The preferences of Chinese LIS journal articles in citing works outside the discipline

2018 ◽  
Vol 74 (1) ◽  
pp. 99-118 ◽  
Author(s):  
Chuanfu Chen ◽  
Qiao Li ◽  
Zhiqing Deng ◽  
Kuei Chiu ◽  
Ping Wang
Keyword(s):  
Information Science ◽  
Interdisciplinary Collaboration ◽  
Academic Community ◽  
Machine Learning Techniques ◽  
Journal Articles ◽  
Content Type ◽  
Learning Techniques ◽  
Faculty Advancement ◽  
The Impact ◽  
Practice Community

Purpose The purpose of this paper is to understand how Chinese library and information science (LIS) journal articles cite works from outside the discipline (WOD) to identify the impact of knowledge import from outside the discipline on LIS development. Design/methodology/approach This paper explores the Chinese LIS’ preferences in citing WOD by employing bibliometrics and machine learning techniques. Findings Chinese LIS citations to WOD account for 29.69 percent of all citations, and they rise over time. Computer science, education and communication are the most frequently cited disciplines. Under the categorization of Biglan model, Chinese LIS prefers to cite WOD from soft science, applied science or nonlife science. In terms of community affiliation, the cited authors are mostly from the academic community, but rarely from the practice community. Mass media has always been a citation source that is hard to ignore. There is a strong interest of Chinese LIS in citing emerging topics. Practical implications This paper can be implemented in the reformulation of Chinese LIS knowledge system, the promotion of interdisciplinary collaboration, the development of LIS library collection and faculty advancement. It may also be used as a reference to develop strategies for the global LIS. Originality/value This paper fills the research gap in analyzing citations to WOD from Chinese LIS articles and their impacts on LIS, and recommends that Chinese LIS should emphasize on knowledge both on technology and people as well as knowledge from the practice community, cooperate with partners from other fields, thus to produce knowledge meeting the demands from library and information practice as well as users.

Demonstrating personal stature: some strategies for the LIS higher doctoral candidate

2014 ◽  
Vol 63 (8/9) ◽  
pp. 590-605
Author(s):  
Andrew K. Shenton
Keyword(s):  
Information Science ◽  
Library And Information Science ◽  
Journal Articles ◽  
Content Type ◽  
Doctoral Candidate ◽  
Unique Experience ◽  
The Impact ◽  
Doctoral Candidates ◽  
Made In

Purpose – The paper aims to explore the approaches that may be used by library and information science (LIS) higher doctoral candidates when preparing their submissions, especially in terms of highlighting the quality of their publications and the impact they have made. Design/methodology/approach – The methods discussed are those that were considered – and often actually used – by the author when assembling his own submission. Frequent references are made in the paper to pertinent literature on research and to British universities’ regulations on higher doctorates. Findings – The author warns against the tendency of applicants to concentrate too heavily on citation data. Although such statistics are undoubtedly important, a more convincing case for being awarded a higher doctorate may be made by drawing on a variety of sources of evidence, by no means all of which will be quantitative. Research limitations/implications – The paper is based on the experiences of one individual, i.e. the author, and consequently the perspective is narrower than would have been the case had it been written by a team of academics, all of whom had prepared their own higher doctoral applications, with each bringing their own unique experience to bear. Practical implications – The article is wholly practical in its focus; it covers a range of issues and offers realistic guidelines that should be considered by applicants. Originality/value – Published advice for the higher doctoral candidate is currently extremely limited. It would appear that no significant books or journal articles offer any support to scholars seeking the qualification. This paper has been written to help plug that gap.

scholarly journals On predicting academic performance with process mining in learning analytics

2017 ◽  
Vol 10 (2) ◽  
pp. 160-176 ◽  
Author(s):  
Rahila Umer ◽  
Teo Susnjak ◽  
Anuradha Mathrani ◽  
Suriadi Suriadi
Keyword(s):  
Machine Learning ◽  
Process Mining ◽  
Learning Experience ◽  
Dropout Rate ◽  
Data Driven ◽  
Machine Learning Techniques ◽  
Content Type ◽  
Machine Learning Classification ◽  
Learning Techniques ◽  
The Impact

