Purpose This analysis aims to determine and prioritise the barriers of effective healthcare service quality (EHSQ) in an emerging economy by deploying an integrated expert mining and interpretive structural modelling cross-impact matrix multiplication applied to a classification (MICMAC) method. Design/methodology/approach This analysis uses a unified method in two parts. In the first part, a structured literature analysis and an expert mining tool have been used to identify and validate the EHSQ barrier. In the subsequent part, an interpretive structural modeling (ISM) has been used to examine the interrelationships among EHSQ barriers to determine a structural model. Subsequently, the MICMAC approach has been deployed to categorise the EHSQ barriers based on their driver and dependence power. Findings This analysis recognised 11 key barriers of EHSQ in an emerging economy and created a hierarchical framework using ISM. Furthermore, EHSQ barriers have been classified into four clusters using the MICMAC approach. In the framework, societal-related EHSQ barriers are primarily at the highest level, operational barriers at the mid-level and service quality-related EHSQ barriers at the bottommost level. Research limitations/implications Results are valuable for strategists in better health governance of an EHSQ. Practical implications The outcomes deliver significant insight for healthcare policymakers to understand the contextual relationships among EHSQ barriers and assist in formulating strategies to abolish the leading EHSQ barriers. Social implications This study’s outcomes are helpful for public health planners to develop an appropriate health policy by removing EHSQ barriers. Originality/value This study first prioritised the EHSQ barriers by integrating ISM–MICMAC.
Purpose This paper aims to explore the phenomenon of real skin and authenticity in the beauty space, focusing on what drives this increased shift, the role of social media both for supporting and impeding this phenomenon, consumers’ response to authenticity over perfectness and differences between engagement by influencers who use the aesthetic of “real skin” against others who maintain the “picture-perfect” aesthetic. Design/methodology/approach In this bibliometric cum qualitative study, a two-phase analysis was carried out to extract viewers’ comments based on selected keywords related to real skin and authenticity. In Phase I, extracted comments were analyzed using Keyword analysis, and in Phase II, patterns and sentiments were further analyzed from the shortlisted comments to understand viewers’ psychology and emotions. Findings The study shows that beauty influencers play a critical role in shifting perceptions and have a major influence on buying decisions. Research limitations/implications The study provides critical insights that beauty brands, influencers and social media sites can draw upon in their pursuit to adapt to new changes in beauty standards and consumer expectations. Originality/value It fills an existing gap in the literature by looking at how influencers who are pushing for real skin impact consumer perception and practice.
Purpose This study aims to offer a systematic assessment and investigation of the implementation of continuous improvement (CI) plans in the health-care industry between 2020 and 2024. The study investigates essential topics such as leadership, innovation, performance management, process improvement and continuous improvement approaches using databases such as Scopus and Web of Science. It looks at issues from a number of theoretical viewpoints, such as lean management, total quality management, organizational change and learning organizations. To develop knowledge and implementation of continuous improvement in health-care settings, the review attempts to address current research gaps, emphasize the theoretical foundations impacting CI in health care and offer directions for future research. Design/methodology/approach The implementation of continuous improvement (CI) in health care is studied in this study using a systematic literature review (SLR) technique. Scopus and Web of Science were the sources of research articles from 2020 to 2024. The review is based on theories such as total quality management, lean management, performance management, organizational change, leadership and learning organizations. Leadership, process improvement, innovation and CI methods are significant issues. Understanding theoretical effects on health-care improvement strategies is the goal. The study fills a major research need by pointing out gaps, offering avenues for future research and progressing our understanding of CI applications in many medical contexts. Findings The five vital concepts in health-care improvement are studied in this assessment. The objective of process improvement is to raise efficiency and save expenditures by using methodical approaches such as define measure analyse improve control (DMAIC) and suppliers inputs process outputs customers (SIPOC). The transformative change is fueled by innovation, which prioritizes sector growth, disruptive models and individualized treatment. Performance management highlights how information and communication technology (ICT) and sustainability are being integrated into formative and goal-oriented processes. By adopting evidence-based approaches and a quality culture, Continuous Quality Improvement (CQI) approaches, such as medical patient review-CQI, greatly improve patient outcomes. Human resources, communication and process success are all influenced by leadership and culture. When taken as a whole, these themes highlight a systematic strategy for improving quality, health-care outcomes and efficiency in dynamic health-care systems. Originality/value This study offers original insights by methodically investigating current research (2020–2024) on the use of continuous improvement (CI) in the health-care industry, a field with thorough examination. This research offers a complete understanding of CI initiatives by integrating numerous theoretical views, including total quality management (TQM), organizational change and lean management, in contrast to earlier fragmented studies. The uniqueness is in pointing out understudied relationships between performance, leadership and innovation in health-care CI practices. The report also recognizes areas that need more investigation, especially in patient-centered and data-driven methodologies, providing a base for academics and professionals to develop CI tactics in the changing health-care environment.
