Generation Z Consumers’ Attitude towards Instant Message Marketing Communications: The Role of Message Characteristics

Keywordsconsumer attitude elaboration likelihood generation Z instant message marketing communication mobile instant messaging applications mobile marketing communication

JEL Classification M31

Full Article

1. Introduction

Generation Z consumers, also known as digital natives (Arora et al., 2020; Sari et al., 2020) are regarded as highly techy-savvy (Feger, 2024), given that they have grown up with unlimited access to the internet, social media and other related mobile communication technologies. According to Hossain (2018), this cohort group possesses greater computer and digital skills than any other previous generation. It is a generation that has considerably higher access to mobile internet services, which allows them to use mobile instant messaging applications (Duffett, 2020). As such, they are constantly connected, always carrying out multiple tasks at once, constantly seeking rapid gratification, and hence, heavily reliant on technology (Feger, 2024). They spend more time online searching for information, sharing buying experiences with peers, and communicating with brands and businesses, (Duffett, 2020; Dwivedi et al., 2021; Feger, 2024).

In an effort to influence Generation Z consumers’ attitude and behaviour, firms are increasingly leveraging instant message applications (MIM apps) like WhatsApp, WeChat, and Telegram among others. This novel and unique marketing communication tool has gained widespread adoption, and opened up new marketing possibilities. Essentially, MIM apps provide firms with simple, convenient, and quick means to communicate with potential and existing clients, particularly young people, (Kremming, 2020). However, Duffett (2016) observed that, “that there is a lack of research into young consumers’ attitudes towards advertising on instant messaging platforms in emerging nations”. More importantly, Zimbabwe’s the demographic profiles indicate that there is a rising young population which account for more than 50% of the national population. In this regard, empirical studies on Gen Z consumers are essential, hence, the study attempts to fill in this gap.

The use of the emerging mobile communication technologies in marketing communication has piqued the interest of both practitioners and academics. These emerging communication platforms have transformed the conduct of MC activities as they present new channels and methods of communication with consumers, (Rehman et al., 2022). Currently, the global expenditure on digital marketing communication is projected to reach over US850bn dollars by 2026 (Dixon, 2024), and more than two-thirds of this figure will be via mobile communication platforms (Dixon, 2024). One of the ways businesses are now actively engaging consumers is through the use of mobile instant messaging (henceforth referred to as MIM) platforms such as WhatsApp Messenger. With over 3 billion users (Dixon, 2024), these MIM apps enable businesses to access and engage a big client base on a regular basis, (Marumbwa and Govender, 2023).

From a marketing communication perspective, MIM apps have a high potential for both push and pull MC (Kremming, 2020). As such, businesses can use IMMC to promote their products and services and communicate directly with customers (Sonnenberg, 2021), through content marketing, product placement, digital display advertising, product news updates, and promotional campaigns (Kremming, 2020). To achieve this, marketers can use the MC capabilities of MIMs namely; personalized messaging, two-way communication, and timely and relevant promotional messaging (Murphy, 2021). Thus, it is evident that this represents some form of transition from impersonal, business and brand promotional messaging to personal, social, and interactive engagement (Kim, 2019). However, this presents opportunities as well as challenges for MC practitioners. In particular, businesses are faced with the major challenge of designing messages which appeal to the Gen Z consumers, so as to influence their attitude towards instant message marketing communication (IMMC).

Some researchers have observed that the attitude of Gen Z towards technology-based MC has yet to be adequately measured, (Duffett, 2016; Tang and Hew, 2022; Safieddine and Nakhoul, 2021). This generation is internet-savvy (Duffett, 2020); and accustomed to certain message and content characteristics of IMMC. As such, it is reasonable to assume that their response to IMMC differs from other generations. Due to the circumstantial socio-cultural backgrounds, Generation Z consumers in developing countries may display unique online behaviours with regards IMMC. This is further accelerated by the dynamic advances in mobile communication technology affordances (Tang and Hew, 2022), which dramatically alter young consumers’ internet behaviour. In addition, some early studies on MIM apps have shown that consumers perceive mobile instant messaging as largely irritating, invasive and intrusive, (Tang and Hew, 2022; Safieddine and Nakhoul, 2021). This, in turn, calls into question the effectiveness of MIM apps as an MC channel.

Hence, in recognition of the marketers' need to identify and understand key design factors of IMMC, it is important to understand the message and content characteristics (central and peripheral route factors) of IMMC that influence the attitude of Generation Z consumers. A lack thereof implies that the MC capabilities and potential of MIM apps is limited. To this end, the study aimed to answer the following questions: what is the influence of central route message characteristics, namely informativeness, entertainment, personalisation and irritation on the attitude of Generation consumers; what is the influence of peripheral route message characteristics, namely; credibility, interactivity and media richness on the attitude of Generation Z consumers?

