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Decision-Making Process and Its Application to Business Analytic
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Decision-Making Process and Its Application to Business Analytic

A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Systems Practice in Social Science".

Deadline for manuscript submissions: closed (20 August 2022) | Viewed by 45907

Special Issue Editor

Dr. Harish Garg

E-Mail Website
Guest Editor
School of Mathematics, Thapar Institute of Engineering & Technology (Deemed University), Patiala 147004, Punjab, India
Interests: expert systems; aggregation operators; reliability & maintenance analysis; computational intelligence; multi-criteria decision making problems; optimization techniques; nature inspired algorithms; intuitionistic fuzzy set theory
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Fuzzy modeling has been applied in a wide variety of fields, such as Engineering and Management Sciences and Social Sciences, to solve a number decision-making problems which involve impreciseness, uncertainty and vagueness in data. Due to the digitalization process these days, the concept of business analytics (BA) is considered a significant investment for enterprises because they have the potential to considerably improve firms’ performance. The research and advances in BA are able to discover the hidden information in the data, improve decision-making processes, and support strategic planning. Among the different techniques, tools and methodologies used in BA, fuzzy logic and soft computing have a prominent position because of the adaptive mechanisms to enable or facilitate intelligent behaviour in complex and changing environments in which BA is usually applied.

In real life problems, multiple criteria and multiple alternatives involved in decision-making process which are always in conflictness in nature, and hence the multi-criteria decision-making (MCDM) methods play an important role in BA practices. To analyze the hidden information about the input related to the various computations, there is a proper need to utilize the appropriate MCDM method so as to get the predictive analytics which exemplify the roles.

This Special Issue aims to publish research articles presenting fuzzy and soft computing-based techniques in the emerging field of business analytic. More specifically, it seeks contributions related to the theory and applications fuzzy techniques including, but not limited to:

  • Intelligent decision analysis;
  • Extensions of fuzzy sets;
  • Decision-making under uncertainty;
  • Behaviour decision;
  • Fuzzy decision-making approaches;
  • Soft computing with application to business analytic;
  • Applications of decision-making in business analytics;
  • Enterprise knowledge computing and evaluation;
  • Decision-support system;
  • Economic decisions with knowledge-based systems;
  • Multiple criteria decision making;
  • Uncertainty analysis;
  • Fuzzy set theory;
  • Knowledge management systems;
  • Strategic decision making;
  • Fuzzy clustering and reasoning.

Dr. Harish Garg
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Systems is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (17 papers)

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Research

22 pages, 4431 KiB  
Article
Comprehensive Evaluation of Low-Carbon City Competitiveness under the “Dual-Carbon” Target: A Cross-Sectional Comparison between Huzhou City and Neighboring Cities in China
by Shouzhen Zeng, Yi Chu, Yiling Yang, Pengkun Li and Huihong Liu
Systems 2022, 10(6), 235; https://doi.org/10.3390/systems10060235 - 27 Nov 2022
Cited by 2 | Viewed by 1323
Abstract
Under the background of “dual-carbon” target construction, the low-carbon environmental protection and ecological construction of Huzhou city in China have received high attention. To scientifically measure the low-carbon construction effect of the city, this study constructs a reasonable comprehensive evaluation system of low-carbon [...] Read more.
Under the background of “dual-carbon” target construction, the low-carbon environmental protection and ecological construction of Huzhou city in China have received high attention. To scientifically measure the low-carbon construction effect of the city, this study constructs a reasonable comprehensive evaluation system of low-carbon city competitiveness from four aspects, including low-carbon economic foundation, low-carbon lifestyle, low-carbon environmental construction, and low-carbon technology development. An integrated weight model of attributes consisting of the analytic hierarchy process (AHP) and entropy weight method is then established, and on this basis, an integrated TOPSIS model is constructed to assess the development of low-carbon competitiveness in Huzhou City. A horizontal comparative analysis of five cities around Huzhou is also conducted, and the current level of low-carbon competitiveness of cities in the central region of the Yangtze River Delta is further explored. Finally, several relevant reference suggestions for Huzhou city are provided to build an ecological model city and a green low-carbon national model and help the government to accelerate the pace of building a low-carbon city in the whole region. Full article
(This article belongs to the Special Issue Decision-Making Process and Its Application to Business Analytic)
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25 pages, 2230 KiB  
Article
The Capacity Decision-Making of Omnichannel Catering Firms Based on Queueing System Considering Customer Reference Behavior
by Wen-Tao Zhan, Xue-Ping Wang, Ming-Hui Jiang, Han Jiang, Da Huo and Yun-Tao Liu
Systems 2022, 10(6), 229; https://doi.org/10.3390/systems10060229 - 21 Nov 2022
Cited by 1 | Viewed by 3238
Abstract
Omnichannel catering firms need to pay attention to the consumer behavior of customers in both online and offline channels to make the corresponding capacity decisions. However, customers’ consumption behavior is not only affected by base utility, but also by reference utility, which indicates [...] Read more.
