Volume 12 Number 1 (January )

Estimating the Impact of R&D Intensity on Manufacturing Firm Performance: An Instrumental Variable (TSLS) Analysis

Tzai-Chaio Lee

This study investigates the causal impact of R&D intensity (RDI) on Chinese manufacturing firms' performance (ROA) using a panel instrumental variable approach. By leveraging enterprise life cycle stages (ELC) and industry competition intensity (DIC) as exogenous instruments, two-stage least squares (TSLS) estimates reveal a significant positive effect of RDI on ROA (0.41, p < 0.01), contrasting with biased OLS results (-0.001). Growth-stage firms and moderate industry competition amplify RDI's benefits, while debt ratios negatively affect performance. Robustness checks confirm instrument validity (Cragg-Donald F = 48.51 > 19.93) and panel data superiority. Policy implications advocate targeted R&D subsidies for growth-phase firms and innovation alliances in competitive sectors. This work resolves the "R&D paradox" by contextualizing innovation impacts, offering actionable insights for industrial upgrading.

Explainable artificial-intelligence methods in decision support for delivery management

Ankur Fnu

The article presents an analysis of the application of explainable artificial intelligence (XAI) methods in supporting managerial decision-making for delivery management. The study is conducted within a theoretical and analytical framework, employing a targeted review of publications, a taxonomy of interpretable methods, and their alignment with typical delivery tasks. Particular attention is paid to the role of XAI in ensuring transparency, consistency, and resilience of decisions, as well as integrating ESG indicators and cyber-resilience criteria into planning and dispatching processes. Based on the analysis of scientific sources, approaches to interpreting forecasts and recommendations (post-hoc methods, built-in relevance mechanisms, neuro-symbolic models) are systematized, and their managerial effects and limitations are identified. Generalizing classifications are presented, including a map of XAI applications in logistics tasks, a summary of quantitative effects by key metrics, and a decision matrix linking approaches to managerial criteria. The challenges of XAI implementation are examined, including the complexity of interpreting deep models, the risk of oversimplified explanations, and the need to adapt algorithms to dynamic operational conditions. A structured model for integrating XAI into decision support system architectures is proposed, focusing on balancing accuracy, cost, and environmental performance. The article will be useful to specialists in logistics and supply chains, DSS developers, XAI researchers, and managers making decisions under high demands for transparency and delivery resilience.

Health Financing, Privatization and Equity in Haryana’s Healthcare System

Pooja, Dr. Karan Singh

Over the last twenty years, healthcare delivery in Haryana has undergone notable change as a result of health-financing reforms and the expanding role of private providers. Increased government spending, the introduction of publicly funded insurance schemes and reliance on private healthcare institutions have collectively improved the availability of services for large sections of the population. For households covered under insurance programmes, dependence on direct out-of-pocket payments has declined, while access to institutional care has improved. These shifts are reflected in better health infrastructure, a rise in institutional deliveries and gradual improvement in indicators such as infant and maternal mortality. However, these gains have not been uniform. Persistent disparities remain due to unequal spatial distribution of facilities, shortages of healthcare personnel in public institutions, administrative challenges in insurance execution and limited oversight of private providers. The experience of Haryana demonstrates that although publicly financed privatization can widen access to healthcare, achieving equity requires continuous public investment, stronger regulatory mechanisms and focused attention on underserved areas.

Features of adapting Lean manufacturing methodology to the requirements of the ISO 13485 standard

Victor Armel Eyanga

The article explores how Lean manufacturing methodology can be effectively adapted to meet the regulatory requirements of ISO 13485 in medical device production. The article used a structured narrative literature review of recent peer-reviewed studies published between 2021 and 2025, examining evidence from case studies, expert interviews, systematic reviews, and technology-focused investigations relevant to Lean, risk management, validation, documentation, and digitalisation in regulated environments. The review brings together a set of recurring features that appear to be essential when Lean is applied within an ISO 13485 quality system. One consistent theme is the need to build documentation and traceability requirements directly into Lean routines rather than managing them separately. Another is the limitation of relying solely on FMEA; the broader risk framework set out in ISO 14971 has to be reflected in improvement work. This point, along with the others identified in the review, should be of practical use to teams involved in Lean work within medical-device manufacturing, particularly where operations and quality or regulatory staff have to plan improvements together. The material may also give researchers a more concrete basis for examining the ways Lean methods intersect with ISO 13485 and where the existing models still fall short.

