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Prior work has shown that the board of directors can alleviate market imperfections that lead to capital investment inefficiency. The authors extend previous work by exploring how board characteristics influence the efficiency of human capital investment, a critical production factor that has remained insufficiently examined. Specifically, this study aims to investigate how board activity, size, the presence of a separate chairman, female directors and board independence affect firm labour investment efficiency in the European context.

The sample contains 4,331 firm-year observations traded on the STOXX® Europe 600 index from 2009 through 2022. This paper applies a lagged ordinary least squares (OLS) regression to test the proposed hypotheses. It also uses a dynamic panel generalised method of moments (GMM) regression to tackle potential endogeneity concerns.

The results show that board gender diversity and the level of independent directors are positively linked to labour investment efficiency, whereas board size and meeting frequency are negatively related to labour investment efficiency. Meanwhile, the presence of a separate chairman on the board does not appear to be significantly associated with labour investment efficiency. In additional subgroup analyses, the authors find that board gender diversity mitigates managers’ inclinations towards both overinvestment and underinvestment in labour. The authors also find that the level of independent directors helps greatly in reducing the underinvestment in labour, while it fails to attenuate the overinvestment in labour. Moreover, the authors find board size to be significantly associated with the tendency to make suboptimal labour decisions, manifesting as both overinvestment and underinvestment in labour. Finally, the results show that board meetings are significantly associated with overinvestment problems, while underinvestment problems seem to be unrelated to meeting frequency.

The empirical results have implications for policymakers and market participants in Europe. Firstly, firms may improve the efficiency of their labour investments by increasing directors’ independence and adding more female voices to corporate boards. Secondly, the evidence shows that some board attributes, such as board activity and size, do not necessarily have a beneficial impact on corporate decisions, particularly labour investment decisions. Finally, market participants are likely to benefit from this paper by understanding the role of board attributes in promoting the efficient allocation of firm resources.

This paper makes two significant contributions. Firstly, it extends the literature on the role of boards of directors in shaping corporate decision-making processes, particularly concerning human capital investment decisions within European firms. By doing so, the authors provide new evidence confirming that certain board attributes, such as board size, director independence and board gender diversity, are important for optimising firms’ resource allocation. Secondly, although numerous studies investigate boards’ role in capital investment decisions, relatively few empirical studies exist on the role of boards in labour investment decisions. This paper, therefore, tries to tackle this void in the literature by investigating firms’ decision-making concerning labour investments.

Digital transformation is a confidence booster in intrapreneurship, but few have examined its impact on intrapreneurship. Further, quantitative analyses exploring the impact of Chinese enterprises' digital transformation on intrapreneurship at the micro-level are rare. Most enterprises do not have the dividend for digital transformation, and few enterprises have successfully achieved digital transformation through intrapreneurship, internal management re-engineering and technological innovation. This study investigates the effect of digital transformation on intrapreneurship in Chinese real economy enterprises.

The study develops and tests a theoretical model that digital transformation impacts intrapreneurship by promoting working capital turnover and furtherly influencing labor input. Panel data of 1,638 Chinese-listed companies between 2007 and 2020 were used to complete the empirical test.

Digital transformation impacted labor input, with an inverted-U shaped relationship between the two, and labor input significantly stimulated intrapreneurship. This effect promoted labor input's impact on working capital. Chinese real economy enterprises generally increase labor investment to promote intrapreneurship. Heterogeneity analysis revealed that enterprises' asset scale and ownership attributes uniformly affected labor input.

This study provided empirical evidence of the promotional effect of real economy enterprises' digital transformation on intrapreneurship. Further, it advanced the literature by examining this relationship at the micro-level. Moreover, the data sample was long-term and included most industries, thus providing representative results with practical implications.

The study aims to investigate the impact of industrial robot application on corporate labor cost stickiness and labor investment efficiency in China.

Using the textual analysis to construct firm-level industrial robot application indicators in China, we implement the methodology in Anderson et al. (2003) and Banker and Byzalov (2014) to estimate cost stickiness.

We argue that the industrial robot uses in China would increase firms’ labor adjustment costs by increasing the employment scale and upgrading the employment structure (i.e. by employing more high-skilled and high-educated labor). Consistent with our expectation through the channel of labor adjustment costs, the use of robotics increases firms’ labor cost stickiness. We further find that the positive impact is more significant among labor-intensive industries, and among state-owned enterprises with lower labor adjustment flexibility. We also find that industrial robot uses do not decrease the labor cost stickiness even when robots are more likely to substitute labor. Finally, we find that industrial robot uses significantly facilitate more efficient hiring practices by mitigating overinvestment in labor (i.e. over-hiring).