Omnichannel catering firms need to pay attention to the consumer behavior of customers in both online and offline channels to make the corresponding capacity decisions. However, customers’ consumption behavior is not only affected by base utility, but also by reference utility, which indicates that customers have reference dependence when making consumption decisions. In order to better help omnichannel catering firms to make capacity decisions more in line with customer consumption behavior in their actual operations, this paper adopts the queuing theory to construct an optimal capacity decision-making model for omnichannel catering firms. We also analyzed the impact of channel information availability on customer reference behavior and the subsequent impact on the firm’s optimal decision-making. The findings were as follows: when the channel information is unavailable, customers in each channel take their expectation of waiting time as the reference point. With the improvement of the sensitivity of customers in different channels to the reference point, firms should improve their safety capacity to meet customers’ needs. Moreover, at a higher reference point, the increase in customer sensitivity can make the firm obtain higher profits. When channel information is available, customers take the waiting time of customers in different channels as the reference point, and the increased sensitivity of online customers to the reference point will prompt firms to reduce safety capacity. Comparing the two scenarios, we also found that omnichannel catering firms could develop lower safety capacities and obtain higher profits more easily when channel information is available. This not only contributes to the development of omnichannel catering firms, but also expands the application scope of reference theory. Full article
(This article belongs to the Special Issue Decision-Making Process and Its Application to Business Analytic)
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27 pages, 1485 KiB  
Article
Selection of Third-Party Reverse Logistics Service Provider Based on Intuitionistic Fuzzy Multi-Criteria Decision Making
by Jiekun Song, Lina Jiang, Zhicheng Liu, Xueli Leng and Zeguo He
Systems 2022, 10(5), 188; https://doi.org/10.3390/systems10050188 - 14 Oct 2022
Cited by 8 | Viewed by 1693
Abstract
The scientific selection of a third-party reverse logistics service provider (3PRLP) is helpful for enterprises to obtain the expected ecological and economic benefits. Different enterprises have different requirements for 3PRLP selection and, thus, should adopt personalized and simplified evaluation criteria. However, there is [...] Read more.
The scientific selection of a third-party reverse logistics service provider (3PRLP) is helpful for enterprises to obtain the expected ecological and economic benefits. Different enterprises have different requirements for 3PRLP selection and, thus, should adopt personalized and simplified evaluation criteria. However, there is a lack of research on criteria screening. Therefore, this paper proposes a criteria screening method based on a rough set for the first time. The 3PRLP selection is a multi-criteria decision making (MCDM) problem in essence, and different criteria can be expressed in different forms. The existing research mostly uses one method for 3PRLP selection, lacking the comprehensive application of various methods. In this paper, various criteria values are transformed into intuitionistic fuzzy numbers (IFNs) for the comparison and combination of various intuitionistic fuzzy MCDM methods. In terms of criteria weighting, a subjective weighting method based on an analytical network process (ANP) is proposed due to the possible correlation between the criteria at the same level. Meanwhile, an objective weighting method based on intuitionistic fuzzy entropy is proposed. The subjective and objective weights are integrated to form the more scientific combination weights. Combining the modeling principles of different intuitionistic fuzzy MCDM methods, the representative methods under each principle are chosen to build a combination evaluation idea that integrates multiple single evaluation models, and the specific evaluation steps are given, including the single evaluation, Kendall compatibility test, combination evaluation, and Spearman consistency test. An illustrative example of 3PRLP selection is provided to verify the feasibility of the methods of criteria screening and weighting and the combination evaluation idea. Full article
(This article belongs to the Special Issue Decision-Making Process and Its Application to Business Analytic)
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24 pages, 805 KiB  
Article
Optimal Capacity Decision-Making of Omnichannel Catering Merchants Considering the Service Environment Based on Queuing Theory
by Wentao Zhan, Minghui Jiang and Xueping Wang
Systems 2022, 10(5), 144; https://doi.org/10.3390/systems10050144 - 07 Sep 2022
Cited by 5 | Viewed by 1798
Abstract
Many catering merchants are currently adopting omnichannel sales methods. At a restaurant, customers can place their orders, and while waiting for the food to be completed, they can enjoy the restaurant’s service environment. Online customers, by placing orders on various apps, can skip [...] Read more.
