A model and case for supporting participatory public decision making in e-democracy

In this paper, focusing on participatory public decision making processes, I propose a framework for group support systems and discuss related research issues. As a case illustrating the feasibility of participatory public decision making, I present the participatory budgeting experience in Porto Alegre, Brazil. The case is analyzed based on the proposed framework.     

Evaluations of Tactics for Automated Negotiations

Automated negotiation under the infrastructure of e-commerce is becoming an important issue. However, although the communication protocols and frameworks of automated negotiation have been extensively investigated, the corresponding tactics and strategies are still underdeveloped and need to be evaluated further. Based on the negotiation model proposed by Faratin et al., this paper examines the performance of automated negotiation tactics and intends to provide concise suggestions for the users of automated negotiation. First, theoretical analysis is used to evaluate the behavior-dependent tactics. Constructive conclusions are obtained when single-issue negotiations are considered. Next, a new framework for applying single-issue tactics to multi-issue negotiation is proposed. Based on this framework, theoretical analysis is then extended to multi-issue cases. Finally, different from the previous work, exhaustive simulations based on two-issue negotiations are performed to evaluate the effectiveness of behavior-dependent and time-dependent tactics. The experimental results provide several important insights into negotiation tactics.     

The antecedents of renegotiations in practice—an exploratory analysis

In order to support business negotiations with electronic tools effectively, a deep understanding of real-life business negotiations is required. Comparing the settings usually applied in negotiation experiments with the every-day experiences of business negotiators, it can be stated that the work of business negotiators is much more iterative and embedded. Renegotiations appear on a regular basis. This observation stresses the importance of flawless communication in business negotiations and raises questions regarding the reasons for renegotiations and the role of information technology in this context. This paper investigates data gathered in a 2005 survey study in order to identify the context factors that drive B2B renegotiations using a preliminary regression model. The rules of interaction, task complexity, and business relationship are found to be significant predictors of the renegotiation likelihood while media richness does not impact the likelihood of renegotiations in practice.     

Comparative Analysis of Text Data in Successful Face-to-Face and Electronic Negotiations

Various combination of Natural Language Processing and Machine Learning methods offer ample opportunities wherever texts are an important element of an application or a research area. Such methods discover patterns and regularities in the data, seek generalization and in effect learn new knowledge. We have employed such methods in learning from a large amount of textual data. Our application is electronic negotiations. The genre of texts found in electronic negotiations may seem limited. It is an important research question whether our methods and findings apply equally well to texts that come from face-to-face negotiations. In order to confirm such more general applicability, we have analyzed comparable collections of texts from electronic and face-to-face negotiations. We present our findings on the extent of similarity between these two related but distinct genres. In this study we have analyzed similarities in the text data of electronic and face-to-face negotiations. The results show that – in certain conditions – vocabulary richness, language complexity and text predictability are similar.This is an expanded version of a paper published in the Proceedings of FINEXIN 2005 (Workshop on the Analysis of Formal and Informal Information Exchange during Negotiations), 31–42, Ottawa, Canada, May 2005.     

Exploring usage continuance of e-negotiation systems: expectation and disconfirmation approach

Online negotiation is becoming increasingly popular and important due to the rapid growth of global e-business, with the factors determining the continuance of e-negotiation systems (ENSs) usage––rather than the mere acceptance of their use––receiving more attention. This study used the expectation-disconfirmation theory to investigate the factors influencing the intention of ENS usage continuance. Using two Web-based ENSs, data were collected from 170 negotiators who participated in an e-negotiation experiment lasting 17 days. A structural-equation modeling technique was adopted to examine the research model and hypotheses. The obtained research results provide novel insights into ENS usage continuance for ENS researchers, developers, and managers. They indicate that positive disconfirmation (i.e., where the actual experience or perceived performance is better than the expectation) plays a crucial role in shaping the intentions of users to continue using an ENS. Therefore, researchers should consider postusage factors when attempting to elucidate the decision-making processes that underlie the continued use of an ENS. Similarly, the development of a successful ENS requires its developers to consider the expectations of users when designing the system specification. To ensure ENS usage continuance, IS managers should continuously monitor the users’ expectation-disconfirmation status to ensure their satisfaction with the ENS.     

