Management and Production Engineering Review

Content

Management and Production Engineering Review | 2022 | vol. 13 | No 2

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Abstract

The main objective of the research work was to identify the dimensions of complexity and study the relationship between these defined dimensions in the industrial automation sector. To achieve these objectives in the study, there was assumed the following major hypothesis: With the increasing role of dynamic cross-section of the complexity there is growing importance of relationship dimension for competitive advantage. In the study there were diagnosed four dimensions of complexity. Existence of the relationship between these four identified dimensions of complexity occurred by the use of the Fisher’s exact test, which is a variant of the test of independence ��2. Furthermore, there were calculated V-Cramer factors to estimate the intensity of the above-mentioned relationship between analyzed dimensions. The research discovered that the three out of four dimensions such as the number of elements, variety of elements and uncertainty depend on the last dimension of complexity which is the relationship between elements. In the turbulent environment there is a growing importance of the relationship dimension. It forms competitive advantage and is a key condition of success in creating a new type of modern enterprise strategy that occurs within complexity management in the industrial automation sector.
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Authors and Affiliations

Anna Lewandowska-Ciszek
1

  1. Poznan University of Economics and Business, Department of Logistics, Poland
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Abstract

This study aims to identify the impact of transformational leadership in improving the performance of employees and its impact on raising the efficiency of organizations by considering that transformational leadership is one of the successful leadership methods to achieve the effectiveness and efficiency of organizations and improve their performance. In this paper, a systematic literature review of existing international papers is used. the meta-analysis method was used to analyze the articles published in scientific journals with high evaluation indexed in Scopus. Through the analysis process, application (WordStat 8) was used to investigate articles and summarize the descriptive statistics, correlation, and cloud keywords. The results reveal the effectiveness of transformational leadership on job performance. whenever managerial leaderships possess the attributes and characteristics of a transformational leader, including positive influence, inspirational motivation, and individual consideration, the more their subordinates will have creative skills and abilities. Also, the results indicate that the leader who possesses the characteristics of a transformational leader contributes significantly to the development of the capabilities of his subordinates, which is positively reflected in the upgrading of the organization's efficiency. In this paper, we present identifiable patterns in the relationship between transformational leadership, improving employee performance, and the raising efficiency of organizations. Then we suggest emerging core topics that deserve more academic attention. This paper's added value is that it undertakes a thorough and complete assessment of the relationship between transformational leadership, boosting employee performance, and increasing organizational efficiency. It also includes a written review of the work as well as an updated reference index covering the years 2011 to 2020, making it valuable for academics and professionals alike.
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Authors and Affiliations

Askar Garad
1
Siswoyo Haryono
Rizal Yaya
2
Suryo Pratolo
2
Alni Rahmawati
2

  1. Doctoral Management Program, Postgraduate Studies, University Muhammadiyah Yogyakarta, Yogyakarta, Indonesia
  2. University Muhammadiyah Yogyakarta, Yogyakarta, Indonesia
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Abstract

Distribution centres are the important elements of modern supply chains. A distribution centre stores and ships products. In this paper, we investigate the model of the dimensioning of shelf space on the rack with vertical and horizontal product categorisation in a distribution centre, where the objective is to maximise the total product movement/profit from all shelves of the rack which is being managed by a packer who needs to complete orders selecting the products from the shelves and picking them to the container. We apply two newly developed heuristics to this problem and compare the results to the optimal solution found by the CPLEX solver. There are 8 steering parameters that allow for reducing the search space implemented in heuristics. Among them are parameters that decrease the number of products on the shelves, the category with a range for assigning most space for the most profitable products within the category; two versions of steering parameters for the number of generated product allocations, the step parameters for the intensity of solution diversification, and the movement/profit below which the solutions are not generated. The computational results are presented and indicate that higher-quality solutions can be obtained using the new heuristics. In 10 from 15 tests, both heuristics can find optimal solutions without exploring the whole solution space. For the rest test sets, the solutions received by heuristics are not less than 92.58%.
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Authors and Affiliations

Kateryna Czerniachowska
1
ORCID: ORCID
Radosław Wichniarek
2
ORCID: ORCID
Krzysztof Żywicki
2
ORCID: ORCID

  1. Wroclaw University of Economics and Business, Wroclaw, Poland
  2. Poznan University of Technology, Poznan, Poland
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Abstract

