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High numbers of housing backlogs as well as inadequate housing for low-income are one of the Indonesian government’s major concerns, especially in urban areas where the price of house is high. This study aims to identify low-income communities’ preferences on house ownership status, renting or buying and house provider, public or private, in Jakarta and surrounding areas.

This study adapts Longley multistage choice model in the Indonesian context to analyze people’s preferences in choosing a place to live in urban areas. This study analyzes two choices of models which are aspects of homeownership (buying or renting) and aspects of residential types (private or public).

Using data collected through a survey of 1,000 households in greater Jakarta (Jakarta, Bogor, Depok, Tangerang, and Bekasi), this study found that households which have fixed employment status, an older age, a larger number of family members, higher level of education and literacy in housing policy, accessible house location and more affordable to own house have a higher probability to choose to own a house. In addition, education level, age, and family size are major determinants of a household’s decision to occupy a public house rather than a private house. The findings provide basic input to government development programs in designing housing policy for low-income people.

There are only a few studies related to house-ownership preferences in low-income people, especially in developing countries, including Indonesia. This study contributes to the housing studies literature by strengthening empirical evidence from developing countries that have large populations and mostly live in urban areas.

Fish quarantine is a measure to prevent the entry and spread of quarantine fish pests and diseases abroad and from one area to another within Indonesia's territory. Based on these backgrounds, this study aims to identify the knowledge, knowledge management (KM) processes and knowledge management system (KMS) priority needs for quarantine fish and other fishery products measures (QMFFP) and then develop a classification model and web-based decision support system (DSS) for QMFFP decisions.

This research methodology uses combination approaches, namely, contingency factor analysis (CFA), the cross-industry standard process for data mining (CRISP-DM) and knowledge management system development life cycle (KMSDLC). The CFA for KM solution design is performed by identifying KM processes and KMS priorities. The CRISP-DM for decision classification model is done by using a decision tree algorithm. The KMSDLC is used to develop a web-based DSS.

The highest priority requirements of KM technology for QMFFP are data mining and DSS with predictive features. The main finding of this study is to show that web-based DSS (functions and outputs) can support and accelerate QMFFP decisions by regulations and field practice needs. The DSS was developed using the CTree algorithm model, which has six main attributes and eight rules.

This study proposes a novel comprehensive framework for developing DSS (combination of CFA, CRISP-DM and KMSDLC), a novel classification model resulting from comparing two decision tree algorithms and a novel web-based DSS for QMFFP.

The paper examines how individuals can be susceptible to payment biases in the context of digital payment behavior by utilizing the concept of mental accounting. Furthermore, the paper investigates the moderating effects of Digital Financial Literacy (DFL) on the relationship between payment methods and spending behavior.

The study employs a survey-based approach to collect data from 503 individuals who use digital payment methods, utilizing purposive sampling from Pakistan. The collected data is analyzed using Smart-PLS 4 software to assess the direct impact of payment methods on spending behavior and the moderating influence of DFL.

The research findings demonstrate that both digital and cash payments significantly affect spending behavior. However, digital payments have a more substantial impact on spending behavior compared to cash payments. The findings also show that DFL significantly positively moderates individual spending. The study validates the mental accounting perspective by evaluating the direct impact of payment methods on consumers' spending behavior.

The findings have practical implications for policymakers, financial institutions, and educators. Policymakers can leverage the insights to design effective strategies that promote responsible spending behavior and enhance the adoption of digital payment methods. Financial institutions can design user-friendly platforms that cater to users' spending preferences, while educators can develop programs to enhance Digital Financial Literacy (DFL) among the public.

This study’s social implications lie in its potential to contribute to individuals' financial well-being by promoting responsible spending through digital payment methods. Enhanced financial literacy and informed spending decisions can lead to better financial management and ultimately contribute to societal financial stability.

The study enriches the understanding of mental accounting, shedding light on how overspending behavior can manifest through digital payment channels. In addition, this research practically provides valuable insights into enhancing the adoption and financial literacy of digital payments among the public.