By addressing the principal research questions mentioned above, the paper contributes to the existing literature in several ways. First, the study helps to understand the fundamental IMMC message characteristics that captures the attention and influence the behaviour of Gen Z consumers. Secondly, the paper contributes to the conceptual discussion of contemporary MC tools such as MIM apps from an elaboration likelihood perspective. Finally, this study adds new insight into how to design effective IMMC messages that influences Gen consumers’ attitude and behavioural responses.

2. Literature Review

2.1. Instant Message Marketing Communication (IMMC)

The concept of instant message marketing communication (IMMC) can be traced to the broader mobile marketing discipline. Early researchers broadly defined mobile marketing the conduct of marketing activities via a ubiquitous network accessible to consumers via personal mobile devices, (Varnali and Toker, 2010). Simply put, it is the use of mobile technologies to conduct marketing and promotional activities. However, as mobile communication technologies advance, researchers viewed mobile marketing as marketing communication conducted via mobile media; mobile advertising; text message marketing; and wireless advertising (Broadbridge, 2018). Hence, given the recent technological developments, the conceptualisation of mobile marketing can now include smartphone advertising, (Martins et al., 2019; Arora and Agarwal, 2020); SMS marketing/advertising (Sharma et al., 2021; Sreejesh et al., 2020;), in-app mobile advertisements, (Sung, 2021; Sirgudsson et al., 2018) and more recently, instant message marketing (Tang and Hew, 2020; Sonnenberg, 2021; Murphy, 2021; Mouakket, 2019).

According to Kim (2019), instant message marketing is the use of MIM applications as a conversational tool to reach people at scale with targeted messages. Gibbons (2018), view it as the act of using MIMs to facilitate conversations and commerce with prospects and customers. Simply put, instant message marketing is a marketer's effort to communicate with past, current, and prospective customers via MIM apps such as WhatsApp, Facebook Messenger, WeChat, and others. Therefore, IMMC is defined in this study as the collective process of leveraging MIM platforms to transmit promotional messages in various multimedia formats to achieve MC objectives (Gibbons, 2018; Kim, 2019). This is a novel form of marketing communication which leverages the communication affordances of mobile instant messaging applications and platforms.

2.2 Elaboration likelihood model (ELM)

In the existing MC literature, it is evident that researchers have used diverse theoretical models to explain consumers’ attitudes toward a company’s MC efforts (Sharma et al., 2021; Marumbwa and Govender, 2023). According to Kitchen et al., (2014), there has been a call to extend the application of traditional MC theories and models to emerging MC tools, such as MIM apps, and new demographic consumer groups, such as the Gen Z cohort. With this in mind, this study employed the elaboration likelihood model (ELM) by Petty and Cacioppo (1981). The elaboration likelihood model (ELM) is generally used to explain how communication results in persuasion through the formation or modification of one's attitude. It is based on the idea that; the central route or peripheral route are two possible ways for customers to react to persuasive messages (Kitchen et al., 2014). The central route views the customer as an engaged party in the communication process who actively listens to the message content. Under the peripheral route, the consumer uses heuristics and other external indicators, such as source credibility, with little cognitive effort on their part. Hence, in this study, the central route comprises IMMC message characteristics such as informativeness (IF), entertainment (EN), personalisation (PS) and irritation (IR) fell into the central route category, whilst, credibility (CR), interactivity (IN) and media richness (MR) is the peripheral route characteristics of IMMC.

Informativeness and consumer attitude

Consumers anticipate marketing communication to be more informative than merely product placement (Arli, 2013). Consequently, some current studies have disclosed a strong positive association between the informativeness of MC and consumers’ attitudes toward online MC (Arora and Agarwal, 2020; Gaber et al., 2019). In a recent on SMS advertising, Sharma et al., (2021) affirm a strong positive relationship between informativeness and consumer attitude. Moreover, an early study on mobile MC by Blanco et al., (2010) asserted this relationship. They stated that consumers’ attitude towards mobile marketing communication is greatly influenced by the informational aspects of mobile marketing communication. This was further confirmed by Drossos et al., (2014) who found that there existed a significant and positive relationship between informativeness and the perception of SMS advertising among younger customers. Accordingly, it is anticipated that perceived informativeness of IMMC will strongly influence the Gen Z consumer’s attitude. Thus, it is hypothesized that:

H1: The perceived informativeness of IMMC will positively influence the attitude of Gen Z consumers towards IMMC.

