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Theory and research of organizational decision making (ODM) is organized in two parts: grouping contributions mainly concerned with the ‘logic’ and the ‘politics’ of ODM. Within each, the analysis develops in three movements. First, it points out how some classic ‘divides’ marked the field’s origin, in relation to how uncertainty and conflict of interests may be dealt with. Second, it traces the key subsequent developments showing how the various models can be positioned on an ideal ‘continuum.’ Next, more recent works and research in relevant and related fields are considered, highlighting how they would allow to go beyond those classic continua and to indicate responses to increasing uncertainty and conflict implying ‘stronger’ rather than ‘weaker’ forms of thought.
- The ‘Logic’ of Organizational Decision Making
- The Rationality Divide
- The Classic Continuum of ODM Models
- ODM for Innovation and Discovery
- The ‘Politics’ of Organizational Decision Making
- The Power/Efficiency Controversy
- Conflict Resolution for Efficiency and Equity
- A Twofold Trend
- Implications for Structures
The field of organizational decision making (ODM) is not easy to define. As to the ‘organizational’ qualification, those who engaged in a conceptual definition have usually contrasted it with individual decision making, as ODM entails multiple individuals – whereby issues of communication and conflict may arise – and multiple occasions over time and matters – thereby excluding one-shot decisions among unrelated players – and have usually conceived it as decision making occurring ‘in organizations,’ intended as entities. However, those definitions are in many ways too narrow, with respect to both conceptual consistency and correspondence to the ODM actual empirical research tradition. In fact, to start with, any decision-making entity can be conceived as ‘unitary’ or not depending on the purpose of analysis. Individuals may not be such a unitary unit of analysis as often taken for granted: There can be conflict between objectives and ‘multiple selves’ also within an individual (Elster, 1985). Conversely, a multiperson system may be conceived as a unitary actor, if on a problem at hand, its behavior can be modeled ‘as if’ it were a homogeneous node of knowledge and preference – for example, a firm in the context of defining an alliance with other firms, or a functional unit in the context of defining a new product with other functions. Second, another important sense in which decision making can be qualified as ‘organizational’ is not related to the multiplicity of actors, but to whether an actor is deciding out of an organizational role or on a private basis (Barnard, 1938). Third, although earlier ODM research has been focused on processes going on within the institutional boundaries of organizations as entities (firms, public agencies, etc.), the main propositions and models are actually applicable to any ongoing cooperation, including interorganizational relations.
Hence, we shall adopt here a broad definition of ODM as both single actor and multiple actors, provided that decisions are taken in an organized context: ongoing relations among actors (not instantaneous transactions), but not necessarily internal to an entity, acting for some purpose of effectiveness (not just for leisure and pleasure). (In spite of its breadth, this definition leads to exclude from our analysis of ODM those ‘phenomenological’ traditions that have described all kinds of decision behaviors that may be observed in organization, without an interest in modeling their properties or conditions for effective or ineffective occurrence.)
As to the meaning of ‘decision making,’ the minimum common denominator of all notions can be found in the etymology of the term: ‘de cedere’ means cutting out, partitioning, discriminating, separating, and opting for some thing(s) rather than others. This activity may be performed in a deliberate and conscious way or not. In an organized context, deliberate and conscious action is of course particularly important, as effectiveness matters. Utility theory models coming from economics, as well as most models generated by the ‘cognitive revolution’ in interpreting human behavior are in fact of that type. Nevertheless, all deliberate decision making processes are unavoidably embedded in other processes and factors that drive, constrain, and reduce the variety of possible actions that go beyond actor control and deliberation. On one side, those factors are embodied in the actors themselves, as ‘taken for granted’ and inherited background knowledge (Simon, 1990), or as ‘normative’ and ‘affective’ factors (Zey, 1992). On the other side, decision making is embedded in ecological processes, whereby it is the context/environment that in the end selects proper or viable actions, ‘as if’ actors’ actions were random or blind variations. (To avoid confusion, it should be noticed that the term ‘ecological rationality’ has been used with various different meanings. In its strongest meaning, it has been used by organizational ecologists, in the sense that ‘it is the environment that optimizes,’ by selecting actions by means of selecting the subjects carrying them. In a second meaning, it has been contrasted with constructivist rationality (see Vernon Smith’s Nobel Lecture) to refer to the emergence of ‘patterned action without design’ out of the combination of myriads of actions, in turn largely ‘determined by cultural and biological inheritage.’ Third, it has been taken to refer (e.g., by Gigerenzer and some related authors) to what in decision-making research (and in the present research paper as well) has always (and I think more properly) called ‘contingent rationality’: the deliberate choice by a subject, of a decision strategy deemed appropriate to (his model of) the environment/problem at hand (actually more a ‘metaconstructivist’ rather than ecological notion of rationality).) Actually, before the upsurge of cognitive sciences, decision behavior was predominantly interpreted in terms of instinct and affect or in terms of context-driven selection of actions.