Purpose The purpose of this paper is to propose a process mining approach to help in making early predictions to improve students’ learning experience in massive open online courses (MOOCs). It investigates the impact of various machine learning techniques in combination with process mining features to measure effectiveness of these techniques. Design/methodology/approach Student’s data (e.g. assessment grades, demographic information) and weekly interaction data based on event logs (e.g. video lecture interaction, solution submission time, time spent weekly) have guided this design. This study evaluates four machine learning classification techniques used in the literature (logistic regression (LR), Naïve Bayes (NB), random forest (RF) and K-nearest neighbor) to monitor weekly progression of students’ performance and to predict their overall performance outcome. Two data sets – one, with traditional features and second, with features obtained from process conformance testing – have been used. Findings The results show that techniques used in the study are able to make predictions on the performance of students. Overall accuracy (F1-score, area under curve) of machine learning techniques can be improved by integrating process mining features with standard features. Specifically, the use of LR and NB classifiers outperforms other techniques in a statistical significant way. Practical implications Although MOOCs provide a platform for learning in highly scalable and flexible manner, they are prone to early dropout and low completion rate. This study outlines a data-driven approach to improve students’ learning experience and decrease the dropout rate. Social implications Early predictions based on individual’s participation can help educators provide support to students who are struggling in the course. Originality/value This study outlines the innovative use of process mining techniques in education data mining to help educators gather data-driven insight on student performances in the enrolled courses.

Resource-sharing through an inter-institutional repository

2015 ◽  
Vol 33 (4) ◽  
pp. 730-748 ◽  
Author(s):  
A Abrizah ◽  
Mohd Hilmi ◽  
Norliya Ahmad Kassim
Keyword(s):  
Resource Sharing ◽  
Information Science ◽  
Research Output ◽  
Academic Community ◽  
Open Access Publishing ◽  
Institutional Repository ◽  
Teaching Resources ◽  
Content Type ◽  
Institutional Repositories ◽  
Digital Repositories

Purpose – The purpose of this paper is to be concerned with the motivations and resistance among an institutional repository (IR) stakeholder – the Library and Information Science (LIS) academicians – with respect to Green Road open access publishing in an inter-institutional repository. Design/methodology/approach – The answers were identified from 47 LIS faculty from three library schools in Malaysia who reported awareness of what an IR is and having had experience in contributing resources to digital repositories. Data were collected using survey and interviews. Findings – The results highlighted the LIS faculty on their motivation to share their intellectual profile, research and teaching resources in an inter-institutional repositories and why the reluctance in contributing. The study reveals that the major motivation to share resources for those practicing self-archiving is related to performance expectancy, social influence, visible and authoritative advantage, career benefit and quality work. The major resistance to share scholarly research output through self-archiving in institutional repositories for those practicing self-archiving is concern on plagiarism, time and effort, technical infrastructure, lack of self-efficacy and insularity. Practical implications – Knowing what conditions predict motivation and resistance to contribute to IRs would allow IR administrators to ensure greater and more effective participation in resource-sharing among LIS academic community. If this resistance is addressed aptly, IRs can be of real benefit to their teaching, scholarship, collaborations, and publishing and to the community that they serve. Originality/value – The first study that has explored the ways LIS academics respond to a situation where knowledge sharing in academe has now been made mandatory through an IR and what makes them resist to do so.