Entertainment and consumer attitude

Hamouda (2018) indicated that the perceived entertainment of MC messages transmitted via new media technologies positively influence consumers’ perceived value and attitude. In a study of mobile advertising, Wang and Genç (2019) revealed that the more the consumer believes that mobile advertising messages provide entertainment experiences, the more positive the consumer attitude. This observation is consistent with the findings by Gaber et al., (2019) and Kim (2020) who established that the perceived entertainment of mobile MC messages favourably influences young consumers’ attitudes. This implies that entertaining MC messages are positively related to positive consumer attitude, hence, to ascertain this relationship in the context of this study, it is hypothesized that:

H2: Perceived entertainment of IMMC will positively influence the attitude of Gen Z consumers towards IMMC

Personalisation and consumer attitude

Trang et al., (2023) suggest that one of the key objectives of personalisation is to ensure the dissemination of the right message to the right audience at the right time. This implies that personalisation involves individualised communication to a specific consumer based on their actual or supposed preferences. To this end, several past studies have confirmed a positive relationship between personalised MC messages and consumer attitude (Arora and Agarwal, 2020; Lee et al., 2017; Xu, 2006; Jung, 2017). A study by Humbani et al., (2015) showed that consumers have a more favourable attitude and thus respond positively to personalized SMS advertising. Furthermore, a recent study by Bakr et al., (2019), concurs that accurate personalisation is crucial to ensure that mobile MC messages are useful and relevant to recipients. In the context of MIM apps, personalisation is considered to be a key determinant factor influencing consumer attitude towards IMMC (Xu, 2006; Sirgudsson et al., 2018). Hence, in accord with the above and to further analyse this relationship for Gen Z consumers in Zimbabwe, the following statement of hypothesis is proposed:

H3: Personalisation of IMMC will positively influence the attitudes of Gen Z consumers in Zimbabwe

Irritation and consumer attitude

Kumar and Mittal (2020) assert that the cost of annoying, offensive and overly irritating MC messages is reduced message efficiency and dwindling trust of a MC channel. As such, MC practitioners need to guard against annoying and distractive MC messages. The drawback of such messages is that they negatively influence consumer attitude. Put simply, an annoyed consumer has a general tendency of developing a negative attitude towards the MC message, (Ducoffe, 1995). In support of this, several previous researches (Sharma et al., 2022; Lee, et al., 2017; Kim & Han, 2014; Arora and Agarwal, 2020; Gaber et al., 2019; Goh et al., 2020; Wang et al., 2019; Sirguddson et al., 2018), affirm a negative association between irritation and consumer attitude. This implies that when consumers regard mobile MC messages as confusing, insulting, or unduly manipulative, they develop a negative attitude towards such messages. In order to explore the relationship further, in particular, in the context of IMMC and Gen Z consumers, the study hypothesizes that:

H4: The irritation felt from IMMC will negatively influence the attitudes of Gen Z consumers in Zimbabwe

Credibility and consumer attitude

The credibility of a message source in a technology-mediated MC environment helps validate the potency of the MC message. Wang and Genç (2019) opine that credibility is at the center of all online MC messages. In an earlier study by Ducoffe (1996), it was reported that the credibility of online MC is positively associated with consumers’ attitudes. The observations are supported by Maseeh et al., (2021) and Gaber et al., (2019) who reported that credibility is a very important factor that has a strong and significant positive influence on consumers’ attitudes. Furthermore, in studying individual user’s adoption of mobile advertising in China, Gao and Zhang (2016) concluded that credibility is positively associated with consumers’ attitudes. Also, Wang and Genç, (2019) studied the path to effective mobile advertising in Asian markets and observed that among other factors, credibility emerged as a significant belief factor that positively influences consumers’ attitudes. This indicates that in the context of IMMC, credibility plays an important role in shaping consumers’ attitudes. Therefore, in light of this above discussion and to further analyse the influence of the credibility of IMMC on Gen Z consumers’ attitudes in Zimbabwe, the study hypothesizes that:

H5: Credibility will positively influence the attitudes of Gen Z consumers in Zimbabwe

Interactivity and consumer attitude

Several studies on technology-mediated MC have discussed the influence of interactivity on consumer attitude, (Srajeesh et al., 2020; Arora and Agarwal 2020; Liu et al., 2019). In the context of mobile MC, past researchers have confirmed that interactivity is a predictor of consumer attitude, (Humbani et al., 2015; Duffet, 2016). In a study of consumer acceptance of mobile advertising, Liu et al., (2019) support this view by stating that interactivity is one of the most key determinants of consumer attitude. They further suggest that interactivity influences the acceptance of emerging MC tools including mobile media, particularly for young consumers. In addition, Arora and Agarwal (2020) and Wang et al., (2020) conclude that interactivity positively influences consumer attitude towards MC in virtual communities. This relationship is further cemented by Park and Yoo, (2020) who found out that the three interactivity dimensions (i.e., controllability, responsiveness, and communication) positively influence consumers’ attitude. Based on these findings, concerning the Gen Z consumers’ attitude in Zimbabwe, it is hypothesized that:

H6: Interactivity will positively influence the attitudes of Gen Z consumers in Zimbabwe

Media richness and consumer attitude

In a study of the efficiency of mobile media richness across different stages of online consumer behaviour, Tseng and Wei (2020) found that media richness has a significantly positive impact on consumer behavioural responses. In their seminal work, Simon and Peppas (2004) revealed that the perceived media richness of a website as an MC tool positively influences users’ attitudes. Previous researches highlighted a positive relationship between media richness and behavioural attitude as measured by MIM app users’ satisfaction and loyalty (Tseng et al., 2016; Tseng et al., 2019). Therefore, the study considers it worthwhile to explore the effect of perceived media richness on consumer attitude for Gen Z consumers in Zimbabwe, hence, it is proposed that:

H7: The perceived media richness of IMMC will positively influence the attitudes of Gen Z consumers in Zimbabwe

3. Research Methodology

The researcher employed the quantitative research approach to collect data through a survey of Generation Z consumers in Zimbabwe. The literature has described Generation Z as the group of people born between 1995 and 2010 (Brown, 2020; Maggs, 2019). Thus, the sample comprised the older generation Z consumers, over 18 years old. A total of 468 questionnaires were issued, of which, 410 were valid for further statistical analysis. A structured questionnaire was designed and employed to collect data. Both the independent and dependent variables were measured using measurement items and scales adapted from pre-validated measured and literature review. In particular, the items used in past studies on SMS advertising, mobile advertising and social media advertising were adopted and adapted to suit the present study. The measures were based on a 5-point Likert scale ranging from strongly disagree (1), disagree (2), Neutral (3) agree (4), strongly agree (5). Overall, the questionnaire comprised two major sections. The first section contained information on the demographic profiles of the respondents in terms of gender, age and area of study. The second section contained questions addressing the research variables (i.e., predictor and outcome) which provided answers to principal research questions and objectives.

4. Analysis and Results

The targeted sample size was 550, of which results from only 410 respondents were eventually considered valid for analysis. This indicates a high response rate of 75% which is acceptable for further statistical analysis of the data. The results in Table 1 show that 52% of the survey respondents were males and 48% were females. In terms of the range, the majority of the respondents (35.4%) fell into the 18 to 22 years age category whilst the 28 to 32 years age category had the least number of respondents (31.7%). As for the study mode, the results in the table above reflect that the highest number of survey respondents (35.9%) were enrolled in the weekend class study mode and the least (30.1%) were enrolled in the block release study mode.

Table 1: Respondents’ socio-demographic profiles

Source: Primary data

4.1 Descriptive Statistics of Central Route Characteristics

As for central route factors, the respondents were asked to indicate their level of agreement using the scale 1 = strongly disagree to 5 = strongly agree to 24 measurement items concerning central route factors under the construct ‘entertainment’, ‘informativeness’, ‘irritation’, and ‘personalization’. The responses and mean values are reflected in Table 2.

Table 2: Descriptive Statistics of Central route characteristics

Source: Primary data

The responses and mean values reflected in Table 3 show that the majority of the respondents agreed with all the statements on entertainment (EN-EN6). The mean score values ranged from 3.87 (EN4) to 4.01 (EN1). For the informativeness construct, the results show that the respondents agreed with all the statements on informativeness. The mean scores ranged from 3.94 (IF5) to 4.10 (IF7). The third central route factor irritation had a total of 6 items. The results indicate that the respondents agreed with all the statements, with the lowest mean score value of 3.27 observed on IR3 and the highest mean score value of 4.07 observed on IR6. Concerning the personalisation construct, the results that respondents agreed with all the statements (PS1-PS5) with the highest mean score observed on PS4 (4.01) and the lowest mean score on PS3 (3.32). The findings show that the respondents consider the central route characteristics of MIM marketing communication messages when making purchase decisions.

Table 3: Response with regard to Peripheral route factors

Source: Primary data

With regards to peripheral route factors, the respondents have presented 15 items under the constructs, namely; ‘credibility’, ‘interactivity’, and ‘media richness’. It is evident from the results reflected in Table 5.3 that the respondents showed agreement with all the statements on peripheral route factors. The lowest mean score was observed on media richness (MR4 = 3.24; SD = 1.08) and the highest mean score on credibility (CR1= 4.10; SD = 1.71). The findings show that the respondents view peripheral route characteristics of MIM marketing communication messages as influential when making purchase decisions.

4.3.2 Assessment of measurement model using Confirmatory Factor Analysis (CFA)

Before the development of the structural model to test the hypothesis of the study, CFA should be conducted to examine measurement model fitness (Saliya, 2022). The Maximum Likelihood Estimation technique was employed, which enables the simultaneous estimation of model parameters by the researcher (Frey, 2022; Thakkar, 2020). As part of the CFA procedure, several measurement model fit indices were examined in this study. In Smart PLS 4, every latent variable was correlated with another to examine if the measurement model met the minimum requirements for CFA. The results show the items for each respective construct as well as the factor loadings. In this diagram, both exogenous and endogenous latent constructs were included to examine measurement model fitness. The results of measurement model fit indices, factor loadings, correlations, construct validity and reliability and discriminant validity are fully explained below.

Measurement model fit indices

Several measurement model fit indices were examined in this study. Table 4 below shows the CFA model fit indices and the comments made with regard to the minimum standards.

