Search results

In this paper, the main focus is on supply and demand auction systems with resource pooling in modern supply chain from a theoretical modeling perspective. The supply and demand auction systems in modern supply chains among manufacturers and suppliers serve as information sharing mechanisms. The purpose of this paper is to match the supply and demand such that a modern supply chain can achieve incentive compatibility and economic efficiency. The authors design such a supply and demand auction system that can integrate resources to efficiently match the supply and demand.

The authors propose three theoretic models of modern supply chain auctions with resource pooling according to the Vickrey auction principle. They are supply auction model with demand resource pooling, demand auction model with supply resource pooling, and double auction model with demand and supply resource pooling. For the proposed auction models, the authors present three corresponding algorithms to allocate resources in the auction process by linear programming, and study the incentive compatibility and define the Walrasian equilibriums for the proposed auction models. The authors show that the solutions of the proposed algorithms are Walrasian equilibriums.

By introducing the auction mechanism, the authors aim to realize the following three functions. First is price mining: auction is an open mechanism with multiple participants. Everyone has his own utility and purchasing ability. So, the final price reflects the market value of the auction. Second is dynamic modern supply chain construction: through auction, firm can find appropriate partner efficiently. Third is resources integration: in business practices, especially in modern supply chain auctions, auctioneers can integrate resources and ally buyers or sellers to gain more efficiency in auctions.

In the paper, the authors propose three theoretic models and corresponding algorithms of modern supply chain auctions with resource pooling according using the Vickrey auction principle, which achieves three functions: price mining, dynamic modern supply chain construction and resources integrating. Besides, these proposed models are much closer to practical settings and may have potential applications in modern supply chain management.

Fairness concerns in the supply chain management have recently caught much attention in the OM research community. The combined effect of fairness and competition on supply chain coordination and the interplay between them, however, have yet to be thoroughly examined.

The authors study a multiplayer supply chain with one supplier and two competing retailers with fairness concerns by a three-player Stackelberg game model. This theoretical study provides equilibrium solutions under different ranges of fairness and competition combinations. Besides theoretical analysis, the authors also conduct standard economic experiments and estimate structural parameters using experimental data.

The authors find that a simple wholesale price can coordinate the whole supply chain with certain conditions of fairness and competition. Moreover, although fairness concerns always decrease the wholesale price and increase retailers' profit share, downstream competition weakens such effects and decreases downstream players' market share. The experiments confirm the existence of fairness concerns and the interaction of competition and fairness, as shown in the theoretical analysis.

A more comprehensive model with both distributional and peer-induced fairness considered could generate better insights in the interactive impact of competition and fairness. Moreover, the authors followed the previous channel competition literature and modeled the demand with linear demand function which makes the game decisions trackable in closed form solution. A more general demand function could result in different solutions and thus new insights.

The authors’ work provides a comprehensive theoretical study of the interaction between fairness concerns and competition and clarifies the in-depth connection between the effects of competition and fairness concerns in the literature.

It is a very prominent problem that Chinese universities lack school-running characteristics. In the past ten years, because of undergraduate teaching assessment requirements of the Ministry of Education, universities attach great importance to school-running characteristics. What is the reality and how to improve the effectiveness of creating the school-running characteristics of universities? It is a problem that needs to be solved. The purpose of this paper is to discuss these issues.

Using the survey method, literature study, case studies and other methods, this study reviewed ten years of school-running characteristics construction and explored some laws of creating school-running characteristics.

This study found although universities in China are beginning to attach great importance to the school-running characteristics, but they are still staying in the summarization of characteristics. School-running characteristics are very rough. Creating school-running characteristics are mainly efforts responding to the superior government. Creating school-running characteristics should be based on category characteristic. Universities need to change in competition and create characteristics within its history and culture. Universities need to refine the core idea of education, develop a big picture and then renew them in the assessment cycle.

