A FUZZY SUBSET CHARACTERIZATION OF A SITE-SELECTION PROBLEM

This paper presents an application of fuzzy subsets to the problem of selecting sites for locating gas stations. Cost minimization and profit maximization models represent typical approaches to location decisions. These approaches are not well-suited to problems like site selection for gas stations because of the difficulty in identifying precise relationships, the uncertainties involved, and the qualitative and imprecise nature of much of the information used for decision making. This paper proposes the use of a model based on linguistic variables and a direct evaluation of the available alternatives via the use of fuzzy variables. Conclusions regarding the practical advantages and limitations of the approach are drawn based on the reported application.     

On qualitative multi-attribute group decision making and its consensus measure: A probability based perspective

This paper focuses on qualitative multi-attribute group decision making (MAGDM) with linguistic information in terms of single linguistic terms and/or flexible linguistic expressions. To do so, we propose a new linguistic decision rule based on the concepts of random preference and stochastic dominance, by a probability based interpretation of weight information. The importance weights and the concept of fuzzy majority are incorporated into both the multi-attribute and collective decision rule by the so-called weighted ordered weighted averaging operator with the input parameters expressed as probability distributions over a linguistic term set. Moreover, a probability based method is proposed to measure the consensus degree between individual and collective overall random preferences based on the concept of stochastic dominance, which also takes both the importance weights and the fuzzy majority into account. As such, our proposed approaches are based on the ordinal semantics of linguistic terms and voting statistics. By this, on one hand, the strict constraint of the uniform linguistic term set in linguistic decision making can be released; on the other hand, the difference and variation of individual opinions can be captured. The proposed approaches can deal with qualitative MAGDM with single linguistic terms and flexible linguistic expressions. Two application examples taken from the literature are used to illuminate the proposed techniques by comparisons with existing studies. The results show that our proposed approaches are comparable with existing studies.     

基于Heronian平均算子的Pythagorean模糊不确定语言决策方法

针对评价信息为Pythagorean模糊不确定语言数、属性权重未知且属性间相互影响的多属性决策问题,提出一种基于灰色关联法和Heronian平均算子的决策方法。首先,提出Pythagorean模糊不确定语言Heronian平均（PFULHM）算子和Pythagorean模糊不确定语言几何Heronian平均（PFULGHM）算子,并证明其满足幂等性、单调性、有界性及可交换性。考虑到属性权重之间重要程度的差异,定义了Pythagorean模糊不确定语言加权Heronian平均（PFULWHM）算子和Pythagorean模糊不确定语言加权几何Heronian平均（PFULWGHM）算子。其次,将灰色关联法运用到Pythagorean模糊不确定语言环境中求解属性权重。最后,提出基于PFULWHM算子和PFULWGHM算子的决策方法,并通过算例分析说明本文提出方法的有效性。     

The global “war for talent”

In this paper we examine the “global war for talent,” the factors that impact it, and organizations' responses to it. Using a comprehensive search of more than 400 contemporary academic and business press articles, the paper reviews relevant research and reassesses the “talent war.” We posit that the dominant approaches to the “talent war” based on a scarcity state of mind and action, often characterized by a tactical and exclusive top talent or “star” focus, are being challenged by the emergence of a more evolutionary paradigm. This new paradigm adopts more strategic, innovative, cooperative and generative approaches which we describe as creative ‘talent solutions.’ The paper also highlights implications for future research, teaching and development in the field.     

Planning a TV advertising campaign: A crisp multiobjective programming model from fuzzy basic data

This paper proposes a crisp two-objective logarithmic programming model to help companies decide their advertising campaigns on TV networks for mature products. Both objectives are: (a) to achieve the highest audience impact and (b) to reduce advertising costs as much as possible. Information input is fuzzily elaborated from statistical data, the fuzzy variables being defuzzified to introduce them into the crisp model. This fuzzy information is elicited by TV experts (often independent consultants). Although these experts know statistical information on audience in the past, they do not fully trust its predictive ability. The approach leads to the strategic advertisement (ad) placement among different broadcasts. Users (often managers of big companies) should inform the analyst about their advertising campaign budget. From Weber and Fechner-based psychological research, the ad impact during the advertising campaign is measured depending on the logarithm of ad repetitions. The crisp two-objective problem is solved by a tradeoff method subject to TV technical constraints. A case study with real world data is developed.     

