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Record W4200568820 · doi:10.5267/j.msl.2021.10.003

The effect of customer orientation on financial performance in service firms: The mediating role of service innovation

2021· article· en· W4200568820 on OpenAlexvenueno aff
Mohammad Zahidul Islam, Zhe Zhang

Bibliographic record

VenueManagement Science Letters · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsnot available
Fundersnot available
KeywordsStructural equation modelingBusinessService (business)MarketingMarket orientationService innovationPledgeFinancial servicesService-orientationIndustrial organizationComputer scienceFinance

Abstract

fetched live from OpenAlex

In service firms, customer orientation and service innovativeness are the important strategic features to pledge sustainable wealth and growth for financial performance. Focusing on customer means, companies must have rigorous knowledge and understanding of customer needs, expectations, and demands. To satisfy those demands and expectations, new products and/or services need to be carefully designed. Customer orientation involves the introduction of something new or different in response to market conditions and can be perceived as an important driver for innovation. The literature on innovation in services demonstrates that this territory is still under-investigated. Our study is an attempt to slightly complement this shortcoming by empirically solving several issues related to service firms. In particular, we propose the service innovativeness as a mediating effect in the relationship between customer orientation and financial performance. A theoretical research model was investigated via structural equation modeling (SEM) using 686 survey responses from the service industry. The findings of the structural equation model indicated that customer orientation is positively related to financial performance and service innovativeness respectively. And service innovativeness was found as a partial mediating effect, which means that the service innovativeness intervenes for some part but not all of the relationships between customer orientation and financial performance.

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)0.003
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.009
GPT teacher head0.232
Teacher spread0.223 · 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 designObservational
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".

Quick stats

Citations7
Published2021
Admission routes1
Has abstractyes

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