Identifying potential service flow and actual service flow: Source-flow-sink-use framework and case study.

ABSTRACT Acoustic propagation delays, bandwidth limits, and node mobility are all big problems for underwater wireless sensor networks (UWSNs). We present a unified analytical framework that combines network function virtualization (NFV) and stochastic network calculus (SNC) to meet the need for reliable communication with low latency. Using VNFs made for underwater environments, our method simulates per‐flow delay limits, queue prioritization, and dynamic service chaining. We test the framework by running many simulations in different UWSN scenarios using OMNeT++. The results show that the end‐to‐end delay, packet delivery ratio, and energy efficiency have all improved significantly. This proves that NFV‐SNC integration can be used in real life for underwater applications like marine farming. To make sure the proposed method works, a comparison of the analytical model and simulation data is done. The goal of this study is to improve network architecture so that it can impose delay limits and improve overall performance. The problem is to achieve reliable and quick communication in UWSNs. People think that dynamic optimization using NFV will greatly improve the reliability and performance of UWSN communication systems.

Patient registration services are the first step in the entire hospital service chain. The manual registration process that is still widely used causes long queses, long waiting times, and reduces patient satisfaction. To overcome this, the Ajibarang Regional General Hospital (RSUD) has developed an innovative barcode based service called SIAP CERIA (Fast, Responsive, Informative, and Accountable Service Application Information System). This study aims to design a simpler, more interactive barcode based outpatient patient registration application user interface that meets the needs of both patients and staff. The method used is the Waterfall model of the System Development Life Cycle (SDLC) approach, through the stages of needs analysis, design, and prototype creation using Figma. The results of this research are the design of an outpatient registration application interface that includes a login page, new patient registration, general and BPJS patient registration, schedule and doctor selection, medical resume, and a barcode feature to speed up the patient check-in process. This interface design is expected to improve the efficiency of registration services, reduce queues, and provide a better user experience.

Purpose The purpose of this study is to use cognitive mapping to identify and analyze the success factors necessary for integrating lean principles into the supply chains of ground handling services in the aviation sector. Design/methodology/approach This study uses cognitive mapping to identify success factors for implementing lean principles in ground handling services. Cognitive mapping visually represents cause-and-effect relationships, highlighting interconnected processes and offering insights for improvement. Data was collected through structured interviews with two ground handling experts and two aviation management academics. Decision Explorer software was used to construct cognitive maps and reveal the importance of various factors. Findings This study identifies 13 success factors crucial for lean integration in ground services and uses cognitive mapping to explore their interconnections. The maps show relationships between key factors such as leadership, employee training, automation and cost management, emphasizing their impact on operational efficiency and customer satisfaction. These findings offer valuable insights for both practitioners and researchers. Originality/value This research contributes to the growing body of knowledge on lean transformation in the aviation sector. It offers guidance for practitioners aiming to enhance efficiency, reduce costs and maintain high safety and quality standards. In addition, it provides a theoretical foundation for further exploration of lean management’s impact on ground handling services and aviation supply chains.

ABSTRACT This study explores the pathway mechanisms of host-guest interaction within the context of costumed tourism. Utilising Actor-Network Theory (ANT) as the analytical framework, this research examines findings from participant observation and an in-depth analysis of 22 interviewees in Xijiang Qianhu Miao Village, resulting in the following conclusions: Diverse human and non-human actors occupy pivotal positions in host-guest interactions, shaping the various stages of costumed tourism. The interaction mechanism exhibits a layered structure, with a central core comprising costumed tourists, and three surrounding layers: the costume service chain, the photography community, and the prevailing atmosphere. This framework introduces a novel layered path model, addressing gaps in knowledge about costumed tourism and enhancing comprehension of indirect and intangible actors in host-guest interactions. Furthermore, the study underscores the value of costumed tourism, while also emphasising the crucial role of governments in these processes.

