Keywords

Social Media, Customer Experience, Customer Engagement, Perceived Usefulness, Trust, Convenience, Cognitive Engagement, Affective Engagement, Loyalty.

Introduction

Today, approximately 4.48 billion people i.e., 56.7% of the total world’s population use SM (social media) sites across the globe, which is more than double from 2.09 billion in 2015. Two decades back, we had no Instagram, no Twitter, no Facebook, no TripAdvisor. Businesses back then were not apprehended by customers sharing any kind of negative experience with other customers. As, it was believed that an unhappy customer might only spread a negative word of mouth to 9-12 people who are closely related, and that was something manageable by the business because that would not lead to a decline in overall sales of the company. But, today, things are different. SM has been the buzz in marketing ever since its inception, which has now proved to be the game-changer for any business/ industry. It is not just a source of entertainment, but, a massive ocean of opportunity for both businesses and its users. By dissolving the communication barriers across continents, it is now regarded as new marketing tools for the promotion of brands, goods or service. SM networking sites constitutes an emergent interactive platform that helps in shaping the customer- brand relationship and also with other users (Hsu, 2012). So, today, if a customer wants to share a negative word of mouth about a business, image the kind of reach he would be having now via SM.

The rise of SM communication network and applications thus empowered formulation and exchange of user-generated content (Kaplan & Haenlein 2010) and also enhanced the level of involvement of the consumers with brands and also with other consumers (Hennig-Thurau et al. 2010; Hoffman & Novak 2011; Schamari & Schaefers 2015). Customers share knowledge, provide feedback, information, brand stories, recommendation or evaluate a brand, or may be co-develop a products/ service with brands on various SM platforms. This non-transactional communication of consumers or with brand is implied as consumer engagement (Schamari & Schaefers 2015). With these social interactions, online SM networking sites like Facebook, Instagram, You-tube, Twitter etc., have become an essential part for redefining customer-brand relationship and also the customer-centric marketing activities of a company.

Customer experiences (CX) on SM have become a new normal for consumer behavior in today’s world (Gensler et al. 2013; Hennig-Thurau et al. 2010). The conception of online CX is largely termed as ‘essential’ or ‘integral’ SM marketing strategy which can provide a new competitive advantage to the companies. SM websites are devised to “generate and reinforce positive brand and product messages, and have become a primary source of information for consumers whether they purchase on or offline” (Karson & Fisher, 2005). Nonetheless, there has not been much emphasis given on the need of SMCX shaping CE (Customer Engagement) behavior. This gap in the available literature has impelled the study. Therefore, with this study we attempt to examine the in-depth impact of CX on SM marketing over CE.

The rationale of this study is to reconcile the above-mentioned constructs, firstly, by providing and statistically testing the conceptual framework to identify and clarify the antecedents of both SMCX and CE. Secondly, we have discussed the transition of CX on SM platforms and its key relationship with CE. Thirdly, we try to identify the different outcomes of that relationship between the constructs. Finally, we discuss the various implications of the study (theoretical plus practical).

Research Objectives

It is imperative to understand and highlight the significance of the drivers of CE on SM platforms and also the role of CX on SM in surging that CE. Therefore, this research mainly deals with four research objectives:

1. To identify various antecedents of SMCX.

2. To identify the antecedents of CE.

3. To understand the influence of SMCX on CE by examining the relationship between the antecedents of both the constructs.

4. To identify the outcomes of CE on SMCX

Conceptual Framework and Hypothesis Development

Customer Engagement (CE): Over the past years the concept of CE was examined in various disciplines like organizational behavior, psychology, sociology etc. CE gained attention in marketing research recently and since then it is considered as an imperative construct to comprehend consumer behavior (Brodie et al., 2011). Engagement is termed as psychological state of sustained attention i.e., getting engrossed, occupied or involved in something. This internal, personal and influential state of mind is a result of CX related to a product or service. Bowden (2009) stated “CE as a psychological process that models the underlying mechanisms by which customer loyalty toward a service brand is formed in new customers, as well as the mechanisms by which that loyalty may be maintained for repeat purchase customers of a service brand”. Brodie et al. (2011) added to the definition of CE as “a psychological state that occurs by virtue of interactive, co-creative CX with a focal agent/ object (e.g., a brand)”. Further, Vivek et al. (2012) explained CE the quality of customer-brand relationship or the intensity to which a customer connects with a brand and participate in the activities and offerings to promote it. Whereas, Hollebeek (2011a) suggested engagement as an intrinsic motivation and context-dependent variable which are formulated during the brand-customer interaction. Few authors also posit the social dimension of CE which includes involvement, enjoyment, recognition, value through online customer-brand interaction.

Even though there exist lack of control, CE especially on SM, still is considered as positive notion as a higher CE led to favorable customer behavior and attitude towards a brand (Brodie et al. 2011; Gummerus et al. 2012; Seraj 2012). The notion of online CE, where customers or even the competitors are just-a-click-away, it’s not easy for a company to design a single experience which can meet all the needs of every customer. CE and experience can be both positive (i.e., providing referrals/ recommendation) or negative (i.e., spreading a bad word-of-mouth). To a large extend companies try to influence and control these experiences or engagement spread by providing customers with brand-generated SM platforms, for example, brand’s Facebook or Instagram page or Twitter handle, in order to monitor and manage customer interaction as an essential part of brand management strategy. Still, there exist a significant level of online CE and experience outside the brand’s home ambit, for example, independent consumer-generated brand communities on Facebook or Twitter or other platforms, which is difficult to control by a brand (Algesheimer et al. 2005; Van and Willemsen 2012; Schamari and Schaefers 2015). Few of the definitions throwing the light on the concept of CE are mentioned below in Table 1.

