Shopping context and consumers’ mental representation of complex shopping trip decision problems

Depending on the shopping context, consumers may develop different mental representations of complex shopping trip decision problems to help them interpret the decision situation that they face and evaluate alternative courses of action. To investigate these mental representations and how they vary across contexts, the authors propose a causal network structure that allows for a formal representation of how context-specific benefits requirements affect consumers’ evaluation of decision alternative attributes. They empirically test hypotheses derived from the framework, using data on consumers’ mental representations of a complex shopping trip decision problem across four shopping contexts that differ in terms of opening hour restrictions and shopping purpose, and find support for the proposed structure and hypotheses.     

Modeling and supporting task-oriented group processes: Purposeful complex adaptive systems and Evolutionary Systems Design

Evolutionary Systems Design (ESD) is a universal general problem solving, formal modeling, design framework for purposeful complex adaptive systems (PCAS) and processes, i.e., task-oriented group processes. These processes constitute policy making, group decision, negotiation, and multiagent problem solving with human and/or artificial agents. ESD is also a framework for computer group support systems (GSS) that support these processes. The ESD general framework can be applied to define and solve specific problems. In this article the ESD framework is presented and illustrated by example. The article provides background for ESD computer implementations discussed in two other related articles (Lewis and Shakun 1996; Bui and Shakun 1996).     

Perspectives on representation and analysis of negotiation: Towards cognitive support systems

The rapid expansion of Decision and Negotiation Support Systems has been built mainly on decision-theoretic approaches. This has resulted in the decision maker being viewed through the lens of the problem. In this article, the focus is on the decision maker's view of the problem. Three levels of problem articulation are described. Special emphasis is placed on the needs level and the implications it carries for the cognitive and instrumental levels. The three levels of articulation, the organizational model of making decision in social settings, and the three basic approaches to decision making form the basis for computer support focused on understanding and change rather than preferences and outcomes. We argue that in the dynamic, interactive context characteristic of negotiations, a cognitive support system based on restructurable modeling provides a richer basis for support.     

Distributed Decision Making: A Proposal of Support Through Cooperative Systems

In this paper we show that decision making processes evolve to be more and more distributed and asynchronous. In order to support decision-makers who are not at the same place at the same time we define cooperation processes and a set of models models able to support designers of Cooperative decision support framework. These models come from a more general architecture of a Cooperative Knowledge Based System and are based on the knowledge acquisition field. A definition of cooperative decision support framework is also given.     

For the Greater Good? A Test for Strategic Bias in Group Environmental Decisions

This paper presents a study which tests for strategic bias in group decision support models. Strategic bias occurs when individuals provide preference information to a group decision model which, they perceive, will improve their own outcomes and not necessarily those of the group. A test is made for strategic bias in a decision model used to allocate funds amongst 14 natural resource management regions in Queensland. The funds are a crucial source of revenue for the regions to achieve environmental objectives. In this real decision problem representatives from each region supplied criteria weights for a multiple criteria analysis model. Results reveal moderate to weak presence of strategic bias. Regions mostly selected weights that would improve their outcome relative to the weights of other regions. But this was not overly pronounced and there were exceptions. Whilst some degree of strategic bias existed these results show a willingness to separate individual and group preferences when interacting with formal decision procedures. Further research is required to see how this changes under unstructured negotiation and arbitration as opposed to a formal model.     

Reaching informed agreement in multispecialist cooperation

Very often, complex decisions must be made by a group of specialists rather than a single decision maker. To make an effective decision, the combination of the group's expertise must be brought to bear on the situation. Fusing expertise where individuals have very detailed knowledge in their own areas and much weaker understanding of others is characterized by many difficulties: (1) agents cannot communicate their expertise in an intelligible way to nonexperts because of differences in vocabulary and conceptual content; (2) the process allows for incorrect inferences; and (3) no one knows what anyone else needs to know. This impasse cannot be broken until shared mental models are developed to provide a level of agreement in evaluating alternatives needed to focus the activity of the group. This article presents a model of decision making by teams of specialists in which agents' evaluations confound expert and naive inferences in judging alternatives. A partitioning of agent knowledge into expert and naive models is proposed. The naive portion of agents' models provides both a common language and the inferential skeleton needed for the development of shared models. Communications are categorized into types of evaluation or justification based on their form and the entities they involve within the agent models. A process of model refinement is outlined, linking communications among agents to modifications of the naive/ shared portions of their models. The process of cooperative problem solving by a team of specialists is characterized as a search among alternatives in which model refinement continually alters the agents' evaluations, leading to progressively greater accuracy and more precisely directed search. The model is intended as a research tool for investigating multiagent problem solving among people and machines.     

