bluuebunny/crossref_metadata_2025_split huggingface dataset:
Master teachers as system leaders of professional learning: master teacher studios in China
Authors: Zhang Meng , Walker Allan David , Qian Haiyan 
Published: July 2021

PurposeThis study aims to describe and analyze an innovative mechanism of teacher-led, system-wide professional learning that has been widely adopted since the beginning of the twenty-first century in China – the Master Teacher Studio (MTS).Design/methodology/approachThis paper drew from policy documents, published Chinese literature relating to MTSs and personal fieldwork experience in Shanghai, Guangdong and Zhejiang province.FindingsThe article first outlines the context framing the system change, including its policy background and evolution, and then the MTS's purpose, formative process and structure. It finally examines major teacher learning activities and the leadership roles of the MTS hosts (leaders).Research limitations/implicationsThis study contributed to the knowledge base of system teacher leaders and how they lead cross-school leading.Practical implicationsThe MTS initiative described in this article shows the power of central system leadership to spread and embed effective teacher learning practices at schools.Originality/valueThis article provides implications for understanding and practicing teacher system leadership to support teacher professional learning in different societies.
Psychological hardiness as a mediator variable between workplace bullying and job anxiety among early childhood teachers: implications for healthcare
Authors: Ahmed Ghada Farghal Gaber 
Published: July 2021

Purpose
Early childhood teachers play a significant role in building children’s success in their first years of school. Therefore, a healthy early childhood workforce in a healthy working environment is an essential aspect of effective early childhood services. This paper aims to explore the extent to which psychological hardiness can be considered as a mediator variable between exposure to workplace bullying and job anxiety among early childhood teachers.

Design/methodology/approach
A homogeneous sample comprised of 200 early childhood teachers. For data collection, the researcher used the workplace bullying scale, the psychological hardiness scale and the job anxiety scale among early childhood teachers (prepared by the researcher).

Findings
The findings indicated that psychological hardiness mediates the relationship between exposure to workplace bullying and job anxiety among early childhood teachers.

Originality/value
The research result highlighted the necessity of providing counseling programs for early childhood teachers helping them eliminate work stress that affects their job performance. In addition, the kindergarten administration must concentrate on how to effectively communicate and cooperate with early childhood teachers in light of regulations, policies and laws to defeat the spread of workplace bullying. The results of this research contributed to the existing literature by examining the relationship between the research variables, particularly in the early childhood education context.
HDPL: a hybrid descriptor for points and lines based on graph neural networks
Authors: Guo Zirui , Lu Huimin , Yu Qinghua , Guo Ruibin , Xiao Junhao , Yu Hongshan 
Published: July 2021

Purpose
This paper aims to design a novel feature descriptor to improve the performance of feature matching in challenge scenes, such as low texture and wide-baseline scenes. Common descriptors are not suitable for low texture scenes and other challenging scenes mainly owing to encoding only one kind of features. The proposed feature descriptor considers multiple features and their locations, which is more expressive.

Design/methodology/approach
A graph neural network–based descriptors enhancement algorithm for feature matching is proposed. In this paper, point and line features are the primary concerns. In the graph, commonly used descriptors for points and lines constitute the nodes and the edges are determined by the geometric relationship between points and lines. After the graph convolution designed for incomplete join graph, enhanced descriptors are obtained.

Findings
Experiments are carried out in indoor, outdoor and low texture scenes. The experiments investigate the real-time performance, rotation invariance, scale invariance, viewpoint invariance and noise sensitivity of the descriptors in three types of scenes. The results show that the enhanced descriptors are robust to scene changes and can be used in wide-baseline matching.

Originality/value
A graph structure is designed to represent multiple features in an image. In the process of building graph structure, the geometric relation between multiple features is used to establish the edges. Furthermore, a novel hybrid descriptor for points and lines is obtained using graph convolutional neural network. This enhanced descriptor has the advantages of both point features and line features in feature matching.
We versus me: Indirect conditional effects of collectivism on COVID-19 public policy hypocrisy
Authors: Bok Stephen , Shum James , Harvie Jason , Lee Maria 
Published: July 2021

