Industry Characteristics Research Articles

A Fractional Gompertz Model with Generalized Conformable Operators to Forecast the Dynamics of Mexico’s Hotel Demand and Tourist Area Life Cycle

This study explores the application of generalized conformable derivatives in modeling hotel demand dynamics in Mexico, using the Gompertz-type model. The research focuses on customizing conformable functions to fit the unique characteristics of the Mexican hotel industry, considering the Tourist Area Life Cycle (TALC) model and aiming to enhance forecasting accuracy. The parameter adjustment in all cases was made by designing a convex function, which represents the difference between the theoretical model and real data. Results demonstrate the effectiveness of the generalized conformable derivative approach in predicting hotel demand trends, showcasing its potential for improving decision-making processes in the Mexican hospitality sector. The comparison between the logistic and Gompertz models, in both integer and fractional versions, provides insights into the suitability of these modeling techniques for capturing the dynamics of hotel demand in the studied regions.

A novel dynamic machine learning-based eXplainable fusion monitoring: Application to industrial and chemical processes

Abstract The complexity and fusion dynamism of the modern industrial and chemical sectors have been increasing with the rapid progress of IR 4.0 to 5.0. The transformative characteristics of Industry 4.0 to 5.0 have not been fully explored in terms of the fundamental importance of explainability. Traditional monitoring techniques for automatic anomaly detection, identifying the potential variables, and root cause analysis for fault information are not intelligent enough to tackle the intricate problems of real-time practices in the industrial and chemical sectors. This study presents a novel dynamic Machine Learning (ML) based eXplainable fusion approach to address the issues of process monitoring in industrial and chemical process systems. The methodology aims to detect faults, identify their key causes and feature variables, and analyze the root path of fault propagation with the time and magnitude of one cause variable to another impact. This study proposed using a time domain multivariate granger-entropy-aided dynamic independent component analysis (ICA) - distributed canonical correlation analysis (CCA) approach, incorporating the dynamics time wrapping supported time delay-signed directed graph. The proposed methodology utilized the application to industrial and chemical processes and verified using the Continuous Stirred Tank Reactor (CSTR) and Tennessee Eastman Process (TEP) as practical application benchmarks. The framework's validations and efficiency are evaluated using established techniques such as classic computed ICA and Dynamic ICA as standard model scenarios. The outcomes and results showed that the newly developed strategy is preferable to previous approaches regarding explainability and robust detection and identification of the actual root causes with high FDRs and low FARs.

Dynamic Relationship Between Environmental Policy and Technological Innovation: Evidence from Firms in Korean Emission Trading Scheme

To cope with radical global environmental regulation, it is necessary to find efficient ways to decrease carbon emissions with a low burden on firms and to design valid policies for a sustainable economy. This study investigates the link between the carbon emissions market and firms’ innovation activities and examines the impact of R&D investment caused by the carbon emissions market on the financial performance of firms participating in the Korean Emission Trading Scheme (KETS). This study assumes that a well-designed carbon emissions market can amplify the effect of R&D investment on improving the financial performance of firms and tests the efficiency of this market based on the KETS data. The results show that the indirect R&D elasticity that affects financial performance is simultaneously negative in the short and long run, except in Phase 1 (2015–2018). From this result, this study concludes that the carbon emissions market cannot induce technological innovation to increase financial performance in Korea, and the dynamic efficiency of the market is low. The industry comparison results confirm that the emissions market has a statistically significant effect on financial performance only in carbon-intensive industries. This study thus shows that the impact of technological innovation induced by the carbon emissions market varies depending on industrial characteristics.

Research on the Model and Application of Data Asset Value Evaluation

In the era of digital economy, the marketization of data factor has become an important feature, attracting the attention of governments and scholars. As of January 1, 2024, data resources have been formally included in the financial statements and become an important asset of enterprises. This paper starts from the dimension of value formation of data assets and takes the income approach as the core, closely combines the characteristics of the application software industry, and builds a targeted data asset value assessment model. At the same time, the optimization model is applied to the excess return of X Company's data assets, thereby evaluating the value of X Company's data assets.

