The dark side of innovation: How new SKUs affect brand choice in the presence of consumer uncertainty and learning

New product activity is critical for sustained success of consumer packaged goods (CPG) brands. However, the impact of new SKUs on the perceived quality, quality uncertainty and subsequent choice of the brand as a whole is, as of yet, not well understood. The authors study how new additions to the brand line shape consumers’ quality perceptions, and how this – next to the mere line length effect – influences their choice of brands over time. They do so in the setting of an emerging market (China), where new product activity is particularly pervasive. Using a unique scanner panel dataset of Chinese households over the period 2011–2014, they estimate a Bayesian learning model that accommodates varying quality, on two CPG categories, and for two types of new-product additions (new sensory SKUs vs. new non-sensory SKUs). They show that while adding new SKUs may lift the brand’s perceived quality level, it also makes consumers more uncertain about the quality of the brand – dampening their brand choice. This holds especially for light customers – an important part of the brand clientele. Managerial implications are discussed.     

中国数字经济空间关联网络及其影响因素分析

基于2013年和2020年29个省的数据，用因子模型测算各省数字经济发展水平，在此基础上使用修正引力模型构建数字经济空间关联网络，并深入分析此网络特征。结果表明：中国数字经济发展水平存在差异，东部地区高于中西部地区；中国数字经济空间关联网络密度不断增大；北京、山东、江苏一直是网络的重要输出省份，近年来西部地区在网络中的作用越来越明显；地理位置相邻、贸易开放度和产业结构对网络的形成有显著影响。     

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.     

A note on the long rate in factor models of the term structure

In this paper, we consider factor models of the term structure based on a Brownian filtration. We show that the existence of a nondeterministic long rate in a factor model of the term structure implies, as a consequence of the Dybvig–Ingersoll–Ross theorem, that the model has an equivalent representation in which one of the state variables is nondecreasing. For two‐dimensional factor models, we prove moreover that if the long rate is nondeterministic, the yield curve flattens out, and the factor process is asymptotically nondeterministic, then the term structure is unbounded. Finally, we provide an explicit example of a three‐dimensional affine factor model with a nondeterministic yet finite long rate in which the volatility of the factor process does not vanish over time.     

闽侯县闲置农地生态安全评价研究

[目的]根据闽侯县农用地闲置情况,结合当地社会经济及生态环境发展情况,深入分析闽侯县闲置农地的生态安全发展水平。[方法]建立闽侯县闲置农地生态安全评价指标体系,分别从农村垃圾处理点数量、财政支农资金、外部进入农村投资、农业生产总值、种粮补贴、自然灾害、农业技术水平、农村生物的多样性程度、农村家庭收入结构、农村生态补偿金额、农地的整理规模及环保支出占GDP比重共确定12个指标进行深入研究,运用普通最小二乘法对设计的多元线性回归模型进行回归,进一步对闽侯县闲置农地的生态安全水平进行评价。[结果]农村垃圾处理点数量、财政支农资金、种粮补贴、环保支出占GDP比重、生态补偿金额、生物多样性程度对闽侯县闲置农地生态安全水平起到促进作用,呈正相关趋势;自然灾害则与闲置农地生态安全水平呈负相关趋势。[结论]整体看来,闽侯县闲置农地的生态安全水平主要受到当地经济、环境及生态基础三大因素的影响。     

新制度经济学视角下的中国农地制度变迁：回顾与展望

研究目的:分析总结中国农地制度变迁的路径特征、决定条件和影响因素,并展望进一步研究方向。研究方法:文献分析法。研究结果:(1)改革开放以来的中国农地制度变迁呈现出一个较清晰的路径,即改革始终沿着市场取向、明晰产权、稳定地权的方向演进;(2)农地使用权制度改革的成功源于诱致性变迁与强制性变迁的结合,即弹性的中央政策制定、渐进式的地方实施以及具有学习效应的农户认知三者的有机互动,并体现出制度变迁的"共生演化"特征及其蕴含的"适应性效率";(3)新制度经济学是解释中国经济改革和农地制度变迁的有效工具,然而由于经典的新制度经济学本质上的静态性以及国家理论的缺乏,难以对现实世界的各类制度变迁给出一般化的解释。研究结论:基于经典的新制度经济学,进一步整合行为经济学、机制设计理论、演化博弈论等理论工具,超越"强制性—诱致性变迁"二分法,构建一个真正动态的制度变迁模型是一个重要研究方向。     