PurposeDuring the early SARS-CoV-2 (COVID-19) pandemic outbreak, the Center for Disease Control and Prevention (CDC) stated masks “may not protect the wearer, but it may keep the wearer from spreading the virus to others”. Health officials revised mask guidelines to include both the wearer and others, but contradiction became a focal point for online debate and credibility. While revised policies eventually became adopted by the public, there was loss time and lives during this critical stage. This study investigates collectivist messaging on public policy support.Design/methodology/approachCOVID-19 public policy hypocrisy was defined as the gap between supporting community policies while rejecting policies more likely to impact the individual. United States participants (N = 1,605) completed questionnaires. Moderated mediation analysis was conducted using SPSS PROCESS.FindingsThose high on collectivism and high on global personal impact associated with lower COVID-19 public policy hypocrisy. These individuals indicated consistent support for community and individual policies, likely requiring personal sacrifices. Indirect conditional effects of lower conscientiousness associated with higher hypocrisy among those collectivistic.Originality/valueParticipants evaluated preference to original public safety ads, representative of basic societal and individual benefits. Those higher on collectivism preferred societal “we” versus individual “me” public safety ads. Implications discuss benefits of personal and communal public health messaging in an individualistic society so businesses can reopen. Entrepreneurs experienced major economic setbacks that effective public health policies could have mitigated.
A tale of the financial inclusion-growth nexus and the degree of financial inclusion: a dynamic panel approach on selected developing countries
Authors: Nandi Biplob Kumar , Hasan Gazi Quamrul , Kabir Md. Humayun 
Published: July 2021

Purpose
This study aims to examine the impact of financial inclusion on per capita gross domestic product (GDP) at varying degrees of financial inclusion for a sample of 76 developing countries between 2011 and 2017. To evaluate the heterogeneous impact, this paper constructs the multi-dimension index of financial inclusion to classify sample countries into two sub-samples in terms of the value of FIID, taking account of three dimensions of financial inclusion: access, usage and availability.

Design/methodology/approach
This study attempts to identify the presence of reverse causality and long-run relationship between financial inclusion and economic growth by using the Granger causality test (Wald test) and three alternative panel cointegration tests (Kao Test, Pedroni Test, Westerlund Test) respectively. Because of the existence of the bi-directional causality between financial inclusion and per capita GDP, this study uses a fixed effect instrumental variable model with lagged dependent variable to get unbiased estimators from the panel regressions for sample countries.

Findings
This paper finds a strong positive impact of financial inclusion on per capita GDP growth in sample developing countries, controlling for labor market structure, financial institutions’ efficacy, infrastructural and governance issues. This study suggests that economic growth will be high in developing economies with a higher level of financial inclusion; however, the positive impact for two sub-samples countries (low and medium level of inclusion and high level of inclusion) are heterogeneous. The estimated result explains that a 1% increase in the financial inclusion index leads to a 0.0153% point increase in the per capita GDP for the countries with a low and medium level of financial inclusion, while this positive impact is significantly higher, 0.0794% point for countries with the high level of financial inclusion. This study also suggests that the higher concentration in the financial market by few agents and the lower level of governance may have an adverse impact on economic growth for the economies with a low and medium level of financial inclusion.

Originality/value
This study is an original study that contributes to the research gap by explaining the heterogeneous impact of financial inclusion on economic growth at varying degrees of inclusion in the two sub-sample countries. Moreover, this study posits greater appeal as it explores the issue using the sample of only developing economies.
A reliable location-inventory-routing three-echelon supply chain network under disruption risks
Authors: Mohebban-Azad Ehsan , Abtahi Amir-Reza , Yousefi-Zenouz Reza 
Published: July 2021

Purpose
This study aims to design a reliable multi-level, multi-product and multi-period location-inventory-routing three-echelon supply chain network, which considers disruption risks and uncertainty in the inventory system.

Design/methodology/approach
A robust optimization approach is used to deal with the effects of uncertainty, and a mixed-integer nonlinear programming multi-objective model is proposed. The first objective function seeks to minimize inventory costs, such as ordering costs, holding costs and carrying costs. It also helps to choose one of the two modes of bearing the expenses of shortage or using the excess capacity to produce at the expense of each. The second objective function seeks to minimize the risk of disruption in distribution centers and suppliers, thereby increasing supply chain reliability. As the proposed model is an non-deterministic polynomial-time-hard model, the Lagrangian relaxation algorithm is used to solve it.

Findings
The proposed model is applied to a real supply chain in the aftermarket automotive service industry. The results of the model and the current status of the company under study are compared, and suggestions are made to improve the supply chain performance. Using the proposed model, companies are expected to manage the risk of supply chain disruptions and pay the lowest possible costs in the event of a shortage. They can also use reverse logistics to minimize environmental damage and use recycled goods.

