bluuebunny/crossref_metadata_2025 huggingface dataset:
Towards a major methodological shift in depression research by assessing continuous scores of recurrence of illness, lifetime and current suicidal behaviors and phenome features: focus on atherogenicity and adverse childhood experiences
Authors: Maes Michael , Jirakran Ketsupar , Vasupanrajit Asara , Boonchaya-Anant Patchaya , Tunvirachaisakul Chavit
Published: February 2023

Background

The binary major depressive disorder (MDD) diagnosis is inadequate and should never be used in research.

Aims

The study’s objective is to explicate our novel precision nomothetic strategy for constructing depression models based on adverse childhood experiences (ACEs), lifetime and current phenome, and biomarker (atherogenicity indices) scores.

Methods

This study assessed recurrence of illness (ROI: namely recurrence of depressive episodes and suicidal behaviors), lifetime and current suicidal behaviors and the phenome of depression, neuroticism, dysthymia, anxiety disorders, and lipid biomarkers (including ApoA, ApoB, free cholesterol and cholesteryl esters, triglycerides, high density lipoprotein cholesterol) in 67 normal controls and 66 MDD patients. We computed atherogenic and reverse cholesterol transport indices.

Results

We were able to extract one factor from a) the lifetime phenome of depression comprising ROI, and traits such as neuroticism, dysthymia and anxiety disorders, and b) the phenome of the acute phase (based on depression, anxiety and quality of life scores). PLS analysis showed that 55.7% of the variance in the lifetime + current phenome factor was explained by increased atherogenicity, neglect and sexual abuse, while atherogenicity partially mediated the effects of neglect. Cluster analysis generated a cluster of patients with major dysmood disorder, which was externally validated by increased atherogenicity and characterized by increased scores of all clinical features.

Conclusions

The outcome of depression should not be represented as a binary variable (MDD or not), but rather as multiple dimensional scores based on biomarkers, ROI, subclinical depression traits, and lifetime and current phenome scores including suicidal behaviors.
A Systematic Evaluation of Machine Learning-based Biomarkers for Major Depressive Disorder across Modalities
Authors: Winter Nils R. , Blanke Julian , Leenings Ramona , Ernsting Jan , Fisch Lukas , Sarink Kelvin , Barkhau Carlotta , Thiel Katharina , Flinkenflügel Kira , Winter Alexandra , Goltermann Janik , Meinert Susanne , Dohm Katharina , Repple Jonathan , Gruber Marius , Leehr Elisabeth J. , Opel Nils , Grotegerd Dominik , Redlich Ronny , Nitsch Robert , Bauer Jochen , Heindel Walter , Groß Joachim , Andlauer Till F. M. , Forstner Andreas J. , Nöthen Markus M. , Rietschel Marcella , Hofmann Stefan G. , Pfarr Julia-Katharina , Teutenberg Lea , Usemann Paula , Thomas-Odenthal Florian , Wroblewski Adrian , Brosch Katharina , Stein Frederike , Jansen Andreas , Jamalabadi Hamidreza , Alexander Nina , Straube Benjamin , Nenadić Igor , Kircher Tilo , Dannlowski Udo , Hahn Tim
Published: February 2023

Background

Biological psychiatry aims to understand mental disorders in terms of altered neurobiological pathways. However, for one of the most prevalent and disabling mental disorders, Major Depressive Disorder (MDD), patients only marginally differ from healthy individuals on the group-level. Whether Precision Psychiatry can solve this discrepancy and provide specific, reliable biomarkers remains unclear as current Machine Learning (ML) studies suffer from shortcomings pertaining to methods and data, which lead to substantial over-as well as underestimation of true model accuracy.

Methods

Addressing these issues, we quantify classification accuracy on a single-subject level in N=1,801 patients with MDD and healthy controls employing an extensive multivariate approach across a comprehensive range of neuroimaging modalities in a well-curated cohort, including structural and functional Magnetic Resonance Imaging, Diffusion Tensor Imaging as well as a polygenic risk score for depression.

Findings

Training and testing a total of 2.4 million ML models, we find accuracies for diagnostic classification between 48.1% and 62.0%. Multimodal data integration of all neuroimaging modalities does not improve model performance. Similarly, training ML models on individuals stratified based on age, sex, or remission status does not lead to better classification. Even under simulated conditions of perfect reliability, performance does not substantially improve. Importantly, model error analysis identifies symptom severity as one potential target for MDD subgroup identification.

Interpretation

Although multivariate neuroimaging markers increase predictive power compared to univariate analyses, single-subject classification – even under conditions of extensive, best-practice Machine Learning optimization in a large, harmonized sample of patients diagnosed using state-of-the-art clinical assessments – does not reach clinically relevant performance. Based on this evidence, we sketch a course of action for Precision Psychiatry and future MDD biomarker research.

