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In nano-scale-based very large scale integration technology, quantum-dot cellular automata (QCA) is considered as a strong and capable technology to replace the well-known complementary metal oxide semiconductor technology. In QCA technique, rotated majority gate (RMG) design is not explored greatly, and therefore, its advantages compared to original majority gate are unnoticed. This paper aims to provide a thorough observation at RMG gate with its capability to build robust circuits.

This paper presents a new methodology for structuring reliable 2n-bit full adder (FA) circuit design in QCA utilizing RMG. Mathematical proof is provided for RMG gate structure. A new 1-bit FA circuit design is projected here, which is constructed with RMG gate and clock-zone-based crossover approach in its configuration.

A new structure of a FA is projected in this paper. The proposed design uses only 50 number of QCA cells in its implementation with a latency of 3 clock zones. The proposed 1-bit FA design conception has been checked for its structure robustness by designing various 2, 4, 8, 16, 32 and 64-bit FA designs. The proposed FA designs save power from 46.87% to 25.55% at maximum energy dissipation of circuit level, 39.05% to 23.36% at average energy dissipation of circuit-level and 42.03% to 37.18% at average switching energy dissipation of circuit level.

This paper fulfills the gape of focused research for RMG with its detailed mathematical modeling analysis.

The mobile phone industry in India is highly competitive, fast paced and technology-driven. In such a hyper competitive era, effective advertising is considered a key success driver for a mobile phone brand. The purpose of this paper is to identify advertisement effectiveness dimensions for Indian mobile phone industry and to develop hierarchical interrelationships among these dimensions in the Indian print context.

Structured Delphi approach is used to derive the set of dimensions for advertisement effectiveness. Further, techniques such as interpretive structural modeling and MICMAC analysis are used to establish hierarchical linkages among identified dimensions.

On the basis of experts’ opinion, refinement through structured Delphi resulted in the identification of 14 advertisement effectiveness dimensions specific to Indian mobile phone industry. Interpretive structural modeling assisted in the development of linkages among these identified dimensions based on their interrelations. Further, attention, relevance, excitability, liking and consumer preference, etc., turned out to be the dimensions of utmost importance for measuring advertisement effectiveness for the Indian mobile phone industry.

The present research work is limited to the recognition and development of hierarchical interrelationships among advertisement effectiveness dimensions specific to mobile phone business in the Indian print context only. Further studies may be carried out for other product or service category in some different media context.

The present research has several significant implications for academics and advertising practitioners involved in designing and developing promotional campaigns for mobile phone brands in India. The identified 14 dimensions and developed hierarchical model provide valuable insights for improving advertisement effectiveness.

This paper demonstrated successful implementation of Delphi and interpretive structural modeling technique to explore the research area of advertisement effectiveness.

The aim of this paper is to explore the brain–computer interface (BCI) as a methodology for generating awareness and increasing reliable use cases of the same so that an individual's quality of life can be enhanced via neuroscience and neural networks, and risk evaluation of certain experiments of BCI can be conducted in a proactive manner.

This paper puts forward an efficient approach for an existing BCI device, which can enhance the performance of an electroencephalography (EEG) signal classifier in a composite multiclass problem and investigates the effects of sampling rate on feature extraction and multiple channels on the accuracy of a complex multiclass EEG signal. A one-dimensional convolutional neural network architecture is used to further classify and improve the quality of the EEG signals, and other algorithms are applied to test their variability. The paper further also dwells upon the combination of internet of things multimedia technology to be integrated with a customized design BCI network based on a conventionally used system known as the message query telemetry transport.

At the end of our implementation stage, 98% accuracy was achieved in a binary classification problem of classifying digit and non-digit stimuli, and 36% accuracy was observed in the classification of signals resulting from stimuli of digits 0 to 9.

BCI, also known as the neural-control interface, is a device that helps a user reliably interact with a computer using only his/her brain activity, which is measured usually via EEG. An EEG machine is a quality device used for observing the neural activity and electric signals generated in certain parts of the human brain, which in turn can help us in studying the different core components of the human brain and how it functions to improve the quality of human life in general.

