Systems, Volume 12, Issue 1 (January 2024) – 36 articles

The platform owner promotes the transaction between independent sellers and consumers, while entering the marketplace of independent sellers to compete with them for consumers. Faced with the threat of platform encroachment, independent sellers establish their own competitive advantages through ex ante category quality selection and ex post product differentiation. This study discusses how independent sellers should determine product positioning (including vertical and horizontal dimensions) in the face of platform category encroachment. We establish a game model and determine the best strategy. In addition, we develop a multi-agent model to reach conclusions for more complex market situations. We show that when the consumer’s platform preference is low, the independent seller is willing to locate in the high-end product market; otherwise, the independent seller is willing to locate in the low-end product market. In a competitive environment, when consumers’ ideal preferences are concentrated, the independent seller vertically positions in the low-end product market and horizontally positions close to the concentrated area of consumers’ ideal preferences. Similarly, the platform owner is more likely to encroach on the low-end product market. However, the independent seller positions in the high-end product market with greater horizontal differentiation, and the platform owner’s motivation to encroach is weakened. Full article

Pricing decisions for construction and demolition waste recycling are severely hampered by consumer uncertainty in assessing the value of recycled building materials. This paper uses a construction and demolition waste (CDW) recycling utilization model that consists of a building materials manufacturer and a building materials remanufacturer and compares both the prices and the profits under different carbon tax scenarios, i.e., consumer risk-averse and risk-neutral scenarios. The main conclusions are as follows. (1) The optimal price of traditional products is always negatively correlated with consumer risk aversion. Unlike traditional products, the optimal price of recycled building materials is negatively related to the degree of consumer risk aversion in the case of a low carbon tax; the opposite conclusion is obtained in the case of a high carbon tax. (2) When the abatement cost coefficient is below the threshold and the carbon tax is low, the profits of the building materials manufacturer and remanufacturer show a U-shaped trend with consumer risk aversion; in the case of a high carbon tax, the profits of the two enterprises are positively correlated with consumer risk aversion. In addition, when the abatement cost coefficient is above the threshold, there is an interval in which the profits of the building materials manufacturer are positively correlated with consumer risk aversion in the case in which the carbon tax satisfies this interval. In all the other cases, there is a U-shaped trend in profits and consumer risk aversion levels for both the building materials manufacturer and the remanufacturer. Full article

This research addresses the strategic issue of why key decision-makers fail to foresee potential extreme ‘black swan’ events. Following a review of the literature, a conceptual framework is developed that identifies two types of organisational blindness that are reflected in Tetlock’s hedgehog cognitive thinking style, being the oversimplification of uncertainty (e.g., inductive biases) and an unquestioned, top-down, reference narrative. This framework is tested using a case study approach and qualitative analysis of secondary data sources available from the Royal Commission of Inquiry and other published reports following the 2010 methane explosion at the Pike River Coal Ltd.’s mine (Pike) in New Zealand, that killed 29 miners and caused the loss of all funds invested. The results indicate that the combined effect of both blindnesses meant that Pike’s collective intelligence was limited, and for the three key decision-makers at the Pike River mine, some type of extreme ‘black swan’ event was apparently inevitable. This research provides theoretical and practical contributions to the analysis of business and public policy decision-making under uncertainty. Full article

The e-books industry is mature, and audiobooks are becoming increasingly popular. More and more publishers are coming to realize that audiobooks could be a potential revenue driver and intend to release audiobooks. Considering that there is a certain substitutability between e-books and audiobooks, publishers need to decide how to release a book in its audible version and its e-book version into the market. In this paper, we incorporate the discount factor and the consumers’ acceptance level for audiobooks into the consumer utility by dividing consumers into two types, high-value type and low-value type, and construct two different release models: releasing the audiobook and the e-book simultaneously and releasing the audiobook after the e-book. Using an optimization tool, we investigate pricing strategies of a monopolistic publisher under two different release models. By comparing the theoretical results of the two models, we find that when the consumers’ patience exceeds a certain threshold, releasing a book in its audible version after its e-book version is better for the publisher, and the publisher should adopt a skimming (refers to decreasing markups over time) pricing strategy for the e-book in this case. Further, the publisher should set a higher price for the audiobook than the e-book, whether or not they release the audiobook after the e-book. In addition, we conduct a numerical analysis to investigate how the discount factor, the percentage of high-value consumers, and the high-value consumers’ acceptance level for audiobooks affect the consumer surplus and the social welfare. This study offers publishers some managerial insights into the complex issues involving pricing and release strategies. Full article

