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Record W3007721621

What Makes Customers Satisfied with the Local Government Agency: A Case Study in Rural Michigan

2019· article· en· W3007721621 on OpenAlexvenueno aff
Henry Wai Leong Ho

Bibliographic record

VenueJournal of rural and community development · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsnot available
Fundersnot available
KeywordsLocal governmentCustomer satisfactionBusinessPolitical scienceWelfare economicsPublic administrationHumanitiesMarketingEconomics
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this paper is to report on how a local government agency in rural Michigan, USA, tried to understand residents’ perceptions of the community features, facilities, and services available to them, in order to better leverage customer value to benefit its current and potential customers and increase customer satisfaction with the city as a whole. A total of 705 questionnaires were completed, collected, and analyzed using SPSS. The results suggested that although customers and residents were satisfied with most of the services currently provided, they had concerns about several amenities made available by the provider. In addition, bivariate correlation analysis showed that 13 variables were significantly related to overall satisfaction with the local authority. These findings have important implications for research and practice. Recommendations are to the local authority are offered for remaining relevant to customers in the provision of services. Keywords: Customer satisfaction, resident satisfaction, local government, small town development, rural local government ---------------------------------------------- Etude de cas : Ce qui rend les clients satisfaits de l’organisme gouvernemental local: une etude de cas dans le Michigan rural Resume Le but de cet article est de rendre compte de la maniere dont un organisme gouvernementale local du Michigan rural, aux Etats-Unis, a tente de comprendre la perception qu'ont les residents des caracteristiques, des installations et des services communautaires a leur disposition, afin de mieux tirer parti de la valeur client au profit de ses clients actuels et potentiels ainsi que d’augmenter la satisfaction des clients avec la ville dans son ensemble. Au total, 705 questionnaires ont ete remplis, collectes et analyses a l'aide de SPSS. Les resultats suggerent que meme si les clients et les residents etaient satisfaits de la plupart des services actuellement fournis, ils avaient des inquietudes au sujet de plusieurs equipements mis a disposition par le fournisseur. De plus, une analyse de correlation bivariee a montre que 13 variables etaient significativement liees a la satisfaction globale a l'egard de l'autorite locale. Ces resultats ont des implications importantes pour la recherche et la pratique. Des recommandations sont adressees aux autorites locales pour que la prestation de services aux clients demeure pertinente. Mots-cles: Satisfaction des clients, satisfaction des residents, gouvernement local, developpement de petites villes, gouvernement local rural

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0090.002
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.019
GPT teacher head0.238
Teacher spread0.219 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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