Table 1 Definitions and Dimensions of Customer Engagement
Customer Engagement Definitions
S.No.	Year	Tittle	Author	Definition	Engagement Dimensionality
1	2005	"The social influence of brand community: Evidence from European car clubs"	Algesheimer et al.	"Consumer’s Intrinsic motivation to interact and cooperate with community members"	Multidimensional: Unilateral, hedonic, social
2	2009	"An experimental study of the relationship between online engagement and advertising effectiveness"	Calder et al.	"A collection of experiences or customer believes about how side fits into his or her life"	Multidimensional: cognitive, affective
3	2010	"Engagement, Telepresence and Interactivity in Online Consumer Experience: Reconciling Scholastic and Managerial Perspectives"	Mollen and Wilson	"The cognitive and affective commitment to an active relationship with the brand as personified by the website or other computer-mediated entities designed to communicate brand value"	Multidimensional: cognitive, affective
4	2014	"Consumer brand engagement in social media: Conceptualization, scale development and validation"	Hollebeek et al.	"A consumer's positively valanced cognitive, emotional and behavioural brand-related activity during, or related to, specific consumer or brand interactions."	Multidimensional: cognitive, affective, behavioural
5	2015	"Online brand community engagement: Scale development and validation"	Baldus et al.	"The compelling, intrinsic motivation to continue interacting with an online brand community"	Intrinsic Motivation/ Affective
6	2017	"Scale development and validation for measuring online engagement"	Paruthi and Kaur	"Psychological state of mind as well as and internal emotion of the consumer"	Multidimensional: cognitive, affective
7	2021	"Revisiting the consumer brand engagement concept"	Obilo et al.	"Consumers' positive and negative behavioural interactions with a brand and all its constituent elements, beyond simple transactions, that result from their interest in and commitment to the brand"	Multidimensional: cognitive, affective, behavioural

Customer Engagement Antecedent

Cognitive and affective engagement: The previous literature on multidimensional concept of CE listed a number of antecedents out of which the three dimensions were given main emphasis to better understand the concept, they are, cognitive engagement, affective engagement and behavioural engagement (Algesheimer et al., 2005; Brodie et al., 2011a; Calder et al., 2009; Dessart et al., 2015; Hollebeek, 2011, Vivek et al., 2012). However, in this study we try to establish the relationship of CE with SMCX by examining the relationship of cognitive and affective dimension with the respective antecedents of SMCX.

Dessart et al. (2015) conceptualised affective engagement as an “enthusiasm, enjoyment pleasure and emotional affection” of someone with respect to something. Cognitive engagement, whereas, refers to “over-all mental activity, which involves attention, adsorption, awareness, cognitive processing” towards something. According to Mollen & Wilson (2010) online CE can be explained by cognitive and affective involvement and commitment of a user to nurture its customer-brand relationship via various websites or SM platforms to communicate the brand value to other users or customers. The context of online CE entrenched on SM, this study lay emphasis on SM engagement as a framework that exhibits customers’ positive or negative inclination towards a brand with regards to cognitive or affective manifestations and expressed in the form of reviews, recommendations, social influencer or as an individual endorser on SM. Thus, we can say that with the help of cognitive and affective aspects of CE which a customer experiences on various SM platform users may impart an inclusive insight towards CE on SM. Although, extant studies have taken place to establish a relationship between SM engagement, as far as we have studied, the studies concluded the brand community engagement via SM aspect and not much of the empirical research has been done to explore the CX aspect on SM to enhance CE.

Social media customer experience SMCX: SM and CX are interrelated. Since last few years, SM has been a game changer in CX purview. Now a days, customers have access to many SM platforms (like Twitter, Instagram, Facebook etc.) to post their product or brand reviews and share a positive or a negative experience. CX basically refers to the sum total of a customer’s interaction which he has with a brand across various channels, including SM sites. In 2007, Gentile et al. coined the concept of CX as, “Originated from a set of interactions between customer, product, manufacturing product companies, and other stakeholder inciting a reaction involving rational, emotional, sensorial, physical, and spiritual involvement of customer at different levels”. CX is “the internal and subjective response that customers have to any direct or indirect contact with a company”. Safko & Brake (2009) define SM as “activities, practices, and behaviours among communities of people who gather online to share information, knowledge, and opinions using conversational media”. With effective business to consumer interaction, SM helps eradicate the traditional barriers and provides new means to build customer loyalty with efficient utilisation of time and resource (Akhtar, 2011).

Global Web Index 2018, data shoes that 54% of total SM users use some or the other SM platforms to search for the information about a brand or a product. Further, a survey done by Lyfe Marketing in the same year concluded that 71% of positive CX customer base recommend a product/ service to their social circle on SM. 93% SM users’ purchase decisions are influence with reviews and recommendations shared on SM. The study also stated that there is a significant growth in business revenues that laid much emphasis on improving its SMCX. Considering the above figures, it’s imperative that SM has become a significant CX puzzle. SM influence on CX is undeniable. One does not buy a product/ service on SM platforms within few minutes of their visit, they collect necessary information on SM like reviews, recommendations, influencers posts on SM before making a purchase decision. So, it is important how a brand administer its SM information to form an overall CX. The above argument signifies the comprehensive role of CX in SM marketing activities that encourage CE and loyalty. Therefore, with this study we strive to identify the factors that can leverage CE on SM and its outcomes.

SMCX Antecedent variables

Perceived usefulness (PU): According to Technology Acceptance Model, a user behavioural intention in order to adopt a given technology can be understood by his perception on the PU and ease-of-use of that technology (Özbek et al., 2015; Abdullah et al., 2016). Davis (1989) defined PU as “the degree to which a person believes that using a particular system would enhance his or her job performance” i.e., PU has a positive effect on behavioural intention. The above definition is in accordance to the dictionary definition of the word usefulness: "capable of being used advantageously".