Many catering merchants are currently adopting omnichannel sales methods. At a restaurant, customers can place their orders, and while waiting for the food to be completed, they can enjoy the restaurant’s service environment. Online customers, by placing orders on various apps, can skip the queue, increasing their utility by reducing the opportunity cost, but they cannot enjoy the restaurant’s service environment. For merchants, it is important to adequately address how to choose the optimal capacity to provide services to customers in different channels and obtain optimal profits based on the service environment. In this paper, we establish a stylized theoretical model to study the impact of the service environment on customers’ shopping behavior online and offline, and we study how merchants can formulate the optimal capacity. Our main results are as follows: First, improving the service environment was conducive to reducing the merchants’ safety capacity and could help them obtain higher profits. In short-term omnichannel operations, merchants obtained higher profits than in traditional offline single-channel operations. Improving the service environment increased profits, but the profit difference between short-term omnichannel and offline single-channel operations gradually decreased. Finally, in long-term operations, the process of online customers transferring to offline channels based on a high-quality service environment might be detrimental to merchants’ profits. Full article
(This article belongs to the Special Issue Decision-Making Process and Its Application to Business Analytic)
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19 pages, 1161 KiB  
Article
Method of Software Development Project Duration Estimation for Scrum Teams with Differentiated Specializations
by Vasyl Teslyuk, Anatoliy Batyuk and Volodymyr Voityshyn
Systems 2022, 10(4), 123; https://doi.org/10.3390/systems10040123 - 17 Aug 2022
Cited by 7 | Viewed by 3152
Abstract
Estimation is an essential step of software development project planning that has a significant impact on project success—underestimation often leads to problems with the delivery or even causes project failure. An important aspect that the classical estimation methods are usually missing is the [...] Read more.
Estimation is an essential step of software development project planning that has a significant impact on project success—underestimation often leads to problems with the delivery or even causes project failure. An important aspect that the classical estimation methods are usually missing is the Agile nature of development processes in the implementation phase. The estimation method proposed in this article aims at software development projects implemented by Scrum teams with differentiated specializations. The method is based on the authors’ system of working-time balance equations and the approach to measuring project scope with time-based units—normalized development estimates. In order to reduce efforts spent on the estimation itself, an analysis of dependencies among project tasks is not mandatory. The outputs of the methods are not recommended to be treated as commitments; instead, they are supposed to be used to inform project stakeholders about the forecasted duration of a potential project. The method is simple enough to allow even an inexpensive spreadsheet-based implementation. Full article
(This article belongs to the Special Issue Decision-Making Process and Its Application to Business Analytic)
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17 pages, 2464 KiB  
Article
Optimization of the Decision-Making System for Advertising Strategies of Small Enterprises—Focusing on Company A
by Jihoon Jeong, Dongchul Hong and Sekyoung Youm
Systems 2022, 10(4), 116; https://doi.org/10.3390/systems10040116 - 06 Aug 2022
Cited by 1 | Viewed by 1951
Abstract
In the post-COVID-19 era, the founding rates of micro enterprises and startups will increase due to the low youth employment rates and increased retirement of baby boomers. Therefore, the portion of small enterprises among all enterprises is expected to grow. The rapid change [...] Read more.
