Trade Information Research Articles

Examining the inconsistency of mercury flow in post-Minamata Convention global trade concerning artisanal and small-scale gold mining activity

In 2017, the Minamata Convention (MC) on mercury (Hg) control entered into force. However, whether the MC is effective and how it reshapes the global Hg flow remain unclear. In this study, we established a method to detect inconsistencies in data on global Hg trade, and calculated the gap between the demand and supply of Hg to the artisanal and small-scale gold mining (ASGM) sector (i.e., the largest source of Hg emissions globally) in 39 countries across four regions. According to our results, inconsistencies in statistical data concerning Hg for ASGM activities exist in both Africa and Central and South America. Asia showed a considerably lower amount of Hg applied to ASGM than apparent Hg consumption; nevertheless, the largest consumer of Hg was Asia, predominantly China and India. Many countries in which ASGM is conducted are already MC parties; however, only few submitted their national action plans (NAPs) or have established/enforced specific laws to curb Hg use in ASGM. Analysis of Hg-related trade information suggests that in 2017, the trade of metallic Hg disappeared in some African and Central and South American countries, but new trade flows of goods with higher Hg content emerged. The method established in this study can support the search for countries implementing ASGM with hidden Hg use and flows, thereby contributing to the planning of further Hg control regulations. To enforce sound Hg management, the submission of NAPs should also be promoted in addition to the expansion of MC parties.

The Impact of Digital Economy of Resource-Based City on Carbon Emissions Trading by Blockchain Technology.

To reduce the carbon emission intensity of resource-based cities and strengthen the sustainable development of these cities, firstly, blockchain technology is analyzed. Secondly, the development of the digital economy is discussed in digital resource-based cities. Finally, according to blockchain technology, a model of carbon emissions trading in the digital economy is designed, and the specific impact of the digital economy on carbon emissions trading is studied according to the model. The research results show that the mean value of the development index of the digital economy (digital) is −0.0168, the maximum value is 4.2560, the minimum value is −1.3429, and the standard deviation is 0.9572, indicating that the quality of digital economy development varies greatly among different regions. And according to the results of the digital model, it is found that the regression coefficient of the variable digital is significantly negative at the 1% level, showing that the digital economy will obviously suppress the carbon emission intensity of cities. After replacing the explained variables, the coefficient of the digital economy is still significantly negative. It indicates that the development of the digital economy can effectively suppress the carbon emission intensity of urban. Therefore, the designed model of carbon emissions trading under the blockchain technology can not only provide a secure platform for carbon emissions trading but also provide more comprehensive trading reference information for carbon emissions trading. It provides technical support for reducing the carbon emission intensity of resource-based cities and also contributes to the development of resource-based cities.

Trends in elephant poaching in the Mid‐Zambezi Valley, Zimbabwe: Lessons learnt and future outlook

Trends in elephant poaching in the <scp>Mid‐Zambezi</scp> Valley, Zimbabwe: Lessons learnt and future outlook

Do Information Communication Technology and Economic Development Impact Environmental Degradation? Evidence From the GCC Countries

The environmental variations compel global countries for restructuring economic growth policies to ensure reliable energy usage. Ecological sustainability is a leading concern of the world for adequate and smooth survival of human beings. The inefficiency of technology is a focal hindrance to attaining the sustainable environment goal. This research aims to probe the cointegration and causal relationship among information communication technology, CO2 emission, economic development, trade, and total population for GCC countries, namely, the United Arab Emirates, Saudi Arabia, Qatar, Oman, Kuwait, and Bahrain, from 2000 to 2018. This research approached the unit-root tests, cointegration test, and FMOLS and DOLS test to determine stationarity of data series, cointegration relationship among variables, and the short- and long-run relationship among variables, respectively. The results of the analytical procession by employing FMOLS and DOLS confirmed that CO2 emission, ICT, and ED are positively significant, while POP was negatively substantial at a 1% level. No relation has been observed between trade and CO2 emission. The long-run relationship among variables is confirmed by FMOLS and DOLS analyses. A negative relationship between population growth and CO2 emission is observed. It is ideal for enhancing environmental sustainability by awareness of people’s importance to the environment. The GCC countries should transform or divide their economic growth sectors instead of only the fossil fuel sector. This research also enlightened the way to reduce environmental destruction by the attraction of foreign investments in other sectors compared to entire fossil fuel industries, and the information communication technologies also move toward green technology using environmentally friendly energy resources.

