Theoretical and methodological problems of measuring social comfort: results of empirical analysis based on Russian data

Theoretical and methodological problems of measuring social comfort: results of empirical analysis based on Russian data

Автор: Shakleina Marina V., Volkova Maria I., Shaklein Konstantin I., Yakiro Stanislav R.

Журнал: Economic and Social Changes: Facts, Trends, Forecast @volnc-esc-en

Рубрика: Theoretical issues

Статья в выпуске: 5 т.13, 2020 года.

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The research is aimed at developing theoretical aspects of the latent category “social comfort”, searching for new assessment methods and opportunities for using various types of information resources (big data, continuous and sample population surveys, state and administrative statistics). Development of the axiomatics of a new category and its modeling are necessary to determine a real level of population's well-being in dynamics, to assess true quality of people's life. The purpose of the research is aimed at development of theoretical and methodological foundations of social comfort as a latent category in the discourse of social processes and the test of its assessment using the method of generalized principal components. The main results of the study include the clarification of connotations and development of axiomatics for the new category “social comfort”; systematization of relevant international surveys, and the formation of reliable categories that ensure the validity of the results; assessment of the level of social comfort using the method of generalized principal components for a space-time sample - the STATIS method. The peculiarity of the method, used for space-time sampling, is an opportunity to simultaneously study object-feature matrices, related to different time points, and the identification of the parameters that mostly determine the scattering of observation objects: in our case, the regions of the Russian Federation, on a plane of main components of the generalized (compromise) space. The scientific novelty of the research is development of the axiomatics of the new category “social comfort”, which allows measuring and studying a person from the point of view of his inclusion in society, semantic correlation of various types of activity with time and external situation, expanding the subjective aspect of measuring the quality of life as one of the most important categories of social and economic science; the formation of new approaches to modeling and evaluating social comfort. The study is of practical interest to researchers, and its results may be used for creating socio-economic development programs in Russian regions.

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Social comfort, axiomatics, synthetic latent category, quality of life, statis

Короткий адрес: https://sciup.org/147225485

IDR: 147225485   |   DOI: 10.15838/esc.2020.5.71.8

Список литературы Theoretical and methodological problems of measuring social comfort: results of empirical analysis based on Russian data

