Smart Mask Hypothesis Chapter

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 buyer’s social influence (Hosseini et al., 2015; Myresten & Setterhall, 2015, p. 5). The factors that shape the buyer’s 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 person’s beliefs that would affect the buyer’s 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 people’s 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 people’s 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 people’s 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 buyer’s 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 consumer’s 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 product’s 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 consumer’s 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 consumer’s 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 person’s 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 re-used several times as they would be re-charged for the in-built technological features to work well with the outer environment and detect any allergic pathogens in the air, possibly risky for the user’s health. The filtration efficiency along with retention of battery, which is expected to be more than five days, are some of the value-added traits with ease of use, like a smooth layer of fabric for keeping it on the face without irritation and that too, for long hours (El-Atab et al., 2021).

Other investigations of the proposed technology mechanism that would be charged within smart masks are the self-sanitizing and filtration efficiency that would enable extra comfort for the user ( De Sio et al., 2020). Certain visions have been adopted for smart masks to work effectively, for instance, through thermal disinfection, light control when the sunlight exposure is high, and an electrospun layer that would help create a resistance against the infectious air particles. The comfort and convenience of the system use are part of the mechanism that would help devise a new side of consumer attitude towards buying and using the masks. The vision was mainly adopted when during Covid-19, the medical professionals had to work long hours at the hospitals with the same mask that were crammed with humidity, breath and infected with several germs while treating numerous patients (De Sio et al., 2020). The idea was to build a high filtration mask with an innovative technology that would be cost-effective and high on performance to mitigate health risks and lung inflammation.

Research has further suggested that consumer engagement, which could be translated into personalization, is imperative for smart devices to prioritize consumer well-being (Henkens et al., 2020). The service providers of smart devices keep technology in the limelight since artificial intelligence has one of the most prominent design features that smart devices have been equipped with (Neuhofer et al., 2015). The customers’ perceived effectiveness of the product is believed to be high when the product or service knows their desires and fulfills their needs. For example, the consumer’s daily lives are made convenient with smart home devices whose smartness creates a new aura of the home with personalization and customer engagement in the form of personalization. This very prodigy, corroborated by research, would instigate more consumer engagement and better consumer intention to disclose their data for improved moderation of smart devices (Scarpi et al., 2022).

With the convenience that the customer is looking for and the perceived effectiveness that the product would provide him, the customer is more apprehensive of how the product would work out for him and whether the perceived usefulness would enhance the performance. For this reason, the willingness to accept the product, predominantly with new technology, is confusing for the potential buyer. He would look for ways to eliminate his confusion, for which social influence is a subjective norm inherited from the theory of reasoned action. The likelihood that a person would opt for a product is the function of other people’s expectations and motivations for behaving in a certain way (Beldad & Hegner, 2017). Sufficient motivation would direct the potential buyer to comply with the social norms of acceptance, creating a phenomenon of social influence. Thus, comes the relevant criteria of willingness to accept a new technology that has been previously accepted and positively reviewed by other members of his society, forming a psychological and sometimes emotional impact on his final decision about the purchase. It is important to note that ‘trust’ plays a significant role in gaining social influence from those peers whom the potential buyer trust. Studies have verified that trust positively influences the buyer’s final purchase decision since perceptions and past experiences are somewhat shared (Wang et al., 2022). The uncertainty is reduced when the potential buyer feels the evaluations of a used product by the other person has been able to mark its confidence over the other person’s mind, from which the potential buyer takes his cue and decides to either accept or reject the reject based on his product evaluation with social influence.

Hence, with the above research on technology integration in products, consumer evaluation of the effectiveness of such products, more specifically smart devices and personalization with value-added benefits, could help in the formation of the following hypotheses:

H3: Consumer evaluation of smart masks on technology aspects will positively influence consumer attitude

H4: Consumer evaluation of smart masks on design aspects will positively influence consumer attitude

H5: Consumer evaluation of smart masks on social acceptability will positively influence consumer attitude

The Influence of Attitude on Intention to Use

Studies have cited that consumer attitude deeply influences his intention to use a product or service (Hussein et al., 2017). The positive or negative attitude towards a product would signify his interest in altering his intention accordingly. The acceptance and rejection of technology are the same attitudes marketers have been aiming to probe with shrewdness shaping customer acceptance of the product with personalization and value addition.

