Credit Values Research Articles

SME credit constraints and access to informal credit markets in Vietnam

PurposeA review of literature has documented that accessing formal credit and other banking services has always been a crucial challenge for small and medium-sized enterprises (SMEs). The alternative, therefore, tends to be informal channels. However, the credit constraint vis-à-vis informal channel link does not appear to be well documented in the literature. This study aims to investigate whether credit constraints significantly affect the probability of accessing informal credit, as well as the credit values of Vietnamese SMEs.Design/methodology/approachThis study uses a trinary approach and correlated random-effects Probit and Tobit techniques to avoid the incidental coefficients problem.FindingsThe results suggest that relative to unconstrained and partially constrained firms, fully constrained firms tend to be more active in the informal credit markets, shown by their higher probability of informal credit access and larger credit values.Originality/valueTo the best of authors’ knowledge, this is the first study on Vietnam that takes a different approach to credit constraints and examines their impact on informal credit access. Policy implications arise and are discussed.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2017-0543

A credit-based dynamical evaluation method for the smart configuration of manufacturing services under Industrial Internet of Things

Most scheduling problems are required to follow rigid metrics, such as the maximum completion time, earliest deadline first, etc., ignoring the flexibility of manufacturing services (MSs) and the effects of their historical data hidden in millions of manufacturing activities. The historical data serves as a powerful basis for describing the comprehensiveness or credibility of the MS itself with the help of Industrial IoT enabling all equipment to communicate and take preventive actions. Similar to the bank credit for individuals, MSs should also have their own referential credit values when choosing the most suitable service for a specific manufacturing task. This paper summarizes the MS attributes from six aspects with sufficient sub-attributes. The fuzzy Analytic Network Process combined with the Cross-Entropy method is employed to evaluate the credit of MSs in the complex manufacturing network system. Such service scoring mechanism (SSM) can personify a comprehensive credit evaluation of services, where, a smart service configuration mode based on credit is proposed for carrying out the supply–demand matching with the help of the data-security technology. Subsequently, a credit-based manufacturing mode is derived under SSM. Numerical examples are carried out to demonstrate the validity of the matching mode. The result may assist manufacturers to allocate their manufacturing tasks in real time in a “credit” way and make quicker decisions in exceptional circumstances, while making the chosen service truly competent enough to finish the work, so as to further improve the customer satisfaction.

Exergo-environmental analysis of an indirect forced convection solar dryer for drying bitter gourd slices

In this study, a low cost indirect forced convection solar dryer integrated with porous bed sensible heat storage medium has been developed and studied under the climatic conditions of Coimbatore for drying bitter gourd slices. The experimental setup consists of a solar collector with 2 m2 area, drying chamber and a centrifugal blower to force the air. The main objective of the study is to investigate the effect of mass flow rate of air on the exegetic and pickup efficiencies of the solar drying system for drying bitter gourd slices. The results indicate that the mass of the bitter gourd slices was reduced from 4000 to 723 g in 7 h at the mass flow rate of air 0.0636 kg/s in solar drying system. The average exergy efficiency values vary from 28.74% to 40.67% for the mass flow rates of air from 0.0141 to 0.0872 kg/s respectively. The average pickup efficiency of the drying air varied from 54.29% to 17.18% for various mass flow rates of air and it decreases with increase in mass flow rate of air. The effective moisture diffusivity of bitter gourd slices was observed from 8.6293 × 10−10 to 12.9585 × 10−10 m2/s, whereas for open sun drying it gives the lowest value of 0.9568 × 10−10 m2/s. Environmental impact analysis indicated that the energy payback time for the indirect solar dryer is found to be 2.21 years only. The CO2 mitigation and earned carbon credit values for the developed system are 33.52 tons and INR 10894 to 43576 for the expected lifetime of 35 years. Impact analysis shows that the solar dryer is a suitable solution for preserving the agricultural products with environmental sustainability.