Herbert Simon (1955) provided the most prominent foundations to the entire ODM field and put cognition center stage with respect to both ‘ecological’ rationality and to unconscious and emotional impulses. In his founding works, Simon, as well as some other important social scientists concerned with the foundations of human action (as Kelly and Bandura) criticized behaviorism and psychologism and invited to develop a variety of cognitive models of decision making, suspending a view of human behavior as driven by imperscrutable intuition and emotion. This invitation did not go unheard; actually it had a paramount influence on the evolution of the field. Simon kept a door open to the possibility that once the cognitive modeling of decision making would have been mature, eventually ‘the pendulum would have swung again’ toward an analysis of their relations with affective factors – something that in fact is an emerging trend nowadays (Gavetti et al., 2007;Hodgkinson and Starbuck, 2012). (Less fortunately, also the use of the notion of ‘intuition,’ as contrasted with analytic decision making, is reemerging in ODM literature. However, as Simon repeatedly noticed (e.g., 1989), distinguishing (no matter whether for opposing or blending) ‘analytic’ from ‘intuitive’ thinking is logically incorrect, because no one knows what intuition is; it is like distinguishing processes which have been analyzed from processes that simply have not been. Actually a core aim in Simon’s research program was precisely to discover which logics, which types of analyses, methods, heuristics lay behind what we call intuition or even genius. Hence, here we do not make any use of the term intuition.) Anyhow, models of decision always imply a mix of constraint and freedom (Loasby, 1976): that very mix is what makes choice an interesting activity, with respect to being completely determined (if there is no choice, decision is impossible) or completely unconstrained (if everything works, decision is irrelevant).
The ‘Logic’ of Organizational Decision Making
The Rationality Divide
The history of thought on ODM did have a ‘big bang,’ with the concept of ‘bounded rationality’ (BR) (Simon, 1955). The theory was developed in contrast with utility theory, the dominant model of conscious, purposeful, effectiveness-oriented decision making available at the time, developed especially in economics, and applicable to the behavior of either individual actors or collective organized actors. Since then, most expositions of ODM models are ‘anchored’ to that model, in the sense of elaborating new models by relaxing some of assumptions of that approach, as to both knowledge and interest, considered to be very restrictive. Those assumptions are deemed to be narrow as they include knowledge of all the relevant alternatives and possible states of the world on a matter or problem, as well as the consequences of their combinations and their possible value (utility) for the decision maker (Simon, 1955). The economic model of rational ODM is still summarized in this way in most accounts (e.g., Hodgkinson and Starbuck, 2012) and ‘therefore’ considered to be practically ‘inapplicable.’ A minority of scholars have in turn criticized this characterization of ‘value maximization’ as a straw man, and pointed out that a complete knowledge assumption is different from a value maximizing strategy, which is nothing else than a set of procedures that can be applied with claim of efficiency if the problem at hand is ‘closed’ (Nutt, 1976), the alternatives in the relevant set are countable (Hatchuel, 2001), the task at hand is not too complex (Beach and Mitchell, 1978; Payne, 1982; Peters, 2003), and if knowledge on cause–effect relations as well as on preferences is available (Thompson and Tuden, 1959) or can be constructed in a valid and reliable way (Grandori, 1984). In those works, accordingly, the ODM models ‘alternative’ to value maximization are considered as alternative, contingently effective decision strategies, applicable in other circumstances, not as rival theories of ODM. Therefore, the adoption of alternative decision strategies is seen as metarational behavior rather than as a form of incapacity or of practically useful but inferior, or even biased thought (as it became in the ‘heuristic and biases’ behavioral decision theory). For one reason or another, anyway, most scholars agree on the point that, on most problems, actors (either individual or collective) cannot or even should not model problems so that utility maximizing calculations are applicable, either because it is too costly or cognitively unfeasible to do so, or because it would require to simplify problems to an extent at which they no longer represent reality well. In addition, economists themselves have highlighted that the existence and uniqueness of optimal solutions faces limitations and paradoxes in many multiple actor, multiple interest, interactive decision-making situations. The main alternative models, with a claim of being applicable and predictive under conditions of strong uncertainty and conflict of interests, are illustrated next.
