Search results

The role of energy or emission intensive firms face contradictory demands from advancing economic development and environmental improvement and protection and thus require appropriate policy interventions to balance the two needs. China's “Green Credit” policy that restricts loans to energy or emission intensive firms provides an example to study the impact of these kinds of policy intervention.

Using the data of all A-share listed companies in Shanghai and Shenzhen stock exchanges, our paper empirically analyzes the impact of the Green Credit Policy on performance of these energy or emission intensive firms.

(1) Using difference-in-difference (DID) and propensity score matching (PSM)-DID method and the dynamic effect method, we found that from 2012 to 2015, the Green Credit Policy had an inhibiting effect on the performance of energy or emission intensive firms. This inhibiting effect was gradually weakened in 2016, and it turned into a positive promoting effect in 2017; (2) The performance's change of these firms around 2015 showed that Green Credit promoted the green transformation and upgrading of these firms; (3) Loans were helpful to the performance of energy or emission intensive firms to some extent, but government subsidies were not significant.

The results suggest that the government, banks and other institutions should dynamically assess the implementation results of the Green Credit Policy on energy or emission intensive firms.

Financial performance has been paid attention at an unprecedented level, which can be confirmed as a fact that the quantitative expansion of financial performance evaluation work. The purpose of this study is to propose a more appropriate model for financial performance evaluation under the unbalanced development.

This paper introduces the differentiation criteria to eliminate the deviation caused by the same principle for multiple performance evaluation objects whose development are unbalanced; Then the generalized grey number is adopted to describe the value of performance evaluation index; and the information entropy weight is used to obtain the index weight to reduce the artificial judgment error; Finally, the generalized grey information entropy weight TOPSIS evaluation model is constructed.

Empirical research shows that in the new evaluation model, the differentiated possibility function effectively eliminates the deviation caused by the same principle, the application of information entropy weight reduces the human judgment error, and the value of generalized grey number further enhances the closeness of the results. Moreover, it is also found that in different scenarios, an adaptive performance evaluation model should be selected to match scientifically reasonable results.

The proposed model offers a solution for financial performance evaluation considering unbalanced development among cities. It can be realized by determining the differentiation possibility function matrix, and then the information entropy weight TOPSIS evaluation model can be constructed. This model reflects the actual situation, improves the performance evaluation accuracy, and can be used under similar conditions.

The purpose of this paper is to describe a simulation and experimental research concerning the effect of recess depth on the lubrication performance of a hydrostatic thrust bearing by constant rate flow.

The computational fluid dynamics and finite volume method have been used to compute the lubrication characteristics of an annular recess hydrostatic thrust bearing with different recess depths. The performances are oil recess pressure, oil recess temperature and oil film velocity. The recess depth has been optimized. A test rig is established for testing the pressure field of the structure of hydrostatic thrust bearing after recess depth optimization, and experimental results show that experimental data are basically identical with the simulation results, which demonstrates the validity of the proposed numerical simulation method.

The results demonstrate that the oil film temperature decreases and the oil film pressure first increases and then decreases with an increase in the recess depth, but oil film velocity is constant. To sum up comprehensive lubrication performance, the recess depth of 3.5 mm is its optimal value for the annular recess hydrostatic thrust bearing.

The computed results indicate that to get an improved performance from a constant flow hydrostatic thrust bearing, a proper selection of the recess depth is essential.

Decision theory holds that the ambiguity of decision information affects the choices of decision makers, who have the emotion of “ambiguity aversion” when making fuzzy decisions. The purpose of this paper is to explore the neural mechanism how the information ambiguity of different sales promotion strategies influences consumers’ purchasing decision.

The paper uses the event-related potential (ERP) technique and experiment.

Results indicate that the information ambiguity of sales promotion strategies did influence the purchasing decision of consumers, and there were significant differences in the amplitudes of brain wave P2, N2 and P3 when consumers encountered the sales promotions of different types (discounts and gift-giving). This reflects the difference in perceived risk, decision-making conflict and decision-making attitude. It means that compared with discounts, the perceived risk and difficulty increased while the decision-making confidence plunged when consumers were faced with gift-giving promotions. This finding gives an explanation on the neural level why consumers prefer discounts, rather gift-giving sales promotions.

For the merchants to promote commodities online, it is suggested that the actual benefit from the sales promotion should be specified to reduce the ambiguity of sales promotion information. As the neuromarketing develops, merchants have obtained more effective approaches to study marketing strategies.

One of the theoretical contributions this paper made is that the authors innovatively explored the consumer’s preference to online sales promotion strategies from the perspective of fuzzy decision. Second, the authors adopted the ERP technique to study the influence of the ambiguity of sales promotion information on the consumer’s purchasing behaviors. Third, this study provides an explanation for why consumers prefer the sales promotion type of discounts according to the neural mechanism of decision making.

The purpose of this paper is to gain more insight into the relationship between social media activities and thinking styles, and its potential mechanism.

The current study conducted four studies using an experimental method and eye-tracking method to evaluate prediction.

Results from studies 1 and 2 showed that social media activities influence individuals’ self-construal, and the impact of self-construal on the relative reliance on cognitive vs affective thinking styles. Study 3 supports the hypothesis that social media activities influence individual’s thinking styles, and self-construal is a critical mediator in this process. Furthermore, the authors replicated these findings using an experimental method and eye-tracking method (Study 4), which enabled us to better understand the consumer’s psychological experience when using social media.

This paper contributes to the social media activity literature in the following ways. First, this research advances the knowledge of social media by demonstrating that social media activities can have significant effects on thinking styles. Second, the current research brings important insights to the literature on self-construal. Finally, using eye-tracking methods, the authors also provided some new insights on consumer thinking and behavior.

