bluuebunny/crossref_metadata_2025 huggingface dataset:
Phyllobacterium melilotisp. nov. a novel non-symbiotic bacterium isolated from root nodules ofMelilotus albus(white sweet clover) grown in Canada
Authors: Bromfield Eden S. P. , Cloutier Sylvie , Hynes Michael F.
Published: November 2024

Two novel bacterial strains isolated from root-nodules of white sweet clover (Melilotus albus) plants grown at a Canadian site were previously characterized and placed in the genusPhyllobacterium. Here we present phylogenomic and phenotypic data to support the description of strain T1293Tas representative of a novel species and present the first complete closed genome sequence of a bacterial strain (T1018) representing the species ‘P. pellucidum’.

Phylogenetic analysis of genome sequences as well as analysis of 53 core genes placed novel strain T1293Tin a highly supported cluster of strains distinct from namedPhyllobacteriumspecies withP. myrsinacearumandP. calauticaeas closest relatives. The highest average nucleotide identity (ANI) and digital DNA-DNA hybridization (dDDH) values of genome sequences of T1293Tcompared to closest species type strains (84.1% and 26.5%, respectively) are well below the threshold values for bacterial species circumscription. The genome of strain T1293Thas a size of 5074034 bp with a DNA G+C content of 55 mol% and possesses three plasmids with sizes of 397619 bp, 476847 bp and 519835 bp. Detected in the genome were Type III and Type VI secretion system genes, implicated in plant-microbe and microbe-microbe interactions, but key nodulation, nitrogen-fixation and photosystem genes were not detected. Further analysis revealed that T1293T, like otherPhyllobacteriumspecies, possesses key genes encoding an enzyme complex implicated in the degradation of glyphosate, a widely used broad-spectrum herbicide that has negative consequences for many microorganisms including the human gut microbiome. A novel prophage (size ∼ 41.5 kb) was also detected in the genome of T1293T. Data for multiple phenotypic tests complemented the sequence-based characterization of strain T1293T. The data presented support the description of a new species and the namePhyllobacterium melilotisp. nov. is proposed with T1293T= LMG32641T= HAMBI 3765Tas the species type strain.
Efficient pheromone navigation via antagonistic detectors
Authors: Wan Xuan , Zhou Tingtao , Susoy Vladislav , Park Core Francisco , Groaz Alessandro , Brady John F. , Samuel Aravinthan D.T. , Sternberg Paul W.
Published: November 2024

Chemotaxis to a potential mate who is moving and emitting a volatile sex pheromone poses a navigation challenge that requires rapid, precise responses to maximize reproductive success. We demonstrate thatCaenorhabditis elegansmales address this challenge by utilizing two pheromone detectors located in head and tail sensory neurons. Despite sharing a receptor SRD-1, AWA head neurons promote forward movement and acceleration, while tail PHD neurons induce reversals and deceleration. In increasing pheromone gradients AWA dominates; whereas weakening gradients inactivate AWAs, allowing PHDs to fine-tune the response and correct the path. Head AWAs are essential for mate-searching, while tail PHDs are crucial for complex tasks. The navigation mode and velocity adapt as males climb a pheromone gradient. A minimal-parameter computational model recapitulates key findings and illuminates the interplay between head and tail signals in adaptive navigation.Graphical abstract:

Spatially separated pheromone detection drives adaptive navigation inC. elegansmales.

Theupper panelillustrates howC. elegansmales utilize spatially separated pairs of sensory neurons, AWA (head) and PHD (tail), that detect the same volatile sex pheromone molecule via the receptor SRD-1. Despite sharing this receptor, head neurons detect gradient changes and activate when concentration increases, suppressing turning, and promoting forward movement and acceleration. In contrast, tail neurons detect absolute concentration and activate at preferred moderate concentrations, inducing reversals and deceleration. Themiddle panelshows that upon initial pheromone introduction, simultaneous activation of head and tail neurons cancels each other out, causing males to transition from random walking to a stationary anchoring state, preventing them from chasing the concentration wave initially. As pheromone concentration increases, head neurons dominate, driving forward locomotion and acceleration. At the highest concentrations, tail neurons become less active while head neurons are highly activated, leading to rapid, goal-directed movement (sprinting). Incorrect directional choices result in AWA deactivation and persistent PHD activity, inducing pausing and local exploration. Repeated unsuccessful attempts trigger area-restricted searching. Thebottom paneldepicts our computational model which recapitulates these behaviors by integrating inputs from head and tail neurons. A confidence metric, which is positively correlated with directional accuracy and speed and negatively correlated with turning, is introduced. Once confidence surpasses a threshold, the model transitions from more random (kinesis) to more directed (taxis) movement. The depicted trajectories represent simulated behavior based on this confidence-driven model.
Neural Encoding of Semantic Structures During Sentence Production
Authors: Giglio Laura , Hagoort Peter , Ostarek Markus
Published: November 2024

