Dowling / Spann Consumer Behavior and Behavioral Biases in the Sharing Economy

1. Auflage 2019
ISBN: 978-3-7504-7243-3
Verlag: Books on Demand
Format: EPUB
Kopierschutz: Wasserzeichen (»Systemvoraussetzungen)

E-Book, Englisch, 192 Seiten

Sharing business models have been rapidly growing over the past decade. The general idea behind these platforms is that they offer consumers temporary access to (underutilized) products instead of ownership, which is mediated by the Internet. Apart from its economic relevance, the Sharing Economy is of particular interest to researchers, as prior studies have shown that the Sharing Economy seems to fundamentally change consumers´ consumption patterns. This dissertation systematically explores consumer behavior and behavioral biases in the Sharing Economy. More specifically, this dissertation analyzes the influence of behavioral biases on consumers´ tariff choice decisions in a sharing context. In doing so, this dissertation employs empirical and experimental methods and draws on theories from both marketing and behavioral economics. This dissertation consists of four articles. Article 1 and Article 2 are conceptual papers that set the foundation of this dissertation by providing theoretical insights on the state-of-the-art research on the Sharing Economy and on behavioral biases in marketing. Building on this theoretical foundation, two empirical articles (Article 3 and Article 4) analyze different research questions related to consumers´ decision-making in a tariff choice context.

Katharina Dowling is a Doctoral Researcher at the Institute of Electronic Commerce and Digital Markets at Ludwig-Maximilians-Universität (LMU) München - Munich School of Management. She holds a B.Sc. and a M.Sc. from the University of Mannheim and the ESSEC Business School in Paris. She earned her Ph.D. in 2019 at LMU´s Munich School of Management.

Autoren/Hrsg.

