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This study aims to explore how to overcome and address the loss of exploratory innovation, thereby achieving greater success in exploratory innovation. This phenomenon of loss occurs when enterprises decrease their investment in and engagement with exploratory innovation, ultimately leading to an insufficient amount of such innovation efforts. Drawing on dynamic capabilities, this study investigates the relationship between organizational foresight and exploratory innovation and examines the moderating role of breakthrough orientation/financial orientation.

This study used survey data collected from 296 Chinese high-tech companies in multiple industries and sectors.

The evidence produced by this study reveals that three elements of organizational foresight (i.e. environmental scanning capabilities, strategic selection capabilities and integrating capabilities) positively influence exploratory innovation. Furthermore, this positive effect is strengthened in the context of a high-breakthrough orientation. Moreover, the relationships among environmental scanning capabilities, strategic selection capabilities and exploratory innovation become weaker as an enterprise’s financial orientation increases, whereas a strong financial orientation does not affect the relationship between integrating capabilities and exploratory innovation.

Ambidexterity is key to successful enterprise innovation. Compared with exploitative innovation, it is by no means easy to engage in exploratory innovation, which is especially important in high-tech companies. While the loss of exploratory innovation has been observed, few empirical studies have explored ways to promote exploratory innovation more effectively. A key research implication of this study pertains to the role of organizational foresight in the improvement of exploratory innovation in the context of high-tech companies.

This paper contributes to the broader literature on exploratory innovation and organizational foresight and provides practical guidance for high-tech companies regarding ways of avoiding the loss of exploratory innovation and becoming more successful at exploratory innovation.

This study aims to examine how knowledge sharing contributes to organizations’ ambidexterity, their overall performance and the role of knowledge quality in this relationship. Knowledge sharing is conceptualized based on tacit and explicit dimensions, and ambidexterity is viewed as comprising exploitative and explorative capabilities.

This study uses a cross-sectional survey-based research design and structural equation modeling to test the proposed model of knowledge sharing and knowledge quality in organizational ambidexterity and the related hypotheses.

The results indicate that tacit knowledge sharing has a significant, direct impact on the exploitative and explorative capabilities of the organization and indirectly impacts both dimensions of ambidexterity (i.e. exploitative and explorative) through knowledge quality. In contrast, explicit knowledge sharing does not have a significant impact on knowledge quality and affects only the exploitative extent of ambidexterity. Both exploitative and explorative capabilities significantly impact organizational performance.

To the best of the authors’ knowledge, this study is the first study to empirically examine the role of knowledge quality in the context of knowledge sharing for ambidexterity, especially within the context of organizations in the United Arab Emirates.

Notwithstanding its significance as a form of strategic human capital investment, employee training has not yielded consistent conclusions among scholars regarding its impact on organizational performance. Some studies deem it effective, while others regard it as ineffective. We contend that distinct types of training impact various facets of firm performance.

In this study, we categorize employee training as either exploitative or explorative. Specifically, we examine their impact on two aspects of organizational performance: short-term performance and long-term competence, using a quasi-experimental setting and a difference-in-differences (DID) method.

We find that exploitative training is more effective in improving firms’ short-term performance (e.g. firms’ sales revenue), while explorative training is more effective in enhancing firms’ long-term competence (e.g. firms’ innovation output).

The findings of this study illuminate concrete benefits of training for practitioners, suggesting that firms can strategically select employee training category to maximize returns on their investment in strategic human capital based on their strategic orientations.

In the current highly volatile and uncertain economic environment, recovery strategies that emphasise attributes and skills are essential for an enterprise to recover and adapt to disruptions. Based on the resource-based view (RBV), this study aims to understand how organisational resilience functions and its outcomes. Specifically, this study establishes links between organisational resilience and internal capabilities in information technology (IT) applications, exploitation-exploration activities and organisational leadership, which are represented by IT competencies, organisational ambidexterity and paradoxical leadership, respectively. The study also analyses the role of government digital transformation policies after the COVID-19 pandemic as an external resource.

This study provides empirical evidence of the dynamic relationships between organisational resilience, ambidexterity and performance under the interactions IT competencies, digital transformation policies and paradoxical leadership by using data collected from 336 small- and medium-sized enterprises (SMEs) in Vietnam and the partial least squares-structural equation modelling technique.

IT competencies and organisational ambidexterity strengthen organisational resilience, reduce missed opportunities and increase organisations’ responsiveness to market volatility. Increasing organisational ambidexterity and resilience enhances the business performance of SMEs. Paradoxical leadership favours organisational ambidexterity and resilience and their outcomes. Digital transformation policies from the government can support SMEs’ IT competencies and resilience.

