Competitiveness Of Manufacturing Industry Research Articles

The Influence of Asset Intensity, Employee Intensity, and Intellectual Capital on the Competitiveness of Manufacturing Industries: Cost Stickiness as a Mediating Variable

The low competitiveness of the Indonesian manufacturing industry is a current phenomenon causing a decline in Indonesia's manufacturing industry competitiveness ranking below that of Singapore, Malaysia, and Thailand. This indicates that Indonesia needs to enhance four factors: national economic performance, policy efficiency, business efficiency, and infrastructure. The purpose of this research is to examine the influence of factors affecting competitiveness. The data analysis technique used in this research is multiple linear regression analysis. The population in this study is companies listed on the Indonesian stock exchange. Data collection used purposive sampling method, with a total sample size of 212, with a sampling quota of 109 companies that have both sales increases and decreases annually. In this study, there are independent variables such as Asset Intensity, Employee Intensity, and Intellectual Capital, dependent variable Competitiveness, and mediating variable Cost Stickiness. The results of the research show that the variables of employee intensity and intellectual capital have an influence in this study, whereas asset intensity does not have an influence in this study. Additionally, Cost Stickiness has not been able to mediate the influence on Asset Intensity, Employee Intensity, and Intellectual Capital.

Optimization of The Use of The I-24/7 Network System by Bagkominter to Overcome Transnational Crime The Realization of Modern Police in The Era 4.0

<em>Indonesia has committed and is ready to implement Industry 4.0 to build a globally competitive manufacturing industry. Polri participates in supporting Indonesia towards the 4.0 era. Through precision towards modern policing, it is hoped that all police officers must be able to make good use of digital technology and continuously improve their capabilities in its implementation. The International Communications Section or abbreviated as Bagkominter has the main task of organizing and developing an information exchange system in efforts to prevent and eradicate international/transnational crimes through the INTERPOL network (I-24/7), ASEANAPOL and other information facilities; as well as collecting information and data processing. Based on the explanation described above, the problem will arise "How to optimize the use of the I-24/7 Network System by the Kominter Unit to Overcome Transnational Crime in the Context of Realizing Modern Police in the 4.0 era?". From these main problems, the author also creates problems, including: "How do you optimize human resources, budget support, infrastructure and methods in using the I-24/7 network system by Bagkominter?" The approach used in this thesis is qualitative by using descriptive analysis method. Data collection techniques using interviews. Data analysis techniques using data reduction. data presentation, and drawing conclusions. Based on the research results, it can be explained that there is still a limited number of personnel and personnel competence, the operating budget for the I-24/7 network system is still inadequate, the facilities and infrastructure owned are still inadequate and the methods for dealing with transnational crimes are still not running optimally</em>

Does digital transformation enhance the core competitiveness?-Quasi-natural experimental evidence from Chinese traditional manufacturing.

In the era of the digital economy, building an internationally competitive manufacturing industry with intelligent manufacturing as its main focus is the only way to promote the transformation of a country into a manufacturing power and achieve high-quality economic development. To explore whether Digital transformation can improve the core competitiveness of traditional manufacturing enterprises, and what factors affect this process, this study establishes the core competitiveness system of enterprises through the principal component analysis(PCA) method and discusses the above issues through the construction of a double difference model. The results of this research from China's traditional manufacturing industry are as follows. (i) The digital transformation of enterprises has significantly improved their core competitiveness and has a certain time lag effect. (ii) In the process of enterprise digital transformation, enterprise management capabilities, environmental uncertainty, and enterprise operational efficiency will positively enhance the results of enterprise digital transformation. (iii) The enhancement of core competitiveness caused by digital transformation is more significant for the market leaders and laggards. (iv) Compared with non-state-owned enterprises, the Digital Transformationn of state-owned enterprises has a more obvious effect on promoting their core competitiveness. (v) In comparison with enterprises with low government subsidies, the Digital Transformation of enterprises with high government subsidies plays a more significant role in promoting their core competitiveness. In addition, this study proposes policy guidance and practical guidance for digital transformation to accelerate the promotion of core competitiveness of traditional manufacturing industry.

