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Heating, ventilating, air-conditioning and cooling (HVAC) systems are crucial in daily health-care facility services. Design-related defects can lead to maintenance issues, causing service disruptions and cost overruns. These defects can be avoided if a link between the early design stages and maintenance feedback is established. This study aims to use experts’ experience in HVAC maintenance in health-care facilities to list and evaluate the risk of each maintenance issue caused by a design defect, supported by the literature.

Following semistructured interviews with experts, 41 maintenance issues were identified as the most encountered issues. Subsequently, a survey was conducted in which 44 participants evaluated the probability and impact of each design-caused issue.

Chillers were identified as the HVAC components most prone to design defects and cost impact. However, air distribution ducts and air handling units are the most critical HVAC components for maintaining healthy conditions inside health-care facilities.

The unavailability of comprehensive data on the cost impacts of all design-related defects from multiple health-care facilities limits the ability of HVAC designers to furnish case studies and quantitative approaches.

This study helps HVAC designers acquire prior knowledge of decisions that may have led to unnecessary and avoidable maintenance. These design-related maintenance issues may cause unfavorable health and cost consequences.

This article aims to focus on implementing Lean Six Sigma (LSS) in steel manufacturing to enhance productivity and quality in the galvanizing process line. In recent trends, manufacturing organizations have expressed strong interest in the LSS since they attempt to enhance its overall operations without imposing significant financial burdens.

This article used lean tools and Six Sigma's DMAIC (Define, Measure, Analyze, Improve and Control) with Yin's case study approach. This study tried to implement the LSS for the steel galvanizing process in order to reduce the number of defects using various LSS tools, including 5S, Value stream map (VSM), Pareto chart, cause and effect diagram, Design of experiments (DoE).

Results revealed a significant reduction in nonvalue-added time in the process, which led to improved productivity and Process cycle efficiency (PCE) attributed to applying lean-Kaizen techniques. By deploying the LSS, the overall PCE improved from 22% to 62%, and lead time was reduced from 1,347 min to 501 min. DoE results showed that the optimum process parameter levels decreased defects per unit steel sheet.

This research demonstrated how successful LSS implementation eliminates waste, improves process performance and accomplishes operational distinction in steel manufacturing.

Since low-cost/high-effect improvement initiatives have not been adequately presented, further research studies on adopting LSS in manufacturing sectors are needed. The cost-effective method of process improvement can be considered as an innovation.

This paper aims to introduce a novel structure for the physical internet (PI)–enabled sustainable supplier selection and inventory management problem under uncertain environments.

To address hybrid uncertainty both in the objective function and constraints, a novel interactive hybrid multi-objective optimization solution approach combining Me-based fuzzy possibilistic programming and interval programming approaches is tailored.

Various numerical experiments are introduced to validate the feasibility of the established model and the proposed solution method.

Due to its interconnectedness, the PI has the opportunity to support firms in addressing sustainability challenges and reducing initial impact. The sustainable supplier selection and inventory management have become critical operational challenges in PI-enabled supply chain problems. This is the first attempt on this issue, which uses the presented novel interactive possibilistic programming method.

Construction experts acknowledge the adverse effects of rework on project performance. However, the limited understanding of its underlying causes remains a significant challenge. Therefore, this study aimed to thoroughly investigate the sources of construction rework.

A mixed review using bibliometric analysis as a quantitative method and content analysis as a qualitative method was performed to understand the current knowledge in the field. The Web of Science (WoS) was selected for its comprehensive collection of major research articles and integrated analytical tools for generating representative data. The study involved an extensive bibliometric analysis of 107 journal articles on rework causes from 1991 to 2023. RStudio Bibliometrix, an R statistical programming package, was used to analyze rework origins. This method involved mapping the research landscape, identifying research gaps and analyzing emerging trends.

The causes of rework can be classified into three main clusters: human- and contractual-based rework causes, design-, quality- and project management-based rework causes and organizational-based rework causes.

Although several studies have addressed rework causes from various perspectives and methods, the topic has not been investigated holistically. This study is the first to leverage the quantitative and qualitative analytical capabilities of the RStudio Bibliometrix package. Innovative approaches, including the use of metrics, such as the h-index, thematic mapping and trend topic analysis, were employed for a comprehensive understanding of rework causes.

