Data-analytics technology can accelerate the innovation process by enabling existing knowledge to be identified, accessed, combined, and deployed to address new problem domains. However, like prior...
{"title":"Data Analytics Supports Decentralized Innovation","authors":"Lynn Wu, Bowen Lou, L. Hitt","doi":"10.2139/ssrn.3351982","DOIUrl":"https://doi.org/10.2139/ssrn.3351982","url":null,"abstract":"Data-analytics technology can accelerate the innovation process by enabling existing knowledge to be identified, accessed, combined, and deployed to address new problem domains. However, like prior...","PeriodicalId":11062,"journal":{"name":"Development of Innovation eJournal","volume":"83 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85118785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract We model and experimentally evaluate the trade-off between innovation and imitation commonly faced by firms. Innovation involves searching for a high payoff opportunity, but paying a cost in order to do so. Imitation involves avoiding that search cost and copying the most successful payoff opportunity uncovered thus far. We formulate a novel model of sequential innovation versus imitation decisions made by a group of n regret minimizing agents. We analyze the consequences of complete versus incomplete information about the distribution of payoffs from innovation on agents’ decisions. We then study these predictions in a laboratory experiment where we find evidence in support of our theoretical predictions.
{"title":"Innovate Versus Imitate: Theory and Experimental Evidence","authors":"J. Duffy, Jason Ralston","doi":"10.2139/ssrn.3359870","DOIUrl":"https://doi.org/10.2139/ssrn.3359870","url":null,"abstract":"Abstract We model and experimentally evaluate the trade-off between innovation and imitation commonly faced by firms. Innovation involves searching for a high payoff opportunity, but paying a cost in order to do so. Imitation involves avoiding that search cost and copying the most successful payoff opportunity uncovered thus far. We formulate a novel model of sequential innovation versus imitation decisions made by a group of n regret minimizing agents. We analyze the consequences of complete versus incomplete information about the distribution of payoffs from innovation on agents’ decisions. We then study these predictions in a laboratory experiment where we find evidence in support of our theoretical predictions.","PeriodicalId":11062,"journal":{"name":"Development of Innovation eJournal","volume":"40 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82951861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Companies and other private institutions see great and promising profits in the use of automated decision-making (‘ADM’) for commercial-, financial- or efficiency in work processing purposes. Meanwhile, ADM based on a data subjects’ personal data may (severely) impact its fundamental rights and freedoms. The General Data Protection Regulation (GDPR) provides for a regulatory framework that applies whenever a controller considers and deploys ADM onto individuals on the basis of their personal data. In the design stage of the intended ADM, article 35 (3)(a) obliges a controller to apply a Data Protection Impact Assessment (DPIA), part of which is an assessment of ADM’s impact on individual rights and freedoms. Article 22 GDPR determines under what conditions ADM is allowed and endows data subjects with increased protection. Research among companies of various sizes has shown that there is (legal) insecurity about the interpretation of the GDPR (including the provisions relevant to ADM). The first objective of the author is to detect ways forward by offering practical handles to execute a DPIA that includes a slidable assessment of impacts on data subjects’ fundamental rights. This assessment is based on four benchmarks that should help to assess the gravity of potential impacts, i.e. i) to determine the impact on the fundamental right(s) at stake, ii) to establish the context in which the ADM is used, iii) the establishment of who is beneficiary of the use of personal data in the ADM and iv) the establishment who is in control over the data flows in the ADM. From the benchmarks an overall fundamental rights impact assessment about ADM should arise. A second objective is to indicate potential factors and measures that a controller should consider in its risk management after the assessment. The proposed approach should help fostering fair, compliant and trustworthy ADM and contains directions for future research.
