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Investment in food supply chain resilience, as a critical infrastructure, has become necessary for all governments. Disruption of food supply chains can lead to significant economic challenges. Building a resilient supply chain requires resources; however, it is difficult for firms to allocate resources to various resilience strategies. This study allocates the budget to resilient capacity, that is, absorptive, adaptive, and restorative capacity, to minimize supply chain costs and maximize service levels. We developed a novel multi-objective mixed-integer nonlinear programming method for problem formulation. The developed model was converted into an equivalent linear model. We used the Monte Carlo approach to generate the scenarios and the average sample approximation to determine the required scenarios. Finally, the Lexicographic max-min approach solves the model using actual data from a dairy supply chain. The analysis revealed that allocating 50% of the budget to restorative capacity and the remaining to adaptive and absorptive capacity optimizes supply chain performance. This study provides insights for managers to make better decisions with a knowledge-based background, allocate resources to various resilient strategies, and build a more resilient and efficient supply chain. [ABSTRACT FROM AUTHOR]

The problem of applying gender budgeting in the development of public infrastructure and the social sphere is a factor in ensuring gender equality and sustainable development in modern democratic states. The effectiveness of gender budgeting is a component of increasing the availability and quality of services for all citizens. The aim of the study is to analyse the impact of gender budgeting on the development of public infrastructure and the social sphere. The article focuses on the identification of prospects and challenges of its application at the local level. The paper provides a detailed analysis of budgeting practices in Ukraine and the countries of the European Union (EU). The results of the study demonstrate that gender budgeting contributes to increasing the efficiency of budget expenditures and taking into account gender aspects in project planning and implementation. The article defines the level of ensuring gender rights, and the main problems and challenges associated with its implementation. Special attention is paid to the development of recommendations for more effective implementation of gender budgeting in Ukraine and other countries. The practical significance of the study is the identified opportunities for improving gender equality through the optimization of budget processes and making proposals for local authorities and stakeholders. [ABSTRACT FROM AUTHOR]

School infrastructure affects the quality of education and the performance of children and youth. Natural hazards such as earthquakes, hurricanes, floods, and landslides, threaten critical infrastructure such as school facilities. Additionally, problems related to the functionality of these facilities are common in the region, such as an inadequate number of classrooms, poor lighting, and insufficient ventilation, among others. At a national level, the decision-making process to prioritize schools' interventions becomes even more challenging due to limited resources and lack of information. Furthermore, there is a lack of a systematic approach to address the need of improving existing infrastructure taking into consideration limited resources. Considering this, a novel decision-making framework is proposed that prioritizes school infrastructure investment with limited budgets, using clustering procedures, a multi-criteria utility function, and an optimization component. This framework allows better public policy decisions and benefits students in terms of buildings quality with a multi-criteria perspective, improving both safety and functional conditions. The framework is illustrated with a case study applied to the public-school infrastructure in the Dominican Republic. [ABSTRACT FROM AUTHOR]

Bridge agencies are often challenged to develop maintenance programs under given budgets. Numerous studies developed budget-allocation models for maintenance programs during defined planning horizons of multiple fiscal years while totally ignoring the crucial aspect of cash flow. The payment schedules (both timing and amount) for contractors might indicate agencies’ cash needs that exceed the available budgets during certain fiscal years, which create cash flow problems. While numerous finance-based scheduling (FBS) models were developed to manage cash flow for contractors, this function was totally overlooked for portfolio owners. Thus, this research reintroduces the FBS from the perspective of portfolio owners. A FBS model is developed to schedule the activities of the portfolio projects, utilize the schedules to define the payment schedules of projects’ contractors, calculate the agencies’ cash needs during the fiscal years, and utilize the multi-objective optimization algorithms of NSGA-II, SPEA-II, and MOPSO to optimize the projects’ schedules to achieve a balance between the cash needs during the fiscal years and the available budgets. The anticipated extensions in projects’ completion represent the conflicting objectives. Finally, the optimized schedules make the contractors’ payment schedules affordable by the agencies’ budgets, which help to complete projects successfully and achieve the programs’ strategic goals. [ABSTRACT FROM AUTHOR]