Identifying the skills requirements related to industrial symbiosis and energy efficiency for the European process industry

The need for sustainable production, efficient use of resources, energy efficiency and reduction in CO2 emission are currently the main drivers that are transforming the European process industry besides Industry 4.0. Since the potential of industrial symbiosis (IS) and energy efficiency (EE) about environmental, economic and social issues has been discovered, the interest in them is gradually increasing. The funding and investments for IS and EE are highly encouraged by the European Commission, while more and more policies as well as research and innovation (R&I) activities are initiated to promote European industry’s advancement towards a circular economy and CO2 neutrality. The aim is to maintain the competitiveness and economic progress of the industry. The key to build a competitive and sustainable European manufacturing industry is to create a competent, highly qualified workforce that is capable of handling the new business models coming with IS and EE requirements and digital technologies. We can generate this by identifying the skills needs and upskilling and reskilling the current workforce accordingly by delivering the suitable training programmes. Therefore, this work identifies the most critical skills needs related to IS and EE for six different energy-intensive sectors (steel, ceramic, water, cement, chemical and minerals) in Europe. The effect of the digital transformation on the skills needs is as well discussed. The identified skills are aimed to be included in vocational education and training (VET), tertiary education and other kinds of training curricula. We also identify the cross-sectoral most representative job profiles linked with EE and IS in these sectors and demonstrate the methodology for the selection process. Furthermore, we present a key tool for identifying the most significant current and future skills requirements. Also, we define the critical skill gaps of the European process industry using this tool. Once the skill gaps are defined, they can be reduced by delivering well-developed continuous trainings. We also link our work to the respectable ESCO, the European Classification of skills, competences, qualifications and occupations, to attain a common ground with other studies and frameworks, minimise the complexity and contribute to their work. Our work is developed to be an academic and industrial guideline to prepare well-developed training programmes to deliver the needed skills.

Segregation of Quality Products on the Production Line

In the highly competitive manufacturing industry, producing high-quality products is crucial for success and reputation. The issue of segregating quality products on the production line has emerged as a critical concern, necessitating effective strategies to tackle that problem. This project aims to design a quality control unit using controllers, sensors, and a robotic arm to segregate products based on height, substance amount, and cap presence. Ensuring product quality enhances customer satisfaction, improves production efficiency, optimizes resources, and boosts profitability through waste reduction and brand preservation. Workforce training will focus on quality standards and defect identification.

Segregation of Quality Products on the Production Line

In the highly competitive manufacturing industry, producing high-quality products is crucial for success and reputation. The issue of segregating quality products on the production line has emerged as a critical concern, necessitating effective strategies to tackle that problem. This project aims to design a quality control unit using controllers, sensors, and a robotic arm to segregate products based on height, substance amount, and cap presence. Ensuring product quality enhances customer satisfaction, improves production efficiency, optimizes resources, and boosts profitability through waste reduction and brand preservation. Workforce training will focus on quality standards and defect identification.

Impact of 3PL Outsourcing on Supply Chain Management in Manufacturing Companies in Norway: Case Study Norsk Hydro

3PL outsourcing is a practice in which a company outsources its logistics and supply chain management functions to a third-party logistics provider. By outsourcing logistics activities to a 3PL provider with advanced technology solutions, organizations can improve their supply chain management and achieve greater efficiency and effectiveness. Supply chain management is the coordination and management of all activities involved in the production and delivery of goods and services from raw materials to end customers. It includes activities like procurement, production, transportation, warehousing, and distribution. The research used the descriptive research design. The target population was 30 Manufacturing Companies in Norway.  The research did sampling of 40 participants that were chosen from the target population of 30 Manufacturing Companies in Norway. Questionnaires were utilized to gather the data. The study concluded that the partnership between manufacturers and 3PL providers has become increasingly critical in Norway's competitive manufacturing industry. This collaboration helps to streamline processes, enhance visibility, and optimize inventory management, leading to greater supply chain performance.  To ensure successful outsourcing, it is essential to conduct a thorough analysis of the supply chain, identify the right 3PL provider, establish clear communication and collaboration, develop a performance monitoring system, and regularly review and assess the outsourcing arrangement. It was recommended that before deciding on whether to outsource logistics functions to a 3PL provider, it is crucial to conduct an in-depth analysis of the current supply chain to identify areas that need improvement. The manufacturing company should establish a clear communication plan with the 3PL provider, outlining expectations, key performance indicators (KPIs), and regular reporting requirements. Effective communication and collaboration are crucial to the success of 3PL outsourcing. Keywords: 3PL Outsourcing, Supply Chain Management, Manufacturing Companies, Norway

Why Manufacturers Need to Engage Employees When Implementing a Smart Factory

Overview: Transformation into a smart factory has a soft side related to people, their motivation, perception, and skills. This study aims to examine staff perceptions about advantages, disadvantages, and barriers that challenge such transformation, and possible supporting measures. Our analysis of a company in a highly competitive manufacturing industry revealed the importance of the human element in the transition to a smart factory. Companies can facilitate the transition by ensuring all employees are aware of and understand the vision and implementation; by engaging with employees to learn about their thoughts and concerns; and by providing opportunities for employees to learn new skills for smart factory jobs. We offer recommendations to help practitioners succeed in transitioning to a smart factory.