Predictive Analytics in Social Commerce: Enhancing Seller Engagement and Inventory Readiness for Viral Product Demand

Shweta Fnu

The article presents a theoretical analysis of the role of predictive analytics in managing viral demand and shaping seller engagement in social commerce. The study is based on an interdisciplinary approach that integrates developments in information management, e-commerce, machine learning, and behavioral economics. Particular attention is paid to the thematic analysis of publications covering the macroeconomic effects of pandemic-driven online retail growth, algorithmic solutions for demand forecasting, and organizational models of live streaming as drivers of engagement. Key mechanisms are identified, including the reduction of the bullwhip effect, improvement of forecasting accuracy through the use of graph convolutional networks and federated learning, and the strengthening of trust in platforms through the integration of predictive tools. A comparative analysis of methods demonstrates the consistent advantage of graph- and transformer-based algorithms in terms of adaptability and sensitivity to short-term demand surges. The necessity of interpreting predictive analytics not as an auxiliary module but as a fundamental element of digital platform architecture, determining their resilience and competitiveness, is substantiated. Promising directions for development are outlined, including the hybridization of algorithmic approaches, the standardization of data exchange protocols, and the expansion of empirical bases across geographies. The article will be useful to researchers and practitioners in e-commerce, digital platform developers, and supply chain management specialists interested in adaptive strategies for responding to viral demand.

A Theoretical and Empirical Analysis of E-Learning Platform and Digital Content in Hospitality Education in India

Dr. Nitin Gupta, Dr. Shiv Mohan Verma, Aswani Kumar

The high pace of digitalization of the education sector has altered the paradigm of teaching-learning in different fields, including hospitality education. E-learning in India has largely adopted e-learning platforms including SWAYAM, NPTEL, institutional Learning Management Systems (LMS), and personal digital platforms, which have seen rapid adoption in recent years and more so after the COVID-19 pandemic. The research paper presents a critical theoretical and empirical research of e-learning systems and online resources in hospitality education in India. The study incorporates the e-learning ecosystem theory, technology adoption themes, and quality frameworks of digital content to address the effectiveness of platforms and satisfaction levels of learners. The study, relying on primary data in form of survey and secondary data sources, uses descriptive statistics and factor analysis to determine determinants of platform adoption and content effectiveness. The results show a wide range of differences in the satisfaction of learners on different platforms and teaching materials, the quality of content, its interactivity, and the interaction with a teacher being the key success factors. The research has added value to the literature on instruction and teaching technology in hospitality industry education since it offers practical advice to policymakers, instructors and web developers.

Development of Automated Material Handling Systems for Truck Body and Trailer Assembly Lines

Siddharth Pareek

The study examines the redesign of material handling for Class-4 refrigerated truck bodies after the introduction of a modular ABS–polyurethane sandwich roof with integrated pickup slots. Motivation derives from the mismatch between legacy crane-dependent routines and the new roof’s weight range, geometry, and fastening sequence, which required a line-coupled, automation-ready solution. Novelty lies in a synthesis that binds cooperative pickup geometry, AMR-based delivery, lean sensor fusion, and near-station quality verification into a single architecture tailored to large thermoplastic-foam panels. The work describes the handling concept, metrology stack, and logistics orchestration; evaluates precision, resource coupling, and quality stability; and formalizes design levers for mixed-model flow. Special attention is paid to suction safety envelopes for ABS skins over rigid foam, error-proofing of roof-to-wall mating, and dispatch strategies that stabilize takt under variability. The goal is to provide a transferable blueprint for heavy panel handling in truck and trailer assembly. Methods include comparative review, constraints-based synthesis, and triangulation of published capabilities with program metrics. The conclusion details measurable improvements in crane engagement, locating precision, and rework containment and outlines generalization conditions for adjacent product families.