Purpose Pharmaceutical innovation is not only about finding new drugs but also about enhancing existing ones. This study aims to explore the role of hybrid applications as a regulatory route in the framework of the European Medicines Agency (EMA) for incremental innovation through changes to authorized reference products. Design/methodology/approach A systematic review of the literature was undertaken carrying out search on PubMed, Scopus, Google Scholar articles along with white and business papers from official websites. The review concentrated on hybrid applications from publications and regulatory documents of 42 studies, European Union regulatory frameworks and innovations that were conducted between 2000 and 2025. Relevant data was organized and arranged systematically into case studies, efficiency, limitations, regulatory and future perspectives. Findings Hybrid applications provide an intermediate regulatory pathway between generic and full applications. They allow developers to capitalize on prior data and submit new nonclinical or clinical data to support changes in indication, formulation or delivery route. Some case studies analyzed illustrate hybrid uses as effective mechanisms for advancing therapies and enhancing patient access. However, it is not without its challenges. Some of these include complicated bridging data needs, regulatory ambiguity and restricted market exclusivity. Achievement is heavily reliant upon initial scientific counsel, strategic planning for development and sound risk handling. Originality/value The review highlights the strategic value of hybrid applications in promoting therapeutic innovation within regulatory frameworks, safety, regulatory efficiency, striking a balance between innovation and efficacy of the European pharmaceutical domain.
Purpose The purpose of the study is to identify systemic challenges in current AI healthcare models and synthesize predictive methodologies, and identify gaps in medical data. Over the recent years, there has been a substantial increase in chronic diseases (CDs) due to environmental conditions and lifestyle of humans. Developing an early diagnosis tool and an efficient treatment is extremely difficult due to the complexity of the different disease mechanisms and underlying symptoms of the patient population. Recently, the artificial intelligence (AI) methods, including deep learning and machine learning, have demonstrated exceptional performance for improving the medical domain. Despite the promising results, the existing diagnosis or detection systems are facing challenges and pose certain constraints for accurate and timely disease diagnosis. Design/methodology/approach Consequently, this study presents a review of around 60 existing literatures for CD diagnosis based on machine learning and deep learning approaches. Specifically, the review explores the merits and challenges of the cutting-edge techniques available in CD diagnosis. In addition, this review provides a brief overview of different methods used in CD diagnosis, particularly heart disease, kidney disease and diabetes, highlighting the tools, challenges and opportunities. Focusing on the recent CD diagnosis methods, the review explores the research gaps, data sets and metrics of such methods, offering significant insights that can guide future improvements rather than providing new experimental results. Findings The research significance is highlighted through data set analysis and achievements of recent methods. Significantly, the review offers a systematic evaluation and comparison, identification of best practices and benchmarks, enhance credibility and understand the applicability in real-world applications. Originality/value Overall, the systematic review analyzes the cutting-edge CD diagnosis methods for clinical deployment based on benchmarking model performance and discusses the opportunities to improve the field of CD diagnosis.
