Methods for the Study of
Structuration in
Information Technology
Marshall Scott Poole
Department of Speech Communication
Texas A&M University
College Station, TX 77843-4234
409-845-5177
409-845-6594 (fax)
[email protected]
Gerardine DeSanctis
Fuqua School of Business
Box 90120
Duke University
Durham, NC 27708
919-660-7848
919-681-6245 (fax)
[email protected]
February 6, 2000
Prepared for the Organization Science Winter Conference, Winter Park, CO, February 6, 2000. Please do not cite without permission.
The impact of the theory of structuration on theorizing in organization science is noteworthy. It is becoming accepted as one of the standard theoretical resources. However, there has been much less attention to how to conduct empirical research on structuration. The purpose of this essay is to address this gap by reviewing the different methods that have been used to study structuration in organizational contexts and considering the options available to researchers.
Structuration is a complex and wide-ranging theory. A review of all applications, even those in organizational studies, would be far more extensive than the current format allows. So we will restrict our consideration to the use of structuration in information systems research. This review specifically focuses on research that attempts to gather evidence on how structuration occurs in information systems and on the impacts of structuration of information technology (IT). Structuration theory has a rather long history of application in this area over the past fifteen years and it can truly be said to be one of the dominant perspective in information systems research. There have been numerous empirical studies, which cover a representative range of modes of inquiry, Hence, a review of studies in this area will cover the field of possible projects pretty well. While IT may seem a specialized and narrow subject, we believe that many of the insights we garner will extend to other applications of structuration theory.
The theory of structuration is fascinating. It is easy to get lost in a contemplative reverie about dualities, the flow of intentionality, the attitude of late modernity, modalities (whatever they are!), and other such issues, and how they apply to information systems research and life as a whole. Because structuration theory attempts to cut across traditional problems connected with the action-structure and stability-change dualisms, it has inspired a number of “calls to arms” that catalog its promise for organization studies in general and information systems in particular (Ransom et al., 1983; Poole, Seibold, & McPhee, 1985; Markus & Robey, 1988; Poole & DeSanctis, 1990; DeSanctis & Poole, 1994). Such exhortations are useful, because they describe the potential of the theory for the field, and point the way for further research. However, without a succession of empirical studies that develop and test the abstract theory in concrete settings, such calls eventually ring hollow. Flesh must be put on the theoretical bones if the theory is to walk and live.
There is another reason that empirical research on structuration theory is important. It is necessary to keep us from letting an attractive theory become a self-sealing. Structuration theory is quite pliable. It is extremely easy for a cognitively complex mind to reinterpret any phenomenon in structurational terms, to see production and reproduction, the mutual entailment of action and institution, etc. in everything. But reading structuration into a phenomenon does not really advance our understanding very much. It is akin to applying one of those other great, seductive theories, exchange theory, to social life. In this case everything becomes an exchange, and the circular exchange theory formula is applied easily and in slapdash fashion:
Why did X do Y?
Because of the exchange: X got something X valued or avoided
something noxious.
How do you know an exchange took place (or was meaningful to X)? Because X did Y.
(or you can start at the bottom and work up; it’s circular!)
In such cases the theory is not really tested, but applied as an article of faith. For our understanding of structuration to advance it is important to have rigorous and critical applications of the framework in empirical research and specification of how structuration happens. This requires concrete research.
Before going further it is necessary to pause to register an important caveat: it is impossible to falsify structuration theory per se. It is one of a handful of “grand” formulations (along with exchange theory) that might be called meta-theories, theories that put forth a particular way of viewing the world which is so general and encompassing that it cannot be refuted or falsified in any definitive way. Meta-theories rest on the theorist’s value choices and are therefore not susceptible to refutation—there is always a way to “save the appearances.” However, what can be empirically explored and (sometimes) tested are structurational theories developed for particular contexts, such as the implementation of information systems. In specific contexts conjectures concerning how structuration occurs, the conditions that influence it, and its consequences or outcomes can be advanced and tested. The context provides the frame—or cage—that confines the theory enough to test it. (However, if it fails the test in any specific context, it can always take flight into the stratus clouds of abstraction and hang there, waiting to pounce upon some other unsuspecting phenomenon.) Perhaps the closest we could come to ”falsifying” structuration theory would be a judgment of its utility on the basis of success or failure across a number of specific phenomena.
Structuration theory comes into contact with the empirical world through research in particular contexts. But how does one conduct research on such a complicated and multilayered process? Where do we start and how do we break the research down into manageable tasks? The following review assumes that the reader is familiar with structuration theory and goes right into methodology. Those unfamiliar with the theory can find a short summary in Appendix A.
The Conduct of Research on Structuration
A General Frame
Giddens (1984) maintains that there are two general strategies for research on structuration: the analysis of strategic conduct and institutional analysis. The analysis of strategic conduct takes institutions as a backdrop and focuses on how actors draw on and reproduce structures in social practices. Institutional analysis assumes that strategic conduct is going on, but focuses on the structural characteristics of institutions and their long-term development. Each approach "brackets" a certain part of the structurational process and uses the rest as an unanalyzed ground for its object of interest. Giddens notes that this bracketing artificially segments structuration, but argues that it is necessary for methodological purposes. While we agree that parts of any structurational process must serve as "ground" against which to discern the "figure", we do not believe that structurational studies have to focus only on action or institutions. An alternative is to shift back and forth between action and institutional levels during an analysis, hoping that the "whole" will convey the nature of structuration. Studies by Smith (1983) and Brewer (1988) do this in a single report.
However, no single study can fill in the whole story behind structuration. Structuration is an encompassing and complex process, and developing a thorough understanding—as opposed to valuable but isolated insights—requires multiple studies that focus on different levels and aspects of a phenomenon. A program of research must explore the processes involved in institutional analysis, strategic action, and the relation of the two realms through multiple studies, each of which captures part of the whole.
An analysis of structuration should address a set of interlocking problems:
(1) It must develop a good analysis of how the system works. This analysis defines the general field in which structuration occurs and its "surface" indicants. It forms a foundation for the analysis of constitution of the group system. By implication, this requires identification of causal links that characterize the system's operation and members' interpretive maps. It also requires determining what features of the context influence structuration.
(2) It must identify the array of relevant structures that are used to constitute the system. This may involve identification of both potential and active structures in both the structuring process and its context. All such identifications are, of course, reifications that "freeze" the modalities of structuration for purposes of analysis.
(3) It must identify structuring moves or processes by which agents appropriate these structures, producing and reproducing them in activity. As Poole and DeSanctis (1992; DeSanctis & Poole, 1994) note, structuration in groups can be studied on at least three levels: the microlevel moves involved in appropriating structures into group interaction, the larger global patterns of appropriation that stretch over several meetings, and at the societal level of general discourse about the relevant structures. Another significant object of inquiry are the impacts of context on structuring moves and processes.
(4) It should also clarify the mediation of one structure by others, as well as the contradictions between structures and their role in the structurational process.
(5) It ultimately should shed light on how social institutions are reproduced or shaped by the process in question. This turns the context issue on its head: how does structuration influence the context itself?
(6) The subjects or actors themselves are produced and reproduced in structuration (Poole et al., 1985). Hence we also have to account for the positioning of the subject in the social system.
(7) It must also undertake critical inquiry into the power dynamics underlying the structuration process and possible relations of dominance among different classes of actors. Power imbalances, covered by ideologies of rationality or equality, can strongly shape structuration, creating relative advantage for certain parties at the expense of other parties and perpetuating preexisting biases in social institutions.
These are not a set of stages for research. Instead they are the “parts” that make up a fully realized structurational theory. Working on any single problem can also produce insights on others. For example, characterizing the structuring moves and structuration in microlevel interaction may lead to identification of additional structures and also to insights as to how the system "works". Insights into how structuration shapes social institutions may shed light on structuring moves through illuminating constraints. Ideally a mature theory of structuration would incorporate these multiple and multilayered analyses into a complex, but coherent whole.
These considerations have several implications for the way in which we go about studying structuration. First, they imply that research on structuration can take two modes. Groups are systems of human interaction, and all action can be described and explained from both the exterior perspective--the viewpoint of the analyst who seeks to understand what causes actions and what makes action effective--and from the interior perspective--in terms of the actions, cognitions, interpretations, feelings, and intentions of the actors. Hence, a first layer of analysis looks at groups from the outside, from the perspective of the observer interested in understanding the factors which cause group behavior and which determine group outcomes. A second layer of analysis attempts to get more of an inside perspective on the group, to study the interpretations that give meaning to events and the actions and interactions that constitute the group, its processes, and member responses to exogenous influences. The goal of the second layer of analysis is to elucidate the processes that constitute the variables, causes, and effects that the first layer of analysis identifies. Each layer of analysis involves a different approach to research, and each reveals different aspects of group processes.
The first layer, functional analysis, focuses on the system itself and depicts it as a network of causal, moderating, and correlational relationships among abstract variables. Exogenous influences, group processes, and outcomes are decomposed into well-defined variables. These variables may be part of the members' lifeworld, but they are defined and operationalized by researchers; they reflect the scientist's perspective and are subjected to analysis of reliability and validity. The validity of a functional analysis depends on its ability to stand up to empirical evaluation; relationships between variables are relevant only insofar as they can be investigated in the laboratory or field. Most current research on groups and GDSSs relies on functional analyses. Hence, most of what we know about groups is stated in causal terms. For example, Poole and Roth (1989b) found that task complexity was inversely related to the complexity of group decision paths. Systems of variables can also be modeled, as this explanation advanced by Homans (1950) and Schacter (1951) illustrates: increased liking among members causes an increase in communication; increased communication causes an increase in perceived similarity among members; increases in perceived similarity causes increased liking (which completes a deviation-amplifying causal loop). However, functional analyses need not be quantitative. Qualitative methods have been used to derive generalizations about behavioral systems since the turn of the century. Interpretive insights into subjects can generate useful and powerful functional theories, such as Lindesmith’s (1947) study of addicts and Glaser and Strauss’s (Strauss, 1987) numerous grounded theories illustrate. And qualitative and quantitative modes of analysis can be combined in functional research, as Weber’s analysis of the Protestant ethic illustrates. Functional analysis is useful, because it permits both explanation and prediction of behavior. It also employs an explanatory scheme that is amenable the application of powerful research and statistical methods to test theories.
