Type Of Industry Research Articles

Factors affecting the quality of accounting disclosures provided in the annual reports for Jordanian firms

AbstractThis study aims to cover the factors that affect Jordanian companies’ annual reports’ accounting disclosures within the country's regulatory framework. This study analyses the qualitative content of accounting disclosures in Jordanian service and manufacturing companies to ascertain whether Jordanian law affects the company's capacity to provide adequate disclosures to stakeholders and whether industry type affects disclosure quality. The content analysis results indicated that Jordanian firms are aware of the laws and regulations governing the preparation of annual reports. Still, corporate governance rules are insufficient. Furthermore, the results revealed that annual report preparers are committed to mandatory and voluntary but provide inadequate CSR disclosures. The findings showed that service firms outperform manufacturing companies in terms of paying attention to narrating events and taking action to reduce their impact. Multiple factors influence the quality of accounting disclosures in Jordan. As for a limitation, content analysis inherently involves some level of subjectivity in interpreting and coding data, which could introduce bias into the analysis. Nevertheless, conducting targeted studies on particular sectors within Jordan could yield valuable information regarding industry‐specific disclosure procedures and obstacles, which could be a future study.

Legacy and alternative plasticizers in sediment from artificial lakes and coastal waters near high-tech industrial complexes in Korea: Contamination, ecological risk, mass inventory, and dilution factor

Few studies have been conducted on the occurrence and distribution of alternative plasticizers (APs) in aquatic environments. Legacy plasticizers (LPs) and APs were measured in sediments collected from four artificial lakes and a bay surrounded by high-tech industrial complexes. Bis(2–ethylhexyl) phthalate (DEHP) and bis(2–ethylhexyl) terephthalate were major plasticizers. The concentrations of LPs and APs in sediment were similar, implying rapid adoption of APs. The highest AP concentrations were observed in sediment from a lake close to semi-conductor, liquid crystal display, and automobile manufactures, suggesting a preferential shift to APs. Contamination profiles of APs differed according to industrial type. The mass inventories of plasticizers in sediment from the lakes were 25 times higher than those from the bay. Hydrophobicity was a major factor determinant of dilution factors of plasticizers in sedimentary environments. The DEHP concentrations in lake sediments exceeded threshold values, indicating potential health risks to benthic organisms.

Mobility of trace elements in a coastal contaminated site under groundwater salinization dynamics

Water pollution is a significant issue resulting from past long-term actions. The remediation projects carried out under law constraints for industrial plants, which have been the major contributors to environmental and water pollution, are currently providing a significant amount of data about contaminated soil, surface waters, and groundwater. Most of such plants worldwide are in coastal zones. Based on a significant amount of chemical and environmental data for a coastal contaminated site subject to variable groundwater salinization, this study aimed to understand the mobility of some trace elements because of coastal zone dynamics. Data concerned 688 groundwater samples, including As, Hg, Cd, Crtot, Cu, Ni, Pb, V, Se, Zn, pH, electrical conductivity, chlorides, total organic carbon and organic contaminants as quantitative variables, enhanced by additional qualitative variables such as groundwater salinity, season, water level, precipitation, and industrial activity type to make the dataset as representative as possible of the site under investigation. The study used robust multivariate statistical analyses to analyse the complex dataset and explain the relevant factors influencing contaminant behaviour under different environmental conditions. The Multivariate Statistical Analysis distinguished three clusters of trace elements with diverse reactivity to changes in groundwater salinization. The first includes Se, Cu, Crtot, V, and Ni, showing the highest correlation with electrical conductivity and chlorides because of their high affinity to form chloride or organic chloride complexes and for ion competition. Zn and Pb cluster in the second group: they are less reactive to groundwater salinization and more influenced by cation and anion competition and organic matter. The mobility of Hg and As (third cluster) significantly correlates with Fe and Mn, underlining the dominant role of reductive dissolution of trace elements-bearing minerals (Fe/Mn/Al-oxy-hydroxides) and metal-organic complexes. The correlation between the clustering of variables in groundwater and soils shows the influence of sediment structure, mineral composition, and physical and chemical soil conditions on the distribution in soils of trace elements and their transport to groundwater. The study proposes a valuable approach for assessing the effects of salinization in contaminated coastal aquifers. It supports planning multi-purpose characterization and monitoring campaigns of contaminated coastal sites and provides guidance on the correct associated remediation projects.

