Influence of E-Wom Conversations from Social Platforms and E-Commerce Platforms on Purchasing Choice

Asif Iqbal; Harshmit Kaur Saluja; Raji

Review Article: 2025 Vol: 29 Issue: 1

Influence of E-Wom Conversations from Social Platforms and E-Commerce Platforms on Purchasing Choice

Asif Iqbal, IMS University of Lucknow, Lucknow

Harshmit Kaur Saluja, Institute of Engineering and Technology Lucknow

Raji, Institute of Engineering and Technology Lucknow

Citation Information: Iqbal, A., Kaur, S.H., & Raji. (2025). Influence of e-wom conversations from social platforms and ecommerce platforms on purchasing choice. Academy of Marketing Studies Journal, 29(1), 1-16.

Abstract

The implications of word-of-mouth marketing affect consumers' buying decisions and have become an important tool for online companies to promote their products on digital platforms. This research study analyses the influence of E-WOM through social media sites and online commerce sites on smartphone buying decisions. 382 respondent's data were collected and confirmatory factor analysis was used to validate the data. Multiple regression analysis was utilized to analytically test the outcome of independent elements (Quality of E-WOM, Quantity of E-WOM, E-WOM attitude towards the product, E-WOM attitude towards the website, and Format of E-WOM) on online purchase intent (dependent factor). According to the findings, three factors including Quality of E-WOM, E-WOM Quantity, and E-WOM attitude towards the website have considerable effects on purchasing choice of smartphone. In contrast, E-WOM attitudes towards the product and format of E-WOM do not have such an influence on purchase intent. This research study clearly explains that E-WOM information and opinions of people on these digital platforms may be of great importance to other individuals as it will change their buying intent and perceptions towards different products and affect their decisions to buy.

Keywords

Consumer Purchase Intention, Quality Of E-WOM, Quantity Of E-WOM, E-WOM Attitude, Format Of E-WOM, Purchase Decision.

Introduction

Word of mouth tends to be quite influential over the years in changing the minds of consumers for making any purchase-related decision. In today’s scenario, consumer decisions are affected by others' word of mouth from their peer groups as most of their reviews are genuinely based on their past experiences. The exchange of reviews or opinions about a product or service from one person to another is abbreviated as Word of mouth (Waibel et al., 2001). The evolution and growth of the internet have replaced conventional word-of-mouth communication with electronic word of mouth (E-WOM) which is more eloquent than orthodox WOM as it is boundless and can reach the masses instantly (Chevalier & Mayzlin, 2006). E-WOM is currently among the strongest efficacious tools for promoting any product (Gruen et al., 2006); (Kumar & Benbasat, 2006); (Zhang et al., 2010). These days, consumers are becoming more conscious about purchasing a product or service. They usually seek former online reviews posted by users before making a buying decision (Pitta & Fowler, 2005). Consumers can easily obtain information through E-WOM using various online sources, including review sites, social platforms, blogs, and the most popular online retail websites (Cheung & Thadani, 2012).

Nowadays, online shopping sites have proven to be amongst the quickest and most efficient means of purchasing any item. Online shopping in India is at an all-time high in 2021 with 780.27 million online users as of May 2021. Despite economic abatement weakened consumer pay-out and dilemma created during the coronavirus pandemic situation in 2019, various online shopping websites such as Amazon, Flipkart, Myntra, and Paytm Mall are anticipating strong sales growth in India in 2021. The online shopping platforms witnessed an increase as the majority of people have started shopping online rather than stepping outside their homes due to the fear of COVID-19. Ample growth in this e-commerce industry has been stimulated by an upsurge in the use of the internet and smartphone penetration (ibef.org). Before making any purchase decision, most consumers search for suitable information and previous comments and reviews about various products mostly on online retail websites. In terms of sharing online reviews, social networking sites also played a strong role in affecting the consumers' purchasing intent. Forbes reports that 81% of purchasing choices are influenced by what their peers circulate on social networks. For a long time, marketers have promoted their goods and services via social networks such as Twitter, Facebook, and Instagram. They recognized social media websites as an easy way to attract consumers to make any purchase. According to Statista Research Department, Facebook is the leading and most popular social media website with over 340 million users in India alone by August 2021(Statista. com). As a result, we can conclude that e-shopping sites and social platforms have become useful alternatives for e-WOM and buying choices of customers.