Winning us with trifles: Adverse selection in the use of philanthropy as insurance

Research Summary: We study the use of corporate philanthropy as a form of reputation insurance, developing a formal model of such insurance to examine how the terms of insurance in equilibrium change under different assumptions about the firm and its stakeholders. We then test the predictions from this model in the U.S. petroleum industry and find that philanthropic donations offer insurance‐like benefits, but are also positively associated with subsequent oil spills—firms that give more, spill more—with this association being stronger for spills that are under firms’ control and in states with low civic capacity. These results are consistent with an adverse selection/moral hazard equilibrium and suggest that the use of philanthropy as reputation insurance may benefit firms at the cost of society. Managerial Summary: Firms that donate to social causes develop a reputation for being socially responsible, and are often given the benefit of doubt when negative information about them comes to light. But are philanthropic firms truly more responsible? We argue that firms that donate more may be more likely to do harm—those that expect to do harm later are likely to give more now, and those that know their reputation protects them may become less careful. Evidence from the U.S. petroleum industry is consistent with this argument, with firms that give more having more subsequent oil spills, but only the type of spills that are under the firm's control, and only in states where the firm faces weaker scrutiny.     

Online adaptive lasso estimation in vector autoregressive models for high dimensional wind power forecasting

Wind power forecasts with lead times of up to a few hours are essential to the optimal and economical operation of power systems and markets. Vector autoregression (VAR) is a framework that has been shown to be well suited to predicting for several wind farms simultaneously by considering the spatio-temporal dependencies in their time series. Lasso penalisation yields sparse models and can avoid overfitting the large numbers of coefficients in higher dimensional settings. However, estimation in VAR models usually does not account for changes in the spatio-temporal wind power dynamics that are related to factors such as seasons or wind farm setup changes, for example. This paper tackles this problem by proposing a time-adaptive lasso estimator and an efficient coordinate descent algorithm for updating the VAR model parameters recursively online. The approach shows good abilities to track changes in the multivariate time series dynamics on simulated data. Furthermore, in two case studies it shows clearly better predictive performances than the non-adaptive lasso VAR and univariate autoregression.     

The Non‐Observed Economy in Portugal: The monetary model and the MIMIC model

This paper offers estimations for the Portuguese path of the Non‐Observed Economy (NOE), in the period 1970–2015, through two seminal approaches: monetary method and the Multiple Indicators Multiple Causes (MIMIC) model. It is observed that the tax burden and social benefits are its main causes. Then, to get a more in‐depth understanding of the phenomenon, it provides a study of the Granger causality between the NOE and the official Gross Domestic Product (GDP), emphasizing the implications of the NOE on the Portuguese economy. Evidence has been found for the existence of bidirectional causality between the NOE and the GDP, suggesting that the formal economy affects the NOE, and conversely that the NOE affects the economic growth.     

From disruptively digital to proudly analog: A holistic typology of digital transformation strategies

Recently booming academic interest in digital transformation aims to provide continuous support to managers in dealing with this important issue. However, as with all new fields, the scholarly literature is characterized by increased variability and diversity of topics covered, constructs used, and the relationships between them, resulting in an unclear and blurry understanding of the whole of digital transformation. Our article closes this gap by identifying distinctive digital transformation strategies in terms of two critical dimensions: usage of digital technologies and readiness of a business model for digital operation. The result is a typology of four generic digital transformation strategies that essentially differ in the primary motivation and target of transformation, leadership style, importance of skills like creativity and entrepreneurial spirit among employees, risks and challenges faced in the process, consequences of potential failure, and available tactics for improvement. By providing heuristics and a systematic basis for comparison of different strategies, it is our belief that the proposed framework will be useful to researchers and managers responsible for and interested in digital transformation.