Probabilistic and membership approaches in the construction of control charts for linguistic data

Abstract

Two approaches for constructing control charts for quality assurance when the observations are in the form of linguistic data are presented. Both approaches are based on fuzzy set theory and use fuzzy subsets to model the linguistic terms used to describe product quality. They differ in the interpretation of the control limits and in the procedure used to reduce the fuzzy subsets to scalars for determining the chart parameters. The results obtained with simulated data suggest that, on the basis of sensitivity to process shifts, the control charts for linguistic data perform better than conventional p control charts. The number of linguistic terms used in classifying the observations was found to influence the sensitivity of these control charts. The transformation method used to obtain the representative values and the amount of fuzziness do not seem to affect the performance of either type of control charts.     

Reconsidering the exploration of power distance: an active case study approach

In this paper, we present what we call an “active case study” and we theorize specifically on the relevance hereof for an exploration of power distance (as conceptualized by Hofstede (Culture's Consequences: International Differences in Work-Related Values, Sage, Beverley Hills, CA, 1980)). As Hofstede conceives it, the notion of “power distance” enables an understanding of the predominant ideas about inequality prevalent in a (national) culture, which in turn infuse work relationships. An active case study approach—as we elucidate in the paper—implies an acknowledgement on the part of those organizing the research of the manner in which their intervention might affect the way “respondents” experience their work relationships. We suggest that our proposed active case study approach offers novel possibilities for exploring power distance and should be added to the repertoire of approaches used to examine this in organizational life. We develop our argument in this regard by offering a detailed account of the application of this approach to a Taiwanese organization (the Kaohsiung Harbor Bureau in Taiwan).     

A Fuzzy Decision Tree for Fault Classification

In plant accident management, the control room operators are required to identify the causes of the accident, based on the different patterns of evolution of the monitored process variables thereby developing. This task is often quite challenging, given the large number of process parameters monitored and the intense emotional states under which it is performed. To aid the operators, various techniques of fault classification have been engineered. An important requirement for their practical application is the physical interpretability of the relationships among the process variables underpinning the fault classification. In this view, the present work propounds a fuzzy approach to fault classification, which relies on fuzzy if-then rules inferred from the clustering of available preclassified signal data, which are then organized in a logical and transparent decision tree structure. The advantages offered by the proposed approach are precisely that a transparent fault classification model is mined out of the signal data and that the underlying physical relationships among the process variables are easily interpretable as linguistic if-then rules that can be explicitly visualized in the decision tree structure. The approach is applied to a case study regarding the classification of simulated faults in the feedwater system of a boiling water reactor.     

Measuring the leanness of manufacturing systems—A case study of Ford Motor Company and General Motors

In spite of the vast research published on lean manufacturing systems in several disciplines in the last decade, the concept remains underdeveloped for two reasons. First, it lacks a generally accepted definition. Different authors define lean in terms of its objectives, which vary, overlap and differ in different firms. Second, no study has developed a systematic and relative measure of lean production systems. With the lack of such a measure, two companies cannot be rated objectively on their progress toward becoming lean. This paper has two goals: first, to define manufacturing leanness as a unifying concept, and, second, to develop a systematic, long-term measure of leanness. Manufacturing leanness is a strategy to incur less input to better achieve the organization’s goals through producing better output. The systematic measure of leanness has seven characteristics: relative, dynamic, long-term fuzzy logical, objective, integrative and comprehensive. The leanness measure utilizes the fuzzy-logic methodology since lean is a matter of degree. Applying the measure to compare the production leanness of Ford Motor Company and General Motors, the paper selects Honda Motor Company as the benchmarking firm. Selecting just-in-time (JIT), Kaizen, and quality controls as lean attributes, the paper uses surrogates for these attributes extracted from audited financial statements over the years 2001–2003. The results show that Ford’s system is more than 17% leaner than GM’s system vis-à-vis the benchmarked company’s system.     

Team leadership

Despite the ubiquity of leadership influences on organizational team performance and the large literatures on leadership and team/group dynamics, we know surprisingly little about how leaders create and handle effective teams. In this article, we focus on leader–team dynamics through the lens of “functional leadership.” This approach essentially asserts that the leader's main job is to do, or get done, whatever functions are not being handled adequately in terms of group needs. We explicate this functional leadership approach in terms of 4 superordinate and 13 subordinate leadership dimensions and relate these to team effectiveness and a range of team processes. We also develop a number of guiding propositions. A key point in considering such relationships is the reciprocal influence, whereby both leadership and team processes influence each other.     

