Traditionally, cognitive, motivational, and volitional determinants have been used to explain and predict health behaviors such as physical activity. Recently, the role of affect in influencing and regulating health behaviors received more attention. Affects as internal cues may automatically activate unconscious processes of behavior regulation. The aim of our study was to examine the association between affect and physical activity in daily life. In addition, we studied the influence of the habit of being physically active on this relationship. An ambulatory (...) assessment study in 89 persons (33.7% male, 25 to 65 years, M = 45.2, SD = 8.1) was conducted. Affect was assessed in the afternoon on 5 weekdays using smartphones. Physical activity was measured continuously objectively using accelerometers and subjectively using smartphones in the evening. Habit strength was assessed at the beginning of the diary period. The outcomes were objectively and subjectively measured moderate-to-vigorous physical activity (MVPA) performed after work. Multilevel regression models were used to analyze the association between affect and after work MVPA. In addition, the cross-level interaction of habit strength and affect on after work MVPA was tested. Positive affect was positively related to objectively measured and self-reported after work MVPA: the greater the positive affect the more time persons subsequently spent on MVPA. An inverse relationship was found for negative affect: the greater the negative affect the less time persons spent on MVPA. The cross-level interaction effect was significant only for objectively measured MVPA. A strong habit seems to strengthen both the positive influence of positive affect and the negative influence of negative affect. The results of this study confirm previous results and indicate that affect plays an important role for the regulation of physical activity behavior in daily life. The results for positive affect were consistent. However, in contrast to previous reports of no or an inverse association, negative affect decreased subsequent MVPA. These inconsistencies may be—in part—explained by the different measurements of affect in our and other studies. Therefore, further research is warranted to gain more insight into the association between affect and physical activity. (shrink)

ObjectiveLong-term isolation, including lockdowns and quarantines, may have a distressing effect on anyone experiencing it. Adolescent brain architecture is very sensitive to environmental adversities, and the mental health development of adolescents may be particularly vulnerable during the pandemic era. In order to better understand the triggers for perceived adolescent stress during the COVID-19 lockdown, the present study aimed to assess the effects of social well-being and changes in time use during the lockdown, as well as the family COVID experience of (...) adolescents.MethodsThe sample for this study comprised n = 3,440 adolescents. Bayesian correlations between PSS, health and well-being variables were assessed. PSS was then modeled as an outcome variable in a series of nested Bayesian multilevel regression models.ResultsThe negative impact of the COVID-19 lockdown was more apparent in girls. PSS was moderately correlated with adolescent health and well-being. The strongest predictor of higher level of PSS was frequent feeling of loneliness. On the contrary, lower level of PSS was most associated with having someone to talk to.ConclusionLong-term social isolation of adolescents could be harmful to their mental health. Psychological coping strategies to prevent the consequences of social isolation and development of mental health problems should be promoted on the individual, family, and even community level. (shrink)

Multilevel item response theory models are used widely in educational and psychological research. This type of modeling has two or more levels, including an item response theory model as the measurement part and a linear-regression model as the structural part, the aim being to investigate the relation between explanatory variables and latent variables. However, the linear-regression structural model focuses on the relation between explanatory variables and latent variables, which is only from the perspective of (...) the average tendency. When we need to explore the relationship between variables at various locations along the response distribution, quantile regression is more appropriate. To this end, a quantile-regression-type structural model named as the quantile MLIRT model is introduced under the MLIRT framework. The parameters of the proposed model are estimated using the Gibbs sampling algorithm, and comparison with the original MLIRT model is conducted via a simulation study. The results show that the parameters of the Q-MLIRT model could be recovered well under different quantiles. Finally, a subset of data from PISA 2018 is analyzed to illustrate the application of the proposed model. (shrink)

