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1 – 10 of 54Yanping Gong, Wei Hou, Qin Zhang and Shuang Tian
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…
Abstract
Purpose
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.
Design/methodology/approach
The paper uses the event-related potential (ERP) technique and experiment.
Findings
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.
Practical implications
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.
Originality/value
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.
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Shuang Zhang, Song Xi Chen and Lei Lu
With the presence of pricing errors, the authors consider statistical inference on the variance risk premium (VRP) and the associated implied variance, constructed from the option…
Abstract
Purpose
With the presence of pricing errors, the authors consider statistical inference on the variance risk premium (VRP) and the associated implied variance, constructed from the option prices and the historic returns.
Design/methodology/approach
The authors propose a nonparametric kernel smoothing approach that removes the adverse effects of pricing errors and leads to consistent estimation for both the implied variance and the VRP. The asymptotic distributions of the proposed VRP estimator are developed under three asymptotic regimes regarding the relative sample sizes between the option data and historic return data.
Findings
This study reveals that existing methods for estimating the implied variance are adversely affected by pricing errors in the option prices, which causes the estimators for VRP statistically inconsistent. By analyzing the S&P 500 option and return data, it demonstrates that, compared with other implied variance and VRP estimators, the proposed implied variance and VRP estimators are more significant variables in explaining variations in the excess S&P 500 returns, and the proposed VRP estimates have the smallest out-of-sample forecasting root mean squared error.
Research limitations/implications
This study contributes to the estimation of the implied variance and the VRP and helps in the predictions of future realized variance and equity premium.
Originality/value
This study is the first to propose consistent estimations for the implied variance and the VRP with the presence of option pricing errors.
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Shuang Wu, Bo Li, Weichun Chen and Minxue Wang
This paper analyzes the advance selling and pricing strategies of fresh products supply chain where the e-retailer provides wholesale contract or agency contract to the fresh…
Abstract
Purpose
This paper analyzes the advance selling and pricing strategies of fresh products supply chain where the e-retailer provides wholesale contract or agency contract to the fresh products supplier.
Design/methodology/approach
This paper constructed a two-period sequential-move game of fresh products supply chain members.
Findings
This analysis showed that the supply chain members had different preferences for contracts under different market conditions. The advance selling of fresh products was not a decision of the seller, but also required the support of other supply chain members. And the advance selling strategy was not always beneficial to all supply chain parties. Under the two contracts, there were market conditions in which the profits of supply chain members were Pareto-improved through the implementation of advance selling.
Research limitations/implications
The model presented in this study focuses solely on the context of monopoly, overlooking the competition from alternative suppliers or retailers. Consequently, exploring the competitive landscape within the fresh products supply chain, particularly in relation to pre-sale pricing, emerges as a crucial avenue for further investigation. By employing empirical research methods, valuable insights are gleaned, thereby significantly augmenting the existing body of relevant theories.
Practical implications
The decision to pre-sell fresh products should be based on market conditions. Supply chain members can control production costs and fresh products circulation losses to maximize profits.
Originality/value
From the perspective of game theory, this study analyzed the optimal advance selling and pricing strategies of fresh products supply chain members under two kinds of contracts. These results can provide practical implications for fresh products suppliers and e-retailers.
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The conventional pedestrian detection algorithms lack in scale sensitivity. The purpose of this paper is to propose a novel algorithm of self-adaptive scale pedestrian detection…
Abstract
Purpose
The conventional pedestrian detection algorithms lack in scale sensitivity. The purpose of this paper is to propose a novel algorithm of self-adaptive scale pedestrian detection, based on deep residual network (DRN), to address such lacks.
Design/methodology/approach
First, the “Edge boxes” algorithm is introduced to extract region of interests from pedestrian images. Then, the extracted bounding boxes are incorporated to different DRNs, one is a large-scale DRN and the other one is the small-scale DRN. The height of the bounding boxes is used to classify the results of pedestrians and to regress the bounding boxes to the entity of the pedestrian. At last, a weighted self-adaptive scale function, which combines the large-scale results and small-scale results, is designed for the final pedestrian detection.
Findings
To validate the effectiveness and feasibility of the proposed algorithm, some comparison experiments have been done on the common pedestrian detection data sets: Caltech, INRIA, ETH and KITTI. Experimental results show that the proposed algorithm is adapted for the various scales of the pedestrians. For the hard detected small-scale pedestrians, the proposed algorithm has improved the accuracy and robustness of detections.
