Success Factors For Implementation Research Articles

A DEMATEL Based Approach for Evaluating Critical Success Factors for Knowledge Management Implementation: Evidence from the Tourism Accommodation Sector

The significance of knowledge management in the tourism accommodation sector is increasingly vital due to rapid market changes and intense competition. Although the value of identifying and implementing critical success factors (CSFs) for knowledge management is widely recognized in the sector, there is still a lack of comprehensive understanding and practical application of these factors. This study employs the decision-making trial and evaluation laboratory (DEMATEL) methodology to systematically identify and analyze the interrelationships among these CSFs. The findings reveal a complex web of dependencies within this network. Specifically, leadership commitment and support is identified as the most influential CSF, acting as a fundamental element that enables the successful adoption and integration of knowledge management initiatives. Additionally, strategic alignment and a supportive organizational culture are crucial, working synergistically to ensure that knowledge management initiatives are aligned with overarching organizational goals and create an environment that encourages change and collaboration. Furthermore, the study highlights a mutually reinforcing relationship between knowledge processes, governance, and employee training. This relationship suggests that strong governance structures and clearly defined knowledge processes facilitate and improve the effectiveness of employee training programs while also creating a continuous improvement cycle where improved training further refines governance and knowledge processes. Moreover, the study highlights the integration of the ISO 30401:2018 standard as a systematic framework to support these CSFs, providing a structured approach to improve knowledge management systems. By mapping the cause-and-effect relationships among the identified CSFs, this research offers practical insights for industry professionals to effectively prioritize and address these factors.

Research on Artificial Intelligence Applications in Global Supply Chains

This research examines the transformative role of artificial intelligence (AI) in global supply chain management, analysing its applications, benefits, and challenges across various supply chain functions. Through a comprehensive analysis of current implementations and industry practices, the study reveals how AI technologies are revolutionizing supply chain operations through enhanced demand forecasting, inventory optimization, logistics management, and supplier risk assessment. The research identifies key success factors in AI implementation while addressing critical challenges including data privacy concerns, technical integration difficulties, cost barriers, and ethical considerations. The findings demonstrate that successful AI integration in supply chains requires a balanced approach combining technological innovation with careful consideration of organizational readiness, data security, and ethical implications. The study concludes by proposing strategic recommendations for organizations seeking to leverage AI in their supply chain operations and highlighting future development directions as AI technology continues to evolve. But the insights from industry leaders like Amazon and Alibaba may not fully apply to SMEs, which face unique challenges such as limited resources and technological readiness, highlighting the need for future research on scalable, cost-effective AI solutions and collaborative strategies to support their adoption.

Critical success factors for implementing a smart IoT-based decision framework in the water industry

ABSTRACT The decentralized nature of information and the widespread use of mobile devices for accessing content make the water sector an excellent platform for using the Internet of Things (IoT) paradigm to streamline procedures, benchmark standards, and create a sustainable environment. Smart devices play an essential role in deploying digital solutions through IoT. They help connect the physical world with the digital universe and are regarded as fundamental entities within a network-integrated through IoT. The study provides a better understanding to assess the critical success factors (CSFs) for smart device implementation in the water sector. The factors are obtained from the literature and shortlisted with the help of experts using the Delphi method. Kappa statistics are used to further validate the experts' consensus. The significant factors identified were leadership, usability, cost of implementation, technology awareness, data privacy, interoperability and community partnership. Mental modeler software has been used to construct a fuzzy logic cognitive mapping of CSFs to represent causal reasoning in diagraphs. Scenario analysis was conducted for each CSF. The study provides recommendations for policymakers to develop precise strategies for integrating IoT in the water industry.

The Value of Applying Big Data Analytics in Health Supply Chain Management

This study aims to evaluate the impact of big data analytics (BDA) on the performance of healthcare supply chain management (HCSCMP) by examining both overall efficiency improvements and identifying critical success factors for effective implementation. Through a systematic literature review, the research investigates how BDA enhances real-time decision-making within healthcare supply chains (HCSCs) and identifies the key enablers required for successful BDA adoption. A comprehensive search strategy was employed to analyze 65 papers, resulting in the inclusion of 39 studies published between 2016 and 2023. The review revealed a preference for literature reviews and questionnaires as the primary research methods. The findings indicate that BDA significantly improves HCSCs’ efficiency, particularly in real-time decision-making and operational management. However, successful BDA implementation depends on addressing critical enablers and overcoming associated challenges.

