Search results

The purpose of this study is to optimize the operational efficiency of the entire system by developing a reasonable maintenance strategy for wind turbines that improves component reliability and safety while reducing maintenance costs.

A hybrid incomplete preventive maintenance (PM) model based on boundary intensity process is established to give dynamic PM intervals for wind turbines using an iterative method with reliability as a constraint; the selection method of PM and replacement is given based on the cost-effectiveness ratio, which in turn determines the optimal number of PM for wind turbines.

The reliability is used to obtain the components’ maintenance cycle, and the cost-effectiveness ratio is used to select the number of maintenance times, thus, getting the optimal maintenance strategy. The validity of this paper’s method is verified by arithmetic cases, which provides a new method for formulating a reasonable PM strategy for wind turbines.

The wind turbine preventive maintenance strategy for Boundary intensity process proposed in this paper can scientifically formulate the maintenance strategy, optimize the cost-effectiveness per unit of time of the wind power generation system, and solve the problems of difficulty in formulating a reasonable maintenance strategy for the wind turbine components and high operation and maintenance costs.

In this paper, the authors describe the failure pattern by a Boundary intensity process, establish a hybrid incomplete PM model by introducing a failure intensity increment factor and an age reduction factor and establish a maintenance strategy optimization model with comprehensive consideration of reliability and cost-effectiveness ratio. Finally, the validity of the model in this paper is verified by arithmetic case analysis.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0153/

This study explores how strategic human resource practices enhance the competitive capability of differentiation and cost-effectiveness by leveraging knowledge resources in Indian IT/software organizations. It examines the mediating effect of knowledge management (KM) processes in the relationship between strategic HR practices, competitive differentiation and cost-effectiveness capabilities.

An online questionnaire survey collected data from 380 knowledge workers in 25 IT/software and consultancy firms. The authors checked data reliability and validity by conducting exploratory factor analysis in SPSS and confirmatory factor analysis in AMOS. The authors evaluated hypotheses using path analysis in structural equational modeling in AMOS.

Strategic HR practices significantly and positively affect KM processes and competitive capabilities-differentiation and cost-efficiency. Both strategic HR practices and KM processes have a closer association with differentiation than cost-effectiveness. Knowledge management processes significantly and positively mediate between strategic HR practices and competitive capabilities. The mediation is more substantial in predicting differentiation than cost-effectiveness.

It is a cross-sectional study with a constrained capacity to predict accurate causal inferences; The authors call for future studies with longitudinal design and objective measures. Further studies are required to explore the impact of various strategic HR configurations on KMP to understand how different routes stimulate a particular competitive strategy. This conceptual framework can be validated across different industry types and sizes.

This study provides practical insights to HR and knowledge managers regarding devising HR and KM processes to accomplish the goals of differentiation and cost-effective, competitive strategies. This study highlights that leveraging human capital for effective KM is crucial for gaining a competitive advantage.

The paper adds to the strategic HR and KM literature by exploring the mediating role of KM processes in enabling strategic HR processes to enhance differentiation and cost-effective, competitive strategies. It provides original empirical evidence from knowledge-intensive IT/software consultancies, particularly in India's emerging economy. It indicates the current state of HR practices adopted for optimum utilization of knowledge resources and the importance of differentiation strategy for Indian knowledge-intensive IT/software firms.

Blockchain technology (BCT) is considered a promising tool to improve the productivity of construction project management. Existing research has studied its potential costs and benefits for the construction industry. However, the potential costs and benefits of BCT failed to be compared as actual costs and benefits of specific applications for stakeholders. To fill this gap, this study seeks to analyze the cost-effectiveness of BCT-based applications in construction project management.

This study is conducted with a customized systematic literature review based on transaction cost theory to enable qualitative comparison. With a deliberately designed structure confining extraneous variables, the costs and benefits of BCT-based applications are identified and compared. The inherent dependent relations of processes and the evolution relations of functions are identified. The cost-effectiveness of blockchain adoption is then analyzed.

Seven functions and six challenges are identified within five processes. The result suggests all identified functions are cost-effective except for manual instruction (coding smart contracts manually). The smart contracts require explicit definition and logic to be effective. However, the construction projects essentially require the institution to be flexible due to unpredictability. The adoption of smart contracts and corresponding additional requirements can increase the transaction cost of bounded rationality.

As manual instruction is fundamental to realize other functions, and its advanced substitute relies on its broad adoption, its cost-effectiveness must be improved for applications to be acceptable to stakeholders. The establishment of a universal smart contract model and a universal, legitimate and efficient database structure are recommended to minimize the cost and maximize the effect of applications.

This study contributes to the knowledge by providing a comprehensive analysis of BCT adoption’s cost-effectiveness in construction project management. The adopted review structure can be extended to analyze the qualitative benefits and challenges of management automation in the early stages.

The main objective of this study is to investigate the factors that influence the adoption intention of cloud computing services among individual users using the extended theory of planned behavior.

