ANALYSIS OF THE TASK-TECHNOLOGY FIT MODEL APPLIED TO WHATSAPP AS A PREFERENCE OF YOUNG USERS OF MOBILE INSTANT MESSENGERS

Autores

  • Luis Hernan Contreras Pinochet Universidade Federal de São Paulo (UNIFESP)
  • Jéssica Priscilla dos Santos Badaró Universidade Federal de São Paulo (UNIFESP)
  • Evandro Luiz Lopes Universidade Federal de São Paulo (UNIFESP) e Universidade Nove de Julho (UNINOVE)
  • Eliane Herrero Universidade Nove de Julho (UNINOVE)
  • Durval Lucas dos Santos Júnior Universidade Federal de São Paulo (UNIFESP)

DOI:

https://doi.org/10.19177/reen.v14e22021217-245

Palavras-chave:

Mobile Instant Messengers, Task-Technology Fit Model, WhatsApp, Young Users.

Resumo

The purpose of this article is to analyze the technology-task adjustment model applied to WhatsApp as a preferred communication method by young Mobile Instant Messengers (MIM) users. Thus, we conducted a survey (n=567) and a multivariate data analysis through Structural Equation Modeling. Only one hypothesis of the model was rejected showing that hedonic needs do not influence needs perceived by users. Users do not realize pleasure as a need when it comes to MIMs with communication-oriented features and is not exclusively for fun. We also found that the behavioral profile of young users to perceive the importance of motivational needs, technological characteristics, perceived needs, satisfaction, and privacy, to generate the intention to continue using the mobile communication tool. 

Biografia do Autor

  • Luis Hernan Contreras Pinochet, Universidade Federal de São Paulo (UNIFESP)
    Professor do Departamento Acadêmico de Administração (DAA) da Universidade Federal de São Paulo (UNIFESP)
  • Jéssica Priscilla dos Santos Badaró, Universidade Federal de São Paulo (UNIFESP)
    Graduanda em Administração pela Universidade Federal de São Paulo (UNIFESP)
  • Evandro Luiz Lopes, Universidade Federal de São Paulo (UNIFESP) e Universidade Nove de Julho (UNINOVE)
    Professor do Departamento Acadêmico de Administração (DAA) da Universidade Federal de São Paulo (UNIFESP) e do Programa de Pós-graduação em Administração (PPGA) da Universidade Nove de Julho (UNINOVE)
  • Eliane Herrero, Universidade Nove de Julho (UNINOVE)
    Doutoranda no Programa de Pós-graduação em Administração (PPGA) da Universidade Nove de Julho (UNINOVE)
  • Durval Lucas dos Santos Júnior, Universidade Federal de São Paulo (UNIFESP)
    Professor do Departamento Acadêmico de Administração (DAA) da Universidade Federal de São Paulo (UNIFESP)

Referências

BAGOZZI, R. P.; YI, Y.; PHILLIPS, L. W. Assessing Construct Validity in Organizational Research. Administrative Science Quarterly, v. 36, n. 3, p. 421–458, 1991.

CHIN, W. W. The partial least squares approach for structural equation modeling. In: Modern methods for business research. Methodology for business and management. Mahwah, NJ, US: Lawrence Erlbaum Associates Publishers, 1998. p. 295–336.

CHO, M.; KIM, J. Development of Wire-Wireless Integrated Web Messenger for Communication of users in a Multi-Organization. Journal of the Korea Institute of Information and Communication Engineering, v. 17, n. 5, p. 1181–1186, 2013.

CHURCH, K.; OLIVEIRA, R. DE. What’s up with whatsapp? comparing mobile instant messaging behaviors with traditional SMS. Proceedings of the 15th international conference on Human-computer interaction with mobile devices and services. Anais...: MobileHCI ’13.New York, NY, USA: Association for Computing Machinery, 27 ago. 2013Disponível em: <https://doi.org/10.1145/2493190.2493225>. Acesso em: 9 nov. 2020

COWLEY, E.; MITCHELL, A. A. The Moderating Effect of Product Knowledge on the Learning and Organization of Product Information. Journal of Consumer Research, v. 30, n. 3, p. 443–454, 2003.

FLAVIÁN, C.; GUINALÍU, M.; GURREA, R. The role played by perceived usability, satisfaction and consumer trust on website loyalty. Information and Management, v. 43, n. 1, p. 1–14, 2006.

FORNELL, C.; LARCKER, D. F. Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, v. 18, n. 1, p. 39–50, 1981.

GILL, T. Convergent Products: What Functionalities Add More Value to the Base?: Journal of Marketing, 1 mar. 2008.

