Group Decision-making Procedure Research Articles

Influence of online digital communication in the Decision-making Process amongst Engineering Students

The research project reflects the impact of internet marketing on engineering learners' decision-making in the Ernakulam District. The goal of the study is to understand how educational organisations use the internet and to determine which online marketing tools and tactics work best for connecting with learners in engineering. The impact of online digital communication on engineering students' decision-making procedure when selecting educational programmes and institutions is also reflected in the study. Information from the sample of engineering students in the study region will be gathered using a survey-based research approach. The purpose of this research is to ascertain the manner in which the target group's decision-making procedure is impacted by digitalization. The study is probably going to help elevate the status of online digital communication in the education sector and offer guidance and knowledge to colleges and marketers that want to reach students in the engineering field.

Using scoring functions in a group decision-making procedure with heterogeneous experts and qualitative assessments

In this paper, we propose a group decision-making procedure to rank alternatives in the context of ordered qualitative scales that not necessarily are uniform (the proximities between consecutive terms of the scales can be perceived as different). The procedure manages two ordered qualitative scales. One of them is used to determine the weights of the experts according to their expertise, taking into account the assessments given by a decision-maker to the experts. And another one, that is used by the experts to assess the alternatives. In order to assign numerical scores to the linguistic terms of the ordered qualitative scales, we have introduced and analyzed some scoring functions. They are based on the concept of ordinal proximity measure that properly represents the ordinal proximities between the linguistic terms of the ordered qualitative scales.

Group Decision Making in Competency-Based Medical Education - Clinical Competency Committee

<p>臨床能力委員會(Clinical Competency Committee, CCC)在勝任能力導向醫學教育的總結性評量中扮演重要的角色。委員會根據以評量藍圖執行的職場觀察評量結果，進行系統性的討論，對學員的能力進展做出公正可靠的判斷，回饋給相關利害關係人，並協助學員擬定個人化之補強訓練計畫。進行會議前應有共識會議、師資培育課程、及學員能力進展資料閱讀，事前的學員自我評量能夠促進學員與教師對學員能力進展的認知，並促進學員對於教師回饋的接納理解程度；會議中須建立結構化的決策過程，最終獲得客觀且可信的決策成果；會議後應向學員提供回饋，並協助制訂補強學習計畫或提供訓練協助規劃。藉由完善的CCC程序，可提升臨床醫事人員的訓練品質、教師教學水準、醫療服務品質及專業認同。</p> <p> </p><p>Clinical Competency Committee (CCC) plays a key role in the summative assessment of competency-based medical education (CBME). Specifically, CCC conducts systematic discussions according to the results of workplace observation and assessment derived from assessment blueprints to provide an accountable and reliable judgment on the progression of trainees’ competencies. CCC then informs assessment results to stakeholders and assists trainees in developing personalized remedial learning plans. CCC members should conduct a consensus meeting, complete faculty training courses, and review trainees’ competency development data before calling a CCC meeting . Student self-assessment should also be completed before the CCC meeting to improve trainees’ and CCC members’ understanding of the progress of their competency development and to ensure that trainees agree with and accept teachers’ feedback. During the CCC meeting, a structured decision-making procedure must be constructed for objective and credible decision-making. After the meeting, feedback should be provided to students to assist them in developing remedial learning plans or training assistance plans. A comprehensive group decision-making procedure should be carried out in CCC to improve the quality of clinical staff training, teaching, and medical services as well as the professional identity of clinical staff.</p> <p> </p>

Steering committee management. Expertise, diversity, and decision-making structures

This paper proposes to analyze how the differences in expertise, diversity, and group decision procedures affect the quality of the strategic decision of steering committees. Strategic decisions are difficult to anticipate, and performances of the alternatives are often not observable in their entirety, which prevent researchers from obtaining controlled empirical studies. This paper proposes to analyze the performance of steering committees where managers can err in their decisions using the Intentional Bounded Rationality (IBR). The majority procedure improves the committee's performance concerning authority when the level of diversity and expertise increases. However, in situations of low expertise, the gains over authority narrow. This work provides guidance in terms of trade-offs between the mentality of managers, their expertise, group decision procedures, and diversity, which in the empirical works are contradictory. This study contributes to current theorizations of committee management using the IBR methodology, which is new and allows quantifying the contribution of the distinct characteristics of the committee.

