E-commerce development in Indonesia has been increasing since more online shops are established. The development of e-commerce triggers the use of e-payment as a payment instrument in online shops. XYZ company as one of the payment solution provider in Indonesia developed an electronic money product named M e-money. By the end of 2014, M e-money users had only reached the number of 1776 while the number of users targeted in the business plan was 142616. This research is intended to identify the barriers and challenges XYZ company faces in the implementation of M e-money. Data was collected through questionairres and interviews. The survey respondents consisted of 125 M e-money users where 93 of the respondents have used M e-money, and 32 of the respondents have never used M e-money. The qualitative data was collected through interviews to the M e-money team in XYZ company. Interviews were also conducted to 9 users of M e-money. The research concludes barriers and challenges faced by XYZ company in the implementation of M e-money. The barriers faced by the M e-money users are the limitation of merchants, limitation of access method, limitation of transaction channel, the cost of transaction, other e-money products existed, and socio-cultural factor. Barriers faced by the management are the lack of experience in B2C business and the difficulty of acquiring new M e-money users. These barriers leads to challenges faced by the company. The challenges faced by the company in the implementation of M e-money are the high competition among similar products, the influence of substitute products, and high expectation from users to have a safe, convenience, and trusted e-money services.

The recent advancement of agent-based modeling is characterized by higher demands on the parameterization, evaluation and documentation of these computationally expensive models. Accordingly, there is also a growing request for "easy to go" applications just mimicking the input-output behavior of such models. Metamodels are being increasingly used for these tasks. In this paper, we provide an overview of common metamodel types and the purposes of their usage in an agent-based modeling context. To guide modelers in the selection and application of metamodels for their own needs, we further assessed their implementation effort and performance. We performed a literature research in January using four di erent databases. Five di erent terms paraphrasing metamodels (approximation, emulator, meta-model, metamodel and surrogate) were used to capture the whole range of relevant literature in all disciplines. All metamodel applications found were then categorized into specific metamodel types and rated by di erent junior and senior researches from varying disciplines (including forest sciences, landscape ecology, or economics) regarding the implementation e ort and performance. Specifically, we captured the metamodel performance according to (i) the consideration of uncertainties, (ii) the suitability assessment provided by the authors for the particular purpose, and (iii) the number of valuation criteria provided for suitability assessment. We selected distinct metamodel applications from studies published in peer-reviewed journals from to . These were used for the sensitivity analysis, calibration and upscaling of agent-based models, as well to mimic their prediction for di erent scenarios. This review provides information about the most applicable metamodel types for each purpose and forms a first guidance for the implementation and validation of metamodels for agent-based models.

The increased frequency and spread of tropical peat fires over the last two decades have attracted global attention because they cause significant environmental and health impacts at local to global scales. To understand the relative importance of key factors controlling tropical peatland burning events, we developed PeatFire, an agent-based model simulating the interaction between human-induced ignitions, fire and peat characteristics. The model describes (1) above- and belowground fires, which spread independently but interact with each other; (2) above- and belowground biomass; and (3) the watertable determining peat dryness and susceptibility to fire. We applied PeatFire to a region in South Sumatra that has experienced profound natural rainforest loss due to peat fires. Sensitivity analysis of the model suggests that fire sizes depend mostly on watertable depth, peat-dry-index and number of dry days before ignition. Using pattern-oriented modelling, these factors were parameterised so that the model output matches spatiotemporal fire patterns observed in the study region in 2015. Our results emphasise the risk of a sudden shift from moderate fire occurrence to complete burning and highlight the importance of local context to peatland regulation, which should consider both biophysical and socioeconomic factors and strategies for peatland fire management.

