Systems

15 pages, 3662 KiB

Open AccessArticle

Applying MBSE to Optimize Satellite and Payload Interfaces in Early Mission Phases

by Shayna Slobin, Zizung Yoon and Susanne Fugger

Systems 2024, 12(8), 310; https://doi.org/10.3390/systems12080310 - 19 Aug 2024

The use of model-based systems engineering (MBSE) has been increasingly explored recently in industries that require multi-discipline engineering coordination. In the European space industry, applying MBSE for the engineering of space systems has been an ongoing undertaking on many missions. In the following [...] Read more.

The use of model-based systems engineering (MBSE) has been increasingly explored recently in industries that require multi-discipline engineering coordination. In the European space industry, applying MBSE for the engineering of space systems has been an ongoing undertaking on many missions. In the following paper, the MBSE activities in CAMEO conducted during the A/B1 phases of a typical Earth observation satellite engineered by Airbus are discussed in detail in the form of a case study. The analyses shown are based around the modeling of the spacecraft electrical interfaces in CAMEO. This model was used to automate electrical interface control documents (EICDs) and enable the control of electrical interface development. These methodologies were further put in the context of Airbus’ satellite design processes to assess the benefits of an MBSE approach to the current electrical interface engineering procedure and the potential for the reuse of CAMEO models between satellite projects. The reduction in system engineering effort through the reuse of models to modularly create similar satellite systems for efficient concept evaluation and comparison is a clear benefit. Full article

(This article belongs to the Special Issue Decision Making with Model-Based Systems Engineering)

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23 pages, 1919 KiB

Open AccessArticle

A Novel Intelligent Prediction Model for the Containerized Freight Index: A New Perspective of Adaptive Model Selection for Subseries

by Wendong Yang, Hao Zhang, Sibo Yang and Yan Hao

Systems 2024, 12(8), 309; https://doi.org/10.3390/systems12080309 - 19 Aug 2024

Abstract

The prediction of the containerized freight index has important economic and social significance. Previous research has mostly applied sub-predictors directly for integration, which cannot be optimized for different datasets. To fill this research gap and improve prediction accuracy, this study innovatively proposes a [...] Read more.

The prediction of the containerized freight index has important economic and social significance. Previous research has mostly applied sub-predictors directly for integration, which cannot be optimized for different datasets. To fill this research gap and improve prediction accuracy, this study innovatively proposes a new prediction model based on adaptive model selection and multi-objective ensemble to predict the containerized freight index. The proposed model comprises the following four modules: adaptive data preprocessing, model library, adaptive model selection, and multi-objective ensemble. Specifically, an adaptive data preprocessing module is established based on a novel modal decomposition technology that can effectively reduce the impact of perturbations in historical data on the prediction model. Second, a new model library is constructed to predict the subseries, consisting of four basic predictors. Then, the adaptive model selection module is established based on Lasso feature selection to choose valid predictors for subseries. For the subseries, different predictors can produce different effects; thus, to obtain better prediction results, the weights of each predictor must be reconsidered. Therefore, a multi-objective artificial vulture optimization algorithm is introduced into the multi-objective ensemble module, which can effectively improve the accuracy and stability of the prediction model. In addition, an important discovery is that the proposed model can acquire different models, adaptively varying with different extracted data features in various datasets, and it is common for multiple models or no model to be selected for the subseries.The proposed model demonstrates superior forecasting performance in the real freight market, achieving average MAE, RMSE, MAPE, IA, and TIC values of 9.55567, 11.29675, 0.44222%, 0.99787, and 0.00268, respectively, across four datasets. These results indicate that the proposed model has excellent predictive ability and robustness. Full article

(This article belongs to the Special Issue Data-Driven Modeling and Predictive Analysis for Business, Social, Economic, and Engineering Applications)

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23 pages, 15505 KiB

Open AccessArticle

Coupling between Population and Construction Land Changes in the Beijing–Tianjin–Hebei (BTH) Region: Residential and Employment Perspectives

by Chen Chen

Systems 2024, 12(8), 308; https://doi.org/10.3390/systems12080308 - 19 Aug 2024

Viewed by 155

Abstract

To gain a deeper understanding of the human–land coupling relationship, this study analyzes the coupling relationships with the spatial distribution of construction land from two perspectives: the residential population and the employment population, exploring the similarities and differences in coupling relationships among different [...] Read more.

To gain a deeper understanding of the human–land coupling relationship, this study analyzes the coupling relationships with the spatial distribution of construction land from two perspectives: the residential population and the employment population, exploring the similarities and differences in coupling relationships among different subsystems. The Beijing–Tianjin–Hebei region of China is selected as the study area, covering the period from 2000 to 2020. An analytical framework is proposed, encompassing three approaches: coupling analysis based on county-level spatial units; mean center position analysis based on construction land grids; and regression fitting and residual analysis based on homogeneous grid units. The analysis results indicate: (1) the coupling between the employment population and construction land shows a significant advantage; (2) the coupling between the residential population and construction land has improved faster in recent years; (3) factors such as location, development level, and strategic opportunities have an important influence on the spatial and temporal changes in the coupling relationship. The study further discusses the trade-off relationship between different subsystems, key measures to enhance coupling degree, and the application pathways of this analytical framework at various stages of planning. Considering the limitations of industry sector differences, spatial unit precision, and construction land development intensity, this paper also outlines future research directions. Full article

(This article belongs to the Topic Sustainable Development and Coordinated Governance of Urban and Rural Areas under the Guidance of Ecological Wisdom)

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25 pages, 3460 KiB

Open AccessArticle

Dynamic Research on the Collaborative Governance in Urban and Rural Black-Odorous Water: A Tripartite Stochastic Evolutionary Game Perspective

by Kangjun Peng, Changqi Dong and Jianing Mi

Systems 2024, 12(8), 307; https://doi.org/10.3390/systems12080307 - 18 Aug 2024

Viewed by 277

Abstract

The issue of black-odorous water (BOW) represents a formidable challenge to the current aquatic ecosystems, and its governance exhibits characteristics of low efficiency, susceptibility to relapse, and fragmented management under the Central Environmental Protection Inspection, thereby emerging as a dynamically complex issue in [...] Read more.

The issue of black-odorous water (BOW) represents a formidable challenge to the current aquatic ecosystems, and its governance exhibits characteristics of low efficiency, susceptibility to relapse, and fragmented management under the Central Environmental Protection Inspection, thereby emerging as a dynamically complex issue in the ecological governance of urban and rural settings. This study introduces Gaussian white noise to simulate environmental uncertainty and design a stochastic evolutionary game model encompassing the central government, local governments, and societal forces based on evolutionary game theory and classical governance theories and concepts. Numerical simulations are conducted to explore trajectories of the strategic evolution of various subjects influenced by numerous factors. Results indicate that under the environment of random disturbances, the strategies of the game subjects show significant fluctuations, but actively cultivating the subject’s initial willingness facilitates collaboration governance in inspection. Moreover, joint construction of a “belief system” by multi-subjects, the intensity of inspection interventions, the integration of heterogeneous resources, and effective punitive measures all influence the governance of BOW, but the efficiency of resource allocation should be considered throughout the governance process. Recommendations are made finally for collaborative governance of urban and rural BOW, promoting the sustainable development of the ecological environment. Full article

(This article belongs to the Topic Sustainable Development and Coordinated Governance of Urban and Rural Areas under the Guidance of Ecological Wisdom)

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27 pages, 6298 KiB

Open AccessArticle

The Role of 4IR-5IR Leadership-Management in the Adoption of Formal Methods

by John Andrew van der Poll

Systems 2024, 12(8), 306; https://doi.org/10.3390/systems12080306 - 18 Aug 2024

Viewed by 435

Abstract

Formal methods (FMs) have been cited as a viable methodology for developing high-quality software. However, the steep learning curve in efficiently using the underlying discrete mathematics and logic has hindered FMs’ adoption, leading to a decline in their initial interest in the 1980s. [...] Read more.

