Constructing an entrepreneurship project evaluation system using a hybrid model

Due to the economic trends around the world and the strong support and guidance of relevant governments, the number of entrepreneurial projects has soared in China. It is necessary to construct a standard assessment system for entrepreneurial projects that is comprehensive and effective. This study extracted six dimensions and 23 criteria for evaluating entrepreneurial projects. This study applies the best and worst methods to obtain the weights of the dimensions and criteria. Then, the Technique for Order Preference by Similarity to an Ideal Solution method was used to evaluate the entrepreneurial projects in an entrepreneurial competition. The results show that team quality, the business model and entrepreneurship ability are the three most important dimensions for evaluating entrepreneurial projects. The improvement of the innovating ability, the training of the team and the value proposition are the three keys to successful implementation of the entrepreneurial projects

Application of the Analytic Hierarchy Process and Grey Relational Analysis for Vendor Selection of Spare Parts Planning Software

The success of after-sales services fundamentally depends on the possibility of symmetry balancing needs, supply and customer satisfaction. Spare parts planning (SPP) software selection is an investment in balancing the symmetry of inventory control, which directly affects the success of after-sales services. This paper presents the analytic hierarchy process (AHP) and grey relational analysis (GRA) as potential multi-criteria decision making (MCDM) methods for software selection. The application of these methods can be decreased by decision-makers’ subjectivity, which leads to consistency and symmetry in the weight values of the criteria. The criteria were evaluated solely based on system functions by business consultants with respect to the modularity of the software to meet various business requirements, distinguishing this paper from other papers that focus on the financial aspects of selecting software. The results suggest that the AHP and GRA are feasible methods for software selection that effectively integrate consultants’ experience to identify the suitable software and the most important function for adoption in real businesses. The findings of our data suggest that inventory optimization is the most important function of SPP software, as the demand forecasting function may be subjective. In conclusion, this paper represents a bridge between practitioners and researchers

Multi-criteria Recommendation Based on Trust

With the quick rise of E-Commerce, personalized recommender systems have been created, which not only stimulate the sales of products and services but also increase customers’ loyalty. Collaborative filtering has been the most common and effective technique applied to recommendation systems. In this study, we applied multi-criteria ratings in movie preference collection for building users’ profiles of different aspects profile and we used regression coefficient, which was derived from multiple regression analysis, for each criterion preference level. In order to improve each criterion prediction quality and alleviate the sparsity problem of Collaborative filtering, we firstly combine users’ preference levels and trust-values as trust-weight in different criterions and then set trustweight threshold to filter users and to find recommendation members. In the final aggregation experiments, we observed that trust-based filtering method also carried out a lower MAE in overall rating prediction and the F1 value has a better recommendation performance. Finally, the approach we proposed can improve the recommendation quality in the multi-criteria recommendation environment

Exploring the Role of Deep Learning Technology in the Sustainable Development of the Music Production Industry

This study explores the role of deep learning technology in the sustainable development of the music production industry. This article surveys the opinions of Taiwanese music creation professionals and uses partial least squares (PLS) regression to analyze and elucidate the importance of deep learning technology in the music production industry. We found that deep learning cannot replace human creativity, but greater investment in this technology can improve the quality of music creation. In order to achieve sustainable development in the music production industry, industry participants need to awaken consumers’ awareness of music quality, actively enhance the unique value of their art, and strengthen cooperation between industries to provide a friendly environment for listeners

A Rough Hybrid Multicriteria Decision-Making Model for Improving the Quality of a Research Information System