The intention has been one of the most stimulating topics in marketing since it interprets the buyer’s behavior towards the product, especially when a novel concept is brought into the market (Gultom et al., 2020). Technology has been shaping the consumer’s lives with enhanced convenience and ease, for which the consumer has shown favorable acceptance to accept it.

Attitude deals with the influencing intention of the buyer toward a product or service and the behavioral stimulation caused by it (Massoro & Adewale, 2019). The willingness to give a new technology at least one try occurs with this intention as the attitudes cause a stir with a subtle hint of influencing motivation. The more positive the attitude, the higher the intention to use a new product, technology, or feature launched into the market (Hussein, 2017).

With this notion, the sixth hypothesis is developed as follows:

H6: Consumer attitude toward smart masks will positively influence intention to use

Technology Acceptance Model

The technology acceptance model (TAM) is taken from the theoretical grounds of the theory of reasoned action (TRA) (Otieno et al., 2016, p. 4). The innovation or technology in a product is accepted with its perceived usefulness and the convenience of use for the consumers. It is only then accepted by the potential buyers when the predicted attitudes are positive. The user’s willingness to try a new design or feature would rely on the perceived enhancement of the job that the product is aimed for (Otieno et al., 2016, p. 4).

The rejection or acceptance of a new innovative product is crucially determined by the fundamental determinant of subjective norms (Otieno et al., 2016). The specific degree up to which the user would be able to use the product or service conveniently is the perceived ease, which is one of the chief determinants of a product’s performance. If the new technology cannot provide convenience to the user and create hassles for him, he would most certainly reject the technology (Otieno et al., 2016, p. 4). The adoption of technology would be based on negative acceptance, which would be considered a failure of the new technology.

The impact of social relevance or influence is central in gauging the intensity of technology adoption (T.A.) (Lorenz & Buhtz, 2017). When interactions with others occur about their opinions and thoughts relevant to a certain product or service, partial acceptance or rejection subtly occurs in the potential buyers’ minds. The interpersonal considerations cause a natural social influence in the form of group acceptance that collaboratively works to adopt new technology (Lorenz & Buhtz, 2017). It is a seeming interplay of social identity, group norms, social networking, and social influence for the adoption process that influence the emotional and social identity within a group. The undermining explanation of the technology adoption with these subjective norms is mandatory for comprehension before giving the consumer a technology that is immensely reliable on how much convenience it has previously provided to other social networks and how much positivity they would induce into his mind for technology adoption.

The Influence of Technology Aspects on the Intention to Use

The influence of technology aspects on the potential buyer’s intention to use is taken from the technology acceptance model since accepting a new form of innovation means a change in the status quo (Moura et al., 2020). Some people are not open to change and, hence, are fearful of unprecedented results (Skoumpopoulou et al., 2018, p. 211). The rejection of innovation is based on the prior rejection or acceptance of other people and their experiences. The failure to adopt new innovative technology means a lack of familiarity with the infrastructure and its outcomes. The intention to use would greatly depend on the potential buyer’s willingness to accept the technology first (Teo & Zhou, 2014).

Henceforth, the seventh hypothesis is developed as follows:

H7: Consumer evaluation of smart masks on technology aspects will positively influence intention to use

References

Amer, A., Yahya, S. & Jani, S.H.M. (2014). Research on hyper-connectivity element and its utilization on consumer performance expectancy: A literature analysis. The SIT Transactions on Industrial and Business Management (IFBM), 2(3), 108-116.

Beldad, A.D. & Hegner, S.M. (2017). Expanding the technology acceptance model with the inclusion of trust, social influence, and health valuation to determine the predictors of German users’ willingness to continue using the fitness app: A structural equation modeling approach. International Journal of Human-Computer Interaction, 34(9), 882-893. https://doi.org/10.1080/10447318.2017.1403220

Chuchinprakarn, S. (2005). Application of the theory of reasoned action to online shopping. https://www.bu.ac.th/knowledgecenter/epaper/jan_june2005/supanat.pdf

De Sio, L., Ding, B., Focsan, M., Kogermann, K., Pascoul-Faria, P., Petronela, F., Mitchell, G., 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 citizen’s 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)