusing on 14 influencers located across quadrants. In-depth findings were then developed for eight illustrative cases.

Findings deepen the knowledge of the virtual influencer sphere by highlighting diversity in human-like, nonhuman-like, imaginative and realistic forms. The authors postulate four types of virtual influencers: hyper-human, antihuman, pan-human and alter-human. These forms are linked to specific personalities and communication styles, addressing various consumer needs. Imaginatively represented virtual influencers may prompt audiences to reevaluate beliefs, values and behaviors. These findings challenge prior work’s focus on attractive, hyperreal and human-like virtual influencers, encouraging consideration of divergent types engaged in novel meaning-shaping activities and targeting different segments.

This research paves the way for consumer and marketing researchers and practitioners to broaden their representations of virtual influencers beyond the human-like, beyond the commercial and into new worlds of fantasy, imagination and posthuman possibility.

Different types of virtual influencers speak to diverse audiences and convey marketing messages in subtly different ways. Some forms of virtual influencers fit into roles like defiant voices, oppositional characters, activists, educators, entertainers and change leaders. As the universe of virtual influencers diversifies, this research opens new avenues of marketing for brands.

This study pioneers comprehensive qualitative research across the universe of virtual influencers and their communities, exploring links to popular culture. It offers connections between virtual influencer forms and communication strategies for marketers.

Product returns are a major challenge for e-businesses as they involve huge logistical and operational costs. Therefore, it becomes crucial to predict returns in advance. This study aims to evaluate different genres of classifiers for product return chance prediction, and further optimizes the best performing model.

An e-commerce data set having categorical type attributes has been used for this study. Feature selection based on chi-square provides a selective features-set which is used as inputs for model building. Predictive models are attempted using individual classifiers, ensemble models and deep neural networks. For performance evaluation, 75:25 train/test split and 10-fold cross-validation strategies are used. To improve the predictability of the best performing classifier, hyperparameter tuning is performed using different optimization methods such as, random search, grid search, Bayesian approach and evolutionary models (genetic algorithm, differential evolution and particle swarm optimization).

A comparison of F1-scores revealed that the Bayesian approach outperformed all other optimization approaches in terms of accuracy. The predictability of the Bayesian-optimized model is further compared with that of other classifiers using experimental analysis. The Bayesian-optimized XGBoost model possessed superior performance, with accuracies of 77.80% and 70.35% for holdout and 10-fold cross-validation methods, respectively.

Given the anonymized data, the effects of individual attributes on outcomes could not be investigated in detail. The Bayesian-optimized predictive model may be used in decision support systems, enabling real-time prediction of returns and the implementation of preventive measures.

There are very few reported studies on predicting the chance of order return in e-businesses. To the best of the authors’ knowledge, this study is the first to compare different optimization methods and classifiers, demonstrating the superiority of the Bayesian-optimized XGBoost classification model for returns prediction.