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In this chapter, we explore the implications of benign and malicious envy in the workplace and suggest methods by which leaders can manage the situational context to minimize negative responses to envy and promote positive responses. We argue that three aspects of the organizational context are especially influential in the development of envy: perceptions of fairness, employees’ feelings of control over their situation, and organizational culture. All three impact whether felt envy will be benign or malicious. In addition, the right organizational culture can prevent any feelings of malicious envy from leading to undesirable behaviors. We suggest that by fostering justice, promoting employee feelings of control, and exemplifying an ethical organizational culture leaders can manage the manifestation of envy and resulting behaviors in a positive direction.

This research provides accounting-ethics authors and administrators with a benchmark for accounting-ethics research. While Bernardi and Bean (2010) considered publications in business-ethics and accounting’s top-40 journals this study considers research in eight accounting-ethics and public-interest journals, as well as, 34 business-ethics journals. We analyzed the contents of our 42 journals for the 25-year period between 1991 through 2015. This research documents the continued growth (Bernardi & Bean, 2007) of accounting-ethics research in both accounting-ethics and business-ethics journals. We provide data on the top-10 ethics authors in each doctoral year group, the top-50 ethics authors over the most recent 10, 20, and 25 years, and a distribution among ethics scholars for these periods. For the 25-year timeframe, our data indicate that only 665 (274) of the 5,125 accounting PhDs/DBAs (13.0% and 5.4% respectively) in Canada and the United States had authored or co-authored one (more than one) ethics article.

We propose a generic algorithm for numerically accurate likelihood evaluation of a broad class of spatial models characterized by a high-dimensional latent Gaussian process and non-Gaussian response variables. The class of models under consideration includes specifications for discrete choices, event counts and limited-dependent variables (truncation, censoring, and sample selection) among others. Our algorithm relies upon a novel implementation of efficient importance sampling (EIS) specifically designed to exploit typical sparsity of high-dimensional spatial precision (or covariance) matrices. It is numerically very accurate and computationally feasible even for very high-dimensional latent processes. Thus, maximum likelihood (ML) estimation of high-dimensional non-Gaussian spatial models, hitherto considered to be computationally prohibitive, becomes feasible. We illustrate our approach with ML estimation of a spatial probit for US presidential voting decisions and spatial count data models (Poisson and Negbin) for firm location choices.

Resurgent interest in the life and work of the Italian Cambridge economist Piero Sraffa is leading to New Directions in Sraffa Scholarship. This chapter introduces readers to some of these developments. First and perhaps foremost is the fact that as of September 2016 Sraffa’s archival material has been uploaded onto the website of the Wren Library, Trinity College, Cambridge University, as digital colour images; this chapter introduces readers to the history of these events. This history provides sharp relief on the extant debates over the role of the archival material in leading to the final publication of Production of Commodities by Means of Commodities, and readers are provided a brief sketch of these matters. The varied nature of Sraffa scholarship is demonstrated by the different aspects of Sraffa’s intellectual legacy which are developed and discussed in the various entries of our Symposium. The conclusion is reached that we are on the cusp of an exciting phase change of tremendous potential in Sraffa scholarship.