Abstract

Using a unique dataset comprising 6313 firm-year observations for Chinese listed firms between 2008 and 2017, we investigate the impact of CEO social capital on cost of debt. Our results show that CEO social capital is negatively related to cost of debt, and the impact of CEO social capital in environments with a low degree of marketization or social trust is more pronounced than in environments with a high degree of marketization or social trust. Moreover, our results reveal that two potential mechanisms, discretionary accruals and information disclosure quality, mediate the impact of CEO social capital on cost of debt.

Introduction

Research into social capital in the area of social economics emerged late last century (e.g., Coleman, 1988 ; Putnam, 1993 , Putnam, 1995 ; Knack and Keefer, 1997 ; Uzzi, 1997 ; Portes, 1998 ; Woolcock, 1998 ; Dasgupta, 2005 ; Fafchamps, 2006 ). Prior studies have acknowledged the significance of the personal social capital embedded in social networks for corporate commercial activities, including corporate financing ( Engelberg et al., 2012 ; Ferris et al., 2017 ; Huang and Shang, 2019 ; Jin et al., 2019 ), corporate investment ( Faleye et al., 2014 ; Fracassi, 2017 ), mergers and acquisitions ( Fracassi and Tate, 2012 ; El-Khatib et al., 2015 ), executive employment and compensation policies ( Hwang and Kim, 2009 ; Fracassi and Tate, 2012 ; Nguyen, 2012 ; Engelberg et al., 2013 ; Ferris et al., 2020 ), risk-taking and accounting practices ( Ferris et al., 2017 , Ferris et al., 2019 ; Panta, 2020 ), and litigation risk ( Zhang et al., 2023 ). Personal social capital embedded in social networks, especially the social capital of corporate executives, has a significant influence on corporate financing. Social capital enhances the trust between borrowers and lenders and increases risk-taking behavior as social capital is seen as an informal insurance. As invisible social credit and a conduit for the exchange of information, CEO social capital benefits corporate financing activities.

We are motivated to investigate the connect between CEO social capital and cost of debt due to the complex institutional background of network and the importance of debt financing in the context of China. Despite China’s remarkable economic growth in recent decades, its financial and legal environments remain underdeveloped. Allen et al. (2005) suggest that in order to sustain this growth, China requires alternative governance mechanisms and informal institutional arrangements. In the Chinese context, China is characterized as a relationship-based society, where social capital embedded in social networks, known as “Guan Xi,” holds significant prevalence and complexity. These networks provide Chinese additional social resources such as information and status ( Song et al., 2012 ; Bian, 2019 ). For example, the CEOs and chairmen of Chinese non-state-owned firms use bank loans to raise funds through their political contacts ( Yu and Pan, 2008 ). Loan approvals and covenants for Chinese corporates are influenced by CEO social capital ( Shen et al., 2009 ; Xu and Li, 2016 ). CEO social capital is negatively associated with firm leverage and short-term debt ratio, and social capital lowers the need for corporate bank borrowing ( Huang and Shang, 2019 ), and the social capital benefits improving the quality of corporate loans ( Jin et al., 2019 ). These studies only reveal the impact of managerial social capital on corporate financing, while the research into the impact of CEO social capital on the cost of debt is relatively scarce, particularly in emerging markets such as China.

Conclusion

This study investigates the relationship between CEO’s social capital and cost of debt. We posit that CEO’s social capital offers incentives for CEOs to provide enhanced information transparency and quality, which lowers the monitoring costs for the borrowers, inducing reduced cost of debt. Additionally, CEO’s social capital creates a sense of trust between the lenders and the borrowers due to the informal tie that social capital creates among the networks. Using a unique dataset consisting with 6313 firm-year observations from the firms listed on the Shanghai and Shenzhen Stock Exchange markets from 2008 to 2017, our results suggest that CEO’s social capital reduces cost of debt in the context of China, and such effect is more pronounced when there is a lack of information verification from the regulators (i.e., marketization) and societal norm (i.e., social trust). Moreover, we find that CEO’s social capital reduces cost of debt through the path of reduced discretionary accruals and information disclosure quality. Our results hold after a battery of robustness checks, including the three individual proxies (betweenness centrality, closeness centrality and degree centrality) for CEO social capital, the two alternative proxies for cost of debt, sample without political capital, excess social capital, the consideration of family business characteristics, the interactive effect of state-owned enterprises and endogeneity concerns.

Abstract

This study theoretically and empirically analyzes the impact and mechanism of corporate green transformation on accrual earnings management using a sample of China’s A-share listed companies from 2015 to 2021. The results indicate that the green transformation of enterprises helps restrain accrual-based earnings management, especially accrual-based earnings management, which increases profits, and that the inhibition effect of enterprise green transformation on earnings management is more significant in high-tech and growth-stage enterprises. The mechanism test shows that corporate green transformation can inhibit accrual-based earnings management by increasing analyst follow-up and easing financing constraints. Using China’s environmental tax law, promulgated in 2018, as an exogenous shock to construct the PSM-DID, the conclusion still holds after alleviating endogeneity. Further research has found that green transformations can also help inhibit real earnings management. This study provides new empirical evidence for a comprehensive understanding and evaluation of the governance role of corporate green transformation and provides a reference value for further comprehensively promoting the green transformation of Chinese enterprises and improving the quality of accounting information.