Supply chain coordination has been a research hot spot in supply chain management. This paper constructs a secondary supply chain system. Taking the abatement of the bullwhip effect and the double marginal effect as the coordination objective, a simulation study of supply chain decision coordination was conducted using system dynamics. First, by controlling the lead time, it was found that in the decentralized decision-making model, the profit of the supplier and the whole supply chain increases with the shortening of the lead time, and vice versa for the retailer. In the centralized decision-making model with the addition of information sharing and contract, it was found that the retailer’s profit is consistent with the trend of the supplier and the supply chain as a whole, and the supplier’s profit is lower than that of decentralized decision making in the pre-cooperation period. In addition, it is also found that adjusting the contract parameters can effectively improve the situation. Finally, the above models were analyzed for supply chain coordination decisions based on two scenarios: “cooperative stability” or “balance of effects”. Full article

With the increasing complexity and frequency of interactions among a large number of heterogeneous nodes within a combat system of systems (SoS), evaluating the capability of the SoS to withstand external attacks and interferences has become an increasingly challenging and urgent issue. However, the complexity of a combat SoS often brings about difficulties in quantitative analysis. This paper proposes a method to assess the resilience of a combat SoS. Firstly, a network model of a combat SoS is constructed, taking into account multi-functional composite nodes. Secondly, the combat capability model of the combat SoS is built based on the capabilities of the kill chains and kill networks. Lastly, an approach is proposed to calculate the combat capability of the system based on the network’s two-terminal connectivity. Moreover, based on the SoS’s combat capability, the resilience is analyzed from the dimensions of anti-destruction, survival, and recovery. The simulation experiments show that, compared to other methods, the method in this paper for calculating the combat capability of the combat SoS does not depend on the number of kill chains and aligns with the combat processes and actual patterns. Additionally, the resilience measurement method can effectively analyze its capability to cope with external interferences. Full article

The transformation of the government into a digital entity is imperative, serving not only as a catalyst for the modernization of China’s governance system and capacity but also as a cornerstone for advancing the digital economy and the establishment of a digital China. This paper presents a multi-level analytical framework designed to assess the digital transformation performance of local governments. Utilizing a dataset comprising macro-regional and micro-individual data from Hubei province, we conduct an extensive analysis to examine the underlying mechanisms that influence the digital transformation performance of local governments and employ the hierarchical linear model (HLM) as the primary analytical instrument. The results of our analysis show that individual-level government–citizen interactions, government image, and district-level department collaborative capacities exert substantial and positive influences on the digital transformation performance of local governments. Furthermore, it is worth noting that department collaborative capacity plays a significant and positive moderating role in the relationship between government image and the digital transformation performance of local governments. These findings not only offer valuable insights for optimizing policy formulation but also contribute to a more comprehensive understanding of the mechanisms underlying the digital transformation performance of local governments. Full article

