Standard Industrial Classification Research Articles

DYNAMIC CAPABILITIES AND PERFORMANCE OF FAMILY BUSINESSES IN EMERGING ECONOMIES

Dynamic capabilities analyze the sources and methods of better performance and wealth creation and capture by firms operating in environments of rapid technological changes. Based on this, The objective of this research was to analyze the relationship between absorptive, adaptive, and innovation capabilities on financial and non-financial performance of family businesses was analyzed in the context of emerging economies, a relationship that has not been analyzed in this context. Through the application of structural equation modeling in a sample of 235 family businesses of agricultural supplies and machinery, located in the G46 and G47 categories of the International Standard Industrial Classification – ISIC, the results allowed us to identify that absorptive capability has a positive influence on financial performance, while innovation capability has a positive influence on no-financial performance. No evidence was found that other capabilities were related to the performance of the organizations analyzed. In addition, it was shown that the size of the companies does not generate any moderating effect in the relationship between these variables. This study contributes to dynamic capabilities theory by exploring how absorptive and innovative capabilities influence financial and non-financial performance in a specific and underexplored context: family businesses in emerging economies. Furthermore, the importance of developing and enhancing absorptive and innovation capabilities is highlighted. This could lead to the implementation of training programs, investment in R&D, and adoption of knowledge management practices.

Structuring the Decision-Making Process Using Quantitative Options Valuation

This study focuses on enhancing decision-making processes in the construction industry by investigating quantitative decision-making models. The construction industry is known for its diverse projects and inherent risks. Effective decision-making is crucial for project success, but it faces challenges due to various factors. The research explores biases and heuristics in decision-making, specifically in entrepreneurial and managerial contexts, with a focus on two biases: overconfidence and representativeness. Data collection involved surveys administered to entrepreneurs and managers in prominent industrial sectors. The surveys measured the levels of overconfidence and representativeness in decision-making. Additionally, the study examined commonly used decision-making models in construction, including multi-criteria decision analysis, decision support systems, decision trees, and mathematical optimization techniques. The objective was to gain insights into applying quantitative models and improve the understanding of decision-making processes in construction projects. The survey achieved a response rate of 54%, and participating managers were categorized based on their two-digit Standard Industrial Classification (SIC) codes, specifically in the 1300, 3400, 3500, 3600, and 3800 categories. Rigorous statistical analyses were conducted to evaluate potential response bias. Comparing usable responses to non-respondents using chi-square tests, no significant evidence of bias was found (χ^2 (4) = 3.973, p = .59). Moreover, a further analysis explored potential response bias across the broader set of five two-digit SIC categories, and again, no significant evidence of bias was observed (χ^2 (5) = 1.782, p = .878). The findings of this study contribute to the improvement of decision-making in construction projects and provide valuable insights into the practical application of quantitative models. By addressing biases and exploring effective decision-making approaches, this research aims to enhance project success within the complex construction industry.

Efficiency of labor allocation: An observation in Indonesian Standard Industrial Classification (ISIC)

This study aims to analyze the efficiency and elasticity of the large and medium manufacturing industry sector in Indonesia from 2012 to 2020. The analysis focuses on the 24 subsectors within the 2-digit Indonesian Standard Industrial Classification (ISIC) principal groups 10 to 33. The efficiency level of the manufacturing industry sector was analyzed using the Cobb-Douglas production function model with linear logarithmic transformation. During the period 2012–2020, the production efficiency of the 24 ISIC 2-digit subsectors increased by an average of 445%, or 4 times higher than before. The ISIC 2-digit subsector (24 subsectors) had output elasticity values smaller than one (EL < 1) or inelastic 45 times. This indicates that the marginal value added of labor was lower than the average value added of labor. Therefore, the additional allocation of labor in large and medium industries tends to reduce the average value added of labor. The computer industry, electronic and optical goods computer, electronic and optical goods had the highest efficiency index in order, according to the data. This can be achieved by focusing on industries such as ISIC 17 (paper and paper goods industry), ISIC 31 (furniture industry), and ISIC 29 (motor vehicle, trailer and semi-trailer industry). To improve the efficiency of labor allocation, it is necessary to optimize the use of labor resources, increase productivity, and remain competitive in the market. To improve efficiency and elasticity, it is recommended to implement a robust workforce planning strategy that aligns labor resources with production needs. Additionally, matching the skills and abilities of the workforce with job roles is crucial. Finally, identifying tasks that can be automated using technology can also increase efficiency.

