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High costs, technical difficulties, and policy uncertainties are the main challenges in carbon capture technology investments. Therefore, innovative financial products are required to develop projects that overcome these difficulties. Some issues must be considered when developing innovative financial products. An important problem in this process is that these features cannot possibly exist together in the new financial product, because each of these features incurs some costs. Therefore, identifying the most important features of innovative financial products is necessary. Accordingly, this study develops a new and innovative financial product to increase the effectiveness of investments in carbon capture technologies. For this purpose, a novel artificial intelligence (AI)-based fuzzy decision-making model is constructed. First, the weights of the experts were calculated by considering AI methodology. Second, the factors affecting investment in carbon capture technologies were weighted using a spherical fuzzy DEMATEL. Finally, the financial features required for investments were ranked using the spherical fuzzy ARAS method. This study's main contribution is its creation of a novel fuzzy decision-making model by integrating AI methodology with fuzzy decision-making theory. In this process, the weights of the experts are calculated using an AI approach. It is concluded that cost-effectiveness must be prioritized in the development of new financial products. Technological competence is another aspect that should be considered in this process. However, innovative financial products should include risk management and flexible financing. [ABSTRACT FROM AUTHOR]

Purpose: This research aims to examine how electronic human resource management (E-HRM) impacts perceived organizational performance (OP) and job performance (JP) in telecommunications organizations, with a particular emphasis on the mediating effect of HR service quality (HRSQ). Research methodology: A questionnaire was developed based on a validated process. Data were collected from 430 employees among the telecommunication companies. However, only 400 questionnaires were valid for the statistical analysis. We use smart PLS and structural equation modeling using Smart PLS v3.2.2 to examine the direct and indirect relationships. Results and findings: The results of this research revealed that E-HRM has a direct, significant, and positive impact on perceived job performance, as well as organizational performance. Moreover, HRSQ significantly mediates the relationships between E-HRM and job and organizational performance. Empirical implications: The research introduces empirical several consequences that are discussed later in this paper. The results highlight the importance of designing and implementing E-HRM systems that support organizational workflow and allow employees to do a variety of tasks more efficiently. Originality: Existing research has shown a link between e-HRM and HR service quality; nonetheless, these studies highlight e-HRM's potential impact on perceived performance, at both the job and organizational performance levels. The study contributes to the HRM literature by identifying how E-HRM might boost perceived performance by improving HR service quality. As a result, the study serves as a foundation for future theoretical developments in this field. [ABSTRACT FROM AUTHOR]

COVID-19 repeated outbreaks in China have significantly impacted residents' lives, particularly in the tourism sector. Accurately assessing the spatio-temporal evolution of tourism flow under the disturbance of COVID-19 is essential for scientific tourism planning and management. This study analyzes the tourism information search index of 296 cities in China to represent tourist flow tendencies and explores the distribution characteristics and formation reasons of tourism flow from both tourist source and destination perspectives. The results are as follows. (1) The COVID-19 has severely affected Chinese tourists' willingness to travel, with a decline of over 50% from 2020 to 2022 compared to 2019. Although a rebound is observed in 2023, it has not yet returned to pre-epidemic levels. (2) COVID-19 has impacted the spatial distribution pattern without altering the essential characteristic of "high in the East and low in the West." The distribution of core tourist sources is "bow-shaped", while that of popular destinations is "U-shaped". (3) In both tourism information inflow and outflow, the number of "head" and "tail" cities is relatively small, with most cities situated in the "middle" echelon. Additionally, the "Matthew effect" has emerged among tourist destination cities, which may aggravate the unbalanced nature of tourism distribution in China. Therefore, future tourism development should be strategically planned, respecting the principles of evolutionary patterns. [ABSTRACT FROM AUTHOR]

In this article, I reexamine the historiography of the economic restratification of western Jewish communities in the modern period (roughly the eighteenth through twentieth centuries). While I acknowledge the possible influence of values and attitudes rooted in Jewish culture and tradition, I express skepticism about their explanatory power across broad historical eras. I emphasize, rather, the cumulative impact of three broad, interrelated social and political currents: the removal of barriers to Jewish economic activity both before and during the age of emancipation; the concentration of Jews in petty commerce on the eve of modernization and their familiarity with the workings of the marketplace; and the revolution of consumption patterns among broad swathes of the population. I argue that historians have not sufficiently recognized the impact of the latter. The diffusion of the ability and the desire to acquire new consumer goods created unprecedented commercial opportunities of which Jews were well-positioned to take advantage. [ABSTRACT FROM AUTHOR]

"J. G. A. Pocock: A Life in Letters" by Quentin Skinner delves into the scholarly career of John Pocock, focusing on his significant contributions to political thought and history. Pocock's correspondence with Skinner reveals his dedication to academic pursuits, despite his formal writing style and conservative leanings. The text also explores Pocock's resistance to technological advancements and his strong connection to his New Zealand roots, highlighting his unique perspective as an outsider in American and European societies. Through his letters, Pocock's warmth, admiration for colleagues, and belief in the importance of the outsider's viewpoint are showcased, providing valuable insights into his life and work. [Extracted from the article]

The paper investigates the resilience of an agriculture supply chain through the lens of complex network perspective. Given the susceptibility of these supply chains to bothrandom events (rainfall and yield uncertainty), and targeted events (income tax raids on millers, strikes, and lockouts), as well as spillover effects of disruptions; we propose a supply chain architecture that helps in achieving a balanced performance against these disruptions. For this, we propose a new attachment rule—'price/cost-based attachment rule', which we use along with degree-based and distance-based attachment rules in generating a resilient supply chain topology. We call the proposed supply chain network—'Balanced Supply Network' whose performance is compared with a scale-free network (BA Network) and a random network (ER Network). The comparison is based on critical performance indicators such as availability (demand and supply availability rate) and connectivity (size of largest all-role connected component). The findings, on expected lines, reveal that our proposed network exhibits a performance trade-off between BA Network and ER Network when subjected to targeted disruptions and disruption propagation scenarios. However, in case of random disruptions, it ensures maximum resilience and even outperforms BA Network due to its construction properties. Further, to optimize resilience, we introduce weights to the attachment rules of our proposed network. These weight assignments enable us to identify the most effective configuration among the three attachment rules for enhancing the network's ability to withstand disruptions. [ABSTRACT FROM AUTHOR]