基于Mo-RVIKOR的混合多属性决策方法

针对复杂性和不确定性多属性决策问题,考虑定量和定性融合的属性形式,提出了模块化随机多准则妥协解排序法（Modular Random VlseKriterijumska Opti-mizacija I Kompromisno Resenje,Mo-RVIKOR）,该方法无需将信息统一,就能处理多种信息形式存在的多属性决策问题。采用精确数、随机变量处理定量评价信息,用概率语义术语集处理定性评价信息;通过改进离差最大化法确定属性权重;根据Mo-RVIKOR对决策对象进行排序;最后以某公司C2B定制化服务质量评测项目为例,验证了所提方法的有效性。     

Authentic leadership and positive organizational behavior: A meso, multi-level perspective

Authentic leadership (AL) and positive organizational behavior (POB) are two important emerging approaches in the organizational sciences. To date, published work on AL and POB has been primarily leader-focused and based on individual differences. In this article, after verifying this individual-level focus via content coding of AL articles, AL and POB are explicated and integrated using a meso, multi-level perspective. Essentially, viewed in terms of multiple levels of analysis, AL promotes various multi-level “primary” criteria and outcomes of POB that, in turn, enhances various multi-level “secondary” criteria and outcomes of performance. Direct effects of AL on performance at multiple levels of analysis also are plausible. Implications for future meso perspectives on leadership theory and research in general and on AL and POB in particular are discussed.     

A fuzzy set approach for R&D portfolio selection using a real options valuation model

Making R&D portfolio decision is difficult, because long lead times of R&D and market and technology dynamics lead to unavailable and unreliable collected data for portfolio management. The objective of this research is to develop a fuzzy R&D portfolio selection model to hedge against the R&D uncertainty. Fuzzy set theory is applied to model uncertain and flexible project information. Since traditional project valuation methods often underestimate the risky project, a fuzzy compound-options model is used to evaluate the value of each R&D project. The R&D portfolio selection problem is formulated as a fuzzy zero–one integer programming model that can handle both uncertain and flexible parameters to determine the optimal project portfolio. A new transformation method based on qualitative possibility theory is developed to convert the fuzzy portfolio selection model into a crisp mathematical model from the risk-averse perspective. The transformed model can be solved by an optimization technique. An example is used to illustrate the proposed approach. We conclude that the proposed approach can assist decision makers in selecting suitable R&D portfolios, while there is a lack of reliable project information.     

The Termination of State-Run International Trade Programs in California: Perspectives on Contributing Factors and Future Policy Options

The paper examines developments that led to the termination of California’s major state-run international trade programs managed by the now defunct Technology, Trade and Commerce Agency and provides perspectives on future policy options. Study findings indicate that what the academic literature refers to as “theory failure” and “implementation failure,” along with deficiencies in leadership and organizational culture, must be seen as the major reasons for the programs’ elimination.     

基于后悔理论的混合型多属性案例决策方法

本文针对决策者的后悔规避行为对案例决策的影响,提出了一种基于后悔理论的混合型多属性案例决策方法。首先,针对案例属性的相似度测算,将案例属性的范围拓展到定性数据、清晰数、区间数、语言变量和区间直觉模糊数五种类型;然后,在案例原有效用基础上考虑决策者的后悔-欣喜值来测算各案例的感知效用;进一步,通过案例相似度对感知效用加权求和得到备选方案的综合感知效用,并依据综合感知效用大小对备选方案进行排序;最后通过一个实例,验证了上述方法的可行性和有效性。     

Towards a Fuzzy Bayesian Network Based Approach for Safety Risk Analysis of Tunnel‐Induced Pipeline Damage

Tunneling excavation is bound to produce significant disturbances to surrounding environments, and the tunnel‐induced damage to adjacent underground buried pipelines is of considerable importance for geotechnical practice. A fuzzy Bayesian networks (FBNs) based approach for safety risk analysis is developed in this article with detailed step‐by‐step procedures, consisting of risk mechanism analysis, the FBN model establishment, fuzzification, FBN‐based inference, defuzzification, and decision making. In accordance with the failure mechanism analysis, a tunnel‐induced pipeline damage model is proposed to reveal the cause‐effect relationships between the pipeline damage and its influential variables. In terms of the fuzzification process, an expert confidence indicator is proposed to reveal the reliability of the data when determining the fuzzy probability of occurrence of basic events, with both the judgment ability level and the subjectivity reliability level taken into account. By means of the fuzzy Bayesian inference, the approach proposed in this article is capable of calculating the probability distribution of potential safety risks and identifying the most likely potential causes of accidents under both prior knowledge and given evidence circumstances. A case concerning the safety analysis of underground buried pipelines adjacent to the construction of the Wuhan Yangtze River Tunnel is presented. The results demonstrate the feasibility of the proposed FBN approach and its application potential. The proposed approach can be used as a decision tool to provide support for safety assurance and management in tunnel construction, and thus increase the likelihood of a successful project in a complex project environment.     