The case captures the origin and initial years of two restaurants Mirchi & Mime and Madeira & Mime, which exclusively employed Speech and Hearing Impaired persons (SHI) as servers (often called “waiters” in India). It documents how the restaurants were set up, captures significant incidents during this initial period and the impact of these incidents on the working of the restaurants. Further, it describes the challenge of opening a fine dining restaurant and a gastropub staffed exclusively by SHI persons as servers. The case narrates the reactions and impact on the SHIs and their families, co-workers within the outlets and the customers visiting these outlets. Finally, the case lists the recognition received by the organisation and outlines plans for the immediate future.

The purpose of this paper is to propose a conceptual framework for the application of blockchain in the Public Distribution System (PDS) in India to manage the supply of food grains to the targeted beneficiaries. The framework will help prevent diversions and leakages of grains at the warehouse and Fair Price Shop (FPS) level. The paper also identifies the enablers and disablers in the context of the framework.

This paper will firstly review the previous literature in PDS and blockchain-enabled agricultural and food supply chains. The study then proposes a framework that could be implemented in the PDS in India using blockchain technology.

The proposed framework provides an effective way to combat corruption, exclusion errors of targeted beneficiaries, leakage of PDS food grains and is cost-effective. The identified enablers and disablers give an insight into the application of blockchain in PDS in India.

The research work may have implications for the Ministry of Food and PDS (Central Government), Food Corporation of India and State Governments to manage the supply of the grains more efficiently and effectively.

The current study caters to the implementation of blockchain technology starting from the warehouse level to the FPSs and consumers and simultaneously connecting them to concerned authorities to ensure transparency and accountability.

This study is the maiden attempt to understand the effect of specific human resource practices (HRPs) on employee retention (ER) with the mediation of job satisfaction (JS) and moderation of work experience (WE) and job hopping (JH) in the context of the textile industry.

This study adopted a quantitative methodology and applied quota sampling to gather data from employees (n = 365) of leading textile companies in India. The conceptual model and hypotheses were tested with the help of Partial Least Squares-Structural Equation Modelling (PLS-SEM).

The findings of a path analysis revealed that compensation and performance appraisal (CPA) have the highest impact on JS followed by employee work participation (EWP). On the other hand, EWP had the highest impact on ER followed by grievance handling (GRH). The study revealed that JS significantly mediates between HRPs like CPA and ER. During Multi-group analysis (MGA) it was found that the importance of EWP and health and safety (HAS) was more in employee groups with higher WE, but it was the opposite in the case of CPA. In the case of JH behavior, the study observed that EWP leads to JS in loyal employees. Similarly, JS led to ER, and the effect was more pronounced for loyal employees.

In the context of the Indian textile industry, this work is the first attempt to comprehend how HRPs affect ER. Secondly, it confirmed that JS is not a guaranteed mediator between HRPs and ER, it could act as an insignificant, partial or full mediator. Additionally, this study establishes the moderating effects of WE and JH in the model through multigroup analysis.

The COVID-19 pandemic has transformed consumer buying behavior across the world. COVID-19 crisis brought a behavioral change in consumers' attitudes toward health, financial and social well-being. The current research work highlights the factors influencing consumer buying behavior during the COVID-19 pandemic considering saving and safety perspectives.

This study attempts to understand the gap in buying behavior with reference to saving and safety. Survey-based study was conducted during the second phase of COVID-19, and the respondents were those who lived in highly affected COVID cities in India. Exploratory factor analysis and multiple regression analysis were carried out for testing the hypotheses.

Seven factors became the prominent factors in consumer buying patterns during the pandemic. Consumers in the times of COVID-19 pandemic spend only on essential items as compared to nice-to-have and non-essential items.

Respondents considered in the research were millennials aged 25–40. The current research is limited to specific geographic location.