The neural representations for compositional processing have so far been mostly studied during sentence comprehension. In an fMRI study of sentence production, we investigated the brain representations for compositional processing during speaking. We used a rapid serial visual presentation sentence recall paradigm to elicit sentence production from the conceptual memory of an event. With voxel-wise encoding models, we probed the specificity of the compositional structure built during the production of each sentence, comparing an unstructured model of word meaning without relational information with a model that encodes abstract thematic relations and a model encoding event-specific relational structure. Whole-brain analyses revealed that sentence meaning at different levels of specificity was encoded in a large left fronto-parieto-temporal network. A comparison with semantic structures composed during the comprehension of the same sentences showed similarly distributed brain activity patterns. An ROI analysis over left fronto-temporal language parcels showed that event-specific relational structure above word-specific information was encoded in the left inferior frontal gyrus (LIFG). Overall, we found evidence for the encoding of semantic meaning during sentence production in a distributed brain network and for the encoding event-specific semantic structures in the LIFG.
Optogenetic stimulation of a cortical biohybrid implant guides goal directed behavior
Authors: Brown Jennifer , Zappitelli Kara M. , Dawson Paul M. , Yoon Eugene , Schiraga Seton A. , Rochford Amy E. , Eltaeb Mohamed , Rodriguez Arturo , Kong Yifan , Hodak Max , Mardinly Alan R.
Published: November 2024

Brain-computer interfaces (BCIs) hold exciting therapeutic potential, but tissue damage caused by probe insertion limits channel count. Biohybrid devices, in which the cell-device interface is crafted in the laboratory, hold promise to address this limitation, but these devices have lacked a demonstration of their applicability for BCI. We developed a biohybrid approach to engraft optogenetically-enabled neurons on the cortical surface housed in a 2D-scaffold of circular microwells. The engrafted neurons survived, exhibited spontaneous activity, and integrated with the host brain several weeks after implantation. We then trained mice with biohybrid implants to perform an optical stimulation task and showed that they could effectively report optogenetic stimulation of their neural graft. This demonstration shows that a cortical biohybrid implant can be used to transmit information to the brain of an implanted animal.
Reprogramming the genome of M13 bacteriophage for all-in-one personalized cancer vaccine
Authors: Huang Shengnan , He Yanpu , Madow Allison , Peng Huaiyao , Griffin Mirielle , Qi Jifa , Huang Mantao , Amoroso Heather , Abrashoff Riley , Heldman Nimrod , Belcher Angela M.
Published: November 2024

Peptide-based vaccines face limitations in immunogenicity and stability, and challenges in co-delivering antigens and adjuvants effectively. Virus-based nanoparticles, particularly M13 bacteriophage, present a promising solution due to their genetic modifiability, intrinsic adjuvanticity, and efficient antigen presentation capabilities. Here we developed a programmable M13 phage-based personalized cancer vaccine enabling single-step antigen-adjuvant assembly. Specifically, we designed a reprogrammed (RP) phage platform that precisely regulates Toll-like receptor 9 activation by programming its genome sequence and modulates antigen density through genetic engineering. Vaccination studies with RP phages demonstrated that the immune response could be modulated by fine-tuning the adjuvanticity and antigen density, revealing an optimal antigen dose and adjuvanticity for maximum vaccine efficacy. The RP phage induced a remarkable 24-fold increase in neoantigen-specific CD8+T cells and eradicated established MC-38 tumors when combined with anti-PD-1 therapy. These findings highlight the RP phage’s potential as a powerful nanovaccine platform for personalized cancer vaccines.
Six-legged-bound: a newly-described insect gait
Authors: Amir A. , Yuval O. , Ayali A.
Published: November 2024

Locomotor behavior is a hallmark of animal biology and ecology. Mole crickets constitute a unique group of subterranean insects that present an exceptional model for locomotion-related research. In response to an aversive stimulus from the front, the mole cricket will consistently adopt a unique backwards gait that we have termed backward-bound. This never before reported six-legged gait comprises a cyclic alternation between the middle and hind-leg pairs with left-right in-phase synchronization, while the front legs display noisy and less consistent phase dynamics. This exceptional gait is transient and is usually expressed for up to a dozen cycles. It is employed to distance the animal quickly away from danger. A gait that can be characterized as “forward-bound” is also displayed by the mole cricket, albeit for a much shorter duration (up to two cycles).
Chlamydia trachomatisgenomes from rectal samples: description of new clade comprisingompA-genotype L4 from Argentina
Authors: Büttner Karina Andrea , Wegner Fanny , Bregy Vera , Entrocassi Andrea Carolina , Gallo Vaulet María Lucía , Aquino Deysi López , La Rosa Luciana , Svidler López Laura , Puolakkainen Mirja H , Hiltunen-Back Eija , Imkamp Frank , Egli Adrian , Seth-Smith Helena MB , Rodríguez Fermepin Marcelo
Published: November 2024