Credit-Based Payments for Fast Computing Resource Trading in Edge-Assisted Internet of Things

The introduction of edge computing into blockchain-enabled Internet of Things (IoT) for offloading computational tasks is attracting increasing attention. Computing resource trading unavoidably happens in edge-assisted IoT. However, efficient computing resource trading cannot be achieved because of the “cold start” and “long return” problems. To address these challenges, we propose to use a credit-based payment for fast computing resource trading in edge-assisted blockchain-enabled IoT; therefore, the IoT nodes can finish fast payment and frequent trading by borrowing resource coins from other IoT nodes based on their credit values. In our resource-coin loan problem, we propose an iterative double-auction-based algorithm, where a broker is introduced to solve the loan allocation problem and to determine the size of the loan each lender would provide to each borrower. Furthermore, the broker enforces specific loan pricing rules to induce the borrowers and lenders to bid truthfully. Then, the hidden privacy information could be extracted to achieve the optimal resource-coin allocation and loan pricing. The proposed algorithm can maximize the economic benefits while protecting privacy. Simulations showed that the proposed algorithm can maximize social welfare. In addition, we compared the proposed algorithm with the credit-bank-based method in terms of the satisfaction function and payments. The experimental results demonstrated that the proposed algorithm was individually rational, truthful, and budget-balanced.

Credit risk and solvency capital requirements

Credit risk permeates the assets of most insurance companies. This article develops a framework for computing credit capital requirements under the constant position paradigm and taking into account recovery rates. Although this framework was originally derived under the Solvency 2 regulation, it also provides concepts that can be useful under other international regulations. After a brief survey of the existing technology on rating transitions and default probabilities, the paper provides new results on risk premium adjustment factors. Then, three different procedures for reconstructing constant position market-consistent histories of credit portfolios from quoted Merrill Lynch indices are given. The reconstructed historical credit values are modeled via mixed empirical-Generalized Pareto Distribution (GPD) dynamics and a detailed parameter estimation is performed. Several validations of the estimation are also provided. Finally, credit Solvency Capital Requirements are computed and an analysis of the results per rating class is given.

ANALISIS PERBANDINGAN PENILAIAN KINERJA PERBANKAN MENURUT SE Bl 1997 DAN SE BI 1998

We can evaluate the bank health from financial ratios in its financial statements. The fi nancial ratios are known as ('AMEL (capital adequacy, asset quality, management, earning, liquidity). The government changes the regulation of evaluation of bank health. The new regulation we use now is SE HI No. 30 23: UPPB, 19 March 1998 and the old one is SE Bl No. 30 2 UPPB. 30 April 1997.The research issue is whether /here any significant changes in bank performance if we use the new reKulation than the old one. The chanRes consist of three financial ratios there are two ratios <?f'asset quality and one liquidity ratio. The measurement calculates the credit values from .financial ratios according to the old regulation and the new one and then comparing the results.The results show that there are any signlficant changes in bank performance using the new regulation. The results also show that using the new regulation to measure the bank health makes more difficultj(Jr the bank to get the predicate as a good bank.

ANALISIS PERBANDINGAN PENILAIAN KINERJA PERBANKAN MENURUT SE Bl 1997 DAN SE BI 1998

We can evaluate the bank health from financial ratios in its financial statements. The fi nancial ratios are known as ('AMEL (capital adequacy, asset quality, management, earning, liquidity). The government changes the regulation of evaluation of bank health. The new regulation we use now is SE HI No. 30 23: UPPB, 19 March 1998 and the old one is SE Bl No. 30 2 UPPB. 30 April 1997.The research issue is whether /here any significant changes in bank performance if we use the new reKulation than the old one. The chanRes consist of three financial ratios there are two ratios <?f'asset quality and one liquidity ratio. The measurement calculates the credit values from .financial ratios according to the old regulation and the new one and then comparing the results.The results show that there are any signlficant changes in bank performance using the new regulation. The results also show that using the new regulation to measure the bank health makes more difficultj(Jr the bank to get the predicate as a good bank.