GOODHUE, D. L.; THOMPSON, R. L. Task-Technology Fit and Individual Performance. MIS Quarterly, v. 19, n. 2, p. 213–236, 1995.

HAIR, J. F. et al. A primer on partial least squares structural equation modeling (PLS-SEM). Los Angeles: SAGE, 2017.

HIRSCHMAN, E. C.; HOLBROOK, M. B. Hedonic Consumption: Emerging Concepts, Methods and Propositions. Journal of Marketing, v. 46, n. 3, p. 92–101, 1982.

HOCH, S. J.; DEIGHTON, J. Managing What Consumers Learn from Experience: Journal of Marketing, 2 nov. 2018.

HOEFFLER, S. Measuring Preferences for Really New Products. Journal of Marketing Research, v. 40, n. 4, p. 406–420, 2003.

IP, R. K. F.; WAGNER, C. Weblogging: A study of social computing and its impact on organizations. Decision Support Systems, v. 45, n. 2, p. 242–250, maio 2008.

KAMBIL, A.; NUNES, P.; WILSON, D. The All-in-One Market. Harvard Business Review, 2000.

KATONA, Z.; ZUBCSEK, P. P.; SARVARY, M. Network Effects and Personal Influences: The Diffusion of an Online Social Network. Journal of Marketing Research, v. 48, n. 3, p. 425–443, 2011.

KATZ, E.; BLUMLER, J. G.; GUREVITCH, M. Utilization of mass communication by the individual. The uses of mass communications : current perspectives on gratifications research, The uses of mass communications : current perspectives on gratifications research. - Beverly Hills, Calif. [u.a.] : Sage Publ., ISBN 0-8039-0340-5. - 1974, p. 19-32. p. 19–32, 1974.

KIM, D. J.; HWANG, Y. A study of mobile internet user’s service quality perceptions from a user’s utilitarian and hedonic value tendency perspectives. Information Systems Frontiers, v. 14, n. 2, p. 409–421, 1 abr. 2012.

KLEIJNEN, M. H. P.; RUYTER, K. DE; WETZELS, M. G. M. An assessment of value creation in mobile service delivery and the moderating role of time consciousness. Journal of Retailing, v. 83, n. 1, p. 33–46, 2007.

KO, H.; CHO, C.-H.; ROBERTS, M. S. INTERNET USES AND GRATIFICATIONS: A Structural Equation Model of Interactive Advertising. Journal of Advertising, v. 34, n. 2, p. 57–70, 1 jun. 2005.

KOZINETS, R. V. et al. Networked Narratives: Understanding Word-of-Mouth Marketing in Online Communities. Journal of Marketing, v. 74, n. 2, p. 71–89, 1 mar. 2010.

LIAO, C.; HUANG, Y.-J.; HSIEH, T.-H. Factors influencing Internet banking adoption. Social Behavior and Personality, v. 44, n. 9, p. 1443–1456, 18 nov. 2015.

LIM, E. A. C.; ANG, S. H. Hedonic vs. utilitarian consumption: A cross-cultural perspective based on cultural conditioning. Journal of Business Research, Cross-Cultural Business Research. v. 61, n. 3, p. 225–232, 1 mar. 2008.

LIN, K.-Y. User communication behavior in mobile communication software. Online Information Review, v. 40, n. 7, p. 1071–1089, 1 jan. 2016.

LIN, K.-Y.; LU, H.-P. Predicting mobile social network acceptance based on mobile value and social influence. Internet Research, v. 25, n. 1, p. 107–130, 1 jan. 2015.

LIN, W.-S. Perceived fit and satisfaction on web learning performance: IS continuance intention and task-technology fit perspectives. International Journal of Human-Computer Studies, Special Issue on User Experience (UX) in Virtual Learning Environments. v. 70, n. 7, p. 498–507, 2012.

LU, H.-P.; YANG, Y.-W. Toward an understanding of the behavioral intention to use a social networking site: An extension of task-technology fit to social-technology fit. Computers in Human Behavior, v. 34, p. 323–332, 1 maio 2014.

MALHOTRA, N. K. Essentials of Marketing Research: A Hands-On Orientation. Disponível em: . Acesso em: 26 jul. 2020.

MALHOTRA, N. K.; KIM, S. S.; AGARWAL, J. Internet Users’ Information Privacy Concerns (IUIPC): The Construct, the Scale, and a Causal Model. Information Systems Research, v. 15, n. 4, p. 336–355, 2004.

MEUTER, M. L. et al. Choosing among Alternative Service Delivery Modes: An Investigation of Customer Trial of Self-Service Technologies. Journal of Marketing, v. 69, n. 2, p. 61–83, 1 abr. 2005.

