{"title":"衡量城市竞争力的享乐幸福指数--一项探索性研究","authors":"Boon-Seng Tan","doi":"10.1108/cr-05-2023-0109","DOIUrl":null,"url":null,"abstract":"<h3>Purpose</h3>\n<p>This paper aims to explore the construction of a valid and reliable measure for the competitiveness of cities that excludes the drivers of competitiveness from the index construction. Not incorporating these drivers in the index avoids the problem of assuming relative contributions (i.e. weights) of these drivers on competitiveness as a maintained hypothesis.</p><!--/ Abstract__block -->\n<h3>Design/methodology/approach</h3>\n<p>From the definition that competitiveness is the ability of a city to sustain prosperity, this study derives a model called the hedonic well-being index (HWI) in which prosperity is measured by using the consumption of goods and service including leisure. This study then uses secondary data sources to construct an exploratory HWI (assuming a Cobb Douglas functional form) and compare this index to three benchmarks, namely, income, gross domestic product (GDP) per capita and the World Happiness Report (WHR) index. This study also review the component expenditure of the index across geographical locations.</p><!--/ Abstract__block -->\n<h3>Findings</h3>\n<p>The HWI is better predicted by the WHR index (a subjective well-being index) than by the GDP per capita (a measure of output), owing to the inclusion of leisure and household production absent in per capita GDP. This study explored and found regional variations in the distribution of the expenditure components in the HWI.</p><!--/ Abstract__block -->\n<h3>Originality/value</h3>\n<p>This paper demonstrates the feasibility of constructing an exploratory HWI to measure the competitiveness of cities using secondary data. The reliability of the index can be improved using primary data in future research. Separating the drivers from the definition of competitiveness allows testing of the contribution and interaction of these drivers on competitiveness.</p><!--/ Abstract__block -->","PeriodicalId":46521,"journal":{"name":"Competitiveness Review","volume":null,"pages":null},"PeriodicalIF":2.9000,"publicationDate":"2023-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The hedonic well-being index for measuring city competitiveness – an exploratory study\",\"authors\":\"Boon-Seng Tan\",\"doi\":\"10.1108/cr-05-2023-0109\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<h3>Purpose</h3>\\n<p>This paper aims to explore the construction of a valid and reliable measure for the competitiveness of cities that excludes the drivers of competitiveness from the index construction. Not incorporating these drivers in the index avoids the problem of assuming relative contributions (i.e. weights) of these drivers on competitiveness as a maintained hypothesis.</p><!--/ Abstract__block -->\\n<h3>Design/methodology/approach</h3>\\n<p>From the definition that competitiveness is the ability of a city to sustain prosperity, this study derives a model called the hedonic well-being index (HWI) in which prosperity is measured by using the consumption of goods and service including leisure. This study then uses secondary data sources to construct an exploratory HWI (assuming a Cobb Douglas functional form) and compare this index to three benchmarks, namely, income, gross domestic product (GDP) per capita and the World Happiness Report (WHR) index. This study also review the component expenditure of the index across geographical locations.</p><!--/ Abstract__block -->\\n<h3>Findings</h3>\\n<p>The HWI is better predicted by the WHR index (a subjective well-being index) than by the GDP per capita (a measure of output), owing to the inclusion of leisure and household production absent in per capita GDP. This study explored and found regional variations in the distribution of the expenditure components in the HWI.</p><!--/ Abstract__block -->\\n<h3>Originality/value</h3>\\n<p>This paper demonstrates the feasibility of constructing an exploratory HWI to measure the competitiveness of cities using secondary data. The reliability of the index can be improved using primary data in future research. Separating the drivers from the definition of competitiveness allows testing of the contribution and interaction of these drivers on competitiveness.</p><!--/ Abstract__block -->\",\"PeriodicalId\":46521,\"journal\":{\"name\":\"Competitiveness Review\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2023-12-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Competitiveness Review\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1108/cr-05-2023-0109\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BUSINESS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Competitiveness Review","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/cr-05-2023-0109","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS","Score":null,"Total":0}
The hedonic well-being index for measuring city competitiveness – an exploratory study
Purpose
This paper aims to explore the construction of a valid and reliable measure for the competitiveness of cities that excludes the drivers of competitiveness from the index construction. Not incorporating these drivers in the index avoids the problem of assuming relative contributions (i.e. weights) of these drivers on competitiveness as a maintained hypothesis.
Design/methodology/approach
From the definition that competitiveness is the ability of a city to sustain prosperity, this study derives a model called the hedonic well-being index (HWI) in which prosperity is measured by using the consumption of goods and service including leisure. This study then uses secondary data sources to construct an exploratory HWI (assuming a Cobb Douglas functional form) and compare this index to three benchmarks, namely, income, gross domestic product (GDP) per capita and the World Happiness Report (WHR) index. This study also review the component expenditure of the index across geographical locations.
Findings
The HWI is better predicted by the WHR index (a subjective well-being index) than by the GDP per capita (a measure of output), owing to the inclusion of leisure and household production absent in per capita GDP. This study explored and found regional variations in the distribution of the expenditure components in the HWI.
Originality/value
This paper demonstrates the feasibility of constructing an exploratory HWI to measure the competitiveness of cities using secondary data. The reliability of the index can be improved using primary data in future research. Separating the drivers from the definition of competitiveness allows testing of the contribution and interaction of these drivers on competitiveness.
期刊介绍:
The following list indicates the key issues in the Competitiveness Review. We invite papers on these and related topics. Special issues of the Review will collect papers on specific topics selected by the editors. Definition/conceptual framework of competitiveness Competitiveness diagnostics and rankings Competitiveness and economic outcomes Specific dimensions of competitiveness Competitiveness and endowments Competitiveness and economic development Location and business strategy International business and the role of MNCs Innovation and innovative capacity Clusters and cluster initiatives Institutions for competitiveness Public policy (e.g., innovation, cluster development, regional development) The Competitiveness Review aims to publish high quality papers directed at scholars, government institutions, businesses and practitioners. It appears in collaboration with key academic and professional groups in the field of competitiveness analysis and policy, including the Microeconomics of Competitiveness (MOC) network and The Competitiveness Institute (TCI) practitioner network for competitiveness, clusters and innovation.