A novel approach for QoS prediction based on Bayesian combinational model

As an important factor in evaluating service, QoS (Quality of Service) has drawn more and more concerns with the rapid increasing of Web services. However, due to the great volatility of services in Mobile Internet environments, such as internet of vehicles, Web services often do not work as announced and thus cause unacceptable problems. QoS prediction can avoid failure before it takes place, which is considered a more effective way to assure quality. However, Current QoS prediction approaches neither consider the highly dynamic of Web services, nor maintain good prediction performance all the time. Consequently we propose a novel Bayesian combinational model to predict QoS by continuously adjusting credit values of the basic models so as to keep good prediction accuracy. QoS attributes such as response time, throughput and reliability are used to validate the proposed model. Experimental results show that the model can provide stable prediction results in Mobile Internet environments.

Listening to Whispers of Ripple: Linking Wallets and Deanonymizing Transactions in the Ripple Network

Abstract The decentralized I owe you (IOU) transaction network Ripple is gaining prominence as a fast, low-cost and efficient method for performing same and cross-currency payments. Ripple keeps track of IOU credit its users have granted to their business partners or friends, and settles transactions between two connected Ripple wallets by appropriately changing credit values on the connecting paths. Similar to cryptocurrencies such as Bitcoin, while the ownership of the wallets is implicitly pseudonymous in Ripple, IOU credit links and transaction flows between wallets are publicly available in an online ledger. In this paper, we present the first thorough study that analyzes this globally visible log and characterizes the privacy issues with the current Ripple network. In particular, we define two novel heuristics and perform heuristic clustering to group wallets based on observations on the Ripple network graph. We then propose reidentification mechanisms to deanonymize the operators of those clusters and show how to reconstruct the financial activities of deanonymized Ripple wallets. Our analysis motivates the need for better privacy-preserving payment mechanisms for Ripple and characterizes the privacy challenges faced by the emerging credit networks.

Credit Benchmarking, Risk Premium Adjustment Factors, and Credit Solvency Capital Requirements. A Recovery-Based Approach

This article constructs a recovery-based framework for computing the credit Solvency Capital Requirements of insurers under the constant position paradigm. Although this framework is most suited under the Solvency 2 regulation, it also provides concepts that can be useful under the Basel regulation. After a brief survey of the extant technology on rating transitions and default probabilities, the paper provides new results on risk premium adjustment factors. Then, three different procedures for reconstructing constant-position market-consistent histories of credit portfolios from quoted Merryll Lynch indices are given. The reconstructed historical credit values are then calibrated to mixed empirical-Generalized Pareto Distribution (GPD) dynamics. Several validations of the calibration are also provided. Finally, credit Solvency Capital Requirements are computed and an analysis of the results per rating class is given.

The Value of Learning about Natural History in Biodiversity Markets.

Markets for biodiversity have generated much controversy because of the often unstated and untested assumptions included in transactions rules. Simple trading rules are favored to reduce transaction costs, but others have argued that this leads to markets that favor development and erode biodiversity. Here, I describe how embracing complexity and uncertainty within a tradable credit system for the Red-cockaded Woodpecker (Picoides borealis) creates opportunities to achieve financial and conservation goals simultaneously. Reversing the effects of habitat fragmentation is one of the main reasons for developing markets. I include uncertainty in habitat fragmentation effects by evaluating market transactions using five alternative dispersal models that were able to approximate observed patterns of occupancy and movement. Further, because dispersal habitat is often not included in market transactions, I contrast how changes in breeding versus dispersal habitat affect credit values. I use an individually-based, spatially-explicit population model for the Red-cockaded Woodpecker (Picoides borealis) to predict spatial- and temporal- influences of landscape change on species occurrence and genetic diversity. Results indicated that the probability of no net loss of abundance and genetic diversity responded differently to the transient dynamics in breeding and dispersal habitat. Trades that do not violate the abundance cap may simultaneously violate the cap for the erosion of genetic diversity. To highlight how economic incentives may help reduce uncertainty, I demonstrate tradeoffs between the value of tradable credits and the value of information needed to predict the influence of habitat trades on population viability. For the trade with the greatest uncertainty regarding the change in habitat fragmentation, I estimate that the value of using 13-years of data to reduce uncertainty in dispersal behaviors is $6.2 million. Future guidance for biodiversity markets should at least encourage the use of spatially- and temporally-explicit techniques that include population genetic estimates and the influence of uncertainty.

