scholarly journals Collection development or data-driven content curation? An exploratory project in Manchester

2016 ◽  
Vol 37 (4/5) ◽  
pp. 275-284 ◽  
Author(s):  
Rachel Joy Kirkwood
Keyword(s):  
Decision Making ◽  
Data Driven ◽  
Team Approach ◽  
Collection Development ◽  
Content Type ◽  
The Uk ◽  
Functional Teams ◽  
The University ◽  
University Of Manchester ◽  
Analytical Tools

Purpose – Collection development in a post-subject librarian age needs to be done differently; utilising data, metadata, analytical tools and automation more fully may offer new possibilities. The purpose of this paper is to report and evaluate an exploratory project into new techniques for collection development at the University of Manchester Library. Design/methodology/approach – The project employed a cross-team approach where a relatively large number of staff tried some innovative and experimental approaches to individual aspects of a large and complex task in a large, research-intensive university library. The overriding aim was to exploit data to support decision making and to push automation as far as possible. Findings – The quality of (meta)data remains a huge hindrance to data-driven approaches. A proper understanding of usage data is an urgent but intractable issue. Human input and relationships are still important. Data are nothing without analysis, and many librarians currently lack the data fluency to work confidently in a world of dynamic content curation. Practical implications – Librarians need both to re-skill and to change their self-identification and the philosophy that underlies it if they are to achieve confident, data fluency. Originality/value – The University of Manchester Library was one of the first libraries in the UK to make a thoroughgoing structural change from subject-based to functional teams. This paper will be of value to other libraries moving in this direction, and to those looking to make more use of data-driven decision making in collections management.

Profiling interdisciplinary accounting research: an analysis of publication descriptors in three leading journals

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lina Xu ◽  
Steven Dellaportas ◽  
Zhiqiang Yang ◽  
Sophia Ji
Keyword(s):  
Interdisciplinary Research ◽  
Environmental Accounting ◽  
Content Type ◽  
Accounting Research ◽  
Complex Process ◽  
The Uk ◽  
The University ◽  
University Of Manchester ◽  
Profiling Analysis ◽  
Practical Implications

Purpose The aim of this study is to profile interdisciplinary accounting research and the facilitating role played by researchers by probing the characteristics of published articles in three leading interdisciplinary accounting research journals, Accounting, Auditing and Accountability Journal (AAAJ); Accounting, Organizations and Society (AOS); and Critical Perspectives on Accounting (CPA). Design/methodology/approach Profiling analysis is undertaken with a broad scan of publication descriptors in AAAJ, AOS and CPA between 2005 and 2016. Profiling stems from identifying and quantifying the characteristics of interdisciplinary research, and with further analysis, infer generalisations about its content and the community of interdisciplinary researchers. Findings The published output of 1,462 articles is produced by 1,688 authors affiliated with 660 institutions in 52 countries. The two most high-ranking topics are social and environmental accounting and management accounting. The highest-ranked authors are Stephen Walker, Rob Bryer, Lee Parker and Yves Gendron. The most productive universities are the University of London, Cardiff University and the University of Manchester. The countries highly involved in interdisciplinary accounting research are the UK, USA, Australia and Canada. Research limitations/implications The data is restricted by the sample of manuscripts based on three interdisciplinary accounting research journals for the period 2005–2016 and does not consider manuscripts published in other accounting and non-accounting journals. Additionally, the process of analysing publication descriptors to generate categorised lists was a complex process that may not be replicated precisely by other researchers. Practical implications The results reported in this study can assist researchers interested in interdisciplinary research on what they may expect to read and understand. Originality/value The present study profiles interdisciplinary research in accounting to gain a picture of the elements that comprise interdisciplinarity, which, at present, is without empirical investigation.

scholarly journals The direct library supply of individual textbooks to students: examining the value proposition

2017 ◽  
Vol 118 (11/12) ◽  
pp. 629-641 ◽  
Author(s):  
Dominic Broadhurst
Keyword(s):  
Online Survey ◽  
Content Type ◽  
Face To Face ◽  
Learning Commons ◽  
Students First ◽  
Academic Faculty ◽  
The Uk ◽  
The University ◽  
University Of Manchester ◽  
Enhanced Learning

Purpose This paper aims to highlight the value of a library led e-textbook programme at a the UK university. Design/methodology/approach The data for the results were obtained from two surveys of students. First, from an online survey of 575 students who received an individual copy of an e-textbook from The University of Manchester Library. Second, from a face to face survey of 146 students, based on a random sample of students entering the Alan Gilbert Learning Commons at the University. In addition, a series of one-to-one interviews were conducted with 40 members of academic faculty, who were teaching the course modules, on which the students received their own e-textbook. Findings This research highlights the significant benefits a library led e-textbook service can offer to students, academic faculty, the wider University and to the profile of the library. Provision of the e-textbooks leads to higher engagement of learning from students, their increased satisfaction with the University and Library, plus addresses issue of reducing their direct costs. It also leads to enhanced pedagogy from the perspective of academic faculty. Practical implications The paper addresses issues of inequality of provision for individual students and contributes to enhanced learning for all students. Originality/value Library led initiatives are very new in this field and this project is one of the first to both undertake this provision and to undertake extensive research to assess the value of the project.