Due to its efficacy, plenty of investigations have been conducted regarding E-WOM's effects on consumers' desire to purchase (Cheung & Thadani, 2012; King et al., 2014). Multiple studies also looked at the influence of E-WOM across social networking platforms (Cheung et al., 2008); (Kim et al., 2018a). However, still there are a few crucial dimensions related to E-WOM that need to be explored. Therefore, this research study explores the effect of E-WOM from digital shopping sites and social websites on the purchasing decision of a smartphone in Uttar Pradesh, India. The current research analyses four elements i.e., Quality of E-WOM, Quantity of E-WOM, E-WOM attitude toward the product, E-WOM attitude toward the website, and Format of E-WOM influencing the intent to buy a smartphone.

Literature Review

WOM and E-WOM

WOM performs a crucial job in changing the mind of the consumer toward any product or service. Word of mouth (WOM) is a method of advertising a good or service that relies on the experiences of customers. WOM defines itself as the sharing of information about a product or company with friends, relatives, or customers. Many researchers have noted WOM's expanding importance, and marketers have recognized it as a successful and trustworthy type of marketing communication (Huang et al., 2007).

Traditional WOM is more reliable and traceable as it is a trustworthy channel of information. However, amidst the arrival of online technology, E-WOM has surpassed orthodox word of mouth, with the potential to reach millions of individuals in a short period. Internet word-of-mouth communication also recognized as E-WOM has evolved as one of the most significant forms of customer interaction for making any purchase choice as the Internet has grown and developed (Huete-Alcocer, 2017). "Any favorable or unfavorable comments notified online by consumers via the internet about any brand or product that has the potential to reach millions of people." is referred to as E-WOM (Hennig-Thurau & Walsh, 2003).

Before making any purchase choice, online word of mouth regarding a company's item or service is becoming the primary source of communication in this era of digital marketing. For advertising professionals, e-WOM becomes essential to draw consumer attention to their products. As a result, several researchers have studied the e-WOM effect on various product categories. Some studies recognized buyers' perceptions of E-WOM information about any product. They discovered that customers place a great deal of faith in credible E-WOM messaging. Besides a few negative remarks can help establish a good opinion of the E-WOM website's credibility. (Doh & Hwang, 2009) Previous researchers explored the effects of adverse E-WOM on consumer inclinations to switch mobile service providers using a qualitative method. They discovered that unfavorable E-WOM communications are more successful than favorable E-WOM messages, resulting in customers changing their intentions toward mobile service providers (Nadarajan et al., 2017).

Social Networking E-WOM and E-Commerce E-WOM

The EWOM influence can vary depending on the platform through which it is disseminated. E-commerce platforms and social platforms, despite both facilitating EWOM, possess distinct characteristics and functionalities that can result in differential effects on consumers' purchase intentions. E-commerce websites provide consumers with a structured and information-rich environment for product browsing and purchasing. These platforms often feature product reviews, ratings, and testimonials from previous customers, enabling the dissemination of EWOM. E-commerce websites offer consumers detailed product descriptions, specifications, images, and customer reviews, allowing them to gather extensive information about products. RV & Varshney (2022) in their study highlighted the purpose of eWOM generated via Flipkart in affecting consumer buying behavior. The competitive landscape between Flipkart and Amazon in India has further intensified the impact of eWOM, as both platforms vied for the attention and trust of Indian consumers through their respective review systems and engagement strategies. Consumers rely on this information to assess product quality, functionality, and suitability for their needs. Positive EWOM and perception on e-commerce websites can significantly influence consumers' purchase intention by providing social proof and enhancing perceived product value.These websites are primarily designed to facilitate online transactions. They emphasize product features, prices, discounts, and other transaction-related information. As a result, EWOM on these platforms tends to have a more direct influence on purchase intention. Consumers who engage with EWOM on e-commerce websites are often in the decision-making phase, seeking information to finalize their purchase. Consumers perceive EWOM on e-commerce websites as more credible and trustworthy due to the review system and rating mechanisms in place.

