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Due to the rapid development of artificial intelligence (AI) technology, increasing the use of AI in healthcare is critical, but few studies have explored the extent to which physicians cooperate with AI in their work to achieve productive and innovative performance, which is a key issue in operations management (OM). We conducted empirical research to answer this question.

We developed a conceptual model based on the ambidextrous perspective. To test our model, we collected data from 200 Chinese hospitals. One senior and one junior physician from each hospital participated in this research so that we could get a more comprehensive view. Based on the sample of 400 participants and the conceptual model, we examined whether different types of AI use have distinct impacts on physicians’ productivity and innovation by conducting hierarchical regression and post hoc tests. We also introduced team psychological safety climate (TPSC) and AI technology uncertainty (AITU) as moderators to investigate this topic in further detail.

We found that augmentation AI use is positively related to overall productivity and innovative job performance, while automation AI use is negatively related to these two outcomes. Furthermore, we focused on the impacts of the ambidextrous use of AI on these two outcomes. The results highlight the positive impacts of complementary use on both outcomes and the negative impact of balance on innovative job performance. TPSC enhances the positive impacts of complementary use on productivity, whereas AITU inhibits the negative impacts of automation and balanced use on innovative job performance.

In the age of AI, organizations face greater trade-offs between performance and technology management. This study contributes to the OM literature from the perspectives of operational performance and technology management in three ways. First, it distinguishes among different AI implementations and their diverse impacts on productivity and innovative performance. Second, it identifies the different conditions under which automation AI use and augmentation are superior. Third, it extends the ambidextrous perspective by becoming an early adopter of this approach to explore the implications of different types of AI use in light of contingency factors.

The purpose of this briefing is to highlight the critical importance of negotiation skills in the everyday lives of real estate professionals. It delves into how negotiators must improve their negotiations skills given the negotiation-intensive nature of real estate. It also helps to handle common pitfalls and challenges in negotiations, particularly in the increasingly volatile, uncertain, complex and ambiguous (VUCA) reality of the real estate industry. The briefing offers strategic insights for preparation and negotiation aimed at improving any real estate negotiator’s average performance.

The expert opinion piece combines a literature review on negotiation strategies with practical insights. It addresses the observed under appreciation of negotiation theory and skill, reflecting on real-world real estate negotiations. The goal is to enhance the use and recognition of negotiation theory in the real estate industry. The approach merges theoretical analysis with practical application, offering actionable recommendations to improve negotiation outcomes.

The negotiation-intensive real estate industry and the transformative impact of VUCA challenges on real estate professionals’ ability to adapt and continuously negotiate successful deals clashes with many real estate’s professional or fixed mind-set over negotiation historically being an art or a talent and mostly being stuck with win-lose strategies. Instead, negotiation is a science that can be learned and deliberately improved to counter stress-induced or fear-based responses that lead negotiators toward suboptimal negotiation strategies, such as win-lose or naive win-win. However, these dynamics are preventable. Well-equipped and well-prepared value win-win negotiators can adopt a growth mind-set, study modern negotiation advice and frameworks to thrive in the negotiation-rich real estate industry and convert even VUCA challenges into an amazing source of value.

Real estate professionals can become more aware of which and how current obstacles and poor choices negatively contribute to their negotiation performance. It contrasts win-lose and win-win strategic frameworks to enable real estate professionals to become more sophisticated when choosing their negotiation strategies. The briefing also helps real estate professionals expand their negotiation repertoire towards improved strategic flexibility when managing the evolving real estate profession reality and challenges.

The originality and value of the briefing lie in its comprehensive approach to addressing the negotiation challenges faced by real estate professionals. It offers a holistic view of real estate negotiation, advocating for a paradigm shift from traditional win-lose tactics to a collaborative, value win-win approach. The briefing integrates modern negotiation theory and emphasises ethical practices, providing practical strategies and best practices for professionals to improve their skills and adapt to industry changes. By empowering real estate professionals with knowledge and tools to navigate negotiations effectively, the briefing contributes to the overall success and professionalism of the industry.

This study aims to explore how subsidiary capabilities collectively configure for performance. Additionally, it seeks to examine whether these configurations of capabilities can provide equifinal solutions through developing a comprehensive research framework that focuses on subsidiaries in China.

With a data set collected through a questionnaire from 172 Korean multinational enterprises (MNEs) in China, this study used a fuzzy-set qualitative comparative analysis to detect the capability conditions and configurations. These configurations represent combinations of various subsidiary capabilities linked to high performance.

