bluuebunny/crossref_metadata_2025_split huggingface dataset:
The role of network relations and previous knowledge in the ACAP of low-tech intensity clusters
Authors: Serra Fernando Antonio Ribeiro , Carneiro-da-Cunha Julio Araujo , Vils Leonardo , Rossetto Carlos Ricardo 
Published: August 2022

PurposeThe mainstream research on knowledge transfer and absorptive capacity (ACAP) in clusters was conducted in high-technology industries in developing countries. However, low technology intensity clusters present a different scenario that might affect this external knowledge transfer and ACAP. This study aims to understand the role of network relations and previous knowledge in the ACAP of a low-technology intensity cluster.Design/methodology/approachThe authors analyzed companies from a low-technology industry in an emerging country. The authors collected 109 questionnaires from companies in the Brazilian footwear manufacturing cluster. Factor analysis led the independent variables to be regrouped into eight variables. This data set was analyzed using regression techniques.FindingsIn a low-tech cluster prevalently populated by small companies, companies have access to novelties and knowledge that influence their products and production through the frequency and stability of the network’s relational ties with the supplier. The quality of relationships with clients may provide access to products, materials, technologies and learning. Small companies consider intra-cluster competition because of limitations in accessing external competition. Although low-tech companies need to exchange knowledge and technology with suppliers and clients outside the cluster, most companies are limited in size because of liabilities. In a low-tech cluster dominated by small companies, access to better purchasing costs, new technologies or innovations is an expected weakness. Intra- and extra-cluster ties positively influenced ACAP, as did organizational capabilities, whereas employees’ skills did not.Originality/valueIndividual skills are not related to ACAP in low-technology intensity clusters. The level of ACAP in small and medium enterprises (SMEs) can be explained by the scope of individuals’ knowledge and other individual capabilities.
Slope reliability analysis using Bayesian optimized convolutional neural networks
Authors: Lin Houlai , Li Liang , Meng Kaiqi , Li Chunli , Xu Liang , Liu Zhiliang , Lu Shibao 
Published: August 2022

PurposeThis paper aims to develop an effective framework which combines Bayesian optimized convolutional neural networks (BOCNN) with Monte Carlo simulation for slope reliability analysis.Design/methodology/approachThe Bayesian optimization technique is firstly used to find the optimal structure of CNN based on the empirical CNN model established in a trial and error manner. The proposed methodology is illustrated through a two-layered soil slope and a cohesive slope with spatially variable soils at different scales of fluctuation.FindingsThe size of training data suite, T, has a significant influence on the performance of trained CNN. In general, a trained CNN with larger T tends to have higher coefficient of determination (R2) and smaller root mean square error (RMSE). The artificial neural networks (ANN) and response surface method (RSM) can provide comparable results to CNN models for the slope reliability where only two random variables are involved whereas a significant discrepancy between the slope failure probability (Pf) by RSM and that predicted by CNN has been observed for slope with spatially variable soils. The RSM cannot fully capture the complicated relationship between the factor of safety (FS) and spatially variable soils in an effective and efficient manner. The trained CNN at a smaller the scale of fluctuation (λ) exhibits a fairly good performance in predicting the Pf for spatially variable soils at higher λ with a maximum percentage error not more than 10%. The BOCNN has a larger R2 and a smaller RMSE than empirical CNN and it can provide results fairly equivalent to a direct Monte Carlo Simulation and therefore serves a promising tool for slope reliability analysis within spatially variable soils.Practical implicationsA geotechnical engineer could use the proposed method to perform slope reliability analysis.Originality/valueSlope reliability can be efficiently and accurately analyzed by the proposed framework.
Comparative study for multi-variable regression methods based on Laguerre polynomial and manifolds optimization
Authors: Li Zibo , Yan Zhengxiang , Li Shicheng , Sun Guangmin , Wang Xin , Zhao Dequn , Li Yu , Liu Xiucheng 
Published: August 2022

