Evaluation of a software positioning tool to support SMEs in adoption of big data analytics

Big data analytics has been widely adopted by large companies to achieve measurable benefits including increased profitability,customer demand forecasting,cheaper development of products,and improved stock control.Small and medium sized enterprises(SMEs)are the backbone of the global economy,comprising of 90%of businesses worldwide.However,only 10%SMEs have adopted big data analytics despite the competitive advantage they could achieve.Previous research has analysed the barriers to adoption and a strategic framework has been developed to help SMEs adopt big data analytics.The framework was converted into a scoring tool which has been applied to multiple case studies of SMEs in the UK.This paper documents the process of evaluating the framework based on the structured feedback from a focus group composed of experienced practitioners.The results of the evaluation are presented with a discussion on the results,and the paper concludes with recommendations to improve the scoring tool based on the proposed framework.The research demonstrates that this positioning tool is beneficial for SMEs to achieve competitive advantages by increasing the application of business intelligence and big data analytics.

Impact of carbon disclosure on debt financing costs

Creditors,such as banks,often use disclosed environmental information to assess a company’s environmental risk and ensure the safety of debt funds.Consequently,carbon disclosures have become an important consideration for creditors when making investments.This study explores the relationship between carbon disclosure and debt financing costs using data on listed companies from 2008 to 2019.The results show that carbon disclosure can reduce the debt financing costs of enterprises,and that this influence is more significant for private companies than for state-owned enterprises.Instrumental variables and Propensity Score Matching(PSM)were used to evaluate the robustness of negative relationships.Furthermore,carbon disclosure has a more significant impact on debt costs with less environmental supervision pressure,weak residents’environmental awareness,and weak product market competition.These findings provide guidance for companies’carbon information disclosure and support the establishment of official carbon disclosure standards.

State-Owned Capital Participation in Private Enterprises:A Perspective of Debt Financing

This study takes debt financing as the entry point and explores the impact of state-owned capital participation in private enterprises from the perspectives of“unarticulated rules”and“articulated rules”.The study finds that state-owned capital participation significantly reduces the debt financing costs of private enterprises and expands the scale of their debt financing.This conclusion remains valid after a series of endogeneity and robustness tests.Further analysis of the mechanism reveals that state-owned capital participation improves the debt financing of private enterprises through multiple channels:Enhancing their social reputation,mitigating the“statistical bias”they face,optimizing their information quality,and reducing the“shareholder-creditor”agency problems.This paper conceptualizes these benefits as the“complementary advantages of heterogeneous shareholders”.This not only constructs a theoretical framework for“reverse mixed-ownership reform”but also better narrates the Chinese story of“mixed-ownership reform”by adopting a more universally applicable theory of equity structure.Additionally,the paper supplements existing research on the macro-and meso-level relationship between the government and the market by exploring the government’s positive role at the micro-level.

The Study on the Problem of the Relationship between the “Heterogeneity” of the Neighbor Enterprise and the Financing Efficiency of SMEs in China<br/>—Empirical Data from China Industrial Enterprises Database

This article tries to introduce the perspective of the “heterogeneity” of the neighbor enterprise into the research on the problem of the financing efficiency of the small and medium sized enterprises (SMEs). It takes enterprises in the China industrial enterprises database from 2005 to 2007 as the object of the research and defines the neighbor enterprise at a town (village, street) scale. This article selects the financing efficiency, enterprise scale, technical innovation of enterprise as the indexes to measure the “heterogeneity” of the neighbor enterprise, and examines whether they have a significant relationship with the enterprises themselves or not. Through building panel data model and the empirical analysis, this article finds that the financing efficiency and the degree of technological innovation of the neighbor enterprise are positively related to the financing efficiency of enterprises themselves, and the scale of the neighbor enterprise has a negative correlation with the financing efficiency of enterprises themselves. What’s more, this paper distinguishes the neighbor enterprise from the industry unusual neighbor according to whether enterprises are belong to the same industry or not at the same town(village, street), finding the neighbor enterprises which are the same industry have a great more relationship with the financing efficiency of SMEs than the neighbor enterprises which are the non trade.

