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This paper comprehensively reviews research on buying centers using a multi-method approach that combines bibliometric analysis and content-based review. The study evaluates over 50 years of buying center literature and identifies critical trends, influential contributors and research gaps. Based on the findings, the paper advocates for a multi-stage, multi-method review process as a benchmark for future literature reviews in marketing.

The paper includes a multi-method approach that combines bibliometric analysis and content-based review employing state-of-the-art tools such as Biblioshiny.

The analysis reveals patterns in the intellectual structure of the research on buying centers as well as patterns of influence. While there has been periodic interest in reviewing and summarizing the literature on buying centers, we find that a multi-method, journal-agnostic review of the literature utilizing multiple databases yields a more comprehensive view of the field.

This paper provides a comprehensive and systematic literature review on the topic of buying centers, utilizing multiple databases and increasing inclusiveness of global research.

Nowadays, an analysis of the circumstances that have led to the development of specific industries within regional entrepreneurial ecosystems (EEs) is extremely relevant. The chapter carries out a twofold analysis, in order to fully explore the reasons that have led to the creation of a specific industrial district. On the one hand, the tissue paper industry in the Italian province of Lucca is analysed through a qualitative approach; on the other hand, the contextual traits of the Toscana EE influencing firm performance are investigated through using a quantitative research approach. This mixed research analysis provides some important hints. First, it helps to understand how systemic, framework and human conditions affect firm performance. Second, it examines how historical, social, and economic factors have shaped regional industries. Through an in-depth analysis, the chapter provides theoretical and empirical insights into the dynamics that affect industrial transformation in response to globalisation, technological innovation, and changing market demands. After completing the chapter, readers will understand how knowledge, collaboration, and shared resources drive regional competitiveness. Through the qualitative analysis, readers will be aware of the tissue paper industry evolution. The combination with the quantitative study allows us to capture the different drivers swaying firm performance, such as infrastructure, innovation capacity, and institutional support. Therefore, the use of empirical data enables for a more objective assessment of the earlier contextual elements, revealing trends and patterns that may not be immediately evident through qualitative analysis.

Integrating social comparison and social identity theories, this study aims to examine students’ emotional and behavioral responses to the use of ChatGPT in academic settings, focusing on intrinsic motivation, dissonance, envy, schadenfreude and artificial intelligence (AI) usage intentions.

The research design consisted of two sequential survey-based studies with undergraduate business students. Study 1, analyzed with SmartPLS, measured students’ intrinsic motivation, cognitive engagement, dispositional envy, emotional dissonance and schadenfreude experienced in response to academic dishonesty related to ChatGPT. Study 2 explored the motivations behind students’ future use of AI tools, examining ethical considerations and emotional responses.

Study 1 determined that higher levels of cognitive engagement reduce dissonance and envy among highly motivated students. Nevertheless, driven by cognitive engagement, dissonance and envy, it was established that highly motivated students experience schadenfreude when others are caught misusing ChatGPT. In contrast, low-motivated students only feel schadenfreude as a product of dissonance and envy. The focus of Study 2 was on the adoption of ChatGPT. Results indicate that future usage is driven by ethical considerations for highly motivated students, whereas less dissonance is key for low-motivated students.

The study’s originality lies in its exploration of schadenfreude in the context of AI use among students, highlighting how cognitive engagement and motivation influence emotional responses. Drawing on social comparison and social identity theories, it sheds new light on the dynamics of academic integrity and the emotional landscape surrounding AI tools like ChatGPT, thus filling a research gap in understanding student behavior and perceptions in higher education.

The preservation of digital records, particularly their authenticity, integrity and accessibility over time, is a critical challenge faced by institutions worldwide. In South Africa, these challenges are further compounded by inadequate infrastructure, legal complexities, ad limited resources, which threaten the long-term sustainability of digital repositories. This study aims to investigate the compliance of selected digital repositories in South Africa with the standards of a Trusted Digital Repository (TDR) and the Open Archival Information System (OAIS) model.