The originality of this study was that it put forward some new laws including changing from summarizing to creating its own school-running characteristics, putting category characteristic as the prerequisite and considering the core idea of education as the focus of school-running characteristics. This research will enrich the theory building of higher education research and has some value in promoting the creation of school-running characteristics.

The purpose of this paper is to propose a formative assessment framework to expose individual student's cognitive learning difficulties in English public speaking. The paper aims to provide student feedback and information during the teaching and learning process. A grey student-construct (S-C) chart is developed to represent the students’ cognitive mapping of the speech difficulties in relation to their overall speech conceptualization. This grey S-C chart can facilitate the instructors to ameliorate the classroom teaching and learning performance in English public speaking.

In total, 26 students in a class of English Speech and Rhetoric participate in the experiment – each student views the online video segments of a great speaker's speech, and then decides what segments would best support the speaking skill constructs and also reflects on his/her own difficulties in the same constructs. The grey relational analysis (GRA) method is used to analyze the empirical data. The individual student's construct localization grey relation grade values are calculated to rank the grey relation for both students and constructs. Accordingly, a grey S-C matrix is constructed and a grey S-C chart can thus be developed.

The grey S-C chart manifestly displays the cognitive difficulties in sequences of both students and constructs.

According to the grey S-C chart, the instructors may modify teaching strategies to enhance the overall classroom performance. The students may adjust learning strategies to eliminate their specific difficulties. Offering individualized advanced and remedial practices to those largely deviating from the norm is also possible.

The study is the first of its kind to apply the GRA method to expose individual student's cognitive learning difficulties in English public speaking. The grey S-C chart is novel in education literature, which can reveal individual student's learning difficulty patterns.

This study analyses Chinese data to revisit the relationship between directors’ and officers’ (D&O) insurance and accounting conservatism, aiming to investigate the impact of investors’ legal protection on the function of D&O insurance.

The study sample included all A-share firms listed on the Shanghai and Shenzhen Stock Exchanges from 2006 to 2019. Multiple regression was used to investigate the association between D&O insurance and accounting conservatism. The Heckman two-stage model and the propensity score matching method were used to check the robustness of the main results.

D&O insured companies exhibited greater accounting conservatism. The higher the indemnity limit, the more conservative a firm’s earnings reporting. The positive correlation was stronger when investor protection was relatively weak. The impact of D&O insurance on accounting conservatism was stronger for companies with weaker internal or external supervision mechanisms.

The study findings show that D&O insurance plays a positive role in the governance of listed companies when investors’ legal protection is weak, which supports the effective supervision hypothesis of D&O insurance.

Sustainability is considered a core trend in the development of the fashion industry. Clarifying the driving factors of consumers’ sharing willingness regarding sustainable image from the perspective of psychology can help fashion brands implement sustainable management and deepen industrial sustainable development.

Based on commitment theory, this paper proposes a conceptual model that includes three antecedents: perception of greenwashing, environmental, social and governance (ESG) and social media content quality. These affect consumers’ sharing willingness regarding sustainable image through affective commitment, continuance commitment and normative commitment. Furthermore, 310 participants reported their tendencies in a formal empirical study.

The results show that unlike green perception, which has a significant negative effect, consumers have a significant positive commitment to high perceived levels of ESG and social media content quality. Besides, all three dimensions under the commitment theory play a partial mediating role between consumer perception and sharing willingness.

This study not only extends the research on the commitment theory to the field of fashion marketing and management but also enriches the research context of brand image sharing willingness, which explains the differential effects of different consumer commitments on their information sharing willingness. Moreover, several management implications applicable to the fashion industry have also been proposed based on the conclusion.

The purpose of this study is to prepare a chemically stable superhydrophobic coating with remarkable mechanical properties and concrete protective properties.

