Zhaosu Meng, Xiaotong Liu, Kedong Yin, Xuemei Li and Xinchang Guo
The purpose of this paper is to examine the effectiveness of an improved dummy variables control grey model (DVCGM) considering the hysteresis effect of government policies in…
Abstract
Purpose
The purpose of this paper is to examine the effectiveness of an improved dummy variables control grey model (DVCGM) considering the hysteresis effect of government policies in China's energy intensity (EI) forecasting.
Design/methodology/approach
Energy consumption is considered as an important driver of economic development. China has introduced policies those aim at the optimization of energy structure and EI. In this study, EI is forecasted by an improved DVCGM, considering the hysteresis effect of energy-saving policies of the government. A nonlinear optimization method based on particle swarm optimization (PSO) algorithm is constructed to calculate the hysteresis parameter. A one-step rolling mechanism is applied to provide input data of the prediction model. Grey model (GM) (1, N), DVCGM (1, N) and ARIMA model are applied to test the accuracy of the improved DVCGM (1, N) model prediction.
Findings
The results show that the improved DVCGM provides reliable results and works well in simulation and predictions using multivariable data in small sample size and time-lag virtual variable. Accordingly, the improved DVCGM notes the hysteresis effect of government policies and significantly improves the prediction accuracy of China's EI than the other three models.
Originality/value
This study estimates the EI considering the hysteresis effect of energy-saving policies in China by using an improved DVCGM. The main contribution of this paper is to propose a model to estimate EI, considering the hysteresis effect of energy-saving policies and improve forecasting accuracy.
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Renhuai Liu, Steven Si, Song Lin, Dean Tjosvold and Richard Posthuma
Chuanjin Ju, Songyan Hou, Dandan Shao, Zhijun Zhang and Zhangli Yu
The purpose of this report is to demonstrate open and distance education (ODE) can support poverty alleviation. Taking the practices of the Open University of China (the OUC) as…
Abstract
Purpose
The purpose of this report is to demonstrate open and distance education (ODE) can support poverty alleviation. Taking the practices of the Open University of China (the OUC) as an example, this paper aims to reveal how open universities make contributions to local residents in rural and remote areas.
Design/methodology/approach
Focusing on 25 poverty-stricken counties, the OUC had invested 58 million RMB to its learning centers in these counties from 2017 to 2020. The first one is to improve ICT and educational facilities in these learning centers. The second approach is to cultivate local residents with degree programs through ODE so as to promote local economic development. The third one is to design and develop training programs according to local context to meet the specific needs of local villagers.
Findings
After 3 years working, cloud-based classrooms and computer rooms have been set up. Bookstores have been founded and printed books have been donated. Hundreds of thousands of digital micro lectures have been supplied to these learning centers which have been improved and fully played their functions. Nearly 50,000 local residents have been directly benefited. Village leaders have helped lift local residents out of poverty. Poverty-stricken villagers have been financed to study on either undergraduate or diploma programs. Local residents have improved their skills by learning with the training programs offered by the OUC.
Originality/value
ODE is proved to be an effective way to eradicate poverty. Open universities are proved to be able to make contributions to social justice. By fulfilling its commitments to eliminate poverty within the national strategy framework, the OUC has built its brand nationwide.
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The aim of this paper is to argue for the values of familial caring and relationships in addition to the provision of social media technology during the COVID-19 pandemic in Hong…
Abstract
Purpose
The aim of this paper is to argue for the values of familial caring and relationships in addition to the provision of social media technology during the COVID-19 pandemic in Hong Kong.
Design/methodology/approach
The discussion of this paper has adopted an inter-disciplinary approach by integrating health care system and psychological analysis, based on cultural philosophical argument through the hermeneutic approach of classical texts and critical analysis.
Findings
The COVID-19 pandemic has exposed the dilemma between the public health measures for COVID-19 and sustaining elderly social psychological health through familial connection. From a Confucian perspective, the practice of filial piety (xiao, 孝), which demands taking care of parents, is essential for one’s moral formation, and for one’s becoming a virtuous (ren, 仁) person. The necessity of taking care of elderly parents by adult children is not something that can be explained in terms of consequentialism. Indeed, the rising trend of instrumental rationality seems to weaken rather than strengthen the sense of filial obligation. In the face of the COVID-19 pandemic which tends to separate connections between family members, the author argues that we should emphasize the values of familial caring and relationship because it enhances the elderly’s characteristic of resilience.
Originality/value
This paper shows that while social media technology has mitigated the negative effect of social distancing, such online relationships should never replace the bodily connections between the elderly and their family members from a Confucian perspective.
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Alexandre Teixeira Dias, Henrique Cordeiro Martins, Valdeci Ferreira Santos, Pedro Verga Matos and Greiciele Macedo Morais
This research aims to identify the optimal configuration of investment which leads firms to their best competitive positions, considering the degree of concentration in the market.
Abstract
Purpose
This research aims to identify the optimal configuration of investment which leads firms to their best competitive positions, considering the degree of concentration in the market.
Design/methodology/approach
The methodology was quantitative and based on secondary data with samples of 124, 106 and 90 firms from competitive environment classified as perfect competition, monopolistic competition and oligopoly, respectively. Proposed models' parameters were estimated by means of genetic algorithms.
Findings
Adjustments on firm's investment are contingent on the degree of competition they face. Results are in line with existing academic research affirmation that the purpose of investments is to create and exploit opportunities for positive economic rents and that investments allow firms to protect from rivals' competitive actions and reinforce the need for investment decision makers to consider the environment in which the firm is competing, when defining the amount of investment that must be done to achieve and maintain a favorable competitive advantage position.
Originality/value
This research brings two main original contributions. The first one is the identification of the optimal amount of capital and R&D investments which leads firms to their best competitive positions, contingent to the degree of concentration of the competitive environment in which they operate, and the size of the firm. The second one is related to the use of genetic algorithms to estimate optimization models that considers the three competitive environments studied (perfect competition, monopolistic competition and oligopoly) and the investment variables in the linear and quadratic forms.