The Role of Emotions in Envisioning Outcomes in Conflict Analysis

A conceptual framework is proposed that accounts for the role of emotions in shaping conflict behavior. The isomorphism between the characteristics that define and drive conflict and those that engender emotions makes it feasible to reconcile emotions with current conflict analysis techniques. Building on Damasio's somatic markers hypothesis, the concept of possibility facilitates modeling the effects of emotion on the scenarios apprehended by the decision makers. Attention is focused on two subsets of the conventional set of feasible states, the hiddenstates that are invisible because of existing emotions (usually negative), and the possiblestates that are invisible because of missing emotions (usually positive). These new concepts can be incorporated within the Graph Model for Conflict Resolution. A model of the confrontation between the United States and North Korea over nuclear weapons demonstrates that the new concepts can simplify analysis and make new predictions that are consistent with the actual unfolding of events. Our main goals are to draw attention to the centrality of emotion in conflict and to the need for research on the incorporation of emotions into conflict analysis and resolution methods.     

Integrating an Option-Oriented Attitude Analysis into Investigating the Degree of Stabilities in Conflict Resolution

Despite the influences on one’s thoughts and actions, the attitude has usually been overlooked in conflict analysis. The purpose of this paper is to develop a new systematic methodology for the graph model for conflict resolution that can be employed to study real-world conflict situations and gain enhanced insights. More specifically, the proposed method starts with the development of an expanded option-oriented preference structure that is derived from decision makers’ attitudes toward others. Then based on this attitude-driven preference structure, the general concepts of stabilities are extended to contain the definitions of different degrees of stabilities under attitude. In addition, the proposed method is embedded in a decision support system, called NUAAGMCR, to facilitate the analytical process. Through a detailed case study of the two-stage environmental conflict of post-Fukushima controversy in Japan, the predicted resolutions are demonstrated to be more accurate and stable than those derived by the general stability analysis.     

Integrating Uncertain Preferences into Status Quo Analysis with Applications to an Environmental Conflict

An algorithm is put forward to conduct status quo analysis when preference uncertainty exists for at least one decision maker (DM) in a strategic conflict. This research integrates into a unified framework two recent expansions of the graph model for conflict resolution, preference uncertainty and status quo analysis. Both of these developments enhance the applicability of the graph model, preference uncertainty by accommodating uncertainty in DMs' preferences and status quo analysis by addressing the dynamics of conflict. The combination of preference uncertainty and status quo analysis improves the flexibility of the graph model in both modelling and analysis. A new model of an environmental conflict is analyzed to demonstrate how the new algorithm can be applied.     

An Integer Programming Approach to Solving the Inverse Graph Model for Conflict Resolution with Two Decision Makers

Group Decision and Negotiation - Operational algorithms for solving the inverse problem for the graph model for conflict resolution are presented for the case of two decision makers (DMs) under a...     

Decision making under conditions of conflict

A real-world application is employed to explain three general types of decision situations that can arise under conditions of conflict. In addition, meaningful connections and relationships among these areas of decision making are clearly pointed out. To permit useful decision technologies to be employed by practitioners for better understanding and for resolving a variety of actual decision problems, a range of flexible decision support systems is discussed. Subsequently, interesting research developments contained in the upcoming sequence of 12 articles on decision making under conflict are summarized and compared. The research articles not only present unique approaches to decision making involving multiple participants, each of whom may have multiple objectives, but suggest a variety of challenging research problems to be investigated in the future.     

Strength of Preference in the Graph Model for Conflict Resolution

A new preference structure that includes a simple relative measure of strength of preference is developed and integrated into some of the stability definitions for the graph model for conflict resolution. In this triplet preference structure, a decision-maker may greatly prefer or prefer one state or scenario to another, or may be indifferent between them. Four stability definitions (solution concepts), Nash stability (R), general metarationality (GMR), symmetric metarationality (SMR), and sequential stability (SEQ), are extended to include strong and weak stabilities for the case of conflicts with two decision makers. Theorems that clarify the interrelationships of the strong and weak versions of these solution concepts are presented. The application of this new preference structure and the associated solution concepts is demonstrated in an environmental conflict model, called the Sustainable Development Conflict. This case shows that valuable strategic insights are gained when strength of preference is integrated into the stability analysis.     

Enhancing National Security and Energy Security in the Post-911 Era: Group Decision Support for Strategic Policy Analysis under Conditions of Conflict

Energy source diversity has become a fundamental principle of both US energy security and national security. The decision of whether or not to approve a new power plant facility in the US involves complex group decision and negotiation processes. These contentious, value-laden, and multi-faceted self organizing processes involve many decision makers (broad constituencies) with conflicting priorities and dynamic preferences, high decision stakes, limited technical information (both in terms of quality and quantity), and difficult tradeoffs. As population pressures and energy demands continue to mount, advances in conflict resolution can help to improve power plant siting processes as well as US energy security and national security. Specifically, this paper uses advances in the Graph Model for Conflict Resolution and its associated decision support system (DSS) GMCR II to analyze strategic aspects of a multi-party energy dispute involving the co-management of a shared air shed in the Fraser Lowland Eco-Region based on Sumas Energy 2 (SE2), a contentious power plant project proposed for the US side of the international border between the city of Abbotsford, British Columbia and town of Sumas, Washington. GMCR II provides strategic insights for enhancing energy security, national security, and environmental risk management in the United States.     