Funding

The German Research Foundation, and the Interdisciplinary Centre for Clinical Research of the University of Münster.
Centrifuge+: improving metagenomic analysis upon Centrifuge
Authors: Liu Junfeng , Ma Runran , Ren Yong , Guo Hao
Published: February 2023

Accurate abundance estimation of species is essential for metagenomic analysis. Although many methods have been developed for classification of metagenomic data and abundance estimation of species, the abundance estimation of species remains challenging due to the ambiguous reads that align equally well to more than one genome. Here, we present Centrifuge+, which introduces unique mapping rate to describe the influence of similarities among species in the reference database when analyzing ambiguous reads. In contrast to the popular Centrifuge, Centrifuge+ improved the accuracy of abundance estimation on simulated reads from 4278 complete prokaryotic genomes.
Phage T3 overcomes the BREX defence through SAM cleavage and inhibition of SAM synthesis
Authors: Andriianov Aleksandr , Triguis Silvia , Drobiazko Alena , Sierro Nicolas , Ivanov Nikolai V. , Selmer Maria , Severinov Konstantin , Isaev Artem
Published: February 2023

Bacteriophage T3 encodes a SAMase that through cleavage of S-adenosyl-methionine (SAM) circumvents the SAM-dependent Type I Restriction-Modification defence of the host bacteriumEscherichia coli. Here, we show that the SAMase also allows T3 to evade BREX defence. SAM degradation weakly affects BREX methylation of host DNA, but completely inhibits the defensive function of BREX, suggesting that SAM is required as a co-factor for BREX-mediated exclusion of phage DNA. The anti-BREX activity of the T3 SAMase is mediated by two independent mechanisms: enzymatic degradation of SAM and downregulation of SAM synthesis through direct inhibition of the host SAM synthase MetK. We determined a 2.8 Å cryo-EM structure of the eight-subunit T3 SAMase-MetK complex. Structure guided mutagenesis of the SAMase-MetK interface revealed that the interaction with MetK stabilizes the T3 SAMasein vivo, thus further stimulating its anti-BREX activity. This work provides insights in the versatility and intricacy of bacteriophage counter-defence mechanisms and highlights the role of SAM as an important co-factor of diverse phage-defence systems.
Unistrand piRNA clusters are an evolutionarily conserved mechanism to suppress endogenous retroviruses across theDrosophilagenus
Authors: van Lopik Jasper , Alizada Azad , Trapotsi Maria-Anna , Hannon Gregory J. , Bornelöv Susanne , Nicholson Benjamin Czech
Published: February 2023

The PIWI-interacting RNA (piRNA) pathway prevents endogenous genomic parasites, transposable elements, from damaging the genetic material of animal gonadal cells. Specific regions in the genome, called piRNA clusters, are thought to define each species’ piRNA repertoire and therefore its capacity to recognize and silence specific transposon families. The unistrand clusterflamenco(flam) is essential in the somatic compartment of theDrosophilaovary to restrictGypsy-family transposons from infecting the neighbouring germ cells. Disruption offlamresults in transposon derepression and sterility, yet it remains unknown whether this silencing mechanism is present more widely. Here, we systematically characterised 119Drosophilaspecies and identify five additionalflam-like clusters separated by up to 45 million years. Small RNA-sequencing validated these as bona-fide unistrand piRNA clusters expressed in somatic cells of the ovary, where they selectively target transposons of theGypsyfamily. Together, our study provides compelling evidence of a widely conserved transposon silencing mechanism that co-evolved with virus-likeGypsy-family transposons.
Radiation-induced persistent DNA damage response and late toxicity in cardiac tissue
Authors: Shigemori Kay , Jiang Yanyan , Martin Jennifer C , Hawkins Maria A , Ryan Anderson J , Parkes Eileen E
Published: February 2023

Background

Radiotherapy treatment is a mainstay of cancer treatments including for thoracic malignancies such as lung or breast cancer. Cardiac toxicity is a recognised long-term complication of thoracic radiotherapy which persists despite improvements in therapeutic modalities. The mechanisms and potential therapeutic targets that could provide cardiac protection in the context of radiation therapy remain incompletely understood. Here we investigated early and late cardiac toxicity following irradiation using the A/J mouse model to identify potential molecular drivers.

Methods

Single doses of irradiation of either 13 or 15 Gy were delivered to female A/J mice aged 6 – 8 weeks using a SmART-PLAN system. ECG traces and analysis were performed on anaesthetised mice. Cardiac tissue was harvested up to 32 weeks following irradiation for histological analysis and second-harmonic imaging microscopy.

Results

Cardiac RT resulted in cardiac conductivity abnormalities including prolonged QTc interval. Additionally, an increase in pericardial and perivascular fibrosis was noted with a marked increase in pericardial fibrosis at 15 Gy compared to 13 Gy. Persistent DNA damage response was identified in cardiomyocytes at 7 days post irradiation and polarisation of cardiac-infiltrating macrophages towards a CD206+ M2-like phenotype at the same timepoint.

