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Dominance techniques are used to analyze and rank inequality, welfare, and poverty across regions in Thailand in the 1990s. Inference-based dominance methods are applied to consumption expenditure microdata from the Household Socio-Economic Surveys (SES) of 1992, 1994, 1996, 1998 and 2000. Attention is focused on the period immediately before and after the economic contraction of 1996–1997. Lorenz dominance is employed to assess inequality, while first-order Engel food share dominance is applied to rank welfare across time and among regions. Poverty is evaluated by comparing truncated food-share quantile functions. The evidence reveals that the economic crisis in 1997 seems to affect inequality in Bangkok (the richest region) more than the Northeast (the poorest region), and most dramatic changes occur in the North and South. Welfare in Bangkok is unambiguously higher than in other regions before and after economic contraction. In fact, the great economic contraction changes the rankings of economic well-being and poverty only in the North, South, and Northeast.

In a period of political change in the European Union, when the European Constitution is in the centre of the debate, the social convergence among European Union countries is a crucial issue. However, the measurement of welfare, inequality and poverty and the comparisons among countries are issues of great controversy. One of the main reasons for this is that implicit or explicit value judgements have to be made, and it is not easy to determine which of these value judgements are the most appropriate ones. In this paper we apply inference-based stochastic dominance methods to study welfare, inequality and poverty in European Union countries in 2000, applying purchasing power parities from the OECD. There are two main advantages of the methods and data used in this work: on the one hand, the stochastic method uses explicit and widely, though not universally, accepted assumptions, and if this small number of assumptions is accepted, the welfare and poverty ranking that the method provides is unambiguous. On the other hand, the use of the European Community Household Panel permits the comparisons in welfare, inequality and poverty among different countries using harmonised data. In addition, the use of inference tests permits a more precise ranking.

Hypothesis tests for dominance in income distributions has received considerable attention in recent literature. See, for example, Barrett and Donald (2003a, b), Davidson and Duclos (2000) and references therein. Such tests are useful for assessing progress towards eliminating poverty and for evaluating the effectiveness of various policy initiatives directed towards welfare improvement. To date the focus in the literature has been on sampling theory tests. Such tests can be set up in various ways, with dominance as the null or alternative hypothesis, and with dominance in either direction (X dominates Y or Y dominates X). The result of a test is expressed as rejection of, or failure to reject, a null hypothesis. In this paper, we develop and apply Bayesian methods of inference to problems of Lorenz and stochastic dominance. The result from a comparison of two income distributions is reported in terms of the posterior probabilities for each of the three possible outcomes: (a) X dominates Y, (b) Y dominates X, and (c) neither X nor Y is dominant. Reporting results about uncertain outcomes in terms of probabilities has the advantage of being more informative than a simple reject/do-not-reject outcome. Whether a probability is sufficiently high or low for a policy maker to take a particular action is then a decision for that policy maker.

The methodology is applied to data for Canada from the Family Expenditure Survey for the years 1978 and 1986. We assess the likelihood of dominance from one time period to the next. Two alternative assumptions are made about the income distributions – Dagum and Singh-Maddala – and in each case the posterior probability of dominance is given by the proportion of times a relevant parameter inequality is satisfied by the posterior observations generated by Markov chain Monte Carlo.

Dominance complementarity, which is the tendency for people to respond oppositely to others along the control dimension of interpersonal behavior, is a means by which people create and perpetuate informal forms of interpersonal hierarchy within social relationships (Tiedens, Unzueta, & Young, 2007b). In the present chapter, I explore the likely effects of such complementarity on group creativity. I propose specifically that expressions of dominance, even those borne not out of formal hierarchy but rather out of such factors as expertise and enthusiasm for the task, are likely to elicit submissive responses from fellow group members when the group is trying to generate creative ideas. As group members behaving submissively are likely to contribute fewer ideas to group discussion, I argue that group members who behave dominantly may, through their influence on other group members, reduce both the number and diversity of ideas generated within the group. I, therefore, propose that dominance complementarity may impair groups' abilities to generate creative ideas.

