Market Information Research Articles

Formation mechanisms of dynamic capabilities based on relational capital of enterprises in emerging economies under institutional change: a multiple case study in the context of China’s reform and opening-up

ABSTRACT This study analyzes how Chinese enterprises build and enhance dynamic capabilities during the reform and opening-up period, illustrating the transition from reliance on personal and political relationships in the startup phase to dependence on technology and global market information in the maturity phase. The research indicates that changes in the policy environment are key drivers for the formation of dynamic capabilities. Enterprises must continuously adjust their strategies and relational capital to swiftly adapt to policy changes and maintain competitiveness. This study not only deepens the understanding of the process-oriented theory of dynamic capabilities but also offers new perspectives on the strategic behavior of enterprises in emerging markets, particularly regarding how the dynamics of the institutional environment influence the formation and utilization of dynamic capabilities. The research emphasizes the strategic importance of relational capital and explores how enterprises continuously adjust relational capital to build and enhance dynamic capabilities. The findings provide concrete operational strategies and deep insights for enterprise managers and policymakers, helping them more effectively grasp the key factors of enterprise growth and environmental adaptation.

Can digital technology promote market participation among smallholder farmers?

Abstract Digital technology holds significant potential for enhancing business efficiency in agricultural marketing. However, empirical research on the use of digital technology among smallholder farmers engaged in staple crop marketing in Sub-Saharan Africa remains limited. Recognizing the pivotal role of digital technology in agriculture, this study aims to analyse and synthesize existing knowledge regarding the impact of mobile phones on market participation among smallholder farmers. Through a comprehensive analysis, we seek to provide a robust understanding that can inform policies and programs aimed at enhancing smallholder market integration. To achieve this objective, we collected cross-sectional data from 360 farmers in southeast Nigeria and implemented a double hurdle model to analyse market participation decisions and the extent of farmers’ involvement in staple crop markets. In addition to traditional econometric methods, we employed propensity score matching to further investigate the impact of mobile phone ownership on market participation. Our analysis revealed that ICT tools, particularly mobile phones and radios, significantly influence both the decision and intensity of market participation among smallholder farmers. Specifically, mobile phones were found to play a crucial role in facilitating access to market pricing information and disseminating knowledge on improved production methods. Given the volatility of farm prices, the timely dissemination of market information through mobile phones is essential for farmers to make informed decisions. With a high percentage of mobile phone ownership and substantial investments in mobile networks in Nigeria, the digitalization of extension services and marketing information delivery systems could catalyse rapid improvements in agribusiness and marketing. This shift towards digital platforms has the potential to address information asymmetry, particularly among smallholder farmers, thereby fostering greater market integration and economic empowerment within rural communities.

Price Dynamics and Integration of Onion Markets in India

The current study uses the Correlation matrix, Vector Auto Regressive model, Granger causality test and Instability index to investigate the level of market integration, price transmission and price instability in the key onion markets in India, namely, Azadpur, Bangalore, Belgaum, Hassan, Haveri, Hubli, Mysore, and Nashik. The findings provided substantial evidence for the co-integration and interdependence of these markets. Bangalore market has a positive relationship with the Nashik and Azadpur markets, with coefficients of 1.15 and 0.54, respectively. Bangalore and Belgaum displayed a solid, significant positive correlation with a coefficient of 0.770. Conversely, some markets show relatively weaker correlations, such as Azadpur and Hassan, with a coefficient of 0.389. Instability across major onion markets revealed that all the markets are volatile, as the instability index was more than 30 per cent. Since there is unidirectional causality from Hubli-Bangalore and Azadpur-Bangalore market pairs, it makes it necessary for future research to examine the influence of internal and external factors like market infrastructure, improving information technology to allow regular flow of market information to assist farmers in increasing their income. Keywords: Granger causality, instability, price transmission, price volatility. JEL Codes: B23, C01, C22, E31.

Crude oil futures and the short-term price predictability of petroleum products

This study investigates the lead-lag effect between crude oil futures and petroleum products from the view of price predictability. The findings of the Granger causality test provide evidence for the leading role of crude oil futures. Further empirical results show that crude oil futures demonstrate strong predictive power for petroleum products both in- and out-of-sample, and this predictability is a short-term phenomenon. During economic recessions, petroleum product prices exhibit stronger predictability, with out-of-sample R2 reaching a maximum of 39.161 %. Additionally, the outstanding forecasting performance remains robust across a range of settings. Finally, two potential economic sources underlying the lead-lag relationship between crude oil and petroleum product markets are provided: the differential response speed to common energy market information and the perspective of raw material supply.

