Management as a system: creating value

Boston University School of Management publication from the 1990s about the MBA programs at BU, aimed at prospective MBA students

Modernization and unification: Strategic goals for NASA STI program

Information is increasingly becoming a strategic resource in all societies and economies. The NASA Scientific and Technical Information (STI) Program has initiated a modernization program to address the strategic importance and changing characteristics of information. This modernization effort applies new technology to current processes to provide near-term benefits to the user. At the same time, we are developing a long-term modernization strategy designed to transition the program to a multimedia, global 'library without walls.' Notwithstanding this modernization program, it is recognized that no one information center can hope to collect all the relevant data. We see information and information systems changing and becoming more international in scope. We are finding that many nations are expending resources on national systems which duplicate each other. At the same time that this duplication exists, many useful sources of aerospace information are not being collected because of resource limitations. If nations cooperate to develop an international aerospace information system, resources can be used efficiently to cover expanded sources of information. We must consider forming a coalition to collect and provide access to disparate, multidisciplinary sources of information, and to develop standardized tools for documenting and manipulating this data and information. In view of recent technological developments in information science and technology, as well as the reality of scarce resources in all nations, it is time to explore the mutually beneficial possibilities offered by cooperation and international resource sharing. International resources need to be mobilized in a coordinated manner to move us towards this goal. This paper reviews the NASA modernization program and raises for consideration new possibilities for unification of the various aerospace database efforts toward a cooperative international aerospace database initiative that can optimize the cost/benefit equation for all participants

Design Principles for Machine Learning Marketplaces in Enterprise Systems

While standardized enterprise systems (ES) have become widely accepted, this is not the case for machine learning (ML) implementations, which are mostly developed individually in company-specific projects. Necessary historical data and rare ML capabilities result in a low cross-market ML utilization. To overcome the high usage barriers of ML, it should be incorporated into ES in a standardized manner. Therefore, we propose to implement an ML marketplace. While marketplaces in ES already exist, this paper proposes a marketplace dedicated to the exchange of ML models in a federated learning approach. Accordingly, this work formulates four meta-requirements based on interviews, which are structured by marketplace governance dimensions. With these meta-requirements, an ML marketplace was implemented in a design science research project, from which eight design principles are derived. The design principles address governance dimensions for making ML accessible to many companies and allow them to integrate ML into existing ES

Water as an economic good: a solution, or a problem ?

Water resource management / Economic aspects / Economic analysis / Irrigated farming / Water rights / Pricing / Privatization / Marginal analysis / Water market / Water policy

Big Data Research in Information Systems: Toward an Inclusive Research Agenda

Big data has received considerable attention from the information systems (IS) discipline over the past few years, with several recent commentaries, editorials, and special issue introductions on the topic appearing in leading IS outlets. These papers present varying perspectives on promising big data research topics and highlight some of the challenges that big data poses. In this editorial, we synthesize and contribute further to this discourse. We offer a first step toward an inclusive big data research agenda for IS by focusing on the interplay between big data’s characteristics, the information value chain encompassing people-process-technology, and the three dominant IS research traditions (behavioral, design, and economics of IS). We view big data as a disruption to the value chain that has widespread impacts, which include but are not limited to changing the way academics conduct scholarly work. Importantly, we critically discuss the opportunities and challenges for behavioral, design science, and economics of IS research and the emerging implications for theory and methodology arising due to big data’s disruptive effects

CUSTOMER-CENTRIC REVENUE MANAGEMENT IN MANUFACTURING - A DECISION SUPPORT SYSTEM

Manufacturing providers aim not only for a revenu maximizing allocation of their limited production capacity but also for the establishment of long-term customer relations. Du to long-term contracts and strategic reference customers, users of traditional revenu management systems already account for varying worthiness of clients, and intuitively ignore or override booking control suggestions, such as order´s denial or pricing level, in order not to endanger customer relations. So with a view to a holistic approach, the integration of both management concepts, each of decisive competitive impact, is advised. However, an implemented IT-system, that provides the revenu analyst with greater insights, higher accuracy, quality and trust in decision process, is still missing in manufacturing industry. This reflects the common frustration of managers and analysts in practice when dealing with conflicting ideas or theories generated by research community. We believe our prototype is the first to supply analysts with formatted and summarized information to make transparent and comprehensible control decisions, suggesting specific booking control actions based on simulation results and integrated usage of provided data. It also accounts for the strategic dimension of the problem when confronted with these partly diametric objectives of revenu vs. customer relationship management