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1 BERUFSBEGLEITENDES STUDIUM DOCTOR OF BUSINESS ADMINISTRATION Studienbeginn Juli 2014

2 Inhaltsverzeichnis Doctor of Business Administration (DBA) 2 Maastricht School of Management (MSM) 3 Kooperation mit der IBS International Business School 3 Expertise Clusters (ECs) der MSM 4 Kurse zum DBA 5 Studienverlauf des DBA Programms 6 Übersicht über die Kursinhalte des DBA 7 Einschreibung / Studiengebühren 13 Anmeldung zum DBA der MSM an der IBS Lippstadt

3 Doctor of Business Administration (DBA) der Maastricht School of Managment (MSM) Der Bedarf an hochqualifizierten und praxisnah ausgebildeten Mitarbeitern, die funktionsübergreifend und in strategischen Zusammenhängen denken können und für einen Auslandseinsatz geeignet sind, ist hoch. Der Doctor of Business Administration (DBA) dient der wissenschaftlichen Weiterentwicklung der des Managements. Dieser Abschluss eröffnet Karrierechancen im gehobenen und höheren internationalen Management, besonders in Unternehmensberatungen, Finanzdienstleistungsunternehmen und bei multinationalen Firmen. Der Doctor of Business Administration soll einen wissenschaftlichen Beitrag zur Professionalisierung des Managements leisten. Die Forschungsarbeit des Doctors of Business Administration trägt direkt zur Weiterentwicklung der aktuellen Managementtheorien bei. Forschungsthemen sind vorzugsweise aus den Arbeitsgebieten der Professoren der Maastricht School of Management (MSM) zu entnehmen. Sie studieren das Doctoral Programme der Maastricht School of Management (MSM) an der IBS International Business School Lippstadt im berufsbegleitenden Studium mit Workshops. Fünf Workshops finden im ersten Doktorandenjahr in den Räumlichkeiten der IBS International Business School statt. Weitere Kontakte und Reports schließen sich in den Folgejahren an. Der zeitliche Rahmen, den Sie für den Doctor of Business Administration (DBA) insgesamt einplanen müssen, beläuft sich auf regulär vier Jahre bis maximal sechs Jahre

4 Maastricht School of Management (MSM) Die Maastricht School of Management (MSM) ist eine der ältesten Business Schools in den Niederlanden und das erste, die ein DBA Programm durchgeführt hat. Zurzeit ist das MsM-DBA-Programm mit mehr als 200 Doktoranden aus aller Welt, das größte DBA Programm in Europa, mit vielseitigen Möglichkeiten für Cross-Cultural Networking und Wissensaustausch. Die Mission des MsM-DBA-Programms ist es, ihre DBA Absolventen zu anerkannten Leadern, Managern und Innovatoren in der professionellen Praxis zu machen. Ein Schwerpunkt der MSM liegt auf den Herausforderungen und Chancen für Schwellen- und Entwicklungsländer in einer sich globalisierenden Welt. Das Studium zum Doctor of Business Administration (DBA) der Maastricht School of Management, das an der IBS International Business School Lippstadt durchgeführt wird, ist vom Ministerium für Innovation, Wissenschaft und Forschung nach Hochschulgesetz staatlich bestätigt. Nach Beschluss der Kultusministerkonferenz vom in der Fassung vom ist der DBA als Dr. vor dem Namen führbar. Die Führung der deutschen Abkürzung Dr. ist für Inhaber von in einem wissenschaftlichen Promotionsverfahren erworbenen Doktorgraden aus Mitgliedstaaten der EU bzw. des EWR ohne Herkunftszusatz möglich. Die Maastricht School of Management wurde 1952 als Institute for Management Science gegründet erhielt sie Ihren heutigen Namen. Seit 1995 wird ein Doktorprogramm angeboten. Die Maastricht School of Management (MSM) ist durch die Association of MBAs (AMBA), durch die International Assembly for Business Education (IACBE) und durch das Accreditation Council for Business Schools & Programs (ACBSP) international akkreditiert. Kooperation mit der IBS International Business School Sie haben die Möglichkeit, an der renommierten Maastricht School of Management (MSM) in Kooperation mit der IBS International Business School Lippstadt den Doctor of Business Administration (DBA) berufsbegleitend zu erwerben. Studienort: IBS International Business School Lippstadt Im Eichholz Lippstadt Tel.: Fax:

5 Expertise Clusters (ECs) der Maastricht School of Management (MSM) Entrepreneurship and Innovation The MsM Entrepreneurship and Innovation EC has a deep knowledge and understanding of all the facets of the field of entrepreneurship, including innovation. It is particularly concerned to study the relationship between entrepreneurship and economic development, recognizing that not all entrepreneurship is good for economic development. Some entrepreneurs are unproductive, and some outright destructive. How the reward structure of society (incentives) can be shaped through institutions, and how public policies can affect productive, innovative entrepreneurship is a central objective of this ECs work. Global Value Chains and Partnerships The Global Value Chain and Partnerships EC follows two approaches in value chain analysis. The first is bottom-up, where the EC examines initiatives to private sector development as a means to include small farms and firms in commercial markets with the aim to reduce poverty in developing countries. High Performance Organization A High Performance Organization (HPO) is defined as an organization that achieves financial and non-financial results that are exceedingly better than those of its peer group over a period of time of five years or more, by focusing in a disciplined way on that what really matters to the organization

6 Kurse zum DBA Der DBA setzt sich aus vier Modulen, Hausarbeiten (Coursework), dem Research Proposal Seminar, Reports zum Fortschritt der Dissertation und der Dissertation als der Doktorarbeit des DBA Studiums zusammen. Reihenfolge der vier Module 1. Quantitative Methods I 2. Research Methods I 3. Quantitative Methods II 4. Research Methods II Research Proposal Seminar mit MPhil Thesis Contacts and Reports to Supervisor DBA Thesis Review and Defense Phase DBA Thesis MSM announces top ranking in May 2013 In the most recent ranking of Doctorate of Business Administration (DBA) programs worldwide, DBAStudies.com ranked the Maastricht School of Management s DBA program at second place in the world. The criteria used for the ranking consisted of: * Academic accreditation such as AMBA and AACSB. * Student support, i.e. how are students supported by the university, professor, and academic office. * International mindset, e.g. does the school promotes international exchange or study opportunities abroad for doctoral students. * Reputation of the DBA course assessed by its current and former students. * Seniority and management experience of student body

7 Studienverlauf des DBA Programms Voraussetzungen für die Aufnahme in das DBA Programm MBA oder Master (auch FH) oder vergleichbarer Diplomabschluss Berufserfahrung Nachweis der Englischkenntnisse z. B. durch TOEFL 600 paper-based oder einen äquivalenten Test Studienform und Studiendauer Der DBA wird regulär berufsbegleitend in einem Zeitraum von vier Jahren erreicht. Die Workshops werden an der IBS International Business School Lippstadt durchgeführt. Am Ende des ersten Studienabschnitts steht nach maximal zwei Jahren das Research Proposal Seminar mit der Verteidigung Ihrer Arbeit. Bei Erfolg wird der MPhil Degree verliehen. Danach dokumentieren halbjährliche Reports in Zusammenarbeit mit den Supervisoren der Doktorarbeit den Fortschritt der Dissertation. Jährlich erhalten die Doktoranden zudem Gelegenheit, an einer Research Conference in Maastricht teilzunehmen und Ihr Dissertations Projekt zu präsentieren. Das Thema der Dissertation sollte im Zusammenhang mit dem beruflichen Umfeld des Studierenden und im Kontext der Forschungsthemen der Maastricht School of Management (MSM) stehen. Die Workshops des berufsbegleitenden DBA Studiums werden von den Professoren und Dozenten der Maastricht School of Management (MSM), Niederlande, geleitet. Sie finden in den Räumlichkeiten der IBS International Business School Lippstadt in Nordrhein-Westfalen NRW statt. Zeitaufwand Der Zeitaufwand ist individuell sehr verschieden. Er hängt von der Themenstellung und den Vorkenntnissen des Kandidaten ab. Hotelnachweis Das Parkhotel Ortkemper in Lippstadt z. B. bietet mit drei Minuten Fußweg zur IBS International Business School Lippstadt günstige Übernachtungsmöglichkeiten für DBA Studenten an. Studium in Kohorten Die fordert, dass dieses Programm in einem Verband mit einer Mindestzahl an Teilnehmern (Kohorte) zu absolvieren ist. Die Maximalzahl beträgt

