An investigation of the relationship between library services and sustainable economic growth
Main Article Content
It is well known that knowledge is the source of modern economic growth, but the roles of library and information services on sustainable economic growth had not been well established. Thus, a case investigation was designed to identify the roles of library services in public libraries with the population, education, and income as a comparison on sustainable regional economic development. Such an investigation was based on organically combining correlation calculation, principal component calculation, and linear regression calculation. Results prove that some library services in public libraries have the highest contribution to the first principal component. It also demonstrates that the first principal component explains 85.0%, 95.0%, and 64.2% of the variation in the normalized gross regional products of Jiangsu Province, Hunan Province, and Gansu Province in China, respectively. Library services in public libraries, the population, education, and income appear to have a similarly important effect on sustainable regional development. Component score coefficients and linear relationships between the principal components and regional gross regional product can be used together to investigate the relationship between library services and sustainable economic growth. The proposed method provides new ideas for evaluating the roles of library services in sustainable economic growth.
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Aabø, S. 2005. Valuing the benefits of public libraries. Information Economics and Policy, Vol. 17, no. 2: 175–198. Available at: https://doi.org/10.1016/ j.infoecopol.2004.05.003.
Ali, A., Shang, J. and Saif, U. 2018. Socio-economic impact of CPEC on agricultural productivity of Pakistan: a principal component analysis. International Journal of Food and Agricultural Economics, Vol. 6, no. 3: 47-57. Available at: https://doi.org/10.22004/ag.econ.283868.
Banda, B. and Chewe, P. 2021. Circulation regulations and their effect on user return of books: the case of University of Zambia library. International Journal of Library and Information Services (IJLIS), Vol. 10, no. 2: 1-9. Available at: http://doi.org/10.4018/IJLIS.20210701.oa12.
Begdache, L., Kianmehr, H., Sabounchi, N., Marszalek, A. and Dolma, N. 2019. Principal component regression of academic performance, substance use and sleep quality in relation to risk of anxiety and depression in young adults. Trends in Neuroscience and Education, Vol. 15: 29-37. Available at: https://doi.org/ 10.1016/j.tine.2019.03.002.
Blagden, J. and Harrington, J. 1990. How good is your library?: A review of approaches to the evaluation of library and information services, London: Aslib.
Bowden, R. 2018. The information theory of comparisons: With applications to statistics and the social sciences, Singapore: Springer.
Carson, R.T. 2012. Contingent valuation: A practical alternative when prices aren't available. The Journal of Economic Perspectives, Vol. 26, no. 4: 27-42. Available at: https://doi.org/10.1257/jep.26.4.27.
Crawford, J.C. 2003. Evaluation of library and information services, London: Routledge.
Crawford, J.C. 2006. The culture of evaluation in library and information services, Oxford: Chandos.
Cummings, R.G. and Taylor, L.O. 1999. Unbiased value estimates for environmental goods: a cheap talk design for the contingent valuation method. The American Economic Review, Vol. 89, no. 3: 649-665. Available at: https://doi.org/10.1257/aer.89.3.649.
Fadhel, S., Delpha, C., Diallo, D., Bahri, I., Migan-Dubois, A., Trabelsi, M. and Mimouni, M.F. 2019. PV shading fault detection and classification based on IV curve using principal component analysis: application to isolated PV system. Solar Energy, Vol. 179: 1-10. Available at: https://doi.org/10.1016/j.solener.2018.12.048.
Fagerberg, J. and Srholec, M. 2013. Knowledge, capabilities, and the poverty trap: the complex interplay between technological, social, and geographical factors. In: P. Meusburger, J. Glückler and M. el Meskioui (eds). Knowledge and the economy, Knowledge and Space, Vol 5: 113-137, Dordrecht: Springer. Available at: doi:10.1007/978-94-007-6131-5_7.
Fox, W.P. 2018. Mathematical modeling for business analytics. Boca Raton, FL: CRC Press.
Glückler, J., Meusburger, P. and El Meskioui, M. 2013. Introduction: knowledge and the geography of the economy. In: P. Meusburger, J. Glückler and M. el Meskioui, eds. Knowledge and the economy, Knowledge and Space, Vol 5. Dordrecht: Springer. Available at: doi: 10.1007/978-94-007-6131-5_1.
