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The first (or "Great") Industrial Revolution occurred in Europe from roughly 1760 to 1860, and marked the end of the centuries-long feudal era and the rise of modern capitalism. To understand the modern industrial economy, it is necessary to consider the profound structural changes that produced it in the 18th and 19th centuries. New industries replaced old systems or businesses with new technologies, products, markets, and business practices, resulting in dramatic changes in economic growth (a measure of material well-being), politics (new institutions, interests, and ideologies), and society (such as urbanization, changes in social mobility, and immigration). Anchored to the rationalist principles of the Enlightenment, the Industrial Revolution emphasized increased productivity across sectors, from agricultural labor to factory production. The Industrial Revolution encompassed and relied on dramatic changes to organizational management, capital structures, resource procurement, and political institutions, marking a culmination of societal transformation that manifested in an explosion of economic development. The word "revolution" suggests a period of radical change, a shift from an old order to a completely new one: the Industrial Revolution was such a shift. This note offers a historical overview of this hugely consequential period in economic history.

This is the course overview note for "The Entrepreneurial Manager," taught in the first year at Harvard Business School. Students will learn how to be opportunity-driven managers and how to lead under uncertainty. They'll learn how to identify opportunities, how to design and develop integrated operating models to pursue those opportunities, how to resource those activities amidst uncertainty, and, ultimately, how (and if) to scale them. The note covers the motivation for the course, historical and contemporary, and the course structure.

Among the many competing definitions of entrepreneurship, the one adopted in The Entrepreneurial Manager at HBS was authored by Howard Stevenson in the 1980s and elaborated on in the decades since. Stevenson provided a managerial take on the term; he described entrepreneurship as a distinct approach to management. That approach is the subject of this brief note. The note provides his definition of entrepreneurship ("the pursuit of opportunity without regard to resources currently controlled") and six domains that differentiate entrepreneurial managers from administrative managers.

The searchable internet contains almost 2 billion websites. And new, text-rich sites are being added at a rapid pace: more than 700 million popped up from 2016 to 2017, according to the International Real Time Statistics Project. A lot of this web-based text is relevant to marketers: online product reviews, information about purchasing behavior, customer-to-customer interactions, and transcribed tele-sales calls. Marketers now have more information from consumers in the form of written words than ever before. The problem, as with any extremely large data set, is determining how best to use the information. The relatively new fields of text analytics and sentiment analysis offer marketers a solution, enabling them to turn vast amounts of emotion-rich, word-based data into actionable information about consumers. This note explores dictionary-based sentiment analysis using programming language R; it also introduces empirical sentiment analysis.

Managers need to be comfortable with financial statement forecasting. Forecasts allow managers to plan properly by weighing consequences and preparing for outcomes. A less-recognized but equally important benefit is that the act of forecasting forces managers to make explicit the many links that exist between decisions, possibly drawing attention to constraints that otherwise might have been overlooked. This is particularly important since financial statements integrate the financial and operating decisions of a firm. This note focuses on forecasting in the context of decision-making. Aspects of forecasting explored include: revenue growth estimates, sources of error, assumptions, typical ratios, and the T-account approach. It also includes a detailed example of a typical financial forecast. The concepts are applied to the hypothetical firm Morgan Industries, a setting that has been integrated across all the Financial Analytics Toolkit series of technical notes. While this note focuses on financial statements, the forecasting techniques described herein are readily transferred to related contexts, such as building cash-flow forecasts and using ratios to evaluate financial performance.

Iconoclasts with strongly held beliefs and a willingness to buck orthodoxy, Apple's Steve Jobs and the Chicago Bulls' Phil Jackson shared similarities in character, leadership style, and life experience that extended beyond the extraordinary successes they achieved in their chosen fields. Both came of age in the United States of the mid-20th century, a time and place characterized by Americans' growing interest in philosophical traditions outside of the Western mainstream. In their teens and twenties, both men became interested in Eastern religious practices. As young men, Jobs (who would as a teenager travel to India to study Buddhism) and Jackson (whose interest in Eastern practices earned him the nickname "The Zen Master") developed a particular affinity for the Zen tradition of Buddhism, which had a lasting influence on each man's worldview. Although Jackson and Jobs were very different leaders operating in remarkably different industries, both men's rise to the top of intensively competitive fields were influenced by their commitment to three Zen principles: nondualism, practical wisdom, and inherent enlightenment. This note gives a brief overview of the history of Zen and the philosophical framework that underpins it, then describes the potential that these three tenets hold for unlocking strategic insights.