An experimental study of alternative preparation aids for international negotiations

We test the relative effectiveness of alternative preparation aids in the context of an international negotiation. We consider three forms of training: reading material, a course on negotiation, and an expert system (NEGOTEX) expressly designed to train negotiators. We conducted a laboratory experiment involving 66 pairs of negotiators—one of each pair being American and the other Chinese. Results suggest that in this context, the course had the greatest effect on performance, followed by NEGOTEX, and then followed by reading material. In addition, we found that training effects were additive: multiple forms of training lead to better results than individual forms of training, suggesting that (1) training forms complement and do not substitute for one another, and (2) multiple forms of training should be considered, especially when stakes are high.     

An object-oriented architecture for group decision support systems

An object-oriented GDSS can produce a rich environment for easily accessing software tools or applications running under a Graphical User Interface and can provide communication among meeting participants. This requires definition of (1) objects to manage the meeting and participant sessions, (2) applications that can run under these sessions, and (3) data storage and data communications capability that handle both private and shared data. This article suggests that a GDSS system can operate under three layers of software: an application-layer, a GDSS environment, and an operating system environment. It defines the structure and behavior of the GDSS environment layer in terms of (1) objects and messages used to communicate among these objects and (2) a message passing protocol between the GDSS environment and the other two layers. These specifications result in an architecture that is sufficiently modular to enable addition of various GDSS software. This article also discusses a prototype implementation of the architecture that is developed in Smalltalk and runs under Microsoft's Windows 3.0.     

Towards a Structured Design of Electronic Negotiations

Global communication networks and advances in information technology enable the design of information systems facilitating effective formulation and efficient resolution of negotiation problems. Increasingly, these systems guide negotiators in clarifying the relevant issues, provide media for offer formulation and exchange, and help in achieving an agreement. In practice, the task of analysing, modelling, designing and implementing electronic negotiation media demands a systematic, traceable and reproducible approach. An engineering approach to media specification and construction has these characteristics. In this paper, we provide a rationale for the engineering approach that allows pragmatic adoption of economic and social sciences perspectives on negotiated decisions for the purpose of supporting and undertaking electronic negotiations. Similarities and differences of different theories that underlie on-going studies of electronic negotiations are identified. This provides a basis for integration of different theories and approaches for the specific purpose of the design of effective electronic negotiations. Drawing on diverse streams of literature in different fields such as economics, management, computer, and behavioural sciences, we present an example of an integration of three significant streams of theoretical and applied research involving negotiations, traditional auctions and on-line auctions.     

Why Agents for Automated Negotiations Should Be Adaptive

We show that adaptive agents on the Internet can learn to exploit bidding agents who use a (limited) number of fixed strategies. These learning agents can be generated by adapting a special kind of finite automata with evolutionary algorithms (EAs). Our approach is especially powerful if the adaptive agent participates in frequently occurring micro-transactions, where there is sufficient opportunity for the agent to learn online from past negotiations. More in general, results presented in this paper provide a solid basis for the further development of adaptive agents for Internet applications.     

Designing the spreadsheet-based decision support systems course: An application of Bloom's taxonomy

Decision support systems (DSS) have played an important role in organizations for many years. As DSS continue to be developed for industry applications, a number of business programs in universities offer a specialized course aimed at helping students better understand and develop DSS systems to support decision making. Spreadsheet software coupled with an application programming language can serve as a useful DSS generation software package for such courses. To help students develop their technical skills for spreadsheet-based DSS, the principles underlying Bloom's taxonomy of educational objectives can serve as a guiding framework for instructional design. This article describes how Bloom's taxonomy has been used to support the design of two different DSS courses, an undergraduate course and an MBA course. Student survey data collected over the past four years from students enrolled in nine sections of the DSS courses are reported. Based on the survey findings, as well as the instructor's observations, it appears that a teaching strategy based on Bloom's taxonomy offers a worthwhile framework for instructors who teach a spreadsheet-based DSS course.     