Within the global sustainability agenda, companies must align their operations with specific Sustainable Goals (SGs) and develop corresponding budgeting strategies. This paper presents a robust multicriteria decision-making model tailored for a Spanish utility company specializing in water services. The model ensures that financial allocations reflect the company's vision and its interpretation of sustainable development within its service areas. This approach aims to promote objectivity, traceability, and sustainability in decision-making, as a critical component in achieving SGs. The article emphasizes the importance of aligning water companies' budget allocations with SGs, highlighting key indicators for consideration. It provides a practical illustration of how the company's financial allocations were synchronized with SGs using a multicriteria decision-making model. A case study is included, involving a budget allocation of 40 million euros compared across four scenarios with the historical average of budgets from the Past Three Investment Plans (P3IP). The results reveal significant variations in budget allocation across different infrastructure categories, demonstrating the system's robustness, such as a 70% variation in production infrastructures, 27% in transportation, 25% in distribution, and 40% in the remaining areas, depending on the scenario. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Student engagement programs served as catalysts for student development, community building, and active participation in campus life. This research explored the state of student engagement programs within the Supreme Student Government (SSG), focusing on their effectiveness and levels of student participation. Utilizing the 5 Whys methodology, the study identified and analyzed critical challenges and opportunities related to student motivation, program structure, and alignment with student interests. The findings revealed that internal communication breakdowns and budget constraints were significant factors impeding the effectiveness of SSG programs. Student participation was only moderate due to conflicting schedules with classes and insufficient program marketing. The rigid structure of SSG programs and a lengthy approval process further limited their ability to meet student needs. A disconnect between program content and student interests hindered engagement. The research concluded that the root causes of these problems lay in the need for more structured communication channels, a complex approval process, and misalignment with student interests. By addressing these underlying motives, recommendations included enhancing internal communication, allocating funds as efficiently as possible, and creating an inclusive learning environment. These strategies aimed to develop more effective and appealing student engagement programs, ultimately fostering a more active and engaged student body. [ABSTRACT FROM AUTHOR]

A System-of-Systems (SoS) is characterized both by independence and by inter-dependency. This inter-dependency, while allowing an SoS to achieve its objectives, also means that failures can cascade throughout the SoS. An SoS needs to be resilient to deal with the impact of complex internal and external environments. In this paper, we propose a resilience analysis method of an SoS based on a hierarchy structure. Firstly, we establish a hierarchy structure, which is ranked from high to low as capability level, activity level and system level. Then, Bayesian Networks (BNs) and Dynamic Bayesian Networks (DBNs) are used to analyze the resilience of the SoS. A resilience-based system importance metric is introduced, which is used in the budget allocation optimization problem during the development domain of an SoS. This paper proposes a mathematical programming model aimed at optimizing SoS resilience by optimally using budget to the subsystem. The application of the proposed approach is demonstrated using a case study: a Next Generation Air Transportation setting. The study results provide evidence that the proposed inter-dependency analysis based on Bayesian theory and the SoS resilience design approach can assist SoS system engineers in increasing expected SoS resilience during the development domain. [ABSTRACT FROM AUTHOR]

Budget Allocation Problem (BAP) for projects is considered one of the critical risks that necessitate the completion of projects in the shortest possible duration. This aspect is significant in extensive projects such as national endeavors directly impacting people's livelihoods. This research focuses on introducing Sustainable, Robust, Resilient, and Risk-averse Budget Allocation for Projects (S3RBAP). A hybrid robust stochastic optimization approach was employed, incorporating Weighted VaR (WVaR) and the minimum function as risk criteria to ensure the robustness of the objective function. This model is designed to minimize the weighted expected value, WVaR, and the minimum progress function, thereby promoting the 3R and sustainability framework to tackle budget fluctuations and enhance project viability. The case study revolves around the construction of national projects in Iran. Ultimately, the project's required budget was allocated within the budgetary constraints. Sensitivity analysis found that the integration of 3R and sustainability led to a 13.5 % reduction in the progress function compared to scenarios without these principles. Furthermore, increasing the conservatism coefficient to 20 % decreased the progress function to −0.58 %. Reducing the resiliency coefficient had an adverse effect by disrupting the budget allocation process. The computational time is increased gradually with the escalation of problem complexity, while the progress function decreases due to the increased number of projects. The findings demonstrate that using an exponential function promotes risk aversion, whereas a sine function encourages risk-seeking behaviour within this research context.

Over the decades, corporate social responsibility (CSR) has been viewed from various perspectives, including CSR engagement, budget allocation, CSR effectiveness, and the comparison of CSR activities between public and private banks. The purpose of this study is to examine the effectiveness of CSR activities in relation to the influence of bank ownership on CSR engagement, particularly in India. This study was conducted among bank employees and customers. A sample of 675 responses was collected, and multiple regression analysis was performed to analyze the data. The proposed hypotheses in this study were found to be effective. The results indicated that CSR activities related to budget allocation and CSR engagement were effectively undertaken. This study provides new insights for both practitioners and researchers, showing how CSR actions can positively influence outcomes and contribute to the existing body of knowledge. The findings also encourage managers to reconsider their CSR policies to foster pro-social behavior among employees. Consequently, the banking industry remains essential to the economic development of the country, with the Indian banking system consistently maintaining efficiency and supporting real sector activities. [ABSTRACT FROM AUTHOR]

