MIS 696/797a group
December 15, 1999
MIS Top REsearchers and key papers
by
Chiening Lin, Dennis C. Wilson, Duffy Gillman,
Gondy Leroy, H.Wayne Anderson, Karen Martin,
Kimberly Brewer, Liming Zhang, Lin Lin, Marsha Ham, Paul Lowry, Taeha Kim, Yousub Hwang
submitted to Dr. Jay Nunamaker
1
Introduction......
Our Model......
MIS Theory......
Key Controversies......
Academic legitimacy......
Methods and Methodologies
Economics/decision science/OR
intro
top researchers
Eric Brynjolfsson......
Morris A Cohen......
Hau L Lee......
James R. Marsden......
Haim Mendelson......
top articles
KM/AI/IR
intro
top researchers
Hsinchun Chen......
Thomas Davenport......
Gary Marchionini......
Gerard Salton (1927-1995)......
Herbert A. Simon......
top articles
HCI/psychology/visualization/communication
Intro
top researchers
Donald Norman......
Jakob Nielsen......
Peter J. Denning
David Liddle
Terry Allen Winograd......
top articles
International (policy foundation)
intro
top researchers
Sy Goodman......
Eli Noam......
Larry Press......
top articles
social issues/ethics
intro
top researchers
Mary J. Culnan......
Sara Kiesler......
Rob Kling......
Richard O. Mason......
top articles
Databases
intro
top researchers
Peter Pin-Shan Chen......
E. F. Codd......
Won Kim......
Salvatore T. March......
Sudha Ram......
top articles
GSS
intro
top researchers
Jerry DeSanctis......
R. Brent Gallupe......
Sara Kiesler......
Jay F. Nunamaker, Jr.
Judy Olsen......
top articles
Telecommunications/security
intro
top researchers
Roch Guerin......
Aurel A. Lazar......
Thomas L. Magnanti......
Steve McCanne......
David Wetherall......
top articles
Systems analysis and design
intro
top researchers
Grady Booch......
Peter Checkland......
Watts Humphrey......
Roger Pressman......
Edward Yourdon......
top articles
E-commerce
intro
top researchers
Lynda Applegate......
Alok Gupta......
Ravi Kalakota......
Andrew B. Whinston......
Vladimir Zwass......
top articles
Appendix A: All Researchers (Alphabetic Order)
Appendix B : Bibliography......
Introduction
Definitions of MIS have been proposed in technical and business literature over the past four decades. Many refer to specific technologies and techniques that may not be broadly applicable to the practice and applications that researchers and IS professionals consider MIS. Widely received definitions include broad statements about the structure of management information systems as entities and as a subject of research. While debate continues within the academic MIS community as to the proper roles of reference disciplines and business practices, a survey of introductory MIS texts resoundingly agrees with the tenets of a definition offered by Brabb[1], chosen here for its succinctness:
A management information system is the complement of people, machines, and procedures that develops the right information and communicates it to the right managers at the right time.
The inclusion of people, machines, procedures, information, communication and management in this definition serves to highlight the critical fact that MIS draws from a wide range of scholarly disciplines. Understanding this fact offers a unique challenge to students and researchers. It is the complexity of MIS, in part, that shapes our map of the prominent research and researchers within MIS.
Our Model
Our model of MIS flows from the multidisciplinary nature of MIS and includes some basic assumptions about the field. The first is that our model should reflect both research streams and historical literature for the field. Second, the model has to capture primary areas of research, their relation to each other, the reference disciplines and their theoretical differences, and trends in research.
This map of the field is intended for an academic audience, and reflects our need as beginning academics to understand this multidisciplinary field, and how our research interests are connected to MIS and to the key researchers in the field. It is not intended to be a complete and comprehensive picture of the MIS field, a review of all of the foundation articles for MIS academics, which would include reviews of the reference disciplines, or our judgement of methods and methodologies used by researchers.
