Search results

This paper aims to investigate whether official development assistance (ODA) inflows to developing countries (lower-middle and low income) can cause the symptoms of Dutch disease or not.

This study applies the methodology of dynamic panel data estimation with a one-step system generalized methods of moment (GMM) for the sample of 59 developing countries from 2001 to 2019.

The results indicate that ODA (as a percentage of gross domestic product (GDP)) rises by 1%, the real effective exchange rate (REER) appreciates by 0.252%. This finding reveals that these selected developing countries have faced the symptoms of Dutch disease. The countries with the higher ODA ratio have a higher effect of the Dutch disease, and the managed floating exchange rate regime is the lowest impacted, when compared to the fixed and flexible exchange rate.

The selected countries are recommended to use ODA inflows right and efficiently. These ODA inflows should be invested in productive sectors or support for production rather than in consumption. The managed float exchange rate regime is applied to reduce the symptom of Dutch disease for the selected countries. The good cooperation of monetary and fiscal policies is important to absorb the huge ODA inflow and sterilize the adverse effects of the disease.

The paper contributes to the literature and empirical of the Dutch disease. An adverse effect of the huge ODA inflow to the developing countries appreciated of the real exchange rate and caused the symptom of the dutch disease.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-12-2022-0777

Demand forecasts are a key component of planning efforts and are crucial for managing core operations. This study aims to evaluate the use of several machine learning (ML) algorithms to forecast demand for residential construction in Jordan.

The identification and selection of variables and ML algorithms that are related to the demand for residential construction are indicated using a literature review. Feature selection was done by using a stepwise backward elimination. The developed algorithm’s accuracy has been demonstrated by comparing the ML predictions with real residual values and compared based on the coefficient of determination.

Nine economic indicators were selected to develop the demand models. Elastic-Net showed the highest accuracy of (0.838) versus artificial neural networkwith an accuracy of (0.727), followed by Eureqa with an accuracy of (0.715) and the Extra Trees with an accuracy of (0.703). According to the results of the best-performing model forecast, Jordan’s 2023 first-quarter demand for residential construction is anticipated to rise by 11.5% from the same quarter of the year 2022.

The results of this study extend to the existing body of knowledge through the identification of the most influential variables in the Jordanian residential construction industry. In addition, the models developed will enable users in the fields of construction engineering to make reliable demand forecasts while also assisting in effective financial decision-making.

This study aims to investigate the factors influencing the citrus trade in Indonesia, the effects of tariff and non-tariff policies on the industry and the welfare of producers and consumers.

The research used annual series data from 1991 to 2021 and employed inferential, simulation, and descriptive analyses. The two-stage least squares (2SLS) of 19 simultaneous equations were used to estimate parameters.

The results indicate that free trade policies and restrictions have influenced the citrus industry, leading to a reduction in Indonesian citrus imports, and increased consumer and producer prices. However, eliminating import tariff policies on citrus from China and import restrictions increased producer surplus while decreasing consumer surplus, government revenue, and total welfare. Therefore, trade policies should be combined with non-trade policies such as citrus region development policies and advancing cultivation technology.

This study provides empirical evidence for the Indonesian government to formulate effective citrus trade and development policies. It emphasizes the importance of carefully considering the impact of trade policy on the citrus industry and the need to implement non-trade policies such as citrus zone development policies and advancing cultivation technology to benefit both producers and consumers.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-02-2023-0148

This paper aims to unravel the puzzle that the United Kingdom’s high-quality government accounting and fiscal architecture is associated with low-quality outcomes, including poor productivity growth, high public debt, public services which do not meet citizen expectations and historically high levels of taxation. It contributes to public sector accounting research in the fields of fiscal transparency and governance.

This paper uses Miller and Power’s (2013) economization framework and Dunsire’s (1990) concept of collibration to explain why being a global leader in public sector accounting reform and in fiscal and monetary architecture has not protected the UK from weak governance. The intersection of economization’s roles of accounting with modes of government accounting clarifies the puzzle.

Whereas accruals government accounting contributes to fiscal transparency, this is not a sufficient condition for well-judged policy and its effective application. Collibration is the dominant mechanism for mediation in the fiscally centralized UK, but it has failed to deliver stable outcomes, in part because Parliament is limited in its ability to hold back inappropriate behaviour by the Executive. Subjectivization has disrupted adjudication because governments at all levels resist constraints on their behaviour, with unpredictable and often damaging consequences.

This paper provides insights through the combined lens of economization and modes of government accounting, demonstrating the practical value of this conceptualization. Although some causes for unsatisfactory outcomes are specific to the UK, there are cautions for accounting and fiscal reformers in other countries, such as Member States of the European Union.

