Transaction Function Research Articles

FINANCIAL TECHNOLOGY PADA PELAKU UMKM: STUDI TENTANG PERSEPSI MANFAAT, PERSEPSI KEMUDAHAN SERTA KEPERCAYAAN TERHADAP PENGGUNAAN STARTUP OVO

Financial technology is a service that is in great demand in today's society. OVO is a financial technology startup which provides electronic wallet service. The presence of OVO as a financial technology service has attracted the attention and interest of the community because of the ease of its transaction function. This study aimed to determine the effect of benefits, convenience, and confidence of micro, small, and medium enterprises on interest in using financial technology. This research was conducted using a quantitative approach. The research sample was determined using the sampling estimation method, and the sample size of 96 respondents was determined using the Lemeshow formula. Data collection techniques were conducted through questionnaires. The collected data were then analyzed using multiple linear regression techniques. The results showed that perceived benefits, perceived comfort, and business needs significantly affected interest in using financial technology.

Estimating Software Functional Size via Machine Learning

Measuring software functional size via standard Function Points Analysis (FPA) requires the availability of fully specified requirements and specific competencies. Most of the time, the need to measure software functional size occurs well in advance with respect to these ideal conditions, under the lack of complete information or skilled experts. To work around the constraints of the official measurement process, several estimation methods for FPA have been proposed and are commonly used. Among these, the International Function Points User Group (IFPUG) has adopted the “High-level FPA” method (also known as the NESMA method). This method avoids weighting each data and transaction function by using fixed weights instead. Applying High-level FPA, or similar estimation methods, is faster and easier than carrying out the official measurement process but inevitably yields an approximation in the measures. In this article, we contribute to the problem of estimating software functional size measures by using machine learning. To the best of our knowledge, machine learning methods were never applied to the early estimation of software functional size. Our goal is to understand whether machine learning techniques yield estimates of FPA measures that are more accurate than those obtained with High-level FPA or similar methods. An empirical study on a large dataset of functional size predictors was carried out to train and test three of the most popular and robust machine learning methods, namely Random Forests, Support Vector Regression , and Neural Networks. A systematic experimental phase, with cycles of dataset filtering and splitting, parameter tuning, and model training and validation, is presented. The estimation accuracy of the obtained models was then evaluated and compared to that of fixed-weight models (e.g., High-level FPA) and linear regression models, also using a second dataset as the test set. We found that Support Vector Regression yields quite accurate estimation models. However, the obtained level of accuracy does not appear significantly better with respect to High-level FPA or to models built via ordinary least squares regression. Noticeably, fairly good accuracy levels were obtained by models that do not even require discerning among different types of transactions and data.

DVIT—A Decentralized Virtual Items Trading Forum with Reputation System

The metaverse provides us with an attractive virtual space in which the value of the virtual property has been increasingly recognized. However, the lack of effective cross-metaverse trading tools and the reputation guarantee makes it difficult to trade items among different metaverses. To this end, a decentralized reputation system for virtual items trading forum named DVIT is devised. To the best of our knowledge, DVIT is the first decentralized cross-metaverse item trading prototype inspired by the online-game trading system. We designed the corresponding transaction function and realized the autonomous governance of the community by introducing the reputation mechanism. An improved election mechanism is proposed to improve efficiency based on Delegated Proof-of-Stake (DPoS). Through token rewards associated with activity levels, users’ motivation can be stimulated. The experiments indicate that our proposed scheme could dynamically measure the trustworthiness degree of the users through the dynamic reputation value and thereby exclude malicious users from the blockchain within 20 epochs.

Risk and Return: An Empirical Analysis of the Optimal Trading Strategies of Gold and Bitcoin from the Perspective of Market Traders with Three Decision Types

