Unravelling Morphological and Topological Energy Contributions of Metal Nanoparticles

Identifying the Structure of Supported Metal Catalysts Using Vibrational Fingerprints from Ab Initio Nanoscale Models

Identifying active sites of supported noble metal nanocatalysts remains challenging, since their size and shape undergo changes depending on the support, temperature, and gas mixture composition. Herein, the anharmonic infrared spectrum of adsorbed CO is simulated using density functional theory (DFT) to gain insight into the nature of Pd nanoparticles (NPs) supported on ceria. The authors systematically determine how the simulated infrared spectra are affected by CO coverage, NP size (0.5-1.5 nm), NP morphology (octahedral, icosahedral), and metal-support contact angle, by exploring a diversity of realistic models inspired by ab initio molecular dynamics. The simulated spectra are then used as a spectroscopic fingerprint to characterize nanoparticles in a real catalyst, by comparison with in-situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) experiments. Truncated octahedral NPs with an acute Pd-ceria angle reproduce most of the measurements. In particular, the authors isolate features characteristic of CO adsorbed at the metal-support interface appearing at low frequencies, both seen in simulation and experiment. This work illustrates the strong need for realistic models to provide a robust description of the active sites, especially at the interface of supported metal nanocatalysts, which can be highly dynamic and evolve considerably during reaction.

Machine Learning-Driven Discovery of Key Descriptors for CO2 Activation over Two-Dimensional Transition Metal Carbides and Nitrides

Fusing high-throughput quantum mechanical screening techniques with modern artificial intelligence strategies is among the most fundamental ─yet revolutionary─ science activities, capable of opening new horizons in catalyst discovery. Here, we apply this strategy to the process of finding appropriate key descriptors for CO₂ activation over two-dimensional transition metal (TM) carbides/nitrides (MXenes). Various machine learning (ML) models are developed to screen over 114 pure and defective MXenes, where the random forest regressor (RFR) ML scheme exhibits the best predictive performance for the CO₂ adsorption energy, with a mean absolute error ± standard deviation of 0.16 ± 0.01 and 0.42 ± 0.06 eV for training and test data sets, respectively. Feature importance analysis revealed d-band center (ε_d), surface metal electronegativity (χ_M), and valence electron number of metal atoms (M_V) as key descriptors for CO₂ activation. These findings furnish a fundamental basis for designing novel MXene-based catalysts through the prediction of potential indicators for CO₂ activation and their posterior usage.

CEO Relational Leadership and Product Innovation Performance: The Roles of TMT Behavior and Characteristics

CEO leadership is considered a critical antecedent of product innovation performance, but the relational aspect of leadership has been largely neglected in this area. Drawing on upper echelons theory and relational leadership literature, this study explores whether, how, and when CEO relational leadership influences product innovation performance. Specifically, we analyze the underlying mechanism of TMT (top management team) voice behavior and two boundary conditions—TMT educational level and TMT age. Based on multi-source and multi-wave data on 105 Chinese firms, this study finds that CEO relational leadership plays an important role in promoting product innovation performance through the intervening mechanism of TMT voice behavior. Furthermore, the positive relationship between CEO relational leadership and TMT voice behavior is stronger in TMTs with higher educational level and lower age. This study contributes to the existing literature by empirically examining the under-investigated relationship between CEO relational leadership and product innovation performance, and by disentangling the underlying mechanism and boundary conditions.

Validation of Polish Version of Dispositional Flow Scale-2 and Flow State Scale-2 Questionnaires

The aim of this study is to evaluate the psychometric properties of the Polish version of the Dispositional Flow Scale-2 (DFS-2) and Flow State Scale-2 (FSS-2), for use with Polish adults and young adults. Currently, there are no tools that would allow us to study flow among Polish speakers. At the same time, due to the great interest in flow and its potential importance for effectiveness, cooperation, and learning, it is worth ensuring that reliable validated measurement questionnaires are available for people studying the Polish population. Study participants completed 856 questionnaires, of which 496 individuals (with an average age of 36.31 years) participated in the DFS-2 study and 360 individuals (with an average age of 33.46 years) participated in the FSS-2 study. The maximum likelihood estimator (MLR) was selected for the CFA analysis. Model fit was assessed using: χ2, comparative fit index (CFI), Tucker-Lewis index (TLI), and standardized root mean square of residuals (SRMR), and root mean square of approximation error (RMSEA). For both questionnaires, formative first-level models with nine factors and second-level models with nine factors loaded on a higher-order flow factor were compared using the Satorra-Bentler Scaled difference χ2 test. The ω coefficient was used to estimate the reliability of the FFS-2 and DFS-2 models tested in the CFA method. Confirmatory factor analysis of both DFS-2 structural models showed satisfactory model fit. Most of the fit indices for the hierarchical 2nd order FSS-2 model presented satisfactory values, except for SRMR. Both DFS-2 and FSS-2 factors tested in the analysis showed good reliability (ω ≥ 0.7). Our findings confirmed the reliability and validity of the Polish versions of DFS-2 and FSS-2 scales. The scales are reliable when applied to Polish adults and young adults.

