The moderating role of age on social media marketing activities and customer brand engagement on Instagram social network

In the context of fashion brands on Instagram platform, this study aims to investigate the impact of age on the relationships between informative, interactive and trendy social media marketing (SMM) activities, customer brand engagement (CBE) and brand loyalty

The moderating role of age on social media marketing activities and customer brand engagement on Instagram social network Joe Hazzamà Abstract Purpose – In the context of fashion brands on Instagram platform, this study aims to investigate the impact of age on the relationships between informative, interactive and trendy social media marketing (SMM) activities, customer brand engagement (CBE) and brand loyalty Design/methodology/approach – A quantitative method was used to collect and analyses the data and to test the conceptual model In total, 241 usable questionnaires were collected and analyzed using structural equation modeling and multi-group moderation analysis Joe Hazzam is based at Faculty of Business and Law, The British University in Dubai, Dubai, United Arab Emirates Findings – The results of this study demonstrate that informativeness of SMM activities relates positively and significantly to CBE in all age groups However, the strength and the significance of interactive and trendy social media activities differ between age groups Research limitations/implications – This study used only two age groups of college students to answer the research questions Despite that tech-savvy millennials and generation Z are highly engaged in social media environment, the results may not be representative of the entire population and the findings may be cautiously generalized to other platform types or product categories Originality/value – By offering a new understanding of perceived SMM in different age groups on Instagram platform, this study contributes to the literature by identifying the types of social media activities that engage different age groups on social media networks Keywords Age, Instagram, Customer engagement, Brand loyalty, Social media marketing, Fast fashion brands Paper type Research paper Introduction The marketing literature suggests that customer brand engagement (CBE) is an essential driver of brand loyalty, positive word of mouth, brand usage and purchasing behaviors (Algharabat et al., 2020; Brodie et al., 2013; France et al., 2016; Hollebeek et al., 2014) Within this rich stream of research, social media marketing (SMM) activities were identified as potent enablers of CBE and brand loyalty (De Vries and Carlson, 2014; Ismail, 2017; Nyadzayo et al., 2020; Ul Islam and Rahman, 2017) Earlier studies have emphasized the role of interactive, informative and trendy SMM activities on CBE and loyalty (Godey et al., 2016; Kim and Ko, 2012; Liu et al., 2019; Yadav and Rahman, 2017) However, these previous studies used specific online platforms such as Facebook or Twitter, and the results might not be generalized to other social media networks such as Instagram (Ul Islam and Rahman, 2017) Besides, the literature did not investigate the moderating role of age on the relationship between SMM activities and CBE Nevertheless, in social media context, the DOI 10.1108/YC-03-2021-1296 Received 17 March 2021 Revised May 2021 26 June 2021 16 August 2021 Accepted 16 August 2021 © Emerald Publishing Limited, ISSN 1747-3616 j YOUNG CONSUMERS j CBE and the use of different social media platforms might differ significantly within diverse age groups (Boardman and McCormick, 2018; Duffett, 2017; Dwivedi, 2015; Nelson et al., 2019) In recent years, many firms adjusted to the rise of consumer power by leveraging the interactive capability of social media networks to enhance customer’s value, develop relationships with communities and communicate efficiently with their customers to achieve brand objectives (Hennig-Thurau et al., 2013; Felix et al., 2017) Besides, social media platforms emphasize customer–brand interactions and facilitate involvement through a farreaching influence on the cognitive, emotional and activation processes of engagement (Hollebeek et al., 2014) The engagement of these customers in a virtual online community support brand connection, value and loyalty (Brodie et al., 2013; France et al., 2015) For example, the Facebook page fans of fashion retailer Zara spend more than non-fans by 138% (Hotspex, 2013) Thus, the identification of social media activities that are relevant and interesting to the brand community members improves their participation, trust, commitment and engagement (Vohra and Bhardwaj, 2019) Previous studies identified different types of SMM activities as essential drivers of CBE and subsequently brand loyalty and equity (Yazdanparast et al., 2016) For example, the accessibility and the interactivity elements on social media platforms between the brands and their millennial customers fulfill their emotional and cognitive needs (Athwal et al., 2019) On the other hand, entertainment, interactive and trendiness of SMM activities are important enablers of consumers’ brand engagement, preference and loyalty toward luxury fashion brands (Godey et al., 2016; Kim and Ko, 2012) These studies advanced the knowledge toward a better understanding of the relationships between SMM activities, CBE and loyalty However, the exclusivity and the premium prices of luxury brands differ from the fast fashion brands which are more affordable and produced in higher volumes (Ajitha and Sivakumar, 2019) Besides, previous studies used Facebook and Twitter as the primary social networks for analysis which might differ from other context and interface designs such as Instagram platform (Ul Islam