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For some years now, Cameroon has seen a significant increase in its electricity demand, and this need is bound to grow within the next few years owing to the current economic growth and the ambitious projects underway. Therefore, one of the state's priorities is the mastery of electricity demand. In order to get there, it would be helpful to have reliable forecasting tools. This study proposes a novel version of the discrete grey multivariate convolution model (ODGMC(1,N)).

Specifically, a linear corrective term is added to its structure, parameterisation is done in a way that is consistent to the modelling procedure and the cumulated forecasting function of ODGMC(1,N) is obtained through an iterative technique.

Results show that ODGMC(1,N) is more stable and can extract the relationships between the system's input variables. To demonstrate and validate the superiority of ODGMC(1,N), a practical example drawn from the projection of electricity demand in Cameroon till 2030 is used. The findings reveal that the proposed model has a higher prediction precision, with 1.74% mean absolute percentage error and 132.16 root mean square error.

These interesting results are due to (1) the stability of ODGMC(1,N) resulting from a good adequacy between parameters estimation and their implementation, (2) the addition of a term that takes into account the linear impact of time t on the model's performance and (3) the removal of irrelevant information from input data by wavelet transform filtration. Thus, the suggested ODGMC is a robust predictive and monitoring tool for tracking the evolution of electricity needs.

China and the United States represent the two largest greenhouse gas emitters in the world. Studies on how US companies react to the natural environment are plentiful and show that stakeholders are one of the key drivers for green decisions. However, we have limited understanding of the stakeholder pressure faced by firms in China. Drawing on stakeholder theory, this study builds from in-depth interviews with 32 businesses in China. We show that government, customers, employees, suppliers, investors, and community are stakeholders most mentioned. Interestingly, findings also seem to suggest that the perceived pressures of non-profit organizations (NGOs) differ by the form of ownership. Multinational firms often view NGOs as allies, while Chinese firms downplay them as powerless and unimportant. Although stakeholders are seen as both threat and opportunity, two-thirds of those surveyed in this study focused on opportunity as opposed to threat.

The purpose of this research is to conduct a theoretical prediction study exploring the effectiveness of different content marketing strategies in expanding the second-hand market for fashion brands, comparing the costs and risks involved in these strategies in practice.

First, the expert interview method is employed to extract the content marketing strategies of the fashion second-hand market. Then, a descriptive space that is able to identify various fashion brand images is established. Then, experts' perceptions of the relationships between content marketing strategies and fashion brand image dimensions are obtained through a subjective evaluation procedure. Data of semantic evaluation were quantified and analyzed using the fuzzy logic method.

When fashion brands expand to the second-hand market, they not only need to focus on improving the individual differentiation of products but also give priority to the quality of products and services and the overall customer experience. Exploring the “social impact strategy” will become an important direction for the development of fashion brands in the future.

The research methodology employed herein exhibits a noteworthy degree of novelty. This study introduces a pioneering theoretical prediction approach utilizing fuzzy logic, marking the inaugural exploration of this emerging and captivating dimension within the context of the study. Simultaneously, the study provides comparative results among content marketing strategies for expanding the fashion second-hand market, offering guidance for market expansion.

The paper aims to elucidate effective strategies for promoting the adoption of green technology innovation within the private sector, thereby enhancing the value of public–private partnership (PPP) projects during the operational phase.

Utilizing prospect theory, the paper considers the government and the public as external driving forces. It establishes a tripartite evolutionary game model composed of government regulators, the private sector and the public. The paper uses numerical simulations to explore the evolutionary stable equilibrium strategies and the determinants influencing each stakeholder.

The paper demonstrates that government intervention and public participation substantially promote green technology innovation within the private sector. Major influencing factors encompass the intensity of pollution taxation, governmental information disclosure and public attention. However, an optimal threshold exists for environmental publicity and innovation subsidies, as excessive levels might inhibit technological innovation. Furthermore, within government intervention strategies, compensating the public for their participation costs is essential to circumvent the public's “free-rider” tendencies and encourage active public collaboration in PPP project innovation.

By constructing a tripartite evolutionary game model, the paper comprehensively examines the roles of government intervention and public participation in promoting green technology innovation within the private sector, offering fresh perspectives and strategies for the operational phase of PPP projects.

The author examines the impact these efficient factors have on factor model comparison tests in US returns using the Bayesian model scan approach of Chib et al. (2020), and Chib et al.(2022).

Ehsani and Linnainmaa (2022) show that time-series efficient investment factors in US stock returns span and earn 40% higher Sharpe ratios than the original factors.

The author shows that the optimal asset pricing model is an eight-factor model which contains efficient versions of the market factor, value factor (HML) and long-horizon behavioral factor (FIN). The findings show that efficient factors enhance the performance of US factor model performance. The top performing asset pricing model does not change in recent data.

The author is the only one to examine if the efficient factors developed by Ehsani and Linnainmaa (2022) have an impact on model comparison tests in US stock returns.

The purpose of this paper is to empirically investigate how top executives’ compensation is associated with environmental performance in the Chinese context and how this association varies with differing levels of industrial competition.

Combining agency and institutional theories, the empirical study is based on a sample of 698 publicly listed firms in China’s manufacturing sector.

