Nowadays information logistics and its integration with information systems is a competitive advantage for a company. The focus is on theoretical knowledge gained from e-maintenance environments, security measures, and objectives. In companies, it is important to conduct a risk analysis and subsequently to specify security measures. Risk analysis focuses on the creation of a Quality Function Deployment (QFD) matrix, taking into account customer requirements, with the outcome being the determination of the importance of these requirements. The result of the regression and correlation analyses confirm the research hypothesis, demonstrating a strong positive relationship (r = 0.849) between flexibility in problem solving and the implementation of security measures. The Mann–Kendall test was used to verify the trend of specified solved problems. When performed on the current data set, the test provided a variance of S = 31 and a standardized test statistic of Zs = 2.0669. The outcomes of this article may guide organizations in refining their security strategies using customer-driven methodologies such as QFD. The field of information logistics and its integration with information systems can be beneficial for companies.

Purpose Rail freight is widely recognized for its economic and environmental advantages, yet it remains weakly integrated into firms' supply chains, particularly in emerging economies. This study aims to investigate the conditions under which rail freight can be effectively integrated into multi-actor supply chains, with specific attention to the role of organizational coordination, information quality and artificial intelligence (AI) in shaping logistics integration outcomes. Design/methodology/approach The study draws on a quantitative survey of 3,185 stakeholders involved in rail-based and multimodal supply chains in Morocco. The data are analyzed using a combination of machine learning, deep learning and artificial neural network models. These methods are used not only to identify the main determinants of rail freight integration but also to capture non-linear relationships, interaction effects and potential integration trajectories that cannot be addressed through conventional linear models. Findings The results show that rail freight integration depends primarily on organizational and informational mechanisms rather than on infrastructure alone. Inter-organizational coordination and logistics information quality emerge as the most influential factors. AI contributes positively to rail freight integration, but its effect is conditional: AI tools significantly enhance integration only when adequate levels of coordination and information sharing are already in place. Scenario simulations further reveal that the strongest integration gains arise from the combined improvement of organizational practices and AI adoption. Originality/value This research contributes to the literature by shifting the focus from infrastructure-centered explanations toward a systemic understanding of rail freight integration. It is among the first studies to empirically combine machine learning, deep learning and artificial neural networks to analyze logistics integration in an emerging-economy context and to show that AI functions as a complementary and amplifying mechanism rather than a standalone solution.

Purpose: This study sought to establish the influence of outsourcing strategies on the performance of selected media houses in Kenya. The study specifically sought to establish the influence of information technology outsourcing, customer care management outsourcing, human resource outsourcing, and logistics outsourcing on the performance of selected media houses in Kenya. Methodology: The study was guided by the following theories: Transaction Cost Theory, Resource-Based View Theory, Core Competency Theory, and Human Resource Theory. A descriptive research design was used in this study. The target population comprised 3 media houses in Kenya, with the unit of observation being employees in managerial positions in the IT department, Customer Care Department, Human Resource Department, and transport and logistics department. The study adopted Yamane’s sampling formula to acquire a sample of 165 respondents from the target population. The instrument for primary data collection in this research was a numerical 5-point Likert scale questionnaire. The data collected was analyzed by employing descriptive statistics and inferential analysis using the Statistical Package for the Social Sciences (SPSS) version 21 and MS Excel Software. Findings: The results of the study revealed that information technology outsourcing, customer care management outsourcing, human resource outsourcing, and logistics outsourcing positively and significantly influence the performance of the selected media houses in Kenya. The findings indicate that these outsourcing practices positively and significantly influence the performance of media houses, underscoring their strategic value in enhancing organizational effectiveness and competitiveness. Unique Contribution to Theory, Practice and Policy: The study recommended that selected media houses strengthen their performance by enhancing strategic outsourcing practices across key functional areas. Specifically, the study advocates for increased information technology outsourcing, including system development, network management, call center operations, and maintenance of applications and operating systems. It further recommends outsourcing customer care management through collaborative customer engagement, support services, and innovative retention strategies implemented by external vendors. In addition, the study emphasizes outsourcing human resource functions such as recruitment, training, performance appraisal, restructuring, and downsizing processes to competent firms. Finally, it highlights the importance of logistics outsourcing, including inventory, procurement, order management, transport, and information management functions.

