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This study aims to posit that managerial value would be one of the responsible factors for the difference in corporate social responsibility practice among businesses. It then empirically tested the effect of managerial value, with the moderation of organizational culture, on corporate social responsibility practice.

The authors have devised a “moderated micro-macro model” type of multilevel model, wherein managerial value took the micro (individual level) predictor variable role, stakeholder-based corporate social responsibility practice the macro (organizational level) outcome variable role and organizational culture the macro level moderating variable role. Because they need the attention of inquiry, large manufacturing firms in the Amhara region of Ethiopia, with a sample size of 53, constituted the organizational level units. The recent performance of the firms against corporate social responsibility practice and organizational culture have been judged by 473 randomly chosen employees. Managerial value has been rated by randomly picked managers, numbered 253. Analytically, Croon and van Veldhoven’s multilevel analytical package and Mplus software suited the designed model.

The study has revealed that managerial value, indeed, is a potential positive driver of CSR practice, the two managerial value dimensions demonstrated differential effects on corporate social responsibility practice and only one of the organizational culture dimensions, hierarchical culture, played a moderation role in managerial value – corporate social responsibility practice link.

The model and this empirical test have not been previously verified.

This research developed a model to understand and predict housing market dynamics and evaluate the significance of house permits data in the model’s forecasting capability.

The research uses a multilevel algorithm consisting of a machine-learning regression model to predict the independent variables and another regressor to predict the dependent variable using the forecasted independent variables.

The research establishes a statistically significant relationship between housing permits and house prices. The novel approach discussed in this paper has significantly higher prediction capabilities than a traditional regression model in forecasting monthly average prices (R-squared value: 0.5993), house price index prices (R-squared value: 0.99) and house sales prices (R-squared value: 0.7839).

The impact of supply, demand and socioeconomic factors will differ in various regions. The forecasting capability and significance of the independent variables can vary, but the methodology can still be applicable when provided with the considered variables in the model.

The resulting model is helpful in the decision-making process for investments, house purchases and construction as the housing demand increases across various cities. The methodology can benefit multiple players, including the government, real estate investors, homebuyers and construction companies.

Existing algorithms and models do not consider the number of new house constructions, monthly sales and inventory in the real estate market, especially in the United States. This research aims to address these shortcomings using current socioeconomic indicators, permits, monthly real estate data and population information to predict house prices and inventory.

The purpose of this study is to examine effects of classroom-level and student-level factors on student engagement in the context of a higher education system vertically differentiated into research, applied and comprehensive university types.

The study used a cross-sectional multilevel design to explain student engagement based on class and student variables. Specifically, the study collects data from 656 students and 61 randomly selected teachers at both levels and uses multilevel modeling to explain relationship patterns.

The results show that institutions vary significantly in student engagement scores. In addition, while a significant variation is found at the student and classroom level, the effects of academic achievement, instructional quality, teaching experience and teacher qualifications on student engagement vary across classrooms in institutions. However, the interaction effect of classroom and student-level variables on student engagement remains non-significant.

The main contribution of this lies in the explanation of student engagement using classroom and student level factors in a vertically differentiated higher education system using multilevel modeling. Student engagement varied in classrooms research universities applied and comprehensive universities.

This study aims to investigate whether social investment (SI) policies improve employment among single mothers.

This paper analyzes the potential effects of SI policies on vulnerable individuals and workers at the macro level by using the employment position of single mothers as a dependent variable. Time-series cross-national data from 18 OECD countries between 1998 and 2017 are analyzed. Multilevel model analysis is also used for robustness check.

I find that public spending on education and family support is positively associated with the employment rates of single mothers. In contrast, active labor market policy (ALMP) spending is negatively associated. ALMP’s negative effects stand out particularly with public spending on job training. Of all family support policies, family allowances are positively associated with single mothers’ employment, which runs counter to the conventional argument that family allowances are a disincentive for women’s or mothers’ employment. Paid leave (length and generosity) is also associated with higher employment for single mothers. There is also some tentative evidence that public spending on maternity leave benefits (spending level) may raise the odds of single mothers being employed, when individual-level factors are controlled for in multilevel analysis we implement for robustness check.

This paper does not analyze the effects of the qualitative properties of SI policies. Future research is necessary in this respect.

