The aim of this paper is the identification of a superordinate research framework for describing emerging ITinfrastructures within manufacturing, logistics and Supply Chain Management. This is in line with the thoughts and concepts of the Internet of Things (IoT), as well as with accompanying developments, namely the Internet of Services (IoS), Mobile Computing (MC), Big Data Analytics (BD) and Digital Social Networks (DSN). Furthermore, Cyber-Physical Systems (CPS) and their enabling technologies as a fundamental component of all these research streams receive particular attention. Besides of the development of an eponymous research framework, relevant applications against the background of the technological trends as well as potential areas of interest for future research, both raised from the economic practice’s perspective, are identified.
Purpose - The emerging technology of Cyber-Physical Systems (CPS) promises new problem solutions in manufacturing, logistics and SCM. In order to enable a structured scientific discussion, a general definition of such systems is needed.
Design/methodology/approach - To deliver such a definition, scientific articles on the relatively young research field of CPS have been identified and analyzed. Methods like literature review and matrix analysis have been applied during research work.
Findings - On an abstract level, seven basic functions of CPS have been identified. Besides these functions, several phenomenological characteristics emerged as well. Combining the functional and the phenomenological view, a generally applicable definition has been constructed. Some first application examples from logistics, manufacturing and general Supply Chain Management illustrate the definition.
Research limitations/implications - The paper aggregates findings from different research streams. They are application and technology agnostic. It would, in a next step, thus be necessary to identify the specific technologies behind those functions, to describe the state of the art from an application perspective, and to develop a framework for future research.
Practical implications - Considering the great potential of CPS within an operational context, this paper aggregates definitional aspects from a consistent scientific perspective. The processing of the literature on hand addresses a tangible demand for economic practice, which seems to be overwhelmed by the sheer amount of different terms and definitions.
Original/value - The presented study provides strong insights into the emerging subject of CPS gearing towards a prospective research-focus on operational aspects.
Introduction: The knowledge about household properties (such as number of inhabitants, living area, heating type, etc.) is highly desirable for utility companies to pave the way to targeted energy efficiency programs, products and services. Raising individual household data via surveys or purchasing it is expensive and time consuming, and often only a small fraction of customers participate.
Recently, data mining methods have been developed to automatically infer house-hold characteristics from smart meter consumption data. However, the slow smart metering rollout hampers practical implementation of these methods in many countries. In this work, we present a machine learning approach that reveals household properties from conventional annual electricity consumption data currently available at a large scale.
In this research study we investigate whether and how ERP system characteristics cause its users to experience stress. In order to do so, we analyze a research model explaining enterprise resource planning systems induced stress with an empirical study in two organizations (N=227). The results reveal that usefulness, complexity, reliability, and pace of change are important ERP system characteristics leading to the perception of stressors and exhaustion. Furthermore, our comparative empirical analysis with young and elderly ERP users indicate that the elderly ones perceive ERP characteristics more negatively and are more stressed and exhausted than the younger users.
Despite the wide dissemination and acceptance of teleworking, there are negative effects for employees. Literature shows that these negative effects of telework lead to undesired outcomes for teleworkers such as telework-exhaustion. The present research, however, goes one step further by identifying three significant telework-characteristics and hypothesizing the relationship between telework-characteristics and telework-enabled stressors. By doing so, one can understand the reason why telework-enabled stressors are perceived and identify the source of these stressors, which can then be counteracted to maintain the advantages of teleworking. Therefore, this research investigates the influence of the following telework-characteristics - information undersupply, autonomy, and isolation - on telework-enabled stressors and accordingly on telework-exhaustion and on the intention to continue teleworking. Results of an analysis on 310 teleworkers show that telework-characteristics influence telework-enabled stressors and accordingly increase the extent of telework-exhaustion and decrease the intention to continue teleworking.
The term NeuroIS appears more frequently within the field of information system (IS). NeuroIS describes the idea of applying cognitive neuroscience theories, methods, and tools to obtain physiological responses of the user while using IS. However, before adopting these methods into IS research, a proper assessment is necessary to determine whether the methods used in other disciplines are also applicable to IS research. The present research introduces the method of measuring the electrodermal activity (EDA). Thereby, the physiology and different measurement parameters are described. By identifying the use of EDA within other disciplines, the present research reveals application areas for EDA in six different research streams in IS research and poses further research questions, which might be answer by applying EDA in these areas.