Perceived Algorithmic Control and Prosocial Behavior

This dataset is derived from a research project aimed at examining the impact of perceived algorithmic control on the prosocial behavior of platform workers. The dataset consists of two parts: data from an online survey and data from a field survey.1. Data Generation Process and Processing MethodsOnline Survey:In Study 1, data were collected from ride-hailing drivers via the CREDAMO platform. The survey measured perceived algorithmic control, self-worth threat, self-affirmation, prosocial motivation, prosocial behavior, and relevant control variables.Field Survey:In Study 2, data were collected from food delivery riders through field surveys. The questionnaire included measures of perceived algorithmic control, self-worth threat, self-affirmation, prosocial motivation, prosocial behavior, and relevant control variables.2. Dataset ContentTemporal and Spatial Information:Data were collected between January 2026 and March 2026, covering multiple cities including Beijing and Shanghai.Number of Records:The online survey contains 263 valid responses, while the field survey includes more than 300 valid responses.3. Data StructureExperimental Data:This dataset includes columns such as participant ID, demographic information, and scale scores for perceived algorithmic control, self-worth threat, self-affirmation, prosocial motivation, prosocial behavior, and related control variables.Survey Data:This dataset includes matching identification codes, demographic information, and scale scores for perceived algorithmic control, self-worth threat, self-affirmation, prosocial motivation, prosocial behavior, and related control variables.Measurement Units:All variables are measured using a 5-point Likert scale, and the data are dimensionless scores.4. Missing Data and ErrorsMissing Data:In the survey data, some participants did not complete all items. Cases with missing responses were removed from the final dataset.Error Range:As the data involve subjective self-reports, potential biases may exist. To minimize such errors, questionnaires with obvious response patterns were excluded, and statistical procedures were applied to reduce their impact.5. Data File DescriptionAll data files are provided in CSV format and include demographic information as well as scale scores for all variables.The files can be opened and processed using common text editors or statistical software such as Excel, SPSS, and Mplus.