But a second layer, constitutive analysis, is necessary to discover how group systems and the variables and relationships that compose them are constructed through group interaction. A functional analysis regards variables and relationships as non-problematic, so long as they satisfy the canons of method. However, any theory grounded in human action is inherently incomplete without an account of how interpretive and interaction processes construct variables and figure in the operation of causal relationships. For example, task is commonly used as a causal variable in systemic studies. However, it is not task per se, but members' interpretation of the task which influences group processes and outcomes. These interpretations may be incorporated in a causal model as "perceived task", but this transforms an interpretive process into a static variable. It cannot capture the role of interpretation in the group's approach to its work. Underlying every variable and relationship in a causal analysis is a process of social construction responsible for making it an active force in the group. A constitutive analysis takes the causal model as a starting point, shows how it operates through member activities, and then adds additional rich detail about these processes.
We believe functional and constitutive analyses, contrasted in Table 1, complement and buttress one another. A constitutive analysis is a useful supplement to functional analysis in such cases, because it reveals the "whole picture" behind seemingly deterministic facts. A constitutive analysis can often help by resolving inconsistencies in causal relations and showing why expected causal relationships do not hold. For example, an early hypothesis was that word
Table 1. Comparison of Functional and Constitutive Modes of Analysis
Functional Analysis Constitutive Analysis
Explanation Causal explanation Causal explanation combined with interpretive explanation
Sample Size Substantial samples possible Relatively small samples
View of Constructs and Relationships Takes variables and relationships as “givens” and nonproblematic Regards constructs and relationships as problematic; concerned with constitution of variables and relationships
Measurement Focuses on variables; uses measurement theory Concerned with faithful representation of participants’ viewpoints and meanings
Validation of Theory Validity of theory depends on empirical test Validity of theory depends on coherency, empirical consistency, and heuristic value
Relation to Other Mode of Analysis Can disclose constraints on constitutive process. Can indicate the practical importance of a constitutive process or factor Captures the processes by which the variables and relationships in functional analysis are realized in the social world
Strengths Enables rigorous, structured research Acknowledges role of agency in social effects
Weaknesses Oversimplification. Omits role of agency How to test or falsify constitutive theories is not clear. These theories are also very complex. Constitution is difficult to study.
processing systems would enhance office productivity. However, only a weak relationship between word processing and productivity was found. Johnson and Rice (198XX ) showed that different offices "reinvented" word processing technology in different ways, and that each of four different reinvention types had different effects on productivity. Social processes involved in technology implementation resulted in different reinventions of the same technology in different groups, which in turn produced different outcomes. In cases where group interaction mediates causal effects, including it can improve causal models. On the other hand, functional analysis can often reveal the powerful causal forces which condition and influence constitutive processes.
Constitutive analysis is also valuable, because some social processes are simply too complex to be "variabilized" and reduced to causal maps. The symbolic convergence process (Bormann, 1986), whereby groups develop shared meanings that inspire them to greater effort and help coordinate activities, may occur in many different ways and defies analysis in terms of tidy variables and causal explanations. So, too, does the process of implementing and adapting technology to individual group situations. While certain aspects of implementation can be captured by functional analysis, the unique adaptations and the give-and-take of interaction can best be understood through in-depth qualitative analysis.
Looking back over the seven issues in structuration research indicates how the two modes of analysis complement one another to give a comprehensive picture of group processes. Functional analysis can lead in the first two tasks, understanding how the system works and the key structural features involved. Previous functional analyses of groups have suggested a wide array of factors that influence how groups work and the findings of functional studies—such as the proportions of variance explained by different factors or the central constructs derived from a grounded theory analysis—can help scholars determine what variables really make a difference in the structuration of group systems. Constitutive analysis can clarify how the various factors fit together and how actions of members influence them. Constitutive analysis takes the lead in tasks 3 through 7, because these research issues concern how the system is produced and reproduced over time. As Fay (19XX) notes, functional analysis is also important in critical inquiry, so it also plays an important role in the seventh task. For tasks 3 through 6, functional analysis can be used to explore and test implications of the findings of constitutive studies. For example, if a constitutive analysis suggested that managers’ interpretations of the IT prejudice how groups form a view of a system, this conjecture and its importance in the group system could be put to a test with a survey. The survey might, for example, gather data on typical dimensions of managerial interpretations identified in the constitutive analysis and determine their impact on eventual group attitudes toward the IT.
A second implication of the seven tasks is that structurational research must include longitudinal studies. The only sure way to determine the nature of a structuring process is to study it as it unfolds, either through direct observation or through analysis of reliable archival data that preserves time ordering of events. Ultimately, structuration research is process research, as this was defined by Mohr (1982) and more recently refined in Poole, Van de Ven, Dooley, and Holmes (in press). Process theories seek to explain a phenomenon by advancing a narrative that shows how it comes to be or is brought about. Process theories can be contrasted to the traditional mode of theory in the social sciences, variance theory, on several dimensions, as shown in Table 1.
As this table indicates the explanatory work in variance theories is done by a continuously operating causal model. In contrast, the process approach explains in terms of the order in which things occur and the stage in the process at which they occur. The story itself is the generative mechanism. The most obvious use of process theories is to explain development and change, and so they are ideal for research on structuration. But a narrative explanation underlies all social scientific theories. All variance theories rely on "stories" to provide the details and justify hypothesized relationships links among variables, and therefore contain implicit process theories.
It is important not to assume an association between variance theory and functional inquiry and between process theory and constitutive inquiry. While they may be associated in current social scientific practice, in conception they are independent of one another. Variance and process approaches represent two different types of explanations, while functional and constitutive inquiry pose two different sets of questions that can be asked about any phenomenon. Either explanatory model can be applied to either set of questions.
The preceding discussion suggests a third implication for structurational research, which may be obvious, but is worth stating: Studies of structuration do not have to be qualitative, as implied by Riley and Banks (1993). They argue for an ethnographic-ethnomethodological approach to the study of structuration (see Smith, 1983, and Brewer, 1988, for examples). While useful, this approach is not the only path to the discovery of valid insights into structuration. Quantitative methods are useful in the study of the system level, because they permit the testing of models to determine which relationships are likely candidates for structurational analysis (Giddens, 1984). Quantitative approaches are also useful for the study of structuration itself, when many observations or cases are available for analysis and when indicators of aspects of structuration can be developed. Studies by Barley (1986), Poole and DeSanctis (1992), and Poole, Lind, DeSanctis, and Watson (1993) illustrate the use of quantitative models in structuration research. Historical studies of structuration are also important, as Giddens' work illustrates.
Choices in Structuration Research
At least seven choices are involved in designing a study of structuration, choices regarding: level of analysis, focus of interest, framing of action, dynamics, model of structure, measurement, and stance of the researcher.
Level of analysis. At what social level should the study be aimed? DeSanctis and Poole (1994) distinguish at least three levels of analysis in structuration research on advanced IT. Level 1, microanalysis is based on the discourse and actions that take place as the IT is used. This level of analysis focuses individual behaviors, speech acts and/or phases and takes the sessions (which might be meetings, discrete periods of use, or arbitrary time periods such as days or weeks) as the unit of analysis. Next is the global level of analysis, which takes the microlevel unit of analysis as its focus. Hence global level analyses look for patterns across sessions (such as entire meetings of a given group). A third level of analysis is the institutional level, in which the focus is on general trends or structural features that hold across multiple groups, organizations, or social systems, and which therefore may signal institutional features.
Table 2. Three Levels of Analysis for Structuration of IT
Level of Analysis
Unit of Analysis
Aspects of Structuration
(Exemplary)
Micro Acts; Speech acts; Phases; Episodes Appropriation moves;
Faithful vs. ironic appropriation;
Instrumental uses of structures;
Attitudes toward structures
Global Sets of micro units; Multiple sets of micro units Dominant appropriation moves;
Degree of faithful appropriation;
Dominant instrumental uses;
Persistent attitudes;
Stable appropriation patterns;
Changes in the above
Institutional Multiple groups, organizations;
Social institutions Structures embedded in larger social units;
Typical moves, instrumental uses, and attitudes;
Characteristics of institutional structures
To understand structuration requires both studies that remain within a given level (e.g., a study of constitution of decisions in quality team interaction) and also studies that cross levels (e.g., a study of how conceptions of voting in different social institutions influence how voting occurs during quality team interaction).
Studies at the different levels build on each other as well. Possible the most logical sequence for studies of group use of IT is to start at the microlevel, then move to the global level, and finally to the institutional level of analysis, progressively investigating more and more strata of the technology's role in organizational change. However, different sequences are also feasible.
Focus. A second choice is the focus of the study: will it concentrate on a single structure or associated set of structures or will it consider the interrelationship among structures in IT structuration? Some studies primarily focus on a limited set of structures of one type. For example, Poole and DeSanctis (1992) analyzed the procedural structures built into a GDSS and how they influenced and were restructured by decision making interaction. Other studies explicitly focus on how two or more distinctive structural features influence one another. For example, Yates and Orlikowski (1992) advanced a model of how the practice of memo writing evolved over time as a function of the interrelationship between the genre of the memo in practice and the set of genres of organizational communication.