Formal methods (FMs) have been cited as a viable methodology for developing high-quality software. However, the steep learning curve in efficiently using the underlying discrete mathematics and logic has hindered FMs’ adoption, leading to a decline in their initial interest in the 1980s. Traditionally, technical approaches have been pursued to address the FMs challenge. Having taken cognisance of a similar pre-4IR decline in AI, the researcher views FMs as technology and considers solutions at intersections of 4IR-5IR technology adoption, leveraged by the support of governors, termed leadership-management in this work. Following a qualitative research choice, scholarly literature is reviewed, and sets of qualitative propositions are defined to develop a conceptual framework for a 4IR-5IR leadership-management adoption of FMs. Aspects that emerged and are incorporated into the framework are cross-functional and executive levels of leadership, transformative, adaptive, and servant leadership styles, using FM tools that embed a high level of user experience, and 4IR technologies, augmented with 5IR human aspects. The framework is hoped to motivate a company’s leadership to contribute to technology and technical ICT-based decision-making increasingly. Future work in this area would involve securing input from practitioners and exercising the framework in an industrial setting. Full article

(This article belongs to the Special Issue Navigating Digital Transformation: Leadership and Decision Making in Today’s Systems)

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25 pages, 1795 KiB

Open AccessArticle

Management Economic Systems and Governance to Reduce Potential Risks in Digital Silk Road Investments: Legal Cooperation between Hainan Free Trade Port and Ethiopia

by Shumin Wang, Qianyu Li and Muhammad Bilawal Khaskheli

Systems 2024, 12(8), 305; https://doi.org/10.3390/systems12080305 - 18 Aug 2024

Viewed by 377

Abstract

This research explores the interplay between innovation, economic systems, governance structures, and law, and how they interact with one another in the context of China and Ethiopia’s investments in the Digital Silk Road. The way cutting-edge methods related to governance and economic systems [...] Read more.

This research explores the interplay between innovation, economic systems, governance structures, and law, and how they interact with one another in the context of China and Ethiopia’s investments in the Digital Silk Road. The way cutting-edge methods related to governance and economic systems might help lower the risks involved in major infrastructure projects, like the Digital Silk Road, particularly in light of law and 5G developments, is investigated. China–Africa connections are to be strengthened, sustainable development is to be encouraged, and healthy economic progress is the goal of the partnership between Ethiopia and the Hainan Free Trade Port. The impact of these transnational investments on fair growth and sustainable development is assessed, while exploring the evolving agendas and procedures governing investments. This research draws attention to how the law and legal cooperation between Ethiopia and China may promote mutually advantageous outcomes, promote transparency and governance mechanisms, and lessen the likelihood of disputes. This research on the factors influencing the future of the Digital Silk Road and its consequences for long-term, sustainable economic growth, and business in the area, aims to provide valuable insights for policymakers, development professionals, and academics, and for the copromotion of China and Ethiopia in terms of digital investment. This research relates to the promotion of the African Continental Free Trade Area (AfCFTA), in terms of construction and economic development. It also examines how the DSR raises concerns about data security and privacy, cross-border transactions, technology transfer, and cyberterrorism, as well as encourages digital investment, such as through enhancing digital governance regulations, modernizing international investment agreements (IIAs), and bolstering global health, coordination, and cooperation; the article concludes by analyzing the implications for Africa. The findings show that such cooperation would support Africa’s digital transformation and sustainable development, while strengthening China–Africa cooperation. Full article

(This article belongs to the Special Issue Business Innovation: From Management Systems to Corporate Social Responsibility)

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19 pages, 385 KiB

Open AccessArticle

The Great Reset as a Realistic Utopia—A Critical Stance from Critical Realism and Complex Systems Theory

by Ermanno C. Tortia

Systems 2024, 12(8), 304; https://doi.org/10.3390/systems12080304 - 16 Aug 2024

Viewed by 382

Abstract

The Great Reset (GR) has been presented by the World Economic Forum (WEF) in response to the COVID-19 pandemic in 2022 as a model through which a “stakeholder economy” would achieve “resilient, equitable, and sustainable” social, economic, and ecological reform. The GR agenda [...] Read more.

The Great Reset (GR) has been presented by the World Economic Forum (WEF) in response to the COVID-19 pandemic in 2022 as a model through which a “stakeholder economy” would achieve “resilient, equitable, and sustainable” social, economic, and ecological reform. The GR agenda includes environmentally sustainable use and more equitable distribution of resources. This article raises the question of whether the Great Reset program should be interpreted as a “realistic utopia” and what its reform potential is. To this end, the GR program is tested against the current state of science and philosophy. The idea of a utopia is analyzed in the light of recent philosophical and scientific approaches, such as critical realism in philosophy, social systems theory in sociology, and complexity theory in science. A comparative conceptual analysis is carried out by introducing the idea of a realistic utopia in Rawls’ theory of justice as fairness. In the final discussion, some doubts are raised about the logical coherence, rigor of scientific theorizing, policy prescriptions, and predictive potential of the Great Reset. It is concluded that utopian projects of radical reform are not realistic due to the supposed long-term repercussions of exogenous shocks or “black swan” events such as the COVID-19 pandemic. Rather, they must offer explanations of the deep structural elements and evolutionary patterns that underlie society and the economy, drawing from these explanations the policy implications, predictions, and prescriptions that can support change. Full article

(This article belongs to the Special Issue Cybernetics and Systems Theory at the Time of Great Reset)

37 pages, 8045 KiB

Open AccessArticle

Linked Links—A Research Project: The Multiple Superimposed Soft Networks as Network Profiles

by Gianfranco Minati

Systems 2024, 12(8), 303; https://doi.org/10.3390/systems12080303 - 14 Aug 2024

Viewed by 406

Abstract

This article, based on network science, aims to contribute to overcoming its geometric and technological phases. The novelty consists in considering links of networks as linked by superimposed networks, termed here multiple superimposed soft networks (MSSN), which is introduced as a research issue. [...] Read more.