New Schemes for Investment in of Small and Medium-Sized Enterprises of China: Role of Access to Finance, Innovation, and Sustainability

Firm innovation relies heavily on financing, which is why it is a hot topic in the fields of finance and innovation management. Organizations can make strategic investments in production factors to develop competitive advantages because they have access to financial resources. This study investigated how financial literacy, innovativeness, and environmental sustainability influence the sustainability of small and medium-sized enterprises (SMEs). This was set as the primary objective in order to better understand the nature of the impact of financial literacy and innovation on the sustainability of SME firms. To test the hypotheses, structural equation modeling (SEM) was applied using data collected from 300 small businesses firms in China. The results revealed that financial literacy and innovativeness significantly influence small firms’ sustainability. Additionally, social inclusion significantly affects small firms’ sustainability, and sequentially has a significant effect on their performance. Research findings suggested that small businesses incorporate sustainability models into their operations and enhance financial knowledge in order to maintain sustainability.

Big Five Personality, Academic Entrepreneurial Motivation, and Academic Entrepreneurial Intention: A Research Method Based on Fuzzy Set Qualitative Comparative Analysis

Scholars are the main force behind academic entrepreneurship. The method of how to stimulate scholars’ academic entrepreneurial intention and how to further promote social and economic development are important questions for the academic community. Research on the “net effect” of the factors affecting academic entrepreneurial intention has achieved some theoretical results. However, the results that affect academic entrepreneurial intention are complex and not influenced by a single factor, but rather by the interaction between various factors. Therefore, this study used a fuzzy set qualitative comparative analysis research method to explore how various factors can affect scholars’ academic entrepreneurial intention from two dimensions: the Big Five personality traits and academic entrepreneurial motivation. Our findings showed two configurations that affect high academic entrepreneurial intention of university scholars: the openness to experience—ribbon—dominant path, and the ribbon—dominant path. Additionally, two configurations were revealed for the formation of not-high academic entrepreneurial intention: extraversion—conscientiousness—inhibition and extraversion—agreeableness—gold—hindrance paths. Moreover, this study revealed that a causal asymmetry exists between the high and the not-high academic entrepreneurial intention configurations. This study broadens the application of the fuzzy set qualitative comparative analysis method in the research of academic entrepreneurial intention and provides theoretical and practical insights for researchers and practitioners on how to effectively stimulate scholars’ academic entrepreneurial intention.

Undergraduate Students' Social Entrepreneurial Intention: The Role of Individual Environmental Responsibility and Absorptive Capacity

As social entrepreneurial intention has received increasing attention from scholars and practitioners, no clear conclusions have been drawn regarding antecedent or external factors that influence social entrepreneurial intention. This study aims to develop a structural model to shape the social entrepreneurial intention of business administration students, which involves the theory of planned behavior (i.e., attitudes, subjective norms), social capital, individual environmental responsibility, and individual absorptive capacity (i.e., potential absorptive capacity and realized absorptive capacity). Furthermore, this study regards potential absorptive capability as a multi-dimensional construct of a higher-order structure. The participants were students from business administration colleges/universities (including general universities and science and technology universities) in Taiwan. The empirical data from 969 participants were analyzed using Smart PLS 3.0 to obtain the results. The results revealed that: (1) social capital had a significant positive effect on attitudes and subjective norms; (2) attitudes, subjective norms, individual environmental responsibility, and realized absorptive capability had a positive effect on social entrepreneurial intention; however, social capital and potential absorptive capability had a negative effect. The results were discussed, and some specific recommendations for practitioners of business administration education were proposed.