Conclusions

Our data introduce the A/J mouse as a novel model for the study of physiologically relevant early and late cardiac toxicities following irradiation. Early events that could contribute to long term toxicities include persistent DNA damage response and repolarisation of macrophages, further investigation of which could identify potential future cardioprotective therapeutic strategies.
Reconstructing the pressure field around a swimming fish using a physics-informed neural network
Authors: Calicchia Michael A. , Mittal Rajat , Seo Jung-Hee , Ni Rui
Published: February 2023

Hydrodynamic pressure is a physical quantity that is utilized by fish and many other aquatic animals to generate thrust and sense the surrounding environment. To advance our understanding of how fish react to unsteady flows, it is necessary to intercept the pressure signals sensed by their lateral line system. In this study, the authors propose a new, non-invasive method for reconstructing the instantaneous pressure field around a swimming fish from 2D particle image velocimetry (PIV) measurements. The method uses a physics-informed neural network (PINN) to predict an optimized solution for the velocity and pressure fields that satisfy in an ℒ2sense both the Navier Stokes equations and the constraints put forward by the measurements. The method was validated using a direct numerical simulation of a swimming mackerel,Scomber scombrus, and was applied to empirically obtained data of a turning zebrafish,Danio rerio. The results demonstrate that when compared to traditional methods that rely on directly integrating the pressure gradient field, the PINN is less sensitive to the spatio-temporal resolution of the velocity field measurements and provides a more accurate pressure reconstruction, particularly on the surface of the body.
Large haplotypes highlight a complex age structure within the maize pan-genome
Authors: Liu Jianing , Dawe R. Kelly
Published: February 2023

The genomes of maize and other eukaryotes contain stable haplotypes in regions of low recombination. These regions, including centromeres, long heterochromatic blocks, and rDNA arrays, have been difficult to analyze with respect to their diversity and origin. Greatly improved genome assemblies are now available that enable comparative genomics over these and other nongenic spaces. Using 26 complete maize genomes, we developed methods to align intergenic sequences while excluding genes and regulatory regions. The centromere haplotypes (cenhaps) extend for megabases on either side of the functional centromere regions and appear as evolutionary strata, with haplotype divergence/coalescence times dating as far back as 450 thousand years ago (kya). Application of the same methods to other low recombination regions (heterochromatic knobs and rDNA) and all intergenic spaces revealed that deep coalescence times are ubiquitous across the maize pan-genome. Divergence estimates vary over a broad timescale with peaks at ∼16 and 300 kya, reflecting a complex history of gene flow among diverging populations and changes in population size associated with domestication. Cenhaps and other long haplotypes provide vivid displays of this ancient diversity.
Gust response analysis based on a nonlinear structural model and the unsteady aerodynamics of a flexible aircraft
Authors: Masrour Javad , Sadati Seyed Hossein , Shahravi Morteza
Published: February 2023

Purpose

This study aims to simulate gust effects on the aeroelastic behavior of a flexible aircraft. The dynamic response of the system for different discreet gust excitations is obtained using numerical simulations.

Design/methodology/approach

Coupled dynamics, including rigid and flexible body coordinates, are considered for modeling the dynamic behavior of the aircraft. Wing is considered flexible and other parts are considered rigid. Wing is modeled with nonlinear Euler Bernoulli beam. Moreover, unsteady aerodynamics based on the Wagner function are used for aerodynamic loading, and the results are compared with those of quasi-steady aerodynamics.

Findings

Von Kármán continuous gust is applied to this aircraft. In addition, the discrete “1- cosine” gust with different gust lengths is applied to the aircraft, and the maximum and minimum accelerations are computed. It is shown that the nonlinear modeling of the system represents the actual behavior and causes limit cycle oscillation phenomena.

Originality/value

This methodology can yield a relatively simple dynamic model for high aspect ratio aircrafts to provide insights into the vehicles’ dynamics, which can be available early in the design cycle.
Consumers' social self-identity drivers on social commerce platforms-based food and beverage
Authors: Bazi Saleh , Attar Razaz Waheeb , Adam Nawal Abdalla , Hajli Nick
Published: February 2023

Purpose

This study aims to investigate the latest breakthroughs in social commerce by examining the characteristics of consumers' social self-identity factors in the food and beverage sector. The objective is to examine how social self-identities factors contribute to exchanging information on social commerce platforms for food and beverage products.

Design/methodology/approach

This study employed partial least squares structural equation modeling (PLS-SEM) to test the measurement and structural model. A total of 238 food and beverage website and apps users were questioned using a structural survey.

Findings

Contrary to expectations, one self-inner driver does not influence consumers' intentions to exchange social commerce information, while up-to-date information, validation and like-minded discussion have a strong impact on the social commerce exchange model.

Originality/value

The findings of this research offer new insights into the brand's abilities to induce social commerce. The findings also assist marketing managers in better managing brand content on these websites.
Self-construal, face concerns and conflict management strategies: a meta-analysis
Authors: Yamini Sara , Fousiani Kyriaki , Wisse Barbara
Published: February 2023

Purpose

In this meta-analysis, the authors investigate the relationship between self-construal and conflict management strategies and shed light on the inconsistent findings in the literature. Moreover, they examine the mediating role of face concerns in this relationship. Importantly, the present meta-analysis is the first to test the assumptions of face-negotiation theory with the meta-analytic structural equation modeling (MASEM), which enabled the authors to test the hypothesized relationships in one single model.

