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1 – 3 of 3Jia Jin, Yi He, Chenchen Lin and Liuting Diao
Social recommendation has been recognized as a kind of e-commerce with large potential, but how social recommendations influence consumer decisions is still unclear. This paper…
Abstract
Purpose
Social recommendation has been recognized as a kind of e-commerce with large potential, but how social recommendations influence consumer decisions is still unclear. This paper aims to investigate how recommendations from different social ties influence consumers’ purchase intentions through both behavior and brain activity.
Design/methodology/approach
Utilizing behavioral (N = 70) and electroencephalogram (EEG) (N = 49) experiments, this study explored participants’ behavior and brain responses after being recommended by different social ties. The data were analyzed using statistical inference and event-related potential (ERP) analysis.
Findings
Behavioral results show that social tie strength positively impacts purchase intention, which can be fitted by a logarithmic model. Moreover, recommender-to-customer similarity and product affect mediate the effect of tie strength on purchase intention serially. EEG findings show that recommendations from weak tie strength elicit larger N100, N200 and P300 amplitudes than those from strong tie strength. These results imply that weak tie strength may motivate individuals to recruit more mental resources in social recommendation, including unconscious processing of consumer attention and conscious processing of cognitive conflict and negative emotion.
Originality/value
This study considers the effects of continuous social ties on purchase intention and models them mathematically, exploring the intrinsic mechanisms by which strong and weak ties influence purchase intentions through recommender-to-customer similarity and product affect, contributing to the applications of the stimulus-organism-response (SOR) model in the field of social recommendation. Furthermore, our study adopting EEG techniques bridges the gap of relying solely on self-report by providing an avenue to obtain relatively objective findings about the consumers’ early-occurred (unconscious) attentional responses and late-occurred (conscious) cognitive and emotional responses in purchase decisions.
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Huimin Li, Chenchen Xu, Yongchao Cao and Chengyi Zhang
The purpose of this paper is twofold: first, it explores the influencing factors of the government’s trust decision-making in the private sector; second, it explores how these…
Abstract
Purpose
The purpose of this paper is twofold: first, it explores the influencing factors of the government’s trust decision-making in the private sector; second, it explores how these influencing factors affect the government’s trust decisions.
Design/methodology/approach
A theoretical model was established, and a questionnaire survey was conducted among 152 professionals. The collected datas were analyzed by the structural equation modeling (SEM) method.
Findings
The study identified four critical factors that influence the government’s decision to trust the private sector in public-private-partnership (PPP) projects. All the four factors have a positively correlated impact on the government’s trust decision-making. The structural equation path analysis shows that the most important factor affecting the government’s trust decision-making is the trustee’s (private sector) trustworthy characteristics, and the path coefficient is 0.92. The path coefficients of risk perception and the trustor’s trust tendency are 0.83 and 0.74, respectively. The influence of the legal system environment on government trust decision-making is moderate, with a path coefficient of 0.68.
Originality/value
This paper contributes to the literature in two aspects. First, the factors influencing decision-making to government trust in the private sector in PPP projects have been identified. Second, a comprehensive view of the mechanism of government trust in the private sector in PPP projects has been theorized by the SEM method.
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Xiaobo Shi, Yaning Qiao, Xinyu Zhao, Yan Liu, Chenchen Liu, Ruopeng Huang and Yuanlong Cui
Modern subway transportation systems need to satisfy increasing safety demands to rapidly evacuate passengers under hazardous emergency circumstances, such as fires, accidents or…
Abstract
Purpose
Modern subway transportation systems need to satisfy increasing safety demands to rapidly evacuate passengers under hazardous emergency circumstances, such as fires, accidents or terrorist attacks, to reduce passenger injuries or life losses. The emergency evacuation capacity (EEC) of a subway station needs to be revised timely, in case passenger demand increases or the evacuation route changes in the future. However, traditional ways of estimating EEC, e.g. fire drills are time- and resource-consuming and are difficult to revise from time to time. The purpose of this study is to establish an intuitive modelling approach to increase the EEC of subway stations in a stepwised manner.
Design/methodology/approach
This study develops an approach to combine agent-based evacuation modelling and building information modelling (BIM) technology to estimate the total evacuation time of a subway station.
Findings
Evacuation time can be saved (33% in the studied case) from iterative improvements including stopping escalators running against the evacuation flow and modifying the geometry around escalator exits. Such iterative improvements rely on integrating agent-based modelling and BIM.
Originality/value
The agent-based model can provide a more realistic simulation of intelligent individual movements under emergency circumstances and provides precise feedback on locations of evacuation bottlenecks. This study also examined the effectiveness of two rounds of stepwise improvements in terms of operation or design to increase the EEC of the station.
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