In this paper, the sine, cosine and cotangent similarity measures of interval rough neutrosophic sets is proposed. Some properties of the proposed measures are discussed. We have proposed multi attribute decision making approaches based on proposed similarity measures. To demonstrate the applicability, a numerical example is solved.

In this paper, we define projection and bidirectional projection measures between interval rough neutrosophic sets and prove their basic properties. Then two new multi attribute decision making strategies are proposed based on interval rough neutrosophic projection and bidirectional projection measures respectively. Then the proposed methods are applied for solving multi attribute decision making problems. Finally, a numerical example is solved to show the feasibility, applicability and effectiveness of the proposed strategies.

The purpose of this study is to propose new similarity measures namely rough variational coefficient similarity measure under the rough neutrosophic environment. The weighted rough variational coefficient similarity measure has been also defined. The weighted rough variational coefficient similarity measures between the rough ideal alternative and each alternative are xxxxx calculated to find the best alternative. The ranking order of all the alternatives can be determined by using the numerical values of similarity measures. Finally, an illustrative example has been provided (...) to show the effectiveness and validity of the proposed approach. Comparisons of decision results of existing rough similarity measures have been provided. (shrink)

In this paper, multi attribute decision making problem based on grey relational analysis in neutrosophic cubic set environment is investigated. In the decision making situation, the attribute weights are considered as single valued neutrosophic sets. The neutrosophic weights are converted into crisp weights. Both positve and negative GRA coefficients, and weighted GRA coefficients are determined. Hamming distances for weighted GRA coefficients and standard (ideal) GRA coefficients are determined. The relative closeness coefficients are derived (...) in order to rank the alternatives. The relative closeness coefficients are designed in ascending order. Finally, a numerical example is solved to demonstrate the applicability of the proposed approach. (shrink)

The paper proposes a new technique for dealing with multi-attribute decision making problems through an extended TOPSIS method under neutrosophic cubic environment. Neutrosophic cubic set is the generalized form of cubic set and is the hybridization of a neutrosophic set with an interval neutrosophic set. In this study, we have defined some operation rules for neutrosophic cubic sets and proposed the Euclidean distance between neutrosophic cubic sets. In the decision making situation, the rating of (...) alternatives with respect to some predefined attributes are presented in terms of neutrosophic cubic information where weights of the attributes are completely unknown. In the selection process, neutrosophic cubic positive and negative ideal solutions have been defined. An extended TOPSIS method is then proposed for ranking the alternatives and finally choosing the best one. Lastly, an illustrative example is solved to demonstrate the decision making procedure and effectiveness of the developed approach. (shrink)

Interval bipolar neutrosophic set is a significant extension of interval neutrosophic set where every element of the set comprises of three independent positive membership functions and three independent negative membership functions. In this study, we first define correlation coefficient, and weighted correlation coefficient measures of interval bipolar neutrosophic sets and prove their basic properties. Then, we develop a new multi-attribute decision making strategy based on the proposed weighted correlation coefficient measure. Finally, we solve an investment problem (...) with interval bipolar neutrosophic information and comparison is given to demonstrate the applicability and effectiveness of the proposed strategy. (shrink)

Bipolar neutrosophic sets are the extension of neutrosophic sets and are based on the idea of positive and negative preferences of information. Projection measure is a useful apparatus for modelling real life decision making problems. In the paper, we define projection, bidirectional projection and hybrid projection measures between bipolar neutrosophic sets. Three new methods based on the proposed projection measures are developed for solving multi-attribute decision making problems. In the solution process, the ratings of (...) performance values of the alternatives with respect to the attributes are expressed in terms of bipolar neutrosophic values. We calculate projection, bidirectional projection, and hybrid projection measures between each alternative and ideal alternative with bipolar neutrosophic information. All the alternatives are ranked to identify the best alternative. Finally, a numerical example is provided to demonstrate the applicability and effectiveness of the developed methods. Comparison analysis with the existing methods in the literature in bipolar neutrosophic environment is also performed. (shrink)

One of the interesting research questions in multi-attribute decision-making is what affects the consideration of shared information between two alternatives. Previous studies have suggested two approaches in finding what characteristics of common features affect their consideration. Two bottom-up factors were found, but no top-down factors were discovered. In the current study, we followed the top-down approach and investigated how subjective importance of a common feature affects its consideration. In two studies, we consistently found that, on both (...) the general and individual level, the level of consideration increased with the SI of the common feature. This result provided a new explanation for the effect of common feature consideration and its individual difference; it also provided insights in explaining the underlying process of multi-attribute decision making. (shrink)

In this paper, we define correlation coefficient measure between any two rough neutrosophic sets. We also prove some of its basic properties.. We develop a new multiple attribute group decision making method based on the proposed correlation coefficient measure. An illustrative example of medical diagnosis is solved to demonstrate the applicability and effecriveness of the proposed method.