Social media platforms have gained immense popularity and transformed the way individuals communicate, connect, and share information. These platforms facilitate the sharing of user-generated content, including EWOM, more informally and interactively. Farzin et al. (2022); Leong et al. (2022) recently identified that social media platforms provide a more informal and interactive environment, where EWOM is shared in the form of comments, likes, and shares. Research has highlighted the considerable influence of EWOM via social networking platforms on buying intention. Social networking platforms provide opportunities for consumers to seek social validation and influence from their peers and opinion leaders. Customers are more prone to be affected by EWOM when it comes from individuals they know, admire, or perceive as experts. Influencers and celebrities play a vital part in forming purchase intention through their EWOM on social media platforms. Consumers may perceive EWOM from these sources as more influential due to their social status and large following (Liu & Park, 2015; Zhou et al., 2021).

E-WOM on Social Networks and its Effect on Purchasing Intention

Increasingly, businesses are utilizing social networking sites to publicize their goods and services. It can be used to not only interact with the intended users but also to raise awareness of the brand and thereby increase product sales. Prior studies have indicated that the personal views of people on social networks have a vital role in consumer choice-making with regard to any product. A recent study ascertained the effects of social network marketing, eWOM, and service quality on buying intent (Black Coffee Shop). The research was implemented in Indonesia, mostly in Balikpapan. With 518 samples, the study's topic was a black coffee user who had utilized coffee products. The research demonstrates that eWOM, SerQual, and social network marketing all had a direct impact on the intention to buy (Armawan et al., 2023). Consumer involvement with E-WOM on social networking sites is influenced by credibility and social capital (social contacts inside the social network), as suggested by the Expectancy Value Theory (EVT) (Gvili & Levy, 2018). Previous studies investigated the influence of a premium brand's advertising approach on buying intent via social networks through E-WOM. The volume of likes, prominent followers, shares, the style of a commercial posting, favorable comments, and the subject of a commercial posting were all determined to be essential variables and greatly influence the purchasing intention of the luxury brand through E-WOM information on social networks. (MajlesiRad & Haji pour Shoushtari, 2020) Prior research assessed the influence of Facebook E-WOM on purchasing intents for fashion-related goods. Trust, homophily, experience, informative influence, and highly fashionable engagement all have a substantial role in influencing online WOM messaging on buying intent, according to the research (Saleem & Ellahi, 2017). Researchers analyzed the role of Facebook E-WOM on customer attitudes and purchasing intention. They found that positive Facebook reviews also have an impact on consumer perceptions of brands and purchase intention (Kudeshia & Kumar, 2017). Previous literature identified the effect of customer attitude, online shopping motivation, and E-WOM intention toward social media messages. They found that social networks does not possess a direct influence on E-WOM intention (Kim et al., 2016). Also, previous studies examined involvement, self-reliance, and risk-taking as the three main antecedents of E-WOM, as well as their effects on social networks and buying decisions. According to the findings, risk-taking and involvement have a beneficial impact on E-WOM. E-WOM also acts as a buffer between social networking site involvement and buying intention. Previous literature concluded due to the widespread usage of social platforms and reliance on E-WOM, consumers are tempted to consume conspicuous yet impulsive products that are not essential (Thoumrungroje, 2014).

Internet consumer reviews on various online platforms have a direct impact on buying decisions. There are a variety of aspects that influence consumers' perceptions of importance when it comes to E-WOM. The research was conducted to ascertain how purchasing intention and brand equity are impacted by eWOM and to further explore the function that brand equity plays as a mediator between eWOM and buying intent across Indian customers of branded clothing. 303 buyers of branded clothing provided the information through a survey. The study's conclusions showed that eWOM significantly and favorably affects brand equity and purchasing intention. Concurrently, there is a partial mediation effect of brand equity across consumers' purchase intent and eWOM for clothing brands (Khan et al., 2023). Previous studies investigated some key elements connected to pessimistic online word of mouth which influence consumers in Malaysia in their purchase intent. According to the data analysis, dissonance reductions, altruism, and seeking advice possess a considerable effect on customers' purchase intent, whereas negative feelings have no such effect (Haque et al., 2020). Another study explored E-WOM's influence, customer involvement, and attitude in conscientious use of second-hand goods clothes in Malaysia.

