Augmented reality advertising (ARA) is increasingly transforming the digital marketing landscape by enabling immersive and interactive ad experiences for consumers. Grounded in the stimulus–organism–response model and supported by the technology acceptance model, this study examines the Triple E dimensions of ARA—Engagement, Experience and Effect—among Indian consumers. Even with the soaring popularity of ARA, little is known about its influence on consumers. Data were collected from 312 respondents using a structured questionnaire administered and analysed using one-way analysis of variance, Tukey’s post hoc tests and the Friedman rank test. The findings indicate that ARA significantly enhances consumer engagement across demographic groups, improves experiential outcomes such as memorability and ease of understanding, and is positively associated with purchase-related responses, particularly among young consumers. The insights from the study can be used by marketers to design captivating and intriguing ads that will maximise consumer engagement, effects and experience.
This article empirically examines the correlation between firm fundamentals and stock return potential during index rebalancing. The required variables panel format data are derived from Prowess IQ for sample companies within the Nifty 50 index, spanning the period from 2009 to 2023, and transformed into trailing-twelve-month format. In addition to employing company-specific fundamentals as predictors, the study has incorporated market premium and lagged stock returns as independent variables to enhance the model’s prediction accuracy. The high-dimensional fixed effects (HDFE) methodology was employed to assess the relationship between variations in specific variables and stock returns by dividing the data set into pre- and post-inclusion and exclusion intervals, utilising two models of the independent variables—one incorporating current realisations and the other incorporating lagged realisations. The study results reveal intriguing findings that the market risk premium and contrarian effects consistently influence stock earnings during pre- and post-exclusion scenarios. Various factors, including sales, return on equity, returns on capital employed and operating profit margins, demonstrate their significance in fluctuations of stock earnings; however, determining their impact in terms of positive or negative direction during index reorganisation is challenging. A commendable finding of the study is that the constants (error terms) for the exclusion cases produced negative coefficients, while the constants for the inclusion cases delivered positive coefficients. This suggests that additional variables beyond firm-specific fundamentals positively influence stock returns during inclusion and negatively affect them during exclusion. They may pertain to investors’ herd behaviour, positive or negative corporate announcements, mergers or demergers, analysts’ recommendations, or fundamental factors not accounted for in the models. The investment community may utilise the study findings to build suitable investment strategies.
The present study aims to investigate the crucial role played by talent acquisition strategies in shaping employee career pathways, moving beyond the traditional objective of merely filling vacancies. It explores how identifying, hiring and onboarding talent contributes to attracting and aligning individuals with organisational goals while supporting their long-term career growth. The primary aim is to investigate how recruitment strategies impact long-term career development within organisations and how retention strategies promote employee engagement and facilitate upward career progression. Adopting a quantitative and exploratory research design, the article employs text analytics techniques such as word cloud visualisation, text trend analysis and t -SNE ( t -distributed Stochastic Neighbour Embedding) clustering. The findings divulge that talent acquisition strategies extend beyond the hiring phase, significantly influencing employee development and retention. The t -SNE analysis identified three thematic clusters—talent acquisition, employee development and workforce planning—highlighting the strategic and developmental contributions of human resources (HR) practices. The main limitation of the study is that it did not focus on establishing any causal relationships, and its findings are context-specific, limiting generalisability. Despite these limitations, the research offers practical insights for HR professionals seeking to align recruitment strategies with both employee career goals and organisational objectives. This study adds value by providing a fresh perspective on the strategic link between talent acquisition and employee retention, helping organisations formulate future-ready HR strategies.
Artificial intelligence (AI) is transforming the advertising industry by reshaping how content is conceived, personalised and delivered. This study applies the SPAR-4-SLR protocol to systematically review the dual role of AI in advertising, with a focus on comparing generative AI and predictive AI (PAI) and examining their implications for advertising practice, consumer engagement and advertising education. Generative AI facilitates automated creativity through technologies such as deepfakes and personalised ad development, while PAI enhances audience segmentation and sentiment analysis. Based on an analysis of 42 peer-reviewed articles published between 2019 and 2025, the review categorises applications, benefits and emerging challenges. Findings indicate that generative AI improves creative efficiency and personalisation but raises ethical concerns surrounding authenticity, ownership and consumer trust. PAI enhances not only targeting precision and decision-making but introduces issues related to privacy, bias and transparency. The analysis highlights AI’s dual role in enhancing short-term advertising efficiency through personalisation, segmentation and automated creative generation, and in shaping long-term brand outcomes, including trust, loyalty and perceptions of authenticity. The study identifies key thematic clusters: (a) PAI for data-driven targeting and behavioural forecasting, and (b) generative AI for automated content production and creative augmentation. Ethical considerations surrounding transparency, bias, privacy and deepfake-based persuasion emerge as central challenges. The findings underscore the need for updated pedagogical frameworks in advertising education, emphasising AI literacy, ethical reasoning and creative–computational collaboration. This review concludes by outlining an agenda for future research on AI-supported advertising practices and the evolving intersection of machine intelligence, creativity and advertising instruction.
