Search results

This article aims to examine whether the organizational changes brought about by digital transformation (DT) -such as a new organizational culture, new leadership and new business models-influence talent management, with the latter being seen as one of the major challenges facing companies in their process of digital transformation.

Using a quantitative methodology, a survey was applied to 314 companies in order to analyze the results of their talent management in the DT process. DT is not only digitalization as demonstrated in this study. Talent management is the key piece that can facilitate or block achieving high levels of digital maturity.

The study finds that the changes brought about by DT impact talent attraction, talent retention, and talent management in general, and also shows that digital transformation does not depend on digitalization, but rather that talent management is the key to either helping or preventing high levels of digital maturity being achieved.

The originality of this work lies in examining the influence of the changes that DT entails in talent management.

Digitalization is one of the major factors that fosters economic growth across the world. However, the level of digitalization varies significantly between developed and developing countries, with the latter often lagging behind. To bridge this gap, it is crucial to pinpoint the drivers of digitalization, specifically from the macroeconomic and country-level governance dimensions. Therefore, this study aims to investigate the determinants of digitalization, particularly for countries in Asia and the Pacific region.

Our study utilizes unbalanced panel data from 46 Asian and Pacific countries for the period of 2001–2021. Initially, we analyzed the data using conventional econometric methods, such as pooled ordinary least squares (POLS), random-effects model (REM) and fixed-effects model (FEM). Moreover, we employed endogeneity-corrected techniques and alternative proxies to enhance the robustness and reliability of our findings.

Our findings reveal that economic development progress, government expenditure relative to country size and political stability are key drivers of digitalization. In contrast, corruption at the country level emerges as a significant impediment. Notably, our results remain robust to endogeneity-corrected techniques and alternative proxies of digitalization. Overall, these insights can inform policymakers, helping them to understand the macroeconomic and governance factors shaping digitalization and guide their decision-making toward effective policy interventions.

This study’s empirical findings add significant value to the existing literature by quantifying the impact of macroeconomic and governance factors on digitalization in selected countries. This offers valuable insights for policymakers, particularly in nations with lower levels of digitalization.

The purpose of this study is to understand the strategy adopted by family firms in using social media for their business. Based on the social media usage, this paper attempts to segment family firms. To do so, a reactive – proactive – innovative (RPI) scale was developed for the study. Then, the family firms were categorised as reactive, proactive or innovative social media users. Further, based on the scale developed, clusters were created. Family firms were placed into different clusters based on the strategy that they had for using social media platforms for their business.

A pilot sample of 50 family firms and a main study of 256 Indian family firm entrepreneurs were surveyed through self-administered questionnaires. Factor analysis reduced the 12 scale-based questions to three distinct factors. Confirmatory factor analysis was then conducted on the main sample to confirm the constructs identified using exploratory factor analysis. Cluster analysis was used to build clusters of entrepreneurs who use social media as part of their digital marketing strategy.

Findings reveal that the Indian family firm market is largely divided into four main segments. These segments represent distinct behaviours with respect to the use of social media. The four segments of family firm entrepreneurs were named as high rollers, ignorant inhabitants, trend-setters, combative crowd based on their social media usage behaviour. These clusters give deep insights into the strategic usage of social media by family firms.

The limitation of this study is that entrepreneurs from all Indian states were not considered in the sample because of cost implications. This research study has only created the segmentation of the family firms as reactive, proactive or innovative social media users and also has created the clusters as high rollers, ignorant inhabitants, trend-setters and combative crowd. Also, the reasons for their behaviour and root cause for the strategic usage have not been studied.

This study reflects on current practices of family firms with respect to usage of social media and groups them into large identifiable clusters. Equipped with the findings from this study, the RPI scale developed for the study and the clusters created, entrepreneurs can now move towards better use of social media for innovation.

Although past studies have advocated the use of social media to spur innovation in firms, this study segments the current market based on their practices. It allows readers to gauge the proportion of family firms using social media for innovation and paves the way for a change in behaviour amongst these firms.

This study examines the mediating roles of the three dimensions of business intelligence (sensing capability, transforming capability and driving capability) in the relationship between the three dimensions of big data analytics capability (big data analytics management, technology and talent capabilities), and radical innovation among Chinese manufacturing enterprises.

A theoretical framework was developed using the resource-based view. The hypothesis was tested using empirical survey data from 326 Chinese manufacturing enterprises.

Empirical results show that, in the Chinese manufacturing context, business intelligence sensing capability, business intelligence transforming capability and business intelligence driving capability positively mediate the impact of big data analytics capability on radical innovation.

The results offer managerial guidance for leaders to properly use big data analytics capability, business intelligence and radical innovation as well as offering theoretical insight for future research in the manufacturing industry’s radical innovation.

This is among the first studies to examine three dimensions of big data analytics capability on the manufacturing industry’s radical innovation by considering the mediating role of three dimensions of business intelligence.

This study aims to examine the impact of environmental sustainability, social sustainability and corporate reputation on the business performance of energy companies operating in an emerging market.

A self-administered questionnaire was distributed to 400 managers in top and middle-level positions in energy companies located in Kuala Lumpur, Malaysia were collected through an online survey. These managers had a strong understanding of the operational aspects of the companies and possessed good knowledge of the company’s performance. The collected data were analyzed using multiple regression analysis to assess the hypothesized relationships.

