group decision

Decision making in the Agriculture domain can be a complex task. The land area allocated to each crop should be fixed every season according to several parameters: prices, demand, harvesting periods, seeds, ground, season etc… The decision to make becomes more difficult when a group of farmers must fix the price and all parameters all together. Generally, optimization models are useful for farmers to find no dominated solutions, but it remains difficult if the farmers have to agree on one solution. We combine two approaches in order to support a group of farmers engaged in this kind of decision making process. We firstly generate a set of no dominated solutions thanks to a centralized optimization model. Based on this set of solution we then used a Group Decision Support System called GRUS for choosing the best solution for the group of farmers. The combined approach allows us to determine the best solution for the group in a consensual way. This combination of approaches is very innovative for the Agriculture. This approach has been tested in laboratory in a previous work. In the current work the same experiment has been conducted with real business (farmers) in order to benefit from their expertise. The two experiments are compared.

In the paper, we adopt the language of weighted formulas to express individual preferences, and we focus on how these preferences can be aggregated: In the classical utilitarian set- ting, the collective utility (or utilitarian social welfare) is the sum of the utilities of the individuals. In fair group decision- making, instead, it is more appropriate to consider egalitar- ian (or Rawlsian) social welfare, which is the utility of the least satisfied agent. For instance, under egalitarianism, find- ing an optimal allocation of indivisible goods to agents is the so-called Santa Claus problem [Bezakova and Dani, 2005; Bansal and Sviridenko, 2006].

2.3. Annotations as the core of organising processes: the annotative practice Despite the huge number of intrinsic qualities of annotations that our literature review and our ground observations point out, still the annotations are considered as second- order elements, useful but not key objects of concern for group decision support or the Computer Supported Cooperative Work (CSCW) field. Now, we will formulate the hypothesis that annotations can be considered opportunely as constitutive elements – not peripheral – in the production of documents and in the forging of organisational texts. Beyond documentary features, we will also characterise them as elementary bricks that are constitutive elements in the organisation of medical work that is closely tied to text production, that intervene in managing patients’ pathology, trajectory and care (Berg, 1999 ; Mayere, Bazet, & Roux, 2012 ; Star & Strauss, 1999 ). Annotations are core elements of the everyday practice of organising in an oncology ward. Care- givers rely on what we could call an ‘annotative practice’ to handle their complex envi- ronment of work and the complex situations of patients they take care of. This annotative practice deals with three valuable data flows (see Figure 2 ):

offers some concluding remarks and perspectives. 2 Related Work Moulin [ 5 ] defined cooperative games as follows: “A cooperative game in society N consists of a feasible utility set for the grand coalition N as well as a utility set for each and every sub-coalition (non-empty subset) of N, including the coalitions containing one agent only.” He then proposed a categorization of many Game Theory axioms. Inspired by his definitions, we define Collaborative Decision Processes as dynamic decision processes involving several actors, who may use Information and Communi‐ cation Technologies, who interact not only by making moves but also by updating their information and beliefs as other participants move. For these Collaborative Decision Processes, the use of Group Decision Support Systems (GDSS) is called for, and the facilitation process takes a central place.

It can be drawn as a conclusion that research on coordination issues in agricultural SCs is in its early development. Moreover, research addressing coordination among actors in the same stage specifically at the farmer stage is even more scarce. In view of this, this paper analyses how the multi-criteria group decision-makingbehavior of small farmers supported by GRUS DSS is affected by the optimal solution knowledge obtained from a mathematical model. Three objectives (criteria) related to the eco- nomic, social and environmental categories are considered to achieve the sustainabil- ity of the horticulture supply chain coping, therefore, with the so-called triple bottom line. Therefore, with this work we contribute to fill the scarcity of works dealing with multiple stakeholder decision analysis, coordination among small farmers, predictive modelling of their decision-makingbehavior and application of hybrid modelling ap- proaches to achieve the sustainability in horticulture SCs.

