Group Decision-making Mechanisms Research Articles

System-level time computation and representation in the suprachiasmatic nucleus revealed by large-scale calcium imaging and machine learning.

The suprachiasmatic nucleus (SCN) is the mammalian central circadian pacemaker with heterogeneous neurons acting in concert while each neuron harbors a self-sustained molecular clockwork. Nevertheless, how system-level SCN signals encode time of the day remains enigmatic. Here we show that population-level Ca2+ signals predict hourly time, via a group decision-making mechanism coupled with a spatially modular time feature representation in the SCN. Specifically, we developed a high-speed dual-view two-photon microscope for volumetric Ca2+ imaging of up to 9000 GABAergic neurons in adult SCN slices, and leveraged machine learning methods to capture emergent properties from multiscale Ca2+ signals as a whole. We achieved hourly time prediction by polling random cohorts of SCN neurons, reaching 99.0% accuracy at a cohort size of 900. Further, we revealed that functional neuron subtypes identified by contrastive learning tend to aggregate separately in the SCN space, giving rise to bilaterally symmetrical ripple-like modular patterns. Individual modules represent distinctive time features, such that a module-specifically learned time predictor can also accurately decode hourly time from random polling of the same module. These findings open a new paradigm in deciphering the design principle of the biological clock at the system level.

Reliability Evaluation of Binary Group Decision-Making Mechanism

Decision-making is an important management activity. This study evaluates the reliability of group decision-making (GDM) and multi-attribute GDM (MAGDM) mechanisms for a class of 0–1 binary decision-making problem. We define the reliability of GDM and MAGDM, use the weighted voting system to model the GDM and MAGDM mechanisms, and propose two algorithms to evaluate the reliability of GDM and MAGDM considering the participation of general or professional decision makers. Additionally, the influence of some system parameters, such as the number of decision makers or attributes, cognitive accuracy of decision makers, and threshold of weighted majority voting rule, on the reliability of GDM and MAGDM was analyzed using random simulation experiments. The results of the random experiment show that: increasing the number of decision makers or attributes could improve the decision accuracy; the reduction in the individual subjective accuracy reduces the overall decision accuracy, which was difficult to compensate for by increasing the number of DMs; guiding DMs to reach consensus through group discussion decreased the decision accuracy of GDM and MAGDM.

A hybrid interval evidential reasoning-regret decision making model and its application to the behavior of Chinese herbal medicine planting selection

This paper studies the optimal selection of planting Chinese Herbal Medicine (CHM), which has many attributes and stakeholders, and where some assessment information cannot be obtained directly from the official websites. The assessment information is categorized into two groups: precise and interval numbers that can be obtained from the official sites, and precise information obtained through expert surveys and questionnaires. A three-step group decision-making mechanism is proposed for the CHM problem. First, an analytical method based on interval evidence reasoning is formed to unify different forms of information into the same interval belief structure. Next, a model based on the geometric area method is formed to obtain the weights of the attributes. Third, the extended interval regret theory is used to rank the alternative solutions. Applying perceived utility value and the ranking of the alternatives, an optimal solution for planting CHM is found. Comparative and sensitivity analyses highlight the flexibility and reliability of the suggested solution. By evaluating the various parameters, decision-makers in CHM can prioritize their decisions for maximal benefit.

SÜRDÜRÜLEBİLİRLİK, RİSKLER VE SEZGİSEL BULANIK ORTAM ALTINDA SIRALAMA PROBLEMLERİ İÇİN ÇOK KRİTERLİ GRUP KARAR VERME YÖNTEMİ

This paper presents a group decision-making mechanism to properly manage outranking problems in an intuitionistic fuzzy environment. TOPSIS, outranking multi-criteria decision-making (MCDM) method, is utilized under intuitionistic fuzzy set theory. A set of criteria employed in decision-making problems, the preferences of a group of decision-makers, and the importance levels of decision-makers are examined in this solution technique. Managers use the outranking methods as a reliable technique for making supplier evaluation decisions. Furthermore, the supply chain suffers from the shortage of materials, transportation problems etc. post COVID-19 era, the need for a practical, and exhaustive tool is explicit. An illustrative case on a supplier selection problem considering sustainability and risks in the post-COVID-19 era is used to demonstrate the applicability of the proposed technique by detailing the procedure step by step. The results show that the presented methodology is applicable to the other areas.

