Abstract
The ever increasing intra- and inter-competition, increased costs, and a lower differentiation margin have led to intense competitive pressures within the domains of wholesaling and retailing. At the same time, the increasing digitization due to technological innovation will radical change the economical and procedural fundamentals. In addition, from an entrepreneurial point of view, it must also be considered that the complexity of decision-relevant framework conditions has increased. Digitalisation is therefore to be seen as an essential driver for optimising business processes and as the basis for a new understanding of products and services. However, it cannot be considered independently of other social trends. The chapter will elaborate the underlying drivers and technological trends empowering the transformation processes within the domain of wholesaling and retailing. Starting from these major drivers we will scrutinize the impact of technological advancements and the opportunities, risks and constraints which are connected with it.
TopIntroduction
The ever increasing intra/inter-competition, increased costs and a lower differentiation margin, have led to intense competitive pressures within the domains of the wholesale and retail industries. At the same time, the increasing digitization, due to technological innovation, will radically change the economical and procedural fundamentals. In addition, from an entrepreneurial point of view, it must also be considered that the complexity of decision-relevant framework conditions has increased. Therefore, digitalization should be viewed as an essential driver for optimizing business processes (Brynjolfsson et al., 2018), as well as the basis for a new understanding of products and services. The permanently emerging new technologies, all labeled as having huge impact on any industry, increasing the complexity even further. Many technologies have great impact, but only on limited industries and use cases. Adopting these technologies too early will certainly lead to frustration; just as the adopting of a technology too late can have a lasting impact which may put one out of business. A clear structure and assessment of upcoming technologies and trends is provided by the “Gartner Hype Cycle” (Walker, 2017), however, it is missing the retail industry specifics. Currently many studies about the application of technologies in retail and wholesale exist but are only limited to single technologies and their potential. Lot of scientific work exists regarding the role of big data and analytics (Bradlow et al., 2017), artificial intelligence (Krüger et al., 2011) or single task areas like pricing or marketing (Abels et al., 2018; Yeoman et al., 2017). But none of this work gathers all available technologies for all possible use-cases within the domain of retailing and wholesaling. This chapter will further elaborate the underlying technological trends, empowering the transformation processes within the domain of wholesaling and retailing. Starting with: the major technologies, the impact of technological advancements and opportunities, and the risks and constraints which are connected with it, are scrutinized. The results are finally summarized following the structure of a framework of the generic processes of trade companies.
A detailed overview of future technological trends that are relevant for retailing and wholesaling are provided. The structure allows scientist and practitioners to evaluate the impact and the potential areas of use, existing use-cases, and the overall potential for their processes of interest.
Key Terms in this Chapter
4D Printing: Multi-material prints, with the capability to transform over time, or a customized material system that can change from one shape, to another.
Commercials UAVs (Drones): Unarmed aircrafts, without a human pilot aboard.
Smart Dust: Low-power computers within a cubic millimeter mote, to allow for an integrated massively distributed sensor network.
5G: The fifth-generation (5G) wireless and mobile communication systems, which uses a much broader spectrum and higher-frequency bands, which allow the support of a much higher data rate up, to several gigabits per second.
Machine Intelligence and Learning: A generic term for the “artificial” generation of knowledge from experience.
Augmented Data Discovery: Tools that allow the user to visualize, analyze and data in the simplest way, without the help of IT or data experts.
Gartner's Hype Cycle: A technology life-cycle model.
Augmented Reality: A technology adding virtual objects, superimposed upon or composited in the real world.
Internet of Things (IoT): A type of network to connect anything with the Internet, based on stipulated protocols, through information sensing equipment, to conduct information exchange and communications, in order to achieve smart recognitions, positioning, tracing, monitoring, and administration.