Modeling the Ukrainian consumption
-
DOIhttps://doi.org/10.21511/gg.02(1).2018.05
-
Article InfoVolume 2 2018, Issue #1, pp. 34-44
- Cited by
- 752 Views
-
109 Downloads
This work is licensed under a
Creative Commons Attribution-NonCommercial 4.0 International License
Consumption is a fundamental determinant of the economic success. Consumer spending is approximately 70 percent of the Gross domestic product (GDP). It is common to divide consumer spending into nondurables (clothing and food), durables (“large” goods, which are not purchased very often), and of course services (day care, banking, medical). The way to identify how the economy influences consumption is to look at specific economic cycles. At the top of the economy (when the economy is strong), people reaction is physically powerful, and consumers spend money freely. When the economy falters, confidence falls; consumers cut back on the spending and conserve their money. They stop buying, getting out of debt and focus on saving money. Understanding consumption is vital to the implementation and development of marketing strategies. The purpose for this empirical research is to review main indicators, which influence on consumption and identify methodological issues in need of resolution, and present possible approaches that may prove helpful in resolving those issues. The growth of interest in modeling consumption has led to behaviorally conceptual models in which selection dynamics play a vital role. The authors introduce two empirical models, which demonstrate correlation between macroeconomic indicators, social factors and Consumer price index (CPI). The first conceptual model shows that the CPI is a straighter measure than per capita Gross domestic product of the standard of living in Ukraine. By including a wide range of thousands of services and goods with the basket (fixed), the CPI can obtain a precise estimate of the cost of living. The second empirical model shows the interdependence of economic indicators (CPI, GDP, and Average wage index (AWI)) and social factors (gender, age, location).
- Keywords
-
JEL Classification (Paper profile tab)M31, O30, O35
-
References25
-
Tables6
-
Figures4
-
- Figure 1. The impact of 14 components on CPI
- Figure 2. The impact of 14 components
- Figure 3. The impact of 14 components
- Figure 4. The impact of 14 components
-
- Table 1. Data variables (economic and social indicators)
- Table 2. Calculations of the result
- Table 3. Principal components analysis
- Table 4. Component weights
- Table 5. Principal Components
- Table A1. Input data (Economic and Social Indicators)
-
- Baldwin, C. Y., Hienerth, C., & Hippel, E. (2006). How user innovations become commercial products: A theoretical investigation and case study. Research Policy, 35(9), 1291-1313.
- Belk, R. W. (1974). An Exploratory Assessment of Situational Effects in Buyer Behavior. Journal of Marketing Research, 11, 156-163.
- Belk, R. W. (1988). Possessions and the Extended Self. Journal of Consumer Research, 15(2), 139-168.
- Franke, N., & Shah, S. (2003). How Communities Support Innovative Activities: An Exploration of Assistance and Sharing Among End-Users. Research Policy, 32(1), 157-178.
- Hippel, E. (2005). Democratizing Innovation. Cambridge MA: MIT Press.
- Hippel, E., Ogawa, S., & de Jong, J. P. J. (2011). The Age of the Consumer-Innovator. MIT Sloan Management Review, 53(1), 27-35.
- Jamrisko, M., Saraiva, C., & Tartar, A. (2015). The 15 Most Miserable Economies in the World
- Laros, F. J. M., & Steenkamp, J.-B. E.M. (2005). Emotions in consumer behavior: a hierarchical approach. Journal of Business Research, 58(10), 1437-1445.
- Lüthje, C., Herstatt, C., & von Hippel, E. (2005). User-innovators and “local” information: The case of mountain biking. Research Policy, 34(6), 951-965.
- Maslow, A. H. (1943). A theory of human motivation. Psychological Review, 50(4), 370-396.
- Raasch, C., Herstatt, C., & Lock, P. (2008). The dynamics of user innovation: drivers and impediments of innovation activities. International Journal of Innovation Management, 12(3), 377-398.
- Roberts, J., Gwin, C., & Martińez, C. R. (2004). The Influence of Family Structure on Consumer Behavior: A Re-Inquiry and Extension of Rindfleisch et al. (1997) in Mexico. Journal of Marketing Theory and Practice, 12(1), 61-79.
- Rugy, V. (2016). And the World’s Most Miserable Economies Are.
- Skinner, B. F. (1938). The Behaviour of Organisms. In R. East (Ed.) (1990), Changing Consumer Behaviour. London: Cassell Educational Limited.
- Solomon, M. R. (1983). The World of Products as Social Stimuli: A Symbolic Interactionism Perspective. Journal of Consumer Research, 10(3), 319-329.
- Solomon, M. R. (1995). Consumer Behaviour (3rd ed.). London: Prentice Hall.
- Stayman, P. H, & Deshpande, R. (1989). Situational Ethnicity and Consumer Behaviour. Journal of Consumer Research, 16(3), 361-371.
- 18. The National Bank of Ukraine (2016). Macroeconomic indicators.
- The State Statistics Service of Ukraine (1999-2013). Structure of total expenditure.
- The State Statistics Service of Ukraine (2016). Economic and Financial Data for Ukraine.
- Tietz, R., Morrison, P., Lüthje, C., & Herstatt, C. (2005). The process of user-innovation: a case study in a user goods setting. International Journal of Product Development, 2(4), 321-338.
- Tobacyk, J., Babin, B., Attaway, J., Socha, S., Shows, D., & James K. (2011). Materialism through the eyes of Polish and American consumers. Journal of Business Research, 64(9), 944-950.
- Tomer, J. (2002). Intangible Factors in the Eastern European Transition: A Socio-Economic Analysis. Post-Communist Economies, 14(4), 421-444.
- Tsalikis, J., & Seaton, B. (2008). Consumer Perceptions of Business Ethical Behavior in Former Eastern Block Countries. Journal of Business Ethics, 82(4), 919-928.
- Trading economics (1987-2016). Ukraine GDP.