Community engagement and online word of mouth


Over the past few years, the online technologies and environment has developed dramatically to enable individuals to create, share and engage with web content rather than being a passive recipient of content. There are two significant online platforms- online brand communities (OBCs) and online word-of-mouth (WOM) channels for increasing customer engagement and boosting profits. Companies deploy an online brand community, where is not only a means to convey the brand message or provide customer support, but an interactive communication to build strong relationships among members. Customers benefit from their ability to recognize in each other while they’re willing to contribute their time and expertise to grow the identity-based networking. Although OBCs and online WOM channels are separated, customers tend to engage in multiple channels simultaneously.

Key findings: 
With regards to cross-channel engagement, the research empirically identifies three key findings:

  1. Consumer engagement in an OBC increases both their generating of online reviews (the volume of WOM) and online review ratings (the valence of WOM) after purchase.
  2. The effects of community engagement on online WOM become stronger among longer-tenured customers.
  3. The shorter-tenured consumers are more likely to have lower levels of engagement and commitment to the brand community.

Fig. 1. The conceptual framework of this study..jpgFig. 1. The conceptual framework of this study.

We can see above framework  how community engagement influences customers’ online WOM behavior in terms of generating online review and review ratings. The research considers several control variables, including product attributes, disconfirmation, review context, and customer attributes. Therefore, the article proposed two main reasons why community engagement will positively impact customers’ review generation. Firstly, community engagement enhances customers’ identification and loyalty, which facilitates their willingness to contribute to the brand or products by generating online product reviews. Secondly, community engagement is able to be geared positive performance in a voluntary environment, and engaged customers are more likely to give online reviews to help other customers make purchase decisions. Hence, here are the proposed hypotheses:

H1: Community engagement has a positive impact on generating online product reviews after purchase.

H2: Community engagement has a positive impact on online product review ratings after purchase.

H3a: The impact of community engagement on generating online product reviews after purchase is stronger for longer-tenured consumers than for shorter-tenured consumers.

H3b: The impact of community engagement on online product review ratings after purchase is stronger for longer-tenured consumers than for shorter-tenured consumers.

In order to test the hypotheses, the research examines a focal firm, which designs, produces, and sells female apparel in an Asian market, collecting all purchase transaction data, incorporating user ID, product ID, review ratings, review context, and the date of leaving review from its e-commerce website. In October 2010, the focal firm, first created its OBC with the objective of encouraging customer engagement. A total of 111,266 purchase records from 10,896 customers were sampled from May 2011 to December 2012. Specifically, 2,286 customers, at least 20% of customers, generated 12,723 post-purchase online product reviews during the time period.

Another strength is the second phase of data collection that the author created custom programs to gathered information from members’ profile pages, analyzing the discussion threads in its online brand community. The research utilized econometric models and set the control approach to achieve consistent estimation. Additionally, the author conduct robustness checks to verify the results of our analyses. The author finalized integrated community engagement data with the purchase data and online product reviews. Meanwhile, the author defined time windows of six weeks for each of the purchase records, which are consistent with the presented results. This implies that customer tenure moderates the relationships between community engagement and the intentions of generating online product reviews after purchase, and this relationship is strengthened when consumers have longer tenure.

Limitations:
First, while the dataset is retrieved from a single focal firm, we lack of exogenous data to compare levels of interaction with other online communities and verify the outcomes to see how and where we may need to change tact to achieve maximum engagement. Second, the research focuses on consumer brand and products, which might cause bias when applying to different product segmentations such as services or technical products, which require a certain amount of professional knowledge. Third, there are two major types in terms of who owns the platforms: consumer-initiated communities and company-initiated communities. The study targets firm-sponsored and we can investigate if different types of online brand communities could impact customer attitudes and behaviors variously.

Conclusion:
In summary, a firm’s OBC is an essential indicators of consumer WOM behaviors, resulting in positive online product review and ratings after purchase. Furthermore, the effect of community engagement on online product review and ratings after purchase is moderated by customer tenure. That’s why it’s important to map out how our business engages with customers across channels and increase channel engagement amongst the recurring customers; in contrast, we may need to lift sales conversions with first-time visitors.

Source:
Ji Wu, Shaokun Fan, J. Leon Zhaoc (2018). Community engagement and online word of mouth: An empirical investigation Vol. 55, Issue 2, 258-270

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