Framing. This choice hinges on the ratio of action to structure that the investigator posits. On the one hand, there may be a strong emphasis on structural influence on action. In this type of study the researcher presumes that structure is the lead player and focuses on how this shapes and constrains actions. Studies of how GDSS structures influence decision outcomes (e.g. Watson, DeSanctis, & Poole, 1989) exemplify this approach. Other types of studies emphasize the role of agency in the operation of structures and in their construction and reconstruction. The Poole and DeSanctis (1992) study of microlevel structuration in the use of GDSSs is an example of the second approach, though it is not radically constructive and offers a rather conservative design.
Dynamics. This choice concerns the ratio of production to reproduction that the study incorporates. Some studies focus primarily on change due to structuration; Blomberg’s (1986) study of changes in work design due to implementation of IT is an example of this. Another approach is to focus on stability and how structuring processes are contributing to the stabilization of IT. For example, implementation of IT has often been argued to favor reigning managerial values (Dutton et al., 1998), and studies of the structuring of IT in the organization might explore how it further embeds existing values into the organization. Still other studiesmight consider both change and stability, but give one or the other primacy.
Type of Structure. Stuctures are social constructions, and so are the theories about them. The researcher must adopt a certain model of structure in any study. Following Giddens’ definition of structures as rules (recipes for action) and resources (authority, wealth, or material goods), some researchers focus on these entities and how they are instantiated in IT. For example, DeSanctis and Poole (1994) describe the structures embodied in GDSS tools. They make the distinction between features (specific tools and interface) and spirit (the philosophy and values that the features are meant to enact). The degree to which the features of IT are used in a way that is consistent with its spirit is termed the faithfulness of appropriation.
Another option is to study ensembles of rules and resources. This presumes that structures tend to come in coherent packages of associated rules and resources. Orlikowski and Yates (1994) study the structuration of genres, where a genre is a specific practice that is associated with a particular context or situation, has a specific form and variants, a particular normative force, and a degree of abstraction. Poole, Jackson, Kirsch and DeSanctis (1998) have identified appropriation types, which reflect the degree of mastery of the IT, the uses it is put to, and the amount of reinvention it undergoes.
A third option is to study attitudes related to the IT, or meanings the IT has for users and others. DeSanctis and Poole (1994) argue that attitudes of groups toward GDSS technology colors their appropriation and thus how they use it. Attitudes that have been associated with structuring of IT include comfort with the technology, respect for the IT, challenge in using the IT, and useability.
In some cases several of these models of structure are combined to yield what might be called “indexes” of structuration. Poole and DeSanctis (1990) posited that appropriations differ in the degree to which they are stabilizing. Degree of stabilization is determined by extent of use, faithfulness of use, favorable attitudes toward the IT, and consensus about how to appropriate the IT.
Measurement. Here “measurement” is used broadly to refer to the means of observing or tapping into structuration employed in a study. One popular method of meaurement is direct observation of structuration. This can involve observation of the process as it unfolds (either live or in records such as videotapes) or reconstruction of the process from historical or archival records so that it can be studied as if it were observed. Direct observation may be highly structured—guided by coding systems, for example—or more open and inductive. Observational studies privilege the viewpoint of the observer and tend to lead to imposition of a model of structure on the system.
Another option is the historical study of structuration, which uses archival data to reconstruct a historical account of the structuration of IT. This approach utilizes all the tools of the historian—colligation, interpretation, multiple readings and dense interconnections of elements of the process.
Studies of structuration also seek to get at the subjects’ point of view. Some employ interviews, which enable subjects to inform researchers concerning what structures and structuring mean from their own perspectives. Another way to get subject viewpoints is through rating scales, which have been used to study attitudes toward a system.
Different researchers have their preferences concerning which methods are best for structurational research. The most adequate stance seems to be that each method has its strengths and weaknesses. For a multifaceted phenomenon like structuration, multiple approaches will probably yield the most complete picture over the long run.
Stance. Researchers also take different stances on the research enterprise. In structuration research there seem to be three stances. The positive stance takes the existence of structuration as a given and seeks to explore how it occurs and how it influences use of IT and outcomes for the system. The critical stance presumes that power inequalities and ideologies drive structuring processes and seeks to uncover these. Giddens (1984) takes a critical stance toward structuration. The skeptical stance is taken by those who believe the utility of structuration as a model is still open for each case. They wish to interrogate each situation in order to determine the utility of the structurational model.
These seven choices enable a mapping of the terrain of structurational research on IT in organizations, to which we will now turn.
Research on Structuration of Information Technologies
Previous studies of structuration of IT can be divided into four basic types: case studies, observational studies, laboratory experiments, and surveys. We will consider each in terms of how they have typically been applied, their strengths, challenges they face, and how they contribute to filling out the structurational research agenda.
Case Studies
The most common type of structural study is the case study, and this is true in the information systems area as well. Giddens’ reinterpretation of Durkheim’s study of suicide is one of the first case studies. A wonderful example of a case study is Barthes’ S/Z, which defines numerous threads of signification that wind through a short story and explores how the reader is situtated by the text as it constructs itself through being read. Case studies have particular advantages for research on structuration: (1) They enable researchers to look at
Table 3. Case Studies of Structural in Information Systems
Studies Design Structures Focus
Yates & Orlikowski (1992) Single-case historical study of memo form Genres,defined by stituation, form, level of abstraction, normative scope 1. Change in genre over time
2. Relation of change in genre to historical context
Blomberg (1986) Single-case study of technology implementation; studied two design groups, one before and one after technology implem. Meaning of software
Task design 1.Difference in task design before and after implem. Contrast between the two design groups.
2.Changes in power
Browning, Boyer, & Shetler (1995) Historical single-case study of Sematech consortium via interviews, supplemented by document coding. Constant comparative method. Subject review and comment on case. Social conditions, defined by event clusters that expressed coherent meaning 1.How social conditions promoted cooperation.
2.Structural concomitants of social conditions.
Browning, Sitkin, Sutcliffe, & Greene (1998) Historical single-case study based on interviews and document review Procedures
Spirit and features
Discursive vs. practical knowledge 1.How discursive and practical knowledge relate to procedural document
2.Spirit vs. features in TQM implementation.
Kwong & Walsham, 1989 Historical single-case study based on records and histories Norms
Interpretive Schemes
Facilities 1.How different types of computer systems were shaped by and reshaped government policy.
a phenomenon in depth, which is necessary to unearth the multiple layers of action involved in structuration. (2) The use of one or a few cases allows researchers the luxury of looking at many parts of phenomenon, which facilitates tracing the effects of context on structuration. Since context is quite complex and there are likely to be many effects, an in-depth view is important.
But there are also challenges that case studies must surmount: (1) They have small sample sizes, which make it difficult to determine whether findings are actually substantial or a produce of peculiarities of the case. All of the cases in Table 3 are single-case studies. As more and more studies are conducted, they cumulate (to the extent they focus on the same aspects of structuration), which mitigates this problem somewhat. (2) A by-product of the publication process is a tendency for case studies to focus on the novel aspects of phenomena. Novelty is “news”, whereas repetition of previous findings is much less likely to get journal space. One consequence of this is that replication across cases is downplayed, which further exacerbates the problem noted in point 1. (3) Cases are reconstructions based on interviews and whatever records were deemed appropriate to preserve. Therefore scholars have not enjoyed direct access to the unfolding process and may be giving an inauthentic view. The other side on this point would argue that the salient features of the process have been preserved in memory and records and that this is an advantageous pre-sorting of dross from gold.
As Table 3 indicates, most case studies of IT structuration have focused identification of structures and institutions relevant to structuration (issue 2 on the structuration agenda), on the relationship between institutional and action levels of analysis (issue 4), and some (Yates & Orlikowski, 1992 and Kwong & Walsham, 1989) have focused on how institutions are reproduced in structuration (issue 5). They have tended to be at the global level of analysis, and focus on the interrelationship among structures. Most have framed structuration as an alternation between action and structural influences (see the figures that accompany some of these studies), which breaks with Giddens’ notion of structuration as a duality and moves close to Buckley’s (1978) competing morphogenetis model. In terms of dynamics, the cases seem to include both stability and change and to give stability something of an edge in the ratio in that the changes are portrayed as occurring against a background of the past structure. This may be a by-product of the types of data available to case studies.
In terms of measurement, structures have been conceptualized as fairly encompassing rule or norm sets or as genres in case studies. This conceptualization of structures as broad and complex entities enables case studies to focus on “the big picture” in structuration. Measurement in cases is primarily accomplished through interviews and archival data.
The stance of the majority of case studies of IT structuration has been positive. Structuration has been assumed to occur and critical aspects of structuration have not be much considered in current cases.
Observational Studies
This is the most common category of research study on structuration, as Table 4 indicates (actually, there are more experimental studies which purport to study structuration, but as we will see, several do not qualify as structuration studies). There is quite a variety of observational studies. In general observation studies seem to have the following advantages for those who study structuration: (1) Given favorable observational access. they enable the development and testing of true process theories of structuration, which meets an important requirement of structurational research. (2) Again, subject to constraints on access, observational studies do not restrict the constructs that scholars can utilize as much as interviews or archives, which by their very nature represent selections. (3) If records of the process such as videotapes or field notes are kept, then deeply layered analyses can be conducted. While there are still restrictions on what can be preserved, the “right” kinds of information are more likely to be preserved since it is the investigator who is collecting the data rather than a possibly self-interested participant or archivist.
