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The domain of monetary donation is evolving with the combination of professional donation platforms and social network sites (SNSs) in the agency process, potentially enhancing information communication and facilitating money transfers between donors and recipients. However, SNS donation avoidance hinders the leveraging of significant economic and social values. To address the limited understanding of the phenomenon of SNS donation avoidance, this study aims to investigate the influencing factors of people's avoidance behavior in the agency process of SNS donation.

A model was devised containing four process-related factors (requests overload, process ambiguity, channel security concerns and perceived distributive injustice) as antecedents of SNS donation avoidance, with probable mediating paths of negative emotions, altruistic outcome expectation and egoistic outcome expectation. Data were collected through a survey of 398 users of WeChat Moment in China. Structural equation modeling was used to analyze the proposed model.

All four process-related factors have positive associations with SNS donation avoidance. Requests overload, channel security concerns and perceived distributive injustice all positively influence people's expectation of negative emotions and lead, in turn, to their SNS donation avoidance. Perceived distributive injustice also leads to SNS donation avoidance via negatively influencing people's expectations of both altruistic and egoistic outcomes.

Theoretically, this empirical study synthetically associates process-related factors to donation avoidance through the paths of emotional responses and rational outcome expectations. Practically, it emphasizes key factors to consider in the process management of SNS donation.

Forecasts of commodity prices are vital issues to market participants and policy makers. Those of corn are of no exception, considering its strategic importance. In the present study, the authors assess the forecast problem for the weekly wholesale price index of yellow corn in China during January 1, 2010–January 10, 2020 period.

The authors employ the nonlinear auto-regressive neural network as the forecast tool and evaluate forecast performance of different model settings over algorithms, delays, hidden neurons and data splitting ratios in arriving at the final model.

The final model is relatively simple and leads to accurate and stable results. Particularly, it generates relative root mean square errors of 1.05%, 1.08% and 1.03% for training, validation and testing, respectively.

Through the analysis, the study shows usefulness of the neural network technique for commodity price forecasts. The results might serve as technical forecasts on a standalone basis or be combined with other fundamental forecasts for perspectives of price trends and corresponding policy analysis.

As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous expansion of the application of AM materials, subtractive processing has become one of the necessary steps to improve the accuracy and performance of parts. In this paper, the processing process of AM materials is discussed in depth, and the surface integrity problem caused by it is discussed.

Firstly, we listed and analyzed the characterization parameters of metal surface integrity and its influence on the performance of parts and then introduced the application of integrated processing of metal adding and subtracting materials and the influence of different processing forms on the surface integrity of parts. The surface of the trial-cut material is detected and analyzed, and the surface of the integrated processing of adding and subtracting materials is compared with that of the pure processing of reducing materials, so that the corresponding conclusions are obtained.

In this process, we also found some surface integrity problems, such as knife marks, residual stress and thermal effects. These problems may have a potential negative impact on the performance of the final parts. In processing, we can try to use other integrated processing technologies of adding and subtracting materials, try to combine various integrated processing technologies of adding and subtracting materials, or consider exploring more efficient AM technology to improve processing efficiency. We can also consider adopting production process optimization measures to reduce the processing cost of adding and subtracting materials.

With the gradual improvement of the requirements for the surface quality of parts in the production process and the in-depth implementation of sustainable manufacturing, the demand for integrated processing of metal addition and subtraction materials is likely to continue to grow in the future. By deeply understanding and studying the problems of material reduction and surface integrity of AM materials, we can better meet the challenges in the manufacturing process and improve the quality and performance of parts. This research is very important for promoting the development of manufacturing technology and achieving success in practical application.

This study aims to examine how the knowledge breadth and depth of a patent affect its likelihood of being pledged. It also seeks to explore whether these relationships change diversely in different technological environments.

A complementary log-log model with random effects was conducted to test the hypotheses using a unique data set consisting of 348,927 invention patents granted by the China National Intellectual Property Administration from 1985 to 2015 belonging to 74,996 firms.

The findings reveal that both knowledge breadth and depth of a patent positively affect its likelihood of being pledged. Furthermore, the knowledge breadth and depth entail different degrees of superiority in different technological environments.

This study focuses on the effect of an individual patent’s knowledge base on its likelihood of being selected as collateral. It does not consider the influence of the overall knowledge characteristics of the selected patent portfolio.

Managers need to pay attention to patents’ knowledge characteristics and the changes in technological environments to select the most suitable patents as collateral and thus improve the success rate of pledge financing.

This study explores the impact of multidimensional characteristics of knowledge base on patent pledge financing within a systematic theoretical framework and incorporates technological environments into this framework.

The purpose of this paper is to analyze the historical pattern of environmental cost due to grain production in China and to provide further implications of technologies and policies for the transformation of China’s agricultural development toward sustainable intensification.

The data sets about grain production, arable land and chemical fertilizer use in China were collected from FAO, NBSC, and IFA. Greenhouse gas emissions were estimated using life cycle assessments. The policies concerning grain production and the environment were collected from the Ministry of Agriculture, and the State Council of China.

China has produced enough food to feed its growing population, but has neglected the resource-environmental costs of grain production since 1978. Consequently, China’s grain production is always accompanied with a high cost of resource and environment sustainability. However, from 2006 to 2015, the growth rate of grain production has surpassed that of chemical fertilizer consumption, resulting in improvement in nutrient use efficiency and decreasing trends of environmental cost for grain production. This could be partially attributed to technology innovations, such as Soil-Testing and Fertilizer-Recommendations (STFR), soil quality and crop management improvement, and so on, and policy supports (policies of STFR, soil quality improvement, and high-yield construction). This indicated that China’s grain production is starting to transform from high-input and high-output model to “less for more.”

