bluuebunny/crossref_metadata_2025_split huggingface dataset:
“Yes, I know you”: the role of source familiarity in the relationship between service adaptive behavior and customer satisfaction
Authors: Shen Yung-Cheng , Lin Heng-Yu , Chou Cindy Yunhsin , Wu Po Han , Yang Wei-Hao 
Published: July 2022

PurposeThis study investigates the role of source familiarity in moderating the effect of service adaptive behavior (SAB) on customer satisfaction. Applying the accessibility–diagnosticity framework and situated cognition theory as the theoretical basis, this research hypothesizes that when customers are familiar with the source that provides the service (i.e. brand familiarity for Study 1 and personal familiarity for Study 2), customer satisfaction responses to SAB would be more moderate than when customers are not familiar with the source. Two studies were conducted to test the hypotheses.Design/methodology/approachTwo experiments manipulating SAB and the brand name familiarity (Study 1) and personal familiarity with the service staff (Study 2) as the source familiarity were conducted. Customer satisfaction as a function of source familiarity was measured to test the hypothesis that source familiarity moderates the relationship between SAB and customer satisfaction.FindingsCompared to unfamiliar sources, familiar sources generated a more moderate response in customer satisfaction as a function of SAB. High familiarity with the brand and service staff induced top-down, memory-based processing that overrides external stimuli as the basis of satisfaction judgment; bottom-up, stimulus-based processing relying on SAB for judgment kicked in only when the source familiarity is low.Practical implicationsFrom a practical point of view, this study indicates the importance of SAB, especially for brands with low awareness, and alludes to the comparative importance of relationship building in service delivery processes.Originality/valueThis study contributes to the literature by validating the role of contextual factors in influencing the impact of SAB on customer satisfaction.
Workload balance-based dynamic two-sided matching decision-making approach for cloud manufacturing tasks and services under uncertain preferences
Authors: Zhang Xuejiao , Yang Yu , Wang Jing 
Published: July 2022

PurposeThis paper aims to develop a dynamic two-sided stable matching method based on preference information of the matching objects in uncertain environments, so as to solve the matching problem of cloud manufacturing tasks and services with load balancing.Design/methodology/approachFor dynamic two-sided matching, due to the complexity of social environment and the limitation of human cognition, hesitation and fuzziness always exist in the process of multi-criteria assessment. First, in order to obtain the accurate preference information of each matching object, uncertain linguistic variables, uncertain preference ordinal and incomplete complementary matrices are used to evaluate multi-criteria preference information. This process is undertaken by considering the probability of each possible matching pair. Second, the preference information at different times is integrated by using the time-series weight to obtain the comprehensive satisfaction degree matrices of the matching objects. Further, the load adjustment parameter is used to increase the satisfaction degree of the matching objects. Afterward, a dynamic two-sided stable matching optimization model is constructed by considering stable matching conditions. The model aims to maximize the satisfaction degree and minimizes the difference in the satisfaction degree of matching objects. The optimal stable matching results can be obtained by solving the optimization model. Finally, a numerical example and comparative analysis are presented to demonstrate the characteristics of the proposed method.FindingsUncertain linguistic variables, uncertain preference orders and incomplete complementary matrices are used to describe multi-criteria preference information of the matching objects in uncertain environments. A dynamic two-sided stable matching method is proposed, based on which a DTSMDM (dynamic two-sided matching decision-making) model of cloud manufacturing with load balancing can be constructed. The study proved that the authors can use the proposed method to obtain stable matching pairs and higher matching objective value through comparative analysis and the sensitivity analysis.Originality/valueA new method for the two-sided matching decision-making problem of cloud manufacturing with load balancing is proposed in this paper, which allows the matching objects to elicit language evaluation under uncertain environment more flexibly to implement dynamic two-sided matching based on preference information at different times. This method is suitable for dealing with a variety of TSMDM (two-sided matching decision-making) problems.
A two level ensemble classification approach to forecast bitcoin prices
Authors: Kundra Harish , Sharma Sudhir , Nancy P. , Kalyani Dasari 
Published: July 2022