Can you measure IT? The UK experience of TechQual+

2014 ◽  
Vol 15 (1/2) ◽  
pp. 32-40 ◽  
Author(s):  
Ian Hall ◽  
Jessica Stephens ◽  
Sarah Kennedy
Keyword(s):  
Data Protection ◽  
Senior Managers ◽  
Web Based ◽  
Content Type ◽  
Survey Tool ◽  
Technology Services ◽  
Protection Legislation ◽  
The Uk ◽  
The University

Purpose – The University of York Library, part of its Information Directorate, has successfully run an annual user survey using LibQUAL+ since 2008. The tool has proven invaluable in understanding user needs and measuring improvements. The ability to benchmark performance has been well received by university senior managers. Following this positive experience, the Directorate piloted the TechQual+ survey to assess its technology services. TechQual+ is a total market-survey tool developed on the same principles as LibQUAL+. York was the first university in the UK to do this. The purpose of this paper is to reflect upon the experience and its relevance to information services. Design/methodology/approach – A team was established to co-ordinate the distribution of the survey, which was e-mailed to all university members. The survey was conducted over a period of three weeks in December 2011 using their web-based tool. The team worked with the survey providers to make amendments in order to comply with UK Data Protection legislation. Findings – The TechQual+ tool provided a rich set of data on the IT needs of University of York students and staff, including a wealth of comments. As the first use of the tool in the UK, a number of outcomes arose from the pilot: methods for running the survey in order to meet UK data protection requirements; feedback on the tool itself, with some questions not understood from a UK context; a rich set of results data, with some similarities (and several differences) to those available through LibQUAL+. Originality/value – The paper presents the first application of the TechQual+ survey in UK and discusses the issues faced when implementing it in a UK context. The case study will be of interest to libraries or converged services interested in assessing their IT provision.

The framework of data-driven and multi-criteria decision-making for detecting unbalanced bidding

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Huimin Li ◽  
Limin Su ◽  
Jian Zuo ◽  
Xiaowei An ◽  
Guanghua Dong ◽  
...  
Keyword(s):  
Decision Making ◽  
Distance Measure ◽  
Public Procurement ◽  
Unit Price ◽  
Data Driven ◽  
Relative Distance ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Content Type ◽  
The Government

PurposeUnbalanced bidding can seriously imposed the government from obtaining the best value for the taxpayers' money in public procurement since it increases the owner's cost and decreases the fairness of the competitive bidding process. How to detect an unbalanced bid is a challenging task faced by theoretical researchers and practical actors. This study aims to develop an identification method of unbalanced bidding in the construction industry.Design/methodology/approachThe identification of unbalanced bidding is considered as a multi-criteria decision-making (MCDM) problem. A data-driven unit price database from the historical bidding document is built to present the reference unit prices as benchmarks. According to the proposed extended TOPSIS method, the data-driven unit price is chosen as the positive ideal solution, and the unit price that has the furthest absolute distance measure as the negative ideal solution. The concept of relative distance is introduced to measure the distances between positive and negative ideal solutions and each bidding unit price. The unbalanced bidding degree is ranked by means of relative distance.FindingsThe proposed model can be used for the quantitative evaluation of unbalanced bidding from a decision-making perspective. The identification process is developed according to the decision-making process. The finding shows that the model will support owners to efficiently and effectively identify unbalanced bidding in the bid evaluation stage.Originality/valueThe data-driven reference unit prices improve the accuracy of the benchmark to evaluate the unbalanced bidding. The extended TOPSIS model is applied to identify unbalanced bidding; the owners can undertake objective decision-making to identify and prevent unbalanced bidding at the stage of procurement.

scholarly journals Data competence maturity: developing data-driven decision making

2018 ◽  
Vol 11 (2) ◽  
pp. 139-158 ◽  
Author(s):  
Thomas G. Cech ◽  
Trent J. Spaulding ◽  
Joseph A. Cazier
Keyword(s):  
Decision Making ◽  
Secondary Education ◽  
Data Science ◽  
Data Driven ◽  
Decision Making Process ◽  
Maturity Model ◽  
Data Driven Decision Making ◽  
Content Type ◽  
Development Data ◽  
Education Performance