Hi,May AI help you? An analysis of the barriers impeding the implementation and use of artificial intelligence-enabled virtual assistants in retail

Artificial Intelligence enabled Virtual Assistants (VAs) are evolving rapidly, offering promising opportunities to provide personalized shopping assistance and 24/7 frontline service. They can reduce the workload of human employees while delivering a seamless customer experience. Despite these benefits, the adoption of AI VAs as a retail marketing channel is patchy. The objective of this study is to reveal the multidisciplinary factors impeding the adoption of AI VAs in retail using the Fuzzy AHP method. Seven main barriers and thirty-seven sub-barriers are identified, classified, and ranked. Findings reveal that customer-related barriers are the most significant. These are followed by technical and financial barriers that retailers face in implementing AI chatbots.     

Negotiation support using the Decision Support System GMCR

The Graph Model for Conflict Resolution constitutes a unique and flexible approach to the representation, analysis, and understanding of strategic conflict. This methodology, as implemented in the Decision Support System GMCR, constitutes a useful tool for negotiation support. Because GMCR includes efficient algorithms for calculating the stability of states, it encourages extensive comparisons of the consequences of different models of negotiators' decision making. GMCR also facilitates modifications to the way in which the conflict is represented, encouraging sensitivity and what-if analyses. The applicability of GMCR to negotiations is discussed in general, and in the context of a specific case study in environmental conflict resolution.     

Using GSS to Design Organizational Processes and Information Systems: An Action Research Study on Collaborative Business Engineering

During an action research study a collaborative business engineering approach was developed, applied, and evaluated. Key characteristic of the approach is its focus on the participative design of organizational processes and supporting information systems. Following the approach, various design activities are carried out in close cooperation with groups of stakeholders supported by a Group Support System (GSS). This paper describes and reflects on the execution of these collaborative design activities in a police organization. Lessons learned with respect to GSS and collaborative design are formulated. Key insights illustrate the stakeholders' perception of the group technology and the way in which it facilitated an efficient design process.     

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.     

Strategies and language trends in learning success and failure of negotiation

In negotiation by electronic means, language is an important deal-making tool which helps realize negotiation strategies. Negotiators may use language to request information, exchange offers, persuade, threaten, as well as reach a compromise or find prospective partners. All this is recorded in texts exchanged by negotiators. We explore the language signals of strategies—argumentation, persuasion, negation, proposition. Leech and Svartvik’s approach to language in communication gives our study the necessary systematic background. It combines pragmatics, the communicative grammar and the meaning of English verbs. Language signals become features in the task of classifying those texts. We employ Statistical Natural Language Processing and Machine Learning techniques to find general trends that negotiation texts exhibit. Our hypothesis is that language signals help predict negotiation outcomes. We run experiments on the Inspire data. The electronic negotiation support system Inspire was gathering data for several years. The data include text messages which negotiators may exchange while trading offers. We conduct a series of Machine Learning experiments to predict the negotiation outcome from the texts associated with first halves of negotiations. We compare the results with the classification of complete negotiations. We conclude the paper with an analysis of the results and a list of suggestions for future work.     

Evolution of group performance over time: A repeated measures study of GDSS effects

Many studies in the group decision support system (GDSS) literature have reported on the behavior and performance of ad hoc groups meeting for the first, and, in fact, the only time. Such one‐time studies of groups may not represent their longer term behavior and performance accurately. Adaptive Structuration Theory (AST) conceives of technology use as a social practice that emerges over time. AST suggests that meeting outcomes reflect the extent to which structures offered by the technology (such as GDSS tool sequences, meeting agenda, etc.) are faithfully appropriated by the group. Such faithful appropriation, however, takes time. This article explicitly recognizes the relevance of this appropriation process and reports on a lab study that examined the impact of computer support on group performance over time. In general, results showed that the performance of computer‐supported groups improved over time, whereas the performance of non‐computer‐supported groups stayed the same or declined. The number of alternatives generated by computer‐supported groups increased considerably as they became more proficient in incorporating the technology into group processes. However, the quality of decisions made by computer‐supported groups began to increase slightly, only during the last session. Both these findings suggest that AST is, in fact, a viable theory for studying group behavior and performance over time. Results from this study also point out the need for conducting more longitudinal studies of group processes in the future.