Predicting satisfaction: perceived decision quality by decision-makers in Web-based group decision support systems

In future, the organizations' likelihood to endure and succeed will depend greatly on the quality of every decision made. It is known that most decisions in organizations are made in group. With the purpose of supporting decision-makers anytime and anywhere, Web-based Group Decision Support Systems (GDSS) have been studied. The amount of Web-based GDSS incorporating automatic negotiation mechanisms such as argumentation has been steadily increasing. Usually, these systems/models are evaluated through mathematical proofs, number of rounds or seconds to propose (reach) a solution. However, those techniques are not very informative in terms of the decision quality. Here, we propose a model that intends to predict the decision-makers' satisfaction (perception of the decision quality), specifically designed to deal with multi-criteria problems. Our model considers aspects such as: meeting's outcomes, decision-maker's intentions, expectations and emotional cost. To validate the proposed model in terms of its ability to predict decision-makers' satisfaction, we developed a prototype of a Web-based GDSS to be used in a case study where the participant had to make a joint decision. The decision process consisted in a set of 5 rounds, where the participant could (re) configure his/her preferences along the process. The satisfaction model ascertained its ability to predict the participants' satisfaction and allowed to understand that (as is stated in the literature) the inclusion of cognitive and emotional variables is essential to evaluate satisfaction more accurately.This paper is a revised and an expanded version of a paper entitled "Evaluating the Perception of the Decision Quality in Web-Based Group Decision Support Systems: A Theory of Satisfaction" presented at International Conference on Practical Applications of Agents and Multi-Agent Systems 2017, Porto, Portugal [12]. This work has been supported by COMPETE Programme (operational programme for competitiveness) within project POCI-01-0145-FEDER-007043, by National Funds through the FCT - Fundacao para a Ciencia e a Tecnologia (Portuguese Foundation for Science and Technology) within the Projects UID/CEC/00319/2013, UID/EEA/00760/2013, NORTE-01-0247-FEDER-021958, and the PhD. grants SFRH/BD/89697/2012 and SFRH/BD/89465/2012 attributed to Joao Carneiro and Pedro Saraiva, respectively

CREATIVITY IN STRATEGIC PLANNING: THE INFLUENCE OF TEMPORAL PERSPECTIVE

As organizational environments become more turbulent and complex and as uncertainty about the future increases, reliance on quantitative decision-making approaches for strategic planning becomes less appropriate. Scenario analysis can be an effective qualitative technique for enhancing strategic planning. Typically, scenarios are presented as alternate futures. Some theorists, however, have suggested that forward and backward thinking are different cognitive processes. In this study, we investigate the effect of presenting scenarios retrospectively; that is, as if future events had already happened. A repeated measures laboratory study compared the performance of professional planners (n = 64) using prospective and retrospective scenarios in two simulated business planning tasks. Measures consisted of objective factors (number of individual planning statements and number of monitoring statements), subjective factors (quality based on an 18-question rating instrument), and subject attitudes concerning their experience with the two treatments. Results suggest that use of retrospective scenarios do increase the number of planning statements. In addition, plans prepared using retrospective scenarios were rated higher overall than those prepared with prospective scenarios. Moreover, evidence emerged that a subset of subjects were better able to make use of the retrospective technique, suggesting that selection along with training may improve planning performance.Information Systems Working Papers Serie

Measuring the Utility of a Cyber Incident Mission Impact Assessment (CIMIA) Process for Mission Assurance

Information is a critical asset on which virtually all modern organizations depend upon to meet their operational mission objectives. Military organizations, in particular, have embedded Information and Communications Technologies (ICT) into their core mission processes as a means to increase their operational efficiency, exploit automation, improve decision quality, and shorten the kill chain. However, the extreme dependence upon ICT results in an environment where a cyber incident can result in severe mission degradation, or possibly failure, with catastrophic consequences to life, limb, and property. These consequences can be minimized by maintaining real-time situational awareness of mission critical resources so appropriate contingency actions can be taken in a timely manner following an incident in order to assure mission success. In this thesis, the design and analysis of an experiment is presented for the purpose of measuring the utility of a Cyber Incident Mission Impact Assessment (CIMIA) notification process, whose goal is to improve the timeliness and relevance of incident notification. In the experiment, subjects are placed into a model environment where they conduct operational tasks in the presence and absence of enhanced CIMIA notifications. The results of the experiment reveal that implementing a CIMIA notification process significantly reduced the response time required for subjects to recognize and take proper contingency actions to assure their organizational mission. The research confirms that timely and relevant notification following a cyber incident is an essential element of mission assurance