{"title":"Detecting New Approaches for a Fundamental Rights Impact Assessment to Automated Decision-Making","authors":"H. Janssen","doi":"10.2139/ssrn.3302839","DOIUrl":"https://doi.org/10.2139/ssrn.3302839","url":null,"abstract":"Companies and other private institutions see great and promising profits in the use of automated decision-making (‘ADM’) for commercial-, financial- or efficiency in work processing purposes. Meanwhile, ADM based on a data subjects’ personal data may (severely) impact its fundamental rights and freedoms. The General Data Protection Regulation (GDPR) provides for a regulatory framework that applies whenever a controller considers and deploys ADM onto individuals on the basis of their personal data. In the design stage of the intended ADM, article 35 (3)(a) obliges a controller to apply a Data Protection Impact Assessment (DPIA), part of which is an assessment of ADM’s impact on individual rights and freedoms. Article 22 GDPR determines under what conditions ADM is allowed and endows data subjects with increased protection. \u0000 \u0000Research among companies of various sizes has shown that there is (legal) insecurity about the interpretation of the GDPR (including the provisions relevant to ADM). The first objective of the author is to detect ways forward by offering practical handles to execute a DPIA that includes a slidable assessment of impacts on data subjects’ fundamental rights. This assessment is based on four benchmarks that should help to assess the gravity of potential impacts, i.e. i) to determine the impact on the fundamental right(s) at stake, ii) to establish the context in which the ADM is used, iii) the establishment of who is beneficiary of the use of personal data in the ADM and iv) the establishment who is in control over the data flows in the ADM. From the benchmarks an overall fundamental rights impact assessment about ADM should arise. A second objective is to indicate potential factors and measures that a controller should consider in its risk management after the assessment. The proposed approach should help fostering fair, compliant and trustworthy ADM and contains directions for future research.","PeriodicalId":11062,"journal":{"name":"Development of Innovation eJournal","volume":"56 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80208207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper examines the likely impact of the development of digital technologies on the future of employment.
本文探讨了数字技术的发展对未来就业的可能影响。
{"title":"Digital Technologies and the Future of Employment","authors":"Joseph Tham","doi":"10.2139/ssrn.3296213","DOIUrl":"https://doi.org/10.2139/ssrn.3296213","url":null,"abstract":"This paper examines the likely impact of the development of digital technologies on the future of employment.","PeriodicalId":11062,"journal":{"name":"Development of Innovation eJournal","volume":"28 2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73352710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Artificial intelligence (AI) is about imbuing machines with a kind of intelligence that is mainly attributed to humans. Extant literature—coupled with our experiences as practitioners—suggests that while AI may not be ready to completely take over highly creative tasks within the innovation process, it shows promise as a significant support to innovation managers. In this article, we broadly refer to the derivation of computer-enabled, data-driven insights, models, and visualizations within the innovation process as innovation analytics. AI can play a key role in the innovation process by driving multiple aspects of innovation analytics. We present four different case studies of AI in action based on our previous work in the field. We highlight benefits and limitations of using AI in innovation and conclude with strategic implications and additional resources for innovation managers.
{"title":"Innovation Analytics: Leveraging Artificial Intelligence in the Innovation Process","authors":"Chinmay Kakatkar, Volker Bilgram, J. Füller","doi":"10.2139/ssrn.3293533","DOIUrl":"https://doi.org/10.2139/ssrn.3293533","url":null,"abstract":"Artificial intelligence (AI) is about imbuing machines with a kind of intelligence that is mainly attributed to humans. Extant literature—coupled with our experiences as practitioners—suggests that while AI may not be ready to completely take over highly creative tasks within the innovation process, it shows promise as a significant support to innovation managers. In this article, we broadly refer to the derivation of computer-enabled, data-driven insights, models, and visualizations within the innovation process as innovation analytics. AI can play a key role in the innovation process by driving multiple aspects of innovation analytics. We present four different case studies of AI in action based on our previous work in the field. We highlight benefits and limitations of using AI in innovation and conclude with strategic implications and additional resources for innovation managers.","PeriodicalId":11062,"journal":{"name":"Development of Innovation eJournal","volume":"35 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83773464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
E-procurement platforms facilitate transactions between suppliers and buyers from all over the world. Over time, suppliers and buyers may develop familiarity from prior experience with earlier transactions. The project team literature has established that prior experience leads to better project performance. In this study, we examine the effectiveness of prior experience between buyers and suppliers in e-procurement platforms with a focus on the moderating roles of temporal distance and language difference between the buyer and the supplier as well as the effect of routine tasks in the project (termed “task routinization”). Using a unique data set from a large e-procurement platform, Freelancer.com, we first find that buyers’ prior experience with a supplier positively affects project outcomes, and temporal distance and language difference both negatively affect project outcomes. This is consistent with previous findings for emerging e-procurement platforms. More interestingly, we find that the effectiveness of prior experience is constrained by both temporal distance and language difference, such that if a greater temporal distance separates the buyer and supplier or if the two speak different languages, prior experience is less likely to be helpful. In addition, while task routinization does not directly affect a project’s success, it has a positive interaction effect with prior experience, suggesting that buyers’ prior experience with a supplier is more effective in enhancing project outcomes when a project comprises routine tasks. Our findings on prior experience, temporal distance, language difference, and task routinization contribute to a better understanding of the e-procurement platform for global outsourcing and procurement. Limitations are discussed and topics are identified for future research.