Against the backdrop of intelligent manufacturing worldwide, our study sheds new insight into the effects of new technologies on corporate labor cost behavior in developing countries. We contribute to scant studies examining how robotics, AI adoption or other automation technologies (e.g. specialized machinery, software, etc.) affect corporate cost behavior.

This paper aims to assess the short- and long-run effects of the interaction between institutional quality and financial development (FD) on the competitiveness of the WAEMU economy over the period 2007–2018.

The methodology consisted of cross-referencing a synthetic indicator of FD with indicators of institutional quality and then estimating an auto regressive distributed lag model.

The results of the pooled mean group and dynamic fixed effect estimation show a positive and significant impact of this interaction on the competitiveness of the economy in the long run. In the short run, the results are quite similar to those in the long run for the direct effects but different for the crosses. Also, the analysis of country specificity shows that the results are similar to those in the short run since the interaction between FD and institutional quality (political stability and government effectiveness) negatively affects the competitiveness of Burkina Faso, Ivory Coast and Mali, and positively affects the competitiveness of Benin and Senegal.

These results suggest the need for effective policies to improve the quality of institutions to enhance the mobilization of financial resources through FD to ensure the competitiveness of economies. Improving the quality of the political and institutional environment is a prerequisite for economic competitiveness.

The paper is in line with the New Institutional Economics that developed in the 1970s. This referential framework is a heterogeneous body of work that encompasses works whose common point is the determination of the role of institutions in economic coordination. Unlike previous studies, which have focused on the contribution of the interaction between institutional quality variables and FD on economic growth, this paper analyzes the effects of this interaction on economic competitiveness. It, therefore, constitutes a contribution to this literature and aims primarily to fill this gap.

This research aims to investigate the relationship between knowledge capabilities, engagement capabilities, operational capabilities and sustainable supply chain flexibility in the steel production industry. In addition, it seeks to understand how these elements contribute toward achieving a net-zero supply chain, under the moderation of industry dynamism.

In total, 371 people have responded to the self-administered survey that the authors developed. The nonresponse bias analysis was carried out before diving into fundamental assumptions, such as homoscedasticity and normality. The data's reliability and construct validity were assessed by using confirmatory factor analysis. The hypothesized conclusions were supported by subsequent regression outputs, strengthening the body of existing academic research.

The research's empirical results highlight the positive relationship among knowledge capabilities, operational capabilities, sustainable supply chain flexibility and net-zero supply chain, particularly under the influence of industry dynamism. Information obtained from the steel production industry corroborates these findings. Moderation role of industry dynamism in the relationship between operational capabilities, engagement capability and sustainable supply chain flexibility was found significant.

This conceptual framework clarifies how knowledge capability, dynamic capabilities and the flexibility of a sustainable supply chain interact. It highlights how these factors collectively work together to attain a sustainable supply chain with net-zero environmental impact.

This paper aims to address the critical labor shortage in the food industry by exploring the potential of 3D food printing technology as a strategic solution. The study investigates how 3D food printing can enhance productivity, reduce labor costs, and offer innovative applications in various sectors of the food industry.

The research employs a comprehensive review of existing literature and case studies to analyze the current state of labor scarcity in the food industry and the technological advancements in 3D food printing. The paper also assesses the technical, operational, regulatory, and ethical challenges of 3D food printing and provides strategic recommendations for stakeholders.

3D food printing technology presents a viable solution by automating labor-intensive tasks, enhancing labor efficiency, and enabling customized food production. The technology’s potential benefits include improved productivity, reduced operational costs, and the ability to meet personalized nutritional needs. However, the adoption of 3D food printing faces challenges such as high initial costs, maintenance requirements, and scalability issues. Additionally, regulatory and consumer acceptance hurdles need to be addressed.

Policymakers are encouraged to support the development and adoption of 3D food printing through funding and clear regulatory frameworks. Business leaders should consider strategic investments in 3D printing technology and training programs to harness its benefits. Technology developers must focus on advancing the capabilities and user-friendliness of 3D food printers. Addressing these aspects can help the food industry overcome labor scarcity and achieve long-term sustainability and efficiency.

This paper provides a comprehensive analysis of 3D food printing technology as a strategic response to labor scarcity in the food industry. It contributes to the existing body of knowledge by highlighting the potential of 3D food printing to revolutionize food production and offering practical recommendations for its adoption and integration.