Introduction

With the continuous adoption of an extensive economic growth model in recent years, China has become the second largest economy in the world. However, this extensive economic growth has seriously damaged China’s environmental resources, making China’s total greenhouse gas emissions the highest in the world [1]. The green economy has always been an important tool for developing countries to achieve sustainable development [2]. Therefore, to avoid environmental degradation caused by greenhouse gas emissions and political pressure affecting sustainable economic development, the Chinese government has proposed a series of economic development strategies based on environmental protection.1 The Chinese government’s green development method of “promoting the construction of a resource-saving and environmentally friendly society” reflects the determination and attitude of the government in formulating and implementing new development policies during the transformation period of national economic development [3]. China’s listed companies have long been the main source of carbon emissions.2 Today, with increasingly serious environmental problems, the traditional “high carbon emission” development model of listed companies is unsustainable, and companies must choose a development path that takes into account both economic and environmental benefits [4], and green transformation can just become an important driving force for the sustainable development of the corporate economy [5]. Therefore, given the Chinese government’s vigorous promotion of the sustainable development of the green economy based on the “dual carbon” goal, the green transformation of listed companies has become a hot topic of concern in all walks of life.

Conclusion

Earnings management has always been a key issue in corporate governance and improving accounting information quality is an emerging market goal. As one of the most important forms of sustainable economic development in China, corporate green transformation has a governance effect on earnings management, and is worthy of study. This study selects A-share listed companies in China’s Shanghai and Shenzhen stock markets from 2015 to 2021 as the research sample and empirically tests the impact of corporate green transformation on accrual earnings management. The results were as follows:

First, there is a negative correlation between corporate green transformation and accrual-based earnings management, indicating that corporate green transformation effectively inhibits accrual-based earnings management. Simultaneously, corporate green transformation has a strong inhibitory effect on accrual-earnings management, which increases profits. After using the environmental protection “fee reform tax” policy issued by the Chinese government in 2018 to employ a PSM-DID analysis to alleviate endogeneity, the conclusion still holds after a series of robustness tests such as replacing explanatory variables and explained variables.

Abstract

     Parental control is widely considered to have a detrimental effect on children’s psychological development. However, it is commonplace and generally accepted in China and is intended to regulate children’s behavior. It is unclear whether Chinese parental control promotes or hinders children’s inhibitory control (IC) development. This study investigated the influence of maternal control on Chinese children’s development of IC using a longitudinal design (N = 163), with attention to the influence of children’s temperamental exuberance and different parenting contexts. Children’s exuberance (at 2 years of age) was assessed via laboratory observations. Maternal control (at 3 years of age) was coded during parent–child interaction in play-based and cleanup contexts. Children’s IC (at 3 years of age) was assessed by day–night and snow–grass tasks. Results suggested that maternal control in the play-based context was negatively related to IC development. The association between maternal control in the cleanup context and IC varied in children with different levels of temperamental exuberance. Specifically, maternal control in the cleanup context impeded low-exuberant children’s IC development but promoted it for highly exuberant children. These findings support the self-determination theory and the goodness-of-fit model and have implications for educational practice in China.

Introduction

     Parental control, which refers to parents’ efforts to intrude and redirect children’s thoughts, feelings, and behaviors, has received great attention for its effect on children’s social adjustment (Grolnick & Pomerantz, 2009). Parental control has invoked a variety of conceptualizations and operationalizations such as behavioral versus psychological control (e.g., Barber, 1996, Steinberg et al., 1989) and firm versus lax control (e.g., Fauber et al., 1990, Rowe, 1981). In the context of self-determination theory, Grolnick and Pomerantz (2009) refined multiple forms of parental control approaches and identified intrusiveness, which may violate children’s autonomy, as a core characteristic of parental control. The current study followed this conceptualization that parental control is parenting characterized by pressure, intrusion, and dominance regardless of whether it is used to regulate children’s thoughts or behaviors. Parents may be well-intended, but their controlling behaviors often do not contribute to children’s ability to regulate their own behaviors they originally intended (Grolnick, 2002). This may be because of the disrupting feelings of autonomy—children who are exposed to great parental control either are used to following their parents’ instructions and thereby lose their intrinsic motivation and regulatory ability or are resistant to their parents’ instructions and become rebellious (Grolnick, 2002).

Results

     In our sample, a child’s age was significantly correlated with exuberance (r = .25, p = .001) and was marginally significantly correlated with IC (r = .16, p = .056) and maternal control in the play-based context (r =
.15, p = .083). A sex (0 = boy, 1 = girl) difference was found in exuberance that girls were less exuberant than boys, t(161) = 2.35, p = .020, Cohen’s d = 0.37). Family income (1 = less than ¥5,000 to 4 = more than ¥30,000) was correlated with IC (r = .25, p = .003). No significant effect of age, sex, and family income was found on the other variables (ps > .26). Maternal education showed no significant effect on key variables (ps > .17). To avoid interference from the child’s age, sex, and family income, we conducted further analyses controlling for these variables.