But there are challenges as well: (1) Observational studies do not enable the researcher to get at the meaning of events for the participants. Instead the observer must deduce what participants must be thinking or feeling if he or she wishes to make claims about meaning or interpretations. In view of well-established attributional biases, these deductions seem unlikely to be entirely accurate. Several observational studies have attempted to address this
Table 4. Observational Studies of Structuration of Information Systems
Studies Design Structures Focus
Robey, Saunders, & Vaverek (1989) Study of computer-conferencing (CC) mediated course with physician, administrator, and nurse participants. Bales’ IPA coding system used to code emessage archive External status structure (preexisting)
Emergent status structure
Interaction patterns
Situational norms for interaction 1.How external structure influences emergent structures in CC
2.How status structures influence interaction patterns.
3.Impact of situational interaction norms (medical care; classroom) on interaction system
4. Evolution of stability of interaction patterns over time.
Orlikowski (1991) Study of single firm, ethnography, interviews, document review Forms of Control: personal, technology, social structure, culture, professional 1.Shift in forms of control due to IT
2.Dialectic of control, whereby IT is used to resist control by organization.
Orlikowski & Yates (1994)
Study of email archive in one organization supplemented by interviews
Genres,defined by situation, form, level of abstraction, normative scope 1.Types of genres that appeared.
2.Change in genres over time
Scott, Quinn, Timmerman, & Garrett (1998).
Qualitative analysis of interviews and transcripts of 26 student groups who used a GDSS GDSS structures (anonymity, equality)
Spirit vs. feature levels
1.Ironic appropriations of GDSSs
2. Variations of ironic use.
(continued on next page)
Table 4 (continued). Observational Studies of Structuration of Information Systems
Studies Design Structures Focus
DeSanctis & Poole (1991) Coded videotapes of 8 groups using GDSS in the field with appropriation function coding system. Longitudinal multiple meeting design. Supplemented with qualitative analysis GDSS structures (tools to support procedures, general organization of system, nature of output) 1.Between group differences in functions of appropriation (task, power, relational, process, etc.) GDSS use.
2.Relationship of appropriation to team effectiveness.
DeSanctis, Poole, Dickson, &Jackson (1993) Coded videotapes of 4 groups using GDSS in the field. Longitudinal multiple meeting design. Supplemented with qualitative analysis. GDSS structures (tools to support procedures, general organization of system, nature of output)
Faithful vs. ironic appropriation
1.Between group differences in GDSS appropriation in terms of extent of use and functions (see previous entry).
2.Relationship of appropriation to team effectiveness
Poole & DeSanctis (1993) Coded videotapes of 8 groups using GDSS in the field with appropriation function coding system. Longitudinal multiple meeting design. Supplemented with qualitative analysis GDSS structures (tools to support procedures, general organization of system, nature of output)
Faithful vs. ironic appropriation
1.Between group differences in GDSS use.
2.Change in appropriations over time and how they occurred (continuously vs. intermittently)
(Continued on next page)
Table 4 (continued). Observational Studies of Structuration of Information Systems
Studies Design Structures Focus
Poole, Jackson, Kirsch, & DeSanctis (1998). Qualitative analysis of videotapes of 8 groups using GDSS in the field with appropriation function coding system. Longitudinal multiple meeting design. Supplemented with coded data. GDSS structures(tools to support procedures, general organization of system, nature of output)
Task structure
1.Appropriation types
2. Alignment of technology and task, and group system in appropriation of GDSS
Chudoba & George (1995) Coding of appropriation of GDSS by 18 laboratory groups GDSS structure (support for tasks; participation equalization)
Faithful vs. ironic appropriation 1.Impact of faithful appropriation on sequence of activities, appropriate use of software, and outcomes
2.Effect of dominant member on appropriation.
drawback by conducting interviews with participants. It is also possible to have participants read and comment on any reports or conclusions. (2) There is a tendency for observational studies focus on microlevel aspects of structuration, making it more difficult to see macrolevel or global dynamics. Observational research that collects multiple cases has a better chance to do this than do studies of single or only a few cases. (3) While observational studies often have more cases than case studies, they still employ somewhat restrictive samples compared to surveys or experiments. An important concern in these studies is selection of cases so that they are a representative sample. The intensive nature of observational studies—which tends to make the intrusive as well—may result in selective sampling of only more cooperative sites or groups.
The variety of observational studies makes characterization of general trends more difficult than it was for case studies. As Table 4 indicates, most observational studies have addressed the nature of the system (issue 1) and identification of important structures relevant to the system (issue 2), though they have not offered as much insight into relevant institutions. They have focused on specification of the structuring process (issue 3) and how institutions enter into structuration at the level of the case (issue 4); these are perhaps the strengths of observational studies. Two observational studies (Orlikowski, 1991, and Orlikowski & Yates, 1994) have also considered the obverse relationship in issue 4 and focused on how structuring processes remake institutions. Observational studies have made little contribution to our understanding of how institutions are reproduced (issue 5) or how actors are positioned/reproduced (issue 6). Nor have they advanced critical analysis of structuration of IT (issue 7).
Observational studies have bridged micro, global and macro levels of analysis, though they are for the most part anchored to the smaller-scale end of the macro level due to their focus on single organizations. Some observational studies have focused on single structures or sets of structures, while others have considered the inter-relationships among structures. Action tends to dominate framing of observational studies, with context serving as a backdrop. Change and stability are both considered in characterizing dynamics, but change is the larger component in the ratio, since it is easier to identify change in direct observation than to sort out continuities. In terms of types of structures studied, observational studies have usually singled out individual rules and resources as they figure in sets. One study has assessed genres through observation. The most common methods of measurement are direct observation supplemented by interviews and documents. As with case studies, the majority of observational studies of IT structuration have been positive in stance.
Experiments
The experiment has also been a common vehicle for the study of structuration in IT, predominantly because studies of GDSSs provide easily accessible labs for the manipulation of structure. At least three types of experimental studies of structuration may be distinguished. First, some studies have employed structuration theory (usually Adaptive Structuration Theory) as part of their theoretical rationale, but not included structuration concepts as independent or dependent variables. This category of study does not really qualify as a structuration study. Second are studies that operationalize structuration indirectly through some variable that is an outcome or concomitant of structuration. For example, Anson et al. (1995) and Wheeler and Valacich (1997) argue that facilitation is a mediator of appropriation. By manipulating facilitation they assume they are manipulating structuration; however, there are no formal measures of structuration constructs, so it is not possible to determine if in fact they are succeeding in their manipulation. The third type of study directly incorporates structuration related measures, such as attitudes toward IT or faithfulness of appropriation.
Table 5. Experimental Studies of Structuration of Information Systems
Studies Design Structures Focus
Anson, Bostrom, & Wynne (1995) 2 (presence vs. absense of facilitation) X 2 GDSS vs. baseline). Used construction task. GDSS use 1.Facilitator impacts on GDSS appropriation and resulting effects on outcomes
Wheeler, Menneck, & Scudder (1993). 2 (composition: high vs. low preference for procedural order) X 2 (high vs. low restrictiveness). None: AST used as partial rationale for predictions, but not tested
Miranda & Bostrom (1993-94) GDSS vs. baseline groups. Studied conflict management over time. None: AST used to support rationale and interpret results, but not tested
Gopal, Bostrom, Chin (1992-1993) 2 (problem solving tasks) X2 (GDSS type). Group attitudes toward GDSS were measured (comfort, respect, challenge, ease of use, compatibility with user). GDSS structures (tools to support procedures, general organization of system, nature of output)
1.Impact of attitudes toward GDSS on outcomes.
2. Shift in relationships among variables over time.
Kahai, Sosik, & Avoilio (1997) 2 (participative vs. directive leadership) X 2 (fairly vs. moderately structured problem) None: AST used to support rationale, but not tested
Wheeler & Valacich (1997) 2 (facilitator vs. none) X 2 (level 1 vs. level 2 GDSS) X 2 (training vs. none). Used hidden profile task. GDSS structures (level of support)
Faithful vs. ironic use 1.Impact of facilitation, training, and level of support on appropriation
2. Impact of faithfulness on use and outcomes
Table 5 (continued). Experimental Studies of Structuration of Information Systems
Studies Design Structures Focus
Watson, DeSanctis, & Poole (1988) Baseline vs. manual vs. level 1 GDSS; budget task GDSS structures (tools to support procedures, general organization of system, nature of output)
1.Not a direct study of structuration, but generates evidence on whether structures affect outcomes
Zigurs, Poole, & DeSanctis (1989) Baseline vs. manual vs. level 1 GDSS; personnel selection task GDSS structures (tools to support procedures, general organization of system, nature of output) 1.Not a direct study of structuration, but generates evidence on whether structures affect outcomes and group interaction
DeSanctis, D'Onofrio, Sambamurthy, & Poole (1989) 2 (Restrictive/Low restrictive) X 3 (Low, Medium, High Comprehensive-ness). Decision making task GDSS structures (varied in terms of restrictiveness and comprehen- siveness) 1.Effects on consensus and attitudes toward GDSS;
2.Effects on interaction patterns.
Sambamurthy & DeSanctis (1990) Level 1 vs. level 2 GDSS vs. manual groups. Cognitive conflict task Level of GDSS structures
Attitudes toward GDSS 1.Effect on consensus and attitudes toward GDSS
Sambamurthy and Poole (1992). Level 1 vs. level 2 GDSS vs. manual groups. Cognitive conflict task Level of GDSS structures 1.Impact of GDSS structures on conflict management in groups.