Originality/value
By applying different models to deal with different scales of pedestrians, the proposed algorithm with the weighted calculation function has improved the accuracy and robustness for different scales of pedestrians.
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Shuang Han, Jing Zhang, Quanyue Yang, Zijian Yuan, Shubin Li, Fengying Cui, Chuntang Zhang and Tao Wang
The performance of the classical car-following system is easily affected by external disturbances. To enhance the performance of the classical car-following model under sudden…
Abstract
Purpose
The performance of the classical car-following system is easily affected by external disturbances. To enhance the performance of the classical car-following model under sudden external disturbances, a novel car-following model is established to smooth traffic flow.
Design/methodology/approach
This paper proposed a Proportion Integration Differentiation (PID) control strategy based on classical control theory and developed a novel car-following model. The linear system theory and Laplace transform are used to derive a closed-loop transfer function. Then, the stability condition is obtained by using the Routh stability criterion and the small gain theorem. Finally, the validity and feasibility of the PID control strategy is proved by numerical simulations.
Findings
The analytic results and the numerical simulation results show that both the integration part and the differential part have the positive effect to suppress traffic oscillation efficiently; the collaboration of these two parts has more power to improve the stability of traffic flow. It means that the proposed model integrated with the PID control strategy has the ability of anti-interference and smooth traffic compared with the classical car-following model.
Originality/value
This paper introduces the PID control strategy into the classical car-following system, which enhances the stability of the system and also provides an efficient method for optimizing the traffic flow system.
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Zhang Yong’an, Geng Zhe and Tian Jie
Science and technology innovation policy has important strategic significance with respect to the promotion of an innovation orientation in our country, and the classification and…
Abstract
Purpose
Science and technology innovation policy has important strategic significance with respect to the promotion of an innovation orientation in our country, and the classification and measurement of regional science and technology innovation policy urgently require research attention.
Design/methodology/approach
In this paper, we use text mining and principal component analysis to analyze the classification and measurement of technology innovation policy based on data obtained from Zhongguancun Science Park.
Findings
The empirical results indicate that regional science and technology innovation policy can be divided into four types: authoritative, guiding, urgent and periodical. The key measurements are function type, intensity, resource supply, funding level and funding effectiveness.
Originality/value
A comparative analysis is performed to investigate the different types of regional science and technology innovation policy measurement. Additionally, the study’s limitations are discussed, and future research directions are proposed.
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Xiaogen Liu, Shuang Qi, Detian Wan and Dezhi Zheng
This paper aims to analyze the bearing characteristics of the high speed train window glass under aerodynamic load effects.
Abstract
Purpose
This paper aims to analyze the bearing characteristics of the high speed train window glass under aerodynamic load effects.
Design/methodology/approach
In order to obtain the dynamic strain response of passenger compartment window glass during high-speed train crossing the tunnel, taking the passenger compartment window glass of the CRH3 high speed train on Wuhan–Guangzhou High Speed Railway as the research object, this study tests the strain dynamic response and maximum principal stress of the high speed train passing through the tunnel entrance and exit, the tunnel and tunnel groups as well as trains meeting in the tunnel at an average speed of 300 km·h-1.
Findings
The results show that while crossing the tunnel, the passenger compartment window glass of high speed train is subjected to the alternating action of positive and negative air pressures, which shows the typical mechanic characteristics of the alternating fatigue stress of positive-negative transient strain. The maximum principal stress of passenger compartment window glass for high speed train caused by tunnel aerodynamic effects does not exceed 5 MPa, and the maximum value occurs at the corresponding time of crossing the tunnel groups. The high speed train window glass bears medium and low strain rates under the action of tunnel aerodynamic effects, while the maximum strain rate occurs at the meeting moment when the window glass meets the train head approaching from the opposite side in the tunnel. The shear modulus of laminated glass PVB film that makes up high speed train window glass is sensitive to the temperature and action time. The dynamically equivalent thickness and stiffness of the laminated glass and the dynamic bearing capacity of the window glass decrease with the increase of the action time under tunnel aerodynamic pressure. Thus, the influence of the loading action time and fatigue under tunnel aerodynamic effects on the glass strength should be considered in the design for the bearing performance of high speed train window glass.
