The reasonant influence of supply chain management practices on organizational performance

A single supply chain management (SCM) practice will have a certain impact on organizational performance(OP). However, since it is placed in a system that many other practices are conducted simultaneously, the practice itself will interact with other ones and have a greater impact on OP. This mechanism is named the "resonant" influence. The technique of Structural equation modelling (SEM) was used to test the above mechanism with data collected from Vietnamese garment enterprises. The tcst results showed that the model without mutual interaction among SCM practices could explain 42.8%, 26.3% and 34% variance of operational performance, customer satisfaction and financial performance. While the one containing this interaction is capable to explain 69.5%, 33.1% and 57.3%, respectively.

Corporate Performance Management através da integração de Business Intelligence e Business Process Management

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Development of an intelligent earthwork optimization system

Tese de Doutoramento em Engenharia Civil.

An emperical study of performance management systems in SMEs in the Republic of Ireland and the People's Republic of China : a cultural perspective

The objectives of this thesis are three. Firstly, finding and analyzing the differences of performance management system in SMEs in Ireland and China. Secondly, finding the cultural differences between China and Ireland and thirdly, integrating the research outcomes of the above research objectives, and then analyzing the effect of these cultural differences on performance management system in SMEs in China and Ireland.

Analysis, design, optimization and realization of compact high performance printed RF filters

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2010

Moderating effects of management control systems and innovation on performance. Simple methods for correcting the effects of measurement error for interaction effects in small samples

In the accounting literature, interaction or moderating effects are usually assessed by means of OLS regression and summated rating scales are constructed to reduce measurement error bias. Structural equation models and two-stage least squares regression could be used to completely eliminate this bias, but large samples are needed. Partial Least Squares are appropriate for small samples but do not correct measurement error bias. In this article, disattenuated regression is discussed as a small sample alternative and is illustrated on data of Bisbe and Otley (in press) that examine the interaction effect of innovation and style of use of budgets on performance. Sizeable differences emerge between OLS and disattenuated regression

The performance of laboratory tests in the management of a large outbreak of orally transmitted Chagas disease

Orally transmitted Chagas disease (ChD), which is a well-known entity in the Brazilian Amazon Region, was first documented in Venezuela in December 2007, when 103 people attending an urban public school in Caracas became infected by ingesting juice that was contaminated with Trypanosoma cruzi. The infection occurred 45-50 days prior to the initiation of the sampling performed in the current study. Parasitological methods were used to diagnose the first nine symptomatic patients; T. cruzi was found in all of them. However, because this outbreak was managed as a sudden emergency during Christmas time, we needed to rapidly evaluate 1,000 people at risk, so we decided to use conventional serology to detect specific IgM and IgG antibodies via ELISA as well as indirect haemagglutination, which produced positive test results for 9.1%, 11.9% and 9.9% of the individuals tested, respectively. In other more restricted patient groups, polymerase chain reaction (PCR) provided more sensitive results (80.4%) than blood cultures (16.2%) and animal inoculations (11.6%). Although the classical diagnosis of acute ChD is mainly based on parasitological findings, highly sensitive and specific serological techniques can provide rapid results during large and severe outbreaks, as described herein. The use of these serological techniques allows prompt treatment of all individuals suspected of being infected, resulting in reduced rates of morbidity and mortality.

Iowa Department of Management Agency Performance Plan

Agency Performance Plan

Optimization of floor cleaning coverage performance of a random path-planning mobile robot

Floor cleaning is a typical robot application. There are several mobile robots aviable in the market for domestic applications most of them with random path-planning algorithms. In this paper we study the cleaning coverage performances of a random path-planning mobile robot and propose an optimized control algorithm, some methods to estimate the are of the room, the evolution of the cleaning and the time needed for complete coverage.

