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Record W2612314243

Customer Satisfaction and Customer Perceived Value and its Impact on Customer Loyalty: The Mediational Role of Customer Relationship Management

2017· article· en· W2612314243 on OpenAlexvenueno aff
Farheen Javed, Sadia Cheema

Bibliographic record

VenueThe Journal of Internet Banking and Commerce · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsnot available
Fundersnot available
KeywordsCustomer retentionCustomer advocacyLoyalty business modelCustomer intelligenceCustomer satisfactionCustomer delightCustomer to customerMarketingBusinessCustomer equityService qualityVoice of the customerService (business)
DOInot available

Abstract

fetched live from OpenAlex

Today’s competitive environment in restaurant sector adds extra barriers to achieve customer loyalty. Customer loyalty is crucial to improve overall performance and build better relationship with potential customers. The existence of high levels of customer satisfaction, customer perceived value and customer relationship management enhance the relationship of customer with the firm which strongly boost up the overall performance of the firm. The focus of this research is to examine the impact of customer satisfaction and customer perceived value on customer loyalty. Additionally, the study will help to analysis the mediating effect of customer relationship management (CRM) in this relationship. The main reason behind this research is to discover significant measures to positively enhance customer loyalty in service sector. Currently, limitedresearch exists on relationship of these variables, especially on restaurant sector in Pakistan. This study also intent to examine more manners to strongly enhance customer loyalty. The research design is based on quantitative research thus the data was collected through primary data, five Likert-scales and Spss 24 was used to compute results. Convince sampling method was used in order to gather data. Different tests were applied to analyze reliability and validity furthermore it is recommended from this study that customer satisfaction, customer perceived value and CRM is key drivers to build customer loyalty. Lastly, this study discussed further ways which can be useful for future 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.

How this classification was reachedexpand

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.219
Threshold uncertainty score0.627

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.025
GPT teacher head0.286
Teacher spread0.261 · 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 teacher head, 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

Citations44
Published2017
Admission routes1
Has abstractyes

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