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Taking into consideration the current human need for agricultural produce such as rice that requires water for growth, the optimal consumption of this valuable liquid is important. Unfortunately, the traditional use of water by humans for agricultural purposes contradicts the concept of optimal consumption. Therefore, designing and implementing a mechanized irrigation system is of the highest importance. This system includes hardware equipment such as liquid altimeter sensors, valves and pumps which have a failure phenomenon as an integral part, causing faults in the system. Naturally, these faults occur at probable time intervals, and the probability function with exponential distribution is used to simulate this interval. Thus, before the implementation of such high-cost systems, its evaluation is essential during the design phase.

The proposed approach included two main steps: offline and online. The offline phase included the simulation of the studied system (i.e. the irrigation system of paddy fields) and the acquisition of a data set for training machine learning algorithms such as decision trees to detect, locate (classification) and evaluate faults. In the online phase, C5.0 decision trees trained in the offline phase were used on a stream of data generated by the system.

The proposed approach is a comprehensive online component-oriented method, which is a combination of supervised machine learning methods to investigate system faults. Each of these methods is considered a component determined by the dimensions and complexity of the case study (to discover, classify and evaluate fault tolerance). These components are placed together in the form of a process framework so that the appropriate method for each component is obtained based on comparison with other machine learning methods. As a result, depending on the conditions under study, the most efficient method is selected in the components. Before the system implementation phase, its reliability is checked by evaluating the predicted faults (in the system design phase). Therefore, this approach avoids the construction of a high-risk system. Compared to existing methods, the proposed approach is more comprehensive and has greater flexibility.

By expanding the dimensions of the problem, the model verification space grows exponentially using automata.

Unlike the existing methods that only examine one or two aspects of fault analysis such as fault detection, classification and fault-tolerance evaluation, this paper proposes a comprehensive process-oriented approach that investigates all three aspects of fault analysis concurrently.

The Grey System Theory (GST) is an emerging area of research within artificial intelligence. Since its founding in 1982, it has seen a lot of multidisciplinary applications. In just a short period, it has garnered some considerable strengths. Based on the 1987–2021 data collected from the Web of Science (WoS), the current study reports the advancement of the GST.

Research papers utilizing the GST in the fields of economics and education were retrieved from the Web of Science (WoS) platform using a set of predetermined keywords. In the final stage of the process, the papers that underwent analysis were manually chosen, with selection criteria based on the information presented in the titles and abstracts.

The study identifies prominent authors, institutions, publications and journals closely associated with the subject. In terms of authors, two major clusters are identified around Liu SF and Wang ZX, while the institution with the highest number of publications is Nanjing University of Aeronautics and Astronautics. Moreover, significant keywords, trends and research directions have been extracted and analyzed. Additionally, the study highlights the regions where the theory holds substantial influence.

The study is subject to certain limitations stemming from factors such as the language employed in the chosen literature, the papers included within the Web of Science (WoS) database, the designation of works categorized as “articles” in the database, the specific selection of keywords and keyword combinations, and the meticulous manual process employed for paper selection. While the manual selection process itself is not inherently limiting, it demands a greater investment of time and meticulous attention, contributing to the overall limitations of the study.

The significance of the study extends not only to scholars and practitioners but also to readers who observe the development of emerging scientific disciplines.

The analysis of trends revealed a growing emphasis on the application of GST in diverse domains, including supply chain management, manufacturing and economic development. Notably, the emergence of COVID-19 as a new research focal point among GST scholars is evident. The heightened interest in COVID-19 can be attributed to its global impact across various academic disciplines. However, it is improbable that this interest will persist in the long term, as the pandemic is gradually brought under control.

This bibliometric mapping study aimed to provide comprehensive insights into the global research landscape of cybernetics. Utilizing the biblioshiny function in R Studio, we conducted an analysis spanning 1958 to 2023, sourcing data from Scopus. This research focuses on key terms such as cybernetics, cybernetics systems, complex adaptive systems, viable system models (VSM), agent-based modeling, feedback loops and complexity systems.

