Main Article Content

Zaira Camoiras-Rodríguez
Universidade de Santiago de Compostela – Facultade de Ciencias Económicas e Empresariais
Concepción Varela-Neira
Universidade de Santiago de Compostela – Facultade de Ciencias Económicas e Empresariais
Vol 29 No 3 (2020), Articles, pages 1-22
Submitted: 28-04-2020 Accepted: 05-11-2020 Published: 09-12-2020
Copyright How to Cite


The advantages that mobile commerce provides have attracted the attention of companies and consumers. Despite its potential benefits, research on the factors that influence how often it is used and bought is still scarce. This research contributes to a greater knowledge and understanding of the factors that influence how often it is bought in a mobile environment by relating the Technology Acceptance Model (TAM) to personality traits literature. This research is based on a sample of 200 individuals who have mobile devices with Internet access. The technique used to test the hypotheses is path analysis. The results show the indirect effect of the need for material resources and task orientation on the number of purchases in mobile commerce. Furthermore, the results reflect the important mediating role of an impulsive purchasing tendency in the level of purchase frequency.

Cited by

Article Details


Adams, D. A., Nelson, R. R., y Todd, P. A. (1992). Perceived usefulness, ease of use, and usage of information technology: A replication. MIS Quarterly, 16(2), 227-247. DOI:

Agyei, J., Sun, S., Abrokwah, E., Penney, E. K., y Ofori-Boafo, R. (2020). Mobile banking adoption: Examining the role of personality traits. SAGE Open, 10(2), 1-15. DOI:

Alalwan, A. A., Algharabat, R. S., Baabdullah, A. M., Rana, N. P., Qasem, Z., y Dwivedi, Y. K. (2020). Examining the impact of mobile interactivity on customer engagement in the context of mobile shopping. Journal of Enterprise Information Management, 33(3), 627-653. DOI:

Aldás-Manzano, J., Ruiz-Mafé, C., y Sanz-Blas, S. (2009). Exploring individual personality factors as drivers of M-shopping acceptance. Industrial Management & Data Systems, 109(6), 739-757. DOI:

Al-Samarraie, H., Eldenfria, A., y Dawoud, H. (2017). The impact of personality traits on users’ information-seeking behavior. Information Processing & Management, 53(1), 237-247. DOI:

Ambre, A., Gaikwad, P., Pawar, K., y Patil, V. (2019). Web and android application for comparison of e-commerce products. International Journal of Advanced Engineering, Management and Science, 5(4), 266-268. DOI:

Anderson, J. C., y Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411. DOI:

Ashraf, A. R., Thongpapanl, N., Menguc, B., y Northey, G. (2017). The role of m-commerce readiness in emerging and developed markets. Journal of International Marketing, 25(2), 25-51. DOI:

Aydın, G. (2019). Do personality traits and shopping motivations affect social commerce adoption intentions? Evidence from an emerging market. Journal of Internet Commerce, 18(4), 428-467. DOI:

Barakat, M. A. (2019). A proposed model for factors affecting consumers' impulsive buying tendency in shopping malls. Journal of Marketing Management, 7(1), 120-134. Recuperado de:

Barnett, T., Pearson, A. W., Pearson, R., y Kellermanns, F. W. (2015). Five-factor model personality traits as predictors of perceived and actual usage of technology. European Journal of Information Systems, 24(4), 374-390. DOI:

Bauer, D. J., Preacher, K. J., y Gil, K. M. (2006). Conceptualizing and testing random indirect effects and moderated mediation in multilevel models: New procedures and recommendations. Psychological Methods, 11(2), 142-163. DOI:

Baumeister, R. F. (2002). Yielding to temptation: Self-control failure, impulsive purchasing, and consumer behavior. Journal of Consumer Research, 28(4), 670-676. DOI:

Baumeister, R. F., Heatherton, T. F., y Tice, D. M. (1994). Losing control: How and why people fail at selfregulation. San Diego, CA: Academic Press.

