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The purpose of this paper is to explore the tourists' perception of smart tourism with the application of virtual reality and design a framework of smart tourism with elements of VR for Indian Tourism especially in the periods of the pandemic COVID-19. The ever-evolving and unprecedented COVID 19 situation had posed extreme challenges for the travel and tourism industry. In such conditions, it is becoming increasingly necessary to rely on digital technologies, ICT and smart tourism. ICT has served as a catalyst for innovations in tourism.

This study investigates the impact of smart tourism and virtual reality technology on the perception of tourists towards travelling decisions during and post COVID-19 scenario. The respondents involved in the study were tourists travelling in India, the tourists come from different parts of India. A structured questionnaire has been administered to collect data from 224 travellers across India. The questionnaire consisted 22 constructs. The constructs in this section were measured using a five-point Likert scale ranging. In the first step, the first order Confirmatory Factor Analysis (CFA) is carried out, by using the software IBM AMOS-20. The initial model is generated ix constructs, and outcomes are used to analyse the model's goodness of fit and construct validity. In the second step, Structural Equation Modelling (SEM) is carried out to do the path analysis of the proposed model. The effect of relationships amongst the theoretical constructs is also analysed using SEM.

The findings imply that the application of smart tourism along with virtual reality forms a positive perception of tourists and provides a sustainable platform for tourism organizations in Indian tourism. Virtual reality-based tourism has emerged as alternate for the tourism industry during the times of Covid, which in long run can be seen as a substitute to traditional tourism. The increasing use of blue ocean concepts, to delivery high-value experience at low cost has complimented the tourism industry. The researchers have made a modest attempt by proposing a blended model of smart tourism with virtual reality as a blue ocean strategy and which would ultimately facilitate the sustainability of the Industry by creating multi-dimensional values of experience for tourists in India.

The researchers have made a modest attempt by proposing a blended model of smart tourism with virtual reality as a blue ocean strategy, which would ultimately facilitate the industry's sustainability by creating multi-dimensional values of experience for tourists in India.

This qualitative study designs a smart tourism system with the use of the recent advances in ICT and Virtual Reality (VR), as a bridging solution and the saviour of the tourism sector in India during COVID 19. The integration of ICT into the travel experience has resulted in the social phenomena of smart tourism. This has led to a rise in use of smart tourism tools among tourism service providers.

The purpose of this paper is to assess the appropriateness of equal weights estimation (sumscores) and the application of the composite equivalence index (CEI) vis-à-vis differentiated indicator weights produced by partial least squares structural equation modeling (PLS-SEM).

The authors rely on prior literature as well as empirical illustrations and a simulation study to assess the efficacy of equal weights estimation and the CEI.

The results show that the CEI lacks discriminatory power, and its use can lead to major differences in structural model estimates, conceals measurement model issues and almost always leads to inferior out-of-sample predictive accuracy compared to differentiated weights produced by PLS-SEM.

In light of its manifold conceptual and empirical limitations, the authors advise against the use of the CEI. Its adoption and the routine use of equal weights estimation could adversely affect the validity of measurement and structural model results and understate structural model predictive accuracy. Although this study shows that the CEI is an unsuitable metric to decide between equal weights and differentiated weights, it does not propose another means for such a comparison.

The results suggest that researchers and practitioners should prefer differentiated indicator weights such as those produced by PLS-SEM over equal weights.

To the best of the authors’ knowledge, this study is the first to provide a comprehensive assessment of the CEI’s usefulness. The results provide guidance for researchers considering using equal indicator weights instead of PLS-SEM-based weighted indicators.

Research and development (R&D) is a vital strategy for firms to sustain their competitive locus and profitability in the global marketplace. Therefore, the existing research is engrossed in the correlation between firm performance (FP) and R&D intensity (RDI) meta-analysis. It also examined the ‘Type of Firm’ as a moderator in this relationship.

This study is motivated by its potential to address existing knowledge gaps, guide decision-making, influence policy and contribute to advancing theoretical and practical insights in the domain of business, economics and innovation.

