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.     

Trends and Future Directions in Online Marketing Research

Over the last decade, the increased adoption of the Internet in public life as well as in developing businesses has led to a phenomenal rise in academic research on online marketing. This article is set to extensively review scholarly articles appearing from 2000 to 2014 on the topic from 10 top-tier academic journals to understand the research trends in the domain. A literature review has reported eight major subjective categories with an analysis of online marketing effectiveness framework. This review found three most significant subject categories: (1) online marketing issues; (2) Internet usage, perception, and attitude; and (3) online shopping and e-commerce. Additionally, some new online marketing research topics such as word-of-mouth, user-generated content, and social network are also highlighted. Finally, a selection of research topics that got the maximum attention of researchers is presented along with discussion of the future research directions in the online marketing space.     

Stock of downstream complementary assets as a catalyst for product innovation during technological change in the U.S. machine tool industry

Research summary : We investigate the effect of incumbents' stock of downstream complementary assets on their product innovation during a disruptive technological change. We theorize that a firm's stock of downstream complementary assets, by providing critical information about shifting demand conditions, will play a catalytic role in firm adaptation during such a change. Using the advent of disruptive computer numerical control machine tools in the U.S. machine tool industry during the 1970s and 1980s as the context, we find that firms with greater stocks of downstream complementary assets are likely to be product innovation leaders during such a change. Managerial summary : Disruptive changes are challenging firms across industries. We concentrate on the U.S. machine tool industry during the 1970s and 1980s when Japanese manufacturers with disruptive computer numerical control systems challenged the U.S. manufacturers. We find that, under the threat of disruption, the greater the stock of downstream complementary assets a U.S. machine tool manufacturer has, the more likely it is to be the product innovation leader with the disruptive technology. Our findings provide novel insights for managers in companies that face disruptive changes and can help them avoid the consequences of such changes as predicted by prior research. Copyright © 2016 John Wiley & Sons, Ltd.     

Visitors’ learning for environmental sustainability: Testing short- and long-term impacts of wildlife tourism experiences using structural equation modelling

Wildlife tourism experiences have the potential to positively impact tourists’ awareness, appreciation and actions in relation to the specific wildlife they encounter and the environment in general. This paper investigates the extent of such impact across multiple sites, and uses Structural Equation Modelling to identify factors that best predict positive long-term learning and environmental behaviour change outcomes. Three sets of variables were measured – visitors’ entering attributes (including pre-visit environmental orientation and motivation for the visit), salient aspects of the experience, and short- and long-term learning and environmental behaviour change outcomes. Although attributes such as pre-visit commitment and motivation to learn were among the best predictors of the long-term impact of the experience, there was evidence that aspects of the experience were also important. In particular, reflective engagement which involved cognitive and affective processing of the experience was found to be associated with short- and long-term environmental learning outcomes. The implications for wildlife tourism managers are discussed.     

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.