Developing a Value-Based Decision-Making Model for Inquiring Organizations

Transcription

1 Developing a Value-Based Decision-Making Model for Inquiring Organizations Dianne Hall Auburn University Auburn AL dhall@auburn.edu Yi Guo Texas A&M University College Station TX mguo@cgsb.tamu.edu Robert A. Davis Southwest Texas State University San Marcos TX rd23@business.swt.edu Abstract The effective management of knowledge is critical for organizations that are striving to gain or maintain a competitive advantage and that are in the process of re-structuring for the new century. Decision-making is an important factor for growing organizational memory with newly created knowledge and a broader base of perspectives to use in subsequent decision-making situations. Given a particular decision context and a decision maker with a set of personal values, it may be very difficult to see all sides of the issue. Yet, being able to view the decision environment from multiple perspectives would enhance the decision maker s ability to make better-informed choices. This article introduces the Value-Based Decision-Making (VBDM) model that extends Courtney s [11] new decision-making paradigm by suggesting that multiple perspectives may be achieved by considering a foundation of individual values as suggested by Spranger [34]. This model provides a framework that decision-makers and researchers can use to better understand and facilitate the use of multiple perspectives in decisionmaking and organizational memory enhancement. This article also suggests the use of agent technology as a basis for multiple perspective decision-making support. 1. Introduction The effective management of knowledge is critical for organizations that are striving to gain or maintain a competitive advantage and that are in the process of re-structuring for the new century. Decision-making (DM), a central component of an integrated knowledge management system, is a major factor for growing organizational memory with newly created knowledge and a broader base of perspectives to use in subsequent DM situations. Organizations that effectively support the use of organizational memory through integrated knowledge management systems may be able to respond more quickly and appropriately to a rapidly changing environment. Organizational learning, knowledge management, and effective decision-making are a function of how the organization views problems and opportunities [27, 11]. Mitroff and Linstone [27] maintain that organizations focus too heavily on a technical perspective (a functional, rational view) and suggest that both social and individual orientations should be included. Courtney [11], building on his idea of an inquiring organization based on the work of Churchman [9, 10], suggests that an organization must also recognize the humanness of its organizational members and should encourage ethical and aesthetic perspectives during the DM process. This paper extends Courtney s new decisionmaking paradigm by suggesting that all the aforementioned perspectives may be achieved by considering a foundation of individual values as suggested by Spranger [34]. It also suggests the use of agent technology as a basis for multiple perspective DM support. First, the paper reviews Courtney s paradigm, then discusses individual values and their place in organizational DM. Next, the proposed Value-Based Decision-Making (VBDM) model is explained. An explanation of agent technology is then presented, followed by a conceptualized agent architecture for facilitating multiple-perspective alternative generation for the decision-making process. 2. Courtney s Paradigm Courtney [11] discusses a new decision-making paradigm for use in complex, dynamic environments.

2 He suggests the use of an inquiring organizational structure to implement such a paradigm, and maintains that, at the center of the paradigm, is a structure known as a mental model. This model is guided by an individual s experience and natural image [33]. A natural image is a way of viewing the world, changeable by experience, but built on a foundation of a collection of personal values. The combination of these values determines an individual s natural image, which in turn defines the primary perspective that an individual uses to make sense of a new problem scenario and to generate potential solutions. As problem scenarios become less structured, a need arises for multiple perspectives to be evident during problem solution generation [for example, 9, 11, 27]. Traditionally, the perspective of most organizations has been largely functional. Mitroff and Linstone [27] suggest that social and individual perspectives are also necessary, thus the development of their Technical-Organizational-Personal (TOP) model. The technical perspective is rational and ordered, the organizational perspective is social and stable, and the personal perspective is political and individualistic. In Courtney s DM paradigm, he maintains that equal consideration must be given to the ethical and aesthetic perspectives to ensure that decisions include the human aspect, particularly in those situations where the problem is of a social nature. As an example of this new paradigm, Courtney examines a city-planning project. Among the perspectives swept in as a result of the new paradigm are those of the individuals who will be impacted by the decision. Other perspectives, such as environmental issues, are included. The model that addresses the planning problem incorporates the perspectives of many of the groups and individuals who will be affected by the final solution. There must be a point at which most perspectives have been acknowledged, but one cannot expect all possible perspectives to be represented in every mental model, whether it is individual or collective. It may be prudent, therefore, to begin the process by defining major perspectives from which individuals may approach a DM scenario, and include those in the model. One way to accomplish this would be to investigate individual values as the foundation of an individual s primary perspective. 