Linsen Yin

The exponential growth in demand for data storage and computing has led to a rapid expansion in the energy consumption and carbon emissions of data centers (DCs). Hybrid energy systems that integrate renewable energy sources are regarded as a sustainable and low-carbon solution for powering the DCs. This study proposes an optimal cooperation scheduling strategy for the hybrid energy system powering the DC and electric vehicles (EVs). The strategy is based on load transferring and operates within a carbon trading mechanism, explicitly addressing the coupling between computational loads and power consumption. An optimization model is constructed that considers economic objectives, including operational cost and a stepped carbon trading cost, to obtain optimal energy dispatch and computational task allocation strategies. This framework ensures the economic interests of EVs’ owners while satisfying the energy demands of both the DC and the EVs. The results of a case study based in Shanghai demonstrate that the proposed hybrid energy system with multiple sources has significant economic and environmental advantages in spite of operational complexity. Furthermore, the collaborative strategy further enhances the cost reduction and carbon emission reduction. Specifically, the cooperative strategy achieves a 5.21% reduction in total cost compared to Case 1 (without V2G) and a 22.80% reduction compared to Case 2 (without computing task transferring). By adopting the optimal scheduling solution, carbon emissions can be reduced by 16.74% relative to Case 1 while remaining at a level comparable to Case 2. Furthermore, the impact of the carbon trading mechanism on the system’s cost and carbon emissions is analyzed. The results indicate that while a stricter carbon trading mechanism leads to an increase in the total cost, it also results in a reduction in carbon emission from the DC’s hybrid energy system.

Purpose: This study investigates three supply chain collaborative compliance strategies under the mandatory and voluntary carbon markets: carbon emission reduction technology collaborative (TC), certified emission reduction (CER) investment collaborative (IC) and a hybrid strategy. It examines their effects on supply chain operations and carbon emission reduction decisions to identify the optimal collaborative compliance strategy in integrated carbon market. Design/methodology/approach: We consider a supply chain consisting of a non-emission controlling supplier and an emission-controlling manufacturer. The model combines carbon emission allowance cap-and-trade and CER offset mechanism in integrated carbon market. Using game theory modeling, we derive optimal wholesale pricing, production quantity and emission reduction levels. We then compare the performance across non-collaborative, single and hybrid supply chain collaborative compliance strategies. Findings: Compared to the non-collaborative strategy, TC enhances manufacturer profit but may not benefit the supplier when collaborative costs are high; IC is less effective for supply chain members when CER prices are low. The supplier’s and manufacturer’s preferences for TC and IC mainly depend on the total investment cost of CER, the CER price and the market-clearing price. The hybrid strategy is preferred by the supplier when CER prices are high or TC costs are low and also preferred by the manufacturer under high CER prices always. Originality/value: This study aims to identify the optimal supply chain collaborative compliance strategy. The findings offer support for the production, carbon emission reduction decisions, as well as the design and optimization of the collaborative compliance contracts.

Introduction: The development of digital technology and upgrading of consumer service demand have led to profound changes in the supply chain, gradually forming a supply chain ecosystem and transforming inter-enterprise cooperation into ecological cooperation. Amidst complex international landscapes and industrial transformation, the role of government has garnered significant attention. Thus, enhancing ecological cooperation in the supply chain during the new development stage and clarifying the government’s role constitute critical research topics.Methods: We analyze strategies of governments, suppliers, and manufacturers using a three-party evolutionary game model. The ideal event is defined within this model, and key influences on the dynamic evolutionary process are examined. A sensitivity analysis of selected parameters is rigorously conducted.Results: Our findings demonstrate that: (1) The government significantly promotes ecological cooperation among supply chain enterprises and can adjust system equilibrium by modulating the subsidy coefficient and regulatory costs. (2) Greater eco-sensitivity enhances advantages in eco-cooperation. (3) Establishing reasonable compensation fees between enterprises ensures effective eco-cooperation. (4) A company’s cost investment in eco-cooperation critically influences its engagement in such collaboration.Discussion: The study confirms the government’s pivotal role in facilitating supply chain ecological cooperation through policy instruments. Eco-sensitivity, inter-firm compensation mechanisms, and cost investments are identified as decisive factors for successful collaboration. Sensitivity analysis further validates the robustness of these parameters in shaping evolutionary outcomes.

