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Generalization in ProcessTheories of CommunicationMarshall Scott Poole aa University of Illinois Urbana-Champaign ,Published online: 05 Dec 2007.

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COMMUNICATION METHODS AND MEASURES, 1(3), 181–190Copyright © 2007, Lawrence Erlbaum Associates, Inc.

HCMS1931-24581931-2466Communication Methods and Measures, Vol. 1, No. 3, Jul 2007: pp. 0–0Communication Methods and Measures

Generalization in Process Theories of Communication

Generalization in Process TheoriesPOOLE Marshall Scott PooleUniversity of Illinois Urbana-Champaign

Communication is a process and should be explained as such. Process theoriesdiffer from traditional variance theories in that they focus on explaining how aprocess unfolds over time as a series of events, such as a sequence of stages or adialectic. Process explanations are couched in terms of formal and final causality inaddition to the efficient causality that is essential to variance-based explanations.As a result, the criteria governing generalization in process research differ fromthose that apply to variance research. This essay contrasts variance and processtheories and research approaches and discusses generalization in process research,along with implications for communication scholarship.

Communication is a process. This is one of the key features of communicationand figures in many of the 100 or more definitions of communication cataloguedby Dance and Larson (1975). Most introductory communication texts incorporatethe notion of process, and process has been a central focus of much communica-tion scholarship.

There has been, however, surprisingly little emphasis on process in communi-cation research in recent years. A perusal of abstracts from 40 communicationjournals in Communication Abstracts from 2000–2005 indicates that fewer than10% deal with process directly. This may be a reflection of a general turn awayfrom process by communication scholars. However, it may also be due to asubmersion of process under other constructs due to lack of methods for thestudy of process and adoption of approaches from other fields such as psychol-ogy that do not emphasize process as much as communication.

Correspondence should be addressed to Marshall Scott Poole, Department of Speech Communi-cation, University of Illinois Urbana-Champaign, 244 Lincoln Hall, 702 S. Wright St., Urbana, IL61801. E-mail: mspoole@uiuc.edu

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This essay will address process research specifically and focus on general-ization from studies of process. The thesis will be that generality is based ondifferent criteria in process research than it is in traditional social scientificapproaches. We will illustrate the process approach with examples from groupcommunication research, which has been one area of communication researchthat has explicitly focused on process for the past two decades. We could alsohave drawn examples from a number of other lines of communication research,including Baxter and Montgomery’s studies of dialectical processes in interper-sonal relationships (Baxter & Montgomery, 1996), constructivist studies of thedevelopment of children’s persuasive skills (Clark & Delia, 1976), research oncommunication of innovations (Rogers, 2003), research on communicationtechnology impacts (Poole & Holmes, 1995), and studies of agenda-setting inmass communication (Rogers & Dearing, 1988).

Mohr (1982) differentiated variance and process approaches in social scientificresearch, and the distinction has been quite influential in fields such as manage-ment and information systems. In general terms, a variance theory explainschange in terms of relationships among independent variables and dependent vari-ables, while a process theory explains how a sequence of events leads to some out-come. Figure 1 shows a pictorial comparison of the two approaches, and Table 1provides a comparison in terms of basic assumptions and characteristics. Varianceand process approaches require us to adopt quite different research strategies andmethods of analysis and imply different standards for assessing generalizability.Before turning to generalizability, however, it is necessary to compare the twoapproaches in somewhat greater detail, drawing on a more extended discussion inPoole, Van de Ven, Dooley, & Holmes (2000) and Poole (2004).

The primary components of a variance theory are variables that represent theimportant aspects or attributes of the subject under study and relationships among

FIGURE 1 Variance and Process Theories.