3. Individual Values and Decision- Making is cognitive mapping. In some arenas, individual values are referred to as cognitive scripts or cognitive maps, [4, 16] or as value schemata (determinants of action) [2, 37]. In an effort to understand how individual values impact organizational DM behavior, studies have been conducted that relate values to DM ethics [15] and group DM effectiveness [21, 35]. One observation that is evident in these research streams is that individual values are an undeniable aspect of individual DM behavior and that encouraging the application of values has a positive impact on organizational DM behavior. Values are also an important issue to Churchman as is evident by his choice of philosophers on whom to base his inquiring systems. Two of the inquiring systems that Churchman [9] discusses are based on the philosophies of John Locke and Edgar Singer, Jr. Locke believed in knowledge as the result of experience. Experience is based on the perspective of the individual, which in turn is based on values. He implied that to understand human behavior one must study the conditions under which the actions occur. Singer believed in individuals striving to do what is best for all mankind, a strongly social value that requires the use of multiple perspectives. An excellent discourse on the potential application of individual values to organizational DM and behavior is found in Buchanan [5]. Using cybernetics [38] as a backdrop, Buchanan explores the function of values in organizational DM and behavior. More importantly, he addresses several of the issues that Churchman addresses. For instance, in defining the place of values within the cybernetic framework, Buchanan indicates that, because values can take on meaning according to organizational goals, they can be regarded as the measure or standard against which something is being compared [5, p. 703]. This applies directly to Churchman s Singerian inquirer in which measurement (and the choice of the measurement tool) is critical. Additionally, the need to synthesize higher-level values in order to reduce the effects of conflict or stress is the basis of the Hegelian inquirer [9]. Individual values are an integral part of an individual s behavior, particularly in the DM process because they form the foundation of an individual s perspective. The next section discusses how individual values fit into the perspective development component of Courtney s paradigm. Courtney suggests that one tool that may be helpful in applying the multiple perspective paradigm

3 4. The Value-Based Decision-Making Model According to Spranger in Types of Men [34], there are six types of personal values (perspectives) that individuals exhibit. They are theoretical, social, political, religious, aesthetic, and economic. The theoretical value is based in the discovery of truth and knowledge in a rational and scientific way. This value is very functional and works best when the situation or problem can be structured. The social value incorporates an interpretive, philanthropic view it seeks human interaction and considers the impact on the group or organization as a whole. The political value is concerned with prestige and power, often at the expense of others, and usually incorporates a critical and power-oriented view. The religious value aspires to make the world a better place, and is usually based on philosophical and interpretive views. The aesthetic value views the world from an artistic, interpretive view and seeks to find form and harmony in a given scenario. The economic value arises from a functional, practical view and seeks usability and material goods. These values are not exclusive to individuals. Organizations exhibit the same types of values, although the economic and political values are often predominant in business. These values generate perspectives that fundamentally restrict the way the individuals see the world, interpret information, and make decisions. The perspectives that are generated from these values are not mutually exclusive. It is common for an individual to be highly social and religious. Likewise, an individual may be motivated by personal gain and evidence of wealth (political and economic). All of these perspectives should be represented in a decision-making scenario, particularly during problem formulation and solution generation. They are additions to the traditional, technical perspective that, according to Mitroff and Linstone [27], organizations usually employ. In fact, there are obvious parallels between Mitroff and Linstone s technical, organizational, and personal perspectives and the values listed above. Likewise, there are parallels between Courtney s ethical and aesthetic perspectives and these values. For instance, like Mitroff and Linstone s technical perspective, the theoretical perspective is rational and functional. Like Courtney s ethical perspective, the religious value is based on morals and ethics, and strives for the betterment of mankind. Each of the values as suggested by Spranger [34] can form the basis of DM perspectives and together are the foundation of the value-based decision-making (VBDM) model outlined below. Mitroff and Linstone [27] examine several facets of the technical, organizational, and personal perspectives, discussing each perspective s goals and worldview, as well as each perspective s mode of inquiry and decision criteria. Other characteristics of the perspectives are discussed. Courtney s perspectives and the additional perspective from Spranger s [34] work can be examined in the same way. The worldview of the ethical (Spranger s religious) perspective is philosophical and morally based. The aesthetic perspective views the world from an artistic lens, while the economic perspective is highly pragmatic. Each of these perspectives has specific goals that match its worldview. The mode of inquiry as discussed by Mitroff and Linstone is the way that the perspective views a problem and formulates the solution. This