{"title":"Effectiveness of Buyer-Supplier Prior Experience on E-Procurement Platforms","authors":"Y. Hong, Benjamin B. M. Shao","doi":"10.2139/ssrn.3294028","DOIUrl":"https://doi.org/10.2139/ssrn.3294028","url":null,"abstract":"E-procurement platforms facilitate transactions between suppliers and buyers from all over the world. Over time, suppliers and buyers may develop familiarity from prior experience with earlier transactions. The project team literature has established that prior experience leads to better project performance. In this study, we examine the effectiveness of prior experience between buyers and suppliers in e-procurement platforms with a focus on the moderating roles of temporal distance and language difference between the buyer and the supplier as well as the effect of routine tasks in the project (termed “task routinization”). Using a unique data set from a large e-procurement platform, Freelancer.com, we first find that buyers’ prior experience with a supplier positively affects project outcomes, and temporal distance and language difference both negatively affect project outcomes. This is consistent with previous findings for emerging e-procurement platforms. More interestingly, we find that the effectiveness of prior experience is constrained by both temporal distance and language difference, such that if a greater temporal distance separates the buyer and supplier or if the two speak different languages, prior experience is less likely to be helpful. In addition, while task routinization does not directly affect a project’s success, it has a positive interaction effect with prior experience, suggesting that buyers’ prior experience with a supplier is more effective in enhancing project outcomes when a project comprises routine tasks. Our findings on prior experience, temporal distance, language difference, and task routinization contribute to a better understanding of the e-procurement platform for global outsourcing and procurement. Limitations are discussed and topics are identified for future research.","PeriodicalId":11062,"journal":{"name":"Development of Innovation eJournal","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85105303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. K. Bagheri, Parya Raoufi, Mojgan Samandar Ali Eshtehardi, Saeed Shaverdy, Bahram Ramezani Akbarabad, B. Moghaddam, A. Mardani
On November 15, 2015, Digikala, one of the largest online stores in the Middle East, launched its first‐ever crowdsourcing contest called ‘A glance at tomorrow’. What distinguishes this contest from common crowd‐based initiatives is that it was aimed at Business Model Innovation (BMI) rather than product and process innovation. Although using the crowd has proven to be an effective way for firms to boost their product and process innovation, its use for BMI is challenging. Based on real large‐scale data from the Digikala’s crowdsourcing contest, this research focuses on the application of crowd‐powered solutions in BMI, which has rarely been investigated previously. Our exploratory case study indicates that the crowd could contribute to the BMI process. Our findings point to a new form of ‘division of innovation labor’ in BMI. Contribution of the crowd in BMI is more likely to be relevant to Value Proposition and Value Delivery, while it might be less relevant to Value Capture and Value Creation. The results also support the notion that crowd‐contributor characteristics affect the quality of proposals for BMI. We argue that this line of research could help companies design and implement customized crowd‐based initiatives to better support their BMI process.
