{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T22:21:59Z","timestamp":1770848519323,"version":"3.50.1"},"posted":{"date-parts":[[2026]]},"group-title":"SSRN","reference-count":31,"publisher":"Elsevier BV","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:p>The growing importance of sustainability in consumer markets in recent years has attractedthe attention of researchers in industry-related fields. Large-scale product networks, which comprisemillions of connections between consumers and green products, facilitate the identificationof consumer-driven relationships between products and enable an understanding of the dynamicsof sustainable consumption. It is well-known that understanding the dynamics of these networks does not require observing the entire network. In this work, we propose an efficient way to analyze the dynamics between consumers and products through an adaptive sampling process that combines the Random Walk and a novel Neighborhood Expansion Framework. Theproposed hybrid framework uses a bipartite network projection, and applies adaptive samplingusing weighted random walks, and neighborhood expansion to enable efficient and representativenetwork exploration. Networks are first projected onto product\u2013product similarity networks,where clusters of co-consumed items may reveal sustainability-oriented market segments. Then,adaptive weighted random walks dynamically balance the representation of popular and nichesustainable products, while neighborhood expansion preserves local structural context. We applythis novel methodology to consumer-product networks of sustainability-related attributesthat influence purchasing decisions, such as rankings and discounts, since the size and heterogeneityof such networks make direct analysis computationally challenging. Comparative resultsshow that the proposed approach outperforms uniform sampling in terms of efficiency, structuralfidelity, and retention of sustainability-related diversity. Empirical applications demonstrate itspotential to identify sustainability clusters, uncover links between eco-labeled and conventionalproducts, and support data-driven strategies for sustainable market transitions.<\/jats:p>","DOI":"10.2139\/ssrn.6221481","type":"posted-content","created":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T21:37:10Z","timestamp":1770845830000},"source":"Crossref","is-referenced-by-count":0,"title":["Adaptive Sampling Strategies for Large-Scale Green ProductNetworks: A Random Walk and Neighborhood ExpansionFramework"],"prefix":"10.2139","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3617-8754","authenticated-orcid":true,"given":"Manuela","family":"Maia","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5495-9434","authenticated-orcid":true,"given":"Pedro","family":"Campos","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"2","key":"ref1","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1016\/0749-5978(91)90020-T","article-title":"The theory of planned behavior","volume":"50","author":"I Ajzen","year":"1991","journal-title":"Organizational Behavior and Human Decision Processes"},{"issue":"4","key":"ref2","first-page":"1","article-title":"Consumer-brand interaction networks and behavioral convergence","volume":"15","author":"S Banerjee","year":"2021","journal-title":"ACM Transactions on Knowledge Discovery from 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