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Due to the attitude-behavior gap in green consumption, it is necessary to conduct more research on consumers' actual purchase behavior. At present, few studies have been conducted on the impact of empathy with nature on green purchase behavior. This research explored the underlying neural mechanism of empathy with nature on consumers' green purchase decisions by applying the event-related potentials (ERPs) approach. Behaviorally, compared with the control group, the experimental group had a higher purchase rate of green products and spent less time when buying green products. For the experimental group, buying green products required less time than buying traditional products. At the neural level, when buying green products, the N2 and N400 amplitudes of the experimental group were smaller than those of the control group. For the experimental group, buying green products elicited a smaller N2 amplitude than buying traditional products. These findings suggested that empathy with nature could reduce consumers' decision conflict when buying green products, thereby promoting consumers' green purchase behavior.

Similar to traditional luxuries, affordable luxuries enjoy a high level of perceived product quality and perceived social status, but the effectiveness of price promotions of purchasing affordable luxury products is different from that of traditional luxuries. In order to further investigate the purchases of affordable luxuries, we used event-related potential (ERP) technology to reveal the formation of the purchase intention toward affordable luxuries at original prices (high or low) and current prices (discounted or non-discounted). Compared with the high-priced affordable luxury without a price promotion and the low-priced affordable luxury with a price promotion, consumers showed a stronger intention toward the high-priced affordable luxury with a price promotion, by weighing up three factors, perceived product quality, perceived social status, and perceived monetary saving at the behavioral level. A shorter reaction time emerged in the price promotion condition than in the absent price promotion condition when the original price was low. At the neural level, a decrease in N2 amplitude was found in the high original price and discounted current price condition than the high original price and non-discounted current price condition and the low original price and discounted current price condition, respectively, suggesting that the price information of the latter two conditions might not be the expectation information of subjects, and thus, the enhanced conflict is produced. The high-priced affordable luxury product without a price discount evoked a more positive LPP amplitude than the high-priced affordable luxury product with price promotions or than the low-priced affordable luxury item without price promotions, demonstrating that participants could regard the former as an evaluative inconsistent condition and the latter as evaluative consistent conditions. These results are helpful to better understand the effects of price promotions on purchasing affordable luxury products at different original prices.

Distant brand extension as an essential strategy of obtaining benefits was highly focused on the normal marketing practice and academic research. In the current study, we aim to recognize that how individuals with different levels of empathy respond to distant extensions under corporate social responsibility (CSR) and corporate competence (CC) associations to explore the corresponding neural mechanisms using event-related potentials (ERPs). We divided subjects into two groups involving a high empathy (HE) group and a low empathy (LE) group according to an empathy measure questionnaire. The subjects first faced a brand name following the CSR or CC association descriptions, and then, they were asked to evaluate the new product of brand by a five-point scale. Current results revealed that the participants of the HE group were more apt to accept the distant extension products than those of the LE group. Additionally, in the HE group, products from a brand with CSR associations were more acceptable than CC associations. Moreover, a larger N2 amplitude was elicited in the LE group than in the HE group. For the LE group, an augment N2 was found under CSR than CC associations, reflecting that LE consumers might perceive conflict when evaluating distant extensions and allocate more cognitive resources to deal with CSR information. At the later stage, the HE group showed a greater P3 than the LE group. For the HE group, an increased P3 was elicited under CSR than CC associations, suggesting that empathic individuals might show motivational salience and helping willingness toward distant extension products, especially under the CSR scenario. These results provide potential electrophysiological evidence for the positive impact of brand associations on the evaluation of distant brand extension in the case of subdividing different empathic individuals.

The emotional factor in mass emergencies with maintained legal rights significantly influences the decision-making of the powerful and vulnerable groups and the course of events. In this paper, we established the game model of rank-dependent expected utility for the powerful and vulnerable groups in mass emergencies with maintained legal rights. And we also explored the influence of different emotional states on the results of strategic equilibrium of both sides of a game. Results show that the behaviours of the powerful or vulnerable groups are not only affected by the choice of their other strategies, but also influenced by the degree of emotion. The more optimistic they are, the more inclined they are to solve the mass emergencies with maintained legal rights; the more pessimistic they are, the more inclined they are to take extreme resistance behaviours and the more likely pessimism is to adversely affect the two groups’ behaviour choices. The numerical simulation with MATLAB further validates this conclusion. Therefore, the emotions of both sides should be controlled and understood when managing mass emergencies to solve problems effectively and reasonably.

Due to consuming hedonic products unnecessary to basic well-being, consumers need justifications for pleasure. However, different justifications have differential influences in promoting hedonic purchases, such as price and quantity promotions (PP and QP), the difference being that the latter requires purchasing additional units to get the same discount as the former. In the present study, even-related potentials (ERPs) was applied to reveal the timing of brain activities to further understand how promotion information consisting of promotion type (PP and QP) and discount depth, deep and shallow discounts (DD and SD) on hedonic products was processed. Behaviorally, consumers were more willing to purchase items in PP and DD conditions than QP and SD conditions, respectively, and spent more time making final purchase decisions in QP and DD condition or PP and SD condition compared to PP and DD condition. Neurophysiologically, DD automatically recruited more attentional resources than SD and led to a higher P2 amplitude. QP and DD condition or PP and SD condition evoked a larger N2 amplitude and enhanced perceptual conflict compared to PP and DD condition. During late stage, PP and DD elicited a more positive LPP amplitude in contrast to QP and SD, respectively, indicating that people have stronger purchase intention and positive affect in PP and DD contexts. These findings provided evidence for the differential influences between PP and QP and what ultimately made consumers buy hedonic products or not.

The ACOR algorithm is an Ant Colony Optimization (ACO) extended to continuous domains, and has been used for training neural network. However, when training neural networks, ACOR does not allow for heuristic information like most conventional ACO algorithms do. So in this work we propose a hybrid ACOR algorithm, named h-ACOR, which incorporates the heuristic information into the framework of ACOR for neural network training. The heuristic information in h-ACOR is a gradient vector obtained by computing the partial derivative of error term of the neural network with respect to weight vector. The h-ACOR is tested on training neural networks for pattern classification problems with UCI datasets: zoo, iris and tic-tac-toe. The experiments were carried out using 10-fold cross-validation method, and the results show that: h-ACOR has better performance than ACOR with almost half of convergence generations; and after completely training by h-ACOR, the average classification accuracy of datasets zoo, iris and tic-tac-toe is 92.6% while that of ACOR is 86.6%.

Complex system is a very common objective reality, the study about complex problem is the frontiers and focuses of science. Complex system which always is hierarchical and has multi-layers, it certainly contains qualitative and quantitative information, and the data of it always are multi-dimensional. This paper proposed that in a complex hierarchical system background, through the method of expressing the multi-dimensional qualitative and quantitative data as multi-dimensional statistical chart, we constructs hierarchical, multi-layers, and has coupled parameters information fusion model. And we use this system for analyzing the authoritative database data to demonstrate the method can be applied in information fusion research.

It is crucial for an instrumentation to have an efficient method of measurement signal analysis. Especially there are multiple sensors in the instrumentation, i.e. the multi-sensor information fusion. In recent years, we intend to discover a new method of multi-source massive data analysis. Based on the research of Formal Concept Analysis theory, we proposed the Hierarchical Concept Graph Model for massive data analysis. In this paper, we briefed the theory of Formal Concept Analysis and Hierarchical Concept Graph Model, and then we represented the result of the application about our theory in massive dataset analysis. The result of our former research has demonstrated that our theory has the potential to be applied in measurement signal analysis.