Design/methodology/approach

The authors used the method of MASEM to test the relationship between self-construal and conflict management and assess the mediating role of face concerns. In this regard, the authors employed one-stage meta-analytic structural equation modeling to perform MASEM and its moderators.

Findings

Two hundred fifty-four effect sizes based on thirty-three studies were pooled in this meta-analysis. The authors found that individuals with stronger independent self-construal and stronger self-face concerns were more likely to use forcing. Moreover, the relationship between independent self-construal and forcing was mediated by self-face concerns. Individuals with a stronger interdependent self-construal and individuals with stronger other-face concerns were more likely to use problem-solving and yielding. The relationship between interdependent self-construal and problem-solving and yielding was mediated by other-face concerns. Finally, interdependent self-construal also had an indirect effect, via other-face concern, on avoiding and compromising.

Originality/value

The present meta-analysis is the first effort that the authors are aware of to test the assumptions of face-negotiation theory (FNT) using MASEM method. The authors used one-stage meta-analytic structural equation modeling viewed as the state of the methods to perform MASEM and its moderators. They employed full information meta-analytic structural equation modeling to show the generalizability and heterogeneity of structural equation modeling parameters. They applied studentized deleted residuals to assess outlier analysis and also conducted different methods to perform MASEM to check the robustness of the findings resulted. Finally, the current study adds multiple methods of assessing for publication bias.
TikTok app usage behavior: the role of hedonic consumption experiences
Authors: Abbasi Amir Zaib , Ayaz Natasha , Kanwal Sana , Albashrawi Mousa , Khair Nadine
Published: February 2023

Purpose

TikTok social media app has become one of the most popular forms of leisure and entertainment activities, but how hedonic consumption experiences (comprising fantasy, escapism, enjoyment, role projection, sensory, arousal and emotional involvement) of the TikTok app determine users' intention to use the app and its resulting impact on the actual usage behavior remains limited in the information systems literature, especially featuring the hedonic consumption perspective in entertainment industry.

Design/methodology/approach

This study employs uses & gratification theory to answer the “why” via predicting the role of hedonic consumption experiences that serve as gratifications to trigger technology acceptance behavior (especially, in form of users' behavioral intention to use the TikTok app and its further impact on usage behavior). This study utilizes the partial least squares-structural equation modeling approach to perform data analyses on 258 TikTok app users.

Findings

Our results provide a strong support such that users' playful consumption experiences (i.e. escapism, role projection, arousal, sensory experience and enjoyment) positively influence their intention to use the TikTok app and its resultant effect on users' actual usage of the app. In contrast, fantasy and emotional involvement fail to influence users' intention to use the TikTok app.

Originality/value

To the best of our knowledge, our investigation is one of the first studies to apply the hedonic consumption experiences as potential gratifications that derive users' intention and its subsequent influence on the actual usage of the TikTok app. Our study results would assist marketing and brand managers to redefine approaches and tactics to create effective strategies that implement essential determinants to increase behavioral intention among entertainment service providers.
Zomato: shaping the future of food
Authors: Ramadan Zahy , Kanso Jana
Published: February 2023

Learning outcomes

The learning outcomes are as follows:

1. assess and evaluate the challenges affecting a mobile food aggregator platform’s business model and its effect on the customer journey in a developing market;

2. understand the relationship between the different stakeholders on such platform, namely, restaurants, end-users and the platform itself, and its implication on the customer journey; and

3. develop different potential marketing strategies under that business context that can be implemented and replicated in a given emerging market.

Case overview/synopsis

Zomato is an online restaurant aggregator and food delivery company that provides information, menus and user reviews of restaurants. While Zomato was growing exponentially in terms of number of users and listed restaurants, the platform had to constantly reinvent itself to stay competitive in light of increasingly aggressive competitors that were launching into the different markets it serves. Maya, the country manager of Zomato Lebanon, faced a key dilemma deciding which potential strategy to replicate from head office into the local market that would help her fend off rising competitors while still increasing the size of the market.

Complexity academic level

This case can be used mainly in senior undergraduate-level business school students. The case can be taught in courses covering marketing and strategy.

Supplementary materials

Teaching notes are available for educators only.

Subject code

CSS 8: Marketing.
Using image analysis to quantify defects and prioritize repairs in built-up roofs
Authors: Mostafa Kareem , Hegazy Tarek , Hunsperger Robert D. , Elias Stepanka
Published: February 2023

Purpose

This paper aims to use convolutional neural networks (CNNs) to provide an objective approach to classify deteriorated building assets according to the type and extent of damage. This research supports automated inspection of buildings and focuses on roofing elements as one of the most critical and externally distressed elements in buildings.