基于SMES装置的车网系统低频振荡抑制策略

近年来,我国电气化铁路发生多起因牵引网网压低频振荡导致的机车保护装置误动作事故,对铁路安全运行造成严重的威胁.现有抑制策略多从机车侧开展,通过对机车控制器参数的修订实现抑制效果,但对于铁路行业的长远发展缺乏灵活性.针对车网系统低频振荡问题,提出从牵引网侧外接超导磁储能(Superconducting Magnetic Energy Storage,SMES)的动态抑制方案.首先,分析SMES抑制车网系统低频振荡的原理,根据车网系统低频振荡的走势对其进行分类,并依据振荡类型设定SMES接入准则;其次,建立车网系统等效阻抗模型,结合阻抗比判据和伯德图分析车网系统稳定性,对SMES接入车网系统前后系统稳定性对比分析,验证所提方案的有效性,并与传统抑制方法进行对比,验证所提方案的灵活性;最后,对单车及多车升弓并网情况下的车网系统进行仿真分析.结果表明:SMES装置接入车网系统后可快速有效地抑制车网系统低频振荡.

电网不平衡下SMES变流器动态演化控制策略研究

针对超导磁储能(SMES)变流器在电网电压不平衡下的工作情况,提出一种新型非线性控制策略,即动态演化控制(DEC)。该控制方法相较于传统PI控制能有效地减小SMES因电网电压不平衡而产生的三相电流畸变以及有功、无功功率产生的二次谐波。文中根据电网不平衡下SMES变流器的工作情况设置三个工作目标;建立了基于DEC的不平衡控制方程,并在Simulink中搭建模型进行仿真分析。通过与传统PI控制作对比,DEC控制具有更强的鲁棒性,更快速的响应能力,理论分析和仿真结果验证了该控制策略的可行性和有效性。

基于MPC的SMES多目标控制

模型预测控制(model predictive control,MPC)性能优越,响应迅速而且可实现多目标控制,已受到广泛关注并逐步应用于大功率变流器,特别是在具有高功重比的超导储能磁体(superconductor magnetics energy storage,SMES)控制系统中,应用前景十分广阔。本文提出的基于MPC的SMES多目标控制,不仅实现SMES线圈在储能时较高精度的电流跟踪,同时可控制SMES线圈充放电时电流变化速率,避免较大的电流冲击,而且能够提高其响应速度与精度。通过搭建仿真实验平台验证了本文提出的SMES系统储能稳流性能、功率平衡稳定性能、动态性能以及充放电速率的控制性能。并与基于PI控制的系统进行比较,结果表明基于模型预测控制的SMES系统不仅可以实现稳态时较高精度的电流跟踪,而且可以实现充放电时电流变化速率的控制。

Universal Health Coverage in Somalia: Charting the Path to Equitable Healthcare Financing and Governance

Somalia is a country facing numerous challenges in achieving universal health coverage (UHC) and ensuring adequate healthcare financing, This article explores the complexities and obstacles that Somalia must overcome in its pursuit of UHC, the paper begins by providing an overview of the current healthcare landscape in Somalia, highlighting the lack of infrastructure, political instability, and limited financial resources that hinder the establishment of a comprehensive and equitable healthcare system. It then examines the role of international aid and non-governmental organizations (NGOs) in filling the healthcare gap, while emphasizing the need for a more sustainable, domestically financed solution. Drawing on a range of data sources and case studies, the article proposes a multi-faceted approach to strengthen healthcare governance, improve resource allocation, and foster local capacity building, the study delves into the unique obstacles that Somalia faces, including a lack of infrastructure, political instability, and limited financial resources, which hinder the establishment of a comprehensive and equitable healthcare system. The paper also examines the role of international aid and non-governmental organizations (NGOs) in filling the healthcare gap, while highlighting the need for a more sustainable, domestically financed solution. The findings underscore the importance of political commitment, international cooperation, and innovative financing mechanisms in advancing towards UHC in Somalia, providing valuable insights for other low resource, conflict affected settings.

Impact of ICTs on Core Competences of SMEs in Bukavu, DRC

Currently, it has been noticed a strong use of ICTs in several companies. The objective of this study was to analyze and measure the impact of the implementation of ICTs on the strategy and structure of management of core competence in SMEs in Bukavu, DRC. The scale used shows the good psychometric properties (χ2 = 75.045;P = 0.16;χ2/ddl = 1.471;CFI = 0.92;IFI = 0.92;RMSEA = 0.049;NFI = 0.79;GFI = 0.94;AGFI = 0.91. This study analyzed primary data collected from 195 SMEs in the city of Bukavu. Data processing was achieved using exploratory and confirmatory factor analysis and flat sorting. The results indicate that the use of ICTs by SME managers in the city of Bukavu has a positive impact on all dimensions of core competence selected in this study. They also reveal that the views of these leaders on the importance attached to the adoption of ICTs were divided and the level of ICT use was above average.

