مقاله انگلیسی رایگان در مورد ارزیابی مصرف مشارکتی خدمات تحویل مواد غذایی – الزویر ۲۰۱۸

Introduction

Collaborative consumption (CC) is a new form of consumer behavior with important implications for business research (Benoit et al., 2017). CC takes place when people coordinate the acquisition and distribution of a resource. This coordination is frequently done for a fee or other non-monetary compensation through trading, bartering, and swapping (Belk, 2014). It is “the peer-to-peer-based activity of obtaining, giving, or sharing the access to goods and services, coordinated through community-based online services” (Hamari et al., 2016), p. 2047. According to some scholars, it is not clear the future growth of CC and its impact on incumbent industries (Barnes and Mattsson, 2017). However, as an emerging phenomenon from the computer-mediated interaction between customers and providers, CC is present in a vast range of business, such as transportation (Uber, Zipcar), lodging (Airbnb), tourism (Couchsurfing), entertainment (Spotify) and online food delivery services (Just-Eat.com, Clickdelivery.com, UberEATS) (Pigatto et al., 2017). Online food delivery services (OFD) offer opportunities for research as they are underrepresented in the literature of CC. According to Pigatto et al. (2017) these services can be characterized as business platforms that provide order services, payment and monitoring of the process but are not responsible for the preparation and order delivery operations. Although large fast-food chains like McDonald’s or Domino’s Pizza offer their delivery services, small or medium restaurants chains have seized the emergence of intermediaries that provide these sort of services (Yeo et al., 2017). Despite the popularity of these platforms nowadays, their connection with CC remains neglected. The words “Online Food Delivery” are missing in most recent papers of CC (Pigatto et al., 2017; Hamari et al., 2016; Benoit et al., 2017; de Rivera et al., 2017), and the publications that aim the study of OFD (Hong et al., 2016; Gupta and Paul, 2016; Yeo et al., 2017) do not mention CC either. This lack of connection does not imply that they are independent and unrelated consumption phenomena. It only means that a relevant theoretical framework that illustrates the relationship between the two remains fragmented and illdefined. Our aim here is to tackle this gap. Our approach posits the relevance of evaluating the impact of traffic conditions on the customer-provider relationship because OFD and CC are intrinsically related to urban transportation. This approach deviates from what we call the “standard methodological approach” that relies on surveys for data collection purposes. Although survey data is often intended to measure quality service through customers’ perception, this perception does not reflect delivery time accurately. We do not claim that surveys are useless to studying the customerprovider relationship. In fact, they are still present along with other data collection techniques in the researcher’s toolbox (Garrett et al., 2017; Scaraboto, 2015). Nonetheless, we grant fundamental importance to the sort of data that is available on websites or smartphone apps, as they reflect the spontaneous information of customers and providers who use a platform to enjoy the benefits of CC. The following example will illustrate this point. Imagine a client ordering a pizza, and the platform notes his pizza will be at home in less than 35 min, but it arrived an hour later due to a massive traffic jam. From a frequent customer’s view, this event might have none impact on the service perception. For a first-time customer, in contrast, this event might be perceived differently. Another important observation regarding these platforms is that they can be strategic tools for business competitiveness (Yeo et al., 2017; Jiang and Tian, 2016; Lindblom and Lindblom, 2017). For example, providers who track and adjust their delivery times according to traffic conditions might increase the number of customers, as their clients will be sure that they will receive their orderings on time or a price discount for delivery delays. This example shows that the everchanging nature of traffic dynamics is relevant for all business segments that rely on transportation to promote CC. The UberEATS application (https://www.ubereats.com/), for example, represents a successful case that shows how a brand like Uber can also be compatible with a related service like food delivery.