PurposeThe purpose of this study is to systematically review empirical research on consumer behavior related to health supplement use to identify dominant theories, research contexts, behavioral constructs and methodological approaches and to develop a consumer-behavior–oriented research agenda. Design/methodology/approachUsing the Theory–Context–Characteristics–Methodology (TCCM) framework and the SPAR-4-SLR review protocol, this paper synthesizes findings from 37 peer-reviewed journal articles published up to March 2025. Studies were examined based on their theoretical foundations, geographic focus, types of supplements investigated and research methods applied. FindingsThis review shows that intention-based health behavior models, especially the Theory of Planned Behavior, dominate the field, while broader consumer behavior theories are used far less frequently. Most research is concentrated in North America and Asia, with limited evidence from low- and middle-income countries. The studies address a variety of supplement types and consumer behaviors, including marketing responses, purchase intentions, use and post-consumption evaluations. Methodologically, the literature relies heavily on cross-sectional surveys, with relatively few experimental or longitudinal studies. Research limitations/implicationsThis review highlights the need for integration of consumer behavior theories, diverse geographic representation and methodological variety. Future studies should also explore symbolic, habitual and lifecycle-based patterns of supplement use. Practical implicationsThe findings of this study offer useful insights for marketers, policymakers and health communicators seeking to understand and influence supplement-related decisions. Originality/valueTo the best of the author’s knowledge, this is the first review to apply the TCCM framework to dietary supplement consumption. By conceptualizing supplement use as a multi-stage consumer decision process (pre-consumption, consumption and post-consumption) and by identifying underexplored areas such as habitual use, identity-based consumption, digital influence and cross-cultural variation, this study lays foundation for depicting the current state in the field and puts a forward-looking agenda for both theory and practice.
PurposeThis study aims to investigate evolution, current state and future directions for pharmaceutical supply chain management (PSCM) research. Analyzing existing research trends and conceptual developments aims to guide scholars and professional managers in addressing emerging challenges and advancing the effectiveness of PSCM decision practices. Design/methodology/approachThis research proposes a T-model and uses quantitative bibliometric analysis, chronological-thematic review and qualitative content analysis to comprehend PSCM research. This thorough method offers comprehension on the progression and provides new insights for directing future academic pursuits in PSCM research. FindingsThe research reveals critical performance measures and the conceptual and social frameworks influencing the PSCM research. A chronological-thematic investigation outlines the evolution of PSCM research and forecasts forthcoming trends in the discipline. Moreover, the content-based analysis of recent research highlights contemporary research focus and suggests interesting avenues for future inquiries. Research limitations/implicationsDynamic updates within databases like Scopus, impacting paper counts and citation metrics, necessitate careful consideration. Practical implicationsResearchers and practitioners can use this study’s findings to gain a thorough understanding of the present PSCM landscape. Awareness of emerging trends in PSCM enables managers to make more informed management decisions. Social implicationsThis review highlights the social imperative of PSCM by emphasizing equitable access to medicines, fair pricing and responsible sourcing. Strengthening resilience and sustainability in pharmaceutical supply chains contributes not only to operational efficiency but also to public trust, patient well-being and societal welfare. Originality/valueThis research is unique in using a mixed-methods approach that integrates results from bibliometric and content analyses, offering a new, evolving and contemporary perspective on PSCM. The research provides deeper insights into the development and trends, notably advancing PSCM scholarship.
PurposeThis study aims to examine the effects of brand authenticity and perceived quality of personalization on brand trust in the pharmaceutical context and the effect of brand trust on patients' medication adherence intention and brand advocacy. The moderating influence of health literacy is also studied to see if the strength of these relationships is conditioned by consumers' capacity to process health information.Design/methodology/approachA conceptual model was developed based on constructs from relational exchange theory, branding research and ability-based information processing models. Data were gathered through a structured online survey of UK consumers who had used prescription medication in the last few months. Structural models were evaluated using partial least squares structural equation modeling (PLS-SEM) and significance was assessed using bootstrapping.FindingsThe results show that brand authenticity and quality of personalization have significant and positive effects on brand trust and the effect of brand authenticity is stronger. Finally, brand trust is predicted to influence both medication adherence intention and brand advocacy, supporting its key role in healthcare branding. Health literacy was found to positively moderate the authenticity - trust relationship, but did not significantly moderate the personalization - trust relationship. Overall, the model showed a significant amount of variance in trust (58%), intention to adhere (35%) and advocacy (43%).Originality/valueThis paper extends branding research by showing how authenticity and personalization quality function in the sensitive and high-stakes context of pharmaceuticals. It examines brand trust as a bridge between branding cues and medication adherence intention and brand advocacy, while incorporating health literacy as a boundary condition.