Importance of value analysis in domestic and international outlook

The value analysis is a well-known and widely used multi-criteria group decision-making procedure that not only looks for the cheapest, or not only the better, but also satisfies the desired and necessary needs at the lowest cost. Covering all important details of the project (product, service, procedure, process), the so-called multidisciplinary team of internal and/or external experts works together with the consultant. Value analysis identifies project functions and focuses on the most impactful intervention points. It then explores alternative solutions and creates optimal solutions for functions to cost-effectively satisfy and/or increase performance. Value analysis is now used by almost every large company in the world and is widespread in all industries. According to expert estimates, around 50,000 value analysis projects are carried out in Europe every year. Based on the provisions of the EN 12.973:2000 Value Management Standard in Hungary, the Public Procurement Act recommends the contracting authority require the tenderer to apply the method. This review paper reviews the process of the formation and development of value analysis, its fields of application in international comparison, the main methodological frameworks, its current challenges, and new opportunities.

Assessment of alternative railway systems for sustainable transportation using an integrated IRN SWARA and IRN CoCoSo model

The long-term sustainability of the railway transportation system is determined by a set of criteria that must be considered. For this reason, multi-criteria decision-making (MCDM) techniques have been used because of their high possibility of providing complementary instruments with successful flexibility. Keeping this in mind, we developed a multi-criteria method to conduct an assessment of currently operational railway systems in West Africa for sustainable transportation based on the examination of key challenges affecting the railway system. This study presents the interval rough step-wise weight assessment ratio analysis-combined compromise solution (IR-SWARA-CoCoSo) model. We have adapted the model to group decision-making by incorporating a new technique for dealing with ambiguity and the utilization of interval rough numbers (IRNs). To evaluate the importance coefficients of criteria in the group decision-making procedure, a new interval rough SWARA method has been introduced as an improvement to handle the issues related to MCDM. For the evaluation of the railway transportation system for sustainable transportation, a novel interval rough CoCoSo method was used. According to the findings, information systems is the most critical challenge to the railway transportation system, while the railway system in Nigeria is the best among others. The results were validated in two stages of sensitivity analysis: a comparison with different interval rough approaches, and the calculation of Spearman's correlation coefficient and WS coefficient for all ranks in the comparative analysis.

Performance Evaluation of Solar Energy Cells Using the Interval-Valued T-Spherical Fuzzy Bonferroni Mean Operators

To find the correspondence between every number of attributes, the Bonferroni mean (BM) operator is most widely used and proven to be a flexible approach. To express uncertain information, the frame of the interval-valued T-spherical fuzzy set (IVTSFS) is a recent development in fuzzy settings which discusses four aspects of uncertain information using closed sub-intervals of [0,1] and hence reduces the information loss greatly. In this research study, we introduced the principle of BM operators with IVTSFS to develop the principle of the inter-valued T-spherical fuzzy (IVTSF) BM (IVTSFBM) operator, the IVTSF-weighted BM (IVTSFWBM) operator, the IVTSF geometric BM (IVTSFGBM) operator, and the IVTSF-weighted geometric BM (IVTSFWGBM) operator. To see the significance of the proposed BM operators, we applied these BM operators to evaluate the performance of solar cells that play an important role in the field of energy storage. To do so, we developed a multi-attribute group decision-making (MAGDM) procedure based on IVTSF information and applied it to the problem of solar cells to evaluate their performance under uncertainty, where four aspects of opinion about solar cells were taken into consideration. We studied the results obtained using BM operators with some previous operators to see the significance of the proposed IVTSF BM operators.