Emergent behavior in repeated collective decisions of minimally intelligent agents—who at each step in time invoke majority rule to choose between a status quo and a random challenge—can manifest through the long-term stationary probability distributions of a Markov chain. We use this known technique to compare two kinds of voting agendas: a zero-intelligence agenda that chooses the challenger uniformly at random and a minimally intelligent agenda that chooses the challenger from the union of the status quo and the set of winning challengers. We use Google Co-Lab's GPU accelerated computing environment to compute stationary distributions for some simple examples from spatial-voting and budget-allocation scenarios. We find that the voting model using the zero-intelligence agenda converges more slowly, but in some cases to better outcomes. [ABSTRACT FROM AUTHOR]

Budget allocation in project risk response is a vital issue in project risk management since it relates to a reasonable utilization of strict project budgets and effective mitigations of the risks that typify projects. This paper presents an integrated method based on an optimization model and fault tree analysis for allocating a risk response budget from a preventive and protective perspective. The proposed method consists of three main steps. The first step is to analyse and calculate risk probabilities and risk losses which involves identifying risk causes that may trigger a risk event to occur using fault tree analysis. It also identifies consequences once the risk event occurs, evaluates the occurrence probabilities of risk causes and expected financial losses of consequences. The second step is to build a relationship between the budget allocated to risk response strategies and the corresponding response effects. The third step is to construct an optimization model aiming at minimizing the total risk cost. We present proofs for the optimal risk response strategy in special cases of the budget allocation model. Furthermore, a detailed computational experiment is performed to gain insights into the three-phased budget allocation model for more general cases. The results show that an optimal risk response budget can be determined and the structure of the risk network has a significant impact on the preferred risk response strategy. [ABSTRACT FROM AUTHOR]

Marketing has proven to be an important asset to every business, and the growth of digital platforms has made it even more crucial, which makes the use of tools to measure and guide advertising strategies almost mandatory. In this context, Marketing Mix Modeling (MMM) has been seen as a powerful tool for backing up this process. However, the sole use of MMM does not help with complex budget allocation decisions, and some of the most used solutions for this modeling lacks on effective or intuitive solutions for this kind of problem. That said, the subject of this article is the proposal of a budget-allocation method consisting of a two-stage differential evolution optimization algorithm that considers the carryover and saturation effects for media channels in the calculations. The model was evaluated on a counterfactual scenario, aiming at the improvement of the Return on Ad Spend over a real scenario of an open database and showed positive results with a significant hypothetical increase in the financial result of the given scenario, proving to be a viable tool for this use. [ABSTRACT FROM AUTHOR]

Sellers on online marketplaces such as Amazon.com use a variety of retail and retail media advertising services to improve their brand performance, including awareness, consideration, and revenue. But how can they measure their progress and drive these metrics? For 122,000 brands, we measure Amazon shoppers' brand awareness, consideration, and purchases and test how they change with ad and retail actions. Furthermore, we compare these brands' past media mix with the recommended allocation based on the model's coefficients. We find that new product launches and upper-funnel retail media advertising are particularly effective for small brands. Medium-sized and large brands benefit most from lower-funnel advertising. For the funnel stages, all three metrics benefit from the number of new reviews, % discount, negative keywords, and geo-reach campaigns. These results are robust across different product categories, but we find notable differences in how upper- and middle-funnel ad products succeed in driving sales. [ABSTRACT FROM AUTHOR]

This study aims to help project-oriented organizations manage their portfolios and arrive at an optimum budget allocation. In this study, the budget allocation process in a portfolio of projects is mathematically formulated. The interactions between the projects as well as the operational and budget constraints are considered. Then, the optimal budget allocation is determined using the particle swarm optimization algorithm. To evaluate the performance of the proposed approach, it is implemented on a portfolio of maintenance projects. In this article, we will explore the application of PSO in portfolio management and how it can help investors make better investment decisions. According to the results, the operational constraints and budget restrictions will significantly affect the optimum budget allocation solution and consequently the revenue of a portfolio. Lack of access to detailed information about the maintenance schedule of dam projects might be a limitation for future application of the proposed approach. It is believed that the proposed approach provides a powerful and efficient tool of optimal budget allocation in portfolio of projects. This research addresses several shortcomings of previous studies for optimal budget allocation. [ABSTRACT FROM AUTHOR]

Since 2015, sustainable development has become the leading goal of all development at the global level. Human development is a crucial aspect of sustainable development planning and strategies. This study analyzes the impact of public policies on the Human Development Index (HDI) in 34 Indonesian provinces from 2015-2020. The study examines budget allocations for education, health, general allocation funds, population, and employment factors. This study employs panel data regression models for different province groups, including all provinces, non-expansion provinces, and expansion provinces. The results indicate that the education budget and population have a positive effect on HDI, while the health budget does not affect HDI in any of the models. However, the general allocation of funds and labor force participation rate have different effects in different models. Therefore, it is suggested that education policies have had more impact than health policies on improving human capital in Indonesia. [ABSTRACT FROM AUTHOR]

It is well known that airport security is an important component of homeland security, since airports are highly vulnerable to terrorist attacks. In order to improve the overall security of the domestic airport network, some work studied the budget allocation of domestic airport network protection. They established a minimax optimization model and designed an exact cutting plane algorithm to solve the problem. However, the exact algorithm can not solve large-scale problems in an acceptable time. Hence, this paper designs a heuristic cutting plane algorithm for solving budget allocation of large-scale domestic airport network protection. Finally, numerical experiments are carried out to demonstrate the feasibility and effectiveness of the new algorithm.

