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This study aims to examine the moderating effect of culture on the phrase expression type that affects product attitude. Moreover, to identify the mechanism by which these effects occur, the authors investigated the mediating role of processing fluency, and examined how such a mediating effect of processing fluency varies with number of alternatives.

Three experiments were conducted to verify the hypotheses presented in this study. Experiment 1 tested the effects of phrase expression type and culture on product attitude; a two-factor design (phrase expression type: explicit expression vs implicit expression) was applied, and culture was classified according to nationality. Experiment 2 tested the mediating effect of processing fluency on product attitude, using the same approach as Experiment 1. Experiment 3 tested the moderated mediating role of the number of alternatives, a between-group experimental design of 2 (phrase expression: explicit expression vs implicit expression) × 2 (number of alternatives: many vs few) was applied.

Experiment 1's results demonstrate that product attitude is more favorable when implicit expressions are used for Asians, whereas it is more favorable with explicit expressions for Westerners. Experiment 2 verifies that the interaction effect between phrase expression type and culture on product attitude is mediated by processing fluency. Experiment 3's results demonstrate that the number of alternatives moderates the mediating role of processing fluency for Westerners, but has no effect on the processing fluency for Asians.

This study provides novel insights and expands the field of study of phrase expression types by separating the ambiguous boundaries among phrase presentation types. Furthermore, this study provides practical guidelines for establishing effective advertising strategies for companies by suggesting suitable phrase expression types based on culture.

The primitive purpose of this manuscript is to develop an effective and efficient computer numerical control (CNC) machine tool evaluation index from the perspective of appraisal and benchmarking of preferred candidate machine tool in subjective information scenario. In this reporting, manager has been facilitated from the decision making tool and methodology in order to evaluate the best one and benchmarking the preferred candidate alternative machine tool under the subjective criterion circumstances.

A MULTI-MOORA (multi-objective optimization by ratio analysis) methodology conjunction with grey number has fruitfully applied in evaluated subjective information against criterion module plate form from the prospectus of handling the vagueness, inconsistency, impreciseness and in order to appraisal and benchmarking of the candidate CNC machine tool alternatives.

In today scenario, the subjective evaluation criterion has even ran over the CNC machine tool evaluation module (index) except other valuable area on account of an abatement of consistent data. The authors found out the subjective information is even necessary/mandatory to handling and tackle such an inconsistent, vagueness, impreciseness which associated uncertain criterion. So, the authors found out that the application of grey number conjunction with MULTI-MOORA decision methodology from the prospectus of appraisal and benchmarking of preferred candidate alternatives machine tool.

The major contribution of this manuscript to exploration of grey number set conjunction with MULTI-MOORA methodology toward appraisal and benchmarking of preferred CNC candidate machine tool alternative, handled and tackled the evaluated subjective information from expert panel against subjective criterion environment, facilitates the multi-criterion decision making (MCDM) module from the prospectus of best one and ranking order the candidate machine tool alternative under the similar subjective criterion circumstances.

The purpose of this paper is to investigate a novel generalised grey target decision method (GGTDM) with index and weight involving mixed attribute values.

The mixed attribute values are transformed into binary connection numbers and also comprised of two-tuple (determinacy, uncertainty) numbers to fulfil the decision-making task. The proposed method constructs the weight function to convert the mixed attribute-based weights into the certain number-based weights and determines the alternatives ranking by the comprehensive weighted Gini–Simpson indices (CWGSIs).

The result of decision making regarding the numerical example by the proposed approach is somewhat different from that obtained by the reported vector-based method. The reasons for this are threefold: the decision-making bases are different, the target centre indices are determined by different mechanisms and certain number-based weights are calculated in different ways.

The proposed method ranks an alternative based on the Gini–Simpson index, as derived from the viewpoint of measuring the uncertainty (heterogeneity): however, the vector-based GGTDM makes a decision based on proximity, as is the case when measuring the similarities between index vectors.

The proposed approach is admissible to solving mixed attribute-based decision making especially for alternative indices and attribute weights containing both uncertain numbers.

The proposed method provides a new perspective on measuring the difference of alternatives to the target centre via the CWGSI: the CWGSI is obtained by relying on the pseudo-probabilities achieved by the ratios of the alternative indices to the target centre indices. It also builds a weight function converting the mixed attribute-based weights into certain number-based weights. This method provides a framework that should be tested in terms of its effective decision making using real data and an actual problem.

The Equal Pay Act 1970 (which came into operation on 29 December 1975) provides for an “equality clause” to be written into all contracts of employment. S.1(2) (a) of the 1970 Act (which has been amended by the Sex Discrimination Act 1975) provides:

There is extensive evidence that decision-makers, faced with increasing information load, may simplify their choice by reducing the amount of information to process. One simplification, commonly referred to as attribute non-attendance (ANA), is a reduction of the number of attributes of the choice alternatives. Several previous studies have identified relationships between varying information load and ANA using self-reported measures of ANA. This chapter revisits this link, motivated by recognition in the literature that such self-reported measures are vulnerable to reporting error.