This paper uses the daily prices of gold and bitcoin from September 2016 to September 2021 to discuss the optimal decision of market traders. LSTM algorithm is used to predict the future price trend of bitcoin and gold. Then, calculate the risk coefficient of Bitcoin and gold trading. Next, the expected returns of gold and bitcoin are obtained according to the determined price forecast value, and combined with the risk coefficient to construct the transaction function. Finally, because the objective function and constraint conditions are linear functions, the results are calculated by using the idea of linear programming. In the whole paper, considering the attitude of market traders in decision-making, three types of decision makers are discussed. Firstly, the time series model is used to predict the data of the same gold and bitcoin. Then, the data predicted by the LSTM model and the time series model are used to calculate the MAE and MSE. By comparing the numerical values, the LSTM model is significantly superior to the time series model, so that the optimal prediction method is proved. Next, for three different decision types of traders, respectively, using the decision model established in 6.1 to find whether the optimal decision point exists and meaningful. The results show that all three types of decision makers can make optimal decisions under the influence of the risk of the predicted data, that is, the risk of the decision model is controllable. Secondly, to demonstrate the sensitivity of transaction costs. Firstly, the fixed commission ratio in the requirements is adjusted, and the commission ratios of bitcoin and gold are adjusted respectively, floating up and down within 20 %. Then, it is brought into 6.1 to calculate the optimal decision-making profit value of traders of three decision-making types. Finally, it is found that the profit value of the optimal decision-making point is very stable. Compared with the profit value calculated by the given commission ratio, the deviation is less than 0.4 %, and the sensitivity analysis of transaction cost is well completed. Finally, but not the most important, it is hoped that the model studied in this paper can help market traders make optimal strategies when making decisions.

Research on Agricultural Product Traceability Technology (Economic Value) Based on Information Supervision and Cloud Computing.

Traditional agricultural product traceability system adopts centralized storage, and the traceability process is solidified, which results in the low reliability of traceability results and the poor flexibility of the system. Aiming to solve this problem, blockchain technology is applied to supply chain traceability, and a supply chain traceability system based on sidechain technology is proposed. Goods management, information sharing, and product traceability in supply chain are realized through Ethereum smart contract. The sidechain technology is adopted to expand Ethereum so that it can meet the needs of practical applications. The experiment results show that the proposed system has a transaction function and information sharing function. Compared with similar trading systems, the proposed system has more advantages in throughput and security.

On the theory of optimization of transaction costs of multifactor manufacturing enterprises

The published article proposes mathematical models for calculating the optimal profit of multifactorial manufacturing enterprises that incur both production (transformational) and certain non-production (transactional) costs, the sources of which may be forced costs of searching for economic information, measuring the parameters of various goods, negotiating and the conclusion of contracts, for the development of specifications and the protection of property rights, for the opportunistic behavior of employees and managers of the enterprise, etc. Anumerical analysis of the presented models for calculating the optimal profit of multifactor enterprises that bear transaction costs shows the unattainability of the maximum possible profit values, since in practice the enterprise management maximizes not the profit itself, but its utility, expressed in the form of the corresponding transaction function.

Teori Pertukaran (Natural Certainty Contract) Dan Teori Percampuran (Natural Uncertainty Contracts)

Introduction/Main Objective: This study aims to determine the theory of exchange (natural certainty contracts) and the theory of mixing (natural uncertainty contracts). Background problems: the theory of exchange (natural certainty contracts) and the theory of mixing (natural uncertainty contracts) are basic concepts in a transaction muamalah, especially in transactions in Islamic banking. Therefore, a deeper understanding of the concepts of exchange theory and mixed theory in Islamic economics is needed first before discussing Islamic banking (real sector based banking). Research Methods: This type of research is included in the category of library research, using a qualitative approach. Findings/Results: Judging from the level of certainty of the results that will be obtained, the tijarah contract can be divided into two, namely in terms of the theory of exchange (natural certainty contract) and in terms of mixed theory ( natural uncertainty contracts). Conclusion: when talking about Islamic finance and banking which cannot be separated from the study of transactions that occur in the real sector, then the issue of contract is the key in these transactions. In the discussion of the contract, it can be seen from the problem of whether or not there is compensation promised by one of the parties. in this case, the contract is divided into two, namely the tabarru' contract and the tijarah contract. In the tabarru' contract, each type of agreement involves not-for-profit transactions (non-profit transactions). But in the tijarah contract, all types of contracts are included in the for profit transaction function. Judging from the level of certainty of the results to be obtained, the tijarah contract can be divided into two, namely in terms of the theory of exchange (natural certainty contracts) and in terms of the theory of mixing (natural uncertainty contracts). These two concepts are the basis in a muamalah transaction, especially in transactions in Islamic banking.