This article, based on network science, aims to contribute to overcoming its geometric and technological phases. The novelty consists in considering links of networks as linked by superimposed networks, termed here multiple superimposed soft networks (MSSN), which is introduced as a research issue. Such links of links (termed here as passive links) concern, for instance, correspondences, incompatibilities, and temporal synchronizations between the occurrences of pairs of active links of effective networks, such as those based on electrical and telecommunication. A possible constitutive mechanism of such passive linkage consists of linkage representations for practices and histories of use expressed by their validating statistical reoccurrences. We consider the possible emergent nature of the passive linkage. The reason for introducing the design and usage of MSSN properties as a research issue involves making new approaches to profile and manage networks available. Correspondence between active linkage and MSSN properties should be a matter for an experiential, machine-learning approach. Research issues relate their possible usage on the active linkage such as for classification, comparations, detection of criticalities, diagnosis, performance evaluation, and regulatory as weak forces. Furthermore, the possible identification of standard corresponding configurations of passive and active linkage is finalized to avoid their establishment or, conversely, in facilitating their establishment and keeping their replication in different contexts (or partially and in combinations) and identifying related standardized approaches (also for classes of configurations having significant levels of equivalence). This research project has methodological generalizing aspects of trans-disciplinarity. We conclude by mentioning related research issues. Full article

(This article belongs to the Section Systems Theory and Methodology)

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24 pages, 5173 KiB

Open AccessArticle

Sharing a Ride: A Dual-Service Model of People and Parcels Sharing Taxis with Loose Time Windows of Parcels

by Shuqi Xue, Qi Zhang and Nirajan Shiwakoti

Systems 2024, 12(8), 302; https://doi.org/10.3390/systems12080302 - 14 Aug 2024

Viewed by 371

Abstract

(1) Efficient resource utilization in urban transport necessitates the integration of passenger and freight transport systems. Current research focuses on dynamically responding to both passenger and parcel orders, typically by initially planning passenger routes and then dynamically inserting parcel requests. However, this approach [...] Read more.

(1) Efficient resource utilization in urban transport necessitates the integration of passenger and freight transport systems. Current research focuses on dynamically responding to both passenger and parcel orders, typically by initially planning passenger routes and then dynamically inserting parcel requests. However, this approach overlooks the inherent flexibility in parcel delivery times compared to the stringent time constraints of passenger transport. (2) This study introduces a novel approach to enhance taxi resource utilization by proposing a shared model for people and parcel transport, designated as the SARP-LTW (Sharing a ride problem with loose time windows of parcels) model. Our model accommodates loose time windows for parcel deliveries and initially defines the parcel delivery routes for each taxi before each working day, which was prior to addressing passenger requests. Once the working day of each taxi commences, all taxis will prioritize serving the dynamic passenger travel requests, minimizing the delay for these requests, with the only requirement being to ensure that all pre-scheduled parcels can be delivered to their destinations. (3) This dual-service approach aims to optimize profits while balancing the time-sensitivity of passenger orders against the flexibility in parcel delivery. Furthermore, we improved the adaptive large neighborhood search algorithm by introducing an ant colony information update mechanism (AC-ALNS) to solve the SARP-LTW efficiently. (4) Numerical analysis of the well-known Solomon set of benchmark instances demonstrates that the SARP-LTW model outperforms the SARP model in profit rate, revenue, and revenue stability, with improvements of 48%, 46%, and 49%, respectively. Our proposed approach enables taxi companies to maximize vehicle utilization, reducing idle time and increasing revenue. Full article

(This article belongs to the Special Issue Application of System Engineering and Complex Theory in Transportation)

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22 pages, 475 KiB

Open AccessArticle

Digital Finance, Digital Transformation, and the Development of Off-Balance Sheet Activities by Commercial Banks

by Yibing Wang and Huwei Wen

Systems 2024, 12(8), 301; https://doi.org/10.3390/systems12080301 - 13 Aug 2024

Viewed by 558

Abstract

The development of digital finance represents a new paradigm for the delivery of financial services that has exerted an external shock on the off-balance sheet (OBS) activities of traditional commercial banks. In response, commercial banks have embarked on a digital transformation to mitigate [...] Read more.

The development of digital finance represents a new paradigm for the delivery of financial services that has exerted an external shock on the off-balance sheet (OBS) activities of traditional commercial banks. In response, commercial banks have embarked on a digital transformation to mitigate the challenges posed by digital finance. However, the impact of external shocks and internal responses on banks’ OBS activities, especially the effect of internal responses, needs to be further clarified in order to inform commercial banks’ decision-making. Using a dataset consisting of 42 Chinese commercial banks’ operating data from 2013 to 2022, this paper employs a two-way fixed effects model and a moderation analysis to conduct an empirical analysis. The results show that digital finance has a significant inhibitory effect on OBS activities; furthermore, digital transformation of commercial banks strengthens this inhibitory effect, indicating that its benefits are outweighed by costs of investment and competitive losses. Additionally, the net interest margin significantly amplifies the inhibitory effect, suggesting a trade-off between income from core business activities and OBS activities under external competitive pressure. Based on these research findings, it is recommended that commercial banks seek differentiated competitive strategies and optimize the product structure of their OBS activities. Furthermore, digital transformation strategies should take into account the overall interests of the bank and strike a balance between long-term and short-term benefits. Full article

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19 pages, 1120 KiB

Open AccessArticle

A Three-Stage Model for Innovation Adoption in Health Systems: Insights from the Health Promotion and System Strengthening Project in Tanzania

by Manfred Stoermer, Ally Kebby Abdallah and Karin Wiedenmayer

Systems 2024, 12(8), 300; https://doi.org/10.3390/systems12080300 - 13 Aug 2024

Viewed by 432

Abstract

We explored the outcomes and challenges encountered during a 12-year collaborative development endeavor in Tanzania, focused on enhancing the healthcare system. The Health Promotion and System Strengthening (HPSS) project, supported by the Swiss Government and implemented by the Swiss Tropical and Public Health [...] Read more.

We explored the outcomes and challenges encountered during a 12-year collaborative development endeavor in Tanzania, focused on enhancing the healthcare system. The Health Promotion and System Strengthening (HPSS) project, supported by the Swiss Government and implemented by the Swiss Tropical and Public Health Institute (Swiss TPH) from 2011 to 2023, aimed to strengthen various aspects of Tanzania’s healthcare landscape. This included reforms in health insurance through the improved Community Health Fund (iCHF), the establishment of a public–private partnership to optimize the health commodity supply chain via a Prime Vendor System (Jazia PVS), the implementation of health technology management innovations, and the facilitation of participatory community and school health promotion initiatives. Operating in a multisectoral, interdisciplinary, and systemic manner, the HPSS project employed a variety of interconnected strategies, focusing on key entry points within the Tanzanian health system, starting from district level to national policies. These efforts followed a three-stages approach to reach a sustainable adoption of the innovations, going through the process of service and product innovation, integration into service delivery systems, and finally their adoption in the respective institutional policies. Each stage presented distinct frameworks and challenges, detailed in this article. The development of innovative concepts was complemented by capacity building through on-the-job training, establishment of new accredited training programs for pre-service trainings, and the development of new IT systems integrated into the governmental IT environment, as well as efforts to improve transparency, accountability, and governance. Activities in these fields were guided by operational research, following the translational approach of Swiss TPH to go from innovation and validation to application. The example of the HPSS project highlights the cycle of developing and testing innovations at the community and district level, followed by endeavoring national-level integration and policy adjustments, consequently resulting in improved service delivery at the district and community level. Full article

(This article belongs to the Special Issue Systems Thinking for District Health Systems: Applications, Issues and Challenges)

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31 pages, 3632 KiB

Open AccessArticle

A Bi-Objective Model for the Multi-Period Inventory-Based Reverse Logistics Network: A Case Study from an Automobile Component Distribution Network

by Mohammad Khalilzadeh, Jurgita Antucheviciene and Darko Božanić

Systems 2024, 12(8), 299; https://doi.org/10.3390/systems12080299 - 12 Aug 2024

Viewed by 654

Abstract

Supply chain management and distribution network design has attracted the attention of many researchers in recent years. The timely satisfaction of customer demands leads to reducing costs, improving service levels, and increasing customer satisfaction. For this purpose, in this research, the mathematical programming [...] Read more.