PU as an important construct gained lots of attention from number of researchers across all fields (Figl & Derntl, 2011; Khayati & Zouaoui, 2013). Its relationship with SM has been backed by various scholars in their recent studies. For Instance, S.-H. Liu et al. (2009) argued that PU has notable effects on an individual’s behavioural intention to use SM platforms. Seif, et al. (2012) also advocate that there exists a direct impact of PU in acceptance and use of SM networking sites to create a positive experience. Thus, PU of using SM networking sites has become our first dimension to evaluate its impact on CE. Hence, we propose the following hypothesis.

H1a: Perceived usefulness is positively related to Cognitive Engagement.

H2a: Perceived usefulness is positively related to Affective Engagement.

Convenience: The notion of convenience was first coined by Copeland (1923) which signified the measure of time and effort that a customer spends in purchasing a particular product. The online convenience on the other hand, refers to, “The capability to ease consumers’ time, energy, and effort while purchasing goods or products online” (Seiders et al., 2007). Due to the lack of time and effort that one can spare to buy a product, convenience today act as a primary benefit that attracts a customer the most and drives his purchase behaviour (Berry & Cooper, 1990). Jiang et al. (2013) in his study developed 5 main categories for convenience in relation to customer buying decision making, they are: “access, search, evaluation, transaction, and possession/post-purchase convenience”.

The prevailing literature on convenience indicate its significant role in influencing customer attitude, purchase decision making, customer-brand relationship building & strengthening, customer retention (Keaveney, 1995; Pan and Zinkhan, 2006; Seiders et al., 2007; Lim et al., 2015; Workman et al., 2018). The existing empirical researches also provided substantial grounds of online convenience regarding availability and accessibility 24*7 of online products forming a positive impact on customer attitude and experience (SivaKumar & Gunasekaran, 2017). Thus, we included convenience in this study as an important dimension in forming SMCX and determining CE.

H1b: Convenience is positively related to Cognitive Engagement.

H2b: Convenience is positively related to Affective Engagement

Trust: Moorman et al. (1993) explained trust as a level of confidence that an individual has over another individual in terms of honesty, reliability and fairness in the exchange transaction. Rousseau et al. (1998) discussed trust as “A psychological state comprising the intention to accept vulnerability based on positive expectations of the intentions or behaviours of another”. Customer trust is an intrinsic characteristic i.e., the degree to which they are confident that the brand is honest and competent in providing the claimed services (Morgan & Hunt, 1994).

On SM customer encounter product related information through various touchpoints which motivate their purchase behaviour and CE if they trust the information provided is true. One of a significant dimension according to CX theory, is customer-brand trust (Bleier et al., 2019). The theory suggests that a customer holding a better trust in a brand is more likely to obtain higher positive CX. So, we can say trust is positively related to SMCX and it plays a vital role in driving online customer purchase behaviour. Whereas, the theory of CE illustrates, a customer is only engaged if they get any direct or may be indirect benefit from a product (Kumar & Pansari 2016). Thus, in this study trust is considered as an important dimension to understand the impact of SMCX on CE. So, we propose the following hypothesis.

H1c: Trust is positively related to Cognitive Engagement.

H2c: Trust is positively related to Affective Engagement.

Consequences of SMCX and CE

Loyalty: Customer loyalty, as a standalone notion, demonstrate an individual’s perception and non-random buying behaviour towards a brand. Oliver et al. (1999) defined loyalty as “a deeply held commitment to re-buy or re-patronize preferred products/services consistently in the future”. In addition to that, Too et al. (2001) discussed customer loyalty in context of relationship marketing as “a multifaceted construct which takes into account both psychological and behavioural components leading to repeat patronage”.

Many studies over a period of time emphasized on the importance of CE to influence customer loyalty towards a brand or product, however, they studied the brand-community engagement aspect of the CE only (both online and offline). The extant literature elaborates that the CE in various brand community engagement has a substantial impact on customer loyalty (Brodie et al., 2011; McAlexander et al., 2002). Further, Casalo et al. (2007) established that higher the brand community engagement, higher will be the influence on customer loyalty for the brand. Furthermore, Tsiotsou (2016) in his study stated the existence of positive CE and loyalty relationship in reference to brand community in both online and offline engagement environment. All the above study reflects the brand-community engagement and loyalty as a major outcome. In our study we endeavour to establish the positive SMCX will influence CE on SM and the consequence of the relationship is customer loyalty. Thus, the following hypothesis.

H3: Cognitive engagement is positively related to Loyalty.

H4: Affective engagement is positively related to Loyalty.

The list of variables used in the study, their definitions and measurements are listed in Table 2, (Figure 1).

