{"id":{"repo_id":"temple","oai_identifier":"oai:scholarshare.temple.edu:20.500.12613/10672"},"canonical_url":"https://search.dev.ndltd.org/etd/temple/oai:scholarshare.temple.edu:20.500.12613/10672","repository":{"repo_id":"temple","name":"Temple University","base_url":"https://scholarshare.temple.edu/server/oai/request"},"display":{"title":"THE POWER OF CROWD IN THE BUSINESS WORLD","abstract":"In this work, we focus on two attractive crowd-based business models, i.e., user-generated content creation and freight-matching long-haul trucking. First, as elaborated in CHAPTER 2, we consider a game theoretical modeling approach for understanding the operation of non-profit UGC platforms that rely on users to create content and maintain financial sustainability. In particular, we examine several interesting research questions with practical importance and unique contributions to the literature. These research questions mainly investigate how changes in critical business factors influence the platforms' strategic effort allocation, user participation, and overall performance. Second, in CHAPTER 3, we focus on the flourishing freight-matching businesses that rely on crowdsourced drivers for long-haul trucking. In particular, although the practice suggests that shippers' ordering behaviors of freight-matching services may remarkably impact crowdsourced drivers' bidding behaviors, the literature has yet to examine this issue formally. Therefore, we collect industrial data and construct a strict empirical schema for understanding the association between shippers' order timing and freight-matching performance. Besides, by deliberately building a theoretical modeling framework and using a data-driven estimation of model parameters, we are able to simulate the freight-matching performance of adopting our empirical findings and evaluate the practical value of our study. By investigating these two prominent business models, we aim to understand the advantages of crowdsourcing businesses and the role of crowds in nowadays' business innovations. Besides, we also provide valuable managerial insights for business runners who are interested in this \"young\" market of crowdsourcing businesses.","abstract_html":"In this work, we focus on two attractive crowd-based business models, i.e., user-generated content creation and freight-matching long-haul trucking. First, as elaborated in CHAPTER 2, we consider a game theoretical modeling approach for understanding the operation of non-profit UGC platforms that rely on users to create content and maintain financial sustainability. In particular, we examine several interesting research questions with practical importance and unique contributions to the literature. These research questions mainly investigate how changes in critical business factors influence the platforms' strategic effort allocation, user participation, and overall performance. Second, in CHAPTER 3, we focus on the flourishing freight-matching businesses that rely on crowdsourced drivers for long-haul trucking. In particular, although the practice suggests that shippers' ordering behaviors of freight-matching services may remarkably impact crowdsourced drivers' bidding behaviors, the literature has yet to examine this issue formally. Therefore, we collect industrial data and construct a strict empirical schema for understanding the association between shippers' order timing and freight-matching performance. Besides, by deliberately building a theoretical modeling framework and using a data-driven estimation of model parameters, we are able to simulate the freight-matching performance of adopting our empirical findings and evaluate the practical value of our study. By investigating these two prominent business models, we aim to understand the advantages of crowdsourcing businesses and the role of crowds in nowadays' business innovations. Besides, we also provide valuable managerial insights for business runners who are interested in this "young" market of crowdsourcing businesses.","abstract_has_math":false,"creators":["Dong, Ziqi"],"institution":"Temple University. 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Therefore, we collect industrial data and construct a strict empirical schema for understanding the association between shippers' order timing and freight-matching performance. Besides, by deliberately building a theoretical modeling framework and using a data-driven estimation of model parameters, we are able to simulate the freight-matching performance of adopting our empirical findings and evaluate the practical value of our study. By investigating these two prominent business models, we aim to understand the advantages of crowdsourcing businesses and the role of crowds in nowadays' business innovations. Besides, we also provide valuable managerial insights for business runners who are interested in this \"young\" market of crowdsourcing businesses."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Ph.D."]},{"key":"dc:title","label":"Title","values":["THE POWER OF CROWD IN THE BUSINESS WORLD"]}]}],"canonical_facts":{"dc:contributor.advisor":["Kong, Guangwen"],"dc:contributor.committeemember":["Kumar, Subodha","Roy, Abhishek","Ayabakan, Sezgin"],"dc:creator":["Dong, Ziqi"],"dc:date.accessioned":["2024-09-12T19:28:47Z"],"dc:date.available":["2024-09-12T19:28:47Z"],"dc:date.issued":["2024-08"],"dc:description.abstract":["In this work, we focus on two attractive crowd-based business models, i.e., user-generated content creation and freight-matching long-haul trucking. 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