Tag Archives: Online communities

Are Virtual Communities Different From Face-to-Face Communities?


A community has always been seen as a group of people that interact with each other, face-to-face. But since the rise of the digital age, a new phenomenon has occurred; digital communities. This blog post tries to give an overview of the original community and the virtual community and how they differ. The blogpost is based on the article “The Experienced “Sense” of a Virtual Community: Characteristics and Processes” by Blanchard and Markus (2002)

Original communities

Original communities are face-to-face communities. There are two types: geographic neighborhoods, so place-based communities and communities of interest. The communities of interest were groups of people that bonded over interests, rather than the geographical location. So, these types of communities were more widespread. Since the limited use of digital devices and or the internet, most of these communities included face-to-face contact and no such thing as chatting. Not all neighborhoods are also communities.

Virtual community

Virtual communities are built around digital devices using the internet. The people within the community are connected mostly digital. In some cases, they know each other in person and also interact face-to-face. But when it comes to the community as a whole, that is only digital. Like in original communities, there is a difference in virtual settlements and virtual communities. Virtual settlements exist when objective measures of computer-mediated interaction exceed some threshold levels. Not all virtual settlements are virtual communities.

Sense of community

So why don’t all neighborhoods count as communities? In order to really be a community, the concept ‘sense of community’ plays an important role. Without this ‘sense of community’, the group of people is just a group of people.

This phenomenon was found in the original communities, but studies showed that this concept was also applicable in the virtual communities.

The definition used in the article is: ” a characteristic of successful communities distinguished by members’ helping behaviors and members’ emotional attachment to the community and other members.” There are some behavioral processes that contribute to the sense of community, namely: exchanging support, creating identities and making identifications and the production of trust. These are quite the same for both type of communities.

Researchers are still in doubt if the sense of community is the reason for communities to exist, or that it is an effect caused by communities. It is mostly presumed that the sense of community is necessary for a community to exist rather than that it is treated as an effect by communities.

The ‘sense of community’ experienced in virtual communities is called ‘sense of virtual community’. When this is experienced, it is called a virtual community. There are also a number of social processes and behaviors that should be present in these communities, namely: providing support, developing and maintaining norms and boundaries, social control and some more.

Sense of community is not forever existing, it can decay or be extinguished. This can be caused by leaders dropping out or if new members with different values join, etcetera.

Active members vs lurkers.

There are different types of members that are involved in most communities. The active members are mostly the leaders of the community, they contribute a lot to the content and interactions within the community. There are also members that are not as involved but still contribute once in a while. The last type are the lurkers. These members are not active, but only present.

In the study, members believed that the newsgroup they were subscribed to, was a community. But their attachment to the community varied with their participation, and their perceived benefits from participating.

Original communities vs Virtual community: what are the differences and what is the same.

The article argues that because the communities have differences in characteristics, the feelings are a little bit different formulated, but are quite similar in meaning. Table 1 gives an overview of the main feelings experiences with sense of community in the two different types of communities.

Table 1: Comparison of SOC and SOVC

Dimensions of SOC Dimensions of SOVC
Feelings of membership Recognition of members
Feelings of influence Exchange of support
Integration and fulfillment of needs Attachment
Shared emotional connection Obligation
Identity (self) and identification (of others)
Relationship with specific members

So, overall the communities have a similar buildup and similar processes. But some differences exist because of using digital devices versus face-to-face interactions.

What are the benefits for companies?

Companies are creating a virtual meeting place or platform for their customers to interact on. The companies try to get (positive) feedback of their consumers. This method is also used to try to motivate people to buy their products or just get the name of the company or product out there. But this group of people that the companies are putting together in this way, does not make a community. In order to have a community, the sense of community is needed. The feelings of belonging and attachment need to develop. The result of the community is that the value is more than all individual people added together.

A community within an organization will among others effect in an increase in job satisfaction and organizational citizenship behavior-loyalty.

This article shows the potential value of creating communities, for commercial reasons as for organization reasons.

From e-commerce to social commerce


A matter of trust

The advancement of Web 2.0 social networks brought new developments to e-commerce. In recent years, e-commerce has transformed to social commerce. Social commerce is a new stream and subset of traditional e-commerce, which combines e-commerce with Web 2.0 social networks.

Social commerce, trust & buying intention

Thanks to social networks consumers can now communicate, rate other products, review others’ opinions, participate in forums, share their experiences and recommend products and services. By bringing the features of Web 2.0 social networks to e-commerce, consumers can support each other in the acquisition of products and services in an online context. This results in more customer-oriented business models where customers can share knowledge, experiences and information about their products and services.

