The Effects of Personal Values on Online Buying Intention
DOI:
https://doi.org/10.14738/assrj.106.2.15007Keywords:
Unified Theory of Acceptance and Use of Technology 2, Schwartz’s Theory of Human Values, Online Buying Intention, User Technology AcceptanceAbstract
E-commerce has emerged to be pervasive channel as consumers continue to adopt the use of digitally enabled technologies to make online purchases. In developing nations, digital commerce continues to gain prominence. This study examines the influence of personal values on online consumer purchase. Using the Theory of Human Values and the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), the effects of personal values Self-Direction, Hedonism, Achievement and Security on the constructs in technology adoption (UTAUT2) model were investigated. Data for this study was collected from 424 respondents and analysed using structural equation modeling. The results show that Self-Direction, Security, Achievement and Hedonism influence various constructs in the UTAUT2 model. Notably, Self-Direction, Security and Hedonism influenced Effort Expectancy and Facilitating Conditions. While Achievement and Hedonism influenced Habit. This elucidates the influence of multiple personal values on the consumer’s motivation towards the performance of online shopping, specifically, to master skills needed (Effort Expectancy), obtain support (Facilitating Conditions) and repeat online buying behaviour (Habit). The findings hope to shed insight on the influence of personal values on the consumers’ motivation to use online purchasing; allowing e-commerce managers to improve consumer communication and digital strategies.
References
UNCTAD (2021, May 3). Global E-commerce Jumps to $26.7 trillion, Covid-19 boosts online sales. https://unctad.org/news/global-e-commerce-jumps-267-trillion-covid-19-boosts-onlinesales
Morgan Stanley. (n.d.). Here’s why e-commerce growth can stay stronger for longer. https://www.morganstanley.com/ideas/global-ecommerce-growth-forecast-2022
Insider Intelligence. (2022). Southeast Asia sees the fastest digital sales growth in the world. https://www.insiderintelligence.com/content/southeast-asia-sees-fastest-digital-sales-growth-world
Vuleta, B. Ecommerce statistics. https://99firms.com/blog/ecommerce-statistics/#gref
Kluckhohn, C. (1951). Values and value-orientations in the theory of action: An exploration in definition and classification. In T. Parsons & E. Shils (Eds.), Toward a general theory of action (pp. 388–433). Cambridge, MA: Harvard University Press.
Rokeach, M., 1973. The nature of human values. Free press.
Schwartz, S.H., 1992. Universals in the content and structure of values: Theoretical advances and empirical tests in 20 countries. In Advances in experimental social psychology (Vol. 25, pp. 1-65). Academic Press.
Sagiv, L., Roccas, S., Cieciuch, J., & Schwartz, S. H. (2017). Personal values in human life. Nature Human Behaviour, 1(9), 630-639.
Austin, J.T. and Vancouver, J.B., 1996. Goal constructs in psychology: Structure, process, and content. Psychological Bulletin, 120(3), p.338.
Baumgartner, H., Pieters, R., Haugtvedt, C., Herr, P. and Kardes, F., 2008. Goal-directed consumer behavior. Handbook of consumer psychology, pp.367-92. 153
Moskowitz, G. B. (2012). The representation and regulation of goals.
Bagozzi, R. P., & Dholakia, U. (1999). Goal setting and goal striving in consumer behavior. Journal of marketing, 63(4_suppl1), 19-32.
Kahle, L. R. (1983). Social values and social change: Adaptation to life in America. Praeger Publishers.
Mitchell, A., 1983. The nine American lifestyles: Who we are and where we're going. Scribner Book Company.
Schwartz, S. H., & Cieciuch, J. (2022). Measuring the refined theory of individual values in 49 cultural groups: Psychometrics of the revised Portrait Value Questionnaire. Assessment, 29(5), 1005-1019.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management science, 35(8), 982–1003.
Venkatesh, V., Morris, M.G., Davis, G.B. and Davis, F.D., 2003. User acceptance of information technology: Toward a unified view. MIS quarterly, pp.425-478.