A Novel Human Error Probability Assessment Using Fuzzy Modeling

Human error is one of the significant factors contributing to accidents. Traditional human error probability (HEP) studies based on fuzzy number concepts are one of the contributions addressing such a problem. It is particularly useful under circumstances where the lack of data exists. However, the degree of the discriminability of such studies may be questioned when applied under circumstances where experts have adequate information and specific values can be determined in the abscissa of the membership function of linguistic terms, that is, the fuzzy data of each scenario considered are close to each other. In this article, a novel HEP assessment aimed at solving such a difficulty is proposed. Under the framework, the fuzzy data are equipped with linguistic terms and membership values. By establishing a rule base for data combination, followed by the defuzzification and HEP transformation processes, the HEP results can be acquired. The methodology is first examined using a test case consisting of three different scenarios of which the fuzzy data are close to each other. The results generated are compared with the outcomes produced from the traditional fuzzy HEP studies using the same test case. It is concluded that the methodology proposed in this study has a higher degree of the discriminability and is capable of providing more reasonable results. Furthermore, in situations where the lack of data exists, the proposed approach is also capable of providing the range of the HEP results based on different risk viewpoints arbitrarily established as illustrated using a real‐world example.     

Just-in-time purchasing: an empirical study of operational practices, supplier development and performance

This paper examines the role of supplier development in establishing and managing efficient buyer–supplier operational links. The paper develops and assesses a measurement instrument for “operational” and “supplier development” just-in-time purchasing practices, followed by an examination of the relationships between the two sets, and an investigation into whether the use of “operational” and “supplier development” practices has a bearing on higher plant performance. A plant-level survey was carried out on a sample of electronics and machinery plants. The study empirically:

• documents the close connection between the buyer–supplier operational link and the buyer’s practices for supplier development;

• demonstrates that recourse to supplier development programs and their nature depend on the kind of vendor–vendee operational connection;

• test whether different plant performance outcomes result from the implementing of different “operational” and “supplier development” practices. It demonstrates that better-performing plants exhibit more advanced design and logistic links with sources, more formalised vendor-rating and ranking procedures, greater use of organisational devices for supplier-organisational integration and place greater importance on supplier assistance and training.

Political leaders in the SYMLOG space: Perceptions of right and left wing leaders by right and left wing constituencies

Systematic Multiple Level Observation of Groups (SYMLOG) was applied to studying images of political leaders. Three left wing and three right wing Israeli leaders were evaluated by left and right wing voters along the SYMLOG's three dimensions—friendliness, task orientation, and dominance. It was found that right wing voters rated right wing leaders higher on friendliness and task orientation than left wing leaders. In a similar fashion, left wing voters viewed left wing leaders as more friendly and task-oriented than right wing leaders. Leaders of the right were viewed as more dominant than leaders of the left by left and right wing voters alike. Right and left wing voters assigned different SYMLOG types to right and left wing leaders. The dimension that distinguished between the various images was the dimension of friendliness. Whereas for right wing voters, all images of right wing leaders included a component of friendliness, none of these three images included an accented component of friendliness when rated by left wing voters. In a similar fashion, left wing voters saw two out of the three left wing leaders as including a component of friendliness, whereas none of the three left wing images included this component for right wing voters. Respondents from the right and the left rated their “ideal leader” as reflecting values of “dominance”, “friendliness,” and “task-orientation”. However, respondents saw leaders affiliated with their own political camp as closer to their image of the ideal leader on friendliness and task-orientation than leaders of the opposite political camp. Both right and left wing voters saw all political leaders as equally similar to their image of “ideal leader” on the “dominance” dimension regardless of that leader's political affiliation.     

On solutions that are better than most

A programmatic approach to solving decision problems by the use of ‘better than most’ (BTM) solutions is introduced. The BTM approach is contrasted to approaches that seek a solution whose outcome would be the best of all outcomes for feasible solutions, again according to criteria taken to represent the decision maker's objectives. This BTM approach is illustrated in terms of a decision problem in binary decision variables. This is followed by a discussion of (1) some of the probabilistic aspects of BTM solutions, including calculational experience, (2) a central BTM problem, akin to the problem of finding optimal methods in the more traditional approaches, (3) some ad hoc methods for overcoming this and other problems associated with the BTM approach, and (4) similarities and differences between the BTM approach and other approaches.