This paper deals with poverty decompositions into subgroups defined with respect to intervals of income and the robustness of comparisons of the absolute contribution of such groups to poverty. For instance, world poverty estimates by the World Bank often distinguish between the extreme poor whose incomes are lower than $1.25 a day (in PPP terms) and the other poor with incomes between $1.25 and $2.5 a day. Existing dominance conditions can tell whether overall poverty and extreme poverty have declined in a robust manner when comparing countries at two points of time, but they cannot say anything for the contribution of the non-extreme poor to overall poverty. In the present paper we propose stochastic generalized dominance criteria to perform robust poverty ordering when the focus is placed on some interval of the poverty domain. Using generated data based on grouped data from World Bank’s PovcalNet tool, the paper finally investigates whether the robust decline of extreme poverty around the world during the last decades was also accompanied by a decline of the contribution of non-extreme poverty.

The purpose of this paper is to construct a novel grey dominance variable precision rough model.

To deal with the problems that the attribute values of the decision-making object are often not exact numbers but interval grey numbers, and the decision-making attributes satisfy a certain preference relationship in the decision-making information because of the complexity and uncertainty of the real world, the authors take advantage of the theoretical thinking of the grey systems, dominance rough set theory and variable precision rough set theory, and construct a novel dominance variable precision rough set model. On the basis of the thinking logic of grey systems, the authors first define the concepts of balance degree, dominance degree and inferior degree, and then the grey dominance relationship based on the comparison of interval grey numbers. Then the authors use the grey dominance relationship to substitute for the indiscernibility relationship of the variable precision rough set so that the grey dominance variable precision rough model is naturally utilized to reduce the system's attributes in order to derive the needed decision rules. At the end, the authors use a decision-making example of the radar target selection to demonstrate the feasibility and effectiveness of the novel model.

The results show that the proposed model possesses certain fault tolerance ability and can well-realize decision rule extraction and knowledge discovery out of a given incomplete information system.

The method exposed in the paper can be used to deal with the decision-making problems with the grey information, preference information and noise data.

The paper succeeds in realizing both the grey decision-making information with preference information and noise data and the extraction of decision-making rules.

Examines the pioneering work of the European Commission, with the support of the European Court of Justice (ECJ) and the European Court of First Instance (ECFI), to apply the merger control of regulation (MCR) to situations of collective as well as to single dominance. Reveals that the Commission first applied the notion of collective dominance in the Nestlé Perrier merger in 1992 but that the legality of this practice was questionable, given that the express wording of the MCR does not mention the notion. The legal challenge arose from the takeover of Mitteldeutsche Kali AG by Kali und Salz with the landmark judgment favouring the stance of the Commission – the MCR does encompass situations of collective dominance. Examines why the court reached this decision, particularly given that the Advocate General’s opinion was exactly the opposite.

The purposes of the study were (1) to examine whether directional dominance between co-existing athlete brands and sponsor brands exists; (2) to explore whether directional dominance influences consumers' memory interference; and (3) to test whether brand interference interacts with directional dominance among brands to influence consumer evaluation and behaviors under multiple endorsement and sponsorship portfolios.

The research is a 3 (directional dominance: symmetric dominance vs. asymmetric dominance with existing vs. asymmetric dominance with newly endorsed brand) x 2 (brand memory interference: interference vs. no interference) between-subjects factorial design.

The results indicate that (1) directional dominance influenced consumer brand interference, and directional dominance interacted with brand interference on (2) brand evaluation and (3) purchase intention in multiple brand portfolios.

Considering that conventional single-sponsor sponsorship or single-endorser endorsement portfolios are increasingly rare, research on concurrent circumstances of multiple endorsers and multiple endorsed brands in multiple brand portfolios was necessary. By expanding and reconceptualizing the context of brand networks, this study provides empirical evidence on how the dominance and directionality between endorser and (existing and newly) endorsed brands—an athlete endorser's strong pre-existing association with an existing endorsed brand in particular—influenced consumer brand interference and the brand evaluation in multiple brand portfolios.

