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In recent years, the trend of hiring external CEOs has become increasingly prevalent. However, the impact of these CEOs' prior experiences in different firms on the innovation of their successor firms has not received sufficient attention. Drawing on upper echelons theory and management power theory, this study explores the non-linear relationship between prior CEO experience and breakthrough innovation, as well as the moderating effects of different types of CEO power.

We selected China’s A-share listed manufacturing companies as samples and used zero-inflated Poisson regression to verify the hypothesis. We employed instrumental variable methodology to address potential endogeneity issues and conducted robustness tests by substituting core variables, changing measures, adding additional control variables, and shrinking the core variables.

We conclude that there exists an inverted U-shaped relationship between prior CEO experience and breakthrough innovation. Furthermore, we analyze the effects of formal and informal CEO power on the role of prior CEO experience in breakthrough innovation and find that the inverted U-shaped relationship is contingent upon the level of CEO power.

The findings extend research on CEO succession and offer a reference for firms aiming to hire external CEOs with prior experience to foster breakthrough innovation.

The model of pay-for-knowledge incentivizes individuals with financial rewards for sharing their expertise, facilitating a transactional exchange between knowledge providers (sellers) and seekers (buyers). While this model is effective in promoting paid contributions, its influence on free knowledge exchanges remains ambiguous, creating uncertainty about its overall impact on platform knowledge ecosystems. This study aims to explore the mechanim of how knowledge payment influences free knowledge contribution. Based on relational signaling theory, this study posits that a buyer’s payment for knowledge acts as a positive relational signal in the buyer–seller relationship and examines how the signaling effect varies across different social contexts through attribution theory.

This paper empirically tests the hypotheses by analyzing a data set comprising 630 instances from 359 unique knowledge sellers on Zhihu, a prominent knowledge-sharing platform in China. This paper use zero-inflated negative binomial models to conduct this analysis.

The findings reveal that when buyers pay for knowledge, this action positively influences sellers to contribute knowledge for free. However, the strength of this influence is moderated by the platform’s social functions: appreciation feedback tends to weaken this effect, while social network ties enhance it.

Prior research has predominantly focused on the financial incentives of pay-for-knowledge and its spillover effects on unpaid users’ activities. This study shifts the focus to the social dimensions of pay-for-knowledge, arguing that buyer-initiated knowledge payments signal buyers’ commitment to foster reciprocal relationships with sellers. It expands the literature on the relationship between knowledge payment and contribution, moving beyond financial incentives to include social factors, thus enriching our understanding of the interplay between paid and free knowledge activities. Additionally, the empirical evidence supports the efficacy of pay-for-knowledge in promoting both free and paid contributions within knowledge-sharing platforms.

Using recent US regional data associated with food system operations, this study aims at building optimization and econometric models to incorporate varying influential factors on food hub location decisions and generate effective facility location solutions.

Mathematical optimization and econometric models have been commonly used to identify hub location decisions, and each is associated with specific strengths to handle uncertainty. This paper develops an optimization model and a hurdle model of the US fresh produce sector to compare the hub location solutions between these two modeling approaches.

Econometric modeling and mathematical optimization are complementary approaches. While there is a divergence between the results of the optimization model and the econometric model, the optimization solution is largely confirmed by the econometric solution. A combination of the results of the two models might lead to improved decision-making.

This study suggests a future direction in which model development can move forward, for example, to explore and expose how to make the existing modeling techniques easier to use and more accessible to decision-makers.

The models and results provide information that is currently limited and is useful to help inform sustainable decisions of various stakeholders interested in the development of regional food systems, regional infrastructure investment and operational strategies for food hubs.

This study sheds light on how the application of complementary modeling approaches improves the effectiveness of facility location solutions. This study offers new perspectives on elaborating key features to encompass facility location issues by applying interdisciplinary approaches.

This study examines how maturity mismatch, a specific type of financial structure of firms, affects corporate outward foreign direct investment (OFDI).

