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Record W4388920756 · doi:10.1108/josm-07-2023-0326

Frontline service employee research: integration of systematic literature reviews and recommendations for future scholarship

2023· article· en· W4388920756 on OpenAlex
Mahesh Subramony, Danielle Van Jaarsveld, Helena Nguyen, Markus Groth, David Solnet

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

VenueJournal of service management · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEmotional Labor in Professions
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsScholarshipSystematic reviewSociologyExtant taxonSituational ethicsValue (mathematics)Knowledge managementEngineering ethicsPsychologyManagement sciencePolitical scienceComputer scienceEngineeringSocial psychology

Abstract

fetched live from OpenAlex

Purpose This paper integrates the findings of the articles included in the special issue (SI) on frontline employee (FLE) research. Articles included in this SI systematically review multiple research domains, including employee and customer engagement, FLE vulnerability, customer mistreatment, service teamwork and service encounters; provide instructions on effectively conducting meta-analyses and discuss the practical applications of FLE research. This paper also provides future directions for FLE scholarship with a focus on theoretical/methodological rigor and relevance. Design/methodology/approach This is a conceptual paper that integrates and critically evaluates extant research and provides directions for future scholarship. Findings An integrative framework of extant FLE research is proposed consisting of situational predictors, psychological mechanisms, attitudinal/behavioral outcomes and boundary conditions/moderators. Further, three main areas for future scholarship are recommended including examining the transformative effects of technology on FLE work, focusing on decent work for FLEs and conducting practically relevant and impactful research. Originality/value This paper provides reflections, integration and future directions for scholarship based on systematic reviews of key domains of FLE research, a primer for conducting systematic reviews (specifically – meta-analysis) and practitioner perspectives on extant research.

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.

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)0.011
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.797
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.259
GPT teacher head0.475
Teacher spread0.216 · 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