Whole genome analysis has provided us with insights into the evolution ofChlamydia trachomatisand recently into circulating strains which cause lymphogranuloma venereum (LGV). A large LGV outbreak of a newompA-genotype, L2b, was first reported in Europe in the early 2000s, primarily affecting men who have sex with men (MSM), and then expanded globally. More recent work shows this outbreak diversifying into variants of describedompA-genotypes, with the same L2b genomic backbone. This study extends the investigation of LGV cases to Argentina and Finland. In 2017, an LGV outbreak was described in Argentina characterized by distinct genomic features shown by bothompA-genotyping and MLST analysis. We have obtained whole genome sequences from cultured isolates and clinical samples via SureSelect (Agilent) target enrichment. Based onompAand phylogenetic analyses, we describe further diversity within theompA-genotype L2b clade, illustrating the transmission dynamics in both Argentina and Finland. A key finding is that of a novel clade of Argentinian samples, characterised by a proposed newompA-genotype L4. Additionally, we present the genome sequence of a non-LGV strain associated with anorectal proctitis. These findings contribute to the investigation of LGV evolution, particularly with the presence of the novel L4 lineage, and provide insights into genomic diversity and transmission dynamics ofC. trachomatis.

Graphical Abstract

Impact statement

The phylogeny ofC. trachomatishas been described in several publications and has been clear for a decade. The evolution of this STI in the intervening years also informs a great deal about the transmission opportunities and selective pressures that the intracellular bacterium is under. Through genome sequencing, also directly from clinical samples, we provide the first LGV genomes from Argentina and Finland, and describe further evidence of global circulation of theompA-genotype L2b lineage. We describe a fully novel lineage of LGVC. trachomatis, from Argentina, proposed asompA-genotype L4. We also find evidence of a strain causing proctitis from the urogenital lineage. Together, these provide significant new findings in the investigation ofC. trachomatis.

Data summary

All illumina sequence data, with human read data removed using Hostile (1) and KrakenTools (https://github.com/jenniferlu717/KrakenTools), is deposited with the European Nucleotide Archive (ENA) under project number PRJEB72167.
Innervation density governs crosstalk of GPCR-based norepinephrine and dopamine sensors
Authors: López Ricardo C. , Noble Natalie , Özçete Özge D. , Cai Xintong , Handy Gillian E. , Andersen Jonathan W. , Patriarchi Tommaso , Li Yulong , Kaeser Pascal S.
Published: November 2024

GPCR-based fluorescent sensors are widely used to correlate neuromodulatory signaling with brain function. While experiments in transfected cells often reveal selectivity for individual neurotransmitters, sensor specificity in the brain frequently remains uncertain. Pursuing experiments in brain slices and in vivo, we find that norepinephrine and dopamine cross-activate the respective sensors. Non-specific activation occurred when innervation of the cross-reacting transmitter was high, and silencing of specific innervation was indispensable for interpreting sensor fluorescence.
Transcriptional Regulation of Neuropeptide Receptors Decodes Complexity of Peptidergic Modulation of Behavior and Physiology
Authors: Ryu SeungHeui , Wei Yanan , Wu Zekun , Lee DoHoon , Kim Woo Jae
Published: November 2024

The modulation of complex behaviors in response to environmental and physiological contexts is a fundamental aspect of animal biology, with neuropeptides (NPs) playing a crucial role in this process. This study investigates the transcriptional regulation of neuropeptide receptors (NPRs) as a mechanism for context-dependent neuropeptidergic modulation of physiology and behavior. We hypothesize that the transcriptional control of NPR genes, rather than the NPs themselves, is a critical determinant in the context-dependent modulation of behavior and physiology. Using a multi-faceted approach, including comparative genomics, transcription factor network analysis, and empirical validation in model organisms such asDrosophila melanogaster, we reveal a complex regulatory landscape where NPR expression is tightly controlled. Our findings demonstrate that NPR genes exhibit a higher number of enhancers, CTCF-binding sites, and open chromatin regions compared to NP genes, suggesting a greater susceptibility to transcriptional modulation. This regulatory architecture allows for precise control over neuropeptidergic signaling, enabling dynamic and context-specific behavioral and physiological responses. Our results highlight the importance of NPR-expressing cells by transcriptional regulation in mediating the effects of NPs on behavior and physiology. We show that this regulation is conserved across species, indicating an evolutionarily significant mechanism for fine-tuning neuropeptidergic signaling. Furthermore, our study provides insights into the distinct regulatory mechanisms underlying the multifunctionality of NPs and their receptors, offering a novel perspective on the transcriptional control of complex behaviors. In conclusion, this study advances our understanding of neuropeptidergic signaling by focusing on the transcriptional regulation of NPRs. Our findings have broad implications for the development of therapeutic strategies targeting neuropeptidergic systems in various neurological and behavioral disorders.
Advanced EXAFS analysis techniques applied to the L-edges of the lanthanide oxides
Authors: Smerigan Adam , Hoffman Adam S. , Ostervold Lars , Hong Jiyun , Perez-Aguillar Jorge , Caine Ash C. , Greenlee Lauren , Bare Simon R.
Published: November 2024

