The Fourth Industrial Revolution poses significant challenges to manufacturing companies from the technological, organizational and management points of view. This paper aims to explore how top executives interpret the concept of Industry 4.0, the driving forces for introducing new technologies and the main barriers to Industry 4.0. The authors applied a qualitative case study design involving 26 semi-structured interviews with leading members of firms, including chief digital officers and chief executive officers. Company websites and annual reports were also examined to increase the reliability and validity of the results. The authors found that management desire to increase control and enable real-time performance measurement is a significant driving force behind Industry 4.0, alongside production factors. Organizational resistance at both employee and middle management levels can significantly hinder the introduction of Industry 4.0 technologies, though these technologies can also transform management functions. Multinational enterprises have higher driving forces and lower barriers to industry 4.0 than small and medium-sized companies, but these smaller companies have good opportunities, too.
Purpose The service sector is at an inflection point with regard to productivity gains and service industrialization similar to the industrial revolution in manufacturing that started in the eighteenth century. Robotics in combination with rapidly improving technologies like artificial intelligence (AI), mobile, cloud, big data and biometrics will bring opportunities for a wide range of innovations that have the potential to dramatically change service industries. The purpose of this paper is to explore the potential role service robots will play in the future and to advance a research agenda for service researchers. Design/methodology/approach This paper uses a conceptual approach that is rooted in the service, robotics and AI literature. Findings The contribution of this paper is threefold. First, it provides a definition of service robots, describes their key attributes, contrasts their features and capabilities with those of frontline employees, and provides an understanding for which types of service tasks robots will dominate and where humans will dominate. Second, this paper examines consumer perceptions, beliefs and behaviors as related to service robots, and advances the service robot acceptance model. Third, it provides an overview of the ethical questions surrounding robot-delivered services at the individual, market and societal level. Practical implications This paper helps service organizations and their management, service robot innovators, programmers and developers, and policymakers better understand the implications of a ubiquitous deployment of service robots. Originality/value This is the first conceptual paper that systematically examines key dimensions of robot-delivered frontline service and explores how these will differ in the future.
Biochemical conversion of lignocellulosic feedstocks to advanced biofuels and other commodities through a sugar-platform process involves a pretreatment step enhancing the susceptibility of the cellulose to enzymatic hydrolysis. A side effect of pretreatment is formation of lignocellulose-derived by-products that inhibit microbial and enzymatic biocatalysts. This review provides an overview of the formation of inhibitory by-products from lignocellulosic feedstocks as a consequence of using different pretreatment methods and feedstocks as well as an overview of different strategies used to alleviate problems with inhibitors. As technologies for biorefining of lignocellulose become mature and are transferred from laboratory environments to industrial contexts, the importance of management of inhibition problems is envisaged to increase as issues that become increasingly relevant will include the possibility to use recalcitrant feedstocks, obtaining high product yields and high productivity, minimizing the charges of enzymes and microorganisms, and using high solids loadings to obtain high product titers.
Recently, a "lead user" concept has been proposed for new product development in fields subject to rapid change von Hippel [von Hippel, E. 1986. Lead users: A source of novel product concepts. Management Sci.32 791-805.]. In this paper we integrate market research within this lead user methodology and report a test of it in the rapidly evolving field of computer-aided systems for the design of printed circuit boards PC-CAD. In the test, lead users were successfully identified and proved to have unique and useful data regarding both new product needs and solutions responsive to those needs. New product concepts generated on the basis of lead user data were found to be strongly preferred by a representative sample of PC-CAD users. We discuss strengths and weaknesses of this first empirical test of the lead user methodology, and suggest directions for future research.
<p>A hybrid method for the numerical solution of the system of delayed linear fuzzy mixed VolterraFredholm integral equations (FMDVFIES) is introduced. Using the hybrid of Bernstein polynomials and blockpulse functions (HBBFs), an approximate solution for the equations system is provided. Firstly, the HBBFs and their operational matrices are introduced, and some of their characteristics are described. Then by applying the operational matrices on FMDVFIES convert it to the algebraic equations system. The numerical solution is obtained by solving this algebraic system. Then the convergence is investigated and some numerical examples are presented to show the effectiveness of the method.</p>
Дмитро АНРДЄЄВ, Олексій ЛИГУН, Андрій ДРОЗД
et al.
Critical infrastructures are fundamental to the seamless operation of modern societies, encompassing sectors such as energy, healthcare, transportation, and communications. Ensuring their reliability, performance, continuous operation, safety, maintenance, and protection is a national priority for countries worldwide.
The digital twins play a crucial role in critical infrastructure, as they enhance security, resilience, reliability, maintenance, continuity, and operational efficiency across all sectors. Among the benefits offered by digital twins are intelligent and autonomous decision-making, process optimization, improved traceability, interactive visualization, and real-time monitoring, analysis, and prediction. Furthermore, the study revealed that digital twins have the capability to bridge the gap between physical and virtual environments, can be used in combination with other technologies, and can be integrated into various contexts and industries.
The use of digital twins was explored as the foundation for developing a modern monitoring system for critical infrastructure facilities enables multi-level assessment of asset conditions in real time, ensuring precise threat detection, anomaly identification, and timely decision-making. Integration with artificial intelligence and big data technologies allows not only the collection and analysis of large volumes of information but also the creation of adaptive behavioral models for systems in emergency situations.
