Many e-commerce firms provide live-chat capability on their Web sites to promote product sales and to offer customer support. With increasing traffic on e-commerce Web sites, providing such live-chat services requires a good allocation of service resources to serve the customers. When resources are limited, firms may consider employing priority-processing and reserving resources for high-value customers. In this article, we model a reserve-based priority-processing policy for e-commerce systems that have imperfect customer classification. Two policy decisions considered in the model are: (1) the number of agents exclusively reserved for high-value customers, and (2) the configuration of the classification system. We derive explicit expressions for average waiting times of high-value and low-value customer classes and define a total waiting cost function. Through numerical analysis, we study the impact of these two policy decisions on average waiting times and total waiting costs. Our analysis finds that reserving agents for high-value customers may have negative consequences for such customers under imperfect classification. Further, we study the interaction between the two policy decisions and discuss how one decision should be modified with respect to a change in the other one in order to keep the waiting costs minimized.
{"title":"Live-chat agent assignments to heterogeneous e-customers under imperfect classification","authors":"Paulo B. Góes, N. Ilk, Wei T. Yue, J. Leon Zhao","doi":"10.1145/2070710.2070715","DOIUrl":"https://doi.org/10.1145/2070710.2070715","url":null,"abstract":"Many e-commerce firms provide live-chat capability on their Web sites to promote product sales and to offer customer support. With increasing traffic on e-commerce Web sites, providing such live-chat services requires a good allocation of service resources to serve the customers. When resources are limited, firms may consider employing priority-processing and reserving resources for high-value customers. In this article, we model a reserve-based priority-processing policy for e-commerce systems that have imperfect customer classification. Two policy decisions considered in the model are: (1) the number of agents exclusively reserved for high-value customers, and (2) the configuration of the classification system. We derive explicit expressions for average waiting times of high-value and low-value customer classes and define a total waiting cost function. Through numerical analysis, we study the impact of these two policy decisions on average waiting times and total waiting costs. Our analysis finds that reserving agents for high-value customers may have negative consequences for such customers under imperfect classification. Further, we study the interaction between the two policy decisions and discuss how one decision should be modified with respect to a change in the other one in order to keep the waiting costs minimized.","PeriodicalId":178565,"journal":{"name":"ACM Trans. Manag. Inf. Syst.","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128480263","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}
The rise of social media has fundamentally changed the way information is produced, disseminated, and consumed in the digital age, which has profound economic and business effects. Among many different types of social media, social broadcasting networks such as Twitter in the U.S. and “Weibo” in China are particularly interesting from a business perspective. In the case of Twitter, the huge amounts of real-time data with extremely rich text, along with valuable structural information, makes Twitter a great platform to build Business Intelligence (BI) systems. We propose a framework of social-broadcasting-based BI systems that utilizes real-time information extracted from these data with text mining techniques. To demonstrate this framework, we designed and implemented a Twitter-based BI system that forecasts movie box office revenues during the opening weekend and forecasts daily revenue after 4 weeks. We found that incorporating information from Twitter could reduce the Mean Absolute Percentage Error (MAPE) by 44% for the opening weekend and by 36% for total revenue. For daily revenue forecasting, including Twitter information into a baseline model could reduce forecasting errors by 17.5% on average. On the basis of these results, we conclude that social-broadcasting-based BI systems have great potential and should be explored by both researchers and practitioners.