is equivalent to the knowledge management perspectives (functional, interpretive, and critical) as discussed by Schultze [31] and applied to inquiring organizations [20]. The functional perspective supports the idea that organizations use knowledge management to achieve organizational objectives, relying on known processes and information to facilitate organizational goals and minimally increase organizational knowledge. Such a perspective is adequate in situations where there are known variables, the problem is at worst moderately unstructured, and a solution is likely to be attained. The interpretive perspective applies a social theory to information, stressing communication and interpretation in the system. Socially-oriented knowledge is the outcome of this perspective. Because knowledge is a dynamic element, learning can be precipitated by critically examining organizational memory. This examination is performed by the critical perspective, which is also concerned with examining the status quo for flaws or contradictions and bringing those shortcomings to light. Both the interpretive and critical perspectives of knowledge management are socially oriented and therefore support the human aspect of a system. On the other hand, current approaches to knowledge management and DM are decidedly functional, with a potential toward some element of the interpretive perspective (for instance, group decision support systems). Each of the value-based perspectives has one knowledge management perspective under which it most naturally functions. A summary of the perspectives generated by Spranger s [34] values and their parallels to both Mitroff and Linstone s TOP model and Courtney s DM paradigm is presented in Table 1.

4 s Spranger [34] Theoretical Social Political Religious Aesthetic Economic Mitroff and Technical Organizational Personal Linstone [27] Courtney [11] Technical Organizational Personal Ethical Aesthetic Worldview Scientific, Collective, Individual, Philosophical, Artistic Practical rational philanthropic power moral Goal Problem Action, stability, Power, influence, Equitability, Harmony, Usability, solving, process prestige elevation of artistry pragmatism product mankind Mode of Inquiry Functional Interpretive Critical Interpretive Interpretive Functional (KM perspective) General Empirical, Altruistic, Competitive, Characteristics rational, seeks philanthropic, the truth ego-centric, seeks power seeks human interaction Moral, ethical, seeks unity with the universe Diverse, appreciates beauty, seeks form and harmony Utilitarian, wealthoriented, seeks tangible goods Decision Criteria Best fit to Societal gain Individual gain Highest level Highest level Highest data of of harmony cost/benefit understanding and design ratio Table 1 Extending Mitroff and Linstone s TOP Model and Courtney s Paradigm with Spranger s Values A traditional problem-solving or DM approach is to react to problem recognition by formulating alternatives quickly from generally known information (that is, foregoing investigation and knowledge creation) and choosing one to implement. Two problems associated with this method are failure to investigate all perspectives (indicating that the alternative chosen may not be the best), and that, very often, the process of DM ends with implementation. Courtney s [11] model addresses both these problems by advocating the use of perspectives and by providing for a continuously updated mental model based not only on the chosen solution, but also the results of the implementation. The mental model that is central to Courtney s paradigm is based on the individual s point of view. How one views the world (worldview), interprets information, or forms decisions is directly related to the breadth of the mental model. It may be possible to overcome the restrictions of a narrow mental model and increase the breadth of that model by allowing perspective development to take place during DM, information gathering, or knowledge generation. Enhanced perspective development will naturally expand an individual s (or organization s) mental model and therefore affect DM. Recent research in negotiation support [36] indicates that synthesizing decision maker s mental models not only increases the level of consensus with the group, but improves the social climate in which the groups operate. This can enhance the DM process by reducing conflict, which is a goal of the VBDM model. All DM, information gathering, and knowledge generation scenarios require some negotiation in terms of acceptable information and solutions. While the authors recognize the importance of ongoing research in negotiations and particularly in negotiation support systems, we believe that the VBDM model is a decision support system. According to Lim and Benbasat [26], such a system is an integral part of a negotiation support system, but does not in itself constitute a negotiation system. The VBDM model supplies the types of support identified by Zachary [40], but is particularly strong in both analysis/reasoning and judgment refinement. Further, the VBDM model is designed to be a cooperative system (irrespective of implementation), whereas a common characteristic of negotiations is that the environment is one of conflict and noncooperation [14]. Figure 1 presents the VBDM model that extends Courtney s paradigm by including six value-based perspectives. The six value-based perspectives outlined here are an integral part of an individual s thinking, and therefore must be acknowledged in organizations whose members base their behaviors on them. For an inquiring organization, these values are even more critical. As Courtney states, the axioms for development of an inquiring organization are based on encouraging relationships among individuals, and celebrating the differences of those individuals. To reduce conflict between organizational members, these relationships must exist in an environment where each perspective is recognized, and this environment must allow for continuous updating of the mental model.

