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The network imperative : how to survive and grow in the age of digital business models
Digital networks are changing all the rules of business. New, scalable, networked business models, like those of Amazon, Google, Uber, and Airbnb, are affecting the growth, scale, and profit potential of companies. But this seismic shift isn't unique to digital start-ups and tech superstars. Digital transformation is impacting all businesses, and as investor capital, top talent, and market buzz continue to shift toward network organizations, the performance gap between fast and slow adopters is widening. So the question isn't whether your organization needs to change, but when and how much. The Network Imperative is a call to action for all leaders to embrace network-based business models. The benefits are indisputable: companies that leverage digital platforms to co-create and share with networks of employees, customers, and suppliers are fast outpacing the market. These companies, or network orchestrators, grow faster, scale with lower marginal cost, and generate the highest revenue multipliers. Based on research of over a thousand companies, Barry Libert, Megan Beck, and Jerry Wind guide leaders and investors through the ten principles that network businesses use to grow and profit. They also share a five-step process for pivoting an organization toward a more scalable and profitable business model. The Network Imperative, brimming with compelling case studies and actionable advice, provides managers with what they really need: new tools and frameworks to thrive in this rapidly changing age.-- Provided by publisher
Book
Practical Industrial Data Communications
The objective of this book is to outline the best practice in designing, installing, commissioning and troubleshooting industrial data communications systems. In any given plant, factory or installation there are a myriad of different industrial communications standards used and the key to successful implementation is the degree to which the entire system integrates and works together.With so many different standards on the market today, the debate is not about what is the best - be it Foundation Fieldbus, Profibus, Devicenet or Industrial Ethernet but rather about selecting the most appropriate technologies and standards for a given application and then ensuring that best practice is followed in designing, installing and commissioning the data communications links to ensure they run fault-free. The industrial data communications systems in your plant underpin your entire operation. It is critical that you apply best practice in designing, installing and fixing any problems that may occur. This book distills all the tips and tricks with the benefit of many years of experience and gives the best proven practices to follow.The main steps in using today's communications technologies involve selecting the correct technology and standards for your plant based on your requirements; doing the design of the overall system; installing the cabling and then commissioning the system. Fiber Optic cabling is generally accepted as the best approach for physical communications but there are obviously areas where you will be forced to use copper wiring and, indeed, wireless communications. This book outlines the critical rules followed in installing the data communications physical transport media and then ensuring that the installation will be trouble-free for years to come.The important point to make is that with today's wide range of protocols available, you only need to know how to select, install and maintain them in the most cost-effective manner for your plant or factory - knowledge of the minute details of the protocols is not necessary. * An engineer's guide to communications systems using fiber optic cabling, copper cabling and wireless technology* Covers: selection of technology and standards - system design - installation of equipment and cabling - commissioning and maintenance* Crammed with practical techniques and know how - written by engineers for engineers
eBook
The evolution of electronic procurement : transforming business as usual
This book responds to the increasing speed with which the domain of electronic procurement has been evolving, as well to the significant advances predicted to take place in the near future. Covering the fundamentals of electronic procurement as well as advanced applications, the main focus is on the critical importance of information technology for modern supply management professionals. Tracing the evolution of electronic procurement over the last 20 years, the book illustrates how the concept has evolved from a novel idea into a standard approach that cannot be neglected, fundamentally transforming business as usual. The transformation is highlighted by the evolution of online reverse auctions, as well as the ensuing expansion of technology to virtually all aspects of strategic sourcing in the form of integrated electronic sourcing suites. Several advances and new applications of electronic procurement are presented, with an emphasis on how social media can be leveraged for supply management and its associated significant potential.
Book
Continuous delivery blueprint : how to implement efficient software change management processes at the enterprise level in the era of clouds, microservices, DevOps, and automation
\"Continuous Delivery Blueprint is a comprehensive guide to building a robust and efficient change management process at scale. It focuses on improving organizational structure, architecture, process, and technology to achieve a fast, high-quality delivery without sacrificing control and transparency. The book describes the executable policy approach to continuous delivery. It shows how new technology advancements in microservices architecture, cloud infrastructure, and intelligent automation can be used to redesign legacy processes and implement change management and security policies in a DevOps way\"--Provided by publisher.