Sambamurthy, Poole, & Kelly, (1993) Level 1 vs. level 2 GDSS vs. manual groups. Cognitive conflict task Level of GDSS structures
Attitudes toward GDSS 1.Impact on task interaction patterns.
2.Effects on consensus and attitudes toward GDSS.
Table 5 (continued). Experimental Studies of Structuration of Information Systems
Studies Design Structures Focus
Poole, Lind, Watson & DeSanctis (1991). Baseline vs. manual vs. level 1 GDSS; budget task GDSS structures (tools to support procedures, general organization of system, nature of output)
Attitudes toward GDSS
1.The impact of faithfulness of appropriation on outcomes.
2.The impact of attitudes toward GDSS on outcomes.
Experiments have a couple of advantages for the study of structuration: (1) They utilize larger samples of groups and therefore more replications of IT use than do the previous two designs. (2) They control factors that might offer competing explanations for results, thereby leading to “cleaner” studies. But experiments also face challenges: (1) Subjects in an experiment are in a controlling situation, so there is the possibility that they may respond more readily and strongly to structural manipulations than they would under normal circumstances. (2) Since experiments control so many extraneous factors, they eliminate the full body of contextual effects, and thus give only an impoverished view of the role of context in structuration. Even the most careful attempts to create a realistic experimental situation still omit many elements of real situations and so are subject to challenges on the grounds of ecological validity.
Several experiments have addressed the basic issue of whether structure makes a difference by contrasting baseline (no support), manual (noncomputerized procedures), and GDSS (computerized procedures) conditions (Miranda & Bostrom, 1993-4; Watson et al., 1988; Zigurs et al., 1989). This design is intended to separate the impact of procedures from that of using the IT: the baseline vs. manual and GDSS comparison tests the impact of procedures and the manual vs. GDSS comparison tests the impact of taking procedures and moving them into IT. Assuming that the baseline groups are given sufficient resources to realistically tackle the task, and that the manual and GDSS groups differ mainly in medium and not in procedural format, then this design enables researchers to assess the validity of a basic assumption of structuration theory, that variations in structure result in variations in behavior and outcomes. This is a blunt-edged hypothesis, because it tells us nothing about the nature of structuration itself, but variation due to different structuring mechanisms should result if structuration processes are occurring in the groups. Other studies have contrasted level 1 GDSSs, which provide communication support, with level 2 GDSSs, which provide both communication support and support for procedures that could not be undertaken manually (the three studies by Sambamurthy; Wheeler & Valacich, 1997). These studies, too, enable us to test the hypothesis that structuring processes make a difference. Still other studies put this hypothesis to the test by varying other structural properties, such as a restrictiveness and comprehensiveness (DeSanctis et al., 1989; Wheeler et al., 1993).
Once basic differences in outcomes due to structural manipulations have been identified, some designs then observe group interaction to determine whether it mediates the impact of the manipulation on outcomes. Some of these studies have coded behavior that does not directly tap appropriation, but should reflect the impacts of structuration (Sambamurthy & Poole, 1992; Sambamurthy, Kelly, & Poole, 1993; Wheeler & Valacich, 1997; Zigurs et al., 1989). Other studies have coded appropriation or use directly (Poole & DeSanctis, 1992; Poole et al., 1993; Wheeler & Valacich, 1997). Such studies illuminate how structuration occurs as well as providing evidence as to whether structuring interaction mediates the impact of IT on outcomes.
Another method for getting at structuration is to measure attitudes toward the system (DeSanctis et al., 1989; Gopal et al. 1992-3; Sambamurthy & DeSanctis, 1990; Sambamurthy et al., 1993). In such analyses these were included as mediators of structural manipulations on other outcomes as well as outcomes in their own right. This procedure enables a test of the hypothesis that it structuration processes mediate the impact of IT on outcomes.
Experiments have explored the nature of the system by identifying key factors that affect group interaction and outcomes (issue 1). They have tested the counterfactual that GDSS structures do not impact interaction and outcomes (issue 2). Coding of group interaction in experiments has helped to characterize the structuring process (issue 3). Experiments have not had much bearing on issues 4 through 7.
In terms of design choices, most experiments have adopted the micro and global levels of analysis and a singular focus, due to their emphasis on manipulation and control. They have generally been framed as studies of contextual effects on structuring. In terms of dynamics, most experiments have focused on stability and change, with more emphasis on stability; the nature of the manipulation does not change during the study and so it becomes a stable intervention that the system reacts to and then stabilizes itself. Structures have typically been modeled as rule and norm sets in experimental research, and very often there has been an attempt to manipulate a single feature. Subject ratings and direct observation have been used to measure characteristics of structuration; in addition, the manipulation in most experiments is an operationalization of the structures given to subjects. The stance of experimental reports is positive with an undercurrent of skepticism. By their very nature, experiments can
Surveys
At least two sets of questionnaires have been developed to measure structurational constructs related to structuration. A group based at University of Calgary (Salisbury, Gopal & Chin, 1996; Chin, Gopal & Salisbury, 1998) have developed instruments to measure perceptions of faithfulness and consensus on appropriation. These have been carefully developed and validated in several studies. DeSanctis and Poole (in press) developed an instrument that taps seven dimensions of workgroup perceptions of appropriation of advanced IT: respect for the IT; comfort with the IT; degree to which the team has adapted the IT; degree of understanding of the IT; extent to which the IT has been used to include members in decision making; extent to which the IT has been used to manipulate the group; and consensus on appropriation. Preliminary analyses suggest that this instrument will be useful in further research.
Surveys are advantageous for structuration research because they tap large samples and can be used in field situations. They are limited in that they do not tap the process of use per se, but rather subjects’ summary recollections and interpretations of it.
Survey approaches seem likely to address the first three issues in the structurational agenda, and less likely to tackle the last four. They gather information at global and macro levels rather than the micro level and can be focused on both singular structures and relationships among structures. They generally frame research to emphasize structure over action, and they emphasize stability over change dynamics (however, longitudinal surveys can capture change to some extent). Surveys have modeled structures as rules and norm sets and as attitudes toward IT, and they gather data directly from subject ratings. They have generally adopted a positive stance toward structuration.
Observations
One noteworthy feature of the empirical studies of structuration in information systems is the broad range of methods that have been utilized. Moreover, the different approaches seem to have the potential to complement one another, since each tends to focus on different issues and has different strengths and weaknesses.
The reality is less sanguine than the potential, however. While studies of structuration could be complementary, adherents of the different camps have made relatively little effort to ensure synergies. Topics addressed in structuration studies are extremely diverse and there is not much sense that studies by researchers using the different methods have built on each other or attempted to address complementary issues. This is not the case within each approach, where there seem to be active efforts to take results of other similar researchers into account.
Two issues in particular seem neglected up to this point in time: the positioning of actors by the technology and critical analysis. There is also less attention to how institutions are produced and reproduced than would be optimal. While there are large lacunae in our knowledge on the other issues, at least research seems to be addressing them.
References
Blomberg, J. L. (1986). The variable impact of computer technologies on the organization of work activities. Proceedings of the Conference on Computer-Supported Cooperative Work.
DeSanctis, G., D'Onofrio, M. J., Sambamurthy, V., & Poole, M. S. (1989). Comprehensiveness and restrictiveness in group decision heuristics: Effects of computer support on consensus decision-making. In J.I. DeGross, J.C. Henderson, & B.R. Konsynski (Eds.), Proceedings of the Tenth International Conference on Information Systems (pp. 131-140). New York: ACM Press.
DeSanctis, G. & Poole, M. S. (1991). Understanding the differences in collaborative system use through appropriation analysis. In J.F. Nunamaker (Ed.), Proceedings of the Twenty-Fourth Annual Hawaii International Conference on System Sciences, Vol. III (pp.547-553). Los Alamitos, CA: IEEE Computer Society Press.
DeSanctis, G., & Poole, M. S. (1994). Capturing the complexity in advanced technology use: Adaptive structuration theory. Organization Science, 5, 121-147.
DeSanctis, G., Poole, M. S., Dickson, G., & Jackson, B. (1993). An interpretive analysis of team use of group technologies. Journal of Organizational Computing, 3, 1-31.
Dickson, G. W., Poole, M. S., DeSanctis, G., & Jackson, B. M. (in press). Electronic communication technology in the transition to new organizational forms: Coordination or chaos? Journal of High Technology Management.
Poole, M. S. (1991). Procedures for managing meetings: Social and technological innovation. In R.A Swanson & B.O. Knapp (Eds.), Innovative meeting management (pp. 53-110). Austin, TX: 3M Meeting Management Institute.
Poole, M. S. & DeSanctis, G. (1990). Understanding the use of group decision support systems: The theory of adaptive structuration. In J. Fulk & C. Steinfield (Eds.), Organizations and communication technology (pp.175-195). Newbury Park, CA: Sage.
Poole, M. S. & DeSanctis, G. (1992). Microlevel structuration in computer-supported group decision-making. Human Communication Research, 19, 5-49.
Poole, M.S., Holmes, M., & DeSanctis (1991). Conflict management in a computer-supported meeting environment. Management Science, 37, 926-953.
Poole, M. S., Jackson, M., Kirsch, L., & DeSanctis, G. (1998). Alignment of system and structure in the implementation of group decision support systems. In S. J. Havlovic (Ed.), Conference Best Paper Proceedings, Academy of Management. (CD-ROM)
Sambamurthy, V. & DeSanctis, G. (1990). An experimental evaluation of GDSS effects on group performance during stakeholder analysis. In J.F. Nunamaker (Ed.) Proceedings of the Twenty-Third Annual Hawaii International Conference on System Sciences, Vol. III (pp. 79-89). Los Alamitos, CA: IEEE Computer Society Press.