Dowling, Katharina

Spann, Martin

Leseproben

Introduction
1 Motivation and Objectives
Sharing business models have been rapidly growing over the past decade (Burtch, Carnahan, & Greenwood, 2018; Proserpio, Xu, & Zervas, 2018). They are referred to as the Sharing Economy, collaborative consumption, on-demand economy, peer economy, or gig economy (Narasimhan et al., 2018; Parente, Geleilate, & Rong, 2018). Despite the various names, the general idea behind these platforms is that they offer consumers temporary access to (underutilized) products instead of ownership, which is mediated by the Internet (Belk, 2014). In contrast to earlier Internet-based platforms such as eBay, sharing platforms focus on facilitating recurring short-term rental or service provision, rather than on a resale in which the asset ownership is transferred (Fraiberger & Sundararajan, 2017). While the concept of “sharing” is not new, the development of sharing platforms as they exist today only accelerated with the technological advancement of network technology and the mass adoption of mobile devices and apps, which reduced transaction costs and simplified the matching of buyers and sellers (Horton & Zeckhauser, 2016). At the core of the Sharing Economy are the so-called peer-to-peer (P2P) platforms (Andersson, Hjalmarsson, & Avital, 2013; Proserpio & Tellis, 2017). On a P2P platform, transactions take place between consumers (i.e., peers), and the platform acts as a matchmaker to pair peers either in a centralized or decentralized way (Perren & Kozinets, 2018). The number of business-to-consumer (B2C) platforms and business-to-business (B2B) platforms is also increasing (Laczko, Hullova, Needham, Rossiter, & Battisti, 2018). On B2C platforms, the platform occupies both the role of the matchmaker and the provider of products. B2B platforms enable transactions between businesses. Prominent examples of P2P platforms are Uber (ride sharing) and Airbnb (hospitality). A typical example of a B2C platform is Zipcar (car sharing). The We Company (workspace) can be an example of both a B2C and a B2B platform, since it offers workspace for individuals or entire firms. Uber, The We Company, and Airbnb are prime examples of the Sharing Economy’s economic relevance. They are valued at $72bn, $47bn, and $31bn, respectively, which places them among the most valuable start-ups in the world (Leskin, 2019). Moreover, the rapid growth of the Sharing Economy is likely to continue. New markets (e.g., emerging markets), new demographic groups (women and the elderly), and new product categories (e.g., fashion and clothing and equipment rental) are expected to drive growth in the next years (Rinne, 2019; Wallenstein & Shelat, 2017). Additionally, technological advancements such as self-driving cars, drones, and delivery robots will further decrease transaction costs, making the temporary access to products even faster and more convenient (Wallenstein & Shelat, 2017). Apart from its economic relevance and projected growth, the Sharing Economy is of particular interest to researchers, as prior studies have shown that the Sharing Economy seems to fundamentally change consumers’ consumption patterns (Zervas, Proserpio, & Byers, 2017). The Sharing Economy not only generates incremental economic activity but also substitutes products supplied by traditional firms (Contreras & Paz, 2018; Zervas et al., 2017). With the expansion of sharing services into a growing number of product categories, consumers are increasingly faced with decisions between access and ownership. What is particularly interesting about this decision is that products that are most suitable for sharing are high-priced durable products (Horton & Zeckhauser, 2016). The process of purchasing a high-priced durable product is typically characterized by high involvement and thorough deliberation due to high investments and status considerations (Putsis & Srinivasan, 1994). However, accessing a durable product through a sharing service is very flexible and convenient (Lamberton & Rose, 2012). The entirely different nature of the two options makes the decision very complex. To decide between access and ownership, consumers need to make assessments regarding their future consumption, the resulting costs, and developments in the market environment (Koenigsberg, Kohli, & Montoya, 2011). Consumer decisions in these complex situations are likely to be biased. Belief-based biases, for example, arise when uncertainty is involved in decisions (DellaVigna, 2009; Rabin, 2002). For instance, consumers could form incorrect beliefs about their future behavior (e.g., monthly usage) and the market environment (e.g., developments in technology or regulation). Applied to the automotive industry, consumers might want to avoid ambiguity with regard to their monthly bill and therefore prefer purchasing a car. However, the overconfidence of consumers could also lead them to underestimate their actual car usage, leading them to choose the allegedly cheaper car sharing option. Apart from the decision between access and ownership, behavioral biases could also help explain consumer behavior in sharing services. Although sharing and owning can be seen as substitutes, consumers’ motives for using a sharing service often differ from those of owning (Lamberton & Rose, 2012). Specific characteristics of sharing services such as flexibility and convenience might yield different bias patterns than those documented for more traditional products. For example, tariff choice research in the context of long-term service contracts has widely documented that consumers do not always make optimal (i.e., cost-minimizing) tariff choice decisions1 (DellaVigna & Malmendier, 2006; Lambrecht & Skiera, 2006). In these contexts, consumers often exhibit a flat-rate “bias”, i.e., consumers choosing a flat-rate, although they would have saved money under a pay-per-use tariff. Given the novelty of sharing services and the increasing tariff range (e.g., the introduction of monthly flat-rates by Uber and Lyft), it is likely that consumers also make “errors” when choosing a pricing plan for a sharing service. A preference for flexibility might induce consumers to choose the pay-per-use option more often in order not to commit to the less flexible flat-rate option, leading to a pay-per-use “bias”, i.e., consumers choosing a pay-per-use tariff, although they would have saved money with a flat-rate (Krämer & Wiewiorra, 2012). Thus, it is unclear whether and how behavioral biases influence tariff choice decisions in a sharing context. A thorough understanding of behavioral effects in the Sharing Economy is important for consumers, platforms, traditional firms, and public policy alike. Consumers can largely benefit from the Sharing Economy through flexible access to products for lower prices and an alternative form of income (Fraiberger & Sundararajan, 2017). However, given the complexity and uncertainty involved in the decision between access and ownership as well as in the decisions within sharing services, consumers are likely to make biased decisions. Seemingly small errors can have large financial effects in the long run (Miravete, 2002), especially in a high-priced durable products context. From a societal perspective, the Sharing Economy has the potential to foster innovation and to help fight major problems such as the waste of resources, traffic, and emissions (Teubner & Flath, 2015). A good understanding of behavioral effects in consumer behavior can help sharing platforms improve their marketing mix and thereby address pressing problems such as platform switching or churn (Lambrecht & Skiera, 2006). Traditional firms need to thoroughly understand the drivers of the decision between access and ownership to identify strategies that will enable them to remain relevant in the future. For example, some traditional firms have decided to offer their own sharing service to counter the competition (e.g., BMW or MediaMarkt). Finally, behavioral effects in the Sharing Economy can inform public policy on how to design regulations that avoid the incorrect processing of information and biased choices. For example, policy makers could make use of framing to adapt the information or choice-elicitation interfaces provided to consumers to attenuate biases and to increase social welfare. In summary, the Sharing Economy is particularly interesting for researchers given its economic relevance and the way in which it changes consumers’ consumption patterns. The uncertainty and complexity involved in consumers’ decisions in a sharing context makes the occurrence of behavioral biases very likely. A thorough understanding of behavioral drivers in a sharing context is important for consumers, firms, and public policy alike. However, the influence of behavioral biases in the Sharing Economy remains largely unexplored. The overall objective of this dissertation is to enhance the understanding of the behavioral drivers of consumer behavior in the Sharing Economy. More specifically, this dissertation analyzes the influence of behavioral biases on consumers’ tariff choice decisions. In doing so, this dissertation employs empirical and experimental methods and draws on theories from marketing and behavioral economics. 2 Contribution of the Dissertation
This dissertation contributes to three streams of research: (1) consumer behavior in the sharing literature, (2) consumers’ tariff choices and biases in the tariff choice literature, and (3) behavioral biases in the marketing literature. First, this dissertation contributes to...