In the post-COVID-19 era, the founding rates of micro enterprises and startups will increase due to the low youth employment rates and increased retirement of baby boomers. Therefore, the portion of small enterprises among all enterprises is expected to grow. The rapid change in consumption patterns due to the COVID-19 pandemic has accelerated the entry of small enterprises into the online advertising market. However, advertising costs spent in running the businesses are taking up a large portion of their sales budgets due to intense competition and various advertising platforms. This study examines the decision-making system to optimize advertising expenditures considering the difference in advertising costs depending on various media types and keywords based on limited advertising budgets for stable management of small enterprises. To this end, this study modeled the advertising system of small enterprise A (Company A) with system dynamics and used the Java-based simulation software AnyLogic. Through simulation modeling, we conducted optimization analysis of two scenarios, maximum buyers and minimum advertising costs, in the post-COVID-19 era. Based on the results, this study forecast the conditions for optimization of decision-making in each advertising platform. Full article
(This article belongs to the Special Issue Decision-Making Process and Its Application to Business Analytic)
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25 pages, 4224 KiB  
Article
Stock Price Crash Warning in the Chinese Security Market Using a Machine Learning-Based Method and Financial Indicators
by Shangkun Deng, Yingke Zhu, Shuangyang Duan, Zhe Fu and Zonghua Liu
Systems 2022, 10(4), 108; https://doi.org/10.3390/systems10040108 - 29 Jul 2022
Cited by 8 | Viewed by 2479
Abstract
Stock price crashes have occurred frequently in the Chinese security market during the last three decades. They have not only caused substantial economic losses to market investors but also seriously threatened the stability and financial safety of the security market. To protect against [...] Read more.
Stock price crashes have occurred frequently in the Chinese security market during the last three decades. They have not only caused substantial economic losses to market investors but also seriously threatened the stability and financial safety of the security market. To protect against the price crash risk of individual stocks, a prediction and explanation approach has been proposed by combining eXtreme Gradient Boosting (XGBoost), the Non-dominated Sorting Genetic Algorithm II (NSGA-II), and SHapley Additive exPlanations (SHAP). We assume that financial indicators can be adopted for stock crash risk prediction, and they are utilized as prediction variables. In the proposed method, XGBoost is used to classify the stock crash and non-crash samples, while NSGA-II is employed to optimize the hyperparameters of XGBoost. To obtain the essential features for stock crash prediction, the importance of each financial indicator is calculated, and the outputs of the prediction model are explained by SHAP. Compared with the results of benchmarks using traditional machine learning methods, we found that the proposed method performed best in terms of both prediction accuracy and efficiency. Especially for the small market capitalization samples, the accuracy of classifying all samples reached 78.41%, and the accuracy of identifying the crash samples was up to 81.31%. In summary, the performance of the proposed method demonstrates that it could be employed as a valuable reference for market regulators engaged in the Chinese security market. Full article
(This article belongs to the Special Issue Decision-Making Process and Its Application to Business Analytic)
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28 pages, 1228 KiB  
Article
A Hybrid Group Decision Approach Based on MARCOS and Regret Theory for Pharmaceutical Enterprises Assessment under a Single-Valued Neutrosophic Scenario
by Yuan Rong, Wenyao Niu, Harish Garg, Yi Liu and Liying Yu
Systems 2022, 10(4), 106; https://doi.org/10.3390/systems10040106 - 28 Jul 2022
Cited by 12 | Viewed by 1857
Abstract
Evaluating pharmaceutical enterprises with sustainable and high-quality development ability (SHQDA) can not only provide strategies for the pharmaceutical management department in formulating enterprise development plans, but also provide suggestions and guidance for enterprises to enhance their core competitiveness. Nevertheless, the prior research possesses [...] Read more.