Corporate tax avoidance is arising as a matter of public concern and getting the researchers’ attention continuously. The available literature on corporate tax avoidance has yielded conflicting results, so the current study aims to comprehend, examine and identify the key themes. This study presents an overview of the evolution of tax avoidance literature over time. For this purpose, the relevant literature is extracted from the Scopus database, and, further, VOSviewer and the bibliometrix package (Biblioshiny) of RStudio have been used to do performance and science mapping analysis. After the exclusion of irrelevant articles to the objectives of the study, a total of 1,792 articles have been taken into consideration for final analysis. The finding shows a tremendous rise in publication over time. This article provides an overview of how the literature on corporate tax avoidance has evolved and a synopsis of the most influential authors, most productive countries, keywords analysis, thematic evolution and themes clustering. This study contributes by providing a comprehensive analysis of the tax-avoiding behaviour of corporations.
Mergers and acquisitions (M&A) impact financial performance, but research on bank acquisitions in Slovakia remains limited. This study examines the financial performance of Prima Bank Slovakia JSC before (2009–2015) and after (2016–2022) its acquisition of Sberbank Slovakia JSC, approved by the National Bank of Slovakia in 2017. Using a case study approach, we analyse five key financial indicators: (a) client deposits, (b) loans granted, (c) profitability, (d) interest income and (e) return on equity (ROE). Drawing on secondary data from FinStat, Registry of Financial Statements and annual reports, our findings reveal that Prima Bank’s post-acquisition financial performance improved, influenced by both economic conditions and M&A effects. Unlike previous studies, this research integrates a SWOT analysis to assess the strategic advantages and challenges for both banks. By focusing on a domestic bank acquiring a foreign entity, our study provides valuable insights into M&A dynamics in the Slovak banking sector.
This article investigates how the internet of things (IoT) enhances customer satisfaction across various industries, including healthcare, retail, e-commerce, transportation, logistics and supply chain. A comprehensive literature review was conducted for this study. Leveraging the Scopus database, 45 relevant studies were identified and analysed to address the research questions. The findings confirm that IoT integration significantly optimises business processes, resulting in improved customer satisfaction. However, the review highlights several critical factors that should be carefully considered prior to IoT implementation, such as privacy, security and cost implications, particularly for developing regions. This study offers a comprehensive understanding of IoT’s role in advancing customer satisfaction and provides insights into the responsible integration of IoT into business processes. The findings aim to guide researchers and policymakers in fostering sustainable, customer-centric IoT adoption, thereby shaping the future of IoT technology in enhancing consumer experiences across industries.
The purpose of the article is to address the relationship between digital literacy and women empowerment in Varanasi. Women empowerment is one of the most crucial challenges in India. This study explores how enhanced digital literacy contributes to increased empowerment among women. This study collected the data with authentic and well-developed questionnaires, and the samples size for the analysis consisted of 402 participants. The causal relationship between empowerment through digital literacy is being examined by estimating empirical data through structural equation modelling in SmartPLS. The result of this study found that digital literacy tools and techniques had positive contributions towards women empowerment. Statistical analysis shows that digital literacy has brought significant changes and development to women in economic, social and technological areas.
The Indian Postal Service, one of the world’s largest and most accessible communication networks, is undergoing a significant transformation driven by artificial intelligence (AI) and digital globalisation. This article explores how AI technologies—such as automated sorting, real-time parcel tracking, route optimisation and fraud detection—are enabling India Post to modernise its operations and better serve the growing demands of e-commerce, especially in rural regions. Drawing from internal performance assessments and external case studies, the study reveals that pilot AI implementations have improved classification accuracy by 30% and reduced delivery times by up to 18%. Strategic partnerships with major e-commerce platforms, like Amazon India, further highlight the postal network’s evolving role in last-mile logistics. Additionally, the integration of AI into India Post Payments Bank is expanding financial inclusion, especially in underserved areas. The findings underscore the importance of sustained investment in technology, infrastructure and workforce training to ensure the long-term viability of India Post in a rapidly digitising global economy.
