This chapter on fringe benefits draws on the theoretical support structure of compensating differentials (Chapter 3), given that workers value fringe benefits (i.e., non-monetary components of pay) and are therefore willing to accept lower monetary pay than they would receive in alternative jobs that do not offer those benefits but that are otherwise identical. The chapter opens with a discussion of workers’ valuations of various fringe benefits and how those valuations may differ from the employers’ costs of providing those benefits. From a managerial standpoint, the main problem with using benefits to compensate workers is inefficiency, in that workers often value those benefits at less than their cash equivalents. Against that disadvantage are a number of advantages of paying workers in benefits, and the chapter covers the main ones. Cafeteria plans mitigate the main disadvantage of benefits compensation while simultaneously weakening some of the advantages. The chapter ends with a lengthy section on pensions that provides a detailed distinction between defined-contribution and defined-benefit plans and the implications for worker behavior (e.g., retirement ages).

Why you care: To design and run a good online controlled experiment, you need metrics that meet certain characteristics. They must be measurable in the short term (experiment duration) and computable, as well as sufficiently sensitive and timely to be useful for experimentation. If you use multiple metrics to measure success for an experiment, ideally you may want to combine them into an Overall Evaluation Criterion (OEC), which is believed to causally impact long-term objectives. It often requires multiple iterations to adjust and refine the OEC, but as the quotation above, by Eliyahu Goldratt, highlights, it provides a clear alignment mechanism to the organization.

This chapter argues that enforceable fiduciary obligations owed by states to Indigenous peoples are best understood as private duties. The private character of state fiduciary duties is unnecessarily obscured by judicial findings that analogise them to private law ones and characterise the relationship as ‘sui generis’. We argue that there is little to be gained by characterising state-Indigenous fiduciary duties, expressly or by implication, as public duties. The private rights and duties generated within state-Indigenous relationships are structurally and substantively distinct from, and sometimes methodologically and normatively opposed to, the more general relationship between state and subjects that underpins public law and liberal political theory. For Indigenous peoples the crucial utility and promise of the state-Indigenous fiduciary relationship depends on the orthodoxy that the state does not, in general, owe fiduciary duties to its subjects. State-Indigenous fiduciary duties can and should function as a corrective to general public and administrative law, one that preserves space for this unique relationship and enables the enforcement of the distinctive rights and duties that attend it. For these reasons we argue that state Indigenous examples should not be used to model an emergent public fiduciary law or fiduciary political theory.

This chapter treats pay in nonprofits and the public sector, where the organization’s objectives are not as straightforward as in the typical for-profit firm. It also covers small businesses, a subject which is neglected in standard compensation texts but which is important because some readers are or aspire to be small-business managers. The opening section defines the 3 entities under discussion. Organizational missions and workers’ intrinsic motivation are described, which relates to compensating differentials in that workers who value the organizational mission interpret it as a non-monetary component of pay that creates an incentive to work hard to further the mission. The chapter revisits external and internal constraints on pay, training (and recruitment of desired worker types), performance pay, and turnover, thereby tying the book’s earlier concepts together. Subjects that were covered in earlier chapters are re-examined through the different lenses of nonprofits, the public sector, and small businesses. The chapter ends with coverage of “distance” between managers and owners, which tends to be shorter in small businesses than in larger ones, and its implications for pay.

This paper pursues two questions: what is it in the fiduciary relationship that grounds this transfer of legal power? And, given this grounds, what kind of reason (e.g. practical, moral or otherwise) does the fiduciary then have to act on behalf of the beneficiary? In response to the first, it argues that the principle modes of grounding the transfer of legal power — mutual consent and presumed consent — both involve trust. And in response to the second, it argues that this involvement of trust entails that a fiduciary’s reason for action is ultimately third personal.

Why you care: Randomized controlled experiments are the gold standard for establishing causality, but sometimes running such an experiment is not possible. Given that organizations are collecting massive amounts of data, there are observational causal studies that can be used to assess causality, although with lower levels of trust. Understanding the space of possible designs and common pitfalls can be useful if an online controlled experiment is not possible.

We started this book with a glimpse into data and data science. Then we spent the rest of the book, especially Parts II and III, learning various tools and techniques to solve data problems of different kinds. Our approach to all of this has been hands-on. And now we have come full circle. As we wrap up, it is important to take a look at where that data comes from, and how we should broadly think about analyzing it. This final chapter, therefore, is dedicated to those two goals, as you will see in the next two sections. One section is an overview of some of the most common methods for collecting/soliciting data, and the other provides information and ideas about how to approach a data analysis problem with broad methods. Then the final section provides a commentary on evaluation and experimentation.

This chapter responds to the growing importance of business analytics on "big data" in managerial decision-making, by providing a comprehensive primer on analyzing compensation data. All aspects of compensation analytics are covered, starting with data acquisition, types of data, and formulation of a business question that can be informed by data analysis. A detailed, hands-on treatment of data cleaning is provided, equipping readers to prepare data for analysis by detecting and fixing data problems. Descriptive statistics are reviewed, and their utility in data cleaning explicated. Graphical methods are used in examples to detect and trim outliers. The basics of linear regression analysis are covered, with an emphasis on application and interpreting results in the context of the business question(s) posed. One section covers the question of whether or not the pay measure (as a dependent variable) should be transformed via a logarithm, and the implications of that choice for interpreting the results are explained. Precision of regression estimates is covered via an intuitive, non-technical treatment of standard errors. An appendix covers nonlinear relationships among variables.

How and why is nationalization central to the politics of resource-rich countries? This chapter opens with a review of current theories on natural resource wealth and nationalization in political science, economics, and public policy, and then describes why existing theories are unable to answer the questions this book seeks to answer. With these questions in mind, this chapter presents the book’s central theory of why leaders nationalize and how leader survival shapes and is shaped by the choice of nationalization. After describing empirical implications of the argument, the chapter offers initial evidence to support these claims in the form of exploratory case studies of Iran and Iraq. In Iran, the shocking collapse of the Shah in 1979 defied the West’s notion of the “island of stability” in the tumultuous Middle East. In Iraq, the fall of the Hashemite monarchy in 1958 ushered in a decade of instability until the unexpected Ba’athist consolidation in 1968, when Hassan al-Bakr established a 35-year single-party dictatorship. These are precisely the types of outcomes in which the book’s theory predicts nationalization should affect the rise and fall of dictatorships.

The final chapter of the book compares the findings from the four issue areas and links them with the theoretical framework presented in Chapter 2. The chapter then asks: Given the EU’s interventions, what have been the impacts on the functioning of private governance and the larger policy field? The chapter argues that the regulatory impacts are twofold: The interventions have both restructured the field of private governance and largely retained private actors’ governing authority and private governance space. The interventions impose baselines that cannot be undercut and that arguably have resulted in some sustainability improvements. At the same time, the interventions are relatively limited since the standards and procedural regulations are minimum baselines with several evident gaps. This situation allows for policy exports and spillovers from private to public governance, both within the EU and beyond, which can potentially strengthen public policy. The chapter then discusses the generalizability of the theory by discussing examples of public interventions at both the international and the domestic level beyond the EU. The book concludes with avenues for further research.

“Just as trees are the raw material from which paper is produced, so too, can data be viewed as the raw material from which information is obtained.” To present and interpret information, one must start with a process of gathering and sorting data. And for any kind of data analysis, one must first identify the right kinds of information sources.

previous chapter, we discussed different forms of data. The height–weight data we saw was numerical and structured. When you post a picture using your smartphone, that is an example of multimedia data. The datasets mentioned in the section on public policy are government or open data collections.