Integration Patterns in Unified AI and Cloud Platforms: A Systematic Review of Process Automation Technologies

This article comprehensively analyzes unified AI and cloud platforms, examining their role in transforming process automation and decision systems across industries. The article investigates the architectural frameworks and integration patterns that enable the convergence of AI tools, machine learning operations, and workflow orchestration within cloud-native environments. The article explores key innovations, including federated AI implementations, real-time data processing architectures, and multi-cloud integration patterns. It provides insights into their practical applications across finance, healthcare, retail, and manufacturing sectors. The article identifies critical success factors in platform implementation, including integrating MLOps frameworks, automated decision engines, and compliance tools for AI governance. Through case study analysis and architectural evaluation, we demonstrate how unified platforms address traditional challenges in AI deployment while enabling scalable, cost-efficient solutions. The findings reveal emerging patterns in platform architecture that facilitate seamless integration of edge computing, real-time analytics, and distributed AI systems, contributing to the broader understanding of enterprise AI implementation strategies. This article provides valuable insights for researchers and practitioners in cloud engineering, artificial intelligence, and systems integration while highlighting future directions for platform evolution and standardization.

Industry 4.0 and lean thinking: the critical success factors perspective

PurposeAcknowledging the importance of both lean thinking (LT) and Industry 4.0 (I4.0) for successful business performance and organisational success, the present study investigates the critical success factors (CSFs) for the concurrent implementation of both approaches, a field not yet significantly explored.Design/methodology/approachThe study conducts two systematic literature reviews (SLRs), one on LT and the other one on I4.0 to map out the CSFs for the effective implementation of each approach. These CSFs are subsequently prioritised with the use of a Delphi Study. Finally, from the set of the common CSFs recognised through the two approaches, a more condensed list is put forward as the first step towards achieving a successful synergy between LT and I4.0.FindingsThe study’s findings suggest the most important CSFs and determine their definition in the context of a concurrent implementation of LT and I4.0. This can provide managers and practitioners with the awareness of crucial factors, enabling them to take the necessary steps for planning and implementing both approaches.Practical implicationsA concise set of CSFs for the concurrent implementation of both LT and I4.0 has been identified, which can be viewed as a starting point for providing top executives and managers with useful insights into enhanced business efficiency and performance. This study furthermore contributes to the overall body of knowledge on LT and I4.0.Originality/valueThe scholarly literature that explores a common set of CSFs for the concurrent implementation of LT and I4.0 is limited. This gap significantly enhances the importance of the present research, contributing to a better understanding amongst both academics and practitioners of the key supporting factors for the integration of the two approaches.

The Value of Applying Big Data Analytics in Health Supply Chain Management

This study aims to evaluate the impact of big data analytics (BDA) on the performance of healthcare supply chain management (HCSCMP) by examining both overall efficiency improvements and identifying critical success factors for effective implementation. Through a systematic literature review, the research investigates how BDA enhances real-time decision-making within healthcare supply chains (HCSCs) and identifies the key enablers required for successful BDA adoption. A comprehensive search strategy was employed to analyze 65 papers, resulting in the inclusion of 39 studies published between 2016 and 2023. The review revealed a preference for literature reviews and questionnaires as the primary research methods. The findings indicate that BDA significantly improves HCSCs’ efficiency, particularly in real-time decision-making and operational management. However, successful BDA implementation depends on addressing critical enablers and overcoming associated challenges.