The effects of SI policies on employment among single mothers have not yet been examined in the literature. This paper seeks to be a first cut at measuring the effects.

This study aims to elucidate institutional analysis as an effective approach to investigating and designing the multilevel policymaking system of online social networks (OSN) for achieving a participatory model.

The institutional mapping approach has been used to analyze Iran’s OSN multilevel policymaking system. A combination of two matrices, including institutions-institutions and institutions-functions, was used to perform the institutional mapping. Two main steps were taken to draw the mentioned matrices. First, a review of related studies in Iran’s OSN policymaking system was conducted and the policy functions mentioned in these studies were identified and categorized using the meta-synthesis. Second, based on analyzing two policy documents of Iran’s OSN, institutions and their interactions were identified and policy functions were allocated to institutions.

Based on the results, the most important policy functions in the current OSN policymaking system in Iran are support, regulatory, monitoring and evaluation, business environment development, culture building and promotion, organizing licenses and permissions, policymaking and legislation. Also, the results show that there are shortcomings in this system, some of the most important of which are lack of transparency in regulatory, little work in culture building and promotion, neglect of the training of specialized human resources and research and development, slow development of the business environment and neglecting the role of nongovernmental organizations in policymaking.

By examining and analyzing how different institutions operate within a multilevel policymaking system, the policymaking process and its overall effectiveness can be enhanced. This analysis helps identify any inconsistencies, overlaps or conflicts in the roles and policies of these institutions, leading to a better understanding of how a multilevel policymaking system is organized.

Drawing on the microfoundations theory and rational choice sociology, this study aims to investigate knowledge-sharing microfoundations through knowledge sabotage behaviours in the workplace. As such, it aims to shed light on the adverse impact of knowledge sabotage on a knowledge-sharing climate.

As a quantitative deductive study, it is based on information collected from 329 employees of European companies by self-administered online surveys. Data validity and reliability has been assessed through a confirmatory factor analysis, and data analysis was carried out by using a covariance-based structural equation modelling technique.

The findings from the empirical investigation supported the baseline hypotheses of the multilevel conceptual model, which is the positive relationship between organizational trust and environmental knowledge sharing. Then, recurring to a microfoundational exploration, this study supports the mediating indirect effect of job satisfaction and knowledge sabotage in affecting knowledge sharing as a social outcome.

This study concurs to broaden knowledge-sharing awareness among scholars and practitioners, by focusing on knowledge sabotage as its most pernicious counterproductive behaviour. Furthermore, this research provides valuable guidance for the future development of research based on multilevel investigations.

This study builds on the need to explore the numerous factors that affect knowledge sharing in economic organizations, specifically focusing on knowledge sabotage. Adapting Coleman’s bathtub, the authors advance the first multilevel conceptual model used to unveil the knowledge-sharing microfoundations from the perspective of a counterproductive knowledge behaviour.

The purpose of this research is to investigate the cross-level effects and mechanisms of inclusive leadership on employee innovation in team contexts, and further explore the boundary conditions of inclusive leadership.

This study collected data from 237 leader-member dyads in 60 teams of Chinese firms. The research utilized multilevel linear models and multilevel structural equation models in the R language to test the hypothesized model.

The findings suggest that inclusive leadership has a positive impact on both employee incremental and radical innovation. Team psychological safety and employee role breadth self-efficacy mediate the effects. Employee risk avoidance propensity negatively moderates the mediating role of role breadth self-efficacy in the relationship between inclusive leadership and incremental innovation.

Leaders should pay attention to team psychological safety, employee role breadth self-efficacy and employee individual risk avoidance propensity that influence employee innovation to maximize the effectiveness of inclusive leadership.

This research expanded the level of analysis from individual to team, exploring cross-level effects and mechanisms of inclusive leadership on employee innovation in team contexts, and clarified the effectiveness conditions of inclusive leadership.

This study aims to examine the relationship between medication for opioid use disorder (MOUD) among pregnant individuals, referral source, mental health, political affiliation and substance use policies in all 50 states in the USA.

This study describes MOUD receipt among pregnant people with an opioid use disorder (OUD) in 2018. The authors explored sociodemographic differences in MOUD receipt, referrals and co-occurring mental health disorders. The authors included a comparison of MOUD receipt among states that have varying substance use policies and examined the impact of these policies and the political affiliation on MOUD. The authors used multilevel binary logistic regression to examine effects of individual and state-level characteristics on MOUD.

