Evaluation of Corporate Sustainability

As a consequence of an increasing demand in sustainable development for business organizations, the evaluation of corporate sustainability has become a topic intensively focused by academic researchers and business practitioners. Several techniques in the context of multiple criteria decision analysis (MCDA) have been suggested to facilitate the evaluation and the analysis of sustainability performance. However, due to the complexity of evaluation, such as a compilation of quantitative and qualitative measures, interrelationships among various sustainability criteria, the assessor’s hesitation in scoring, or incomplete information, simple techniques may not be able to generate reliable results which can reflect the overall sustainability performance of a company. This paper proposes a series of mathematical formulations based upon the evidential reasoning (ER) approach which can be used to aggregate results from qualitative judgments with quantitative measurements under various types of complex and uncertain situations. The evaluation of corporate sustainability through the ER model is demonstrated using actual data generated from three sugar manufacturing companies in Thailand. The proposed model facilitates managers in analysing the performance and identifying improvement plans and goals. It also simplifies decision making related to sustainable development initiatives. The model can be generalized to a wider area of performance assessment, as well as to any cases of multiple criteria analysis

Estimation of indirect cost and evaluation of protective measures for infrastructure vulnerability: A case study on the transalpine transport corridor

Infrastructure vulnerability is a topic of rising interest in the scientific literature for both the general increase of unexpected events and the strategic importance of certain links. Protective investments are extremely costly and risks are distributed in space and time which poses important decision problems to the public sector decision makers. In an economic prospective, the evaluation of infrastructure vulnerability is oriented on the estimation of direct and indirect costs of hazards. Although the estimation of direct costs is straightforward, the evaluation of indirect cost involves factors non-directly observable making the approximation a difficult issue. This paper provides an estimate of the indirect costs caused by a two weeks closure of the north-south Gotthard road corridor, one of the most important infrastructure links in Europe, and implements a cost-benefit analysis tool that allows the evaluation of measures ensuring a full protection along the corridor. The identification of the indirect cost relies on the generalized cost estimation, which parameters come from two stated preference experiments, the first based on actual condition whereas the second assumes a road closure. The procedure outlined in this paper proposes a methodology aimed to identify and quantify the economic vulnerability associated with a road transport infrastructure and, to evaluate the economic and social efficiency of a vulnerability reduction by the consideration of protective measures.infrastructure vulnerability, choice experiment, cost-benefit analysis, freight transport

Difficulties in Career Decision Making and Self-Evaluations: A Meta-Analysis

This meta-analysis examined the association between two types of difficulties in career decision making—indecision and indecisiveness—and four types of self-evaluations: generalized self-efficacy, process-related self-efficacy, content-related self-efficacy, and self-esteem. Analyses were conducted on data from 86 studies (N ¼ 54,160): Process-related self-efficacy showed stronger negative associations with career indecision than did generalized self-efficacy, content-related self-efficacy, or self-esteem. In contrast, self-esteem showed stronger negative associations with indecisiveness than with career indecision. The second part of this meta-analysis focused on differential associations between two types of self-evaluations (process-related self-efficacy and self-esteem) and the three major clusters of difficulties in career decision making (lack of readiness, lack of information, and inconsistent information). Based on 19 studies (N ¼ 7,953), the findings showed that process-related self-efficacy was strongly and negatively associated with lack of information and inconsistent information. In contrast, self-esteem was only weakly related to the three major clusters of difficulties in career decision making. In showing that each type of self-evaluation was more strongly associated with certain types and causes of difficulties in career decision making, the present article highlighted the importance of self-evaluations in the career decision-making process

Visual Analytics Evaluation Based on Judgment Analysis Theory

In this paper we propose a framework to quantitatively evaluate user awareness and the level of support that visual analytics decision support systems (VADS) provide. For the framework, which has a theoretical underpinning from the field of judgement analysis, we propose a model for VADS system. The framework bridges the gap between judgment analysis and VADS evaluation by conceptually connecting judgment analysis concepts to visual analytic. The proposed approach offers an insights based evaluation to measure the importance and the utility of the insights. We propose to model insights and user findings as random variables that parametrize user decisions. The mixed methodology used in our framework has the potential to study user decision process in real situations while producing results that can be generalized. Our contributions in this work appear in the modeling of VADS system and the evaluation framework we propose which quantifies situation awareness. Other advantages include evaluating collaboration and analyzing joint decisions. Some limitations of the framework are also discussed including the requirement of large testing data