     Correlations between primary variables are reported in Table 1. Maternal control in two contexts was significantly correlated. Temperamental exuberance did not show any significant correlation with maternal control in either context or IC.

Abstract

     We study financial reporting and disclosure practices in China using survey methods similar to prior studies of U.S. firms (i.e., Graham et al., 2005; Dichev et al., 2013). Comparing earnings features, motives to manage and smooth earnings, and voluntary disclosure practices between the two countries, we reveal three major differences. First, Chinese firms exhibit a stronger preference for predictive, relative to verifiable, attributes of earnings that can signal stable firm performance to their stakeholders. Second, smooth earnings are desired by various stakeholders and can be achieved through coordination among connected stakeholders, which is conceptually different from earnings management. Third, Chinese firms consider public disclosure as less relevant in the reduction of the cost of capital. In addition, Chinese firms do not have a bias towards conservative reporting. We explain and reconcile these differences as resulting from some unique institutional features of China. Our study provides novel field evidence that contributes to, expands, and directly corroborates existing empirical studies.

Introduction

     China’s economic significance has grown in recent decades, making it the second largest economy in the world. While China has continuously introduced new regulations to assimilate shareholder-driven practices of financial markets in the West, various institutional differences spanning cultural norms and socio-economic structures still play a considerable role in shaping the Chinese capital market. For instance, prior studies suggest that connections among many non-arm’s length stakeholders contribute to the functioning of capital markets in China (e.g., Ball et al., 2000; Allen et al., 2005; Wong, 2020). In this paper, we use a field-based survey approach to directly study how such institutional factors shape firms’ financial reporting and disclosure practices in China.

     A survey approach enables us to extend prior archival studies, providing evidence about unobservable coordination efforts and private communication channels among non-arm’s length stakeholders in China. While a series of surveys of CFOs at U.S. public firms have allowed academics to validate and reconcile findings on financial reporting and disclosure practices in the accounting and finance literature (e.g., Graham and Harvey, 2001; Graham et al., 2005; Dichev et al., 2013), these survey findings primarily reflect the financial reporting incentives of arm’s length shareholders. Our study extends this prior research by examining firm responses in China, where information demand is shaped by various stakeholders that are non-arm’s length. Moreover, our study complements the extensive archival literature on financial reporting and disclosure practices in China (Lennox and Wu, 2022).

Conclusion

     This paper provides novel field-based evidence on financial executives’ opinions and perceptions for financial reporting and disclosure practices in China. Chinese executives of public firms are directly asked about their incentives and the motives for their firms’ financial reporting and disclosure practices. Using financial executive opinions and motives at U.S. firms as a benchmark, we find that Chinese firms differ in what they consider as “high quality earnings”, in their motives for earnings management and earnings smoothing, and in their incentives to disclose bad news relative to good news voluntarily. Further field-based evidence suggests that these differences are primarily rooted in the institutional differences associated the dominance of retail investors, concentrated ownership structures, weak legal systems, and the role of diverse stakeholder groups – including arm’s length investors and non-arm’s length stakeholders.

     Our field evidence is consistent with a stakeholder-driven corporate governance model in China. Financial reporting is often considered as a vehicle to mitigate agency conflicts between firms and outside shareholders. The Chinese setting highlights that financial reporting may also have the important role of signaling stable performance to a variety of different stakeholders, including customers, suppliers, employees, and the government. Many of them constitute non-arm’s length stakeholders, and may have private communication channels with firms, which undermines the effect of public disclosures to mitigate agency problems. That is, public disclosure in China helps to signal the ability to coordinate among major stakeholders to maintain stable firm performance.

Abstract

Introduction

     Globally, COVID-19 pandemic has a significant impact on mental health. In Nepal, COVID-19 positive cases have to self-isolate at home in multi-generational and multi-family households. This could be strongly associated with depression, anxiety, and stress-related health outcomes. Additionally, COVID-19 related stigma and fear of transmission may intensify depression, anxiety, and stress symptoms. This study determined the prevalence of depression, anxiety, and stress symptoms and their association with presence of COVID-19 symptoms and comorbid conditions among home isolated COVID-19 positives in the Karnali province, Nepal.

Methods

     We conducted a cross-sectional study to assess depression, anxiety, and stress symptoms among 402 home isolated COVID-19 patients of Karnali province from January to May 2021 using “Depression, Anxiety and Stress Scale-21 (DASS-21)”. We interviewed patients to collect socio-demographic, DASS-21, COVID-19 symptoms, comorbid conditions, and self-treatment. We conducted a telephonic interview using a standardized questionnaire using Kobotoolbox. We calculated the prevalence of depression, anxiety, and stress symptoms. We utilized univariate and multivariate logistic regression to determine their association with the presence of COVID-19 symptoms and comorbid conditions. In multivariate logistic regression, we adjusted sociodemographic factors (age, gender, ethnicity, marital status, monthly family income, education level), smoking status and history of self-treatment. We reported adjusted odds ratios (aOR) with 95% confidence intervals. All analyses were conducted in R (version: 4.0.3).