Originality/value
The research results provide data support for the analysis of mechanical characteristics, damage mechanism, strength design and structural optimization of high speed train glass.
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Muhammad Jawad Sajid, Qingren Cao, Ming Cao and Shuang Li
Presentation of the different industrial carbon linkages of India. The purpose of this paper is to understand the direct and indirect impact of these industrial linkages.
Abstract
Purpose
Presentation of the different industrial carbon linkages of India. The purpose of this paper is to understand the direct and indirect impact of these industrial linkages.
Design/methodology/approach
This study uses a hypothetical extraction method with its various extensions. Under this method, different carbon linkages of a block are removed from the economy, and the effects of carbon linkages are determined by the difference between the original and the post-removal values. Energy and non-energy carbon linkages are also estimated.
Findings
“Electricity, gas and water supply (EGW)” at 655.61 Mt and 648.74 Mt had the highest total and forward linkages. “manufacturing and recycling” at 231.48 Mt had the highest backward linkage. High carbon-intensive blocks of “EGW” plus “mining and quarrying” were net emitters, while others were net absorbers. “Fuel and chemicals” at 0.08 Mt had almost neutral status. Hard coal was the main source of direct and indirect emissions.
Practical implications
Net emitting and key net forward blocks should reduce direct emission intensities. India should use its huge geographical potential for industrial accessibility to cheaper alternative energy. This alongside with technology/process improvements catalyzed by policy tools can help in mitigation efforts. Next, key net-backward blocks such as construction through intermediate purchases significantly stimulate emissions from other blocks. Tailored mitigation policies are needed in this regard.
Originality/value
By developing an understanding of India’s industrial carbon links, this study can guide policymakers. In addition, the paper lays out the framework for estimating energy and non-energy-based industrial carbon links.
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Shuang Geng, Lijing Tan, Ben Niu, Yuanyue Feng and Li Chen
Although digitalization in the workplace is burgeoning, tools are needed to facilitate personalized learning in informal learning settings. Existing knowledge recommendation…
Abstract
Purpose
Although digitalization in the workplace is burgeoning, tools are needed to facilitate personalized learning in informal learning settings. Existing knowledge recommendation techniques do not account for dynamic and task-oriented user preferences. The purpose of this paper is to propose a new design of a knowledge recommender system (RS) to fill this research gap and provide guidance for practitioners on how to enhance the effectiveness of workplace learning.
Design/methodology/approach
This study employs the design science research approach. A novel hybrid knowledge recommendation technique is proposed. An experiment was carried out in a case company to demonstrate the effectiveness of the proposed system design. Quantitative data were collected to investigate the influence of personalized knowledge service on users’ learning attitude.
Findings
The proposed personalized knowledge RS obtained satisfactory user feedback. The results also show that providing personalized knowledge service can positively influence users’ perceived usefulness of learning.
Practical implications
This research highlights the importance of providing digital support for workplace learners. The proposed new knowledge recommendation technique would be useful for practitioners and developers to harness information technology to facilitate workplace learning and effect organization learning strategies.
Originality/value
This study expands the scope of research on RS and workplace learning. This research also draws scholarly attention to the effective utilization of digital techniques, such as a RS, to support user decision making in the workplace.
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Tengjiang Yu, Haitao Zhang, Junfeng Sun, Yabo Wang, Shuang Huang and Dan Chen
Using typical structure of asphalt pavement in Harbin area of China, and the formula of generalized friction coefficient between base and surface layers of asphalt pavement in…
Abstract
Purpose
Using typical structure of asphalt pavement in Harbin area of China, and the formula of generalized friction coefficient between base and surface layers of asphalt pavement in cold area is established.
Design/methodology/approach
Through structural characteristics analysis of asphalt pavement in cold area, the generalized formula of friction coefficient between base and surface layers of asphalt pavement in cold area is derived. The formula can quickly calculate the friction coefficient between layers of asphalt pavement.
Findings
Based on quantitative analysis to the contacting state between layers of asphalt pavement in cold area, the relationships between generalized friction coefficient and resilient modulus of asphalt mixtures, temperature shrinkage coefficient and temperature have been established.
Originality/value
The findings can enrich the description methods about the contacting state between layers of asphalt pavement, and have a certain theoretical and practical value. Through the application of the formula of generalized friction coefficient between layers, it can provide a technical basis for the asphalt pavement design, construction and maintenance in cold area.
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