Champions, converts, doubters, and defectors: the impact of shifting perceptions on momentum for change

Maintaining momentum is a key influence on the ultimate success of large-scale change. In this paper, we develop theory to explain how stable vs. shifting change-supportive perceptions over time differentially influence the perceived momentum associated with goal-directed change (i.e., change-based momentum). We use cross-level polynomial regression and data obtained early and one year later within an organization implementing a lean manufacturing transformation to model changes in individual perceptions. Results suggest that momentum perceptions are higher for “Champions” (stable and high perceptions over time) as compared to “Converts” (increasing perceptions over time), but momentum perceptions are lower for “Defectors” (decreasing perceptions over time) as compared to “Doubters” (stable and low perceptions over time). We find that even if participants converge upon change-supportive perceptions later in the change process, early divergent perceptions influence subsequent momentum for the change. These findings highlight the important role of temporal shifts in perceptions for organizational change processes

Understanding Crowd-Powered Search Groups: A Social Network Perspective

Background: Crowd-powered search is a new form of search and problem solving scheme that involves collaboration among a potentially large number of voluntary Web users. Human flesh search (HFS), a particular form of crowd-powered search originated in China, has seen tremendous growth since its inception in 2001. HFS presents a valuable test-bed for scientists to validate existing and new theories in social computing, sociology, behavioral sciences, and so forth. Methodology: In this research, we construct an aggregated HFS group, consisting of the participants and their relationships in a comprehensive set of identified HFS episodes. We study the topological properties and the evolution of the aggregated network and different sub-groups in the network. We also identify the key HFS participants according to a variety of measures. Conclusions: We found that, as compared with other online social networks, HFS participant network shares the power-law degree distribution and small-world property, but with a looser and more distributed organizational structure, leading to the diversity, decentralization, and independence of HFS participants. In addition, the HFS group has been becoming increasingly decentralized. The comparisons of different HFS sub-groups reveal that HFS participants collaborated more often when they conducted the searches in local platforms or the searches requiring a certain level of professional knowledge background. On the contrary, HFS participants did not collaborate much when they performed the search tas

A Hierarchical Taxonomy of Psychopathology Can Transform Mental Health Research

For more than a century, research on psychopathology has focused on categorical diagnoses. Although this work has produced major discoveries, growing evidence points to the superiority of a dimensional approach to the science of mental illness. Here we outline one such dimensional system-the Hierarchical Taxonomy of Psychopathology (HiTOP)-that is based on empirical patterns of co-occurrence among psychological symptoms. We highlight key ways in which this framework can advance mental-health research, and we provide some heuristics for using HiTOP to test theories of psychopathology. We then review emerging evidence that supports the value of a hierarchical, dimensional model of mental illness across diverse research areas in psychological science. These new data suggest that the HiTOP system has the potential to accelerate and improve research on mental-health problems as well as efforts to more effectively assess, prevent, and treat mental illness