Transaction Modes Research Articles

Galaxybase: A High Performance Native Distributed Graph Database for HTAP

We introduce Galaxybase, a native distributed graph database that addresses the increasing demands for processing large volumes of graph data in diverse industries like finance, manufacturing, and government. Designed to handle the requirements of both transactional and analytical workloads, Galaxybase stands out with its novel data storage and transaction mechanisms. At its core, Galaxybase utilizes a Log-Structured Adjacency List coupled with an Edge Page structure, optimizing read-write operations across a spectrum of tasks such as graph traversals and single edge queries. A notable aspect of Galaxybase is its execution of custom distributed transaction modes tailored for HTAP transactions, allowing for the facilitation of bidirectional and interactive transactions. It ensures data integrity and minimal latency while enabling simultaneous processing of OLTP and OLAP workloads without blocking. Experimental results show that Galaxybase achieves high throughput and low latency in both OLTP and OLAP workloads, across various graph query scenarios and resource conditions. Galaxybase has been deployed in leading banks, education, telecommunication and energy sectors in China, consistently maintaining robust performance for HTAP workloads over the years.

Research on an Improved Carbon Emission Flow Model Considering Electric Vehicle Charging Fluctuation and Hybrid Power Transaction

With the update of the power transaction mode and the access of increasing electric vehicles with high randomness to the power grid, the existing carbon emission flow calculation method cannot consider the influence of carbon emission due to the fluctuation in electric vehicle charging and various transaction modes. Given the above shortcomings, this paper proposes an improved carbon emission flow model considering electric vehicle charging fluctuations and hybrid power transactions. The model first considers different transaction modes, allocates the network loss to both sides of power generation, and forms a lossless network, realizing the decoupling of the bilateral transaction mode, pool transaction mode, and network loss and then calculating the day-ahead network’s carbon emission. Then, the changes in different transaction modes caused by the fluctuation in electric vehicle charging under different transaction modes are analyzed and the nodes of ‘spontaneous change’ are found to form a day-ahead intra-day deviation network and calculate its carbon emission flow. Finally, the calculation results are combined to obtain an improved power system carbon emission flow considering electric vehicle charging fluctuations and transaction modes. In this paper, the 33-node system is used for verification.

The Development Trend and Policy Support of Cross-border E-commerce in China

Due to the advanced technology of the 21st century, online shopping has been fully integrated into the daily life of human beings. China and the world are setting off a new trendy way of shopping: cross-border e-commerce. Since 2011, China has taken the lead in concluding transactions between trading entities in different country geographies using e-commerce, ordering online, paying, and settling. China's cross-border e-commerce can be divided into business-to-business (B2B) and business-to-consumer (B2C) trade models in terms of transaction modes. This paper is mainly based on the present Chinese cross-border e-commerce policy, using quotes, data analysis, and case studies to predict future developments and make policy recommendations.

Equilibrium analysis of transaction modes and recycling channels in a closed-loop supply chain with an online platform

Due to resource shortages and environmental protection, recycling of used products and remanufacturing have attracted more attention. This paper develops a game-theoretic model to investigate a key question the supply chain members are facing: When should the platform use the agency mode instead of the traditional reselling mode, and when should the manufacturer outsource recycling activities to the platform instead of recycling by himself? The results demonstrated the following: it is better for the manufacturer to outsource the recycling activities (recycle by himself) to the platform if the platform uses the agency mode (reselling mode); for the platform, the best choice is always the agency mode no matter what the recycling channel is; as a result, the equilibrium outcome will be the case where the platform uses the agency mode while the manufacturer chooses to outsource the collection of used products to the platform. This equilibrium leads to the highest recycling ratio, but does not guarantee the supply chain members get the highest but also is not the lowest profits. This study sheds light on how the decisions of transaction modes and recycling channels interact with each other and demonstrates the impact of such interactions on the platform, the manufacturer and the consumers. Furthermore, the results can help one to identify the most appropriate transaction modes and recycling channels for the platform and the manufacturer respectively.