Social commerce has three main constructs that empower customers and increase the sociability of e-commerce:

  • Forums and communities: Online discussion sites that support information sharing;
  • Ratings and reviews: Provide comprehensive information about a product for potential customers;
  • Referrals and recommendations: Unlike brick and mortar stores, in online stores it is not possible to interact with staff, so customers rely more on other customers’ recommendations.

Trust is a central issue in e-commerce. Social commerce has helped to establish more trust in e-commerce platforms. Customers experience higher levels of trust as they can support each other through information exchange. This is because interactions and interconnectivity reduce the perceived risk in online transactions. Reviews, ratings and recommendations can indicate the trustworthiness of an online seller as customers consider reviews from other customers to be more reliable than information from a commercial website.

Hajli (2015) found that the three social commerce constructs significantly positively influence the user’s intention to buy. Trust appeared to be a mediating variable. Social commerce constructs have a positive effect on user’s trust, which in turn positively influences the intention to buy (Figure 1). To arrive at these findings, Hajli (2015) conducted a survey study with four constructs: intention to buy, social commerce constructs, perceived usefulness and trust. A five point Likert-scale was used in the questionnaire. Data was collected at universities in the UK. The final sample consisted of 243 completed and usable questionnaires. Next, Structural Equation Modelling (SEM) was used for data analysis. The hypotheses were tested with the Partial Least Squares (PLS) method. The findings underline that social commerce constructs, like customer reviews, are more likely to increase trust, and in turn increase customers’ intention to buy.

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Amazon customer reviews

From a practical perspective, this study encourages online businesses to make a plan for reviews and to manage social networks effectively as it significantly impacts customers’ purchasing decisions. It recommends them to engage with their customers through reviews to develop trust. Other research indeed shows that 91 percent of customers read online reviews and that 84 percent trusts online reviews as much as a personal recommendation (Bloem, 2017) In practice, this implies that not offering customer reviews is similar to ignoring 84 percent of your buying population by not giving them the information they want to support them in their buying decision (DeMers, 2015).

To illustrate, Amazon optimised its business model based on customer reviews and ratings. Customer reviews are one of the most important ranking factors in Amazon’s A9 algorithm. It ranks product search results based on the positivity of customer reviews and rating. (Grosman, 2017)

Fake review problem

A weakness in the study of Hajli (2015) is that it does not consider that information related to the identity of the reviewers influences the perceived trustworthiness of a review.  The paper simply finds that more reviews increases trust, which in turn increases the buying intention.  However, in reality, it might not be that straight forward anymore with the rise of fake product reviews. Nowadays, it is hard for customers to decide which reviews to trust. There is looming crisis of confidence in online product reviews, which used to be a key factor in customers’ buying decision. (Silverman, 2017) As customers cannot trust reviews anymore, it can be questioned whether the positive relation between the number of reviews, trust and buying decision still holds.

Increasingly, customers pay careful attention to reviews, e.g. looking for reviews with a Verified Purchase tag. Nearly 66.3 percent of Amazon reviews are five-star ratings, which is highly unrealistic. Reviews on Amazon are a key factor when making a purchasing decision and without reviews it is difficult for online retailers to gain sales. In an attempt to boost sales, retailers offer reviewers free or discounted samples in return for a positive customer review. So, it is no surprise that 96 percent of paid reviews on Amazon is rated four- or five-star.  (Cipriani, 2016)

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Source credibility

Many authors have investigated the positive impact of online reviews on sales of products and services. However, given the importance of source credibility, I believe more research is needed on trustworthiness of reviewers as an important construct. The source credibility theory explains how a recommendation persuasiveness is affected by the perceived credibility of its source. Actually, customers accept reviews depending on the perceived trustworthiness of the reviewer, which consequently impacts the buying decision. Reviewer trustworthiness is therefore an important moderating variable that positively moderates the impact of review-based online reputation. (Banerjee, Bhattacharyya, & Bose, 2017)

Concluding, instead of solely increasing the number of (positive) customer reviews, online retailers should also build a good review-based online reputation that encourages and identifies top trustworthy reviewers and that ranks reviews based on reviewer trustworthiness.

This post was inspired by: Hajli, N. (2015). Social commerce constructs and consumer’s intention to buy. International Journal of Information Management, 183-191

References:

Banerjee, S., Bhattacharyya, S., & Bose, I. (2017). Whose online reviews to trust? Understanding reviewer trustworthiness. Decision Support Systems, 17-26.