SummaryThe nutritional status of under-five children is a sensitive sign of a country's health status as well as economic condition. This study investigated the differential impact of some demographic, socioeconomic, environmental and health-related factors on the nutritional status among under-five children in Bangladesh using Bangladesh Demographic and Health Survey 2007 data. Two-level random intercept binary logistic regression models were used to identify the determinants of under-five malnutrition. The analyses revealed that 16% of the children were severely stunted and 25% (...) were moderately stunted. Among the children under five years of age 3% were severely wasted and 14% were moderately wasted. Furthermore, 11% of the children were severely underweight and 28% were moderately underweight. The main contributing factors for under-five malnutrition were found to be child's age, mother's education, father's education, father's occupation, family wealth index, currently breast-feeding, place of delivery and division. Significant community-level variations were found in the analyses. (shrink)

Interactions with teachers and peers are critical for children’s social, behavioral, and academic development in the classroom context. However, these two types of interpersonal interactions in the classroom are usually pursued via separate lines of inquiries. The current study bridges these two areas of research to examine the way in which teachers influence child-perceived peer social support and peer victimization for 2,678 children within 183 classrooms in preschool through grade three. Two levels of teacher influence are considered, namely teacher-child closeness (...) and conflict relationships at the child-level, and teacher management of interpersonal interactions at the classroom-level. Results of multilevel regression models showed that teacher-child closeness was associated with the growth of child-perceived peer social support from fall to spring, whereas teacher-child conflict and teachers’ behavior management practices were associated with the change in child-perceived peer victimization across the academic year. These associations were unique and above and beyond the influence of children’s actual peer social interactions, including reciprocal friendships and the collective classroom reputation of peer victimization. Collectively, findings highlight the multi-faceted teacher roles in shaping children’s perceptions of their peer social experiences during the earliest years of schooling. (shrink)

We present a visual world eye-tracking study on Tseltal (a Mayan language) and investigate whether verbal information can be used to anticipate an upcoming referent. Basic word order in transitive sentences in Tseltal is Verb–Object–Subject (VOS). The verb is usually encountered first, making argument structure and syntactic information available at the outset, which should facilitate anticipation of the post-verbal arguments. Tseltal speakers listened to verb-initial sentences with either an object-predictive verb (e.g., “eat”) or a general verb (e.g., “look for”) (e.g., (...) “Ya slo’/sle ta stukel on te kereme,” Is eating/is looking (for) by himself the avocado the boy/ “The boy is eating/is looking (for) an avocado by himself”) while seeing a visual display showing one potential referent (e.g., avocado) and three distractors (e.g., bag, toy car, coffee grinder). We manipulated verb type (predictive vs. general) and recorded participants' eye movements while they listened and inspected the visual scene. Participants’ fixations to the target referent were analyzed using multilevel logistic regression models. Shortly after hearing the predictive verb, participants fixated the target object before it was mentioned. In contrast, when the verb was general, fixations to the target only started to increase once the object was heard. Our results suggest that Tseltal hearers pre-activate semantic features of the grammatical object prior to its linguistic expression. This provides evidence from a verb-initial language for online incremental semantic interpretation and anticipatory processing during language comprehension. These processes are comparable to the ones identified in subject-initial languages, which is consistent with the notion that different languages follow similar universal processing principles. (shrink)

Sex ratios have widely been recognized as an important link between demographic contexts and behavior because changes in the ratio shift sex-specific bargaining power in the partner market. Implicitly, the literature considers individual partner market experiences to be a function of local sex ratios. However, empirical evidence on the correspondence between subjective partner availability and local sex ratios is lacking so far. In this paper, we analyzed how closely a set of different local sex ratio measures correlates with subjective partner (...) market experiences. Linking a longitudinal German survey to population data for different entities, we used multilevel logistic regression models to explore associations between singles’ subjective partner market experiences and various operationalizations of local sex ratios. Results suggest that local sex ratios correlated only weakly with subjective partner market experiences. Adult sex ratios based on broad age brackets, including those for lower-level entities, did not significantly predict whether individuals predominantly met individuals of their own sex. More fine-grained, age-specific sex ratios prove to be better predictors of subjective partner market experiences, in particular when age hypergamy patterns were incorporated. Nevertheless, the respective associations were only significant for selected measures. In a complementary analysis, we illustrate the validity of the subjective indicator as a predictor of relationship formation. In sum, our results suggest that subjective partner availability is not adequately represented by the broad adult sex ratio measures that are frequently used in the literature. Future research should be careful not to equate local sex ratios and conscious partner market experiences. (shrink)