The analysis leveraged R Studio’s biblioshiny function to perform bibliometric mapping. Keyword searches were conducted within titles, abstracts and keywords, targeting terms central to cybernetics. The timespan, 1958–2023, provides a comprehensive overview of the evolution of cybernetics-related literature. The data were extracted from Scopus to ensure a robust and widely recognized source.

The results revealed a rich and interconnected global research network in cybernetics. The word cloud analysis highlights prominent terms such as “agent-based modeling,” “complex adaptive systems,” “feedback loop,” “viable system model” and “cybernetics.” Notably, the journal Kybernetes has emerged as a focal point, with significant citations, solidifying its position as a key source within the cybernetics research domain. The bibliometric map provides visual clarity regarding the relationships between various concepts and their evolution over time.

This study contributes original insights by employing advanced bibliometric techniques in R Studio to map the cybernetics research landscape. The comprehensive analysis sheds light on the evolution of key concepts and the global collaborative networks shaping cybernetics research. The identification of influential sources, such as Kybernetes, adds value to researchers seeking to navigate and contribute to the dynamic field of cybernetics. Furthermore, this study highlights that cybernetics not only provides a useful framework for understanding and managing major economic shocks but also offers perspectives for understanding phenomena in various fields such as economics, medicine, environmental sciences and climate change.

By following the “employee-centric” approach, this study aims at identifying the impact of high-performance work systems (HPWS) on specific employee attitudinal outcomes such as work engagement, job satisfaction and affective commitment in the Indian healthcare industry.

The target population for this study includes the nurses working in large private multi-specialty tertiary care hospitals in India. Partial Least Squares Structural Equation Modelling (PLS-SEM) techniques are used on a sample of 152 nurses working in two large specialty hospitals.

In the Indian healthcare industry context, the nurse's perception of HPWS has shown a significant positive effect on their attitudinal variables such as work engagement, job satisfaction and affective commitment. When checked for mediation of work engagement and job satisfaction variables in HPWS – affective commitment relationship, nurse's job satisfaction partially mediated the relationship, but nurse's work engagement has shown no mediation effect.

This is one of the pioneering studies conducted in the Indian healthcare industry context, especially on the nurse's sample in identifying the impact of high-performance work systems on their attitudinal outcomes. Underscoring the paucity of HPWS research in the Indian healthcare industry, this study's findings will be an addition to the HPWS literature and also to the nursing research in the Indian healthcare settings.

With the emergence of the different Industry 4.0 technologies and the interconnectedness between the physical and cyber components within manufacturing systems, the manufacturing environment is becoming more susceptible to unexpected disruptions, and manufacturing systems need to be even more resilient than before. Hence, the purpose of this work is to explore how does incorporating Industry 4.0 into current manufacturing systems affects (positively or negatively) its resiliency.

A Systematic Literature Review (SLR) was performed with a focus on studying the manufacturing system’s resilience when applying Industry 4.0 technologies. The SLR is composed of four phases, which are (1) questions formulation, (2) determining an adequate search strategy, (3) publications filtering and (4) analysis and interpretation.

From the SLR results’ analysis, four potential research opportunities are proposed related to conducting additional research within the research themes in this field, considering less studied Industry 4.0 technologies or more than one technology, investigating the impact of some technologies on manufacturing system’s resilience, exploring more avenues to incorporate resiliency to preserve the state of the system, and suggesting metrics to quantify the resilience of manufacturing systems.

Although there are a number of publications discussing the resiliency of manufacturing systems, none fully investigated this topic when different Industry 4.0 technologies have been considered. In addition to determining the current research state-of-art in this relatively new research area and identifying potential future research opportunities, the main value of this work is in providing insights about this research area across three different perspectives/streams: (1) Industry 4.0 technologies, (2) resiliency and (3) manufacturing systems and their intersections.

Several conceptual works suggest that more digitalized information systems in management accounting have the potential to make this corporate function more effective. Against this backdrop, this study aims to investigate the impact of information systems quality in management accounting on the effectiveness of management control systems. Additionally, this study examines the moderating effect of process automation.

A cross-sectional survey of 125 German Mittelstand firms and hierarchical regression analyses were used for data collection and analysis.