Variance Theory Process Theory

Amt ProblemAnalysis (X1)

Number of Options (X2)

Task Complexity(X3)

DecisionMakingEffectiveness

(Y)

Y = f(X1, X2, X3)

ProblemDefinition

ProblemAnalysis

SolutionGeneration

SolutionEvaluation

Decision

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GENERALIZATION IN PROCESS THEORIES 183

those variables. Explanations in variance theories take the form of causalstatements or models that incorporate these variables (e.g., X causes Y whichcauses Z), and an implicit goal of variance research is to establish the conditionsnecessary to bring about an outcome. Causation is literally the driving force ofvariance theories in that causes are assumed to produce the effects in a regularmanner, and knowing the values of the causal variables is sufficient to knowwhat effects will occur. Causes are assumed to act in the manner of Aristotle’sefficient cause, as the immediate forces which bring something about or changesomething. Due to its focus on variables, variance research is concerned withdeveloping reliable and valid measures of those variables and is grounded in thegeneral linear model that underlies most common statistical methods, includingANOVA, regression, factor analysis, and structural equation modeling. A keycriterion for assessing variance theories is their generality, which refers to therange of cases, phenomena, or situations to which the causal explanation applies.

A variance theory of group decision-making based on functional theory, forexample, could explain decision-making effectiveness in terms of variables suchas amount of problem analysis, number of options considered, group cohesion,and task complexity (Gouran & Hirokawa, 1996; Hollingshead, 2005). Func-tional theory posits that amount of problem analysis and number of optionsshould positively affect decision-making effectiveness. Group cohesion shouldhave a curvilinear affect on decision-making effectiveness: effectiveness shouldincrease as cohesion increases up to a point. However, after a group gets verycohesive, its effectiveness should go down, because members are more interestedin enjoying each other than in conducting careful analysis. Task complexity

TABLE 1Variance and Process Approaches Contrasted

Variance Approach: Key Assumptions

• Focus on fixed entities with variable attributes (variabilization of phenomena).• Satisfactory explanations are based on necessary and sufficient causality.• Satisfactory explanation is based on efficient causality.• The generality of an explanation depends on its ability to apply uniformly across a broad range of

cases & contexts.• Monotonic, “well-behaved” causal flow through hierarchical levels.

Process Approach: Key Assumptions• The world is composed of entities which participate in events and which may change as a result.• Satisfactory explanations are based on necessary causality.• Satisfactory explanations are based on final and/or formal causality combined with efficient

causality.• Generality of explanations depends on their versatility.• Temporal ordering is critical to the outcome.• Explanations include layers of causation operating at different levels and temporal scales.• Causes are often not “well-behaved.”

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should have a negative relationship with effectiveness and should interact withproblem analysis so that more problem analysis for complex problems willenhance effectiveness (Hirokawa, 1990). To test the theory, an experiment orsurvey might be conducted, and these variables could be entered into a regressionequation predicting effectiveness.

In this theory, the variables are assumed to capture the aspects of group activitythat are relevant to explaining effectiveness. The variables are “where the actionis” in a variance theory. Note also that two of the variables, amount of problemanalysis and number of options, are surrogate measures of group process that sum-marize the nature of the interaction in synoptic constructs. They are, in essence,external indicators of the nature of the group’s process. A third, group cohesive-ness, is viewed by some as an outcome of group processes that subsequently influ-ences interaction and other outcomes and by others as an emergent from groupinteraction that immediately influences other outcomes and ongoing interaction.Note also that the variables are treated as though they were immediate, efficientcauses of effectiveness in this theory, just as a blow with a hammer drives in anail, so increases in number of options enhances decision-making effectiveness.

In contrast, a process theory conceptualizes the communication process as aseries of events that bring about or lead to some outcome. The unit of analysis isnot the variable but rather an evolving central subject that makes events happen andto which events occur (Abbott, 1988); the unit of observation is the event. Explana-tions in process theories take the form of theoretical narratives that account for howone event led to another, and that one to another, and so on to the final outcome.These theoretical narratives tend to be more complex than the causal chainsadvanced in variance explanations due to the complexity of events, the need toaccount for temporal connections among events, different time scales in the sameprocess, and the dynamic nature of processes. Process explanations may include:

• an account of how one event leads to and influences subsequent events(e.g., events of type A have a .7 probability of being succeeded by events oftype B and a .3 probability of being succeeded by events of type C);

• an explication of an overall pattern that generates the series (e.g., the processdevelops in three stages, A, B, and C);

• an explication of the generative mechanism that drives the process (e.g.,emergence of norms in interaction is a function of evolutionary processeswhereby random variations in current norms are tested and selected ingroup interaction and preserved through repetition); or

• preferably, two or more of the above (in which case the connections amongthem should be articulated).