Trade credit financing for supply chain coordination under financial challenges:a multi‑leader–follower game approach

This study is designed to solve supply chain inefficiencies caused by some members’financial problems,such as capital shortages and financing restrictions in a stochastic environment.To this end,we have established a supply chain finance framework by designing two novel coordinating contracts based on trade credit financing for different problem settings.These contracts are modeled in the form of multi-leader Stackelberg games that address horizontal and vertical competition in a supply chain consisting of multiple suppliers and a financially constrained manufacturer.However,previous studies in the trade credit literature have addressed only simple vertical competition,that is,seller-buyer competition.To solve the proposed models,two algorithms were developed by combining population-based metaheuristics,the Nash-domination concept,and the Nikaido-Isoda function.The results demonstrate that the proposed supply chain finance framework can eliminate supply chain inefficiencies and make a large profit for suppliers,as well as the financially constrained manufacturer.Furthermore,the results of the contracts’analysis showed that if the manufacturer is required to settle its payments to suppliers before the end of the period,the trade credit contract cannot coordinate the supply chain because of a lack of incentive for suppliers.However,if the manufacturer is allowed to extend its payments to the end of the period,the proposed trade credit financing contract can coordinate the supply chain.Finally,the sensitivity analysis results indicate that the worse the financial status of the manufacturer,the more bargaining power suppliers have in determining the contract parameters for more profit.

The Polish SMEs as Intelligent Organizations in an Era of Digital Transformation

The impact that the digital transformation(DT)has on businesses,suppliers,and other third parties has increased significantly now.Digital transformation means improving traditional manufacturing processes with the help of digital technologies.The goal of digital transformation is to increase production efficiency and reduce costs,improve the quality of goods and services produced,and quickly adapt to changes in the global market.The state of industrial production is constantly changing due to the instability of global,economic and political decisions,so the adoption and expansion of digital solutions based on Industry 4.0,the Internet of things,machine learning,and other technologies of the future is accelerating.With the help of these technologies,companies are trying to change approaches and find new ways to solve problems.In this article the author analyzed the phenomenon of a complex system of knowledge management with tools as SMAC,AI,IoT and Edge computing in intelligent organizations as a part of intelligent economy.The arguments are illustrated with the results of own research conducted by the author in 2021-2022 in selected SMEs from the Polish Wielkopolska Province and their reference to the general development trends in this area.

Delivery Service Management System Using Google Maps for SMEs in Emerging Countries

This paper proposes a Delivery Service Management(DSM)system for Small and Medium Enterprises(SMEs)that own a delivery fleet of pickup trucks to manage Business-to-Business(B2B)delivery services.The proposed DSM system integrates four systems:Delivery Location Positioning(DLP),Delivery Route Planning(DRP),Arrival Time Prediction(ATP),and Communication and Data Sharing(CDS)systems.These systems are used to pinpoint the delivery locations of customers,plan the delivery route of each truck,predict arrival time(with an interval)at each delivery location,and communicate and share information among stakeholders,respectively.The DSM system deploys Google applications,a GPS tracking system,Google Map APIs,ATP algorithms(embedded in Excel Macros),Line,and Telegram as supporting tools.To improve the accuracy of the ATP system,three tech-niques are applied considering driver behaviors.The proposed DSM system has been implemented in a Thai SME.From the process perspective,the DSM system is a systematic procedure for end-to-end delivery services.It allows the interactions between planner-driver decisions and supporting tools.The supporting tools are simple,can be easily used with little training,and require low capital expenditure.The statistical analysis shows that the ATP algorithm with the three techniques provides high accuracy.Thus,the proposed DSM system is beneficial for practitioners to manage delivery services,especially for SMEs in emerging countries.

Journal Introduction:China Finance Review International

Background The China Finance Review International is a flagship academic journal broadly covering the Chinese and international financial markets.The journal is founded by Antai College of Economics and Management at Shanghai Jiao Tong University,one of the top universities in Asia.The China Finance Review International aims to publish quality empirical and theoretical works on important financial and economic issues in the profession.We encourage ground-breaking research related to new and niche areas in finance,such as Fintech and cryptos,ESG,climate finance,and socially responsible investments.We welcome critiques of existing literature and comparative analysis between emerging markets and developed economies.