Critical success factors for circular economy implementation toward sustainable construction: an iterative stationary approach

ABSTRACTS The continuous depletion of natural resources, coupled with negative environmental impacts and increasing costs of construction projects, has drawn the attention of stakeholders in the construction industry to the circular economy (CE) concept. Over the past decade, the investigations of CE have increased significantly. Yet, this is not the case for developing countries, where the CE practice is still in an infant stage. This paper explores the critical success factors (CSFs) in order to advance knowledge of the implementation of CE in the Nigerian construction industry. The CSFs were compiled from previous studies and subsequently reviewed and classified through a semi-structured interview. A questionnaire survey consisting of the CSFs was subsequently sent to the construction professionals for their response. The relative importance index was further employed to determine the significant factors within each group. In this paper, an iterating stationary approach was adopted to further examine the factors by using Ginni's mean measure of dispersion to create a uniform weight for the index numbers. The Lebesgue integral measure to the mean value was used to provide a value range within the relative importance index (RII). This technique evaluated the impacts of the CE CSFs on the Nigerian construction industry. The results indicate a geometric mean stationary value of 0.7040, which signifies that the CSFs for CE implementation in the Nigerian construction industry are alleviating the fragmented construction industry through the stakeholder’s collaboration having the RII value of 0.71, and the availability of technologies for end of the life management of buildings with the RII value of 0.7.

Critical success factors for EHR systems implementation in developing countries: a systematic review

Purpose This study aims to identify the barriers that hinder the effective implementation of electronic health records (EHR) systems in developing countries while also uncovering the critical success factors (CSFs) that can facilitate their implementation. This study focused on the sociotechnical and environmental challenges that influenced the implementation of EHR systems. Design/methodology/approach This study used a systematic literature review methodology guided by the modified sociotechnical theory. It followed PRISMA guidelines to identify barriers and CSFs. This review included a comprehensive search of academic databases such as Taylor & Francis, Google Scholar, Emerald and PubMed, covering studies published between 2012 and mid-2024. The studies were screened and analysed using thematic analysis. Findings The review identified several barriers to EHR implementation, including a lack of information and communication technology infrastructure, inadequate training, and limited government support. It also highlighted CSFs such as enhancing training programmes, improving technical infrastructure, fostering government support and addressing privacy and security concerns. This study concluded that a holistic approach addressing technical, social and environmental factors was critical for the success of EHR systems in low-resource settings. Practical implications This study offered actionable recommendations for policymakers and health-care leaders in developing countries. These include strategies for enhancing user training, improving technical infrastructure, ensuring government support and addressing data privacy and security issues, which are crucial for successfully adopting EHR systems. Originality/value This research comprehensively examined the factors influencing EHR implementation in developing countries, offering a unique perspective by applying the modified sociotechnical theory. It bridged a significant gap in the literature by focusing on the specific challenges faced in resource-constrained environments.

Critical Success Factors of Sustainability Implementation in the Construction Industry

Sustainability is one of the emerging areas in building construction, and it is widely investigated in terms of bringing sustainable technology into construction. However, one of the biggest challenges in the construction industry is implementing sustainability. Building contractors and construction practitioners mostly struggle with the implementation of sustainability due to the lack of certain parameters that define sustainability. Therefore, this study investigates the factors for effective sustainability implementation to provide industry practitioners with the benefit of the extensive list of parameters when designing their sustainability program. To research the parameters, a questionnaire was designed and administered to construction professionals with wide experience in sustainability implementation. The respondents were asked to evaluate a set of sustainability factors in the economic, social, and environmental domains. This way, the study provides reflections from construction practitioners working on large projects. The findings indicated that Ethical and Relational Factors in economic sustainability, Historical and Social Relations Factors in social sustainability, and Material Usage Factors in environmental sustainability are the most important for effective sustainability implementation. The findings are expected to help construction practitioners understand metrics of sustainability, effectively manage their projects, and successfully implement sustainability with the consideration of proper metrics.