Design/methodology/approach

In this paper, 5,000+ images of deteriorated roofs from several buildings were collected to design a CNN system that automatically identifies and sizes roofing defects. Experimenting with different CNN formulations, the best accuracy is achieved using two-stage CNNs. The first-stage CNN classifies images into defect/no defect, while the second stage classifies the defected images according to the damage type. Based on the image classification, optimization is used to prioritize roof repairs by maximizing the return from limited rehabilitation funds.

Findings

The developed CNNs reached 95% and 97% accuracy for the first and second phases, respectively, which is higher than achieved in previous literature efforts. Using the proposed model to automate inspection and condition assessment activities proved to be faster than conventional methods. Repair/replace strategy for a case study of 21 campus buildings based on their condition and budgetary constraints was suggested.

Research limitations/implications

Future research includes testing different data acquisition technologies (e.g. infrared imaging), performing severity-based classification and integrating with BIM for defect localization.

Originality/value

This study provides an objective approach to automate asset condition assessment and improve funding decisions using a combination of image analysis and optimization techniques. The proposed approach is applicable toward other asset types and components.
Scenario-based incident response training: lessons learnt from conducting an experiential learning virtual incident response tabletop exercise
Authors: Angafor Giddeon Njamngang , Yevseyeva Iryna , Maglaras Leandros
Published: February 2023

Purpose

This paper aims to discuss the experiences designing and conducting an experiential learning virtual incident response tabletop exercise (VIRTTX) to review a business's security posture as it adapts to remote working because of the Coronavirus 2019 (COVID-19). The pandemic forced businesses to move operations from offices to remote working. Given that this happened quickly for many, some firms had little time to factor in appropriate cyber-hygiene and incident prevention measures, thereby exposing themselves to vulnerabilities such as phishing and other scams.

Design/methodology/approach

The exercise was designed and facilitated through Microsoft Teams. The approach used included a literature review and an experiential learning method that used scenario-based, active pedagogical strategies such as case studies, simulations, role-playing and discussion-focused techniques to develop and evaluate processes and procedures used in preventing, detecting, mitigating, responding and recovering from cyber incidents.

Findings

The exercise highlighted the value of using scenario-based exercises in cyber security training. It elaborated that scenario-based incident response (IR) exercises are beneficial because well-crafted and well-executed exercises raise cyber security awareness among managers and IT professionals. Such activities with integrated operational and decision-making components enable businesses to evaluate IR and disaster recovery (DR) procedures, including communication flows, to improve decision-making at strategic levels and enhance the technical skills of cyber security personnel.

Practical implications

It maintained that the primary implication for practice is that they enhance security awareness through practical experiential, hands-on exercises such as this VIRTTX. These exercises bring together staff from across a business to evaluate existing IR/DR processes to determine if they are fit for purpose, establish existing gaps and identify strategies to prevent future threats, including during challenging circumstances such as the COVID-19 outbreak. Furthermore, the use of TTXs or TTEs for scenario-based incident response exercises was extremely useful for cyber security practice because well-crafted and well-executed exercises have been found to serve as valuable and effective tools for raising cyber security awareness among senior leadership, managers and IT professionals (Ulmanová, 2020).

Originality/value

This paper underlines the importance of practical, scenario-based cyber-IR training and reports on the experience of conducting a virtual IR/DR tabletop exercise within a large organisation.
Mapping mentee outcomes in mentoring programs for managers
Authors: Gisbert-Trejo Nuria , Fernández-Ferrín Pilar , Albizu Eneka , Landeta Jon
Published: February 2023

Purpose

This paper aims to identify, assess and classify the most significant mentee outcomes of formal mentoring processes aimed at managerial development.

Design/methodology/approach

After conducting an extensive literature review to identify the most significant mentee outcomes in the management field, a survey was conducted with a sample of 80 experienced mentees. An exploratory factor analysis (EFA) has been performed to simplify and contribute to operationalizing these results. Finally, focus group and nominal group techniques were conducted with practitioners to better understand the findings.

Findings

A total of 27 mentee outcomes have been identified in the literature. EFA analysis has allowed us to downsize the 27 outcomes into four factors encompassing the most relevant mentee outcomes. The authors then provide an interpretation and discussion of the results.

Originality/value

This work compiles, reviews and systematizes existing studies on mentee outcomes in the field of management, classifying the results in a novel manner.
Spillovers and connectedness between Chinese and ASEAN stock markets during bearish and bullish market statuses
Authors: Yousaf Imran , Mensi Walid , Vo Xuan Vinh , Kang Sanghoon
Published: February 2023

Purpose

This study aims to examine the tail connectedness between the Chinese and Association of Southeast Asian Nations (ASEAN) stock markets. More specifically, the authors measure the return spillovers at three quantile levels: median (t = 0.5), lower extreme (t = 0.05) and upper extreme (t = 0.95). The connectedness at extreme upper and lower quantiles provides insightful information to investors regarding tail risk propagation, which ultimately suggests that investors adjust their portfolios according to the extreme bullish and bearish market conditions.

Design/methodology/approach

The authors employ the quantile connectedness approach of Ando et al. (2022) to examine the quantile transmission mechanism among the ASEAN and Chinese stock markets.