Real Option Approach on Infrastructure Investment in Vietnam: Focused on Smart City Project

The electricity shortage, the natural disasters and the emission of greenhouse gasses have been challenges that Vietnam has to confront to sustain high economic growth in the long-term. We are moving forward to “Smart City” project in Japan that brings a better life for citizens through public services, utilization of resources and less impact onenvironment. However, this project requires huge investment of financial amounts and long term to profitability under uncertainties. Therefore, real options analysis is used as a theoretical framework to better account for the technological and market uncertainties and irreversibility that impact the investment and innovation decisions of firms. This paper shows how to use the quadranomial approach for two sources of uncertainty and with compound rainbow options. The specific one is if the investors decide to invest in R&D of the project, they will get the different carbon credit values created from this project changing at the same volatility of project’s products in each investing node through Clean Development Mechanism. From this volatility estimated from fuel price data and two different net present values of project, this paper created the value-based event tree to value research and development (R&D) project which influences the dynamic shaping of investment decisions of firms in the green industry.

Spatial forest valuation: The role of location in determining attitudes toward payment for ecosystem services policies

Forests provide many benefits (e.g., esthetics, water purification, habitat, carbon sequestration) to humans when they are conserved. However, forest conservation efforts may conflict with other uses, particularly timber harvest. Incentives for forest conservation can be established through payment for ecosystem services (PES) policies. PES policies rely on forest valuation studies which traditionally have valued the whole forest, or characteristics of a forest. Methods that allow variability in estimated forest values over space can provide valuation information at a finer scale and aid in the optimization of PES policies. These spatially explicit values provide information critical to many policy decisions, particularly conservation prioritization and planning.Using moderate resolution satellite remote sensing (i.e., LandSat) and a forest use survey conducted in Kam Cha i, Thailand, methods to estimate forest product valuation for spatially heterogeneous plots are demonstrated. These estimates are produced using geographic information system (GIS) multicriteria decision analysis (MCDA). The MCDA method combines forest use data with associated travel costs and vegetation cover estimates to provide spatially explicit estimates of forest values. This information is then used to compare local use values against potential carbon credit values estimated from the literature. The results show that a majority of the forest plots have higher PES values than for local forest products. Some do not, however, which suggests a possible cause for resistance against potential PES policies implemented in these areas.

English

In recent years Internet has emerged as an important tool for gaining information. But people confronts with abundance of data. High performance information searching is required to cope with this situation. Recommender systems search appropriate documents or filter out inappropriate documents from several information streams in order to match with a user's general interests. Recent developments in recommender systems implements user classes as per the demographic data. Collaborative Filtering is the most vital component of recommender system as it recommends items by considering the ratings of similar users. We argued that additional factors have an important role to play in guiding recommendation. In this paper, we propose the design of Credit Based Collaborative Filtering (CBCF) approach for recommender systems which employs prioritized features of items to improve the efficiency of recommendations. In our suggested plan, each recommender is assigned with a credit value which signifies the goodness of a recommender. The profile similarity in combination with credit value influences the decision making ability of recommender system. Further this credit value gets updated after every recommendation as user gives feedback about likeliness of the item. Eventually these modified credit values make the recommender system learn and thereby to improve the prediction accuracy in comparison to the classical recommender systems. We have supplemented our approach with a case study of a movie recommender system. A comparison of the generated recommendations using CBCF approach to the classical approach establishes the validity of the proposed system.