{"title":"Designing a social-broadcasting-based business intelligence system","authors":"Huaxia Rui, Andrew Whinston","doi":"10.1145/2070710.2070713","DOIUrl":"https://doi.org/10.1145/2070710.2070713","url":null,"abstract":"The rise of social media has fundamentally changed the way information is produced, disseminated, and consumed in the digital age, which has profound economic and business effects. Among many different types of social media, social broadcasting networks such as Twitter in the U.S. and “Weibo” in China are particularly interesting from a business perspective. In the case of Twitter, the huge amounts of real-time data with extremely rich text, along with valuable structural information, makes Twitter a great platform to build Business Intelligence (BI) systems. We propose a framework of social-broadcasting-based BI systems that utilizes real-time information extracted from these data with text mining techniques. To demonstrate this framework, we designed and implemented a Twitter-based BI system that forecasts movie box office revenues during the opening weekend and forecasts daily revenue after 4 weeks. We found that incorporating information from Twitter could reduce the Mean Absolute Percentage Error (MAPE) by 44% for the opening weekend and by 36% for total revenue. For daily revenue forecasting, including Twitter information into a baseline model could reduce forecasting errors by 17.5% on average. On the basis of these results, we conclude that social-broadcasting-based BI systems have great potential and should be explored by both researchers and practitioners.","PeriodicalId":178565,"journal":{"name":"ACM Trans. Manag. Inf. Syst.","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131329133","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}
In December of 2009, several founders of the Information Systems (IS) academic discipline gathered for a panel discussion at the International Conference on Information Systems to present their visions for the future of the field, and their comments were summarized in the inaugural issue of TMIS [Davis et al., 2010; J. F. J. Nunamaker et al., 1991]. To assure a robust future, they argued, IS journals, conferences, reviewers, promotion committees, teachers, researchers, and curriculum developers must broaden the scope of IS. This article explores the need for a broader vision to drive future development of the IS discipline.
2009年12月，信息系统(IS)学科的几位创始人聚集在国际信息系统会议上进行小组讨论，展示了他们对该领域未来的愿景，他们的评论被总结在TMIS的创刊号中[Davis et al.， 2010;[j].武汉大学学报(自然科学版)。他们认为，为了确保一个强大的未来，信息系统期刊、会议、审稿人、推广委员会、教师、研究人员和课程开发者必须扩大信息系统的范围。本文探讨了需要一个更广阔的视野来推动信息系统学科的未来发展。
{"title":"Toward a broader vision for Information Systems","authors":"J. Nunamaker, R. Briggs","doi":"10.1145/2070710.2070711","DOIUrl":"https://doi.org/10.1145/2070710.2070711","url":null,"abstract":"In December of 2009, several founders of the Information Systems (IS) academic discipline gathered for a panel discussion at the International Conference on Information Systems to present their visions for the future of the field, and their comments were summarized in the inaugural issue of TMIS [Davis et al., 2010; J. F. J. Nunamaker et al., 1991]. To assure a robust future, they argued, IS journals, conferences, reviewers, promotion committees, teachers, researchers, and curriculum developers must broaden the scope of IS. This article explores the need for a broader vision to drive future development of the IS discipline.","PeriodicalId":178565,"journal":{"name":"ACM Trans. Manag. Inf. Syst.","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115130115","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 research addresses complexities inherent in dynamic decision making settings represented by global disasters such as influenza pandemics. By coupling a theoretically grounded Equation-Based Modeling (EBM) approach with more practically nuanced Agent-Based Modeling (ABM) approach we address the inherent heterogeneity of the “influenza pandemic” decision space more effectively. In addition to modeling contributions, results and findings of this study have three important policy implications for pandemic containment; first, an effective way of checking the progression of a pandemic is a multipronged approach that includes a combination of pharmaceutical and non-pharmaceutical interventions. Second, mutual aid is effective only when regions that have been affected by the pandemic are sufficiently isolated from other regions through non-pharmaceutical interventions. When regions are not sufficiently isolated, mutual aid can in fact be detrimental. Finally, intraregion non-pharmaceutical interventions such as school closures are more effective than interregion nonpharmaceutical interventions such as border closures.