The study assessed how savings and safety influence consumer buying behavior. The 2S framework model for consumer buying behavior during pandemic has been developed. The findings of the study provides a road map to the companies, policy makers, managers and consumers in understanding the consumer buying behavior during pandemic.

The current research work observe the changes in the behavioral patterns of consumers in the context of 2S framework, i.e. saving and safety. This study offer novel contribution as there is no available literature that examined the saving and safety aspects together for consumer buying behavior during crisis.

The purpose of this paper is to determine the role of service quality (SQ), trust and commitment to customer loyalty (CL) for telecom service users. Further, the moderating role of gender, marital status and connection type within the model was tested.

A measurement model was created based on valid 615 responses from Indian TSUs for SQ, trust, commitment and loyalty with the help of partial least squares structural equation modeling (PLS-SEM). Multi-group analysis (MGA) was conducted to understand the moderating effect of marital status, gender and connection type within the model.

The results suggest that, out of five dimensions of SQ, only responsiveness, assurance and empathy have a significant positive relationship with both commitment and trust. Tangibility has a significant positive relationship with trust only. Both commitment and trust have a significant impact on loyalty. It was noticed that both commitment and trust act as mediators between three SQ dimensions (assurance, empathy and responsiveness) and CL. MGA revealed that empathy and responsiveness positively induce trust in telecom users who are single. Whereas, assurance increases commitment toward telecom service providers in married users. Assurance and empathy significantly contribute toward commitment and trust, respectively, in male users as compared to females. Empathy was found important for postpaid users for trust-building, whereas trust was found to be more important for prepaid users to stay loyal to the service provider.

This article contributes toward understanding the role of SQ, trust and commitment to CL moderated by marital status, gender and connection type in an integrated model concerning telecom service.

This study aims to develop and demonstrate a deposition framework for the implementation of a region-based adaptive slicing strategy for the Tungsten Inert Gas (TIG) welding-based additive manufacturing system. The present study demonstrates a deposition framework for implementing a novel region-based adaptive slicing strategy termed as Fast Interior and Accurate Exterior with Constant Layer Height (FIAECLH).

The mentioned framework has been developed by performing experiments using the design of experiments and analyzing the experimental data. Analysis results have been used to obtain the mathematical function to integrate customization in the process. The paper, in the end, demonstrates the FIAECLH framework for implementing region-based adaptive slicing strategy on the hardware level.

The study showcase a new way of implementing the region-based adaptive slicing strategy to arc-based metal additive manufacturing. The study articulating a new strategy for its implementation in all types of wire and arc additive manufacturing processes.

Wire-arc-based technology has the potential to deliver cost-effective solutions for metal additive manufacturing. The research on arc welding-based processes is being carried out in different dimensions. To deposit parts with complex geometry and better dimensional accuracy implementation of a novel region-based adaptive slicing strategy for the arc-based additive manufacturing process is an essential task. The successful implementation of an adaptive slicing strategy would ease the fabrication of complex geometry in less time. This paper accomplishes this need of implementing a region-based adaptive slicing strategy as no experimental investigation has been reported for the TIG-based additive manufacturing process.

In today’s highly competitive business scenario, advertising symbolizes one of the key marketing activities. The purpose of this paper is to understand the relationship between advertisement effectiveness and consumer buying behavior for major automobile companies of central India.

A judicious mix of qualitative (focus group and Delphi technique) and quantitative (structured questionnaire survey) research methods was used for the present study.

Study found that for automobile sector, effective advertisements have a positive impact on consumer buying behavior. It suggests that customer’s attitude can be shaped favorably through effective advertising. Automobile companies must arrange special training sessions and learning programs for their sales force to ensure supportive customer purchasing behavior.

The scope of the present study is limited to major automobile companies of central India only. Although, the findings can be interpreted and generalized in a global business scenario.

The research work is first of its kind that attempts to study the impact of effective advertising on consumer buying behavior in Indian automobile context. The findings and recommendations can be used for strategic planning of training sessions and workshops for different stakeholders in automobile industry.