Nan Maxwell

Data and Decision Making Same Organization, Different Perceptions; Different Organizations, Different Perceptions

This study examines the perceptions of data-driven decision making (DDDM) activities and culture in organizations driven by a social mission. Analysis of survey information from multiple stakeholders in each of eight social enterprises highlights the wide divergence in views of DDDM. Within an organization, managerial and nonmanagerial staff working for the organization and staff from a prominent funder all expressed different perceptions of the same organization’s DDDM activities and culture. Study findings also provide insights into how to improve an organization’s capacity to build and use performance management systems, which include building a common understanding about what activities are—or are not—being undertaken. Finally, findings provide insights about structuring research on DDDM, which indicate that information from only one respondent in an organization or only one organization might not be reliable or generalizable.

Compensation and Intrinsic Motivation in Nonprofit and For-Profit Organizations

We develop a theoretical model in which for-profit and nonprofit employers compete to hire a worker who derives intrinsic motivation from the nonprofit’s social mission. We also use a unique data set of California establishments to provide new evidence on sectoral differences in pay and HRM systems, finding a greater incidence of training and benefits in nonprofits, lower wages (with the wage gap increasing in skill level), and less incentive pay than in for-profits. The model is used to interpret both this new evidence and other empirical results from the literature, including the inconclusive sign of the FP-NP wage differential.

Understanding the Probability of a Disability Resulting from Work-Related Injuries

Objectives: To assess the conditions under which the measured risk of a workplace injury resulting in a disability changes. Methods: Multivariate regression analysis and administrative claims data build an understanding of the factors that underlie the probability that a workplace injury results in a disability (disability probability). Results: First, jointly examining injury incidence rates and disability probabilities challenges some conclusions suggested by examining the two separately. Second, some characteristics identified as risk factors for disability when studied in isolation are not risk factors. Third, risk factors are qualitatively consistent across groups of workers but quantitatively different. Conclusions: Policymakers might draw incorrect conclusions about the risk of a workplace injury becoming a disability unless the research provides a joint assessment of incidence rates and disability probabilities and a comprehensive analysis of risk factors across worker groups.