A purposive sampling technique was used to collect a total of 339 data points, which were analyzed using SmartPLS to derive variance-based structural equation modeling and fuzzy-set qualitative comparative analysis (fsQCA).

The results obtained from PLS-SEM indicate that attitude towards cloud computing, subjective norms, perceived behavioral control, perceived security, cost-effectiveness, and performance expectancy all have a positive and significant impact on the adoption intention of cloud computing services among individual users. On the other hand, the findings from fsQCA provide a clear interpretation and deeper insights into the adoption intention of individual users of cloud computing services by revealing the complex relationships between multiple combinations of antecedents. This helps to understand the reasons for individual users' adoption intention in emerging countries.

This study offers valuable insights to cloud service providers and cyber entrepreneurs on how to promote cloud computing services to individual users in developing countries. It helps these organizations understand their priorities for encouraging cloud computing adoption among individual users from emerging countries. Additionally, policymakers can also understand their role in creating a comfortable and flexible cloud computing access environment for individual users.

This study has contributed to the increasingly growing empirical literature on cloud computing adoption and demonstrates the effectiveness of the proposed theoretical framework in identifying the potential reasons for the slow growth of cloud computing services adoption in the developing world.

Cloud computing services are game-changing in empowering organizations to drive innovation and unlock new growth opportunities. Accordingly, this study aims to examine the determinants of cloud computing adoption in SMEs and assess their impact on firm financial performance, specifically focusing on the mediating role of organizational agility in driving cloud-enabled financial improvements.

Data were collected from 405 owners and managers of SMEs who used cloud computing. A “variance based-structural equation modelling” (PLS-SEM) was employed to test the hypothesis.

The PLS-SEM result shows that relative advantage, cost-effectiveness, compatibility and external environment support significantly influence cloud computing adoption in SMEs. However, complexity insignificantly impacts cloud computing adoption. The analysis also revealed that cloud computing adoption substantially influences organizational agility. Similarly, cloud computing adoption and organizational agility significantly influence firms’ financial performance.

The present research provides valuable suggestions to service providers, policymakers and managers on developing and expanding cloud computing in developed and developing nations. Additionally, cloud providers can recognize their role in creating a supportive and adaptable environment that ensures convenient access to cloud computing users.

This research is an initial attempt to blend the strength of diffusion of innovation (DOI) theory with two additional constructs (i.e. cost-effectiveness and external environment support) for making a comprehensive model of cloud computing adoption and its influence on firm financial performance. By doing this, the research adds to the empirical knowledge on cloud computing adoption and provides an institutional framework to interpret the impact of cloud-based information technology.

Health technologies are advancing rapidly and becoming more expensive, posing a challenge for financing healthcare systems. Health technology assessment (HTA) improves the efficiency of resource allocation by facilitating evidence-informed decisions on the value of health technologies. Our study aims to create a customized HTA roadmap for Oman based on a gap analysis between the current and future status of HTA implementation.

We surveyed participants of an advanced HTA training program to assess the current state of HTA implementation in Oman and explore long-term goals. A list of draft recommendations was developed in areas with room for improvement. The list was then validated for its feasibility in a round table discussion with senior health policy experts to conclude on specific actions for HTA implementation.

Survey results aligned well with expert discussions. The round table discussion concluded with a phasic action plan for HTA implementation. In the short term (1–2 years), efforts will focus on building capacity through training programs. For medium-term actions (3–5 years), plans include expanding the HTA unit and introducing multiple cost-effectiveness thresholds while from 6–10 years, publishing of HTA recommendations, critical appraisal reports, and timelines is recommended.

Although the HTA system in Oman is still in its early stages, strong initiatives are being taken for its advancement. This structured approach ensures a comprehensive integration of HTA into the healthcare system, enhancing decision-making and promoting a sustainable, evidence-based system addressing the population’s needs.

This study aims to address the challenges faced by healthcare manufacturing SMEs in high-mix, high-volume environments, particularly in light of the COVID-19 pandemic.The authors propose the implementation of the Production Wheel framework as a solution to optimize operational efficiency and cost-effectiveness. Using real-world anonymized data from a high-mix, high-volume manufacturing project, the authors evaluate the feasibility and impact of this framework. The findings indicate significant reductions in changeover and inventory costs, with notable improvements in production efficiency. The study highlights the potential of the Production Wheel in healthcare manufacturing while providing insights based on authentic industry data.

The Production Wheel framework is introduced as an 8-step method that encompasses analyzing historical volumes, identifying key product families, developing current and future state value stream maps, assessing capacity utilization and implementing Kanban-based pull systems with supermarkets between processes. This approach is grounded in Lean manufacturing principles and is tailored to the specific needs of the healthcare manufacturing industry.

The adoption of the Production Wheel framework enables healthcare manufacturers to align their production more closely with actual demand, minimizing waste and reducing overheads. This agile approach facilitates the adaptation to a high mix of products without compromising efficiency, ensuring a resilient and responsive supply chain that can effectively meet the evolving needs of the market.