Venkatesh, V., Thong, J.Y. and Xu, X., 2016. Unified theory of acceptance and use of technology: A synthesis and the road ahead. Journal of the association for Information Systems, 17(5), pp.328-376.
Jayawardhena, C., 2004. Personal values’ influence on e‐shopping attitude and behaviour. Internet Research. https://doi.org/10.1108/10662240410530844
Wu, L., Cai, Y., & Liu, D. (2011). Online shopping among Chinese consumers: An exploratory investigation of demographics and value orientation. International journal of consumer studies, 35(4), 458-469.
Makkonen, M., Frank, L. and Kemppainen, T., 2019. The Effects of Individual Values on Online Shopping Spending. In Bled eConference. University of Maribor.
Bagozzi, R.P., 2007. The legacy of the technology acceptance model and a proposal for a paradigm shift. Journal of the Association for Information Systems, 8(4), p.3.
Kahle, L.R. and Xie, G.X., 2008. Social values in consumer psychology. Handbook of consumer psychology, pp.575-585.
Schwartz, S., 2006. A theory of cultural value orientations: Explication and applications. Comparative sociology, 5(2-3), pp.137-182.
Verplanken, B., & Holland, R. W. (2002). Motivated decision making: effects of activation and selfcentrality of values on choices and behavior. Journal of personality and social psychology, 82(3), 434.
Allport, G. W., & Vernon, P. E. (1931). A test for personal values. Journal of Abnormal and Social Psychology, 26(3), 231-248.
Homer, P.M. and Kahle, L.R., 1988. A structural equation test of the value-attitude-behavior hierarchy. Journal of Personality and social Psychology, 54(4), p.638.
Kahle, L. R. (1986). The nine nations of North America and the value basis of geographic segmentation. Journal of Marketing, 50(2), 37-47. 154 Ang, Y. S. M. (2023). The Effects of Personal Values on Online Buying Intention. Advances in Social Sciences Research Journal, 10(6.2). 138-158.
Beatty, S.E., Kahle, L.R. and Homer, P., 1991. Personal values and gift-giving behaviors: A study across cultures. Journal of Business Research, 22(2), pp.149-157.
Novak, T. P., de Leeuw, J., & MacEvoy, B. (1992). Richness curves for evaluating market segmentation. journal of Marketing Research, 29(2), 254-267.
Kamakura, W. A., & Novak, T. P. (1992). Value-system segmentation: Exploring the meaning of LOV. Journal of consumer research, 19(1), 119-132.
Chaiken, S., Wood, W., & Eagly, A. H. (1996). Principles of persuasion.
Nasir, V. A., & Karakaya, F. (2014). Consumer segments in organic foods market. Journal of consumer marketing.
Gutman, J. (1982). A means-end chain model based on consumer categorization processes. Journal of marketing, 46(2), 60-72.
Reynolds, T. J., & Gutman, J. (1988). Laddering theory, method, analysis, and interpretation, Journal of Advertising Research, 28, 11 – 34
Bagozzi, R. P., & Dabholkar, P. A. (2000). Discursive psychology: An alternative conceptual foundation to means–end chain theory. Psychology & Marketing, 17(7), 535-586.
Brunsø, K., Scholderer, J., & Grunert, K. G. (2004). Testing relationships between values and food-related lifestyle: results from two European countries. Appetite, 43(2), 195-205.
Bagozzi, R. P., & Lee, K.-H. (1999). Consumer resistance to, and acceptance of, innovations. NA-Advances in Consumer Research Volume 26.
Emmons, R.A., 1996. Striving and feeling: Personal goals and subjective well-being.
Locke, E.A. and Latham, G.P., 1990. Work motivation and satisfaction: Light at the end of the tunnel. Psychological science, 1(4), pp.240-246.
Locke, E. A., & Henne, D. (1986). Work motivation theories. International review of industrial and organizational psychology, 1, 1-35.