This study is the first to determine the detailed, historical role of technological innovation and agri-environmental policy on the sustainability of grain production in China. The findings should have significant implications for technology and policy for the transformation of China’s agriculture development to sustainable intensification.

The aim of this study is to investigate the impact of local political uncertainty on the asymmetric cost behavior (i.e. cost stickiness) for listed firms in China.

In this study, the authors manually collect the turnover data of prefecture-city officials as a measure of exogenous fluctuations in political uncertainty and obtain firm-level financial information from the China Stock Market Accounting Research (CSMAR) database. To perform the analysis, the authors augment the traditional cost stickiness model by including the interaction terms of the prefecture-city official turnover, and firm-level and prefecture-city level control variables.

The authors find that political turnover leads to a higher degree of cost stickiness, implying that firms retain slack resources when political uncertainty is high. Moreover, the effect of political turnover on cost stickiness is more pronounced for firms residing in regions with weaker institutional environments, and firms that are privately owned and with smaller size. The authors further provide evidence that policy uncertainty and the threat of losing political connection are two underlying channels. Overall, this study documents that the local political process is an important channel that influences corporate operational decisions.

This study provides the first piece of evidence on the relation between political uncertainty and cost stickiness at the local government level. Moreover, the authors propose and demonstrate two underlying channels through which political uncertainty affects firms' asymmetric cost behavior.

The purpose of this article is the effect of doping minor Ni on the microstructure evolution of a Sn-xNi (x = 0, 0.05 and 0.1 wt.%)/Ni (Poly-crystal/Single-crystal abbreviated as PC Ni/SC Ni) solder joint during reflow and aging treatment. Results showed that the intermetallic compounds (IMCs) of the interfacial layer of Sn-xNi/PC Ni joints were Ni₃Sn₄ phase, while the IMCs of Sn-xNi/SC Ni joints were NiSn₄ phase. After the reflow process and thermal aging of different joints, the growth behavior of interfacial layer was different due to the different mechanism of element diffusion of the two substrates. The PC Ni substrate mainly provided Ni atoms through grain boundary diffusion. The Ni₃Sn₄ phase of the Sn0.05Ni/PC Ni joint was finer, and the diffusion flux of Sn and Ni elements increased, so the Ni₃Sn₄ layer of this joint was the thickest. The SC Ni substrate mainly provided Ni atoms through the lattice diffusion. The Sn0.1Ni/SC Ni joint increases the number of Ni atoms at the interface due to the doping of 0.1Ni (wt.%) elements, so the joint had the thickest NiSn₄ layer.

The effects of doping minor Ni on the microstructure evolution of an Sn-xNi (x = 0, 0.05 and 0.1 Wt.%)/Ni (Poly-crystal/Single-crystal abbreviated as PC Ni/SC Ni) solder joint during reflow and aging treatment was investigated in this study.

Results showed that the intermetallic compounds (IMCs) of the interfacial layer of Sn-xNi/PC Ni joints were Ni₃Sn₄ phase, while the IMCs of Sn-xNi/SC Ni joints were NiSn₄ phase. After the reflow process and thermal aging of different joints, the growth behavior of the interfacial layer was different due to the different mechanisms of element diffusion of the two substrates.

In this study, the effect of doping Ni on the growth and formation mechanism of IMCs of the Sn-xNi/Ni (single-crystal) solder joints (x = 0, 0.05 and 0.1 Wt.%) was investigated.

In this study, a novel glutathione (GSH) surface molecular imprinting polymer (SMIP) was successfully prepared by using macroporous adsorption resins (MAR) as substrate, which could separate and purify GSH efficiently.

SMIP was synthesized by chloromethylated modified MAR (LX1180-Cl) as the substrate, N, N’-methylenebisacrylamide (NMBA) as a crosslinker, GSH as a template, acrylamide (AM) and N-vinylpyrrolidone (NVP) as functional monomers. The morphology and structure of the polymer were characterized by scanning electron microscope and Fourier transforms infrared spectroscopy.

The maximum adsorption capacity toward GSH was 39.0 mg/g and the separation decree had relation to L-cysteine (L-cys) was 4.2. The optimal operation conditions were studied in detail and the got as follows: the molar ratios of NMBA, AM, GSH and NVP, were 7.0, 0.8 and 0.5. The optimal time and temperature were 14 h and 40°C, respectively. The Langmuir and pseudo-first-order model were fitting these adsorption characteristics well.

GSH has a diversity of medicinal and bioactive functions, so the purpose of this study representing a method in separate and purify technology of GSH, which provided a way for the development of medicine.

This contribution provided a novel way to separate GSH from L-cys. Under the optimal conditions, the maximum adsorption capacity toward GSH was 39.0 mg/g and the separation decree had relation to L-cys was 4.2.

This paper identifies and models the effect of eight attributes that influence hotel room rents in India. These attributes are conceptually grouped into three factors: (1) site factors including the presence or absence of a “swimming pool,” “free breakfast,” and the “hotel capacity”; (2) situational factors including, “distance from the airport,” “weekend/weekday,” “city population,” “cost of living”; and (3) a reputation factor indicated by “star rating.” Our regression model uses secondary data collected from a hotel booking website for 570 hotels across 18 cities of India. The results indicate that six out of these eight variables namely, presence of swimming pool, free breakfast, hotel capacity, distance from the airport, city population, and hotel star rating have a significant impact on hotel room rents in India.