Locations appraisal framework for floating photovoltaic power plants based on relative-entropy measure and improved hesitant fuzzy linguistic DEMATEL-PROMETHEE method

Floating photovoltaic power generation has received extensive attention for its advantages of saving land resources, proximity to urban load centers and high power generation efficiency. Reasonable site selection contributes to the sustainable development of floating photovoltaic power plants to select proper location(s), this paper constructs a multi-criteria group decision-making framework. Firstly, a comprehensive criteria system consisting of veto indicators and evaluation indicators is established. Then, the hesitant fuzzy linguistic term sets are adopted to describe the hesitancy of decision-makers and the uncertainty inherent in site selection problems. Thereafter, the group decision-making procedure is divided into two stages: group aggregation and alternative selection. In the first phase, a relative-entropy based similarity measure is defined to calculate the decision-makers’ weights. In the second phase, an improved hesitant fuzzy linguistic Decision Making Trial and Evaluation Laboratory - Preference Ranking Organization Methods for Enrichment Evaluation method is proposed to rank alternatives and characterize the psychological factors. Finally, the proposed framework is applied in a case study to certificate the feasibility. The calculation results illustrate that the ranking order may vary with the change of decision-makers’ risk attitudes. This research can effectively improve the site selection decision-making quality and also extend the methods and applications in the decision-making field.

So how to make group decisions? Arrow's impossibility theorem 70 years after

PurposeIn 1951, Kenneth Arrow proved that it is not possible to have a group decision-making procedure that satisfies reasonable requirements like fairness. From the theoretical viewpoint, this is a great result – well-deserving the Nobel Prize that was awarded to Professor Arrow. However, from the practical viewpoint, the question remains – so how should we make group decisions? A usual way to solve this problem is to provide some reasonable heuristic ideas, but the problem is that different seemingly reasonable idea often lead to different group decision – this is known, e.g. for different voting schemes.Design/methodology/approachIn this paper we analyze this problem from the viewpoint of decision theory, the basic theory underlying all our activities – including economic ones.FindingsWe show how from the first-principles decision theory, we can extract explicit recommendations for group decision making.Originality/valueMost of the resulting recommendations have been proposed earlier. The main novelty of this paper is that it provides a unified coherent narrative that leads from the fundamental first principles to practical recommendations.

Assessment and prioritization method of key engineering characteristics for complex products based on cloud rough numbers

Accurate assessment of engineering characteristics in the design phase is vital for complex products because it can effectively determine the orientation of subsequent design practice strategies. This assessment can be regarded as a multi-attribute group decision-making procedure comprising two parts: construction of engineering characteristic indicator system and identification of key engineering characteristics (KECs). Previous studies have provided many indicator systems to extract the KECs that affect the whole system significantly. However, they usually only consider a few factors and ignore the influence of low-dimension factors. In addition, the KEC identification usually is conducted based on the assessment of decision-makers, which involves intrapersonal judgment fuzziness and interpersonal consensus inconsistency. However, existing studies still have some limitations, such as only considering single intrapersonal or interpersonal vagueness, lacking the mechanism to manipulate various uncertainties simultaneously, and inadequate calculating the relative weights of experts and evaluation criteria, which may weaken the accuracy of final results. Therefore, this study develops an integrated assessment and prioritization method of engineering characteristics by constructing a comprehensive list of engineering characteristic indicators, developing the cloud rough number model that can simultaneously handle various uncertainties, and considering the objectively optimal weight of both experts and criteria. Additionally, a well-defined Excel computational program is also presented to reduce the calculation. Finally, a real case of KECs prioritization and a result comparison to the previous methods are presented to demonstrate its feasibility and effectiveness.