The unique properties of the lanthanide (Ln) elements make them critical components of modern technologies, such as lasers, anti-corrosive films and catalysts. Thus, there is significant interest in establishing structure–property relationships for Ln-containing materials to advance these technologies. Extended X-ray absorption fine structure (EXAFS) is an excellent technique for this task considering its ability to determine the average local structure around the Ln atoms for both crystalline and amorphous materials. However, the limited availability of EXAFS reference spectra of the Ln oxides and challenges in the EXAFS analysis have hindered the application of this technique to these elements. The challenges include the limited k-range available for the analysis due to the superposition of L-edges on the EXAFS, multielectron excitations (MEEs) creating erroneous peaks in the EXAFS and the presence of inequivalent absorption sites. Herein, we removed MEEs to model the local atomic environment more accurately for light Ln oxides. Further, we investigated the use of cubic and non-cubic lattice expansion to minimize the fitting parameters needed and connect the fitting parameters to physically meaningful crystal parameters. The cubic expansion reduced the number of fitting parameters but resulted in a statistically worse fit. The non-cubic expansion resulted in a similar quality fit and showed non-isotropic expansion in the crystal lattice of Nd2O3. In total, the EXAFS spectra and the fits for the entire set of Ln oxides (excluding promethium) are included. The knowledge developed here can assist in the structural determination of a wide variety of Ln compounds and can further studies on their structure–property relationships.
TOMOMAN: a software package for large-scale cryo-electron tomography data preprocessing, community data sharing and collaborative computing
Authors: Khavnekar Sagar , Erdmann Philipp S. , Wan William
Published: November 2024

Cryo-electron tomography (cryo-ET) and subtomogram averaging (STA) are becoming the preferred methodologies for investigating subcellular and macromolecular structures in native or near-native environments. Although cryo-ET is amenable to a wide range of biological problems, these problems often have data-processing requirements that need to be individually optimized, precluding the notion of a one-size-fits-all processing pipeline. Cryo-ET data processing is also becoming progressively more complex due to the increasing number of packages for each processing step. Though each package has its strengths and weaknesses, independent development and different data formats make them difficult to interface with one another. TOMOMAN (TOMOgram MANager) is an extensible package for streamlining the interoperability of packages, enabling users to develop project-specific processing workflows. TOMOMAN does this by maintaining an internal metadata format and wrapping external packages to manage and perform preprocessing, from raw tilt-series data to reconstructed tomograms. TOMOMAN can also export these metadata between various STA packages. TOMOMAN includes tools for archiving projects to data repositories, allowing subsequent users to download TOMOMAN projects and directly resume processing. By tracking essential metadata, TOMOMAN streamlines data sharing, which improves the reproducibility of published results, reduces computational costs by minimizing reprocessing, and enables the distribution of cryo-ET projects between multiple groups and institutions. TOMOMAN provides a way for users to test different software packages in order to develop processing workflows that meet the specific needs of their biological questions and to distribute their results to the broader scientific community.
Shaping a future research agenda across diverse knowledge spaces in architecture and urbanism – through the lens of Archnet-IJAR
Authors: Patil Madhavi P. , Salama Ashraf M.
Published: November 2024

Purpose

The objective of this article is to articulate a research agenda in architecture and urbanism by reviewing the contributions to Archnet-IJAR: International Journal of Architectural Research from 2022 to 2024. The article aims to develop a robust classification into established, evolving and emerging knowledge spaces. Such a classification seeks to offer insights into the role Archnet-IJAR plays in shaping current and future global research trends in architecture and urbanism.

Design/methodology/approach

A combination of bibliometric and textual analysis was employed, utilising tools such as VosViewer and Infranodus to map thematic structures and research trends. The examined articles were categorised into established, evolving and emerging knowledge spaces to assess how the journal dynamically adapts to and reflects global shifts in architectural and urban discourse. This classification offers a strategic lens into the influence of Archnet-IJAR on research trajectories and shaping the future landscape of scholarship in architecture and urbanism.

Findings

The study identifies three primary areas of discourse: sustainability and resilience, technology and innovation, and community-centred design. Key trends include the rise of AI and smart technologies, the impact of the COVID-19 pandemic on design strategies, and the integration of SDGs into architectural education and practice. Established knowledge spaces such as urban morphology and cultural heritage remain foundational while evolving spaces such as sustainability and resilience are gaining prominence. Emerging spaces such as smart technologies and bioclimatic architecture appear to be the future trajectory of research in the field.

