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Towards Global Localization (Routledge Library Editions: Economic Geography)
This volume redefines the genre of sector studies. The first part of the book compares the experiences of Britain and France in the very voltaile world of high-tech industries during the 1980s. The macroeconomic regulation approach is carried over a microeconomic level in the empirical chapters through an analysis of studies of firms, each chapter written by authors well-placed to give a pan-European perspective.
‘(The authors) research a contemporary complex of themes with admirable theoretical and empirical depth and make a valubale contribution to industrial geography.’ Erdkunde
‘Essential reading for social scientists concerned for how high-tech industry is leading our world towards ever-increasing globalization.’ Environment and Planning
1. Computing and Communications in the UK and France: Innovation, Regulation and Spatial Dynamics – An Introduction Philip Cooke 2. High Technology and Flexibility Olivier Weinstein 3. Accumulation and Organization in Computing and Communications Industries: A Regulationist Approach Frank Moulaert & Erik Swyngedouw 4. Globalization and Its Management in Computing and Communications Philip Cooke and Peter Wells 5. The Regional Patterns of Computing and Communications Industries in the UK and France Erik Swyngedouw, Martine Lemattre, Peter Wells 6. The Computer Hardware Industry in the 1980s: Technological Change, Competition and Structural Change Peter Wells & Philip Cooke 7. The Telecommunications Equipment Industry: The Great Transformation Olivier Weinstein 8. Services: The Bridge Between Computing and Communications Frank Moulaert 9. Global Localization in Computing and Communications: Conclusions Philip Cooke
eBook
Towards Global Localization
This volume redefines the genre of sector studies. The first part of the book compares the experiences of Britain and France in the very voltaile world of high-tech industries during the 1980s. The macroeconomic regulation approach is carried over a microeconomic level in the empirical chapters through an analysis of studies of firms, each chapter written by authors well-placed to give a pan-European perspective.
eBook
The Role of Push-Pull Technology in Privacy Calculus: The Case of Location-Based Services
Location-based services (LBS) use positioning technologies to provide individual users with reachability and accessibility that would otherwise not be available in the conventional commercial realm. While LBS confer greater connectivity and personalization on consumers, they also threaten users' information privacy through granular tracking of their preferences, behaviors, and identity. To address privacy concerns in the LBS context, this study extends the privacy calculus model to explore the role of information delivery mechanisms (pull and push) in the efficacy of three privacy intervention approaches (compensation, industry self-regulation, and government regulation) in influencing individual privacy decision making. The research model was tested using data gathered from 528 respondents through a quasi-experimental survey method. Structural equations modeling using partial least squares validated the instrument and the proposed model. Results suggest that the effects of the three privacy intervention approaches on an individual's privacy calculus vary based on the type of information delivery mechanism (pull and push). Results suggest that providing financial compensation for push-based LBS is more important than it is for pull-based LBS. Moreover, this study shows that privacy advocates and government legislators should not treat all types of LBS as undifferentiated but could instead specifically target certain types of services.
Journal Article
GBH-YOLOv5: Ghost Convolution with BottleneckCSP and Tiny Target Prediction Head Incorporating YOLOv5 for PV Panel Defect Detection
Photovoltaic (PV) panel surface-defect detection technology is crucial for the PV industry to perform smart maintenance. Using computer vision technology to detect PV panel surface defects can ensure better accuracy while reducing the workload of traditional worker field inspections. However, multiple tiny defects on the PV panel surface and the high similarity between different defects make it challenging to accurately identify and detect such defects. This paper proposes an approach named Ghost convolution with BottleneckCSP and a tiny target prediction head incorporating YOLOv5 (GBH-YOLOv5) for PV panel defect detection. To ensure better accuracy on multiscale targets, the BottleneckCSP module is introduced to add a prediction head for tiny target detection to alleviate tiny defect misses, using Ghost convolution to improve the model inference speed and reduce the number of parameters. First, the original image is compressed and cropped to enlarge the defect size physically. Then, the processed images are input into GBH-YOLOv5, and the depth features are extracted through network processing based on Ghost convolution, the application of the BottleneckCSP module, and the prediction head of tiny targets. Finally, the extracted features are classified by a Feature Pyramid Network (FPN) and a Path Aggregation Network (PAN) structure. Meanwhile, we compare our method with state-of-the-art methods to verify the effectiveness of the proposed method. The proposed PV panel surface-defect detection network improves the mAP performance by at least 27.8%.
Journal Article
Neighbourhood effects on firm success and strategy
Neighbourhood Effects on Firm Success and Strategy As a result of economic transitions and several societal developments over the past 50 years, residential neighbourhoods have developed from being places where people predominantly live into places where people also work. A growing number of small- and medium-sized firms are located in residential neighbourhoods, many of which are home-based. Triggered by relatively high levels of turbulence in residential neighbourhoods and inter-locality variation in firm survival, firm growth and firm relocation, this study concerned whether and how neighbourhood characteristics influence the success of local firms and the strategic options of their entrepreneurs. The research demonstrates that some ‘neighbourhood effects’ on firm success and strategy do exist, especially for the growing group of solo entrepreneurs and firms in locally-oriented sectors. In particular the social context in which entrepreneurs are embedded matters, as cohesive neighbourhoods trigger both firm growth and entrepreneurial investments. Furthermore, the accumulation of liveability-related problems in disadvantaged neighbourhoods seems to contribute to an unfavourable business climate.
