Market Analysis Research Articles

Efficiency Analysis of the Traditional Market in Surakarta: Application of Data Envelopment Analysis Methods

This research aims to analyze the efficiency level of eight traditional markets in Surakarta before, during and after the COVID-19 pandemic, using the Data Envelopment Analysis (DEA) method. Primary data that has obtained from the Surakarta Trade Office is the number of visitors based on parking fees and traditional market capacity in 2019, 2021 and 2023. The analysis result shows that in 2019 and 2023, Gede Market and Singosaren Market showed the same level of efficiency, while in 2021, Mojosongo Market, Singosaren Market and Kadipolo Market showed efficiency. However, the other six markets showed inefficiencies. There were differences between projected values and actual data on input and output variables, with an increase in all output variables and a decrease in all input variables in 2021 and 2023. Radial movement occurred in input variables in several markets in 2019, 2021 and 2023, while slack movement occured in income output and the number of visitors in several markets in the same year. This research provides a deeper understanding of the efficiency of traditional markets in Surakarta and the changes that have occurred along with the impact of the COVID-19 pandemic.

A Comprehensive Economic Analysis of Tobacco Farming Potential in Grobogan Regency, Central Java

This study aims to investigate the planning for the Tobacco Products Industrial Area (KIHT) development in Grobogan Regency, Central Java, based on economic analysis. KIHT is an area where the activities of the tobacco products industry are concentrated, equipped with infrastructure, facilities, and supporting facilities for the tobacco products industry. The study was designed with a survey approach, in-depth interview, and focus group discussion (FGD) with 100 key informants to obtain facts from the existing phenomena and find information factually. The number of key informants is based on the number all of tobacco numbers in Grobogan regency. The study, therefore, analyzes tobacco competitiveness, labor absorption, product market, and macroeconomic analysis. To sharpen the analysis, the study was supported with a questionnaire instrument to see how far tobacco farmers were prepared in KIHT development. Empirically, the results showed that tobacco farming absorbed 150 HOK/ha per season, greater than corn farming which only absorbed 52 HOK per season per ha and rice farming which absorbed 87 HOK per season per ha. It had high competitiveness with the oligopsony market structure. In addition, the market for tobacco products was experiencing a significant upward trend, and it is in accordance with the Cobweb Theorem law that the behavior of farmers will try to increase the planting area when there is a previous price increase. From the potential of tobacco products, Grobogan Regency received an excise duty of IDR 14.87 billion or 2% of the total excise duty of Central Java Province. This revenue-sharing fund will increase the regional fiscal capacity.

Analysis Of Business Feasibility Study On The Development Of Father Yulianto's Tofu And Tempe Msme Business Reviewed From The Production And Marketing Aspects

This research aims to evaluate the feasibility of Pak Yulianto's tofu and tempeh factory business in terms of marketing and production. This feasibility analysis uses market and competition analysis. The results show that Pak Yulianto's tofu and tempe business from the production aspect is declared feasible because the business location is strategic and easy to reach for consumers and the production process is easy. Meanwhile, the results of the research from the marketing aspect stated that it was worthy of a quality product because it used quality raw materials, and the price was affordable so that all groups could buy it and the promotion that the owner gave was enough to make consumers aware of the product he was selling.

Candlestick Pattern Recognition in Cryptocurrency Price Time-Series Data Using Rule-Based Data Analysis Methods

In the rapidly evolving domain of cryptocurrency trading, accurate market data analysis is crucial for informed decision making. Candlestick patterns, a cornerstone of technical analysis, serve as visual representations of market sentiment and potential price movements. However, the sheer volume and complexity of cryptocurrency price time-series data presents a significant challenge to traders and analysts alike. This paper introduces an innovative rule-based methodology for recognizing candlestick patterns in cryptocurrency markets using Python. By focusing on Ethereum, Bitcoin, and Litecoin, this study demonstrates the effectiveness of the proposed methodology in identifying key candlestick patterns associated with significant market movements. The structured approach simplifies the recognition process while enhancing the precision and reliability of market analysis. Through rigorous testing, this study shows that the automated recognition of these patterns provides actionable insights for traders. This paper concludes with a discussion on the implications, limitations, and potential future research directions that contribute to the field of computational finance by offering a novel tool for automated analysis in the highly volatile cryptocurrency market.

Veterinary Telemedicine in Lithuania: Analysis of the Current Market, Animal Owner Knowledge, and Success Factors for Digital Transformation of Clinics.

