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This research focused on intervening in the optimization algorithm used by the Computational Reverse-Engineering Analysis for Scattering Experiments (CREASE) tool to analyze small-angle scattering (SAS) profiles using the Rigid-Body model. CREASE uses the genetic algorithm (GA) with dynamic adaptation as its optimization algorithm. The aim is to evaluate the performance of CREASE by replacing the GA with a Harmony Search (HS)-based metaheuristic, specifically the Nobel Global Harmony Search (NGHS), in the analysis of SAS profiles of low-concentration solutions vesicles-assembled amphiphilic macromolecules. Results showed that NGHS achieved similar accuracy to GA but with higher efficiency, achieving similar quality solutions with only one-sixth, and in some cases one-tenth, the number of fitness function evaluations used by GA. Besides, CREASE-NGHS achieved SAS profile analysis convergence with less than half the number of fitness function evaluations, saving computational resources and facilitating a more complete analysis. In addition, NGHS addressed some shortcomings of the GA optimization process and facilitated its use and adaptation to distinct types of samples for users with little experience in optimization.

Evolving market trends, characterized by an increasing demand for personalized products with short life cycles and variable demands, pose a significant challenge to the industry. One of the industry's strategies is to adopt robotic assembly systems to improve productivity and increase system flexibility. The widespread adoption of robots in assembly processes is evident; however, success is not guaranteed with implementation alone. Equally critical is addressing assembly planning and scheduling problems in robotic systems. To facilitate understanding, this review offers, in Section 2, a classification of robotic assembly systems, with an emphasis on a new layout termed the robotic matrix-structure assembly system. Section 3 classifies the planning and scheduling problems applied to the robotic assembly systems. In Section 4, we discuss the approaches and techniques used to formulate and solve the planning and programming challenges. Finally, statistical data are presented to illustrate current research trends and identify gaps for future research.

Sustainable production is not limited to environmental concerns only; It also provides economic benefits for businesses. Businesses that adopt sustainability principles can gain advantages in matters such as cost savings, competitive advantage, risk management, legal compliance and corporate reputation. Therefore, sustainability is no longer an option but a strategic imperative for businesses. For this reason, studies on energy-sensitive scheduling have started to increase recently. Another important factor in sustainable manufacturing is the reduction of scrap. Rework operations are required to reduce scrap. In this study, the multi-objective flexible job shop scheduling problem (MO-FJSP) that considers energy efficiency is discussed. The created model aims to minimize the energy consumption, total machine workload and makespan. In this study, new job arrivals are considered as dynamic events. Another dynamic event added to the model is the addition of rework processes between operations to reduce the scrap rate when a scrap decision is made during the production stages. The enhanced NSGA II algorithm was applied to solve this problem. The enhanced NSGA II algorithm was applied to test instances and its performance was compared using some of the multi-objective performance indicators. These experimental results prove the effectiveness of the proposed solution method.

As an integral part of production planning control, order release management is critical to enhance the competitiveness and production efficiency of companies. Previous literature shows limited application of optimization-based models in assembly job shops, primarily due to the intricate nature of product structures and assembly operations. Therefore, based on the idea of the allocated clearing function (ACF) model, we introduce material flow constraints and complex assembly structure constraints during the assembly stage, proposing the assembly job shop allocated clearing function (AACF) model. The performance of the AACF model and the rule-based mechanisms in terms of cost and timing measures are compared through experiments containing 6 factors and 96 scenarios. The results show that the AACF model performs better in terms of cost management, service level and order due date deviation. In addition, a sensitivity analysis of the objective function parameters is performed to confirm the robustness of the AACF model. Finally, a case application in a real assembly shop illustrates the feasibility and validity of the proposed AACF model.

Assembly buildings, in the context of the low-carbon transformation of the construction industry, achieve superior outcomes in terms of carbon emission reduction, enhancement of building uniformity, and optimization of resource utilization as compared to traditional buildings. However, the supply chain for assembly building is marked by a significant susceptibility to risk and a need for timely fulfillment of requirements. This paper examines the risk of disruption and capacity limitations in the assembly building supply chain resulting from supply disruptions. It establishes a three-tier supply chain for assembly buildings, including primary component suppliers, backup suppliers, assembly manufacturers, and retailers. The study compares the optimal decision-making and coordination strategies of the supply chain members under centralized, decentralized, and joint agreements. The supply chain dual-source procurement decision coordination model is constructed by incorporating capacity constraints and analyzing the effects of supply disruption probability, repurchase coefficient, revenue sharing coefficient, cost, and other parameters on the expected profits of the supply chain members using arithmetic simulation. Research has indicated that when the likelihood of a disturbance occurring rises, the anticipated financial gain for the main provider decreases, while the predicted financial gain for the secondary supplier increases. The implementation of a collaborative agreement between the assembly maker and the parts backup provider would result in much greater anticipated profits compared to the decentralized decision-making approach. The impact of the revenue sharing coefficient on the predicted earnings of retailers and assembly manufacturers is more significant compared to the repurchase coefficient. The selection bias between NA and NB techniques under capacity constraints mostly arises from the assertiveness of the wholesale asking prices of inexpensive component suppliers, leading assembly manufacturers to increasingly prefer the NA option. This paper's research successfully achieves the contractual coordination of the assembly building supply chain, enhances the resilience of the assembly building supply chain, and promotes the long-term sustainable development of the assembly building supply chain.

With the organic integration of the Internet and remanufacturing industry, traditional manufacturers can recycle used products and sell products (including new and remanufactured products) through e-commerce retail platforms. A recycling and remanufacturing supply chain with three members (manufacturer, e-commerce retail platform, third-party recycler) is constructed in this paper. Manufacturer has remanufacturing capabilities, and the e-commerce retail platform can provide logistics service. In response to the organic integration of the Internet and remanufacturing industry, we mainly consider the pricing decisions of consumer preferences for online sales models and recycled products’ quality. Based on the impact of consumer used product recycling promotion activities on supply chain, a pricing game model was constructed for three recycling channels: manufacturer, e-commerce retail platform, and third-party recycler. Optimal pricing decision, logistics service level, used product recycling promotion intensity index, and recycling rate were obtained. Research has shown that consumer preferences can significantly improve supply chain logistics service level, pricing, market demand, and profits; Strengthening consumer awareness of remanufacturing used products and improving recycled products’ quality can not only lower consumer purchase prices and expand consumer demand, but also increase profits of supply chain members.

