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This investigation seeks to elaborate on how proactive market orientation (MO) and responsive MO motivate firms to conduct business model innovation (BMI) through the breadth of market knowledge search (BMKS) and the depth of market knowledge search (DMKS).

Based on the survey data of 259 high-tech firms in the industrial parks of the Yangtze River Delta, this study uses multiple hierarchical regressions to examine the hypotheses and conducts Sobel and bootstrapping methods to further test the mediating effects.

The findings indicate that the positive effects of proactive and responsive MO on BMI are mediated by BMKS and DMKS. It also shows that proactive MO has a greater impact on BMKS than responsive MO, while responsive MO has a stronger impact on DMKS than proactive MO.

Firms with different MOs can choose different types of market knowledge search to promote BMI, which reminds managers to give attention to the importance of bridging MOs with knowledge search strategies in BMI.

This study introduces a constructive theoretical framework by examining the roles of MO and market knowledge search on BMI. The findings reveal that MO as a key initiating factor and market knowledge search as an important conduit play vital roles in the experimental process of BMI and identify the differential effects of proactive and responsive MO on two types of market knowledge search.

This paper investigates whether China's R&D tax deduction policy triggers firms to manipulate their R&D expenditures upward.

This paper employs the ratio of actual tax savings as a proxy for the benefits of the R&D tax deduction policy based on manually collected and systematically cross-checked data. The relationship between tax benefits and abnormal R&D spending is estimated in a sample of Chinese A-share listed companies for the period 2007–2018.

The findings suggest that tax deductions lead to positive abnormal R&D spending and that this deviation in R&D spending may be attributed to firms' upward R&D manipulation for tax avoidance. The results also indicate that this behavior is more significant for the period after the policy revision, in non-HNTEs (high and new technology enterprises), and in firms with a high ratio of R&D expenses.

It is difficult to establish a sophisticated and unified model to identify the specific strategy of upward R&D manipulation that firms use to obtain tax benefits.

Managers should take into account upward R&D manipulation when designing governance mechanisms. Policymakers in developing countries may further pursue preferential tax policies that cover every stage of innovation activities gradually; the local provincial governments need to leverage their proximity and flexibility advantages to develop a tax collection and administration system.

This study contributes to the understanding of the complex effect of R&D tax incentives and helps more fully illuminate firms' upward R&D manipulation behavior from the perspective of tax planning strategies, which are underexplored in previous research.

Aside from grappling with technological advancements, enterprises in the industrial internet era are embracing business model innovation to align with the evolution of the industrial internet. However, a gap persists in the existing research regarding the strategies and methods available to small and medium-sized enterprises (SMEs) for executing business model innovation. Therefore, this paper aims to explore the connotation, characteristics and logic of business model innovation for SMEs in the industrial internet era.

To explore the business model innovation logic of small and medium-sized enterprises in the era of industrial internet, the paper adopts a longitudinal single-case study approach, with PAYA, a medium-sized enterprise in the electromechanical industry, serving as the subject of research. It systematically analyzes PAYA’s business model innovation, centering on four key elements of the business model: value proposition, value creation, value delivery and value capture.

The study proposes two types of business model innovation, namely, “Migration” and “Expansion”, and explains the logic of business model innovation for SMEs in the industrial internet era: faced with a rapidly changing market environment, entrepreneurs put forward the value proposition through the insight of the market environment, then enterprises conduct technological innovation to support the value creation by their own unique experience and knowledge, and then improve the legitimacy of the market by expanding the influence of market acceptance of the new business model to promote the value delivery, and finally capture the economic value and ecological value.

The types and logic of business model innovation proposed in this paper contribute to supplementing and developing the theory of business model innovation and meanwhile have important reference value for SMEs in the industrial internet era.

This study aims to explore the relationship between non-market strategies and organizational resilience, using a Chinese private enterprise as an example.

This study collected data through semi-structured interviews and analyzed them through grounded theory, using a three-step approach of open coding, axial coding and selective coding to analyze and construct a model of the mechanism of the impact of non-market strategies on organizational resilience.