Veterinary telemedicine is used to provide animal health care information, education, and care remotely. Digital transformation of veterinary clinics is a fundamental process for the evolution of telemedicine and is changing the way veterinary care and animal health services are delivered. This study aimed to evaluate the current televeterinary market and to assess the knowledge of animal owners and clinic managers. The goals of this study were met by conducting an analysis of the current televeterinary market through a pet owner (n = 200) survey as well as clinic owner (n = 5) interviews. In contrast to other countries, only 1.85% of Lithuanian veterinary clinics offered a paid veterinary remote consultation service on their websites. In addition, more than half of animal owners who participated in the survey did not even know that remote veterinary consultations existed. The most important established factors for the success of digital transformation of veterinary telemedicine were investments in the marketing of the services, management leadership, the competencies and experience of veterinarians, convenient working hours for the client, faster service availability, and lower price. It is recommended to involve marketing and information technology company professionals and to invest in the specialty, digital, and communication skills of veterinarians.

Practice Briefing: The implications of a move towards explicit discounted cash flow (DCF) models for property investment valuations

PurposeThe primary purpose of this Practice Briefing is to examine the implications of the recommendations of the Royal Institution of Chartered Surveyors (RICS) Review of Investment Valuations to shift towards (explicit) discounted cash flow (DCF) valuations on valuers, clients, risk management and market data.Design/methodology/approachThis Practice Briefing will develop a conceptual framework to articulate the impact of the shift towards explicit modelling assumptions in valuations. A comparative analysis is conducted to contrast traditional valuation approaches with an explicit DCF approach.FindingsThe proposed shift to DCF valuations in the real estate industry carries both subtle and profound implications. While on the surface, the move appears to bring minimal change since current valuations are already DCF-based, a deeper exploration reveals a potential transformation to the understanding, analysis and measurement of pricing and risks in commercial real estate.Practical implicationsThe traditional techniques adopted in valuations have become pervasive in the industry, hindering more sophisticated modelling and analysis of individual assets and portfolios. Explicitly modelling assumptions in both the initial years of cash flow and perpetuity calculations would unveil fundamental relationships and rationales that have previously been buried within, and perhaps ignored by, an All Risks Yield (ARY).Originality/valueThis briefing identifies the cause of confusion when interpreting ARY differentials on implied target returns and risk and demonstrates how a change to explicit assumptions, such as growth and letting periods, would enhance transparency, enabling more informed client–valuer discussions, which in-turn will boost confidence in valuation accuracy, lead to more sophisticated asset modelling, market data, forecasting and market analysis.

Market analysis and quality management of healthy food products for vegetarians

Market analysis and quality management of healthy food products for vegetarians

User Cost of Housing Analysis of the German Real Estate Market

Background: This study looks at the development of the German real estate landscape, which recorded a continuous rise in prices between 2009 and 2022. These were due to a genuine excess demand, a shortage of supply and favorable financing conditions. In the course of 2022, mortgage rates then rose after a historically long period of low interest rates. Aim: This study aims in particular to assess whether the financial advantage of home ownership remains robust. The aim is to determine the relative attractiveness of home ownership compared to renting in all 401 German districts and independent cities. Methods: The owner-occupier costs are determined using the user cost of housing approach and compared with the current rental prices in the respective cities and districts. Various factors are taken into account, including the purchase price, financing costs, maintenance and rental prices. Results: The results of the analysis show that home ownership still offers a considerable cost advantage on average across Germany: In mid-2023, it is around 57% cheaper per square meter to invest than to rent. However, it is important to point out that this result does not take into account differences in the population’s ability to afford home ownership. Furthermore, the analysis raises questions about the sustainability of past house price growth and whether this increase is due to fundamental factors or low mortgage rates. In this sense, the study confirms that home ownership on the German real estate market remains economically favorable compared to renting, even with increased interest rates. It underlines how important it is to consider the long-term benefits for wealth accumulation when deciding between owning and renting. Practical relevance/social implications: The study is of practical relevance for people who rent an apartment or house in Germany and are considering whether it is sensible and economical for them to invest in property. The findings from the analysis are helpful for current purchasing decisions. Originality/value: It also offers original results and provides the reader with added value, as it captures and evaluates current real estate developments on the German market in a well-founded manner.