The occurrence of fires has frequently been used to highlight environmental hazards at regional and global scale, and as a proxy for the effectiveness of protected areas. In contrast, the mechanism behind wildfire dynamics in tropical peat land protected areas had been poorly addressed thus far. Our study provides a novel application of assessing fire patterns from a tropical peatland protected area and surrounding landscape. We investigated the importance of both climatic factors (top-down mechanism) and human interventions (bottom-up mechanism) on fire occurrences through analyzing 15-year (2001 -2015) LANDSAT and MODIS images of the Padang Sugihan Wildlife Reserve (PSWR). Fire density along side road and canal construction were analyzed jointly together with the monthly and annual precipitation, and evidences of climatic anomalies. The reserve was effective in limiting fire occurrences from surrounding landscapes only in wet years. We revealed that peat fire patterns in the protected area and the landscape matrix emerged beyond climatic factors, and the distance from canal system could explain the fire occurrences. Our results show that it is essential to address processes at a landscape level, particularly at the surroundings of the reserve, in order to increase the effectiveness of fire protection, including the development of fire-prone classes maps. 2 other causal factors, fires are frequently used as an important indicator to evaluate the 3 effectiveness management of protected areas [2, 3]. A common approach to manage fire 4 in protected areas is applying active fire management or prescribed burning [4-7] which 5 aims to reduce fuel availability for preventing and controlling wildfire [8]. Nowadays, a 6 paradigm shift resulted in managers purposely burning grassland and forests to 7maintain the ecological mechanisms which drive ecosystem dynamics and diversity [7,9]. 8 Anthropogenic and natural factors lead to different patterns of fire occurrences in 9 protected areas across various ecosystems. Fire density was found to be two times 10 higher in non-protected areas than within protected areas in Myanmar [10] and 11 PLOS 1/15Amazonian regions [2]. It has been shown that human intervention influences a 12 protected areas susceptibility to disturbance. At a global scale, forest loss rates in 13 protected areas is associated with high proportions of agricultural land in the country 14 [11]. Managing anthropogenic factors which include fewer road construction, less human 15 impact mechanisms [2] as well as fire-free land management [12] in the reserves has 16 shown their effectiveness in reducing fire-driven deforestation. In contrast to fire 17 occurrences in tropical areas, natural mechanisms caused higher fire density in 18 protected areas than in non-protected areas in West and Central Africa [13]. More fires 19 occurred in 59 percent of the area where deforestation rates dropped between 2000 and 20 2007, since more fuel was available for ignition [12]. Here, controlled ignition and active 21 fire mana...

Agent-based models have been developed and widely employed to assess the impact of disturbances or conservation management on animal habitat use, population development, and viability. However, the direct impacts of canopy disturbance on the arboreal movement of individual primates have been less studied. Such impacts could shed light on the cascading effects of disturbances on animal health and fitness. Orangutans are an arboreal primate that commonly encounters habitat quality deterioration due to land-use changes and related disturbances such as forest fires. Forest disturbance may, therefore, create a complex stress scenario threatening orangutan populations. Due to forest disturbances, orangutans may adapt to employ more terrestrial, as opposed to arboreal, movements potentially prolonging the search for fruiting and nesting trees. In turn, this may lead to changes in daily activity patterns (i.e., time spent traveling, feeding, and resting) and available energy budget, potentially decreasing the orangutan's fitness. We developed the agent-based simulation model BORNEO (arBOReal aNimal movEment mOdel), which explicitly describes both orangutans' arboreal and terrestrial movement in a forest habitat, depending on distances between trees and canopy structures. Orangutans in the model perform activities with a motivation to balance energy intake and expenditure through locomotion. We tested the model using forest inventory data obtained in Sebangau National Park, Central Kalimantan, Indonesia. This allowed us to construct virtual forests with real characteristics including tree connectivity, thus creating the potential to expand the environmental settings for simulation experiments. In order to parameterize the energy related processes of the orangutans described in the model, we applied a computationally intensive evolutionary algorithm and evaluated the simulation results against observed behavioral patterns of orangutans. Both the simulated variability and proportion of activity budgets including feeding, resting, and traveling time for female and male orangutans confirmed the suitability of the model for its purpose. We used the calibrated model to compare the activity patterns and energy budgets of orangutans in both natural and disturbed forests . The results confirm field observations that orangutans in the disturbed forest are more likely to experience deficit energy balance due to traveling to the detriment of feeding time. Such imbalance is more pronounced in males than in females. The finding of a threshold of forest disturbances that affects a significant change in activity and energy budgets suggests potential threats to the orangutan population. Our study introduces the first agent-based model describing the arboreal movement of primates that can serve as a tool to investigate the direct impact of forest changes and disturbances on the behavior of species such as orangutans. Moreover, it demonstrates the suitability of high-performance computing to optimize the calibration of complex agent-based models describing animal behavior at a fine spatio-temporal scale (1-m and 1-s granularity).