This paper explores the critical role of venture capital in innovation and entrepreneurship,as well as its impact on global transformation and technology diffusion. Venture capital serves as a vital source of funding for startups,particularly when traditional financial instruments fail to meet the financing needs of innovative enterprises,significantly enhancing their innovative output. However,venture capital also has limitations,including a narrow investment focus and susceptibility to technological cyclicality,which create financing gaps in foundational technology sectors and emerging markets.

Furthermore,this paper analyzes the rise of emerging markets within the global venture capital and entrepreneurship wave,with a particular emphasis on Chinas important role. Data indicate that the share of venture capital invested in emerging markets as a share of the total global transaction volume has significantly increased,with financial performance exceeding that of public markets,illustrating a trend towards multipolarity in global venture capital. Additionally,the rise of innovation and entrepreneurship in China is notably pronounced,with its technological and business models exerting significant spillover effects on other emerging markets,thereby accelerating their innovation and entrepreneurial processes.Finally,this paper presents policy recommendations to promote venture capital, emphasizing the need to cultivate the venture capital ecosystem and patient capital that supports innovation and entrepreneurship.

The significance of venture capital in the rise of emerging markets is substantial. On the one hand,emerging markets are at a critical stage of economic transformation and upgrading,presenting tremendous potential market demand. On the other hand,the level of development of their financial systems is relatively low,making it more challenging for small and medium-sized innovative enterprises to secure financing compared to developed countries. Consequently,with its forward-looking investment capabilities,support for startups,and ability to nurture innovation ecosystems,venture capital is increasingly recognized as an important financial tool in emerging markets. As the significance of emerging markets in the global economy continues to rise,the role of venture capital will become even more crucial,and its value in promoting economic growth,driving industrial upgrading,and stimulating innovation will be further realized.

In the context of global technological competition shifting from “single-point breakthroughs” to “ecosystem dominance”,unicorn enterprises have emerged as critical “incubators” of new productive forces and strategic “barometers” of national competitiveness. This study investigates the relationship between the investment activity of Chinese Government-Guided Funds (GGFs) and the cultivation of unicorn enterprises,utilizing comprehensive venture capital and private equity (VCPE) investment data,including GGF transactions,from 2009 to 2023. Drawing from 156226 investment events encompassing 588 unicorn enterprises,the research reveals significant overlaps between GGF investment sectors and unicorn industry distributions,highlighting the synergistic interplay between policy guidance and market selection. The findings demonstrate that increased GGF investment activity positively correlates with regional unicorn growth,moderated by regional differentiation indices and business environment quality.

Three core drivers are identified to enhance GGF efficacy in cultivating unicorns: precision investment (X) to anchor technological strengths,ecological empowerment (Y) to optimize regional capabilities,and collaborative deepening (Z) to reconfigure innovation networks. The empirical results confirm that GGF investment frequency and capital size directly stimulate unicorn emergence,particularly in high-potential sectors such as semiconductors,biotechnology,and artificial intelligence. For instance,a one-unit increase in GGF investment frequency raises the number of GGF-cultivated unicorns by 0.017,while a 100 million yuan increase in investment amplifies this effect by 0.083. Regionally,GGF investments exhibit indirect spillover effects,with investment frequency and capital contributing to 0.012 and 0.061 unicorns per unit,respectively. Crucially,regional differentiation indices amplify these effects: a one-unit rise in differentiation enhances the marginal impact of GGF investment frequency by 1.8%. Meanwhile,superior business environments in top-tier regions double GGF efficiency compared to underdeveloped areas,underscoring the catalytic role of institutional ecosystems.

Spatiotemporal analyses reveal evolving dynamics in GGF strategies. Early-stage GGF investments focused on technical breakthroughs in eastern coastal regions (e.g.,semiconductors in Jiangsu and Guangdong),while central and western provinces later adopted differentiated niches (e.g.,chip packaging in Henan and photovoltaics in Gansu). However,declining regional differentiation signals risks of redundant resource allocation,necessitating adaptive mechanisms to balance specialization and diversification. Case studies,such as Hefeis AI cluster (e.g.,USTC Silicon Valley) and Gansus large-scale green funds supporting the construction of  a local photovoltaic industrial chain,illustrate how localized “innovation ecosystems” integrate policy,capital,and talent to accelerate unicorn incubation.

