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Dr. Martin Pech
University of South Bohemia in Ceske Budejovice

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Research Keywords & Expertise

0 Corporate Culture
0 Entrepreneurship
0 Lean Manufacturing
0 Supply Chain Management
0 Industry 4.0

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Industry 4.0
Supply Chain Management
Entrepreneurship

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Project

Project Goal: The aim of the project is the analysis of supply chains in the context of Industry 4.0.

Starting Date:01 January 2020

Current Stage: Data analysis

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Project

Project Goal: The aim of the project is to analyze the outputs of CFEBT in the environment of small and medium enterprises and in various sectors.

Starting Date:01 January 2020

Current Stage: Data Analysis

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Project

Project Goal: Analysis of enterprises management under Industry 4.0 era

Starting Date:01 January 2019

Current Stage: Data Analysis

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Project

Project Goal: The proposed project is based on information concerning the actual situation of labour and production organization in manufacturing enterprises. The project is oriented first of all on Small and middle sized enterprises, where the condition for management of production and applying different useful methods is more complicated than in big enterprises. Necessary data will be received by means of questionnaires, used by students of Economic faculty JU, which will fulfil them in enterprises together with firm’s managers. This way of obtaining data increases their reliability. The project is divided into two parts: The choice of enterprises depends on students only.

Starting Date:01 March 2017

Current Stage: Finished project

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Project

Project Goal: The aim of the project is to design an effective tool of fraud risk management of accounting errors and fraud in the form of anti-fraud system, especially applicable as part of the internal control systems of medium and small entities.

Starting Date:01 March 2017

Current Stage: Finished project

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Project

Project Goal: The main goal of the project is to test the usability of fuzzy logic in the application of logistic controlling and benchmarking. Based on the possible positive findings of the project, prepare a proposal for a methodology for logistic controlling and benchmarking of small and medium-sized enterprises.

Starting Date:01 January 2009

Current Stage: Finished project

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Project

Project Goal: The intention of the paper is to introduce the research project No. 2E06044 of the National Research Programme II of the Czech Ministry of Education: "Managerial Audit as a Tool for Sustainable Development of Small and Medium Enterprises". Work on the project has started in July 2006 and will continue troughout 2007 and 2008. The project targets cooperation among research and educational institutions and the business sphere. The metholodology of assessing (managerial audit) and empowering (coaching) small- and medium-sized enterprises has been developed in order to provide recent approaches to assist further growth of those businesses. The project also provides numerous opportunities for young scholars to participate in the research agenda.

Starting Date:01 January 2006

Current Stage: Finished project

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Journal article
Published: 30 June 2021 in Journal on Efficiency and Responsibility in Education and Science
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Entrepreneurial education (EE) has recently become popular at universities of economics almost all over the world. Various teaching methods play a very important role in the development of the future entrepreneurs. Therefore, in order for a student to become a successful entrepreneur, it is important to find the most effective tool for the teachers to support entrepreneurship education and find the ideal connection between the needs of the students and the right choice of a teaching method. There is a large gap between the needs of the business environment and university studies of this area. The research is based on 214 questionnaires, which were filled in by the students of the University of South Bohemia in České Budějovice in 2018-2019. The aim of the paper is to find and analyse the preferences of teaching methods for students of management based on the following criteria: gender, faculty, degree of study. The students expected to be taught by active methods, e.g. experts lectures and business simulators. Differences in the use of teaching methods were the most evident among students from different faculties.

ACS Style

Martin Pech; Petr Řehoř; Michaela Slabová. Students Preferences in Teaching Methods of Entrepreneurship Education. Journal on Efficiency and Responsibility in Education and Science 2021, 14, 66 -78.

AMA Style

Martin Pech, Petr Řehoř, Michaela Slabová. Students Preferences in Teaching Methods of Entrepreneurship Education. Journal on Efficiency and Responsibility in Education and Science. 2021; 14 (2):66-78.

Chicago/Turabian Style

Martin Pech; Petr Řehoř; Michaela Slabová. 2021. "Students Preferences in Teaching Methods of Entrepreneurship Education." Journal on Efficiency and Responsibility in Education and Science 14, no. 2: 66-78.