The Classic Continuum of ODM Models
Simon outlined the most important of these models, the ‘satisficing model’ of search and choice. The simplest basic version of that model states that actors will accept the first encountered alternative superior to a given aspiration level, truncating search at that point. If it is difficult to find acceptable alternatives, aspiration levels fall, and if it is easy, they rise. In that version, satisficing would describe primarily a decision behavior capable of generating ‘good’ solutions while reducing the costs of search. Various other decision models, with claims of being able to manage even stronger conditions of uncertainty and conflict, have also been formulated in ODM research.
An ‘incremental model’ has been identified in research on ODM especially in the context of public administration (Lindblom, 1959). A starting provocative empirical finding has been that the best predictor of a year’s budget for a program or activity in local government is the budget of the previous year (Wildavsky, 1964). In an incremental process, the decision system should be able at least to discern where it wants to go: increase rather than reduce production capacity, improve levels of education, and increase well-being. However, it can generate action without making use of theories on the cause– effect relationships that regulate how the action system works and changes. Rather it employs a ‘linear’ choice rule – try ‘incremental’ solutions that differ marginally from those in use and learn afterward.
A cybernetic model, built in conceptual frames such as of control theory and stimulus/response behaviorism, relies even more heavily on ex post learning, and more precisely on learning by reinforcement (Steinbrunner, 1974). A cybernetic decision strategy implies only the following kinds of judgment: the capacity to recognize situations (e.g., a configuration of costs); the capacity to recognize performance gaps with respect to a standard (works/does not work; positive/negative); and possessing a repertory of possible actions that are applicable to eliminate the gap or respond to the situation, adjourned by a principle of reinforcement (repeat successful action, avoid previously failing actions). Processes that can be described and predicted fairly well as cybernetic processes range from some real-time unreflexive stimulus–response motivation processes to some innovation processes (e.g., the diffusion of codified technologies).
A garbage can model of ODM, elaborated in the early 1970s and enjoying a period of significant popularity afterward, can be seen as a limiting case, in which actions are tried at random, guided by chance encounters between actors, with an opening of attention at a certain time, and the emergence of choice occasions (Cohen et al., 1972). It is supposed to be relevant especially under ambiguity: Research using that model has typically studied institutions or processes with ‘ambiguous’ goals or highly unpredictable consequences (e.g., universities and cultural institutions). Although it has been seen as a provocative criticism of the means-ends ‘determinism’ of rationalist models of ODM, and as opposed to rational choice, the actual finding of the ‘garbage can model’ is that if knowledge and preferences are unclear, and alternatives tend to be ‘undistinguishable,’ then random choice (with eventual ex post learning) is the only (and arguably rational) option.
In sum, the main ODM models specified in the second part of the 1900s have been developed by relaxing and extending some of the conditions of uncertainty and conflict which characterized Simon’s initial satisficing model, similarly to how the latter model was developed by relaxing and extending some conditions characterizing economic value maximizing models.
The general pattern envisaged and the implicit or explicit conjecture laying behind all these models is that the higher the level of uncertainty and conflict among interests becomes, the less ‘rational’ the sense of comprehensive and deductively ordered the logic of ODM becomes; the less investment in ex ante knowledge acquisition and the more reliance on ex post learning is made; and the less preferences are integrated and limited agreement is sought on action.
This orderly range of discrete behavioral alternatives on a ‘continuum,’ though, does not tell the whole story, nor makes justice to more recent developments in ODM research.