Signifying the Relationship Between Psychological Factors and Turnover Intension: The Mediating Role of Work-Related Stress and Moderating Role of Job Satisfaction

Human capital plays a significant role in an organization's advancement. In recent years, emerging work-related psychological issues have become a critical factor, demanding considerable attention from management. As such, this study measures the role of job satisfaction in work-related stress and employees' turnover intentions. There is a mediating relationship between work-related stress-such as emotional exhaustion, work engagement, role conflict, and psychosocial risks-and turnover intentions. The study used primary data collection techniques to gather data and purposive sampling to analyze the data. The study's sample size consisted of 270 employees working in Chinese organizations. SmartPLS software was used to test the research hypothesis. The study results show the mediating role of work-related stress and moderating role of employees' job satisfaction. Accordingly, the study provides implications for managers, encouraging them to take the necessary steps in controlling the turnover rate by enhancing employees' morale (i.e., job satisfaction) and work engagement.

The Dark Side of Social Media: Content Effects on the Relationship Between Materialism and Consumption Behaviors

This study contributes to the emerging literature on the negative effects over consumption that social media users may develop as a consequence of being engaged on social media platforms. The authors tested materialism's direct and indirect impacts on compulsive, conspicuous, and impulsive buying, adding two novel mediators: attitudes toward social media content (SCM) and social media intensity (SMI). The study uses a convenience sample of 400 Thai social media users analyzed using structural equation modeling. The results confirmed the well-established positive relationships between materialism and each of the three-negative consumption behaviors also in the social media domain. A novel finding showed the important role played by SMI which was found to be a strong predictor of each of the three negative consumption behaviors and it was also found to significantly mediate the relationship between materialism and the three-negative consumption behaviors. An additional contribution of the study was found on the role of attitudes which, contrary to what is commonly believed, were often not significant in predicting any negative behavior.

Research on the Initiative Scientific Research and Innovation Behavior of Postgraduates: Based on the Theory of Planned Behavior

To clarify the generative mechanism and influencing factors of graduate students' willingness and behavior of initiative scientific research and innovation, this research builds a quantitative model consisting of six variables: academic interest, regulatory pressure, conditions for improving scientific research and innovation capabilities, willingness to take initiative in scientific research and innovation, the promotion of achievements in scientific research, and initiative scientific research and innovation behavior. In total, 684 valid questionnaires were distributed and collected through WeChat Moments. Descriptive statistical analysis, reliability and validity analysis, factor analysis, path analysis, and conditioning analysis were conducted using the SPSS and structural equation model (SEM). The results showed that: (1) academic interest, regulatory pressure, and conditions for improving scientific research and innovation capabilities have a positive impact on the intention of initiative scientific research and innovation, but the impact of regulatory pressure is extremely insignificant. (2) The willingness to take initiative in scientific research and innovation has a positive and significant impact on initiative scientific research and innovation behavior, and the promotion of achievements in scientific research plays a negative moderating effect. Finally, this manuscript puts forward the suggestions on how to promote the initiative scientific research and innovation behavior of postgraduate students based on the research results.

A Scoping Review of Flow Research

Flow is a gratifying state of deep involvement and absorption that individuals report when facing a challenging activity and they perceive adequate abilities to cope with it (EFRN, 2014). The flow concept was introduced by Csikszentmihalyi in 1975, and interest in flow research is growing. However, to our best knowledge, no scoping review exists that takes a systematic look at studies on flow which were published between the years 2000 and 2016. Overall, 252 studies have been included in this review. Our review (1) provides a framework to cluster flow research, (2) gives a systematic overview about existing studies and their findings, and (3) provides an overview about implications for future research. The provided framework consists of three levels of flow research. In the first “Individual” level are the categories for personality, motivation, physiology, emotion, cognition, and behavior. The second “Contextual” level contains the categories for contextual and interindividual factors and the third “Cultural” level contains cultural factors that relate to flow. Using our framework, we systematically present the findings for each category. While flow research has made progress in understanding flow, in the future, more experimental and longitudinal studies are needed to gain deeper insights into the causal structure of flow and its antecedents and consequences.

