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Article
Publication date: 14 November 2023

Flavian Emmanuel Sapnken, Mohammed Hamaidi, Mohammad M. Hamed, Abdelhamid Issa Hassane and Jean Gaston Tamba

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…

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Abstract

Purpose

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)).

Design/methodology/approach

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.

Findings

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.

Originality/value

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.

Details

Grey Systems: Theory and Application, vol. 14 no. 2
Type: Research Article
ISSN: 2043-9377

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Article
Publication date: 17 January 2025

Shuli Yan, Xiaoyu Gong and Xiangyan Zeng

Meteorological disasters pose a significant risk to people’s lives and safety, and accurate prediction of weather-related disaster losses is crucial for bolstering disaster…

6

Abstract

Purpose

Meteorological disasters pose a significant risk to people’s lives and safety, and accurate prediction of weather-related disaster losses is crucial for bolstering disaster prevention and mitigation capabilities and for addressing the challenges posed by climate change. Based on the uncertainty of meteorological disaster sequences, the damping accumulated autoregressive GM(1,1) model (DAARGM(1,1)) is proposed.

Design/methodology/approach

Firstly, the autoregressive terms of system characteristics are added to the damping-accumulated GM(1,1) model, and the partial autocorrelation function (PACF) is used to determine the order of the autoregressive terms. In addition, the optimal damping parameters are determined by the optimization algorithm.

Findings

The properties of the model were analyzed in terms of the stability of the model solution and the error of the restored value. By fitting and predicting the losses affected by meteorological disasters and comparing them with the results of four other grey models, the validity of the new model in fitting and prediction was verified.

Originality/value

The dynamic damping trend factor is introduced into the grey generation operator so that the grey model can flexibly adjust the accumulative order of the sequence. On the basis of the damping accumulated grey model, the autoregressive term of the system characteristics is introduced to take into account the influence of the previous data, which is more descriptive of the development trend of the time series itself and increases the effectiveness of the model.

Details

Grey Systems: Theory and Application, vol. 15 no. 1
Type: Research Article
ISSN: 2043-9377

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Publication date: 22 August 2017

Cubie L. L. Lau

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…

Abstract

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.

Details

Modern Organisational Governance
Type: Book
ISBN: 978-1-78714-695-2

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Article
Publication date: 29 December 2023

Lingwen wei, Yan Hong and Xianyi Zeng

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…

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Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Originality/value

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.

Details

Journal of Fashion Marketing and Management: An International Journal, vol. 28 no. 5
Type: Research Article
ISSN: 1361-2026

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Article
Publication date: 12 November 2024

Shitao Jin

Mega construction projects (MCPs), characterized by their vast scale, numerous stakeholders and complex management, often face significant uncertainties and challenges. While…

98

Abstract

Purpose

Mega construction projects (MCPs), characterized by their vast scale, numerous stakeholders and complex management, often face significant uncertainties and challenges. While existing research has explored the complexity of MCPs, it predominantly focuses on qualitative analysis and lacks systematic quantitative measurement methods. Therefore, this study aims to construct a complexity measurement model for MCPs using fuzzy comprehensive evaluation and grey relational analysis.

Design/methodology/approach

This study first constructs a complexity measurement framework through a systematic literature review, covering six dimensions of technical complexity, organizational complexity, goal complexity, environmental complexity, cultural complexity and information complexity and comprising 30 influencing factors. Secondly, a fuzzy evaluation matrix for complexity is constructed using a generalized bell-shaped membership function to effectively handle the fuzziness and uncertainty in the assessment. Subsequently, grey relational analysis is used to calculate the relational degree of each complexity factor, identifying their weights in the overall complexity. Finally, the weighted comprehensive evaluation results of project complexity are derived by combining the fuzzy evaluation results with the grey relational degrees.