Empirical Analysis of Critical Success Factors for Mechatronics Implementation in Architecture, Engineering, Construction and Operations Projects in Nigeria

The Fourth Industrial Revolution (4IR) has ushered in a new era of technological advancements that are transforming industries worldwide. One such technology that is revolutionizing the construction industry is mechatronics, which has the propensity to enhance the operations, activities, productivity and efficiency of the sector’s activities. Despite the numerous advantages of mechatronic technologies, their successful implementation in the context of developing countries poses unique challenges and considerations. Therefore, this study seeks to identify and evaluate the critical success factors (CSFs) for mechatronics implementation in architecture, engineering, construction and operations (AECO) projects. Existing CSFs were extracted from extant studies, which helped formulate the questionnaire disseminated to 372 construction professionals in Nigeria, including architects, builders, quantity surveyors, and engineers (mechanical, civil, electrical). The methodology also employed exploratory factor analysis (EFA), which facilitated the identification of key themes within the data. Through this application, six clusters of CSFs were revealed: organizational factors, financial considerations, technological aspects, collaboration and knowledge sharing, regulatory and policy factors, and sustainability and environmental considerations. From a theoretical perspective, the identified clusters of critical success factors provide a comprehensive framework that encompasses various dimensions of successful mechatronics adoption in the Nigerian construction industry. This study advances scientific knowledge on CSFs for the adoption of mechatronic technologies in the Nigerian construction industry, providing a comprehensive understanding of the factors that drive successful implementation. For policymakers, this study’s findings will be invaluable in shaping supportive policies and strategies that foster the widespread adoption of mechatronics in the construction sector.

Optimizing pharmaceutical supply chain management through AI-driven predictive analytics: A conceptual framework

The pharmaceutical supply chain is a complex, multi-layered system that faces unique challenges, including fluctuating demand, stringent regulatory requirements, and logistical constraints. This paper explores the role of AI-driven predictive analytics in optimizing pharmaceutical supply chain management, presenting a conceptual framework that enables companies to leverage advanced data analytics for improved decision-making, risk management, and operational efficiency. Key AI techniques, such as machine learning, data mining, and predictive demand forecasting, are discussed as tools for addressing critical supply chain issues, including inventory optimization, demand variability, and regulatory compliance. The proposed framework details essential components—data collection, processing, integration with existing systems, and real-time decision-making—and outlines critical success factors for effective implementation. By offering insights into the transformative potential of predictive analytics, this paper provides actionable recommendations for pharmaceutical companies seeking to build resilient and responsive supply chains. Future research directions are also proposed, emphasizing the need for adaptable predictive models and the ethical implications of AI applications in pharmaceuticals. Keywords: Pharmaceutical Supply Chain, AI-driven Predictive Analytics, Machine Learning, Demand Forecasting, Inventory Optimization, Regulatory Compliance.

Orchestration Workflows in Distributed Systems: A Systematic Analysis of Efficiency Optimization and Service Coordination

This article presents a comprehensive analysis of orchestration workflows in modern software architectures, examining their role in optimizing service efficiency and coordination across distributed systems. Through a systematic investigation of implementation patterns and operational strategies, we demonstrate how orchestrated workflows enhance service integration, automate complex processes, and improve system reliability. The article employs a mixed-method approach, combining quantitative performance metrics from real-world implementations with qualitative analysis of architectural patterns across diverse enterprise environments. The findings reveal that organizations implementing robust orchestration workflows experienced a 47% reduction in service integration failures, 35% improvement in resource utilization, and 62% faster deployment cycles. The article also identifies critical success factors in orchestration implementation, including dynamic resource management, automated error handling, and comprehensive monitoring frameworks. Furthermore, The article proposes a novel framework for evaluating orchestration effectiveness in cloud-native environments, considering factors such as service mesh integration, container orchestration, and distributed tracing. This article contributes to the growing body of knowledge in service optimization by providing empirical evidence of orchestration benefits and offering practical guidelines for implementing scalable, resilient software systems through advanced workflow orchestration strategies.