FDI or International-Trade-Driven Green Growth of 24 Korean Manufacturing Industries? Evidence from Heterogeneous Panel Based on Non-Causality Test

Manufacturing, as an energy-intensive industry, plays a major role in economic growth. Its green growth is the focus of national planning for sustainable development, especially for a country such as Korea, which has a scarcity of fossil energy of its own. While internationalization has brought Korea scarce energy, serious carbon emissions have become a pressing issue. It is still necessary to explore the relationship between globalization and green growth in manufacturing. Thus, our paper aims to observe their relationship by using 24 manufacturing industries from 2011 to 2019. Through the panel Granger non-causality test and the Dumitrescu–Hurlin test, we find that imports and inward foreign direct investment (FDI) causes green growth at the overall manufacturing level, but their causality relationships exist in different industries. The green-growth causality relationship of inward FDI mainly exists in capital-intensive and internationally competitive manufacturing industries (manufacture industries of basic metals; furniture; food products; coke, briquettes, and refined petroleum products; and chemicals and chemical products, except pharmaceuticals and medicinal chemicals). Furthermore, the green-growth causality relationship of imports primarily exists in the fossil-energy-consumption-intensive manufacturing industry (manufacture industries of motor vehicles, trailers, and semitrailers and coke, briquettes, and refined petroleum products). Furthermore, in our regression analysis, we find that only inward FDI robustly promotes the Korean manufacturing sector’s green growth; the positive effect is in the range from 0.005 to 0.009. Though the parameter estimates are positive and significant for FDI, they are close to zero, suggesting very limited positive effects that are close to almost zero. Conversely, imports have no significant impact, which we speculate is related to the import structure of Korea. Hence, the Korean manufacturing development model suggests that developing countries with similar country characteristics need to develop and guide the formation of capital-intensive and competitive industries. Additionally, it is imperative to decarbonize energy-intensive industries and to work on renewable energy development and diffusion. Finally, it is essential to introduce various green monitoring mechanisms to reduce carbon emissions. The government needs to strengthen its support for research and development of innovative technologies to reduce carbon emissions as well as promote the development of environmental and energy-saving related professional service enterprises.

Why Competitiveness of Light Manufacturing Industries Matters to East African Countries: In the Case of Ethiopia, Rwanda, Tanzania, and Uganda

Competitive manufacturing industries help in modernizing the agriculture sector which forms the backbone of the country’s economy and reduces the heavily dependent of people on agricultural income. The purpose of the study assesses the competitiveness of manufacturing sectors in East African countries (Ethiopia, Rwanda, Tanzania, and Uganda) and explore the policy, strategies, and agreements of the countries to enhance the competitiveness of the manufacturing sectors, analyse the government’s supporting package and identify the constraints that hinder the manufacturing sector’s competitiveness. The result finds that most of the light manufacturing industries’ products produced are used to meet the needs of domestic demand even though the rate of employment increased. And their export performance was very weak. Therefore, the government focuses on the quality of human aspects and export goods than quantity through enhancement of the strategic plans to remain a competitive manufacturing industry.

An Empirical Study on the International Competitiveness of China's Manufacturing Industry

The manufacturing industry is the stabilizer of a country's national economy. The level of international competitiveness of the manufacturing industry determines the strength of a country's international competitiveness to a certain extent. Based on the relevant data from 30 China's provinces and cities from 2013-2021, this paper measures the international competitiveness of China's manufacturing industry by using factor analysis to form a comprehensive index of four single indexes measuring international competitiveness. The results show that the international competitiveness of China's manufacturing industry shows a geographical distribution pattern of "strong in the east and weak in the west." Based on the empirical findings, policy recommendations are proposed to improve the international competitiveness of China's manufacturing industry.

The impact of digital economy on the export competitiveness of China's manufacturing industry.

The digital economy is an important driving force for the high-quality development of the manufacturing industry. This paper uses 2013-2019 manufacturing panel data to empirically test the impact of digital economic growth on China's manufacturing export competitiveness. The results show that, first, the degree of integration of manufacturing and digital economy in the eastern region is higher than that in the central and western regions. Second, the development of the digital economy has indeed had a significant positive impact on the export competitiveness of China's manufacturing industry. Third, the digital economy has different impacts on the export competitiveness of manufacturing industries in different industries and regions. Based on the findings, some suggestions are made to further enhance the export competitiveness of China's manufacturing industry, such as paying attention to the development of digital infrastructure, optimizing the mode of integration of the manufacturing sector and the digital economy, and enhancing international collaboration in digital technology innovation.

