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Technological expansion and adoption in university libraries have precipitated cybercrimes and the need to equip library personnel with the required knowledge to combat this menace. Consequently, this study aims to examine cyber security in university libraries and its implication for Library and Information Science education.

The study adopted descriptive research design, while questionnaire and interview were used to elicit data from library personnel and heads of library schools, respectively. A total of 134 responses were elicited through structured questionnaire (administered online due to the closure of universities) while six heads of library schools were interviewed, one from each of the six geopolitical zones in Nigeria.

The data from the questionnaire which were descriptively analysed revealed that the perceived knowledge of cyber security among the librarians was moderately low. Also, the university libraries were exposed to various cyber threats, with cyber security/guideline been one of the critical measures to combat cybercrime. Also, the result showed that librarians displayed high level of adherence to cyber ethics. However, the disposition of library management towards cyber security issues was revealed to be the main challenge to the deployment of cyber security in university libraries, follow by poor password management. Majority of the librarians possess basic knowledge of cyber security, though with serious interest to learn more about it. They were not taught cyber security in library school and they indicated enthusiasm to learn about it. The result of the interview with heads of library schools showed majority of these schools do not offer cyber security course due to dearth in skilled manpower.

The study presents cybercrime as a menace, if not tackled, would affect the university libraries’ sustainability as information institution, compromising their ability to deliver quality services.

This study aims to examine Big Data and the management of libraries in the era of the Fourth Industrial Revolution and its implications for policymakers in Nigeria.

A qualitative methodology was used, involving the administration of open-ended questionnaires to librarians from six selected federal universities located in Southwest Nigeria.

The findings of this research highlight that a significant proportion of librarians are well-acquainted with the relevance of big data and its potential to positively revolutionize library services. Librarians generally express favorable opinions concerning the relevance of big data, acknowledging its capacity to enhance decision-making, optimize services and deliver personalized user experiences.

This study exclusively focuses on the Nigerian context, overlooking insights from other African countries. As a result, it may not be possible to generalize the study’s findings to the broader African library community.

To the best of the authors’ knowledge, this study is unique because the paper reported that librarians generally express favorable opinions concerning the relevance of big data, acknowledging its capacity to enhance decision-making, optimize services and deliver personalized user experiences.

This study addresses the need for a theory-guided, rich, descriptive account of research data repositories' (RDRs) understanding of data quality and the structures of their data quality assurance (DQA) activities. Its findings can help develop operational DQA models and best practice guides and identify opportunities for innovation in the DQA activities.

The study analyzed 122 data repositories' applications for the Core Trustworthy Data Repositories, interview transcripts of 32 curators and repository managers and data curation-related webpages of their repository websites. The combined dataset represented 146 unique RDRs. The study was guided by a theoretical framework comprising activity theory and an information quality evaluation framework.

The study provided a theory-based examination of the DQA practices of RDRs summarized as a conceptual model. The authors identified three DQA activities: evaluation, intervention and communication and their structures, including activity motivations, roles played and mediating tools and rules and standards. When defining data quality, study participants went beyond the traditional definition of data quality and referenced seven facets of ethical and effective information systems in addition to data quality. Furthermore, the participants and RDRs referenced 13 dimensions in their DQA models. The study revealed that DQA activities were prioritized by data value, level of quality, available expertise, cost and funding incentives.

The study's findings can inform the design and construction of digital research data curation infrastructure components on university campuses that aim to provide access not just to big data but trustworthy data. Communities of practice focused on repositories and archives could consider adding FAIR operationalizations, extensions and metrics focused on data quality. The availability of such metrics and associated measurements can help reusers determine whether they can trust and reuse a particular dataset. The findings of this study can help to develop such data quality assessment metrics and intervention strategies in a sound and systematic way.

To the best of the authors' knowledge, this paper is the first data quality theory guided examination of DQA practices in RDRs.

This paper aims to explore the key risk factors affecting the Personnel Localization Management of international construction projects under the major public emergencies represented by the novel coronavirus pneumonia pandemic (hereinafter COVID-19) and how the public emergency affected the Personnel Localization Management from three levels: staff turnover rate, the number of different personnel, the salary and performance of workers. The paper also helps to enhance the construction enterprises' response capacity of major public emergencies and provides a comprehensive framework of optimization strategies for the Personnel Localization Management of international construction projects (hereinafter projects).

The main research method of this paper is the case study, and ten representative international construction projects are selected for case study in China construction enterprises (hereinafter CCE). And this study used the failure mode and effects analysis (FMEA) and comparative analysis to find out all potential risk factors under the COVID-19 and analyze how the epidemic affects the Personnel Localization Management of projects which based on the primary data from 10 projects obtained through in-depth interviews and the secondary data from China First Metallurgical Group and Central South Construction Group's Overseas Enterprise.

