bluuebunny/crossref_metadata_2025_split huggingface dataset:
Female leadership in communication management in Spain: making a difference in a sexist culture
Authors: Zeler Ileana , Fuentes-Lara Cristina , Moreno Ángeles 
Published: November 2022

PurposeThis paper aims to explore the position of women in the communication management sector in Spain from their own experiences. The study examines female communication and leadership styles, emphasising the cost of leadership in which they are leaders or led.Design/methodology/approachThis study used a qualitative methodology based on in-depth interviews with 22 women actively working in top companies and agencies: female communication directors, female employees with a female leader and female employees with a male leader. Data were analysed through thematic analysis.FindingsResults show mixed communication and leadership styles. In addition, the high level of self-demand of female communication managers stands out, making it challenging to achieve a work-life balance and the implementation of successful role models.Social implicationsExploring the factors of female leadership remains necessary to understand and make their situation in various industries and positions visible. It also helps remove barriers to leadership, guide organisations in addressing gender discrimination issues and develop mechanisms for the internal promotion of female professionals.Originality/valueTo the best of authors' knowledge, this is the first study exploring the leadership and communication styles of women in the Spanish Public Relations (PR) and communication management industries. It also highlights the aspects influencing the cost of leadership.
Influence of big data analytical capability on new product performance – the effects of collaboration capability and team collaboration in high-tech firm
Authors: Chen Chi-hsiang 
Published: November 2022

Purpose
As the application of artificial intelligence (AI) becomes more prevalent, many high-tech firms have employed AI applications to deal with emerging societal, technological and environmental challenges. Big data analytical capability (BDAC) has become increasingly important in the AI application processes. Drawing upon the resource-based view and the theory of planned behavior, this study aims to investigate how BDAC and collaboration affect new product performance (NPP). Practically, a harmonic working team is particularly important for creating management synergies, this empirical analysis demonstrates the importance of BDAC and collaboration for NPP.

Design/methodology/approach
This paper focuses on the performance of firms that applied AI in their operations. This study collected data from firms in Greater China, including China and Taiwan, as Greater China is currently the leading manufacturer of semiconductor, electronic and electric products for AI applications in the manufacturing process. Confirmatory factor analysis and structural equation modeling is employed for statistical analysis.

Findings
The analytical results indicate that BDAC positively relates to collaboration capability (CC) in AI applications but not to team collaboration (TC). CC positively correlates with TC, and both CC and TC positively correlate with NPP. Further, the mediating effect was examined using the Sobel t-test, which reveals that CC is a significant mediator in the influence of BDAC on NPP.

Practical implications
The strategic implementation of BDAC and collaboration can allow an enterprise to improve its NPP when driven by the external environment to use AI, which further enhances NPP. These processes indicate that AI and BDAC are both crucial for the success of a company’s collaboration and for effective management to improve NPP in the face of global competition.

Originality/value
This study introduces the concept of BDAC to explain the relationship between CC and TC, as they pertain to NPP. This study presented a discussion of the theoretical and practical implications of the research findings and could provide a framework for managing BDAC.
Examining the nonlinear relationships of corporate social responsibility, innovation and construction firm performance: the moderating role of construction firms' competitive position
Authors: Zheng Xian , Deng Jiawei , Song Xiangnan , Ye Meng , Luo Lan 
Published: November 2022