The findings indicated that E-WOM had a direct impact on consumer engagement, mindful consumption behavior, and consumers' attitudes toward second-hand clothes (Mohammad et al., 2020). Some researchers assessed the pertinent elements related to E-WOM on consumer intentions to purchase, depending on meta-analysis and weight analysis. They discovered that trust in the message, E-WOM usefulness, attitude toward the product, argument quality, and valence are perhaps the most compelling predictors, with E-WOM credibility, attitude toward shopping online, website attitude, and emotional trust being the leading factors of customer purchasing intentions (Ismagilova et al., 2020). Previous studies identified that trust operates as a positive moderator among E-WOM and buying intention, and positive E-WOM communications have a stronger influence on buying intent contrasted with negative messages through E-WOM (Harun et al., 2020). Researchers also discovered that a favorable review had a more profound effect on buyer attitudes regarding E-WOM compared to an adverse or neutral one. Furthermore, benefit-centric information has a greater impact on customer attitudes and buy intent than attribute-centric information (Wang et al., 2015). Previous researchers examined that consumers' purchasing intentions are influenced by four aspects of E-WOM: accuracy, timeliness, relevance, and comprehensiveness. When compared to other factors, they discovered that E-WOM accuracy has a greater impact on customer purchasing intention (Sa’ait et al., 2016). Previous literature found that customer self-efficacy, moral duty, trust, altruism, sense of belongingness, and informational influence are major E-WOM elements that influence consumer brand image and buy intent. Also, favorable E-WOM messages on social media websites had a greater effect on the buying intent of customers and brand image (Farzin & Fattahi, 2018). Researchers observed the consequences of online traveler trust on the purchasing intent of airline e-tickets and E-WOM. Independent factors included credibility, expertise, similarity, trustworthiness, expertise, quality, and tie strength. According to the findings, online trust is a mediating factor in the purchase intent of airline e-tickets and E-WOM. E-WOM also demonstrates a favorable and significant association with airline e-ticket buying intent (Ahmad et al., 2020). Some studies analyzed the outcome of E-WOM on reviving the association across a brand and its old and new customers in Turkey. This study includes five factors namely tie strength, the expertise level of the receiver, the perceived expertise degree of the sender, argument quality, and perceived risk to determine the reviving effect of E-WOM (Güçlü Sözer, 2018).

Research Methodology

Based on the thorough study of extensive literature reviews on WOM and E-WOM communications, we become acquainted with E-WOM's impact on consumer purchasing choices. Consumers' purchasing intent is significantly influenced by E-WOM positively or negatively as their decisions are affected by others' word of mouth whether to purchase or not based on their perceived effectiveness of a product or a service. Online shopping websites and social media are the two main platforms inducing the consumers' buying intent (Yan et al., 2016). There are many aspects associated with electronic WOM including credibility, quality, and attitude which influence consumers' purchase intentions in different ways depending on how effective they are seen to be (Erkan & Evans, 2016); (Mehyar et al., 2020). These characteristics are regarded as acceptable for our research study as well because our research framework explores the electronic WOM influence on e-shopping websites and social sites affecting smartphone buying intention. These characteristics served as independent variables as shown in our research framework. Our conceptual framework differs from previous research works as we have included a novel independent variable, E-WOM format.

In this research, we are examining internet word-of-mouth's influence concerning smartphone purchase decisions made through social platforms and e-shopping platforms. Based on the previous literature studies, we have taken our variables as Quality of E-WOM, Quantity of E-WOM, E-WOM Attitude towards the product and website, and format of E-WOM as independent factors and online purchase decision as the dependent factor. The hypothesis of our research is constructed based on these components. The following Figure 1 illustrates the theoretical structure for developing the study aims and hypotheses.

academy-marketing-studies-independent-factors

Figure 1 Independent Factors' Influence on the Dependent Factor

Research Model

Hypothesis

Quality of E-WOM

The E-WOM quality may be described as the degree to the information /comments posted online are considered to be useful, relevant, and persuasive. If the digital reviews for a product say smartphones are easy to understand, valuable, and effective, there is a higher likelihood that opinions will affect the customers' decision to purchase a smartphone. Most of the customers are influenced by the quality of internet-based reviews available via online platforms when they search for previous comments about their preferred product (Cheung & Thadani, 2010). Therefore, the quality of E-WOM information could be considered an important element in assessing the customer's intent to buy smartphones. Thus, we assume the following hypothesis:

H₁: The quality of E-WOM had a significant influence on the purchasing choice of a smartphone.