가업상속공제와 공동주택관리업 적용에 관한 연구

In order to support the stable life of the heirs and their families even after the death of the decedent, the Inheritance Tax and Gift Tax Act provides for deductions of a certain amount of money in consideration of the personal situation of the heirs and the material situation of the inherited property, and stipulates the family business inheritance deduction system.
 Accordingly, the Korea Housing Management Association announced that 2023. 9. Through an inquiry to the competent authority, the condominium management business was inquired whether the condominium management business is eligible for the deduction of the family business inheritance company, and the competent authority replied that the condominium management business is not a company eligible for the deduction of the family business inheritance business.
 However, it is necessary to re-examine whether the condominium management business is included in the family business inheritance deduction related to Article 15, Paragraphs 1 and 2 of the Enforcement Decree of the Inheritance Tax and Gift Tax Act.
 First, since the Special Act on the Safety and Maintenance of Facilities defines apartment houses as buildings and classifies them as facilities, it should be interpreted to include the business facility management and business resource service businesses among the business facility management and business resource service businesses that are subject to the family business inheritance deduction according to the Korean Standard Industrial Classification for small and medium-sized enterprises eligible for family business inheritance deduction.
 Second, the same article [Annex] of the same Act defines the types of business under the provisions of individual laws and includes the housing rental management business under the “Special Act on Private Rental Housing”, but the Private Rental Housing Act applies to matters not stipulated in this Act with respect to the construction, supply and management of housing, etc., and thus applies to the “Housing Act”, “Building Act”, “Apartment Housing Management Act”, and “Housing Lease Protection Act”.
 In the same way that the housing rental management business under the Special Act on Private Rental Housing is defined as a company subject to the family business inheritance deduction under the individual law, the condominium management business under the Apartment Housing Management Act, which has the same content, should be included as a company subject to the family business inheritance deduction under the individual law.

ANALYSIS OF EFFICIENCY AND ELASTICITY OF LABOR ALLOCATION IN MANUFACTURING INDUSTRY IN INDONESIA

AbstractThe purpose of this study is to analyse the level of efficiency and elasticity of the large and medium manufacturing industry sector during 2012 - 2020 in the Indonesian Standard Industrial Classification (ISIC) 2-digit level (major groups 10 to 33), consisting of 24 types of manufacturing sub-industries. In this study, the Cobb-Douglas production function model with linear logarithmic was used to analyse the manufacturing efficiency index. The results showed that: (1) during the period 2012-2020, the production efficiency of the 2-digit ISIC sub-sector (24 sub-sectors) increased on average by 445% or 4. 45 times, (2) all the output elasticity values of the 2-digit ISIC subsector (24 subsectors) were less than one (EL < 1), which showed that the marginal value added of labour was lower than the average value added of labour, so that the additional allocation of labour in large and medium-sized industries tended to reduce the average value added of labour, (3) the highest efficiency index in order were ISIC 26 (computer, electronic and optical products), ISIC 17 (paper and paperboard), ISIC 18 (electrical machinery and equipment), ISIC 19 (machinery and equipment) and ISIC 20 (machinery and equipment); ISIC 17 (paper and paper products); ISIC 31 (furniture) and ISIC 29 (motor vehicles, trailers and semi-trailers).