This study identified several complex pathways with distinct configurations for high subsidiary performance. The findings demonstrate the importance of configurations over individual conditions. Thus, the results highlight that the effectiveness of diverse capabilities, which are widely believed to singularly contribute to the high performance of MNE subsidiaries, depends on how each combines with other capabilities. Overall, the findings provide a richer and fine-grained understanding of the role and relative importance of various forms of MNE subsidiary capabilities and how the joint effect of these subsidiaries contributes to high performance.

This study suggests that MNE managers should comprehensively understand how subsidiary capabilities are configured to produce subsidiary performance outcomes. This specifically illustrates the importance of understanding the mutually conflicting yet collectively exhaustive results of multi-selective solutions and aims to align with China’s industrial and regional heterogeneity.

By examining the role of MNE subsidiary capability configurations, which may collectively influence the subsidiary’s performance, this study contributes to the literature. It elucidates how MNE subsidiaries may achieve superior performance by developing and possessing various capabilities tailored to the local context.

As of now, the digitization of corporate finance presents a paradigm shift in business strategy, innovation, financing and managerial capability around the globe. However, the prevailing finance scholarly works hardly document the impact of the digitalization of corporate finance on firm performance with global evidence and analysis. Hence, the contemporary debate on whether firm performance is genuinely stimulated because of the digitalization of corporate finance or not has been a pressing issue in the relevant literature. Therefore, the purpose of this study is to identify a data-driven, concise response to an unaddressed finance issue if the performance of high-digitalized firms (HDFs) outperforms that of their counterpart peers for wealth maximization.

The first stage test models examine the firm performance of relatively high-digitalized firms as opposed to low-digitalized firms based on the system GMM. The second stage test of the probabilistic (logit) model infers that the probability of being HDFs explores because of better performance. Then, the authors execute robust checks based on the different quantile regressions and Z-score-based system GMM. In addition, the authors recheck and present the test results of the fixed effect and random effect to capture time-invariant individual heterogeneity. Finally, the supplementary test findings of firms’ credit strength by using Altman five- and four-factor Z-score models are presented.

By using cross-country panel analysis as 15 years’ test bed for HDFs and low digitalized firms (LDFs), the test results indicate that the overall firm performance of a digitalized firm is significantly better than that of a non-digitalized firm. The global evidence documents that HDFs are exposed to higher values and are financially more persistent as compared to their counterparts. The finding is remarkably concomitant across several possible subsample analysis, such as country–industry–size–period analysis.

This study can be remarkably effective in encouraging managers, policymakers and investors to acknowledge the need for adopting the required digitalization. Overall, this original study addresses a core research gap in the corporate finance literature and remarkably provides further direction to rethink the assumptions of firm digitalization on additive value and thereby identify optimal decisions for wealth maximization. The findings also imply that investors require an additional risk premium if they invest in relatively LDFs, which have relatively lower market value and weaker firm performance.

From an investors point of view, the academic novelty contributes to an innovative and unsettled issue on the impact of digitization of corporate finance on firm performance because there is a new question of high or low digitization of corporate finance in the global market. Hence, this academic novelty contributes to sharing global evidence of the digitalization of corporate finance and its effect on firm performances. In addition, an intensive critical review analysis is conducted based on the most recent and relevant scholarly works published in the top-tier journals of finance and business stream to fix the hypothesis. Overall, this study addresses a core research gap in the corporate finance literature; notably provides further direction to rethink firm digitalization; and thereby identifies optimal decisions for shareholders’ wealth maximization.

The present paper aims to address challenges associated with path planning and obstacle avoidance in mobile robotics. It introduces a pioneering solution called the Bi-directional Adaptive Enhanced A* (BAEA*) algorithm, which uses a new bidirectional search strategy. This approach facilitates simultaneous exploration from both the starting and target nodes and improves the efficiency and effectiveness of the algorithm in navigation environments. By using the heuristic knowledge A*, the algorithm avoids unproductive blind exploration, helps to obtain more efficient data for identifying optimal solutions. The simulation results demonstrate the superior performance of the BAEA* algorithm in achieving rapid convergence towards an optimal action strategy compared to existing methods.

