Knowledge that Transforms

In order to facilitate the development of new research agendas, pioneering authors in AOS embarked on difficult journeys in search of the interconnections between accounting and the social. Contributions such as Burchell et al (1980) located a number of roles of accounting in society and inspired agenda-shifting historical investigations. However, as Hopwood (1985) recognised, the participation of historians in this project requires reinvestments in theoretical and epistemological thinking. This paper encourages renewed explorations of the concepts that might guide accounting history research seeking to probe the social. Such investments are especially pressing given that notions of ‘society’ and the ‘social’ have shifted since the early years of AOS. The study charts the problems of connecting accounting and the social, indicates how social historians have addressed similar issues, and reveals the scope for drawing on other notions of the ‘social’ that have the potential to extend historical understandings of the roles of accounting in society. The latter is illustrated through a discussion of the interactions between accounting and social control.

This study examines management control (MC) combinations that are effective in different strategic contexts through two related approaches – MC as a package and MC as a system. First, this study identifies how a set of MC practices combine (i.e. MC packages) to achieve effective control outcomes for firms operating in defender and prospector strategic contexts by applying fuzzy set qualitative comparative analysis (fsQCA). Using data from a survey of top managers the analysis reveals that there are multiple ways by which firms can effectively combine MC practices in a given strategic context. Furthermore, the analysis shows that not all MC practices found to be relevant in isolation are relevant when examined simultaneously as a package. Second, based on a comparison of effective MC packages this study examines interdependencies between MC practices (i.e. MC systems). Results show that in defender firms a diagnostic control use of accounting and mechanistic structural controls act as complements, while mechanistic structural controls and measure diversity act as substitutes. In prospector firms an interactive control use of accounting and organic structural controls are found to have complementary effects. These results indicate that the effectiveness of accounting control and structural control choices are determined not only by their fit with strategic context but also by how they fit with each other. This study also demonstrates how an understanding of MC packages can provide guidance for theory development and empirical analysis of MC systems.

This study proposes and tests an alternative to the extant earnings management explanation for zero and small positive earnings surprises (i.e., analyst forecast errors). We argue that analysts’ ability to strategically induce slight pessimism in earnings forecasts varies with the precision of their information. Accordingly, we predict that the probability that a firm reports a small positive instead of a small negative earnings surprise is negatively related to earnings forecast uncertainty, and we present evidence consistent with this prediction. Our findings have important implications for the earnings management interpretation of the asymmetry around zero in the frequency distribution of earnings surprises. We demonstrate how empirically controlling for earnings forecast uncertainty can materially change inferences in studies that employ the incidence of zero and small positive earnings surprises to categorize firms as suspected of managing earnings.

We show that the personal traits of analysts, as revealed by their political donations, influence their forecasting behavior and stock prices. Analysts who contribute primarily to the Republican Party adopt a more conservative forecasting style. Their earnings forecast revisions are less likely to deviate from the forecasts of other analysts and are less likely to be bold. Their stock recommendations also contain more modest upgrades and downgrades. Overall, these analysts produce better quality research, which is recognized and rewarded by their employers, institutional investors, and the media. Stock market participants, however, do not fully recognize their superior ability as the market reaction following revisions by these analysts is weaker.

Practitioners have long criticized risk-factor disclosures in the 10-K as generic and boilerplate. In response, regulators emphasize the importance of being specific. By using a computing algorithm, this paper establishes a new measure (Specificity) to quantify the level of specificity of firms’ qualitative risk-factor disclosures. We first examine determinants of variations in Specificity, and document that firms with high proprietary costs provide less specific risk-factor disclosures. More importantly, we find that, controlling for numerous determinants, the market reaction to the 10-K filing is positively and significantly associated with Specificity. In addition, our results suggest that analysts are better able to assess fundamental risk when firms’ risk-factor disclosures are more specific. Together, these findings suggest that more specific risk-factor disclosures benefit users of financial statements.