and Rahman, 2017) Moreover, previous studies did not investigate how different age groups impact the relationship between SMM activities and CBE Studies that investigate the impact of perceived social media activities on CBE focused mainly on millennials using Twitter and Facebook social media platforms (Kim and Ko, 2012; Samala and Katkam, 2019; Ul Islam and Rahman, 2017) While these studies advanced the knowledge on social media activities and CBE, their findings inform specific age group and did not consider young consumers whom digital behaviors differ significantly from their millennials counterpart (Bolton et al., 2013; Nguyen et al., 2019) Furthermore, Instagram has unique characteristics, and consumers might perceive the platform’s social media activities differently in comparison to other types such as Facebook and Twitter (Chen, 2017) This study attempts to address these research gaps by investigating how different types of fast fashion SMM activities are effective in engaging customers from different age groups on Instagram social networks Also, this study focus on the Middle East region, and specifically the United Arab Emirates which might provide new knowledge on the attitude of consumers toward social media in developing countries Thus, the research aims to answer the primary question: “Does age moderate the relationship between SMM activities and customer brand engagement towards fast fashion brands?” This research question is grounded in the stimulus-organism-response paradigm (Eroglu et al., 2001; Jacoby, 2002) Accordingly, we propose that different types of SMM activities stimulate the consumer as an organism to engage with the brand leading to a response such as brand loyalty However, the organism is the storehouse of prior experiences and attitudes which is influenced by the individual age (Jacoby, 2002) Thus, the impact of SMM stimulus on the organism emotive and cognitive systems might differ between different age groups such as Millennials and generation Z (Duffett, 2017) j YOUNG CONSUMERS j First, the objective of the study is to measure the relationships between SMM, CBE and brand loyalty on Instagram social network of fast fashion brands Second, the research investigates the age groups differentiated engagement behaviors in response to different types of SMM activities The following sections highlight the study background, the research conceptual framework and hypotheses development Then, we present the method used and the findings Finally, we discuss the theoretical and managerial implications, limitations of the study and the recommendations for future research Research background In recent years, the performance of fast fashion brands, such as Zara and H&M, explained impressive global performance (Kim et al., 2013) These brands business models are defined as agile, highly responsive to latest trends and changes in consumer lifestyle, and their prices are reasonable (Su and Chang, 2018) Fast fashion brands represent a quick shift to the new emerging trends of consumer’s demands These brands highlight efficient production processes and maintain lower prices (Gabrielli et al., 2013) Besides, the complementary effect of enhanced design and quick response production matched the supply to demand and impacted the consumer purchasing behaviors (Cachon and Swinney, 2011) These customers explain the fast fashion environment as creative and associated with fun, enjoyment and pleasure (Miller, 2013) The fast fashion brands approach of offering a variety of alternatives and affordable prices attract young and more mature consumers (Bhardwaj and Fairhurst, 2010) Thus, the continuous engagement with customers is an essential success factor of fast fashion brands which focus on customer demands within a time-constrained environment (Payne, 2016) Previous studies posit that social media platforms facilitate higher level of customer–brand interactions, and the communication is faster and happens in real-time with a higher number of customers (Hamilton et al., 2016; Rathore et al., 2016) These interactions enhance CBE and contribute positively to brand loyalty and value (Dwivedi, 2015; France et al., 2016; Hollebeek et al., 2014) Prior research investigated the influence of different types of SMM activities on CBE using either Facebook or Twitter of luxury fashion brands (Kim and Ko, 2012; Nyadzayo et al., 2020; Ul Islam and Rahman, 2017) However, empirical findings on the impact of age on the relationships between SMM and CBE remain a gap in the literature, especially for fast fashion brands on Instagram platforms Recent statistics have highlighted that more than 60% of Instagram users are aged between 18 and 34 years old, and fashion is one of top user interests suggesting higher ads spend by fast fashion brands on this platform (Facebook, 2021; Statista, 2021) Thus, as shown in the research conceptual model (Figure 1), the purpose of this research is to understand the impact of age on the relationship between SMM activities and CBE, and to test the relationship between CBE and brand loyalty of fast fashion brands on Instagram social media platform Theoretical background Kaplan and Haenlein (2010, p 61) define social media as: “a group of Internet-based applications that build on the ideological and technological foundations of Web 2.0, and that allow the creation and exchange of User Generated Content.” The effective use of SMM facilitates co-creation of value and enhances customers’ interactions and relationships (Felix et al., 2017) However, perception and receptivity of SMM exert significant roles in changing consumer behaviors and engagement with the brands (Hollebeek et al., 2014; Kumar et al., 2016; Ul Islam and Rahman, 2017) Social media environments differ from