Fuzzy inference based Hegselmann–Krause opinion dynamics for group decision-making under ambiguity

This paper considers a group decision-making mechanism for a group of social agents with ambiguous interactions. First, a fuzzy inference approach is introduced to describe bounded confidence based interaction rules among social agents for a certain object in a social network platform. Second, an influence graph is introduced to model the communication network topology associated with the group of agents. A fuzzy inference based opinion dynamics model is built when the defuzzified interaction weights among agents are used in the opinion update scheme for each agent. Third, the patterns of the collective final opinions are analyzed under the proposed fuzzy opinion dynamics model. The fuzziness of opinion gaps and interaction weights among agents are respectively investigated in the collective opinion evolution. Simulation results show the influence of fuzzy values of opinion gaps and interaction weights on the pattern of the collective final opinions and reveal the quantitative relationships of opinion gap and interaction weights between the original HK opinion dynamics model and the fuzzy HK opinion dynamics model.

Modeling household relocation choice: An egalitarian bargaining approach and a comparative study

Accompanying the rapid urban expansion and fast population growth is a progressive trend of residential relocation in developing countries, which necessitates a thorough understanding of households’ relocation decisions. Previous studies generally treated home relocation as an individual or unitary household decision, ignoring the interactive and collaborative decision-making mechanisms that household members may adopt when making group decisions. In view of this research gap, this study examines the feasibility of applying the egalitarian bargaining approach to simulating households’ group decisions concerning residential relocation and further compares its performance with the Nash bargaining and the conventional utilitarian approach. Moreover, the study experiments with the possibility of accommodating three possible group decision-making mechanisms using the latent class modeling framework. The proposed modeling approaches are applied to an empirical case study in Beijing. Results show that models based on the egalitarian and Nash bargaining principles have better model fits than the utilitarian principle, suggesting the importance of considering egalitarianism when modeling household members’ collaborative choice on residential relocation. Moreover, the model based on Nash bargaining has the best model fit, indicating that instead of merely seeking egalitarianism or utilitarianism, household members are more likely to strike a balance between fairness and efficiency.

Distributed Resilient Voltage and Reactive Power Control for Islanded Microgrids under False Data Injection Attacks

This paper addresses the problem of voltage and reactive power control of inverter-based distributed generations (DGs) in an islanded microgrid subject to False Data Injection (FDI) attacks. To implement average voltage restoration and reactive power sharing, a two-layer distributed secondary control framework employing a multiagent system (MAS)-based dynamic consensus protocol is proposed. While communication network facilitates distributed control scheme, it leads to vulnerability of microgrids to malicious cyber-attacks. The adverse effects of FDI attack on the secondary controller are analyzed, and the necessary and sufficient conditions to model stealthy attack and probing attack are discussed in detail. A trust-based resilient control strategy is developed to resist the impacts of FDI attack. Based on the forward-backward consistency criterion, the self-monitoring and neighbor-monitoring mechanisms are developed to detect the misbehaving DGs. A group decision-making mechanism is also introduced to settle conflicts arising from the dishonest trust index caused by colluding attacks. A novel mitigation countermeasure is designed to eliminate the adversarial effects of attack: the discarding information mechanism is used to prevent the propagation of false data in the cooperative network while the recovery actions are designed to correct the deviations of collective estimation error in both transient disturbance and continuous FDI attack scenarios. Through a theoretical analysis, it is proved that the proposed mitigation and recovery mechanism can maintain the correct average estimates of voltage and reactive power, which ensures the secondary control objectives of microgrids under FDI attack. Simulation results on an islanded microgrid show the effectiveness and resilience of the proposed control scheme.

