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This study aims to extend existing theories and fills research gaps regarding the acceptance and use of new technologies by consumers by exploring the adoption of app-cab services in India. Through the application and comparison of a unified theory of acceptance and use of technology (UTAUT) and UTAUT 2/expanded-UTAUT (E-UTAUT) models, this paper empirically tests the relationships between important constructs related to technology adoption, acceptance and utilization in India’s emerging economy.

In total, 612 responses to a questionnaire of active and regular users of app-cab services in India are examined. Path analysis and structural equation modeling presents interesting findings indicating that the expanded models have huge implications for the Indian app-cab industry.

This paper finds that the UTAUT 2/E-UTAUT models are a good fit for consumers and their behavior toward technology-based services. In particular, this study, one of the first of its kind, examines consumer acceptance and use behavior and identifies the factors that influence customer behavior with regard to new technology (app-cab services) in an emerging economy (India). Theoretical and practical implications are discussed.

Very few studies are available on app-cab adoption in emerging economies.

This study aims to empirically indicate that environment-friendly products may be used as a consumption strategy for improving the environmental well-being of a sizable consumer base and show that there are great possibilities and opportunities available for companies to come up with the right marketing mix for consumers in the rural market. There is a great dearth of empirical research on consumer behavior facets on environment-friendly products for rural market in India.

Conclusive cross-sectional descriptive research design has been used to study the environmentally concerned consumer behavior (ECCB) for environment-friendly products with the help of a survey instrument relevant for empirical research. This paper adds to the existing literature by developing one model in the Indian context for the rural market. The research study used exploratory factor analysis and confirmatory factor analysis with structural equation modeling approach to analyze the collected data from consumers.

The major finding of the study is that consumers living in rural areas are aware about the environmental movement, but marketers have probably not fully explored the potential for environment-friendly products. The study strongly argues that organizations should leverage on the rural market opportunity in India. It confirms the need to tailor marketing mix for rural markets for determining behavioral dimensions of consumer decision-making.

This empirical research paper is developed and applied in the Indian context, with special reference to the rural market of the country. Results may change when applied to different rural locations in the same country and/or different countries depending on their demographic variables, psychosocial factors and socioeconomic conditions. The findings of this study need to be viewed within the context of certain limitations of location, social and economic issues. The study provides the initial base for further research on the theme, as there are no such studies available on environment-friendly products.

This research study is highly useful for the business firms deciding on marketing mix variables for environment-friendly products in rural market scenario in India, and it provides inputs for formulating major policy decisions in marketing. The study provides insights for managers, policymakers and organizations operating in rural markets and working on different facets of environmental protection issues in different forms.

It has been investigated across global markets that human activities have altered the natural ecosystem, so to make natural resources available for the future generation, there is a greater need to achieve more sustainable forms of development. The study provides insights from the rural Indian market for better adoption of environment-friendly products and will motivate marketers to explore the rural market horizon.

The study has been conducted with consumers who are residents of one small town in India. So far, no study has been conducted, and it is first such attempt to analyze the rural Indian market for environment-friendly products and consumer behavior ever since such products were launched in the country. This study provides an early glimpse into the workings of marketing practitioners who work on consumer strategy formulation and rural marketing decision-making for environment-friendly products.

Natural food products are becoming more popular, and their health-related benefits are widely acknowledged. The authors wanted to see the influence of different consumption values on purchase intention of natural food products. To address this gap, the current study proposes to use theory of consumption values to explain customers purchase intention towards natural food products.

The authors used theory of consumption values (TCV), attitude and purchase intention to develop a comprehensive model. About 464 respondents have responded to the structured questionnaire which was floated through email and WhatsApp. Finally, the authors used structural equation modelling and moderation analysis to arrive at the final results.

Except for social value, all constructs named conditional, functional, emotional and epistemic were found to have a favourable and significant impact on consumers’ purchase intention towards natural food products. The study shows that attitude has a moderating effect on the association between emotional value and purchase intention.

This research illuminates the TCV which enable the long-term use of natural food products. In addition, the importance of attitude as a moderator of purchase intent provides a deep understanding of customer behaviour.

This model is the first of its kind in the current literature, using consumption values from the TCV with attitude to regulate purchase intention towards natural food products. In addition, theoretical advancements pave the path for future research.

The purpose of this paper is to explore the dimensions of online customer experience (OCE) and their impact on satisfaction and loyalty in the clothing e-retail context. Furthermore, it explores the influence of gender on the OCE-satisfaction-loyalty chain.

OCE dimensions were drawn from the literature and then adapted and validated using two samples (217 – exploratory factor analysis, 651 – confirmatory factor analysis) of experienced online clothing shoppers in India. An analysis was done using structured equation modelling.

Six OCE psychological factors and four OCE functionality factors were revealed. Both OCE dimensions impact loyalty either directly or indirectly through satisfaction. Gender is observed to moderate the relationship among three OCE factors (e-distrust, e-negative beliefs and website interactivity) and satisfaction.

The research results are limited to the factors related to each of the two OCE dimensions explored within the clothing e-retail context in India.

Clothing e-retailers need to focus on both the OCE dimensions to drive business sustenance. Furthermore, their OCE strategies should be in line with the gender-based differences highlighted by the study.

The study facilitates in the adaptation and validation of the OCE dimensions in the clothing e-retail category in an emerging market. While all factors associated with both OCE dimensions are important for driving satisfaction and loyalty, the study underscores the need for a higher focus on visual engagement by e-retailers in the given context. Gender moderates the OCE-satisfaction paths, but does not moderate the OCE-loyalty paths.

While advances in big data analytics (BDA) provide valuable business insights and immense business value, many firms find it difficult to gain advantage from their BDA initiatives. Noting the strategic role of firm-specific knowledge, we develop a framework examining the relation between firm specificity of BDA knowledge and competitive advantage. We also examine the dynamic evolution of BDA capabilities and the associated knowledge management strategies.

We review the resource-based view (RBV), capabilities life cycles and absorptive capacity perspectives along with the literature on BDA competitive advantage. Identifying two key BDA factors, application customization and data proprietorship, we develop a BDA competitive advantage framework. We also investigate the absorptive capacities employed by firms to advance their BDA capabilities. We use anecdotal cases to support our theoretical arguments.

We propose that BDA solutions with vendor-based applications (noncustomized) and public data will not generate firm-specific knowledge and therefore not provide competitive advantage. In contrast, BDA solutions with custom applications and proprietary data will provide high-level firm-specific knowledge and potentially result in sustained competitive advantage. We further suggest the relevant absorptive capacities and the knowledge management strategies for BDA capability development.

Our framework provides managers with insights into how to develop and enhance firm-specific knowledge from their BDA solutions to gain competitive advantage.

Our study offers a new BDA firm-specific knowledge framework for competitive advantage.

While marketers want to drive higher repurchases for better business sustainability, repeat shopping experiences may change customer perceptions of the online channel, resulting in the emergence of new segment typologies. Therefore, the purpose of this paper is to explore the segmentation of online clothing shoppers using a repeat online clothing shopper base. Further, it analyses segment positions in a perceptual space to derive relevant positioning insights for the various segments.

Segmentation is done using dual bases of e-lifestyle and website quality factors for which the scales are derived from literature and then adapted and validated using a two-phase process across two samples of 271 and 644 experienced shoppers, respectively, in India. Positions of the segments are explored using the discriminant analysis-based perceptual mapping technique.

Three segments are found, namely disengaged averse online shoppers, interactive convenience seekers and adept online shopping optimists with the latter two having a higher propensity to purchase clothes online. Perceptual mapping of the segment positions reveals dimensions, which can be used for appropriate positioning.

The research methodology may be replicated for other products and country contexts, and additional factors may be explored for further insights.

The study reveals insights on the evolving nature of segments as shoppers gain experience of online shopping for clothes and highlights the varied reasons for the growing acceptability of the online channel. The findings reveal key targeting and positioning strategies for e-marketers.

This is one of the first studies of its kind in India, which explores the segmentation of repeat online clothing shoppers in India using dual bases. Another distinctive feature of the study is its use of the perceptual mapping technique to draw inferences about factors that differentiate multi-segment buying behavior.

This study investigates the aerodynamics of the airflow over low-rise houses subjected to turbulent cyclonic winds along the South-eastern peninsular India, routinely afflicted by tropical cyclones. The purpose of this paper is to demonstrate how the power of modern computational fluid dynamics (CFD) and its engineering application accentuate decision-making at the planning stage of house designing in vulnerable areas.

The Weather Research and Forecasting (WRF) model was used for first simulating the landfall of cyclone Hudhud, a real storm, and its effect in extant and new house designs. Results from the WRF model were utilized to configure further CFD simulations of airflow around house designs. The analyses yielded deep insights, often non-intuitive, into airflow patterns around these houses with disparate roof forms indicating new possibilities in redesigning houses along Indian coastal areas.

This study shows that storm-induced high TKE values warranted a fuller CFD-based study. The second major finding showed that for a 90° angle of attack, arguably the most destructive attack angle, a pitched roof (with a pitch angle of 10°) worked best – this is about half the recommended angle sourced from earlier empirical estimates dating back to the British Raj period. There is a thin layer of padded air cushion shielding the roof's vulnerable surface from the storm's most energetic parts.

The originality of this research lies in its discourse to systematically resolve the TKE distribution of a cyclone impacting a standalone house. In particular, the study presents a lucid demonstration of all the probable scenarios connecting cyclonic stresses with a roof response, inferred from a careful combination of results garnered from cyclonic storm modelling coupled with CFD analysis. Additionally, the paper also shows a graphic visual representation of the forces induced on different roof designs, presented as a checklist for the first time. This should serve as a ready reckoner for civic authorities involved in disaster management over cyclone-ravaged areas.

The paper aims to investigate materialism as one of the retail shopping motives along with utilitarian/hedonic motivations in the Indian context. It aims to identify the key shopping motivations, which explain the shopping value in the context of malls. Furthermore, it intends to develop a shopping motivations-based typology of Indian mall shoppers, and to profile the motivational and demographic characteristics of the discerned segments.

The data were collected through a mall intercept survey. The shopping motivations were identified through literature, and established scales were utilised to collect data. Exploratory factor analysis was used to understand the underlying structure of mall shopping motives. Hierarchical and K-means clustering were used to cluster the consumers. Additionally, ANOVA along with post hoc tests were used to explore the mean differences between the various clusters. Cross-tabulation along with the chi-square statistic was used to understand the demographic characteristics of the clusters.

Indian mall shoppers are motivated by hedonistic, materialistic and utilitarian motives. They can be primarily classified into four clusters, namely, balanced shoppers, materialist shoppers, hedonistic shoppers and value shoppers.

Knowledge of distinct consumer segments will aid marketers in formulating marketing and promotional strategies for augmenting mall footfalls.

Although past research has accentuated hedonic and utilitarian motivations as the primary shopping motives, little research has been conducted to examine materialism as a shopping motive. Rise of materialism in the emerging Indian market has metamorphosed the consumer behaviour. The study examines the utilitarian, hedonistic and materialistic dimensions of shopping and unfolds a typology of mall shoppers. It contributes to the repository of cross-national research on shopping behaviour by unravelling the shopping motivations of Indian consumers.