GROUP BEHAVIORAL BIASES AFFECT FINANCIAL DECISIONS UNLIKE INDIVIDUAL BEHAVIORAL BIASES

This work presents a new approach to behavioral finance with a theoretical contribution by suggesting and discussing with examples a list of group behavioral biases along with established individual behavioral biases, bringing, hence, an additional outlook on how behavioral biases affect financial decisions. While individual behavioral biases are detected in individuals acting alone, group behavioral biases require the scrutiny of group behavior. This awareness may be particularly important to institutional investors, whose decisions basically stem from a committee or a group that will exhibit behavioral biases depending on how the group members interact between themselves when making a decision, which may include negotiation activities and not necessarily be related to personality or hierarchy. The focus on individual investors deciding on personal investments explain the need of work already developed in behavioral finance, which focus on individual behavioral biases, which may be a consequence from either cognitive errors or emotional biases. However, decisions from institutional investors basically stem from a committee or a group that will exhibit behavioral biases depending on how the group members interact between themselves when making a decision. To address the challenge of identifying causes and consequences for unexpected or unsuitable financial decision-making within a group, this work initially retrieves previous work on individual behavioral biases, linking emotional biases and cognitive errors to the “system 1” and “system 2” decision-making framework. Then, a conceptual contribution of this paper, which may be particularly relevant for institutional investors, is to explain with examples - after research and experience - which are the group behavioral biases and their impact upon financial decisions. Individual behavioral biases already acknowledged in other works on behavioral finance are contrasted in this work to the suggested group behavioral biases. Furthermore, this work suggests that there are two broad types of group behavioral biases: group dynamics biases and information-acceptance biases. Each broad type is subdivided into biases related to the structure of the group and biases related to how the group decision-making procedure occurs. Group dynamics biases related to the manner the group is structured are the following: kin bias (belonging bias), harmony bias, and competition bias. On the other hand, group dynamics biases may be sorted according to five different decision-making procedures, namely: herding, fad bias, Plato bias (denial bias), scarcity bias, and home bias.

A new approach to cubic q-rung orthopair fuzzy multiple attribute group decision-making based on power Muirhead mean

The q-rung orthopair fuzzy sets (q-ROFSs) have been proved to be an efficient tool in expressing decision makers’ (DMs) evaluation values in multiple attribute group decision-making (MAGDM) procedure. To more effectively represent DMs’ evaluation information in complicated MAGDM process, this paper proposes a new tool, called cubic q-rung orthopair fuzzy sets (Cq-ROFSs), based on the combination of q-ROFSs with interval-valued q-ROFSs. Then, we investigate MAGDM problems in which DMs’ preference information is given in terms of cubic q-rung orthopair fuzzy numbers. First, the definition, operations and comparison method of Cq-ROFSs are introduced. Second, to effectively aggregate cubic q-rung orthopair fuzzy information we propose the cubic q-rung orthopair fuzzy power average operator, the cubic q-rung orthopair fuzzy power Muirhead mean operator as well as their weighted forms. We illustrate the powerfulness and flexibility of the proposed operators in fusing cubic q-rung orthopair fuzzy decision-making information. Third, on the basis of the proposed operators we give the main steps of a novel cubic q-rung orthopair fuzzy MAGDM method. We utilize the method to solve real MAGDM problems to prove its effectiveness and validity. Finally, we explain why DMs should choose our proposed method rather than some others through comparison analysis.

A comparative study for consistency-based decision making with interval multiplicative preference relations

ABSTRACTTo ensure the reasonable application and perfect the theory of decision making with interval multiplicative preference relations (IMPRs), this paper continues to discuss decision making with IMPRs. After reviewing previous consistency concepts for IMPRs, we find that Krejčí’s consistency concept is more flexible and natural than others. However, it is insufficient to address IMPRs only using this concept. Considering this fact, this paper researches inconsistent and incomplete IMPRs that are usually encountered. First, programming models for addressing inconsistent and incomplete IMPRs are constructed. Then, this paper studies the consensus of individual IMPRs and defines a consensus index using the defined correlation coefficient. When the consensus requirement does not satisfy requirement, a programming model for improving consensus level is built, which can ensure the consistency. Subsequently, a procedure for group decision making with IMPRs is offered, and associated examples are provided to specifically show the application of main theoretical results.

