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Fish quarantine is a measure to prevent the entry and spread of quarantine fish pests and diseases abroad and from one area to another within Indonesia's territory. Based on these backgrounds, this study aims to identify the knowledge, knowledge management (KM) processes and knowledge management system (KMS) priority needs for quarantine fish and other fishery products measures (QMFFP) and then develop a classification model and web-based decision support system (DSS) for QMFFP decisions.

This research methodology uses combination approaches, namely, contingency factor analysis (CFA), the cross-industry standard process for data mining (CRISP-DM) and knowledge management system development life cycle (KMSDLC). The CFA for KM solution design is performed by identifying KM processes and KMS priorities. The CRISP-DM for decision classification model is done by using a decision tree algorithm. The KMSDLC is used to develop a web-based DSS.

The highest priority requirements of KM technology for QMFFP are data mining and DSS with predictive features. The main finding of this study is to show that web-based DSS (functions and outputs) can support and accelerate QMFFP decisions by regulations and field practice needs. The DSS was developed using the CTree algorithm model, which has six main attributes and eight rules.

This study proposes a novel comprehensive framework for developing DSS (combination of CFA, CRISP-DM and KMSDLC), a novel classification model resulting from comparing two decision tree algorithms and a novel web-based DSS for QMFFP.

This paper is one of the first studies to examine specificities, including limits of mindfulness at work in an African organisational context, whilst dealing with the ongoing COVID-19 pandemic. It specifically addresses the role of organisational and managerial support systems in restoring employee wellbeing, social connectedness and attachment to their organisations, in order to overcome the exclusion caused by the ongoing pandemic.

The study uses a qualitative research methodology that includes interviews as the main data source. The sample comprises of 20 entrepreneurs (organisational leaders) from Ghana and Nigeria.

The authors found that COVID-19-induced worries restricted the practice of mindfulness, and this was prevalent at the peak of the pandemic, particularly due to very tough economic conditions caused by reduction in salaries, and intensified by pre-existing general economic and social insecurities, and institutional voids in Africa. This aspect further resulted in lack of engagement and lack of commitment, which affected overall team performance and restricted employees’ mindfulness at work. Hence, quietness by employees even though can be linked to mindfulness was linked to larger psychological stress that they were facing. The authors also found leaders/manager’s emotional intelligence, social skills and organisational support systems to be helpful in such circumstances. However, their effectiveness varied among the cases.

This paper is one of the first studies to establish a link between the COVID-19 pandemic and mindfulness limitations. Moreover, it is a pioneering study specifically highlighting the damaging impact of COVID-19-induced concerns on leader–member exchange (LMX) and team–member exchange (TMX) relationships, particularly in the African context. It further brings in a unique discussion on the mitigating mechanisms of such COVID-19-induced concerns in organisations and highlights the roles of manager’s/leader’s emotional intelligence, social skills and supportive intervention patterns. Finally, the authors offer an in-depth assessment of the effectiveness of organisational interventions and supportive relational systems in restoring social connectedness following a social exclusion caused by COVID-19-induced worries.

The e-learning-based approach is critical in keeping the wheels of education turning in the face of the COVID-19 epidemic. In this scenario, analyzing the implementation of the e-learning system is required to properly grasp the needs. The purpose of this paper is to demonstrate the relationship between technical system quality, information quality, service quality, educational system quality, support system quality, learner quality, instructor quality, perceived satisfaction, perceived usefulness, e-learning system use and benefits.

This study was carried out by giving online questionnaires to students attending private institutions in Indonesia. A total of 593 students participated in the study and provided responses. The structural equation model, which is supported by the program WarpPLS7.0, is used to analyze the data.

Maintaining the quality of the technological system, the information system, the learners and the educational system can help achieve the goal of increasing perceived utility. In the meanwhile, factors such as inadequate service quality, educational system quality, support system quality and teacher quality can all pose challenges to perceived levels of satisfaction. To get the most out of e-learning apps, users' expectations about how fun, useful and easy to use they are need to be met.

This study was carried out in the midst of the COVID-19 epidemic with a restricted number of participants from Indonesian institutions of higher education. This research has the potential to be expanded into a variety of different types of higher education in the future.

The main thing that will determine whether an e-learning system model works is the quality of the learners.

The institution should think about changing the material offered in the e-learning system to make it easier for students to grasp by describing the current material and providing digital handouts of lecturers' explanations. This study expanded the e-learning system success model and applied it to the evaluation of e-learning deployment in Indonesian higher education. This study will improve student comprehension of the e-learning model and contribute to the body of knowledge about e-learning applications and technology.