E-WOM Attitude towards the Product and Website

The conviction of a person towards a specific entity is referred to as attitude. E-WOM attitudes can be favorable or negative depending on the way someone feels towards a website or a product. The attitude of E-WOM toward any product differs depending on how buyers perceive a given product. Prior studies have found that E-WOM on social networks can affect the customer's attitude toward any product or service (Ladhari & Michaud, 2015).

Researchers proposed that a positive or negative attitude towards an online review is a key preceding in anticipating consumer attitudes towards a website, which in turn influences their purchase intentions (Kim et al., 2018b). Also, previous studies discovered that a favorable opinion of an online commerce website had a noteworthy and favorable impact on consumers' purchasing choice of products (Lee et al. 2011). Accordingly, we put on the subsequent hypothesis:

H₂: E-WOM Attitude towards the product had a significant influence on the purchasing choice of a smartphone.

H₃: E-WOM Attitude towards the website has a significant influence on the purchasing choice of a smartphone.

Quantity of E-WOM

E-WOM quantity represents the overall volume of comments or reviews regarding any item or service posted by users of online platforms . Most of the customers are lured toward a product that has a substantial amount of reviews in comparison to a product with a smaller number of reviews. Based on the number of digital comments or opinions regarding a particular product, customers frequently speculate the product is popular and trending on online platforms. As a result of multiple reviews and comments, e-shopping platforms are the primary source of information for many customers who search for past reviews about their preferred product before making any purchase intent. In light of this, the subsequent hypothesis is predicted:

H₄: Quantity of E-WOM had a significant influence on the purchasing choice of a smartphone.

Format of E-WOM

The term "E-WOM format" denotes the display of internet reviews in a variety of formats, including image-based, textual, and visual, or a mix of these. Nowadays, Visual and audio reviews of cell phones is available on several digital buying platforms such as Amazon and Flipkart, in addition to social sites like Instagram, Facebook, and YouTube (King et al., 2014). Researchers suggested that buyers favor internet reviews having detailed descriptions of a product along with pictures and videos (Teng et al., 2014). Also, video-generated opinions are considered to be more convincing in affecting the consumers' buying intent as they include a visual communication of different products (Xu, 2014). Therefore, the hypothesis is framed as:

H₅: The format of E-WOM had a significant influence on the purchasing choice of a smartphone.

Data Collection and Sample

A questionnaire survey was utilized to gather data to evaluate the hypothesis. The questionnaire consists of three components. Part I addresses the demographic profile of the participants. The second section contains questions about purchase intent based on the frequency and choice of accessing social platforms and e-shopping websites. The primary body of the survey is covered in the third section which comprises 18 items based on the factors used in our research. Some of the statements for our conceptual framework were originated from past research and altered to meet the scope of our research study. This increased the validity of the results. Likert scale was employed to evaluate the factors, utilizing a 1 to 5 scale indicating "strongly disagree" and 5 signifying "strongly agree."

The study IAMAI-Kantar ICUBE 2020 shows that India had an enormous quantity of users of the Internet closest to 622 million in 2020. There were 448 million social media users by 2020 (datareportal.com) and 150 million online shoppers in India by 2020 (statista.com). Uttar Pradesh is the highest populous state in India; our research survey primarily focuses on social networking users and digital shoppers on buying decisions on smartphones. Three hundred and eighty-two respondents were taken as a sample including both males and females who are using e-shopping websites and social networks.

The particulars of the sample are shown in Table 1. Regarding the demographic breakdown, there were 250 men and 132 women among the responders (65.4% and 34.6%, respectively). Adult respondents made up the majority, with 57.1% of them being between the ages of 24 and 34. According to the survey, 214 respondents always examine internet evaluations, while 133 respondents do so occasionally while deciding whether or not to buy a smartphone.

Table 1 Sample Characteristics
Measure	Frequency	Percentage
Gender Male Female	250 132	65.4 34.6
Age Below 24 24-34 35-45 Above 45	97 218 43 24	25.4 57.1 11.3 6.3
Education UG Graduate Postgraduate P. h d Internet reviews usage Always for purchasing a smartphone Sometimes Very rare Never	61 138 155 28 214 133 29 6	16.0 36.1 40.6 7.3 56.0 34.8 7.6 1.6

Analysis and Findings

The variables' dependence was evaluated employing Cronbach's alpha. The Cronbach alpha scores for each of the independent and dependent factors are higher than 0.75 (Table 2). All of the variables in our research study were found to be reliable based on these results.