Review
Published: 20 February 2021 in Sensors
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With the arrival of new technologies in modern smart factories, automated predictive maintenance is also related to production robotisation. Intelligent sensors make it possible to obtain an ever-increasing amount of data, which must be analysed efficiently and effectively to support increasingly complex systems’ decision-making and management. The paper aims to review the current literature concerning predictive maintenance and intelligent sensors in smart factories. We focused on contemporary trends to provide an overview of future research challenges and classification. The paper used burst analysis, systematic review methodology, co-occurrence analysis of keywords, and cluster analysis. The results show the increasing number of papers related to key researched concepts. The importance of predictive maintenance is growing over time in relation to Industry 4.0 technologies. We proposed Smart and Intelligent Predictive Maintenance (SIPM) based on the full-text analysis of relevant papers. The paper’s main contribution is the summary and overview of current trends in intelligent sensors used for predictive maintenance in smart factories.

ACS Style

Martin Pech; Jaroslav Vrchota; Jiří Bednář. Predictive Maintenance and Intelligent Sensors in Smart Factory: Review. Sensors 2021, 21, 1470 .

AMA Style

Martin Pech, Jaroslav Vrchota, Jiří Bednář. Predictive Maintenance and Intelligent Sensors in Smart Factory: Review. Sensors. 2021; 21 (4):1470.

Chicago/Turabian Style

Martin Pech; Jaroslav Vrchota; Jiří Bednář. 2021. "Predictive Maintenance and Intelligent Sensors in Smart Factory: Review." Sensors 21, no. 4: 1470.

Journal article
Published: 30 December 2020 in Sustainability
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Sustainability has recently become a phenomenon; small and medium-sized enterprises (SMEs) are increasingly emphasizing the principles of sustainability in their corporate governance. They implement these changes through project management. The purpose of the paper is to determine the critical success factors in project management, as seen by the managers of Czech manufacturing enterprises, related to the most to the successful completion of the projects. We aim to analyze the relation of these success factors to Industry 4.0, Human Resources, and sustainability. We determined the possible interconnectedness of the critical success factors using correlation coefficients. Then, we compared them using the Mann-Whitney test with new corporate management trends. The results show that companies consider Leadership and Experiences, and Employees and Flexibility to be key factors in project management’s success. The most important critical factor for the sustainability of projects focused on Industry 4.0 is the finances that decide the implementation of projects. The benefits of Industry 4.0 concerning sustainability have been identified in projects aimed at implementing new energy sources. In addition to the results obtained, the development of a methodology for evaluating Industry 4.0 projects’ success concerning sustainability may be based on critical success factors in the future.

ACS Style

Jaroslav Vrchota; Petr Řehoř; Monika Maříková; Martin Pech. Critical Success Factors of the Project Management in Relation to Industry 4.0 for Sustainability of Projects. Sustainability 2020, 13, 281 .

AMA Style

Jaroslav Vrchota, Petr Řehoř, Monika Maříková, Martin Pech. Critical Success Factors of the Project Management in Relation to Industry 4.0 for Sustainability of Projects. Sustainability. 2020; 13 (1):281.

Chicago/Turabian Style

Jaroslav Vrchota; Petr Řehoř; Monika Maříková; Martin Pech. 2020. "Critical Success Factors of the Project Management in Relation to Industry 4.0 for Sustainability of Projects." Sustainability 13, no. 1: 281.

Journal article
Published: 27 July 2020 in Applied Sciences
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Due to Industry 4.0 technologies, small- and medium-sized enterprises have a great opportunity to increase their competitiveness. However, the question remains as to whether they are truly able to implement such modern technologies faster and carry out digital transformation. The main aim of the paper is to classify small- and medium-sized enterprises into various groups, according to the level of implementation of Industry 4.0, using the Index of Industry 4.0. Based on the results of the cluster analysis, the small and medium enterprises are categorized into four different groups, according to the level of implementation of Industry 4.0. There are top Industry 4.0 technological enterprises, I4 start enterprises, noobs enterprises, and I4 advances enterprises. So far, the largest group consists of the small- and medium-sized enterprises that are just starting out with the introduction of Industry 4.0 technologies, such as IT infrastructure, digitalization (data, cloud, data analysis, and information systems), and sensors. On the other hand, the top I4 technological enterprises group is the least numerous. The analysis carried out comparing the small- and medium-sized enterprises with the large enterprises shows that the SMEs still have a lower level of Industry 4.0 implementation. This confirms the assumption that the large enterprises have greater opportunities to use new technologies and transform them into smart factories. However, this situation may change in the future if new technologies become more accessible, and SMEs are worth investing in Industry 4.0 in terms of the return on investment.