5 Problem Recogniton Development Results Mental Models T S P R A E Actions Synthesis Figure 1 The Value-Based Decision-Making (VBDM) Model To achieve the goal of broadened perspectives, organizations should encourage individuals to think more broadly about problems, and to consider the viewpoints of others. When an individual is particularly strongly linked to one or more of the six predominant perspectives, encouraging this growth may be difficult. Recent research [17, 18] indicates that systems designed to facilitate the development of multiple perspectives may be beneficial in encouraging individuals to overcome their innate mental models during specific problem-solving contexts. It may be necessary to rely on specially developed technology to aid this process, particularly to provide the ability to update mental models. Recent advances in technology may enable organizations to facilitate the process of populating organizational memory with multiple perspectives, thus enabling organizational members to refer to those perspectives and the knowledge produced as needed. Courtney [11] suggests several Web-based technological avenues whereby this may be possible for instance, chats, , applets, and knowledge repositories. It is suggested here that an additional avenue for facilitating multiple perspectives may be to employ agent technology. 5. Using Technology to Support Multiple- Decision-Making While applying agent technology to problem solving is a current and active research stream, there has been little application of the technology to encourage the use of multiple perspectives. A suggestion for incorporating agent technology into a multiple-perspective system is outlined below after a brief introduction of related agent concepts. technology is based in artificial intelligence, the goal of which is to study and to build intelligent entities [30]. A software agent ( agent ) is a self-contained program capable of controlling its own decision-making and acting, based on its perception of its environment, in pursuit of one or more objectives [23]. In particular, agents enjoy properties of autonomy, responsiveness, proactiveness, and social ability, which make an agent a "computer system, situated in some environment, that is capable of flexible autonomous action in order to meet its design objectives [22, p. 276]. Two key distinguishing characteristics of agents are that they are capable of handling relatively high-level tasks, and they exist in an environment that may dynamically affect their problem-solving behavior and strategy. Many researchers agree that autonomous agents and multi-agent systems represent a new way of analyzing, designing, and implementing complex software systems [22]. The agent-based view offers a powerful repertoire of tools, techniques, and metaphors that have the potential to considerably improve the way people conceptualize and implement many types of software, including that designed for DM and information management. Multi-agent systems, where the system is designed and implemented as several interacting agents, are

6 ideally suited to representing problems that have multiple problem solving methods, multiple perspectives and/or multiple problem solving entities" [22, p. 277]. In addition to the traditional advantages of distributed and concurrent problem solving, agent technology also has advantages of sophisticated patterns of interaction (cooperation, coordination, and negotiation). However, there is comparably less literature on how to implement these more complex, multi-level systems. Applying agent technology to the development of decision support systems and knowledge management systems is quite natural given the level of sophistication of software agents today. Software agents are often referred to as intelligent entities with some degree of DM capability and knowledge representation mechanism. For example, Chuang and Yadav [7] developed an agent-based architecture to realize an adaptive decision support system proposed by them [6, 8]. Multi-agent systems are used to support knowledge network and corporate memory [1]. In particular, the coordination