Group decision support systems for current times: Overcoming the challenges of dispersed group decision-making

We are living a change of paradigm regarding decision-making. On the one hand, there is a growing need to make decisions in group at both professional and personal levels, on the other hand, it is increasingly difficult for decision-makers to meet at the same place and at the same time. The Web-based Group Decision Support Systems intend to overcome this limitation, allowing decision-makers to contribute to the decision process anytime and anywhere. However, they have been defined inadequately which has been compromising its success. This work discusses the current Group Decision Support Systems limitations in terms of challenges and possible impediments for their acceptance by the organizations and propose a conceptual definition of a Web-based Group Decision Support System that intends to overcome the existing limitations and help them to affirm as a reliable and useful tool. In addition, some crucial topics are addressed, such as communication and perception, that are essential and sometimes forgotten in the support of dispersed decision-makers. We concluded that there are still some limitations, mostly in terms of models and applications, that prevent the design of higher quality systems.This work was supported by the GrouPlanner Project (POCI-01-0145-FEDER-29178) and by National Funds through the FCT – Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within the Projects UIDB/00319/2020 and UIDB/00760/2020

Arguing with behavior influence: A model for web-based group decision support systems

In this work, we propose an argumentation-based dialogue model designed for Web-based Group Decision Support Systems, that considers the decision-makers' intentions. The intentions are modeled as behavior styles which allow agents to interact with each other as humans would in face-to-face meetings. In addition, we propose a set of arguments that can be used by the agents to perform and evaluate requests, while considering the agents' behavior style. The inclusion of decision-makers' intentions intends to create a more reliable and realistic process. Our model proved, in different contexts, that higher levels of consensus and satisfaction are achieved when using agents modeled with behavior styles compared to agents without any features to represent the decision-makers' intentions.- (undefined

An Examination into How Group Performance is Influenced by Various Communication Channels

This purpose of this research was to look at the how group performance is influenced by various communication channels. Specifically, this research sought to determine what communication factors are affected when groups are forced to use different communications channels. The three communications channels tested were face-to-face communications, audio conferencing, and computer-mediated communications through an Internet chat program. Each channel was measured on accuracy, efficiency, and total number of ideas generated. The research found that the groups using computer-mediated communications had a difficult time completing the exercises in the allotted time. Additionally, the computer-mediated produced significantly fewer total words and total inputs during the experiment. This research produced no statistical difference between any of the groups in total number of ideas generated and no statistical difference in any of the three categories between the face-to-face and audio conference groups