Turnover in the US early childhood education (ECE) workforce is associated with worse outcomes for children. Greater workplace spirituality, or the perception of meaningful work, sense of community, and alignment with organizational values, is associated with reduced turnover. However, this association has not been examined in ECE professionals. We administered an online survey to 265 ECE professionals in Pennsylvania (US) in the spring of 2021. Respondents were asked about their intention to stay in their current program, if given the option to leave. Workplace spirituality was measured with a 21-item scale assessing the dimensions of meaningful work, sense of community, and alignment with organizational values. The survey was completed by 246 (92.8%), and data were analyzed for 232 respondents. Of these, 94.8% were female, 54.4% were non-Hispanic White, and 70.7% had a bachelor's or graduate degree. The prevalence of intention to stay was 33.2%. After adjusting for all covariates, including gender, age, race/ethnicity, education, job position, workplace stress, and economic hardships, the prevalence (95% confidence interval [CI]) of intention to stay increased across tertiles of workplace spirituality from low to medium to high: 16.4% (7.9%, 24.9%) to 38.6% (28.4%, 48.8%) to 43.7% (32.1%, 55.3%), respectively. ECE professionals who perceived greater workplace spirituality were more likely to report they intended to stay in their current program. Turnover in the ECE workforce could potentially be reduced through efforts to increase a sense of meaning and community at work and to align the values of ECE programs with those who work in them. [ABSTRACT FROM AUTHOR]

In the rapidly evolving landscape of open innovation, understanding the dynamics of learning is pivotal for corporate success. Yet, the constraints and thresholds inherent in the novel technology sourcing processes remain under-explored. We study 163 firms during the third wave of corporate venture capital activity characterized by the primary focus on innovation to investigate the effects of technology sourcing ambidexterity (the simultaneous pursuit of internal and external sources of innovative ideas) on corporate patenting and realized innovation. Acknowledging limitations of organizational learning, our results indicate the presence of the inverted U-shaped relationship between technology sourcing ambidexterity and innovation and suggest that beyond a certain threshold, increases in ambidexterity are detrimental to organizational learning and corporate innovation because boundary conditions to experimentation as a key element to learning arise. Such restrictions are alleviated by organizational slack, which enhances organizational abilities to orchestrate resources and take calculated risks to go beyond existing internal competencies. Plain English Summary: Proponents of open innovation suggest that combining internal and external sources of innovative ideas often leads to success. We demonstrate that this may be true in some circumstances, but there is a learning threshold for organizations. We argue and demonstrate that this combination, known as technological sourcing ambidexterity, is only beneficial up to a certain point, beyond which further investments in the dual internal–external search for innovative ideas are detrimental for reasons that have to do with organizational learning. Moreover, for those same reasons, the benefits are most likely to be observed for firms with substantial organizational slack. Lean organizations that do not have much slack are less likely to gain strategically from investing in technology sourcing ambidexterity. [ABSTRACT FROM AUTHOR]

Organizational learning begins with experience. However, it remains an open question whether firms learn from a particular type of experience: exporting. This study aims to speak into this debate by examining when learning by exporting occurs. Our core thesis is that the timing of learning by exporting depends on a firm's home market economic development. Drawing on classic theories of organizational learning, we posit that firms in more developed home markets will enjoy greater opportunities for learning before exporting whereas firms in less developed home markets will enjoy greater opportunities for learning after exporting. The former will be observed as a divergence in productivity among firms from different home markets, whereas the latter will be observed as convergence over time. The proposed hypotheses were tested and supported using longitudinal data from the World Bank Enterprise Survey. A range of theoretical and practical contributions are discussed. Plain English Summary: When do firms learn by exporting? Analysis of data from the World Bank suggests that the answer depends on a firm's home market. Firms from more developed economies seem to learn before exporting whereas firms from less developed economies seem to learn after exporting. We argue that these differences in learning rates occur because firms in more developed countries are able to access more advanced knowledge and technology domestically in preparation for entering foreign markets whereas firms in less developed countries are only able to access such knowledge by serving foreign markets. The analysis conducted on longitudinal data from the World Bank corroborates our arguments and has important implications for firms and society in general. Importantly, it suggests that exporting may be one avenue through which firms are able to level the playing field in the global competitive landscape. [ABSTRACT FROM AUTHOR]

"Fail fast and learn fast" is a principle commonly advanced to quickly grow and scale startups and SMEs. However, the literature lacks detailed insights into how such learning is organized. The paper aims to investigate how knowledge-intensive SMEs learn from failures through organizational learning processes. To answer this question, we present in-depth case studies of three SMEs that operate in a dynamic context where quick adaption to changes, failures, and learning are natural modes of practice. Our findings present the learning from the failure process, which includes three phases: (1) failure recognition, (2) interactive sensemaking, and (3) organizational adaptation. We condense our insights into a framework disentangling how SMEs succeed and fail and how they can learn from failures through their underlying learning processes. We contribute to prior literature on organizational learning in SMEs by focusing on knowledge-intensive SMEs and practices that enable effective learning from failures. Plain English Summary: The "fail fast and learn fast" mindset provides an opportunity for an organization not only to experiment, make mistakes, and fail but also to learn from this experience and use it for future success. However, research has not yet managed to provide detailed insights into how such learning can best be organized and facilitated. In this article, we investigate how knowledge-intensive SMEs learn from failures through organizational learning processes. We show that SMEs should strive to learn from failure and that this learning can be organized over three phases: failure recognition, interactive sensemaking, and organizational adaptation; each with underlying sub-activities and principles. We contribute to prior literature on organizational learning by focusing on knowledge-intensive SMEs and describing practices that enable effective learning from failure. We also provide insights for managers on how to facilitate rapid learning from failure in their knowledge-intensive SMEs. [ABSTRACT FROM AUTHOR]

This paper investigates the learning patterns of small and medium-sized enterprises (SMEs) from heterogeneous work accidents (i.e., minor and severe and fatal accidents). Work safety cannot be overlooked, and the focus of this study on learning from failure allows to understand how SMEs match safety problems with solutions generated by past experience with work accidents and knowledge acquisition; while acknowledging that accident heterogeneity influences SMEs' learning. The analysis uses a sample of 108 Spanish SMEs during 2006–2009. The results show that SMEs learn to modify safety practices, and that experience with both minor and severe and fatal accidents impact learning outcomes—measured as changes in the unit accident cost—through different mechanisms. Cumulative experience with past work accidents supports exploitative learning, but this effect was found only for minor accidents. Although the adoption of safety-enhancing tools (i.e., OHSAS 18001) does not affect learning, the findings reveal the value of ambidextrous learning: SMEs adopting the OHSAS 18001 learn more from severe and fatal accidents than from minor accidents by triggering drastic modifications in their safety practices. Plain English Summary: Work safety cannot be overlooked, and the study shows that SMEs learn from minor and severe and fatal work accidents through different mechanisms. Understanding how SMEs learn from failure opens a window of opportunity for optimizing their processes and performance. The study found that SMEs' learning ability depends on the characteristics of work accidents. Frequently occurring minor accidents are a valuable source of experiential learning that allows SMEs to introduce corrective actions that reduce the unit accident cost. By contrast, for SMEs to learn from severe and fatal work accidents, a different path was found. Severe and fatal work accidents are rare and require unique solutions, and reductions in the unit accident cost can be achieved through ambidextrous learning resulting from exploiting past experience from this type of accident with the changes in safety practices that follow the adoption of the OHSAS 18001. The study offers practical implications for SMEs on how to capitalize on different sources of knowledge to mitigate work accidents. [ABSTRACT FROM AUTHOR]

