Attributions and behavioral intentions of inexperienced salespersons to failure: An empirical investigation

The goal of this research was to determine how inexperienced sales representatives (rookies) interpret and respond to their sales failure situations. The authors studied 296 rookie financial services sales representatives'performance attributions for a previous unsuccessful sales interaction and their intended behaviors for a future, similar selling situation. This provided the authors the opportunity to compare their results with Dixon, Spiro and Jamil's (2001) findings for experienced sales representatives (veterans). In the event of a sales failure, rookies'responses do not parallel those of veterans. The results suggest that rookies are likely to engage in several inappropriate behaviors in response to failed sales encounters. Implications for managers and directions for future research are discussed. Andrea L. Dixon (Andrea. Dixon@uc.edu) (Ph.D., Indiana University) is an assistant professor of marketing at the University of Cincinnati. Her research focuses on selling behaviors, team selling, integrating technology and personal selling, and the role of developmental relationships in enhancing creativity and productivity in the sales division. The primary focus of her research is improving the performance of sales representatives and the sales organization or unit. She has published in theJournal of the Academy of Marketing Science, theJournal of Marketing, and theJournal of Personal Selling and Sales Management. She currently serves on the editorial review boards of theJournal of the Academy of Marketing Science and theJournal of Personal Selling and Sales Management. Dixon is the vice chair for conference programming of the Selling and Sales Management Special Interest Group of the American Marketing Association. Rosann L. Spiro (spiro@ indiana.edu), Ph. D., is a professor of marketing and chairperson of the Marketing Department at Indiana University in Bloomington, Indiana, where she teaches Sales Management, Personal Selling, International Marketing, Business-to-Business Marketing Strategy, and Managerial Research in Marketing. Her research interests focus on sales strategy, sales management, and personal selling. Her work has appeared in numerous publications, including theJournal of Marketing Research, theJournal of Marketing, theJournal of Consumer Research, theJournal of Business, and theJournal of Personal Selling and Sales Management. She currently serves on the editorial review boards of theJournal of Personal Selling and Sales Management andMarketing Management. She is also a coauthor of a leading sales management text,Management of a Sales Force (11 th ed.). She formerly served as the chairperson of the Board of the American Marketing Association. Curtently she serves on an Advisory Board for the Univted States Bureau of Census and is the chair of the Selling and Sales Management Special Interest Group of the American Marketing Association. Lukas P. Forbes (Lukas.Forbes@wku.edu) is an assistant professor of marketing in the Gordon Ford College of Business at Western Kentucky University. He received his B.S. from the United States Military Academy at West Point, his M.B.A. from worcester Polytechnic Institute, and is completing his Ph.D. at the University of Kentucky. His research interests include personal selling, services, and product development. He has previously published in the American Marketing Association Educators and Frontiers in Services conference proceedings.     

Neural network approximation for superhedging prices

This article examines neural network-based approximations for the superhedging price process of a contingent claim in a discrete time market model. First we prove that the α-quantile hedging price converges to the superhedging price at time 0 for α tending to 1, and show that the α-quantile hedging price can be approximated by a neural network-based price. This provides a neural network-based approximation for the superhedging price at time 0 and also the superhedging strategy up to maturity. To obtain the superhedging price process for $t>0$, by using the Doob decomposition, it is sufficient to determine the process of consumption. We show that it can be approximated by the essential supremum over a set of neural networks. Finally, we present numerical results.     

The multifaceted impact of US trade policy on financial markets

We study the multifaceted effects of trade policy shocks on financial markets using a structural vector autoregression identified via event day heteroskedasticity. We find that restrictive US trade policy shocks affect US and international stock prices heterogeneously, but generally negatively. They increase market uncertainty, lower US interest rates, and lead to an appreciation of the US dollar. The effects are significant for several weeks or quarters. Decomposing the trade policy shocks further suggests that trade policy uncertainty dominates tariff level effects. Chinese trade policy shocks against the United States further hurt US stocks.     

Accounting for employee flows

This paper examines employee flows and the association with firm earnings and interest rates. We use administrative employer–employee matched panel data from Denmark spanning 17 years and hence exploit actual data on employee arrivals (labor inflows) and departures (labor outflows). Three main findings emerge. First, we condition by firms’ economic conditions. Departures predict earnings increases for prior-year loss firms, while they predict earnings decreases for prior-year profit firms, suggesting that this conditioning can help explain the mixed results in the literature. Arrivals predict earnings increases, though only for prior-year profit firms. These effects are stronger for high-paid employees than for low-paid ones. Second, the effects of departures are generally larger than the effects of arrivals, consistent with departures disrupting operations. Third, we find that lenders price employee flow information but only for departures of high-paid employees, despite the predictive ability of the flow of other employees for future earnings. Overall our results suggest that employee flows predict firm financial performance but are only partially priced by lenders.     

Device-mediated customer behaviour on the internet: A systematic literature review

The proliferation of smartphones, tablets and other digital devices in addition to traditional computers has transformed the Internet into a device-mediated environment. While these devices provide immediate access to similar Internet sources, they differ significantly in their characteristics, such as screen size, operation mode and context of use. As a consequence, behaviours on the Internet along the customer journey vary substantially depending on the device used. To summarize the fast-growing body of research on device-mediated customer behaviour, a systematic, framework-based literature review of 59 articles from the last decade was conducted. Through an examination of the antecedents, decisions and outcomes investigated in the publications, the review presents a conceptual framework that highlights the relation between device characteristics, decision processes and behavioural outcomes. The review further summarizes the theories, contexts and methods employed in the studies and sets an extensive future research agenda. We found that the extant literature lacks comprehensive theories and clear definitions of digital devices in the omnichannel environment. Furthermore, existing findings should be generalized for other contexts (e.g. industries and countries) and validated via the introduction of other research designs and methods. The understanding of device-mediated behaviour and the consequently arising marketing measures remains scarce. Thus, this review advances the comprehension of customer behaviour on the Internet and provides researchers and practitioners with information on the implications for customer experience and omnichannel management.