traditional media and represents a new kind of organism that is stimulated by marketing inputs to achieve marketing outcomes (Peters et al., 2013) This conceptualization relates to the stimulus-organism-response framework that posits an arousal influence of stimulus on the organism cognitive and affective psychological state to produce an outcome (Eroglu et al., 2001) Stimulus consist of the external things that encounter the customers such as j YOUNG CONSUMERS j brands, logo, communications and other factors Organism refers to the internal process and activation of the stimulus Response underlines nonverbal, verbal and behavioral responses (Jacoby, 2002) In this study, marketing inputs explain the characteristics of SMM stimulus such as informative, interactive or trendy activities (Kim and Ko, 2012; Yadav and Rahman, 2017) These communication messages stimulate the organism psychological state represented by customer engagement with the brand to achieve a response such as loyalty (Algharabat et al., 2020; Hollebeek et al., 2014) Besides, these psychological processes interact with other customer physical systems such as demographics including age among other variables (Jacoby, 2002) Literature review and hypotheses development 4.1 Social media marketing and customer brand engagement Social media platforms become an indispensable part of young consumers’ daily life for communications and interactions with their friends or preferred brands (Duffett, 2017) These online social networks change the traditional way of communication, information acquisition, customer relationship and value creation (Kumar et al., 2016; Stephen, 2016; Trainor, 2012) According to Hanna et al (2011), social media interactive communication and tools revolutionize the marketing ecosystem and provide brands’ community pages the opportunity to interact and engage with their customers through exchange of information and knowledge (Samala and Katkam, 2019) Accordingly, SMM represents the stimulus that arouse customers’ internal state and facilitates involvement through a far-reaching influence on the cognitive, emotional and activation processes of engagement (Brodie et al., 2013; Ul Islam and Rahman, 2017) Previous studies outline that social media communications influence: consumers’ level of processing thought in a specific interaction with the brand referring to cognitive engagement, consumers’ degree of positive affect toward the brand explaining emotional engagement and consumers’ level of energy, effort and time interacting with the brand highlighting the activation process (Hollebeek et al., 2014; Samala and Katkam, 2019) Social media tools accommodate different types of brand stimulus and drive engagement through multiple creative strategies (Ashley and Tuten, 2014) SMM activities on Instagram might be interactive, informative and trendy (Godey et al., 2016; Yadav and Rahman, 2017) For instance, SMM interactive activities refer to the extent customers share content, views and exchange information with the brand messages and other customers (Ul Islam and Rahman, 2017; Yadav and Rahman, 2017) These interactive messages explain that the brand is listening and responding promptly to customers (Bozkurt et al., 2020) According to Loureiro et al (2019), the interactivity of fast fashion brands on Instagram empowers consumers to engage with the brands and participate in decision-making process Therefore, interactive brand stimulus activates two-way communication and enhances customers’ engagement for value creation (France et al., 2016; Merrilees, 2016): H1 Interactivity of SMM activities is positively related to CBE SMM activities that deliver accurate, useful and comprehensive information might be perceived as informative (Yadav and Rahman, 2017) The information in the message stimulates consumers’ exposure and attention predicting engagement with the brands (Shareef et al., 2019) On the other hand, the visual information presented with audio-visual or video format generates higher response on Instagram (Kusumasondjaja, 2019) For example, the information, news and promotion posted on Zara Instagram account trigger the users to engage with the brand (Nedra et al., 2019) These findings were confirmed by Yazdanparast et al (2016) suggesting that SMM informative activities influence CBE by stimulating a two-way conversation and reinforcing brand associations Therefore, the informative brand messages that are relevant and valuable drive customer engagement (Ul Islam and Rahman, 2017) j YOUNG CONSUMERS j H2 Informativeness of SMM activities is positively related to CBE Trendiness refers to the perceived SMM activities that provide trendy content (Kim and Ko, 2012; Yadav and Rahman, 2017) This trendy content informs consumers about latest fashion ideas and serves as a stimulus to engage with the brand and make better purchase decisions (Godey et al., 2016) Trendy activities keep consumers updated about social environments and inspire them with new and creative ideas that stimulate their engagement with the brand (Godey et al., 2016) These trendy SMM activities stimulate customers seeking a sense of uniqueness and style which enhance their level of engagement with the brand (Ajitha and Sivakumar, 2019) H3 Trendiness of SMM activities is positively related to CBE 4.2 Customer brand engagement and brand loyalty The customer levels of energy, effort and time spent during a specific direct online interaction with the brand refer to CBE, and this engagement might add value to the brand beyond economic transactions (Brodie et al., 2011; Hollebeek et al., 2014; Vivek et al., 2012) The development of a positive relationship with the brand enhances customer engagement and increases the intention of brand usage, positive