ACS Style

Martin Pech; Jaroslav Vrchota. Classification of Small- and Medium-Sized Enterprises Based on the Level of Industry 4.0 Implementation. Applied Sciences 2020, 10, 5150 .

AMA Style

Martin Pech, Jaroslav Vrchota. Classification of Small- and Medium-Sized Enterprises Based on the Level of Industry 4.0 Implementation. Applied Sciences. 2020; 10 (15):5150.

Chicago/Turabian Style

Martin Pech; Jaroslav Vrchota. 2020. "Classification of Small- and Medium-Sized Enterprises Based on the Level of Industry 4.0 Implementation." Applied Sciences 10, no. 15: 5150.

Review
Published: 24 July 2020 in Sustainability
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Green processes are very important for the implementation of green technologies in production to achieve positive sustainability outcomes in the Industry 4.0 era. The scope of the paper is to review how conventional green processes as a part of Industry 4.0 provide sustainability outcomes in manufacturing. The paper is based on the methodology of systematic literature review through the content analysis of literary resources. Twenty-nine studies were included in our content analysis. The results show the main focus of current literature related to Industry 4.0, sustainability outcomes and green processes. The authors present a conceptual Sustainability Green Industry 4.0 (SGI 4.0) framework that helps to structure and evaluate conventional green processes in relation to Industry 4.0 and sustainability. The study summarizes which technologies (big data, cyber-physical systems, Industrial Internet of Things and smart systems) and green processes (logistics, manufacturing and product design) are important for achieving a higher level of sustainability. The authors found that the most often common sustainability outcomes are energy saving, emission reduction, resource optimalization, cost reduction, productivity and efficiency and higher economic performance, human resources development, social welfare and workplace safety. The study suggests implications for practice, knowledge and future research.

ACS Style

Jaroslav Vrchota; Martin Pech; Ladislav Rolínek; Jiří Bednář. Sustainability Outcomes of Green Processes in Relation to Industry 4.0 in Manufacturing: Systematic Review. Sustainability 2020, 12, 5968 .

AMA Style

Jaroslav Vrchota, Martin Pech, Ladislav Rolínek, Jiří Bednář. Sustainability Outcomes of Green Processes in Relation to Industry 4.0 in Manufacturing: Systematic Review. Sustainability. 2020; 12 (15):5968.

Chicago/Turabian Style

Jaroslav Vrchota; Martin Pech; Ladislav Rolínek; Jiří Bednář. 2020. "Sustainability Outcomes of Green Processes in Relation to Industry 4.0 in Manufacturing: Systematic Review." Sustainability 12, no. 15: 5968.

Journal article
Published: 01 April 2020 in Quality Innovation Prosperity
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Purpose: The paper deals with the differences of supplier performance management characteristics by different size of the enterprises and sectors of industry.Methodology/Approach: The research is based on a questionnaire survey carried out in 2016-2019 in 366 enterprises. Four hypotheses were formulated, focused on supplier selection preferences, frequency of supply evaluation, providing feedback to the suppliers about their performance and quality control. The results are analyzed by the tests of Chi-square statistics.Findings: The results show that the enterprises differ in the criteria of the selection of the supplier, frequency of supply evaluation and providing feedback to the suppliers about their performance according to their sector industry. In terms of the size of the enterprises, differences were found only in the evaluation of suppliers and evaluation feedback. Enterprises did not differ in quality control of the deliveries.Research Limitation/implication: The results show that quality is the most evaluated criterion in the selection of the suppliers. In the future, the importance of other environmental and Industry 4.0 criteria will grow. It is recommended combining supplier evaluation and reviews with the feedback to the suppliers to improve the performance of the suppliers.Originality/Value of paper: The study compares the enterprises in terms of their size and industries in the area of supplier performance management characteristics. These criteria are often not mentioned nor compared in other publications.

