HYPOTHESIS CHAPTER

Hypothesis Chapter: Smart Mask

Theory of Reasoned Action (TRA)

The theory of reasoned action is one of the key theories for understanding consumer behavior, intention, and planned purchase for a specific product or service. The theory, formulated by Fishbein and Ajzen, attempts to predict the behavioral intention of the buyer based on two factors: the attitudes that would lead to adopting the buying behavior and the subjective norms that come from the buyers social influence (Hosseini et al., 2015; Myresten & Setterhall, 2015, p. 5). The factors that shape the buyers social influences mainly include the beliefs held by his surrounding people, which impact his decision-making process. There is an element of trust over the other persons beliefs that would affect the buyers action, which is highly dependent on the past behavior or experience (Chuchinprakarn, 2005).

The resulting behavior is shaped by the attitudes modified by the held beliefs, which are subjective norms in reality. The motivation of an individual to fulfill other peoples expectations, particularly when his beliefs influence his mind, then the action is altered accordingly (Hosseini et al., 2015). The subjective norms or beliefs would be positive when the person is motivated by other peoples positive expectations and would soon be witnessed in his affirmative actions (Hosseini et al., 2015). On the contrary, the negatively held subjective norms or beliefs would result in negative ideas when he would perceive peoples expectations as negative, taking the form of de-motivation.

With the theoretical foundation of the theory of reasoned action, it is interpreted that the consumer would evaluate the information from his peers about the same product or service that he intends to buy so that the positive or negative attitudes of those peers could help him translate into his own decision of making the final purchase (Haris et al., 2017). The intention of his buying is highly dependent on the previously held beliefs of his peers and social network that would shape his rejection or acceptance of the product. It is a deduction; it could be the potential buyers way of perceiving the obtained information from his peers with subjectivity that would support him in evaluating the product (Haris et al., 2017). The evaluation process would assist in making his mind about a yes or no for the product, leading to his final purchase action.

The Influence of Consumers Evaluation on Attitude

The consumers expectations regarding a certain product and meeting those expectations are the goals that modern marketers are looking to achieve prudently for devising a fool-proof plan for a products success. The product quality evaluation results are the consumer valuations of the product in terms of design, optimization, quality, and fulfillment of the service it is meant for (Xu et al., 2018).

Companies become successful only if they can come out with products that can rightly target the consumers needs and connect with them. Connecting means that they should be more personalized with their changing needs, as in the time of technology today. The hyper-connectivity that technology has provided in contemporary times has allowed the companies to produce a dynamic digital ecosystem with which a completely streamlined consumer attitude could be supported (Amer et al., 2014). The businesses are now in a better position to facilitate the consumer with improved features of the products they use and that too, with an enhanced version of their design, features, and performance. This mainstream phenomenon helps businesses capture the consumers needs and improve their lives with high levels of performance expectancy by the user or customer evaluation (Amer et al., 2014). Technology allows the firm to stay connected with their changing or upgrading needs each day so that a cohesive customer experience could be suggested with the smart features the products possess (Riegger et al., 2022). It could be inferred that the more consumer engagement, the more personalized the product would be and the higher the customer evaluation results.

The value-added features that personalization offers through smart technology have been included in certain products, such as smart home devices (Raff et al., 2020). They tend to provide modern homes with the convenience of home automation. The particular needs of one household are fulfilled by the specially designed features of one device so that task performing is done intelligently (Georgiev & Schlogl, 2018). The integration and evolvement of services occur through the connectivity specialization called the Internet of Things (IoT) (Kumar et al., 2019). This is why consumers have evaluated these products for better life ease and increased security of the people living inside the house. The positive consumer attitude that is delivered through product evaluations proves that consumers want to make their lives better with the integration of smart technology and features within products, and even making them an ambitious part of their lives (Korneeva et al., 2021).

The same is the case with the smartwatch that takes data from the consumer, uses the consumer information, and presents it in a personalized manner, such as managing calls and messages, handling calendar tasks, giving reminders of physical activities like exercise or walking or even drinking water notifications, etc. (Siepmann & Kowalczuk, 2021). The sensory digitization of the watch lets the human body monitor three major psychological needs based on self-determination theory (SDT): autonomy, competence, and relatedness (Siepmann & Kowalczuk, 2021). The wearable devices like smartwatches have the functionalities of providing a healthy lifestyle, expected to reduce healthcare expenses.

A smart mask is a new concept that would help digitize consumer health and protection against infections before time. The respiratory sensations with real-time data integration would be useful for conducting immediate safety measures for those who wear them (Hyysalo et al., 2022). The health data is collected from the user, and his health and history are created. Sensory reception, artificial intelligence (A.I.), wireless technology, software, and the Internet of Things (IoT) are some of the technological features that the smart mask would use for real-time data enhancement for the device (Hyysalo et al., 2022). This is the value-added benefits with extra personalization by using the customer health data, which is the backbone of its design.

The technology that is embedded within smart masks is unique. It has a suggested system that dynamically detects the occurrence of nearby airborne particles (Kalavakonda et al., 2021). The sensory data identify the particles that contain viruses and are airborne pathogens. The technology enhancement is done for size distribution, pathogen properties, size, and concentration detection. The aerosol spread is mitigated by the inherited technological strategy rooted within the smart mask. The two mechanisms are built for the smart mask: particle sensors and their active mitigation. The quality of air and the risk for a persons health are some of the features that are conducive to personalization, value-addition for better design and effectiveness for the user, favorable for gaining positive consumer evaluation, and greater influence on consumer attitude.