Ho, R. 2018. Understanding statistics for the social sciences with IBM SPSS. Boca Raton: CRC Press.
Jobson, J.D. 1992. Applied multivariate data analysis - Volume II: categorical and multivariate methods, New York: Springer-Verlag.
Juntumaa, J.H., Laitinen, M.A. and Kirichenko, S. 2020. The Net Promoter Score (NPS) as a tool for evaluation of the user experience at culture and library services. Qualitative and Quantitative Methods in Libraries, Vol. 9, no. 2: 127-142.
Karouzakis, E., Raza, K., Kolling, C., Buckley, C.D., Gay, S., Filer, A. and Ospelt, C. 2018. Analysis of early changes in DNA methylation in synovial fibroblasts of RA patients before diagnosis. Scientific Reports, Vol. 8, no. 1: 7370. Available at: doi: 10.1038/s41598-018-24240-2.
Kinzig, A.P., Carpenter, S,. Dove, M., Heal, G., Levin, S., Lubchenco, J., Schneider, S.H. and Starrett, D. 2000. Nature and society: an imperative for integrated environmental research. In: Executive summary of a workshop sponsored by NSF (National Science Foundation), Developing Research Agenda for Linking Biogeophysical and Socioeconomic Systems, (p. 72), Tempe, Arizona: NSF.
Knight, C. 1856. Knowledge is power: a view of the productive forces of modern society and the results of labor, capital and skill, The Library of Congress: Boston, Gould and Lincoln. Available at: https://www.loc.gov/item/ltf89000239/.
Krolak, L. 2005. The role of libraries in the creation of literate environments. Paper presented at the Education for All (EFA) Global Monitoring Report 2006, Literacy for Life, Hamburg, Germany: UNESCO Institute for Education (UIE).
Kuznets, S.S. 1966. Economic growth and structure: selected essays, London: Heinemann.
Lee, S.J. and Chung, H.K. 2012. Analyzing altruistic motivations in public library valuation using contingent valuation method. Library & Information Science Research, Vol. 34, no. 1: 72-78. Available at: doi: 10.1016/j.lisr.2011.05.001.
Linhartová, V. and Stejskal, J. 2017. Public libraries services and their economic evaluation. Scientific Papers of the University of Pardubice, Series D, Vol. XXIV, no. 41(3/2017): 90-101.
Liu, J. 2007. The evaluation of worldwide digital reference services in libraries, Oxford: Chandos.
Made, H.W.G. 2018. An evaluation on library services using servqual method. SHS Web of Conferences, Vol. 42: 00071. Available at: doi: 10.1051/shsconf/20184200071.
Melnik, R. 2015. Mathematical and computational modeling: With applications in natural and social sciences, engineering, and the arts, Hoboken: John Wiley & Sons.
Mendes, M. 2011. Multivariate multiple regression analysis based on principal component scores to study relationships between some pre- and post-slaughter traits of broilers. Journal of Agricultural Sciences, Vol. 17, no. 1: 77-83. Available at: doi: 10.1501/Tarimbil_0000001158.
Missingham, R. 2005. Libraries and economic value: A review of recent studies. Performance Measurement and Metrics, Vol. 6, no. 3: 142-158. Available at: doi: 10.1108/14678040510636711.
Mofrad, H.V., Hemmat, M., Keshtkar, Z. and Yousefi, A. 2016. Quality evaluation of library services in Hamadan University of Medical Sciences based on European Foundation for Quality Management model (EFQM). Journal of Health Administration, Vol. 18, no. 62: 52-63.
Mokyr, J. 2002. The gifts of Athena: Historical origins of the knowledge economy, Princeton: Princeton University Press.
Mokyr, J. 2016. A culture of growth: The origins of the modern economy, Princeton: Princeton University Press.
Mukherjee, S.P., Sinha, B.K. and Chattopadhyay, A.K. 2018. Statistical methods in social science research, Singapore: Springer Nature.
National Bureau of Statistics of China. 2012. Statistical communiqué of the People’s Republic of China on the 2021 national economic and social development. Available at: http://data.stats.gov.cn.
Nesselroade, K.P. and Grimm L.G. 2019. Statistical applications for the behavioral and social sciences, 2nd Ed., Hoboken: John Wiley & Sons.
