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.     

Contracting and Reporting Conservatism around a Change in Fiduciary Duties*

We exploit an influential 1991 Delaware court ruling to examine simultaneously two types of conservatism that play important roles in resolving creditor–owner agency conflicts: contracting conservatism and reporting conservatism. The ruling expanded managerial fiduciary duties in favor of creditors for Delaware-incorporated firms in the vicinity of insolvency. In those firms, following the ruling, debt contracts are less likely to include conservative adjustments to accounting numbers used for covenant compliance (i.e., contracting conservatism decreases), while public financial reporting becomes more conservative (i.e., reporting conservatism increases). The decrease in contracting conservatism is concentrated in firms that exhibit a greater increase in reporting conservatism, suggesting that reporting conservatism is more cost-effective in resolving agency conflicts. In addition, the substitution effect is more pronounced in firms facing greater business uncertainty and firms with greater board independence.     

Is the system reliability profitable for retailing and consumer service of a dynamical system under cross-price elasticity of demand?

Retailing strategy is one of the most crucial factors for industries. A proper retailing strategy can help to enhance consumer service and increase the industry's profit. An improved approach to retailing is suggested in this research to deliver superior customer service while maximizing profits in a dynamic system. The study analyzes a retailing strategy for a demand with cross-price elasticity upon the retail price. A product's cross-price elasticity and the system reliability are critical factors in retailing. Understanding the cross-price elasticity of demand between products helps retailers to make pricing decisions that maximize profits by maintaining demand. Imperfect products are produced due to an imperfect production system. The imperfect ones must be adjusted with some costs to make them perfect for better retailing. The system failure rate is crucial for retailing under cross-price elasticity of demand patterns. Production system reliability, cross-price elasticity of demand, and consumer service are all essential factors that can impact a company's success in the market. The production rate is considered time- and system failure rate-dependent. Contradictory to the literature, a dynamical system is proposed for improved retail management, which is solved using the Euler-Lagrange theory. Finally, one can achieve the expected maximum profit for this retail system with optimum selling prices for different products by reducing the system failure rate. Some numerical illustrations with graphical representations are provided to validate the current study. Numerical examples show that applying cross-price elasticity of demand for more than two identical products provides 35% more profit for the retail industry than a single type of product.     

Deep learning for modeling the collection rate for third-party buyers

This study evaluates a wide range of machine learning techniques such as deep learning, boosting, and support vector regression to predict the collection rate of more than 65,000 defaulted consumer credits from the telecommunications sector that were bought by a German third-party company. Weighted performance measures were defined based on the value of exposure at default for comparing collection rate models. The approach proposed in this paper is useful for a third-party company in managing the risk of a portfolio of defaulted credit that it purchases. The main finding is that one of the machine learning models we investigate, the deep learning model, performs significantly better out-of-sample than all other methods that can be used by an acquirer of defaulted credits based on weighted-performance measures. By using unweighted performance measures, deep learning and boosting perform similarly. Moreover, we find that using a training set with a larger proportion of the dataset does not improve prediction accuracy significantly when deep learning is used. The general conclusion is that deep learning is a potentially performance-enhancing tool for credit risk management.     

“Going natural”: Black women’s identity project shifts in hair care practices

Hair care, a seemingly mundane consumption practice, is packed with sociocultural meanings and constitutes an important realm of identity work for consumers. Drawing upon existing literature on consumer identity projects, this paper investigates the experiences of urban, Black women in Kenya as they disengage from the normative practice of altering their natural hair texture using chemical straighteners (a practice that conforms to Eurocentric beauty ideals of straight, flowing hair), and adopt the non-normative hair care practice of “going natural,” in which they embrace their natural hair texture and hairstyles. This paper traces the historical, sociocultural, and political events that underpin the normative ideology associated with the identity marker of natural Black hair, and how this ideology influences the women’s “going natural” experience. Findings reveal tensions that emerge in the women’s identity project disengagement and reconstruction process, and how the women navigate their position as they reimagine their embodied identity quest.     

Some Potential Linkages for Input-Output Analysis with Flow-of-Funds

Three major, interrelated accounting statements, at the frontiers of quantitative economic analysis, are three interrelated systems, namely: (1) National income and product accounts (NIPA), (2) The input-output tableaux, (IO), and (3) flow-of- funds accounts (FF). The third-mentioned system is somewhat less available and used in only limited areas of macroeconomic analysis. This paper is mainly concerned with use of FF accounting systems. This system shows where financial resources originate, and where they go in support of real capital formation. In this respect, interest rates and other market-based financial rates are of key importance. While much macroeconomic analysis is based on the rates that fit the yield curve, showing the interest rate structure over various maturities of debt associated with a given degree of risk. In contrast, the FF accounts throw light on the whole spectrum of interest rates, across maturities and debt qualities. For example, in analysis of the real estate market and funding of capital formation there, it is important to have a full understanding of the course of mortgage rates of different maturities and qualities. In short, it is necessary to develop a full appreciation of supply and demand forces in the mortgage market, which often is not obviously related to movements of the operative rate for monetary policy, such as very short-term inter bank rates or call money rates. This paper attempts to provide material from the flow-of-funds accounts that would make it possible to analyze the movement of relevant mortgage rates or whatever other rates are needed to understand the financing of capital formation in real estate.     

我国国债的风险评估与防范

从国债的可持续性、国债的货币扩张效应、国债对经济增长的影响三个层面评估了我国当前的国债风险，并针对我国的国债特点，提出了防范国债风险的措施。     

国债规模的均衡数量及优化

笔者基于世代交叠模型,假定政府执行赤字预算体制,在市场结清的均衡状态下得到了确定国债规模与私人资本规模之比值的解析式。通过模拟发现税率、基本财政支出率、产出关于私人资本的弹性等是决定该比值大小的主要因素。     

Factors affecting households’ seafood purchasing decisions in Auckland,New Zealand: an empirical analysis

This paper uses the binary choice model to identify the factors that are significantly influencing the household purchase decisions of seafood products for home consumption in Auckland, New Zealand. It is found that ‘quality’ and ‘cooking easiness’ are the main product attributes that significantly influence households’ choices of seafood in Auckland. Also, the representative household has shown a strong preference for fresh and other alternative seafood products, including processed, smoked and canned, over frozen products. Retail outlets are found to be more attractive to the household purchasing seafood for home consumption. The New Zealand seafood industry may find this baseline study useful as a guide to developing future research structure on the domestic market.     

满意度测评结果分类分析

满意指数已经成为许多国家衡量经济产出质量的重要指标，为宏观经济管理提供了有效的决策参考依据，但是，如何进一步开发利用满意指数调查信息，加大对微观层面的经济组织经营管理活动的指导作用，仍然是满意度研究的重要课题。本文利用真实的用户满意指数测评调查数据，对营销管理中用户类型划分问题进行了分析，结果表明，用户满意指数测评调查数据，可以准确地将用户划分为逃离型、趋利型、受制型和忠诚型。