Purpose As government services have become increasingly anthropomorphic, intelligent and comprehensive, digital governments are introducing anthropomorphic design methods commonly used in the commercial field to build chatbots. However, government services are different from commercial services in seriousness, authority and other characteristics; if the use of anthropomorphism is not good, it may strengthen the public's stereotype of the government and reduce its credibility. Therefore, the questions of whether and how anthropomorphism should be applied to government services must be answered. Design/methodology/approach By constructing an interactive chain of government services, this study examined the impact of government chatbot anthropomorphism on users' perceived trust in the government from the perspectives of service providers, service receivers and service results. A research model was constructed with the anthropomorphic degree of the government chatbot as the independent variable, psychological distance and trust in the chatbot as the serial medium, trust in government as the dependent variable and self-construction and service outcome titers as the moderating variables. Three formal studies were conducted using the method of situational manipulation experiment. SPSS (version 26.0) was used for the statistical analysis of the experimental data to verify the research hypothesis. Findings The results show that the degree of anthropomorphism of government chatbots has a positive impact on trust in government, psychological distance and trust in chatbots play a mediating role in the above process, and psychological distance plays a moderating role between the degree of anthropomorphism of chatbots and trust in chatbots. Authoritarian obedience personality (high versus low) moderates the relationship between psychological distance and chatbot trust. Originality/value The findings demonstrate that conclusions about meeting user expectations through technology in the business sector can also be applied to government services due to the similarities between the two. This study defines the service interaction chain from the perspectives of service receivers, providers and outcomes, applying it to government services – thereby expanding and enriching service chain theory. Additionally, it uncovers the mechanisms behind trust in government, representing a novel application of trust transfer theory in the context of government affairs. The study contributes to existing theoretical research and offers practical recommendations for government management departments and digital government service providers.

In 2024, China’s cross-border exports of beauty and personal-care products exceeded USD 42 billion, of which transactions completed through the TikTok ecosystem leapt from 6.7 per cent in 2022 to 28.4 per cent—becoming the fastest-growing single channel. Drawing on triangulated data released by the General Administration of Customs of China, GoodsFox and TikTok Ltd., this paper traces the evolutionary trajectory of Chinese beauty brands on TikTok in terms of transaction volume, traffic structure and user equity. The findings reveal that the emerging paradigm of “content-as-shelf” has re-configured the conventional person–goods–place logic. However, rapid expansion has been accompanied by a triad of tensions—regulatory uncertainty, cultural discount and insufficient supply-chain resilience—leading to a 4.3-percentage-point year-on-year increase in return rates in Europe and North America during the first half of 2024 and a repurchase rate 9.6 percentage points lower than that of Japanese and Korean competitors. To address these pain-points, we propose a compliance-front-loaded, data-driven dual-circular interest-commerce framework that embeds U.S. FDA and EU EC No 1223/2009 regulatory nodes into the entire chain of product selection, live streaming, payment and after-sales service, while a DeepSeek time-series model forecasts sub-national tax burdens and public sentiment in real time to enable dynamic pricing and inventory diversion. The case of KANS, which topped Douyin’s beauty GMV list for eleven consecutive months in 2023–2025, illustrates how the brand replicated the loop of “short-drama seeding – KOL conversion – private-domain retention” in Vietnam, Thailand and Malaysia, raising quarterly repurchase rates in Southeast Asia to 42.7 % and increasing average order value by 18.5 % compared with legacy shelf-commerce. We argue that only by translating compliance capabilities into differentiated narratives and upgrading data assets into brand equity can Chinese beauty brands build a sustainable competitive moat within TikTok’s decentralized traffic arena.

This study aims to draw attention to important issues related to cell phone SIM cards in terms of obligations and rights by elaborating the reality of these SIM cards and defining the contractual relations between customers and telecommunication companies in the chain of services associated with these SIM cards with their various characteristics and privileges. It has become very important to know the Sharῐ'ah regulations in this new transaction that has emerged from the scientific development in our era as the use of cell phones has become a necessity of daily life. Therefore, it is necessary to know the jurisprudential adaptation of this multidimensional service, duties and rights. The study relies on the descriptive analytical method in collecting and analyzing scientific data to achieve the objectives. Therefore, the main topics of this study are: jurisprudential adaptation of contractual relations between customers and telecommunication companies when purchasing SIM cards. The impact of SIM cards for cell phones and their credit balances. The impact of the services of SIM cards for cell phones and their credit balances. The study concluded that the contractual relationships between telecommunication companies and customers consist of several hybrid relationships between sale and condition, leasing and subscription, but are not free from objections as they involve some transactions that violate the terms of sale and leasing. The study also pointed out the need to differentiate between the acquisition of SIM cards through a monthly subscription contract and their acquisition through a purchase contract and condition, and that the jurisprudential adaptation of the cell phone service must be taken into account by the parties involved in this contract and each party must adapt to what suits it in terms of form and legal regime according to the consequences it entails.