The city of Kruja (Albania)contains three types of dwellings that date back to different periods of time: the historic ones, the socialist ones, the modern ones. This paper has to deal only with the historic building's typology. The questionnaire that is applied will be considered for the development of mathematical regression based on specific data for this category. Variation between the relevant variables of the questionnaire is fairly or inverse-linked with a certain percentage of influence. The aim of this (...) study is to have better insights into the important role of building occupancy, people's lifestyle, economic level, and the quality of life of the residents in the inner medieval citadel, the physics characteristics, and the energy efficiency of the historical dwellings. The variables such as the number of residents, quality of life, the surface of the dwellings, heating instruments and time spent in the dwelling, current living conditions, monthly bills, level of satisfaction, restoration, and building improvements, interact with each other with probabilities with different positive or negative percentages. (shrink)

Whether level 1 predictors should be centered per cluster has received considerable attention in the multilevel literature. While most agree that there is no one preferred approach, it has also been argued that cluster mean centering is desirable when the within-cluster slope and the between-cluster slope are expected to deviate, and the main interest is in the within-cluster slope. However, we show in a series of simulations that if one has a multilevel autoregressive model in which the (...) level 1 predictor is the lagged outcome variable (i.e., the outcome variable at the previous occasion), cluster mean centering will in general lead to a downward bias in the parameter estimate of the within-cluster slope (i.e., the autoregressive relationship). This is particularly relevant if the main question is whether there is on average an autoregressive effect. Nonetheless, we show that if the main interest is in estimating the effect of a level 2 predictor on the autoregressive parameter (i.e., a cross-level interaction), cluster mean centering should be preferred over other forms of centering. Hence, researchers should be clear on what is considered the main goal of their study, and base their choice of centering method on this when using a multilevel autoregressive model. (shrink)

How does personality influence the relationship between appraisals and emotions? Recent research suggests individual differences in appraisal structures: people may differ in an emotion's appraisal pattern. We explored individual differences in interest's appraisal structure, assessed as the within-person covariance of appraisals with interest. People viewed images of abstract visual art and provided ratings of interest and of interest's appraisals (novelty–complexity and coping potential) for each picture. A multilevel mixture model found two between-person classes that reflected distinct within-person appraisal (...) styles. For people in the larger class (68%), the novelty–complexity appraisal had a stronger effect on interest; for people in the smaller class (32%), the coping potential appraisal had a stronger effect. People in the larger class were significantly higher in appetitive traits related to novelty seeking (e.g., sensation seeking, openness to experience, and trait curiosity), suggesting that the appraisal classes have substantive meaning. We conclude by discussing the value of within-person mixture models for the study of personality and appraisal. (shrink)

Following Brunswik (1952), social judgement theorists have long relied on regression models to describe both an individual's judgements and the environment about which such judgements are made. However, social judgement theory is not synonymous with these compensatory, static, structural models. We compared the characterisations of physicians' judgements using a regression model with that of a non-compensatory process model (called fast and frugal). We found that both models fit the data equally well. Both models suggest that physicians (...) use few cues, that they disagree among themselves, and that their stated cue use is discrepant with the models' stated cue use. However, the fast and frugal model is easier to convey to physicians and is also more psychologically plausible. Implications for how social judgement theorists conceptualise the process of vicarious functioning are discussed. (shrink)

The price of copper is unstable but it is considered an important indicator of the global economy. Changes in the price of copper point to higher global growth or an impending recession. In this work, the forecasting of the spot prices of copper from the New York Commodity Exchange is studied using a machine learning method, support vector regression coupled with different model schemas (recursive, direct and hybrid multi-step). Using these techniques, three different time series analyses are built (...) and its performance are compared. The numerical results show that the hybrid direct-recursive obtains the best results. (shrink)