  • Easterlin R.A. Explaining happiness. Proceedings of the National Academy of Sciences, 2003, vol. 100, no. 19, pp. 11176–11183. DOI: 10.1073/pnas.1633144100
  • Frey B.S., Stutzer A. Happiness and Economics: How the Economy and Institutions Affect Human Well-Being. Princeton University Press, 2010. 220 p.
  • Powdthavee N. Unhappiness and crime: Evidence from South Africa. Economica, 2005, vol.72, no. 287, pp. 531–547. DOI: 10.1111/j.0013-0427.2005.00429.x
  • Miringoff M., Miringoff M.L. The Social Health of the Nation: How America is Really Doing. Oxford University Press, 1999. 241 p.
  • Lane R.E. Quality of life and quality of persons: A new role for government? Political theory, 1994, vol. 22(2), pp. 219–252. DOI: 10.1177/0090591794022002002
  • Layard P.R.G., Layard R. Happiness: Lessons from a New Science. Penguin UK, 2011. DOI: 10.2307/20031793
  • Aivazyan S.A. Analiz kachestva i obraza zhizni naseleniya: monografiya [Analysis of the Quality and Lifestyle of the Population: Monograph]. Moscow: TsEMI RAN, 2012. 432 p.
  • Antipina O.N. Economics of happiness as an academic research discipline. Voprosy ekonomiki=Voprosy Ekonomiki, 2012, no. 2, pp. 94–107. DOI: 10.32609/0042-8736-2012-2-94-107 9 (in Russian).
  • Rodionova L.A. Methodological aspects of measuring and modeling the level of happiness. Ekonomika. Upravlenie. Pravo= Economics.Management. Law, 2012, no. 1-2(25), pp. 25–30 (in Russian).
  • Cobb C., Halstead T., Rowe J. The Genuine Progress Indicator: Summary of Data and Methodology. Redefining Progress, San Francisco, 1995. Vol. 15.
  • Estes R.J. Praxis: Resources for social and economic development. School of Social work & Practice, University of Pennsylvania, 1995.
  • Rahman T., Mittelhammer R.C., Wandschneider P. Measuring quality of life across countries: A multiple indicators and multiple causes approach. The Journal of Socio-Economics, 2011, vol. 40(1), pp.43–52. DOI: 10.1016/j.socec.2010.06.002
  • Kacapyr E. Are you middle class? American Demographics, 1996, vol. 18(10), pp. 30–35.
  • Andreev E.M., Alekseev A.I., Zubarevich N.V. Rossiya regionov: v kakom sotsial’nom prostranstve my zhivem? [Russia of Regions: What Social Space Do We Live in?]. Moscow: Pomatur, 2005. 278 p.
  • Schmidt-Traub G, Kroll C., Teksoz K., Durand-Delacre D., Sachs D. National baselines for the sustainable development goals assessed in the SDG Index and dashboards. Nature Geoscience, 2017, vol. 10, pp. 547–555. DOI: 10.1038/NGEO2985
  • Ferrans C., Powers M. Quality of life index: Development and psychometric properties. Advances in Nursing Science, 1985, vol. 8, pp. 15–24. DOI: 10.1097/00012272-198510000-00005
  • Raphael D., Waalen J., Karbanow A. Factor analytic properties of the quality of life profile: Examination of the nine subdomain Quality of Life model. Psychological Reports, vol. 88(1), pp. 265–276. DOI: 10.2466/ pr0.2001.88.1.265
  • Hagerty M. et al. Quality of life Indexes for National Policy: Review and Agenda for Research. Social Indicator Research, 2001, vol. 55(1), pp. 1–97. DOI: 10.1023/A:1010811312332
  • Veenhoven R. Happy life expectancy: A comprehensive measure of quality of life in nations. Social Indicators Research, 1996, vol. 39(1), pp. 1–58. DOI: 10.1007/BF00300831
  • Kahneman D., Deaton A. High income improves evaluation of life but not emotional well-being. Proceedings of the National Academy of Sciences, 2010, vol. 107(38), pp. 16489–16493. DOI: 10.1073/pnas.1011492107
  • How’s Life? 2020: Measuring Well-being. Paris, OECD Publishing, 2020. DOI: 10.1787/9870c393-en
  • Prata D.N. et al Social data analysis of Brazilian’s mood from Twitter. International Journal of Social Science and Humanity, 2016, vol. 6(3), pp. 179. DOI: 10.7763/IJSSH.2016.V6.640
  • Nguyen Q.C. Leveraging geotagged Twitter data to examine neighborhood happiness, diet, and physical activity. Applied Geography, 2016, vol. 73, pp. 77–88. DOI: 10.1016/j.apgeog.2016.06.003
  • Yang C., Srinivasan P. Life satisfaction and the pursuit of happiness on Twitter. PloS one, 2016, vol. 11(3), pp. 1–30. DOI: 10.1371/journal.pone.0150881
  • Wang W., Hernandez I., Newman D.A., He J., Bian J. Twitter analysis: Studying US weekly trends in work stress and emotion. Applied Psychology, 2016, vol. 65(2), pp. 355–378. DOI: 10.1111/apps.12065
