I. PURPOSE

This review describes theories associated with the pandemic and how they affect marketing and service quality.

II. THEORY OF REASONED ACTION (TRA)

TRA was founded in the late 1970s by Hill, Fishbein and Ajzen (Hill, Fishbein & Ajzen, 1977). The TRA highlights the importance of pre-existing attitudes in the decision-making process. Determinants of TRA include the following:

• Attitude is how we feel about behaviour and is measured as a favourable or unfavourable mindset.
• Subjective norm is defined as how the behaviour is viewed by our social circle or those who influence our decisions.
• The intention is defined as the propensity or intention to engage in the behaviour.

The behaviour construct mainly deals with consumer choice related to a service or product. The last construct, the Intention behaviour related to an intention to purchase a product, also reflects consumers' preference. Peslak, Ceccucci and Sendall (2012) found that both attitude toward social networking and "subjective norm" is associated with the intention to use social networking. The authors highlighted two key deterministic aspects of social networking, mainly the effect of social networks on demographics and the main benefit of cost savings. One of the shortcomings of only considering demographics is that social networking may target a specific target market, typically a younger population that frequently use social media. Studies have found generational differences in the use of social media. The millennials use social networking as their means of communication, while generation X favours professional social channels connected to work needs, Facebook, Twitter, LinkedIn, WhatsApp, Youtube, Zoom, MS Teams, mobile apps, and Skype (Kapoor et al., 2018; Ali Taha, Pencarelli & Škerháková, 2021). Thus, these characteristics are critical aspects of purchasing behaviour of consumers when it comes to health insurance, highlighting an essential aspect of digital marketing function- market segmentation. Saut and Saing (2021) investigated factors that affect consumer purchase intention towards environmentally friendly products. The study found that willingness to pay for a product affects purchase intention. The study also finds that subjective norm has the weakest influence to purchase intention. Thus, indicating that the constructs do not always go in the same direction or influence intention may vary.

Consumers' purchase decisions on tangible products or services are a complex phenomenon as it functions many attributes. This complexity is even more prevalent in purchasing intangible products such as health insurance purchases where such products are intangible. Studies have found that consumers' purchase decisions are influenced by their attitudes, behavioural intention, and local environmental security perception (Hanaysha, 2018; Joshi & Rahman, Rita, Oliveira & Farisa, 2019).

Sandro (2016) contest that Health generally is not considered a public good, as those who pay (through health insurance companies or medical schemes) versus those who do not pay (access care in the public sector) are not always privy to the same quality and standards as a result may not be able to achieve good health. Health is a public good, and purchasers view it as a grudge purchase as such attributes as attitude and norms around the product impact the intention. Bateman also argued that the grudge purchase syndrome often drives negative behaviour (Bateman, 2012). A health insurance product is complex by design and often not comparable to other product types; as a result, consumer behaviours become difficult to measure. Other external factors, such as pandemics, also affect consumer behaviour, and there is little research on the impact of a pandemic on consumer behaviour (Mason et al., 2021). Recent studies have also found the COVID-19 pandemic and found that the COVID-19 pandemic altered consumers' product needs, shopping and purchasing behaviours, and post-purchase satisfaction levels (Mason et al., 2021).

III. THEORY OF PLANNED BEHAVIOUR (TPB)

Azjen (1985) developed the theory of Planned Behaviour in the '80s. This theory extends the Theory of Reasoned Action and aims to model and understand how human beings sequence and process intentions and behaviour (Hill, Fishbein & Ajzen, 1977). Planned behaviour assumes that customers will make rational choices based on the information at their disposal. Both the TPB and RBT to theories are key to marketing management, where marketers base their assumptions about the specific campaign, a product or service on the planned behaviour of customers. According to Ajzen (2020), the consumer's behaviour is a function of intention to perform the behaviour; the intention is based on attitude, subjective norm, and perceived behavioural control concerning the behaviour.