Purpose The purpose of this paper is to lay out the data competence maturity model (DCMM) and discuss how the application of the model can serve as a foundation for a measured and deliberate use of data in secondary education. Design/methodology/approach Although the model is new, its implications, and its application are derived from key findings and best practices from the software development, data analytics and secondary education performance literature. These principles can guide educators to better manage student and operational outcomes. This work builds and applies the DCMM model to secondary education. Findings The conceptual model reveals significant opportunities to improve data-driven decision making in schools and local education agencies (LEAs). Moving past the first and second stages of the data competency maturity model should allow educators to better incorporate data into the regular decision-making process. Practical implications Moving up the DCMM to better integrate data into their decision-making process has the potential to produce profound improvements for schools and LEAs. Data science is about making better decisions. Understanding the path laid out in the DCMM to helping an organization move to a more mature data-driven decision-making process will help improve both student and operational outcomes. Originality/value This paper brings a new concept, the DCMM, to the educational literature and discusses how these principles can be applied to improve decision making by integrating them into their decision-making process and trying to help the organization mature within this framework.

scholarly journals Hardware-in-the-loop simulator of wind turbine emulator using labview

2019 ◽  
Vol 10 (2) ◽  
pp. 971
Author(s):  
Himani Himani ◽  
Navneet Sharma
Keyword(s):  
Wind Turbine ◽  
Condition Monitoring ◽  
Wind Turbines ◽  
Control Strategies ◽  
Hardware In The Loop ◽  
Data Acquisition Card ◽  
Terminal Voltage ◽  
The Uk ◽  
The University ◽  
University Of Manchester

<p><span>This paper describes the design and implementation of Hardware in the Loop (HIL) system D.C. motor based wind turbine emulator for the condition monitoring of wind turbines. Operating the HIL system, it is feasible to replicate the actual operative conditions of wind turbines in a laboratory environment. This method simply and cost-effectively allows evaluating the software and hardware controlling the operation of the generator. This system has been implemented in the LabVIEW based programs by using Advantech- USB-4704-AE Data acquisition card. This paper describes all the components of the systems and their operations along with the control strategies of WTE such as Pitch control and MPPT. Experimental results of the developed simulator using the test rig are benchmarked with the previously verified WT test rigs developed at the Durham University and the University of Manchester in the UK by using the generated current spectra of the generator. Electric subassemblies are most vulnerable to damage in practice, generator-winding faults have been introduced and investigated using the terminal voltage. This wind turbine simulator can be analyzed or reconfigured for the condition monitoring without the requirement of actual WT’s.</span></p>

Factors influencing collection development process at the University of Nairobi Library

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Grace Wambui Kamau ◽  
Aggrey Luyiya Elegwa
Keyword(s):  
Development Policy ◽  
Development Process ◽  
Research Output ◽  
Background Information ◽  
Collection Development ◽  
University Libraries ◽  
Content Type ◽  
University Library ◽  
Factors Influencing ◽  
The University

PurposeThe purpose of this study was to investigate the factors influencing the collection development process at the University of Nairobi library and suggest ways for improvement.Design/methodology/approachA qualitative approach was employed to collect, analyze and interpret data from collection development librarians at the University of Nairobi purposively selected. Data were collected through structured interviews and documentary review. Data were analyzed using content analysis and descriptive statistics.FindingsThe study established that the library has a written collection development policy which was revised in 2014 and is strictly adhered to. However, the policy has a gap on the role of faculty as stakeholders in the selection process. In addition, the criteria for selection are not explicitly stated. Findings also indicate that budget allocation, collection development policy, user demands, quality of staff, library consortium and the Public Procurement and Asset Disposal Act of 2015 influence the collection development process at the University of Nairobi Library.Research limitations/implicationsThe study was conducted in one public university library in Kenya. However, the findings may be applicable in similar university libraries in the country.Practical implicationsThe findings of this study may benefit students and faculty in the University of Nairobi from improved collection development process that would ensure that their information needs are met in a timely manner. This would lead to improved research output by students and faculty and ultimately improved research output by the university. University library management may also benefit in improving the collection development process, thereby making it more economical. The findings may also be useful in decision-making and policy development on matters pertaining to collection development at the University of Nairobi and other universities. Furthermore, the findings may be used by researchers to provide context and background information for future research on collection development in public universities locally and regionally.Originality/valueThis paper fulfills the need to make the collection development process in university libraries more efficient by proposing ways of addressing the challenges experienced.