  • Liu P., Tov W., Kosinski M., Stillwell D.J., Qiu L. Do Facebook status updates reflect subjective well-being? Cyberpsychology, Behavior, and Social Networking, 2015, vol. 18(7), pp. 373–379. DOI: 10.1089/cyber.2015.0022
  • LiKamWa R., Liu Y., Lane N.D., Zhong L. Moodscope: Building a mood sensor from smartphone usage patterns. Proceeding of the 11th annual international conference on Mobile systems, applications, and services, 2013, pp. 389–402. DOI: 10.1145/2462456.2464449
  • Schwartz H.A., Sap M., Kern M.L., Eichstaedt J.C., Kapelner A., Agrawal M., Kosinski M. Predicting individual well-being through the language of social media. Biocomputing 2016: Proceedings of the Pacific Symposium, 2016, pp. 516–527, DOI: 10.1142/9789814749411_0047
  • Carlquist E., Nafstad H., Blakar R., Ulleberg P., Delle Fave A., Phelps J. Well-being vocabulary in media language: An analysis of changing word usage in Norwegian newspapers. The Journal of Positive Psychology, 2017, vol. 12 (2), pp. 99–109, DOI: 10.1080/17439760.2016.1163411
  • Algan Y., Beasley E., Guyot F., Higa K., Murtin F.,Senik,C. Big data measures of well-being: Evidence from a Google well-being index in the United States. OECD Statistics Working Papers, 2016. 38 p. DOI: 10.1787/5jlz9hpg0rd1-en
  • Fantazzini D., Shakleina M., Yuras N. Big data for computing social well-being indices of the Russian population. Applied Econometrics, 2018, vol. 50, pp. 43–66.
  • Mavragani A., Tsagarakis K. YES or NO: Predicting the 2015 Greek Referendum results using Google Trends. Technological Forecasting and Social Change, 2016, vol. 109, pp. 1–5. DOI: 10.1016/j.techfore.2016.04.028
  • Oliveira-Brochado A. Google search-based sentiment indexes. IIMB Management Review, 2019, pp. 1–38. DOI: 10.1016/j.iimb.2019.10.015
  • Da Z., Engelberg J., Gao P. The sum of all FEARS investor sentiment and asset prices. The Review of Financial Studies, 2015, vol. 28(1), pp. 1–32. DOI: 10.1093/rfs/hhu072
  • Singer E. The use of incentives to reduce nonresponse in household surveys. Survey nonresponse, 2002, vol. 51, pp. 163–177.
  • Vissing-Jorgensen A. Perspectives on behavioral finance: Does” irrationality” disappear with wealth? Evidence from expectations and actions. NBER macroeconomics annual, 2003, vol. 18, pp. 139–194. DOI: 10.1086/ma.18.3585252
  • Askitas N., Zimmermann K.F. Google econometrics and unemployment forecasting. 2009. Available at: https://ssrn.com/abstract=1465341
  • Varian H.R. Big data: New tricks for econometrics. Journal of Economic Perspectives, 2014, vol. 28(2), pp. 3–28. DOI: 10.1257/jep.28.2.3.
  • Reimsbach-Kounatze C. The proliferation of “big data” and implications for official statistics and statistical agencies: A preliminary analysis. OECD Digital Economy Papers, no. 245. OECD Publishing, 2015. DOI: 10.1787/5js7t9wqzvg8-en
  • Della Penna N., Huang H. Constructing consumer sentiment index for US using Google searches. Working Papers, no. 26. University of Alberta, 2009. 22 p.
  • Benjamin D.J. Beyond happiness and satisfaction: Toward well-being indices based on stated preference. American Economic Review, 2014, vol. 104, no. 9, pp. 2698–2735. DOI: 10.1257/aer.104.9.2698
  • Baker S., Fradkin A. The impact of unemployment insurance on job search: Evidence from Google search data. Review of Economics and Statistics, 2017, vol. 99(5), pp. 756–768. DOI: 10.1162/REST_a_00674
  • Josselin R. The Diary of Ralph Josselin, 1616–1683(vol.3). OUP Oxford, 1991. 707 p.
  • Crowley J.E. The Invention of Comfort: Sensibilities and Design in Early Modern Britain and Early America. JHU Press, 2003. 349 p.
  • Berens L.H. The Digger Movement in the Days of the Commonwealth, 2014. 315 p.
  • Smith A. An Inquiry into the Nature and Causes of the Wealth of Nations. JJ Tourneisen and JL Legrand, 1791. DOI: 10.1093/oseo/instance.00043218
  • Odile-Bernez M. Comfort, the acceptable face of luxury: An Eighteenth-century cultural etymology. Journal for Early Modern Cultural Studies, 2014, vol. 14(2), pp. 3–21. DOI: 10.1353/jem.2014.0015
  • Scitovsky T. The Joyless Economy: The Psychology of Human Satisfaction. Oxford University Press on Demand, 1992. 449 p.