PurposeCorporate social responsibility (CSR) and innovation are the two main approaches firms utilize to promote sustainable development. However, as yet, scholars have reached no consensus regarding their precise impact on construction firm performance (CFP), hindering efforts to implement effective sustainable development strategies that improve CFP. In view that a simple linear relationship may not be sufficient to capture their precise pattern, this study aims to unveil the nonlinear impact of CSR and innovation on CFP, especially when construction firms take up a distinct competitive position.Design/methodology/approachThis study first proposed four hypotheses to establish a new theoretical model by incorporating CSR, innovation, CFP and construction firms' competitive position (CFCP). Then the model was tested by using 292 annual observations collected from 75 construction firms in China. A multiple regression model analysis was carried out to analyze the survey data and validate the hypotheses.FindingsThe results reveal that both CSR and innovation have a U-shaped impact on the price-to-book ratio of a construction firm, a specific CFP measure. CFCP negatively moderates the U-shaped relationship between CSR and CFP, but positively moderates the U-shaped relationship between innovation and CFP.Originality/valueThis study goes beyond a simple linear view, instead of unveiling the nonlinear U-shaped effects of CSR and innovation on CFP that deepen the understanding of their complex relationships in the construction industry and makes construction firms aware that CSR and innovation can only improve performance if they reach a certain level. The moderating role of CFCP provides important implications for construction firms seeking to adopt appropriate competitive strategies related to social responsibility and innovation that both promote CFP and achieve sustainable development.
Examining the pathway linking workplace incivility and employee well-being: a study among frontline hotel employees in India
Authors: Kuriakose Vijay , Paul V. Maria Tresita , Bishwas Sumant Kumar 
Published: November 2022

Purpose
This study aims to analyze the direct relationship between workplace incivility and employee well-being among frontline hotel employees. Anchoring on affective events theory, this study also analyzes the explanatory role of loneliness and the role of workplace social support as a boundary condition influencing the proposed relationships in the model.

Design/methodology/approach
Responses were collected from 243 frontline hotel employees using established scales in two-time points through survey method. The proposed hypotheses were analyzed using SPSS PROCESS macros.

Findings
The results confirmed the detrimental effect of incivility at work on employee well-being and the mediating role of loneliness at work. This. study has also demonstrated that workplace social support conditions the mediated effect of workplace incivility on employee well-being via loneliness.

Practical implications
This study has vital practical implications for mitigating the adverse effects of workplace incivility on employee well-being through loneliness at work by developing interventions that foster social support among employees. This study also provides directions to reduce workplace incivility and loneliness at work.

Originality/value
This study provides a unique understanding of the consequences of workplace incivility on employee well-being. To the best of the authors’ knowledge, this could be the first study that has established loneliness as a pathway linking workplace incivility and employee well-being. This study results have unique significance in the management of hospitality employees.
Nonlinear effects of employee engagement and satisfaction on turnover intention
Authors: Oh Haemoon , Jeong Miyoung , Shin Hyejo Hailey , Schweyer Allan 
Published: November 2022

Purpose
This study aims to advance the understanding of the relationships between employee engagement (EE), satisfaction and turnover intention (TI) beyond their known linear functions by providing a set of significant empirical evidence on nonlinear functions including quadratic, cubic and interactive effects.

Design/methodology/approach
This study used four 2 × 2 between-subjects experiments sampling 640 hospitality sales professionals through online data collection methods. EE and employee satisfaction (ES) were examined in disaggregation into personal and organizational dimensions. Residual regression models controlling for age and gender as covariates were the main approaches for analyzing data for nonlinear effects.

Findings
Both EE and ES consistently have significant negative quadratic and positive cubic effects on employees’ TI. EE and ES have a negative interaction effect, that is, complementing each other, on TI such that the effect is more pronounced at higher levels than lower levels of EE and satisfaction.

Practical implications
Organizations need to understand some threshold phenomena that may exist in the widely believed linear effects of EE and satisfaction on TI. Doing so may help allocate resources more effectively for EE and satisfaction.

Originality/value
This study examined the nonlinear as well as interactive nature of the relationships between EE and TI and ES and TI to expand our understanding of these relationships beyond the known linearity and add new empirical evidence to the literature.
Demand forecasting accuracy in the pharmaceutical supply chain: a machine learning approach
Authors: Yani Luh Putu Eka , Aamer Ammar 
Published: November 2022

Purpose
Demand foresting significantly impacts supply chain (SC) design and recovery planning. The more accurate the demand forecast, the better the recovery plan and the more resilient the SC. Given the paucity of research about machine learning (ML) applications and the pharmaceutical industry’s need for disruptive techniques, this study aims to investigate the applicability and effect of ML algorithms on demand forecasting. More specifically, the study identifies machine learning algorithms applicable to demand forecasting and assess the forecasting accuracy of using ML in the pharmaceutical SC.

