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Record W4200024870 · doi:10.26686/wgtn.17143646

Motivations for Virtual Community Participation in Social Commerce: Customers and Sellers in the Malay Lifestyle Blogging Community

2016· dissertation· en· W4200024870 on OpenAlexaff
Syahida Hassan

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsUniversity of Saskatchewan
FundersUniversiti Utara Malaysia
KeywordsBlogosphereSocial mediaInfluencer marketingMalayVirtual communitySet (abstract data type)Public relationsSociologyAdvertisingBusinessMarketingPolitical scienceThe InternetWorld Wide Web

Abstract

fetched live from OpenAlex

Although the field of social commerce has gained a lot of attention recently, there are many areas that still remain unexplored. A new phenomenon emerging within virtual communities is a blurring between social and commercial activities. To date, scholars in the social commerce literature have either focused on customers in the community or on medium to large scale businesses. There has been little research on social commerce communities which include micro-businesses despite their rapid growth in South East Asian countries. This study explores a social commerce community of Malay lifestyle bloggers, who are a subset of the Malaysian blogosphere community. Bloggers begin by using the personal genre, some then move on to set up online businesses using their personal blogs as a platform. The characteristic of blogging’s ease of use means there are low barriers to starting a small business, merging blogging and commerce. This changes the nature of the community by bringing in a new relationship, as well as relationships between bloggers and readers, there are now also relationships between sellers and customers. This study aims to understand the motivations for both sellers and customers, and how their relationships as bloggers and readers influence their participation in social commerce within the same community. To address the research objective, 20 sellers and 21 customers who also play a role as bloggers or readers were interviewed. In-depth interviews using laddering and semi-structured interview techniques were carried out to explore social commerce behaviour, the perceived consequences, and goals or values of participation. In addition, observation was also conducted on the platform used by the sellers. Data was coded using NVivo whilst the themes arising from the coding process were transformed into an implication matrix and hierarchical value map using Ladderux software. This study found that strong ties within the community, influenced by homophily and the sense of virtual community, motivated the customers to participate in commercial activities in order to obtain their goals which included a sense of obligation, loyalty, satisfaction and self-esteem. The relationships influenced customers to trust each other, provide social support and made purchasing products more convenient. Sellers were influenced by the convenience of using social media and the social support provided by the customers which helped them to achieve their goals which are profit and business sustainability. This study contributes to social commerce theory by highlighting an underexplored type of social commerce setting and addressing how trust can be transferred from social to commercial activities. The findings provide a useful insight for businesses, regardless of their size, to build an understanding of the need to create a good relationship with their customers. For macro-businesses, this model can be used to identify what is lacking in their social media marketing strategy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0040.003
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.050
GPT teacher head0.379
Teacher spread0.329 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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