Online Community Referrals and Commitment: How Two Aspects of Community Life Impact Member Participation

The Internet now hosts an ever-increasing collection of tools (e.g., list-servers, discussion groups, chat rooms, bulletin boards, social networking sites, and wikis) that help people connect, communicate, and collaborate. The development of these technological tools, together with the desire to capitalize on the collective efforts of like-minded individuals has led to the formation of a wide variety of online communities. While some community oriented ventures have been extremely successful (e.g., MySpace and Wikipedia), this is not the norm. Online communities are faced with significant challenges associated with attracting and maintaining a voluntary membership base - and many fail to do so. The success and failure of these communities lies in their ability to attract and maintain a membership base of users that are willing to participate. A key to attracting and retaining members is to better understand how members join, and how their relationship with the community, impact their behavior in the community. The primary purpose of this dissertation research is to propose and test different aspects of community life that links how people join the community, and the bonds they form with the community, influence their participation in the community. A secondary objective is to expand the conceptualization of participation beyond traditional "frequency of contribution" constructs, to one that incorporates a wider range of community behaviors that need to be performed by a community's members. Towards these objectives, this work examines how two different aspects of community life, joining and commitment, affect different aspects of participation, including content provision, content seeking, and informal moderation. The first study draws on literature of word-of-mouth from marketing and organizational recruiting to explain how community joining processes, specifically member referrals, can shape member participation behaviors. The second study, draws on the organizational commitment literature, to theorize how the member-community relationship impacts member participation. Data to test these models proposed in each study was collected from a large community. The community promotes itself as a "general discussion" community, with the goal of supporting social conversation amongst its members.This dissertation finds that member referrals and community commitment play an important role in members' participation within online communities. These factors exert their influences at different stages of a member's association with a community. Referrals appear to be most influential at the earliest stages of community life, facilitating the return of members after they join and the level of their participation in the short term. This may be useful in helping communities overcome initial judgments of members with respect to the potential value of the community, giving the community a chance. However, communities must also be able to develop committed members to sustain participation in the long term. The commitment that develops between a member and the community influences member's participation, with the various types of commitment (continuance, affective, normative) leading members to participate in different ways. This may be useful in helping community administrators, who face the challenge of achieving an appropriate mix of participation to maintain the quality of the member-generated content pool over time.Taken together the results of the studies presented provide a theoretical foundation for linking relational models of community engagement and content contribution models. In doing so, expands the range of behaviors that should be considered by both researchers and practitioners, and provide a foundation for richer, more powerful, and potentially more useful models of behavior in online contexts

Thank You, Come Again: Examining the Role of Quality and Trust on eCommerce Repurchase Intentions

As the pertinence of online consumer shopping continues to grow, more and more e-retailers are erecting websites. In this increasingly competitive environment, building customer loyalty and retaining customers is integral to achieving sustained profitability. While one stream of literature has suggested that e-retailers should concentrate on improving quality, another stream has recommended that the focus should be on building trust with customers. This paper represents an early, working attempt to synthesize these parallel streams, investigating how the interplay between three forms of quality (information, system, and service) and trust help to retain customers. Integrating information systems and marketing research, the results of this paper suggest that trust mediates the relationship between each type of quality and both satisfaction and repurchase intentions. Furthermore, of the three types of quality that are examined, service quality engenders the greatest impact on trust, followed by information quality then system quality. The paper concludes with a discussion of this preliminary model as well as directions for the future development of this project

They Call for Help, But Don\u27t Always Listen: The Development of the User-Help Desk Knowledge Application Model

The IS help desk function plays a central role in boundary spanning knowledge exchanges within organizations. Help desk employees provide technical support to users in an effort to transfer knowledge and enable users to autonomously apply this knowledge in the future. However, despite their importance, little is known about the factors that affect knowledge application within this context. Adopting interpersonal influence theory, this paper develops a model that examines how dimensions of source credibility - expertise, trustworthiness, and attractiveness impact users’ knowledge application in a help desk environment. The model is tested using a sample of working adults at a large Midwestern hospital who had significant experience requesting help from an IS help desk. Results indicate that all three dimensions of source credibility predict users’ ability to apply the knowledge transferred from a help desk employee. The implications of these results are discussed