Table 2 Cronbach’s Alpha
Variables	No. of items	Cronbach's Alpha
Quality of E-WOM	4	0.822
Quantity of E-WOM	3	0.840
E-WOM ATTITUDE towards the product	2	0.831
E-WOM ATTITUDE towards the website	2	0.835
Format of E-WOM	3	0.833
Online purchase decision	4	0.837

Statistical Model and Hypothesis Testing

Confirmatory Factor Analysis

Confirmatory factor analysis (CFA) is a methodological approach to statistics that looks at the connections between implicit constructs and observable variables to examine and validate theoretical frameworks. In this study, CFA was utilized to validate the constructs and to know the degree to which the suggested model matches the observed data, ensuring that the chosen indicators accurately measure the intended theoretical concepts using JASP software. The conducted confirmatory factor analysis (CFA) provides valuable insights into the underlying structure of variables related to E-WOM and their influence on buying intention. The results indicate a well-fitting model, as evidenced by various statistical tests and parameters. Firstly, both the KMO and Bartlett's test demonstrate the data's appropriateness for factor evaluation, with a high KMO value of 0.885 and a test statistic of 2086.171 with a p-value below 0.001 (Table 3). These initial assessments suggest that the variables are sufficiently correlated to proceed with CFA.

Table 3 KMO and Bartlett's Test of Sphericity
KMO 0.885
X²	df	p
2086.171	153	<0.001

Moving on to the factor loadings table, the analysis reveals the relationships among the constructs and the key factors. Each variable corresponds to a certain factor, with factor loadings indicating the strength and direction of these associations. For instance, variables such as q6 and q10 exhibit strong positive loadings on factors related to E-WOM attitude, suggesting that they play a significant role in shaping consumers' attitudes towards electronic word-of-mouth. Similarly, variables like q1 and q4 show strong loadings on factors associated with purchase intention, indicating their importance in predicting consumers' likelihood to make a purchase based on E-WOM (Table 4). Furthermore, the average variance extracted (AVE) scores provide insights into the convergence of items within each factor. Higher AVE values indicate that the factors capture a greater proportion of the variance in the observed variables relative to measurement error. The AVE scores varying from 0.485 to 0.560 suggest that the identified factors effectively capture the underlying variance in the dataset, further supporting the validity of the factor structure (Table 5). Finally, the chi-square test evaluates the extent to which the proposed factor model fits the observed data. The significantly lower chi-square value for the factor model compared to the baseline model, along with a p-value below 0.001 as shown in table 3, indicates the proposed factor model offers a noticeably better match to the data. This suggests that the identified factors successfully account for the associations between the parameters, validating the indicated factor structure Figure 2.

Table 4 Factor Loadings
						95% Confidence Interval
Factor	Indicator	Estimate	Std. Error	z-value	p	Lower	Upper
Quality of E-WOM	q5	0.563	0.07	8.051	< .001	0.426	0.7
	q6	0.805	0.067	12.078	< .001	0.674	0.935
	q7	0.391	0.057	6.8	< .001	0.278	0.503
	q8	0.504	0.051	9.937	< .001	0.405	0.603
E-WOM attitude towards the product	q9	0.388	0.055	6.993	< .001	0.279	0.496
	q10	0.554	0.059	9.339	< .001	0.438	0.671
E-WOM attitude towards the website	q11	0.426	0.063	6.749	< .001	0.302	0.55
	q12	0.507	0.06	8.379	< .001	0.388	0.625
Quantity of E-WOM	q13	0.593	0.079	7.462	< .001	0.437	0.748
	q14	0.508	0.069	7.322	< .001	0.372	0.643
	q15	0.661	0.082	8.028	< .001	0.5	0.823
Format of E-WOM	q16	0.557	0.085	6.555	< .001	0.391	0.724
	q17	0.561	0.083	6.73	< .001	0.398	0.724
	q18	0.332	0.064	5.199	< .001	0.207	0.456
purchase intention	q1	0.521	0.05	10.482	< .001	0.423	0.618
	q2	0.599	0.058	10.37	< .001	0.486	0.713
	q3	0.433	0.065	6.706	< .001	0.306	0.559
	q4	0.593	0.055	10.849	< .001	0.486	0.7

Table 5 Average Variance Extracted
Factor	AVE
Quality of E-WOM	0.56
E-WOM attitude	0.485
Quantity of E-WOM	0.513
Format of E-WOM	0.489
purchase intention	0.527

Figure 2 Factor Model

Regression Analysis

The regression analysis has been employed for examining the research hypothesis. The impact of independent elements (Quality of E-WOM, E-WOM attitude towards the product, E-WOM attitude towards the website, Quantity of E-WOM, and Format of E-WOM) on dependent factor online purchase decision was determined by the statistical significance values as shown in the regression analysis data.