The objective of this article is to carry out a systematic review of the literature on multivariate statistical process control (MSPC) charts used in industrial processes. The systematic review was based on articles published via Web of Science and Scopus in the last 10 years, from 2010 to 2020, with 51 articles on the theme identified. This article sought to identify in which industry the MSPC charts are most applied, the types of multivariate control charts used and probability distributions adopted, as well as pointing out the gaps and future directions of research. The most commonly represented industry was electronics, featuring in approximately 25% of the articles. The MSPC chart most frequently applied in the industrial sector was the traditional T2 of Harold Hotelling (Hotelling, 1947), found in 26.56% of the articles. Almost half of the combinations between the probabilistic distribution and the multivariate control graphs, i.e., 49.4%, considered that the data followed a normal distribution. Gaps and future directions for research on the topic are presented at the end.
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Authors and Affiliations

Renan Mitsuo Ueda
1
Ìcaro Romolo Sousa Agostino
2
Adriano Mendonça Souza
1

  1. Federal University of Santa Maria, Brazil
  2. Federal University of Santa Catarina, Brazil
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Abstract

We investigate the effect on firm performance of the motivation for applying maturity models in manufacturing and information technology organizations. We expect the association between profitability and maturity models to be less if motivated by external contract requirements (e.g., for certain government contracts), than if motivated internally to improve processes. Using a sample of firm-year observations for 1,105 SEC registrants in the manufacturing (Standard Industry Classification (SIC): 3600-3812) and IT industries (SIC: 7370-7374) for 2017 and 2018, and CMMI information from the CMMI institute published appraisal results system, it is observed that 28 public firms (17 IT firm-years and 23 manufacturing firm-years) in the sample had CMMI appraisals between 2017 and 2018. We use logistic regression to test if the likelihood of CMMI appraisal is positively associated with government sales. The results support for the manufacturing industry, but not for the IT industry, prior research’s assertion that maturity is a source for competitive advantage.
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Authors and Affiliations

Louise Hayes
1
Jing Lu
1
Davar Rezania
1

  1. Department of Management, Gordon S. Lang School of Business and Economics, University of Guelph, Canada
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Abstract

The green logistics item as a part of distribution processes represents an innovative perspective in many views. This perspective is current from an offer and demand point of view. Many authors examine only the businesses aspect, while labour market acceptance is important. The aim of this article is to create and verify a green distribution model and this examines the green distribution perception from the consumer’s point of view in a context of chosen demographic characteristics. The creation of a green distribution model is supported by secondary research at which consists of four parts – input, transport, production and sale. Model verification was taken with primary research which base was created of 409 respondents. In the study, we use many statistical and mathematical, as well as scientific and philosophical methods. Among the most significant belong Cronbach’s alpha and McDonald’s omega. We used to verify and estimate model reliability, correlation analysis for relation research, one-way ANOVA test for research hypotheses verification and cluster analysis for identification of possible hidden clusters. The model can be considered a reliable one. Results indicate a low influence of distribution ecological factor in a consumer’s perspective, as well, it can be stated, the age, contrary to sex, represents a significant factor in a green distribution perception. Results can be used in both the academic and commercial spheres in various fields and disciplines. The primary survey was conducted in Slovakia, but it would be appropriate to examine the model in other countries, as well as to identify factors that may affect the model of green distribution in the future.
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Authors and Affiliations

Marián Cvirik
1
ORCID: ORCID
Naqibullah Daneshjo
1
ORCID: ORCID

  1. Department of Management, Gordon S. Lang School of Business and Economics, University of Guelph, Canada
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Abstract

The EFQM recognition system is an acknowledged method of assessing business excellence understood as the degree of implementation of quality management in an organization. The paper aims to examine whether a high rating under the EFQM recognition system simultaneously means a high general management maturity level. The investigation covers the 35 organizations that won EFQM awards in Portugal. The study is based on points awarded to organizations under the EFQM recognition system and on questionnaires/interviews with managers responsible for quality management in the studied organizations. The results indicate a positive and robust correlation between the quality management implementation (rating under the EFQM recognition system) and general management maturity. The study helps to close the gap in the literature regarding the relationship between quality management and management maturity in an organization.
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Authors and Affiliations

Luís Pimentel
1
ORCID: ORCID
Piotr Rogala
2
ORCID: ORCID

  1. BRU-UNIDE, ISCTE-IUL, University Institute of Lisbon; Universidade Europeia (Lisbon), Portugal
  2. Wroclaw University of Economics and Business, Department of Quality and Environmental Management, Poland
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Abstract