Feasibility study of automatically performing the concrete delivery dispatching through machine learning techniques

2015 ◽  
Vol 22 (5) ◽  
pp. 573-590 ◽  
Author(s):  
Mojtaba Maghrebi ◽  
Claude Sammut ◽  
S. Travis Waller
Keyword(s):  
Machine Learning ◽  
Human Resources ◽  
Design Methodology ◽  
Machine Learning Techniques ◽  
Mixing Process ◽  
Content Type ◽  
Practical Solution ◽  
Learning Techniques ◽  
Ready Mixed Concrete ◽  
Practical Implications

Purpose – The purpose of this paper is to study the implementation of machine learning (ML) techniques in order to automatically measure the feasibility of performing ready mixed concrete (RMC) dispatching jobs. Design/methodology/approach – Six ML techniques were selected and tested on data that was extracted from a developed simulation model and answered by a human expert. Findings – The results show that the performance of most of selected algorithms were the same and achieved an accuracy of around 80 per cent in terms of accuracy for the examined cases. Practical implications – This approach can be applied in practice to match experts’ decisions. Originality/value – In this paper the feasibility of handling complex concrete delivery problems by ML techniques is studied. Currently, most of the concrete mixing process is done by machines. However, RMC dispatching still relies on human resources to complete many tasks. In this paper the authors are addressing to reconstruct experts’ decisions as only practical solution.

Association between mass collaboration and knowledge management: a case ofJordan companies

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hosam Alden Riyadh ◽  
Laith T. Khrais ◽  
Salsabila Aisyah Alfaiza ◽  
Abdulsatar Abduljabbar Sultan
Keyword(s):  
Knowledge Management ◽  
Organizational Structure ◽  
Structural Equation ◽  
Manufacturing Sector ◽  
Equation Modeling ◽  
Content Type ◽  
Mass Collaboration ◽  
Organization Level ◽  
Learning Techniques ◽  
The Impact

Purpose The key purpose of this research paper was to identify the association between mass collaboration and knowledge management in the context of Jordanian companies. Apart from that, this study also aims to examine the moderating effect of trust and leadership on the association between mass collaboration and knowledge management. Design/methodology/approach In this study, the researcher has followed theprimary quantitative method. For data collection, the researcher has conducted a survey questionnaire, whereas the sample was based on 323 participants from the manufacturing sector of Jordan specifically for data analysis; the technique of structural equation modeling was implemented. Findings All the independent variables, including organizational structure, adoptedtechnologies in mass collaboration and collaborative learning techniques, have a significantimpact on knowledge management and leadership. Moreover, leadership was also found to be significantly moderating the association between adopted technologies in mass collaboration and knowledge management. Similarly, trust also significantly moderates the association of organizational structure and adopted technologies in mass collaboration significantly with knowledge management. Research limitations/implications All study respondents were from Jordan, which might limit the generalizability of the findings. The researchers also invited for more researchers in the incorporation of the time sequence in the proposed causal relations and in the organization level through which mass collaboration and knowledge management. Originality/value This study promises to make a valuable contribution to the existing literature, as there was a lack of evidence in the previous studies regarding the impact of mass collaboration on knowledge management within the context of Jordan.

Coping mechanisms of Philippine tourism and hospitality family businesses during the COVID-19 pandemic: a non-parametric approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Andrea Santiago ◽  
Fernando Martin Roxas ◽  
John Paolo Rivera ◽  
Eylla Laire Gutierrez
Keyword(s):  
Rural Areas ◽  
Family Firms ◽  
The Philippines ◽  
Academic Community ◽  
Family Businesses ◽  
Content Type ◽  
Family Enterprises ◽  
Tourism And Hospitality ◽  
The Impact ◽  
Non Parametric

PurposeFamily businesses (FB), mostly small-sized, dominate the tourism and hospitality industry (THI), especially in the rural areas. While many would have been used to the impact of demand seasonality, it is unknown how these businesses would have survived through the restrictions imposed to contain the coronavirus disease 2019 (COVID-19) pandemic as compared to non-family business (NFB) counterparts. This study aims to determine if there were differences on how family and non-family enterprises in the THI coped with government restrictions.Design/methodology/approachBy subjecting the survey data from tourism enterprises to non-parametric techniques, the authors establish empirical evidence on similarities and differences of coping strategies adopted by FBs and NFBs; their required support from government and their perceptions of a post-pandemic THI.FindingsThe analysis revealed that family-owned tourism and hospitality businesses in the Philippines tended to collaborate with other businesses to manage the impact of the pandemic restrictions. Since they hired more seasonal workers prior to the restrictions, they tended to avoid hiring workers during the restricted period. NFBs, on the other hand, that were generally larger in size and more professionally managed with more regular employees, tended to streamline operations for greater efficiency.Research limitations/implicationsThe study relied on survey results distributed and collected online. There is an innate bias against those firms that did not have access to the survey links.Practical implicationsThe comparative study suggests that interventions to assist firms in the THI should consider the differences in firm ownership as “one size does not fit all.”Social implicationsThe study provides evidence about how environmental factors impact the operations of family firms. Thus, it provides valuable insights for both the academic community and industry practitioners.Originality/valueThis is the first study in the Philippines that was able to capture response of family and non-family firms in the THI during the COVID-19 lockdown.

