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Available. Open Access. Open Access
Article
Publication date: 9 November 2018

Fan Conglai and Xie Chaofeng

As the essential requirement of socialism with Chinese characteristics, common prosperity stands for both the goal of and the approach to economic growth. Shared development is a…

2232

Abstract

Purpose

As the essential requirement of socialism with Chinese characteristics, common prosperity stands for both the goal of and the approach to economic growth. Shared development is a new stage of the process of common prosperity. From the perspective of economic growth, it requires the low- and middle-income groups to gain more from the growth than high-income groups. The paper aims to discuss these issues.

Design/methodology/approach

Based on provincial panel data, the random effect model and the dynamic panel model are used in this paper to analyze the path to achieve pro-poor growth.

Findings

The keys to achieve pro-poor growth are first to promote new urbanization with people at the center, diversify the forms of employment and improve the income structure of the residents, and second to improve the accuracy in designing redistribution policies.

Originality/value

After the realization of “some get rich first” policy, it is important to swiftly adapt to a new mindset of shared development, which charters a new course to the Marxist common prosperity. There exist few established economic theories or action plans with respect to shared development. Pro-poor growth, however, offers a perspective to achieve both sharing and development.

Details

China Political Economy, vol. 1 no. 2
Type: Research Article
ISSN: 2516-1652

Keywords

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Article
Publication date: 24 February 2025

Chaofeng Shen, Jun Zhang and Yueyang Song

Accurately predicting the installed capacity of wind energy is essential for energy strategic planning, given the growing need for environmental protection worldwide and the quick…

0

Abstract

Purpose

Accurately predicting the installed capacity of wind energy is essential for energy strategic planning, given the growing need for environmental protection worldwide and the quick development of renewable energy. In order to provide an unprecedented high-precision scheme for wind energy installed capacity prediction and to further become the primary driving force in the process of energy planning and decision-making, this research focuses on overcoming the limitations of conventional prediction models and creatively proposes a multi-parameter collaborative optimization GM(1,1) power model. This will help the energy field advance in a more efficient and scientific direction.

Design/methodology/approach

The theoretical framework of the fundamental GM(1,1) power model is thoroughly examined in this study and serves as the basis for further optimizations. To unlock the potential of each parameter optimization, single-parameter optimization investigations of the model are conducted from the viewpoints of the fractional optimization, background value optimization and grey action optimization, respectively. Conversely, an inventive multi-parameter collaborative optimization power model is built. The model is given dynamic flexibility by adding time-varying parameters. The sine function and interpolation technique are used to further optimize the background value. The model’s meaning is enhanced by the inclusion of a power exponent. Furthermore, several parameters are cooperatively tuned with the aid of the sophisticated Firefly algorithm, giving the model stronger predictive powers. A multi-dimensional and multi-regional model comparison analysis is formed by selecting the wind energy installed capacity data of North America, Italy, Japan and South Korea for in-depth empirical analysis in order to confirm the model’s validity.

Findings

The findings show that the multi-parameter collaborative optimization model (Model 5) has an exceptional in-sample and out-of-sample prediction effect. The relative prediction error MAPEs are 0.41% and 0.31%. It has a clear advantage over the simple GM(1,1) power model and other single optimization models in applications in North America, South Korea, Japan, and Italy. Its seven variable parameters are the reason for this. These factors help create a very accurate prediction effect through joint optimization from multiple perspectives. It is noteworthy that Model 4’s nonlinear optimization of the grey action is impressive. It performs better than background value optimization and fractional-order optimization. Furthermore, according to the model’s prognosis, North America’s installed wind energy capacity is expected to develop linearly and reach 513.214 bn kilowatts in 2035. This gives the planning for energy development in this area a vital foundation.

Originality/value

The novel idea of the multi-parameter collaborative optimization GM(1,1) power model and its clever integration with the firefly method to accomplish parameter optimization constitute the fundamental value of this study. The substantial benefits of multi-parameter optimization in the stability of the prediction effect have been firmly validated by a thorough comparison with the basic and single-optimization models. Like a lighthouse, this novel model illuminates a more accurate path for wind energy installed capacity prediction and offers high-value reference bases for a variety of aspects, including government energy planning, enterprise strategic layout, investor decision-making direction, fostering technological innovation, advancing academic research and developing energy transformation strategies. As a result, it becomes a significant impetus for the growth of the energy sector.

Highlights

  • (1)

    This study proposes a new gray prediction model. Compared with the traditional grey prediction model, the modeling mechanism of this model is optimized.

  • (2)

    This study is based on multi-parameter collaborative optimization to achieve the improvement of model prediction effect. The traditional grey model is two-parameter, while the model proposed in this study is seven-parameter collaborative optimization;

  • (3)

    In this study, swarm intelligence algorithm-firefly algorithm is used to optimize the hyperparameters, so as to obtain the best cooperative optimization multi-parameter values;

  • (4)

    The application of the model is divided into two parts: empirical and application. In the empirical stage, 5 kinds of prediction models are used to predict, which proves that the model proposed in this paper is effective and improves the prediction accuracy. The application part uses the model to forecast the installed wind power capacity in North America, and the future development trend is linear growth, which is expected to double the installed capacity by 2035.

This study proposes a new gray prediction model. Compared with the traditional grey prediction model, the modeling mechanism of this model is optimized.