Construction Model of E-Commerce Agricultural Product Online Marketing System Based on Blockchain and Improved Genetic Algorithm

To build an agricultural product network marketing system in the era of e-commerce, it is necessary for agricultural product business enterprises or farmers to recognize the benefits of using e-commerce to market agricultural products and face up to its influencing factors and to build a support system, application system, and guarantee system with the support of the government to promote agricultural product e-commerce marketing to obtain healthy development. In this study, we study the construction mode of e-commerce agricultural product online marketing system based on the end of blockchain and improved genetic algorithm. This study adopts the design idea of coalition chain and proposes a multichain agricultural product trading information blockchain application technology including agricultural product trading information chain, user information chain, and agricultural product information chain. The agricultural product information chain provides detailed information of agricultural products and ensures the traceability and non-tamperability of the information. It automatically divides the profits of transactions through smart contracts to improve execution efficiency and reduce transaction costs and finally establishes a transparent, efficient, and applicable blockchain architecture for agricultural product transactions.

Event-Based Supply Chain Network Modeling: Blockchain for Good Coffee

Blockchain and distributed ledger technology (BC/DLT) provides distributed databases with decentralized governance, tamper-proof recording, high availability and non-copyable digital assets, which have made it a natural technological basis for supply chain management. In this paper, we introduce REALISTIC, a novel event-based modeling framework for supply chain networks (SCNs) that includes production processes. It extends McCarty’s Resources-Events-Agents (REA) accounting model with secure transformations, which, across the entire SCN, guarantee that certified output resources cannot be digitally produced ex nihilo, but require certified input resources of at least the same amount as what is produced. This generalizes the no-double-spend guarantee of current BC/DLT to (digital twins of) physical resources and their production. Authenticated human or robotic Internet of Things (IoT) actors digitally sign and cryptographically commit to the veracity of real-world events on an immutable database, without having to take responsibility for their aggregate consequences. User-specifiable interpretations, corresponding to queries and analytical functions in database systems, provide auditable aggregate information computed from recorded events across the entire SCN. This includes fine-grained and trustworthy tracing of final products through multiple stages of production processes, semi-finished products, quality certifications and transportation all the way back to their raw materials. We present a case study for an end-to-end coffee supply chain that tracks fine-grained and detailed information from a farmer’s coffee cherries to retail coffee bags, involving all its actors. Our model handles product provenance; auditable sustainability, quality and trade information; production processes from parchment via green to roasted coffee; product quality tests; farmer certifications; and transportation across the entire coffee supply chain. It is based on field work involving farmers, cooperatives, processors, traders, importers, and a major roasting company stretching from Colombia to Scandinavia. Its REALISTIC-based modeling is the foundation for the design of our prototype implementation, which includes Ethereum blockchain code, RDBMS-based server code and a web app client. Their source code is publicly available on GitHub.

The Decomposition of Information and Communication Technology Products Trading: A Case Study of China

Technology is recognised as one of the most important factors in world economic development, particularly contributing to the trade growth of information and communications technology (ICT) products. The decomposition of export growth has been a popular way to analyse how trade has been influenced since 2000. However, there is little investigation regarding the structure of ICT product trading of China, which is the de facto largest trader of ICT goods export and import. This paper contributes to the existing methods with a non-parametric model. The coefficient estimates which functions of their factors represent a dynamic analysis of the factors’ influence on decomposed trade growth. The empirical study shows that China’s strategy tends to be conservative, as the growth of trade to developed countries mostly came from the volume increase of existing trade lines instead of the increase of trade varieties. Suggestions include that the trade growth could benefit from resource reallocation in ICT industries and the procedure simplification of exporting ICT products. This paper also provides empirical evidence that the Belt and Road Initiative (BRI) increased the trading volume and frequency by completing the transportation chain and decreasing the variable trade costs. Furthermore, suggestions are provided on improving the impact on the globalisation of ICT.

