From an ecosystem perspective, mergers and acquisitions (M&A) are one of the key paths for firms to foster complementary sectors and gain complementary assets. From the perspective of sustainable development, M&A can reallocate resources from target to asset to achieve better synergy and prolong the operation of a merged firm. However, M&A activities are characterized by high risk due to the high cost and uncertainty. Thus, a prediction model of M&A decisions is valuable for firms’ strategy design from an ecosystem and sustainable development perspective. By adopting a machine learning technique, this study measured the cross-border M&A decisions by analyzing firm-level cross-sectional data of the global financial marketplace under ecosystem mapping for the application of various country, deal and firm-level indicators related to sustainable development. Our paper can support the hypotheses of corporate governance, ecosystem stakeholder theory, ecosystem risk and institution theory in explaining that firms can increase their success rate of M&A to achieve sustainable development. Methodologically, we used AdaBoost to train several weak classifiers (decision trees) to achieve a strong decision-making model with a large financial transaction database of 215,160 deal activities. Results achieved 80.1% prediction accuracy by using the AdaBoost model through 10-fold cross validation. We found that differences exist on prediction features of M&A with different characteristics of sustainable development. For a robustness check, comparable results were obtained with a support vector machine (SVM) model. By analyses of the features during the cross-border M&A decision-making processing, this study is expected to contribute to the utilization of machine learning in ecosystem studies.

After experiencing the COVID-19 pandemic, the status and mechanisms of leadership, and the challenges for medical workers in terms of family–work conflicts, have caused widespread concern. In the post-pandemic era, based on role theory and the stressor-detachment model, this paper seeks to break the “black box” of negative effects that can be caused by leadership, research the mechanism and boundary conditions of those negative effects, and explore factors to reduce those negative effects. We recruited 1,010 Chinese medical workers fighting COVID-19 on the frontline. Our study results showed that there was a significant negative correlation between empowering leadership and work–family conflict, and this relationship was completely mediated by role stress, while psychological detachment moderated the relationship between role stress and work–family conflict. Moreover, psychological detachment moderated the mediating effect of empowering leadership on work–family conflict through role stress. Therefore, higher levels of psychological detachment were less conducive to medical workers' family–work conflict. This study has important theoretical significance and practical value for revealing the negative effects and mechanisms of empowering leadership and for medical workers to better deal with work–family relations.

In the era of artificial intelligence, smart clothing, as a product of the interaction between fashion clothing and intelligent technology, has increasingly attracted the attention and affection of enterprises and consumers. However, to date, there is a lack of focus on the demand of silver-haired population’s consumers for smart clothing. To adapt to the rapidly aging modern society, this paper explores the influencing factors of silver-haired population’s demand for smart clothing and proposes a corresponding consumer-consumption-need theoretical model (CCNTM) to further promote the development of the smart clothing industry. Based on literature and theoretical research, using the technology acceptance model (TAM) and functional-expressive-aesthetic consumer needs model (FEAM) as the foundation, and introducing interactivity and risk perception as new external variables, a consumer-consumption-need theoretical model containing nine variables including perceived usefulness, perceived ease of use, functionality, expressiveness, aesthetics, interactivity, risk perception, purchase attitude, and purchase intention was constructed. A questionnaire survey was conducted among the Chinese silver-haired population aged 55–65 using the Questionnaire Star platform, with a total of 560 questionnaires issued. The results show that the functionality, expressiveness, interactivity, and perceived ease of use of smart clothing significantly positively affect perceived usefulness (P < 0.01); perceived usefulness, perceived ease of use, aesthetics, and interactivity significantly positively affect the purchase attitude of the silver-haired population (P < 0.01); perceived usefulness, aesthetics, interactivity, and purchase attitude significantly positively affect the purchase intention of the silver-haired population (P < 0.01); functionality and expressiveness significantly positively affect perceived ease of use (P < 0.01); risk perception significantly negatively affects purchase attitude (P < 0.01). Through the construction and empirical study of the smart clothing consumer-consumption-need theoretical model, this paper hopes to stimulate the purchasing behavior of silver-haired population’s consumers towards smart clothing and enable them to enjoy the benefits brought by scientific and technological advancements, which to live out their golden years in comfort, also, promote the rapid development of the smart clothing industry.

Amidst technological advancements in artificial intelligence, rapid economic growth, and intense social transformation, college students are facing unprecedented challenges to their learning concentration. In the field of education, confronted with an era of scarce concentration resources, based on affective events theory and the effort-recovery model, this paper seeks to probe into the positive effects of MBSS on learning concentration, investigate the underlying mechanisms and pathways through which these positive effects occur, and explore factors that may enhance such beneficial outcomes. Using cluster random sampling, a questionnaire survey was conducted among 578 college students from three universities in Shandong province. The results indicate a significant positive correlation between MBSS and learning concentration ( β = 0.292, p < 0.01). This relationship is mediated separately by study detachment and positive emotions (mediation effect values: 0.044, 95% CI = [0.008, 0.105] and 0.059, 95% CI = [0.018, 0.118], respectively), and further explained through a chain mediating model (mediation effect value: 0.013, 95% CI = [0.004, 0.031]). This study holds important theoretical and practical implications for elucidating the positive influence and mechanisms of MBSS on learning concentration, as well as for informing policy-makers and educators in developing relevant strategies and interventions.