Abstract This study investigates the impact of human resource (HR) training on supply chain efficiency (SCE) among enterprises in Guiyang, China. A quantitative approach was used to analyse data from 316 respondents across ten key industrial sectors. Structural equation modelling (SEM) was applied to analyse the relationships between HR training, organisational culture, technological adaptability, and supply chain efficiency. The measurement model demonstrated adequate convergent validity (average variance extracted > 0.50) and internal consistency (composite reliability > 0.70). Discriminant validity was confirmed through the Fornell-Larcker criterion and HTMT ratio (< 0.85). The structural model revealed a positive influence of HR training on organisational culture (β = 0.664, p < 0.01), technological adaptability (β = 0.399, p < 0.01), and SCE made directly (β = 0.262, p < 0.05) and indirectly through organisational culture and technological adaptability (β = 0.272, p < 0.05). The model fit indices (χ²/df = 1.295; CFI = 0.984; TLI = 0.976; RMSEA = 0.031) confirmed its robustness. The findings suggest that HR training enhances SCE by improving employee skills, fostering technological integration, and cultivating an adaptive organisational culture. This research contributes to the theoretical understanding of HR development in supply chain management. It provides policymakers and business leaders with practical insights on leveraging workforce training as a strategic tool to enhance supply chain performance in regions such as Guiyang.

Abstract This paper examines the effects of foreign direct investments (FDIs) on economic development and the transfer of knowledge and technology (technology spillover) in developing countries, specifically focusing on the Republic of Serbia. The analysis is based on a comparative review of EU countries and Serbia in terms of statistical data on R&D activities and patent applications. The study synthesises existing research and proposes a methodological framework for future empirical studies. Findings indicate that technology spillover - horizontal and vertical - has not yet reached the desired levels in Serbia. Despite the presence of FDIs, the anticipated improvements in domestic innovation and technological advancement remain limited. This study contributes to the literature by contextualising technology spillover in Serbia and identifying gaps in its realisation. It also provides a foundation for future research on the mechanisms by which FDIs influence domestic enterprise performance and national economic development. The paper offers insights for policymakers and business leaders seeking to maximise the FDI benefits. It suggests the need for strategic policies to enhance technology transfer, support domestic R&D, and foster stronger linkages between foreign investors and local firms to accelerate economic development.

Abstract Modern work in sales & service is increasingly enhanced and supported by digital technologies. As a result, frontline employees’ digital competencies are becoming a key success factor for sales & service work. Nevertheless, especially with regards to professional work, there is still a lack of knowledge about how to measure digital competencies. So far, specific empirical contribution focussing on professional digital work environments being increasingly knowledge-intense, collaborative, and virtualized are still very rare. In this article we seek to make a substantial contribution in that area of research. Based on the state-of-the art literature about digital competence among employees in professional work this article is one of the very few that introduces an empirically evaluated scale of digital competence based on a sample size of N=1,283. We suggest a context-related set of five dimensions of digital competence named (1) effective usage of technologies and tools, (2) farsighted & critical information handling, (3) sustained cooperation & communication, (4) integrative knowledge generation, and (5) co-creative problem solving. Evaluation of these five dimensions is conducted with the help of technostress, virtualization of work, space-time flexibility at work and availability for work-related issues. Finally, we present a critical reflection about the scale’s five dimensions.

Abstract In modern production systems, ensuring high product quality while minimising risk is a critical challenge. Traditional quality assessment methods often rely on expert judgment or complex models, which may introduce subjectivity or require large datasets. This study aims to develop a universal methodology for assessing product quality risks using a mathematically grounded approach that eliminates the need for expert-based evaluations and can be easily implemented in various industrial contexts. A qualimetric method based on nonlinear mathematical dependence using the error function “erf” is proposed. The method transforms measured quality indicators into a dimensionless scale and derives functionally dependent statistics under the assumption of a uniform distribution. The model is validated through analytical derivations and numerical experiments on piston components in precision mechanical engineering. A new mathematical model was established to calculate the probability density function of transformed quality indicators. The methodology enables the estimation of the probability that a quality indicator will fall within a risky range near tolerance limits. Numerical experiments confirmed the validity of the model, demonstrating its applicability to real-world production scenarios and its alignment with known principles of qualimetry. The proposed method provides a universal, objective, and practical tool for risk-based quality assessment. It can be applied across different industries, integrated into existing quality management systems, and used to support decision-making in production control. Future research should expand the model to accommodate nonuniform distributions and explore its integration with real-time quality monitoring systems.

Abstract The paper introduces a new multi-factor critical chain buffer estimation model and designs a dynamic monitoring method based on the project elements. A literature analysis determined a research gap and a research problem. It was found that the existing methods offer scarce collaborative studies on buffer setting and monitoring and insufficient research on buffer setting considering project economic indicators. However, these topics are often given priority consideration in practical engineering applications. Therefore, the study proposes a multi-factor critical chain buffer setting and its dynamic monitoring method. The planning stage analyses the impact of income, resources, and probability of success on buffer size setting and defines the calculation model of capacity constraint buffer. The execution stage dynamically sets buffer monitoring points according to the progress of project implementation, monitors the remaining buffer amount at the completion of each activity on the critical chain, and takes corresponding actions to ensure that the progress is controllable. The method was applied in a multi-project of a Chinese software enterprise. To further verify the effectiveness of this research, the method is compared with the traditional static buffer monitoring method (TBMM) and the relative buffer monitoring method (RBMM), and the construction period of the real project is simulated through the computer program for analysis. Results show that the research method can reduce unreasonable buffer settings, enhance the robustness of a buffer against complex environments, and reduce the probability of false warnings in the monitoring process.