The relationship between top management team (TMT) members' learning behavior and the innovation strategy of technology ventures remains unclear, especially when complicated by social hierarchies within the team. We draw on organizational learning theory to theorize that diversity in TMT members' learning behavior has both positive and negative latent effects that produce an inverted U-shaped relationship between TMT learning diversity and a firm's radical innovation strategy. Building on the social hierarchy literature, we also suggest that CEO power moderates this relationship by altering the latent forces: structurally powerful CEOs neutralize the benefits of TMT learning diversity, turning the link between learning diversity and radical innovation strategy predominantly negative, whereas prestigiously powerful CEOs neutralize the costs of TMT learning diversity, turning its relationship with the firm's radical innovation strategy predominantly positive. Longitudinal, multi-source data from 77 TMTs support our model. The findings contribute to the research on learning and social hierarchies by illustrating how hierarchies rooted in different sources of power have different effects on the relationship between TMT learning diversity and innovation strategy. Plain English Summary: How can teams benefit from diversity? Two CEO approaches to power determine whether and when differences in learning behavior make SME top management teams more innovative. Top management teams (TMT) try to harness the power of diversity by combining team members who prioritize learning and constantly try to explore new areas with others who focus on implementing existing insights. This study investigates the effects of learning diversity in TMT on a firm's innovation strategy in the context of technology ventures. First, we found that a moderate level of diversity in learning behavior is linked to more radical innovations but that too much diversity hurts firm innovativeness. Moreover, we show that the power that CEOs wield plays a central role in these processes: if CEOs are prestigiously powerful (i.e., when they hold many other board appointments), they can guide their teams in ways that allow them to benefit from learning diversity. However, if CEOs are structurally powerful (i.e., they are also chairperson of the own board), their TMT will struggle to harness the power of diversity and end up seeing less radical innovation in their firm. These findings contribute to research by offering a novel theoretical account of diversity in learning behavior. Our study has implications for the design of TMTs, in the context where these teams' impact on firm innovation strategy is substantial. [ABSTRACT FROM AUTHOR]

Despite the valuable contributions of earlier learning studies, the specific analysis of how entrepreneurs and small- and medium-sized enterprises (SMEs) learn has been sidelined in the literature. Significant research opportunities remain open in various unexplored realms. By adopting a multidisciplinary perspective that combines a variety of frameworks (i.e., organizational, economic, and innovation management), the collection of 11 studies of this special issue dedicated to learning delivers valuable insights into how entrepreneurs and SMEs capitalize on learning processes, while identifying how these processes are affected by the type of experience (i.e., success and failure). This paper first overviews the contributions of the 11 papers included in the special issue. Next, we discuss a number of yet unresolved topics that deserve academic attention, paying special attention to entrepreneurs' direct and indirect experiences, knowledge obsolescence caused by technology upgrading, and the role of digital technologies—i.e., Internet-of-things and artificial intelligence—in the learning processes. Plain English Summary: From the literature on learning, which has mostly evaluated organizational learning, an evident gap emerges, that of the analysis of how entrepreneurs and SMEs learn from different types of experiences. The 11 studies included in this special issue bring together research that addresses various aspects related to learning from the entrepreneur and SME levels. This special issue advances our knowledge by providing clear nuances of how both entrepreneurs and SMEs can learn and generate different benefits from both successful and failure experiences. After examining the papers in this special issue, promising future research should focus on the analysis of entrepreneurs' direct and indirect experience, knowledge obsolescence caused by technology upgrading, and the role of Internet-of-things (IoT) and artificial intelligence (AI) in enabling learning processes. [ABSTRACT FROM AUTHOR]

This paper analyzes the relationship between capitalized Research and Development (R&D) expenditures under IFRS and innovation performance measured by patent data. Under IFRS, development expenditures are capitalized when the success of an R&D investment is highly likely. Hence, such capitalization could be a leading indicator for future innovation performance. We analyze this question based on a hand-collected sample of R&D capitalization data under IFRS and patent data from the European Patent Office's Worldwide Patent Statistical Database. We find that the capitalization rate of R&D is positively related to future patent applications and citations as measures of future innovation performance. We also find a positive association with measures of future financial performance. The results imply that the rate of R&D capitalization is informative and can be considered a leading indicator for future innovation performance. [ABSTRACT FROM AUTHOR]

This study investigates the impact of conservative financial reporting on corporate diversification, in order to explore whether accounting policy plays a role in mitigating agency problems associated with corporate decisions. Based on a sample of U.S. publicly listed firms in the period 2000–2017, this study initially reveals that diversification has an adverse effect on firm value. Our findings indicate that the increase in accounting conservatism leads to a subsequent reduction in the degree of corporate diversification. Additionally, the increase in accounting conservatism helps enhance the excess value attributed to diversification, suggesting that conservatism can alleviate the detrimental influence of diversification on firm value. Our results further indicate that the effect of accounting conservatism is more pronounced for firms with higher information asymmetry or poor corporate governance structure. Overall, the findings suggest that conservative accounting plays an effective monitoring role in disciplining management's corporate strategies of diversification, and therefore, benefits shareholders and capital markets. [ABSTRACT FROM AUTHOR]

This research examines how option trading activity reduces information asymmetry through the CEO's and ordinary employee's awareness of firm value and their pay related to firm performance. Our findings demonstrate that companies with more options trading activity have a higher CEO-employee pay ratio, which is consistent with the tournament theory. Option trading illustrates that both CEOs and employees understand their relevant payment based on the precise firm value. This advantage of option trading becomes weak for firms with higher profitability, for employees with more bargaining power, and for CEOs with a higher risk incentive. [ABSTRACT FROM AUTHOR]

It is a stylized fact that trading activity, volatility and liquidity in equity and other financial markets follow specific intraday patterns. These patterns are to a large extent determined by institutional features such as exchange trading hours or batch settlement procedures. We analyze the intraday patterns that emerge when these institutional constraints are absent. We compile a large sample of 1940 currency pairs traded on 38 cryptocurrency exchanges located on five continents. These exchanges operate 24 h a day, seven days a week, and settle trades instantly. We find that there are pronounced time-of-day patterns in trading activity, volatility and liquidity. These patterns are remarkably similar across exchanges, time zones and cryptocurrency pairs. Specifically, trading activity, volatility and illiquidity all peak between 16:00 and 17:00 Coordinated Universal Time (UTC), i.e. during U.K. tea time. We find that characteristics of the exchanges (such as their locations) and of the traded currency pairs (e.g. whether two pairs share a common currency) explain some, but not all of the commonality in intraday patterns. [ABSTRACT FROM AUTHOR]

