ASU Scholarship Showcase

This study is an attempt to use group information collected on climate change from farmers in eastern Uttar Pradesh, India to address a key question related to climate change policy: How to encourage farmers to adapt to climate change? First, we investigate farmers’ perception of and adaptation to climate change using content analysis and group information. The findings are then compared with climatic and agriculture information collected through secondary sources. Results suggest that though farmers are aware of long-term changes in climatic factors (temperature and rainfall, for example), they are unable to identify these changes as climate change. Farmers are also aware of risks generated by climate variability and extreme climatic events. However, farmers are not taking concrete steps in dealing with perceived climatic changes, although we find out that farmers are changing their agricultural and farming practices. These included changing sowing and harvesting timing, cultivation of crops of short duration varieties, inter-cropping, changing cropping pattern, investment in irrigation, and agroforestry. Note that these changes may be considered as passive response or adaptation strategies to climate change. Perhaps farmers are implicitly taking initiatives to adapt climate change. Finally, the paper suggests some policy interventions to scale up adaptation to climate change in Indian agriculture.

We present a novel paradigm to identify shared and unique brain regions underlying non-semantic, non-phonological, abstract, audio-visual (AV) memory vs. naming using a longitudinal functional magnetic resonance imaging experiment. Participants were trained to associate novel AV stimulus pairs containing hidden linguistic content. Half of the stimulus pairs were distorted images of animals and sine-wave speech versions of the animal's name. Images and sounds were distorted in such a way as to make their linguistic content easily recognizable only after being made aware of its existence. Memory for the pairings was tested by presenting an AV pair and asking participants to verify if the two stimuli formed a learned pairing. After memory testing, the hidden linguistic content was revealed and participants were tested again on their recollection of the pairings in this linguistically informed state. Once informed, the AV verification task could be performed by naming the picture. There was substantial overlap between the regions involved in recognition of non-linguistic sensory memory and naming, suggesting a strong relation between them. Contrasts between sessions identified left angular gyrus and middle temporal gyrus as key additional players in the naming network. Left inferior frontal regions participated in both naming and non-linguistic AV memory suggesting the region is responsible for AV memory independent of phonological content contrary to previous proposals. Functional connectivity between angular gyrus and left inferior frontal gyrus and left middle temporal gyrus increased when performing the AV task as naming. The results are consistent with the hypothesis that, at the spatial resolution of fMRI, the regions that facilitate non-linguistic AV associations are a subset of those that facilitate naming though reorganized into distinct networks.

We study whether people became less likely to switch Medicare prescription drug plans (PDPs) due to more options and more time in Part D. Panel data for a random 20 percent sample of enrollees from 2006-2010 show that 50 percent were not in their original PDPs by 2010. Individuals switched PDPs in response to higher costs of their status quo plans, saving them money. Contrary to choice overload, larger choice sets increased switching unless the additional plans were relatively expensive. Neither switching overall nor responsiveness to costs declined over time, and above-minimum spending in 2010 remained below the 2006 and 2007 levels.

We argue that the strength with which the organization communicates expectations regarding the appropriate emotional expression toward customers (i.e., explicitness of display rules) has an inverted U-shaped relationship with service delivery behaviors, customer satisfaction, and sales performance. Further, we argue that service organizations need a particular blend of explicitness of display rules and role discretion for the purpose of optimizing sales performance. As hypothesized, findings from 2 samples of salespeople suggest that either high or low explicitness of display rules impedes service delivery behaviors and sales performance, which peaks at moderate explicitness of display rules and high role discretion. The findings also suggest that the explicitness of display rules has a positive relationship with customer satisfaction.

The impacts of information technology (IT) on total factor productivity (TFP) are assessed through an integrative framework of IT-induced externalities and IT-leveraged innovations. Based on network externalities and endogenous growth theory, our study aims to reconcile the seeming discrepancy between the recent observed evidence and the prediction by neoclassical growth theory. We argue that computerization has reshaped the competitive landscape into a network economy with IT-induced externalities that benefit not only IT purchasers but also other stakeholders. Moreover, IT is a platform technology that can leverage innovations to enhance the technological level of production process. Consequently, these two factors of IT-induced externalities and IT-leveraged innovations exert positive impacts on TFP, suggesting IT plays a more pivotal role than input consumption and accumulation that neoclassical growth theory assumes for IT. We use panel data from 30 Organization of Economic Cooperation and Development (OECD) countries over the period of 2000–2009 to empirically test hypotheses on this IT-TFP link. Implications are drawn from our findings for future research to measure IT׳s contributions at the macro level more accurately, and policymakers are urged to cultivate IT׳s positive impacts on TFP to help sustain long-term economic growth.

Mobile applications markets with app stores have introduced a new approach to define and sell software applications with access to a large body of heterogeneous consumer population. This research examines key seller- and app-level characteristics that impact success in an app store market. We tracked individual apps and their presence in the top-grossing 300 chart in Apple's App Store and examined how factors at different levels affect the apps' survival in the top 300 chart. We used a generalized hierarchical modeling approach to measure sales performance, and confirmed the results with the use of a hazard model and a count regression model. We find that broadening app offerings across multiple categories is a key determinant that contributes to a higher probability of survival in the top charts. App-level attributes such as free app offers, high initial ranks, investment in less-popular (less-competitive) categories, continuous quality updates, and high-volume and high-user review scores have positive effects on apps' sustainability. In general, each diversification decision across a category results in an approximately 15 percent increase in the presence of an app in the top charts. Survival rates for free apps are up to two times more than that for paid apps. Quality (feature) updates to apps can contribute up to a threefold improvement in survival rate as well. A key implication of the results of this study is that sellers must utilize the natural segmentation in consumer tastes offered by the different categories to improve sales performance.

Mild Cognitive Impairment (MCI) is a transitional stage between normal aging and dementia and people with MCI are at high risk of progression to dementia. MCI is attracting increasing attention, as it offers an opportunity to target the disease process during an early symptomatic stage. Structural magnetic resonance imaging (MRI) measures have been the mainstay of Alzheimer's disease (AD) imaging research, however, ventricular morphometry analysis remains challenging because of its complicated topological structure. Here we describe a novel ventricular morphometry system based on the hyperbolic Ricci flow method and tensor-based morphometry (TBM) statistics. Unlike prior ventricular surface parameterization methods, hyperbolic conformal parameterization is angle-preserving and does not have any singularities. Our system generates a one-to-one diffeomorphic mapping between ventricular surfaces with consistent boundary matching conditions. The TBM statistics encode a great deal of surface deformation information that could be inaccessible or overlooked by other methods. We applied our system to the baseline MRI scans of a set of MCI subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI: 71 MCI converters vs. 62 MCI stable). Although the combined ventricular area and volume features did not differ between the two groups, our fine-grained surface analysis revealed significant differences in the ventricular regions close to the temporal lobe and posterior cingulate, structures that are affected early in AD. Significant correlations were also detected between ventricular morphometry, neuropsychological measures, and a previously described imaging index based on fluorodeoxyglucose positron emission tomography (FDG-PET) scans. This novel ventricular morphometry method may offer a new and more sensitive approach to study preclinical and early symptomatic stage AD.

We use Spain’s Equality Law to test for the existence of agency problems between party leaders and their constituents. The law mandates a 40 percent female quota on electoral lists in towns with populations above 5,000. Using pre- and postquota data by party and municipality, we implement a triple-difference design. We find that female quotas resulted in slightly better electoral results for the parties that were most affected by the quota. Our evidence shows that party leaders were not maximizing electoral results prior to the quota, suggesting the existence of agency problems that hinder female representation in political institutions.

This study examined the impact of three alternative types of goals (specific learning, general “do your best” learning, and specific performance) on team performance. Eighty-four-person teams engaged in an interdependent command and control simulation in which the team goal and task complexity were manipulated. Contrary to research at the individual level, teams with specific learning goals performed worse than did teams with general “do your best” learning goals or specific performance goals. The negative effects of specific learning goals relative to general “do your best” learning goals and specific performance goals were amplified under conditions of increased task complexity and were explained by the amount of coordination in the teams.

Buyers often make supplier selection decisions under conditions of uncertainty. Although the analytical aspects of supplier selection are well developed, the psychological aspects are less so. This article uses supply chain management and behavioral decision theories to propose that attributes of the purchasing situation (category difficulty, category importance, and contingent pay) affect cognition that, in turn, affects a supply manager's choice. We conducted a supplier selection behavioral experiment with practicing managers to test the model's hypotheses. When the context involves an important or difficult sourcing category, higher risk perceptions exist that increase preference for a supplier with more certain outcomes, even when that choice has a lower expected payoff. However, the presence of contingent pay decreases risk perceptions through higher perceived supplier control. We also find that a manager's risk propensity increases preferences for a supplier with less certain outcomes regardless of perceived risk. Our model and results provide a theoretical framework for further study into the cognitive aspects of supplier selection behavior and provide insight into biases that influence practicing supply chain managers.