Understanding of how to implement Lean successfully and how it contributes to performance in manufacturing organizational is still relatively lacking so that Lean exploration is still needed in the management aspect. This research will examine the effect of LMS, LWRT on LBR. This research was conducted on 30 companies in industrial centers in Indonesia, and the data were processed using the Structural Equation Model method. It was found that LMS has no significant effect on LBR, but LMS has a significant effect on LWRT, while LWRT has a significant effect on LBR. In detail, LBR variation of 78.8% is simultaneously influenced by LMS and LWRT, 21.2% is influenced by other variables. While 72.7% LWRT variation is influenced by LMS variation, and 27.3% is influenced by other variables. This result confirms Bergmiller’s research (2009) that LMS has a significant effect on LBR through LWRT for the manufacturing industry in Indonesia.
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Authors and Affiliations

Herry Agung Prabowo
1
Farida Farida
1
Erry Yulian T. Adesta
2

  1. Industrial Engineering, Universitas Mercu Buana Jakarta, Indonesia
  2. Department of Industrial Safety and Health Engineering, Universitas Indo Global Mandiri (UIGM), Indonesia
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Abstract

Employers signal difficulties in sourcing technically-educated staff. They often engage, though to a limited degree, in cooperation with vocational schools to mitigate this difficulty. One of the reasons for the limited involvement of enterprises in cooperation with schools is the difficulty in assessing the benefits that it may bring. The aim of the study in the article was to develop and initially verify a model for evaluating the results of supporting secondary technical schools by manufacturing enterprises. The article features a multiple case study using several types of interviews, a distributed questionnaire and an analysis of secondary sources. The study was conducted in cooperation with four large manufacturing enterprises. The result of the research is a more thorough understanding of the possibilities and limitations in evaluating the results of support for schools. This support should translate in enterprises into more effective and efficient management of the competences of the future.
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Authors and Affiliations

Maciej Szafrański
1

  1. Faculty of Engineering Management, Poznan University of Technology, Poland
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Abstract

This article presents the assessment of the creative culture and the level of innovativeness in selected manufacture enterprises. The theoretical part of the article discusses the space for creativity in the company and the microfoundations of the pyramid of needs related to creative culture. The pyramid consists of different microfoundations, which were used to create a questionnaire to assess the level of creative culture. This study assessed creative culture according to a model of the hierarchy of needs, developed by the author of this study based on Maslow’s pyramid of needs. The assessment used an innovation questionnaire and a creative culture questionnaire. This article presents a sample analysis of the results obtained from two of the companies that participated in the study. Furthermore, the article summarizes the results obtained from all participating companies and gives recommendations related to establishing creative culture based on these results. Every company should implement appropriate standards to help it develop a creative working environment. The goal of assessing creative culture in a company is to assist managers in building a workplace that fosters creativity, since such a workplace is a significant factor affecting the emergence of innovation. The analysis of the creative culture of the companies revealed their weaknesses and strengths in this respect. The developed methodology will undoubtedly influence an increase of awareness and knowledge of enterprises in the field of creating a pro-creative company culture. Such actions will contribute to the increase of company’s innovation, thus influencing its development.
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Authors and Affiliations

Kamila Tomczak
1
ORCID: ORCID

  1. Opole University of Technology, Poland
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Abstract

The activities of the organisation concentrate mainly on meeting customers’ requirements. For this purpose, various activities are being conducted for customer satisfaction surveys. In this context, it is important to predict the quality of the product and the changes in the cost of the purchase product. The purpose of this study is to propose a method for predicting the quality level of a product and change the cost of the product considering current customers’ requirements for a combination of product feature states and pro-quality changes. The method includes the calculation of the quality level of the product using the punctationformalised method, where the level depends on a combination of values of states (parameters) attributes of the product, that is, current and modified. The method was tested as an example of a household vacuum cleaner for which 20 attributes were determined. According to the Pareto rule (20/80), the four product attributes important for customers were selected. Thereafter, for important attributes, possible combinations of the values of these attributes were determined. In addition, an algorithm for determining the possible combinations of product attribute states in the MATLAB program was developed. Additionally, the change in the current cost of the product considering the change in the quality level was estimated. The product cost changes were determined based on the actual cost of the product and the current product quality level. The method allows the determination of all combinations of values of state attributes of the product, such that it is possible to take appropriate improvement actions both in terms of quality and cost. The results from the method allow the prediction of product satisfaction for customers and they are favourable in terms of production cost. Therefore, it is possible to design the product in advance and support the producer in preparatory activities.
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Authors and Affiliations

