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This systematic literature review aims to elaborate on the research progress and features of information source preferences to help other researchers attain a more comprehensive understanding of the field.

Following a systematic review protocol, 139 research articles from 11 academic databases were analyzed.

Overall, five separate results were obtained: first, information source horizon theory is the main theoretical foundation of information source preferences research, while other theories have been applied less. Second, information source preference research has strong context sensitivity and involves health, work, consumption, learning, survival and development and emergencies. Third, preference criteria can be summarized into three categories: information characteristics, user characteristics, needs characteristics and corresponding specific criteria. Fourth, information source preferences are influenced by both internal and external factors, including five specific aspects, namely demographics, the user's cognition, the user's affection, capital and contextual factors. Fifth, this field is dominated by quantitative methods and an information horizon mapping method could be applied more.

This study is the first to reveal the general picture of information source preferences. It also elaborates on the characteristics of this field and presents potential development directions.

This paper discusses data-collection strategies that use digitized historical newspaper archives to study social conflicts and social movements from a global and historical perspective focusing on nationalist movements. I present an analysis of State-Seeking Nationalist Movements (SSNMs) dataset I, which includes news articles reporting on state-seeking activities throughout the world from 1804 to 2013 using the New York Times and the Guardian/Observer. In discussing this new source of data and its relative value, I explain the various benefits and challenges involved with using digitized historical newspaper archives for world-historical analysis of social movements. I also introduce strategies that can be used to detect and minimize some potential sources of bias. I demonstrate the utility of the strategies introduced in this paper by assessing the reliability of the SSNM dataset I and by comparing it to alternative datasets. The analysis presented in the paper also compares the labor-intensive manual data-coding strategies to automated approaches. In doing so, it explains why labor-intensive manual coding strategies will continue to be an invaluable tool for world-historical sociologists in a world of big data.

The occurrence of COVID-19 has impacted the wide-reaching dimensions of manufacturing, materials, procurement, management, etc., and has loaded disruptions in the wide range of supply chain (SC) activities. The impact of COVID-19 has twisted supplier performance and influenced stakeholders’ thinking towards selecting supplier sources and making strategic sourcing decision for convinced arrangement of construction management (CM) resources. Nowadays, suppliers are intently evaluated by stakeholders in post-COVID-19 phase to induce agile availability of CM resources. Accordingly, this paper aims to demonstrate competent CM dimensions under post COVID-19 scenario for ease managing construction projects by the stakeholders.

The authors have implicated Grey Sets Theory along with decision-making trial and evaluation laboratory (DEMATEL) technique for understanding significant outcomes. Varieties of diverse decision aspects responsible for strategically influencing supplier sourcing decision is projected under post COVID-19 scenario for handling construction projects by the stakeholders.

This study investigated sustainable construction management dimensions (SCMD) at the stage of resource deliveries and client aspirations under post COVID-19 situation. The study demonstrated “Lead time” as the most crucial, “Product Range” as the second and “Customers dealings and relationship” as the third crucial aspect considering by the stakeholders for selecting supplier sources based on the attainment of performance score of 0.1338, 0.1273 and 0.1268, respectively. It is found that high lead time stimulates the stakeholders to divert their orders to other competent supplier sources holding a low degree of lead time as compared.

The present study rollovers its existence by serving critical thinking, conceptual modelling, criteria identification and evaluation under CM domain for drafting effectual strategies by the suppliers. The study investigated the impact of COVID-19 on stakeholders’ decision-making and enlisted SCMD that strategically stimulated them in choosing supplier sourcing decision.

The present study realizes the insights of stakeholders in the post COVID-19 scenario related to the supplier sources based on performance score. The study quantified sustainable supplier attribute for construction work and practices. The study analysed the expectations of the stakeholders purchasing different varieties of construction materials from supplier sources for civil works in the post COVID-19 scenario.

