Industry Level Research Articles

A Comprehensive and Structured Maturity Model for Measuring AI Adoption Levels in Industry 4.0

Industry 4.0 is driving significant transformations, even in complex and uncertain industrial environments. This concept represents an innovation strategy aimed at redefining the manufacturing sector, enhancing global competitiveness through cost reduction, more agile processes, and superior product quality. Concurrently, Artificial Intelligence (AI) is at the forefront of a profound shift in organizational management and operations, reshaping professional routines and redefining society's interaction with technology. The increasing complexity of business environments, particularly the inherent challenges within industrial sectors, alongside continuous technological advancements, establishes AI as a critical tool not only for fostering innovation but also for optimizing efficiency and enhancing competitiveness across all organizational domains. In this context, this study introduces a structured model grounded in the theoretical exploration of Industry 4.0 maturity models to assess the current maturity levels of AI utilization in the industry. Thus, this work presents the development of a standard for measuring AI adoption levels in Industry 4.0. This index will illuminate companies’ readiness and proficiency in integrating AI into both daily operations and strategic processes. Through the continued application of this tool, companies will also gain insights into their growth across the evaluated domains.

Arginine accumulation suppresses heat production during fermentation of the biocontrol fungus Beauveria bassiana.

Beauveria bassiana (Bb) is one of the most widely used biocontrol agents, and its products constitute more than one-third of the global market share of fungal insecticides. Solid-state fermentation (SSF) is widely used in the production of Beauveria bassiana (Bb) because of its economic practicality and high production efficiency. However, the heat generated during fermentation can sharply reduce both the yield and quality of Bb, and current industrial methods to mitigate high temperatures during fermentation are inadequate, leading to increased production costs. Thus, exploring the underlying mechanism of how heat is produced by Bb is crucial for improving the SSF procedure and yield. This study employed multiomics data analysis of Bb during SSF to explore the relationships between fungal fermentation and environmental factors. We found that the heat production period for SSF was 12 hours to 48 hours post-inoculation. To further explore the underlying mechanism during this heating period, we identified 454 temperature-correlated metabolites (TCMs) and 1,994 temperature-correlated genes (TCGs). Annotations of the above TCMs and TCGs revealed significant enrichment in the arginine biosynthesis pathway; specifically, the expression level of glutamine synthetase, a TCG, decreased with fermentation time, whereas the expression levels of the TCGs L-arginine and L-glutamine increased with fermentation time, and glutamine synthetase and L-glutamine in the arginine biosynthesis pathway cycle produced the end product L-arginine. Furthermore, when the substrates of the SSF were treated with exogenous arginine, the temperature peak of the SSF significantly decreased with increasing concentration of exogenously added arginine.IMPORTANCEA large amount of experimental evidence from the field has shown that Bb is an irreplaceable mature product that protects the health of our agriculture and ecosystem. In addition to high efficiency and host extensiveness, low cost is a critical merit that makes Bb products frequently used in the field. However, the growing cost of power and labor in the Bb industry, especially the SSF procedure, has significantly increased the price of its products, thus restricting the use of Bb in the field. This study not only fills the theoretical knowledge gaps concerning the molecular basis of the interrelationship between Bb and the fermentation environment during SSF but also provides an economical and applicable strategy (the addition of arginine to the fermentation media) to further lower the cost and increase the yield of Bb during SSF at the industrial level.

The panel threshold analysis of digitalization on manufacturing industry’s green total factor productivity

Green and sustainable development of manufacturing industry has become the developing trend, and green total factor productivity is an important indicator for measuring the green growth of the manufacturing industry. The rapid development of digitalization provides new opportunities for the improvement of manufacturing industry’s green total factor productivity (IGTFP). However, there exists two different perspectives of “digital promotion effect” and “digital inhibition effect” presently, which causes “digital paradox”. That is, digitalization may have a non-linear effect on IGTFP. Therefore, this study focuses on the industry level and aims to test the threshold impact of digitalization on IGTFP. Furthermore, this study tries to explore the boundary conditions and applicability of the green driving effect of digitalization on sub-industries from the perspective of heterogeneous technological innovation abilities in different industries. The empirical study is based on the panel data of 29 manufacturing industries in China 2012–2019. The empirical results show that: (1) Digitalization has a significant threshold impact on IGTFP, and the research results are still robust according to changing the threshold variable algorithm and carrying on a Winsorize test. (2) Industry technological innovation (ITI) plays a threshold role in the process of digitalization impact on IGTFP. (3) Heterogeneity analysis shows that the impact mechanism varies depending on differentiated industry factor intensity and industry pollution degree. Therefore, policymakers should formulate differentiated industry digitalization strategies.