Facilitating Peer Interaction Regulation in Online Settings: The Role of Social Presence, Social Space and Sociability

A plethora of studies stress students' self-regulated learning (SRL) skills to be conditional for successful learning in school and beyond. In general, self-regulated learners are actively engaged in constructing their own understanding also including the regulation of contextual features in the environment. Within the contextual features, the regulation of peer interaction is necessary, because college courses increasingly require peer learning. This goes along with the increasing interest for online learning settings, due in no small part to the recent COVID-19 pandemic. In the present study we explore how social presence (i.e., the degree to which the other person is perceived as physical "real"), social space (i.e., trust building between peers) and sociability (i.e., the degree to which the virtual learning environment supports social presence and social space) are essential elements in the regulation of online peer interaction. To shed light in this matter, higher education students were qualitatively followed for 1 year in an online academic writing course by using retrospective interviews (n = 7) and reflective questions (n = 62). Additionally, for social presence, students' perceptions were quantitatively measured with a validated questionnaire (n = 41). The results show that the planning phase is the most important phase for supporting students' social presence because that is where the regulation of peer interaction becomes important. The sociability has an important role here as well becoming less prominent further on in the self-regulation process. In the SRL follow-up phases, students look for other ways to increase their social presence and social space in order to shape the regulation of peer interaction from a position of trust. In the evaluation phase, students are aware of the importance of social presence but less of social space for the regulation of peer interaction. We conclude with some design principles to facilitate students' regulation of peer interaction in online settings.

Modeling and Analyzing the Impact of the Internet of Things-Based Industry 4.0 on Circular Economy Practices for Sustainable Development: Evidence From the Food Processing Industry of China

The Industry 4.0 concept proposes that new cutting-edge technologies, such as the Internet of Things (IoT), will grow. The acceptance of IoT in the circular economy (CE) is still in its infancy, despite its enormous potential. In the face of growing environmental affairs, IoT based Industry 4.0 technologies are altering CE practices and existing business models, according to the World Economic Forum. This research investigates the function of IoT-based Industry 4.0 in circular CE practices, as well as their impact on economic and environmental performance, which in turn influences overall organizational performance. China-based enterprises provide information for the study, which includes data from 300 companies. Utilizing a structural equation modeling framework known as partial least squares structural equation modeling (PLS-SEM). The major findings are presented in the study: (I) the IoT significantly improves the activities of the CE; (II) the IoT significantly improves the practices of the CE; and (III) the IoT meaningfully advances the practices of CE (green manufacturing, circular design, remanufacturing, and recycling). Moreover, the findings shows that environmentally friendly business practices help enhance environmental performance of firm, while also stimulating their economic performance; and improved environmental performance has a significant positive influence on firm performance. This research lays the groundwork for contributing nations/companies to attain economic and long-term sustainability goals at the same time by incorporating IoT-based Industry 4.0 technology into CE practices.

The Impact of Language Diversity on Knowledge Sharing Within International University Research Teams: Evidence From TED Project

In today's knowledge economy, knowledge and knowledge sharing are fundamental for organizations to achieve competitiveness and for individuals to strengthen their innovation capabilities. Knowledge sharing is a complex language-based activity; language affects how individuals communicate and relate. The growth in international collaborations and the increasing number of diverse teams affect knowledge sharing because individuals engage in daily knowledge activities in a language they are not native speakers. Understanding the challenges they face, and how they manage the emerging difficulties is the main aim of this manuscript. For this purpose, an explorative case study was conducted in an international university research project, namely the TED project. Both interviews and direct observations were employed to understand the phenomenon better and deliberately triangulate data and improve validity. Results show that non-native language use determines the emergence of different language proficiency, depending on the nature of the knowledge domain-job-related vs. non-job-related. Within non-job-related knowledge domains, the lack of linguistic abilities, summed to the perceived cultural diversities, mainly affects people's propensity to engage in personal and more intense social relationships. Under such circumstances, tacit knowledge sharing is reduced with negative consequences on the project's long-term innovative performance. Since the project is still running, detecting language challenges will allow the partners to design and apply effective measures to support cooperation with language and cultural barriers. Among them, code switching, adopted by "bridge" actors, already emerges as tool supporting communication and knowledge exchange.

The Nexuses Between Social Media Marketing Activities and Consumers' Engagement Behaviour: A Two-Wave Time-Lagged Study

This study examined how social media marketing activities (SMMA) influence consumers' engagement behaviour in developing countries. Based on the stimulus-organism-response theory, we examined the effect of SMMA on consumers' engagement intention and further investigated the moderating effect of social media sales intensity. The study employed a time-lagged design with two waves to confirm the hypothesised framework. The study findings showed that SMMA positively influence consumers' engagement intention and engagement behaviour. In addition, social media sales intensity strengthens the link between engagement intention and engagement behaviour. This study adds to the literature on social media and discusses its practical implications.