High Stakes Decision Making: Normative,Descriptive and Prescriptive Considerations

This paper reviews the state of the art of research on individual decision-making in high-stakes, low-probability settings. A central theme is that resolving high-stakes decisions optimally poses a formidable challenge not only to naïve decision makers, but also to users of more sophisticated tools, such as decision analysis. Such decisions are difficult to make because precise information about probabilities is not available, and the dynamics of the decision are complex. When faced with such problems, naïve decision-makers fall prey to a wide range of potentially harmful biases, such as failing to recognize a high-stakes problem, ignoring the information about probabilities that does exist, and responding to complexity by accepting the status quo. A proposed agenda for future research focuses on how the process and outcomes of high-stakes decision making might be improved.     

Consciousness, Spirituality and Right Decision/Negotiation in Purposeful Complex Adaptive Systems

Both cybernetic and self-organizing, purposeful complex adaptive systems (PCAS) express purpose by solving problems defined by choosing and delivering values to participants as operational goals through decision making. Individuals, groups, organizations, and economies are PCAS. Here we focus on indviduals and groups. Evolutionary Systems Design (ESD) is a universal (culture independent) general problem solving, formal modeling/design framework for PCAS that can be computer implemented in same time/same place or telework modes. Formally, in ESD sets of elements and their relations modeling a PCAS evolve through cybernetics/self organization. Spirituality and the concept of right decision/negotiation in PCAS are discussed in relation to consciousness. Rightness comes from spirituality, i.e., consciousness experiencing oneness. Oneness is integrally bound with love; hence the term oneness/love. Through right decision/negotiation PCAS try to realize their ultimate purpose to live Two (the relative, the process of all there is) as One (the absolute, all there is). Oneness/love, connectedness to One, promotes problem solving and negotiation - expressed formally in the ESD problem representation - that is at the same time right. Simply put, right problem solving requires oneness/love and delivers oneness/love. Computer and receiver modes of consciousness are discussed in relation to oneness/love and its absence experienced as separateness/fear. Ways to transit from the latter to the former are considered. P.L. Yu's Habitual Domain (HD) framework is introduced and discussed in relation to ESD. Evolutionary heuristics for evolution of an ESD right problem representation through cybernetics/self-organization are presented based on combined HD and ESD concepts. Then operational procedures for defining and validating a right problem for an individual or group and associated right decision/negotiation outcome are considered. Thus, the work contributes to procedural rationality - how decisions should be or are made - in purposeful complex adaptive systems. The paper suggests that for humans to live fully (awake) is to live in our love-based spirituality, in the moment, consciousness experiencing oneness/love at the edge of chaos, challenged in our purpose to live Two as One by spiritual or right decision/negotiation through cybernetics/self-organization, i.e., problem solving under oneness. Artificial agents in PCAS may participate in right decision/negotiation. They may in principle have consciousness but the nature of the subjective experience is unclear.     

Multiple Criteria Decision Making Models in Group Decision Support

Use of multiple criteria decision making (MCDM) models to aid the group decision process was tested. Two multiple criteria group decision support systems (MCGDSS) were studied, one using the AHP/Tchebycheff method of Iz and the other using Kersten's NEGO system. These systems were compared with a commercial GDSS, VisionQuest. VisionQuest does not include multiple criteria tools. To make the study comparable, VisionQuest was augmented with an ad hoc linear programming model that could generate solutions with specified characteristics requested by the using group. The three systems were compared on the dimensions of solution quality and decision support effectiveness.One of the hypotheses was that MCDM models would force participants to examine criteria, preferences, and aspirations more thoroughly, thus leading to decisions of better quality. Subjects using the MCGDSSs were expected to have higher mean quality and effectiveness values. However, the quality and effectiveness values of the VisionQuest/ad hoc system were found to be better on the dimension of effectiveness. Explanations for this result are included in the paper.Another hypothesis was that the AHP/Tchebycheff method of Iz, a value-oriented system, would yield more effective group support than the goal-oriented NEGO system. However, the NEGO system was found to yield solutions with better quality measures than the solutions obtained with the AHP/Tchebycheff system.Observation of the groups using the MCDM systems indicate that both the AHP/Tchebycheff and NEGO methods can be revised to enhance their effectiveness. The primary difficulty encountered with the AHP/Tchebycheff method was in the large number of pairwise comparisons required by AHP. The NEGO method can be enhanced by including specification of desired attainment levels in the first stage of the method. Both MCDM techniques have potential to benefit group decision support by giving using groups a means to design better solutions.     