First of all, the decision procedures and heuristics that ‘usually characterize’ a decision pattern or model may actually be combined to generate hybrid decision behavior that better suits circumstances or captures the advantages of different decision modes simultaneously. Actually, it can be noticed that decision rules traditionally belonging to different models, being respectively focused on the different subprocesses of search, choice and learning, may well ‘need each other’ and be complementary rather than alternative (before applying any choice rule, a problem needs be defined and alternative generated through search and research; and any choice, even if taken according to a correct procedure, may result to be wrong upon test, hence learning is always worthwhile). In addition, it has been noticed early that all these traditional models, including both classic maximizing models and classic BR models, do not seem to encompass all feasible decision behavior or to specify the ‘continuum’ of decision strategies (if it is a continuum) completely. What is neglected is that in decision making, as in any knowledge-based processes, there are ‘epistemic’ issues, which perhaps are the most important issues, such as interpretation and mindful ‘sense-making’ (Weick, 1979), the reliability of information and of action based on it (Weick et al., 1999), and the validity of the knowledge generated and used in the process (Grandori, 2010). In one word, ‘epistemic rationality’ is of paramount importance in good judgment under uncertainty, but it has not been well represented and analyzed in the classic models of ODM.
More precisely and provocatively, traditional ODM research falls short of modeling those decision behaviors which respond to uncertainty not by avoiding it, but by investing in research and knowledge construction, and more precisely in reliable and valid knowledge generation, thereby leading to effective discovery and innovative decision behaviors (Grandori, 1984). At the time this observation was made, though, innovation was not so central as it is nowadays. In the next section, more recent research on effective ODM for innovation, which can fill this gap, is reviewed.
ODM for Innovation and Discovery
A fair amount of research is available on ODM in areas such as entrepreneurship, technological innovation, and strategic innovation. Studies on decision processes in the more innovative and knowledge-intensive parts of the economy show a rich array of decision procedures and heuristics that interestingly differ from those contemplated in the classic approaches so far considered. Rather than postulating a reduced content or a weaker form of thought in decision making as uncertainty increases, research on innovative ODM overall highlights that the opposite strategy – invest more effort and use stronger forms of thought – is conceptually and empirically possible, and even justified as a ‘superior’ strategy according to the canons of logics and epistemology, as a set of ‘rational heuristics’ for discovery. (See Grandori (2010, 2013), for a wider review and assessment of those heuristics, as well as for indications of the various studies from which they can be extracted, which cannot be quoted here for reasons of space.) For example, research on the entrepreneurial discovery of new products and services has consistently shown that effective logics include ‘disciplined’ and ‘systematic search’; the reasoned formulation and controlled test of hypotheses; and processes of ‘theoretical’ and ‘causal’ modeling, rather than only of experiential learning. Research on the logic of technological innovation has highlighted how it can exploit the multifunctionality of resources and the multipurposedness of action, whereby logics of ‘resources/alternatives in search of uses/problems to be solved,’ rather than the classic reverse, can increase the rate of success in discovery and reduce downside risk in implementation. Studies on processes of strategic innovation are rich with instances of what Bandura called a ‘modeling’ approach to the discovering and learning of successful action, as opposed to experiential direct or vicarious learning: constructing causal models of a situation using theory and relevant empirical evidence rather than ‘experience,’ and then ‘test’ them through action.
Considered together, these ODM processes can be considered as offering a further broad family of ‘epistemic’ models of ODM, complementing the two classic families of ‘economic’ and ‘behavioral’ models.
The ‘Politics’ of Organizational Decision Making
The Power/Efficiency Controversy
A different track of development of ODM studies has been concerned more with the problem of diverging interests and the relative ‘weight’ or power of actors holding them than on the problem of knowledge. A starting point has been a criticism of Simon’s ‘administrative man’ for ‘neglecting,’ or not being particularly concerned with, the political and strategic dimensions (Pettigrew, 1973).
American ODM research on the politics of ODM has often contrasted organizational actors’ power with organization system’s efficiency, showing empirically that often the particularistic objectives and interests of subunits have more weight on the allocation of resources than the overall effectiveness and efficiency objectives held by the central agents of the system (Pfeffer and Salancik, 1974) and that ‘subgoal pursuit’ typically leads to ‘fatter’ organization (e.g., larger slack, larger organizational boundaries) (Williamson, 1964).
European studies have considered actors’ power in a more positive light, casting the ODM problem as ‘the integration of the many,’ as contrasted with the ‘one actor theorem.’ (See Grandori (1995) for a review of the European tradition in ODM.) Research conducted in that perspective has been especially concerned with the strategic use of uncertainty and the determinants of the decision weight of organizational units and groups (Crozier and Friedberg, 1977; Hickson et al., 1971). It has been argued and found that the relative influence of organizational actors in ODM is a function of ‘the control of critical uncertainties,’ of the degree of substitutability, of the centrality in work and information flows, and of the perception and use of these atouts as bases of negotiation power. In that perspective, then, organizational power is a dependent rather than independent variable, and its allocation as a function of critical uncertainty may even be considered efficient, rather than an alternative to efficiency (Grandori, 1993).