Design/methodology/approach
This research used a single-case explanatory methodology. The exploratory approach examined the study’s objective and the acquisition of information technology impact. In this research, three experimental designs were carried out to test training data partitioning, apply ML algorithms and test different ranges of exclusion factors. The Konstanz Information Miner platform was used in this research.

Findings
Based on the analysis, this study could show that the most accurate training data partition was 80%, with random forest and simple tree outperforming other algorithms regarding demand forecasting accuracy. The improvement in demand forecasting accuracy ranged from 10% to 41%.

Research limitations/implications
This study provides practical and theoretical insights into the importance of applying disruptive techniques such as ML to improve the resilience of the pharmaceutical supply design in such a disruptive time.

Originality/value
The finding of this research contributes to the limited knowledge about ML applications in demand forecasting. This is manifested in the knowledge advancement about the different ML algorithms applicable in demand forecasting and their effectiveness. Besides, the study at hand offers guidance for future research in expanding and analyzing the applicability and effectiveness of ML algorithms in the different sectors of the SC.
Long memory in Bitcoin and ether returns and volatility and Covid-19 pandemic
Authors: Sosa Miriam , Ortiz Edgar , Cabello-Rosales Alejandra 
Published: November 2022

Purpose
The purpose of this research is to analyze the Bitcoin (BTC) and Ether (ETH) long memory and conditional volatility.

Design/methodology/approach
The empirical approach includes ARFIMA-HYGARCH and ARFIMA-FIGARCH, both models under Student‘s t-distribution, during the period (ETH: November 9, 2017 to November 25, 2021 and BTC: September 17, 2014 to November 25, 2021).

Findings
Findings suggest that ARFIMA-HYGARCH is the best model to analyze BTC volatility, and ARFIMA-FIGARCH is the best approach to model ETH volatility. Empirical evidence also confirms the existence of long memory on returns and on BTC volatility parameters. Results evidence that the models proposed are not as suitable for modeling ETH volatility as they are for the BTC.

Originality/value
Findings allow to confirm the fractal market hypothesis in BTC market. The data confirm that, despite the impact of the Covid-19 crisis, the dynamics of BTC returns, and volatility maintained their patterns, i.e. the way in which they evolve, in relation to the prepandemic era, did not change, but it is rather reaffirmed. Yet, ETH conditional volatility was more affected, as it is apparently higher during Covid-19. The originality of the research lies in the focus of the analysis, the proposed methodology and the variables and periods of study.
Predicting the impacts of climate change on the biological control of Plutella xylostella by Diadegma semiclausum
Authors: Wang Leyun , Zhao Zihua , Walter Gimme H. , Furlong Michael J. 
Published: November 2022

Abstract
The parasitoid Diadegma semiclausum Hellén (Hymenoptera: Ichneumonidae) has been widely adopted as a biological control agent for Plutella xylostella L. (Lepidoptera: Plutellidae) over the last 80 years. Earlier studies have found differential responses to temperature between the host and its parasitoid and demonstrated the multiple ways in which the parasitoid is more susceptible to elevated temperatures.
Using data from experimental studies, the modelling package CLIMEX was used to investigate the suitability of current climates for the host and its parasitoid and the effects on their potential global geographical distributions. The study was then extended to investigate possible changes to these distributions that might result under different climate change scenarios by 2080. The models predict that the global distributions of both the host and parasitoid will be reduced. These changes will not be proportionate and many areas in tropical, sub‐tropical, and temperate regions that are currently suitable for D. semiclausum are predicted to become unsuitable for the parasitoid, whereas retaining suitability for P. xylostella. The seasonal dynamics of both the host and parasitoid are also predicted to be significantly reshaped under climate change.
Analysis of associations between annual P. xylostella outbreaks and weather conditions in three provinces in China with field data collected between 1995 and 2017 indicated significant effects of temperature on P. xylostella outbreaks at the beginning of the peak season in warmer provinces where P. xylostella can overwinter; such associations were not found in the colder provinces where it is unable to survive harsh winters.
Effectiveness and costs of a stepwise versus an all‐in‐one approach to diagnose mild bleeding disorders
Authors: Heubel‐Moenen Floor C. J. I. , Ansems Loes E. M. , Verhezen Paul W. M. , Wetzels Rick J. H. , van Oerle Rene G. M. , Straat Ron J. M. H. E. , Megy Karyn , Downes Kate , Henskens Yvonne M. C. , Beckers Erik A. M. , Joore Manuela A. 
Published: November 2022

