Abstract
Today, when technological developments are accelerating, the number of devices we use is increasing and household goods are equipped with smart functions and gain a more important place in our lives. Especially with the pandemic, the search for practical solutions that make housework easier has made online purchasing behavior indispensable. In this study, the problem of ranking the 6 best-selling new generation vacuum cleaner (NVC) types in a leading shopping site in Türkiye’s e-commerce market was discussed. For this purpose, the electronic word-of-mouth communication (e-WOM) for these products on a review platform in Türkiye where customers share evaluations of their experiences with the products or services was examined. In the first part of the study, the criteria of these products as specified on the review platform were evaluated by interviewing salespeople working in different electronics stores. Then, these criteria weights were obtained by using the Pythagorean Fuzzy Analytical Hierarchy Process (PFAHP) method. In the second part of the study, the most suitable NVC type was determined by the Pythagorean Fuzzy Technique for Order Preference by Similarity to Ideal Solutions (PFTOPSIS) method, taking the criteria weights into account obtained with PFAHP and customer satisfaction scores (CSS) on the review platform. Microsoft Excel 2010 program was used in the calculations. With the results obtained from the calculations, the type of vacuum cleaner that can adequately respond to the requests of the users and provide the highest satisfaction among the NVC with the highest sales has been determined. As far as is known, no study has employed hybrid PFAHP-PFTOPSIS method for the product ranking by using CSS. As a result, we think that this study provides a different perspective to the literature in this field.
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Kumcu, S., Tasdemir, B.D., Ozyoruk, B. (2024). Determination of the Most Suitable New Generation Vacuum Cleaner Type with PFAHP-PFTOPSIS Techniques Based on E-WOM. In: Şen, Z., Uygun, Ö., Erden, C. (eds) Advances in Intelligent Manufacturing and Service System Informatics. IMSS 2023. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-99-6062-0_7
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