Results

     The prevalence of depression, anxiety and stress symptoms among home isolated COVID-19 patients were 8.0% (95% CI: 5.5 to 11.1), 11.2% (95% CI: 8.3 to 14.7), and 4.0% (95% CI: 2.3 to 6.4) respectively. Higher odds of depression symptoms (aOR: 2.79; 95% CI: 1.08–7.20, p = 0.03), anxiety symptoms (aOR: 3.65; 95% CI: 1.57 to 8.52; p = 0.003) and stress symptoms (aOR: 7.41; 95% CI: 1.37 to 39.94; p = 0.02) were associated significantly with presence of COVID-19 symptoms in past week. Higher odds of anxiety symptoms were associated with the presence of comorbid conditions (aOR = 2.79; 95% CI: 1.05 to 7.44; p = 0.04).

Conclusion

     Depression, anxiety, and stress symptoms were present in a significant proportion of home isolated COVID-19 patients in western Nepal and positively associated with the presence of COVID-19 symptoms. In this global COVID-19 pandemic, it is important to provide timely counseling to high-risk groups like those with comorbidities and COVID-19 symptoms to maintain a high level of mental health among home isolated COVID-19 patients.

Introduction

     There is growing evidence that the current COVID-19 pandemic is causing severe mental health effects on people globally [[1], [2], [3], [4]]. Studies conducted globally found a positive association between mental health with the presence of COVID-19 symptoms [5] and comorbid status [6]. The COVID-19 pandemic spread throughout the globe, it instilled significant fear, worry, and concern in the general public, as well as in specific groups such as older individuals, caregivers, and those with underlying health issues [7]. The COVID-19 pandemic is likely to exacerbate social isolation and loneliness which are strongly associated with anxiety, depression, self-harm, and suicide attempts across the lifespan [[8], [9], [10]]. The misinformation from the media, lack of knowledge on COVID-19, lack of effective treatments, and significant economic losses may have resulted in higher levels of depression, anxiety, and stress during the COVID-19 pandemic [11,12]. Anxiety and depression might also be triggered by COVID-19 symptoms such as fever and shortness of breath [13]. Psychological trauma could result in a mixture of emotional surges like nightmares, self-blame, and experiencing recurrent thoughts of trauma [14]. COVID-19 has the potential to cause mental health crises with long-term consequences, particularly in Nepal [15].

Conclusion

     The prevalence of depression symptoms, anxiety symptoms, and stress among home isolated COVID-19 patients of Karnali province were common. They were positively associated with the presence of COVID-19 symptoms whereas anxiety symptoms with comorbid status. One key implication of this study is that, in this global COVID-19 pandemic, Nepal government should provide timely counseling and psychological support to those who are already affected with depression symptoms, anxiety symptoms and stress; and those under high-risk like those with comorbidities and COVID-19 symptoms to maintain a high level of mental health among home isolated COVID-19 patients.

Abstract

     Today, more and more enterprises are achieving co-innovation across borders by joining digital platforms. However, many SMEs face difficulties in developing and benefiting from strong digital platform capability (DPC) due to limited experience, resources, and funds, which hinders innovation opportunities. This study constructs a model to explore how SMEs can enhance their innovation performance (IP) by adopting digital platforms based on resource orchestration theory. We then introduce ecological institutional norms (EIN) as the moderating variable to observe whether effective platform governance impacts enterprises’ value co–creation (VCC) and IP. We conduct a questionnaire survey on 346 SMEs in China’s manufacturing industry that participate in digital platforms, and the regression analysis and the bootstrap test results indicate that (1) DPC has a significantly positive impact on IP; (2) DPC has a significantly positive impact on VCC; (3) VCC partially mediates DPC and IP; (4) EIN positively moderate the relationship between DPC and VCC and positively moderate the mediating effect of VCC. These findings add to the literature on digital platforms theoretically and fill the gap in research on how participation in digital platforms can enhance enterprises’ innovation and development from the perspective of SMEs. Finally, the study has important managerial implications for SMEs to cultivate DPC, carry out VCC, and participate in platform governance.

Introduction

     Innovation is a critical component for enterprises to take the leading edge and occupy a dominant competitive position in the market in the context of information technology development and industrial integration [1,2]. In the digital economy age, digital technology provides infrastructural support for economic development [[3], [4], [5]]. However, most small and medium–sized enterprises (SMEs) in China lack core technologies and the digital divide further increases the resistance to breaking through low–end lock–in. SMEs need to deeply integrate into the digital economy and explore new value growth points through digital process transformation and cross–border integration based on network effects. Therefore, digital platforms and the internal digital business ecosystem (DBE), which can break the boundaries of time, space, and organization with the support of digital technology, are gradually attracting attention [[6], [7], [8]]. Industry leaders such as Ali, Tencent, and Haier are trying to build digital platforms and DBEs to break organizational barriers and achieve technological collaborative innovation [9]. However, most of the current research on digital platforms is centered on large enterprises, with less attention given to SMEs [10,11].