This article argues that complexity scientists have been searching for a universal complexity in the form of a “theory of everything” since some important theoretical breakthroughs such as Bertalanffy’s general systems theory, Wiener’s cybernetics, chaos theory, synergetics, self-organization, self-organized criticality and complex adaptive systems, which brought the study of complex systems into mainstream science. In this respect, much attention has been paid to the importance of a “reductionist complexity science” or a “reductionist theory of everything”. Alternatively, many scholars strongly argue for a holistic or emergentist “theory of everything”. The unifying characteristic of both attempts to account for complexity is an insistence on one robust explanatory framework to describe almost all natural and socio-technical phenomena. Nevertheless, researchers need to understand the conceptual historical background of “complexity science” in order to understand these longstanding efforts to develop a single all-inclusive theory. In this theoretical overview, I address this underappreciated problem and argue that both accounts of the “theory of everything” seem problematic, as they do not seem to be able to capture the whole of reality. This realization could mean that the idea of a single omnipotent theory falls flat. However, the prospects for a “holistic theory of everything” are much better than a “reductionist theory of everything”. Nonetheless, various forms of contemporary systems thinking and conceptual tools could make the path to the “theory of everything” much more accessible. These new advances in thinking about complexity, such as “Bohr’s complementarity”, Morin’s Complex thinking, and Cabrera’s DSRP theory, might allow the theorists to abandon the EITHER/OR logical operators and start thinking about BOTH/AND operators to seek reconciliation between reductionism and holism, which might lead them to a new “theory of everything”. Full article

Recruitment is a fundamental aspect of Human Resource Management to drive organizational performance. Traditional recruitment processes, with manual stages, are time-consuming and inefficient. Artificial Intelligence (AI), which demonstrates its potential in various sectors such as healthcare, education, and notable cases of ChatGPT, is currently reshaping recruitment by automating tasks to improve efficiency. However, in Thailand, where there is a growing demand for talents, the application of AI in recruitment remains relatively limited. This study focuses on human resources (HR) and recruitment professionals in Thailand, aiming to understand their perspectives on the integration of AI in recruitment. It utilized the Unified Theory for Acceptance and Use of Technology (UTAUT) model, customized to suit the specific requirements of Thailand recruitment practices. The study explores the factors influencing users’ intention to adopt AI in recruitment. Survey questionnaire items were created based on prior literature and refined with insights from HR and recruitment experts to ensure applicability in the context of recruitment in Thailand. A survey involving 364 HR and recruiting professionals in the Bangkok metropolitan area supplied comprehensive responses. The study reveals that several factors, including perceived value, perceived autonomy, effort expectancy, and facilitating conditions, significantly impact the intention to adopt AI for recruitment. While social influence and trust in AI technology do not have a direct influence on intention, social influence directly affects perceived value. Trust in AI technology positively influences Effort Expectancy. This study provides valuable benefits for HR and recruitment professionals, organizations, and AI developers by offering insights into AI adoption and sustainability, enhancing recruitment processes and promoting the effective use of AI tools in this sector. Full article

Individual model verification is a common practice that increases the quality of design on the left side of the Vee model, often before costly builds and prototypes are implemented. However, verification that spans multiple models at higher levels of abstraction (e.g., subsystem, system, mission) is a complicated endeavor due to the federated nature of the data. This paper presents a tool-agnostic approach to higher-level verification tasks that incorporates tools from Semantic Web Technologies (SWTs) and graph theory more generally to enable a three-pronged verification approach to connected data. The methods presented herein use existing SWTs to characterize a verification approach using ontology-aligned data from both an open-world and closed-world perspective. General graph-based algorithms are then introduced to further explore structural aspects of portions of the graph. This verification approach enables a robust model-based verification on the left side of the Vee model to reduce risk and increase the visibility of the design and analysis work being performed by multidisciplinary teams. Full article

From the first to the fourth industrial revolutions (4IR) or Industry 4.0 (i4.0), the manufacturing sector has always been at the forefront of innovation and digital technology adoption. However, 4IR or i4.0 comes with diverse and integrated technologies that tend to sweep off all the old orders. This study undertakes a science mapping of research on the role of virtual reality simulation (VRSIM) in manufacturing in the 4IR, which reveals several roles and benefits. The analysis of the conceptual structure of relevant literature highlights the contexts, applications, and relevance of VRSIM in the i4.0 era, including its potent role in predictive modeling and simulation, digital twin and predictive maintenance, additive manufacturing and 3D printing, and virtual manufacturing and immersive virtual digital factory simulation. VRSIM also offers a realistic virtual environment for mapping human–robot collaboration in different manufacturing environments, such as aircraft and automotive assembly lines, evaluating processes, training factory workers on safety, and assessing workers’ ergonomics in digital production and operations. VRSIM in manufacturing offers active research activities, with increasing literature publications and impacts attracting core sources in industrial engineering, manufacturing systems, production and operations, and information technology. Full article