VII. C ONCLUSION The problem of social interactions in group decision- making, issues rarely considered in the decision support literature, has been explored in this paper. The notions of social vicinity, social feelings (positive or negative) towards others, altruism or selfishness, etc. have been introduced and formalized. Finally, the decision-making process have two levels: at the local level, each decision-maker determines some parameters using formalized procedures, that will be used at the group level by aggregation (in the broadest sense) to arrive at the final solution. Many traditional ways of aggregating individual choices to arrive to a group choice such voting (ticking on alternative at most, approval voting, majority voting, Borda approach, etc.) as well as newer concept such as consenus seeking are compatible with the approach developped so fare in this paper; furthermore somme indices that can be used to measure whow the social interactions influence individual behavior have been developped. An illustrative application based on real world problem shows the applicability of this approach.

Mireille Ducassé 1 and Peggy Cellier 1 1 IRISA-INSA de Rennes, Campus Universitaire de Beaulieu, 35042 Rennes, France Mireille.Ducasse@irisa.fr, Peggy.Cellier@irisa.fr Abstract: Information overload is a key issue in group decision. A heuristics, called “take-the-best”, has been shown useful to face multicriteria decisions while reducing information overload: when making decisions people often take criteria in a predefined order, the first criterion which discriminates the alternatives at stake is used to make the decision. In order to rationalize group work, Briggs and de Vreede have proposed collaboration design patterns, called thinkLets. This article presents the LogicalMulticriteriaSort thinkLet that can be seen as a generalization of the take- the-best heuristics. It also proposes to consider criteria one at the time but once a criterion has been found discriminating it is kept in a record, and the process is iterated. The thinkLet is supported by a GDSS, based on Logical Information Systems, which gives an instantaneous feedback of each micro decision and keeps tracks of all of the decisions taken so far. The LogicalMulticriteriaSort thinkLet guarantees more fairness and speed than the ChauffeurSort thinkLet. It also avoids the need to give artificial values and weights to the criteria as opposed to the Multicriteria thinkLet. A successful test case is reported.

It can be drawn as a conclusion that research on coordination issues in agricultural SCs is in its early development. Moreover, research addressing coordination among actors in the same stage specifically at the farmer stage is even more scarce. In view of this, this paper analyses how the multi-criteria group decision-makingbehavior of small farmers supported by GRUS DSS is affected by the optimal solution knowledge obtained from a mathematical model. Three objectives (criteria) related to the eco- nomic, social and environmental categories are considered to achieve the sustainabil- ity of the horticulture supply chain coping, therefore, with the so-called triple bottom line. Therefore, with this work we contribute to fill the scarcity of works dealing with multiple stakeholder decision analysis, coordination among small farmers, predictive modelling of their decision-makingbehavior and application of hybrid modelling ap- proaches to achieve the sustainability in horticulture SCs.

We believe that our research is unique and brings sufficient contributions in area of supply chain due to the following rea- sons: Despite of many articles employed integrated and intelligent tools in order to compare the performance of suppliers and logis- tic providers, none of them designed a platform or prototype of a DSS for their objectives. Whilst the existing literature noticed no particular study assigned to the modelling of a DSS for the evaluation of logistic providers, we announce that our GRUS sys- tem would allow a more holistically successful direction on logis- tic decision making and therefore a more sustainable supply chain can be achieved. In addition of that, none of the decision sup- port tools in the past studies, to best of our knowledge, reported a customer/stakeholder-driven approach with utilization of QFD. Pre- vious research projects reported logistic provider’s assessment by different perspective and far from customer satisfaction. Therefore, these shortcomings existed in the current supply chain investiga- tions will be captured and resolved in this paper. We adopted a decision support system through the integration of quality function deployment aided by fuzzy TOPSIS. A group decision making struc- ture with a systematic procedure can reduce the effect of arbitrary decisions by managing tension among decision makers and accel- erate the evaluation process using a rational aggregation of group decisions and application of information technology and computer programming. With confidence, it can be interpreted that this is the first DSS which combines QFD and fuzzy TOPSIS in order to evaluate logistic service providers by a real-world project.