Evaluating pharmaceutical enterprises with sustainable and high-quality development ability (SHQDA) can not only provide strategies for the pharmaceutical management department in formulating enterprise development plans, but also provide suggestions and guidance for enterprises to enhance their core competitiveness. Nevertheless, the prior research possesses several deficiencies in coping with the assessment of enterprises with SHQDA under uncertain environments to predict the psychological behavior of the evaluator and the correlation among the evaluation criteria. To conquer the aforementioned defects, we propose an integrated framework for rating pharmaceutical enterprises that incorporates regret theory, measurement alternatives and ranking based on the compromise solution (MARCOS) and Heronian mean operating within a single-value neutrosophic set (SVNS) environment. First, the single-valued neutrosophic number (SVNN) is employed to portray the assessment information of experts. Then, a novel single-valued neutrosophic score function is presented to enhance the rationality of the SVNN comparison. Next, a combined criteria weight model is constructed by synthesizing the best and worst method (BWM) and criteria importance through intercriteria correlation (CRITIC) approach to attain more reasonable and credible weight information. Furthermore, the integrated assessment framework combining regret theory-MARCOS method and Heronian mean operator is put forward to assess and select the enterprises with SHQDA under a single-valued neutrosophic setting. Ultimately, an empirical concerning the pharmaceutical enterprises assessment is presented within SVNS to illustrate the usefulness and effectiveness of the presented SVNS regret theory-MARCOS method. Thereafter, the sensitivity analysis and comparison analysis are implemented to provide evidence for the rationality and superiority of the proposed method. Full article
(This article belongs to the Special Issue Decision-Making Process and Its Application to Business Analytic)
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19 pages, 469 KiB  
Article
A DEMATEL-Based Method for Linguistic Multiple Attributes Group Decision Making Using Strict t-Norms and t-Conorms
by Lijuan Yao and Zhihong Yi
Systems 2022, 10(4), 98; https://doi.org/10.3390/systems10040098 - 09 Jul 2022
Cited by 4 | Viewed by 1500
Abstract
To evaluate fuzzy information precisely, researchers and practitioners are apt to use linguistic variables to model vague or uncertain contexts in natural language. In this paper, some new operation laws for continuous linguistic terms using strict t-norms and t-conorms are defined. Significantly, these [...] Read more.
To evaluate fuzzy information precisely, researchers and practitioners are apt to use linguistic variables to model vague or uncertain contexts in natural language. In this paper, some new operation laws for continuous linguistic terms using strict t-norms and t-conorms are defined. Significantly, these operation laws have some desirable properties and are closed on the restricted continuous linguistic term set. On the basis of these new linguistic operation laws, a series of triangular t-(co)norm-based linguistic generalized power geometric operators are developed. In order to consider the interactive influence and interrelationship of decision makers (DMs) and attributes, a decision-making trial and evaluation laboratory (DEMATEL)-based method for linguistic multiple attributes group decision making (MAGDM) is proposed. In the method, the weighting information for DMs and attributes are dependent on the initial direct-relation matrices among DMs and attributes, respectively. Finally, a numerical example is provided. In comparison with the existing methods, two aspects of the DEMATEL-based method for linguistic MAGDM in the work can be highlighted: the underlying operators for linguistic terms using strict t-norms and t-conorms that are closed on the set of the restricted continuous linguistic term set; and the techniques in determining the weighting information, with which the weighting information for DMs and attributes are determined by the interactive influence and interrelationship among DMs or attributes. Full article
(This article belongs to the Special Issue Decision-Making Process and Its Application to Business Analytic)
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12 pages, 765 KiB  
Article
Designing a MCDM Model for Selection of an Optimal ERP Software in Organization
by Nguyen Van Thanh
Systems 2022, 10(4), 95; https://doi.org/10.3390/systems10040095 - 05 Jul 2022
Cited by 12 | Viewed by 3128
Abstract
Among the growth of the Industrial Revolution 4.0 and moving towards 5.0, the application of science and technology is a decisive factor in catching up with new business trends. In particular, the application of the enterprise resources planning (ERP) towards enterprise management is [...] Read more.
Among the growth of the Industrial Revolution 4.0 and moving towards 5.0, the application of science and technology is a decisive factor in catching up with new business trends. In particular, the application of the enterprise resources planning (ERP) towards enterprise management is extremely important. ERP systems help businesses save time and effort in managing projects and utilizing resources. Instead of manual handling, the processes are carried out automatically. At the same time, the system operates correctly and efficiently which avoids errors. In this work, the author explored the application of a fuzzy multicriteria decision making (FMCDM) method including Fuzzy Analytic Hierarchy Process model (FAHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) model for the evaluation of various ERP software (mainly warehouse and inventory management module). First, the fuzzy AHP model is applied to calculate the weights of criteria, and then, the obtained weights are used in the TOPSIS method for ranking of the alternatives. This study would assist decision makers in an ERP implementation environment in deciding a suitable ERP software for various industries. Full article
(This article belongs to the Special Issue Decision-Making Process and Its Application to Business Analytic)
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27 pages, 3597 KiB  
Article
Multi-Objective Sustainable Closed-Loop Supply Chain Network Design Considering Multiple Products with Different Quality Levels
by Amirhossein Soon, Ali Heidari, Mohammad Khalilzadeh, Jurgita Antucheviciene, Edmundas Kazimieras Zavadskas and Farbod Zahedi
Systems 2022, 10(4), 94; https://doi.org/10.3390/systems10040094 - 02 Jul 2022
Cited by 9 | Viewed by 3849
Abstract
International laws and increasing consumer awareness have led to drastic changes in traditional supply chain network designs. Moreover, because of environmental and social requirements, traditional supply chain networks have changed to sustainable supply chain networks. On the other hand, reverse logistics can be [...] Read more.
