Abstract
Although major progress has been made in describing the nature of information systems (IS) theory (Gregor, 2006; Gregor & Jones, 2007) and in evaluating and refining existing theories (Grover et al., 2008; Weber, 2012), the status of theories in IS has come under intense debate (Avison & Malaurent, 2014; Gregor, 2014; Grover, 2012; King & Lyytinen, 2004; Straub, 2012; Weber, 2006). Avison and Malaurent’s (2014) and “theory fetish” critique suggests the emphasis on IS theory has produced less-than-interesting research; Grover and Lyytinen (2015) claim that scripted research strategies that domesticate theories from other disciplines lead to a lack of boldness and originality in IS research; Markus (2014) suggests that lack of contribution may be due to narrow definitions or conflicting notions of IS theory as opposed to an overemphasis on IS theory; and Gregor (2014) argues that the discussion surrounding theory in IS may lead to questioning “theory” in itself and proposes that the IS field should strive to understand the theorizing process rather than debate “theory.”
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Notes
- 1.
Theorizing in biology thus takes a different form than theorizing in medicine because they are different discourses, even though statements about organs of the human body, tissues, and cells are found in both disciplines. The rules of discourse of biology concern the study of organic structures that support life. Conversely, the rules of discourse of medicine concern the observation of the human body to identify diseases that affect its health. Similarly, Revens (1972, p. 486) describes the discourse of CS as “computing techniques and appropriate languages for general information processing, for scientific computation, for the recognition, storage, retrieval, and processing of data … and … automatic control and simulation of processes,” which concerns the rules surrounding symbol processing (Denning et al., 1989) and differs from that of IS even though they share the same core concern: the computer.
- 2.
When an IS researcher applies economic theory to study the use of computers using rules concerning value, prices, costs, and trade-offs, which are part of the discursive formation of economics, the power of the economic discourse influences the direction of the study and by extension the IS field. These cross-disciplinary activities present an interesting dilemma to IS researchers. The legitimacy already established by the recognized rules from these “reference disciplines” provides an effective career-building path for IS researchers but at the cost of not building a cumulative tradition within the IS discourse. Additionally, this phenomenon raises the key issue of which discourse rules one should follow: IS or economics. The related issue is whether the researcher is conducting economics research, IS research, or economics research in an IS context. The choice of applying specific rules of discourse has wide-ranging implications, especially in the ability of the IS field to invent its own native theories. If the field believes that the growth of its knowledge depends on inventing its own concepts, statements, and theories (Markus & Saunders, 2007), then leveraging the discourse of other disciplines is unlikely to support such a goal and the IS field will remain multimodal, unable to produce theories with a capital “T.”
- 3.
During its formative stages, IS largely followed the rules laid down by the psychological discourse (cf. Mason & Mitroff, 1973) and, even today, social psychology continues to exert a strong influence (cf. Davis, 1989; Venkatesh et al., 2003). Later, the strategic management field exerted its influence (cf. Ives & Learmouth, 1984; Parsons, 1983) followed by other discourses such as CS, engineering, management, economics, and communication.
- 4.
Field-specific questions determine one particular statement or proposition over that of another. Why was this theory formulated instead of another? Why were certain boundary conditions chosen? For example, medical questions will produce different answers related to suicide compared to, say, psychological or sociological questions even though the phenomenon is the same.
- 5.
As illustration, Darwin, C.—(Darwin, 1859). On the Origin of Species. John Murray—asks what explains the “coadaptation of organic beings to each other and to their physical conditions of life” (p. 4) such that everything fits perfectly? This question, which reframed the discipline of biology, led Darwin to draw an analogy between the practice of selective breeding (artificial selection) that resulted in the change of the animal’s characteristics with the natural phenomenon of slow successive modifications. This analogy generated the concept of natural selection, which became a key component of the theory of evolution.
- 6.
The questions that he was asking distinguished his unique discourse from that of medicine or psychology and framed his theories within sociology. Among the many novel concepts that Durkheim, É. (Durkheim, 1951/1897)—On Suicide: A Study in Sociology. Free Press—generated for sociology were the new concept of social cohesion along with sociological concepts of suicide, including altruistic, anomic, fatalistic, and egoistic forms of suicide.
- 7.
For instance, Mason’s—Mason, R. O., & Mitroff, I. I. (Mason & Mitroff, 1973). A Program for Research on Management Information Systems. Management Science, 19(5), 475–487—early framework for IS began with answering the questions: “What is ‘knowledge,’ ‘effectiveness,’ ‘action;’ and further, who defines them and for what ‘purpose?’” (p. 475). Answering these questions created a framework connecting psychological types, problem types, and presentation modes. These questions did not fit exclusively into management, CS, or psychology alone. Similarly, Davis’s—Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 318–340—TAM asks: “What qualities of systems increases its acceptance and the intensity of its use?”, a question seldom addressed in CS after a system is delivered.
- 8.
Minsky, M.—(1975). A Framework for Representing Knowledge. In J. Haugeland (Ed.), Mind Design II (pp. 111–142). MIT Press—a pioneer of artificial intelligence, acknowledges Kuhn, T.—(1970). The Structure of Scientific Revolutions (2nd ed.). University of Chicago Press—as inspiration for his frame theory: “the basic frame idea itself is not particularly original—it is in the tradition of the ‘schema’ of Bartlett and the ‘paradigms’ of Kuhn” (p. 113). Likewise, in the social sciences, Berger, P. L., & Luckmann, T.—(1966). The Social Construction of Reality. Anchor Books.—credit Kuhn, T. S.—(1957). The Copernican Revolution: Planetary Astronomy in the Development of Western Thought. Harvard University Press—for their understanding of the social construction of reality, and Ritzer’s Ritzer, G.—(1980). Sociology: A Multiple Paradigm Science. Allyn and Bacon, Inc. Sociology: A Multiple Paradigm Science—was based on the Kuhnian paradigm. The influence of Kuhn’s paradigms is particularly evident in science and technology studies, in which Kuhnian concepts of normal science, worldviews, and scientific revolutions forever changed the understanding of progress in science and technology. Other concepts influenced by the Kuhnian paradigm include but are not limited to: Collins and Pinch’s—Collins, H. M., & Pinch, T. J. (1982). Frames of Meaning: The Social Construction of Extraordinary Science. Routledge and Kegan Paul—frame of meaning; Constant’s Constant, E. W.—(1980). The Origins of the Turbojet Revolution. Johns Hopkins University—technological tradition; Rosenberg’s—Rosenberg, N. (1976). Perspectives on Technology. Cambridge University Press—focusing devices; Gutting’s—Gutting, G. (Ed.). (1980). Paradigms and Revolutions: Applications and Appraisals of Thomas Kuhn’s Philosophy of Science. University of Notre Dame Press—technological paradigm; and Jenkins’s—Jenkins, R. V. (1975). Images and Enterprise: Technology and the American Photographic Industry, 1839 to 1925. Johns Hopkins University Press—technological mind-set.