Belk, R. W. (1984). Three scales to measure constructs related to materialism: Reliability, validity, and relationships to measures of happiness. En T. C. Kinnear (Ed.), Advances in Consumer Research, 11 (pp. 291-297). Provo, UT: Association for Consumer Research. Recuperado de:

Belk, R. W. (1985). Materialism: Trait aspects of living in the material world. Journal of Consumer Research, 12(3), 265-280. DOI:

Bentler, P. M. (1990). Comparative fit indices in structural models, Psychological Bulletin, 107(2), 238-246. DOI:

Bollen, K. A. (1989). A new incremental fit index for general structural equation models. Sociological Methods & Research, 17(3), 303-316. DOI:

Bosnjak, M., Galesic, M., y Tuten, T. (2007). Personality determinants of online shopping: Explaining online purchase intentions using a hierarchical approach. Journal of Business Research, 60(6), 597-605. DOI:

Brown, S. P., y Peterson, R. A. (1994). The effect of effort on sales performance and job satisfaction. Journal of Marketing, 58(2), 70-80. DOI:

Bruner, G. C., y Kumar, A. (2005). Explaining consumer acceptance of handheld Internet devices. Journal of Business Research, 58(5), 553-558. DOI:

Burton-Jones, A., y Hubona, G. S. (2006). The mediation of external variables in the technology acceptance model. Information & Management, 43(6), 706-717. DOI:

Chang, A., Hsieh, S. H., y Lin, F. (2013). Personality traits that lead members of online brand communities to participate in information sending and receiving. International Journal of Electronic Commerce, 17(3), 37-62. DOI:

Chen, J. V., Su, B.-C., y Widjaja, A. E. (2016). Facebook C2C social commerce: A study of online impulse buying. Decision Support Systems, 83, 57-69. DOI:

Chen, Y. F., y Lan, Y. C. (2018). An empirical study of the factors affecting mobile shopping in Taiwan. In Mobile Commerce: Concepts, methodologies, tools, and applications (pp. 1329-1340). Hershey, PA: IGI Global. DOI:

Chen, Y. M., Hsu, T. H., y Lu, Y. J. (2018). Impact of flow on mobile shopping intention. Journal of Retailing and Consumer Services, 41, 281-287. DOI:

Chong, A. Y. L. (2013). Mobile commerce usage activities: The roles of demographic and motivation variables. Technological Forecasting and Social Change, 80(7), 1350-1359. DOI:

Chopdar, P. K., Korfiatis, N., Sivakumar, V. J., y Lytras, M. D. (2018). Mobile shopping apps adoption and perceived risks: A cross-country perspective utilizing the Unified Theory of Acceptance and use of technology. Computers in Human Behavior, 86, 109-128. DOI:

Costa, P. T., y McCrae, R. R. (1992). Revised NEO personality inventory (NEO PI-R) and NEO five-factor inventory (NEO-FFI): Professional manual. Odessa, FL: Psychological Assessment Resources.

Cox, J. (2004). Ubiquitous consumption and the marketing mix. Journal of Internet Commerce, 3(2), 21-32. DOI:

Cudeck, R., y Browne, M. W. (1993). Alternative ways of assessing model fit. En K. A. Bollen y J. S. Long (Eds.), Testing structural equation models (pp. 1-9). Newbury Park, CA: Sage.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. DOI:

Dawson, J. F. (2014). Moderation in management research: What, why, when, and how. Journal of Business and Psychology, 29(1), 1-19. DOI:

Dickerson, M. D., y Gentry, J. W. (1983). Characteristics of adopters and non-adopters of home computers. Journal of Consumer research, 10(2), 225-235. DOI:

Dickman, S. J. (1990). Functional and dysfunctional impulsivity: Personality and cognitive correlates. Journal of Personality and Social Psychology, 58(1), 95-102. DOI:

Edwards, J. R., y Lambert, L. S. (2007). Methods for integrating moderation and mediation: A general analytical framework using moderated path analysis. Psychological Methods, 12(1), 1-22. DOI:

Faqih, K. M. S., y Jaradat, M.-I. R. M. (2015). Assessing the moderating effect of gender differences and individualism-collectivism at individual-level on the adoption of mobile commerce technology: TAM3 perspective. Journal of Retailing and Consumer Services, 22, 37-52. DOI:

Fishbein, M. A., y Ajzen, I., (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.

Fornell, C., y Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. DOI:

Groß, M. (2015). Exploring the acceptance of technology for mobile shopping: An empirical investigation among smartphone users. The International Review of Retail, Distribution and Consumer Research, 25(3), 215-235. DOI:

Gupta, A., y Arora, N. (2017). Understanding determinants and barriers of mobile shopping adoption using behavioral reasoning theory. Journal of Retailing and Consumer Services, 36, 1-7. DOI:

Hair, J. F., Anderson, R. E., Tatham, R. L., y Black, W. C. (1999). Análisis multivariante. Madrid: Prentice Hall.