The stochastic contextual bandit problem, recognized for its effectiveness in navigating the classic exploration-exploitation dilemma through ongoing player-environment interactions, has found broad applications across various industries. This utility largely stems from the algorithms’ ability to accurately forecast reward functions and maintain an optimal balance between exploration and exploitation, contingent upon the precise selection and calibration of hyperparameters. However, the inherently dynamic and real-time nature of bandit environments significantly complicates hyperparameter tuning, rendering traditional offline methods inadequate. While specialized methods have been developed to overcome these challenges, they often face three primary issues: difficulty in adaptively learning hyperparameters in ever-changing environments, inability to simultaneously optimize multiple hyperparameters for complex models, and inefficiencies in data utilization and knowledge transfer from analogous tasks. To tackle these hurdles, this paper introduces an innovative transfer learning-based approach designed to harness past task knowledge for accelerated optimization and dynamically optimize multiple hyperparameters, making it well-suited for fluctuating environments. The method employs a dual Gaussian meta-model strategy—one for transfer learning and the other for assessing hyperparameters’ performance within the current task —enabling it to leverage insights from previous tasks while quickly adapting to new environmental changes. Furthermore, the framework’s meta-model-centric architecture enables simultaneous optimization of multiple hyperparameters. Experimental evaluations demonstrate that this approach markedly outperforms competing methods in scenarios with perturbations and exhibits superior performance in 70% of stationary cases while matching performance in the remaining 30%. This superiority in performance, coupled with its computational efficiency on par with existing alternatives, positions it as a superior and practical solution for optimizing hyperparameters in contextual bandit settings.

Increasing customer apprehensions regarding the security and nutritional value of agricultural goods are compelling governments and industries to implement traceable, transparent, and reputable logistics management systems. Blockchain-based agricultural logistics management systems guarantee the permanence of data once it is uploaded but cannot cope with the risk of data being falsified before uploading to the blockchain. In this work, we developed a collaborative game model between government bodies and agricultural enterprises based on the evolutionary game theory and explored the influencing factors of enterprises following the rules to share the real traceability information through numerical simulation using MATLAB. The findings show that government incentives and penalties promote positive behavior, and consumer and media supervision contribute to supply chain transparency, but firms tend to share truthful information only when it benefits them. This study builds upon existing research on the impact of social variables on both members' decision-making behavior. It highlights the positive roles of consumers and the media in the supervision of agricultural product traceability, which can help to raise public awareness of social responsibility and thus promote positive interaction in the market.

The Covid-19 pandemic has significantly impacted consumer behavior and commerce, prompting a shift towards online goods and services. The surge in demand has led to inefficiencies and disruptions, especially in the last-mile delivery (LMD) process. Because of the LMD, the final stage of the supply chain, plays a crucial role in transporting goods from businesses to consumers, challenges such as the cost inefficiencies of direct home delivery have underscored the need for innovative solutions. In this study, the collection delivery points (CDPs) approach was adopted instead of direct home delivery. It focuses on addressing these challenges by adopting service points as dynamic CDPs and handling the problem as a dynamic location routing problem (DLRP). Two solutions approaches are proposed, to select candidate depots strategically and determine efficient route configurations, to aim to minimize travel distance. One of them is a two-phased hierarchical method that starts with clustering and continues with an Ant Colony Optimization (ACO) based-hybrid algorithm, and the other one is based solely on an ACO-based hybrid algorithm. The performance of these approaches is evaluated on modified benchmark instances from the literature. It has been observed that the ACO based-hybrid algorithm is more successful in terms of total travel distance, and if an evaluation is made in terms of the number of routes, it is recommended that the results of the two-phased hierarchical method should also be considered. Furthermore, a real word case study was conducted with the proposed methods and the results were compared from different perspectives. The results corroborate the findings regarding benchmark instances, thereby providing additional validation to the results obtained.

Trolley rack is a material handling that significantly affects production productivity in Indonesian Tea factories. The design of this tool needs to consider the anthropometric approach. This study raises the problem of the dimensions of the trolley racks used in the industry without thinking about the anthropometric approach. Of the twenty-two trolley rack operators, 92.5% of workers experienced back pain when operating the equipment. This problem has an impact on musculoskeletal disorders (MSDs), which causes a decrease in effectiveness and workers. The REBA and Nordic Body Map Questionnaire methods are used to obtain optimal operator posture analysis related to the redesign of the trolley rack. Five anthropometric dimensions of a comfortable trolley rack were obtained, including shoulder height (SH), standing shoulder width (STW), leg length (FL), foot width (FW), and hand grip width (HGW). The final anthropometric dimensions of this tool are SH = 126 cm, STW = 33 cm, FL = 11 cm, FW = 13 cm, and HGW = 5 cm. Using new trolley racks in this study increased productivity by 80%.

Additive manufacturing, or 3D printing, has become very common in professional applications in many industries. The 3D printing technology is especially suitable for making prototypes, demonstrators and small-batch production. The stiffness and strength of 3D prints depend on many factors, including among others infills, which are specific to this technology, as well as the orientation of the object during 3D printing. Where the stiffness or strength of an element is crucial, the only way is to empirically assess its properties. The advantage of 3D printing, i.e. incomplete infill of the interior of an object with the use of different types of infills (patterns) and different amounts of material, means that its mechanical properties differ from those of a solid element. The application of numerical tests, i.e. the finite element method (FEM), requires the creation of a 3D model while taking this infill into account. The modelling of elements for performing numerical strength calculations is time-consuming and labour-intensive. The article presents a proprietary original analytical method for generating various types of infills with varying infill density. The method was developed for typical infills (Grid, Triangular, Honeycomb). It was next implemented in the CAD environment using the iLogic tool of Autodesk Inventor. As a result, a tool for creating 3D models of objects consistent with those obtained from 3D printing was obtained. The method and tool were verified. Next, the influence of selected parameters of the 3D print on its mechanical properties was presented on three real objects. The results of numerical analyses revealed measurable benefits of such tests. The research conclusions also constitute recommendations for selecting the type and infill density of an object and its orientation in the printer with regard to the strength and stiffness obtained.

