Keywords

Customer Brand Engagement, Social Media, Generation Y & Generation Z, Effective Strategies, SEM, Smart PLS

Introduction

In the current era where businesses tend to be highly dynamic and evolving all the time, and everyone is surrounded with the always on and constantly connected digital technologies; now practitioners in the business field have understood that to gain long term and sustainable competitive advantage; businesses need to retain, develop and sustain its customer base (Doorn et al., 2010), which is required not only on financial basis, but on nonfinancial basis too. One of these non-monetary assets to create competitive advantage include Customer Engagement (CE).

Customer Engagement (CE) can be defined as, “a psychological state that occurs by virtue of interactive customer experiences with a focal object (like a brand, or firm, etc.) in a service relationship” (Brodie, Hollebeek, Juric & Ilic, 2011). Customer engagement has emerged as a vital strategy to ensure a firm’s superior performance enabled through increased growth in sales, profitability, and competitive advantage’s superiority (Hollebeek, Srivastava & Chen, 2019).

The Customer Engagement’s concept has been one of the top priority areas of research of Marketing Science Institute (MSI) since year 2010 and till current year i.e., 2020, which reflects its increased significance. MSI first focused on the definition and scope clarification of the concept; whereas now in latest priority streams i.e., of year 2018-2020, it has added Customer Engagement’s concepts’ further explanation, with respect to marketing strategies’ perspectives, i.e., which strategies drive deep and lasting engagement with firms, more effectively (Marketing Science Institute, 2010, 2018). So, this study has focused mainly on this stream and tried to answer the call to contribute to fill that stated gap in Customer Engagement’s literature, by MSI.

This research work has taken CE’s further extension in relation to brands i.e., Customer Brand Engagement (CBE), i.e., concept of customer engagement from engagement with brand perspective. Customer Brand Engagement is the process of customer’s unpaid efforts for a firm’s marketing by contributing his resources (Pansari & Kumar, 2018). CBE defines engagement through a consumer's behavioral, cognitive and emotional related activities around specific consumer/brand interactions (Brodie, Ilic, Juric & Hollebeek, 2013).

According to a report published by Gallup, visiting and spending ratios are higher for engaged consumers than of disengaged consumers (Sorenson & Adkins, 2014).

Customer Brand Engagement (CBE) strategy is not a pre-defined or a standardized strategy. But any kind of activity, program or offering, initiated by the firm with the goal of connecting or engaging with their current as well as potential customers can be termed as customer engagement strategies (Vivek, Beatty & Hazod, 2018).

Though much attention this customer engagement has taken, but still a good recipe to develop effective customer engagement strategies or programs, is not very clear yet and need to be explored in more explicit way (Vivek et al., 2018). This research work has also addressed this gap and tried to provide the right mix of ingredients for an effective customer engagement recipe mix.

As central focus of marketing has always been on the management of consumers through strategies, which has transited from transaction to relationship marketing, and now its again evolving and shifting from relationship marketing to customer engagement (Pansari & Kumar, 2018).

There are many types of strategic contents used as a base for strategy development, which include personalization level, experiential related content, creative content and emotional contents, etc. This study has focused on mainly four strategic contents, upon which most of the marketing strategies are built. Those strategic bases which are studied in this research include: i) personalization, ii) humanization (as brand personality), iii) experiential and iv) emotional contents.

Digital marketing is on boom; hence presence over social media is proving to be one of the foundational marketing strategies for any business to use. The meaning of being present on social media refers to, “how someone post and engage in all of one’s accounts”. It describes the type and frequency of posted content and the engagement level of consumers on social media (Schluter, Hinkel, Bots & Arlinghaus, 2014). Social media represent a significant way to communicate with targeted segments, for companies (Murdough, 2009). This study has also analyzed social media’s influence between the relationship of marketing strategies (as strategic marketing contents being used for strategy formulation) and Customer Brand Engagement (CBE).

Finally, this research work has also tried to address and contribute to another research gap, identified in the Pakistan’s region, i.e., the study of consumers on the basis of their generational cohorts (based on Generational Cohort Theory).

The purpose of this research is manifold. Firstly, it will contribute to fill the gap as stated by MSI by analyzing what are the most effective strategic contents to drive deeper and lasting customer brand engagement with the firm? Secondly, it will not provide a generic analysis but it will provide more specific consumer segments’ analysis, by performing comparative analyses between two consumer cohorts i.e., Generation Y and Generation Z. So, this study will reveal more specific strategic contents to be opted for the targeted consumer segments by the apparel sector. Thirdly, as social media has become a vital part of everyone’s life, so social media’s impact will also be studied, that whether social media’s presence makes any difference or not, in the impact of these strategies to foster customer brand engagement in the apparel sector of Pakistan.

Apparel and textile sectors are one of the largest industrial sectors of Pakistan, which contributes significantly to the economic growth of Pakistan. 9.5 % of GDP contribution comes from this sector only, whereas 57% of export earnings, 37% of employment of industrial labor and 27% of complete industrial output come from this sector respectively (Khan, 2017).

Background

Customer Brand Engagement (CBE)

Customer Brand Engagement (CBE) concentrates consumers from interactive experience perspective and is “a consumers' positively valanced brand-related cognitive, emotional and behavioral activity during or related to focal consumer/brand interactions” (Hollebeek, Glynn & Brodie, 2014). Customer engagement initiatives by an organization works only if the firm implements clear engagement strategies to initiate customer engagement; for instance, provoking customers for the sharing of their viral marketing campaigns, to like and share brand’s owned Facebook page, or to involve and participate in online community that is made by that particular brand or firm (Beckers, van Doorn & Verhoef, 2018). “Customer engagement is a psychological condition which develops with the interaction of customer’s co-creative experiences with the focused engagement object in a central service relationship” (Boride et al., 2011). Pansari & Kumar (2018) define Customer Engagement as “the mechanics of a customer’s value addition to the firm, either through direct or indirect contribution”. CBE has three dimensions.

i) Cognitive Processing: This dimension of CBE refers to the “consumer’s level of thinking process and explanation related to brand in a specific consumer to brand interaction”.

ii) Affection: this dimension of CBE refers to the “consumer’s degree of positive affect related to a brand in a specific consumer to brand interaction”.

iii) Activation: this dimension of CBE also known as behavioral dimension refers to “the consumer's level of energy, effort and time spent on a brand in a particular consumer/brand interaction” (Hollebeek, Glynn & Brodie, 2014).

Brand engagement can occur with not only just one customer, rather it can also occur with the brand and the brand’s related community (Liu et al., 2018).

Strategies for Customer Brand Engagement (CBE)

Strategies for Customer Brand Engagement (CBE) or customer engagement marketing, refers to a firm’s intended or planned attempt to stimulate, empower, and evaluate a consumer’s unpaid contribution to a firm’s marketing process which is not related to main marketing functions, and does not involve and economic arrangement (Harmeling et al., 2017). The main motive behind the firm initiated customer engagement is not to prompt sale like as it’s the case in traditional marketing initiatives; but it intend to develop strong and long lasting relationships with its customers (Beckers et al., 2018). The activities and programs initiated by the organization with the major goal or intent to get connected with its current as well as potential customers; can be known as CE strategies (Vivek et al., 2018).

There are unlimited marketing strategies which a firm can utilize to generate desired response, but there are few bases or building blocks on which any strategy in marketing is built. For instance, television advertisement or online advertisement is a marketing strategy, but it could be built on the basis of personalized advertisement, or it may be generated on the basis of emotional content to bind or attract a customer by triggering his or her emotions, and so on. So, strategy could be same or distinctive in nature, but these bases to form it are basics, like emotional base, personalization base, experiential base, etc. so, basically that basic base to devise any marketing strategy is the core of this research. Hence, four commonly and widely used such bases to build strategic content has been chosen for the study, and their impact on Customer Brand Engagement has been examined. These are as follows:

Personalization

Personalization refers to the ‘ability to deliver tailored content and services to people based on their preferences and behaviors’ (Adomavicius & Tuzhilin, 2005). Personalization marketing or strategy is based upon the idea of designing and delivering of products or services by matching its content with the customers’ preferences (Kramer, Spolter-Weisfeld & Thakkar, 2007). Personalization can be defined as the customization of some aspects of the products or services to make customers avail these and other related benefits on lower prices and with convenience (Moon, Chadee & Tikoo, 2008). Firms tend to apply individualized marketing strategy to foster customer engagement, and one of such widely used strategy is personalization (Arora, et al., 2008), to produce deeper connections (Urban, Liberali, Macdonald, Bordley & Hauser, et al., 2014). Personalized advertisements let the brands engaged with its customers on personal level, thus a more efficacious relationship is built with consumers by fulfilling consumer’s needs more effectively (Shanahan, Tran & Taylor, 2019). It allows firms and its customers to get engage and interact indirectly; while at the same time it increases brand awareness, customer satisfaction, customer loyalty and customer retention (Maslowska, Smit & Putte, 2016). Additionally, when messages are molded according to consumer preferences, personalization plays a key role in differentiating related ads and content from spam, hence benefiting consumer brand engagement (Vesanen, 2007).