Both executive corruption and corporate innovation are important factors affecting corporate development. This paper explores the impact of executive corruption on corporate innovation and examines the mechanism of their effects from the perspective of financing constraints. It is found that executive corruption significantly inhibits corporate innovation in general. In addition, financing constraints act as a mediator between executive corruption and corporate innovation, i.e., executive corruption exacerbates the financing constraints faced by firms and affects the access to and allocation of corporate resources, thus leading to a decrease in corporate innovation inputs and outputs. Further, the inhibitory effect of executive corruption on firm innovation is more pronounced in firms with low quality internal controls, strong professional background of executives, low quality external audit, low shareholding of institutional investors, strong political affiliation, and state-owned enterprises. Full article

The management of product quality is a crucial process in factory manufacturing. However, this approach still has some limitations, e.g., depending on the expertise of the engineer in evaluating products and being time consuming. Various approaches using deep learning in automatic defect detection and classification during production have been introduced to overcome these limitations. In this paper, we study applying different deep learning approaches and computer vision methods to detect scratches on the surface of microfasteners used in rechargeable batteries. Furthermore, we introduce an architecture with statistical quality control (SQC) to continuously improve the efficiency and accuracy of the product quality. The proposed architecture takes advantage of the capability of deep learning approaches, computer vision techniques, and SQC to automate the defect detection process and quality improvement. The proposed approach was evaluated using a real dataset comprising 1150 microfastener surface images obtained from a factory in Korea. In the study, we compared the direct and indirect prediction methods for predicting the scratches on the surface of the microfasteners and achieved the best accuracy of 0.91 with the indirect prediction approach. Notably, the indirect prediction method was more efficient than the traditional one. Furthermore, using control charts in SQC to analyze predicted defects in the production process helped operators understand the efficiency of the production line and make appropriate decisions in the manufacturing process, hence improving product quality management. Full article

This paper introduces a hybrid framework for port container throughput forecasting, which is essential in global trade and transportation systems. It uses a multidisciplinary method that combines artificial intelligence, link prediction, and complex networks. To better grasp the interconnection and dynamics of port operations, time series data are first transformed using complex network theory into a network structure. The framework applies 13 similarity metrics, encompassing various aspects of network structural similarity, to form a feature set representing the complex port operation network. The most effective features are selected using the maximum relevance minimum redundancy (mRMR) method, adhering to systems theory’s efficiency principles. These features are processed through SVM, DNN, and LSTM models for link prediction, which is crucial for forecasting in port logistics. Finally, the methodology concludes with regression analysis to obtain container throughput forecasts, which is a key metric in port systems management. Case studies of Shanghai Port and Shenzhen Port validate the framework’s effectiveness, demonstrating a significant improvement in forecasting accuracy over the baseline models. This study contributes to systems analysis by showcasing a hybrid, AI-enhanced approach for managing and forecasting critical aspects of maritime trade systems. Full article

Due to persistent technological impacts on ecological efficiency (eco-efficiency) and variations in economic power and resource endowments among regions, considering regional and temporal heterogeneity becomes imperative. Ecosystems, often divided into economic production and environmental governance stages, necessitate a holistic assessment incorporating regional, temporal heterogeneity and stage distinctions. To address potential issues of a technology gap ratio (TGR) exceeding 1 within a two-stage network structure with dual heterogeneity, we introduce a segmented projection three-layer meta-frontier analysis method. In empirical study, we systematically examined eco-efficiency, emissions inefficiency and technology gaps across management, regional and temporal dimensions in 30 Chinese provinces from 2016 to 2020. Findings reveal disparities in management eco-efficiency, with the central provinces outperforming the east. Regional differences indicate advanced technology in the east, contributing to superior eco-efficiency. Temporal analysis highlights the positive role of scientific and technological development. Emissions inefficiency improvements are noted, necessitating attention toward management and regional technology levels. Eastern provinces exhibit superior emissions efficiency, emphasizing the role of regional and technological development. Recommendations include prioritizing environmental governance, strengthening regional collaborations and implementing policies to bridge technology gaps. Full article