Overall equipment effectiveness (OEE) is a key indicator to measure the effectiveness of production systems. This paper aims to evaluate and improve a plastic production line based on OEE evaluation. An integrated framework is proposed to enhance the production system efficiency. This paper presents the data for a Plastic production line in Jordan under real working conditions. The data covers three months. A framework process to improve the OEE of the Plastic production system was proposed. Six major stoppage losses were inspected with the help of Pareto analysis. Furthermore, the actual availability, efficiency, and quality rate measures, together with the whole OEE for each working day, week, and month of the production line were shown. The methodology is based on determining the OEE of a Plastic production line after determining the causes of failures. The fishbone diagram tool is used to determine the root causes of failures. To improve the OEE measure, several losses are identified. The results reveal that the company should improve its policy to improve the production line’s performance and reduce losses. Top management should also pay attention to reducing the speed losses, which consist of 58.1%, and eliminate the planned and unscheduled disruptions covering 12.73% of all losses. This can be achieved by establishing a proper operation management procedure and strategy. This, in turn, optimized the equipment’s effectiveness. The quality procedure should include the changeover program that may be executed every day. Similarly, all preventive maintenance procedures for the six machines should be properly executed in predetermined intervals. There are several limitations in the research. Firstly, the research case study is only the plastic production system. Secondly, the research is related to the downtime or stoppage by analyzing it using fishbone diagram. Further, supported by other techniques such as the Pareto chart, six big losses analyses and CED. This research conducted on a Plastic industry. However, similar studies can be carried out in future in other manufacturing industries like electronic, pharmaceutical, textile industries, etc., and service industry. However, as future research work the contributions of this paper with other lean manufacturing concept like six sigma, quality function deployment, TQM, and just-in-time manu-facturing, can also be conducting to assess the overall production line efficiency. On the other hand, several statistical tests can be implemented based on data collected of TPM performance indicators. The proposed method supports policymakers in their decision-making process on the operations management line. Further-more, it improves the production systems’ productivity quality, and performance, reducing unplanned stop-pages and breakdowns, and reducing maintenance costs.

This article examines the utilization of computer simulation techniques for optimizing warehouse locations, an essential component of efficient supply chain management. The study employs a detailed simulation model built using FlexSim software to analyze various decision-making scenarios and identify the optimal warehouse locations while considering market demand for different products. The model integrates a finite set of decision variables and constraints specific to the logistics problem, offering a structured approach to evaluate alternative strategies. Key stages in the development of the simulation model are outlined, including the definition of input parameters, the execution of simulations, and the interpretation of results. The findings demonstrate that virtual simulation modeling significantly enhances decision-making processes by providing precise insights into the interactions within the distribution network. Additionally, the use of simulation results in considerable time and cost savings by reducing the need for costly physical trials. This research underscores the effectiveness of computer simulation in optimizing warehouse locations, contributing to improved supply chain performance and operational efficiency.

The article presents the author’s approach to the classification of types of attractiveness that may be characteristic of certain European countries. The migration attractiveness of countries is highlighted and a list of factors that can affect it is given. Factors were ranked according to the level of their impact on population migration, among which the following were highlighted: the economic development of countries, production processes, the use of more modern technologies, ensuring one’s financial well-being, and the culture of the production environment. The dynamics of the number of immigrants who moved to the studied European countries since 2020 are given. The main programs under which European countries accept migrants for permanent residence are considered the issues of providing housing, employment in the industrial infrastructure, and increasing the level of professional competence in various fields. To conduct a comparative assessment of the attractiveness of European countries for potential migrants, a set of available statistical indicators was selected, which fully reflects the main parameters of the countries’ attractiveness. Individual results obtained in the process of assessing the migratory attractiveness of the countries of the European Continent are presented, and proposals for its improvement are presented. It is proved that increasing migration attractiveness is possible by improving the social and economic attractiveness of countries. To do this, countries should create conditions for the development of various industries, create additional jobs, provide high wages, social services, protection, etc. to attract as many highly skilled labor resources from other countries as possible. As a result, the growth in the number of professional labor migrants in countries will contribute to the development of those industries that are common in the respective countries.

The furniture industry is one of the industrial sectors that has a potential market in Indonesia. This industry requires a lot of wood raw materials but is faced with a wood legality verification system that limits raw materials. Industrial players still need to start using waste as raw materials, which will reduce the use of primary raw materials. The circular economy concept can be applied to waste treatment. This study aims to design a pump-gallon product made from waste, considering the relatively high level of gallon container consumption. With this design, it is hoped to utilize waste into economically valuable products while reducing the environmental impact it causes. The product design process uses an integrated QFD-TRIZ method combined with circular economy principles. QFD functions to determine consumer desires and make technical responses, while TRIZ resolves contradictions in technical responses. The circular economy attribute is used as a reference in making gallon pump products from wood waste. After the design process is complete, it is followed by an economic feasibility analysis using the cost-benefit ratio. The result of this research is the design of multifunctional and modular products for gallon pumps. The gallon storage is designed to store not only gallons but also a small table for placing dirty glass and a drawer at the bottom that can be used to keep the glass or other items. There is a detachable system between the upper and lower components, making it easier to repair and use. At the bottom, they mounted castor wheels to facilitate product movement. Designing products made from waste will increase the income of furniture SMEs. In addition, it is expected that this will overcome waste management problems and shortages of raw materials experienced by furniture SMEs. Future research can utilize powder and smaller pieces of wood.

Supply chain (SC) efficacy and efficiency can be severely hampered by supplier delays in orders, especially in the fast-paced business environment of today. Effective risk reduction necessitates the identification of suppliers who are prone to delays and the precise prediction of future interruption. Accurately predicting availability dates is therefore a key factor in successfully executing logistics operations. By leveraging machine learning (ML) techniques, organizations can proactively identify high-risk suppliers, anticipate delays, and implement proactive measures to minimize their impact on manufacturing processes and overall SC performance. This study explores and utilizes various regression and classification ML algorithms to predict future delayed delivery, determine the status of order deliveries, and classify suppliers according to their delivery performance. The employed models include K-Nearest Neighbors (KNN) Random Forest (RF) Classifier and Regression, Gradient Boosting (GB) Regression and Classifier, Linear Regression (LR), Decision Trees(DT) Classifier and Regression, Logistic Regression and Support Vector Machine (SVM) Based on real data, our experiments and evaluation metrics including Mean Absolute Error (MAE), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE) demonstrate that the ensemble based regression algorithms (RF Regression and GB Regression) provide the best generalization error and outperforms all other regression models tested. Similarly, Logistic regression and GB Classifier outperforms other classification algorithms according to precision, recall, and F1-score metrics. The knowledge obtained from this study could aid in the proactive identification of high-risk suppliers and the application of proactive actions to increase resilience in the face of unanticipated disruptions, in addition to increasing SC efficiency and decreasing manufacturing disturbances.