According to the multiple regression outcomes, a noteworthy analytical effect regarding all the factors was obtained with an r2 of .403 and a significant value of .000 (Tables 6 and 7) which specifies that the predictive model described 40.3% of the difference and all the factors were essential indicator of purchasing choice. Considering the hypothesis presented, three hypotheses were accepted and two were rejected. Following the findings of regression analysis, the E-WOM quality, Quantity of E-WOM, and E-WOM attitude towards the website have a crucial bearing on the purchasing decision of smartphones as their significance values are less than 0.05 (Table 8). These three independent variables make the strongest and most significant contribution in anticipating the dependent variable purchase decision. So, hypotheses H1, H2b, and H3 were supported. Since E-WOM's attitude towards the product and format of E-WOM do not have a considerable influence on the purchasing choice of smartphones as their beta values are 0.052 and 0.350 respectively, they were the insignificant predictor of purchase intention. So, the hypothesis H2a and H4 were rejected. According to the overall findings, the significance values of E-WOM attitude towards the product and format of E-WOM were less than 0.05, indicating rejection of both hypotheses (at a 95% confidence interval). Therefore, three hypotheses were supported and two were rejected.

Table 6 Chi-Square Test
Model	X²	df	p
Baseline model	2129.846	153
Factor model	1358.350	135	< .001

Table 7 R Square Value
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	0.635a	.403	0.395	0.51473

Table 8 Probability Value
Model		Sum of Squares	Df	Mean Square	F	Sig.
1	Regression	67.316	5	13.463	50.814	.000b
	Residual	99.621	376	0.265
	Total	166.937	381
a. Dependent Variable: Online purchase decision
b. Predictors: (Constant), Format of EWOM, EWOM ATTITUDE towards the website, Quantity of EWOM, EWOM ATTITUDE towards the product, Quality of EWOM

Discussion

This research study analyses the E-WOM effect on the purchasing decision of a smartphone via online shopping websites and social networking platforms. Previous researchers have looked into the effects of WOM communication and E-WOM on numerous product categories (Nadarajan et al., 2017; Saleem & Ellahi, 2017). Recognizing the extensive utilization of the web and social networking sites, E-WOM has become a crucial tool and a means of communication while choosing a product to buy. Various studies have been conducted to assess the E-WOM influence through online shopping websites and social websites independently on the purchase intent of consumers (Alhidari et al., 2015; MajlesiRad & Haji pour Shoushtari, 2020). Nonetheless, the impact of these two digital platforms on a specific product has yet to be examined, as their impact on different product categories may provide different findings and outcomes. The reviews and comments on social media about any product have also affected the purchase decisions of consumers as people get influenced by their social groups. Contrary, the reviews, and comments on online purchasing sites are more thorough and numerous as compared to social media platforms with a smaller number of comments. As a result, the E-WOM influence on the buying intention of a specific product through these two digital platforms differs significantly as far as their efficacy is concerned.

We have proposed five hypotheses for our research study (Table 9) and found the results according to our expectations. The results of the confirmatory factor analysis facilitate the existence of meaningful dimensions related to E-WOM and purchasing intention with the derived model providing a good fit to the data. The multiple regression tool disclosed that the independent factors (quality of E-WOM, quantity of E-WOM, as well as E-WOM attitude towards the website) significantly affect the variable of dependence (online purchase decision) on the purchase decision of smartphones. The findings indicated that the comments posted on online shopping websites as well as social media affected the consumer's purchase decision of smartphones.

