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tom Vol. 13, nr 2
21-32
EN
The objective of the present study is to demonstrate the application of multicriteria decision making methods in selecting the most efficient option of quality management system in food industry. Most studies concentrate on single aspects of quality management, instead of looking at the problem more holistically by analysing all factors and often complex relations between them. In response to this shortage, the present study proposes a more holistic model of successful quality management of food products. The Analytic Network Process (ANP) were applied to build and analyse the problem. The successful quality management has been defined here as a goal of improving the quality of food products and increasing the company management effectiveness. The overall model comprises Benefits, Opportunities, Costs and Risks and consider a range of various factors influencing the decision problem. The ANP results are based on empirical survey (questionnaire interviews) carried out with managers in three leading food enterprises in Poland. The problem presented in this paper is very important not only in Poland. B,O,C,R models of improving the quality of food products and increasing the company management effectiveness can be successfully applied by food enterprises to choose the most appropriate quality management systems. Other methods applied to solve this problem would likely fail to analyse these dependencies so thoroughly. Last but not least, the rules of building the B,O,C,R models to select the best option of quality management system in food industry can also be applied in other than food companies.
EN
The purpose of this paper is to derive a procedure to evaluate a group of alternatives or units considered as systems where a certain transformation process consums heteregenous input attributes or items (to be understood in a broad sense including effort that must be done, a negative impact, consumable resources, ...) to produce or deliver heteregenous output items (including subjective satisfaction, tangible products, beneficial impact. ...). In general, many actors with, different points of view as well as different information sources more or less reliable will be involved in the evaluation process. The evaluation context we consider here consists in stakeholders (decission makers, experts, users. ...) that give then- opinion regarding the impact of each item with, regard to the evaluation goal ; the information or data (values of items for different alternatives) about items are collected from or supplied by different more or less reliable information or data sources (news papers, magazines, web. agencies and consulting cabinets, experts. ...). The established model aims to integrate the interactions between these different components (stakeholders, items. information sources and alternatives) and consists bassically for each alternative or unit in computing two measures: an aggregated measure known as the selectability at the output of the system and an aggregated measure at the input known as the rejectability in the framework of satisficing game theory. The derivation of these measures is carried up by a pairwise comparison process using the analytic network process (ANP) approach, an extension of the well known analytic hierarchy process (AHP), that allows to take into account complex interactions of evaluation process components such as dependency and feedback.
EN
Lean manufacturing has been the most deliberated concept ever since its introduction. Many organization across the world implemented lean concept and witnessed dramatic improvements in all contemporary performance parameters. Lean manufacturing has been a sort of mirage for the Indian automotive industry. The present research investigated the key lean barriers to lean implementation through literature survey, confirmatory factor analysis, multiple regression, and analytic network process. The general factors to lean implementation were inadequate lean planning, resource constraints, half-hearted commitment from management, and behavioral issues. The most important factor in the context of lean implementation in Indian automotive industry was inadequate lean planning found with the help of confirmatory factor analysis and multiple regression analysis. Further analysis of these extracted factors through analytic network process suggested the key lean barriers in Indian automotive industry, starting from the most important were absence of proper lean implementation methodology, lack of customer focus, absence of proper lean measurement system, inadequate capital, improper selection of lean tools & practices, leadership issues, resistance to change, and poorly defined roles & responsibilities. Though literature identifying various lean barriers are available. The novelty of current research emerges from the identification and subsequent prioritization of key lean barriers within Indian automotive SMEs environment. The research assists in smooth transition from traditional to lean system by identifying key barriers and developing customized framework of lean implementation for Indian automotive SMEs.
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nr 2
11-22
PL
Celem artykułu jest ranking województw Polski ze względu na poziom wykorzystania technologii informacyjno-telekomunikacyjnych w przedsiębiorstwach, w 2010 r. W badaniach wykorzystano metody wielokryterialnego wspomagania decyzji: AHP (ang. Analytic Hierarchy Process) i ANP (ang. Analytic Network Process). Uzyskane, za pomocą dwóch metod, wyniki porównano i na tej podstawie wykazano różnice pomiędzy zastosowanymi podejściami. Wykorzystane algorytmy pozwoliły na analizę położenia województw z uwagi na różne zaawansowanie obszarów w przestrzeni teleinformatycznej.
EN
The article ranks Polish voivodships in terms of utilization of information and telecommunication technologies in enterprises during the year 2010. In the research, there have been used multi-criteria decision support methods: AHP (Analytic Hierarchy Process) and ANP (Analytic Network Process). Results, obtained through the two methods, have been then compared, which gave us a clear picture of differences between approaches applied in the process. The algorithms which have been used, enabled the analysis of voivodships’ positions in the ranking with regard to varying advancement of specific areas in the ICT area.
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