The GNAR-edge model: a network autoregressive model for networks with time-varying edge weights

Abstract In economic and financial applications, there is often the need for analysing multivariate time series, comprising of time series for a range of quantities. In some applications, such complex systems can be associated with some underlying network describing pairwise relationships among the quantities. Accounting for the underlying network structure for the analysis of this type of multivariate time series is required for assessing estimation error and can be particularly informative for forecasting. Our work is motivated by a dataset consisting of time series of industry-to-industry transactions. In this example, pairwise relationships between Standard Industrial Classification (SIC) codes can be represented using a network, with SIC codes as nodes and pairwise transactions between SIC codes as edges, while the observed time series of the amounts of the transactions for each pair of SIC codes can be regarded as time-varying weights on the edges. Inspired by Knight et al. (2020, J. Stat. Softw., 96, 1–36), we introduce the GNAR-edge model which allows modelling of multiple time series utilizing the network structure, assuming that each edge weight depends not only on its past values, but also on past values of its neighbouring edges, for a range of neighbourhood stages. The method is validated through simulations. Results from the implementation of the GNAR-edge model on the real industry-to-industry data show good fitting and predictive performance of the model. The predictive performance is improved when sparsifying the network using a lead–lag analysis and thresholding edges according to a lead–lag score.

Analyzing the incidence of silicosis across various industries in Taiwan: a study of occupational disease surveillance by linking national-based workers’ and medicoadministrative databases

ObjectivesThis study aimed to establish an occupational disease surveillance system by identifying high-risk industries for silicosis in Taiwan using a national database linkage approach. MethodsThe study was based on a comprehensive analysis of benefit claims from the National Labor Insurance Research Database and medical records from the National Health Insurance Research Database between 2004 and 2020, providing coverage for more than 88.5% of the workforce and 99.9% of citizens. Silicosis was defined as having received compensation for labor insurance benefits or having received a diagnosis of silicosis (International Classification of Diseases, 10th Revision: J62 or International Classification of Diseases, Ninth Revision: 502). The study used the International Standard Industrial Classification of All Economic Activities for industry-specific classification. Cox proportional hazard models were used to compare the silicosis incidence and risk among each industry and identify high-risk industries for silicosis. ResultsThis study analyzed 1466 cases of silicosis between 2004 and 2020 and found that 28 industries had incidence rates of over 40 cases per 100,000 workers, indicating more than double the risk of developing silicosis. Of these industries, 14 were considered high risk (relative risk of over four times). Among these, this study identified industries rarely mentioned in the past, such as wholesale of brick, sand, cement, and products, artistic creation, landscape construction, and materials recovery. Stratification by years of work experience reveals those industries such as quarrying of stone, sand, clay, and other mining, construction of buildings, landscape construction, site preparation, foundation and structure construction, building completion and finishing, manufacture of ships, boats, and floating structures, and plumbing, heat, and air conditioning installation display higher hazard ratios for individuals with <10 years of work experience. ConclusionsThe current surveillance system has identified certain industries that are at a higher risk of developing silicosis, which could be used for future occupational epidemiological surveys and targeted preventive measures in these sectors.

Occupational characteristics and risk factors associated with endometriosis among Korean female workers.

Endometriosis is a chronic and debilitating condition that affects daily working life. Characterization of the factors associated with endometriosis in the working population can facilitate the development of prevention and intervention strategies for those at risk of endometriosis. This population-based retrospective study was conducted using the 2007-2015 National Health Insurance Service-Female Employees database. Overall, 151,386 female workers aged 15-64 years were included in the study. Participants with endometriosis were identified using the diagnosis codes in the claims data. Multivariable Cox regression analyses were used to evaluate the effect of sociodemographic, lifestyle, health, and occupational factors on endometriosis risk. Of the 151,386 participants, 4,457 were diagnosed with endometriosis. The risk of endometriosis was significantly higher in 41-60 years group (HR = 1.47 (95% CI, 1.06-2.04)) and in those with body mass index (BMI) < 18.5 kg/m2 (HR = 1.16 (95% CI, 1.05-1.27)) than 15-20 years group and those with normal BMI, respectively. According to the international standard industrial classification, occupational groups with financial and insurance activities, public administration and defence, compulsory social security, and manufacturing were at a higher risk of endometriosis. Although there was no significant association between the risk of endometriosis and type of work, the cumulative prevalence of endometriosis from 2007 to 2015 continued to rise in office workers, manual workers, and both types of workers together. The risk of endometriosis was closely linked to the occupational characteristics of female workers. This study provides a foundation for developing occupational safety and health guidelines for female workers.

