Toward a Definition of IS Identity
Proposing a prototype system for conducting objective, explorative research of the IS discipline
Dr. Jay F. Nunamaker, Jr
Chris Diller
Ximing Yu
Gray Ross
Ming Yang
Jeffrey Jenkins
Contents
Introduction 4
Scope 6
Theoretical Background 8
The IS Identity in Literature 9
Past Projects 10
Lessons Learned from Past Projects 13
The Essential Core as the Central Component of IS Research 13
The Need of an Automatic Classification Algorithm 15
The Internal structure of the IS Discipline 15
The Internal Structure of the IS Discipline will Change Over Time 20
Overview of Seminal Articles and Leading IS Researchers 22
Development of Prototype System 23
Test Data and Results 27
Data Set 1: Key Words 27
Data Set 2: Categories 31
Implications of the Prototype 40
Technical Shortcomings 40
Analytical Shortcomings 41
Future Research 41
Lessons Learned and Conclusion: 42
Works Cited 44
Appendix 1 – Code 48
Exhibit 1.A - Code - WordNet::Similarity Perl Scripts Sample 48
Exhibit 1.B - Code - WordNet::Similarity Interface 49
Exhibit 1.C - Code - Self Organizing Map Interface 55
Appendix 2 – Key Words and Analyses 55
Exhibit 2.A – Key Word Input Used for the Analysis 55
Exhibit 2.B - Seminal Article Keyword WordNet::Similarity Calculations 61
Exhibit 2.C – Category Sample Data from 2008 102
Introduction
The identity of the information systems (IS) discipline has been a topic of much debate in academia and in past MIS 696 projects. Most past definitions of the IS identity have been articulated from individual opinions, which are subjective and debatable by nature. Hence, a widely accepted definition of the IS identity has not been found yet. To help overcome this obstacle, we propose a prototype to perform an objective analysis of the IS discipline. The advantage of a tool that provides an objective analysis is that the resulting definition of the IS identity is subject to less debate. When in question, one can say, “this is what we did, and this is what we found”.
Our prototype helps discover the IS identity by proving the means of performing a within analysis of the discipline as well as an in-between analysis of the discipline and other disciplines. The prototype accomplishes this by creating a self-organizing map. We briefly describe each type of analysis below:
The within analysis answers the question of “what constitutes the IS discipline?” The prototype uses a self-organizing map to generate clusters within the discipline. This helps us understand the structure of the discipline (e.g., what major content topics are being studied) and what elements IS studies share (e.g., rigor, relevance, IT artifacts, etc.). A graphical depiction of a within analysis is shown below:
Figure 1: Within analysis of the IS discipline establishing the structure of the IS disciplineThe in-between analysis answers the question of “what distinguishes IS research from research of other disciplines?” Using the prototype, several separate disciplines can be mapped into naturally occurring clusters. These clusters will demonstrate what the disciplines have in common and how they are distinct. We refer to the factor(s) that distinguish IS research from other research as the IS Essential Core. A graphical depiction of the in-between analysis is shown in figure 2.
Figure 2: In-between analysis of the IS discipline determining the essential core of the disciplineScope
This study is a proof-of-concept of using an objective, automated tool to help define the IS identity. Hence, this study does not claim to have found the ultimate definition of the IS identity, but rather provides a tool and justification for performing an objective analysis of the IS discipline for future groups to utilize with more complete data sets. Hence the remaining of our paper proceeds as follows:
1. We examine from a conceptual perspective the IS discipline. This allows us to develop an understanding to gauge the success of our prototype in developing meaningful clusters. We do this through a) examining theoretical perspectives of what constitutes IS, b) we survey past IS literature discussing the IS identity, c) we examine past MIS 696 projects to see how past groups have defined information systems, and d) survey IS seminal articles and leading IS researchers.
2. We develop a prototype system for performing an objective within and in-between analyses.
3. We perform a pilot study based on seminal IS articles selected in previous year projects to perform only a within analysis of the IS discipline.
