Customer knowledge is a strategic element, and its importance is growing all the time. The role of the vast quantities of information available in customer relationship management (CRM) systems, when processed using emerging big data techniques, is still in its infancy. Customer relationship management needs big data to improve customer experience and the right targeting of marketing actions. The study aims at designing a hierarchical model via the fuzzy approach of the indicators of the big data marketing approaches and the possible effects on the CRM. The results suggest that CRM initiatives based on big data could be envisaged as a supportive trend in relation to various managerial and structural dimensions. The study also identified major difficulties of big data analysis in CRM, such as storage, quality, process, and cost issues.

Qualitative research methodologies have long been undervalued and overshadowed by quantitative approaches in science and management. However, there is an inherent attractiveness and power in qualitative studies that lies in their ability to unveil the nuanced complexities and rich contextual elements often overlooked by purely numerical analyses. This chapter aims to illuminate the intricate artistry of conducting impactful qualitative research within these domains. The chapter also navigates the intricate process of data analysis, interpretation, and theory-building, underscoring the importance of reflexivity, triangulation, and the iterative nature of qualitative inquiry. Ultimately, this chapter serves as a compelling manifesto for embracing the subtleties of qualitative research, recognizing its vital role in uncovering the rich tapestry of human existence and organizational realities within the scientific and managerial realms.

The physical store provides a shopping experience that can't be replaced by digital means. However, the combination of the two has infinite potential and it's called the phygital shopping experience. In a retail context, phygital marketing is about finding the right amount of digital technology to incorporate into the store, to offer the shopper a unique shopping experience. Moreover, phygital marketing is a recent discipline that lacks practical and theoretical information. This study aims to contribute to the conceptualization of the latter through a netnography, and by linking the practice of phygital marketing to the behavioral science concept which is “the pain of paying.” This expression refers to the negative emotions felt during the process of paying for a product. Thus, a thematic content analysis opens the way to define a competitive advantage through phygital marketing.

Contemporary managerial thinking and practices have been developed in an economic context dominated by industrial logic. This logic conceals the imposing weight of services. Logistics is an activity that is undergoing major changes due to new technologies and managerial innovations. The advent of the supply chain service (SSCM), as a dual concept combining both traditional supply operations and the coordination of various resources, with a view to customer satisfaction, while integrating constraints of time, capacity, shared resources, and co-production, has turned logistics research upside down. The purpose of this chapter is to establish a qualitative analysis of the impact of MCSS practices on the performance of the service company. The theoretical analysis and the review of interviews show that SSCM approaches differ, and that company performance is viewed differently depending on each SSCM practice, and also depending on the multiple facets of this performance. Based on this qualitative review, several observations are identified. Request access from your librarian to read this chapter's full text.

The chapter aims to understand customer perception after the introduction of robots in the robotic mobile fulfillment system (RMFS) storage areas for Amazon. Based on a netnographic analysis focused on the use of RMFS by the American company Amazon, the work is mainly aimed at improving our understanding of the performance of RMFS and the perception of this technology by customers of service companies in general and retail companies in particular. Improved productivity, reduced operation time, agility and flexibility, improved picking accuracy, optimal space utilization, cost of capital, and work ergonomics are the main motivations perceived and discussed by the virtual community behind the introduction of RMFS in Amazon's storage areas. Several risks of RMFS robotization are discussed based on the qualitative study conducted. Finally, a classification of the customers' perception of this new technology is made by distinguishing the variables of perceived usefulness and ease of use.