PurposeBitcoin has indeed been universally acknowledged as an investment asset in recent decades, after the boom-and-bust of cryptocurrency values. Because of its extreme volatility, it requires accurate forecasts to build economic decisions. Although prior research has utilized machine learning to improve Bitcoin price prediction accuracy, few have looked into the plausibility of using multiple modeling approaches on datasets containing varying data types and volumetric attributes. Thus, this paper aims to propose a bitcoin price prediction model.Design/methodology/approachIn this research work, a bitcoin price prediction model is introduced by following three major phases: Data collection, feature extraction and price prediction. Initially, the collected Bitcoin time-series data will be preprocessed and the original features will be extracted. To make this work good-fit with a high level of accuracy, we have been extracting the second order technical indicator based features like average true range (ATR), modified-exponential moving average (M-EMA), relative strength index and rate of change and proposed decomposed inter-day difference. Subsequently, these extracted features along with the original features will be subjected to prediction phase, where the prediction of bitcoin price value is attained precisely from the constructed two-level ensemble classifier. The two-level ensemble classifier will be the amalgamation of two fabulous classifiers: optimized convolutional neural network (CNN) and bidirectional long/short-term memory (BiLSTM). To cope up with the volatility characteristics of bitcoin prices, it is planned to fine-tune the weight parameter of CNN by a new hybrid optimization model. The proposed hybrid optimization model referred as black widow updated rain optimization (BWURO) model will be conceptual blended of rain optimization algorithm and black widow optimization algorithm.FindingsThe proposed work is compared over the existing models in terms of convergence, MAE, MAPE, MARE, MSE, MSPE, MRSE, Root Mean Square Error (RMSE), RMSPE and RMSRE, respectively. These evaluations have been conducted for both algorithmic performance as well as classifier performance. At LP = 50, the MAE of the proposed work is 0.023372, which is 59.8%, 72.2%, 62.14% and 64.08% better than BWURO + Bi-LSTM, CNN + BWURO, NN + BWURO and SVM + BWURO, respectively.Originality/valueIn this research work, a new modified EMA feature is extracted, which makes the bitcoin price prediction more efficient. In this research work, a two-level ensemble classifier is constructed in the price prediction phase by blending the Bi-LSTM and optimized CNN, respectively. To deal with the volatility of bitcoin values, a novel hybrid optimization model is used to fine-tune the weight parameter of CNN.
Social capital and corporate entrepreneurship: the role of absorptive capacity in emerging markets
Authors: Fayad Yasmin , El Ebrashi Raghda 
Published: July 2022

PurposeThis paper studies the role of inter-firm supply chain social capital and intra-firm social capital in enabling Corporate Entrepreneurship (CE), and also investigates the moderating and mediating effect of absorptive capacity.Design/methodology/approachA correlational descriptive survey research is employed for 200 firms; adopting a 13-item Likert scale obtained from Wang and Li (2016) for measuring inter-firm social capital, and an eight item Likert scale for measuring absorptive capacity. This is in addition to a nine item Likert scale obtained from De Clercqet al.(2013) to measure the intra-firm social capital, and a nine item semantic differential scale developed by Covin and Slevin (1989) for measuring the level of corporate entrepreneurship. Statistical analysis packages SPSS V.24 and AMOS V.24 were used.FindingsResults provide evidence that structural supply chain social capital has an effect on corporate entrepreneurship; mediated by potential absorptive capacity. Additionally, the effect of relational supply chain social capital on corporate entrepreneurship is fully mediated by potential absorptive capacity. Furthermore, the effect of cognitive supply chain social capital on corporate entrepreneurship is fully mediated by potential absorptive capacity. On the other hand, results show that both intra-firm social capital and realized absorptive capacity moderate the relationship between potential absorptive capacity and corporate entrepreneurship.Research limitations/implicationsThe convenience sampling technique increases the probability of selection bias. In addition, the research focused on two aspects of intra-firm social capital, namely relational and cognitive dimensions, and overlooked the structural dimension of social capital.Practical implicationsProviding managers with insights about the critical role of developing social capital among supply chain partners to facilitate the transfer and exchange of crucial knowledge necessary for product development and innovation. This is in addition to the need to capitalize on intra-collaborations and cross-functional routines to facilitate CE.Originality/valueThis study provides a required extension to the previous literature, which has not empirically modeled the role of potential absorptive capacity as means by which supply chain social capital dimensions enable CE. Also, the research identifies contingency factors that enable the effect of potential absorptive capacity on CE; namely intra-firm social capital and realized absorptive capacity.
Women's spaces in the vernacular Qatari courtyard house: how privacy and gendered spatial segregation shape architectural identity
Authors: AL-Mohannadi Asmaa , Furlan Raffaello , Grosvald Michael 
Published: July 2022

