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On the basis of labor economics theories, this study examines how adjustment in human capital accounts for labor cost stickiness.

This study makes use of employee education level as a measure of the quality of human capital and relies on data from Chinese public firms to conduct the empirical test. This study focuses on two important components of labor cost changes: one corresponding to the adjustment in the number of employees (capacity adjustment) and another corresponding to the adjustment in the mix of employee education levels (quality adjustment).

This study reveals that labor cost changes driven by the adjustment of employee education level are sticky. This stickiness cannot be explained by the standard adjustment cost theory. This further shows that firms that actively adjust their employee quality during downturns experience improved future performance. The findings are robust to alternative measures and specifications.

This study provides new evidence for and insights into the cost behavior literature. Previous studies treat input resources in a homogenous way and focus on the effect of capacity adjustment. This study considers the heterogeneity of resources and examines three dimensions of salary cost adjustment: capacity, structure, and unit cost. In line with the economic theory of sticky costs proposed by Banker et al. (2013a), the study’s evidence sheds light on the additional underlying economic mechanisms driving cost stickiness behavior. Specifically, managers asymmetrically adjust both employee structure and average salaries, in addition to employee number. This study also adds to the existing knowledge of the consequences of managers' actions regarding cost behavior.

Corporate site visits increase labor investment efficiency.

Our empirical model for the baseline analysis follows those of Jung et al. (2014) and Ghaly et al. (2020).

We show that corporate site visits are associated with significantly higher labor investment efficiency; more specifically, site visits reduce both over-hiring and under-hiring of employees. The effect of site visits on labor investment efficiency is more pronounced for firms with higher labor adjustment costs, greater financial constraints, weaker corporate governance and lower financial reporting quality. We also find that site visits mitigate labor cost stickiness.

First, while the literature has suggested how the presence of institutional investors and analysts may affect labor investment decisions, we focus on institutional investors and analysts’ activities and interactions with firm executives. We provide direct evidence that institutional investors and analysts may use corporate site visits to improve labor investment efficiency. Second, our study adds to a line of recent studies on how corporate site visits reduce information asymmetry and agency conflicts. We show that corporate site visits allow institutional investors and analysts to influence labor investment efficiency. We also provide new evidence that corporate site visits reduce labor cost stickiness.

A country’s institutional environment influences every facet of its business. This paper aims to identify institutional factors (state ownership, government attention on employment and employees’ educational background) that affect the asymmetric cost behavior in China.

Using 2,570 listed firms’ data between 2002 and 2015, we use empirical models to explore the effects of state ownership, government attention on employment and employees’ educational background on the asymmetric cost behavior in China.

This study found that the asymmetric cost behavior of central state-owned enterprises (CSOEs) is greater than local state-owned enterprises (LSOEs). Meanwhile, the empirical results show that government attention on employment is reflected in five-year government plans, and employees’ educational backgrounds are positively associated with asymmetric cost behavior.

This study contributes to the economic theory of sticky costs, institutional theory and asymmetric cost behavior literature by providing evidence that shows how government intervention and employee educational background limit the flexibility of corporate cost adjustments. Additionally, this study provides guidance to policymakers by showing how government long-term plans affect firm-level resource adjustment decisions.

This paper aims to examine the level of economic efficiency and factors that influence economic efficiency among seed potato producers in South-western Uganda.

The paper analyses the economic efficiency of 499 informal and 137 formal seed producers using primary data collected through a structured questionnaire. A multi-stage sampling technique was used to select the study sites and specific farmers. A one-step estimation procedure of normalized translog cost frontier and inefficiency model was employed to determine the level of economic efficiency and the influencing factors.

The results showed that mean economic efficiencies were 91.7 and 95.2% for informal and formal seed potato producers, respectively. Furthermore, results show significant differences between formal and informal seed potato producers in economic efficiency at a one percent level. Market information access, credit access, producers' capacity and experience increase the efficiency of informal while number of potato varieties, market information access and producers' experience increase economic efficiency for formal counterparts.

Most seed potato producers, especially the informal ones do not keep comprehensive records of their production and marketing activities. This required more probing as answers depended on memory recall.

Future research could explore panel data approach involving more cropping seasons with time variant economic efficiency and individual unobservable characteristics that may influence farmers' efficiency to validate the current findings.

The paper shows that there is more potential for seed potato producers to increase their economic efficiency given the available technology. This has a direct implication on the economy through increased investment in the production and promotion of high yielding seed potato varieties to meet the growing national demand for potatoes.

The paper bridges the gap in literature on economic efficiency among seed potato producers, specifically in applying the normalized translog cost frontier approach in estimating economic efficiency in the context of potato sub-sector in Uganda.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-10-2021-0641

This study aims to examine the impact of China's “Manufacturing and Internet Integration Development Pilot Demonstration Project” (MIP) policy on the digital transformation (DT) and labor structure optimization (LSU) of manufacturing enterprises, reveal the relationship between DT and LSU at the micro level and investigate the mechanism between them.

This study employs MIP as a quasi-natural experiment and develops a time-varying difference-in-difference (DID) model based on a sample of 2,445 Chinese A-share listed manufacturing enterprises in the Shanghai and Shenzhen markets from 2013 to 2021.

The implementation of MIP significantly increases DT by 0.4366 and optimizes LSU by 0.0507. By enhancing the two mediated variables of organizational learning inputs (SI) and employees' personal digital cognition (PDC), DT can optimize the LSU of pilot enterprises by 0.035 and 0.034, according to the results of the mechanism analysis. The study also reveals that the impact of MIP on LSU is highly heterogeneous. With effects of 0.0691 and 0.0632, the optimization effect is more pronounced in state-owned firms and firms with low ownership concentration, respectively.

