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The purpose of this paper is to design a modified version of the double sampling plan to handle the inspection processes requiring a minimum sample size to assure the median life for the products under the new Weibull–Pareto distribution. The economic design of the proposed plan is also considered to assure the product's lifetime with minimum cost.

The authors have developed an optimization model for obtaining the required plan parameters by solving simultaneously two non-linear inequalities and such inequalities have been formed based on the two points on the operating characteristic curve approach.

The results show that the average sample number, average total inspection and total inspection cost under the proposed plan are smaller than the same of a single sampling plan. This means that the proposed plan will be more efficient than a single sampling plan in reducing inspection effort and cost while providing the desired protection.

The proposed modified double sampling plan designed to assure the median life of the products under the new Weibull–Pareto distribution is not available in the literature. The proposed plan will be very useful in assuring the product median lifetime with minimum sample size as well as minimum cost in all the manufacturing industries.

This paper aims to propose a new method to derive custom dynamic cyber risk metrics based on the well-known Goal, Question, Metric (GQM) approach. A framework that complements it and makes it much easier to use has been proposed too. Both, the method and the framework, have been validated within two challenging application domains: continuous risk assessment within a smart farm and risk-based adaptive security to reconfigure a Web application firewall.

The authors have identified a problem and provided motivation. They have developed their theory and engineered a new method and a framework to complement it. They have demonstrated the proposed method and framework work, validating them in two real use cases.

The GQM method, often applied within the software quality field, is a good basis for proposing a method to define new tailored cyber risk metrics that meet the requirements of current application domains. A comprehensive framework that formalises possible goals and questions translated to potential measurements can greatly facilitate the use of this method.

The proposed method enables the application of the GQM approach to cyber risk measurement. The proposed framework allows new cyber risk metrics to be inferred by choosing between suggested goals and questions and measuring the relevant elements of probability and impact. The authors’ approach demonstrates to be generic and flexible enough to allow very different organisations with heterogeneous requirements to derive tailored metrics useful for their particular risk management processes.

This study aims to investigate key aspects of public ownership of land, expropriation and compensation laws and practices in Ethiopia with special reference to Burayu Town.

A mixed research technique of descriptive and analytic approach is applied in the research. This study used a purposive sampling technique to select case study counties and a systematic method for sampling households. Questionnaire surveys, focus group discussions, interviews and observations were used to collect empirical data. Average, percentage and paired-sample t-test analyses are used for quantitative data analysis.

Significant discrepancies exist between the expropriation laws and how property valuation and compensation are practiced in Ethiopia. The findings include the arbitrariness in designating public interest status to projects; unfair property valuation practice that neglects location factor to determine market value due to a skewed understanding of public ownership of land; and the assignment of property valuators who have no valuation expertise and proper knowledge of expropriation related laws. Findings revealed the socio-economic status of expropriated households has deteriorated due to the expropriation of their landholding.

It was difficult to locate the relocated persons as they were resettled in different localities. Furthermore, the town officers were not forthcoming to provide complete information on the expropriation and compensation procedures they followed. However, this study overcame the limitations through persistent requests and availing time for the data gathering.

The findings indicated the need to redefine relationships between public ownership of land, public interest and expropriation of landholding. A proper understanding of the triad will pave the way for better expropriation practice in Ethiopia and in countries where land is under public ownership.

The social implication of the study revealed that the socio-economic situation of relocated persons was adversely affected due to the poor implementation of laws.

The disparity between public ownership of land and the rights of citizens on landholding is misunderstood by policymakers. Research has shown for the first time the root cause for the discontent of expropriated persons in Ethiopia.

This study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into the logistics management field.

Rooting their analytical categories in the LMD literature, the authors performed a deductive, theory refinement SLR on 307 interdisciplinary journal articles published during 2015–2022 to integrate this emergent phenomenon into the field.

The authors derived the potentials, challenges and solutions of drone deliveries in relation to 12 LMD criteria dispersed across four stakeholder groups: senders, receivers, regulators and societies. Relationships between these criteria were also identified.

This review contributes to logistics management by offering a current, nuanced and multifaceted discussion of drones' potential to improve the LMD process together with the challenges and solutions involved.

The authors provide logistics managers with a holistic roadmap to help them make informed decisions about adopting drones in their delivery systems. Regulators and society members also gain insights into the prospects, requirements and repercussions of drone deliveries.

