Rather than re-examine the question of whether doing good generally helps a company to do well, this study draws on contingency theory to empirically examine when doing good helps a company do as well as possible. Using panel data, we examine the effects of industry life cycle, munificence, and instability on the relationship between corporate social responsibility (CSR) and corporate financial performance (CFP). Our findings indicate that life cycle has a significant impact on the CSR-CFP relationship, as does industry instability. (...) These findings suggest that CSR helps the bottom line considerably – if it is applied at the right time. (shrink)

The Centre for Aesthetics, Religion and Contemporary Culture and the Haas Library at the Universitat Pompeu Fabra are pleased to announce the new call for applications for two individual J&M Villavecchia Fellowships for 2022-2023. This call is open to both artists and postdoctoral researchers with original and innovative proposals that make use of the themes and materials of the Haas Library. -/- Fellowships are for a period of three months. One fellowship will be granted for the winter semester (from September (...) to February), and another for the spring semester (from February to July). -/- Applications deadline: March 1st, 2022. (shrink)

Many of the commentators—let’s ignore their sex for the moment—suggested including women in the Feyerabend conference. Then the question was raised, “but are they of the right quality, status, rank?” That is, do they bring down the average quality of the conference in virtue of their being of inferior status, or, in Vincenzo Politi’s words, not “someone whose work is both relevant to the topic of the conference and also as widely recognized as the work of the invited speakers” (HOPOS-L (...) archive, “CFP: Feyerabend Conference,” Tuesday, July 17, 2012, 14:57:20)? It is extremely important that such a discussion of quality, status, and rank recognize the scourge of evaluation bias and its long-term and pervasive consequences. One well-designed study this past year, published by the National Academy of Sciences, established prominent evaluation bias among both male and female science faculty in their evaluations of a student applying for a managerial job, who was randomly assigned either a male or a female name (Moss-Racusin et al. 2012). These professors examined the qualifications of the students and decided whether to hire them, what salary to give them, and whether to mentor themand howmuch to do so.The resultswere that both male and female scientists hired more men, gave them higher salaries, and offered more mentoring to them, even though themale applications were identical to the female applications. When probed about their reasons for not hiring or mentoring the female applicants, the professors explained that they based their decisions on the inferior competence of the applicant: the female applicants were perceived as less competent by all professors (with identical applications between males and females). This is what “evaluation bias” looks like, and it has been established in many, many contexts since the 1970s—this is only the most recent. (shrink)