Decarbonization pathways analysis and recommendations in the green steel supply chain of a typical steel end user-automotive industry

China's automotive industry, the world's largest producer and consumer, has reached a crucial stage in its transition from rapid expansion to high-quality and low-carbon development. Considering the decarbonization of the whole automotive industry, in addition to reducing the CO2 emissions from fuel supply and exhaust pipes, which account for 65–80 % of the total value chain CO2 emissions, the automotive industry should also accelerate the decarbonization of raw materials, which contribute to 18–22 % of these CO2 emissions. Many automotive manufacturers are collaborating with steel producers on green steel initiatives due to the high CO2 emissions from steel production, the integrated nature of the steel supply chain, and the need for early planning in low-carbon steel production routes transformation. To clarify the carbon emission characteristic of the automotive steel supply chain, this research establishes a mathematical method for calculating cradle-to-gate carbon footprint of automotive steel product based on BF (Blast furnace)-BOF (Basic oxygen furnace), Scrap-EAF (Electric arc furnace), and DRI (Direct reduced iron)-EAF steel production routes. The cradle-to-gate carbon footprints of BF-BOF, Scrap-EAF, and DRI-EAF steel production routes are 1711.84 kgCO2/t-sp (steel product), 916.39 kgCO2/t-sp, and 2738.53 kgCO2/t-sp. A projection of CO2 emissions in automotive steel supply chain from 2020 to 2060 has been investigated, taking into account production structure adjustment, scrap recycling, and low-carbon electricity adoption, as well as the demand for automotive steel products. Projections from 2020 to 2060 indicate that the CO2 emission intensity of the automotive steel supply chain will decrease by 28.25 % by 2030 and 93.99 % by 2060, with total emissions dropping by 28.47 % and 96.92 %, respectively. This research identifies effective decarbonization measures in the automotive steel supply chain, including internal and end-of-life (EOL) steel scrap recycling, which offer significant CO2 emissions reduction without increased costs, demonstrating high cost-effectiveness. In a word, this research provides a technical framework and data foundation for decarbonizing the automotive steel supply chain.

A Method for Evaluating Demand Response Potential of Industrial Loads Based on Fuzzy Control

Demand response (DR) can ensure electricity supply security by shifting or shedding loads, which plays an important role in a power system with a high proportion of renewable energy sources. Industrial loads are vital participants in DR, but it is difficult to assess DR potential because of many complex factors. In this paper, a new method based on fuzzy control is given to assess the DR potential of industrial loads. A complete assessment framework including four steps is presented. Firstly, the industrial load data are preprocessed to mitigate the influence of noisy and transmission losses, and then the K-means algorithm considering the optimal cluster number is used to calculate baseline load of industrial load. Subsequently, an open-loop fuzzy controller is designed to predict the response factor of different industrial loads. Three strongly correlated indicators, namely peak load rate, electricity intensity, and load flexibility, are selected as the input of fuzzy control, which represents response willingness. Finally, the baseline load of diverse clustering scenarios and the response factor are used to calculate the DR potential of different industrial loads. The proposed method takes into account both economic and technical factors comprehensively, and thus, the results better represent the available DR potential in real-world situations. To demonstrate the effectiveness of the proposed method, the case of a medium-sized city in China is studied. The simulation focuses on the top eight industrial types, and the results show they can contribute about 189 MW available DR potential.

The Choice of the Financial Year-End: Does It Matter? An International Evidence

This paper examines how specific firm characteristics (size, industry, audit fees and age) and firm performance influence the choice of financial year-end (December vs. non-December). The sample consists of companies from Australia, France, Germany, Japan, the United Kingdom and the United States to tackle issues with international diversity. Both domestic and international regulations for each country are addressed in developing expectations and conclusions. The results of the study show that December is generally becoming less and less ‘popular’ compared to a few years back. The results also revealed that December year-end firms tend to be larger and operate in certain types of industries with some industries preferring to close their books at certain dates, whether a December or a non-December month. As a result, financial-reporting comparability issues may arise if firms depart from the year-end chosen by most similar firms. It is also found that older firms tend to have December as their year-end, while relatively younger firms prefer a non-December year-end. Moreover, firms tend to prefer December as audit fees go up. Finally, firms with better performance are less likely to have December as their fiscal year-end. These findings show the importance of the topic and suggest conducting more research by academics and standard setters.

