{"title":"Design Rules Volume 2 Chapter 21—Capturing Value via Strategic Bottlenecks in Digital Exchange Platforms","authors":"Carliss Y. Baldwin","doi":"10.2139/ssrn.3909098","DOIUrl":null,"url":null,"abstract":"The purpose of this chapter is to use value structure analysis to better understand how sponsors of digital exchange platforms capture value and maintain strategic bottlenecks. I begin by describing the three core technological processes that lie at the heart of all digital exchange platforms: (1) search and ad placement; (2) dynamic pricing; and (3) data analysis and prediction. These processes are carried out automatically and at high speed by computerized algorithms. The algorithms consist of steps, all of which are essential to the successful completion of a transaction or transmission of a message. However, bottlenecks are inevitable any synchronized multi-step flow process. The platform sponsor’s first responsibility is thus to resolve bottlenecks in its core processes when and where they arise. One of an exchange platform’s critical core processes is to generate predictions as to what the user would like to see and/or purchase. Better predictions speed up the flow and reduce the unproductive time users spend on the platform. Thus to be competitive today, platform sponsors must have the ability to gather data, generate predictions and test hypotheses within time intervals measured in milliseconds. Predictions can be improved by tracking individuals’ behavior online, but only at the cost of reducing their privacy. The inevitable tension between performance and privacy has yet to be resolved. The chapter goes on to discuss how platform sponsors can “lock-in” members of an ecosystem through a combination of visible instructions, data storage, and specific inertia. It concludes by describing successful and unsuccessful attempts to disintermediate exchange platforms.","PeriodicalId":288317,"journal":{"name":"International Political Economy: Globalization eJournal","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Political Economy: Globalization eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3909098","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The purpose of this chapter is to use value structure analysis to better understand how sponsors of digital exchange platforms capture value and maintain strategic bottlenecks. I begin by describing the three core technological processes that lie at the heart of all digital exchange platforms: (1) search and ad placement; (2) dynamic pricing; and (3) data analysis and prediction. These processes are carried out automatically and at high speed by computerized algorithms. The algorithms consist of steps, all of which are essential to the successful completion of a transaction or transmission of a message. However, bottlenecks are inevitable any synchronized multi-step flow process. The platform sponsor’s first responsibility is thus to resolve bottlenecks in its core processes when and where they arise. One of an exchange platform’s critical core processes is to generate predictions as to what the user would like to see and/or purchase. Better predictions speed up the flow and reduce the unproductive time users spend on the platform. Thus to be competitive today, platform sponsors must have the ability to gather data, generate predictions and test hypotheses within time intervals measured in milliseconds. Predictions can be improved by tracking individuals’ behavior online, but only at the cost of reducing their privacy. The inevitable tension between performance and privacy has yet to be resolved. The chapter goes on to discuss how platform sponsors can “lock-in” members of an ecosystem through a combination of visible instructions, data storage, and specific inertia. It concludes by describing successful and unsuccessful attempts to disintermediate exchange platforms.