Supply chain management and distribution network design has attracted the attention of many researchers in recent years. The timely satisfaction of customer demands leads to reducing costs, improving service levels, and increasing customer satisfaction. For this purpose, in this research, the mathematical programming models for a two-level distribution network including central warehouses, regional warehouses, and customers are designed so that several products with definite demands in multiple periods are distributed from central warehouses to customers. In this problem, two objective functions are considered. The first objective function seeks to minimize the costs of establishment, transportation, inventory, and shortage, and the second objective function attempts to maximize the satisfaction level corresponding with the supply rate of different goods for numerous customers. The presented models include the basic model, inventory-based model, multi-period inventory-based model, and multi-period inventory-based reverse logistics model. The validation and applicability of the proposed models were demonstrated by implementation in a real case study of the automobile industry. The LINGO software 20.0 was used to solve the models. The results show that incorporating the inventory management policies into the basic model and converting from a single-period to a multi-period reverse logistics model will significantly increase company profitability and customer satisfaction. Full article

(This article belongs to the Special Issue Multi-criteria Decision Making in Supply Chain Management)

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19 pages, 1439 KiB

Open AccessArticle

A Testing and Evaluation Method for the Car-Following Models of Automated Vehicles Based on Driving Simulator

by Yuhan Zhang, Yichang Shao, Xiaomeng Shi and Zhirui Ye

Systems 2024, 12(8), 298; https://doi.org/10.3390/systems12080298 - 12 Aug 2024

Viewed by 524

Abstract

The continuous advancement of connected and automated driving technologies has garnered considerable public attention regarding the safety and reliability of automated vehicles (AVs). Comprehensive and efficient testing is essential before AVs can be deployed on public roads. Current mainstream testing methods involve high [...] Read more.

The continuous advancement of connected and automated driving technologies has garnered considerable public attention regarding the safety and reliability of automated vehicles (AVs). Comprehensive and efficient testing is essential before AVs can be deployed on public roads. Current mainstream testing methods involve high costs in real-world settings and limited immersion in numerical simulations. To address these challenges and facilitate testing in mixed traffic scenarios involving both human-driven vehicles (HDVs) and AVs, we propose a testing and evaluation approach using a driving simulator. Our methodology comprises three fundamental steps. First, we systematically classify scenario elements by drawing insights from the scenario generation logic of the driving simulator. Second, we establish an interactive traffic scenario that allows human drivers to manipulate vehicles within the simulator while AVs execute their decision and planning algorithms. Third, we introduce an evaluation method based on this testing approach, validated through a case study focused on car-following models. The experimental results confirm the efficiency of the simulation-based testing method and demonstrate how car-following efficiency and comfort decline with increased speeds. The proposed approach offers a cost-effective and comprehensive solution for testing, considering human driver behavior, making it a promising method for evaluating AVs in mixed traffic scenarios. Full article

(This article belongs to the Special Issue Application of System Engineering and Complex Theory in Transportation)

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24 pages, 2384 KiB

Open AccessArticle

Optimized Decisions for Smart Tourism Destinations: A Cross-Generational Perspective Using an Improved Importance–Performance Analysis

by Elena-Aurelia Botezat, Olimpia-Iuliana Ban, Adela Laura Popa, Dorin-Cristian Coita and Teodora Mihaela Tarcza

Systems 2024, 12(8), 297; https://doi.org/10.3390/systems12080297 - 12 Aug 2024

Viewed by 462

Abstract

Our study introduces an enhanced version of the Importance–Performance Analysis (IPA) method, a powerful tool that can be applied across various domains. This method plays a crucial role in our research, aiding in making well-informed decisions about smart tourism destination attributes. We achieved [...] Read more.

Our study introduces an enhanced version of the Importance–Performance Analysis (IPA) method, a powerful tool that can be applied across various domains. This method plays a crucial role in our research, aiding in making well-informed decisions about smart tourism destination attributes. We achieved this by evaluating how 911 consumers from four different generations (Baby Boomers, Generation X, Millennials, and Generation Z) rated these attributes based on their most recent tourist destination visit. Unlike traditional methods that often rely on subjective opinions or complex statistical models, the Improved IPA (IIPA) method offers a clear approach to decision-making. It enables decision-makers to focus on the most crucial attributes that drive consumer interest, thereby optimizing resource allocation and marketing efforts. Specifically, to remain competitive, decision-makers for smart tourist destinations should focus on queuing-time forecast and applications, websites, and content accessible for travelers with disabilities for Baby Boomers; e-complaint handling for Generation X; smart emergency response system for Millennials; and tourist-flow forecast, real-time traffic broadcast, electronic-entrance guard systems, and accessible data about physical design features of accommodation, restaurants, and tourist attractions for Generation Z. Theoretically, this study advances the research on managerial decision-making by demonstrating the effectiveness of the IIPA as a clear and straightforward method for making optimal decisions about product or service attributes. In practice, the study provides decision-makers with valuable insights into the importance of different categories of smart attributes in shaping the overall holiday experience at a tourist destination for Baby Boomers, Generation X, Millennials, and Generation Z tourism consumers. Full article

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31 pages, 2287 KiB

Open AccessArticle

Can Relocation Influence Human Acceptance of Connected and Automated Vehicles?

by Ying Zhang, Chu Zhang, Jun Chen, Guang Yang and Wei Wang

Systems 2024, 12(8), 296; https://doi.org/10.3390/systems12080296 - 11 Aug 2024

Viewed by 763

Abstract

Connected and automated vehicles (CAVs) are poised to revolutionize mobility. The relocation feature of CAVs enhances parking convenience for the public. Users can instruct CAVs to arrive at their work destination, drop them off, and then assign CAVs to a cost-effective parking facility [...] Read more.