Application of Face Recognition in E-commerce Security Authentication in the Era of Big Data

Although Internet technology brings invaluable benefits to all walks of life, the security of network and information is becoming more and more prominent. The leakage of personnel information caused by Internet security incidents causes irreparable harm and loss to individuals or enterprises. E-commerce is a virtual transaction mode based on Internet technology. Its security requirements for transactions are more stringent than those for traditional transaction modes. Traditional identity authentication technology can no longer meet its security needs. People urgently need a reliable identity authentication system, meaning to ensure the security of e-commerce. According to the actual application scenarios of the algorithm in e-commerce, this paper, based on the research on face recognition technology, focuses on the in-depth research on face detection technology under the background of big data in order to introduce face recognition technology in this paper. This paper proposes a feature-based face matching algorithm. The face image is preprocessed to improve the accuracy of real-time face detection and reduce the false detection rate. Based on the research of traditional facial feature extraction technology, a virtual sample set that can effectively support a traditional facial feature extraction algorithm is constructed to solve the problem of insufficient training samples in practical applications. The experimental results showed that the accuracy of the method in this paper can reach up to 79.5% and that the minimum time consumption is only 0.142 s. Compared with the traditional method, the accuracy rate is higher and the time consumption is shorter.

Pricing heterogeneity and transaction mode: Evidence from the French fish market

While information technology has led to increased market integration, in many markets there are still significant heterogeneity associated with factors such as product characteristics, market location, market lots, transaction mode and buyer and seller characteristics. Using a data set of 40 million observations of up-streams fish sales in Atlantic France, we use the rich attribute information to investigate the extent to which the price differences in a highly heterogenous market can be explained, with a particular focus on the importance of transaction mode. While 78% of the quantity is sold at auctions, the remainder are over-the-counter transactions and this share is increasing. Estimation of hedonic price regressions controlling for fish attributes, local market, buyer and seller heterogeneity show that there is a price differential of 1.7% between the two transaction modes. This result remains robust when taking into account the endogeneity of the sale method through an exact matching of auction and over-the-counter transactions.

The Role of E-Marketing Costs in Maximizing Corporate Profit

Marketing is a societal process, which discerns consumers' needs and specializes in services or products to fulfill one's needs, trying to mold the clients in the direction of the products or services offered. With extrude in time, advertising and marketing additionally have definitely been affected with advanced era. E-marketing and marketing have delivered a thrill to advertising and marketing professionals. With the improvement of technology and the extension of online users, e-trade structures step by step, and efficaciously, acquire social assets such as manpower and capital. More and extra traditional businesses integrate online and offline enterprise as their operation and trade methods. E-trade, as a new channel, has turned to be one of the important transaction modes in society. This article is a systematic literature review, aiming to identify the relationship between e-marketing budget and corporate profit maximization. E-marketing cost is positively correlated to profit maximization. Where e-marketing have helped corporations to increase and boom their profit via means of growing the budget allocated for e-marketing, which allows those corporations to have more the access to clients via all digital means, particularly social media and digital applications.

How Land Transactions Affect Carbon Emissions: Evidence from China

Land use change has become the second-largest source of greenhouse gas emissions after fossil energy combustion. In the context of developing a low-carbon economy, it is important to study how to achieve energy savings and emission reduction by adjusting land prices, and transforming land trading methods and land use types. Utilizing a balanced panel dataset about 291 sample cities in China, during the period of 2010–2016, this paper divided land transactions into three dimensions: land transaction price, land transaction modes, and land transfer structure; then employed a fixed-effect model to investigate the relationship between land transactions and carbon emissions. On top of this, we further analyzed the moderating role of economic development level and emission reduction policy. This study found that land transaction price can significantly inhibit carbon emissions; the amount of land sold by auction and listing has a stronger inhibitory effect on carbon emissions than by bidding; the higher the transfer proportion of industrial land, the higher the carbon emissions, while the transfer proportion of residential land is significantly negatively correlated with carbon emissions; the moderating mechanism shows that the level of economic development and emission reduction policy can play a moderating role in the relationship between land transactions and carbon emissions, but the moderating effect of emission reduction policy is limited, only existing in the relationships between land transaction price, the amount of listed land, and carbon emissions.