The Design and Simulation of a New Dynamic Credit and Role based Access Control Strategy

In order to solve the shortage of the access control method based on role and credit, a novel dynamic credit and role based access control method is proposed. The method controls an entity’s access behavior through its credit value, and introduces penalty and feedback mechanism to dynamically adjust entity’s credit value. In order to manage an amount of entities effectively, entities with different credit values are divided into different roles in system, and roles are assigned to corresponding privileges respectively. Experimental simulation results showed that the proposed method has good controllability of entity’s credit value and manipulability to protect system’s resources.

An adaptive distributed certificate management scheme for space information network

The security vulnerability of space information network is stimulating interest in developing security mechanisms study of heterogeneous network. However, it is noted that neither the single certificate authority (CA) nor the distributed CA can meet the security requirements for this type of network. In this study, the authors propose an adaptive distributed certificate management scheme in which the nodes that provide certificate services are selected dynamically in the network. The security risks caused by the static nodes are avoided in the proposed scheme. The status of the nodes in the network is completely equal and the credit values that vary with the operation of the network are the only criterion to measure their responsibilities. The scheme can effectively prevent attackers from getting permission of the certificate services and could be applicable to the complex and dynamic networks.

Delay-Constrained Admission and Bandwidth Allocation for Long-Reach EPON

Next generation Passive Optical Network (PON) technology has been evolving to consolidate the metro and access networks in order to offer enhanced capacity, high split ratio and reduced deployment cost per subscriber. However, transmission of the signals to long distances up to 100km leads to increased propagation delay whereas high split ratio may lead to long cycle times resulting in large queue occupancies and long packet delays. In this article, we present a delay-constrained admission control mechanism and adapt this scheme to our previously proposed bandwidth allocation technique, namely Periodic GATE Optimization (PGO). We call this new scheme Delay-Constrained Periodic GATE Optimization (DC-PGO). DC-PGO is designed to run for multiple service classes as it inherits the advantages of PGO by periodically building and solving an ILP formula- tion at the OLT in order to obtain the appropriate credit values for the overloaded ONUs. At the ONU side, DC- PGO runs an admission control scheme before pushing the arriving packets in the sub-queues. The admission control scheme uses statistical information consisting of the local data at the ONU and the previously received GATE messages from the OLT. Through simulations, we show that DC-PGO enhances the performance of multi-threaded polling in long- reach Ethernet PON when packets of differentiated service classes arrive with pre-specified delay requirements. Index Terms—Dynamic bandwidth allocation, Ethernet PON, long-reach passive optical networks, multi-threaded polling

CARBON SEQUESTRATION IN EIGHT WOODY NON-TIMBER FOREST SPECIES AND THEIR ECONOMIC POTENTIALS IN SOUTHWESTERN CAMEROON

Carbon sequestration potentials of 8 woody species were assessed on an ecosystem level, using the CO 2FIXV.2 model, for two scenarios. Net carbon sequestration potentials ranged from 246.23 to 306.22 Mg C ha -1 with complete rotation every 40 years, and 292 to 359.3 Mg C ha -1 with partial cut. Ricinodendron heudelotii had the highest net carbon sequestration potential (306.22 and 359.3 Mg C ha -1 for the complete and partial cuts respectively), while Cola lepidota had the least under both scenarios. There were higher carbon stocks in plant biomass than soil for all agroforests under both management regimes. Fine litter had the highest soil carbon fraction and soluble compounds had the least in all the agroforests. Under complete rotation, the agroforests had potential carbon credit values ranging from US$2756 to $3264/ha/rotation, and $ 3114 to $3678/ha/rotation with partial cut. Partial cuts allowed for higher rates of carbon accumulation, and the farmer always has a standing crop. Economic prioritization showed that Irvingia wombulu was the best (US$6.67/Kg), followed by Ricinodendron heudelotii and Afrostyrax lepidophyllus ($5.55/Kg) and the least was Trycocypha abut ($0.33/Kg). These results would aid policy makers in mitigating climate change, improving rural livelihoods, and contributing to sustainable development. Keywords: carbon stocks, CO 2FIXV.2 model, sustainability, climate change and carbon trade