BackgroundTo improve institutional healthcare quality and enhance the service delivery experiences of hospitalized patients and family members, it is essential to identify and address their core experiential needs at both the systemic and individual levels. Admission and discharge are critical points in the hospital service chain that significantly shape overall service experience. Traditional workflows are often fragmented and inefficient, resulting in reduced patient satisfaction and service efficiency. In response, a “one-stop” smart admission and discharge service was introduced in a tertiary hospital in Qingdao, China. It integrated digital functions, including registration, inpatient payment, insurance processing, and discharge settlement, into a streamlined, patient-centered system. This study aimed to identify the core experiential dimensions of this service from the perspectives of patients and family members. It offers practical insights for service optimization and digital health innovation.MethodsA descriptive qualitative study was conducted between February and April 2024. Semi-structured interviews were performed with 11 patients and 12 family members across four inpatient departments. Data were analyzed using Colaizzi’s seven-step phenomenological method. The Consolidated Criteria for Reporting Qualitative Research (COREQ) checklist was applied to guide reporting and ensure methodological rigor.ResultsTwo overarching themes emerged: (1) perceived benefits of the service for patients and family members, including improved procedural efficiency, reduced non-medical waiting time, and enhanced convenience; and (2) perceived areas for improvement of the “one-stop” smart admission and discharge service, such as limited digital support for older adults, occasional system instability, and insufficient integration with insurance platforms.ConclusionsThe service was generally perceived positively by patients and family members, who appreciated its efficiency and convenience. However, several practical challenges were identified. Enhancing user support, particularly for vulnerable groups, and strengthening system stability, financial security, and interoperability through stakeholder collaboration may further optimize patient-centered care delivery in digital health contexts.

Abstract The BTS structure was used for the Smooth service chains coaching to support wellbeing services counties to design multiprofessional service chains and pathways for clients in vulnerable positions. The teams consisting of professionals from different services and of an expert-by-experience attended four workshops and active working periods within 12-15 months. Coaches assisted the teams to use different Lean tools to analyse the current situation (e.g. value stream map), to set SMART goals, to model an ideal service path and plan PDSAs to support designing the process and/or implementing it. Also, the teams were advised to collect data to analyse the achieved change and report their models and evaluation results in a national website that operates as a platform for innovation and co-design. A process evaluation was conducted to analyse how the coaching model was implemented, how the activities triggered change and how external factors influenced functioning of the coaching. The data was collected from two coaching rounds which had a total 18 teams participating. Of these, six development teams (n = 31) and five process owners (n = 9) attended group interviews. Also, an interview of coaches (n = 4) and the design team (n = 3) were conducted. The data also includes feedback surveys of all participants in the studied rounds (n = 97) and reporting sheets for teams’ results. The main benefits the participants experienced concerned being able to model the service chain or pilot a new solution, gaining new skills for development work, learning to use different tools, understanding how to form measurable aims and track changes, and becoming familiar with other stakeholders’ work. The challenges included how the new service chains can be implemented and sustained and how to measure the outcomes after the coaching ended. To conclude, the original functions of the Model for Improvement were present but designing and implementing a new service path within the time was challenging.

Abstract Background Mental health conditions (MHCs) are becoming one of the most urgent public health issues in youth across Europe, especially among young women. These include depression, anxiety, substance use, and suicidal behaviour. Many of these conditions start already before the age of 24. However, many current approaches still focus too much on individual diagnoses and symptoms. We need a broader understanding that includes social, environmental, and systemic risk exposures. The EARLY project is addressing this gap by using a transdiagnostic and multi-level approach, with focus on prevention and early intervention through caring and proxy-caring strategies. Objectives The aim of this roundtable is to present new ways to understand and support youth mental health in Europe. Drawing on EARLY's mixed-methods, multi-country evidence base, we discuss how mental health is influenced by a wide range of factors beyond the individual level, and how multicomponent interventions-developed together with young people and communities-can improve outcomes. This includes support not only for the youth themselves, but also for their families, schools, and local environments. Structure After a short introduction by the chairs, six expert contributions will explore: 1. An overview of the transdiagnostic and exposure-based framework developed in EARLY. 2. Main findings from a recent umbrella review of mental health models. 3. An assessment of youth mental health and psychosocial care structures across Europe, including a first-hand local perspective from Helsinki, Finland. 4. Description of a multi-level and gender-sensitive intervention piloted in the EARLY project. 5. The role of the European Public Health Association (& public health networks) in dissemination of EARLY's project results for a sustainable impact. Local relevance The Roundtable entails an experience from Helsinki, Finland. A local report based on consultations with young people and service providers shows that mental health services are often fragmented. Many young adults with mental health problems fall between services. A recent participatory assessment involving young adults and professionals highlighted the need for integrated, relational approaches-such as the “pair method”-that build long-term trust with young adults “stuck at home” and bridges gaps in service chains. Audience engagement The second part of the session is a moderated discussion, inviting audience interaction and debate, supported by the Sli.do platform. Participants will be invited to share examples, raise questions, and reflect on how these approaches can be used in different local or national settings. Key messages • Youth mental health is a Public Mental Health challenge. • Interdisciplinary and intersectoral collaboration is needed to better respond to youth mental health needs. Speakers/Panellists Jutta Lindert Hochschule Emden-Leer, Emden, Germany Giuseppe La Torre Sapienza University of Rome, Rome, Italy Erika Valtonen Ukraine Henrique Barros ASPHER, Porto, Portugal