PurposeThis research study aims to explore sociocultural factors such as privacy and gender segregation as they relate to the spatial perception of women's spaces within the vernacular Qatari household, and the activities, habits and practiced culture of its inhabitants.Design/methodology/approachThis analysis utilizes the Space Syntax methodology to examine a sample of vernacular courtyard houses with respect to space connectivity, conducting an analytical exploration of the role of women based on the system of activities.FindingsThe findings shed light on the spatial complexity and sensitivity of the Qatari household as it reflects the prevailing sociocultural imperatives in Qatari urbanities, including the country's capital, Doha.Research limitations/implicationsThis research study thus reinforces the importance of traditional residential architecture in conserving Qatar's distinctive architectural identity, rooted in its sociocultural attributes.Social implicationsSociocultural features such as privacy and gender segregation are among the most prominent factors influencing the spatial form of vernacular courtyard houses in the Arabian Gulf country of Qatar.Originality/valueIt is argued that within a typical vernacular Qatari household, women's spaces are the least connected (most segregated) areas, due mainly to the influence of privacy norms and gender segregation on the spatial configuration of the house.
Employer’s investments in job crafting to promote knowledge worker’s sustainable employability: a moderated mediation model
Authors: Irfan Syed Muhammad , Qadeer Faisal , Abdullah Muhammad Ibrahim , Sarfraz Muddassar 
Published: July 2022

PurposeThe primary study purpose is to examine whether managerial support triggers job crafting and sustainable employability, and to what extent work uncertainty moderates the managerial support and sustainable employability relationships mediated by job crafting using a moderated mediation approach. Thus, this study aims to uncover new antecedent and outcomes of job crafting using job demands and resources (JD–R) theory as no such research has yet examined these relationships.Design/methodology/approachThe structural equation modeling (SEM) technique was employed to test the proposed relationships based on survey data that include a final 483 knowledge workers of the services sector. The authors tested the structural model using self-developed estimates for AMOS 24.0 to examine the moderated mediation process models (process models 7, 14 and 58) rather than using a conventional process macro through SPSS.FindingsConsistent with the formulated hypothesis, the results of this study indicate that managerial support directly stimulates job crafting and sustainable employability. Further, job crafting mediates the relationships between managerial support and sustainable employability. This validates the JD–R theory assumption that managerial support as job resources initiates a motivational process through job crafting, leading to sustainable employability as the outcome of the motivational process. Additionally, the moderated mediation results show that in the presence of high work uncertainty, employees are more engaged in job crafting to boost their sustainable employability.Practical implicationsOrganizations may incorporate these findings while developing human resources (HR) management policies and practices to align top-down and bottom-up job re(design) approaches. For example, by designing line managers’ role in implementation of supportive HR practices, their supportive leadership behavior towards employees will successfully trigger job crafting and nurture their sustainable employability.Originality/valueThis research adds to the work design and employability literature. No such study has yet examined whether managerial support triggers job crafting and sustainable employability. Prior studies examine personality traits, some individual difference variable, job characteristics, or leadership influence as antecedents of job crafting. Utilizing the JD–R theory, we empirically validate that job crafting plays a vital role in the motivational process initiated by the job resources (managerial support), leading to sustainable employability as an outcome of the motivational process. The authors further show that in the presence of high job demands (work uncertainty), employees are more engaged in job crafting and more conscious to boost their sustainable employability.
Leaf nitrogen from the perspective of optimal plant function
Authors: Dong Ning , Prentice Iain Colin , Wright Ian J. , Wang Han , Atkin Owen K. , Bloomfield Keith J. , Domingues Tomas F. , Gleason Sean M. , Maire Vincent , Onoda Yusuke , Poorter Hendrik , Smith Nicholas G. 
Published: July 2022

Abstract

Leaf dry mass per unit area (LMA), carboxylation capacity (Vcmax) and leaf nitrogen per unit area (Narea) and mass (Nmass) are key traits for plant functional ecology and ecosystem modelling. There is however no consensus about how these traits are regulated, or how they should be modelled. Here we confirm that observed leaf nitrogen across species and sites can be estimated well from observed LMA and Vcmax at 25°C (Vcmax25). We then test the hypothesis that global variations of both quantities depend on climate variables in specific ways that are predicted by leaf‐level optimality theory, thus allowing both Narea to be predicted as functions of the growth environment.

