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This study examines how the introduction of mobile money transfers, while making it efficient and convenient to access funds, has affected rural households’ savings behavior and the banking sector.

This study utilizes Fiji’s most recent agricultural census data to model the agricultural household’s saving decision. The study estimates an probit model to examine rural households' savings behavior. Furthermore, it utilizes time series secondary data to examine how funds transfer has been channeled to rural households in Fiji.

Firstly, the results demonstrate that with the mobile money transfer platform launch, the banking sector has lost substantial money previously used to pass through its system, thus losing service fees and interest income. Furthermore, the findings demonstrate that those using mobile wallet platforms to receive money are more likely not to have a savings account with the bank. Noting the cultural systems and social settings of the native households and the ease of payments via the mobile platform, they tend to spend more on consumption rather than saving, thus making these households more vulnerable during shocks such as natural disasters.

While mobile money transfer is hailed as a revolution, no research has yet picked up the downside to it, that of undermining the very effort by policymakers to get low-income rural households to save. Secondly, this study also highlights how mobile money transfer deprives the banking system of a significant transfer fee income and a source of funds to pool and lend to earn interest income. Furthermore, this study brings to the forefront a dichotomy about how a rural indigenous community sees the welfare and prosperity of their community much differently than what economics textbooks portray.

Whether a human body has a healthy carrying capacity is calculated by body mass index (BMI). The BMI is found by dividing body weight in kilograms by the square of body length. If the person's body weight is more than the heaviness that the body can carry healthily, it is called obesity. Destinations have a specific area, just like a human body. Therefore, any destination whose carrying capacity is exceeded can be called an “obese destination”. This study's primary purpose is to reveal the importance of destination carrying capacity through the concept of obesity.

Content analysis, one of the qualitative research methods, was employed, and graffiti reflecting the feelings of the local people toward tourists were used as data. Graffiti was considered as a social carrying capacity indicator to identify obese destination symptoms. Fifty graffiti obtained from search engines about destinations with obesity problems were analyzed.

The study's findings reveal that anti-tourist graffiti indicates obese destination symptoms. Furthermore, when the content analysis of graffiti is examined, it is seen that the obese destination's local people have intense anger toward tourists. This is a clear manifestation of the destination's health deterioration.

This study, in which the concept of obese destination is used for the first time, suggests that destinations' health may worsen just like people. If destinations with over-tourism are called obese, a more expansive awareness will be created about the destinations' problems. The study suggests that nonecolabel can be used as a mandatory diet tool for obese destinations. Anti-tourist graffiti has been addressed as an obese destination symptom.