A Proposal: Human Factors Related to the User Acceptance Behavior in Adapting to New Technologies or New User Experience

Author

Hima Bindu Sadashiv Reddy , Roopesh Reddy Sadashiva Reddy,Ratnaditya Jonnalagadda


Abstract

We are aware of the tremendous growth of new mobile phones released in the market every year. The increase in the users’ needs with respect to the new devices is not to be ignored as well. Each product has so many brands with n-number of models and versions.The way the users choose to buy these products is perplexing. For example,decision made to buy a new mobile or change to new brand or even continuing the same brand is not an easy task. The user acceptance for any new behavior is very complex. This paper explores all the possible human factors connected to either pleasant or unpleasant user experiences. Various researchstudies discovered that loyalty of the users for a particular brand plays an important role for the success of the product. Long-term usage of the product by a user would have a negative impact, as the user is not willing to switch to other brands and this has a positive impact on the companies. User memory, expectations and experiences are closely knit to understand the user acceptance for choosing a product. A positive emotion such as pleasant user experience is significant because users recommend the products to others based on these emotional experiences. Age plays an important role with respect to user experience. Old age users were not enthusiastic in going for a change as they preferred to continue with the same technology. Cultural aspects of users are interesting to know in understanding the product purchases. There was biased information regarding user’s visual attractiveness and long-term usage memory. Certain studies explored UX curve and user burden scale that was used to analyze user experiences. It was interesting to know sensory characteristics formed a base for both pleasant and unpleasant user experiences. This research will help companies of mobile devices in identifying the various factors (both positive and negative) related to user experiences and behavior. Future research will be conducted in the areas of short-term user experience and in areas where illiteracy prevail. This study will help the companies to improve their product better based on customer satisfaction


Keywords

Human Computer Interaction, User Experience, User Withdrawal, Long-Term User Experience, Short-term User Experience


DOI : https://doi.org/10.55248/gengpi.2022.3.8.1


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References


Suh, H., Shahriaree, N., Hekler, E. B., & Kientz, J. A. (2016, May). Developing and validating the user burden scale: A tool for assessing user burden in computing systems. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (pp. 3988-3999). ACM.

 

Kujala, S., & Miron-Shatz, T. (2015, September). The evolving role of expectations in long-term user experience. In Proceedings of the 19th International Academic Mindtrek Conference (pp. 167-174). ACM.

 

Kujala, S., & Miron-Shatz, T. (2013, April). Emotions, experiences and usability in real-life mobile phone use. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 1061-1070). ACM.

 

Park, J., Han, S. H., Kim, H. K., Oh, S., & Moon, H. (2013). Modeling user experience: A case study on a mobile device. International Journal of Industrial Ergonomics, 43(2), 187-196.

 

Karapanos, E. (2013). User experience over time. In Modeling Users' Experiences with Interactive Systems (pp. 57-83). Springer Berlin Heidelberg.

Tuch, A. N., Trusell, R., & Hornbæk, K. (2013, April). Analyzing users' narratives to understand experience with interactive products. In Proceedings of the SIGCHI Conference on human factors in computing systems (pp. 2079-2088). ACM.

 

Nicolas, O., Carlos, J., & Aurisicchio, M. (2011). The scenario of user experience. In DS 68-7: Proceedings of the 18th International Conference on Engineering Design (ICED 11), Impacting Society through Engineering Design, Vol. 7: Human Behaviour in Design, Lyngby/Copenhagen, Denmark, 15.-19.08.

 

Kujala, S., Roto, V., Väänänen-Vainio-Mattila, K., Karapanos, E., & Sinnelä, A. (2011). UX Curve: A method for evaluating long-term user experience. Interacting with Computers, 23(5), 473-483.

 

Kujala, S., Roto, V., Väänänen-Vainio-Mattila, K., & Sinnelä, A. (2011, June). Identifying hedonic factors in long-term user experience. In Proceedings of the 2011 Conference on Designing Pleasurable Products and Interfaces (p. 17). ACM.