4. We discuss the implications of the prototype, future research, and lessons learned.
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Figure 3: Progression of Research ProjectTheoretical Background
We adopt an ontological view of the IS discipline. In other words, IS as a discipline exists in reality. In schools with IS programs, the university administration recognizes information systems as a distinct department. The IS discipline has its own journals, conferences, and professional organizations. IS departments are distinct from computer science, business management, accounting, and other related disciplines in terms of curriculum and emphases.
Given that information systems has organization and is distinct in practice, we propose that theoretically the IS discipline must have an internal structure and an essential core that distinguishes IS research from research in other disciplines. The internal structure can include content subdomains, research standards (e.g., rigor and relevance), accepted methodologies, etc. An essential core is the central, innermost part of a discipline that distinguishes the discipline from other disciplines (Raghupathi & Friedman, 2009). The essential core is the set of research elements that indentify the relevant and important research topics of a discipline.
The IS Identity in Literature
Defining what constitutes the IS identity has been largely debated in acedamia. Some scholars posit that the essential core of information systems is the IT artifact and its immediate nomological net (Benbasat & Zmud, 2003; Orlikowski & Iacono, 2001). The IT artifact is conceptualized as the “application of IT to enable or support some task(s) embedded within a structure(s) that itself is embedded with a context(s)” (Benbasat & Zmud, 2003, p. 186), or a “bundle of material and cultural properties packaged in some socially recognizable form such as hardware and/or software” (Orlikowski & Iacono, 2001, p. 121). The immediate nomological net includes 1) how IT is conceived, constructed, and implemented, 2) how IT is used, supported, and evolves, and 3) how IT impacts the contexts with which they are embedded (Benbasat & Zmud, 2003). IT artifact and its immediate nomological net excludes factors such as online customer behavior, trust-building, research methodology, online services delivery, collaboration, decision making, knowledge management, resource allocation, online communication, the context of the artifact, and supply chain management (Benbasat & Zmud, 2003).
However, there are several limitations of this definition of IS identity. First, much gray area exists of what is an IT artifact and what is not an IT artifact (Whinston & Geng, 2004). Second, the definition of the IT artifact and its immediate nomological net is a very narrow view of IS identity. For this reason, Alter (2003) suggest that the “work system” is a more appropriate definition of IS identity. A work system consist of humans and machines perform work using technology and information (Alter, 2003). This perspective moves away from the technology-only artifact to a system that includes people (Raghupathi & Friedman, 2009). This broader-view of IS identity allows for a more diverse range of research to be classified as information systems research including topics like outsourcing, collaboration, institutional changes, trust in IT and so forth.
From examination of extant literature, however, it is obvious that an accurate or at least agreed upon definition of IS identity has not yet been articulated. One reason for this is that past definitions of the IS identity have been subjective in nature; they are one’s opinion of what the essential core should be. For this purpose, we propose a tool that could aid in determining the essential core of information systems through an objective analysis.
Past Projects
We now examine past MIS 696 projects to see how they can aid us in conceptually understanding the IS core and help us understand the challenges that are impeding an agreed upon definition of the IS core. Table 1 summarizes past year projects. Following the table, we discuses lessons learned from past projects.
Table 1. Summary of past year projects
2008 / Utilizing analyses, models, and reports from previous classes, the class of 2008 categorized 185 research articles collected, built a database, populated it with the articles in both PDF and text format, conducted a variety of statistical and data/text mining analyses, and summarized their findings.
2007 / Took the first steps toward automating the classification of MIS research by developing an algorithm and decision tree to aid readers in defining and identifying key MIS research articles and how they fit within the MIS continuum.
2006 / Extended the previous projects by exploring various research methodologies and methodological paradigms. They discussed positivist and interpretivist research paradigms, and seventeen research methodologies.
2005 / Compiled the models of MIS from 2002, 2003, and 2004 into one comprehensive model and identified key researches. In addition, they included charts explaining the quantitative contribution of research in each subdomain.
