Artificial intelligence (AI) is widely heralded as a new and revolutionary technology that will transform the world of work. While the impact of AI on human resource (HR) and people management is difficult to predict, the article considers potential scenarios for how AI will affect our field. We argue that although popular accounts of AI stress the risks of bias and unfairness, these problems are eminently solvable. However, the way that the AI industry is currently constituted and wider trends in the use of technology for organising work mean that there is a significant risk that AI use will degrade the quality of work. Viewing different scenarios through a paradox lens, we argue that both positive and negative visions of the future are likely to coexist. The HR profession has a degree of agency to shape the future if it chooses to use it; HR professionals need to develop the skills to ensure that ethics and fairness are at the centre of AI development for HR and people management.
Financial management is a critical aspect of firms, and entails the strategic planning, direction, and control of financial endeavors. Risk assessment, fraud detection, wealth management, online transactions, customized bond scheme, customer retention, virtual assistant and so on, are a few of the critical areas where Industry 4.0 technologies intervention are highly required for managing firms' finance. It has been identified from the previous studies that they are limited studies that have addressed the significance and application of integrating of Industry 4.0 technologies such as Internet of Things (IoT), cloud computing, big data, robotic process automation (RPA), artificial intelligence (AI), Blockchain, Digital twin, and Metaverse. With the motivation from the above aspects, this study aims to discuss the role of these technologies in the area of financial management of a firm. Based up on the analysis, it has been concluded that these technologies assist to credit risk management based on real-time data; financial data analytics of risk assessment, digital finance, digital auditing, fraud detection, and AI- and IoT- based virtual assistants. This study recommended that digital technologies be deeply integrated into the financial sector to improve service quality and accessibility, as well as the creation of innovative rules that allow for healthy competition among market participants.
The purpose of this paper is to investigate the implications for supply chain risk management (SCRM) by applying internet of things (IoT). Therefore, the impact and effects on the SCRM process, as well as the internal and external pathway and the outcome of SCRM are examined.,This study adopts a multiple case study methodology with twelve companies from the manufacturing industry. This study is guided by the information processing theory (IPT) and a theory-grounded research framework to provide insights into information requirements and information processing capabilities for IoT-supported SCRM.,The studied cases demonstrate an increase in data availability in the companies that contribute to improved process transparency and process management. Furthermore, the process steps, risk transparency, risk knowledge and risk strategies have been enhanced, which enabled improved SCRM performance by fitting information requirements and information processing capabilities, thus allowing for competitive advantage.,This study offers in-depth insights for SCRM managers into the structure of IoT systems, primary use cases and changes for the process itself. Furthermore, implications for employees, incentives and barriers are identified, which could be used to redesign SCRM.,This study addresses the requirement for additional empirical research on technology-enhanced SCRM, supported by IPT as a theoretical foundation. The radical change of SCRM by IoT is demonstrated while discussing the human role, implications for SCRM strategies and identifying relevant topics for future development.