Personal data protection compliance assessment: A privacy policy scoring approach and empirical evidence from Thailand's SMEs

Privacy policies, intended to provide information to individuals regarding how their personal data is processed, are often complex and challenging for users to understand. Businesses often demonstrate non-compliance with personal data protection laws, ranging from the absence of privacy policies to the existence of policies that do not adhere to legal requirements. This paper aims to (1) develop a quantitative and systematic tool for evaluating privacy policies' compliance with the Personal Data Protection Act (PDPA), (2) assess compliance among Small and Medium Enterprises (SMEs) in Thailand, and (3) provide recommendations for enhancing compliance practices. To achieve this, we proposed a multi-criteria privacy policy scoring model integrated with comprehensive statistical data analyses. The privacy policy scoring model consists of ten privacy principles and 31 privacy criteria, providing a structured framework for evaluating privacy policies. During a two-year postponement period for enforcing the PDPA law, we conducted a stratified random-sampling survey of 384 SMEs to evaluate their privacy policies using the proposed scoring model. The accomplished results revealed significantly lower scores than anticipated, with the nationwide average score of SMEs reaching only 6.1909 out of 100 points. More than half of the SMEs collected personal data without announcing privacy policies, and those with privacy policies adhered to an average of only 12.15 out of 31 privacy criteria. These findings highlight the pressing need to improve compliance practices among SMEs in Thailand. The proposed methodology can be customized and applied to align with the requirements of personal data protection laws in other countries. Additionally, our findings indicate that compliance with the PDPA is influenced by the Thailand Standard Industrial Classification (TSIC) sections, suggesting the adoption of tailored approaches by policymakers to address the specific needs of different TSIC sections.

Pollution Haven Hypothesis and the Bilateral Trade Between India and China

The pollution haven hypothesis is studied from a bilateral trade perspective in this study, taking the reference of two Asian giants, namely, India and China. For this purpose, trade in pollution-intensive industries is analysed using data collected from the United Nations Comtrade dataset based on Standard Industrial Trade Classification codes for 1992–2019. The analysis helps us argue that between the two, China's demand is more pollution-intensive and India is the major supplier of pollution-intensive products. From an environmental perspective, this implies that China seems to be gaining from trade, and India is becoming a pollution haven in its trade with China.

The geography of commercial activities in business parks in Cape Town

ABSTRACT Business parks have increasingly become part of Cape Town’s industrial built environment over the last 25 years. It signifies a shift from large industrial premises to smaller units in communal industrial settings. This paper investigates the types of business activities found in the business parks using the conceptual underpinnings of location theory and industrial cluster theory. Online and fieldwork surveys of the businesses found in 49 business parks in Cape Town, South Africa, were conducted to compile a database of businesses and their activities. Each business was classified using the South African Standard Industrial Classification (SIC) codes to establish which economic sectors are represented in the business parks. It was found that the predominant economic sectors in business parks were the wholesale and retail trade, which included the repair of motor vehicles, motorcycles and personal and household goods and catering and accommodation, as well as the financial sector consisting of banking, insurance, real estate and business services. Manufacturing activities and commercial, social and personal services were also well represented. The findings indicate that business parks are the popular location for retail-orientated businesses and small manufacturing concerns and affirm the growing importance of the professional and business service sectors. The paper lays the groundwork for further investigation into the multi-scalar economic linkages of firms in business parks in Cape Town.