Originality/value
In this paper, the problem definition is based on a real case; it is about the deficiencies in the after-sale services in the automobile industry. It considers the disruption risk at the first level of the supply chain, selects the supplier considering the parameters of price and disruption risk and examines surplus capacity over distributors’ nominal capacity.
Analysis and genetic algorithm optimization of a series system with K-out-of-(n + m): G mixed standby subsystems subject to imperfect switching and elapsed repair time
Authors: Temraz Neama 
Published: July 2021

PurposeIn this paper, a new general system consisted of l subsystems connected in series is introduced. Each subsystem connected in K-out-of-(n + m): G mixed standby configuration.Design/methodology/approachThe lifetime of the system's units is assumed to be exponentially distributed and there is elapsed repair time with general distribution. The switch in each subsystem is assumed to be imperfect with the failure process follows an exponential distribution. A genetic algorithm is applied to the system to obtain the optimal solution of the system and solve the redundancy allocation problem.FindingsAnalysis of availability, reliability, mean time to failure and steady-state availability of the system is introduced. The measures of the system are discussed in special two cases when the elapsed repair time follows gamma and exponential distribution. An optimization problem with bi-objective functions is introduced to minimize the cost of the system and maximize the reliability function. A numeric application is introduced to show the implementation and effectiveness of the system and redundancy allocation problem.Originality/valueA new general K-out-of-(n + m): G mixed standby model with elapsed repair time and imperfect switching is introduced.
Systematic literature review on business process re-engineering approaches in logistics
Authors: Li Na , Nazif Habibeh 
Published: July 2021

PurposeBPR is “the central reconsideration and thorough restructuring of business procedures to enhance the critical and contemporary aspects of performance like the expense, quality, service, and speed”. Also, as it's a key factor for guaranteeing businesses' achievement, however, the profound discussion about the BPR is very rare as far as we know. We need more studies regarding the subject due to the absence of BPR works in the logistics industry. Hence, this study investigates the Systematic Literature Review (SLR) of BPR for logistics companies, leading the managers and writers active in BPR, and making them aware of the present, past and future trends in this discipline.Design/methodology/approachAs BPR is a necessary foundation for ensuring enterprise systems' success, this study will systematically investigate the BPR in logistics. The proposed BPR in logistics research classification framework is based on a comprehensive literature review, which concentrates on peer-reviewed journal papers published until 2019. A total of 22 academic sources have been retrieved and analyzed in terms of research purpose and nature, the employed method, theoretical approach and analysis level.FindingsThe findings of this paper showed that BPR companies outperform the non-BPR ones regarding information computing, technology uses, organizational architecture, coordination and all key logistics procedures. The results can motivate non-BPR logistics organizations to reassess the feasibility of these plans.Research limitations/implicationsThis paper provides an overview of BPR to young academics. Also, it identifies some distinct research gaps that could be worth studying. However, this paper may be restricted by choice of dimensions and the selection of relevant articles. In turn, researchers need to become more innovative in terms of their research techniques when examining BPR implementation.Practical implicationsThis paper guides researchers and practitioners to insight into published research work and their findings. The findings are valuable to logistics firms in an emerging market, as logistics resources may affect logistics service costs and quality. Also, it discusses indications for future research in BPR. It emphasizes the need to bridge the lacuna between BPR theory and evidence-based practice. Furthermore, it provides a better understanding of BPR implementation, which can be applied toward overcoming operational difficulties during the implementation process.Originality/valueThis paper fulfills an identified need for a comprehensive classification framework of BPR in logistics studies. We can consider it as the first-evaluated methodically gathered workaround BPR in logistics. It essentially provides both academics and practitioners with a conceptual map of existing BPR in logistics research and points out future research opportunities.
Effects of personality on the efficacy of judgmental adjustments of statistical forecasts
Authors: Eroglu Cuneyt , Sanders Nada R. 
Published: July 2021