To optimize GGF performance,this study proposes a “precision+ecology+collaboration” framework:

First,precision investment: Prioritize sectoral differentiation based on regional advantages,avoiding homogeneous “checklist-driven” allocations. Eastern regions can target frontier technologies (e.g.,quantum computing and gene editing),supported by “national laboratory-fund” linkage mechanisms,while central/western areas leverage resource endowments (e.g.,renewable energy in Gansu and lithium reserves in Qinghai) to establish “single-champion cultivation funds.”
Second,ecological empowerment: Strengthen institutional ecosystems via streamlined governance (e.g.,Shenzhens “instant approval” system reducing registration time from 15 days to 1 hour),industrial synergies (e.g.,Anhuis “USTC Silicon Valley” integrating academia,industry,and policy),and digital platforms (e.g.,Zhejiangs “Tech Brain” database enabling dynamic profiling of 170000+enterprises).

Third,collaborative deepening: Foster cross-regional innovation networks through gradient collaboration (e.g.,R&D in the east,technology transformation pilots in central China,and industrial support in the west) and interprovincial coordination (e.g.,cross-regional joint due diligence committees) to mitigate redundant investments.

Mechanistically,the study advocates for long-term value incentives,including extended evaluation cycles (5-10 years for strategic sectors like semiconductors),milestone-based funding (e.g.,phased capital release for biotech clinical trials),and “fault-tolerant” mechanisms (e.g.,dual-track assessments for project-level and portfolio-level risks). By aligning state strategic resolve with market-driven resource allocation,GGFs can transcend their role as fiscal instruments to become sustainable “innovation catalysts”.

This research contributes to academic and policy discourse in three dimensions: First,the study enriches existing theoretical frameworks on unicorn cultivation by validating the proactive role of GGF in incubating regional unicorns,particularly the “leverage amplification” effects of regional differentiation and business environments. The study bridges a critical gap in existing scholarship,which has largely overlooked GGFs dual function as both direct financiers and indirect ecosystem catalysts.Second,leveraging the latest GGF investment data,the study comprehensively maps provincial-level disparities in GGF investment activity and sectoral allocation,thereby unveiling the socioeconomic value of “localized adaptation” strategies. The empirical evidence provides actionable insights for optimizing fund deployment,operational mechanisms,and risk-reward balancing,particularly in mitigating homogeneous investments and enhancing resource efficiency; This study also provides policy implications,findings empower policymakers to reconcile “national strategies” with “market principles”. On the one hand,GGFs should address market failures—such as early-stage financing gaps and prolonged exit cycles—through tailored policy tools (e.g.,extended investment horizons and milestone-based funding). On the other hand,market-driven mechanisms must be prioritized to invigorate innovation vitality while avoiding efficiency losses from administrative overreach. This dual imperative not only enhances fiscal efficacy but also serves as a cornerstone for Chinas “strategic overtaking” in global technological competition,enabling the nation to leapfrog entrenched industrial paradigms.

Youth entrepreneurship and employment have long been key topics for academics,policymakers,and society as a whole.The relationship between youth entrepreneurship and employment is interrelated,where entrepreneurial activities generate direct and indirect employment opportunities while stimulating economic growth.The post-pandemic era has intensified global economic uncertainty,disproportionately affecting youth employment.While entrepreneurship is recognized as a critical buffer for labor market instability,existing literature suffers three gaps,namely,overreliance on small-sample surveys,failure to account for dynamic shifts in entrepreneurial behavior,and focus primarilyon university graduates,paying limited attention to broader youth demographics.This study intends to address these gaps by integrating large-scale microdata and a multi-method framework to analyze youth entrepreneurships role in stabilizing employment.