The authors find that top executives’ cash pay has a positive association, and equity ownership a negative association, with corporate environmental performance. Furthermore, in more competitive industries, both pay and ownership are more strongly associated with environmental performance, indicating that industrial competition plays a moderating role in these relationships.

The findings imply that different incentive schemes can motivate executives toward environmental management in the Chinese context in opposite directions. They highlight the importance of improving regulation in order to motivate firms to engage in further environmental management.

Previous work on the relationship between executives’ compensation and socially responsible activities has mainly focussed on developed countries. This study is set in an emerging economy, and identifies new evidence to show that the effect of executive incentives is institutionally specific. In addition, it explores the effect of industrial competition on executives’ incentives to engage in environmental management, suggesting an explanation for the contradictory evidence found in previous research.

While internationalization of firms can be a source of growth in profitability, it can also result in huge losses due to the risky internationalized environment. Success in the home countries does not guarantee success internationally. The objective of this study is to identify the main business factors affecting performance of firms in the process of internationalization.

Ten business factors have been selected to investigate their relationship with the business performance in the internationalization process of Chinese manufacturing firms. The ten business factors are transformed into four dimensions (principal factors) using the method of factor analysis. Using the categorical regression method, relationships between return on assets (ROA) and the four dimensions extracted are examined.

The findings reveal that marketing capability of firms plays the most important role in improving performance of firms that embrace internationalization.

The study is confined to data collected from the Yangtze River Delta region via the method of survey, and it is generally agreed that China is a large market composed of distinctively different regional sectors, and there are significant differences in the level of development among the regions.

Performance of firms that embrace internationalization is affected by different business factors. If these factors could be identified, it would be possible to engineer the performance of firms.

From a political perspective, the research provides a better understanding on how to improve the internationalization performance for firms, which do not have such experience in the emerging economies.

The purpose of this paper is to identify and screen continuous innovation capability enablers (CICEs) in Indonesia’s manufacturing sectors, develop a relationship among these enablers and determine their driving power and dependence power in the sector.

The initial CICEs identification process is based on a literature review, while a fuzzy Delphi method (FDM) was used for the screening process of CICEs. Total interpretive structural modelling (TISM) was used to develop contextual relationships among various CICEs. The results of the TISM are used as an input for the matrix of cross-impact multiplications applied to classification (MICMAC) to classify the driving power and dependence powers of the CICEs.

This paper selected 16 CICEs classified in seven dimensions. TISM results and MICMAC analysis show that leadership, as well as climate and culture, are enablers with the highest driving power and lowest dependence powers; followed by information technology. The results of this study indicate that efforts to continuously develop innovation capabilities in the Indonesian manufacturing industries are strongly influenced by their leadership capability, climate and culture, also information technology-related capability.

The framework assessed in this study provides business managers and policymakers to obtain a bigger picture in developing policies with evidence-based strategy and priority in regard to continuous innovation capability.

The results will be useful for business managers and policymakers to understand the relationship between CICEs and identify key CICEs in Indonesia’s manufacturing sectors, which were previously non-existent.

The authors intend to investigate the relations between corporate strategic positioning and environmental information disclosure (EID) behaviors in the context of the circular economy. The authors argue that the development of the circular economy is crucial to address environmental issues and achieve sustainable development, and companies play a vital role in this process as micro-entities. By examining corporate EID behaviors, the authors could understand their adoption of circular practices to a certain extent.

The authors conduct a content analysis of companies' annual fiscal reports, social responsibility reports and environmental reports and develop text-based proxies for both strategic positioning and EID quality to explore the relationship between them.

The authors find that corporate strategic positioning does affect corporate EID behaviors. Specifically, firms that implement a prospector strategy are more likely to engage in high-quality EID. Furthermore, the results suggest that green innovation is one of the mediators through which strategic positioning affects EID. Compared with defenders, prospectors are more likely to engage in green innovation, which, in turn, leads to higher-quality EID and demonstrates a more active approach to the circular economy.

This study contributes to the literature on strategic positioning and corporate EID by providing empirical evidence on the impact of corporate strategic positioning on EID behaviors. Moreover, the study employs a textual analysis approach to measure corporate strategy and EID, which is a relatively new research method in this field.

The purpose of this study is to identify the factors determining collaborative innovation effect of manufacturing firms in emerging economies.

Based on a survey of 1,206 Chinese manufacturing firms and using structural equation modelling, this study explores the factors determining the effect of collaborative innovation among manufacturing firms (namely, internal capabilities, government policies, collaboration mechanisms and social networks) and examines the relationship between collaborative innovation effect and innovation performance.

The study finds that there are significantly positive relationships between firms’ internal capabilities, government policies, collaboration mechanisms and social networks and collaborative innovation effect among firms.

These findings reveal that policymakers should create an effective institutional culture and market environment to facilitate firms’ collaborative innovation.

This paper draws on the resource-based view of firms and contributes to understanding of how the development of factors determining firms’ collaborative innovation effect can improve innovation performance. This study extends established frameworks on collaborative innovation in relation to four dimensions, namely, firms’ internal capabilities, government policies, collaboration mechanisms and social networks, uniquely identifying the limits of specific dimensions. Moreover, this study addresses government policies and “Guanxi culture” specific to China that provide new insights into how firms’ collaborative innovation is improved from the perspectives of business–governmental relations and social networks.