Paradigm of engineering recalcitrant non-model microorganism with dominant metabolic pathway as a biorefinery chassis

The development and implementation of microbial chassis cells have profound impacts on circular economy. Non-model bacterium Zymomonas mobilis is an excellent chassis owing to its extraordinary industrial characteristics. Here, the genome-scale metabolic model iZM516 is improved and updated by integrating enzyme constraints to simulate the dynamics of flux distribution and guide pathway design. We show that the innate dominant ethanol pathway of Z. mobilis restricts the titer and rate of these biochemicals. A dominant-metabolism compromised intermediate-chassis (DMCI) strategy is then developed through introducing low toxicity but cofactor imbalanced 2,3-butanediol pathway, and a recombinant D-lactate producer is constructed to produce more than 140.92 g/L and 104.6 g/L D-lactate (yield > 0.97 g/g) from glucose and corncob residue hydrolysate, respectively. Additionally, techno-economic analysis (TEA) and life cycle assessment (LCA) demonstrate the commercialization feasibility and greenhouse gas reduction capability of lignocellulosic D-lactate. This work thus establishes a paradigm for engineering recalcitrant microorganisms as biorefinery chassis.

Spatial Heterogeneity and Clustering of County-Level Carbon Emissions in China

At present, China is the world’s largest carbon emitter and has also made significant efforts in energy conservation and emission reduction. This study utilized the EDGAR dataset of remote-sensing image inversion to investigate the spatial heterogeneity and clustering patterns of carbon emissions across 2184 counties in China through a data-driven approach. By analyzing the impact of socioeconomic factors on carbon emissions with the Spatial Clustering Autoregressive Panel (SCARP) model, significant regional variations were uncovered. The results reveal significant differences in carbon emission drivers between resource-dependent regions and economically developed areas. For instance, regions with heavy industries, such as Inner Mongolia and Xinjiang, exhibit higher carbon emissions, underscoring the need for policies focused on industrial restructuring and clean energy adoption. In contrast, economically advanced regions such as the Yangtze River Delta and Pearl River Delta show slower emission growth, indicating the potential for further reductions through green technology innovations and energy efficiency improvements. These findings highlight the necessity of regionally tailored carbon reduction strategies, offering policymakers a precise framework to address the specific socioeconomic and industrial characteristics of different regions in China.

Research on the Communication and Development of Heilongjiang Cultural and Creative Industry under the Background of “Belt and Road”

This paper focuses on the research on the dissemination and development of cultural and creative industries in Heilongjiang Province under the background of “Belt and Road.” Firstly, the paper analyzes the main characteristics of cultural and creative industries in Heilongjiang Province and then puts forward the leading advantages of the government to promote the development of cultural and creative industries. The government gives full play to its regional advantages and creates Longjiang cultural products, while also accelerating regional industrial cooperation and innovative cultural communication forms. In-depth discussion is made on integrating scientific and technological means of the times and strengthening the cultivation of innovative talents. The government optimizes the communication and development path of the Heilongjiang cultural entrepreneurship industry and brings positive influence to the stable development of the Heilongjiang region in the future.

Analysis of Incentive Compatibility Mechanism for Content Services of Gas Companies under the Background of Universal Service

In recent years, the issue of gas billing has attracted widespread attention from the public, leading to a crisis of trust in gas public goods and services. From the perspective of universal service, based on the characteristics of the gas supply industry under monopoly conditions, this paper analyzes the reasons for the lack of motivation of gas companies to provide perfect content services, and uses incentive theory to explore the incentive compatibility mechanism of gas companies' content services, in order to promote gas companies to use the Internet, big data, cloud computing technology to provide consumers with perfect content services, so as to enhance social harmony and stability.

