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This study investigates the impact of large-scale teaching in higher education on students’ preparedness for the workforce within the context of evolving labour market demands, the expansion of higher education and the application of high-impact teaching strategies. It synthesizes perspectives on employer work readiness, the challenges and opportunities of large-scale teaching and strategies for fostering a dynamic academia-industry feedback loop. This multifaceted approach ensures the relevance of curricula and graduates’ preparedness while addressing the skills gap through practical recommendations for aligning teaching methodologies with employer expectations.

The research methodically examines the multifaceted challenges and opportunities inherent in large-scale teaching. It focuses on sustaining student engagement, maintaining educational quality, personalizing learning experiences and cultivating essential soft skills in extensive student cohorts.

This study highlights the critical role of transversal skills in work readiness. It also uncovers that despite its challenges, large-scale teaching presents unique opportunities. The diversity of large student groups mirrors modern workplace complexities, and technological tools aid in personalizing learning experiences. Approaches like peer networking, innovative teaching methods, real-world simulations and collaborative resource utilization enrich education. The importance of experiential learning for augmenting large-scale teaching in honing soft skills is emphasized.

This manuscript contributes to the discourse on large-scale teaching, aligning it with employer expectations and the dynamic requirements of the job market. It offers a nuanced perspective on the challenges and opportunities this educational approach presents, providing insights for crafting engaging and effective learning experiences in large cohorts. The study uniquely integrates experiential learning, co-creation in education and industry-academia feedback loops, underscoring their importance in enhancing student work readiness in large-scale teaching.

This chapter reviews the econometric approaches typically used to deal with the spike of zeros when modelling non-negative outcomes such as expenditures, income, or consumption. Relying on the assumptions of selection on observables for evaluating a policy or treatment, this chapter discusses other issues that arise with spikes of zeros in the data, including the analyst's choice between full information versus quasi-likelihood methods, considering whether observed zeros are true or masking more complex behavioural decisions, and dealing with zeros that arise due to self-selection. This chapter ends with discussions of empirical strategies to deal with these behavioural assumptions and a brief review of the literature where such strategies were employed.

Humane Entrepreneurship (HumEnt) is strongly purpose-oriented and characterized by a focus on inclusiveness and social and environmental sustainability, with attention to both internal and external stakeholders and their needs. In the attempt to provide new research in this field, this study aims to conduct an empirical investigation within the theory of HumEnt and, in particular, of the Human Resource Orientation (HRO) model among Italian Small and Medium-size Enterprises.

Based on quantitative data, this study used a deductive approach to investigate the relationship between the HumEnt model and firms’ relational embeddedness with different types of stakeholders (value chain stakeholders and societal stakeholders, respectively). More concretely, to investigate the relationships between the dimensions of the HumEnt model and firms’ relational embeddedness, partial least squares structural equation modeling was applied.

Findings of this study suggest that Entrepreneurial Orientation (EO) directly contributes only to value chain embeddedness. However, the results also show that if EO is mediated by an HRO (i.e. companies with a high HRO), a high level of societal embeddedness is also present.

This study represents a first attempt to provide comprehensive empirical evidence about the different dimensions characterizing the HumEnt theoretical model, and to highlight their relevance in supporting companies’ relational embeddedness capacity with different categories of stakeholders.

We seek to quantify the relationship between urbanization and economic growth in China using recent advances in econometric techniques.

This study adopts a smoothed instrumental variables quantile regression (SIVQR) estimator to obtain consistent estimates of the effects of urbanization on economic growth in China. Our approach accounts for the differential impacts of urbanization across the conditional distribution of economic growth while allowing for an identification strategy that addresses the endogeneity of urbanization. Our main findings reveal that ignoring urbanization endogeneity leads to inconsistent estimates of urbanization effects. Further, we find a positive relationship between urbanization and growth resembling an inverted U-shape. This supports the hypothesis that the beneficial effects of urbanization intensify at initial stages while diminishing beyond a certain threshold, due perhaps to weakening scale economies.

Our main results indicate that the individual productivity gains brought by urbanization outweigh the negative effects thereof that impede productivity, thus contributing to the economic growth in China. Further, we find that ignoring differential impacts of urbanization underestimates the beneficial effects of urbanization for provinces whose quality of governance is in the vicinity of the center of quality distribution. Ignoring the endogeneity of urbanization generates inconsistent estimates of the elasticity of economic growth with respect to urbanization. Finally, we estimate an inverted U-shape resembling relationship between urbanization and growth.