{"title":"Using the Crowd for Business Model Innovation: The Case of Digikala","authors":"S. K. Bagheri, Parya Raoufi, Mojgan Samandar Ali Eshtehardi, Saeed Shaverdy, Bahram Ramezani Akbarabad, B. Moghaddam, A. Mardani","doi":"10.1111/radm.12353","DOIUrl":"https://doi.org/10.1111/radm.12353","url":null,"abstract":"On November 15, 2015, Digikala, one of the largest online stores in the Middle East, launched its first‐ever crowdsourcing contest called ‘A glance at tomorrow’. What distinguishes this contest from common crowd‐based initiatives is that it was aimed at Business Model Innovation (BMI) rather than product and process innovation. Although using the crowd has proven to be an effective way for firms to boost their product and process innovation, its use for BMI is challenging. Based on real large‐scale data from the Digikala’s crowdsourcing contest, this research focuses on the application of crowd‐powered solutions in BMI, which has rarely been investigated previously. Our exploratory case study indicates that the crowd could contribute to the BMI process. Our findings point to a new form of ‘division of innovation labor’ in BMI. Contribution of the crowd in BMI is more likely to be relevant to Value Proposition and Value Delivery, while it might be less relevant to Value Capture and Value Creation. The results also support the notion that crowd‐contributor characteristics affect the quality of proposals for BMI. We argue that this line of research could help companies design and implement customized crowd‐based initiatives to better support their BMI process.","PeriodicalId":11062,"journal":{"name":"Development of Innovation eJournal","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84118374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Face reputation is a nicely-researched region, but one key region now not addressed by means of many traditional strategies is that sensible face identity operates below an “open-universe” assumption wherein a few faces ought to be diagnosed, but no longer others (called distracters). In Bob’s graduation case, satisfactory friends need to be tagged on the same time as distinct faces have to be not noted. The acting face reputation within the presence of blur are based totally definitely on the convolution model and can't cope with non-uniform blurring situations that regularly rise up from tilts and rotations in hand held cameras. In this paper, we recommend a technique for face recognition within the presence of vicinity-diverse motion blur comprising of arbitrarily-original kernels.
We version the blurred face as a convex combination of geometrically transformed times of the centered gallery face, and display that the set of all images acquired through non-uniformly blurring a given image forms a convex set. We first endorse a non uniform blur-sturdy set of rules with the aid of way of using the notion of a sparse virtual digital camera trajectory inside the digital camera movement vicinity to assemble an energy function with l1-norm constraint on the digital camera movement. The framework is then prolonged to deal with illumination variations with the aid of exploiting the reality that the set of all images obtained from a face photo by using manner of non-uniform blurring and converting the illumination paperwork a bi-convex set.
{"title":"Image Reputation of Non-Uniform Blur, Illumination and Pose Using Mobilap","authors":"N. Sumalatha","doi":"10.2139/ssrn.3288365","DOIUrl":"https://doi.org/10.2139/ssrn.3288365","url":null,"abstract":"Face reputation is a nicely-researched region, but one key region now not addressed by means of many traditional strategies is that sensible face identity operates below an “open-universe” assumption wherein a few faces ought to be diagnosed, but no longer others (called distracters). In Bob’s graduation case, satisfactory friends need to be tagged on the same time as distinct faces have to be not noted. The acting face reputation within the presence of blur are based totally definitely on the convolution model and can't cope with non-uniform blurring situations that regularly rise up from tilts and rotations in hand held cameras. In this paper, we recommend a technique for face recognition within the presence of vicinity-diverse motion blur comprising of arbitrarily-original kernels. <br><br>We version the blurred face as a convex combination of geometrically transformed times of the centered gallery face, and display that the set of all images acquired through non-uniformly blurring a given image forms a convex set. We first endorse a non uniform blur-sturdy set of rules with the aid of way of using the notion of a sparse virtual digital camera trajectory inside the digital camera movement vicinity to assemble an energy function with l1-norm constraint on the digital camera movement. The framework is then prolonged to deal with illumination variations with the aid of exploiting the reality that the set of all images obtained from a face photo by using manner of non-uniform blurring and converting the illumination paperwork a bi-convex set.","PeriodicalId":11062,"journal":{"name":"Development of Innovation eJournal","volume":"102 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75720547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper examines the relationship between competition and product development innovation using the U.S. trademark database. We find that greater import competition spurs corporate product innovation measured by newly launched trademarks. However, such increase in foreign competition is associated with lower survival rate of new product trademarks. Moreover, firms tend to launch new trademarks in old and familiar areas in response to intensified import competition. We further show that the negative impact of competition on firm’s future performance is mitigated by product innovation. Our main results are similar when we use common domestic competition measures. Overall, our results suggest that competitive markets can promote product innovation.
