An accuracy-enhanced group recommendation approach based on DEMATEL

Wang, Yuqing; Qi, Lianyong; Dou, Ruihan; Shen, Shigen; Hou, Lijun; Liu, Yuwen; Yang, Yehui; Kong, Lingzhen

doi:10.1016/j.patrec.2023.02.008

Cited by 12 publications

(5 citation statements)

References 57 publications

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“…Altuntas and Gok [22] applied DEMATEL to making correct quarantine decisions, aiming to reduce the burden of the COVID-19 pandemic on the hospitality industry. Wang et al [23] suggested a new approach for group recommendation, named GroupRecD, which utilizes data mining and the DEMATEL technique to allocate user weights scientifically and rationally. Si et al [24] conducted a systematic review of DEMATEL.…”

Section: Mcdm Methodsmentioning

confidence: 99%

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Ranking Startups Using DEMATEL-ANP-based Fuzzy PROMETHEE II

Nguyen¹,

Chu²

2023

Preprint

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Accelerators play a critical role in fostering innovative ecosystems and nurturing startups. The evaluation and selection of startups, particularly technology-based startups, for acceleration programs are essential in accelerator economy and management. Assessment of startups requires consideration of numerical and qualitative criteria such as sales, prior startup experience, demand validation, and product maturity. Startups must be ranked based on the varying importance of criteria, which can be identified as a fuzzy multi-criteria decision-making (MCDM) problem. MCDM methods have proven effective in managing complex problems. However, the use of MCDM techniques in startup selection and evaluation of criteria interrelationships from the accelerator perspective is yet to be researched. This study proposes a hybrid DEMATEL-ANP-based fuzzy PROMETHEE II model to rank startups and examine the interrelationships between factors. The final preference values are fuzzy numbers, making a fuzzy ranking method necessary for decision-making. An extension of ranking fuzzy numbers using a spread area-based relative maximizing and minimizing set is suggested to improve the flexibility of existing ranking MCDM methods. Algorithms and formulas are derived and a comparison demonstrates the merits of the proposed method. Finally, a numerical experiment is designed to address the viability of the hybrid DEMATEL-ANP-based fuzzy PROMETHEE II model.

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Section: Mcdm Methodsmentioning

confidence: 99%

“…Next, the prominence (D+R) and relation (D-R) values are calculated using Eqs. ( 22) and (23). Thereafter, the threshold value is set, which determines the filtered factors.…”

Section: Aamentioning

confidence: 99%

Ranking Startups Using DEMATEL-ANP-based Fuzzy PROMETHEE II

Nguyen¹,

Chu²

2023

Preprint

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“…Altuntas and Gok [25] applied DEMATEL to making correct quarantine decisions, aiming to reduce the burden of the COVID-19 pandemic on the hospitality industry. In 2023, Wang et al [26] suggested a new approach for group recommendation, named GroupRecD, which utilizes data mining and the DEMATEL technique to allocate user weights scientifically and rationally. Si et al [27] conducted a systematic review of DEMATEL.…”

Section: Dematelmentioning

confidence: 99%

Ranking Startups Using DEMATEL-ANP-Based Fuzzy PROMETHEE II

Nguyen

Chu

2023

Axioms

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In entrepreneurship management, the evaluation and selection of startups for acceleration programs, especially technology-based startups, are crucial. This process involves considering numerical and qualitative criteria such as sales, prior startup experience, demand validation, and product maturity. To effectively rank startups based on the varying importance of these criteria, a fuzzy multi-criteria decision-making (MCDM) approach is needed. Although MCDM methods have been successful in handling complex problems, their application in startup selection and evaluating criteria interrelationships from the accelerator perspective is underexplored. To address this gap, a hybrid DEMATEL-ANP-based fuzzy PROMETHEE II model is proposed in this study, facilitating startup ranking and examining interrelationships among factors. The resulting preference values are fuzzy numbers, necessitating a fuzzy ranking method for decision-making. An extension of ranking fuzzy numbers using a spread area-based relative maximizing and minimizing set is suggested to enhance the flexibility of existing ranking MCDM methods. Algorithms, formulas, and a comparative analysis validate the proposed method, while a numerical experiment verifies the viability of the hybrid model. The final ranking of four startup projects is A4<A1<A3<A2 which indicates that startup project A2 has the highest comprehensive potential, followed by startup project A3.

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“…MCDM is widely used to solve highly complex and uncertain decision-making problems in many areas that traditional methods cannot solve. DEMATEL was developed in the 1970s for evaluating interdependent relationships among factors; it has gained popularity in recent years [28,29]. In general, DEMATEL is a mathematical computational method that aims to explore the cause-effect relationship among criteria.…”

Section: Literature Reviewmentioning

confidence: 99%

Key Factors for a Successful OBM Transformation with DEMATEL–ANP

et al. 2023

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Production costs and global competition have increased sharply in recent years, forcing manufacturers to upgrade to the original brand manufacturer (OBM) to survive and thrive and capture more profit margins. However, studies that explore key factors that affect the success of such an important transition are lacking. Therefore, this study aims to investigate the key factors that will influence the success of contract manufacturers to upgrade to the OBM on the basis of a decision-making trial and evaluation laboratory with an analytic network process. Our results identify six key factors that exhibit a cause-and-effect relationship among the key criteria. Moreover, organizational innovation will determine the difference between the success and the failure of an OBM transition apart from material and component stability. Our findings can help researchers, policy makers, and practitioners increase their understanding of how to upgrade manufacturers successfully in global value chains.

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An accuracy-enhanced group recommendation approach based on DEMATEL

Cited by 12 publications

References 57 publications

Ranking Startups Using DEMATEL-ANP-based Fuzzy PROMETHEE II

Ranking Startups Using DEMATEL-ANP-based Fuzzy PROMETHEE II

Ranking Startups Using DEMATEL-ANP-Based Fuzzy PROMETHEE II

Key Factors for a Successful OBM Transformation with DEMATEL–ANP

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