The findings show that the outbreak of the major public emergencies not only greatly increased eight risk factors but also directly led to an increase in staff turnover rate. Meanwhile, the numbers of Chinese and local managers and workers are all affected, and an increase in the number and the salary performance of local workers can be reduced, to a certain extent, to the cost-to-output ratio of the projects. The findings would help construction enterprises better cope with Personnel Localization Management and enhance the response capacity of major public emergencies.

This study will broaden researchers' horizons regarding “Personnel Localization Management under major public emergencies” and “risk factors of Personnel Localization Management in an international context.” Furthermore, construction enterprises looking for a better mechanism of Personnel Localization Management can benefit from research findings and lessons learned from the authors' case study during or before an outbreak of major public emergency. Lastly, the framework of optimization strategies for Personnel Localization Management can be used both for research purposes and practice issues in international construction projects.

The findings from the authors' case study offer the direction for international construction enterprises in China and other countries to formulate effective measures, strengthen overseas business and establish a crisis management mechanism for Personnel Localization Management under major public emergencies, and the findings provide emergency plans for projects to improve the public crisis handling capacity and respond to major public emergencies such as the COVID-19.

This study analyzes the impact of the COVID-19 on the Personnel Localization Management of international construction projects from the perspective of personnel. This study provides a theoretical reference for the international construction industry to actively respond to major public emergencies. Besides, the research is conducive to improving the emergency response mechanism in the construction industry, and further promoting the high-quality and globalized development of international construction.

This study provides other researchers with a comprehensive understanding of the risk factors affecting the Personnel Localization Management of projects under the COVID-19 and insight for further research on localization management, risk management, and project management.

This research has been taken up by the human resource center of organization X, for designing a curriculum for a training course named “Basic Computer Application”, by optimizing topics and finalizing teaching strategies, based on needs and expectations collected from past and prospective training participants from different ranks of employees of X. The study aims to discuss this issue.

The research strategy adopted is based on a survey conducted using a specially designed questionnaire. The questionnaire was circulated to 256 personnel selected randomly having computer backgrounds as well as non-computer backgrounds, who had either attended past batches of the same training course or attended different training courses. The data thus collected was processed using VOC Table and the affinity diagram and subsequently fed into the house of quality (HOQ) for obtaining desired output.

The study has identified and optimized topics for the course, based on employee needs/wants, using the two-stage QFD approach. After delivering the course with an optimized curriculum and teaching strategy, it is observed that the overall participant satisfaction performance of the course has increased from 3 to 4.6, which is higher than the goal set at 4. This indicates an overall enhancement in the satisfaction of participants with the delivery of the new improved course curriculum.

As indicated by the survey findings, the competence level of personnel with computer backgrounds is higher than that of personnel without computer backgrounds, which would result in different design considerations while constructing QFDs for these two entirely different groups of participants. This study has been limited to the course curriculum design for personnel with non-computer backgrounds only. The curriculum design for personnel with computer backgrounds will be addressed separately, in a future study.

This is an original study conducted on randomly selected employees across the country from among personnel working for different establishments of organization X. The approach taken in this study for optimizing a course curriculum is unique in the way that it uses a two-stage QFD, which is traditionally used for the design of a product, its components, and the subsequent manufacturing process. This study has employed a planning matrix that incorporated participant-given ratings for each individual need and also participant-decided benchmarking ratings of other similar courses. Estimation of final target has been done by factoring in participants' competence ratings for each individual topic, for a more truthful representation of participant opinion on the final output. This study has also adopted a unique approach of considering only top 80% (in terms of frequency of occurrence) of total responses while calculating weighted averages, instead of calculating the mean value of all data points. In this way, only the significant contributors have been considered while analyzing data.

This paper aims to examine the influence of big data (BD) on human resource management (HRM). It defines how these data can be a useful tool in the decision-making process of companies’ human resources to obtain a sustainable competitive advantage.

This paper emphasizes the need to develop a holistic approach to emphasize these relations. Starting from these observations, the document proposes empirical research employing Eurostat data to test the benefits of BD in HRM decisions that optimize the relationship between training, productivity, and well-being.

The findings estimate HRM decisions and their impact in a broader macroeconomic and microeconomic perspective.

BD research is emerging as a crucial discipline in human resources. To overcome this problem, the paper develops an analysis of the literature on cleaner production and sustainability context; it creates a conceptual framework to clarify whether the existing studies consider the growing intensity of BD on human resources.

This study aims to investigate the impact of human resource investment in internal controls (hereinafter, IC personnel) on managers’ goodwill impairment decisions.

The authors use the ratio of IC personnel to the number of employees in the firm and the average work experience of IC personnel as quantitative and qualitative measures for IC personnel, respectively.

