The rise of hybrid work models has changed traditional employee dynamics, creating new challenges for maintaining engagement and productivity. This study investigates how employee engagement relates to organizational productivity in hybrid workplaces, highlighting the mediating role of communication quality and the moderating impact of leadership style. Using the Job Demands–Resources (JD-R) and Social Exchange theories, the research employs a mixed-method approach. Quantitative data were collected through standardized surveys from hybrid employees across various industries, while qualitative interviews with HR managers provided contextual insights. The results show that employee engagement significantly influences organizational productivity, with communication quality serving as an important mediator. Moreover, supportive and transformational leadership styles strengthen this relationship by fostering trust and collaboration in dispersed teams. The study contributes to the HRM literature by clarifying how engagement mechanisms operate in hybrid contexts and by offering practical guidance for organizations seeking to enhance workforce productivity through engagement-focused strategies.

This study investigates how transformational leadership (TL) fosters innovation and enhances employee effectiveness in Indian organizations navigating digital transformation. Drawing on Social Exchange Theory (SET) and the Resource-Based View (RBV), we propose and test a mediation model where innovation links TL to employee effectiveness. Data were collected from 502 employees across multiple industries and analyzed using Structural Equation Modeling (SEM). Results indicate that TL significantly drives both innovation and employee effectiveness, with innovation partially mediating the relationship. These findings highlight TL’s role in cultivating innovation-friendly climates that enhance workforce adaptability and productivity. The study extends leadership theory to India’s collectivist, hierarchical context, while offering practical implications for leadership development, HR strategy, and digital readiness. By situating TL in the digital age, this research contributes to both scholarly debates and managerial practice.

The lifestyle and fashion retail market in India is expanding rapidly, driven by reasons such as increased disposable incomes, urbanization, and a trend toward branded retail. In addition, several global enterprises are entering the market, and new technologies have been embraced to improve the shopping experience. The Indian lifestyle and fashion retail sector is extremely competitive, with renowned local brands and an expanding presence of foreign retailers. This rivalry is spurred by causes such as the expanding e-commerce industry, shifting consumer preferences, and continued infrastructure and logistics development. While increased rivalry poses issues for certain firms, it also provides opportunity for innovation and expansion throughout the sector. The fashion and retail business in Kolkata has risen significantly as a result of the establishment of fashion and retail outlet stores such as Pantaloons, Reliance Trends, Shoppers Stop, Westside, Max and Zudio. This survey aims to determine which fashion and retail outlets are most popular with Kolkata customers. Furthermore, this study seeks to identify the elements that impact Kolkata customers' perceptions regarding  the efficacy of fashion and lifestyle retail establishments.

Consumer purchase behavior has traditionally been at the center of attention for marketers aiming to create persuasive advertisements and to increase engagement. Conventional survey-based methods, which are still the popular choice, have their limitations in terms of self-report biases and they do not fully measure subconscious reactions that usually influence consumer decisions. Neuromarketing, which is the application of neuroscience to marketing research, is equipped with impartial instruments to determine consumers' responses by physiological and neural measures.  This research is about applying brain science in marketing research, especially the use of EEG and eye-tracking, to figure out if a consumer is going to buy a product. The physiological data of 285 people were studied in order to figure out the relationships between physiological responses and self-reported purchase intent in response to marketing stimuli. The descriptive, correlation, and regression analyses were used to investigate the relationships between the independent variables (type of advertisement and product category) and the dependent variable (purchase intent). According to the findings, both neural engagement, which was assessed through frontal alpha and beta activity, and visual attention, which was gauged through fixation duration and number of fixations, substantially predicted purchase intent with fixation duration being the most powerful predictor. The emotional advertisements produced higher purchase intent than the informational advertisements, and the product category had a moderating effect on these changes. This research shows the potential of EEG and eye-tracking integration in the comprehension of consumer behavior and offers practical suggestions to marketers who want to improve their advertising ‍‌‍‍‌‍‌‍‍‌strategies.