Unconscious thought theory (UTT) states that all information is taken into account and the attributes are weighted optimally resulting in better decisions in complex decision problems during unconscious thought. Very few studies have investigated the actual amount of information processed in the unconscious thought condition. We hypothesized that only a small subset of information might be considered during unconscious thought (like conscious thought). To test this possibility and to explore the way attribute information is selected and combined, we (...) performed computer simulations on the datasets used by previous researchers. The simulations showed that considering a small subset (3-4) of attributes, yields results comparable to previous studies. There is no need to posit infinite capacity in the unconscious thought condition. The results also suggest that weight information is used for attribute selection that could potentially explain the difficulties in replicating the deliberation-without-attention effect. (shrink)

This paper is devoted to present Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method for multi-attribute group decision making under rough neutrosophic environment. The concept of rough neutrosophic set is a powerful mathematical tool to deal with uncertainty, indeterminacy and inconsistency. In this paper, a new approach for multi-attribute group decision making problems is proposed by extending the TOPSIS method under rough neutrosophic environment. Rough neutrosophic set is characterized by (...) the upper and lower approximation operators and the pair of neutrosophic sets that are characterized by truth-membership degree, indeterminacy membership degree, and falsity membership degree. In the decision situation, ratings of alternatives with respect to each attribute are characterized by rough neutrosophic sets that reflect the decision makers’ opinion. Rough neutrosophic weighted averaging operator has been used to aggregate the individual decision maker’s opinion into group opinion for rating the importance of attributes and alternatives. Finally, a numerical example has been provided to demonstrate the applicability and effectiveness of the proposed approach. (shrink)

Trapezoidal interval type-2 fuzzy sets are a special kind of type-2 fuzzy sets. TIT2FSs are useful in dealing with fuzziness inherent in decision data and the decision-making process. For multi-attribute group decision-making problems in which the attribute values and attribute weights are TIT2FSs, a new decision-making approach is proposed. On the basis of the concept of barycenters, a new approach to ranking TIT2FSs is given. Four kinds of geometric aggregation (...) operators for TIT2FSs are developed, including the TIT2FS weighted geometric average operator, TIT2FS ordered weighted geometric average operator, TIT2FS hybrid weighted geometric average operator, and extended TIT2FS hybrid weighted geometric average operator. The individual comprehensive values of alternatives are derived through the extended TIT2FS weighted geometric average operators. Using the TIT2FS hybrid weighted geometric average operator and the expert weights, the individual comprehensive values of alternatives are integrated into the collective ones, which are used to rank the alternatives. The practicability and effectiveness of the developed method are illustrated with a teaching quality assessment example. (shrink)

Trapezoidal cubic fuzzy numbers (TzCFNs) are an extraordinary cubic fuzzy set on a real number set. TzCFNs are useful for dealing with well-known quantities in decision data and decision making problems themselves. This paper is about multi-attribute group decision making problems in which the attribute values are stated with TzCFNs, which are solved by developing a new decision method based on power average operators of TzCFNs. The new operation laws for TzCFNs (...) are given. Hereby, the power average operator of real numbers is extended to four kinds of power average operators of TzCFNs, involving the power average operator of TzCFNs, the weighted power average operator of TzCFNs, the power ordered weighted average operator of TzCFNs, and the power hybrid average operator of TzCFNs. In the proposed group decision method, the individual overall evaluation values of alternatives are generated by using the power average operator of TzCFNs. Applying the hybrid average operator of TzCFNs, the specific general evaluation standards of alternatives are then combined into the collective ones, which are used to rank the alternatives. The example analysis shows the practicality and effectiveness of the proposed method. (shrink)