A critical observation, on this way of ‘extending’ ODM models for accommodating conditions of different interests, is parallel to that raised toward the type of ‘extension’ of economic models of decision making for accommodating strong uncertainty provided by BR models. In the face of strong conflict, as in the face of strong uncertainty, and especially in the face of both, a loss of rationality and fairness is expected. An objection to this position is that this is not the sole possible behavior, nor it seems to be the best response that social and economic actors may be capable of. Also on the terrain of conflict resolution under uncertainty, a ‘third’ approach is possible and indeed followed both in theory and practice. Streams of studies highly relevant for ODM, combining the acknowledgment of both conflict and uncertainty, and a concern with efficiency and equity in conflict resolution do exist, although they are seldom included in standard reviews of ODM.
Conflict Resolution for Efficiency and Equity
Organizations are typically systems composed by parts. Actually one basic definition of the organization of a system is the mode in which it is partitioned and in which parts are related. Hence, it is more the rule than the exception that a system cannot be modeled properly as ‘one single actor,’ It might be so, for some classes of decisions (as clarified in the Introduction). But for most decisions, the ‘locus’ of knowledge and interests is more elementary than the entire organization; actually one basic raisons d’etre of organization is precisely to integrate and coordinate a constellation of interdependent nodes of knowledge and preference. Therefore, rather than asking whether power or efficiency are more important in actually shaping organizational structures and actions, in this perspective the relevant question is to devise structures and actions that are ‘superior’ for all the relevant actors having a claim to decide on a matter.
A core mechanism which may sustain this type of search is negotiation. There is plenty of evidence, in the negotiation literature, that many if not most organizational actions, and even organization structures themselves, are defined by negotiation. A negotiation perspective is quite different from a ‘power perspective’ as, while not neglecting the bargaining power of the actors, negotiation analysis provides tools for assessing solutions in terms of efficiency and fairness.
Negotiation is not the only mechanism for solving conflicts in an efficient and fair way though. Other coordination mechanisms are effective alternatives and/or complements to negotiation and negotiated orders in the governance of pluralistic systems and have also been studied in strands of organization studies connected or contiguous with ODM research: for example, voting and organizational democracy constitute another important alternative; alternatively, gaming through both unilateral strategies and coalition formation are possible and indeed likely and can be assessed in terms of Pareto efficiency and fairness and equilibrium of solutions. If these ‘voting and gaming’ conflict resolution mechanisms have to work effectively, though, problems need be structured, alternatives well defined, and payoffs clear; hence they are applicable to narrower conditions with respect to negotiation.
Hence, the models concerned with the ‘politics of ODM’ could be ordered on a sort of continuum, as the models concerned with the ‘logic of ODM.’ Again, the selection of a mode can be conceived in contingency terms, as a function of the clarity and differentiation of knowledge and interests. If at one extreme we locate systems for the aggregation of well-defined preferences over well-defined alternatives, as vote-based organizational democracies and gaming-based organizational poliarchies, at the other extreme we may find ‘organized anarchies’ (Cohen et al., 1972). In fact, the latter type of decision systems and processes has been identified and connected to conditions of extreme ambiguity, in which preferences and participants themselves are unclear/shifting; there is no predefined pattern or mechanism according to which to take decisions, and everyone is free to address any problem and coalesce with any other actor.
Although connected poliarchies, democracies, negotiated orders, and organized anarchies provide alternatives to markets and hierarchies for governing pluralistic and interdependent decision making in complex systems, those distributed decision- making systems also have costs and limits and differ in terms of the types of performance outcomes they are more likely to produce.
Economists have typically emphasized that the wider and more internally differentiated the set of actors holding decision rights, the better the representation/fairness of the decision system is, but the costlier decision processes are. On the other side, differentiated and integrated ODM, either through simple aggregation of preferences and judgments, or, and even more, through voice, discussion, and negotiation, is likely to produce more innovation than either a disconnected poliarchy or a completely connected and homogeneous community (Grandori, 2009).
