Hesitancy In Decision Research Articles

A circular intuitionistic fuzzy evaluation method based on distances from the average solution to support multiple criteria intelligent decisions involving uncertainty

This study aims to construct an evaluation method based on distances from the average solution (EDAS) based on circular intuitionistic fuzzy (C-IF) sets to support intelligent decision-making involving multiple criteria and intricate uncertainty. C-IF sets possess a resilient circular structure that can model decision-makers’ hesitancy and indecision like intuitionistic fuzzy sets and can add ambiguity to fuzzy membership and nonmembership functions like type-2 fuzzy sets. Related to the existing literature on EDAS in uncertain environments, a new interpretation is needed so that the decision assistance procedure can exploit higher-order fuzzy membership functions as well as in type-2 fuzzy settings, and can address decision hesitancy as well as in IF settings. However, EDAS has not been studied to discuss its applicability in C-IF circumstances and make headway a suitable extension model, which forms a research question worth exploring. To address this issue, this study endeavors to construct a C-IF EDAS methodology and propound novel concepts and measurements that can improve the core techniques of traditional EDAS, enabling them to handle complicated C-IF information and treat highly equivocal and indistinct decision-making tasks. The C-IF analytical procedure for decision-making is mainly built upon two representations from semantic assessments, namely C-IF assessment ratings and C-IF importance weights. This study puts forth the concept of aggressive and conservative estimates to identify anchored datum-based measurements that provide new interpretations of positive distance and negative distance concerning the C-IF average solution; besides this study evolves an extended EDAS decision rule in C-IF circumstances. Based on an aggregated operation and a membership score function, anchored datum-based (normalized) weighted sums about positive/negative distances can be rendered to produce a joint appraisal score for a compromise ranking of available alternatives. To corroborate the applicability of the established notions and measurements, this study utilizes the C-IF EDAS model and decision procedure to tackle a realistic site selection issue for a pandemic hospital within C-IF environments. The suitability, robustness, and flexibility of the developed C-IF EDAS methodology are confirmed through some comparative analyses and experimental studies. First, this study verifies the correctness and trustworthiness of the executive outcomes from the viewpoints of membership, nonmembership, and vague score functions. Next, this study confirms the effectuality and rationality of the proposed C-IF EDAS by comprehensive comparison with several related methods. Furthermore, this study suggests a flexible way of setting appraisal and distance parameters in the C-IF EDAS to facilitate intelligent decision-making in reality. Finally, some conclusive discussions of the C-IF EDAS solution are systematically investigated to reveal its practicality and application merits in the realm of multiple criteria decision analysis with information uncertainty; it is also confirmed that the C-IF set is well suited as a fundamental of problem modeling within complex decision-making environments.

Tackling Comprehensive Evaluation of Tourism Community Resilience: A Probabilistic Hesitant Linguistic Group Decision Making Approach

Community-based tourism (CBT) has been adopted as an effective and practical solution to land use policies by governments that simultaneously pursue upgrading of local economy, conservation of local ecosystem and development of local communities. Confronting with new normality of detrimental eventualities in situated environments, destination management organizations (DMOs) or local governments have to employ effective governance strategies for fostering tourism community resilience in order to sustain development of CBT destinations. In viewing of that facilitating development through evaluation usually manifests as an efficient strategy in governance practices, this paper contributes to fill two main gaps in tackling comprehensive evaluation of tourism community resilience. Firstly, by noticing the fact that current literature overlooks processual characteristics of tourism community resilience, which originate from integration of disaster management and destination management (DM2), we have developed an analytical framework comprised of six attributes for comprehensively evaluating tourism community resilience. Secondly, aiming at the phenomena that cognitive assessments on attributes of tourism community resilience often exhibit complicate uncertainties caused by low-structured or ill-structured problem nature, we have put forward a powerful expression tool of probabilistic dual hesitant fuzzy uncertain unbalanced linguistic set (PDHF_UUBLS) to simultaneously capture evaluators’ cognitive characteristics of decision hesitancy, bipolar epistemic notions and relative importance among assessments. Then by formalizing comprehensive evaluation of tourism community resilience as a multiple attributes decision making process, we construct an effective multiple attributes group decision making (MAGDM) approach with assessments in the form of PDHF_UUBLS. Theoretical analyses verify the effectiveness of our constructed MAGDM approach and also show the approach avoids potential information distortion in comparison with other approaches. Overall, this paper provides effective and pertinent solutions, with both analytical framework and methodology, to the urgent task of comprehensive evaluation of tourism community resilience in DM2 agenda, thereby is of apparent significance in governance practice of CBT.

