{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T13:51:09Z","timestamp":1774446669496,"version":"3.50.1"},"reference-count":73,"publisher":"Emerald","issue":"11","license":[{"start":{"date-parts":[[2022,8,22]],"date-time":"2022-08-22T00:00:00Z","timestamp":1661126400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["K"],"published-print":{"date-parts":[[2023,11,9]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title><jats:p>The incentive cost of enterprises increases significantly with the rapid growth of the social commerce (SC) market. In this context, enterprises need to develop the optimal strategy to improve incentive effectiveness and reduce cost. Different types of consumers\u2019 responses to incentives bring different values to enterprises. Hence, this paper proposes the social commerce value network (SCVN) to help enterprises study the contributions of different types of consumers to the network.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>Based on the graphical evaluation and review technique (GERT), the authors construct the social commerce value GERT (i.e. SCV-GERT) network and design three progressive experiments for estimating the value contributions of \u201cnetwork stage\u201d, \u201cconsumer type\u201d, and \u201cresource type\u201d to the SCVN under the same incentives. The authors initialize the SCV-GERT model with consumer data in SC and distinguish the most valuable consumers by adjusting the incentive parameters.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>The results show that the SCV-GERT model can well describe the value flow of SCVN. The incentive on forwarding consumers brings the greatest value gain to the SCVN, and social trust contributes the most to forwarding consumers.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Practical implications<\/jats:title><jats:p>Under the guidance of the results, platforms and enterprises in SC can select the optimal type of consumers who bring the maximum network value so as to improve the effectiveness of incentive strategy and reduce marketing costs. A four-level incentive system should be established according to the ranking of the corresponding value gains: forwarding consumers\u00a0&gt;\u00a0agent consumers\u00a0&gt;\u00a0commenting consumers\u00a0&gt;\u00a0potential consumers. Enterprises also need to find ways to improve the social resource investments of consumers participating in SC.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>This paper investigates the incentive problem in SC grounded in the SCVN and uses the GERT method to construct the SCV-GERT model, which is the first attempt to introduce GERT into the SC context. This study also makes up for the lack of comparative research on different types of consumers in SC and can provide support for enterprises\u2019 customer relationship management and marketing decisions.<\/jats:p><\/jats:sec>","DOI":"10.1108\/k-03-2022-0384","type":"journal-article","created":{"date-parts":[[2022,8,17]],"date-time":"2022-08-17T13:46:12Z","timestamp":1660743972000},"page":"5530-5560","source":"Crossref","is-referenced-by-count":5,"title":["Distinguishing the most valuable consumers in social commerce using graphical evaluation and review technique \u2013 in the view of incentives"],"prefix":"10.1108","volume":"52","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3167-2358","authenticated-orcid":false,"given":"Xu","family":"Chen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0248-7900","authenticated-orcid":false,"given":"Yingliang","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2493-2526","authenticated-orcid":false,"given":"Junfeng","family":"Liao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2233-2511","authenticated-orcid":false,"given":"Wenming","family":"Zuo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2590-4607","authenticated-orcid":false,"given":"Rujie","family":"Zhong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","published-online":{"date-parts":[[2022,8,22]]},"reference":[{"issue":"2","key":"key2023110803375815600_ref001","doi-asserted-by":"publisher","first-page":"217","DOI":"10.1287\/mksc.1100.0596","article-title":"Identifying social influence: a comment on opinion leadership and social contagion in new product diffusion","volume":"30","year":"2011","journal-title":"Marketing Science"},{"key":"key2023110803375815600_ref002","doi-asserted-by":"publisher","first-page":"1352","DOI":"10.1287\/mnsc.2014.1936","article-title":"Tie strength, embeddedness, and social influence: a large-scale networked experiment","volume":"60","year":"2014","journal-title":"Management Science"},{"key":"key2023110803375815600_ref003","doi-asserted-by":"publisher","first-page":"557","DOI":"10.1016\/j.jbusres.2018.07.008","article-title":"Authenticity under threat: when social media influencers need to go beyond self-presentation","volume":"117","year":"2020","journal-title":"Journal of Business Research"},{"key":"key2023110803375815600_ref004","doi-asserted-by":"publisher","first-page":"407","DOI":"10.1016\/j.jbusres.2017.11.047","article-title":"Customer segmentation in e-commerce: applications to the cashback business model","volume":"88","year":"2018","journal-title":"Journal of Business Research"},{"issue":"3","key":"key2023110803375815600_ref005","doi-asserted-by":"publisher","first-page":"589","DOI":"10.1007\/s11846-018-0316-x","article-title":"Predicting customer quality in e-commerce social networks: a machine learning approach","volume":"13","year":"2019","journal-title":"Review of Managerial Science"},{"issue":"8","key":"key2023110803375815600_ref006","doi-asserted-by":"publisher","first-page":"1902","DOI":"10.1287\/mnsc.2014.2081","article-title":"Do your online friends make you pay? 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