The findings reveal significant influences of corporate reputation, environmental sustainability and social sustainability on the business performance of energy companies operating in an emerging market. Notably, corporate reputation emerges as the primary predictor, underscoring the significance of emphasizing the fundamental aspects of companies such as superior products or services, effective management practices and investment quality. A strong reputation is essential for attracting investors, customers and other stakeholders by meeting their expectations for high-quality products or services. It serves as a crucial factor in establishing trust and credibility, which are vital for sustained success in the market.

Energy companies should proactively integrate corporate reputation into their operational strategies to enhance business performance. Furthermore, they should develop and execute comprehensive environmental and social sustainability initiatives within their organizations. By doing so, they can effectively enhance both financial and non-financial performance while fostering a culture of employee engagement aimed at further enhancing productivity.

This study stands out as a unique and significant contribution to theory by using the triple bottom line framework as the underlying theory and integrating corporate reputation into the proposed framework. It represents a novel approach, particularly within the context of energy companies operating in an emerging market. This research serves as a valuable complement to prior studies primarily conducted in developed (Western) economies, expanding the knowledge base in this field.

This study demonstrates how artificial intelligence (AI) shapes the strategic planning process in volatile, uncertain, complex and ambiguous (VUCA) business environments. Having adopted various domains of the Cynefin framework, the research explores AI's transformative potential and provide insights regarding how organisations can harness AI-driven solutions for strategic planning.

This conceptual paper theorises the role of AI in strategic planning process in a VUCA world by integrating extant knowledge across multiple literature streams. The “model paper” approach was adopted to provide a theoretical framework predicting relationships among considered concepts.

The paper highlights potential application of the Cynefin framework to manage complexities in strategic decision-making process, the transformative impact of AI at different stages of strategic planning, the required strategic planning characteristics within VUCA to be supported by AI and the attendant challenges posed by AI integration in the uncertain business landscape.

This study pioneers a theoretical exploration of AI's role in strategic planning within the VUCA business landscape, guided by the Cynefin framework. Thus, it enriches scholarly discourse and expands knowledge frontiers.

The purpose of this study is to investigate the relationship between artificial intelligence (AI) and decision making in the development of AI-related capabilities. We investigate if and how AI-driven decision making has an impact on firm performance. We also investigate the role played by environmental dynamism in the development of AI capabilities and AI-driven decision making.

We surveyed 346 managers in the United States using established scales from the literature and leveraged p modelling to analyse the data.

Results indicate that AI-driven decision making is positively related to firm performance and that big data-powered AI positively influences AI-driven decision making. Moreover, there is a positive relationship between big data-powered AI and the development of AI capability within a firm. It is also found that the control variables of firm size and age do not significantly affect firm performance. Finally, environmental dynamism does not have a positive and significant moderating effect on the path connecting big data-powered AI and AI-driven decision making, while it exerts a positive moderating effect on the development of AI capability to strengthen AI-driven decision making.

These findings extend the resource-based view by highlighting the capabilities developed within the firm to manage big data-powered AI. This research also provides theoretically grounded guidance to managers wanting to align their AI-driven decision making with superior firm performance.

The authors investigate conditions that drive innovation performance in foreign-owned subsidiaries. The authors study five variables affecting innovation performance: organizational agility and digital capabilities as the main drivers and competencies and embeddedness in internal and external networks as complementary antecedents of innovation.

The authors draw on the neo-configurational perspective and apply fuzzy set qualitative comparative analysis (fsQCA) to empirically test survey data from subsidiaries located in the emerging economies of Thailand and Vietnam.

While the authors find no single condition on its own determining innovation performance, the authors do find that in concert they form four configurations of high innovation performance. The results indicate that all configurations contain competencies, as well as that subsidiaries should prioritize between internal and external networks to complement agility, digital capabilities, to achieve high innovation performance. The authors also reveal intriguing contextual differences in the innovation performance configurations between the two host countries.

By incorporating causal complexity as well as substitutability and complementarity of innovation drivers, the authors extend the current understanding of subsidiary innovation performance outcomes.

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.

Establishing an effective educational system is directly tied to academic leadership, a multifaceted concept that differs from one environment to another. The purpose of this research is to investigate the role of digital leadership (DL) aspects in the enhancement of technical knowledge sharing (KS) and dealing with emotional intelligence (EI) among the teaching faculty of higher education institutions (HEIs).

Following a quantitative and cross-sectional research design, convenient sampling is employed for data collection via a self-administered questionnaire from 320 faculty members of private HEIs in Pakistan.

Structural equation model (SEM) is used for path analysis. The results reveal a positive and significant effect of DL, aspects like visionary leadership (VL), digital citizenship (DC), systematic improvement (SI), on knowledge sharing (KS), and emotional intelligence (EI).

This study has highlighted the significance of DL in private HEIs. The findings of the study imply that institutional heads of higher education institutions (HEIs) can successfully manage the knowledge assets that they have and those of their staff members, ensure the successful adoption of technology and foster product and process innovation that improves organizational performance and integrates successful strategies into the educational system by demonstrating DL aspects. The research also analyzes institutional heads' present leadership strategies to enhance response to technological change and innovations, which are considered fundamental pillars of organizational success. Ultimately, this will extend the literature on adopting DL techniques towards digital transformation in the education system.

This study empirically confirms the role of DL aspects such as VL, DC, and SI towards KS and EI. Most of the research demonstrates the direct impact of DL on EI, whereas the aspects of DL are not directly related to KS and EI. Studies have also shown how DL enhances its role in incorporating leadership in organizations, industries, and education, mainly in Western countries. This research addresses the gap in understanding the direct effects of DL aspects on KS and EI in non-Western countries, particularly within the education sector.