We provide an economic interpretation of the practice consisting in incorporating risk measures as constraints in an expected prospect maximization problem. For what we call the infimum of expectations class of risk measures, we show that if the decision maker (DM) maximizes the expectation of a random prospect under constraint that the risk measure is bounded above, he then behaves as a “generalized expected utility maximizer” in the following sense. The DM exhibits ambiguity with respect to a family of (...) utility functions defined on a larger set of decisions than the original one; he adopts pessimism and performs first a minimization of expected utility over this family, then performs a maximization over a new decisions set. This economic behaviour is called “maxmin under risk” and studied by Maccheroni (Econ Theory 19:823–831, 2002). As an application, we make the link between an expected prospect maximization problem, subject to conditional value-at-risk being less than a threshold value, and a non-expected utility economic formulation involving “loss aversion”-type utility functions. (shrink)

In most decision-making situations, there is a plethora of information potentially available to people. Deciding what information to gather and what to ignore is no small feat. How do decision makers determine in what sequence to collect information and when to stop? In two experiments, we administered a version of the German cities task developed by Gigerenzer and Goldstein (1996), in which participants had to decide which of two cities had the larger population. Decision makers were (...) not provided with the names of the cities, but they were able to collect different kinds of cues for both response alternatives (e.g., “Does this city have a university?”) before making a decision. Our experiments differed in whether participants were free to determine the number of cues they examined. We demonstrate that a novel model, using hierarchical latent mixtures and Bayesian inference (Lee & Newell, 2011) provides a more complete description of the data from both experiments than simple conventional strategies, such as the take–the–best or the Weighted Additive heuristics. (shrink)

“Rough set” is a theory put forward by the polish scholar Z. Pawlak, which is a useful mathematics tool for dealing with vague and uncertain information. Rough set theory can achieve a subset of all attribute which preserves the discernible ability of original features, by using the data only with no additional information. As a typical system of multi-agent, the decision-making system of soccer robot has the features of multi-layered, antagonism, and cooperation. On the bases (...) of rough set theory, this paper established a decision making system with complete information for soccer robot, and then reduce the condition and decision attributes and their values, to get the simply decision rules. On the otherwise, considering the situation of information loss, we study decision making of imperfect information system, extract the decision rules and calculate the reliability, so that the rules can assist the agent to make right decision in competition. The simulation result shows that the algorithm is correct and effective. (shrink)

On the basis of the combination of single-valued neutrosophic sets and hesitant fuzzy sets, this article proposes a single-valued neutrosophic hesitant fuzzy set as a further generalization of the concepts of fuzzy set, intuitionistic fuzzy set, single-valued neutrosophic set, hesitant fuzzy set, and dual hesitant fuzzy set. Then, we introduce the basic operational relations and cosine measure function of SVNHFSs. Also, we develop a single-valued neutrosophic hesitant fuzzy weighted averaging operator and a single-valued neutrosophic hesitant fuzzy weighted geometric operator and (...) investigate their properties. Furthermore, a multiple-attribute decision-making method is established on the basis of the SVNHFWA and SVNHFWG operators and the cosine measure under a single-valued neutrosophic hesitant fuzzy environment. Finally, an illustrative example of investment alternatives is given to demonstrate the application and effectiveness of the developed approach. (shrink)

As a generalization of both single-valued neutrosophic element and hesitant fuzzy element, single-valued neutrosophic hesitant fuzzy element is an efficient tool for describing uncertain and imprecise information. Thus, it is of great significance to deal with single-valued neutrosophic hesitant fuzzy information for many practical problems. In this paper, we study the aggregation of SVNHFEs based on some normalized operations from geometric viewpoint. Firstly, two normalized operations are defined for processing SVNHFEs. Then, a series of normalized aggregation operators which fulfill some (...) basic conditions of a valid aggregation operator are proposed. Additionally, a decision-making method is developed for resolving multiattribute decision-making problems based on the proposed operators. Finally, a numerical example is provided to illustrate the feasibility and effectiveness of the method. (shrink)

In this paper, we propose a new hybrid neutrosophic multi criteria decision making (MCDM) framework that employs a collection of neutrosophic analytical network process (ANP), and order preference by similarity to ideal solution (TOPSIS) under bipolar neutrosophic numbers. The MCDM framework is applied for chief executive officer (CEO) selection in a case study at the Elsewedy Electric Group, Egypt. The proposed approach allows us to assemble individual evaluations of the decision makers and therefore perform accurate personnel (...) selection. The outcomes of the proposed method are compared with those of the related works such as weight sum model (WSM), weight product model (WPM), analytical hierarchy process (AHP), multiobjective optimization based on simple ratio analysis (MOORA) and ANP methods to prove and validate the results. (shrink)