Improving the quality of research information systems is an important goal in the process of improving the performance of research management in Chinese universities. Since the evaluation of information system (IS) quality is a multicriteria decision problem, it is critical to identify the interrelationships among the dimensions and criteria, and decide on the important criteria for proposed improvement strategies. This paper suggests a hybrid multicriteria decision-making (MCDM) model for improving the quality of a research information system. First, a rough method combined with the decision-making trial and evaluation laboratory and analytical network process (rough DANP) model is used to improve the objectivity of expert judgements. Additionally, the rough DANP can be used to construct an influential network relationship map (INRM) between research information system components to derive the criterion weights. The complex proportional assessment of alternatives with rough numbers (COPRAS-R) is applied to evaluate the performance of the research information system. A Chinese university research information system is chosen to illustrate the usefulness of the proposed model. The results show that efficiency, effectiveness, and user frequency have the highest priorities for improvement. Selected management implications based on the actual case study are supplied

Developing A Sustainable Urban-Environmental Quality Evaluation System in China Based on A Hybrid Model

In China, with the acceleration of urbanization, people pay more attention to the quality of urban environment. Air pollution, vegetation destruction, water waste and pollution, and waste sorting have restricted the sustainable development of urban environment. It is important to evaluate the impact of these environmental concerns as a prerequisite to implement an effective urban environmental sustainability policy. The aim of this paper is to establish a system for evaluating sustainable urban environmental quality in China. We extracted six dimensions and 29 criteria for assessing urban sustainable environment. Then, a fuzzy technique and the best worst method were applied to obtain the weights for the dimensions and criteria. Next, grey possibility values were applied to evaluate the sustainable environmental quality of five cities: Beijing, Shanghai, Shenzhen, Guangzhou, and Hangzhou in China. A sensitivity analysis was performed to identify how the ranking of these five cities changed when varying the weights of each criterion. The results show that pollution control, the natural environment, and water management are the three most important dimensions for urban environmental quality evaluation. We suggest that controlling pollutant emissions, strengthening food waste management, improving clean production processes, and utilizing heat energy are the effective measures to improve the urban environment and achieve sustainable urban environmental development

Improving the Green Building Evaluation System in China Based on the DANP Method

Against the background of sustainable development, green building practices could be part of the strategy for solving environmental and energy problems in developing countries. The aim of this paper is to explore a system for the assessment of green buildings in China that provides the government and stakeholders with ways to improve their strategies for green building development. We apply a hybrid model, developed by integrating the Decision-Making Trial and Evaluation Laboratory and Analytical Network Process (called DANP) method, to build an influential network relationship map (INRM) between assessment systems and to derive the criterion weights. The INRM and derived weights can help us to understand this complex assessment system and to set improvement priorities for green building development. The results demonstrate that indoor environment, materials, and smart facilities are the top three critical factors for green building evaluation. Finally, we discuss some management implications based on an actual case study with solutions provided using this model

Associations between Vitamin D Deficiency and Carbohydrate Intake and Dietary Factors in Taiwanese Pregnant Women

This cross-sectional observation study investigated the vitamin D (VD) status in Taiwanese pregnant women and the effects of VD supplementation and macronutrient intake on serum 25-hydroxy-vitamin D (25[OH]D) level. Data on VD intake, daily sunlight exposure, and carbohydrate intake were obtained from 125 pregnant women at 30–37 weeks’ gestation. Serum 25[OH]D level was measured before delivery in all enrolled women; and the mean 25(OH)D level was 43 nmol/L or 17.2 ng/mL. The 25(OH)D level was significantly correlated with total VD intake of pregnant women (r = 0.239; p = 0.007). The severe VD deficiency group (n = 16; mean of 25(OH)D level = 8.5 ng/mL) had significantly lower total VD intake and supplementation than the groups with VD deficiency (n = 69), insufficiency (n = 32), and sufficiency (n = 8). Those with ≥400 IU/day total VD intake (including VD from food and supplementation) had significantly higher 25(OH)D concentration than those with p = 0.031). In conclusion, VD deficiency was highly prevalent in Taiwanese pregnant women. VD supplementation was the most effective method for increasing 25(OH)D concentration in pregnant women. Higher carbohydrate intake might reduce 25(OH)D levels