{"title":"Decision support for containing pandemic propagation","authors":"Hina Arora, T. S. Raghu, A. Vinze","doi":"10.1145/2070710.2070714","DOIUrl":"https://doi.org/10.1145/2070710.2070714","url":null,"abstract":"This research addresses complexities inherent in dynamic decision making settings represented by global disasters such as influenza pandemics. By coupling a theoretically grounded Equation-Based Modeling (EBM) approach with more practically nuanced Agent-Based Modeling (ABM) approach we address the inherent heterogeneity of the “influenza pandemic” decision space more effectively. In addition to modeling contributions, results and findings of this study have three important policy implications for pandemic containment; first, an effective way of checking the progression of a pandemic is a multipronged approach that includes a combination of pharmaceutical and non-pharmaceutical interventions. Second, mutual aid is effective only when regions that have been affected by the pandemic are sufficiently isolated from other regions through non-pharmaceutical interventions. When regions are not sufficiently isolated, mutual aid can in fact be detrimental. Finally, intraregion non-pharmaceutical interventions such as school closures are more effective than interregion nonpharmaceutical interventions such as border closures.","PeriodicalId":178565,"journal":{"name":"ACM Trans. Manag. Inf. Syst.","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128953991","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}
The quality of Wikipedia articles is debatable. On the one hand, existing research indicates that not only are people willing to contribute articles but the quality of these articles is close to that found in conventional encyclopedias. On the other hand, the public has never stopped criticizing the quality of Wikipedia articles, and critics never have trouble finding low-quality Wikipedia articles. Why do Wikipedia articles vary widely in quality? We investigate the relationship between collaboration and Wikipedia article quality. We show that the quality of Wikipedia articles is not only dependent on the different types of contributors but also on how they collaborate. Based on an empirical study, we classify contributors based on their roles in editing individual Wikipedia articles. We identify various patterns of collaboration based on the provenance or, more specifically, who does what to Wikipedia articles. Our research helps identify collaboration patterns that are preferable or detrimental for article quality, thus providing insights for designing tools and mechanisms to improve the quality of Wikipedia articles.
{"title":"Who does what: Collaboration patterns in the wikipedia and their impact on article quality","authors":"Jun Liu, S. Ram","doi":"10.1145/1985347.1985352","DOIUrl":"https://doi.org/10.1145/1985347.1985352","url":null,"abstract":"The quality of Wikipedia articles is debatable. On the one hand, existing research indicates that not only are people willing to contribute articles but the quality of these articles is close to that found in conventional encyclopedias. On the other hand, the public has never stopped criticizing the quality of Wikipedia articles, and critics never have trouble finding low-quality Wikipedia articles. Why do Wikipedia articles vary widely in quality? We investigate the relationship between collaboration and Wikipedia article quality. We show that the quality of Wikipedia articles is not only dependent on the different types of contributors but also on how they collaborate. Based on an empirical study, we classify contributors based on their roles in editing individual Wikipedia articles. We identify various patterns of collaboration based on the provenance or, more specifically, who does what to Wikipedia articles. Our research helps identify collaboration patterns that are preferable or detrimental for article quality, thus providing insights for designing tools and mechanisms to improve the quality of Wikipedia articles.","PeriodicalId":178565,"journal":{"name":"ACM Trans. Manag. Inf. Syst.","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129807159","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}
Quantitative assessments of researchers' productivity and impacts are crucial for the information systems (IS) discipline. Motivated by its growing popularity and expanding use, we offer a perspective on the h index, which refers to the number of papers a researcher has coauthored with at least h citations each. We studied a partial list of 232 top IS researchers who received doctoral degrees between 1957 and 2003 and chose Google Scholar as the source for our analyses. At the individual level, we attempted to identify some of the most productive, high-impact researchers, as well as those who exhibited impressive paces of productivity. At the institution level, we revealed some institutions with relatively more productive researchers, as well as institutions that had produced more productive researchers. We also analyzed the overall IS community by examining the primary research areas of productive scholars identified by our analyses. We then compared their h index scores with those of top scholars in several related disciplines
{"title":"Analyzing information systems researchers' productivity and impacts: A perspective on the H index","authors":"P. H. Hu, Hsinchun Chen","doi":"10.1145/1985347.1985348","DOIUrl":"https://doi.org/10.1145/1985347.1985348","url":null,"abstract":"Quantitative assessments of researchers' productivity and impacts are crucial for the information systems (IS) discipline. Motivated by its growing popularity and expanding use, we offer a perspective on the h index, which refers to the number of papers a researcher has coauthored with at least h citations each. We studied a partial list of 232 top IS researchers who received doctoral degrees between 1957 and 2003 and chose Google Scholar as the source for our analyses. At the individual level, we attempted to identify some of the most productive, high-impact researchers, as well as those who exhibited impressive paces of productivity. At the institution level, we revealed some institutions with relatively more productive researchers, as well as institutions that had produced more productive researchers. We also analyzed the overall IS community by examining the primary research areas of productive scholars identified by our analyses. We then compared their h index scores with those of top scholars in several related disciplines","PeriodicalId":178565,"journal":{"name":"ACM Trans. Manag. Inf. Syst.","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128573913","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}
D. McKnight, Michelle Carter, J. Thatcher, Paul F. Clay
Trust plays an important role in many Information Systems (IS)-enabled situations. Most IS research employs trust as a measure of interpersonal or person-to-firm relations, such as trust in a Web vendor or a virtual team member. Although trust in other people is important, this article suggests that trust in the Information Technology (IT) itself also plays a role in shaping IT-related beliefs and behavior. To advance trust and technology research, this article presents a set of trust in technology construct definitions and measures. We also empirically examine these construct measures using tests of convergent, discriminant, and nomological validity. This study contributes to the literature by providing: (a) a framework that differentiates trust in technology from trust in people, (b) a theory-based set of definitions necessary for investigating different kinds of trust in technology, and (c) validated trust in technology measures useful to research and practice.
