Hybrid Rough Set and Data Envelopment Analysis Approach to Technology Prioritisation

Chodakowska, Ewa; Nazarko, Joanicjusz

doi:10.3846/tede.2020.12538

Cited by 9 publications

(5 citation statements)

References 83 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…e residual histogram and the normal probability diagram (P − P diagram) show that the residual is normal. e residual determined by the scatter plot of the normalized residual prediction value satisfies the isovariance [18]. As shown in Table 10, the correlation analysis of entrepreneurial attitude, subjective norms, perceived behavior control, and entrepreneurial intention is carried out.…”

Section: Regression Analysis Of Entrepreneurialmentioning

confidence: 99%

Exploring the Entrepreneurship Training Mode of Medical Students in Beijing-Tianjin-Hebei Universities under the Strategic Background of “Healthy China” from the Perspective of Mixed Big Data

Gong

Wang

Jiangtao

2022

Mobile Information Systems

View full text Add to dashboard Cite

In order to solve the problem that postgraduates are affected by the traditional concept of career choice of the native family and their entrepreneurial intention is obviously low, a method to explore the entrepreneurial spirit training model of medical students in Beijing-Tianjin-Hebei colleges and universities from the perspective of mixed big data is proposed. This article chooses to conduct research by conducting a survey on the entrepreneurial willingness of postgraduates in universities in the Beijing-Tianjin-Hebei and its influencing factors. From the perspective of master students from five universities in the Beijing-Tianjin-Hebei region, the selection of personal background information, entrepreneurial attitude, subjective norms, perceived behavior control, and entrepreneurship education index factors establish the index system of the influencing factors of graduate students’ entrepreneurial intention and use the TPB theoretical model and SPSS data statistics and other tools to analyze the obtained data results. The results show that gender, major, place of origin, part-time experience, and entrepreneurial experience of relatives and friends correspond to 0.000, 0.000, 0.482, 0.172, 0.003, and 0.004, respectively. It can be seen that the independent variables, major and place of origin, have no statistical significance. In the statistics of college students’ willingness to start a business, 23.33% of the students said “nothing at all,” and 27.8% of the students said “thought, but would not start a business.” It can be seen that entrepreneurial attitude, subjective norm, and perceived behavioral control all positively affect entrepreneurial willingness, and only learning ability, opportunity grasping ability, self-recognition ability, and decisiveness have a significant effect on entrepreneurial willingness.

show abstract

Section: Regression Analysis Of Entrepreneurialmentioning

confidence: 99%

Exploring the Entrepreneurship Training Mode of Medical Students in Beijing-Tianjin-Hebei Universities under the Strategic Background of “Healthy China” from the Perspective of Mixed Big Data

Gong

Wang

Jiangtao

2022

Mobile Information Systems

View full text Add to dashboard Cite

show abstract

“…Many scholars have proposed various methodologies regarding the inevitable importance of sustainable supplier selection. In this paper, the literature has been restricted to sustainable supplier selection methodologies since 2012, including those using the fuzzy interference system [12], Fuzzy AHP (Analytic Hierarchy Process), Fuzzy Multi-Objective Linear Programming [13], Decision-making Trial and Evaluation Laboratory (DEMATEL) approach [14], Fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) [15], Rough set theory and Data Envelopment Analysis (DEA) [16], (Analytic Network Process) ANP and improved GRA (Grey Relational Analysis) [17], Fuzzy axiomatic design [18], a fusion of fuzzy information approach, 2-tuple linguistic [19], Bayesian framework with Monte Carlo Markov Chain (MCMC) simulation [20], Grey DEMATEL [21], AHP and Taguchi loss functions [22], ANP and improved Grey relational analysis [23], the integrated framework of enhanced Russell measure and data envelopment analysis [24], the integrated Fuzzy sets, and (Viekriterijumsko Kompromisno Rangiranje) VIKOR and TOPSIS [25].…”

