The impact of influencers' multi-SNS use on followers’ behavioral intentions: An integration of cue consistency theory and social identity theory

The considerable marketing potential brought by the rapid growth of social media has been extensively examined in the literature, particularly in terms of the impact of influencers' recommendations on their followers' decisions. However, little attention has been given to how the individual influencers' use of multiple social networking sites affects their followers' behavioral intentions. Hence, this academic gap warrants further exploration. Drawing on cue consistency theory, social identity theory, and stimulus-organism-response framework, this research proposes three research questions and constructs an integrated research model to explore how the influencers' cue consistency affects the social identification of their followers, subsequently influencing their behavioral intentions. A structural equation modeling technique is performed to analyze the data of 510 valid respondents. The findings show that influencers' consistent cues (i.e., information and image consistency) across social media have positive impacts on followers' cognitive and affective identification toward the influencers. Furthermore, the determinants for followers' purchase intention and electronic word-of-mouth intention are affirmed to serve as both cognitive and affective identification. Especially, the results indicate that the relationships between followers’ social identifications and behavioral intentions are moderated by the type of influencer (i.e., lifestyle vs. review). Accordingly, the results indicate how the use of multiple social networking sites by influencers impacts the behavioral intentions of their followers. The findings offer new insights into influencer marketing and provide important lessons for marketers.     

Paired comparison models with age effects modeled as piecewise quadratic splines

We propose new models for analyzing pairwise comparison data, such as that relating to sports. We focus on changes in players’ strengths and the prediction of future results. Our models are based on the Thurstone-Mosteller and Bradley–Terry models, and make use of the time variation in the parameters. Furthermore, we apply our models to data from the Japanese traditional sport sumo, and analyze this data. The proposed models perform better than the standard Thurstone-Mosteller and Bradley–Terry models according to both the Akaike information criterion and the Brier score. We compare the proposed models in detail by focusing on individual sumo wrestlers.     

Jensen's alpha and the market‐timing puzzle

Theory predicts that market‐timing activities bias Jensen's alpha (JA). However, empirical studies have failed to find consistent evidence of this bias. We tackle this puzzle in a nested model analysis and show that the bias contains an exogenous market component that is unrelated to market‐timing skill. In a comprehensive empirical analysis of US mutual funds, we find that the timing‐induced bias in JA is mainly driven by this market component, which is uncorrelated with measured timing activities. Measures of total performance that allow for timing activities are virtually identical to JA, even if timing activities are present in the evaluated fund. Hence, we conclude that JA is a sufficient measure of total performance.     

Bayesian selection of technology assumptions for the transformation from supply-use to input–output tables

ABSTRACT

In the construction of input–output models from supply-use tables, technology assumptions disambiguate how an industry uses inputs in the production recipe of multiple outputs. This paper uses Bayes' theorem to select technology assumptions, taking into account empirical observations. The paper presents a formulation to explore hybrids between product and industry technology assumptions in product-by-product tables. We then present Markov chain Monte-Carlo techniques to implement the Bayesian method for selecting technology assumptions. We apply the method in a case study using Eurostat supply-use tables of 2004 and 2005, exhibiting a volume of secondary products of less than 13%, and 59 products and industries per country. The results show that the choice of technology is not important, given that there is no strong evidence in favour of any of them.     

险资股权投资的结构性改革研究*——基于险资投资的倒U型效应分析

保险资金作为重要的机构投资者能否发挥促进公司绩效提升的作用在已有研究和监管政策制定上都存在较大争议。本文以2005-2017年A股上市公司为研究样本，发现险资持股比例对上市公司绩效以及估值影响存在显著的倒U型曲线效应，相应机制研究表明险资持股通过显著影响两类代理成本的渠道发挥治理作用。在适度持股比例以下，险资增持能够降低被投资公司管理费用率和其他应收款占比，并提高资产周转率，从而降低两类代理成本；持股超过一定比例反而造成两类代理成本上升。险资持股比例变化对保险机构调研次数的影响则从公司治理参与角度印证了以上结论。对倒U型曲线效应的深入分析既有助于深化对机构投资者影响公司绩效的多重效应和机制的认识，同时为在金融机构层面落实金融供给侧结构性改革、增强险资服务实体经济能力提供参考。     

Correction to: Optimal and robust combination of forecasts via constrained optimization and shrinkage

We provide a correction to Proposition 1 in Optimal and robust combination of forecasts via constrained optimization and shrinkage, published in the International Journal of Forecasting 38(1):97-116 (2021). This correction has no impact on any other result (neither theoretical nor empirical) provided in the above paper.     

基于模糊多属性群决策的维护方式选择研究

维护方式选择是维护管理中的重要工作之一,合理的维护方式既能达到保障设备的稳定运行,又能同时兼顾其它各个方面的要求。由于对维护方式的评价涉及多个部门、人员和属性,有些指标只是一个模糊的概念,因而采用模糊多属性群决策的方法对维护方式进行优先抉择。本文结合A公司的设备维护方式选择问题,尝试使用模糊多属性群决策折衷算法求解最佳的维护方式。     

A model of tourism advertising effects

This study develops the AIEDA tourism advertising effects model and examines this model by tourism destination types and advertising formats in a field experiment. The AIEDA model extends the traditional AIDA model in the advertising field and additionally considers the unique features of tourism products. It includes five hierarchical stages: Attention→ Interest→Evaluation (Perceived Usefulness→ Perceived Credibility) → Desire →Action. Findings of experimental research indicate that destination type and advertising format have main effects and interaction effects on tourism advertising effects. In addition, this study discovered that, for natural and cultural destinations, video ads yielded similar or more positive advertising effects than virtual reality ads, whereas print was the least effective advertising format.     

Classification of intraday S&P500 returns with a Random Forest

Stock markets can be interpreted to a certain extent as prediction markets, since they can incorporate and represent the different opinions of investors who disagree on the implications of the available information on past and expected events and trade on their beliefs in order to achieve profits. Many forecast models have been developed for predicting the future state of stock markets, with the aim of using this knowledge in a trading strategy. This paper interprets the classification of the S&P500 open-to-close returns as a four-class problem. We compare four trading strategies based on a random forest classifier to a buy-and-hold strategy. The results show that predicting the classes with higher absolute returns, ‘strong positive’ and ‘strong negative’, contributed the most to the trading strategies on average. This finding can help shed light on the way in which using additional event outcomes for the classification beyond a simple upward or downward movement can potentially improve a trading strategy.     

Markups of Exporters and Importers: Evidence from Hungary

In this paper, we study the relationship between different proxies of firm‐level markups and trade status, using balance sheet information linked to detailed trade data from Hungary between 1995 and 2003. We find that importing is strongly positively correlated with markup measures, both across and within firms. We argue that this correlation can reflect three channels: self‐selection, higher physical productivity resulting from access to a larger variety of inputs, and quality upgrading based on high‐quality imported intermediate inputs. We present evidence for the relevance of the third channel by showing that importers’ markup premium is higher when inputs arrive from developed countries, and that importing is correlated with higher‐quality (price‐adjusted revenue) exports. We find no robust evidence for exporter premium when controlling for importing. We argue that the non‐existent exporter premium might result from the stronger competition in export markets relative to domestic markets.