Therefore, it was proposed that personalization of marketing strategy content will increase customer brand engagement with the firm, for apparel brands.

H1 Personalization content is positively associated with Customer Brand Engagement (CBE)

Humanization

Humanization of brands as described earlier refers to the incorporation of human like elements in a brand; which is done by building a brand personality. Many researchers state that, it can be observed that consumers build their associations with brands as they develop it with people (Liu & Chang, 2017). Brand personality can be defined as, ‘the set of human characteristics related to a brand, that is based on the approach that emerge from the personification of that brand’ (Aaker, 1997), hence it’s a concept which is developed by the association of a brand with human traits and emotions, so it can depict the features of human personality (Kim, Vaidyanathan, Chang & Stoel, 2018). After so much research work, five main dimensions of brand personality were categorized as: i-Sincerity, ii- Excitement, iii- Competence, iv-Sophistication, and v-Ruggedness (Aaker, 1997), which were derived from the psychology literature of personality and based on the adapted dimension of Big Five model (Aguilar, Guillen & Roman, 2016).

Brand personality can play a significant role in fostering customer engagement and bonding with the brand, due to the fact that now brands have their own different personalities like other individuals (Bouhlel, Mzoughi, Hadiji & Slimane, 2011).

A powerful brand personality motivates consumers’ will for the usage and engagement with a particular brand, as through it the emotional need of that customer is fulfilled, and those active consumer behaviors are fostered which ultimately increase customer engagement with the brand (Bairrada, Coelho & Lizanets, 2019).

Studies revealed that brand personality has positive influence on customer brand engagement (Banahene, 2017; Peco-Torres, Polo-Pena & Frias-Jamilena, 2020). Therefore, it was proposed that there is a positive relationship between a brand’s humanization contents and Customer Brand Engagement (CBE).

H2 Humanization content is positively associated with Customer Brand Engagement (CBE).

Experiential

Experiential marketing refers to the marketing a product or a service through experiences that engage and create emotional attachment of the customer with product or service (Wong, 2013). It can also be explained as a “marketing approach designed by a firm to stage the whole physical environment and the operational processes for its consumers to experience” (Yuan & Wu, 2008). As consumers nowadays do not purchase products based on their functional aspects and benefits, but they are more interested to choose those products and services which attach some experiential aspects with the offerings (Zarantonello & Schmitt, 2010). Strength of the relationship between a brand and its consumer is highly dependent upon the consumer’s experiences with brand as positive relationship between these two is based on distinctive and catchy experiences (Wiedmann, Labenz, Haase & Hennings, 2018); whereas engagement implies a bond or a connection between two parties, based on their level of interactivity; and the party can be an individual, a firm or a society (Vivek, Beatty, Dalela & Morgan, 2014; Hollebeek, 2011). Customer’s experience with the brand builds psychological connection between a consumer and a brand; this connection leads towards the creation of intense customer responses like repeated purchase, brand recommendation, brand-firm relationship development through positive feedback; which ultimately results in customer loyalty (Bairrada et al., 2019; Prentice, Wang &Loureiro., 2019), which are reflective of customer engagement concept (Kumar, Rajan, Gupta & Pozza, 2019).

Experiences are related to psychological factors, and strong customer engagement is based on strongly nurtured psychological connection with the brand, which leads towards long lasting relationship with brand and results in purchase repetition (Hapsari, Clemes & Dean, 2017). The ultimate goal of any marketing strategy is to make a consumer purchase the product or service, but now customers in actual do not intend to purchase products, rather they purchase those products which have some experience behind them (Hollebeek & Macky, 2019).

From the literature it is apparent that brand experience which is a means for experiential marketing, is a way to engage customers with the brands. From this the relationship between experiential marketing content and CBE can be hypothesized as:

H3 Experiential content is positively associated with Customer Brand Engagement (CBE).

Emotional

Emotion can be defined as: “a qualitative, descriptive state, which occurs with changes on one or more levels: feeling, physical state and expression” (Schmidt-Atzert, Peper & Stemmler, 2014). It’s a significant part of human behaviors, which influences thinking, actions and decisions of consumers (Izard, 2009). The emotional content in the marketing strategy is capable of grabbing consumers’ attention and evoking the required level of engagement with the firm (Schreiner & Riedl, 2018).

The stronger emotions result in long term relationship building between a customer and a brand (Blasco-Arcas, Hernandez-Ortega & Jimenez-Martinez, 2016), that is the ultimate root of CBE concept. If a customer attains the feelings of pleasure and dominance during these interactive experiences, he will build a positive perception regarding the firm and its products (Mazaheri, et al., 2014). Furthermore, high level of arousal in individuals is also required in these interactive experiences, which impact their level of engagement (Vivek, Beatty & Morgan, 2012). Different kinds of emotions generate different kind of influences on individuals. Emotions like happiness, humor, love, excitement, etc., are capable enough to grab consumer’s attention and engage those (Rossiter & Bellman, 2012). Emotions based advertising has found to be significantly associated with different buying behaviors of consumers, as it increases the understanding level of message conveyed through advertisement, hence cultivating a strong bonding with the brand and its customers (Samovar, Porter & McDaniel, 2012). Despite some conceptual research has proposed a significant role of emotional concepts in developing customer engagement; the relationship of emotions and engagement has not been empirically tested widely, in past; except this study which found that emotions experienced by consumers during their interaction in engagement platforms positively influence customer engagement between firm and its consumer (Blasco-Arcas et al., 2016). Emotional content plays a significant role to arouse engagement by seeking attention of consumers, but it has become a great challenge for firms and brands to create such a content which can do the stated task (Tafesse, 2015). From the literature it can be observed that emotions’ role in influencing customer engagement has been discussed highly but on conceptual and theoretical basis. So, based on the conceptual relationship; the proposed hypothesis for the relationship between emotional content and Customer Brand Engagement (CBE) is as follows:

H4 Emotional content is positively associated with Customer Brand Engagement (CBE).

The Mediating Role of Social Media Presence (SMP)

The dawn of social media has empowered customers to better voice their ideas and reach a broad range of customers, it has cause firms to lose control over their audience (Schamari & Schaefers, 2015); that is why Customer Brand Engagement (CBE) is setting off to be a priority strategy in branding and playing a major role in shaping new customer-centric approach of marketing (Hollebeek, 2011). Regardless of the fact that CBE is not so much developed up till now, yet its already thought as a basic driver of the customer’s decision-making process (Sprott, Czellar & Spanggenberg, 2009); and if we observe its benefits from customer’s side, social media gives such a platform to consumers where they can have a two-way communication with the brand, which was not possible in traditional media usage (Yang, Lin, Carlson & Jr. Ross, 2016), hence providing a best place for customer engagement to occur as it depends on the co-creation or two way interaction between consumers and firms, and to other consumers as well. Many firms allocate a significant amount of their budget to build interactive consumer relationships, and very often they do it by using social media (Baldus, Voorhees & Calantone, 2017), and relationship set the base for consumers to get engage with the brand. As social media does not only provide a communication platform by targeting specific target market but it can be a great and effective tool for fostering customer engagement (Constantinides, Romero & Boria, 2008).

To make sure the presence over one or more types of social media platforms, a number of significant resources are being devoted by most of the international brands, to underpin customer brand relationships and foster greater customer engagement (Kumar, Bezawada, Rishika, Janakiraman & Kannan, 2016).