General unemployment and serious workplace injury rates: Workers compensation claims analysis from the Canadian province of Saskatchewan, 2007-2018.

There is conflicting published evidence that unemployment impacts workplace safety. Some studies suggest that the workplace injury rate decreases during economic contractions, while others propose an increased rate of injuries during periods of economic contractions. This study investigated the association between unemployment rates and traumatic work-related non-fatal injury (WRNFI) in Saskatchewan, 2007-2018, in order to provide new insight into injury prevention. Saskatchewan's retrospective linked workplace claims data from 2007 to 2018 were grouped by year, season, and worker characteristics (e.g., age and sex). Total employment, total labour force, and the number of unemployed workers from the Statistics Canada Labour Force Survey were grouped by year, season, sex, and age. These data were linked to the worker's compensation board injury claim data to determine the number of people at risk, serving as the denominator (offset term) for WRNFI rates, calculated as WRNFI cases per total employed workers. A negative binomial generalized additive model was used to examine the association between unemployment rates and WRNFI, adjusted for age, sex, industry types, and seasons. The WRNFI rate has declined since 2007. On average, workers aged 20-29years had the highest WRNFI rate (541.6 ± 84.8/100,000). Men had 3.2 times higher WRNFI risk than women (RR = 3.2, 95% CI 3.12-3.22), with the highest WRNFI risk observed in the manufacturing (RR = 1.68, 95% CI 1.63-1.73) and construction (RR = 1.67, 95% CI 1.63-1.72) industries. WRNFI risk decreased non-linearly with an increasing unemployment rate, indicating a pro-cyclic pattern. This analysis showed that WRNFI rates tracked unemployment rates. This suggests a need to increase prevention strategies and reduce disincentives for under-reporting during an economic downturn.

Investigating the links between questionable research practices, scientific norms and organisational culture

BackgroundThis study investigates the determinants of engagement in questionable research practices (QRPs), focusing on both individual-level factors (such as scholarly field, commitment to scientific norms, gender, contract type, and career stage) and institution-level factors (including industry type, researchers' perceptions of their research culture, and awareness of institutional policies on research integrity).MethodsUsing a multi-level modelling approach, we analyse data from an international survey of researchers working across disciplinary fields to estimate the effect of these factors on QRP engagement.ResultsOur findings indicate that contract type, career stage, academic field, adherence to scientific norms and gender significantly predict QRP engagement. At the institution level, factors such as being outside of a collegial culture and experiencing harmful publication pressure, and the presence of safeguards against integrity breaches have small associations. Only a minimal amount of variance in QRP engagement is attributable to differences between institutions and countries.ConclusionsWe discuss the implications of these findings for developing effective interventions to reduce QRPs, highlighting the importance of addressing both individual and institutional factors in efforts to foster research integrity.

A Study on the Layoff Problem After COVID-19 Based on Decision Tree Ensemble Methods

The COVID-19 pandemic, a cataclysmic event in modern history, has upended the global economy, precipitating extensive layoffs across diverse sectors. This study delves into the determinants of these workforce reductions through the lens of decision tree ensemble methods. By scrutinizing a comprehensive dataset, we harnessed statistical and machine learning algorithms to assess the significance of key variablesincluding industry type, geographic location, company development stage, and capital acquisitionon the scale of layoffs. This analysis further entailed predicting the total number of employees laid off and examining their distribution. The use of decision tree ensemble methods, such as random forests and gradient boosting, provided robust insights into the complex interplay of factors influencing layoff decisions. We discovered that industry type and company development stage were particularly critical in predicting layoff patterns, while geographic location and capital acquisition also played notable roles. This research offers a data-driven perspective on the layoff phenomena, shedding light on the multifaceted influences at play and offering a foundation for further inquiry and strategic policy development in response to economic downturns. By understanding these dynamics, policymakers and business leaders can better navigate future economic crises, potentially mitigating the adverse impacts on the workforce and promoting more resilient economic structures.