Findings

The results show significant evidence of a higher level of connectedness between Chinese and ASEAN stock markets at extreme upper and lower quantiles compared to the median quantiles, which suggests the use of a quantile-based connectedness approach instead of an average-measure-based one. Furthermore, the time-varying connectedness analysis shows that the total spillovers reach the highest peaks during the global financial crisis, the Chinese stock market crash and the COVID-19 pandemic at the upper, lower and median quantiles. Finally, the static and dynamic pairwise spillovers between the Chinese and ASEAN markets vary over quantiles as well.

Originality/value

This study is the first attempt to examine quantile vector autoregression (VAR)-based return spillovers between China and ASEAN stock markets during different market statuses. Besides, the COVID-19 has intensified the uncertainty in Asian countries, mainly China and ASEAN economies.
Affect and information technology use: the impact of state affect on cognitions and IT use
Authors: Dinger Michael , Wade Julie T. , Dinger Steven , Carter Michelle , Thatcher Jason Bennett
Published: February 2023

Purpose

This paper investigates the dynamics between state affect and trusting cognitive beliefs on post-adoptive information technology (IT) use behaviors in the form of intention to explore and deep structure usage. That state affect can influence behaviors is recognized in practice. In fact, some studies examine the impact of affective constructs, but the way state affect impacts how individuals use IT remains largely unexplored. The authors theorize that state affect, in the form of positive and negative affect, will influence trusting cognitive beliefs regarding an IT artifact (in terms of perceived helpfulness, capability and reliability) and, more importantly, directly influence intention to explore and deep structure usage.

Design/methodology/approach

The authors test the model using a sample of 357 IT users. Survey items were derived from established measures, and the data were analyzed using structural equation modeling.

Findings

Results of this study suggest that positive affect and negative affect impact trusting cognitive beliefs. Trusting cognitive beliefs positively impact intention to explore with an IT and deep structure usage of an IT. Even in the presence of trusting beliefs, though, positive affect directly impacts intention to explore. Positive affect and negative affect both also have various indirect, mediated effects on intention to explore and deep structure usage.

Originality/value

In order to maximize value from workplace IT, the results suggest managers foster an authentic, positive work environment in order to harness or redirect employees' emotional energies.
Solution exemplars and sales performance arising in online outsourcing: the moderating role of expertise
Authors: Yang Xi , Zhou Zhiyuan , Zhao Quanwu , London Jackie (Jake) , Tan Guangzhu
Published: February 2023

Purpose

Service providers on highly competitive online outsourcing platforms employ various signals to entice buyers to make online purchases. One such signal—the solution exemplars—attracts attention through depictions of exemplary prior work completed by the service providers. Unfortunately, it is not known the extent to which solution exemplar characteristics affect sales performance nor is it clear how such signals perform in the presence of complementary signals such as service provider expertise. This paper explores these issues.

Design/methodology/approach

Extending signaling theory, the authors develop a model to explore the effects of solution exemplar characteristics (i.e. exemplar quantity, exemplar diversity and exemplar popularity) on sales performance under the moderating impact of service provider expertise. The authors test the model using proprietary data from ZBJ.com, a leading online outsourcing platform in China.

Findings

Exemplar quantity and exemplar popularity positively affect sales performance; exemplar diversity has no significant impact on sales performance and service provider expertise positively moderates the relationships between exemplar quantity, exemplar popularity and sales performance.

Originality/value

This work makes several significant contributions. First, the authors enrich the research on signals in online outsourcing by exploring the impact of solution exemplar characteristics on sales performance. Second, the authors analyze three solution exemplar characteristics: exemplar quantity, exemplar diversity and exemplar popularity. Third, this work shows that service provider expertise moderates the relationship between solution exemplar characteristics and sales performance. Important practical implications for both online outsourcing platforms and service providers are discussed.
Relationship dynamics of trailing spouses before and during a time of crisis
Authors: Végh Judit , Dúll Andrea , Luu Lan Anh Nguyen
Published: February 2023

Purpose

This qualitative study explores how trailing spouses form their relationships before and after a crisis such as the COVID-19 pandemic and what patterns can be observed. It explores their significant relationships with friends and extended family, focusing on dynamics and change.

Design/methodology/approach

The authors conducted semi-structured interviews with seven trailing spouses in Malaysia: before the pandemic, in the beginning and at the end of the first year of the pandemic. The authors used longitudinal interpretative phenomenological analysis (LIPA).

Findings

Being aware of the limits of resources emerged as a key factor in how trailing spouses develop and maintain relationships with friends and extended family. The fact that the pandemic changed the dynamics of their social networks illuminates how crucial these relationships or their absence are in their adjustment and readjustment process. Children play a significant role in these relationships.

Research limitations/implications

Comparative research into the friendships and relationships of different groups of trailing spouses in various locations could capture more specificity of the relationship dynamics.

Practical implications

The explored patterns can promote a better understanding of the relationship dynamics of trailing spouses' networks, which can, in turn, support and facilitate both adjustment and repatriation processes. They can help explain how and what kind of social networks best support trailing spouse transition during a time of crisis or adjustment. These findings could be incorporated into intercultural training programs.