A qualitative research approach was used, assessing five purposefully selected repositories based on their significance in preserving South Africa’s digital cultural heritage. Data collection involved semi-structured interviews with key personnel, content analysis of relevant documents (such as policies and procedures) and direct observations of repository environments to evaluate operational frameworks and technological infrastructure. A review of relevant literature informed the development of assessment criteria, while data from interviews, content analysis and observations were triangulated to ensure reliability.

The findings reveal significant shortcomings in compliance with OAIS and TDR standards, particularly in areas such as policy implementation, staffing, financial sustainability and technological infrastructure. None of the repositories fully met the OAIS responsibilities, and all lacked systems to ensure the independent understandability of digital records by designated communities.

The study highlights the need for improved staff training, stronger preservation policies and increased financial and technological investment to enhance compliance with international standards. Recommendations emphasize capacity building, strategic planning and collaborative efforts to sustainably manage South Africa’s digital heritage.

The study highlights the importance of preserving South Africa’s digital cultural heritage, which holds value for both present and future generations. Ensuring the authenticity, accessibility, and long-term sustainability of digital records is crucial for fostering a sense of national identity, supporting historical research and promoting inclusivity in cultural representation. By improving digital preservation practices, these repositories can serve as reliable resources for education, cultural engagement and community empowerment, ultimately strengthening social cohesion and collective memory in South Africa.

This study provides a comprehensive evaluation of digital repository compliance within South Africa, a context marked by unique infrastructural and resource constraints. The recommendations offer a foundation for addressing gaps in repository management and contribute to the broader discourse on sustainable digital preservation.

This study aims to explain the privacy paradox, wherein individuals, despite privacy concerns, are willing to share personal information while using AI chatbots. Departing from previous research that primarily viewed AI chatbots from a non-anthropomorphic approach, this paper contends that AI chatbots are taking on an emotional component for humans. This study thus explores this topic by considering both rational and non-rational perspectives, thereby providing a more comprehensive understanding of user behavior in digital environments.

Employing a questionnaire survey (N = 480), this research focuses on young users who regularly engage with AI chatbots. Drawing upon the parasocial interaction theory and privacy calculus theory, the study elucidates the mechanisms governing users’ willingness to disclose information.

Findings show that cognitive, emotional and behavioral dimensions all positively influence perceived benefits of using ChatGPT, which in turn enhances privacy disclosure. While cognitive, emotional and behavioral dimensions negatively impact perceived risks, only the emotional and behavioral dimensions significantly affect perceived risk, which in turn negatively influences privacy disclosure. Notably, the cognitive dimension’s lack of significant mediating effect suggests that users’ awareness of privacy risks does not deter disclosure. Instead, emotional factors drive privacy decisions, with users more likely to disclose personal information based on positive experiences and engagement with ChatGPT. This confirms the existence of the privacy paradox.

This study acknowledges several limitations. While the sample was adequately stratified, the focus was primarily on young users in China. Future research should explore broader demographic groups, including elderly users, to understand how different age groups engage with AI chatbots. Additionally, although the study was conducted within the Chinese context, the findings have broader applicability, highlighting the potential for cross-cultural comparisons. Differences in user attitudes toward AI chatbots may arise due to cultural variations, with East Asian cultures typically exhibiting a more positive attitude toward social AI systems compared to Western cultures. This cultural distinction—rooted in Eastern philosophies such as animism in Shintoism and Buddhism—suggests that East Asians are more likely to anthropomorphize technology, unlike their Western counterparts (Yam et al., 2023; Folk et al., 2023).

