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The purpose of this study is to investigate Koreans' preferences for FCDM versus SDM and explored the influence of Asian cultural values on decision-making in the context of managing chronic illnesses, such as type 2 diabetes mellitus (T2DM). Shared decision-making (SDM) emphasizes collaboration between providers and service recipients to decide on the best treatment options. However, it may not fully account for the role of families in managing chronic illness, particularly for people from Eastern cultural backgrounds who value active participation from their families in decisions. In response, family-centered decision-making (FCDM) has been proposed as an alternative approach. Using a vignette experiment design, data (n = 316) were collected from Koreans in the US and in Korea who were randomly presented with either SDM or FCDM processes for reaching T2DM treatment decisions. In addition to demographic information, participants reported on three dimensions of their decision-making experience: satisfaction, perceived effectiveness, and perspective-taking. They also rated their Asian cultural values and familiarity with T2DM. Results show better satisfaction, perceived effectiveness, and perspective taking for FCDM compared to SDM when examined in context of treatment types and perceived illness severity. Moderation effects were found for familiarity of illness, with familiarity effects varying by perceived severity. Study findings provided some evidence in favor of FCDM in Asian communities addressing the disabilities and chronic illness of a family member. Although the current study investigated treatment decisions for T2DM during doctor's visits, FCDM has shown potential to be applied in other service settings.

This paper aims to add to the theorization of family dynamics and women’s entrepreneurship by examining women’s influence on decision-making in family businesses. Business decisions in family firms, in particular, are not free from family influence in terms of goals and strategies, and the role of women in decision-making processes is of particular interest. Consequently, the role of women entrepreneurs in family firms and their influence on business development requires a more fine-grained analysis of the family dynamic within the family and the business.

This study draws on a qualitative study and focuses on the life story narratives of nine women in rural family businesses in rural communities of Småland province in Sweden to empirically examine the decision-making processes. This region is known both for its entrepreneurial culture and traditional gender order. Based on the narrative accounts of women entrepreneurs in family businesses, the data analysis method is thematic, using a Gioia-inspired method.

The complexity of decision-making in rural family firms is further complicated in part due to a closeness with the rural community. Thus, a typology of three decision-making modes in family firms emerges an informal family-oriented mode, a semistructured family/employee consensus mode and a formal board mode with at least one nonfamily member. Moreover, the advantages, disadvantages and strategies that women use to influence decisions within the respective mode are outlined.

This work contributes to the study of women’s agency and its implications in family business and entrepreneurship in the rural context. The study implies that women’s agency shapes the (rural) entrepreneurship context and, likewise, the (rural) entrepreneurship context influences women’s agency. Hence, the author challenges the view of women as only caregivers and sheds light on the practices and processes behind the scenes of entrepreneurial family businesses.

This chapter discusses various aspects of family planning initiatives on a global scale, with a specific focus on their influence in Asian contexts, including Bangladesh. This chapter examines the diverse range of family planning programs and policies implemented worldwide, in Asia and Bangladesh considering cultural factors that significantly shape family planning decisions. By highlighting the unique approaches and challenges faced in different regions, it provides valuable insights into the evolving landscape of family planning efforts and their impact on population dynamics.

This paper examines the integration of artificial intelligence (AI) within family businesses, focusing on how AI can enhance their competitiveness, resilience and sustainability. The study seeks to provide insights into AI’s application in family business contexts, addressing the unique strengths and challenges these businesses face.

A systematic literature review was conducted to synthesize existing research on the adoption and integration of AI in family businesses. The review involved a comprehensive analysis of relevant academic literature to identify key trends, opportunities, challenges and factors influencing AI adoption in family-owned enterprises.

The review highlights the significant potential of AI for family businesses, particularly in improving operations, decision-making and customer engagement. It identifies opportunities such as analysing customer data, enhancing brand building, streamlining operations and improving customer experiences through technologies like Generative AI, Machine Learning, AI Chatbots and NLP. However, challenges like resource constraints, inadequate infrastructure, low customization and AI knowledge gaps inhibit AI adoption in family firms. The study proposes an AI adoption roadmap tailored for family businesses and outlines future research directions based on emerging themes in AI use within these enterprises.