Colleges and universities play a crucial role in fostering innovation, making it essential to explore effective strategies for promoting innovation at the institutional policy level. This paper focuses on the establishment of intellectual property model cities as a starting point and conducts an empirical analysis using innovation data from 234 cities and 942 colleges and universities between 2007 and 2017. By constructing a multi-temporal double-difference model, this study reveals that the establishment of intellectual property model cities effectively fosters innovation in colleges and universities. Further analysis demonstrates that this promotional effect is particularly significant in the western region, key cities, and key colleges and universities, as well as in the fields of invention and utility model patents. These conclusions withstand a series of robustness tests, confirming their validity. This study reveals that the national intellectual property pilot city policy has a significant influence on university innovation. It achieves this by encouraging investment in research and development and enhancing collaboration in innovation. The findings of this study provide important policy suggestions for maximizing the innovation potential of the intellectual property model city policy. This, in turn, can contribute to economic transformation, upgrading, and the promotion of innovation development in China. Full article

The value stream method, a key tool in industry to analyze and visualize value streams in production, aims to holistically optimize process steps, reduce waste, and achieve continuous material flow. However, this method primarily relies on data from a single on-site inspection, which is subjective and represents just a snapshot of the process. This limitation can lead to uncertainty and potentially incorrect decisions, especially in industries producing customer-specific products. The increasing digitization in production offers a solution to this limitation by supporting the method through data provision. The concept of the digital shadow emerges as a key tool that systematically captures, processes, and integrates necessary data into a model to enhance traditional value stream mapping. This addresses the method’s shortcomings, especially in heterogeneous IT landscapes and complex value streams. To effectively implement the digital shadow this study identifies concepts of digital shadows and their key components and evaluates them for their relevance in industrial environments using an expert study. Based on the results, a design model is defined. This model entails guidelines to support companies with the practical implementation of the digital shadow of a value stream. Lastly, the model is evaluated on a realistic value stream in a learning factory. Full article

The global economy has been profoundly affected by the COVID-19 pandemic. This impact is particularly evident in the restaurant industry, where restaurant traffic has dropped significantly, leading to a decline in revenue. In response to the impact of the pandemic, non-contact services, such as overseas delivery and door-to-door delivery, have been implemented to reduce interpersonal contact and minimize the spread of the virus. Contactless service not only provides consumers with more choices and convenience but is also an important means of livelihood for restaurant service staff during the pandemic. This study takes the Taiwanese chain restaurant Kura Sushi as an example to explore the impact of service contacts on authenticity consumption and experience value in the context of non-contact services. A total of 318 valid responses to a questionnaire were collected and analyzed using IBM SPSS 25.0 and IBM AMOS 25.0 software. This study made the following findings: (1) service staff performance has a significant positive impact on authenticity perception; (2) the physical restaurant environment has a positive impact on consumers’ perceptions of authenticity; (3) active interactions with other customers significantly enhance the sense of reality; (4) experience values significantly promote real consumption; and (5) experience values also significantly affect consumer satisfaction. Full article

Collaborative Model-based Systems Engineering between companies is becoming increasingly important. The utilization of the modeling possibilities of the standard language SysML v2 and the multilateral data exchange via Dataspaces open new possibilities for efficient collaboration. Based on systemic approaches, a modeling concept for decomposing the system into sub-systems is developed as a basis for the exchange. In addition, based on the analysis of collaboration processes in the context of Systems Engineering, an architectural approach with a SysML editor and Dataspace for the exchange is elaborated. The architecture is implemented on the basis of open-source solutions. The investigations are based on an application example from precision engineering. The potential and challenges are discussed. Full article

