Investigating the Role of Aesthetics in Consumer Moral Judgment and Creativity

ABSTRACT As human beings, we have a profound affinity for beauty, and an overwhelming amount of research recognizes our attraction to high aesthetics. Aesthetics significantly affect consumer behavior, such as purchase intention, product perception, consumer satisfaction, and product evaluation. Leading brands such as Apple are adored and coveted due to the high aesthetics and superior design of their products, which enables them to create and sustain competitive advantage. Because consumers often give more importance to aesthetics than functional attributes when choosing a product, marketers take aesthetics into account in their marketing strategies. This research explores aesthetics’ diverse relationships to consumer behavior. Specifically, I examine the relationship of aesthetics to consumers’ moral judgment and creativity and consider the moderating roles of individual traits, such as the centrality of aesthetics in one’s life and construal level. In essay I, I start by summarizing the general literature on aesthetics and the literature that is specific to marketing and consumer behavior. In essay II, I explore the effects of beauty on consumers’ moral judgment. Consumers often have to choose between what is right and what is easy, such as in paying more for fair-trade coffee, purchasing low-carbon footprint products, or recycling. Typically, consumers sacrifice money, time, or effort to make moral choices, and several factors are salient to these decision-making processes. The findings of the initial studies indicate that beauty does affect moral judgment. Additionally, verbal and visual beauty cues have distinct effects on moral judgment. Visual beauty cues overpower moral judgment, making consumers are less willing to forgo beauty to make morally responsible choices. On the other hand, verbal beauty cues induce consumers to make morally sound decisions when visual cues are not present. There is a dearth of research on the effects of product aesthetics on consumers’ moral judgment, and I seek to fill this gap. In essay III, I focus on the relationship between nature scenes and creativity while accounting for the centrality of visual product aesthetics. Additionally, I explore the moderating role of construal level. I posit that consumers who assign higher importance to product aesthetics are more likely to be creative when exposed to nature scenes. Research indicates that spending time in nature has soothing and restorative properties, such as stress relief, lower depression, and overall wellbeing. Moreover, research shows that a soothing natural environment facilitates the mental wellbeing that is conducive to creativity. The results indicate an interaction between scenery and creativity and that this relationship is moderated by the centrality of aesthetics in one’s life. Specifically, I observe improved creativity on exposure to nature scenes, and this relationship is significant for individuals who give higher importance to product aesthetics, finding that the centrality of aesthetics in one’s life extends to the appreciation of beauty in nature, as anticipated, and enhances creativity. The results also indicate a significant interaction between scenery and construal level; as anticipated, individuals with a low/concrete construal demonstrate a higher propensity toward creativity on exposure to nature scenes when compared to individuals with a high/abstract construal. This research provides a fresh perspective on the salience of aesthetics and contributes to the scarcity of research into moral judgment and creativity in consumer behavior

Customer Sentiment Analysis Based on App Reviews for the Automotive Industry

This paper places a strong emphasis on the importance of customer feedback and sentiments which are available on digital media. OEMs must organize their digital strategy, budget their IT spending, and integrate IT with their corporate goal to improve their brand's perception and win over customers. For this research, the methodology adopted was to do the customer sentiment analysis towards the IT applications that automobile companies are offering by analyzing the customer feedback and reviews in the app market. It will help the companies understand customer sentiment and what customers like and dislike about their offerings. Businesses can use this input to improve their products or services, which will encourage repeat business by building a loyal customer base. it is crucial for automakers to track all of their customer’s touchpoints and enhance their experience at each one by considering customer feedback and implementing new application features and technology

Propolis Prevents Hepatorenal Injury Induced by Chronic Exposure to Carbon Tetrachloride

Carbon tetrachloride (CCl4) is a well-known hepatotoxicant, and its exposure induces hepatorenal injury via oxidative stress and biochemical alterations. This study had been conducted to confirm the protective role of propolis extract on CCl4-induced hepatorenal oxidative stress and resultant injury. Propolis extracts collected from Gwalior district and 24 female Sprague Dawley rats were used for experiment. Animals were exposed to CCl4 (0.15 mL/kg, i.p.) for 12 weeks (5 days/week) followed by treatment with propolis extract (200 mg/kg, p.o.) for consecutive 2 weeks. CCl4 exposure significantly depleted blood sugar and hemoglobin level and raised the level of transaminases, alkaline phosphatase, lactate dehydrogenase, protein, urea, albumin, bilirubin, creatinine, triglycerides, and cholesterol in serum. Lipid peroxidation was enhanced, whereas GSH was decreased significantly in liver and kidney in CCl4-intoxicated group. Ethanolic extract of propolis successfully prevented these alterations in experimental animals. Activities of catalase, adenosine triphosphatase, glucose-6-phosphatase, acid, and alkaline phosphatase were also maintained towards normal with propolis therapy. Light microscopical studies showed considerable protection in liver and kidney with propolis treatment, thus, substantiated biochemical observations. This study confirmed hepatoprotective potential of propolis extract against chronic injury induced by CCl4 by regulating antioxidative defense activities

Chaotic Convection in a Viscoelastic Fluid Saturated Porous Medium with a Heat Source

Chaotic convection in a viscoelastic fluid saturated porous layer, heated from below, is studied by using Oldroyd’s type constituting relation and in the presence of an internal heat source. A modified Darcy law is used in the momentum equation, and a heat source term has been considered in energy equation. An autonomous system of fourth-order differential equations has been deduced by using a truncated Fourier series. Effect of internal heat generation on chaotic convection has been investigated. The asymptotic behavior can be stationary, periodic, or chaotic, depending upon the flow parameters. Construction of four-scroll, or “two-butterfly,” and chaotic attractor has been examined

Multiscale materials modelling using DFT-based localization relationships

With the tremendous amount of research done in the field of numerical methods for engineering the number of possible applications as well as users have drastically increased. However, mostly these tools have been developed independently for solving problems of a particular kind, by particular methods on a particular scale, which leads to some limitations. One of these limitations, interoperability, will be dealt with in this thesis and a methodology to resolve it for a small use-case of finite element problems at a continuum scale will be proposed.Multiscale modelling is the need of the hour, and this can be con rmed from the fact that several initiatives have been taken to bring together researchers from di erent domains by formation of projects like Integrated Computational Materials Engineering (ICME), Materials Genome Initiative etc. This increasing interest can be pertained to the fact that there is a need for creating new materials with desired e ective properties for new applications like Additive Manufacturing (AM). Until recently the discovery of new materials was based on empirical methods of trial and error, which takes roughly twenty years to bring in a new material into manufacturing. Therefore, it is important to address these two difficult problems. First is Multiscale modelling, which enables communication between constitutive models at di erent length scales, thus improving accuracy of failure predictions and second, is Accelerated Material Discovery, which can reduce the development time of new materials with desired properties. As it turns out, both these problems are closely related and can be addressed simultaneously. The key to success in both these areas is making problem solving data driven, i.e., convertint these non-trivial problems Big Data friendly so that the techniques from Data Science can be used for building scalable, robust and computationally efficient solutions. Another good reason to use data science for these problems is that it makes data reusable i.e., data that was produced during solution of one problem can be used in solving another problem by establishing syntactic material databases, where not only e ective properties but also the internal structure of the materials is readily available. In this thesis, one such mathematical framework called Material Knowledge Systems (MKS) is used to solve both the above mentioned problems. MKS is derived from the Statistical Continuum theories, and has been successfully implemented in real world problems. MKS is based on the rigorous mathematical framework called Material Sensitive Design (MSD), which is further derived from generalized homogenization theories. MSD provides a rigorous methodology for quanti cation of the internal structure of the material, which spans multiple length and time scales with a microstructure function . But the biggest achievement of MSD is that it allows us to incorporate the n-point spatial correlations in the homogenization theories. Also it addresses the problem of localization, which has been under addressed as compared to the homogenization problems. The use of n-point spatial correlations to represent the internal structure of the material is very rigorous, thus, the amount of structural information is substantially large. To deal with this increased amount of information, dimensional reduction techniques like Principal Component Analysis, Naive Bayes etc., from the eld of Data Science. Using these techniques, the material designer can not only visualize the structure-property linkages, but can also begin to solve the inverse problem of creating microstructures using hybrid processes which exhibit the desired effective properties. These linkages are also called Property-Structure-Process (PSP) relations. Establishment of such PSP linkages will change the way how materials are created in the future

Characterization of Aspergillus species associated with commercially stored triphala powder

About 82 triphala powder samples were analyzed for the association of different fungi. Results reveal the predominance of Aspergillus as the major genera with six predominant species namely, A. niger, A. flavus, A. fumigatus, A. terreus, A. nidulans and A. amstelodami. Therefore, these six isolated Aspergillus species were characterized morphologically, microscopically and molecularly. In addition, an attempt was made to characterize the frequently occurring aflatoxigenic and non toxic Aspergillus species at molecular level along with their identification. Morphological variability was detected among isolates in regard to colony morphology, conidia colouration, exudates and reverse, colony texture and growth rate. Microscopic characteristics for the identification were conidial heads, stipe, colour and length of vesicles, shape and seriation, metulae covering, conidia size and shape. For molecular characterization, internal transcribed spacer (ITS)-4, a universal fungal primer was utilized. Differences in band patterns and number of bands obtained after polymerase chain reaction (PCR) amplification clearly differentiates between the Aspergillus species. Results also reveal that only A. flavus showed amplification with all the three aflatoxigenic primers apa-2, ver-1 and omt-1, which means that only A. flavus was identified as aflatoxigenic and other Aspergillus species as non-toxigenic after PCR analysis. Hence, morphological, microscopic and molecular methods are important for the complete identification of important Aspergillus species and other fungi isolated from stored commodities.Key words: Aspergillus, triphala, identification, macroscopic and microscopic characteristics, molecular methods

Role of Growth Factor Signaling in Cancer

Growth factors may be defined as any group of protein that stimulate the growth of specific tissues and play an important role in promoting cellular differentiation and cellular division. Growth factors impart one of the important hallmark of cancer i.e sustaining proliferative signaling. They may act through paracrine, autocrine and endocrine signaling to effect growth and proliferation of cancer cells. They may act through various signaling cascades like MAPK, PI3K/AKT, JAK/STAT etc to activate their downstream mediates affecting various pathlogical and physiological functions. Abrupt signaling patterns of growth factors can induce oncogenic transformations. An enhanced understanding of these pathways can help targeting neoplastic transformation at an early stage. This review summarizes various mechanisms for targeted therapeutics against growth factor in cancer and their future prospective.