Dominika Siwiec
1
ORCID: ORCID
Andrzej Pacana
1
ORCID: ORCID

  1. Rzeszow University of Technology, Faculty of Mechanical Engineering and Aeronautics, Poland

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REVIEW PROCESS

Received manuscripts are first examined by the Management and Production Engineering Review Editors.
Manuscripts clearly not suitable for publication, incomplete or not prepared in the required style will be sent back to the authors without scientific review, but may be resubmitted as soon as they have been corrected.
The corresponding author will be notified by e-mail when the manuscript is registered at the Editorial Office (https://www.editorialsystem.com/mper/). The responsible editor will make the decision either to send the manuscript to another reviewer to resolve the difference of opinion or return it to the authors for revision. The ultimate decision to accept, accept subject to correction, or reject a manuscript lies within the prerogative of the Editor-in-Chief and is not subject to appeal. The editors are not obligated to justify their decision.
All manuscripts submitted to MPER editorial system ( https://www.editorialsystem.com/mper/) will be sent to at least two and in some cases three reviewers for passing the double-blind review process.
The material formatted in the MPER format must be unpublished and not under submission elsewhere.

REVIEWERS
Once a year a list of co-operating reviewers is publish in electronic version of MPER. All articles published in MPER are published in open access.


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In order to provide free access to readers, and to cover the costs of copyediting, typesetting, long-term archiving, and journal management, an article processing charge (APC) of 800 PLN (about 180 Euro, VAT included) for 10-page article applies to papers accepted after peer review. Each additional page of the article (over 10 pages) costs 80 PLN (about 18 Euro, VAT included).
Maximum length of the article is 18 pages (using MPER template).
There is no submission charge.

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The non-commercial use of the article will be governed by the Creative Commons Attribution license as currently displayed on https://creativecommons.org/licenses/by/4.0/.

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The ethics statements for the journal Management and Production Engineering Review are based on the guidelines of Committee on publication ethics (COPE) and the ELSEVIER publishing ethics resource kit.
For Authors: All articles, published in the journal Management and Production Engineering Review have to comprise a list of references which correspond with the journal’s Instructions to authors for paper preparation. The authors should ensure that they have written entirely original works, and if the authors have used the work and/or words of others that this has been appropriately cited or quoted. All articles are tested using antyplagiarism programme. An author should not in general publish manuscripts describing essentially the same research in more than one journal or primary publication. Submitting the same manuscript to more than one journal concurrently constitutes unethical publishing behaviour and is unacceptable. Authorship should be limited to those who have made a significant contribution to the conception, design, execution, or interpretation of the reported study. The corresponding author should ensure that all co-authors have seen and approved the final version of the paper and have agreed to its submission for publication. All authors should disclose in their manuscript any financial or other substantive conflict of interest that might be construed to influence the results or interpretation of their manuscript. All sources of financial support for the project should be disclosed.
Authors are accountable for the originality, validity and integrity of the content of their submissions. In choosing to use AI tools, authors are expected to do so responsibly and in accordance with our editorial policies on authorship and principles of publishing ethics. Authorship requires taking accountability for content, consenting to publication via an author publishing agreement, giving contractual assurances about the integrity of the work, among other principles. These are uniquely human responsibilities that cannot be undertaken by AI tools. Therefore, AI tools must not be listed as an author. Authors must, however, acknowledge all sources and contributors included in their work. Where AI tools are used, such use must be acknowledged and documented appropriately.
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For Reviewers: Peer review helps the editor in making editorial decisions and also assist the author in improving the paper. Any selected referee who feels unqualified to review the research reported in a manuscript or knows that its prompt review will be impossible should notify the editor and excuse himself from the review process. Any manuscripts received for review must be treated as confidential documents. They must not be shown to or discussed with others except as authorized by the editor. Reviews should be conducted objectively. Personal criticism of the author is inappropriate. Reviewers should identify relevant published work that has not been cited by the authors. Any statement that an observation, derivation, or argument had been previously reported should be accompanied by the relevant citation. A reviewer should also call to the editor's attention any substantial similarity or overlap between the manuscript under consideration and any other published paper of which they have personal knowledge. Information obtained through peer review must be kept confidential and not used for personal advantage. Reviewers should not consider manuscripts in which they have conflicts of interest resulting from competitive, collaborative, or other relationships or connections with any of the authors, companies, or institutions connected to the papers. Other sources: http://apem-journal.org/


Peer-review Procedure

Received manuscripts are first examined by the Management and Production Engineering Review Editors. Manuscripts clearly not suitable for publication, incomplete or not prepared in the required style will be sent back to the authors without scientific review, but may be resubmitted as soon as they have been corrected. The corresponding author will be notified by e-mail when the manuscript is registered at the Editorial Office (marta.grabowska@put.poznan.pl; mper@put.poznan.pl). The ultimate decision to accept, accept subject to correction, or reject a manuscript lies within the prerogative of the Editor-in-Chief and is not subject to appeal. The editors are not obligated to justify their decision. All manuscripts submitted to MPER editorial office (https://www.editorialsystem.com/mper/) will be sent to at least two and in some cases three reviewers for passing the double-blind review process. The responsible editor will make the decision either to send the manuscript to another reviewer to resolve the difference of opinion or return it to the authors for revision.