Investigation on buying behaviour and awareness in online shopping with special reference to consumer purchasing product

Electronic business, regularly known as web based business is a sort of industry, where purchasing and offering of items or administrations are directed over electronic frameworks, for example, the web and other PC systems. Electronic business draws on innovations, for example, portable trade, electronic finances exchange, store network administration, web advertising, online exchange handling, electronic information trade (EDI), stock administration frameworks and robotized information accumulation frameworks. Current electronic trade regularly utilizes the Internet in any event at one point in the exchange's lifecycle, despite the fact that it might include a more extensive scope of innovations, for example, email, cell phones, web based life and phones also. In this manner, it very well may be ascribed that electronic trade is by and large thought to be the business part of e-business. It additionally comprises of the trading of information to encourage the financing and installment parts of business exchanges. This examination center around viability of procurement on buyer merchandise towards online shopping discovering office and quality of internet obtaining and having potential wellsprings of utilizing on the online shopping.

TINJAUAN HUKUM TANDA TANGAN ELEKTRONIK (DIGITAL SIGNATURE) DALAM PERJANJIAN DAN TRANSAKSI ELEKTRONIK (E-COMMERCE)

This study discusses the Legal Review Analysis of the Use of Electronic Signatures (Digital Signature) in Electronic Agreements and Transactions (E-Commerce). In information gathering strategy, the writer uses a writing concentrate approach, which is the single technique used in standardizing halal exploration. Where the writer searches for and then researches, studies, analyzes, sorts, codes material or writing in the library and then turns it into the purpose of the examination to be discussed. The results of the research found that the position and legal power of electronic marks as evidence can be considered substantial with the assumption that the electronic mark uses an electronic structure that is in accordance with the laws and regulations in Indonesia. This refers to Article 11 of Government Regulation Number 11 of 2008 concerning Electronic and Information Trading. These guidelines state an endorsement that regardless of whether it is simply a code, an electronic mark has legal force and legal effect. The requirements as referred to in Article 11 of the ITE Guidelines are essential requirements that must be met for every electronic brand. Electronic evidence for this condition electronic alerts can have great power if the information is undeniable, representable, possible, and proven, further demonstrating what happened. Confirmation of the appearance of the power individual must have the option to provide information in his possession is from the beginning of the secret electrical framework

Deterrence effect of risk aversion information sharing on supplier encroachment

This paper investigates the incentive of a fashion retailer to share her risk aversion information unde[r potential supplier encroachment. In fashion industries, retailers tend to be risk averse when facing uncertain market demand and the threat of supplier encroachment. Although conventional wisdom suggests that a risk-averse retailer should not expose her risk concerns to the upstream supplier, our results show that the retailer may voluntarily share private risk aversion information ex ante to deter supplier encroachment when her selling cost advantage is in an intermediate range, or trade information for some side payment when her cost advantage is small. However, when the retailer’s cost advantage is large or the supplier ex ante encroaches on the market, the retailer will never divulge private information regardless of whether the supplier offers a side payment. Moreover, we examine the retailer’s incentive for information disclosure from an ex post perspective. Specifically, when the supplier’s selling cost is either high or low, the unobservability of information acquisition enables the retailer to selectively withhold unfavourable risk aversion information; otherwise, the firms are engaged in a tacit bargaining, and their efforts to reach a consensus thwart the supplier’s incentive for encroachment.

Value of Information: Exploring Behavioral and Social Factors

There is growing interest within and beyond the economics community in assessing the value of information (VOI) used in decision making. VOI assessments often do not consider the complex behavioral and social factors that affect the perception, valuation, and use of information by individuals and groups. Additionally, VOI assessments frequently do not examine the full suite of interactions and outcomes affecting different groups or individuals. The behavioral and social factors that we mention are often (but not always) innately-derived, less-than-conscious influences that reflect human and societal adaptations to the past. We first discuss these concepts in the context of the recognition and use of information for decision making. We then find fifteen different aspects of value and information pertinent to VOI assessments. We examine methodologies and issues related to current VOI estimation practices in economics. Building on this examination, we explore the perceptions, social factors, and behavioral factors affecting information sharing, prioritization, valuation, and discounting. Information and valuation issues are then considered in the context of information production, information trading and controls, and information communication pathologies. Lastly, we describe issues relating to information useability and actionability. Our examples mention the value and use of geospatial information, and more generally concern societal issues relating to the management of natural resources, environments, and natural and anthropogenic hazards. Our paper aims to be instrumentally relevant to anyone interested in the use and value of science.

