Understanding Usage Behaviour in a Peer-to-Peer Task Community

Publication Type

Contribution to conference

Authors

Deliège, F., Ates, Z., Benoit, S., Büttgen, M.

Year of publication

2016

Published in

Conference Proceedings AMA SERVSIG 2016

Page (from - to)

96-100

Conference name

SERVSIG Conference

Conference location

Maastricht, the Netherlands

Conference date

June 17-19, 2016

Abstract

Understanding Usage Behaviour in a Peer-to-Peer Rental Community

The popularity of peer-to-peer (P2P) rental communities is growing both in academic research and business practice (Belk 2014, Chakravarty, Kumar et al. 2014). This trend fosters the emergence of new markets and innovative business models which challenges the viability of existing industry practices but creates major opportunities for companies as well (Ozanne and Ballantine 2010, Baumeister, Scherer et al. 2015). This trend is part of broader phenomena called Collaborative Consumption or the P2P Economy: “it is people coordinating the acquisition and distribution of a resource for a fee or other compensation” (Belk 2014) as well as Access-Based Consumption: “”instead of buying and owning things, consumers want access to goods and prefer to pay for the experience of temporarily accessing them” (Bardhi and Eckhardt 2012). Consumers are increasingly curious about these alternative consumption modes and most of them have now at least once used a car sharing system, shared their house, participated to a crowdfunding platform, been a member of a collaborative garden, etc. (Stern 2015).  

Regarding P2P rental communities, it has been estimated at 26$ billion and a rapid growth is still expected for the coming years (Sacks 2011, Owyang, Samuel et al. 2014). These P2P rental communities, also called two-sided markets, are new business models with a new channel format (Watson IV, Worm et al. 2015). Indeed, it differs from a dyadic channel, which is the most commonly studied format in marketing research, as it only implies interactions between two entities (manufacturers with distributors and distributors with consumers). On the contrary, P2P rental communities imply a triadic relationship, which occurs via an online platform. The members coordinate the disposition and the use of a resource between demanders and suppliers whereas the companies only act as a trusted third party by simply facilitating the transaction (Dervojeda, Verzijl et al. 2013). Furthermore, it also differs from traditional markets as companies do not own any resource. Companies’ main objectives are to attract and to retain members as well as to match both sides of the community (Chakravarty, Kumar et al. 2014).

To cope with this change in the business environment, managers who want to innovate and to develop new P2P rental communities need to better understand both sides of the community with regard to users’ profiles, needs and behaviours (Baumeister, Scherer et al. 2015, Watson IV, Worm et al. 2015). However, only little research in the field of marketing focuses on P2P rental communities as well as on the two-sided market (Watson IV, Worm et al. 2015). Furthermore, the existing literature fails to investigate both sides of P2P rental communities as the two-sided market literature mainly focuses on selling and buying transactions. Finally, most of the existent research on access-based consumption focuses on product access but it largely ignores tasks access and it assumes consumers behaviour as homogeneous.

Understanding both sides of community, this study contributes to identify and to define different usage behaviour within P2P-task rental communities (P2P-TRC) through (1) an examination of usage’ behaviour heterogeneity in the context of P2P-TRC and (2) an exploration of profiles of one-time users as well as their perceived motives and barriers. This study is based on three-years transaction-level data provided by Listminut, a large P2P community that allows demanders to post a task (e.g., cleaning a house or babysitting) and suppliers who claim to have the specific capacity or expertise to send a proposal to fulfil the task. All members have the option to engage in both sides of the community. They can be either one-way users (demanders or suppliers), two-way users (demanders and suppliers), non-users (members who have not participated yet in any transaction but they might do so in the future) (Philipa, Ozanne et al. 2015). The database gathers around 20.000 members with more than 5.000 posted tasks, 6.500 offers, 1.500 accepted offers and 13.000 conversations. A three-step mixed-method approach is used to empirically identify and explore different behaviours of demanders and suppliers.