Local governments around the world have implemented various budget participation mechanisms to overcome the drawbacks of representative-directed budget allocation by allowing the public to participate directly in the budget process. How far these budget participation mechanisms influence budget allocation decisions and produce the desired financial outcomes is still under debate. This article explains South Korean local government budget participation practices and reveals that adopting public budget participation mechanisms with greater citizen empowerment and inclusiveness increases expenditures that benefit the majority at the expense of special interest groups. The authors' findings will be helpful for local government managers and policy-makers who are considering adopting budget participation mechanisms. In this article, the authors investigate how participatory budgeting affects local spending. They test their hypothesis on a large N sample in South Korea that budget institutions with a higher participation level (higher empowerment and inclusiveness) increase their spending on the majority of the public and limit spending for the exclusive interests of the few. [ABSTRACT FROM AUTHOR]

In the contemporary business landscape, effective financial management strategies play a pivotal role in determining the success and sustainability of firms. This article delves into the intricate relationship between budget allocation, investment policies, and firm performance. Budget allocation serves as a fundamental aspect of financial management, influencing resource distribution across various organizational functions. The efficacy of budget allocation strategies directly impacts the financial health and operational efficiency of firms. Moreover, investment policies represent critical decisions that shape the allocation of financial resources towards diverse investment avenues. The alignment between investment policies and organizational objectives is imperative for optimizing returns and mitigating risks. By examining the interplay between budget allocation and investment policies, this study aims to elucidate their combined impact on firm performance. Furthermore, firm performance serves as a comprehensive measure of organizational success, encompassing financial indicators, market position, and operational effectiveness. The integration of prudent budget allocation practices and strategic investment policies fosters sustainable growth and enhances competitive advantage, thereby augmenting overall firm performance. Through empirical analysis and theoretical frameworks, this article elucidates the synergistic relationship between budget allocation, investment policies, and firm performance. Insights derived from this study offer valuable implications for financial managers, policymakers, and stakeholders seeking to optimize financial management strategies in dynamic business environments. [ABSTRACT FROM AUTHOR]

Whether organizational performance shapes government resource allocations or not has long been a contentious issue, especially since the 1990s when the New Public Management movement vitalized performance-based budgeting across countries. To contribute to this ongoing debate, this study examines if different levels of organizational performance achievement affect annual budget changes, focusing on Washington State's public programs from 2006 to 2015. This study finds a significant relationship between program performance and budget changes, particularly during fiscally hard times. The findings also suggest the reward mechanism associated with performance-based resource allocation, indicating that higher program performance may lead to budget increases. [ABSTRACT FROM AUTHOR]

This paper explores the multifaceted expectations of Disability Inclusive Budgeting (DIB) among disabled people, emphasizing its significance beyond mere disability mainstreaming within development goals. Informants' insights reveal that DIB carries diverse meanings and potential impacts. Firstly, there is an anticipation that DIB can facilitate the integration of disability considerations across all government programs through appropriate budget allocations. Additionally, the study participants express a broader aspiration: they believe that DIB has the potential to empower them to fulfill their civic responsibilities by positioning them as active agents of development. This, in turn, would enable their meaningful contributions to state-led development initiatives.

A System-of-Systems (SoS) is characterized both by independence and by inter-dependency. This inter-dependency, while allowing an SoS to achieve its objectives, also means that failures can cascade throughout the SoS. An SoS needs to be resilient to deal with the impact of complex internal and external environments. In this paper, we propose a resilience analysis method of an SoS based on a hierarchy structure. Firstly, we establish a hierarchy structure, which is ranked from high to low as capability level, activity level and system level. Then, Bayesian Networks (BNs) and Dynamic Bayesian Networks (DBNs) are used to analyze the resilience of the SoS. A resilience-based system importance metric is introduced, which is used in the budget allocation optimization problem during the development domain of an SoS. This paper proposes a mathematical programming model aimed at optimizing SoS resilience by optimally using budget to the subsystem. The application of the proposed approach is demonstrated using a case study: a Next Generation Air Transportation setting. The study results provide evidence that the proposed inter-dependency analysis based on Bayesian theory and the SoS resilience design approach can assist SoS system engineers in increasing expected SoS resilience during the development domain.

