Technology Acceptance Model and Technology Readiness Research Paper

Introduction

There are many models of how people choose whether to use a new system or product or not. Some models have predictive validity, allowing to partially predicting the use of a new product or feature using questionnaires. One of the most famous is the technology acceptance model and technology readiness. Their integration helps to understand better users’ intentions and the system of tracking technologies in the tourism environment, taking into account individual differences.

Technology Acceptance Model

The technology acceptance model (TAM) operates on two basic concepts: subjective utility and subjective ease of use. Perceived usefulness is a value that reflects the degree of confidence of the user that the technology used will increase their productivity (Yoo et al., 2017). A high index of the first concept indicates that the technology goals correspond to the user’s goals and vice versa (Tubaishat, 2018). Nugroho Bakar and Ali (2017, p. 29) define perceived ease of use as “a degree to which a person believes that using the system would be free of effort”. Based on TAM, a questionnaire can be developed (Rachman and Napitupulu, 2018). It will allow measuring the subjective simplicity and usefulness of a product and partially predicting how much it will be used.

Technology Readiness

The second important aspect that needs to be considered is technology readiness (TR). Blut and Wang (2020, p. 1) describe that this construct “aims to better understand people’s propensity to embrace and use cutting-edge technologies”. The technology can be considered a general state of mind, which results from formed mental stimuli that determine a person’s predisposition to use any new technologies. Technology readiness has four main dimensions: optimism, innovation, discomfort, and insecurity (Sunny, Patrick and Rob, 2019). Thus, the technology of readiness determines the level of readiness of customers to use a particular technology in their lives.

Integration Theory of Technology Readiness and Acceptance Model

The combined use of TAM and TR can help better explain consumer intentions and predict people’s behavior adopting technology. These technologies can be used incredibly effectively in the radio frequency identification system (RFID), a technology tracking system, in the context of tourism, taking into account individual differences. Honarzade, Mahmoudinia and Anari (2017, p. 2) define RFID as “one of the automatic detection technologies that use radio waves to identify objects and collect information without human intervention”. Tourism plays an important role not only in the personal life of every person but also in the economy of any country.

The use of new technologies would help develop the tourism area even more and make it easier to use. Alghamdi (2019) in work suggests that the use of RFID technologies can help the blind in the field of shopping and tourism. All the needed actions and steps people can do independently using only their smartphone. The use of technologies contributes to the calculation of the readiness of individuals to implement such technologies, the effectiveness, and the need to use them in everyday life.

In one study, Balouchi et al. (2017) investigated the factors influencing the behavioral intent of Iranian tourists in using specialized websites. As a basis, TRAM was used when considering how visitors planned their trip. Using the technology, the authors concluded that perceived trustworthiness is the most vital factor reflecting behavioral intentions. In addition, the most significant relationship is between perceived usefulness and perceived ease of use (Indarsin and Ali, 2017). Thus, the tourism industry has to quickly adapt to the new reality and the use of new technologies will only accelerate this process.

Conclusion

The TAM and TR models are used directly for technologies, but their principles are applicable in many other areas. To simplify it, the technology acceptance model says that people want to use the technology if they perceive it as valuable and easy to use. At the same time, TR shows the degree of readiness and openness of people to new inventions. Their integration contributes to more effective and informative results.

Reference List

Alghamdi, S. (2019). ‘Shopping and tourism for blind people using RFID as an application of IoT’, 2019 2nd International Conference on Computer Applications & Information Security (ICCAIS), pp. 1-4.

Balouchi, M., Aziz, Y. A., Hasangholipour, T., Khanlari, A., Abd Rahman, A., & Raja-Yusof, R. N. (2017). ‘Explaining and predicting online tourists’ behavioural intention in accepting consumer generated contents’, Journal of Hospitality and Tourism Technology, 8(2), pp. 168-189.

Blut, M., & Wang, C. (2020). ‘Technology readiness: a meta-analysis of conceptualizations of the construct and its on technology usage’, Journal of the Academy of Marketing Science, 48(4), pp. 649-669.

Honarzade, M., Mahmoudinia, M., & Anari, M. S. (2018). ‘Identifying and Ranking Influencing Factors in Using RFID Technology in Tourism Industry via the Use of Structural Equation Modeling’, International Journal of Information Systems in the Service Sector, 10(4), pp. 1-20.

Indarsin, T., & Ali, H. (2017). ‘Attitude toward Using m-commerce: The analysis of perceived usefulness perceived ease of use, and perceived trust: Case study in Ikens Wholesale Trade, Jakarta–Indonesia’, Saudi Journal of Business and Management Studies, 2(11), pp. 995-1007.

Nugroho, A. H., Bakar, A., & Ali, A. (2017). ‘Analysis of technology acceptance model: Case study of Traveloka’, Arthatama, 1(1), pp. 27-34.

Rachman, T., & Napitupulu, D. (2018). ‘User acceptance analysis of potato expert system application based on TAM approach’, Int. J. Adv. Sci. Eng. Inf. Technol, 8(1), pp. 185-191.

Sunny, S., Patrick, L., & Rob, L. (2019). ‘Impact of cultural values on technology acceptance and technology readiness’, International Journal of Hospitality Management, 77, pp. 89-96.

Tubaishat, A. (2018). ‘Perceived usefulness and perceived ease of use of electronic health records among nurses: application of technology acceptance model’, Informatics for Health and Social Care, 43(4), pp. 379-389.

Yoo, C., Kwon, S., Na, H., & Chang, B. (2017). ‘Factors affecting the adoption of gamified smart tourism applications: An integrative approach’, Sustainability, 9(12).