International brands incorporating their significant resources to remain present on either one or more kinds of social media platforms, like Facebook, Instagram, WeChat, etc. to increase customer engagement with the branded content, hence strengthening the customer’s relationship with the brand (Kumar et al., 2016); as engagement with content is necessary for firms to gain overall marketing objectives (Schreiner & Riedl, 2018).

As the literature states that social media platforms have become an important means to reach and connect customers; hence increasing their engagement with the branded content, so it is hypothesized for this study that Social Media Presence (SMP) on platforms like Facebook and Instagram, can positively increase the association of strategic marketing content’s bases (used for marketing strategy formulation) with customer brand engagement. Hence, the following hypotheses were proposed:

H5 SMP (i.e., Social Media Presence) is positively associated with CBE.

H6 SMP positively mediates the relationship between personalization contents and CBE.

H7 SMP positively mediates the relationship between humanization contents and CBE.

H8 SMP positively mediates the relationship between experiential contents and CBE.

H9 SMP positively mediates the relationship between emotional contents and CBE.

Generation Y and Generation Z

Generation refers to such a cohort of people, who’s birth date falls in the specified time frame and shares key life experiences such as cultural trends, national and international events, education, social norms, job experiences, etc. (Denton & Voth, 2016). There are four to five generations based on their age range years, in which these were born in. Only two generations are the focus of this study i.e., Generation Y and Generation Z consumers.

Generation Y

Generation Y is also famously known as Millennials. This generational cohort comes after the generation X. Generation Y’s birth range is 1980 to 1995. In year 2016, they would have gained age of 21 to 36 years (Zhang, Omran & Cobanoglu, 2017). This study has focused on the age range of generation Y consumers starting from year1980, so their age ranges from 25 years to 40 at the time of data collection i.e., year 2020.

Due to the increasing purchasing power of the generation Y in the marketplace, business practitioners are inclined towards the understanding of generation Y’s purchase behavior (Rieke, Fowler, Chang & Velikova, 2016). Millennials take their family and friends more reliable and trustworthy than any other source for gathering information (Monaco, 2018). Because of this cohort’s uniqueness, many businesses have highly invested in this cohort’s study, to understand attitudes and behaviors of Millennial (Zhang, Omran & Cobanoglu, 2017), as according to research estimation these Millennials are expected to spend more than 10 trillion dollars throughout their lifespan (Rieke, et al., 2016). In year 2015, only in US, 27% of the people of the country belonged to the Generation Y group, whereas their annual spending increased from ‘97.3 million dollars in 2003 to 200 billion dollars in 2015’ (Bowen & Chen McCain, 2015). In spite of such a huge spending ratio and constituting a significant number of populations, the marketers face a great challenge in forecasting the behavior of Generation Y than previous generations, i.e., Baby Boomers and Generation X (Amin, 2016).

Generation Y is one of the biggest role players in the global business world, but how business and brands are engaging them is still being discovered (Zhang, Omran & Cobanoglu, 2017). So, this study has taken this segment of consumers as this form the largest customer base of present times.

Generation Z

Generation Z is also known as Digital Natives or iGeneration or Next Generation (Barreiro & Bozutti, 2017). Generation Z is the youngest cohort born after 1995, are highly competent, creative, innovation-oriented and technology savvy (Priporas, Stylos & Fotiadis, 2017). This generation is pioneer for whom virtual world matters the most and information transmission through different social media platforms is a must to do task for this generation in form of life casting on internet (Van den Bergh & Pallini, 2018). Generation Z tend to characterize more according to its inclination towards the need of increased innovation, convenience, security and its’ desire to escape, which is mostly facilitated by the usage of technology advancements (Wood, 2013).

These Digital Natives are heavy users of technologies; which are considered ‘a must have’ for them (Van den Bergh & Behrer, 2016). This generation is more multi-tasking, more imaginative, more flexible, hence shows less rigidity than previous generations (Marcus, 2008). An Ad Agency named as Sparks and Honey, conducted a research and found that they are more likely to spend more of their time outdoor than in school, i.e., 41% as compared to 22% in past decade (Sparks & Honey Ad Agency, 2014).

Generation Z is entering in colleges and universities; as well as entering in their early careers and also making a youngest cohort of customers now, who have the purchasing power and would like to take its decisions regarding purchase.

Previously, many studies are found in western countries, which have studied other generations in depth i.e., generation X and generation Y, but studies on this cohort Z, are not only lacking in South Asian region, but are also lacking in other regions of the world as well.

Hypothesis for Generation Y & Generation Z

As this study aims to analyze the difference and similarity of effects of strategic contents on CBE of Gen. Y. & Gen. Z. separately to further enhance the knowledge to tap these two consumer groups, so the above developed hypotheses were further developed separately for Gen. Y. as well as Gen. Z.

Hypotheses for Generation Y

H1a Personalization content is positively associated with CBE (Customer Brand Engagement).

H2a Humanization content is positively associated with CBE.

H3a Experiential content is positively associated with CBE.

H4a Emotional content (in marketing) is positively associated with CBE.

H5a SMP (Social Media Presence) is positively associated with CBE.

H6a SMP positively mediates the relationship between personalization contents and CBE.

H7a SMP positively mediates the relationship between humanization contents and CBE.

H8a SMP positively mediates the relationship between experiential contents and CBE.

H9a SMP positively mediates the relationship between emotional contents and CBE.

Hypotheses for Generation Z

H1b Personalization content is positively associated with CBE (Customer Brand Engagement).

H2b Humanization content is positively associated with CBE.

H3b Experiential content is positively associated with CBE.

H4b Emotional content (in marketing) is positively associated with CBE.

H5b SMP (Social Media Presence) is positively associated with CBE.

H6b SMP positively mediates the relationship between personalization contents and CBE.

H7b SMP positively mediates the relationship between humanization contents and CBE.

H8b SMP positively mediates the relationship between experiential contents and CBE.

H9b SMP positively mediates the relationship between emotional contents and CBE.

Conceptual Framework

Based on the above literature and this research’s underpinning theoretical lenses known as ‘Relationship Marketing’ and ‘Social Exchange Theory’, as many researchers used these theories individually to ground their work on customer brand engagement (Hollebeek & Macky, 2019; Roy, Shekhar, Lassar & Chen, 2018; Luo, 2002); the proposed conceptual framework of this study is depicted in Figure 1 in which at the left side four Independent Variables (IVs) including personalization, humanization, experiential, and emotional; and in middle one Mediating Variable (MV) i.e., social media presence; and at the right side one Dependent Variable (DV) i.e., Customer Brand Engagement (CBE), are represented.

Methodology

Sample

For this research the research sample was based upon two groups of consumers of branded apparel sector of Pakistan that is Generation Y and Generation Z consumers. Age range for Generation Y consumers was 25 to 40 years, whereas for Generation Z consumers it was 8 to 24 years (as in year 2020 i.e., at the time of data collection).

Measures

For the measurement of all the variables of this study as illustrated in Figure 1 all measuring scales has been adapted for this study, i.e., all these measures have been used and tested by other researchers already, but in a different context.

This study has one dependent and four independent variables which are termed as strategic contents used as a foundation to develop marketing strategies to increase CBE.

Items to measure Customer Brand Engagement (CBE), were adapted from the work of Hollebeek in 2014; to measure personalization were adapted from the work of Ball (2006); to measure humanization (i.e., brand personality), items were adapted from the work of Aaker (1997) with its modified version used by Geuens, et al., (2009); whereas to measure experiential content items were adapted from the work of Brakus, et al., (2009). All these items used a 7-point Likert scale (where 1=strongly disagree and 7=strongly agree) (Hollebeek, Glynn & Brodie, 2014; Ball, Coelho & Vilares, 2006; Geuens, Weijters & Wulf, 2009; Brakus, Schmitt & Zarantonello, 2009).

To measure emotional content’s influence, based on Plutchik’s widely used eight emotions proposed in 1980, scale was adapted from the work of Machleit in 2000. To what extent these emotions were experienced during a shopping experience of a particular brand was measured on 5-point Likert scale, where 1 represents the ‘low extent’ and 5 represents the ‘high extent’ on a 1 to 5 continuum.

To study mediating effect of social media presence, i.e., to analyze that whether the active participation in activities over the social media platforms influence the relationship between dependent and independent variables, measures were adapted from the work of Kim & Ko, in year 2012 based on 7-point Likert scale (Kim & Ko, 2012).

