Regulating Data as Property: A New Construct for Moving Forward

The global community urgently needs precise, clear rules that define ownership of data and express the attendant rights to license, transfer, use, modify, and destroy digital information assets. In response, this article proposes a new approach for regulating data as an entirely new class of property. Recently, European and Asian public officials and industries have called for data ownership principles to be developed, above and beyond current privacy and data protection laws. In addition, official policy guidances and legal proposals have been published that offer to accelerate realization of a property rights structure for digital information. But how can ownership of digital information be achieved? How can those rights be transferred and enforced? Those calls for data ownership emphasize the impact of ownership on the automotive industry and the vast quantities of operational data which smart automobiles and self-driving vehicles will produce. We looked at how, if at all, the issue was being considered in consumer-facing statements addressing the data being collected by their vehicles. To formulate our proposal, we also considered continued advances in scientific research, quantum mechanics, and quantum computing which confirm that information in any digital or electronic medium is, and always has been, physical, tangible matter. Yet, to date, data regulation has sought to adapt legal constructs for “intangible” intellectual property or to express a series of permissions and constraints tied to specific classifications of data (such as personally identifiable information). We examined legal reforms that were recently approved by the United Nations Commission on International Trade Law to enable transactions involving electronic transferable records, as well as prior reforms adopted in the United States Uniform Commercial Code and Federal law to enable similar transactions involving digital records that were, historically, physical assets (such as promissory notes or chattel paper). Finally, we surveyed prior academic scholarship in the U.S. and Europe to determine if the physical attributes of digital data had been previously considered in the vigorous debates on how to regulate personal information or the extent, if at all, that the solutions developed for transferable records had been considered for larger classes of digital assets. Based on the preceding, we propose that regulation of digital information assets, and clear concepts of ownership, can be built on existing legal constructs that have enabled electronic commercial practices. We propose a property rules construct that clearly defines a right to own digital information arises upon creation (whether by keystroke or machine), and suggest when and how that right attaches to specific data though the exercise of technological controls. This construct will enable faster, better adaptations of new rules for the ever-evolving portfolio of data assets being created around the world. This approach will also create more predictable, scalable, and extensible mechanisms for regulating data and is consistent with, and may improve the exercise and enforcement of, rights regarding personal information. We conclude by highlighting existing technologies and their potential to support this construct and begin an inventory of the steps necessary to further proceed with this process

LICSTER -- A Low-cost ICS Security Testbed for Education and Research

Unnoticed by most people, Industrial Control Systems (ICSs) control entire productions and critical infrastructures such as water distribution, smart grid and automotive manufacturing. Due to the ongoing digitalization, these systems are becoming more and more connected in order to enable remote control and monitoring. However, this shift bears significant risks, namely a larger attack surface, which can be exploited by attackers. In order to make these systems more secure, it takes research, which is, however, difficult to conduct on productive systems, since these often have to operate twenty-four-seven. Testbeds are mostly very expensive or based on simulation with no real-world physical process. In this paper, we introduce LICSTER, an open-source low-cost ICS testbed, which enables researchers and students to get hands-on experience with industrial security for about 500 Euro. We provide all necessary material to quickly start ICS hacking, with the focus on low-cost and open-source for education and research

Automation, Digitalization, and Changes in Occupational Structures in the Automobile Industry in Germany, the United States, and Japan: A Brief History from the Early 1990s Until 2018

In the current public discussion, it is considered certain that we are living in a time of rapidly advancing automation, which is driven in particular by the use of robots. Accordingly, many academic publications use robot density as the central indicator of automation. The present study challenges this perspective. It examines two central questions: First, what approaches to automation and digitalization have been pursued in the automotive industry in Germany, Japan and the USA? Second, how have employment and its occupational composition in the automotive industry developed in the three countries? The first part of the study focuses on the development of automation and digitalization approaches in the automotive industry from the early 1990s until today. It combines a qualitative analysis of press articles and a quantitative evaluation of the development of the stock of industrial robots from 1993 to 2018 based on the statistics of the International Federation of Robotics. The second part of the study focuses on the change in employment structures using occupational statistics from the Bureau of Labor Statistics (USA), the Federal Employment Agency (Germany) and the Statistics Bureau of Japan. The study questions the perception of an automation-related threat to employment and especially to production employment. At the same time, it discusses developments in Germany, Japan and the USA in comparison and highlights differences in automation and digitalization approaches as well as different paths of change in employment structures

Contextual impacts on industrial processes brought by the digital transformation of manufacturing: a systematic review

The digital transformation of manufacturing (a phenomenon also known as "Industry 4.0" or "Smart Manufacturing") is finding a growing interest both at practitioner and academic levels, but is still in its infancy and needs deeper investigation. Even though current and potential advantages of digital manufacturing are remarkable, in terms of improved efficiency, sustainability, customization, and flexibility, only a limited number of companies has already developed ad hoc strategies necessary to achieve a superior performance. Through a systematic review, this study aims at assessing the current state of the art of the academic literature regarding the paradigm shift occurring in the manufacturing settings, in order to provide definitions as well as point out recurring patterns and gaps to be addressed by future research. For the literature search, the most representative keywords, strict criteria, and classification schemes based on authoritative reference studies were used. The final sample of 156 primary publications was analyzed through a systematic coding process to identify theoretical and methodological approaches, together with other significant elements. This analysis allowed a mapping of the literature based on clusters of critical themes to synthesize the developments of different research streams and provide the most representative picture of its current state. Research areas, insights, and gaps resulting from this analysis contributed to create a schematic research agenda, which clearly indicates the space for future evolutions of the state of knowledge in this field