Table 2 Variables Used in Conceptual Framework and their Measurements
Variables used in Conceptual Framework, their definition, suggested scale and relationship with CE
S.no.	Variables used in the study	Definition	Suggested scale	Relationship with CE
1	Customer experience	"Holistic in nature involving the customer’s cognitive, affective, emotional, social, and physical responses to the entity, product, or service" (Verhoef et al. 2009)	Klaus and Maklan (2011) proposed 19 items, 7-point Likert scale measuring various dimensions of experience with a reliability score of 0.93.	“CX is a cognitive measure that is an outcome of the firm’s actions and may not include the actions of the customer toward the firm. However, CE is a measure of the customers’ actions toward the firm”.
2	Perceived Usefulness	"The degree to which a person believes that by use of a specific product would enhance his effectiveness" (Davis, 1989).	Davis (1989) in his study, suggested two 6- item scale for measuring PU, ease of use which display high correlation between PU and usage behavior for a product, with a reliability score of .98 for PU.	“CE is a significant consequence of customer satisfaction which is influenced by perceived usefulness and perceived ease of use”.
3	Convenience	"The time and effort that consumers invest in purchasing a product rather than a characteristic or attribute of a product" (Brown 1990).	Seiders et al. (2007) developed 17 items, 5-point Likert scale measuring 5 crucial dimensions of convenience (access, transaction, benefit, decision, post purchase benefit) with a reliability score of 0.75.	“Convenience shows the amount of time and effort invested by the customer to purchase a good/ service. A high on convenience is a positive predictor of customer satisfaction, which can lead to high CE”.
4	Trust	"Willingness to rely on an exchange partner in whom one has confidence" (Moorman et al. (1993)	Garbarino and Johnson (1999) suggested a 5-point Likert scale to calculate customer trust consisting dimensions like risk involved, quality, confidence, reliability. The reliability score was above 0.75	“Trust is the breadth of the attitude toward the brand, which is embedded in CE in the form of enhanced purchases, referrals, and word-of-mouth”.
5	Cognitive engagement	“A consumer's level of brand-related thought processing and elaboration in a particular consumer/brand interaction” (Hollebeek L.et al., 2014).	Hollebeek et al. (2014) proposed a 7-point Likert scale to manifest CE by evaluating cognitive, affective and behavioral aspect of CE, with an average reliability of 0.9.	“Cognitive Engagement is a way to use the brain’s ability to think about itself as a way to form a connection with a customer and create brand engagement and conversions”.
6	Affective engagement		Hollebeek et al. (2014) proposed a 7-point Likert scale to manifest CE by evaluating cognitive, affective and behavioral aspect of CE, with an average reliability of 0.9.	“Affective engagement is the emotional bond between a consumer and a brand, which represents a direct result of the immersion that assumes a proactive and favorable psychological state for the consumer”.
7	Loyalty	"A favorable attitude toward a brand resulting in consistent purchase of the brand over time" (Assael, 1992)	Oliver (1997), suggested a 4-dimensional, 5-point Likert scale with a reliability of over 0.78, measuring cognitive loyalty, affective loyalty, conative loyalty, action loyalty.	“Loyalty measures only repeated purchase transactions of the customer and focuses only on the revenue of the firm. CE focusses on four different behaviors of customer (purchases, referrals, influence, and feedback). Further, CE goes beyond the revenue of the firm and looks at overall firm profits”.

Measures and Sampling Techniques

For the current research study, primary data was collected using the measuring items which were obtained, adopted and modified from prevailing studies to confirm validity and quality of the instrument. Thus, a well-structured online questionnaire was developed covering the demographic characteristics of respondents, as well as various dimension of Perceived usefulness, Convenience, Trust, Cognitive, Affective engagement and Loyalty. The items incorporated statements to be rated by respondents on 5-point Likert Scale ranging 1 (=Strongly Disagree) to 5 (=Strongly Agree). In total, 21 items were developed in the survey questionnaire.

Since the number of SM users are very high, non-probability random sampling technique using snowball data collection method was applied in the study. The validity of all the constructs considered in the study was discussed and tested with a panel of experts. A pilot study was also done on first 50 responses in order to establish the reliability of the study. The value of Cronbach’s alpha(α) was observed to be 0.826 which suggest existence of high reliability of the items and study.

Data collection and sample characteristics: Considering the purpose of this study, to analyse the impact of SMCX on CE, we employed quantitative research through a survey approach for collecting the data. The population considered for the study was active SM users on various SM platforms like Facebook, Twitter, Instagram etc. The respondents were asked for voluntary participation and were assured of the anonymity and confidentiality of the responses submitted by them. The researcher of the study avoided use of any kind of hypothetical question in the questionnaire and respondents were asked to response the question based on their personal experience solely. The data for this study was collected in the time period of two month and the data was analysed collectively for testing the proposed hypothesis. With regards to the premises of research instrument, the questionnaire was divided into 3 sections, the initial section inquired about the SM platforms they are most active on, number of hours spent on SM sites every day, what interests them most on SM sites, and their buying frequency on SM sites. The next section covered the items related to the variables included in the study and last section focused on the evaluation of the demographic profile of the respondents Table 3.

Table 3 Demographic Profile
Descriptions (n=409)	Frequency	Percentage (%)
Gender
Male	216	52.81%
Female	193	47.19%
Age
Below 20	41	10.02%
20 - 40 years old	228	55.74%
40 - 60 years old	106	25.92%
Above 60	34	8.32%
Education
Under Graduation	53	12.96%
Graduation	231	56.48%
Post-Graduation	116	28.36%
Others	9	2.20%
Employment
Salaried	211	51.59%
Self-employed	96	23.47%
Unemployed	34	8.31%
Retired	9	2.20%
Homemaker	37	9.05%
others	22	5.38%

Measurement Evaluation, Reliability, and Validity

Exploratory factor analysis approach: To execute the test careful data screening, editing (by identifying the missing or error values) and coding was done for the responses collected. For analysis SPSS 24.0 was used. We performed EFA (Exploratory Factor Analysis) to refine the measuring items forming a construct and also to assure the factor structure using varimax rotation. All the measuring items were included in EFA and the results extracted 6 factors in all without any cross-loading of the factors. Hair et al. (2010) argued that a factor can be called a construct if its eigenvalue is > 1.0. The communalities extraction loading results range between 0.75- 0.96, which signifies highly positive results and also indicate the suitability of EFA technique used in the study. Values of EFA for individual item is mentioned in. The basic recommended ideal percentage for total variance explained is 60%, whereas our six-factor model explained 72.46% of the variance indicating good results.

Further, to evaluate the adequacy and the appropriateness of the data collected from the survey, Kaiser-Meyer Olkin (KMO), Bartlett's Test of Sphericity was performed. The results of KMO and Bartlett's Test were greater than the cut-off level and are acceptable (0.742) along with significant p-value, df= 276, suggesting there exist a substantial correlation in the data of the study Figure 2.

