Integrating social network effects in the share-of-choice problem
dc.contributor.author | Danış, Dilek Günneç | |
dc.contributor.author | Raghavan, S. | |
dc.date.accessioned | 2017-02-06T08:25:49Z | |
dc.date.available | 2017-02-06T08:25:49Z | |
dc.date.issued | 2017-12 | |
dc.identifier.issn | 0011-7315 | en_US |
dc.identifier.uri | http://hdl.handle.net/10679/4771 | |
dc.identifier.uri | http://onlinelibrary.wiley.com/doi/10.1111/deci.12246/full | |
dc.description.abstract | Accounting for social network effects in marketing strategies has become an important issue. Taking a step back, we seek to incorporate and analyze social network effects on new product development and then propose a model to engineer product diffusion over a social network. We build upon the share-of-choice (SOC) problem, which is a strategic combinatorial optimization problem used commonly as one of the methods to analyze conjoint analysis data by marketers in order to identify a product with largest market share, and show how to incorporate social network effects in the SOC problem. We construct a genetic algorithm to solve this computationally challenging (NP-Hard) problem and show that ignoring social network effects in the design phase results in a significantly lower market share for a product. In this setting, we introduce the secondary operational problem of determining the least expensive way of influencing individuals and strengthening product diffusion over a social network. This secondary problem is of independent interest, as it addresses contagion models and the issue of intervening in diffusion over a social network, which are of significant interest in marketing and epidemiological settings. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Wiley | en_US |
dc.relation.ispartof | Decision Sciences | en_US |
dc.rights | restrictedAccess | |
dc.title | Integrating social network effects in the share-of-choice problem | en_US |
dc.type | Article | en_US |
dc.peerreviewed | yes | en_US |
dc.publicationstatus | published | en_US |
dc.contributor.department | Özyeğin University | |
dc.contributor.authorID | (ORCID 0000-0002-0749-2584 & YÖK ID 121183) Günneç, Dilek | |
dc.contributor.ozuauthor | Danış, Dilek Günneç | |
dc.identifier.volume | 48 | |
dc.identifier.issue | 6 | |
dc.identifier.startpage | 1098 | |
dc.identifier.endpage | 1131 | |
dc.identifier.wos | WOS:000418132700003 | |
dc.identifier.doi | 10.1111/deci.12246 | en_US |
dc.subject.keywords | Genetic algorithm | en_US |
dc.subject.keywords | Marketing | en_US |
dc.subject.keywords | Optimization | en_US |
dc.subject.keywords | Peer Influence | en_US |
dc.subject.keywords | Product design | en_US |
dc.subject.keywords | Social networks | en_US |
dc.identifier.scopus | SCOPUS:2-s2.0-84992549051 | |
dc.contributor.authorFemale | 1 | |
dc.relation.publicationcategory | Article - International Refereed Journal - Institutional Academic Staff |
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