Universal structure modeling approach to customer satisfaction index

Ali Turkyilmaz, Asil Oztekin, Selim Zaim, Omer Fahrettin Demirel

Research output: Contribution to journalArticle

26 Citations (Scopus)

Abstract

Previous researches have proven that customer satisfaction and loyalty are affected by complicated relationships and are challenging to European customer satisfaction index (ECSI) model. Existing approaches mostly limit their hypotheses to linear relationships, which hinder much information that would lead to better modeling and understanding the relationship between customer satisfaction and loyalty. The purpose of this paper is to reveal potential nonlinear and interaction effects that might be embedded in antecedents of ECSI by exemplifying it in Turkish telecommunications sector. This papar has justified the validity and reliability of the ECSI model implementation in Turk Telekom Company. The path models are tested via conventional structural equation modeling (SEM) and using a novel method, i.e. universal structure modeling with Bayesian neural networks. The findings of this study reveal that quality has the most important impact on customer satisfaction. The next important construct was found to be the company image. The relationship between customer expectation and customer satisfaction was revealed to be insignificant. This study reveals the fact that while using the ECSI model more attention must be paid to the consideration of potential nonlinear relationships that might be available among model constructs. This research presents uniqueness in that it reveals significant nonlinear relationships between the model constructs of the ECSI model. Previous studies have identified purely linear relationships, which may not hold true in reality. However, in this study it is revealed that improving one determinant of customer satisfaction may not be as worthy as it is assumed to be in theory, which refers to a nonlinear relationship.

Original languageEnglish
Pages (from-to)932-949
Number of pages18
JournalIndustrial Management and Data Systems
Volume113
Issue number7
DOIs
Publication statusPublished - Aug 16 2013
Externally publishedYes

Fingerprint

Customer satisfaction
Modeling
Telecommunication
Industry
Neural networks
Index model

Keywords

  • Bayesian neural networks
  • Customer satisfaction
  • Customer satisfaction index
  • SEM
  • Telecommunication
  • Universal structure modeling

ASJC Scopus subject areas

  • Management Information Systems
  • Industrial relations
  • Computer Science Applications
  • Strategy and Management
  • Industrial and Manufacturing Engineering

Cite this

Universal structure modeling approach to customer satisfaction index. / Turkyilmaz, Ali; Oztekin, Asil; Zaim, Selim; Fahrettin Demirel, Omer.

In: Industrial Management and Data Systems, Vol. 113, No. 7, 16.08.2013, p. 932-949.

Research output: Contribution to journalArticle

Turkyilmaz, Ali ; Oztekin, Asil ; Zaim, Selim ; Fahrettin Demirel, Omer. / Universal structure modeling approach to customer satisfaction index. In: Industrial Management and Data Systems. 2013 ; Vol. 113, No. 7. pp. 932-949.
@article{5e70188827c5486c9607d055513ee83c,
title = "Universal structure modeling approach to customer satisfaction index",
abstract = "Previous researches have proven that customer satisfaction and loyalty are affected by complicated relationships and are challenging to European customer satisfaction index (ECSI) model. Existing approaches mostly limit their hypotheses to linear relationships, which hinder much information that would lead to better modeling and understanding the relationship between customer satisfaction and loyalty. The purpose of this paper is to reveal potential nonlinear and interaction effects that might be embedded in antecedents of ECSI by exemplifying it in Turkish telecommunications sector. This papar has justified the validity and reliability of the ECSI model implementation in Turk Telekom Company. The path models are tested via conventional structural equation modeling (SEM) and using a novel method, i.e. universal structure modeling with Bayesian neural networks. The findings of this study reveal that quality has the most important impact on customer satisfaction. The next important construct was found to be the company image. The relationship between customer expectation and customer satisfaction was revealed to be insignificant. This study reveals the fact that while using the ECSI model more attention must be paid to the consideration of potential nonlinear relationships that might be available among model constructs. This research presents uniqueness in that it reveals significant nonlinear relationships between the model constructs of the ECSI model. Previous studies have identified purely linear relationships, which may not hold true in reality. However, in this study it is revealed that improving one determinant of customer satisfaction may not be as worthy as it is assumed to be in theory, which refers to a nonlinear relationship.",
keywords = "Bayesian neural networks, Customer satisfaction, Customer satisfaction index, SEM, Telecommunication, Universal structure modeling",
author = "Ali Turkyilmaz and Asil Oztekin and Selim Zaim and {Fahrettin Demirel}, Omer",
year = "2013",
month = "8",
day = "16",
doi = "10.1108/IMDS-12-2012-0444",
language = "English",
volume = "113",
pages = "932--949",
journal = "Industrial Management and Data Systems",
issn = "0263-5577",
publisher = "Emerald Group Publishing Ltd.",
number = "7",