The objective of the paper is to implement and validate diagnosis in the medical field via refined neutrosophic fuzzy logic (RNFL). As such, we have proposed a Max-Min composition (MMC) method in RNFL. This method deals with the diagnosis under certain constraints like uncertainty and indeterminacy. Further, we have considered the diagnosis problems to validate the sensitivity analysis of the novel multi attribute decision-making technique. Finally, we gave the graphical representations and compared the obtained results with (...) other existing measures in refined neutrosophic fuzzy sets. (shrink)

The paper compares use of willingness to pay values with multi-attribute utility as ways of modelling social choice problems in the environment. A number of reasons for moving away from willingness to pay are reviewed. The view proposed is that social choice is about the integration of competing claim types (utilities, rights, social contracts and beliefs about due process). However, willingness to pay is only indirectly related to the first of these and assumes an Arrovian approach, namely one (...) in which social choice is regarded as the aggregation of people's preferences. (shrink)

One of the new topics that has attracted the attention of researchers in recent years is neuro-marketing. The purpose of the present study is to achieve an insight into the progress of studies on neuro-marketing through review of scientific articles in this field with methodology text-mining. A total of 394 articles were selected between 2005 and 2017 using the search for “neuro-marketing” in valid databases. By reviewing the title, abstract, and keywords at various stages of screening, the researchers selected 311 (...) articles related to the neuro-marketing topic in order to carry out the text mining process. Then, pre-processing of data was performed and using cluster analysis, 6 optimal clusters were obtained according to Davis Bouldin index. Using the multi-attribute decision-making technique, the most important roots were ranked in each cluster. The results showed that interest in research on neuro-marketing has increased in recent years and clusters created around topics such as marketing strategies, advertising and video ads, ethical issues, advertising message components, neuroscience in marketing, economics and consumer behavior, and decision making and brand selection. The study shows that the researchers’ attention is moving from the concepts and principles of the use of neuroscience in marketing, economics and consumer behavior to design and develop marketing strategies using neuroscience. (shrink)

This paper presents a mathematical model for decision making processes where the knowledge for the decision is constructed automatically from subjective information on the Internet. This mathematical model enables us to know the required degree of accuracy of knowledge acquisition for constructing decision support systems using two technologies: automated knowledge acquisition from information on the Internet and automated reasoning about the acquired knowledge. The model consists of three elements: knowledge source, which is a set of subjective (...) information on the Internet, knowledge acquisition, which acquires knowledge base within a computer from the knowledge source, and decision rule, which chooses a set of alternatives by using the knowledge base. One of the important features of this model is that the model contains not only decision making processes but also knowledge acquisition processes. This feature enables to analyze the decision processes with the sufficiency of knowledge sources and the accuracy of knowledge acquisition methods. Based on the model, decision processes by which the knowledge source and the knowledge base lead to the same choices are given and the required degree of accuracy of knowledge acquisition is quantified as required accuracy value. In order to show the way to utilize the value for designing the decision support systems, the value is calculated by using some examples of knowledge sources and decision rules. This paper also describes the computational complexity of the required accuracy value calculation and shows a computation principle for reducing the complexity to the polynomial order of the size of knowledge sources. (shrink)

The interval neutrosophic uncertain linguistic variables can easily express the indeterminate and inconsistent information in real world, and TOPSIS is a very effective decision making method more and more extensive applications. In this paper, we will extend the TOPSIS method to deal with the interval neutrosophic uncertain linguistic information, and propose an extended TOPSIS method to solve the multiple attribute decision making problems in which the attribute value takes the form of the interval neutrosophic (...) uncertain linguistic variables and attribute weight is unknown. Firstly, the operational rules and properties for the interval neutrosophic variables are introduced. Then the distance between two interval neutrosophic uncertain linguistic variables is proposed and the attribute weight is calculated by the maximizing deviation method, and the closeness coefficients to the ideal solution for each alternatives. Finally, an illustrative example is given to illustrate the decision making steps and the effectiveness of the proposed method. (shrink)