Development of Uni-HEALS: Semantic Search and Forecasting-Enhanced University Health Care Management System

Camilo G. Villaviza Jr., Rachel T. Alegado

This study presents the development of Uni-HEALS: a Semantic Search and Forecasting-Enhanced University Health Care Management System aimed at improving efficiency, accessibility, and decision-making in university health services. Conventional health care systems in academic institutions often suffer from fragmented records, limited retrieval capabilities, and the absence of predictive analytics for service planning. To address these challenges, UNI-HEALS was designed and developed using the Agile methodology and evaluated during a pilot deployment at NEUST University's health clinic – Sumacab Campus - to define the study’s scope and operational context clearly. IT experts assessed system quality and end users using the ISO/IEC 25010 Software Product Quality Model, and end users also evaluated the system’s acceptability. Quantitative results revealed that IT experts rated the system with a grand mean of 3.59, verbally interpreted as an Excellent Quality System, indicating that Uni-HEALS meets and exceeds the required software quality standards. End-users similarly assessed the system with a grand mean of 3.64, indicating Excellent Quality and high satisfaction with performance, effectiveness, and ease of use. Moreover, the system’s acceptability had an overall mean of 3.70, interpreted as Highly Acceptable, demonstrating that Uni-HEALS met all acceptability criteria and showed no significant weaknesses during implementation. In addition to performance metrics, a comprehensive cost-benefit analysis was conducted to evaluate the feasibility of system deployment, including hardware and software. These findings confirm that the system consistently satisfied both technical and user requirements, supporting its viability for enhancing health care management and decision support in university clinic environments and contributing to innovative campus health system initiatives and practicality.

Gender Gaps in Healthcare and Nutritional Outcomes: A District-Level Analysis in Haryana

Kavita

Gender inequality in healthcare and nutrition continues to be a significant issue in India, especially in states with deep-rooted patriarchal values like Haryana. Although the country has experienced substantial economic growth and improved public health infrastructure, gender disparities in accessing healthcare and achieving nutritional health remain evident throughout Haryana. This research examines gender differences in healthcare access and nutritional status across districts in Haryana, using a detailed district-level analysis. The study uses secondary data from sources such as the National Family Health Survey (NFHS-5, 2019–21), the Census of India, and official government reports. It assesses gender disparities by analysing key indicators of healthcare access, such as antenatal care and institutional deliveries, as well as nutritional outcomes, including anaemia prevalence and body mass index (BMI). Descriptive and comparative analyses are performed to investigate differences across genders and districts. The findings highlight notable gender disparities in healthcare use and nutritional health, with women generally experiencing worse outcomes than men across various districts. Significant differences between districts suggest that state-level averages hide regional inequalities. Areas with lower female literacy rates, limited healthcare services, and strong socio-cultural norms tend to show greater gender gaps. The study finds that tackling gender inequality in healthcare and nutrition in Haryana needs district-specific, gender-sensitive policies. Enhancing women-focused healthcare services, providing better nutritional support for at-risk groups, and challenging social norms are key to ensuring gender-equitable health outcomes. This research adds empirical evidence to the ongoing discussion on gender disparities in Haryana and provides valuable insights for designing targeted policies.

Shipping line digital workflow efficiency on service quality and delivery

In this paper, we examine the influence of digital workflow efficiency on service quality and delivery performance outcomes in the Philippine shipping line industry. As global logistics evolve through digital transformation and rising e-commerce demands, shipping lines face increasing pressure to modernize operations and eliminate manual inefficiencies. Using a quantitative descriptive-correlational design, the researchers surveyed 50 logistics professionals in Metro Manila to assess perceptions of digitalization across key areas: real-time data, tracking portals, e-documentation, delivery orders, online freight payment, quotation rates, and container management. Statistical analysis, including Pearson correlation, revealed significant positive relationships between digital workflow systems and operational efficiency indicators. The findings show that digital tools enhance transparency, responsiveness, coordination, and overall operational agility, leading to improved service quality and customer satisfaction. Real-time data and tracking portals emerged as the most influential factors, while e-documentation also contributed to streamlined processes and reduced administrative delays. Despite these benefits, challenges such as system errors, data accuracy, user adaptation, and staff training remain. The study concludes that digitalization is a strategic enabler of competitiveness, resilience, and long-term sustainability in maritime logistics, and recommends continued investment in digital infrastructure, workforce development, and system integration to fully realize its transformative potential in the Philippine shipping sector.