An Adaptive Algorithm for Selling On‐Site Renewable Energy of Data Centers in Two Transaction Modes

The data center operator has diverse options to sell redundant energy generated by its on‐site renewable generators to obtain payoff, where options include the grid and surrounding consumers. Different options and combinations of options mean different transaction modes for the data center operator. However, current works mainly investigate the selling of renewable energy in a fixed transaction mode, which will lead to payoff loss of data center operator. To heighten the payoff of data center operator, this paper designs two frameworks to model two transaction modes (i.e., single‐channel transaction mode and dual‐channel transaction mode) based on the Stackelberg game, where the Stackelberg game is used to address the conflict of interest between data center operator and electric utility company. The Stackelberg equilibrium, the optimal payoff of the data center operator, in two transaction modes is derived. Based on the difference of calculated optimal payoff in two transaction modes, an algorithm is proposed to adaptively choose the transaction mode that can bring more payoff. Simulation results show that the proposed algorithm is able to increase the payoff of the data center operator compared with that in fixed mode. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

A new double‐market parallel trading mechanism for competitive electricity markets

The current electricity market trading mechanism mainly includes the bilateral negotiation transaction and centralized transaction, with defects such as information asymmetry, insufficient competition, and weak price discovery. Thus, a new double-market parallel trading mechanism is proposed to improve the efficiency of the competitive electricity market in this paper. Regard the electricity market as a price-searching market and divide into two sub-markets composed of a price-searching market for buyers and a price-searching market for sellers. Market entities can trade synchronously in two sub-markets as price searchers or bidders. Searchers are responsible for organizing transactions in line with the market clearing rule library, and bidders participate in transactions initiated by searchers. Under the parallel mechanism, the traditional trading mechanism is also applicable. the framework of the proposed mechanism is presented from four aspects, including the description, clearing process, operation mode, and linkage between two sub-markets. Then, a market clearing model of the proposed mechanism is built with several traditional transaction modes as special cases of the presented double-market parallel transactions. Finally, taking the centralized transaction as an example, results show that the proposed mechanism can effectively provide market entities more chances to win contracts, and enhance the market liquidity.

Intention to adopt cryptocurrency: a robust contribution of trust and the theory of planned behavior

PurposeAt present, the adoption of cryptocurrency investment has brought consideration to the globe. The present paper attempts to investigate the intention to adopt cryptocurrency (IACR) among the potential investors of Pakistan.Design/methodology/approachThe theory of planned behavior (TPB) is applied to underpin the conceptual framework. The study uses a quantitative approach. The study collects cross-sectional data through an online survey questionnaire. In the last, the authors utilized 334 samples for outcomes.FindingsFindings of the SEM reveal a significant positive effect of attitude, subjective norms (SNs), perceived behavioral control (PBC) and trust on IACR.Practical implicationsThe outcomes of an investigation would develop further intention and trust towards cryptocurrency adoption. The results would support developing favorable policies regarding the reduction of the ban on cryptocurrency in Pakistan to make easier transactions of the investors further. Possibly, it brings several opportunities in all segments of society in making the digital transaction modes through cryptocurrency. Finally, the findings would further validate the TPB in the context of cryptocurrency.Originality/valueThe study provides a better understanding of cryptocurrency and investors IACR. The empirical evidence further develops the other individuals' intentions towards cryptocurrency usage.

Role of Reputation in Sustainable Performance of Online Crowdsourcing Vendors: An Explanation From Transaction Cost Theory

This study reveals a new finding on the impact of reputation growth on crowdsourcing vendors’ sustainable performance in different modes of markets using fixed-effect panel data regression models. To this end, we extract data from a large Chinese crowdsourcing platform named zbj.com for the period of 2012–2014, which was a key stage for the establishment of market diversification. Based on different transaction modes, the study divides the markets on the crowdsourcing platform into task-based market (TBM) and employment market (EPM). By applying the multiple framework, the empirical results exhibit a negative and significant effect of vendors’ reputation on participation rate (PR) in TBM and EPM. At the same time, reputation also has a consistent effect on vendors’ revenue share (RS) of each market. Moreover, this study shows that the significant reputation impact on PR and RS of EPM will be, respectively, weakened and strengthened in fixed-price mode and customized mode when vendors participate more in large-scale projects. The findings suggest that the growth of reputation will promote market transfer of vendors, that is, showing different sustainability in different markets, which will lead to uneven development of the crowdsourcing markets. By adopting the perspective of transaction cost theory (TCT), this study elaborates and analyses these phenomena and derives corresponding policy implications.