For decisions between many alternatives, the benchmark result is Hick's Law: that response time increases log-linearly with the number of choice alternatives. Even when Hick's Law is observed for response times, divergent results have been observed for error rates—sometimes error rates increase with the number of choice alternatives, and sometimes they are constant. We provide evidence from two experiments that error rates are mostly independent of the number of choice alternatives, unless context effects induce participants to trade speed for accuracy (...) across conditions. Error rate data have previously been used to discriminate between competing theoretical accounts of Hick's Law, and our results question the validity of those conclusions. We show that a previously dismissed optimal observer model might provide a parsimonious account of both response time and error rate data. The model suggests that people approximate Bayesian inference in multi-alternative choice, except for some perceptual limitations. (shrink)

In this paper, we introduce the concepts of Pythagorean fuzzy valued neutrosophic set (PFVNS) and Pythagorean fuzzy valued neutrosophic (PFVNV) constructed by considering Pythagorean fuzzy values (PFVs) instead of numbers for the degrees of the truth, the indeterminacy and the falsity, which is a new extension of intuitionistic fuzzy valued neutrosophic set (IFVNS). By means of PFVNSs, the degrees of the truth, the indeterminacy and the falsity can be given in Pythagorean fuzzy environment and more sensitive evaluations are made by (...) a decision maker in decision making problems compared to IFVNSs. In other words, such sets enable a decision maker to evaluate the degrees of the truth, the indeterminacy and the falsity as PFVs to model the uncertainty in the evaluations. (shrink)

Individual differences in decisiveness: pre-decisional information search and decision strategy use We investigated whether individual differences in decisiveness are associated with a tendency to use different decision strategies during pre-decisional information search. To explore these potential links we administered the Need for Cognitive Closure questionnaire to 62 participants, followed by a probabilistic inference, multi-attribute choice task. Participants high in decisiveness dimension, compared to ‘low decisives’, spent less time and acquired less information prior to making decisions, (...) especially in the first trials of the choice task. ‘High decisives’ also had a greater tendency to use a simple Lexicographic heuristic than ‘low decisives’. The results support the view that high decisiveness is associated with greater tendency to simplify the decision process. (shrink)

We propose a descriptive version of the classical multi-attribute utility model; to that end, we add a new parameter, momentary salience, to the customary formulation. The addition of this parameter allows the theory to accommodate changes in the decision maker’s mood and circumstances, as the saliencies of anticipated consequences are driven by concerns of the moment. By allowing for the number of consequences given attention at the moment of decision to vary, the new model mutes the (...) criticism that SEU models call for an omniscient decision maker. Use of the model is illustrated with a large-scale longitudinal study showing that adolescent smokers have higher utility for smoking than nonsmokers. We also propose to use the model hierarchically to describe everyday decisions that people deal with repeatedly. Big decisions, which set policy, guide a host of nested little decisions, which in turn lead to action. For a little decision, one of the options will be consistent with the policy, and will inherit its high utility. Accordingly, most little decisions will be made quickly and will follow the policy. However, people do sometimes decide to violate their own policies, and we describe how these lapses can lead to collapse of the policy. (shrink)

Making investment decisions is usually considered a challenging task for investors because it is a process based on risky, complex, and consequential choices. When it comes to Investments in human capital, such as startups fundings, the aspect of decision-making becomes even more critical since the outcome of the DM process is not completely predictable. Indeed, it has to take into consideration the will, goals, and motivations of each human actor involved: those who invest as well as those (...) who seek investments. We define this specific DM process as multi-actor DM since not a group is making decisions but different actors, or groups of different actors, who – starting from non-coinciding objectives – need to reach a mutual agreement and converge toward a common goal for the success of the investment. This review aims to give insights on psychological contributions to the study of complex DM processes that deal with IHC to provide scholars and practitioners with a theoretical framework and a tool for describing the complex socio-ecological systems involved in the DM processes. For this purpose, we discuss in the paper how the third generation of activity theory could be used as an appropriate model to explain the specificities of MADM construct, focusing on the particular case of startup funding. Design thinking techniques will be proposed as a methodology to create a bridge between different activity systems. (shrink)