International laws and increasing consumer awareness have led to drastic changes in traditional supply chain network designs. Moreover, because of environmental and social requirements, traditional supply chain networks have changed to sustainable supply chain networks. On the other hand, reverse logistics can be effective in terms of environmental and economic aspects, so the design of the supply chain network as a closed loop is necessary. In addition, customers have a demand for different products with different quality levels. Considering different types of customers with a variety of consumption trends can be a challenging issue, and is addressed in this study. The main contributions of this research are considering different quality levels for products as well as different tendencies of customers towards environmental issues. In this study, a sustainable closed-loop supply chain model is designed that seeks to balance economic, environmental, and social responsibilities. In this paper, costs and customer demands for different types of products at different quality levels are considered under uncertain conditions using a robust possibilistic programming method. The proposed multi-objective model is solved using the Augmented Epsilon Constraint (AEC) method that provides an efficient set of solutions for all decision-making levels. The results show that the robust possibilistic programming method is more effective in dealing with uncertainties than the possibilistic programming method. Full article
(This article belongs to the Special Issue Decision-Making Process and Its Application to Business Analytic)
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16 pages, 6238 KiB  
Article
Spillover Network among Economic Sentiment and Economic Policy Uncertainty in Europe
by Jose Arreola Hernandez, Sang Hoon Kang, Zhuhua Jiang and Seong-Min Yoon
Systems 2022, 10(4), 93; https://doi.org/10.3390/systems10040093 - 30 Jun 2022
Cited by 6 | Viewed by 2450
Abstract
We explore the directional spillover network among economic sentiment indicators and the economic policy uncertainty (EPU) index from Europe. We derive our results by fitting the directional spillover index approach to the monthly frequency data of eleven European countries, economic sentiment indicators and [...] Read more.
We explore the directional spillover network among economic sentiment indicators and the economic policy uncertainty (EPU) index from Europe. We derive our results by fitting the directional spillover index approach to the monthly frequency data of eleven European countries, economic sentiment indicators and the European EPU index, spanning from 1 January 1987, to 1 February 2019. The empirical results indicate that the economic sentiment indicators of the largest European economies (Germany, France, and Italy) spillover with each other the most. The economic sentiment indicators of Germany and France most strongly influence the EU and Euro area economic sentiment indicators. The economic sentiment indicators of France and Italy have the most influence on the European EPU index, while the latter has the strongest influence on the economic sentiment indicators of Germany and France. Full article
(This article belongs to the Special Issue Decision-Making Process and Its Application to Business Analytic)
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18 pages, 1058 KiB  
Article
Combining the MDM and BWM Algorithm to Determine the Optimal Crowdfunding Tokenization Solution for Digital Assets Market Startups
by Chien-Heng Chou and Chun-Yueh Lin
Systems 2022, 10(4), 87; https://doi.org/10.3390/systems10040087 - 28 Jun 2022
Viewed by 1540
Abstract
This study aimed to use the modified Delphi method and best worst method to establish an evaluation model for analyzing the perspectives and key influencing factors used in evaluating startups’ optimal token-financing solutions. In accordance with the modified Delphi method, a list of [...] Read more.