HFMADM method based on nondimensionalization and its application in the evaluation of inclusive growth

Inclusive growth, which encompasses different aspects of life, is a growth pattern that allows all people to participate in and contribute to growth process. In this paper, a novel hesitant fuzzy multiple attribute decision making (HFMADM) approach based on the nondimensionalization of decision making attributes is presented and then applied to the evaluation of inclusive growth in China. Firstly, a novel generalized hesitant fuzzy distance measure is proposed to calculate the difference and deviation between two hesitant fuzzy elements (hfes) without adding any values into the shorter hesitant fuzzy element. Secondly, the coefficient of variation and efficacy coefficient method are extended to accommodate hesitant fuzzy environment and then used to cope with HFMADM. In the analysis process, non-dimensional treatment for hesitant fuzzy decision data is produced. Lastly, the method proposed in this paper is applied to an example of inclusive growth evaluation problem under hesitant fuzzy environment and the case study illustrates the practicality of the proposed method. Beyond that, a comparative analysis with some other approaches is also conducted to demonstrate the superiority and feasibility of the proposed method

IT&C AND THE PERSONAL DEVELOPMENT

In this paper I explore the phenomenon of personal development in an "unconventional" way. The contribution of this paper is to use a different method (i.e. in -depth interviews) to focus on a different unit of analysis (i.e. managerial couples) in a different context. In addition the information and communication technologies (IT&C) are entering all the fields: business, state institutions, education and the day-by-day life. This paper contributes to the field by suggesting a different theoretical approach to personal development conflict as a decision-making problem. I propose using social exchange theory to explain personal development conflict as a complex evaluation of cost and benefits of exchanges between multiple actors on the basis of personal values and beliefs. The critical thinking is one of the most popular learning objects in the English speaking countries and they are also offering most of hopes to distance learning and also the critical thinking is a reflective one. This paper suggests that the field may be overlooking some fundamental variables. Content analysis of the interview transcripts reveals the crucial importance of implicit values and benefits, immanent or tacit actions such as decision-making and learning and communication and mutual understanding. Communication and personal development is essential in this respect. It's difficult to separate work, family and personal development and communication is fundamental in all directions. To conceptualize personal development conflict as a decision-making problem while taking into account exchanges and interactions between multiple actors and we can draw on equity theory or social exchange theory.Future research should test whether decision making is central for the understanding of personal conflict only in managers or in other collectives as well. I recommend the couple as the best unit of analysis to address issues such as accommodation within couples and complex decision- making in both individuals and couples. Future research should draw on boarder and different samples to replicate our study and check the generalizability of its findings - because if it can be generalized it may have strong implication for theoretical development.e-learning, critical thinking, IT training

M-generalised q-neutrosophic extension of CoCoSo method

Nowadays fuzzy approaches gain popularity to model multi-criteria decision making (MCDM) problems emerging in real-life applications. Modern modelling trends in this field include evaluation of the criteria information uncertainty and vagueness. Traditional neutrosophic sets are considered as the effective tool to express uncertainty of the information. However, in some cases, it cannot cover all recently proposed cases of the fuzzy sets. The m-generalized q-neutrosophic sets (mGqNNs) can effectively deal with this situation. The novel MCDM methodology CoCoSomGqNN is presented in this paper. An illustrative example presents the analysis of the effectiveness of different retrofit strategy selection decisions for the application in the civil engineering industry

How to Assess the Value of Medicines?

