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Converting users into customers : the role of user profile information and customer journey analysis
(2016)
Due to the digital transformation, the importance of web analysis and user profiling for enterprises is increasing rapidly as customers focus on digital channels to obtain information about products and brands. While there exists a lot research on these topics, only a minority of firms use them to their advantage. This study aims to tighten the link between research and business such that experimental methods can be used for the improvement of communication strategies in practice. Therefore, a systematic literature analysis is conducted, workshops are observed and documented and an empirical study is used to integrate single steps into a framework for the
practical usage of user profiling and customer journey analysis.
The Internet of Things (IoT) refers to the interconnectedness of physical objects, and works by equipping the latter with sensors and actuators as a means to connect to the internet. The number of connected things has increased threefold over the past five years. Consequently, firms expect the IoT to become a source of new business models driven by technology. However, only a few early adopters have started to install and use IoT appliances on a frequent basis. So it is still unclear which factors drive technological acceptance of IoT appliances. Confronting this gap in current research, the present paper explores how IoT appliances are conceptually defined, which factors drive technological acceptance of IoT appliances, and how firms can use results in order to improve value propositions in corresponding business models. lt is discovered that IoT appliance vendors need to support a broad focus as the potential buyers expose a large variety. As conclusions from this insight, the paper illustrates some flexible marketing strategies.
The question of why individuals adopt information technology has been present in the information systems research since the past quarter century. One of the most used models for predicting the technology usage was introduced by Fred David: The Technology Acceptance Model (TAM). It describes the influence of perceived usefulness and perceived ease of use on attitude, behavioral intention and system usage. The first two mentioned factors in turn are influenced by external variables. Although a plethora of papers exists about the TAM , an extensive analysis of the role of the external variables in the model is still missing. This paper aims to give an overview ove the most important variables. In an extensive literature review, we identified 763 relevant papers, found 552 unique single extenal variables, characterized the most important of them, and described the frequency of their appearance. Additionally, we grouped these variables into four categories (organizational characteristis, system characteristics, user personal characteristics, and other variables). Afterwards we discuss the results and show implications for theory and practice.