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Governments in developing countries manage their considerable state assets for public service delivery directly. In Indonesia, the Directorate of State Asset Management responsible for developing the national strategy for state asset optimization requires the determination of key elements and prioritization tools. The purpose of this paper is to show that a simple calculation using the combination of the balanced scorecard (BCS) and analytical hierarchy process (AHP) will help in the prioritization of strategy development.

A questionnaire survey of 131 multistakeholder respondents to identify the most important key elements and the best alternative for asset optimization was done in this study.

The respondents agree on the most important key elements, and that the best alternative for asset optimization is the efficient maintenance of assets. Competitive human resources comprise the recommended second key element, and that improvements in asset performance and value will improve public service as the second-highest alternative. This study also shows the importance of the integration of asset optimization in existing government strategic instruments supported by a comprehensive data set related to public assets and their performance.

This paper provides a new contribution to integrating asset optimization strategies as the core of the organization’s performance and prioritization strategies. Additional BSC perspectives are suggested, with the inclusion of AHP for prioritization. In addition, this study includes the opinions of all the stakeholders, from external users to the central management. The flexibility of the tools to adapt to the existing strategic framework will allow their application by different agencies and in different countries.

School infrastructure is one of critical factors that significantly contribute to the educational outcomes, and therefore, maintaining the high quality of school infrastructure becomes of critical importance. Due to the ageing of school assets over time in combination with budget constraint and rapid growth of student enrolment, many public schools are currently struggling to maintain the required standard for long term. However, to date, the goal of providing the best maintenance practices to public schools has not been achieved.

The present study focuses on studying the balance between the asset and maintenance management strategies and the funding model through conducting state-of-the-art literature review and qualitative analysis in the context of public schools in Australia and other developed countries around the world. Review of journal articles, different government reports and other available resources were used to collect and analyse the data in this study.

As part of this review, significant under investment in maintenance and asset renewals were identified as main challenges in asset management in public school facilities. Although different maintenance strategies were used in school infrastructure, adequate funding, adequate robust asset management plans (AMPs) and the involvement of private sectors have been identified as the key factors that govern the success in school infrastructure maintenance. It also shows that funding of approximately 2–3% of asset replacement value (ARV) on school infrastructure is required to maintain school facilities for long-term. Further, the procurement methods such as public private partnership including private finance initiatives (PFIs) have shown great improvements in maintenance process in school infrastructure.

The study provides a review of different AMPs and funding models in school infrastructure and their efficiencies and shortcoming in detail. Different states and countries use different maintenance models, and challenges associated with each model were also discussed. Further this study also provides some conclusive evidence for better maintenance performance for school buildings.

This chapter provides an overview of the potential use of Intelligent Transport Systems (ITS) and associated artificial intelligence (AI) techniques in the land transport sector in an attempt to achieve related United Nations Sustainable Development Goals (SDGs) targets. ITS applications that have now been extensively tested worldwide and have become part of the everyday transport toolkit available to practitioners have been discussed. AI techniques applied successfully in specific ITS applications such as automatic traffic control systems, real-time image processing, automatic incident detection, safety management, road condition assessment, asset management and traffic enforcement systems have been identified. These methods have helped to provide traffic engineers and transport planners with novel ways to improve safety, mobility, accessibility and efficiency in the sector and thus move closer to achieving the various SDG targets pertaining to transportation.

Over the years, public sector reforms in emerging economies have focused on improving national budget systems and financial management practices to promote sustainable development. In the context of the COVID-19 crisis, this article examines whether the strength or effectiveness of national budget systems and related financial management practices moderates the impact of fiscal policy measures on economic recovery and resilience.

The article uses bivariate correlations and difference-in-difference analyses to examine the relationship between budget system effectiveness, government stimulus measures and forecasts of economic recovery and resilience. The analysis uses data from the Public Expenditure and Financial Accountability (PEFA) program, International Monetary Fund (IMF) and World Bank.

The article finds that estimates of economic recovery and resilience are higher in countries with more reliable budget processes and more transparent public finances. Also, the strength or effectiveness of the budget system before the pandemic appears to moderate the impact of government stimulus measures on economic recovery and resilience over a medium-term forecast horizon.

This is a prospective analysis based on economic forecasts from the IMF, which are subject to change in the coming years. In addition, the analysis uses subjective budget system indicators, which present measurement challenges that often influence this area of research. Better comparative data in the future, for example, large administrative datasets, will enable researchers to explore these issues with less estimation bias.