In this paper, utilizing the Chinese context, we investigate whether and how the regional gambling culture affects bond risk premiums. Using a lottery-based measure of the local gambling culture, our empirical results show that this culture significantly increases the risk premium of local bonds via an increase in corporate risk preferences, including operating, investment and internal control risks. Our findings are robust to various sensitivity tests, including gambling crime measures of the gambling culture and endogeneity tests. In addition, we find that regional crackdowns on gambling, legal environment and corporate information quality effectively all restrain the bond risk premium caused by the local gambling culture. Finally, we find that only the investor-pay credit rating can identify the bond investment risk caused by the local gambling culture, while bonds issued by firms located in high gambling areas are more prone to default. [ABSTRACT FROM AUTHOR]

Prior literature documents a positive (negative) relation between past (future) stock returns and both external financing and capital expenditures. In this study, we examine whether managers' financing and capital expenditure decisions are associated with firm-level investor favoritism (neglect) and, therefore, whether managers exploit investor mispricing by issuing more (less) capital and investing more (less) in capital expenditures when firm-level investor sentiment is high (low), which leads to more negative future stock returns. We employ both a stock's extreme return momentum and extreme trading volume to capture firm-level investor favoritism (neglect), which reflects firm-level investor overpricing (underpricing) due to investor sentiment. We find that both external financing and capital expenditure decisions are positively (negatively) associated with favoritism (neglect) and that the previously documented negative association between future stock returns and external financing is more pronounced in periods of favoritism. However, we find no association between future stock returns and capital expenditures after controlling for external financing. These findings suggest that managers' financing and capital expenditure decisions are associated with firm-level investor favoritism/neglect, and that managers exploit investor mispricing in making financing decisions, resulting in lower future stock returns. [ABSTRACT FROM AUTHOR]

We investigate return spillover effects and depict a connectedness network among U.S. and Asian stock markets, comparing the spillovers during three crisis sub-periods and the entire period. Our findings are summarized as follows: First, regarding a puzzle in Choi (Econ Anal Policy 73:179-193, 2022) we find that total and net-pairwise spillover index during the global financial crisis (GFC) period are greater than those during COVID-19 pandemic period for stock markets studied, with the exception of Hong Kong which shows contrary results. Second, particularly, we decompose total spillover into two directional spillovers. The directional spillover from U.S. to Asian markets is greater during GFC period than that during COVID-19 period, whereas the directional spillover from Asian markets to U.S. display the contrary results. Third, different from S&P500 used by the literature, we use DJIA index to obtain the results conformable with the studies showing that U.S. is the strongest contributor and net transmitter of shocks to 9 Asian markets. Finally, analogous to findings in the literature, spillover indices across stock markets intensify during crisis periods. Our findings provide practical implications that understanding spillover effects among U.S. and Asian markets can help investors and portfolio managers to execute diversification strategy. [ABSTRACT FROM AUTHOR]

Asset and debt management are two essential managerial tasks in any firm. The traditional view holds that asset management is the primary driver of real estate investment trust (REIT) returns for the following reasons: (1) interest tax shields are not a source of incremental value for REITs and (2) the plain tangibility of real estate assets helps to diminish the financial distress costs of REITs. This paper examines empirically whether debt management also matters for the operating returns (i.e., ROA, ROE, ΔROA or ΔROE) of a portfolio of REITs. Both applying a novel dynamic decomposition method to ΔROA or ΔROE and also defining ROA and ROE under the net income and the funds from operations metrics guide the empirical approach of this paper. Our findings show that the effects of debt management on REITs' operating profitability cannot be ruled out. However, the direction of these effects appears to be opposite to that of asset management. These results call for renewed and further investigations into the optimal capital structure questions for REITs. [ABSTRACT FROM AUTHOR]

The high-risk decision environment and information asymmetries associated with investing in early-stage startups in pitch competitions make angel investors prone to biased decision-making. Drawing from social perception theory, this study examines how angel investors' decisions are influenced by observed personal characteristics of entrepreneurial teams, based on representative stereotypes. Analyzing a dataset of N = 553 startup pitches from the German televised competition Die Höhle der Löwen, this study reveals that the likelihood of securing deals with German angel investors and the resulting business valuations are linked to certain superficial team characteristics. Specifically, the age, diverse ethnicity, and physical attractiveness of the entrepreneurial team have a significant positive effect on deal probabilities. Moreover, angel investors offer lower deal valuations to teams of older and female entrepreneurs, suggesting the presence of a systematic bias. These insights contribute to understanding the role of stereotypes in entrepreneurial finance and address the challenges related to bias in access to capital for early-stage startups in Germany. [ABSTRACT FROM AUTHOR]

This paper explores the impact of green credit policy on the green innovation of heavily polluting enterprises by taking the implementation of the "Green Credit Guidelines" in 2012 in China as an exogenous shock. Using the sample of industrial enterprises from the Chinese Industrial Enterprises Database, our empirical results show that, after 2012, the quantity of green innovation represented by the number of green utility model patents and green invention patents is significantly reduced in heavily polluting enterprises. The quality of green innovation represented by the knowledge complexity of green patents increases significantly. The conclusions are valid in a series of robustness tests. The implementation of green credit policy strengthens both the internal financial constraints and the external financial constraints of heavily polluting enterprises. Mediating effect tests reveal that the strengthened internal financial constraints hinder green innovation, while the strengthened external financial constraints promote the knowledge complexity of green patents. There are also firm-level and region-level heterogeneities. The negative effect of green credit policy does not differ between the listed enterprises and non-listed enterprises. It is greater on the green invention patents of the non-state-owned firms. The green innovation of the foreign-owned enterprises declines in all aspects: green utility model patents, green invention patents, and knowledge complexity. Regional intellectual property protection can only significantly mitigate the negative effect on the green utility model patents. [ABSTRACT FROM AUTHOR]

The extent to which firms can emerge as green innovators driving the eco-friendly transformation of an economy largely hinges on the efficacy of government policies in incentivizing firms to innovate in a sustainable manner. Based on the data of 825 listed firms in China, this study surveys how environmental subsidies affect green innovations for the firms and examines the moderating effect of these subsidies on firm scale expansion and green innovations. It is found that environmental subsidies significantly stimulate green innovation, and substantial green innovations and green management innovations contribute to the firms' expansion through the innovation effect. Second, environmental regulation positively moderates the relationship between environmental subsidies and both substantive and strategic green innovation. Chief executive officer green background positively moderates the relationship between environmental subsidies and different types of green innovations. Third, firms with environmental subsidies are more likely to opt for a "quality-focused" green innovation strategy. The conclusions provide policy recommendations aimed at improving the effectiveness of subsidy policies as well as accelerating the firm's green transition. [ABSTRACT FROM AUTHOR]