The foundation articles and the list of key researchers have the same limitations and cautions. The articles were chosen because they provide the necessary foundation for understanding MIS research. The list of researchers is not intended to be comprehensive or exhaustive, but to act as an abbreviated directory of key MIS researchers who are influencing the direction of research. This excludes some very influential researchers who consider their primary research domain to be one of the reference disciplines.
Keeping the above precautions in mind, our model divides MIS into the following research focus areas:
Economics of IS /Decision Science/OR
Knowledge Management/Artificial Intelligence/Information Retrieval
HCI/Psychology/Visualization/Communication
International IS (Policy Issues)
Social Issues/Ethics
Databases
GSS
Data Communication/Security
System Analysis and Design
Electronic Commerce
Each of these research areas is represented as a layer along three axes:
- The Behavioral - Technical axis represents research according to its focus on the behavioral or technical aspects of MIS.
- The Rigor - Relevance axis represents the research methodology and methods used to gain knowledge. These labels are only convenient abstractions and do not reflect our judgements about the usefulness or theoretical content of the research: Rigor refers to the basis and methods of research. Dr. Dror's research, for example, relies heavily on mathematical proofs, which would place it on the rigor side of the axis. Rigor also includes the use of controlled laboratory experiments. Relevance, on the other hand, refers to the applicability of the research for practitioners. Dr. Nunamaker's system-building approach (if we ignore for a moment its theoretical underpinnings and implications) would be placed on the relevance side of this axis.
- The third axis, Emerging, is intended to show changes in the direction of research over time and the growth of new streams within the research area.
The layers can be superimposed on each other to show overlaps, give an overview of the field, and show interrelationships among researchers and research streams.
Color, distance, and groupings aid in the interpretation of the model. New layers can be created as research areas are established and layers can be retired, as they become part of the core of the discipline.
MIS Theory
MIS theory is a reflection of the theoretical underpinnings of the reference disciplines and the emergence of a stream of IS research. With some philosophical reservations, we have accepted the IS research framework and terminology proposed in Marcus and Robey, 1988, as the common basis for our evaluation of theory of MIS. Because much IS research is grounded in the conflicting theories and methodologies of the reference disciplines, we limited ourselves to basic IS theory. There are three main schools of thought and research streams:
- The Technological Imperative school assumes that information technology changes behavior. Researchers from this school often refer to the "impact of technology."
- The Organizational Imperative school assumes that rational actors choose technologies and apply them to information needs.
- The Emergent school assumes that the intersection of technologies and people creates complex interactions. [2]
Key Controversies
Academic legitimacy
Multidisciplinary programs are relatively new to postwar academia. Traditional disciplines view multidisciplinary programs as threats, competitors, atheoretical, unnecessary, nonacademic, or simply as research themes. These perceptions and characterizations of MIS (and other multidisciplinary programs)
are held as strongly today as they were in 1980, when Peter Keen presented his paper at the 1st ICIS.[3] The legitimacy of MIS as an academic discipline is still not established for the much of academe.