Among 8,790 pregnant admissions with OUD, the majority who received MOUD occurred in the Northeast region (71.52%), and 14.99% were referred by the criminal justice system (n = 1,318). Of those who were self-referred, 66.39% received MOUD, while only 30.8% of referrals from the criminal justice system received MOUD. Those referred from the criminal justice system or who had a co-occurring mental health disorder were least likely to receive MOUD. The multilevel model showed that while policies were not a significant predictor, a state’s political affiliation was a significant predictor of MOUD.

The study has some methodological limitations; a state-level analysis, even when considering the individual factors, may not provide sufficient description of community-level or other social factors that may influence MOUD receipt. This study adds to the growing literature on the ineffectiveness of prenatal substance use policies designed specifically to increase the use of MOUD. If such policies are consistently assessed as not contributing to substantial increase in MOUD among pregnant women over time, it is imperative to investigate potential mechanisms in these policies that may not facilitate MOUD access the way they are intended to.

Findings from this study aid in understanding the impact that a political affiliation may have on treatment access; states that leaned more Democratic were more likely to have higher rates of MOUD, and this finding can lead to research that focuses on how and why this contributes to greater treatment utilization. This study provides estimates of underutilization at a state level and the mechanisms that act as barriers, which is a stronger assessment of how state-specific policies and practices are performing in addressing prenatal substance use and a necessary step in implementing changes that can improve the links between pregnant women and MOUD.

To the best of the authors’ knowledge, this is the first study to explore individual-level factors that include mental health and referral sources to treatment that lead to MOUD use in the context of state-level policy and political environments. Most studies estimate national-level rates of treatment use only, which can be useful, but what is necessary is to understand what mechanisms are at work that vary by state. This study also found that while substance use policies were designed to increase MOUD for pregnant women, this was not as prominent a predictor as other factors, like mental health, being referred from the criminal justice system, and living in a state with more Democratic-leaning affiliations.

Internal knowledge transfer is crucial for firms to improve their employees’ abilities and improve their work performance. However, there is still a gap in the knowledge management field regarding whether internal knowledge transfer can leverage employee personality traits and service performance in service-oriented organizations. To address this gap, this study aims to validate a multilevel model of the mediating (i.e. internal knowledge transfer as a mediator) and moderating (i.e. task interdependence as a moderator) mechanisms underlying personality traits and employee service performance.

Multilevel structural equation modeling was applied for model validation using an original data set from 45 team leaders and 333 employees working in Chinese hotels.

Internal knowledge transfer mediated the link between extraversion and employee service performance and the link between openness to experience and employee service performance. Task interdependence played a moderating role that strengthened both the impacts of extraversion and openness to experience on internal knowledge transfer.

Through the use of an original data set, this study advances the knowledge management discipline by investigating the mediating impact of internal knowledge transfer between personality traits and employee service performance and revealing the moderating impact of task interdependence that underlies the links between personality traits and internal knowledge transfer.

Although emerging markets are distinctly known for the rapid growth and international expansion of their state-owned enterprises, little is known about the influence of parent resource advantages and mixed state ownership on a subsidiary’s performance. Using the resource-based view, this study aims to investigate how resource advantages from the parent company and state ownership influence the performance of subsidiaries.

This study included a unique data set of 207 subsidiaries from 33 large Brazilian multinationals located in 32 countries from 2000 to 2015. The authors used a hierarchical linear modeling and a multilevel structure based on data at different levels to analyze the influence of home-country parent resource advantages and state ownership on host-country subsidiary’s performance.

This study illustrates that state ownership can alleviate the resource advantages of parent companies. Evidence is presented, indicating that low and medium degrees of state ownership have a negative impact on the resource advantages of the parent company, consequently reducing the subsidiary’s performance. Moreover, this study highlights that low and medium degrees of state ownership lead to conflicting interests between state ownership and parent resource advantages, resulting in an overall decline in subsidiary performance.

This research contributes new evidence regarding state ownership and resource advantages to the field of international business studies and the domain of Latin American multinational enterprises, Multilatinas. The results suggest that low and medium levels of state ownership diminish the influx of resources from parent companies, thereby restricting the subsidiary’s performance.