Nowadays, the importance of water and the management of its resources are among the most controversial issues at the global level due to climate change. This issue is especially important in Iran, which suffers from continuous drought. Therefore, the current research aims to explain the determinants affecting water reporting in the listed companies on the Tehran Stock Exchange. For this purpose, by using the data of 102 companies during the years 2012 to 2021 which were selected by elimination method, the determinants affecting the disclosure of water reporting were identified and analyzed using stepwise regression and multiple regression methods. The results of this research showed that the highest amount of disclosure related to water belonged to chemical and oil industry companies, Additionally, in the investigation of the determinants affecting water reporting, it was found that the determinants affecting water reporting, it was found that the determinants of firm age, board size, financial expertise of the audit committee, concentration of ownership, institutional ownership, return on assets, average annual rainfall, reputation, regulation, and sensitivity of the industry to water had an impact on corporate water reporting. These findings can be useful for planning and controlling water management, as well as for investors to know the drivers of corporate disclosure in forming their optimal portfolio. IntroductionNowadays, the importance of water and the management of its resources are among the most controversial issues at the global level due to climate change. This issue is especially important in Iran, which suffers from continuous drought. Therefore, the current research aims to explain the determinants affecting water reporting in the listed companies on the Tehran Stock Exchange.Research Question(s): What are the determinants influencing the disclosure of water reporting in Tehran Stock Exchange member companies? What is the impact of these determinants on the disclosure of water reporting? Literature ReviewAlthough the limitation of water resources and its serious role in sustainable life and economic activities are not hidden from anyone, with increasing concerns about water and its pollution, and the effects of climate change, how to effectively manage water and report it at the corporate level has become more important. This attention has been such that today the disclosure of water management information and its risks has become part of the strategy and sustainability efforts of companies. Water reporting at the company level is a tool for transferring information about water risks, the effects of risk, and the company's water resources strategy.Multiple theoretical frameworks can be used to justify the necessity of water reporting at the company level and its determinants. These theories are in the same direction and complement each other, such that they are competing theories because all of them are trying to explain corporate water reporting. These theories include legitimacy theory, stakeholders theory, social responsibility theory, and resource-based theory. MethodologyThe population studied in this research comprises the companies that are members of the Tehran Stock Exchange over a period of 10 years from 2012 to 2021, and ultimately, 102 companies (1020 company-years) were selected using the systematic elimination method. The method used in this research to explain the determinants affecting the disclosure of water reporting included five steps: In the first step, the study of literature related to water reporting and the determinants affecting it was conducted. In the second step, a comprehensive review of the literature was carried out by referring to Springer, Wiley, Science Direct, Google Scholar, and ResearchGate databases. The preliminary search identified a number of articles that focused on broad areas of disclosure. The process of studying the abstracts and introductions of the articles led to the exclusion of some out-of-scope studies. After filtering the results, only eight of these articles related to water disclosure were selected. In the third step, a questionnaire was prepared and distributed among experts to confirm and complete the components. This step was used as a complementary method, according to the experts, to confirm and complete the determinants extracted from the literature, taking into account the local conditions of Iran. The fourth step involved finalizing the determinants after reviewing the questionnaires; finally, ten responses were received from the questionnaires sent to the experts, and the questionnaires were tested with the independent t-test method. The results showed that all the determinants included in the questionnaire, except for gender diversity, were approved by the board of directors and the audit committee. In the fifth step, the stepwise regression method was used to examine the effective variables and select the effective stimuli on water reporting, and then the multiple regression method was used to measure the impact of each of the approved stimuli. ResultsIn the stepwise regression method, the dependent variable (water reporting disclosure) and independent variables (firm size, firm age, financial leverage, audit committee size, audit committee financial expertise, independent members of the audit committee, board size, ownership concentration, institutional ownership, government ownership, return on assets, corporate social responsibility, average annual rainfall, GDP growth, reputation, and sensitivity of the industry to water) were selected and, over 10 stages, various regressions were formed and finally, ten independent variables were confirmed. The adjusted coefficient of determination of this regression is equal to 0.322, which has the highest coefficient of determination compared to other models, and the value of the significance level of the model is equal to 0.000, which shows the significance of the model. Finally, in response to the research question of what are the drivers of water reporting in companies, the following variables can be mentioned: firm age, audit committee financial expertise, board size, ownership concentration, institutional ownership, return on assets, average annual precipitation, reputation, regulation, and industry sensitivity to water. Subsequently, to check the impact of each of the factors, the variables selected in the previous step were entered into the regression and analyzed with the multiple regression method. Finally, the regression equation was obtained as follows:WaterDisclosure= -3.327 – 0.620 LnAge + 0.764 BoardSize + 1.450 Concentration + 0.895 ROA + 0.119 Co-financial + 3.191 Reputation – 0.001 Rainy – 0.977 Regulation+ 1.450 Institutional + 0.162 Sensetive DiscussionBy reviewing the literature, it was found that several determinants were effective in water reporting in companies; some of these determinants were related to the structural characteristics of the company, some to the characteristics and ownership structure, and finally to the financial performance of the company. Also, determinants such as the existence of foreign regulation and supervision, the company's attention from major shareholders, and reputation, as well as the level of social responsibility of companies, can lead to more disclosure of water-related information. In this research, in addition to these determinants, some other determinants such as the country's economic growth, annual rainfall, and audit committee characteristics were investigated by interviewing experts. ConclusionAccording to the findings of the research, companies with higher profitability and reputation also have higher disclosure. In addition, the findings suggested that considering there is still no codified and general regulation for water management applicable to all companies in Iran, it is recommended, according to the theory of stakeholders, that legislators and the environmental organization establish specific and enforceable regulations for companies to adhere to and disclose information related to water in their reports. Furthermore, since there is currently a requirement for listed companies to prepare sustainable reporting, providing information on water and how to manage water and its risks can be combined with other information on social activities and governance. This integration of reports will enable better monitoring for policy-makers and foster collaboration among stakeholders for responsible water management and achieving sustainable goals at both the corporate and global levels.
