Gyula Vastag

7003473947

Publications - 6

Mapping quality linkages based on tacit knowledge

T. B. Ladinig Gyula Vastag

Publication Name: International Journal of Production Economics

Publication Date: 2021-03-01

Volume: 233

Issue: Unknown

Page Range: Unknown

Description:

A structured conceptualization method, concept mapping, is applied to visualize the conceptual domain of explicit and tacit quality linkages in a complex, causally ambiguous production system of a premium automotive OEM. Experts, intimately familiar with all facets of the conceptual domain, defined sources of quality problems and rated their impact on product quality. These inputs, formative measures for a latent construct, were used to create concept maps and clusters for the sources of quality problems. Differences and disagreements between subgroups were highlighted by pattern matching. The concept map and the preferred cluster solution, based on user-defined measures, served as inputs in the development of a causal loop diagram and an action plan for better resource allocation to specific improvement activities. The approach, using formative rather than the more commonly used reflective indicators, uses key informants and explanation building processes of high internal validity. In the spirit of the “proximal similarity model,” the presented methodology is also highly transferable to similar settings of other automotive OEMs and beyond.

Open Access: Yes

DOI: 10.1016/j.ijpe.2020.108006

Sensemaking support system (S3) for manufacturing process improvement

T. B. Ladinig Krishna S. Dhir Gyula Vastag

Publication Name: International Journal of Production Research

Publication Date: 2021-01-01

Volume: 59

Issue: 8

Page Range: 2406-2425

Description:

Production management teams often face unfamiliar situations where each team member must understand new phenomena individually before the team can make mutually understandable and acceptable decisions. Contradicting subjective judgments can distort the group’s decision-making process because team members understand situations differently and are generally prone to behavioural biases. This paper presents the development of a sensemaking support system (S3,S cube) for selecting improvement projects in a complex,small-volume batch production system of a premium car manufacturer. All phases of the sensemaking process are facilitated by making various sources of information available to a team of managers and experts to reduce conflicts regarding the selection of improvement projects. S3 is based on a lens model which combines judgments of the management team with discrete event simulation and provides visual representations of the differences and misjudgements related to various improvement options. The results–that can easily be generalised to many similar settings–indicate different understanding and lack of coherence within the management team which prevents them from defining mutually acceptable actions. This is countered with the creation of an action proposal,summarising and visualising causal relationships,and connecting them to improvement options to improve performance of the production system.

Open Access: Yes

DOI: 10.1080/00207543.2020.1733700

Banking applications of FCM models

F. Hatwágner Gyula Vastag L. T. Koczy Vesa A. Niskanen

Publication Name: Studies in Computational Intelligence

Publication Date: 2019-01-01

Volume: 796

Issue: Unknown

Page Range: 61-72

Description:

Fuzzy Cognitive Map (FCMs) is an appropriate tool to describe, qualitatively analyze or simulate the behavior of complex systems. FCMs are bipolar fuzzy graphs: their building blocks are the concepts and the arcs. Concepts represent the most important components of the system, the weighted arcs define the strength and direction of cause-effect relationships among them. FCMs are created by experts in several cases. Despite the best intention the models may contain subjective information even if it was created by multiple experts. An inaccurate model may lead to misleading results, therefore it should be further analyzed before usage. Our method is able to automatically modify the connection weights and to test the effect of these changes. This way the hidden behavior of the model and the most influencing concepts can be mapped. Using the results the experts may modify the original model in order to achieve their goal. In this paper the internal operation of a department of a bank is modeled by FCM. The authors show how the modification of the connection weights affect the operation of the institute. This way it is easier to understand the working of the bank, and the most threatening dangers of the system getting into an unstable (chaotic or cyclic state) can be identified and timely preparations become possible.

Open Access: Yes

DOI: 10.1007/978-3-030-00485-9_7

Improved behavioral analysis of fuzzy cognitive map models

F. Hatwágner Gyula Vastag L. T. Koczy Vesa A. Niskanen

Publication Name: Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics

Publication Date: 2018-01-01

Volume: 10842 LNAI

Issue: Unknown

Page Range: 630-641

Description:

Fuzzy Cognitive Maps (FCMs) are widely applied for describing the major components of complex systems and their interconnections. The popularity of FCMs is mostly based on their simple system representation, easy model creation and usage, and its decision support capabilities. The preferable way of model construction is based on historical, measured data of the investigated system and a suitable learning technique. Such data are not always available, however. In these cases experts have to define the strength and direction of causal connections among the components of the system, and their decisions are unavoidably affected by more or less subjective elements. Unfortunately, even a small change in the estimated strength may lead to significantly different simulation outcome, which could pose significant decision risks. Therefore, the preliminary exploration of model ‘sensitivity’ to subtle weight modifications is very important to decision makers. This way their attention can be attracted to possible problems. This paper deals with the advanced version of a behavioral analysis. Based on the experiences of the authors, their method is further improved to generate more life-like, slightly modified model versions based on the original one suggested by experts. The details of the method is described, its application and the results are presented by an example of a banking application. The combination of Pareto-fronts and Bacterial Evolutionary Algorithm is a novelty of the approach.

Open Access: Yes

DOI: 10.1007/978-3-319-91262-2_55

Supply Chain Decisions in Governmental Organizations

Gyu M. Lee Gyula Vastag Geraldo Ferrer

Publication Name: Decision Sciences

Publication Date: 2016-12-01

Volume: 47

Issue: 6

Page Range: 995-997

Description:

No description provided

Open Access: Yes

DOI: 10.1111/deci.12263

Achieving Sustainable Supply Chains: Applying Group Concept Mapping to Prioritize and Implement Sustainable Management Practices

E. Süle Thompson McDaniel Gyula Vastag

Publication Name: Logistics

Publication Date: 2025-09-01

Volume: 9

Issue: 3

Page Range: Unknown

Description:

Background: Sustainability in supply chain management (SCM) practices is becoming increasingly important as environmental responsibility and social concerns, as well as enterprises’ competitiveness in terms of innovation, risk, and economic performance, become increasingly urgent. This paper aims to identify and prioritize concepts for implementing sustainable supply chains, drawing on sustainable supply chain management (SSCM) and green supply chain management (GSCM) techniques. Corporate supply chain managers across various industries, markets, and supply chain segments brainstormed management practices to enhance the sustainability of their supply chains. Four industry sectors were surveyed across five different value chain segments. Methods: A group concept mapping (GCM) approach incorporating multi-dimensional scaling (MDS) and hierarchical cluster analysis (HCA) was used. A hierarchy of practices is proposed, and hypotheses are developed about achievability and impact. Results: A decision-making matrix prioritizes eight solution concepts based on two axes: impact (I) and ease of implementation (EoI). Conclusions: Eight concepts are prioritized based on the optimal effectiveness of implementing the solutions. Pattern matching reveals differences between emerging and developed markets, as well as supply chain segments, that decision-makers should be aware of. By analyzing supply chains from a multi-part perspective, this research goes beyond empirical studies based on a single industry, geographic region, or example case.

Open Access: Yes

DOI: 10.3390/logistics9030099