}

TY - JOUR

T1 - Universal structure modeling approach to customer satisfaction index

AU - Turkyilmaz, Ali

AU - Oztekin, Asil

AU - Zaim, Selim

AU - Fahrettin Demirel, Omer

PY - 2013/8/16

Y1 - 2013/8/16

N2 - Previous researches have proven that customer satisfaction and loyalty are affected by complicated relationships and are challenging to European customer satisfaction index (ECSI) model. Existing approaches mostly limit their hypotheses to linear relationships, which hinder much information that would lead to better modeling and understanding the relationship between customer satisfaction and loyalty. The purpose of this paper is to reveal potential nonlinear and interaction effects that might be embedded in antecedents of ECSI by exemplifying it in Turkish telecommunications sector. This papar has justified the validity and reliability of the ECSI model implementation in Turk Telekom Company. The path models are tested via conventional structural equation modeling (SEM) and using a novel method, i.e. universal structure modeling with Bayesian neural networks. The findings of this study reveal that quality has the most important impact on customer satisfaction. The next important construct was found to be the company image. The relationship between customer expectation and customer satisfaction was revealed to be insignificant. This study reveals the fact that while using the ECSI model more attention must be paid to the consideration of potential nonlinear relationships that might be available among model constructs. This research presents uniqueness in that it reveals significant nonlinear relationships between the model constructs of the ECSI model. Previous studies have identified purely linear relationships, which may not hold true in reality. However, in this study it is revealed that improving one determinant of customer satisfaction may not be as worthy as it is assumed to be in theory, which refers to a nonlinear relationship.

AB - Previous researches have proven that customer satisfaction and loyalty are affected by complicated relationships and are challenging to European customer satisfaction index (ECSI) model. Existing approaches mostly limit their hypotheses to linear relationships, which hinder much information that would lead to better modeling and understanding the relationship between customer satisfaction and loyalty. The purpose of this paper is to reveal potential nonlinear and interaction effects that might be embedded in antecedents of ECSI by exemplifying it in Turkish telecommunications sector. This papar has justified the validity and reliability of the ECSI model implementation in Turk Telekom Company. The path models are tested via conventional structural equation modeling (SEM) and using a novel method, i.e. universal structure modeling with Bayesian neural networks. The findings of this study reveal that quality has the most important impact on customer satisfaction. The next important construct was found to be the company image. The relationship between customer expectation and customer satisfaction was revealed to be insignificant. This study reveals the fact that while using the ECSI model more attention must be paid to the consideration of potential nonlinear relationships that might be available among model constructs. This research presents uniqueness in that it reveals significant nonlinear relationships between the model constructs of the ECSI model. Previous studies have identified purely linear relationships, which may not hold true in reality. However, in this study it is revealed that improving one determinant of customer satisfaction may not be as worthy as it is assumed to be in theory, which refers to a nonlinear relationship.

KW - Bayesian neural networks

KW - Customer satisfaction

KW - Customer satisfaction index

KW - SEM

KW - Telecommunication

KW - Universal structure modeling

UR - http://www.scopus.com/inward/record.url?scp=84883297812&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84883297812&partnerID=8YFLogxK

U2 - 10.1108/IMDS-12-2012-0444

DO - 10.1108/IMDS-12-2012-0444

M3 - Article

AN - SCOPUS:84883297812

VL - 113

SP - 932

EP - 949

JO - Industrial Management and Data Systems

JF - Industrial Management and Data Systems

SN - 0263-5577

IS - 7

ER -