Applicability evaluation of blockchain technology in distributed power transaction

With the proposal of peaking carbon dioxide emissions and carbon neutrality target, distributed generation, especially distributed renewable energy generation, will play a more and more important role in the future power system and become the main source of power supply. The rapid development of blockchain technology provides more imagination and development opportunities for distributed power transaction. Its security, decentralization and rapidity are very suitable for distributed power transaction. This paper analyzes the key factors affecting the level of distributed power transaction, establishes the applicability model of various transaction modes for distributed transaction, analyzes the applicability of blockchain technology for distributed transaction, and puts forward the improvement direction of blockchain technology in distributed power transaction in the future.

The Bilateral Negotiation or Centralized Bidding? How to Choose the Transaction Mode with Power Users for Power Plants

At present, there are mainly two kinds of transaction modes in the power market: bilateral negotiation mode and centralized bidding mode. Bilateral negotiation mode means users' purchases power directly from power plants, whereas centralized bidding mode means power plants and power users conduct power transactions through a Power Trading Center. This paper adopts evolutionary game theory to model this mechanism and explores the behavioral patterns of different entities at equilibrium. This paper is organized as follows. First, we build an evolutionary game model of this mechanism. Then, we discuss the existence and stability of equilibrium outcomes. Furthermore, we compare the equilibrium results under different conditions. We find that different market supply‐demand conditions lead to different equilibrium outcomes. Besides, we find that the bilateral negotiation mode does not necessarily improve the overall profit of the power market. When the demand exceeds the supply in the centralized bidding market, introducing the bilateral negotiation mode would reduce the overall market profit. In addition, the increase of the bidding heterogeneity leads to the increase of profits of power plants in the market. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

A Mixed-Integer Linear Programming for Nodal Clearing Price in Day Ahead Market Considering Security Constraints

A nodal clearing price model in day ahead market considering security constraints is established. First, the intra-region and inter-region transaction modes are explained, and the order types are shown. The clearing model takes the total social welfare as the goal, considers the security constraints of the network, and specifies the market clearing price expressed by the Lagrangian multiplier. Then the mixed linear programming algorithm is used to solve the model in this paper, and a verification method based on the N-1 criterion is performed. Finally, a numerical case is performed to calculate the clearing price of the network, which illustrates the effectiveness of the proposed method and model.

Research on Profit Maximization of New Retail E-Commerce Based on Blockchain Technology

With the development of science and technology and the extension of online users, e-commerce platforms gradually and effectively gather social resources such as manpower, technology, production, and capital. More and more traditional enterprises combine online and offline business as their operation and trade methods. E-commerce, as a new channel, has become one of the main transaction modes in the society. Under the background of reform of the supply side, and with the high-speed development of E-commerce, we will promote stock adjustment through incremental reform and optimize the structure of investment and financing in the process of increasing investment of e-commerce enterprises. High-quality products and diverse trading experience are the new development pattern in e-commerce. There are different profit maximization strategies for e-commerce enterprises when they face different economic situations. Besides, cross-border business is an advised way to expand business when the enterprise is under bigger profit. Via all these methods, e-commerce enterprise can help to optimize the structure of industries, circulation, and consumption and promote resource integration and optimization, and people’s living standards will be further improved. Finally, the e-commerce enterprise profit maximization will come true.

Internet and firm development

Purpose This paper aims to provide a survey of existing literature on the economic impacts of the internet on firm development, and outlines an overall framework of the existing studies. The purpose is to show how the internet affects firm development, which may help policymakers and other researchers to have a better knowledge of existing research characteristics, problems and future directions. Design/methodology/approach The authors review the studies on the economic impacts of the internet on firm characteristics and external environment, identify the characteristics of the existing literature and problems and discuss the directions of possible future research. Findings The authors find that the impacts of the internet on firm development mainly display two relevant mechanisms (firm characteristics and external environment), and they can be grouped into six channels (firm innovation, firm business mode, firm performance, firm productivity, firm import and export trade and firm location selection). Originality/value This study builds up a framework of how the internet impacts on firm development, which can add value to the future research of firm intelligent transaction modes in the crowd intelligence network.