word of mouth and customers’ constructive feedback (Labrecque, 2014) Customers that are more engaged with brands are more likely to interact, create value and tend to be brand loyal (France et al., 2015; Hollebeek, 2011; Van Doorn et al., 2010) Previous studies established the relationship between customer engagement and loyalty (Pansari and Kumar, 2017) For instance, Algharabat et al (2020) found a positive relationship between CBE and brand loyalty using the Facebook fan page of mobile phone service providers On the other hand, Ul Islam and Rahman, (2017) tested this relationship in online brand communities and confirmed that SMM stimulates higher level of CBE which in turn generates a response such as brand loyalty (De Vries and Carlson, 2014; Jacoby, 2002) Thus, the following hypothesis is proposed: H4 CBE is positively related to brand loyalty 4.3 Moderation hypothesis Age is an essential demographic factor that affects the consumption and purchase decisions of fashion brands (Ajitha and Sivakumar, 2019) For instance, brand, style, price and social identity influence the millennial attitude and purchase decisions of fashion apparel (Valaei and Nikhashemi, 2017) Besides, the customer’s motivation, engagement and shopping behaviors differ within age groups (Sharma et al., 2019) For example, the Mcommerce is the preferred shopping channel for younger generations owing to the convenience, selection and exploration However, the enjoyment and the convenience of the physical stores remained popular for the 60ỵ years old (Boardman and McCormick, 2018) These differences in customer engagement and shopping behaviors between age groups were augmented by the emergence of social media (Duffett, 2017) For instance, the millennials spent their whole lives in a digital context and relies mostly on technology to engage with their preferred brands (Nadeem et al., 2015) The millennials and the younger generation Z are the most engaged consumers on social media platforms and specifically  et al., 2018; with fashion brands on Instagram social network (Bolton et al., 2013; Casalo Nyadzayo et al., 2020) Thus, age represents a strong determinant of social media engagement and usage (Pittman and Reich, 2016) According to Nelson et al (2019), the millennials use Instagram to seek fashion information and interact with their preferred brands On the other hand, Priporas et al (2019) argue that the generation Z are more socially connected than previous generations, and their usage of social media is extensive which might lead to different engagement behaviors as compared to other generations These differences in social media usage between age groups might provide insights on j YOUNG CONSUMERS j Figure Research conceptual framework and hypotheses how to better connect and communicate with customers (Yazdanparast et al., 2016) Therefore, the differences in experiences, attitudes and perceptions between Millennials and generation Z might influence the relationship between SMM different types of stimulus and engagement (Duffett, 2017; Jacoby, 2002) This study aims to understand the customer engagement with SMM activities of fast fashion brands by including both millennials and generation Z Thus, the following hypotheses are proposed (Figure 1): H5a Age moderates the relationship between the interactivity of SMM activities and CBE H5b Age moderates the relationship between the informativeness of SMM activities and CBE H5c Age moderates the relationship between the trendiness of SMM activities and CBE Research methodology 5.1 Sampling and data collection The study used an online survey to collect data from undergraduate and postgraduate students at a university located in United Arab Emirates The target respondents are students that represent the tech-savvy millennials and the extensively engaged generation Z in social media environment (Nadeem et al., 2015; Priporas et al., 2019) Besides, these two generations are major consumers of fast fashion brands, and they engage notably in online brand communities (Bolton et al., 2013; Nelson et al., 2019) The survey started with a filtering question technique to validate that the respondents follow a fast fashion brand on Instagram The students answered the question: “Do you follow at least one of the fast fashion brands listed below on Instagram?” The list of fast fashion brands was developed by reviewing previous literature (Ajitha and Sivakumar, 2019; Miller, 2013) The fast fashion brands identified are Zara, H&M, Topshop, Gap, Diesel, Benetton, Armani exchange, Superdry, Forever 21 and Jack & Jones Then, only those participants that follow a fast fashion brand on Instagram are able to complete the questionnaire Moreover, the participants were asked to think about the fast fashion brands that they follow on Instagram while answering the survey The survey was sent to a target of 650 students A total of 241 participants successfully completed the questionnaire with 102 (42.3%) of the respondents aged between 18 and 24 and represented the generation Z Besides, 139 (57.7%) of the participants were aged between 25 and 34 and represented the generation Y In terms of gender, the female respondents were 145 (60.2%) and the male participants were 96 (39.8%) The majority of the respondents (173, 71.8%) were using social media for more than h per day Table provides the characteristics of the respondents j YOUNG CONSUMERS j 5.2 Measurement development The literature review supported the development of the questionnaire items and scales for data collection The study aims to measure the moderating role of age on the relationship between SMM activities and CBE and to test the relationship between CBE and brand loyalty A seven-point Likert scale was used to measure all the study