Artificial Intelligence in SAP S/4HANA: Transforming Enterprise Resource Planning through Intelligent Automation

This comprehensive article investigates the transformative impact of AI-enhanced SAP S/4HANA Finance across healthcare, manufacturing, scientific research, auto, food & Oil &Gas sectors, focusing on human-AI collaboration patterns and implementation outcomes. Through a mixed-methods approach analyzing 15 organizations over 18 months, the research examines how AI integration transforms traditional ERP functionalities into intelligent financial management systems. The article collected data from 450 end-users and 45 key stakeholders, employing both quantitative metrics and qualitative assessments to evaluate implementation patterns, challenges, and success factors. The findings reveal significant improvements across all sectors: healthcare organizations achieved 40% reduction in billing processing time and 15% improvement in collection rates; manufacturing entities realized 35% reduction in unplanned downtime and 22% decrease in working capital requirements; while research institutions demonstrated 45% faster grant processing and 35% improved budget forecasting accuracy. The article introduces the Adaptive Financial Intelligence Framework (AFIF) for conceptualizing human-AI collaboration in financial management, contributing to both theoretical understanding and practical implementation strategies. The article concludes that successful AI integration depends on industry-specific adaptations, comprehensive training programs, and robust governance frameworks while highlighting the critical role of human expertise in maximizing system benefits. These findings provide valuable insights for organizations pursuing AI-enhanced financial management solutions while offering a roadmap for future developments in human-AI collaboration within enterprise systems.

Reducing low-value imaging - stakeholders’ assessment of an intervention to improve imaging services

BackgroundAn intervention to reduce low-value magnetic resonance imaging (MRI) was designed and implemented in private imaging centres in Norway in October 2022. The intervention used return letters for poor referrals of MRI of the lower back, brain and knee at private imaging centres in Norway. The study aimed to investigate key stakeholders’ experiences and assessment of the intervention and the specific research questions were:• How many return letters were sent during the study period?• What were the medical directors’ and managers’ experiences with and reflection on success factors for the intervention implementation and using return letters?MethodsThe number of return letters sent was collected directly from Norway’s two main private imaging providers. Two semi-structured individual interviews were conducted with the medical directors of the imaging providers, as well as two focus group interviews with nine managers from the various private imaging centres operated by the two imaging providers.ResultsIn total, 1,182 return letters were sent for patients undergoing one of the three types of MRI examinations, and the number of return letters was highest at the beginning of the intervention. The interview analysis resulted in five categories: general experience, anchoring, organisation, return letter procedure and outcome. Sufficient information, anchoring and support were identified as crucial success factors.ConclusionsThis study provides insights into the practical and crucial details of implementing interventions to reduce low-value imaging. The intervention was generally well received, and the high initial number of return letters decreased rapidly over the course of the study. Several key success factors were identified.

Success Factors for Conceptual Digital Voting Model

With the advancement of technology in the digital age, blockchain technology has evolved into a technology critical to delivering secure and reliable decentralized applications. An application that has brought blockchain technology is elections to close the gap in traditional elections for transparency and credibility However, in COVID-19, bringing this technology to change elections allows access to all citizens to be able to vote. This research uses a structural equation model (SEM) questionnaire to explore the success factors of election implementation using blockchain technology was analysed from 400 voters who responded to the questionnaire using Mplus Version 7. This research has prepared a conceptual model supporting the effecting factors in implementing an election system using blockchain technology with voters The researcher has created an electoral system using blockchain technology that is readily available. Technology acceptance factor and credibility were utilized from the voters’ point of view in 9 Factors. Those interested in applying the model to improve elections using blockchain technology can study to improve elections. In addition, Conceptual model ideas were used to develop a model for acceptance and trust in elections using blockchain technology.