Table 9 Regression Model Evaluation of E-Wom Variables Through Social Platforms and E-Shopping Platforms
Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
		B	Std. Error	Beta	t	Sig.
1	(Constant)	1.022	.190		5.381	.000
	Quality of EWOM	.196	.054	.205	3.662	.000
	EWOM ATTITUDE towards the website	.242	.051	.244	4.759	.000
	EWOM ATTITUDE towards the product	.094	.048	.103	1.947	.052
	Quantity of EWOM	.174	.043	.203	4.074	.000
	Format of EWOM	.050	.053	.050	.935	.350

Moreover, based on overall results and findings, the attitude of E-WOM towards the product and E-WOM format has no discernible impact on the purchasing decision of the smartphone.

Furthermore, the findings are new to the body of research already available on E-WOM and may be explored in the future by other researchers related to the E-WOM effect with different products on purchase intentions. Therefore, this research study clearly explains that E-WOM information and opinions of people on these digital platforms may be of great importance to other individuals as it will change their buying intent and perceptions towards different products and influence their purchase decisions. Additionally, depending on reviews posted online for various product categories with other parameters, the outcomes may alter on these two digital sites (Table 10).

Table 10 Results of Hypothesis Testing
No.	Hypothesis	Results
H1 H2a H2b H3 H4	The quality of E-WOM had a significant influence on the purchasing choice of a smartphone. E-WOM attitude towards the product had a significant influence on the purchasing choice of a smartphone. E-WOM attitude towards the website had a significant influence on the purchasing choice of a smartphone. The quantity of E-WOM had a significant influence on the purchasing choice of a smartphone. The format of E-WOM had a significant influence on the purchasing choice of a smartphone.	Accepted Rejected Accepted Accepted Rejected

Conclusion

The main motive of this research study was to determine the impact of E-WOM on smartphone purchasing decisions through e-shopping platforms and social platforms. We anticipated that E-WOM via social sites and e-shopping websites would have a substantial impact on buying decisions regarding a smartphone referring to the five factors of E-WOM as online reviews on social platforms come from individuals known to the consumers, and they are typically brief and extreme as well as reviews on e-shopping platforms are more detailed and comprehensive. So, these two digital platforms were best suited for our research analysis. According to the assumed hypothesis, the results are identical. E-WOM generated by both platforms had a major impact on buying choices regarding the smartphone. Besides that, as per the research findings, this study arrives at the verdict that E-WOM influences consumer purchase decisions, and E-WOM information through social platforms and e-shopping websites is more significant in terms of quality, quantity, and attitude towards the website in influencing smartphone purchase decisions in Uttar Pradesh, India. The identified factors and their associated variables provide insightful observations on consumer actions concerning online word-of-mouth, offering implications for marketing strategies and further theoretical developments in this domain. Furthermore, the outcomes on these two digital platforms may alter depending on the online reviews for various product categories and characteristics.

Future Research Scope

Although the criteria considered in our study was the E-WOM’s influence through social networks and e-shopping platforms, future research could incorporate other E-WOM aspects connected to purchasing decisions. Furthermore, future studies ought to focus on the effect of E-WOM on different sorts of products as well as in different Indian states with varying sample sizes and populations. To further advance the field, future investigations should take longitudinal research into account to monitor evolving trends in the Indian market continually. Segmenting the e-WOM's influence across various demographic segments and product groups can uncover hidden patterns and opportunities for targeted strategies.

Limitations

This study does have certain limitations. The context-dependency of the findings suggests that they may not be universally applicable across all product categories or demographics. Future research endeavors should explore these nuances to develop a more comprehensive learning of e-WOM's effects. Additionally, assessing the accuracy and reliability of e-WOM data, particularly on social networks, presents a challenge. Researchers and businesses must exercise caution when relying on user-generated content. Moreover, the rapidly evolving digital landscape raises concerns about the temporal relevance of current findings. Regular updates and longitudinal studies are imperative to capture evolving trends and shifts in the influence of e-WOM.

References

Ahmad, A.M. K., Abuhashesh, M., Obeidat, Z., & AlKhatib, M. J. (2020). E-WOM and airline e-ticket purchasing intention: Mediating effect of online passenger trust. Management Science Letters, 10(12), 2729–2740.

Academy of Marketing Studies Journal (Print ISSN: 1095-6298; Online ISSN: 1528-2678)

Influence of E-Wom Conversations from Social Platforms and E-Commerce Platforms on Purchasing Choice

Abstract

Keywords

Introduction

Literature Review

Research Methodology

Discussion

Conclusion

Future Research Scope

Limitations

References