An Application of Analytic Hierarchy Process and Entropy Weight Method in Food Cold Chain Risk Evaluation Model

The food cold chain is a special type of cold chain that refers to a system in which refrigerated and frozen food is always kept in the specified low-temperature environment in all links from production, storage, transportation, sales, distribution to consumption, so as to ensure food quality and to prevent food deterioration caused by temperature fluctuation. In recent years, the coronavirus disease 2019 (COVID-19) has brought a great impact on people's life and the social economy and also threatened the large-scale food cold chain. Through the effective identification and evaluation of high-risk factors in the food cold chain, this article has found the major risks that have a great impact on the entire food cold chain and proposes the specific measures of risk management and control to solve the problems of food cold chain and reduce risks quickly and efficiently to ensure the stability and safety of food cold chain and avoid the serious food safety accidents. The contribution of this article is reflected in three aspects, namely, (1) applies the expert system based on professional knowledge and rich experience and constructs a classification and identification system structure of food cold chain risk indexes, which lay a foundation for further identifying and evaluating the major risks of the food cold chain; (2) designs a comprehensive index weighting method combining the AHP method and entropy weight method to quantitatively evaluate the major risks. This comprehensive method combines a hierarchical structure system, evaluation algorithm, subjective factor correction algorithm, and so on. The evaluation results are more accurate, have a high matching degree with reality, and have good theoretical and practical significance; (3) analyzes and explains the major risks of the food cold chain in the non-epidemic situations and COVID-19 situations. Proposals and measures for risk management and control are put forward, which have wide practical significance.

Impact of News Overload on Social Media News Curation: Mediating Role of News Avoidance

In this global village, easy access to news has resulted in many changes in the preferences and patterns of people for accessing news. Therefore, the present study has attempted to investigate the effects of news relevance, perceived quality, and news overloading on people's news curation preferences. This study has also examined the mediating role of news avoidance between the news relevance, perceived quality, and news overloading on the news curation. A quantitative technique has been employed to check the relationships proposed in the study. A sample size of 217 has been analyzed to check these hypotheses. The findings of the study revealed that news relevance has a negative impact while news overload positively and significantly impact the news curation. However, the news avoidance only mediated the relationship of news quality and news curation. Theoretically, the study has contributed to the literature of journalism and social media by finding that relevance of news has a negative significant impact on the news curation behavior of people, such that if they do not find the news relevant, they happily curate it. Practically, the study implies that the people are more prone to the quality of news rather than quantity; therefore, it is important for the news agencies to ensure that they produce and deliver the quality based news considering the accuracy to penetrate the Theoretic lass level.

The Effects of Contextual Factors, Self-Efficacy and Motivation on Learners' Adaptability to Blended Learning in College English: A Structural Equation Modeling Approach

Objective

Few research efforts have substantially introduced relevant studies on Chinese students' adaptability in relation to the ineffectiveness of blended learning mode in College English. This study is guided by social cognitive theory, and related literature has been reviewed concerning adaptability. In this study, we aim to examine the involved relationships among contextual factors, self-efficacy, motivation, and adaptability to blended learning mode among non-English majored Chinese learners in the College English course.

Methods

The quantitative research method was employed in this study, and 595 respondents were eventually collected to enable the data analysis. The structural equation modeling (SEM) approach was used to analyze the data.

Results

(1) The non-English majored learners' adaptability to blended learning mode in College English was at a low level with a mean value of 2.26, indicating that students still suffer difficulties from class conducted in blended learning; (2) the fit indices were at the level of good fit, and it suggested the structural model had an overall good fit to the data as shown: x 2/df = 2.496, RMESA = 0.050, GFI = 0.956, AGFI = 0.936, NFI = 0.968, RFI = 0.959, IFI = 0.980, TLI = 0.975, CFI = 0.980; (3) adaptability was positively related to contextual factors, self-efficacy, and motivation (p < 0.001); (4) contextual factors exerted an indirect effect on the adaptability not only through the separate mediating role of self-efficacy and motivation, but through the chain mediating role of self-efficacy and motivation (p < 0.01).

Implications

This study theoretically extends previous studies on adaptability by investigating the affecting factors in the framework of social cognitive theory. More practically important is that this study sheds light on the impact mechanism of positive and enjoyable environment, self-efficacy and motivation on non-English majored learners' adaptability to blended learning mode in English course, which would provide a vital insight for administrators and College English instructors to reconsider the role of learners' responses in the mixed mode to improve their English achievement more effectively, as well as to enhance and promote their user experience of the offered blended learning service.