This study leverages a dataset of over 200000 entrepreneurs (including>100000 youth aged ≤35) from Peking Universitys Online Survey of Micro and Small Enterprises (OSOME),spanning 2020 Q4-2024 Q3.A multi-method analytical framework was adopted for the subsequent investigation,including using ①descriptive statistics to outline demographic profiles and dynamic trends among young entrepreneurs,②K-means clustering to identify three subgroups based on age,gender,geography,education,and entrepreneurial tenure,and ③fixed-effects panel regression to examine the impact of economic shifts (e.g.,GDP fluctuations,policy adjustments) on youth entrepreneurship across 31 provinces over 16 quarters.

The key findings of this study include the following.First,in terms of  Demographic and Structural Trends,Chinese youth entrepreneurship exhibits distinct demographic patterns and structural shifts.Young entrepreneurs are predominantly male (76%),with a rising average age of 27.9 years and increasing educational attainment (average years of schooling rose from 12.6 to 13.5 over the observation period).Geographically, more than 50% are concentrated in southeastern coastal provinces(e.g.Guangdong, Zhejiang, Fujian) and tier-1 cities(Beijing, Shanghai, Shenzhen),aligning with regional economic opportunity gradients. At a sectoral level, service industry dominates throughout the observation period, while share of manufacturing sector declined over time, reflecting broader industrial upgrading trends.

Second,in terms of Subgroup Heterogeneity,Cluster analysis reveals three distinct youth entrepreneur subgroups: ①rural and high-school educated entrepreneurs (51.3%) who are predominantly located in rural and county-level areas with limited formal education; ②urban and highly educated professionals (30.6%) that are concentrated in cities,holding bachelors or advanced degrees; and ③mid-career,college graduates (18.1%) who are predominantly mature-age entrepreneurs leveraging prior work experience in their ventures.

Third,in terms of Operational Dynamics and Challenges,this study further reveals that young entrepreneurs face unique operational challenges compared to older counterparts.Their quarterly revenues are significantly lower,and cash flow volatility is more pronounced,heightening susceptibility to economic shocks.Their financing remains a critical barrier,characterized by “high demand,multi-channel reliance,and elevated costs.” Lastly,their policy engagement is uneven where only 43%~62% have had access to subsidies,credit,or tax relief,hindered by information asymmetry,bureaucratic complexity,and misaligned incentives.

Fourth,with regard to the policy “reservoir” function,the study shows that amid COVID-19 disruptions (2020 Q4-2021 Q4),youth entrepreneurship acted as a critical labor market “reservoir,” absorbing surplus workers as their share of total entrepreneurs surged from 60.55% to 71.14%.In particular,regression analyses underscore a dual relationship with macroeconomic conditions,where a positive relationship exists between youth entrepreneurship with growth indicates the latter is aligned with GDP expansion and a negative correllation,where pandemic-related restrictions temporarily suppressed entrepreneurial activity,revealing sensitivity to policy shocks.

Based on the above-mentioned key findings,the paper identified a number of policy gaps and proposed recommendations to address them.The primary challenges that confront youth entrepreneurs are sluggish post-pandemic consumer demand and rising costs.To address these gaps,four targeted pathways are proposed: ①Demand-side boosts: implement consumption incentives and infrastructure investment to stimulate market demand; ②Financial innovation: introduce risk-differentiated credit assessments and equity-based funding for early-stage ventures; ③Tax incentives: design progressive tax benefits tailored to capital-intensive sectors and nascent businesses; ④Precision targeting: provide differentiated support-capacity-building for rural/high-school educated entrepreneurs,innovation ecosystems for urban professionals,and transition assistance for mid-career switchers.

In summary,this study establishes the first systematic profile of Chinese youth entrepreneurs using microdata,validating entrepreneurships “reservoir” role in stabilizing labor markets during crises.Methodologically,it advances entrepreneurship theory through cluster analysis and dynamic modeling,revealing subgroup heterogeneity and environmental drivers.Policy-wise,the findings offer actionable solutions-such as demand-side stimulation,financial innovation,and precision targeting-to bridge systemic gaps in youth entrepreneurship.These recommendations align with Chinas national priorities of high-quality development and inclusive growth,providing empirical grounding for policies that enhance entrepreneurial resilience and economic adaptability.