Data Analysis Procedure

For the analysis purpose Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM) was used and analyzed through Smart PLS and SPSS 21.

A total of 500 useable responses were used in this study, among which 250 were generation Y consumers as well as 250 were generation Z consumers. Data was collected through survey method, by using convenience sampling technique.

Overall demographic information of the respondents include: 20 % male and 80% females. Both generational cohorts had equal number of respondents i.e., 50% of each group was present in the sample. A snapshot of demographic profile of the study is presented in the Table 1.

Table 1 Respondents’ Demographic Profile
Variable	n (total number)	%
Gender
Male	100	20
Female	400	80
Age Range
25 to 40 years (i.e., Gen. Y)	250	50
8 to 24 years (i.e., Gen. Z)	250	50
Marital Status
Single	325	65
Married	161	32.2
Engaged	10	2
Divorced	4	0.8
Level of Education
Below Matric	9	1.8
Matric	22	4.4
Intermediate	48	9.6
Bachelors	258	51.6
Masters or Above	163	32.6
Professional Level
Student	284	56.8
Housewife	97	19.4
Business Man/Woman	13	2.6
Job Holder	67	13.4
Others	39	7.8
Social Class
Upper Class	27	5.4
Upper Middle Class	206	41.2
Middle Class	246	49.2
Lower Middle Class	18	3.6
Lower Class	3	0.6

Results

Internal Consistency, Reliability, Convergent and Discriminant Validity

The internal composite reliability was checked by the Cronbach's alpha. All the six factors including CBE (0.895), Personalization (0.769), Humanization (0.827), Emotional (0.795), Experiential (0.830), and Social Media Presence (0.805); were reliable, because all the values of Cronbach's alpha were greater than 0.70, which indicates that the factors are reliable.

As stated earlier Partial Least Square Structural Equation Modeling (PLS-SEM) was used to asses measurement model followed by structural model assessment and hypothesis testing. All the Lower Order Constructs (LOC) used in the model had a reflective nature of measurement. These included all the six factors of this study. Reflective constructs need to be assessed for internal consistency reliability, convergent validity and discriminant validity.

Indicator Reliability represents how much of the variation in an item is explained by a variable (Hair et al., 2013). Indicator reliability of the measurement model is measured by examining the item loadings. A measurement model is said to have satisfactory indicator reliability when each item’s loading is at least 0.7 and is significant at least at the level of 0.05 (Hair, Ringle & Sarstedt, 2013). In this study, Indicator reliability was assessed using the outer loadings through Smart PLS. Hair, et al., (2013) suggested that items having a loading at least 0.70 to be retained, while items having an outer loading value less than 0.50 should be omitted. So, the outer loadings having value less than 0.5 were also omitted in this study.

Though Cronbach’s Alpha (CA) has been a commonly used method for measuring the reliability, but numerous scholars have indicated that Composite Reliability (CR) is preferred over Cronbach’s alpha because CR has certain limitations (Hair Jr et al., 2017; Rasoolimanesh et al., 2017; Ringle et al., 2018). A measurement model is considered to have satisfactory internal consistency reliability when the Composite Reliability (CR) of each construct exceeds the threshold value of 0.7. Furthermore, a CR value 0.60 to 0.70 is acceptable, 0.70 to 0.90 is considered from satisfactory to good, whereas 0.95 and higher CR value is not desired, as it reflects redundancy in the items and a lack of construct validity (Hair et al., 2019). The results of Composite Reliability (CR) of the outer measurement model in Table 2 reflects those constructs of this study have a satisfactory level of internal consistency reliability by showing CR values higher than the threshold value 0.70. This established internal consistency reliability of the measurement model used in this study.

Table 2 shows that all of the constructs have CR value higher than the threshold value 0.5 ranging from 0.516 to 0.598 higher than the threshold value of 0.5 on the lower side, which indicates that convergent validity is adequate, as when constructs have an average variance extracted (AVE) value at least 0.5 or more (Hair et al., 2017; Cheah & Sarstedt et al., 2018b).

Table 2 Outer Loadings For All Factors
Factors	Items	Outer Loadings	Composite Reliability	Average Variance Extracted (AVE)
Customer Brand Engagement	DV1_Interest	0.713	0.814	0.516
	DV1_Wear	0.749
	DV1_Think	0.69
	DV2_Feel	0.762
	DV2_Happy	0.738
	DV2_Positive	0.792
	DV2_Proud	0.746
	DV3_Preferred	0.712
	DV3_Time	0.669
	DV3_Use	0.703
Emotional	Em_ Acceptance	0.76	0.812	0.52
	Em_ Expectancy	0.704
	Em_ Joy	0.765
	Em_ Surprise	0.751
Experiential	Ex1_Impression	0.78	0.766	0.548
	Ex1_Interesting	0.694
	Ex2_Emotional	0.744
	Ex2_Feelings	0.793
	Ex3_Actions	0.771
	Ex3_Bodily	0.699
	Ex4_Curiosity	0.741
	Ex4_Thinking	0.727
Humanization (as Brand Personality)	H1_Down	0.726	0.771	0.566
	H1_Responsible	0.802
	H1_Stable	0.752
	H2_Active	0.794
	H2_Dynamic	0.726
	H2_Innovative	0.717
	H5_Romantic	0.758
	H5_Sentimental	0.795
Personalization	P_Changed	0.783	0.816	0.598
	P_Find	0.826
	P_Satisfy	0.803
Social Media Presence	MV1_Content	0.761	0.821	0.517
	MV1_Fun	0.743
	MV2_Exchange	0.727
	MV2_InfoSharing	0.746
	MV2_Opinion	0.746
	MV3_Newest	0.767
	MV3_Trendy	0.757
	MV4_CustomizedInfo	0.716
	MV4_Service	0.682
	MV5_Friends	0.762
	MV5_Upload	0.777

The examination of cross-loadings and use of the Fornell-Larcker criterion were accepted methods for assessing the discriminant validity of a PLS model. The cut-off point of the heterotrait correlations should be smaller than monotrait correlations, meaning that the HTMT ratio should be below 1.0 or Clark & Watson (1995) ; Kline (2011) use the more stringent cut-off point was 0.85. In this study all the values were less than 1 or 0.85. It indicated that all variables are assessing the discriminant validity for the SEM.

Multicollinearity

All the outer and inner VIF (Variance Inflation Factor) values were less than 5, indicating that in SEM model, no multicollinearity issue was found.

SEM Analysis

In structural model assessment, second step is to explore the significance and relevance of hypothesized relationships among the constructs. In PLS-SEM, path coefficients represent these relationships, which are obtained through the bootstrapping technique. As in this study comparative analysis between two consumer groups (i.e., Gen. Y & Gen. Z) are drawn, so an overall SEM analysis for the study was run as well as a separate SEM analysis for each of the groups was run also.

Table 3 Complete Structural Equation Model With Path
	?	S.E	t-values	p-values	Hypothesis
Emotional -> CBE	0.07	0.045	1.57	0.133	Reject
Emotional -> SMP	0.072	0.045	1.592	0.119	Reject
Experiential -> CBE	0.292	0.044	6.703	0	Accept
Experiential -> SMP	0.278	0.044	6.266	0	Accept
Humanization -> CBE	0.058	0.045	1.314	0.224	Reject
Humanization -> SMP	0.341	0.045	7.496	0	Accept
Personalization -> CBE	0.258	0.042	6.125	0	Accept
Personalization -> SMP	0.183	0.045	4.082	0	Accept
SMP -> CBE	0.296	0.052	5.689	0	Accept

Coefficients and P-Values

The table 3 indicated that the complete Model’s path coefficients and their significance. The results indicated that SMP plays a partial mediation role between personalization and CBE and experiential and CBE. It also showed that the SMP plays a complete mediation role between humanization and CBE. The SMP cannot play a mediation role between Emotional and CBE.