Table 4: CFA Model Fit Indices

Source: Primary data

The results in Table 3 above show that the CFA model developed for this study met the minimum requirements for all the above model fit indices. The Chi-square/DF was 2.942 which was below the minimum threshold of 5 and this suggested that the model was acceptable. The RMSEA and SRMR are 0.069 (less than 0.08) and 0.031 (0.05) suggesting a good model fit. The NFI, and TLI were 0.932 and 0.947 respectively. These indices were above the minimum threshold of 0.9 suggesting good model fit. Additionally, the CFI value of 0.954 was above the recommended threshold of 950 suggesting a highly satisfactory model fit. The results of the measurement model suggested that the items used in this study were the true representations of the underlying constructs. By the same token, these indices suggested that the model fitted the data well as recommended in running structural equation modeling (Denis, 2021; Yang and Luo, 2022). The next step was to examine the factor loadings.

Measurement model factor loadings

Table 5 below shows the CFA factor loadings for the study. Factor loadings show which questionnaire items are mini representations of the underlying construct (Hair et al., 2021; Sarstedt et al., 2020). Values above 0.7 are satisfactory for an item to be included in the modelling framework (Denis, 2021; Hair et al., 2021; Hamaker et al., 2021).

Table 5: CFA Factor Loadings

Source: Primary data

According to Mehmetoglu and Venturini, (2021), factor loadings assist the researcher in the selection of items that can explain the highest variance in the underlying construct. The higher the factor loading, the better the item is a mini representation of the underlying latent construct. In our study, behavioral intention had 6 items with factor loadings ranging from 0.925 to 0.971. The other constructs had three or four items with factor loadings above 0.7 except for subjective norms which had only two items. The study retained 2 items for subjective norms to preserve model validity and reliability as well explanatory power of the construct. The items for SN had good factor loadings above 0.95. The results of the factor loadings above suggested that all the items included in the analysis had acceptable values in explaining the respective constructs.

Correlation coefficients between latent constructs

After examination of the factor loadings, the next step was to observe the correlation coefficients between the variables of interest. Table 6 shows the correlation coefficients between the different sets of latent constructs.

Table 6: Correlation coefficients of exogenous latent constructs

Source: Primary data

The purpose of running correlation analysis in SEM is to observe the extent to which the latent constructs are related and detect multicollinearity (Hair et al., 2021; Sarstedt et al., 2020). In structural equation modeling, latent constructs should be allowed to correlate but should not suffer from multicollinearity. In this study, both exogenous and endogenous constructs were included as part of the correlation analysis. The highest correlation was observed between information and entertainment with a coefficient of 0.904, followed by irritation and personalization of 0.834. Multicollinearity is a situation whereby 1 two or more sets of predictor variables are highly related thereby leading to inaccurate results about the effect of 1 variable on another. All the other exogenous constructs had coefficients less than 0.8 suggesting the absence of multicollinearity. In this study, most of the constructs had weak to moderately strong correlations, suggesting that multicollinearity was not a major concern. Therefore, this study observed that the exogenous constructs included in the analysis were independent of each other.

Construct reliability and validity

Construct validity and reliability measures for the study were estimated. These measures include the Cronbach’s alpha, composite reliability, and average variance extracted. The results are presented in Table 7 below.

Table 7: Validity and reliability measures for model variables

Source: Primary data

After presenting the results of reliability indicators, the next step in evaluating the measurement model involves examining internal consistency reliability. Kock (2015) suggested that in SEM, one of the primary measures used for this purpose is composite reliability (C.R), which indicates the level of reliability. Higher values of C.R. indicate higher levels of reliability (Chang et al., 2016; Cheah et al., 2018). For all the constructs in this study, the C.R values exceeded 0.7, indicating satisfactory internal consistency. The coefficients for all the latent constructs met the criteria for both Cronbach's alpha and C.R measures. As can be seen above, the Cronbach’s alpha coefficients were also above 0.7.

The results of the convergent validity assessment are also presented in Table 6 above. Hair et al., (2020) noted that convergent validity refers to the extent to which a construct explains the shared variance among its indicators. To evaluate convergent validity, the average variance extracted (AVE) was calculated. A minimum threshold of 0.50 is typically considered acceptable for AVE (Hair et al., 2020). A value of 0.50 or higher indicates that the construct accounts for 50 percent or more of the observed variance in its indicators. In Table 6, the highest value of 0.967 was for CA. The measurement model satisfied the requirements of convergent validity. The subsequent step involved examining discriminant validity for all the constructs.

4.3 Structural Equation Model (SEM): Central route factors, peripheral route factors and consumer attitude

After examination of the CFA model, the next step was to develop the structural model. In this study, central root factors, and peripheral root factors were hypothesized to have a direct influence on consumer attitudes. As reflected in Figure 5.2, the central route factors (IF=informativeness, EN=entertainment, PS=personalisation and IR=irritation) and peripheral route factors (CR=credibility, IN=interactivity and MR=media richness) influenced consumer attitude. Additionally, consumer attitude (CA) also affected behavioural intentions (BI).