     Resource orchestration theory suggests that static enterprise resources cannot meet the needs of enterprise development. Thus, the ability to allocate, integrate, and utilize resources is key to establishing a sustainable competitive advantage [12]. Joining a digital platform does not directly generate benefits: enterprises can only achieve efficient value creation when they actively and spontaneously allocate resources in a digital platform [[13], [14], [15]]. Based on the digital platform scenario, some scholars have pointed out that digital platform capability (DPC) involves combining the resources obtained by enterprises based on information and communication technology (ICT) with other internal and external resources [16]. A stronger DPC can enhance online communication, collaboration, and marketing for efficient and cost–effective resource expansion, which further increases the identification and integration opportunities of critical shared knowledge. It also facilitates enterprises to reallocate internal and external resources to flexible respond to rapidly shifting market environment [[17], [18], [19]]. However, due to the disadvantages in resources, capital, experience, and other aspects, SMEs’ cooperative innovation with other enterprises in the digital platform is often accompanied by risks such as leakage of core resources and misaligned partnerships [20,21]. As a result, many managers of SMEs are resistant and reluctant to join digital platforms. In light of these contradictions, some intriguing questions arise: Can SMEs actually benefit from digital platforms? How does DPC affect the innovation performance (IP) of SMEs?

Discussion

     This study proposes a moderated mediating model to explore the relationship between DPC and IP and how governance mechanisms in the DBE environment impact the above relationship. Focusing on SMEs, we collected 346 valid questionnaires, tested the theoretical assumptions using empirical analysis, and found some interesting conclusions.

     First, DPC has a significantly positive impact on SMEs’ IP. The result is consistent with resource orchestration theory, which proposes that the orchestration, combination, and flexible allocation of heterogeneous resources can help enterprises maintain their long–term competitive advantage [100]. This suggests that stronger digital platform integration capability enables SMEs to quickly access the large amount of heterogeneous resources aggregated in digital platforms [18] and to accelerate the speed of value feedback between subjects through digital channels [50], continuously optimizing the information quality on the platform. At the same time, we found that DPC positively influences VCC. Stronger digital platform integration capability can effectively monitor and evaluate data elements and strengthen the quality of plans developed jointly between subjects [72]; it can reduce the cooperation risk [71] and effectively promote the willingness of subjects to engage in joint problem solving; it can provide more critical information and promote the flexibility of SMEs to adjust their relationships with partners [16]. Stronger digital platform reconfiguration capability can reduce the cooperation cost [57] and enhance the willingness to engage in joint planning among platform subjects; it can optimize the allocation of platform resources [13] and improve the efficiency of cooperating subjects in joint problem solving; it can make platform subjects behave in a loosely coupled state [60] and promote enterprises’ flexibility and mobility to adjust existing cooperative relationships.

Abstract

Artificial Intelligence (AI) is taking centre stage in economic growth and business operations alike. Public discourse about the practical and ethical implications of AI has mainly focussed on the societal level. There is an emerging knowledge base on AI risks to human rights around data security and privacy concerns. A separate strand of work has highlighted the stresses of working in the gig economy. This prevailing focus on human rights and gig impacts has been at the expense of a closer look at how AI may be reshaping traditional workplace relations and, more specifically, workplace health and safety. To address this gap, we outline a conceptual model for developing an AI Work Health and Safety (WHS) Scorecard as a tool to assess and manage the potential risks and hazards to workers resulting from AI use in a workplace. A qualitative, practice-led research study of AI adopters was used to generate and test a novel list of potential AI risks to worker health and safety. Risks were identified after cross-referencing Australian AI Ethics Principles and Principles of Good Work Design with AI ideation, design and implementation stages captured by the AI Canvas, a framework otherwise used for assessing the commercial potential of AI to a business. The unique contribution of this research is the development of a novel matrix itemising currently known or anticipated risks to the WHS and ethical aspects at each AI adoption stage.

Introduction

Artificial intelligence (AI) has given rise to a new type of machine, a prediction machine, which can automate cognitive tasks traditionally associated with white-collar workers. These smart machines are lowering the cost and effort of making accurate predictions in operational processes. The AI technology may thus have potential benefits, such as increasing productivity, streamlining processes, and integrating value chains. Advocates of AI maintain that companies that do not take advantage of these benefits risk being driven out of the marketplace by others that do. As human expertise is being outperformed by AI, companies may prefer delivering their products and services, internally as well as externally, with the help of AI. The impact that such operational and logistical change in the workplaces may have on workers, however, remains uncertain.

