Case Study Of Project Research Articles

Why anti-corruption projects and programmes fail in some African countries: a case study of an anti-corruption project that drowned in corruption and the lessons learned

Purpose The pandemic of corruption in Africa reflects the more general climate of the lack of both ethical leadership and appropriate anti-corruption systems found throughout most of the continent. The purpose of this study is to examine the manner in which corruption was perpetrated in an anti-corruption project that was intended to produce outcomes to reduce and control said corruption, in a sub-Saharan Africa country, for sustained development outcomes, including progress in meeting the sustainable development goals. Design/methodology/approach Based on a field experience, and drawing on the active participant observation research methodology, buttressed by open-ended interviews, this work provides a qualitative analysis and assessment case study of corruption in the implementation process of the anti-corruption project. Findings It is shown that corruption remains a significant barrier to positive development outcomes, especially in those environments where certain social norms and collectivist behaviour are prominent. In such environments, special systems need to be in place for project implementation success even in cases where a project itself is designed to reduce and control that corruption. Key lessons learned include the imperatives of recruiting qualified and ethical personnel and the importance of country ownership, political will and persistent project monitoring including by the citizen beneficiaries of sustainable development projects. Originality/value The paper’s value is the insights it provides through the mapping of the key lessons learned for successful implementation of projects and systems to control corruption and improve ethical behaviour in Africa and beyond.

Commentary: Strengthening System Readiness for Health Interventions: Lessons for Implementing Interventions and Implementation Support in Low-And Middle-Income Countries.

In low- and middle-income countries (LMICs), barriers such as low system readiness, contextual mismatches, and resource limitations impede effective implementation of evidence-based interventions. This commentary offers insights into overcoming these challenges with a case study of the PRISM project, designed to reduce behavioral and psychological symptoms of dementia in older adults living in Thailand. The case highlights how combining two evidence-based models - the Reducing Disability in Alzheimer's Disease clinical intervention and the Getting To Outcomes implementation science process enhances program success. Using interviews with stakeholders across various health system levels, we identify factors critical to successful program implementation: (1) integrating interventions into policy frameworks, (2) empowering local implementers, (3) fostering collaborative learning, and (4) adapting interventions to local contexts. The case demonstrates that building system readiness through local engagement and ownership is central to scaling up health programs in LMICs. This commentary's contribution lies in its emphasis on the role of implementation science as a vehicle for translating research into practice. It presents a practical, adaptive model for embedding interventions into routine health systems, thereby offering a pathway for successfully scaling up evidence-based programs in LMICs. Such findings provide lessons for overcoming barriers to implementation in resource-limited environments.

How to build a powerline: Fast policies for decarbonization, the slow work of public participation, and the profitability of energy capital

Community opposition to new low-carbon energy infrastructure – and resulting project delays and cancellations – is increasingly taken by some climate activists, policymakers, and scholars as evidence of the incompatibility between urgent decarbonization and expanded public participation. This paper argues that too narrow a focus on this duality risks overlooking an additional mandate: the profitability of energy capital. This paper intervenes in the ‘rapid vs. just transitions’ debate by arguing that building low-carbon energy infrastructure requires a balancing of trade-offs between speed, local support, and profit for private developers. Using a case study of a controversial transmission project in the northeastern United States, I argue that project delays are attributable not (just) to uncooperative publics, but to energy capital's drive for profit, which discourages compromises with host communities that would increase project costs but cultivate local support. By treating the social legitimacy of low-carbon energy infrastructure as contingent on its ability to meet criteria for public acceptability, this paper argues that the slow work of public participation can in fact be the route to ‘fast policies’ for decarbonization when it fosters developer norms in line with community expectations for projects.