Kruja is a middle-range city located in the center of Albania. The city of Kruja dates back to its existence from the V-VI century and extends to the city around the VI and IX centuries. It becomes the first capital of Albania in the XI-th century, specifically in 1190. This paper is going to deal with only two groups of buildings that are an integral part of the historical city of Kruja, the historical dwellings (XVIII century) and the socialist ones (...) (1960-1985). This paper aims to analyze through linear regressions the relation between two parameters: moisture content and temperature of the indoor walls and floors of the historic and socialist buildings in the city of Kruja. Three types of historic dwelling and three types of socialist apartments have been analyzed, relatively uniformly oriented. The measurements with specific instruments are done on the same day, for three hours. The degree of reactivity is different for both groups of buildings. The historical buildings are more sensitive to temperature rise. They respond invers to it (as the temperature rise, the level of the moisture content decreases), with a higher coefficient than socialist ones, and appear to be more efficient in reducing the level of the moisture, despite the average moisture content being higher. This paper takes into consideration also the analysis of the materials of the construction for both categories. If the level of moisture is reduced, the buildings will be improved and the quality of life indicators of the inhabitance will be improved too. (shrink)

When analyzing complex longitudinal data, especially data from different educational settings, researchers generally focus only on the mean part (i.e., the regression coefficients), ignoring the equally important random part (i.e., the random effect variances) of the model. By using Project English Language and Literacy Acquisition (ELLA) data, we demonstrated the importance of taking the complex data structure into account by carefully specifying the random part of the model, showing that not only can it affect the variance estimates, (...) the standard errors, and the tests of significance of the regression coefficients, it also can offer different perspectives of the data, such as information related to the developmental process. We used xxM (Mehta, 2013), which can flexibly estimate different grade-level variances separately and the potential carryover effect from each grade factor to the later time measures. Implications of the findings and limitations of the study are discussed. (shrink)

Water quality control helps in the estimation of water bodies and detects the span of pollutants and their effect on the neighboring environment. This is why the water quality of the northern part of Lake Manzala has been studied here from January to March, 2016. This study aims to model and create a program for linear and nonlinear regression of the water elements in Lake Manzala to assess and predict the water quality. Water samples have been extracted from (...) various depths, and physio-chemical properties and heavy metal concentrations have been evaluated. This study has proposed a new algorithm for predicting water quality called “Algorithm of Estimation Regression Model”. On the contrary, in renewable energy applications, statistical modeling and forecasting the solar radiation remains a significant issue with detect to reinforce power management. A new proposed method for forecasting the average Monthly Global Solar Energy in Queensland, Australia, is called, Converting Data Set into Markov Model. It was used to obtain Markov transition probability matrices for three and six states of the solar energy. The proposed forecasting method yielded accurate results with minimal error. (shrink)

The authenticity of the company’s accounting information is an important guarantee for the effective operation of the capital market. Accounting fraud is the tampering and distortion of the company’s public disclosure information. The continuous outbreak of fraud cases has dealt a heavy blow to the confidence of investors, shaken the credit foundation of the capital market, and hindered the healthy and stable development of the capital market. Therefore, it is of great theoretical and practical significance to carry out the research (...) on the identification and governance of accounting fraud. Traditionally, accounting fraud identification is mostly based on linear thinking to build the fraud identification model. However, more and more studies show that fraud has typical nonlinear characteristics, and the multiobjective of fraud means also determines the limitations of using the linear model for identification. Considering that the traditional identification methods may have the defects of model setting error and insufficient information extraction, this paper constructs the support vector machine and logistic regression model to identify accounting fraud. The support vector machine is used to improve the learning ability and generalization ability of unknown phenomena, and the explanatory power of each variable to the whole model is identified by the logistic regression model. This paper breaks through the linear constraint hypothesis and explores the model setting form which is more suitable for the law of corporate fraud behaviour to extract the fraud identification information more fully and provide more powerful support for investors to effectively identify fraud. (shrink)