REGULATING HARM - GAMBLING TECHNOLOGY AND THE CHALLENGES FOR GREAT BRITAIN

Livingstone & Adams 1 describe the consequences of the unprecedented experiment conducted by the governments of Australasia in the 1990s, when machine gaming was introduced on a large scale into local communities. The results of that expansion are now becoming increasingly clear, and should serve as a cautionary tale to government and regulatory authorities in this country as they come to terms with the new legislative regime of gambling. That said, the structure, geography and political economy of Britain's 248 000 machines 2 differs from those in Australia and New Zealand. Machines exist in a variety of locations. Some are concentrated in casinos, bingo halls, adult gaming centres and family entertainment centres, others dispersed in betting shops, pubs and clubs. Sizes of stakes and prizes also vary, with stakes ranging from £100 to £0.10 and prizes from £4000 to £5 (this refers to cash stakes and prizes only, and is based only on machines currently licensed in Britain: Category As, with unlimited stakes and prizes, do not operate at present). Like Australasian ‘pokies’, some machines are truly random, while others use a form of compensatory mechanism, providing guaranteed payouts over shorter time-periods 3. Certain structural features of these products—including reinforcement schedules, spin speeds and credit values—are designed to attract and retain customers or, in industry terms, to maximize ‘time on device’4, and have been shown to be associated with higher levels of harm than other forms of gambling 5, 6. British machines operate within a new legislative and regulatory regime 7, 8. The 2005 Gambling Act, implemented in 2007, swept away its predecessors' principle of ‘unstimulated demand’ and is based on the premise that ‘gambling is a massive global industry and is entitled to a regulatory framework that ensures continued growth’9. While creating a regulator to oversee the industry and ensure player protection, its market philosophy of competition and consumer choice has also brought about an expansion of gambling opportunities, participation and expenditure 10. The legislation emphasizes the notion of ‘individual responsibility’ as a means of controlling behaviour: an emphasis which, it should be noted, is promoted increasingly by the new coalition government in the field of public health issues 11 and which, as Livingstone & Adams point out, is not conducive to upstream public health interventions. While the legislation removed some machines from ‘ambient’ locations, it also allows the siting of up to four Category B2 machines in betting shops, with larger numbers permitted in casinos. B2s [previously Fixed Odds Betting Terminals (FOBTs)] are electronic devices that offer a variety of games, with stakes up to £100 and prizes up to £500. The gross profit from these high-stake/prize machines in betting shops in 2008/09 was £1138 million. As a point of comparison, the gross profit on all other forms of betting-shop activity was £1717 million in the same period 2. These machines are associated with higher levels of problems than other forms of gambling: the national problem gambling helpline reported that 31% of their calls in 2009/10 concerned FOBTs, while another 18% related to other types of machines 12 (figures for FOBTs include the category ‘roulette machine’, which describes the same type of machine). An emerging trend appears to point towards the clustering of betting shops containing FOBTs in urban areas, creating concerns about impacts in low-income communities 13, 14. While the Australasian case described by the authors should serve as a case study on the risks of EGM proliferation, it needs to be remembered that the harms of these global products are mediated by a range of local factors, including product variations, location and regulatory controls. At present not enough is known about the interaction of these variables in this country. Research is now required—and is beginning 15 (see the Gambling Commission's programme of research into gaming machines)—to investigate the potential harms of the structural and distributional features of British machines, as well as the types of regulatory controls and interventions that may be required to ameliorate them. The author is Chair of the Research Panel of the Responsible Gambling Strategy Board, the independent body which advises the Gambling Commission on research and policy issues.

Taking Credit

This article presents some general concepts about capacity credit values, which are illustrated by theoretical examples as well as practical experience from the Swedish electricity market. The capacity credit of a wind generating unit (or a block of generating units) represents the contribution of the unit to the supply adequacy of the system. The capacity credit of a power plant is an abstract quantity based on probability calculations and requires knowledge of the probability distributions for available generation capacity and load. To secure the reliability of supply, the Swedish system operator was given the responsibility to purchase annual contracts for a "power reserve".