Introduction: This study investigates the effect of recently implemented quote limits policy in China’s A-share Main Board market, a mechanism designed to enhance market stability. We examine whether this policy achieves its goals uniformly across distinct large-cap (HS300) and mid-to-small cap (CSI500) market segments.Methods: Utilizing the Multifractal Detrending Moving Average Cross-Correlation analysis (MF-X-DMA) and the nonlinear Granger causality test, we assess the policy’s potential heterogeneous impact on these two indices.Results: Our findings reveal that the policy decreases market efficiency and increases cross-market co-movement complexity for HS300, while conversely improving market efficiency and information flow for CSI500.Discussion: We offer novel empirical evidence on this policy using nonlinear methods. Our findings highlight the potentially divergent and unintended consequences of “one-size-fits-all” financial regulations across varied market segments, providing valuable insights for policymakers.

In recent years, the development and iteration of information technology have prompted the financial industry to transform and upgrade to financial technology (FinTech), which has received emerging attention from the global financial industry. While the FinTech industry is growing rapidly around the world, however, few studies have foucusd on the shortage of talent and difficulties in recruiting talent. First, this paper clarifies the shortage of FinTech talent through expert interviews and a questionnaire survey of 112 financial industry enterprises in Shanghai, China. Following, based on role theory, we construct a talent capability evaluation index system using 5 primary and 17 secondary indicators. Based on the exploration above, a gray optimization model is designed to support talent recruitment strategy for FinTech enterprises. The results indicate that Chinese FinTech talent should have composite abilities with outstanding professional technical skills and learning abilities, innovation and teamwork ability, project experience, and international vision. This study provides methodological guidelines for global FinTech talent evaluation and recruitment strategies and broadens the application of role theory and gray clustering theory.

Traditional management accounting methods are difficult to provide the necessary information for environmental economic management decisions. In response to the increasingly urgent need for decision-related information, a new branch of accounting, environmental management accounting, has emerged and is receiving increasing attention. Material Flow Cost Accounting (MFCA) is a useful tool for managing complex resource and waste streams. However, MFCA is mainly used for ex-post accounting and reporting and no efforts are made to use it for forecasting. In this study, we introduce MFCA method into the budgeting process of manufacturing firms, and thus construct an MFCA-ABB (Activity-Based Budget) model. This model is applied to JLC Company which is a fragrant liquor manufacturer in China, in order to forecast and plan for its resource consumption, positive product output, and negative product generation. Based on the forecasts of involved material flows, inefficiencies in the company’s liquor production process are identified; scenario analysis is then conducted to determine the optimal process and the technology adopted. The proposed MFCA-ABB model turns a pure operating budget into an environmental-economic budget, thus achieving both environmental and economic benefits for the company. Besides, this study makes an attempt to apply ABB in environmental management accounting, which suggests the possibility of applying the conventional management accounting tools, after modified, to the environmental-economic management of manufacturing firms in the future.

During the venture capital development, replacing the management work team or keeping up the status quo is a key strategy choice for venture capitalist and venture entrepreneur about the long-term development of enterprise and the control right transferring. In fact, the contract designing focuses on the distribution of cash flow to encourage both efforts in order to avoid double moral hazard, and the strategy behavior has similar effects according to the developing condition of venture enterprise. In this paper, we consider both contract design and strategic behavior, regarding this strategic behavior choice as a motivator and combining strategic behavior with financial instrument options. The main innovation is to redesign and optimize the contract based on dynamic perspective, which will analyze initial contract designed to motivate both sides effort if a venture enterprise is in good state, and then renegotiate whether to replace the management work team or keep up the status quo according to the venture enterprises development state in the process of venture investment cooperation. The paper also puts forward some conclusions: joint effort of both sides can be motivated through strategic behavior choice and then lead to increasing the overall value of the venture enterprise; after the venture enterprise has gained private benefits in the early stage, the venture capitalist needs to make appropriate assignments and demisability in benefits to remotivate the venture enterprises efforts, aiming to further balance venture enterprises private benefits and the earnings redistributed by venture capitalist.

Portfolio investment is adopted by the venture capital to diversify those risks involved in project selection, investing or operating so that the venture capitalist can expect a relatively stable income and lower financing risks. Based on the design of portfolio investment contract with unlimited funds developed by Kanniainen and Keuschnigg, and Inderst et al., this article makes a modification and presents a model given the limitation of funds available for the venture capitalist. It is demonstrated that the marginal benefit of efforts paid by the entrepreneurs exceeds the marginal cost, given the limitation of funds available, which will conduce to a high-level engagement of the entrepreneurs. Thus, by adopting the design of renegotiation contract, the venture capitalist can manage to stimulate the entrepreneurs to make efforts, which is to result in moral hazard reduction.