Using the number of newly established foreign subsidiaries in a given year as firm-level OFDI and utilizing data from Chinese listed firms between 2007 and 2022, we employ a negative binomial regression model to examine the impact of corporate maturity mismatch on the OFDI. We also make efforts to ensure the robustness of the result, such as employing an exogenous policy to establish a difference-in-difference model.

The empirical result indicates that maturity mismatch inhibits firms' OFDI. Additional test shows that maturity mismatch increases firms' financing costs and reduces firms' research and development (R&D) investment and that the negative impact of maturity mismatch on OFDI is predominantly observed in firms with high financial constraints and low R&D intensity, indicating that maturity mismatch may affect firms' OFDI through the financing cost channel and the R&D investment channel.

Corporate maturity mismatch is common in China and similar emerging markets. However, research on the economic consequences of maturity mismatch, especially its impact on firms' overseas expansions, is rare. This study establishes the relationship between corporate maturity mismatch and OFDI, contributes to the literature on the relationship between financial factors and OFDI, and provides policy implications for emerging market countries.

This study investigates two internationalization strategies, foreign direct investment (FDI) expansion and export expansion, and their effects on the innovation performance of Chinese multinational enterprises (MNEs). Additionally, it explores the moderating roles of both formal and informal political connections in the relationship between these internationalization strategies and innovation performance.

The hypotheses were tested using the Poisson panel model and data on 2,106 observations from 645 Chinese-listed firms between 2010 and 2017.

FDI expansion significantly enhances the innovation performance of Chinese MNEs compared to export expansion. Moreover, formal and informal political connections are found to have distinct moderating effects: formal political connections amplify the positive effect of FDI expansion on firm innovation, whereas informal political connections tend to weaken it.

This study contributes to the discourse on innovation and political connections, especially in the context of EMNEs. It enriches the theoretical understanding of internationalization strategies and innovation performance in EMEs, contrasting with the technology-utilization motives observed in MNEs from developed economies.

The objectives of the proposed model are: aiding nursing staff in documentation tasks, which can be onerous and stressful; and helping management by offering an estimate of the nursing workload, which can be considered for administrative purposes, such as staff scheduling.

An exploratory-descriptive study was conducted in order to identify, investigate, and describe the problem of documenting nursing activities and workload estimation in an intensive care unit. Technological solutions were explored, and models were proposed to address these issues.

Cross-dataset experiments were performed, and the model was able to offer an adequate estimate of the nursing workload. The results suggest that continuous retraining is essential for maintaining high accuracy. While the proposed model was considered in the context of an adult ICU, it can be adapted to other contexts, such as elderly care.

While the proposed solution seems promising, further research is required, such as deploying this system in an ICU and facing challenges in the areas of computer security, medical ethics, and patient data privacy. More patients’ variables could also be collected to improve the workload estimates.

Nursing workload assessment is critical to improve the cost-benefit ratio in health care, offer high-quality patient care, and reduce unnecessary expenses, and this process is usually manual. An automated device can automatically document the amount of time spent in patient care activities in a more transparent, efficient, and accurate manner, freeing staff for more urgent activities and keeping management better informed about day-to-day nursing operations.

Micro and small enterprises (MSE) play a critical role in the Swiss economy but had no meaningfully adopted working from home (WFH) policy before the COVID-19 crisis. The timing of the study’s data collection allowed a unique assessment of Swiss MSEs’ adoption of WFH enabled by the adoption of digital technologies due to the first government-mandated COVID-19 lockdown. The study also set out to assess the permanence of any changes in the adoption of WFH by MSEs after initial government COVID-19 restrictions ended.

The study uses a threefold theoretical framework combining social, technical and spatial dimensions. Data were collected via telephone interviews. The utilised sampling frame included 153,000 small businesses with 4–49 employees, and the realised sample for the study was 503 interviews with MSE owners and managing directors (MDs).

The Swiss government’s COVID-19 crisis lockdown policies accelerated the digital transformation of work by employees in Swiss MSEs by increasing the number of employees WFH. However, the number of MSEs with WFH employees decreased after the first lockdown ended. Small business leadership is an important influence on the persistence of any increases in WFH.