Connected and automated vehicles (CAVs) are poised to revolutionize mobility. The relocation feature of CAVs enhances parking convenience for the public. Users can instruct CAVs to arrive at their work destination, drop them off, and then assign CAVs to a cost-effective parking facility through an optimized itinerary. However, realizing the benefits of CAVs depends on user acceptance, and the impact of relocation features on CAV acceptance remains an area that is yet to be explored. This study introduces a novel acceptance model to mainly investigate the effects of relocation-related factors on CAV acceptance through 717 valid responses. The results indicate that the perceived convenience of relocation (PCOR) indirectly increases human acceptance through three determinants, initial trust, perceived usefulness (PU), and perceived ease of use (PEOU), while initial trust, PU, and PEOU directly increase human acceptance. The public expectations of saving on parking fees (EOSPF) can enhance PCOR. Additionally, a multigroup analysis revealed that PCOR exerts a more positive impact on PU or PEOU in subgroups including males, pre-Generation-Z individuals, experienced drivers, and those with autopilot riding experience. The findings on mediators are also discussed. This study provides valuable insights for further research and the practical adoption of emerging CAVs. Full article

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22 pages, 3266 KiB

Open AccessArticle

How Can Scientific Crowdsourcing Realize Value Co-Creation? A Knowledge Flow-Based Perspective

by Ran Qiu, Guohao Wang, Liying Yu, Yuanzhi Xing and Hui Yang

Systems 2024, 12(8), 295; https://doi.org/10.3390/systems12080295 - 11 Aug 2024

Viewed by 525

Abstract

Presently, the practice of scientific crowdsourcing still suffers from user loss, platform operational inefficiency, and many other dilemmas, mainly because the process mechanism of realizing value co-creation through interaction between users and platforms has not yet been elaborated. To fill this gap, this [...] Read more.

Presently, the practice of scientific crowdsourcing still suffers from user loss, platform operational inefficiency, and many other dilemmas, mainly because the process mechanism of realizing value co-creation through interaction between users and platforms has not yet been elaborated. To fill this gap, this study takes Kaggle as the research object and explores the realization process and internal mechanism of scientific crowdsourcing value co-creation from the perspective of knowledge flow. The results show that the operation process of Kaggle-based scientific crowdsourcing can be decomposed into five progressive evolutionary stages, including knowledge sharing, knowledge innovation, knowledge dissemination, knowledge application, and knowledge advantage formation. The knowledge flow activates a series of value co-creation activities of scientific crowdsourcing, forming a dynamic evolution and continuous optimization of the value co-creation process that includes the value proposition, value communication, value consensus, and all-win value. Institutional logic plays a key role as a catalyst in the value co-creation of scientific crowdsourcing, effectively facilitating the realization of value co-creation by controlling and guiding the flow of knowledge. The study unlocks the “gray box” from knowledge flow to value co-creation, providing new theoretical support and guidance for further enhancing the value co-creation capacity and accelerating the practice of scientific crowdsourcing. Full article

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21 pages, 6465 KiB

Open AccessArticle

Soft Systems Methodology in Standardizing the Method for Applying Dolphin-Assisted Therapies in Neurodivergent Patients: Case Study of Delfiniti Mexico

by Ana Lilia Coria Páez, Brenda Lorena Flores Hidalgo, Oswaldo Morales Matamoros, Jesús Jaime Moreno Escobar and Hugo Quintana Espinosa

Systems 2024, 12(8), 294; https://doi.org/10.3390/systems12080294 - 11 Aug 2024

Viewed by 466

Abstract

Dolphin-assisted therapy (DAT) currently lacks a standard for their application, making it difficult to collect the consistent data necessary for comparative studies and the development of new evidence-based therapeutic strategies. Due to their high social component, DAT requires a standardized method that identifies [...] Read more.

Dolphin-assisted therapy (DAT) currently lacks a standard for their application, making it difficult to collect the consistent data necessary for comparative studies and the development of new evidence-based therapeutic strategies. Due to their high social component, DAT requires a standardized method that identifies the elements that affect them, understands their complex situations, and proposes solutions to the challenges. This study aims to establish the first steps towards standardizing DAT, using the Soft Systems Methodology (SSM) as the central approach. SSM is suitable for addressing complex and ambiguous problems that involve multiple actors and perspectives. Through SSM, the study seeks to visualize problems, clarify conflict relationships that hinder standardization, and propose effective solutions. To establish an initial standard method, a time and motion study is performed to identify activities that disrupt the sequence of operations and the capture of EEG signals collected before, during, and after DAT. SSM allows for summarizing the current system situation, identifying and analyzing problems, clarifying challenges, and proposing pertinent solutions to achieve the standardization of this therapy. This methodology facilitates the identification of critical points and the development of intervention strategies that could improve the efficiency and effectiveness of the therapeutic process, establishing a more coherent framework for the implementation of DAT. Thus, the contribution of this work is based on systems thinking to strategic management, as it demonstrates the potential role of systems thinking, specifically SSM, in analyzing complex problems, improving strategy mapping, fostering strategic decision making, and planning for the future in the context of strategic management. Full article

(This article belongs to the Special Issue The Systems Thinking Approach to Strategic Management)

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23 pages, 2850 KiB

Open AccessArticle

Settlement Selection Strategic Analysis for Self-Operated E-Commerce Platforms under Market Competition

by Yu-Wei Li, Gui-Hua Lin and Peixin Chen

Systems 2024, 12(8), 293; https://doi.org/10.3390/systems12080293 - 9 Aug 2024

Viewed by 402

Abstract

This paper focuses on the settlement selection strategic analysis for self-operated e-commerce platforms on hybrid e-commerce platforms under market competition. Taking factors such as the market share, price competition, commission, and customer loyalty into account, a multi-leader–follower game model with the platforms as [...] Read more.

This paper focuses on the settlement selection strategic analysis for self-operated e-commerce platforms on hybrid e-commerce platforms under market competition. Taking factors such as the market share, price competition, commission, and customer loyalty into account, a multi-leader–follower game model with the platforms as leaders and the manufacturers as followers is established. Then, we solve the model with the help of some mathematical techniques and describe some numerical experiments to analyze settlement strategies for the self-operated platforms and their impact on other members in the network. The numerical results reveal the following revelations: a lower commission rate is more suitable for the self-operated platforms; once the commission rates are determined, the self-operated platforms prefer to settle in the hybrid platforms under lower medium price competition; when the price competition is fierce, as customer loyalty increases, the self-operated platforms should settle with a low market share; if the self-operated platforms settle in the hybrid platforms, then a higher price competition is advantageous for all members and can facilitate supply chain coordination. Full article

(This article belongs to the Section Supply Chain Management)

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24 pages, 1740 KiB

Open AccessArticle

Impact of Quality Investment and Vertical Shareholding in Hybrid Competing Supply Chains

by Shouyao Xiong and Tao Zhou

Systems 2024, 12(8), 292; https://doi.org/10.3390/systems12080292 - 9 Aug 2024

Viewed by 427

Abstract

Product quality is a key factor affecting consumers’ willingness to buy, providing greater advantages to an enterprise than product price. This paper investigates the impact of two factors, price and quality, on the operational decisions of hybrid competing supply chains. Supply chain I, [...] Read more.