The following conclusions were drawn from this study. (1) Stakeholders, internal and external environment and entrepreneurship are important motivations that influence private firms to implement non-market strategies to enhance organizational resilience, with entrepreneurship being the key driver. (2) Non-market strategies contain three dimensions, and different non-market behaviors have different mechanisms of action on the organizational resilience of firms. (3) Non-market strategies and organizational resilience form an interactive spiral relationship. This mutually reinforcing effect promotes firm growth and sustainable corporate development. The research results enrich the theoretical connotation of non-market strategies, construct a model of the mechanism of influence of non-market strategies on organizational resilience, and describe three explanatory paths for the relationship between the two–incentive mechanism, functional mechanism and transformation mechanism.

This study's single case is unique and based on the Chinese context. In addition, this study adopts a rooted qualitative research approach and although the coding and model construction strictly follow the steps of grounded theory research, a degree of subjectivity is inevitable. On this basis, future research can adopt quantitative analysis methods to test and improve the model.

This paper explores the important role of non-market strategies in the Chinese context under the impact of traditional market mechanisms, based on the perspective of Chinese private enterprises, and provides new insights and revelations for private enterprises to achieve sustainable development.

This study innovatively explores the formation mechanism of organizational resilience from the perspective of non-market strategies, adding a new perspective to the literature. Additionally, it examines the mechanisms between long-term non-market strategy and organizational resilience, particularly their relationship in times of crisis, utilizing a rooted approach that goes beyond static analysis.

This study aims to use event system theory and job demands–resources (JD-R) model to examine the double-edged sword effect of event strength of Beijing Winter Olympics (BWO) on volunteers’ in-role performance and proactive behavior as mediated by work overload and meaningfulness.

The sample included 193 volunteer–leader dyads working at one BWO venue. The authors conducted a multitime and multisource study using Mplus 8 to examine the hypotheses.

Volunteers’ perceived BWO event strength was positively related to work overload, which reduced in-role performance and proactive behavior. Volunteers’ perceived BWO event strength was also positively related to work meaningfulness, which promoted in-role performance and proactive behavior. Perceived organizational support served as a moderator by mitigating the positive relationship between perceived BWO event strength and work overload; however, it did not strengthen the positive relationship between perceived BWO event strength and work meaningfulness.

This study developed a comprehensive model of how BWO event strength affected volunteers’ performance from the perspective of event system theory and the JD-R model, which enriches theoretical application and research in the context of mega sport events.

本研究运用事件系统理论和工作需求-资源(JD-R)模型, 探讨了2022年北京冬奥会（BWO）事件强度通过工作负荷和工作意义感知进而对志愿者角色内绩效和主动性行为的双刃剑效应。

我们在冬奥会场所之一实施了多时点、多来源的收集数据的方式, 最终样本包括193份志愿者-领导配对数据, 并使用Mplus 8来检验我们的假设。

志愿者感知的BWO事件强度与工作负荷呈正相关, 进而会降低他们的角色内绩效和主动性行为。志愿者感知的BWO事件强度与工作意义感也呈正相关, 进而会促进他们的角色内绩效和主动性行为。感知的组织支持通过弱化BWO事件强度与工作负荷之间的正相关关系, 进而调节了志愿者的角色内绩效和主动性行为; 然而, 感知的组织支持并没有强化BWO事件强度与工作意义感之间的正相关关系。

本研究结合事件系统理论和JD-R模型, 发展了一个BWO事件强度对志愿者绩效表现影响的综合模型, 丰富了有关大型体育赛事志愿者的理论应用和研究。

Este estudio utiliza la teoría del sistema de eventos y el modelo de demandas de trabajo-recursos (JD-R) para examinar el efecto de doble filo de la fuerza del evento de los Juegos Olímpicos de Invierno de Pekín (BWO) sobre el rendimiento en el rol y el comportamiento proactivo de los voluntarios, mediado por la sobrecarga laboral y la significatividad del trabajo.

Nuestra muestra incluyó 193 díadas de voluntarios-líderes que trabajaban en una sede de BWO. Realizamos un estudio multitemporal y multifuente utilizando Mplus 8 para examinar nuestras hipótesis.