Abstract This article expands the historiography of nineteenth-century architecture by centering the logistics of information and money, people, and materials. Beginning with the 1857–58 uprising in India, it examines both buildings and infrastructure through previously unexplored archival material at the British Library and the British National Archives, alongside unpublished clerks’ memoirs and a range of gray literature. These sources and the methodological approach taken foreground previously unexplored aspects of the building’s interiors and equipment related to bureaucracy and political economy, addressing the India Office not as a singular object but as part of a system that enabled military, financial, and colonial operations. Through transregional analysis, the article situates the monumental India Office headquarters in London within a broader network of British imperialism that includes an off-site warehouse (the India Store Depot), a hostel for migrant workers (the Strangers’ Home), telegraph offices across India, and global financial markets.

Purpose This study investigated the influence of logistics information flow on resilient disaster relief operations in Tanzania. It aimed to determine how different aspects of logistics information sharing contribute to enhanced coordination and responsiveness during humanitarian interventions. Design/methodology/approach The study adopted a positivist philosophy and employed an explanatory research design, guided by coordination theory. Data were collected using questionnaires and interviews from humanitarian practitioners in Dodoma, Dar es Salaam and Kigoma. A sample of 192 was drawn from a population of 369 using Slovin's formula. Data analysis utilized SPSS version 27, combining both quantitative and qualitative approaches. A multiple linear regression model was applied to examine the significance and predictive power of logistics information flow variables (LOIF1–LOIF6). Findings Logistics information flow variables demonstrated statistically significant effects (p = 0.000), with an R-squared of 0.78 and an Adjusted R-squared of 0.76. Timely and accurate information sharing (LOIF1, β = 0.351) had the highest impact, followed by automated inventory tracking (LOIF4, β = 0.298) and structured information exchange (LOIF2, β = 0.289). Real-time control (LOIF3) and integrated databases (LOIF5) contributed positively, though with slightly lower coefficients. Research limitations/implications The geographic scope was limited to three Tanzanian regions, but can be generalized in other developing economies. Future studies should expand to more diverse contexts and explore longitudinal impacts. Practical implications Humanitarian actors should institutionalize real-time information systems and automate tracking mechanisms to improve coordination, reduce delays and enhance disaster response effectiveness. Social implications Effective logistics information flow improves the timely delivery of aid, reduces human suffering and promotes social cohesion and trust between communities and humanitarian agencies. Originality/value The study advances coordination theory by modeling logistics information flow as a strategic enabler of disaster relief resilience.

Abstract The logistics industry currently faces a prevalent "data silo" issue. This leads to information isolation and system fragmentation and severely restricts the ability of cross-platform business collaboration and intelligent decision-making. To address this problem, this paper proposes a non-intrusive logistics system architecture design for data silo integration. The architecture is based on key mechanisms such as edge access, protocol abstraction, and a unified data bus. It realizes lightweight integration of heterogeneous logistics information systems, and features low coupling, high compatibility, and strong adaptability. The designed system includes acquisition layer protocol adaptation components, transport layer edge routing mechanisms, and platform layer intelligent processing engines. It supports multi-protocol concurrent access and fault self-recovery capabilities. Deployment and testing in enterprise scenarios show that the system outperforms traditional solutions in data acquisition delay control, stability maintenance, and multi-protocol adaptation. The non-intrusive system not only leads significantly in throughput, reaching 12,000 entries per second. This is much higher than the 7,500 entries per second of traditional Application Programming Interface (API) integration and the 9,200 entries per second of the Enterprise Service Bus (ESB) architecture. It also performs excellently in average response time, which is only 45 milliseconds, significantly lower than the other two solutions. In particular, this system achieves efficient integration without modifying the original systems and effectively solves the problem of coexisting multi-systems and non-interoperable data in enterprises. This paper provides a promotable reference architecture for the informatization transformation of logistics.