The development of the digital economy provides crucial support and impetus for enhancing green innovation efficiency. This connection between the digital economy and green innovation manifests in many dimensions. While within the research on the pathways through which the digital economy influences green innovation, the sequential order of these transmission pathways is of paramount importance. This bears significant implications for optimizing resource allocation, enhancing the efficiency of green innovation, and providing guidance for government policy formulation. This study utilizes data from 30 provinces in China from 2012 to 2021 and employs the SBM-DDF model considering undesired output to estimate green innovation efficiency. Furthermore, a multiple mediation model is constructed from three levels: macro-environment, industrial structure, and micro-enterprises, in order to investigate the transmission mechanism of the impact of the digital economy on green innovation efficiency. The research findings indicate that the rapid development of the digital economy significantly improves the regional green innovation efficiency, and this conclusion remains valid after conducting robustness tests. Additionally, there is a lagging effect in the enhancement of green innovation efficiency from the digital economy. The digital business environment, coordination of industrial structure, and level of enterprise digital transformation play significant mediating and moderating roles in the relationship between the digital economy and regional green innovation efficiency. In the chain mediation effect model, the impact of the digital economy on green innovation efficiency follows a "bottom-up" transmission process, while the 3-Layer chain mediation effect of the digital economy on green innovation efficiency is almost negligible. [ABSTRACT FROM AUTHOR]

Stock price prediction plays an important role in financial decision-making, enabling investors and analysts to make informed choices regarding trading and investment strategies. Traditional statistical methods have been utilized for the prediction of stock price, but it is often difficult for them to capture complex patterns, adapt to changing market conditions, handle large datasets, and automatically extract relevant features. Recent advancements in machine learning and deep learning offer promising solutions to address these challenges. In this paper, we propose a new approach to enhance the stock price prediction by leveraging generative adversarial networks (GANs) and transformer-based attention mechanisms. GANs are utilized to generate synthetic stock price data, and incorporating market sentiment and volatility. Attention mechanisms will selectively concentrate on the important features and patterns in the data, which may do good to the identification of key market indicators which will impact stock prices. By integrating market social media news which can tell about the sentiment and volatility, our model aims to improve the accuracy and robustness of stock price forecasts. We also address the limitations of GANs and attention mechanisms separately used in stock price prediction, such as unrealistic data generation and overfitting, by employing regularization techniques and incorporating additional data sources. Experimental evaluations using real-world stock market data will be conducted to compare the performance of our proposed models with conventional approaches. The findings of this research have implications for investors, financial analysts, and other stakeholders who are engaged in the stock market ecosystem, providing valuable insights for the investment strategies. [ABSTRACT FROM AUTHOR]

We investigate the role of local amenities in shaping compensating wage differentials in labor market populated by high-skilled workers. Using 10 years of longitudinal data on workers productivity along with information on firms and location amenities, we evaluate whether workers are willing to pay to join a better firm and if firms with undesirable attributes must provide higher wages to attract workers. By accounting for unobserved workers heterogeneity, we show that superstars receive positive wage differentials for lower location amenities as well as riskier employments. [ABSTRACT FROM AUTHOR]

To meet the shifting needs and preferences of the contemporary sales workforce, sales organizations are deploying idiosyncratic deals (I-deals), or mutually beneficial individualized workplace arrangements between salespeople and the organization. However, research is lacking on how, and under what conditions, I-deals facilitate work engagement and performance among salespeople. In this study, based on analysis of data gathered from 221 business-to-business salespeople, we demonstrate that I-deals are positively related to two foci of salesperson work engagement (i.e., social engagement and change engagement) and salesperson performance. Furthermore, we find that ethical self-leadership, which is driven by ethical leadership, functions as an internal self-governance mechanism that strengthens the impact of I-deals on salesperson work engagement. Based on these results, we delineate novel theoretical and practical implications on the role of I-deals in facilitating effective sales talent management. [ABSTRACT FROM AUTHOR]

We examine the impact of corporate culture on environmental performance using a sample of 7199 firm-year observations over the period of 2002–2018. We find that stronger corporate culture improves environmental performance, measured by the amount of toxic chemical release (TCR). Our result is both statistically and economically significant. We also show that cultural norms of innovation, quality and teamwork as well as a technology-oriented corporate culture have a greater impact on enhancing environmental performance. Further analyses show that managerial competence and strong institutional ownership moderate the relationship between corporate culture and environmental performance. We introduce the decomposition of expected and unexpected components of TCR and document that firms with a strong corporate culture implement strategies to reduce the unexpected component of TCR in addition to the expected component of TCR. Finally, we document that strong corporate culture and environmental performance improve firms' financial performance. Our results are robust to several sensitivity tests and procedures to mitigate endogeneity and self-selection problems. From a practical point of view, our findings suggest that a firm's culture can determine its environmental sustainability and ethical practices. [ABSTRACT FROM AUTHOR]

Extant literature has documented mixed findings concerning the relationship between abusive supervision and employee performance. While most studies show a negative relationship, others reveal that abusive supervision can be motivating and performance-enhancing, and still others find no effect. To advance our understanding of this relationship, the present study examines employees' objective and quantifiable key performance indicators (KPIs) as an outcome, while investigating employment contract type as a critical boundary condition. This study also explores an alternative outcome of abusive supervision by examining whether its effects extend to employees' behavior towards customers, specifically in the form of customer-directed sabotage. A two-wave multi-source field study was conducted with 1,331 customer service representatives from 139 call-center teams. Findings suggest an alarming phenomenon: for probationary employees, an inverted U-shaped relationship exists between abusive supervision and employees' KPIs, such that low to moderate levels of abusive supervision increase, but moderate to high levels of abusive supervision decrease, their job performance. For permanent employees, KPIs are less affected by abusive supervision. However, abusive supervision is positively related to employees' customer-directed sabotage behavior, and this effect is stronger for permanent (vs. probationary) employees. The theoretical and practical implications of the findings for leadership and business ethics are discussed. [ABSTRACT FROM AUTHOR]

