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Drawing on the challenge–hindrance stressor framework and the “too-much-of-a-good-thing” principle, this study examined the curvilinear effects of two emic social challenge stressors (guanxi beliefs and participative decision-making (PDM)) and the moderating effect of an etic social hindrance stressor (perceived organizational politics) on Hong Kong and United States nurses’ job satisfaction.

A quantitative survey method was implemented, with the data provided by 355 Hong Kong nurses and 116 United States nurses. Structural equation modeling was used to examine the degree of measurement equivalence across Hong Kong and US nurses. The proposed model and the research questions were tested using nonlinear structural equation modeling analyses.

The results show that while guanxi beliefs only showed an inverted U-shaped relation on Hong Kong nurses’ job satisfaction, PDM had an inverted U-shaped relation with both Hong Kong and United States nurses’ job satisfaction. The authors also found that Hong Kong nurses experienced the highest job satisfaction when their guanxi beliefs and perceived organization politics were both high.

The results add to the comprehension of the nuances of the often-held assumption of linearity in organizational sciences and support the speculation of social stressors-outcomes linkages.

Managers need to recognize that while the nurturing and development of effective relationships with employees via social interaction are important, managers also need to be aware that too much guanxi and PDM may lead employees to feel overwhelmed with expectations of reciprocity and reconciliation to such an extent that they suffer adverse outcomes and become dissatisfied with their jobs.

First, the authors found that influences of guanxi beliefs and PDM are not purely linear and that previous research may have neglected the curvilinear nature of their influences on job satisfaction. Second, the authors echo researchers’ call to consider an organization’s political context to fully understand employees’ attitudes and reactions toward social interactions at work. Third, the authors examine boundary conditions of curvilinear relationships to understand the delicate dynamics.

This paper investigates the interrelationships of destination social responsibility (DSR), emotional attachment, self-congruity, experiential satisfaction and environmentally responsible behavior (ERB).

Using a sample of 294 visitors to the Guangzhou Zoo in China, this study tested the aforementioned relationships via structural equation modeling.

Emotional attachment mediates the effect of DSR on experiential satisfaction, while emotional attachment and experiential satisfaction mediate the effect of DSR on ERB sequentially. Moreover, self-congruity moderates the relationship between DSR and emotional attachment.

The management of zoos should use DSR communication strategies more proactively to make visitors become well-aware of their economic, philanthropic, environmental and social activities in the host community. This will result in many positive consequences, including visitors’ ERBs.

The study adds to the DSR literature by introducing multiple mediation mechanisms and paths that lead to visitors’ ERBs.

我们的论文调查了目的地社会责任 (DSR) 情感依恋、自我一致性、体验满意度和对环境负责的行为 (ERB) 之间的相互关系。

我们的研究以中国广州动物园的 294 名游客为样本, 通过结构方程模型测试了上述关系。

情感依恋介导 DSR 对体验满意度的影响, 而情感依恋和体验满意度依次介导 DSR 对 ERB 的影响。 此外, 自我一致性调节 DSR 与情感依恋之间的关系。

动物园的管理层应该更积极地使用 DSR 沟通策略, 让游客充分了解他们在东道社区的经济、慈善、环境和社会活动。 这将带来许多积极的后果, 包括访客的 ERB。

该研究通过引入多种调解机制和导致访客 ERB 的路径增加了 DSR 文献。

nuestro artículo investiga las interrelaciones de la responsabilidad social del destino (DSR), el apego emocional, la autocongruencia, la satisfacción experiencial y el comportamiento ambientalmente responsable (ERB).

utilizando una muestra de 294 visitantes del zoológico de Guangzhou en China, nuestro estudio probó las relaciones antes mencionadas a través del modelo de ecuaciones estructurales.

el apego emocional media el efecto de DSR en la satisfacción experiencial, mientras que el apego emocional y la satisfacción experiencial median el efecto de DSR en ERB secuencialmente. Además, la autocongruencia modera la relación entre DSR y apego emocional.

la administración de los zoológicos debe utilizar estrategias de comunicación de DSR de manera más proactiva para que los visitantes estén bien informados sobre sus actividades económicas, filantrópicas, ambientales y sociales en la comunidad anfitriona. Esto tendrá muchas consecuencias positivas, incluidos los ERB de los visitantes.

el estudio se suma a la literatura de DSR al presentar múltiples mecanismos de mediación y caminos que conducen a los ERB de los visitantes.

The digital transformation revolution has brought outstanding changes to business organizations, especially in the digital accounting transformation domain. Consequently, the purpose of this study is to explore the important role of digital accounting transformation in improving business performance in the context of the banking industry.

Data were collected through a questionnaire from the Jordanian bank sector with a sample of 190 respondents. Partial least squares structural equation modeling (PLS-SEM) was used to analyze the collected data and test the hypotheses.

The results have shown that the adoption of digital accounting, adoption of FinTech innovation and technological competition are the major drivers for improving business performance. All direct paths leading to improving business performance were found to be significant in the hypothesized directions, while technological savvy was found to indirectly affect the relationship between (the adoption of digital accounting and FinTech innovation) and improving business performance.