This chapter employs a recently developed modelling approach that has been shown to effectively infer ANA, the random parameters attribute non-attendance (RPANA) model. The empirical setting systematically varies the information load across respondents, on a number of dimensions.

Confirming earlier findings, ANA is accentuated by an increase in the number of attribute levels, and a decrease in the number of alternatives. Additionally, specific attributes are more likely to not be attended to as the total number of attributes increases. Willingness to pay (WTP) under inferred ANA differs notably from when ANA is self-reported. Additionally accounting for varying information load, when inferring ANA, has little impact on the WTP distribution of those that do attend. However, due to varying rates of non-attendance, the overall WTP distribution varies to a large extent.

This is the first examination of the impact of varying information load on inferred ANA that is identified with the RPANA model. The value lies in the confirmation of earlier findings despite the evolution of methodologies in the interim.

Most decision-making problems in construction are complex and difficult to solve, as they involve multiple criteria and multiple decision makers in addition to subjective uncertainties, imprecisions and vagueness surrounding the decision-making process. In many instances, the decision-making process is based on linguistic terms rather than numerical values. Hence, structured fuzzy consensus-reaching processes and fuzzy aggregation methods are instrumental in multi-criteria group decision-making (MCGDM) problems for capturing the point of view of a group of experts. This chapter outlines different fuzzy consensus-reaching processes and fuzzy aggregation methods. It presents the background of the basic theory and formulation of these processes and methods, as well as numerical examples that illustrate their theory and formulation. Application areas of fuzzy consensus reaching and fuzzy aggregation in the construction domain are identified, and an overview of previously developed frameworks for fuzzy consensus reaching and fuzzy aggregation is provided. Finally, areas for future work are presented that highlight emerging trends and the imminent needs of fuzzy consensus reaching and fuzzy aggregation in the construction domain.

In today's competitive global marketplace, performance management has been identified as a key strategic consideration towards achieving an efficient supply chain management. The task of estimating supply chain performance extent is seemed a complex problem entitled with multiple subjective performance measures and metrics; subjected to decision-making environment which involves an inherent vagueness, inconsistency and incompleteness associated with decision-makers (DMs) (expert panel) commitment towards assessment of various subjective (quantitative) evaluation indices. Consequently, it becomes difficult towards making a comparative study on performances of alternative supply chains. It is, therefore, indeed essential to conceptualize and develop an efficient appraisement platform helpful for benchmarking of alternative supply chains based on their performance extent. The paper aims to discuss these issues.

The work explores the concept of grey numbers combined with multi-objective optimization by ratio analysis (MOORA) in perceptive to evaluate best alternative from among available alternative supply chains.

The method has been found fruitful to facilitate such a multi-criteria group decision-making (MCGDM) problem under uncertain environment and provides an appropriate compromise ranking order with respect to available possible alternatives.

Supply chain performance appraisement provides necessary means by which an organization can assess whether its supply chain is performing well, whether it has been improved or degraded as compared to the past record. The purpose of this research is to develop and to empirically test a multiple-indices hierarchical appraisement model for benchmarking of supply chain performance and its impact on competitiveness of manufacturing industries.

Defines an “evoked set” as those brands which become alternatives to those goods chosen by a buyer in a buying situation. Examines why the buyer chooses only to evaluate a limited number of possible choice alternatives, and investigates the number of alternatives which enter into the buyer's considerations. Tries to locate factors influencing the number of alternatives evaluated. Suggests that the size of the “evoked set” is largely determined by the buyer's experience of the buying situation and insight.

There have always been concerns about task complexity and respondent burden in the context of stated choice (SC) studies, with calls to limit the number of alternatives, attributes and choice sets. At the same time, some researchers have also made the case that too simplistic a design might be counterproductive given that such designs may result in issues of omitting important decision variables. This paper aims to take another look at the effects of design complexity on model results. Specifically, we make use of an approach devised by Hensher (2004)¹ in which different respondents in the study are presented with designs of different complexity, and look specifically at effects on model scale in a UK context, adding to previous Chilean evidence by Caussade et al. (2005). The results of our study indicate that the impact of design complexity may be somewhat lower than anticipated, and that more complex designs may not necessarily lead to poorer results. In fact, some of the more complex designs lead to higher scale in the models. Overall, our findings suggest that respondents can cope adequately with large number of attributes, alternatives and choice sets. The implications for practical research are potentially significant, given the widespread use, especially in Europe, of stated choice designs with a limited number of alternatives and attributes.