Keywords: annotations management, complex tasks, caregivers’ coordination, data flows management. 1 Annotations to handle complex environments Our main research topic consists in the understanding and the computer support of organizing processes in uncertain, fast changing and complex environment [1]. We conduct an empirical and qualitative research in a palliative ward of an oncology hospital for more than 5 years. This led us to consider annotation practice and annotative process (to be defined thereafter) as the core elements of organizational work of caregivers in the ward to grab complexity and coordinate collective action in this highly evolving environment. We present in this paper a tool based on annotations management that we conceived for group decision making and for the support of work organizing practices.

The results addressed certain factors that require careful consideration in the design of group decision processes and group decision support. One such factor is the impact of the homogeneity of the group. Cohesive groups can agree more easily, especially if there are dominant leaders, but the consequence is to limit creative solutions. Another concern that could be tested is the view that the use of GDSS reduces complexity, not only because of the larger numbers of group members, but also because the only way to find shared criteria is to look for the “lowest common denominator.” Cultural effects could also influence the results, and it is our intention to test them by conduct- ing other experiments in other countries.

Abstract. Collective decision processes remain a common management ap- proach in most organizations. In such processes, it seems important to offer par- ticipants the opportunity to confront the differences in their points of view. To this end, cognitive and technical tools are required that facilitate the sharing of individuals’ reasoning and preferences, but at the same time allow them to keep some information and attitudes to themselves. The aim of our study is to assess whether, in the multi-criteria approach to problem structuring, decision-makers can be comfortable using shared criteria in addition to private criteria. For this purpose, an exploratory experiment with student subjects was conducted using the Group Decision Support System, GRUS.

3 University of Waterloo, Waterloo, Canada Abstract. Because collective decision processes are central to the management function of most organizations, it is important to understand them better and to improve them if possible. One common view of group decision processes is that they should offer participants the opportunity to confront and resolve the differ‐ ences in their points of view. New cognitive and technical tools may help to facilitate the sharing of individuals’ reasoning and preferences, but only if they do not require participants to reveal information that they wish to keep private, perhaps for strategic or personal reasons. The aim of this study is to test experi‐ mentally one such approach, contained in the Group Decision Support System, GRUS, which allows decision makers to use a multi-criteria approach to problem structuring that can involve both public (shared) and private criteria.

a b s t r a c t Social networks are the most preferred mean for the people to communicate. Therefore, it is quite usual that experts use them to carry out Group Decision Making processes. One disadvantage that recent Group Decision Making methods have is that they do not allow the experts to use free text to express themselves. On the contrary, they force them to follow a specific user–computer communication structure. This is against social network nature where experts are free to express themselves using their preferred text structure. This paper presents a novel model for experts to carry out Group Decision Making processes using free text and alternatives pairwise comparisons. The main advantage of this method is that it is designed to work using social networks. Sentiment analysis procedures are used to analyze free texts and extract the preferences that the experts provide about the alternatives. Also, our method introduces two ways of applying consensus measures over the Group Decision Making process. They can be used to determine if the experts agree among them or if there are different postures. This way, it is possible to promote the debate in those cases where consensus is low.

As such, the contribution of our study is threefold. First, our model contributes to the literature by addressing three objectives simulta- neously to locate RDCs in disasters response which, to the best of our knowledge, have not yet been covered in the literature. We benchmark our findings against UN World Food Programme (UN WFP)’s operations and examine the sensitivity of model suggestions to changes in the main parameters. Second, the suggested approach contributes to under- standing what trade-offs actually matter in a given logistics decision. This information offers DMs an indication of where they might need further discussions in the presence of several non-dominated location alternatives. We support this contribution by applying our proposal to the UN WFP’s real dataset for the 2015 Nepal earthquake response. Third, we add to the existing body of research about the value of Monte Carlo Simulations to address the uncertainties and ambiguities [ 21 ] regarding the preferences of multiple DMs in disasters response. To validate our proposal and support the second contribution, we conduct a group decision-making experiment based on the described case with participants from multiple HOs.