Research limitations/implications

The study focuses on three years (2022–2024) of analysing Archnet-IJAR content within an overarching contextualisation over the past decade. However, this may not capture longer-term trends.

Originality/value

The study presents a critical classification of architectural and urban discourse, highlighting the evolving nature of the field in response to global challenges. The notion of the knowledge spaces as a unique conceptualisation that integrates various thematic areas is emphasised.
Expatriate staffing in foreign subsidiaries and host market contestability
Authors: Zajc Kejžar Katja , Golob Šušteršič Tina
Published: November 2024

Purpose

This paper aims to study the decision of multinational enterprises (MNEs) whether to employ a host-country (HCN) or a parent-country national (PCN) manager in their subsidiaries, focusing on the role of host market contestability.

Design/methodology/approach

We develop an empirical model for the probability of appointing a PCN manager in the population of all foreign-owned firms registered in Slovenia over a nine-year period. We combine four different micro databases: a matched employer–employee database, firm-level inward FDI data, firm-level outward FDI data and firm-level financial data, and apply a heteroskedastic probit model, a random effects probit estimator and a fixed effects panel data estimator. The final, fully merged database contains on average of about 28,000 firms per year.

Findings

We find that the propensity to appoint a PCN manager is higher in subsidiaries that compete with less-productive local rival firms in tacit knowledge-intensive industries with lower competition. The results also suggest that the likelihood of employing expatriates is higher in larger, younger and more export-oriented subsidiaries in less distant locations. In addition, cultural distance between the investing and host countries has been found to be more relevant than physical distance and to account for much of the differences between investors from different regions.

Originality/value

An important advantage of our paper is that we use comprehensive firm-level data on the entire population of firms operating in a host country, including both domestic and foreign-owned firms. This allows us to introduce a wide range of host-country market structure and local rival firm characteristics into our empirical model of the expatriation decision, which have not been previously tested. Additionally, we account for MNE heterogeneity in terms of investor origin, while controlling for investor country characteristics such as cultural, institutional and geographical distance from the host country.
Review of artificial intelligence applications in construction management over the last five years
Authors: Zhang Jingqi , Jiang Shaohua
Published: November 2024

Purpose

This paper provides a thorough examination of the advancements and impacts of artificial intelligence (AI) on construction management (CM) over the past five years, particularly focusing on its role in mitigating prevalent challenges such as inefficiency and ensuring quality. By methodically reviewing and synthesizing the body of research conducted in this period, it underscores key contributions and breakthroughs in the application of AI within construction management (AICM). Additionally, the study aims to shed light on emerging trends and forecast future directions for technological innovation in the construction management sector.

Design/methodology/approach

Guided by the preferred reporting items for systematic reviews and meta-analyses (PRISMA) framework, this research conducts a bibliometric analysis of 176 relevant publications from the past five years. The analysis focuses on the adoption of AICM across three critical areas: construction equipment management, improvement of construction safety and construction cost optimization. Additionally, the study systematically identifies and examines 14 emerging themes within this domain, ensuring a comprehensive exploration aligned with PRISMA guidelines.

Findings

This manuscript summarizes recent research from the past five years in three key areas: construction equipment management, construction safety management and construction cost management within the realm of AICM. It identifies key gaps and outlines future research directions, including enhancing AI-driven equipment integration, developing sophisticated AI-based safety systems and optimizing cost management with advanced data analytics. These findings and directions are essential for steering the field toward greater digital innovation and sustainability.

Originality/value

This research provides a detailed analysis of the literature within the AICM domain, thoughtfully compiling significant findings and highlighting the importance of addressing user needs. The insights and recommendations shared aim to be beneficial for both academic researchers and industry professionals, contributing to the ongoing development of AICM as it moves toward a future characterized by digital innovation and sustainability.
Larsen & Toubro: constructing competencies and building the nation
Authors: Mital Amita , V. Krishnan , Mehta Yuvraj
Published: November 2024

Learning outcomes

The following are the objectives of the case study: building and leveraging core competence, realizing the strategic advantage of incumbency and contribution to nation building as a business potential.

Case overview/synopsis

Larsen and Toubro (L&T) started as a trading company in 1938. By 2023 L&T was a mammoth infrastructure company with a market cap INR 4,750bn operating 800–1,000 projects in engineering and construction at any point in time. It also worked in the domain of hydrocarbons, power and heavy engineering including defence engineering, financial services and development projects supported by technology. The company went through several phases of environmental disruptions in the form of the Second World War and India’s independence, which brought several opportunities for growth. L&T built competencies to leverage these opportunities, which also contributed to the nation building efforts in India. In 2023, several changes were occurring in the ecosystem in the form of energy changes, sustainability becoming a way of life and digitalization impacting every aspect of business. The managing director and chief executive officer Mr S.N. Subrahmanyan reiterated the need to focus on performance to make L&T a global leader in futuristic tech-driven engineering and solutions. He faced three major challenges – reducing exposure in non-core businesses, adopting technology to strengthen traditional business and leveraging the competence built over 85 years to improve the performance of L&T, while contributing to nation building.