Venkatesh, V., Thong, J.Y. and Xu, X., 2012. Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS quarterly, pp.157-178.
Shaw, N. and Sergueeva, K., 2019. The non-monetary benefits of mobile commerce: Extending UTAUT2 with perceived value. International Journal of Information Management, 45, pp.44-55.
Ramírez-Correa, P., Rondán-Cataluña, F. J., Arenas-Gaitán, J., & Martín-Velicia, F. (2019). Analysing the acceptation of online games in mobile devices: An application of UTAUT2. Journal of Retailing and Consumer Services, 50, 85-93.
Alalwan, A.A., Dwivedi, Y.K. and Rana, N.P., 2017. Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information Management, 37(3), pp.99-110.
Morosan, C. and DeFranco, A., 2016. It's about time: Revisiting UTAUT2 to examine consumers’ intentions to use NFC mobile payments in hotels. International Journal of Hospitality Management, 53, pp.17-29.
Oliveira, T., Thomas, M., Baptista, G. and Campos, F., 2016. Mobile payment: Understanding the 155 determinants of customer adoption and intention to recommend the technology. Computers in Human Behavior, 61, pp.404-414.
Lallmahomed, M. Z., Lallmahomed, N., & Lallmahomed, G. M. (2017). Factors influencing the adoption of e-Government services in Mauritius. Telematics and Informatics, 34(4), 57-72.
Escobar-Rodríguez, T. and Carvajal-Trujillo, E., 2013. Online drivers of consumer purchase of website airline tickets. Journal of Air Transport Management, 32, pp.58-64.
Dwivedi, Y.K., Shareef, M.A., Simintiras, A.C., Lal, B. and Weerakkody, V., 2016. A generalised adoption model for services: A cross-country comparison of mobile health (m-health). Government Information Quarterly, 33(1), pp.174-187.
Lian, J.W., 2015. Critical factors for cloud-based e-invoice service adoption in Taiwan: An empirical study. International Journal of Information Management, 35(1), pp.98-109.
Sharifi fard, S., Tamam, E., Hj Hassan, M. S., Waheed, M., & Zaremohzzabieh, Z. (2016). Factors affecting Malaysian university students’ purchase intention in social networking sites. Cogent Business & Management, 3(1), 1182612.
Hew, J. J., Lee, V. H., Ooi, K. B., & Wei, J. (2015). What catalyses mobile apps usage intention: an empirical analysis. Industrial Management & Data Systems.
Agudo Peregrina, Á. F., Chaparro Peláez, J., Hernández García, Á., Iglesias Pradas, S., Navarro Carrillo, E., Pascual Miguel, F. J., & Portillo García, J. (2013). Creación de empresas en entornos universitarios. Madrid, España: Universidad Politécnica de Madrid.
Wong, C. H., Wei-Han Tan, G., Loke, S. P., & Ooi, K. B. (2014). Mobile TV: a new form of entertainment? Industrial Management & Data Systems, 114(7), 1050-1067.
Suyoto, S. M. (2016). Pranowo, “. In Exploring Mobile Wallet Adoption in Indonesia Using UTAUT2,” 2016 2nd International Conference on Science and Technology (ICST) (pp. 11-16).
Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: Toward a conceptual model of utilization. MIS quarterly, 125-143.
Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice-Hall.
Brown, S. A., & Venkatesh, V. (2005). Model of adoption of technology in households: A baseline model test and extension incorporating household life cycle. MIS quarterly, 399-426.
Childers, T. L., Carr, C. L., Peck, J., & Carson, S. (2001). Hedonic and utilitarian motivations for online retail shopping behavior. Journal of retailing, 77(4), 511-535.
Dodds, W. B., Monroe, K. B., & Grewal, D. (1991). Effects of price, brand, and store information on buyers’ product evaluations. Journal of marketing research, 28(3), 307-319.
Limayem, M., Hirt, S. G., & Cheung, C. M. (2007). How habit limits the predictive power of intention: The case of information systems continuance. MIS quarterly, 705-737.