It is difficult to accurately predict and assess the instability of the stope. This article uses the improved Mathews stability graph method to scientifically analyse and evaluate the quality and stability of the surrounding rock. It utilizes the failure factor (FF) to express the degree of rock failure under different stress states based on the Mohr–Coulomb criterion and to determine the new rock stress factor. This new method is successfully applied in a case study at a lead–zinc mine in Hongling and makes a comparative analysis with the actual situation of the site.
AbstractThe purpose of this study is to investigate the effect of blockchain technology on digital marketing. This study is applicable in terms of purpose, and of a quantitative research type, which is a survey-cross-sectional study in terms of data collection. The statistical population of this study consists of online marketing managers and activists. The entire statistical population was considered unlimited. Due to the unlimited nature of the statistical population, 384 people were considered as a sample, based on the Morgan table. The data collection tool is a questionnaire. The standard questionnaire was extracted based on the study by Wiratma et al., (2021). Confirmatory factor analysis and model fit test and structural equation model were used to examine the data to test the hypotheses expressed in the study. The data analysis method was also using smart.PLS software. The results of the study showed that blockchain has a positive and significant effect on mega-data, which in its turn, has a positive and significant effect on digital marketing. Blockchain has a positive and significant impact on digital marketing.Extended AbstractIntroductionWith the rapid growth of e-commerce, exchanges and transactions through information technology tools and methods have increased significantly. The adoption and use of various electronic payment services and its application are important topics considered in the use of new technologies (Li & Bai, 2010). Today, much of the attention on blockchain is focused on financial services; and very little has been discussed about non-financial services companies and how blockchain technology can impact organizations, their business models, and the way they create and deliver value (Morkunas et al, 2018).Blockchain technology has emerged as a promising innovation that can not only disrupt operational processes in the supply chain of products and services, but also facilitate risk management in the complex and interconnected global supply chain ecosystem through increased information and process flexibility (Tonnissen & Teuteberg, 2020; Esmaeili et al, 2020; Wamba & Queiroz, 2020; Gory, 2019). With the rapid growth of e-commerce, exchanges and transactions through information technology tools and methods have increased dramatically. The adoption and application of various electronic payment services and their applicability are important issues considered in the use of new technologies (Li & Bai, 2010). Much of the attention on blockchain today is focused on financial services, with very little discussion of non-financial services companies and how blockchain technology can impact organizations, their business models, and the way value is created and delivered (Morkunas et al, 2018). It monitors interactions between individuals, organizations, companies, communities, and people. They guide management and social actions. Blockchain technology at the heart of Bitcoin and other cryptocurrencies, is a chain blockmarket of an open, distributed ledger that can efficiently record transactions between two parties in a verifiable, permanent, and secure manner. This technology is protected against deletion, tampering, and financial transactions (Rega et al, 2019).Blockchain technology is predicted to play a significant role in digital marketing in the future. According to a report in Semupdates.com (2019) of the 20 digital marketing trends that will go viral in 2020; one of them is blockchain technology in search engine advertising. The use of blockchain is a technology much broader than the financial world that can be applied to the world of digital marketing, as its functions are transparent and provide benefits to the branding process. The figure below shows the size of the blockchain technology market worldwide from 2018 to 2025, where it is predicted that the blockchain technology market will be worth $39.7 billion by 2025. This chart shows the blockchain market forecasts that also show the use of blockchain technology (Wiratama et al, 2021).For this purpose, the present study seeks to answer the following question: What is the impact of the application of blockchain technology on digital marketing?Theoretical FrameworkBlockchainBlockchain concepts have brought about widespread changes in the legal industry, simplifying and