Highways play an important role in economic and social development at both national and regional levels. As a major component of highway infrastructure, pavements require significant funding to be maintained at an acceptable level of service. Allocating the budget for pavement maintenance and rehabilitation (M&R) is a complex decision-making process for a highway agency. This allocation of funding across M&R activities and across districts becomes a challenging process with the presence of multiple stakeholders, constrained budgets, customer satisfaction, agencies' strategic goals, and deteriorating pavement conditions. This paper proposes an extended goal-programming framework for allocating the available pavement M&R budget across multiple management districts of a highway agency over its planning horizon. A case study of applying the proposed model is conducted using data from the Texas Department of Transportation (TxDOT), where five objectives are considered: maximise the proportion of pavement sections with best conditions, minimise the proportion of pavement sections with worst conditions, minimise crash severities through pavement M&R, minimise energy consumption due to M&R activities, and maximise the total lane mile of pavement sections receiving M&R treatments. A sensitivity analysis is also conducted to examine the effect of different parameter values on the results of budget allocation. [ABSTRACT FROM AUTHOR]

A novel approach was developed that combined LP-based row generation with optimization-based sorting to tackle computational challenges posed by budget allocation problems with combinatorial constraints. The proposed approach dynamically generated constraints using row generation and prioritized them using optimization-based sorting to ensure a high-quality solution. Computational experiments and case studies revealed that as the problem size increased, the proposed approach outperformed simplex solutions in terms of solution search time. Specifically, for a problem with 50 projects (N = 50) and 2,251,799,813,685,250 constraints, the proposed approach found a solution in just 1.4 s, while LP failed due to the problem size. The proposed approach demonstrated enhanced computational efficiency and solution quality compared to traditional LP methods. [ABSTRACT FROM AUTHOR]

Copyright of GeSec: Revista de Gestao e Secretariado is the property of Sindicato das Secretarias e Secretarios do Estado de Sao Paulo (SINSESP) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

AbstractThe United Nations’ seventh Sustainable Development Goal (SDG) calls for clean and affordable energy to boost social mobility, especially in disadvantaged rural communities. Regional off-grid budget-allocation planning for rural electrification is traditionally performed following a minimum energy-cost paradigm. However, such a planning paradigm has had little impact on communities’ development. This study proposes a human-centered approach as an alternative planning paradigm. In this regard, we outline a bi-objective optimization model that evaluates the potential contributions of different budget-allocation strategies on energy costs and rural communities’ human development. The model is applied to the Colombian Pacific Coast, an impoverished region with several communities with various unmet human needs including education, nutrition, and health. Our results indicate that when budget-allocation decisions are made by the national government following the energy cost-minimization paradigm only a few communities benefit, leaving many with poor energy access for potential future human development. However, if the maximization of the Human Development Index (HDI) is employed as a planning paradigm the most disadvantaged subregions improve their energy service for a marginal cost, increasing their chances for potential improvements in human development. The results also suggest that the current off-grid electrification budget provided by the national government is not enough to improve the region’s chances of advancing its HDI level from low (HDI < 0.55) to medium (HDI ≥ 0.55), but doubling the budget would do so. Thus, this study contributes to the energy-sustainability literature by proposing a new planning paradigm for regional off-grid electrification.

The European context calls for strategic decisions to streamline, rationalize and improve the performance of pre-university education by re-evaluating its internal structures, especially the human resources involved in the activity. Changes in structure and function find their ultimate purpose, in terms of optimization and specialization, only when they are linked to the diversity of human factors. The rationale of Romanian educational policies is articulated in the context of developments at the European level and within European states in the last two decades. The considerations in question are based on issues related to changes in the operating environment, whether at international, global, regional, continental or domestic levels: national, regional and local. The presence of the international dimension can be felt by including the United States and Asian countries in the comparative analysis. By coordinating education systems within a common educational framework, in order to obtain the best educational practices from each EU Member State to form a system, it is possible to integrate European programmes between peoples with different histories and cultural values.

Chain‐form crime partnerships and intelligence sharing by national authorities to detect cross‐border partners create multiple externalities in the combat against transnational crimes and illicit trafficking. Cooperative enforcements that minimize global harms prioritize the country with lower intelligence production and/or superior detection capability. In equilibrium, as in practice, national enforcements are underbudgeted and might prioritize the wrong side – predominantly the high‐budget, high‐harm country. Governments might not share intelligence out of fear of importing enforcement burden, and harmonizing criminal sanctions alone might not be effective. Shocks on crime deterrence in a target country are first absorbed by source countries, implying weaker horizontal crime transfer effects than projected. [ABSTRACT FROM AUTHOR]

