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Management practices and manufacturing firm responses to a randomized energy audit
Increasing the efficiency of industrial energy use is widely considered important for mitigating climate change. We randomize assignment of an energy audit intervention aimed at improving energy efficiency and reducing energy expenditures of small- and medium-sized metal processing firms in Shandong Province, China, and examine impacts on energy outcomes and interactions with firms’ management practices. We find that the intervention reduced firms’ unit cost of electricity by 8% on average. Firms with more developed structured management practices showed higher rates of recommendation adoption. However, the post-intervention electricity unit cost reduction is larger in firms with less developed practices, primarily driven by a single recommendation that corrected managers’ inaccurate reporting of transformer usage at baseline, lowering their electricity costs. By closing management-associated gaps in awareness of energy expenditures, energy audit programmes may reduce a firm’s unit cost of energy but have an ambiguous impact on energy use and climate change.
Skill dependencies uncover nested human capital
Modern economies require increasingly diverse and specialized skills, many of which depend on the acquisition of other skills first. Here we analyse US survey data to reveal a nested structure within skill portfolios, where the direction of dependency is inferred from asymmetrical conditional probabilities—occupations require one skill conditional on another. This directional nature suggests that advanced, specific skills and knowledge are often built upon broader, fundamental ones. We examine 70 million job transitions to show that human capital development and career progression follow this structured pathway in which skills more aligned with the nested structure command higher wage premiums, require longer education and are less likely to be automated. These disparities are evident across genders and racial/ethnic groups, explaining long-term wage penalties. Finally, we find that this nested structure has become even more pronounced over the past two decades, indicating increased barriers to upward job mobility.
Sustainable supply chain management practices and performance: The moderating effect of stakeholder pressure
Currently, sustainable supply chain management practices have become an important strategy for firms to improve performance and gain competitive advantage. However, there is a current debate over the performance outcomes of sustainable supply chain management practices. Additionally, the role of stakeholder pressure is frequently overlooked. Drawing on Natural Resources-Based View and Stakeholder Theory, this study aims to elucidate the ambiguous connection between sustainable supply management, sustainable process management, stakeholder pressure and performance, and investigate the mediation role of sustainable process management and the moderation effect of stakeholder pressure. Our analysis, based on data collected from 235 Chinese manufacturing firms, reveals significant insights. First, stakeholder pressure positively moderates the relationship between sustainable process management and performance, while negatively moderates the relationship between sustainable supply management and performance. Second, sustainable process management has a complete mediation effect on the relationship between sustainable supply management and performance. The conclusion not only explains the inconsistent relationship between sustainable supply chain management practice and performance, but also reveals clearly the relationship between sustainable supply management and sustainable process management. Besides, it also highlights the difference in performance outcomes of sustainable supply management and sustainable process management under stakeholder pressures, and has valuable guidance to the practice of sustainable supply chain management in Chinese manufacturing firms.
Professional demand analysis for teaching Chinese to speakers of other languages: a text mining approach on internet recruitment platforms
The rapid development of international education in China highlights the growing importance of employment analysis in Teaching Chinese to Speakers of Other Languages (TCSOL). This study explores the enterprise demands for TCSOL professionals using text mining techniques to analyze recruitment data collected from four major platforms: Boss Zhipin, Zhaopin.com, 51job.com, and Liepin.com. Combining descriptive statistics, LDA topic modeling, BERT-BiLSTM-CRF-based named entity recognition, and co-occurrence network analysis were used. Results show that there is a high demand for TCSOL professionals, especially for small-scale enterprises located in first-tier cities such as Beijing, Shanghai, Guangzhou, and Shenzhen. Employers tend to favor candidates with at least a bachelor’s degree and 1–3 years of work experience. The topic model highlighted three central themes in job descriptions, emphasizing a shift toward a more diverse skill set. Named entity recognition identified essential attributes such as “communication ability”, “teaching experience”, “bachelor’s degree or above” and “responsibility” as core recruitment requirements. The co-occurrence network analysis revealed the importance of “teaching” and “priority” as core skill nodes. Time series analysis showed seasonal fluctuations in recruitment demand, peaking during spring recruitment and graduation periods. A hierarchical model of talent demand and development in TCSOL is proposed, integrating the perspectives of employers, job seekers, educators, and policymakers. This study provides valuable insights for aspiring TCSOL professionals, offering guidance to better align talent training with market needs and improve employment prospects.
When the customers comes to you: mobile apps and corporate investment efficiency
Firms are increasingly shifting towards digital channels, yet the implications of this shift remain underexplored. Using a unique database of customer behaviors extracted from the top 2000 mobile apps developed by companies in China, this study investigates the impact of mobile apps on inefficient corporate investments. The results indicate that metrics such as active user count, usage duration, and app launch frequency can mitigate inefficient investments, notably by curtailing overinvestment. These findings survive a series of robustness checks such as altering the measures of inefficient investment, extending the analysis to include the top five apps, incorporating H-share listed firms, and employing instrumental variables regression. Moreover, the mechanism analysis indicates that mobile apps help reduce inefficient investments by lowering agency costs and relaxing financial constraints. Further analysis examines the business models of these apps (paid vs. free) as well as their reputation mechanisms, revealing that the pricing strategies of apps and the reputation of corporate brands also play a role in how the adoption of mobile apps affects inefficient investment.
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