Reporting delays and the information content of off‐market trades

AbstractThis paper examines the impact of reporting delays in off‐market trades on informed trading and information efficiency. We examine this issue using a natural experiment in Financial Times Stock Exchange futures contracts provided by the Intercontinental Exchange, which eliminated the ability of market participants to request a delay in reporting smaller sized off‐market trades in 2018. We find that, while reporting delays increase the time taken to release information to the market by the length of the reporting delay, thereby prima facie reducing information efficiency, such delays encourage informed trading and potentially increase the informativeness of trading and, therefore, information efficiency.

Informativeness of trades around macroeconomic announcements in the foreign exchange market

• We study the extent of private information revealed through trades in the foreign exchange market. • We find the intraday variation in the proportion of permanent price variations driven by trade-related information has a repetitive periodic pattern, • We show the information share of private information in trades evolves across trading periods in the FX markets. • We find that, among market participants, heterogeneous interpretation of announcements and opinion disagreement after the announcement are revealed from order flow, and the efficient price is still driven by information implicit in trading activities after the announcement. We study the extent to which private information is revealed through trades in the foreign exchange market. The trade informativeness measured from the VAR framework of trades and quotes allows us to quantify the impact of asymmetric information on return variation. We find the intraday variation in the proportion of permanent price variation driven by trade-related information has a repetitive periodic pattern, and trades in the overlapping trading hours of London and New York carry most information than the other time segments. The results show the fraction of trade-related component to exchange rate variation positively relates to trading volume and reversely relates to effective spread. With a comprehensive set of 48 real-time US, European, and Japanese macroeconomic news surprises variables, and controlling for the effect of trading volume, spread, and volatility, we find news of production-related economic indicator, e.g., GDP and industrial production, has a positive relationship with the trade informativeness in a trading period, suggesting the increased private information share may be attributed to heterogeneous interpretations of the announcement among market participants. Announcement-related information is gradually resolved into the price, and the information is transited via the channel of trading activities.

Digital economy integration in Asia and the Pacific: Insights from DigiSRII 1.0

This paper presents the results from using the Digital and Sustainable Regional Integration Index version 1 (DigiSRII 1.0) framework of ESCAP (2020b) to uncover digital economy integration trends across the Asia-Pacific region. The results show that Asia and the Pacific has made good progress with regard to conventional digital economy integration, especially because of the significant improvements in the digital economy infrastructure and liberalization of trade of information and communications technology (ICT) goods. However, capacity-building of the workforce and investment in infrastructure are required to bridge the digitalization gaps among the digitalized economies in the region. Moreover, the fairly low regulatory uniformity among regional economies further highlights the importance of regional regulatory harmonization in order to foster regional trade in digitally enabled goods and services. From a sustainable development perspective, inclusivity and equity of access to digitalization and required infrastructure remain key challenges. While Internet penetration in the region has been rising, female participation in the digital economy has remained relatively low in general and extremely low in lowincome economies. In addition, there is room to enhance cybersecurity in most Asia-Pacific economies. Regional digital policies should focus on harmonizing data protection protocols and building a safer network of servers that would promote economic activity and enable sensitive matters to be conducted online. Fostering a more inclusive digital transformation may considerably boost network-effects and accelerate the transition to a competitive and sustainable regional digital economy.

Consumer Price Prediction using Machine Learning Algorithms

Now a day in the economy, there is a profound impact of the Consumer market or equity market. Prediction of stock prices is extremely complex, chaotic, and the presence of a dynamic environment makes it a great challenge. Behavioral finance suggests that decision-making process of investors is to a very great extent influenced by the emotions and sentiments in response to particular news. Thus, to support the decisions of the investors, we have presented an approach combining two distinct fields for analysis of stock exchange. The system combines price prediction based on historical and real-time data along with news analysis. LSTM (Long Short-Term Memory) is used for predicting. It takes the latest trading information and analysis indicators as its input. For news analysis, only the relevant and live news is collected from a large set of business new. The filtered news is analyzed to predict sentiment around companies. The results of both analyses are integrated together to get a response which gives a recommendation for future increases.

Consumer Price Prediction using Machine Learning Algorithms

Now a day in the economy, there is a profound impact of the Consumer market or equity market. Prediction of stock prices is extremely complex, chaotic, and the presence of a dynamic environment makes it a great challenge. Behavioral finance suggests that decision-making process of investors is to a very great extent influenced by the emotions and sentiments in response to particular news. Thus, to support the decisions of the investors, we have presented an approach combining two distinct fields for analysis of stock exchange. The system combines price prediction based on historical and real-time data along with news analysis. LSTM (Long Short-Term Memory) is used for predicting. It takes the latest trading information and analysis indicators as its input. For news analysis, only the relevant and live news is collected from a large set of business new. The filtered news is analyzed to predict sentiment around companies. The results of both analyses are integrated together to get a response which gives a recommendation for future increases.