Myanmar has implemented budget reforms to decentralize its budgeting processes, and this study intends to investigate how those reforms have affected its allocation patterns based on budget incrementalism and punctuated equilibrium theory. We empirically analyzed the government's spending in seven sectors over 19 years. We found that political and institutional changes have different effects on different sectors. The sectors that the government paid attention to and set as highly prioritized policies showed more punctuation. After the reform, the government paid more attention to capital budgets to achieve its political goals, leading to more punctuation in the capital budget. We also examined the directions and frequencies of budget punctuation before and after the reform by extending the punctuated equilibrium theory literature based on both corrective and trend models. Different budget punctuation patterns were observed with different frequencies across sectors due to the unique characteristics of each sector and changing policy priorities over time. [ABSTRACT FROM AUTHOR]

This paper introduces a newly developed decision support model for allocating a budget for bridge maintenance. The model is built based on capturing the experts' knowledge for the prioritization of criteria for selecting a bridge maintenance plan. A literature review and interviews with a group of nine local experts were carried out to identify the criteria for bridge prioritization for maintenance. A questionnaire survey was then designed and administered, utilizing multi-criteria decision-making techniques through face-to-face meetings with local bridge maintenance managers to determine the weights of the identified criteria and develop the utility curves for each criterion. The developed model consists of four major modules: (1) bridge ranking module; (2) prioritization module of bridge structural elements; (3) optimization-based simulation module; and (4) the outputs module. The model was validated in a hypothetical network of four bridges. The validation reveals that the model can assist bridge maintenance managers in setting a bridge maintenance plan, with a high level of confidence using efficient frontier analysis technique. Utilizing frontier analysis enables comparisons of mean costs of different bridge maintenance plans against different levels of risk to enable decision-makers to make informed decisions. The result of this study indicated that bridge structural condition was the most important criterion amongst all the criteria influencing the decision of bridge prioritization for maintenance, followed by traffic and bridge location. Moreover, bridge deck and parapet, followed by bearing pads, were found to be the most important of the bridge's structural elements. [ABSTRACT FROM AUTHOR]

This study introduces a multicriteria tradeoff analysis method based on Dempster-Shafer (DS) theory in conjunction with the Mixed Aggregation by Comprehensive Normalization Technique (MACONT) and the e-STEP method, termed DSM-eSTEP method, to assist transportation agencies in making optimal investment decisions under alternative budget allocation scenarios. Specifically, the DS evidence theory is employed to develop belief functions from preferences of multiple transportation performance criteria revealed by transportation decision-makers. The belief functions are transformed to probability functions using the pignistic transformation technique, leading to a set of initial weights that could reflect the priorities of decision-makers on the performance criteria. To enhance the robustness of relative weights assigned, the MACONT technique and the entropy measure are employed to derive refined weights via context-dependent adjustments. Having established the refined weights of transportation performance measures, the multi-objective budget allocation formulation according to various tradeoff scenarios could be converted to a linear programming model readily solvable for optimality. An empirical study is conducted for optimal budget allocation of 233 highway bridge and pavement preservation projects proposed for a U.S. state-maintained urban Interstate highway network. Cross comparisons of budget allocation results are made between the proposed method and the widely used compromise programming (CP) method. It shows that the proposed DSM-eSTEP method could generate efficient investment outcomes and slightly outperform the CP method.

In Africa, nearly 46% of all mortality will be attributed to non-communicable diseases (NCDs) by 2030. While the cost of inaction far exceeds the cost of action against NCDs, global funding for the prevention and control of NCDs is minimal. The objective of this was to explore the Ministry of Health budget allocations for NCDs from 2010 to 2020 as well as the effect of the terrorism crisis on these allocations. The methodology was based on the budget tracking tool developed by the Scaling Up Nutrition Movement. Twenty-nine budget lines related to the prevention and/or control of NCDs have been identified. About 29.9 million USD were allocated to the fight against NCDs with an absorption rate of more than 98%.There is an upward trend of allocated budget characterized by an exponential increase from the development of the national integrated strategic plan for the fight against NCDs (2016–2020). In 2017, an increase of 184% compared to 2016 was observed. However, the efforts were challenged by the emergence of the terrorist threat which triggered in January 2016, leading to a drastic reduction in allocations for NCDs in favor likely of defense and security priorities as well as addressing the needs of internally displaced persons. A trend analysis suggests that the NCDs budget significantly decrease as the country global terrorist index increase. Further analysis is needed to better understand the implication on NCD incidence, and identify advocacy opportunities for mitigating the negative impact of the terrorist treat on NCDs and other development issues.