Specifying accurate informative prior distributions is a question of carefully selecting studies that comprise the body of comparable background knowledge. Psychological research, however, consists of studies that are being conducted under different circumstances, with different samples and varying instruments. Thus, results of previous studies are heterogeneous, and not all available results can and should contribute equally to an informative prior distribution. This implies a necessary weighting of background information based on the similarity of the previous studies to the focal study (...) at hand. Current approaches to account for heterogeneity by weighting informative prior distributions, such as the power prior and the meta-analytic predictive prior are either not easily accessible or incomplete. To complicate matters further, in the context of Bayesian multiple regression models there are no methods available for quantifying the similarity of a given body of background knowledge to the focal study at hand. Consequently, the purpose of this study is threefold. We first present a novel method to combine the aforementioned sources of heterogeneity in the similarity measure ω. This method is based on a combination of a propensity-score approach to assess the similarity of samples with random- and mixed-effects meta-analytic models to quantify the heterogeneity in outcomes and study characteristics. Second, we show how to use the similarity measure ωas a weight for informative prior distributions for the substantial parameters in Bayesian multiple regression models. Third, we investigate the performance and the behavior of the similarity-weighted informative prior distribution in a comprehensive simulation study, where it is compared to the normalized power prior and the meta-analytic predictive prior. The similarity measure ω and the similarity-weighted informative prior distribution as the primary results of this study provide applied researchers with means to specify accurate informative prior distributions. (shrink)

Economic burden of private supplementary tutoring is increasing around the world. Demand for private supplementary tutoring, contributing factors, and their effects are investigated in the study. For this purpose, data were collected through questionnaire, and multistage non-probability technique was used. Hurder model was used to find the factors affecting demand for private supplementary tutoring at the higher secondary level. Linear regression model was used to find the economic burden of family and factors affecting the demand for private (...) tutoring. The findings showed that several factors have a significant effect on the demand for private supplementary tutoring, and some of them significantly impact on the economic burden. The study recommends regulating the market of shadow education because of differentiated tuition fee in different tuition centers to cut down the burden of private tutoring for households. (shrink)

Compared with traditional statistics, only a few social scientists employ Bayesian analyses. The existing software programs for implementing Bayesian analyses such as OpenBUGS, WinBUGS, JAGS, and rstanarm can be daunting given that their complex computer codes involve a steep learning curve. In contrast, this paper introduces a new open software for implementing Bayesian network modelling and analysis: the bayesvl R package. The package aims at providing an intuitive gateway for beginners of Bayesian statistics to construct and analyse mathematical models in (...) social sciences... (shrink)

Infertility is a huge problem nowadays, not only from the medical but also from the social point of view. A key step to improve treatment outcomes is the possibility of effective prediction of treatment result. In a situation when a phenomenon with more than 2 states needs to be explained, e.g. pregnancy, miscarriage, non-pregnancy, the use of multinomial logistic regression is a good solution. The aim of this paper is to select those features that have a significant impact on (...) achieving clinical pregnancy as well as those that determine the occurrence of spontaneous miscarriage. Two multi-factor models were obtained, used in predicting infertility treatment outcomes. One of the models enabled to conclude that the number of follicles and the percentage of retrieved mature oocytes have a significant impact when prediction of treatment outcome is made on the basis of information about oocytes. The other model, built on the basis of information about embryos, showed the significance of the number of fertilized oocytes, the percentage of at least 7-cell embryos on day 3, the percentage of blasts on day 5, and the day of transfer. (shrink)

Predicting suspended sediment load in water resource management requires efficient and reliable predicted models. This study considers the support vector regression method to predict daily suspended sediment load. Since the SVR has unknown parameters, the observer-teacher-learner-based Optimization method is integrated with the SVR model to provide a novel hybrid predictive model. The SVR combined with the genetic algorithm is used as an alternative model. To explore the performance and application of the proposed models, five input combinations (...) of rainfall and discharge data of Cham Siah River catchment are provided. The predictive models are assessed using various numerical and visual indicators. The results indicate that the SVR-OTLBO model offers a higher prediction performance than other models employed in the current study. Specifically, SVR-OTLBO model offers highest Pearson correlation coefficient, Willmott’s Index, ratio of performance to IQ, and modified index of agreement and the lowest relative root mean square error in comparison with SVR-GA and SVR models, respectively. (shrink)