The average time during which the preliminary assessment of manuscripts is conducted - 14 days
The average time during which the reviews of manuscripts are conducted - 6 months
The average time in which the article is published - 8.4 months

Reviewers

2024
No Name Surname Affiliation
1 Abd El-Rahman Abd El-Raouf Ahmed Agricultural Engineering, Agricultural Engineering Research Institute, Giza , Egypr
2 Wiktor Adamus Jagiellonian University, Poland
3 Shoaib Akhtar Fatima Jinnah Women University, Pakistan
4 Mohammad Al-Adaileh "COLLEGE OF ENGINEERING Engineering, Technology, and Management Assistant Professor of Instruction, United States"
5 Hind Ali University of Technology, Iraq
6 Katarzyna Antosz Rzeszow University of Technology, Poland
7 Muhammad Asrol Binus University, Indonesia
8 Lucia Bednarova Technical University of Kosice, Slovak Republic
9 Haniyah Bilal Haverford university, United States
10 Berihun Bizuneh "Bahir Dar University Bahir Dar Univ, Ethiopian Inst Text & Fash Technol, Bahir Dar, Ethiopia, Ethiopia"
11 Łukasz Brzeziński Katedra Organizacji i Zarządzania, Wyższa Szkoła Logistyki w Poznaniu, Poland
12 Waldemar Budner Katedra Logistyki, Uniwersytet Ekonomiczny w Poznaniu, Poland
13 Anna Burduk Wrocław University of Science and Technology, Poland
14 Vishnu C R Department of Humanities and Social Sciences, Indian Institute of Technology Tirupati, India
15 Fatih Çetin Başkent Üniversitesi, Turkey
16 Danylo Cherevatskyi Institute of Industrial Economics of NAS of Ukraine: Kiev, UA, Ukraine
17 Claudiu Cicea Bucharest University of Economic Studies Romania, Romania
18 Hasan Huseyin Coban Department of Electrical Engineering, Bartin University, Turkey
19 Juan Cogollo-Florez Universidad Nacional de Colombia, Colombia
20 David Coopler Universitat Politècnica de València, Romania
21 Ömer Cora Karadeniz Technical University, Turkey
22 Margareta Coteata Gheorghe Asachi Technical University of Iasi, Department of Manufacturing Engineering, Romania
23 Szymon Cyfert Poznań University of Economics and Business, Poland
24 Valentina Di Pasquale Department of Industrial Engineering, University of Salerno, Italy
25 Milan Edl University of West Bohemia, Czech Republic
26 Luis Edwards Cornell University, United States
27 Joanna Ejdys Bialystok University of Technology, Poland
28 Abdellah El barkany Sidi Mohamed Ben Abdellah University Faculty of Science and Technology of Fez, Morocco
29 Chiara Franciosi CRAN UMR 7039, Université de Lorraine, France
30 Mose Gallo Materials and Industrial Production Engineering, University of Napoli Federico, Italy
31 Tetiana Galushkina State Ecological Academy of Postgraduate Education and Management, Ukraine
32 Józef Gawlik Cracow University of Technology, Institut of Production Engineering, Poland
33 Rohollah Ghasemi, College of Management, University of Tehran, Iran
34 Arkadiusz Gola, Lublin University of Technology, Faculty of Mechanical Engineering, Poland
35 Alireza Goli Department of industrial engineering, Yazd university, Yazd, Iran
36 Magdalena Graczyk-Kucharska, Politechnika Poznańska, Poland
37 Adriana Grenčíková Industry 4.0, Human factor, Ergonomic, Slovak Republic
38 Patrik Grznár, Department of Industrial Engineering, University of Žilina Faculty of Mechanical Engineering, Slovak Republic
39 Anouar Hallioui INTI International University, Malaysia
40 Adam Hamrol Mechanical Engineering, Poznan University of Technology, Poland
41 ni luh putu hariastuti itats, Indonesia
42 Paula Heliodoro, Polytechnic Institute of Setubal, Portugal
43 Vitalii Ivanov Department of Manufacturing Engineering, Machines and Tools, Sumy State University, Ukraine
44 Ali Jaboob Dhofar University, Oman
45 Zamberi Jamaludin Universiti Teknikal Malaysia Melaka, Malaysia
46 Izabela Jonek-Kowalska, Wydział Organizacji i Zarządzania Politechnika Śląska, Poland
47 Satishbabu ACE India
48 Prasad Kanaka Institute of Industrial Relations and Human Resource Development, India
49 Anna Karwasz Poznan University of Technology, Poland
50 Waldemar Karwowski University of Central Florida, United States
51 Osmo Kauppila University of Oulu, Finland
52 Tauno Kekale Merinova Technology Centre, Finland
53 Mahmoud Khedr Faculty of Engineering at Shoubra, Benha University, Cairo, Egypt, Egypt
54 Peter Kostal Department of Production Systems, Metrology and Asembly, Slovenská Technická Univerzita V Bratislave, Faculty of Material Science and Technology, Slovak Republic
55 Boris Kostow University of Angela Kyncheva in Ruse, Bulgaria
56 Martin Krajčovič, University of Žilina, Faculty of Mechanical Engineering, Slovak Republic
57 Caroline  Kristian Uppsala University, Sweden
58 Robert Kucęba Wydział Zarządzania, Politechnika Częstochowska, Poland
59 Agnieszka Kujawińska Poznan University of Technology