A new global compilation of field measurements was used to quantify the empirical relationships of leaf N to Vcmax25 and LMA. Relationships of observed Vcmax25 and LMA to climate variables were estimated, and compared to independent theoretical predictions of these relationships. Soil effects were assessed by analysing biases in the theoretical predictions.

LMA was the most important predictor of Narea (increasing) and Nmass (decreasing). About 60% of global variation across species and sites in observed Narea, and 31% in Nmass, could be explained by observed LMA and Vcmax25. These traits, in turn, were quantitatively related to climate variables, with significant partial relationships similar or indistinguishable from those predicted by optimality theory. Predicted trait values explained 21% of global variation in observed site‐mean Vcmax25, 43% in LMA and 31% in Narea. Predicted Vcmax25 was biased low on clay‐rich soils but predicted LMA was biased high, with compensating effects on Narea. Narea was overpredicted on organic soils.

Synthesis. Global patterns of variation in observed site‐mean Narea can be explained by climate‐induced variations in optimal Vcmax25 and LMA. Leaf nitrogen should accordingly be modelled as a consequence (not a cause) of Vcmax25 and LMA, both being optimized to the environment. Nitrogen limitation of plant growth would then be modelled principally via whole‐plant carbon allocation, rather than via leaf‐level traits. Further research is required to better understand and model the terrestrial nitrogen and carbon cycles and their coupling.
Circular RNA circ_0006089 promotes the progression of gastric cancer by regulating the miR‐143‐3p/PTBP3 axis and PI3K/AKT signaling pathway
Authors: Lin Guang Rong , Chen Wei Rong , Zheng Pei Hong , Chen Wei Shan , Cai Gao Yang 
Published: July 2022

ObjectivesCircular RNAs (circRNAs) play pivotal roles in malignancies including gastric cancer (GC). We aimed to investigate the biological function and regulatory mechanism of circ_0006089 in GC.MethodsCirc_0006089, microRNA (miR)‐143‐3p, and polypyrimidine tract‐binding protein 3 (PTBP3) expressions were measured via quantitative reverse transcriptase polymerase chain reaction (qRT‐PCR) in GC cell lines. Cell proliferative capacity was determined by colony formation and CCK‐8 assays. Flow cytometry was employed for measuring cell apoptosis. Cell invasion and migration were measured via transwell and wound‐healing assays. Western blot analysis was utilized for detecting protein expressions of E‐cadherin, N‐cadherin, vimentin, PTBP3, PI3K, p‐PI3K, AKT, and p‐AKT. Dual‐reporter luciferase analysis was conducted to confirm the association between miR‐143‐3p and circ_0006089 or PTBP3. The role of circ_0006089 in vivo was detected via establishing a mice xenograft model.ResultsCirc_0006089 expression was increased in GC. Circ_0006089 downregulation suppressed the proliferation and metastasis and induced apoptosis of GC cells, which was counteracted by miR‐143‐3p inhibition or PTBP3 overexpression. In addition, circ_0006089 overexpression could promote GC progression. MiR‐143‐3p specially bound to circ_0006089 and PTBP3 was targeted by miR‐143‐3p. Moreover, circ_0006089 could regulate PTBP3 expression and the PI3K/AKT pathway by sponging miR‐143‐3p. Circ_0006089 knockdown also suppressed tumor growth.ConclusionCirc_0006089 regulated miR‐143‐3p/PTBP3/PI3K/AKT pathway to facilitate GC progression.
Chromosome‐level genome assembly defines female‐biased genes associated with sex determination and differentiation in the human blood fluke Schistosoma japonicum
Authors: Xu Xindong , Wang Yifeng , Wang Changhong , Guo Gangqiang , Yu Xinyu , Dai Yang , Liu Yaobao , Wei Guiying , He Xiaohui , Jin Ge , Zhang Ziqiu , Guan Qingtian , Pain Arnab , Wang Shengyue , Zhang Wenbao , Young Neil D. , Gasser Robin B. , McManus Donald P. , Cao Jun , Zhou Qi , Zhang Qingfeng 
Published: July 2022