The findings are relevant for policymakers and budget officials in developing countries in Africa who are engaged in plans to improve national budget systems and enhance resilience to crises, such as the COVID-19-induced economic crisis. The findings also have implications for developing countries beyond Africa with similar economic and fiscal conditions.

The findings have implications for economic and budgetary planning for the social sector as well as the efficient delivery of public services in developing countries. Public managers have a critical role to play in adapting national budget systems and financial management reforms within complex and evolving economic circumstances even after the coronavirus pandemic.

The authors use novel and latest data on country responses to the COVID-19 pandemic as well as medium-term economic forecasts to examine the relationship between national budget systems and post-pandemic economic recovery and resilience in the African context. Previous research has only addressed these issues in the context of industrialized countries, and a limited number of empirical studies examine these relationships. The findings also have significant value for policymakers outside Africa who are facing similar challenges related to the coronavirus pandemic.

The objective of this study is to examine the perceived usefulness of accrual accounting-based financial information for accountability and for supporting decision-making in public sector organisations.

A questionnaire survey adapted from Kober et al. (2010) was used to survey Malaysian Federal Government accountants to ascertain their views on the usefulness of accrual accounting information across 12 situations regarding accountability and decision-making. Mean scores and mean score ranking were computed on a total of 165 usable responses received. The independent t-test was conducted to investigate the differences in the perception between “accountants with” and the “accountants without” prior work experience in the private sector.

The study provides evidence that Malaysian Federal Government accountants consider accrual accounting information as very useful for decision-making. The three most important decision-usefulness indicators in the survey are “To assist in managing the department’s assets and liabilities”, “To assess cash flow needs of a department” and “For departmental resource allocation decisions”. The least useful accrual accounting information as perceived by the Malaysian public sector accountants is “To assist in discharging the department’s accountability obligations”.

The study provides valuable insights into the extent to which accrual accounting information is considered useful for accountability and decision-making, lending support to the Malaysian Government’s reform agenda of moving towards using accrual accounting in public sector organisations at the federal level.

The aim of the study is to review the extant literature on International Public Sector Accounting Standards (IPSAS) adoption in emerging economies (EEs) and low-income countries (LICs) (“what do we know?”), and to propose an agenda for future research (“what do we need to know?”).

An analytical framework that builds on diffusion theory is developed. The authors follow the “PRISMA Flow Diagram” to reduce a total of 427 articles from four databases to a final sample of 41 articles. These studies are examined, aided by the analytical framework.

The authors find that IPSASs are a relevant issue for EEs/LICs. Overall, existing research is often explorative. The authors discover that the majority of articles rely on secondary data collection. While two-thirds of the studies perform a content analysis of pre-existing material, about one-fifth of the articles each collect primary data through means of interviews and questionnaires. The findings offer a holistic understanding of where and at what stages IPSAS reforms stand in EEs/LICs, and what factors influence the progression of reforms to the next stage of diffusion.

The authors outline a number of avenues for further research after discussing the dominating trends and structuring the literature based on our analytical framework. These stem from looking at the blank spots and an identified need to contextualise IPSASs adoption in EEs/LICs.

This chapter introduces the concept of financial market and highlights the role of e-payment systems in the financial market by focusing on the keywords of financial innovation, e-payment and sustainability.

The primary aim of this paper is to concurrently use the data types to enhance econometric analysis in the housing market in developing countries, particularly Namibia.

Scholarly discussions on econometric analysis in the housing market in sub-Saharan Africa suggest that the inadequacy of time series data has impeded studies of such nature in the region. Hence, this paper aims to comparatively analyse the impact of economic fundamentals on house prices in Namibia using real and interpolated data from 1990 to 2021 supported by the ARDL model.

It was discovered that in all the three types of data house prices were affected by fundamentals except real GDP in the long term. It was also noted that there were not much significant variations between the real data and the interpolated data frequencies. However, the results of the annual data and the semi-annual interpolated data were more analogously comparable to the quarterly interpolated data

It is suggested that the adoption of interpolated data frequency type should be based on the statistical significance of the result. In addition, the need to monitor the nexus of the housing market and fundamentals is necessary for stable and sustainable housing market for enhanced policy direction and prudent property investment decision.

The study pioneer to concurrently use the data types to enhance econometric analysis in the housing market in developing countries.