One synthetic step was adopted to prepare superhydrophobic coating. The process and product were analyzed and confirmed by fourier transform-infrared spectroscopy (FT-IR), thermogravimetric analysis (TGA), water contact angle (WCA), transmission electron microscopy (TEM), scanning electron microscope (SEM), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS). The mechanical properties were confirmed by tensile test. The concrete protective properties were confirmed by solution immersion test and rapid chloride migration coefficient test.

MSiO₂ nanoparticles (NPs) were chosen to enhance the hydrophobicity of fluorosilicone coatings. With a 4:1 mass ratio of fluorosilicone resin and MSiO₂ NPs, the coatings show superhydrophobicity with a WCA of 156° and a SA of 3.1°. In addition, the tensile mechanical property was improved, and the chloride ion diffusion coefficient was decreased significantly after the addition of MSiO₂ NPs.

This new fluorosilicone coating hybrid by MSiO₂ NPs could be applied as a concrete protective layer with properties of self-cleaning, antifouling, etc.

Introduction of MSiO₂ NPs hybrid to prepare fluorosilicone coating with superhydrophobicity on concrete surface has not been systematically studied previously.

The purpose of this paper is to construct an optimal resource reallocation model of the limited resource by a moderator for reaching the greatest consensus, and show how to reallocate the limited resources by using optimization methodology once the consensus opinion is reached. Moreover, this paper also devotes to theoretically exploring when or what is the condition that the group decision-making (GDM) system is stable; and when new opinions enter into the GDM, how the level of consensus changes.

By minimizing the differences between the individuals’ opinions and the collective consensus opinion, this paper constructs a consensus optimization model and shows that the objective weights of the individuals are actually the optimal solution to this model.

If all individual deviations of the decision makers (DMs) from the consensus balance each other out, the information entropy theorem shows this GDM is most stable, and economically each individual DM gets the same optimal unit of compensation. Once the consensus opinion is determined and each individual opinion of the DMs is under an acceptable consensus level, the consensus is still acceptable even if additional DMs are added, and the moderator’s cost is still no more than a fixed upper limitation.

The optimization model based on acceptable consensus is constructed in this paper, and its economic significance, including the theoretical and practical significance, is emphatically analyzed: it is shown that the weight information of the optimization model carries important economic significance. Besides, some properties of the proposed model are discussed by analyzing its particular solutions: the stability of the consensus system is explored by introducing information entropy theory and variance distribution; in addition, the effect of adding new DMs on the stability of the acceptable consensus system is discussed by analyzing the convergence of consensus level: it is also built up the condition that once the consensus opinion is determined, the consensus degree will not decrease even when additional DMs are added to the GDM.

The purpose of this paper is to study the properties of derived grey verhulst prediction model with multiplication transformation and reduce its modeling complexity.

The paper discussed the parameter characteristics of grey derived verhulst model under multiple transformation, and demonstrated its effect on its simulative value and predictive value by investigating the multiple transformation acting on the raw data sequence of this grey model. The parameter characteristics of this model under multiple transformations and its effect of the simulation value and forecasting value are analyzed by studying the properties of multiply transformation of this model.

The research finding shows that the modeling accuracy of derived grey verhulst model is in no relation to multiple transformations.

The above results imply that the data level can be reduced; the process of building derived grey verhulst model can be simplified; but the simulative and predictive accuracy of this model remain unchanged.

The paper succeeds in realising the properties of derived grey verhulst model by using the method of multiplication transformation, which is helpful to understand the modeling mechanism and expand the application range of derived grey verhulst model.

The purpose of this paper is to predict hospital respiratory system infection rate by using the gray GM(1,1) model, and to provide theoretical basis for the prospective study on hospital respiratory system infection management.

The annual respiratory system infection rate of a comprehensive third-class hospital in Yan’an is collected from 2011 to 2017. The GM(1,1) model is used for prediction, and mean absolute percentage error is used to evaluate the prediction accuracy of the model.

GM(1,1) statistical prediction model is established with good fitting degree and high reliability of extrapolation prediction.

The GM(1,1) model can well predict the respiratory system infection rate of the hospital.