The sustainability of the construction industry is associated with the productivity, profitability and competitiveness of the firms, which are significantly affected by inefficient site supervision and labour management approaches. This study aims to use a case study with mixed methods to evaluate the site supervisory characteristics in labour management, labour performance assessment and labour productivity measurement towards developing meaningful guidelines in polishing construction supervision attributes.

Well-developed modern apprenticeship elements were applied to 62 construction supervisors who were selected using the snowball sampling method, and their relevant competency characteristics were assessed using a comprehensively developed grading mechanism connected with useful training manuals/tools. Academic reviews, experts’ consultations and other meticulous mixed approaches were applied at different stages of the research plan’s sequential layout.

The mean performance scores of supervisors indicate proficient-level grades in the competency characteristics related to applying efficient labour management procedures and developing-level grades in designing productivity measurement tools, performing assessments on efficiency and productivity and proposing enhancement practices on efficiency and productivity for site operations. The findings point to a modern generalised guideline that establishes the ranges of supervisory attributes within the scope of the study. The validity, reliability, adaptability and generalisability of the findings were assured by using pertinent statistical tests and professional assessments.

Though the study’s conclusions/findings are primarily applicable to the construction environment of a developing country comparable to the Sri Lankan context, they will considerably impact current/future industrial practices in various other countries and emerging industries.

The research has produced a conceptualised modern tool that guides determining the capacity levels of supervisory attributes for carrying out labour management, labour performance assessment and labour productivity measurement aspects in construction. The research has opened a pump that inflows new values of highly workable supervision features for strengthening the site management structures and filling the industry’s knowledge vacuum in the methodical execution of apprenticeships.

This study aims to explore the spatial impact of an increase in the minimum wage on the labor productivity of star-rated hotels in China.

The impact is analyzed by using the dynamic spatial Durbin model.

The authors find a U-shaped link between the increase in minimum wage and labor productivity of star-rated hotels. The long-term impact of a minimum wage increase has a greater influence on labor productivity than its short-term effects. While there is no notable spatial spillover impact observed in the sample of 31 provinces in China, the authors do identify a spatial spillover effect of the minimum wage rises on the labor productivity of star-rated hotels in the central area. Furthermore, they observe heterogeneity across China. The eastern and western regions exhibit a U-shaped relationship, whereas the central region exhibits an inverted U-shaped relationship.

The findings of this study allow government agencies to get a more comprehensive comprehension of the actual consequences of minimum wage hikes on the tourism and hospitality sector, thereby establishing a solid basis for them to develop appropriate policies. Moreover, it offers a variety of suggestions aimed at enhancing the quality and efficiency of hotel management.

Research on the effects of minimum wage standards is scant in the hospitality industry. Based on human capital investment theory, this study examines the effect of the minimum wage standard hikes on labor productivity of star-rated hotels from the spatial perspective, filling the existing research gap.

This study aims to clarify the direct impact of digitalization on export performance (EP) by synthesizing previous research and testing this relationship empirically. Furthermore, the study investigates digitalization types, contextual moderators and method moderators affecting the impact of digitalization on EP.

The study uses meta-analysis to test the digitalization–EP relationship (k = 81) using data from 106 independent samples involving 62,082 respondents across nearly 30 countries.

The study finds digitalization’s positive and significant effect on EP (r = 0.36). The impact of digitalization on EP is also subject to different moderators, including digitalization type (i.e. digital capabilities), contextual factors (i.e. institutions, export experience, development of the region and industry) and method factors (i.e. back translation and strategy measurement).

Scholars have initiated studies on the impacts of diverse digitalization types on EP, while empirical findings on these effects remain inconclusive. Based on resource-based theory, the study develops and validates a comprehensive meta-analytic framework, revealing the important influence of digitalization on EP. The moderator findings further highlight the impact of internal and external contingencies on the outcomes of exporting firms’ digitalization.

This study investigates the relationships among digital transformation, technological innovation, industry–university–research collaborations and labor income share in manufacturing firms.

The relationships are tested using an empirical method, constructing regression models, by collecting 1,240 manufacturing firms and 9,029 items listed on the A-share market in China from 2013 to 2020.

The results indicate that digital transformation has a positive effect on manufacturing companies’ labor income share. Technological innovation can mediate the effect of digital transformation on labor income share. Industry–university–research cooperation can positively moderate the promotion effect of digital transformation on labor income share but cannot moderate the mediating effect of technological innovation. Heterogeneity analysis also found that firms without service-based transformation and nonstate-owned firms are better able to increase their labor income share through digital transformation.

This study provides a new path to increase the labor income share of enterprises to achieve common prosperity, which is important for manufacturing enterprises to better transform and upgrade to achieve high-quality development.