To the best of the authors’ knowledge, this study based on the RBV is the first to show how integrating external resources with dynamic capabilities such as organisational ambidexterity and resilience can help SMEs build and maintain a sustainable competitive advantage in highly uncertain environments. This research emphasises the vital role of organisational resilience in improvising changes in working processes in response to unexpected events and the importance of a strategy for developing the capability to anticipate a wide variety of situations and seize opportunities quickly.

From the lens of organizational ambidexterity, the energy sector companies in India are confronted with numerous human resources (HR) challenges as they explore new avenues in the renewable sector while exploiting non-renewable (conventional) resources. This study aims to decode these challenges and identifies key competencies to address these.

Data were gathered and analysed using a sequential mixed methodology (qualitative and quantitative) in three phases. In Phase 1, a focused group discussion with eight senior management employees was carried out to identify the HR challenges and competencies required for meeting those challenges. The themes derived from this were used in designing the questionnaire for use in Phase 2 to capture the perceptual differences between HR and Line managers on these challenges. The identified competencies by senior management were prioritized using the analytical hierarchy process in Phase 3.

The study provides insight into the HR challenges in the pursuit of organizational ambidexterity by energy sector companies in India. Also, key competencies to deal with these challenges have been prescribed.

While previous studies have identified generic HR challenges in this domain, the present study is unique in decoding the HR challenges as these organizations are simultaneously exploring and exploiting energy sources for achieving excellence in the Indian context.

Although businesses continue to take up artificial intelligence (AI), concerns remain that companies are not realising the full value of their investments. The study aims to provide insights into how AI creates business value by investigating the mediating role of Business Process Management (BPM) capabilities.

The integrative model of IT Business Value was contextualised, and structural equation modelling was applied to validate the proposed serial multiple mediation model using a sample of 448 organisations based in the EU.

The results validate the proposed serial multiple mediation model according to which AI adoption increases organisational performance through decision-making and business process performance. Process automation, organisational learning and process innovation are significant complementary partial mediators, thereby shedding light on how AI creates business value.

In pursuing a complex nomological framework, multiple perspectives on realising business value from AI investments were incorporated. Several moderators presenting complementary organisational resources (e.g. culture, digital maturity, BPM maturity) could be included to identify behaviour in more complex relationships. The ethical and moral issues surrounding AI and its use could also be examined.

The provided insights can help guide organisations towards the most promising AI activities of process automation with AI-enabled decision-making, organisational learning and process innovation to yield business value.

While previous research assumed a moderated relationship, this study extends the growing literature on AI business value by empirically investigating a comprehensive nomological network that links AI adoption to organisational performance in a BPM setting.

With the recent proliferation of AI, organisations are transforming not only their organisational design but also the input and output operational processes of the hiring process. The purpose of this paper is to explore the organisational and operational dimensions resulting from the deployment of AI during talent acquisition process.

The authors conducted semi-structured interviews and meetings with human resources (HRs) professionals, recruiters and AI hiring platform providers in Sweden. Using an inductive data analysis rooted in the principles of grounded theory, the study uncovered four aggregate dimensions critical to understanding the role of AI in talent acquisition.

With insights from algorithmic management and ambidexterity theory, the study presents a comprehensive theoretical framework that highlights four aggregate dimensions describing AI’s transformative role in talent recruitment. The results provide a cautionary perspective, advising against an excessive emphasis on operational performance driven solely by algorithmic management.

The study is limited in scope and subject to several constraints. Firstly, the sample size and diversity are restricted, as the findings are based on a limited number of semi-structured interviews and meetings with HRs professionals, recruiters, and AI hiring platform providers. Secondly, the rapid evolution of AI technologies means that the study’s findings may quickly become outdated as new advancements and applications emerge.

The results provide managers with actionable information that can lead to more precise and strategic management practices, ultimately contributing to improved organizational performance and outcomes. Plus, enhancing their ability to make informed decisions, optimize processes and address challenges effectively.

The results signal both positive and negative impacts on employment opportunities. On the positive side, AI can streamline recruitment processes, making it easier for qualified candidates to be identified and hired quickly. However, AI systems can also perpetuate existing biases present in the data they are trained on, leading to unfair hiring practices where certain groups are systematically disadvantaged.