Background and Research Aims: The conservation of Bengal tigers is a global concern due to their exponential decline in population around the world. In 2010, all Tiger Range Countries (TRCs) committed to double their tiger population by 2022. As a member of the TRCs, Bangladesh has launched and conducted many tiger conservation projects with a heavy financial investment. However, the tiger population has not increased in the country. Therefore, there is an urgent need to investigate why those funded projects' outcomes were unsatisfactory compared to neighboring countries such as India and Nepal. Methods: This review was conducted purely based on previous archival tiger conservation related documents. Six specific tiger conservation projects implemented in Bangladesh, India, and Nepal were selected to investigate the effectiveness of tiger conservation in Bangladesh. Allocated fund distributions were segmented into five groups: capacity building, planning policy and reports, infrastructural development, tiger–human conflict (THC) reduction, and in-field actions to increase the tiger population. Results: The analysis showed that India and Nepal spent most of their budget on in-field activities and least on planning. A moderate amount was spent on THC reduction, capacity building, and infrastructural development. In contrast, Bangladesh spent the majority of its fund on planning. India and Nepal also developed a sustainable funding mechanism to reduce their dependency on donor agencies, which was absent in the case of Bangladesh. Conclusion: It is recommended that future tiger conservation initiatives in Bangladesh should address more in-field action, such as patrolling to stop poaching and the illegal extraction of resources, sustainable long-term alternative income generation activities, and health issues such as identifying diseases, inbreeding effects, and captive breeding. Implications for Conservation: Bangladesh needs to develop a sustainable long-term funding mechanism for in-field actions for tiger protection. [ABSTRACT FROM AUTHOR]

This article presents evidence that high-ranking public officials in the Ministry of Strategy and Finance in South Korea affect local budget allocation. Applying a regression model on a uniquely constructed panel dataset, I found that the growth rate of the per-capita National Subsidy, which is a subcomponent of the national budget susceptible to discretionary behaviors, increases approximately 7 percent in the hometowns of high-ranking bureaucrats. To validate these findings and address causality, I conducted a battery of auxiliary robustness checks, which yielded confirmatory results. This study also found that enhancing transparency in the budget allocation system can alleviate concerns about bureaucratic hometown favoritism, providing suggestive evidence of bureaucrats' rent-seeking behaviors without government transparency. [ABSTRACT FROM AUTHOR]

This study developed an engineering consulting project budget allocation and control model based on baseline productivity of staff of various positions for each work item. The research model included two modules, namely the staff budget and time budget. The staff budget module determined the working hours and budgets of staff of various positions for each work item of the new project. The time budget module is to plan an implementation period and budget allocation for each work item of the new project. Four findings were inferred from the obtained results. First, the control chart method was an appropriate method for determining the baseline productivity of engineering consulting project. Second, the root mean square error (RMSE) of the staff budget module was 1.99 – 2.81 NT$/m, and the budget allocation results obtained with this module were similar to those produced by experienced project managers. Third, the RMSE of the time budget module was 2.23%, which is more accurate than are existing practical methods. Fourth, the accuracy of the budget stress index proposed by this study was 81.48%–84.00%. This index can assist project managers in determining projects, work items, and cost control benchmarks for staff working at various positions. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Engineering (17264073) is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Road freight transportation sustainability is gaining increasing importance due to an ever-increasing freight movement, globalisation and operational flexibility. The transport managers across the globe are finding it difficult to manage the increasing risks in its operation and implementation of risk-mitigation strategies under economical sustainability. However, very few literatures have examined the impact of sustainable risk management practices on road freight transportation. Our study addresses this important gap in the literature by proposing an integrated fuzzy failure mode and effects analysis (FMEA) approach in the selection of risk-mitigation strategy on the trucking industry. Our findings direct to the managers that risk-mitigation strategies must be selected considering the criticality of risks along with the limited budget. In addition, we find that considering subjective evaluations of expert's judgment and cost benefit justification gives a convincing outcome while calculating of risk-mitigation number in FMEA approach. Proposed approach provides supportive guidelines to the manager to improve the decision-making process. [ABSTRACT FROM AUTHOR]

AbstractTo facilitate forest management as part of climate change mitigation and adaptation, the Forest Environment Transfer Tax (FETT) was introduced in Japan in 2019, representing a form of payment for ecosystem services. In this study, we focused on the introduction of the tax and the status of its use based on an analysis covering Japan’s 47 prefectures. This involved reviewing policy processes related to FETT and conducting a survey among relevant prefectural officers to identify how FETT is being used, with a focus on plans, policies, and systems related to forest data development and exchanges. The proportions of both total and FETT budgets used for forest data development were significant. Several prefectures are improving forest-related data in a two-way manner by coordinating with municipalities. Correlation analysis revealed that prefectures with greater proportions of privately owned forests allocated more budget to forest data development, which is in line with the FETT’s intended purpose. This result suggests that the absolute size of such forestlands is less important, but that the proportion of privately owned forests carries political and social weight that could be a critical factor in budget allocation.