First, future studies would benefit from incorporating more data as provinces further east on the mainland become more urbanized and urbanization runs its course. Second, controlling the barriers to rural-urban mobility would contribute to the robustness of the estimated relationship between urbanization and growth once such data became available. Unveiling the impact of government-imposed barriers is key to designing optimal policies that help fuel economic growth in the country. Finally, future research could benefit from information on urbanization sources not considered here such as inter-provincial migration, as such data become publicly available.

Quantifying the beneficial effects of urbanization on economic growth can help guide the government in China to further fuel the growth through a set of relevant policy tools that promote urbanization.

Rural-urban migration in China lays the groundwork for economic advancement in recipient cities and economies, as it may induce scale economies. This can benefit both the economy at large and the migrants.

The SIVQR estimator accounts for potential heterogeneous effects of urbanization across the entire conditional distribution of growth while allowing for an identification strategy that addresses the endogeneity of urbanization. An additional distinguishing feature of the current study is our use of the most recent novel, provincial-level data obtained from the National Bureau of Statistics of China. Our focus on a single country allows sidestepping issues arising from the inconsistency of the definition of urban across different countries while accounting for intra-country urbanization drivers intrinsic to China, such as natural features and geographic characteristics. Therefore, our approach has the potential to sidestep the bias resulting from the differences in mechanisms behind urbanization-growth relationships across different countries.

This paper aims to analyse the influence of board characteristics on corporate reputation.

In total, 128 Brazilian publicly traded companies from Refinitiv Eikon were analysed between 2016 and 2020. The dependent variable was corporate reputation, whereas the independent variables were board size, gender diversity, board independence and audit committee presence. Multivariate analysis was used.

The results presented empirical evidence that board members can impact corporate reputation. Findings showed that board size, gender diversity and independence positively influence Brazilian companies’ corporate reputation. Conversely, an audit committee had no significant impact on corporate reputation.

The paper presents a contribution to the significance of board members in shaping a company's corporate reputation, using the signalling theory and the resource-based view (RBV) theory.

Regarding practical implications, this work provides subsidies for managers to value board characteristics because they directly reflect on corporate reputation and competitive advantage, leading to more sustainable performance.

The research findings highlight that a diverse board encourages the organisation to improve its workforce, human rights, relations with the community and responsibility for manufactured products.

The relationship between board characteristics and corporate cooperation is poorly established in the literature. Furthermore, the results prove the RBV theory in an emerging context. Similarly, the signalling theory proved helpful in improving Brazilian firms’ corporate reputation.

The purpose of this mixed-methods study was to explore how medical secretaries experience digital transformation in a Swedish healthcare organisation, with a focus on workplace climate and health.

Data were collected using a sequential exploratory mixed-methods design based on grounded theory, with qualitative data collection (a Quality Café and individual interviews) followed by quantitative data collection (a questionnaire).

Four categories with seven underlying factors were identified, emphasising the crucial need for effective organisation of digital transformation. This is vital due to the increased knowledge and skills in utilising technology. The evolving roles and responsibilities of medical secretaries in dynamic healthcare settings should be clearly defined and acknowledged, highlighting the importance of professionality. Ensuring proper training for medical secretaries and other occupations in emerging techniques is crucial, emphasising equal value and knowledge across each role. Associations were found between some factors and the health of medical secretaries.

This study adds to the knowledge on digital transformation in healthcare by examining an important occupation. Most data were collected online, which may be a limitation of this study.

Several aspects of the medical secretaries’ experiences were identified. Knowledge of these is valuable for healthcare managers to make digital transformation more effective while avoiding excessive strain on medical secretaries.

Medical secretaries are expected to contribute to the digitalisation of healthcare. However, minimal research has been conducted on the role of medical secretaries in workplace digitalisation, focusing on workplace roles and its dynamics.

Coordinating low-carbonization and digitalization is a practical implementation pathway to achieve high-quality economic development. Regions are under great emission reduction pressure to achieve low-carbon development. However, why and how regional emission reduction pressure influences enterprise digital transformation is lacking in the literature. This study empirically tests the impact of emission reduction pressure on enterprise digital transformation and its mechanism.

