Managerial and Decision Economics最新文献

Despite the prolonged use of external sources of finance, the financing gap for industrialisation in Africa, especially for countries along the Gulf of Guinea, is still enormous amidst numerous episodes of shocks to external sources of finance. This study investigates the influence of institutional strength on the relationship between insurance and industrialisation in 13 countries situated along the Gulf of Guinea. The results consistently show the negative impact of insurance activities on industrialisation across all distribution levels, particularly for countries in the upper quantile. The results from the interaction analysis show that institutional quality in the Gulf of Guinea countries is insufficient to mitigate the negative effect of insurance activities on industrialisation. All stakeholders in the government and the financial system should prioritise floating low-risk and credible debt instruments (insurance premiums) to increase the stock of finance available to induce industrialisation within the region.

Live commerce allows manufacturers to sell products directly to a broad online audience while engaging multichannel networks (MCNs) in promotions. This study investigates two strategic models for manufacturers: vertically integrating an MCN or collaborating with one. Considering the herd effect and the risk of consumer–product mismatch in livestream shopping, we formulate a Stackelberg game model that includes a manufacturer, a retailer, and an MCN. The results show that the effect of the return rate and commission rate on the manufacturer's profit is nonmonotonic. Under the integration model, livestream selling favors the manufacturer when the associated costs are low. In the collaboration model, the manufacturer is incentivized to introduce a less efficient livestream channel. This strategy serves a dual purpose: it constrains the revenue captured by the MCN and leverages inter-channel competition to strengthen the manufacturer's control over the retail channel. Our analysis establishes that the two livestreaming models have distinct applicability conditions. A key finding is that the manufacturer may lack the incentive to integrate the MCN, even when it incurs no cost. This analysis provides valuable insights for manufacturers devising their entry strategy into the livestreaming e-commerce sector.

Green factories, as the central component of the green manufacturing system, represent a critical institutional mechanism for driving the green transformation of the manufacturing sector. This study systematically evaluates the impact of green factory certification on firms' green total factor productivity (GTFP) using data from manufacturing companies listed on the Shanghai and Shenzhen A-shares between 2012 and 2023, employing a multiperiod difference-in-differences model. The findings indicate that the green factory certification policy significantly enhances firms' GTFP, thereby facilitating the green transformation of the manufacturing industry. This conclusion remains robust after conducting several robustness checks, including parallel trend tests, Bacon decomposition, and machine learning techniques. Mechanism analysis reveals that the policy drives improvements in GTFP by alleviating financing constraints, stimulating green technological innovation, and enhancing the quality of environmental information disclosure. Heterogeneity analysis further demonstrates that the policy has a more pronounced effect in high-pollution industries, whereas its impact is relatively weaker for firms with stronger market bargaining power or political ties. Additionally, the moderating effect analysis reveals that well-established internal corporate governance and external societal supervision can significantly enhance the policy's effectiveness. The study provides empirical evidence and policy recommendations to optimize the green manufacturing policy framework, improve policy precision, and enhance green performance.

This study investigates how elections affect banking efficiency in an African emerging economy (Ghana), by inferring from the political choice theory and further decoupling the ownership effects of elections on diverse efficiency proxies. The study employs Tobit regression models and instrumental variable models (Tobit and fixed effect) as robustness models with year control effects for 29 banks between 2000 and 2020. While banking efficiency in the forms of technical, pure-technical, scale, cost, allocative, and revenue is measured using DEA across private, state, listed, unlisted, domestic, and foreign banks, election is measured as a dummy. The study reveals that elections significantly lower banking efficiencies. However, the reducing effect of elections varies across types of banking efficiency indicators and ownership structures. Specifically, while elections adversely affect technical, cost, scale, allocative, and revenue efficiencies of banks, private, state, unlisted, listed, and foreign banks were mostly affected. These suggest that the decline in banking efficiencies during electioneering periods is attributable to political, policy, and fiscal uncertainties and differs significantly depending on bank ownership and efficiency types. While the study presents significant insights, future studies may investigate the effect of elections in phases to include the pre-, during-, and post-election phases to understand the temporal dynamics of election effects in other emerging economies other than Ghana. The results explain the need for political stability and transparency, fostered by electoral and policy reforms, to ensure continuity and a reduction in election-related inefficiencies. Also, bank managers must recognize and factor elections into their efficiency decision-making. To the best of our knowledge, this study is the first to provide empirical evidence on how elections affect the diverse array of banking efficiencies across different ownership types and nature in an African emerging economy context.

