Search Results (24)

This study employs k-means clustering to group 30 Chinese provinces into four CO₂ emission patterns, characterized by increasing emission levels and distinct energy consumption structures, and captures their dynamic evolution from 2000 to 2021 using a discrete endogenous Markov chain approach. While Shanghai, Jiangxi, and Hebei retained their original classifications, provinces such as Beijing, Fujian, Tianjin, and Anhui transitioned from higher to lower emission patterns, indicating notable reversals in emission trajectories. To identify the determinants of these transitions, GDP growth rate, population growth rate, and energy investment are incorporated as time varying covariates. The empirical findings demonstrate that GDP growth substantially increases interpattern mobility, thereby weakening state persistence, whereas population growth and energy investment tend to reinforce emission pattern stability. These results imply that policy responses must be tailored to regional dynamics. In rapidly growing regions, fiscal incentives and technological upgrading may facilitate downward transitions in emission states, whereas in provinces where emissions remain persistent due to demographic or investment related rigidity, structural adjustments and long term mitigation frameworks are essential. The study underscores the importance of integrating economic, demographic, and investment characteristics into carbon reduction strategies through a region specific and data informed approach. Full article

This study investigates whether government subsidies promote R&D cost stickiness in the new energy vehicle (NEV) industry in China—that is, whether public funding encourages firms to retain R&D resources even during periods of declining sales. While prior literature primarily explores the relationship between subsidies and R&D investment levels, it often overlooks firms’ financial position and dynamic cost behaviors. Given that R&D investment has high adjustment costs and is sensitive to cash flows, reductions in R&D spending during downturns may reflect managerial cost asymmetry rather than a crowding-out effect of subsidies. Moreover, government subsidies may serve as a signal of long-term market optimism, motivating managers to retain R&D resources during economic downturns. Using a panel dataset of 573 listed new energy vehicle (NEV) firms in China’s A-share market from 2007 to 2021, we construct a model based on the asymmetric cost behavior framework to empirically assess the impact of government subsidies on R&D cost stickiness. The results show that government subsidies significantly increase the degree of R&D cost stickiness. Serving as a signal of future market optimism, subsidies raise managerial expectations and incentivize decisions to retain R&D-related costs during economic downturns. This positive relationship is more pronounced in firms with high levels of green innovation, large-scale enterprises, and non-state-owned firms. These findings suggest that public funding alleviates managerial pressure to cut R&D expenses amid revenue declines, thereby supporting firms’ long-term innovation strategies. Our study contributes to the cost management literature by highlighting a novel channel through which subsidies influence managerial discretion under uncertainty. It also provides policy implications for the future phase-out of subsidies, emphasizing the need for complementary market mechanisms to sustain innovation investment, particularly for small, young, and financially constrained firms. Full article

Existing research critically examines the influence of environmental, social, and governance (ESG) ratings on corporate financial performance (CFP), with outcomes varying considerably. This study employs a dataset of publicly traded firms across 16 countries within the hospitality sector from 2005 to 2022 to examine the ESG-CFP relationship. Fixed effects regression results demonstrate a positive linkage between ESG ratings and CFP, utilizing both comprehensive ESG ratings and discrete pillar ratings. These findings remain robust across various performance measures including return on assets, return on equity, and Tobin’s Q. Heteroscedasticity and endogeneity concerns are mitigated through generalized least squares and two-stage least squares methods, respectively. Moreover, the positive impact of ESG on CFP exhibits greater potency in the United States relative to other countries and was more pronounced during the COVID-19 era. These findings offer valuable insights for business executives, investors, and policymakers in supporting ESG initiatives, guiding investment decisions, and formulating effective policy directives. Full article

Since 2016, strict regulatory policies have limited the size and financing channels of China’s urban real estate market. To adapt to the new situation, real estate developers need to adjust their development strategies and adopt more precise investment methods. In this respect, cost reduction, an accurate market positioning, and conducting detailed market research are particularly crucial. Given that the uneven development of the urban housing market has exacerbated urban segregation, urban residential space was subdivided into multiple potential submarkets. This study focuses on the land acquisition and the development of commercial residential projects in Hangzhou, China, from 2003 to 2022. Using the latent class analysis method based on the discrete choice model, the potential submarkets of Hangzhou’s housing development market are identified, and the project positioning and land selection preferences of developers are assessed. The results show that Hangzhou’s residential projects can be divided into five potential market categories: high-rise basic demand dwellings, high-end-improvement-type dwellings, luxury low-density dwellings, primary-improvement-type dwellings, and large-scale mixed-density dwellings. The importance of different land elements for developers when developing various types of projects is evaluated by calculating the willingness-to-pay coefficient. The findings of this study provide a comprehensive perspective for the government, real estate developers, and property owners to better understand the development dynamics on the supply side of the real estate market. Full article