Group-decision making with induced ordered weighted logarithmic aggregation operators

This paper presents the induced generalized ordered weighted logarithmic aggregation (IGOWLA) operator, this operator is an extension of the generalized ordered weighted logarithmic aggregation (GOWLA) operator. It uses order-induced variables that modify the reordering process of the arguments included in the aggregation. The principal advantage of the introduced induced mechanism is the consideration of highly complex attitude from the decision makers. We study some families of the IGOWLA operator as measures for the characterization of the weighting vector. This paper presents the general formulation of the operator and some special cases, including the induced ordered weighted logarithmic geometric averaging (IOWLGA) operator and the induced ordered weighted logarithmic aggregation (IOWLA). Further generalizations using quasi-arithmetic mean are also proposed. Finally, an illustrative example of a group decision-making procedure using a multi-person analysis and the IGOWLA operator in the area of innovation management is analyzed.

Aggregation of pragmatic operators to support probabilistic linguistic multi-criteria group decision-making problems

In this paper, a multi-attribute group decision-making method based on aggregation operators is presented to solve the decision-making problems which the evaluation values take the form of probabilistic linguistic terms sets (PLTSs). Firstly, some properties of the PLTS are defined, such as the concept and the linguistic terms transformation function, the existing comparison methods and the proposed score function and distance. Secondly, some novel operators are proposed by combining the Heronian mean operator with the centered OWA operator and the power average operator under probabilistic linguistic environment, such as the probabilistic linguistic weighted centered order weighted generalized Heronian mean operator and the probabilistic linguistic weighted power generalized Heronian mean operator. Thirdly, the model of deriving the criteria weight is put forward based on the ideology of deviation maximizing and customized individual attitudinal. Furthermore, based on the proposed aggregation operators and EDAS method, a scientific group decision-making procedure is put forward under probabilistic linguistic environment. Finally, an illustrative example is also given to demonstrate the feasibility and practicality of the proposed method.

Uncertain multi-attribute group decision making based on linguistic-valued intuitionistic fuzzy preference relations

The preference relations have shown some advantages in handling multi-attribute group decision making problems, which can assist decision makers to set priorities and make a reasonable decision. In real-life situations, decision makers sometimes express their preference with fuzzy and uncertain linguistic information including positive and negative sides at the same time. In order to deal with the decision-making problems with uncertain linguistic information, we propose an approach for uncertain multi-attribute group decision making based on linguistic-valued intuitionistic fuzzy preference relations (LIFPR). The presented LIFPR based on linguistic truth-valued intuitionistic fuzzy lattice can better express positive and negative evaluation information in the meanwhile. To aggregate linguistic information and reduce information loss of aggregation process, we propose linguistic-valued intuitionistic fuzzy 2-tuple representation model (LIF 2-tuple) and two kinds of linguistic-valued intuitionistic fuzzy aggregation operators. To deal with incomparable LIF 2-tuples, we present positive and negative LIF 2-tuple reference nearness degrees according to preferences. For the inconsistent LIFPR caused by subjective uncertainty, a consistency checking algorithm based on linguistic-valued intuitionistic fuzzy similarity is introduced to check and repair the consistency of a LIFPR. For the incomplete LIFPR caused by objective uncertainty, an improved LIFPR based on additive transitivity is presented to complement the LIFPR. We discuss the procedure of group decision making based on LIFPR with positive and negative evaluation information. An illustrate example shows the proposed approach for group decision making seems more effective for decision making under an uncertain linguistic environment.

A procedure for group decision making with interval-valued intuitionistic linguistic fuzzy preference relations

To express the uncertain preferred and non-preferred qualitative judgments of decision makers, interval-valued intuitionistic linguistic fuzzy sets (IVILFSs) are proposed in a similar way as Atanassov and Gargov’s interval-valued intuitionistic fuzzy sets. Considering the application of IVILFSs, the concept of interval-valued intuitionistic linguistic fuzzy variables (IVILFVs) is defined and a ranking order is offered. Then, we introduce interval-valued intuitionistic linguistic fuzzy preference relations (IVILFPRs) whose elements are IVILFVs. Furthermore, an additive consistency concept is presented and a model for judging the consistency of IVILFPRs is built. Meanwhile, optimization models for deriving additively consistent IVILFPRs and for determining missing linguistic variables in incomplete IVILFPRs are constructed, respectively. For group decision making, optimization models for determining the weights of the decision makers and for improving the consensus level are established, respectively. A procedure for group decision making with IVILFPRs is developed that can cope with inconsistent and incomplete IVILFPRs. Finally, a practical group decision-making problem about evaluating express companies is selected to show the application of the new results.