Market intelligence applications leveraging a product-specific Sentence-RoBERTa model

Market intelligence, which collects and analyzes market trends and competitive landscape, is crucial for business success in the market. In particular, defining market scope is important because the market analysis outcomes vary depending on where the market boundaries are. However, this has been challenging due to the difficulty in scoping a number of similar products into the target market appropriately. To address this challenge, this study devised a novel method for acquiring reliable market intelligence utilizing the Sentence-RoBERTa (SRoBERTa) model, a pre-trained language model (PLM) specialized in computing sentence similarity. The SRoBERTa model was fine-tuned with 26,248,771 data on product relations and built a product-specific SRoBERTa model (named Pro-SRoBERTa) for effectively identifying the products that fall within the market scope. It outperformed the untrained model by up to 82.8 % on the hierarchical product categorization task. Finally, the Pro-SRoBERTa model was applied to determine the scope of the market followed by obtaining diverse market intelligence. The analysis module was successfully implemented in the market information system using a large-scale, real-world dataset.

Design and optimization strategy of electricity marketing information system supported by cloud computing platform

This paper provides an in-depth discussion on the comprehensive requirements analysis, design implementation, algorithm optimization, and experimental evaluation of an electric power marketing information system, aiming to build a modern information system that is efficient, secure, and user-friendly. In the requirements analysis phase, the importance of business process optimization, data management analysis, security compliance, system integration and scalability is emphasized, while the diversified needs of end customers are considered. For the design and implementation part, the system architecture is based on microservices and cloud-native technologies to ensure high performance and security; and modularized development is achieved through Spring Boot, Vue.js and other technology stacks. For algorithm optimization, LSTM is used for power demand prediction and anomaly detection by combining integrated learning and self-encoder, which improves the prediction accuracy and anomaly identification capability. Experimental evaluation shows that the system demonstrates good performance, security and scalability in cloud computing environment, and the cost-effectiveness is significantly better than traditional deployment.

The Value of Information in Competitive Markets: Evidence from Small and Medium Enterprises

The Value of Information in Competitive Markets: Evidence from Small and Medium Enterprises

Information, sentiment, and margin trading of Chinese stock market

AbstractThis paper examines whether information or sentiment drives margin trading in the Chinese stock market. At the aggregate level, no conclusive evidence indicates a dominance of either information‐driven or sentiment‐driven margin trading activities. However, at the individual firm level, we observe both types of margin trading, underscoring the need to consider the heterogeneity of margin trading when reconciling previous research findings. Moreover, we find that the likelihood of sentiment‐driven margin trading significantly declined following regulators' implementation of stricter rules for margin trading in 2015.

Allocating labor across small firms: Experimental evidence on information constraints

We document interest in labor reallocation among small firm owners in Ghana; 60% and 41%, respectively, self-report willingness to hire or work for the average local firm owner. Firm owners also exhibit high willingness-to-pay for information on a random subset of hiring firms and jobseeking firm owners during a Becker–Degroot–Marschak exercise. Conditionally random variation in access to this information generates immediate labor adjustments within and between firms, though rarely of firm owners themselves, and impacts firm closure 5-months post-intervention. Our findings suggest that labor market information of this kind is both valuable and actionable in our context.

Motivation and Performance Analysis of Spin-offs and Listings: A Case Study of Ningbo-Zhoushan Port

Spin-off and listing is one of the means of contractile asset operation. This paper takes Ningbo Zhoushan Port (hereinafter referred to as Ningbo Port), the first case of "A split A" of China's port and shipping enterprises, as the research object, explores the motivation of Ningbo Port's spin-off and listing of Ningbo China Ocean Shipping(Group) Company (COSCO), and analyzes the risks of the spin-off to enterprises and market investors based on some financial indicators of the parent and subsidiary before and after the spin-off. The results show that from the perspective of the overall spin-off effect, the spin-off effect of Ningbo Port is not significant. From the perspective of the realization of specific motivations, the spin-off of Ningbo COSCO by Ningbo Port conforms to the external development trend and the characteristics of the enterprise in its own mature stage. From the perspective of market reaction, the market is not optimistic about the prospect of this spin-off, and the stock price of Ningbo Port has fallen before and after the spin-off. At the same time, after Ningbo Port spun off Ningbo COSCO and listed, Ningbo Port's control over Ningbo COSCO has declined, which also makes investors worried. This study hopes to provide a reference for the spin-off and listing of Chinese port enterprises in terms of broadening financing channels and reducing market information asymmetry.

