Subtopic Deep Dive

Collaborative Consumption
Research Guide

What is Collaborative Consumption?

Collaborative consumption refers to peer-to-peer exchanges of goods and services through digital platforms, enabling consumers to access underutilized assets without ownership transfer.

This subtopic examines consumer motivations, trust dynamics, and economic impacts in sharing platforms like car-sharing and Airbnb. Key studies include Bardhi and Eckhardt (2012) with 1920 citations defining access-based consumption and Benoit et al. (2017) with 525 citations proposing a triadic framework for motives, activities, and capabilities. Over 10 high-citation papers from 2011-2020 analyze patterns in tourism, hospitality, and circular economy contexts.

15
Curated Papers
3
Key Challenges

Why It Matters

Collaborative consumption reshapes markets by reducing ownership needs, as shown in Zervas et al. (2013, 557 citations) estimating Airbnb's impact on hotels using econometric models on Boston data. Bardhi and Eckhardt (2012) reveal how car-sharing alters possession meanings, informing platform design. Ter Huurne et al. (2017, 430 citations) identify trust antecedents, guiding risk mitigation in peer exchanges. These insights predict consumer shifts and optimize platforms like Uber.

Key Research Challenges

Building Platform Trust

Users face opportunism risks in peer exchanges, requiring trust in strangers and platforms. Ter Huurne et al. (2017) systematically review antecedents like reputation systems. Benoit et al. (2017) highlight capability gaps in triadic actor interactions.

Measuring Economic Impacts

Quantifying sharing effects on traditional sectors remains complex due to data scarcity. Zervas et al. (2013) use difference-in-differences to estimate Airbnb's hotel impact. Langley and Leyshon (2017) critique platform capitalization metrics.

Motivating Sustained Participation

Psychological and social barriers hinder long-term engagement. Bardhi and Eckhardt (2012) contrast access with ownership motives in car-sharing. Schor et al. (2020) examine precarity in platform labor dynamics.

Essential Papers

1.

Smart tourism: foundations and developments

Ulrike Gretzel, Μαριάννα Σιγάλα, Zheng Xiang et al. · 2015 · Electronic Markets · 2.0K citations

Abstract Smart tourism is a new buzzword applied to describe the increasing reliance of tourism destinations, their industries and their tourists on emerging forms of ICT that allow for massive amo...

2.

Access-Based Consumption: The Case of Car Sharing: Table 1.

Fleura Bardhi, Giana M. Eckhardt · 2012 · Journal of Consumer Research · 1.9K citations

Access-based consumption, defined as transactions that can be market mediated but where no transfer of ownership takes place, is becoming increasingly popular, yet it is not well theorized. This st...

3.

Platform capitalism: The intermediation and capitalisation of digital economic circulation

Paul Langley, Andrew Leyshon · 2017 · Finance and Society · 879 citations

Abstract A new form of digital economic circulation has emerged, wherein ideas, knowledge, labour and use rights for otherwise idle assets move between geographically distributed but connected and ...

4.

The Rise of the Sharing Economy: Estimating the Impact of Airbnb on the Hotel Industry

Georgios Zervas, Davide Proserpio, John W. Byers · 2013 · SSRN Electronic Journal · 557 citations

5.

Understanding platform business models: A mixed methods study of marketplaces

Karl Täuscher, Sven M. Laudien · 2017 · European Management Journal · 550 citations

6.

A triadic framework for collaborative consumption (CC): Motives, activities and resources & capabilities of actors

Sabine Benoit, Thomas L. Baker, Ruth N. Bolton et al. · 2017 · Journal of Business Research · 525 citations

This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommon...

7.

What do Airbnb users care about? An analysis of online review comments

Mingming Cheng, Xin Jin · 2018 · International Journal of Hospitality Management · 463 citations

Reading Guide

Foundational Papers

Start with Bardhi and Eckhardt (2012, 1920 citations) for access-based consumption theory; Zervas et al. (2013, 557 citations) for empirical impact estimation; Leismann et al. (2013, 242 citations) for resource-saving culture links.

Recent Advances

Study Benoit et al. (2017, 525 citations) triadic framework; ter Huurne et al. (2017, 430 citations) trust review; Schor et al. (2020, 455 citations) on platform precarity.

Core Methods

Econometric models like difference-in-differences (Zervas et al., 2013); systematic literature reviews (ter Huurne et al., 2017); triadic actor frameworks (Benoit et al., 2017); qualitative access contrasts (Bardhi and Eckhardt, 2012).

How PapersFlow Helps You Research Collaborative Consumption

Discover & Search

Research Agent uses searchPapers('collaborative consumption motives') to retrieve Bardhi and Eckhardt (2012), then citationGraph to map 1920 citing works, and findSimilarPapers for trust studies like ter Huurne et al. (2017). exaSearch uncovers niche platform precarity papers like Schor et al. (2020).

Analyze & Verify

Analysis Agent applies readPaperContent on Benoit et al. (2017) triadic framework, verifyResponse with CoVe to check motive classifications against raw data, and runPythonAnalysis for regression replication from Zervas et al. (2013) using pandas on extracted datasets. GRADE grading scores evidence strength in trust reviews.

Synthesize & Write

Synthesis Agent detects gaps in trust-motivation links across Bardhi (2012) and ter Huurne (2017), flags contradictions in economic impact claims, and uses exportMermaid for actor diagrams. Writing Agent employs latexEditText for framework revisions, latexSyncCitations for 10-paper bibliographies, and latexCompile for polished reports.

Use Cases

"Replicate Airbnb hotel impact regression from Zervas et al. 2013"

Research Agent → searchPapers → Analysis Agent → readPaperContent + runPythonAnalysis (pandas diff-in-diff) → matplotlib plots of occupancy drops.

"Draft LaTeX review of collaborative consumption frameworks"

Synthesis Agent → gap detection on Benoit 2017 + Bardhi 2012 → Writing Agent → latexEditText + latexSyncCitations + latexCompile → camera-ready PDF with diagrams.

"Find GitHub repos implementing sharing economy simulations"

Research Agent → citationGraph on Langley 2017 → Code Discovery → paperExtractUrls → paperFindGithubRepo → githubRepoInspect → runnable agent-based models.

Automated Workflows

Deep Research workflow conducts systematic review of 50+ collaborative consumption papers, chaining searchPapers → citationGraph → GRADE grading for structured trust antecedent report. DeepScan applies 7-step analysis with CoVe checkpoints to verify Bardhi (2012) access motives against recent citations. Theorizer generates hypotheses on platform precarity from Schor et al. (2020) and Langley (2017).

Frequently Asked Questions

What defines collaborative consumption?

Collaborative consumption involves market-mediated access to assets without ownership, as defined by Bardhi and Eckhardt (2012) in car-sharing contexts.

What methods study participation motives?

Benoit et al. (2017) use a triadic framework analyzing motives, activities, and actor capabilities; ter Huurne et al. (2017) apply systematic review to trust antecedents.

What are key papers?

Bardhi and Eckhardt (2012, 1920 citations) on access-based consumption; Zervas et al. (2013, 557 citations) on Airbnb impacts; Benoit et al. (2017, 525 citations) on triadic framework.

What open problems exist?

Sustained participation amid precarity (Schor et al., 2020); scalable trust beyond reviews (ter Huurne et al., 2017); long-term economic displacement measurement.

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