Complexity academic level

This case study is suitable for MBA and executive programmes.

Supplementary materials

Teaching notes are available for educators only. Video of protagonist in conversation with Anant Maheshwari, President Microsoft India discussing the future plans of L&T for adopting new age technology. The video is available at the following YouTube link https://www.youtube.com/watch?v=OKb-_z_ch4E

Subject code

CSS 11: Strategy.
Mega-influencer follower effect: the mediating role of sense of control in brand attitudes, purchase intentions and engagement
Authors: Dong Xuebing , Zhou Run , Liao Junyun
Published: November 2024

Purpose

In influencer advertising, followers engage in more frequent and timely interactions compared to nonfollowers, making them the primary audience for these advertisements. Building on this premise, this study aims to examine the impact of different influencer types, categorized by follower count, on the advertised brands.

Design/methodology/approach

The authors tested the hypotheses in four studies, including one secondary data analysis and three experiments.

Findings

Combining real-world data with a series of experiments, the authors show that the followers of mega-influencers (vs micro influencers) have a more positive response to the advertised brands, with more positive brand attitudes, greater purchase intentions and higher engagement. The authors call this the “mega-influencer follower effect.” It is driven by the sense of control. This effect only occurs among the followers and not nonfollowers. Moreover, the mega-influencer follower effect only existed in human influencers, not virtual influencers.

Research limitations/implications

This study takes influencer followers as influencer advertising audiences and investigates the effect of influencer types (based on the number of followers) on the advertised brands; however, future research may investigate how consumers respond to brands in different categories endorsed by influencers.

Practical implications

The authors argue that influencer advertising audiences are more likely to be followers of the influencer. From this perspective, the results suggest that marketers should cooperate with mega-influencers.

Originality/value

Through emphasizing the value of followers rather than nonfollowers as audiences, this study expands the literature on influencer marketing and the explanatory mechanisms regarding which types of influencers are more effective.
Examining inter-relationships among 21st century learning skills and their impacts on tertiary learners’ readiness for careers in Industry Revolution 4.0 era
Authors: Yeoh Hong Beng , Wei Chooi Yi , Kaur Surindar , Kaur Malvin
Published: November 2024

Purpose

As the world is embarking on Industry Revolution 4.0 (IR 4.0), employers demand more learning and soft skills from graduates to adapt to agile and disruptive work environments. Hence, 21st century learning skills are vital for sustainable career advancement in the current job paradigm shift initiated by IR 4.0-driven technologies. This research examines inter-relationships among 21st century skills and their effects on tertiary learners’ readiness for future employment in IR 4.0 era.

Design/methodology/approach

The quantitative research methodology with a questionnaire survey is used. Question items in the questionnaire were adapted from past studies. A sample of tertiary learners who are currently pursuing their final year degree programs in a comprehensive university are recruited using a multi-staged cluster sampling technique. Partial least square-structural equation modeling (PLS-SEM) is applied to analyze data collected from 174 respondents.

Findings

The research findings reveal that tertiary learners’ critical thinking and problem-solving skills significantly influence their perceived readiness to face future employment in IR 4.0 era. Tertiary learners’ communication skills facilitate better collaboration skills that directly influence their problem-solving skills. Their critical thinking skills partially mediate the effect of tertiary learners’ creativity skills on their problem-solving skills.

Originality/value

These research findings provide insights into the inter-relationships among 21st century learning skills that significantly influence tertiary learners’ readiness for their future careers so that stakeholders, including tertiary learners, lecturers and higher education policymakers, can work hand-in-hand toward enhancing employability among fresh graduates in IR 4.0 era.
Online review based IPA and IPCA: the case of Korean mobile banking apps
Authors: Kim Sohui , Ryu Min Ho
Published: November 2024

Purpose

This study introduces a novel approach to conducting importance-performance analysis (IPA) and importance-performance competitor analysis (IPCA) by utilizing online reviews as an alternative to traditional survey-based marketing research.

Design/methodology/approach

In order to conduct IPA and IPCA utilizing online reviews, the following three steps were executed: (1) Extract key attributes of the product/service with latent Dirichlet allocation (LDA) topic modeling. (2) Measure the importance of each attribute with keyword analysis. (3) Measure the performance of each attribute with KoBERT-based sentiment analysis.

Findings

By utilizing LDA, we were able to identify significant attributes identified by real users’ reviews. The approach of evaluating attribute importance using keyword metrics offers the advantage of straightforward computations, reducing computational expenses and facilitating intuitive metric assessments. The evaluation of BERT-based performance involved adapting pre-trained language models to the specific analysis domain, resulting in substantial time savings without compromising accuracy, ultimately bolstering the dependability of the metrics. Lastly, the case study’s findings indicate a growing emphasis on the aesthetic aspects of mobile banking apps in South Korea while highlighting the pressing need for enhancements in critical areas such as stability and security, which are particularly pertinent to the finance industry.

