Using quantum spherical fuzzy decision support system as a novel sustainability index approach for analyzing industries listed in the stock exchange

Kayacık, Mahmut; Dınçer, Hasan; Yüksel, Serhat

doi:10.1016/j.bir.2022.10.001

Cited by 47 publications

(9 citation statements)

References 62 publications

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“…In conjunction with that, another literary gem revealed a procedure for constructing a DSS backwards analysis sensitivity model for effective interventions and maintenance in manufacturing using the example of a predictive mode from the electronics industry (Shojaeinasab et al, 2022), where this model is being used in the steel industry for the development and testing of production execution systems (Lee at el., 2020). In addition, smart manufacturing technologies have also utilised this model to provide decision-making support to manufacturers via enhanced monitoring, analysis, modelling, and simulation to generate increasingly better intelligence about manufacturing systems (Connell et al, 1992;Kayacık et al, 2022). However, obstacles and challenges have hindered the adoption of smart manufacturing technologies, and efforts are required to promote a common understanding among the manufacturing community that can enable standardisation efforts and the innovation required to continue the adoption and use of smart manufacturing technologies (Noriega, 2020;Jakku et al, 2010).…”

Section: Recent Decision Support System (Dss) Trendsmentioning

confidence: 99%

How well do decision support systems help decision makers? An examination of adopting lean manufacturing processes

Shafee,

Mohamad,

Rahman

et al. 2024

Multidiscip. Rev.

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Choice is crucial for industrial enterprises as their success or failure may depend on it. Consequently, emerging technologies, especially Industry 4.0 (I4.0) are making precision decisions and enabling enriching collaborations with the industry’s computer-assisted decision support systems (DSSs). However, the arrival of Industry 4.0 poses challenges to this emerging application in terms of data variations and interconnectivity. A thorough search across Scopus, Web of Science, and Emerald Science databases yielded 2023 relevant documents. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), the top 250 academic documents were meticulously filtered and analysed in this study. The analysis resulted in the classification of the four main purposes of a DSS as data evaluation, optimisation, scheduling, and selection. The research also investigated the impact of DSSs on the performance of lean manufacturing (LM). Next, this research discussed the controversies with regard to the confidence, prejudice, and discrimination of users, discipline-based DSS application bias, as well as criticisms and suggestions for the future development of DSS, especially in the manufacturing industry. It is believed that, based on its novel findings, this work will pave the way for future research in the same field.

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Section: Recent Decision Support System (Dss) Trendsmentioning

confidence: 99%

How well do decision support systems help decision makers? An examination of adopting lean manufacturing processes

Shafee,

Mohamad,

Rahman

et al. 2024

Multidiscip. Rev.

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“…Hence, this theory is used with fuzzy decision-making methodology in this study to minimize uncertainties. Equations ( 1)-(3) denote this situation where u refers to event, θ shows phase angle, φ 2 identify amplitude and ς indicates a collection of events (Kayacık et al, 2022).…”

Section: Quantum-based Fuzzy Sets With Golden Ratiomentioning

confidence: 99%

Neuro quantum-inspired decision-making for investor perception in green and conventional bond investments

Birzhanova,

Nurgaliyeva,

Nurmagambetova

et al. 2024

Investment Management and Financial Innovations

Self Cite

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The purpose of this study is to make a comprehensive analysis of investor perceptions in the context of green and conventional bond investments. For this purpose, a new model is presented by considering two steps. First, a criteria set is generated by considering balanced scorecard perspectives that are finance, customer, organizational effectiveness and learning and growth. After that, the neuro Quantum fuzzy M-SWARA method is considered to weight these criteria. Secondly, seven critical determinants for bond investments are identified that are coupon rates, volume, maturity, riskiness, liquidity, volatility, and tax considerations. Neuro Quantum fuzzy TOPSIS approach is employed to rank these factors. The main contribution of the study is that by combining the balanced scorecard framework and quantum-inspired decision-making techniques, this paper offers a novel and sophisticated decision-making model to understanding investor behavior. Similarly, in the proposed model, a new methodology is generated by the name of M-SWARA. In this framework, some enhancements are adopted to the SWARA technique. The weighting results indicate that meeting customer expectations is the most critical factor that affects the investor perception to make investments to the bonds. Moreover, according to the ranking results, it is concluded that coupon rates are the most important item for both conventional and green bond investors. On the other hand, with respect to the conventional bond investor, tax is the second most essential factor. However, regarding the green bond investors, volatility plays a critical role. AcknowledgmentThis research has been/was/is funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (№ AP 19679105 “Transformation of ESG financial instruments in the context of the development of the green economy of the Republic of Kazakhstan”).

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“…Quantum mechanics aim to understand the probabilities of various conditions. In this context, angles (𝜃 2 ) and amplitude results (𝜑 2 ) are taken into consideration (Kayacık et al, 2022). This situation helps to solve complex problems in a more effective manner (Yüksel and Dinçer, 2023).…”

Section: Quantum Spherical Fuzzy Sets With Golden Cutmentioning

confidence: 99%

Serving SDGs via Bank Mergers: Neuro-Quantum Fuzzy Analysis of SDG-Based Bank Mergers in Qatar

Al-Binali¹,

Aysan²,

Dınçer³

et al. 2023

Preprint

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This paper analyzes the potential strategies for a bank merger from a Sustainable Development Goals (SDG) perspective, focusing on three key criteria: profitability, market share, and service quality. In the short-term, the merged bank should prioritize optimizing financial performance through cost management, revenue stream identification, and risk management practices. Market share expansion can be achieved through targeted customer acquisition and retention efforts, market research, and competitive analysis. Service quality can be enhanced through improved customer service, efficient complaint resolution processes, and leveraging technology. These short-term plans align the merged bank's operations with the identified criteria and promote responsible banking practices that contribute towards the SDGs. In the long-term, the merged bank should focus on diversifying revenue streams, expanding its customer base, and optimizing cost structure. Long-term strategies should include establishing a strong brand presence, customer loyalty programs, and continuous improvement in service quality. The paper emphasizes the importance of monitoring progress, making necessary adjustments, and aligning with SDGs for sustained profitability and long-term success in the marketplace. The findings of this study provide valuable insights for banks considering a merger and highlight the significance of considering SDGs in their strategic planning.

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Using quantum spherical fuzzy decision support system as a novel sustainability index approach for analyzing industries listed in the stock exchange

Cited by 47 publications

References 62 publications

How well do decision support systems help decision makers? An examination of adopting lean manufacturing processes

How well do decision support systems help decision makers? An examination of adopting lean manufacturing processes

Neuro quantum-inspired decision-making for investor perception in green and conventional bond investments

Serving SDGs via Bank Mergers: Neuro-Quantum Fuzzy Analysis of SDG-Based Bank Mergers in Qatar

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