Consumer behaviour comes from intentions that are influenced by subjective attitudes and norms. The three factors responsible for behavioural intentions are subjective norms, perceived behavioural control, and attitudes toward the behaviour. Studies have recommended new component components to be added to the TPB model. TPB has recently been applied in healthcare to examine participants' intention toward seeking help for COVID-19 (Aldalaykeh, Al-Hammouri, Rabbah, & AlDwaikat, 2021). The authors found attitudes toward COVID-19, subjective norms, perceived behavioural control, and COVID-19 knowledge as the main predictors of intentions to seek help (Aldalaykeh, Al-Hammouri, Rababah, & AlDwaikat, 2021). Some studies assess the intention to get vaccinated for COVID-19. Chu, Gupta and Unni found a strong positive correlation between the intention to receive the flu vaccine and attitude and subjective norm; however, a moderate correlation between intention and perceived behavioural control (Ariffin et al., 2021; Chu, Gupta & Unni, 2021). Hossain et al. (2021) used TPB to demonstrate how targeted interventions reduce vaccine hesitancy and increase vaccine uptake to prevent COVID-19. Studies have used the TPB to predict intentions successfully and actual behaviours related to social distancing, PCR testing, and compliance with health protocols; however, very few studies have employed this theory to understand purchasing behaviour (Adiyoso & Wilopo, 2021; Gibson et al., 2021). Even though studies have shown a high level of knowledge regarding COVID-19 amounts to study participants, planned behaviour control is challenging to realize or even measure.

Furthermore, this has mainly been used in studies examining consumer or patient perspectives. The main shortcoming of these studies is the accurate measure of intentions rather than the actual seeking behaviour. Studies showed a gap between the two concepts (Fishbein & Ajzen, 2010; Ajzen; 2020).

There remains a gap on how TPB can fully help health insurance companies to understand consumer attitudes and behaviours during a pandemic. Externalities such as information asymmetry about the COVID-19 pandemic have a considerable potential to influence or even alter consumers' perceptions, leading to behavioural changes. Furthermore, the emergence of new variants makes it challenging to understand and even predict how the unprecedented COVID-19 pandemic will unfold in the future. One of the primary outcomes of lock-down due to COVID-19 was consumers' panic buying phenomenon, which was evident in the global landscape. Studies have found that attitudes, subjective norms, scarcity, time pressure, and perceived competition positively influenced customers' panic buying intention (Singh et al., 2021). Opinions and beliefs mainly drove the pandemic; the literature review revealed both negative and positive opinions on the role of attitudes on behavioural Intention (Alexa, Apetrei & Sapena, 2021). Literature also reveals a positive attitude toward a brand or service that desires behavioural Intention (Vermeir & Verbeke, 2008). Social norms and behavioural control have also been found to affect attitudes, which indirectly influence the intention. However, this could also be difficult to assess in a dynamic environment shaped by shocks such as the COVID-19 pandemic (Alexa, Apetrei & Sapena, 2021). These factors extend TPB beyond the three main factors, manly attitude, subjective norm, and perceived behavioural control. Health belief model dimensions have also been shown to affect perceived scarcity of products, thus one of the critical determinants of purchase behaviour, which should be studied further to service quality and satisfaction (Chua, Yuen, Wang & Wong, 2021).

IV. DIFFUSION OF INNOVATION THEORY (DOI)

Studies have assessed key factors that affect the adoption of an innovation, whether this is in a form of a new technology or improvement in business processes, services, or products broadly. Rogers developed the Diffusion of Innovation Theory (DOI) in 1962, one of the oldest social science theories (Rogers, 1962, 1995, 2003, 2010). The five constructs of DOI that all impact or influence innovation adaption (Rogers, 1995) include the following:

• Relative advantages,
• Complexity,
• Trialability,
• Observability, and
• Compatibility

A study by Mavetera, Jokonya, and Maradung (2017) investigated the adoption of Internet banking. Zhang, Yu, Yan. et al. (2015) argues that it remains unclear if patients are willing and able to accept and use innovations such as e-health. The study found that key factors that affect adoption are perceived ease of use, usefulness, and compatibility. Recently, studies have used consumer behaviour theories to explain consumers' resistance and non-adoption of digital innovation (Talwar S, Talwar M, Kaur P & Dhir A, 2020).