Understanding the impacts of ecological projects on household livelihoods is important in ensuring their sustainability. However, existing studies typically cover only a limited, discrete temporal point. Insufficient study duration makes it difficult to determine the full impact and dynamics of a project, affecting the veracity of the results. Representing one of the world’s largest investments in an ecosystem service programs, the Grain for Green Project (GGP) has an objective of increasing household incomes. Using data from 7112 questionnaires collected through 12 consecutive years (2007–2018) of field survey monitoring, this study examined the long-term impacts of the GGP on household livelihoods in the Beijing–Tianjin Sandstorm Source Control Project area through comparisons between participant households (PHs) and non-participant households (NPHs). The results show that GGP subsidies significantly increased household incomes only during the period 2007–2015, and their share of total household income decreased from 9.21% in 2007 to 1.62% in 2018. Subsidies for GGP cannot compensate farmers for losses due to the reduction in farmland. The above findings suggest that the effect of subsidies diminishes over time. Increased investment in jobs and skills training is needed to consolidate the GGP results. This provides new perspectives and empirical support for the study of international ecological compensation policies and sustainable development. Full article

The present paper deals with an integrated sustainable supply chain model with the effect of learning for an imperfect production system under a cloudy fuzzy environment where the demand rate is treated as a cloudy triangular fuzzy (imprecise) number, which means that the demand rate of the items is not constant, and shortages and a warranty policy are allowed. The vendor governs the manufacturing process to serve the demand of the buyer. When the vendor supplies the demanded lot after the production of items, it is also considered that the delivery lots have some defective items that follow an S-shape learning curve. After receiving the lot, the buyer inspects the whole lot, and the buyer classifies the whole lot into two categories: one is the defective-quality items and the other is the imperfect-quality items. The buyer returns the defective-quality items to the seller after a screening process, for which a warranty cost is included. During the transportation of the items, a lot of carbon units are emitted from the transportation, damaging the quality of the environment. The seller includes carbon emission costs to achieve sustainability as per considerations. A one-time discrete investment is also included for the minimizing of the setup cost of the seller for the next cycles. We developed models for the scenario of the separate decision and for the integrated decision of the players (seller/buyer) under the model’s consideration. Our aim is to jointly optimize the integrated total fuzzy cost under a cloudy fuzzy environment sustained by the seller and buyer. Numerical examples, sensitivity, analysis limitations, future scope and conclusions have been provided for the justification of the proposed model, and the impact of the input parameters on the decision variables and integrated total fuzzy cost for the supply chain are provided for the validity and robustness of this proposed model. The effect of learning in a cloudy fuzzy environment was positive for this proposed model. Full article

With the acceleration of urbanization, the ecosystem around cities is facing severe challenges. The drastic changes in the landscape pattern, especially in urban–suburban areas, are usually regarded as one of the main drivers. However, the spatiotemporal heterogeneous impacts of landscape patterns on the ecosystem services in this region remain unclear. To address this issue, we propose a novel framework integrating the InVEST-based ecosystem service assessment and spatiotemporal weighted regression (STWR)-based analysis of the spatiotemporal heterogeneity in urban–suburban areas, and apply it to the empirical study of Fuzhou City from 2000 to 2020. It first utilized the InVEST model to build a comprehensive ecosystem service index (CES) from five aspects (i.e., habitat quality, carbon storage, water yield, soil retention, and water purification capacity). Then, four landscape pattern indices (LPIs) (i.e., patch density (PD), area-weighted mean fractal dimension (FRAC_AM), splitting (SPLIT), and Shannon’s diversity (SHDI) index) were selected to build the STWR model. We compared and analyzed the differences in the spatial coefficient surfaces and significance tests generated by the STWR model in urban, urban–suburban, and rural areas. Results show that the following: (1) The CES in Fuzhou shows an upward trend from the urban area to the urban–suburban and rural areas, with significant gradient differences. (2) Compared with other areas, the LPIs in urban–suburban areas show more fragmentation, discreteness, and diversity, indicating more socioeconomic activities. (3) Although LPIs’ impacts on CES change over time (increasing from 2005 to 2010 and 2020 but decreasing in 2015), their effects are relatively low in urban–suburban areas, significantly lower than in urban areas. (4) Interestingly, the LPI coefficients near the urban–suburban boundary seem more significant. (5) This framework can effectively reveal the spatiotemporal heterogeneous relationships between various LPIs and CES, thus guiding concrete policies and measures that support decision-making for improving the ecosystem services surrounding cities through shaping landscape patterns. Full article

