A multi-stage satisfaction index estimation model integrating structural equation modeling and mathematical programming

Aktepe, Adnan; Ersöz, Süleyman; Toklu, Bilal

doi:10.1007/s10845-015-1166-x

Cited by 7 publications

(6 citation statements)

References 26 publications

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“…An element to highlight the study, following previous studies, 19,23,26,33 is that it does not assume the same weights used to measure satisfaction, which allows an exact understanding of the level of satisfaction that exists and of those about which it is more convenient to act to improve it. In this sense, the use of expert methods and the AHP 29 is used to assign weights to each criterion, depending on the perceived importance of achieving external customer satisfaction.…”

Section: Discussionmentioning

confidence: 99%

“…In order to establish the attributes, dimensions, and interrelationships that allow to explain customer satisfaction, several mathematical processes have been proposed, some of which are well known as SERVQUAL, 24 or more recent ones such as the use of postulates of fuzzy logic 25 ; in addition to various quantitative methods like AHP, 26 –30,18 genetic algorithms, 31 structural equations, 32 –34 Bayesian statistics, 35 neural networks, 36 among others. Table 1 shows a summary of the most common methods used for these purposes.…”

Section: Theoretical Analysismentioning

confidence: 99%

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Tools for measuring and improving external customer satisfaction in stores of Santo Domingo, Ecuador

Sánchez-Rodríguez

Pérez-Campdesuñer

García-Vidal

et al. 2017

International Journal of Engineering Business Management

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This article is based on the development and application of a procedure to measure and improve external customer satisfaction, allowing a rational intervention in the variables related to the quality of service and leading to the progressive improvement of quality management in stores of Santo Domingo, Ecuador. It was possible to measure the levels of satisfaction experienced by customers based on perceptions about the service they receive. In addition, it allowed the modeling of indicators measuring the degree of customer satisfaction and loyalty, both globally and by processes, from a multi-attribute approach, which uses a linear additive model of attributes that characterize it and identifies those essential and critical of according to its importance and current valuation, in the framework of the specific procedure developed to evaluate the level of service performance, allowing to focus the management actions towards the solution of problems and the improvement of vital aspects of the execution of the service and in this way to maintain a continuous monitoring of the indicators of performance of the customer satisfaction in the selected organization.

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Section: Discussionmentioning

confidence: 99%

Section: Theoretical Analysismentioning

confidence: 99%

Tools for measuring and improving external customer satisfaction in stores of Santo Domingo, Ecuador

Sánchez-Rodríguez

Pérez-Campdesuñer

García-Vidal

et al. 2017

International Journal of Engineering Business Management

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“…Thus, the measurement of the latent variable is made possible (Byrne, 2010). A measurement variable is a type of variable that can be observed with questionnaire forms and collected data (Aktepe et al, 2015). The schematic representation of the SEM model to be used in our study is shown in Figure 3.…”

Section: Methodsmentioning

confidence: 99%

“…The weight expressed by Equation ( 2) is used to calculate the index score (Ej) of the mean j latent variable. In this equation, nj, j. the number of measurement variables in the dimension; w ji , obtained at the end of the structural equation model solution, where j is the latent variable and i is the external weight of the measurement variable; y ji , j. is the average of the measurement variable values in the dimension and k are the maximum value of the scale of the questionnaire used in data collection (Aktepe et al, 2015). Index scores calculated as percentages using the formula in Equation (2) are shown in Figure 7.…”

Section: Performance Index Score Of Each Dimensionmentioning

confidence: 99%

Investigation of Food Supply Chain Sustainability Performance for Turkey's Food Sector

Yontar

Ersöz

2020

Front. Sustain. Food Syst.

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Increasing product demands, environmental aspects, and overpopulation have an impact on the sustainability of a supply chain, especially in the food sector. In a food supply chain from production to consumption, there are many parameters (resources, packaging, waste management, etc.) that need to be taken into account for sustainability. The aim of this study is to determine the parameters affecting sustainable food supply chain management for the food sector and to measure the performance of the parameters along the supply chain. In this study, several performance indices and sub-criteria are defined by reviewing the indices previously discussed in the literature and accounting for expert opinions on the sustainable food supply chain. Customer satisfaction, resource utilization, product safety, innovation, reliability, company information, packaging, and waste management are defined as the parameters, as these are dimensions that should be improved in sustainable food supply chain management. The performance score for each dimension is calculated via Structural Equation Modeling and the Analytic Hierarchy Process. Customer satisfaction is calculated to have the highest performance, with a score of 86.23% in sustainable food supply chain management performance evaluation, followed by the product safety dimension, at 84.65%, while the performance index score of the reliability dimension is 82.97%, that of the packaging dimension is 78.81%, that of the company information dimension is 75.10%, that of resource utilization is 71.41%, and that of the waste management dimension is 67.83%. The sustainable food supply chain performance evaluation for the food sector in Turkey indicates that it has an overall performance of 79.7%. The results of this study include feedbacks on parameters in the food chain from agriculture to consumers.

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“…Regarding methods to evaluate customer satisfaction, these vary in their mathematical treatment, from the oldest ones known as the SERVQUAL (Stefano et al 2015) to more current or less used ones such as the use of fuzzy logic (Saeedpoor et al 2015), genetic algorithms (Hao et al 2015), structural equations (Aktepe et al 2015a(Aktepe et al , 2015bSatsanguan et al 2015), or more recently as neural networks (Leong et al 2015), among others. Each of them with their usefulness and limitations regarding their requirements to be applied, or the results they give.…”

Section: Similar Proposal Makes Buhalis (2000)mentioning

confidence: 99%

Structural Equation Model: Influence on Tourist Satisfaction With Destination Atributes

Pérez-Campdesuñer¹,

García-Vidal²,

Sánchez-Rodríguez³

et al. 2017

Tour. hosp. manag.

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Purpose -To present a model that expresses the relationships observed between a set of independent variables that condition overall satisfaction with a tourist destination, allowing to discover the potential for improvement of this indicator. Methodology -An instrument is designed to measure the satisfaction of tourists with a destination, starting from a list of attributes used in the literature that are submitted to the research of experts. A reliability analysis of the results and an evaluation of construct validity were performed. Through a confirmatory factor analysis, the factorial structure of the set of observed variables was identified. Finally, a structural equations model was created to understand the interrelationship between the variables considered in the study and their incidence in general satisfaction with the destination. Findings -The application of the instrument designed to the calculated sample allowed to identify the latent variables existing in the practical construct studied, identifying through the factorial analysis four aspects associated to the satisfaction of tourists with the destination: access, lodging, facilities and attractions. The construction of the structural equations model corroborated the previous results and evidenced the level of incidence of each factor studied in the overall satisfaction as well as the incidence of each attribute in the factor that integrates. Originality -It is achieved define a structural equations model that represents and explains the relationship between the variables considered in the quality management of a destination and the degree to which they relate to each other and influence the level of satisfaction experienced by tourists.

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A multi-stage satisfaction index estimation model integrating structural equation modeling and mathematical programming

Cited by 7 publications

References 26 publications

Tools for measuring and improving external customer satisfaction in stores of Santo Domingo, Ecuador

Tools for measuring and improving external customer satisfaction in stores of Santo Domingo, Ecuador

Investigation of Food Supply Chain Sustainability Performance for Turkey's Food Sector

Structural Equation Model: Influence on Tourist Satisfaction With Destination Atributes

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