As productions show characteristics of multi-varieties and small batch in a recent new product system, it is more difficult to acquire its failure rate data. With the help of expert experience information, the authors can get the interval estimation of failure rate data under different methods, so how to make the interval convergence with the new information is an important problem to be solved. The paper aims to discuss this issue.

In this paper, the concept of generalized standard grey number is used to characterize the multi-source heterogeneous uncertainty failure rate data into a unified framework. Then, the engineering construction method is used to calculate the average failure rate and build the grey exponential distribution reliability function, whose image is presented as the possible region of the two-curve envelope.

Further, according to the normal distribution assumption of the regional convergence based on the information supplement, the convergence problem of the reliability function is transformed into the convergence of the area of the curve envelope region, and construct the multi-objective programming model with the minimum envelope area and the lowest total cost of information acquisition, acquire the conclusion that the failure rate is equal to the nuclear of the average failure rate when the envelope region converges.

Through the case analysis of the equipment ejection system of the Harbinger system, five groups of results are obtained by Matlab simulation, which verify the rationality and feasibility of the model described in this paper.

The purpose of this paper is to propose a method to help firms assess lifetime profitability of customers whose buying behaviors are characterized by purchasing cycles, which are determined by both intrinsic purchasing cycles and cumulative effects of firms’ marketing solicitations.

This paper first proposes a probability model to predict customers’ responses to firms’ marketing solicitations in which a customer’s inter-purchase times are assumed to follow a Poisson distribution, whose parameters vary across customers and follow a gamma distribution. The paper then proposes a customer profitability scoring model that uses customers’ responses as an input to assess their lifetime profitability at a given point of time.

The paper illustrates the proposed method using individual-level purchasing data of 529 customers from a catalog firm. The paper shows that the proposed model outperforms the benchmark model in terms of both explaining and predicting customers’ purchases. The paper also demonstrates significant profit consequences to the firm if incorrect methods are used instead of the proposed method.

The proposed method can help firms select or eliminate customers based on their lifetime profitability so that firms can focus their marketing efforts in a more targeted manner to increase total profits.

The proposed Gamma-Poisson probability model and the profitability scoring method are easy to implement due to the attractive conjugacy property. It is valuable for firms’ customer relationship management applications from the standpoint of making customer selection and inventory management decisions.

The purpose of this paper is to preset a spherical element subdivision method for the numerical evaluation of nearly singular integrals in three-dimensional (3D) boundary element method (BEM).

In this method, the source point is first projected to the tangent plane of the element. Then two cases are considered: the projection point is either inside or outside the element. In both cases, the element is subdivided into a number of patches using a sequence of spheres with decreasing radius.

With the proposed method, the patches obtained are automatically refined as they approach the projection point and each patch of the integration element is “good” in shape and size for standard Gaussian quadrature. Therefore, all kinds of nearly singular boundary integrals on elements of any shape and size with arbitrary source point location related to the element can be evaluated accurately and efficiently.

Numerical examples for planar and slender elements with various relative location of the source point are presented. The results demonstrate that our method has much better accuracy, efficiency and stability than conventional methods.

This paper aims to comprehensively clarify the research status of thermal transport of supercritical aviation kerosene, with particular interests in the effect of cracking on heat transfer.

A brief review of current research on supercritical aviation kerosene is presented in views of the surrogate model of hydrocarbon fuels, chemical cracking mechanism of hydrocarbon fuels, thermo-physical properties of hydrocarbon fuels, turbulence models, flow characteristics and thermal performances, which indicates that more efforts need to be directed into these topics. Therefore, supercritical thermal transport of n-decane is then computationally investigated in the condition of thermal pyrolysis, while the ASPEN HYSYS gives the properties of n-decane and pyrolysis products. In addition, the one-step chemical cracking mechanism and SST k-ω turbulence model are applied with relatively high precision.

The existing surrogate models of aviation kerosene are limited to a specific scope of application and their thermo-physical properties deviate from the experimental data. The turbulence models used to implement numerical simulation should be studied to further improve the prediction accuracy. The thermal-induced acceleration is driven by the drastic density change, which is caused by the production of small molecules. The wall temperature of the combustion chamber can be effectively reduced by this behavior, i.e. the phenomenon of heat transfer deterioration can be attenuated or suppressed by thermal pyrolysis.

The issues in numerical studies of supercritical aviation kerosene are clearly revealed, and the conjugation mechanism between thermal pyrolysis and convective heat transfer is initially presented.

The Convolution Quadrature Method (CQM) has been widely applied to solve transient elastodynamic problems because of its stability and generality. However, the CQM suffers from the problems of huge memory requirement in case of direct implementation in time domain or CPU time in case of its reformulation in Laplace domain. The purpose of this paper is to combine the CQM with the pseudo-initial condition method (PICM) to achieve a good balance between memory requirement and CPU time.

The combined methods first subdivide the whole analysis into a few sub-analyses, which is dealt with the PICM, namely, the results obtained by previous sub-analysis are used as the initial conditions for the next sub-analysis. In each sub-analysis, the time interval is further discretized into a number of sub-steps and dealt with the CQM. For non-zero initial conditions, the pseudo-force method is used to transform them into equivalent body forces. The boundary face method is employed in the numerical implementation. Three examples are analyzed. Results are compared with analytical solutions or FEM results and the results of reformulated CQM.

Results demonstrate that the computation time and the storage requirement can be reduced significantly as compared to the CQM, by using the combined approach.

The combined methods can be successfully applied to the problems of long-time dynamic response, which requires a large amount of computer memory when CQM is applied, while preserving the CQM stability. If the number of time steps is high, then the accuracy of the proposed approach can be deteriorated because of the pseudo-force method.