The findings confirm the assumed positive effect of information systems quality in management accounting on management control effectiveness. They also confirm the assumed moderating effect of process automation. The authors find that the relationship between information systems quality in management accounting and management control effectiveness is more pronounced if the firm features a higher degree of process automation.

Several earlier case studies and a few quantitative studies indicated the potentially positive effect of high-quality information systems in management accounting on management control effectiveness. To the best of the authors‘ knowledge, this study is among the first to deliver quantitative proof of this relationship in the context of German Mittelstand firms. Moreover, the authors add to this literature the moderating effect of process automation in the relationship between information systems quality in management accounting and management control effectiveness.

Given the regional heterogeneity of economic development, electricity consumption in various regions exhibits a discrepant growth pattern. The purpose of this study is to construct a grey system forecasting model with intelligent parameters for predicting provincial electricity consumption in China.

First, parameter optimization and structural expansion are simultaneously integrated into a unified grey system prediction framework, enhancing its adaptive capabilities. Second, by setting the minimum simulation percentage error as the optimization goal, the authors apply the particle swarm optimization (PSO) algorithm to search for the optimal grey generation order and background value coefficient. Third, to assess the performance across diverse power consumption systems, the authors use two electricity consumption cases and select eight other benchmark models to analyze the simulation and prediction errors. Further, the authors conduct simulations and trend predictions using data from all 31 provinces in China, analyzing and predicting the development trends in electricity consumption for each province from 2021 to 2026.

The study identifies significant heterogeneity in the development trends of electricity consumption systems among diverse provinces in China. The grey prediction model, optimized with multiple intelligent parameters, demonstrates superior adaptability and dynamic adjustment capabilities compared to traditional fixed-parameter models. Outperforming benchmark models across various evaluation indicators such as root mean square error (RMSE), average percentage error and Theil’s index, the new model establishes its robustness in predicting electricity system behavior.

Acknowledging the limitations of traditional grey prediction models in capturing diverse growth patterns under fixed-generation orders, single structures and unadjustable background values, this study proposes a fractional grey intelligent prediction model with multiple parameter optimization. By incorporating multiple parameter optimizations and structure expansion, it substantiates the model’s superiority in forecasting provincial electricity consumption.

Innovation is vital for sustainable regional development. Government is generally not a source of innovation per se, but the authors shows that by establishing and funding an industrial innovation ecosystem, it can create fertile conditions for research institutions to introduce innovative technologies into industry and for industry to introduce its gaps and needs to motivate and direct academic research. This paper aims to present a case study of the Jiangsu Industrial Technology Research Institute (JITRI) as a “triple helix” collaboration model engaging Industry-University-Research (IUR) institutions. The authors aim to provide a fresh perspective on constructing innovation ecosystems, promoting value creation and advancing the adoption of industrial technology.

Taking JITRI as a case study, this research examines its innovative approaches to interfacing with IUR organizations within China’s Yangtze Delta region. The authors propose a multilayered framework where JITRI serves as the core, facilitating the formation of a robust innovation ecosystem with diverse IUR entities.

This framework comprises three layers: core, platform and support. JITRI acts as the central nexus, binding these elements together and fostering a cohesive innovation ecosystem. By analyzing the operational mechanisms of the Jiangsu Provincial innovation system, the authors gain valuable insights into how JITRI bridges the gap between academia and industry. This facilitates the efficient commercialization of technologies. The success of the JITRI approach presents a compelling model for emulation by other provincial innovation ecosystems seeking to enhance their innovation capabilities.

This study enriches the ongoing conversation on innovation ecosystems, proposing novel avenues for further research. However, the field requires continuous monitoring through longitudinal studies. Given the long-term nature of such initiatives, the full impact of this approach might only be realized over several decades.

JITRI aims to create a robust and innovative provincial innovation ecosystem through its focus on IUR collaboration. This unique approach offers valuable insights and ideas for fostering the development of thriving innovation ecosystems in other provinces. These insights encompass new perspectives on innovation ecosystem development, value creation and industrial advancement.

This study pioneers the use of the JITRI system as a case study, offering valuable insights with potential application to innovation ecosystems across China and globally.

Vietnam has repositioned itself from a war-torn country to a popular tourist destination. Although research on Vietnam tourism has grown in number, a macro analysis of national tourism governance and policies has largely been missing.

