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The aim of this paper is to present an online framework for building a domain taxonomy, called TaxoLine, from Web documents automatically.

TaxoLine proposes an innovative methodology that combines frequency and conditional mutual information to improve the quality of the domain taxonomy. The system also includes a set of mechanisms that improve the execution time needed to build the ontology.

The performance of the TaxoLine framework was applied to nine different financial corpora. The generated taxonomies are evaluated against a gold-standard ontology and are compared to state-of-the-art ontology learning methods.

The experimental results show that TaxoLine produces high precision and recall for both concept and relation extraction than well-known ontology learning algorithms. Furthermore, it also shows promising results in terms of execution time needed to build the domain taxonomy.

Although interdisciplinary research is an increasing trend in scientific funding projects, they are suffering from a lower probability of being funded. The purpose of this paper is to analyze the current situation on successful case of funding application and provides suggestions on how libraries can expand services to help scientific funding application.

This paper utilizes the co-occurrences of disciplinary application codes to construct an interdisciplinary knowledge flow network. Based on 193517 sponsored projects of the National Natural Science Foundation of China, the authors study the interdisciplinary flow of knowledge and investigate the evolution of network structure using social network analysis.

Results show that the interdisciplinary knowledge flow network is not only a small-world network but also a scale-free network. Two main knowledge flow paths across scientific departments exist, showing the heterogeneity of knowledge distributions across scientific disciplines. The authors also find that if two disciplines in the same scientific department both have a wide influence to other disciplines, they are more prone to link together and create a knowledge chain.

Funding consultation currently has not occupied an advisory role either in library services or in the research team. This paper conducts a co-occurrences network analysis of interdisciplinary knowledge flow in scientific funding projects. Considering the complexity of funding application and the advantage of traditional library services on information collection, integration, and utilization, the authors conclude the possibility and necessity of embedding funding consultation in traditional library services.

This paper aims to integrate Big Data in e-government in Oman, also known as “e-Oman”, wherein Big Data might be better harnessed to tackle real-time challenges.

Besides a description of the concepts of e-government and Big Data in general, the paper underscores the dimensions of “e-Oman”. Following a qualitative approach, the paper asserts how integration of Big Data in “e-Oman” may be useful by invoking examples from four short case studies across different sectors.

The paper supports the integration of “e-Oman” and Big Data wherein besides providing smooth public services, the government is encouraged to forge inter- and intra-ministerial collaboration and public-private partnership. The paper probes through the challenges and opportunities in effecting this integration.

The paper provides a platform for the policymakers to conceive of a synchronized programme for integrating “e-Oman” and the Big Data generated by it. This integration would go a long way in building upon the economy of Oman, besides providing better public services to the individuals and businesses on a real-time basis.

The paper does throw light on the issues of privacy and confidentiality of data available with the government. There are challenges of cybercrime as well. Therefore, the paper posits that a robust fool-proof infrastructure should be instituted by the government for effecting integration of e-government and Big Data.

This paper seeks to fill the gap in extant literature which remains scant on the integration of e-government with Big Data. This is especially true in the case of Oman where not a single study has been presented to probe this issue. Given that “e-Oman” is expanding its scope over the years, this paper foresees the concomitant opportunities and challenges in the integration of Big Data in “e-Oman”.

Whereas integration of big data in “e-Oman” – the e-government face of Oman – is a significant prospect, this paper aims to underscore the challenges of privacy concerns in effecting such integration.

Providing a brief description about the concepts of e-government and big data, the paper follows a discussion on “e-Oman”. While drawing a framework for integration of big data in “e-Oman”, the paper throws light on the privacy concerns in effecting such an integration following a qualitative approach.

Integration of big data in “e-Oman” is fraught with ethical challenges in terms of privacy issues which have social implications.

While the pros of integration of big data in “e-Oman” are noteworthy, technical and administrative constraints vis-à-vis the cons of such integration need to be taken care of. It may be underlined that there is a trade-off between the norms of transparency and privacy of individuals versus the deployment of big data in “e-Oman” for effective real-time problem-solving.

Technical and administrative infrastructure needs to be robust for countering challenges of cybercrimes. Furthermore, confidentiality and privacy of individuals may be at stake; the government needs to tackle these issues.

Integration of big data in “e-Oman” needs to be probed, and this paper seeks to fill this gap. Second, the paper underscores that it is important that ethical norms are being accounted for while effecting this integration.