Hair, J. F., Anderson, R. E., Tatham, R. L., y Black, W. C. (2010). Multivariate data analysis: A global perspective. (7th ed.). Upper Saddle River, NJ: Pearson Prentice-Hall.

Hernandez, B., Jimenez, J., y Martin, M. (2009). The impact of self-efficacy, ease of use and usefulness on e-purchasing: An analysis of experienced e-shoppers. Interacting with Computers, 21(1-2), 146-156. DOI:

Hirschman, E. C. (1980). Innovativeness, novelty seeking, and consumer creativity. Journal of Consumer Research, 7(3), 283-295. DOI:

Hu, L.-T., y Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: a Multidisciplinary Journal, 6(1), 1-55. DOI:

Huang, J., y Zhou, L. (2018). Timing of web personalization in mobile shopping: A perspective from uses and gratifications theory. Computers in Human Behavior, 88, 103-113. DOI:

Igbaria, M. (1992). An examination of microcomputer usage in Taiwan. Information & Management, 22(1), 19-28. DOI:

Igbaria, M., y Tan, M. (1997). The consequences of information technology acceptance on subsequent individual performance. Information & Management, 32(3), 113-121. DOI:

Igbaria, M., y Toraskar, K. (1992). Impact of end user computing on the individual: An integrated model. Information Technology & People, 6(4), 271-292. DOI:

Igbaria, M., Guimaraes, T., y Davis, G. B. (1995). Testing the determinants of microcomputer usage via a structural equation model. Journal of Management Information Systems, 11(4), 87-114. DOI:

Jiménez, N., San-Martín, S., y Puente, N. (2019). The path to mobile shopping compatibility. The Journal of High Technology Management Research, 30(1), 15-26. DOI:

Kacen, J. J., y Lee, J. A. (2002). The influence of culture on consumer impulsive buying behavior. Journal of Consumer Psychology, 12(2), 163-176. DOI:

Kamal, S., Chu, S. C., y Pedram, M. (2013). Materialism, attitudes, and social media usage and their impact on purchase intention of luxury fashion goods among American and Arab young generations. Journal of Interactive Advertising, 13(1), 27-40. DOI:

Kapoor, A. P., y Vij, M. (2018). Technology at the dinner table: Ordering food online through mobile apps. Journal of Retailing and Consumer Services, 43, 342-351. DOI:

Kats, R. (19 de febrero de 2020). AliExpress and Amazon are bolstering Spain’s booming ecommerce market. New York, NY: eMarketer. Recuperado de:

Kenny, D. A., Kaniskan, B., y McCoach, D. B. (2015). The performance of RMSEA in models with small degrees of freedom. Sociological Methods & Research, 44(3), 486-507. DOI:

Khan, A. N., Cao, X., y Pitafi, A. H. (2019). Personality traits as predictor of M-payment systems: A SEM-neural networks approach. Journal of Organizational and End User Computing (JOEUC), 31(4), 89-110. DOI:

Khorrami, M. S., Esfidani, M. R., y Delavari, S. (2015). The effect of situational factors on impulse buying and compulsive buying: Clothing. International Journal of Management, Accounting and Economics, 2(8), 823-837.

Kim, C., Li, W., y Kim, D. J. (2015). An empirical analysis of factors influencing M-shopping use. International Journal of Human-Computer Interaction, 31(12), 974-994. DOI:

Kim, M., Kim, J., Choi, J., y Trivedi, M. (2017). Mobile shopping through applications: Understanding application possession and mobile purchase. Journal of Interactive Marketing, 39, 55-68. DOI:

Kim, N. Y. (2018). The effect of advertising content control on advertising effectiveness in the different forced exposure circumstance. Journal of Promotion Management, 24(6), 845-862. DOI:

Lee, H. (2018). Intrinsic and extrinsic motivations affecting impulse-buying tendency in mobile shopping. Social Behavior and Personality: An International Journal, 46(4), 683-694. DOI:

Lee, T., Park, C., y Jun, J. (2014). Two faces of mobile shopping: Self-efficacy and impulsivity. International Journal of E-Business Research (IJEBR), 10(1), 15-32. DOI:

Lejoyeux, M., Mathieu, K., Embouazza, H., Huet, F., y Lequen, V. (2007). Prevalence of compulsive buying among customers of a Parisian general store. Comprehensive Psychiatry, 48(1), 42-46. DOI:

Li, M., Huang, L., Tan, C. H., y Wei, K. K. (2013). Helpfulness of online product reviews as seen by consumers: Source and content features. International Journal of Electronic Commerce, 17(4), 101-136. DOI:

Lim, S. H., Lee, S., y Kim, D. J. (2017). Is online consumers’ impulsive buying beneficial for e-commerce companies? An empirical investigation of online consumers’ past impulsive buying behaviors. Information Systems Management, 34(1), 85-100. DOI:

Lissitsa, S., y Kol, O. (2019). Four generational cohorts and hedonic m-shopping: Association between personality traits and purchase intention. Electronic Commerce Research, 1-26. DOI:

Liu, S., y Xiao, L. (2018). Research on the influence of website characteristics on consumers' impulsive purchase intention. En Proceedings of the 2018 2nd International Conference on Education, Economics and Management Research (ICEEMR 2018). Singapore (Singapore), June 9-10, 2018. Atlantis Press. DOI:

Lu, J., Yao, J. E., y Yu, C.-S. (2005). Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology. The Journal of Strategic Information Systems, 14(3), 245-268. DOI:

Luarn, P., y Lin, H.-H. (2005). Toward an understanding of the behavioral intention to use mobile banking. Computers in Human Behavior, 21(6), 873-891. DOI:

Mahatanankoon, P. (2007). The effects of personality traits and optimum stimulation level on text-messaging activities and m-commerce intention. International Journal of Electronic Commerce, 12(1), 7-30. DOI:

McDonald, R. P., y Ho, M.-H. R. (2002). Principles and practice in reporting structural equation analyses. Psychological Methods, 7(1), 64-82. DOI:

Miao, M., Jalees, T., Qabool, S., y Zaman, S. I. (2019). The effects of personality, culture and store stimuli on impulsive buying behavior. Asia Pacific Journal of Marketing and Logistics, 32(1), 188-204. DOI:

Millar, M., y Thomas, R. (2009). Discretionary activity and happiness: The role of materialism. Journal of Research in Personality, 43(4), 699-702. DOI:

Mowen, J. C. (2000). The 3M model of motivation and personality: Theory and empirical applications to consumer behavior. Norwell, MA: Kluwer Academic Press. DOI:

Natarajan, T., Balasubramanian, S. A., y Kasilingam, D. L. (2017). Understanding the intention to use mobile shopping applications and its influence on price sensitivity. Journal of Retailing and Consumer Services, 37, 8-22. DOI:

Natarajan, T., Balasubramanian, S. A., y Kasilingam, D. L. (2018). The moderating role of device type and age of users on the intention to use mobile shopping applications. Technology in Society, 53, 79-90. DOI:

Nicholls, J. (1984). Conceptions of ability and achievement motivation. En R. Ames y C. Ames (Eds.), Research on motivation in education (pp. 39-73). New York, NY: Academic Press.

Nicholls, J. (1989). The competitive ethos and democratic education. Cambridge, MA: Harvard University Press.

Observatorio Nacional de las Telecomunicaciones y de la Sociedad de la Información. (2019). El comercio electrónico B2C en España. 2018. Madrid: ONTSI. DOI:

O'Guinn, T. C., y Faber, R. J. (1989). Compulsive buying: A phenomenological exploration. Journal of Consumer Research, 16(2), 147-157. DOI:

Okazaki, S., y Mendez, F. (2013). Exploring convenience in mobile commerce: Moderating effects of gender. Computers in Human Behavior, 29(3), 1234-1242. DOI:

Otero-López, J. M., y Villardefrancos, E. (2013). Five-Factor Model personality traits, materialism, and excessive buying: A mediational analysis. Personality and Individual Differences, 54(6), 767-772. DOI:

Parsad, C., Prashar, S., y Tata, V. S. (2019). Influence of personality traits and social conformity on impulsive buying tendency: Empirical study using 3M model. International Journal of Strategic Decision Sciences (IJSDS), 10(2), 107-124. DOI:

Parsad, C., Prashar, S., Vijay, T. S., y Kumar, M. (2018). In-store stimuli and impulsive buying behaviour: Modeling through regression equation. International Journal of Strategic Decision Sciences (IJSDS), 9(3), 95-112. DOI:

Patel, V., Das, K., Chatterjee, R., y Shukla, Y. (2020). Does the interface quality of mobile shopping apps affect purchase intention? An empirical study. Australasian Marketing Journal (AMJ). DOI:

Peck, J., y Childers, T. L. (2006). If I touch it I have to have it: Individual and environmental influences on impulse purchasing. Journal of Business Research, 59(6), 765-769. DOI:

Podoshen, J. S., y Andrzejewski, S. A. (2012). An examination of the relationships between materialism, conspicuous consumption, impulse buying, and brand loyalty. Journal of Marketing Theory and Practice, 20(3), 319-334. DOI:

Preacher, K. J., Rucker, D. D., y Hayes, A. F. (2007). Addressing moderated mediation hypotheses: Theory, methods, and prescriptions. Multivariate Behavioral Research, 42(1), 185-227. DOI:

Putrawan, I. M. (2020). Personality on green consumer behaviour. International Journal of Psychosocial Rehabilitation, 24(2), 2374-2379. DOI:

Richins, M. L. (2013). When wanting is better than having: Materialism, transformation expectations, and product-evoked emotions in the purchase process. Journal of Consumer Research, 40(1), 1-18. DOI:

Roger, E. M. (1995). Diffusion of innovation. (4th ed.). New York, NY: The Freeman Press.

Rook, D. W. (1987). The buying impulse. Journal of Consumer Research, 14(2), 189-199. DOI:

Rook, D. W., y Fisher, R. J. (1995). Normative influences on impulsive buying behavior. Journal of Consumer Research, 22(3), 305-313. DOI:

Rose, P. (2007). Mediators of the association between narcissism and compulsive buying: The roles of materialism and impulse control. Psychology of Addictive Behaviors, 21(4), 576-581. DOI:

Sarrazin, P., Roberts, G., Cury, F., Biddle, S., y Famose, J. P. (2002). Exerted effort and performance in climbing among boys: The influence of achievement goals, perceived ability, and task difficulty. Research Quarterly for Exercise and Sport, 73(4), 425-436. DOI:

Seegers, G., van Putten, C. M., y De Brabander, C. J. (2002). Goal orientation, perceived task outcome and task demands in mathematics tasks: Effects on students' attitude in actual task settings. British Journal of Educational Psychology, 72(3), 365-384. DOI:

Šeinauskienė, B., Maščinskienė, J., Petrike, I., y Rutelionė, A. (2016). Materialism as the mediator of the association between subjective well-being and impulsive buying tendency. Inžinerinė Ekonomika, 27(5), 594-606. DOI:

Shahjehan, A., Zeb, F., y Saifullah, K. (2012). The effect of personality on impulsive and compulsive buying behaviors. African Journal of Business Management, 6(6), 2187-2194. Recuperado de:

Silvera, D. H., Lavack, A. M., y Kropp, F. (2008). Impulse buying: The role of affect, social influence, and subjective wellbeing. Journal of Consumer Marketing, 25(1), 23-33. DOI:

Soutter, A. R. B., Bates, T. C., y Mõttus, R. (2020). Big five and HEXACO personality traits, proenvironmental attitudes, and behaviors: A meta-analysis. Perspectives on Psychological Science, 15(4), 913-941. DOI:

Spence, J. T., y Helmreich, R. L. (1983). Achievement-related motives and behaviors. En J. T. Spence (Ed.), Achievement and achievement motives: Psychological and sociological approaches (pp. 10-74). San Francisco, CA: Freeman.

Statista (2020). Porcentaje de usuarios que realizaron compras a través de dispositivos móviles en España entre 2014 y 2018. Recuperado de:

Stefańska, M., y Śmigielska, G. (2020). Impulse purchase in virtual environment and price sensitivity of young consumers: Results of empirical research. Economy & Market Communication Review/Casopis za Ekonomiju i Trzisne Komunikacije, 10(1).

Steiger, J. H., y Lind, J. C. (1980). Statistically-based tests for the number of common factors. En The Meeting of the Psychometric Society. Iowa City, IA.