- 9.
Using the metaphor of the pump, Schön, D. A.—(1983). The Reflective Practitioner: How Professionals Think in Action. Basic Books—describes how to generate new ideas for designing a paintbrush. Although the pump and the brush are two different products with two different delivery paradigms, they share developmental lines of thought in delivering paint such that the already familiar processes of one can be readily and creatively transferred to the other.
- 10.
Francis Bacon once defined inductive reasoning as “nothing more than those laws and determinations of absolute actuality which govern and constitute any simple nature, as heat, light, weight, in every kind of matter and subject that is susceptible of them.” Spedding, J., Ellis, R. L., & Heath, D. D. (Eds.). (1901). The Works of Francis Bacon Vol IV. Houghton Mifflin.
- 11.
Boland, R. J. (1982). Myth and technology in the American accounting profession. Journal of Management Studies, 19(1), 109–127, and Boland, R. J., & Pondy, L. R. (1983). Accounting in organizations: A union of natural and rational perspectives. Accounting, Organizations and Society, 8(2–3), 223–234, introduced the notion of rational and nonrational myths, highlighting the need for research that includes both types to understand the interaction of organizations and technology. Boland, R. J. (1987). The in-formation of information systems. In R. J. Boland & R. A. Hirschheim (Eds.), Critical Issues in Information Systems Research (pp. 363–379). John Wiley & Sons, for example, asserts that the “rational system” myth is noteworthy because users expect systems to meet developers’ costs and efficiency demands while simultaneously accomplishing mythical goals. Theorizing using nonrational myths identifies many factors with equal or greater influence on the effectiveness of system development strategies: Franz, C. R., & Robey, D. (1984). An investigation of user-led system design: rational and political perspectives. Communications of the ACM, 27(12), 1202–1209; Hirschheim, R. A., & Newman, M. (1991). Symbolism and information systems development: myth, metaphor and magic. Information Systems Research, 2(1), 29–62. For example, early critics of management information systems (MIS) invoked the “myth of real-time systems”—Dearden, J. (1966). Myth of real-time management information. Harvard Business Review, 44(3), 123–132—to expose several fallacies regarding the assumed capabilities of computers to support management functions. Boland, R. J. (1987). The in-formation of information systems. In R. J. Boland & R. A. Hirschheim (Eds.), Critical Issues in Information Systems Research (pp. 363–379). John Wiley & Sons, they described five pervasive myths, which he pejoratively called “fantasies,” about information that he believed obstruct progress in IS research.
- 12.
In using analogies, researchers select key similarities between domains rather than features of individual objects. For example, physics researchers draw an analogy between the flow of electrons in an electrical circuit and the flow of people in a crowded subway. The analogy depicting the flow of electrons via the flow of people emphasizes the movement of the objects, not the size or shape of the people compared to electrons. Gentner, D. (1983). Structure-Map**: A theoretical framework for analogy. Cognitive Science, 1, 155–170; Gentner, D. (1989). Mechanisms of analogical reasoning. In S. Vosniadou & A. Ortony (Eds.), Similarity and Analogical Reasoning (pp. 199–241). Cambridge University Press.
- 13.
Early examples propose organismic, sports team, and city-state metaphors for IS strategic planning, offering <?IndexRangeStart ID="ITerm148"?>alternatives to the war metaphor that dominated strategic thinking at the time. Mason, R. M. (1991). Metaphors and strategic information systems planning. 24th Hawaii International Conference on System Sciences, Kauai, HI. Several IS articles explored the use of other metaphors to theorize about system development. Kendall, J. E., & Kendall, K. E.—(1993). Metaphors and methodologies: Living beyond the systems machine. MIS Quarterly, 17(2), 149–171, ibid.—emphasized the need for developers to understand the metaphors applied to system development to better communicate with users, whereas Oates, B. J., & Fitzgerald, B.—(2007). Multi-metaphor method: organizational metaphors in information systems development. Information Systems Journal, 17(4), 421–449—later described how metaphors help developers theorize about organizations to tailor the methodology and process for specific IS development contexts. Some IS scholars have<?IndexRangeEnd ID="ITerm148"?> applied Schön’s—Schön, D. A. (1979). Generative Metaphor: A Perspective on Problem-Setting in Social Policy. In A. Ortony (Ed.), Metaphor and Thought (pp. 254–283). Cambridge University Press—notion of a “generative metaphor” to the planning and development of systems to accommodate a multiplicity of interests and relationships. Atkinson, C. J. (2003). The Nature and Role of Generative Systemic Metaphor within Information Systems Planning and Development. In E. H. Wynn, E. A. Whitley, M. D. Myers, & J. I. DeGross (Eds.), Global and Organizational Discourse about Information Technology (Vol. 110, pp. 323–343). IFIP/Springer. Using the metaphor of magic as it is applied to generally accepted rituals in IS development, Hirschheim, R. A., & Newman, M.—(1991). Symbolism and information systems development: myth, metaphor and magic. Information Systems Research, 2(1), 29–62—theorized about the social nature of IS development and how it affects a project’s probability of success. Brynjolfsson, E., Hofmann, P., & Jordan, J.—(2010). Cloud Computing and Electricity: Beyond the Utility Model. Communications of the ACM, 53(5), 32–34—applied the metaphor of electrical utilities to describe the types of services expected of cloud computing as a utility while also theorizing several dissimilarities between electrical utilities and cloud computing.
- 14.
Using notions of positive analogies (i.e., common properties between two different objects), negative analogies (i.e., properties that differ between objects), and neutral analogies (i.e., uncertain as to whether positive or negative analogies exist), a model can be defined as an imperfect copy of the phenomenon of interest, consisting of positive and neutral analogies. Hesse, M. B. (1966). Models and Analogies in Science. University of Notre Dame Press. By analyzing the extent of positive, negative, and neutral analogies, researchers can draw out horizontal relations between model properties to the phenomenon of interest and speculate on vertical or causal relations stemming from those similarities. If both horizontal and vertical relations exist, Hesse would call those analogies material analogies, which enable predictions to be made from the model.
- 15.
As Harré, R.—(1970). The Principles of Scientific Thinking. University of Chicago Press—explains, a model is no more than a putative analog for a real mechanism, modeled on things, materials, and processes that we already understand. Ibid. describes several types of models distinguished according to whether the subject of the model is also the source of the model. For instance, Weber’s—Weber, M. (1930). The Protestant Ethic and the Spirit of Capitalism (T. Parsons & R. H. Tawney, Trans.). G. Allen & Unwin, Ltd.—ideal types are models in which the subject of the model (e.g., the Protestant capitalist) is also the source of the model, just as a model airplane in a wind tunnel is constructed based on the original airplane. Harré terms these models homeomorphs, which can differ in terms of scale, purity, and level of detail. Models in which the subject is not the same as the model are termed paramorphs, which are used to model a process that is unknown or yet to be investigated. Economic models that demonstrate how the economy “expands” and “contracts” as a result of flows of activity are other examples of paramorphs. The subject of the model, the growth or shrinking of the economy, is not the same as its source, which is that of a balloon expanding or contracting.
