Impact of EWOM on Restaurant Purchase Intentions via Snapchat

Impact of Electronic Word of Mouth on Restaurant Purchase Intentions via Snapchat

An in-depth quantitative research analysis using statistical modeling on the influence of electronic word of mouth (EWOM) through the Snapchat platform on restaurant purchase intentions. This study focuses on the vibrant platform of Snapchat and its implications for residents of Saudi Arabia. With participants spanning various age groups, educational backgrounds, and income levels, this research paints a comprehensive picture of how EWOM impacts consumer behavior.

Objectives:

The primary goal was to examine the data and use statistical modeling to answer our research questions, while exploring the conceptual framework.

Our first stop before going to statistical modeling, involved exploring descriptive statistics for the variables in our dataset. Through various charts and tables, we gain valuable insights into how the data is distributed.

Demographical Characteristics:

For instance, we learn that the majority of participants fall in the age group of 25 to 34, and a striking 73.75% of participants are female. When it comes to education, 66.25% of participants hold master’s degrees or doctorates.

Restaurant Visits:

Understanding participants’ restaurant habits is key. It turns out that 36.25% of participants visit restaurants 2 to 3 times a month, while 17.5% frequent restaurants more than 6 times a month.

Social Media Preferences:

Snapchat takes the lead as the most-visited social media platform for 53.75% of participants, followed by Instagram (18.75%) and Twitter (17.5%).

Key Influences:

We discover that recommendations from friends and family (32.91%) and online social networking sites like Snapchat (41.77%) are powerful motivators for restaurant visits.

Snapchat Usage:

A whopping 92.59% of participants have Snapchat accounts, with many spending 4 to 6 hours on the platform per week.

User Perceptions:

More than half of participants (64.2%) agree that Snapchat is useful for their communication, with 13.58% neither agreeing nor disagreeing.

Positive EWOM:

Participants’ responses indicate that they often find positive word of mouth impactful in their restaurant choices, with over 50% agreeing or strongly agreeing with statements related to positive EWOM.

We then dive into inferential statistics using Structural Equation Modeling (SEM), which is an advanced type of statistical modeling, based on regression analysis and path analysis. Our research hypotheses (H1 to H4) examine the influence of positive EWOM on purchase intentions, its impact on EWOM intentions on social networking sites, and the role of tie strength in influencing these intentions.

Model Refinement:

The SEM process involves refining our models to ensure they fit the data accurately. Model modification is guided by several statistical indicators, including the normed chi-squared value, Incremental Fit Index (IFI), Comparative Fit Index (CFI), Root Mean Square Error of Approximation (RMSEA), and Akaike Information Criterion (AIC). These indicators help us build a model that best fits our research objectives.

Key Findings:

Our analysis reveals that positive EWOM significantly influences both giving intention and purchase intentions. The p-values (significance levels) are strikingly low, indicating strong statistical significance.

The Takeaway:

When positive EWOM score increases by 1, purchase intentions score also increase by 1.117, and giving intentions score increase by 0.641. Furthermore, the effect of positive EWOM on purchase intentions is nearly twice as impactful as on giving intentions.

This research opens a window into the power of EWOM and its potential to drive consumer behavior. It underscores the significance of recommendations and positive experiences shared on platforms like Snapchat. As the digital landscape continues to shape consumer choices, understanding and harnessing the dynamics of EWOM is paramount for businesses looking to thrive in the modern era.