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This study aims to provide a scientific framework for the selection of suitable substation technology in an electrical power distribution network.

The present paper focuses on adopting an integrated multi-criteria decision-making approach using the Delphi method, analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS). The AHP is used to ascertain the criteria weights, and the TOPSIS is used for choosing the most fitting technology among choices of air-insulated substation, gas-insulated substation (GIS) and hybrid substation, to guarantee educated and supported choice.

The results reveal that the GIS is the most preferred technology by area experts, considering all the criteria and their relative preferences.

The current research has implications for public and private organizations responsible for the management of electricity in India, particularly the distribution system as the choice of substations is an essential component that has a strong impact on the smooth functioning and performance of the energy distribution in the country. The implementation of the chosen technology not only reduces economic losses but also contributes to the reduction of power outages, minimization of energy losses and improvement of the reliability, security, stability and quality of supply of the electrical networks.

The study explores the impact of substation technology installation in terms of its economic and environmental challenges. It emphasizes the need for proper installation checks to avoid long-term environmental hazards. Further, it reports that the economic benefits should not come at the cost of ecological degradation.

The present study is the first to provide a decision support framework for the selection of substation technologies using the hybrid AHP-TOPSIS approach. It also provides a cost–benefit analysis with short-term and long-term horizons. It further pinpoints the environmental issues with the installation of substation technology.

The presence of random noise as well as narrow band coherent noise makes the structural health monitoring a really challenging issue and to achieve efficient structural health assessment methodology, very good extraction of noise and analysis of the signals are essential. The purpose of this paper is to provide optimal noise filtering technique for Lamb waves in the diagnosis of structural singularities.

Filtration of time-frequency information of multimode Lamb waves through the noisy signal is investigated in the present analysis using matched filtering technique and wavelet denoising methods. Using Shannon’s entropy criterion, the optimal wavelet function is selected and verification is made via the analysis of root mean square error of filtered signal.

The authors propose wavelet matched filter method, a combination of the wavelet transform and matched filtering method, which can significantly improve the accuracy of the filtered signal and identify relatively small damage, especially in enormously noisy data. Correlation coefficient and root mean square error are additionally computed for performance evaluation of the filters.

The present study provides detailed information about various noise filtering methods and a first attempt to apply the combination of the different techniques in signal processing for the structural health monitoring application. A comparative study is performed using the statistical tool to know whether filtered signals obtained through three different methods are acceptable and practicable for guided wave application or not.

The real challenge in the solution of contact problems is the lack of an optimal adaptive scheme. As the contact zone is a priori unknown, successive refinement and iterative method are necessary to obtain a high-accuracy solution. The purpose of this paper is to provide an optimal adaptive scheme based on second-generation finite element wavelets for the solution of non-linear variational inequality of the contact problem.

To generate an elementary multi-resolution mesh, the authors used hierarchical bases (HB) composed of Lagrange finite element interpolation functions. These HB functions are customized using second-generation wavelet techniques for a fast convergence rate. At each step of the algorithm, the active set method along with mesh adaptation is used for solving the constrained minimization problem of contact case. Wavelet coefficients-based error indicators are used, and computation is focused on mesh zones with a high error indication. The authors take advantage of the wavelet transform to develop a parameter-free adaptive scheme to generate an appropriate and optimal mesh.

Adaptive wavelet Galerkin scheme (AWGS), a newly developed method for multi-scale mesh adaptivity in this work, is a combination of the second-generation wavelet transform and finite element method and significantly improves the accuracy of the results without approximating an additional problem of error estimation equations. A comparative study is performed taking a solution on a highly refined mesh and results are generated using AWGS.

The proposed adaptive technique can be utilized in the simulation of mechanical and biomechanical structures where multiple bodies come into contact with each other. The algorithm of the method is easy to implement and found to be successful in producing a sufficiently accurate solution with relatively less number of mesh nodes.

Although many error estimation techniques have been developed over the past several years to solve contact problems adaptively, because of boundary non-linearity development, a reliable error estimator needs further investigation. The present study attempts to resolve this problem without having to recompute the entire solution on a new mesh.

The real challenges in online crack detection testing based on guided waves are random noise as well as narrow-band coherent noise; and to achieve efficient structural health assessment methodology, magnificent extraction of noise and analysis of the signals are essential. The purpose of this paper is to provide optimal noise filtering technique for Lamb waves in the diagnosis of structural singularities.

Filtration of time-frequency information of guided elastic waves through the noisy signal is investigated in the present analysis using matched filtering technique which “sniffs” the signal buried in noise and most favorable mother wavelet based denoising methods. The optimal wavelet function is selected using Shannon’s entropy criterion and verified by the analysis of root mean square error of the filtered signal.

Wavelet matched filter method, a newly developed filtering technique in this work and which is a combination of the wavelet transform and matched filtering method, significantly improves the accuracy of the filtered signal and identifies relatively small damage, especially in enormously noisy data. A comparative study is also performed using the statistical tool to know acceptability and practicability of filtered signals for guided wave application.

The proposed filtering techniques can be utilized in online monitoring of civil and mechanical structures. The algorithm of the method is easy to implement and found to be successful in accurately detecting damage.

Although many techniques have been developed over the past several years to suppress random noise in Lamb wave signal but filtration of interferences of wave modes and boundary reflection is not in a much matured stage and thus needs further investigation. The present study contains detailed information about various noise filtering methods, newly developed filtration technique and their efficacy in handling the above mentioned issues.

Purpose: This chapter aims to identify and evaluate the various components of business model disclosures in an Integrated Report and ascertain how the notion of business model is perceived among practitioners.