Timely and continuous drug availability is a key indicator of hospital service quality; however, drug stagnation (overstocking) and stockouts persist as critical challenges in the Pharmacy Unit of North Buton Regional Hospital. This qualitative case study aimed to analyze the implementation of drug logistics management and its contribution to these problems, involving in-depth interviews with drug logistics managers, the head of the pharmacy unit, and hospital management, complemented by document review and field observations. Data were thematically analyzed using NVivo and benchmarked against the indicators stipulated in the Indonesian Minister of Health Regulation No. 72 of 2016. The findings reveal that most stages of logistics management planning, procurement, receiving, storage, distribution, and control were suboptimally implemented. Drug stagnation was primarily driven by inaccurate demand forecasting and uneven distribution, whereas stockouts resulted from supply delays, weak procurement coordination, and the limited effectiveness of the Pharmacy and Therapeutics Committee. Overall, deficiencies in the logistics information system, constrained human and financial resources, and poor inter-unit integration emerged as the main underlying factors, indicating the urgent need for strengthening data-driven demand planning, optimizing the role of the Drug Logistics Unit (KFT), and developing an integrated logistics information system to improve drug availability and service performance at the hospital.

BackgroundDiabetic foot (DF) is a severe complication of type 2 diabetes mellitus (T2DM), contributing to significant morbidity and healthcare costs globally. Early prediction and intervention are critical for preventing amputations and improving patient outcomes. However, traditional statistical methods lack the capacity to handle high-dimensional clinical data and identify optimal predictive features. This study aimed to develop and validate machine learning models for DF risk prediction using feature selection strategies based on binary logistic regression and information theory.MethodsA retrospective cohort of 1,179 patients (95 DF cases, 1,084 T2DM controls) was analyzed using clinical and biochemical data from 2019 to 2025. Three data sets were constructed: (1) original features; (2) features selected via binary logistic regression (F1); and (3) features selected via information-theoretic global learning (F2). Six models—extreme learning machine (ELM), kernel extreme learning machine (KELM), and their variants trained on the three data sets—were evaluated using fivefold cross-validation. Performance metrics included area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and computational efficiency.ResultsAge, blood–urea–nitrogen (BUN), homocysteine (Hcy), albumin (ALB), and fasting blood glucose (FBG) were identified as independent DF risk factors. The information theory-based KELM (IT–KELM) model achieved the highest AUC of 0.799 (sensitivity: 0.792 and specificity: 0.710) on F2, outperforming other models. Feature selection improved predictive accuracy while reducing computational time, with IT–KELM requiring 0.138 s for training and 0.0023 s for testing. The SHAP summary dot plot and bar chart revealed that the top five features contributing to the model were TP, RBC, ALB, BMI and HB.ConclusionsIntegrating information theory with KELM enhances DF risk prediction by optimizing feature subsets and leveraging nonlinear kernel mapping. The IT–KELM model demonstrates robust diagnostic performance and clinical feasibility for early DF screening. Future multi-center studies are needed to validate generalizability and refine model interpretability in real-world settings. This approach provides a cost-effective tool for precision medicine in diabetes care.Graphical abstractSupplementary InformationThe online version contains supplementary material available at 10.1186/s12938-025-01494-2.

To quantify and map regional variations in antibiotic consumption across Tanzania using national supply-chain data to guide antimicrobial stewardship (AMS) priorities. A retrospective facility-level analysis was conducted using antibiotic distribution data from the electronic Logistics Management Information System (eLMIS), covering the period from July 2020 to June 2024. Public healthcare facilities across Tanzania's 26 administrative regions. Antibiotic consumption was standardized using the WHO Anatomical Therapeutic Chemical (ATC) classification and expressed as defined daily doses per 1,000 inhabitants per day (DID). Variations by region, facility level, and antibiotic class were analyzed descriptively and visualized through geospatial mapping. National trends and forecasts for 2025-2027 were modeled using autoregressive integrated moving average (ARIMA) and polynomial regression models. A total of 1.63 million facility-level records were analyzed. National antibiotic consumption rose from 142.4 to 182.8 DID between 2020-2021 and 2023-2024 (a 28% increase). Dispensaries accounted for 71% of the total DID, underscoring the dominant role of primary-care facilities in antibiotic distribution. Dar es Salaam (37.9 DID), Ruvuma (34.5 DID), and Lindi (34.0 DID) recorded the highest cumulative consumption, whereas Katavi (13.7 DID) and Geita (15.4 DID) had the lowest. Access-category antibiotics comprised ≥60% of all consumption, Watch agents 35-40%, and Reserve agents ≤0.1%. Forecasting predicts continued national growth, reaching ≈ 215 DID by 2027 if current trends persist. Antibiotic consumption in Tanzania is concentrated in the coastal and southern regions. Geospatial analytics and digital supply chain enable targeted, data-driven stewardship interventions in resource-limited settings.

