2022
DOI: 10.4018/978-1-6684-4496-2.ch016
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Demystifying Neuromarketing

Abstract: This study tries to decipher the role of neuromarketing in the myriad fields of business employing in-depth review of literature. This work thus proposes abundant acumens into important facets of neuromarketing in the business world employing a bibliometric investigation. The chapter presents an assessment of important neuromarketing enablers and their function in several business disciplines aimed superior business performance. The existing literature was classified based on a variety of bibliometric factors … Show more

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Cited by 8 publications
(5 citation statements)
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References 47 publications
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“…This systematic literature review consists of three components: keyword co‐occurrence analysis, thematic analysis and qualitative content analysis. Keyword co‐occurrence analysis is a bibliometric method that uses computer software to statistically analyse keyword occurrences in the examined corpus to identify prominent research clusters (Chandel & Kaur, 2022; He, 1999; Lis, 2018; Wang et al, 2021). It is used to complement and guide the content analysis of the literature, such that the review process can be conducted thematically under the identified research areas.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…This systematic literature review consists of three components: keyword co‐occurrence analysis, thematic analysis and qualitative content analysis. Keyword co‐occurrence analysis is a bibliometric method that uses computer software to statistically analyse keyword occurrences in the examined corpus to identify prominent research clusters (Chandel & Kaur, 2022; He, 1999; Lis, 2018; Wang et al, 2021). It is used to complement and guide the content analysis of the literature, such that the review process can be conducted thematically under the identified research areas.…”
Section: Methodsmentioning
confidence: 99%
“…A bibliometric software, VOSviewer, was adopted for keyword co‐occurrence analysis to identify major research domains in the existing sustainable packaging literature. VOSviewer is chosen because of its clear visualisation feature and its embedment of text mining function to statistically identify keyword clusters (Chandel & Kaur, 2022). Bibliographic data including citation information, abstract and author's keywords of all selected publications were imported into VOSviewer for keyword co‐occurrence analysis.…”
Section: Methodsmentioning
confidence: 99%
“…Similarly, an analysis of the co-occurrence of keywords was conducted to show the main channels of the study of incorporating fintech in social protection service provision (Contreras and Abid 2022). VOSviewer is an instrument for the graphic analysis of system charts founded on citations, co-citations, and the co-occurrence of keywords that elucidates the intellectual and social structure of a research study (Wong 2018;Setyowati 2022;Chandel and Kaur 2022). The functionality of VOSviewer is particularly valuable in its ability to display huge bibliometric charts in the most simplified way for easy interpretation (Van Eck and Waltman 2010).…”
Section: Methodsmentioning
confidence: 99%
“…Given the research's specific focus on ecocide, only studies aligning with the defined research objectives were chosen. In this context, the PRISMA framework was employed to ensure the inclusion of relevant studies [2,3]. The PRISMA framework consists of four key phases: identifying and documenting studies through database searches, reviewing the documented studies, verifying eligibility, and making the final selection of studies.…”
Section: Figure 1: Year Wise Publications On Ecocidementioning
confidence: 99%
“…Based on the notion that keywords offer a robust and logical basis for elucidating the content of research papers, keyword analysis has emerged as a valuable analytical approach for investigating specific themes in marketing or other fields of literature, gaining increased recognition [2,3]. In the realm of bibliometrics, four distinct analysis techniques are applied: co-word association, co-word clustering, co-word frequency, and burst word monitoring.…”
Section: 2mentioning
confidence: 99%