2004 / Added to the body of knowledge by identifying U.S. departments of key researchers and their corresponding key research. They also represented the MIS domain visually with observation, experimentation, theory building, and systems development at the core, surrounded by sub-domains and reference disciplines
2003 / Identified the top 101 MIS researchers, categorizing them by nine subdomains. The class of 2003 also presented a three-dimensional model of MIS research characteristics with axes representing behavior vs. technical, application vs. theory, and rigor vs. relevance. Each seminal work was mapped onto the three-dimensional model for enhanced visualization. In addition, profiles of researchers with key contributions were identified. The Class of 2003 developed an Endnote reference library of the research articles that they had collected.
2002 / Re-categorized MIS into nine subdomains with a visual representation of the subdomain relationships. They represented the MIS domain visually with observation, experimentation, theory building, and systems development at the core, surrounded by sub-domains and reference disciplines.
2001 / Identified key researchers in MIS based on eight subdomains defined and they presented a timeline of events in MIS.
2000 / Expanded the research domains to 15—listing 90 key researchers and highlighting key research contributions for each researcher. They represented sub-domains of the MIS field through Venn diagram, capturing relationship of MIS with reference disciplines.
1999 / Identified ten research areas in MIS:
Economics of information/decision science/operations research, Knowledge management/artificial intelligence/information retrieval, Human-computer interaction/psychology/visualization/communication, International information systems, Social/ethics of information systems, Databases, Group support systems, Data communications/security, Systems analysis and design, Electronic commerce
Created a list of 47 key researchers in MIS and grouped by these ten research areas. The 1999 class also created a three-dimensional representation for MIS subdomains – behavioral vs. technical, rigor vs. relevance, emerging vs. contracting trends.
1998 / Listed seven subdomains of MIS:
Overall MIS, Database technology, Software development and engineering, Technology, Human-computer interaction, Organizational/behavioral, Decision sciences
They listed over 45 influential researchers and provided a one-paragraph biography for each researcher.
Lessons Learned from Past Projects
The Essential Core as the Central Component of IS Research
We learn that for research to be categorized as IS research, it must have the IS essential core. Several past projects have suggested that the essential core is what “ties” subdomains of IS research together and have classified influential researchers and seminal articles in subdomains based on the research topic (e.g., collaboration, artificial intelligence, databases, etc.). For example, the 2003 project proposed a circular model with the middle representing the essential core. All of the subdomains of information systems radiated outward from the essential core suggesting the identifying component of information systems research is the essential core. The 2007 project suggests that essential core is the IT component represented as a box between the other disciplines and applied MIS research. These models are shown in figure 4.
Figure 4: The 2003 and 2007 suggesting an essential core as the common factor of IS researchHowever, providing a robust definition of the IS essential core was not in the scope of these past studies. For example, the class of 2003 intentionally left the middle of their circular model representing the essential core empty. They acknowledge that the core does not exist in their model, however, they recognize that defining this essential core is beyond the resources and time-allotment of their project. Our project helps fill this gap by providing a means to objectively determining the IS essential core.
The Need of an Automatic Classification Algorithm
The class of 2007 suggests that for a nonbiased depiction of the IS discipline and proper classifications of IS research, one must develop objective classification algorithms. We agree with this assessment and propose that this principle should also be applied to defining the IS identity. The most accurate depiction of how the IS discipline is structure and how it is unique from other disciplines will come from an objective within and between groups analysis of IS research and research of other disciplines.
The Internal structure of the IS Discipline
Past projects have suggested that the IS discipline has an internal structure: pillars of research subdomains, accepted methodologies, etc. This structure should not be mistaken as the essential core. Recall the essential core should be what distinguishes information systems research from the research of other disciplines. From this perspective, “subdomains” of IS research based on research topic do not uniquely identify a discipline because they usually originate from other disciplines.
This internal structure has been debated. For example, the number of subdomains has varied by topic by number over the last 10 years (table 2). Furthermore, most groups have acknowledge that the subdomains collected are only representative of the articles seminal suggested by the staff of the University of Arizona and should not be interpreted as the discipline as a hole. Our prototype will allow for a fast and objective analysis of the internal structure for future groups and allow them to quickly incorporate a broader sample size of articles.