Distributions of human foraging success across age have implications for many aspects of human evolution. Estimating the distribution of foraging returns is complicated by (1) the zero-inflated nature of hunting returns, as many if not most trips fail, and (2) the substantial variation among hunters, independent of age. We develop a multilevel mixture analysis of human foraging data to address these difficulties. Using a previously published 20-year record of hunts by 147 individual Aché hunters in eastern Paraguay, we estimate (...) returns-by-age functions for both hunting failures and the size of harvests, while also estimating the heterogeneity among hunters. Consistent with previous analyses, we find that most hunters peak around 40 years of age. We can also show, however, that much more of the variation among Aché hunters arises from heterogeneity in failure rates (zero returns), not harvest sizes. We also introduce a new R package, glmer2stan, to assist in defining and fitting similar multilevel mixture models. (shrink)

Media use is a pervasive aspect of children’s home experiences but is often not considered in studies of the home learning environment. Media use could be detrimental to children’s language and literacy skills because it may displace other literacy-enhancing activities like shared reading and decrease the quantity and quality of caregiver-child interaction. Thus, the current study asked whether media use is associated with gains in children’s language and literacy skills both at a single time point and across a school year (...) and whether age moderates any association. Children (N = 1583) were from preschool through third grade classrooms and language and literacy skills were measured in the fall and spring of the school year. Parents reported how much time their child spends using media on a typical school day. Regression analyses showed that using 4 hours or more of media was related to lower literacy gains, but not to language gains. Multilevel models conducted as a robustness check showed that this effect did not hold when accounting for classroom. In neither set of models was there an interaction between age and media use. Single-time-point models did show some associations that did not manifest in more stringent models, highlighting the limitations of correlational designs that do not have measures of children’s skills over time. Given the concern and popular press coverage around children’s media use, it is important to acknowledge nonsignificant effects in this domain. These nonsignificant associations suggest that societal fears around children’s media use may be exaggerated. Notably, however, characteristics of children’s media use, like educational content or adult co-use, may moderate any effects. The relation between media use and language and literacy growth did not differ across the age range investigated suggesting that, within this range, younger children are not more vulnerable to detrimental effects. (shrink)

We examine and test alternative models for explaining the relationships between resource stress, beliefs that gods and spirits influence weather, and customary beyond-household sharing behavior. Our model, the resource stress model, suggests that resource stress affects both sharing as well as conceptions of gods’ involvement with weather, but these supernatural beliefs play no role in explaining sharing. An alternative model, the moralizing high god model, suggests that the relationship between resource stress and sharing is at least (...) partially mediated by religious beliefs in moralizing high gods. We compared the models using a worldwide sample of 96 cultures from the Standard Cross-Cultural Sample, newly coded data on supernatural involvement with weather, and previously coded data on food and labor sharing. We conducted three types of analysis: multilevel and society-level regressions, and mediational path modeling using Monte Carlo simulations. Resource stress shows a robust effect on beliefs that high gods are associated with weather, that superior gods help the food supply through weather, and that minor spirits hurt the food supply through weather. Resource stress also predicts greater belief in moralizing high gods. However, no form of high god belief that we test significantly predicts more sharing. Mediational models suggest the religious beliefs do not significantly explain why resource stress is associated with food and labor sharing. Our findings generally accord with the view that resource stress changes religious belief and has a direct effect on sharing behavior, unmediated by high god beliefs. (shrink)

Based on the social identity theory, the relationship and influencing mechanism between high-performance human resource practices and employees’ voice behavior were explored by constructing a moderated mediation model, and the relationship between the field of human resources and the field of organizational behavior was also established. Through 1,178 paired samples of supervisor-employee survey and multilevel linear model analysis technology, it was found that HPHRPs had a positive impact on employees’ voice behavior; perceived insider status played a mediating (...) role between HPHRPs and voice behavior; voice efficacy played a moderating role between perceived insider status and voice behavior; and voice efficacy played a mediating role in the relationship between “HPHRPs-perceived insider status-voice behavior.”. (shrink)