Application of Copula Models in Stock Market Analysis

Objectives. The objective of the study is to use copula models to analyze shares of the Russian stock market and describe changes in the relationship between the shares before and during the coronavirus infection (COVID-19).Methods. An algorithm for using copulas and functions of the R programming language in its implementation is presented. To model the dynamics of financial series the ARMA-GJR-GARCH process (autoregressive moving average Glosten-Jagannathan-Runkle model with generalized autoregressive conditional heteroskedasticity) is used. The selection of optimal families and parameters of copula models is carried out. The adequacy of the obtained models is checked and the results of the study of the relationship between the series are analyzed.Results. An algorithm has been developed for a relatively new approach to using copulas in conjunction with the ARMA-GJR-GARCH model. The approach was used to study the impact of coronavirus in the context of the Russian economy. It is revealed that during the COVID-19 period the dependence between different stocks increases. It is shown that the effect of volatility in financial series increases after the outbreak of the pandemic.Conclusion. The research algorithm using copula models in conjunction with the ARMA-GJR-GARCH process has shown its feasibility. This approach can be used with other GARCH-type models to study finance and other areas.

Accounting Information Systems for Strategic Management: The Role of Intellectual Capital in Mediating the Relationship between Customer, Company, and Performance

This research aims to investigate the role of Intellectual Capital (IC), Managing Accounting Information Structures (MAIS), Internal Task Productivity (ITP), and Customer Performance (CP) in moderating the link between strategies and Financial Productivity (FP). The population for this study consisted of medium and enormous manufacturing enterprise business units located in Java. In this study, the enterprise unit is the specific part of the firm accountable for producing and marketing a product or group of items. It is organized based on the type of item that it deals with and operates independently from other companies or divisions within the parent organization. The company unit has a distinct set of competitors, separate from those of different units. It is overseen by an executive liable for establishing and carrying out strategies to meet the specified profit goal. An approach to invention, including product invention, task creativity, and technology, significantly influences firm performance if there is a robust ITP, dependable market analysis, intelligence systems, and effective competitive positioning. The ITP enhances the alignment between the approach and the FP by including operational management activities, customer management chores, Invention Tasks (IT), and regulatory and social tasks. This research found no impact of IC on CP and ITP; similarly, MAIS did not influence FP. Information systems affect financial performance by ITP infrastructure and corporate processes. The contributions of this study include the novel application of the continuous invention approach, integrating product invention and task and information technological devices, which past studies have not explored; the utilization of IC, MAISs, ITP, and CP as mediating factors; the adoption of a holistic method by incorporating aspects of IC, MAIS, and non-FP as contextual factors, about contingency methods, which have not been investigated in the previous study; the development of novel ideas in conjunction with the balanced scoring framework; and the examination of both single and numerous mediating effects on the impact of sustainable approaches to the invention on FP.

Changes in the Trade Pattern in China Under the RCEP: An Analysis of Trade Creation and Diversion Using the SMART-WITS Model

The Regional Comprehensive Economic Partnership (RCEP), one of the globe's most expansive free trade agreements (FTAs), has profoundly influenced its member countries' trading patterns. This fact is especially critical for a major economic powerhouse such as China. Understanding its trade creation and trade diversion within the RCEP context can facilitate successful formulation strategies and result in effective economic policies. In this study, we utilize the World Integrated Trade Solution Software for Market Analysis and Restrictions on Trade (WITS-SMART), a partial equilibrium modeling tool, on both state-level and industrial-tier tariff reductions under two distinct scenarios. Our findings confirm that China will benefit from impactful trade results across all RCEP members. Looking from industry point of view: machinery, chemicals, metals sector together with plastics and rubber production are projected to enjoy maximum rewards through increased trade creation and diversion opportunities from Japan and Korea. On the contrary, Australia and ASEAN have the greatest influence on the animal and vegetable sector. This crucial understanding creates strategic indicators that aid in evaluating the most appropriate alignments to harness the untapped potential in the RECP domain.

Recent Trends in Life Insurance: Innovations, Challenges, and Implications

This research paper explores recent trends in the life insurance industry, focusing on innovations, challenges, and implications for insurers, consumers, and regulators. Drawing on a comprehensive review of literature, market analysis, and industry reports, the paper examines key trends shaping the landscape of life insurance in the digital age. It highlights the impact of technological advancements, changing consumer preferences, regulatory developments, and demographic shifts on product design, distribution channels, underwriting practices, and risk management strategies. The paper also discusses emerging opportunities and challenges for life insurers in addressing the evolving needs and expectations of customers, enhancing operational efficiency, and navigating regulatory complexities. Through a critical analysis of recent trends, the paper aims to provide insights into the future direction of the life insurance industry and inform stakeholders about potential strategies for sustainable growth and innovation.