Information and dynamic trading with the Gambler’s fallacy

Information and dynamic trading with the Gambler’s fallacy

Joint optimization of e-commerce supply chain financing strategy and channel contract

With the rise of the e-economy, online retailers, which are often financial-constrained, can choose to borrow from e-commerce platforms in addition to traditional financial institutions. Many e-commerce platforms adopt two types of market channel cooperation contracts: Reselling or Marketplace. We model their interaction as a Stackelberg game, studying the interaction between the financing strategies of the online retailers and the channel sales cooperation contracts of the e-commerce platforms. We observe the characteristics and applicable conditions in four modes. Results show that the working capital level of the online retailer will affect the preferences of both parties. Specifically, when working capital is low, platform direct financing has no advantage over bank financing. By contrast, a higher level will affect the operational decisions of the e-commerce platform, mainly due to the trade-off between sales revenue and interest income. Combined with the characteristics of online trading information collected by e-commerce platforms, we find that platform can provide a means of risk control to guarantee the benefits of both parties and solve the financing dilemma caused by low working capital. We further determine that the fixed commission rate of the platform should not be too large, otherwise the profits of the online retailer will be greatly weakened. This paper proves the necessity of the existence of transfer payment platform usage fee. Our findings not only complement the emerging online marketplace literature for e-commerce platforms but also provide enlightenment on working capital management for small and medium-sized enterprises and self-employed individuals such as online retailers.

Mobile Wireless Rechargeable UAV Networks: Challenges and Solutions

Unmanned aerial vehicles (UAVs) can help facilitate cost-effective and flexible service provisioning in future smart cities. Nevertheless, UAV applications generally suffer severe flight time limitations due to constrained onboard battery capacity, causing a necessity of frequent battery recharging or replacement when performing persistent missions. Utilizing wireless mobile chargers, such as vehicles with wireless charging equipment for on-demand self-recharging has been envisioned as a promising solution to address this issue. In this article, we present a comprehensive study of \underline{v}ehicle-assisted \underline{w}ireless rechargeable \underline{U}AV \underline{n}etworks (VWUNs) to promote on-demand, secure, and efficient UAV recharging services. Specifically, we first discuss the opportunities and challenges of deploying VWUNs and review state-of-the-art solutions in this field. We then propose a secure and privacy-preserving VWUN framework for UAVs and ground vehicles based on differential privacy (DP). Within this framework, an online double auction mechanism is developed for optimal charging scheduling, and a two-phase DP algorithm is devised to preserve the sensitive bidding and energy trading information of participants. Experimental results demonstrate that the proposed framework can effectively enhance charging efficiency and security. Finally, we outline promising directions for future research in this emerging field.

A STUDY ON FINANCIAL PERFORMANCE OF S.M.I.L.E MICROFINANCE LIMITED

Microfinance at first has been a type of deliberate assistance to the most denied populace. In any case, today it addresses a market answer for alleviation of destitution and goes about as a turn of events and financial device in achieving monetary consideration in India. Microfinance has arisen as a practical choice to come to the until recently unreached for their social and financial strengthening through friendly and monetary inter- mediation. The establishments that are giving microfinance administrations, for example, reserve funds, credit, protection and settlement administrations to poor are called Microfinance Institutions (MFIs). The review focuses on investigating the monetary presentation of S.M.I.L.E MICROFINANCE Restricted. The information have been gathered from the Microfinance Information Trade from the financial year 2015 to 2019. The measurable devices, to be specific, Descriptive insights and development rates have been utilized for investigating the information.. As far as in general monetary execution, Indian MFIs have better ROE and OSS. Indian MFIs have shown higher monetary income by resources, the yield on gross portfolio (ostensible) and lower working cost by resources, yet at the same time it couldn't cover the complete cost and monetary costs. In truth, Indian MFIs have uncovered better effectiveness and efficiency as estimated by working cost by advance portfolio, normal compensation by GNI per capita and advances per staff part.