In this article, we extend the Bayesian nonparametric regression method Gaussian Process Regression to the analysis of longitudinal panel data. We call this new approach Gaussian Process Panel Modeling (GPPM). GPPM provides great flexibility because of the large number of models it can represent. It allows classical statistical inference as well as machine learning inspired predictive modeling. GPPM offers frequentist and Bayesian inference without the need to resort to Markov chain Monte Carlo-based approximations, which makes the approach exact (...) and fast. GPPMs are defined using the kernel-language, which can express many traditional modeling approaches for longitudinal data, such as linear structural equation models, multilevel models, or state-space models but also various commonly used machine learning approaches. As a result, GPPM is uniquely able to represent hybrid models combining traditional parametric longitudinal models and nonparametric machine learning models. In the present paper, we introduce GPPM and illustrate its utility through theoretical arguments as well as simulated and empirical data. (shrink)

At present, the research on the influence mechanism of psychological capital on farmers’ entrepreneurial behavior is relatively mature. However, the relationship between farmers’ entrepreneurial behavior and macroeconomics by entrepreneurial psychological capital is still unclear. Based on this, firstly, this work analyzes the entrepreneurial PsyCap in detail. Secondly, the research hypothesis is put forward and a conceptual model is implemented. A questionnaire is designed to analyze the current situation of farmers’ entrepreneurial PsyCap and entrepreneurial behavior. Finally, a structural equation (...) class='Hi'>model is implemented to explore the relationship between farmers’ entrepreneurial behavior and macroeconomics. The path test of the SEM is utilized to obtain the following. Macroeconomic growth has a significant positive impact on entrepreneurial behavior. Macroeconomics can affect farmers’ entrepreneurial behavior to varying degrees by affecting the four entrepreneurial PsyCap of farmers’ subjective cognition, Tenacity, hope and open-mindedness. This indicates that entrepreneurial PsyCap plays an intermediary role between farmers’ entrepreneurial behavior and macroeconomics. The purpose of this work is to explore the relationship among farmers’ entrepreneurial behavior, macroeconomics, and the role of entrepreneurial PsyCap through empirical analysis, thereby providing a theoretical reference for the subsequent country’s optimization of farmers’ entrepreneurial strategies. (shrink)

This paper aims to model multilevel interdependencies in complex organisational systems and proposes application for resilience analysis. Most of the existing research studied interdependencies only at the single-level and overlooked their multilevel character. In response to this gap, we propose a multilevel approach to better comprehend the complexity of interdependencies in organisational systems. More specifically, the study focuses on how interdependencies are shaped across multiple organisational levels. To understand the research problem, we use multilevel and (...) social network theories to elaborate the concept at five organisational levels, namely, individual, intraunit, interunit, intraorganisational, and interorganisational. Further, we show the application of multilevel interdependencies into analysis of organisational resilience. To this end, we construct a multiplex model of a real world organisational system that comprises formal and informal relations of different social exchange strength. Using the agent-based simulations of the organisational system, we investigate the relations between organisational interdependencies and organisational performance in normal and disrupted conditions. With the results, we argue that managing multilevel interdependencies is crucial to reduce vulnerability of organisational systems. By introducing the multilevel conceptualisation of interdependencies and presenting their influence on organisational resilience, we hope to pave a path to managing the complexity of interdependencies and strategic resilience enhancement in organisational systems. (shrink)