- 16.
Carroll’s—Carroll, A. B. (1979). A Three-Dimensional Conceptual Model of Corporate Performance. Academy of Management Review, 4(4), 497–505—conceptual model theorizes the question of what social responsibility means for a corporation by building on three dimensions: (1) categories of social responsibility (i.e., ethical, legal, economic); (2) types of social issues that must be addressed (i.e., environmental, product safety, discrimination); and (3) the philosophy of the response (i.e., reactive, defensive, accommodative). Contrary to the typical theoretical demands of top IS journals, ibid. offers no theories to serve as the basis for this model of corporate social responsibility. Yet, it is a seminal work (with nearly 15,000 citations at the time of writing this article).
- 17.
These theories describe two different models of innovation. Diffusion of innovations theory (DIT) originates in the communication field and models innovation in terms of the flow of information. Consequently, flow-related analogies, such as channels that carry information, the time taken for the rate of adoption, and the social system engaging in the flow, provide a rich set of concepts and constructs to be researched. The theory of reasoned action (TRA) is a theory of behavior predicated on an individual’s behavioral intention, which in turn is affected by the individual’s attitude. Comparing DIT to TRA, because DIT includes a time element, it is able to describe the logistics curve of innovation, which is not possible when using TRA. Conversely, TRA’s focus on attitude is only tangentially addressed by DIT.
- 18.
Sartori, G. (Ed.)—(1984). Social Science Concepts: A Systematic Analysis. Sage Publications—considers concepts as the basic unit of thinking in the same way that Dubin, R.—(1969). Building Theory. The Free Press—refers to concepts as “units” of theory. As Satori explains, “it can be said that we have a concept of A (or of A-ness) when we are able to distinguish A from whatever is not-A” (p. 74). Concepts are always associated with observable objects of study and are discipline-specific because they are superimposed on our experiences as a way for us to understand the world. Several concepts can be combined to form a gestalt that engenders certain expectations.
- 19.
Providing an alternative to the positivistic approach of the natural sciences, Dilthey, W.—(1883/1989). Introduction to the Human Sciences. Princeton University Publishers—argues that positivist representational facts fail to capture the human experience and that “no real blood flows in the veins of the knowing subject constructed by Locke, Hume and Kant” (p. 50). He proposes that an emphatic understanding of human behavior (verstehen) is necessary to capture the “knowledge of the forces that rule society, of the causes that have produced its upheavals, and of society’s resources for promoting healthy progress [that] has become of vital concern to our civilization” (p. 56). This emphatic understanding opened the doors to a new category of disciplines of the human sciences.
- 20.
He notes that “the new concept grows out of the making, elaboration, and correction of the metaphor” (p. 53). He calls this process the displacement of concepts, in which words undergo transposition (i.e., applying an old concept to a new situation), interpretation (i.e., assigning that concept to a specific aspect of the new situation), correction (i.e., an adjustment resulting from adaptation and modification), and spelling out (i.e., resolving commonalities and differences) as a way of addressing problems or improving understanding. Another way of creating concepts is by inductively deriving them from data using methods such as grounded theory. The process of coding in grounded theory is itself the process of conceptualizing data. Strauss, A., & Corbin, J. (1990). Basics of Qualitative Research: Grounded Theory Procedures and Techniques. Sage Publications. Philosophers like Foucault, M.—(1972). The Archaeology of Knowledge and the Discourse on Language (A. M. S. Smith, Trans.). Pantheon Books.—suggest creating new concepts by first observing the context from which the objects of study emerge, what kind of authorities delineate and acknowledge their existence, and how the objects of study can be classified and organized. Depending on these factors, concepts will exhibit different forms of ordering and demonstrate various justifications for their validity and ability to transfer their meaning to different domains.
- 21.
A variable is a term that varies for concepts whose applications rely on direct or indirect (inferred) observation. In situations where the concept cannot be observed directly or even inferred, it is called a construct, which is a concept that is neither directly nor indirectly observable and can be defined only in relation to observables. Kaplan, A.—(1964). The Conduct of Inquiry: Methodology for Behavioral Science. Chandler Pub. Co.—added that when the construct is hypothetical and its existence is dependent on the theory that creates it, it becomes a theoretical term. Keen, P. G. W.—(1980). MIS research: reference disciplines and a cumulative tradition. International Conference on Information Systems (ICIS 1980), Philadelphia, PA—was correct to criticize the IS field for not agreeing on a dependent variable; unfortunately, his analysis of the field’s use of constructs and indirect observables was lost in the confusion. Keen proposed that the IS field should abandon using observables and constructs such as usage and user satisfaction because they have little theoretical significance to the core concern of the field: information. For Keen, the IS field needed to agree on a definition of information before a theoretically sound and practice-relevant dependent variable could be established. Indeed, in the positivist vein, how could the usage or usefulness of information be measured when information itself had yet to be defined? Yet decades of research in IS are dedicated to such a pursuit.
- 22.
These complex abstractions combine multiple concepts belonging to the field, making it difficult to unpack their actual content. Dubin, R.—(1969). Building Theory. The Free Press.—called these formative constructs or abstractions summative units, which is similar to Kaplan’s—Kaplan, A. (1964). The Conduct of Inquiry: Methodology for Behavioral Science. Chandler Pub. Co.—notion of collective terms or composite variables.
- 23.
Concepts such as themes, meanings, and essences of human experiences are gathered using various means, such as (1) close involvement with the participants in the field, observing, listening, interviewing, and reflecting (e.g., case research, ethnography, grounded theory); (2) coming to an understanding of or interpreting texts and social action (i.e., hermeneutics); and (3) describing human experience (i.e., phenomenology). In the nonpositivist tradition, observations and interviews are primary research methods for accessing experiences, which are typically documented in textual, visual, or other formats like field notes, transcriptions, memos, narratives, or recordings. After some form of validation, these experiences undergo an interpretive process by the researcher that transforms them into abstract concepts that are indirectly observable or nonobservable. Analogous to positivist research, the interpretation of the researcher becomes the construction. Flick, U. (1998). An Introduction to Qualitative Research. SAGE Publications; Miles, M. B., Huberman, A. M., & Saldana, J. (2014). Qualitative Data Analysis: A Methods Sourcebook. Sage Publications; Silverman, D. (2006). Interpreting Qualitative Data. SAGE Publications.
