Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/1AE82B36-B672-4850-9D3B-0A13B37F3B92 | ||
| Year | 2024 | ||
| Type of Item | Diploma Work | ||
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| Bibliographic Citation | Arista Gavioti, "Study of consumer behavior in online shopping and benchmarking of online stores", Diploma Work, School of Production Engineering and Management, Technical University of Crete, Chania, Greece, 2024 https://doi.org/10.26233/heallink.tuc.101263 | ||
| Appears in Collections |
The widespread dissemination of e-commerce in recent years and the changes it has brought to consumer behavior have brought it to the forefront, making it a subject of study for many business professionals. This thesis examines consumer behavior in six online stores operating in the Greek market. A specially designed questionnaire was used in the form of an electronic form that was posted publicly. Demographic data for the sample that responded were collected, as well as information on behavior and preferences related to the online purchases made. The primary data, after basic preprocessing, were evaluated for the completeness and consistency of the various variables corresponding to the submitted responses and were examined for their statistical characteristics, followed by visualization to observe patterns. Subsequently, methods and tests from descriptive statistics were used to derive useful conclusions regarding the relationship between various categorical variables among the demographic data and the consumer profiles of the sample. The Markex multicriteria analysis methodology was then applied, where the UTASTAR method was applied, to calculate the overall utilities of the stores and the significance of the evaluation criteria. The stores were ranked based on the values consumers assigned to the various criteria. The results of this research provide valuable insights into understanding consumer behavior in online shopping to make important business decisions. The process followed consists of a sequence of steps, starting with the design of the data collection for the research, the application of various data analysis methods (descriptive statistics, multicriteria analysis), as well as the utilization of appropriate tools (collection, processing, analysis, visualization). A comprehensive methodology emerges that can be used in other fields of application as well.
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