Activation path of Yunnan folk pottery based on feature cognition and value evaluation

Yunnan is rich in cultural heritage, with its primitive pottery techniques coexisting with modern pottery techniques, and is known as the “Museum of Ceramic History”. Due to regional and socio-economic development factors, some folk pottery and craftsmen have faded out of sight or only circulated in a few small areas and specific environments. The study analyzes and summarizes the characteristics of Yunnan folk pottery and industry and evaluates the Yunnan folk pottery value based on the conditional valuation method. The study takes the folk pottery of the Bai nationality in Dali, Yunnan as an example and obtains the evaluation results of the purchasing motivation value of the pottery through a questionnaire survey. 45.26% of people pay for their existence value, 26.03% pay for their choice value, and 28.71% pay for their legacy value. Based on the evaluation results, the study proposes targeted activation paths for Yunnan folk pottery, including innovative development combined with new technologies, highlighting the functional characteristics of pottery, and brand building. This study will help Yunnan folk pottery find more suitable ways of protection and inheritance in the rapid development of materials and technology. This study can help inheritors gain the possibility of sustainable development and provide reference value for the activation path of other traditional folk.

Carbon Footprint Accounting and Verification of Seven Major Urban Agglomerations in China Based on Dynamic Emission Factor Model

Amidst the prevailing trends in environmental conservation and the imperatives of energy conservation and emission reduction, the precision in assessing and forecasting carbon emissions has acquired heightened significance. The conventional emission factors, typically derived from historical data and empirical knowledge, often remain unchanged and fail to swiftly account for the reductions in emissions that are a consequence of technological advancements and green innovations. (1) This paper establishes a dynamic emission factor model, then uses city data and provincial data to verify the model, and compares the research results of other relevant researchers. The research results show that this method not only considers the different characteristics of energy types, but also considers regional differences and industry characteristics, making the emission factor more suitable for the actual situation. The results show that the method takes into account not only the different characteristics of energy types, but also regional differences and industry characteristics, making the emission factor more suitable for the actual situation. (2) This paper systematically compares the diverse methods for calculating the carbon footprints of Chinese provinces and cities. It encompasses a spectrum of methods, including carbon footprint accounting based on emission factors, accounting based on dynamically adjusted emission factors, and accounting from the perspective of carbon sinks. Each of these methods possesses its own set of applicable scenarios and inherent limitations. The emission factor method is apt for basic carbon emission accounting, while the adjusted emission factor method is tailored for scenarios where the evolution of technology and shifts in energy paradigms are pivotal. Concurrently, the carbon sink accounting framework is optimally suited for the evaluation of the carbon footprint within the realm of natural ecosystems.

CEO deaths and credit relationships: evidence from an emerging market

Abstract In a sample representing 40% of Peru’s formal economy, firms shocked by the death of their chief executive officer experience lower sales and a higher probability of exit, lower borrowing amounts and credit performance, and a reduced number of lenders compared with very similar firms. Existing lenders bear the negative consequences. Monthly risk assessments by lenders worsen immediately after the death events. The negative effects are observed across various firm sizes, while industry characteristics, incorporation, and family ties are relevant dimensions of heterogeneity. Lenders with a longer relationship history, and those less constrained for loan-making, protect themselves by introducing collateral clauses. (JEL D25, G30, L25).

Development of a starch-fermenting Zymomonas mobilis strain for bioethanol production