Product quality is a key factor affecting consumers’ willingness to buy, providing greater advantages to an enterprise than product price. This paper investigates the impact of two factors, price and quality, on the operational decisions of hybrid competing supply chains. Supply chain I, which consists of a manufacturer and a retailer, is a decentralized structure. Supply chain II, where the manufacturer and retailer are integrated, is a centralized structure. Quality investment and vertical shareholding are introduced into the decentralized supply chain. Models are constructed for three different scenarios, examining whether the manufacturer makes a quality investment and whether the retailer holds shares in the quality investment. By comparing the equilibrium results, solved by the Stackelberg game method, the following conclusions are drawn: (1) Quality investment and shareholding can enhance product quality and price. (2) The retail price in a centralized supply chain is consistently lower than that in a decentralized one, leading to generally higher total profits for centralized supply chain. (3) The total profit of the decentralized supply chain only exceeds that of the centralized ones when the degree of substitution between products is lower than 0.6285 and the quality effort cost factor is within a specific range. While centralized supply chain is generally more advantageous, decentralized supply chain can outperform him under specific conditions. Full article

(This article belongs to the Special Issue Multi-criteria Decision Making in Supply Chain Management)

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21 pages, 1011 KiB

Open AccessArticle

The Impact of the Digital Economy on Carbon Emissions Based on Regional Development Imbalance

by Xiaoxia Jia and Weiyi Guang

Systems 2024, 12(8), 291; https://doi.org/10.3390/systems12080291 - 9 Aug 2024

Viewed by 826

Abstract

Digital economy is an important direction of the new round of technological revolution and a key driving force for realizing the “double control of carbon emissions”. This paper utilizes the panel data of 30 provincial-level administrative regions in China from 2011 to 2021 [...] Read more.

Digital economy is an important direction of the new round of technological revolution and a key driving force for realizing the “double control of carbon emissions”. This paper utilizes the panel data of 30 provincial-level administrative regions in China from 2011 to 2021 to measure the development level of the digital economy, total carbon emissions, and carbon emission intensity and explores the impact of the digital economy on the dual control of carbon emissions and the mechanism of its effect by applying the mediating and moderating effect models. The results show that the digital economy can play a significant inhibitory effect on total carbon emissions and carbon emissions intensity, and this conclusion is still robust after a series of tests. From the government level, there exists a transmission path of “digital economy → environmental regulation stringency → dual control of carbon emissions”; from the enterprise and research organization level, there also exists a transmission path of “digital economy → R&D intensity → dual control of carbon emissions”. From the perspective of regional imbalance, there are large regional differences in the impact of the digital economy on the dual control of carbon emissions, and there are also large differences in the impact of the various subdivided indicators of the digital economy on the dual control of carbon emissions. In addition, this paper also finds that the positive effect of the digital economy on the dual control of carbon emissions is more obvious in regions with a smaller proportion of SOEs. These findings add new evidence to the study of “the impact of the digital economy on the dual control of carbon emissions” and provide new ideas for accelerating the realization of green and sustainable development. Full article

(This article belongs to the Section Systems Practice in Social Science)

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37 pages, 5239 KiB

Open AccessArticle

A Model-Based Systems Engineering Approach for Effective Decision Support of Modern Energy Systems Depicted with Clean Hydrogen Production

by Svetlana Lawrence and Daniel R. Herber

Systems 2024, 12(8), 290; https://doi.org/10.3390/systems12080290 - 8 Aug 2024

Viewed by 422

Abstract

A holistic approach to decision-making in modern energy systems is vital due to their increase in complexity and interconnectedness. However, decision makers often rely on narrowly-focused strategies, such as economic assessments, for energy system strategy selection. The approach in this paper helps considers [...] Read more.

A holistic approach to decision-making in modern energy systems is vital due to their increase in complexity and interconnectedness. However, decision makers often rely on narrowly-focused strategies, such as economic assessments, for energy system strategy selection. The approach in this paper helps considers various factors such as economic viability, technological feasibility, environmental impact, and social acceptance. By integrating these diverse elements, decision makers can identify more economically feasible, sustainable, and resilient energy strategies. While existing focused approaches are valuable since they provide clear metrics of a potential solution (e.g., an economic measure of profitability), they do not offer the much needed system-as-a-whole understanding. This lack of understanding often leads to selecting suboptimal or unfeasible solutions, which is often discovered much later in the process when a change may not be possible. This paper presents a novel evaluation framework to support holistic decision-making in energy systems. The framework is based on a systems thinking approach, applied through systems engineering principles and model-based systems engineering tools, coupled with a multicriteria decision analysis approach. The systems engineering approach guides the development of feasible solutions for novel energy systems, and the multicriteria decision analysis is used for a systematic evaluation of available strategies and objective selection of the best solution. The proposed framework enables holistic, multidisciplinary, and objective evaluations of solutions and strategies for energy systems, clearly demonstrates the pros and cons of available options, and supports knowledge collection and retention to be used for a different scenario or context. The framework is demonstrated in case study evaluation solutions for a novel energy system of clean hydrogen generation. Full article

(This article belongs to the Special Issue Decision Making with Model-Based Systems Engineering)

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23 pages, 2480 KiB

Open AccessArticle

Adaptation of Tourism Transformation in Rural Areas under the Background of Regime Shift: A Social–Ecological Systems Framework

by Jia Chen, Wenqian Chen, Fei Wang and Mengqi Deng

Systems 2024, 12(8), 289; https://doi.org/10.3390/systems12080289 - 8 Aug 2024

Viewed by 459

Abstract

The rural transformation driven by regime shift is obvious around the world, and there is still insufficient research exploring related effective analytical frameworks and ideas. Transformation adaptation is widely used in the field of disaster research as a concept of dynamic systems’ evolutionary [...] Read more.

The rural transformation driven by regime shift is obvious around the world, and there is still insufficient research exploring related effective analytical frameworks and ideas. Transformation adaptation is widely used in the field of disaster research as a concept of dynamic systems’ evolutionary development, emphasizing fundamental changes in the structure or function of systems and promoting equity and justice for communities in social–ecological systems. This paper critically reviews and synthesizes the literature on adaptation to construct an evaluation framework of transformative adaptation of social–ecological systems. This framework is applied to the analysis of the adaptive process, capacity, and outcomes of rural tourism transformation in different cases of Shaanxi Province, China. The results were as follows: (1) The shift of regime state in the process of rural transformation adaptation has diversified, while the tourism regime shift with active adaptation has better adaptive capacity and outcomes; (2) a strong community foundation and benefit-sharing tourism development model can promote adaptation in the rural system; and (3) social relationship networks, farmers’ collective interests and discourse power, and rural economic and material conditions are the key factors affecting the adaptation of rural tourism transformation. This study provides practical analytical tools and opportunities for improving adaptation of the rural tourism transformation at the global level. Full article

(This article belongs to the Special Issue Socio-Ecological Systems and Their Applications)

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19 pages, 729 KiB

Open AccessReview

Cell Formation Problem with Alternative Routes and Machine Reliability: Review, Analysis, and Future Developments

by Paulo Figueroa-Torrez, Orlando Durán and Miguel Sellitto

Systems 2024, 12(8), 288; https://doi.org/10.3390/systems12080288 - 7 Aug 2024

Viewed by 468

Abstract

The Cell Formation Problem (CFP) is a widely studied issue that aims to group machines effectively based on criteria such as productivity, lower costs, and greater efficiency. In recent years, more characteristics were summarized relating to this problem. This paper provides a bibliographic [...] Read more.