 

Novick, D. G., Santaella, B., Cervantes, A., & Andrade, C. (2012, October). Short-term methodology for long-term usability. In Proceedings of the 30th ACM international conference on Design of communication (pp. 205-212). ACM.

 

Fenko, A., Schifferstein, H. N., & Hekkert, P. (2010). Shifts in sensory dominance between various stages of user–product interactions. Applied ergonomics, 41(1), 34-40.

 

Fenko, A., Schifferstein, H. N., & Hekkert, P. (2009). Which senses dominate at different stages of product experience?

 

Karapanos, E., Zimmerman, J., Forlizzi, J., & Martens, J. B. (2010). Measuring the dynamics of remembered experience over time. Interacting with Computers, 22(5), 328-335.

 

Roto, V., Rantavuo, H., & Väänänen-Vainio-Mattila, K. (2009, October). Evaluating user experience of early product concepts. In Proc. DPPI (Vol. 9, pp. 199-208).

 

Kacen, J. J., & Lee, J. A. (2002). The influence of culture on consumer impulsive buying behavior. Journal of consumer psychology, 12(2), 163-176.

 

Sayago, S., Sloan, D., & Blat, J. (2011). Everyday use of computer-mediated communication tools and its evolution over time: An ethnographical study with older people. Interacting with Computers, 23(5), 543–554.

 

Rodriguez, K. M., Reddy, R. S., Barreiros, A. Q., & Zehtab, M. (2012, June). Optimizing Program Operations: Creating a Web-Based Application to Assign and Monitor Patient Outcomes, Educator Productivity and Service Reimbursement. In DIABETES (Vol. 61, pp. A631-A631). 1701 N BEAUREGARD ST, ALEXANDRIA, VA 22311-1717 USA: AMER DIABETES ASSOC.

 

 Kwon, D., Reddy, R., & Reis, I. M. (2021). ABCMETAapp: R shiny application for simulation-based estimation of mean and standard deviation for meta-analysis via approximate Bayesian computation. Research synthesis methods, 12(6), 842–848. https://doi.org/10.1002/jrsm.1505

 

 Reddy, H. B. S., Reddy, R. R. S., Jonnalagadda, R., Singh, P., & Gogineni, A. (2022). Usability Evaluation of an Unpopular Restaurant Recommender Web Application Zomato. Asian Journal of Research in Computer Science, 13(4), 12-33.

 

 Reddy, H. B. S., Reddy, R. R. S., Jonnalagadda, R., Singh, P., & Gogineni, A. (2022b). Analysis of the Unexplored Security Issues Common to All Types of NoSQL Databases. Asian Journal of Research in Computer Science, 14(1), 1-12.

 

  Singh, P., Williams, K., Jonnalagadda, R., Gogineni, A., &; Reddy, R. R. (2022). International students: What’s missing and what matters. Open Journal of Social Sciences, 10(02),

 

 Jonnalagadda, R., Singh, P., Gogineni, A., Reddy, R. R., & Reddy, H. B. (2022). Developing, implementing and evaluating training for online graduate teaching assistants based on Addie Model. Asian Journal of Education and Social Studies, 1-10.

 

 Sarmiento, J. M., Gogineni, A., Bernstein, J. N., Lee, C., Lineen, E. B., Pust, G. D., & Byers, P. M. (2020).Alcohol/illicit substance use in fatal motorcycle crashes. Journal of surgical research, 256, 243-250.

 

 Brown, M. E., Rizzuto, T., & Singh, P. (2019). Strategic compatibility, collaboration and collective impact for community change. Leadership & Organization Development Journal.

 

 Sprague-Jones, J., Singh, P., Rousseau, M., Counts, J., & Firman, C. (2020). The Protective Factors Survey: Establishing validity and reliability of a self-report measure of protective factors against child maltreatment. Children and Youth Services Review, 111, 104868

 

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