La intensidad percibida por los voluntarios en los eventos de BWO también se relacionó positivamente con la significación del trabajo, que promovió el rendimiento en el rol y el comportamiento proactivo. Además, el apoyo organizativo percibido sirvió como moderador al mitigar la relación positiva entre la intensidad percibida del evento BWO y la sobrecarga de trabajo; sin embargo, no reforzó la relación positiva entre la intensidad percibida del evento BWO y la significatividad del trabajo.

Este estudio desarrolló un modelo integral de cómo la fuerza del evento BWO afectaba al rendimiento de los voluntarios desde la perspectiva de la teoría del sistema de eventos y el modelo JD-R, lo que enriquece la aplicación teórica y la investigación en el contexto de los megaeventos deportivos.

Since 2013, China has implemented targeted poverty alleviation policies, successfully eradicating absolute poverty nationwide by 2021. The fiscal funds allocated for poverty alleviation have significantly contributed to reducing poverty in impoverished areas. However, to date, there has been a lack of scholarly research specifically examining the effects of these fiscal poverty alleviation funds on both poverty reduction and economic growth. This study aims to address two key questions: What role do fiscal poverty alleviation funds play in reducing poverty? Additionally, do these funds contribute to economic growth?

Provincial panel data in China from 2010 to 2020 are used to test the impact of fiscal poverty alleviation funds on poverty reduction and economic growth. The empirical study of this paper primarily employs panel data within difference and two-stage least squares (2SLS) estimation for causal identification.

Poverty alleviation funds positively influence China’s economic growth and significantly reduce the rural poverty rate. During the sample period, the contribution of poverty alleviation funds to economic growth reached 7.3%, and the contribution to the reduction of the poverty incidence rate was 8.4%.

The key contribution of this study lies in its novel approach of using empirical methods to probe the impacts of fiscal poverty alleviation funds on provincial economic growth. Additionally, this paper also empirically tests the mechanisms by which fiscal poverty alleviation funds promote growth and reduce poverty, mainly by improving the infrastructure development conditions in impoverished areas.

The purpose of the study is to investigate the impact of artificial intelligence (AI), machine learning (ML), and data science (DS) on unemployment rates across ten high-income economies from 2015 to 2023.

This study takes a unique approach by employing a dynamic panel data (DPD) model with a generalised method of moments (GMM) estimator to address potential biases. The methodology includes extensive validation through Sargan, Hansen, and Arellano-Bond tests, ensuring the robustness of the results and adding a novel perspective to the field of AI and unemployment dynamics.

The study’s findings are paramount, challenging prevailing concerns in AI, ML, and DS, demonstrating an insignificant impact on unemployment and contradicting common fears of job loss due to these technologies. The analysis also reveals a positive correlation (0.298) between larger government size and higher unemployment, suggesting bureaucratic inefficiencies that may hinder job growth. Conversely, a negative correlation (−0.201) between increased labour productivity and unemployment suggests that technological advancements can promote job creation by enhancing efficiency. These results refute the notion that technology inherently leads to job losses, positioning AI and related technologies as drivers of innovation and expansion within the labour market.

The study’s findings suggest a promising outlook, positioning AI as a catalyst for the expansion and metamorphosis of employment rather than solely a catalyst for automation and job displacement. This insight presents a significant opportunity for AI and related technologies to improve labour markets and strategically mitigate unemployment. To harness the benefits of technological progress effectively, authorities and enterprises must carefully evaluate the balance between government spending and its impact on unemployment. This proposed strategy can potentially reinvent governmental initiatives and stimulate investment in AI, thereby bolstering economic and labour market reliability.

The results provide significant perspectives for policymakers and direct further investigations on the influence of AI on labour markets. The analysis results contradict the common belief of technology job loss. The study’s results are shown to be reliable by the Sargan, Hansen, and Arellano-Bond tests. It adds to the discussion on the role of AI in the future of work, proposing a detailed effect of AI on employment and promoting a strategic method for integrating AI into the labour market.