Uncertainty analysis in product service system: Bayesian network modelling for availability contract

There is an emerging trend of manufacturing companies offering combined products and services to customers as integrated solutions. Availability contracts are an apt instance of such offerings, where product use is guaranteed to customer and is enforced by incentive-penalty schemes. Uncertainties in such an industry setting, where all stakeholders are striving to achieve their respective performance goals and at the same time collaborating intensively, is increased. Understanding through-life uncertainties and their impact on cost is critical to ensure sustainability and profitability of the industries offering such solutions. In an effort to address this challenge, the aim of this research study is to provide an approach for the analysis of uncertainties in Product Service System (PSS) delivered in business-to-business application by specifying a procedure to identify, characterise and model uncertainties with an emphasis to provide decision support and prioritisation of key uncertainties affecting the performance outcomes. The thesis presents a literature review in research areas which are at the interface of topics such as uncertainty, PSS and availability contracts. From this seven requirements that are vital to enhance the understanding and quantification of uncertainties in Product Service System are drawn. These requirements are synthesised into a conceptual uncertainty framework. The framework prescribes four elements, which include identifying a set of uncertainties, discerning the relationships between uncertainties, tools and techniques to treat uncertainties and finally, results that could ease uncertainty management and analysis efforts. The conceptual uncertainty framework was applied to an industry case study in availability contracts, where each of the four elements was realised. This application phase of the research included the identification of uncertainties in PSS, development of a multi-layer uncertainty classification, deriving the structure of Bayesian Network and finally, evaluation and validation of the Bayesian Network. The findings suggest that understanding uncertainties from a system perspective is essential to capture the network aspect of PSS. This network comprises of several stakeholders, where there is increased flux of information and material flows and this could be effectively represented using Bayesian Networks

What Turkey expects from logistics outsourcing ?

Copyright @ 2011 Yasar UniversityThe economies of the world have become increasingly interdependent, and organizations have come under tremendous pressure to maximize productivity and profitability. Creating value through outsourcing has emerged as a popular competitive strategy for firms of all sizes in all types of industries. The aim of this research is to investigate the use of third party logistics in Turkish companies from the users’ perspective to identify the types of logistics services outsourced, problems encountered in outsourcing these services, logistics costs, decision makers in outsourcing logistics activities, and information sources used in the decision-making process. A structured survey was selected as the tool for data collection. The field study involved face-to-face interviews with 204 companies out of top 500 companies ranked in terms of turnover that are registered with industrial associations and chambers of commerce in Turkey. Moreover, a decision support system based on Bayesian Causal Map is proposed for 3PLs in order to assist them in their service proposals for different sectors. This study is a first attempt to reveal and compare the outsourcing perception of the companies in different sectors, to expose the firms’ underlying motives as well as the respective importance of these motives for outsourcing logistics activities in Turkey. The use of Bayesian Causal Map based on the survey results provides an important guide to the 3PL providers to pick a suitable strategy and to prioritize their operational activities in different sectors in such a way to achieve a competitive advantage

Efficiency and University Size: Discipline-wise Evidence from European Universities

Strategic management of universities must build the best possible relation between inputs and outputs. One relevant question, in this perspective, is whether the unit is making the best use of existing resources, or whether technical efficiency is in place. Here we address the question of technical efficiency with respect to university’s size. The crucial concept in this analysis is conditional efficiency and the ratio of size-conditional to unconditional efficiency measures. In particular we take use of robust order-m efficiency scores presented in Cazals, Florens and Simar (2002) and generalized in Daraio and Simar (2005a,b) to analyze data from four European countries and four different research fields. Our results are still explorative and mainly show how heterogeneous international datasets could be used to analyze productivity differences.Universities;efficiency;International comparisons

Unobserved Heterogeneity: Evidence and Implications for SMEs' Hedging Behavior

Financial research indicates that several firm characteristics are related to the use of derivatives. Less attention has been paid to the role of the characteristics of managers, which are particularly important when studying derivative usage of small and medium sized enterprises (SMEs). In this paper we focus on the influence of manager's level of education, the manager's decision-making unit, and the fundamental determinants of risk management - managerial risk attitude and managerial risk perception - on SMEs' commodity derivative usage. In empirical studies to date, the heterogeneity of derivative users has been neglected. We propose a generalized mixture regression model that estimates the relationship between commodity derivative usage and a set of explanatory variables across segments of an industry. Accounting for unobserved heterogeneity reveals that segments of the industry have different determinants of derivative use. Moreover, the heterogeneity at the segment level appears to mask significant effects at the aggregate level, most notably the effects of risk attitude and risk perception.Marketing,

Comprehensive Security Framework for Global Threats Analysis

Cyber criminality activities are changing and becoming more and more professional. With the growth of financial flows through the Internet and the Information System (IS), new kinds of thread arise involving complex scenarios spread within multiple IS components. The IS information modeling and Behavioral Analysis are becoming new solutions to normalize the IS information and counter these new threads. This paper presents a framework which details the principal and necessary steps for monitoring an IS. We present the architecture of the framework, i.e. an ontology of activities carried out within an IS to model security information and User Behavioral analysis. The results of the performed experiments on real data show that the modeling is effective to reduce the amount of events by 91%. The User Behavioral Analysis on uniform modeled data is also effective, detecting more than 80% of legitimate actions of attack scenarios

Quality Risk and Profitability in Cattle Production: A Multivariate Approach

This study evaluates quality, production, and price risk within the context of overall profit variability in fed cattle production. The approach used offers a flexible way to estimate a large system of equations with more than three jointly related censored outcomes. Trade-offs between quality and yield grade levels and production measures, such as average daily gain and feeding efficiency, are evaluated. Simulation procedures are used to assess the impact of quality risk on overall profit variability. Results make an important contribution to existing research by explaining why price signals through grid quality grade premiums may not generate intended producer responses.censoring, copula, fed cattle, grid pricing, multivariate, quality risk, Livestock Production/Industries,

Automatic Software Repair: a Bibliography

This article presents a survey on automatic software repair. Automatic software repair consists of automatically finding a solution to software bugs without human intervention. This article considers all kinds of repairs. First, it discusses behavioral repair where test suites, contracts, models, and crashing inputs are taken as oracle. Second, it discusses state repair, also known as runtime repair or runtime recovery, with techniques such as checkpoint and restart, reconfiguration, and invariant restoration. The uniqueness of this article is that it spans the research communities that contribute to this body of knowledge: software engineering, dependability, operating systems, programming languages, and security. It provides a novel and structured overview of the diversity of bug oracles and repair operators used in the literature

Modeling and Robust Design of Networks under Risk: The Case of Information Infrastructure

Study of network risks allows to develop insights into the methods of building robust networks, which are also critical elements of infrastructures that are of a paramount importance for the modern society. In this paper we show how the modern quantitative modeling methodologies can be employed for analysis of network risks and for design of robust networks under uncertainty. This is done on the example of important problem arising in the process of building of the information infrastructure: provision of advanced mobile data services. We show how portfolio theory developed in the modern finance can be used for design of robust provision network comprising of independent agents. After this the modeling frameworks of Bayesian nets andMarkov fields are used for the study of several problems fundamental for the process of service adoption such as the sensitivity of networks, the direction of improvements, and the propagation of user attitudes on social networks