Research on the Impact Mechanism of ETS on Green Innovation in China’s High-Carbon Industries: A Perspective of Enterprise Heterogeneity

Green technology innovation is an important driving force for low-carbon development of enterprises. As a market-based environmental policy to promote greenhouse gas emission reduction, whether carbon emission trading scheme (ETS) can encourage enterprises to carry out green technology innovation under the background of “dual carbon” goal deserves further research. Taking Chinese A-share listed enterprises in the five major sectors as samples, this study constructed a modified Difference-in-Differences (DID) model to test the causal effect of ETS on green innovation in high-carbon industries. Three significant results can be summarized from the empirical study. Firstly, the ETS has a significant promoting effect on green innovation of high-carbon enterprises. And it can effectively promote high-carbon enterprises to achieve an average of a 13.24–19.56% increase in low-carbon innovation capabilities. Secondly, enterprises with different characteristics have heterogeneity in the impact of ETS implementation on green innovation. Secondly, the implementation of ETS exerts heterogeneous effects on green technology innovation across enterprises that possess diverse characteristics. Enterprises with a large capital scale (low equity concentration) have a more significant promoting effect than those with a small capital scale (high equity concentration). Thirdly, the green innovation effect of ETS exhibits significant heterogeneity across different types of industries. In the mining, manufacturing, and construction sectors, the ETS has effectively stimulated green innovation to a certain extent. There has been no significant change in green innovation in the sector of electricity, heat, gas, and water production and supply. In particular, after the implementation of the ETS, green innovation has actually been weakened in the transportation sector. As such, for policy makers, differentiated ETS policies should be implemented based on the actual situation of different industries and types of carbon-emitting enterprises.

Exploring the co-creation-innovativeness paradox: distance as an ecosystem characteristic of university spin-offs

Through empirical investigations into university spin-offs (USOs), we discovered innovativeness benefits derived from maintaining both academia and business partners at a distance. Distance should not be misconstrued as isolation; rather, it emphasises specific attributes where partners are maintained at arm’s length, affecting co-creation. Consequently, this paper explores how distance impacts the co-creation and innovativeness of USOs. It presents a longitudinal case study of a Swedish USO and conceptualises various types of distances, including actor-type, industry, supply-chain, geographical and knowledge-related distances. We explore the interplay between these different distance types as antecedents to USOs’ innovativeness and co-creation activities. The paper contributes to the existing literature by introducing the concept of distance as a critical characteristic affecting innovativeness and co-creation. By delineating various types of distances, it refines previous research on the characteristics of firm connections within university and business ecosystems.

Influencing factors on sustainability reporting quality based on sustainable development goals (SDGS) considering COVID-19

In 2020, the major companies in the Asia Pacific region faced challenges in sustainability performance reporting, primarily attributed to disruptions caused by the COVID-19 pandemic. This crisis compelled companies to reassess their sustainability goals. This study aims to analyze the relationship between corporate governance and corporate characteristics such as industry type and government ownership of sustainability reporting quality based on sustainable development goals (SDGs) with a population of 200 companies in ASEAN countries, including Indonesia, Malaysia, Thailand, and the Philippines, listed on each country’s stock exchange. The research sample consisted of 84 companies selected through purposive sampling. The hypothesis testing model employed a multiple linear regression method and utilized the panel data regression analysis approach. The findings indicate that the three corporate governance components examined in this research board independence, audit committee, and managerial ownership, along with government ownership do not exert a significant influence on sustainability reporting quality based on the seventeen SDGs goals. Furthermore, we believe that this research is very important to be carried out in Indonesia, given that environmentally sensitive industries face the risk of environmental damage and therefore need legitimacy to maintain their operations, demonstrated through sustainability report reporting.