  • Slater K. Human Comfort. Vol. 1. USA: CC Thomas Pub Ltd., 1985.
  • Kolcaba K. Comfort Theory and Practice: A Vision for Holistic Health Care and Research. Springer Publishing Company, 2003. 201 p.
  • Tetior A.N. Ekologicheskaya garmoniya, krasota, komfortnost’ goroda (na baze ekologicheskoi infrastruktury) [Ecological Harmony, Beauty, Comfort of the City (based on Ecological Infrastructure)]. Moscow: FGOU VPO MGUP, 2010. 312 p.
  • Tetior A.N. Ekologicheskaya infrastruktura i sreda zhizni [Ecological Infrastructure and Living Environment]. Moscow: REFIA, 2002. 102 p.
  • Merinov Yu.N., Merinova Yu.Yu. Ecological and social comfort of the population in the southwestern part of the Rostov region. In: Aktual’nye voprosy i innovatsionnye tekhnologii v razvitii geograficheskikh nauk [Topical issues and innovative technologies in the development of geographical sciences], 2020. Pp. 328–331 (in Russian).
  • Cabanac M. Pleasure and joy, and their role in human life. In: Creating the Productive Workplace. D. Clements-Croome ed. London: E&FN Spon, 2006. Pp. 40–50.
  • Lyons A.C., Spicer J. A new measure of conversational experience: The speaking extent and comfort scale (SPEACS). Assessment, 1999, vol. 6(2), pp. 189–202. DOI: 10.1177/107319119900600206
  • Owens T.J., Stryker S., Goodman N. (ed.) Extending Self-Esteem Theory and Research: Sociological and Psychological Currents. UK: Cambridge University Press, 2001, pp. 198–222.
  • Spake D., Beatty S., Brockman B., & Crutchfield T. Consumer comfort in service relationships: Measurement and importance. Journal of Service Research, 2003, vol. 5(4), pp. 316–332. DOI: 10.1177/1094670503005004004
  • Cole R.J. Re-contextualizing the notion of comfort. Building Research & Information, 2008, vol. 36(4), pp. 323–336. DOI: 10.1080/09613210802076328
  • Shin J. Toward a theory of environmental satisfaction and human comfort: A process-oriented and contextually sensitive theoretical framework. Journal of Environmental Psychology, 2016, vol. 45, pp. 11–21. DOI: 10.1016/ j.jenvp.2015.11.004
  • Stiglitz J., Sen A., Fitoussi J. Report by the Commission on the Measurement of Economic Performance and Social Progress, 2009.
  • McGregor A., Sumner A. Beyond business as usual: what might 3-D wellbeing contribute to MDG momentum? IDS Bulletin, 2010, vol. 41(1), pp. 104–112. DOI: 10.1111/j.1759-5436.2010.00111.x
  • Allin P., Hand D.J. The Wellbeing of Nations: Meaning, Motive and Measurement. UK: John Wiley & Sons, 2014. DOI: 10.1002/9781118917046
  • Leshchaikina M.V. Econometric cross-country analysis of the living population social comfort. Prikladnaya ekonometrika=Applied Econometrics, 2014, no. 36 (4), pp. 102–117 (in Russian).
  • Scitovsky T. The Joyless Economy. An Inquiry into Human Satisfaction and Consumer Dissatisfaction. London: Oxford University Press, 1976. 310 р.
  • Obraztsova O.I., Popovskaya E.V. An essay on the multidimensional statistical methods to characterize the entrepreneurial context in Russian regions. Sotsiologicheskie issledovaniya=Sociological Studies, 2017, no. 4, pp. 93–106 (in Russian).
  • Escoufier Y. L’analyse conjointe de plusieurs matrices de données. In: M. Jolivet (Ed.) Biométrie et Temps. Paris: Société Française de Biométrie, 1980. Pp. 59–76.
  • Lavit C., Escoufier Y., Sabatier R., Traissac P. The ACT (STATIS method). Computational Statistics & Data Analysis, 1994, v. 18, pp. 97–119. DOI: 10.1016/0167-9473(94)90134-1
  • Rivadeneira F.J., Figueiredo A.M.S., Figueiredo F.O.S., Carvajal S.M. and Rivadeneira R.A. Analysis of Wellbeing in OECD Countries through STATIS Methodology. HOLOS, 2016, vol. 7, pp. 335–351.
  • Nguyen L.H., Holmes S. Ten quick tips for effective dimensionality reduction. PLoS Comput Biol 15(6), 2019, pp. 1006907. DOI: 10.1371/journal.pcbi.1006907.
  • Corrales D., Rodriguez O. Interstatis: The STATIS method for interval valued data. Rev. Mat, 2014, vol. 21(1), pp. 73–83.
  • Plato K. Two years after the report of the Stiglitz-Sen-Fitoussi Commission: What’s new in statistical measurement of social welfare and sustainable development? Voprosy statistiki=Voprosy Statistiki, 2011, no. 11, pp. 3–11 (in Russian).
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