Aplicação de técnicas de Clustering ao contexto da Tomada de Decisão em Grupo

Nowadays, decisions made by executives and managers are primarily made in a group. Therefore, group decision-making is a process where a group of people called participants work together to analyze a set of variables, considering and evaluating a set of alternatives to select one or more solutions. There are many problems associated with group decision-making, namely when the participants cannot meet for any reason, ranging from schedule incompatibility to being in different countries with different time zones. To support this process, Group Decision Support Systems (GDSS) evolved to what today we call web-based GDSS. In GDSS, argumentation is ideal since it makes it easier to use justifications and explanations in interactions between decision-makers so they can sustain their opinions. Aspect Based Sentiment Analysis (ABSA) is a subfield of Argument Mining closely related to Natural Language Processing. It intends to classify opinions at the aspect level and identify the elements of an opinion. Applying ABSA techniques to Group Decision Making Context results in the automatic identification of alternatives and criteria, for example. This automatic identification is essential to reduce the time decision-makers take to step themselves up on Group Decision Support Systems and offer them various insights and knowledge on the discussion they are participants. One of these insights can be arguments getting used by the decision-makers about an alternative. Therefore, this dissertation proposes a methodology that uses an unsupervised technique, Clustering, and aims to segment the participants of a discussion based on arguments used so it can produce knowledge from the current information in the GDSS. This methodology can be hosted in a web service that follows a micro-service architecture and utilizes Data Preprocessing and Intra-sentence Segmentation in addition to Clustering to achieve the objectives of the dissertation. Word Embedding is needed when we apply clustering techniques to natural language text to transform the natural language text into vectors usable by the clustering techniques. In addition to Word Embedding, Dimensionality Reduction techniques were tested to improve the results. Maintaining the same Preprocessing steps and varying the chosen Clustering techniques, Word Embedders, and Dimensionality Reduction techniques came up with the best approach. This approach consisted of the KMeans++ clustering technique, using SBERT as the word embedder with UMAP dimensionality reduction, reducing the number of dimensions to 2. This experiment achieved a Silhouette Score of 0.63 with 8 clusters on the baseball dataset, which wielded good cluster results based on their manual review and Wordclouds. The same approach obtained a Silhouette Score of 0.59 with 16 clusters on the car brand dataset, which we used as an approach validation dataset.Atualmente, as decisões tomadas por gestores e executivos são maioritariamente realizadas em grupo. Sendo assim, a tomada de decisão em grupo é um processo no qual um grupo de pessoas denominadas de participantes, atuam em conjunto, analisando um conjunto de variáveis, considerando e avaliando um conjunto de alternativas com o objetivo de selecionar uma ou mais soluções. Existem muitos problemas associados ao processo de tomada de decisão, principalmente quando os participantes não têm possibilidades de se reunirem (Exs.: Os participantes encontramse em diferentes locais, os países onde estão têm fusos horários diferentes, incompatibilidades de agenda, etc.). Para suportar este processo de tomada de decisão, os Sistemas de Apoio à Tomada de Decisão em Grupo (SADG) evoluíram para o que hoje se chamam de Sistemas de Apoio à Tomada de Decisão em Grupo baseados na Web. Num SADG, argumentação é ideal pois facilita a utilização de justificações e explicações nas interações entre decisores para que possam suster as suas opiniões. Aspect Based Sentiment Analysis (ABSA) é uma área de Argument Mining correlacionada com o Processamento de Linguagem Natural. Esta área pretende classificar opiniões ao nível do aspeto da frase e identificar os elementos de uma opinião. Aplicando técnicas de ABSA à Tomada de Decisão em Grupo resulta na identificação automática de alternativas e critérios por exemplo. Esta identificação automática é essencial para reduzir o tempo que os decisores gastam a customizarem-se no SADG e oferece aos mesmos conhecimento e entendimentos sobre a discussão ao qual participam. Um destes entendimentos pode ser os argumentos a serem usados pelos decisores sobre uma alternativa. Assim, esta dissertação propõe uma metodologia que utiliza uma técnica não-supervisionada, Clustering, com o objetivo de segmentar os participantes de uma discussão com base nos argumentos usados pelos mesmos de modo a produzir conhecimento com a informação atual no SADG. Esta metodologia pode ser colocada num serviço web que segue a arquitetura micro serviços e utiliza Preprocessamento de Dados e Segmentação Intra Frase em conjunto com o Clustering para atingir os objetivos desta dissertação. Word Embedding também é necessário para aplicar técnicas de Clustering a texto em linguagem natural para transformar o texto em vetores que possam ser usados pelas técnicas de Clustering. Também Técnicas de Redução de Dimensionalidade também foram testadas de modo a melhorar os resultados. Mantendo os passos de Preprocessamento e variando as técnicas de Clustering, Word Embedder e as técnicas de Redução de Dimensionalidade de modo a encontrar a melhor abordagem. Essa abordagem consiste na utilização da técnica de Clustering KMeans++ com o SBERT como Word Embedder e UMAP como a técnica de redução de dimensionalidade, reduzindo as dimensões iniciais para duas. Esta experiência obteve um Silhouette Score de 0.63 com 8 clusters no dataset de baseball, que resultou em bons resultados de cluster com base na sua revisão manual e visualização dos WordClouds. A mesma abordagem obteve um Silhouette Score de 0.59 com 16 clusters no dataset das marcas de carros, ao qual usamos esse dataset com validação de abordagem

Defining agents’ behaviour for negotiation contexts

Agents who represent participants in the group decision-making context require a certain number of individual traits in order to be successful. By using argumentation models, agents are capable to defend the interests of those who they represent, and also justify and support their ideas and actions. However, regardless of how much knowledge they might hold, it is essential to define their behaviour. In this paper (1) is presented a study about the most important models to infer different types of behaviours that can be adapted and used in this context, (2) are proposed rules that must be followed to affect positively the system when defining behaviours and (3) is proposed the adaptation of a conflict management model to the context of Group Decision Support Systems. We propose one approach that (a) intends to reflect a natural way of human behaviour in the agents, (b) provides an easier way to reach an agreement between all parties involved and (c) does not have high configuration costs to the participants. Our approach will offer a simple yet perceptible configuration tool that can be used by the participants and contribute to more intelligent communications between agents and makes possible for the participants to have a better understanding of the types of interactions experienced by the agents belonging to the system.This work is part-funded by ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) within project FCOMP-01-0124-FEDER-028980 (PTDC/EEISII/1386/2012) and by National Funds through the FCT - Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) with the João Carneiro PhD grant with the reference SFRH/BD/89697/2012.info:eu-repo/semantics/publishedVersio