streamlining various processes. The same type of simplification can be seen in the accounting field. Another entity that can benefit from blockchain technology is the government. However, the benefits of this blockchain can go beyond the small projects they have implemented. Three benefits that governments can realize are increasing citizen trust in authorities, protecting crucial data, and reducing costs by increasing efficiency. While the cost savings in the financial industry can be extensive, the legal field can also implement this technology with great success. While there are many applications for which blockchain technology can be used, it can be seen that the main place where it is used is to better organize information, which raises questions about the potential untrustworthiness of the information itself. With the emergence of smart contracts in blockchain technology, the credit requirement required in many international sales transactions is becoming obsolete and useless (Benson, 2019).Digital MarketingThe term digital marketing has been referred to as a subset of marketing management and advertising management for two decades (Kamnan, 2017). Digital marketing includes all the tools and activities used to market products and services on a digital platform (web, internet, mobile or other (digital) tools) (Vaziri Gohar & Abdolhosani, 2020).Roshanak et al, (2024) investigated the effect of marketing mix on blockchain technology with the mediating role of perceived usefulness in customers of the National Bank of Iran in Tehran. The results of the study indicate that senior management support, supply chain integration, and innovation capability have a significant effect on blockchain technology. Also, supply chain risk did not affect blockchain technology. Finally, the role of marketing mix has been shown on perceived usefulness. Also, perceived usefulness affects blockchain technology.Moradi ziba et al, (2023) investigated the model of digital marketing strategies in successful Iranian startups. The results of the qualitative section indicated that 241 primary codes, 46 pivotal codes, and 14 selective codes were identified and extracted. The results of the study showed that the causal conditions with 4 variables of network capability, use of artificial intelligence, marketing capability and customer knowledge have an effect on digital marketing strategies; and the results of confirmatory factor analysis showed that the model fit indices were approved.Research MethodologyThis study is applicable in terms of purpose, and of a quantitative research type, and a survey-cross-sectional study in terms of data collection. The statistical population of this study consists of online marketing managers and activists. The entire statistical population was considered unlimited. Due to the unlimitedness of the statistical population, 384 people were considered as a sample based on the Morgan table. The data collection tool is a questionnaire. The standard questionnaire was extracted based on the study of Wiratma et al. (2021). Confirmatory factor analysis and model fit test and structural equation model were used to examine the data to test the hypotheses expressed in the study.Research findingsThe data analysis method was carried out by smart.PLS software. The research results showed that blockchain has a positive and significant effect on megadata. The megadata has a positive and significant effect on digital marketing. Blockchain has a positive and significant effect on digital marketing.ConclusionThe present study was conducted with the aim of investigating the effect of the application of blockchain technology on digital marketing. The results of this study are consistent with the results of Roshanak et al, (2024), Moradi ziba et al, (2023), Bagheri Anilu et al, (2023), Zhang et al, (2023), Dana et al, (2022) Gholipour Domyeh (2023), Ahmadi et al, (2022), Da Silva & Moro (2021), Clohessy et al, (2020), Grishikashvili et al, (2014), Rejeb et al, (2020), Brauer & Eriksson (2020), Ertemel (2018), and Kecskes (2018). Roshanak et al, (2024) showed that top management support, supply chain integration, and innovation capability have a significant impact on blockchain technology. Also, supply chain risk did not have an effect on blockchain technology. Finally, the role of the marketing mix on perceived usefulness has been shown. Also, perceived usefulness has an effect on blockchain technology.According to the results of the research, it is suggested that online marketing managers and activists strengthen the technical knowledge of employees in this field by holding meetings and training courses in the field of blockchain technology. On the other hand, by focusing on emerging technologies such as blockchain and their capabilities, they should align their marketing strategy with digital marketing based on these emerging technologies.