This study aimed to use the modified Delphi method and best worst method to establish an evaluation model for analyzing the perspectives and key influencing factors used in evaluating startups’ optimal token-financing solutions. In accordance with the modified Delphi method, a list of influencing factors was obtained through expert opinions and a literature review, and, further, adopted to construct an evaluation model and the subsequent weights. Thereafter, the relative weight of each factor in the best worst method framework was determined, to obtain the optimal token-financing solution. This study makes important contributions in theory and in practice by providing a decision-making model based on the modified Delphi method and the best worst method, which can serve as a valuable reference and measurement tool for startups to evaluate optimal solutions, when undertaking token financing. Academically, it contributes to the literature by providing an application process that integrates the modified Delphi method and the best worst method, and introduces an optimal evaluation framework for startups to use when undertaking token financing. In addition, it makes a practical contribution in the context of the rapid development of FinTech, as the evaluation model proposed in this study can be a valuable measurement tool for startup entrepreneurs who intend to use token financing to improve the capital turnover rate of their equity. Full article
(This article belongs to the Special Issue Decision-Making Process and Its Application to Business Analytic)
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23 pages, 2218 KiB  
Article
A Heterogeneous Information-Based Multi-Attribute Decision Making Framework for Teaching Model Evaluation in Economic Statistics
by Weihua Su, Le Zhang, Chonghui Zhang, Shouzhen Zeng and Wangxiu Liu
Systems 2022, 10(4), 86; https://doi.org/10.3390/systems10040086 - 25 Jun 2022
Cited by 3 | Viewed by 1748
Abstract
A teaching model is a stable teaching procedure established under the guidance of certain teaching ideas or theories. As a methodological major in higher education, economic statistics cross various fields of natural science and social science, showing the characteristics of intersection, integration, and [...] Read more.
A teaching model is a stable teaching procedure established under the guidance of certain teaching ideas or theories. As a methodological major in higher education, economic statistics cross various fields of natural science and social science, showing the characteristics of intersection, integration, and marginality. Therefore, this paper proposes a multi-attribute decision-making (MADM) framework for teaching model evaluation based on heterogeneous information. First, the attribute system of competition–academic research–master of knowledge–practical operation (CAMP) is constructed. Second, heterogeneous information is introduced in the process of teaching model evaluation; Third, a weight determination method based on a trust relationship of the fuzzy–social network is proposed, which provides a better solution to the problem of decision makers’ (DMs’) weight allocation in teaching model evaluation. Furthermore, a combined attribute weights determination method under an intuitionistic fuzzy number is constructed, which improves the shortcomings of the weight method in teaching model evaluation. Finally, through empirical research and stability analysis, the proposed evaluation framework has good effectiveness and feasibility, and policy suggestions for improvements to the economic statistical teaching model are then proposed. Full article
(This article belongs to the Special Issue Decision-Making Process and Its Application to Business Analytic)
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22 pages, 787 KiB  
Article
Enhancing Digital Innovation for the Sustainable Transformation of Manufacturing Industry: A Pressure-State-Response System Framework to Perceptions of Digital Green Innovation and Its Performance for Green and Intelligent Manufacturing
by Shi Yin, Nan Zhang, Kifayat Ullah and Shuo Gao
Systems 2022, 10(3), 72; https://doi.org/10.3390/systems10030072 - 27 May 2022
Cited by 103 | Viewed by 6850
Abstract
Low carbon and digitalization are the general trends of manufacturing upgrading and transformation. Digital technology enables the whole process of green manufacturing and breaks down the spatial barrier. To achieve the dual carbon goals, the pressure-state-response (PSR) model, in which digital technology enables [...] Read more.
