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The global COVID-19 crisis posed many managerial and leadership challenges for principals. More specifically, after the crisis passed noticeable changes in school climate manifested and affected principal management style. The present study examined perceptions of principals regarding school climate and its impact on management style. The research literature clearly affirms the profound impact of school climate in terms of the relationship between students and school leaders. The study focused solely on religious high schools because, in Israel, the negative impact of the pandemic was most marked there.

The study was qualitative in nature, and included semi-structured interviews with 10 religious school principals in Israel. Study participants were asked about the existing school climate and their management style in light of the COVID-19 period.

This study indicated that positive school climate and interpersonal relationships between principals and students were affected by the COVID-19 crisis. Study participants reported that principals had to work arduously in the post-COVID-19 period to restore and improve positive school climate and consequently their management style also needed altering. Specifically, restoring open lines of communication and a sense of belonging as the main components of the school climate were the main foci of principal work. The principals' management style had to be more open and inclusive to restore a sense of belonging and security among students.

The study highlights the importance of an open and inclusive management style to restore positive school climate after crises.

The purpose of this paper is to explore existing and desired methodologies for systematic quality work to promote quality in preschools from the principal’s perspective.

A collaborative approach was used in this research project, and principals were asked to complete portfolio assignments. Their answers to those portfolio assignments were analysed by the research team and subsequently compared to total quality management values.

Existing and desired methodologies for systematic quality work are presented and sorted into 13 and 17 groups, respectively. The principals desire four times more methodologies than they are presently using to promote systematic quality work, and the results show that they must extend their methodologies to support TQM values.

This research is based on answers collected from 18 principals in one municipality in Sweden.

The use of the cornerstone model provides a framework to illustrate the application of TQM in preschools.

Principals struggle to find time for systemic quality work. The presented results can be used to work systematically with quality in preschools and other organizations.

The purpose of this study was to explore school principals’ job crafting profiles during the prolonged COVID-19 crisis in 2021, and investigate profile differences regarding principals’ own perceived servant leadership, stress and work meaningfulness.

Using latent profile analysis (LPA), two job crafting profiles were identified: (1) active crafters (55%) and (2) average crafters (45%). By auxiliary measurement-error-weighted-method (BCH), we examined whether and how job crafting profiles differed in terms of servant leadership, stress and work meaningfulness.

Active crafters reported higher than the overall mean level of approach-oriented job crafting (increasing job resources and demands), whereas average crafters reported an overall mean level of approach-oriented job crafting. Avoidance-oriented job crafting by decreasing hindering job demands did not differentiate the two profiles. Active crafters reported significantly higher servant leadership behavior, stress and work meaningfulness than average crafters.

Study findings provide new knowledge and reflect the implications that the unprecedented pandemic had for education. This study contributes to the existing literature within the scholarship of job crafting through empirical research during the prolonged COVID-19 pandemic. For practitioners, these study findings reflect contextual constraints, organizational processes and culture, and leadership in workplaces.

This research aimed to assess the leadership role of principals in the implementation of peace education in selected secondary schools in the Western Cape, South Africa.

This study employed qualitative research approach to assess the leadership role of principals in the implementation of peace education in selected secondary schools in the Western Cape, South Africa. Data were gathered from a small sample of six principals from six selected secondary schools which were engaged in the implementation of a peace education programme, and data were analysed using thematic content analyses.

Findings of the study suggest that principals possess a low level of understanding or awareness of their leadership role in the implementation of peace education. The study pointed out the constraints such as time constraints and learners' negative attitudes and social influences hinder the effective implementation of peace education in selected secondary schools.

First, the data were self-reported and therefore subject to social desirability bias; participants may have provided socially desirable responses rather than their true belief or experiences. Thus, participants may have overstated their role in and commitment to the peace education programme.

Studies that aim to explore alternative approaches to combat violence, such as peace education, are still limited in South Africa. Hence, this paper served to close that gap by contributing to the growing body of research on the leadership role of the principal in the implementation of peace education in the school and exploring barriers hampering its effective implementation.

This paper extends the authors’ previous research work investigating resilience for municipal infrastructure from an asset management perspective. Therefore, this paper aims to formulate a pavement resilience index while incorporating asset management and the associated resilience indicators from the authors’ previous research work.