Alkali-fusion as an effective method for activating low-reactivity silicate wastes: A comparative study

Silicate wastes are used as supplementary cementitious materials (SCM) in Portland cement production, and as precursors to produce alkali-activated materials such as geopolymers to lower the environmental impact of construction. The high crystallinity of some of these wastes lowers their reactivity and hence the production of cementing hydrates. This paper includes a comparative analysis of the efficiency of alkali-fusion to activate three distinct types of silicate waste sourced from diverse sectors. The paper underscores the robustness of this method and its applicability in a wide composition range. It provides a solid foundation for the application of alkali-fusion across a wide spectrum of industrial waste types. Fly ash (FA), crop bottom ash (CBA) and aluminium processing sludge (APS); were fused with NaOH at 600 °C. XRD and FTIR analyses revealed that alkali-fusion disrupts highly cross-linked Si-O-Si structures transforming them into more reactive phases (sodium aluminosilicate and sodium silicates). Alkali-fusion is efficient even at low NaOH dosage(15 %). 15 % NaOH-fusion increased the mechanical activity index of FA, CBA and APS by 108.19 %, 494.61 % and 27.96 % respectively. The mineral composition of the wastes changed at 50 % alkali content: quartz was largely digested, and sodium silicate emerged as the dominant phase. After alkali-fusion, dense and compact matrices with rich hydrates were found evidencing the enhancement of the pozzolanic reaction. Alkali-fusion at relatively low temperature (600 °C) is successful in activating low-reactivity silicate waste, transforming the waste into valuable SCMs.

Heritage Tourism Development Should Take Care of Industrial Heritage Protection: A Study on the Development Strategy of Industrial Heritage Tourism in Nanjing

The tourism development of industrial heritage is an effective way to activate cultural heritage and can provide new solutions for the renewal and protection of industrial heritage. This study focuses on the industrial heritage in Nanjing, aiming to explore its spatial distribution pattern, tourism development strategy, and sustainable development model. This study adopts a combination of quantitative and qualitative research methods. First, relevant information on 93 sites of industrial heritage type historic buildings in Nanjing is collected. Secondly, ArcGIS was used to visualize the evolution of industrial buildings and the spatial distribution of industrial heritage type historic buildings. Finally, the spatial analysis tools of ArcGIS and the accessibility analysis method in space syntax theory are superimposed to comprehensively analyze the spatial distribution pattern and traffic accessibility characteristics of Nanjing’s industrial heritage. The research results propose a specific plan to promote the value transformation of industrial heritage through tourism: based on the spatial distribution characteristics of Nanjing’s industrial heritage along the water system and traffic arteries, a tourist route of “multi-point, two-axis, one-center” is planned; the tourism development strategy of “point protrusion, linear links, and surface darning” is implemented; and a sustainable development model under the guidance of low-carbon environmental protection goals is explored. This study provides a reference for the protective development of industrial heritage and the expansion of tourism and opens up a new perspective for the regeneration and planning of other urban heritage.

How Traditional Fishing Villages Move Towards Sustainable Management: A Case Study of Industrial Transformation and Multi-Party Governance Models

The purpose of this study is to explore the key roles and functions of institutions or organizations in the process of the spatial activation and industrial transformation of leisure fishing villages and to summarize this operating model. This study takes Xunpu Village, Quanzhou City, Fujian Province as the research object, which is well-known for its recreational fisheries. It mainly uses case study methods and uses on-site surveys and interviews to understand the formation time, spatial distribution, and business type information of the Zanhuawei shops in Xunpu Village. Zanhuawei, which refers to the traditional hairstyle of Xunpu women, was later applied for national intangible cultural heritage status in China. After the outbreak, the spread of Zanhuawei on the Internet inspired a large number of tourists to visit Xunpu Village to experience Zanhuawei. The study found that (1) Zanhuawei industry replaced traditional fishery and became the leading industry type in Xunpu Village. (2) The operating model led by the government and integrating public and private funds has had a stimulating effect on the revitalization of local commercial and residential space, and a large number of idle spaces have been reactivated. (3) The cooperation model between a large number of investors and local fisherwomen has completely changed the economic model of the village. Zanhuawei industry mobilized all official and media resources to promote spatial activation at various scales, including regions, settlements and commercial spaces.