Process theories may incorporate several different types of explanatory fac-tors, including critical events and turning points, contextual influence at various

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points in the process, formative patterns that give overall direction to the change,and causal factors that influence the sequencing of events. Process explanationsmay incorporate as many as three of Aristotle’s four causes, adding formal andfinal causation to the efficient causation that is the basis of causal explanation invariance research (Poole et al., 2000). Efficient causation exerts itself through thefactors that operate immediately within events and also sometimes through“pushes” that move the central subject from one event to the next. The essence ofa process theory, however, is accounting for change over time, and this is prima-rily done through articulating larger patterns in the events that account for orbring about change. Such accounts cannot be framed in terms of efficient causal-ity, which only operates in the immediate moment.

While efficient causality plays a role in process explanations, its role issecondary to the patterning explanations that final and formal causes provide.Final causality posits an end or goal that guides the unfolding of developmentand change. We most often think of goals in terms of human agency, but finalcausality also includes natural ends and outcomes of natural processes. In itsbroadest sense, final causality is any end state that attracts a developmental orchange process to itself. As such, the final cause draws the central subject alongthe path it follows, within the constraints of particular events and conjuncturesthat occur along the way. Some of these events and conjunctures function toadvance the final cause, while others are “accidents” in that they neither servenor detract from attainment of the final cause. For example, the decision canserve as a final cause of the decision-making process. Since decisions typicallyare actions that respond to problems or exigencies, the nature of the end shapeswhat happens in the discussion, encouraging the group to analyze the problemand consider options that address it. Formal causation stems from a template thatpatterns change. The form must be applied to the developing entity, eitherthrough plan or through some other governing mechanism. In the group arena,for example, form may be materialized as a blueprint for the group to follow or aprocedural chart, such as a list of requirements that a quality team must fulfill incarrying out its projects. In the case of decision making, one or more group mem-bers are likely to have learned the decision-making procedure that mandates anal-ysis of problems before solutions, carefully evaluating whether solutions actuallysolve problems, etc. Members use the procedure to steer the discussion so that itfollows the sequence. Both final and formal causes provide patterns that shapethe unfolding of the process over time. In Mohr’s (1982, p. 59) terminology,process theories incorporate a “pull-type causality: X [the precursor] does notimply Y [the outcome], but rather Y implies X”. The purpose and form to berealized are what drive the process.

A process theory of group decision making based on functional theory wouldposit that groups make a decision by working through several phases: orientation,problem definition, problem analysis, solution generation, solution analysis,

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choice, and implementation planning. The degree to which the group carries outthe activities in each phase completely and effectively would determine the ulti-mate effectiveness of the decision. The sequence of phases is defined in terms ofa logic of decision making that follows John Dewey’s discussion of reflectivethinking as a description of how effective decision making proceeds from doubtto certainty, and thus embodies formal causality driven by the form of a gooddecision process. To the extent that the group does not adequately and fully carryout each phase, the group is likely to run into problems and either need to doubleback to “redo” previous phases or simply finish out the sequence with an inferiordecision.

In the process theory of group decision making, the decision is represented asa sequence of micro-level events, or actions, that are organized into macro-levelevents, or phases, that are the means of getting from the beginning of thediscussion to the decision. The decision is explained in terms of the theoreticalnarrative of the progression through a sequence of phases that is necessary tomake a good decision, and effectiveness is explained in terms of adherence tothis sequence. In this model, variables are not the primary focus; instead, events(actions, phases) are primary. To test the adequacy of the theory, the investigator(a) determines the degree of correspondence between the actual temporal patternof events and that expected based on the theory and (b) tests for additionalindicators that the generative mechanism is in operation (Poole at al., 2000,pp. 84–86 and 98–99). One such additional indicator might be evidence thatgroup members are actively trying to manage their discussion so that it followsthe steps of reflective thinking.