Calibration of parameters and predictive control strategy of a wind turbine for improvement of energy harvesting

Applied mathematical modeling of the various energy resources has contributed widely in their design and operation improvements. Among renewable energy sources, wind energy systems have gained a significant attention for their rapid and continuous growth, which resulted from their cost effectiveness and clean power generation. However, research effort on the industry and university levels is still needed to enhance the characteristics of existing wind turbines and allow larger amounts of their share. This thesis presents an accurate model of a wind turbine (TWT-1.65) system for time-based dynamic simulations. The parameters of the power coefficient have been identified, calibrated and verified using different meta-heuristic optimization techniques, which are the Wild Horse Optimizer (WHO), Whale Optimizer (WO), and Genetic Algorithm (GA) to enhance the model accuracy over the previously related studies. The new version of the parameters has resulted in a higher accuracy while being practically meaningful, with the best achieved MSE of 0.006. The system model has been then integrated with two predictive controllers which are the linear Model Predictive Control (MPC) and Neural Network Predictive Control (NNPC) to regulate the pitch angle trends for the target of maximum energy harvesting. With proper selection of the controllers’ parameters, off-line simulation studies have shown improved production trends of the power output with constrained and safe trajectory of the pitch angle, which can be translated to be an improve in the total average harvested power of 34% and 44.5% over the complete time window of 5760 min using NNPC and Linear MPC respectively.

Microbial engineering for monocyclic aromatic compounds production.

Aromatic compounds, serve pivotal roles in plant physiology and exhibit antioxidative and antimicrobial properties, leading to their widespread application such as in food preservation and pharmaceuticals. However, direct plant extraction and petrochemical synthesis often struggles to meet current needs due to low yield or facing economic and environmental hurdles. In the past decades, systems metabolic engineering enabled eco-friendly production of various aromatic compounds, with some reached industrial levels. In this review, we highlight monocyclic aromatic chemicals, which have relatively simple structures and are currently the primary focus of microbial synthesis research. We then discuss systems metabolic engineering at the enzyme, pathway, cellular and bioprocess levels to improve the production of these chemicals. Finally, we overview the current limitations and potential resolution strategies, aiming to provide reference for future studies on the biosynthesis of aromatic products.

Measurement and Decomposition Analysis of Occupational Income Inequality in China

Using the China CFPS database, this paper measures the degree of intra-occupational inequality in China with the Pareto coefficient and uses the generalized entropy index to decompose the top income gap by region as well as by industry. The empirical results show that, firstly, the degree of income inequality between occupations in China has increased significantly in recent years. The provinces with a higher degree of income inequality between occupations are mostly located in the more economically developed regions in the central and eastern parts of the country, while the degree of inequality between occupations in the western part is lower. Secondly, the highest-income occupations are mainly in the manufacturing industry, with relatively high levels in the construction industry, the education sector, the wholesale and retail trade, and public administration and social organizations, while the levels in other occupations are relatively low. Lastly, the top income gap primarily originates from within industries. However, the contribution rate of the top income gap between industries is gradually increasing, while the contribution rate of the top income gap within industries is gradually decreasing.

A simple and inexpensive design of radioactive source for accurate level and height gauging in petrochemical industries

A simple and inexpensive design of radioactive source for accurate level and height gauging in petrochemical industries

Synergistic governance efficiency of industrial pollution and CO2 emissions under the digital economy.

Using panel data for 284 Chinese cities, this study explores the nonlinear relationship between the digital economy and the synergistic governance efficiency of industrial pollution and CO2 emissions (SGEIPCE). The study also investigates the transmission mechanism of two-way knowledge flows within this relationship using the double fixed effect model and two-stage least square method. The results show that the digital economy has a significant U-shaped relationship on the SGEIPCE: the impact first decreases and then increases. When the level of digital economy exceeds infection point, the SGEIPCE increases. The marginal effect identified through the heterogeneity analysis indicates that Chinese cities with high innovative talent agglomeration and low industrial Internet level are the first to cross the inflection point of the U-shaped relationship, and the promoting effect of the digital economy on the SGEIPCE is greater in these two types of cites. Further, when the digital economy crosses the inflection point, it indirectly improves the SGEIPCE by increasing the level of knowledge absorption and knowledge overflow. Knowledge overflow is the most critical transmission mechanism by which China's digital economy affects SGEIPCE. These results provide empirical support and a decision-making basis for promoting the mutually beneficial cooperation between digital economy and industrial synergistic governance.