Anniversary and Numerical Worship: Based on Research on Typical Traditional Industries in China

Anniversary and Numerical Worship: Based on Research on Typical Traditional Industries in China

PREDICTION OF HEALTH INSURANCE PRODUCT PURCHASE ALLOCATION IN VARIOUS INDUSTRIES IN INDONESIA USING THE RANDOM FOREST METHOD

<p>The objective of this research is identifying which industry can absorb the product of wealth management such as health insurance. Secondly is to identify what the most factors important to determine closing the health insurance premium. The life insurance penetration and density in Indonesia is the lowest level among the Asian country, so the data population in this research is from 38 different companies from different types of industries with 143 data sample, by using the purposive sampling. Most factors which influence the purchasing of health insurance are Listrik, Industry, domicile, age and position, whether the industry that the most contribution for the health insurance sales is banking and education industry. The methodology that is used in this research is called CRIPS-DM (Cross Industrial Standards Program Data Mining). The first steps what is the purpose of the organization, and the second is what data that needed, and continue to data preparation, after modeling, it will make an interpretation of the result, and the final steps is deployment, it will plan how it will be implemented in the real world, and the accuracy score from this model is 58%. From the result of the projection closing health insurance from each industry, it can be concluded that the most industry that closed the health insurance is Banking Industry, the second is from insurance and the third is education and the next is education, retail, health, manufacturing and finance, hospitality, legal, publishing, technology and government and service industries.</p>

Sustainability Reporting and Financial Performance: Examine the Correlation between Sustainability Disclosures Financial Performance in Publicly Traded Companies

Sustainability reporting has increasingly gained prominence in academia and practice over the past few decades. With growing stakeholder expectations for companies to report on environmental, social, and governance issues, sustainability reporting allows companies to communicate non-financial impacts. While sustainability reporting aims to enhance accountability and transparency, questions remain regarding its influence on corporate financial performance. Some studies have found a positive correlation between sustainability reporting and financial metrics like profitability and share price, arguing reporting leads to more efficient resource management and risk mitigation. However, other research has found no significant relationship or negative impact, noting that reporting requirements incur costs that may outweigh benefits. This comprehensive review aims to provide an in-depth analysis of the existing literature on the correlation between sustainability disclosures and the financial performance of publicly traded companies. Relevant studies from various regions and sectors published between 1990 and 2023 will be reviewed. The methodologies applied, measurement variables, sample sizes, and time frames considered will be evaluated to understand the scope and limitations of each study. Key findings related to the direction and strength of the reported relationship between the two parameters will be summarized and compared. Moderating factors such as company size, industry, cultural context, and disclosure type will also be examined to determine their influence on research outcomes. The review will conclude by outlining existing knowledge gaps, inconsistencies in current empirical evidence, and areas that require further research.

How to Improve Your Warehouse Operating Efficiencies

How to improve your warehouse operating efficiency helps to understand the critical factors that influence the productivity of the warehouse operations. As we know logistics is essential for supply chain in today’s world to reach the products on time and in full (OTIF). To attain better OTIF rate, operating the warehouse to the fullest efficiency is critical. There are various types of warehouses, at different sizes (in Sq. ft), diverse operating models, several applications are available in the market. Warehouses of each industry types have their own uniqueness in operating model, and it comes its own complexity. Operating warehouses to the maximum efficiency is always challenging, constant automation with process and system re-engineering is needed to keep up the pace. Inefficient warehouse operations can bring the business to a standstill unless its upbeat to meet the needs of the customers. Warehouse applications complement to the performance of the deliverables from logistics perspective, fulfilling the customer service level agreements (SLA).

Intellectual capital as a driver of value creation in Serbian entrepreneurial firms

PurposeThis paper analyses the role of intellectual capital (IC) as a factor of the financial performance of entrepreneurial firms, which are recognized as the main drivers of economic growth and employment.Design/methodology/approachThe sample consists of 188 business owners from Serbia. The primary data are collected using the questionnaire, while the secondary data come from the annual financial statements of their companies. The elements of IC as independent variables are grouped into three components: human, structural and relational capital; sales revenue and operating profit CAGR (5y) are used as dependent variables, while company size and industry type are used as control variables. Statistical analysis involves factor and regression analyses.FindingsThe results reveal that IC components contribute to the long-term financial performance of entrepreneurial firms. Specifically, the following elements have positive effects on financial performance: knowledge of the entrepreneur, process improvement and organisational culture. On the other hand, entrepreneurs’ social skills and tenacity were found to have a negative impact on revenue and operating profit growth, while support from informal networks had a negative effect on the growth of sales revenue.Originality/valueThis study aims to fill a gap in the literature on the impact of IC on the financial performance of entrepreneurial firms.