The authors find that the relationship between the likelihood of impairment and the expected impairment is not associated with the ratio of IC personnel. However, the average experience of IC personnel increases the likelihood that a company will record an impairment when there are market and financial indicators of impairment. The findings suggest that the effectiveness of IC is determined by practical proficiency rather than size. Furthermore, our analyses demonstrate that the greater the experience of the IC personnel in the accounting/finance or IT departments, the more likely the manager will record an expected impairment. Overall, our findings emphasize the importance of IC personnel expertise to enhance the effectiveness of IC for financial reporting.

Using unique data available only in Korea, to the best of the authors’ knowledge, this is the first study to show the effect of human resource investment in IC on goodwill impairment.

Assess the realistic impacts of implementing an Radio Frequency Identification (RFID)/Internet of Things (IoT) uniforms’ distribution system for managing medical personnel’s scrubs in operating rooms. The authors use a hybrid simulation framework to address the following objectives and challenges: a) reduce and control operating rooms’ level of inventory; b) stabilize scrubs’ demand and c) improve infection control and prevention of cross-contamination (through scrubs over manipulation and hoarding).

The authors adopt a Design Science approach. This methodological approach is used to design, develop, create and evaluate information technology “artifacts” (e.g. constructs, models, methods and instantiations) intended to solve organizational problems and make research contributions (Peffers et al., 2007). More specifically, the authors follow the Design Science Research Methodology process model which includes six steps: problem identification and motivation, definition of the objectives for a solution, design and development, demonstration, evaluation, and communication.

To assess the realistic impacts of implementing an RFID-IoT uniforms’ distribution system for managing medical personnel’s scrubs in operating rooms, the authors adopted a design science approach and initiated the research by documenting the business case and reviewed the existing literature to build a comparative analysis of existing uniforms’ distribution systems. The authors used a hybrid simulation model to assess the impact of three business cases: present mode of operation, implementing smart shelves or the smart distributors. The authors show that smart dispensers allow a greater control on scrubs’ utilization while eliminating the cross-contamination of the medical personnel.

Through this research study, the authors provide hospitals’ managers a scientific support for uniforms’ (scrubs) distribution process improvement. The authors use a hybrid simulation model to compare innovative solutions for uniforms’ distribution systems in the form of “smart cabinets” supported by Radio Frequency Identification (RFID)/Internet of Things (IoT) technologies and choose the most appropriate design for the hospital to meet two main challenges: a) inefficiency of uniform replenishment-distribution system and b) noncompliancy with infection control regulations caused by the distribution system.

From a methodological perspective, this paper addresses concerns from researchers calling quantitative research methods and using case-based research strategy to address IoT issues and assess the system in practice. From a broader point of view, this work confirms the predominant interest of RFID-IoT research work in the arena of supply chain management and logistics as the technology is used for tracking purpose and for monitoring applications. It is also one response to the research community suggesting that “hospitals should evaluate the medical effectiveness of the new technologies as well as the cost before adoption”.

This study aims to examine the necessity effects of big data analytics capabilities (BDAC) on decision-making performance (DMP), particularly in the public sector.

The authors used the combined methods of partial least square structural equation modeling (PLS-SEM) and necessary condition analysis (NCA) to test the hypothesized relationships.

The findings show that the presence of all three BDAC (infrastructure, management and personnel) is significant and necessary to achieve higher levels of DMP. Specifically, the results revealed big data management capabilities to be of higher necessity to achieve the highest possible DMP. The findings provide public-sector practitioners with insights to support the development of their BDAC.

Time-sensitive domains such as the public sector require insight and quality decision-making to create public value and achieve competitive advantage. This study examined BDAC in light of the combined methods of (PLS-SEM) and NCA to test the hypothesized relationships in the public sector context.

This paper aims to increase understanding of pertinent exogenous and endogenous antecedents that can reduce data privacy breaches.

A cross-sectional survey was used to source participants' perceptions of relevant exogenous and endogenous antecedents developed from the Antecedents-Privacy Concerns-Outcomes (APCO) model and Social Cognitive Theory. A research model was proposed and tested with empirical data collected from 213 participants based in Canada.

The exogenous factors of external privacy training and external privacy self-assessment tool significantly and positively impact the study's endogenous factors of individual privacy awareness, organizational resources allocated to privacy concerns, and group behavior concerning privacy laws. Further, the proximal determinants of data privacy breaches (dependent construct) are negatively influenced by individual privacy awareness, group behavior related to privacy laws, and organizational resources allocated to privacy concerns. The endogenous factors fully mediated the relationships between the exogenous factors and the dependent construct.

This study contributes to the budding data privacy breach literature by highlighting the impacts of personal and environmental factors in the discourse.

The results offer management insights on mitigating data privacy breach incidents arising from employees' actions. Roles of external privacy training and privacy self-assessment tools are signified.

Antecedents of data privacy breaches have been underexplored. This paper is among the first to elucidate the roles of select exogenous and endogenous antecedents encompassing personal and environmental imperatives on data privacy breaches.