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While the relationship between non-family CEOs and corporate innovation in China has been widely studied, the results remain inconclusive. This study explores the relationship between non-family CEOs and corporate innovation in the context of intergenerational succession. It considers the background and background characteristics of non-family CEOs in an attempt to provide a theoretical foundation for human resource management and innovative strategic management that can be applied in the transformation of family companies.

The authors develop, then test, a series of hypotheses using an econometric analysis of a large sample of Chinese listed family firms. To control for endogeneity problems, such as missing variables in the model and the selectivity bias of the sample, propensity score matching (PSM) model is applied to analyze the panel data of 452 listed family firms from 2009–2019.

This study first validates the mechanism by which non-family CEO background characteristics affect innovation performance in family firms. It then reveals the varying moderating effects of two stages of intergenerational succession (i.e. later-generation participation in management and later-generation take-over management) that influence the relationship between non-family CEOs and corporate innovation.

The study's findings based on upper echelon and imprinting theory complement and extend existing research by revealing the impact of non-family CEOs from different backgrounds, and also identifying the role of intergenerational succession in the relationship between non-family CEO background characteristics and innovation performance.

This paper aims to investigate the singular Hopf bifurcation and mixed mode oscillations (MMOs) in the perturbed Bonhoeffer-van der Pol (BVP) circuit. There is a singular periodic orbit constructed by the switching between the stable focus and large amplitude relaxation cycles. Using a generalized fast/slow analysis, the authors show the generation mechanism of two distinct kinds of MMOs.

The parametric modulation can be used to generate complicated dynamics. The BVP circuit is constructed as an example for second-order differential equation with periodic perturbation. Then the authors draw the bifurcation parameter diagram in terms of a containing two attractive regions, i.e. the stable relaxation cycle and the stable focus. The transition mechanism and characteristic features are investigated intensively by one-fast/two-slow analysis combined with bifurcation theory.

Periodic perturbation can suppress nonlinear circuit dynamic to a singular periodic orbit. The combination of these small oscillations with the large amplitude oscillations that occur due to canard cycles yields such MMOs. The results connect the theory of the singular Hopf bifurcation enabling easier calculations of where the oscillations occur.

By treating the perturbation as the second slow variable, the authors obtain that the MMOs are due to the canards in a supercritical case or in a subcritical case. This study can reveal the transition mechanism for multi-time scale characteristics in perturbed circuit. The information gained from such results can be extended to periodically perturbed circuits.

According to extensive analysis, employee agility is influenced by teamwork, coordination and the organizational environment. However, less consideration has been given to the role of work stressors (challenge, hindrance) in influencing employee agility. To address this research gap, this study sheds light on how the use of enterprise social media (ESM) for social and work purposes influences employee agility through work stressors.

This research also explores how ESM visibility enhances the interaction between work stressors and employee agility by using primary data obtained from Chinese workers. A total of 377 entries were analyzed using AMOS 24.10 tools. All the hypotheses were tested using structural equation modeling (SEM).

The findings revealed that ESM use (social and work) negatively impacts challenge and hindrance work stressors. The results also reflect that challenge stressors have a significant impact on employee agility, whereas hindrance stressors are negatively related to it. Furthermore, the outcome also indicated that increased ESM visibility reinforces the connection between challenge stressors and employee agility. However, ESM visibility did not indicate a significant moderating impact on the link between hindrance stressors and employee agility.

This study describes how ESM usage effects agility of stressed employees. This research also explores how ESM visibility improves the interaction between work stressors and employee agility. The study results contribute to growing research on social media and employee agility and suggest several points of guidance for managers.

In this paper, the impact of stock-based compensation and further the joint effects of stock-based compensation and investor sentiment on pension discount rate choice is examined.

The hypotheses is tested using fixed effects models and instrumental variable analysis where pension discount rate is the dependent variable, and stock-based compensation and investor sentiment are our variables of interest.

It was found that pension discount rate is negatively associated with managers' stock-based compensation. Further analysis indicates that managers with larger stock-based compensation tend to adjust down their pension discount rates in higher (smaller) degree, responding to high (low) investor sentiment.

The findings provide important insights into how managers use pension discount rates to engage in earnings management. Understanding these relationships has implications for interpreting pension numbers reported in the financial statements and designing pension accounting rules that minimize the possibility that managers take advantage of the complexity associated with pension accounting to influence the reported earnings and executive compensation. Moreover, the findings suggest the need for increased attention from boards of directors, auditors and regulators to reported pension liabilities and service costs, especially for firms paying higher proportion of stock-based compensation to managers and during periods of high investor sentiment.

The findings contribute to the extant literature by identifying the joint impacts of stock-based compensation and investor sentiment as incentives for pension discount rate manipulation. The empirical results of this study also have important implications for corporate governance and regulation.

This study aims to investigate the effect of the virtual spokesperson type on the consumers' preference for new products. To meet the consumer needs of Generation Z, virtual spokespeople have become new assistants in brand marketing. However, how virtual spokespersons drive consumer preference for new products is minimally understood.