8 Übersicht über die Kursinhalte des DBA MODULE TITLE: Quantitative Methods I COURSE OBJECTIVES Quantitative Methods 1 is the first of four courses in the doctoral (M Phil/DBA) program at MSM. Once students complete these four courses, they generally present a research proposal to a Reader and then a presentation to Examiners resulting, when successful, in the awarding of the MPhil degree. Students then transition to writing their dissertation either in the DBA program at MSM or a PhD program at a participating Dutch university. The objective of QM1 is to give students a practical introduction to quantitative methods (primarily statistical), including such analysis tools as SPSS, AMOS, LISREL, R, EVIEWS, online testing sites, Excel Solver (optimization), etc., and to become creative analysts and problem solvers. Position in Curriculum This is the first course students take in their doctoral programme at MsM. It is followed by Research Methods 1, then Quantitative Methods 2, and finally Research Methods 2. Upon completion of QM1, students should be able to understand which statistical methods are applicable to what problem, they should be able to search for new methods when the situation calls for it, and they should be able to extend their world view. Learning Goals After successfully completing this course, the student will be able to: [- know and understand analyze and interpret research data using a variety of parametric and nonparametric statistical procedures. - apply this knowledge to the student s primary interest area as well as elsewhere. - critically assess or judge.the correct questions to ask in a research query, and be able to answer these research questions in a formal way (statistical hypothesis testing). Students should also be able to use and interpret exploratory data analysis procedures in those instances in which they are presented with an existing data set. - communicate. their results in a meaningful way. Students must internalize that we are a very visual society, and learn to present results of a statistical experiment in a way that communicates the essence of their ideas and conclusions. - learn... to accept the challenge to identify a problem in an ambiguous situation, recommend an approach for problem solution, and then follow through with that approach until a decision is made

9 Feedback, tests, evaluation and grading As a doctoral level course, students are required to design their own experiment in which they are presented with a data set, and must identify components of that data set as well as procedures to be used for analysis and extrapolation of that data. While some structure is obviously provided, students have a variety of solution as well as analysis approaches and must pick from among them and make a final recommendation. Conjecturing about a relationship is always required, and students learn to do this in the context of a formal test of a hypothesis. Grading at the Doctoral level is pass/fail. Students are evaluated on their base knowledge, creativity, and ability to present their results. MODULE TITLE: Research Methods I COURSE OBJECTIVES Research Methodology (RM) is one of the required coursework workshop series in the MSM Doctoral program. It is delivered in two courses. This is the first course, Research Methods 1, which discusses, firstly, the issues of research strategy, design and methods in general. Later on, this course shows a special emphasis on the qualitative paradigm type of research. In particular, we look at the way it differs and contrasts with the quantitative paradigm type of research, which is the focus of the second course in this series, Research Methods 2. The first objective of this type of coursework is to prepare the candidate conceptually and practically, so that he or she is able to structure and design as well as conduct a research study. In this context, a number of philosophical issues related to the essence of new knowledge as well as scientific evidence in social sciences, including management, will be discussed. The second objective is to survey various approaches and methods of data analysis likely to be needed during the doctoral program, and after the program in the graduate s research career. This wide-ranging survey is supplemented with computer laboratory workshops which will evolve around problem-based case-studies in business and management research. The focus will be less on computational aspects and more on the goals of the methods, the assumptions underlying the techniques of data analysis, and the method of data analysis required, according to the type of research design. How should the student interpret and validate the results? The third and final objective of this series of workshops is to tackle the issues of research findings, including oral and written presentation, as well as publication for different audiences including doctoral dissertation writing and defense. In this context, the critical analysis of published works will also be discussed