Market lore recounts a host of fabled asset price bubbles: the Dutch tulip bubble of the 1630s, the South Sea and Mississippi bubbles of 1720, the dot-com bubble of the late 1990s, and the global real estate bubble of the mid-2000s. One survey reported the occurrence of some 60 bubbles since the 17th century. Despite their apparent prevalence, asset price bubbles are a challenging theoretical and empirical concept. The aims of this note are to: explore the concept of an asset price bubble; consider some tell-tale signs of a bubble from the standpoints of economic theory, empirical research, and market lore; survey evidence about the existence of bubbles; summarize theories about the causes of bubbles-especially the apparent irrationality of bubbles and the behavior of rational sophisticated investors in buying into them; and finally, highlight some of the regulatory dilemmas that bubbles present. Although the existence of the occasional asset price bubble may seem obvious to the casual observer, this note explains why bubbles are hard to identify and challenging to trade upon.

Debates on issues about the economy, growth, inequality, fiscal responsibility, and financial crises frequently reduce to debates about money. Moreover, debates about money often reduce to the soundness of money, meaning the ability of a unit of currency to retain its value. Eventually, discussions about soundness touch on the classic era of the gold standard. The aims of this note are to (1) describe the mechanism of the international monetary system known as the gold standard during the time that it had the greatest influence on the global economy; (2) place the gold standard in context with other systems that preceded and followed it; and (3) dispel some enduring misconceptions.

For more than two decades, scientific advances have been driving profound changes in drug discovery and the drug industry itself. This case provides an overview and description of these technical and scientific advances. Written for the nonscientific reader, it may be used as companion reading for other case materials that require basic knowledge of the tools, techniques, and approaches used in the pharmaceutical and biotechnology industries.

This note provides essential information on funding sources and valuation topics facing deep technology startups-ventures that are capital-intensive, with high technical and market uncertainty, and require long gestation periods. Both dilutive and non-dilutive sources of investment are described, along with empirical examples and figures.

This note focuses on the development of the drone industry in recent years and provides insights on the drone technology, regulations, applications, market size, top players, and ecosystem. This note was written in conjunction with the case study "Parrot: Navigating the Nascent Drone Industry" (HBS No. 619-085).

Driven largely by advances in perception and situational awareness, robots in the 2010s were gaining functionality that allowed them to be applied to fundamentally new types of work. The expanding range of new types of tasks that could be completed by machines had significant implications for businesses, the workforce, and society. This primer grounds conversations about these implications by illustrating real-world examples of the new types of activities that robots were becoming able to perform. It describes the functionality limitations which dictated how earlier robots could be deployed and the advances in underpinning technology which have moved these boundaries and led to the current inflection point.

This note explores the technology and economics of emerging 5G networks.

Options trading is an appealing investment alternative that can enable investors to profit from both share price movements and non-volatile market environments. This note provides a guide for entry-level options traders and is a logical progression from An Introduction to the Pricing of Options (905N14). The note reviews characteristics of options and the factors affecting their valuation, and it outlines several trading mechanisms that new options traders might use as they seek their most effective strategies, including long call, short put, bull call spread, short call, long put, bear put spread, short straddle, short strangle, long butterfly, long straddle, and long strangle.

Go (or Wei-ch'i, as it is known in China) is a centuries-old board game popular across Asia. Many have drawn parallels between military successes and the game's complex methods, in which a player encircles, isolates, and captures enemy pieces and geography, but Go also offers lessons for business. This technical note offers a basic description of Go, followed by a collection of business-strategy anecdotes punctuated by comparisons to Go strategies and quotes from Sun Tzu.