Bibliographic record
Abstract
Purpose The quality of being fully engaged during service interactions is essential for service providers, as it reflects a commitment to meeting customers’ expectations and needs. While engagement is recognized as an important aspect of service delivery, the concept of maintaining sustained attentiveness throughout the entire service journey – referred to here as service presentness – has received limited conceptualization in existing research. Therefore, this study aims to conceptualize service presentness, elaborate on its key dimensions and illustrate how it contributes to enhancing the flow of service interactions. Design/methodology/approach Building on Jaakkola’s (2020) and Ulaga et al.’s (2021) theory synthesis approaches, we situate service presentness within a service-dominant logic perspective. Drawing from role theory and the principle of sequential interdependence, we develop a conceptual framework that clarifies the outward-oriented, real-time engagement required to optimize the service interaction flow. Findings Service presentness denotes the provider’s sustained, deep focus and genuine engagement throughout the entire service experience, ensuring a continuously attentive customer journey. Its core dimensions – disciplined focus, empathetic listening, continuous facilitation, customer-centric orientation and authenticity – collectively strengthen relational quality and guide seamless progression from one service phase to the next. Sustaining service presentness is thus crucial for achieving cohesive service delivery, ultimately enhancing customer trust and satisfaction. Originality/value This study introduces service presentness as a distinct yet complementary construct to existing mindfulness literature in service marketing. By emphasizing the provider’s ongoing, outward-facing engagement, our conceptual framework offers a foundation for empirical inquiry into how service presentness can be cultivated and measured across diverse service contexts.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".