A decision support model for buying battery electric vehicles considering consumer learning and psychological behavior

Developments in battery electric vehicles (BEVs) have received more and more attentions in the last decades due to alleviating carbon emissions and energy crisis. Consequently, how to rank alternative BEVs to assist consumers make better purchasing decisions is a worthy research study. However, there are still some defects in the existing studies for ranking of BEVs: 1) the evaluation index system of BEVs is not comprehensive; 2) the determination of criteria weights cannot be well applied to the actual purchase scenarios; and 3) the psychological behavior of consumers is ignored. To address those shortcomings, this paper proposes a decision support model to assist with consumers to buy BEVs. First, a systematic evaluation criteria system of BEVs including quantitative and qualitative indicators from parameter configurations and online reviews is constructed. Then, a weight algorithm considering consumer learning is proposed to determine the criteria weights. Furthermore, a decision support process considering consumers' regret avoidance behavior is proposed. Finally, an actual BEV purchase case is given to illustrate the practicability of the decision support model. This can be seen in case studies the proposed support model can be well applied to consumers with different regret avoidance behaviours.     

Systemic risk network of Chinese financial institutions

The Chinese stock market crash in June 2015 has demonstrated necessary to improve understanding of systemic risk from the perspective of financial network. This study constructs a tail risk network to present overall systemic risk of Chinese financial institutions, given the macroeconomic and market externalities. Employing the Least Absolute Shrinkage and Selection Operator (LASSO) method of high-dimensional models, our results show that firm's idiosyncratic risk can be affected by its connectedness with other institutions. The risk spillover effect from other companies is the main driving factor of firm-specific risk, comparing with macroeconomic state, firm characteristics and historical price movement. The number of connections between institutions significantly increases during June 2014 to June 2016. Moreover, we utilize the Kolmogorov-Smirnov statistic to test significance of systemic risk beta based on tail risk and further rank the systemic risk contribution. Finally, we test the determinants of systemic risk contribution in a forward-looking way. Regulators could detect those firms that are most threatening to the stability of system.     

Does justice affect brand advocacy? Online brand advocacy behaviors as a response to hotel customers’ justice perceptions

This study focuses on customers' information-sharing behavior in the context of online brand advocacy behavior regarding hotel brands. We aim to explain hotel customers' online brand advocacy behavior through three-sided justice evaluations (i.e., justice for employees, justice for the self, and global belief in a just world), and their hotel satisfaction. Hypotheses are tested by using survey data acquired from 688 individuals on Amazon's Mechanical Turk (MTurk) through partial least squares structural equation modeling (PLS-SEM). The findings show that customers' perceptions of justice for the self positively affect their hotel satisfaction, perceptions of justice for employees and the global belief in a just world positively affect online brand advocacy behavior, and hotel satisfaction also positively affects online brand advocacy behavior. We expand current research efforts on online brand advocacy research and provide theoretical and managerial implications for the development of marketing and management research and practice.     

发明人角色识别及二元创新能力差异分析——社会资本视角的解释

发明人的创新活动嵌入在合作创新网络中。基于社会资本视角，从结构资本和认知资本两个维度辨识并定义4类发明人角色，包括“明星”、“纽带”、“平庸”和“活跃”发明人。以人工智能领域在德温特专利数据库（DII）授权的专利数据为样本，运用负二项模型，对4类发明人的二元创新能力进行实证对比分析。结果表明，不同角色发明人的二元创新能力显著不同。其中，“明星”发明人的二元创新能力最高，“平庸”发明人的二元创新能力最低，“活跃”发明人的二元创新能力高于“纽带”发明人，即认知资本对二元创新的影响大于结构资本。结论对提升发明人二元创新能力具有重要参考价值。     

基于碳排放的闭环供应链政府奖惩机制研究

温室气体的排放问题已成为国际社会亟待解决的问题，解决这一问题的必由之路就是通过降低产品碳排量实现从源头上减排。本文研究由一个制造商和一个零售商组成的逆向供应链系统，建立了政府实施回收奖惩机制的动态博弈模型，比较分析了有无政府回收奖惩机制两种情形下零售商的回收比例、供应链参与方的期望利润和产品的碳排放总量。研究结果表明，政府回收奖惩机制提高了回收比例和碳减排水平；当再制造减排程度较小时，政府回收奖惩机制降低了碳排放总量；基于消费者低碳偏好的政府回收奖惩机制提高了制造商和零售商的利润，更大程度的降低了产品总碳排放量；政府回收奖惩机制下较小的目标回收率能够最大化零售商利润。     

平台企业主导的创新生态系统稳定性研究：基于企业间网络关系视角

平台企业主导的创新生态系统作为一种特殊类型生态系统，是由平台主导企业提供基本创新架构并与其它相关企业及关联机构组成的网络组织，企业间网络关系是创新生态系统的本质特征。基于企业间网络关系分析平台企业主导的创新生态系统网络的成员、联系、结构及功能特征,讨论网络结构变量对平台企业主导的创新生态系统稳定性的影响，以山东省30个平台企业主导的创新生态系统为调研样本，通过问卷调查方式，对所提出的假设进行检验。数据相关分析和回归分析结果表明：强有力的创新生态系统主导企业、系统内伙伴企业密度、企业本地化以及企业异质性4个因素对创新生态系统稳定性具有显著正向影响；系统内伙伴企业互惠性和居间性与创新生态系统稳定性之间关系不显著。最后，基于研究结论，提出保持平台企业主导的创新生态系统网络稳定性的政策建议。     

排他性与非排他性策略下创新授权契约机制研究

分析了不完全信息下,拥有提高产品质量技术的创新企业,在(非)排他性授权策略下,向进行Cournot竞争生产低质量产品的生产企业技术授权的契约优化问题。研究表明,在排他性授权策略下,双重收费契约下信息不完全能使接受授权生产企业赢取更多的创新企业特许权补贴;在非排他性授权策略下,不完全信息能够削弱创新企业通过双重收费契约设计对产品间接市场的垄断程度。在排他性授权交易下,信息不完全使特许权收费契约优于固定收费契约成为可能,这不同于Li and Wang的研究结论。基于提高社会创新能力视角,政府应鼓励创新企业更多采用特许权收费授权契约,削弱信息不对称的影响,赢取更多研发投资利润回报。     

谈我国中央与地方政府间税权配置的进一步改进

本文从介绍政府间税权配置的基本原则及中央与地方政府间税权配置的基本模式出发,认为目前我国中央与地方政府间在税权配置上仍存在着许多问题。为了更好地实现政府间“事权与财权”的相对统一,有必要对我国中央与地方政府间的税权配置做进一步的改进。     

对地方政府吸引台商投资政策的新探讨——从企业集群角度分析

吸引外商投资作为解决资金瓶颈的一种有效手段,正被各地政府视作一项重要任务。作为现代企业进行投资生产最重要的特征就是企业集群,但在实际工作中,以政府主导的吸引外资行为却很少受到企业集群理论的指导,因而产生招不到“商”或即使招到“商”也留不住的现象。对于台资企业,这一现象尤为明显。根据企业集群根植性的理论对台资企业群现存问题进行深入分析,对地方政府吸引台商投资的行为提出积极的政策建议。