- 24.
Similarly, statements such as the “earth is round” and “organisms evolve” do not constitute the same statement before and after Copernicus (for the former), or before and after Darwin (for the latter), because those statements depend on the concepts, theories, and discursive formations of these scientists’ respective disciplines and thus exist in different modes in different times. Namely, these statements are closely related to the theories that they represent.
- 25.
Several statements together can express a single proposition, and a single statement can give rise to different propositions. For instance, the table of elements in chemistry is composed of many signs but contains few sentences. Nevertheless, the grou** of signs, arranged in a special tabular manner, enunciates numerous statements about chemical elements. Likewise, a statement is not the same as a proposition. The sentences “no other element besides gold has the atomic number 79” and “it is true that gold has 79 protons in its atom” express the same logical proposition but are grammatically distinct sentences and modally distinct statements. In the field of accounting, for example, multiple different statements may make the same proposition regarding the financial health of a company.
- 26.
Alavi, M., & Leidner, D. E.—(2001). Knowledge management and knowledge management systems: Conceptual foundations and research issues. MIS Quarterly, 25(1), 107–136—keenly demonstrate these types of nonrelational propositions in their highly cited knowledge management research. Based on their review, they propose three common applications of knowledge management that can all be empirically tested: (1) the coding and sharing of best practices, (2) the creation of corporate knowledge directories, and (3) the creation of knowledge networks.
- 27.
For example, the classic Miles and Snow typology of organizational strategy—Miles, R. E., Snow, C. C., Meyer, A. D., & Coleman, H. J., Jr. (1978). Organizational strategy, structure, and process. Academy of Management Review, 3(3), 546–562, ibid.—categorizes organizations into prospectors, analyzers, and defenders.
- 28.
Within the nonpositivist tradition, statements play an even more critical role in research because the crux of any interpretive, ethnographic, phenomenological, grounded, critical, or other nonpositivist tradition is statements made about the meanings and essence of human experience. Whereas positivist research creates statements by seeking out cause-effect relationships among its concepts and constructs, phenomenological research brackets out prejudgments, biases, and preconceptions to capture the essence and meaning of human experience and consciousness. Moustakas, C. (1994). Phenomenological Research Methods. SAGE Publications. Conversely, prejudgments and biases are foregrounded and highlighted in the way hermeneutical research forms its statements. Gadamer, H. G. (1975). Truth and Method (2nd ed.). Continuum Publishing Group.. That is, the form of statements in nonpositivist research is determined less by the relationships between concepts and constructs (as can be seen in the typical box-arrow diagram in the IS field) than by how the researcher participates in the experiences of the research subjects (i.e., ethnography); induces, deduces, and verifies meaning from the data (i.e., grounded theory); understands and interprets text (i.e., hermeneutics); and perceives and reduces the quality of the experience to the things themselves (i.e., phenomenology).
- 29.
The metaphor of the organization as a machine is exemplified by the notion of the “total information system” of the 1960s research (that use supposed “objective” data and formal reports to optimize decision-making processes and enable total systems management), supporting the prevailing myth of the total MIS. Mintzberg, H. (1972). The Myths of MIS. California Management Review, 15(1), 92–97. The biological metaphor of managers as intuitive and social elements of organizations is at odds with the machine metaphor, resulting in major implications regarding a manager’s information requirements. If managers’ behavior is predominantly intuitive, the information provided by formal, logical MIS will conflict with their needs. This conflict indicates why managers did not buy into newly introduced advanced communication technologies at the time—such as video-conferencing systems, supposedly capable of transmitting verbal and visual information.
References
Abbott, A. D. (2001). Chaos of disciplines. University of Chicago Press.
Abbott, A. D. (2004). Methods of discovery: Heuristics for the social sciences. Norton.
Adam, F., & Fitzgerald, B. (2000). The status of the IS field: Historical perspective and practical orientation. Information Research, 5(4) Retrieved from http://www.informationr.net/ir/5-4/paper81.html
Agarwal, R., & Lucas, H. C., Jr. (2005). The information systems identity crisis: Focusing on high-visibility and high-impact research. MIS Quarterly, 29(3), 381–398.
Ågerfalk, P. J. (2014). Insufficient theoretical contribution: A conclusive rationale for rejection? European Journal of Information Systems, 23(6), 593–599.
Alavi, M., & Leidner, D. E. (2001). Knowledge management and knowledge management systems: Conceptual foundations and research issues. MIS Quarterly, 25(1), 107–136.
Alvesson, M., & Sandberg, J. (2011). Generating research questions through problematization. Academy of Management Review, 36(2), 247–271.
Alvesson, M., & Sandberg, J. (2013). Constructing research questions: Doing interesting research. SAGE.
Alvesson, M., & Sandberg, J. (2014). Habitat and habitus: Boxed-in versus box-breaking research. Organization Studies, 35(7), 967–987.
Angst, C. M., Agarwal, R., Sambamurthy, V., & Kelley, K. (2010). Social contagion and information technology diffusion: The adoption of electronic medical records in US hospitals. Management Science, 56(8), 1219–1241.
Ashby, W. R. (1968). Principles of self-organizing systems. In W. Buckley (Ed.), Modern systems research for the behavioral scientist (pp. 108–118). Aldine.
Atkinson, C. J. (2003). The nature and role of generative systemic metaphor within information systems planning and development. In E. H. Wynn, E. A. Whitley, M. D. Myers, & J. I. DeGross (Eds.), Global and organizational discourse about information technology (Vol. 110, pp. 323–343). IFIP/Springer.
Avison, D., & Malaurent, J. (2014). Is theory king?: Questioning the theory fetish in information systems. Journal of Information Technology, 29(4), 327–336.
Bacharach, S. B. (1989). Organizational theories: Some criteria for evaluation. Academy of Management Review, 14(4), 496–515.
Bagnall, J. (2012). What’s the difference between analogy, metaphor and simile. Quora. https://www.quora.com/Whats-the-difference-between-analogy-metaphor-and-simile.
Bal, M. (2002). Travelling concepts in the humanities: A rough guide. University of Toronto Press.
Banville, C., & Landry, M. (1989). Can the field of MIS be disciplined? Communications of the ACM, 32(1), 48–60.
Beer, S. (1972). Brain of the firm. Penguin.
Beer, S. (1979). The heart of enterprise. Wiley.
Benbasat, I., & Zmud, R. (2003). The identity crisis within the IS discipline: Defining and communicating the discipline’s core properties. MIS Quarterly, 27(2), 183–194.
Berger, P. L., & Luckmann, T. (1966). The social construction of reality. Anchor Books.
Bijker, W. E. (1995). Of bicycles, bakelites, and bulbs: Toward a theory of sociotechnical change. MIT Press.
Bijker, W. E., Hughes, T. P., & Pinch, T. J. (1987). The social construction of technological systems. MIT Press.