Analisis Rantai Pasok Kopi Pada Kelompok Tani Kopi Rejo Di Desa Wisata Gombengsari Banyuwangi

The supply chain of the tourism industry and the creative economy is very closely related through efforts to develop industrial ecosystems including business partnerships from upstream to downstream. One of the culinary sub-sectors that is growing rapidly, and has even become a new lifestyle for the people, is Indonesian coffee. The increase in the amount of national coffee consumption is of course followed by the level of archipelago coffee production. Banyuwangi Regency has strategic coffee-producing locations, one of which is located in Gombengsari Village. This study aims to analyze the coffee supply chain in the Gombengsari Coffee and Tourism Village, so that the authors can determine the priority of development recommendations in order to improve the performance of coffee supply chain management in the Gombengsari Coffee and Tourism Village. The research method used is descriptive analysis using case study research techniques with data testing, namely using marketing analysis, marketing margins, farmer's share, and marketing efficiency. The results of this study indicate that there are three patterns of coffee flow. Farmers can apply partnerships and creative economy concepts to increase tourism development in the Gombengsari Coffee and Tourism Village, Banyuwangi Regency.

Factor-GAN: Enhancing stock price prediction and factor investment with Generative Adversarial Networks.

Deep learning, a pivotal branch of artificial intelligence, has increasingly influenced the financial domain with its advanced data processing capabilities. This paper introduces Factor-GAN, an innovative framework that utilizes Generative Adversarial Networks (GAN) technology for factor investing. Leveraging a comprehensive factor database comprising 70 firm characteristics, Factor-GAN integrates deep learning techniques with the multi-factor pricing model, thereby elevating the precision and stability of investment strategies. To explain the economic mechanisms underlying deep learning, we conduct a subsample analysis of the Chinese stock market. The findings reveal that the deep learning-based pricing model significantly enhances return prediction accuracy and factor investment performance in comparison to linear models. Particularly noteworthy is the superior performance of the long-short portfolio under Factor-GAN, demonstrating an annualized return of 23.52% with a Sharpe ratio of 1.29. During the transition from state-owned enterprises (SOEs) to non-SOEs, our study discerns shifts in factor importance, with liquidity and volatility gaining significance while fundamental indicators diminish. Additionally, A-share listed companies display a heightened emphasis on momentum and growth indicators relative to their dual-listed counterparts. This research holds profound implications for the expansion of explainable artificial intelligence research and the exploration of financial technology applications.

АНАЛИЗ РОССИЙСКОГО РЫНКА БЕНЗОЛА

The article provides an analysis of the Russian benzene market, its volumes, structure and applica-tions in industrial production. The problems of purification of imported benzene from sulfur impurities are considered

Multilevel modelling, location and property valuations: an application to the Italian residential market

PurposeThe use of statistical methods in the field of real estate appraisals presents a trade-off between the efficiency of the estimates (that would require the use of sophisticate econometric models) and the ease of the economic interpretation of the outcomes (that characterises the hedonic pricing models). This paper shows that multilevel modelling (MLM) can represent a suitable solution to this trade-off.Design/methodology/approachThis paper uses the so-called “multilevel modelling” (henceforth MLM). MLM can represent a further step forward in the use of statistical methods in property appraisals. MLM is easy to implement and the MLM estimates have a clear economic meaning. Furthermore, MLM provides more efficient estimates of hedonic prices (the prices of housing attributes) with respect to standard hedonic pricing models. Finally, MLM is particularly suitable for the housing market analysis, where the feature “location” plays a key role.FindingsFor the Italian context, characterised by many “benchmark locations” (small municipalities that share similar geographic, historic, and socioeconomic characteristics), the paper finds that multilevel modelling (MLM) is needed to correctly estimate the hedonic prices also in a micro-area.Practical implicationsMLM allows to further enhance the key role of “location”. Location is indeed used as the “grouping variable” in MLM, instead of being treated as a generic housing attribute in hedonic pricing models. When the benchmark locations are many, therefore, MLM represents a very effective compromise between the estimates’ efficiency and the ease of outcomes’ economic interpretation.Originality/valueUnlike the related literature that, basically, use MLM to investigate what are the main determinants (levels) of housing prices, this paper uses MLM to make more efficient the estimation of hedonic prices.