10 Position in Curriculum The course is to be completed after the first of the two courses in Quantitative Methods. The program has four major courses. They are sequenced as QM1- RM1-QM2-RM2. Learning Goals After successfully completing this course, the student will be able to: 1. Know and understand in a systematic way the philosophical premises of various research and investigative approaches, and thus be in a better position to defend his or her methodological choices in his or her chosen field of study. 2. Appreciate the difference between the three major research paradigms (qualitative, quantitative and mixed). 3. Know and understand how to use specific methods of research, in the qualitative paradigm research in particular. 4. Apply all this knowledge in drawing up a research proposal (in the qualitative paradigm). 5. Ultimately, conceive, design, draw up and defend his or her research (as a doctoral) proposal, synthesizing new and complex ideas worthy of doctoral-level investigation. 6. Ultimately, write scholarly papers and publish in refereed journals. 7. Critically review, evaluate and assess scholarly literature to prepare an acceptable literature review, and the position of his or her research area within the literature. 8. Feedback, tests, evaluation and grading 1. There will be continuous assessment and feedback to the students throughout the course presentations and discussions. 2. This is a pass/fail course. Passing the course requires performance on all the above items, at a level of quality that suggests success in the subsequent doctoral process

11 MODULE TITLE: Quantitative Methods II COURSE OBJECTIVES Quantitative Methods 2 is the third of four courses in the doctoral (DBA/PhD) program at MSM. The objective of QM2 is to deepen students knowledge about quantitative techniques beyond material covered in QM1 using computer software like Excel, SPSS (especially), EVIEWS, AMOS, online testing sites and so forth. Based on experience in their first research methods course (RM1), students will make an informal presentation to the class of a topic that interests them, and as a group, we will discuss appropriate statistical analysis procedures for each. Position in Curriculum This is the third course students take in their doctoral programme at MSM. Quantitative Methods 2 is preceded by Quantitative Methods 1 and Research Methods 1 (Qualitative Research Analysis), and is succeeded by Research Methods 2 (Quantitative Research Analysis), in which students are required to present a full literature review of their proposed dissertation research topical area, as well as discuss appropriate analysis procedures. Upon completion of QM2, students should be able to understand which statistical methods are applicable to what problem at a level which has advanced beyond the level covered in QM 1. They should be very familiar with statistical analysis software now, and should be further able to recommend new methods based on additional statistical procedures discussed in this seminar (when required for their dissertation research, especially). Additional analysis procedures beyond QM1 are indicated below in Topics or Tasks and Schedule). Learning Goals After successfully completing this course, the student will be able to: - know and understand analyze and interpret research data using a variety of parametric and nonparametric statistical procedures at an advanced level beyond the level covered in Quantitative Methods 1. - apply this knowledge to the student s primary interest area as well as elsewhere with ease and familiarity. - critically evaluate, assess or judge.the correct questions to ask in a research experiment, and be able to answer these research questions in a formal way (statistical hypothesis testing). Students should also be able to use and interpret exploratory data procedures in those instances in which they are presented with an existing data set. - communicate. Their results in a meaningful way. Students must internalize that we are a very visual society, and learn to present results of a statistical experiment in a way that communicates the essence of their ideas and conclusions. This is emphasized in both QM courses in the Doctoral program. The expecta

12 tions are much higher in QM2. - learn... to accept the challenge to identify a problem in an ambiguous situation, recommend an approach for problem solution, and then follow through with that approach until a decision or recommendation is made. Feedback, tests, evaluation and grading As a doctoral level course, students are required to design their own experiment in which they are presented with a data set, and must identify components of that data set as well as procedures to be used for analysis and extrapolation of that data. In the instance of QM2, we most often provide the students with the data set, and then request that they make meaningful conclusions (statements) based on an analysis of that data. While some assistance and structure is provided, students have a variety of solution as well as analysis approaches and must pick from among them and make a final recommendation. Conjecturing about a relationship is always required in the two Quantitative Methods courses, and students learn to do this in the context of a formal test of a hypothesis once again in QM2. Grading at the Doctoral level is pass/fail. Students are evaluated on their base knowledge, creativity, and ability to present their results. We again stress the importance of being able to communicate effectively the results of their analysis. MODULE TITLE: Research Methods II COURSE OBJECTIVES This is the second course in Research Methods, this time focusing on the quantitative/ scientific paradigm type of research. It explores the philosophy, various quantitative techniques as well as their applications in social science and business research. See Course Objectives for Research Methods 1 for more details. Position in Curriculum The Research Methods 2 course should be completed at the end of the series of coursework subjects taken in the program. It should be completed after the second Quantitative Methods (2) course. Thus the sequence is QM1, RM1,QM2 ending with RM2. Learning Goals After successfully completing this course, the student will be able to: 1. Understand the steps that take the student to a successful dissertation conception, design, implementation, adaptation - with the chance to ask questions and address anxieties. The student will learn the parallel nature of these three