With the increasing competition in the market and the rapid changes in the business environment,innovation has become one of the indispensable factors that determine the competitive advantage,return on investment,and long-term development of an organization.The attention that managers allocate to the topic of innovation determines the innovation of the firm.

In this paper,based on the Attention-based View of the Firm,we analyze the MD&A sections from the annual reports of all Chinese listed companies from 2009 to 2021.Using the Word2Vec algorithm,we construct a comprehensive and objective innovation dictionary,which allows us to calculate an indicator for top management team attention to innovation (TMTAI) and analyze its impact on corporate innovation inputs and outputs.To explore whether external environments affect the role of TMTAI in corporate innovation,we measure the innovation environment of each province from four aspects:infrastructure,human resources,technology market,and government system.This helps us construct an indicator for the innovation environment and analyze its influence on the relationship between TMTAI and corporate innovation.Lastly,we examine how TMTAI affects corporate performance and the specific mechanisms behind this impact,providing an in-depth understanding of its overall impact on corporate development.

Our empirical analyses reveal the following findings:① TMTAI positively impacts corporate innovation inputs,total innovation outputs,substantive innovation outputs,and strategic innovation outputs.② In an innovation-friendly environment,TMTAI has a stronger positive effect on innovation inputs,total innovation outputs,and strategic innovation outputs.However,the enhanced positive impact on substantive innovation outputs is insignificant.This may be because strategic innovation mainly involves improvements in product design,appearance,and usage,which are more susceptible to external support.In contrast,substantive innovation,involving new technologies,methods,or products,relies more on a companys internal technological reserves and innovation capabilities,thus receiving less external support.③ TMTAI positively affects future corporate performance with a lagged effect.Innovation inputs,total innovation outputs,substantive innovation outputs,and strategic innovation outputs partially mediate this impact,with innovation outputs playing a more crucial role in enhancing performance than innovation inputs.

Our study has three main innovations compared to previous research:① Using the MD&A text from annual reports,we construct an innovation dictionary via word embedding.This method is more objective,comprehensive,and efficient than manual word selection and has proven more robust.It offers a reference for building attention-related indicators and new ideas for applying machine learning in business research.②Unlike existing literature focusing solely on innovation inputs or outputs,we examine the comprehensive impact of TMTAI on innovation inputs,total innovation outputs,and different innovation outputs.We also explore the role of the innovation environment in the relationship between TMTAI and corporate innovation,providing insights into how external environments can better promote corporate innovation.③ We analyze the impact and mechanisms of TMTAI on corporate performance,expanding research on the economic consequences of TMTAI.

This study investigates the mechanisms through which Chinese listed firms use convertible bonds as a tool for indirect equity financing. Using a comprehensive sample of publicly issued convertible bonds from 2006 to 2022, we adopt a full life-cycle perspective—from issuance to delisting—to examine how firms employ convertible bonds to achieve equity financing goals, particularly when traditional equity issuance channels, such as private placements, face regulatory or market constraints.

We begin by identifying a significant substitution effect between convertible bond issuance and private equity placements. Following the regulatory tightening of private placements in 2017,the annual number of such issuances declined sharply,while convertible bond issuances surged in parallel. Conversely,when the regulatory environment eased in 2020,the trend reversed. This inverse relationship suggests that when private placements are restricted,firms tend to choose convertible bonds as an alternative financing instrument. To further test the hypothesis of convertible bonds being a tool for indirect equity financing,we evaluate the difficulty of conducting private placements by examining both market conditions and regulatory constraints. Empirical results indicate a significant negative correlation between the difficulty of private placements and the probability of convertible bond issuance,highlighting the conclusion that firms are more likely to issue convertible bonds when equity financing through private placements becomes less viable.