This study is based on multi-parameter collaborative optimization to achieve the improvement of model prediction effect. The traditional grey model is two-parameter, while the model proposed in this study is seven-parameter collaborative optimization;

In this study, swarm intelligence algorithm-firefly algorithm is used to optimize the hyperparameters, so as to obtain the best cooperative optimization multi-parameter values;

The application of the model is divided into two parts: empirical and application. In the empirical stage, 5 kinds of prediction models are used to predict, which proves that the model proposed in this paper is effective and improves the prediction accuracy. The application part uses the model to forecast the installed wind power capacity in North America, and the future development trend is linear growth, which is expected to double the installed capacity by 2035.

Details

Grey Systems: Theory and Application, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2043-9377

Keywords

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Article
Publication date: 1 September 2016

Hai-ling Guan

With the development of social economy, the urbanization of the world has presented a new development trend. The green, ecological, and economic city has gradually attracted…

48

Abstract

With the development of social economy, the urbanization of the world has presented a new development trend. The green, ecological, and economic city has gradually attracted people's attention. How to plan new cities and towns to coordinate economic development with nature has been the focus of domestic and foreign scholars. Based on this premise, this article elaborates the domestic and foreign research status of ecological city and puts forward a new type of green ecological civilization from the perspective of evolution of civilization. From the perspective of green ecological economy, the evolution of China's urban planning is studied in terms of the urban and rural areas, nature, pollution, industry, culture, and other aspects. To accumulate experience, green ecological planning in New York is also analyzed at multiple levels, such as urban expansion, energy, and urban water use. According to the development of our country in the past 30 years, the development strategy of urbanization suitable to China's national conditions is introduced on the basis of ecological economy. From the perspective of green ecological planning and economy, practice has proved that new urban planning is able to promote the establishment of a resource-saving society, to enhance the coordinated development of the population, resources, environment, and economy, and to comprehensively improve people's quality of life.

Details

Open House International, vol. 41 no. 3
Type: Research Article
ISSN: 0168-2601

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Article
Publication date: 13 May 2024

Chao Feng, Shirui Ding, Hui Chen and Yue Zhang

This study aims to explore whether and how the two potential antecedents (i.e. relationship quality at the dyadic level and network density at the network level) affect firms’…

164

Abstract

Purpose

This study aims to explore whether and how the two potential antecedents (i.e. relationship quality at the dyadic level and network density at the network level) affect firms’ internet-interactive capability (FIIC), referring to the capability of a specific firm to communicate and interact with the relevant partner firms on the basis of internet-interactive technologies in the internet environment and, at the same time, the following influence of FIIC on collaborative activities (i.e. joint planning and joint problem-solving).

Design/methodology/approach

This study designed a questionnaire and collected data on-site from 400 manufacturers. SmartPLS is used to validate the research model.

Findings

The results suggest that the dyadic relationship quality and network density of the partner group are both positively connected with a firm’s FIIC. Besides, FIIC is positively related to collaborative activities with its partners.

Research limitations/implications

Given the nature of our data (i.e. cross-sectional), the authors can collect longitudinal or experimental data to retest the hypotheses.

Practical implications

This study gives certain guidance for firms to be aware of the factors that motivate FIIC and use their FIIC to influence their employees’ collaborative activities in their relationships with partners, thereby promoting cooperation performance.

Originality/value

This study attempts to extend the resource-based theory based on the logic of motivation-capability by exploring the potential antecedents of FIIC and makes contributions to the current studies on the antecedents of FIIC, which provides actionable insights for firms to play the role of FIIC in interfirm interactions.

Details

Journal of Business & Industrial Marketing, vol. 39 no. 9
Type: Research Article
ISSN: 0885-8624

Keywords

Available. Open Access. Open Access
Article
Publication date: 5 December 2022

Carlos Alberto Rojas Trejos, Jose D. Meisel and Wilson Adarme Jaimes

The purpose of this paper is to review the relevant literature in order to identify trends and suggest some possible directions for future research in the framework of…

3849

Abstract

Purpose

The purpose of this paper is to review the relevant literature in order to identify trends and suggest some possible directions for future research in the framework of humanitarian aid distribution logistics with accessibility constraints.

Design/methodology/approach

The authors developed a systematic literature review to study the state of the art on distribution logistics considering accessibility constraints. The electronic databases used were Web of science, Scopus, Science Direct, Jstor, Emerald, EBSCO, Scielo and Redalyc. As a result, 49 articles were reviewed in detail.

Findings

This study identified some gaps, as well as some research opportunities. The main conclusions are the need for further studies on the interrelationships and hierarchies of multiple actors, explore intermodality, transshipment options and redistribution relief goods to avoid severe shortages in some nodes and excess inventory in others, studies of the vulnerability of transport networks, correlational analysis of road failures and other future lines.

Research limitations/implications

The bibliography is limited to peer-reviewed academic journals due to their academic relevance, accessibility and ease of searching. Most of the studies included in the review were conducted in high-income countries, which may limit the generalizability of the results to low-income countries. However, the authors focused on databases covering important journals on humanitarian logistics.

Originality/value

This paper contextualises and synthesises research into humanitarian aid distribution logistics with accessibility constrains, highlights key themes and suggests areas for further research.

Details

Journal of Humanitarian Logistics and Supply Chain Management, vol. 13 no. 1
Type: Research Article
ISSN: 2042-6747

Keywords

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