By examining the balance between transactional efficiency and relational engagement, the research addresses a crucial trade-off that organizations face when implementing AI in recruitment. The originality lies in its critique of the prevailing emphasis on e-recruiting.

This study offers practical insights into how generative artificial intelligence (AI) can enhance responsible manufacturing within the context of Industry 5.0. It explores how manufacturers can strategically maximize the potential benefits of generative AI through a synergistic approach.

The study developed a strategic roadmap by employing a mixed qualitative-quantitative research method involving case studies, interviews and interpretive structural modeling (ISM). This roadmap visualizes and elucidates the mechanisms through which generative AI can contribute to advancing the sustainability goals of Industry 5.0.

Generative AI has demonstrated the capability to promote various sustainability objectives within Industry 5.0 through ten distinct functions. These multifaceted functions address multiple facets of manufacturing, ranging from providing data-driven production insights to enhancing the resilience of manufacturing operations.

While each identified generative AI function independently contributes to responsible manufacturing under Industry 5.0, leveraging them individually is a viable strategy. However, they synergistically enhance each other when systematically employed in a specific order. Manufacturers are advised to strategically leverage these functions, drawing on their complementarities to maximize their benefits.

This study pioneers by providing early practical insights into how generative AI enhances the sustainability performance of manufacturers within the Industry 5.0 framework. The proposed strategic roadmap suggests prioritization orders, guiding manufacturers in decision-making processes regarding where and for what purpose to integrate generative AI.

Well-constructed transportation infrastructure may effectively decrease barriers to the flow of innovative human resources and inventive elements, accelerating enterprise innovation activities. This study will explore how HSR helps enterprises achieve ambidextrous innovation, including the mediating mechanism of absorbed slack resources, innovative talents, and the heterogeneous effects of management shareholding ratio and financing constraints.

Based on resource dependence theory and social network theory, this study employs a quasi-natural experiment of China’s high-speed railway and builds a multi-time point DID model to investigate its influence on enterprise ambidextrous innovation.

Results suggest that the HSR positively influences both exploitative and exploratory innovation, and the influence is more substantial on exploitative innovation. Further analysis finds two influencing channels through which HSR influences enterprise ambidextrous innovation: providing redundant resources and attracting innovative talents. Heterogeneity analysis indicates that HSR has a more significant positive effect on exploratory innovation for enterprises with high management shareholding. In the low financing constraint group, the HSR opening has a more significant impact on ambidextrous innovation.

In ambidextrous innovation, enterprises should rationalize the allocation of resources, attach importance to the innovative talent introduction, and choose differentiated paths based on intrinsic characteristics. Meanwhile, the government should actively improve the HSR routes and continuously improve the innovative environment.

This study enriches the theoretical research framework of HSR and ambidextrous innovation by identifying the channel mechanisms and boundary conditions through which HSR affects ambidextrous innovation and expands the consequences of HSR and the antecedents of ambidextrous.

Managers must make numerous strategic decisions in order to initiate and implement a business model innovation (BMI). This paper examines how managers perceive the management team interacts when making BMI decisions. The paper also investigates how group biases and board members’ risk willingness affect this process.

Empirical data were collected through 26 in-depth interviews with German managing directors from 13 companies in four industries (mobility, manufacturing, healthcare and energy) to explore three research questions: (1) What group effects are prevalent in BMI group decision-making? (2) What are the key characteristics of BMI group decisions? And (3) what are the potential relationships between BMI group decision-making and managers' risk willingness? A thematic analysis based on Gioia's guidelines was conducted to identify themes in the comprehensive dataset.

First, the results show four typical group biases in BMI group decisions: Groupthink, social influence, hidden profile and group polarization. Findings show that the hidden profile paradigm and groupthink theory are essential in the context of BMI decisions. Second, we developed a BMI decision matrix, including the following key characteristics of BMI group decision-making managerial cohesion, conflict readiness and information- and emotion-based decision behavior. Third, in contrast to previous literature, we found that individual risk aversion can improve the quality of BMI decisions.

This paper provides managers with an opportunity to become aware of group biases that may impede their strategic BMI decisions. Specifically, it points out that managers should consider the key cognitive constraints due to their interactions when making BMI decisions. This work also highlights the importance of risk-averse decision-makers on boards.

This qualitative study contributes to the literature on decision-making by revealing key cognitive group biases in strategic decision-making. This study also enriches the behavioral science research stream of the BMI literature by attributing a critical influence on the quality of BMI decisions to managers' group interactions. In addition, this article provides new perspectives on managers' risk aversion in strategic decision-making.