The authors, as a first step, start running a series of linear regressions aiming at identifying the transactional and demographic variables which have an impact on the performance indicators. These indicators represent, for demanders, a posted task which was successfully outsourced and, for suppliers, an offer which was accepted. Fifteen relevant variables (e.g. average price proposed by demander, average conversation received by posted task, average estimated time to handle the task) have been found. As a second step, these relevant independent variables are used in a cluster analysis combining both hierarchical (Ward’s method) and non-hierarchical (k-means method) methods. The authors identify four different segments of suppliers: concession-makers (11%), multi-skills suppliers ready for everything (31%), money driven suppliers with poor performance (36%) and non-active ones (22%) as well as four different segments of demanders: match-makers (55%), demanders afraid to trust (11%), socializers arising little interest (27%) and popular requesters with high expectations (7%). The creation of the segments relies mainly on usage characteristics rather than on demographic data. On both sides of the community, segments show significant differences regarding the clustering variables. In addition, for each cluster, the authors strengthen their interpretation and refine the members’ profile by using the performance indicators, other variables that characterise the task (for example: the required skills to perform a task such as physical, social and knowledge ability as well as trust level) but do not relate directly to members and variables that are not significant with regard to the regression analysis. All segments show different success performance and different behaviours among users. First of all, the results indicate that demanders and suppliers behaviours are partly influenced by the skills required to perform the task. Secondly, the results show that demanders’ success is influenced by their own expectations, usage and interaction characteristics. For example, successful demanders connect often to the platform but they do not interact that often with suppliers and they have no expectation for high level of trust, physical ability or specific knowledge with regard to the suppliers’ skills. Thirdly, suppliers’ success is highly driven by the ability of those to meet demanders’ expectations and not necessarily by their own expectations. Indeed, their success is characterised by low salary acceptance, long duration job and high usage intensity that means frequent connexion to the online platform and frequent interaction with demanders. Finally, all segments are characterised by a high percentage of one-time users who start using the platform and then decide to stop after the first successful or unsuccessful use of it. This is the result of the third step of this study which aims at exploring profiles, motives and barriers of one-time users through qualitative interviews. The authors will conduct 20 semi-structured interviews with customers (suppliers and demanders) who have started once using Listminut platform and who are now, for one year at least, inactive members. The objective is twofold: to find factors that influence members’ retention and to understand what could influence one-time users’ re-activation.

This study contributes to extant literature in several ways: First, the present research identifies and explores different users’ behaviours for both sides of a P2P rental community and for customers who have been considered as homogenous so far. Understanding heterogeneity among customers can help managers to better target potential users and to communicate more effectively to their members. Second, the research identifies relevant factors which explain transaction success for both sides of the community. Better understanding how to satisfy suppliers and demanders is a critical issue for P2P rental communities as it increases the chance of a perfect match. Third, it investigates deeper the one-time users scenarios in relation with their perceived motives and barriers. This can help P2P rental communities to develop strategies to keep users active. Furthermore, using transactions data to establish some main effects and a qualitative approach to investigate the logic behind these effects makes the study unique and reflects accurately the reality of P2P-TRC.  Finally, this work gives recommendations to managers on which retention strategies should be developed according to users’ profile (success / usage).

 

 

 

References

Bardhi, F. and G. M. Eckhardt (2012). "Access-Based Consumption: The Case of Car Sharing." Journal of Consumer Research 39(4): 881-898.

Baumeister, C., A. Scherer and F. v.Wangenheim (2015). "Branding access offers: the importance of product brands, ownership status, and spillover effects to parent brands

" Journal of the Academy Marketing Science.

Belk, R. (2014). "You Are What You Can Access: Sharing and Collaborative Consumption Online." Journal of Business Research 67: 1595–1600.

Chakravarty, A., A. Kumar and R. Grewal (2014). "Customer Orientation Structure for Internet-Based Business-to-Business Platform Firms." Journal of Marketing 78(5): 1-23.

Dervojeda, K., D. Verzijl, F. Nagtegaal, M. Lengton, E. Rouwmaat, E. Monfardini and L. Frideres (2013). The Sharing Economy: Accessibility Based Business Models for Peer-to-Peer Markets. European Commission: Business Innovation Observatory

Owyang, J., A. Samuel and A. Grenville. (2014). "Sharing Is The New Buying."   Retrieved October, 1 2015, 2015, fromhttp://www.web-strategist.com/blog/research/.

Ozanne, L. K. and P. W. Ballantine (2010). "Sharing As a Form of Anti-Consumption? An Examination of Toy Library Users." Journal of Consumer Behaviour 9(6): 485-498.

Philipa, H. E., L. K. Ozanne and P. W. Ballantinea (2015). "Examining temporary disposition and acquisition in peer-to-peer renting." Journal of Marketing Management 31(11-12): 1310-1332.

Sacks, D. (2011). "The sharing economy." fromhttp://www.fastcompany.com/1747551/sharing-economy.

Stern, N. (2015). Enquête "Je partage! Et vous?".

Watson IV, G. F., S. Worm, R. W. Palmatier and S. Ganesan (2015). "The Evolution of Marketing Channels: Trends and Research Directions." Journal of Retailing.