Link prediction, which aims to forecast potential or missing links in a complex network based on currently observed information, has drawn growing attention from researchers. To date, a host of similarity-based methods have been put forward. Usually, one method harbors the idea that one similarity measure is applicable to various networks, and thus has performance fluctuation on different networks. In this paper, we propose a novel method to solve this issue by regarding link prediction as a multiple-attribute decision- (...) class='Hi'>making problem. In the proposed method, we consider RA, LP, and CAR indices as the multiattribute for node pairs. The technique for order performance by similarity to ideal solution is adopted to aggregate the multiattribute and rank node pairs. The proposed method is not limited to only one similarity measure, but takes separate measures into account, since different networks may have different topological structures. Experimental results on 10 real-world networks manifest that the proposed method is superior in comparison to state-of-the-art methods. (shrink)

Community detection is one of the key research directions in complex network studies. We propose a community detection algorithm based on a density peak clustering model and multiple attribute decision-making strategy, TOPSIS. First, the two-dimensional dataset, which is transformed from the network by taking the density and distance as the attributes of nodes, is clustered by using the DBSCAN algorithm, and outliers are determined and taken as the key nodes. Then, the initial community frameworks are formed and (...) expanded by adding the most similar node of the community as its new member. In this process, we use TOPSIS to cohesively integrate four kinds of similarities to calculate an index, and use it as a criterion to select the most similar node. Then, we allocate the nonkey nodes that are not covered in the expanded communities. Finally, some communities are merged to obtain a stable partition in two ways. This paper designs some experiments for the algorithm on some real networks and some synthetic networks, and the proposed method is compared with some popular algorithms. The experimental results testify for the effectiveness and show the accuracy of our algorithm. (shrink)

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 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 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 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. (shrink)

With the desired outcome of social good within the wider robotics ecosystem, trust is identified as the central adhesive of the human–robot interaction (HRI) interface. However, building trust between humans and robots involves more than improving the machine’s technical reliability or trustworthiness in function. This paper presents a holistic, community-based approach to trust-building, where trust is understood as a multifaceted and multi-staged looped relation that depends heavily on context and human perceptions. Building on past literature that identifies dispositional and (...) learned stages of trust, our proposed decision to trust model considers more extensively the human and situational factors influencing how trust manifests within social relations. Priority is given to the human user of technology—the initiator of human—robot trust relations—at all stages of decision-making. The envisioned formation of optimal conditions in which trust emerges requires the collective participation of practitioners, policymakers, and members of the community. With trust facilitating the smooth transition of robots into more socially embedded roles, positive receptivity of the best engineering project arises from the presence of harmonious robot-human trust relations in community spaces. (shrink)

The construction industry is typically characterized as a fragmented, multi-organizational setting in which members from different technical backgrounds and moral values join together to develop a particular business or project. The most challenging obstacle in the construction process is to achieve a successful practice and to identify and apply an ethical framework to manage the behavior of involved specialists and contractors and to ensure the quality of all completed construction activities. The framework should reflect a common moral ground for (...) myriad people involved in this process to survive and compete ethically in today’s turbulent construction market. This study establishes a framework for moral judgment of behavior and actions conducted in the construction process. The moral framework provides the basis of judging actions as “moral” or “immoral” based on three levels of moral accountability: personal, professional, and social. The social aspect of the proposed framework is developed primarily from the essential attributes of normative business decision-making models identified in the literature review and subsequently incorporates additional attributes related to professional and personal moral values. The normative decision-making models reviewed are based primarily on social attributes as related to moral theories. The professional and moral attributes are established by identifying a set of common moral values recognized by professionals in the construction industry and required to prevent common construction breaches. The moral framework presented here is the complementary part of the ethical framework developed in Part I of this article and is based primarily on the personal behavior or the moral aspect of professional responsibility. The framework can be implemented as a form of preventive personal ethics, which would help avoid ethical dilemmas and moral implications in the first place. Furthermore, the moral framework can be considered as a decision-making model to guide actions and improve the moral reasoning process, which would help individuals think through possible implications and the consequences of ethical and moral issues in the construction industry. (shrink)

The convergence of India’s rich cultural and religious heritage with its rapidly transforming economy provides a unique opportunity to understand how senior executives navigate the demands of the business environment within the context of their religious convictions. Forty senior executives with varying religious backgrounds and global responsibilities within Indian multinational corporations participated in this study. Drawing from virtue ethics theory and using systematic content analysis, several themes emerged for ethical virtues. The analysis illustrates how these deeply seated ethical virtues helped (...) to form and refine these executives’ ethical mindsets via guiding principles such as an ethical culture, environment, molding, education, commitment and leadership. In turn, these ethical mindsets influenced the executives’ ethical decision-making processes. We find that these executives’ ethical virtues and mindsets are inspired by their religious backgrounds. In summary, a very complex mental tug-of-war appears to take place as these executives rationalize and negotiate unethical circumstances while being cognizant of personal religious beliefs. We contend that in a pluralistic multi-faith society such as India, it is critical for corporations to align the virtues of its senior executives with those of the corporation so that virtues are applied consistently when dealing with various stakeholders. The findings present several theoretical and practical implications, which are discussed. (shrink)