Improving the M&A Decision-Making Process: Learning from Serial Acquirers

Mergers and acquisitions (M&A) represent a substantial means to implement corporate and business unit strategy. However, capturing expected value proves to be very challenging. While previous studies on acquisition decision-making have identified a number of impediments to process, they lack a rich and theoretically grounded description of how to systematically mitigate those obstacles. Our research setting is four firms from the German industry sector. Using a multi-case inductive study, we analyze how serial strategic acquirers—all equipped with a dedicated M&A function—have designed their M&A decision-making process. We find that firms rely on group decision-making mechanisms, following three procedural strategies and one governance strategy.

Dynamics of social groups’ decision-making in evacuations

The possible presence of social groups amongst occupants in indoor evacuation scenarios and the potential discrepancies between their behaviour and that of single individuals have been acknowledged in the evacuation dynamics literature. Yet, empirical studies on the behavioural characteristics of social-group evacuees, particularly those related to their decision-making mechanism, are relatively underrepresented. This study reports on a lab-in-the-field experiment of evacuations that investigates the effect of group size and stress level on multiple aspects of groups’ behaviour. These aspects include pre-movement time, decision time (i.e. time taken to reach a directional exit decision), exit-choice behaviour, exit-choice changing and intra-group decision dynamics. Our main findings showed that:(I)Group size had a significant effect on pre-movement times and decision times (and to lesser extent, on evacuation times). People took longer to initiate their movement or to make a directional exit decision when in groups compared to when acting alone. The influence of group size on pre-movement and decision times, however, was not monotonic. For smaller group sizes (sizes 2 and 3), pre-movement and decision times increased with the group size. But for the larger group size (size 4), the effect was reversed.(II)The exit-choice mechanism of groups, overall, showed a great degree of similarity to that of single individuals. This suggests that, from a modelling perspective, the directional exit choices of groups could be approximated with the models obtained from datasets of individually-made choices.(III)Groups were more likely to revisit and change their initial exit decisions under the higher level of stress. In addition, social influence was a major factor in triggering changes in the exit choices of groups. Nearly 50% of the changes in group decisions occurred shortly after another neighbour group changed its exit decision. In other words, instances of group decision-changing was often followed by another group taking a similar action.(IV)As to the within-group dynamics of decision-making, our analyses suggested that, regardless of the group size, leadership was the dominant group decision-making mechanism (compared to the consensus or the conform-to-majority mechanisms). In nearly 50% of the cases, group decisions were made by one individual taking the lead and hinting the direction of the movement to other members of the group.

Report on Information on Groups

On 26 January 2015, the European Commission requested the Informal Company Law Expert Group (ICLEG) to consider the issue of information on groups. In response to this call one member, Martin Winner, was charged with producing a report on behalf of the Group.The Commission’s action plan of 2012 announced an initiative on simplified communication of a group’s structure to investors. This announcement was based inter alia on the Report of the Reflection Group from 2011, which recommended making basic information on the group structure readily available to investors and presenting that information in an investor-friendly manner. The report presents the state of the play regarding transparency of groups of companies in the Member States and at the EU level. It includes several recommendations. Among others, it recommends that listed companies should make public basic information on the group functioning and management in standardised visual form and inform investors in a simplified manner of the central group structure, especially by visualisation. The Commission should consult on whether such information should be mandatory, given on a comply-or-explain basis in the Corporate Governance Statement or encouraged in a non-legislative manner. The Commission should also consult on whether disclosure should be limited to the identity of the ultimate parent or also include verbal information on group decision-making mechanisms. The Commission should consult on the method of disclosure, especially whether disclosure should be made via the company website, the national company register, the company’s correspondence or any combination of the above.

Modelling group navigation: transitive social structures improve navigational performance.

Collective navigation demands that group members reach consensus on which path to follow, a task that might become more challenging when the group's members have different social connections. Group decision-making mechanisms have been studied successfully in the past using individual-based modelling, although many of these studies have neglected the role of social connections between the group's interacting members. Nevertheless, empirical studies have demonstrated that individual recognition, previous shared experiences and inter-individual familiarity can influence the cohesion and the dynamics of the group as well as the relative spatial positions of specific individuals within it. Here, we use models of collective motion to study the impact of social relationships on group navigation by introducing social network structures into a model of collective motion. Our results show that groups consisting of equally informed individuals achieve the highest level of accuracy when they are hierarchically organized with the minimum number of preferred connections per individual. We also observe that the navigational accuracy of a group will depend strongly on detailed aspects of its social organization. More specifically, group navigation does not only depend on the underlying social relationships, but also on how much weight leading individuals put on following others. Also, we show that groups with certain social structures can compensate better for an increased level of navigational error. The results have broader implications for studies on collective navigation and motion because they show that only by considering a group's social system can we fully elucidate the dynamics and advantages of joint movements.