variables The SMM activities items and scale were adapted from Kim and Ko (2012) and Yadav and Rahman (2017) and consist of three items that measure the interactivity, three items that measure the informativeness and three items that measure the trendiness of SMM activities The CBE items and scale were adapted from Hollebeek et al (2014) and consist of three items that measure the cognitive processing, four items that measure the affective and three items that measure the activation dimension of CBE The brand loyalty items and scale were adapted from Algharabat et al (2020) and consist of three items Table shows the results of the measurement items and constructs’ psychometric properties Data analysis and results 6.1 Preliminary analysis and measurement model The data was collected using the same questionnaire during the same period Therefore, we tested for the existence of common method bias using Harman’s single factor test which could inflate or deflate the estimates between the latent constructs (Bagozzi and Youjae, 1988) The common method bias exists if only one factor explains 50% of the variance among the measures during the exploratory factor analysis with unrotated factor solutions (Podsakoff et al., 2012) In our study, the highest variance explained by a single factor was 45.52% As this is less than the 50% cut-off criteria, it confirms the absence of the common method bias Moreover, results of Kaiser-Meyer-Olkin analysis (0.90) confirm the data adequacy as it exceeds the 0.60 requirement (Kaiser, 1970) Also, we tested for nonresponse bias by comparing early and late respondents’ differences across means of the main study constructs following the recommendation of Armstrong and Overton (1977) The Levene’s test for equality of variance indicates that no significant differences exist between early and late respondents for interactive SMM (F = 0.27, p > 0.05), informative SMM (F = 1.72, p > 0.05), trendy SMM (F = 0.36, p > 0.05), CBE (F = 0.33, p > 0.05) and brand loyalty (F = 3.84, p > 0.05) The results of the initial exploratory factor analysis (EFA) explained seven components, and all the items loaded above the threshold of 0.50 (Hair et al., 2014) The confirmatory factor analysis (CFA) follows the EFA and indicates how well the measured variables represent the research constructs (Anderson and Gerbing, 1988; Gallagher et al., 2008) The CFA results indicate that the measurement model showed adequate goodness-of-fit indices ( x = 288.639, x 2/df = 1.169, p < 0.001, normed fit index [NFI] = 0.950, comparative fit index [CFI] = 0.992, Tucker–Lewis index [TLI] = 0.991 and root mean square error of Table Characteristics of respondents Variable Age 18–24 25–34 Gender Female Male Social media use per day Less than h 3–4 h More than h Frequency (n) (%) 102 139 42.3 57.7 145 96 60.2 39.8 68 79 94 28.2 32.8 39.0 j YOUNG CONSUMERS j Table Measurement items, standardized factor loadings and Cronbach’s alpha coefficients Constructs SFLs Interactivity My fast fashion brand enables content sharing with others on Instagram My fast fashion brand interacts regularly with its followers and fans on Instagram My Fast fashion brand facilitates two way interaction with others on Instagram 0.873 0.873 0.841 Informativeness My fast fashion brand offers accurate information on Instagram My fast fashion brand offers useful information on Instagram The information provided by my fast fashion brand on Instagram is comprehensive 0.856 0.914 0.818 Trendiness Contents visible on my fast fashion brand Instagram page is the latest trend Using my fast fashion brand Instagram page is really trendy Anything trendy is available on my fast fashion brand Instagram page 0.867 0.908 0.851 CBE cognitive processing Using my fast fashion brand’s Instagram page get me to think about it I think about my fast fashion brand’s Instagram page a lot when I’m using it Using my fast fashion brand’s Instagram page stimulate my interest to learn more about it 0.829 0.873 0.803 CBE affection I feel very positive when I use my fast fashion brand’s Instagram page Using my fast fashion brand’s Instagram page makes me happy I feel good when I use my fast fashion brand’s Instagram page I’m proud to use my fast fashion brand’s Instagram page 0.895 0.920 0.943 0.869 CBE activation I spend a lot of time using my fast fashion brand’s Instagram page compared to other brands Whenever I’m using fast fashion brands on Instagram, I usually use my fast fashion brand’s Instagram page I use my fast fashion brand’s Instagram page a lot 0.876 0.923 0.909 Brand loyalty I consider myself to be loyal to my fast fashion brand’s Instagram page My fast fashion brand’s Instagram page would be my first choice I intend to remain a customer to my fast fashion brand on its Instagram page 0.951 0.960 0.939 a 0.896 0.896 0.906 0.872 0.948 0.929 0.965 Notes: a: Cronbach’s alpha coefficient; SFLs: standardized factor loadings approximation [RMSE]) = 0.027) Table shows that the values of the standardized factors’ loading estimates were higher than 0.7 with statistical significance and without any loadings above or below À1 Besides, the Cronbach’s alpha showed values higher than the recommended 0.7 (Churchill, 1979) 6.2 Convergent and discriminant validity Convergent validity refers to the common shared variance between the indicators of the same construct, and discriminant validity evaluates the construct’s divergence and how it differs from others and not measuring the same thing (Gallagher et al., 2008) To assess convergent validity, the composite reliability (CR) and the average variance extracted (AVE) were calculated According to research standards, the CR should be greater than 0.70 and the AVE should be greater than 0.5 (MacKenzie et al., 2011; Fornell and