This paper aims to consolidate the state of research on information behaviour. Regardless of the scholarly surge on information behaviour using numerous models and extended ones, gaps still exist on the development of more pragmatic frameworks that explain and/or predict the information behaviour across different fragmented environmental situations. Therefore, this paper extends technology-organization-environment (T-O-E) framework and synthesizes different research positions into a multi-dimensional framework that assists small and medium enterprises (SMEs) to understand their information behaviour and to make informed decisions on the adoption of emerging information communication technology (EICT).

This study deployed an inductive approach; data were generated from unstructured and semi-structured interviews with 20 participants drawn purposively from Luton directories.

This study developed a more integrated framework underpinned by T-O-E framework, which helped to identify how EICT adoption is critically shaped by perceived information need, information sources selection and the factors determining information source selection.

Qualitative research is normally subjective, inductive, interpretive and limited on the sample used. However, because of the limited number of interviews used, as well as industry-specific nature of the study, the generalization of the framework and the findings will be difficult, hence, the need to test the framework on a broader population and cross-context testing.

The T-O-E framework is extended to Expectancy (T-O-E-E) to provide a more robust insight into information behaviour of SMEs from a multi-dimensional perspective. It also offers a more analytical framework for exploring critical issues identified and demonstrates the capacity to provide a reliable explanation to the findings. Further, it serves as a tool for assessing the benefits or challenges of SMEs information behaviour especially on the EICT adoption decision.

International development projects are a dominant means by which aid is distributed to countries. Over the past 70 years, the distribution of trillions of dollars of development aid has been mediated by the United Nations (UN). However, most of this aid has failed to deliver the expected outcomes for which it was assigned. Nevertheless, a significant proportion of projects can be considered successful. Despite the glaring question as to which factors contribute to the success or failure of projects, no study has comprehensively documented the relationship between procurement mechanisms invoked to deliver aid projects and project outcomes. This study aims to assess this relationship.

Leveraging network analysis methodology, this study examines the World Bank data set of over 247,000 developmental contracts worldwide granted over the past 20 years. It identifies the range of procurement practices used and interrogates their ability to deliver satisfactory project outcomes.

Eleven prevalent practices are identified covering aid projects across twelve sectors. As might be expected, Africa is the largest recipient of aid, while the Middle East is the least. Overwhelmingly, international competitive bidding (ICB) is the leading procurement procedure, both in terms of contract number and total dollar value. However, ICB does not always deliver the best outcomes, with other, more boutique approaches sometimes doing better.

The breadth of this study, encompassing such a vast data resource, and generating such a rich pool of findings will now empower researchers to take the next important step, which is to progress this study in exploring why it is that certain procurement strategies have worked for some sectors, but not others. Countries, financial institutions, the UN and construction enterprises alike will be very interested in the results.

The spectrum of outcomes identified will be of interest to academics and practitioners alike wishing to investigate further the drivers behind the results described here.

Recent studies on search-as-learning (SAL) have recognized the significance of identifying users' learning needs as they evolve for acquiring knowledge during the search process. In this study, the authors clarify the extent to which search behaviors reflect the learning outcome and foster the users' knowledge of Chinese art.

The authors conducted an exploratory-sequential mixed-methods approach using simulated work task situations to collect empirical data. The authors used two types of simulated learning tasks for topics related to painting and antique knowledge. A lot of 25 users participated in this evaluation of digital archives (DAs) at the National Palace Museum (NPM) in Taiwan. For each set of topics, a close-ended task related to lower-level learning goals and an open-ended task related to higher-level learning goals.

The learning criteria reflect changes in the users' knowledge structure, revealing the SAL process. Furthermore, users achieved better task performance on the higher-level creative-learning task, which suggests that they met more learning criteria, exhibited a greater variety of search patterns when exploring the topics via interaction with various sources. Finally, there is a close relationship between creative-learning tasks, prior knowledge, keyword search actions and learning outcomes.

The authors discuss implications with respect to the design of DAs in practice and contributions to the body of SAL knowledge in DAs of online museums. For future reference, the authors provide implications for the development of learning measures from the perspective of user search behavior with associated learning outcomes in the context of DAs.

