Pre-release member participation as potential predictors of post-release community members’ adoption behaviour: evidence from the motion picture industry

Abstract

Web 2.0-based online communities have seen a growing popularity in recent years both in terms of the volume of academic research publications and practical implications. Earlier studies have investigated the consequences of member participation in online brand communities such as improving brand image, product recommendation behaviour, creating oppositional loyalty towards competitor brands, etc. As a development of this research, this study shows pre-release member participation and members’ online activities as potential predictors of community members’ future adoption behaviour by (1) focusing on product-specific member participation and (2) by differentiating between pre-release and post-release member participation. Community members participate in online communities not only after product purchase or usage but also long before the product is introduced in the market (i.e. pre-release member participation) and especially in response to firms’ announcement of upcoming product releases. Within this context of new product preannouncement, the Theory of Planned Behaviour is applied to show that pre-release member participation in online activities is a potential predictor of the entire community's post-release adoption behaviour, using a movie-based online community. Moreover, the community adoption behaviour shows a strong positive association (mirroring effect) with market adoption behaviour suggesting that online community is a good representation of market adoption behaviour.

Keywords:

• online community
• customer participation
• community behaviour
• market behaviour

Notes

Examples of communities based on multiple brands of different firms are (1) phonearena.com – provides information about upcoming mobile phones from different brands and companies, (2) ign.com – provides information about upcoming video games), (3) cnet.com – provides information, tools and advice to help purchase decisions, (4) movie-based communities such as Flixter.com, Fandango.com, ClevverMovies.com, Comingsoon.net – all of them provide information about upcoming movie releases and (5) ebay.com and amazon.com – online shopping centers for various product categories and brands also provide online forums for customers.

For example, the age group of members who rated a children/family movie ‘Cloudy with a Chance of Meatballs’ were younger than 18 years (22 members rated it), 18–24 years old (117 members), 25–34 years old (120 members), 35–44 years olds (73 members), 45–54 years old (23 members) and 55 years and older (15 members).

166,467 community members represent the sum of the ‘total member participation’ of each of the 373 movies released during a 16-month period starting from September 2009 to December 2010.

In the case of movie adoption, examples of perceived behaviour control for moviegoers include availability of time available to watch a movie, money, etc., and assuming that all community members have control over these factors control over these factors .

Members with weak ties to community and low consumption activity.

Members with weak ties to community but high consumption activity.

Members with strong ties to community and high consumption activity.

Members with strong ties to community but low consumption activity.

In this case, carryover effect means that the box office revenues collected in the opening week influences the revenue collection in the 2nd week, and the 2nd week BO collection influences BO revenues in the 3rd week and so on.