The fast fashion industry is one of the most polluting industries. For this reason, the industry should look into new circular business models in order to reduce its material footprint as well as the amount of waste produced. This article focuses on the question of how the sharing economy, as one possible circular business model, can contribute to achieving Sustainable Development Goal 12 (SDG 12) “Ensuring Sustainable Consumption and Production.” After a brief introduction to SDG 12, a short outline of the current development of the sharing economy in the fast fashion sector is given. To develop consumer buying behavior toward environmental sustainability, it is important to understand their motives. Utilitarian and hedonic motives are examined in order to determine to what extent they can positively influence buying intention and thus the acceptance of fashion sharing platforms. The database gathered through a master thesis is used to investigate the specific influence these motives have on buying intention. To increase the acceptance and thus the use of fashion sharing platforms, recommendations for action are developed in the final step of this chapter throughout the five steps of the buying cycle model. Circular business models will play a key role in the context of sustainable transformation in the future. Therefore, it is particularly important to derive concrete recommendations for action based on research in order to get the ecological footprint of environmentally harmful industries – such as the fast fashion industry – under control.

The adoption and usage of information and communication technology (ICT) has introduced transformation in the tourism arena with ICT applications extensively used in tourism industry. In addition to ICT, an advanced infrastructure is essential for the development of tourism industry. Thus, the goal of present research is to probe the impact of ICT and infrastructure on tourism development (TD) in 28 Asian economies using method of moments panel quantile regression (MM-QR) model introduced by Machado and Silva (2019) applied to a panel data from 2008 to 2020. Empirical findings demonstrate that there is an asymmetric non-linear effect of ICT and infrastructure through all quantile range. This indicates that ICT has negative effect on TD in poor countries while positive impact in rich countries. Negative impact in poor countries may be due to higher establishment cost and information technology (IT) productivity paradox. However, results confirm the importance of ICT and infrastructure in endorsing the development of tourism sector in Asian nations by lessening time and money costs and facilitating travelers.

Most Asians are directly or indirectly dependent on agriculture, and most live in rural areas. Since Asia is primarily an agricultural economy, rural tourism and agrotourism are critical in enabling growth. Agrotourism is a term that refers to the fusion of tourism and agriculture. The freshwater turtles (Batagur sp.) are a group of six turtles that once roamed southern Asia's great rivers and estuaries from the Indian Subcontinent to the Indonesian islands. Therefore, this review is to investigate the current state of agrotourism in Batagur sp. conservation and assess the associated challenges and opportunities. This review paper recognized the impacts and benefits for the rural site as an agrotourism industry. Moreover, three initiatives in Batagur sp. conservation programs were also discussed. Agrotourism, with a focus on the conservation of Batagur sp., is a vital driver of economic growth in rural Asian regions. It diversifies rural communities' income sources, enhancing economic stability and resilience.

Calculating an organization's carbon footprint is crucial for assessing and implementing emission reductions. Although Finnish higher education institutions (HEIs) aim for carbon neutrality by 2030, limited research exists on plans to reach a similar target in any country. This paper aims to address the shared and individual challenges Finnish HEIs have with carbon footprint calculations, reductions, resources and offsetting.

A survey was targeted to sustainability experts in all 38 HEIs in Finland to identify key patterns and trends in the focus fields of the study. SWOT analysis was used to classify main strengths, opportunities, weaknesses and threats, based on which a series of policy recommendations was drafted.

Finnish HEIs are committed to carbon footprint tracking (97%, annually by 87%). The lack of standardization and the number of external stakeholders complicate accounting indirect emissions, impeding comparability and reliability. Only 39% had set separate emission reduction targets, suggesting a preference for carbon footprint over other environmental impact indicators. Insufficient monetary and human resources emerged in 23% of institutions, especially those smaller in size. Only 52% had clear offsetting plans, with shared concerns over trust and responsibility.

By including both research universities and universities of applied sciences, the findings provide an unprecedented outlook into the entire Finnish HEI sector. The policy recommendations guide HEIs both locally and globally on how to improve their transparency and scientific integrity, reflect on core successes and weaknesses and how they complete their objectives of education, research and social impact while promoting stronger sustainability.

This chapter examines three common fintech use cases transforming the financial industry. First, the chapter introduces fintech's role in enhancing financial services and promoting financial inclusion, especially through digital platforms. Second, it investigates various fintech applications that support financial institution management by harnessing the power of artificial intelligence (AI) and machine learning (ML). Finally, the chapter explores fintech use cases related to the regulatory environment, including regulatory technology (regtech), blockchain technology, and cryptocurrencies. The insights presented in this chapter cater to researchers and practitioners keen on better understanding fintech's diverse applications in the ever-evolving financial industry landscape.