Touching the Untouchable: Exploring Multi-Sensory Augmented Reality in the Context of Online Retailing

Mental intangibility during product evaluation remains one of the greatest drawbacks for online purchasing. However, emerging multi-sensory Augmented Reality (m-AR) applications offer a potential solution for this online retailing problem. Drawing on active inference theory, this article proposes a conceptual framework to assess how sensory control and feedback modalities affect consumer value judgements by reducing mental intangibility. We show how touch control, compared to voice control, positively affects consumers’ willingness-to-pay. The underlying mechanism is a sequential process of reduced mental intangibility and increased feeling of decision comfort. In addition, we highlight a positive moderating effect of congruent auditory feedback on decision comfort. We also demonstrate a novel consumer boundary condition. Consumers high in assessment orientation experience a stronger reduction in mental intangibility. The results are consistently replicated across three experiments implying theoretical and managerial contributions for m-AR in the context of online retailing.     

Applying Multiattribute-Based Group Decision Making Techniques in Complex Equipment Selection Tasks

A practicing industrial engineer, even an experienced decision maker, needs help in the sense that there is a necessity to use more logical or analytical decision support tools, especially when dealing with control and instrumentation projects which are often worth millions of dollars. In this article we propose an algorithm which can support the process of group decision making relating to industrial automation, especially involving the selection of control and instrumentation equipment. The aim of this article is to look only at the algorithm's application and how it is applied. To this end, two test cases are used as examples: (1) selecting a local area network for installation in an academic environment; and (2) selecting an integrated control system for a real-world pulp and paper mill. Obtained results show that the algorithm leads to a satisfactory solution. A software form of the algorithm is being programmed for use as a decision support tool.     

On automated e‐business negotiations: Goal,policy, strategy,and plans of decision and action

In recent years, there has been increasing interest in automated e‐business negotiations. The automation of negotiation requires a decision model to capture the negotiation knowledge of policymakers and negotiation experts so that the decision‐making process can be carried out automatically. Current research on automated e‐business negotiations has focused on defining low‐level tactics (or negotiation rules) so that automated negotiation systems can carry out automated negotiation processes. These low‐level tactics are usually defined from a technical perspective, not from a business perspective. There is a gap between high‐level business negotiation goals and low‐level tactics. In this article, we distinguish the concepts of negotiation context, negotiation goals, negotiation strategy, and negotiation tactics and introduce a formal decision model to show the relations among these concepts. We show how high‐level negotiation goals can be formally mapped to low‐level tactics that can be used to affect the behavior of a negotiation system during the negotiation process. In business, a business organization faces different negotiation situations (or contexts) and determines different sets of goals for different negotiation contexts. In our decision model, a business policymaker sets negotiation goals from different perspectives, which are called goal dimensions. A negotiation policy is a functional mapping from a negotiation context to some quantitative measures (or goal values) for the goal dimensions to express how competitive the policymaker wants to reach that set of goals. A negotiation expert who has the experience and expertise to conduct negotiations would define the negotiation strategies needed for reaching the negotiation goals. Formally, a negotiation strategy is a functional mapping from a set of goal values to a set of decision‐action rules that implement negotiation tactics. The selected decision‐action rules can then be used to control the execution of an automated negotiation system, which conducts a negotiation on behalf of a business organization.     