Black, F., & Scholes, M. (1973). The pricing of options and corporate liabilities. Journal of Political Economy, 81(3), 637–654.
Blaug, M. (1997). Economic theory in retrospect. Cambridge University Press.
Blumer, H. (1954). What is wrong with social theory? American Sociological Review, 11(1), 3–10.
Bodensteiner, W. D. (1970). Information channel utilization under varying research and development project conditions: An aspect of inter-organizational communication channel usages. [Unpublished PhD dissertation]. The University of Texas at Austin.
Boland, R. J. (1982). Myth and technology in the American accounting profession. Journal of Management Studies, 19(1), 109–127.
Boland, R. J. (1987). The in-formation of information systems. In R. J. Boland & R. A. Hirschheim (Eds.), Critical issues in information systems research (pp. 363–379). Wiley.
Boland, R. J., & Pondy, L. R. (1983). Accounting in organizations: A union of natural and rational perspectives. Accounting, Organizations and Society, 8(2–3), 223–234.
Boulding, K. E. (1956). General systems theory: The skeleton of science. Management Science, 2(3), 197–208.
Brewer, E., Demmer, M., Du, B., Ho, M., Kam, M., Nedevschi, S., et al. (2005). The case for technology in develo** regions. IEEE Computer, 38(6), 25–38.
Bromberger, S. (1992). On what we know we don't know: Explanation, theory, linguistics, and how questions shape them. University of Chicago Press.
Brown, R. H. (1976). Social theory as metaphor: On the logic of discovery for the sciences of conduct. Theory and Society, 3(2), 169–197.
Brynjolfsson, E., Hofmann, P., & Jordan, J. (2010). Cloud computing and electricity: Beyond the utility model. Communications of the ACM, 53(5), 32–34.
Burton-Jones, A., & Straub, D. W. (2006). Reconceptualizing system usage: An approach and empirical test. Information Systems Research, 17(3), 228–246.
Campbell, N. R. (1920). Foundations of science: The philosophy of theory and experiment. Dover.
Carroll, A. B. (1979). A three-dimensional conceptual model of corporate performance. Academy of Management Review, 4(4), 497–505.
Cassirer, E., & Verene, D. P. (1979). Symbol, myth, and culture: Essays and lectures of Ernst Cassirer, 1935–1945. Yale University Press.
Chen, W., & Hirschheim, R. (2004). A paradigmatic and methodological examination of information systems research from 1991 to 2001. Information Systems Journal, 14(3), 197–235.
Cohen, P. S. (1969). Theories of myth. Man, 4(3), 337–353.
Collins, H. M., & Pinch, T. J. (1982). Frames of meaning: The social construction of extraordinary science. Routledge & Kegan Paul.
Constant, E. W. (1980). The origins of the turbojet revolution. Johns Hopkins University Press.
Copi, I. M., & Cohen, C. (2001). Introduction to logic. Prentice-Hall.
Corley, K. G., & Gioia, D. A. (2011). Building theory about theory building: What constitutes a theoretical contribution. Academy of Management Review, 36(1), 12–32.
Corvellec, H. (2013). Why ask what theory is? In H. Corvellec (Ed.), What is theory? Answers from the social and cultural sciences (pp. 9–24). Liber CBS Press.
Cronbach, L. J., & Meehl, P. E. (1955). Construct validity in psychological tests. Psychological Bulletin, 52(4), 281–302.
Czarniawska, B. (2013). What social science theory is and what it is not. In H. Corvellec (Ed.), What is theory? Answers from the social and cultural sciences (pp. 99–118). Liber CBS Press.
Daft, R. L. & Lengel, R. H. (1983. Last updated). Information richness: A new approach to managerial behavior and organization design (No. TR-ONR-DG-02): Department of Management, Texas A&M University. Retrieved from https://apps.dtic.mil/sti/citations/ADA128980.
Daft, R. L., & Lengel, R. H. (1986). Organizational information requirements, media richness and structural design. Management Science, 32(5), 554–571.
Daft, R. L., Lengel, R. H., & Trevino, L. K. (1987). Message equivocality, media selection, and manager performance: Implications for information systems. MIS Quarterly, 11(3), 355–366.
Daft, R. L., & Wiginton, J. C. (1979). Language and organization. Academy of Management Review, 4(2), 179–191.
Darwin, C. (1859). On the origin of species. John Murray.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 318–340.
Davis, M. S. (1971). That’s interesting: Towards a phenomenology of sociology and a sociology of phenomenology. Philosophy of the Social Sciences, 1(4), 309–344.
Dearden, J. (1966). Myth of real-time management information. Harvard Business Review, 44(3), 123–132.
Delone, W. H., & McLean, E. R. (1992). Information system success: The quest for the dependent variable. Information Systems Research, 3(1), 60–95.
Denning, P. J., Comer, D. E., Gries, D., Mulder, M. C., Tucker, A., Turner, A. J., et al. (1989). Computing as a discipline. Communications of the ACM, 32(1), 9–23.
Dennis, A. R., & Kinney, S. T. (1998). Testing media richness theory in the new media: The effects of cues, feedback, and task equivocality. Information Systems Research, 9(3), 256–274.
Dilthey, W. (1883/1989). Introduction to the human sciences. Princeton University Publishers.
Doty, D. H., & Glick, W. H. (1994). Typologies as a unique form of theory building: Toward improved understanding and modeling. Academy of Management Review, 19(2), 230–251.
Dubin, R. (1969). Building theory. The Free Press.
Durkheim, É. (1951/1897). On suicide: A study in sociology. Free Press.
Ein-Dor, P., & Segev, E. (1981). A paradigm for management information systems. Praeger.
Fawcett, J. (1998). The relationship of theory and research. F. A.
Feyerabend, P. (1978). Against method. Verso.
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior. Addison-Wesley.
Fishbein, M., & Ajzen, I. (1977). Belief, attitude, intention and behavior. Addison-Wesley.
Fiss, P. C. (2011). Building better causal theories: A fuzzy set approach to typologies in organization research. Academy of Management Journal, 54(2), 393–420.
Flick, U. (1998). An introduction to qualitative research. SAGE.
Flyvbjerg, B. (2006). Five misunderstandings about case-study research. Qualitative Inquiry, 12(2), 219–245.
Foucault, M. (1970). The order of things: An archeology of the human sciences. Pantheon Books.
Foucault, M. (1972). The archaeology of knowledge and the discourse on language. Pantheon Books.
Franz, C. R., & Robey, D. (1984). An investigation of user-led system design: Rational and political perspectives. Communications of the ACM, 27(12), 1202–1209.
