Towards strategic-decision quality in Flemish municipalities: the importance of strategic planning and stakeholder participation

Legislation put forth by the Flemish government mandated Flemish municipalities to adopt strategic planning for their 2014-2019 policy cycle. The government’s assumption is that strategic planning’s approach to decision-making results in strategic-decision quality. Despite this assumption, it remains unclear whether and how strategic planning actually contributes to municipal decision-making. This study elucidates this issue. Drawing on survey data from 271 informants within 89 Flemish municipalities, we find that the systematic dimension of formal strategic planning and the participation of both core and peripheral stakeholders contribute to strategic-decision quality. However, the analytic dimension of formal strategic planning offers no significant contribution

An Overview of Human Reliability Analysis Techniques in Manufacturing Operations

In recent years, there has been a decrease in accidents due to technical failures through technological developments of redundancy and protection, which have made systems more reliable. However, it is not possible to talk about system reliability without addressing the failure rate of all its components; among these components, "man" – because his rate of error changes the rate of failure of components with which he interacts. It is clear that the contribution of the human factor in the dynamics of accidents – both statistically and in terms of severity of consequences – is high [2]. Although valid values are difficult to obtain, estimates agree that errors committed by man are responsible for 60–90% of the accidents; the remainder of accidents are attributable to technical deficiencies [2,3,4]. The incidents are, of course, the most obvious human errors in industrial systems, but minor faults can seriously reduce the operations performances, in terms of productivity and efficiency. In fact, human error has a direct impact on productivity because errors affect the rates of rejection of the product, thereby increasing the cost of production and possibly reduce subsequent sales. Therefore, there is need to assess human reliability to reduce the likely causes of errors [1]. The starting point of this work was to study the framework of today’s methods of human reliability analysis (HRA): those quantitative of the first generation (as THERP and HCR), those qualitative of second (as CREAM and SPAR-H), and new dynamic HRA methods and recent improvements of individual phases of HRA approaches. These methods have, in fact, the purpose of assessing the likelihood of human error – in industrial systems, for a given operation, in a certain interval of time and in a particular context – on the basis of models that describe, in a more or less simplistic way, the complex mechanism that lies behind the single human action that is potentially subject to error [1]. The concern in safety and reliability analyses is whether an operator is likely to make an incorrect action and which type of action is most likely [5]. The goals defined by Swain and Guttmann (1983) in discussing the THERP approach, one of the first HRA methods developed, are still valid: The objective of a human reliability analysis is ‘to evaluate the operator’s contribution to system reliability’ and, more precisely, ‘to predict human error rates and to evaluate the degradation to human–machine systems likely to be caused by human errors in association with equipment functioning, operational procedures and practices, and other system and human characteristics which influence the system behavior’ [7]. The different HRA methods analysed allowed us to identify guidelines for determining the likelihood of human error and the assessment of contextual factors. The first step is to identify a probability of human error for the operation to be performed, while the second consists of the evaluation through appropriate multipliers, the impact of environmental, and the behavioural factors of this probability [1]. The most important objective of the work will be to provide a simulation module for the evaluation of human reliability that must be able to be used in a dual manner [1]: In the preventive phase, as an analysis of the possible situation that may occur and as evaluation of the percentage of pieces discarded by the effect of human error; In post-production, to understand what are the factors that influence human performance so they can reduce errors. The tool will also provide for the possibility of determining the optimal configuration of breaks through use of a methodology that, with assessments of an economic nature, allow identification of conditions that, in turn, is required for the suspension of work for psychophysical recovery of the operator and then for the restoration of acceptable values of reliability [1]

Human reliability analysis: exploring the intellectual structure of a research field

Humans play a crucial role in modern socio-technical systems. Rooted in reliability engineering, the discipline of Human Reliability Analysis (HRA) has been broadly applied in a variety of domains in order to understand, manage and prevent the potential for human errors. This paper investigates the existing literature pertaining to HRA and aims to provide clarity in the research field by synthesizing the literature in a systematic way through systematic bibliometric analyses. The multi-method approach followed in this research combines factor analysis, multi-dimensional scaling, and bibliometric mapping to identify main HRA research areas. This document reviews over 1200 contributions, with the ultimate goal of identifying current research streams and outlining the potential for future research via a large-scale analysis of contributions indexed in Scopus database

AFWAL space control technology program

An overview of space oriented control technology programs which are applicable to flexible large space structures is presented. The spacecraft control activity is interdisciplinary with activities in structures, structural dynamics and control brought together. The large flexible structures to be controlled have many physical factors that influence the final controllability of the vehicle. Factors are studied such as rigidity of both structural elements and joints, damping inherent in both material as well as discrete dampers located throughout the structure, and the bandwidth of both sensors and actuators used to sense motion and control it. Descriptions of programs both in-house and contracted are given

Strategic Rethinking: Combination of Balanced Scorecard-based Approach and Fuzzy Analytic Network Process to Enhance the Education Quality

Educational providers should monitor and measure their performance continuously, in terms of delivering qualified education to the students and to improve their accountability. Although the importance of such an assessment process has been stressed in the literatures, policies and regulations, there is no framework that has been proposed to consider all the different relevant factors and determines semantically the level of the quality of education being delivered. In order to provide such an approach, in this paper we propose a framework by which the quality of education being delivered in a subject in an Indonesian university can be determined by using the Balanced Scorecard (BSC). The proposed approach will capture the different factors to be considered from the different perspectives and assimilate them to determine the quality of education. The resultant analysis will provide important inputs to the different stakeholders involved in taking appropriate measures to ensure that students\u27 learning experiences can be maintained at a certain desired level

A decision support methodology to enhance the competitiveness of the Turkish automotive industry

This is the post-print (final draft post-refereeing) version of the article. Copyright @ 2013 Elsevier B.V. All rights reserved.Three levels of competitiveness affect the success of business enterprises in a globally competitive environment: the competitiveness of the company, the competitiveness of the industry in which the company operates and the competitiveness of the country where the business is located. This study analyses the competitiveness of the automotive industry in association with the national competitiveness perspective using a methodology based on Bayesian Causal Networks. First, we structure the competitiveness problem of the automotive industry through a synthesis of expert knowledge in the light of the World Economic Forum’s competitiveness indicators. Second, we model the relationships among the variables identified in the problem structuring stage and analyse these relationships using a Bayesian Causal Network. Third, we develop policy suggestions under various scenarios to enhance the national competitive advantages of the automotive industry. We present an analysis of the Turkish automotive industry as a case study. It is possible to generalise the policy suggestions developed for the case of Turkish automotive industry to the automotive industries in other developing countries where country and industry competitiveness levels are similar to those of Turkey

Balanced Scorecard-Based Approach to Ascertain the Quality of Education

Educational Providers should continually monitor and measure their performance in terms of delivering quality education to the students. Although the importance of such an assessment process has been stressed in the literature, no framework has been proposed that considers all the different relevant factors and determines semantically the level of the quality of education being delivered. In order to provide such an approach, in this paper we propose a framework by which the quality of education being delivered in a subject in an Indonesian university can be determined by using the Balanced Scorecard (BSC). The proposed approach will capture the different factors to be considered from the different perspectives and assimilate them to determine the quality of education. The resultant analysis will provide important inputs to the different stakeholders involved in taking appropriate measures to ensure that students' learning experiences can be maintained at a certain desired level