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Banking sector is an important subset of any economy and plays a very crucial and significant part in its growth and development. The expansion and credibility of banking sector is attributed to the fact that it caters to the financial needs and accordingly provides customised solutions for the people at large. The new millennium has witnessed metamorphosis in the banking sector. The pace and trend of transformation is all set to accelerate in the coming decade. The process of Liberalisation, Privatisation and Globalisation Model (LPG Model) banking practices which being unleashed a few decades back will reach to greater heights as we step into the next decade. The innovative technology has brought about a paradigm shift in all aspects of banking like routine operations, transactions, products and processes, delivery of services in terms of various e-channels, credit administration and credit management, audit and compliance and Fin-Techs partnership. Digital transformations in the banking sector have received much needed thrust because of ‘The Digital India Moment’. The current study attempts to highlight the role of technology in banking and how technology-led innovations and initiatives will determine the business of banking as a whole. The significance of these technology-driven innovations and transformations is that they put both banker and customer in a win-win situation as drawn from existing literature related to financial institutions. The focus is on investigating the digital innovations adopted by the different banks both public and private to understand the economic structural changes resulted out of it.

This study aims to examine the roles of minimalist and citizenship behaviors in influencing sustainable tourism practices. It further examined the role of moral credit as a mediating factor in these relationships. Additionally, this research scrutinizes the moderating effects of age and gender on these behavioral influences.

This study used a descriptive, quantitative and cross-sectional design to examine the data of 451 tourists visiting three destinations in India. The proposed conceptual model was evaluated through partial least squares structural equation Modeling, and the impact of the control variables was examined via PLS-Multi Group Analysis.

The results confirmed that minimalist and citizenship behaviors significantly influence pro-environmental actions. Moral credit has emerged as a pivotal bridge between these behaviors and sustainable tourism practices, underscoring its mediating role. Additionally, the analysis revealed that age and gender substantially moderated these relationships, highlighting the demographic-specific dynamics.

This study provides novel insights into how behaviors such as minimalism and citizenship contribute to sustainable travel practices. The identification of moral credit as a key mediator, along with the demographic nuances of age and gender, offers unique perspectives on sustainable consumer behavior dynamics within tourism. These findings provide valuable directions for stakeholders in sustainable tourism and policymakers aiming to cultivate positive consumer behaviors and advance the sustainability of the sector.

This study explores how the battle against the COVID-19 pandemic highlights the tourism industry's vulnerabilities and consequently leads to a paradigm shift towards adaptability, digitalization, diversification and closer collaboration with governmental and international entities. It encompasses a diverse range of industry involved parties, examining the responses and adaptations of various tourism entities to the pandemic's challenges. Through qualitative data analysis, including network analysis and word clouds, this study furnishes viable strategies that emphasize cultural sensitivity, environmental stewardship, technological integration, conservation-focused tourism and public–private partnerships. The study identifies key forthcoming challenges, including the standardization of environmental impact assessments, the promotion of eco-certifications, responsible tourism initiatives and the ethical treatment of wildlife, which will shape the future trajectory of sustainable tourism.

This study aims to investigate the relationship between political instability and the performance of Islamic banks in emerging countries.

For a data sample of 93 Islamic banks in 20 emerging countries during the period from 2011 to 2016, the authors identify indicators that matter most for the activities of Islamic banks.

The study finds that a stable government and law and order are positively correlated with the health of Islamic financial institutions. On the other hand, corruption and military involvement in politics can create an unstable environment for businesses, leading to uncertainty and risk. The study also reveals that Islamic banks operating in regions or communities with lower risk of socio-economic conditions tend to exhibit higher levels of profitability.

Overall, the study provides valuable insights into the impact of political instability on Islamic banks in emerging countries.

In this study, the central objective is to foresee stock market signals with the use of a proper structure to achieve the highest accuracy possible. For this purpose, three hybrid models have been developed for the stock markets which are a combination of support vector machine (SVM) with meta-heuristic algorithms of particle swarm optimization (PSO), imperialist competition algorithm (ICA) and genetic algorithm (GA).All the analyses are technical and are based on the Japanese candlestick model.

