Search results

The effectiveness of rhetorical structure is essential to communicate key messages in research articles (RAs). The interdisciplinary nature of library and information science (LIS) has led to unclear patterns and practice of using rhetorical structures. Understanding how RAs are constructed in LIS to facilitate effective scholarly communication is important. Numerous studies investigated the rhetorical structure of RAs in a range of disciplines, but LIS articles have not been well studied.

In this study, the authors encoded rhetorical structures to 2,216 articles in the Journal of the Association for Information Science and Technology covering a period from 2001 to 2018 with the approaches of co-word analysis and visualization. The results show that the predominant rhetorical structures used by LIS researchers follow the sequence of Introduction-Literature Review-Methodology-Result-Discussion-Conclusion (ILMRDC).

The authors' temporal examination reveals the shifts of evolutionary pattern of rhetorical structure in 2008 and 2014. More importantly, the authors' study demonstrates that rhetorical structures have varied greatly across research areas in LIS community. For example, scholarly communication and scientometrics studies tend to exclude literature review in articles.

The present paper offers a first systematic examination of how rhetorical structures are used in a representative sample of a LIS journal, especially from a temporal perspective.

The purpose of this study is to identify the impact of online learning on university librarians’ professional development and library services.

A mixed-methods study through an explanatory research design was applied to address the study’s objectives. Quantitative data were gathered from 341 librarians working in 221 universities, while qualitative data were gathered from 27 experts working in 21 different universities of Pakistan.

The findings of the study revealed that online learning has a significant positive impact on the professional development of university librarians. Results revealed that online learning assists in the provision of sustainable, innovative library services in university libraries.

The study has offered a model in light of the study's quantitative and qualitative findings. It contributes to theoretical understanding by expanding the existing knowledge base. It offers managerial insights, enabling the development of policies that foster the professional development of library personnel and the implementation of smart library services.

This article aims to explore the potential of feminist phenomenology as a conceptual framework for advancing women’s entrepreneurship research and the suitability of interpretative phenomenological analysis (IPA) to the proposed framework.

The article critically examines the current state of women’s entrepreneurship research regarding the institutional context and highlights the benefits of a shift towards feminist phenomenology.

The prevailing disembodied and gender-neutral portrayal of entrepreneurship has resulted in an equivocal understanding of women’s entrepreneurship and perpetuated a male-biased discourse within research and practice. By adopting a feminist phenomenological approach, this article argues for the importance of considering the ontological dimensions of lived experiences of situatedness, intersubjectivity, intentionality and temporality in analysing women entrepreneurs’ agency within gendered institutional contexts. It also demonstrates that feminist phenomenology could broaden the current scope of IPA regarding the embodied dimension of language.

The adoption of feminist phenomenology and IPA presents new avenues for research that go beyond the traditional cognitive approach in entrepreneurship, contributing to theory and practice. The proposed conceptual framework also has some limitations that provide opportunities for future research, such as a phenomenological intersectional approach and arts-based methods.

The article contributes to a new research agenda in women’s entrepreneurship research by offering a feminist phenomenological framework that focuses on the embodied dimension of entrepreneurship through the integration of IPA and conceptual metaphor theory (CMT).

This paper aims to design a hybrid model of knowledge-based performance management system (KBPMS) for facilitating Lean Six-Sigma (L6s) application to increase contractor productivity without compromising human safety in Indonesian upstream oil field operations that manage ageing and life extension (ALE) facilities.

The research design applies a pragmatic paradigm by employing action research strategy with qualitative-quantitative methodology involving 385 of 1,533 workers. The KBPMS-L6s conceptual framework is developed and enriched with the Analytical Hierarchy Process (AHP) to prioritize fit-for-purpose Key Performance Indicators. The application of L6s with Human Performance Modes analysis is used to provide a statistical baseline approach for pre-assessment of the contractor’s organizational capabilities. A comprehensive literature review is given for the main pillars of the contextual framework.

The KBPMS-L6s concept has given an improved hierarchy for strategic and operational levels to achieve a performance benchmark to manage ALE facilities in Indonesian upstream oil field operations. To increase quality management practices in managing ALE facilities, the L6s application requires an assessment of the organizational capability of contractors and an analysis of Human Performance Modes (HPM) to identify levels of construction workers’ productivity based on human competency and safety awareness that have never been done in this field.

The action research will only focus on the contractors’ productivity and safety performances that are managed by infrastructure maintenance programs for managing integrity of ALE facilities in Indonesian upstream of oil field operations. Future research could go toward validating this approach in other sectors.