To ensure the successful conversion of convertible bonds into equity,firms often engage in strategic behavior,notably earnings management. We observe a statistically significant increase in upward earnings management in the periods prior to convertible bond delisting,which pushes stock prices above the price threshold required to exercise call provisions. This earnings management behavior disappears following the delisting of the convertible bonds,suggesting that such behavior is primarily intended to facilitate conversion.

Two contractual clauses are important in facilitating bond conversion: the downward adjustment clause and the call provision. When a firms stock price underperforms relative to the conversion price at a specific level,firms can exercise the downward adjustment clause to lower the conversion price,making conversion more attractive to bondholders and more likely to meet the call condition. Our analysis reveals that firms typically reduce conversion prices to just above the regulatory minimum—on average only 5% higher—suggesting that the clause is primarily used to promote conversion.

The call provision allows firms to force conversion once specific market conditions are satisfied—most commonly when the stock price exceeds 130% of the conversion price for a designated number of trading days. Under such circumstances,firms can redeem the bonds at a relatively low price,prompting rational investors to convert bonds into equity shares  to avoid financial loss. We find that 94% of convertible bond exits during the sample period were executed through call provisions,with an average conversion rate of 95%,emphasizing the effectiveness of this clause in achieving the equity financing goals.

Interestingly,despite strong incentives to achieve conversion,we document a widespread phenomenon of delayed calls after the conditions for calling are met. The average delay is approximately three months,and in more than half the cases,calls were postponed by over one month. Although this may appear inconsistent with the indirect equity financing hypothesis,further analysis reveals that such delays are often driven by the selling motivations of controlling shareholders and institutional investors. Immediate calls can lead to a sharp decline in bond value,as the option value disappears,and stock prices typically fall after conversion. To avoid such losses,these large investors can influence the timing of the call,allowing them to sell their bond holdings before the bond is called. This behavior benefits large shareholders at the expense of retail investors,highlighting an important agency issue in the convertible bond market.

Based on these findings,we propose three policy recommendations aimed at improving Chinas convertible bond market and its regulatory framework. First,the minimum conversion price should be raised,and the design of convertible bond terms should be refined. Although current regulations impose a lower limit on conversion prices,the presence of downward adjustment clauses gives firms too much flexibility to reduce them,undermining the hybrid nature of convertible bonds and turning them into simple equity issuance instruments. Second,earnings management practices related to convertible bond conversions should be more strictly monitored. Firms often manage earnings in the period prior to the bond delisting,misleading investors and distorting stock valuations. Third,regulatory oversight of call provision execution should be strengthened to protect retail investors. Under current rules,firms can freely determine the timing of calls,which can be exploited by controlling shareholders and institutional investors. Stricter and more transparent guidelines on call execution are necessary to reduce information asymmetry and ensure a fairer convertible bond market.

The rapid development of technologies like artificial intelligence (AI) and big data has driven the rise of marketing technology (hereafter,MarTech). By integrating advanced tools into marketing management,MarTech optimizes strategies,improves supply-demand matching,and enhances firms competitiveness. Its applications include real-time data analysis,intelligent forecasting,personalized marketing,and cost reduction. MarTech now extends beyond traditional marketing to support digital transformation across various industries,playing a crucial role in driving innovation and industrial optimization. This becomes more important with the increasing popularity of large language models (LLMs),which have been widely examined in recent literature related to market research enhancement,predictive accuracy,and content creation,as well as the impact of AI on sales and customer service. MarTechs complex ecosystem involves multiple stakeholders,such as platforms,merchants,and consumers,whose interactions shape market dynamics. Effective governance should balance these interests to ensure sustainable development,particularly in platform economies. Furthermore,the adoption of MarTech may widen the competitive gaps between large enterprises and small and medium-sized enterprises,while AI-generated products introduce new concerns regarding market efficiency. Furthermore,there is a need to design and implement effective governance policies to address the potential social equity issues arising from the application of MarTech. 

