How and Why Decision Models Influence Marketing Resource Allocations

We study how and why model-based Decision Support Systems (DSSs) influence managerial decision making, in the context of marketing budgeting and resource allocation. We consider several questions: (1) What does it mean for a DSS to be "good?"; (2) What is the relationship between an anchor or reference condition, DSS-supported recommendation and decision quality? (3) How does a DSS influence the decision process, and how does the process influence outcomes? (4) Is the effect of the DSS on the decision process and outcome robust, or context specific? We test hypotheses about the effects of DSSs in a controlled experiment with two award winning DSSs and find that, (1) DSSs improve users' objective decision outcomes (an index of likely realized revenue or profit); (2) DSS users often do not report enhanced subjective perceptions of outcomes; (3) DSSs, that provide feedback in the form of specific recommendations and their associated projected benefits had a stronger effect both on the decision making process and on the outcomes.Our results suggest that although managers actually achieve improved outcomes from DSS use, they may not perceive that the DSS has improved the outcomes. Therefore, there may be limited interest in managerial uses of DSSs, unless they are designed to: (1) encourage discussion (e.g., by providing explanations and support for the recommendations), (2) provide feedback to users on likely marketplace results, and (3) help reduce the perceived complexity of the problem so that managers will consider more alternatives and invest more cognitive effort in searching for improved outcomes.marketing models;resource allocation;DSS;decision process;decision quality

How Feedback Can Improve Managerial Evaluations of Model-based Marketing Decision Support Systems

Marketing managers often provide much poorer evaluations of model-based marketing decision support systems (MDSSs) than are warranted by the objective performance of those systems. We show that a reason for this discrepant evaluation may be that MDSSs are often not designed to help users understand and internalize the underlying factors driving the MDSS results and related recommendations. Thus, there is likely to be a gap between a marketing manager’s mental model and the decision model embedded in the MDSS. We suggest that this gap is an important reason for the poor subjective evaluations of MDSSs, even when the MDSSs are of high objective quality, ultimately resulting in unreasonably low levels of MDSS adoption and use. We propose that to have impact, an MDSS should not only be of high objective quality, but should also help reduce any mental model-MDSS model gap. We evaluate two design characteristics that together lead model-users to update their mental models and reduce the mental model-MDSS gap, resulting in better MDSS evaluations: providing feedback on the upside potential for performance improvement and providing specific suggestions for corrective actions to better align the user's mental model with the MDSS. We hypothesize that, in tandem, these two types of MDSS feedback induce marketing managers to update their mental models, a process we call deep learning, whereas individually, these two types of feedback will have much smaller effects on deep learning. We validate our framework in an experimental setting, using a realistic MDSS in the context of a direct marketing decision problem. We then discuss how our findings can lead to design improvements and better returns on investments in MDSSs such as CRM systems, Revenue Management systems, pricing decision support systems, and the like.Learning;Feedback;Marketing Decision Models;Marketing Decision Support Systems;Marketing Information Systems

Digital leisure for development: Reframing new media practice in the global south.

Photoshopping of newlyweds, downloading the latest movies, teens flirting on social network sites and virtual gaming may seem like typical behavior in the West; yet in the context of a village in Mali or a slum in Mumbai, it is seen as unusual and perhaps an anomaly in their new media practice. In recent years, some studies (Ganesh, 2010; Mitra, 2005; Arora, 2010; 2012; Rangaswamy & Nair, 2012; Kavoori, Chadha & Arceneaux, 2006) have documented these leisure-oriented behaviors in the global south and argued for the need to emphasize and reposition these user practices within larger and contemporary discourses on new media consumption. Yet, for the most part, studies in the field of Information and Communication Technologies for Deve

Repair of Oxidative DNA Damage and Cancer: Recent Progress in DNA Base Excision Repair

SIGNIFICANCE: Reactive oxygen species (ROS) are generated by exogenous and environmental genotoxins, but also arise from mitochondria as byproducts of respiration in the body. ROS generate DNA damage of which pathological consequence, including cancer is well established. Research efforts are intense to understand the mechanism of DNA base excision repair, the primary mechanism to protect cells from genotoxicity caused by ROS. RECENT ADVANCES: In addition to the notion that oxidative DNA damage causes transformation of cells, recent studies have revealed how the mitochondrial deficiencies and ROS generation alter cell growth during the cancer transformation. CRITICAL ISSUES: The emphasis of this review is to highlight the importance of the cellular response to oxidative DNA damage during carcinogenesis. Oxidative DNA damage, including 7,8-dihydro-8-oxoguanine, play an important role during the cellular transformation. It is also becoming apparent that the unusual activity and subcellular distribution of apurinic/apyrimidinic endonuclease 1, an essential DNA repair factor/redox sensor, affect cancer malignancy by increasing cellular resistance to oxidative stress and by positively influencing cell proliferation. FUTURE DIRECTIONS: Technological advancement in cancer cell biology and genetics has enabled us to monitor the detailed DNA repair activities in the microenvironment. Precise understanding of the intracellular activities of DNA repair proteins for oxidative DNA damage should provide help in understanding how mitochondria, ROS, DNA damage, and repair influence cancer transformation

Molecular detection and characterization of phytoplasma associated with China aster (Callistephus chinensis) phyllody in India

China aster (Callistephus chinensis L.) is one of the most popular annual flowering plant grown through-out the world. Phyllody disease of China aster is a phytoplasma associated disease that induces severe economic losses. Phytoplasmal disease in China aster was assessed for phytoplasma by direct polymerase chain reaction primed by using phytoplasma universal primer pairs PI/P7. A 1.8 Kb DNA fragments encoding the portion of phyto-plasma 16SrDNA amplified by PCR was cloned and sequenced. Sequencing of the PCR product and BLAST analy-sis indicated that China aster phyllody phytoplasma strain shared maximum sequence identity (99%) with strains of Peanut Witches’ broom (16SrII) phytoplasma group. Phylogenetic relationship of 16SrDNA sequence of China aster phyllody phytoplasma strain in the present study confirmed association of Peanut Witches’ broom (16SrII) group of phytoplasmas with China aster phyllody disease in India

How and Why Decision Models Influence Marketing Resource Allocations

We study how and why model-based Decision Support Systems (DSSs) influence managerial decision making, in the context of marketing budgeting and resource allocation. We consider several questions: (1) What does it mean for a DSS to be "good?"; (2) What is the relationship between an anchor or reference condition, DSS-supported recommendation and decision quality? (3) How does a DSS influence the decision process, and how does the process influence outcomes? (4) Is the effect of the DSS on the decision process and outcome robust, or context specific? We test hypotheses about the effects of DSSs in a controlled experiment with two award winning DSSs and find that, (1) DSSs improve users' objective decision outcomes (an index of likely realized revenue or profit); (2) DSS users often do not report enhanced subjective perceptions of outcomes; (3) DSSs, that provide feedback in the form of specific recommendations and their associated projected benefits had a stronger effect both on the decision making process and on the outcomes. Our results suggest that although managers actually achieve improved outcomes from DSS use, they may not perceive that the DSS has improved the outcomes. Therefore, there may be limited interest in managerial uses of DSSs, unless they are designed to: (1) encourage discussion (e.g., by providing explanations and support for the recommendations), (2) provide feedback to users on likely marketplace results, and (3) help reduce the perceived complexity of the problem so that managers will consider more alternatives and invest more cognitive effort in searching for improved outcomes

Validation of SSR Markers Linked to the Bean Common Mosaic Virus (BCMV) Resistance in Cowpea (\u3cem\u3eVigna unguiculata\u3c/em\u3e L.) Genotypes

