When age does not harm innovative behavior and perceptions of competence: Testing interdepartmental collaboration as a social buffer

Can older managers overcome stereotypes relating age to low competence? We integrate the literature on age and cognitive ability with research on innovation to explore whether—and if so, when—employees' age harms performance and promotability appraisals made by their supervisors. Multisource, time‐lag data from 305 project managers indicate that the negative stereotypes can be explained through decreased innovative behavior. However, older employees are not always seen as poorer performers with less potential to be promoted due to their reduced innovative behavior. Rather, interdepartmental collaboration moderates these effects. Specifically, older employees with low interdepartmental collaboration are less innovative and receive worse performance and promotability appraisals than younger employees, but the “age handicap” vanishes when older employees collaborate with members of other departments. Organizations should foster formal or informal collaboration among units to prevent negative consequences of an aging workforce.     

Forecast quality improvement with Action Research: A success story at PharmaCo

There is a gap in the forecasting research surrounding the theory of integrating and improving forecasting in practice. The number of academically affiliated consultancies and knowledge transfer projects that there are around, due to a need for improvements in forecast quality, would suggest that many interventions and actions are taking place. However, the problems that surround practitioner understanding, learning and usage are rarely documented. This article takes the first step toward trying to rectify this situation by using the specific case study of a fully engaged company. A successful action research intervention in the Production Planning and Control work unit improved the use and understanding of the forecast function, contributing to substantial savings, enhanced communication and improved working practices.     

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.     

Are You a Chocolate Lover? An Investigation of the Repurchase Behavior of Chocolate Consumers

This study aimed to understand the factors affecting repurchase behavior of chocolate brands and, consequently, customer retention and acquisition. The study adopted a qualitative, inductive approach using in-depth interviews with 31 Australian consumers. The factors identified in the extant literature as antecedents of customers’ repurchase intention in the chocolate industry, including brand recognition, sales promotion, product price value, variety, taste, texture, size, packaging, and customer satisfaction, were confirmed. The results also indicated that functional value, product selection value, self-gratification value, socialization value, and transactional value were also considered during the consumer decision-making process. Implications for practitioners are provided.     

Exploring job crafting: Diagnosing and responding to the ways employees adjust their jobs

Recent research has developed an in-depth understanding of how workers change their jobs on their own to improve their performance and well-being, a process called job crafting. This research suggests that managers, coworkers, and organizations need a better understanding of how to manage job crafting to capitalize on its benefits and reduce costs. This article will help organizations diagnose the occurrence of job crafting, recognize the differences between goal-oriented approaches to job crafting as opposed to withdrawal-oriented avoidance job crafting, and identify the seven specific types of job crafting: work role expansion, social expansion, work role reduction, work organization, adoption, metacognition, and withdrawal. We conclude with recommendations for managers, coworkers, and organizations on how to diagnose and manage job crafting.     

Is it U.S. GAAP or IFRS? Understanding how R&D costs affect ratio analysis

While financial reporting standards under U.S. GAAP and IFRS are fundamentally similar, differences do exist that may affect our analysis of company financial statements. This is particularly true when comparing a U.S. company following U.S. GAAP to a firm that uses IFRS. To illustrate, we compare research and development (R&D) accounting methods under both sets of standards and illustrate how they affect the analysis of financial results of firms in a specific industry—automotive manufacturers. Our results provide insight into settings in which differences in R&D accounting may have the greatest impact on financial analysis.     

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.     

Twenty-Five Years after the Fall of the Berlin Wall: An Empirical Revisit of West German Consumers' Attitudes Toward Products and Brands from Former East Germany

More than 25 years after the German reunification, data show that products/brands from the eastern regions of Germany (“Neue Länder”) still do not have significant shares in the country's western part (“Alte Länder”). To analyze potential reasons for this phenomenon, our current study replicates a previous study that investigated selected attitudes of Alte Länder consumers toward products/brands from the Neue Länder. It is shown that factors such as consumer ethnocentrism, product judgment, willingness to buy, and economic animosity continue to influence consumer behavior and as such our study offers potential explanation for the failure of Neue Länder products/brands in the western regions of Germany.     

Media-Based Sentiment Indices as an Alternative Measure of Consumer Confidence

In this paper, we consider the feasibility of constructing online sentiment indices, using large amounts of media data, as an alternative to the conventional survey method used to create the consumer confidence index in South Africa. A clustering framework is adopted to provide an indication of possible candidate sentiment indices constructed from a combination of different text sources and dictionaries that best mimic the traditional survey-based consumer confidence index from the South African Bureau for Economic Research (BER). The results conclude that it is possible to create an index using sentiment analysis using online editorial data that does resemble the BER’s consumer confidence index. The different media-based sentiment indices (MSI) show a significant level of correlation and co-movement with the BER’s CCI. Impulse responses and cross-correlation functions indicate that the MSI could potentially lead the survey-based method up to two quarters. Furthermore, Granger-causality tests show that the media-based indices are good predictors of future consumer confidence index values. The results provide motivation for further study on the use of sentiment-based techniques and online media data sources to track consumer confidence within an emerging market such as South Africa.     

A REVIEW OF THE EMPIRICAL LITERATURE ON FARMER COOPERATIVES: PERFORMANCE,OWNERSHIP AND GOVERNANCE,FINANCE, AND MEMBER ATTITUDE

The empirical literature on farmer cooperatives is now fast emerging and developing in the areas of performance, ownership and governance, finance, and member attitude. We discuss 56 peer‐reviewed publications to illustrate the main findings and conclusions while outlining challenges and opportunities for future research. Generally, cooperative membership is found to positively impact price, yield, input adoption, income, and other indicators of member performance, yet there is growing evidence of an uneven distribution of benefits for small and large producers. In terms of structure, evidence of a causal relationship of ownership and governance to performance has been elusive, yet there are now many findings of inherent equity and long‐term debt constraints, often in the context of consolidation to drive scale and scope economies. Further inefficiency is observed to be driven by increased heterogeneity in member attitudes and objectives, in particular in terms of commitment and participation. Thus, overall, empirical work portrays farmer cooperatives as flawed and complex business organizations which nonetheless have a strong positive impact on its members. While applied research may progress in various directions, a general improvement in empirical methodologies is needed to allow robust analysis of mixed objectives in dynamic environments.