This paper focuses on the governance issues arising alongside the application of MarTech. To achieve long-term,sustainable growth,it is not enough to concentrate solely on the economic benefits of technological applications; we must also give deeper consideration to how market efficiency,fairness,and social welfare can be balanced. With the large-scale adoption of MarTech,a range of governance challenges have gradually surfaced,exposing potential issues in areas such as ethics,security,and social equity. At the micro level,consumer data privacy is a growing concern,with risks such as data-driven price discrimination and data misuse. At the firm level,algorithm designs and applications are expected to balance profits and social responsibility,mitigating the risks associated with biased data and model inefficiencies. At the macro level,new technologies are reshaping market structures,necessitating effective regulatory strategies. Through a systematic review and analysis of existing literature in related fields,both domestic and international,the study identifies research gaps and offers recommendations for sustainable MarTech development,highlighting the importance of fairness,transparency,and social responsibility within the digital marketing ecosystem.

Executive turnover and succession not only affect the personal career of executives,but also determine the stability and development of the entire organization.Since Grusky (1960) first placed succession under a more scientific and rigorous framework,relevant theoretical and empirical research has been abundant.In response,Finkelstein et al.(2009) systematically reviewed the research progress in this field over the past 50 years,and proposed future research directions in the form of 26 propositions.Yi et al.(2017) reviewed relevant studies from 2001 to 2016 and compared Chinese and Western literature,but did not propose new propositions.In the following seven years,the field has accumulated many new achievements.However,since Finkelstein et al.(2009),no studies have systematically examined the validation of their propositions,let alone proposed new propositions.This paper aims to fill these research gaps.

This research defines an executive as a member of the executive team who can influence the strategic decisions of the company,including the CEO and all executives at the level of vice president or above who report directly to the CEO (for example,COO,CFO,senior vice president,president,chairman,vice chairman,etc.).Since the whole process of turnover starts from resignation,this paper regards senior management turnover as the sum of turnover/departure and succession,which mainly involves three themes:first,senior management turnover is the premise for new executives to take office; Second,the succession process involves many issues such as the selection of succession methods and the characteristics of successors.Third,the effect of replacement.Based on the work of Finkelstein et al.(2009),this paper aims to systematically review the quantitative research results on executive turnover and succession in both Chinese and English from 2008 to 2024,test the validation of their propositions,and propose new propositions for future empirical exploration.Furthermore,17 new propositions are proposed in this paper to point out the direction for further research.Among them,the Chinese papers are derived from 85 of the National Natural Science Foundation,while the English papers cover FT50 journals.A total of 190 papers from 54 Chinese and English journals were ultimately selected.Among them,there are 31 Chinese journals with 78 papers,and 23 English journals with 112 papers.

On this basis,this paper first sorted out the antecedents and effects of CEO departure and succession.Subsequently,the antecedents and effects of non-CEO executive turnover were reviewed and compared with the CEO.This paper summarizes the antecedents of departure,dynamics of succession progress,and turnover effects of CEOs and non-CEO executives,covering multiple aspects such as compensation,performance,corporate governance,and the internal and external environment of the organization.Afterward,the research analyzes the particularity of executive replacement in state-owned enterprises and family enterprises in the Chinese context,and makes a comparative analysis of executive replacement studies in the Chinese and Western contexts:①First,Chinas research on state-owned enterprises and family enterprises is more abundant;②Some unique entry points are put forward in the discussion of the reasons before turnover and succession in the Chinese context,such as salary policy,director type,gender,etc.; ③Research on dimission and succession effects in China is more diversified,and also involves environmental governance behavior,internationalization,etc.; ④China pays more attention to the research on the replacement of TMT members.Among them,the research on non-ceos in China mainly focuses on CFOs.Finally,by comparing existing research deficiencies,future research directions were pointed out from six aspects:①diversify data sources and innovate research methods; ②Pay attention to the internal causes of departure and refine the types of departure and succession; ③Expand the boundary of effects and explore regulatory and mediating effects; ④Focus on the antecedents and effects of non-CEO executives turnover; ⑤Based on the Chinese context,provide inspiration for the development of management practice and theory; ⑥Combined with the background of The Times,explore the new characteristics of executive departure and succession.