Uncertainty in Building Inspection and Diagnosis: A Probabilistic Model Quantification

In the field of building inspection and diagnosis, uncertainty is common and surveyors are aware of it, although it is not easily measured. This research proposes a model to quantify uncertainty based on the inspection of rendered façades. A Bayesian network is developed, considering three levels of variables: characteristics of the building, façade and exposure conditions; causes of defects; and defects. To compute conditional probabilities, the results of an inspection campaign from the literature are used. Then, the proposed model is validated and verified using inspection results from another sample, the combination of a strength-of-influence diagram and sensitivity analysis and the application of the model to a case study. Results show that the probabilities computed by the model are a reasonable representation of the hesitancy in decision making during the diagnosis process based only on visual observation. For instance, design and execution errors show lower probabilities due to not being verifiable a posteriori without detailed documentation. The proposed model may be extended and replicated for other building materials in the future, as it may be a useful tool to improve the perception of uncertainty in a key stage of building maintenance or rehabilitation.

Probabilistic Hybrid Linguistic Approaches for Multiple Attribute Group Decision Making with Decision Hesitancy and the Prioritization of Attribute Relationships

Focusing on ill-structured multiple attribute decision-making (MADM) problems, including decision hesitancy and attribute prioritization relationships, this paper investigates appropriate approaches for decision making. Firstly, we introduce the probabilistic hybrid linguistic term set (P-HLTS) for capturing probabilistic preferences about possible linguistic labels belonging to a wide range of hesitant linguistic term sets. Entropy and distance measurements for P-HLTS are developed without arbitrary complementing operations. To facilitate decision making with attribute prioritization relationships, we present a probabilistic uncertain balanced linguistic-prioritized weighted average (PUBL-PWA) operator and the probabilistic uncertain balanced linguistic-induced prioritized ordered weighted average (PUBL-IPOWA) operator. In terms of the strength of the above tools, we further construct two multiple attribute group decision-making (MAGDM) approaches under P-HLTS environments, namely, an approach for decision-making situations where attribute prioritization relationships are known in advance and the relative importance of decision makers (DMs) or decision-making units (DMUs) is not required for consideration, and second approach for decision-making situations where both attribute prioritization relationships and the weighted vectors of DMs or DMUs are explicitly unknown. In general, our proposed approaches are more flexible and practical when considering heterogeneous opinions, avoiding information distortion brought about by complementing operation-based distance measures. Furthermore, illustrative application studies are conducted to verify our developed approaches.

A New Decision Making Approach for Supplier Selection: Hesitant Fuzzy Axiomatic Design

This paper deals with the hesitancy in decision making. Since the decision makers generally doubt to evaluate the alternatives and the criteria in hesitant situations, the existing methods do not satisfy them. Therefore, hesitant versions of Fuzzy-AHP (HF-AHP) and Fuzzy Axiomatic Design (HF-AD) are introduced in this paper. HF-AHP lets the decision makers to use hesitant fuzzy linguistic terms while performing the pairwise comparisons when they are indecisive. HF-AD is used to define the system and design ranges of the items in a hesitant situation. In addition, a case study is revealed as a numerical example in which the best supplier is selected among six alternatives regarding five criteria. In that case study, both weighted and unweighted versions of HF-AD are used. In the weighted version, HF-AHP is used to determine the weights of the criteria. Furthermore, sensitivity analysis is performed to check the robustness of the decision. Moreover, these proposed techniques are compared with non-hesitant versions. According to the results, the decision makers feel more confident with the hesitant versions. Hence, the primary contributions of this study are to develop HF-AD and HF-AHP which are helpful for the decision makers to express their preferences in hesitant situations.