The Economic Costs of Financial Distress

We estimate the economic costs of financial distress by exploiting cross-supplier variation in real estate assets and leverage, and the timing of real estate shocks. We show that for the same client buying from different suppliers, its purchases from suppliers in financial distress decline by an additional 10% following a drop in local real estate prices. The effect is more pronounced in more competitive industries, manufacturing and durable goods industries, for producers of less-specific goods, and when the costs of switching suppliers are low. Our results suggest that the indirect costs of financial distress are economically important.

Implications of Lean 4.0 Methods on Relevant Target Dimensions: Time, Cost, Quality, Employee Involvement, and Flexibility

Industry 4.0 is expected to provide a framework for coping with the increasing market dynamics and complexity in the highly competitive manufacturing industry. As the holistic approach of Lean Production has been applied in many industries as a standard for several decades, the interdependency of Lean Production and Industry 4.0 plays a crucial role. Thus, combining both paradigms into one integrated approach, commonly known as Lean 4.0, is of high topicality in the academic and industrial environment. However, the effects on target dimensions of Lean 4.0 in a manufacturing system remain unclear. In this scientific contribution, an impact analysis is conducted to measure the implications of Lean 4.0 on relevant target dimensions. The intention is to unhide relevant impacts and support manufacturers’ decision-making for reaching aspired objectives. Lean 4.0 use cases are created based on existing literature to assess concrete Lean 4.0 scenarios concerning the identified target dimensions. In expert interviews, following the Delphi study method, the relevant data is collected, in which the participants assess the implications of the use cases on the target dimension. The results show that the implications can highly differentiate depending on the applied Lean Production method and Industry 4.0 technologies. Thus, the choice of Lean methods combined with Industry 4.0 technologies needs to be well aligned with the manufacturer’s objectives, and additionally, possible trade-offs must be considered.

Competitiveness Evaluation of Manufacturing Industry based on Weighted Grey Correlation

Manufacturing industry is playing an important role in social and economic system,while it is “big but not strong” that is more prominent in developing regions. In order to upgrade manufacturing industry, competitiveness evaluation of manufacturing industry is studied based on weighted grey correlation using analytical hierarchy process and grey correlation analysis.First, statistical data concerned withmanufacturing industry competitiveness are summarized and compared in six developing regions. Then, an evaluation system of manufacturing industrycovering 22 indicators is constructed from economics, scale, R&D and ecology points of view. Furthermore, by using weighted grey correlation which is combined with analytic hierarchy process and grey correlation analysis methods, a simulation approach considering uncertainty on weight and identification coefficient is developed to make a more reliable assessment. Finally, on the basis of the models and approaches, an empirical study on manufacturing industry competitiveness is carried out and simulation results show that this novel approach can provide information and insights for competitiveness evaluation.

Bayesian Testing Procedure on the Lifetime Performance Index of Products Following Chen Lifetime Distribution Based on the Progressive Type-II Censored Sample

With the high demands on the quality of high-tech products for consumers, assuring the lifetime performance is a very important task for competitive manufacturing industries. The lifetime performance index CL is frequently used to monitor the larger-the-better lifetime performance of products. This research is related to the topic of asymmetrical probability distributions and applications across disciplines. Chen lifetime distribution with a bathtub shape or increasing failure rate function has many applications in the lifetime data analysis. We derived the uniformly minimum variance unbiased estimator (UMVUE) for CL, and we used this estimator to develop a hypothesis testing procedure of CL under a lower specification limit based on the progressive type-II censored sample. The Bayesian estimator for CL is also derived, and it is used to develop another hypothesis testing procedure. A simulation study is conducted to compare the average confidence levels for two procedures. Finally, one practical example is given to illustrate the implementation of our proposed non-Bayesian and Bayesian testing procedure.