Toward a roadmap for sustainable lean adoption in hospitals: a Delphi study

BackgroundThe benefits of lean adoption in healthcare include improved process efficiency and quality of patient care. However, research indicates that lean implementation in healthcare, and specifically hospitals, is often not sustained. Furthermore, there is a need for maturity models that guide lean implementation, specifically in hospitals. This study develops a prescriptive maturity model named the Sustaining of Lean Adoption in Hospitals Roadmap (SOLAR) that acts as a practical guideline for the sustainable adoption of lean in hospitals.MethodsThe SOLAR has three theoretical foundations, namely lean implementation success factors in hospitals, implementation science, and change management theory. A systematic literature review was conducted to determine the lean implementation success factors in hospitals as the first building block. Secondly, practices from implementation science were used to create the action items in the SOLAR. Ten change steps were elicited from change management theory as the third theoretical building block of the roadmap. We refined the roadmap through three Delphi rounds that verified its useability in hospitals.ResultsThe final SOLAR consists of four maturity phases (prepare, plan, experiment and learn, and sustain) and includes action items for each phase related to the hospital’s strategy, resources, engaging of people, and culture. The action items and change management steps shown in the SOLAR are not intended as an exhaustive list but provide guidelines on aspects hospitals must consider when they aim to adopt lean sustainably.ConclusionsThe strong theoretical base of the SOLAR enables hospitals to safely experiment and learn which implementation methods are best suited to their unique environment. The SOLAR is, therefore, an actionable guideline that informs both academics and practitioners involved in lean adoption in hospitals. This roadmap can guide future retrospective longitudinal or action research.

Analysis of critical success factors for blockchain technology implementation in supply chain: a Delphi study

Analysis of critical success factors for blockchain technology implementation in supply chain: a Delphi study

Identifying the success factors for TQM implementation among automotive spare parts companies using analytic hierarchy process (AHP): evidence from Palestine

PurposeThis paper aims to identify the success factors (SFs) for total quality management (TQM) implementation in automotive spare parts companies to improve their business performance. It also intends to rank these factors in a hierarchical structure in descending order of their criticality.Design/methodology/approachIn this study, a significant number of automotive spare parts companies were extensively surveyed to ascertain the contributions made by various factors toward the successful deployment of TQM practices. The collective and individual evaluation and ranking of the SFs were determined using the analytical hierarchy process (AHP) approach to develop the framework based on the prioritisation of the identified SFs.FindingsThe findings of the study show that five success factors, namely, internal environment, top management involvement, process management, supplier management and external environment, were ranked as critical factors with a total weight of 49.2%. Nine success factors, namely, employee training, teamwork, customer satisfaction, continuous improvement, communications, using new technologies, zero-defect processes, employee empowerment and benchmarking, were ranked as important with a total weight of 39.1%. The last five success factors, namely, strategic planning, quality policy, employee satisfaction, self-assessment and cost of quality, were ranked as minor factors with a total weight of 11.7%.Originality/valueThe current study adds to the existing body of knowledge for scholars and practitioners of TQM by specifically focusing on identifying and categorising the critical SFs for TQM implementation. The 19 categorised critical SFs have been used to construct a framework for TQM implementation in the Palestinian automotive spare parts companies. Such a framework would offer a comprehensive overview of the SFs, their categories, significance and priorities within a TQM environment in the automotive spare parts companies.

Industry 4.0 technologies: an examination of benefits, challenges and critical success factors for implementation in the Saudi construction industry

Purpose The construction industry is witnessing a paradigm shift as a consequence of the fourth industrial revolution (IR 4.0). The implementation of IR4.0 technologies is, however, elementary in emerging economies such as Saudi Arabia. Therefore, the purpose of this paper is to carry out an examination of benefits, challenges and critical success factors for IR4.0 implementation in the construction industry in Saudi Arabia. Design/methodology/approach The methodology entailed a thorough review of the extant literature and consultation with experienced construction professionals in Saudi Arabia through questionnaire surveys. The data collected was further analyzed using the relative importance index approach and the confirmatory factor analysis. Findings The most important benefits, challenges and critical success factors established by this study include “Improved Communication and Coordination,” “Cost of implementation (initial investment and maintenance)” and “Clear goals and objectives,” respectively. Confirmatory factor analysis established a theoretical model to serve as a foundation for IR4.0 adoption in the Saudi construction industry. Research limitations/implications The limitations may be perceived in terms of the local context of the research, as well as the sample size. This prevents the potential for generalization of the study’s results. Practical implications It is of practical value to the Saudi construction industry in facilitating the successful implementation of technology through policies, frameworks and best practice guidance. Originality/value The study advances the theoretical knowledge of technology implementation in the construction industry. Emerging economies such as Saudi Arabia seeking to leverage the capabilities of digital technologies will find the results of this to be of crucial value.