Abstract There are several training models to support the implementation of scientific evidence to improve quality or effectiveness of care. Meanwhile, participatory approaches for workplace-oriented development and design of new practices, processes and services have been increasingly used in health and social care. Implementation research has long discussed the possibility to transfer models to new contexts. Because contexts differ, transferring may require making adaptations to the model, for example, regarding the forms of support or the target group. However, sometimes the model or intervention drifts because of misapplications or abandonment of core components. This session aims at discussing the adaptations of The Breakthrough Series (BTS) in Finland. BTS is the most well-known model for the quality improvement collaboratives (QIC), and it was developed in the institute for Health Improvement (IHI) in 1995. The model is freely available and is widely spread around the world. According to IHI, a BTS process typically lasts 6-18 months. The key elements of BTS are 1) selecting a topic where existing scientific knowledge is sound, but not widely used, 2) group of experts designs the aims, measurement strategies and list of evidence-based changes and 3) provides coaching to 4) multidisciplinary teams from multiple sites. The teams then participate in 5) learning sessions and 6) in active working periods in-between the sessions, the teams test changes in their local settings and collect data to measure these changes while 7) they learn carrying out the Model for Improvement including Plan-Do-Study-Act cycles (PDSA). In 2022-2025, the BTS model was integrated into two national development programs in Finland. The Ministry of Social Affairs and Health mandated that all wellbeing services counties receiving EU Recovery and Resilience Facility funding (2022-2025) participate in BTS, facilitated by the Finnish Institute for Health and Welfare, and develop multiprofessional service chains for vulnerable groups. Secondly, projects funded by the Good Work Programme (2022-2027), initiated by Prime Minister Orpo's Government, were guided by the Ministry to participate in BTS facilitated by the Finnish Institute of Occupational Health, aiming to improve personnel attraction and retention models. The BTS model was chosen as a pedagogical model because it had been used in several projects in Finland to improve the waiting times of health services (2010-2023). However, applying the model for two entirely new purposes required several changes and adaptations. Therefore, the three presentations in the session discuss the history of transferring the model between countries, how its theoretical and epistemological backgrounds have evolved, and what kinds of results and impact the training model's elaborated versions have produced in Finland. Key messages • Training and coaching models tend to adopt culturally convenient and popular theoretical resources while they transfer between countries. • Eclectic combinations of theoretical approaches in training and coaching models both enrich and create incompatible dynamics from the participants’ perspective for learning.

BACKGROUND:Regionalized health systems are expected to provide an integrated chain of services for a defined population. However, developing such systems is possible only through alignment across policy, administrative/coordinative, and operational levels. The present study aimed to identify the requirements for such alignment among various levels of Iran’s health system.METHODS AND MATERIAL:This qualitative study was conducted with experts in related departments of the Ministry of Health and Medical Education in Iran and selected universities over five months in 2023–2024. Fifteen semi-structured interviews were conducted with policymakers and academic experts to collect the study data. The data were grouped into three themes based on thematic content analysis using the MAXQDA software.RESULTS:Three main categories of requirements for developing regionalized health systems, encompassing policy, administrative/coordinative, and operational levels, and 23 sub-themes, were extracted. Like other hierarchical health systems, the country’s health system faces fundamental challenges due to insufficient organizational infrastructure, which hinders its transition into an integrated healthcare management system.CONCLUSIONS:Given the legal obligations imposed on the Ministry of Health and Medical Education to establish an integrated regionalized health system and the failure of the relevant initiatives, it is critical to develop the essential infrastructural requirements across levels to achieve this goal.