Cowpea, Vigna unguiculata (L.) is one of the important grain and fodder legume crops in the world, especially in tropics and subtropics. Which can adapted different climatic conditions such as high temperature and drought. It is not only important as a grain and fodder but also improve fertility of poor soils by fixing atmospheric nitrogen. An estimated cultivated area of cowpea is 12.5mha in worldwide (FAOSTAT, 2013). The grain and fodder productivity of cowpea are greatly affected by a number of biotic factors such as plant pathogens and insect pests. Among plant pathogens, viruses are considered to be a major constraint (Gioi et al., 2010). More than 40 viruses are reported from cowpea growing areas of the world. Among viruses, Bean common mosaic virus (BCMV) is very serious problem on cowpea in southern part of India especially cowpea growing areas of Karnataka. The BCMV is a member of potyvirus group and it can infect other legume crop family. Virus is seed borne and easily spread by aphids. Its chemical and cultural control neither economical nor ecofriendly. The host plant resistance has been proved the best strategy for its management. Hence it is necessary to identify stable resistance sources for BCMV disease in cowpea. Therefore large scale screening is needed to identify the durable resistance among diverse genotypes of cowpea. The basic requirements for any crop improvement programme are genetic variation for the trait of interest

How Feedback Can Improve Managerial Evaluations of Model-based Marketing Decision Support Systems

Marketing managers often provide much poorer evaluations of model-based marketing decision support systems (MDSSs) than are warranted by the objective performance of those systems. We show that a reason for this discrepant evaluation may be that MDSSs are often not designed to help users understand and internalize the underlying factors driving the MDSS results and related recommendations. Thus, there is likely to be a gap between a marketing manager’s mental model and the decision model embedded in the MDSS. We suggest that this gap is an important reason for the poor subjective evaluations of MDSSs, even when the MDSSs are of high objective quality, ultimately resulting in unreasonably low levels of MDSS adoption and use. We propose that to have impact, an MDSS should not only be of high objective quality, but should also help reduce any mental model-MDSS model gap. We evaluate two design characteristics that together lead model-users to update their mental models and reduce the mental model-MDSS gap, resulting in better MDSS evaluations: providing feedback on the upside potential for performance improvement and providing specific suggestions for corrective actions to better align the user's mental model with the MDSS. We hypothesize that, in tandem, these two types of MDSS feedback induce marketing managers to update their mental models, a process we call deep learning, whereas individually, these two types of feedback will have much smaller effects on deep learning. We validate our framework in an experimental setting, using a realistic MDSS in the context of a direct marketing decision problem. We then discuss how our findings can lead to design improvements and better returns on investments in MDSSs such as CRM systems, Revenue Management systems, pricing decision support systems, and the like

Biological relationship of Bean common mosaic virus (BCMV) infecting cowpea with leguminous plant species

Bean common mosaic virus (BCMV) associated with cowpea mechanically inoculated to different legumi-nous plants. Out of nineteen including cowpea Var.C-152, the virus was easily transferred to ten different legumi-nous hosts. All other hosts assessed for the presence of BCMV were found to be uninfected. The number of days taken for symptom expression and symptoms were varied within plant species. Pole bean expressed mosaic symp-tom after long incubation period (15-18 days) whereas, shorter incubation period was observed in common bean and rice bean (7- 10 days). BCMV produced chlorosis, mosaic, leaf distortion, puckering, vein banding, vein clearing and vein netting on cowpea(C-152). A typical virus symptom, mosaic was observed in green gram, common bean, lime bean, rice bean and yard long bean, whereas, leaf rolling and leaf distortion was observed in black gram, pole bean and snap bean. The virus-host relationship was confirmed by back inoculation test to C. amaranticolor. Further symptomatic plants were subjected for Reverse Transcriptase polymerase chain reaction (RT-PCR) for molecular confirmation using BCMV coat protein (CP) specific primer pair. A PCR fragment size of 439bp was amplified for the symptomatic plants. The results generated indicated the ability of a plant to support virus expression and host speci-ficity of BMCV within the leguminous plant species