This paper addresses the critical issue of managing biomass parks, a key component in the shift towards sustainable energy sources. The research problem centers on optimizing the management of these parks to enhance production and economic viability. Our aim was to bridge the gap in current research by developing and applying mathematical models tailored for biomass park management. The study commenced by constructing a basic model based on assumptions such as uniform biomass and steady input rates. Progressing from this initial model, we explored sophisticated control strategies, including Pontryagin’s maximum principle and dynamic programming, and employed numerical methods to tackle the nonlinearities and complexities inherent in biomass management. Our approach’s scope extended to predicting and managing biomass flow, highlighting each method’s distinct advantages. The simple model laid the groundwork for understanding, while optimal control techniques revealed the system’s intricate dynamics. The numerical methods provided practical solutions to complex equations. We found that while each method is beneficial on its own, their combined use can significantly improve decision-making in biomass park management. This research emphasizes the importance of aligning the chosen method with specific operational challenges and desired outcomes for optimal efficacy, offering both theoretical insights and practical applications in the field of renewable energy management. Full article

The burden of type 2 diabetes mellitus (T2DM) and hypertension (HTN) has increased worldwide in recent decades, particularly in low- and middle-income countries (LMICs). In these countries, health systems often struggle to provide effective health care services for the management of chronic conditions. We have developed a study protocol with the aim of conducting a realist review to delve into the complexities behind the management of T2DM and HTN in LMICs. First, we have developed a causal loop diagram (CLD) serving as the initial program theory to represent the health system drivers associated with the effective (or ineffective) management of T2DM and HTN. Next, we will search, select, appraise, extract and analyze the relevant evidence. This evidence will be used to refine and extend the initial program theory to transform it into a middle-range program theory. This will then be verified through Group Model Building (GMB) sessions. The evidence will be summarized applying RAMESES (Realist And MEta-narrative Evidence Syntheses: Evolving Standards). In combining a systems thinking approach with a realist approach to program evaluation, we aim to unravel the mechanisms that govern the management of T2DM and HTN, and the relation between health system-related factors, which lead to outcomes, in different contexts. Full article

Education is a complex system with implications for educational policy and management. Education systems that are more comprehensive generate more equal outcomes, fostering access to opportunities for all children. On the other hand, systems with early selection and tracking are more stratified and register higher inequalities in educational outcomes. Educational inequalities imply unequal access to education and, subsequently, career opportunities. The present study employs classification techniques, such as decision trees, in order to highlight lines of stratification and inequality in the upper secondary education system in Romania, focusing on the selection of students in general or vocational programs. Our results show that the education of parents and area of residence are factors that influence the stratification of students in the Romanian secondary education system, and the selection process contributes to the reproduction of social inequalities. The conclusions of this study are consistent with the cultural capital theory in education. Policy and strategic management implications are discussed in light of our results. Full article

Army installation commanders need timely weather information to make installation closure decisions before or during adverse weather events (e.g., hail, thunderstorms, snow, and floods). We worked with the military installation in Fort Carson, CO, and used their Weather Warning, Watch, and Advisory (WWA) criteria list to establish the foundation for our algorithm. We divided the Colorado Springs area into 2300 grids (2.5 square kilometers areas) and grouped the grids into ten microclimates, geographically and meteorologically unique regions, per pre-defined microclimate regions provided by the Fort Carson Air Force Staff Weather Officers (SWOs). Our algorithm classifies each weather event in the WWA list using the National Weather Service’s and National Digital Forecast Database’s data. Our algorithm assigns each event a criticality level: none, advisory, watch, or warning. The traffic network data highlight the importance of each road segment for travel to and from Fort Carson. The algorithm also uses traffic network data to assign weight to each grid, which enables the aggregation to the region and installation levels. We developed a weather dashboard in ArcGIS Pro to verify our algorithm and visualize the forecasted warnings for the grids and regions that are or may be affected by weather events. Full article