This synthesis paper offers a systemic analysis of Vietnam’s tourism accommodating intensified government intervention and dramatic market changes in recent decades. The authors offer a chronological analysis of tourism development along with the major political and economic turns of the country.

The patterns of tourism development reflect a compromise between centralization and decentralization of the governance system and a trade-off between economic and social objectives of development. Balancing these opposites, the internal strength of the domestic market and the resilience of communities and businesses become key assets for growth in circumstances where the socialist market economy continues to inform the current and future development of the industry.

Although the case of Vietnam is unique, the adaptive mechanism of the tourism industry highlighted in this paper offers a useful lesson for other developing countries. The research addresses tourism in the political economy in developing countries, which is valuable for researchers, policy analysts as well as practitioners in tourism.

The practical contribution of the study is derived from authors’ academic and industrial backgrounds. Findings from the study serve as a useful reference for those who embark on the study of tourism governance and policy-making in developing countries and problems associated with the economic transitional process. Those problems of the disparity between centralization and decentralization of the political system might not be only significant in Vietnam, but also prevail in developing countries. Thus, this study offers a point of departure for future empirical and comparative research on the kindship of tourism and political economy in a full scale.

The transitional economy as viewed through the tourism industry is prominently presented in the “evolutionary” approach to the transitional economy, which exhibits several unique features: the transition from a centrally planned (command) economy to a market economy and the manifestations of a socialist orientation in the modern economic management system (Vuong et al., 2019). While data from this study is mainly illustrative of the first point, the transition from a planned economy to a market economy, the second characteristic, the manifestation of a social orientation has only slightly been addressed and will need further elaboration in a future study. While Vietnam’s tourism positions itself in a socialist market-oriented economy might set a unique case, the study highlights the politics of tourism is shaped by the politico-economic system. The authors conclude that the adaptation of Vietnam tourism to a socialist market-orientated economy is better perceived as a social evolution achievement rather than a feature of capitalism.

The latest study on tourism governance (Bui et al., 2022) has outlined the evolution of the tourism administrative system and markets in the country; however, linkages of tourism to the broader political economic system have yet to be addressed. Addressing this gap, the authors carry out analysis of policies and governance from the insider’s viewpoint, when team members have been involved in numerous tourism planning and development projects, both on international and national scales. The practical experience along with thorough review of literature and statistical data contributes to shaping a fresh understanding of tourism in a transitional economy.

这篇综述对越南旅游业进行了系统分析, 包括近几十年来不断增强的政府干预以及巨大的市场变化。作者根据时间顺序分析了旅游业的发展以及该国的主要政治及经济的转变。此外, 政策文件的内容分析及旅游市场分析进一步说明了政治经济体系对旅游治理及政策的影响。

越南已将自己从一个饱受战争的国家重新定位成备受欢迎的旅游目的地。尽管对越南旅游业的研究不断增多, 但对国家旅游治理和政策的宏观分析却被之前的探究所忽略。此研究通过展示越南转型经济中的旅游治理模式连接了两个学科, 并且丰富了政治经济学和旅游学的文献。

旅游政策和市场分析反应了治理体系集权与分权之间的折中以及经济和社会发展目标之间的权衡。国内市场的内在优势以及社区及企业的韧性可以成为成长的关键资产来平衡这些对立面, 同时社会主义市场经济将继续影响产业的当前及未来的发展。因此我们的结论是, 越南旅游业适应社会主义市场经济应该被视为社会进化的成就, 而不是资本主义的特征。

考虑到一篇文章所能解决的问题有限, 作者无法就转型经济与中国进行比较研究。我们的研究为未来亚洲旅游与政治经济之间联系的实证和比较研究提供了一个出发点。

研究结果为发展中国家旅游治理和政策制定研究提供了有益的参考。

研究结果对于发展中国家旅游治理及政策制定研究具有重要参考意义。这项研究的成果对于发展中国家的旅游政策分析师, 特别是亚洲的研究人员来说很有价值。

当前的研究弥补了政治经济学中的一个研究不足, 即马克思主义学说及其与旅游业的对话。知识转移是本研究的一个亮点, 它源自对国家政治经济议程中的旅游治理的批判性分析。

Vietnam ha pasado de ser un país devastado por la guerra a convertirse en un popular destino turístico. Aunque la investigación sobre el turismo en Vietnam ha crecido en número, ha faltado en gran medida un macroanálisis de la gobernanza y las políticas turísticas nacionales. Nuestra investigación ha enriquecido la literatura tanto de la economía política como del turismo tendiendo un puente entre ambas disciplinas al presentar las pautas de la gobernanza del turismo en la economía de transición de Vietnam.

