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With the development of economy and the progress of science and technology, the function of Luoyang city is constantly enriched and expanded. The city is no longer a simple area for people to live in. The function structure of the city is affected by the external factors and is constantly expanding. Urban logistics is one of the important influencing factors. To more comprehensively and accurately understand the status and role of logistics network space in urban planning, the characteristics and development law of urban logistics structure from the theoretical point of view are analyzed in this paper with Luoyang City as the research background. The city logistics function is determined as one of the main factors affecting the economic growth of the city is determined through the literature search method, consulting professionals and other research methods. Urban road planning and design are the focus of the study; the planning and development of urban logistics road network in Luoyang City are compared and analyzed. In full consideration of the necessity of the optimization of the urban logistics network space, the preliminary optimization scheme design and suggestion of Luoyang logistics is introduced. At the end of this paper, the sustainable development and the status of the future urban logistics function are analyzed and prospected. Continuous research and analysis of multiple subjects and angles are still needed.

Rural folk custom ecotourism is one of the most unique tourism projects today, which relies on the unique landscape of the country for architectural planning and tourism. In the article, the architectural planning and design based on the protective development of rural folk custom ecotourism was studied. Based on this, firstly, the characteristics and development background of rural tourism were expatiated, and the theoretical research background of current landscape planning and design was analyzed; then the principles and methods of planning and designing of rural folk custom ecotourism landscape architecture were analyzed, and the functions of architecture and space use were described in detail, so as to meet the need for protective and sustainable development; in addition, through the analysis and planning of specific projects, the concrete methods of architectural planning and design were discussed and the localization of architectural planning and design was achieved.

The purpose of this paper is to provide a method that can better evaluate the credit risk (CR) under PPP project finance.

The principle to evaluate the CR of PPP projects is to calculate three critical indicators: the default probability (DP), the recovery rate (RR) and the exposure at default (EAD). The RR is determined by qualitative analysis according to Standard & Poor’s Recovery Scale, and the EAD is estimated by NPV analysis. The estimation of the DP is the focus of CR assessment because the future cash flow is not certain, and there are no trading records and market data that can be used to evaluate the credit condition of PPP projects before financial close. The modified CreditMetrics model and Monte Carlo simulation are applied to evaluate the DP, and the application is illustrated by a PPP project finance case.

First, the proposed method can evaluate the influence of the project’s cash flow uncertainty on the potential loss of the bank. Second, instead of outputting a certain default loss value, the method can derive an interval of the potential loss for the bank. Third, the method can effectively analyze how different repayment schedules and risk preference of banks influence the evaluating result.

The proposed method offers an approach for the bank to value the CR under PPP project finance. The method took into consideration of the uncertainty and other characteristics of PPP project finance, adopted and improved the CreditMetrics model, and provided a possible loss range under different project cash flow volatilities through interval estimation under certain confident level. In addition, the bank’s risk preference is considered in the CR evaluating method proposed in this study where the bank’s risk preference is first investigated in the CR evaluating process of PPP project finance.

In this paper, the four popular multiple-criteria decision-making (MCDM) methods in fuzzy environment are utilized to reflect the vagueness and uncertainty on the judgments of decision-makers (DMs), because the crisp pairwise comparison in these conventional MCDM methods seems to be insufficient and imprecise to capture the right judgments of DMs. Of these methods, as Fuzzy analytic hierarchy process (F-AHP) is used to calculate criteria weights, the other methods; Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (F-TOPSIS), Fuzzy Grey relational analysis (F-GRA) and Fuzzy Preference Ranking Organization METhod for Enrichment of Evaluations (F- PROMETHEE II) are used to rank alternatives in the three different ways for a comparative study.

The demand for green products has dramatically increased because the importance and public awareness of the preservation of natural environment was taken into consideration much more in the last two decades. As a result of this, especially manufacturing companies have been forced to design more green products, resulting in a problem of how they incorporate environmental issues into their design and evaluate concept options. The need for the practical decision-making tools to address this problem is rapidly evolving since the problem turns into an MCDM problem in the presence of a set of green concept alternatives and criteria.

The incorporation of fuzzy set theory into these methods is discussed on a real-life case study, and a comparative analysis is done by using its numerical results in which the three fuzzy-based methods reveal the same outcomes (or rankings), while F-GRA requires less computational steps. Moreover, more detailed analyses on the numerical results of the case study are completed on the normalization methods, distance metrics, aggregation functions, defuzzification methods and other issues.