The Impact of Digital Finance on High-Quality Development of the Chengdu-Chongqing Economic Circle

This paper developed a comprehensive evaluation system that was able to quantify the levels of high-quality development across the cities within the Chengdu-Chongqing economic circle,and investigate the impact that digital finance had on the cities’high-quality development and the underlying mechanisms through which it achieved this.This comprehensive evaluation system was constructed using statistical data from these cities for the period 2014 to 2020 while also taking China’s high-quality development philosophy into account.The key findings revealed that:(a)Digital finance was able to significantly promote high-quality development in the Chengdu-Chongqing economic circle;(b)Digital finance had a significant positive effect in promoting innovative,coordinated,green,open,and shared development;(c)Digital finance was able to stimulate the high-quality development in the Chengdu-Chongqing economic circle by boosting entrepreneurial dynamism;(d)Digital finance had a significant impact on the high-quality development of the axis areas,while its impact was less discernible in non-axis areas.The insights from this research offer a deeper understanding of the factors that drive high-quality development,the role digital finance plays,and the mechanisms through which digital finance is able to propel high-quality development at the city cluster scale.

Survey Explores Symbiotic Relationship between China's Nonofficial Finance and SMEs

Domestic and foreign studies have revealed the existence of an interactive development relationship between nono cial nance and small and medium-sizedenterprises.Based on the empirical findings of a Hangzhou case study,this article substantiates the existence of a very strong symbiotic relationship between China’s nono cial nance and small and medium-sized enterprises(SMEs).This symbiotic relationship is an equilibrium outcome among three market players:formalnance,nono cial nance and SMEs.Meanwhile,it is also a rational choice and suboptimal equilibrium point reached under the existing institutional spaceconstraints.In our empirical study,we found that formal nance failure left a space for symbiosis to survive in two ways:the comparative advantages of nono cialnance created an institutional basis for symbiosis to grow,and immense SME fund shortages created a market space for symbiosis to thrive.In this article,we alsoput forward some recommendations for further development of such a symbiotic relationship.

An Alternative Proposal for Financing for the Agricultural Sector (Agricultural SME’s Bonds)

In today’s environment,where SME’s financing continues to be a serious problem,systems that facilitate non-bank financing models different from traditional ones should be considered.In the present article a model of financing based on bonds for SME’s is proposed,very suitable for the agricultural sector or any group with little access to traditional financing.To improve the analysis,a fuzzy logic system is proposed that allows the most representative variables to be properly selected and take into account the uncertainty of the environment and the subjectivity of the analysts.

Deep Learning for Financial Time Series Prediction:A State-of-the-Art Review of Standalone and HybridModels

Financial time series prediction,whether for classification or regression,has been a heated research topic over the last decade.While traditional machine learning algorithms have experienced mediocre results,deep learning has largely contributed to the elevation of the prediction performance.Currently,the most up-to-date review of advanced machine learning techniques for financial time series prediction is still lacking,making it challenging for finance domain experts and relevant practitioners to determine which model potentially performs better,what techniques and components are involved,and how themodel can be designed and implemented.This review article provides an overview of techniques,components and frameworks for financial time series prediction,with an emphasis on state-of-the-art deep learning models in the literature from2015 to 2023,including standalonemodels like convolutional neural networks(CNN)that are capable of extracting spatial dependencies within data,and long short-term memory(LSTM)that is designed for handling temporal dependencies;and hybrid models integrating CNN,LSTM,attention mechanism(AM)and other techniques.For illustration and comparison purposes,models proposed in recent studies are mapped to relevant elements of a generalized framework comprised of input,output,feature extraction,prediction,and related processes.Among the state-of-the-artmodels,hybrid models like CNNLSTMand CNN-LSTM-AM in general have been reported superior in performance to stand-alone models like the CNN-only model.Some remaining challenges have been discussed,including non-friendliness for finance domain experts,delayed prediction,domain knowledge negligence,lack of standards,and inability of real-time and highfrequency predictions.The principal contributions of this paper are to provide a one-stop guide for both academia and industry to review,compare and summarize technologies and recent advances in this area,to facilitate smooth and informed implementation,and to highlight future research directions.

Relevance in the Application of IFRS 16 for Financial Statements:Empirical Evidence the Impact of the Financial Method in SMEs

Leasing is confirmed among the preferred forms of financing by SMEs(Small and Medium Enterprises),even if its use grows both among large companies and private individuals.The stipulated in Europe increased in 2017 by 8.3%over the previous year.From 1 January 2019 the new accounting standard IFRS 16 is in force,which concerns the accounting of leasing contracts.The new methods of accounting for leasing contracts in the financial statements drawn up based on international accounting standards come into force.In fact,as from 1 January 2019,the IAS adopters are required to apply the new IFRS 16 standard,introduced in place of IAS 17,with the aim of standardizing the methods for recognizing leasing contracts in the financial statements.Scientifically,the most important researches concerning leasing have dealt with the topic focusing on accounting harmonization,accounting for leasing,capitalization of leasing and tax.Through the theoretical analysis and the simulation of our case study we want to answer a question:How the change in the accounting of leases is reflected in the financial statements?