Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 401

The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.

How attachment affects user stickiness on live streaming platforms: A socio-technical approach perspective

Li, You, Li, Xiaolin, Cai, Jiali·2021·Journal of Retailing and Consumer Services
DOI 10.1016/j.jretconser.2021.102478
Open this paper in CoChat — free account

Abstract

Abstract User stickiness is an important factor in the development of live streaming shopping platforms, which describes the degree of users' attention to the platforms. Although some e-commerce websites have provided live streaming services to improve the purchase experience of consumers, few people know how the services affect user stickiness. Building upon attachment theory and socio-technical approach, we developed a theoretical model to understand how live streaming service affects the user stickiness through users' attachment, which is tested by using 425 live streaming shopping platform's users. The results showed that technical factors (synchronicity and vicarious expression) and social factors (interaction and identification) positively affect emotional attachment to streamers and platform attachment respectively, which in turn increase the user stickiness.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.jretconser.2021.102478

Cites

11 of 11 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 11 references

Research works printed but not linked: 59

  1. Ashforth, 2008, Identification in organizations: An examination of four fundamental questions, J. Manag., 34, 325
  2. Bentler, 1983, Some contributions to efficient statistics in structural models: Specification and estimation of moment structures, Psychometrika., 48, 493, 10.1007/BF02293875 · DOI
  3. Bhatnagar, 2004, An analysis of frequency and duration of search on the internet, J. Bus., 77, 311, 10.1086/381277 · DOI
  4. Bhattacharya, 2003, Consumer-company identification: A framework for understanding consumers’ relationships with companies, J. Market., 67, 76, 10.1509/jmkg.67.2.76.18609 · DOI · Paper page
  5. Brown, 2005, Spreading the word: investigating antecedents of consumers positive word-of-mouth intentions and behaviors in a retailing context, J. Acad. Market. Sci., 33, 123, 10.1177/0092070304268417 · DOI
  6. Chen, 2017, Customers purchase decision-making process in social commerce: A social learning perspective, Int. J. Inf. Manag., 37, 627
  7. Chen, 2018, What drives live-stream usage intention? the perspectives of flow, entertainment, social interaction, and endorsement, Telematics Inf., 35, 293, 10.1016/j.tele.2017.12.003 · DOI · Paper page
  8. Chen, 2019, The influence of ecommerce live streaming on lifestyle fit uncertainty and online purchase intention of experience products, 1, 10.24251/HICSS.2019.610 · DOI
  9. Choi, 2013, Information systems attachment: An empirical exploration of its antecedents and its impact on community participation intention, Journal of the Association for Information Science and Technology, 64, 2354
  10. Clark, 2007, Stereotypes help people connect with others in the community: A situated functional analysis of the stereotype consistency bias in communication, J. Pers. Soc. Psychol., 93, 1028, 10.1037/0022-3514.93.6.1028 · DOI
  11. Danaher, 2006, Factors affecting web site visit duration: A cross-domain analysis, J. Market. Res., 43, 182, 10.1509/jmkr.43.2.182 · DOI
  12. Fedorikhin, 2008, Beyond fit and attitude: The effect of emotional attachment on consumer responses to brand extensions, J. Consum. Psychol., 18, 281, 10.1016/j.jcps.2008.09.006 · DOI · Paper page
  13. Fiedler, 2014, Influence of community design on user behaviors in online communities, J. Bus. Res., 67, 2258, 10.1016/j.jbusres.2014.06.014 · DOI
  14. Fornell, 1981, Evaluating structural equation models with unobservable variables and measurement error, J. Market. Res., 18, 39, 10.1177/002224378101800104 · DOI · Paper page
  15. Friedrich, 2019, The impact of social commerce feature richness on website stickiness through cognitive and affective factors: An experimental study, Electron. Commer. Res. Appl., 36, 10.1016/j.elerap.2019.100861 · DOI