SEM Analysis for Generation Y

Table 4 Generation Y (25 To 40 Years) Structural Equation Model With Path Coefficients And P-Values
	?	S.E	t-values	p-values	Hypothesis
Emotional à CBE	0.122	0.065	1.871	0.072*	Accept
Emotional à SMP	0.064	0.071	0.902	0.361	Reject
Experiential àCBE	0.334	0.058	5.759	0.000***	Accept
Experiential à SMP	0.346	0.06	5.766	0.000***	Accept
Humanization àCBE	0.042	0.075	0.563	0.548	Reject
Humanization àSMP	0.292	0.067	4.376	0.000***	Accept
Personalization àCBE	0.255	0.061	4.191	0.000***	Accept
Personalization àSMP	0.174	0.053	3.308	0.001***	Accept
SMP à CBE	0.243	0.082	2.969	0.003***	Accept

*** p< 0.001, **p<0.05, *p<0.10

The results indicated that SMP plays a partial mediation role between personalization and CBE and Experiential and CBE. It also showed that the SMP plays a complete mediation role between humanization and CBE. The SMP cannot plays a mediation role between Emotional and CBE.

SEM Analysis for Generation Z

Table 5 Generation Z (8 To 24 Years) Structural Equation Model With Path Coefficients And P-Values
	?	S.E	t-values	p-values	Hypothesis
Emotional -> CBE	-0.005	0.052	0.101	0.919	Reject
Emotional -> SMP	0.068	0.051	1.313	0.179	Reject
Experiential -> CBE	0.248	0.059	4.226	0.000***	Accept
Experiential -> SMP	0.19	0.067	2.825	0.002***	Accept
Humanization -> CBE	0.093	0.054	1.729	0.070*	Accept
Humanization -> SMP	0.406	0.059	6.821	0.000***	Accept
Personalization -> CBE	0.275	0.058	4.718	0.000***	Accept
Personalization -> SMP	0.218	0.072	3.043	0.002***	Accept
SMP -> CBE	0.346	0.06	5.749	0.000***	Accept

The results indicated that SMP plays a partial mediation role between personalization and CBE, Experiential and CBE, and Humanization and CBE. The SMP cannot plays a mediation role between Emotional and CBE.

Coefficient of Determination through R²

In the complete SEM model, there were two separate R2 values was established. The first R² value 0.586 indicated that the experiential, humanization, emotional, personalization and SMP explained the variation among in CBE up to 58.7% which indicated that this model is good fitted. The second R² value 0.457 indicated that the experiential, humanization, emotional and personalization explained the variation among in SMP up to 58.7% which indicated that this model is good fitted.

Hypotheses Analysis

As in the above analysis, its apparent that which independent variables are significant and which are insignificant, and based on those hypotheses results are summarized to be either accepted or rejected. There were two types of relationships studied in this research, one was direct effects of independent variables on dependent variable and the other was indirect effects of independents variables on dependent variable passing through the mediating variable. But for a clear elaboration of the acceptance and rejection of this study’s hypotheses, in the following a table of all SEM analyses, i.e., complete as well as comparative is given and all those hypotheses which are developed in the study are given with their results.

Table 6 Comparative Analysis of SEM of Gen. Y. and Gen. Z
	? Complete	? Generation Y	? Generation Z
	(8 to 40 Years)	(25 to 40 Years)	(8 to 24 Years)
Personalization à CBE	0.258***	0.255***	0.275***
	0	0	0
Personalization à SMP	0.183***	0.174***	0.218***
	0	-0.001	0
Experiential à CBE	0.292***	0.334***	0.248***
	0	0	0
Experiential àSMP	0.278***	0.346***	0.190**
	0	0	-0.002
Humanization à CBE	0.058	0.042	0.093*
	-0.224	-0.548	-0.07
Humanization à SMP	0.341***	0.292***	0.406***
	0	0	0
Emotional à CBE	0.07	0.122*	-0.005
	-0.113	-0.072	-0.919
Emotional à SMP	0.072	0.064	0.068
	-0.119	-0.361	-0.179
SMP à CBE	0.296***	0.243***	0.346***
	0	-0.003	0

*** p< 0.001, **p< 0.05, *p< 0.10

Hypothesis analysis of complete sample. Hypotheses accepted on overall sample included H1, H3; which implies that personalization and experiential content has a positive/direct influence on Customer Brand Engagement (CBE) in apparel sector. Whereas H2, H4 were rejected, implying that the humanization and emotional contents do not impact CBE directly. Social Media Presence (SMP) has a positive influence on CBE i.e., H5 also accepted. When Social Media Presence (SMP) was used as a mediator the all hypotheses H6 and H9 were accepted, implying that SMP partially mediates the relationship between these contents and CBE.

While H7 was also accepted, which means that SMP plays a complete mediation role for the influence of humanization content on CBE. H8 was rejected i.e., SMP does not mediate the relationship.

Hypothesis analysis of Generation Y. Hypotheses analysis for Generation Y was performed separately. H_1a, H_3a, and H_4a were accepted, implying that personalization, emotional and experiential contents have a positive influence over the CBE of Generation Y consumers, while H_2a was rejected means humanization content does not influence CBE of Gen. Y consumers, directly.

H_5a was also accepted, which means that SMP has a direct impact on CBE of Gen. Y. When SMP was used as a mediator between the relationship of strategic marketing contents and CBE, the H_6a & H_8a were accepted meaning that SMP partially mediates the relationship between personalization, experiential contents and CBE of Gen Y. Whereas H_7a was also accepted which means that SMP completely mediates the relationship between humanization and CBE of Gen Y, i.e., with social media presence humanization element also affect CBE positively. Another result indicated that SMP negatively mediates the impact of emotional content on CBE for Gen. Y., who was positively influenced by emotional content without the usage of social media, as H_9a was rejected.

Hypothesis analysis of Generation Z. Hypotheses analysis for Generation Z was performed separately. H_1b, H_2b, and H_3b were accepted, implying that personalization, humanization and experiential contents have a positive influence over the CBE of Generation Z consumers, while H4b was rejected means humanization content does not influence CBE of Gen. Z consumers, directly.

H_5b was also accepted, which means that SMP has a direct impact on CBE of Gen. Z. When SMP was used as a mediator between the relationship of strategic marketing contents and CBE, the H_6b, H_7b & H_8b were accepted meaning that SMP partially mediates the relationship between personalization, humanization & experiential contents and CBE of Gen Z. Whereas H9b was rejected, implying that SMP also cannot enhance the effect of emotional contents for Gen. Z.

Discussion

The major research theme of this study was to analyze what are the most effective strategic marketing content to drive deep and lifelong Customer Brand Engagement (CBE) with the firm, as in accordance with the latest research call as their top research priority area of year 2018 to 2020, by one of the major marketing research hubs in the world i.e., Marketing Science Institute (Marketing Science Institute, 2018). To answer this call there were two ways, either to examine the relationship of actual marketing strategies (like virtual marketing, social media marketing, retailing, advertising, etc.) and CBE, or to analyze the influence of marketing strategic contents (i.e., the base or foundational elements used to build any marketing strategy, i.e., emotions, experiences, etc.) on customer brand engagement. For this research work, the later approach was chosen that is the influence of four strategic marketing contents on customer brand engagement was studied. These contents included: i) personalization, ii) humanization (i.e., brand personality), iii) experiential, and iv) emotional.

This research priority was further attached with the comparative analysis of two consumer groups by applying one of the widely used sociological theory in literature, that is ‘Generational Cohort Theory’ i.e., two consumer groups were chosen for this study which include Generation Y (25 to 40 years) and Generation Z (8 to 24 years) in apparel sector of Pakistan. Because these two generations are the current as well as future consumer cohorts in the world. The concept of generation was chosen as its application in marketing literature is extensive now in the west countries, but its application in eastern nations, particularly South Asian region is limited, and

Pakistan in one of the South Asian countries. So, due to this gap this generation Z was chosen, as well as generation Y, to examine if there exist any differences among these two generations, or both groups have same behavior outcomes when marketing strategies are used to engage customers with the brand.

The results showed that Personalization marketing content has been found to influence Customer Brand Engagement (CBE) positively for both generational groups, as personalization is one of the two possible strategies to foster customer engagement in an influential way (Bleier et al., 2018). But the extent of influence of personalization on CBE of Generation Z is more, as compared to Generation Y. It implies that personalization of goods and services matters for Gen. Z more. Advantage of personalization in the interactive process between a firm and its consumers is that, it allows firms to build relationship with its users; which results in the generation of a deeper customer engagement with the firm (Blasco-Arcas et al., 2016; Maslowska et al., 2016), i.e., the relationship fostered on the basis of effective personalization increase customer engagement with the brand (Shanahan et al., 2019).