BackgroundBiorefinery using microorganisms to produce biofuels and value-added biochemicals derived from renewable biomass offers a promising alternative to meet our sustainable energy and environmental goals. The ethanologenic strain Zymomonas mobilis is considered as an excellent chassis for constructing microbial cell factories for diverse biochemicals due to its outstanding industrial characteristics in ethanol production, high specific productivity, and Generally Recognized as Safe (GRAS) status. Nonetheless, the restricted substrate range constrains its application.ResultsThe truncated ice nucleation protein InaK from Pseudomonas syringae was used as an autotransporter passenger, and α-amylase was fused to the C- terminal of InaK to equip the ethanol-producing bacterium with the capability to ferment renewable biomass. Western blot and flow cytometry analysis confirmed that the amylase was situated on the outer membrane. Whole-cell activity assays demonstrated that the amylase maintained its activity on the cell surface. The recombinant Z. mobilis facilitated the hydrolysis of starch into oligosaccharides and enabled the streamlining of simultaneous saccharification and fermentation (SSF) processes. In a 5% starch medium under SSF, recombinant strains containing Peno reached a maximum titer of 13.61 ± 0.12 g/L within 48 h. This represents an increase of 111.0% compared to the control strain's titer of titer of 6.45 ± 0.25 g/L.ConclusionsBy fusing the truncated ice nucleation protein InaK with α-amylase, we achieved efficient expression and surface display of the enzyme on Z. mobilis. This fusion protein exhibited remarkable enzymatic activity. Its presence enabled a cost-effective bioproduction process using starch as the sole carbon source, and it significantly reduced the required cycle time for SSF. This study not only provides an excellent Z. mobilis chassis for sustainable bioproduction from starch but also highlights the potential of Z. mobilis to function as an effective cellular factory for producing high-value products from renewable biomass.

Electron microscopy method in assessing the quality of cell cryopreservation

During its existence, electron microscopy has become one of the reference methods for assessing the structural and functional state of cells, tissues and organs, and an extensive evidence base has been formed that allows its use in the creation and formation of a biobank. The selection of sources for the literature review was carried out using keywords based on publications over the past 20 years. The publications presented in the review were selected by searching the eLIBRARY.RU, PubMed and Scopus databases. Based on foreign and domestic experience in the work of biobanks, we can distinguish four areas that determine the effectiveness of the use of electron microscopy studies as a component of its work. Firstly, it is control of microbiological contamination of a biological sample. The effectiveness of electron microscopy in detecting contamination of a biological sample with bacteria, fungi and viruses is comparable to the effectiveness of classical microbiological techniques. Secondly, it is a diagnostic tool that allows you to identify or confirm the presence in a sample of a pathogenetic process that is of interest for biobanking: tumor growth, atherosclerotic vessel damage, etc. Thirdly, it is quality control for cryopreservation of samples. A wide range of morphological characteristics of the ultramicroscopic structure of cells and microanatomical formations makes it possible to characterize the quality of cryopreservation and quantify the degree of damage, which contributes to the unification and standardization of biobanking. Transmission electron microscopy is the most informative in this matter. Fourthly, this is the basis for digitalization of the results obtained and the formation of an interdisciplinary biobank repository, which allows the use of “big date” technologies for fundamental research. The compliance of the biobank profile with the economic, scientific and industrial characteristics of the infrastructure of the industry or region is of great importance. Electron microscopy data are successfully combined with the results of molecular studies, which allows the formation of interdisciplinary metadata databases suitable for interregional and interdisciplinary scientific integrations. The latter makes it possible to use electron microscopy data to solve a wide range of applied and interdisciplinary problems. The above allows us to consider scanning and transmission microscopy methods as one of the key methods in the development of biobanking in the region.

Revisiting the Productivity Paradox: What is Next for the BRICS and European Banking Systems?

Information technology is a critical driver of productivity growth in modern economies. However, there has been no convincing explanation for the observed discrepancy in the literature, increasing suspicion on whether IT can improve institutional performance in contemporary banking markets. The fallacy of productivity adds credence to Robert Solow’s dictum, “You can see the computer age everywhere except in productivity statistics”. We employ two extensive bank-level datasets of 5,794 institutions across 37 nations to estimate the total factor productivity (TFP) payoffs from IT in BRICS and European markets. A DEA-based, Malmquist productivity index quantifies TFP change and its respective components. Findings provide evidence against the paradox as both regions experience IT-fueled productivity growth. Nevertheless, such associations vary across banking sector development, rationalizing how IT spending can explain productivity differences across nations. For BRICS banks, a significant proportion of TFP growth originates from frontier expansion instead of frontier progression, signaling a widening of technology gap. Contrastingly, IT has diminished the technology gap between European banks. Intra-country comparisons suggest that if IT-driven productivity growth is regarded as a nation’s long-term goal, industry characteristics should govern the distribution of knowledge capital.