Este documento de síntesis ofrece un análisis sistemático del turismo de Vietnam que abarca la intensificación de la intervención gubernamental y los drásticos cambios del mercado en las últimas décadas. Los autores ofrecen un análisis cronológico del desarrollo del turismo junto con los principales giros políticos y económicos del país. Además, el análisis del contenido de los documentos políticos y el análisis del mercado turístico ilustran mejor las repercusiones de los sistemas político-económicos en la gobernanza y las políticas turísticas.

Las políticas turísticas y el análisis del mercado revelan un compromiso entre la centralización y la descentralización del sistema de gobernanza y un compromiso entre los objetivos económicos y sociales del desarrollo. Al equilibrar estos opuestos, la fuerza interna del mercado nacional y la resistencia de las comunidades y las empresas se convierten en activos clave para el crecimiento en unas circunstancias en las que la economía de mercado socialista sigue informando el desarrollo actual y futuro de la industria. Concluimos que la adaptación del turismo vietnamita a una economía socialista orientada al mercado se percibe mejor como un logro de la evolución social que como una característica del capitalismo.

Dentro del limitado abanico de cuestiones que podrían abordarse en un solo artículo, los autores no pueden establecer un estudio comparativo con China, en lo que respecta a la economía de transición. Nuestro estudio ofrece un punto de partida para futuras investigaciones empíricas y comparativas sobre la conexión entre turismo y economía política en Asia.

Las conclusiones del estudio sirven de referencia útil para quienes se embarcan en el estudio de la gobernanza y la formulación de políticas turísticas en los países en desarrollo.

Los resultados de la investigación son valiosos para los investigadores del sudeste asiático en particular y para los analistas de la política turística del mundo en desarrollo en general.

La presente investigación contribuye a un área poco investigada de la economía política, a saber, la doctrina marxista y su diálogo con el turismo. La transferencia de conocimientos es un aspecto destacado de esta investigación, que se ha derivado de un análisis crítico de la gobernanza del turismo en la agenda económica política nacional.

The increased capital requirements and the implementation of new liquidity standards under Basel III sparked various concerns among researchers, academics and other stakeholders. The question is whether Basel III regulation is ideal, that is, adequate to deal with a crisis, such as the 2007–2009 global financial crisis? The purpose of this paper is threefold: First, perform a stress testing exercise on the US banking sector, while examining liquidity and solvency risk indicators jointly under the Basel III regulatory framework. Second, allow the study to cover the post-crisis period, while referring to key Basel III regulatory requirements. And third, focus on the resilience of domestic systemically important banks (D-SIBs), which are supposed to support the US financial system in times of stress and therefore whose failure causes the entire financial system to fail.

The authors used a sample of the 24 largest US banks observed over the period Q1-2015 to Q1-2021 and a scenario-based vector autoregressive conditional forecasting approach.

The authors found that the model successfully produces accurate forecasts and simulates the responses of the solvency and liquidity indicators to different real and historical macroeconomic shocks. The authors also found that the US banking sector is resilient and can withstand both historical and hypothetical macroeconomic shocks because of its compliance with the Basel III capital and liquidity regulations, which consist of encouraging banks to hold high-quality liquid assets and stable funding resources and to strengthen their capital, which absorbs the losses incurred in a crisis.

The authors developed a framework for testing the resilience of the US banking sector under macroeconomic shocks, while examining liquidity and solvency risk indicators jointly under Basel III regulatory framework, a point not yet well studied elsewhere, and most studies on this subject are based on precrisis data. The authors also focused on the resilience of D-SIBs, whose failure causes the failure of the entire financial system, which previous studies have failed to examine.