The EFA values also signifies the existence of construct validity especially discriminant and convergent validity of the data as all the factor loadings are > 0.50, which validates convergent validity of all the six constructs used in the study and in conceptual model. The author then performed Cronbach’s alpha (α) test of reliability to evaluate the construct reliability of the data. The results show a satisfactory outcome as the value range between 0.75 – 0.93, suggesting reliability of the data set, as it is recommended that the coefficient value closer to 1.0 reflects higher internal consistency of the variable. The variable and item wise results of EFA, mean, standard deviation and Cronbach’s alpha (α) values are listed in Table 4.

Table 4 Construct, Items, EFA, Mean, SD, Reliability.
Construct, measurement items, reliability, and validity estimates
Constructs	Items	EFA	Mean	SD	Cronbach’s alpha (α)
Perceived Usefulness	PU1	0.839	3.464	0.924	0.761
	PU2	0.813
	PU3	0.801
Convenience	CON1	0.855	3.962	0.843	0.837
	CON2	0.838
	CON3	0.892
Trust	TRST1	0.821	3.193	0.841	0.812
	TRST2	0.813
	TRST3	0.774
Cognitive Engagement	CE1	0.778	3.713	0.938	0.762
	CE2	0.829
	CE3	0.813
Affective Engagement	AE1	0.781	3.501	0.808	0.838
	AE2	0.775
	AE3	0.784
Loyalty	LYT1	0.834	3.074	0.877	0.921
	LYT2	0.886
	LYT3	0.888
	LYT4	0.861
	LYT5	0.874

Confirmatory Factor-Analytic Approach

To establish unidimensionality, measure composite reliability (CR), and test convergent and discriminant validity, the confirmatory factor analytic (CFA) approach was used, which is an expansion of EFA approach. The data was analysed using AMOS-26. The CFA model, which includes six components, is depicted in Figure 2 and discussed in Table 5. The goodness-of-fit indices (χ 2 = 338.313, df = 154, CMIN/DF = 2.197, significance level at p < .001, RMSEA =.054; GFI = 0.927, AGFI = 0.901, CFI = 0.951, TLI = 0.939, NFI = 0.914, IFI = 0.951, RMR = .029) revealed that the model fit the data well; all factor loadings of the items for each latent component exceeded the suggested threshold of (Ford et al., 1986). Further, the results of AVE (Average Variance Extracted) for each variable range between 0.5 - 0.75, exceeding the widely accepted minimum cut-off value of 0.5. Hence, convergent validity and discriminant validity were supported. The CR of Perceived usefulness is 0.763, Convenience is 0.838, Trust is 0.812, Cognitive Engagement is 0.765, Affective engagement is 0.815 and Loyalty is 0.925. The above values of CR denote all the constructs have good reliability in measurement model. Thus, we can establish the reliability of data and of each construct used in the study. The values of standardized estimates, CR, AVE, and factor correlation matrix are discussed in Table 5 & 6, Figure 3.

Table 5 Results of CFA - Composite Reliability, Average Variance Extracted, Standardized Loadings
Construct, measurement items, Standardized loadings, CR, AVE
Constructs	Items	Standardized loadings	CR	AVE
Perceived Usefulness	PU1	0.797	0.763	0.519
	PU2	0.695
	PU3	0.663
Convenience	CON1	0.773	0.838	0.634
	CON2	0.769
	CON3	0.844
Trust	TRST1	0.802	0.812	0.591
	TRST2	0.762
	TRST3	0.741
Cognitive Engagement	CE1	0.614	0.765	0.523
	CE2	0.811
	CE3	0.733
Affective Engagement	AE1	0.75	0.815	0.595
	AE2	0.844
	AE3	0.715
Loyalty	LYT1	0.78	0.925	0.712
	LYT2	0.869
	LYT3	0.881
	LYT4	0.811
	LYT5	0.85

Table 6 Correlation Between Constructs (Off-Diagonal)
	AE	PU	CON	TRST	CE	LYT
AE	0.772
PU	0.123	0.721
CON	0.052	-0.053	0.796
TRST	0.658	0.11	0.1	0.769
CE	0.317	0.152	0.177	0.254	0.724
LYT	0.148	0.097	0.098	0.088	-0.002	0.844

Structural equation modelling: Next, author performed Structural Equation Modelling (SEM) to evaluate the impact of independent variables on dependent variables and their interdependency with the help of multiple regression with CFA using SPSS AMOS 26.0. summarises the results of structural model of the study. Maximum likelihood method was employed to evaluate the model and for overall model fit index. The model fit index is based on some of the significant indices that represent a good model fit and they are GFI, AGFI, RMSEA, CFI, TLI, IFI. The model score is in line with standardized regression coefficients (beta). The model fit values are (χ 2 = 324.484, df = 158, with significance level at p < .001 suggesting highly significant. The CMIN/DF value 2.054 indicating a good fit. The other important indices like GFI = 0.929, CFI = 0.955, TLI = 0.938, IFI = 0.956 are all above the minimum required limit of 0.9. Whereas, AGFI = 0.905 > 0.80 indicating a good fit. Moreover, the Root Mean Square Error of Approximation (RMSEA) = 0.051 also suggesting that the data fit well in the structural model. The summary of the model fit indices Figure 4 & 5.

Hypothesis Testing

The main objective of the study is to find out the impact of SMCX on CE. For the study, we further identified two key dimensions or antecedents of CE i.e., cognitive dimension of CE and affective or emotional dimension of CE. The results of the study are a new revelation which open up scope for further in detailed research in the field of evaluating CE on various SM networking sites and on CX in related fields.