The current study is differentiated from other studies by developing a theoretical research model to incorporate the adoption of digital accounting, adoption of FinTech innovation, technological competition, technological savvy and business performance in the Jordanian context under the digital transformation revolution. For practitioners, the findings provide policymakers with meaningful insight for organizations looking to adopt these digital technologies for improved business performance.

This study aims to investigate how job self-efficacy mediates the relationship between online knowledge sharing and employee innovation. To fully understand this relationship, this study also tests the moderating role of an innovative climate.

This study gathered data from 353 full-time employees working at information technology companies in Vietnam. This study used structural equation modeling to test hypotheses.

The results showed that online knowledge sharing positively influenced employee innovation directly and indirectly through job self-efficacy. Moreover, innovative climate positively affected employee innovation as well as moderated the nexus between online knowledge sharing and employee innovation.

First, this study provides further evidence that job self-efficacy plays a mediator linking online knowledge sharing with employee innovation. Second, this paper confirms that an innovative climate can play a mixed moderator that not only influences employee innovation but also moderates the association between online knowledge sharing and employee innovation.

Pandemics are a serious challenge for humanity, as their social and economic impacts can be tremendous. This study aims to understand how innovation based in the sharing economy (SE) business models can contribute to overcoming the challenges arising from the Covid-19 pandemic.

Following a netnographic approach, the authors studied the computer-mediated social interactions of internet-based virtual innovation communities.

This study found that the SE business models contribute to overcome the challenges of the Covid-19 pandemic by redistributing idle resources to lessen the impacts of confinement. This was achieved through process innovations and an innovative use of the network, which enabled fast-open and decentralized innovation processes, and quick implementation of innovations. This innovation process is based on a decentralized decision-making approach, clear rules, informal relationship among community members and open communication channels, as well as in evasive strategies to avoid facing challenges, institutional restrictions and barriers in the adoption of innovations.

This study was limited to a virtual innovation community of highly specialized and educated experts and nine community projects focused on institutional contexts of a developed country. Future research should focus on the institutional contexts of less specialized communities and developing countries and study other community innovation projects in pandemics to understand the processes of fast-open, decentralized and evasive innovation and the importance of relational capabilities for innovation in digital contexts.

The findings can guide innovation managers and public policymakers in implementing effective strategies and policies to overcome pandemic challenges using SE business models. This research also provides important insights into the types and processes of innovation in organizations that create solutions to overcome social and business challenges during pandemics. In addition, this study highlights the contributions of netnographic approaches to conducting research on innovation and in pandemic periods when measures of confinement are in place.

This study uses an innovative framework to map the types of innovation and highlights two different types of innovation processes.

The purpose of this study is to identify the relationship between collaborative innovation and the financial performance of information technology (IT) firms through the mediating role of strategic agility and absorptive capacity. Customer knowledge management capability (CKMC) is also explored as a potential moderator.

Data were collected from 300 respondents working in different small to medium IT enterprises operating in different cities around Portugal. The simple random sampling method was used for data collection, and Smart partial least squares-structural equation modeling (Smart PLS-SEM version 3.2.8) was used to test the hypotheses.

The findings demonstrate that collaborative innovation contributes significantly to the financial performance of IT firms in Portugal. The results also indicate that absorptive capacity and strategic agility both positively and significantly affect the relationship between collaborative innovation and firms’ financial performance. However, while the moderating role of CKMC has a positive and significant effect on the relation between collaborative innovation and strategic agility, CKMC insignificantly moderates the relation between collaborative innovation and absorptive capacity.

Few studies have explicitly connected collaborative innovation with firms’ financial performance; this study attempts to fill that gap. Moreover, this research investigates the mediating role of strategic agility and absorptive capacity in the relationship between collaborative innovation and financial performance. Finally, by discussing the moderating effect of CKMC, which leads to enhanced financial performance, this study proposes that when complex and unpredictable situations occur, managers should focus on customer-oriented strategies and innovation at the same time to outpace their competitors.

The purpose of this study is to establish a method for accurately extracting torch and seam features. This will improve the quality of narrow gap welding. An adaptive deflection correction system based on passive light vision sensors was designed using the Halcon software from MVtec Germany as a platform.

This paper proposes an adaptive correction system for welding guns and seams divided into image calibration and feature extraction. In the image calibration method, the field of view distortion because of the position of the camera is resolved using image calibration techniques. In the feature extraction method, clear features of the weld gun and weld seam are accurately extracted after processing using algorithms such as impact filtering, subpixel (XLD), Gaussian Laplacian and sense region for the weld gun and weld seam. The gun and weld seam centers are accurately fitted using least squares. After calculating the deviation values, the error values are monitored, and error correction is achieved by programmable logic controller (PLC) control. Finally, experimental verification and analysis of the tracking errors are carried out.

The results show that the system achieves great results in dealing with camera aberrations. Weld gun features can be effectively and accurately identified. The difference between a scratch and a weld is effectively distinguished. The system accurately detects the center features of the torch and weld and controls the correction error to within 0.3mm.