Network loss management and allocating the transmission losses to loads and generation units according to their transactions

During recent years, allocating the network losses to loads and generation units based on network transactions is an important issue in the power industry. This study presents an appropriate method to allocate the network losses to loads and generation units according to their network transactions. This method is appropriate and faster than other loss allocation techniques and does not consider unreasonable assumptions in the loss allocation process. This method explicitly assigns the network losses according to individual transactions, and this leads to allocate the network losses among all network transactions. This approach is based on the share of the loads and generation units on active and reactive power flows passing through the lines according to transactions. The implementation of the method on large networks is simple and fast. To approve the performance of the presented method, the proposed loss allocation technique has been applied to a three-bus case study system and the IEEE 14-bus test system. Also, several different transaction modes are used to show the performance of the presented method for transmission loss allocation based on transactions.

Intelligent transaction: definition, modes, and research directions

Purpose In the crowd intelligence networking era, the smart connections of human, machines and things enable point-to-point trustable transactions and distributed efficient collaboration; the smart connections among government, enterprises, organizations and the public would enable active participation of the public in society management and decision-making and improve the efficiency of government management and services. All interactions among various agents can be viewed as the transaction activity. The social division of labor system drives the evolution of transaction. The transaction mode also differentiated into different patterns with the development of human society. What will be the intelligent transaction in the crowd intelligence networking era? What will be the transactions modes and rules in the crowd intelligence networking era? The answers to these questions are of great importance to the future development of transactions. Design/methodology/approach The authors review the evolution of traditional transaction and transaction modes and analyze the driving forces of it. They attempt to give the definitions of intelligent transaction and intelligent transaction mode. They also review the traditional transaction modes and rules, analyze the characteristics of the intelligent transaction and classify the intelligent transaction modes. Findings The authors find the intelligent transaction is mainly reflected in the intellectualization of transaction subject, transaction object and transaction process. They summarize the characteristics of intelligent transaction and develop four modes for the intelligent transactions based on the modularization level of the transaction objects and the quantity of transaction subjects, including the demand side and the supply side. The authors also show representative examples to further illustrate rules and features of these transaction modes and point out the potential research directions. Originality/value This study is among the first to analyze the characteristics of the intelligent transaction, and the proposed division framework of the intelligent transaction modes could not only add value to the future research of intelligent transaction modes and rules but also help to guide the transactions in the crowd intelligence network.

Identification of Key Influencing Factors of Sustainable Development for Traditional Power Generation Groups in a Market by Applying an Extended MCDM Model

With the deepening reform of the power market, the external environment of China’s power industry is going through a huge change. China’s traditional power generation groups (TPGGs), with assets all over the country, are, due to a lack of market awareness about energy policies, facing serious challenges in developing competitive advantages, improving power transaction modes, optimizing profit models, and even realizing basic corporate strategies. In this study, we focus on identifying the key factors influencing sustainable development in an unprecedented market environment for TPGGs, so as to achieve overall sustainable development for the whole power generation sector in China. A hybrid framework based on Multiple-Criteria Decision-Making (MCDM) was proposed to recognize the key influencing factors under vague rule conditions. We developed a novel method combining three different MCDM methods with triangular fuzzy numbers (TFNs), fuzzy Delphi, fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL), and Analytic Network Process (ANP), to cover uncertainty and make the problem-solving approach closer to the actual problem. A series of analyses indicate that the final 14 factors covering the five dimensions are considered to be important factors in the sustainable development of TPGGs. Based on the results, it can be said that “Gross energy margin” and “Pricing bidding strategy” dominate the impacts of TPGG’s sustainable development. Finally, we give some advice relating to practical measures to help TPGGs achieve sustainable development in the market-oriented industry environment.