PurposeThe purpose of this paper is to overcome the application limitations of other multi-variable regression based on polynomials due to the huge computation room and time cost.Design/methodology/approachIn this paper, based on the idea of feature selection and cascaded regression, two strategies including Laguerre polynomials and manifolds optimization are proposed to enhance the accuracy of multi-variable regression. Laguerre polynomials were combined with the genetic algorithm to enhance the capacity of polynomials approximation and the manifolds optimization method was introduced to solve the co-related optimization problem.FindingsTwo multi-variable Laguerre polynomials regression methods are designed. Firstly, Laguerre polynomials are combined with feature selection method. Secondly, manifolds component analysis is adopted in cascaded Laguerre polynomials regression method. Two methods are brought to enhance the accuracy of multi-variable regression method.Research limitations/implicationsWith the increasing number of variables in regression problem, the stable accuracy performance might not be kept by using manifold-based optimization method. Moreover, the methods mentioned in this paper are not suitable for the classification problem.Originality/valueExperiments are conducted on three types of datasets to evaluate the performance of the proposed regression methods. The best accuracy was achieved by the combination of cascade, manifold optimization and Chebyshev polynomials, which implies that the manifolds optimization has stronger contribution than the genetic algorithm and Laguerre polynomials.
Development of zero-based budgeting approach for multinational construction contractors
Authors: Kazar Gokhan , Mutlu Ugur , Tokdemir Onur Behzat 
Published: August 2022

PurposeCost overruns remain a persistent problem in the construction industry. Although various cost management strategies have been implemented, innovative approaches are still required. Therefore, the authors attempted to introduce and test a new cost management strategy for the construction industry.Design/methodology/approachZero-based budgeting (ZBB) is one such method whose effectiveness has been proven in different industries over many years. Therefore, the authors initially developed two different frameworks related to the integration of ZBB into a multinational construction contractor and the application process of ZBB for a construction project in this study. Then, the effectiveness and feasibility of the proposed frameworks are tested via an actual field study in a mega construction project.FindingsThe results show savings of 0.81% of the total project budget and 4.74% of the focused cost items by following the ZBB framework compared to the traditionally estimated project budget. The feedback received from the employees in the construction company shows that ZBB could be efficiently implemented during ongoing construction projects.Research limitations/implicationsThe authors believe that implementing new cost management strategies such as ZBB will open doors to deal with the complex cost overrun issues and improve construction cost performances.Originality/valueThis manuscript is the first actual application of the ZBB cost management approach in the construction industry.
For concurrent enrollment, collaboration, not alignment, is the better story
Authors: Scarbrough Burke 
Published: August 2022

PurposeAs concurrent enrollment (CE) programs continue to expand in the USA, a growing share of English teaching at the first-year university level is taking place in secondary schools. Though much of the discourse surrounding CE courses relates to quality control, the purpose of this paper is to argue for a reconsideration of the terms by which these courses are valued, calling for a shift from alignment to collaboration as the crucial work for participating English teachers.Design/methodology/approachThis essay responds to scholarship and primary source documents related to CE programs in light of the author’s experience as liaison for a CE literature course at a Midwestern regional university in the USA.FindingsAn ethic of alignment pervades discourse about CE programs. The quality control promised by this “alignment story” presupposes a stable university course to be aligned with and the emulation of college faculty pedagogy as the high-priority intellectual labor. This alignment story is undermined by the variation within and between on-campus and high school iterations of the literature course. Rather than justifying an alignment ethic, this variation continually renews important questions about what constitutes college-level engagement with literature and how to best help students achieve it in a particular setting. These questions call for deliberation among a community of English teachers, not alignment of one constituency to another.Originality/valueThis essay builds on previous scholarship about the importance of alignment and the opportunity for collaboration in CE by exploring how an emphasis on the former misrecognizes the importance of the latter.
Spatio-temporal vegetation cover analysis to determine climate change in Papua New Guinea
Authors: Sekac Tingneyuc , Jana Sujoy Kumar , Pal Indrajit 
Published: August 2022

Purpose
The climate change and related impacts are experienced around the world. There arise different triggering factors to climate change and impact. The purpose of this study is to figure out how changes in vegetation cover may or may not have an impact to climate change. The research will produce ideas for vegetation preservation and replant.

Design/methodology/approach
The investigation was probed for 34 years’ time period starting from the year 1981 to 2015. After testing and checking for serial autocorrelation in the vegetation data series, Mann–Kendal nonparametric statistical evaluation was carried out to investigate vegetation cover trends. Sen’s method was deployed to investigate the magnitude of vegetation cover change in natural differential vegetation index (NDVI) unit per year. Furthermore, the ArcGIS spatial analysis tools were used for the calculation of mean NDVI distribution and also for carrying out the spatial investigation of trends at each specific location within the study region.

Findings
The yearly mean NDVI during the study period was observed to have a decreasing trend. The mean NDVI value ranges between 0.32 and 0.98 NDVI unit, and hence, this means from less or poor vegetated zones to higher or healthier vegetated zones. The mean NDVI value was seen decreasing toward the highlands regions. The NDVI-rainfall correlation was observed to be stronger than the NDVI-temperature correlation. The % area coverage of NDVI-rainfall positive correlation was higher than the negative correlation. The % area coverage of NDVI-temperature negative correlation was higher than the positive correlation within the study region. Rainfall is seen as a highly influencing climatic factor for vegetation growth than the temperature within the study region.