The findings of this study offer valuable insights for developers, policymakers and educators navigating the rapidly evolving landscape of intelligent technologies. First, regarding technology design, the study suggests that AI chatbot developers should not focus solely on functional aspects but also consider emotional and social dimensions in user interactions. By enhancing emotional connection and ensuring transparent privacy communication, developers can significantly improve user experiences (Meng and Dai, 2021). Second, there is a pressing need for comprehensive user education programs. As users tend to prioritize perceived benefits over risks, it is essential to raise awareness about privacy risks while also emphasizing the positive outcomes of responsible information sharing. This can help foster a more informed and balanced approach to user engagement (Vimalkumar et al., 2021). Third, cultural and ethical considerations must be incorporated into AI chatbot design. In collectivist societies like China, users may prioritize emotional satisfaction and societal harmony over privacy concerns (Trepte, 2017; Johnston, 2009). Developers and policymakers should account for these cultural factors when designing AI systems. Furthermore, AI systems should communicate privacy policies clearly to users, addressing potential vulnerabilities and ensuring that users are aware of the extent to which their data may be exposed (Wu et al., 2024). Lastly, as AI chatbots become deeply integrated into daily life, there is a growing need for societal discussions on privacy norms and trust in AI systems. This research prompts a reflection on the evolving relationship between technology and personal privacy, especially in societies where trust is shaped by cultural and emotional factors. Developing frameworks to ensure responsible AI practices while fostering user trust is crucial for the long-term societal integration of AI technologies (Nah et al., 2023).

The study’s findings not only draw deeper theoretical insights into the role of emotions in generative artificial intelligence (gAI) chatbot engagement, enriching the emotional research orientation and framework concerning chatbots, but they also contribute to the literature on human–computer interaction and technology acceptance within the framework of the privacy calculus theory, providing practical insights for developers, policymakers and educators navigating the evolving landscape of intelligent technologies.

The emergence of social media platforms has revolutionized how brands develop partnerships with social media influencers (SMIs). However, users are seeking more meaningful engagement with SMIs, and little is known about how brands can shift their focus from transient engagements to continued engagement that builds long-term brand–consumer relationships. Extant research has provided inconsistent findings regarding consumer engagement behavior. To address this knowledge deficit, we contribute to the consumer engagement literature by developing and testing a conceptual model that explores and explains the relationships between the factors that influence continued engagement intention (CEI), a form of behavioral intention.

A literature review was conducted to identify gaps and develop a theoretically informed conceptual model and hypotheses. Survey data from 604 Instagram SMI followers were analyzed using partial least squares structural equation modeling using SmartPLS 3.3.3 to assess the structural model relationships and conduct post hoc analysis.

The findings suggest that it is important to positively influence consumer responses to elicit CEI. Furthermore, homophily attitudes toward SMIs moderate the relationship between SMI experience and CEI.

Brands must work with SMIs to create positive SMI experiences and develop CEI. Furthermore, SMIs should focus on brands that fit their lifestyles to enhance homophily attitudes and forge CEI.

This study contributes to the literature by combining social exchange and flow theories to develop and test a holistic framework for examining CEIs regarding SMIs and brands. The findings show that creating positive SMI experiences benefits brands seeking CEI.

This paper describes oral language as a multi-faceted and unconstrained phenomenon, including its social purpose in societies and the implications of this for education. It provides a critique of the concepts of oral language which have come to dominate literacy and language education policy across the Organisation of Economic Collaboration and Development (OECD) in Anglophone countries like Australia. This paper synthesises the interdisciplinary evidence regarding the nature of oral language from the broad field of “language sciences” and explains the implications of this for literacy education. The paper includes recommendations for educational research, school leaders and policymakers.

A synthesis of interdisciplinary evidence from across the “language sciences” is outlined, drawing on Aristotle’s notion of sound with meaning. The evidence highlights the emphasis given to “sound” and “meaning” within various perspectives and shows that meaning is essential to oral language and provides a lens with which to evaluate educational policy and practice.

Findings from a synthesis of evidence across the language sciences and research on school-based practice suggest a number of implications for policy and practice in linguistically diverse settings. Firstly, phonological awareness through musical and drama processes can be applied in the early years of oral language development. Secondly, that oral language is a complementary communicative tool rather than an isolated practice. Finally, that oral language for the classroom may better reflect language’s social purpose to coordinate around meaning.