The purpose of this paper is to propose a novel data-driven approach for predicting energy performance of buildings that can address the scarcity of quality data, and consider the dynamic nature of building systems.

This paper proposes a reinforcing machine learning (ML) approach based on transfer learning (TL) to address these challenges. The proposed approach dynamically incorporates the data captured by the building management systems into the model to improve its accuracy.

It was shown that the proposed approach could improve the accuracy of the energy performance prediction compared to the conventional TL (non-reinforcing) approach by 19 percentage points in mean absolute percentage error.

The case study results confirm the practicality of the proposed approach and show that it outperforms the standard ML approach (with no transferred knowledge) when little data is available.

This approach contributes to the body of knowledge by addressing the limited data availability in the building sector using TL; and accounting for the dynamics of buildings’ energy performance by the reinforcing architecture. The proposed approach is implemented in a case study project based in London, UK.

The purpose of this study is to explore the association between select human resource management practices and employee performance in academic libraries in India.

The current study uses the quantitative method of research. Partial least squares-structural equation modelling (PLS-SEM) was used to analyse the results. The current study uses a cross-sectional approach by using a convenient sampling method. The sample size of the study was 163, which was adequate for conducting PLS-SEM analysis.

The study found a significant positive correlation between human resource management practices and employee performance in academic libraries. This suggests that the implementation of effective human resource management practices has a beneficial impact on various aspects of employee performance.

The study’s cross-sectional design may limit the ability to establish causality or determine the direction of the relationship between human resource management practices and employee performance. The study may have limitations regarding the sample size and its representativeness. If the sample is small or limited to specific academic libraries in India, it may not be possible to generalise the findings to a broader population of academic libraries in the country or to libraries in other regions or countries.

The study has practical implications for academic libraries in India. By recognising the significant correlation between human resource management practices and employee performance, libraries can prioritise the implementation of effective human resource management strategies. This includes aligning human resources practices with organisational goals, focusing on employee development and engagement and adopting best practices in recruitment, training and performance management.

This study can have broader social implications by promoting a supportive and productive work culture that positively impacts the academic library community.

The paper focuses on a quite important and largely unexplored area of human resource management within the academic libraries sector.

The concept of green urban mobility has emerged as one of the best approaches for promoting environmental-friendly transportation in local communities. Green urban mobility aims to reshape public transportation system and enhance mobility, with emphasis on deploying digital technologies to promote sustainable public transportation. Therefore, this study aims to analyze existing public transportation policies by exploring how local communities can facilitate green urban mobility by developing a sociotechnical urban-based mobility model highlighting key factors that impact regions transitioning toward sustainable transportation.

This study investigates “the role of data for green urban mobility policies toward sustainable public transportation in local communities” in the form of a systematic literature review and insights from Norway. Secondary data from the literature and qualitative analysis of the national transport plan document was descriptively analyzed to provide inference.

Findings from this study provides specific measures and recommendations as actions for achieving a national green mobility practice. More important, findings from this study offers evidence from the Norwegian context to support decision-makers and stakeholders on how sustainable public transportation can be achieved in local communities. In addition, findings present data-driven initiatives being put in place to promote green urban mobility to decrease the footprint from public transportation in local municipalities.

This study provides green mobility policies as mechanisms to be used to achieve a sustainable public transportation in local communities. Practically, this study advocates for the use of data to support green urban mobility for transport providers, businesses and municipalities administration by analyzing and forecasting mobility demand and supply in terms of route, cost, time, network connection and mode choice.

This study provides factors that would promote public and nonmotorized transportation and also aid toward achieving a national green urban mobility strategy. Socially, findings from this study provides evidence on specific green urban mobility measures to be adopted by stakeholders in local communities.

This study presents a sociotechnical urban-based mobility model that is positioned between the intersection of “human behavior” and “infrastructural design” grounded on the factors that influence green urban mobility policies for local communities transiting to a sustainable public transportation. Also, this study explores key factors that may influence green urban mobility policies for local communities toward achieving a more sustainable public transportation leading to a more inclusive, equitable and accessible urban environment.