Evaluating a Framework for Multi-Stakeholder Decision Support in Water Resources Management

In this paper we describe a framework for multicriteria modeling and support of multi-stakeholder decision processes. We report on its testing in the development of a new water level management policy for a regulated lake-river system in Finland. In the framework the stakeholders are involved in the decision process from the problem structuring stage to the group consensus seeking stage followed by a stage of seeking public acceptance for the policy. The framework aims at creating an evolutionary learning process. In this paper we also focus on the use of a new interactive method for finding and identifying Pareto-optimal alternatives. Role playing experiments with students are used to test the practical applicability of a negotiation support procedure called the method of improving directions. We also describe the preference programming approach for the aggregation of the stakeholder opinions in the final evaluation of alternatives and consensus seeking.     

Evaluation of a decision support training effectiveness measure

Resource constraints affect the US Department of Defense's ability to simultaneously sustain current operations and recapitalize for future challenges. An assumption is that decision support training may improve resource allocation decisions; however, few instruments are available to measure the effectiveness of decision support training to verify that assumption. The purpose of this research is to evaluate an instrument to measure decision support training effectiveness. Using data collected from a resource allocation simulation, we found a significant positive relationship between decision support training and outcomes in a controlled field study involving a complex problem. Thus, in the proper context, the resource allocation simulation described herein may be a reliable measure of decision support training effectiveness. Copyright © 2008 ASAC. Published by John Wiley & Sons, Ltd.     

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.     

Determinants of Ethical Decision Making: The Relationship of the Perceived Organizational Environment

This study attempts to help explain the ethical decision making of individual employees by determining how the perceived organizational environment is related to that decision. A self- administered questionnaire design was used for gathering data in this study with a sample size of 245 full-time employees. Perceived supervisor expectation, formal policies, and informal policies were used to assess the expressed ethical decision of the respondents. The findings indicate that the perceived organizational environment is significantly related to the ethical decision of the respondent.     

Technology and Group Decision Process in Going-Concern Judgements

Accounting and auditing practices are continually being affected by advances in technology. This study empirically examined the effect of group decision processes and technological advances on group going-concern decision making. Groups with access to group decision support systems (GDSS) were compared to groups without access to GDSS for their going-concern judgments. The results show group discussion induced auditors to be more conservative and to consider factors which may have overlooked at the individual level, though neither structure significantly reduced the considerable variance in the individual going-concern judgments. Further, as compared to their counterparts in the face-to-face discussion groups, GDSS groups indicated much higher confidence in their group's final assessment of the client's going-concern status and a higher level of satisfaction and agreement with the group decision processes. The findings suggest that while group discussions did not significantly reduce auditors' considerable variance in going-concern judgments, future research should investigate which explicit models would improve the consensus on going-concern evaluations.     

A multiobjective decision support system for multiresource forest management

A multiobjective and/or multiperson decision support system for analyzing multiresource forest management problems is developed in this paper. The procedure includes formulating the problem in a multiobjective and group decision making framework, and solving it using two solution techniques which consist of a distance-based compromise programming (CP) and a cooperative game theoretic approach of the Nash equilibrium type. The problem consists of five forest resources management objective functions to be maximized. Solving the problem using the two solution techniques enables determining a satisfactory compromise solution of the five forest resource management objectives. Sensitivity analysis of the two techniques shows compromise programming to be more sensitive to changes in the weight and the p-parameter of the technique while the cooperative game theoretic approach is relatively robust with respect to changes in the worst utility set.     

Global Sourcing Decision‐Making Processes: Politics,Intuition, and Procedural Rationality

Global sourcing (GS) is a firmly established phenomenon in modern business practice that requires specific expertise from different organizational functions, such as purchasing, production, logistics, and research and development to analyze and select sourcing alternatives effectively. In this context, global sourcing decision‐making (GSDM) processes pose major challenges because two dimensions of functional politics, namely goal misalignment and power imbalance across functions, appear to influence procedural rationality in a manner not understood to date. Likewise, intuition also seems to play a role for the procedural rationality of GSDM processes. To elucidate the conditions under which procedural rationality is hampered or enhanced by politics and intuition, we studied five cross‐functional GSDM processes, in front of extant strategic decision‐making literature. We derive formal propositions on how functional politics and intuition influence the procedural rationality and present contingencies for the divergent role of intuition as well as functional politics in GDSM processes. Our research contributes to existing GS literature by providing a theoretical model of important microfoundations of how GSDM processes evolve. The findings also guide managers on how to structure GSDM processes such that GS projects can be conducted in a more rational fashion.