Originality/value

Previous studies have limitations in assessing significance solely based on sentiment scores and review ratings, resulting in an inability to independently measure satisfaction and importance metrics. This research addresses these limitations by introducing a keyword frequency-based importance metric, enhancing the accuracy and suitability of these measurements independently. In the context of performance measurement, this study utilizes pre-trained large language models (LLMs), which provide a cost-effective alternative to previous methods while preserving measurement accuracy. Additionally, this approach demonstrates the potential for industry-wide competitive analysis by enabling comparisons among multiple competitors. Furthermore, the study extends the application of review data-based IPA and IPCA, traditionally used in the tourism sector, to the evaluation of financial mobile applications. This innovation expands the scope of these methodologies, indicating their potential applicability across various industries.
Empowering homes through energy efficiency: A comprehensive review of smart home systems and devices
Authors: Singh Seema , Aggarwal Neha , Prince  , Dabas Devika
Published: November 2024

Purpose

In recent years, both homeowners and the research community have shown a growing interest in home automation devices and smart homes. About one-third of all primary energy resources are used by homes worldwide, which consume significant energy. This has raised concerns regarding energy accessibility and the quick depletion of energy sources, the growing need for building services, the improvement of comfortable lifestyles and the increased time spent at home. This study aims to offer a comprehensive and significant examination of state-of-the-art intelligent control systems used for managing energy and ensuring comfort in smart homes.

Design/methodology/approach

After conducting a comprehensive search in the Scopus database, a total of 55 articles were carefully selected. Using the Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4 SLR) technique for systematic reviews, the current study synthesized prior research on energy efficiency in smart homes and conducted a detailed descriptive analysis to describe the current state of knowledge.

Findings

Future research on energy efficiency in smart homes could delve into various prospective areas that would strengthen existing knowledge and practices. Using innovative technologies in smart homes can reduce energy consumption in residential areas by offering convenience and improved features.

Originality/value

To the best of the authors’ knowledge, this is the first systematic literature review focused on intelligent control systems for energy and comfort management in smart homes, as well as residents’ interaction with indoor comfort.
Enhancing human behavior recognition with dynamic graph convolutional networks and multi-scale position attention
Authors: Huang Peng , Jiang Hongmei , Wang Shuxian , Huang Jiandeng
Published: November 2024

Purpose

Human behavior recognition poses a pivotal challenge in intelligent computing and cybernetics, significantly impacting engineering and management systems. With the rapid advancement of autonomous systems and intelligent manufacturing, there is an increasing demand for precise and efficient human behavior recognition technologies. However, traditional methods often suffer from insufficient accuracy and limited generalization ability when dealing with complex and diverse human actions. Therefore, this study aims to enhance the precision of human behavior recognition by proposing an innovative framework, dynamic graph convolutional networks with multi-scale position attention (DGCN-MPA) to sup.

Design/methodology/approach

The primary applications are in autonomous systems and intelligent manufacturing. The main objective of this study is to develop an efficient human behavior recognition framework that leverages advanced techniques to improve the prediction and interpretation of human actions. This framework aims to address the shortcomings of existing methods in handling the complexity and variability of human actions, providing more reliable and precise solutions for practical applications. The proposed DGCN-MPA framework integrates the strengths of convolutional neural networks and graph-based models. It innovatively incorporates wavelet packet transform to extract time-frequency characteristics and a MPA module to enhance the representation of skeletal node positions. The core innovation lies in the fusion of dynamic graph convolution with hierarchical attention mechanisms, which selectively attend to relevant features and spatial relationships, adjusting their importance across scales to address the variability in human actions.

Findings

To validate the effectiveness of the DGCN-MPA framework, rigorous evaluations were conducted on benchmark datasets such as NTU-RGB + D and Kinetics-Skeleton. The results demonstrate that the framework achieves an F1 score of 62.18% and an accuracy of 75.93% on NTU-RGB + D and an F1 score of 69.34% and an accuracy of 76.86% on Kinetics-Skeleton, outperforming existing models. These findings underscore the framework’s capability to capture complex behavior patterns with high precision.

Originality/value

By introducing a dynamic graph convolutional approach combined with multi-scale position attention mechanisms, this study represents a significant advancement in human behavior recognition technologies. The innovative design and superior performance of the DGCN-MPA framework contribute to its potential for real-world applications, particularly in integrating behavior recognition into engineering and autonomous systems. In the future, this framework has the potential to further propel the development of intelligent computing, cybernetics and related fields.
Challenges and solutions when implementing lesson study from the perspective of German primary schools
Authors: Vock Miriam , Bucher Julian , Kager Klara
Published: November 2024

Purpose

This study examines the experiences of five German primary schools implementing Lesson Study over a five-year period. When lesson study is to be implemented in Germany, teachers are typically skeptical and do not believe that it will work in their schools. Although four of the schools from our project consider the implementation at their school to be quite successful and report many positive effects, in this article, we focus on the difficulties and strategies for overcoming them. We also report the schools’ recommendations for other schools wishing to implement lesson study.