The Cell Formation Problem (CFP) is a widely studied issue that aims to group machines effectively based on criteria such as productivity, lower costs, and greater efficiency. In recent years, more characteristics were summarized relating to this problem. This paper provides a bibliographic examination of methodologies addressing the CFP in cellular manufacturing, focusing on novel approaches such as alternative routes and machine reliability. The articles were obtained from Scopus and Web of Science and filtered using the PRISMA methodology. Classification based on objective functions, constraints, and methodologies facilitated informative visualizations for analysis. Findings indicate a focus on capital utilization optimization, with cost reduction via intercellular moves minimization as the primary objective. Common constraints include limits on the number of machines per cell, restricting machines to a single cell and singular production routes per part. The genetic algorithm predominates as a non-exact solution approach, while the “

ε

-constraint” method is commonly used. This study offers insights into contemporary trends in solving the CFP with alternative routings and machine reliability, aiding researchers and professionals in the field to improve the quality of their investigations. Full article

(This article belongs to the Section Systems Engineering)

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16 pages, 702 KiB

Open AccessArticle

Complexity in Systemic Cognition: Theoretical Explorations with Agent-Based Modeling

by Davide Secchi, Rasmus Gahrn-Andersen and Martin Neumann

Systems 2024, 12(8), 287; https://doi.org/10.3390/systems12080287 - 6 Aug 2024

Viewed by 431

Abstract

This paper presents a systemic view of human cognition that suggests complexityis an essential feature of such a system. It draws on the embodied, distributed, and extended cognition paradigms to outline the elements and the mechanisms that define cognition. In doing so, it [...] Read more.

This paper presents a systemic view of human cognition that suggests complexityis an essential feature of such a system. It draws on the embodied, distributed, and extended cognition paradigms to outline the elements and the mechanisms that define cognition. In doing so, it uses an agent-based computational model (the TS 1.0.5Model) with a focus on learning mechanisms as they reflect on individual competence to gain insights on how cognition works. Results indicate that cognitive dynamics do not depend solely on macro structural elements, nor do they depend uniquely on individual characteristics. Instead, more insights and understanding are available through the consideration of all elements together as they co-evolve and interact over time. This perspective illustrates the essential role of how we define the meso domain and constitutes a clear indication that cognitive systems are indeed complex. Full article

(This article belongs to the Special Issue Theoretical Issues on Systems Science)

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21 pages, 11188 KiB

Open AccessArticle

Optimal Allocation of Multi-Type Vaccines in a Two-Dose Vaccination Campaign for Epidemic Control: A Case Study of COVID-19

by Jin Zhu, Qing Wang and Min Huang

Systems 2024, 12(8), 286; https://doi.org/10.3390/systems12080286 - 5 Aug 2024

Viewed by 599

Abstract

As a typical case of the optimal planning for the provision of restricted medical resources, widespread vaccination is considered an effective and sustainable way to prevent and control large-scale novel coronavirus disease 2019 (COVID-19) outbreaks. However, an initial supply shortage of vaccines is [...] Read more.

As a typical case of the optimal planning for the provision of restricted medical resources, widespread vaccination is considered an effective and sustainable way to prevent and control large-scale novel coronavirus disease 2019 (COVID-19) outbreaks. However, an initial supply shortage of vaccines is inevitable because of the narrow production and logistical capacity. This work focuses on the multi-type vaccine resource allocation problem in a two-dose vaccination campaign under limited supply. To address this issue, we extended an age-stratified susceptible, exposed, infectious, and recovered (SEIR) epidemiological model to incorporate a two-dose vaccination campaign involving multiple vaccine types to fully characterize the various stages of infection and vaccination. Afterward, we integrated the proposed epidemiological model into a nonlinear programming (NLP) model to determine the optimal allocation strategy under supply capacity and vaccine hesitancy constraints with the goal of minimizing the cumulative number of deaths due to the pandemic over the entire planning horizon. A case study based on real-world data from the initial mass vaccination campaign against COVID-19 in the Midlands, England, was taken to validate the applicability of our model. Then, we performed a comparative study to demonstrate the performance of the proposed method and conducted an extensive sensitivity analysis on critical model parameters. Our results indicate that prioritizing the allocation of vaccines to elderly persons is an effective strategy for reducing COVID-19-related fatalities. Furthermore, we found that vaccination alone will not be sufficient for epidemic control in the short term, and appropriate non-pharmacological interventions are still important for effective viral containment during the initial vaccine rollout. The results also showed that the relative efficacy of the first dose is a vital factor affecting the optimal interval between doses. It is always best to complete the two-dose vaccination schedule as soon as possible when the relative efficacy of the first dose is low. Conversely, delaying the second dose of a vaccine as long as possible to increase the proportion of the population vaccinated with a single dose tends to be more favorable when the relative efficacy of the first dose is high. Finally, our proposed model is general and easily extendable to the study of other infectious disease outbreaks and provides important implications for public health authorities seeking to develop effective vaccine allocation strategies for tackling possible future pandemics. Full article

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22 pages, 11012 KiB

Open AccessArticle

Complex-Systems Analysis of the CSI 300 Index: Evolution, Resilience, and Prediction in Stock Correlation Network

by Xinyuan Luo, Jian Yin and Danqi Wei

Systems 2024, 12(8), 285; https://doi.org/10.3390/systems12080285 - 5 Aug 2024

Viewed by 452

Abstract

With the outbreak and evolution of the pandemic worldwide, the financial market has experienced unprecedented shocks and adjustments, and the volatility and correlation of the stock market, as an important indicator of economic activities, have shown new features and trends during the pandemic. [...] Read more.

With the outbreak and evolution of the pandemic worldwide, the financial market has experienced unprecedented shocks and adjustments, and the volatility and correlation of the stock market, as an important indicator of economic activities, have shown new features and trends during the pandemic. Based on the CSI 300 Index, we construct a three-stage sequential network representing the pre-pandemic, pandemic, and post-relaxation phases. We investigate the evolving dynamics and resilience of the network, forecasting potential future connections, thus offering fresh insights into comprehending market recovery. Our findings unveil that the market adapts dynamically to the pandemic’s progression, witnessing an overall augmentation in network interconnectedness. While the financial sector maintains its pivotal role, the influence of non-financial sectors experiences an upsurge. Despite the network demonstrating poor stability and heavy reliance on key nodes, there exists a positive recovery trajectory. Non-financial sectors such as energy and transportation emerge as pivotal catalysts for market rejuvenation. We provide suggestions for government regulators and investors, providing strong support for optimizing the market structure and promoting the long-term healthy development of the market. Full article

(This article belongs to the Special Issue Sustainability, Complexity and Resilience: Insights from Complex Systems Approaches)

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13 pages, 1285 KiB

Open AccessArticle

Measuring the Impact of COVID-19 Vaccination Rates on Carbon Emissions Using LightGBM Model: Evidence from the EU Region

by Xinran Yue and Yan Li

Systems 2024, 12(8), 284; https://doi.org/10.3390/systems12080284 - 4 Aug 2024

Viewed by 462

Abstract

COVID-19 vaccination status has become a significant factor influencing carbon emissions in recent years. This paper explores the relationship between vaccination programs and CO₂ emissions to provide scientific support for future emergency management. The study utilizes daily carbon emissions data and daily [...] Read more.