Background: In a typical multiechelon supply chain, the supplier makes semifinished items, from which the manufacturer produces finished products to eventually get sold at retailers. However, the majority of existing supply chain models consider the remanufacturing of defective products by solely one organization, despite the fact that both the supplier and manufacturer can produce defective products. This study considers the remanufacturing of defective products with fresh materials and additional expenses by both the supplier and manufacturer. Contrary to well-established articles that hold major partners to be accountable for reducing carbon emissions under a carbon cap-and-trade policy, the proposed model presumes an initial green technological investment by each chain partner. Methods: This study represents a varying market with fuzzy cost components that are then defuzzified with $\lambda$-integral method. This study determines the critical values of three discrete and four other continuous decision variables that globally maximize the profitability of the proposed model. Results: Slower production with a longer cycle boosts profitability in a developing market. To increase profit, a case study on the oil and natural gas business suggested to reduce the production of defective items and cutting emission through green investments. Conclusions: Managers can sustainably boost profit via careful production, modern machinery, and slightly longer cycles. Full article

We examine how the policies of Chinese regional governments affect the investment location decisions of firms. Using a dataset compiled from the reports on the investment decisions of 498 listed Chinese companies headquartered in the provinces of Guangdong, Jiangsu, Shanghai, and Zhejiang, we estimate discrete choice models of the investment decisions of these firms. The variables of interest relate to government policies, but we also control for both market and firm characteristics. The provision of superior communications infrastructure leads to an increased probability of investment, as does a lower proportion of state-owned enterprises and a lower burden of regional government administrative expenses. We quantify potential changes in the probability of attracting investment by calculating the average marginal effects over a range of values of the variables of interest. Our extraction of primary data on firms directly from their annual reports allows us to address a gap in the literature with respect to the influence of regional government policies on investment decisions during a historical period (2000–2010) when inter-regional investment was particularly important as it saw a move to the decentralisation of decision making to regional government level. Our results provide useful guidance as to how local governments can best attract investment, namely by focusing on improving communications infrastructure, reducing government ownership of the means of production, and reducing administrative burden. Although there is currently a renewed focus on central government control, these findings remain relevant and can contribute to the ongoing debate concerning the optimal balance between centralisation and decentralisation. Full article

As marine cargo traffic continues to grow, ports are experiencing increasing problems with congestion. To address this issue without requiring significant capital investment, neighboring ports can share their capacity to meet the rising demand for cargo throughput. While there are many planning level studies on inter-port cooperation, there is a scarcity of operational-level studies, and there is currently no available dry port integrated cooperation scheme for port clusters that utilizes a microsimulation approach. This study aims to contribute to the existing literature by proposing a conceptual port integration scheme that includes a dry port for improved coordination between ports in clusters. The discrete event simulation (DES) approach was used to construct three representative microsimulation models with dry port integration considering vessel transfer policies and no-cooperation scenario. The outputs of the models were evaluated using performance metrics (vessel delays, storage capacities, and the number of serviced vessels) using t-test statistics. The results show that the cooperation scheme with the vessel transfer policy and the strategic management of vessel transfer can significantly reduce the vessel operation delay by over 39% for the no-cooperation scenario with an integrated dry port and this value is further improved to 62% if a simulation-based port selection module (PSM) is used for vessel transfer policy. Additionally, the mean number of containers of the average of two port storages decreased by 40% and further decreased by 69% with the PSM. In terms of decision-making performance for vessel transfer decisions with varying quay lengths, PSM was determined to be superior to the vessel transfer policy considering the number of vessels in port queues. The proposed conceptual port integration model and approach can assist decision-makers in evaluating the effectiveness of different cooperation schemes and vessel transfer policies for adjacent ports in port clusters. Full article

Rooftop solar photovoltaic (PV) systems could significantly contribute to renewable energy production and reduce domestic energy costs. In Italy, as in other countries, the current incentives generate a modest annual increase after the generous fiscal incentives that kick-started the PV market in the 2008–2013 period. Several factors are, however, at play that can speed up the installation process, such as the improvements in PV technology at declining prices, the increased availability of battery-storage (BS) systems, the growing use of electric appliances, the uptake of electric cars, and the increased environmental awareness. We integrate two research methodologies, discrete choice modeling and agent-based modeling, to understand how these factors will influence households’ decisions regarding PV and BS installations and how agents interact in their socioeconomic environment. We predict that in Italy, given the preference structure of homeowners, the continuing decline in costs, and the social interaction, 40–45% of homeowners will have PV or PV and BS installed by 2030, thanks to the existing investment tax credit policy. Full article