This study aims to discuss approaches to assessing the value of medicines. Economic evaluation assesses value by means of the incremental cost-effectiveness ratio (ICER). Health is maximized by selecting medicines with increasing ICERs until the budget is exhausted. The budget size determines the value of the threshold ICER and vice versa. Alternatively, the threshold value can be inferred from pricing/reimbursement decisions, although such values vary between countries. Threshold values derived from the value-of-life literature depend on the technique used. The World Health Organization has proposed a threshold value tied to the national GDP. As decision makers may wish to consider multiple criteria, variable threshold values and weighted ICERs have been suggested. Other approaches (i.e., replacement approach, program budgeting and marginal analysis) have focused on improving resource allocation, rather than maximizing health subject to a budget constraint. Alternatively, the generalized optimization framework and multi-criteria decision analysis make it possible to consider other criteria in addition to value

When Decision Meets Estimation: Theory and Applications

In many practical problems, both decision and estimation are involved. This dissertation intends to study the relationship between decision and estimation in these problems, so that more accurate inference methods can be developed. Hybrid estimation is an important formulation that deals with state estimation and model structure identification simultaneously. Multiple-model (MM) methods are the most widelyused tool for hybrid estimation. A novel approach to predict the Internet end-to-end delay using MM methods is proposed. Based on preliminary analysis of the collected end-to-end delay data, we propose an off-line model set design procedure using vector quantization (VQ) and short-term time series analysis so that MM methods can be applied to predict on-line measurement data. Experimental results show that the proposed MM predictor outperforms two widely used adaptive filters in terms of prediction accuracy and robustness. Although hybrid estimation can identify model structure, it mainly focuses on the estimation part. When decision and estimation are of (nearly) equal importance, a joint solution is preferred. By noticing the resemblance, a new Bayes risk is generalized from those of decision and estimation, respectively. Based on this generalized Bayes risk, a novel, integrated solution to decision and estimation is introduced. Our study tries to give a more systematic view on the joint decision and estimation (JDE) problem, which we believe the work in various fields, such as target tracking, communications, time series modeling, will benefit greatly from. We apply this integrated Bayes solution to joint target tracking and classification, a very important topic in target inference, with simplified measurement models. The results of this new approach are compared with two conventional strategies. At last, a surveillance testbed is being built for such purposes as algorithm development and performance evaluation. We try to use the testbed to bridge the gap between theory and practice. In the dissertation, an overview as well as the architecture of the testbed is given and one case study is presented. The testbed is capable to serve the tasks with decision and/or estimation aspects, and is helpful for the development of the JDE algorithms

When Decision Meets Estimation: Theory and Applications

In many practical problems, both decision and estimation are involved. This dissertation intends to study the relationship between decision and estimation in these problems, so that more accurate inference methods can be developed. Hybrid estimation is an important formulation that deals with state estimation and model structure identification simultaneously. Multiple-model (MM) methods are the most widelyused tool for hybrid estimation. A novel approach to predict the Internet end-to-end delay using MM methods is proposed. Based on preliminary analysis of the collected end-to-end delay data, we propose an off-line model set design procedure using vector quantization (VQ) and short-term time series analysis so that MM methods can be applied to predict on-line measurement data. Experimental results show that the proposed MM predictor outperforms two widely used adaptive filters in terms of prediction accuracy and robustness. Although hybrid estimation can identify model structure, it mainly focuses on the estimation part. When decision and estimation are of (nearly) equal importance, a joint solution is preferred. By noticing the resemblance, a new Bayes risk is generalized from those of decision and estimation, respectively. Based on this generalized Bayes risk, a novel, integrated solution to decision and estimation is introduced. Our study tries to give a more systematic view on the joint decision and estimation (JDE) problem, which we believe the work in various fields, such as target tracking, communications, time series modeling, will benefit greatly from. We apply this integrated Bayes solution to joint target tracking and classification, a very important topic in target inference, with simplified measurement models. The results of this new approach are compared with two conventional strategies. At last, a surveillance testbed is being built for such purposes as algorithm development and performance evaluation. We try to use the testbed to bridge the gap between theory and practice. In the dissertation, an overview as well as the architecture of the testbed is given and one case study is presented. The testbed is capable to serve the tasks with decision and/or estimation aspects, and is helpful for the development of the JDE algorithms