Unlinkable Collaborative Learning Transactions: Privacy-Awareness in Decentralized Approaches

Smart contracts (SCs) and collaborative learning (CL) are disclosed publicly, in which most transactions and activities that occur by the parties can be bared in real-time. Both are strengthened in a decentralized manner. CL allows numerous clients to collectively build deep learning models privately by aggregating the gradient values from clients’ devices, yet it lacks the incentive mechanism for the contributing clients. On the other hand, the merits of SCs can be a plausible solution as an incentive mechanism in the CL system because self-executing contracts with immutable data records are resistant to failure. The clients can claim the rewards by stating their contribution arbitrarily in the SCs and tendering a proof transaction function. Nevertheless, directly adopting SCs in the CL system could breach clients’ privacy because the transactions are exposed openly. The observer can infer the properties of the clients’ resources. Therefore, we designed schemes that can overcome observers’ ability to link clients’ information with their associated devices during training. In essence, our schemes are unbiased. We also provide a secure incentive mechanism for the parties in the CL system by obscuring the information values. Finally, the numerical results indicate that the proposed schemes satisfy the design goals.

Triple Personality: Creating, Performing and Appreciating Physical Theatre

"This article represents a closer examination of the triadic perspective of creating, performing and appreciating a performative event. This type of analysis is directly linked to choreological studies, a domain which is not yet part of the Romanian academic field, but, in essence, it does exist through other forms of theatrical studies and practices. I localize every scholarly aspect in current performative practices, more precisely, in that of physical and dance theatre. Through this article I would like to bring more attention to the way these forms of performing arts are created, performed and spectated by individuals who are able to deal with all three processes. Therefore, this analysis will have a more personal mark, thanks to the interviews integrated, with two internationally known artists in physical theatre: Hannes Langolf and Rob Hayden. It is a closer unveiling of how processes of transaction function within a piece of work. It is a way of constant questioning every participant in an artistic event should confront him/herself with. Keywords: choreology, movement, physical theatre, creator, performer, spectator, interview, Hannes Langolf, Rob Hayden"

Reward meritocracy or nepotism: The case of independent financial advisors appointed by Chinese listed companies

As independent financial advisors, securities firms are the core intermediaries in major asset reorganization (MAR) of listed companies. Furthermore, they play the dual roles of transaction and authentication. Based on this institutional background, this paper studies how listed companies choose between industry experience (“meritocracy”) and relationships (“nepotism”). Using the MAR of A-share listed companies from 2008 to 2013 as the sample, this paper shows that higher transaction costs (i.e., greater demand for the transaction function of advisors) are related to the higher possibility of advisors with weaker relationships and more industry experience being hired. It also shows that higher suspicion of tunneling (i.e., greater demand for the signal of fairness associated with advisors’ authentication function) is related to the higher possibility of advisors with weaker relationships being hired, but it is not significantly related to whether advisors have more or less industry experience. This paper also shows that reputation has a certain governance effect on the negative consequences of relationship. For the most part, listed companies reward meritocracy but not nepotism when appointing independent financial advisors.

THE PROBLEM OF THE OPTIMAL VOLUME OF ENTERPRISE PRODUCTION IN THE LIGHT OF THE THEORY OF TRANSACTION COSTS AND THE PRACTICE OF OUTSOURCING

The purpose of the article was to determine the importance of outsourcing and transaction costs accompanying it in the process of optimizing company structures. The practical reference of the adopted research objective was to indicate the optimal size of the enterprise. The aim is also to indicate, based on literature research, the impact of the transaction cost theory on the development of outsourcing. The findings of research show that the optimal size of the enterprise corresponds to the production volume at which the transaction function indicates the decreasing level of their marginal product, until the value reaches 0. With a high specificity of the company’s resources, which requires the use of specific technologies, there are transaction costs on this account that shape the price of the goods being the subject of the transaction. Thus, when further increasing the size of the production company, one should also take into account the added transaction costs, among others, control and monitoring of transactions. Modern enterprises focus their actions on key areas of activity. They give up production of what outsourcing providers can do more effectively, leaving what is specific for a given product, determining the company’s identity and the essence of production.