This paper introduces a set of holistic-based key indicators that reflect municipal infrastructure resiliency. Thenceforth, the indicators were integrated using the weighted sum mean method to form the proposed resilience index. Resilience indicators weights were determined using principal components analysis (PCA) via IBM SPSS®. The developed framework for the PCA was built based on an optimization model output to generate the required weights for the desired resilience index. The output optimization data were adjusted using the standardization method before performing PCA.

This paper offers a mathematical approach to generating a resilience index for municipal infrastructure. The statistical tests conducted throughout the study showed a high significance level. Therefore, using PCA was proper for the resilience indicators data. The proposed framework is beneficial for asset management experts, where introducing the proposed index will provide ease of use to decision-makers regarding pavement network maintenance planning.

The resilience indicators used need to be updated beyond what is mentioned in this paper to include asset redundancy and structural asset capacity. Using clustering as a validation tool is an excellent opportunity for other researchers to examine the resilience index for each pavement corridor individually pertaining to the resulting clusters.

This paper provides a unique example of integrating resilience and asset management concepts and serves as a vital step toward a comprehensive integration approach between the two concepts. The used PCA framework offers dynamic resilience indicators weights and, therefore, a dynamic resilience index. Resiliency is a dynamic feature for infrastructure systems. It differs during their life cycle with the change in maintenance and rehabilitation plans, systems retrofit and the occurring disruptive events throughout their life cycle. Therefore, the PCA technique was the preferred method used where it is data-based oriented and eliminates the subjectivity while driving indicators weights.

This study addressed a relatively understudied process of school leadership: the principal-teacher conversation about instructional change. Two distinct conversation structures were examined: controlling conversation and transformative leadership conversation (TLC). Self-determination theory (SDT) was used to make the case that TLC is a better fit for instructional change than controlling conversation. Hypotheses were developed on the relationship between principal-teacher conversation and teacher trust in the principal, teacher autonomy and teacher vitality. These mental states were identified for empirical testing because of their influence on change processes.

The empirical study used a correlational research design with survey data. The data came from a random sample of 2,500 teachers from the population of certified teachers in a southwestern state in the USA. Useable survey responses were obtained from 1,615 teachers, for a response rate of 65 percent. Teachers in the sample averaged 15 years of teaching experience, with 7 years in their current school. Around 81% of teachers identified as female and 18 percent as male and 79% of teachers listed a racial identification as white. Hypotheses were tested in a path model using AMOS 28.0 with robust maximum likelihood (MLR).

As hypothesized, TLC had moderate to strong positive relationships with teacher trust in the principal, teacher autonomy and teacher vitality. Controlling conversation had small, negative relationships with teacher trust in the principal and teacher autonomy. Controlling conversation was not related to teacher vitality in the path analysis. Compared with controlling conversation, TLC had stronger relationships with teacher mental states.

The results of this study begin to reveal useful evidence on the inherent social-psychological mechanisms active in principal-teacher conversations. With results indicating that conversation structure has consequences for positive teacher mental states, the study directs attention to a ubiquitous yet understudied leadership process.

Although risk culture is a key determinant for an effective risk management, identifying the risk culture of a firm can be challenging due to the abstract concept of culture. This paper proposes a novel approach that uses unsupervised machine learning techniques to identify significant features needed to assess and differentiate between different forms of risk culture.

To convert the unstructured text in our sample of banks' 10K reports into structured data, a two-dimensional dictionary for text mining is built to capture risk culture characteristics and the bank's attitude towards the risk culture characteristics. A principal component analysis (PCA) reduction technique is applied to extract the significant features that define risk culture, before using a K-means unsupervised learning to cluster the reports into distinct risk culture groups.

The PCA identifies uncertainty, litigious and constraining sentiments among risk culture features to be significant in defining the risk culture of banks. Cluster analysis on the PCA factors proposes three distinct risk culture clusters: good, fair and poor. Consistent with regulatory expectations, a good or fair risk culture in banks is characterized by high profitability ratios, bank stability, lower default risk and good governance.

The relationship between culture and risk management can be difficult to study given that it is hard to measure culture from traditional data sources that are messy and diverse. This study offers a better understanding of risk culture using an unsupervised machine learning approach.

Investors often utilize brokers to assist them in property acquisitions. These brokers are compensated through a cooperative commission, or bonus, that is publicized on the listing service. The purpose of this paper is to determine the relationship between advertised compensation packages and selling price, time-on-market and listing characteristics.