  16. Grisaffe, 2011, Antecedents of emotional attachment to brands, J. Bus. Res., 64, 1052, 10.1016/j.jbusres.2010.11.002 · DOI
  17. Holmes, 2000, Social relationships: the nature and function of relational schemas, Eur. J. Soc. Psychol., 30, 447, 10.1002/1099-0992(200007/08)30:4<447::AID-EJSP10>3.0.CO;2-Q · DOI
  18. Hsiao, 2016, Configurational path to customer satisfaction and stickiness for a restaurant chain using fuzzy set qualitative comparative analysis, J. Bus. Res., 69, 2939, 10.1016/j.jbusres.2015.12.063 · DOI
  19. Hu, 2020, Understanding followers stickiness to digital influencers: The effect of psychological responses, Int. J. Inf. Manag., 54
  20. Hu, 2017, Why do audiences choose to keep watching on live video streaming platforms? an explanation of dual identification framework, Comput. Hum. Behav., 75, 594, 10.1016/j.chb.2017.06.006 · DOI · Paper page
  21. Hu, 2016, The influence of peer characteristics and technical features of a social shopping website on a consumers purchase intention, Int. J. Inf. Manag., 36, 1218
  22. Huang, 2009, Searching for experience on the web: An empirical examination of consumer behavior for search and experience goods, J. Market., 73, 55, 10.1509/jmkg.73.2.55 · DOI · Paper page
  23. Ilicic, 2011, Effects of multiple endorsements and consumercelebrity attachment on attitude and purchase intention, Australas. Mark. J., 19, 230, 10.1016/j.ausmj.2011.07.005 · DOI · Paper page
  24. Kim, 2016, Seniors’ loyalty to social network sites: Effects of social capital and attachment, Int. J. Inf. Manag., 36, 1020
  25. Kirk, 2015, How do digital natives and digital immigrants respond differently to interactivity online?: A model for predicting consumer attitudes and intentions to use digital information products, J. Advert. Res., 55, 81, 10.2501/JAR-55-1-081-094 · DOI
  26. Klimmt, 2007, Effectance and control as determinants of video game enjoyment, Cyberpsychol., Behav. Soc. Netw., 10, 845, 10.1089/cpb.2007.9942 · DOI
  27. Klimmt, 2012, Forecasting the experience of future entertainment technology: interactive storytelling and media enjoyment, Game. Cult., 7, 187, 10.1177/1555412012451123 · DOI
  28. Krotov, 2015, Critical success factors inm-learning: a socio-technical perspective, Commun. Assoc. Inf. Syst., 36, 105
  29. Ladhari, 2020, Youtube vloggers popularity and influence: The roles of homophily, emotional attachment, and expertise, J. Retailing Consum. Serv., 54, 10.1016/j.jretconser.2019.102027 · DOI · Paper page
  30. Li, 2006, Why do internet users stick with a specific web site? a relationship perspective, Int. J. Electron. Commer., 10, 105, 10.2753/JEC1086-4415100404 · DOI · Paper page
  31. Li, 2013, Helpfulness of online product reviews as seen by consumers: source and content features, Int. J. Electron. Commer., 17, 101, 10.2753/JEC1086-4415170404 · DOI
  32. Lin, 2019, Understanding the interplay of social commerce affordances and swift guanxi:An empirical study, Inf. Manag., 56, 213, 10.1016/j.im.2018.05.009 · DOI
  33. Lin, 2007, Online stickiness: its antecedents and effect on purchasing intention, Behav. Inf. Technol., 26, 507, 10.1080/01449290600740843 · DOI
  34. Lin, 2010, Is stickiness profitable for electronic retailers, Commun. ACM, 53, 132, 10.1145/1666420.1666454 · DOI
  35. Liu, 2019, Hybrid influences of social subsystem and technical subsystem risks in the crowdsourcing marketplace, IEEE Trans. Eng. Manag., 1
  36. Liu, 2003, Developing a scale to measure the interactivity of websites, J. Advert. Res., 43, 207, 10.2501/jar-43-2-207-216 · DOI · Paper page
  37. Lu, 2010, Demographic differences and the antecedents of blog stickiness, Online Inf. Rev., 34, 21, 10.1108/14684521011024100 · DOI
  38. Manz, 1981, Vicarious learning: the influence of modeling on organizational behavior, Acad. Manag. Rev., 6, 105, 10.2307/257144 · DOI
  39. Ng, 2015, The incremental validity of organizational commitment, organizational trust, and organizational identification, J. Vocat. Behav., 88, 154, 10.1016/j.jvb.2015.03.003 · DOI