issue in using multi-agent systems to support knowledge management in supply chain systems is studied by Wu [39] and Barbuceanu and Fox [3]. Applying agents to negotiation is also evident in the literature [14, 25]. However, in these efforts, there is no explicit support for multiple perspectives. In the rest of this article, the Belief-Desire-Intention (BDI) model of agents is applied to facilitate multiple perspective development. The BDI model of agents, developed by Australian Artificial Intelligence Institute, has become one of the best known and most studied models for agents. The model is based on folk psychology in that BDI agents are characterized by a mental state with three components: beliefs, desires, and intentions [28]. Generally speaking, beliefs are what is contained in the agent s local knowledge base, and desires are what the agent is trying to achieve based on its beliefs. Intentions are currently adopted plans, which are predetermined sequences of actions (or sub-goals) that can accomplish specified tasks. An agent s practical reasoning involves repeatedly updating beliefs from information in the environment, deciding what options are available, filtering these options to determine new intentions, and acting on the basis of these intentions. In some cases, this reasoning may also include an effort to coordinate with other agents in the system in order to synthesize beliefs and desires into an achievable, consensual plan of action. In a similar fashion, agent-oriented programming [32] is a multi-agent programming model in which agents are explicitly programmed in terms of mentalistic notions. In a multi-agent system, agents can have different beliefs and goals, and there may be multiple instances of any given type of agent. Multiple perspectives are implicitly embedded in a given agent s worldview. Hall, Guo, and Davis [19] conceptually map the Technical-Organizational-Personal (TOP) model [27] to the BDI agent's mental states. An agent s beliefs can be partitioned into two components. The first component contains the fundamentals of the particular perspective or axioms base (worldview) on which the agent is to act. In the VBDM model, these are meta-beliefs. The other component contains the actual facts that the agent collects from the environment, which are interpreted through the lens of the meta-beliefs. Beliefs are parallel to the concept of a mental model. That is, they are continuously updated as the environment changes, yet the underlying foundations often remain undisturbed. Desires are the goal or motivation of the agent. By using certain decision criteria and other methods, the agent adopts the best intention/plan under the circumstance. 5.1 Modeling the System To model a multiple-agent system, both external and internal views are necessary. The internal structure for each agent is composed of a belief model, a goal model, and a plan model [24]. A belief model describes the information about the environment and internal state. The possible beliefs of an agent and their properties are defined by a belief set. An agent's local knowledge (worldview) is comprised of instances of the belief set, called belief states. The goal model describes the goal that an agent may have according to its beliefs. A data structure called a goal set is used define the goal and its associated event domains. An agent can have one or more goal states, which are instances of the goal set. The plan model describes the plans available to the agent. It consists of a plan set that defines individual plans in terms of properties and control structure. In order to make a BDI agent more socially aware, a social component (model) based on speech acts can be added [13]. The internal structure is the same for all agents, although the contents of each are impacted by each agent s beliefs. Contents can be similar among agents but will be interpreted differently (for instance, prioritizing) according to the belief component. Likewise, the social plans may include a social network of cooperative agents. This network would, of course, be different for each agent type and under different contexts.