This is one of the first SLRs on drone applications in LMD from a logistics management perspective.

Construction industry faces challenges in making objective decisions due to monetary value attached to quality. Among various quality management techniques available, cost of quality (COQ) is one such method used to address the concern. However, the absence of measurable COQ factors to monitor quality costs hampers the implementation of COQ framework in the construction industry. Therefore, this study aims to identify COQ factors focused on visible factors (VF) and hidden factors (HF) and the current requirements to achieve it.

This study is based on Preferred Reporting Items for Systematic Review and Meta-Analyses protocol guidelines. The present study identified 57 articles published between 1992 and 2023 in peer-reviewed journals.

The findings reveal 22 factors, which are grouped into four categories based on COQ. Through systematic review, the authors observed limited methodological and theoretical diversity. In fact, there are no quantitative frameworks to calculate COQ. The study, therefore, developed a framework comprising four major routes/paths of COQ factors within the framework.

The COQ routes developed through this study will enable the practitioners to meticulously categorise VF and HF, facilitating quantifying of quality throughout the lifecycle of project, which is currently absent from the existing quality assurance/quality control (QA/QC) approach. In addition, these COQ routes stand as essential construction strategies, significantly enhancing outcomes related to time, cost, quality, sustainability and fostering closer relationships within project frameworks.

The current study contributes significantly to the existing body of knowledge by developing various COQ routes and proposing future research directions to address gaps in the literature.

The equipment resale price plays an important role in calculating the optimum time for equipment replacement. Some of the existing models that predict the equipment resale price do not take many of the influencing factors on the resale price into account. Other models consider more factors that influence equipment resale price, but they still with low accuracy because of the modeling techniques that were used. An easy tool is required to help in forecasting the resale price and support efficient decisions for equipment replacement. This research presents a machine learning (ML) computer model helping in forecasting accurately the equipment resale price.

A measuring method for the influencing factors that have impacts on the equipment resale price was determined. The values of those factors were measured for 1,700 pieces of equipment and their corresponding resale price. The data were used to develop a ML model that covers three types of equipment (loaders, excavators and bulldozers). The methodology used to develop the model applied three ML algorithms: the random forest regressor, extra trees regressor and decision tree regressor, to find an accurate model for the equipment resale price. The three algorithms were verified and tested with data of 340 pieces of equipment.

Using a large number of data to train the ML model resulted in a high-accuracy predicting model. The accuracy of the extra trees regressor algorithm was the highest among the three used algorithms to develop the ML model. The accuracy of the model is 98%. A computer interface is designed to make the use of the model easier.

The proposed model is accurate and makes it easy to predict the equipment resale price. The predicted resale price can be used to calculate equipment elements that are essential for developing a dependable equipment replacement plan. The proposed model was developed based on the most influencing factors on the equipment resale price and evaluation of those factors was done using reliable methods. The technique used to develop the model is the ML that proved its accuracy in modeling. The accuracy of the model, which is 98%, enhances the value of the model.

This study aims to minimize the cost and time of blood delivery in the whole blood supply chain network (BSCN) in disaster conditions. In other words, integrating all strategic, tactical and operational decisions of three levels of blood collection, processing and distribution leads to satisfying the demand at the right time.

This paper proposes an integrated BSCN in disaster conditions to consider four categories of facilities, including temporary blood collection centers, field hospitals, main blood processing centers and medical centers, to optimize demand response time appropriately. The proposed model applies the location of all permanent and emergency facilities in three levels: blood collection, processing and distribution. Other essential decisions, including multipurpose facilities, emergency transportation, inventory and allocation, were also used in the model. The LP metric method is applied to solve the proposed bi-objective mathematical model for the BSCN.

The findings show that this model clarifies its efficiency in the total cost and blood delivery time reduction, which results in a low carbon transmission of the blood supply chain.

The researchers proposed an integrated BSCN in disaster conditions to minimize the cost and time of blood delivery. They considered multipurpose capabilities for facilities (e.g. field hospitals are responsible for the three purposes of blood collection, processing and distribution), and so locating permanent and emergency facilities at three levels of blood collection, processing and distribution, support facilities, emergency transportation and traffic on the route with pollution were used to present a new model.

The purpose of this study is to examine the management of cash waqf fund generation through the implementation of istibdal in Kedah.

