PROGRESS IN GEOGRAPHY ›› 2015, Vol. 34 ›› Issue (4): 482-493.doi: 10.11820/dlkxjz.2015.04.010

• Special Column: Big Data and Smart City • Previous Articles     Next Articles

Measures of subjective well-being: a review

Fenglong WANG1,2(), Donggen WANG1()   

  1. 1. Department of Geography, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China
    2. Institute of Urban Development and Research, East China Normal University, Shanghai 200062, China
  • Online:2015-04-10 Published:2015-04-10

Abstract:

In recent years, subjective well-being has attracted increasing attention in psychology, economics, and sociology. Geographical studies on the topic in English language is also growing rapidly. Since measurement is the foundation of empirical studies, this article reviews the major approaches to measuring subjective well-being. We first provide a theoretical framework of subjective well-being, in which two major components are identified: the cognitive component which is mainly known as life satisfaction; and the affective well-being which is usually termed as positive affect and negative affect. Each component can be further divided according to its temporal span. Previous studies mainly adopt self-reported scales to measure different components of subjective well-being, while some facial or ecological indicators are also developed to measure short-term emotions. The self-reported scales are quite flexible and probably provide the most proper insights into individuals' subjectively experienced well-being. These scales can be classified into two types: while the reflective scales select items based on a latent model, the formative scales consider the items as different facets which can be aggregated within an aggregate model or profile model. In general, more reflective scales of subjective well-being have been developed as compared to formative scales. The most widely used scales to measure life satisfaction include the single-item self-anchoring scale and the 5-item Satisfaction with Life Scale . Some formative scales such as the 8-item Personal Well-Being Index (PWI) were also developed to assess one's global life satisfaction. The most often applied measures of affective well-being include the single-item Gurin scale, the multi-item core affect model, and PANAS. Special methods such as the Experience Sampling Method and Day Reconstruction Method and artificial indicators such as U-index were also developed to measure emotional experiences in activity episodes. The current article also reviews the strengths and weakness of those measures. In order to reduce the biases and errors of measurement caused by respondents'cognitive process and the artificially assigned weights for various sub-domains, the multi-item reflective scales are recommended. However, future studies should develop better understanding of the convergence among various measures of subjective well-being. It is also necessary to pay more attention to the cognitive mechanism of evaluating global well-being and select proper models in empirical analysis. Based on the review of measures of subjective well-being and empirical studies in English literature, this article proposes some important topics and issues for future studies in Chinese human geography. This review article mainly contributes to existing literature by providing a framework to understand and design measures of subjective well-being and introducing some widely adopted scales which are readily available for the Chinese geographers to collect data in future studies. This article also points out that existing studies about smart cities mainly focus on the application of information technologies in the analysis of urban built environment and human activities. However, not many studies have investigated the question to what extent smart cities may promote people's subjective well-being. Therefore, the measures of subjective well-being summarized in this article may provide a pool of indicators to monitor national well-being and facilitate the development of smarter cities.

Key words: subjective well-being, measures, life satisfaction, affective well-being, smart city