COVID-19 vaccination status has become a significant factor influencing carbon emissions in recent years. This paper explores the relationship between vaccination programs and CO₂ emissions to provide scientific support for future emergency management. The study utilizes daily carbon emissions data and daily vaccination program data from six sectors within the European Union. It compares the accuracy of various machine learning models by incorporating 11 economic control variables. Additionally, it quantitatively decomposes the contribution of each variable to carbon emissions during the pandemic using SHAP values. The findings indicate that the LightGBM model predicts carbon emissions much more accurately than other models. Furthermore, COVID-19-related variables, such as daily vaccination volumes and cumulative vaccination totals, are identified as significant factors affecting carbon emissions. Full article

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35 pages, 3932 KiB

Open AccessArticle

Low-Carbon Supply Chain Decision-Making and CSR Strategy Evolution Analysis Considering Heterogeneous Consumer Preferences

by Jinghua Zhao, Ruishu Zhang, Zhuang Wang and Shaoyun Cui

Systems 2024, 12(8), 283; https://doi.org/10.3390/systems12080283 - 3 Aug 2024

Viewed by 478

Abstract

Decision-making regarding the low-carbon supply chain, considering corporate social responsibility (CSR) and the heterogeneous preferences of consumers, has become an urgent topic to be explored. This paper explores the decision-making problem of a low-carbon supply chain considering the heterogeneous preferences of consumers under [...] Read more.

Decision-making regarding the low-carbon supply chain, considering corporate social responsibility (CSR) and the heterogeneous preferences of consumers, has become an urgent topic to be explored. This paper explores the decision-making problem of a low-carbon supply chain considering the heterogeneous preferences of consumers under different CSR situations, analyzes the influence of important parameters on each equilibrium solution, compares the size relationship of each equilibrium solution under different CSR situations, and verifies the conclusions obtained through numerical simulation. Then, based on the obtained equilibrium solution, a CSR evolutionary game model of the low-carbon supply chain is constructed, and the evolutionary stability strategies of the two sides on the CSR game are solved. Finally, the evolutionary trajectory of the game system is intuitively presented using a simulation method, and the influence of the main parameters on the evolutionary trends of the two sides is analyzed. The findings are as follows: (1) When both manufacturers and retailers undertake CSR, the retail price and wholesale price are their lowest, while carbon emission reduction, total market demand, manufacturer utility, retailer utility, and supply chain total utility are the highest. (2) When a company undertakes CSR, carbon emission reduction, total market demand, manufacturer utility, retailer utility, and supply chain total utility all increase with the increase in the CSR degree of the company and the ratio of the potential scale of low-carbon consumers to the potential scale of ordinary consumers. (3) The evolutionary stability strategy for both manufacturers and retailers is to undertake CSR. In addition, the initial proportion of manufacturers and retailers that undertake CSR, the low-carbon preference of low-carbon consumers, and the increase in the ratio of the potential scale of low-carbon consumers to the potential scale of ordinary consumers can encourage both members of the supply chain to undertake CSR. Full article

(This article belongs to the Special Issue Multi-criteria Decision Making in Supply Chain Management)

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17 pages, 2795 KiB

Open AccessArticle

Taxi Travel Distance Clustering Method Based on Exponential Fitting and k-Means Using Data from the US and China

by Zhenang Song, Jun Cai and Qiyao Yang

Systems 2024, 12(8), 282; https://doi.org/10.3390/systems12080282 - 3 Aug 2024

Viewed by 447

Abstract

The taxi travel distance distribution can be used to forecast the origin and destination (OD) distribution of taxis and private cars. Most of the existing studies on taxi trip distributions have summarized a “low–high–low” trend and approached zero at both ends; however, they [...] Read more.

The taxi travel distance distribution can be used to forecast the origin and destination (OD) distribution of taxis and private cars. Most of the existing studies on taxi trip distributions have summarized a “low–high–low” trend and approached zero at both ends; however, they failed to explain the reason for this distance distribution. The key indicators and parameters identified by various researchers using big data for the same city and year typically differ, especially in terms of the mode and mean values of distance and time. This study uses New York yellow and green taxi data (a total of 417,018,811 data points) from 2017 to 2022, as well as data from China, to obtain a general law of the taxi travel distance distribution through an analysis of the relative distance and relative frequency. The travel mode was 0.54 times the relative distance, while the data tended towards zero at 2.0 times the relative distance. We verified the reliability of the research method based on reference and survey data. The results reveal the formation mechanism of the taxi travel distance distribution characteristics, which follow an exponential distribution. These laws can be used in the context of urban planning and transportation research. We propose a taxi form distance clustering method based on the k-means approach, chosen for its effectiveness on large datasets, interpretability, and alignment with our research objectives. This method provides visual results for the travel distance and accurate information for urban transportation planning and taxi services. The practical implications for policymakers, urban planners, and taxi services are discussed, demonstrating how the identified travel distance distribution laws can influence urban planning and taxi service optimization. Finally, the problems of data collection, cleaning, and processing are identified from the perspective of data statistics and analysis. Full article

(This article belongs to the Section Systems Engineering)

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17 pages, 717 KiB

Open AccessArticle

Exploring Intrinsic Motivation and Mental Well-Being in Private Higher Educational Systems: A Cross-Sectional Study

by Fayyaz Qureshi, Sarwar Khawaja, Katarina Sokić, Mirjana Pejić Bach and Maja Meško

Systems 2024, 12(8), 281; https://doi.org/10.3390/systems12080281 - 2 Aug 2024

Viewed by 499

Abstract

In the realm of digital transformation, effective leadership and motivation are pivotal for organisations navigating the complexities of today’s systems. This study explores the intersection of intrinsic motivation and mental well-being among mature students—an analogy that sheds light on strategies applicable to organisational [...] Read more.

In the realm of digital transformation, effective leadership and motivation are pivotal for organisations navigating the complexities of today’s systems. This study explores the intersection of intrinsic motivation and mental well-being among mature students—an analogy that sheds light on strategies applicable to organisational contexts. In developed nations like the UK, mental health for mature students is increasingly recognised as a crucial component of their educational journey. Mature students, who typically enrol in higher education after an educational gap and upon turning 21, often face specific challenges that can impact their mental well-being while pursuing academic goals. The primary objective of our study was to assess the relationship between intrinsic motivation and the mental well-being of mature students. The study included 248 full-time undergraduate mature students enrolled in private higher education institutions in the UK. These participants were 21 years and older. The research employed two measurement scales: the four-item Intrinsic Motivation Scale, adapted from Jaramillo, and the Warwick–Edinburgh Mental Well-Being Scale. Data collection utilised online Google Forms with multiple choice self-report formatted questions, and our analysis involved both descriptive and inferential statistics. Our research revealed a significant positive correlation between variables of intrinsic motivation and mental well-being. Confirmatory factor analysis (CFA) results confirmed the construct in the model. The results indicated that intrinsic motivation significantly predicts mental well-being among mature students (Cohen’s effect size value, f² = 0.54). Recognising and addressing the unique difficulties individuals encounter and providing appropriate support can enhance their well-being and contribute to the overall success of the higher education community. Full article

(This article belongs to the Special Issue Navigating Digital Transformation: Leadership and Decision Making in Today’s Systems)

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