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This study aims to ground the assessment of the various costing perspectives associated with the dynamics of processed food supply chains (FSCs), for questing the avenues of profitability within a food processing enterprise.

This study underpins the development of the relation hierarchical model, binding the cluster of the key costing enactors, with the various incurred costs in the food supply chain performance system. The developed model is seeded by the inputs gathered from the case enterprises under consideration, which is further contemplated by extending the fundamentals of bipolar fuzzy sets with the methodology of ELECTRE-II.

Secured primacies owing to the mutual correspondence between the costing cluster reveal the impact of procurement cost in the dynamics of FSC. Furthermore, an inference is grounded relative to the other entities of total costs like investment, production, transportation, distribution and retailing by considering the perspective of a case enterprise. It yields that procurement costing procedurals need to be deliberated supremely, considering the vitality of the costing perspective associated with the other procedurals of the case enterprise.

The framework developed in the presented work clusters the various costing enactors along with the costings in processed FSCs, binding its holistic perspective rather than the discrete approach. The present research work provides an origin to explore the various miniatures more precisely succeeding to secure primacies for upscaling the profit-cost notions. As costing determines the avenues bundled with the production and consumption of various food commodities.

This research aims to aid product development managers to estimate the expected cost associated with the development of cost-intensive physical prototypes considering transitions associated with pertinent states of quality of the prototype and corresponding decision policies under the Markovian setting.

The authors evolve two types of optimization-based mathematical models under both deterministic and randomized policies. Under the deterministic policy, the product development managers take certain decisions such as “Do nothing,” “Overhaul,” or “Replace” corresponding to different quality states of prototype such as “Good as new,” “Functional with minor deterioration,” “Functional with major deterioration” and “Non-functional.” Under the randomized policy, the product development managers ascertain the probability distribution associated with these decisions corresponding to various states of quality. In both types of mathematical models, i.e. related to deterministic and randomized settings, minimization of the expected cost of the prototype remains the objective function.

Employing an illustrative case of the operator cabin from the construction equipment domain, the authors ascertain that randomized policy provides us with better decision interventions such that the expected cost of the prototype remains lower than that associated with the deterministic policy. The authors also ascertain the steady-state probabilities associated with a prototype remaining in a particular quality state. These findings have implications for product development budget, time to market, product quality, etc.

The authors’ work contributes toward the development of optimization-driven mathematical models that can encapsulate the nuances related to the uncertainty of transition of quality states of a prototype, decision policies at each quality state of the prototype while considering such facets for all constituent subsystems of the prototype. As opposed to a typical prescriptive study, their study captures the inherent uncertainties associated with states of quality in the context of prototype testing, etc.

Implementing building information modeling (BIM) in construction projects offers many benefits. However, the use of BIM in project cost management is still limited. This study aims to review the current trends in the application of BIM in project cost management.

This study systematically reviews the literature on the application of BIM in project cost management. A total of 46 related articles were identified and analyzed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses method.

Eighteen approaches to applying BIM in project cost management were identified. The approaches can be grouped into cost control and cost estimation. Also, BIM can be applied independently or integrated with other techniques. The integrated approaches for cost control include integration with genetic algorithms, Monte Carlo simulation, lean construction, integrated project delivery, neural network and value engineering. On the contrary, integrated approaches for cost estimation include integration with cost-plus pricing, discrepancy analysis, construction progress curves, estimation standards, algorithms, declarative mappings, life cycle sustainability assessment, ontology, Web-based frameworks and structured query language.

To the best of the authors’ knowledge, this study is the first to systematically review prior literature on the application of BIM in project cost management. As a result, the study provides a comprehensive understanding of the current state of the art and fills the literature gap. Researchers and industry professionals can use the study findings to increase the benefits of implementing BIM in construction projects.

Various approaches have emerged to assist practitioners in making more informed decisions in highway construction projects. However, industry practitioners are still using subjective ways to make decisions. Also, researchers have developed tools and techniques with similar objectives. Lack of information on what has been developed might lead to those issues. Therefore, this paper aims to review trends of evolution, pinpoint strengths and gaps in the literature and identifies potential future directions for decision-making research in highway construction projects.

A systematic review was conducted on published articles on decision-making in highway construction projects using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) technique.

The analysis of 101 articles revealed that existing decision-making research in highway construction projects targets improvements in four areas: feasibility, conceptual, detailed scope and detailed design. The four areas consist of sixteen subthemes that are detailed in this study. In addition, most research involved developing decision support tools and systems as well as decision-making models, techniques and frameworks. Lastly, several research areas have emerged, such as adding more decision criteria including those with uncertainties, expanding existing decision-making models into decision support systems, benchmarking decision criteria between different sample populations and exploring inter-and intra-relationships between decision criteria.

This paper provides an overview of existing research on decision-making in highway construction projects. Also, it reveals research gaps in the body of knowledge to point out directions for future research. Finally, industry practitioners can use the findings to develop strategies for effective decision-making processes.

The purpose of this study is to identify how the responsibilities and costs of planning, controlling and executing the material, resource and waste flows are shifted between actors when introducing a construction logistics setup (CLS) as a product innovation in a construction project, compared to the traditional way of organizing these activities.

This study is an analytical conceptual research study which aims to bring new insights into a problem through logical relationship building. Empirical data are gathered in two cases where CLSs are used, through observations and interviews regarding how the activities within the order-to-delivery process are performed. The results have been discussed at workshops with suppliers, installation companies, contractor firms and trade unions.

The outcome of this study is a model for illustrating how costs and responsibilities are shifted in the construction project and supply chain when a CLS is introduced. The cost shift is dependent on the activity shift that accompanies the services included in the setup.