Straub, D., Limayem, M., y Karahanna-Evaristo, E. (1995). Measuring system usage: Implications for IS theory testing. Management Science, 41(8), 1328-1342. DOI:

Sun, G., Wang, W., Cheng, Z., Li, J., y Chen, J. (2017). The intermediate linkage between materialism and luxury consumption: Evidence from the emerging market of China. Social Indicators Research, 132, 475-487. DOI:

Sun, T., y Wu, G. (2011). Trait predictors of online impulsive buying tendency: A hierarchical approach. Journal of Marketing Theory and Practice, 19(3), 337-346. DOI:

Tenenbaum, G., Hall, H. K., Calcagnini, N., Lange, R., Freeman, G., y Lloyd, M. (2001). Coping with physical exertion and negative feedback under competitive and self-standard conditions. Journal of Applied Social Psychology, 31(8), 1582-1626. DOI:

Thompson, R. L., Higgins, C. A., y Howell, J. M. (1991). Personal computing: Toward a conceptual model of utilization. MIS Quarterly, 15(1), 125-143. DOI:

Turkyilmaz, C. A., Erdem, S., y Uslu, A. (2015). The effects of personality traits and website quality on online impulse buying. Procedia-Social and Behavioral Sciences, 175, 98-105. DOI:

Vahdat, A., Alizadeh, A., Quach, S., y Hamelin, N. (2020). Would you like to shop via mobile app technology? The technology acceptance model, social factors and purchase intention. Australasian Marketing Journal (AMJ). DOI:

Venkatesh, V., y Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273-315. DOI:

Venkatesh, V., Thong, J. Y., y Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157-178. DOI:

Verplanken, B., y Herabadi, A. (2001). Individual differences in impulse buying tendency: Feeling and no thinking. European Journal of Personality, 15(S1), S71-S83. DOI:

Verplanken, B., Herabadi, A. G., Perry, J. A., y Silvera, D. H. (2005). Consumer style and health: The role of impulsive buying in unhealthy eating. Psychology & Health, 20(4), 429-441. DOI:

Wells, J. D., Parboteeah, V., y Valacich, J. S. (2011). Online impulse buying: Understanding the interplay between consumer impulsiveness and website quality. Journal of the Association for Information Systems, 12(1), 32-56. DOI:

Wills, T. A., Sandy, J. M., y Yaeger, A. (2000). Temperament and adolescent substance use: An epigenetic approach to risk and protection. Journal of Personality, 68(6), 1127-1151. DOI:

Wixom, B. H., y Todd, P. A. (2005). A theoretical integration of user satisfaction and technology acceptance. Information Systems Research, 16(1), 85-102. DOI:

Wong, Y.-T., Osman, S., Jamaluddin, A., y Yin-Fah, B. C. (2012). Shopping motives, store attributes and shopping enjoyment among Malaysian youth. Journal of Retailing and Consumer Services, 19(2), 240-248. DOI:

Wu, J.-H., y Wang, S.-C. (2005). What drives mobile commerce?: An empirical evaluation of the revised technology acceptance model. Information & Management, 42(5), 719-729. DOI:

Wu, W., Wang, H., Lee, H.-Y., Lin, Y.-T., y Guo, F. (2019). How machiavellianism, psychopathy, and narcissism affect sustainable entrepreneurial orientation: The moderating effect of psychological resilience. Frontiers in psychology, 10, 779. DOI:

Xiao, S. H., y Nicholson, M. (2013). A multidisciplinary cognitive behavioural framework of impulse buying: A systematic review of the literature. International Journal of Management Reviews, 15(3), 333-356. DOI:

Yang, K., y Forney, J. C. (2013). The moderating role of consumer technology anxiety in mobile shopping adoption: Differential effects of facilitating conditions and social influences. Journal of Electronic Commerce Research, 14(4), 334-347. Recuperado de:

Yazdanparas, A., y Alhenawi, Y. (2017). Personality and borrowing behavior: An examination of the role of need for material resources and need for arousal traits on household's borrowing decisions. Financial Services Review, 26(1), 55-85.

Zhang, L., Zhu, J., y Liu, Q. (2012). A meta-analysis of mobile commerce adoption and the moderating effect of culture. Computers in Human Behavior, 28(5), 1902-1911. DOI:

Zhang, X., Prybutok, V. R., y Strutton, D. (2007). Modeling influences on impulse purchasing behaviors during online marketing transactions. Journal of Marketing Theory and Practice, 15(1), 79-89. DOI:

Zheng, X., Men, J., Yang, F., y Gong, X. (2019). Understanding impulse buying in mobile commerce: An investigation into hedonic and utilitarian browsing. International Journal of Information Management, 48, 151-160. DOI:

Zhou, T., y Lu, Y. (2011). The effects of personality traits on user acceptance of mobile commerce. International Journal of Human–Computer Interaction, 27(6), 545-561. DOI:

Ziano, I., y Villanova, D. (2019). You’d use it more than me: Overestimating products’ usefulness to others because of self-serving materialism attributions. PsyArXiv. DOI: