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Women empowerment becomes an important policy discussion in development economics and modernization theory. The empowerment of women can lead to an increase in the quality viz-a-viz the capacity of human resources accessible for economic development. The purpose of this study is to evidence the impact of social and economic dimensions on women empowerment through financial inclusion in rural India.

To reveal the research objective, the study has utilized a primary survey of women respondents from the Gujarat state of India by a simple random sampling method and applied a logistic regression approach to identify the relationship between the need of a bank account (determinant of financial inclusion) as a dependent variable and social and economic dimensions of women empowerment such as earning status, participation in financial decision-making, recipient of social welfare schemes and perception towards the safety of saving as independent variables.

The results of this study show that earning status, participation in financial decision-making at household level and recipient of social welfare schemes by women have a significant impact on women empowerment through financial inclusion; however, safety of their savings is observed as an insignificant variable, yet the odd value is very high (2.437) in the present study.

The present study is the first of its kind to examine the social and economic status of women and its impact on their requirement of a formal bank account for the overall empowerment of women in rural India.

The paper aims to capture the rack-level thermal dynamics in data center. It proposes the rack-level response experiments as well as transient Computational Fluid Dynamics (CFD) analysis to characterize the local thermal environment of the system.

A single sever simulator rack and its two neighboring racks with its cold and hot aisle containment have been modeled with known cold air supply temperature and flow rate for transient CFD analysis. The heat load was kept constant initially and varied case-to-case basis, which includes capturing the rack-level response with respect to changes in input. However, the response experiments on simulator rack were performed for 14 h by variation of server heat loads as step and ramp input.

The paper provides the detailed transient CFD analysis of data center racks. The local cold air flow rates and temperature at the vicinity of the racks showed significant effect due to changes in input. It was concluded that the rack-level dynamics impacts the thermal environment of data center and hence cannot be ignored.

The high computing devices and faster internet demands have led to major thermal management concerns for data center operators. To tackle this issue, capturing the system thermal dynamics is imperative. However, the system-level CFD analysis is computationally expensive. Therefore, this paper deals with the rack-level transient CFD study using commercial tool STAR CCM+.

This paper includes the modeling of the servers as a porous media as well as the multigrid method to enhance the computational speed. The successful implementation of this approach validated through experiments. This would help to establish a base for research in any type of data center.

This paper provides the porous media approach to model servers and multigrid method to enhance the computational speed. At the same time, the thought of characterizing the local dynamics at the vicinity of data center racks is unique.

The purpose of this paper is to identify the barriers to consumers’ intention to purchase energy efficient appliances. It uses multiple regression analysis to predict the factors that deter consumers’ purchase intention.

Five barriers to consumers’ intention to purchase energy efficient appliances were identified through an exhaustive literature survey. Data were gathered from 300 respondents from Pune city from the state of Maharashtra in India through a survey. The items were measured on a five-point Likert scale. Validity and reliability of the scale were established. Multiple regression analysis was conducted to predict consumers’ intention to purchase energy efficient appliances based on factors identified.

Findings revealed that some degree of uncertainty was associated with energy efficient appliance purchase. In addition to possessing lower degrees of awareness on energy efficient appliances, consumers tend to disbelieve claims made on labels of energy efficient appliances. Consumers also feel inconvenience in identifying these appliances, spending time to know about them and paying the price to purchase them. Hence, the factors – scepticism towards label claims and perceived personal inconvenience – were found to have negative impact on consumers’ purchase intention. Societal norm was found to have a positive impact on consumers’ purchase intention. Interestingly, price sensitivity and perceived product risk (which were expected to have a negative relationship with consumers’ purchase intention) displayed a positive relationship.

The model proposed here is based on the researcher’s identification of the barriers. There might have been unidentified barriers that were not considered. The research does not account for manufacturing or policy-based issues that might also pose as barriers. The study encourages marketers to re-examine marketing and communication policies associated with the sale of energy efficient appliances.

The paper provides insights into the external barriers faced by consumers while purchasing an energy efficient appliance. This research enables managers to understand consumer’s preference for conventional products over energy efficient ones. It attempts to check the presence of barriers to energy efficient appliances, identified from literature in a tier 1 city of India. Tier 1 city is the city with population greater than 1,00,000 as per 2001 census of India.

Multiple length and time scales arise in a wide variety of practical and fundamental problems. It is important to obtain accurate and validated numerical simulation results, considering the different scales that exist, in order to predict, design and optimize the behavior of practical thermal processes and systems. The purpose of this paper is to present modeling at the different length scales and then addresses the question of coupling the different models to obtain the overall model for the system or process.

Both numerical and experimental methods to obtain results at the different length scales, particularly at micro and nanoscales, are considered. Even though the paper focusses on length scales, multiple time scales lead to similar concerns and are also considered. The two circumstances considered in detail are multiple length scales in different domains and those in the same domain. These two cases have to be modeled quite differently in order to obtain a model for the overall process or system. The basic considerations involved in such a modeling are discussed. A wide range of thermal processes are considered and the methods that may be used are presented. The models employed must be validated and the accuracy of the simulation results established if the simulation results are to be used for prediction, control and design.

Of particular interest are concerns like verification and validation, imposition of appropriate boundary conditions, and modeling of complex, multimode transport phenomena in multiple scales. Additional effects such as viscous dissipation, surface tension, buoyancy and rarefaction that could arise and complicate the modeling are discussed. Uncertainties that arise in material properties and in boundary conditions are also important in design and optimization. Large variations in the geometry and coupled multiple regions are also discussed.

The paper is largely focussed on multiple-scale considerations in thermal processes. Both numerical modeling/simulation and experimentation are considered, with the latter being used for validation and physical insight.

Several examples from materials processing, environmental flows and electronic systems, including data centers, are given to present the different techniques that may be used to achieve the desired level of accuracy and predictability.

Present state of the art and future needs in this interesting and challenging area are discussed, providing the impetus for further work. Different methods for treating multiscale problems are presented.

This paper aims to take stock of research done in the domain of relationship marketing (RM). Additionally, this article aims to identify the potential areas of future research.

The authors have used machine learning-based structural topic modelling using R-software to analyse the dataset of 1,905 RM articles published between 1978 and 2020.

Structural topic modeling (STM) analysis led to identifying 14 topics, out of which 7 (viz. customer loyalty, customer relationship management systems, interfirm and network relationships, relationship selling, services and relationship management, consumer brand relationships and relationship marketing research) have shown a rising trend. The study also proposes a taxonomical framework to summarize RM research.

This is the first comprehensive review of RM research spanning over more than four decades. The study’s insights would benefit future scholars of this field to plan/execute their research for greater publication success. Additionally, managers could use the practical implications for achieving better RM outcomes.

The purpose of this paper is to identify and examine the most important factors that could predict the Saudi customer’s continued intention towards adoption of mobile banking.

The proposed conceptual model was based on the technology acceptance model (TAM) and task-technology fit (TTF) model. This is also expanded by considering two additional factors: perceived privacy and perceived security. By using a self-administered questionnaire, the data were collected from a convenience sample of Saudi banking customers from different parts of Saudi Arabia.

The main results based on structural equation modelling analyses supported the impact of perceived privacy, perceived security, perceived usefulness and TTF on the customers’ continued intention to use mobile banking.

The moderation influence of the demographic factors (i.e. age, gender, income level, educational level) was not tested. The data were also collected using a self-report questionnaire; however, it would be more accurate to utilise more statistics from the bank database about the users of m-banking.

This study represents a worthy attempt to test such novel technology (m-banking) in the KSA where there is a scarcity of literature. A considerable theoretical contribution was also made by integrating the TTF model with the TAM in addition to consider privacy and security in one single model. Moreover, considering both perceived privacy and security in the current model creates an accurate picture about the adoption of m-banking especially as there are a limited number of m-banking studies that have considered privacy and security alongside the TTF model and TAM in the same model.

The purpose of this paper is to identify the factors influencing the citizens of India to prevent cybercrimes in the proposed Smart Cities of India.