Engineering Value in Projects Building Construction: Case Research Sofifi 3-Story ASN Official House - North Maluku Province

The sustainability of construction projects often hinges on managing costs effectively, as illustrated by the case study of an ASN housing building project in Sofifi, North Maluku. This research aims to achieve significant cost savings by optimizing the selection of construction materials and methods, utilizing the Value Engineering Method. This method systematically assesses the value of each component relative to its function, promoting an innovative approach to minimizing unnecessary expenditures. The research followed several structured stages: information gathering, creative ideation, analysis, evaluation, and development, each focusing on identifying feasible alternatives to reduce costs. The analysis identified two key solutions: replacing conventional flooring with precast materials for floor work and substituting lightweight brick walls with red brick walls. Implementing these changes reduced the total project cost from IDR 2,295,005,206 to IDR 1,698,939,324, achieving savings of IDR 596,115,883 (35%). The findings of this study provide practical implications for construction project management, offering a structured approach to material and method selection that can be adapted to broader-scale projects for enhanced cost-efficiency.

Retraction Note: The role of fixed capital formation, renewable and non-renewable energy in economic growth and carbon emission: a case study of Belt and Road Initiative project.

Retraction Note: The role of fixed capital formation, renewable and non-renewable energy in economic growth and carbon emission: a case study of Belt and Road Initiative project.

A self-organizing map clustering adaptive artificial neural network model for analysis critical success factors in different phases of MTO projects case study: electrical equipment manufacturer and supplier in Iran

PurposeThe purpose of this paper is to investigate the benefit of critical success factors (CSFs) clustering in different phases of make-to-order (MTO) projects and develop standards for management.Design/methodology/approachThis study is based on a questionnaire survey. First of all, collecting data by structured interviews, relying on a questionnaire and second from leader contractors who are active in the engineering and steel industry (in Iran). So, the requirements and objective of the research are presented to the top management of MTO projects to gain their support in data collection. Then 20 CSFs were identified by the literature review so a questionnaire survey was prepared for the CSFs assessment and interview with the experts. Finally analyzing the importance and performance of CSFs in project phases and cluster them in different project phases with self-organizing map as one of the artificial neural network (ANN) approaches due to high predictive accuracy. Review the research result with the top management of MTO project and examine the results obtained from neural networks and validation indices.FindingsCluster analysis shows that the implementation phase is the most important stage in MTO organizations and the other phases like feasibility and start-up, design and planning, delivery and end-phase should be also considered as effective phases in determining the level of organization performance. Different industries with additional data at different periodic times will verify the result. Furthermore, testing the other ANN model will improve risk analysis and could shift this classification approach to a regression type.Research limitations/implicationsThe main limitation of the research is related to the sample. Research findings are limited to the time of data collection so validity is limited to the mentioned time. Different industries with additional data will verify the result. Furthermore, testing different ANN models such as K-MEANS, non-negative matrix factorization (NMF) analyses will improve risk analysis and could meet different classification results to find gaps.Practical implicationsIn this paper, CSF and project phase dimensions are viewed together which is necessary to meet better results for simplifying social and economic benefits. Merge the new findings and latest technologies could prepare the best results and enable managers to create a better framework or implement key factors for minimizing waste.Originality/valueThis paper moves the definition of MTO organizations beyond measuring cost, complexity and financial variables by clustering CSFs in different phases of projects. So, the results enable managers to use this concept in their daily production to minimize waste and could be implemented to efficiently choose factors.

A More Effective Social Protection System for Older Workers: A Case Study of the Older Adult Employment Project in Thailand

The phenomenon of old-age pensioners reentering the workforce is neither new nor unique and has been well-reported in several published literature. However, there are remaining challenges to this group of job seekers whose needs have yet to be well-documented from employer’s perspectives, especially regarding decent work, legal landscape, and organizational culture. Our study seeks to provide a better understanding of the underlying causes of these and to help policymakers introduce social protection policies to create a more welcoming and supportive environment for older workers. The study used a case study from service companies in Thailand that participated in the Thai government’s campaign on promoting older employment. Data was collected from interviews with top managers of the human resources department, and that information was analyzed by thematic analysis. Key findings highlighted that the supportive mechanisms for matching decent work, a room for integrating legal framework, and a culture that values inclusivity and fair treatment of all workers, regardless of age, can enhance the social protection system for older workers. The establishment of a modern database of older workers’ skills, which ensures easy accessibility to both employers and older workers, the establishment of a task force specific for monitoring laws and regulations concerning older employment, and the development of effective measures against workplace discrimination are recommended as effective interventions for social protection.