The data are obtained through literature and empirical data. The authors first review the literature on the importance of waqf fundraising, the implementation factors of istibdal waqf and the relevance of istibdal method as a waqf fund generation medium to understand the extent to which the scholarly articles have discussed these topics. Furthermore, the authors conducted face-to-face interviews with two Kedah Islamic Religious Council (Majlis Agama Islam Kedah [MAIK]) officers, who were directly involved in the affairs of istibdal waqf to obtain holistic information regarding implementing istibdal waqf properties in Kedah. As a result, several themes are defined from the interview data before being analysed based on the content analysis method.

The results of the study show two istibdal implementation processes outlined by the Kedah Islamic Religious Council (MAIK), namely, the istibdal implementation process for waqf land registered title deed, and waqf land registered as reserve certificate for religious use like mosque and cemetery. The results also showed three factors in implementing istibdal in Kedah: the acquisition of waqf land by the state authority (PBN), istibdal application by the state education department (JPN) and istibdal application by the mosque committee. Out of eight cases of istibdal implementation, four have generated cash funds for MAIK through investment methods from the sale of waqf lands and rental of replaced shophouses that are able to cover the expenses of managing waqf properties in Kedah. Several suggestions are also recommended for MAIK to improve its istibdal policy, thus enabling the institution to generate cash waqf funds at the maximum rate.

This study only focused on the implementation factors and the generation of cash waqf funds through istibdal in Kedah, while it can be expanded to other states like Terengganu, Kelantan and Penang. Furthermore, this study only interviewed officers who manage matters related to the affairs of waqf properties, as the session can actually be extended to other respondents, such as those specialising in cash fund generation investments and others.

This study proposed some improvements to the policy and guidelines of istibdal waqf property to MAIK after a few shortcomings were identified throughout this study. If improved, these proposals will have a significant impact, especially on the waqf properties involved in the implementation of istibdal, where it has the potential to bring cash generation and ensure the constant economic value of waqf properties.

This study has a tremendous impact on society, in which their areas have cash waqf funds that can be developed. It can benefit the needy and increase funds for the welfare expenditure of Muslims through rental income, investment and development. Progress on waqf property provides a high indication of the efficiency of an organisation in managing the waqf property. Thus, the public, especially the rich, is motivated to fulfil their charitable practices through waqf mechanism and share their wealth with the needy.

This study contributes to comprehensive field data on the implementation factors and generation of cash waqf funds through the implementation of istibdal in Kedah. The results of this study are significant to be used by waqf property management.

Efficient management of earthmoving equipment is critical for decision-makers in construction engineering management. Thus, the purpose of this paper is to prudently identify, select, manage and optimize the associated decision variables (e.g. capacity, number and speed) for trucks and loaders equipment to minimize cost and time objectives.

This paper addresses an innovative multiobjective and multivariable mathematical optimization model to generate a Pareto-optimality set of solutions that offers insights of optimal tradeoffs between minimizing earthmoving activity’s cost and time. The proposed model has three major stages: first, define all related decision variables for trucks and loaders and detect all related constraints that affect the optimization model; second, derive the mathematical optimization model and apply the multiobjective genetic algorithms and classify all inputs and outputs related to the mathematical model; and third, model validation.

The efficiency of the proposed optimization model has been validated using a case study of earthmoving activities based on data collected from the real-world construction site. The outputs of the conducted optimization process promise the model’s originality and efficiency in generating optimal solutions for optimal time and cost objectives.

This model provides the decision-maker with an efficient tool to select the optimal design variables to minimize the activity's time and cost.

Extensive macro- and micro-economics research has been conducted on China's tax reform, which replaced business tax with value-added tax (VAT). However, existing studies have not clarified the reform's impact on firm-level investment decisions. Hence, this study explored the effect of replacing business tax with VAT on firms' investment efficiency.

The study used 2010–2018 data from China's A-share listed companies and a difference-in-differences (DID) model to explore the effect of the reform on firm-level investment decisions.

The authors found that China's tax reform has improved investment efficiency in underinvested firms, increased liquidity and decreased the level of reliance on external financing. The tax reform had a greater effect on investment efficiency in firms with lower liquidity and higher external financing reliance. Its effect was also more significant among non-state-owned and small companies.

This study fills the aforementioned research gap by exploring the effects of China's tax reform, thus providing a theoretical reference and a basis for policymaking.