This study also included a moderating variable impulsiveness (IM). To estimate the interaction effects as part of the moderation analysis, double mean centering (Mehmetoglu and Venturini, 2021; Sarstedt et al., 2020) was that is the appropriate approach in the development of the variable CAIM (which indicates consumer attitude multiplied by impulsiveness). Table 8 below shows the standardized regression coefficients for the central route factors, peripheral route factors and the theory of planned behavior variables.

Table 8: Standardized regression coefficients

Source: Primary data

As previously noted, the first research question pertains to the central route factors. These were informativeness, entertainment, personalization and irritation. These variables had different influences on consumer attitude is fully explained below.

5. Discussion and conclusion

Informativeness had a non-significant negative influence on consumer attitude as reflected by the standardized regression coefficient of -0.039 with a p-value of 0.462. These results suggest that informativeness does not have a significant influence on consumer attitudes among Generation Z consumers in Zimbabwe. Therefore, the hypothesis that informativeness has a significant positive influence on consumer attitude was rejected. The possible implication of these results is that informativeness is not a significant factor among Generation Z consumers when it comes to MIM apps. That is, despite the expected influential role of informativeness, Gen Z consumer did not consider promotional messages in MIM apps to be a good source of information about products. They also did not believe that IMMC supplied relevant information on products or brands, provided up-to-date complete product or brand information. These findings are not consistent with results reported on similar online MC efforts, namely; social media advertising (Arora and Agarwal, 2020), digital advertising (Panggati et al., 2023) and SMS advertising (Amaoko et al., 2023). These researchers affirm that informativeness, which denotes the reliability of information presented in a MC message, positively influence consumer attitude.

Entertainment was also another central route factor of interest in this study. The study established that entertainment had a non-significant positive influence on consumer attitude as reflected by the regression coefficient of 0.07 with a p-value of 0.167. Therefore, the hypothesis that entertainment has a significant positive influence on consumer attitudes among Generation Z consumers was rejected. In the context of this study, chances are high that Generation Z consumers find entertainment to be of no significant influence on their attitudes towards instant messaging mobile applications communication messages. Hassan concluded that entertainment had no significant influence on consumer attitude. This is also supported by other researchers such as Roth-Cohen et al., (2022) and Smith, (2017). These authors argued that the non-significant correlation of entertainment and attitude of Gen Z consumers is attributed to the notion that, any strong positive emotion will influence Gen Z consumers other than humorous, fun, pleasurable or enjoyable IMMC messages.

This study established that personalization had a significant positive influence on consumer attitude as shown by the regression coefficient of 0.101 with a p-value of 0.015. These results suggested that a unit increase in personalization will result in consumer attitudes toward MIM applications increasing by approximately 0.101 units. If advertisers and marketers personalize their different instant messages, chances are high that this increases consumer attitude among Generation Z consumers. Therefore, the hypothesis that personalization has a significant positive influence on consumer attitude could not be rejected. This affirms the observations reported in several prior studies by De Keyzer et al., (2021) who observed that the perceived personalisation of MC messages improves the consumers’ attitudes. This is achieved through increasing the consumers’ perceptions of the relevance of the MC message and decreasing the perceived intrusiveness. The aforementioned findings imply that the attitude of Gen Z consumers can be influenced by disseminating the right message to the right audience at the right time. Hence, individualised communication with a specific consumer based on their actual or supposed preferences may trigger positive responses. This is supported by Koyen (2022) who argues that the nature of communication in MIM apps provides a holistic mobile MC approach.

The study also established that irritation had a significant negative influence on consumer attitude as reflected by the coefficient of -0.098 with a p-value of 0.026. A unit increase in irritation among Generation Z consumers will result in their attitude decreasing by approximately 0.098 units. Therefore, their hypothesis that irritation has a significant negative influence on consumer attitudes among generations that consumers could not be rejected.

With respect to hypothesis H4, which stipulated that the irritation felt from IMMC will negatively influence the attitudes of Gen Z consumers, the findings confirmed this relationship. The study established that irritation had a significant negative influence on consumer attitude as reflected by the coefficient of -0.098 with p-value of 0.026. This implies that when Gen Z consumers regard IMMC messages as confusing, insulting, or unduly manipulative, they develop a negative attitude towards such messages. For this reason, it is imperative that IMMC practitioners address the several facets of irritation such as interrupting MIM app users’ activities. For example, they can avoid to send text messages, make phone calls, or provide subpar IMMC content. In addition, they can desist from bombarding users with irrelevant information or inundating Gen Z consumers with MC messages they did not seek, (Murillo-Zegarra et al., 2020). A similar opinion was expressed by Sharma et al., (2022) who argue that, the increased usage of digital MC exposes consumers to excessive amounts of MC messages, which may trigger their annoyance and raise concerns about overall MC effectiveness. Furthermore, the findings are supported by the psychological reactance theory, which contends that, individuals have a tendency of responding negatively when they feel as though their freedoms are in danger, (Brehm, 1989; Roth-Cohen et al., 2022). Thus, one can suggest that Gen Z consumers may negatively respond to IMMC messages which are intrusive or contain offensive and insulting language.