7 Beliefs Plan Repository Environmental Meta-beliefs Predefined Social Interpretation Intention Generator (planner) Sensor Effector Figure 2 shows the internal structure model of an agent. The sensor is the component that monitors the changes in the environment to which the agent reacts. The beliefs component contains both meta-beliefs and the environmental interpretation module, and the plan repository contains both predefined plans of action and social laws representing speech act coordination rules. The goals of an agent can be expressed in a separated module or embedded in its Intention Generator. The intention generator uses information based on beliefs and the plan repository components along with embedded algorithms to generate appropriate plans of action to achieve its goals. The effector implements the chosen plan. Externally, two models are needed. These are an agent model and an interaction model [24], which are extensions of object-oriented modeling for agentoriented systems. The agent model describes the hierarchical relationships among agent classes, both abstract (roles) and concrete (agents). The interaction model describes other relationships among agent classes, such as responsibilities, services, and control, as well as interfaces to other components of the systems, such as users and external data sources. A context specific example is presented next and is followed by a general diagram of a multiple perspective agent system. 5.2 Example of Synthesis with Value-Based s It is our belief that multiple-perspective decisionmaking is best supported by extending Courtney s [11] paradigm to include individual perspectives based on an innate value structure. The following simple example is designed to show how six agents, Figure 2 Internal Structure of an one representing each of Spranger s [34] values, may interact during a DM scenario. In this example, often called the foundation task, [12] an amount of money has been gifted to a community that has identified six programs where funding is necessary. The gift states only that all the money must be distributed and must benefit the community, but does not stipulate how the money should be distributed among the programs. The funds may be given to one or all the programs. Each of the six programs aligns naturally with one of the six value states. The programs are establishment of a crime lab (theoretical), emergency assistance for victims of natural disasters (social), renovation of government facilities (political), establishment of an arboretum (aesthetic), medical care for low-income individuals (economic), and endowment to the School of Philosophy at a local university (religious). When agents in such a multi-agent system approach the above problem, there is continuous discussion feedback among agents, during which agents may adjust their beliefs or plans. Specifically in the context of the example, there would be a minimum of six agents, one for each of the six value perspectives. Additionally, there may be other agents available to facilitate the process. A coordinating agent may be engaged to ensure that all the perspective agents have equal access to available information and opportunity to post proposed solutions and feedback to the discussion area. A duplication agent may be used to prevent duplicate postings to the discussion area, or a discovery agent may be employed to acquire additional information relevant to the problem at hand. According to Churchman [9], the power of encouraging multiple perspectives is in the breadth of possible solutions. Each stakeholder in the decision

8 will favor those solutions that support their perspective base. However, not all stakeholders need to agree with all of the possible solutions. The Lockean consensus simply requires that all of the solutions presented as alternatives be agreed on. However, for this to happen it is important that all parties have a basic understanding of the desires, beliefs, and intentions of all the others. The discussion area facilitates this process. The perspective development component of VBDM model is the point where the belief set is populated based on the context of the problem at hand. The perspective synthesis of the model is the point at which discussion occurs and alterative solutions are created and agreed upon. The outcome of this discussion will be a knowledge base, populated with information, perspectives, and new knowledge relevant to the problem. When the system first receives the problem (problem is recognized), each perspective agent examines a database containing information regarding each program, community demographics, etc. to find information with which to further examine the problem. Each agent will examine the same information, but will perceive as important and interpret the information chosen relative to their foundational perspective. Initially, it is expected that each agent would argue that 100% of the funds should be given to the program with which that agent most closely identifies. Regardless, each agent will initially post a proposed solution to the discussion area. All agents will have a chance to react to the postings and to post feedback. As this process moves forward, agents continue to refer to the database and the discussion area to refine suggestions. s may form alliances to strengthen the possibility that the program they support will receive some funding. In this particular context, the social and economic perspectives can see value in the other s programs. For example, providing low-income individuals with healthcare benefits not only reduces overall illness in the community, possibly reducing incidents of communicable diseases (economic perspective), but also improves the quality of life for those individuals (social perspective). Likewise, providing emergency assistance to victims of natural disaster not only helps people who are suffering (social perspective), but also provides income to hotels, restaurants, home improvement stores, and other retail or service establishments where the displaced persons are likely to do business (economic perspective). Social plans and predefined plans for each agent would recognize that alliance-built alternatives are more likely to be chosen than plans supported by only one stakeholder. Theoretical Social Central Database Political Religious Discussion Area Knowledge Base with Alternative Solutions to Problem Economic Aesthetic Potential Alliance Figure 3 Representation of Synthesis Component of the VBDM Model Implemented with Technology

