Hasan Humayun;Mohammad Nauman Malik;Masitah Ghazali
{"title":"利用长尾理论分析众包中的动机理论:系统性文献综述","authors":"Hasan Humayun;Mohammad Nauman Malik;Masitah Ghazali","doi":"10.26599/IJCS.2023.9100010","DOIUrl":null,"url":null,"abstract":"Motivational theories have been extensively studied in a wide range of fields, such as medical sciences, business, management, physiology, sociology, and particularly in the natural sciences. These theories are regarded as crucial in motivating online workers to engage in crowdsourcing. Nevertheless, there is a dearth of research on an overarching review of these theories. We performed a systematic literature review of peer-reviewed published studies focusing on motivational theories to identify popular theories and risks associated with nascent theories presented over the last decade in crowdsourcing. Based on a review of 91 papers from the domain of the natural sciences, we identified 35 motivational theories. The long tail theory helped us to identify the contribution of major influencing theories in a crowdsourcing environment. The results justify the long tail theory based on the Pareto principle of 80/20, which underlines the 20% of the popular motivation theories, namely self-determination, expectancy-value, game, gamification, behavior change, and incentive theory, as a cause of 80%. Similarly, we discussed the risks associated with 10 theories presented over the long tail, which have a frequency equal to 2. Understanding the significant impact, approximately 80%, of widely recognized motivational theories and their role in risk identification is crucial. This understanding can assist researchers in optimizing their results by effectively integrating these theories.","PeriodicalId":32381,"journal":{"name":"International Journal of Crowd Science","volume":"8 1","pages":"10-27"},"PeriodicalIF":0.0000,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10445691","citationCount":"0","resultStr":"{\"title\":\"Analysis of Motivational Theories in Crowdsourcing Using Long Tail Theory: A Systematic Literature Review\",\"authors\":\"Hasan Humayun;Mohammad Nauman Malik;Masitah Ghazali\",\"doi\":\"10.26599/IJCS.2023.9100010\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Motivational theories have been extensively studied in a wide range of fields, such as medical sciences, business, management, physiology, sociology, and particularly in the natural sciences. These theories are regarded as crucial in motivating online workers to engage in crowdsourcing. Nevertheless, there is a dearth of research on an overarching review of these theories. We performed a systematic literature review of peer-reviewed published studies focusing on motivational theories to identify popular theories and risks associated with nascent theories presented over the last decade in crowdsourcing. Based on a review of 91 papers from the domain of the natural sciences, we identified 35 motivational theories. The long tail theory helped us to identify the contribution of major influencing theories in a crowdsourcing environment. The results justify the long tail theory based on the Pareto principle of 80/20, which underlines the 20% of the popular motivation theories, namely self-determination, expectancy-value, game, gamification, behavior change, and incentive theory, as a cause of 80%. Similarly, we discussed the risks associated with 10 theories presented over the long tail, which have a frequency equal to 2. Understanding the significant impact, approximately 80%, of widely recognized motivational theories and their role in risk identification is crucial. This understanding can assist researchers in optimizing their results by effectively integrating these theories.\",\"PeriodicalId\":32381,\"journal\":{\"name\":\"International Journal of Crowd Science\",\"volume\":\"8 1\",\"pages\":\"10-27\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10445691\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Crowd Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10445691/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Decision Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Crowd Science","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10445691/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Decision Sciences","Score":null,"Total":0}
Analysis of Motivational Theories in Crowdsourcing Using Long Tail Theory: A Systematic Literature Review
Motivational theories have been extensively studied in a wide range of fields, such as medical sciences, business, management, physiology, sociology, and particularly in the natural sciences. These theories are regarded as crucial in motivating online workers to engage in crowdsourcing. Nevertheless, there is a dearth of research on an overarching review of these theories. We performed a systematic literature review of peer-reviewed published studies focusing on motivational theories to identify popular theories and risks associated with nascent theories presented over the last decade in crowdsourcing. Based on a review of 91 papers from the domain of the natural sciences, we identified 35 motivational theories. The long tail theory helped us to identify the contribution of major influencing theories in a crowdsourcing environment. The results justify the long tail theory based on the Pareto principle of 80/20, which underlines the 20% of the popular motivation theories, namely self-determination, expectancy-value, game, gamification, behavior change, and incentive theory, as a cause of 80%. Similarly, we discussed the risks associated with 10 theories presented over the long tail, which have a frequency equal to 2. Understanding the significant impact, approximately 80%, of widely recognized motivational theories and their role in risk identification is crucial. This understanding can assist researchers in optimizing their results by effectively integrating these theories.