The paper adopts a careful design focusing on the development and evaluation of the BAEA* for mobile robot path planning, based on the reference [18]. The algorithm has remarkable adaptability to dynamically changing environments and ensures robust navigation in the context of environmental changes. Its scale further enhances its applicability in large and complex environments, which means it has flexibility for various practical applications. The rigorous evaluation of our proposed BAEA* algorithm with the Bidirectional adaptive A* (BAA*) algorithm [18] in five different environments demonstrates the superiority of the BAEA* algorithm. The BAEA* algorithm consistently outperforms BAA*, demonstrating its ability to plan shorter and more stable paths and achieve higher success rates in all environments.

The paper adopts a careful design focusing on the development and evaluation of the BAEA* for mobile robot path planning, based on the reference [18]. The algorithm has remarkable adaptability to dynamically changing environments and ensures robust navigation in the context of environmental changes. Its scale further enhances its applicability in large and complex environments, which means it has flexibility for various practical applications. The rigorous evaluation of our proposed BAEA* algorithm with the Bi-directional adaptive A* (BAA*) algorithm [18] in five different environments demonstrates the superiority of the BAEA* algorithm.

The rigorous evaluation of our proposed BAEA* algorithm with the BAA* algorithm [18] in five different environments demonstrates the superiority of the BAEA* algorithm. The BAEA* algorithm consistently outperforms BAA*, demonstrating its ability to plan shorter and more stable paths and achieve higher success rates in all environments.

The originality of this paper lies in the introduction of the bidirectional adaptive enhancing A* algorithm (BAEA*) as a novel solution for path planning for mobile robots. This algorithm is characterized by its unique characteristics that distinguish it from others in this field. First, BAEA* uses a unique bidirectional search strategy, allowing to explore the same path from both the initial node and the target node. This approach significantly improves efficiency by quickly converging to the best paths and using A* heuristic knowledge. In particular, the algorithm shows remarkable capabilities to quickly recognize shorter and more stable paths while ensuring higher success rates, which is an important feature for time-sensitive applications. In addition, BAEA* shows adaptability and robustness in dynamically changing environments, not only avoiding obstacles but also respecting various constraints, ensuring safe path selection. Its scale further increases its versatility by seamlessly applying it to extensive and complex environments, making it a versatile solution for a wide range of practical applications. The rigorous assessment against established algorithms such as BAA* consistently shows the superior performance of BAEA* in planning shorter paths, achieving higher success rates in different environments and cementing its importance in complex and challenging environments. This originality marks BAEA* as a pioneering contribution, increasing the efficiency, adaptability and applicability of mobile robot path planning methods.

This paper examines firm-level accountability and performance implications under a state-dominated institutional environment, China, for firms engaged in the space economy. Extant studies on the rapidly evolving civil space economy predominantly focus on developed Western economies at national or sector levels, frequently ignoring alternative institutional contexts. Additionally, limited attention has been given to firm-level empirical evidence and analysis, including corporate social responsibility (CSR) practice-R&D quality relationships in the space economy. The paper addresses each of these areas.

This paper utilises multiple regression, propensity score matching and split sampling methods applied to a proprietary dataset of Shanghai and Shenzhen Stock Exchange-listed A-share firms. Results are robust to endogeneity issues, alternative measurement of dependent variables and sampling.

China’s space firms demonstrate superior CSR performance to their counterparts in other sectors, supporting CSR‘s role in maintaining legitimacy. Their CSR practices also positively contribute to firm patent quality. The link is more pronounced among firms facing higher economic policy uncertainty and for state-owned enterprises (SOEs). The latter is due to SOEs’ government support, advantages in financing and attracting and retaining a high-quality workforce.

This paper adds to discussion on major space power’s, by examining China’s state-dominated civil space sector. It also addresses a lack of empirical firm-level evidence on space firm behaviour by examining the impact of firm-level CSR practices on R&D quality outcomes, areas in which there is a limited literature.

Financial and nonfinancial disclosures (sustainable accounting) are crucial in the annual financial reports of many firms. This study aims to explore the dynamic relationship between sustainability disclosure quality (SDQ) and financial performance (FP) within mandatory disclosure frameworks. SDQ is evaluated across six dimensions, encompassing both the quality and quantity of disclosures, aiming to understand their reciprocal influence.

Using the generalized method of moments (GMM), this research analyzes data from 2013 to 2019, focusing on 99 listed Indian firms within the S&P Bombay stock exchange (BSE) 500 index. The study uses rigorous measurement criteria to assess SDQ and uses statistical methods to unveil the causal link between SDQ and FP.

The results show a positive causal connection between SDQ and FP, where organizations with good FP make relatively higher disclosures across FP proxies than their counterparts. Additionally, the study investigates the impact of research and development (R&D) expenditure and dividend payments (DIVD) on SDQ. Notably, lower R&D spending is associated with higher quality SDs, and companies with superior SDQ exhibit increased DIVD.