Multiple Attributes Group Decision-Making under Interval-Valued Dual Hesitant Fuzzy Unbalanced Linguistic Environment with Prioritized Attributes and Unknown Decision-Makers’ Weights

Aiming at a special type of ill-defined complicate multiple attributes group decision-making (MAGDM) problem, which exhibits hybrid complexity features of decision hesitancy, prioritized evaluative attributes, and unknown decision-makers’ weights, we investigate an effective approach in this paper. To accommodate decision hesitancy, we employ a compound expression tool of interval-valued dual hesitant fuzzy unbalanced linguistic set (IVDHFUBLS) to help decision-makers elicit their assessments more comprehensively and completely. To exploit prioritization relations among evaluating attributes, we develop a prioritized weighted aggregation operator for IVDHFUBLS-based decision-making scenarios and then analyze its properties and special cases. To objectively derive unknown decision-makers’ weighting vector, we next develop a hybrid model that simultaneously takes into account the overall accuracy measure of the individual decision matrix and maximizing deviation among all decision matrices. Furthermore, on the strength of the above methods, we construct an MAGDM approach and demonstrate its practicality and effectiveness using applied study on a green supplier selection problem.

Multiple Attributes Group Decision-Making Approaches Based on Interval-Valued Dual Hesitant Fuzzy Unbalanced Linguistic Set and Their Applications

Aiming at multiple attributes group decision-making (MAGDM) problems that characterize uncertainty nature and decision hesitancy, firstly, we propose the interval-valued dual hesitant fuzzy unbalanced linguistic set (IVDHFUBLS) in which two sets of interval-valued hesitant fuzzy membership degrees and nonmembership degrees are employed to supplement the most preferred unbalanced linguistic term, as an effective hybrid expression tool to elicit complicate preferences of decision-makers more comprehensively and flexibly than existing tools based on classic linguistic term set. Basic operations for IVDHFUBLS are further defined; also a novel distance measure is developed to avoid potential information distortion that could be brought about by traditional complementing methodology for hesitant fuzzy set and its derivatives. In view of the fundamental role of aggregation operators in MAGDM modelling, we next develop some extended power aggregation operators for IVDHFUBLS, including power aggregation operator, weighted power aggregation operator, and induced power ordered weighted aggregation operator; their desirable properties and special cases are also analyzed theoretically. Subsequently, with support of the above methods, we develop two effective approaches for our targeted complex decision-making problems and verify their effectiveness and practicality by numerical studies.

Tackling Complexity in Green Contractor Selection for Mega Infrastructure Projects: A Hesitant Fuzzy Linguistic MADM Approach with considering Group Attitudinal Character and Attributes’ Interdependency

Continuous environmental concerns regarding construction industry have been driving general constructors of mega infrastructure projects to incorporate green contractors. Although conventional multiple attributes decision‐making (MADM) methodologies have provided feasible ways to select contractor, high complexity in scenarios of megaprojects still challenges existing MADM methods in concurrently accommodating three key issues of decision hesitancy, attributes interdependency, and group attitudinal character. To elicit decision‐makers’ hesitant fuzzy assessments more objectively and comprehensively, we define an expression tool called interval‐valued dual hesitant fuzzy uncertain unbalanced linguistic set (IVDHF_UUBLS) and develop aggregation operators through its operations. To exploit attributes interdependency, we establish a synthesized attributes’ weighting model to fuse an attributes interdependency‐based weighting vector and an argument‐dependent weighting vector, which are, respectively, derived through Decision‐Making and Trial Evaluation Laboratory (DEMATEL) technique and maximizing deviation method. To effectively utilize decision‐makers’ group attitudinal characters, we also develop a TOPSIS‐based method to rationally transform group ideal attitudes into order‐inducing vectors. On the strength of the above methods, an integrated MADM approach is then constructed. Finally, illustrative case study and experiments are conducted to validate our approach.