Larcker, 1981) Table shows that the values of the AVE were greater than 0.5 and CR above 0.7 indicate convergent validity (Anderson and Gerbing, 1988) Discriminant validity is achieved if the squared root of the AVE of any two constructs is higher than their correlation estimate Table shows that the square root AVE of the seven study constructs in the diagonal is greater than their correlations below the diagonal line (Fornell and Larcker, 1981) Thus, the research constructs achieve discriminant validity j YOUNG CONSUMERS j 6.3 Structural model results The second stage of structure equation modeling is the path analysis and hypothesis testing The AMOS software was used to investigate the relationships between interactivity, informativeness, trendiness, CBE and brand loyalty The CBE was taken as second-order construct with three factors at the first order in the structural model Besides, the first structural model did not count for the moderation effects of age groups This procedure is followed by a multi-group path analysis, which is suitable for testing the study hypotheses by comparing specific path parameters across the two age groups (Stephenson et al., 2006) The structural model highlighted acceptable fit indices ( x = 4.749, x 2/df = 1.583, p < 0.001, NFI = 0.992, CFI = 0.997, TLI = 0.972 and RMSEA = 0.049) Table indicates that SMM interactivity relates positively and significantly to CBE ( b = 0.146, t = 2.205, p = 0.027), thus supporting H1 Besides, H2 was supported as the relationship between SMM informativeness and CBE is positive and significant ( b = 0.239, t = 3.335, p < 0.001) In support of H3, SMM trendiness explained a positive and significant relationship with CBE ( b = 0.314, t = 4.814, p < 0.001) Finally, H4 was supported as CBE is related positively and significantly to brand loyalty ( b = 0.430, t = 6.682, p < 0.001) 6.4 Multi-group moderation analysis Prior to multi-group moderation analysis, we test for invariance by specifying a full constrained model set to be equal across all age groups Then, the model was compared to a freely estimated parameters model The groups are different at the model level if the x difference test is significant (Byrne, 2010) The results show that D x 2(12) = 19.298 (p = 0.082), and the age groups are different at the model level Thus, the study proceeds to multi-group moderation path analysis The model showed acceptable fit indices ( x = 20.364, x 2/df = 2.036, p < 0.001, NFI = 0.968, CFI = 0.982, TLI = 0.899 and RMSEA = 0.066) Further, we performed multi-group moderation tests using the critical ratio for differences in AMOS to compare if there are significant path differences between different types of SMM activities and CBE in different age groups Table shows that the relationship between SMM interactivity and CBE is not moderated by age groups (z-score = 0.016, Table Convergent and discriminant validity Constructs Mean SD CR CBE cognitive processing CBE affection CBE activation Brand loyalty Interactivity Informativeness Trendiness 4.993 4.905 4.542 4.657 5.618 5.069 5.197 1.239 1.230 1.288 1.659 0.995 0.912 1.086 0.873 0.948 0.929 0.965 0.896 0.897 0.907 0.835 0.516 0.461 0.274 0.324 0.462 0.416 0.906 0.482 0.343 0.394 0.417 0.417 0.902 0.479 0.346 0.362 0.436 0.950 0.347 0.172 0.314 0.861 0.598 0.472 0.863 0.582 0.875 Notes: CR: construct reliability, SD: standard deviations, Square root AVE: average variance extracted is the diagonal number in italic Table Results of the structural equation modeling No Hypothetical relationships H1 Interactivity ! CBE H2 Informativeness ! CBE H3 Trendiness ! CBE H4 CBE ! brand loyalty Path coefficient t-value Result 0.146à 0.239ÃÃà 0.314ÃÃà 0.430ÃÃà 2.205 3.335 4.814 6.682 Supported Supported Supported Supported Notes: à p < 0.05 level; Ãà p < 0.01; ÃÃà p < 0.001 j YOUNG CONSUMERS j p > 0.05) despite that this relationship was positive and significant for generation Z ( b = 0.142, p = 0.073) with a confidence level of 90% as opposed to generation Y ( b = 0.140, p = 0.168) Thus, hypothesis H5a was not supported Besides, the relationship between SMM informativeness and CBE was positive and significant for the two generations However, age did not moderate this relationship (z-score = 0.428, p > 0.05) and H5b was rejected On the other hand, the relationship between SMM trendiness and CBE was significantly moderated by age groups (z-score = 3.426, p < 0.05) This relationship is significant and positive for the generation Z ( b = 0.537, p < 0.001) and not significant for generation Y ( b = 0.113, p = 0.113) supporting H5c In a post hoc analysis that follows the same procedure of x invariance test and multi-group path analysis for female and male groups, the result shows that gender did not moderate the relationships between the different types of SMM activities and CBE Discussion This research attempts to understand the impact of SMM activities of fast fashion brands on CBE in different age groups on Instagram The study shows that generation Y and generation Z engage similarly with interactive and informative SMM activities Millennials are interactive and informative social being seeking and exchanging information with their preferred brands (Samala and Katkam, 2019) However, the trendiness of SMM is affecting positively and significantly the engagement of generation Z specifically The result is consistent with the premises of the stimulus-organism-response framework explaining that SMM activities stimulate CBE which in turn has subsequent effect on brand loyalty (Ul Islam and Rahman, 2017) On the other hand, this study contributes to the engagement literature by proposing that social media stimulus is not consistent across generation Y and Z members The impact of these activities differs