This study examines the influence of AI-powered and emerging technologies on pedagogical practices in higher education, focusing on their role on behavioural intention (BI) and actual usage among educators and students. The research hypothesises that the relationship between each Unified Theory of Acceptance and Use of Technology (UTAUT) constructs - Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), and Facilitating Conditions (FC) - and BI to use AI is mediated by Attitude towards AI. Additionally, it explores the mediation of the relationship between Technological, Organisational, and Environmental (TOE) framework and BI to use AI by Attitude towards AI. Furthermore, it hypothesises that the relationship between UTAUT constructs, and the actual Usage of AI is mediated by BI. Data were collected from 115 respondents through a survey measuring perceptions of UTAUT and technology-organisation-Environment (TOE) constructs. Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed to analyse the data, alongside PLS-Multi-Group Analysis (PLS-MGA) to explore gender differences. The key results indicated that PE and EE significantly influenced Attitude towards AI (F = 14.861 and F = 33.887, respectively), which in turn significantly influenced BI (β = 0.468, t = 5.106). However, SI had an insignificant effect (F = 0.346), and FC had a minimal influence (F = 2.225). The study found that Organisational Context played a significant role in shaping Attitude towards AI, influencing BI, whereas the direct influence of TOE on BI was not significant (F = 1.356), indicating full mediation by Attitude. Additionally, higher BI did not necessarily translate to increased AI usage (β = -0.381, t = 4.749), suggesting external barriers or moderating factors. These findings provide valuable insights for developing strategies to enhance AI-driven pedagogical innovations, emphasising the importance of fostering positive attitudes and addressing practical challenges in AI adoption. [ABSTRACT FROM AUTHOR]

This paper uses multivariate Hawkes processes to model the transactions behavior of the US stock market as measured by the 30 Dow Jones Industrial Average individual stocks before, during and after the 36-min May 6, 2010, Flash Crash. The basis for our analysis is the excitation matrix, which describes a complex network of interactions among the stocks. Using high-frequency transactions data, we find strong evidence of self- and asymmetrically cross-induced contagion and the presence of fragmented trading venues. Our findings have implications for stock trading and corresponding risk management strategies as well as stock market microstructure design. [ABSTRACT FROM AUTHOR]

This paper investigates the influence of community characteristics (community leaders' enthusiasm and community members' offline activities) on destination brand equity (destination brand image and destination brand awareness) by considering value co-creation in virtual tourism communities. By obtaining 344 usable questionnaires, it was possible to perform structural equation modeling to test hypotheses. This study finds that virtual tourism community leaders' enthusiasm and community members' offline activities have positive influences on community members' value co-creation behavior, which consequently impacts destination brand image and destination brand awareness. Furthermore, community members' value co-creation behavior partially mediates the influence of community leaders' enthusiasm on destination brand image and destination brand awareness. This study contributes by offering new evidence for destination brand equity antecedents, enriching virtual tourism community literature, and guiding community leaders in fostering positive member behavior, while providing valuable insights for local brand managers and destination management organizations in tourism planning and policy formulation. [ABSTRACT FROM AUTHOR]

In recent years, "gazelles"—a small set of high-growth firms—have attracted considerable interest from researchers for their capacity to contribute significantly to the competitiveness of nations. However, in management literature, the research on this topic is still incomplete, and a broad but focused review is needed to understand the phenomenon fully. Therefore, the paper aims to analyse in depth the literature on "gazelles" published in the Business, Management, and Accounting and Decision Sciences fields, shedding light on opportunities arising from emerging research topics related to the phenomenon. In meeting this aim, the work is built on a systematic literature review, and Elsevier's Scopus database was selected and scanned to access publications. The analysis identifies in the sample under investigation the quantitative characteristics (temporal distribution of publications, journals included in the sample, and methodological approach adopted by authors), as well as seven main topics resulting from the qualitative coding process (performance, policy and employment, innovation, entrepreneurship, corporate governance and decision-making, human resources, and strategy). Finally, a comprehensive outlook and a critical analysis of the state-of-the-art research on these specific high-growth firms have been provided through the proposal of a conceptual framework. This study also proposes a research agenda for scholars while providing insightful suggestions from a practical point of view. [ABSTRACT FROM AUTHOR]

The objective of this study is to examine the relationships between market orientation, organizational culture, proactive management, organizational climate, and organizational structure on the innovative orientation (exploitative and exploratory innovation). Little research has been conducted to examine the relationship between these organizational dimensions and innovation orientation. This study offers this and provides a particular type of companies (agribusiness) and context (Extremadura, Spain). Quantitative approach, by using structural modelling equations, to analyze data from 151 innovative agri-food firms was used in this study. Then, using a fuzzy set qualitative comparative analysis (fsQCA), was carried out to obtain additional insights. The main result find that market orientation plays a key role both in exploitative and exploratory innovation in agribusiness firms. Innovation exploitation is influenced by the firm's organic structure. Results from fsQCA provide valuable findings showing that innovation exploitation and exploration result from distinct organizational configurations, thus providing valuable insights for decision and policy-making. [ABSTRACT FROM AUTHOR]

Current methodologies for finding portfolio rules under the Merton framework employ hard-to-implement numerical techniques. This work presents a methodology that can derive an allocation à la Merton in a spreadsheet, under an incomplete market with a time-varying dividend yield and long-only constraints. The first step of the method uses the martingale approach to obtain a portfolio rule in a complete artificial market. The second step derives a closed-form optimal solution satisfying the long-only constraints, from the unconstrained solution of the first step. This is done by determining closed-form Lagrangian dual processes satisfying the primal-dual optimality conditions between the true and artificial markets. The last step estimates the parameters defined in the artificial market, to then obtain analytical approximations for the hedging demand component within the optimal portfolio rule of the previous step. The methodology is tested with real market data from 16 US stocks from the Dow Jones. The results show that the proposed solution delivers higher financial wealth than the myopic solution, which does not consider the time-varying nature of the dividend yield. The sensitivity analysis carried out on the closed-form solution reveals that the difference with respect to the myopic solution increases when the price of the risky asset is more sensitive to the dividend yield, and when the dividend yield presents a higher probability of diverging from the current yield. The proposed solution also outperforms a known Merton-type solution that derives the Lagrangian dual processes in another way. [ABSTRACT FROM AUTHOR]

This paper investigates the implied barrier option characteristics of controlling shareholders' equity pledge loans and establishes a pricing model for the equity pledge rate that simultaneously considers the down-and-in put implied barrier option and the dividend policy. Meanwhile, the pricing model is used to empirically calculate the equity pledge rates of A-share listed companies in China from the viewpoint of application. The findings are as follows. (i) The probability of the pledged stock price falling below the closing line increases monotonically about the equity pledge rate, and the probability of the stock price falling below the closing line is higher under a fixed dividend policy than the corresponding probability under a fixed dividend yield policy. (ii) The equity pledge rate has an inverse relationship with the loan maturity and volatility. (iii) The equity pledge rate on controlling shareholders' equity pledges varies in the same direction as the loan interest rate. (iv) The relationship between the change in the equity pledge rate level and the fixed dividend is affected by the merits of the firm's performance. The equity pledge rate level has an inverse variation relationship with the fixed dividend yield. [ABSTRACT FROM AUTHOR]