In total eight hypothesis were formulated to statistically test the impact of SMCX on CE. Table 7 represents the summary of path coefficient results of hypotheses tested along with statistics related to the same. The results show Perceived Usefulness and Convenience has a positive influence on Cognitive engagement, confirmed by hypotheses H1a (p = **, β = 0.130, t = 2.092) and H1b (p = **, β = 0.151, t = 2.537). Whereas, Perceived Usefulness and Convenience does not influence Affective engagement, rejecting hypotheses H2a (p = 0.258, β = 0.057, t = 1.068) and H2b (p = 0.915, β = -0.005, t = 0.106). However, Trust influence both cognitive and affective engagement on SM networking platforms, supported by hypothesis H1c (p= ***, β = 0.258, t = 4.212) and H2c (p= ***, β = 0.661, t = 10.038) denoting highly significant level. Further, the hypothesis testing results show that Loyalty is influenced by Affective engagement confirmed by hypothesis H4 (p= ***, β = 0.161, t = 2.829) but not influenced by Cognitive engagement, rejected by hypothesis H3 (p=0.442, β = -0.044, t = 0.768).

Table 7 Path Coefficients and their Significance
Hypothesis	Path Description	Coefficient	t value	P value	Supported/ Not supported
H1a	Perceived Usefulness ----→ Cognitive Engagement	0.130	2.092	**	Supported
H2a	Perceived Usefulness ----→ Affective Engagement	0.057	1.068	0.258	Not Supported
H1b	Convenience ----→ Cognitive Engagement	0.151	2.537	**	Supported
H2b	Convenience ----→ Affective Engagement	- 0.005	- 0.106	0.915	Not Supported
H1c	Trust ----→ Cognitive Engagement	0.258	4.212	***	Supported
H2c	Trust ----→ Affective Engagement	0.661	10.038	***	Supported
H3	Cognitive Engagement ----→ Loyalty	-0.044	0.768	0.442	Not Supported
H4	Affective Engagement ----→ Loyalty	0.161	2.829	***	Supported

Discussion

With the growing popularity and sustainable growth, SM has become a crucial marketing tool where consumers share their experiences related to a brand or a product. This study is an attempt to explore all the possible explanations to analyse the impact of SMCX on CE. Interestingly, the results of the study found that there is a positive influence of perceived usefulness on the cognitive engagement of the customer i.e., the customer need influence the rational thinking or engagement of the customer, but it does not impact the affective or emotional aspect of engagement. The results are in accordance with the previous findings Yang et al. (2017), Andonova & Yana (2016), who verified in their research that perceived usefulness has a positive impact on over all CE, but in those studies also they did not provide a probable explanation to which dimension of CE is actually influence and which dimension is not influence by perceived usefulness of customer. Hence, our study lay foundation to the in-depth exploration of the first crucial impact of SMCX on CE, which is till now unexplored in the prevailing studies.

The study also found that customer’s convenience to acquire a product from SM networking site has a positive and significant influence on cognitive engagement of the customers but it does not have a significant influence on the affective engagement of the customers. That means, if the availability of the product is convenient to the customer it will influence the rational thinking and purchase decision of the customer, but it will not have an impact on emotional engagement of the customer to a particular brand or product. The study is in line with some previous findings of the study by Yang et al. (2017) i.e., convenience has no influence on CE, yet again there exist a gap in these studies i.e., not calculating the detailed impact of convenience on the cognitive and affective aspect of CE, which is empirically and statistically proved in this current research study. However, Trust as an imperative antecedent of SMCX has a positive and significant influence on both cognitive and affective dimension of CE, i.e., Trust impacts the overall CE on SM networking site. The above finding is consistence with various previous studies by Al-Debei et al. (2015), Lin (2011) and Limbu et al. (2012).

Surprisingly, when evaluating the consequence of the relationship impact of SMCX and CE, loyalty as an outcome is influenced with the affective dimension of the CE and not with the cognitive dimension of CE. Since cognitive thinking process involves shrewd calculations of the engagement outcomes whereas Loyalty is internal and not calculative in nature. It is mainly driven by emotion, excitement, and feelings which is in fact the affective dimension of the CE. Thus, Affective engagement has a positive and significant impact on customer loyalty towards a brand or a product. Many studies have lined their findings on the significant impact of over-all CE on customer loyalty, nonetheless, previous studies ignored the individual impact of CE dimensions on loyalty, which is acutely and statistically tested in this study.

Theoretical, Managerial Implications

The study contributes and also suggests several applications to both academic and practical consequences. First, from theoretical point, the current research study significantly contributes to the existing literature on SMCX, CE and their various antecedents and outcomes by providing systematic conceptualization and validation to the above concepts. Second, by suggesting a new conceptual framework model and statistically examining it based on the empirical and source credible data collected from well-structured survey. Third, by individually examining the relationship of various antecedents of SMCX and CE to further investigate the individual impact of each antecedent on various dimensions of CE which provides grounds for future empirical researches. The findings of our study can assist as proxy to evaluate the customer perception about SMCX, i.e., what motivates them or impact them the most, rationally and emotionally to participate with a brand/ product on SM. Finally, by contributing to the literature of customer loyalty. Specifically, providing evidences that affective engagement has a meaningful and significant impact than cognitive engagement on customer loyalty. The finding is novel and stimulating, which pave ways for future study including some more insightful factors of SMCX that may impact individual CE dimensions.