Firm demography in Russian industry in the context of small business specifics: Is there a silver lining?

In this article, an empirical assessment of demographic changes in Russian manufacturing industries has been carried out for the first time. We mainly focus on the analysis of business death and the structural analysis of closed firms. The empirical basis for the study was provided by data from Rosstat and the Central Bank of Russia for 2005—2023, as well as a sample of 262,719 Russian manufacturing enterprises that were liquidated between 2016 and 2022. Methods of fundamental analysis, contextual, and structural approaches were used: the study was conducted at both the macro-level and the industry and individual enterprise levels, considering business birth and death rates, proportions of active and inactive firms, and the structure of closed companies by age, closure type, and degree of activity. The calculation of a modified death rate in industry has been carried out, taking into account the closure of only those enterprises whose death causes real damage to the economy. Its value turned out to be ten times lower than the traditional Rosstat coefficient. This proves that the well-established opinion about negative trends in business demography in Russia cannot be considered objective, as the death rate has been overestimated, and the trend towards its growth in most cases is due to the exclusion of economically inactive firms from USRLE (with zero balance sheets and fly-by-night companies).

Flagship demonstration of industrial-scale production of nutrient resources from mealworms to develop a bioeconomy new generation

Flagship demonstration of industrial-scale production of nutrient resources from mealworms to develop a bioeconomy new generation Farmÿng will demonstrate a large-scale, first-of-its-kind bio-based value chain producing sustainable and premium feed ingredients from an innovative origin: the Tenebrio molitor larvae. Farmÿng will expand the technology from demo plant to industrial plant level to process them into proteins and lipids for fish feed and pet food end markets. Manure will be recovered for soil fertilisation applications.

Economic winners and losers of the COVID-19 pandemic: evidence from New Zealand

PurposeThis study investigates the impacts of the COVID-19 pandemic on the primary, manufacturing, and services industries in New Zealand.Design/methodology/approachThis study uses quantitative research design and quarterly panel data at industry level. It uses macroeconomic data and novel contextual variables capturing the impacts of the social restrictions and lockdowns in a linear regression model which is estimated using Two Stage Least square and Difference-in-Difference approach.FindingsThe findings reveal a stark contrast between services and primary industry sectors, while the Information, Media, and Telecom sector experienced a substantial 2.8% GDP gain, driven by increased online activity and remote work, the Forestry and Logging sectors suffered significant losses of 5.5%. Furthermore, using a Difference-in-Difference estimation approach, the study provides evidence of asymmetric impacts on essential and non-essentials industry sectors. These disparities highlight the role of government policies, particularly in designating certain sectors as essential services, in shaping the pandemic's winners and losers.Research limitations/implicationsThis study focuses only on five macroeconomic variables such as GDP at industry level, unemployment, inflation, immigration and retail spending.Practical implicationsThe main findings are of particular importance to business strategist, managers and policymakers in New Zealand and other developed countries, as understanding the drivers that transmitted supply and demand shocks will enable better quantification and comprehension of the pandemic’s impacts that are still being felt globally.Originality/valueThis study provides new empirical evidence using macro and microeconomic level indicators that have not been studies empirically in the COVID-19 pandemic context.

Coopetition and internationalization of SMEs: an institutional approach

ABSTRACT This study highlights how formal institution agents (FIAs) promote internationalization of Small and Medium Enterprises (SMEs) in emerging economies. Our article takes a theory-building approach, conducting 21 interviews with representatives from SMEs and FIAs from three Brazilian industries and with industry experts. The roles of FIAs vary depending on industry characteristics and level of firm adherence and participation. Our results highlight SMEs compete domestically and cooperate internationally, while FIAs support national brand building and SME internationalization. We propose a framework that models how SME type and industry conditions affect coopetition, shaping the internationalization processes of SMEs from emerging economies.