The complexity and compatibility of the offered product are the underlying factors in adopting a new service, product, or innovation. Health insurance companies need to look at product simplicity and standardization. Talwar et al. (2020) further argue that value is the cornerstone of addressing the usage barrier related to the usability of the service or product and the changes that consumers need to undergo to use it.

COVID-19 forced many companies globally to be more innovative in their branding strategies and engage with consumers. When promoting an innovation, different strategies appeal to the different adopter categories. The product offering is also a key marketing feature; some medical schemes use market segmentation strategies to attract a specific target market. Innovation has become a more prominent component of product development where medical schemes must develop products that appeal to specific market segments and customer needs. The pandemic has also sparked innovation in insurance and other industries. Companies are integrating innovation in technology, talent, and business models into changing environments which is also a function of consumer behaviour (Deloitte, 2021). The effect of social media has been the innovative strategies that have been used globally to reduce the spread of COVID-19 through priority audience segments, desired behaviours, audience insights - barriers and desired benefits, and marketing intervention tools to help citizen behaviour change (Lee, 2020).

Adopting social media as an innovation strategy to respond to pandemics has relative advantages. However, some studies show relative disadvantages such as anxiety; Ahmad and Murad (2020) found that social media has played a vital role in spreading anxiety about the COVID-19 outbreak. Indeed, the COVID-19 era has seen significant adoption of social; however, mainly communication and information sharing in the traditional sense, one is yet to see the full exploration of social media adoption mainly focused on systems-level than the industry or company level. Fosso Wamba and Carted (2014) investigated factors affecting SMEs' social media adoption. The study found that managers' age, firm size, innovativeness, and the industrial sector positively related to adoption. Furthermore, financial resources are the deterministic factors for companies to innovate, which is currently not a component of DOI, thus indicating a lack of research on the size and company level.

The three main factors that have been affected by lack of innovation in medical schemes are product offering and benefit design, operating environment, and the size effect. Willie (2021) found that those closed schemes spend significantly less on marketing than open medical schemes, thus indicating the effect of the sector. Restricted schemes (employer or sector-based medical schemes) operative in defined markets do not compete for membership. Large schemes ( $\ge 30$ 000 beneficiaries) spend more on marketing fees than medium ( $\ge 6000$ members and less than 30 000 beneficiaries) and small ( $\le 6000$ members) on the size factor. The effect of product offering in terms of many benefit options was also one of the deterministic factors of marketing expenditure. There is evidence that product offering in medical schemes does not offer value for beneficiaries despite the increasing marketing fees. Medical schemes with more benefit options also attract higher marketing expenses (Willie, 2021). Despite many benefit options currently offered in the sector, the Health Market Inquiry (HMI) recommendations further highlight a need for a more competitive environment for medical schemes to compete for a product offering that adds value for consumers (CompCom, 2019). The recommendations further highlight the complexity of product offering in that medical schemes currently compete on risk selection and the proliferation of benefit options that are neither standardized nor comparable.

Barriers to innovation from a product offering perspective is the lack of value creation. Most medical schemes have focused on cost-saving. Other constraints are lack or scarcity of qualified and competent workforce, lack of appetite from the board, and lack of specific knowledge of understanding that mediums such as social media channels can play in new customers (Bogea & Brito, 2018). Kuikka and Akkinen (2011) identified five categories of internal challenges involving the management challenges within the company, impacting social media adoption barriers. These included either financial or otherwise resource constraints—unclear strategy on digital marketing strategies and the value they can bring.

V. TECHNOLOGY ACCEPTANCE MODEL (TAM)

TAM model is considered one of the most effective approaches to investigating the adoption and usage of Social Media Marketing by businesses (Fei, Ozgur, & Bernhard, 2015). Davies initially presented TAM in the late 1900s and the theory. The main attributes of the TAM include the following:

• Perceived Usefulness (PU),
• Perceived Ease of Use (PE) and,
• User Acceptance (UA).