  40. Park, 2010, Brand attachment and brand attitude strength: Conceptual and empirical differentiation of two critical brand equity drivers, J. Market., 74, 1, 10.1509/jmkg.74.6.1 · DOI
  41. Park, 2014, An investigation of information sharing and seeking behaviors in online investment communities, Comput. Hum. Behav., 31, 1, 10.1016/j.chb.2013.10.002 · DOI
  42. Ren, 2012, Building member attachment in online communities: applying theories of group identity and interpersonal bonds, Management Information Systems Quarterly, 36, 841, 10.2307/41703483 · DOI · Paper page
  43. Saxton, 2016, The social network effect: the determinants of giving through social media, Nonprofit Voluntary Sect. Q., 43, 850, 10.1177/0899764013485159 · DOI · Paper page
  44. Scheibe, 2016, Information behavior on social live streaming services, J. Inf. Sci. Theory Pract., 4, 6
  45. Scheibe, 2019, Game mechanics on social live streaming service websites, 1486, 10.24251/HICSS.2019.180 · DOI
  46. Stever, 2011, Fan behavior and lifespan development theory: Explaining para-social and social attachment to celebrities, J. Adult Dev., 18, 1, 10.1007/s10804-010-9100-0 · DOI · Paper page
  47. Thomson, 2006, Human brands: Investigating antecedents to consumers’ strong attachments to celebrities, J. Market., 70, 104, 10.1509/jmkg.70.3.104 · DOI
  48. Todd, 2017, Gender and live-streaming: source credibility and motivation, J. Res. Indian Med., 12, 79
  49. Trist, 1964, Organizational choice. capabilities of groups at the coal face under changing technologies. the loss, re-discovery and transformation of a work tradition, Rev. Fr. Sociol., 5, 482, 10.2307/3319635 · DOI
  50. Wan, 2017, How attachment influences users willingness to donate to content creators in social media, Inf. Manag., 54, 837, 10.1016/j.im.2016.12.007 · DOI
  51. Wang, 2019, What motives users to participate in danmu on live streaming platforms? the impact of technical environment and effectance, Data Inf. Manag., 3, 117
  52. Wang, 2016, The stickiness intention of group-buying websites, Inf. Manag., 53, 625, 10.1016/j.im.2016.01.006 · DOI · Paper page
  53. Warrington, 2000, An empirical investigation of the relationship between product involvement and brand commitment, Psychol. Market., 17, 761, 10.1002/1520-6793(200009)17:9<761::AID-MAR2>3.0.CO;2-9 · DOI
  54. Waters, 2011, Tweet, tweet, tweet: A content analysis of nonprofit organizations twitter updates, Publ. Relat. Rev., 37, 321, 10.1016/j.pubrev.2011.03.002 · DOI
  55. Xiao, 2019, Exploring the moderators and causal process of trust transfer in online-to-offline commerce, J. Bus. Res., 98, 214, 10.1016/j.jbusres.2019.01.069 · DOI
  56. Xu, 2018, What affects the user stickiness of the mainstream media websites in China, Electron. Commer. Res. Appl., 29, 124, 10.1016/j.elerap.2018.05.001 · DOI
  57. Yi, 2003, Developing and validating an observational learning model of computer software training and skill acquisition, Inf. Syst. Res., 14, 146, 10.1287/isre.14.2.146.16016 · DOI
  58. Zhang, 2017, Influence of customer engagement with company social networks on stickiness, Int. J. Inf. Manag., 37, 229
  59. Zhang, 2019, Exploring short-form video application addiction: Socio-technical and attachment perspectives, Telematics Inf., 42

Cited by

See all 401

Metadata

Authors
Li, Y., Li, X., & Cai, J.
Venue
Journal of Retailing and Consumer Services
Publisher
Elsevier BV
Published
2021-05
Volume
60
Pages
102478
ISSN
0969-6989 (ISSN-L)
DOI
10.1016/j.jretconser.2021.102478
OpenAlex
W3129752296
Cited by
401
References
11
FWCI
55.42
Type
journal article
Language
en
Open access
closed
Licence

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: How attachment affects user stickiness on live streaming platforms: A socio-technical approach perspective. https://app.cochat.ai/papers/10.1016/j.jretconser.2021.102478
The paper
Li, Y., Li, X., & Cai, J. (2021). How attachment affects user stickiness on live streaming platforms: A socio-technical approach perspective. Journal of Retailing and Consumer Services. https://doi.org/10.1016/j.jretconser.2021.102478

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.