The textile industry contributes 2 and 3% to the global and Indian Gross Domestic Product (GDP), respectively. India supplies a quarter of global cotton yarn. Yet, most yarn manufacturing companies use outdated methods and lack organisational skills and strategies. Improvement in processes in India could significantly help the industry worldwide.

The variables that influence the performance of the system were identified. Their interrelationships and impact were identified from the employees in the chosen case study, a yarn manufacturing industry. A System Dynamics (SD) approach was employed to study the benefits of implementing 5S lean strategies. The impact of each variable on various performance measures such as throughput, Work In Progress, processing time, waiting time, idle time, over-processing and scraps was analysed.

Improvement in outcomes reflected an enhanced adoption of leanness in the industry. The decision-makers can utilise this study to optimise the necessary parameters in the system and attain the desired productivity levels. Better resource management and reduced processing time helped increase the despatch rate by 9.735% and decrease the WIP by 23.01%. Time management helped to reduce the inventory, idle time and waiting time. Over-processing, defects and scraps were minimised, indicating a shift towards lean.

This study pioneers the use of SD simulation models for optimising yarn manufacturing using lean strategies. Improvement in performance measures by integrating these strategies opens avenues for future research using multiple approaches to address a problem.

Implementing 5S lean principles and simulations enhances productivity, reduces waste and optimises resource management for the yarn manufacturing industry. Decision-makers can employ simulation to witness the outcomes of their changes without investing cost and time and without associated implementation risks.

The use of a simulation model to witness the benefits of incorporating lean strategies in yarn production has not been explored. This approach could help the managers and policymakers understand their existing system's shortcomings and critical areas that require improvement.

Innovation is critical for businesses to stay competitive in today's world, as it allows them to constantly look for new ways to differentiate their products or services from their competitors as well as improve cost-effectiveness. This study explore the role of strategic human resource practices in developing organizations' competitive capabilities-differentiation and cost-effectiveness, which, improves their innovation performance to create a competitive advantage.

The authors collected data from 387 employees from 25 knowledge-intensive information technology organizations in India through a questionnaire-based survey. After checking for biases, reliability and validity, the hypothesized relationships were tested by structural equational modeling using AMOS 26.

Strategic HR practices have a significant and positive effect on innovation performance and both competitive capabilities-differentiation and cost-effectiveness. While the differentiation capability had a strong positive effect on innovation performance, cost-effectiveness capability was not significantly related to innovation performance. The differentiation capability mediates the relationship between strategic HR practices and innovation performance link, whereas the cost-effectiveness capability did not have a mediating effect.

This study provides practical insights to HR and knowledge managers to focus on development of human capital and invest in hiring, training, development, strategic performance management practices to enhance employees' knowledge behaviors, which, stimulates innovation performance.

The paper adds to the strategic HRM paradigm by clarifying the underlying process of how strategic HR practices leads to higher innovation. It affirms the vitality of choosing appropriate competitive capabilities, and supporting organizational factor for business's success. It fills an important research gap by providing original empirical evidence from knowledge intensive information technology organizations in the emerging economy of India.

The construction industry continues to struggle to deliver a right first time culture, seeking a panacea for improvement whilst maintaining project milestones. Complex construction projects demand stringent programmes, however, (un)foreseen changes, political influences and human behaviours all have significant impacts on delivering schemes without error. Previous studies have questioned the ability of the construction industry to successfully learn from errors. A major barrier has been the sharing of sensitive data from failed outcomes. Hence, this paper investigates non-conformance on an existing scheme and suggests avenues for improvement.

A mixed-method approach was adopted whereby 1,260 non-conformance reports (NCRs) from a highways megaproject were interrogated using root cause analysis (RCA) techniques to uncover the most frequent and costly areas. This was followed by a survey to industry professionals within a tier 1 principal contractor to gain insight into their perceptions of non-conformance and rework on construction projects.