This study is based on the secondary data. The researcher uses ‘Meta- Essentials 1.5’ for meta-analysis covering the studies of developed and emerging economies from 1985 to 2022.

The outcome conveys a small effect of magnitude between RDI and FP. It also indicates the positively significant linkage between them, directing that investing in R&D projects leads to improvement in the performance of companies. It also points out that private firms engaging in R&D activities have a negative while public firms have a positive correlation with their performance.

Understanding this linkage is imperative as it aids managers in making strategic decisions, the government in funding research-related schemes and investors in choosing R&D projects for investment.

The mounting focus on environmental, social and governance (ESG) factors in business has sparked substantial curiosity in understanding the nexus between ESG and the companies’ strategic decisions. This study aims to investigate the influence of firms’ ESG disclosure scores on their dividend payout. Furthermore, it examines the nuanced dynamics of this relationship by exploring the moderating role of the country’s investor protection regulations and regulatory enforcement.

This study uses pooled ordinary least square regression with year, industry and country effects. It analyzes a balanced panel data set of 192 non-financial firms drawn from the primary equity indices of BRICS nations. This study examined the data of six years spanning 2015–2020.

The findings discover a significantly positive relationship between ESG scores and dividend payout ratio, conveying that firms with higher ESG scores allocate more of their profits as dividends. Furthermore, the finding reveals that country-level robust investor protection and effective regulatory enforcement mechanisms undermine the positive association between ESG ratings and payouts of dividends, suggesting that the ESG disclosure of firms operating in a setting characterized by enhanced investor safeguards and stricter regulatory oversight will exert less influence on their dividend decisions.

To the best of the authors’ knowledge, this is the first study to concentrate on the ESG–dividend nexus in the BRICS countries. Furthermore, this study used each country’s investor protection index and regulatory enforcement scores to comprehend the influence of country-level legal frameworks in shaping the relationship between ESG and dividend decisions, thus adding value to the existing literature on corporate sustainability.

The purpose of this research study is to improve sentiment analysis (SA) at the aspect level, which is accomplished through two independent goals of aspect term and opinion extraction and subsequent sentiment classification.

The proposed architecture uses neighborhood and dependency tree-based relations for target opinion extraction, a domain–ontology-based knowledge management system for aspect term extraction, and deep learning techniques for classification.

The authors use different deep learning architectures to test the proposed approach of both review and aspect levels. It is reported that Vanilla recurrent neural network has an accuracy of 83.22%, long short-term memory (LSTM) is 89.87% accurate, Bi-LSTM is 91.57% accurate, gated recurrent unit is 65.57% accurate and convolutional neural network is 82.33% accurate. For the aspect level analysis, ρ_aspect comes out to be 0.712 and Δ²_aspect is 0.384, indicating a marked improvement over previously reported results.

This study suggests a novel method for aspect-based SA that makes use of deep learning and domain ontologies. The use of domain ontologies allows for enhanced aspect identification, and the use of deep learning algorithms enhances the accuracy of the SA task.

The purpose of the study is to identify the factors affecting the entrepreneur's choice of the dairy value chain and evaluate the impact of the value chain on farm performance (profit).

Primary data were collected from dairy entrepreneurs in India, covering nine states. A multinomial treatment effect model (controlling for selection bias and endogeneity) was used to evaluate the impact of the choice of the value chain on entrepreneurs' profit.

Dairy entrepreneurs operating in any recognized value chain other than the value chain driven by the consumer household realize a comparatively lesser profit. Dairy farmers have established direct linkages with customers in urban areas – who could pay premium prices for safe and quality milk. Food safety compliance is positively associated with profit and entrepreneurs (who have undergone formal training in dairying) preferred partnerships with a formal value chain. The prospects of starting a dairy enterprise are slightly higher in villages compared to urban areas.

