Key Concepts in E-commerce: Digital Markets and Digital Goods in a Global Marketplace

The location, timing, and revenue models of business are based in some part on the cost and distribution of information. The Internet has created a digital marketplace where millions of people all over the world can exchange massive amounts of information directly, instantly, and free. As a result, the Internet has changed the way

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Types of E-commerce

There are many ways to classify electronic commerce transactions—one is by looking at the nature of the participants. The three major electronic commerce categories are business-to-consumer (B2C) e-commerce, business-to-business (B2B) e-commerce, and consumer-to-consumer (C2C) e-commerce. Business-to-consumer (B2C) electronic commerce involves retailing prod­ucts and services to individual shoppers. Amazon, Walmart, and iTOnes are examples of

E-commerce Business Models

Changes in the economics of information described earlier have created the conditions for entirely new business models to appear while destroying older business models. Table 10.5 describes some of the most important Internet busi­ness models that have emerged. All, in one way or another, use the Internet (including apps on mobile devices) to add

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Uber: Digital Disruptor

You’re in New York, Paris, Chicago, or another major city and need a ride. Instead of trying to hail a cab, you pull out your smartphone and tap the Uber app. A Google map pops up displaying your nearby sur­roundings. You select a spot on the screen designat­ing an available driver, and the app

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E-commerce Revenue Models

A firm’s revenue model describes how the firm will earn revenue, gener­ate profits, and produce a superior return on investment. Although many e-commerce revenue models have been developed, most companies rely on one, or some combination, of the following six revenue models: advertising, sales, subscription, free/freemium, transaction fee, and affiliate. 1. Advertising Revenue Model

Behavioral Targeting

Many e-commerce marketing firms use behavioral targeting techniques to increase the effectiveness of banners, rich media, and video ads. Behavioral targeting refers to tracking the clickstreams (history of clicking behavior) of in­dividuals on thousands of websites to understand their interests and intentions and expose them to advertisements that are uniquely suited to their online

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Social E-commerce and Social Network Marketing

In 2019, one of the fastest-growing media for branding and marketing is social media. Companies will spend an estimated $30 billion in 2019 using social networks such as Facebook, Instagram, Twitter, and LinkedIn to reach mil­lions of consumers who spend hours a day on social sites. Expenditures for social media marketing are much smaller

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“Socializing” with Customers

More than 3 billion people worldwide use social media, making it an obvious platform for companies seeking to engage consumers, amplify product mes­sages, discover trends and influencers, build brand awareness, and take action on customer requests and recommendations. More than 80 million busi­nesses have Facebook brand pages, enabling users to interact with the brand

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How has e-commerce affected business-to-business transactions?

Trade between business firms (business-to-business commerce, or B2B) repre­sents a huge marketplace. The total amount of B2B trade in the United States in 2019 is estimated to be about $13.5 trillion, with B2B e-commerce (online B2B) contributing about $6.2 trillion of that amount (U.S. Bureau of the Census, 2018; authors’ estimates). By 2020, B2B

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What is the role of m-commerce in business, and what are the most important m-commerce applications?

Walk down the street in any major metropolitan area and count how many people are pecking away at their iPhones, Samsungs, or BlackBerrys. Ride the trains or fly the planes, and you’ll see fellow travelers reading an online news­paper, watching a video on their phone, or reading a novel on their Kindle. As the

What issues must be addressed when building an e-commerce presence?

Building a successful e-commerce presence requires a keen understanding of business, technology, and social issues as well as a systematic approach. Today, an e-commerce presence is not just a corporate website but also includes a social network site on Facebook, a Twitter feed, and smartphone apps where customers can access your services. Developing and

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What is the role of knowledge management systems in business?

Knowledge management and collaboration systems are among the fastest- growing areas of corporate and government software investment. The past decade has shown an explosive growth in research on knowledge and knowl­edge management in the economics, management, and information systems fields. Knowledge management and collaboration are closely related. Knowledge that cannot be communicated and shared

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Evolution of AI

In the last decade, significant progress has been made within this limited vision of AI. The major forces driving the rapid evolution of AI are the development of Big Data databases generated by the Internet, e-commerce, the Internet of Things, and social media. Secondary drivers include the drastic reduction in the cost of computer

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Major Types of AI

Artificial intelligence is a family of programming techniques and technologies, each of which has advantages in select applications. Table 11.2 describes the major types of AI: expert systems, machine learning, neural networks, deep learning, genetic algorithms, natural language processing, computer vision sys­tems, robotics, and intelligent agents. Let’s take a look at each type of

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Expert Systems

Expert systems were developed in the 1970s and were the first large-scale applications of AI in business and other organizations. They account for an es­timated 20 percent of all AI systems today. Expert systems capture the knowl­edge of individual experts in an organization through in-depth interviews, and represent that knowledge as sets of rules.

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Machine Learning

More than 75 percent of AI development today involves some kind of machine learning (ML) accomplished by neural networks, genetic algorithms, and deep learning networks, with the main focus on finding patterns in data, and classifying data inputs into known (and unknown) outputs. Machine learning is based on an entirely different AI paradigm than

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Neural Networks

A neural network is composed of interconnected units called neurons. Each neuron can take data from other neurons, and transfer data to other neurons in the system. The artificial neurons are not biological physical entities as in the human brain, but instead are software programs and mathematical models that perform the input and output

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Genetic Algorithms

Genetic algorithms are another form of machine learning. Genetic algorithms are useful for finding the optimal solution for a specific problem by examining a very large number of alternative solutions for that problem. Their method of solving problems is based on ideas inspired by evolutionary biology such as inheritance, mutation, selection, and crossover (recombination).

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Natural Language Processing, Computer Vision Systems, and Robotics

Other important AI techniques include natural language processing, computer vision systems, and robotics. 1. Natural Language Processing Human language is not always precise. It is often ambiguous, and meanings of words can depend on complex variables such as slang, regional dialects, and so­cial context. Natural language processing (NLP) makes it possible for a com­puter

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Intelligent Agents

Intelligent agents are software programs that work in the background without direct human intervention to carry out specific tasks for an individual user, business process, or software application. The agent uses a limited built-in or learned knowledge base to accomplish tasks or make decisions on the user’s behalf, such as deleting junk email, scheduling