The findings advocate for strengthened regulatory compliance, incentivized sustainable practices and heightened reporting standards for a transparent business environment and achieving the relevant United Nations Sustainable Development Goals.

This research contributes original insights by uncovering the intricate relationship between SDQ and FP, shedding light on the impact of R&D expenditure and DIVD on SDQ. These findings contribute to a nuanced understanding of the interplay between FP and sustainability reporting within the context of mandatory disclosure frameworks.

The study aims to conduct an empirical research to examine how green human resource management (GHRM) can influence sustainable organizational performance (SOP) in terms of financial performance (FP) and operational performance (OpP), both directly and through employee green behavior (EGB), in the backdrop of the Indian information and communication technology (ICT) sector.

The study is based on primary data collected through a questionnaire survey from 387 employees engaged in the ICT sector. Confirmatory factor analysis validates the measurement model, while structural equation modeling (SEM) using the partial least squares (PLS) method examines the hypothesized relations.

Results confirm that GHRM significantly contributes to EGB, FP and OpP, with a theoretical underpinning concerning resource-based view (RBV) and ability-motivation-opportunity (AMO) concepts. The study also confirms that connections of GHRM with both FP and OpP are significantly and positively mediated by EGB.

The study provides evidence-based implications of different GHRM practices toward EGB, FP and OpP, which are highly pertinent to strategists, policymakers, managers and supervisors in implementing GHRM for adding value to both operational and financial statements while protecting nature and natural resources through the green efforts of employees.

The study bridges a significant theoretical and practitioner gap by providing a deeper understanding of GHRM as a sustainable human resource management (HRM) model in the context of the Indian ICT sector. It empirically explores the connections between GHRM and OpP, which is a crucial dimension of SOP, and highlights noteworthy implications for promoting EGB, an individual micro-sustainability dimension directed toward the achievement of broader organizational goals, which are essentially oriented to macro-sustainability.

This study explores the role of knowledge management capabilities (KMCs) in enhancing competitive advantage and organisational performance in fashion retailing. Employing the resource-based view (RBV) and knowledge-based view (KBV) perspectives, it investigates the interplay between managing knowledge effectively and fashion products’ complexity. The goal is to provide new insights into optimising KMC for greater agility and success in the fashion retail industry.

The study analysed survey data from 322 US fashion retail professionals using partial least squares structural equation modelling (PLS-SEM).

The results revealed that knowledge infrastructure capability enhanced both competitive advantage and organisational performance significantly. In contrast, knowledge process capability did not significantly affect competitive advantage, it improved organisational performance. Importantly, product complexity moderated the relationship between competitive advantage and organisational performance negatively.

This study underscores the necessity for retailers in the fashion industry to enhance their KMC to bolster competitive advantage and organisational performance, while it also acknowledges product complexity’s effect on these strategies. These insights offer actionable guidance for industry leaders to optimise knowledge management to navigate the rapidly evolving retail landscape.

This research offers novel insights into the interplay of product complexity and KMC in fashion retail and highlights the unique effects on competitive advantage and organisational performance valuable for both academia and industry.

Grounded in upper echelon (UE) theory, this study aims to examine the role of managerial competencies (business experience, financial literacy and digital literacy) in sustainable development strategy, with resource management as a mediator.

The empirical data collection is conducted through a survey completed by 297 top management teams of small and medium-sized enterprises (SMEs) operating in Pakistan. Structural equation modelling in Smart PLS is used to substantiate the hypotheses.

The findings reveal that financially and digitally literate managers significantly contribute to the sustainable development strategies of SMEs. However, experienced managers do not focus significantly on sustainable development strategies. Resource management partially mediates the nexus between financial literacy and sustainable development strategy, as well as between digital literacy and sustainable development strategy. In contrast, resource management does not mediate the nexus between business experience and sustainable development strategy.

This study recommends that SMEs should prioritize managers with digital and financial literacy over those with experience. SMEs led by a management team with digital and financial literacy are more effective in resource management for sustainable development practices, whereas experienced managers may not significantly prioritize managing resources for sustainability.

While research based on the UE theory significantly contributes to the body of knowledge on sustainable development, the role of managerial competencies, particularly business experience, financial literacy and digital literacy, in sustainable development strategy via resource management is neglected. This research fills this gap in the context of UE theory and thereby enriches the literature.