The expanding digital economy now totally relies on artificial intelligence (AI), blockchain, cryptocurrencies and digital payment systems because of their rapid growth. The technological progress has resulted in major security risks and moral problems with AI, along with regulatory difficulties in financial operations. The research applies cybersecurity risk management framework and technology acceptance model to examine security aspects from technical and human behaviour perspectives. The analysis examines worldwide cybersecurity threats that consist of ransomware incidents and fraud and data breaches, together with regulatory actions, which include the EU’s Markets in Crypto-Assets framework and the SEC’s cryptocurrency oversight framework. The study establishes a digital payment security system that combines blockchain identity authentication with AI anomaly detection and quantum-secure encryption. The examination defines ethical challenges related to AI decision systems and privacy protection but supports explainable AI together with multi-tiered governance structures for transparency alongside accountability. Policy study across the United States, the European Union and China identifies the necessity to establish worldwide regulations which maintain innovation versus security equilibrium. The study offers usable directions which aid policymakers as well as financial institutions and technology developers to establish a secure, ethical and resilient digital economy.
The convergence of cybersecurity, financial technology (fintech) and artificial general intelligence (AGI) signifies a major transformation in how digital financial ecosystems operate and are protected. This article critically examines the intersections of these domains and their effects on risk detection, data governance and the delivery of financial services. By synthesising existing literature, empirical data and case-based insights, the study investigates the opportunities and threats arising from the integration of AGI into fintech environments. It also evaluates the effectiveness of current cybersecurity strategies in addressing algorithmic threats and regulatory gaps. The findings indicate that while AGI enhances operational efficiency and threat detection, it also introduces new ethical, technical and governance challenges. This study provides a framework for navigating these complexities and urges stakeholders to adopt adaptive regulatory strategies and interdisciplinary collaboration to ensure security, innovation and trust in the digital financial ecosystem era.
The use of artificial intelligence (AI) in human resource analytics (HRA) has transformed how organisations handle talent acquisition, assess employee performance and manage their workforce. However, the pervasive challenge of embedded prejudices within AI algorithms poses significant ethical, operational and legal concerns. This article examines the challenges of implementing AI-driven HRA, highlighting how biases in training data, algorithm design and decision-making processes can reinforce systemic discrimination. It underscores the importance of transparency, accountability and inclusivity in AI systems to promote fair and equitable outcomes. Additionally, the study investigates strategies for mitigating biases and enhancing the reliability of AI in HR decision-making. By addressing these challenges, organisations can harness AI’s potential while fostering a fair and inclusive workplace environment.
This research examines how user motivations relate to the effectiveness of influencer marketing campaigns. Based on the uses and gratifications theory (UGT), it analyses how five user motivations—seeking information, entertainment, inspiration, self-expression and social interaction—impact consumer engagement, trust, attitudes and intentions to purchase. A quantitative study involving 206 social media users was performed, and the data were examined using correlation, regression and mediation analyses. The results indicate that social interaction and information-seeking are the most significant predictors of user engagement, whereas inspiration greatly improves consumer attitudes and their intention to purchase. Trust somewhat influences the relationship between user motivations and campaign results. The research ends by offering actionable suggestions for brands to create influencer marketing strategies focused on users that address consumers’ psychological requirements, thereby enhancing engagement and promoting favourable brand attitudes.
This study explores the integration of artificial intelligence (AI) in the Indian stock market, focusing on its impact on equity trading and investment decisions. The research adopts a mixed-methods approach, utilising surveys and interviews to analyse traders’ profiles, social media influence and the effectiveness of AI-driven tools. Findings reveal that most traders are young investors allocating less than 25% of their portfolios to equities. Social media platforms, particularly Telegram and Instagram, play a significant role in shaping investment decisions, with stock analysis and recommendations being the most consumed content. AI tools, such as stock screeners and financial news aggregators, have moderately improved decision-making efficiency, though concerns regarding their reliability persist. The study underscores the need for enhanced educational initiatives for traders, improved AI tool functionality and stricter regulatory frameworks to ensure transparency and trust in AI-driven trading. By addressing these challenges, stakeholders can harness AI’s potential to foster a more efficient and competitive financial ecosystem in India.
The convergence of artificial intelligence and startups has become a key area of research, spurring innovation and transforming the entrepreneurial environment. This study aims to provide an in-depth insight into the intellectual structure and evolution of this dynamic field in the Web of Science database from 2015 to 2025 using Biblioshiny (R studio) and VOSviewer. By employing bibliometric techniques, such as performance analysis and science mapping, it reveals a significant increase in academic and practical interest in artificial intelligence (AI)-driven startups, with an annual growth rate of 28.73% and a peak of 106 publications in 2024. The analysis highlights the leading contributions from authors, institutions and countries, with China, the USA and Italy emerging as key research hubs. The work of Warner and Wäger on digital transformation emerges as the most influential, underscoring the strategic renewal within the AI–startup ecosystem. The thematic analysis showcases a transition from early studies on AI implementation in startups to more advanced themes, such as AI-driven business models, digital transformation, big data analytics and entrepreneurial orientation. Emerging themes, including sentiment analysis and open innovation, alongside foundational areas such as big data analytics and competitive advantage, outline critical pathways for advancing research and practical applications in this field.