Tackling Complex Emergency Response Solutions Evaluation Problems in Sustainable Development by Fuzzy Group Decision Making Approaches with Considering Decision Hesitancy and Prioritization among Assessing Criteria

In order to be prepared against potential balance-breaking risks affecting economic development, more and more countries have recognized emergency response solutions evaluation (ERSE) as an indispensable activity in their governance of sustainable development. Traditional multiple criteria group decision making (MCGDM) approaches to ERSE have been facing simultaneous challenging characteristics of decision hesitancy and prioritization relations among assessing criteria, due to the complexity in practical ERSE problems. Therefore, aiming at the special type of ERSE problems that hold the two characteristics, we investigate effective MCGDM approaches by hiring interval-valued dual hesitant fuzzy set (IVDHFS) to comprehensively depict decision hesitancy. To exploit decision information embedded in prioritization relations among criteria, we firstly define an fuzzy entropy measure for IVDHFS so that its derivative decision models can avoid potential information distortion in models based on classic IVDHFS distance measures with subjective supplementing mechanism; further, based on defined entropy measure, we develop two fundamental prioritized operators for IVDHFS by extending Yager’s prioritized operators. Furthermore, on the strength of above methods, we construct two hesitant fuzzy MCGDM approaches to tackle complex scenarios with or without known weights for decision makers, respectively. Finally, case studies have been conducted to show effectiveness and practicality of our proposed approaches.

The Symptoms of Postpartum Depression in Fathers in the City of Elbasan

This study makes an exploration of Postpartum Depression symptoms of fathers in the city of Elbasan. The aim of this study is the recognition of the existence of Postpartum Depression in fathers identifying them in the picture of the symptoms. The study sample consisted of 40 fathers who had a maximum of a year that became parents, with a stable job and the average educational level of formation. Sample selection was carried out in public kindergartens number 1 (one) and 2 (two) in the city of Elbasan. For the methodology of this study are used quantitative methods. The collection of data for this study was conducted in a period of about four months, during the months of February, March, April, May, 2015. The instruments used in this study are the Beck Depression Inventory, Postpartum Depression Scale Edingurgh. Beck Depression Inventory and Edingurgh rate were used as tools because both measure Postpartum Depression Depression and that has the same picture symptoms episode of major depression with the only change the time of development. Instruments that are used to obtain the data necessary to test hypotheses raised in this study were initially piloted before applying them in the final stage. Results of this study showed that 85% of fathers taken in the study showed symptoms of postpartum depression as dissatisfaction with the activities, criticism of themselves, concern / irritability, changes in sleep, lack of interest in people / activities, lack of energy, fatigue, hesitancy in decision making, feelings of guilt, difficulty concentrating, pessimism, frustration, failures of the past, sorrow. The study suggests that measures should be taken for public awareness of the symptoms of postpartum depression are present and in fathers and the Postpartum Depression is not attributed only to women.

The Symptoms of Postpartum Depression in Fathers in the City of Elbasan

This study makes an exploration of Postpartum Depression symptoms of fathers in the city of Elbasan. The aim of this study is the recognition of the existence of Postpartum Depression in fathers identifying them in the picture of the symptoms. The study sample consisted of 40 fathers who had a maximum of a year that became parents, with a stable job and the average educational level of formation. Sample selection was carried out in public kindergartens number 1 (one) and 2 (two) in the city of Elbasan. For the methodology of this study are used quantitative methods. The collection of data for this study was conducted in a period of about four months, during the months of February, March, April, May, 2015. The instruments used in this study are the Beck Depression Inventory, Postpartum Depression Scale Edingurgh. Beck Depression Inventory and Edingurgh rate were used as tools because both measure Postpartum Depression Depression and that has the same picture symptoms episode of major depression with the only change the time of development. Instruments that are used to obtain the data necessary to test hypotheses raised in this study were initially piloted before applying them in the final stage. Results of this study showed that 85% of fathers taken in the study showed symptoms of postpartum depression as dissatisfaction with the activities, criticism of themselves, concern / irritability, changes in sleep, lack of interest in people / activities, lack of energy, fatigue, hesitancy in decision making, feelings of guilt, difficulty concentrating, pessimism, frustration, failures of the past, sorrow. The study suggests that measures should be taken for public awareness of the symptoms of postpartum depression are present and in fathers and the Postpartum Depression is not attributed only to women.

