Study on Chinese consumer attitudes on energy-saving household appliances and government policies: based on a questionnaire survey of residents in Chongqing, China

Mandatory energy efficiency label is an effective way to change consumers’ consumption habits and guide them to buy energy-saving appliances. However, few studies concerned about the impact of energy efficiency label on consumers’ purchasing behavior. Based on the theory of planned behavior (TPB), social cognitive theory and signaling theory, this paper constructs a theoretical model of the effect of the energy label on consumers’ purchasing behavior of energy-saving household appliances. The survey data of 396 household appliance consumers in Mianyang City, China, are collected by the interception method, and the theoretical model is tested by structural equation modeling (SEM). Empirical results of this study indicate that consumers’ cognition and perceived value of energy efficiency label significantly affect label trust. Perceived value has a significant impact on consumers’ purchasing behavior of energy-saving appliances, while label cognition and label trust indirectly influence consumers’ purchasing behavior through the intermediary variable of purchase intention. External environmental factors such as publicity and education as well as subjective norms affect consumers’ actual purchasing behavior through the intermediary effect of purchase intention. This study provides important insights into the policy intervention measures to promote consumers’ purchasing behavior of energy-saving appliances.

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CONSUMER ATTITUDES AND BUYING INTENTIONS AS AIDS TO MARKETING FORECASTING AND GOVERNMENT POLICIES (WAPOR SESSION)

Public Opinion Quarterly ◽

10.1093/poq/34.3.459 ◽

1970 ◽

Vol 34 (3) ◽

pp. 459-461

Author(s):

G. Heald

Keyword(s):

Consumer Attitudes ◽

Government Policies

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EFISIENSI PEMAKAIAN LISTRIK DENGAN PELATIHAN SAVING ENERGY DI DESA PANEMO

Jurnal ABDI ◽

10.26740/ja.v5n1.p7-14 ◽

2019 ◽

Vol 5 (1) ◽

pp. 7

Author(s):

Yussi Anggraini ◽

Irna Tri Yuniahastuti

Keyword(s):

Program Evaluation ◽

Data Analysis ◽

Energy Saving ◽

Community Service ◽

Descriptive Analysis ◽

Electrical Energy ◽

Community Partnership ◽

Household Appliances ◽

Counseling Training ◽

Partnership Program

Energy saving training for housewives is the goal of this community partnership program. Themethod used is various types including discussion, counseling, training and mentoring. The stages ofimplementing this program start from pre-survey, formal surveys, community service activities,partner roles, monitoring, and program evaluation. The subjects in this PKM are the mothers of thevillage PKK panemon sugihwaras bojonegoro. Data analysis uses descriptive analysis. Based on theresearch of the community partnership program, it was found that the knowledge possessed aboutsaving energy was still in the medium category of 46%. This is due to the lack of knowledge ofhousewives related to energy saving and there has never been any socialization about this training.The knowledge gained in this PKM activity includes (1) knowledge of equipment that requireselectricity (2) knowledge of the function of household appliances that require electricity (3)knowledge of the use of electrical energy and knowledge of energy saving methods (4) knowledge ofhow to respond to hazards electricity and (5) knowledge of assistance to people who areelectrocuted. Therefore it can be concluded that the existence of energy saving training for motherspkk can help increase knowledge about energy-saving life in the household.

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The Residential Intelligent Power Consumption Management System

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.394.265 ◽

2013 ◽

Vol 394 ◽

pp. 265-269

Author(s):

Yan Wu ◽

Li Fang Wang ◽

Cheng Lin Liao

Keyword(s):

Power Consumption ◽

Energy Saving ◽

Power Management ◽

Management System ◽

Electrical Equipment ◽

Scientific Management ◽

Management Service ◽

Smart Power ◽

Household Appliances ◽

Saving Effect

Because of lacking of effective management and various energy-saving measures, a family smart power management system is introduced. The system includes the servers, LAN and smart power management terminal; the system can control the equipment to achieve the scientific management, and provide users a platform to interact with electrical equipment; the user can use the phone , PAD, PC and other mobile devices log the specified smart power management service website anytime, anywhere to control the electrical household electrical household appliances and query the power consumption, also can control the electrical household electrical household appliances at home through the smart power management terminal. According to the test of the system, the performances verify the system can effectively improve the power consumption rate, and achieve a good energy saving effect.

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Forecasting China's energy intensity by using an improved DVCGM (1, N) model considering the hysteresis effect

Grey Systems Theory and Application ◽

10.1108/gs-02-2020-0022 ◽

2020 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Zhaosu Meng ◽

Xiaotong Liu ◽

Kedong Yin ◽

Xuemei Li ◽

Xinchang Guo

Keyword(s):

Energy Saving ◽

Energy Intensity ◽

Small Sample Size ◽

Time Lag ◽

Small Sample ◽

Hysteresis Effect ◽

Grey Model ◽

Government Policies ◽

Energy Structure ◽

Content Type

PurposeThe 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/approachEnergy 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.FindingsThe 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/valueThis 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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Study on Cognition, Attitude and Behavioral Path of Energy Saving and Carbon Reduction: Using University Students in Taiwan as Examples

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.448-453.4486 ◽

2013 ◽

Vol 448-453 ◽

pp. 4486-4490

Author(s):

Wen Chin Lin ◽

Tsair Rong Chen

Keyword(s):

University Students ◽

Energy Saving ◽

Structural Equation Model ◽

Questionnaire Survey ◽

Structural Equation ◽

Equation Model ◽

Descriptive Statistics ◽

Cluster Sampling ◽

Carbon Reduction ◽

One Way Anova

By questionnaire survey, this study probes into university studentscurrent cognition and attitude toward energy saving and carbon reduction and conducts path analysis. The research tool is self-designed questionnaire on cognition and attitude toward energy saving and carbon reduction. First, 9 experts and scholars are invited to test content validity of questionnaires and conduct questionnaire pretest. The researcher revises the questionnaire, practices questionnaire survey, analyzes data and selects 685 university students by stratified cluster sampling. There are 617 valid questionnaires. Data obtained are analyzed by descriptive statistics, independent sample t test, One-way ANOVA and structural equation model.

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