Book
CCNA Security 210-260 Certification Guide
With a CCNA Security certification, you can demonstrate the skills required to develop a security infrastructure, recognize threats to networks, and mitigate security threats. Geared towards Cisco Security, the practical aspects of this book will help you clear the CCNA Security Exam (210-260) by increasing your knowledge of Network Security.
eBook
An artificial intelligence lightweight blockchain security model for security and privacy in IIoT systems
The Industrial Internet of Things (IIoT) promises to deliver innovative business models across multiple domains by providing ubiquitous connectivity, intelligent data, predictive analytics, and decision-making systems for improved market performance. However, traditional IIoT architectures are highly susceptible to many security vulnerabilities and network intrusions, which bring challenges such as lack of privacy, integrity, trust, and centralization. This research aims to implement an Artificial Intelligence-based Lightweight Blockchain Security Model (AILBSM) to ensure privacy and security of IIoT systems. This novel model is meant to address issues that can occur with security and privacy when dealing with Cloud-based IIoT systems that handle data in the Cloud or on the Edge of Networks (on-device). The novel contribution of this paper is that it combines the advantages of both lightweight blockchain and Convivial Optimized Sprinter Neural Network (COSNN) based AI mechanisms with simplified and improved security operations. Here, the significant impact of attacks is reduced by transforming features into encoded data using an Authentic Intrinsic Analysis (AIA) model. Extensive experiments are conducted to validate this system using various attack datasets. In addition, the results of privacy protection and AI mechanisms are evaluated separately and compared using various indicators. By using the proposed AILBSM framework, the execution time is minimized to 0.6 seconds, the overall classification accuracy is improved to 99.8%, and detection performance is increased to 99.7%. Due to the inclusion of auto-encoder based transformation and blockchain authentication, the anomaly detection performance of the proposed model is highly improved, when compared to other techniques.
Journal Article
A graph-based CNN-LSTM stock price prediction algorithm with leading indicators
In today’s society, investment wealth management has become a mainstream of the contemporary era. Investment wealth management refers to the use of funds by investors to arrange funds reasonably, for example, savings, bank financial products, bonds, stocks, commodity spots, real estate, gold, art, and many others. Wealth management tools manage and assign families, individuals, enterprises, and institutions to achieve the purpose of increasing and maintaining value to accelerate asset growth. Among them, in investment and financial management, people’s favorite product of investment often stocks, because the stock market has great advantages and charm, especially compared with other investment methods. More and more scholars have developed methods of prediction from multiple angles for the stock market. According to the feature of financial time series and the task of price prediction, this article proposes a new framework structure to achieve a more accurate prediction of the stock price, which combines Convolution Neural Network (CNN) and Long–Short-Term Memory Neural Network (LSTM). This new method is aptly named stock sequence array convolutional LSTM (SACLSTM). It constructs a sequence array of historical data and its leading indicators (options and futures), and uses the array as the input image of the CNN framework, and extracts certain feature vectors through the convolutional layer and the layer of pooling, and as the input vector of LSTM, and takes ten stocks in U.S.A and Taiwan as the experimental data. Compared with previous methods, the prediction performance of the proposed algorithm in this article leads to better results when compared directly.
Journal Article
Graph convolutional networks: a comprehensive review
Graphs naturally appear in numerous application domains, ranging from social analysis, bioinformatics to computer vision. The unique capability of graphs enables capturing the structural relations among data, and thus allows to harvest more insights compared to analyzing data in isolation. However, it is often very challenging to solve the learning problems on graphs, because (1) many types of data are not originally structured as graphs, such as images and text data, and (2) for graph-structured data, the underlying connectivity patterns are often complex and diverse. On the other hand, the representation learning has achieved great successes in many areas. Thereby, a potential solution is to learn the representation of graphs in a low-dimensional Euclidean space, such that the graph properties can be preserved. Although tremendous efforts have been made to address the graph representation learning problem, many of them still suffer from their shallow learning mechanisms. Deep learning models on graphs (e.g., graph neural networks) have recently emerged in machine learning and other related areas, and demonstrated the superior performance in various problems. In this survey, despite numerous types of graph neural networks, we conduct a comprehensive review specifically on the emerging field of graph convolutional networks, which is one of the most prominent graph deep learning models. First, we group the existing graph convolutional network models into two categories based on the types of convolutions and highlight some graph convolutional network models in details. Then, we categorize different graph convolutional networks according to the areas of their applications. Finally, we present several open challenges in this area and discuss potential directions for future research.
Journal Article
NETWORKS, PLATFORMS, AND STRATEGY: EMERGING VIEWS AND NEXT STEPS
Research summary: A substantial and burgeoning body of research has described the influence of platform-mediated networks in a wide variety of settings, whereby users and complementors desire compatibility on a common platform. In this review, we outline extant views of these dynamics from the industrial organization (IO) economics, technology management, and strategic management perspectives. Using this review as a foundation, we propose a future research agenda in this domain that focuses the on the relative influence of network effects and platform quality in competitive outcomes, drivers of indirect network effects, the nature and attributes of complementors, and leveraging complementor dynamics for competitive advantage. Managerial summary: In many industries, such as social networks and video games, consumers place greater value on products with a large network of other users and a large variety of complementary products. Such \"network effects\" offer lucrative opportunities for firms that can leverage these dynamics to create dominant technology platforms. This article reviews current perspectives on network effects and the emergence of platforms, and offers several areas of future consideration for optimal strategies in these settings.
Journal Article