Jaipuria Institute of Management

An essential role in any firm is human resource management, or HRM, with effective matching of employees to suitable positions remaining the main employment issue. Traditional methods often rely on simplistic data models, which fail to fully capture the complex relationships between employee attributes, job requirements, and performance outcomes. To overcome these issues, this manuscript is proposed. This manuscript presents a novel approach, Hierarchical Dilated Parrot Causal Convolutional Attention Networks (HieDil-P2CAN), designed to enhance human resource recommendations. The input dataset, titled “human resource recommendations,” contains synthetic employee data generated for comprehensive HR analysis. Preprocessing is performed using the Fuzzy Min–Max Neural Network. The technique creates regular presentations of data that are easy to understand. Feature extraction is achieved through the Q-value Regularized Transformer, which captures the critical attributes influencing job matching. The prediction phase employs the HieDil-P2CAN, integrating Dilated Causal Convolution Networks with Hierarchical Attention Models and optimized using the Parrot Optimizer to effectively predict and recommend the best human resource solutions. The framework demonstrates an impressive 99.4% accuracy, optimizing human resource recommendations by accurately matching employees to suitable jobs based on their skills and performance metrics. This results in improved employee satisfaction and organizational efficiency. The system also significantly reduces computational time and enhances the precision of HR decision-making processes.

Purpose This study aims to examine the increasing role of religious identity in influencing retail brand dynamics and to incorporate a hybrid review by summarising current information on the role of religiosity in consumer behaviour and brand relationships, charting significant themes, theories, contexts, constructs and methods in the literature. Design/methodology/approach A hybrid review was used, along with a systematic literature review, BERTopic and bibliometric analysis. The Theory–Context–Characteristics–Method (TCCM) framework was used to categorise literature into six primary thematic areas, while the Antecedents–Decisions–Outcomes (ADO) model explains the impact of religious identity on consumer behaviour and retail brand dynamics. Findings This study identifies six prevailing themes: religious influence on marketing ethics and consumer behaviour; faith-based and Islamic branding strategies, religion in advertising and messaging, religiosity and purchase behaviour, religious sentiment in tourism and community outreach and social identity and communication in religious communities. Notable gaps include overreliance on quantitative techniques, insufficient theoretical heterogeneity and lack of qualitative and longitudinal studies. The ADO model explains how religious identity shapes consumer behaviour, brand meaning and retail experiences. The study develops seven theory-driven propositions that explain underexplored linkages between religiosity, decision processes and retail brand outcomes. Originality/value This hybrid review integrates bibliometric, SLR and topic-modelling methods to investigate the topic of religious identity in retail branding. This study contributes in developing seven actionable and testable propositions grounded in the TCCM and ADO frameworks, which offer a structured agenda for future research. Results indicate growth in religion-based retail studies after 2010, particularly in India, Saudi Arabia, the UK and Malaysia, with emphasis on Islamic marketing, halal consumption and faith-based finance. While rising, other areas such as digital and gendered religiosity are underexplored and require more in-depth qualitative, cross-cultural and intersectional research.

Digital marketing today is shaped by automated decision systems and data-driven personalization, which expand customer engagement but also amplify intrusions into private and professional spaces. This chapter introduces marketer behavior as a lens to study how professional intentions and practices affect digital consumer experience. Moving beyond technical and consumer-centric analyses, it highlights marketer agency in strategies that alternate between value creation and intrusive persistence. A conceptual framework is proposed to classify marketer behavior by ethical orientation and intrusiveness, supported by an ethical calibration index to assess autonomy, transparency, and contextual sensitivity. The discussion critiques current tendencies and advances responsible digital engagement by promoting ethical accountability. It argues that enduring loyalty depends not on predictive precision alone but on evolving ethics of marketer conduct that are aligned with consumer trust.