SHOULD I STAY OR SHOULD I GO: THE ROLE OF REFERRALS ON ONLINE COMMUNITY MEMBER TURNOVER AND TENURE

Communities are often faced with challenges associated with attracting and maintaining a membership base, which affects their ability to develop a pool of resources and ultimately impacts their sustainability. A potential resolution to this challenge lies in the members of the community referring non-members to the community – member referrals. While community joining has been acknowledged as important stage in the life cycle of community members; however, the way in which a member becomes aware of a community and its resulting influence on their engagement with the community has not been examined. This research-in-progress paper outlines the examination of the role of referrals on member turnover and tenure. Drawing upon theories of referrals from organizational behavior and marketing, the paper theorizes that referrals have the potential to facilitate the awareness of, and interest in, a community, which ultimately influences new members to return to, and stay, in a community

I Didn\u27t Know You Could See That: The Effect of Social Networking Environment Characteristics on Publicness and Self-Disclosure

Web 2.0 technologies have changed the way users interact with the Internet. Users play a growing role in the generation of content, and while doing so disclose a piece of themselves. We seek to provide a theoretical link between the boundary characteristics of a social networking website and self-disclosure. Utilizing Communication Privacy Management Theory, we focus on two forms of boundaries: mode of entry boundary and ingroup/outgroup boundary. We propose that these boundaries play a role in the implicit boundary coordination and negotiation between the users of the environment and the website. This negotiation influences users’ perceived publicness of the environment, which influences their self-disclosure behaviors due to their risk avoidance. It is believed that by recognizing the public aspect of participation in online social networks, we can provide suggestions on how its perception can be managed to encourage, or discourage, contributions and disclosures of information by users

A single dose of the γ-secretase inhibitor semagacestat alters the cerebrospinal fluid peptidome in humans

BACKGROUND: In Alzheimer’s disease, beta-amyloid peptides in the brain aggregate into toxic oligomers and plaques, a process which is associated with neuronal degeneration, memory loss, and cognitive decline. One therapeutic strategy is to decrease the production of potentially toxic beta-amyloid species by the use of inhibitors or modulators of the enzymes that produce beta-amyloid from amyloid precursor protein (APP). The failures of several such drug candidates by lack of effect or undesired side-effects underscore the importance to monitor the drug effects in the brain on a molecular level. Here we evaluate if peptidomic analysis in cerebrospinal fluid (CSF) can be used for this purpose. METHODS: Fifteen human healthy volunteers, divided into three groups, received a single dose of placebo or either 140 mg or 280 mg of the γ-secretase inhibitor semagacestat (LY450139). Endogenous peptides in CSF, sampled prior to administration of the drug and at six subsequent time points, were analyzed by liquid chromatography coupled to mass spectrometry, using isobaric labeling based on the tandem mass tag approach for relative quantification. RESULTS: Out of 302 reproducibly detected peptides, 11 were affected by the treatment. Among these, one was derived from APP and one from amyloid precursor-like protein 1. Nine peptides were derived from proteins that may not be γ-secretase substrates per se, but that are regulated in a γ-secretase-dependent manner. CONCLUSIONS: These results indicate that a CSF peptidomic approach may be a valuable tool both to verify target engagement and to identify other pharmacodynamic effects of the drug. Data are available via ProteomeXchange with identifier PXD003075. TRIAL REGISTRATION: NCT00765115, registered 30/09/2008. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13195-016-0178-x) contains supplementary material, which is available to authorized users

Multimodal brain age estimates relate to Alzheimer disease biomarkers and cognition in early stages: A cross-sectional observational study

BACKGROUND: Estimates of \u27brain-predicted age\u27 quantify apparent brain age compared to normative trajectories of neuroimaging features. The brain age gap (BAG) between predicted and chronological age is elevated in symptomatic Alzheimer disease (AD) but has not been well explored in presymptomatic AD. Prior studies have typically modeled BAG with structural MRI, but more recently other modalities, including functional connectivity (FC) and multimodal MRI, have been explored. METHODS: We trained three models to predict age from FC, structural (S), or multimodal MRI (S+FC) in 390 amyloid-negative cognitively normal (CN/A-) participants (18-89 years old). In independent samples of 144 CN/A-, 154 CN/A+, and 154 cognitively impaired (CI; CDR \u3e 0) participants, we tested relationships between BAG and AD biomarkers of amyloid and tau, as well as a global cognitive composite. RESULTS: All models predicted age in the control training set, with the multimodal model outperforming the unimodal models. All three BAG estimates were significantly elevated in CI compared to controls. FC-BAG was significantly reduced in CN/A+ participants compared to CN/A-. In CI participants only, elevated S-BAG and S+FC BAG were associated with more advanced AD pathology and lower cognitive performance. CONCLUSIONS: Both FC-BAG and S-BAG are elevated in CI participants. However, FC and structural MRI also capture complementary signals. Specifically, FC-BAG may capture a unique biphasic response to presymptomatic AD pathology, while S-BAG may capture pathological progression and cognitive decline in the symptomatic stage. A multimodal age-prediction model improves sensitivity to healthy age differences. FUNDING: This work was supported by the National Institutes of Health (P01-AG026276, P01- AG03991, P30-AG066444, 5-R01-AG052550, 5-R01-AG057680, 1-R01-AG067505, 1S10RR022984-01A1, and U19-AG032438), the BrightFocus Foundation (A2022014F), and the Alzheimer\u27s Association (SG-20-690363-DIAN)

