Understanding Cooperative Learning in Context-aware Recommender Systems

A User-system Interaction Perspective

Na Jiang, Chee-Wee Tan, Weiquan Wang, Hefu Liu, Jibao Gu

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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Abstract

Context-Aware Recommender Systems (CARSs) are becoming commonplace. Yet, there is a paucity of studies that investigates how such systems could affect usage behavior from a user-system interaction perspective. Building on the Social Interdependence Theory (SIT), we construct a research model that posits cooperative learning as a trait of users’ interactions with CARSs and outline a proposed empirical study for validating the hypothesized relationships in this model. Specifically, we draw on interdependencies in human-machine relationships to postulate positive interdependence as an antecedent of users’ promotive interaction with CARSs, which in turn, dictates the performance of such recommender systems. Furthermore, we introduce scrutability features as design interventions that can be harnessed by developers to mitigate the impact of users’ promotive interaction on the performance of CARSs.
Original languageEnglish
Title of host publicationICIS 2017 Proceedings
Place of PublicationAtlanta, GA
PublisherAssociation for Information Systems. AIS Electronic Library (AISeL)
Publication date2017
Pages11
Publication statusPublished - 2017
EventICIS 2017: Transforming Society with Digital Innovation - Coex Convention Center , Seoul, Korea, Republic of
Duration: 10 Dec 201713 Dec 2017
Conference number: 38
https://icis2017.aisnet.org/

Conference

ConferenceICIS 2017
Number38
LocationCoex Convention Center
CountryKorea, Republic of
CitySeoul
Period10/12/201713/12/2017
Internet address
SeriesProceedings of the International Conference on Information Systems
ISSN0000-0033

Keywords

  • Context-aware
  • Recommender systems
  • Cooperative learning
  • User-system interaction
  • Human-machine relationships

Cite this

Jiang, N., Tan, C-W., Wang, W., Liu, H., & Gu, J. (2017). Understanding Cooperative Learning in Context-aware Recommender Systems: A User-system Interaction Perspective. In ICIS 2017 Proceedings (pp. 11). Atlanta, GA: Association for Information Systems. AIS Electronic Library (AISeL). Proceedings of the International Conference on Information Systems
Jiang, Na ; Tan, Chee-Wee ; Wang, Weiquan ; Liu, Hefu ; Gu, Jibao. / Understanding Cooperative Learning in Context-aware Recommender Systems : A User-system Interaction Perspective. ICIS 2017 Proceedings. Atlanta, GA : Association for Information Systems. AIS Electronic Library (AISeL), 2017. pp. 11 (Proceedings of the International Conference on Information Systems).
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title = "Understanding Cooperative Learning in Context-aware Recommender Systems: A User-system Interaction Perspective",
abstract = "Context-Aware Recommender Systems (CARSs) are becoming commonplace. Yet, there is a paucity of studies that investigates how such systems could affect usage behavior from a user-system interaction perspective. Building on the Social Interdependence Theory (SIT), we construct a research model that posits cooperative learning as a trait of users’ interactions with CARSs and outline a proposed empirical study for validating the hypothesized relationships in this model. Specifically, we draw on interdependencies in human-machine relationships to postulate positive interdependence as an antecedent of users’ promotive interaction with CARSs, which in turn, dictates the performance of such recommender systems. Furthermore, we introduce scrutability features as design interventions that can be harnessed by developers to mitigate the impact of users’ promotive interaction on the performance of CARSs.",
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Jiang, N, Tan, C-W, Wang, W, Liu, H & Gu, J 2017, Understanding Cooperative Learning in Context-aware Recommender Systems: A User-system Interaction Perspective. in ICIS 2017 Proceedings. Association for Information Systems. AIS Electronic Library (AISeL), Atlanta, GA, Proceedings of the International Conference on Information Systems, pp. 11, ICIS 2017, Seoul, Korea, Republic of, 10/12/2017.

Understanding Cooperative Learning in Context-aware Recommender Systems : A User-system Interaction Perspective. / Jiang, Na; Tan, Chee-Wee; Wang, Weiquan; Liu, Hefu; Gu, Jibao.

ICIS 2017 Proceedings. Atlanta, GA : Association for Information Systems. AIS Electronic Library (AISeL), 2017. p. 11 (Proceedings of the International Conference on Information Systems).

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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Jiang N, Tan C-W, Wang W, Liu H, Gu J. Understanding Cooperative Learning in Context-aware Recommender Systems: A User-system Interaction Perspective. In ICIS 2017 Proceedings. Atlanta, GA: Association for Information Systems. AIS Electronic Library (AISeL). 2017. p. 11. (Proceedings of the International Conference on Information Systems).