Sociologists of work have long argued that workplace technologies are a key instrument of social change, reshaping labour relations and introducing new systems of worker discipline and control (Barley 1988; Braverman 1974; Kellogg et al. 2020; Zuboff 1988). From this critical sociological perspective, AI technologies in the workplace represent a new, contested domain for workers, raising questions around job security, worker autonomy, and worker status for which there is yet no clear social consensus. There is emerging research evidence on the qualitative impacts of AI on workers in specific industries, particularly insecure workers in the gig economy (Myhill et al. 2020; Convery et al. 2020). While the COVID-19 pandemic of 2020 has, at least temporarily, normalized flexible and remote work, many firms had already integrated complex, networked technologies integrating AI even before the pandemic to deliver products and services across borders and time zones, and to deploy skilled workers in more effective ways. The rise of networked technologies and “digital first” business strategy played out in the global economic context of increasingly precarious forms of employment, unequal wage growth, the transformation of manufacturing, and a growing income and skills divide in the workforce leading to reduced economic and social mobility. These outcomes are not inevitable, but are the result of personal, economic and political decisions (Srnicek and Williams 2016; Benanav 2020). Whether the new technologies adversely affect the security and wellbeing of employees in a workplace is above all a question of whether they are permitted to do so, or whether instead these risks are contained by regulation and oversight.

Conclusion

A growing use of AI will change economies, the manufacturing of goods and delivery of services. It will also affect human relations at a societal level, including how we collect, use fairly and keep safe the data that drive AI. Whilst much of the debate of the ethical use of AI has focussed on the societal level, AI also has profound implications in and for the workplaces where it is being used. These workplaces are currently and in most industrial and late-industrial nations regulated by WHS guidelines, rules and prescriptions, which rarely address the specific impact of AI on processes, job roles, and communication among employees, and between employees and managers.

In this paper, we have outlined a model for detecting risks and hazards that AI may bring to workplaces, using a set of AI Ethics Principles, as endorsed by the Australian Government, and the AI Canvas, a technical stages model of AI implementation. The explorative process commenced with a review of the literature on AI risks and hazards as they may apply to workplaces. These potential risks and hazards were further explored in consultation with AI experts, professionals and users—a process that also helped to populate the risk assessment matrix with examples of workplace specific AI risks and hazards. These risk examples were further developed and validated during consultations with AI adopters and WHS professionals. Each of these risks and hazards was linked to statutory WHS principles as advocated by SWA, the Australian WHS regulators and oversight agency.

Abstract

     This paper analyses US payroll share and components across states for the period 1977–2017. Findings include that spatial clustering in payroll shares decreased until the year 2000. States are clustered in low and high productivity groups. We relate this phenomenon to dualism. High labour productivity states featured high payroll shares early on, but now feature low payroll shares. We label this phenomenon decoupling of labour productivity from real wages. A Divisia Decomposition documents that Rust Belt states dominated the decline in US payroll share in the 1980s, whereas more recently large (coastal) states dominated. While we do not explain (potentially different) mechanisms, decoupling is apparent throughout.

Introduction

     The labour share of income is equivalent to the ratio of real wage and labour productivity. Its precipitous decline has led to a growing literature investigating underlying causes, not least since it illuminates interactions between labour incomes and technology. This paper provides novel evidence on the sources of the decline with a focus on spatial dimensions. We decompose the aggregate US payroll share – which excludes income from self-employment from compensation – by states for the period 1977–2017 and analyse its components from several angles. These state payroll shares are driven by the sectoral composition of each state’s economy, and therefore related to geographical factors and agglomeration effects. The former include endowments – a bay facilitating a port and transportation hub; the Bakken Formation facilitating an extractive boom – but the focus of the latter has been on the returns to density. These ideas build on Smith (1776), Marshall (1890) and Krugman (1991, 2011) and have been categorized as related to (1) reduced transportation costs, and improved flows of (2) labour and (3) ideas. More recently, such agglomeration economies have been critically examined in light of the ubiquity of information technology (Ellison et al., 2010; Giuliano et al., 2019; Glaeser & Gottlieb, 2009). The evidence suggests that agglomeration still matters in manufacturing, albeit less today than earlier; and that certain service activities crucially benefit from agglomeration due to (2) and (3). Throughout our analysis, we distinguish between (1) progressive and stagnant sectors and (2) states with (predominantly) progressive or stagnant sectors. In his seminal paper, Baumol (1967, p. 415) defines ‘technologically progressive activities in which innovations, capital accumulation, and economies of large scale all make for a cumulative rise in output per man hour’ (emphasis added).

Conclusion

     This paper investigates the decline of the US labour share by states. We conduct three exercises. First, a spatial Gini index illuminates regional patterns in payroll share changes. A key result is that spatial dependence of payroll shares decreased throughout the 1980s and 1990s. Further, spatial dependence is highest for manufacturing employment shares. The decline in spatial dependence occurs simultaneously with deindustrialization in (spatially clustered) Rust Belt states. Future research could investigate whether these results are robust to further disaggregation.