Findings

To validate the model’s effectiveness, the 2020 Xi’an Silk Road International Conference Center construction project is used as a case study. The results indicate that the overall complexity level of the project is moderate, with goal complexity being the highest, followed by organizational complexity, environmental complexity, technical complexity, cultural complexity and informational complexity. The empirical analysis demonstrates that the model can accurately reflect the variations across different dimensions of MCP complexity and can be effectively applied in real-world projects.

Originality/value

This study systematically integrates research on MCPs complexity, establishing a multidimensional complexity measurement framework that addresses the limitations of previous studies focusing on partial dimensions. Moreover, the proposed quantitative measurement model combines fuzzy comprehensive evaluation and grey relational analysis, enhancing the accuracy and objectivity of complexity measurement while minimizing subjective bias. Lastly, the model has broad applicability and can be used in MCPs across different countries and regions, providing a scientific and effective basis for identifying and managing MCP complexity.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

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Article
Publication date: 11 December 2023

Zehui Bu, Jicai Liu and Xiaoxue Zhang

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…

138

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Originality/value

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.

Details

Kybernetes, vol. 54 no. 3
Type: Research Article
ISSN: 0368-492X

Keywords

Available. Open Access. Open Access
Article
Publication date: 11 June 2024

Julian Rott, Markus Böhm and Helmut Krcmar

Process mining (PM) has emerged as a leading technology for gaining data-based insights into organizations’ business processes. As processes increasingly cross-organizational…

580

Abstract

Purpose

Process mining (PM) has emerged as a leading technology for gaining data-based insights into organizations’ business processes. As processes increasingly cross-organizational boundaries, firms need to conduct PM jointly with multiple organizations to optimize their operations. However, current knowledge on cross-organizational process mining (coPM) is widely dispersed. Therefore, we synthesize current knowledge on coPM, identify challenges and enablers of coPM, and build a socio-technical framework and agenda for future research.

Design/methodology/approach

We conducted a literature review of 66 articles and summarized the findings according to the framework for Information Technology (IT)-enabled inter-organizational coordination (IOC) and the refined PM framework. The former states that within inter-organizational relationships, uncertainty sources determine information processing needs and coordination mechanisms determine information processing capabilities, while the fit between needs and capabilities determines the relationships’ performance. The latter distinguishes three categories of PM activities: cartography, auditing and navigation.

Findings

Past literature focused on coPM techniques, for example, algorithms for ensuring privacy and PM for cartography. Future research should focus on socio-technical aspects and follow four steps: First, determine uncertainty sources within coPM. Second, design, develop and evaluate coordination mechanisms. Third, investigate how the mechanisms assist with handling uncertainty. Fourth, analyze the impact on coPM performance. In addition, we present 18 challenges (e.g. integrating distributed data) and 9 enablers (e.g. aligning different strategies) for coPM application.

Originality/value

This is the first article to systematically investigate the status quo of coPM research and lay out a socio-technical research agenda building upon the well-established framework for IT-enabled IOC.

Details

Business Process Management Journal, vol. 30 no. 8
Type: Research Article
ISSN: 1463-7154

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Article
Publication date: 15 January 2024

Michael O'Connell

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…

53

Abstract

Purpose

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).

Design/methodology/approach

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.

Findings

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.

Originality/value

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.

Details

Journal of Economic Studies, vol. 51 no. 5
Type: Research Article
ISSN: 0144-3585

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Article
Publication date: 19 October 2015

H. L. Zou, S. X. Zeng, H. Lin and X. M. Xie

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…

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Abstract

Purpose

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.

Design/methodology/approach

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

Findings

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.

Practical implications

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.

Originality/value

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.

Details

Management Decision, vol. 53 no. 9
Type: Research Article
ISSN: 0025-1747

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Article
Publication date: 6 March 2009

Saixing Zeng, X.M. Xie, C.M. Tam and T.W. Wan

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…

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Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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

Research limitations/implications

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.

Practical implications

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.

Originality/value

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.

Details

Management Decision, vol. 47 no. 2
Type: Research Article
ISSN: 0025-1747

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