Motivation and Engagement of Students: A Case Study of Automatics and Robotics Projects

Automatics and Robotics students usually engage in some interdisciplinary approaches on their courses at universities, joining the areas of computer science and control theory. During the limited duration of these courses, some knowledge must be acquired by the students. Remote education, temporarily enforced by the COVID-19 pandemic in recent years, has posed new challenges related to the limited contact that students have with academic staff, as well as the limited access students have to hardware facilities. This paper discusses the motivations of students after the COVID-19 pandemic based on a case study of student projects completed at the University of Zielona Gora (Poland). The conducted study was student-centered and highlighted some important aspects of motivation from the point of view of the students, focusing mostly on the emerging challenges, how they have been overcome, and what the students have learned from them. The results indicate that the students, minimally supported by an academic teacher, were able to plan everything by themselves and bring the project to completion according to their own intuition. In comparison to before the COVID-19 pandemic, students are now more independent and self-motivated.

Safety-risk assessment system for prefabricated building construction in China

PurposePrefabricated building (PB) uses factory production and onsite assembly, which differs from traditional construction methods. This special construction approach may lead to dissimilar safety risks and challenges. Traditional safety assessment methods may not adequately and accurately assess the safety risks of PB construction. This paper aims to develop a new concept and methodology for targeted improvement in assessing PB safety risks.Design/methodology/approachRisk factors and indicators were established based on literature review and expert inputs. A structural equation model (SEM) was developed to investigate the relationships among three main risk categories: objects, workers and management. SEM analyzed the intricate associations between indicators and deepened understanding of safety risks. The model was tailored for China’s PB construction projects to enhance safety-risk management.FindingsThe cloud model evaluation validated the SEM model. A PB case study project tested and verified the model, evaluated its efficacy and quantified its safety performance and grade. We identified significant safety risk impacts across the three risk categories, safety-control level and specific areas that require improvement. The SEM model established a robust safety evaluation indicator system for comprehensive safety assessment of PB construction.Practical implicationsPractical recommendations provide valuable insights for decision-makers to enhance construction efficiency without compromising safety. This study contributed to the conceptual foundation and devised a novel method for evaluating safety performance in PB construction for safer and more efficient practices.Originality/valueThis study departed from the traditional method of calculating weights, opting instead for the SEM method to determine the weights of individual risk indicators. Additionally, we leveraged the cloud model to mitigate the influence of subjective factors in analyzing questionnaire survey responses. The feasibility and reliability of our proposed method were rigorously tested and verified by applying it to the PB case.

Sustainability assessment of urban water public‐private partnership projects with environmental, social, and governance (ESG) criteria

AbstractWith the acceleration of urbanization, the sustainability of urban water infrastructure projects has become pivotal to social development. This research aims to construct a comprehensive sustainability assessment model for urban water public‐private partnership (PPP) projects based on the environmental, social, and governance criteria. First, a multi‐level assessment indicator system is established considering the economic, social, ecological, and governance sustainability dimensions. Then, the extended analytic hierarchy process is utilized to determine the weights of indicators based on expert scoring. To address the ambiguity of qualitative linguistic variables, the interval‐valued intuitionistic fuzzy set method is applied to aggregate expert assessments. An empirical case study of an urban water project verifies the feasibility of the proposed approach. Results demonstrate that experts emphasize economic sustainability, while social sustainability is an overlooked dimension that requires improvement. The research contributes to the field by developing an applied, industry‐specific sustainability evaluation model for urban water PPP projects using advanced decision‐making techniques. This model provides practical tools for stakeholders to enhance the sustainable performance of urban water infrastructure projects.