9 These alliances may be made and broken several times during any perspective synthesis process. In agent technology, such alliances may be referred to as joint intention [29]. At the end of the process, the agents will have placed alternative solutions and any supporting knowledge in the knowledge base, and each agent will have agreed that all of the alternative solutions are feasible. Additionally, each agent will have continuously updated its mental model and modified its perspective as necessary. In this context, the human agents (hu-gents) are responsible for populating the central database from which the agents draw demographic data, information regarding the programs, etc. Additionally, the hu-gents will be responsible for choosing the alternative that will then begin the action process of the model. Figure 3 shows a possible representation of the VBDM model s perspective synthesis component; in this case, the relationships between the hu-gents, the central database, the agents, and the knowledge base. 6. Conclusion As organizations continue to strive for sustainable gains in productivity and excellence, the importance of effective DM continues to increase. The DM environment faced by organizations today is often complex and very dynamic. It is critical that organizations consider the contribution that organizational learning and effective knowledge management makes to decision-making. Given a particular decision context and decision maker with a set of personal values, it would be very difficult to see all sides of the issue under consideration. Yet, being able to view the decision environment from multiple perspectives would enhance the decision maker s ability to make better-informed choices. The Value-Based Decision-Making model described in this paper provides a framework that decision makers and researchers can use to better understand and facilitate the use of multiple perspectives in DM and organizational memory enhancement. The foundation of the VBDM model is Courtney s new decision-making paradigm. The Courtney paradigm has been enhanced by the addition of six value-based perspectives. These values are an integral part of individuals and determine how they react in different situations. Effective DM requires consideration of multiple perspectives, even those not apparent to an individual because of their personal values. Also introduced in this paper is the use of agent technology to encourage the use of multiple perspectives in DM. Each agent demonstrated here represents one of the six value perspectives and would interact during the DM process. An example of multiple-perspective decision-making with valuebased agents is provided along with a diagram describing the interaction of the software agents with human agents (hu-gents). References [1] J. L. Aguirre, R. Brena, and F. J. Cantu, Multiagentbased knowledge networks, Expert Systems with Applications, vol. 20, pp , [2] G. W. Allport, The Person in Psychology: Selected Essays. Boston, MA: Beacon Press, [3] M. Barbuceanu and M. S. Fox, Integrating Communicative Action, Conversations and Decision Theory to Coordinate s, presented at Autonomous s Conference, Marina Del Rey, CA, [4] K. L. Bettenhausen and K. J. Murnighan, The Emergence of Norms in Competitive Decision Making Groups, Administrative Science Quarterly, vol. 30, pp , [5] B. Buchanan, Assessing Human Values, Kybernetes, vol. 26, pp , [6] T.-T. Chuang and S. B. Yadav, A Conceptual Model of an Adaptive Decision Support System (ADSS), presented at Americas Conference on Information Systems, Phoenix, AZ, [7] T.-T. Chuang and S. B. Yadav, An -based Architecture of an Adaptive Decision Support System, presented at Americas Conference on Information Systems, Indianapolis, IN, [8] T.-T. Chuang and S. B. Yadav, The Development of an Adaptive Decision Support System, Decision Support Systems, vol. 24, pp , [9] C. W. Churchman, The Design of Inquiring Systems: Basic Concepts of Systems and Organizations. New York, London: Basic Books, Inc., [10] J. F. Courtney, David T. Croasdell, David B. Paradice, Inquiring Organizations, Australian Journal of Information Systems, vol. 6, pp. 3-15, [11] J. F. Courtney, Decision Making and Knowledge Management in Inquiring Organizations: A New Decision-Making Paradigm for DSS, Decision Support Systems Special Issue on Knowledge Management, vol. 31, pp , [12] G. DeSanctis, M. S. Poole, M. Limayem, and D. Luitjens, The GDSS Research Project: Experimental Task Materials, University of Minnesota, Minneapolis, MN [13] F. Dignum and B. van Linder, Modelling Social s: Communication as Action, in Intelligent III, vol. LNAI, M. Wooldridge, J. Muller, and N. Jennings, Eds.: Springer-Verlay, 1997, pp [14] B. Espinasse, G. Picolet, and E. Chouraqui, Negotiation Support Systems: A Multi-Criteria and Multi- Approach, European Journal of Operational Research, vol. 103, pp , 1997.