Further as per the results achieved, the most suitable algorithm is chosen to anticipate sell and buy signals. Moreover, the authors have compared the results of the designed model validations in this study with basic models in three articles conducted in the past years. Therefore, SVM is examined by PSO. It is used as a classification agent to search the problem-solving space precisely and at a faster pace. With regards to the second model, SVM and ICA are tested to stock market timing, in a way that ICA is used as an optimization agent for the SVM parameters. At last, in the third model, SVM and GA are studied, where GA acts as an optimizer and feature selection agent.

As per the results, it is observed that all new models can predict accurately for only 6 days; however, in comparison with the confusion matrix results, it is observed that the SVM-GA and SVM-ICA models have correctly predicted more sell signals, and the SCM-PSO model has correctly predicted more buy signals. However, SVM-ICA has shown better performance than other models considering executing the implemented models.

In this study, the data for stock market of the years 2013–2021 were analyzed; the long length of timeframe makes the input data analysis challenging as they must be moderated with respect to the conditions where they have been changed.

In this study, two methods have been developed in a candlestick model; they are raw-based and signal-based approaches in which the hit rate is determined by the percentage of correct evaluations of the stock market for a 16-day period.

This study attempts to analyze the overall effectiveness of Lean System (LS)-based India post facility layout design (FLD) selection.

We have grouped all Lean Six Sigma elements into three different categories: Lean Technical Practices, Lean Workplace Environment Practices, and Lean Ergonomics Practices based on literature support and field surveys in the Indian postal service. Further, it employs a mathematical model known as the graph theory (GT) method. From the GT approach, interactions were identified through LS tools represented through the digraph, matrix model approach. This study was directed at the National Sorting Hub in Mysuru, Karnataka, in the southern part of India. A number of insights were given in the GT area where FLD is possible to evaluate.

The results showed that Layout five has the highest value, followed by Layout one from the GT approach. The relative relevance and effect values are given as inputs to the permanent function in the digraph technique, and an evaluation index is obtained as an output.

When solving any optimization issue with a high number of attributes, the digraph and matrix technique is successful. The layouts that have been identified have yielded valuable insights into how to enhance critical decision-making processes, which are necessary to accomplish company strategic objectives like growing postal business services.

The process operations carried out in India post service as well as its heterogeneity of articles and the intangible measures of production are the significant challenges to keenly analyze the layout design through lean service principles.

Despite the growing interest in blockchain technology (BCT) applications in the agri-food industry, evidence of their economic and strategic implications remains scarce. This study aims to contribute to filling this gap by jointly investigating how BCT adoption affects transactional relationships, and how it contributes to the firm’s strategic resources.

An explanatory case study is conducted based on a theoretical framework grounded on transaction cost economics and the resource-based-dynamic capabilities view. Six BCT implementations by agri-food firms are studied. Data were collected through semi-structured interviews and analysed using thematic analysis.

Findings reveal that BCT benefits depend on how companies integrate technology across their supply chains. In fact, the results suggest that overall transaction efficiency within the supply chain is enhanced only for those firms prioritising stakeholder engagement during technology implementation and leveraging existing trust relationships with economic agents. Moreover, the results suggest that BCT is not yet perceived as a strategic resource, but rather that it has the potential to enhance firms’ operational-adaptive, absorptive and innovative capabilities. When all supply chain actors clearly understand blockchain’s functionality and value, the development of these capabilities becomes more pronounced.

The study identifies two BCT adoption configurations. One primarily focuses on enhancing supply chain efficiency and transparency (dynamic BCT), while the other uses BCT mainly for marketing purposes (static BCT). These configurations lead to varied possibilities for leveraging BCT’s potential advantages. Furthermore, they show how a mismatch between a strategic approach and its chosen configuration could work against any positive impact and lead to disillusionment with the BCT. Thus, managers should assess carefully the impact of such different configuration choices on performance.

To the best of the authors’ knowledge, this is the first study to attempt to analyse the economic implications of adopting BCT in the food sector from both a firm and supply chain perspective. Additionally, it shows how interpreting these impacts is contingent on the diverse modalities for embedding BCT into existing supply chains.

The purpose of this paper is to develop a more comprehensive understanding of the consequences of retaliations and our evidence indicates that retaliations are beneficial for firms with supranormal earnings by making their higher earnings more persistent, but harmful for firms with subnormal earnings by slowing the recovery of their earnings.