The data collection uniquely captures the effects of externally driven digital transformation of work in small businesses by the adoption of WFH. The findings show that small businesses can rapidly learn new ways of working and support the claim that Swiss MSE MDs play a critical role in the adoption of WFH. They also confirm the importance of digital leadership and culture for realising the potential of WFH in small businesses.

Key core technology is the most important weapon of the country, and breaking through the “strangled” problem is one of the real problems that China’s emerging industries and enterprises must solve. Accurately identifying the “strangled” problem will help China accelerate the realization of high-level scientific and technological self-reliance and win the battle against key core technologies.

Combined with the characteristics of key core technologies, the key core technology evaluation system was constructed from four dimensions: technology innovation, technology radiation, technology economy and technology safety. We adopt the entropy TOPSIS method to evaluate the patents, and the patents with the top 5% scores are identified as key core technology patents. Then, this study identifies key core technology “strangled” problems in three dimensions: technology value advantage, competitive advantage and quantitative advantage.

Taking the patent data of the global new generation information technology industry from 2011 to 2023 as a sample, 178 moderately “strangled” technologies and 49 severely “strangled” technologies are selected. The study results are consistent with the current situation of the new generation information technology industry’s development, and verify the feasibility and reliability of the key core technology “strangled” problem identification model.

This study uses patent data to identify key core technologies and “Strangled” in the new generation information technology industry. It can provide a reference for relevant national departments and agencies, as well as universities and enterprises.

The study examines the relationship between news intensity, media sentiment and market microstructure invariance-implied measures of trading activity and liquidity of Chinese property developer stocks during the 2020–2022 Chinese property sector crisis.

The authors adopt the extension of the news article invariance hypothesis, which is a generalization of the market microstructure invariance conjecture, from January 2020 to January 2022 to test specific quantitative relationships between the arrival rate of public information, trading activity and a nonlinear function of a proxy for the probability of informed trading. Empirical tests are based on a dataset of 22,412 firm-day observations and two count-data models to correct for overdispersion and the excess number of zeros. Seventy-five stocks of Chinese companies from the property development industry (including the China Evergrande Group) were included in the sample.

The authors reject the news article invariance hypothesis but document a positive and significant relationship between the flow of public information and risk liquidity. Additionally, the authors find that the proxy for informed trading activity is positively related to the arrival rates of public information from October 2021 to January 2022.

The findings support the hypothesis that negative (positive) media sentiment induces significant deterioration (insignificant improvement) in stock liquidity. The authors find that an increase in the number of news articles about a company corresponds to a higher liquidity of Chinese property developers' stocks after controlling for media sentiment.

Drawing on the pleasure-arousal-dominance (PAD) emotion model, the emotional states of consumers embedded in online reviews can be described through three dimensions, that is, pleasure, arousal and dominance, rather than only the one-dimensional positive and negative polarity, as in previous studies. Therefore, this study aims to explore the effect of online review emotion on perceived review helpfulness based on these three basic emotional dimensions.

A lexicon-based method is developed to analyze PAD emotions of online reviews from JD.com. The zero-inflated negative binomial regression is utilized to empirically validate the study hypothesis. The authors examine the influence of pleasure, arousal, dominance, emotion diversity and emotion deviation on review helpfulness, as well as the moderating effect of product type on the relationship between all independent variables and online review helpfulness.

The study results show that the pleasure emotion impairs the helpfulness of online reviews, while the arousal and dominance emotions have a positive impact. Moreover, the authors find that compared with search products, the effects of pleasure, arousal and dominance on perceived helpfulness are strengthened for experience products. However, the emotional diversity and emotional deviation have opposite effects on the helpfulness of search products and experience products. Additionally, the results show that dominance emotion plays a more important role in the interaction effect.

The empirical findings confirm the applicability of PAD in the online review context and extend the existing knowledge of the influence of review emotion on helpfulness. A feasible scheme for extracting PAD variables from Chinese text is developed. The study findings also have significant implications for reviewers, merchants and platform managers of e-commerce websites.