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Under the “dual carbon” framework, the article explores the equilibrium points among the government, agricultural enterprises and village committees, and uses sensitivity analysis to reveal the dynamic factors affecting these stakeholders, thereby proposing methods to enhance agricultural disaster resilience.

The article uses MATLAB to construct a game model for the three parties with interests: agribusiness, government and village council. It examines the stability of strategies among these entities. Through graphical simulation, the paper analyzes the sensitivity of agricultural enterprises carbon emissions and village committees’ rent-seeking behaviors in the decision-making process, focusing on significant factors such as government carbon tax and regulatory policies.

A single government reward and punishment mechanism is insufficient to influence the strategic choices of enterprises and village committees. The cost of rent-seeking does not affect the strategic choices of enterprises and village committees. A key factor influencing whether the village committee engages in rent-seeking is the level of labor income of the village committee as an “intermediary”.

This paper focuses on the dynamic game between three stakeholders (the government, agricultural enterprises and village committees), seeking dynamic equilibrium and conducting sensitivity analysis through visualization to provide the government with optimal policy recommendations.

The production planning problem with fine-grained information has hardly been considered in practice. The purpose of this study is to investigate the data-driven production planning problem when a manufacturer can observe historical demand data with high-dimensional mixed-frequency features, which provides fine-grained information.

In this study, a two-step data-driven optimization model is proposed to examine production planning with the exploitation of mixed-frequency demand data is proposed. First, an Unrestricted MIxed DAta Sampling approach is proposed, which imposes Group LASSO Penalty (GP-U-MIDAS). The use of high frequency of massive demand information is analytically justified to significantly improve the predictive ability without sacrificing goodness-of-fit. Then, integrated with the GP-U-MIDAS approach, the authors develop a multiperiod production planning model with a rolling cycle. The performance is evaluated by forecasting outcomes, production planning decisions, service levels and total cost.

Numerical results show that the key variables influencing market demand can be completely recognized through the GP-U-MIDAS approach; in particular, the selected accuracy of crucial features exceeds 92%. Furthermore, the proposed approach performs well regarding both in-sample fitting and out-of-sample forecasting throughout most of the horizons. Taking the total cost and service level obtained under the actual demand as the benchmark, the mean values of both the service level and total cost differences are reduced. The mean deviations of the service level and total cost are reduced to less than 2.4%. This indicates that when faced with fluctuating demand, the manufacturer can adopt the proposed model to effectively manage total costs and experience an enhanced service level.

Compared with previous studies, the authors develop a two-step data-driven optimization model by directly incorporating a potentially large number of features; the model can help manufacturers effectively identify the key features of market demand, improve the accuracy of demand estimations and make informed production decisions. Moreover, demand forecasting and optimal production decisions behave robustly with shifting demand and different cost structures, which can provide manufacturers an excellent method for solving production planning problems under demand uncertainty.

In China, having a home before getting married is viewed as being a crucial indicator of the sincerity of romance. Despite recent increases in housing costs, men who have their homes ready for marriage stand out in the marriage market. This study aims to explore the association between readiness to marry, marriage age and the home that men purchase prior to marriage using the China Labor-force Dynamics Survey, the first countrywide follow-up survey with the theme of labor force.

The authors suggest new standards for determining the marital residence. In addition, contrary to the existing literature, which focuses on “Sheng Nu” (women who do not marry by the traditional marriage age in China), the authors focus on “Sheng Nan” (men who do not marry by the traditional marriage age in China).

The results show that men who own a house before marriage are reluctant to get married. The authors document robust evidence that the preexistence of the marital house decreases the willingness to marry and postpones the marriage date, regardless of location and time.

The authors document robust evidence that the preexistence of the marital house decreases the willingness to marry and postpones the marriage date, regardless of location and time.

The recent meeting of G-20 world leaders, held in New Delhi, in 2023, highlighted that the physical effect of climate change has considerable macro-economic costs at the national and global levels and they have also pledged to accelerate the clean, sustainable and inclusive energy transition along a variety of pathways. Climate change could pose various emerging risks to the firm’s operational and financial activities, specifically for those which are belonging to the energy sector. Thus, this study aims to investigate the impact of climate risks on the financial performance of select energy companies from G-20 countries.

The study considered 48 energy companies from G-20 countries as the sample for the period of 2017 to 2021. To measure the climate change-related physical risks, the study has considered the ND-GAIN climate vulnerability score and the firm’s financial performance has been measured by return on assets, return on equity, return on capital used and price-to-book ratio. To examine the impact of climate risks on the financial performance of the sample companies, the authors have used pooled ordinary least squares (OLS) and fixed/random effect regression analysis and required data diagnosis tests are also performed.

The empirical results suggested that climate risks negatively impacted the financial performance of the sample companies. The market performances of the firms are also being impacted by the physical climate change. The results of panel data regression analysis also confirmed the robustness of the empirical results derived from the pooled OLS analysis suggesting that firms that operated in a less climate-risky country, financially performed better than the firms that operated in a more climate-risky country.

The paper has significant practical implications like it could be helpful for the policymakers, investors, suppliers, researchers and other stakeholders in developing deeper insights about the impact of climate risks on the energy sectors from an international perspective. This study may also help the policymakers in developing policies for the management of climate risk for the energy sector.

This study adds insights to the existing literature in the area of climate risks and firm’s financial performance. Moreover, this may be the first study that attempts to evaluate the impact of climate risks on the financial performance of select energy companies from the G-20’s perspective.

This study underscores the critical need to enhance innovation capacity within higher education institutions (HEIs), particularly in developing nations, as a strategic response to global economic challenges. It aims to compare the innovation capacities of Timor Leste Business School and Indonesia Business School using the HEInnovate framework.

The study employs a qualitative research methodology involving in-depth interviews with academic leaders such as the dean, vice dean and heads of study programs at both institutions. Thematic analysis was applied to identify patterns and challenges across the eight dimensions of the HEInnovate framework, including leadership, governance, entrepreneurial teaching and digital transformation.

Indonesia Business School outperforms Timor Leste Business School across all innovation capacity dimensions. Timor Leste faces significant challenges in infrastructure development and entrepreneurial support. However, both institutions show potential for growth through enhanced collaboration with industry stakeholders and increased internationalization.

This study focuses on two institutions, which may limit the generalizability of the results. Future research could include a broader range of institutions in different contexts to provide a more comprehensive understanding of innovation capacity in HEIs.

The research offers practical insights for policymakers, highlighting the need to reinforce innovation strategies by optimizing organizational structures and fostering collaboration with industry and international partners.

The study highlights the potential for HEIs to foster entrepreneurial mindsets and skills among faculty members, contributing to developing a more entrepreneurial society. This contribution has the potential to reduce unemployment and increase social mobility as more graduates may be empowered to create their businesses or contribute to innovative sectors of the economy.

This study provides a novel comparative analysis of innovation capacity in developing country HEIs, using the HEInnovate framework to enhance innovation strategies. It offers 13 propositions for future research and policy development in higher education innovation.