DOI: 10.57760/sciencedb.psych.00139
title: Algorithmic Regulation Pressure and Service Performance
title: 算法规范压力与服务绩效

description: This dataset originates from a research project aimed at exploring the dual-edged effects of algorithmic norm pressure on gig workers' service performance. The dataset consists of two parts: scenario experiment data and field survey data.1. Data Generation Process and Processing MethodsScenario Experiment:In Study 1, we designed scenario materials representing high and low algorithmic norm pressure conditions. Participants' stress responses, job crafting behaviors, and service performance were collected through an online experimental platform. The dataset includes participants' scenario response scores along with other variable ratings.Field Survey:In Study 2, we conducted a field survey to collect self-reported and peer-reported data from gig workers on algorithmic transparency, online community support, job crafting behavior, and service performance.2. Dataset OverviewTime and Geographic Scope:Data collection was conducted between October 2023 and January 2024, covering major cities such as Beijing, Shanghai, and Guangzhou.Number of Records:Scenario experiment data: Over 300 participants' experimental records.Field survey data: Over 300 valid survey responses.3. Data StructureScenario Experiment Data: Includes variables such as participant ID, scenario condition, stress rating, job crafting behavior rating, and other variable scores.Survey Data: Includes variables such as participant ID, demographic information, algorithmic transparency rating, online community support rating, job crafting behavior rating, and service performance rating.Measurement Units: All ratings are based on a 7-point Likert scale, and the data is expressed as dimensionless scores.4. Data Missingness and Error ControlMissing Data: Some participants in the field survey did not complete all questions; these cases were removed from the dataset.Error Range: Since the data collection involves subjective ratings, participant biases may exist. Data cleaning and statistical analysis were conducted to minimize errors.5. Data File DescriptionScenario Experiment Data File: Stored in .xlsx format, including participant ID, scenario condition, stress rating, job crafting behavior rating, and other key variables. Additionally, two scenario videos are included.Survey Data File: Stored in .xlsx format, containing demographic information and variable scores.The dataset can be accessed and processed using common text editors or statistical software, such as Excel, SPSS, and Mplus.
description: This dataset originates from a research project aimed at exploring the dual-edged effects of algorithmic norm pressure on gig workers' service performance. The dataset consists of two parts: scenario experiment data and field survey data.1. Data Generation Process and Processing MethodsScenario Experiment:In Study 1, we designed scenario materials representing high and low algorithmic norm pressure conditions. Participants' stress responses, job crafting behaviors, and service performance were collected through an online experimental platform. The dataset includes participants' scenario response scores along with other variable ratings.Field Survey:In Study 2, we conducted a field survey to collect self-reported and peer-reported data from gig workers on algorithmic transparency, online community support, job crafting behavior, and service performance.2. Dataset OverviewTime and Geographic Scope:Data collection was conducted between October 2023 and January 2024, covering major cities such as Beijing, Shanghai, and Guangzhou.Number of Records:Scenario experiment data: Over 300 participants' experimental records.Field survey data: Over 300 valid survey responses.3. Data StructureScenario Experiment Data: Includes variables such as participant ID, scenario condition, stress rating, job crafting behavior rating, and other variable scores.Survey Data: Includes variables such as participant ID, demographic information, algorithmic transparency rating, online community support rating, job crafting behavior rating, and service performance rating.Measurement Units: All ratings are based on a 7-point Likert scale, and the data is expressed as dimensionless scores.4. Data Missingness and Error ControlMissing Data: Some participants in the field survey did not complete all questions; these cases were removed from the dataset.Error Range: Since the data collection involves subjective ratings, participant biases may exist. Data cleaning and statistical analysis were conducted to minimize errors.5. Data File DescriptionScenario Experiment Data File: Stored in .xlsx format, including participant ID, scenario condition, stress rating, job crafting behavior rating, and other key variables. Additionally, two scenario videos are included.Survey Data File: Stored in .xlsx format, containing demographic information and variable scores.The dataset can be accessed and processed using common text editors or statistical software, such as Excel, SPSS, and Mplus.