The transformation of supply chains is an important factor for European Automotive OEMs to compete internationally. But it turns out that these are not as resilient as required. A resilient supply chain requires appropriate risk management measures that minimize internal and external influences. However, in some areas of value creation and supply chains, weaknesses are evident that are determined by a high dependence on international supplier markets. This approach to research in this area investigates whether Automotive OEM internal departments perceive certain risks differently. This was done by means of a survey of European OEMs to reveal different perceptions on important aspects of risk-based factors. Internal resilience would be necessary as a first step towards strengthening the supply chains in order to subsequently position themselves against stronger emerging competition from the Asian and US economies. This requires a strong European centering of supplier and partner networks, for example in the area of physical goods such as semiconductors and batteries. In order to support these necessary developments, networks are being established and promoted by the EU. GAIA-X and especially Catena-X are bases for the Automotive industry to adapt and optimize resilience and compliance regulations to governmental and intranational guidelines. As result of this research, it remains to be said that the realignment of supply chains must succeed in improving cooperation and delivery conditions across the entire OEM spectrum while at the same time reducing costs. In this way, the European Automotive market can be positioned as a resilient, strong market player for the future. The basic prerequisite for this is a uniform and coordinated view of risk-based factors in the individual companies and departments.

The present research discusses the application of risk management tools and Real Option Analysis (ROA) to assess and quantify managerial flexibility in machine replacement decisions under uncertain conditions. Different management configurations are used for the real options approach: options to execute, options to delay, and options to cancel. This reflects the uncertainty inherent to each stage of planning. Uncertainties such as future demand and life-cycle costs are implemented in the model as probability distributions. Monte Carlo simulation is employed to deal with such uncertainties and to facilitate experimental trials. The net present value is used as a decision criterion to determine the best replacement option under different replacement and real option scenarios. Herein, a case study to evaluate different replacement alternatives was conducted for the garment industry. Results of the stochastic net present value, mean-standard-deviation scatter plot, and stochastic dominance showed that the best option was to rent and then buy a new machine of reduced size but greater technological advancement. Finally, tornado diagrams and perfect control methods were used to analyze uncertain factors in order to improve the model and further minimize uncertainty effects.

Fused deposition modeling (FDM) is a commonly used additive manufacturing (AM) technique in both domestic and industrial end-product fabrications. It produces prototypes and parts with complex geometric designs, which has the major benefits of eliminating the need for expensive tooling and flexibility. However, the produced parts often face poor part strength due to anisotropic fabrication strategies. The printing procedure, the kind of material utilized, and the printing parameters all have a significant impact on the mechanical characteristics of the printed item. In order to predict the mechanical properties related to printed components made with the use of FDM and Polylactic Acid (PLA) material, this study concentrates on developing a prediction model utilizing Artificial Neural Networks (ANNs). This study used the Taguchi design of experiments technique, utilizing (L25) orthogonal array as well as a Neural Network (NN) method with two layers and 15 neurons. The effect of FDM parameters (layer thickness (mm), percentage of infill density, number of top/bottom layers, shell thickness (mm), and infill overlap percentage) on ultimate tensile and compressive strength (UTS and UCS) was examined through analysis of variance (ANOVA). With an ANOVA result of 67.183% and 40.198%, respectively, infill density percentage was found to be the most significant factor influencing UCS and UTS dependent on other parameters. The predicted results demonstrated valuable agreement with experimental values, with mean squared errors of (0.098) and (0.326) for UTS and UCS, respectively. The predictive model produces flexibility in selecting the optimal setting based on applications.

Making a Master Production Schedule (MPS) is a very important activity for a manufacturing industry. This is due to the fact that MPS serves as an input for material and production planning. Between the years 2020 and 2022, there were significant fluctuations observed in container freight rates. As response, a lot of manufacturing industry focus on optimizing their container delivery schedule. Hence, there is a need for aligning the master production schedule with the delivery schedule. This paper presents the development of a novel heuristic approach to address problems with the creation of MPS. Specifically, the focus is on the situation where container delivery schedules are prearranged and serve as a main input for creating the MPS. There are two objective functions that are going to be reached: 1) minimize the total number of product variations or Stock Keeping Units (SKU) per month; and 2) minimize the number of SKU per container. The proposed heuristic approach uses the similarity concept to group objects in a clustering technique. It is then implemented in a real-world case of a furniture manufacturing company. Further results were obtained and then compared to the heuristic technology that had previously been used by business entities. The results show that the number of product variations (SKU) that must be performed per month is 10% lower than that of the existing heuristic. In addition, the ratio of SKU variations per container is 9% lower than that of the existing heuristic. The time required to complete the task of creating MPS is less than one minute, as opposed to the one working day required by the company’s existing heuristic.

Electrical Discharge Machining (EDM) process is considered as one of the ultimate famously process used in the components production like tools of surgical, dies, punch and aerospace. The EDM technique perform on the control of loss metal principle according to power as thermal-electric through the electrode and blank piece. Alloy steel (X210) was selected as a workpiece, whereas copper electrodes selected by in different angled electrodes (0°, 22.5°, 45°, 67.5°, and 90°). The technique of composite design (CCD) was applied in this work and accomplish (ANOVA) was concluded to consider the highly important variables. The experimental results show that the material removal rate is accelerate at highest value using Angle of Electrode (E A 67.5°) and (I 30A). Electrode Wear Rate (EWR) can be attained using (E A 22.5°) and (I 20A).Thickness of White Layer (WLT) is increased at (E A 22.5°) with enlarge current at maximum magnitude (30 A), minimize WLT is obviously at (E A 45°) and current is (15A). An optimization technique was utilize to conclude of optimal parameters at maximize MRR and consequently reduce EWR. The optimum values for the responses such as MRR and EWR with optimum value are gained with the following parameters: (E A 22.5°), (I 27), (P-on299) and (P-off 50).

The introduction of the obligation to prepare ESG reports taking into account EU Taxonomy is a challenge for enterprises, but at the same time opens up the possibility of using disclosures in this area to assess entities in the context of environmentally sustainable activities. Legal changes in the field of the Green Deal have been introduced in the last three years, and in the area of EU taxonomy this process is still ongoing, resulting in a deficit of research on the effects of implementing the new legal regulations. The main goal of our study is to assess the importance of the newly applicable ESG reporting and environmental disclosure requirements under EU Taxonomy in improving the quality and comparability of sustainability reporting and the creation of ESG ratings. A qualitative research method was applied based on multiple case studies using content analysis on the basis of ESG reports for 2021-2022 for entities listed on the Warsaw Stock Exchange. The research results indicate a very low level of activities classified as environmentally sustainable and taxonomy-aligned. Additionally, the results may also indicate problems with implementing the new solutions in reporting practice. At the same time, a positive impact is noted of the implementation of taxonomic reports on improving the comparability and detail of disclosures.

