Too cute to be bad? Cute brand logo reduces consumer punishment following brand transgressions

Research on brand transgressions has suggested that when a brand is involved in a transgression and perceived as harmful, consumers will punish the brand. The present research seeks to extend this literature by investigating how having a cute brand logo may reduce consumer punishment of a transgressing brand. Across five experimental studies, this research shows that a brand logo with high (vs. low) levels of cuteness associated with a transgressing brand can motivate consumers to protect the brand from harm, thus reducing consumer punishment of that brand. Notably, such motivations to protect the brand are driven by an incremental belief about the brand’s development. Moreover, the cuteness effect is attenuated in the case of repeated transgressions. Theoretical contributions to the literature on cuteness, brand logo, and brand transgression are discussed, as well as practical implications.     

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.     

理性人的人情味：快手“老铁经济”的内在机制和逻辑

以中国用户规模最大短视频平台之一快手头部主播直播带货推广项目的案例和数据分析为基础,构建解释快手直播电商经济底层逻辑的社会学机制模型.提出快手直播电商经济背后的3种社会学机制:关键影响者逻辑、身份认同逻辑和社会网络逻辑.通过LDA文档主题生成模型将快手主播的直播语义字段进行文档主题生成归类,发现情感因素和理性因素词交互影响受众的购买决策,它背后的社会学作用机制是关键影响者逻辑和身份认同逻辑.2020年快手直播电商半年交易额已达1044亿元,理解快手直播背后的影响机制,能够持续优化推广模型,在互联网流量广告领域具有重要的应用价值.     

Forecasting the UK economy with a medium-scale Bayesian VAR

We estimate a Bayesian VAR (BVAR) for the UK economy and assess its performance in forecasting GDP growth and CPI inflation in real time relative to forecasts from COMPASS, the Bank of England’s DSGE model, and other benchmarks. We find that the BVAR outperformed COMPASS when forecasting both GDP and its expenditure components. In contrast, their performances when forecasting CPI were similar. We also find that the BVAR density forecasts outperformed those of COMPASS, despite under-predicting inflation at most forecast horizons. Both models over-predicted GDP growth at all forecast horizons, but the issue was less pronounced in the BVAR. The BVAR’s point and density forecast performances are also comparable to those of a Bank of England in-house statistical suite for both GDP and CPI inflation, as well as to the official Inflation Report projections. Our results are broadly consistent with the findings of similar studies for other advanced economies.     

Multilayer financial networks and systemic importance: Evidence from China

In this paper, we develop a multilayer network structure and reveal the relationship between network structure and systemic risk. Unlike many previous studies, our model considers both liability and cross-holding of shares between financial institutions simultaneously. We propose a new systemic risk measurement by exploring the dynamic mechanism of financial contagion in the multilayer network. We display the network structure of Chinese financial institutions, including connectivity and diversity, and identify the systemic importance of them. We demonstrate that the multilayer network plays a non-linear role in financial risk spreading. Using the panel regression model and several experiment evidences, we show that the systemic risk can be explained more effectively by the linkage diversity more than the connectivity at both the institutional level and the system level. Our results highlight the importance of considering contagion mechanisms that go beyond a simple single-layer network structure.     

Application of collective knowledge diffusion in a social network environment

ABSTRACT

We present a group dynamics model that shows knowledge integration as a process occurring over time. As each individual in the group contact others, his own knowledge changes, and over time the collective knowledge is obtained. This allows modeling knowledge diffusion in a social network and while the models presented in this paper are not competitive in that area, they approach the problem from previously unconsidered direction. We test the behavior of the model in a multi-agent simulation and we test a simple advertisement campaign in a social network. We provide discussion of elements needed for making model more competitive.     

Market microstructure in a global B2B network

On‐line marketplaces raise several interesting issues, among them the relevance of location when content is digitized, and the assessment of a supplier's capabilities when buyers worldwide only have electronic contact with sellers. In global B2B on‐line marketplaces, market microstructures, i.e. which firms compete for the same customers, are thus likely to be influenced by how customers value location and firm capabilities in their decisions to do business with different suppliers on‐line. We suggest that both these sets of attributes will continue to matter on‐line—firms possessing similar capabilities, as well as firms that are similar in location by country, time zones or clusters, will compete for business from the same customers. We model the similarity in competitive positions between pairs of firms based on the overlap in their customer networks, using data on actual interactions between supplier and customer banks on an electronic trading system. Using QAP network regression techniques on the 100 largest banks in this industry, we find that similarity in capabilities influences who competes with whom, and that location still matters in a global B2B exchange. Interestingly, location influences who a firm's competitors are, but not where its customers are from. Copyright © 2001 John Wiley & Sons, Ltd.