The Graph Model for Conflict Resolution: Past,Present, and Future

The Graph Model for Conflict Resolution is a methodology for the modeling and analysis of strategic conflicts. An historical overview of the graph model is presented, including the basic modeling and analysis components of the methodology, the decision support system GMCR II that is now used to apply it, and the recent initiatives that are currently in various stages of development. The capacity of this simple, flexible system to provide advice to decision-makers facing strategic conflicts is emphasized throughout, and illustrated using a real-life groundwater contamination dispute.     

Behavioral research and empirical modeling of marketing channels: Implications for both fields and a call for future research

Game theoretic models of marketing channels typically rely on simplifying assumptions that, from a behavioral perspective, often appear naïve. However, behavioral researchers have produced such an abundance of behavioral regularities that they are impossible to incorporate into game theoretic models. We believe that a focus on three core findings would benefit both fields; these are: first, beliefs that are held by the various players regarding profit consequences of different actions are incomplete and often biased; second, players’ preferences and optimization objectives are not commonly known; and third, players have insufficient cognitive abilities to achieve optimization objectives. Embracing these three findings shifts the focus from rational decision making to how decision makers learn to improve their decision-making skills. Concluding, we believe that greater convergence of game theoretic modeling and behavioral research in marketing channels would lead to new insights for both fields.     

Competitive intelligence and strategic group decisions: A new diagnostic tool

The use of competitive intelligence (information on competitors, technology, market developments, etc.) in strategic group decision making is of great interest to practitioners and strategy researchers alike, yet relatively little is known about the availability of competitive intelligence and the actual need for intelligence by decision makers. This article develops a decision-dependent input/participants matrix which is the basis for the derivation of seven intelligence availability and demand indices. The indices are diagnostic tools to help companies design and monitor strategic competitive intelligence gathering and distribution. They constitute part of an organizational intelligence support system designed to strengthen group decisions such as launching a new product. Practitioners can use the indices to diagnose problems countered by groups of decision makers in the intelligence gathering and distribution activities of organizations, and researchers can use them in the systematic study of this new field. An application of the tool to a pharmaceutical company is described.     

Advances in Drama Theory for Managing Global Hazards and Disasters. Part I: Theoretical Foundation

Global risk and disaster management challenges are complex and ill-structured group decision processes characterized by time-sensitive, multi-faceted, and self-organizing negotiations, high decision stakes, extreme uncertainty, and dynamic, value-laden tradeoffs. Drama theory asserts that conflict resolution requires players to engage in a rational-emotional process of re-defining both the game and their “positions” in it until agreement on a satisfactory resolution is reached. While game theory has been widely applied to problems dealing with hazards, risk, and disasters, it assumes fixed players, options, and preferences, and hence does not allow for the re-definition of the conflict under consideration. Results show that drama theory constitutes a flexible and powerful tool for modeling group decision and negotiation processes involving natural, man-made, and health-related hazards, risk, and catastrophes in the post-911 security environment by modeling emotional responses that, throughout the course of a game, can lead to unanticipated reactions and change basic assumptions. This is achieved through the use of option boards to construct and analyze emergency, disaster, or crisis models that are structurally similar to game models. Finally, drama theory is compared and contrasted to conflict analysis, which developed from common roots in metagame analysis. The strengths and weaknesses of drama theory are critically evaluated in the context of global climate change and the mounting risk of a worldwide influenza pandemic.     

An Ethics of Care or an Ethics of Justice

A conflict within the community of those investigating business ethics is whether decision makers are motivated by an ethics of justice or an ethics of caring. The proposition put forward in this paper is that ethical orientations are strongly related to cultural backgrounds. Specifically, Hofstede's cultural stereotyping using his masculine-feminine dimension may well match a culture's reliance on justice or caring when decisions are made. A study of college graduates from six countries showed that Hofstede's dimension was remarkably accurate in predicating a justice or caring orientation for decision makers from five of the six countries.     

Conjoint models of family decision making

The objective of this research is to develop viable approaches to modeling joint decisions. Using conjoint-analysis-type preference data, three methods are developed to combine individual preferences to approximate joint preferences and predict joint decisions. The first is an equal weighting model, which is a simple average of individual members' part-worth utilities. The second is a relative influence model, which combines individual utility functions using a measure of derived influence. The third is a conflict resolution model, which combines utility functions using a measure of conflict. In addition to these three combination models, individual member models and a joint model based on the joint preferences are available.The application area in which the models are operationalized is family decision making. The decision involves choice of a job by MBA students and spouses at a major private university. The models are first calibrated using preference data on hypothetical jobs from MBAs, spouses, and couples and then evaluated on their ability to predict the actual job chosen.     