The main objective of the work was to assess the possibility of using and implementing the FMEA method as an effective support for the HACCP system in a selected food industry enterprise. The research entity was a food enterprise located in central Poland and the subject of the research was canned meat with gravy in glass jars and their production line. In the study, programs such as draw.io, Excel, and Statistica were used. The study was conducted based on interviews with company employees, value stream analysis and nonconformance reports. During the site visit, an assessment of the company’s infrastructure was also carried out to evaluate the possibility of implementing the FMEA method. Data analysis showed that in the examined company there are non-compliances with varying degrees of impact on the final quality of the product or on the production process of this product. The analysis of the company’s infrastructure, in turn, confirms that it is possible to integrate the HACCP system with the FMEA method. The results indicate that the synergy of HACCP and FMEA will bring benefits to the company in the form of improved risk management, quality control and safety in food production. The results of this study suggest that implementing such a connection may bring many, various benefits to food companies not only in Poland but also in another countries.

This research aims to examine the role of corporate strategy as a mediating influence between unique capabilities and environmental turbulence on the performance of Legal Entity Universities (Perguruan Tinggi Negeri Berbadan Hukum - PTNBH university). Corporate strategy is important in supporting unique capabilities and environmental volatility to achieve performance. The population of this study were leaders at the PTNBH University in Central Java. The sample collection technique uses purposive sampling, namely data collection, by considering the criteria: it is a state university with a legal entity, and it has been active in structural positions for at least 1 year. The number of samples was a total of 109 respondents. The results found that unique capabilities do not directly influence university performance but directly influence corporate strategy, and environmental turbulence directly influences corporate performance and strategy. The unique capabilities possessed by universities are good capital in the increasingly fierce competition because they can be used to develop higher education strategies. The results of indirect testing (mediation) show that corporate strategy plays a mediating role between unique capabilities and environmental turbulence on the performance of PTNBH University. Future researchers can combine or add other predictor variables to generalize this research.

This study aims to explore how tax planning practices impact firm value, with a specific focus on gender diversity as a moderating factor shaping the relationship between tax planning and firm value. Data collection involved purposive sampling, resulting in 121 samples drawn from manufacturing companies listed on the Indonesia Stock Exchange between 2018 and 2022. Employing panel data analysis supplemented by moderated regression analysis, the research uncovered several key insights. Tax planning and inflation rates exert a negative influence on firm value, whereas dividend policy and profitability have a positive impact. Interestingly, board gender diversity was found to weaken the effect of tax planning on firm value, implying that board gender diversity can significantly affect the efficacy of tax planning strategies in enhancing company value. These findings offer valuable insights for refining tax planning strategies within the manufacturing sector, considering various factors that influence firm value. Moreover, this study contributes to the existing literature on tax planning and corporate governance, laying a groundwork for further exploration and aiding in the evolution of more robust theories and frameworks in this scope.

This research identifies leadership styles at private universities in Central Java, analyzes organizational culture, and formulates strategies for the success/survival of private universities. Primary data was obtained through in-depth interviews with 9 university leaders as informants, with stratified sampling based on excellent, excellent, and good accreditation categories. Semi-structured interviews focused on leadership approaches, organizational culture, success strategies, and challenges. The data were analyzed using ATLAS.TI with thematic analysis. The results show that private universities have characteristics, such as leadership styles, that form different organizational cultures. There are differences in higher education management strategies between accreditation categories, especially in strategic priorities according to institutional goals. Superiorly accredited universities tend to prioritize research excellence, international collaboration, and innovative academic programs. The implication is that understanding the relationship between leadership, organizational culture, and strategic priorities can help universities align these elements for optimal effectiveness in achieving success in the competitive environment of higher education.

Digital transformation has become essential for all organizations as innovation and digital technology continue to evolve. This research focuses on the impact of organizational agility on digital transformation in the government sector, as well as the role of Collaborative Knowledge Creation (CKC), innovation, and Digital Transformational Leadership (DTL) as antecedents and factors that influence organizational agility. Quantitative research using the Structural Equation Model (SEM) method began in 2023. The unit of analysis involved 103 work units in government organizations that focus on the development of science and technology (S&T). The results of this study show that the role of organizational agility can improve digital transformation in the government sector, and the role of innovation and DTL as antecedents and factors, can affect organizational agility. This shows that in driving change towards digital transformation in organizations, the role of organizational agility is very important. This research has managerial implications for government organizations, especially organizational leaders and work unit leaders in building digital transformation. Organizational leaders must realize that implementing sound management strategies fostering organizational agility, including designing adaptive policies, cultivating a responsive organizational culture, and establishing structures that promote collaboration and innovation can facilitate government organizations digital transformation.

The impetus for this research is Generation Z's lack of understanding of social media marketing and brand image in relation to buying local products, because local brands are generally less successful. Self-congruence is new to assess consumer alignment with brands, which ultimately influences purchase decisions. The study's gap focuses on brand image, highlighting challenges consumers face in identifying with brands via social media. This study aims to show the impact of social media marketing on customer self-alignment, brand image, and purchase decision. The research data was collected by distributing questionnaires using a purposive sampling method to 217 gen Z participants who use local skincare and analyzed using SEM. The results show that all hypotheses influence each other by applying the self-expansion theory, where consumers will align themselves with brands from local products so that consumers will expand their self-concept and culminate in purchasing decisions. This study will also examine customer characteristics by gender and age as control variables that can be fully predicted. The findings of this study indicate a difference in gender, where women are more easily attracted to try than men. Younger consumers were found to prefer shopping online rather than physically, in contrast to older consumers.

This research aims to develop and evaluate an empirical model of the role of QRIS (Quick Response Code Indonesian Standard) Contactless Payment Quality, including Perceived Ease of Use (PEOU), Perceived Usefulness (PU), and Service Security (SS), in shaping User Satisfaction (US) and Continuous Usage (CU) among QRIS payment users in Central Java. The empirical model is built based on the Technology Acceptance Model (TAM) and existing literature on Contactless Payment Quality. For this purpose, an online survey was conducted with approximately 232 QRIS payment users aged 17 and above, and the data were analyzed using the Structural Equation Modeling (SEM) approach with the SmartPLS program. The study found that PEOU significantly influences PU. Additionally, the three components of Contactless Payment Quality (PEOU, PU, and SS) jointly determine US, and both US and SS together impact CU. Furthermore, this research demonstrates that US truly mediates the relationship between PEOU, PU, and SS with CU. Therefore, the findings contribute to the development of a holistic TAM and Contactless Payment Quality framework by providing a comprehensive model of antecedents and consequences of user satisfaction for QRIS payment users. The study also offers valuable insights for managers of companies managing QRIS systems.