Special attention was given to the method of optimizing critical IT infrastructure using digital twins, which combines virtual modeling, predictive algorithms, and automated management. The proposed approach enhances the reliability of digital systems, minimizes downtime, optimizes maintenance costs, and strengthens cybersecurity. This system is especially relevant in the context of growing risks and increasing demands for the stability of strategically important infrastructure assets.
The application of digital twins for monitoring and optimizing critical infrastructure demonstrates considerable potential for improving its resilience, safety, and operational efficiency. The approaches discussed in the study confirm the relevance of implementing digital models as tools for timely risk identification, failure prediction, and informed decision-making. By integrating such technologies, organizations can reduce operational costs, minimize downtime, and improve the overall stability of infrastructure operations. Therefore, digital twins represent a vital step toward the digital transformation and modernization of mission-critical systems across various sectors.
Evariste Sindani, Simon Ntumba Badibanga, Pierre Kafunda Katalay
et al.
This study proposes an integrated approach to digitalizing human resources (HR) in African public institutions by developing a performance optimization model. Based on five key variables—processing time, operational cost, service quality, degree of automation, and employee satisfaction—this model aims to enhance the overall efficiency of HR processes. The study is applied to the case of the National Office for Population Identification (ONIP) in the Democratic Republic of Congo and highlights substantial improvements in human resource management. Theoretically, the approach contributes to the digital transformation field through modeling, and practically, by offering a reproducible and adaptable framework for other public organizations with limited resources.
Keywords: Digitalization, HR process optimization, ONIP, HR performance, HRIS.
The advent of digital financial technology left the business community and its clients celebrating convenient ways of online shopping, paying bills and money transfers. However, digital banking technology came with its share of challenges, due to highly digitalised economies in the context of the Fourth Industrial Revolution, cyber fraudsters are increasingly targeting and leveraging on financial market infrastructures. Cyber security of banking institutions and the financial systems across the globe remains a major concern of Central Banks, investors, internal auditors and financial risk managers. The purpose of this research paper was to examine the efficacy of cyber fraud prevention measures used by commercial banks in Zimbabwe. The study also looked into the difficulties encountered in managing cyber-fraud. Results indicate that cyber fraud risk management strategies adopted by Commercial banks are partly effective which indicates existence of opportunities for cyber fraudsters to attacks and get away with it at the expense of clients, banks and the financial system as a whole. Results also indicate that Commercial banks are facing quite a number of challenges which include the following: lack of sophisticated systems, cyber attackers are always ahead, some of the clients do not take awareness messages send to them seriously, some clients share passwords and credit cards and lack of enough education and knowhow of employees. The study therefore concludes that, cyber fraud risk management strategies adopted by Commercial banks are partly effective. Monetary and fiscal authorities need to continue monitoring Commercial banks with regard to implementation of cyber security risk based supervision framework.
The sparrow search algorithm (SSA) is a metaheuristic algorithm developed based on the foraging and anti-predatory behavior of sparrow populations. Compared with other metaheuristic algorithms, SSA also suffers from poor population diversity, has weak global comprehensive search ability, and easily falls into local optimality. To address the problems whereby the sparrow search algorithm tends to fall into local optimum and the population diversity decreases in the later stage of the search, an improved sparrow search algorithm (PGL-SSA) based on piecewise chaotic mapping, Gaussian difference variation, and linear differential decreasing inertia weight fusion is proposed. Firstly, we analyze the improvement of six chaotic mappings on the overall performance of the sparrow search algorithm, and we finally determine the initialization of the population by piecewise chaotic mapping to increase the initial population richness and improve the initial solution quality. Secondly, we introduce Gaussian difference variation in the process of individual iterative update and use Gaussian difference variation to perturb the individuals to generate a diversity of individuals so that the algorithm can converge quickly and avoid falling into localization. Finally, linear differential decreasing inertia weights are introduced globally to adjust the weights so that the algorithm can fully traverse the solution space with larger weights in the first iteration to avoid falling into local optimum, and we enhance the local search ability with smaller weights in the later iteration to improve the search accuracy of the optimal solution. The results show that the proposed algorithm has a faster convergence speed and higher search accuracy than the comparison algorithm, the global search capability is significantly enhanced, and it is easier to jump out of the local optimum. The improved algorithm is also applied to the Heating, Ventilation and Air Conditioning (HVAC) system control optimization direction, and the improved algorithm is used to optimize the parameters of the HVAC system Proportion Integral Differential (PID) controller. The results show that the PID controller optimized by the improved algorithm has higher control accuracy and system stability, which verifies the feasibility of the improved algorithm in practical engineering applications.
In this paper, starting from the "holistic" approach of the European Banking Authority (EBA) which reinforces the relevance of antimoney laundering in the prudential assessment of banks, a conceptual scheme is proposed for the calculation of the Economic Value Added of banking products showing how, in the face of various activities required for AML purposes (from onboarding to alert management to constant monitoring), the economic convenience of a relationship can be determined ex ante, at least for each product.
The results confirm that for the same creditworthiness and cost of capital, the AML variable strongly affects the economic convenience of the individual products. Considering the partially inelastic nature of AML costs, the size of the operation is equally fundamental in determining whether to initiate relationships with certain types of customers.