Japan’s critical metals in the medium term: a quasi-dynamic approach incorporating probability

Japan has a competitive manufacturing industry that relies significantly on mineral resources, but few studies not initiated by the government exist to help us understand which metals are critical. In other major economies, concerns about the availability of and access to mineral resources have prompted researchers to suggest multiple methods to identify critical materials—mineral resources with high economic importance and a high risk of supply disruption—but the methods proposed so far, though sensible, should be improved. This study proposes a quasi-dynamic approach that incorporates probabilities to measure vulnerability to supply restriction as a way to improve the existing criticality methodologies. The study identifies unique probabilities for absolute price changes for 18 metals and identifies critical metals for Japan for 2000, 2005, 2011, and 2015. The study finds that niobium, molybdenum, rare earths, vanadium, tungsten, and cobalt are critical metals for Japan, and they will remain critical for the medium term (5–10 years). The study also proposes strategies for Japan to secure its supply of these critical metals.

An effective adaptive customization framework for small manufacturing plants using extreme gradient boosting-XGBoost and random forest ensemble learning algorithms in an Industry 4.0 environment

The prevailing competitive manufacturing industry calls for continuous customer satisfaction for business sustainability. With the emergence of the Industry 4.0 paradigm, product customization, which gives customers the means to personalized products to meet their needs, has become a strategy to increase companies’ value. High-tech manufacturing firms are already diving deep into Industry 4.0 standards adopting innovative strategies to outstand themselves in the market, while small manufacturing plants are slow in embracing the digital transformation. The high cost involved in acquiring indispensable resources and the lack of expertise are some of the obstacles low-tech businesses face in endorsing this new paradigm. Inspired by the customization challenges of a small manufacturing plant, our main research contribution is to develop an effective adaptive customization platform that encodes the customization data history of a small manufacturing plant, from a static database, into a dynamic machine learning model to produce personalized products for their customers accurately. Our research improves customers’ experience by reducing the customization system’s complexity consisting of inputting several parameters to obtain personalized products to a single entry. The back-end of the platform uses powerful machine learning (ML) algorithms like extreme gradient boosting (XGBoost) and Random Forest (RF) ensemble learning to match a single customer input to the desired customized product category. Our research experiments convey insights, such as the best scenarios to use XGBoost over RF algorithms for regression problems with non-linear data. The excellent experimental results achieved on both machine learning models show the merits of this customization platform.

Research on the development and competitiveness evaluation of manufacturing industry in Yangtze River Economic Belt

To promote the high-quality development of the Yangtze River economic belt is a major development strategy in China. As the lifeblood of the national economy, manufacturing industry is of great significance to realize the high-quality development of the Yangtze River economic belt. Based on the analysis of the overall situation of the manufacturing industry in the Yangtze River economic belt and the diamond model theory, this paper constructs an evaluation index system of manufacturing industry competitiveness with 4 first-class indexes and 16 second-class indexes, comprehensively evaluates the manufacturing industry competitiveness of each region by entropy method, and ranks the whole country. The results show that the manufacturing competitiveness of 11 provinces and cities in the Yangtze River economic belt is quite different and has obvious regional characteristics. The competitiveness of manufacturing industry in downstream regions is strong, while that in Yunnan and Guizhou provinces is weak, ranking at the bottom. Through in-depth analysis, it is found that there are some problems, such as unbalanced development, homogenization of industry, unreasonable layout of manufacturing industry. Combined with the development experience of excellent manufacturing industry and the regional characteristics of the Yangtze River economic belt, this paper proposes that we should speed up the industrial agglomeration, adhere to the innovation driven strategy, optimize the industrial layout and other ways to enhance the manufacturing competitiveness of the Yangtze River economic belt and promote the high-quality development of the Yangtze River economic belt.

The effects of liability dollarization on manufacturing competitiveness

Purpose- This study aims to investigate the effect of liability dollarization on competitiveness of sub-sectors operating in Turkish manufacturing industry. Within the scope of the NACE Rev-2 classification, the study used annual data covering the 2008-2016 period for the sub-sectors of the manufacturing industry. Methodology- A group of econometric tests; fixed effects and random effects approaches have been estimated from panel data methods. Findings- Variables affecting the manufacturing industry competitiveness were found to be liability dollarization, economic globalization index, energy prices, economic crisis, trade openness, and basket exchange rate. The variable to be used as the “measure of competitiveness” to represent the dependent variable is the ratio of net exports to foreign trade volume. The estimation results show that increase in liability dollarization rate, presence of the economic crisis, and change in energy prices negatively affect competitiveness of sectors, whereas economic globalization index and trade openness have a positive effect on the competitiveness. There is no statistical significant impact of basket exchange rate on competitiveness. Conclusion- The results of this study indicate that to increase sectoral competitiveness of Turkish manufacturing sector should be increased openness effect and decreased debt dollarization ratio. While sectors increase openness, they can reach new markets and so they can increase their trade activities. But, to increase sectoral economic activity strongly, their fund problems should be solved.