Originality/value
This study in this country is a new approach for climate change monitoring and planning for the survival of the people of Papua New Guinea, especially for the farmer and those who is living in the coastal area.
How instructional leaders promote parental involvement: the Israeli case
Authors: Shaked Haim 
Published: August 2022

PurposeInstructional leadership is an educational leadership approach in which principals are regularly and actively involved in a wide range of activities aimed at improving teaching and learning. The current study sought to answer how the principal's role in promoting parental involvement is part of their instructional leadership responsibility.Design/methodology/approachData were collected through semi-structured interviews with 24 Israeli principals. Data analysis was a three-step process: sorting, coding, and categorizing.FindingsThis study revealed that principals encouraged two types of parental involvement: academic-oriented, designed to support student learning and achievement, and non-academic-oriented, designed to accomplish other goals. From the instructional leadership perspective, principals should mainly prioritize academic-oriented parental involvement. Implications and further research are discussed.Originality/valueThe question of how the role of principals in encouraging parental involvement can become a part of principals' instructional leadership has not yet been explored. The present study narrows this gap in the existing research literature.
Promoting workplace inclusion and self-efficacy among skilled migrant workers in Australia
Authors: Ng Eddy S. , Rajendran Diana , Waheduzzaman Wahed 
Published: August 2022

PurposeAlthough skilled migrants have a high capacity for integration, many report experiences of exclusion which impacts their ability to contribute fully to the host country. This experience of exclusion, which can diminish their self-efficacy at work, is especially acute for skilled migrants from non-English speaking backgrounds when functioning in a new or exclusionary environment. In this paper, we explore the relationship between workplace inclusion and self-efficacy and identify factors that contribute to perceived inclusion for skilled migrant workers.Design/methodology/approachParticipants were recruited through social network groups representing migrant workers via LinkedIn. Through snowball sampling, participants were asked to recommend recent (3–5 years) skilled migrants to participate. A total of 210 skilled migrant workers to Australia completed the survey. Structural equation modelling (SEM) is used to test our model on the relationship between inclusion and self-efficacy.FindingsMigrants' perceptions of inclusion at work are related to their self-efficacy at work. We also find that some dimensions of inclusion are more important than others in enhancing self-efficacy for skilled migrants. Meaningful exchanges with supervisors, a sense of belonging at work and workgroup cohesion (being accepted by co-workers) are more important than senior management support or getting involved in organizational social activities as determinants of perceived inclusion.Social implicationsAlthough skilled migrants are often assumed to be a self-select group of highly motivated, high achieving workers, many experience poor adjustment and feel excluded after arriving in the host country. Public policies have limited effects in promoting inclusion of skilled migrant workers in organizations. These policies may be supplemented with an inclusive organizational climate to improve migrant worker success. Organizations and employers are thus critical partners in fostering migrant workers' sense of inclusion and supporting the career outcomes of skilled migrant workers in the host country.Originality/valueThis study supports the link between perceived inclusion and self-efficacy among skilled migrant workers. It also sharpens the evidence of organizational-level factors that contribute to perceived inclusion for migrant workers.
Feverish sentiment, lockdown stringency, oil volatility, and clean energy stocks during COVID-19 pandemic
Authors: Solarin Sakiru Adebola , Gorus Muhammed Sehid , Yilanci Veli 
Published: August 2022

PurposeThis study seeks to investigate role of the coronavirus disease 2019 (COVID-19) pandemic on clean energy stocks for the United States for the period 21 January 2020–16 August 2021.Design/methodology/approachAt the empirical stage, the Fourier-augmented vector autoregression approach has been used.FindingsAccording to the empirical results, the response of the clean energy stocks to the feverish sentiment, lockdown stringency, oil volatility, dirty assets, and monetary policy dies out within a short period of time. In addition, the authors find that there is a unidirectional causality from the feverish sentiment index and the lockdown stringency index to the clean energy stock returns; and from the monetary policy to the clean energy stocks. At the same time, there is a bidirectional causality between the lockdown stringency index and the feverish sentiment index. The empirical findings can be helpful to both practitioners and policy-makers.Originality/valueAmong the COVID-19 variables used in this study is a new feverish sentiment index, which has been constructed using principal component analysis. The importance of the feverish sentiment index is that it allows us to examine the impact of the aggregate level of fear in the economy on clean energy stocks.
When servitized manufacturers globalise: becoming a provider of global services
Authors: Kreye Melanie E. 
Published: August 2022