To answer the second research question, three peripheral route factors were also examined in this study. These are credibility, personalisation and media richness. The effect of each variable on consumer attitude is fully explained below.

Credibility had a significant positive influence on consumer attitude as shown by the coefficient of 0.131 with a p-value of 0.000. These results suggest that a unit increase in credibility would result in an attitude towards MIM applications by approximately 0.131 among Generation Z consumers. If advertisers increase the credibility of their MIM apps, chances are high that consumer attitudes will be enhanced. Therefore, the hypothesis that credibility has a significant positive influence on consumer attitude could not be rejected. These results also suggested that consumer attitude is enhanced if customers perceive the MIM app as coming from a credible source. These findings can be supported by several other studies (Murillo-Zegarra et al., 2020; Goh et al., 2020), that credible mobile MC messages improve the attitude of consumers. As such, researchers such as Martins et al., (2019), Maseeh et al., (2021), Lütjens et al., (2022) emphasize that credibility is a key antecedent of consumer attitude.

This study also established that interactivity had a significant positive influence on consumers’ attitude as reflected by a coefficient of 0.085 with a p-value of 0.004. A unit increase in interactivity in the instant messaging app will result in consumer attitude increasing by approximately 0.085 units. The possible implication of these results is that marketers who make their messages interactive are more likely to realize positive consumer attitudes among Generation Z consumers. Therefore, the hypothesis that interactivity has a significant positive influence on customer attitude could not be rejected. Based on this finding, it is apparent that MC practitioners can enhance the positive attitudes of Gen Z consumers towards IMMC through ensuring the following: consumers feel that MIM apps allow them to respond to promotional messages very fast; have a lot of control over what to do when they want to communicate back on MIM apps; and they can get instantaneous information when they respond to promotional messages. This is similar to the propositions by Park and Yoo, (2020) who reported that three interactivity dimensions (i.e., controllability, responsiveness, and communication) positively influence consumers’ attitude. Since MIM platforms like WhatsApp allow consumers to decide when they can be online, users feel that they control of their internet behaviour.

Media richness had a significant positive influence on consumer attitude as reflected by the coefficient of 0.077 with a p-value of 0.019. A unit increase in media richness will result in consumer attitudes towards MIM apps increasing by approximately 0.077 units. Therefore, the hypothesis that media richness has a significant positive influence on consumer attitude could not be rejected. The possible implication of these results is that if the media is rich with enough content, attitudes towards MIM apps will be enhanced among Generation Z consumers. Marketers who share rich messages with their customers are more likely to realize increased positive attitudes toward MIM applications. This finding resonates with the view put forward by Tang and Hew (2020) who argue that MIM apps offer multiple cues and language variety which helps to create common understanding between MIM users. This therefore influences affective responses towards IMMC messages. A similar opinion was expressed by Tseng and Wei (2020) who agree that media richness has a significantly positive impact on consumer behavioural responses. The implication of the findings is that, if an IMMC message is rich with enough content, attitudes towards that IMMC message will be enhanced among Generation Z consumers. Therefore, IMMC practitioners who share rich messages with their customers are more likely to realize increased positive attitudes towards IMMC messages.

5.1 Conclusions

With regard to the first research question which sought to determine the influence of central route characteristics of IMMC on the attitude of Gen Z consumers in Zimbabwe, four hypotheses were postulated relating entertainment, informativeness, personalisation and irritation and consumer attitude. The findings revealed a positive significant association between personalisation and the attitude of Gen Z consumers, whilst a negative and significant relationship was reported between irritation and the attitude of Gen Z consumers towards IMMC. It also emerged from the study that both entertainment and informativeness of IMMC had no significant association with the attitude of Gen Z consumers in Zimbabwe. Therefore, it can be concluded that, whereas personalised IMMC messages positively influence the attitude of Gen Z consumers in Zimbabwe, irritation has a negative association, while entertaining and informative IMMC messages have no significant influence on the attitude of Gen Z consumers in Zimbabwe.

As for the second research questions which aimed to establish the relationship between the peripheral route characteristics of IMMC and the attitude of Gen Z consumers in Zimbabwe, IMMC characteristics such as credibility, interactivity, and media richness were investigated. Three hypotheses were postulated and tested to achieve this objective. The findings demonstrated that all the three dimensions of peripheral route characteristics (credibility, interactivity and media richness) of IMMC have a positive and significant influence on the attitude of Gen Z consumers in Zimbabwe. These findings confirm the notion that, Gen Z consumers, who are regarded as the first generation born in the digital era, are more likely to be influenced by the peripheral route as opposed to central characteristics of IMMC messages.