Digital transformation enhances sustainability in public sector pharmaceutical supply chains by optimizing sources, improving traceability, and promoting circular economy principles. This research converges on the circular economies principles to transform the Indian public sector pharmaceutical supply chains for flexibility by a mixed method approach. This study uses the Technology-Organization-Environment (TOE) Framework integrated with a Delphi study to identify and prioritize the key enablers of digital transformation and circular economy principles to enhance supply chain flexibility in the Indian public sector pharmaceutical services. The relative importance of each identified enablers was measured using the best worst method to confirm focused resource allocation and strategic prioritization for optimal impact in public sector pharmaceutical services. The study further uses the Bayesian network approach to determine the most prominent enabler of digital transformation and circular economy principles, which enhance supply chain flexibility in the Indian public sector pharmaceutical services. This research highlights that technology-driven investments enhance supply chain flexibility, supplier collaboration is critical for continuous circular economy transitions, and strong regulatory policies are needed for effective adoption. These insights provide policymakers and practitioners with a comprehensive framework to drive sustainable transformation and operational excellence in the public sector pharmaceutical sector services. • Mixed methods integrate TOE & Delphi to identify and classify digital transformation & circular economy enablers in pharma SCs. • The Best-Worst Method evaluates the strategic prioritization of each enabler in public pharma services for better SCF. • Bayesian analysis reveals tech investments and supplier collaboration as key enablers for sustainable change. • Strong regulatory frameworks drive effective adoption of circular economy practices in public pharma services.

Generative AI can enhance venture creation education, yet faculty adoption remains limited. This study explores why through a three-stage mixed-methods approach. Stage 1 reviewed 2020–25 literature to identify 23 barriers across pedagogical, technical, institutional, and ethical domains. Stage 2 involved interviews with experienced entrepreneurship educators, refining and reducing the list to 15 context-specific challenges. Stage 3 used a fuzzy-DEMATEL survey to capture expert causal judgments, while thematic coding of interviews added narrative depth. The resulting influence map highlights a clear hierarchy: lack of staff training, unclear governance, and weak technical support are key upstream barriers, while concerns like plagiarism and over-reliance are downstream effects. Cluster analysis groups drivers into pedagogical, organisational, and infrastructural clusters, suggesting a phased response: begin with training and transparent policy, then invest in tools and assessments.

Purpose Consumer behaviour has changed dramatically with the digital revolution, especially in the alcoholic beverage industry, in which the online alcohol purchase (OAP) platforms become very popular. This study aims to examine the app-based antecedents (smartphone satisfaction, app usefulness and app aesthetics) on continuance intention, with the impact of harmonious and obsessive passion and the mediating role of satisfaction and habit in this relationship. Design/methodology/approach The investigation integrates the dual theory of passion and continuity theory. Data were collected from an online survey of 351 OAP users in West Bengal and Odisha, India. Structural equation modelling was used to test relationships among passion, satisfaction, habit and app-based factors. Findings Harmonious passion positively relates to users’ attitudes towards OAP platforms, while obsessive passion has no significant effect. Continuance intention is driven through satisfaction and habit, which mediate. User satisfaction is significantly predicted by the website’s security and interactivity; however, customisation and social factors do not directly have any impact. Research limitations/implications Businesses should create genuine user interest and enjoyment and seamless and satisfying experiences. In addition, they must invest into good security and extendable capabilities. These plans are able to make users more satisfied, make them want to use the app as a habit and foster long term loyalty. Originality/value The study examines the relationship between passion, satisfaction, habit and app-related variables in online alcohol purchase. It adds to the existing body of literature on e-commerce and consumer behaviour as well as gives a macro picture of the effect OAP platforms have on user involvement and retention.

Distributed power (DP) generation through solar and wind energy holds immense potential in meeting future energy demands. Recent advancements in grid technology enable efficient utilization of local energy sources, minimizing transmission line losses and facilitating enhanced power distribution capabilities. This study focuses on examining the impacts of disturbances and faults within a four-area system linked to a Doubly Fed Induction Generator (DFIG) using discrete-time modeling. The primary control approach within the four-area system involving the DFIG incorporates various discrete-time Power System Stabilizers (PSSs). A comparative analysis of time-domain responses is conducted across various scenarios, including systems without controllers (no PSS), systems equipped with traditional PSSs such as Delta Omega, Multi-Band, Delta Pa and Fuzzy Logic (FL) based PSSs. A discrete-time mode PSS is specifically tailored for the silent-pole synchronous generator associated with the DFIG system. To assess the performance of the Fuzzy Logic (FL) controller in ensuring power system stability, a test DFIG model is employed. Time-domain simulations of the test DFIG model are carried out using the MATLAB/Simulink (R2015a) environment.