MSMEs in Indonesia face fundamental problems in developing business strategies. This research explores the impact of strategic orientation (SO) on business performance. SO involves the integrated role of entrepreneurial orientation (EO), market orientation (MO), and collective orientation (CO) in improving performance. This research also examines the mediating role of CO, MO and the moderating role of EO. Demographic variables are used as control variables. Data obtained from 192 creative industries in Malang Raya with a response rate of 65 percent (124 MSMEs). This study utilizes PLS-SEM methodology to investigate target relationships. The results show that MSME performance is significantly influenced by SO, both EO and MO, but not CO. This confirms the direct influence of EO and MO on performance, as well as the indirect influence of MO on the EO-performance relationship. In addition, this research reveals that the performance of MSMEs managed by women tends to be lower than MSMEs managed by men. This is because the EO characteristics of men are greater than those of women. The implication of these findings is that MSMEs must improve EO and MO. Effective CO needs to be strengthened so that it can make a major contribution to sustainability of MSMEs.

Green banking combines operational improvement, technological advancement, and modifications to client behavior in commercial banking. Activities in environmental, social, and corporate governance (ESG) management are part of the banking industry's adoption of sustainable green banking. The goal of ESG disclosure in banking organizations is to spur market growth, boost consumer confidence in banking goods and services, and give investors essential information for making investment decisions. This study intends to empirically demonstrate the impact of audit firm affiliation and financial stability on the degree of disclosure of sustainable green banking. A banking firm with an observation period of 2019–2022, listed on the Indonesia Stock Exchange, serves as the study's sample. The quantitative data used in this study were taken from published annual reports. Purposive sampling is a strategy used to obtain data. The study's independent variables are affiliation with an audit firm and financial stability as measured by return on equity (ROE). While the Environment, Social, and Governance Index (ESGI) will be used as a proxy for the dependent variable in this study, which is the degree of sustainable green banking. The natural logarithm of total assets is employed in this study's control variable for business size. The hypothesis being investigated is that the development of sustainable green accounting is positively influenced by financial stability and affiliation with audit firms. Several regression tests are used to evaluate this hypothesis. The findings of this study are intended to give banking organizations a general overview of the value of sustainable green banking in enhancing investor trust and improving their capacity to compete in the capital market.

The tourism industry in Bali is currently experiencing improvement after experiencing hibernation during the pandemic. This situation will certainly have an impact on all supporting businesses, including hotels in general and employees in particular. This research aims to investigate the relationship between transformational leadership and organizational culture, work motivation, and job satisfaction. Survey data was collected from 264 four-star hotel employees in Bali. Then the data was analyzed using Smart PLS 3.2.9. The findings of this research show that transformational leadership has no effect on job satisfaction, but has a significant effect on organizational culture and work motivation. Furthermore, organizational culture and work motivation act as mediators of the relationship between transformational leadership and job satisfaction. Thus, organizational culture and work motivation play an important role in maintaining and increasing job satisfaction. In addition to showing direct influence, they also act as mediators.

This research aims to analyze the retirement planning of employees belonging to the sandwich generation by considering financial literacy, collectivist culture, and family financial responsibility that promote financial and psychological well-being. We run the SEM-PLS to analyze the data from 200 sandwich-generation employees between 25-55 years old. The results demonstrate that financial literacy positively affects financial and psychological well-being, collectivist culture positively affects family financial responsibility, family financial responsibility affects retirement planning and psychological well-being, as well as retirement planning positively affects financial and psychological well-being. These findings indicate that personal and financial factors contribute to retirement planning for sandwich generation employees. It is hoped that planning for retirement early can break the chain of births of the next sandwich generation in the family, so that financial and psychological well-being can be achieved. This paper implies that sandwich-generation employees must plan their retirements early and wisely to achieve financial well-being and even break the chain of the next sandwich-generation.

This research investigates the impact of Interaction Capability on Customer Participation, influencing the development of Perceived Holistic Value in transformative human services aimed at enhancing customer well-being. An innovative aspect introduced in this study is Religious Interaction Capability, which supplements the existing dimensions of Interaction Capability: Individualized Interaction, Relational Interaction, Empowered Interaction, and Ethical Interaction Capability. The study involved 192 outpatient participants from Islamic hospitals in Central Java, Indonesia, selected through purposive sampling. Data analysis utilized Structural Equation Modeling (SEM) with AMOS 22.0. The results suggest that Religious Interaction Capability and other interaction capabilities significantly motivate religiously oriented patients to seek and responsibly share information. Furthermore, all factors facilitating Customer Participation contribute to the formation of Perceived Holistic Value, extending beyond transactional aspects such as process and outcome value to include a broader dimension of religious value. These findings have implications for strengthening the Resource-based View theory.

The mental health and overall quality of seafarers are critical to the safety and efficiency of maritime operations. This study investigates the factors influencing the quality of Indonesian seafarers, with a particular focus on mental health as a mediating variable. Using Structural Equation Modeling (SEM) with Partial Least Squares (PLS), we analyzed data from 280 respondents, including skippers and crew members working on Indonesian flagged ships. The study examines the impact of working conditions, recruitment and placement, training and development, and safety culture on seafarer quality, both directly and indirectly through mental health. Our findings indicate that mental health significantly mediates the relationship between these factors and the quality of seafarers. Training and development emerged as the most influential factor, followed by safety culture, recruitment and placement, and working conditions. The results emphasize the importance of enhancing mental health support to improve working conditions, recruitment processes, training initiatives, and safety culture, thereby increasing productivity and the overall quality of seafarers. This research addresses an empirical gap by providing practical strategies to improve Indonesian seafarers' quality and job stability in the global maritime industry. Future research should expand the geographic scope and explore additional factors affecting seafarer quality and mental health.

The corporate world is growing more competitive as customers become more savvy. SMEs require a wide range of material and immaterial resources, as well as the capacity to change into more adaptable and lucrative forms to adapt to the shifting demands of the business market, in order to remain competitive. This study aims to examine the correlation between human capital and total quality management with entrepreneurial orientation and their impact on performance. Specifically, the study will investigate how market orientation functions as a mediating factor in the link between TQM, HC, EO, and the performance of small and medium-sized enterprises (SMEs) in Semarang. Empirical research has largely neglected to investigate the role of market orientation in mediating the links between TQM, HC, EO, and business performance. This study aims to address the existing knowledge gaps by investigating the direct as well as indirect impacts of TQM, HC, and EO on the performance of SMEs, with MO serving as a mediator. In this study, a questionnaire was employed to gather data from subject matter experts (SMEs) to evaluate the theoretical framework. PLS is utilised in the investigation and testing of hypotheses.