Humanization marketing content has a positive effect on customer brand engagement of Generation Z, whereas for Generation Y this content is not influential in fostering engagement, i.e., it has found to be insignificant in Gen. Y.’s case. Brand personality has positive influence on customer brand engagement (Banahene, 2017; Peco-Torres et al., 2020), so Gen. Z.’s CBE has been influenced positively by the brand personality of apparel brands. But the concept of brand personality has given different results in Pakistan context, as compare to western countries. This contradiction of results is not new, as brand personality i.e., humanization is such kind of a construct which produces different results in different cultural settings and contexts, as it has been indicated through my empirical research works (Milas & Mlacic, 2007).

Experiential marketing content has significant impact on Customer Brand Engagement (CBE) for both of the consumer groups, as consumers tend to be more attentive to the brands which provides unique and memorable experiences to its customers (Gentile, Spiller & Noci, 2007). A customer values that brand, which provides more brand experience, hence generates experiential as well as functional value to consumers (Cleff, Lin & Walter, 2014). But the extent of influence of experiential marketing content is more on Generation Y as compared to Generation Z. Experiences which are created through experiential marketing, are related to psychological factors, and strong customer engagement is based on strongly nurtured psychological connection with the brand, which leads towards long lasting relationship brand and results in purchase repetition (Hapsari, Clemes & Dean, 2017).

As there was a gap in Pakistan regarding the analysis of emotional advertising’s influence in apparel industry (Kamran & Siddiqui, 2019), so emotional content’s effect on CBE was analyzed. Emotional marketing content has found to have effect on CBE of only Generation Y consumers. It does not influence customer brand engagement of Generation Z consumers, in apparel sector. These findings about emotional content’s impact are contrary to many studies found in west, in which emotions are found to play a substantial role in generating purchase appeals (Batra & Ray, 1986). A logical reason for emotional content’s influence on Generation Y only, could be due to the age factor of this generation. As Generation Y are more mature, and involved in practical lives, have their own kids and families, tend to be more emotional as compared to Generation Z consumers which are young, and mostly are in their early stages of life where they are singles, have no their own families, so not emotionally mature enough to accept or understand the emotional content’s influence.

As there are multiple social media platforms nowadays, including Facebook, LinkedIn, Twitter, WhatsApp, YouTube, Instagram, WeChat, etc. (Duffet, 2017), both of these consumer groups were familiar more with Facebook, Instagram, YouTube, and Snapchat, less were familiar with Twitter and Pinterest in Pakistani context. Most preferred social media platform by Generation Y was Facebook, whereas Generation Z preferred Instagram more.

When Social Media’s Presence (SMP) is incorporated with these four strategic contents what effects it may produce have been found by employing mediation analysis between the relationship of marketing contents and CBE for Gen. Y. and Gen. Z. Because social media being an influential marketing tool, the impact of such digital platforms on various consumer behavioral outcome like psychological and economic constructs were highly recommended research areas by the researchers (Stephen, 2016).

When social media is used by the brands, the effects of personalization content prove to be significant. But the extent of this personalization effect is less for Generation Y, whereas personalization impacts more on the customer brand engagement of Generation Z, when these apparel brands mark their presence on social media platforms, as perceived personalization of advertisement in social media leads towards powerful brand attachment and increased consumer brand engagement (Shanahan et al., 2019).

The effects of the humanization content on CBE remain insignificant for Generation Y, even when social media is used; but humanization content influence significantly CBE of Generation Z, with the incorporation of social media platforms, because due to wide use of different types of social media platforms, the traditional media usage is declining (Akar & Topcu, 2011). It implies that social media platforms are a means to gain Generation Z’ engagement with the brand when brand personality is developed for an apparel brand.

The effects of experiential content on CBE when SMP is used by the brands, remains significant, as both direct and indirect effects of brand experiences on customer engagement are found (Prentice et al., 2019). But the extent of the experiential’s effect on CBE via SMP, increases for Generation Y, whereas it declines for Generation Z.

The effects of the emotional content on CBE are significant for Generation Y; but its’ influence remains insignificant for CBE of Generation Z as well as Generation Y, with the incorporation of social media platforms. It implies that social media platforms do not impact Generation Y and Generation Z’s engagement with the brand when emotional contents are used to develop engagement strategies for an apparel brand. These insignificant results of emotional content’s influence on customer brand engagement through social media platforms, are contrary to the previous researches in which it was revealed that emotions experienced by consumers during their interaction in engagement platforms positively influence customer engagement between firm and its consumer (Blasco-Arcas, et al., 2016).

Conclusion

This study aimed to study the most effective strategic marketing content to drive deeper CBE of Generation Y and Generation Z with the firm. From the above analysis it was found that the personalization and humanization (with incorporation of social media only) contents were found to be most effective strategic marketing contents to engage Generation Z customers; whereas experiential content was found to be most effective for strategy formulation for Generation Y consumers in apparel sector.

Even the difference in the extent of influence of all the chosen four strategic contents were apparently found between the Gen. Y and Gen. Z consumers. The findings of this research also revealed that, when Social Media Platforms (SMP) are used by the firms, it provides different results. But in most cases, it enhances the extent of influence of the chosen four strategic contents on CBE.

Theoretical and Practical Contributions

At first, theoretically this study has contributed to customer engagement’s literature by addressing major gaps in the current literature of customer engagement, i.e., from a branding and strategic marketing perspective, which was explicitly denoted by Marketing Science Institute’s tier one priority research stream for year 2018 to 2020; by empirically testing the conceptual assertions with engagement concepts, but from a branding perspective. Secondly, by doing so, it has added up in the existing knowledge of brand management that which strategic marketing contents can be used as a base to design effective marketing strategies to increase Customer Brand Engagement (CBE), especially through utilization of these four specific strategic marketing contents, which are not extensively researched and tested in empirical way, directly with the CBE concept i.e., customer engagement but with branding perspective. Thirdly, on one hand, this study is conducted in a totally different context as compared to current available studies on Customer Engagement which are conducted in western countries, and Pakistan is a South Asian country, enriched with eastern culture and values, which makes it a totally different market. So, this study has also advanced the knowledge by extending the application of these concepts in a totally different context, whereas on another hand this study has also contributed to existing knowledge of ‘generational cohort theory’ by applying this concept in Pakistan’s context where this concept’s application from marketing perspective is lacking, especially the available studies have focused on Generation Y, no study on Generation Z is available till date. So, there is a huge gap. This study has not only addressed this gap by targeting Generation Z, but has also reported the similarities and differences among these two generations from the perspective of Customer Brand Engagement (CBE) built through selected marketing contents. Lastly, as this era is full of technological innovations, and digitalization is on its boom, so social media marketing, has gained very high status not only from marketing but from business’ perspectives too. This study has also contributed to the existing knowledge of social media marketing, that how the utilization of social media platforms, between the interaction of strategies and CBE, influence the extent of impact on customer brand engagement.

This study has also practical implications for marketing practitioners and business’ policy makers, especially for branded apparel sector of Pakistan.

In this study these Generation’s similarities and differences in preference of type of brands and social media platforms, provides guidance for practitioners that what kind of channels to use to get these consumers engaged. For instance, if an apparel brand intends to introduce a product, for which it has targeted Generation Z consumers, so, this study can be guide in directing it, that if an apparel wants to engage Generation Z consumers effectively through the utilization of social media platforms, so the most preferred and used social media type for this generation is ‘Instagram’ followed by Facebook as second most widely used social media platform. So, is the case of Generation Y consumers, that is, if an apparel brand wants to use social media marketing for a product for this generational cohort, then the most suitable social media platform is ‘Facebook’.

of social media platforms, so the most preferred and used social media type for this generation is ‘Instagram’ followed by Facebook as second most widely used social media platform. So, is the case of Generation Y consumers, that is, if an apparel brand wants to use social media marketing for a product for this generational cohort, then the most suitable social media platform is ‘Facebook’.

Even, when social media platforms are on the agenda of firms to be used as a tool for digital marketing, this study guides that when social media is used, then which strategic contents are more powerful to engage customers of these two generations. For instance, if an apparel brand wish to target Generation Z, and both online and offline engagement strategies are desired, then to engage these customers on social media ‘humanization content’ should be utilized i.e., a strong brand personality should be developed; whereas when Generation Y is targeted and CBE strategy in online context needs to be developed, then marketers must focus on ‘experiential content’ to design online customer brand engagement strategies.