The municipal street network acts as a multifunctional asset by providing people, vehicles and public services with a well-functioning infrastructure. To keep it in good condition, optimal maintenance measures are required which would result in an efficient use of taxpayers’ money. This paper investigates the street network deterioration processes and the management practices that the municipal administrations have applied in Sweden. The study is based on a survey with Swedish municipalities using questionnaires and complementary interviews. The answers provide insight into a wide range of common pavement distresses and deterioration factors, along with pavement management practices. The study identifies that potholes, surface unevenness and alligator cracking are the most cited challenges, while pavement ageing, heavy traffic and patches are the most noted causes. Similarly, the cold climate and population density are influential factors in pavement deterioration. Allocation of the maintenance and rehabilitation and reconstruction budget is higher in the northern part of the country as well as in densely populated municipalities. Condition data collection and use of commercial Pavement Management Systems (PMS) are limited. Addressing the challenges effectively may be possible through the enhancement of the budget, feasible/clear guidelines from municipal councils/politicians, and reducing the gap between street network administrations and utility service providers.

Brainstorming has been a common approach in many industries where the result is not always accurate, especially when procuring automobile spare parts. This approach was replaced with a scientific and optimized method that is highly reliable, hence the decision to optimize the inventory inflation budget based on spare parts and miscellaneous costs of the typical automobile industry. Some factors required to achieve this goal were investigated. Through this investigation, spare parts (consumables and non-consumables) were found to be mostly used in Innoson Vehicle Manufacturing (IVM), Nigeria but incorporated miscellaneous costs to augment the cost of spare parts. The inflation rate was considered first due to the market's price increase. Different types of vehicles were used to implement the Non-preemptive goal programming model and to predict the cost of procurement of the spare parts and miscellaneous and the profit for the current year. The result proved that the solution did not fully achieve the goals since the objective function is not equal to zero, but deviations for going below the profit goal and above the cost of procurement goal were significantly minimized.

The need for a study of project portfolio optimization in pharmaceutical R&D has become all the more urgent with the outbreak of COVID-19. This study examines a new model for optimizing R&D project portfolios under a decentralized decision-making structure in a pharmaceutical holding company. Specifically, two levels of decision makers hierarchically decide on budget allocation and project portfolio selection-scheduling to maximize their profit, and we formulate the problem as a bi-level multi-follower mixed-integer optimization model. At the upper level, the investment company has complete knowledge of the subsidiaries' response, acts first, and decides on the best budget allocation. At the lower level, each subsidiary responds to the allocated budget and decides on its portfolio scheduling. Since the lower level represents several mixed-integer programming problems, solving the resulting bi-level model is challenging. Therefore, we propose an efficient hybrid solution approach based on parametric optimization and convert the bi-level model into a single-level mixed-integer model. To validate it, we solve a case and discuss the optimal strategy of each actor. The experimental results show that the planned project portfolio for each subsidiary of the holding company is drastically affected by the allocated budget and its decisions. [ABSTRACT FROM AUTHOR]

This paper presents an experience-oriented model of budget allocation and cost control for engineering consulting projects. The proposed model comprised two modules: a work item module and a work duration module. Regarding the work item module, a project manager employed the analytic hierarchy process (AHP) to determine the budget percentage allocated to each work item. Regarding the work duration module, this study compiled all S-curves appearing in each budget percentage range in past projects. A project manager then selected the optimal curve shape for each work item to determine the daily budget allocation and cost control limits throughout the work duration of each work item. Testing revealed that the proposed model facilitates project managers' budget allocation decision-making, determines budget control limits for the overall project and for each work item and identifies work items that may be out of control at an early stage. [ABSTRACT FROM AUTHOR]

We develop and analyze a dynamic finite-budget allocation scheme for stratified sampling for general purposes on the unit hypercube with adaptive variance reduction applied by strata. By batching the parallelized tasks, the proposed scheme succeeds to update the budget allocation only occasionally yet effectively takes into account the decreasing stratum variances while simultaneously estimating the stratum means and updating the variance reduction parameter s throughout. The scheme is designed to accommodate a variety of existing algorithms for the parameter search procedure. In particular, when stochastic approximation is employed, we derive optimal stratum batchwise learning rates in accordance with the adjusted batch size along the way. Numerical results are provided to support the theoretical findings and to illustrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

A novel approach was developed that combined LP-based row generation with optimization-based sorting to tackle computational challenges posed by budget allocation problems with combinatorial constraints. The proposed approach dynamically generated constraints using row generation and prioritized them using optimization-based sorting to ensure a high-quality solution. Computational experiments and case studies revealed that as the problem size increased, the proposed approach outperformed simplex solutions in terms of solution search time. Specifically, for a problem with 50 projects (N = 50) and 2,251,799,813,685,250 constraints, the proposed approach found a solution in just 1.4 s, while LP failed due to the problem size. The proposed approach demonstrated enhanced computational efficiency and solution quality compared to traditional LP methods.