Best practices for measuring community resources across Canada: A comparison of coding classifications

AbstractSocial scientists, geographers, criminologists, and health scientists are often tasked with finding data to best capture the impact of “community context” on individual outcomes, including residential services, physical resources, and social institutions. One outlet for such data in Canada is Digital Map Technologies Inc. (DMTI) Spatial, which offers a national repository of over one million businesses and recreational points of interest. The database is generated through CanMap Streetfiles, which includes geocodes of each point's precise location. These data are available to researchers from their university data library and Esri Canada, but primarily available to private sector and government markets. That said, the goal of the current paper is to encourage researchers to access this rich yet under‐utilized data source. Each service, business, or resource in the DMTI Spatial database is assigned to a respective category using Standard Industrial Classification codes and North American Industrial Classification System codes. It is not clear, however, which is the more reliable coding criteria. We provide an overview of our review of DMTI Spatial data and take‐away suggestions for using this valuable resource for future research on meso‐level residential markers.

Cancer incidence among male construction workers in the Republic of Korea: a standardized incidence ratio analysis, 2009-2015.

Construction workers face an elevated risk for several types of cancer. Nevertheless, there is a lack of large-scale epidemiological studies examining the risk of all cancers in construction workers. This study aimed to investigate the risk of various cancers in male construction workers using the Korean National Health Insurance Service (NHIS) database. We used data from the NHIS database from 2009 to 2015. Construction workers were identified using the Korean Standard Industrial Classification code. We calculated the age-standardized incidence ratios (SIRs) and 95% confidence intervals (CIs) for cancer occurrence in male construction workers compared to all male workers. Compared to all male workers, the SIRs for esophageal cancer (SIR=1.24; 95% CI, 1.07-1.42) and malignant neoplasms of the liver and intrahepatic bile ducts (SIR=1.18; 95% CI, 1.13-1.24) were significantly higher in male construction workers. The SIRs for malignant neoplasms of the urinary tract (SIR=1.19; 95% CI, 1.05-1.35) and non-Hodgkin lymphoma (SIR=1.21; 95% CI, 1.02-1.43) were significantly elevated in building construction workers. The SIR for malignant neoplasms of the trachea, bronchus, and lung (SIR=1.16; 95% CI, 1.03-1.29) was significantly higher in heavy and civil engineering workers. Male construction workers have an increased risk for esophageal cancer, liver cancer, lung cancer, and non-Hodgkin's cancer. Our results indicate that tailored strategies for cancer prevention should be developed for construction workers.

ANALYSIS OF THE ECONOMIC POTENTIAL OF KARANGANYAR DISTRICT IN 2017-2022

The primary objective of economic development is to promote community prosperity. Assessing the progress of economic development relies on observing the region's economic growth, which is closely tied to the utilization of its existing economic potential. Maximizing the exploration and utilization of regional potential is crucial for fostering development. Identifying key sectors is instrumental in stimulating economic growth. The economic growth in Karanganyar Regency experienced fluctuations between 2017 and 2022. Thus, this study aims to identify the fundamental sectors in Karanganyar Regency, determine the potential and leading economic sectors to be developed, and contribute to economic growth in the region. Additionally, it analyzes the classification of regional economic sector growth in Karanganyar Regency from 2017 to 2022. The study employs secondary data, specifically time series data spanning from 2017 to 2022, obtained from the Central Statistics Agency (BPS) of Karanganyar Regency and Central Java Province. The data used encompass the Gross Regional Domestic Product (GRDP) by industry sectors based on the 2010 Standard Industrial Classification for Karanganyar Regency and Central Java Province. The research utilizes various methodologies, including Location Quotient (LQ) analysis, Growth Ratio Method (MRP), overlay analysis, and Klassen Typology. The findings of this study reveal that Karanganyar Regency, from 2017 to 2022, consists of (1) five fundamental economic sectors, (2) ten economically promising sectors with significant growth, (3) three potential economic sectors, and (4) three advanced and rapidly expanding sectors in Karanganyar Regency.

Disparity of Bladder Cancer Incidence Among Male Workers Across Industries: A Population Based Cohort Study From South Korea.