Stakeholder Perspectives and Business Risk Perception

Stakeholder theory calls for decision makers to balance stakeholder interests, but before this can happen, management must understand how other parties view its decisions. Effective stakeholder dialogues convened to reach this understanding require management to appreciate how others perceive the risks posed by their decision. Although understanding others’ risk perception is crucial for effective communications, we do not have a clear idea of how viewing a situation from multiple stakeholder perspectives affects risk perception. Based on a technique derived from risk perception studies of health and environmental issues, an experiment with 224 business students examined how an individual’s risk perception can account for both managerial and customer perspectives. Factors described as customer participation, extent of the effect, and management input, together with the respondent’s self-assessed understanding of the decision process, help categorize overall risk perceptions and are shown to be associated with behaviors based on the decision’s riskiness. Discussion includes implications for designs of business communications, including their content and transparency, and for understanding the audience for these communications.     

The effect of decision makers’ time perspective on intention–behavior consistency

This research demonstrates that decision makers?? time perspective??a cognitive, temporal bias that leads people to overemphasize the past, present, or future in their decision making??systematically influences self-reported behavioral intentions and thus intention?Cbehavior consistency for distant-future behaviors. Whereas present-hedonistic individuals overstate their intentions, present-fatalistic individuals understate theirs, so both types exhibit low intention?Cbehavior consistency. Future time-oriented individuals instead exhibit high intention?Cbehavior consistency because they are less likely to overstate their intentions. The findings are contributed to decision makers?? time perspective influencing the construal of distant-future behavior when reporting behavioral intentions. Accounting for decision makers?? time perspectives helps improve predictive accuracy and may change insights obtained from causal models that use self-reported intentions as a proxy for actual, distant-future behavior.     

Critical Situations for Decision Making: A Support Based on a Modelling Tool

This paper proposes to give a toll to help decision makers in critical situations. The principle of our research is based on a modelling approach for Cooperative Knowledge Based Systems. This approach is based on a Task/Method paradigm that we describe. We then propose to take into account collateral effects of tasks in order to support decision makers in a critical context. The proposed tool can then generate a degraded solution for which, collateral effects of previous tasks have been taken as new goals to reach. This study is possible thanks to the definition of several kinds of models: a Good Functioning Model and a Degraded Tasks Library.     

Corporate Social and Financial Performance Re-Examined: Industry Effects in a Linear Mixed Model Analysis

In this research, we shed new light on the empirical link between corporate social performance (CSP) and corporate financial performance (CFP) via the application of empirical models and methods new to the CSP?CCFP literature. Applying advanced financial models to a uniquely constructed panel dataset, we demonstrate that a significant overall CSP?CCFP relationship exists and that this relationship is, in part, conditioned on firms?? industry-specific context. To accommodate the estimation of time-invariant industry and industry-interaction effects, we estimate linear mixed models in our test of the CSP?CCFP relationship. Our results show both a significant overall CSP effect as well as significant industry effects between CSP and CFP. In conflict with expectations, the unweighted average effect of CSP on CFP is negative. Our industry analysis, however, shows that in over 17% of the industries in our sample, the effect of CSP on CFP for socially responsible firms is positive. We also examine the multidimensional nature of the CSP construct in an industry context by exploring the CSP dimension?Cindustry nexus and identify dimensions of social performance that are associated with either better or worse financial performance. Our results confirm the existence of disparate CSP dimension?Cindustry effects on CFP, thus our results provide important and actionable information to decision makers considering whether and how to commit corporate resources to social performance.     

The Interplay of Emotion Regulation and Sales Experience in Salesperson Conflicts: Evidence from an Emerging Economy

ABSTRACT

It is human nature that personal interactions are often charged with emotions and laden with conflicts. Workplace encounters are not immune from this reality. Despite this, few studies have examined ways to reduce interpersonal conflict in the workplace. This study examines the interpersonal impact of emotion regulation on salesperson relationships with stakeholders. Using structural equation modeling, results of the analysis showed that salesperson's regulation of emotions was negatively related to interpersonal conflict with co-workers as well as with customers; and positively impacted customer-oriented sales behaviors. The results also support the moderating role of selling experience in the relationship between emotion regulation and interpersonal conflict with customers. That is, the negative relationship between regulation and conflict with customers is stronger for salespeople with lower sales experience. These findings put forward important managerial implications with regard to the recruitment and training of sales professionals.     

Selection of a Representative Value Function for Robust Ordinal Regression in Group Decision Making

In this paper, we introduce the concept of a representative value function in a group decision context. We extend recently proposed methods UTA^GMS-GROUP and UTADIS^GMS-GROUP with selection of a compromise and collective preference model which aggregates preferences of several decision makers (DMs) and represents all instances of preference models compatible with preference information elicited from DMs. The representative value function is built on results of robust ordinal regression, so its representativeness can be interpreted in terms of robustness concern. We propose a few procedures designed for multiple criteria ranking, choice, and sorting problems. The use of these procedures is conditioned by both satisfying different degrees of consistency of the preference information provided by all DMs, as well as by some properties of particular decision making situations. The representative value function is intended to help the DMs to understand the robust results, and to provide them with a compromise result in case of conflict between the DMs.