Furneaux, B., & Wade, M. (2009). Theoretical constructs and relationships in information systems research. In Y. K. Dwivedi, B. Lal, M. D. Williams, S. L. Schneberger, & M. Wade (Eds.), Handbook of research on contemporary theoretical models in information systems (pp. 1–17). IGI Global.
Gadamer, H. G. (1975). Truth and method (2nd ed.). Continuum Publishing Group.
Galbraith, J. R. (1973). Designing complex organizations. Addison-Wesley.
Geary, J. (2009). Metaphorically speaking. TED. https://www.ted.com/talks/james_geary_metaphorically_speaking?language=en
Geertz, C. (1973). The interpretation of cultures. Basic Books.
Gentner, D. (1983). Structure-map**: A theoretical framework for analogy. Cognitive Science, 1, 155–170.
Gentner, D. (1989). Mechanisms of analogical reasoning. In S. Vosniadou & A. Ortony (Eds.), Similarity and analogical reasoning (pp. 199–241). Cambridge University Press.
Gibbs, J. P. (1972). Sociological theory construction. .
Gilbert, W. (1893/1600). On the loadstone and magnetic bodies and on the great magnet the earth. Wiley.
Gkeredakis, M., & Constantinides, P. (2019). Phenomenon-based problematization: Coordinating in the digital era. Information and Organization, 29(3), Article 100254.
Glaser, B. G., & Strauss, A. L. (1967). The discovery of grounded theory: Strategies for qualitative research. De Gruyter.
Goles, T., & Hirschheim, R. (2000). The paradigm is dead, the paradigm is dead … Long live the paradigm: The legacy of Burrell and Morgan. Omega, 28(3), 249–268.
Gorry, G. A., & Scott Morton, M. S. (1971). A framework for management information systems. Sloan Management Review, 13(1), 55–70.
Gregor, S. (2006). The nature of theory in information systems. MIS Quarterly, 30(3), 611–642.
Gregor, S. (2014). Theory: Still king but needing a revolution! Journal of Information Technology, 29(4), 337–340.
Gregor, S., & Jones, D. (2007). The anatomy of a design theory. Journal of the Association for Information Systems, 8(5), 312–335.
Grover, V. (2012). The information systems field: Making a case for maturity and contribution. Journal of the Association for Information Systems, 13(4), 254–272.
Grover, V., & Lyytinen, K. (2015). New state of play in information systems research: The push to the edges. MIS Quarterly, 39(2), 271–296.
Grover, V., Lyytinen, K., Srinivasan, A., & Tan, B. C. Y. (2008). Contributing to rigorous and forward thinking explanatory theory. Journal of the Association for Information Systems, 9(2), 40–47.
Gutting, G. (Ed.). (1980). Paradigms and revolutions: Applications and appraisals of Thomas Kuhn’s philosophy of science. University of Notre Dame Press.
Hambrick, D. C. (2003). On the staying power of defenders, analyzers, and prospectors. Academy of Management Executive, 17(4), 115–118.
Hanson, N. R. (1958). Patterns of discovery: An inquiry into the conceptual foundations of science. Cambridge University Press.
Harré, R. (1970). The principles of scientific thinking. University of Chicago Press.
Hart, C. (1998). Doing a literature review. SAGE.
Hassan, N. R. (2014a). Paradigm lost … paradigm gained: A hermeneutical rejoinder to Banville and Landry’s “Can the Field of MIS be Disciplined?”. European Journal of Information Systems, 23(6), 600–615.
Hassan, N. R. (2014b). Value of IS research: Is there a crisis? Communications of the Association for Information Systems, 34, 801–816.
Hassan, N. R., Mathiassen, L., & Lowry, P. B. (2019). The process of information systems theorizing as a discursive practice. Journal of Information Technology, 34(3), 198–220.
Hassan, N. R., & Mingers, J. C. (2018). Reinterpreting the Kuhnian paradigm in information systems. Journal of the Association for Information Systems, 19(7), 568–599.
Hempel, C. G. (1965). Aspects of scientific explanation and other essays in the philosophy of science. Free Press.
Hempel, C. G., & Oppenheim, P. (1948). Studies in the logic of explanation. Philosophy of Science, 15(2), 135–175.
Hesse, M. (1967). Models and analogy in science. In P. Edwards (Ed.), The encyclopedia of philosophy (Vol. 5, pp. 354–359). The Macmillan & The Free Press.
Hesse, M. B. (1966). Models and analogies in science. University of Notre Dame Press.
Hirschheim, R. (2019). Against theory: With apologies to Feyerabend. Journal of the Association for Information Systems, 20(9), 1340–1357.
Hirschheim, R., & Klein, H. K. (2012). A glorious and not-so-short history of the information systems field. Journal of the Association for Information Systems, 13(4), 188–235.
Hirschheim, R. A., & Newman, M. (1991). Symbolism and information systems development: Myth, metaphor and magic. Information Systems Research, 2(1), 29–62.
Hovorka, D. S., Germonprez, M., & Larsen, K. R. (2008). Explanation in information systems. Information Systems Journal, 18(1), 23–43.
Iivari, J., Hirschheim, R., & Klein, H. K. (1998). A paradigmatic analysis contrasting information systems development approaches and methodologies. Information Systems Research, 9(2), 164–193.
Ives, B., Hamilton, S., & Davis, G. B. (1980). A framework for research in computer-based management information systems. Management Science, 26(9), 910–934.
Ives, B., & Learmouth, G. P. (1984). The information system as a competitive weapon. Communications of the ACM, 27(12), 1183–1201.
Jenkins, R. V. (1975). Images and enterprise: Technology and the American photographic industry, 1839 to 1925. Johns Hopkins University Press.
Kaarst-Brown, M. L., & Robey, D. (1999). More on myth, magic and metaphor: Cultural insights into the management of information technology in organizations. Information Technology & People, 12(2), 192–217.
Kahn, H. (1965). On escalation: Metaphors and scenarios. Praeger.
Kaplan, A. (1964). The conduct of inquiry: Methodology for behavioral science. .
Keen, P. G. W. (1980). MIS research: Reference disciplines and a cumulative tradition. In Paper presented at the International Conference on Information Systems.
Keil, M. (1995). Pulling the plug: Software project management and the problem of project escalation. MIS Quarterly, 19(4), 421–447.
Keil, M., & Robey, D. (1999). Turning around troubled software projects: An exploratory study of the deescalation of commitment to failing courses of action. Journal of Management Information Systems, 15(4), 63–87.
Keil, M., Tan, B. C. Y., Wei, K.-K., Saarinen, T., Tuunainen, V., & Wassenaar, A. (2000). A cross-cultural study on escalation of commitment behavior in software projects. MIS Quarterly, 24(2), 299–325.
Kendall, J. E., & Kendall, K. E. (1993). Metaphors and methodologies: Living beyond the systems machine. MIS Quarterly, 17(2), 149–171.