Purpose This study aims to investigate how review quality (RQ), rating tone and source credibility (SC) influence patients’ healthcare choices, emphasizing the mediating roles of trust and perceived usefulness. It integrates information adoption, persuasion and trust theories to explain cognitive and emotional decision-making processes. Design/methodology/approach This study used a quantitative design with a structured questionnaire to measure RQ, rating valence (RV), SC, trust, usefulness and decision intent. Data were gathered via a cross-sectional survey with informed consent, then analyzed using factor analyses and structural equation modeling. Findings The results show that RQ, RV and SC strongly shape healthcare decision intentions, both directly and through trust in the provider and perceived usefulness of reviews. SC was most influential, with trust emerging as the stronger mediator. This dual mediation advances Elaboration Likelihood Model by incorporating web trust dynamics (Xu et al., 2022) and supports information adoption in high-risk domains (Zackary, 2020). Originality/value This study integrates information adoption, persuasion and trust theories to provide a cohesive framework for understanding online healthcare review mechanisms. It contributes to digital healthcare literature by highlighting the cognitive and affective pathways through which reviews shape patient decisions.
Purpose The purpose of this study is to characterize how TikTok influencers promote gut-health dietary supplements, focusing on message framing, creator credibility, policy-relevant disclosures and engagement patterns. Design/methodology/approach A quantitative content analysis was conducted on 117 English-language TikTok videos about gut-health supplements. Findings Most creators lacked professional credentials. Health claims without supporting evidence were common, while DSHEA disclaimers appeared in only one video. The vast majority of videos utilized gain framing (98.3%) to highlight positive improvements in everday bodilty function. Practitioners more often used scientific framing and cited research; influencers favored soft framing, weight-loss cues and were more frequently engaged in affiliate/paid promotion. Despite lower credentialing, influencer videos received more likes and saves. Originality/value This is, to the best of the authors’ knowledge, the first systematic audit of TikTok gut-health supplement promotions linking framing choices, regulatory indicators and engagement by credential status, yielding concrete targets for disclosure policy and platform enforcement. This study contributes to literature on influencer marketing and supplement advertising by highlighting risks from unregulated health claims and the need for stricter regulations to protect consumers from misinformation.
Purpose The purpose of this study is to investigate the interplay between digital integration (DI), knowledge management practices (KMPs) and organizational agility (OA) in enhancing health-care delivery performance (HDP) within pharmaceutical supply chains. This study specifically examines how these mechanisms contribute to improved service quality, patient trust and organizational reputation in resource-constrained health-care contexts.Design/methodology/approach A cross-sectional survey was conducted in Jordan's pharmaceutical sector. Data were collected from 312 professionals operating across pharmaceutical supply chain organizations using validated measurement scales. Partial least squares structural equation modeling was used to test both direct and mediated relationships linking DI, KMP and OA to HDP.Findings The results of this study indicate that DI significantly enhances HDP, with its strongest effects occurring indirectly through KMPs and OA. Knowledge routines strengthen OA, which in turn drives service reliability, delivery continuity and patient-focused responsiveness. The sequential mediation pathway (DI -> KMP -> OA -> HDP) confirms that digital technologies create value only when embedded within knowledge-driven and adaptive organizational processes.Originality/value This study empirically validates a hybrid Knowledge-Based View-Dynamic Capabilities Theory (KBV-DCT) framework in an emerging pharmaceutical market. This study contributes novel insights by demonstrating how DI translates into superior health-care service quality, marketing advantage and societal value. The findings of this study offer actionable implications for managers and policymakers by highlighting the importance of aligning digital investments with knowledge management and agility-building strategies to strengthen patient trust and HDP.