Strategies for Migrating Monolithic Software Systems to a Microservice Architecture

Artem Agaev

The article examines strategies for migrating monolithic software systems to a microservice architecture amid increasing demands for modularity, scalability, and integration in corporate and industrial environments. The study integrates findings on legacy system modernization, the use of modular monoliths as an intermediate form, stepwise component replacement patterns, ontology-based service identification methods, automated decomposition models, practices of polyglot persistence, and operational characteristics of microservice platforms. The analysis shows that migration strategies emerge within a multi-component structure in which the formal basis of methods, the quality of input artifacts, the degree of automation, and the operational context jointly determine service boundaries, the distribution of data responsibilities, and the risk profile. Based on a comparison of approaches, a conceptual migration framework is proposed that links method selection to the requirements of governmental, cloud, and industrial environments, demonstrating that the success of the transition is shaped not by any single technique but by a managed combination of methods and the phased restructuring of data, interactions, and operational processes. The article argues that disregarding architectural trade-offs associated with network latency, distributed consistency, and increased security complexity leads to biased risk assessment and reduced controllability of system evolution. The findings may be useful for architects, engineers, and decision-makers planning the transition from monolithic solutions to microservice architectures in corporate and industrial contexts.

Navigating Modernity: Consumer Perceptions of Awadhi Culinary Heritage Through a Sociodemographic Lens

Amarjeet Kundu, Dr. Sandeep Malik

This study investigates how consumers in Lucknow City perceive traditional Awadhi food, critically examining these perceptions within the context of modernity's influence and the diverse sociodemographic profiles of urban dwellers. Recognizing Awadhi cuisine's profound cultural significance and its burgeoning potential for gastronomic tourism, the research seeks to understand its contemporary resonance. An extensive literature review, encompassing over 50 academic articles, systematically identified 18 salient variables influencing consumer food choices, such as authenticity, quality, flavor, price, and perceived health benefits, all operationalized for this empirical investigation. The primary objectives were to discern the critical factors driving consumer choices for traditional Awadhi food and to delineate contemporary consumer perceptions of this distinct regional cuisine. Employing a quantitative research design, data were meticulously collected from 250 consumers via a structured online questionnaire, utilizing a five-point Likert scale. Following rigorous pilot testing to ensure instrument validity and reliability (Cronbach's Alpha = 0.981), factor analysis was applied to the collected data using SPSS. The analysis yielded a robust three-factor solution, collectively explaining 95.847% of the total variance, thus providing a parsimonious representation of underlying perceptual structures. Findings indicate that Awadhi cuisine is predominantly perceived as highly flavoursome, of superior quality, authentically prepared, distinguished by unique recipes, and a significant promoter of local tourism. Conversely, a notable perception suggests it is complex to prepare and generally associated with a higher price point. These comprehensive insights offer actionable strategies for stakeholders within the hospitality and tourism sectors to strategically enhance the promotion, accessibility, and sustained cultural and economic value of Awadhi cuisine in an era of rapid social and economic change.

Graduate Employability and Skills Utilization: A Tracer Study of BSBA Marketing Management and BS Entrepreneurship 2024 Graduates of NEUST Atate Campus

This tracer study assessed the employability of BS Entrepreneurship and BSBA Marketing Management graduates of Nueva Ecija University of Science and Technology (NEUST) Atate Campus, Batch 2024. Using a descriptive design and total enumeration approach, the study covered 60 graduates from the second semester of Academic Year 2023–2024. Data were collected through an online survey and analyzed using descriptive statistics to evaluate employment status, job alignment, earnings, and training adequacy. Results show that 72% of graduates are employed, with employment rates of 77% among BSBA graduates and 62% among BS Entrepreneurship graduates. Most respondents secured employment within three months after graduation, indicating strong workforce readiness. The majority work in jobs related to their degree and report high utilization of communication, leadership, and problem-solving skills. Graduates perceive their academic training as highly adequate and recommend expanded training programs, stronger industry partnerships, and curriculum modernization. The findings confirm that NEUST Atate Campus produces employable graduates while underscoring the importance of continuous curriculum improvement.