60 Edyta Kulej-Dudek Politechnika Częstochowska, Poland
61 Bhakaporn Kuljirundhorn Foxford University, Canada
62 Rajeev Kumar Doon University, India
63 Sławomir Kłos Institute of Mechanical Engineering, University of Zielona Góra, Poland
64 Yu Lee National Tsing Hua University, Taiwan
65 Anna Lewandowska-Ciszek Department of Logistics, Poznań University of Economics and Business, Poland
66 Wojciech Lewicki West Pomeranian University of Technology in Szczecin, Poland
67 Tetiana Likhouzova National Technical University of Ukraine, “Igor Sikorsky Kyiv Polytechnic Institute”, Ukraine
68 Damjan Maletič University of Maribor, Faculty of Organizational Sciences, Slovenia
69 Marcela Malindzakova Technical University, Slovak Republic
70 Ildiko Mankova Technical University of Košice, Slovakia
71 Arnaud  Marcelline University of Nantes, France
72 Józef Matuszek University of Bielsko-Biała, Poland
73 Marcin Matuszny Department of Production Engineering, Faculty of Mechanical Engineering and Computer Science, University of Bielsko-Biala, ul. Willowa 2, 43-300 Bielsko-Biała
74 Giovanni Mazzuto Università Politecnica Delle Marche, Italy
75 Tomasz Małkus Uniwersytet Ekonomiczny w Krakowie, Katedra Procesu Zarządzania, Poland, Poland
76 Rafał Michalski Katedra Systemów Zarządzania i Rozwoju Organizacji, Politechnika Wrocławska, Poland
77 Jerzy Mikulik AGH University of Krakow, Poland
78 Rami Mokao MIS - Management Information Systems, HIAST, Syria
79 Norsyahida Mokhtar International Islamic University Malaysia, Malaysia
80 Ig. Jaka Mulyana Industrial Engineering, Widya Mandala Surabaya Catholic University, Indonesia
81 Nor Hasrul Akhmal Ngadiman School of Mechanical Engineering, Universiti Teknologi Malaysia, Malaysia
82 Duc Duy Nguyen Department of Industrial Systems Engineering, Ho Chi Minh Technology University (HCMUT), Viet Nam
83 fernando Nino Polytechnic University of San Luis Potos, Mexico
84 Filscha Nurprihatin Sampoerna University, Indonesia
85 Rebecca Oliver Stockton University, United States
86 Anita Pavlenko Kryvyi Rih State University of Economics and Technology, Ukraine
87 Aleksandar Pesic, MB University, Faculty of Business and Law, Belgrade, Serbia, Serbia
88 Huy Phan Education Technology University, Vietnam, Viet Nam
89 Anna Piekarczyk Poznan School of Logistics (WSL), Poland
90 Alin Pop University of Oradea, Romania
91 Humiras Purba Industrial Engineering, Associate Professor, Universitas Mercu Buana, Jakarta, Indonesia, Indonesia
92 Tengku nur Azila Raja Mamat Universiti Tun Hussein Onn Malaysia (UTHM), Malaysia
93 Silvijo  Renato University of Rijeka, Croatia
94 Piotr Rogala Department of Quality and Environmental Management, Wroclaw University of Economics and Business, Poland
95 Michał Rogalewicz, Faculty of Mechanical Engineering, Poznan University of Technology, Poland
96 Izabela Rojek Institute of Computer Science, Kazimierz Wielki University, Poland
97 Adam Sadowski Katedra Strategii i Zarządzania Wartością Przedsiębiorstwa, Uniwersytet Łódzki, Poland
98 Mansia Sadyrova Al-Farabi Kazakh National University, Kazakhstan
99 Nadia Saeed University of the Punjab, Pakistan
100 Sebastian Saniuk Uniwersytet Zielonogórski, Poland
101 Krzysztof Santarek Faculty of Mechanical and Industrial Engineering, Warsaw University of Technology, Poland
102 shankar sehgal Panjab University Chandigarh, India
103 Piotr Senkus University of Warsaw, Poland
104 Jarosław Sęp Politechnika Rzeszowska, Wydział Budowy Maszyn i Lotnictwa, Poland
105 Robert Sika Faculty of Mechanical Engineering and Management, Institute of Materials Technology, Poland
106 Dariusz Sobotkiewicz Instytut Nauk o Zarządzaniu i Jakości, Uniwersytet Zielonogórski, Poland
107 Beata Starzyńska Poznan University of Technology
108 Klaudia Tomaszewska Faculty of Management Engineering, Bialystok University of Technology, Poland
109 Stefan Trzcielinski Poznan University of Technology, Poland
110 Cang Vo Binh Duong University, Viet Nam
111 Somporn Vongpeang Faculty of Technical Education, Rajamangala University of Technology Thanyaburi, Thailand
112 Jaroslav Vrchota University of South Bohemia České Budějovice, Faculty of Economics, Czech Republic
113 Gerhard-Wilhelm Weber Poznań University of Technology, Poland
114 Ewa Więcek-Janka Wydział Inżynierii Zarządzania, Politechnika Poznańska, Poland
115 Linda Winters Czech University of Life Sciences, Czech Republic
116 Zbigniew Wisniewski Lodz University of Technology, Poland
117 Piotr Wróblewski Faculty of Engineering, University of Technology and Economics H. Chodkowska in Warsaw, Poland
118 Iseul  Young Hanyang University, Korea (South)
119 Chong Zhan Hubei University, China
120 Sylwia Łęgowik-Świącik Czestochowa University of Technology Poland, Poland