The C2B2C model mitigates trust risks in secondhand transactions by enabling platforms to intervene deeply in logistics activities, such as pickup, inspection, delivery, and after-sales services, thereby making logistics service quality a critical determinant of user experience and platform competitiveness. However, the multinode and high-uncertainty nature of C2B2C logistics processes renders user needs more sensitive and exhibits pronounced nonlinear characteristics. Against this background, this study employs text-based corpus analysis and the Kano model to identify user demand attributes in C2B2C secondhand e-commerce logistics services. The impacts of different service elements on user satisfaction are further evaluated using Better-Worse coefficients and four-quadrant analysis. On the basis the results, four attractive logistics service demands are identified: timely pickup response, rapid return collection, flexible delivery modification, and transparent logistics information. Subsequently, the TRIZ methodology is introduced to translate these demand characteristics into actionable logistics optimization strategies. Scenario-based simulations are then conducted, combining two-proportion Z-tests and bootstrap resampling, to assess potential improvements in satisfaction following strategy implementation. Results indicate that under reasonable improvement scenarios, the proposed TRIZ-based strategies yield statistically significant or marginally significant improvements in user satisfaction across all four key logistics services. Overall, this study develops an integrated logistics service improvement and validation framework that combines corpus analysis, the Kano model, and TRIZ, providing a systematic decision-support reference for optimizing logistics operations and enhancing user experience in C2B2C secondhand e-commerce platforms.

Beyond Bilateralism: Why the United Kingdom Must Align with AfCFTA's Digital Model

This study aims to analyze the application of management functions in the management of drugs and medical consumables (BMHP) to enhance efficiency and effectiveness at the Regional General Hospital (RSUD) of Nunukan Regency. The research focuses on the four key management functions: planning, organizing, actuating (implementation), and controlling (supervision), while also identifying the challenges and implications of BMHP logistics management for healthcare service quality. Using a qualitative research approach, data were collected through in-depth interviews, direct observation, and document analysis. Informants included hospital leaders, pharmacy installation heads, pharmacists, logistics staff, and patients. The results show that the planning function is carried out based on consumption methods and VEN (Vital, Essential, Non-Essential) and ABC analysis, but still lacks support from an integrated information system. The organizational structure exists, but its implementation is not yet optimal. The implementation function follows SOPs, although constrained by billing system issues and geographical challenges. Supervision is conducted both internally and externally, but regular monitoring is still limited. Key obstacles include budget constraints, payment delays, and logistics challenges due to the hospital's remote border location. Efficient and effective management has a direct impact on the quality of patient services, particularly in drug availability, service timeliness, and patient satisfaction. This research recommends improving logistics information systems, strengthening interdepartmental coordination, adjusting budgeting strategies, and increasing accountability to ensure high-quality pharmaceutical governance in regional public hospitals.

The article groups the main functional areas of logistics and marketing management in the current conditions of war and economic crises in the country. The importance of integrating marketing approaches into the logistics management system to ensure the stability of supply chains and the adaptation of enterprises to an unstable external environment is substantiated. Three groups of logistics management functions are analyzed: planning and coordination of the activities of participants in the logistics process; regulation of the progress of work on the fulfillment of received orders; control over the movement of material flows. An attempt is made to substantiate the main logistics functions: supply, production and sales, and the marketing processes of their adaptation to modern logistics processes in Ukraine are considered. The article describes the main functional areas of logistics and an integrated tool for increasing the effectiveness of marketing and logistics management. However, in logistics management, the functional areas of logistics are described in a broader sense, namely by the concepts of "inbound logistics", focused on supply and procurement functions, and "outbound logistics", associated with distribution operations. The author's position coincides with the opinion that a broader or narrower interpretation of functional areas in relation to the formation of a structural unit of a company depends on the volume of logistics operations and various marketing strategies of modern economic conditions. Therefore, in the article, traditional types of logistics and marketing management are supplemented by such functional areas as financial and information logistics. At the same time, the goal of logistics management at an enterprise is the accuracy and timeliness of fulfillment of obligations, as well as ensuring optimal flow movement at any level in the state. Studying the functional areas of logistics and marketing management will allow making effective management decisions for any variant of flow movement at an enterprise in conditions of war and crises in Ukraine. Thanks to effective logistics management and timely marketing, it can also sell its products at lower costs or provide a higher level of service to consumers-clients, and thus gain a good reputation in the market. The results obtained are of practical importance for the formation of a strategy for managing the logistics activities of enterprises, the development of state policy in the field of logistics development and marketing.