Exploring the Impact of Executive Team Background Characteristics on Corporate Earnings Management

This study uses the modified Jones model, supported by upper echelon theory, to measure two types of earnings management strategies: accrual-based and real earnings management. The study examines how the overall background characteristics of executive teams, such as age, gender, education level, and experience in the financial industry, influence the choice of earnings management strategies. The findings suggest that executive teams nearing retirement age or with a higher proportion of women tend to avoid earnings management, while teams with higher education levels are more likely to engage in real earnings management.

Rethinking work-life integration: empowering talent in emerging hospitality and tourism work paradigms

Purpose This study aims to explore work–life integration (WLI) as a crucial mechanism underpinning the transformation of the hospitality and tourism industry from shifts in work paradigms, including rapid technological advancements, flexible work forms, quiet quitting, increasing awareness of well-being, cultural diversity and gender disparity. It further develops the coping strategies and research agenda. Design/methodology/approach Through the bridged lens of the work–life boundary theory and conservation of resources theory, this research critically analyzes the literature on emerging work paradigms and WLI and develops a conceptual framework guiding the systematic examination of the WLI mechanisms underpinning the influence from work paradigm shifts. Findings The analysis reveals the underpinning mechanisms in managing WLI, highlighting the importance of systematic and customized work–life management strategies in adapting to evolving work paradigms. An integrated conceptual framework is developed to guide future research and practical applications. Practical implications This study underscores the critical need for strategic WLI management, emphasizing its importance for sustainable industry development. It also proposes actionable work–life management strategies for stakeholders, aiming for positive outcomes at personal, organizational and industrial levels amid the paradigm shifts. Originality/value The comprehensive conceptual framework uniquely bridged two theories that afford a novel, interconnected and in-depth approach to analyzing how work paradigm shifts reshape the industry. It further broadens the research agenda on WLI, with promising research directions proposed for advancing the understanding of the ever-evolving hospitality and tourism work landscapes.

The Coordinated Development and Identification of Obstacles in the Manufacturing Industry Based on Economy–Society–Resource–Environment Goals

Given the deficiencies in the definition of connotation, the construction of index systems, and the coordination of targets within the research on sustainable development in the manufacturing industry, an evaluation index system for sustainable development has been established. This system includes economic benefits, social benefits, resource management, and environmental goals and is built upon a clear definition of the concept’s connotation. The CRITIC–entropy–TOPSIS–CCDM approach is employed for the computation of the coordinated development level of the manufacturing industry. To identify the main factors influencing the coupling coordination degree (CCD) from a mechanistic and compositional point of view, a logarithmic mean divisia index (LMDI) is used. Furthermore, the obstacle degree model analyzes the factors that restrict subsystem development. The results show the following. (1) The coordinated development level of the Chinese manufacturing industry has been maintained at 0.6–0.7, while the CCD of Hainan, Qinghai, and Xinjiang remains to be enhanced. (2) The key factor affecting the CCD is the coupling degree. The evaluation value of the economy and employment system determines the trend of coordinated development in the regional manufacturing industry. (3) The economic and employment scenarios in most provinces (cities) led to a significant decrease in the CCD compared to the baseline scenario, with average growth rates of −10.55% and −12.69%. This suggests that policymakers’ priorities significantly influence the CCD. The research presents a theoretical framework for assessing the sustainability of the manufacturing industry, offering valuable insights to guide the industry towards more sustainable practices.

Study of the Hibridation of Ablation Casting and Laser Wire Metal Deposition for Aluminum Alloy 5356

The rapidly growing field of metal additive manufacturing (AM) has enabled the fabrication of near-net-shape components with complex 3D structures in a more reliable, productive, and sustainable way compared to any other manufacturing process. The productivity of AM could be significantly increased combining conventional and AM technologies. However, the application at an industrial level requires the validation of the AM process itself and the assurance of the soundness of the junction between the substrate and the deposited metal at a sufficiently rapid metal deposition rate. In this work, the validation of additively manufactured samples of Al-5356 alloy was performed. These were manufactured partially via an ablation casting process and partially via laser metal deposition using a metallic wire (LMwD). The deposited material showed low porosity levels, i.e., below 0.04%, and a small number of lack-of-union defects, which are detrimental to the mechanical properties. In the tensile samples centred at the junction between the ablated and deposited materials, it was found that when the AM part of the sample exhibited no lack-of-union defects, the region manufactured using LMwD showed higher strength than the ablation-cast part. These results suggest that the combination of ablation casting and LMwD is a competitive technique for the manufacturing of Al-5356 alloy parts with complex geometries.