Dairy entrepreneurs can make a shift in accordance with the study's findings and boost their profitability. It aids in comprehending how trainees (who obtained advice and training for raising dairy animals from R&D organizations) and non-trainee dairy farmers make value chain selections, which ultimately affect profitability. However, purposive sampling and a small sample size limit the universal implications of the study.

Developing entrepreneurial behavior and startup culture is at the center of policymaking in India. The findings imply that the emerging value chain not only enhances the profit of dairy farmers by resolving consumer concerns about food safety and the quality of milk and milk products but also builds consumer trust.

This paper offers insight into how the benefits of dairy entrepreneurs vary with their participation in the different value chains. The impact of skill development/training programs on value chain selection and farm profitability has not yet been fully understood. Here is an attempt to fill this gap. This paper through light on how trained and educated dairy entrepreneurs are able to establish a territorial market by approaching premium customers – this is an addition to the existing literature.

Environmental tourism impacts are considered to be unbalanced. The implementation of environmental sustainability focuses on restoring a balance through environmentally responsible behavior. As Generation Z was found in recent studies to exhibit divergent levels of environmentally responsible behavior compared to other generations, but also to have intra-generational differences, this study aims to explore the underlying reasons and explanations behind their attitudes and behavioral attempts.

Four focus group discussions with young people belonging to Generation Z allow to probe deep into their environmental sustainability orientation.

The results of this study demonstrate that Generation Z’s environmental attitude is triggered by social pressure, social media, as well as by the COVID-19 pandemic. For their touristic behavioral intention, they concentrate predominantly on climate-friendly travel and on-site mobility, waste avoidance as well as emphasizing economic and social sustainability. By furthermore highlighting Generation Z’s responsibility ascription to the supply and the demand side, in addition to illustrating the demand for framework conditions to be created from governments and destinations, the knowledge scope on environmental sustainability is expanded.

In particular, this study enriches environmentally responsible behavior research by incorporating the perspective of Generation Z, while it deepens Generation Z’s behavioral understanding. Furthermore, the results of this study allow to derive implications for tourism policymakers.

环境旅游影响被认为是不平衡的。环境可持续性的实施侧重于通过对环境负责的行为来恢复平衡。由于最近的研究发现Z一代与其他几代人相比表现出不同的环境责任行为水平, 且存在代际差异, 本研究探讨了他们的态度和行为尝试背后的潜在原因和解释。

采用四个焦点小组与Z世代年轻人讨论, 深入探究他们的环境可持续性导向。

这项研究的结果表明, Z世代的环境态度是由社会压力、社交媒体以及COVID-19大流行引发的。对于他们的旅游行为意向, 他们主要关注气候友好型旅行和现场移动性, 避免浪费以及强调经济和社会的可持续性。通过进一步强调Z世代对供给侧和需求侧的责任归因, 并阐释政府和目的地对框架条件的需求, 扩大了环境可持续性的知识范围。

特别地, 本研究通过纳入Z世代的视角, 丰富了环境责任行为研究, 加深了Z世代的行为理解。此外, 本研究的结果可以为旅游政策制定者提供启示。

Los impactos medioambientales del turismo se consideran desequilibrados. La implementación de la sostenibilidad medioambiental se centra en restablecer el equilibrio mediante un comportamiento responsable con el medio ambiente. Estudios recientes señalan que la Generación Z muestra niveles divergentes de comportamiento responsable con el medio ambiente en comparación con otras generaciones, pero también presenta diferencias intra-generacionales. Este estudio explora las razones y explicaciones subyacentes a sus actitudes e intenciones de comportamiento.

Cuatro grupos de discusión con jóvenes de la Generación Z permiten profundizar en su orientación hacia la sostenibilidad medioambiental.

Los resultados de este estudio evidencian que la actitud medioambiental de la Generación Z está provocada por la presión social, medios sociales, así como por la pandemia del COVID-19. En cuanto a su intención de comportamiento turístico, se concentran predominantemente en los viajes respetuosos con el clima y la movilidad in situ, evitar residuos, así como en hacer hincapié en la sostenibilidad económica y social. Al destacar la responsabilidad que la Generación Z atribuye a la oferta y la demanda, además de inculcar la demanda para la creación de condiciones marco por parte de gobiernos y destinos, se amplía el alcance del conocimiento sobre la sostenibilidad medioambiental.