The designing and manufacturing environmental-friendly products in a product design process has been a vital issue for many companies which take care of reflecting environmental issues into their product design and meeting standards of recent green guidelines. These companies have utilized these guidelines by following special procedures at the design phase. Along the design process consisting of various steps, the environmental issues have been considered an important factor in the end-of-life of products since it can reduce the impact on the nature. In the stage of developing a new product with the aim of environmental-friendly design, the green thinking should be incorporated as early as possible in the process.

The case study was inspired from the previous work of the author, which was realized in a hot runner systems manufacturer, used in injection molding systems in a Canada. In a new product development process, the back- and front-ends of development efforts mainly determine the following criteria: cost, risk, quality and green used in this paper. The case study showed that the three fuzzy MCDM methods come to the same ranking outcomes. F-GRA has a better time complexity compared to the other two methods and uses a smaller number of computational steps. Moreover, a comparative analysis of the three F-MCDM methods; F-PROMETHEE II, F-TOPSIS and F-GRA used in ranking for green concept alternatives using the numerical results of the case study. For the case study; as seen in table 20, the three F-MCDM methods produced the numerical results on the rankings of the green concept alternatives as follows; {Concept A-Concept C–Concept B–Concept D}.

Inclusion of environmental-related criteria into concept selection problem has been gaining increasing importance in the last decade. Therefore, to facilitate necessary calculations in applying each method especially with its fuzzy extension, it can be developed a knowledge-based (KB) or an expert system (ES) to help the DMs make the required calculations of each method, and interpret its results with detailed analysis.

The objective of the research was to propose a F-AHP based F-MCDM approach to green concept selection problem through F-PROMETHEE II, F-TOPSIS and F-GRA methods. As the F-AHP is used to weight evaluation criteria, the other methods are respectively used for ranking the concept alternatives and determine the best concept alternative.

Economic ties and formation of trade blocks escalates the movement of goods among the participants and bring different economic and structural changes. Therefore, the current research emphasises on the distribution of market structure and industrial value added among the participant countries of China–Pakistan economic corridor project while focussing on pre and post FTA status.

This study utilises the footloose capital model for analysing whether China or Pakistan is more suitable for attracting factors of production to increase their share of industrial value added. For econometric analyses the current research utilises data from 1995 to 2018 and maximum likelihood effect method to assess factors that affect regional value-added distribution.

Results show that both countries owe different level of economic developments. Effect of capital is, comparatively, similar for both countries while Pakistan supports trade openness which points towards the fact of positive utilisation of abundant labour resources in Pakistan by establishing industrial structure either through domestic capital formation or foreign investment. Whereas, share of labour and trade openness of China positively affect value added production of China.

This is one of the unique studies that studies the regional economic treaties usefulness for any developing country across Asia. Where this study uses the footloose capital model and maximum likelihood method for its analysis which is not previously done, while for detailed analyses the study further divides the timeframe into two parts as pre-FTA ranges from 1995 to 2006, post-FTA from 2007 to 2018 while overall results consist of whole-time frame.

Short-form health science videos have become an important medium for disseminating health knowledge and improving public health literacy. However, the factors that determine viewer engagement are not well understood. This study aims to address this research gap by investigating the association between doctor image features and viewer engagement behavior, building on the personal branding theory and information signaling theory.

A sample of 1245 health science short-form videos was collected, and key video features related to doctor images were extracted through manual labeling. Multi-variable regression analysis and SPSS process model were employed to test the hypotheses.

The results show that doctor image features are significantly associated with viewer engagement behavior. Videos featuring doctors in medical uniforms receive more viewer likes, comments and shares. Highlighting the doctor's title can increase viewer collections. Videos shot in a home, white wall, or study room setting receive more like, comments and sharing. The doctor's appearance demonstrates a positive nonlinear relationship with viewer likes and comments. Young doctors with title information tend to attract more video collections than older doctors with title information. The positive effect of the doctor's appearance and showing title information, become more significant among male doctors.

This research provides novel insights into the factors that determine viewer engagement behavior in short-form health science videos. Specific doctor image features can enhance viewer engagement by signaling doctor professionalism. The results also suggest that there may be age and gender biases in viewers' perceptions.