Kendler, H. H., & Kendler, T. S. (1962). Vertical and horizontal processes in problem solving. Psychological Review, 69(1), 1–16.
Khazanchi, D. & Munkvold, B. E. (2003). On the rhetoric and relevance of IS research paradigms: A conceptual framework and some propositions. In Paper presented at the Hawaii International Conference on System Sciences.
King, J. L., & Lyytinen, K. (2004). Reach and grasp. MIS Quarterly, 28(4), 539–552.
Kinney, S. T. & Watson, R. T. (1992). The effect of medium and task on dyadic communication. In Paper presented at the International Conference on Information Systems.
Kirby, J. T. (1997). Aristotle on metaphor. American Journal of Philology, 118(4), 517–554.
Kuechler, W., & Vaishnavi, V. (2012). A framework for theory development in design science research: Multiple perspectives. Journal of the Association for Information Systems, 13(6), 395–423.
Kuhn, T. (1970). The structure of scientific revolutions (2nd ed.). University of Chicago Press.
Kuhn, T. S. (1957). The Copernican revolution: Planetary astronomy in the development of Western thought. Harvard University Press.
Kuhn, T. S. (1977). The essential tension: Selected studies in scientific tradition and change. University of Chicago Press.
Lachman, R. (1960). The model in theory construction. Psychological Review, 67(2), 113–129.
Larsen, T. J., & Levine, L. (2008). Citation patterns in MIS: An analysis of exemplar articles. In G. León, A. M. Bernardos, J. R. Casar, K. Kautz, & J. I. DeGross (Eds.), Open IT-based innovation: Moving towards cooperative it transfer and knowledge diffusion (pp. 23–38). Springer.
Lengel, R. H. (1983). Managerial information processing and communication media source selection behavior. [Unpublished PhD dissertation]. Texas A&M University.
Lengel, R. H. & Daft, R. L. (1984. Last updated). An exploratory analysis of the relationship between media richness and managerial information processing (No. TR-ONR-DG-08). Department of Management, Texas A&M University. Retrieved from: https://apps.dtic.mil/sti/citations/ADA143503
Lévi-Strauss, C. (1963). Structural anthropology. Basic Books.
Lévi-Strauss, C. (1966). The savage mind. Weidenfeld & Nicolson.
Lewis, B. R., Templeton, G. F., & Byrd, T. A. (2005). A methodology for construct development in MIS research. European Journal of Information Systems, 14(4), 388–400.
Lim, S., Saldanha, T., Malladi, S., & Melville, N. P. (2009). Theories used in information systems research: Identifying theory networks in leading IS journals. In Paper presented at the International Conference on Information Systems.
Linnaeus, C. (1735). Systema naturea. M. A. David.
Liu, F., & Myers, M. D. (2011). An analysis of the AIS basket of top journals. Journal of Systems and Information Technology, 13(1), 5–24.
MacCorquodale, K., & Meehl, P. E. (1948). On a distinction between hypothetical constructs and intervening variables. Psychological Review, 55(2), 95–107.
Markus, M. L. (1994). Electronic mail as the medium of managerial choice. Organization Science, 5(4), 502–527.
Markus, M. L. (2014). Maybe not the king, but an invaluable subordinate: A commentary on Avison and Malaurent’s advocacy of ‘theory light’ IS research. Journal of Information Technology, 29(4), 341–345.
Markus, M. L., & Rowe, F. (2018). Is IT changing the world? Conceptions of causality for information systems theorizing. MIS Quarterly, 42(4), 1255–1280.
Markus, M. L., & Saunders, C. S. (2007). Editorial comments: Looking for a few good concepts … And theories … For the information systems field. MIS Quarterly, 31(1), iii–vi.
Mason, R. M. (1991). Metaphors and strategic information systems planning. In Paper presented at the 24th Hawaii International Conference on System Sciences.
Mason, R. O., & Mitroff, I. I. (1973). A program for research on management information systems. Management Science, 19(5), 475–487.
Maxwell, J. A. (2013). Qualitative research design (3rd ed.). SAGE.
McKeon, R. P. (1941). The basic works of Aristotle. Random House.
McLuhan, M., & McLuhan, E. (1988). Laws of media: The new science. University of Toronto Press.
Mendeleev, D. (1869). Über die beziehungen der eigenschaften zu den atomgewichten der elemente (On the relationship of properties to the atomic weights of elements). Zeitschrift für Chemie (Journal of Chemistry), 12, 405–406.
Meyer, M. (1995). Of problematology: Philosophy, science, and language. University of Chicago Press.
Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook. SAGE.
Miles, M. B., Huberman, A. M., & Saldana, J. (2014). Qualitative data analysis: A methods sourcebook. SAGE.
Miles, R. E., Snow, C. C., Meyer, A. D., & Coleman, H. J., Jr. (1978). Organizational strategy, structure, and process. Academy of Management Review, 3(3), 546–562.
Mingers, J. (2004). Paradigm wars: Ceasefire announced who will set up the new administration. Journal of Information Technology, 19(3), 165–171.
Minsky, M. (1975). A framework for representing knowledge. In J. Haugeland (Ed.), Mind design II (pp. 111–142). MIT Press.
Mintzberg, H. (1972). The myths of MIS. California Management Review, 15(1), 92–97.
Mintzberg, H. (1973). The nature of managerial work. Harper & Row.
Mintzberg, H. (1975). The manager’s job: Folklore and fact. Harvard Business Review, 68(2), 163–176.
Moody, D., Iacob, M.-E., & Amrit, C. (2010). In search of paradigms: Identifying the theoretical foundations of the IS field. In Paper presented at the European Conference on Information Systems.
Moore, H. L. (2004). Global anxieties: Concept-metaphors and pre-theoretical commitments in anthropology. Anthropological Theory, 4(1), 71–88.
Mousavidin, E. & Goel, L. (2007). Seeking dragons in IS research. In Paper presented at the Americas Conference on Information Systems.
Moustakas, C. (1994). Phenomenological research methods. SAGE.
Oates, B. J., & Fitzgerald, B. (2007). Multi-metaphor method: Organizational metaphors in information systems development. Information Systems Journal, 17(4), 421–449.
Orlikowski, W. J., & Baroudi, J. J. (1991). Studying information technology in organizations: Research approaches and assumptions. Information Systems Research, 2(1), 1–28.
Orlikowski, W. J., & Iacono, C. S. (2001). Research commentary: Desperately seeking the “IT” in IT research: A call to theorizing the IT artifact. Information Systems Research, 12(2), 121–134.
Ortony, A. (Ed.). (1979). Metaphor and thought. Cambridge University Press.
Parsons, G. L. (1983). Information technology: A new competitive weapon. Sloan Management Review, 35(1), 3–14.
Petter, S., Straub, D., & Rai, A. (2007). Specifying formative constructs in information systems research. MIS Quarterly, 31(4), 623–656.