Further, this study contributes in a number of ways from managerial point of view also. First, the conceptual model provides a metrics to the businesses to better comprehend the factors influencing CE on SM, and it also improves the managerial understanding of the relationship outcome to influence customer loyalty. As, customer engaged on SM platforms with a positive CX can act as real-time economic brand endorsers to improve product sales, organization financial performance and can also provide a competitive advantage to the businesses. Thus, the above model can act as a gismo while designing SM marketing strategies. Second, the findings of the study are equally interesting from a managerial point of view also, as it provides meaningful comprehensions as to what factor influence which dimension of CE and if used tactfully by altering SM engagement strategies, it can further result into enhancing more and more CE on SM platforms. Lastly, the result also put emphasis on the importance of cognitive dimension in the initial stages of the CE process on SMCX, which further (in later stages) lay foundation for affective engagement of a customer with a brand/ product which ultimately influence customer loyalty. This finding provides new directions to the managers to alter their SM marketing strategies to add customer value and CX on various SM networking sites Table 8.

Table 8 Transportation Services
		Frequency	Percent	Valid Percent	Cumulative Percent
Freight Consolidation	very important extremely important	4 21	16.0 84.0	16.0 84.0	16.0 100.0
	Total	25	100.0	100.0
Customs Clearance	very important extremely important	5 20	20.0 80.0	20.0 80.0	20.0 100.0
	Total	25	100.0	100.0
Track Trace	very important extremely important	5 20	20.0 80.0	20.0 80.0	20.0 100.0
	Total	25	100.0	100.0
Freight Forwarding	very important extremely important	5 20	20.0 80.0	20.0 80.0	20.0 100.0
	Total	25	100.0	100.0

Conclusion and Recommendations

The ubiquity characteristic of SM platform, thus make it the biggest platform for business-customer interaction and consequently the most effective and crucial tool for the promoting brands, goods or service. Since, there exist a substantial impact of SM in shaping CX, the advanced technology like SM marketing can effectively enrich the customers’ knowledge and develop positive CX. SM marketing strategy can provide a new competitive advantage to the companies by getting engaged in the right SM channel. As a result, business can acquire high growth and a dominant position in the market as compared to its competitors. Companies who are able to profoundly comprehend plus integrate SM with positive CX can actually motivate customer loyalty by engaging and encouraging them to participate at a certain level and spread positive word of mouth about the brand. It can benefit the business in the following ways, firstly, company can find the gaps in brand performance with the help of effective market research. Secondly, can reach out to the most likely customer in every corner of the market. Thirdly, develop and foster customer relation with a brand. Lastly, enhance CX with the brand by positive CE. Thus, we can say, that by developing right SM marketing strategies, a company can frame effective decision making and can focus on providing positive CX on SM and also enhance right dimension of CE with the brand/ product.

References

Abdullah, D., Jayaraman, K., & Kamal, S. B. M. (2016). A conceptual model of interactive hotel website: The role of perceived website interactivity and customer perceived value toward website revisit intention. Procedia economics and finance, 37, 170-175.

Indexed at, Google Scholar, Cross Ref

Akhtar, S. (2011). Social Media and Brand Loyalty. Retrieved December 18, 2019.

Google Scholar

Al-Debei, M. M., Akroush, M. N., & Ashouri, M. I. (2015). Consumer attitudes towards online shopping: The effects of trust, perceived benefits, and perceived web quality. Internet Research, 25(5), 707-733.

Indexed at, Google Scholar, Cross Ref

Algesheimer, R., Dholakia, U. M., & Herrmann, A. (2005). The social influence of brand community: Evidence from European car clubs. Journal of marketing, 69(3), 19-34.

Indexed at, Google Scholar, Cross Ref

Andonova, Y. (2016). Customer engagement: perceived benefits and effect of individual and brand personality on engagement behaviors.

Indexed at, Google Scholar

Berry, L. L., & Cooper, L. R. (1990). Competing with time-saving service. Business, 40(2), 3-7.

Google Scholar

Bleier, A., Harmeling, C. M., & Palmatier, R. W. (2019). Creating effective online customer experiences. Journal of marketing, 83(2), 98-119.

Indexed at, Google Scholar, Cross Ref

Bowden, J. L. H. (2009). The process of customer engagement: A conceptual framework. Journal of marketing theory and practice, 17(1), 63-74.

Indexed at, Google Scholar, Cross Ref

Brodie, R. J., Hollebeek, L. D., Jurić, B., & Ilić, A. (2011). Customer engagement: Conceptual domain, fundamental propositions, and implications for research. Journal of service research, 14(3), 252-271.

Google Scholar

Calder, B. J., Malthouse, E. C., & Schaedel, U. (2009). An experimental study of the relationship between online engagement and advertising effectiveness. Journal of interactive marketing, 23(4), 321-331.

Indexed at, Google Scholar, Cross Ref

Copeland, M. T. (1923). Relation of consumers' buying habits to marketing methods. Harvard business review, 1(2), 282-289.

Google Scholar

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.

Indexed at, Google Scholar, Cross Ref

Dessart, L., Veloutsou, C., & Morgan-Thomas, A. (2015). Consumer engagement in online brand communities: a social media perspective. Journal of Product & Brand Management, 24(1), 28-42.

Indexed at, Google Scholar, Cross Ref

Figl, K., & Derntl, M. (2011, October). The impact of perceived cognitive effectiveness on perceived usefulness of visual conceptual modeling languages. In International Conference on Conceptual Modeling (pp. 78-91). Berlin, Heidelberg: Springer Berlin Heidelberg.

Indexed at, Google Scholar, Cross Ref

Gensler, S., Völckner, F., Liu-Thompkins, Y., & Wiertz, C. (2013). Managing brands in the social media environment. Journal of interactive marketing, 27(4), 242-256.

Indexed at, Google Scholar, Cross Ref

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.

Indexed at, Google Scholar, Cross Ref

Gummerus, J., Liljander, V., Weman, E., & Pihlström, M. (2012). Customer engagement in a Facebook brand community. Management Research Review, 35(9), 857-877.