The contributions of this research mainly include three aspects:First,in terms of research objects,this research covers both CEOs and non-CEOs,not just CEOs,breaking through the limitations of Yi  et al.(2017) in terms of research objects,so as to better highlight the team dynamics brought about by the interaction of executive team members.Second,this study reviewed and examined in detail the validation of Finkelstein et al.(2009) related propositions in subsequent studies.It not only updated the research results of recent years,but also proposed 17 new propositions based on the theory,which realized the integration of both time and proposition,and thus provided the direction for carrying out empirical tests.Third,it analyzes the particularity of executive turnover and succession in the Chinese context,and further improves and expands the classic analytical framework of executive turnover and succession by Finkelstein et al.(2009).

The rapid advancement of Industry 4.0 has prompted manufacturing firms worldwide—especially in emerging economies like China—to embrace high levels of automation in pursuit of greater efficiency,consistency,and scalability. While automation streamlines production and reduces dependency on manual labor,it also imposes new cognitive and coordination demands on frontline employees. In particular,unanticipated events such as peer turnover can destabilize these tightly coupled human-machine systems,raising critical questions about how automation interacts with organizational shocks to affect individual productivity over time. However,existing literature has yet to fully investigate the dynamic and contingent nature of this interaction. To address this gap,this study draws on Information Processing Theory (IPT) to examine how peer turnover influences employee performance under varying levels of job automation,and how workers recover from such disruptions.

Using a unique panel dataset from a leading heavy-equipment manufacturing firm in North China,we track monthly productivity data for 333 frontline employees across a 5-year period (2019—2023),yielding 7087 worker-month observations. This rich longitudinal design enables us to isolate and analyze productivity patterns before,during,and after peer turnover events. We adopt a mixed-effects discontinuous growth model to estimate short- and medium-term changes in productivity trajectories,and triangulate our findings through 18 semi-structured interviews with workers and supervisors to uncover the underlying mechanisms of disruption and adaptation.

Our empirical analysis reveals a U-shaped trajectory in employee productivity surrounding peer turnover. Specifically,productivity drops significantly in the month of a coworkers departure and begins a gradual recovery thereafter. This pattern is consistent with IPTs prediction that unanticipated organizational change temporarily exceeds employees information processing capacity,triggering performance setbacks until adaptation processes are activated. Importantly,our moderation analysis shows that job automation intensifies the negative effects of turnover and slows the pace of recovery. Workers assigned to highly automated production lines—characterized by rigid process interdependence,real-time system control,and limited task discretion—experience both a steeper decline and a more protracted rebound in performance compared to their counterparts in less automated roles. These findings challenge the prevailing view of automation as a stabilizing buffer against labor-related disruptions,and instead suggest that automation can amplify disruption effects by constraining adaptive flexibility and increasing information load.

The qualitative evidence supports these findings by identifying three key breakdowns in information processing during the post-turnover period. Firstly,task overload—remaining workers must absorb additional responsibilities without preparation,stretching their cognitive and physical capacity; Secondly,disrupted informal coordination—peer-to-peer knowledge exchange,tacit guidance,and situational troubleshooting diminish,hampering effective task calibration; Thirdly,low system transparency—automated systems often lack intuitive feedback channels,making it difficult for workers to interpret problems or adjust their behaviors in real-time. In highly automated contexts,these breakdowns persist longer and are harder to correct due to the inherent rigidity of the system and the limited affordance for improvisation. During the recovery phase,the three gradual adaptation mechanisms also take effect. Workers develop operational fluency,engage in trial-and-error learning,and collaboratively restructure task responsibilities within their teams. Yet these mechanisms unfold at a slower pace in automated environments,where employees have less room to experiment and reconfigure workflows.