This paper discusses the implications of developing the hybrid KBPMS- L6s enriched with AHP methodology and the application of HPM analysis to achieve a 14% reduction in inefficient working time, a 28% reduction in supervision costs, a 15% reduction in schedule completion delays, and a 78% reduction in safety incident rates of Total Recordable Incident Rate (TRIR), Days Away Restricted or Job Transfer (DART) and Motor Vehicle Crash (MVC), as evidence of achieving fit-for-purpose KPIs with safer, better, faster, and at lower costs.

This paper does not discuss social implications

This paper successfully demonstrates a novel use of Knowledge-Based system with the integration AHP and HPM analysis to develop a hybrid KBPMS-L6s concept that successfully increases contractor productivity without compromising human safety performance while implementing ALE facility infrastructure maintenance program in upstream oil field operations.

This study aims to systematically review various behavioral biases that impact an investor’s decision-making process. The prime objective of this paper is to thematically explore the behavioral bias literature and propose a comprehensive framework that can elucidate a more reasonable explanation of changes in financial markets and investors’ behavior.

Systematic literature review (SLR) methodology is applied to a portfolio of 71 peer-reviewed articles collected from different electronic databases between 2007 and 2021. Content analysis of the extant literature is performed to identify the research themes and existing gaps in the literature.

This research identifies publication trends of the behavioral biases literature and uncovers 24 different biases that impact individual investors’ decision-making. Through thematic analysis, an attribute–consequence–impact framework is proposed that explains different biases leading to individual investors’ irrationality. The study further proposes directions for future research by applying the theory–characteristics–context–methodology framework.

The results of this research will help scholars and practitioners in understanding the existence of various behavioral biases and assist them in identifying potential strategies which can evade the negative effects of these biases. The findings will further help the financial service providers to understand these biases and improve the landscape of financial services.

The essence of the current paper is the application of the SLR method on 24 biases in the area of behavioral finance. To the best of the authors’ knowledge, this study is the first attempt of its kind which provides a methodical and comprehensive compilation of both cognitive and emotional behavioral biases that affect the individual investor’s decision-making.

This research study aims to inquire into the technostress phenomenon at an organizational level from machine learning (ML) and artificial intelligence (AI) deployment. The authors investigated the role of ML and AI automation-augmentation paradox and the socio-technical systems as coping mechanisms for technostress management amongst managers.

The authors applied an exploratory qualitative method and conducted in-depth interviews based on a semi-structured interview questionnaire. Data were collected from 26 subject matter experts. The data transcripts were analyzed using thematic content analysis.

The study results indicated that role ambiguity, job insecurity and the technology environment contributed to technostress because of ML and AI technologies deployment. Complexity, uncertainty, reliability and usefulness were primary technology environment-related stress. The novel integration of ML and AI automation-augmentation interdependence, along with socio-technical systems, could be effectively used for technostress management at the organizational level.

This research study contributed to theoretical discourse regarding the technostress in organizations because of increased ML and AI technologies deployment. This study identified the main techno stressors and contributed critical and novel insights regarding the theorization of coping mechanisms for technostress management in organizations from ML and AI deployment.

The phenomenon of technostress because of ML and AI technologies could have restricting effects on organizational performance. Executives could follow the simultaneous deployment of ML and AI technologies-based automation-augmentation strategy along with socio-technical measures to cope with technostress. Managers could support the technical up-skilling of employees, the realization of ML and AI value, the implementation of technology-driven change management and strategic planning of ML and AI technologies deployment.

This research study was among the first few studies providing critical insights regarding the technostress at the organizational level because of ML and AI deployment. This research study integrated the novel theoretical paradigm of ML and AI automation-augmentation paradox and the socio-technical systems as coping mechanisms for technostress management.

While the potential of human resource practices (HRPs) for promoting performance is widely recognized, even though crucial, employees’ assessment of HRPs remains under-researched, especially in emerging economies. Hence, the purpose of this research is to examine the influence of employee satisfaction with HRPs on job performance through the mediating role of job dedication (JD) and the moderating role of incentive gamification.

The current research adopts a quantitative method. Specifically, using a questionnaire survey, 418 valid responses collected (through purposive sampling) via cross-sectional method from the employees of Nigerian Information and Communication Technology (ICT) firms were used to test the research hypotheses empirically.