5.2 Theoretical Contributions

From a theoretical perspective, the insights generated from this study add to and complement the theoretical discussion on MC in the context of mobile media. In particular, the study contributes to the emerging stream of literature on the application of new media technologies such as MIM apps in MC. More specifically, the study makes significant contributions to this body of knowledge by highlighting the critical central route and peripheral route characteristics of IMMC. In essence, the integration of established MC theories helped to strengthen the predictive power of the research model and develop a framework that explains the relationship between the attitude of Gen Z consumers and behavioural intentions regarding IMMC. Thus, this integrative approach may provide insights into the effectiveness of this novel mobile MC tool as compared to traditional avenues. In this regard, the study provides important directions on the relationship between IMMC and the attitude and behavioural intentions of Gen Z consumers in Zimbabwe and other developing economies.

5.3 Managerial Implications

The mobile technology revolution has significantly transformed people’s lives including the conduct of marketing activities. This has been spurred by the increasing rate of mobile phone penetration and overall mobile internet access and connectivity. This, in turn, has resulted in the widespread adoption and use of MIM applications. From the business viewpoint, MIM apps have transformed MC by creating a ubiquitous, pervasive, and rich channel that supports interactive and dialogic communications with consumers. For business managers, marketers and MC practitioners, this calls for the need to keep abreast with and manage the transition from traditional MC channels to mobile MC tools. These emerging MC tools have the potential to affect the attitude and behavioural intentions of the Gen Z cohort group. Not only does this cohort group require strategic and effective MC tactics, but, the future of MC as it relates to young consumers promises to be even more challenging. In light of this background, it is envisaged that the results of this study become even more important as they shed more light concerning, the key determinant factors that influence the attitude and behavioural intent of Gen Z consumers regarding IMMC.

More importantly, the findings of this study can assist MC practitioners in appraising the role of MIM apps as a distinct MC tool for influencing consumer behaviour, and realization of sustainable competitive advantage. The insights gained from the findings of this study provide business managers, marketers and MC practitioners with the relevant ammunition for the effective design, implementation and evaluation of IMMC efforts. In particular, by highlighting the central route characteristics and peripheral route characteristics of IMMC which influence the attitude of Gen Z consumers in Zimbabwe, the results of the study lay the groundwork for critical assessment and or projection of the expected outcome of any company’s IMMC effort. Thus, the benefits of the outcomes of this study extend to other consumer groups in different countries, operating in different industries or economic sectors. This may also extend to other technology-mediated MC tools outside MIM apps and their respective users and audiences.

Furthermore, given the proliferation and growing popularity of MIM apps, combined with the resulting decline and shift away from traditional MC tools, the study advises that business managers and MC practitioners learn the best practices for planning effective IMMC campaigns which trigger positive consumer behavioural responses. Accordingly, the outcomes of the study indicate the key considerations for IMMC message design in light of the expectations of Gen Z consumers. For instance, the study has important business and marketing implications since it recognizes the critical role of central route and peripheral route message characteristics in influencing the attitude of Gen Z consumers regarding IMMC. As a result, when designing IMMC messages, MC planners and designers must consider such important content characteristics as personalisation, irritation, credibility, interactivity and media richness.

5.4 Limitations and areas of Further Research

Even though this study was premised on sound theoretical and methodological foundations, certain shortcomings and limitations were taken into account. These are highlighted in the ensuing discussion. First, the participants in this study were drawn up from a population of Gen Z consumers situated in the city of Masvingo, Zimbabwe. This may compromise the representativeness of the research population and the generalizability of the research findings. Future studies may consider a survey of Gen Z consumers from all provinces of Zimbabwe to gauge the attitudinal responses regarding IMMC. Secondly, it is worth noting that the research model was formulated based on the research constructs culled from the Elaboration Likelihood Model. Several variables from other MC theories such as the Hierarchy of Effects Model could be explored to provide more insightful outcomes and depth in understanding the antecedent factors influencing consumer attitude in the context of IMMC. In particular, future studies may consider several dimensions of consumer attitude, such as, cognitive, affective and behavioural. They may also consider other message characteristics such as infotainment as well the mediating effects of emotional attachment to MIM apps, degree of message involvement, message valence among others. Thirdly, although WhatsApp is the most popular and widely used MIM app in most developing countries, future studies could explore MC in the context of other MIM apps such as Telegram in either emerging or developed economies. It is believed that this would enhance the knowledge of how these mobile social media tools are influencing the attitudes and behavioural intentions of young consumers who form the majority of today’s world population. Finally, in this study, a quantitative research approach was adopted and as such, it is suggested that future studies consider a mixed-methods approach or qualitative research approach to broaden the understanding of consumer attitudes and behavioural intentions regarding IMMC.

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Author Contributions: John Marumbwa: Conceptualization, Methodology, Writing - Original Draft. Krishna K. Govender: Validation, Writing- Reviewing and Editing, Supervision

Funding: This research received no external funding

Conflicts of Interest: The authors state that they have no conflicts of interest

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Disclaimer/Publisher’s Note: The views, statements, opinions, data and information presented in all publications belong exclusively to the respective Author/s and Contributor/s, and not to Sprint Investify, the journal, and/or the editorial team. Hence, the publisher and editors disclaim responsibility for any harm and/or injury to individuals or property arising from the ideas, methodologies, propositions, instructions, or products mentioned in this content.

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