Energy-efficient task scheduling algorithms in hybrid CPU-GPU systems

Khushboo Kumari Yadav, Ankur Yadav

This article presents a systematic analysis of energy-efficient task scheduling algorithms in hybrid CPU–GPU systems, where heterogeneous computing resources exhibit fundamentally different performance and energy characteristics. Such systems are widely used in high-performance computing, data centers, and AI-driven workloads, where increasing computational demand and energy constraints limit the effectiveness of scheduling strategies focused solely on execution time. The study is conducted as a review-and-analytical synthesis of peer-reviewed publications published between 2022 and 2025, without quantitative aggregation of results due to heterogeneity of experimental setups, metrics, and energy models. Particular attention is paid to the role of optimization metrics, quality of input energy data, and integration of power management mechanisms in shaping the observed effectiveness of scheduling algorithms. The analysis shows that reported improvements strongly depend on the choice and aggregation level of performance and energy metrics, as well as on the accuracy of task energy characterization, rather than on the algorithmic class alone. It is demonstrated that single-objective formulations fail to capture the behavior of hybrid CPU–GPU systems, while composite time–energy criteria and explicit device-selection policies provide a more consistent basis for evaluation. The study establishes that meaningful comparison of energy-efficient scheduling approaches requires a clear separation between architectural scheduling frameworks and concrete algorithms, along with explicit fixation of the energy management context. The article is intended for researchers and practitioners working on scheduling, power-aware computing, and heterogeneous system design in high-performance and data-intensive environments.

Design of an Open-Source Device for Immersion Staining of Cytological Samples

This project details the design of a staining machine for processing samples in cytological tests for a clinical laboratory. The objective is to design a staining machine using local materials and components, ensuring a low manufacturing cost compared to commercial staining machines, and offering reliable staining through sequences programmable via a graphical interface. The designed device was based on a linear mechanism, in which the worktable consists of a separating base for cuvettes containing the chemical solutions for the stain. The samples are held in place by a basket, which adheres to the machine by means of electromagnets activated by the control system. Bipolar stepper motors were used for movement, activating a power screw mechanism. These motors were controlled using an Arduino Uno. Finally, an interface and a touchscreen were developed to allow execution of the staining sequences. Mechanical elements were selected according to local availability, achieving a competitive manufacturing cost.

Multi-Layer Microwave Filter for WLAN

Hassan Ali Shah

Due to the development of wireless communications and the appearance of new systems there is high demand in small size, low cost filters with high performance. Hence, miniaturization of band pass filters with improvement of their characteristics is a big challenge in modern filters design. This is achieved by improvement of conventional concepts and approaches, as well as by introduction of new topologies and designs. Multi-layer concept in conventional filter designing prove to be the best approach to meet the challenges in modern filter design. In this research work, a new method to design a Multi-layer band pass filter (BPF) is presented for WLAN applications. This method is based on a simple principle: different substrates (dielectric constants) will result different resonant frequencies for a resonator. The basic structure of this method is studied and then a planar band pass filter is designed to utilize in this structure. To reduce the filter size, dual layer filter is proposed but increase in insertion loss due to multi-layer coupling. To overcome this issue, the Substrate Integrated Waveguide (SIW) filter is established based on multilayer technique. To prove the concept of microwave WLAN filter, the operating central frequency of 2.44 GHz is demonstrated and validated through simulation and measurement. Finally, the multilayer configuration with dielectric substrates showed that the bandwidth is broaden up, insertion loss, return loss and size are reduced than single layer configuration.

Industrial Shock Stabilization of Bakery Products: Technological Standardization of Freezing Regimes to Preserve Organoleptic and Rheological Characteristics

Mandzhgaladze Levan

The paper addresses the preservation of quality in frozen bakery semi-finished products, a matter of growing scientific and technological importance given increased demand for highly ready-to-bake baked goods and the need to extend logistical chains within the Russian market. This study investigates the degradation of the rheological structure and sensory properties of laminated yeast-leavened products during conventional freezing. Industrial shock stabilization is achieved through a substantiated methodology of ultra-rapid cooling within the range of -35 0C to -40 0C. Using a production case study and laboratory monitoring data, it is demonstrated that technological standardization of freezing regimes minimizes damage to the gluten network by promoting the formation of a microcrystalline ice structure, thereby preserving the rheological properties and sensory characteristics of the finished product at levels comparable to freshly baked equivalents. The scientific novelty of the work lies in the development and industrial validation of adapted process sheets for laminated products. Practical process sheets and recommendations are provided to adapt shock-stabilization parameters to specific equipment, facilitating industrial implementation, subject to local validation and regulatory requirements. The practical significance of the research is the substantiation of a technology that can extend product shelf life by up to 6 months, thereby enabling wider distribution and greater assortment diversification. The results will be useful to food-production engineers and managers, cold-chain logistics specialists, and formulation developers (including manufacturers of cryoprotectants and dough improvers) interested in prolonging shelf life and expanding the geographic reach of ready-to-bake pastry products.