This article takes the data of non-financial listed companies from 2011 to 2020 as a sample. The digital transformation index is measured by entropy value method. The bidirectional fixed effect model was used to test the hypothesis.

The research results show that emission reduction pressure forces enterprise digital transformation. The mechanism lies in that emission reduction pressure improves digital transformation by promoting enterprise innovation, and digital economy moderates the nexus between emission reduction pressure and digital transformation. Furthermore, the effect of emission reduction pressure on digital transformation is more significant for non-state-owned, mature and high-tech enterprises.

This paper discusses the mediating role of enterprise innovation between carbon emission reduction pressure and enterprise digital transformation, as well as the moderating role of digital economy. The research expands the body of knowledge about dual carbon targets, digitization and technological innovation. The author’s findings help update the impact of regional digital economy development on enterprise digital transformation. It also provides theoretical guidance for the realization of digital transformation by enterprise innovation.

As a disruptive technology, blockchain technology brings new opportunities and challenges to operations management. We aim to examine the influences of blockchain cooperation project announcements (BCPAs) on firms’ stock market reactions in an emerging market. From 2016 to 2021, a total of 113 BCPAs of listed firms from the Chinese A-share market are selected as samples.

This study is based on the loose coupling theory and uses the event study method and probit regression analysis.

We find BCPAs positively affect the firm’s stock price on the day they are released. Compared with vertical BCPAs in a supply chain, horizontal BCPAs exert a more positive market reaction. Moreover, a BCPA with a partner within a shorter geographical distance exerts a more positive influence on market reaction. Contrary to the intuition of the decentralized blockchain feature that one-to-many cooperation leads to better benefits, one-to-one BCPAs exert a more positive effect on market reaction than one-to-many BCPAs. We further find that (1) industry type has a certain impact on cooperation mode selection, and (2) manufacturing firms are more inclined to choose one-to-one cooperation than those in service industry.

We focus on the impact of blockchain cooperative announcements and additionally use the probit regression models to analyze the influencing factors of cooperation mode selection and find the critical role of the industry type, which complements the existing empirical research on blockchain announcements and is conducive to provide decision-making reference for managers.

In order to improve the efficiency and reliability of simulation analysis for composite riveting structures in engineering products, a comparative study was conducted on different forms of riveting simulation methods.

Five different rivent simulation models were established using the finite element method, including rigid element CE, flexible element Rbe3 and beam element, and their results were future compared and analyzed.

Under the given technical parameters, the simulation method of Rbe3 (with holes) + beam can meet the analysis requirements of complex engineering products in terms of the rationality of rivet load distribution, calculation error and relatively efficient modeling.

This study proposes a simulation method for the riveting structure of carbon fiber composite materials for engineering applications. This method can satisfy the simulation analysis requirements of transportation vehicles in terms of modeling time, computational efficiency and accuracy. The research can provide technical support for the riveting process and mechanical analysis between carbon fiber composite components in transportation products.

The purpose of this study is to provide new insights into the relationship between fiscal policy and total factor productivity (TFP) while accounting for several economic and econometric issues of the phenomenon like non-stationarity, fiscal feedback effects, persistence in productivity, country heterogeneity and unobserved global shocks and local spillovers affecting heterogeneously the countries in the sample.

The paper is empirical. It builds an Error Correction Model (ECM) specification within a dynamic heterogeneous framework with common correlated effects and models both reverse causality and feedback effects.

The results of this study highlight some new findings relative to the existing related literature. The outcomes suggest some relevant evidence at both the academic and policy levels: (1) the causal effects going from fiscal deficit/surplus to TFP are heterogeneous across countries; (2) the effects depend on the time horizon considered; (3) the long-run dynamics of TFP are positively impacted by improvements in fiscal budget, but only if the austerity measures do not exert slowdowns in aggregate growth.

The main originality of this study is methodological, with possible extensions to related phenomena. Relative to the existing literature, the gains of this study rely on the way econometric techniques, recently proposed in the literature, are adapted to the economic relationship of interest. The endogeneity due to the existence of reverse causality is modelled without implying relevant performance losses of the models. Moreover, this is the first article that questions whether the effects of fiscal budget on productivity depend on the impact of the former on aggregate output growth, thus emphasising the importance of the quality of fiscal adjustments.