Purpose Healthcare innovation relies on more than just expertise in technical matters, but also requisite relational behavior that enables cooperation and collaboration. This study aims to investigate the effects of both content-related and context-related training on employees' innovative work behavior (IWB) through organizational citizenship behavior toward individuals (OCBI), as well as the moderating roles of person-organization fit (PoFit) and weekly working hours.Design/methodology/approach This study is based on a survey carried out among 262 employees (nurses, doctors, health staff) working in private hospitals located in Sulaimania city, Kurdistan. The hypothesized model has been examined using structural equation modeling and moderation analyses.Findings It has been found that the effect of content-based training directly affects healthcare employees' IWB, context-based training indirectly enhances healthcare employees' IWB through OCBI. Moreover, PoFit serves as a strong moderator, in that the effect of content-based training on OCBI is significant only at high level of PoFit.Research limitations/implications Limitations include the single-region sample and cross-sectional design; future research should explore longitudinal effects and additional moderators such as leadership style.Practical implications Practical implications include tailoring technical and relational training to improve innovative outcomes in resource-constrained hospital settings.Originality/value These findings highlight dual training pathways to innovation and emphasize the role of fit and time as boundary conditions.
PurposeThis study aims to explore the influence of healthcare professionals (HCPs) on consumers' purchasing decisions, including how their recommendations change consumers' choices and the impact of interactive processes on consumers' satisfaction and loyalty.Design/methodology/approachThis study uses qualitative interview analysis method and Kotler's 5A Theory as the analytical framework, with dental clinics as the research field, to explore how medical professionals influence patients' cognition and acceptance of teeth whitening products. This study collects data through in-depth interviews with 28 medical professionals, patients and general sales personnel.FindingsSurprisingly, research results show that the advice of medical professionals plays an important role in the patient's decision-making process in terms of product safety and effectiveness evaluation.Research limitations/implicationsThis study believes that medical marketing should found a professional image with transparent communication in market, strengthen the collaboration and digital application of all parties, and help enhance the influence of medical professionals in marketing communication.Originality/valueThis study uniquely demonstrates the role of HCPs who enhance consumers' confidence in healthcare by facilitating greater public awareness of the efficacy and safety of various teeth whitening treatments through consumers' feedbacks, helping to bridge the knowledge gap related to the products, and making purchasing decisions easier for consumers.
PurposeThe purpose of this study is to investigate the digital synergy between social media influence (SMI), value co-creation and customer adoption with the moderating role of artificial intelligence (AI) chatbot adoption in the dermatology pharmaceutical industry.Design/methodology/approachThe convenience sampling method is used to gather the data from the customers of dermatology pharmaceutical firms using the survey method. PLS-SEM is used for analyzing this study.FindingsThe findings indicate the positive effects of SMI on adoption rate, but findings indicate non-significance of AI chatbot adoption as moderating relationship between SMI and value co-creation. Findings also indicate the significance of value co-creation mediating the relationship between SMI and customer adoption of value co-created products. Value co-creation refers to customers' active involvement in shaping products, services or experiences through interaction, feedback and collaboration with firms.Practical implicationsThis study has practical implications for the dermatology pharmaceutical industry since consumers are practically involved in creating value for themselves jointly with dermatology product manufacturers and sellers, where customers seek information, reviews and opinions from specialists prior to purchasing skincare and dermatological treatments.Originality/valueIn this study, behavioral reasoning theory was used to validate the SMI and AI chatbot adoption with mediation of value-co-creation, leading to the customer adoption, that has rarely been researched.
PurposeThis study aims to measure medication errors rates in a tertiary care hospital and recommends Quality Function Deployment (QFD) framework on the lines of socio-technological systems theory as an intervention in converting voice of customers (VoC), i.e. healthcare workers into technological improvements in the existing hospital's electronic medical record (EMR) system using them to reduce medication errors.Design/methodology/approachUsing observational data and error reporting documents this cross-sectional study was carried out in Punjab state of India for a period of three months. Medication errors were categorized into prescription, documentation, administration, monitoring, indenting, dispensing and transcription errors. The QFD framework divided in four steps was applied to convert VoC into with technical Features in the EMR system.FindingsPrescription errors were the most common (61%), followed by documentation (17%), administration (9%) and monitoring errors (7%). Less frequent but significant errors included indenting, dispensing and transcription. The study identified automated error alerts, standardized ordering processes and dropdown medication lists as high-priority EMR features capable of reducing medication errors. Training modules for nurses were also deemed essential.Practical implicationsEMR-based interventions, supported by user-centered training, can meaningfully reduce medication errors and strengthen clinician trust in digital systems. Ensuring regular updates and managing false alerts remain critical for sustained EMR adoption. The study highlights QFD as a strategic link between patient-safety science and health-IT implementation, with the potential to enhance patient trust, reinforce safety as a competitive differentiator and contribute to a stronger hospital brand reputation.Originality/valueThis study uniquely applies the QFD framework to link healthcare provider needs with EMR design features, emphasizing technical and human-centered strategies for reducing medication error in an Indian hospital context.