Optimalisasi Manajemen Strategi Untuk Menjadikan UMKM Yang Unggul Dalam Persaingan Bisnis

In the current era of globalization and digitalization, Micro, Small, and Medium Enterprises (MSMEs) face increasingly complex challenges in maintaining and improving their competitiveness. Optimizing strategic management is crucial to ensure that MSMEs can not only survive but also excel in the tight business competition. This study aims to identify and analyze effective management strategies for MSMEs to improve their competitiveness. The research methodology involves qualitative and quantitative analysis through case studies of MSMEs in various industrial sectors. Data were obtained from in-depth interviews with MSME owners, surveys, and internal documentation analysis. Key findings indicate that MSMEs that successfully implement optimal management strategies—such as product innovation, utilization of digital technology, effective human resource management, and targeted marketing strategies—can significantly improve their competitive position. This study concludes that the implementation of strategic management based on a deep understanding of market needs, adaptation to changes in the business environment, and the use of modern technology are key factors in achieving competitive advantage. Practical recommendations for MSMEs include developing market analysis capabilities, improving digital skills, and implementing more structured management practices. By implementing these recommendations, MSMEs are expected to increase their competitiveness and contribute more to local and national economic growth.

Exporting Beekeeping Products: Importance of Detailed Market Analysis and Brand Positioning

To strengthen the export potential of Georgian bees and intervene in international markets, it is necessary to make a comprehensive and profound analysis. The article discusses the influences of market segmentation, consumers’ preferences, international trading agreements, legal regulations, product certification, technological innovations and competition on the development of marketing and branding strategies, supporting the efficient positioning of the high-quality Georgian bee products on the international markets and increase in export. Competition evaluation is critical for determining market possibilities and positioning Georgian beekeeping on global markets. The physiological and qualitative functions of the Georgian mountain grey bee must be emphasized: its gentleness, excessive productivity, and resistance to ailments. The article additionally mentions the importance of a strategic method to boost export capability in integrating technological improvements and contemporary advertising strategies, which include digital technology and database analytics, which will have an instantaneous effect on increasing the charm of beekeeping products. Determining purchaser preferences, cooperation with international organizations and obtaining first-rate certificates are crucial for the global reputation of Georgian beekeeping manufacturers and gaining agreement with customers. Market analysis, contemporary branding, and dynamic marketing are considered the basis for the hit export of Georgian beekeeping products and their established order in international markets.

Luxury Car Leasing

This study aims to provide insights and knowledge to new entrepreneurs on developing their businesses by utilizing luxury car leasing services, focusing on the benefits of leasing versus buying, personalizing the lease experience, and supporting business activities through upgraded personal branding. The objectives are to analyze the advantages of luxury car leasing over purchasing, explore the personalized leasing experience for customers, and examine the role of luxury car leasing in enhancing business operations and personal branding. This research employs a qualitative approach, utilizing case studies and interviews with both leasing companies and lessees. Data was collected through structured interviews with key stakeholders in the luxury car leasing industry, including leasing company representatives and customers who have leased luxury cars. Additionally, market analysis and literature reviews were conducted to support the findings. The findings indicate that luxury car leasing offers significant advantages over purchasing, including financial flexibility, access to the latest car models, and lower maintenance costs. Personalized leasing experiences were highly valued by customers, contributing to higher satisfaction and loyalty. Furthermore, leasing luxury cars positively impact personal branding and business operations by providing entrepreneurs with a sophisticated image and reliable transportation for business activities.

Strategic financial decision-making in sustainable energy investments: Leveraging big data for maximum impact

In the context of escalating environmental concerns and the transition towards a greener economy, sustainable energy investments have emerged as a pivotal area for financial growth and innovation. This paper outlines a strategic framework for financial decision-making in sustainable energy investments, emphasizing the transformative role of big data. By integrating big data analytics into the investment process, stakeholders can enhance market analysis, risk assessment, performance monitoring, and predictive modeling, leading to more informed and effective investment strategies. The paper delves into various big data sources, analytical tools, and technologies that facilitate the collection, processing, and interpretation of vast amounts of information. Additionally, it presents case studies illustrating successful applications of big data in solar and wind energy projects, highlighting best practices and common challenges. The discussion extends to future trends, including advancements in artificial intelligence and machine learning, which are poised to further revolutionize the sector. The paper concludes with strategic recommendations for developing a data-driven investment approach, building robust data infrastructures, and fostering a culture of continuous learning and adaptation. By leveraging big data, investors can maximize the impact of their investments, drive sustainable growth, and contribute to the global energy transition. Keywords: Sustainable Energy Investments, Big Data Analytics, Strategic Financial Decision-Making, Market Analysis, Risk Assessment, Predictive Modeling.