The rechargeable and re-use features are other useful attributes of smart masks that could help in their adoption. These two benefits would help bring low-cost masks into the market as masks would no longer be disposable (El-Atab et al., 2021). They could be...…Zussman, E. & Peirini, F. (2020). Personalized reusable face masks with smart nano-assisted destruction of pathogens for Covid-19: A visionary road. Chemistry- A European Journal, 27(20), 6112-6130. https://doi.org/10.1002/chem.202004875

El-Atab, N., Mishra, R.B. & Hussain, M.M. (2021). Toward nanotechnology-enabled face masks against SARS-CoV-2 and pandemic respiratory diseases. Nanotechnology, 33. https://doi.org/10.1088/1361-6528/ac3578

Georgiev, A. & Schlogl, S. (2018, February). Smart home technology: An exploration of end-user perceptions [Paper presentation]. Smarter Lives, Innsbruck, Austria. https://www.researchgate.net/publication/327136969_Smart_Home_Technology_An_Exploration_of_End_User_Perceptions

Gultom, S., Dalle, J., Restu, Baharuddin, Hairudioar & Gultom, S. (2020). The influence of attitude and subjective norm on citizens intention to use e-government services. Journal of Security and Sustainability Issues, 9(M), 173-187. https://doi.org/10.9770/jssi.2020.9.M(14)

Haris, A., Kefeli, Z., Ahamad, N. & Nurazira, S. (2017). Consumers intention to purchase dates: Application of theory of reasoned action (TRA). Malaysian Journal of Consumer and Family Economics, 20, 1-15.

Henkens, B., Verleye, K., & Larivire, B. (2020). The smarter, the better?! Customer well-being, engagement, and perceptions in smart service systems.International Journal of Research in Marketing, Advance online publication. https://doi.org/10.1016/j.ijresmar.2020.09.006

Hosseini, Z., Gharlipour Gharghani, Z., Mansoori, A., Aghamolaei, T., & Mohammadi Nasrabadi, M. (2015). Application of the theory of reasoned action to promoting breakfast consumption.Medical Journal of the Islamic Republic of Iran,29, 289.

Hussein, Z., Oon, S.W. & Fikry, A. (2017). Consumer attitude: Does it influence the intention to use mHealth? Procedia Computer Science, 105, 340-344. https://doi.org/10.1016/j.procs.2017.01.231

Hussein, Z. (2017). Leading to intention: The role of attitude in relation to technology acceptance model in e-learning. Procedia Computer Science, 105, 159-164. https://doi.org/10.1016/j.procs.2017.01.196

Hyysalo, J., Dasanayake, S., Hannu, J., Schuss, C., Rajanen, M. Leppanen, T., Doermann, D. & Sauvola, J. (2022). Smart mask- wearable IoT solution for improved protection and personal health. Internet of Things, 18. https://doi.org/10.1016/j.iot.2022.100511

Kalavakonda, R.R., Masna, N.V.R., Mandal, S. & Bhunia, S. (2021). A smart mask for active defense against airborne pathogens. Scientific Reports, 11. https://doi.org/10.1038/s41598-021-99150-x

Korneeva, E., Olinder, N. & Strielkowski, W. (2021). Consumer attitudes to the smart home technologies and the Internet of Things (IoT). Energies, 14. https://doi.org/ 10.3390/en1423791

Kumar, S. Tiwari, P. & Zymbler, M. (2019). Internet of Things is a revolutionary approach for future technology enhancement: A review. Journal of Big Data, 6. https://doi.org/10.1186/s40537-019-0268-2

Lorenz, G. & Buhtz, K. (2017, June 5-10). Social influence in technology adoption research: A literature review and research agenda [Paper presentation]. 25th European Conference on Information Systems (ECIS), Guimaraes, Portugal. https://core.ac.uk/download/pdf/301372418.pdf

Massoro, Z.Z. & Adewale, N.T. (2019). Infleunce of attitude, subjective norms and personal innovativeness on intention to use open access journals: A case of agricultural research institutes. Library Philosophy and Practice (e-Journal). https://www.researchgate.net/publication/333104047_Influence_of_Attitude_Subjective_Norms_and_Personal_Innovativeness_on_Intention_to_Use_Open_Access_Journals_a_case_of_Agricultural_Research_Institutes

Moura, I.V., de Almeida, L.B., da Silva, W.V., de Veiga, C.P. & Costa, F. (2020). Predictor factors of intention to use technological resources: A multi-group study about the approach of technologyacceptance model. Sage Open. https://doi.org/10.1177/2158244020967942

Myresten, E. & Setterhall, M. (2015). Theory of reasoned action and the role of external factors in organic food purchase [Masters thesis, Uppsala University]. Diva-Portal.org. https://www.diva-portal.org/smash/get/diva2:824923/FULLTEXT01.pdf

Neuhofer, B., Buhalis, D. & Ladkin, A. (2015). Smart technologies for personalized experiences: A case study in the hospitality domain. Electron Markets, 25, 243-254. https://doi.org/10.1007/s12525-015-0182-1

Otieno, O.C., Liyala, S., Odongo, B.C. & Abeka, S. (2016). Theory of reasoned action as an underpinning to technological innovation adoption studies. World Journal of Computer Application and Technology, 4(1), 1-17. https://doi.org/10.13189/wjcat.2016.040101

Raff, S., Wentzel, D. & Obwegesser, N. (2020). Smart products: Conceptual review, synthesis, and research directions. Journal of Product Innovation Management, 37(5), 379-404. https://doi.org/10.1111/jpim.12544

Riegger A., Merfeld, K., Klein, J.F. & Henkel, S. (2022). Technology-enabled personalization: Impact of smart technology choice on consumer shopping behavior. Technology Forecasting and Social Change, 181. https://doi.org/10.1016/j.techfore.2022.121752

Scarpi, D., Pizzi, G. & Matta, S. (2022). Digital technologies and privacy: State of the art and…