This paper addresses the underexplored area of AI integration in family businesses, contributing to the academic understanding of the intersection between AI and family-owned enterprises. The study offers a comprehensive synthesis of existing research, providing valuable insights and practical recommendations for enhancing the competitiveness and sustainability of family businesses through AI adoption.

This study explores the integration of Artificial Intelligence (AI) within family businesses. It seeks to understand how family-owned enterprises navigate the adoption of AI technologies amidst balancing traditional business values and the imperatives of digital transformation. The research addresses the gap in the existing literature by providing insights into the strategic, operational and cultural dynamics influencing AI adoption in family businesses, highlighting the unique challenges and opportunities they face in leveraging AI for competitive advantage while preserving their legacy.

Employing a qualitative research design, this study utilizes semi-structured interviews with key stakeholders in Turkish family businesses actively engaging in AI projects. Purposive sampling was adopted to ensure a diverse representation of industries and AI adoption stages. The interviews aimed to capture in-depth insights into the motivations, strategies and outcomes of AI integration within these enterprises. Thematic analysis was conducted on the interview transcripts to identify recurring themes and patterns, providing a nuanced understanding of the factors driving AI adoption decisions in the context of family business values and traditions.

The findings reveal that family businesses in Turkey perceive AI as a strategic tool to enhance operational efficiency and customer engagement. However, integrating AI technologies is often met with challenges, including resource constraints, digital literacy gaps and concerns over maintaining family legacy. Notably, businesses that successfully navigate AI adoption tend to employ tailored strategies that align with their core values, involving key family members in the decision-making process and fostering a culture of innovation. The study also highlights the importance of ethical considerations and governance in ensuring AI initiatives resonate with the family business ethos.

The study’s reliance on qualitative interviews within a single country context limits the generalizability of the findings. Future research could expand the geographical scope and incorporate quantitative methods to validate the identified themes across broader populations. Additionally, exploring the impact of generational differences within family businesses on AI adoption could offer more profound insights. The study underscores the need for a more nuanced understanding of the interplay between technology and tradition in family businesses, suggesting avenues for further investigation into how these enterprises can leverage AI to foster innovation while preserving their legacy.

This research offers practical guidance for family businesses contemplating AI integration. It emphasizes the importance of aligning AI strategies with family values and involving stakeholders across generations in the adoption process. The findings suggest that family businesses can benefit from investing in digital literacy and fostering a culture open to technological innovation. Additionally, the study highlights the need for robust governance structures to navigate ethical considerations in AI adoption. By adopting a strategic approach to AI integration, family businesses can enhance their competitiveness without compromising their core values, ensuring long-term sustainability and success in the digital era.

Integrating AI in family businesses has significant social implications, particularly regarding employment and preserving the family legacy. The study suggests that thoughtful AI adoption can contribute to job creation and skill development, counteracting concerns over job displacement. Moreover, by leveraging AI to align with their core values, family businesses can reinforce their role as stewards of social and economic stability within their communities. This research underscores the potential of AI to support the intergenerational transfer of knowledge and values, fostering innovation while preserving the unique cultural heritage of family enterprises.

This study contributes to the emerging literature on AI adoption in family businesses by exploring the Turkish context. It fills a gap in the literature by examining the unique challenges and opportunities family businesses face in integrating AI, highlighting the interplay between technological innovation and traditional values. The research offers valuable insights into tailored strategies for successful AI adoption that respect the legacy and ethos of family enterprises. By focusing on the socio-cultural dimensions of technology integration, this study enriches our understanding of how family businesses can navigate digital transformation while preserving their identity.

This paper investigates the impact of board gender diversity on the readability of the annual reports of family-controlled public companies.

Grounded in the premises of the restricted and extended views of the socioemotional wealth (SEW) approach and executive power theory, this paper explores the ways in which family-affiliated female directors influence report readability in a sample of 133 publicly traded US companies listed in the Fortune 1,000. We use the system GMM estimator, which deals with two key sources of endogeneity by controlling first for reverse causality, using the lags of the endogenous variables as instruments, and then for omitted variables, capturing the individual effect.