In order to meet the new demand for talent in the digital transformation of the logistics industry, and to solve the problems of disconnection between teaching and industry, as well as the solidification of teaching modes in logistics man-agement majors in higher vocational education, this study takes the course "Lo-gistics Information Technology and Application" as the object and explores the teaching reform path under the background of digitalization. Through literature research, industry investigation, empirical research, and other methods, analyze the characteristics of the curriculum and the current teaching situation, propose four teaching objectives of "strengthening theory, emphasizing practice, im-proving interest, and cultivating skills", construct an integrated teaching model of "curriculum research competition innovation", and implement strategies of "strengthening foundation, emphasizing practice, multi-dimensional evaluation, and good innovation". Through pre class preparation, integration of theory and practice during class, and post class expansion, the entire process design incor-porates elements of digital teaching. The results indicate that the reform plan can effectively improve teaching quality, enhance students' job adaptability and innovation ability. The research results can provide practical reference for the digitalization reform of logistics courses in higher vocational education and en-rich the teaching theory of vocational education.

This paper addresses real-world agricultural transport logistics optimization in Uzbekistan, focusing on physical loading constraints and their impact on route efficiency. The study analyzes routing challenges specific to agricultural transportation – including vehicle capacity, delivery deadlines, and Last-In-First-Out (LIFO) loading requirements. Field measurements demonstrate that vibration exposure significantly affects product quality, with damage rates varying from 2-35 % depending on road conditions. A hybrid optimization approach combining differential evolution, genetic algorithms, and local search is proposed and validated using real operational data. Experiments on 450 delivery requests show 14.3 % distance reduction and 46 % reduction in product damage. The system achieves return on investment within 2.3 months with measurable improvements in transport efficiency and product quality preservation.

<b>Research background and purpose:</b> The logistics sector, both globally and in Turkey, has become a strategically important and rapidly evolving industry. Technological advancements are reshaping service delivery, enabling faster and more efficient transportation. Within this dynamic landscape, understanding user expectations and perceived service quality is essential. This study investigates the impact of exporter enterprises’ trust tendencies toward logistics service providers on perceived logistics service quality, while also examining the moderating role of logistics information technologies (LIT). <b>Design/methodology/approach:</b> The study was conducted with exporter enterprises using services from five major logistics providers. A purposive sampling method was applied to target firms engaged in international trade. Data were collected via an online questionnaire; after removing 16 invalid responses, the final sample consisted of 434 enterprises. This exceeded the minimum sample size (n > 384) required by the infinite population formula. Data were analyzed using SmartPLS 2024. <b>Findings:</b> Exporter firms’ trust in logistics providers—especially regarding helpfulness and competence—significantly and positively affects perceived logistics service quality. However, as the use of LIT increases, the importance of interpersonal trust declines. Instead, system-based factors such as security and reliability gain prominence in shaping service quality perceptions. <b>Value added and limitations:</b> The study offers empirical evidence of the moderating effect of LIT in the trust–service quality relationship, contributing valuable insights for logistics professionals and exporter enterprises. However, its scope is limited to specific exporters and logistics firms. Future research should consider a broader range of enterprise types and examine trust–technology interactions in varied logistics contexts. Keywords: User Trust Tendency, Logistics Service Quality, Logistics Information Technology, Exporters, Logistics Service Enterprises JEL Classification: L91, L86, M15, D83