Factors Affecting the Timely Construction of National Pride Projects of Nepal: A Case Study Of KTFT Road Project

Factors Affecting the Timely Construction of National Pride Projects of Nepal: A Case Study Of KTFT Road Project

Practical considerations for numerical simulation of large-diameter monopiles for offshore wind turbines in overconsolidated sand: A case study of the VIBRO project in Cuxhaven, Germany

Monopiles are typically the preferred foundation for offshore wind turbines, which are becoming increasingly large. While 3D finite element modelling can aid the design process of monopile foundations, achieving reliable results requires precise constitutive soil models and input parameters derived from laboratory and field data, as well as careful consideration of soil sample preparation method. This study explores various soil preparation methods, including moist tamping, dry tamping, and air pluviation, along with two sample ratios (1 and 2) during triaxial tests. It uses an advanced soil model, the DeltaSand model, and a practical industry model, the Hardening Soil model with small strain (HSsmall). To evaluate model performance, the Vibro project performed in Cuxhaven, Germany, is used as a case study. Simulations using the DeltaSand model show good agreement with field data. The effects of soil preparation methods and sample ratios are more pronounced in HSsmall model simulations, in which better results are obtained when the model is calibrated using dry tamping data and a sample ratio of one.

Innovations in Wind Turbine Blade Engineering: Exploring Materials, Sustainability, and Market Dynamics

This manuscript delves into the transformative advancements in wind turbine blade technology, emphasizing the integration of innovative materials, dynamic aerodynamic designs, and sustainable manufacturing practices. Through an exploration of the evolution from traditional materials to cutting-edge composites, the paper highlights how these developments significantly enhance the efficiency, durability, and environmental compatibility of wind turbines. Detailed case studies of notable global projects, such as the Hornsea Project One, the Gansu Wind Farm, and the Block Island Wind Farm, illustrate the practical applications of these technologies and their impact on energy production and sustainability. Additionally, the manuscript examines the critical role of regulatory frameworks and industry standards in fostering these technological advancements, ensuring safety, and promoting global adoption. By analyzing the current trends and future directions, this study underscores the potential of modern turbine technologies to meet the increasing global demand for renewable energy and contribute to sustainable development goals. The findings advocate for continued innovation and policy alignment to fully harness the potential of wind energy in the renewable energy landscape.

A physics-constrained neural network for predicting excavation-induced ground surface settlement in clay

Accurate prediction of ground surface settlement (GSS) adjacent to an excavation is important to prevent potential damage to the surrounding environment. Previous studies have extensively delved into this topic but all under the limitations of either imprecise theories or insufficient data. In the present study, we proposed a physics-constrained neural network (PhyNN) for predicting excavation-induced GSS to fully integrate the theory of elasticity with observations and make full use of the strong fitting ability of neural networks (NNs). This model incorporates an analytical solution as an additional regularization term in the loss function to guide the training of NN. Moreover, we introduced three trainable parameters into the analytical solution so that it can be adaptively modified during the training process. The performance of the proposed PhyNN model is verified using data from a case study project. Results show that our PhyNN model achieves higher prediction accuracy, better generalization ability, and robustness than the purely data-driven NN model when confronted with data containing noise and outliers. Remarkably, by incorporating physical constraints, the admissible solution space of PhyNN is significantly narrowed, leading to a substantial reduction in the need for the amount of training data. The proposed PhyNN can be utilized as a general framework for integrating physical constraints into data-driven machine-learning models.

