Treffer: Enhancing International B2B Sales Training in the Wine Sector Through Collaborative Virtual Reality: A Case Study from Marchesi Antinori.

This study aims to identify and evaluate the essential design features, strengths, and limitations of a virtual reality (VR) application that has been developed to train an international sales force effectively for a premium global wine brand. The study emphasizes the value of stakeholder-driven iterative development and systematic evaluations. A case study methodology was adopted for the research, focusing on a VR training application, developed for Marchesi Antinori. The Scrum framework was employed to facilitate iterative stakeholder collaboration. A qualitative evaluation was conducted using focus groups, comprising marketing, communications, and sales representatives. A systematic application of natural language processing (NLP) embedding techniques and recursive clustering analyses was undertaken to interpret stakeholder feedback. The findings suggest that stakeholder-driven, iterative processes can significantly enhance the effectiveness of VR applications by providing a clear structure for immersive storytelling that focuses on terroir characteristics, vineyard operations, and cellar practices. Stakeholders acknowledged the potent educational benefits of VR in regard to business-to-business (B2B) sales training. However, they also highlighted significant limitations, including user discomfort, concerns about authenticity, and variations in market receptivity. Alternative immersive technologies, including augmented reality and immersive multimedia environments, have emerged as valuable complementary approaches. This study addresses a significant gap in the literature by examining the application of VR technology for B2B sales training in the premium wine industry. The study integrates an iterative Scrum methodology with advanced natural language processing (NLP) analytical techniques to derive nuanced, context-rich insights. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Theoretical & Applied Electronic Commerce Research is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Volltext ist im Gastzugang nicht verfügbar. Login für vollen Zugriff.