A conceptual model has been developed for identifying factors preventing cybercrimes. The conceptual model was validated empirically with a sample size of 315 participants from India. Data were analyzed using structural equation modeling with SPSS and AMOS softwares.

The study reveals that the “awareness of cybercrimes” significantly influences the actual usage of technology to prevent cybercrimes in Smart Cities of India. The study reveals that government initiative (GI) and legal awareness are less influential in spreading of the awareness of cybercrimes (AOC) to the citizens of the proposed smart cities.

The conceptual model utilizes two constructs from the technology adoption model, namely, perceived usefulness and ease of use. The study employs other factors such as social media, word of mouth, GIs, legal awareness and organizations constituting entities spreading awareness from different related literature works. Thereby, a comprehensive theoretical conceptual model has been proposed which helps to identify the factors that may help in preventing cybercrimes.

This study provides an insight to the policy maker to understand several factors influencing the AOC of the citizens of the proposed Smart Cities of India for the prevention of cybercrimes.

There are few existing studies analyzing the effect of AOC to mitigate cybercrimes. Thus, this study offers a novel contribution.

The purpose of this paper is to explore the history, classification, regulation, the current market and consumer trends and health effects of alcopops.

The articles reviewed were selected based on the following key descriptors such as alcopop, history, classification, types, production and consumption trend, health benefits and adverse effect.

“Alcopop” is a collective term used to refer to flavored alcoholic beverages (FAB), also known as malt alcoholic beverage; ready-to-drink beverage (RTD); pre-packaged spirit or premium packaged spirit; high-strength (HS) pre-mixed beverage; pre-mixed caffeinated alcoholic beverage or alcoholic energy drink, etc. Alcopops were introduced into the market in 1990s. Starting with the introduction of FAB in the form of wine coolers, a large number of alcoholic beverages have been introduced. FAB are sweet, containing relatively low alcohol content and especially designed for the young drinkers also called the “entry-level” drinkers. They are popular among young and underage drinkers, teenage girls particularly, and the industries use packaging materials and marketing strategies that appear to target the youth. These products are now marketed globally, and their production, classification and marketing vary by country based on national regulatory restrictions. In countries such as USA and Australia, the industry represents that the products were malt beverages for regulatory purpose which were found to be false as other products were derived from distilled spirits. The product has no health benefits so far, the government need to reform their regulations and include new definitions of alcopops with available restrictions that would be practice at both national and state levels until and unless there have been another scientifically approved method of production through which the beverage could be beneficial for human consumption.

This is a unique and comprehensive review that will provide a brief overview of alcopops, i.e., a global perspective on the new category of alcoholic beverage.

The purpose of this paper is to dig out enablers of sustainable industrial ecosystem to develop a framework.

To test the framework statistically, a structured questionnaire was designed. Measures for the questionnaire were adopted from an extensive literature review. Further, the questionnaire was pretested and further pilot study was conducted. Adding to this, the reliability and validity of the constructs was examined using confirmatory factor analysis followed by covariance-based structural equation modeling to test research hypotheses.

The statistical analyses suggest that the model exceeds the threshold limit for goodness of fit after undergoing through few iterations. Normative pressure has a low effect than rest of the factors.

The present study is a unique contribution in terms of its theoretical implications and practical use. Finally, research findings are concluded and further research directions is outlined.

This paper explores the reasons behind the slow uptake of mobile payment (m-payment) from a switching intention (SI) perspective. The antecedents of SI from cash to m-payment were explored using an integrated conceptual model of the push-pull-mooring (PPM) framework and the status quo bias (SQB) perspective.

A self-administered survey was used to collect data, which are empirically tested using SmartPLS 3.0.

The push factor was found to have an insignificant effect on SI to m-payment whereas the pull factor was significant. Furthermore, the results revealed that the two mooring variables have contrasting results as trust is not a significant determinant of SI to m-payment while perceived security and privacy (PSP) is. Additionally, all SQB-related relationships were found to be statistically significant

This study determined the factors that play vital roles in the consumers' decision-making to transition from cash to m-payment. This was done via a uniquely developed conceptual model that incorporated the PPM framework with the SQB perspective.