Limitations and Future Research Directions

There were many limitations, majorly due to the time constraint. Firstly, only two generational cohorts i.e., Gen. Y and Gen. Z were selected, whereas other cohorts of consumers like Gen. X or the baby boomers, could also be added for more concise differences and similarities. Secondly, multiple technologies are in use for marketing purposes, but only social media platform were used in this study. Thirdly, other factors like gender effects, social status, cultural differences, perceptions and usage patterns, etc. could also be studied. Lastly, due to the large sample size and complex nature of analysis, i.e., causal comparative study, this study only used one industry of the country i.e., branded apparel sector; while to make this study’s results more robust multiple industries (including cosmetics, jewelry, etc.) could have been used.

In future research should be conducted by utilizing this framework by adding different moderators like demographic factors, brand category, product usage, etc. Further this research can be extended by analyzing this framework in online as well as in offline settings separately. Another key area of research could be as this research has used Plutchik’s measure for the measurement of emotional content, the other dominant emotional measures like PAD model can be used to see whether the emotional content remains insignificant for generation Z.

References

1. Aaker, J.L. (1997). Dimensions of brand personality. Journal of Marketing Research, 34, 347 – 356.
2. Akar, E., & Topcu, B. (2011). An examination of the factors influencing consumers’ attitudes towards social media marketing. Journal of Internet Commerce, 10(1).
3. Adomavicius, G., & Tuzhilin, A. (2005). Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE transactions on knowledge and data engineering, 17(6), 734-749.
4. Aguilar, A.G., Guillén, M.J.Y., & Roman, N.V. (2016). Destination brand personality: An application to Spanish tourism. International Journal of Tourism Research, 18(3), 210-219.
5. Amin, M. (2016). Internet banking service quality and its implication on e-customer satisfaction and e-customer loyalty. International Journal of Bank Marketing, 34, 280-306.
6. Arora, N., Dreze, X., Ghose, A., Hess, J.D., Iyengar, R., …& Jing, B. (2008). Putting one-to-one marketing to work: Personalization, customization, and choice. Marketing Letters, 19(3-4), 305-321.
7. Bairrada, C.M., Coelho, A., & Lizanets, V. (2018). The impact of brand personality on consumer behavior: The role of brand love. Journal of Fashion Marketing and Management, 23(1).
8. Baldus, B.J., Voorhees, C., & Calantone, R. (2017). Online brand community engagement: Scale development & validation. Journal of Business Research, 68(5), 978-985.
9. Ball, D., Coelho, P.S., & Vilares, M.J. (2006). Service personalization and loyalty. Journal of Services Marketing, 20(6), 391-403.
10. Banahene, S. (2017). The impact of brand personality and student’s self-concept on brand engagement. International Journal of Business and Social Research, 7(8), 12-25.
11. Barreiro, S.C., & Bozutti, D.F. (2017). Challenges and difficulties to teaching engineering to generation Z: A case research. Propósitos y representaciones, 5(2), 127-183.
12. Batra, R., & Ray, M.L. (1986). Affective acceptance responses of mediating advertising. Journal of Consumer Research, 13(2), 234–249.
13. Beckers, S.F., van Doorn, J., & Verhoef, P.C. (2018). Good, better, engaged? The effect of company-initiated customer engagement behavior on shareholder value. Journal of the Academy of Marketing Science, 46(3), 366-383.
14. Blasco-Arcas, L., Hernandez-Ortega, B.I., & Jimenez-Martinez, J. (2016). Engagement platforms: The role of emotions in fostering customer engagement and brand image in interactive media. Journal of Service Theory and Practice, 26(5), 559–589.
15. Bouhlel, O., Mzoughi, N., Hadiji, D., & Slimane, I.B. (2011). Brand personality’s influence on the purchase intention: A mobile marketing case. International Journal of Business and Management, 6(9).
16. Bowen, J.T., & Chen McCain, S.L. (2015). Transitioning loyalty programs: A commentary on “the relationship between customer loyalty and customer satisfaction. International Journal of Contemporary Hospitality Management, 27, 415-430.
17. Brakus, J.J., Schmitt, B.H., & Zarantonello, L. (2009). Brand experience: What is it? How is it measured? Does it affect loyalty? Journal of marketing, 73(3), 52-68.
18. Brodie, R.J., Hollebeek, L.D., Juri?, B., & Ili?, A. (2011). Customer engagement: Conceptual domain, fundamental propositions, and implications for research. Journal of service research, 14(3), 252-271.
19. Brodie, R.J., Ilic, A., Juric, B., & Hollebeek, L. (2013). Consumer engagement in a virtual brand community: An exploratory analysis. Journal of business research, 66(1), 105-114.
20. Cheah, J.H., Sarstedt, M., Ringle, C.M., Ramayah, T., & Ting, H. (2018). Convergent validity assessment of formatively measured constructs in PLS-SEM. International Journal of Contemporary Hospitality Management, 27, 415-430.
21. Cleff, T., Lin, I.C., & Walter, N. (2014). Can you feel it? The effect of brand experience on brand equity. Journal of Brand Management.
22. Constantinides, E., Lorenzo, C., & Gómez, M.A. (2008). Social media: A new frontier for retailers? European Retail Research, 22, 1–28
23. Denton, R.E., & Voth, B. (2016). Social fragmentation and the decline of American democracy: The end of the social contract. Springer International Publication.
24. Doorn, J.V., Lemon, K.N., Mittal, V., Nass, S., Pick, D., Pimer, P., & Verhoef, P.C. (2010). Customer engagement behavior: Theoretical foundations and research directions. Journal of Service Research, 13(3).
25. Duffett, R.G. (2017). Influence of social media marketing communication on young consumers’ attitudes. Young Consumers, 18(1).
26. Gentile, C., Spiller, N., & Noci, G. (2007). How to sustain the customer experience: An overview of experience components that co-create value with the customer. European Management Journal, 25(5), 395–410.
27. Geuens, M., Weijters, B., & Wulf, K.D. (2009). A new measure of brand personality. International Journal of Research in Marketing, 26, 97-107.
28. Hair, J.F., Ringle, C.M., & Sarstedt, M. (2013). Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. Long range planning, 46(1-2), 1-12.
29. Hair Jr, J.F., Sarstedt, M., Ringle, C.M., & Gudergan, S.P. (2017). Advanced issues in partial least squares structural equation modeling. Sage publications.
30. Hapsari, R., Clemes, M., & Dean, D. (2016). The impact of service quality, customer engagement and selected marketing constructs on airline passenger loyalty. International Journal of Quality and Service Sciences, 9, 21-40.
31. Harmeling, C.M., Moffett, J.W., Arnold, M.J., & Carlson, B.D. (2017). Toward a theory of customer engagement marketing. Journal of the Academy of Marketing Science, 45(3), 312-335.
32. Hollebeek, L. (2011). Exploring customer brand engagement: Definitions and themes. Journal of Strategic Marketing, 19(7), 555-573.
33. Hollebeek, L.D., Glynn, M.S., & Brodie, R.J. (2014). Consumer brand engagement in social media: Conceptualization, scale development and validation. Journal of Interactive Marketing, 28(2), 149-165.
34. Hollebeek, L.D., & Macky, K. (2019). Digital content marketing’s role in fostering consumer engagement, trust, and value: Framework, fundamental propositions, and implications. Journal of Interactive Marketing, 45, 27–41.
35. Hollebeek, L.D., Srivastava, R.K., & Chen, T. (2019). SD logic–informed customer engagement: Integrative framework, revised fundamental propositions, and application to CRM. Journal of the Academy of Marketing Science, 47(1), 161-185.
36. Izard, C.E. (2009). Emotion theory and research: Highlights, unanswered questions, and emerging issues. Annual Review of Psychology, 60(1), 1-25.
37. Kamran, Q., & Siddiqui, D.A. (2019). The impact of emotional advertising on consumer buying behavior for home appliance products in Pakistan. Business and Management Horizons, 7(1).