Sambamurthy, V. & Poole, M. S. (1992). The effects of variations in capabilities of GDSS design on management of cognitive conflict in groups. Information Systems Research, 3, 224-251.
Sambamurthy, V., Poole, M. S., & Kelly, J. (1993). Effects of level of sophistication of a group decision support system on group decision-making processes. Small Group Research, 24, 523-546.
Watson, R. W., DeSanctis, G., & Poole, M. S. (1988). Using a GDSS to facilitate group consensus: Some intended and unintended consequences. MIS Quarterly, 12 463-480.
Zigurs, I., Poole, M. S., & DeSanctis, G. (l988). A study of influence in computer-mediated group decision making. MIS Quarterly, 12, 625-644.
Appendix A
An Example of the Basic Concepts of Structuration, as applied to Group Decision Support Systems
(from DeSanctis and Poole, 1994)
To illustrate the principles of AST, we consider the small group meeting and the use of a group decision support system (GDSS). A GDSS is an interesting technology for study because its structures can be arranged in a myriad of ways and social interaction unfolds as the GDSS is used. Consequently, the structure of the technology and the emergent structure of social action provide fascinating foci for the researcher. We begin by positioning AST among competing theoretical perspectives of technology and change. Next, we describe the theoretical roots and scope of the theory as it is applied to GDSS use and state the essential assumptions, constructs, and premises of AST. We conclude by outlining an analytic strategy for applying AST principles and by providing an illustration of how our analytic approach can shed light on the process of technology use and behavioral change in small group decision making.
1.0 Introduction
Information plays a distinctly social, interpersonal role in organizations (Feldman & March 1981). Perhaps for this reason, development and evaluation of technologies to support the exchange of information among organizational members has become a research tradition within the organization and information sciences (Goodman 1986; Keen & Scott Morton 1978; Van de Ven & Delbecq 1974). The past decade has brought advanced information technologies, which include electronic messaging systems, executive information systems, collaborative systems, group decision support systems, and other technologies that enable multiparty participation in organizational activities through sophisticated information management (Huber 1990; Huseman & Miles 1988; Rice 1984). Developers and users of these systems hold high hopes for their potential to change traditional organizational design, intelligence, and decision-making for the better, but what changes do these systems actually bring to the workplace? What technology impacts should we anticipate, and how can we interpret the changes that we observe?
Many researchers believe that the effects of advanced technologies are less a function of the technologies themselves than of how they are used by people. For this reason, actual behavior in the context of advanced technologies frequently differs from the "intended" impacts (Kiesler 1986; Markus & Robey 1988; Siegel et al. 1986). People adapt systems to their particular work needs, or they resist them or fail to use them at all; and there are wide variances in the patterns of computer use and, consequently, their effects on decision making and other outcomes. We propose adaptive structuration theory (AST) as a framework for studying variations in organizational change that occur as advanced technologies are used. The central constructs of AST, structuration (Bourdieu 1978; Giddens 1979) and appropriation (Ollman 1971), provide a dynamic picture of the process by which groups incorporate advanced technologies into their work practices. According to AST, group adaptation of technology structures is a key factor in organizational change. There is a "duality" of structure (Orlikowski in press) whereby there is an interplay between the types of structures that are inherent to advanced technologies and the structures that emerge in human action as people interact with these technologies.
The focus of our analysis is the small group using a group decision support system (GDSS). A GDSS is one type of advanced information technology; it combines computing, communication, and decision support capabilities to aid in group idea generation, planning, problem solving, and choice making. In a typical configuration, a GDSS provides a computer terminal and keyboard to each participant in a meeting so that information (e.g., facts, ideas, comments, votes) can be readily entered and retrieved; specialized software provides decision structures for aggregating, sorting, and otherwise managing the meeting information (Dennis et al. 1988; DeSanctis & Gallupe 1987; Huber 1984). A GDSS is an interesting technology for study because its features can be arranged in a myriad of ways and social interaction is intimately involved in GDSS use. Consequently, the structure of the technology and the emergent structure of social action are in prominent view for the researcher to study. There currently is burgeoning interest in GDSSs and their potential role in facilitating organizational change.
In this paper we outline the assumptions of AST and detail a methodological strategy for studying how advanced technologies such as GDSSs are brought into group interaction to effect behavioral change. We begin by positioning AST among an array of theoretical perspectives on technology and change. Next, we describe the theoretical roots and scope of the theory as it is applied to GDSS use and state the essential assumptions, constructs, and premises of AST. Finally, we outline a method for identifying structuring moves and present an illustration of its application. Together, the theory and method provide an approach for penetrating the surface of advanced technology use to consider the deep structure of technology-induced organizational change.
2.0 Theoretical Roots of AST
2.1 Competing Views of Advanced Information Technology Effects
Two major schools of thought have pursued the study of information technology and organizational change (see Table 1). The decision-making school has been more dominant. This school presumes that decision making is "the primordial organizational act" (Perrow 1986); it emphasizes the cognitive processes associated with rational decision making and adopts a psychological approach to the study of technology and change. Decision theorists espouse "systems rationalism" (Rice 1984), the view that technology should consist of structures (e.g., data and decision models) designed to overcome human weaknesses (e.g., "bounded rationality" and "process losses"). Once applied, the technology should bring productivity, efficiency, and satisfaction to individuals and organizations. Variants within the decision school include "task-technology fit" models (Jarvenpaa 1989), which stress that technology must match work tasks in order to bring improvements in work effectiveness, and so-called "garbage can" models (Pinfield 1986), which emphasize the timing of events and the need for technology to support information scanning and information search activities.
Decision theorists tend toward an engineering view of organizational change, believing that failure to achieve desired change reflects a failure in the technology, its implementation, or its delivery to the organization. Research hypotheses are grounded in either hard-line determinism, the belief that certain effects inevitably follow from the introduction of technology, or more moderate contingency views, which argue that situational factors interact with technology to cause outcomes (see Gutek, Bikson & Mankin 1984). Decision theorists favor quantitative research approaches that measure the effects of technology manipulation on outcomes.
Within the GDSS literature, technology design guidelines put forth by Dennis et al. (1988), DeSanctis & Gallupe (1987), and Huber (1984), and experimental studies conducted by Jarvenpaa, Rao, and Huber (1988), Watson, DeSanctis and Poole (1988), and others (Connolly, Jessup, & Valacich 1990; Gallupe, DeSanctis, & Dickson 1988) exemplify the decision school perspective. This line of research evaluates the effectiveness of GDSS technology by comparing groups given GDSS support with those given manual or no decision structuring, or by comparing groups given certain types of GDSS structures with those given alternative designs of structures. Assuming a technological imperative, researchers expect GDSS conditions to yield more desirable outcomes than groups in other conditions.
The decision school has yielded an extensive literature on GDSSs and other advanced technologies, but the approach has not produced a consensus on how these systems should be designed or on how they affect the people and organizations who use them . For example, some researchers report that GDSS use improves group consensus and decision quality, whereas others report the reverse (see George et al. 1990). Similarly, a number of studies have found differences in attitudes or patterns of use of the same technology design across groups (e.g., Hiltz & Johnson 1987; Kerr & Hiltz 1982). Recently, decision researchers have tried to sort out GDSS impacts by isolating specific features or properties of the technology for study. For example, Connolly et al. (1990) manipulated anonymity and the evaluative tone of electronically communicated comments and measured effects on idea generation, solution quality, and satisfaction. Others have considered the degree of "social presence" of the GDSS media (Hiltz & Johnson 1990); but these approaches have led to mixed results as well, with values on outcome measures being improved in some cases and worsened in others (Jessup, Connolly, & Galegher 1990).
There is no doubt that technology properties and contextual contingencies can play critical roles in the outcomes of GDSS use. The difficulty is that there are not clearcut patterns indicating that some technology properties or contingencies consistently lead to positive outcomes of GDSS use whereas others do not. Observed effects do not hold up robustly across studies, and, even more disturbing, there is often a great deal of variance on outcome measures within even one treatment of any given study (e.g., Jarvenpaa et al. 1988). To achieve greater consistency in empirical findings, decision school researchers advocate progressively finer, feature-at-a-time evaluation of technology and more complex contingency classifications schemes (e.g., see Pinsonneault & Kraemer 1989; Connolly et al. 1990). The difficulty is, of course, the repeating decomposition problem: there are features within features (e.g., options within software options) and contingencies within contingencies (e.g., tasks within tasks). So how far must the analysis go to bring consistent, meaningful results?
Researchers within the institutional school advocate a different approach: the study of technology as an opportunity for change, rather than as a causal agent of change (Barley & Tolbert 1988; Kling 1980). The focus of study for institutionalists is less on the structures within technology, and more on the social evolution of structures within human institutions. Institutionalists criticize decision theorists for the "technocentric" assumption that technology contains inherent power to shape human cognition and behavior; this assumption, they contest, leads to "gadgetphilia," an overemphasis on hardware and software and an underemphasis on the social practices that technologies involve (Finlay 1987; Markus & Robey 1988). A strategic choice model is advocated instead: technology does not determine behavior; rather, people generate social constructions of technology using norms, interpretive schemes, and power resources embedded in the larger institutional context (Orlikowski in press). Many institutionalists emphasize the role of ongoing discourse in generating social constructions of technology (e.g., Barley & Tolbert 1988; Scott 1987), with a consequent emphasis on human interaction (rather than technology per se) in studies of advanced technology effects.