Employment is the cornerstone of people's livelihood. It is closely tied to the fundamental interests of the public and serves as the foundation of social well-being. Using the 2012 launch of the Intellectual Property (IP) Demonstration City pilot program as a quasi-natural experiment, this paper applies a multi-period difference-in-differences (DID) approach to empirically examine the impact of IP protection on enterprise employment size. The findings are as follows: (1) The IP Demonstration City pilot significantly promotes enterprise employment expansion through channels such as increased production, alleviated financing constraints, and enhanced physical investment, and the results are robust to various tests; (2) Heterogeneity analysis shows that the pilot has a significantly positive effect on the employment size of enterprises located in inland regions, in high-tech industries, and in areas with relatively weak IP protection environments; (3) Further analysis reveals that the pilot facilitates human capital upgrading and increases wage levels of workers in pilot cities, but has a negative effect on labor efficiency. The employment-promoting effect of IP protection is more pronounced in firms that receive higher government subsidies and tax incentives. This study provides theoretical and empirical evidence on how to encourage enterprises to expand employment and improve the quality and adequacy of jobs, offering valuable policy implications for the government to achieve stable and high-quality employment.

The study checks the opportunities and challenges in using different competition models between downstream channel partners, namely, comparable channel power, distinct channel power and crisis cartel during production cost disruption. We employed a supply chain consisting of a manufacturer-modern trade outlet-e-tailer, and different game theoretic models like Nash, Stackelberg and Collusion games were used to analyse the pre-disruption and disruption cases. The research revealed that the downstream channel partners could enhance profitability during disruptions by engaging in crisis cartels or operating under the competitor's leadership, surpassing pre-disruption levels. However, models involving channel leadership and comparable channel power yield lower profits for downstream partners during disruption. Surprisingly, none of the models offer improved profitability for the manufacturer during production cost disruptions, and both the crisis cartel and channel leadership models prove detrimental to the manufacturer's profits. Similarly, none of the models could improve the consumer surplus of customers. Additionally, we extend the basic model by analysing the impact of customer channel preference and the price elasticity of demand during production disruptions. We found that the channel preference coefficient plays a crucial role in determining the profitability of all supply chain partners. Furthermore, the price elasticity of demand significantly affects pricing strategies for the modern trade outlet and e-tailer but does not influence the manufacturer.

Industrial robots play a vital role in transforming and upgrading the manufacturing industry. They harness automation technologies to drive industrial production and enhance their value through innovations in production tools and knowledge. This paper analyzes annual data from China's A-share nonfinancial manufacturing listed companies during the period from 2007 to 2019, examining the impact of industrial robot applications on corporate cash holdings. The study discovers that the application of industrial robots notably reduces corporate cash holdings, thereby confirming the effect of capital allocation. The analysis rules out the possibility that this reduction occurs through alleviating agency problems. Mechanism analysis reveals that the application of industrial robots reduces cash holdings for precautionary motives by reducing labor leverage and enhancing labor productivity and operational efficiency. Additional tests reveal that the reduction in corporate cash holdings due to industrial robot applications is more pronounced in enterprises with intense market competition, labor-intensive and nonstate-owned enterprises. This study deepens the research focus on industrial robot applications and corporate cash holdings, providing a theoretical basis for policymakers to promote technological innovation and industrial advancement.

To address the disparities between medical resources and patient needs in large general hospitals (GHs), this study examines the coordination of referral processes between GH and community health centers (CHCs) enabled by telemedicine-based online service channels used by GH as gatekeepers. A three-stage game model is developed within a queuing theory framework to investigate the dynamic decision-making interactions among patients, CHC, and GH. The equilibrium decisions are given concerning the arrival rates of both initial offline and online patients, the service capacity of CHC, and the referral threshold of GH. The analysis compares system performance under partial and full referral scenarios. The findings reveal a counterintuitive result: Partial reverse referral from online services may prompt the CHC to reduce its service capacity for profit-seeking purposes, thereby diminishing patient welfare. Numerical experiments indicate that the online reverse referral mechanism is effective when the scale of online patients is sufficiently large. When patient scale is inadequate, the CHC, lacking profit margins, tends to withdraw from the referral system. Moreover, under conditions of expanded GH service capacity, partial reverse referral outperforms full reverse referral in improving overall system efficiency.