Originality/value

No current study that the authors know of has explored trailing spouses' relationship dynamics in a longitudinal study before and during a crisis.
How strategic knowledge hiding drives competitive individuals to establish research superiority: a case in UK Business Schools
Authors: Mahamed Ismail Ashmiza , Welch Christine Elizabeth
Published: February 2023

Purpose

Why and when people working in organisations hide their knowledge has received considerable academic attention. However, little attention has been paid to knowledge hiding in academia itself, even though universities are known as places where knowledge is shared. This study aims to consider the dilemma faced by academics when undertaking research work: should they share or hide what they are doing?

Design/methodology/approach

Using empirical evidence drawn from 20 academics in a number of UK Business Schools, the authors carried out in-depth interviews to investigate the effects of strategic knowledge hiding (SKH) on research knowledge work. The authors argue that SKH can drive competitive individuals to establish research superiority.

Findings

The findings revealed that most respondents have, for strategic reasons, hidden their tacit and/or explicit knowledge from others during ongoing research processes, but have, at the same time, purposefully sought for knowledge from targeted colleagues.

Originality/value

The findings extend the previous literature by revealing not only the distinctive individual antecedents of SKH but also its positive outcomes. The findings illustrate a pioneering contribution of a systematic model of SKH among university business school academics.
The writing is on the wall: predicting customers' evaluation of customer-firm interactions using computerized text analysis
Authors: Ferreira Caitlin , Robertson Jeandri , Chohan Raeesah , Pitt Leyland , Foster Tim
Published: February 2023

Purpose

This methodological paper demonstrates how service firms can use digital technologies to quantify and predict customer evaluations of their interactions with the firm using unstructured, qualitative data. To harness the power of unstructured data and enhance the customer-firm relationship, the use of computerized text analysis is proposed.

Design/methodology/approach

Three empirical studies were conducted to exemplify the use of the computerized text analysis tool. A secondary data analysis of online customer reviews (n = 2,878) in a service industry was used. LIWC was used to conduct the text analysis, and thereafter SPSS was used to examine the predictive capability of the model for the evaluation of customer-firm interactions.

Findings

A lexical analysis of online customer reviews was able to predict evaluations of customer-firm interactions across the three empirical studies. The authenticity and emotional tone present in the reviews served as the best predictors of customer evaluations of their service interactions with the firm.

Practical implications

Computerized text analysis is an inexpensive digital tool which, to date, has been sparsely used to analyze customer-firm interactions based on customers' online reviews. From a methodological perspective, the use of this tool to gain insights from unstructured data provides the ability to gain an understanding of customers' real-time evaluations of their service interactions with a firm without collecting primary data.

Originality/value

This research contributes to the growing body of knowledge regarding the use of computerized lexical analysis to assess unstructured, online customer reviews to predict customers' evaluations of a service interaction. The results offer service firms an inexpensive and user-friendly methodology to assess real-time, readily available reviews, complementing traditional customer research. A tool has been used to transform unstructured data into a numerical format, quantifying customer evaluations of service interactions.
The lens of Yin-Yang philosophy: the influence of paradoxical leadership and emotional intelligence on nurses’ organizational identification and turnover intention
Authors: Lo Wei-Yuan , Lin Yu-Kai , Lee Hsiang-Ming , Liu Tsui-Yau
Published: February 2023

Purpose

This study aims to use “both–and” thinking of Yin-Yang philosophy to extend the field of leadership literatures and explore the influences of paradoxical leadership and emotional intelligence on organizational identification and turnover intentions of nurses.

Design/methodology/approach

The authors adopted a cross-sectional survey completed by 285 nurses in Taiwan. SPSS 22, PROCESS and AMOS 21 were used for data analysis.

Findings

The results reveal that paradoxical leadership has a significant positive relationship with nurses’ organizational identification and a significant negatively relationship with their turnover intentions, and organizational identification partially mediated the relationship between paradoxical leadership and turnover intentions. The results further show that emotional intelligence strengthens the effect of paradoxical leadership on organizational identification, and paradoxical leadership had a stronger indirect effect on turnover intentions through organizational identification under strong emotional intelligence.

Originality/value

Paradoxical leadership can strengthen managers’ abilities in dealing with interrelated and substantial issues and correspond to organizing and belonging paradoxes in holistic thinking processes. Health-care organizations must shape a coordinated institution and offer training initiatives to increase managers’ ability and attitude to control organizational rules and procedures while allowing employees’ flexibility and autonomy according to the requirements of the situation, which will maintain both organizational short-term benefits and long-term growth.
Coproducing leadership: a reason to resist destructive leaders
Authors: Almeida Teresa , Ramalho Nelson , Esteves Francisco
Published: February 2023

Purpose

Follower's individual differences have been receiving increased attention in studying destructive leadership because followers may enable or disable it. One of these yet under-researched features is the role of followers' leadership coproduction beliefs (a role construal) in explaining their resistance to destructive leaders. Departing from the proactive motivation theory, this paper explores the robustness of coproduction beliefs by testing its ability to predict followers' resistance to destructive leaders across four situations – abusive supervision, exploitative leadership, organization directed behaviors and laissez-faire.