The purpose of this work is to optimize the monitoring of vibrations on dynamometric test rigs for railway brakes. This is a quite demanding application considering the continuous increase of performances of high-speed trains that involve higher testing specifications for brake pads and disks.

In this work, authors propose a mixed approach in which relatively simple finite element models are used to support the optimization of a diagnostic system that is used to monitor vibration levels and rotor-dynamical behavior of the machine. The model is calibrated with experimental data recorded on the same rig that must be identified and monitored. The whole process is optimized to not interfere with normal operations of the rig, using common inertial sensor and tools and are available as standard instrumentation for this kind of applications. So at the end all the calibration activities can be performed normally without interrupting the activities of the rig introducing additional costs due to system unavailability.

Proposed approach was able to identify in a very simple and fast way the vibrational behavior of the investigated rig, also giving precious information concerning the anisotropic behavior of supports and their damping. All these data are quite difficult to be found in technical literature because they are quite sensitive to assembly tolerances and to many other factors. Dynamometric test rigs are an important application widely diffused for both road and rail vehicles. Also proposed procedure can be easily extended and generalized to a wide value of machine with horizontal rotors.

Most of the studies in literature are referred to electrical motors or turbomachines operating with relatively slow transients and constant inertial properties. For investigated machines both these conditions are not verified, making the proposed application quite unusual and original with respect to current application. At the same time, there is a wide variety of special machines that are usually marginally covered by standard testing methodologies to which the proposed approach can be successfully extended.

Exploratory search activities are ubiquitous in various information systems. Much potentially useful or even serendipitous information is discovered during the exploratory search process. Given its irreplaceable role in information systems, exploratory search has attracted growing attention from the information system community. Since few studies have methodically reviewed current publications, researchers and practitioners are unable to take full advantage of existing achievements, which, in turn, limits their progress in this field. Through a literature review, this study aims to recapitulate important research topics of exploratory search in information systems, providing a research landscape of exploratory search.

Automatic and manual searches were performed on seven reputable databases to collect relevant literature published between January 2005 and July 2023. The literature pool contains 146 primary studies on exploratory search in information system research.

This study recapitulated five important topics of exploratory search, namely, conceptual frameworks, theoretical frameworks, influencing factors, design features and evaluation metrics. Moreover, this review revealed research gaps in current studies and proposed a knowledge framework and a research agenda for future studies.

This study has important implications for beginners to quickly get a snapshot of exploratory search studies, for researchers to re-align current research or discover new interesting issues, and for practitioners to design information systems that support exploratory search.

The purpose of the study is to explore the relationship among organisation information technology support (OITS), knowledge sharing behaviour (KSB) and service innovation performance (SIP) in the context of the Indian Hospitality Industry (IHI). This study also attempts to examine the role of KSB as a mediator in the relationship between IT support and SIP and the firm age test as a moderating variable for service innovation performance.

Proposed relations are empirically examined, and the study was carried out on 115 employees from 71 randomly selected hotels situated in the major five travel destinations of Uttarakhand state of India. Initially, confirmatory factor analysis was performed to validate the construct, afterword structural equation modeling (SEM)-Path analysis was accomplished. The researcher examines the mediation and moderation relations of the variables through statistical tests executed with the help of AMOS 24 and SPSS 26.

The study result indicated that organisation IT support has a positive influence on knowledge sharing and SIP. The mediation result findings showed KSB is partially mediated between OITS and SIP. Sequentially, firm age moderation found the statistical results shown significant difference in young and old hotels.

This study only covers the aspect of the “knowledge sharing behaviour” dimension among the major organizations’ IT support capabilities and examined both variables that might be anticipated in SIP. Considering this limitation, new areas of research investigation are open to future researchers.

The study has both theoretical and managerial implications for academicians, practitioners and researchers. An attempt to conceptualise detailed insights on organisational IT support adaptation and KSB enhancement, which further leads to lifting SIP. Moreover, the study recommended for professionals to implement KM practices and mobilise the knowledge resources optimally to achieve better organizational outcomes.

The study attempts to delineate the proposed relationship and provides valuable insights for practitioners and academicians by including the knowledge sharing dimension to improve the SIP context of the IHI.

The purpose of this review paper was identifying barriers to the use of telemedicine systems in primary health-care individual level among professionals.