The practical contribution of this work is twofold. First, this study provides a methodology of how to evaluate the impact of logistics services on the actors in the construction project. Second, this study shows shifts in costs and responsibilities in logistics activities with the introduction of construction logistics services.

The theoretical contributions of the model and this study lie in the inclusion of a multi-actor perspective in total cost modelling in supply chains.

The purpose of the study is to propose a framework for fleet management and make suitable distribution solution choices in the food industry.

This study reviews the literature to examine food distribution criteria. These criteria are used in the analytic hierarchy process (AHP) assessment and combined with discrete events simulation in a structured framework, which is validated through an empirical study.

The empirical case results demonstrate that both the AHP and discrete events simulation converge toward the same solution in most cases.

This study contributes to the literature on distribution management and develops a framework that can both guide future research and aid logistics practitioners in analysing distribution decision-making systems in dynamic environments.

The study aims to estimate the short- and long-run effects of monetary policy on residential property prices in South Africa. Over the past decades, there has been a monetary policy shift, from targeting money supply and exchange rate to inflation. The shifts have affected residential property market dynamics.

The Johansen cointegration approach was used to estimate the effects of changes in monetary policy proxies on residential property prices using quarterly data from 1980 to 2022.

Mortgage finance and economic growth have a significant positive long-run effect on residential property prices. The consumer price index, the inflation targeting framework, interest rates and exchange rates have a significant negative long-run effect on residential property prices. The Granger causality test has depicted that exchange rate significantly influences residential property prices in the short run, and interest rates, inflation targeting framework, gross domestic product, money supply consumer price index and exchange rate can quickly return to equilibrium when they are in disequilibrium.

There are limited arguments whether the inflation targeting monetary policy framework in South Africa has prevented residential property market boom and bust scenarios. The study has found that the implementation of inflation targeting framework has successfully reduced booms in residential property prices in South Africa.

This study explores the causes of delayed mandatory annual report filings of private companies in Estonia.

The authors use an online survey targeting companies that had submitted annual reports for 2017 late (late-filers) or failed to submit these by July 2020 (non-filers). The responses of 492 late-filers and 122 non-filers are analysed with exploratory factor analysis, Mann–Whitney U-Test and logistic regression.

Annual report filing decisions of both, late-filers and non-filers, are strongly driven by administrative costs attached to the preparation and submission of reports with non-filers perceiving these to be significantly greater. The relevance of other disclosure-related costs and benefits remains similar for both late-filers and non-filers. While proprietary and privacy concerns remain rather unimportant, benefits of timely disclosure, in the form of access to financing and possibilities to continue ordinary business activities, remain important disclosure timing drivers.

Policy interventions should focus on preventive measures that hinder companies' ordinary business activities in case of non-compliance to reporting deadlines. Monetary sanctions can be used to strengthen the desired behaviour alongside broader clarification of the purpose of mandatory reporting and available exemptions.

The authors propose an empirically testable comprehensive one-period model of disclosure timing decisions of private companies differentiating late-filers and non-filers. The authors address the limitations of previous studies through a survey that allows the authors to draw direct inferences about the trade-offs between different decision drivers and the motivations behind managers' disclosure timing decisions.

Many countries around the world are facing great challenges from their ageing population with shrinking workforce, this will put more pressure on their financial system and will increase the public spending on care costs provided to older people. Egypt is in the phase of establishing a new law for older people care's rights, a law that will organise how older people in need for care would benefit from access to government financial support and how will families support their older relatives financially and how the care costs will be shared between the older people, their families and the government.

The paper examines the suitability two cost-sharing methods and applying them to assess the effect on the individuals and families' income strain.

The preferred approach can be used for sharing costs as it applies a gradual funding withdrawal by the government and provide more fairness and flexibility for application in different regions. Besides, the parameters of this approach can be used by policy makers to control the levels of funding.

The paper will be the first to discuss the intergenerational fairness from a financial perspective in Egypt to avoid forcing older people into poverty or resorting to poverty trade-off.

Deep learning (DL) is on the rise because it can make predictions and judgments based on data that is unseen. Blockchain technologies are being combined with DL frameworks in various industries to provide a safe and effective infrastructure. The review comprises literature that lists the most recent techniques used in the aforementioned application sectors. We examine the current research trends across several fields and evaluate the literature in terms of its advantages and disadvantages.

The integration of blockchain and DL has been explored in several application domains for the past five years (2018–2023). Our research is guided by five research questions, and based on these questions, we concentrate on key application domains such as the usage of Internet of Things (IoT) in several applications, healthcare and cryptocurrency price prediction. We have analyzed the main challenges and possibilities concerning blockchain technologies. We have discussed the methodologies used in the pertinent publications in these areas and contrasted the research trends during the previous five years. Additionally, we provide a comparison of the widely used blockchain frameworks that are used to create blockchain-based DL frameworks.

By responding to five research objectives, the study highlights and assesses the effectiveness of already published works using blockchain and DL. Our findings indicate that IoT applications, such as their use in smart cities and cars, healthcare and cryptocurrency, are the key areas of research. The primary focus of current research is the enhancement of existing systems, with data analysis, storage and sharing via decentralized systems being the main motivation for this integration. Amongst the various frameworks employed, Ethereum and Hyperledger are popular among researchers in the domain of IoT and healthcare, whereas Bitcoin is popular for research on cryptocurrency.

There is a lack of literature that summarizes the state-of-the-art methods incorporating blockchain and DL in popular domains such as healthcare, IoT and cryptocurrency price prediction. We analyze the existing research done in the past five years (2018–2023) to review the issues and emerging trends.