AMCIS 2006 Panel Summary: Towards the Service Oriented Enterprise Vision: Bridging Industry and Academics

The complexities and costs of current information architectures, infrastructures, and distributed data and software have provided impetus to emerging conceptualizations of the Service Oriented Enterprise (SOE). The foundations for SOE can be found in current applications of service oriented architecture (SOA), service oriented infrastructure (SOI), business process and workflow, computing resource virtualization, business semantics, service level agreements, increasing standardization, and other areas of applied research. This article reports on a panel held at the 2006 Americas Conference on Information Systems (AMCIS) in Acapulco, Mexico, regarding the impacts of SOE tenets on the IS field. Two organizations that are at the leading edge of the SOE continuum [American Express and Intel] in terms of vision and experiences were represented by Margaret Mitchell and George Brown. In addition, MIS academics were represented on the panel by the authors, researchers from Arizona State University. Both industry and academics brought unique perspectives. American Express\u27 SOE approach addresses organizational structure and business intelligence project workflow issues. The company hosts one of the largest IT infrastructures capable of handling untold numbers of transactions each second. Intel\u27s SOE approach addresses the orchestration of services and workflows in the cross-architecture environments characterizing the modern extended global enterprise. Intel is playing a lead role in establishing the OASIS (the Organization for the Advancement of Structured Information Standards) SOA Reference Model (called \u27ebSOA\u27)

PREDICTIVE MODEL MARKETS: DESIGN PRINCIPLES FOR MANAGING ENTERPRISE-LEVEL ADVANCED ANALYTICS

As advanced analytics penetrate a wide range of business applications, companies face the challenge of managing analytics-based assets, such as predictive models. Tasks ahead include model selection, scoring and deployment planning. One way to optimize model selection is to tap the combined knowledge of company staff through a “prediction market,” a virtual market designed to reveal participants’ aggregate wisdom by seeing where people “invest” their money. In the context of predictive-model selection, this paper refers to such devices as predictive-model markets. This paper examines design possibilities for building experimental markets that can ultimately be used to test whether predictive-model markets will improve model selection and deployment. The researchers test two types of incentives for participation: economic and social. Study results indicate that such markets can effectively work using either; a surprising finding is that social incentives did not improve effectiveness when added to economic incentives

THE IMPACT OF NATIONAL CULTURE ON BUSINESS INTELLIGENCE MATURITY MODELS

Maturity level modeling has been a well-established and important stream of IS research. Maturity models have played a significant role in guiding organizational process improvements in many areas. It is therefore surprising that maturity model design and development methodologies have not yet been scrutinized from cross-cultural and international perspectives. In this research, we have prescribed a rigorous approach to identifying, validating and calibrating maturity models constructs for cross-cultural application. We have employed this new methodology in the context of widely accepted business intelligence maturity model that has been initially developed in Germany. Our current effort involves following our proposed methodology to target and calibrate those nationally specific model components that need modification and calibration for application in the US. We report on our progress, and we discuss implications in terms of both findings relevant to culture in IS research, maturity model methodology research and BI maturity model research

Organizational Data and Analytics Contracting in Smart City Fog Computing Platforms

Smart City infrastructures require contracts between public and private organizations collaborating in what is frequently referred to as fog computing platforms. We investigate contract provision variations from different stakeholder perspectives. Our methodology relies on complex adaptive systems theory, and we simulate different contract provision scenarios to identify patterns that emerge. The specific contract provisions we investigate in this paper are related to analytical model and data ownership paradigm variations. We find that some variations offer advantages to stakeholders that include those who participate in the smart city fog platform and those who may have ownership of smart city fog platform infrastructure

A Model of Two-Zoned Networks for Platform-Mediated Markets: Theory and Practical Applications

Two-sided networks enabled by information technology (IT) represent an emerging type of platform-mediated market in the digital economy. Researchers have studied the associated economic and strategic issues from both theoretical and managerial perspectives; however, we have noticed inadequacy in the extant literature when observing some real-world cases that cannot be fully explained by the framework of two-sided networks. A more comprehensive model is needed to explicate the broader market structure and understand the underlying market dynamics. To achieve this aim, we propose a theoretical model of two-zoned networks. In extending the existing dimension of “side,” we add the “zone” dimension at a higher level to study two-zoned networks, which include two-sided networks as a special case. In the proposed model, two-zoned networks consist of two, two-sided networks and a core platform that serves both networks as their connection point at the nexus of two zones. Using the proposed model of two-zoned networks, we analyze four real-world business cases to demonstrate the model’s practical applications. Finally, strategic implications of this model, in terms of operational and legal ramifications, are described. We conclude with topics for future research

Business Intelligence and Big Data in Higher Education: Status of a Multi-Year Model Curriculum Development Effort for Business School Undergraduates, MS Graduates, and MBAs

Business intelligence (BI), “big data”, and analytics solutions are being deployed in an increasing number of organizations, yet recent predictions point to severe shortages in the number of graduates prepared to work in the area. New model curriculum is needed that can properly introduce BI and analytics topics into existing curriculum. That curriculum needs to incorporate current big data developments even as new dedicated analytics programs are becoming more prominent throughout the world. This paper contributes to the BI field by providing the first BI model curriculum guidelines. It focuses on adding appropriate elective courses to existing curriculum in order to foster the development of BI skills, knowledge, and experience for undergraduate majors, master of science in business information systems degree students, and MBAs. New curricula must achieve a delicate balance between a topic’s level of coverage that is appropriate to students’ level of expertise and background, and it must reflect industry workforce needs. Our approach to model curriculum development for business intelligence courses follows the structure of Krathwohl’s (2002) revised taxonomy, and we incorporated multi-level feedback from faculty and industry experts. Overall, this was a long-term effort that resulted in model curriculum guidelines

Introduction to the Minitrack on Artificial Intelligence and Big Data Analytics Management, Governance, and Compliance

This article is an introduction to the Minitrack on Artificial Intelligence and Big Data Analytics Management, Governance, and Compliance at the 53rd Hawaii International Conference on System Sciences

Service-Oriented Software Development

This paper describes a methodology for planning and executing software development projects based on the service-oriented paradigm called Service-Oriented Software Development (SOSD). This does not refer to a methodology for developing software services or service-oriented architectures. Rather, it is a method for managing the process of software development in a service-oriented approach in which the actions performed by individuals and groups are modeled as “services” which can be choreographed and orchestrated. SOSD has been adopted informally by many organizations in various forms and it runs somewhat contrary to some of the recent trends toward agile development methodologies. Interestingly, it performs well in certain situations where agile methods tend to break down. In addition to describing the basics of SOSD and its theoretical underpinnings, we outline its benefits and potential shortcomings. As evidence, project data is provided from a Fortune 500 company which has gradually adopted SOSD over the last two years