Group Decisions for the Emergency Response Process: A Case of a High-Speed Railway Accident in China

ABSTRACT Quick and efficient decisions should be made when unconventional emergencies occur. This paper develops an emergency group decision-making mechanism for use in unconventional emergency responses. The scenario analysis approach provides analysis results of current situations and future trends of emergency events as important decision information. The paper also utilizes Dynamic Bayesian Networks theory to build a scenario-response model of emergency group decision-making. A case study of the “7·23” high-speed railway accident in China is conducted to test the effectiveness of the proposed model. The analysis results show that the scenario-response model contributes to initiative and efficiency in unconventional emergency responses. The results also suggest that current situations and possible trends of unconventional emergencies should be considered as decision support information in the emergency decision-making process. Emergency response managers can utilize the research model to learn experience from existing emergency events and develop decision-making mechanisms for emergencies in the future.

Intergroup trust and reciprocity in strategic interactions: Effects of group decision-making mechanisms

I examined the impact of the consensus-making mechanism, where members reach a common decision via an intra-group discussion, on intergroup trust and reciprocity in a strategic setting. Data from a trust game generated the following results. First, compared to individual decision-makers, consensus groups exhibited (a) lower psychological trust, (b) higher behavioral trust, after controlling for psychological trust, and (c) lower reciprocity. Second, compared to decisions made by group-representatives, who are responsible for unilateral decisions on behalf of their groups, group consensus decisions were more trusting but less reciprocating. Thus, the specific decision-making mechanism adopted by groups in a strategic interaction may profoundly change the nature and the interplay of the interaction. Lastly, results show that the level of behavioral trust is driven by reciprocity expectations, while the level of reciprocity behavior, measured as a proportion of the trust received, does not change systematically with the level of trust experienced.

Modeling household activity travel behavior: Examples of state of the art modeling approaches and research agenda

Even though the importance of representing group decision-making mechanisms of household behavior has been recognized since the 1980s in the context of the activity-based approach, studies about group behavior in transportation are relatively new and consequently limited, compared with the research about individual decisions. In line with the special issue “Modeling Intra-Household Interactions and Group Decision-Making” published in the Journal of Transportation in 2005, and motivated by the recent progress of group behavior research in transportation, this special issue presents examples of state-of-the-art modeling approaches to household activity travel decisions. We hope it will stimulate more intensive discussion about future research directions from both methodological and practical perspectives. Five papers are selected to cover diverse methodologies, including group decision theory, utility theory, latent class modeling, rule-based modeling, and micro-simulation approaches. The topics cover household task and time allocation, car ownership, vehicle transaction, mode choice, activity generation, and activity scheduling behavior.

Modeling household discrete choice behavior incorporating heterogeneous group decision-making mechanisms

To represent heterogeneous group decision-making mechanisms in choice behavior, this paper attempts to develop a new household discrete choice model by integrating different types of household choice models based on latent class modeling approach under the principle of random utility maximization, where household utility function at each model is defined to theoretically reflect its members’ preferences and intra-household interaction. A latent class corresponds to a particular group decision-making mechanism. The proposed model can deal with not only the choice situations where multiple household members involved in joint decision are known a priori, but also the situations where the involved members are unknown. As a case study, three types of household utility functions are dealt with: multi-linear, maximum and minimum types, in the context of couples’ car ownership behaviors. Due to the limited sample size, paired combinations of the three utilities are examined and compared. Using the data collected in two Japanese cities in 2004, the effectiveness of the proposed household decision model is empirically confirmed. It is found that changes of utility combinations result in very complicated variations in both signs and values of the model parameters and choice probabilities by multi-linear utility show small variations across different combinations.