Determining Process Model Using Time-Based Process Mining and Control-Flow Pattern

Determining right model of business process from event log is the purpose of process discovery. However some problems i.e the inability to discover OR, noise and event log incompleteness are emmerged while determining right model of business process. First, OR relation is often discovered as AND relation. Second, noise problem is occured when there are truncated and low frequency traces in event log. Thus control-flow pattern is used to solve issues of same noise relation frequency hence it discovers relation based on transaction function of activity. Consequently, it can refine non noise relation in business process model. Third, incompleteness leads to incorrect discovery of parallel process model; therefore we used Timed-based Process Mining which utilized non-linear dependence to solve the incompleteness. Finally this paper proposed combination of Timed-based Process Mining and control-flow pattern to discover OR and handle same frequency noise and incompleteness. From the experiment in section 3, this proposed method manages to get right process model from event log.

Understanding the Impact of Online Reviews on Customer Choice: A Probability Discounting Approach

ABSTRACTThis study uses the concept of probability discounting to understand the impact of online customer reviews on consumer choice. Probability discounting describes how the subjective value of an outcome alters when its delivery shifts from certain to uncertain. An experimental study with 29 participants was conducted. Participants were run through an online shopping scenario where they had to choose whether to buy a product from a Web shop with customer reviews on reliability or from a Web shop without reviews but with a lower product price. A titration procedure over sales price for the Web shop without reviews was run over seven probability conditions. The mean switching points where participants chose where to buy the product were extracted from the experimental data, and probability discounting factors were calculated. The results supported the assumption that online reviews indicate the probability of a successful transaction online and function as a guide to choices. Implications for marketers as well as suggestions for future research are discussed.

Transaction Estimation of Institutions

The paper represents the fundamental principles and ideas of the transaction theory of economic institutions, which supposes quantification of the quality of institutions through evaluation of economic transactions. The major works of the founders as well as the practical pathways of implementing the theory are discussed. The paper consolidates the author’s main contributions to the study of companies’ transactions based on their market potential, the technique of institutional atlas design, institutional effects of the staff opportunism decrease, assessment of the transaction costs of hybrid organizations, and the formal representation of the company’s external transaction function.

An exploratory study on the accuracy of FPA to COSMIC measurement method conversion types

BackgroundFunctional size measurement methods are increasingly being adopted by software organizations due to the benefits they provide to software project managers. The Function Point Analysis (FPA) measurement method has been used extensively and globally in software organizations. The COSMIC measurement method is considered a second generation FSM method, because of the novel aspects it brings to the FSM field. After the COSMIC method was proposed, the issue of convertibility from FPA to COSMIC method arose, the main problem being the ability to convert FPA historical data to the corresponding COSMIC Function Point (CFP) data with a high level of accuracy, which would give organizations the ability to use the data in their future planning. Almost all the convertibility studies found in the literature involve converting FPA measures to COSMIC measures statistically, based on the final size generated by both methods. ObjectivesThis paper has three main objectives. The first is to explore the accuracy of the conversion type that converts FPA measures to COSMIC measures statistically, and that of the type that converts FPA transaction function measures to COSMIC measures. The second is to propose a new conversion type that predicts the number of COSMIC data movements based on the number of file type references referenced by all the elementary processes in a single application. The third is to compare the accuracy of our proposed conversion type with the other two conversion types found in the literature. MethodOne dataset from the management information systems domain was used to compare the accuracy of all three conversion types using a systematic conversion approach that applies three regression models: Ordinary Least Squares, Robust Least Trimmed Squares, and logarithmic transformation were used. Four datasets from previous studies were used to evaluate the accuracy of the three conversion types, to which the Leave One Out Cross Validation technique was applied to obtain the measures of fitting accuracy. ResultsThe conversion type most often used as well as the conversion type based on transaction function size were found to generate nonlinear, inaccurate and invalid results according to measurement theory. In addition, they produce a loss of measurement information in the conversion process, because of the FPA weighting system and FPA structural problems, such as illegal scale transformation. Our proposed conversion type avoids the problems inherent in the other two types but not the nonlinearity problem. Furthermore, the proposed conversion type has been found to be more accurate than the other types when the COSMIC functional processes comprise dataset applications that are systematically larger than their corresponding FPA elementary processes, or when the processes vary from small to large. Finally, our proposed conversion type delivered better results over the tested datasets, whereas, in general, there is no statistical significant difference between the accuracy of the conversion types examined for every dataset, particularly the conversion type most often used is not the most accurate. ConclusionsOur proposed conversion type achieves accurate results over the tested datasets. However, the lack of knowledge needed to use it over all the datasets in the literature limits the value of this conclusion. Consequently, practitioners converting from FPA to COSMIC should not stay with only one conversion type, assuming that it is the best. In order to achieve a high level of accuracy in the conversion process, all three conversion types must be tested via a systematic conversion approach.