This study demonstrates the dual effects of the MIP pilot on DT and LSU. In addition, this study pioneers research on the significance of optimizing the labor structure through SI and PDC on the basis of DT, which provides an empirical foundation for the Chinese Government to expand the scope of MIP pilots and revise policy content, as well as for manufacturing enterprises to upgrade the labor structure.

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.

Forced labour is one of the most exploitative practices in supply chains, generating serious human right abuses. The authors seek to understand how relationships for reducing forced labour are influenced by institutional logics. The emerging supply chain efforts of social enterprises offer particularly intriguing approaches, as their social mission can spur creative new approaches and reshape widely adopted management practices.

The authors study supplier relationships in the smartphone industry and compare the evolving practices of two cases: the first, a growing novel social enterprise; and the second, a high-profile commercial firm that has adopted a progressive role in combating forced labour.

The underlying institutional logic influenced each firm's willingness to act beyond its direct suppliers and to collaborate in flexible ways that create systematic change. Moreover, while both focal firms had clear, well-documented procedures related to forced labour, the integration, rather than decoupling, of forced labour and general supply chain policies provided a more effective way to reduce the risks of forced labour in social enterprises.

As authors’ comparative case study approach may lack generalizability, future research is needed to broadly test their propositions.

The paper identifies preconditions in terms of institutional logics to successfully reduce the risk of forced labour in supply chains.

This paper discusses how social enterprises can provide a learning laboratory that enables commercial firms to identify options for supplier relationship improvement.

The health of an economy is heavily dependent on the productivity of the economy's major industries including construction. While most macro-measures of productivity in the USA construction industry indicate a decline, corresponding studies at the individual task level indicate an increase in productivity. Therefore, this paper aims to identify areas where productivity challenges exist and thus provide recommendations for improvement in the construction industry.

A model that relates the way construction projects are executed with the sources of data that inform productivity analyses is developed and presented. This effort/value-flow model informs the data analysis that is performed to determine productivity trends for management and field labor. Further analysis for field labor productivity using field data and management productivity was separately conducted. Management productivity was particularly difficult to gauge, resulting in the use of surrogate measures.

It was observed that while both field labor and management productivities at the industry level have been decreasing, the decrease in management productivity was five times that of field labor productivity. A similar trend was observed for management productivity at the project level.

The primary contribution of this paper to the body of knowledge and industry is the introduction of a holistic analysis of USA construction productivity. Recommendations to improve management productivity include the use of technology, especially project management software.

Digital data acquisition is crucial for operations in the digital transformation era. Reality capture (RC) has made an immeasurable contribution to various fields, especially in the built environment. This paper aims to review RC applications, potentials, limitations and the extent to which RC can be adopted for cost monitoring of construction projects.

A mixed-method approach, using Bibliometric analysis and the PRISMA framework, was used to review and analyse 112 peer-reviewed journal articles from the Scopus and Web of Science databases.

The study reveals RC has been applied in various areas in the built environment, but health and safety, cost and labour productivity monitoring have received little or no attention. It is proposed that RC can significantly support cost monitoring owing to its ability to acquire accurate and quick digital as-built 3D point cloud data, which contains rich measurement points for the valuation of work done.

The study’s conclusions are based only on the Scopus and Web of Science data sets. Only English language documents were approved, whereas others may be in other languages. The research is a non-validation of findings using empirical data to confirm the data obtained from RC literature.

This paper highlights the importance of RC for cost monitoring in construction projects, filling knowledge gaps and enhancing project outcomes.

The implementation of RC in the era of the digital revolution has the potential to improve project delivery around the world today. Every project’s success is largely determined by the availability of precise and detailed digital data. RC applications have pushed for more sustainable design, construction and operations in the built environment.

The study has given research trends on the extent of RC applications, potentials, limitations and future directions.

This study aims to focus on the supply chain (SC) cost drivers of healthcare industries in the USA, as SC costs have increased 40% over the last decade. The second-most significant expense, the SC, accounts for 38% of total expenses in a typical hospital, while most other industries can operate within 10% of their operating cost. This makes healthcare centers supply-chain-sensitive organizations with limited facilities for high-quality healthcare services. As the cost drivers of healthcare SC are almost unknown to managers, their jobs become more complex.

Guided by pragmatism and positivism paradigms, a cross-sectional study has been designed using quantitative and deductive approaches. Both primary and secondary data were used. Primary data were collected from health centers across the country, and secondary data were from healthcare-related databases. This study examined the attributes that explain the most significant variation in each contributing factor. With multiple regression analysis for predicting cost and Student's t-tests for the significance of contributing factors, the authors of this study examined different theories, including the market-based view and five-forces, network and transaction cost analysis.

This study revealed that supply, materials and services represent the most significant expenses in primary care. Supply-chain cost breakdown results in four critical factors: facility, inventory, information and transportation.

This study examined the data from primary and secondary care institutions. Tertiary and quaternary care systems were not included. Although tertiary and quaternary care systems represent a small portion of the healthcare system, future research should address the supply chain costs of highly specialized organizations.

This study suggests methods that can help to improve supply chain operations in healthcare organizations worldwide.

This study presents an empirically proven methodology for testing the statistical significance of the primary factors contributing to healthcare supply chain costs. The results of this study may lead to positive policy changes to improve healthcare organizations' efficiency and increase access to high-quality healthcare.