The emergence of increasingly complex global supply networks and the rising risk of unpredictable events may have far-reaching consequences for various industries and the global economy. The impact unpredictable events have on supply chains remains a relatively underexplored area that requires further research and analysis. Current studies primarily concentrate on singular events, particularly the COVID-19 pandemic and its effects on supply chains. This research aims to identify the main challenges in supply chain management resulting from unforeseen events and the actions taken in supply chains in response to them. The research is based on individual in-depth interviews conducted with a purposive sample of experts in supply chain management using a partially structured interview questionnaire. The research results were analysed using Nvivo v. 17.1, software for qualitative data analysis. A hybrid approach was employed for data coding. The research indicates several problems and the main remedial actions in supply chains in response to unforeseen events. Unforeseen events in the supply chain affect almost all supply chain operations: procurement, planning (including inventory planning and maintenance of company resources and production lines), logistics management (including transportation), and order management. The research indicated that cooperation, integration, and information exchange within the supply chain are crucial for effective responses to unforeseen events. Furthermore, the research highlighted the positive impact of unforeseen events on supply chain innovation. Moreover, there is an observed prevalence of intuitive management, particularly when responding to unexpected events. The research findings can serve as a basis for further discussions and studies on the potential impact and consequences of future unexpected events on supply chain resilience.

This research aimed to use a sustainable approach based on the internalisation of external cost analysis of intermodal transportation of freight to assess the impacts of these activities on the environment. This research used two approaches to develop a model that illustrates the internalisation of the external cost of freight transport. The first approach was used to calculate the cost of emissions for each route considering the transportation and its’ cost in the country of destination. The second approach calculated the external cost considering only the distance travelled by the vehicle. The results showed that the companies operating in the selected scenarios would have to pay an additional cost for the transportation of goods. The scenarios had different pollutants emitted during the transportation, which means that the negative impact on human health and the environment is evident. The urgency to limit carbon dioxide and other greenhouse gases in the atmosphere has increased concerns for all activity sectors. Climate change has drawn the attention of governments, companies, and academics, promoting initiatives that mitigate the impact of their activities. The model for measuring emissions was used due to the need for a comprehensive cost analysis to further assess the impact on the environment. Regarding the internalisation of the external cost emissions, the findings showed that different scenarios had a different pollutant emitted during the transportation, which means that the negative impact for human health and the environment is evident. Findings also indicate that to minimise the impact during the transportation, considering the “user-pays principle”, these impacts should be discussed in more detail between stakeholders.

Changes taking place in the economy affect the emergence of innovations. It is primarily technological progress that influences the creation of new solutions. Logistics is one area where innovations and improvements are needed. New solutions are primarily process improvements, the implementation of autonomous vehicles, solutions that help to supervise transport processes, and the effectiveness and costs of their implementation. The greatest benefits of technological progress are the provision of knowledge and information about the journey, the efficiency of a given car and driver, and changes in the market (e.g., information about the demand and supply for given services). This article aims to identify the possibilities of using freight exchanges in transport and forwarding management. It is based on a literature analysis and statistical data from systems dedicated to transport and forwarding, as well as surveys conducted by the author. The article uses analyses of demand, supply and prices based on data from transport exchanges. Possibilities of obtaining information for better management of a transport company were presented. Possibilities of obtaining information for better management of a transport company were presented. The article presents the relationship between the use of the transport exchange and the size of the company, fleet and the number of countries served as part of transport services. The possibilities of using transport exchanges and the possibility of replacing software dedicated to transport and forwarding by the discussed programs were indicated.

Requirements of the international standard ISO 45001:2018 were analysed to identify the need for monitoring, measuring and analysing the functioning of the occupational health and safety management system. This analysis has made it clear that the effectiveness of the development and implementation of the occupational health and safety management system depends on the assessment methodology. The study focused on existing studies and publications on the assessment of processes, including those related to occupational safety, assessment methods or qualitative methods, and statistical methods used for assessment. As a result, the topic has been proven relevant, and the goal of the article was determined: to study the possibility of using qualimetric methods for evaluating the labour safety management system. A survey was conducted among workers at a machine-building enterprise to evaluate the occupational health and safety management system. Verbal scales were proposed to process the study results as they allow quantitative ratings to be obtained on the coded scale of the desirability function. The study result is a technique for obtaining a quantitative assessment of the occupational health and safety management system. This technique is universal and can be applied to any enterprise. It can also be used to make managerial decisions regarding the improvement of the occupational health and safety management system.

The article addresses the issue of the future of European universities on the path to sustainable development. The main aim of the article is to describe foreseeable future directions of the sustainable development of universities and ways to achieve Sustainable Development Goals. In effect, the authors identify weaknesses, assess threats and recommend coordinated solutions and alternatives for the sustainable development of universities. This research will contribute to future work by explaining what the future of universities will look like on their sustainability journey. The results of the Delphi study conducted with the participation of 201 experts from 47 countries allowed for the identification of factors shaping the future of universities on the path to sustainable development.

Industry 4.0 (I4.0) became an important paradigm to bridge the gap between technologies and humans. The paper aims to diagnose sustainability performance and I4.0 maturity in Poland’s printing and packaging sector and identify research areas where further actions for improvements are necessary. This article adopts a mixed-method study combining in-depth interviews of eleven heterogeneous enterprises, supported with a quantitative survey on a representative sample of 301 companies. The findings revealed an insignificant correlation from a statistical point of view (0.44) between the adopted I4.0 technologies currently used and sustainable best practices. Internet of Things technologies are more often adopted in the printing industry (27.2 %) than in the packaging industry (14 %). The study concludes that using I4.0 technologies boosts the execution of sustainable practices and/or realising sustainable development practices requires I4.0 technology adoption. The paper clarifies that more in-depth analyses are needed to help achieve sustainable objectives for printing and packaging companies through digital technologies. The methodology is replicable and might be applied in other economies across separate multinational enterprises to influence sustainable digitalised business strategy.

This study investigates the relationship between internal and external factors of pro-environmental and pro-social engagement, sustainable consumption behaviour and personal characteristics such as age, gender, financial situation and level of education in the Lithuanian population. A quantitative method was used to collect data from 904 respondents in Lithuania. The study results suggest that women are more concerned about pro-environmental and pro-social issues. In addition, pro-environmental commitment, biospheric values, personal norms and perceived responsibility were important for women. Meanwhile, egoistic values, self-efficacy, social norms, biospheric values, and attachment to place were identified as more important for men. The results reveal that older age increasingly correlates with a stronger expression of place attachment, egoistic values and self-efficacy, pro-environmental and pro-social engagement, and sustainable consumption behaviour. The results of this empirical study allow for identifying the determinants that have the most significant impact on men and women or different age groups. Knowledge of factors that significantly impact pro-environmental and pro-social engagement, which promotes sustainable consumption behaviour as a mediator, can allow policymakers, community representatives or leaders to organise social campaigns and/or provide guidelines for project activities.