This study makes three theoretical contributions. Firstly，It  extends Information Processing Theory by demonstrating how automation not only alters the structure of task execution but also reshapes the flow and burden of information processing during organizational transitions. Secondly,it introduces a dynamic and context-sensitive perspective to understanding the performance effects of peer turnover,highlighting the role of technological context as a key moderator. Thirdly,it contributes to the literature on socio-technical systems by detailing how automation conditions the interplay between human cognition,coordination mechanisms,and adaptive capacity. From a practical perspective,the study offers several implications for firms engaged in production automation transformation. Managers should recognize that automation does not uniformly mitigate disruptions,and may in fact increase organizational fragility in response to labor shocks. Therefore,firms should invest in modular task design,cross-functional training,and supportive automation systems that empower employees to respond flexibly to unexpected changes. Furthermore,organizations should prioritize building redundant communication channels and enhancing workforce-system integration to ensure resilience during critical personnel transitions. 

In summary,this study provides a comprehensive,data-driven exploration of how peer turnover interacts with automation to shape productivity dynamics on the factory floor. By integrating panel data econometrics with qualitative field insights,it advances theoretical and practical understanding of human adaptability in technology-intensive work settings. The findings hold broad relevance for researchers and practitioners interested in organizational resilience,workforce management,and the human implications of industrial automation in emerging markets.

With the rapid development of mobile Internet technology,online health communities (OHCs) have emerged and quickly become an important complement to traditional offline healthcare.These platforms allow patients to access medical advice,share experiences and interact with healthcare professionals from the comfort of their own homes.Online healthcare has significantly changed the traditional doctor-patient communication model,moving from in-person consultations to communication via text,voice,and other digital media.This shift in communication methods has raised important questions about how physicians can improve the quality of their services and increase patient satisfaction after consultations,making it a major focus of healthcare research.

This paper examines the factors that influence patients reciprocal behavior toward physicians,with a particular focus on the use of text and voice as communication media.Based on social support theory,a theoretical model is proposed to explore the determinants that drive patientsdecisions to reciprocate after a consultation.To analyze the voice data,the spectral centroid mean (SC) is used to measure the brightness of the sound,while the maximum consecutive voice messages are examined to assess the concentration and focus of the voice communication.In the case of text data,the number of emoticons is quantified as an indicator of the emotional expressiveness of the text,while the proportion of deterministic vocabulary is used to assess the degree of affirmation conveyed by the tone.In the empirical part,the research draws on a dataset that includes personal information and consultation data of doctors from a specific Online Health Community (OHC) platform,covering the period from January 2022 to June 2022.The dependent variable in this analysis is the patients decision to reciprocate,while the four aforementioned variables are treated as independent factors.In addition to the four independent variables mentioned above,we also introduce two types of control variables:one is the doctors personal information,and the other is the variable measuring the scale of doctor-patient interaction dialogues.

A logistic regression model is constructed to examine the impact of these variables on the likelihood of patients engaging in reciprocal behaviors.The results show that when physicians communicate via text,a more positive tone and increased use of emoticons significantly increase the likelihood that patients will reciprocate.In addition,when physicians send voice messages,speech that is more focused and has a brighter tone correlates with a higher likelihood that patients will engage in reciprocal behavior.These findings provide important insights into how different modes of communication can influence the dynamics of doctor-patient interaction in online healthcare environments.

From a theoretical perspective,this paper explores the various factors that influence both the transmission of information and the exchange of emotions in doctor-patient communication.By examining these dynamics,it aims to enrich and expand the scope of social support theory while uncovering the critical role and underlying influence mechanisms of communication media in online doctor-patient interactions.This research contributes to a better understanding of how digital platforms mediate the exchange of health information and emotional support and shape the overall experience.From a ctical management perspective,the findings of this study provide valuable insights and actionable guidance for physicians and online healthcare platforms.These conclusions can help optimize interaction strategies during consultations,fostering stronger and more positive doctor-patient relationships.Ultimately,such improvements will help improve overall service quality and patient satisfaction in the rapidly evolving online healthcare sector.