Virtual reality in digital marketing: research agenda based on bibliometric reflection

Abstract

PurposeThis study unravels the intellectual structure of virtual reality (VR) in digital marketing (DM) research, identifies core research gaps and presents future research avenues. The study also conducts a performance analysis of publications in the field and identifies the most important stakeholders of the stated topic.Design/methodology/approachThe Web of Science database was used to retrieve the publications that were relevant to the topic between 2012 and 2022. Biblioshiny, a shiny app for the Bibliometrix R package, is used to conduct a bibliometric analysis by decoding the results into several visual representations.FindingsThis report includes the most prolific contributors, keyword analysis results, productive nations, authors and connections, as well as the most often cited publications on VR in DM. In DM research, numerous perspectives on VR were looked at, explored and revealed.Practical implicationsThe findings provide a new perspective and understanding of the issue for researchers in order to improve their research insights in the field. This study will also benefit marketing practitioners in ensuring the sustainability and innovativeness of technology used to run their DM campaigns.Originality/valueThis research provides the first bibliometric analysis of the citation works and productivity in the field of VR in DM using Biblioshiny, identifies core research gaps and provides future research agenda which can be useful to advance the research understanding in this context.

Robotic process automation: bibliometric reflection and future opportunities

“…The customizable, interactive and user-friendly features of Biblioshiny make it an appealing choice for researchers and analysts who want to analyse and visualise bibliographic data. It is a strong and versatile instrument for exploring bibliographic data (Zaki et al ., 2023). We followed future research directions reporting as demonstrated by Balzano (2022) and Turzo et al .…”

Marketing and Virtual Reality: A Bibliometric Analysis

“…When bibliometric studies on virtual reality were examined, it was seen that studies were intense in the fields of education (Huang et al, 2016;Fernandez-Herrero et al, 2018;Calabuig-Moreno et al, 2020;Soto et al, 2020;Agbo et al, 2021;Rojas-Sánchez et al, 2023), and health (Yeung et al, 2021;Liu et al, 2022). However, there are also bibliometric studies in the literature on marketing and virtual reality (Bardhan, 2020;Damar, 2021;Goel et al, 2022;Ha et al, 2023;Hanaa & Abdul, 2023;Knani et al, 2022;Molina-Collado et al, 2022;Sousa et al, 2022;Tran & Nguyen, 2023;Yüksek et al, 2020;Zaki et al, 2023). There are many marketing and virtual reality themed studies in the literature on topics such as tourism marketing, virtual tourism, metaverse, read-made clothing industry, digital marketing and augmented reality.…”

A Method of Applying Virtual Reality Converged Remote Platform Based on Crawfish Optimization Algorithm to Improve ESN Network

“…The integration effect analysis methods mainly include random forest, support vector machine, neural network, deep learning, intelligent optimization algorithm and other methods [9]. Literature [10] used various types of distance learning data, combined with the random forest algorithm, to build a fusion distance platform effect analysis model; literature [11] explored the impact of diversified virtual reality technology on the distance classroom, used the support vector regression algorithm to build the effect analysis model, verified the effectiveness of virtual reality technology teaching, and analyzed the effect value of the fusion of virtual reality technology in the distance classroom; literature [12 ] by exploring the combination of virtual reality and education on the modernization and intelligent promotion of teaching, designing a neural network-based effect analysis model, and verifying the effectiveness of the intelligent effect analysis method in the fusion remote platform; Literature [13] designed a cloud-based virtual operating platform, combined with the machine learning method, to develop the analysis program of virtual reality fusion remote platform, and verified the feasibility of quantifying the effect; Literature [14] proposed a remote teaching evaluation method based on decision tree algorithm, while combining virtual reality technology, analyzed the application integration effect, thus improving the quality of teaching; literature [15] extracted the virtual reality technology fusion remote platform effect analysis indexes by dividing and established the virtual reality technology fusion remote platform evaluation model based on the intelligent optimization algorithm optimization and improvement of machine learning, to provide a new analysis method for the effect analysis method ideas; Literature [16] combines integrated learning technology and deep learning technology to propose a virtual reality technology fusion intelligent remote platform effect analysis model based on virtual reality technology, which verifies the efficiency of integrated learning and deep learning technology. For the above literature analysis, the existing integration effect analysis methods have the following defects [18]:…”