This controversy is reflected within the discipline, too. In a pair of papers published back-to-back in 1996, Benbasat and Weber dispute Robey's claim that diversity in methods and methodologies is a source of strength for the MIS field. Benbasat and Weber call for common MIS research methodologies and methods because they see the continued dependence on the reference disciplines as a threat to IS. They point out that founding researchers have deserted the field, that reference disciplines are "poaching" on traditionally IS research themes, and that there are serious disputes within the field over the "validity" and "theoretical content" of different research methods.[4] Robey argues that it is the nature of multidisciplinary studies that creates these disputes and also the opportunity to examine or even resolve them by including different perspectives.[5]
Methods and Methodologies
MIS research is characterized by the wholesale adoption of methods and methodologies from the reference disciplines. Some, however, have been adapted to the unique needs of IS research. One typical approach is to use survey methodology. Pinsonneault and Kraemer's critique of survey research in MIS includes suggestions for a uniquely MIS methodology to ensure the quality and validity of research.[6] Their approach is an extension and expansion of Detmar Straub's call for validation of research instruments.[7]
At the same time, in order to address the concerns of researchers with a natural sciences background, Allen Lee proposes a case study methodology that "satisfies the standards of the natural science model of scientific research."[8] In order to address concerns that case study research in general is atheoretical, Kathleen Eisenhardt describes a process for building testable, empirically valid theory using case study research.[9]
Reflecting the multidisciplinary nature of MIS, many researchers advocate the use of multiple methodologies and methods. Kaplan and Duchon's call to combine quantitative and qualitative methods and perspectives to a single research problem lets researchers gain insights that a single methodology or method cannot provide.[10] Orlikowski and Baroudi found common threads among research methods and methodologies used and also call for a multidisciplinary and multi-methodological approach to IS research.[11]
Another important approach to MIS research is Jay Nunamaker's system-building approach, which is explicitly multi-methodological and provides a map for building systems that test assumptions, and includes observation, laboratory experimentation and case studies as necessary elements.[12]
Economics/decision science/OR
intro
We chose top researchers and key papers in economics of information systems and operation management field. This field can be called, in a word, the quantitative research of information systems. Key researchers are recognized most influential by the interview with our faculty members (Dr. Thatcher, Dr. Pingry, and Dr. Dror), Web of Science references, current academic positions, and current publication streams. As you quickly find out, they are all successful in their positions and most influential in their own specialties. Key papers are the significant cornerstones of this field, so that they must be read to understand this field. These papers are chosen by the interview with our faculty members and web of science reference. These articles are commonly used in most courses of quantitative research in IS.
top researchers
Eric Brynjolfsson
Contact Information:
Sloan School, 50 Memorial Dr. E53-313
Massachusetts Institute of Technology
Cambridge, MA 02142
(617) 253-4319, E-mail:
Awards:
Time Magazine's Board of Economists
Current Research:
IT and the structures of markets and firms, the impact of IT investments on productivity and business value, Internet commerce and information goods
Morris A Cohen
Contact Information:
Matsushita Professor of Manufacturing and Logistics
Professor of Operations and Information Management and Systems Engineering
Co-Director, Fishman Davidson Center for Service and Operations Management
3209 Sh-Dh/6366
(215) 898-6431, E-mail:
Awards:
S.J. Hardy Award for Best Paper in Operations Management, Decision Sciences Institute,
Lauder Institute Prize for Advances in Theory and Practice of International Management
Current Research:
Three-dimensional concurrent engineering for the design of products, processes and supply chains - develop an architectural framework that captures the interaction of these design decisions at a strategy/industry level.
Design for service - analysis of product design from the perspective of product life cycle performance and after-sales service support.
Global operations strategy - supply chain model of material and cash management in international manufacturing and service networks.
Supply chain coordination - development of incentives and information sharing policies to support material management in supplier/buyer relationships.
Hau L Lee
Contact Information:
TERMAN 346 Stanford, CA, 94305-4024
(650) 723-0514, E-mail:
Awards:
Eugene Grant Award of Outstanding Teaching, Stanford University, 1996.
Best Paper for the Lauder Institute Award for the Best Advances in the Theory and Practice of International Management Science, presented by the Lauder Institute of Management and International Studies and the Institute of Management Science, 1989
2nd Runner-Up, Edelman Practice Prize by the Institute of Management Science, 1989
Department Service Award, Department of Industrial Engineering and Engineering Management, Stanford University, 1988.
Outstanding Teacher Award, Department of Industrial Engineering and Engineering Management, Stanford University, 1986.
First place, Health Application Section Spotlight Prize, Operations Research Society of America, 1984
Sigma Xi Ph.D. Dissertation Grant Award, National Center for Health Services Research, U.S.A., 1981.
M.I.S., Institute of Statisticians, United Kingdom, 1983
Current Research:
Supply chain management, global logistic system design and control, multi-echelon inventory systems, manufacturing and distribution strategy, design for supply chain management.
