Exploring the Relationship between Social Environment and Customer Experience
Bibliographic record
Abstract
The emergence of “experience” as another forms of business offerings (Pine and Gilmore, 1999) and the failure of implementing customer relationship management to create the expected levels of value for customers and profitability for organizations (Palmer, 2010; Barnes, 2002) have prompted the practitioners and academic scholars to explore the successor of customer relationship management, which is known as customer experience. Pine and Gilmore (1999) asserted that companies need to create memorable experiences to each customer for the purpose of generating greater economic value in the experience-based economy, instead of simply making goods and delivering services to the customers (Kim, Cha, Knutson and Beck, 2011). For the purpose of creating differentiated and memorable customer experience, this research paper would like to evaluate the direct and indirect relationship between social environment and customer experience (including sensory experience, emotional experience and social experience). A total of 330 respondents participate in this research. The findings revealed thatsocial environment is related to the sensory experience and emotional experience respectively.Furthermore, the research findings also concluded the interactive relationships between the dimensions of the customer experience: (1) the sensory experience is positively related to the emotional experience; (2) the emotional experience is positively related to the social experience; and (3) the sensory experience is positively related to the social experience.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".