Inter-firm imitation of artificial intelligence: Towards innovation and competitive edge in business

In an era where artificial intelligence (AI) is rapidly transforming businesses, executives are at the forefront of steering their organizations through the complexities of technology adoption. This article provides a practitioner-focused perspective on how executives can strategically manage the adoption and integration of AI to drive innovation and maintain a competitive edge through the dynamics of inter-firm imitation of AI. By leveraging theories of imitation, knowledge transfer, and competitive advantage, it discusses how firms adopt AI technologies by emulating their competitors and subsequent effects on their innovation capabilities. Research examines the implications for firm strategy, including the potential for competitive parity, role of absorptive capacity, and the influence of industry characteristics on the effectiveness of imitative AI-driven innovation. The paper introduces a conceptual framework that integrates imitation, AI adoption, and innovation outcomes, offering a strategic roadmap for firms navigating the complex landscape of AI technology. Ultimately, the article provides managerial recommendations for firms to harness AI imitation as a tool for sustained innovation and competitive differentiation, drawing insights from six distinct case studies.

Analysing the Impact of Capital Structure on Firm Value: A Study in Corporate Finance

Abstract: This study investigates the relationship between capital structure and firm value across various industries. Using a cross-sectional quantitative analysis, the research examines how different levels of debt, equity, and financial leverage affect firm value, measured by market capitalization and Tobin's Q. The findings suggest that firms with moderate debt levels experience enhanced firm value, benefiting from the tax shields provided by debt without incurring significant financial distress. However, excessive financial leverage negatively impacts firm value, as firms face increased risk of financial instability. The study supports key theories such as the trade-off theory and pecking order theory, demonstrating that capital structure decisions are influenced by factors such as firm size, profitability, and industry characteristics. The implications for corporate managers and investors include optimizing debt-equity balance to maximize firm value while managing financial risk. Future research should focus on industry-specific dynamics and longitudinal analyses to further explore these relationships.

축제 산업생태계 네트워크 구조 분석 : 명예 문화관광축제를 중심으로

The demand for the industrialization of festivals has become increasingly prominent both academically and in policy discussions. Approaching festivals from an industrial perspective is regarded as a key strategy for improving supply chain efficiency and expanding the festival business ecosystem. The demand for the industrialization of festivals is increasingly strong, both academically and in policy discussions. This study aims to analyze the structural characteristics (connectivity and cohesion) and positional characteristics (influence) of South Korea's festival industry through social network analysis, grounded in industry ecosystem theory. The research utilizes 595 expenditure data points from four major cultural tourism festivals in Korea. The data were preprocessed in Excel, using pivot tables to identify relationships between attributes. After data cleaning, the dataset was divided into node and edge files, which were analyzed using Gephi 0.10, an open-source Java-based software optimized for large-scale network analysis. This multidimensional approach was critical in visualizing and optimizing the network data. The findings reveal that Korea’s festival business ecosystem displays characteristics of early-stage industrialization, characterized by low network density and limited two-way interactions between actors. While cohesive clusters within the network show diversity, the influence of major networks remains low, highlighting the need for focused efforts to strengthen them. In terms of positional characteristics, festival organizations, venue construction industries, and content development companies were identified as influential actors. Academically, this study contributes to the empirical identification of the network structure within the festival business ecosystem, providing foundational data for understanding its dynamic changes. Practically, it offers policy recommendations, including fostering key actors to enhance cohesion and expanding opportunities for inter-company collaboration to further develop the ecosystem.

