Managerial and Decision Economics最新文献

As a new financial innovation, consumer credit services are increasingly embraced by e-commerce platforms. This paper presents a stylized model to determine when an e-commerce platform should launch credit services and whether to share them with third-party sellers. Our findings indicate that the platform benefits from launching credit services only when consumer preference outweighs the delinquency rate. Furthermore, service sharing can create a win-win scenario with moderate fees and high consumer preference. Contrary to common belief, sharing services with sellers can reduce consumer surplus, suggesting that widespread use of consumer credit services is not necessarily beneficial for consumers.

This paper analyzes the effects of cross-ownership on green managerial delegation contracts in a Cournot duopoly market with emission tax policy. We show that higher cross-ownership will always exacerbate environmental degradation and diminish societal welfare, even with green managerial delegation. Compared with sales delegation, green managerial delegation under such ownership always yields higher environmental damage and lower social welfare. Compared to concurrent regulation, noncommitted emission taxation always leads to lower environmental damage and higher social welfare, although green managerial delegation will not be chosen in the latter. Our findings have important policy implications.

Drawing on organizational learning theory and knowledge-based view, this study investigates the relationship between firms' innovation failures and the quality of subsequent innovations. We find an inverted U-shaped relationship between innovation failures and the quality of subsequent innovations. We theoretically decompose the curvilinear effects of innovation failures on the quality of subsequent innovations into two underlying counteracting forces: the positive impact of learning from innovation failures (LFIF) and the negative impact of survival pressures. Furthermore, firms' knowledge breadth and depth flatten the inverted U-shaped curve. Our findings reveal the risks and benefits of LFIF.

Governments and enterprises are paying more and more attention to carbon emissions. Considering the dynamic of carbon emissions reduction (CER) and the government intervention, this study discusses the optimal CER effort level, price, and government intervention intensity in a two-echelon supply chain consisting of a government and two manufacturers. The two manufacturers have two competitive behaviors: Cournot and Stackelberg. Two differential game models are constructed for the two different behaviors, and the optimal decisions under the two models are obtained. The comparisons of these optimal solutions are analyzed, and the influence of some parameters on the optimal solution in the two models is investigated under two scenarios. Furthermore, the optimal government intervention intensity is obtained with the goal of maximizing government utility. The results show that the Stackelberg game allows manufacturers to achieve higher profits and CER but is disadvantageous to consumers, and the manufacturer as the leader has a first-mover advantage. Fierce market competition leads to greater CER and profits, but higher prices reduce consumer surplus. Larger penalties can promote enterprises to reduce carbon emissions when carbon emissions are large. Compared with the Cournot behavior game, the Stackelberg allows manufacturers to obtain higher profits and CER, but the prices are higher that are detrimental for consumers. The fierce market competition is good for manufacturers, the environment, and the society, but it reduces the consumer surplus. The low CER efficiency causes high costs and reduces the manufacturer's motivation to CER, which harm the environment and reduce profits. The government intervention is negatively correlated with the intensity of market competition and the sensitivity of manufacturers to policies.

In this paper, we examine the effect of board cultural diversity (BCD) on European banks nonperforming loans (NPLs) and whether boardroom gender diversity (BGD) moderates the BCD-NPLs relationship. We used a sample of 75 banks in 20 European countries from 2011 to 2022. The System Generalized Method of Moment was performed as an econometric approach. We find that greater BCD increases NPLs and BGD moderates the BCD-NPLs relationship. The sensitivity analysis results indicate that only large banks benefit from an interaction between BGD and BCD because it lowers the NPLs ratio. Our results are robust to alternative econometric methods.

Based on the double machine learning model, this study examines the impact of perception of policy uncertainty (PPU) on labor income share (LIS). We find that PPU negatively influences LIS. Mechanism test indicates that PPU not only results in a reduction in fixed asset investment, distorting human capital structure, but leads to a financing dilemma for firms, ultimately exerting a detrimental effect on LIS. Additionally, PPU primarily diminishes LIS of ordinary employees rather than executives. Furthermore, the inhibitory effect of PPU on LIS is significantly more pronounced in firms characterized by smaller union scales and those operating within monopolistic industries.

We find that robot adoption significantly increases firm-level TFP, but factor market distortion hinders the promotion effect of robot adoption on firm-level TFP. Mechanism analysis reveals that the cost-saving and labor productivity improvements brought about by industrial robot application stimulate market entry by new firms and elevate the exit risk for incumbent enterprises. This dynamic intensifies competition, resulting in an enhanced market environment that contributes to firm-level TFP. However, factor market distortions impede the survival of the fittest among firms and stifle the competitive effects of market entry and exit. This ultimately leads to sluggish growth in firm-level TFP.

“Specialized, Refined, Unique, and Innovative” (SRUI) enterprises are a crucial part of the national innovation system and play a significant role in enhancing national core competitiveness by leveraging strengths and addressing weaknesses. Given the limited quantitative analysis on the productivity of SRUI enterprises in the academic field, this paper constructs an enterprise-level artificial intelligence index based on text analysis and machine learning. Using panel data from 2018 to 2022, we investigate the impact of artificial intelligence on the productivity of SRUI small- and medium-sized enterprises (SMEs). The research findings indicate that (1) artificial intelligence significantly enhances the productivity of SRUI SMEs, and for each one standard deviation increase in artificial intelligence, the productivity level of SRUI enterprises will increase by 6.82%. (2) Mechanism tests reveal that artificial intelligence improves productivity by optimizing labor structure, improving labor resource allocation, stimulating endogenous motivation and innovation vitality within enterprises, and enhancing management level and investment efficiency. (3) Heterogeneity analysis indicates that at the regional level, artificial intelligence significantly boosts the productivity of enterprises with well-developed network infrastructure and robust intellectual property protection systems. At the industry level, AI has a more pronounced effect on the productivity of technology-intensive and competitive industries. Additionally, we also find that the impact of AI on productivity is more significant in enterprises with younger executive teams and executives with digital and intelligent education backgrounds. This study expands the research scope of productivity and provides valuable insights for the government to optimize digital economy policies and for enterprises to formulate digital innovation strategies.

This article takes crowdsourcing as the research background, collects secondary data from the Yipin Freelancer website, constructs panel data of “respondent–date,” and uses the research framework of the elaboration likelihood model (ELM) to study the key factors influencing the bid-winning probability of respondents. The study found that for the central path, there is a nonlinear inverted U-shaped relationship between the respondents' success experience and skill diversity and the bid-winning probability. For the peripheral path of task settings, the study found that a larger task bonus, more bonus recipients, and longer task deadlines are beneficial for respondents to win bids successfully. Finally, this article discusses the theoretical and practical significance of the research.