While this conceptual paper introduces the Production Wheel framework in the context of healthcare manufacturing, future research should focus on the practical implementation and empirical validation of the proposed approach. Case studies and quantitative analyses of the framework’s impact on operational efficiency, inventory management and cost-effectiveness would provide valuable insights for academics and practitioners.

The Production Wheel framework offers a practical approach for healthcare manufacturers to navigate the challenges posed by the COVID-19 pandemic and the increasing demand for customized products. By integrating this methodology alongside flexible manufacturing systems, manufacturers can enhance their ability to adapt to market disruptions while maintaining optimal operational performance.

This paper contributes to the Lean Manufacturing literature by introducing the Production Wheel concept as a novel framework for healthcare manufacturing. The proposed approach addresses the unique challenges faced by the healthcare manufacturing sector in the wake of the COVID-19 pandemic and provides a strategic roadmap for optimizing operational efficiency and cost-effectiveness.

This paper aims to introduce an innovative decision-making framework designed to optimize egress location selection in buildings, significantly enhancing safety during emergencies. By integrating social, economic and technical criteria through the fuzzy analytic hierarchy process (F-AHP), this framework effectively manages the uncertainties inherent in emergency scenarios, providing a robust tool for safeguarding lives and property.

The proposed methodology employs the F-AHP to systematically integrate and evaluate social, economic and technical criteria for egress location selection. A comprehensive case study conducted on a one-story school building demonstrates this approach’s practical application and effectiveness.

The analysis reveals that economic criteria are the most significant in determining the optimal egress location, constituting 61.9% of the overall weight, followed by technical criteria at 26.8% and social criteria at 11.3%. The findings highlight the practical application and effectiveness of the proposed approach in addressing uncertainties and optimizing egress location selection. Integrating social, economic and technical considerations gives decision-makers a robust tool to optimize safety, cost-effectiveness and evacuation efficiency.

The findings underscore the practical benefits and effectiveness of the proposed approach in managing uncertainties and improving the selection of optimal egress locations. Integrating social, economic and technical considerations gives decision-makers a robust tool to optimize safety, cost-effectiveness and evacuation efficiency. This approach equips practitioners with a comprehensive framework for enhancing emergency preparedness and resilience in various building scenarios.

This research introduces a novel framework for egress location selection that addresses the limitations of existing studies by integrating multiple criteria – social, economic and technical – into a cohesive decision-making process. Using the F-AHP in a case study illustrates the framework’s practicality and adaptability, providing a dynamic solution that enhances the overall effectiveness of emergency plans. By prioritizing safety, cost-effectiveness and efficiency, this framework ensures that emergency plans are robust and adaptable, thereby significantly enhancing resilience in the face of emergencies.

Pressure to address drug shortages is increasing, and calls for cross-national stockpiling solutions are on the rise. This paper argues that cross-national stockpiling presents an important opportunity for operations and supply chain management (OSCM) research to help improve medicine access in the short- and long-term.

To substantiate our claims for future research, we conducted an empirical analysis of shortage co-occurrence on twelve EU member-states, reviewed practice reports and academic literature, and held extensive discussions with pharmaceutical supply chain stakeholders.

We show that the potential for cross-national stockpiling is unmistakably there and that, although OSCM research has touched upon important facets of cross-national stockpiling, many open questions still require novel research.

We present opportunities for impactful research along various dimensions, including understanding barriers and stakeholder behavior, quantifying cost-effectiveness and potential knock-on effects, analyzing the positive and negative implications of product standardization and determining novel equitable mechanisms for allocation and financing cross-national stockpiles.

This study proposes low-carbon technology (LCT) solutions from the perspective of incremental cost-effectiveness and public satisfaction based on calculating carbon emissions and economic costs.

According to the citation frequency, 11 indicators of low-carbon neighborhood (LCN) were selected so as to construct the low-carbon renewal potential evaluation model. Five neighborhoods were selected to evaluate low-carbon renewal potential based on the driving-pressure-state-impact-response (DPSIR). Moreover, the neighborhoods with the highest renewal potential were selected for further analysis. Then, the feasibility decision was carried out among seven typical LCTs based on the value engineering (VE) method. Finally, the TOPSIS method was applied to calculate the public satisfaction and demand so as to get the priorities of these LCTs. Through comprehensive analysis, the final LCT solutions could be carried out.

Our practice proves that the evaluation model combined with the decision-making methods can provide scientific decision-making support for the LCT solutions. Some LCTs perform consistently across different neighborhoods by comparing VE results and TOPSIS rankings. The solar photovoltaic (PV) (T3) has high value and significant attention which gives it a top priority for development, while the energy-efficient windows and doors (T2) have relatively low value.

There is a lack of research that considers the economic cost, low-carbon efficiency and public satisfaction when proposing LCT solutions for neighborhood renewal projects. Faced with the problem, we practice the decision-making from two dimensions, that is, the “feasibility decision with VE” and the “priorities decision with TOPSIS.” In this way, a balance between incremental cost-effectiveness and public satisfaction is achieved, and LCT solutions are proposed.