Papi, M. and Caracciolo, G. 2018. Principal component analysis of personalized biomolecular corona data for early disease detection. Nano Today, Vol. 21: 14-17. Available at: doi: 10.1016/j.nantod.2018.03.001.
Romão, J. and Neuts, B. 2017. Territorial capital, smart tourism specialization and sustainable regional development: experiences from Europe. Habitat International, Vol. 68: 64-74. Available at: doi: 10.1016/j.habitatint.2017.04.006.
Sharma, C. 2013. Beginning of diverse quality management methodologies in libraries: An outline. International Journal of Management, IT and Engineering, Vol. 3, no. 8: 617-624.
Sharma, S. 1996. Applied multivariate techniques, New York: John Wiley & Sons.
Sîrbu, M., Doinea, O. and Mangra, M.G. 2009. Knowledge based economy-the basis for insuring a sustainable development. Annals of the University of Petrosani, Economics, Vol. 9, no. 4: 227-232.
Smith, L.C. and Wong, M.A. 2016. Reference and information services: An introduction, 5th Ed., Santa Barbara, CA: ABC-CLIO.
Sousa, S.I.V., Martins, F.G., Alvim-Ferraz, M.C.M. and Pereira, M.C. 2007. Multiple linear regression and artificial neural networks based on principal components to predict ozone concentrations. Environmental Modelling & Software, Vol. 22, no. 1: 97-103. Available at: doi: 10.1016/j.envsoft.2005.12.002.
Stehr, N. 2007. Societal transformations, globalisation and the knowledge society. International Journal of Knowledge and Learning, Vol. 3, no. 2-3: 139-153.
Stejskal, J. and Hájek, P. 2015. Evaluating the economic value of a public service—the case of the Municipal Library of Prague. Public Money & Management, Vol. 35, no. 2: 145-152. Available at: doi:10.1080/09540962.2015.1007711.
Sterlacchini, A. 2008. R&D, higher education and regional growth: uneven linkages among European regions. Research Policy, Vol. 37, no. 6-7: 1096-1107. Available at: doi: 10.1016/j.respol.2008.04.009.
Strawinska-Zanko, U. and Liebovitch, L.S. 2018. Introduction to the mathematical modeling of social relationships. In: U. Strawinska-Zanko, and L. S. Liebovitch, eds. Mathematical Modeling of Social Relationships. Computational Social Sciences, Cham: Springer. https://doi.org/10.1007/978-3-319-76765-9_1.
Swain, A. 2005. Education as social action: knowledge, identity and power, London: Palgrave Macmillan.
Sweeney, R.T. 1994. Leadership in the post-hierarchical library. Library Trends, Vol. 43, no. 1: 62–94.
Throsby, D. 2003. Determining the value of cultural goods: how much (or how little) does contingent valuation tell us? Journal of Cultural Economics, Vol. 27, no. 3/4: 275-285. Available at: doi: 10.1023/A:1026353905772.
United Nation. 2002. Report of the World Summit on Sustainable Development. Johannesburg, South Africa, 26 August – 4 September 2002. Available at: https://digitallibrary.un.org/record/478154.
Warne, R.T. 2017. Statistics for the social sciences: a general linear model approach, Cambridge: Cambridge University Press. Available at: doi: 10.1017/9781316442715.
World Commission on Environment and Development. (1987). Our common future: The Brundtland Report. Oxford: Oxford University Press.
Xi, Q., Zhao, H., Hu, Y., Tong, Y. and Bao, P. 2018, Case studies and comparison between two models for assessing library service quality. The Electronic Library, Vol. 36, no. 6: 1099-1113. Available at: doi: 10.1108/EL-11-2016-0246.
Yockey, R.D. 2017. SPSS demystified: a simple guide and reference, New York: Routledge.
Zhao, Z., Fan, X., Qi, Y. and Zhai, Y. 2017. Multi-angle insulator recognition method in infrared image based on parallel deep convolutional neural networks. In: J. Yang et al. eds. Chinese Conference on Computer Vision, CCCV 2017. Communications in Computer and Information Science, Vol. 773: 303-314. Singapore: Springer. Available at: doi: 10.1007/978-981-10-7305-2_27.