İktisadi ve İdari Bilimler Fakültesi / Faculty of Economics and Administrative Sciences

Permanent URI for this collectionhttps://hdl.handle.net/11727/1399

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Author: search.filters.author.Atalay, Kumru Didemsearch.filters.applied.f.rights: search.filters.rights.info:eu-repo/semantics/closedAccess

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    Quality Improvement Strategies of Highway Bus Service Based On A Fuzzy Quality Function Deployment Approach
    (2016) Kurtulmusoglu, Feride Bahar; Pakdil, Fatma; Atalay, Kumru Didem; A-7058-2017
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    Focusing on the big picture while observing the concerns of both managers and passengers in the post-covid era
    (2021) Samanci, Simge; Atalay, Kumru Didem; Isin, Feride Bahar
    This study reveals how to improve and define the issues of service quality in the airline sector after the outbreak of COVID-19, to what extent customer needs (important issues) and expectations (expected performances) will differ, and the priorities of airline sector managers in terms of resource allocation, costs, planned strategies, and operational efficiency and effectiveness. It offers a systematic and interactive perspective by simultaneously providing the perspective of both airline managers and passengers by using a new hybrid method, namely Fuzzy Importance, Expected Performance, and Priority Analysis (FIEPA) with VIKOR. This method allows the use of different perspectives of different managers in the analysis, which can be prioritized with different weights. According to the results of the study, in which 449 passengers participated on Twitter, the attributes on which airline managers should focus were determined, having three distinctive characteristics of being important for customers, having high priority according managers, and having low expected performance according customers. Twenty-two attributes related to the service quality of airlines during outbreak periods were classified into three main dimensions as "social distance and hygiene during flight", "information awareness and concern", and "infection alert procedure".
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    The effects of consumer confusion on hotel brand loyalty: an application of linguistic nonlinear regression model in the hospitality sector
    (2020) Kurtulmusoglu, Feride Bahar; Atalay, Kumru Didem
    The aim of the study is to estimate the interaction and quadratic relationships between dimensions by estimating a model for the confusion dimensions that affect hotel brand loyalty, thus providing the interested parties with a perspective and direction regarding consumer confusion. This study also aimed to strengthen the use of FLS in the field of social sciences and will use this method to transform the discrete ordinal variable into a continuous variable while preserving the semantic meaning. Four hundred and six individuals participated in the study. Hypotheses demonstrating the interaction and quadratic effects between the continuous variables have been analysed using nonlinear multiple regression analysis. This study proposes a survey-based method to estimate a model for the confusion dimensions that affect hotel brand loyalty. The results demonstrated that ambiguity confusion, overload confusion, similarity confusion, quadratic effect of similarity confusion and interaction of ambiguity, overload and similarity confusion decrease the hotel brand loyalty. Also, quadratic effect of ambiguity confusion, interaction of ambiguity and overload confusion, interaction of overload and similarity confusion, interaction of ambiguity and similarity confusion increase the hotel brand loyalty. Despite its importance for marketing and consumer behaviour, the definition, measurement, dimensions and existing results of consumer confusion have begun to be discussed and examined recently in a limited scope. Studies have demonstrated that consumer confusion about tourism products is a non-functional and under-evaluated area but also is utmost prominent for tourism product. This study aimed to obtain a stronger model in which all the interactions between variables and their (quadratic) increasing effects are considered using a nonlinear regression model.