In this paper we propose to use a BLF in the collective decision problem to accept or reject a candidate. We propose to organize the decision by letting agents vote about the features that hold for the candidate but agents are never allowed to vote about the goals that would be achieved by selecting the candidate. Hence we separate the decision into three phases, the phase where the criteria associated to a good decision are defined (the BLF construction which is out of the scope of this paper), the phase where the candidates are evaluated by the voters, and the final decision to accept or reject the candidate (which is an automatic phase using the BLF with the precise features concerning the current candidate). In the literature the specification of a CUF is an aggregation of the agent preferences hence this is somewhat mixing the three phases. Moreover, in order to show that this rich and visual framework is well founded we show how the use of a common BLF may reduce the impact of manipulation strategies in the context of group decision making. The term manipulation is used in a weak sense, since the results presented are not of a game-theoretic nature, in particular, they do not admit deviating behavior. However since agents have the right to omit some information we consider that this behavior is a kind of manipulation.

4 E-Governance as a tool for supporting group decision making The modern communication tools like internet allow us in some kind to “externalize” our brains and nerve system, enabling us to exchange and expand our ideas, exposing new hypothesis to criticism and improving our ability of knowledge generation. A special avatar of those communication systems called “e-Government” or “e- Democracy” is also a part of complex puzzle map capacitating the modern society to perform group decisions, providing a data interchange infrastructure between society members and institutions [14]. What is the main point of possibilities provided with e- Government and e-Democracy tools? As mentioned before the main important resource of modern society is the generation of scientific knowledge where conjecture and criticism are important factors of making rational explanations for phenomena. The knowledge about how to make a group decision in society effectively is also not an exception and every time when we are ready to make a next “experiment” in our society we make a group decision – e.g. for an acceptance of a new law or an absolution of an old one [15]. How can we be sure that our group decision in this case will be effective, that our decision will minimize the negative effects and maximize benefits for the society as a whole? The principles here are not too much different from those ones used to explain a new scientific hypothesis: we have to expose our “hypothesis” – e.g. our new legislative project - to maximum of criticism that will give explanations which benefits and costs will this or that law bring to different interest groups [16]. And this will be the basis for making the next group decision in out legislation [17].

In this paper we propose to use a BLF in the collective decision problem to accept or reject a candidate. We propose to organize the decision by letting agents vote about the features that hold for the candidate but agents are never allowed to vote about the goals that would be achieved by selecting the candidate. Hence we separate the decision into three phases, the phase where the criteria associated to a good decision are defined (the BLF construction which is out of the scope of this paper), the phase where the candidates are evaluated by the voters, and the final decision to accept or reject the candidate (which is an automatic phase using the BLF with the precise features concerning the current candidate). In the literature the specification of a CUF is an aggregation of the agent preferences hence this is somewhat mixing the three phases. Moreover, in order to show that this rich and visual framework is well founded we show how the use of a common BLF may reduce the impact of manipulation strategies in the context of group decision making. The term manipulation is used in a weak sense, since the results presented are not of a game-theoretic nature, in particular, they do not admit deviating behavior. However since agents have the right to omit some information we consider that this behavior is a kind of manipulation.

a b s t r a c t This paper addresses the collaborative group decision making problems considering a consensus pro- cesses to achieve a common legitimate solution. The proposed resolution model is based on individual bipolar assessment. Each decision maker evaluates alternatives through selectability and rejectability measures which respectively represent the positive and negative aspects of alternatives considering objectives achievement. The impact of human behavior (influence, individualism, fear, caution, etc.) on decisional capacity has been taken into account. The influence degrees exerted mutually by decision makers are modeled through concordance and discordance measures. The individualistic nature of deci- sion makers has been taken into account from the individualism degree. In order to achieve a common solution(s), models of consensus building are proposed based on the satisficing game theory formalism for collective decision problems. An application example is given to illustrate the proposed concepts.

We develop a 5-year empirical investigation that is giving us broad and deep insights to characterise activity management in the palliative ward of an oncology hospital, and offer effective support for group decision-making and collaborative activity of caregivers. Following this observation period, we propose a software prototype based upon annotations in which dealing with patients’ state and evolution is a complex organisational task. We based our conception of an annotation tool on the observations of the rich writing practices of medical professionals. We rely on the innovative strategy of intermediate management to introduce a new technology able to bridge heterogeneous, valuable data flows that addresses both management support and activity support in a single tool.