     Second, uni- and bivariate mixture models indicate that the distribution of labour productivity – but not that of real wages – across states has become increasingly dislocated. Our results support the hypothesis that labour productivity in US states differs in a statistically significant manner. Particularly bivariate mixture model results show that during the last two periods, states with higher labour productivity feature relatively low payroll shares, and vice versa. In the earlier periods, states with high labour productivity featured high payroll shares. This emerging dualism does not feature strong spatial clustering at the level of the state. Nevertheless, results appear consistent with recent literature on agglomeration economies (Ellison et al., 2010; Giuliano et al., 2019; Glaeser & Gottlieb, 2009).

Abstract

     Since the COVID-19 pandemic arrived, various options have been created to export products, with the creation and development of startups becoming a viable and significant option. Previous research has described the influence of competitive business advantage on international performance. However, the novelty of the current research was to evaluate the influence of the company’s capabilities, through the competitive advantage of the company as a mediator in international performance. The study was based on the responses of 200 active startups in Peru. The PLS-SEM technique was utilized with the company’s capabilities linked to internationalization processes as independent variables, as well as market intelligence, product innovation, and pricing. The mediating variable was competitive advantage, and the dependent variable was international performance. It was found that all three capabilities influenced competitive advantage and, ultimately, international performance. It was concluded that competitive advantage does not act as a mediator between pricing capabilities and the international performance of startups. Moreover, it was determined that competitive advantage acts as a mediator between two of the three assessed capabilities: market intelligence capabilities and product innovation capabilities. The results were supported by the reflective and formative evaluation of the results obtained through the applied technique. These results could help create better programs to promote startups interested in internationalizing and exporting products.

Introduction

     In the last 30 years, the resource-based theory (RBT) [1] has been shown as one of the most relevant for the description, explanation and prediction organization. It should be noted that RBT only took shape in the 1990s, because in the 1980s, theories were focused on the outside of organizations, such as Porter’s forces. In the first decade of the new century, the application of RBT could be supported in different disciplines. Today, RBT can be recognized as an influential approach in strategic management. The framework of RBT is composed of four elements: (a) value, (b) being rare, (c) immobility, and (d) sustainability. These are the characteristics that a company needs to have for the strategic planning reference and hold a sustained competitive advantage. The four conditions of RBT suggest that poor organizational policies, processes and procedures can weaken a resource’s potential competitive advantage.

     There is also the concept of dynamic capabilities (DC), which can be considered an extension of the resource-based view (RBV) because of its ability to respond to rapid technological changes. Although this concept was born at the end of the 1950s, it was through the publication of Teece, Pisano and Shuen [2] in 1997 that it gained prominence in strategic management. DC is defined as “the firm’s ability to integrate, build, and reconfigure internal and external competences to address rapidly changing environments” [2]. First of all, dynamic capabilities can be conceptualized as those meta-capabilities that give companies the ability to adapt to new changes and that at the same time can be specific to the company, i.e., very difficult to imitate. There are six functions that can be performed by DCs to enter a new market or position themselves more strongly in a market already won: renew, recombine, redeploy, replicate, retrench, and retire the resources/capabilities. With this, it can be identified that it is not only a matter of creating resources, but also of eliminating those that do not contribute to the creation of competitive advantage. There is no consensus on when to use DC, since on the one hand, it can be argued that it works well in a scenario of rapid changes, especially technological ones, but it can also be argued that in non-repetitive changes, its use is not advisable because it could be reconfiguring the company’s resources for a very short period, and its benefit could be minimal. The organization who possesses DCs can meet the change that is necessary to build a competitive advantage. Both RBT and CD contain elements that are crucial to a company’s competitive advantage. On the one hand, the value of the processes, products and services that an organization must have must be identified, understood and measured, so that it can be known why the company’s capabilities are valuable. Rarity is also identified, i.e., these capabilities are unique in the marketplace; it is also expected that they cannot be copied by competitors. Dynamic capabilities need the company’s continuous work to make them evolve to ensure that they remain rare and inimitable, achieving such a positioning that they are not substitutable.

Results

     As previously mentioned, we performed PLS-SEM to examine our hypotheses, for this, a bootstrapping was used of 5000 subsamples, this technique was performed used to estimate summary statistics, such as the mean or standard deviations, considering that it is the most approved setting for PLS-SEM [137]. As seen in Table 5, the capabilities of product innovation, marketing intelligence, and price are firmly related to the variable of competitive advantage; in other words, hypotheses H1, H2, and H3 are supported. Additionally, Table 5 shows that competitive advantage is also firmly connected to the international performance of startups; as a result, hypothesis H4 is also supported. The variance inflation factor (VIF), which was also examined to identify if our result has multicollinearity problems, demonstrates that it is not a problem between the exogenous latent constructs. Every VIF value that is not a problem is between 1 and 2, below 5. In the case of the R square values in Table 5, our model explained 29.2% of the competitive advantage variance and 16.2% of the international performance of the startups, which means that this model fits our data very well because the predictive relevance confirms the rule of thumb that says it must not be negative [137].