Abstract This study examines the pivotal role of the logistics sector in corporations, particularly those with diverse product portfolios. It focuses on the time-intensive “picking” process, driven by various products and material handling requirements for order fulfilment. The research presents a methodology that combines distribution centre modelling for simulation with an optimisation algorithm to enhance operational efficiency. The goal is to determine an optimal route for product retrieval, minimising employee travel distances, using the simulated annealing algorithm. The results showcase a significant 7 % reduction in employee travel distance during collection. This research is relevant to academia and practical applications as it presents an opportunity to reduce operational costs in distribution centres, enhance the efficiency of picking operations, and improve the competitiveness of companies. Furthermore, it contributes to operations research by addressing a complex problem with significant practical implications using a rather unused method to solve this problem of picking operations. The approach is empirically applied in a prominent Brazilian beverage company. This methodology proves valuable for optimising logistics operations in various industrial contexts, highlighting its practical applicability.

Abstract 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.

Abstract This article provides a systematic review of innovations in smart fruit-growing. The research aims to highlight the technological gap and define the optimal studies in the near future moving toward smart fruit-growing based on a systematic review of literature for the period 2021–2022. The research object is the technological gap until the smart fruit-growing. The research question of the systematic review was related to understanding the current application of vehicles, IoT, satellites, artificial intelligence, and digital twins, as well as active studies in these directions. The authors used the PRISMA 2020 approach to select and synthesise the relevant literature. The Scopus database was applied as an information source for the systematic review, completed from 10 May to 14 August 2022. Forty-three scientific articles were included in the study. As a result, the technology gap analysis was completed to highlight the current studies and the research trends in the near future moving toward smart fruit-growing. The proposed material will be useful background information for leaders and researchers working in smart agriculture and horticulture to make their strategic decisions considering future challenges and to optimise orchard management or study directions. Considering the current challenges, authors advise paying attention to decision-making, expert, and recommendation systems through the digital twin paradigm. This study will help the scientific community plan future studies optimising research to accelerate the transfer to new smart fruit-growing technologies as it is not sufficient to develop an innovation, but it must be done at the appropriate time.

Abstract Risk, as an effect of uncertainty, is associated with every human activity. Like any other industry, construction companies are eager to reduce the uncertainty of reluctant events. A well-planned risk communication system could contribute to the success of a construction project. A proper announcement protocol could be a mitigating lever for identified or unidentified risks during planning and monitoring processes. This research aims to present a risk communication management system (RCMS) for construction companies involved in large projects. The proposed model includes a step-by-step communication procedure considering the authority level within the organisational hierarchical structure. The model aims to remove the ambiguity of risk communications during the construction process under uncertain conditions. It leaves no or little room for the emergence of unplanned risks. The proposed communication structure has been implemented in GRC cladding construction projects, and the risk communication time and response have been significantly improved.

Abstract The paper aims to identify how Industry 4.0 technologies affect the quality and speed of the managers’ decision-making process across the different stages of the value chain, based on the example of the manufacturing sector. The paper adopts qualitative research, based on nine in-depth interviews with key informants, to capture senior executives’ experiences with implementing Industry 4.0 technologies in their organisations. The research is focused on three manufacturing industries: the automotive, food and furniture industries. The research shows that depending on the stage of the value chain, different Industry 4.0 technologies are more suitable for the support of managers’ decisions. Various Industry 4.0 technologies support decision-making at different stages of the manufacturing value chain. In the Design stage, 3D printing and scanning technologies play a crucial role. In the case of Inbound Logistics, robotisation, automation, Big Data analysis, and Business Intelligence are most useful. During the Manufacturing stage, robotisation, automation, 3D printing, scanning, Business Intelligence, cloud computing, and machine-to-machine (M2M) integration enable quick decision-making and speed up production. Sensors and the Internet of Things (IoT) optimise distribution in the Outbound Logistics stage. And finally, Business Intelligence supports decisions within the Sales and Marketing stage. It is also the most versatile technology among all particular stages. The paper provides empirical evidence on the Industry 4.0 technology support in decision-making at different stages of the manufacturing value chain, which leads to more effective value chain management, ensuring faster and more accurate decisions at each value-chain stage. When using properly selected Industry 4.0 technologies, managers can optimise their production processes, reduce costs, avoid errors and improve customer satisfaction. Simultaneously, Industry 4.0 technologies facilitate predictive analytics to forecast and anticipate future demand, quality issues, and potential risks. This knowledge allows organisations to make better decisions and take proactive actions to prevent problems.