Producers must mark packaging with various warning signs, including the harm of alcohol consumption. The most popular warnings inform about the required consumer age (e.g., “alcohol only for adults”), consequences of drunk driving (e.g., “don’t drink and drive”), and advisable abstaining from drinking during pregnancy.

The aim of this paper is to develop design options for Augmented Reality (AR)-based remote service business models to support the implementation of AR technology for remote services currently taking place in the manufacturing industry. The design options were developed using a qualitative content analysis based on the results of a systematic literature review and on focus group discussions with 19 service-responsible industry experts from 12 German manufacturing companies. The application of a conceptual approach to taxonomy development resulted in a novel morphological framework with a total of 18 dimensions, each with two to six distinct characteristics representing the targeted design options of AR-based remote service business models. Since previous research on AR for remote services has largely neglected the business model perspective, this work makes a significant contribution to this scarcely explored research field by providing a systematic basis for describing and classifying such business models in terms of their design. The results provide industrial practice with the most important aspects to consider when designing AR-based remote service business models.

The main purpose of the paper is to identify ways to establish process security in the constantly changing risk and control environment and to introduce a new model. The research is based on a literature review of process security components. Qualitative content analysis was used to establish a linkage between the certified management systems and the level of process security. Elaborations have been conducted based on the survey data of the International Standards Organisation (ISO) and served as a basis for analysis of certification types and their sectoral division in the European Union (EU) member states. A new Balanced Scorecard has been developed to cover the security pillars in the context of standard management systems and serve as a framework for process security measurement. The research paper processes the state-of-the-art issue of process security, introduces components that help to establish process security, and establishes a linkage between the level of process security and certified management systems. An analysis was based on the ISO certification information related to different management system standards. Management systems were analysed in the context of process security and corresponding process performance measures. A brief walkthrough has been prepared to demonstrate the processes behind the underlying performance measures. A new Balanced Scorecard approach has been developed that maps and covers different security aspects retrieved from and linked to different management system standards. The new Balanced Scorecard based on different security aspects of entities can be leveraged by any organisation, regardless of its size or business profile.

Over the last decade, our world exposed to many types of unpredictable disasters (recently Coronavirus). These disasters have clearly shown the uncertainty and vulnerability of supply chain systems. Also, it confirmed that adopting Just-in-Time (JIT) strategy to reduce the logistic chain cost may lead to inbuilt complexity and risks. Efficient tools are therefore needed to make complexity optimized supply chain decisions. Evolutionary algorithms, including genetic algorithms (GA), have proven effective in identifying optimal solutions that address the trade-offs between total supply chain cost and carbon emissions regulatory policy represented by carbon tax charges. These solutions pertain to the design challenges of supply networks exposed to potential disruption risks. However, GA have a set of parameters must be chosen for effective and robust performance of the algorithms. This paper aims to set the most suitable values of these parameters that used via GA – ased optimization cost and risk reduction model in firms using a JIT as a delivery system. The model has been conceptualized for addressing the design complexities of the supply chain, referred to as SCRRJITS (Simultaneous Cost and Risk Reduction in a Just-in-Time System). A complete analysis of the different parameters and operators of the algorithm is carried out using design of experiments approach. The algorithm performance measure used in this study is convergence of solutions. The results show the extent to which the quality of solution can be changed depending on selection of these parameters.

The incorporation of artificial intelligence (AI) into industrial processes has seen substantial development, characterized by the shift from Industry 4.0 to the future concept of Industry 5.0. The article identifies a significant gap in knowledge regarding how openness in AI engagement influences consumer trust and confidence in news media. This gap highlights the need for further exploration into the relationship between transparency in AI processes and consumer perceptions. The research utilises a combination of qualitative and quantitative approaches, gathering insights from academic literature, industry viewpoints, and actual data. We conduct an extensive analysis of existing literature to investigate the process of incorporating artificial intelligence into news creation and its influence on the level of confidence consumers have in the news. We have identified a significant lack of knowledge about the impact of openness in AI engagement on consumer views and trust in news media. Expanding on this discrepancy, we suggest a systematic methodology that incorporates controlled experiments and surveys to evaluate the influence of different degrees of openness on consumer trust and involvement with AI-generated news content. In addition, the paper examines the difficulties in establishing confidence in artificial intelligence (AI) inside the European Union, including several aspects such as technological, ethical, social, and legal considerations. The document presents a thorough plan to guarantee the secure development and execution of AI, with a focus on the significance of transparency, ethics, and teamwork. The study’s results provide vital insights for politicians, news organisations, and industrial businesses as they navigate the intricate process of integrating AI. Comprehensive Plan for Secure AI Development, to address the challenges outlined, the article presents a thorough plan for ensuring the secure development and execution of AI within the European Union. This plan emphasizes the significance of transparency, ethics, and collaboration in building trust and confidence in AI technologies.

The article presents the conceptual assumptions of the Smart City in its different phases of development - Smart City 1.0, Smart City 2.0, Smart City 3.0, Smart City 4.0, Smart City 5.0 and Smart Sustainable City. With reference to „Transforming our world: the 2030 Agenda for Sustainable Development” containing 17 Sustainable Development Goals, the article specifically presents the assumptions and practical solutions for SDG Goal 11. A critical analysis of the literature on the subject and a content analysis of the SDG reports revealed a juxtaposition of the diverse capabilities of smart technologies and their insufficient implementation to meet the Sustainable Development Goals in Smart Cities. The reality is not encouraging. The population of people living in slums is growing rapidly, social inequalities are widening, and there is a lack of access to convenient urban transport. There is chaotic urban sprawl, air pollution and insufficient public open spaces. Solutions to urban problems are often interventionist rather than preventive. The rational and sustainable use of modern technology can change this.

Numerous research studies have focused on the Simple Assembly Line Balancing Problem (SALBP). Although many of these studies have attempted to minimise the number of workstations for a given cycle time (SALBP-1) or min-imise the cycle time for a given number of workstations (SALBP-2), few have focused on the E-type of the SALBP, which is a general NP-hard problem. Therefore, a Systematic Literature Review (SLR) in this area is extremely important. The SALB-E problem involves scheduling a given set of tasks in an orderly sequence of workstations, where task precedence relations are satisfied, and finding the optimal pair of number of workstations and cycle time that maximises line efficiency. The aim of this systematic review was to examine existing research on SALB-E issues and predict future directions for studies on this topic. A systematic methodology was used to review papers published between 1995 and 2023, selected from the Scopus, ScienceDirect, and Google Scholar data-bases. The review showed that future studies should focus on multi- and mixed-model U-shaped and two-sided lines in the SALBP-E. In addition, it may be important to evaluate multiple objective functions rather than just a single one. To solve this problem, it is preferable to develop and refine genetic algorithms and investigate new approaches within the metaheuristic framework.