Role of digitalization of logistics outsourcing in sustainable development of automotive industry in China

Relevance. Digital technologies can bring regional logistics outsourcing in the automotive industry to a new level of performance. However, the digitalization of logistics outsourcing and its role in improving the sustainability of the automotive industry are poorly understood.Research objective. To develop the conceptual framework of the digital ecosystem of regional logistics outsourcing in the automotive industry. The object of the study is the automotive industry in China.Data and methods. Prospects for the digitalization of regional logistics outsourcing of the automotive industry and its impact on the sustainability of the industry are considered in terms of the economics of transaction costs and a resource-based approach. The data sources involved the national policy documents reflecting the strategic directions of digital development of China, statistical data provided by the National Bureau of Statistics of China, as well as research papers presented in the Scopus database.Results. The authors analyzed the trends of digital transformations in the geographic clusters of production of the automotive industry in China. The digitalization of regional logistics outsourcing was determined to influence the sustainability of the automotive industry development in the context of its economic, social, environmental and technological components. The logistics ecosystem model developed by Capgemini was supplemented by the conceptual framework of the digital logistics outsourcing ecosystem for the Chinese automotive industry. The key components of this framework were determined.Conclusions. It can be concluded that digitalization of regional logistics outsourcing will contribute to increasing the sustainability of the automotive industry. However, this requires the formation of a digital landscape of logistics outsourcing, which involves changes in the entire supply chain management system. The results of the study can be used to improve the efficiency of supply chain management in the automotive industry

Digitalization and IT Backsourcing: Towards a Transformational Model for the German Automobile Industry

Many organisations are now confronted with the new phenomenon of digitalization and are faced with the challenge of formulating and implementing a company-wide digital transformation strategy. Digitalization is associated with significant and extremely rapid change, and, in some cases, even the replacement of established business models. In manufacturing companies, this transformation is part of what is often termed Industry 4.0 and, in large companies, where the provision of information technology (IT) has hitherto been outsourced (in whole or in part), the introduction of these new technologies may be the catalyst for IT backsourcing. This entails bringing previously outsourced activities back in-house to regain ownership and control, in order to be more flexible and respond more effectively to rapidly changing demands. This study reviews the extant literature to assess existing thinking on the motivation for backsourcing, and then examines the potential role of digitalization in driving IT backsourcing in the German automotive industry. A provisional conceptual framework for subsequent research is put forward, using a knowledge-based view of the firm. The study is in its initial stages, but the model is being developed through more in-depth interviews to provide operational guidance for practitioners and subsequent research studies

The interplay between data-driven decision-making and digitalization: A firm-level survey of the Italian and U.S. automotive industries

With the diffusion of information systems and new technologies for the real-time capturing of data, especially in rapid technological and managerial innovation contexts such as the automotive industry, data-driven decision-making (DDM) has now the potential to generate dramatic improvements in the performance of manufacturing firms. However, there is still a lack of evidence in literature on whether these technologies can actually enhance the effectiveness of data-driven approaches. The aim of this article is to investigate the impact of DDM on operational performance moderated by two main dimensions of digitalization: data integration and the breadth of new digitization technologies. The results of a cross-country survey of 138 Italian and U.S. auto-supplier firms, which was supported by plant visits and interviews, suggest that an interplay between DDM and the two dimensions exists. Higher degrees of data integration in information systems increase the positive effect of DDM on the probability of cost reductions. On the other hand, introducing multiple emerging digitization technologies leads to worse DDM results, in terms of cost performance. The conclusion that can be drawn is that the operational employees of auto-supplier firms are now facing difficulties in successfully combining real-time operational data from various sources and in exploiting them for decision-making. Managers and workers need to align their intuition, experience and analytical capabilities to initiate the digitalization process. The challenge, in the medium term, is to limit the difficulties of implementing new digitization technologies and integrating their data, to embrace DDM and fully grasp the potential of data analytics in operations

Automatic assessment of the ergonomic risk for manual manufacturing and assembly activities through optical motion capture technology

Abstract Safeguard the operator health is nowadays a hot topic for most of the companies whose production process relies on manual manufacturing and assembly activities. European legislations, national regulations and international standards force the companies to assess the risk of musculoskeletal disorders of operators while they are performing manual tasks. Furthermore, international corporates typically require their partners to adopt and implement particular indices and procedures to assess the ergonomic risks specific of their industrial sector. The expertise and time required by the ergonomic assessment activity compels the companies to huge financial, human and technological investments. An original Motion Analysis System (MAS) is developed to facilitate the evaluation of most of the ergonomic indices traditionally adopted by manufacturing firms. The MAS exploits a network of marker-less depth cameras to track and record the operator movements and postures during the performed tasks. The big volume of data provided by this motion capture technology is employed by the MAS to automatically and quantitatively assesses the risk of musculoskeletal disorders over the entire task duration and for each body part. The developed hardware/software architecture is tested and validated with a real industrial case study of a car manufacturer which adopts the European Assembly Worksheet (EAWS) to assess the ergonomic risk of its assembly line operators. The results suggest how the MAS is a powerful architecture compared to other motion capture solutions. Indeed, this technology accurately assesses the operator movements and his joint absolute position in the assembly station 3D layout. Finally, the MAS automatically and quantitatively fill out the different EAWS sections, traditionally evaluated through time- and resource-consuming activities