From Greenwashing to Machinewashing: A Model and Future Directions Derived from Reasoning by Analogy

Journal of Business Ethics - This article proposes a conceptual mapping to outline salient properties and relations that allow for a knowledge transfer from the well-established greenwashing...     

R&D employment effects of financial slack generated by R&D tax exemption: The importance of firm-level contingencies

This paper focuses on R&D employment effects due to financial slack generated by an R&D tax exemption scheme in Belgium. The tax exemption is granted without firm-level requirements, which facilitates testing firm-level contingencies on the influence of the generated financial slack. We find that R&D employment effects increase with the level of the R&D tax exemption related to financial slack resources and that this positive relation is more outspoken for older firms and for firms with an intermediate share of R&D tax exemptions in the overall mix of R&D policy support. No effects are found for firm size and its R&D intensity. These findings suggest targeting the R&D tax exemption support according to firm characteristics to obtain longer term R&D employment effects. The focus on R&D employment adds to the literature on the evaluation of R&D policies which is largely oriented toward R&D expenditure and innovation outputs.     

Household Determinants of the Adoption of Improved Cassava Varieties using DNA Fingerprinting to Identify Varieties in Farmer Fields: A Case Study in Colombia

We examine factors affecting the adoption of improved cassava varieties of 217 households in the Cauca Department in southwest Colombia. Using DNA fingerprinting through Single Nucleotide Polymorphisms (SNPs), we identified different cultivars in farmers fields. We also used this information to remove possible bias in the adoption model that could have resulted from a misclassification of improved varieties (IVs). As a result, we found that farmers substantially overestimate their use of IVs and there are important differences in the determinants of adoption between farmer self‐identification and DNA fingerprinting. This finding implies that the incorporation of DNA fingerprinting in IV adoption studies is important to ensure the accuracy of future agricultural economic research and the relevance of subsequent policy recommendations.     

Khat-chewing in liminal leisure spaces: British-Somali youth on the margins

Khat-chewing, a controversial leisure activity within the Somali diaspora in Britain, has received little attention within the academic field of Leisure Studies. This paper reports on ethnographic research to provide insights into the unique locations where young British-Somali men chew khat, exposing the liminal qualities of such localities. The paper begins with an overview of the contentious position khat-chewing occupies within Somali communities in Britain, highlighting reasons why young British-Somali men hide their association with the leisure practice. The discussion that follows considers how young male khat users conceptualise spatial environments, exposing how these locations temporarily produce a dual sense of privacy and sociality. The ambiences of such temporary leisure spaces remain open to the prospect of discovery, resulting in the use of discretionary tactics to maintain a sense of secrecy. In this context, we discuss how khat-chewing offers a sense of cultural identity and belongingness while also marking young British-Somali men as outsiders – even within their own communities.     

Building relationship innovation in global collaborative partnerships: big data analytics and traditional organizational powers

This study examines how relationship innovation can be developed in global collaborative partnerships (alliances, joint ventures, mergers, and acquisitions). The recently emerging theory of big data analytics linked with traditional organizational powers has attracted a growing interest, but surprisingly little research has been devoted to this important and complex topic. Therefore, after developing the theoretical foundations, our study empirically quantifies the links between the theoretical constructs based on the data collected from chief executive officers, managing directors, and heads of departments who work in contemporary global data‐and‐information driven collaborative partnerships. The results from structural equation modeling indicate that the relationship innovation depends on the power of big data analytics and non‐mediated powers (NMP, expert and referent). The power of big data analytics also mediates the correlation between NMP and relationship innovation. However, mediated powers (coercive and manipulative) negatively affect the power of big data analytics and relationship innovation. The interaction effects further depict that analytically powered partnerships have better relationship innovation compared with those which focus less on the analytical power. Consequently, the contributions of this study provide a deeper understanding of mechanisms of how modern collaborative partnerships can use big data analytics and traditional organizational powers to co‐create relationship innovation.     

Monetary Policy Implementation: Making Better and More Consistent Use of the Federal Reserve's Balance Sheet

Since December 2015, the Federal Reserve has operated a new “floor system” in which it brings about desired changes in its targeted federal funds rate by managing the interest rate it pays on bank reserves and other short‐term liabilities. The design of this new system reflects the tendency of Fed officials to view monetary policy as affecting the economy through Keynesian” interest rate channels. From this Keynesian perspective, policy actions that change the size of the balance sheet are seen as tools for influencing credit market conditions that operate in addition to and independently of the Fed's monetary policy stance. The alternative monetarist framework proposed by the author views monetary policy and its effects as operating through the interaction between money supply and demand. Use of this framework makes clear that, even under a floor system, monetary policy actions designed to affect the aggregate price level and the rate of inflation must be accompanied sooner or later by traditional open market operations that have implications for the size and composition of the Fed's balance sheet. Use of the monetarist framework also underscores the likelihood that the Fed, by paying interest on reserves, has unknowingly contributed to the restrictiveness of its own monetary policies since the financial crisis, a period during which inflation has run consistently below target. More generally, the monetarist framework downplays the importance of the zero lower interest rate bound and suggests that monetary policy could be conducted more effectively by adopting and adhering to a consistent, rule‐like manner during good times and bad.     

Target‐Setting,Pay for Performance,and Quality Improvement: A Case Study of Ontario Hospitals’ Quality‐Improvement Plans

This study examines whether difficult targets and quality indicators in executives' pay‐for‐performance (P4P) plans affect performance. The impact of target‐setting and P4P plans on quality improvement in the public sector is unclear. The Ontario government initiated the Quality Improvement Plan (QIP), which requires hospitals to set targets for quality indicators annually and link executive pay to target achievement since 2011. Analyzing Health Quality Ontario's database and hospitals' 2012–2013 QIPs, this study shows greater quality improvement in hospitals with difficult targets than hospitals with easy targets or without assigned targets; however, the positive impact disappears for high‐performance hospitals relative to their peers. We find no significant effect of the use of quality indicators in executives' P4P plans on quality improvement. Copyright © 2018 ASAC. Published by John Wiley & Sons, Ltd.     

Time series copulas for heteroskedastic data

We propose parametric copulas that capture serial dependence in stationary heteroskedastic time series. We suggest copulas for first‐order Markov series, and then extend them to higher orders and multivariate series. We derive the copula of a volatility proxy, based on which we propose new measures of volatility dependence, including co‐movement and spillover in multivariate series. In general, these depend upon the marginal distributions of the series. Using exchange rate returns, we show that the resulting copula models can capture their marginal distributions more accurately than univariate and multivariate generalized autoregressive conditional heteroskedasticity models, and produce more accurate value‐at‐risk forecasts.