2025
No. Name Surname Affiliation
1 akshat gaurav akshat Asia University, Taiwan
2 luma Al-kindi University of Technology, Iraq
3 Hind Ali University of Technology, Iraq
4 Katarzyna Antosz Rzeszow University of Technology, Poland
5 Gilmar Batalha Universidade de Sao PauloUniv Sao Paulo, Mech Engn Dept, Escola Politecn, Sao Paulo, SP, Brazil, Brazil
6 Lucia Bednarova Technical University of Kosice, Slovak Republic
7 Anna Burduk Wrocław University of Science and Technology, Poland
8 Danylo Cherevatskyi Institute of Industrial Economics of NAS of Ukraine: Kiev, UA, Ukraine
9 Dorota Czarnecka-Komorowska Faculty of Mechanical Engineering, Poznan University of Technology, Poland
10 SUGANYA Devi National Institute of Technology,Silchar, India
11 Jacek Diakun Poznan University of Technology, Poland
12 Milan Edl University of West Bohemia, Czech Republic
13 João Furtado Santa Cruz do Sul University, Brazil
14 Bożena Gajdzik "Politechnika Śląska Wydział Inżynierii Materiałowej Katedra Informatyki Przemysłowej, Poland"
15 Mose Gallo Materials and Industrial Production Engineering, University of Napoli Federico, Italy
16 Remigiusz Gawlik Department of Public Management, Krakow University of Economics (KUE), Poland
17 Raja Reddy GNV University of Saskatchewan, Canada
18 Arkadiusz Gola Department of Production Informatisation and Robotisation, Lublin University of Technology,Poland
19 Alireza Goli Department of industrial engineering, Yazd university, Yazd, Iran Iran, Iran
20 Cristian Gómez Universidad Nacional de Colombia, Colombia
21 José-Armando HIDALGO CRESPO ENSAM, Spain
22 Magdalena HRYB Faculty of Mechanical Engineering, Poznan University of Technology, Poland
23 Katarzyna Hys Opole University of Technology, Poland
24 Izabela Jonek-Kowalska "Wydział Organizacji i Zarządzania Politechnika Śląska, Poland"
25 Amirhossein Karamoozian, University of Chinese Academy of Sciences, China
26 Anna Karwasz Poznan University of Technology, Poland
27 khaoula khlie Liwa college, Morocco
28 Jerzy Kisilowski
29 Peter Kostal, Slovenská Technická Univerzita V Bratislave, Faculty of Material Science and Technology, Slovak Republic
30 Herbert Kotzab Institute for Logistics and Supply Chain Management, University of Bremen, Germany
31 Martin Krajčovič University of Žilina, Faculty of Mechanical Engineering, Slovak Republic
32 Krzysztof Krystosiak Toronto Metropolitan University, Graphic Communications Management, Canada
33 Wiesław Kuczko Poznan University of Technology, Poland
34 Agnieszka Kujawińska Poznan University of Technology, Poland
35 Edyta Kulej-Dudek Politechnika Częstochowska, Poland
36 Anup Kumar Inst Management Technol NagpurInst Management Technol Nagpur, Nagpur, Maharashtra, India, India
37 Sławomir Kłos Institute of Mechanical Engineering, University of Zielona Góra, Poland
38 Quynh Le Song Thanh Ho Chi Minh Technology University, Viet Nam
39 Yu Lee National Tsing Hua University, Taiwan
40 Stanisław Legutko Faculty of Mechanical Engineering, Poznan University of Technology, Poznan, Poland, Poland
41 Anna Lewandowska-Ciszek Department of Logistics, Poznań University of Economics and Business, Poland