Purpose This study aims to examine a two-echelon, multi-product, multi-period pharmaceutical supply chain in Tunisia, involving a public hospital pharmacy and an emergency pharmacy. The emergency pharmacy’s inventory is represented using a mixed integer linear programming (MILP) model, aiming to minimize costs of ordering, holding and handling shortages or overstock. Design/methodology/approach With an estimated cost benefit of 18%−30%, the MILP model successfully lowers the expense of managing an emergency pharmacy’s drug inventory. Using economies of scale in scenarios with higher demand demonstrates the model’s scalability and cost-effectiveness. Stockout penalties, however, limit cost reductions, underscoring its adaptability to changing demand and cost conditions. A decision support system (DSS) is introduced to optimize drug inventory management in the hospital emergency room, ensuring pharmaceutical availability and reducing operating expenses through mathematical optimization. The suggested DSS is a prime example of how interactive tools and operational research may improve healthcare logistics while striking a balance between essential service requirements and cost effectiveness. Findings With an estimated cost benefit of 18%−30%, the MILP model successfully lowers the expense of managing an emergency pharmacy’s drug inventory. DSS is introduced to optimize drug inventory management in the hospital emergency room, ensuring pharmaceutical availability and reducing operating expenses through mathematical optimization. The suggested DSS is a prime example of how interactive tools and operational research may improve healthcare logistics while striking a balance between essential service requirements and cost effectiveness. Originality/value The DSS incorporates three critical functional components to optimize medication management. First, the use of the MILP, exact approach, to determine the optimal reorder point and the ordered quantity for different medication classes. Second, comprehensive performance indicators provide real-time monitoring of: stock status relative to safety thresholds, days of remaining coverage based on consumption patterns and detailed cost analytics of inventory holding versus procurement. Third, the system demonstrates robust workflow integration, seamlessly interfacing with existing hospital operations through: bidirectional data exchange with pharmacy management systems and support for two-echelon distribution networks spanning hospital pharmacy and emergency pharmacy. This tripartite architecture ensures both theoretical rigor in inventory optimization and practical adaptability to clinical workflows.
PurposeThis study aims to examine the marketing drivers influencing medical device selection among surgeons in suburban Tier II Indian cities, with an explicit focus on the mediating role of surgeon training. The research addresses a major gap in existing research where multiple marketing and product-related drivers have not been jointly analysed, nor has the mediating role of surgeon training been explored in resource-constrained suburban Tier II Indian markets. Design/methodology/approachA cross-sectional structured survey of 394 surgeons across 40 suburban Tier II Indian cities was conducted. Using partial least squares structural equation modeling, the effects of device safety, performance, innovation, vendor reliability, peer influence and cost consideration on device selection were assessed. Surgeon training was assessed as a mediator. Reliability, validity, mediation and structural effects were assessed using a bootstrapped sample of 5,000 iterations. FindingsAll predictors significantly influenced device selection (beta = 0.1117-0.358, p < 0.01). Surgeon training partially mediated the relationships between device safety, performance, innovation and peer influence, strengthening the impact of marketing-related and peer-driven influences on adoption. The model demonstrated strong predictive power (R & sup2; = 0.71) and acceptable fit (SRMR = 0.045). Research limitations/implicationsThe cross-sectional design limits causal inference. Specialty-specific behaviors were not analyzed. Future research should investigate longitudinal adoption patterns and comparative analysis between urban Tier I and suburban Tier II cities. Practical implicationsMedical device marketers targeting suburban Tier II Indian cities should prioritize surgeon training initiatives as a strategic lever to increase medical device selection. Building strong vendor relationships, emphasizing safety and performance and leveraging peer endorsements can enhance device selection. Social implicationsPolicymakers can institutionalize and facilitate accredited surgeon training programs, introduce evidence-based procurement policies, introduce vendor reliability ratings and leverage key opinion leaders in government panels to aid device adoption. Originality/valueThis is one of the first empirical studies to integrate marketing, technical and social drivers into a unified model of medical device selection in a developing-country context. It advances theoretical understanding by identifying surgeon training as a critical cognitive mechanism linking marketing and clinical attributes to adoption behavior. The findings offer actionable insights for medical device marketers and policymakers operating in low-resource markets.