AbstractSchistosomiasis is a neglected tropical disease of humans caused by blood flukes of the genus Schistosoma, the only dioecious parasitic flatworm. Although aspects of sex determination, differentiation and reproduction have been studied in some Schistosoma species, almost nothing is known for Schistosoma japonicum, the causative agent of schistosomiasis japonica. This mainly reflects the lack of high‐quality genomic and transcriptomic resources for this species. As current genomes for S. japonicum are highly fragmented, we assembled and report a chromosome‐level reference genome (seven autosomes, the Z‐chromosome and partial W‐chromosome), achieving a substantially enhanced gene annotation. Utilizing this genome, we discovered that the sex chromosomes of S. japonicum and its congener S. mansoni independently suppressed recombination during evolution, forming five and two evolutionary strata, respectively. By exploring the W‐chromosome and sex‐specific transcriptomes, we identified 35 W‐linked genes and 257 female‐preferentially transcribed genes (FTGs) from our chromosomal assembly and uncovered a signature for sex determination and differentiation in S. japonicum. These FTGs clustering within autosomes or the Z‐chromosome exhibit a highly dynamic transcription profile during the pairing of female and male schistosomula, thereby representing a critical phase for the maturation of the female worms and suggesting distinct layers of regulatory control of gene transcription at this development stage. Collectively, these data provide a valuable resource for further functional genomic characterization of S. japonicum, shed light on the evolution of sex chromosomes in this highly virulent human blood fluke, and provide a pathway to identify novel targets for development of intervention tools against schistosomiasis.
Outcomes of the National Heart, Lung, and Blood Institute K12 program in emergency care research: 7‐year follow‐up
Authors: Morris Cynthia D. , Cook Jennifer N. B. , Lin Amber , Scott Jane D. , Kuppermann Nathan , Callaway Clifton W. , Yealy Donald M. , Lowe Robert A. , Richardson Lynne D. , Kimmel Stephen , Holmes James F. , Collins Sean , Becker Lance B. , Storrow Alan B. , Newgard Harrison J. , Baren Jill , Newgard Craig D. 
Published: July 2022

AbstractBackgroundLong‐term follow‐up for clinician–scientist training programs is sparse. We describe the outcomes of clinician–scientist scholars in the National Heart Lung and Blood Institute (NHLBI) K12 program in emergency care research up to 8.7 years after matriculation in the program.MethodsThis was a cohort study of faculty clinician–scientist scholars enrolled in a NHLBI K12 research training program at 6 sites across the US, with median follow‐up 7.7 years (range 5.7–8.7 years) from the date of matriculation. Scholars completed electronic surveys in 2017 and 2019, with the 2019 survey collecting information for their current work setting, percent time for research, and grant funding from all sources. We used NIH RePorter and online resources to verify federal grants through March 2021. The primary outcome was a funded career development award (CDA) or research project grant (RPG) where the scholar was principal investigator. We included funding from all federal sources and national foundations.ResultsThere were 43 scholars, including 16 (37%) women. Over the follow‐up period, 32 (74%) received an individual CDA or RPG, with a median of 36 months (range 9–83 months) after entering the program. Of the 43 scholars, 23 (54%) received a CDA and 22 (51%) received an RPG, 7 (16%) of which were R01s. Of the 23 scholars who received a CDA, 13 (56%) subsequently had an RPG funded. Time to CDA or RPG did not differ by sex (women vs. men log‐rank test p = 0.27) or specialty training (emergency medicine versus other specialties, p = 0.59).ConclusionsAfter 7 years of follow‐up for this NHLBI K12 emergency care research training program, three quarters of clinician–scientist scholars had obtained CDA or RPG funding, with no notable differences by sex or clinical training.