Bloem, C. (2017, July 31). 84 Percent of People Trust Online Reviews As Much As Friends. Here’s How to Manage What They See. Opgehaald van Inc.: https://www.inc.com/craig-bloem/84-percent-of-people-trust-online-reviews-as-much-.html

Cipriani, J. (2016, March 14). Why You Shouldn’t Trust All Amazon Reviews. Opgehaald van Fortune: http://fortune.com/2016/03/14/paid-amazon-reviews/

DeMers, J. (2015, December 28). How Important Are Customer Reviews For Online Marketing? Opgehaald van Forbes: https://www.forbes.com/sites/jaysondemers/2015/12/28/how-important-are-customer-reviews-for-online-marketing/#35eccc711928

Grosman, L. (2017, February 28). Five Tips To Improve Your Ranking On Amazon. Opgehaald van Forbes: https://www.forbes.com/sites/forbescommunicationscouncil/2017/02/28/five-tips-to-improve-your-ranking-on-amazon/#3079c5f89fed

Hajli, N. (2015). Social commerce constructs and consumer’s intention to buy. International Journal of Information Management, 183-191.

Silverman, D. (2017, April 20). A Matter of Trust: Amazon Declares War on Fake Product Reviews. Opgehaald van Clavis Insight: https://www.clavisinsight.com/blog/matter-trust-amazon-declares-war-fake-product-reviews

How to understand Word-of-Mouth marketing in online communities?


Introduction
Word-of-mouth (WOM) marketing is also known as social media marketing and leads to an intentional influence of consumer-to-consumer communication. Many marketers and sociologists recognize the importance of WOM as it affects many purchase decisions. WOM marketing is continuously changing as the Internet becomes more powerful; the accessibility, reach and transparency have empowered marketers to monitor WOM as never before.

The transformation of WOM
The researchers provide three WOM models before they discuss the research questions. These models are used as basic knowledge and as conceptual models in the paper.

Markets change so marketing theories should change as well to accommodate them. A review of the development of WOM is given in below and consists of three models. All three models currently coexist, and each pertains to different circumstances.

Model A
This model assumes that WOM occurs naturally among customers when marketers bring a new product to the market and perform an effective product notification through promotions and advertisement.

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Model B
This model assumes that some consumers are viewed as opinion leaders. Marketers could target these opinion leaders to influence them with advertising and promotions. All the other consumers need to be influenced with advertising and promotions as well.

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Model C
This model assumes that marketers have become more interested in directly managing WOM through targeted one-to-one communication programs. Marketers see consumers as co-producers of the value and meaning of WOM as the communication is produced in consumer network. This influence is creative and even hard to resist.

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Research questions and findings
Three research questions are answered so that further understanding of the network coproduction model (model C) can be developed. The three questions are as follows; How do communities respond to community-oriented WOMM? What patterns do WOM communicator strategies assume? And Why do they assume these patterns? A blog-based campaign in six North American cities is used to answer the three research questions.

The findings indicate that differences are observed in the way the members of online communities respond to WOMM campaigns. The researchers introduce a new narrative model to show that a network of communication offers four different communication strategies; evaluation, embracing, endorsement and explanation. This is also shown in below. Each of them is influenced by character narrative, communication forum, communal norms, and the nature of the marketing promotion. Thus, WOM marketing does not simply increase marketing messages, but the messages are altered in the process of embedding them.

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Strengths
The main strength of this paper is that the researchers provide a standpoint for both theoretical and managerial implications. For the theoretical part, the researchers focused on the motivations to participate in the bold new world of network coproduction of WOM. These motivations are more complex, culturally embedded and influenced by communities with moral hazard. This research is more extensively compared with previous research that indicates that consumers engage in online communication because of altruism, reciprocity or to gain a higher status (Dichter et al., 1966).
The managerial part offers several practical suggestions for managers and marketers who employ WOM marketing techniques. The paper convinces managers and marketers to understand that WOM marketing techniques should be presented in a way that it is congruent with the ongoing character narratives, communication forums, norms and WOM environment and that their provided new narrative model should be considered.

Weaknesses
A downside of this article is that the gathered data consists of textual, online blogs. The interpretation and analyzing of the most important parts of these textual blogs takes a lot of time and effort. The researchers are completely dependent on the participants’ productivity and writing skills. I would suggest the researchers to use different studies as well (case study, interviews etc.), especially in combination with textual blog data.
The last note is that the limitations of this paper have not been discussed. I would suggest to include the limitations to make the paper more reliable.

Sources
Kozinets, R. V., De Valck, K., Wojnicki, A. C., & Wilner, S. J. (2010). Networked narratives: Understanding word-of-mouth marketing in online communities. Journal of marketing, 74(2), 71-89.

Grandma knows best: Online knowledge contribution


Today, one of my group members stained my suede jacket with permanent marker whilst discussing our business idea. After panicking, the first thing I did is type the sentence “how to get ink out of suede” into Google. The pages I end up at are online communities, in which people share their experiences on the same problem and provide me with the knowledge I need to remove the stain. This example might sound very familiar to you: There are more than 2550 of such communities worldwide! These online knowledge sharing platforms provide a space for social interaction where individuals can obtain knowledge and feedback and exchange opinions on certain topics, such as stain removal.

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