Rotten web citations cited in scholarly journals: use of time travel for retrieval

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
B. Niveditha ◽  
Mallinath Kumbar ◽  
B.T. Sampath Kumar
Keyword(s):  
Media Studies ◽  
Information Science ◽  
Editorial Staff ◽  
Time Travel ◽  
Reference List ◽  
Journal Articles ◽  
Scholarly Journals ◽  
Content Type ◽  
Use Of Time ◽  
Research Findings

PurposeThe present study compares the use of web citations as references in leading scholarly journals in Library and Information Science (LIS) and Communication and Media Studies (CMS). A total of 20 journals (each 10 from LIS and CMS) were selected based on the publishing history and reputation published between 2008 and 2017.Design/methodology/approachThe present study compares the use of web citations as references in leading scholarly journals in LIS and CMS. A PHP script was used to crawl the Uniform Resource Locators (URLs) collected from the reference list. A total of 12,251 articles were downloaded and 555,428 references were extracted. Of the 555,428 references, 102,718 web citations were checked for their accessibility.FindingsThe research findings indicated that 76.90% URLs from LIS journals and 84.32% URLs from Communication and Media Studies journals were accessible and others were rotten. The majority of errors were due to HTTP 404 error code (not found) in both the disciplines. The study also tried to retrieve the rotten URLs through Time Travel, which revived 61.76% rotten URLs in LIS journal articles and 65.46% in CMS journal articles.Originality/valueThis is an in-depth and comprehensive comparative study on the availability of web citations in LIS and CMS journals articles spanning a period of 10 years. The findings of the study will be helpful to authors, publishers, and editorial staff to ensure that web citations will be accessible in the future.

Information science’s contributions towards emerging open evaluation practices

2019 ◽  
Vol 20 (1) ◽  
pp. 2-16
Author(s):  
Leonor Gaspar Pinto ◽  
Paula Ochôa
Keyword(s):  
Information Science ◽  
Stakeholder Participation ◽  
Open Science ◽  
General Tendency ◽  
Sustainability Transitions ◽  
Transdisciplinary Approach ◽  
Content Type ◽  
Research On Evaluation ◽  
Social Sciences And Humanities ◽  
The Impact

Purpose The purpose of this paper is to discuss emerging practices in open evaluation, namely, the concept of co-evaluation and how research on evaluation developed within information science can contribute to enhance stakeholders and citizens’ involvement in open science. Design/methodology/approach A meta-evaluative and transdisciplinary approach – directed toward the intersection between information science, evaluation, competences management, sustainability transitions management and participatory methodologies – provided the basis for the identification and subsequent reflection on the levels of stakeholder participation embedded into ISO 16439’s (2014) methods for assessing the impact of libraries and on the domains and competences to be mobilized for (co)evaluation. The contributions of Engaged 2020 Action Catalogue, as well as several taxonomies of evaluator competences and the Council of Europe’s (2016) conceptual model of competences for a democratic culture were particularly relevant for this (re)construction process. Findings Two results of the line of research carried out since 2012 at the Faculty of Social Sciences and Humanities of the Universidade NOVA de Lisboa (Portugal) can significantly contribute to improve stakeholders’ participation in Open Science: ISO 16439’s systematization of methods and procedures for assessing the impact of libraries and the (co-)evaluation competency framework. Originality/value This paper presents the transdisciplinary concept of co-evaluation and examines the current epistemological challenges to science by analyzing the general tendency to openness through the lens of research on evaluation and participatory methods developed within information science.