MUKHERJEE, A.; HOYER, W. D. The Effect of Novel Attributes on Product Evaluation. Journal of Consumer Research, v. 28, n. 3, p. 462–472, 1 dez. 2001.

NAM, S.-T.; KIM, D.-G.; JIN, C.-Y. A study on the continuous intention to use for Smartphone based on the innovation diffusion theory: Considered on the loyalty between users of iOS and Android platform. Journal of the Korea Institute of Information and Communication Engineering, v. 17, n. 5, p. 1219–1226, 2013.

O’BRIEN, H. L. The influence of hedonic and utilitarian motivations on user engagement: The case of online shopping experiences. Interacting with Computers, v. 22, n. 5, p. 344–352, 1 set. 2010.

OGHUMA, A. P. et al. An expectation-confirmation model of continuance intention to use mobile instant messaging. Telematics and Informatics, v. 33, n. 1, p. 34–47, 1 fev. 2016.

OKADA, E. M. Justification Effects on Consumer Choice of Hedonic and Utilitarian Goods. Journal of Marketing Research, v. 42, n. 1, p. 43–53, 2005.

PETERSON, R. A. A Meta-analysis of Cronbach’s Coefficient Alpha. Journal of Consumer Research, v. 21, n. 2, p. 381–391, 1 set. 1994.

PIMENTEL, R. W.; REYNOLDS, K. E. A model for consumer devotion: affective commitment with proactive sustaining behaviors. Academy of Marketing Science Review, n. 5, p. 48, 2004.

RAACKE, J.; BONDS-RAACKE, J. MySpace and Facebook: applying the uses and gratifications theory to exploring friend-networking sites. Cyberpsychology & Behavior: The Impact of the Internet, Multimedia and Virtual Reality on Behavior and Society, v. 11, n. 2, p. 169–174, abr. 2008.

STAFFORD, T. F.; STAFFORD, M. R.; SCHKADE, L. L. Determining Uses and Gratifications for the Internet. Decision Sciences, v. 35, n. 2, p. 259–288, 2004.

VAN DER HEIJDEN, H. User acceptance of hedonic information systems. MIS QUARTERLY, v. 28, n. 4, p. 695–704, 1 dez. 2004.

WEI, H.-L. et al. Understanding the intentions of users to ‘stick’ to social networking sites: a case study in Taiwan. Behaviour & Information Technology, v. 34, n. 2, p. 151–162, 1 fev. 2015.

WEISS, S. Privacy threat model for data portability in social network applications. International Journal of Information Management, v. 29, n. 4, p. 249–254, 1 ago. 2009.

WESTBROOK, R. A. Product/Consumption-Based Affective Responses and Postpurchase Processes. Journal of Marketing Research, v. 24, n. 3, p. 258–270, 1987.

WETZELS; ODEKERKEN-SCHRÖDER; VAN OPPEN. Using PLS Path Modeling for Assessing Hierarchical Construct Models: Guidelines and Empirical Illustration. MIS Quarterly, v. 33, n. 1, p. 177, 2009.

WOONGSUP, L.; HOWON, L. Performance Evaluation of Coordinated Multi-Point Transmission and Reception in Indoor Mobile Communication Systems. Journal of information and communication convergence engineering, v. 11, n. 3, p. 167–172, 2013.

WU, J.-J.; TSANG, A. S. L. Factors affecting members’ trust belief and behaviour intention in virtual communities. Behaviour & Information Technology, v. 27, n. 2, p. 115–125, 1 mar. 2008.

YANG, H. ‘CHRIS’. Bon Appétit for Apps: Young American Consumers’ Acceptance of Mobile Applications. Journal of Computer Information Systems, v. 53, n. 3, p. 85–96, 1 mar. 2013.

YEN, D. C. et al. Determinants of users’ intention to adopt wireless technology: An empirical study by integrating TTF with TAM. Computers in Human Behavior, Advancing Educational Research on Computer-supported Collaborative Learning (CSCL) through the use of gStudy CSCL Tools. v. 26, n. 5, p. 906–915, 1 set. 2010.

YU, J. et al. User acceptance of location-based social networking services: An extended perspective of perceived value. Online Information Review, v. 37, n. 5, p. 711–730, 1 jan. 2013.

ZHOU, Z. Y.; JIN, X.; FANG, Y. Moderating role of gender in the relationships between perceived benefits and satisfaction in social virtual world continuance. Decision Support Systems, v. 65, p. 69–79, set. 2014.

Publicado

2021-11-08

Edição

Seção

Artigos Científicos