Predicting Internet banking adoption in India: a perceived risk perspective

The emergence of Internet banking has transformed the banking systems across the globe. As a channel to market, Internet banking allows geographical constraints to be overcome by offering various products and services at lower customer costs. An understanding of the factors influencing customer adoption of Internet banking is both relevant and timely. This study integrates technology acceptance model and perceived risk theory in understanding Internet banking acceptance among Indian bank account holders. Specifically, this study categorizes perceived risk as external risk and internal risk, and examines its influence on customer beliefs and adoption of Internet banking. Using two-step predictive analytics of structural equation modeling and artificial neural network analysis, the 270 responses reveal that both external risk and internal risk inhibit customer acceptance of Internet banking. More importantly, neural network analysis reveals that perceived ease of use and external risk are two important factors determining how well Internet banking is accepted by customers. The implications of the study findings and future research directions are presented.     

Identifying the Effects of WIC on Food Insecurity Among Infants and Children

The Women, Infants, and Children (WIC) Program is considered a crucial component of the social safety net in the United States, yet there is limited supporting evidence on the effects of WIC on the nutritional well‐being and food security of infants and young children. Using data from the National Health and Nutrition Examination Survey, we apply recently developed partial identification methods to jointly account for unobserved counterfactual outcomes and systematic underreporting of WIC participation. Under nonparametric assumptions, we find that WIC reduces the prevalence of child food insecurity by at least 3.6 percentage points (20%).     

Leadership,Creative Problem‐Solving Capacity,and Creative Performance: The Importance of Knowledge Sharing

This article presents two studies that examine whether leader supportive behaviors facilitate knowledge sharing and employee creative problem‐solving capacity, thereby enhancing creative performance. The findings from both studies indicate that leader supportive behaviors are directly and indirectly related, through both internal and external knowledge sharing, to employee creative problem‐solving capacity. In addition, creative problem solving was related to the two dimensions of creative performance—fluency and originality. However, a test of the mediation model indicated that creative problem solving only mediated the relationship between internal knowledge sharing creative performance and originality. These findings highlight the complex process by which leaders facilitate both internal and external knowledge sharing and employee creative problem‐solving capacity, thereby improving employee creative performance.     

Dynamics of judicial service supply chains

Behavioral issues, coupled with temporary capacity imbalances, dictate the characteristics that a service supply chain assumes in the long run. The paper looks at a service chain in which two factors, backlogs and incentives, influence human agent processing times and, hence, service supply chain capacity. The paper finds that servers within the supply chain change their processing speeds in order to maintain a backlog of cases that is acceptable and credible. The backlog must not be too small, so as to avoid the impression that work is scant and there is idleness; but it must not be too large, so as to avoid the impression of laziness. Simultaneously, the paper finds that there are implicit incentives in the formal hierarchy that impinge upon throughput rates at certain stages of the supply chain: agents upstream try not to overwhelm their bosses' stations downstream with excess work. Hence, this paper looks at the effects of perceived backlogs within service supply chains and also at capacity unbalances that stem from such incentives. The study explores these issues in the context of a managerial intervention in a judicial service supply chain. The study identifies the structure of a seemingly unstructured decision execution that leads to the observed outcomes. The research results in a preliminary system dynamics model that suggests several operational steps to overcome bottlenecks and incompetency.     

Predicting Corporate Bankruptcy: An Evaluation of Alternative Statistical Frameworks

Corporate bankruptcy prediction has attracted significant research attention from business academics, regulators and financial economists over the past five decades. However, much of this literature has relied on quite simplistic classifiers such as logistic regression and linear discriminant analysis (LDA). Based on a large sample of US corporate bankruptcies, we examine the predictive performance of 16 classifiers, ranging from the most restrictive classifiers (such as logit, probit and linear discriminant analysis) to more advanced techniques such as neural networks, support vector machines (SVMs) and “new age” statistical learning models including generalised boosting, AdaBoost and random forests. Consistent with the findings of Jones et al. ( 2015 ), we show that quite simple classifiers such as logit and LDA perform reasonably well in bankruptcy prediction. However, we recommend the use of “new age” classifiers in corporate bankruptcy modelling because: (1) they predict significantly better than all other classifiers on both the cross‐sectional and longitudinal test samples; (2) the models may have considerable practical appeal because they are relatively easy to estimate and implement (for instance, they require minimal researcher intervention for data preparation, variable selection and model architecture specification); and (3) while the underlying model structures can be very complex, we demonstrate that “new age” classifiers have a reasonably good level of interpretability through such metrics as relative variable importances (RVIs).     

Nontraded Goods and Real Exchange Rates in a Multi‐Good Ricardian Model

The two‐country Ricardian trade model with discrete goods and uniform transport costs for tradable goods is applied to the decomposition of the real exchange rate into traded and nontraded components. The real exchange rate is driven almost entirely by changes in the productivity differentials in nontraded goods and also explains the Balassa–Samuelson effect of a lower cost of living in poor countries, but extraordinary transport costs for some nontraded goods are necessary to easily explain the Balassa–Samuelson effect.     

An investigation of cultural cohesion in a community bank

This study examines the culture of a medium-sized community bank based in the Western United States. The study aims to identify the organization's culture and then measure the level of cultural cohesion that exists three years after a major cultural campaign was launched. The cultural characteristics the organization valued most highly were integrity, willingness to serve the customer and teamwork - all components of the official bank document on culture. Interestingly, the analysis uncovered some significant value differences among different employee groups and also employees and management; differences which can affect firm performance levels. The analysis also revealed that changing the culture in an organization does not necessarily lead to cultural cohesion.     

Media,Education and Corruption: Investigating the Associations

We study the interactive association of press freedom, access to media and education with a nation's corruption levels. A free press generates unbiased information that greater access to the media helps propagate; and a greater degree of education, in the same context, helps individuals apply that information. This entire process generates a vigilant and corruption‐free economy. It is therefore important to consider these factors in conjunction.