SummaryThe diagnostic work‐up of patients referred to the haematologist for bleeding evaluation is performed in a stepwise way: bleeding history and results of screening laboratory tests guide further diagnostic evaluation. This can be ineffective, time‐consuming and burdensome for patients. To improve this strategy, the initial laboratory investigation can be extended. In a model‐based approach, effectiveness and costs of a conventional stepwise versus a newly proposed all‐in‐one diagnostic approach for bleeding evaluation were evaluated and compared, using data from an observational patient cohort study, including adult patients referred for bleeding evaluation. In the all‐in‐one approach, specialized platelet function tests, coagulation factors, and fibrinolysis tests were included in the initial investigation. Final diagnosis, hospital resource use and costs and patient burden were compared. A total of 150 patients were included. Compared to the stepwise approach, in the all‐in‐one approach, 19 additional patients reached a diagnosis and patient burden was lower, but total costs per patient were higher [€359, 95% bootstrapped confidence interval (BCI) 283–518, p = 0.001]. For bleeding evaluation of patients referred to the haematologist, an all‐in‐one diagnostic approach has a higher diagnostic yield and reduces patient burden, at a higher cost. This raises the question what costs justify the diagnosis of a bleeding disorder and a less burdensome diagnostic strategy.
Let‐7b‐5p inhibits colon cancer progression by prohibiting APC ubiquitination degradation and the Wnt pathway by targeting NKD1
Authors: Dai Yuyang , Liu Jinsong , Li Xuyan , Deng Jianzhong , Zeng Cheng , Lu Wenbin , Hou Yongzhong , Sheng Ying , Wu Honglin , Liu Qian 
Published: November 2022

AbstractNaked cuticle homolog 1 (NKD1), which is expressed at low levels in many tumors, is considered an inhibitor of the Wnt/β‐catenin pathway, but it is highly expressed in colon cancer and can promote colon cancer cell proliferation. miRNAs are involved in the occurrence and progression of many tumors. However, miRNAs that can regulate NKD1 and the mechanisms by which NKD1 regulates tumor progression remain ambiguous. This research aims to reveal the potential regulatory network of NKD1 in colon cancer. miRNA data downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were analyzed by bioinformatics to screen for potential miRNAs targeting NKD1. Let‐7b‐5p was found to inhibit proliferation, migration, and invasion of colon cancer cells targeting NKD1. Further studies suggested that let‐7b‐5p can modulate Wnt signaling activity, and the nuclear accumulation of β‐catenin was significantly restrained by let‐7b‐5p through targeting NKD1. Moreover, NKD1 could prohibit the expression of the APC protein. Further studies manifested that NKD1 bound to APC and promoted the ubiquitination degradation of APC through restraining the expression of the deubiquitinating enzyme USP15 and blocking the combination between USP15 and APC. Functionally, NKD1 enhanced the proliferation and migration of colon cancer cells by inhibiting APC expression. This research revealed a novel mechanism by which the let‐7b‐5p‐NKD1‐APC‐β‐catenin signaling pathway inhibited colon cancer cell progression.
Median raphe cysts: A clinico‐pathologic and immunohistochemical study of 52 cases
Authors: Carrasco Loreto , Torre‐Castro Juan , Ortiz Sebastián , Cuevas Santos Jesús , Jo Margarita , Rodríguez Peralto Jose Luis , Beer Trevor , Requena Luis 
Published: November 2022