PurposeThis paper aims to propose a novel decision-making framework that integrates fuzzy logic with machine learning to tackle uncertainties in supply chain management and production planning. The focus is on optimizing inventory levels, balancing supply and demand and achieving production targets within a closed-loop supply chain (CLSC).Design/methodology/approachAn intelligent algorithm is developed to monitor and adapt plant operations in real time using fuzzy inference and machine learning. The framework is validated through two case studies: an industrial hospital laundry (IHL) with 16,000 kg daily production, and a furniture company facing seasonal demand fluctuations. Performance is evaluated through inventory stability, production efficiency and cost savings, aligned with Industry 4.0 / 5.0 objectives.FindingsThe system effectively mitigates supply-demand imbalances, reducing inventory deviations by up to 28% and improving production schedule adherence by 21%. In the IHL case, fuel and detergent costs were reduced by 12-15% with an 18% rise in machine utilization. For the furniture company, forecasting accuracy improved by 24%, leading to 17% fewer stockouts and a 14% reduction in holding costs. Overall, the framework enhanced operational efficiency by nearly 20% while demonstrating strong adaptability under uncertain conditions.Originality/valueBy combining fuzzy logic and machine learning for real-time decision-making, this study contributes a scalable and intelligent solution for CLSC environments. Its quantifiable improvements in cost, efficiency and resilience underscore its relevance to sustainable, digitalized supply chains under the Industry 4.0 / 5.0 paradigm.
PurposeThis study aims to investigate the adoption of active noise cancelling (ANC) headphones among Generation Z consumers in Vietnam. Given the increasing risk of hearing loss caused by prolonged exposure to high-volume audio, ANC headphones emerge as a health-supportive consumer technology. By integrating the technology acceptance model (TAM) and protection motivation theory (PMT), this research tests both functional and psychological determinants of ANC headphone adoption in a health-care-relevant context.Design/methodology/approachA structured questionnaire was distributed using purposive sampling, yielding 311 valid responses. Structural equation modeling was conducted using covariance-based structural equation modeling (CB-SEM) to test and confirm the hypothesized relationships.FindingsPerceived usefulness, perceived ease of use and self-efficacy significantly influenced behavioral intention across both models. Unexpectedly, perceived severity negatively impacted behavioral intention while perceived vulnerability showed no effect, suggesting that Generation Z may be resistant to fear-based health appeals. Response efficacy and response costs were not significant, indicating that the perceived effectiveness of protective actions does not strongly shape behavioral intentions in this context.Originality/valueThis study extends the application of TAM and PMT to the context of wearable health-related technology among an emerging market demographic. It reveals generational resistance to traditional health fear appeals and highlights the importance of self-efficacy and perceived usefulness in shaping health-tech adoption.
PurposeThis study aims to investigate the influence of short-form videos on consumers' purchase intentions toward medical aesthetic products, focusing on how informational value, interactivity, credibility and visual appeal affect perceived value.Design/methodology/approachData were collected through an online survey and analyzed using structural equation modeling to examine the relationships among content attributes, perceived value and purchase intention.FindingsCredibility, informational value, visual appeal and interactivity significantly affect perceived value, which in turn influences purchase intention. Credibility emerged as the most influential attribute, highlighting the importance of trust and expertise in high-involvement, high-risk contexts.Originality/valueThis study extends digital marketing research to the medical aesthetics industry, demonstrating how multiple content attributes jointly shape consumer perceptions and purchase intentions. Practical insights are provided for marketers to design effective, credible and engaging short-form video content.