{"title":"Trust in a specific technology: An investigation of its components and measures","authors":"D. McKnight, Michelle Carter, J. Thatcher, Paul F. Clay","doi":"10.1145/1985347.1985353","DOIUrl":"https://doi.org/10.1145/1985347.1985353","url":null,"abstract":"Trust plays an important role in many Information Systems (IS)-enabled situations. Most IS research employs trust as a measure of interpersonal or person-to-firm relations, such as trust in a Web vendor or a virtual team member. Although trust in other people is important, this article suggests that trust in the Information Technology (IT) itself also plays a role in shaping IT-related beliefs and behavior. To advance trust and technology research, this article presents a set of trust in technology construct definitions and measures. We also empirically examine these construct measures using tests of convergent, discriminant, and nomological validity. This study contributes to the literature by providing: (a) a framework that differentiates trust in technology from trust in people, (b) a theory-based set of definitions necessary for investigating different kinds of trust in technology, and (c) validated trust in technology measures useful to research and practice.","PeriodicalId":178565,"journal":{"name":"ACM Trans. Manag. Inf. Syst.","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132451539","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}
We introduce a novel dataset with a news sentiment index that was constructed from a selection of over 300,000 newspaper articles from five of the top ten U.S. newspapers by circulation. By constructing ARMA models, we show that news and consumer sentiment, when combined with other macroeconomic variables, achieve statistically significant results to explain changes in private consumption. We make three distinct findings with respect to sentiment in consumption behavior models: first, both consumer and news sentiment add explanatory power and statistical significance to conventional consumer behavior models. Second, consumer sentiment, measured by the University of Michigan Index of Consumer Sentiment, adds more explanatory power and statistical significance than news sentiment when tested individually. Third, news sentiment is able to determine the signs of all coefficients in the model correctly, whereas consumer sentiment does not. In general, we conclude that news sentiment is a useful variable to add in consumer behavior models, especially when coupled with consumer sentiment and other macroeconomic variables. Tested individually, news sentiment is as good a proxy as personal income for explaining private consumption growth when tested individually.