Analysis of human capital for infrastructure development relation to industrialization in Indonesia

This research aims to analyze the value-added between infrastructure and industrialisation in Indonesia and both as critical aspect that supports the achievement of 9 Sustainable Development Goals (SDG). SDG 9 focuses on building durable infrastructure, promoting inclusive and sustainable industrialisation, and encouraging innovation. This research focuses on analyze the impact of infrastructure on the level of industrialisation, taking into account the modulation by human capital. Data analysis was conducted using Stata version 16 software with the aim of testing the direct impact of variables as well as testing the indirect impact through the application of the Sobel test. The Sobel test aims to analyse the dataset from 1990-2022. This research specifically explores the Indonesian context as a case study, identifying infrastructure variables that are significant in shaping the level of industrialisation in the country. In addition, this research involves an in-depth analysis of the role of human capital in moderating the impact of infrastructure on the level of industrialisation. The significance of this research lies in its potential to address critical knowledge gaps in understanding the complex interplay between infrastructure development, industrialization, and economic growth in Indonesia. The implication of the study that investment on infrastructure for industrialization can absorb labor.

The Nexus Between ICT Diffusion, Financial Development, Industrialization and Economic Growth: Evidence from Sub-Saharan African Countries

ABSTRACT This study examines the nexus between ICT diffusion, financial development, industrialization, and economic growth using a novel panel VAR approach in the generalized method of moments (GMM) estimation. Different proxies were used to measure the aforementioned variables, diverging from the commonly used measures in prior literature. Based on panel data covering 45 countries from 2000 to 2018, the empirical results suggest that there is bidirectional causality between ICT diffusion and economic growth, financial development and industrialization, financial development and economic growth, as well as industrialization and economic growth. The findings further provide evidence that financial development, levels of industrialization, and economic growth are not significant or positive predictors of ICT diffusion. The study’s implications for policy are profound, suggesting that SSA governments should adopt a holistic approach to economic policy development, integrating ICT, financial, and industrial policies to harness these interdependencies effectively.

Standardization for Data Generation and Collection in the Dairy Industry: Addressing Challenges and Charting a Path Forward.

Standards for data generation and collection are important for integration and for achieving data-driven actionable insights in dairy farming. Data integration and analysis are critical for advancing the dairy industry, enabling better decision-making, and improving operational efficiencies. This commentary paper discusses the challenges of and proposes pathways for standardizing data generation and collection based on insights from a multidisciplinary group of stakeholders. Drawing from a series of meetings of industry experts, academics, and farmers organized under the Dairy Brain Project's Coordinated Innovation Network (CIN), we explore the benefits of creating uniform data generation and collection protocols to ensure compatibility and reliability across different data sources. Key insights include the importance of defining standardization at both farm and industry levels, the role of education and incentives, and the potential for using existing frameworks such as the International Committee for Animal Recording. Additionally, we highlight industry-specific case studies, including successful examples from Brazil such as GERAR, which focuses on reproductive performance data, and Labor Rural, which integrates data from multiple farms to provide valuable insights to farmers and milk processors. The paper concludes with recommendations for implementing these protocols and highlights the need to foster collaboration among stakeholders for the successful implementation and adoption of standardized data generation and collection protocols in the dairy industry.

Banking Market Structure and Heterogeneous Response of Bank Lending to Monetary Policy: Evidence from Uganda

This paper investigates the heterogeneous response of bank lending following a monetary policy change. The study was conducted in the context of developing countries and is based on dynamic panel error correction methods using quarterly Ugandan bank level data for the period 2009 - 2019. Results support the presence of heterogeneity in bank lending response to monetary policy changes by bank size and ownership type. Specifically, monetary policy pass through is weaker in large foreign banks and stronger in smaller Pan African banks. Moreover, bank lending response to monetary policy is asymmetric with insignificant effects when the policy rate is falling. Risk, government borrowing, capital, and liquidity at the bank level, competition at the industry level, and inflation at the macro level are some of the factors that explain the response of bank lending to monetary policy.