Need for the Study: According to previous research, the International Integrated Reporting Council’s (IIRC) objective of improving corporate reporting by encouraging organisations to disclose their business model has not found the desired recognition. Therefore, the study elaborates on the various components of business model reporting and their implications on corporate reporting in general.

Methodology: A review of literature was conducted to identify and analyse research based on business models and their disclosures in integrated reporting. A narrative review was undertaken for selected literature.

Findings: The findings suggest that most large-sized organisations use integrated reporting for impression management and are not inclined to disclose too much about their business models for fear of competition. There is still a lack of clear understanding of what a business model should entail.

Practical Implication: This study adds to the research on business model disclosures in integrated reporting. Voluntary disclosure and a better understanding of such disclosures will prepare organisations of all sizes and industries for an event when Integrated Reporting becomes statutory.

This paper aims to underscore how the digitization of content and the convergence in the telecommunications sector has prompted a wave of consolidation between telecom and content players.

Using interdisciplinary insights from competition policy and business strategy, the paper draws attention to the interplay between business model innovation and merger control in the converged telecoms sector.

Technological innovation and business model innovation led to the emergence of over-the-top (OTT) services. This innovation in turn led to two key effects, first, successful commercialization of content and the emergence of the “smart pipes” that in turn has led to the second effect, which is increased mergers and acquisitions (M&As) in the converged telecommunications sector. Emergence of OTT with big data as a key advantage challenged the strategy and business models of the more established players, such as the AT&T, Time Warner, Liberty Global and Fox, which in turn led to the current trend of M&As in the sector.

This paper makes the following key contributions to the literature on M&As between the fixed/mobile and content players. First, it elucidates how the existing market players can benefit from competition policy, such as merger remedies to enter new and related markets. Second, it advocates that the US and the European competition authorities while assessing these M&As, take due account of innovation in business models, as business model innovation not only promotes innovation in the market but also enhances consumer welfare, considering that it offers the merged firm economies of scale and scope to offer better-quality goods and services at subsidized prices.

Heritage tourism is an increasingly popular form of tourism that allows individuals to connect with the past and immerse themselves in cultural and historical narratives. Hence, the purpose of this study is to explore the intricate relationships among vicarious nostalgia (VNOS), memorable tourism experiences (MTEXs) and their collective influence on tourists’ behavioral intentions (BINTs). Additionally, this study examines the moderating effect of social return (SN) in the context of heritage tourism.

Data were gathered using a self-administered questionnaire from 259 tourists visiting heritage sites in Jaipur. The proposed model was tested using structural equation modeling.

The results confirmed that VNOS had a significant positive impact on BINT in the context of heritage tourism. The causal relationship between VNOS and BINT was fully mediated by MTEX. The results further verified that the presence of SN strengthens the association between MTEXs and BINT.

This research will guide the firms associated with heritage tourism to target specific cohorts interested in heritage tourism. Policymakers may find it easier to create unique offerings and packages that appeal to visitors interested in historical sites and produce memorable travel experiences. One key implication is to create “social media friendly spaces” at different locations of the sites. To increase tourism, managers may use the findings from this research to create plans for the ethical promotion and protection of cultural and natural heritage sites.

Overall, this research advances the understanding of the role of VNOS in heritage tourism by elucidating its cognitive and emotional aspects and their subsequent influence on the memorability of tourist experiences and BINT s. Additionally, by considering the moderating effect of SN, this study provides a comprehensive view of how these factors collectively shape tourists’ decisions and actions in the context of heritage destinations. This research has been conducted in the heritage city of Jaipur (North-Western India), which, surprisingly – despite its popularity as a heritage tourism site – has not been sufficiently explored in the scholarly research.

All aspects like finances, marketing strategy, competitors, etc. have been taken into account to provide the readers a complete and realistic image about the working, decisions and their outcomes for boAt. Secondary data has been used from blogs, company website and other sources in this study.

This case presents boAt’s growth in the Indian market because of India’s exponentially growing customer base in the tech and audio industry. This case brings to light all the factors considered and the business decisions to be made while growing in the market. The challenges faced by boAt after they entered the market and the company’s business decisions to overcome these challenges are also discussed. This case provides an opportunity for students to understand the dynamics associated with expanding in a competitive market to maintain growth and maximize profits.

This case is suitable for undergraduate and postgraduate students and can be used for courses in strategy, marketing, entrepreneurship and business management.

The exponential rise of digital payments has underscored the critical importance of digital payment security, particularly in payment gateway systems. This chapter delves into the vulnerabilities within these systems and proposes a comprehensive security enhancement framework to address them. Recent security breaches, such as those at SONY and Ontario’s birth registry, have emphasised the urgent need for improved protective measures. The proposed framework integrates advanced technologies like data encryption, next-generation firewalls (NGFWs), unified threat management (UTM), network traffic analysis, and multi-factor authentication (MFA). It aims not only to defend against current cyber threats but also to remain adaptable to future vulnerabilities, ensuring the integrity, confidentiality, and availability of transactional data. Moreover, aligning with regulatory standards such as the Payment Card Industry Data Security Standard (PCI DSS) and the General Data Protection Regulation (GDPR) is crucial for building trust and ensuring security in the digital transaction ecosystem. This chapter also highlights the importance of balancing security measures with user experience and advocates for user education and user-centric security solutions. Emerging technologies like artificial intelligence (AI) and blockchain are proposed for real-time fraud detection and maintaining immutable transaction records, offering innovative solutions to contemporary security challenges. Empirical analysis supports the efficacy of the proposed framework, showing improvements in data loss prevention, user satisfaction, and fraud mitigation. This framework, termed ‘Guardians of Trust’, represents a paradigm shift in payment gateway security, providing a scalable and forward-looking model that balances robust security protocols with user experience and compliance considerations. This chapter contributes significantly to the academic discourse on digital payment security.