In today's economic landscape, with its increasingly brief economic cycles and ever-changing market conditions, forecasting has become more critical than ever. In the specific case of small and medium-sized enterprises (SMEs), a crucial aspect is to anticipate the state of bankruptcy due to the low life expectancy of this type of company. A requirement that has been recommended by several international organizations such as the European Union, especially because SMEs contribute significantly to job creation and added value and to overcoming the effects of economic crises. Despite the progress in this field, there are economies that have been little or poorly addressed by the literature. This is the case for Spain, an economy where SMEs account for a significant share of its business landscape. To close this gap, this paper addressed the problem of predicting the insolvency of Spanish SMEs from a Machine Learning perspective. Leveraging a dataset encompassing financial and non-financial data from 58,267 Spanish SMEs spanning the period 2009–2020, we adjusted several decision tree models to address two scenarios of practical value in the Spanish context. Additionally, we conducted a thorough analysis of the most influential predictors of insolvency from a financial perspective. To empower Spanish SMEs, we provided them with a free software tool implementing the best models for the considered scenarios. The tool is intended to serve as an additional means to proactively and early assess solvency status. [ABSTRACT FROM AUTHOR]

Private equity (PE) represents the acquisition of stakes in non-listed companies, often long-term, with the objective of improving the performance and value of the company to obtain significant benefits at time of disinvestment. PE has gained particular importance in the global financial system for delivering superior risk-adjusted returns. Knowing the PE return drivers has been of great interest among researchers and academics, and some studies have developed statistical models to determine PE return drivers. Still, the explanatory capacity of these models has certain limitations related to their precision levels and exclusive focus on groups of countries located in Europe and the EE.UU. Therefore, in the current literature, new models of analysis of the PE return drivers are demanded to provide a better fit in worldwide scenarios. This study contributes to the accuracy of the models that identify the PE return drivers using computational methods and a sample of 1606 PE funds with a geographical focus on the world's five regions. The results have provided a unique set of PE return drivers with a precision level above 86%. The conclusions obtained present important theoretical and practical implications, expanding knowledge about PE and financial forecasting from a global perspective. [ABSTRACT FROM AUTHOR]

The strategic management of supply chains, by ensuring closed-loop manufacturing processes and a constant reduction of industrial waste, is an essential pillar of sustainability. This is the pattern behind the, so-called, circular supply chains. The effective adoption of this paradigm demands the supply chains actors to establish robust integration and relationships, so that waste and by‐products of an industry or industrial process become the raw materials for others. This circular network is defined as industrial symbiosis. Starting from a background on this topic, this working paper explores the potential of blockchain as enabling technology of Industry 4.0 to disseminate industrial symbiosis practices within the modern industrial scenario. A preliminary two-step framework, i.e., conceptual and operative, is presented including insights and win–win synergies showing the potential of blockchain technology in supporting informative flows of industrial symbiosis. Preliminary field experiences are suggested, along with existing limitations and perspectives on future research. [ABSTRACT FROM AUTHOR]

This study empirically tests the Eisenegger and Imhof reputation risk theory to provide new insights into a robust conceptualization and measurement of corporate reputation risk (CRRisk) as well as its relationship with firm value (FV). We further investigate whether enterprise risk management quality (ERMQ) matters for the CRRisk-FV nexus. Using panel data of listed non-financial firms from sub-Saharan Africa from 2014 to 2020, analyzed using the least square dummy variable (LSDV) estimator, we provide empirical evidence that CRRisk diminishes FV. Also, we find considerable evidence that ERMQ attenuates CRRisk towards FV. We also provide evidence that high-quality ERM is contingent on firm size, profitability, environmental uncertainty, and corporate risk-taking. Our findings are robust to channel and regional analyses, dimensions of CRRisk, and endogeneity using the GMM estimator. Our findings remind shareholders and regulators to intensify pressure on firms to increase their investment in high-quality ERM systems to signal a commitment to sound risk governance, curbing managerial opportunism, and monitoring decisions detrimental to firms' reputations and value. [ABSTRACT FROM AUTHOR]

As remote and flexible work becomes increasingly prevalent, the importance of building bonds among coworkers is emphasized. Beyond health considerations, the role of company community sports (CCS) in fostering integration at the group and organizational levels remains unclear, especially for underrepresented employees. This study investigates the impact of CCS participation on employees' internal group and external organizational integration using data from 12 organizations (N = 2018; Age = 30.8 ± 8.4 years; Female = 47.6%). Social integration was measured through workplace trust, organizational identification, and coworker interaction. The organizational settings and participation quality of CCS were examined to analyze their effect on integration. The results indicate that frequent and high-quality participation in CCS significantly enhances both internal group integration and external organizational integration, while CCS professionalism and intense competition have very little effect on the overall effects. However, female employees experienced lower integration levels, highlighting the need for inclusive CCS initiatives. CCS activities should cater to the diverse interests and capabilities of all employees to promote greater participation and ensure inclusivity for underrepresented groups. [ABSTRACT FROM AUTHOR]

Stock investment is an economic activity characterized by high risks and high returns. Therefore, the prediction of stock prices or fluctuations is of great importance to investors. Stock price prediction is a challenging task due to the nonlinearity and high volatility of stock time series. Existing deep learning models may not capture the periodic and non-periodic features of stock data effectively. In this paper, we propose a novel model that leverages Complete Ensemble Empirical Mode Decomposition (CEEMD), Time2Vec, and Transformer to better capture and utilize various patterns in stock data for enhanced prediction performance, and we call it ETT. CEEMD decomposes the stock data into different frequency components based on their intrinsic scales. Time2Vec provides a time vector representation that captures both periodic and non-periodic patterns while being invariant to time scaling. Transformer learns the long-term dependencies and global information from the data. We apply ETT to predict stock prices in the Chinese A-share market and compare it with several baseline models. The results show that ETT reduces the mean squared error (MSE) by an average of 4% and increases the average cumulative return by 58% on the CSI 100 and Hushen 300 datasets. [ABSTRACT FROM AUTHOR]