Decision-making system for higher education university selection: comparison of priorities pre- and post-COVID-19

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Krishnadas Nanath ◽  
Ali Sajjad ◽  
Supriya Kaitheri
Keyword(s):  
Higher Education ◽  
Decision Making ◽  
Higher Education Institutions ◽  
Mode Of Delivery ◽  
Primary Data ◽  
Final Decision ◽  
Content Type ◽  
University Selection ◽  
The University ◽  
The Impact

PurposeUniversity selection in higher education is a complex task for aspirants from a decision-making perspective. This study first aims to understand the essential parameters that affect potential students' choice of higher education institutions. It then aims to explore how these parameters or priorities have changed given the impact of the COVID-19 pandemic. Learning about the differences in priorities for university selection pre- and post-COVID-19 pandemic might help higher education institutions focus on relevant parameters in the post-pandemic era.Design/methodology/approachThis study uses a mixed-method approach, with primary and secondary data (university parameters from the website and LinkedIn Insights). We developed a university selector system by scraping LinkedIn education data of various universities and their alumni records. The final decision-making tool was hosted on the web to collect potential students' responses (primary data). Response data were analyzed via a multicriteria decision-making (MCDM) model. Portal-based data collection was conducted twice to understand the differences in university selection priorities pre- and post-COVID-19 pandemic. A one-way MANOVA was performed to find the differences in priorities related to the university decision-making process pre- and post-COVID-19.FindingsThis study considered eight parameters of the university selection process. MANOVA demonstrated a significant change in decision-making priorities of potential students between the pre- and post-COVID-19 phases. Four out of eight parameters showed significant differences in ranking and priority. Respondents made significant changes in their selection criteria on four parameters: cost (went high), ranking (went low), presence of e-learning mode (went high) and student life (went low).Originality/valueThe current COVID-19 pandemic poses many uncertainties for educational institutions in terms of mode of delivery, student experience, campus life and others. The study sheds light on the differences in priorities resulting from the pandemic. It attempts to show how social priorities change over time and influence the choices students make.

The Single Most Consequential Thing We Do in Universities

2013 ◽  
pp. 304-329
Author(s):  
Grant Campbell
Keyword(s):  
Decision Making ◽  
Learning Outcomes ◽  
Academic Careers ◽  
Important Thing ◽  
Constructive Alignment ◽  
The University ◽  
University Of Manchester ◽  
Giving Feedback

Assessing students (including giving feedback and making decisions based on assessments) is arguably the single most important thing done in universities in terms of tangible impacts on people’s lives, but assessment is hard to do. Academics are seldom trained in assessment, and for many it is the most worrying aspect of the job. The University of Manchester operates a New Academics Programme for its probationary lecturers, running over three years and encompassing research, teaching, and administrative aspects of academic careers, culminating in a reflective portfolio. This case study describes the introduction of an assessment component into this programme, including its motivation, content, implementation, and evolution, and its reception by the new academics. The assessment component of the New Academics Programme is now delivered in two sessions at different times of the year. The first covers the importance of assessment and gives guidance for designing good assessments and giving feedback. The second session goes more deeply into constructive alignment and learning outcomes, leading on to decision making in exam boards, and ending with a focus on cultivating academic judgement.

Stream processing data decision model for higher environmental performance and resilience in sustainable logistics infrastructure

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yasanur Kayikci
Keyword(s):  
Decision Making ◽  
Transport System ◽  
Environmental Performance ◽  
Stream Processing ◽  
Data Driven ◽  
Content Type ◽  
Sustainable Logistics ◽  
Processing Data ◽  
Decision Making Model ◽  
Resilience Capacity

PurposeAs the global freight transport network has experienced high vulnerability and threats from both natural and man-made disasters, as a result, a huge amount of data is generated in freight transport system in form of continuous streams; it is becoming increasingly important to develop sustainable and resilient transport system to recover from any unforeseen circumstances quickly and efficiently. The aim of this paper is to develop a stream processing data driven decision-making model for higher environmental performance and resilience in sustainable logistics infrastructure by using fifteen dimensions with three interrelated domains.Design/methodology/approachA causal and hierarchical stream processing data driven decision-making model to evaluate the impact of different attributes and their interrelationships and to measure the level of environmental performance and resilience capacity of sustainable logistics infrastructure are proposed. This work uses fuzzy cognitive maps (FCMs) and fuzzy analytic hierarchy process (FAHP) techniques. A real-life case under a disruptive event scenario is further conducted.FindingsThe result shows which attributes have a greater impact on the level of environmental performance and resilience capacity in sustainable logistics infrastructure.Originality/valueIn this paper, causal and hierarchical stream processing data decision and control system model was proposed by identified three domains and fifteen dimensions to assess the level of environmental performance and resilience in sustainable logistics infrastructure. The proposed model gives researchers and practitioners insights about sustainability trade-offs for a resilient and sustainable global transport supply chain system by enabling to model interdependencies among the decision attributes under a fuzzy environment and streaming data.

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