Design/methodology/approach

Using maximum variation sampling, we conducted semi-structured interviews with ten German primary teachers and principals from five schools taking part in the nationwide LemaS project. The interviews were recorded, transcribed and analyzed using qualitative content structuring analysis.

Findings

The study identified several challenges, ranging from fundamental criticism of lesson study to a lack of resources. All but one school found ways to navigate these challenges. The main themes for success included fostering motivation for lesson study and adequate support from the school leadership.

Practical implications

This study offers examples of strategies of schools to overcome typical hurdles when implementing lesson study. We also present a list of ten recommendations derived from the interviewees that can serve as pragmatic guidelines for practitioners and researchers willing to implement and sustain lesson study.

Originality/value

This study captures the experiences of both teachers and school leaders, providing practical insight for schools wishing to implement the lesson study in a sustainable way.
The free shipping endowment: exploring omnichannel fulfillment steering by nudging consumers toward alternative order fulfillment methods
Authors: Brockhaus Sebastian , Taylor Daniel , Knemeyer A. Michael , Murphy Paul R.
Published: November 2024

Purpose

This research explores the concept of omnichannel fulfillment steering (OFS) and demonstrates how retailers can influence a consumer’s fulfillment decisions through commonly used financial incentives such as discounts, credits and the opportunity to avoid home delivery fees.

Design/methodology/approach

We present insights from two theoretically grounded experiments to examine how different types of financial incentives can be used by omnichannel retailers to steer consumers from home delivery toward three alternative order fulfillment methods (AOFM) – buy-online-pickup-in-store, curbside-pickup and ship-to-locker.

Findings

Our analysis suggests that an opportunity to avoid shipping fees (penalty-avoidance) is a more effective OFS nudge than offering discounts or store credits (rewards). No difference was observed between offering discounts or credits as steering mechanisms; further, no omnichannel steering benefits were observed among the tested AOFMs. Collectively, these findings provide possible justification for retailers’ prioritization of credits to foster customer in-store visits, thus encouraging greater customer engagement and facilitating cross-selling opportunities. Finally, we uncover a penalty-avoidance endowment effect for “free shipping” of purchases over the current industry-standard free shipping threshold.

Practical implications

Retailers might prioritize store credits over discounts as nudges to steer customers toward an AOFM, with buy-online-pickup-in-store offering the greatest benefits for most retailers. Furthermore, using penalty-avoidance OFS incentives over a typical free shipping threshold may increase AOFM selection rates but engender adverse customer reactions.

Originality/value

Advancing the concept of OFS, this study directly informs retailers’ omnichannel incentive programs to nudge customers back into the store. Countering intertemporal choice theory, we could not demonstrate that delayed incentives are less effective than immediate ones. Based on prospect theory, we identify a free shipping endowment effect at a specific reference point along a purchase amount continuum.
The impact of the COVID-19 pandemic on e-learning adoption in an emerging market: a longitudinal study using the UTAUT model
Authors: Nair Manas Somakumar , Nair Jessy , Chellasamy Aarthy
Published: November 2024

Purpose

The COVID-19 pandemic provided unprecedented impetus to the evolution of the e-learning learning ecosystem by compelling students to adopt e-learning systems. This paper aims to use the UTAUT model to provide insight into the differences in factors influencing the adoption of e-learning systems before and after the pandemic.

Design/methodology/approach

This longitudinal study uses two surveys conducted among graduate students in the city of Bengaluru in India. One prior to the start of the COVID-19 pandemic and a second in its aftermath. PLS-SEM is used to analyze both data sets to draw insights into the constructs that influence Behavioral intention to adopt e-learning systems. The moderating effect of gender is also analyzed.

Findings

Pre COVID-19, Facilitating Conditions, Performance Expectancy and Effort Expectancy (quadratic behavior) were dominant factors influencing the adoption of e-learning technologies. Post pandemic, Performance Expectancy and Social Influence are drivers of e-learning adoption. Effort Expectancy and Facilitating Conditions grouped as Ease of Use is a significant driver of e-learning adoption post pandemic. Gender is found to not have a moderating influence.

Originality/value

The unique longitudinal study of the differences in factors influencing students’ intention to adopt e-learning pre- and post-COVID-19 can prove useful to policy makers in the higher education sector. Academics can use the post-pandemic e-learning model’s findings in multiple contexts such as generational cohorts, educational contexts and social contexts.