Yazar "Simonetti, Biagio" seçeneğine göre listele

Listeleniyor 1 - 5 / 5
  • [ X ]
    Öğe
    Determining factors affecting healthcare service satisfaction utilizing fuzzy rule-based systems
    (Taylor & Francis Ltd, 2016) Demir, Mehmet Ozer; Basaran, Murat Alper; Simonetti, Biagio
    Health communication, which is a multi-attribute concept, is a generic title describing clinical practice. The literature shows that the relation between health communication and healthcare service satisfaction (HSS) has been found to be significant. The main objective of pursuing better health communication is to achieve the best outcome and patient satisfaction where healthcare systems are supposed to deliver. However, the health communication is a complex process. Also, measuring patients' satisfaction is not an easy task since satisfaction is a complex notion with several factors. In this study, questions in the questionnaire directed to patients are factor-analyzed in order to obtain components which are used as independent attributes that will be modeled by fuzzy rule-based systems (FRBS) in order to explain HSS. Utilizing FRBS brings two different advantages, one of which is to use mathematical functions called membership functions for linguistically expressed responses. The second one is to observe the transition among the linguistic values expressed by patients. The four independent variables, namely, doctor-patient communication (DPC), information seeking behavior (ISB), equal behavior and tolerance to cultural differences (TCD) and the dependent variable HSS are employed in the modeling. Although both DPC and ISB have positive effects on HSS, TCD has none. One interesting finding about DPC is that if DPC scores below the average value tend to lower, it does not have a decreasing effect on HSS, which means that if a patient does expect to have average DPC, his or her evaluation on HSS does not lower, which says that if a patient knows that the doctor has a poor communication skill, the patient does not pay attention to this attribute.
  • [ X ]
    Öğe
    Fuzzy correlation and fuzzy non-linear regression analysis
    (Springer Int Publishing Ag, 2016) Başaran, Murat Alper; Simonetti, Biagio; D'Ambra, Luigi
    In this chapter, we will deal with fuzzy correlation and fuzzy non-linear regression analyses. Both correlation and regression analyses that are useful and widely employed statistical tools have been redefined in the framework of fuzzy set theory in order to comprehend relation and to model observations of variables collected as either qualitative or approximately known quantities which are no longer being utilized directly in classical sense. When fuzzy correlation and fuzzy non-linear regression are concern, dealing with several computational complexities emerging due to the nature of fuzzy set theory is a challenge. It should be noted that there is no well-established formula or method in order to calculate fuzzy correlation coefficient or to estimate parameters of the fuzzy regression model. Therefore, a rich literature will accompany with the readers. While extension principle based methods are utilized in the computational procedures for fuzzy correlation coefficient, the distance based methods preferred rather than mathematical programming ones are employed in parameter estimation of fuzzy regression models. That extension principle combined with either fuzzy arithmetic or non-linear programming is two different methods proposed in the literature will be examined with small but illustrative examples in detail for fuzzy correlation analysis. Fuzzy non-linear regression has been a relatively new studied method when compared to fuzzy linear regression. However, both employ similar tools. S-curve fuzzy regression and two types of quadratic fuzzy regression models in the literature will be discussed.
  • [ X ]
    Öğe
    Political segmentation based on pictorial preferences on social media
    (Springer Science and Business Media B.V., 2021) Demir, Mehmet Özer; Simonetti, Biagio; Gök Demir, Zuhal
    Social media platforms, which are accepted as a channel for selling, listening and receiving continuous feedback from customers, have the opportunity to expand beyond the limits of traditional mass media channels. Social media mechanisms work well if the right message is delivered to the right person, so knowing the person concerned is a prerequisite for communication. This article aims to explore the potential of photos shared, liked and commented on social media as a consumer segmentation tool. The findings of study should help understand customer segments and deliver customized products, services, and advertisements. An online survey consisting of pictures and items was conducted in Turkey. The aim was to evaluate users' pictorial preferences to identify different consumer segments. The Support Vector Machine procedure revealed the existence of two clusters. It enables them to recognize different segments, to see marketers as individuals in order to communicate with themselves and to understand world views from a variety of perspectives. © 2021, The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature.
  • [ X ]
    Öğe
    Quantification of qualitative assessments using computing with words: In framework of fuzzy set theory
    (Springer, 2020) Başaran, Murat Alper; Simonetti, Biagio; Başaran, Alparslan Abdurrahman
    When qualitative data are collected, which is a widespread situation encountered in several disciplines ranging from social sciences to decision making to engineering as a result of dealing with ill-defined concepts or with complex tasks to assess, there is a certain need to crunch them and infer from them. Hence, quantification, namely computing with words (CW), emerges as a research area. Even though social science disciplines deal with these types of data numerically using various Likert scales, fuzzy set theory first proposed by Zadeh dealing words or sentences with mathematically oriented manner in order to create machines that mimic the reasoning of human being brings new perspectives. Since then, its applicability has expanded into various disciplines for different purposes to transform subjectivity into objectivity. In this manuscript, the effort of transformation from subjectivity into objectivity will be reviewed based on the available proposed methods in the literature. Two illustrative examples will be employed. While the first illustrative example, which consists of balanced and unbalanced linguistic term sets, is used for each reviewed method in the literature to show its computations step by step, the second of which, balanced linguistic term set, is an example used in the literature that is employed. Therefore, a comprehensive review of the proposed methods with illustrative examples is presented.
  • [ X ]
    Öğe
    Voter classification based on susceptibility to persuasive strategies: A machine learning approach
    (Springer, 2020) Demir, Mehmet Özer; Simonetti, Biagio; Başaran, Murat Alper; Irmak, Sezgin
    The current literature on the campaigns of political marketing is based on mass communication. However, the online community introduces new opportunities, one of them is captology. As a part of captology, the persuasive strategies take increasing attention from both authors and practitioners. There is a growing literature that persuasive technologies are useful in the attitudinal and behavioral change of the targeted group, which is the aim of political marketing. This research introduces the persuasive strategies into political marketing literature. In this manuscript, respondents are discriminated based on their susceptibility to the persuasive strategies to determine which persuasive strategy has effects on liberals and conservative. Findings suggest that liberals and conservatives can be discriminated based on their susceptibility to persuasive strategies using machine learning algorithms. The findings of the study offer new insights into political marketing campaigns.