Section: Supply Chain Methodologiesmentioning

confidence: 99%

A Hybrid Grey Decision Methodology in Social Sustainable Supplier Selection

Nasseri,

Chen,

Huo

et al. 2023

Sustainability

View full text Add to dashboard Cite

In the past decade, sustainable supply chain management has received much attention from practitioners and academics due to the heightened emphasis on environmental, economic, and social sustainability by customers, for-profit and non-profit institutions, community organizations, legislation, and government oversight. Evaluating and selecting a suitable supplier is considered a critical choice, crucial in supply chain management. Social sustainability in the supplier selection process is an important factor that has not received sufficient attention from academicians. Social and societal challenges are increasingly impacting supply chains. To tackle this challenge in the agricultural section of nations with emerging economies, this study proposed a new methodology using Grey FUCOM (Full Consistency Method) and Gray PROMTHEE (Preference Ranking Organization Method for Enrichment Evaluation) methods for evaluating the social sustainability of wheat and barley seed production companies. This study assists seed users in identifying the most significant supplier selection criteria and one of the most effective suppliers for ecological sustainability throughout the supply chain while maintaining market competitiveness. The results demonstrated a consistent and dependable rating behavior about the weight coefficients of the criteria. Improving the procedures used to evaluate wheat and barley seed suppliers results in a healthier society. So, the proposed model can efficiently evaluate a critical component of the food supply chain in the early stages.

show abstract

“…He has authored or co-authored 39 chapters in collective publications, 80 scientific articles and 77 abstracts, speeches or communications. He has published in reputable scientific journals, for example IEEE Transactions on Power Delivery (Broadwater et al, 1997), IEEE Transactions on Power Systems (Sargent et al, 1994), IEEE Transactions on Engineering Management (Nazarko et al, 2022b), IEEE Sensors Journal (Gao et al, 2021), Foresight and STI Governance (Ejdys et al, 2019), Progress in Planning (Bokun & Nazarko, 2023), and Technological and Economic Development of Economy (Chodakowska & Nazarko, 2020b;. Many of his works are indexed in prestigious scientific databases such as Web of Science and Scopus.…”

Section: Scientific Work and Accomplishmentsmentioning

confidence: 99%

Exploring the Synergy of Technical and Social Sciences: An Overview of Professor Joanicjusz Nazarko’s 45-Year Scientific Journey

Wilczewska,

Bokun,

Ginevičius

2024

Journal of Business Economics and Management

View full text Add to dashboard Cite

This article presents Professor Joanicjusz Nazarko’s outstanding achievements in research, scientific cooperation, teaching and organizational work, in celebration of the 45th jubilee of his scientific work. Over the years, Professor Nazarko has contributed significantly to the development of technical and social sciences in Poland. He authored more than 300 publications, which constitutes a substantial knowledge base on its own. Using bibliometric and statistical methods and techniques, we present an overview of Professor’s most important scientific achievements and major works. We also highlight his efforts to establish a national and international network for scientific cooperation. Lastly, we present his didactic successes. This jubilee serves as the opportunity to recognize and honour Professor Joanicjusz Nazarko’s significant contribution to the development of science in Poland.

show abstract

Hybrid Rough Set and Data Envelopment Analysis Approach to Technology Prioritisation

Cited by 9 publications

References 83 publications

Exploring the Entrepreneurship Training Mode of Medical Students in Beijing-Tianjin-Hebei Universities under the Strategic Background of “Healthy China” from the Perspective of Mixed Big Data

Exploring the Entrepreneurship Training Mode of Medical Students in Beijing-Tianjin-Hebei Universities under the Strategic Background of “Healthy China” from the Perspective of Mixed Big Data

A Hybrid Grey Decision Methodology in Social Sustainable Supplier Selection

Exploring the Synergy of Technical and Social Sciences: An Overview of Professor Joanicjusz Nazarko’s 45-Year Scientific Journey

Contact Info

Product

Resources

About