The acquisition of periodicals is one of the more neglected areas of practical librarianship. There is a strong tendency among library managers to leave the handling of periodicals to junior staff once the initial decision‐making on the choice of agent has been made. The manager then only hears how the system is operating when something goes drastically wrong — by which time it is usually too late.

The purpose of this study is twofold: to investigate the role of big data in firms’ co-knowledge and value creation and to understand the underlying drivers behind value creation through big data in the oil and gas industry by underscoring the role of firms’ capabilities, trends and challenges.

Following an inductive approach, semi-structured interviews were conducted with senior managers and analysts working in oil and gas companies across eight countries. The data collected from these key informants were then analysed using the qualitative data analysis software ATLAS.ti.

Value creation through big data is an important factor for enhancing performance. It has a positive impact on both tangible (organisational performance) and intangible (societal) aspects depending on the context. Oil and gas companies understand the importance of big data to creating value in their operations. However, implementing and using big data has been problematic. In this study, a framework was developed to show that factors such as the shortage of data experts, poor data quality, the risk of cyber-attacks and unsupportive organisational cultures impede its implementation and utilisation.

The findings from this study have implications for managers and executives implementing big data and creating value across various data-intensive industries. The research findings, are contextual, however, and should be applied cautiously.

This study contributes to the value creation literature in the big data context. The findings identify the key areas to be considered for the effective implementation and utilisation of big data in the oil and gas sector. This study addresses a broad but under-explored issue (i.e. knowledge creation from big data and its implementation) and strengthens the academic debate within this research stream.

Attributing blame for performance failure and credit for success is ubiquitous in organizations. These responsibility attributions can play an important role in aligning individual and organizational performance expectations, but may also exacerbate conflict in groups and organizations. Theory suggests that an actor's organizational role will affect blame and credit attributions, yet empirical work on this prediction is lacking. This article tests an organizational role approach by assessing the effect of the responsible actor's hierarchical position and whether he or she acted as an individual or as part of a group on blame and credit attributions. The study finds that in response to organizational failures and successes leadership roles attract more blame than other positions, but in contrast to previous predictions, these roles do not attract more credit than lower level roles. In addition, upper level positions tend to be assigned greater blame than credit, while lower level positions show a reversed pattern: they attract more credit than blame. Groups are less likely to be assigned blame and more likely to be credited than are individuals, and occupants in flat organizational structures are assigned higher levels of blame and credit than are occupants in taller organizational structures.

In this paper, a theoretical and applied understanding is brought to the study of acute myocardial infarction [AMI] care‐seeking behavior. The time between the onset of an AMI and the initiation of definitive medical care is presently the single most important factor impeding reduced mortality and improved morbidity from thrombolytic therapy. It is suggested that the acknowledged, yet relatively neglected, area of emotional response is a key element in understanding why individuals may delay seeking definitive health care services following the onset of AMI symptoms. Emotionally significant dimensions of the care‐seeking process and a model for intervention to reduce morbidity and mortality are presented.

This article outlines the factors Chief Executive Officers consider critical in the development of their own careers. In a study of British CEOs five major factors were identified: interpersonal influencing skills; responsibility for a business sector; a need to achieve results; early leadership experience; and width of business experience. These factors are examined and the implications for managerial work are assessed.

The main objective is to investigate the effects of antecedents of word-of-mouth (WOM) towards sustainable fashion, using the Personality Traits theory. More specifically, this study wants to examine the impact of the Big Five personality traits on social media activities, which could affect eco-friendly behaviour and environmental concerns for fashion production. This impact is influenced by the use of WOM on sustainability in the fashion industry.

The partial least squares structural equation modelling (PLS SEM) technique is used to evaluate the internal and external measurement model with a sample size of 272.

The three most active personality traits on social media are extraversion, openness to experience and agreeableness. Additionally, the active use of social media has a positive impact on the optimisation of users' eco-friendly behaviour and an increase in users' concerns for fashion production. Eco-friendly behaviour and environmental concerns for fashion production are important factors that lead to the spread of WOM.

This study contributes to the existing literature by evaluating the effects of the Big Five personality traits on using social networking and how will this improve the creation of WOM towards sustainability. This study is among the several scientific studies which combine the theory of Big Five personality traits with social networking, green behaviour and the WOM in a sustainability context.