ACS Style

Martin Pech; Drahoš Vaněček. Supplier Performance Management in Context of Size and Sector Characteristics of Enterprises. Quality Innovation Prosperity 2020, 24, 88 -103.

AMA Style

Martin Pech, Drahoš Vaněček. Supplier Performance Management in Context of Size and Sector Characteristics of Enterprises. Quality Innovation Prosperity. 2020; 24 (1):88-103.

Chicago/Turabian Style

Martin Pech; Drahoš Vaněček. 2020. "Supplier Performance Management in Context of Size and Sector Characteristics of Enterprises." Quality Innovation Prosperity 24, no. 1: 88-103.

Journal article
Published: 31 March 2020 in Journal of Competitiveness
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The scientific periodical journal (indexed on Web of Science) published by the Tomas Bata University in Zlin offers results of basic and applied economic research in the English language.

ACS Style

Martin Pech; Jaroslava Prazakova; Lucie Pechova. The Evaluation of the Success Rate of Corporate Failure Prediction in a Five-Year Period. Journal of Competitiveness 2020, 12, 108 -124.

AMA Style

Martin Pech, Jaroslava Prazakova, Lucie Pechova. The Evaluation of the Success Rate of Corporate Failure Prediction in a Five-Year Period. Journal of Competitiveness. 2020; 12 (1):108-124.

Chicago/Turabian Style

Martin Pech; Jaroslava Prazakova; Lucie Pechova. 2020. "The Evaluation of the Success Rate of Corporate Failure Prediction in a Five-Year Period." Journal of Competitiveness 12, no. 1: 108-124.

Journal article
Published: 10 December 2019 in Applied Sciences
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Industry 4.0 includes digital process transformation, information technology (IT) development, mobile devices, learning software, automation, and robotics, as well as intelligent sensors to collect large datasets, store, analyze, and use them in business, including simulation, virtual reality, and digital twins. The aim of the paper is to characterize the readiness of the enterprise to use Industry 4.0. In the research, a questionnaire survey was carried out on a sample of 276 enterprises mainly from the manufacturing industry. Using explorative factor analysis, the index of Industry 4.0 (VPi4) was designed to determine the level of Industry 4.0 implementation in the enterprises. The results were further verified by a statistical analysis, using Mann–Whitney test and correlation coefficients. The results indicate that the VPi4 index was consistent in terms of distribution when comparing the results on the verification sample. Its results correlate with the subjective perception of the enterprises, and different levels of the index reflect the difference in technological intensity of the industry. The VPi4 index enables the enterprises to determine their own level of current state of readiness for Industry 4.0, to better prioritize business development. The proposed solution categorizes Industry 4.0 components into a useful theoretical framework. Further research offers the possibility of applying the index in other sectors, its relation to the size of enterprises, and updating with respect to new trends in information technology.

ACS Style

Jaroslav Vrchota; Martin Pech. Readiness of Enterprises in Czech Republic to Implement Industry 4.0: Index of Industry 4.0. Applied Sciences 2019, 9, 5405 .

AMA Style

Jaroslav Vrchota, Martin Pech. Readiness of Enterprises in Czech Republic to Implement Industry 4.0: Index of Industry 4.0. Applied Sciences. 2019; 9 (24):5405.

Chicago/Turabian Style

Jaroslav Vrchota; Martin Pech. 2019. "Readiness of Enterprises in Czech Republic to Implement Industry 4.0: Index of Industry 4.0." Applied Sciences 9, no. 24: 5405.