This study aimed to investigate the bladder cancer risk across workers' industries. This study was conducted using Korean National Health Insurance claims data. Workers were included in this study to build a retrospective cohort of the entire working population. Workers' industries were divided into 77 industries according to the Korean Standard Industry Classification division category. The standardized incidence ratio was calculated by comparing 77 industries according to the Korean Standard Industry Classification with the educational public officer. Bladder cancer risk was particularly high in the following industrial sectors: passenger land transport, except transport via railways; sea and coastal water transport; restaurants and mobile food service activities; telecommunications; and computer programming, consultancy, and related activities. Our result provides evidence regarding the disparity of bladder cancer incidence among male workers across industries.

Investigation of incidence and geographic distribution of gliomas in Canada from 1992 to 2010: a national population-based study highlighting the importance of exposure to airport operations.

Gliomas account for over two-thirds of all malignant brain tumors and have few established risk factors beyond family history and exposure to ionizing radiation. Importantly, recent studies highlighted the exposure to ultrafine particles (UFP) as a putative risk factor for malignant brain tumors. Clinical and geographic data encompassing all provinces and territories from 1992 to 2010 was obtained from the Canadian Cancer Registry and Le Registre Québécois du Cancer. Linear regression and joinpoint analyses were performed to assess incidence trends. Significantly higher and lower incidence postal codes were then interrogated using Standard Industrial Classification codes to detect significant industrial activity. In Canada, between 1992 and 2010, there were ~32,360 cases of glioma. Of these, 17,115 (52.9%) were glioblastoma. The overall crude incidence rates of 5.45 and 2.87 cases per 100,000 individuals per year for gliomas and glioblastomas, respectively, were identified. Our findings further revealed increasing crude incidence of gliomas/glioblastomas over time. A male predominance was observed. Provinces leading in glioma incidence included Quebec, Nova Scotia, and New Brunswick. Significantly lower crude incidence of glioma was found in Nunavut, Northwest Territories, Ontario, and Alberta. A putative regional clustering of gliomas was observed, with higher incidence rates in postal code areas correlating with industrial activity related to airport operations. This study describes the geographic distribution of the glioma disease burden and, potentially, identifies industrial activity related to airport operations as potentially being associated with higher incidence of this cancer.

Evaluating Green Efficiency of Manufacture Sector and Its Determinants in East Java Province

East Java is one of the provinces in Indonesia that carries out intensive development in the industrial sector to improve the welfare of its society. However, massive industrial activity will pose its challenges, such as increased emissions and environmental degradation. This study aims to determine the manufacturing sub-sector that produces CO2 emissions and has the lowest green efficiency as well as its determinant variables. There are three stages of analysis applied in this research i.e. carbon emission measurement, Slack Based Measurement-Data Envelopment Analysis (SBM-DEA), and Tobit regression. The study use 5-digit manufacturing subsector data based on the International Standard Industrial Classification (ISIC) system, obtained from the Indonesian Central Agency of Statistics (BPS) which is deflated against the East Java Regional Gross Domestic Product (GRDP) deflator with 2010 as the base year. The results of the analysis show that in general, the manufacturing subsector in East Java produces quite high CO2 emissions of 85.28 tons. The subsector with the highest average CO2 emissions in East Java in 2017 was the fertilizer industry, in 2018 the non-ferrous base metal manufacturing industry, and in 2019 the steel rolling industry. Then, the drying industry and tobacco depreciation became the sub-sector with the lowest average green efficiency in East Java Province in 2017. Meanwhile, in 2018 it was the milling industry of various nuts (including Leguminous) and in 2019 it was the coffee processing industry. The Tobit regression results show that the energy structure and industrial concentration have no significant effect on the green efficiency value of the manufacturing subsector. Meanwhile, spending on R&amp;D has a significant negative effect on green efficiency. Therefore, the recommendations given are encourage the use of environmentally friendly raw materials and fuels, increasing green innovation, and increasing consumer awareness regarding environmental issues.