Systems engineering (SE) solves the most complex problems, bringing together societal issues, theoretical engineering, and the transformation of theory into products and services to better humanity and reduce suffering. In industry, the effort to transform theoretical concepts into practical solutions begins with the product life cycle concept stage, where systems engineering estimates and derives technologies, costs, and schedules. It is crucial to have a successful concept stage as today’s industries focus on producing the most capable technologies at an affordable cost and faster time to market than ever before. The research of this paper utilizes a transdisciplinary SE process model in the concept stage to develop and propose training for early-in-career engineers, effectively bridging the gap from university learning to industry practice. With a focus on the concept stage of the product life cycle and the industry’s demands of expeditiously proposing complex technical solutions, the paper aims to create an efficient learning program. The main objective of this research is to create a learning program to bring up-to-speed early-in-career engineers using a transdisciplinary SE process model, with six key components: (1) disciplinary convergence—creating a collective impact; (2) TD collaboration; (3) collective intelligence; (4) TD research integration; (5) TD engineering tools; and (6) analysis and TD assessment. The research will then conclude with a case study piloting the TD learning program and analyzing its effectiveness, ultimately aiming to enhance early-in-career engineers’ skills in proposing technical solutions that meet customer demands and drive business profitability. Full article

Innovation systems consist of different organisations from the quadruple helix, as well as the interactions and linkages between them. Smart technologies and ICT play a key role in the efficiency of systems. At the same time, regional scale is considered crucial for studying innovation in systems. However, the lack of many important data at the regional level compounds the efforts to study them. The paper proposes a novel methodological approach to the regionalisation of national-level indicators in order to address this issue. This is based on the model fit approach, using regressions to “regionalise” national-level indicators based on similar indicators that are available. The approach is tested on the data for Greek NUTS 2 regions and produces regional-level estimates for four innovation indicators, based on four available indicators that are found to be strongly correlated to them. However, the same approach can be used for any EU country or the whole of the EU. The results, their prospects for future research, and potential applications are considered. Overall, the availability of regional-level indicators is considered crucial for the formulation of impactful development policies. Full article

The rapid development of digital technology has injected new vitality into green technological innovation within manufacturing enterprises. Proper application of digital technology during the innovation process can propel global sustainable development. Using Chinese publicly traded manufacturing firms as a sample, this study employed a constructed digital technology innovation network and OLS models to unveil the mechanisms through which digital technology application affects green technological innovation. This research reveals a significant positive impact of the breadth and depth of digital technology applications on companies’ green technological innovation performance. Green human resource allocation serves as an intermediary in this relationship. Furthermore, the embeddedness and structural embeddedness of the digital technology innovation network play a significantly positive moderating role in the relationship between digital technology applications and green human resource allocation. This discovery provides a theoretical foundation for how companies can harness digital technology to promote green innovation within China’s digital strategy. It aids manufacturing enterprises in optimizing digital technology applications, improving green human resource allocation, and facilitating the development of digital technology innovation networks, advancing more sustainable development and contributing to global environmental goals. Full article

IT projects are becoming increasingly complex due to rapidly advancing technologies, the need to tackle more difficult problems, and the involvement of a larger variety of experts with different backgrounds and experiences from different countries and cultures. It is also common for these teams to often work remotely in virtual settings. In this context, besides conflicts between IT project team members, cross-functional and cross-hierarchical organizational conflicts might emerge as well. These conflicts can vary in terms of their origin, nature, and intensity. This paper is a qualitative study focused on understanding interpersonal communication-based conflicts in multicultural and multidisciplinary IT project teams. The purpose is to find a common approach that can mitigate and eventually resolve these conflicts, aiming to promote shared knowledge and ultimately reduce the gap in understanding and the likelihood of conflicts. Both secondary research (a literature survey) and primary research (involving experienced managers and experts from project teams in the Romanian IT industry) were conducted in order to reach the objectives, besides sets of lessons learned and recommendations, to develop a framework for systematic conflict analysis and to propose a practice for a transcultural framework of common team vocabulary. To achieve these, a number of conflicts were investigated in IT project teams and corresponding cases. Based on the research findings, the authors concluded that a more formal approach is needed to address the problem of conflicts. From a theoretical standpoint, this paper suggests the concept of management diversity and provides a typology of organizational conflicts. Nevertheless, the framework for systematic analysis of conflict typology (FACT) and the framework of common team vocabulary in the multicultural environment of IT organizational project teams, as well as the sets of lessons learned and recommendations, might be useful and inspiring for both scholars and managers, not only in the IT sector. Full article

