ENBIS: European Network for Business and Industrial Statistics
Forgotten your password?
Not yet a member? Please register
ENBIS-8 in Athens
21 – 25 September 2008 Abstract submission: 14 March – 11 August 2008The following abstracts have been accepted for this event:
-
On t and EWMA t Charts for Monitoring Changes in the Process Mean
Authors: Philippe CASTAGLIOLA (1), Gemai CHEN (2), Lingyun ZHANG (2)
Affiliation: (1) Université de Nantes & IRCCyN UMR CNRS 6597, Carquefou, France, (2) University of Calgary, Calgary, Alberta, T2N 1N4, Canada
Primary area of focus / application:
-
Common terminology as a pre-requisite for a common use in international standardisation of basic concepts for expressing measurement uncertainty in metrology and testing
Authors: Franco Pavese
Affiliation: INRIM, Torino, Italy
Primary area of focus / application:
Keywords: Meteorology, Measurement Uncertainty
Submitted at 28-Apr-2008 09:30 by Franco Pavese
Accepted
It is supposed to address especially the users in laboratories at the field level in either industry or services (food, health, biology, pharmaceutical labs, environment, calibration, etc.), to help in understanding some of the differences occurring between written standards and also, when the case, to warn about possible misunderstandings. -
Latent Class Models for Marketing Strategies: an Application to Promotion in the Pharmaceutical Sector
Authors: Francesca Bassi
Affiliation: University of Padova, Italy
Primary area of focus / application:
Submitted at 28-Apr-2008 12:21 by Francesca Bassi
Accepted
LC models for multilevel data were applied in order to identify market segments, i.e., groups of doctors with similar attitudes toward pharmaceutical representatives’ activities. A second aim of the paper is to verify which aspects of firms’ promotional activity may be determinant in influencing doctors’ prescriptions. LC regression models were estimated for this purpose.
Traditional LC models assume that observations are independent. However, in our case this assumption was violated since doctors judged more than one pharmaceutical industry; multilevel LC models make it possible to modify the above assumption. A multilevel LC model consists of a mixture model equation for level-1 and level-2 units, in which a group-level discrete variable is introduced so that parameters are allowed to differ across latent classes or groups. Our level-1 units were judgments expressed by doctors on the seven aspects of the promotional activity; our level-2 units were doctors. We were interested in defining clusters of doctors (classes).
LC regression models estimate a linear relation between a dependent variable and a set of explanatory variables, accounting for the fact that observations may arise from a number of unknown heterogeneous groups in which regression coefficients differ. LC regression models can be viewed as random-coefficient models that, like multilevel or hierarchical models, can take into account dependencies between observations. This extends the application of LC regression models to situations with repeated measurements. In our case, the dependent variable was the percentage of drugs produced by a certain pharmaceutical industry prescribed by practitioners, and predictors were the judgments expressed by doctors on the seven aspects of promotional activity. -
The application of the Taguchi method to optimize the glycosaminoglycan extraction protocol from nails
Authors: Rozina Vavetsi Department of Experimental Pharmacology, School of Medicine, University of Athens and T.E.I Piraeus/University of Paisley, Scotland 75 M.Asias St., Goudi 15669 Athens, Greece E-mail: rvavetsi@med.uoa.gr Chrysanthi Papanastasopoulou Department of Experimental Pharmacology, School of Medicine, University of Athens 75 M.Asias St., Goudi 15669 Athens, Greece E-mail: chpapan@med.uoa.gr Georgia Dougekou Department of Experimental Pharmacology, School of Medicine, University of Athens 75 M.Asias St., Goudi 15669 Athens, Greece E-mail: ssapounas@gmail.com George J. Besseris T.E.I Piraeus/University of Paisley, Scotland, Argirokastrou 30 St., Drosia 14572 Athens, Greece E-mail: besseris@teipir.gr Nikolaos M. Sitaras Department of Experimental Pharmacology, School of Medicine, University of Athens 75 M.Asias St., Goudi 15669 Athens, Greece E-mail: nsitar@med.uoa.gr
Primary area of focus / application:
Submitted at 28-Apr-2008 21:18 by Rozina Vavetsi
Accepted
The aim of the present study was a) to investigate the content of glycosaminoglycans in human nails and optimize the extraction laboratory protocol so the maximum of them is liberated, and b) study the presence of dermatan sulphate in this material.
Unpolished human nails were obtained from 30 healthy individuals and GAGs were sequentially extracted with guanidinium chloride (Gu-HCl). To optimize the extraction protocol the Taguchi method was applied. Cellulose acetate electrophoresis was performed for the qualitative identification of GAGs. Enzymatic treatment with specific lyases followed, to study the presence of dermatan sulphate in this material.
The results indicated the best combination of the extraction parameters that liberated the maximum concentration of GAGs from nails, being 116 ± 15.8 μg/g of tissue. Cellulose acetate electrophoresis after treatment with specific enzymes revealed a metachromatic band with mobility identical to dermtan’ s sulfate -
Factors affecting the near-miss reporting
Authors: Yousif Rahim and Prof. Ron Kenett
Affiliation: University of Torino, Italy
Primary area of focus / application:
Yousif Rahim
University of Torino, Italy
Det Norske Veritas, Norway
yousif.rahim@unito.it
Prof. Ron Kenett
University of Torino, Italy
KPA, Israel
ron@kpa.co.il
An effective safety improvement system needs an effective system for reporting all types of incidents including near miss. Reactive safety strategies incorporate various monitoring techniques for accidents, cases of ill-health and near misses as near miss is an opportunity to improve safety practice based on a condition, or an incident with the potential for more serious consequences.
Under-reporting is a problem in many sectors of industry, and this is significant since; if reporting levels are low, the accident data will not provide the full picture of accidents that have occurred and analysis of such data may be of limited use in determining the real problem areas.
The problem of under-reporting and especially of near-miss reporting can only be solved by having an organisation-wide culture for solution oriented and not the penalisation of the party responsible. To achieve this goal, there must be a continuous commitment on the part of top management to the issue of reporting all incidents and follow up the implementation of corrective measures and actions.
Objectives:
1. To find out and ensure that near-misses are reported
2. To find an appropriate method for reporting near miss
3. Find factors encouraging employees to report near miss
4. Utilising near miss information, in order to take action to prevent serious accidents occurring
5. To describe how reporting leading to improvement in safety performance.
Methods.
Conducting relevant literature review on state of art in the field of safety management systems, includes review of both white papers and grey literature. Review the Safety management system documents for the major oil and gas companies. Relevant databases will be interrogated with main focus on usability and quality of the accident data.
Discussion
Design a process for containing and explaining all near miss consecutive stages:
- Identification
- Disclosure
- Distribution
- Direct and Root Cause Analysis
- Solution identification
- Dissemination to implementers
- Resolution
The importance of near miss data for operations and corporate level effectiveness will be highlighted through the effect of near-miss reporting in improvement of corporate health, safety and environment performance.
The study will focus on how the near-misses reporting system and data can provide essential data and information to find and discover the potential broken safety barriers and weaknesses in the management system of companies. -
Method for VaR-based Portfolio Selection
Authors: Xu, Chunhui and Ng, Peggy
Primary area of focus / application:
Submitted at 28-Apr-2008 23:46 by Peggy Ng
Accepted
An investment experiment is performed using data from the New York stock market. Portfolios suggested by the soft method are compared to two commonly used investment strategies. The results show that the portfolio selected by the soft method may produce a higher return at lower risk than the two investment strategies, which demonstrates the effectiveness of the proposed method. The results also suggest that VaR could be applied as a measure of risk in portfolio selection from a computational point of view.