The impact of economic policy uncertainty on earnings value relevance

AbstractEarnings value relevance, defined by the predictive and explanatory power of corporate earnings information for market value, reflects accounting earnings decision utility and the capital market's information efficiency. Economic policy uncertainty (EPU) reduces information quality, impairs the information environment, and disrupts interpretation of information, diminishing earnings value relevance. Using a dataset comprising Chinese A‐share listed companies from 2006 to 2019, we empirically examine the impact of EPU on earnings value relevance. Our finding indicates that EPU reduces earnings value relevance, and the effect is more pronounced in firms with lower governance effectiveness and higher firm complexity. Channel analysis demonstrates that decreasing information quality, undermining the information environment, and impeding investor decision‐making are the main three mechanisms. In light of these findings, the government should strive to enhance stability in economic policies and improve information efficiency, fostering a positive interaction between firms and the capital market.

Marketing Efficiency of Banana in Yenagoa Metropolis, Bayelsa State, Nigeria

The study examines the marketing efficiency of bananas in Yenagoa Metropolis of Bayelsa State, Nigeria. The objectives were to describe the socio-economic characteristics of banana marketers; determine the marketing margin and efficiency of banana marketers; identify marketing channels of bananas; and identify the constraints associated with banana marketers in the study area. Ninety (90) questionnaires were retrieved and used for the analysis out of the one hundred and four (104) questionnaires distributed to the banana marketers selected through a multistage random sampling technique from eight (8) markets in Yenagoa Metropolis of Bayelsa State using a structured questionnaire. Descriptive Statistics and marketing margin and efficiency formulas were used to analyse the data. The result showed that banana marketers were predominantly female. Budgetary analysis showed marketing efficiency greater than one which indicated profitability of the market. The Likert type showed the constraints, which significantly affect banana marketing as high perishability (3.88), high cost of transportation (2.98), inadequate market information (2.85) and heavy imposition of tax/levies (2.63). The study, therefore, recommends that Marketers should be encouraged to have market informants that will inform them of the increase or decrease in the prices of bananas in different markets in the study area.

Internet development, information availability, and Chinese enterprises’ cooperative green technology innovation

Cooperative green technology innovation is potentially the answer to the lack of motivation for independent green innovation, which can effectively alleviate many difficulties faced by enterprises engaging in independent green innovation. Internet development provides new opportunities to stimulate innovative cooperation of enterprises. However, little literature has studied the impact of Internet development on enterprises' cooperative green technology innovation. Based on the data of Chinese A-share 3284 listed companies from 2010 to 2019, this paper uses a panel two-way fixed effects model to assess the effect of Internet development on enterprises' cooperative green innovation. The findings are: (1) Internet development significantly drives firms' collaborative green innovation behavior. The result remains robust even after performing a series of robust tests. (2) The Internet empowers green innovation cooperation among firms by improving information availability, including market information availability and technical information availability. (3) The heterogeneous results show enterprises use the Internet to accomplish high-quality collaborative green innovation. Internet development is more helpful in encouraging the cooperative green innovation of enterprises located in central cities and state-owned enterprises. This study provides novel and targeted policy implications to empower enterprises’ green innovation cooperation and drive sustainable economic development through Internet development.

Forward-looking disclosure effects on stock liquidity in China: Evidence from MD&A text analysis

We investigate the impact of forward-looking disclosures in annual reports on stock liquidity in China. Analysis of the MD&A sections within annual reports demonstrate a strong positive correlation between forward-looking disclosures and a company's stock liquidity. This promotional effect appears more pronounced within high-tech companies and those with lower levels of information transparency. Mechanistic tests indicate that the increase in equity liquidity attributable to forward-looking disclosures can be traced to heightened interest from analysts and media coverage. Further examination of the impact of MD&A textual characteristics reveals that improvements in the readability and tone of the text strengthen the effect of forward-looking information on enhancing stock liquidity. Economic consequence tests show that forward-looking disclosures not only enhance stock liquidity but also contribute to expanding investment scale, reducing financing costs, and improving both future firm performance and market valuation. These findings suggest that augmenting the efficiency of capital market information dissemination could significantly bolster financial support for the real economy.

