| dc.contributor | Universitat Ramon Llull. Esade | |
| dc.contributor.author | Mora-Lopez, Juan Pablo | |
| dc.contributor.author | Lopez-Lopez, David | |
| dc.contributor.author | Rivera-Hernaez, Olga | |
| dc.date.accessioned | 2026-04-13T07:41:24Z | |
| dc.date.available | 2026-04-13T07:41:24Z | |
| dc.date.issued | 2026-04 | |
| dc.identifier.issn | 1389-5753 | ca |
| dc.identifier.uri | http://hdl.handle.net/20.500.14342/6121 | |
| dc.description.abstract | The rapid emergence of Generative AI (GAI) in recent years, coupled with its potential to revolutionize a vast array of industries, functions, and tasks, has led to an increasing number of companies—including digital businesses and e-commerce firms—to evaluate its immediate application at both operational and strategic levels. One of the existing tools to support such business decisions is the Gartner Hype Cycle (GHC), where AI in general, and GAI in particular, have been positioned for years. Notably, in Gartner’s latest report, GenAI occupies a concerning position, as it appears to be entering a phase where declining investment and interest are driven by its inability to meet initial expectations. This paper aims to assess whether the scenario outlined in the report can be objectively confirmed through public and replicable indicators that any researcher can utilize to address this question. Additionally, we explore the possibility that certain technologies—such as GAI, that due to its training and improvement requirements have been introduced in the market as a free tool and targeting individual users rather than solely corporate clients —may bypass some phases of the Gartner curve. Our main contribution is the proposal and testing of indicators that can be used for this purpose, yielding key insights from an exploratory rather than confirmatory perspective, with implications for companies’ adoption of GAI and particularly for digital and e-commerce businesses. Finally, we highlight the main limitations identified and outline future research avenues to address them. | ca |
| dc.format.extent | 29 p. | ca |
| dc.language.iso | eng | ca |
| dc.publisher | Springer Nature | ca |
| dc.relation.ispartof | Electronic Commerce Research, Vol. 26(2) | ca |
| dc.rights | © L'autor/a | ca |
| dc.rights | Attribution 4.0 International | * |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
| dc.subject.other | Generative AI | ca |
| dc.subject.other | Large language models (LLMs) | ca |
| dc.subject.other | Gartner Hype Cycle | ca |
| dc.subject.other | AI adoption | ca |
| dc.subject.other | Digital commerce | ca |
| dc.title | Unveiling the Generative AI boom: what hype metrics reveal for digital business and E-commerce | ca |
| dc.type | info:eu-repo/semantics/article | ca |
| dc.rights.accessLevel | info:eu-repo/semantics/openAccess | |
| dc.embargo.terms | cap | ca |
| dc.identifier.doi | https://doi.org/10.1007/s10660-025-09984-0 | ca |
| dc.description.version | info:eu-repo/semantics/publishedVersion | ca |