This study examines how service quality dimensions in Indian business schools influence institutional image, perceived value, student satisfaction, and alumni give-back intentions. Using PLS-SEM analysis of data from 536 management students across South Indian states like Telangana, Tamilnadu, Karnataka. The research tests an integrated model linking five service quality dimensions—academic aspects, infrastructure, technology, placements, and industry collaborations—to behavioral outcomes through the Stimulus-Organism-Response framework. Results reveal asymmetric effects: academic aspects, infrastructure, technology, and placements significantly enhance institutional image, while infrastructure, technology, placements, and industry collaborations drive perceived value. Notably, academic quality influences image but not perceived value, whereas industry collaborations show the reverse pattern. Student satisfaction emerges as a crucial mediator, translating institutional image (β=0.167) and perceived value (β=0.091) into give-back intentions. The findings demonstrate that contemporary management students evaluate educational value primarily through employability outcomes and technological sophistication rather than traditional academic metrics alone.

Digital transformation (DT) is fundamentally changing the way businesses work by using new technologies like artificial intelligence (AI), cloud computing, Internet of Things (IoT), and big data analytics in the organizations' systems. While it offers efficiency, innovation, and new value propositions, the traditional firms which are still stuck with the old ways of doing things, have to face cultural resistance, the hardness of the old system, and lack of necessary skills that make the implementation process complex. This paper empirically studies how digital transformation affects business model innovation (BMI) and firm performance (FP) of 312 Indian firms from different sectors such as manufacturing, retail, and services. The research, grounded in the Dynamic Capabilities Theory and the Business Model Innovation framework assesses how the implementation of technology, the flexibility of the organization, the support from the leadership, and the digital competence of the employees can help the organization to achieve the transformation outcomes. The research tools used for data analysis were SPSS 28 and AMOS 26. The evidence obtained through confirmatory factor analysis and structural equation modelling shows that the different aspects of DT have a significantly strong positive impact on BMI, which in turn, is the mediator in the relationship between DT and FP. The organizational flexibility or agility is one of the mediators that only partially mediates these connections, while the obstinacy of the legacy system negatively affects DT’s influence on FP. The results indicate that the digital transformation success is not only a matter of technological integration, but it also requires the organization to be agile and have human capabilities. The research accomplishes the theory goal of linking dynamic capabilities with business model reconfiguration and supplies the actionable insights to the managers and community leaders. In the case of the traditional firms, the way to digital victory is by changing the structures, retraining the workforce, and rejuvenating the strategic intent.

The rapid evolution of employment models in the digital economy has paved the way for alternative talent strategies, notably fractional employment. Tech startups increasingly rely on high-skill, part-time professionals—such as fractional CTOs, CMOs, and legal advisors—to drive strategic decision-making while maintaining financial agility. However, existing research has predominantly focused on gig work, freelancing, and remote employment in lower-skilled contexts (Kässi & Lehdonvirta, 2018), leaving a significant gap regarding the HR challenges associated with managing fractional experts. This study empirically investigates these challenges, with specific attention to onboarding processes, performance evaluation, role integration, legal compliance, and communication barriers. A structured, closed-ended questionnaire was administered to HR professionals in tech startups, targeting key areas where traditional HR practices intersect with the demands of a flexible workforce. The research tests four hypotheses examining the relationships between onboarding, contractual clarity, performance evaluation, integration practices, and overall organizational outcomes. Findings are expected to offer actionable HR strategies that optimize the management of fractional talent and contribute to both HR management theory and practical frameworks for contemporary startup environments.

The role of artificial intelligence (AI) in the digital transformation era's educational landscape and its impact on student achievement has grown in recent years. The proposed study will examine the application of AI-based learning tools by students enrolled in institutions of higher learning and the degree to which these learning tools can affect their performance in terms of efficiency and engagement in learning and overall academic performance. A quantitative and empirical method was used to gather data on 310 students spread across the state of Karnataka using a structured questionnaire. The analysis has used statistical packages such as Pearson correlation, regression and ANOVA to analyse correlation between awareness, adoption, usefulness and ethical issues and institutional support. Research shows that students' academic achievement is positively correlated with their familiarity with and use of AI technologies. Perceived usefulness was a significant factor in determining learning involvement and challenges and ethical issues were observed to be interconnected with each other, and the introduction of AI in the responsible way is a necessity. Also, the institutional support proved to be one of the major predictors of the entrepreneurial success of students in AI-driven ventures. The research finds that AI does not only improve learning experience and interaction, but also innovation and academic performance, assuming the accessibility, ethics, and institutional facilitation is well-handled.