This research conducts three experiments to investigate the influence of virtual spokesperson type on consumers' preference for new products.

The research shows that, for radically new products, competent virtual spokespersons improve consumers' perception of self-efficacy and thus consumers' preference; for incrementally new products, warm virtual spokespersons improve consumers' perception of social connection and thus consumers' willingness to buy.

This study broadens research on brand spokespersons and virtual spokespersons. This research also enriches and expands research on the consideration of new product types in brand spokespersons.

The sources and platforms utilized for environmental communication have been significantly expanded by the emergence of social media. The validity, form, and content of environmental communication processes are particularly radical departures from conventional media, making personal green blogs important of study as areas of everyday culture politics where people make understanding of environmental challenges. There is currently a lack of research on how social media might encourage green behaviours. This research reveals the impact of social media use and green blogging on green purchasing behaviour, which is supported by the social learning theory. Present study shows that social media use and green blogging have a substantial positive connection, drawing on a sample of 580 respondents from Pakistan examined using structural equation modelling. Both notions have a considerable impact on consumers' intentions to make green purchases, and social media trust plays a moderating role in this relationship. Furthermore, social media trust considerably modifies the connections between green blogging and social media use that is related to green behaviour. The current study is novel and offers important information to understand how social media might promote eco-friendly habits and behaviour.

Organisational learning plays a critical role for firms to keep abreast of a supply chain environment filled with volatility, uncertainty, complexity and ambiguity (VUCA). This study investigates the extent to which supply chain learning (SCL) affects operational resilience under such circumstances.

This study developed a research framework and underlying hypotheses based on SCL and information processing theory (IPT). An empirical test was carried out using secondary data derived from the “Supply Chain Policy” launched by the Chinese government and two large related conferences.

SCL positively relates to operational resilience, and several moderators influence the relationship between them. The authors argue that digital-technological diversity could weaken the role of SCL in operational resilience, whereas customer concentration, and participating in a pilot programme could enhance the effect of SCL.

Firms should embrace the power of SCL in building resilience in the VUCA era. Meanwhile, they should be cautious of a digital-technological diversification strategy, appraise the customer base profile and proactively engage in pilot programmes.

This research develops the SCL construct further in the context of China and empirically measures its power on operational resilience using a unique dataset. This contributes to the theorisation of SCL.

The purpose of this study is to explore how digital construction policy (DCP) drives enterprise green innovation (EGI) from an information processing theory (IPT) perspective, including the mediating mechanisms of market information accessibility and operational risk, the moderating role of intellectual property protection (IPP) and product market competition (PMC) and the heterogeneous effects of ownership, Internet development and managerial ability.

Based on the matched panel data of A-share listed enterprises from 2011 to 2019 and the Broadband China policy as a quasinatural experiment, this study investigates the impact of DCP on EGI by constructing a multi-time point difference-indifferences (DID) model.

Digital construction policies can significantly promote EGI. DCP works in two fundamental ways, namely by increasing market information accessibility and reducing operational risk. IPP and PMC significantly increased the contribution of digital construction policies to EGI. Heterogeneity analysis found that digital technology has a stronger promotion effect for SOEs, high-managerial-ability enterprises and enterprises in regions with low Internet development levels.

The study provides new insights about the antecedents of EGI from a DCP perspective. It also enlightens emerging economies to actualize green innovation under the digital wave.

From the perspective of IPT, this study explains the mechanism of DCP-driven EGI. It enhances understanding of the relationship between DCP and EGI.

Online reviews serve as valuable sources of information, reflecting tourists’ attentions, preferences and sentiments. However, although the existing research has demonstrated that incorporating online review data can enhance the performance of tourism demand forecasting models, the reliability of online review data and consumers’ decision-making process have not been given adequate attention. To address the aforementioned problem, the purpose of this study is to forecast tourism demand using online review data derived from the analysis of review helpfulness.

The authors propose a novel “identification-first, forecasting-second” framework. This framework prioritizes the identification of helpful reviews through a comprehensive analysis of review helpfulness, followed by the integration of helpful online review data into the forecasting system. Using the SARIMAX model with helpful online review data sourced from TripAdvisor, this study forecasts tourist arrivals in Hong Kong during the period from August 2012 to June 2019. The SNAÏVE/SARIMA model was used as the benchmark model. Additionally, artificial intelligence models including long short-term memory, back propagation neural network, extreme learning machine and random forest models were used to assess the robustness of the results.

The results demonstrate that online review data are subject to noise and bias, which can adversely affect the accuracy of predictions when used directly. However, by identifying helpful online reviews beforehand and incorporating them into the forecasting process, a notable enhancement in predictive performance can be realized.

First, to the best of the authors’ knowledge, this study is one of the first to focus on the data issue of online reviews on tourism arrivals forecasting. Second, this study pioneers the integration of the consumer decision-making process into the domain of tourism demand forecasting, marking one of the earliest endeavors in this area. Third, this study makes a novel attempt to identify helpful online reviews based on reviews helpfulness analysis.