The rapid evolution of artificial intelligence and machine learning technologies has reached a critical juncture where theoretical advances are materializing into practical applications across mission-critical sectors, particularly in financial services and supply chain management. This article examines the emergence of three transformative AI paradigms—Reinforcement Learning, Federated Learning, and Explainable AI—which collectively form an interdependent "Trust Triad" that addresses the complex requirements of dynamic decision-making, privacy-preserving collaboration, and regulatory transparency in high-stakes environments. The article demonstrates that effective AI deployment in regulated industries requires simultaneous integration of these technologies rather than sequential implementation, as each paradigm addresses complementary challenges inherent in modern business operations. Reinforcement Learning provides adaptive optimization capabilities essential for navigating volatile market conditions and complex supply networks, while Federated Learning enables collaborative intelligence development across organizational boundaries without compromising data privacy or competitive sensitivities. Explainable AI ensures the transparency and accountability demanded by regulatory frameworks and stakeholder trust requirements. Through a comprehensive analysis of implementation strategies, case studies, and emerging challenges, this article reveals that successful AI adoption necessitates holistic risk management frameworks addressing both traditional business risks and novel AI-induced meta-risks including algorithmic bias, security vulnerabilities, and societal implications. The article indicate that organizations achieving integrated Trust Triad implementations demonstrate superior performance in operational efficiency, risk management precision, and regulatory compliance while maintaining competitive positioning. However, success requires substantial organizational transformation encompassing technical infrastructure, interdisciplinary collaboration, governance frameworks, and change management strategies that extend beyond mere technology deployment to fundamental business model evolution.

Next-generation networks require more efficiency in scaling and programming capabilities. Since SR facilitates effective path computation, service chaining, and traffic engineering, it appears essential for next-generation network routing. In this document, I introduce a novel evaluation framework called Segment Routing - Performance Evaluation and Routing Framework (SR-PERF) which aims to evaluate the operational effectiveness, scalability as well as Quality of Service (QoS) compliance of segment routing protocols - SR-MPLS and SRv6 - in contemporary IP and SDN contexts. The SR-PERF model merges a multi-metric evaluation engine with key performance indicators such as path setup latency, end-to-end delay, control plane expenses including overhead, segment loss under dynamic links, and packet loss during dynamic link conditions. Using custom topologies within Mininet together with ONOS and FRRouting controllers enables simulation. Results presented show SRv6 improving on metrics such as backbone convergence time by 13.7% when compared to SR-MPLS alongside better adaptability during link drop scenarios despite slightly higher memory consumption due to header overhead stemming from IPv6. Moreover hybrid deployments incorporating intent-based path selection outperformed static OSPF/MPLGS baselines demonstrating improved throughput by 21% while reducing packet drops by 17%. This paper also studies the impact of increasing node density alongside traffic flow on the scalability of segment routing. The results point out that the control plane stability and the segment stack depth have a greater impact on SRv6 performance past 128 nodes, revealing some design compromises for hardware-limited systems. Lastly, described in this work are dashboards provided by the proposed SR-PERF framework which visualize routes and segments in real time aiding proactive segmentation optimization in programmable networks. The results also highlight that with SR-PERF it is possible to benchmark SR variants in a diverse setting enabling better informed selection and tuning of protocols for deployment within carrier-grade and cloud-native infrastructures.

This study explores the adoption of artificial intelligence (AI) in digital commerce platforms and whether such adoption is aligned with market positioning changes. Focusing on five of the largest e-commerce companies—Amazon, Apple, Shein, Temu, and IKEA—the study examines the application of AI in six key areas of operation: customer service, logistics, personalization, security, and supply chain management. A two-stage qualitative method was employed: a Scopus database-organized literature review, and a walkthrough examination of each company’s home page. There is extensive diversity in the deployment strategies of AI, which business models and digital maturity drive, the findings show. Amazon has end-to-end integration, but newer entrants such as Shein and Temu are concentrating on customer-facing AI tools. Apple, although it uses AI across its ecosystem, illustrates few examples in its online store. Notably, the rankings of firms under study align with their 2023 revenue rankings. Although no cause-and-effect relationship is assumed between the adoption of AI and revenue performance enhancement, the existence of a correlation suggests that AI could facilitate strategic differentiation. A comparative method for analyzing the adoption of AI is proposed in the study and highlights the importance of ethical, organizational, and regulatory concerns. Subsequent research should involve empirical measures of performance, longitudinal monitoring, and user-led assessments to enhance understanding of the impact of AI on digital trade.