It's Time to Break Up: Dynamics Surrounding Young-Established Firm Alliance Duration

While young firms often benefit from their relationships with established firms, these relationships can be risky. Hence, during their relationship with established firms, young firms must constantly monitor signs of a failing partnership and terminate it before being in a disadvantageous position. However, discontinuing the alliance with an established firm can also be risky, especially if the young firm has limited alternative collaborative opportunities. Our study adopts the young firm's perspective and dynamically weighs the tradeoffs between the risks of continuing and discontinuing its relationship with established firms, thereby deciding on its termination. We first develop an analytical model to understand how the alliance duration (time from alliance formation to termination) between young and established firms is affected by alliance, firm, and industry characteristics. We then test the resulting hypotheses on a sample of 1,111 alliances with licensing deals formed between 159 established pharmaceutical firms and 448 young biotechnology firms during the 1986 to 2000 period, which straddles the technological discontinuity of combinatorial chemistry. Our empirical results provide partial support for the hypotheses derived from the analytical model, informing us of firms’ rational alliance duration decisions as well as their deviations from rationality. In presenting both optimal alliance duration decisions and suboptimal alliance duration practices, our mixed-method approach offers important implications for theory and practice.

Corporate Social Responsibility and Financial Performance of Nawiri Sacco Society Limited in Embu County, Kenya

This study explored the relationship between Corporate Social Responsibility (CSR) and financial performance in the context of Nawiri Sacco Society Limited in Embu County, Kenya. Given the dynamic nature of CSR and the divergent results from global studies on its impact on financial performance, this research aimed to shed light on whether CSR activities contributed positively to Nawiri Sacco's financial outcomes. Specifically, it examined how stakeholder expectations, regulatory compliance, CSR-related costs and risks, and industry characteristics affected the Sacco’s financial performance. The research employed a regression model to evaluate these factors, with a notable emphasis on how stakeholder pressures and regulatory frameworks shaped CSR's financial implications. Data was collected from 85 executive members through structured questionnaires, achieving an impressive 88.9% response rate, which supported the reliability of the results.The findings indicated a significant relationship between CSR and financial performance, revealing mixed effects among the different CSR factors. For instance, stakeholder expectations showed a negative impact on financial performance, suggesting that while stakeholder engagement was critical, excessive focus could strain financial resources. Conversely, regulatory compliance, cost implications, and industry characteristics demonstrated a positive association, highlighting the potential of CSR to improve financial outcomes when effectively managed. These insights reinforced the need for a balanced CSR strategy that aligned with both social responsibilities and financial goals. This study contributed to existing literature by focusing on a Sacco's CSR practices, adding a unique perspective on how socially responsible initiatives could affect financial performance in cooperative institutions, particularly within the Kenyan context.

Integrating Machine Learning for Enhanced Agricultural Productivity: A Focus on Bananas and Arecanut in the Context of India’s Economic Growth

AbstractAgriculture is one of the sectors that has an important impact, taking into account the problem of sufficient food supply on a global level. The process of predicting the yield of crops is among the most challenging undertakings in the agricultural industry. Agriculture is the main source of income for most developing nations. The purpose of the study is to investigate the significant role that agriculture plays in boosting India's economic growth. Additionally, the research considers the challenges posed by a growing population and a changing environment in terms of agricultural production and food security. The research focuses on analysing the complex characteristics of the agricultural industry, with a particular emphasis on the nutritional importance of tropical fruits, notably bananas and arecanut. These fruits are well-known for their vital nutrients and their role in ensuring world food security. This study acknowledges the importance of sustainable agriculture practices and incorporates sophisticated machine learning algorithms as dynamic tools to forecast crop yields and enhance decision-making processes throughout the crop development cycle. The main aim of this study is to create strong machine learning models and statistical techniques that can accurately predict crop yield by combining a variety of environmental parameters, then assess which models outperform each other. Assist yield projections may provide governments and policymakers with valuable information to make well-informed choices about food security, import–export policies, and resource allocation. It facilitates national- and regional-level food supply planning. The validation method utilises important metrics like R square (R2), Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE). This present research adds to the continuing discussion on using creative methods to promote sustainable agricultural growth and ensure food security.