Abstract

     Numerous countries cut payroll taxes in response to COVID-19, including China, which reduced employer contributions by up to 21 percentage points. We use administrative data on more than 800,000 Chinese firms to evaluate payroll tax cuts as a business relief measure. We estimate that the tax cuts cover 31.5% of the decline in business cash flow, but labor informality causes 53% of registered firms-24% of aggregate economic activity-to receive no benefits at all. We quantify the targeting of the policy in terms of how much benefits flow to small firms less able to access external finance and to sectors worse hit by COVID-19. We find that (1) small firms and vulnerable industries are comparatively more labor intensive, which leads to desirable targeting; (2) labor informality worsens, but does not eliminate, targeting by firm size; and (3) labor informality is uncorrelated with the COVID-19 shock, and therefore does not affect targeting by sector.

Policy background

     In the mid- to late-1990s, China adopted a mandatory “pay-as-you-go” pension system, Basic Old Age Insurance (BOAI), for employed persons funded mainly through employer contributions (see Fang and Feng (2018) for a history of pension programs in China). Likewise, in the early 2000s, a medical insurance (MI) program for employed persons was established, also funded by payroll taxes (Huang, 2020). These two programs are the largest components of the SI system. As of 2019, the nationally prescribed employer contribution rate for BOAI and MI was 16 and 8% of wages, respectively. BOAI and MI also require employee-side contributions-8 and 2%-which are recorded in notional individual accounts that are efectively pay-as-you-go.

Discussion and conclusion

     Many advanced economies responded to the COVID economic shock with fscal policies unprecedented in both scale and form. In comparison, China’s response to COVID by way of additional spending and foregone revenue is moderate as a proportion of its GDP and more typical for developing countries.28 Its payroll tax cuts amounted to about 1.68% of 2020 GDP, whereas in the USA the Paycheck Protection Program alone delivered government support equal to 4.55% of 2020 GDP.29 China’s choice of policy instrument was also conservative: instead of launching novel spending programs, it temporarily reduced rates under an existing tax.

Abstract

     We analyze an unbalanced panel of monthly predictions of nonfarm payroll (NFP) changes between January 2008 and December 2020 sourced from Bloomberg. Unsurprisingly, we find that prediction quality varies across economists and we reject the hypothesis of equal predictive ability. In an error decomposition, we find evidence of significantly biased forecasts. Participation rate in the survey is affecting this bias. We find that survey participants under-predict job losses in times of market turmoil while also under-predicting the recovery thereafter, especially during the COVID19 labor shock. For prediction of NFP changes, autoregressive models are outperformed by a deep learning long short-term memory network. However, the consensus forecast yields better forecasts than model-based approaches and are further improved by combining the forecasts of the best performing economists. The COVID19 labor shock is shown to have adverse effects on the prediction performance of economists. However, not all economists are affected equally.

Introduction

     Nonfarm payroll (NFP) figures and monthly changes thereof are important and immediate indicators of the development of the economy in the U.S., particularly the labor market itself. Published by the Bureau of Labor Statistics (BLS) on a monthly basis, nonfarm payroll represents the number of payroll jobs and its month-to-month changes. The NFP covers most of the non-agricultural industry contributing roughly 80% of the GDP. As such, the monthly development in the labor market is an important precursor to the development and publication of other macroeconomic variables. Monthly NFP releases cause short- and medium term reactions to stock, bond, and FX markets which is documented in literature (Fleming, Remolona, 1999, Dungey, McKenzie, Smith, 2009, Dungey, Hvozdyk, 2012). The released numbers are perceived with a signaling effect, in particular when released numbers exceed or fall short of (market) expectations. Measuring and correctly quantifying these expectations—as for any micro- or macroeconomic variable—are of relevance in view of their impact and more importantly, their economic implications.

Concluding remarks

     We analyze an unbalanced panel of nonfarm payroll predictions from January 2008 to December 2020 from 181 forecasters. Based on the framework of Davies and Lahiri (1995), we decompose the forecasting error of each forecaster into three components, of which two are further studied. Firstly, we focus on the temporal shock component that affects all forecasters equally per forecasting period. These shocks, a general over- or under-prediction of all forecasters for a particular month represents a news effect where an under-prediction of job increases is considered a positive shock and vice versa. From these estimated shocks, we find that the sample of predicting economists under-estimate job losses in times of prolonged market turmoil. In addition, recovery phases are under-predicted as well, leading to positive shocks.

     In general, we find that the mean predictions are rather stable, causing the shock estimate to alternate regularly. Secondly, we focus on the individual bias, which describes a systematic over- or under-prediction of a particular forecaster. We find the bias of several forecasters to be statistically significant. More importantly, we find that with increasing participation rate, the individual bias is decreasing, yielding a lower prediction error. This indicates that economists that regularly make predictions are incorporating differing information sets than those with very few predictions. If we decompose the forecast errors based on a more precise measure for job market figures, the most recent publication, we observe a downward shift and a generally negative bias, underlining a tendency to under-predict true or more precise values of NFP changes. This suggests that forecasters make limited use of subsequent revisions of NFP changes and their focus remains on the initial and preliminary numbers. In view of the applied framework, we find that the impact of these revisions affects the temporal shock to a lesser extent than the individual bias.