AbstractBackgroundMedian raphe cysts (MRC) are epithelial‐lined cystic lesions of the genital area that do not communicate with the urethra or the overlying epidermis. Immunohistochemically, MRC show positivity for cytokeratin (CK) 5‐6, CK 7, carcinoembryonic antigen, p63 and uroplakin III (URO III). GATA3 and human milk fat globulin 1 (HMFG1) are immunohistochemical markers that have been not previously studied in MRC.MethodsWe conducted a study of 52 patients diagnosed with MRC in the Pathology Departments of eight hospitals between 1990 and 2016. The monoclonal antibodies used were CK5‐6, CK7, CK20, URO III, p63, GATA3, and HMFG1. HMFG1 was studied in five cases of apocrine hidrocystomas and compared with five cases of MRC from our series.ResultsCK 5‐6, CK7, and p63 expression showed strong positivity in the urothelial epithelium of 48 cases. CK20 was focally positive in areas of mucinous differentiation in three cases. GATA3 showed intense nuclear staining in 30 cases. HMFG1 was positive in three cases of MRC and in three cases of apocrine hidrocystoma.ConclusionPositivity of GATA3 and CK7 in MRC supports the urothelial origin of these cysts. We found no differences in HMFG1 expression between MRC and apocrine hidrocystomas.
Validation of a risk prediction model for early chronic kidney disease in patients with type 2 diabetes: Data from the German/Austrian Diabetes Prospective Follow‐up registry
Authors: Kress Stephan , Bramlage Peter , Holl Reinhard W. , Möller Christian Dominik , Mühldorfer Steffen , Reindel Jörg , Seufert Jochen , Landgraf Rüdiger , Merker Ludwig , Meyhöfer Sebastian M. , Danne Thomas , Fasching Peter , Mertens Peter R. , Wanner Christoph , Lanzinger Stefanie 
Published: November 2022

AbstractAimTo validate a recently proposed risk prediction model for chronic kidney disease (CKD) in type 2 diabetes (T2D).Materials and MethodsSubjects from the German/Austrian Diabetes Prospective Follow‐up (DPV) registry with T2D, normoalbuminuria, an estimated glomerular filtration rate of 60 ml/min/1.73m2 or higher and aged 39‐75 years were included. Prognostic factors included age, body mass index (BMI), smoking status and HbA1c. Subjects were categorized into low, moderate, high and very high‐risk groups. Outcome was CKD occurrence.ResultsSubjects (n = 10 922) had a mean age of 61 years, diabetes duration of 6 years, BMI of 31.7 kg/m2, HbA1c of 6.9% (52 mmol/mol); 9.1% had diabetic retinopathy and 16.3% were smokers. After the follow‐up (~59 months), 37.4% subjects developed CKD. The area under the curve (AUC; unadjusted base model) was 0.58 (95% CI 0.57‐0.59). After adjustment for diabetes and follow‐up duration, the AUC was 0.69 (95% CI 0.68‐0.70), indicating improved discrimination. After follow‐up, 15.0%, 20.1%, 27.7% and 40.2% patients in the low, moderate, high and very high‐risk groups, respectively, had developed CKD. Increasing risk score correlated with increasing cumulative risk of incident CKD over a median of 4.5 years of follow‐up (P < .0001).ConclusionsThe predictive model achieved moderate discrimination but good calibration in a German/Austrian T2D population, suggesting that the model may be relevant for determining CKD risk.
School‐as‐Institution or School‐as‐Instrument? How to Overcome Instrumentalism without Giving Up on Democracy
Authors: Biesta Gert 
Published: November 2022

AbstractIn contemporary societies, there is a strong push toward seeing education as an instrument for the delivery of particular societal agendas. On such a view, the only questions that remain are how effective education is at delivering such agendas and how its effectiveness can be increased. While this might be a desirable way forward for those who believe that a consensus about the agenda for education can easily be achieved, it is at odds with the idea that a democratic society is characterized by a fundamental plurality of visions about what schools are supposed to be for. Yet the democratic critique of educational instrumentalism cannot be confined to giving each and every vision its own school, as this would simply multiply educational instrumentalism rather than oppose it. A true democratic response thus needs to take education's own interest seriously as well, which, as Gert Biesta argues in this paper, amounts to a defense of the school as institution.