Supply chain risk management plays a critical role in the any business or industry environments, and it enables a good coordination of the input and outputs parameters that may affect the smooth processes development such as a manufacturing process for example. However, the supply chain risk management is often prone to the impact of various uncertainties associated with supply chain disruptions caused by meteorological, pandemic, resources shortage, etc. Therefore, one way to quantify these uncertainties are the stochastic modeling approaches of supply chain management. The stochastic modeling is a powerful tool that can predict with certain probability the events that may occur within the supply chain such as that associated with manufacturing processes. In the present research a stochastic model, based on probability theory, is developed and proposed for the analysis of supply chain risk management, for manufacturing processes. Therefore, the studies are performed to investigate the impact of the number of manufacturing processes on the supply chain proper evolution. The current study shows that the increase of the number of the manufacturing processes results in an increase of uncertainty in the supply chain management and thus, it increases the probability of supply chain disruption occurrences, within the supply chain. Therefore, it is recommended that a supply chain should contain a minimum number of manufacturing process, if the delivery time and final product allows.
This investigation focuses on refining software effort estimation (SEE) to enhance project outcomes amidst the rapid evolution of the software industry. Accurate estimation is a cornerstone of project success, crucial for avoiding budget overruns and minimizing the risk of project failures. The framework proposed in this article addresses three significant issues that are critical for accurate estimation: dealing with missing or inadequate data, selecting key features, and improving the software effort model. Our proposed framework incorporates three methods: the Novel Incomplete Value Imputation Model (NIVIM), a hybrid model using Correlation-based Feature Selection with a meta-heuristic algorithm (CFS-Meta), and the Heterogeneous Ensemble Model (HEM). The combined framework synergistically enhances the robustness and accuracy of SEE by effectively handling missing data, optimizing feature selection, and integrating diverse predictive models for superior performance across varying project scenarios. The framework significantly reduces imputation and feature selection overhead, while the ensemble approach optimizes model performance through dynamic weighting and meta-learning. This results in lower mean absolute error (MAE) and reduced computational complexity, making it more effective for diverse software datasets. NIVIM is engineered to address incomplete datasets prevalent in SEE. By integrating a synthetic data methodology through a Variational Auto-Encoder (VAE), the model incorporates both contextual relevance and intrinsic project features, significantly enhancing estimation precision. Comparative analyses reveal that NIVIM surpasses existing models such as VAE, GAIN, K-NN, and MICE, achieving statistically significant improvements across six benchmark datasets, with average RMSE improvements ranging from 11.05% to 17.72% and MAE improvements from 9.62% to 21.96%. Our proposed method, CFS-Meta, balances global optimization with local search techniques, substantially enhancing predictive capabilities. The proposed CFS-Meta model was compared to single and hybrid feature selection models to assess its efficiency, demonstrating up to a 25.61% reduction in MSE. Additionally, the proposed CFS-Meta achieves a 10% (MAE) improvement against the hybrid PSO-SA model, an 11.38% (MAE) improvement compared to the Hybrid ABC-SA model, and 12.42% and 12.703% (MAE) improvements compared to the hybrid Tabu-GA and hybrid ACO-COA models, respectively. Our third method proposes an ensemble effort estimation (EEE) model that amalgamates diverse standalone models through a Dynamic Weight Adjustment-stacked combination (DWSC) rule. Tested against international benchmarks and industry datasets, the HEM method has improved the standalone model by an average of 21.8% (Pred()) and the homogeneous ensemble model by 15% (Pred()). This comprehensive methodology underscores our model’s contributions to advancing software project management (SPM) through advanced predictive modeling, setting a new benchmark for software engineering effort estimation.