42 José Machado University of Minho · School of Engineering, Portugal
43 Damjan Maletič University of Maribor, Faculty of Organizational Sciences, Slovenia
44 Marcela Malindzakova Technical University, Slovak Republic
45 Tomasz Malkus Department of Management Process, Cracow University of Economics, Poland
46 Mengistu Manaye, Kombolcha Institute of Technology, Wollo University, Ethiopia, Ethiopia
47 Marcin Matuszny, Faculty of Mechanical Engineering and Computer Science, University of Bielsko-Biala, Poland
48 Tomasz Małkus, Uniwersytet Ekonomiczny w Krakowie, Katedra Procesu Zarządzania, Poland, Poland
49 Rami Mokao MIS - Management Information Systems, HIAST, Syria
50 Beata Mrugalska Poznan University of Technology, Poland
51 Ig. Jaka Mulyana Industrial Engineering, Widya Mandala Surabaya Catholic University, Indonesia
52 fernando Nino Polytechnic University of San Luis Potos, Mexico
53 Shimon Nof Purdue University, United States
54 Hana Pacaiová KLI, Faculty of Mechanical Engineering, Faculty of Aeronautics, Technical University of Košice, Slovak Republic
55 Arun Kiran Pal Printing Engineering Department, Jadavpur University, India
56 Michal Patak University of Pardubice, Czech Republic
57 Ivan Pavlenko Department of General Mechanics and Machine Dynamics, Sumy State University, Ukraine
58 Miriam Pekarcikova Department of industrial and digital engineering, Technical University of Košice, Faculty of Mechanical Engineering, Slovak Republic
59 Alin Pop University of Oradea, Romania
60 Praveen Prabhu School of Engineering and Technology, Shivaji University, Kolhapur., India
61 Humiras Purba Industrial Engineering, Associate Professor, Universitas Mercu Buana, Jakarta, Indonesia, Indonesia
62 Paulina Rewers Faculty of Mechanical Engineering, Poznań University of Technology, Poland
63 Michał Rogalewicz Division of Production Engineering, Institute of Materials Technology, Faculty of Mechanical Engineering, Poznan University of Technology, Poland
64 Izabela Rojek Institute of Computer Science, Kazimierz Wielki University, Poland
65 David Romero Tecnológico de Monterrey, Mexico
66 Adam Sadowski Katedra Strategii i Zarządzania Wartością Przedsiębiorstwa, Uniwersytet Łódzki, Poland
67 Abdu Salam Abdul Wali Khan Univ MardanAbdul Wali Khan Univ Mardan, Dept Comp Sci, Mardan 23200, Pakistan, Pakistan
68 fernando sampaio KMITL, Brazil
69 Sebastian Saniuk Uniwersytet Zielonogórski, Poland
70 Iman Sharaf "Higher Technological Institute - Egypt Higher Technol Inst, Dept Basic Sci, Cairo, Egypt, Egypt"
71 Robert Sika Faculty of Mechanical Engineering and Management, Institute of Materials Technology, Poland
72 Beata Starzyńska Poznan University of Technology
73 Robert Ulewicz Politechnika Częstochowska, Poland
74 Wiesław Urban Politechnika Białostocka, Poland
75 Cang Vo Binh Duong University, Viet Nam
76 Jaroslav Vrchota University of South Bohemia České Budějovice, Czech Republic
77 Ewa Więcek-Janka Wydział Inżynierii Zarządzania, Politechnika Poznańska, Poland
78 Sylwia Łęgowik-Świącik Czestochowa University of Technology Poland, Poland

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