The results revealed that satisfaction with HRPs has a positive influence on job performance. Satisfaction with human resource practices has a positive influence on job dedication. Job dedication has a positive influence on job performance. The link between employees’ satisfaction with human resource practices and job performance is mediated by job dedication. The link between satisfaction with human resource practices and job dedication is moderated by incentive gamification, that is, the positive link is stronger when incentive gamification is high. The link between satisfaction with human resource practices and job performance is moderated by incentive gamification, that is, the positive link is stronger when incentive gamification is high.

The current study highlights the importance of employees’ assessments of human resource practices, which may be used to promote employee dedication, which in turn results in improved performance. The findings are helpful to open the black box of the impact of satisfaction with HRPs on job performance. The results also offer important new valuable guidance for practitioners and will aid the management of human resource practice design, audits, and communication.

For the provision of smart library services to end users, tools of the Internet of Things (IoT) play a significant role. The study aims to discover the factors influencing the adoption of IoT in university libraries, investigate the impact of IoT on university library services and identify challenges to adopt IoT applications in university libraries.

A systematic literature review was carried out to address the objectives of the study. The 40 most relevant research papers published in the world’s leading digital databases were selected to conduct the study.

The findings illustrated that rapid growth in technology, perceived benefits, the networked world and the changing landscape of librarianship positively influenced the adoption of IoT in university libraries. The study also displayed that IoT supported library professionals to initiate smart library services, assisted in service efficiency, offered context-based library services, provided tracking facilities and delivered effective management of library systems. Results also revealed that a lack of technical infrastructure, security and privacy concerns, a lack of technological skills and unavailability of policy and strategic planning caused barriers to the successful adoption of IoT applications in university libraries.

The study has provided theoretical implications through a valuable addition to the current literature. It has also offered managerial implications for policymakers to construct productive policies for the implementation of IoT applications in university libraries for the attainment of fruitful outcomes. Finally, the study provides a baseline for understanding the adoption of IoT in academic libraries.

The COVID-19 pandemic has posed many challenges in almost all sectors around the globe. Because of the pandemic, government entities responsible for managing health-care resources face challenges in managing and distributing their limited and valuable health resources. In addition, severe outbreaks may occur in a small or large geographical area. Therefore, county-level preparation is crucial for officials and organizations who manage such disease outbreaks. However, most COVID-19-related research projects have focused on either state- or country-level. Only a few studies have considered county-level preparations, such as identifying high-risk counties of a particular state to fight against the COVID-19 pandemic. Therefore, the purpose of this research is to prioritize counties in a state based on their COVID-19-related risks to manage the COVID outbreak effectively.

In this research, the authors use a systematic hybrid approach that uses a clustering technique to group counties that share similar COVID conditions and use a multi-criteria decision-making approach – the analytic hierarchy process – to rank clusters with respect to the severity of the pandemic. The clustering was performed using two methods, k-means and fuzzy c-means, but only one of them was used at a time during the experiment.

The results of this study indicate that the proposed approach can effectively identify and rank the most vulnerable counties in a particular state. Hence, state health resources managing entities can identify counties in desperate need of more attention before they allocate their resources and better prepare those counties before another surge.

To the best of the authors’ knowledge, this study is the first to use both an unsupervised learning approach and the analytic hierarchy process to identify and rank state counties in accordance with the severity of COVID-19.

This study aims to understand workplace conflict outcomes (WCO) literature and identify the research gaps by mapping its knowledge base and theoretical evolution.

This study combines bibliometric and qualitative analysis and encompasses 1,043 Scopus-indexed documents published between 1972 and 2022. The bibliometric analysis used VOSviewer, Excel and Tableau software for descriptive statistics, citation and co-citation analyses of publication patterns, authors, documents and journals. The qualitative analysis critiqued main theoretical perspectives and topical interests.

This study revealed a significant increase in literature after 2000, with authors representing 70 societies, primarily the USA, China, Australia, Canada and the Netherlands. Influential authors and their canonical articles were identified, including Jehn, De Dreu, Spector, Amason and Pelled. Highly cited articles focused on task, relationship, role and process conflict. Four main theoretical schools were categorized: conflict type paradigm, individual differences, conflict cooccurrence and conflict dynamics. Influential journals spanned psychology, management, negotiation and decision-making and business and marketing fields, including JAP, AMJ, ASQ, JM, JOB, AMR, IJCMA and OS.

This study provides implications for future bibliometric analyses, theoretical and empirical studies, practitioners and society based on its quantitative and qualitative findings.

To the best of the authors’ knowledge, this study represents the first bibliometric review of WCO literature, serving as a baseline for tracking the field’s evolution and theoretical advancements.