This paper use annual Compustat files based on Fama-French 48 industry. The time-varying competitive reactions (CRs) for each firm are captured using quarterly rolling-window estimation across 41 windows with five years (i.e. 20 observations) in each window. This paper measure earnings persistence as the slope coefficient (ß1) from regressing future earnings on current earnings. The result remains qualitatively similar to the main findings when alternative measures of earnings persistence.

Abnormal earnings are expected to dissipate in the long run owing to competitive forces, but this paper show that more retaliatory CRs increase earnings persistence. This is good news for supranormal firms as they can sustain high profitability. However, it will be harder to revert subnormal earnings to the industry mean if such firms conduct more retaliatory CRs. This paper also show that these associations are stronger for less competitive industries.

First, high earnings persistence per se would not be a major consideration in the firm’s strategic decisions but a natural by-product of such decisions spanning an extended period of operations. Second, though this paper focus on the period of 2004–2018 that includes the rebound after financial crisis in 2008, an extension of the observation period over a longer economic cycle would verify our results.

CRs are regarded as an evolving portfolio of dynamic marketing decisions and tools for strategic decisions in our study. It helps how firms manage competition over time to lengthen the superior performance. Also it helps the low-profitability firms attempting to improve profitability by showing nonretaliation may be a more appropriate strategy than retaliation.

Firms in financial distress suffer from illiquidity, survival of firms is contingent on meeting their financial obligations, thus need for turnaround decisions. However, retaliations under financial distress can mitigate the effect of such turnaround decisions and thereby aggravate the situation.

Greater persistence extends the benefits of superior earnings, thus increasing the opportunities for value exploitation, but it may also restrict earnings recovery. This paper finds that the way that firms react within the competition explain the differences in earnings persistence. Although a large body of research has examined the static drivers (e.g. firm size and diversification) of the differential persistence of earnings, there has been little research on dynamic drivers that explicitly recognize the erosion process for earnings.

The home page design of a digital news website is a key factor in determining its attractiveness to readers. This study aims to propose an approach to manage the frequent adjustment of the dynamic layout of the news content on the website home page in a real-time environment to increase its attractiveness to readers.

This paper shows that this news website layout design problem can be modeled as an optimization problem based on the information of news contents that change within a multiple-period planning horizon similar to the dynamic facility layout problem. A hybrid genetic algorithm-based approach integrated with local search heuristic methods is also proposed to improve the solution.

This paper finds that the DPLP model is effective in modeling the changing layout of a digital news website. The problem can solved in a timely manner using the proposed hybrid genetic algorithm.

This paper was based on hypothetical data and on the assumption of equal section size. Actual data would help fine-tune the application of the dynamic facility layout model. As well the algorithm could be enhanced for unequal size sections.

The model should help online newspapers apply sophisticated algorithms to optimize the layout of news websites dynamically in a timely manner.

News websites are increasingly the desired medium to consume news. So it has an important role in educating society. Thus optimizing and improving the process will help in this regard.

To the best of the authors’ knowledge, this paper is the first one to apply the DPLP model to the digital newspaper website dynamic design problem.

This chapter reviews the Metaverse’s inception and digitalization’s impact on the fashion and apparel retail industry. This review demonstrates how digital clothing rooted in the Metaverse assists industry environmental sustainability, the planet, and consumers, providing business strategies for growth through research in theory and an analysis of practices. Virtual checkout uses digital tools to help marketers and designers better understand their target audience. In the foreseeable future, the Metaverse of our works will be a well-known and safe space for budding designers. Designers will find it much simpler to bring their concepts to life thanks to the immediate relationship that Metaverse technology creates with humans.

Eco-friendly methods and technology found in the Metaverse will transform the industry. Expanding acceptance of Metaverse could lead to a 97% decrease in the amount of carbon dioxide in approximately per item 4,000 L of water, reducing its carbon footprint by around thirty percent during the company’s design and development phases.

Digital apparel may be extremely helpful leading up to the real physical manufacturing of a garment, applied to sampling, marketing and modeling prior the actual variants are put into manufacturing, significantly lowering the environmental impact of a clothing item’s entire lifecycle. Computer-generated representations of clothing cannot replace real garments entirely, and they can help reduce waste and help address overproduction-related difficulties.

This chapter clarifies how digital fashion based on the Metaverse assists business environmental sustainability, users, and acts as a resource to improve approaches.