N-Nitrosamines and their precursors in wastewater effluents from selected industries in Spain

N-nitrosamines (NAs), and N-nitrosodimethylamine (NDMA) in particular, are hazardous disinfection byproducts (DBPs) relevant when wastewater impacts drinking water sources and, in water reuse practices. Our study investigates the concentrations of NDMA and five additional NAs and their precursors in industrial wastewater effluents. Aiming to identify potential differences between industrial typologies, wastewaters from 38 industries belonging to 11 types of the UN International Standard Industrial Classification of All Economic Activities system (ISIC) were analysed. Results show that the presence of most NAs and their precursors cannot be linked to a specific industry type as these were in general very different within the classes. Nevertheless, N-nitrosomethylethylamine (NMEA) and N-nitrosopiperidine (NPIP) as well as precursors for N-nitrosodiethylamine (NDEA), NPIP and N-nitrosodibuthylamine (NDBA) could be rank with different concentrations between ISIC classes (p-value < 0.05). Specific industrial wastewater with notable high concentrations of NAs and their precursors were identified too. The effluents with the highest concentration of NDMA belong to the ISIC C2011 class (Manufacture of basic chemical), while the effluents with the highest concentration of NDMA precursors were from the ISIC C1511 class (Tanning and dressing of leather; dressing and dyeing of fur). Other relevant NAs found were NDEA in ISIC class B0810 (Quarrying of stone, sand, and clay) and ISIC class C2029 (Manufacture of other chemical products).

Could we estimate industrial wastewater flows composition using the UN-ISIC classification system?

Although we have extensive datasets on the location and typology of industries, we do not know much on their generated and discharged wastewater. This lack of information compromises the achievement of the sustainable development goals focused on water (Sustainable Development Goal 6) in Europe and globally. Thus, our goal was to assess to which degree the chemical composition of industrial wastewater could be estimated based on the industry's typology according to its International Standard Industrial Classification of All Economic Activities (ISIC) class. We collected wastewater effluent water samples from 60 industrial wastewater effluents (before any wastewater treatment process), accounting for 5 samples each of 12 ISIC classes, analyzed the composition of key contaminants (i.e. European Commission rated priority compounds and watchlist), and statistically assessed the similarities and differences amongst ISIC classes using ordination and random forest analyses. The results showed statistically significant linkages between most ISIC classes and the composition of produced wastewater. Among the analytical parameters measured, the random forest methodology allowed identifying a sub-set particularly relevant for classification or eventual contamination prediction based on ISIC class. This is an important applied research topic with strong management implications to (i) determine pollution emission caps for each individual ISIC class, (ii) define monitoring schemes to sample and analyze industrial wastewater, and (iii) enable predicting pollutant loads discharged in river basins with scarce information. These encouraging results urge us to expand our work into other ISIC classes and water quality parameters to draw a full picture of the relationship between ISIC classes and produced wastewater.

Analysis on technical structure and competitiveness of ICT manufacturing industries

In order to analyze the technical structure and international comparative advantage of the information and communication technology (ICT) manufacturing industry, a complete set of ICT manufacturing product categories has been constructed by matching National Economical Industry Classification (GB/T4754-2017) with Harmonized System (HS) Codes, based on the relevant definitions in International Standard Industrial Classification (ISIC). The proposed definition overcomes inherent defects such as inaccurate scopes, lagging data and rough categories, which are characterized by commonly utilized product-level based classification approaches. Within the given framework, this paper has designed the technology content related indicators from the perspective of production distribution, and divided ICT product categories into high-end, medium-end and low-end manufacturing classifications according to respective global shares. Then, we have calculated international market shares (IMS), revealed comparative advantages (RCA), and market penetration rates (MPR) of ICT manufacturing exports for major economies from 2010 to 2021. Finally, development characterizations of ICT manufacturing industries for China's Mainland are analyzed, and several practical suggestions are provided.