Modeling Group Decision-Making Mechanisms in Household Travel Behavior: Theories and an Application

Modeling Group Decision-Making Mechanisms in Household Travel Behavior: Theories and an Application

Trust and reciprocity in inter-individual versus inter-group interactions: The effects of social influence, group dynamics, and perspective biases

Using an experimental trust game, I examine whether the perspectives and behavior of group representatives and consensus groups differ from those of the same individuals in an analogous inter-individual situation. A primary goal of this research is to extend past work on trust and reciprocity by examining the impact of the social contexts within which social interactions are characteristically embedded. Specifically, this research concerns whether norms and dynamics of trust and reciprocity differ in the contexts of inter-individual and inter-group interactions. First, I examine whether dynamics of trust and reciprocity differ in various inter-group interactions where inter-group decisions are operationalized as 1) autonomous group representatives, i.e., individuals who are given the responsibility of unilaterally making a decision on behalf of a three-person group engaging with a group representative of another such group; and 2) consensus groups, i.e., group members making a consensus trust or reciprocity decision for their groups via a collective process with another such group. Results of these studies show that 1) people trust less and reciprocate less when responsible for a group or organizational decision as autonomous group representatives; 2) consensus groups do not differ from individuals in their level of trust but show dramatically less reciprocity. The group consensus mechanism in fact produced by far the lowest reciprocity level, significantly lower than that exhibited by either individuals or autonomous group representatives. Thus, inter-group trust and reciprocity dynamics are not readily inferable from their inter-individual counterparts. Moreover, an important implication is emerging here: the extent and direction of the discrepancy between individual and group choices in regard to trust and reciprocity levels and possibly other social preferences in general may depend importantly on the precise details of the group decision-making mechanism, for example whether decisions are made consensually, by majority vote, or by a group leader or representative. In addition to examining the level of trust and reciprocity that occur in these various situations, I also studied, using both behavioral and questionnaire data, the roles of self-interest, social influence, and group dynamics in trust and reciprocity perceptions and behavior. The results showed that there exist discrepancies between behavioral forecasts and the actual behavior, and that trusting behavior is driven strongly by expectation of level of reciprocation, while reciprocating behavior is driven strongly by the difference between trust expectation and actual trust received.

Survey and Model Development of Household Residential Choice Behavior with Group Decision-Making Mechanisms

Survey and Model Development of Household Residential Choice Behavior with Group Decision-Making Mechanisms

Survey and Model Development of Household Residential Choice Behavior with Group Decision-Making Mechanisms

Survey and Model Development of Household Residential Choice Behavior with Group Decision-Making Mechanisms

A model for joint choice of daily activity pattern types of household members

Intra-household interactions constitute an important aspect in modeling activity and travel-related decisions. Recognition of this importance has recently produced a growing body of research on various aspects of modeling intra-household interactions and group decision-making mechanisms as well as first attempts to incorporate intra-household interactions in regional travel demand models. The previously published research works were mostly focused on time allocation aspect and less on generation of activity episodes, trips, and travel tours that are necessary units for compatibility with regional travel demand models. Also, most of the approaches were limited to household heads only and did not consider explicitly the other household members as acting agents in the intra-household decision making. A model is proposed for joint choice of daily activity pattern (DAP) types for all household members that explicitly takes into account added group-wise utilities of joint participation in the same activity. The model is based on the aggregate description of individual DAP types by three main categories – mandatory travel pattern, non-mandatory travel pattern, and at-home pattern. Important intra-household interactions can be captured already at this aggregate level. A choice structure considers all possible combinations of DAPs of all household members as alternatives. Utility function of each alternative includes components corresponding to each individual DAP type as well as group-wise interaction terms that correspond to joint choice of the same pattern by several household members. Statistical analysis of intra-household interactions and estimation results of the choice model are presented. The model estimation has confirmed a strong added utility of joint choice of the same pattern for such person types as non-worker or part time worker in combination with child, two retired persons, two children, and others. The proposed model represents a part of the advanced regional model system being developed for the Atlanta Regional Commission.