10 [15] D. J. Fritzsche, Personal Values: Potential Keys to Ethical Decision Making, Journal of Business Ethics, vol. 14, pp , [16] D. Giola and P. P. Poole, Scripts in Organizational Behavior, Academy of Management Review, vol. 9, pp , [17] Y. Guo and D. Hall, Supporting a Comprehensive Knowledge Management System with Technology, presented at Americas Conference on Information Systems, Boston, MA, [18] D. J. Hall, Testing Performance and in an Integrated Knowledge Management System, in Information and Operations Management. College Station, TX: Texas A&M University, 2002, pp [19] D. J. Hall, Y. Guo, and R. Davis, Cooperative Multi- Systems as a Means to Facilitate Multiple Decision-Making, Working Paper, Texas A&M University, [20] D. J. Hall and D. B. Paradice, Decision Support Systems for Inquiring Organizations, presented at Americas Conference on Information Systems, Long Beach, California, [21] R. A. Henry, J. Kmet, E. Desrosiers, and A. Landa, Examining the Impact of Interpersonal Cohesiveness on Group Accuracy Interventions: The Importance of Matching versus Buffering, Organizational Behavior and Human Decision Processes, vol. 87, pp , [22] N. R. Jennings, K. Sycara, and M. Wooldridge, A Roadmap of Research and Development, Autonomous s and Multi- Systems, vol. 1, pp , [23] N. R. Jennings and M. J. Wooldridge, Software, IEEE Review, vol. 42, pp , [24] D. Kinny, M. Georgeff, and A. Rao, A Methodology and Modelling Technique for Systems of BDI s, presented at Seventh European Workshop on Modelling Autonomous s in a Multi- World, MAAMAW'96, [25] K. J. Lee, Y. S. Chang, and J. K. Lee, Time-Bound Negotiation Framework for Electronic Commerce s, Decision Support Systems, vol. 28, pp , [26] L.-H. Lim and I. Benbasat, A Theoretical of Negotiation Support Systems, Journal of Management Information Systems, vol. 9, pp , [27] I. I. Mitroff and H. A. Linstone, The Unbounded Mind: Breaking the Chains of Traditional Business Thinking, 1st ed. New York: Oxford University Press, [28] A. S. Rao and M. P. Georgeff, BDI s: From Theory to Practice, presented at First International Conference on Multi- Systems, San Francisco, [29] A. S. Rao, M. P. Georgeff, and E. A. Sonenberg, Social Plans: A Preliminary Report, presented at Third European Workshop on Modelling Autonomous s in a Multi- World, Amsterdam, The Netherlands, [30] S. J. Russell and P. Norvig, Artificial Intelligence: A Modern Approach: Prentice Hall, Inc., [31] U. Schultze, Investigating the Contradictions in Knowledge Management, presented at IFIP Working Groups 8.2 and 8.6 Joint Working Conference on Information Systems: Current Issues and Future Changes, Helsinki, Finland, [32] Y. Shoham, -Oriented Programming, Artificial Intelligence, vol. 60, pp , [33] E. A. Singer Jr., Experience and Reflection. Philadelphia, PA: University of Pennsylvania Press, [34] E. Spranger, Types of men; the psychology and ethics of personality. New York, NY: Johnson, 1928/1966. [35] J. E. Stoddard and E. F. Fern, Buying Group Choice: The Effect of Individual Group Member's Prior Decision Frame, Psychology & Marketing, vol. 19, pp , [36] R. I. Swaab, T. Postmes, P. Neijens, M. H. Kiers, and A. C. M. Dumay, Multiparty Negotiation Support: The Role of Visualization's Influence on the Development of Shared Mental Models, Journal of Management Information Systems, vol. 19, pp , [37] J. Weber, Adapting Kohlberg to Enhance the Assessment of Managers' Moral Reasoning, Business Ethics Quarterly, vol. 1, pp , [38] N. Wiener, Cybernetics. Cambridge, MA: The MIT Press, [39] D. J. Wu, Software for Knowledge Management: coordination in multi-agent supply chains and auction, Expert Systems with Application, vol. 20, pp , [40] W. Zachary, A Cognitively Based Functional Taxonomy of Decision Support Techniques, Human- Computer Interaction, vol. 2, pp , 1986.