The TAM model has been well-known for decades and has been used widely by many scholars in understanding the behavioural context of technology usage and adoption by consumers and businesses

(Gefen, David, et al., 2003; Rauniar et al., 2014). The exponential increase in technology adoption in the COVID-19 era creates new interests in utilizing TAM in the health sector, particularly in the health insurance industry (Bickley, Chan, Skali et al., 2021; Cascella, Rajnik, Aleem, et al., 2022; Zalat, Hamed, Bolbol, 2021; Dawn, 2021; Abbas, Wang, Su & Ziapour, 2021).

TAM focuses on establishing the relationship between technology acceptance and user factors and is considered a powerful model for predicting user acceptance. Studies have shown that other than the TAM model's fundamental salient determinants (perceived usefulness, perceived ease, and user acceptance) (Kalayou, Endehabtu & Tilahun, 2020; Buabeng-Andoh, 2018).

Several studies have reviewed the TAM model and included a set of new determinants. Kaur and Malik (2019) extended the TAM model with electronic service quality, and the study investigated factors influencing Indian customers' intentions and adoption of internet banking. Most ATM model studies have focused on internal factors with fewer references to social factors and other environmental factors. The emergence of COVID-19 is impacted by numerous external factors and uncertainties that have not been considered in the ATM model. Other social-media-related factors such as ser's critical mass (CM), social networking site capability (CP), perceived playfulness (PP), trustworthiness (TW) also affect strategies impact on the intention to use social networking.

VI. SOCIAL COGNITIVE THEORY (SCT)

Bandura introduced SCT in the later 1980s and is the improved view of the original Social Learning Theory (SLT) introduced by Miller and Dollard in 1941 (Momani & Jamous, 2017; Miller & Dollard, 1941; Bandura, 1986). SCT assumes that people learn by observing each other and is influenced by three determinants (personal, behavioural, and environmental factors). Subsequently, the theory assumes that previous experiences create expectations of specific outcomes concerned with human behaviour (Momani & Jamous, 2017). The application of the SCT in investigating the usage and adoption behaviour of technology was discussed by Thompson, Compeau & Higgins (206). The authors proposed an improved list of constructs to apply in the technology field. They reviewed seven theories and models focused on the study of technology acceptance by users from two distinct viewpoints - behavioural and social viewpoints-that have been widely applied and studied in scholarly research. Although most theories on technology acceptance behaviour have been developed over the years and were extended into new models and approaches, the limitations still exist. TRA and TPB are the general models that are not valid in investigating the behavioural characteristics of the technology acceptance nature of individuals.

On the other hand, TAM and TAM2, also basic models, effectively understand a general picture of the user's intention to adopt the technology. Both are ineligible in describing their technology adoption behaviour (Lai, 2017; Momani & Jamous, 2017). Furthermore, Diffusion of Innovations Theory (DOI) investigates the innovation adoption behaviour from the organizational and environmental perspective and is less effective in practical evaluation of the process than other technology acceptance models. In general, different terminologies are adopted to define the model's constructs by different theories, while the majority are found to represent the same components (Momani & Jamous, 2017).

VII. THE UNIFIED THEORY OF ACCEPTANCE & USE OF TECHNOLOGY

The UTAUT was first introduced by Venkatesh et al. in 2003, combining alternative views on user and innovation acceptance. The theory is derived based on the integration of previously developed theories on technology acceptance such as Theory TRA and TAM, the Motivational Model (MM), the TPB model, IDT, a combined TPB/TAM model, the Model of PC Utilization and Social. The UTAUT theory consists of four primary constructs: performance expectancy, effort expectancy, social influence, and facilitating conditions. The theory considers additional constructs - gender, age, experience, and voluntariness of use- to influence the user's behaviour. Akinnuwesi et al. (2022) studied factors influencing the behavioural intention of people to accept COVID-19 (CDTT) using the UTAUT. The application of the UTAUT model has been prevalent in the COVID-19, with studies investigating the use of digital technology for tackling COVID-19. The study found that performance expectancy (PE), facilitating conditions (FC) and social influence (SI) are the best predictors of people's BI to accept CDTT (Akinnuwesi, Uzoka, Fashoto et al., 2022).