Optimal Location for Tower Crane and Dynamic Trailer Parking in High-Rise Modular Building Construction Project

Optimization of tower crane positioning is essential in precast building construction to ensure that a crane is in the right position to offer the best value for placing precast elements. The first goal is the optimization of transportation distances made by tower cranes, which will address the issues of efficiency and cost. This is done in a way that provides for minimization of the distances that lie between the trailer parking where elements are parked, the tower crane, and the construction installation point. However, current research fails to address the dynamic movement efficiency of trailers, especially when handling multiple trailers and several models of tower cranes, making this scenario an optimization problem that is classified as NP-hard due to the likelihood of causing a combinatorial explosion. This work endeavors to present a new mathematical model that has been applied to the Genetic Algorithm (GA). The ideal demand-generated model is designed to solve the optimal model and position of tower cranes and the prospective positioning of trailers for parking. The feasibility and applicability of the method exploited in the study are also established through a project case study. When adopting the proposed planning model compared to the earlier planning scale, comparisons highlight a small yet significant saving of 6% in time and cost when lifting elements instead of providing them from the trailers by setting up a new on-site stockyard. In addition, a great deal of enhancement is also observed in the final solution aspects, where the developed GA has even reduced the operational time and cost by half a percent each. The results of this research offer best-practice approaches to the position analysis of tower cranes in precast building construction to bring scalability and cost optimization to bear on the construction business.

Application of limit equilibrium and shear strength reduction techniques for stability assessment of slope cuts- A case study of Khalid-Dijo dam project, Southern Ethiopia

Dam failure can occur due to foundation instability, downstream and upstream slopes instabilities. This study assesses the stability of upstream and downstream slope cuts at Khalid-Dijo irrigation dam project, which is located in Southern Ethiopia, 3km south of Werabe town. Limit equilibrium and finite element shear strength reduction methods are adopted. Validation of results and comparisons between those methods are carried out. The analysis considers anticipated site conditions, including static dry, static saturated, dynamic dry and dynamic saturated conditions. Slope material properties are measured from insitu, laboratory tests and used as input parameters for the analysis to obtain factor of safety and critical strength reduction factors. The properties considered in the analysis include unit weight, cohesion, angle of internal friction, poison’s ratio, dilation angle and Young’s modulus. The analysis indicates that the factor of safety values for limit equilibrium methods and the critical strength reduction factor for finite element method are very similar across the three slope cuts under all anticipated conditions. The lowest factor of safety and critical strength reduction factor is 1.56 and 2.07 respectively. Generally, the proposed dam project is safe against upstream and downstream slope failures. These studies suggest that maintained the average safety factor values of both methods during the design stage are crucial to avoid unnecessary risk.

Multi-objective optimal allocation of construction project risks, ant colony optimization algorithm

PurposeThe purpose of this paper is to introduce a new approach for finding the most appropriate risk allocation among construction contract parties. Although risk allocation is a strategic decision that can greatly affect the cost and time of the project, it is often made based on the personal judgments of employers. That is why owners usually find it a very time-consuming and expensive decision process, while most contractors feel that risk sharing is not done fairly. In this paper, a quantitative model for risk allocation is introduced to fulfill clients’ conflicting expectations in the risk allocation process.Design/methodology/approachBy defining conflicting expectation of owners in the form of three quantitative objectives (lowest cost, maximum reliability and minimum risk exposure), a multi-objective optimization algorithm was developed to select the most appropriate risk allocation. Using experts’ knowledge through fuzzy set theory, a multi-objective decision-making model is developed based on an ant colony optimization algorithm. The proposed model is able to find the optimum risk allocation at the lowest cost and highest reliability while protecting the client against risk exposure within multiple parties projects.FindingsThe proposed model has the ability to select the most appropriate risk allocation in multi-parties projects (such as public–private partnerships) and quantitatively measure the impact of each employer’s choice on project results in the form of cost and time. The results of implementing the proposed model in a case study project revealed that optimum risk allocation requires a balanced attitude, and the transfer of all risks to the other parties will not necessarily lead to the lowest cost. The client should bear more responsibilities in risk management to avoid extreme time delay and cost overrun.Research limitations/implicationsThe proposed model can be implemented in multi-parties projects (such as public–private partnership), while other methods introduced in previous studies can only be used for projects with two party (client and contractor).Practical implicationsBy implementing the proposed model in a real project in this article and comparing its results with previous works, it has been shown that the proposed model has a good performance. Using this model can help clients drastically reduce cost and time and ultimately successfully conclude risk allocation negotiations (which is the most difficult part of any contract negotiation).Originality/valueIn this paper, the risk allocation process is modeled in the form of a multi-objective decision problem. This method helps employers to measure their conflicting goals and choose the most appropriate risk allocation according to their objectives. Also, in this article, the conflicting expectations of the employer in the process of contract negotiations are introduced as three measurable goals, which gives the decision-maker the ability to balance his expectations and not miss an objective. In the final step, an optimization model is developed to select the best option, which can choose the most appropriate party to bear the risk in a short time and among an unlimited number of participants.