PurposeTo increase the global competitiveness of their service business, servitized manufacturers transition towards global services. Yet, the literature has not addressed this development. This study is one of the first to investigate how servitized manufacturers can manage the globalisation of their service business.Design/methodology/approachThe study explores two cases of servitized manufacturers that transitioned from a local organisation of multi-domestic international services to a global-service organisation. The data were collected via semi-structured interviews, observations, and secondary sources.FindingsThe authors identify four elements of global service provision: operating model, global performance management, relationship governance, and staffing and employee development. The authors discuss each element and the connections between them, which the authors summarise in a proposed framework for global service provision.Originality/valueThe contributions of this research relate to the proposed framework of global service provision, which extends current conceptualisation of globalisation of routine services. The authors show the unique elements of global service provision of servitized manufacturers and discuss the theoretical and practical implications of the work.
Analysis of seepage and lubrication characteristics of bilayer porous bearing under mixed lubrication
Authors: Zhang Guotao , Cai Weijie , Wang Xiaoyi , Xu Junpeng , Yin Yanguo , Wei Xicheng 
Published: August 2022

Purpose
The purpose of this paper is to put forward the lubrication model of oil bearing and enrich the design theory under the condition of mixed lubrication.

Design/methodology/approach
A mixed lubrication model of bilayer porous bearing is established. The effects of the working conditions on the lubrication performance and seepage behavior were analyzed.

Findings
Results show that the oil film pressure mainly occurs in the bearing convergence zone and contact pressure mainly occurs near the minimum film thickness. The oil infiltrates into the porous matrix in the contact area and precipitates out to the friction surface at the inlet of the contact area. The oil seepage velocity and dynamic pressure effect at the friction interface can be improved by reasonably matching the load and speed. With the decrease of the external load or increase of the rotating speed, the lubrication performance becomes well.

Originality/value
This study provides a reference for the design and application of oil bearing under harsh working conditions.
Are you willing to forgive AI? Service recovery from medical AI service failure
Authors: Chen Aihui , Pan Yueming , Li Longyu , Yu Yunshuang 
Published: August 2022

PurposeAs an emerging technology, medical artificial intelligence (AI) plays an important role in the healthcare system. However, the service failure of medical AI causes severe violations to user trust. Different from other services that do not involve vital health, customers' trust toward the service of medical AI are difficult to repair after service failure. This study explores the links among different types of attributions (external and internal), service recovery strategies (firm, customer, and co-creation), and service recovery outcomes (trust).Design/methodology/approachEmpirical analysis was carried out using data (N = 338) collected from a 2 × 3 scenario-based experiment. The scenario-based experiment has three stages: service delivery, service failure, and service recovery. The attribution of service failure was divided into two parts (customer vs. firm), while the recovery of service failure was divided into three parts (customer vs. firm vs. co-creation), making the design full factorial.FindingsThe results show that (1) internal attribution of the service failure can easily repair both affective-based trust (AFTR) and cognitive-based trust (CGTR), (2) co-creation recovery has a greater positive effect on AFTR while firm recovery is more effective on cognitive-based trust, (3) a series of interesting conclusions are found in the interaction between customers' attribution and service recovery strategy.Originality/valueThe authors' findings are of great significance to the strategy of service recovery after service failure in the medical AI system. According to the attribution type of service failure, medical organizations can choose a strategy to more accurately improve service recovery effect.
Asset pricing in global scenario: a bibliometric analysis
Authors: Keshari Aditya , Gautam Amit 
Published: August 2022

PurposeThis study aims to organise and present the development of asset pricing models in the international environment. The stock market integration and cross-listing lead us to another objective of bibliometric analysis for “International Asset Pricing” to provide a complete overview and give scope and directions for future research.Design/methodology/approachWeb of Science database is used to search with “International Asset Pricing.” Of 3,438 articles, 2,487 articles are selected for the final bibliometric analysis. Various research such as citation analysis, keyword analysis, author’s and corresponding author's analysis have been conducted.FindingsThe bibliometric analysis finds that the USA comes out to be the country where the maximum research was conducted on the topic. The keyword analysis was also analysed to evaluate the significant areas of the research. Risk, return and international asset pricing are the most frequently used keywords. The year 2020 has the maximum number of published research articles and citations due to the change in the market structure worldwide and the effect of Covid-19 across the world.Originality/valueThe present paper provides the collection, classification and comprehensive analysis of “International Asset pricing,” which may help the academicians, researchers and practitioners for future research for the relevant subject area.