Several other aspects of process research are noteworthy in the example. First,temporal ordering is critical to process explanations. A group that follows thenormative sequence closely is fundamentally different from a group that goes toconsider solutions first, without defining or characterizing its problem. From this,it follows that the significance and impact of later events is critically dependenton the specific events that precede them (i.e., the process is path dependent).Third, process theories can provide necessary though not sufficient explanations.Each event in a sequence of events is a necessary condition and influences thoseevents that follow. However, no event is sufficient to bring about a particularsequence of subsequent events. The complex influences in operation in processesguarantee that until the final event in the sequence has occurred, there is nosufficiency. Fourth, explanations in process research are always after the fact inthe sense that, until the process is complete, there is no way to determine if agiven pattern applies. These characteristics make process explanations funda-mentally different from variance explanations. Finally, efficient causes operate atseveral levels in this explanation as well. They may operate at the micro-level toinfluence moves from act to act (e.g., a directive leader may move the group to anew stage in the process), or external events such as a rejection of the group’s

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decision by an upper-level manager may cause a reorientation of the decision theprocess at a single point in time.

Process research employs eclectic designs that identify or reconstruct theprocess through direct observation, archival analysis, or multiple case studies.Analysis of process data requires methods that can (a) identify and test temporallinkages between events and also overall temporal patterns (Poole et al., 2000)and (b) cope with the multiple time scales that often occur in processes (wheresome events extend for years, other events embedded in them run for shorterperiods, and others embedded within these even shorter periods) (Langley,1999). Whereas the great majority of variance research follows hypothetico-deductive procedures, process research employs a mixture of approaches. Mostoften, process studies derive theory from observation, but in some cases they testhypothesized models of the change process, and in others they use “retroduction”whereby theories are used to guide observation that further specifies the theories(Poole et al., 2000, pp. 115–117). Indeed, in-depth studies of processes mayemploy two or even all three of these approaches (e.g., Van de Ven, Polley,Garud, & Venkatraman, 1999) As a result, both qualitative and quantitativeapproaches are used in process research (Langley, 1999).

With the differences between variance and process research in mind, we cannow turn to the issue of generalization. As these differences may suggest,generalization in process research is based on different criteria than generaliza-tion in variance research. Generalizability in variance research is a function ofidentifying an underlying generative mechanism that specifies causal relation-ships in the phenomenon that applies uniformly across a range of similar cases(generalization to the population) or to other dissimilar cases (generalizationacross populations) or to other phenomena (generalization across contexts)(Shapiro, 2002). In contrast, generalizability of a process theory derives notfrom its uniformity and consistency but from its versatility, the degree to whichit specifies a generative mechanism for a process that can encompass a broaddomain of developmental patterns without modifying its essential character.The broader its domain, the greater the variety of cases, contexts, events, andpatterns a process theory can adapt to, and the more general the explanation.An important difference between process and variance explanations hinges onthe use of terms such as “encompass” and “adapt.” These terms capture a basicquality of process explanations, which attempts to discern a common genera-tive mechanism in a range of complex and seemingly disparate events andsequences.

A defining feature of processes that are empirically observed is their inherentcomplexity. Processes that follow the same theoretical narrative often differ con-siderably in specific sequences due to the particular conjunctions of causes andcontextual factors operating in specific cases. Narrative causality as specified inthe generative mechanisms in a process theory (e.g., a stage-wise developmental

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sequence, a dialectic, an evolutionary model) is “loose” in that it specifies onlythe pattern or form that arranges events in space and time; therefore, it does notexert the deterministic influence over events that efficient causes exert invariance theories. Moreover, in process theories efficient causation may intro-duce perturbations in the process. As a result, cases explainable in terms of thesame theoretical narrative may vary considerably in the nature and patterns ofevents that transpire. Further, the same process may run at different speeds in dif-ferent contexts.