Indexed at, Google Scholar, Cross Ref

Hennig-Thurau, T., Malthouse, E. C., Friege, C., Gensler, S., Lobschat, L., Rangaswamy, A., & Skiera, B. (2010). The impact of new media on customer relationships. Journal of service research, 13(3), 311-330.

Indexed at, Google Scholar, Cross Ref

Hollebeek, L. D. (2011). Demystifying customer brand engagement: Exploring the loyalty nexus. Journal of marketing management, 27(7-8), 785-807.

Indexed at, Google Scholar, Cross Ref

Hsu, Y. L. (2012). Facebook as international eMarketing strategy of Taiwan hotels. International journal of hospitality management, 31(3), 972-980.

Indexed at, Google Scholar

Jiang, L. A., Yang, Z., & Jun, M. (2013). Measuring consumer perceptions of online shopping convenience. Journal of Service management, 24(2), 191-214.

Indexed at, Google Scholar, Cross Ref

Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of Social Media. Business horizons, 53(1), 59-68.

Indexed at, Google Scholar, Cross Ref

Karson, E. J., & Fisher, R. J. (2005). Predicting intentions to return to the web site: extending the dual mediation hypothesis. Journal of Interactive Marketing, 19(3), 2-14.

Indexed at, Google Scholar, Cross Ref

Keaveney, S. M. (1995). Customer switching behavior in service industries: An exploratory study. Journal of marketing, 59(2), 71-82.

Indexed at, Google Scholar, Cross Ref

Khayati, S., & Zouaoui, S. K. (2013). Perceived usefulness and use of information technology: The moderating influences of the dependence of a subcontractor towards his contractor. Journal of Knowledge Management, Economics and Information Technology, 3(6), 68-77.

Indexed at, Google Scholar

Kumar, V., & Pansari, A. (2016). Competitive advantage through engagement. Journal of marketing research, 53(4), 497-514.

Indexed at, Google Scholar, Cross Ref

Lim, Y. M., & Cham, T. H. (2015). A profile of the Internet shoppers: Evidence from nine countries. Telematics and Informatics, 32(2), 344-354.

Indexed at, Google Scholar, Cross Ref

McAlexander, J. H., Schouten, J. W., & Koenig, H. F. (2002). Building brand community. Journal of marketing, 66(1), 38-54.

Indexed at, Google Scholar, Cross Ref

Mollen, A., & Wilson, H. (2010). Engagement, telepresence and interactivity in online consumer experience: Reconciling scholastic and managerial perspectives. Journal of business research, 63(9-10), 919-925.

Indexed at, Google Scholar, Cross Ref

Moorman, C., Deshpande, R., & Zaltman, G. (1993). Factors affecting trust in market research relationships. Journal of marketing, 57(1), 81-101.

Indexed at, Google Scholar, Cross Ref

Morgan, R. M., & Hunt, S. D. (1994). The commitment-trust theory of relationship marketing. Journal of marketing, 58(3), 20-38.

Indexed at, Google Scholar, Cross Ref

Muntinga, D. G., Moorman, M., & Smit, E. G. (2011). Introducing COBRAs: Exploring motivations for brand-related social media use. International Journal of advertising, 30(1), 13-46.

Indexed at, Google Scholar

KOÇ, F., ŞAHİN, N. K., & KAŞ, E. THE EFFECTS OF PERCEIVED RISK AND COST ON TECHNOLOGY ACCEPTANCE: A STUDY ON TOURISTS’USE OF ONLINE BOOKING Volkan ÖZBEK1 Mustafa GÜNALAN2.

Google Scholar

Rousseau, D. M., Sitkin, S. B., Burt, R. S., & Camerer, C. (1998). Not so different after all: A cross-discipline view of trust. Academy of management review, 23(3), 393-404.

Indexed at, Google Scholar, Cross Ref

Safko, L., & Brake, D. K. (2009). The Social Media Bible. 1: a upplagan. Hoboken.

Google Scholar

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(1), 20-33.

Indexed at, Google Scholar, Cross Ref

Seiders, K., Voss, G. B., Godfrey, A. L., & Grewal, D. (2007). SERVCON: development and validation of a multidimensional service convenience scale. Journal of the academy of Marketing Science, 35, 144-156.

Indexed at, Google Scholar, Cross Ref

Seraj, M. (2012). We create, we connect, we respect, therefore we are: intellectual, social, and cultural value in online communities. Journal of Interactive Marketing, 26(4), 209-222.

Indexed at, Google Scholar, Cross Ref

SivaKumar, A., & Gunasekaran, A. (2017). An empirical study on the factors affecting online shopping behavior of millennial consumers. Journal of Internet Commerce, 16(3), 219-230.

Indexed at, Google Scholar, Cross Ref

Tsiotsou, R. H. (2016). The social aspects of consumption as predictors of consumer loyalty: Online vs offline services. Journal of Service Management, 27(2), 91-116.

Indexed at, Google Scholar, Cross Ref

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.

Indexed at, Google Scholar, Cross Ref

Workman, J. E., & Lee, S. H. (2018). Attitudes toward technology, digital activities, and use of internet shopping features among Chinese and US college students. Chinese Consumers and the Fashion Market, 73-94.

Indexed at, Google Scholar, Cross Ref

Yang, S. B., Hlee, S., Lee, J., & Koo, C. (2017). An empirical examination of online restaurant reviews on Yelp. com: A dual coding theory perspective. International Journal of Contemporary Hospitality Management, 29(2), 817-839.

Google Scholar

Received: 02-Sep-2023, Manuscript No. ASMJ-23-13263; Editor assigned: 04-Sep-2023, PreQC No. ASMJ-23-13263(PQ); Reviewed: 18- Sep-2023, QC No. ASMJ-23-13263; Revised: 22-Sep-2023, Manuscript No. ASMJ-23-13263(R); Published: 29-Sep-2023