Journal article
Published: 31 July 2018 in Quality Innovation Prosperity
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Purpose: Quality in manufacturing can be improved by using lean production methods. The paper discusses traditional and modern methods of lean production and their use in different enterprises.Methodology/Approach: Through a questionnaire survey and research, 90 industrial enterprises were classified by the size, production scope and their ownership. The research results were analyzed by means of statistical methods to determine the differences in the use of lean production methods.Findings: Regarding the lean production and its different methods, the size of the enterprise is an important factor. The statistics revealed that large enterprises tend to use lean production more. It was also proved that some methods of lean production are not completely common in the Czech Republic. Moreover, some methods are quite new to the majority of the enterprises.Research Limitation/implication: Some questionnaire surveys conducted in different countries (especially in the US) use a different enterprise size classification. As the research results show, there is still a large potential for the introduction of lean production methods in small and middle-sized enterprises that can help enterprises to improve the quality of their production.Originality/Value of paper: The application of lean production methods has been investigated so far, especially in large engineering enterprises. The paper deals with the use of these methods also in small and medium sized enterprises. The authors focused their research also on non-engeneering enterprises in the field of the food industry and production of products for domestic use too.

ACS Style

Martin Pech; Drahoš Vaněček. Methods of Lean Production to Improve Quality in Manufacturing. Quality Innovation Prosperity 2018, 22, 01 -15.

AMA Style

Martin Pech, Drahoš Vaněček. Methods of Lean Production to Improve Quality in Manufacturing. Quality Innovation Prosperity. 2018; 22 (2):01-15.

Chicago/Turabian Style

Martin Pech; Drahoš Vaněček. 2018. "Methods of Lean Production to Improve Quality in Manufacturing." Quality Innovation Prosperity 22, no. 2: 01-15.

Journal article
Published: 02 May 2018 in Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis
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ACS Style

Drahoš Vaněček; Martin Pech; Michael Rost. Innovation and Lean Production. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 2018, 66, 595 -603.

AMA Style

Drahoš Vaněček, Martin Pech, Michael Rost. Innovation and Lean Production. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis. 2018; 66 (2):595-603.

Chicago/Turabian Style

Drahoš Vaněček; Martin Pech; Michael Rost. 2018. "Innovation and Lean Production." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 66, no. 2: 595-603.

Preprint
Published: 01 January 2011
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During recent years, the supply chain performance management has become a key strategic consideration. Many manufacturers seek to collaborate with their suppliers and customers in order to upgrade their competitiveness and management performance. Because of complexity, uncertainty and vagueness inherent in supply chains, performance measurement using fuzzy approach was also identified as a new research direction. The main aim of the paper is focused on evaluation of logistic dimensions (sets of logistic indicators) in supply chain, where the uncertainty arises from the inability to perform adequate measurement, and deals with application of fuzzy approach, that provides a formal method for modeling imprecise, vagueness or incomplete relationships inherent in supply chains. Gathered data from questionnaires are analyzed by cluster analysis. Afterwards fuzzy methods are used evaluations of basic five dimensions, which contain several numbers of logistic indicators. The new methodology adopted from Soyer, Kabak, & Asan (2007) research based on the intersection of fuzzy sets and fuzzy entropy method has been applied to evaluations in a case study. Results are afterwards modified by a applying of different membership functions, and changes of dimensions measures are analyzed. Finally supply chain modifying by adding new companies with capability of bind to supply chain are examined. New results of evaluation are compared according to new companies’ membership to different clusters.

ACS Style

Jaroslava Smolová; Martin Pech. Fuzzy approach to supply chain management. 2011, 1 .

AMA Style

Jaroslava Smolová, Martin Pech. Fuzzy approach to supply chain management. . 2011; ():1.

Chicago/Turabian Style

Jaroslava Smolová; Martin Pech. 2011. "Fuzzy approach to supply chain management." , no. : 1.

Journal article
Published: 30 August 2021
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ACS Style

Martin Pech. Financial statements risk: Case study of a small accounting unit. 2021, 1 .

AMA Style

Martin Pech. Financial statements risk: Case study of a small accounting unit. . 2021; ():1.

Chicago/Turabian Style

Martin Pech. 2021. "Financial statements risk: Case study of a small accounting unit." , no. : 1.

Book
Published: 30 August 2021 in The role of centres in supply network information distribution
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ACS Style

Martin Pech. The role of centres in supply network information distribution. The role of centres in supply network information distribution 2021, 1 .

AMA Style

Martin Pech. The role of centres in supply network information distribution. The role of centres in supply network information distribution. 2021; ():1.

Chicago/Turabian Style

Martin Pech. 2021. "The role of centres in supply network information distribution." The role of centres in supply network information distribution , no. : 1.