The life we considered normal was disrupted due to measures taken to limit the spread of the novel coronavirus. Quarantine, isolation, social distancing, and community containment have influenced consumer behavior and contributed to the rapid development of e-commerce. In pandemic times, even those unfamiliar with the online environment have had to adapt and make acquisitions in this new manner. Hence, we focused our research on measuring the perception of consumers on how the restrictive measures imposed to limit the spread of (...) the COVID-19 virus had influenced their decision to buy a product or service from the online environment, given that purchases are highly subjective and influenced by cumulative effects of economic, social, psychological and behavioral factors. Our paper comes with additional insights from the literature. It adds empirical evidence that reveals that the number of transactions and the value per transaction increased during the COVID-19 pandemic and highlights that online purchases will continue as such even after the pandemic. (shrink)

The role and influence of workplace spirituality on individual and organisational outcomes continue to draw attention among management scholars. Despite this increased attention, extant literature has yielded limited insights particularly into the impact and influence processes of workplace spirituality on performance outcomes at both the individual and unit levels of analysis. Addressing this gap in research, we proposed and tested a multilevel model, underpinned by social cognitive theory, that examines the processes linking perceptions of workplace spirituality and performance (...) outcomes at the individual and organisational level of analysis. Data were obtained from 51 branches of a retail organisation in the United Kingdom. Results from structural equation modelling analysis revealed three salient findings. First, workplace spirituality was positively related to ethical climate, prosocial motivation, and moral judgment. Second, ethical climate partially mediated the relationship between workplace spirituality and prosocial motivation and moral judgment, respectively. Third, aggregated ethical climate significantly relates to branch-level helping behaviour and service performance. (shrink)

According to the "experimenter's regress", disputes about the validity of experimental results cannot be closed by objective facts because no conclusive criteria other than the outcome of the experiment itself exist for deciding whether the experimental apparatus was functioning properly or not. Given the frequent characterization of simulations as "computer experiments", one might worry that an analogous regress arises for computer simulations. The present paper analyzes the most likely scenarios where one might expect such a "simulationist's regress" to surface, and, (...) in doing so, discusses analogies and disanalogies between simulation and experimentation. I conclude that, on a properly broadened understanding of robustness, the practice of simulating mathematical models can be seen to have sufficient internal structure to avoid any special susceptibility to regress-like situations. (shrink)

I develop and test a multilevel trust-based model of ethical public leadership, which links ethical leadership, trust and leadership outcomes both within and across organizational levels. I examine how both ethical leadership and trust relate to employee well-being and satisfaction, group organizational citizenship behaviour and perceived organizational performance. The findings, based on data collected from an online quantitative survey conducted in three local councils of the north east of England, provide evidence in support of positive relationships between ethical (...) leadership and employees’ trust in leaders at multiple levels. This trust is in turn shown to influence employees’ attitudes, behaviours and cognitions. (shrink)

Highlighting the implications of entrepreneurship education, this study examines the effects of entrepreneurship education in predicting the entrepreneurial intention of university students. The study also explores the mediating role of opportunity recognition and the moderating role of entrepreneurial learning in this process. To test our multilevel-moderated mediation model, based on a dataset containing 1,150 university students from 55 universities in the Guangdong-Hong Kong-Macao Greater Bay Area of China, hierarchical linear modeling is utilized to test the research hypotheses. The (...) findings reveal that entrepreneurship education can promote the entrepreneurial intention of students through opportunity recognition. Furthermore, entrepreneurial learning plays a moderating role in the link between entrepreneurship education and opportunity recognition. Implications for the design and delivery of entrepreneurship education are discussed. (shrink)

In the past 2 decades latent variable modeling has become a standard tool in the social sciences. In the same time period, traditional linear structural equation models have been extended to include non-linear interaction and quadratic effects (e.g., Klein and Moosbrugger, 2000 ), and multilevel modeling (Rabe-Hesketh et al., 2004 ). We present a general non-linear multilevel structural equation mixture model (GNM-SEMM) that combines recent semiparametric non-linear structural equation models (Kelava and Nagengast, 2012 ; Kelava et al., (...) 2014 ) with multilevel structural equation mixture models (Muthén and Asparouhov, 2009 ) for clustered and non-normally distributed data. The proposed approach allows for semiparametric relationships at the within and at the between levels. We present examples from the educational science to illustrate different submodels from the general framework. (shrink)