An adaptive correction system based on a passive light vision sensor is designed which corrects the field-of-view distortion caused by the camera’s position deviation. Differences in features between scratches and welds are distinguished, and image features are effectively extracted. The final system weld error is controlled to 0.3 mm.

The purpose of this study is to identify the main perspectives and trends in educational data mining (EDM) in the e-learning environment from a managerial perspective.

This paper proposes a systematic literature review to identify the main perspectives and trends in EDM in the e-learning environment from a managerial perspective. The study domain of this review is restricted by the educational concepts of e-learning and management. The search for bibliographic material considered articles published in journals and papers published in conferences from 1994 to 2023, totaling 30 years of research in EDM.

From this review, it was observed that managers have been concerned about the effectiveness of the platform used by students as it contains the entire learning process and all the interactions performed, which enable the generation of information. From the data collected on these platforms, there are improvements and inferences that can be made about the actions of educators and human tutors (or automatic tutoring systems), curricular optimization or changes related to course content, proposal of evaluation criteria and also increase the understanding of different learning styles.

This review was conducted from the perspective of the manager, who is responsible for the direction of an institution of higher education, to assist the administration in creating strategies for the use of data mining to improve the learning process. To the best of the authors’ knowledge, this review is original because other contributions do not focus on the manager.

This paper aims to investigate the impact of political stability on corruption by drawing upon a sample encompassing both developed and developing European and Asian countries.

The dataset, sourced from the Refinitiv database, spans from July 2014 to May 2022. Panel data techniques, specifically pooled estimation and dynamic panel data [generalized method of moments (GMM)] are employed. The analysis encompasses both fixed and random effects models to capture country-specific cross-sectional effects. To validate our findings, we perform a robustness test by including in the investigation four control variables, namely poverty, type of governance, economic freedom and inflation. To test heterogeneity, the dataset is further divided into two distinct subsamples based on the countries’ locations.

Empirical findings substantiate that political stability (viewed as the risk of government destabilization) has a positive and significant impact on corruption in all analyzed samples of European and Asian countries, though some differences are observed in various subsamples. When we take into account the control variables, these analysis results are robust.

This research provided a panel data analysis with GMM, while other empirical methodologies could also be used, like the difference-in-difference approach. However, our results should be validated by extending the time and the sample to a worldwide sample and using alternative measures of corruption and political stability. Moreover, our focus was on a linear and unidirectional relationship between the considered variables, but it would be interesting to test in our further research a non-linear and bidirectional correlation between them. Furthermore, we have introduced in the robustness test only four economic variables, but to consolidate our findings, we plan to include socioeconomic and demographic variables in future studies.

These outcomes imply that authorities should be aware of the necessity of implementing anti-corruption policies designed to establish effective agencies and enforcement structures for combating systemic corruption, to improve the political environment and the quality of institutions and to apply coherent economic strategies to accelerate economic growth because higher political stability and sustainable development determine a decrease in levels of corruption.

At the microeconomic level, the survival of organizations may be in danger from new types of corruption and money laundering. Therefore, in order to prevent financial harm, the top businesses worldwide should respond to instances of corruption through strengthened supervisory procedures. This calls for the creation of a mechanism inside the code of conduct where correct reporting of suspected situations of corruption would have a prompt procedure to be notified of. To avoid corruption in operational procedures, national plans and policies should be developed by government officials, executives and legislators on a national level, as well as by senior management and the board of directors on an organizational level. This might lower organizations' extra corruption-related expenses, assure economic growth and improve global welfare.

A novel feature of our research resides in its broad examination of a sizable sample of European and Asian countries regarding the nexus between corruption and political stability. The paper also investigates a less explored topic in economic literature, namely the impact of political stability on corruption. Furthermore, the study depicts policy recommendations, outlining effective and reasonable measures aimed at improving the political landscape and combating corruption.

In recent years, there has been growing interest in the use of stainless steel (SS) in reinforced concrete (RC) structures due to its distinctive corrosion resistance and excellent mechanical properties. To ensure effective synergy between SS and concrete, it is necessary to develop a time-saving approach to accurately determine the ultimate bond strength τ_u between the two materials in RC structures.

Three robust machine learning (ML) models, including support vector regression (SVR), random forest (RF) and extreme gradient boosting (XGBoost), are employed to predict τ_u between ribbed SS and concrete. Model hyperparameters are fine-tuned using Bayesian optimization (BO) with 10-fold cross-validation. The interpretable techniques including partial dependence plots (PDPs) and Shapley additive explanation (SHAP) are also utilized to figure out the relationship between input features and output for the best model.

Among the three ML models, BO-XGBoost exhibits the strongest generalization and highest accuracy in estimating τ_u. According to SHAP value-based feature importance, compressive strength of concrete f_c emerges as the most prominent feature, followed by concrete cover thickness c, while the embedment length to diameter ratio l/d, and the diameter d for SS are deemed less important features. Properly increasing c and f_c can enhance τ_u between ribbed SS and concrete.

An online graphical user interface (GUI) has been developed based on BO-XGBoost to estimate τ_u. This tool can be utilized in structural design of RC structures with ribbed SS as reinforcement.