according to the organism age highlighting the influence of customer’s physical system and their engagement with brand’s social media stimulus (Jacoby, 2002) The moderation analysis indicates that younger consumers relate more to new ideas and latest information that inspire them to engage and stay loyal to the brand This finding confirms that these consumers engage and build relationships with brands differently from their millennials counterpart (Duffett, 2017) This result addresses a gap in the literature on how different age groups perceived SMM activities of fast fashion brands on Instagram, and how these types of online communications influence their CBE and loyalty Previous research found that brand communities on Facebook and Twitter positively influence customer–brand relationship and engagement (Gensler et al., 2013; Godey et al., 2016) Also, SMM activities enhance communication and improve CBE and loyalty (De Vries and Carlson, 2014; Sashi, 2012) This research confirmed and extended previous findings to Instagram social network and found that interactivity, informativeness and trendiness of SMM activities relate positively and significantly to CBE that in turn, can contribute to brand loyalty Thus, this result is in line with previous studies that found a positive and significant relationship between SMM activities and CBE (Ul Islam and Rahman, 2017; Yadav and Rahman, 2017) and more specifically on social media platforms of luxury fashion brands (Kim and Ko, 2012; Nyadzayo et al., 2020) Table Moderation analysis – generation Y vs generation Z No Hypotheses H5a Interactivity ! CBE H5b Informativeness ! CBE H5c Trendiness ! CBE Path coefficients ( b ) – generation Y Path coefficients ( b ) – generation Z z-score Result 0.140 0.312à 0.138 0.142 0.246Ãà 0.537ÃÃà 0.016 0.428 3.426ÃÃà Not supported Not supported Supported Notes: à p < 0.05 level; Ãà p < 0.01; ÃÃà p < 0.001 j YOUNG CONSUMERS j Demographic factors were used to segment the market, and age impacts the consumers’ taste, preferences and their involvement with the brands (Ajitha and Sivakumar, 2019) This study extended the role of age to the online brand communities and found that the perception of SMM activities impacts the CBE differently in younger age groups such as generation Z The interactivity and the informativeness of SMM activities remain major drivers of CBE in all age groups Brands that share relevant information ensure seamless experience among young consumers searching online prior to their engagement in the purchase process (Sharma et al., 2019) However, the trendiness of these online brand communications is essential to engage the generation Z and not the generation Y with fast fashion brands on Instagram platform 7.1 Theoretical implications The findings of the study indicate that CBE differs in different age groups While generations Y and Z engaged equally with informative and interactive SMM activities of fast fashion brands on Instagram, the results highlight that trendiness of these activities engages only generation Z This result supports the application of stimulus-organism-response framework to understand the influence of SMM inputs on consumer brand engagement and response processes (Eroglu et al., 2001; Jacoby, 2002) SMM stimuli are effective drivers of engagement which in turn influenced the response toward these activities such as brand loyalty Further, the finding highlights that customer physical system such as age interacts with social media stimulus and CBE processes (Jacoby, 2002) This research advances the literature on SMM and CBE by identifying the role of age as a moderator of this relationship Even though previous studies found a positive relationship between SMM activities and CBE of luxury fashion brands on Facebook and Twitter social media networks (Liu et al., 2019; Nyadzayo et al., 2020; Ul Islam and Rahman, 2017), these studies did not consider whether this relationship varies within age groups This study addresses this gap by investigating the moderation role of age on the relationships between different types of SMM activities and CBE Further, this study confirmed the importance of the CBE construct as a facilitator of fast fashion brand loyalty on Instagram Algharabat et al (2020) found that CBE relates positively to brand loyalty of Facebook telecommunication company pages Therefore, this study answered the call of previous research and validate this relationship in the context of fast fashion brands on Instagram (Hollebeek et al., 2014) Young consumer are frequent users of Instagram and their interactions with brands on social media platforms influence their consumption and purchasing habits (Samala and Katkam, 2019) This empirical study extended previous research of SMM activities on Facebook and Twitter platforms to Instagram social media networks While informative and interactive SMM activities are major drivers of CBE on Facebook and Twitter (Kim and Ko, 2012; Ul Islam and Rahman, 2017), the findings of the path analysis indicate that trendiness on Instagram platform is required to engage younger generation seeking new ideas and updated information about their preferred brands and social environments 7.2 Practical implications The study offers marketing managers several recommendations on how to craft their SMM activities to engage their customers and engender brand loyalty on Instagram The results indicate that marketers need age based strategies to stimulate CBE and develop loyalty The influence of SMM activities on CBE depends on their physical system explaining different characteristics across age groups Customers might reciprocate favorably toward the brands depending on their perception of their SMM activities (Bozkurt et al., 2020) First, the findings suggest