{"title":"Explaining U.S. consumer behavior with news sentiment","authors":"Matthias W. Uhl","doi":"10.1145/1985347.1985350","DOIUrl":"https://doi.org/10.1145/1985347.1985350","url":null,"abstract":"We introduce a novel dataset with a news sentiment index that was constructed from a selection of over 300,000 newspaper articles from five of the top ten U.S. newspapers by circulation. By constructing ARMA models, we show that news and consumer sentiment, when combined with other macroeconomic variables, achieve statistically significant results to explain changes in private consumption. We make three distinct findings with respect to sentiment in consumption behavior models: first, both consumer and news sentiment add explanatory power and statistical significance to conventional consumer behavior models. Second, consumer sentiment, measured by the University of Michigan Index of Consumer Sentiment, adds more explanatory power and statistical significance than news sentiment when tested individually. Third, news sentiment is able to determine the signs of all coefficients in the model correctly, whereas consumer sentiment does not. In general, we conclude that news sentiment is a useful variable to add in consumer behavior models, especially when coupled with consumer sentiment and other macroeconomic variables. Tested individually, news sentiment is as good a proxy as personal income for explaining private consumption growth when tested individually.","PeriodicalId":178565,"journal":{"name":"ACM Trans. Manag. Inf. Syst.","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114895050","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}
Internet storage services allow businesses to move away from maintaining their own internal storage networks. Service providers currently follow a utility pricing model which translates to them absorbing all the risk that arises from the fluctuating storage needs of their customers. The risk borne by the Internet storage service providers has large revenue implications as Internet startups and smaller companies, which face significant demand stochasticity, constitute an important segment of their clientele. We develop an option pricing mechanism to hedge against this risk and evaluate its effectiveness vis-à-vis forward contracts. We obtain the conditions under which options dominate forward contracts and the trade-offs involved when the provider has to decide on appropriate pricing mechanisms. Our empirical study uses publicly obtainable traffic data of Amazon S3 clients to validate the analytical results. We show that providers can significantly benefit from including options in their risk-hedging portfolio, especially when there is less variation in the costs faced by the buyers in building their own data networks as opposed to using cloud services.
{"title":"Risk hedging in storage grid markets: Do options add value to forwards?","authors":"Anna Ye Du, Sanjukta Das, R. Gopal, R. Ramesh","doi":"10.1145/1985347.1985351","DOIUrl":"https://doi.org/10.1145/1985347.1985351","url":null,"abstract":"Internet storage services allow businesses to move away from maintaining their own internal storage networks. Service providers currently follow a utility pricing model which translates to them absorbing all the risk that arises from the fluctuating storage needs of their customers. The risk borne by the Internet storage service providers has large revenue implications as Internet startups and smaller companies, which face significant demand stochasticity, constitute an important segment of their clientele. We develop an option pricing mechanism to hedge against this risk and evaluate its effectiveness vis-à-vis forward contracts. We obtain the conditions under which options dominate forward contracts and the trade-offs involved when the provider has to decide on appropriate pricing mechanisms. Our empirical study uses publicly obtainable traffic data of Amazon S3 clients to validate the analytical results. We show that providers can significantly benefit from including options in their risk-hedging portfolio, especially when there is less variation in the costs faced by the buyers in building their own data networks as opposed to using cloud services.","PeriodicalId":178565,"journal":{"name":"ACM Trans. Manag. Inf. Syst.","volume":"148 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120981662","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. Bhattacharjee, R. Gopal, J. Marsden, R. Sankaranarayanan
This research commentary examines the changing landscape of digital goods, and discusses important emerging issues for IS researchers to explore. We begin with a discussion of the major technological milestones that have shaped digital goods industries such as music, movies, software, books, video games, and recently emerging digital goods. Our emphasis is on economic and legal issues, rather than on design science or sociological issues. We explore how research has been influenced by the major technological milestones and discuss the major findings of prior research. Based on this, we offer a roadmap for future researchers to explore the emergent changes in the digital goods arena, covering different aspects of digital goods industries such as risk management, value chain, legal aspects, transnational and cross-cultural issues.
{"title":"Digital goods and markets: Emerging issues and challenges","authors":"S. Bhattacharjee, R. Gopal, J. Marsden, R. Sankaranarayanan","doi":"10.1145/1985347.1985349","DOIUrl":"https://doi.org/10.1145/1985347.1985349","url":null,"abstract":"This research commentary examines the changing landscape of digital goods, and discusses important emerging issues for IS researchers to explore. We begin with a discussion of the major technological milestones that have shaped digital goods industries such as music, movies, software, books, video games, and recently emerging digital goods. Our emphasis is on economic and legal issues, rather than on design science or sociological issues. We explore how research has been influenced by the major technological milestones and discuss the major findings of prior research. Based on this, we offer a roadmap for future researchers to explore the emergent changes in the digital goods arena, covering different aspects of digital goods industries such as risk management, value chain, legal aspects, transnational and cross-cultural issues.","PeriodicalId":178565,"journal":{"name":"ACM Trans. Manag. Inf. Syst.","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130720707","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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