En particular, este estudio enriquece la investigación sobre el comportamiento responsable con el medio ambiente al incorporar la perspectiva de la Generación Z y profundizar en la comprensión del comportamiento de esta generación. Asimismo, los resultados de este estudio permiten desarrollar implicaciones para los responsables de las políticas turísticas.

This paper aims to present the design development and measurement of two aerodynamic slotted X-bands back-to-back planer substrate-integrated rectangular waveguide (SIRWG/SIW) to Microstrip (MS) line transition for satellite and RADAR applications. It facilitates the realization of nonplanar (waveguide-based) circuits into planar form for easy integration with other planar (microstrip) devices, circuits and systems. This paper describes the design of a SIW to microstrip transition. The transition is broadband covering the frequency range of 8–12 GHz. The design and interconnection of microwave components like filters, power dividers, resonators, satellite dishes, sensors, transmitters and transponders are further aided by these transitions. A common planar interconnect is designed with better reflection coefficient/return loss (RL) (S₁₁/S₂₂ ≤ 10 dB), transmission coefficient/insertion loss (IL) (S₁₂/S₂₁: 0–3.0 dB) and ultra-wideband bandwidth on low profile FR-4 substrate for X-band and Ku-band functioning to interconnect modern era MIC/MMIC circuits, components and devices.

Two series of metal via (6 via/row) have been used so that all surface current and electric field vectors are confined within the metallic via-wall in SIW length. Introduced aerodynamic slots in tapered portions achieve excellent impedance matching and tapered junctions with SIW are mitered for fine tuning to achieve minimum reflections and improved transmissions at X-band center frequency.

Using this method, the measured IL and RLs are found in concord with simulated results in full X-band (8.22–12.4 GHz). RLC T-equivalent and p-equivalent electrical circuits of the proposed design are presented at the end.

The measurement of the prototype has been carried out by an available low-cost X-band microwave bench and with a Keysight E4416A power meter in the microwave laboratory.

The transition is fabricated on FR-4 substrate with compact size 14 mm × 21.35 mm × 1.6 mm and hence economical with IL lie within limits 0.6–1 dB and RL is lower than −10 dB in bandwidth 7.05–17.10 GHz. Because of such outstanding fractional bandwidth (FBW: 100.5%), the transition could also be useful for Ku-band with IL close to 1.6 dB.

This study aims to propose a unique algorithm-based hysteresis current control technique (HCCT) for induction motor using a single-phase voltage source inverter (SPVSI) to eliminate both sub and inter harmonics (SIH) and electromagnetic interference (EMI). The total harmonic distortion (THD) of the load current also reduces in comparison to standard HCCT and modified technique-based existing HCCT.

Matlab simulation has been carried out to develop an SPVSI model and the unique algorithm-based HCCT. The same platform has also been used to develop a few existing HCCTs such as standard, dual-band and modified. The switching frequency and harmonic analysis of load currents for all the HCCTs have been compared in the paper. The hardware implementation of the proposed algorithm-based HCCT was also verified and compared with the simulation results.

The proposed unique algorithm-based HCCT provides the benefits of both unipolar and bipolar switching techniques. It reduces the switching frequency as unipolar switching scheme and eliminates the EMI. It also reduces THD and nullifies SIH of the load current. This enables an improvement in the overall performance and efficiency of the motor.

This proposed HCCT eliminates the SIH and improves the overall efficiency of the motor, hence can prevent overheating, vibration, acoustic noise, pulsating torque and braking of the rotor shaft of the motor and increasing the reliability of the system.

It can be implemented for the motors that are used in household applications and electric vehicles through one-phase inverter.

This proposed HCCT has detected the zero crossing point of reference current, allowed samples and shifted the necessary amount of hysteresis band at zero crossing region to eliminate SIH and THD.