PV energy generates economic and environmental benefits (e.g., energy cost-saving, GHG emissions reduction, etc.), which can be capitalized into market prices. There is, therefore, growing interest in assessing the value that PV systems add to solar homes (i.e., homes equipped with PV production plants) market prices. Although the number of solar homes has experienced rapid growth in Europe and Italy, literature investigating the impact of PV power plants on home values is still very limited. This paper aims to fill this gap. We implement a Discrete Choice Experiment (DCE) approach to estimate individuals’ WTP for different typologies of domestic PV plants, which vary in technical characteristics. Our findings show that homebuyers are willing to pay a price premium for solar homes, ranging from some 3% to some 15%, depending on PV panels’ characteristics. These results can provide a wealth of recommendations to different interested parties such as homeowners, homebuyers, realtors, and governments, seeking knowledge on the capitalization effect of residential PV plants on the housing market to implement cost-effective investment strategies or design optimal policy incentives. Full article

Background: Vaccination is one of the most cost-effective health investments to prevent and control communicable diseases. Improving the vaccination rate of children is important for all nations, and for China in particular since the advent of the two-child policy. This study aims to elicit the stated preference of parents for vaccination following recent vaccine-related incidents in China. Potential preference heterogeneity was also explored among respondents. Methods: A discrete choice experiment was developed to elicit parental preferences regarding the key features of vaccines in 2019. The study recruited a national sample of parents from 10 provinces who had at least one child aged between 6 months and 5 years old. A conditional logit model and a mixed logit model were used to estimate parental preference. Results: A total of 598 parents completed the questionnaire; among them, 428 respondents who passed the rational tests were analyzed. All attributes except for the severity of diseases prevented by vaccines were statistically significant. The risk of severe side effects and protection rates were the two most important factors explaining parents’ decisions about vaccination. The results of the mixed logit model with interactions indicate that fathers or rural parents were more likely to vaccinate their children, and children whose health was not good were also more likely to be vaccinated. In addition, parents who were not more than 30 years old had a stronger preference for efficiency, and well-educated parents preferred imported vaccines with the lowest risk of severe side effects. Conclusion: When deciding about vaccinations for their children, parents in China are mostly driven by vaccination safety and vaccine effectiveness and were not affected by the severity of diseases. These findings will be useful for increasing the acceptability of vaccination in China. Full article

Sub-Saharan African countries present chronic energy shortages and heavy reliance on oil imports for diesel. The small demand and high production costs in some countries have compromised the economic feasibility of the biodiesel industry in the region. Therefore, to overcome these limitations a model of “multi-countries” cooperated production and consumption of biodiesel was proposed for a group of seven neighboring countries. The model explored linear programming and simulations to the problem of minimizing biodiesel production costs considering different types of production and demand restrictions. The data processing was realized using the Solver and Linear Interactive Discrete Optimizer software (LINDO). The simulations and scenarios revealed that palm oil is the crop that minimize the production costs (US$0.82/L) and that, although jatropha was classified in the second place (US$1.05/L), it is the crop with the biggest job creation potential (5.0 times that of the palm oil seeds). These results reveal the presence of a trade-off in the strategy and the choice between different oilseeds: (a) to produce biodiesel from the crop with minimal costs (palm oil) or (b) to choose the one that has the biggest potential for job creation (jatropha). Considering the diesel price between US$0.60 and US$1.14/L at service stations in the region in 2016, both the biodiesel from palm oil and jatropha will need subsidies and fiscal incentives (tax reductions) to be competitive in the fuel market (diesel). The volume of biodiesel to supply the B10 demand in 2031 has the potential to reduce US$ 1.98 billion/year of the expenses on oil imports. It is worth observing that this decision-support model adds the “multi-countries” cooperation perspective as a contribution to the methodological and political approaches about biofuels production and consumption and can be exploited as a starting point for the formulation of policies, strategies, and investment decisions for the establishment of biodiesel production programs. Full article

This study explains about a serial smart production system where a single-type of product is produced. This system uses an unequally sized batch policy in subsequent stages. The setup cost is not always deterministic, it can be controllable and reduced by increasing the capital investment cost, and that the production rates in the system may vary within given limits across batches of shipments. Furthermore, as imperfect items are produced in long-run system, to clean the imperfectness autonomation policy is adopted for inspection, which make the process smarter. The shipment lot sizes of the deliveries are unequal and variable. In long-run production system, defective items are produced in “out-of-control” state. In this model, the defect rate is random with a uniform distribution which is clean from the system by autonomation. In addition, in the remanufacturing process, it is assuming that all defective products are repaired, and no defective products are scrapped. The main theme of developing this model is to determine the number of shipments and the optimal production lot size to adjust the production rates and decrease the total system cost under a reduced setup cost by considering the discrete investment and make a serial smart production system. A solution procedure along with an advanced algorithm was proposed for solving the model. Numerical examples with some graphical representations are provided to validate the model. Full article