The costs and difficulties of all these pluralistic governance decision systems can be shifted downward, though. One way is the institutionalization of framing norms and rules, of ‘constitutional orders’ which reduces the ‘degrees of freedom,’ and the variance in actors’ preferences; that is, the embedding or blending of conscious, deliberate, ad hoc analysis and choice with the suspension of critical judgment in certain zones of action. Another way is to increase the capacity of information processing through information systems: A set of supports that in the current context of massive development of information and communication technologies (ICTs) are obviously gaining importance and radically enhancing the feasibility of distributed decision making.
Finally, as for decision strategies, recent contributions have highlighted that solutions may be improved and tradeoffs simplified by combining coordination mechanisms, rather than considering them as mutually exclusive. In fact, in a design perspective on distributed ODM, there is an increasing awareness of the imperfections and paradoxes of any single mode and model and a combination of them recommended to sustain effective and innovative ODM (Grandori 2013).
A Twofold Trend
It is common to recognize that the economic and social world is becoming increasingly complex, more uncertain, differentiated, and conflict laden. The evolution of ODM models in fact is marked by attempts to address increasingly complex conditions. However, this trend has been twofold: Two different types of response and direction of study can be identified in the ODM models for a complex world.
On one side, there are models and studies driven by the hypothesis that in the face of an increasing complexity of the world, thought becomes weaker and rationality more and more limited, with respect to both problem solving and conflict resolution.
On the other side, there are models and studies building on the hypothesis that in the face of the increasing complexity of the world, actors can stretch and strengthen their minds, invest in research rather than reduce search, and try to solve conflicts by devising fair higher-order rules of the game and constitutions rather than indulge in power games.
These two trends may well reflect a polarization of ODM system in reality. The first type of reaction is likely to be more common, to describe well average behavior, but to ‘leave resource on the table.’ The second type of reaction is likely to be less frequent but ‘superior,’ likely to be found in ‘outliers’ more than in mainstream practice, but inspired to the ‘best patterns of thought and action’ that are logically and practically possible. As an agenda for future research, the second perspective may deserve more attention, not only because the majority of mainstream ODM can be located in the first approach, but also for its higher potential for improving ODM under complexity.
Implications for Structures
ODM is influenced by organizational architectures, and vice versa structures are influenced by ODM processes and approaches. Information processing-based organization theory stated a wide set of propositions on how to design organization structures so as to set ‘decision premises’ stimulating more optimizing and computational decision processes in units dealing with structured tasks and devoted to the exploitation of existing resources, leaving space for more heuristic and experiential approaches in unstructured task environments and exploration-oriented parts of the organization.
The enrichments that occurred in decision models for knowledge-intensive and innovative decision making highlighted that in those conditions there are further implications for structures. Organizational systems should become, almost by definition, less ‘decomposable’ if problems are not known enough for being decomposed and new knowledge is to be generated in ODM processes. Hence, somewhat contrary to some current organizational fashions, effective structures for the growth of knowledge should be expected to become not only less hierarchical, but also more connected, that is, less ‘loosely coupled’ and less ‘modularized’ (in fact, hierarchy is quite modular a system). The general principle that, in managing uncertainty and innovation, both differentiation and integration are required, seems to remain valid; however, the forms of specialization and coordination that are likely to be most innovative are expanded by the examined recent trends in ODM. The classic notion was that some units should be flexible and exploration oriented and some structured and devoted to exploitation. The emerging model is more networked: If the growth of knowledge is central, the ‘parts’ or units should be characterized by differentiated knowledge that should be all integrated to contribute to organizational learning. As illustrated in the decision logic section, heuristics such as ‘resources in search of uses’ and multipurposedness imply that the very search for better exploitation of existing resources implies exploring new uses, activities, and services. Hence, in terms of future research, some of the currently popular distinctions in ODM, in particular that between ‘exploration’ and ‘exploitation,’ may deserve some revision in the light of the logics of ODM for innovation and discovery specified in recent research.
More horizontal, paritarian, pluralistic, and representative organization forms should also be favored by the multiplication of the relevant actors and constituencies, as illustrated in the politics of decision-making section. To put the study of pluralistic governance arrangements high on research agendas seems to be overdue in economic and management sciences, still seeing governance as limited to command-based, incentive-driven, or conflict-free communitarian alternatives. The development of new information and communication technologies should provide extensive and yet far from fully exploited support to forms of ODM that are both pluralistic and connected.
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