Popper, K. R. (1970). Normal science and its dangers. In I. Lakatos & A. Musgrave (Eds.), Criticism and the growth of knowledge: International colloquium in the philosophy of science (Bedford College 1965) (pp. 51–58). Cambridge University Press.
Ravitch, S. M., & Riggan, M. (2012). Reason and rigor: How conceptual framework guides research. SAGE.
Revens, L. (1972). The first twenty-five years: ACM 1947–1962. Communications of the ACM, 15(7), 485–490.
Rice, R. E. (1992). Task analyzability, use of new media, and effectiveness: A multi-site exploration of media richness. Organization Science, 3(4), 475–500.
Richardson, H., & Robinson, B. (2007). The mysterious case of the missing paradigm: A review of critical information systems research 1991-2001. Information Systems Journal, 17(3), 251–270.
Ritzer, G. (1980). Sociology: A multiple paradigm science. Allyn & Bacon.
Robey, D., & Markus, M. L. (1984). Rituals in information system design. MIS Quarterly, 8(1), 5–14.
Rogers, E. M. (1983). Diffusion of innovations (3rd ed.). The Free Press.
Rosenberg, N. (1976). Perspectives on technology. Cambridge University Press.
Rosenblueth, A., & Wiener, N. (1945). The role of models in science. Philosophy of Science, 12(4), 316–321.
Runkel, P. J., & Runkel, M. (1984). A guide to usage for writers and students in the social sciences. Rowman & Allanheld.
Sabherwal, R., Hirschheim, R., & Goles, T. (2001). The dynamics of alignment: Insights from a punctuated equilibrium model. Organization Science, 12(2), 179–197.
Salmon, W. C. (1984). Scientific explanation and the causal structure of the world. Princeton University Press.
Sarker, S., Chatterjee, S., **ao, X., & Elbanna, A. (2019). The sociotechnical axis of cohesion for the IS discipline: Its historical legacy and continued relevance. MIS Quarterly, 43(3), 695–719.
Sartori, G. (1975). The tower of babel. In G. Sartori, F. W. Riggs, & H. Teune (Eds.), Tower of Babel: On the definition and analysis of concepts in the social sciences (Vol. No. 6, pp. 7–37). International Studies Association.
Sartori, G. (Ed.). (1984). Social science concepts: A systematic analysis. SAGE.
Schaller, R. R. (1997). Moore’s law: Past, present and future. IEEE Spectrum, 34(6), 52–59.
Schiffrin, D., Tannen, D., & Hamilton, H. E. (Eds.). (2001). The handbook of discourse analysis. .
Schön, D. A. (1963). The displacement of concepts. Tavistock.
Schön, D. A. (1979). Generative metaphor: A perspective on problem-setting in social policy. In A. Ortony (Ed.), Metaphor and thought (pp. 254–283). Cambridge University Press.
Schön, D. A. (1983). The reflective practitioner: How professionals think in action. Basic Books.
Scriven, M. (1962). Explanations, predictions, and laws. In H. Feigl & G. Maxwell (Eds.), Minnesota studies in the philosophy of science (Scientific explanation, space and time) (Vol. 3). University of Minnesota Press.
Silverman, D. (2006). Interpreting qualitative data. SAGE.
Slife, B. D., & Williams, R. N. (1995). What’s behind the research: Discovering hidden assumptions in the behavioral sciences. SAGE.
Spedding, J., Ellis, R. L., & Heath, D. D. (Eds.). (1901). The works of Francis Bacon (Vol. 4). Houghton Mifflin.
Straub, D. (2012). Editorial: Does MIS have native theories. MIS Quarterly, 36(2), iii–xii.
Strauss, A., & Corbin, J. (1990). Basics of qualitative research: Grounded theory procedures and techniques. SAGE.
Street, C. T., & Denford, J. S. (2012). Punctuated equilibrium theory in IS research. In Y. K. Dwivedi, M. R. Wade, & S. L. Schneberger (Eds.), Information systems theory: Explaining and predicting our digital society (Vol. 1, pp. 335–354). Springer.
Suppe, F. (1977). The structure of scientific theories. University of Illinois Press.
Thomson, G. P. (1961). The inspiration of science. Oxford University Press.
Torgerson, W. S. (1958). Theory and methods of scaling. Wiley.
Trice, H. M., & Beyer, J. M. (1984). Studying organizational cultures through rites and ceremonials. Academy of Management Review, 9(4), 653–669.
Tsoukas, H. (1993). Analogical reasoning and knowledge generation in organization theory. Organization Studies, 14(3), 323–346.
Valacich, J. S., Mennecke, B. E., Wachter, R. M., & Wheeler, B. C. (1994). Extensions to media richness theory: A test of the task-media fit hypothesis. In Paper presented at the 27th Hawaiian International Conference on System Sciences.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478.
Walsham, G. (2006). Doing interpretive research. European Journal of Information Systems, 15(3), 320–330.
Weber, M. (1930). The Protestant ethic and the spirit of capitalism. G. Allen & Unwin, Ltd..
Weber, R. (2003). Editor’s comment: Still desperately seeking the IT artifact. MIS Quarterly, 27(2), iii–xi.
Weber, R. (2006). Reach and grasp in the debate over the IS core: An empty hand? Journal of the Association for Information Systems, 7(10), 703–713.
Weber, R. (2012). Evaluating and develo** theories in the information systems discipline. Journal of the Association for Information Systems, 13(1), 1–30.
Weick, K. E. (1979). The social psychology of organizing (2nd ed.). Random House.
Weick, K. E. (1995). What theory is not, theorizing is. Administrative Science Quarterly, 40(3), 385–390.
Weiss, G., & Wodak, R. (2003). Introduction: Theory, interdisciplinarity and critical discourse analysis. In G. Weiss & R. Wodak (Eds.), Critical discourse analysis: Theory and interdisciplinarity (pp. 1–32). Palgrave Macmillan.
Whewell, W. (1840/1967). The philosophy of the inductive sciences, founded upon their history. Johnson Reprint Corp.
Willcocks, L., Hirschheim, R. A., & Dennis, A. R. (2019). Panel presentation. In Paper presented at the SIGPHIL@ICIS Workshop on the Death of Theory in IS and Analytics, Munich, Germany.
Zhang, P., Scialdone, M., & Ku, M.-C. (2011). IT artifacts and the state of IS research. In Paper presented at the International Conference on Information Systems.
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Hassan, N.R., Lowry, P.B., Mathiassen, L. (2023). Useful Products in Information Systems Theorizing: A Discursive Formation Perspective. In: Willcocks, L.P., Hassan, N.R., Rivard, S. (eds) Advancing Information Systems Theories, Volume II. Technology, Work and Globalization. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-031-38719-7_2
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