James R. Marsden
Contact Information:
School of Business Administration, University of Connecticut
368 Fairfield Road, U-41 IM
Storrs, Connecticut 06269-2041
(860) 486-5295, E-mail:
Awards:
The founding Chair and Philip Morris Professor of Information Systems , Department of Decision Science and Information Systems, University of Kentucky
Director of the MIS and DSS Research Labs, University of Kentucky
Departmental Editor (DSS Impacts and Evaluation) for Decision Support Systems Expert Systems Minitrack co-coordinator for HICSS.
Phi Beta Kappa, Phi Mu Alpha, Evans Scholar, James Scholar
National Science Foundation Post Doctoral Fellow
Current Research:
Management of information, decision support systems, legal issues in information technology, quantitative methods, and econometrics.
Haim Mendelson
Contact Information:
Graduate School of Business, Stanford University
Stanford, CA 94305-5015
(650) 725-8927,E-mail:
Awards:
Co-Director, Center for the Study of Electronic Commerce, Strategic Uses of Information Technology, Strategy and Entrepreneurship in the Information Technology Industry, Stanford Business School
Editorial Board, Information Systems Research
Associate Editor, Management Science, MIS Quarterly, Communications of the Association for Computing Machinery, Organizational Computing and Electronic Commerce
Current Research:
IT and Time-Based Competition in Financial Markets,
Information and Organization for Horizontal Multi-market Coordination,
A New Approach to the Regulation of Trading Across Securities Markets,
Information and Organization for Horizontal Multi-market Coordination,
Further Evidence on the Risk-Return Relationship, an Empirical Analysis of Software and Hardware Spending,Volatility, Efficiency and Trading: Evidence from the Japanese Stock Market, Liquidity, Maturity and the Yields on U.S. Treasury Securities.
top articles
1. Barua, A., & Lee, C. S. (1996). The calculus of reengineering. Information Systems Research, 7(4), 409-428.
Advances in new Information Technologies (IT) and changes in the business environment such as globalization and competitive pressure have prompted organizations to embark on reengineering projects involving significant investments in IT and business process redesign. However, the evidence of payoff from such investments can be classified as mixed as' best, a problem we partly attribute to the absence of a strong theoretical foundation to assess and analyze reengineering projects. The authors seek to apply complementarity theory and a business value modeling approach to address some questions involving what, when, and how much to reengineer.
Complementarity theory is based on the notion that the value of having more of one factor increases by having more of another complementary factor. Further, related developments in the optimization of ''supermodular'' functions provide a useful way to maximize net benefits by exploiting complementary relationships between variables of interest.
Combining this theory with a multi-level business value model showing relationships between key performance measures and their drivers, the authors argue that organizational payoff is maximized when several factors relating to IT, decision authority, business processes and incentives are changed in a coordinated manner in the right directions by the right magnitude to move toward an ideal design configuration. The analysis further shows that when a complementary reengineering variable is left unchanged either due to myopic vision or self-interest, the organization will not be able to obtain the full benefits of reengineering due to smaller optimal changes in the other variables. This paper also shows that by increasing the cost of changing the levels of design variables, unfavorable preexisting conditions (e.g., too much heterogeneity in the computing environment) can lead to reengineering changes of smaller magnitude than in a setting with favorable conditions.
2. Brynjolfsson, E., & Hitt, L. (1996). Paradox lost? Firm-level evidence on the returns to information systems spending. Management Science, 42(4), 541-558.
The ''productivity paradox'' of information systems (IS) is that, despite enormous improvements in the underlying technology, the benefits of IS spending have not been found in aggregate output statistics. One explanation is that IS spending may lead to increases in product quality or variety which tend to be overlooked in the aggregate statistics, even if they increase output at the firm-level. Furthermore, the restructuring and cost-cutting that are often necessary to realize the potential benefits of IS have only recently been undertaken in many firms.
This study uses new firm-level data on several components of IS spending for 1987-1991. The dataset includes 367 large firms which generated approximately 1.8 trillion dollars in output in 1992. Authors supplemented the IS data with data on other inputs, output, and price deflators from other sources. As a result, they could assess several econometric models of the contribution of IS to firm-level productivity.