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Purpose – The aim of this study is to analyze the effects of macro- and micro-economic variables on the ratio of troubled financing (Non-Performing Financing, NPF).

Design/Methodology/Approach – The method used in this research is the data panel fixed effect with 13 banks and 4 periods of data report (semi-annual report 2014–2015).

Findings – The regression result achieved that variable inflation significantly influences the ratio of NPF. Variable Gross Domestic Product and assets total significantly influence the ratio of NPF too. While the SBI sharia’s variable and Financing to Deposit Ratio did not significantly affect NPF in Syariah’s Unit of Aceh Bank Pembangunan Daerah (BPD) in Indonesia.

Research Limitations/Implications – This study uses panel data which are a combination of time series data and cross-section.

Practical Implications – The policymakers can design a macro-policy carefully and better fiscal policies.

Originality/Value – This research was conducted on the Syariah’s Unit of BPD in Indonesia during the period 2014–2015 and it has not been done before.

The increasing frequency and intensity of the extreme weather events could cause devastating consequences in tourism. Climate change–related extreme weather events and their relation to tourism is an emerging field for education and research. The purpose of this study is to categorize the impact of climate change on tourist destinations with regard to extreme weather-related risks in outdoor recreation and tourism. Managerial implications for policymakers and stakeholders are discussed.

To outline the risks from climate change associated with tourism, this study uses the Prisma analysis for identification, screening, checking for eligibility and finding relevant literature for further categorization.

Based on a thoroughly examination of relevant literature, risks and threats posed by climate change could be categorized into following four areas: reduced experiential value in outdoor winter recreation; reduced value in beach scenery and comfort; land degradation and reduced biodiversity; and reduced value in personal safety and comfort in tourism. It also focuses on the significance of using big data applications in catastrophic disaster management and risk reduction. Recommendations with technology and data analytics to continuously improve the disaster management process in tourism education are provided based on findings of this study.

Primary contributions of this study include the following: providing a summarized overview of the risks associated with climate change in terms of tourist experiential value for educational implications; and revealing the role of data analytics in disaster management in the context of tourism and climate change for tourism education.

This paper aims to identify variables that determine the differing levels of environmental quality on Java and other islands in Indonesia.

Using a quantitative approach, secondary data were sourced from the Central Statistics Agency and the Ministry of Environment and Forestry. The data were obtained through the collection of documentation from 33 provinces in Indonesia. The analytical approach used was discriminant analysis. The research variables are Trade Openness, Foreign Direct Investment (FDI), industry, HDI and population growth.

The variables that distinguish between the levels of environmental quality in Indonesian provinces on the island of Java and on other islands are Industry, HDI, FDI and population growth. The openness variable is not a differentiating variable for environmental quality. The most powerful variable as a differentiator of environmental quality on Java Island and on other islands is the Industry variable.

This study has not classified the quality of the environment based on the Ministry of Environment and Forestry's categories, namely, the very good, good, quite good, poor, very poor and dangerous. For this reason, further research is needed using multiple discriminant analysis (MDA).

Industry is the variable that most strongly distinguishes between levels of environmental quality on Java and other island, while the industrial sector is the largest contributor to gross regional domestic product (GDRP). Government policy to develop green technology is mandatory so that there is no trade-off between industry and environmental quality.

This study is able to identify the differentiating variables of environmental quality in two different groups, on Java and on the other islands of the Indonesian archipelago.

This paper aims to identify key factors for a contextualised Systemic Risk Governance (SRG) framework and subsequently explore how systemic risks can be managed and how local institutional mechanisms can be tweaked to deal with the complex Indonesian risk landscape.

Using a case study from Palu triple-disasters in Central Sulawesi, Indonesia, the authors demonstrate how inland earthquakes in 2018 created cascading secondary hazards, namely tsunamis, liquefactions and landslides, caused unprecedented disasters for the communities and the nation. A qualitative analysis was conducted using the data collected through a long-term observation since 2002.

The authors argue that Indonesia has yet to incorporate an SRG approach in its responses to the Palu triple-disasters. Political will is required to adopt more appropriate risk governance modes that promote the systemic risk paradigm. Change needs to occur incrementally through hybrid governance arrangements ranging from formal/informal methods to self- and horizontal and vertical modes of governance deemed more realistic and feasible. The authors recommend that this be done by focusing on productive transition and local transformation.

There is growing awareness and recognition of the importance of systemic and cascading risks in disaster risk studies. However, there are still gaps between research, policy and practice. The current progress of disaster risk governance is not sufficient to achieve the Sendai Framework for Disaster Risk Reduction (2015–2030) unless there is an effective governing system in place at the local level that allow actors and institutions to simultaneously manage the interplays of multi-hazards, multi-temporal, multi-dimensions of vulnerabilities and residual risks. This paper contributes to these knowledge gaps.