This paper is an important clarifier at a time when the place of oral language has become constrained within particular educational models in the Anglosphere. This paper highlights that oral language is a basis for learning to read and write throughout the schooling years, but also in life in the ongoing generative work that language allows and demands.

The goal of this study was to assess changes in eating self-efficacy after participating in a brief psychoeducational group intervention, grounded in the cognitive-behavioral model, delivered by dieticians in community-based health facilities.

The study was conducted using a quasi-experimental, pre-post design. A total of 110 program participants took part in the study. They were asked to complete the Eating Self-Efficacy Scale before the start of the intervention, at the end of the intervention, and three months after the intervention ended. Data were analyzed using the Linear Mixed Model.

Participants’ personal sense of control over their eating behaviors significantly increased after they completed the program and continued to increase up to the three-month follow-up. The effect of the intervention remained significant after controlling for differences in age and whether participants had access to other forms of individual support or completed the follow-up during the COVID-19 general lockdown.

By promoting participants’ sense of eating self-efficacy, this intervention could lead to positive dietary changes, which in turn could promote better health and healthy aging.

This community intervention is readily accessible and represents a cost-effective approach to promote healthy eating, reducing the risk of chronic disease and the need for medical care, thereby cutting costs for the healthcare system.

(1) This study addresses a gap in the scientific literature as there was limited published research to date that investigated this intervention. (2) The three-month follow-up made it possible to evaluate whether changes in eating self-efficacy were maintained over time. (3) Potential confounding variables, including age, having access to other forms of individual support and the COVID-19 general lockdown, were taken into account.

The purpose of this study was to investigate the impact of using a jigsaw learning strategy integrated with computer simulation (JLSICS) on the academic achievement and attitudes of students, along with exploring the relationships between them in the process of learning about acids and bases.

The research design used in the study was quasi-experimental, using non-equivalent comparison groups for both pre- and post-tests. A quantitative approach was used to address the research problem, with three groups involved: two experimental and one comparative group. The treatment group, which received the JLSICS intervention, consisted of two intact classes, while the comparison group included one intact class. Data collection involved achievement tests and attitude scale tests on acid and base. Various statistical analyses such as one-way analysis of variance, one-way multivariate analysis of variance, Pearson product-moment correlation, mean and standard deviation were used for data analysis.

The study’s results revealed that the incorporation of the JLSICS had a beneficial influence on the academic achievement and attitudes of grade 10 chemistry students towards acid and base topics. The JLSICS approach proved to be more successful than both conventional methods and the standalone use of the jigsaw learning strategy (JLS) in terms of both achievement and attitudes. The research demonstrated a correlation between positive attitudes towards chemistry among high school students and enhanced achievement in the subject.

The study only focused on one specific aspect of chemistry (acid and base chemistry), which restricts the applicability of the findings to other chemistry topics or subjects. In addition, the study used a quasi-experimental design with a pretest-posttest comparison group, which may introduce variables that could confound the results and restrict causal inferences.

This study addresses the gap in instructional interventions and provides theoretical and practical insights. It emphasizes the importance of incorporating contemporary instructional methods for policymakers, benefiting the government, society and students. By enhancing student achievement, attitudes and critical thinking skills, this approach empowers students to take charge of their learning, fostering deep understanding and analysis. Furthermore, JLSICS aids in grasping abstract chemistry concepts and has the potential to reduce costs associated with purchasing chemicals for schools. This research opens doors for similar studies in different educational settings, offering valuable insights for educators and policymakers.

The originality and value of this study are in its exploration of integrating the jigsaw learning strategy with computer simulations as an instructional approach in chemistry education. This research contributes to the existing literature by showing the effectiveness of JLSICS in improving students’ achievements and attitudes towards acid and base topics. It also emphasizes the importance of fostering positive attitudes towards chemistry to enhance students’ overall achievement in the subject.