To address the prevalence and complexities of sustainable development challenges around the world, organizations in the business, government, and non-profit sectors are increasingly collaborating via multi-stakeholder partnerships. Because complex problems can be neither understood nor addressed by a single organization, it is necessary to bring together the knowledge and resources of many stakeholders. Yet, how these partnerships coordinate their collaborative activities to achieve mutual and organization-specific goals is not well understood. This study takes an organization design perspective of collaborative (...) decision-making processes to explore how they impact the effectiveness of multi-stakeholder partnerships. We compare the decision-making processes of 94 sustainability-focused multi-stakeholder partnerships and find that collaborative decision-making has an indirect and positive impact on partnership capacity through systems that keep partners informed, coordinate partner interactions, and facilitate ongoing learning. The implications of this study for multi-stakeholder partnership research and practice are that partnership capacity is contingent on the design of decision-making processes, as well as internal mechanisms that coordinate and monitor collaborative activities. (shrink)

Discrete choice experiments—selecting the best and/or worst from a set of options—are increasingly used to provide more efficient and valid measurement of attitudes or preferences than conventional methods such as Likert scales. Discrete choice data have traditionally been analyzed with random utility models that have good measurement properties but provide limited insight into cognitive processes. We extend a well-established cognitive model, which has successfully explained both choices and response times for simple decision tasks, to complex, multi-attribute discrete (...) choice data. The fits, and parameters, of the extended model for two sets of choice data (involving patient preferences for dermatology appointments, and consumer attitudes toward mobile phones) agree with those of standard choice models. The extended model also accounts for choice and response time data in a perceptual judgment task designed in a manner analogous to best–worst discrete choice experiments. We conclude that several research fields might benefit from discrete choice experiments, and that the particular accumulator-based models of decision making used in response time research can also provide process-level instantiations for random utility models. (shrink)

This paper explores lexicographically additive representations of multi-attribute preferences on finite sets. Lexicographic additivity combines a lexicographic feature with local value tradeoffs. Tradeoff structures are governed by either transitive or nontransitive additive conjoint measurement. Alternatives are locally traded off when they are close enough within threshold associated with a dominant subset of attributes.

Regarding police procedures with alcohol-intoxicated witnesses, Swedish police officers have previously reported inconsistent and subjective decisions when interviewing these potentially vulnerable witnesses. Most officers have also highlighted the need for national policy guidelines aiding in conducting investigative interviews with intoxicated witnesses. The aims of the two studies presented here were to investigate whether police officers’ inconsistent interview decisions are attributable to a lack of research-based knowledge; their decision to interview, as well as their perceptions of the witnesses’ credibility could (...) be influenced by scientific research; and police officers decision-making and perceptions of witness credibility are biased by pre-existing social norms. In two separate randomized online experiments, police professionals and recruits watched a recorded fictive witness interview to which they were asked to rate the probability of interviewing the witness, the witness’ credibility, and to estimate the witness’ level of intoxication. Results showed that interview probability and perceived witness credibility were affected by witness intoxication level. While it cannot be stated definitely from the present research, these findings provided indications that police officers and recruits lacked research-based knowledge. Results also showed that interview probability, but not perceptions of credibility, was influenced by a research-based message. In line with research, interview probability for the most intoxicated witness increased after reading the message. Unexpectedly, neither interview probability nor witness credibility was affected by social norms. The current findings added to the legal psychology literature by showing that a breath alcohol concentration as low as.04% was enough for police officers and recruits to consider intoxicated witnesses less credible than sober witnesses. Findings also indicated that, despite the lower credibility assessment, police may have some understanding that these witnesses can be interviewed at low intoxication levels. However, this willingness to interview intoxicated witnesses ceased at a BrAC lower than the levels where research has found intoxicated witnesses as reliable as sober witnesses. Future directions for research and policy development as well as theoretical and practical implications of the present findings are discussed. (shrink)