Showing 9-16 of 272 results
Innovation Idea Generation for a Bookstore's Holiday Promotion

Innovation Idea Generation for a Bookstore's Holiday Promotion

Claus
Open Dataset
Creators: Claus Hegmann-Napp, Tijmen P. J. Jansen
Publication Date: 2025-11-18
Creators: Claus Hegmann-Napp, Tijmen P. J. Jansen

This dataset contains 460 observations from an experimental study focused on idea generation. The goal of the study was likely to examine how individual differences and attitudes toward artificial intelligence (AI) influence the ideas produced for a specific task (holiday promotions for a bookstore).

The dataset features 460 rows (observations) and 9 variables, including the text of the generated ideas and a suite of participant metrics such as personality scores, self-reported task metrics, and ratings of AI opinions.

Consumer Responses to Radio Advertisements: Perceptual Sound Features and Attitudinal Outcomes

Consumer Responses to Radio Advertisements: Perceptual Sound Features and Attitudinal Outcomes

Tijmen
Open Dataset
Creators: Tijmen P. J. Jansen and Maximilian Witte
Publication Date: 19.11.2025
Creators: Tijmen P. J. Jansen and Maximilian Witte

This dataset contains perceptual, acoustic, and evaluative measures for a series of radio advertisements. Each ad was produced using different voice profiles, allowing analysis of how sound characteristics influence advertising effectiveness. The dataset includes subjective evaluations of the ad (liking, appealingness, purchase intent) alongside objective audio measurements such as loudness, brightness, pitch, vocal tract length, and harmonics-to-noise ratio. The dataset is suitable for research on auditory advertising effects, persuasion, sound engineering, and voice-based marketing.

Digital Twins Dataset

Digital Twins Dataset

Stefan
Open Dataset
Creators: Olivier Toubia, George Z. Gui, Tianyi Peng, Daniel J. Merlau, Ang Li and Haozhe Chen
Publication Date: 2025
Creators: Olivier Toubia, George Z. Gui, Tianyi Peng, Daniel J. Merlau, Ang Li and Haozhe Chen

The Twin-2K-500 dataset is a publicly released, large-scale survey dataset designed to support the construction of digital twins of individuals.

  • It covers 2,058 U.S. participants who completed four waves of data collection.

  • Across the first three waves, each person responded to about 500 questions spanning a rich battery of measures: demographic variables, personality and psychological scales, cognitive performance tasks, economic preferences, behavioral experiments (heuristics & biases), and a pricing survey.

  • The fourth wave re-administered selected behavioral tasks (from earlier waves) to establish a test-retest baseline for assessing prediction fidelity.

  • On average, participants spent around 2.42 hours total responding across all waves.

  • The survey was implemented via Qualtrics; participants who completed all waves were compensated.

  • The structure of the dataset is organized into different “persona” representations (JSON/text) and wave splits for training/evaluation of models.

In sum: Twin-2K-500 provides richly annotated, multi-wave behavioral and psychological data on over two thousand individuals, enabling researchers to train and evaluate digital-twin models that predict human responses across domains.

Operational Firm Risk Dataset

Operational Firm Risk Dataset

Stefan
Open Dataset
Creators: Vivek Astvansh and Joseph Simpson
Publication Date: 2025
Creators: Vivek Astvansh and Joseph Simpson

The authors score 131,920 firm-years (16,959 firms, 2005 to 2024) on eight risk factors: (1) accounting, (2) finance, (3) international, (4) legal, (5) management, (6) marketing, (7) operations, and (8) technology. We measure each transformer’s performance on eight metrics.

Their OSF repository (https://osf.io/gz93b/files/osfstorage?view_only=9086f51f8704462d8933a8131b22da25) includes an Excel file that contains a data dictionary (dataset_dictionary.xlsx) and count and probability scores of the eight risk factors for 131,920 firm-years (16,959 firms, 2005 to 2024) (dataset.xlsx).

CEO Dismissal and Turnover Dataset for S&P 1500 Firms (1992–2022)

CEO Dismissal and Turnover Dataset for S&P 1500 Firms (1992–2022)

carol.reyes.dulong
Open Dataset
Creators: Richard J. Gentry, Joseph Harrison, Timothy Quigley, Steven Boivie
Publication Date: 2023-11-09
Creators: Richard J. Gentry, Joseph Harrison, Timothy Quigley, Steven Boivie

This dataset captures CEO departures across S&P 1500 firms from 1992 to 2022, with qualitative codes identifying the reason for each turnover (e.g., dismissal, retirement, new opportunity). Each entry includes company and executive identifiers, tenure details, and announcement/departure dates. The data support alignment with Execucomp and are intended for research in corporate governance, executive leadership, firm performance, and succession planning. Regularly updated, this open-access dataset includes supporting notes and source references.

Agricultural, Climate, and Water Management Data for Australia’s Murray–Darling Basin

Agricultural, Climate, and Water Management Data for Australia’s Murray–Darling Basin

carol.reyes.dulong
Open Dataset
Creators: Will Rafey, UCLA Department of Economics
Publication Date: 2023-01-18
Creators: Will Rafey, UCLA Department of Economics

This dataset collection compiles key information on agriculture, climate, and water resource management in Australia’s Murray–Darling Basin. It brings together information from multiple sources, including ABARES, the Bureau of Meteorology (BoM), and the Australian Water Markets Report (AWMR). The collection includes crop calendars and coefficients, irrigation production estimates (GVIAP), monthly climate indicators such as rainfall and evapotranspiration, and economic data on water prices and allocations. Geospatial boundary files and supporting metadata are also provided to enable spatial and temporal analysis. The collection supports research on agricultural planning, water use efficiency, and environmental policy in the basin.

Geospatial and Environmental Exposure Data for U.S. Census-Based Analysis (2000–2016)

Geospatial and Environmental Exposure Data for U.S. Census-Based Analysis (2000–2016)

carol.reyes.dulong
Open Dataset
Creators: Janet Currie, Princeton University; John Voorheis, United States Census Bureau; Reed Walker, University of California-Berkeley
Publication Date: 2022-12-20
Creators: Janet Currie, Princeton University; John Voorheis, United States Census Bureau; Reed Walker, University of California-Berkeley

This dataset collection contains publicly available geospatial, environmental, and demographic data used to examine the relationship between PM2.5 exposure and population characteristics across the United States from 2000 to 2016. It includes annual satellite-based and monitor-based PM2.5 estimates (Di et al., EPA, van Donkelaar), county-level nonattainment status under the Clean Air Act, and geographic boundary files for U.S. states, census blocks, and commuting zones. Demographic data at the tract and block level are provided via IPUMS NHGIS and the U.S. Census Bureau. These files are designed for spatial matching, environmental exposure assignment, and policy-related research on air quality and health disparities.

Cross-National Data on Obesity Perceptions, Beliefs, and Health Indicators

Cross-National Data on Obesity Perceptions, Beliefs, and Health Indicators

carol.reyes.dulong
Open Dataset
Creators: Elisa Macchi, MIT
Publication Date: 2023-01-15
Creators: Elisa Macchi, MIT

This dataset collection compiles a range of data sources related to body weight perceptions, demographic characteristics, and obesity prevalence across countries. It includes individual-level experimental and survey data on how people perceive others based on physical appearance and descriptive information, as well as their associated beliefs and attitudes. Additional files provide demographic details, regional obesity rates for the U.S. and Europe, global GDP per capita data, and country-level health indicators from sources like IPUMS DHS and the World Bank. The datasets are suitable for research on health perception, socioeconomic evaluation, and international comparisons in public health.

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