The Impact of Word of Mouth on Service Purchase Decisions: Examining Risk and the Interaction of Tie Strength and Involvement
Bibliographic record
Abstract
Purpose – Primarily, the purpose of this paper is to investigate the interaction and direct effects of tie strength between sender and receiver of word of mouth (WOM) and the receiver’s service purchase decision involvement on WOM influence. A secondary aim is to investigate how a distinctive conceptualization of perceived risk, consisting of two types (outcome risk and psychosocial risk), affects service purchase decision involvement. A conceptual model incorporating these constructs and associated hypotheses is developed and tested. Design/Methodology/Approach – In a survey of actual service consumers, respondents were asked to recall a recent instance where they had received service purchase information via WOM, and relate their responses to this instance. Established scales were used to measure the constructs. The hypothesized model was tested using structural equation modeling. Findings – Principally, findings demonstrate a strong interaction effect between service purchase decision involvement and tie strength. Also, results highlight the complexity of the perceived risk construct, suggesting that it is appropriately modeled as two types: outcome risk, and psycho-social risk. Research limitations/Implications – This research has contributed to the service marketing literature by testing a model that predicts WOM influence. Evidence confirmed that the effect of service purchase decision involvement on WOM influence is moderated by tie strength. Additionally, a conceptualization of two different types of risk associated with purchase decisions was suggested, together with empirical confirmation of their hypothesized antecedent effects on service purchase decision involvement. Findings have special implications for the literatures of persuasion, social and interpersonal influence, as well as consumer behavior in general. Practical Implications – To harness the power of WOM, managers should understand who their target audience is and how consumers are related to each other (tie strength) and to the service purchase decision (service purchase decision involvement). Recommendations are made with specific illustrations of how firms can leverage tie strength under conditions of low service purchase decision involvement to enhance WOM influence. Originality/Value – The formidable power of WOM wields substantial influence on consumers, particularly within a service (vs goods) purchase context, typically characterized by higher perceived risk and lower search qualities. The significant interaction between tie strength and service purchase decision involvement is a unique contribution to the service WOM literature.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".