University students involved in a sustainable world: assessing sustainable consumption in Spain

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Clara Margaça ◽  
Brizeida Hernández Sánchez ◽  
José Carlos Sánchez-García
Keyword(s):  
University Students ◽  
Sustainable Consumption ◽  
Academic Community ◽  
Validity And Reliability ◽  
Content Type ◽  
Agenda 2030 ◽  
Original Proposal ◽  
Use Of Resources ◽  
Responsible Consumption ◽  
The Impact

Purpose To achieve sustainable development to protect the environment and society, an increasing number of scholars have conducted in-depth research on sustainable and responsible consumption behaviors. The outputs demonstrate that consumers are increasingly concerned and aware of the issues associated with the excessive use of resources. The purpose of this paper is to analyze the validity and reliability of the Sustainable Consumption Scale (SC-S) in the Spanish context. Design/methodology/approach The adaptation of SC-S to Spanish was carried out in accordance with international methodological standards. The Spanish version of this scale was applied empirically to the research sample was composed of 962 university students (49.1% male and 50.9% female) from 54 Universities in 15 regions of Spain that participated in the study. Findings The analyses carried out to verify the psychometric properties retained 16 items from the original proposal, grouped equally in three factors: Cognitive – six items; Affective – seven items; and Conative – four items. The scale presented adequate adjustment indexes, as well as optimal values of the different measures of reliability, recommended by the literature. Originality/value This instrument can be used by the Spanish academic community, which will contribute to the assessment and prediction regarding a sustainable consumption attitude. From these screenings, it will be also possible to understand the impact and development of the objectives outlined by Agenda 2030.

scholarly journals Machine learning analysis of lifeguard flag decisions and recorded rescues

2019 ◽  
Vol 19 (11) ◽  
pp. 2541-2549
Author(s):  
Chris Houser ◽  
Jacob Lehner ◽  
Nathan Cherry ◽  
Phil Wernette
Keyword(s):  
Machine Learning ◽  
The United States ◽  
Machine Learning Techniques ◽  
Public Health Issue ◽  
Rip Currents ◽  
Effective Strategies ◽  
Wave Forcing ◽  
Learning Techniques ◽  
Yellow Flag ◽  
The Impact

Abstract. Rip currents and other surf hazards are an emerging public health issue globally. Lifeguards, warning flags, and signs are important, and to varying degrees they are effective strategies to minimize risk to beach users. In the United States and other jurisdictions around the world, lifeguards use coloured flags (green, yellow, and red) to indicate whether the danger posed by the surf and rip hazard is low, moderate, or high respectively. The choice of flag depends on the lifeguard(s) monitoring the changing surf conditions along the beach and over the course of the day using both regional surf forecasts and careful observation. There is a potential that the chosen flag is not consistent with the beach user perception of the risk, which may increase the potential for rescues or drownings. In this study, machine learning is used to determine the potential for error in the flags used at Pensacola Beach and the impact of that error on the number of rescues. Results of a decision tree analysis indicate that the colour flag chosen by the lifeguards was different from what the model predicted for 35 % of days between 2004 and 2008 (n=396/1125). Days when there is a difference between the predicted and posted flag colour represent only 17 % of all rescue days, but those days are associated with ∼60 % of all rescues between 2004 and 2008. Further analysis reveals that the largest number of rescue days and total number of rescues are associated with days where the flag deployed over-estimated the surf and hazard risk, such as a red or yellow flag flying when the model predicted a green flag would be more appropriate based on the wind and wave forcing alone. While it is possible that the lifeguards were overly cautious, it is argued that they most likely identified a rip forced by a transverse-bar and rip morphology common at the study site. Regardless, the results suggest that beach users may be discounting lifeguard warnings if the flag colour is not consistent with how they perceive the surf hazard or the regional forecast. Results suggest that machine learning techniques have the potential to support lifeguards and thereby reduce the number of rescues and drownings.

Sign in / Sign up

Export Citation Format

Share Document