Andreas Hilbert

Shaping the Next Incarnation of Business Intelligence

The body of knowledge generated by Business Intelligence (BI) research is constantly extended by a stream of heterogeneous technological and organizational innovations. This paper shows how these can be bundled to a new vision for BI that is aligned with new requirements coming from socio-technical macro trends. The building blocks of the vision come from five research strings that have been extracted from an extensive literature review: BI and Business Process Management, BI across enterprise borders, new approaches of dealing with unstructured data, agile and user-driven BI, and new concepts for BI governance. The macro trend of the diffusion of cyber-physical systems is used to illustrate the argumentation.The realization of this vision comes with an array of open research questions and requires the coordination of research initiatives from a variety of disciplines. Due to the embedded nature of the addressed topics within general research areas of the Information Systems (IS) discipline and the linking pins that come with the underlying Dynamic Capabilities Approach such research provides a contribution to IS.

Student Relationship Management in Germany – Foundations and Opportunities

The objective of the article is to introduce to the topic of Student Relationship Management (SRM) in Germany. The concept has been derived from the idea of a Customer Relationship Management (CRM), which has already been successfully implemented in many enterprises. Its objective is to canvass for customers, obtain their loyalty towards the company and, if necessary, win them back. Furthermore, potential uses of a SRM within the context of Higher Education Management will be demonstrated by means of examples of German universities and by applying new methods.

Critical Success Factors for Data Mining Projects

Due to the strategic reorientation of many companies in recent years data mining, as a tool for the analytical customer relation management, became more and more important. Because, however, the success of data mining is not always guaranteed, this paper wants to explain whether respectively under which conditions the investment in data mining projects could be profitable. Using the theoretical background of critical success factors, data mining and some related topics, a model to explain the success of a data mining project in a company has been developed. The derived hypotheses have been tested in an empirical study of German companies. As a result the following critical success factors could be proofed: the commitment of the top management, the existence of a change management, a fixed budget for the project, a good integration of the data mining process in the IT landscape as well as a high quality of the used data.

What is the Conversation About?: A Topic-Model-Based Approach for Analyzing Customer Sentiments in Twitter

In Social Commerce customers evolve to be an important information source for companies. Customers use the communication platforms of Web 2.0, for example Twitter, in order to express their sentiments about products or discuss their experiences with them. These sentiments can be very important for the development of products or the enhancement of marketing strategies. The research goal is to analyze customer sentiments in Twitter. The first step in the research is the detection of topics in Twitter entries which contain patterns of interest. For the topic detection, the authors use Latent Dirichlet Allocation for topic modeling. The authors found event based topics in the exemplary context of Sonys 3D TV sets. In future work, the authors will implement sentiment analysis algorithms in order to determine sentiments in the entries corresponding to the detected topics.

Process performance measurement system – towards a customer-oriented solution

Purpose – Based on a systematic literature review, requirements on a PPMS are identified in order to derive concrete demands and design features for such a system by using quality function deployment (QFD). The purpose of this paper is to formulate a proposal for design recommendations toward a holistic, customer-oriented Process Performance Measurement System (PPMS). Design/methodology/approach – A literature review is used to identify customer demands and design features that characterize a PPMS. To determine the critical design features of a customer-oriented solution, the QFD method is applied. Findings – The paper confirms that there is currently no published concept for an integrated, holistic PPMS. Therefore it provides a first approach to the formulation of a design recommendation based on the customer requirements and design features. A literature-based weighting facilitates a first identification of critical design features. The identified conditions specify the context which can be regarded as ...

Prozessverbesserung im Kontext von Industrie 4.0 — ein Geschäftsmodellansatz für IT-Unternehmen

ZusammenfassungIm industriellen Umfeld macht das komplexe Zusammenspiel von Mensch-Maschine und Maschine-Maschine Prozessbeherrschung und Prozessverbesserung zu einer Herausforderung. Umfangreiche Prozessdatenbestände bergen das Potenzial, menschliches Erfahrungswissen um nicht triviale Zusammenhänge zwischen Einfluss- und Prozessergebnisgrößen zu erweitern. Neue Wertschöpfungsarchitekturen ermöglichen es, sowohl den Menschen als auch die historisierte Prozessdatenbasis einzubeziehen, um validierte Wirkungsbeziehungen für eine proaktive Prozesssteuerung und -überwachung zu erhalten.

Integration of Customer Value into Revenue Management

This paper studies how information related to the customer value can be incorporated into the decision on the acceptance of booking requests. Information requirements are derived from the shortcomings of transaction-oriented revenue management and sources of this information are identified in the booking process. Afterwards, information related to customer value is integrated into the network approach of inventory control.

Menschliches Expertenwissen und Prozessdaten im Verbund

Erklärungsmodelle dienen der Abbildung existierender Systeme, um Wissen über ein System zu erhalten. Six Sigma und Data Mining sind jeweils etablierte Ansätze zur Identifikation von Erklärungsmodellen in Form von Ursache-WirkungsBeziehungen. Während sich Six Sigma bei der Analyse auf menschliches Erfahrungswissen stützt, bieten Verfahren des Data Mining die Möglichkeit, nicht triviale Zusammenhänge zwischen Einfluss- und Prozessergebnisgrößen aus maschinengenerierten Prozessdaten zu ermitteln. Eine Integration beider Ansätze besitzt das Potenzial, Erklärungsmodelle zur Beherrschung und Verbesserung komplexer Prozesse in soziotechnischen Systemen zu schaffen.

Data Mining in Higher Education

The aim of this paper is the critical discussion of different data mining methods in the context of the demand-oriented development of bachelor and master study courses at german universities. The initial point of the investigation was the question, to what extent the knowledge concerning the selection of the so-called “Fachkernkombinationen” (major fields of study) at the Fakultat Wirtschaftswissenschaften of the Technische Universitat Dresden, could be used to provide new important and therefore demand-oriented impulses for the development of new bachelor and master courses. In order to identify these entrainment combinations it is obvious to examine the combinations of the major fields of study by means of different data mining methods. Special attention applies to the association analysis which is classical used within the ranges trade (basket analysis) or e-business (web content and web Usage mining) — an application in the higher education management is missing until now.

Alumni Loyalty: Systematic Literature Review

ABSTRACT The term alumni loyalty (AL) is widely used by scientists in various disciplines and particularly often in discussions of the key factors influencing alumni contributions. However, research in this field varies considerably in its assumptions and methods and contains contradictory findings. Additionally, there is no consistent definition of AL. This situation makes it difficult for the university administration to see the overall picture or to evaluate which results are most reliable and should be used as the basis for practice and policy decisions. A systematic literature review (SLR) would address these problems by identifying, meticulously evaluating, and integrating findings of the relevant studies. To date, no SLR has been undertaken in the field of alumni loyalty. The purpose of this study is twofold. First, the paper conducts an SLR in this research area. Second, the study provides a more comprehensive definition of alumni loyalty. The research identified 102 relevant articles and classified them according to seven theoretical approaches: microeconomics, charitable giving, management, relationship marketing, educational science, services marketing, and the integrative approach, which combines the above disciplines. Having determined four primary aspects of AL (behavioral, attitudinal, material and nonmaterial), the paper derives four quadrants of AL definitions and assigns each publication to one or two of them. Following this step, the overall picture and definition of AL were derived. The findings can be used by academics as a framework to position new research activities appropriately and by practitioners as a roadmap to enhance AL rate.