Sustainable development has elevated the role of green entrepreneurship, notably in China's electric vehicle (EV) components sector, which presents vast opportunities for SMEs. While studies have explored the success and failure of Green Entrepreneurial Intention, factors influencing it remain under-researched, particularly from the perspective of individual intentions. Existing research primarily focuses on policies, regulations, and macro-environments affecting green business models, with limited attention to influence entrepreneurial and sustainable initiatives. This study aims to bridge this gap by examining the impact of Perceived Attitude, Perceived Behavioural Control, Subjective Norms, and Organizational Commitment on Green Entrepreneurship Intention, using Openness to Experience as a moderating factor. Data were collected through a cross-sectional survey from 383 SMEs in China, employing a simple random sampling technique. PLS-SEM regression analysis was used to test the hypotheses, guided by the Theory of Planned Behaviour (TPB) and Organizational Commitment (OC) theory. The findings revealed that Perceived Attitude significantly and positively influences green entrepreneurship intentions. Highly integrative subjective norms were also positively correlated with green entrepreneurship intentions. Furthermore, Perceived Behavioural Control and Organizational Commitment facilitated green entrepreneurship intentions. Openness to Experience emerged as a strong moderator in the relationships between Perceived Attitude and Subjective Norms with Green Entrepreneurship Intention. This study contributes to the existing knowledge base by highlighting the gaps and inconsistencies in the literature regarding TPB and OC factors influencing green entrepreneurship intention. The results have theoretical and managerial implications, emphasizing the importance of fostering green entrepreneurship. [ABSTRACT FROM AUTHOR]

As PhD programmes across disciplines face many questions about return on investment and the many challenges in pursuing the degree, popular discourse surrounding leaving academia has included questions of whether PhD holders regret their PhD. Using a heterogenous choice model, this study shows that despite the many detractors, those who do complete the degree largely affirm their decision. But when examining personal and employment factors including sociodemographics, field of study, job sector, and level of relatedness between the PhD field and field of work, we found that when controlling for how well the PhD prepared individuals for their current employment, background and employment characteristics predicted higher levels of affirmation of the PhD decision in three phases: 1) in general, 2) in the same field, and 3) at the same institution. In particular, this paper found that students of colour were more likely to affirm their decisions perhaps indicating the importance of the credential to the individual but also to the importance individuals place in realizing structural diversity among advanced degree holders across disciplines. These findings illustrate the importance of efforts to improve climate in PhD programmes as well as expanding pathways into careers across sectors. [ABSTRACT FROM AUTHOR]

This study explores the trade relations between Florence and the Ottoman Empire during the reign of Mehmed II the Conqueror (1451–1481). Drawing on various sources, including documents of the Florentine Commune, The Chronicle of Benedetto Dei, travelogues of Western travelers, and accounting records, the study examines both the interactions between Mehmed II and the Medici family and the broader trade relations between the two powers. An analysis of period documents reveals the existence of active political and commercial ties, which intensified during the rule of Lorenzo the Magnificent (1469–1492). Within the context of these trade relations, Florence’s role in the Levant becomes evident, as the city pursued an independent policy aimed at maximizing political and economic advantages from its favorable relations with the Ottoman sultan. This policy occasionally diverged from the plans of other Western states to organize a crusade against the Ottomans. [ABSTRACT FROM AUTHOR]

This article examines the status of foreigners in Bulgarian territories during the late Middle Ages, focusing particularly on the existence and nature of a capitulation regime. The study traces all relevant documents regulating relations with key trading centers such as Dubrovnik (Ragusa), Venice, Brașov, and Genoa. Through these sources, the article analyzes the legal frameworks and practical implications of foreign presence and commerce in the region. [ABSTRACT FROM AUTHOR]

This article explores conflict transportation among people with a Somali background in Finland by focusing on how it is felt every day. By focusing on affect, the article highlights the contradictive and differentiated dynamics at play in conflict transportation and how it is located and navigated in everyday practices. The findings show how conflict transportation is simultaneously reinforced and resisted as well as how it is a non-static, fluid phenomenon that is experienced day-to-day life as well as tied deeply to belonging. The article argues that an affective approach to conflict transportation helps undo essentialising notions of diasporic spaces and calls for research on diasporas and conflict that is also located outside of politically mobilised diasporic spaces. [ABSTRACT FROM AUTHOR]

Background: In the healthcare sector, the quality of medical services largely depends on the work of medical staff. Improving employee performance can impact the efficiency and productivity of a healthcare entity. Therefore, proper talent management practices are needed to achieve good outcomes. It is also worth answering what other factors affect this performance. The aim of the study was to investigate the impact of talent management practices and other factors on employee performance in the public healthcare sector. Methods: Data was collected using a questionnaire method with a Likert scale. The study population consisted of 558 employees in the public Polish healthcare sector. The research instrument's structure, reliability, and validity were assessed using exploratory and confirmatory factor analysis. Descriptive analysis was used to analyze the structure of respondents, and a covariance-based structural equation modelling (CB-SEM) was used to test the model and verify hypotheses. Survey data were analyzed using SPSS v8 and AMOS v. 29 (Predictive Solution Poland). Results: In the structural equation model, CFI = 0.997, GFI = 0.992, AGFI = 0.973, and RMSEA = 0.033, showing the model has a good fit. Significant relationships were found between job mobility and employee performance (β = 0.195, p < 0.001) between talent management practices and employee performance (β = 0.246, p < 0.001). This analysis also showed a positive, significant and strong relationship between age and employee performance (β = 0.230; ρ value < 0.001). Conclusions: The structural equation model showed that talent management practices consisting of talent attraction, talent development, and talent evaluation had a significant and positive impact on medical staff performance. We also found that, in addition to these three talent management practices, such factors as job mobility, and age were significant predictors of employee performance. It is, therefore, important to create formal talent management processes that support personal development and appreciate the individual performance of employees. [ABSTRACT FROM AUTHOR]

Background: Grounding on the Resource-Based View (RBV) and organization support theory (OST), this study examines the effect of talent management practice (TMP) on perceived organizational support (POS), organizational performance (OP), and employee performance (EP) within the Jordanian telecom sector, with a specific focus on the mediating effect of POS's between TMP-EP and OP relationship. Methods: This study uses a cross-sectional method to collect data from 397 personnel at three Jordanian telecom enterprises. The Smart-PLS application assisted with structural equation modeling, which was used to examine the data. Results: The findings show that TMP and POS have large and favorable effects on EP and OP, with TMP having a particularly strong influence on POS. The interplay of TMP and POS has a significant favorable influence on EP and OP, with POS acting as a mediator between TMP and both EP and OP. These results advance the comprehension of theories of RBV and organizational support by illuminating the relationship and relevance of TMP and POS in the setting of Jordanian telecommunications enterprises. Conclusion: The study provides HR managers with practical insights into improving EP and OP by optimizing TMP and POS strategies. Recognizing the constraints of the cross-sectional methodology and self-reported assessments, the study recommends further studies to investigate the causal and longitudinal effects of TMP and POS on EP and OP and the mediating mechanisms of these interactions. [ABSTRACT FROM AUTHOR]