Using Pareto analysis, the authors find that materials management, workmanship (poor quality execution) and supervision issues are the most frequently occurring and costly root causes of non-conformance on a major highways scheme. Furthermore, the authors link corresponding viewpoints of two project professional groups to the posed, achieving a high degree of consensus for the areas requiring development. Lastly, the authors suggest avenues for improvement via lessons learnt. These include greater emphasis on quality culture via a strong leadership mandate, enhanced vetting of workforce competence and improving the way materials are managed by embracing technology to drive efficiency.

This paper interrogates a current highways scheme using a uniquely rich, sensitive dataset to determine how the construction sector may improve efforts to achieving right first time outcomes.

The purpose of this paper is to examine the resistance behavior of smart factories in small and medium-sized enterprises (SMEs). Drawing upon dual factor perspective, this study examines how two types of quality and perceived usefulness impact user resistance as enabling factors and how switching cost, skepticism, habit and inertia contribute to user resistance as inhibiting factors. Additionally, multi-group analysis is employed to compare small and medium enterprises.

Purposive sampling technique was employed to collect 460 Korean SMEs employees, consisting of 235 small enterprises and 225 medium enterprises. Partial least squares structural equation modeling was used for data analysis.

The results reveal that all three inhibiting factors, switching cost, skepticism and habit, are key antecedents of inertia. In small enterprises, skepticism has a greater impact on inertia, which in turn strongly affects resistance. Additionally, system quality is more crucial for small enterprises, whereas information quality holds more importance for medium enterprises in mitigating resistance. Moreover, when the implementation level of a smart factory is high, the effect of perceived usefulness on user resistance diminishes.

This study has revealed the importance of considering both enabling and inhibiting factors for the adoption of smart factory systems in the context of SMEs. Additionally, it has provided evidence that as the level of the smart factory system increases, the effect of perceived usefulness on user resistance decreases, thus making the transition to smart factory systems more challenging.

This research objective is to (1) examine the effect of organizational factors on quality performance, (2) examine the effect of quality performance on competitive advantage and (3) examine the mediating role of quality performance between organizational factors and competitive advantage.

The research sample includes 140 employees in the Windusari village-owned enterprise, in Magelang, Indonesia. Data are collected using 5-Likert scale questionnaires which follow Ferdousi et al. (2019). The dependent variable is a competitive advantage. The Independent variable is organizational factors which are top management support, employee empowerment, employee involvement, reward and recognition, training and customer focus. The mediating variable is quality performance. Data analysis uses path analysis provided by structural equation modeling.

Based on path analysis, organizational factors have a positive effect on quality performance, quality performance has a positive effect on competitive advantage and quality performance mediates the effect of organizational factors on competitive advantage. The results confirm the concept of quality management where continuous improvement of products and services can meet customer expectations and bring the organization to a better position in the industry to face other competitors.

This research extends the previous studies of the relationship between organizational factors and organizational outcomes by considering the effectiveness of the organizational process. This research also contributes to giving new evidence about the relationship between organizational factors, quality management and competitive advantage in the village-owned enterprise in Magelang, Indonesia. This research also contributes to updating the literature on the theory of quality management.

The success of construction projects can be indicated by measuring their performance. For effective project performance (PP), the successful execution of a construction projects is very important. A systematic review of the literature on performance areas and performance assessment models was undertaken. The purpose of this paper is to develop a mathematical formulation for construction PP areas to suit the Indian context by modifying the current project quarterback rating (PQR) model.

Based on the literature, the PQR model has not been validated for suitability in the Indian context. To validate the PQR model and modify the same for the Indian context, a survey instrument was used to collect data on performance areas and a multivariate data analysis technique was carried out to develop a modified model. Delphi technique was used to assign the weights for each performance metric in performance areas.

This study concluded the importance of three additional performance areas, namely, productivity, stakeholder satisfaction and environment for assessing PP for Indian construction projects. It also identified the interrelationship between the performance areas and the PP.

The developed modified PQR model (MPQR) will guide the concerned stakeholders to take corrective actions for improving the performance of construction projects.

The MPQR proposed in this paper covers ten areas and is a comprehensive single score that can be used to benchmark and compare performance over different projects to achieve continuous improvement.