政府动态奖惩机制下绿色建筑供给侧演化博弈研究

从绿色建筑供给侧角度出发，构建消费者效用函数、开发商利润函数和政府与开发商的演化博弈模型，分析消费者绿色偏好、建筑绿色度、成本等因素对建筑价格、需求和利润的影响以及政府动态奖惩政策下系统的演化稳定策略。结果表明：消费者绿色偏好支付系数和建筑绿色度的增大有利于绿色建筑价格、需求和利润的提高，但高成本却使需求和利润降低；政府采用静态补贴与静态税收政策时，博弈系统不存在演化稳定策略，采用动态补贴与静态税收、静态补贴与动态税收、动态补贴与动态税收三种政策组合时，系统存在演化稳定策略；动态补贴与静态税收的政策组合在推动绿色建筑发展方面优于其他政策；开发商开发绿色建筑的概率与补贴上限值呈负相关，与税收上限值呈正相关。     

平台与互补商协同创新的制度逻辑及其作用机制

平台与互补商的协同专业化对于创新生态系统的构建具有重要作用.然而,平台企业与互补商可能各自具有冲突的或互补的制度逻辑,它们彼此要实现协同创新的目标,就必然在达成协作共识的过程中形成主导型制度逻辑,进而规范双方的创新活动与行为.但是,这种主导型制度逻辑如何产生?它们的作用机制是什么?过去的研究还很少涉及这类问题.本文通过OPPO的案例研究,结果表明:(1)平台与一般互补商合作时,平台的谈判能力相对较强,平台的制度逻辑占据主导地位;(2)平台对瓶颈互补商具有较强的依赖时,互补商拥有较强的谈判能力,平台在两者的合作中会选择妥协,此时互补商的制度逻辑占主导地位;(3)平台与瓶颈互补商的关系是双向依赖时,两方合作形成的制度逻辑是混合逻辑;(4)面对强大的外部制度压力时,平台与互补商的合作会形成或遵循新的制度逻辑.     

CIO自身技能、需求方领导力与数字化创新

现有研究强调数字化创新对企业的战略价值,但学术界对企业如何进行数字化创新的认识却较为有限.借鉴变革型领导理论,本文提出CIO需求方领导力正向影响企业数字化创新水平,同时,CIO结构权力可以增强CIO需求方领导力与企业数字化创新水平的正向关系.此外,从CIO自身技能方面识别出CIO需求方领导力的三个重要前因:战略IT知识、政治悟性以及网络能力.通过采集179份CIO-TMT的企业配对问卷数据进行实证分析,实证结果较好地支持了研究假设.本文提出的假设模型为企业发挥CIO在推进数字化创新中的主导作用提供了理论基础和实践启示.     

Human Error in Autonomous Underwater Vehicle Deployment: A System Dynamics Approach

The use of autonomous underwater vehicles (AUVs) for various applications have grown with maturing technology and improved accessibility. The deployment of AUVs for under-ice marine science research in the Antarctic is one such example. However, a higher risk of AUV loss is present during such endeavors due to the extremities in the Antarctic. A thorough analysis of risks is therefore crucial for formulating effective risk control policies and achieving a lower risk of loss. Existing risk analysis approaches focused predominantly on the technical aspects, as well as identifying static cause and effect relationships in the chain of events leading to AUV loss. Comparatively, the complex interrelationships between risk variables and other aspects of risk such as human errors have received much lesser attention. In this article, a systems-based risk analysis framework facilitated by system dynamics methodology is proposed to overcome existing shortfalls. To demonstrate usefulness of the framework, it is applied on an actual AUV program to examine the occurrence of human error during Antarctic deployment. Simulation of the resultant risk model showed an overall decline in human error incident rate with the increase in experience of the AUV team. Scenario analysis based on the example provided policy recommendations in areas of training, practice runs, recruitment policy, and setting of risk tolerance level. The proposed risk analysis framework is pragmatically useful for risk analysis of future AUV programs to ensure the sustainability of operations, facilitating both better control and monitoring of risk.     

Human Factors Analysis for Maritime Accidents Based on a Dynamic Fuzzy Bayesian Network

Human factors are widely regarded to be highly contributing factors to maritime accident prevention system failures. The conventional methods for human factor assessment, especially quantitative techniques, such as fault trees and bow-ties, are static and cannot deal with models with uncertainty, which limits their application to human factors risk analysis. To alleviate these drawbacks, in the present study, a new human factor analysis framework called multidimensional analysis model of accident causes (MAMAC) is introduced. MAMAC combines the human factors analysis and classification system and business process management. In addition, intuitionistic fuzzy set theory and Bayesian Network are integrated into MAMAC to form a comprehensive dynamic human factors analysis model characterized by flexibility and uncertainty handling. The proposed model is tested on maritime accident scenarios from a sand carrier accident database in China to investigate the human factors involved, and the top 10 most highly contributing primary events associated with the human factors leading to sand carrier accidents are identified. According to the results of this study, direct human factors, classified as unsafe acts, are not a focus for maritime investigators and scholars. Meanwhile, unsafe preconditions and unsafe supervision are listed as the top two considerations for human factors analysis, especially for supervision failures of shipping companies and ship owners. Moreover, potential safety countermeasures for the most highly contributing human factors are proposed in this article. Finally, an application of the proposed model verifies its advantages in calculating the failure probability of accidents induced by human factors.     