This paper studies the multi-modal collaborative optimization problem of Internet of Things (IoT) information logistics supply chain based on Federated Learning and Digital Twin (FL-DT) architecture, proposes a distributed optimization framework that integrates federated learning and decision tree, and uses multi-modal data collected by IoT technology to improve supply chain efficiency. The experiment uses real-time IoT data and order, inventory and historical logistics data for analysis. The results show that the FL-DT architecture significantly optimizes supply chain performance: order processing time is shortened by 33.33%, inventory turnover rate is increased by 26.15%, logistics cost is reduced by 20.33%, response time is compressed by about 40% and order fulfillment accuracy rate is increased from 92% to 97%. Multi-modal data fusion makes the model accuracy reach 91.2%, which is 7.8% higher than that of single-modal, the transportation efficiency is increased by 23% and the carbon emission is reduced by 14%. The digital twin simulation shows that the transportation timeliness deviation is only −0.7%, but the inventory cost deviation is [Formula: see text]2.4%, and the fitting degree is 86.4%. The dynamic prediction needs to be improved. The FL-DT architecture has small loss fluctuations in abnormal events, which is better than traditional systems. The amount of communication data is reduced by 82% to 12.7 MB/round, demonstrating high efficiency and robustness. This study provides a new method for IoT supply chain optimization, verifies its potential in efficiency improvement, cost reduction and intelligent transformation, and can be expanded to more fields in the future.

The influence of Cost Efficiency in Logistics, Information Technology, and Service Quality Impact on Supply Chain Performance. is a scientific article in the literature study within the scope of the field of science. The purpose of this article is to develop a hypothesis about the influence between variables that will be used in future research. The research objects are from online libraries such as Google Scholar, Mendeley, and other academic online platforms. The research method uses library research sourced from e-books and open access e-journals. The analysis used is descriptive qualitative. The results of this article: 1) Cost efficiency in logistics affects supply chain performance .; 2) Information technology affects supply chain performance.; and 3) Service quality affects supply chain performance.

Healthcare supply chains constantly experience the difficulty of demand forecasting especially in the events of disruption, which includes a pandemic. Conventional model dominated approaches to artificial intelligence (AI) and machine learning (ML) frequently face challenges of not keeping accurate predictions to such circumstances with inconsistent, incomplete, or poorly engineered inputs. The given research suggests an initiative of a data-centric AI approach to healthcare supply chain forecasting where the advanced data engineering practice is merged with ML and deep learning frameworks. The framework uses an extensible data pipeline that consumes heterogeneous information of procurement, consumption, logistics, and external information intake of epidemiological reports, mobility reports. Quality of data is checked using clear measures such as completeness, timeliness and representativeness and provide predictive models with credible inputs. The experiment conducted with the data on hospital networks proves that the addition of characteristics that have domain considerations to datasets can significantly enhance the accuracy of predictions. The data centric framework (over model centric baselines) improved the root mean squared error (RMSE) and stock-out rates by as much as 40% during disrupted demand conditions. These findings formulate the importance of data quality and engineering as key building blocks to resilient healthcare forecasting against earthquakes. The paper concludes that a more sustainable approach to finding a reliable adaptive supply chain process of supply chain intelligence implies looking beyond the concept of algorithmic optimization and to look instead at systematic data improvement.

Persons living with dementia (PLWDs) and their care partners (CPs) have seldomly been included during early intervention development stages despite the potential for greater user engagement and adherence. Moreover, there is limited existing guidance for investigators to incorporate PLWDs and CPs in intervention design. In developing an emergency department care transition intervention, our goal was to conduct a Design Thinking Workshop (DTW), identify lessons learned, and provide recommendations for future intervention design processes targeting the population of PLWDs and CPs. Inclusive of PLWDs and their CPs, a total of 23 individuals participated in a DTW with components including empathy map review, preliminary technology intervention demonstration and feedback, current and future state discussion, among others. The design team collectively grouped challenges, successes, and processes of the DTW into 10 "lessons learned" with associated recommendations for effective inclusion of PLWDs and CPs. The 10 lessons learned and associated recommendations were categorized into three groups, including pre-workshop considerations (lessons 1 to 2), workshop principles and attitudes (lessons 3 to 7), and additive resources (lessons 8 to 10). Collectively, they are: (1) Recruit a participant pool resembling the target population; (2) Provide clear, detailed logistics information; (3) Ensure PLWDs and CP dyads are central in every aspect; (4) Dedicate sufficient time for introductions and contextualization; (5) Balance agenda items and time demands; (6) Select a lead facilitator(s) possessing direct experience with the target population and in design thinking; (7) Allow exercise flexibility; (8) Use multiple modalities to promote participant engagement; (9) Engage a transcriber and a visual artist; and (10) Ensure formal collection of post-workshop feedback. Investigators including PLWDs and their CPs during intervention development phases may benefit from the Design Thinking Workshop lessons learned and recommendations to refine workshop practices and maximize end user engagement.