The Cinderella moment: Exploring consumers' motivations to engage with renting as collaborative luxury consumption mode

Abstract

Past literature argued that the purchase of luxury goods is driven by people's motivation to conform or fit into our economic and social system. In this study, the authors focus on a new aspect of consumption, that is, renting instead of purchasing luxury goods, backed by the emerging opportunities of sharing economy platforms. Drawing upon the analysis of spontaneous consumers' online communications(in the form of tweets), this study aims to investigate the motivations to engage with luxury garment renting within a collaborative consumption context. To this end, a series of automatic content analyses, via two studies, were conducted using the tweets posted with respect to the Run the Runway collaborative consumption platform. Results demonstrate consumers' increased willingness to show their social status through renting rather than owning luxurious apparel based on five main motivators (need to wear new clothes for a special event, inspirations created by the products/brands, possibility to explore a new way of consuming luxury goods, need to make more sustainable choices, and to increase the life cycle of each luxury product). The implications of these findings are discussed, while they pave the way for future research in collaborative consumption of luxury retailing.

Consumer Acceptance and Value in Use-Oriented Product-Service Systems: Lessons from Swedish Consumer Goods Companies

“…For example, their consumers expressed joining u-PSS as "taking responsibility and giving products a second life" and as "consuming without feeling guilty". The latter statement confirms findings from recent studies where seemingly contradictory drivers, e.g., shaping social status through luxury apparel rental and sustainability aspirations, have been reported to influence consumer acceptance of u-PSS [48,74]. However, sustainability was often not the most prominent consumer value, nor is it a primary value communicated by the case companies.…”

When a luxury brand bursts: Modelling the social media viral effects of negative stereotypes adoption leading to brand hate

“…Finally, drawing upon recent studies considering consumer generated contents on social media as trustable source for consumer research that mainly focused on Twitter ( Aleti et al, 2019 , Athwal et al, 2019 , Dindar and Yaman, 2018 , Giglio et al, in press , Pantano and Stylos, 2020 , Walasek et al, 2018 ), our study adds new knowledge on the evaluation of Instagram posts as data source, by confirming that also this platform might provide useful insights for marketing research. In this way, our study further extends the few works ( Arora et al, 2019 , Casalo et al, 2020 , Riquelme et al, 2018 ), by describing how extracts consumers’ insights Instagram through new metrics and analytics, with emphasis on the specific sector of luxury brands.…”

“…The analysis of spontaneous information generated online by consumers is largely acquiring scholars’ interest because it provides a reliable source of insights for consumer research ( Aleti et al, 2019 , Arora et al, 2019 , Athwal et al, 2019 , Klostermann et al, 2018 , Pantano and Stylos, 2020 , Tellis et al, 2019 , Villarroel Ordens et al, 2017 ), including the fashion industry ( Pantano and Stylos, 2020 , Walasek et al, 2018 ). Since the analyses of users’ generated contents on Facebook, Instagram, Twitter allow determining how and how much certain concepts are mentioned and associated with by consumers ( Walasek et al, 2018 ), analyzing specifically the contents provides deeper insights if compared with the traditional research based on surveys ( Dindar & Yaman, 2018 ).…”

“…To evaluate the distribution of the popularity across time (from October to December 2018), the software provides a set of machine learning algorithms that can be used to extract information from unstructured data like posts shared on social networks ( Pantano and Stylos, 2020 , Valdivia et al, 2017 ). Machine learning algorithms are considered particularly efficient to extract patterns and make prediction on large data sets (as posts published online and shared among users) ( Giglio et al, in press ); in particular, the software provides the machine learning algorithms as pre-trained methods capable of manipulating and analyzing a wide range of unstructured data from different sources ( Zotos, 2007 ).…”

Counterfeit luxury consumption: A review and research agenda

“…As many consumers lack the resources to buy the first‐hand luxury, in the absence of sustainable modes of acquisition, consumers resort to counterfeits as affordable substitutes (Yoo & Lee, 2009). Luxury brands must, therefore, endeavor to offer sustainable modes of acquiring luxury goods, which not only can co‐create value for key stakeholders but also increase the life‐cycle of luxury goods (Pantano & Stylos, 2020). The phenomenon of sustainable consumption is tied to the disposing and the acquisition of used products (Turunen & Leipämaa‐Leskinen, 2015).…”