eBook
Mining co-location patterns of manufacturing firms using Q statistic and additive color mixing
The agglomeration effect significantly influences firms’ site selection. Manufacturing firms often exhibit intricate spatial co-location patterns that are indicative of agglomerations due to their reliance on material input and product output across various subdivisions of manufacture. In this study, we present an analytical approach employing the Q statistic and additive color mixing visualization to assess co-location patterns of manufacturing firms. We identified frequent pairs and triplets of manufacturing divisions, mapping them to reveal distinct categories: labor-intensive clusters, upstream/downstream industrial chains, and technology-spillover clusters. These agglomeration categories concentrate in different regions of the city. Policy implications are proposed to promote the upgrade of labor-intensive divisions, enhance the operational efficiency of upstream/downstream industrial chains, and reinforce the spillover effects of technology-intensive divisions.
Journal Article
Spatial cloaking for anonymous location-based services in mobile peer-to-peer environments
This paper tackles a privacy breach in current location-based services (LBS) where mobile users have to report their exact location information to an LBS provider in order to obtain their desired services. For example, a user who wants to issue a query asking about her nearest gas station has to report her exact location to an LBS provider. However, many recent research efforts have indicated that revealing private location information to potentially untrusted LBS providers may lead to major privacy breaches. To preserve user location privacy, spatial cloaking is the most commonly used privacy-enhancing technique in LBS. The basic idea of the spatial cloaking technique is to blur a user’s exact location into a cloaked area that satisfies the user specified privacy requirements. Unfortunately, existing spatial cloaking algorithms designed for LBS rely on fixed communication infrastructure, e.g., base stations, and centralized/distributed servers. Thus, these algorithms cannot be applied to a mobile peer-to-peer (P2P) environment where mobile users can only communicate with other peers through P2P multi-hop routing without any support of fixed communication infrastructure or servers. In this paper, we propose a spatial cloaking algorithm for mobile P2P environments. As mobile P2P environments have many unique limitations, e.g., user mobility, limited transmission range, multi-hop communication, scarce communication resources, and network partitions, we propose three key features to enhance our algorithm: (1) An
information sharing scheme
enables mobile users to share their gathered peer location information to reduce communication overhead; (2) A
historical location scheme
allows mobile users to utilize stale peer location information to overcome the network partition problem; and (3) A
cloaked area adjustment scheme
guarantees that our spatial cloaking algorithm is free from a “center-of-cloaked-area” privacy attack. Experimental results show that our P2P spatial cloaking algorithm is scalable while guaranteeing the user’s location privacy protection.
Journal Article
An Overview of Privacy Dimensions on the Industrial Internet of Things (IIoT)
The rapid advancements in technology have given rise to groundbreaking solutions and practical applications in the field of the Industrial Internet of Things (IIoT). These advancements have had a profound impact on the structures of numerous industrial organizations. The IIoT, a seamless integration of the physical and digital realms with minimal human intervention, has ushered in radical changes in the economy and modern business practices. At the heart of the IIoT lies its ability to gather and analyze vast volumes of data, which is then harnessed by artificial intelligence systems to perform intelligent tasks such as optimizing networked units’ performance, identifying and correcting errors, and implementing proactive maintenance measures. However, implementing IIoT systems is fraught with difficulties, notably in terms of security and privacy. IIoT implementations are susceptible to sophisticated security attacks at various levels of networking and communication architecture. The complex and often heterogeneous nature of these systems makes it difficult to ensure availability, confidentiality, and integrity, raising concerns about mistrust in network operations, privacy breaches, and potential loss of critical, personal, and sensitive information of the network's end-users. To address these issues, this study aims to investigate the privacy requirements of an IIoT ecosystem as outlined by industry standards. It provides a comprehensive overview of the IIoT, its advantages, disadvantages, challenges, and the imperative need for industrial privacy. The research methodology encompasses a thorough literature review to gather existing knowledge and insights on the subject. Additionally, it explores how the IIoT is transforming the manufacturing industry and enhancing industrial processes, incorporating case studies and real-world examples to illustrate its practical applications and impact. Also, the research endeavors to offer actionable recommendations on implementing privacy-enhancing measures and establishing a secure IIoT ecosystem.
Journal Article
From Silicon Valley to Shenzhen
This seminal study explores the significant changes in the global IT industry as production has shifted from the developed world to massive sites in the developing world that house hundreds of thousands of workers in appalling low-wage conditions to minimize labor costs. Yet little is known about this phenomenon as the major contract manufacturers deliberately hide their names from the public on behalf of brand-name customers such as Apple. In short, the authors argue, globalization is not always helping the IT workers of the world, many of whom are working in unbearable factory conditions. From Silicon Valley to Shenzhen traces the development of the new networks of globalized mass production in the IT industry and the reorganization of work since the 1990s, capturing the systemic nature of an industry-wide restructuring of production and work in the global context. Their wide-ranging and detailed analysis makes an important contribution to ongoing academic and political debates on the globalization of production, especially by taking these debates beyond narrow perspectives of determining criteria of “success” for participation in global production networks. Rather, they emphasize the changing nature of work, employment relations, and labor policies and their implications for the possibilities of sustainable economic and social development.
eBook