With the implementation of AGV technology and automated scheduling, storage and retrieval systems have become widely utilized in warehouse management. However, due to the use of unidirectional channels, AGV movement is restricted, and detours may occur frequently. Additionally, as the number of AGVs increases, deadlocks can arise, which lead to delays in order packaging and a decrease in overall warehouse performance. Hence, this paper proposes a dynamic scheduling method for task assignment and route optimization of AGVs to prevent collisions. The routing optimization method is based on an improved A* algorithm, which takes into account the dynamic map as input. Moreover, this paper investigates highly complex collision scenarios in bidirectional channels. Through simulation experiments, it is evident that scheduling methods based on bidirectional channels offer a clear advantage in terms of efficiency compared to those based on unidirectional channels. Full article

Complex organisations require coherence to achieve adaptive goals through agency. This paper introduces Mindset Agency Theory (MAT), a metatheoretical framework designed for modelling and diagnosing agency within culturally diverse populations. MAT, a cybernetic multi-ontology framework, delineates five formative traits defining agency character. Its cognitive style trait (with bipolar values of Patterning–Dramatising) elucidates how agencies acquire information. Examining diverse agencies requires an appreciation of the social relationships that exist there, but MAT is currently devoid of this capability. Using the configuration approach to enable the integration of Tönnies’ social organisation theory into MAT, social relationships can be suitably explored, thus enhancing its capacity to investigate agency coherence. Tönnies’ theory of social organisation (with bipolar values of Gemeinschaft-Gesellschaft) that frames inter-agent interactions is configured within MAT. This integration births a new formative trait, pairing cognitive style with social organisation, and is thus capable of indicating the likelihood of operative coherence. Configuration is applied by relating propositional attributes of a holding metatheory framework such as MAT, with an entry theory such as Tönnies’ social organisation theory as determined from the literature. The elaborated MAT serves as a diagnostic tool, linking trait instabilities with agency pathologies that deliver dysfunction. A subsequent paper will apply this framework to ASEAN, a regional intergovernmental organisation addressing cultural diversity issues. The study aims to evaluate ASEAN’s mindset and diagnose its pathologies, such as narcissism and paradoxical behaviour. Full article

Visualization systems play a crucial role in industry, education, and research domains by offering valuable insights and enhancing decision making. These systems enable the representation of complex workflows and data in a visually intuitive manner, facilitating better understanding, analysis, and communication of information. This paper explores the potential of augmented reality (AR) visualization systems that enhance multi-modal perception and interaction for complex decision making. The proposed system combines the physicality and intuitiveness of the real world with the immersive and interactive capabilities of AR systems. By integrating physical objects and virtual elements, users can engage in natural and intuitive interactions, leveraging multiple sensory modalities. Specifically, the system incorporates vision, touch, eye-tracking, and sound as multi-modal interaction methods to further improve the user experience. This multi-modal nature enables users to perceive and interact in a more holistic and immersive manner. The software and hardware engineering of the proposed system are elaborated in detail, and the system’s architecture and preliminary function testing results are also included in the manuscript. The findings aim to aid visualization system designers, researchers, and practitioners in exploring and harnessing the capabilities of this integrated approach, ultimately leading to more engaging and immersive user experiences in various application domains. Full article