PurposeThe purpose of this paper is to investigate the effects of personality dimensions (conscientiousness, neuroticism, extraversion, agreeableness, openness to experience, locus of control) on the efficacy of judgmental adjustments of statistical forecasts.Design/methodology/approachThis paper uses a two-level hierarchical linear model to analyze a large data set obtained from an organizational setting (a quick service restaurant chain) that includes 3,812 judgmental adjustments of sales forecasts made by 112 store managers.FindingsThe results indicate that the average forecast accuracy improves as a result of judgmental adjustments, but performance of individual forecasters varies considerably based on their personality. Specifically, the trait of openness to experience tends to improve forecast accuracy while extraversion and external locus of control have negative effects.Originality/valueIntegration of human judgment with analytics algorithms is a major challenge for organizations. Documenting the impact of these traits on forecast accuracy opens the door for forecasting support system design, training, personnel selection and correction strategies that can be applied to judgmental adjustments.
Gamification and customer experience: the mediating role of brand engagement in online grocery retailing
Authors: Jami Pour Mona , Rafiei Khadije , Khani Monireh , Sabrirazm Atena 
Published: July 2021

Purpose
In recent years, the concept of gamification is one of the fastest-growing trends in the field of marketing to persuade, motivate and manipulate customer behavior. The application of gamification has become a priority for marketers as a new way of exploiting customers. Despite the increasing use of gamification mechanisms in marketing activities, there remain limitations. Although there is extensive literature in the field of customer experience and gamification, few studies have empirically examined how gamification influences customer experience by considering the mediating role of brand engagement in the online retailing context.

Design/methodology/approach
To obtain this aim, a cross-sectional survey was used. The statistical population was customers of online grocery retailers. The convenience sampling technique was used as a sampling technique. Out of 402 received questionnaires, 384 were selected for analysis. Structural equation modeling approach was applied to test the research hypotheses using AMOS 24 and SPSS 22 software.

Findings
The results indicated that all research hypotheses were supported. Gamification has a significant and positive impact on customer experience, gamification has a positive and significant effect on user customer brand engagement and customer brand engagement has a positive and significant impact on customer experience. Also, it revealed that customer brand engagement mediates between gamification and customer experience.

Originality/value
A review of the digital marketing literature reveals that there are few empirical studies, which adequately examined significant effective factors of customer experience in online grocery retailing; despite, the majority of researchers consider customer experience as the most important concept in digital marketing. The main contribution of this study is to examine the role of gamification on customer experience through the mediating role of customer engagement in the online grocery context. It adds value to the digital marketing and online retailing literature by providing new insight about determinants of customer experience in online grocery.
Bankruptcy filings, flooding, real estate prices and Leading Index
Authors: Brotman Billie Ann 
Published: July 2021

PurposeFlood damage to uninsured single-family homes shifts the entire burden of costly repairs onto the homeowner. Homeowners in the United States and in much of Europe can purchase flood insurance. The Netherlands and Asian countries generally do not offer flood insurance protection to homeowners. Uninsured households incur the entire cost of repairing/replacing properties damaged due to flooding. Homeowners’ policies do not cover damage caused by flooding. The paper examines the link between personal bankruptcy and the severity of flooding events, property prices and financial condition levels.Design/methodology/approachA fully modified ordinary least squares (FMOLS) regression model is developed which uses personal bankruptcy filings as its dependent variable during the years 2000 through 2018. This time-series model considers the association between personal bankruptcy court filings and costly, widespread flooding events. Independent variables were selected that potentially act as mitigating factors reducing bankruptcy filings.FindingsThe FMOLS regression results found a significant, positive association between flooding events and the total number of personal bankruptcy filings. Higher flooding costs were associated with higher bankruptcy filings. The Home Price Index is inversely related to the bankruptcy dependent variable. The R-squared results indicate that 0.65% of the movement in the dependent variable personal bankruptcy filings is explained by the severity of a flooding event and other independent variables.Research limitations/implicationsThe severity of the flooding event is measured using dollar losses incurred by the National Flood Insurance program. A macro-case study was undertaken, but the research results would have been enhanced by examining local areas and demographic factors that may have made bankruptcy filing following a flooding event more or less likely.Practical implicationsThe paper considers the impact of the natural disaster flooding on bankruptcy rates filings. The findings may have implications for multi-family properties as well as single-family housing. Purchasing flood insurance generally mitigates the likelihood of severe financial risk to the property owner.Social implicationsNatural flood insurance is underwritten by the federal government and/or by private insurers. The financial health of private property insurers that underwrite flooding and their ability to meet losses incurred needs to be carefully scrutinized by the insured.Originality/valuePrior studies analyzing the linkages existing between housing prices, natural disasters and bankruptcy used descriptive data, mostly percentages, when considering this association. The study herein posits the same questions as these prior studies but used regression analysis to analyze the linkages. The methodology enables additional independent variables to be added to the analysis.