http://hdl.handle.net/10071/5821 Sat, 13 Oct 2018 12:49:06 GMT 2018-10-13T12:49:06Z http://hdl.handle.net/10071/16055 Title: The effect of emotions on brand recall by gender using voice emotion response with optimal data analysis Authors: Wang, W.-C.; Pestana, M. H.; Moutinho, L. Abstract: Purpose—To analyses the effect of emotions obtained by oral reproduction of advertising slogans established via Voice Emotion Response software on brand recall by gender; and to show the relevance for marketing communication of combining “human–computer Interaction (HCI)” with “affective computing (AC)” as part of their mission. Design/methodology/approach—A qualitative data analysis did the review of the scientific literature retrieved from Web-of-Science Core Collection (WoSCC), using CiteSpace’ scientometric technique; the quantitative data analysis did the analysis of brand recall over a sample of Taiwan’ participants by “optimal data analysis”. Findings—Advertising effectiveness has a positive association with emotions; brand recall varies with gender; and “HCI” connected with “AC” is an emerging area of research. Research limitations/implications—The selection of articles obtained depend on the terms used in WoSCC, and this study used only five emotions. Still the richness of the data gives some compensation. Practical implications—Marketers involved with brands need a body of knowledge on which to base their marketing communication intelligence gathering and strategic planning. Originality/value—It provides exploratory research findings related to the use of automatic tools capable of mining emotions by gender in real time, which could enhance the feedback of customers toward their brands. Mon, 01 Jan 2018 00:00:00 GMT http://hdl.handle.net/10071/16055 2018-01-01T00:00:00Z http://hdl.handle.net/10071/16054 Title: The knowledge domain of affective computing: a scientometric review Authors: Pestana, M. H.; Wang, W.-C.; Moutinho, L. Abstract: Purpose – The aim of this study is to investigate the bibliographical information about Affective Computing identifying advances, trends, major papers, connections, and areas of research. Design/methodology/approach – A scientometric analysis was applied using CiteSpace, of 5,078 references about Affective Computing imported from the Web-of-Science Core Collection, covering the period of 1991-2016. Findings – The most cited, creative, burts and central references are displayed by areas of research, using metrics and througout-time visualization. Research limitations/implications – Interpretation is limited to references retrieved from theWeb-of-Science Core Collection in the fields of management, psychology and marketing. Nevertheless, the richness of bibliographical data obtained, largely compensates this limitation. Practical implications – The study provides managers with a sound body of knowledge on Affective Computing, with which they can capture general public emotion in respect of their products and services, and on which they can base their marketing intelligence gathering, and strategic planning. Originality/value – The paper provides new opportunities for companies to enhance their capabilities in terms of customer relationships. Mon, 01 Jan 2018 00:00:00 GMT http://hdl.handle.net/10071/16054 2018-01-01T00:00:00Z