A brief coverage of amplitude modulation (AM) and angle modulation techniques is provided. The basic principles of conventional AM, double-sideband suppressed carrier AM, single-sideband AM, and vestigial sideband AM are described both through time-domain and frequency-domain techniques. Frequency and phase modulation are described and their equivalence is argued. A comparison of different analog modulation techniques in terms of complexity, power, and bandwidth requirements is made. Conversion of analog signals into a digital form through sampling and quantization is studied. Proof of the sampling theorem is given. Scalar and vector quantizers are described. Uniform and non-uniform scalar quantizer designs are studied. The Lloyd-Max quantizer design algorithm is detailed. The amount of loss introduced by a quantizer is quantified by computing the mean square distortion, and the resulting signal-to-quantization noise ratio. Pulse code modulation (PCM) as a waveform coding technique, along with its variants – including differential PCM and delta modulation – is also studied.

Economics equates rationality with the satisfaction of a set of axioms. We discuss these axioms and the associated empirical evidence. Topics discussed include completeness and transitivity of preferences, limited attention, overconfidence, and whether humans can successfully construct the full sampling distributions. We then consider procedural rationality and the unreasonable cognitive requirements for solving simple dynamic programming problems. We examine alternatives to mathematical optimization in which people use simple rules of thumb (heuristics) to make decisions. We highlight the heuristics and biases program which clearly shows that the “as if” assumption in neoclassical economics is routinely violated. These heuristics include the representativeness heuristic, the gambler’s fallacy, the hot hand fallacy, the conjunction fallacy, the availability heuristic, the affect heuristic, the anchoring heuristic, base rate underweighting in Bayes’ law, conservatism from underweighting the likelihood of a sample, hindsight-bias, confirmation-bias, false consensus, and regression to the mean. Incentives do not eliminate biases. We also discuss the “great rationality debate.”

Chapter 7 acknowledges that, despite the best planning for positive engagement, students will still exhibit disengaged and disruptive behaviours. It examines the research to discuss which behaviours are the most common and the most difficult to manage in a classroom environment. It makes the distinction between frequent disengaged behaviour and rare ‘challenging’ behaviour discussed in Chapters 9 and 10.

Building on previous chapters, this chapter also discusses the best ways to prevent disengaged behaviours through implementing consistent classroom routines, structures and expectations, including the explicit teaching of expected behaviour. Ongoing strategies such as social-emotional learning to build strong relationships, low-key techniques to remind and redirect behaviours, class meetings to support student voice and engaging lessons are explored.

In September 2008, the oldest investment bank on Wall Street, Lehman Brothers, declared bankruptcy. Immediately, the world’s financial system seized up. Hundreds of billions of dollars’ worth of financial assets were frozen in place, the value of securities made uncertain, and the solvency of seemingly rock-solid financial institutions called into question. By the end of 2008, the United States’ economy was in freefall, shrinking at an annualized rate of 8%. Growth rates in other major industrialized economies also plummeted as well. The recession was so deep, and the recovery so labored that it took more than a decade for output to return to full employment levels. Figure 19.1 illustrates the situation rather dramatically.

We live in an era of globalization, in which most producers operate internationally on a global scale. We, as consumers, are affected by events taking place on distant shores – to say we live in an age of interconnectedness is a cliché, but it is still true. Just check out the labels on the clothes in your closet. Your shirts, sweaters, jackets, and jeans were probably not produced in the United States. More likely, they were made in China, Bangladesh, Vietnam, India, Sri Lanka, or Mexico. The same is true for your shoes.

You may not know it, but the tomato has always been the subject of controversy. Botanists debate whether the tomato is a vegetable or a fruit (it is actually a fruit). Linguists debate whether it is pronounced as to-may-toe or to-mah-toe (who cares!). Meanwhile, agricultural economists debate where the best place to produce this nutritious and delicious crop might be.

Mathematical optimization models are mathematical means to find the best possible solutions to real-life optimization problems. They consist of three parts: decision variables that describe possible solutions, constraints that define conditions that these solutions need to satisfy, and an objective function that assigns a value to each solution, expressing how “good” it is.

In all the optimization problems discussed so far, we treated the quantities in the problem description as exact, but, in reality, they cannot always be trusted or assumed to be what we think. Uncertainty might negatively affect solutions to an optimization problem in the following forms:

• Estimation/forecast errors (increasingly important in an ML-driven world):

  • – in a production planning problem, future customer demand is a forecast;

  • – in a vehicle routing problem, travel times along various roads are real-time updated forecasts;

  • – in a wind farm layout problem, power production levels are based on wind forecasts.

• Measurement errors:

  • – a warehouse manager might have errors in the data records regarding current stock levels;

  • – the concentration level of a given chemical substance is different from expected.

• Implementation errors:

  • – a given quantity of an ingredient is sent to production in a chemical company, but due to device errors, a slightly smaller amount is actually received;

  • – electrical power sent to an antenna is subject to the generator’s errors.

Strategy and Organizational Forms argues for the importance of closely considering the environment in which globally operating firms are embedded, along with the pressures that shape organizational orientations, strategies, and forms. It recognizes the primacy of context and explains how the forces of global integration and local responsiveness shape organizational orientations, strategies, and forms. Major organizational forms in multinational enterprises are described. The ways in which organizations grow includes a particular focus on acquisitions and strategic alliances including joint ventures. Approaches to global business by small- and medium-size enterprises are explored. Trends in organizing related to digital transformations and lateral collaboration are identified.