Returning to the example of decision development, it is possible for one groupfollowing the basic Deweyian sequence to take an hour to define its problem andanother two hours to analyze it, then only a half hour to generate solutions(perhaps due to constraints placed by the problem) and select a final course ofaction A second group might define and analyze its problem in 15 minutes (per-haps because one member has already done some research and presents it) andthen spend 3 hours generating and choosing solutions. In a third group, the groupspends an hour defining and analyzing the problem and then during optionsgeneration discovers a flaw in the definition, which it has to go back and take halfan hour to correct; then it proceeds to generate and evaluate options for anotherhour and half. The first two of these groups follow the same sequence but exhibitmuch different decision paths in that the lengths of their phases differ consider-ably. The third group could also be considered to follow the basic sequence if weallow that its short “loop back” was only a minor departure from an otherwisebasic sequence (following rules for “smoothing” out small deviations in decisionpaths; see Poole & Roth, 1989a, for an example).

The central aspect of this example is that the groups follow the same modeldespite widely different actual decision paths, because the generative mechanismcan produce a pattern that is versatile enough to be stretched in some parts andshrunken in others yet still be recognizable overall. This pattern may sometimeseven be interrupted briefly yet clearly resembles the basic sequence, for allpractical purposes.

In the case of the Deweyian decision model, the generative mechanism is thelogical sequence of experience, which moves from encountering problems orblocks to experimentally developing ways to solve or come to terms with them.This provides a logic that dictates the ordering of the phases. In Poole’s (1983)multiple sequence model of decision development, members’ implicit theories ofhow decisions should be made interact with task characteristics such as complex-ity to shape how the group decision unfolds. If all members have been trained inthe Deweyian sequence and the task is not terribly complex, then the group islikely to follow the basic sequence. If there are several different implicit decisiontheories and/or a complex task, the developmental pattern is likely to be morecomplex than the basic model posits and the group will fall under a differentcategory of the decision path typology (Poole & Roth, 1989a and b).

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So researchers seeking to conduct process studies must tackle two tasks. First,they must test whether the pattern expected by a given process theory holds. Thistest must be sensitive enough to recognize the pattern in a range of processesworking at different paces and experiencing “noise” that confuses the observedpattern, but not so liberal that it fails to recognize when the pattern does not fit.Poole et al. (2000) discuss ways to test for basic patterns in processes. Second,the researchers must test for whether the generative mechanism underlying thepattern holds. This often requires evidence beyond the pattern itself. In the caseof the members who hold the Deweyian model, evidence that they discussed it asthey initiated activity would be an example.

The challenges for process researchers are to create theories versatile enoughto discover common narrative forms and to elucidate generative mechanismsapplicable to a broad range complex and disparate cases. The process approachattempts to encompass the uniqueness of individual cases that share a commondevelopmental process. It does not categorize all differences among cases as“error variance” but considers the uniqueness in individual cases to add nuance tothe general explanation.

A versatile explanation enables the researcher to recognize family resem-blance among a broad range of seemingly different events and sequences. Thisincludes recognizing resemblance among events that differ in duration, havemultiple particularizing features, and are enacted by diverse central subjects.Variation in the pattern can be captured in typologies of sequences. These shouldenable the researcher to recognize resemblance among patterns that differ inlength, exhibit different degrees of overlap among contiguous events, and exhibit“noise” in the form of nonessential events which complicate the sequence andalso to recognize clear differences in patterns. Returning to the decision-develop-ment example, Poole and Roth (1989a) developed a typology of decision pathswith three major types and subtypes within each. These represented empiricallydistinctive approaches to making decisions in the groups they observed andprovided the grounds for future classifications and theory development.

Process theories offer a different view of communicative phenomena thantraditional variance approaches. The two perspectives complement each other.Variables characterizing the process such as complexity of decision path, numberof recycles, and conformity to the basic sequence can be used in traditional statis-tical analyses (Poole & Roth, 1989b). This provides useful information on theimpact of the process on outcomes and on variables that influence the process.The process analysis gives useful information on how communication occurs andthe dynamics of the process, as well as critical events and the role of efficientcausality. The two different forms of generality also complement each other, withone referring to generality based on efficient causation and the other based onformal and final causation. Together they capture both active agency and the con-straints that all communication operates within.

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