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.     

Mobile Commerce Website Success: Antecedents of Consumer Satisfaction and Purchase Intention

With the rapid development of apparel mobile commerce in the United States, more companies view mobile commerce as a new source of competitive advantage. Despite the importance of apparel mobile website quality and its effect on consumer satisfaction and future purchase stimulus, extant research has paid little attention to these topics. This study proposes a website quality–consumer satisfaction–purchase intention research model based on the self-regulatory process theory. Six dimensions of apparel mobile website quality—website visual appeal, apparel visual appeal, brand trust, website information quality, website response time, and website security—were investigated. In all, 293 eligible responses were collected via an online survey. Multiple regression analysis was utilized to test the proposed relationships. Results reveal that website information quality, website visual appeal, apparel visual appeal, and website security positively affect consumer satisfaction toward apparel mobile commerce websites, while website response time and brand trust show insignificant impacts on consumer satisfaction. With higher satisfaction on an apparel mobile commerce website, consumers are more likely to purchase apparel through the website.     

Online marketing: When to offer a refund for advanced sales

Advance selling is a marketing strategy commonly used by online retailers to increase sales by exploiting consumer valuation uncertainty. Recently, some online retailers have started to allow refunds on products sold in advance. On the one hand this reduces the net advance sales, but on the other hand it allows a higher advance sales price. This research is the first to explore the overall effect of allowing a refund on profits from advance sales, identifying conditions where advance selling with or without refunds (or no advance selling at all) is best. We analytically compare the profits of three advance selling strategies: none, without refund, and with refund. We show that selling in advance and allowing a refund is optimal for products with a relatively small profit margin and small strategic market size, and that the added profit can be considerable. Our results guide managers in selecting the right advance selling strategy. To facilitate this, we graphically display, based on the two dimensions of regular profit margin and strategic market size, under what conditions the different strategies are optimal.     

The effect of activity identity fusion on negative consumer behavior

Negative consumer behavior is an important research topic as it explores consumer behaviors that threaten a brand's image and financial stability. However, prior research offers conflicting findings on whether a strong consumer‐brand relationship hurts or protects a brand after a market disruption or a brand transgression. To provide clarity on this issue, this work argues that disrupting the consumer‐activity relationship motivates consumers to reaffirm and protect their identity, thereby leading to negative consumer behavior. The data reveal that, after a brand‐initiated market disruption, consumers with high activity identity fusion are more likely to spread negative word‐of‐mouth, boycott the brand, and avoid repurchasing the brand in the future. Moreover, the data suggest that high brand identity fusion protects the brand during market disruptions; therefore, prior conflicting results may be due to the fact that the consumer‐activity relationship was not accounted for. Theoretically, this work establishes that consumers' relationship with their consumption activities has significant impacts on consumer behavior. Brand managers and marketers are urged to develop strategies that focus on strengthening the consumer‐brand relationship and not the consumer‐activity relationship.     

Neither an Authentic Product nor a Counterfeit: The Growing Popularity of Shanzhai Products in Global Markets

Counterfeits have been a longstanding concern to global brand manufactures. However, recently, a new product category that partly imitates and partly innovates under the term shanzhai has entered into market. Shanzhai products mimic original leading brands through visual or functional similarities and may also provide additional features. Given this new copycat phenomenon, our study for the first time conceptually distinguishes shanzhai products from counterfeits, theoretically compares the values of consumers choosing shanzhai products versus counterfeits, and empirically tests such differences in one integrative model. Specifically, shanzhai buyers value product functional benefits more than counterfeit buyers, while counterfeit buyers value status consumption, yet experience less self‐clarity than shanzhai buyers. Our findings offer important implications for imitative innovation literature as well as for practitioners.     

Going Through Hell: Increased Work Effort in the Aftermath of Terrorism in Norway*

I analyze how sickness‐absence behavior in Norwegian municipalities was affected by exposure to the terrorist attack in Norway in 2011. The main finding is that in municipalities from which a resident was killed in the attack, sickness absence declined by 4 percent compared with municipalities without victims. The effect is precise, stable, and persistent. The results do not seem to be driven by changing labor market composition. The effect is found also in neighboring municipalities and is larger for people close to the age of the victims.     

Sustainable product innovation and changing consumer behavior: Sustainability affordances as triggers of adoption and usage

This conceptual paper argues that for sustainable product innovation to make a contribution to addressing sustainability issues, we need to understand not only why consumers adopt sustainable products but also what makes them use these in sustainable way. To explain how specific product features can change the ways in which consumers engage with sustainable products in the adoption and usage phase, we draw on affordance theory. Affordances refer to the potential for agentic action of users in relation to a technological object. We develop a conceptual framework that explains how sustainable product innovation can lead to the design of sustainability affordances that stimulate adoption and sustainable usage. The framework shows how three forms of agency—material, firm, and user agency—interact and together influence a product's sustainability affordances that drive adoption and a change in consumer behavior. The framework explains how trade-offs between a product's environmental features and consumer expectations regarding desired functionalities and user experience can be overcome.     

Is bank staff interaction associated with customer saving behavior in banks?

Major changes are underway in the U.S. retail banking sector toward heavy investments in technology and fewer in personnel. Using the 2017 survey of household economics and decision‐making (SHED) (n = 11,359), we examine the relationship between saving behavior related to emergency, long‐term and periodic expenses and personal, technological, and hybrid bank account access methods. Binary logistic regression models were used to estimate the odds of reporting various saving behaviors in relation to various banking access methods. Findings suggest that the personal access method is positively associated with savings behavior for periodic expenses for the general population, and negatively associated with emergency savings in people with lower education attainment. Technology is associated with all types of saving behavior, while the hybrid access method is associated only with saving for periodic expenses. As investments in self‐service technology increase, the importance of access methods to savings behavior must be considered.     

品牌社交媒体广告内容对消费者社交媒体参与度的影响

基于参与度理论与社交媒体特点定义消费者社交媒体参与度与它的四个维度：意识、产生情感、产生理性思考、认同。建立社交媒体广告内容分类标准，收集二手数据后使用方差模型分析品牌社交媒体广告内容对消费者社交媒体参与度的影响。结果显示社交媒体广告内容类型显著影响消费者社交媒体参与度，新产品内容效果最好，其次是促销、游戏/抽奖、社会责任内容。此研究结果不仅可丰富消费者行为视角的品牌社交媒体广告相关理论研究，也可为品牌设计社交媒体广告内容营销提供管理建议。