Quantifying Operational Synergies of M&A: An Stochastic Equilibrium Approach

With the increase in merger and acquisitions (M&A) activities, managers of bidder firms need to make informed decisions on quantifying the operational synergies in an M&A. This paper considers a stochastic variational inequality approach to quantifying the operational synergies in a horizontal M&A through the integration of a supply chain network, in which each firm is represented as a network of economic activities associated with manufacturing, distribution, and storage. Specifically, we seek to quantify the gains, if any, associated with M&A. The model is stochastic and sufficiently general to handle many decision-makers and their independent behaviors. This paper extends Nagurney (2009) in which the cost functions (including both the production function and the transaction function) and the pricing cost are deemed as stochastic. Quasi-Monte Carlo approximating and homogeneous interior-point methods are used to solve the stochastic problem. Numerical results are provided.

Stochastic Variational Inequality for Supply Chain Network

Abstract In this paper, we propose a stochastic variational inequality approach for a supply chain network, in which the cost functions (including both the production function and the transaction function) and the pricing cost function are contaminated by stochastic parameters. The proposed network structure of the supply chain is identified and the stochastic variational inequality model is derived for the supply chain network. A sampling approximation algortihm is proposed to solve the resulting stochastic variational inequality problem by combining Quasi-Monte Carlo sampling method and homogeneous interior point method. The global convergence of the algorithm is proved and a preliminary example is given to show the efficiency of the proposed method.

A rule-based approach for estimating software development cost using function point and goal and scenario based requirements

Function point is a method used to measure software size and estimate the development cost. However, for large complex systems, cost estimation is difficult because of the large number of requirements expressed in natural language. In this paper we propose a rule-based approach for estimating software development cost in the requirements analysis phase. It combines goal and scenario based requirements analysis with function point based cost estimation. In our proposed approach, Context Analysis Guiding rules, Data Function Extraction Guiding rules, and Transaction Function Extraction Guiding rules have been developed to identify function points from text based goal and scenario descriptions. These rules are established based on a linguistic approach. The contribution of the proposed approach is to help project managers decide which requirements should be realized.

Measuring the Cost Efficiency of International Tourist Hotels in Taiwan

This study employs data envelopment analysis (DEA) to evaluate the relative cost efficiency of 49 international tourist hotels in Taiwan. The study uses five different measures: overall efficiency (OE), allocative efficiency (AE), technical efficiency (TE), scale efficiency (SE) and pure technical efficiency (PTE). Applying efficiency measures derived from the DEA estimation, hotel efficiency determinants are evaluated using the Tobit regression model. A bootstrapping technique is applied to overcome the interdependency problem of the DEA efficiency scores adopted in the regression analysis. The empirical results demonstrate that the international tourist hotel industry in Taiwan is inefficient, with most efficiency losses attributable to technical inefficiencies, of which scale inefficiencies are the primary cause – the scale of operations of international tourist hotels in Taiwan being too small to enable the cost-savings associated with larger-scale operations. The Tobit regression results indicate that the proportion of foreign individual travellers (FIT), online transaction function (WEB) and franchising (HOTELTYPE) are related to a better performance of international tourist hotels in Taiwan. The number of years a hotel has been operating (AGE) is not significantly related to any of the efficiency measures.

Video service utilizing networked image retrieval system

A new video service is proposed. The system utilizes a directory server featuring image retrieval for a specific sequence of a video stream of a baseball game designated by a specific customer. A number of pitching shots, used as the keys to retrieve the desired baseball game scenes, are stored in the index table of the directory server. An index table consisting of a number of sets of start and stop time codes, which specify the playing time spans for a number of continuous pitching shots, is used for the retrieval. The video board with a transaction function is used to respond to the request from a user terminal and to transfer the video stream specified by the user. When the customer at the user terminal specifies a cue to start, the designated video stream can appear on the user terminal.