The focus of this research is on the IT service relationships that exist between clients and prov... more The focus of this research is on the IT service relationships that exist between clients and providers in cloud computing. Cloud computing is an important context in IT services management since it has become an increasingly popular delivery model. We use coordination theory and a case study of a cloud computing-based company to investigate how cloud service relationships are managed. Evidence of both the standardized and customized relationships is based on a case study of SiteWit, a new startup company that is both a user and provider of cloud services. This company is an interesting case to study, given the real-time, intensive nature of the technical demands, the multiple service relationships that must be managed, while at the same time minimizing costs.
The corporate bond market is one of the areas that has witnessed profound changes since the last ... more The corporate bond market is one of the areas that has witnessed profound changes since the last financial crisis, prompting regulators (and industry participants) to question its resilience under stress. We are building agent-based models to better understand bond market dynamics using simulations. Simulations offer an intriguing method of capturing the second-order feedback loops that can affect prices under conditions of stress. However, understanding all the data and emergent behaviors from these complex systems remains a difficult challenge. In this paper, we begin investigating visualization and sonification techniques that might help us meet this challenge at both agent (micro) and system-wide (macro) levels, with the goal of assembling an effective mixture of visual elements. Sonification offers a novel way to enrich our visualizations with sound, setting markets to music. An experiment assessing the impact of mutual fund market share on bond market stability provides an int...
This research aims to uncover commercial bank business models through cluster analysis. Detailed ... more This research aims to uncover commercial bank business models through cluster analysis. Detailed regulatory snapshots of bank balance sheet data are used to derive a small set of bank lending features for clustering. These snapshots can be considered chronologically to better understand trends in the banking industry. For instance, the number of commercial banks has dramatically declined from 1980 to 2013 (the window of analysis). In addition, commercial bank business models have become more uniform or homogeneous with respect to lending activities. Characterizing banking business models is part of a larger research initiative focusing on agent-based modeling and simulation of the Federal funds market, as well as the detailed inter-bank lending market. Understanding banking business models is key to populating the agent ecosystem, implementing better behavior models and interpreting the simulation results. Unsupervised learning methods such as cluster analysis are a natural fit for this business model discovery challenge.
Journal of Systems and Information Technology, 2008
PurposeThe purpose of this paper is to contribute to the growing body of research in prediction m... more PurposeThe purpose of this paper is to contribute to the growing body of research in prediction markets by using trading data as a means of characterizing trader behavior in these markets. Traders are placed in homogenous groups based on common Trading habits using clustering algorithms. Several behavioral themes are used to guide the analyses.Design/methodology/approachSeveral market experiments were run to collect trading data, which was then exported into a data warehouse. A secondary data analysis is performed on variables derived from the original trade data. In particular, k‐means clustering is used to form groups of traders that share common characteristics.FindingsParticipants can be classified into homogenous groups based on their trading behavior. Groups tend to differ based on the overall level of participation, how much of their trading activity is spent buying or selling, and how early they enter the market.Research limitations/implicationsMore research should be done u...
Health care decision makers and researchers often use reporting tools (eg Online Analytical Proce... more Health care decision makers and researchers often use reporting tools (eg Online Analytical Processing (OLAP)) that present data aggregated from multiple medical registries and electronic medical records to gain insights into health care practices and to understand and improve patient outcomes and quality of care. An important limitation is that the data are usually displayed as point estimates without full description of the instability of the underlying data, thus decision makers are often unaware of the presence of outliers or ...
Ricardo Lasa, CEO and co-founder of SiteWit Corporation, was always chastising his technical team... more Ricardo Lasa, CEO and co-founder of SiteWit Corporation, was always chastising his technical team that the “biggest risk facing the company is the engine.” SiteWit provided cross-platform services aimed at helping small (or even medium-sized) business customers effectively advertise on search engines like Google (AdWords) and Bing (adCenter), as well as other online social networking or display advertising venues. Essentially, SiteWit was a web analytics company that tracks all the detailed organic and paid advertising traffic on client websites. SiteWit used this very detailed data to deliver software-as-a-service (SaaS) products that handled a variety of tasks from automated keyword bidding to campaign optimization. These products relied on a foundation of website analytic data warehousing and automated data mining, so data quality was of paramount concern. Lasa and his team faced a critical technology challenge in scaling the core database systems to meet rapidly escalating data ...