To examine variables likely to influence earnings of the buyers' broker, this study utilizes multiple and logistic regressions. Given the range of prices found in the 196,276 listings, the data was sorted on listing price and then split into ten, approximately equal, deciles.

The explanatory power of models with cooperative commission as the dependent variable was highest in the lowest deciles with type of financing, size and distressed status being highly significant. When comparing list- to selling price the average was 96.1%. As cooperative commission increased, the higher priced parcels sold at a higher price relative to list price. This potentially justifies higher cooperative commissions or exemplifies the principal-agent problem where effort is based on potential earnings. Fixed bonuses were used predominately for parcels under $62,234, likely to provide a minimum earnings amount. However, surrounding the median, it seems they may differentiate a property.

This research provides insight for practitioners on the impact of different variables, including cooperative commissions, on sale price and time-on-market. For example, cooperative commission increased for properties in the outer deciles implying that agents may be compensating for suspected difficulty. Additionally, the seasonality findings imply that agents can determine when to list and when to provide a fixed bonus to solicit attention. Results also suggest that practitioners will find it beneficial to market at an appropriate price rather than list high to create negotiating room.

This paper follows only one paper that covered a similar topic. However, this paper uses twenty years of multi-unit property listings from a major US city from 1996 to 2015. The focus on multi-unit properties is an effort to focus on a more sophisticated group of buyers that may be more experienced and make decisions more rationally.

Current school leadership research has primarily utilized quantitative methods to explore the relationship between leadership and teacher learning. However, there is a notable gap in understanding how principals facilitate professional learning, especially in centralized educational settings. This study aims to address this gap by examining the role of school leadership in enhancing teacher professional learning within a highly centralized education system.

This qualitative case study delves into the lived experiences of 15 teachers and eight school leaders in eight primary schools in Mashhad, Iran. Through semistructured interviews, researchers employed open and axial coding to systematically explore and categorize qualitative data. The study focuses on understanding the role of principal leadership in facilitating teacher professional learning by connecting themes and sub-themes across transcripts.

Effective principals worked on the cultivation of a culture that champions perpetual personal growth and development, the nurturing of a collaborative learning community, and the provision of essential resources and support. Findings showed the pivotal role of principals in promoting teachers' self-development, facilitating idea exchange and acknowledging their efforts. Principals appeared as key to encouraging information sharing, fostering collective learning, promoting professional development, overseeing teaching practices and ensuring the availability of resources to cultivate a supportive climate in a centralized education context.

We concluded that in centralized education, leadership practices for promoting teacher learning share similarities and differences with decentralized settings. The findings offer guidance for principals in centralized systems, supporting them in facilitating teacher professional learning in their schools.

The swivel construction method is a specially designed process used to build bridges that cross rivers, valleys, railroads and other obstacles. To carry out this construction method safely, real-time monitoring of the bridge rotation process is required to ensure a smooth swivel operation without collisions. However, the traditional means of monitoring using Electronic Total Station tools cannot realize real-time monitoring, and monitoring using motion sensors or GPS is cumbersome to use.

This study proposes a monitoring method based on a series of computer vision (CV) technologies, which can monitor the rotation angle, velocity and inclination angle of the swivel construction in real-time. First, three proposed CV algorithms was developed in a laboratory environment. The experimental tests were carried out on a bridge scale model to select the outperformed algorithms for rotation, velocity and inclination monitor, respectively, as the final monitoring method in proposed method. Then, the selected method was implemented to monitor an actual bridge during its swivel construction to verify the applicability.

In the laboratory study, the monitoring data measured with the selected monitoring algorithms was compared with those measured by an Electronic Total Station and the errors in terms of rotation angle, velocity and inclination angle, were 0.040%, 0.040%, and −0.454%, respectively, thus validating the accuracy of the proposed method. In the pilot actual application, the method was shown to be feasible in a real construction application.

In a well-controlled laboratory the optimal algorithms for bridge swivel construction are identified and in an actual project the proposed method is verified. The proposed CV method is complementary to the use of Electronic Total Station tools, motion sensors, and GPS for safety monitoring of swivel construction of bridges. It also contributes to being a possible approach without data-driven model training. Its principal advantages are that it both provides real-time monitoring and is easy to deploy in real construction applications.