A New Methodology for Before–After Safety Assessment Using Survival Analysis and Longitudinal Data

The widely used empirical Bayes (EB) and full Bayes (FB) methods for before–after safety assessment are sometimes limited because of the extensive data needs from additional reference sites. To address this issue, this study proposes a novel before–after safety evaluation methodology based on survival analysis and longitudinal data as an alternative to the EB/FB method. A Bayesian survival analysis (SARE) model with a random effect term to address the unobserved heterogeneity across sites is developed. The proposed survival analysis method is validated through a simulation study before its application. Subsequently, the SARE model is developed in a case study to evaluate the safety effectiveness of a recent red‐light‐running photo enforcement program in New Jersey. As demonstrated in the simulation and the case study, the survival analysis can provide valid estimates using only data from treated sites, and thus its results will not be affected by the selection of defective or insufficient reference sites. In addition, the proposed approach can take into account the censored data generated due to the transition from the before period to the after period, which has not been previously explored in the literature. Using individual crashes as units of analysis, survival analysis can incorporate longitudinal covariates such as the traffic volume and weather variation, and thus can explicitly account for the potential temporal heterogeneity.     

基于个性化需求的产品竞争供应链结构选择

基于"制销分离"与"定制一体"两种结构选择，构建个性化产品供应链处于非竞争与竞争环境下的博弈模型，在引入一个实际案例的基础上，运用算例仿真比较分析两种运营模式下的供应链运作策略和盈利差异。结果显示：与制销分离结构相比，个性化产品供应链选择定制一体结构，有利于匹配产品个性化制造、提升产品个性化水平和市场需求、增加供应链的期望收益；个性化产品供应链选择制销分离结构时，适度的批发价格激励能够提升产品个性化水平、更好满足消费者个性化需求、改善供应链的运营绩效，分销商适度让利加大批发价格激励力度可显著促进产品个性化制造互动、提升产品个性化水平；竞争将消减个性化产品供应链的运营绩效，但选择定制一体结构可显著提升竞争力。     

自我建构对消费者促销方式偏好的影响

  形式多样的促销手段成为企业在激烈市场竞争中赢得胜利的重要方式。已有研究涉及的促销方式直接受益实体都是消费者自身，随着消费者社会责任意识的提高，直接受益实体为慈善机构的捐赠促销活动不断出现，然而很少有学者对不同受益实体的促销方式的效果进行比较。         基于信息框架理论和调节定向理论，以打折促销和捐赠促销为研究对象，运用分类变量中介检验和3阶交互效应方法，通过Spss软件中的Process插件进行Bootstrap中介效应分析，解释调节定向在不同自我建构消费者对两种促销方式偏好关系中的中介作用机制，并引入感知风险和感知稀缺两个变量，探究其在自我建构对消费者促销方式偏好影响中的调节作用。         研究结果表明，调节定向在自我建构与促销方式选择的关系中起中介作用，即拥有独立自我建构的消费者认为促进定向信息说服力更强，从而偏好打折促销方式；拥有依存自我建构的消费者认为防御定向信息说服力更强，从而偏好捐赠促销方式。当感知风险较高时，防御定向信息强化依存自我建构的消费者对捐赠促销方式的偏好；当感知风险较低时，促进定向信息强化独立自我建构的消费者对打折促销方式的偏好。当感知稀缺较高时，防御定向信息强化独立自我建构的消费者对打折促销方式的偏好；当感知稀缺较低时，促进定向信息强化依存自我建构的消费者对捐赠促销方式的偏好。         在理论上拓展了信息框架效应的相关研究，揭示了自我建构与调节定向作用关系的适用边界。通过检验不同自我建构消费者对调节定向相匹配的促销信息评价机制，证明促销活动中的匹配机制可使促销效果更佳。在实践上，为企业在不同消费情景下面对不同特点消费者制定相应的促销活动提供了策略指导，从而提升企业的销售利润。     

‘It is not fair that you do not know we have problems’: Perceptual distance and the consequences of male leaders' conflict avoidance behaviours

This study investigates perceptual distance in terms of managers' conflict avoidance behaviour and its consequences for subordinates. We argue that perceptual distance, or the disagreement between a manager's perception and that of his or her subordinates of his or her conflict avoidance, is a genuine phenomenon. We examine the extent to which the perceptual distance regarding managers' avoidance behaviour influences a team's justice climate as well as the role of gender. The data collected from three multinational companies in China show that the perceptual distance of a male manager's avoidance behaviour exists and that it is associated with a negative justice climate within the team. These findings provide evidence of gender's effect on leadership and highlight the benefits of female leadership.     

Quality Provision with Heterogeneous Consumer Reservation Utilities

This study examines a firm's quality and price decisions when consumers differ not only in their willingness‐to‐pay for quality but also in their reservation utility for the basic product. We find that while the firm offers lower‐quality products when consumers' valuations for quality deteriorate, the optimal quality may increase with a negative shift in consumers' reservation utilities. We also investigate the optimal price and quality of the products within a vertically differentiated product line when the number of products is exogenously given. The existing literature shows that when consumers differ only in their willingness‐to‐pay for quality, the firm sets the efficient quality for consumers with the highest valuation for quality, whereas the concern for cannibalization pushes down the quality of inferior products. We find that when consumers are heterogeneous in both their reservation utility and valuation for quality, the concern for cannibalization may distort the quality upwards, even for consumers with the highest willingness‐to‐pay for quality. In addition, a low‐quality product may enjoy a higher profit margin than a high‐quality product within the product line.