This study used Scopus and PubMed databases for scientific records identification. A systematic review of the literature structured by PRISMA guidelines was conducted on 37 included papers published between 2009 and 2019. A qualitative approach was used to synthesize insights into using telemedicine by primary care professionals.

Three barriers were identified and classified: system quality, data quality and service quality barriers. System complexity in terms of usability, system unreliability, security and privacy concerns, lack of integration and inflexibility of systems-in-use are related to system quality. Data quality barriers are data inaccuracy, data timeliness issues, data conciseness concerns and lack of data uniqueness. Finally, service reliability concerns, lack of technical support and lack of user training have been categorized as service quality barriers.

This review identified and mapped emerging themes of barriers to the use of telemedicine systems. This paper also through a new conceptualization of telemedicine use from perspectives of the primary care professionals contributes to informatics literature and system usage practices.

Current school leadership research has primarily utilized quantitative methods to explore the relationship between leadership and teacher learning. However, there is a notable gap in understanding how principals facilitate professional learning, especially in centralized educational settings. This study aims to address this gap by examining the role of school leadership in enhancing teacher professional learning within a highly centralized education system.

This qualitative case study delves into the lived experiences of 15 teachers and eight school leaders in eight primary schools in Mashhad, Iran. Through semistructured interviews, researchers employed open and axial coding to systematically explore and categorize qualitative data. The study focuses on understanding the role of principal leadership in facilitating teacher professional learning by connecting themes and sub-themes across transcripts.

Effective principals worked on the cultivation of a culture that champions perpetual personal growth and development, the nurturing of a collaborative learning community, and the provision of essential resources and support. Findings showed the pivotal role of principals in promoting teachers' self-development, facilitating idea exchange and acknowledging their efforts. Principals appeared as key to encouraging information sharing, fostering collective learning, promoting professional development, overseeing teaching practices and ensuring the availability of resources to cultivate a supportive climate in a centralized education context.

We concluded that in centralized education, leadership practices for promoting teacher learning share similarities and differences with decentralized settings. The findings offer guidance for principals in centralized systems, supporting them in facilitating teacher professional learning in their schools.

Despite its crucial role in ensuring food safety, traceability remains underutilized by small and medium-sized enterprises (SMEs), a vital component of China’s agricultural supply chain, thereby compromising the integrity of the supply chain traceability system. Therefore, this study sets out to explore the factors influencing SMEs’ adoption of traceability systems and the impact of these factors on SMEs’ intent to adopt such systems. Furthermore, the study presents a model to deepen understanding of system adoption in SMEs and provides a simulation demonstrating the evolutionary trajectory of adoption behavior.

This study considers the pivotal aspects of system adoption in SMEs, aiming to identify the influential factors through a grounded theory-based case study. Concurrently, it seeks to develop a mathematical model for SMEs’ adoption patterns and simulate the evolution of SMEs’ adoption behaviors using the Q-learning algorithm.

The adoption of traceability among SMEs is significantly influenced by factors such as system attributes, SMEs’ capability endowment, environmental factors and policy support and control. However, aspects of the SMEs’ capability endowment, specifically their learning rate and decay rate, have minimal impact on the adoption process. Furthermore, group pressure can expedite the attainment of an equilibrium state, wherein all SMEs adopt the system.

This study fills the existing knowledge gap about the adoption of traceability by SMEs in China’s agricultural supply chain. This study represents the pioneer study that identifies the factors influencing SMEs’ adoption and examines the effects of these factors on their traceability adoption, employing a multi-methodological approach that incorporates grounded theory, mathematical modeling and the Q-learning algorithm.

Large optical mirror processing systems (LOMPSs) consist of multiple subrobots, and correlated disturbance terms between these robots often lead to reduced processing accuracy. This abstract introduces a novel approach, the nonlinear subsystem adaptive dispersed fuzzy compensation control (ADFCC) method, aimed at enhancing the precision of LOMPSs.

The ADFCC model for LOMPS is developed through a nonlinear fuzzy adaptive algorithm. This model incorporates control parameters and disturbance terms (such as those arising from the external environment, friction and correlation) between subsystems to facilitate ADFCC. Error analysis is performed using the subsystem output parameters, and the resulting errors are used as feedback for compensation control.

Experimental analysis is conducted, specifically under the commonly used concentric circle processing trajectory in LOMPS. This analysis validates the effectiveness of the control model in enhancing processing accuracy.

The ADFCC strategy is demonstrated to significantly improve the accuracy of LOMPS output, offering a promising solution to the problem of correlated disturbances. This work holds the potential to benefit a wide range of practical applications.