Design/methodology/approach

With a sample of 359 participants that answered a scenario-based survey, the present study tests the relationship between coproduction beliefs and resistance behaviors in the four mentioned groups, while controlling for alternative explanations. A multigroup analysis was conducted with PLS-SEM.

Findings

Constructive resistance is always favored by coproduction beliefs independently of the leader's type of destructive behavior. Dysfunctional resistance, however, is sensitive to the leader's type of destructive behavior.

Originality/value

This paper extends knowledge on the role of coproduction beliefs as an individual-based resource against destructive leaders.
Airborne inoculum dynamics of Polystigma amygdalinum and progression of almond red leaf blotch disease in Catalonia, NE Spain
Authors: Pons‐Solé Gemma , Miarnau Xavier , Torguet Laura , Lázaro Elena , Vicent Antonio , Luque Jordi
Published: February 2023

The dynamics of airborne ascospores and disease progress of red leaf blotch (RLB) of almond, caused by Polystigma amygdalinum, and their correlations with weather variables were studied from 2019 to 2021 in two almond orchards located in Lleida, NE Spain. Airborne ascospores were detected and quantified by real‐time qPCR using species‐specific primers for P. amygdalinum. Ascospores were detected mainly from April to June, with a high variability between the yearly cumulative concentrations. Positive significant correlations were found between the weekly proportion of airborne ascospores and the number of wet and mild days—either combined or separated— accumulated rainfall, number of rainy days, accumulated low temperatures on wet days, and mean and maximum relative humidity. In contrast, several thermal variables (maximum temperature, VPD, and number of warm days) were negatively correlated with ascospore catches. Positive significant correlations were found between the cumulative proportion of ascospores and RLB incidence and severity. Weekly variations in RLB incidence and severity showed significant positive correlations with the number of warm days while negative with the number of mild days. Severity was also positively correlated with several thermal variables (mean, maximum, and minimum temperature, and VPD), and negatively correlated with the number of cold days and wet and mild days. Stronger correlations were generally found with ascospore catches or disease progress when using concurrent weekly weather data. Gompertz, monomolecular, and logistic growth models were evaluated to describe RLB disease progress.
Full‐length transcriptome sequencing reveals extreme incomplete annotation of the goat genome
Authors: Zhang Huanhuan , Liang Yilin , Chen Shaomei , Xuan Zeyi , Jiang Yu , Li Ran , Cao Yanhong
Published: February 2023

Despite recent advances in generating high‐quality reference genome assemblies, the genome sequences for most livestock species, including goats, are still poorly annotated. Single‐molecule long‐read sequencing has greatly facilitated gene annotation by obtaining full‐length transcripts. In this study, we generated full‐length transcriptome data for samples from abomasum (n = 2) and testicle (n = 1), using PacBio Iso‐Seq technology. We further combined these data with published data from abomasum (5ZY, SRR8618141) to evaluate and improve the gene annotation of the goat genome. We identified 14.5–16.3% of novel genes per sample from the four Iso‐Seq datasets. At the transcript level, 40.6% of them were novel, including 29.7% novel transcripts from known genes and 10.9% from novel genes. We further verified the expression of novel genes in four additional RNA‐seq data and found that the expression level of novel genes was significantly lower than that of known genes, indicating that the lowly expressed genes tend to be missed in the current genome annotation. This study shows the superiority of full‐length transcriptome data in gene annotation, and more such data are required to improve the gene annotation for goat genome and other species.
Implementation of a relapse prevention program among smokers undergoing arthroplasty: lessons learned
Authors: Wilker Olivia G. , Stevens Elizabeth R. , Gold Heather T. , Haber Yaa , Slover James D. , Sherman Scott E.
Published: February 2023

Background

Surgery is a potent motivator to help people quit smoking to reduce the risk of complications. Many patients who smoke receive tobacco cessation counseling prior to surgery and are able to quit, but do not receive the same resources after surgery and often resume smoking.

Methods

We present a case study describing the recruitment process, study components, and lessons learned from StayQuit, a comprehensive relapse prevention program designed to prevent relapse after arthroplasty. Lessons learned were examined post hoc to determine challenges related to program implementation, using existing study procedures and information collected.

Results

While a comprehensive postoperative relapse prevention program may be beneficial to patients, implementation of StayQuit is unlikely to be feasible under current circumstances. The primary challenges to successful implementation of StayQuit focused on themes of lack of engagement in the preoperative Orthopedic Surgery Quit Smoking Program (OSQSP) and an environment unfavorable to in‐person enrollment on the day of surgery.

Conclusions

Postoperative relapse prevention programs may be beneficial for patients who quit smoking prior to elective surgery. To help guide implementation, it is important to consider surgeon behavior, the collaboration of clinical and non‐clinical teams, and best practices for study enrollment in surgical settings.