Institutionalists began with the study of communities and society as a whole (Giddens 1979; Selznick 1969), but institutional theory has been developed for organizations as well (Kling 1980). Theoretical perspectives aligned with the institutional school in the study of organizations include social information processing theory, which emphasizes the social construction of meaning (Fulk et al. 1987; Salancik & Pfeffer 1978); and symbolic interactionism, which focuses on the role of communication in the creation and preservation of the social order, i.e., roles, norms, values, and other social practices (Reichers 1987). For institutionalists, the creation, design, and use of advanced technologies are inextricably bound up with the form and direction of the social order. It follows that studies of technology and organizational change must focus on interaction and capture historical processes as social practices evolve. Qualitative, process-oriented methods are favored over quantitative, outcome studies, and ideographic, interpretive accounts are preferred over nomothetic research designs (Barley & Tolbert 1988). Within the institutional school, technology is considered to be interpretively flexible (Orlikowski in press), and so analysis is the process of looking beneath the obvious surface of technology's role in organizational change to uncover the layers of meaning brought to technology by social systems.
There is growing interest in institutional analyses of advanced information technologies, including GDSSs, though actual accounts are sparse (Barley 1986; Finlay 1987; Kling & Scacchi 1982; Markus & Forman 1989; Robey, Vaverek & Saunders 1989). These analyses describe the interplay between technology and power distribution, politics, stratification, and other social processes. Institutional accounts of organizational change are inherently less interested in the properties of technology than in human interpretations of technology and the evolution of social practices. Consequently, the purely institutional approach underplays the role of technology in organizational change. A more complete view would account for the power of social practices without ignoring the potency of advanced technologies for shaping interaction and thus bringing about organizational change.
2.2 An Integrative Perspective
How might the decision and institutional perspectives be integrated? Several theoretical views synthesize assumptions from these competing schools to form what we will refer to as the social technology perspective. This third school of thought advocates "soft-line" determinism, or the view that technology has structures in its own right but that social practices moderate their effects on behavior (Gutek et al. 1984). For example, sociotechnical systems theory argues that the impacts of advanced information technologies depend on how well social and technology structures are jointly optimized; technology adoption is interpreted as a process of organizational change (Bostrom & Heinen 1977; Hiltz & Johnson 1990; Pasmore 1988). Similarly, structuration theory, largely associated with Giddens' institutional theory of social evolution (1979), has been applied to explain organizational adoption of computing and other technologies (Barley 1986, 1990; Orlikowski in press; Robey et al. 1989). To date, structurational models have studied how technology changes the social systems of organizations, professions, and departments; they have not been applied to small group settings.
A third social technology model, structural symbolic interaction theory, takes a more "micro" view, examining interpersonal interaction as the media of advanced technology are varied (Saunders & Jones 1990; Trevino, Lengel & Daft 1987). The theory more fully explores the inherent structure of technology than structurational models, but it has been applied more to the study of peoples' perceptions of technology than to their actual behavior. Also, the theory does not explain the dynamic way in which technology and social structures mutually shape one another over time.
Adaptive structuration theory extends current structural models of technology-triggered change to consider the mutual influence of technology and social processes in small group settings. AST provides a detailed account of both the structure of advanced technologies as well as the unfolding of social interaction as these technologies are used. Its goal is to confront "structuring's central paradox: identical technologies can occasion similar dynamics and yet lead to different structural outcomes" (Barley 1986, p. 105). To present the theoretical premises of AST, we focus here on small group interaction in the context of GDSS technology, but the basic concepts and relationships posited here could be applied to other advanced technologies. We consider both the structures of GDSS technology and the structures realized in interaction, but we particularly attend to the latter in this exposition. We leave more in-depth analyses of GDSS and related advanced information technology structures to other discussions (DeSanctis et al. 1989, DeSanctis, Snyder & Poole 1990; Huber 1990; Silver 1991). The theoretical premises presented here can be refined to formulate specific research hypotheses, thus providing an empirical research agenda (e.g., see DeSanctis et al. 1989; Poole & DeSanctis 1990; Poole, Holmes & DeSanctis 1991).
3.0 Premises of Adaptive Structuration Theory
AST provides a model of that describes the interface between advanced information technologies, institutional structures, and human interaction. AST focuses on structures, rules and resources provided by technologies and institutions as the basis for human activity. Structures are the information and procedures that serve as templates for planning and accomplishing tasks. A GDSS presents a group with an array of potential structures to draw into its work, including procedures (e.g., voting routines) and resources (e.g., stored data, public display screens). Other institutional features such as work tasks, organizational knowledge, and standard operating procedures also provide structures for activity.
3.1 GDSS Technologies as Social Structures
GDSSs and other advanced information technologies bring social structures, which enable and constrain interaction, to the workplace. Whereas traditional computer systems support accomplishment of business transactions and discrete work tasks, such as billing, inventory management, financial analysis, and report preparation, advanced information technologies support coordination between people and provide social processes for accomplishing interpersonal exchange. GDSSs, for example, provide electronic paths for exchanging ideas between meeting participants and formulas for integrating the work of multiple parties. In this sense, GDSSs have greater potential than traditional business computer systems to influence the social aspects of work.
The social structures inherent to a GDSS can be described in two ways: the specific structural features in the given GDSS and the spirit of this feature set. Structural features are the specific types of rules and resources, or capabilities, offered by the system. They govern exactly how information can be gathered and otherwise managed by users. Features within a GDSS, for example, might include anonymous recording of ideas, periodic pooling of comments, or alternative voting algorithms for making group choices. A given GDSS can be described and studied in terms of the specific structural features that its design contains, but most GDSSs are really "sets of loosely bundled capabilities and can be implemented in many different ways" (Gutek et al. 1984, p. 234). Because of the variety of implementations and possible combinations of features, a parsimonious approach is to scale GDSSs along a meaningful set of dimensions that reflect their social structures. Numerous dimensions for describing GDSSs and other advanced technology structures have been proposed. For example, Silver (1991) characterizes decision support systems in terms of their relative restrictiveness. The more restrictive the technology, the more limited is the set of possible actions the user can take; the less restrictive the technology, the more open is the set of possible actions for applying the structural features. GDSSs might also be described in terms of their level of sophistication and their degree of comprehensiveness. For example, DeSanctis and Gallupe (1987) have identified three general levels of GDSS: Level 1 systems provide communication support; level 2 systems provide decision modeling; and level 3 systems provide rule-writing capability so that groups can develop and apply highly specific procedures for interaction. Abualsamh, Carlin & McDaniel (1990) and Cats-Baril and Huber (1987) characterize systems based on their degree of comprehensiveness, or the richness of their structural feature set. The more comprehensive the system, the greater the number and variety of features offered to users. Scaling structural feature sets in terms of restrictiveness, level of sophistication, comprehensiveness, or other dimensions, can be accomplished by consulting user manuals, reviewing the statements of designers or marketers of the technology, or noting the comments of people who use the technology.
GDSS structures can also be described in terms of their spirit (Poole & DeSanctis 1990). These are the general purposes or goals underlying a given set of structural features. Whereas the features contain specific resources and rules, the spirit is the principle of coherence associated with the bundle of features, or overall design of the GDSS. Spirit is a property of the technology, though it may reflect designers' intentions. The spirit of a GDSS can be identified by regarding it as a "text" and developing a reading of its philosophy and basic principles based on analysis of (a) the design metaphor underlying the system (e.g., "electronic chalkboard"), (b) how features are named and presented, particularly in the interface, and (c) training materials and system help facilities. For example, the spirit a GDSS developed at the University of Minnesota, known as Software Aided Meeting Management (SAMM) (DeSanctis, Sambamurthy & Watson 1987), is to promote participative group meetings that result in the most thorough and balanced deliberations possible. The SAMM design assumes that decision-making should be rational and democratic, with decisions made on the strength of good reasons and reasons that appeal to most members. It also assumes that members should not be pressured into agreeing but should consent because they actually agree with good reasons. When considering the technology spirit we are more concerned with questions like, "What kind of atmosphere is being promoted by the GDSS?" or "What kind of leadership is being supported?" than we are with questions like "What does the system look like?" or "What modules does it contain?" Table 2 gives example dimensions for characterizing the spirit of a GDSS. DeSanctis et al. (1990) provide a method for scaling the structural features and spirit of a GDSS based on both designer and user perspectives.
The spirit and structural feature sets form the structural potential of a GDSS, thereby encouraging particular social structures in interaction. For example, a restrictive, level 2 system with a spirit of high formalism and efficiency might be expected to promote a parsimonious, step-by-step, data-oriented approach to group decision making. Group members might be expected to stick closely to the agenda and procedures provided by the GDSS, with little room to diverge from the prescribed approach or to invoke decision structures other than those embedded in the GDSS. On the other hand, a less restrictive, level 1 system with an informal spirit might lead to a looser application of the GDSS structures to the decision process, with a relaxed atmosphere and a mixture of GDSS and other structural use appearing in the group's interaction. In sum, we propose the following:
P1. GDSSs contain embedded social structures, and these social structures can be described in terms of the structural features and spirit of the GDSS. To the extent that GDSSs vary in their spirit and structural features sets, different forms of group interaction are encouraged by the technology.