Evaluating Emergency Response Solutions for Sustainable Community Development by Using Fuzzy Multi-Criteria Group Decision Making Approaches: IVDHF-TOPSIS and IVDHF-VIKOR

Emergency management is vital in implementing sustainable community development, for which community planning must include emergency response solutions to potential natural and manmade hazards. To help maintain such solution repository, we investigate effective fuzzy multi-criteria group decision making (FMCGDM) approaches for the complex problems of evaluating alternative emergency response solutions, where weights for decision makers and criteria are unknown due to problem complexity. We employ interval-valued dual hesitant fuzzy (IVDHF) set to address decision hesitancy more effectively. Based on IVDHF assessments, we develop a deviation maximizing model to compute criteria weights and another compatibility maximizing model to calculate weights for decision makers. Then, two ideal-solution-based FMCGDM approaches are proposed: (i) by introducing a synthesized IVDHF group decision matrix into TOPSIS, we develop an IVDHF-TOPSIS approach for fuzzy group settings; (ii) when emphasizing both maximum group utility and minimum individual regret, we extend VIKOR to develop an IVDHF-VIKOR approach, where the derived decision makers’ weights are utilized to obtain group decision matrix and the determined criteria weights are integrated to reflect the relative importance of distances from the compromised ideal solution. Compared with aggregation-operators-based approach, IVDHF-TOPSIS and IVDHF-VIKOR can alleviate information loss and computational complexity. Numerical examples have validated the effectiveness of the proposed approaches.

Operations on hesitant fuzzy sets: Some new results

Hesitant fuzzy sets, introduced by Torra and Narukawa [10] present a powerful tool for study of hesitancy in decision making. The main strength of this generalization will be realized by studying the properties and the operations that can be defined on hesitant fuzzy sets. This paper presents a number of properties in the light of operations defined by Torra [11] and Xia and Xu [13] on hesitant fuzzy sets.

An Accurate Method for Determining Hesitant Fuzzy Aggregation Operator Weights and Its Application to Project Investment

As a generalization of fuzzy sets, hesitant fuzzy set is a very useful technique to represent decision makers' hesitancy in decision making. Various hesitant fuzzy weighted operators have been developed to aggregate hesitant fuzzy information, but it seems that there is no investigation on the weighted approach of obtaining their weights, which is decisive for the calculation and comparison of hesitant fuzzy elements HFEs in multicriteria group decision making. In this paper, we propose an accurate weighted method AWM of monotonicity and proportionality, based on nothing but the score function and the new deviation function. Because of the above properties, AWM may be an accurate and objective technique to calculate the weights of HFEs and aggregation operator. Then, based on this weighted approach, we develop two new hesitant fuzzy ordered weighted aggregation operators, that is, hesitant fuzzy ordered accurate weighted averaging and hesitant fuzzy ordered accurate weighted geometric operators, and study their relationships and properties. In the end, an illustrative project investment problem is used to demonstrate how to apply the proposed weighted approach and to observe the computational consequences resulting from new aggregation operators. This work contributes significantly to improve the hesitant fuzzy theory, and proposes two new hesitant fuzzy aggregation operators.

Conscious processing of sexual information: interference caused by sexual primes.

The concept Sexual Content-Induced Delay (SCID) refers to a hesitancy in decision making related to erotic material (Geer & Bellard, 1996; Geer & Melton, 1997). Empirical evidence about SCID stems from lexical decision tasks. Our previous studies also showed SCID effects in sex versus neutral categorization tasks in which pictures were used. In these tasks, recognition of sexual pictures is delayed when preceded by consciously presented sexual primes. In the current study, 2 manipulations were added to the categorization task to investigate underlying information processing mechanisms of SCID. Firstly, the appraisal process was influenced by varying the instructions. Secondly, primes with nonsexual emotional content were added to test the specificity of the SCID effect. Thirty-seven undergraduates were asked to categorize sexual and neutral pictures that were primed by sexual, threatening, and neutral primes. Participants ignored or focussed prime content dependent on 2 different instructions. Results showed that the SCID effect only emerged when sexual primes were ignored; however, threatening primes also decelerated recognition of sexual pictures after the ignore instruction. Results of the focus instruction were qualitatively different, that is, participants recognized sexual pictures faster when primed sexually. It was suggested that SCID can be interpreted as the activation of regulatory modules by emotional stimuli in the stage of elicitation of emotional response. In contrast, when the sexual system is already activated, it appears that decisions regarding sexual information are facilitated.