Wisdom of crowds or awkward squad? Social interaction and the information efficiency of the Chinese capital market

Existing studies on the impact of social media on the information efficiency of capital markets have opposing views. One often-overlooked aspect in these studies is the role of investor interaction, a core feature of social media. To address this gap, we employ social network analysis (SNA) to investigate how investor interactions on Eastmoney, China's largest online stock forum, influence capital market efficiency. Our findings indicate that online investor communication can effectively disseminate firm-specific information through social networks when investor interactions are at a moderate level. However, beyond a certain threshold, heightened interactions contribute to market noise, thereby distorting the stock price discovery process. Our mechanistic analysis reveals that increased investor interactions stimulate irrational emotions at both market and stock levels, ultimately impairing capital market efficiency. This study contributes to social network analysis and behavioral finance by illuminating the impact of online social interactions among retail investors on capital market information efficiency.

Peran Asosiasi Pengusaha Indonesia (APINDO) Memanfaatkan kebijakan Sistem Informasi Pasar Kerja (SIPK) 2024

The Indonesian Employers Association (APINDO) plays a crucial role in addressing the gap between workforce supply and industrial demand. This study explores how APINDO leverages the Labor Market Information System (SIPK) to align human resources with industry needs, thereby enhancing employment rates and improving the efficiency of the labor market. The SIPK provides comprehensive data on labor market trends, job vacancies, and skill requirements, enabling employers to make informed decisions about hiring and training. Through interviews with key stakeholders and analysis of SIPK data, this research highlights the effectiveness of APINDO's strategies in optimizing human resource absorption. The findings indicate that APINDO's utilization of SIPK not only bridges the gap between job seekers and employers but also contributes to the development of a more responsive and adaptive workforce, meeting the evolving needs of industries in Indonesia. The study concludes with recommendations for enhancing the SIPK platform and expanding APINDO's initiatives to further support the alignment of labor supply and demand.

Navigating the Dynamics of Brent Crude Oil Prices: Factors, Trends, and Insights

Accurate Brent Crude Oil price prediction is essential for informed decision-making and risk control in the global energy market. This paper examines the dynamics of Brent Crude Oil prices over the previous 35 years, utilizing predictive modelling techniques to project future prices and analyzing historical trends and relationships with the GDPs of major economies. The statistical methods used in this paper include the moving average and Pearson correlation coefficient. While correlation studies show significant positive links between Brent Crude Oil prices and the GDPs of major economies like China, Saudi Arabia, Europe, Russia, and the United States, historical data analysis reveals large price volatility. Highly accurate price forecasting using LSTM (Long Short-Term Memory) modelling approaches provides detailed risk management and decision-making information in the global energy market. The application of the Neural Network and the ARIMA model shows an increase in the price of Brent crude oil in the next year, 2024. Identifying the importance of the Brent crude oil price forecast and its effect on the international market is highly needed. This paper thus might help to increase economic growth. These results highlight the importance of advanced modelling techniques and economic indicators in managing oil price changes and help make informed decisions in the energy industry.

Market Participation and Farmers’ Adoption of Green Control Techniques: Evidence from China

As a standard clean production technology, the wide use of green control techniques (GCT) helps improve the quality of agricultural products and protect the environment. However, the level of application of GCT by Chinese farmers is not high. The market, as the ultimate place to realize the value of grain and the returns of grain farmers, plays an essential part in promoting GCT. Based on survey data from grain farmers in Sichuan Province, China, this study used a conditional mixed process (CMP) model to examine the effect of farmers’ market participation on their GCT adoption behavior and a mediated effects model to test the impact mechanism. The study further explored the effect of farmers’ market participation capability on their GCT adoption behavior. The results showed that (1) farmers’ market participation could significantly increase the likelihood of adopting GCT. (2) Market participation could influence farmers’ adoption behavior through agricultural income, market information, and green cognition. (3) Further research found that farmers were more likely to adopt GCT if their market participation capability was strong. These findings highlight the fact that developing countries have increased their efforts to encourage farmers to participate in markets and to enhance their market participation capability, thereby facilitating the adoption of GCT by farmers.

Fair value estimates for illiquid cryptocurrency

To address the need for reporting and disclosure of cryptocurrency holdings in compliance with the FASB guidance for the use of fair value measurements for cryptocurrency (FASB, 2023), this paper develops a modeling process for reporting entities to measure the market value of cryptocurrencies with limited or no observable transactions. In this valuation model, we consider the last observable market information with time decay, its comparable assets market index, and dynamic real-time market participants’ sentiment and attention. Notably, the application of exogenous variables allows us to maximize the observable inputs in measuring fair value, such as asset classification based on economic traits and market participants’ attention and sentiment measurement with online media textual analytics. We propose a valuation framework and construct a prediction model that can achieve a prediction accuracy of 87 % on target asset resurging prices.

Extracting Structured Labor Market Information from Job Postings with Generative AI

Extracting Structured Labor Market Information from Job Postings with Generative AI