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Record W2349605838 · doi:10.1287/serv.2016.0125

Testing Service Innovation: A Methodological Review of Video Experiments

2016· review· en· W2349605838 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueService Science · 2016
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicService and Product Innovation
Canadian institutionsWestern UniversityUniversity of Victoria
Fundersnot available
KeywordsService (business)Computer scienceService designExperiential learningTask (project management)Knowledge managementService providerMarketingPsychologyBusiness

Abstract

fetched live from OpenAlex

Experimenting with and testing new or improved service designs is often a challenging task for managers. In this paper, we promote the use of video experiments as a dynamic method for testing service innovation. We conducted a systematic review of over 40 articles from five prominent journals that span the disciplines of organizational behavior, operations management, marketing, and service management to summarize how researchers have used video experiments to develop managerial theory. We found that video experiments provide service researchers and practitioners the opportunity to effectively communicate important experiential aspects of service systems such as emotions and psychological effects. Moreover, customer responses to service design choices can be assessed based on the results of a video experiment. Consequently, we position video experiments as a particularly well-suited method for examining innovations that are related to the application of behavioral science insights or what we term as behavioral-based service innovations. To advance the future use of video experiments in service innovation research, we present a suggested guide for developing a video experiment and discuss important methodological considerations. We also review future research opportunities for studying behavioral-based service innovations through the use of video experiments.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
gptno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
models agreeAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Bibliometrics, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.843
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.033
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.407
GPT teacher head0.441
Teacher spread0.034 · 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