Богдан Ковальов, Ігор Пономаренко, Артем Боруха
et al.
This scientific article examines the problems of economic and resource security in Ukraine and emphasises the importance of using disruptive technologies to achieve sustainable development. It was found that disruptive technologies lead to radical changes in production technologies, work organisation, and the socio-economic landscape. They affect the structure of the economy, the labour sphere, and social relations, which contribute to industrial revolutions. Scientists describe the Third, Fourth and Fifth industrial revolutions, which affect the development of the green economy, cyber-physical systems and the harmony between man and technology. Ukrainian researchers are also studying the concept of Industry 4.0 and disruptive technologies, including digital technologies, artificial intelligence, the Internet of Things, and production automation, to increase the competitiveness of the industrial sector and the development of the economy. During their research, the authors discuss four disruptive technologies: renewable energy, cyber security, artificial intelligence and blockchain, and their potential to ensure the country's economic and resource security. Renewable energy can reduce dependence on traditional energy sources and promote sustainable development. Cybersecurity is an essential aspect of the digital world, and disruptive technologies in this field can ensure the adequate protection of information systems. Artificial intelligence can improve productivity and quality of life by automating processes and developing innovative solutions. Blockchain technology can ensure the security and transparency of data management and improve the efficiency of supply chain management. The integration of these disruptive technologies into the economy and resource management of Ukraine can have a significant impact on the country's sustainable development and security. These technologies can increase productivity, reduce risk, improve resource efficiency, and better protect against cyber threats. Disruptive technologies are a critical factor in achieving the economic and resource well-being of Ukraine.
The development of digital production technologies, taking place within the framework of the global fourth industrial revolution, creates conditions for increasing the level of customization of industrial production, i.e. the ability to manufacture products that reflect the preferences of small groups of consumers and even individual customers. Product customization, as one of the most important aspects of the fourth industrial revolution, is of great interest for researchers and has been becoming one of the promising trajectories for the development of new production technologies and methods of organizing production. But at the same time, the economic effect of increasing the customization of products remains not fully understood. This study is aimed at identifying various economic effects arising from customization in industrial enterprises, and their quantitative assessment in relation to the manufacturing industries of the Russian industry. Using a systematic review of available scientific research and analytical reports, the study quantifies the economic effects of customization in various sectors of the Russian economy. The results show the colossal effect of further customization in Russian enterprises. The authors conclude that the annual effect of revenue growth in all industries, even under the most pessimistic scenarios and estimates, is 1.9 trillion rubles, and the effect of cost reduction – 1.4 trillion rubles. The results obtained can form the basis of government measures to stimulate the customization of products of Russian industrial enterprises.
Golubović Tamara A., Spasojević-Brkić Vesna K., Perišić Martina B.
In recent decades, process safety control and process safety risk assessment have become very attractive topics. The way control is carried out, using tools such as HAZOP, FMEA, FTA, and similar is not sufficient to adequately prevent or control accidents with serious consequences in the process industry. The need to analyze the causes of the causes themselves, with special emphasis on the impact of organizational factors has arisen. This research results in the development of an original, reliable, and valid measuring instrument for assessing organizational factors important for risk assessment methodologies in working with pressure equipment. The initial instrument was designed based on the previous research and then checked by statistical analysis, using the Kaiser-Meyerto-Olkin test, exploratory factor, and reliability analysis. The proposed instrument has reduced 71 to 48 dimensions, describing 10 organizational factors important for risk management of pressure equipment. Providing a valid and reliable measurement instrument is essential for a proactive approach, which enables managers employed in the organization to mitigate the risks of pressure equipment operation, and prevent accidents. The proposal of further research is the application of confirmatory factor analysis or/and structural equation modeling on data collected.