BackgroundChina’s 3-child policy has increased the demand for scientific and personalized pregnancy health management. The convenience of mobile health has promoted the use of pregnancy management apps among pregnant women. User satisfaction has a significant impact on continued use intention. Systematically evaluating user satisfaction with pregnancy management apps is of great significance in promoting the digital transformation of maternal-infant health care.ObjectiveThis study aimed to explore user satisfaction with pregnancy management apps by mining user-generated content and analyzing the differences in user satisfaction among different operating systems. Under the guidance of Herzberg two-factor theory, this study explored the demand structure in user experience and investigated the influencing factors on satisfaction from 2 aspects: user satisfaction and dissatisfaction, providing reference for the development of mobile health apps for pregnancy management.MethodsWe screened pregnancy management apps from the app stores of 5 mobile phone manufacturers in mainland China and collected the app-based reviews and ratings posted by users. We performed topic clustering and semantic parsing using the latent Dirichlet allocation and DeepSeek-R1 models. Influencing factors for satisfaction and dissatisfaction were identified using the Tobit regression model. The Kano model was used to classify the factors as basic or attractive. The Wald test was applied to analyze the differences in the effects across various factors.ResultsWe examined 86 pregnancy management apps, amounting to 180,107 reviews in total. The overall satisfaction rate with pregnancy apps was relatively high (72.34%). Android users had higher satisfaction rates than iOS users (89.32% vs 60.75%). User reviews were clustered into 12 themes, categorized into 3 types: technical security support, basic service experience, and maternal-infant scenarios. The basic factors causing dissatisfaction included system login (β=2.829; P<.001) and privacy disclosure (β=1.955; P<.001). Attractive factors boosting satisfaction included storage optimization (β=0.220; P<.001), page design (β=0.223; P<.001), function provision (β=0.023; P=.001), platform feedback (β=0.222; P<.001), physicians’ inquiries (β=0.356; P<.001), menstrual management (β=0.209; P<.001), pregnancy guidelines (β=0.306; P<.001), parenting science popularization (β=0.238; P<.001), growth record (β=0.401; P<.001), and maternal-infant community (β=0.307; P<.001).ConclusionsThere were significant differences in user satisfaction between the iOS and Android platforms, reflecting the heterogeneity of responses to user demands in different technological ecosystems. Twelve themes showed the multilevel needs of pregnant women for pregnancy management apps, forming a progressive service chain: security guarantee to demand satisfaction to experience improvement. Twelve factors had asymmetric correlations with user satisfaction and dissatisfaction with pregnancy management apps. Two factors were related to basic attributes of the apps and 10 factors to attractive attributes. By distinguishing between basic and attractive factors, the use of pregnancy management apps may be improved.

This article focuses on the AI enabled full chain school enterprise collaborative education model. By analyzing the current research status and practical difficulties of universities at home and abroad, it reveals the value logic of this model in reconstructing talent training processes, improving educational visualization efficiency, and supporting intelligent talent supply. We have developed a model for the collaborative education mechanism between schools and enterprises throughout the entire chain under the empowerment of AI. The implementation strategy includes promoting the deep application of AI technology in the entire chain of demand forecasting, teaching process, practical management, and employment services, improving data sharing security mechanisms, smart contract benefit distribution mechanisms, and policy and institutional guarantees, achieving precise integration between education and industry, effectively solving the problem of industry education "chain breakage", and promoting the development of education models to a deeper level.

Biodiversity-Climate-Society Nexus assessment through Participatory System Dynamics Model. The case study of Amazon forest-based value chain.

In the digital age, high-quality visual content plays a critical role in marketing, real estate, and personal branding. However, traditional image and video editing workflows remain manual, fragmented, and time-consuming. This paper proposes an expert system that automates the entire service chain of photo, video, and virtual architectural editing by integrating advanced technologies such as AI, chatbots, cloud computing, and blockchain. The system intelligently analyzes customer requests, assigns tasks to AI modules or human editors, ensures quality control, and securely manages payments through smart contracts. Designed as a cloud-native, microservice-based architecture, the platform is scalable and resilient, offering services through both web and mobile interfaces. Simulation results show a significant reduction in turnaround time, enhanced consistency in output quality, and increased processing capacity. By automating both technical and operational processes, the proposed system aims to transform digital content services into a seamless, efficient, and trusted experience. It has strong potential to attract customers and investors, especially in industries demanding fast, cost-effective, and scalable media solutions.