13 processes - the research process, the dissertation-writing process, and the management decision process. 2. Understand the primacy of logic and evidence in the research process. 3. Categorize and discuss the ways research aids management strategy and decision-making. 4. Appreciate the variety of published and publicly/commercially available data, and gain expertise and critical insights into finding research tools and sources. The student will become familiar with MSM s plagiarism policy and with what is proper and improper in using other peoples words and ideas. The student will learn the basics of designing and executing surveys, and generating usable responses. 5. Understand the considerations to take when matching a research objective to the specification of data and the choice of analytical technique(s). Appreciate the value of planning these things up front, before delving into research tasks. 6. Learn new aspects of sampling, and the relative importance of sampling and non-sampling errors. Revisit validity as it applies to scales. 7. Be able to distinguish good data from bad, and know the steps needed to generate good data, and to sort and clean data before analysis, using critical analysis, and techniques of evaluation and synthesis. 8. Gain an appreciation of the variety of analytical tools available. The student will become able to choose among them for the purposes of his or her thesis research. 9. Work with target businesses during the academic research phase in an effective manner. 10. Learn how much information to hit the audience with at one time. By seeing how data can be presented intentionally to mislead, the student will learn how to present data in a neutral manner. Exercises will be provided to help the student to write clearly and concisely, and avoid common errors. Helpful hints will be provided improve student presentations. The student will be helped to understand what it takes to bring a research paper or dissertation to press. 11. Understand the responsibility involved in researching subjects and sponsors as well as to society as a whole, and have an opportunity to debate these matters with peers in the scholarly community. Ultimately, extending the frontiers of knowledge and publishing in scholarly, refereed journals, promoting technological, social and cultural advancement. 12. Understand the responsibilities involved in a career in industry, government or academe for a doctoral degree holder. Feedback, tests, evaluation and grading The student performance is monitored and tracked through continuous assessment and feedback on exercises, case analyses and class presentations

14 Einschreibung / Studiengebühren Anmeldungen zum DBA sind jederzeit möglich. Bitte nutzen Sie für eine Bewerbung den Link zur Bewerbung auf der DBA Webseite bzw. senden Sie der IBS Ihre Bewerbungsunterlagen zu. Studiengebühren * (vgl. MSM DBA Webseite) Master of Philosophy program (1 st year) Tuition fee 1st instalment of 25% 4,000 2nd instalment of 25% 4,000 3rd instalment of 25% 4,000 4th instalment of 25% 4,000 Total 16,000 Doctoral Program Tuition Fee 2nd year 1st instalment of 50% to be paid in March 3,500 2nd instalment of 50% to be paid in September 3,500 Total 7,000 Tuition Fee 3rd year 1st instalment of 50% to be paid in March 3,500 2nd instalment of 50% to be paid in September 3,500 Total 7,000 Tuition Fee 4th year 1 1st instalment of 50% to be paid in March 3,000 2nd instalment of 50% to be paid in September 3,000 Total 6,000 Total Fees for the Doctoral Program (4 years) 36,000 Ansprechpartner Dr. Matthias Zünkler, IBS International Business School Lippstadt, koordiniert dieses Programm und ist unter der Telefonnummer zu erreichen. * Eine Anpassung der Gebühr durch die Maastricht School of Management (MSM) ist möglich

15 Anmeldung zum DBA der MSM an der IBS Lippstadt Ich melde mich für das Studium Doctor of Business Administration (DBA) der Maastricht School of Management, Niederlande, an. Name: Vorname: Staatsangehörigkeit: Geburtsort: Geburtsdatum: Anschrift: Telefon: Fax: E -Mail: Folgende Unterlagen habe ich beigefügt: Curriculum Vitae (Lebenslauf) in Englisch Englischsprachiger Nachweis eines abgeschlossenen MBA- oder Master-Studiums (Zeugnis und Urkunde) Nachweis der Englischkenntnisse TOEFL (Test of English as a Foreign Language) oder IELTS (International English Language Testing System) oder Preliminary DBA Research Proposal (Details erhalten Sie auf Anfrage) 2 Passbilder (bzw. 1 digitales Passbild) Kopie des Personalausweises Ort / Datum Unterschrift Fax an: an:

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