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Background While economics is growing in Indonesia, its Happiness Index remains steady. Regarding the average concentration of dissolved particles, Indonesia is ranked sixth globally. Many factors can affect happiness. Environmental conditions, especially air quality, are considered to influence individual happiness. Therefore, this research investigates the impact of air quality and health on happiness. Methods Data used in this study is the microdata of Indonesia’s Happiness Survey (SPTK) in 2021. With more than 70,000 respondents, the study uses Ordered Probit as an analysis method with subjective happiness as the dependent variable. The independent variables used in this study are air quality, age, gender, housing area per capita, marital status, and health status. All independent variables except age are categorical. The variable of interest, air quality, is coded “1” if the IKU achieves the Strategic Plan’s target of 84.2 and “0” otherwise. IKU is a regional air quality index that combines two substances. Results At a significance level of 5%, there is a positive relationship between subjective happiness and air quality. In other words, if air quality (IKU) meets the Strategic Plan target (≥ 84.2), then a person is more likely to have a higher level of happiness. It can be explained more with the marginal effect. The marginal effect concludes that if the target is achieved, the probability of having a lower level of happiness decreases by up to 2.8%, and a very high level of happiness rises by 5.1%. Regarding health status, the rarer someone gets sick, the happier she/he is. Conclusion The study finds that air pollution could lower happiness, while better health increases happiness. Therefore, it is important to meet the target of IKU and to improve public health. Some good practices can be adopted to achieve this goal.
Background While economics is growing in Indonesia, its Happiness Index remains steady. Regarding the average concentration of dissolved particles, Indonesia is ranked sixth globally. Many factors can affect happiness. Environmental conditions, especially air quality, are considered to influence individual happiness. Therefore, this research investigates the impact of air quality and health on happiness. Methods Data used in this study is the microdata of Indonesia’s Happiness Survey (SPTK) in 2021. With more than 70,000 respondents, the study uses Ordered Probit as an analysis method with subjective happiness as the dependent variable. The independent variables used in this study are air quality, age, gender, housing area per capita, marital status, and health status. All independent variables except age are categorical. The variable of interest, air quality, is coded “1” if the IKU achieves the Strategic Plan’s target of 84.2 and “0” otherwise. IKU is a regional air quality index that combines two substances. Results At a significance level of 5%, there is a positive relationship between subjective happiness and air quality. In other words, if air quality (IKU) meets the Strategic Plan target (≥ 84.2), then a person is more likely to have a higher level of happiness. It can be explained more with the marginal effect. The marginal effect concludes that if the target is achieved, the probability of having a lower level of happiness decreases by up to 2.8%, and a very high level of happiness rises by 5.1%. Regarding health status, the rarer someone gets sick, the happier she/he is. Conclusion The study finds that air pollution could lower happiness, while better health increases happiness. Therefore, it is important to meet the target of IKU and to improve public health. Some good practices can be adopted to achieve this goal.
Humanity has consumed a large amount of energy and resources to maintain the rapid development of the economy and society, causing greenhouse gas and air pollutants to rise continuously, generating enormous pressures for the sustainable development of many cities. It is economical to control greenhouse gas and air pollutants from the synergy perspective. To identify the key driving factors involved in synergistic control, this paper uses the pressure-state-response (PSR) model to design a performance evaluation model of greenhouse gas and air pollutants synergistic control (GASC) utilizing pressure, state, and response dimensions. The performance evaluation factor system of GASC comprises three primary aspects and 18 criteria. The analytic hierarchy process (AHP) was used to determine the weight of each factor in the evaluation system. The technique for order preference by similarity to an ideal solution (TOPSIS) method was used to calculate the ranking of the synergistic control effects of the four representative provinces in China. We use Importance-performance analysis (IPA) to analyze the performance of driving factors of synergistic control in the province with the lowest ranking from 2016 to 2020. The research shows that in Northeast China, represented by Liaoning province, the government’s response should include changing the support strategy for the new energy consumer, introducing synergistic control standards and policies, and making flexible adjustments to the supply chain. The research provides a scientific basis for the performance evaluation of GASC and decision-making support for lean response strategies.
Electric vehicles (EVs) have garnered significant attention in the context of sustainable transportation. Despite this growing interest, the adoption of electric cars in Indonesia, particularly in Medan city, remains at an early stage. Medan is a worthwhile case study of a fastgrowing city in a developing country. Several existing literatures have taken Indonesia uniquely into context and emerged as a foundation framework. However, there still remains little comprehension regarding the perceptions and intentions of conventional car users. To address the gap in research, this study focuses on the intention of car drivers in Medan to adopt electric cars through conversion rather than addition. By examining the factors influencing this adoption intention, we contribute early insights into the context of a developing city (Medan) in developing countries. Our structured questionnaire collected responses from 390 car drivers in Medan Selayang Sub-district. We employ an ordinal logistic regression (OLR) to model the impact of explanatory variables, including socioeconomic background, attitudinal perception, and spe-cific travel characteristics, on the adoption intention. An OLR model was used since our dependent variable (adoption intention) is in ordinal form. Our findings reveal significant links between socioeconomic and attitudinal variables and adoption intention. Notably, variables such as car ownership, daily driving range, and monthly maintenance expenses of conventional cars owned by respondents positively influence the likelihood of adopting electric cars in the future. The result indicates middle-to-high income people as the potential electric car market in this context. We further discuss how the maturity of widespread information regarding electric cars might influence the perception of current conventional car users. These findings hold implications for the design of targeted interventions to promote electric car adoption in Medan city and similar contexts.
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