The Doughnut Biotool: A tool to assess life-cycle biodiversity impacts from building projects

Abstract Life-cycle assessment (LCA) is widely used in certifications, regulations, and voluntary declarations covering the climate impact of buildings over their entire value chain. However, biodiversity impacts and other environmental impact categories are often disregarded. Conversely, there is a trend towards more systematic assessments of the biodiversity impacts that occur on-site as part of development projects (e.g. land transformation on the project site). However, off-site biodiversity impacts occurring throughout the rest of the value chain (e.g. from forestry activities, mining, manufacturing, heat and electricity production) are rarely considered. To bridge this gap, this article introduces the Doughnut Biotool, an open-source calculation tool to assess biodiversity impacts throughout the entire life cycle of development projects. The tool was initially developed to help implement Doughnut Economics and absolute sustainability principles in development projects. It constitutes a first step towards a better consideration of biodiversity impacts related to material- and energy use in building and construction projects. This paper presents the design of the tool and the method and data it relies on. The tool is applied to two separate case study projects, and used as a basis to discuss hotspots of biodiversity impacts within the building’s life cycle. Finally, the paper includes a discussion of the main challenges and opportunities for the future development and use of the tool, as well as for biodiversity impact assessments in the building sector as a whole.

Have I Been Here Before? The Script System in Clinical Supervision

This paper is a theoretical research-based reflection on the process of clinical supervision. It presents two case study projects focusing on the occurrence and use of the script system and the process of change and assimilation of the problematic script material during supervision. One of the cases is an experienced therapist, “Sarah,” and the other is a novice, “Adam,” both of whom were supervised by an experienced TA supervisor. The authors offer a discussion on the prevalence of script themes within the supervision process and ways of working with them while respecting the supervisory relationship, the level of supervisees’ experience, and the teach/treat boundary. They also reflect on the occurrence of the parallel process and its implications. This led to the development of the script system model and the addition of a relational field between the supervisor and the supervisee that can be used as a supervisory tool.

The risk of shifting environmental burdens in biobased construction - Life cycle assessment of a residential renovated building case study in Belgium

Abstract The construction industry is a major contributor to environmental degradation, resource depletion, and energy consumption. As global concerns about sustainability and environmental impact continue to rise, it becomes imperative to reassess the materials used in building construction. This research paper presents a comprehensive life cycle assessment (LCA) using the Belgian TOTEM tool according to EN15804+A2 for evaluating material choices in building construction with a focus on the renovation of residential buildings in Belgium. The study aims to provide a holistic understanding of the environmental implications associated with biobased construction materials enabling informed decision-making for sustainable building practices. To achieve this, we conducted an analysis of the life cycle environmental performance of biobased materials used in external walls of a renovation case study project and compared it to common built-up scenarios of conventional construction materials applied in the same case study. The research results show that using biobased materials for renovation can significantly reduce embodied GHG emissions but can lead to burden shifting such as resulting in an increased impact on land use, particulate matter emissions, depletion of abiotic resources and eco-toxicity. The study not only underscores the importance of comprehensive cradle-to-grave life cycle thinking but also provides valuable insights for stakeholders in the construction industry.