Over the past few decades, China has emerged as a dominant force in global manufacturing, producing large shares of key products, such as personal computers, mobile phones and electric vehicles. Along with this production boom, Chinese multinational enterprises (CMNEs) have aggressively pursued cross-border mergers and acquisitions to secure strategic assets in developed countries. This mirrors Japan’s global expansion in the 1970s and the 1980s, raising concerns regarding the strategic motives behind China’s growing influence. This study examines the strategic asset-seeking behaviour of CMNEs, focusing on the case studies of Lenovo and Haers. It uses a framework that integrates the strategic intent view with the resource-based view to explore two key questions: What are the strategic intents of CMNEs behind their strategic asset seeking and acquisition? How are cross-border strategic asset acquisitions used to propel CMNEs towards their strategic intent? The findings offer insights for Western companies into the long-term objectives of CMNEs and the strategies employed to achieve their strategic intents, enabling them to respond strategically rather than tactically. Moreover, emerging market firms can acquire valuable lessons from this research, including best practices for strategy development and resource utilisation, while being aware of the potential risks of associating Western brands with products from emerging markets.
Competencies of an individual are very important for performing their jobs efficiently and effectively. They help in determining the performance level of the employees. The study identifies the differential competencies of healthcare employees—nurses and doctors—and analyses their impact on patient satisfaction. Primary data have been collected from the patients to understand their perception with regard to employees’ competence. The regression analysis results suggested certain competencies of the nurses had a significant and positive impact on the patient satisfaction, whereas certain other competencies of the doctors had a significant impact on patient satisfaction. The regression analysis conducted separately for the doctors and nurses suggests some other findings which have been discussed in detail in the study. The findings of the study are expected to help the HR professionals in the healthcare units identify the areas of improvement for the nurses and doctors and plan the training and developmental programmes accordingly to bring patient satisfaction.
This study explores how people-focused values—diversity, equity, inclusion and belongingness—influence digital transformation and business innovation. Data were collected from 386 people working in various businesses. The results show that equity (fair treatment), inclusion (involving everyone in decision-making) and belongingness (feeling part of the team) have a strong positive impact on how businesses use digital technologies. However, diversity by itself did not have a major effect. The study also found that when companies go through digital transformation, it leads to better innovation and new ideas. To study these relationships, advanced tools such as structural equation modelling and confirmatory factor analysis were used. These results highlight that companies that treat employees fairly, include their opinions and help them feel connected are more likely to succeed in adopting digital tools and staying innovative. This research offers useful insights for both scholars and business managers, showing how people-centred values can drive digital and innovative success in a competitive world. It encourages companies to focus on fairness, inclusion and belonging to stay ahead.
This research article presents an econometric analysis examining fiscal components of India and their influence on the gross domestic product (GDP). The study’s objectives encompass measuring growth rates of fiscal components and GDP, determining causality between them and assessing the specific impact of government receipt and expenditure components on GDP growth. Methodologically, the analysis employs various statistical techniques, including year-over-year and Compound Annual Growth Rate calculations, descriptive statistics, Pearson correlation coefficient, Augmented Dickey–Fuller test, Granger causality test and regression analysis. Findings indicate that interest payments and capital outlay positively affect GDP, while subsidies and capital receipts have negative impacts. Additionally, lagged GDP demonstrates a significant positive relationship with current GDP. The regression model exhibits substantial explanatory power, though positive autocorrelation in residuals suggests scope for improvement. Implications extend to policymakers and investors, offering empirical insights for formulating effective fiscal policies and making informed investment decisions.
As Generation Z (Gen Z) becomes an increasingly influential demographic in the beauty and personal care market, understanding their attitudes and behaviours is crucial for industry stakeholders. Brands and e-commerce platforms need to adapt to the preferences of this generation by enhancing their digital presence, fostering trust and championing ethical and sustainable practices. Using behavioural reasoning theory, this study focuses on understanding the attitudes and preferences of Gen Z consumers towards Indian beauty and personal care websites, a demographic known for its tech-savvy nature and unique consumer behaviour. Preliminary findings reveal that Gen Z consumers exhibit a strong affinity for online shopping, with convenience and a wide product selection being the primary driving factors. This research contributes to the body of knowledge on Gen Z consumer behaviour, offering insights that can guide strategies in the ever-evolving beauty and personal care industry. In conclusion, this study provides a comprehensive examination of Gen Z consumers’ attitudes and preferences towards Indian beauty and personal care websites, shedding light on the factors that influence their online shopping choices and the challenges they encounter.