The features of a GDSS are generally intended to promote its spirit; however, spirit and features are functionally independent. Members may use features in ways contrary to the system's spirit. The implications of this are discussed in section 3.3. 3.2 Other Sources of Structure
GDSS technologies are but one source of structure for users. The structures contained in GDSSs may be used directly, but more likely they are invoked in combination with other structures. The content and constraints of a given work task are a major source of structure (McGrath 1984; Poole, Seibold, & McPhee 1985). For example, if alternative projects are being prioritized for budgeting purposes, then information about these projects and standard organizational procedures for computing budgets are important resources and rules for group members as they undertake the prioritization task. Similarly, the organizational environment provides a major source of structure. For example, current pressures to reduce spending or circumstances that favor certain projects over others may be brought into group interaction as members confront a budgeting task. Corporate information, histories of task accomplishment, cultural beliefs, modes of conduct, and so on, all provide structures that groups can invoke when using an advanced information technology. These structural opportunities and constraints can affect what technology structures the group selects for use, how the results are interpreted, and how they are applied. AST is consistent with contingency theories in proposing that the effects of technology may vary across contexts:
P2. The effect of GDSS technology structures on interaction may vary depending on the task, the environment, and other contingencies that provide social structures for interaction.
So the major sources of structure for group members as they interact with a GDSS are: the GDSS itself, the task, and the organizational environment. As these structures are applied, their outputs become additional sources of structure for the group. For example, after the group enters data into the GDSS, the information generated by the system becomes another source of social structure. Similarly, information generated by applying task knowledge or environmental knowledge constitutes a source of social structures. In this sense, the group has emergent sources of rules and resources upon which it can draw as social action unfolds. The GDSS itself is but one source of social structure for the group.
P3. New sources of structure emerge as the GDSS technology, the task, and environmental structures are applied during the course of group interaction.
3.3 GDSSs in Action
AST views technology as a trigger for social change, along with other sources of structure, such as task, environment, and the outputs of each. AST assumes that these structures are not simply unchanging tools, but that the act of bring a structure into action is the key to its ultimate impact and survival. The process by which structures enter into action is termed structuration. Structuration is a process by which systems (e.g., groups and organizations) are produced and reproduced through members' use of rules and resources. For example, suppose that a GDSS contains brainstorming and notetaking techniques (level 1 features, with low compre-hensiveness) that are highly flexible in their application (low restrictiveness) and that these features are presented to a group as promoting a spirit of efficiency and democratic participation. Structuration occurs as the group applies the brainstorming and notetaking techniques to their meeting, or strives for a spirit of efficiency or democracy.
A key assumption of AST is that not only is the system (i.e., the group) produced and reproduced through structuration, but the structures themselves are too. So, for example, when a group uses a voting procedure built into a GDSS, it is employing these rules to act, but--more than this--it is reminding itself that these rules exist, working out a way of using the rules, perhaps creating a special version of them. In short, the group is producing and reproducing the rules for present and future use. Structuration implies not only the use of these techniques in a given group or meeting, but also the institutionalization of these techniques or emergent forms of the techniques as they are used and reused over time by the group. When the technology structures become shared sets of cognitive scripts, or norms for interacting in the group, then the structural potential of the GDSS has brought about organizational change.
As noted earlier (P2 and P3), members actively adapt GDSS structures as part of a larger social context. Giddens (1979) terms these appropriations of structures into concrete situations "modalities" of structuration. Here we follow Ollman (1971) and simply call them appropriations, which are the immediate, visible actions that evidence deeper structuration processes. GDSS-triggered organizational change is conceived as a process of group appropriation, adaptation, and reinvention of technological structures in the context of the group task and other environmental demands. Structures are stabilized if the group appropriates them in a consistent way, reproducing them in similar form over time. In the same vein, the group may intentionally or unintentionally change structural features; reproduction does not necessarily imply replication. One common way in which structures are changed is by merging them with other structures. For example, if a group with a strict hierarchy of authority attempts to use an egalitarian-oriented GDSS to change to a self-managed style, it may change the GDSS slightly as it merges it into the existing authority system.
In sum, the structures embedded in GDSSs provide occasions for behavioral change, but change only occurs if these structures are actually brought into action. As GDSS structures are applied, interpreted, perhaps combined with other structures (e.g., task), and perhaps constrained by others (e.g., environment), they are produced and later reproduced as they are applied again by the group. Over time, new forms of social structure may emerge that represent reinventions of GDSS structures, or blendings of technology with other structures (e.g., task and environment). Once emergent structures are widely-used and widely-accepted, they may become institutions in their own right and the change is fixed in the organization.
P4. The social structures derived from appropriation of a GDSS may evolve into new forms as they are used and reused over time.
Appropriation and decision making processes. Appropriations are not automatic or deterministic as a result of technology designs. When using a GDSS group members actively choose structural features from among a large set of potentials. Further, they may choose to appropriate a given feature in different ways, invoking one of many possible appropriation moves. The features of a GDSS are designed to promote its spirit, but they are functionally independent and may be appropriated in ways that are not faithful to the spirit. Group members may choose to appropriate GDSS features faithfully or unfaithfully; they may also choose to appropriate the features for different instrumental uses, or purposes; and they may vary in their attitudes toward appropriation of the GDSS. (In section 4.1 of this paper we define these appropriation processes and outline an approach for analyzing them.) Appropriation processes may be subtle and difficult to observe, but they are evidenced in the interaction that makes up group decision processes; appropriations are, in essence, the "deep structure" of group decision making. How group members appropriate GDSS and other potential structures will influence the decision processes that unfold.
Decision theorists argue that GDSS features are designed to overcome common difficulties, or "process losses," associated with group interaction (Huber 1984). The assumption is that use of GDSS features, such as anonymous input and display of ideas, computation and display of group member opinions, and quantitative decision models, will improve the processes and outcomes of group decision making (DeSanctis & Gallupe 1987; Huber 1984). Decision process improvements include:
• expanded idea generation (Nunamaker, Applegate & Konsynski 1988)
• more even participation by members in expressing their opinions (Dennis et al. 1988)
• more effective conflict management behavior (Poole et al. in press)
• more even influence by members on the ultimate choices made by the group
(Zigurs, Poole & DeSanctis 1988)
• greater focus on the task, relative to social concerns (McLeod & Liker 1989)
Improvements in these decision processes are expected to lead to desirable outcomes:
• efficient identification of choices (Nunamaker, Vogel & Konsynski 1989)
• accurate choices, or high quality solutions (Bui & Sivasankaran 1990)
• high group consensus (Watson et al. 1988)
• strong commitment to implementing the group decision (Dennis et al. 1988)
AST argues that whether or not the desired processes and outcomes of GDSS use are achieved depends on how the technology structures are appropriated in group interaction. In other words, decision processes and outcomes are realized based on the particular kinds of appropriations made by the group. For example, in general we would expect that faithful appropriations would lead to decision processes that "match" those intended by system designers, thus encouraging desired decision outcomes; on the other hand, unfaithful appropriations of the GDSS are probably less likely to lead to improved decision processes and outcomes. Along the same lines, we would expect desired decision processes and outcomes to be more likely to result when: the amount of GDSS appropriation moves is high (rather than low), the instrumental uses of the GDSS are more task or process-oriented (rather than power or exploratory-oriented), and attitudes toward appropriation are positive (rather than negative).
P5. Group decision processes are influenced by the nature of GDSS appropriations.
Factors influencing the appropriation of structures. Although appropriation processes may not always be conscious or deliberate (Barley 1990), groups make active choices in how technology or other structures will be used in their deliberations. A given structure may be appropriated quite differently depending on the group's internal system, which is the nature of members and their relationships inside the group (see Homans 1950). Factors that might influence how a group appropriates available structures include:
• Members' style of interacting. For example, an autocratic leader may introduce and use GDSS structures very differently than a democratic leader (Hiltz, Turoff, & Johnson 1981). Other stylistic differences, such as differences in group conflict management styles, may also influence appropriation processes (Poole et al. in press).
• Members' degree of knowledge and experience with the structures embedded in the technology. For example, understanding of possible pitfalls and pratfalls in the structures may contribute to more skillful use by certain members (Poole et al. 1991).
• The degree to which members believe that other members know and accept the use of the structures. The better known the structure is, the less members may deviate from the typical form of use.
• The degree to which members agree on which structures should be appropriated. There may be uncertainty about which structures are most appropriate for the given situation or power struggles over which structural features should be used. Greater agreement on appropriation of structures, should lead to more consistency in the group's usage patterns (Poole et al. 1991).
These assumptions imply the following theoretical premise:
P6. The nature of GDSS appropriations will vary depending on the group's internal system.
Appropriation and decision making outcomes. The model presented in Figure 1, which summarizes the relationships discussed in this section, has important implications for the study of GDSS effects on organizational change. A major implication of P1 through P6 is that clean predictions about how GDSS structures will be appropriated, or what the ultimate outcomes of that appropriation will be, are difficult to formulate. The structural features of the GDSS, along with the task, the organizational environment, and the group's internal system, act as opportunities and constraints in which appropriation occurs. Improvement in decision outcomes will emerge only if the group's interaction facilitates successful appropriation of the GDSS and other structures and only if these, in turn, lead to improved decision processes. Thus there is a "double contingency":
P7. Given GDSS and other structural conditions, n1...nk, and optimal appropriation processes and optimal group decision process, then desired outcomes of GDSS use will result.
If group interaction processes are less than optimal, the outcomes of group use of GDSS structures will be less predictable and, on the whole, less favorable. There is a dialectic of control (Giddens 1979) between the group and the GDSS; technology structures shape the group (P1), but the group likewise shapes the structures (P6), exerting control over their use and the new structures that emerge from their use (P3). Organizational change occurs gradually, as GDSS structures are appropriated and bring change to decision processes. Over time, new social structures may become a part of the larger organizational life (P4). The change is evidenced in group interaction (e.g., methods of idea generation, participation, or conflict management). In this way, GDSSs can serve to trigger organizational change, although they cannot fully determine it.