Low carbon and digitalization are the general trends of manufacturing upgrading and transformation. Digital technology enables the whole process of green manufacturing and breaks down the spatial barrier. To achieve the dual carbon goals, the pressure-state-response (PSR) model, in which digital technology enables the green innovation of the manufacturing industry, was theoretically analyzed in this study. The measurement system of the digital green innovation (DGI) in the manufacturing industry was constructed according to the PSR framework. An evaluation model based on the analytic hierarchy process and the deviation maximization technique for order preference by similarity to an ideal solution method was constructed to measure the level of DGI. The results of this study from Chinese manufacturing are as follows. (i) The measurement system of the level of DGI in manufacturing industry includes a pressure system, state system and response system. (ii) In the past five years, the comprehensive index of the DGI in manufacturing industry has generally shown a trend of fluctuating rise. There are overall low and unbalanced phenomena in all regions. The gap decreased from 0.1320 to 0.1187, showing a gradually narrowing trend. (iii) Compared with other regions, the composite index of DGI is generally higher in the regions with a better ecological environment in the east and a more developed economy in the north. State parameters are higher than pressure and response parameters in most areas. (iv) Compared with other regions, the composite index of DGI in western and southern regions is lower, and the parameters of pressure, status and response are basically coordinated. (v) The application degree of digital technology, the emission intensity of waste water/exhaust gas of output value of one hundred million yuan and the expenditure intensity of digital technology adopted by enterprises are the key influencing factors of DGI in the manufacturing industry. This study not only proposed an evaluation index system of the digital green innovation level, but also puts forward policy guidance and practical guidance of digital technology to accelerate the green and intelligent manufacturing industry. Full article
(This article belongs to the Special Issue Decision-Making Process and Its Application to Business Analytic)
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25 pages, 1080 KiB  
Article
Online Teaching Quality Evaluation of Business Statistics Course Utilizing Fermatean Fuzzy Analytical Hierarchy Process with Aggregation Operator
by Shouzhen Zeng, Yan Pan and Huanhuan Jin
Systems 2022, 10(3), 63; https://doi.org/10.3390/systems10030063 - 12 May 2022
Cited by 15 | Viewed by 2370
Abstract
Due to the full-scale outbreak of COVID-19, many universities have adopted the way of online teaching to ensure the orderly development of teaching plans and teaching contents. However, whether online and offline teaching can develop homogeneously and how to ensure the teaching effect [...] Read more.
Due to the full-scale outbreak of COVID-19, many universities have adopted the way of online teaching to ensure the orderly development of teaching plans and teaching contents. However, whether online and offline teaching can develop homogeneously and how to ensure the teaching effect is a major challenge for colleges and universities. Therefore, it is urgent to construct a reasonable index system and evaluation approach for the quality of network teaching. Combined with the influencing factors and characteristics of online teaching, this study first puts forward a multi-index evaluation index system and then proposes a novel evaluation method for online teaching based on the analytical hierarchy process (AHP) and Dombi weighted partitioned Muirhead Mean (PMM) operator under Fermatean fuzzy (FF) environment. This presented method not only adapts to changeable evaluation information but also handles the elusive interrelationships among indexes, realizing the flexibility and comprehensiveness both in form and in the polyaddition process. The applicability and feasibility of this presented method are then discussed through the practical online teaching quality evaluation of a business statistics course case, and a group of tentative about the sensitivity analysis and comparative analysis further demonstrates the effectiveness and flexibility of the proposed method. Full article
(This article belongs to the Special Issue Decision-Making Process and Its Application to Business Analytic)
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18 pages, 1849 KiB  
Article
The Determinants of Passengers’ Consumption Motivation at High-Speed Rail Stations
by Sheng-Hau Lin, Chin-Yu Ho, Song-Ying Lu and Jing-Chi Hsieh
Systems 2022, 10(2), 45; https://doi.org/10.3390/systems10020045 - 06 Apr 2022
Viewed by 2526
Abstract
Exploring passengers’ consumption motivation can provide the basis for arranging commercial activities in high-speed rail (HSR) stations to generate more revenue for operations. This study uses a mixed multiple-attribute decision-making model for exploring the consumption motivation at HSR stations and complex influential relationships [...] Read more.
Exploring passengers’ consumption motivation can provide the basis for arranging commercial activities in high-speed rail (HSR) stations to generate more revenue for operations. This study uses a mixed multiple-attribute decision-making model for exploring the consumption motivation at HSR stations and complex influential relationships from the passengers’ perspective. The passenger traffic at five major HSR stations in Taiwan were evaluated. Based on the results of decision-making trial and evaluation laboratory (DEMATEL) and DEMATEL-based on the analytical network process methods, it is shown that station attributes and consumption environment attributes are key factors that impact product attributes. Moreover, store location, commercial activities offered, product diversity, time pressure, and service convenience have a “cause” characteristic and, therefore, should be focused on when deploying commercial services at HSR stations. The findings from the modified VlseKriterjumska Optimizacija I Kom-promisno Resenje method reveal that time pressure has the largest gap to aspiration level at almost all the stations. Finally, corresponding management implications to HSR stations are proposed. Full article
(This article belongs to the Special Issue Decision-Making Process and Its Application to Business Analytic)
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