Multimodal brain age estimates relate to Alzheimer disease biomarkers and cognition in early stages: a cross-sectional observational study

BACKGROUND: Estimates of 'brain-predicted age' quantify apparent brain age compared to normative trajectories of neuroimaging features. The brain age gap (BAG) between predicted and chronological age is elevated in symptomatic Alzheimer disease (AD) but has not been well explored in presymptomatic AD. Prior studies have typically modeled BAG with structural MRI, but more recently other modalities, including functional connectivity (FC) and multimodal MRI, have been explored. METHODS: We trained three models to predict age from FC, structural (S), or multimodal MRI (S+FC) in 390 amyloid-negative cognitively normal (CN/A-) participants (18-89 years old). In independent samples of 144 CN/A-, 154 CN/A+, and 154 cognitively impaired (CI; CDR > 0) participants, we tested relationships between BAG and AD biomarkers of amyloid and tau, as well as a global cognitive composite. RESULTS: All models predicted age in the control training set, with the multimodal model outperforming the unimodal models. All three BAG estimates were significantly elevated in CI compared to controls. FC-BAG was significantly reduced in CN/A+ participants compared to CN/A-. In CI participants only, elevated S-BAG and S+FC BAG were associated with more advanced AD pathology and lower cognitive performance. CONCLUSIONS: Both FC-BAG and S-BAG are elevated in CI participants. However, FC and structural MRI also capture complementary signals. Specifically, FC-BAG may capture a unique biphasic response to presymptomatic AD pathology, while S-BAG may capture pathological progression and cognitive decline in the symptomatic stage. A multimodal age-prediction model improves sensitivity to healthy age differences. FUNDING: This work was supported by the National Institutes of Health (P01-AG026276, P01- AG03991, P30-AG066444, 5-R01-AG052550, 5-R01-AG057680, 1-R01-AG067505, 1S10RR022984-01A1, and U19-AG032438), the BrightFocus Foundation (A2022014F), and the Alzheimer's Association (SG-20-690363-DIAN)

Predicting continuous amyloid PET values with CSF and plasma Aβ42/Aβ40

INTRODUCTION: Continuous measures of amyloid burden as measured by positron emission tomography (PET) are being used increasingly to stage Alzheimer\u27s disease (AD). This study examined whether cerebrospinal fluid (CSF) and plasma amyloid beta (Aβ)42/Aβ40 could predict continuous values for amyloid PET. METHODS: CSF Aβ42 and Aβ40 were measured with automated immunoassays. Plasma Aβ42 and Aβ40 were measured with an immunoprecipitation-mass spectrometry assay. Amyloid PET was performed with Pittsburgh compound B (PiB). The continuous relationships of CSF and plasma Aβ42/Aβ40 with amyloid PET burden were modeled. RESULTS: Most participants were cognitively normal (427 of 491 [87%]) and the mean age was 69.0 ± 8.8 years. CSF Aβ42/Aβ40 predicted amyloid PET burden until a relatively high level of amyloid accumulation (69.8 Centiloids), whereas plasma Aβ42/Aβ40 predicted amyloid PET burden until a lower level (33.4 Centiloids). DISCUSSION: CSF Aβ42/Aβ40 predicts the continuous level of amyloid plaque burden over a wider range than plasma Aβ42/Aβ40 and may be useful in AD staging. HIGHLIGHTS: Cerebrospinal fluid (CSF) amyloid beta (Aβ)42/Aβ40 predicts continuous amyloid positron emission tomography (PET) values up to a relatively high burden.Plasma Aβ42/Aβ40 is a comparatively dichotomous measure of brain amyloidosis.Models can predict regional amyloid PET burden based on CSF Aβ42/Aβ40.CSF Aβ42/Aβ40 may be useful in staging AD