that managers might utilize interactive, informative and trendy social media strategies to drive engagement and build relationship with their customers However, the types of brand j YOUNG CONSUMERS j social media activities should be different depending on customers’ age and types of platforms used For instance, marketing managers might use the interactivity and informativeness of Facebook and Twitter to fulfill several communication objectives and engage their millennials customers In return, customers seek information and provide feedback and suggestions to improve the brand (Samala and Katkam, 2019) On the other hand, these managers might use Instagram social network to interact with younger generation and deploy the platform to engage generation Z using trendy activities For example, the trendiness of SMM activities on Instagram might facilitate the engagement of fast fashion customers that seek a sense of uniqueness and style (Ajitha and Sivakumar, 2019) Second, marketing managers might use different types of platforms to support the launching of sale promotions, new products and events since customers are equally engage with informative SMM activities on Facebook, Twitter and Instagram social media networks For example, young consumers are more receptive toward eco-friendly fashion brands, and social media informative activities that educate consumers about reuse and recycling evoke higher level of engagement within this age group (Joshi and Srivastava, 2019) Finally, the result confirmed the importance of CBE construct as a key driver of brand loyalty (Algharabat et al., 2020; Ul Islam and Rahman, 2017) Thus, marketing managers are required to enhance their customer’s brand engagement with tailored social media activities since these customers are willing to stay loyal to the brand Instagram page, which will remain their first choice for information search and interaction with fast fashion brands Young consumers appreciate brands that value their investment in time and effort and provide updated information through their social media platform pages (Samala and Katkam, 2019) 7.3 Research limitations and future research This research presents several limitations and recommendations for future studies First, the research was conducted only for fast fashion brands using Instagram social networks Thus, findings of this study should be cautiously interpreted, and future research might include other types of brands (e.g sports and luxury) and social media networks (e.g Facebook and Twitter) to enhance the generalization of the results Besides, the study was conducted in United Arab Emirates including a small sample size representing generation Z Future studies might consider other countries focusing on younger generation including bigger sample size to validate the findings and the results of hypotheses testing Second, the conceptualization of the CBE was based on the work of Hollebeek et al (2014) Future studies might consider the brand engagement in self-concept which incorporates a social dimension and includes customer’s active participation, involvement, trust and satisfaction (Sprott et al., 2009; Vohra and Bhardwaj, 2019) Third, the study investigates the impact of SMM activities as antecedents and brand loyalty as outcome of CBE Thus, future studies might consider other drivers of CBE (e.g consumer involvement and rewards) and outcomes (e.g positive WOM and purchase intention) Besides, other factors such as cultural values, country of origin, brand quality perceptions and economic factors might differently influence CBE Finally, the nature of cross-sectional survey did not allow the determination of cause–effect links Thus, future research might adopt different designs, such as longitudinal studies, big data analytics and natural language processing (Liu et al., 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perception of social media marketing activities in e-commerce industry: scale development & validation”, Telematics and Informatics, Vol 34 No 7, pp 1294-1307 Yazdanparast, A., Joseph, M and Muniz, F (2016), “Consumer based brand equity in the 21st century: an examination of the role of social media marketing”, Young Consumers, Vol 17 No 3, pp 243-255 About the author Joe Hazzam is the Head of Marketing, Communications and External Relations, and Lecturer in Marketing at The British University in Dubai, United Arab Emirates He also delivers workshops and training on social media and digital marketing strategies He received his PhD from the British University in Dubai Joe has published in journals such as Journal of Strategic Marketing, The International Journal of Management Education, International Journal of Educational Management and Journal of Marketing Theory and Practice His research interests include digital marketing capabilities, social media and online customer brand engagement Joe Hazzam can be contacted at: joe.hazzam@buid.ac.ae For instructions on how to order reprints of this article, please visit our website: www.emeraldgrouppublishing.com/licensing/reprints.htm Or contact us for further details: permissions@emeraldinsight.com j YOUNG CONSUMERS j ... investigating the moderation role of age on the relationships between different types of SMM activities and CBE Further, this study confirmed the importance of the CBE construct as a facilitator of fast... development The literature review supported the development of the questionnaire items and scales for data collection The study aims to measure the moderating role of age on the relationship between... However, the trendiness of these online brand communications is essential to engage the generation Z and not the generation Y with fast fashion brands on Instagram platform 7.1 Theoretical implications