Murray, K. B., & Häubl, G. (2007). Explaining cognitive lock-in: The role of skill-based habits of use in consumer choice. Journal of Consumer Research, 34(1), 77-88.
Kim, S.S., Malhotra, N.K. and Narasimhan, S., 2005. Research note—two competing perspectives on automatic use: A theoretical and empirical comparison. Information systems research, 16(4), pp.418-432. Ang, Y. S. M. (2023). The Effects of Personal Values on Online Buying Intention. Advances in Social Sciences Research Journal, 10(6.2). 138-158.
Cieciuch, J. and Schwartz, S.H., 2017. Values and the Human Being. The Oxford Handbook of the Human Essence, p.62.
Schwartz, S.H., 2012. An overview of the Schwartz theory of basic values. Online readings in Psychology and Culture, 2(1), pp.2307-0919.
Schwartz, S.H. and Bilsky, W., 1987. Toward a universal psychological structure of human values. Journal of personality and social psychology, 53(3), p.550.
Shim, S. and Eastlick, M.A., 1998. The hierarchical influence of personal values on mall shopping attitute and behavior. Journal of Retailing, 74(1), pp.139-160.
Choden, K., Bagchi, K.K., Udo, G.J. and Kirs, P.J., 2019. The influence of individual values on internet use: A multinational study. International Journal of Information Management, 46, pp.198-209.
Hansen, T., 2008. Consumer values, the theory of planned behaviour and online grocery shopping. International Journal of Consumer Studies, 32(2), pp.128-137.
Byrne, B.M., 2010. Structural equation modeling with AMOS: basic concepts, applications, and programming (multivariate applications series). New York: Taylor & Francis Group, 396, p.7384.
Ramayah, T., Cheah, J., Chuah, F., Ting, H. and Memon, M.A., 2018. Partial least squares structural equation modeling (PLS-SEM) using smartPLS 3.0.
Hair Jr, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM) Sage Publications. Thousand Oaks, CA, USA.
Diamantopoulos, A., & Siguaw, J. A. (2006). Formative versus reflective indicators in organizational measure development: A comparison and empirical illustration. British journal of management, 17(4), 263-282. [75] Henseler, J., Hubona, G. and Ray, P.A., 2016. Using PLS path modeling in new technology research: updated guidelines. Industrial Management & Data Systems.
Bagozzi, R.P. and Yi, Y., 1988. On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), pp.74-94.
Fornell, C. and Larcker, D.F., 1981. Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), pp.39-50.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing theory and Practice, 19(2), 139-152.
Geisser, S. (1974). A predictive approach to the random effect model. Biometrika, 61(1), 101-107.
Cohen, J. (1988). Set correlation and contingency tables. Applied psychological measurement, 12(4), 425-434.
Ajzen, I. and Fishbein, M., 2000. Attitudes and the attitude-behavior relation: Reasoned and Automatic Processes. European review of social psychology, 11(1), pp.1-33.
Bardi, A. and Schwartz, S.H., 2003. Values and behavior: Strength and structure of relations. Personality and Social Psychology Bulletin, 29(10), pp.1207-1220.
Huffman, C., Ratneshwar, S. and Mick, D.G., 2000. Consumer goal structures and goal determination processes: An integrative framework. The why of consumption: Contemporary perspectives on consumer motives, goals, and desires, pp.9-35.
Kline, R.B., 2011. Principles and practice of structural equation modeling (3. Baskı). New York, NY: Guilford.
Venkatesh, V., 2000. Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information systems research, 11(4), pp.342-365.
Black, K. (2010). Business Statistics for Contemporary Decision-Making 6th Edition.
Wold, H. (1975). Path models with latent variables: The NIPALS approach. In Quantitative sociology (pp. 307-357). Academic Press.
Sarstedt M, Ringle CM and Hair JF. (2017a) Partial Least Squares Structural Equation Modeling. In: Homburg C, Klarmann M and Vomberg A (eds) Handbook of Market Research. Heidelberg: Springer.
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