The purpose of this paper is to investigate whether innovation effort is lower for firms exhibiting signs of higher chief executive officer (CEO) dominance and whether such CEOs can be incentivized to pursue risky ventures such as innovation projects in line with shareholder's interests that are geared toward the long-term growth of the firm.

The paper utilizes panel data of US publicly listed companies (2007–2016) to address the influence of CEO dominance on firm innovation effort and the moderating effects of incentives in this relationship through ordinary least squares (OLS) estimations. A two-stage least squares (2SLS) technique is also employed to address possible endogeneity. As a robustness check, further analysis is conducted utilizing an alternative proxy for CEO incentive as well as Tobit analysis (with panel-level random effects).

Results from both OLS and Tobit estimations offer two key findings. First, there is a significantly negative relationship between CEO pay slice and firm research and development (R&D) intensity. Second, the interaction effect of CEO incentives and CEO dominance is significant and positive.

When provided with the right incentives, such as those that reward long-term performance, dominant CEOs can be incentivized to go after risky ventures like innovation projects that are crucial to promoting the long-term growth of the firm.

This paper utilizes R&D instead of patent outputs as proxies for innovation where the former enables studying R&D efforts for more recent periods compared to prior studies that utilize patent data.

With respect to multiple attribute group decision-making (MAGDM) in which the assessment values of alternatives are denoted by normal discrete fuzzy variables (NDFVs) and the weight information of attributes is incompletely known, this paper aims to develop a novel fuzzy stochastic MAGDM method based on credibility theory and fuzzy stochastic dominance, and then applies the proposed method for selecting the most desirable investment alternative under uncertain environment.

First, by aggregating the membership degrees of an alternative to a scale provided by all decision-makers into a triangular fuzzy number, the credibility degree and expect the value of a triangular fuzzy number are calculated to construct the group fuzzy stochastic decision matrix. Second, based on determining the credibility distribution functions of NDFVs, the fuzzy stochastic dominance relations between alternatives on each attribute are obtained and the fuzzy stochastic dominance degree matrices are constructed by calculating the dominance degrees that one alternative dominates another on each attribute. Subsequently, calculating the overall fuzzy stochastic dominance degrees of an alternative on each attribute, a single objective non-linear optimization model is established to determine the weights of attributes by maximizing the relative closeness coefficients of all alternatives to positive ideal solution. If the information about attribute weights is completely unknown, the idea of maximizing deviation is used to determine the weights of attributes. Finally, the ranking order of alternatives is determined according to the descending order of corresponding relative closeness coefficients and the best alternative is determined.

This paper proposes a novel fuzzy stochastic MAGDM method based on credibility theory and fuzzy stochastic dominance, and a case study of investment alternative selection problem is provided to illustrate the applicability and sensitivity of the proposed method and its effectiveness is demonstrated by comparison analysis with the proposed method with the existing fuzzy stochastic MAGDM method. The result shows that the proposed method is useful to solve the MAGDM problems in which the assessment values of alternatives are denoted by NDFVs and the weight information of attributes is incompletely known.

The contributions of this paper are that to describe the dominance relations between fuzzy variables reasonably and quantitatively, the fuzzy stochastic dominance relations between any two fuzzy variables are redefined and the concept of fuzzy stochastic dominance degree is proposed to measure the dominance degree that one fuzzy variable dominate another; Based on credibility theory and fuzzy stochastic dominance, a novel fuzzy stochastic MAGDM method is proposed to solve MAGDM problems in which the assessment values of alternatives are denoted by NDFVs and the weight information of attributes is incompletely known. The proposed method has a clear logic, which not only can enrich and develop the theories and methods of MAGDM but also provides decision-makers a novel method for solving fuzzy stochastic MAGDM problems.