Our analysis confirms that the significant enhancement in annual report readability is associated with the presence of female family directors, particularly those who are insiders within the company. In contrast, non-family female directors and family outsider directors appear to have a negative impact on annual report readability.

While scholars have increasingly focused on variations in annual report readability among family firms, the contribution of female directors to this phenomenon has received minimal attention. In our study, we integrate the theories of restricted and extended SEW perspectives with the theory of women’s executive power within the board. This integration is essential for considering two critical factors: firstly, the primacy of their SEW objectives, and, secondly, their legitimacy within the board.

This study investigates whether a firm’s character as a mature micro and small family or non-family business may impact the managing owner’s choice of a potential exit strategy.

The empirical evidence was provided through a sample of 302 entrepreneurs (170 respond-ents from mature micro and small family businesses and 132 from non-family businesses) who participated in a survey on potential exit strategies.

The primary finding indicates that there is no significant difference in exit strategy preferences between family and non-family entrepreneurs from mature micro and small-sized firms. It was found that both groups of entrepreneurs mostly opt for internal succession.

This paper presents a novel perspective, demonstrating that while non-family firms are not typically anticipated to adopt the same exit strategies as family firms, they may still opt for internal succession. Furthermore, we provide an insight into potential exit strategy decisions made in smaller firms, which have been less frequently analyzed compared to larger firms in the field of entrepreneurial exit.

The purpose of this study is to understand the link between psychological ownership and organizational innovation in family businesses. The research also explored the mediating effect of knowledge transfer alongside the moderating role of governance practices.

A total of 116 family businesses across India took part in the study. Data were collected with the help of a structured questionnaire supplied to the seniormost family member of each firm. The data were analyzed by using the moderated mediation model analysis in R.

The findings indicate that psychological ownership is a key driver of organizational innovation in family businesses. The transfer of knowledge mediates the relationship between psychological ownership and organizational innovation. Moreover, governance practices of the businesses moderate the association between psychological ownership and knowledge transfer, and its downstream consequences on organizational innovation.

While previous research has explored various aspects of nurturing innovation, the present study explores the effect of psychological ownership in the context of family businesses in India. This study also gives insights into how knowledge transfer and governance practices work together to influence innovation in these businesses.

This study aims to find the key drivers of green innovation in family firms by examining firm characteristics and geographical factors. It seeks to develop a conceptual framework that explains how internal resources and external environments influence environmental innovation practices in these businesses.

Using machine learning (ML) methods, this study develops a predictive model for green innovation in family firms, drawing on data from 3,289 family businesses across 27 EU Member States and 12 additional countries. The study integrates the Resource-Based View (RBV) and Location Theory to analyze the impact of firm-level resources and geographical contexts on green innovation outcomes.

The results show that both firm-specific resources, such as size, digital capabilities, years of operation and geographical factors, like country location, significantly influence the likelihood of family firms engaging in environmental innovation. Larger, technologically advanced firms are more likely to adopt sustainable practices, and geographic location is crucial due to different regulatory environments and market conditions.

The findings reinforce the RBV by showing the importance of firm-specific resources in driving green innovation and extend Location Theory by emphasizing the role of geographic factors. The study enriches the theoretical understanding of family businesses by showing how noneconomic goals, such as socioemotional wealth and legacy preservation, influence environmental innovation strategies.

Family firms can leverage these findings to enhance their green innovation efforts by investing in technology, fostering sustainability and recognizing the impact of geographic factors. Aligning innovation strategies with both economic and noneconomic goals can help family businesses improve market positioning, comply with regulations and maintain a strong family legacy.

This research contributes a new perspective by integrating the RBV and Location Theory to explore green innovation in family firms, highlighting the interplay between internal resources and external environments. It also shows the effectiveness of machine learning methods in predicting environmental innovation, providing deeper insights than traditional statistical techniques.