Group decision making based on DEA cross-efficiency with intuitionistic fuzzy preference relations

The aim of this paper is to investigate a novel approach to group decision making based on DEA cross-efficiency with intuitionistic fuzzy preference relations, which can avoid information distortion and obtain more credible decision making results. An interval transform function is defined, which can transform an intuitionistic fuzzy preference relation into an interval multiplicative preference relation. Then, an interval transform function based data envelopment analysis model is developed to obtain the ranking vector of consistent intuitionistic fuzzy preference relation, in which each of the alternatives is viewed as a decision making unit. Moreover, for any intuitionistic fuzzy preference relations, we propose two DEA cross-efficiency models to get the cross-efficiency values of all alternatives, and we can calculate the normalized intuitionistic fuzzy priority weight vector of the intuitionistic fuzzy preference relation based on the cross-efficiency values. A goal programming model is investigated to derive the weight vector of decision makers. A step-by-step procedure for group decision making approach based on DEA cross-efficiency with intuitionistic fuzzy preference relations is presented. Finally, numerical examples are given to illustrate the validity and applicability of the proposed method. This is the first attempt of employing the DEA cross-efficiency to the group decision making with intuitionistic fuzzy preference relations.

Second-Guessing in Group Decision Making

While numerous studies have demonstrated the difficulty minority opinion holders face when trying to persuade a majority, the present research investigated the conditions under which minority members might second-guess themselves and become advocates for the majority’s position even when they have the best information. In a laboratory experiment, we examined whether the structure of monetary incentives (fixed amount vs. performance-based) and group decision-making procedure (collective decisions vs. group discussion then individual decisions) might mitigate second-guessing by minority members when they initially favor the objectively best choice. Our results indicated that compared with fixed-amount incentives, performance-based incentives increased overall information sharing in collective decision-making groups but not in individual decision-making groups. Second-guessing by minority members was most likely to occur in groups that received performance-based incentives and made decisions individually. As a result of second-guessing, these groups also made poorer decisions.

Two regression methods for hesitant multiplicative preference relations with different consistencies

Multiplicative preference relation (MPR) is an efficient and widely used tool in describing the preferences of decision makers. The hesitant multiplicative preference relation (HMPR), as an extension of the MPR, is commonly used in collecting and representing all hesitant preferences and judgements of the decision makers. Considering that there usually appear some random or illogical preference degrees in the process of constructing the HMPRs, so it is necessary to derive a pithy preference relation (such as MPR) from the original HMPR through selecting the most proper and abandoning improper preference degrees, at the same time, the derived MPR is with the advantage of both terseness and the best consistency. Based on the multiplicative consistency measure of HMPRs, this paper proposes two regression methods to transform the HMPR into MPRs (called reduced MPRs). With the error analysis, the first proposed regression method provides some steps to not only extract the reduced MPRs from original HMPR but also calculate the consistencies of both the HMPR and the reduced MPRs. A case study reflects that the reduced MPR is with the highest consistency degree among those possible separated MPRs from HMPR. To apply this method to solve practical problems conveniently, a group decision-making procedure with hesitant multiplicative information is further given based on the first regression method. Time complexity comparison between our proposed method and an existing method indicates the effectiveness of our method. In addition, according to the weak consistency, we develop the second regression method and design an algorithm to obtain the reduced MPRs from the HMPR. Furthermore, we provide a method to check the weak consistency of the HMPR and repair the inconsistent one. Numerical examples verify that the second regression method proposed in this paper is an effective technique for checking the weak consistency and modifying the inconsistency HMPR to the one with weak consistency.