38. Khan, M.J. (2017). An exploratory evidence of the types of challenges and opportunities perceived by the Small and Medium Enterprises (SMEs) in the Apparel Export Sector of Pakistan. Abasyn Journal of Social Sciences, 10(2).
39. Kim, A.J., & Ko, E. (2012). Do social media marketing activities enhance customer equity? An empirical study of luxury fashion brand. Journal of Business research, 65(10), 1480-1486.
40. Kim, P., Vaidyanathan, R., Chang, H., & Stoel, L. (2018). Using brand alliances with artists to expand retail brand personality. Journal of Business Research, 85, 424-433.
41. Kramer, T., Spolter-Weisfeld, S., & Thakkar, M. (2007). The effect of cultural orientation on consumer response to personalization. Marketing Science, 26(2), 246-258.
42. Kumar, A., Bezawada, R., Rishika, R., Janakiraman, R., & Kannan, P. (2016). From social to sale: The effects of firm-generated content in social media on customer behavior. Journal of Marketing, 80(1), 7-25.
43. Kumar, V., Rajan, B., Gupta, S., & Pozza, I. D. (2017). Customer engagement in service. Journal of Academy of Marketing Science, 47(1), 138-160.
44. Liu, H.H., & Chang, J.H. (2017). Relationship type, perceived trust, and ambiguity aversion. Marketing Letters, 28(2), pp. 255-266.
45. Liu, R.L., Sprott, D.E., Spangenberg, E.R., & Czellar, S. (2018). Engaging with brands: The influence of dispositional and situational brand engagement on customer advocacy. Customer Engagement Marketing, 269-292.
46. Luo, X. (2002). Trust production and privacy concerns on the Internet. Industrial Marketing Management, 31(2), 111–118.
47. Machleit, K.A., & Eroglu, S.A. (2000). Describing and measuring emotional response to shopping experience. Journal of business research, 49(2), 101-111.
48. Marcus, C. (2008). Generation Z: Bullied and blighted by mental illness, meet the savvy teens that don’t exist. The Sun Herald.
49. Maslowska, E., Smit, E.G., & Putte, B.V. (2016). It is all in the name: A study of consumers' responses to personalized communication. Journal of Interactive Advertising, 16(1), 74–85.
50. Mazaheri, E., Richard, M.O., Laroche, M., & Ueltschy, L.C. (2014). The influence of culture, emotions, intangibility, and atmospheric cues on online behavior. Journal of Business Research, 67(3), 253-259.
51. Milas, G., & Mlacic, B. (2007). Brand personality and human personality: Findings from ratings of familiar Croatian brands. Journal of Business Research, 60(6), 620-626.
52. Monaco, S. (2018). Tourism and the new generations: Emerging trends and social implications in Italy. Journal of Tourism Futures, 4(1), 7-15.
53. Moon, J., Chadee, D., & Tikoo, S. (2008). Culture, product type, and price influences on consumer purchase intention to buy personalized products online. Journal of Business Research, 61(1), 31-39.
54. Murdough, C. (2009). Social media measurement. Journal of Interactive Advertising, 10(1), 94-99.
55. Pansari, A., & Kumar, V. (2018). Customer engagement marketing. Customer Engagement Marketing, 1-27.
56. Peco-Torres, F., Polo-Pena, A.I., & Frias-Jamilena, D.M. (2020). Brand Personality in cultural tourism through social media. Tourism Review
57. Prentice, C., Wang, X., & Loureiro, S.M.C. (2019). The influence of brand experience and service quality on customer engagement. Journal of Retailing and Consumer Services, 50, 50-59.
58. Priporas, C.V., Stylos, N., & Fotiadis, A.K. (2017). Generation Z consumers' expectations of interactions in smart retailing: A future agenda. Computers in Human Behavior, 77, 374-381.
59. Rieke, S.E., Fowler, D.C., Chang, H.J., & Velikova, N. (2016). Exploration of factors influencing body image satisfaction and purchase intent: Millennial females. Journal of Fashion Marketing and Management: An International Journal, 20, 208-229.
60. Rossiter, J., & Bellman, S. (2012). Emotional branding pays off: How brands meet share of requirements through bonding, companionship, and love. Journal of Advertising Research, 52(3), 291-296.
61. Roy, S.K., Shekhar, V., Lassar, W.M., & Chen, T. (2018). Customer engagement behaviors: The role of service convenience, fairness and quality. Journal of Retailing and Consumer Services, 44, 293-304.
62. Samovar, L.A., Porter, R.A., & McDaniel, E.R. (2012). Intercultural communication (3rd edition). Boston.
63. Schamari, J., & Schaefers, T. (2015). Leaving the home turf: How brands can use webcare on consumer-generated platforms to increase positive consumer engagement. Journal of Interactive Marketing, 30, 20–33.
64. Schluter, M., Hinkel, J, Bots, P.W.G., & Arlinghaus, R. (2014). Application of the SES Framework for model-based analysis of the dynamics of social-ecological systems. Ecology and Society, 19(1).
65. Schmidt-Atzert, L., Peper, M., & Stemmler, G. (2014). Emotions psychology: A textbook. Kohlhammer Verlag.
66. Schreiner, M., & Riedl, R. (2018). Effect of emotion on content engagement in social media communication: A short review of current methods and a call for neurophysiological methods. Information Systems and Neuroscience, 29, 195-202.
67. Shanahan, T., Tran, T.P., & Taylor, E.C. (2019). Getting to know you: Social media personalization as a means of enhancing brand loyalty and perceived quality. Journal of Retailing and Consumer Services, 47, 57-65.
68. Sorenson, S., & Adkins, A. (2014). Why customer engagement matters so much now. Business Journal.
69. Sparks & Honey Ad Agency. (2014). Meet generation z: Forget everything you learned about Millennials.
70. Sprott, D., Czellar, S., & Spangenberg, E. (2009). The importance of a general measure of brand engagement on market behavior: Development and validation of a scale. Journal of Marketing Research, 46, 92–104.
71. Stephen, A.T. (2016). The role of digital and social media marketing in consumer behavior. Current Opinion in Psychology, 10, 17-21.
72. Tafesse, W. (2015). Content strategies and audience response on facebook. Marketing Intelligence & Planning, 33(6), 927-943.
73. Urban, G.L., Liberali, G.G., Macdonald, E., Bordley, R., & Hauser, J.R. (2014). Morphing banner advertising. Marketing science, 33(1), 27–46.
74. Van den Bergh, J., & Behrer, M. (2016). How cool brands stay hot: Branding to Generations Y and Z. Kogan Page Publishers.
75. Van den Bergh, J., & Pallini, K. (2018). Marketing to generation Z. Research World, 2018(70), 18-23.
76. Vesanen, J. (2007). What is personalization? A conceptual framework. Europeon Journal of Marketing, 41(5/6), 409–418
77. Vivek, S.D., Beatty, S.E., Dalela, V., & Morgan, R.M. (2014). A generalized multidimensional scale for measuring customer engagement. Journal of Marketing Theory and Practice, 22(4), 401-420.
78. Vivek, S.D., Beatty, S.E., & Hazod, M. (2018). If you build it right, they will engage: A study of antecedent conditions of customer engagement. Customer Engagement Marketing, 31-51.
79. Vivek, S.D., Beatty, S.E., & Morgan, R.M. (2012). Customer engagement: Exploring customer relationships beyond purchase. Journal of Marketing Theory and Practice, 20(2), 122-146.
80. Wood, S. (2013). Generation Z as consumers: Trends and innovation. Institute for Emerging Issues: NC State University, 1-3.
81. Wong, I.A. (2013). Exploring customer equity and the role of service experience in the casino service encounter. International Journal of Hospitality Management, 32, 91-101.
82. Yang, S., Lin, S., Carlson, J., & Jr. Ross, W. (2016). Brand engagement on social media: Will firms’ social media efforts influence search engine advertising effectiveness? Journal of Marketing Management, 32(5-6), 526-557.
83. Yuan, Y.H.E., & Wu, C.K. (2008). Relationship among experiential marketing, experiential value, and customer satisfaction. Journal of Hospitality & Tourism Research, 32(3).
84. Zarantonello, L., & Schmitt, B.H. (2010). Using the brand experience scale to profile consumers and predict consumer behavior. Journal of Brand Management, 17(7), 532-540.
85. Zhang, T.C., Omran, B.A., & Cobanoglu, C. (2017). Generation Y’s positive and negative eWOM: Use of social media and mobile technology. International Journal of Contemporary Hospitality Management, 29(2).