The focus of this research is on the IT service relationships that exist between clients and prov... more The focus of this research is on the IT service relationships that exist between clients and providers in cloud computing. Cloud computing is an important context in IT services management since it has become an increasingly popular delivery model. We use coordination theory and a case study of a cloud computing-based company to investigate how cloud service relationships are managed. Evidence of both the standardized and customized relationships is based on a case study of SiteWit, a new startup company that is both a user and provider of cloud services. This company is an interesting case to study, given the real-time, intensive nature of the technical demands, the multiple service relationships that must be managed, while at the same time minimizing costs.
The corporate bond market is one of the areas that has witnessed profound changes since the last ... more The corporate bond market is one of the areas that has witnessed profound changes since the last financial crisis, prompting regulators (and industry participants) to question its resilience under stress. We are building agent-based models to better understand bond market dynamics using simulations. Simulations offer an intriguing method of capturing the second-order feedback loops that can affect prices under conditions of stress. However, understanding all the data and emergent behaviors from these complex systems remains a difficult challenge. In this paper, we begin investigating visualization and sonification techniques that might help us meet this challenge at both agent (micro) and system-wide (macro) levels, with the goal of assembling an effective mixture of visual elements. Sonification offers a novel way to enrich our visualizations with sound, setting markets to music. An experiment assessing the impact of mutual fund market share on bond market stability provides an int...
This research aims to uncover commercial bank business models through cluster analysis. Detailed ... more This research aims to uncover commercial bank business models through cluster analysis. Detailed regulatory snapshots of bank balance sheet data are used to derive a small set of bank lending features for clustering. These snapshots can be considered chronologically to better understand trends in the banking industry. For instance, the number of commercial banks has dramatically declined from 1980 to 2013 (the window of analysis). In addition, commercial bank business models have become more uniform or homogeneous with respect to lending activities. Characterizing banking business models is part of a larger research initiative focusing on agent-based modeling and simulation of the Federal funds market, as well as the detailed inter-bank lending market. Understanding banking business models is key to populating the agent ecosystem, implementing better behavior models and interpreting the simulation results. Unsupervised learning methods such as cluster analysis are a natural fit for this business model discovery challenge.
Journal of Systems and Information Technology, 2008
PurposeThe purpose of this paper is to contribute to the growing body of research in prediction m... more PurposeThe purpose of this paper is to contribute to the growing body of research in prediction markets by using trading data as a means of characterizing trader behavior in these markets. Traders are placed in homogenous groups based on common Trading habits using clustering algorithms. Several behavioral themes are used to guide the analyses.Design/methodology/approachSeveral market experiments were run to collect trading data, which was then exported into a data warehouse. A secondary data analysis is performed on variables derived from the original trade data. In particular, k‐means clustering is used to form groups of traders that share common characteristics.FindingsParticipants can be classified into homogenous groups based on their trading behavior. Groups tend to differ based on the overall level of participation, how much of their trading activity is spent buying or selling, and how early they enter the market.Research limitations/implicationsMore research should be done u...
Health care decision makers and researchers often use reporting tools (eg Online Analytical Proce... more Health care decision makers and researchers often use reporting tools (eg Online Analytical Processing (OLAP)) that present data aggregated from multiple medical registries and electronic medical records to gain insights into health care practices and to understand and improve patient outcomes and quality of care. An important limitation is that the data are usually displayed as point estimates without full description of the instability of the underlying data, thus decision makers are often unaware of the presence of outliers or ...
Ricardo Lasa, CEO and co-founder of SiteWit Corporation, was always chastising his technical team... more Ricardo Lasa, CEO and co-founder of SiteWit Corporation, was always chastising his technical team that the “biggest risk facing the company is the engine.” SiteWit provided cross-platform services aimed at helping small (or even medium-sized) business customers effectively advertise on search engines like Google (AdWords) and Bing (adCenter), as well as other online social networking or display advertising venues. Essentially, SiteWit was a web analytics company that tracks all the detailed organic and paid advertising traffic on client websites. SiteWit used this very detailed data to deliver software-as-a-service (SaaS) products that handled a variety of tasks from automated keyword bidding to campaign optimization. These products relied on a foundation of website analytic data warehousing and automated data mining, so data quality was of paramount concern. Lasa and his team faced a critical technology challenge in scaling the core database systems to meet rapidly escalating data ...
Uploads
Papers by Don Berndt