Iowa Homeland Security & Emergency Management Division Performance Report, FY 2005

Agency Performance Report

Materials and Mix Optimization Procedures for PCC Pavements, March 2006

Severe environmental conditions, coupled with the routine use of deicing chemicals and increasing traffic volume, tend to place extreme demands on portland cement concrete (PCC) pavements. In most instances, engineers have been able to specify and build PCC pavements that met these challenges. However, there have also been reports of premature deterioration that could not be specifically attributed to a single cause. Modern concrete mixtures have evolved to become very complex chemical systems. The complexity can be attributed to both the number of ingredients used in any given mixture and the various types and sources of the ingredients supplied to any given project. Local environmental conditions can also influence the outcome of paving projects. This research project investigated important variables that impact the homogeneity and rheology of concrete mixtures. The project consisted of a field study and a laboratory study. The field study collected information from six different projects in Iowa. The information that was collected during the field study documented cementitious material properties, plastic concrete properties, and hardened concrete properties. The laboratory study was used to develop baseline mixture variability information for the field study. It also investigated plastic concrete properties using various new devices to evaluate rheology and mixing efficiency. In addition, the lab study evaluated a strategy for the optimization of mortar and concrete mixtures containing supplementary cementitious materials. The results of the field studies indicated that the quality management concrete (QMC) mixtures being placed in the state generally exhibited good uniformity and good to excellent workability. Hardened concrete properties (compressive strength and hardened air content) were also satisfactory. The uniformity of the raw cementitious materials that were used on the projects could not be monitored as closely as was desired by the investigators; however, the information that was gathered indicated that the bulk chemical composition of most materials streams was reasonably uniform. Specific minerals phases in the cementitious materials were less uniform than the bulk chemical composition. The results of the laboratory study indicated that ternary mixtures show significant promise for improving the performance of concrete mixtures. The lab study also verified the results from prior projects that have indicated that bassanite is typically the major sulfate phase that is present in Iowa cements. This causes the cements to exhibit premature stiffening problems (false set) in laboratory testing. Fly ash helps to reduce the impact of premature stiffening because it behaves like a low-range water reducer in most instances. The premature stiffening problem can also be alleviated by increasing the water–cement ratio of the mixture and providing a remix cycle for the mixture.

Iowa Department of Management Agency Performance Plan, 2007

Agency Performance Plan

A randomized concave programming method for choice network revenue management

Models incorporating more realistic models of customer behavior, as customers choosing froman offer set, have recently become popular in assortment optimization and revenue management.The dynamic program for these models is intractable and approximated by a deterministiclinear program called the CDLP which has an exponential number of columns. However, whenthe segment consideration sets overlap, the CDLP is difficult to solve. Column generationhas been proposed but finding an entering column has been shown to be NP-hard. In thispaper we propose a new approach called SDCP to solving CDLP based on segments and theirconsideration sets. SDCP is a relaxation of CDLP and hence forms a looser upper bound onthe dynamic program but coincides with CDLP for the case of non-overlapping segments. Ifthe number of elements in a consideration set for a segment is not very large (SDCP) can beapplied to any discrete-choice model of consumer behavior. We tighten the SDCP bound by(i) simulations, called the randomized concave programming (RCP) method, and (ii) by addingcuts to a recent compact formulation of the problem for a latent multinomial-choice model ofdemand (SBLP+). This latter approach turns out to be very effective, essentially obtainingCDLP value, and excellent revenue performance in simulations, even for overlapping segments.By formulating the problem as a separation problem, we give insight into why CDLP is easyfor the MNL with non-overlapping considerations sets and why generalizations of MNL posedifficulties. We perform numerical simulations to determine the revenue performance of all themethods on reference data sets in the literature.

A new compact linear programming formulation for choice network revenue management

The choice network revenue management model incorporates customer purchase behavioras a function of the offered products, and is the appropriate model for airline and hotel networkrevenue management, dynamic sales of bundles, and dynamic assortment optimization.The optimization problem is a stochastic dynamic program and is intractable. A certainty-equivalencerelaxation of the dynamic program, called the choice deterministic linear program(CDLP) is usually used to generate dyamic controls. Recently, a compact linear programmingformulation of this linear program was given for the multi-segment multinomial-logit (MNL)model of customer choice with non-overlapping consideration sets. Our objective is to obtaina tighter bound than this formulation while retaining the appealing properties of a compactlinear programming representation. To this end, it is natural to consider the affine relaxationof the dynamic program. We first show that the affine relaxation is NP-complete even for asingle-segment MNL model. Nevertheless, by analyzing the affine relaxation we derive a newcompact linear program that approximates the dynamic programming value function betterthan CDLP, provably between the CDLP value and the affine relaxation, and often comingclose to the latter in our numerical experiments. When the segment consideration sets overlap,we show that some strong equalities called product cuts developed for the CDLP remain validfor our new formulation. Finally we perform extensive numerical comparisons on the variousbounds to evaluate their performance.