Chess databases as a research vehicle in psychology : modeling large data

The game of chess has often been used for psychological investigations, particularly in cognitive science. The clear-cut rules and well-defined environment of chess provide a model for investigations of basic cognitive processes, such as perception, memory, and problem solving, while the precise rating system for the measurement of skill has enabled investigations of individual differences and expertise-related effects. In the present study, we focus on another appealing feature of chess—namely, the large archive databases associated with the game. The German national chess database presented in this study represents a fruitful ground for the investigation of multiple longitudinal research questions, since it collects the data of over 130,000 players and spans over 25 years. The German chess database collects the data of all players, including hobby players, and all tournaments played. This results in a rich and complete collection of the skill, age, and activity of the whole population of chess players in Germany. The database therefore complements the commonly used expertise approach in cognitive science by opening up new possibilities for the investigation of multiple factors that underlie expertise and skill acquisition. Since large datasets are not common in psychology, their introduction also raises the question of optimal and efficient statistical analysis. We offer the database for download and illustrate how it can be used by providing concrete examples and a step-by-step tutorial using different statistical analyses on a range of topics, including skill development over the lifetime, birth cohort effects, effects of activity and inactivity on skill, and gender differences

Stakeholder communication in 140 characters or less: a study of community sport foundations

Community sport foundations (CSFs), like other non-profit organizations, are increasingly employing social media such as Twitter to communicate their mission and activities to their diverse stakeholder groups. However, the way these CSFs utilize social media for communicating such practices remains unclear. Through a mixed-method approach of content analysis of tweets from 22 CSFs established by English professional football clubs and interviews with key individuals within these CSFs (n = 7), this study examines the extent to which CSFs’ core activities are being communicated through Twitter and identifies the strategies employed for doing so. Reflecting the target audiences CSFs are seeking to reach through Twitter and the challenges associated with communication about projects involving marginalized groups, tweets largely concern programs related to sports participation and education. The most frequently employed communication strategy is to inform, rather than interact or engage with stakeholders. However, CSFs with higher organizational capacity attempt to go beyond mere informing towards engaging with stakeholder groups that relate to their social agenda, highlighting the importance of trained and dedicated social media personnel in optimizing CSFs’ use of Twitter for communication

Collecting data on TMTs’ organizational design: good practices from the StiMa project

Studying how Top Management Teams (TMTs) organize their managerial labor and decision-making processes is a relevant research avenue in light of the prominence of TMTs within modern firms. However, data on TMTs’ organizational design are usually not available from secondary sources and must instead be collected through surveys given to top executives. To help researchers in this difficult endeavor, the present paper offers a set of good practices for designing and implementing surveys on TMTs’ organizational design. To this end, we use as a basis the first-hand experience that we gained by working on the StiMa project, a large-scale data collection effort concerning the TMTs of a representative sample of Italian firms. We describe in detail all of the steps that we followed in preparing and administering the survey and in setting up and executing the additional data collection from secondary sources, which integrates survey data. We are confident that the lessons we learned from the StiMa project will help scholars in gathering better data on TMTs’ organizational design, thus advancing academics’ and practitioners’ conversations on the topic