{"title":"Competition and Product Development Innovation: The Case of Newly Launched Trademarks","authors":"Qianqian Huang, Bingkun Yang","doi":"10.2139/ssrn.3419613","DOIUrl":"https://doi.org/10.2139/ssrn.3419613","url":null,"abstract":"This paper examines the relationship between competition and product development innovation using the U.S. trademark database. We find that greater import competition spurs corporate product innovation measured by newly launched trademarks. However, such increase in foreign competition is associated with lower survival rate of new product trademarks. Moreover, firms tend to launch new trademarks in old and familiar areas in response to intensified import competition. We further show that the negative impact of competition on firm’s future performance is mitigated by product innovation. Our main results are similar when we use common domestic competition measures. Overall, our results suggest that competitive markets can promote product innovation.","PeriodicalId":11062,"journal":{"name":"Development of Innovation eJournal","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88323735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper is a preliminary attempt to analyze information as a factor of production in international trade. It is a first attempt to get a handle on the direction and balance of information flows. We have obtained quantitative data about Web-related data flows between countries, and we explore how those flows are correlated to trade in goods . Using Telegeography data on “Server Location as a Percentage of Top Websites,” we found that 2/3 of all web traffic is transnational. More than half of the top 100 web sites in 9 of the world’s 13 sub-regions are hosted in the United States. Central Asia and Eastern Europe, for whom 37% and 41% of their most popular websites, respectively, are requested from the US. Even well-developed Western Europe makes almost half of its top 100 web site requests to US-based sites. For US users, on the other hand, only about 26 of the top 100 websites are hosted outside the country, and 20 of them are in Europe.Ironically, East Asia, which has a huge goods trade surplus with the developed economies, particularly with the US, has the largest negative balance in the relationship between incoming and outgoing Web requests. Indeed, we found a very strong negative correlation (-0.878) between web traffic balances and the balance of trade in goods across all subregions. Once these aspects of transnational data flows are quantified, the paper discusses the implications of these findings for policy, especially trade policy. It raises the question whether the goal of a free and open digital economy is best advanced by placing information exchanges in the trade paradigm and pushing for free trade, or by asserting a more general human right to free and open information exchanges across borders, which has social and political as well as economic consequences. These two approaches are not mutually exclusive, of course, but by making these distinctions we clarify the debate over international policy in the digital world.
{"title":"Is It “Trade?�? Data Flows and the Digital Economy","authors":"Milton L. Mueller, Karl Grindal","doi":"10.2139/SSRN.3137819","DOIUrl":"https://doi.org/10.2139/SSRN.3137819","url":null,"abstract":"This paper is a preliminary attempt to analyze information as a factor of production in international trade. It is a first attempt to get a handle on the direction and balance of information flows. We have obtained quantitative data about Web-related data flows between countries, and we explore how those flows are correlated to trade in goods . Using Telegeography data on “Server Location as a Percentage of Top Websites,” we found that 2/3 of all web traffic is transnational. More than half of the top 100 web sites in 9 of the world’s 13 sub-regions are hosted in the United States. Central Asia and Eastern Europe, for whom 37% and 41% of their most popular websites, respectively, are requested from the US. Even well-developed Western Europe makes almost half of its top 100 web site requests to US-based sites. For US users, on the other hand, only about 26 of the top 100 websites are hosted outside the country, and 20 of them are in Europe.Ironically, East Asia, which has a huge goods trade surplus with the developed economies, particularly with the US, has the largest negative balance in the relationship between incoming and outgoing Web requests. Indeed, we found a very strong negative correlation (-0.878) between web traffic balances and the balance of trade in goods across all subregions. Once these aspects of transnational data flows are quantified, the paper discusses the implications of these findings for policy, especially trade policy. It raises the question whether the goal of a free and open digital economy is best advanced by placing information exchanges in the trade paradigm and pushing for free trade, or by asserting a more general human right to free and open information exchanges across borders, which has social and political as well as economic consequences. These two approaches are not mutually exclusive, of course, but by making these distinctions we clarify the debate over international policy in the digital world.","PeriodicalId":11062,"journal":{"name":"Development of Innovation eJournal","volume":"69 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90386788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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