Asymmetries in Attachments to Groups and to their Members: Distinguishing between Common-Identity and Common-Bond Groups

Prentice, Deborah A.; Miller, Dale T.; Lightdale, Jenifer R.

doi:10.1177/0146167294205005

Cited by 368 publications

(339 citation statements)

References 23 publications

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“…We illustrate this point with the subgroup slightly overlapping the superordinate identity. At the least inclusive level are relational groups, including friends, family, work, and category groups (Brewer & Gardner, 1996;Prentice et al, 1994). Figure 1 displays the three forms of relational group: A, B and C. Circle A represents external socialisation, which involves a relational group that exists aside from the superordinate identity that socialises a person into (1) superordinate identification, (2) subgroup identification, or (3) a combination of both.…”

Section: Theoretical Frameworkmentioning

confidence: 99%

“…The least inclusive level of the MIIF includes groups that require face-to-face interaction and some degree of interpersonal attachment between individuals (Prentice et al, 1994). We use the term relational group, instead of relational subgroup, as the interpersonal attachments that exist in family, friendship, vocational, or social categories may form outside the superordinate identity and operate in other circumstances aside from team support (e.g., James, 2001;Spaaij & Anderson, 2010).…”

Section: Relational Groupsmentioning

confidence: 99%

“…In a more complex scenario, Katz and Heere (2013) elucidated how different relational groups came together to form tailgating groups, based the leaders existing social networks. Both examples illustrate groups of different sizes and complexity, which formed through interpersonal attraction, not because of an attraction to group totems, symbols, or characteristics (Prentice et al, 1994). Consumers attend matches in a variety of relational groups.…”

Section: Relational Groupsmentioning

confidence: 99%

See 2 more Smart Citations

The Multiple In-group Identity Framework

Lock

Funk

2016

Sport Management Review

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The effects of team identification on sport consumer behaviour are well established.Recent research, however, has moved beyond this perspective to examine the influence of groups within and beyond the team identity on consumption. Assimilating previous research findings, we advance a Multiple In-group Identity Framework (MIIF), which consists of three levels: (1) superordinate (i.e., team identity), (2) subgroup (e.g., specific stadium area), and (3) relational group (e.g., friends or family). The MIIF conceptualises the complex array of groups to which a consumer may belong within a superordinate identity. Each level includes groups with varying degrees of inclusiveness, homogeneity, and interpersonal attachment between members.Individuals seek out sub and relational group membership because solely identifying at the superordinate level may not provide optimal distinctiveness or sufficient interpersonal attachment. This provides additional self-concept benefits that nourish and operate in complement with the superordinate identification. The extent that different in-group identities influence behaviour relates to their importance in a consumer's self-concept and relevance to context. We provide implications for theory and practice.

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Section: Theoretical Frameworkmentioning

confidence: 99%

Section: Relational Groupsmentioning

confidence: 99%

Section: Relational Groupsmentioning

confidence: 99%

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The Multiple In-group Identity Framework

Lock

Funk

2016

Sport Management Review

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“…We drew insights from theories of group identity theory (Hogg, 1996 ) and interpersonal bonds (Berscheid, 1994 ) to calculate social benefi ts, and we drew insights from resource-based theory (Butler, 2001 ) and information overload theory (Jones, Ravid & Rafaeli, 2004 ) to calculate informational benefi ts. Theories of group identity and interpersonal bonds propose that members commit and contribute to a group if they feel psychologically attached to the group or its members (Prentice, Miller & Lightdale, 1994 ). Information overload theory proposes that human beings' information processing capacity is limited and too much information or irrelevant information is aversive (Rogers & Agarwala-Rogers, 1975 ).…”

Section: Following the Roadmap: Using Abm To Inform The Design Of Onlmentioning

confidence: 99%

Agent Based Modeling to Inform the Design of Multiuser Systems

Ren

Kraut

2014

Ways of Knowing in HCI

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Decades have passed since the inception of the fi eld of Human-Computer Interaction. The emergence of the Internet has shifted researchers' attention from understanding how individuals interact with computers to understanding how individuals interact with one another using computer technologies. A wide range of systems designed for multiple users have been labeled as groupware, collaborative computing, multiuser applications, and more recently social computing technologies. Designing these types of system is more challenging than designing singleuser ones because other people and their behaviors are integral elements of the system as experienced by users (Grudin, 1994 ). The system itself, therefore, is nondeterministic and evolutionary because the experience of some users is partly the result of decisions that earlier users have made. Because the behavior of a multiuser system is not stable until a critical mass of users has developed a routine way of using it, it is diffi cult to predict how groups of users will respond to a particular design before the stable state is reached. As a result, interactive design and evaluation cycle, perhaps the most successful HCI technique for system design, is insuffi cient for the design of multiuser applications.Consider the design of an online health support group like breastcancer.org and the decision about whether to employ moderators who ensure group members spend their time discussing cancer-related topics, channel off-topic content to sub-forums, or prevent users from posting advertisements. A member's decision to participate in

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“…The model proposes that CONTACT with a customer community, measured by participation in group events and activities, is positively related to members' SENTIMENTS toward the community, as measured by member attachment and group attachment. 38 The SENTIMENTS latent variable is, in turn, positively related to BEHAVIOURAL INTENTIONS, which is defined by three indicator variables: positive referral, intention to repurchase and a willingness to pay more. 39 For identification purposes, the uniqueness term for the contact indicator was fixed using an internal consistency reliability estimate generated from the data.…”

Section: Simulation Studymentioning

confidence: 99%