Planning and Evaluation of New Academic Library Services by Means of Web-based Conjoint Analysis

Decker, Reinhold; Hermelbracht, Antonia

doi:10.1016/j.acalib.2006.06.016

Cited by 14 publications

(9 citation statements)

References 10 publications

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“…ACA has not been used as much in education research, but it is becoming increasingly more popular. Educational studies that have used ACA were primarily higher education studies in which researchers investigated recruitment (Bickel & Brown, 2005; Sohn & Ju, 2009; Sontar & Turner, 2002), student course choice and preference (Maringe, 2006; Moogan, Baron, & Bainbridge, 2001; Zufryden, 1983), and effectiveness of academic services (Crawford, 1994; Decker & Hermelbracht, 2006; Howard & Sobol, 2004).…”

Section: Methodsmentioning

confidence: 99%

Preservice Music Teachers’ Employment Preferences

Robinson

2012

Journal of Research in Music Education

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This study was designed to investigate preservice music teachers’ ( N = 187) perceptions of employment preferences when considering future teaching positions. Adaptive Conjoint Analysis, a business market–based research tool, was used to determine preferences for personal factors (e.g., salary, commute), school environmental factors (e.g., administrative support, school type, student race-ethnicity, student socioeconomic status [SES]), and music teaching factors (e.g., resources, facilities, program sustainability, parental and community support). Results indicated that preservice music teachers perceived administrative support, parental and community support, and program sustainability as most important factors and student SES and student race-ethnicity composition as least important factors when considering future employment.

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Section: Methodsmentioning

confidence: 99%

Preservice Music Teachers’ Employment Preferences

Robinson

2012

Journal of Research in Music Education

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“…In the USA, it is important to highlight the study presented by Nicholson (2003a) that compares the effectiveness of four different data mining functions: logistic regression, memory-based reasoning, decision/classification tree and neural networks to discover Webbased scholarly research works. Moreover, in 2006, two out of four articles report a case study implementation in Germany, all implemented by Decker and colleagues (Decker & Hermelbracht, 2006;Decker & Höppner, 2006). Data analysis and characterization are the most used techniques, except for the years 2002-2004, in which more formal data mining techniques are implemented.…”

Section: Distribution Of Articles By Year Of Publicationmentioning

confidence: 97%

Literature Review of Data Mining Applications in Academic Libraries

Siguenza-Guzmán

Saquicela

Avila-Ordóñez

et al. 2015

The Journal of Academic Librarianship

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“…The sum of the part-worth utility values for an alternative is assumed to be an estimate of its unknown (latent) utility. The goal is to compute the part-worth utility values such that the computed utilities of the considered alternatives reflect the original rank orderings of the alternatives considered as accurate as possible (see Decker and Hermelbracht, 2006 for methodical details). Figure 2 illustrates the preferences, or rather part-worth utility values, regarding future options for lending and delivering books at Bielefeld University Library.…”

Section: Data and Methods For Generating Customer Intelligencementioning

confidence: 99%

“…using expertise from our employees, from external experts, and from the literature. A list of about 250 services ranked essential for the future constituted the basis of a comprehensive Conjoint Analysis study to measure the preferences of our customers (Decker and Hermelbracht, 2006). In addition, four internal working groups developed first drafts of detailed product sheets for library services, which should establish a catalogue of services later on.…”

Section: Strategic Planning At Bielefeld University Librarymentioning

confidence: 99%

Strategic planning and customer intelligence in academic libraries

Decker¹,

Höppner²

2006

Library Hi Tech

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Purpose: The paper refers to a current discussion on the effectiveness and efficiency of Bielefeld University Library and concentrates on requirements and conditions of implementing customer intelligence in academic libraries. Moreover, a conceptual framework for a library management information system based on a data warehouse that links external and internal data to support strategic planning processes is introduced. Design/methodology/approach: Content-related and technical aspects of customer intelligence in academic libraries are outlined and analogies are drawn to commercial enterprises to motivate the conceptual reflections. The paper closes with two examples that demonstrate how multifaceted the data pool for customer intelligence can be in librarianship. Findings: The paper sensitizes to the advantages of systematically generating customer knowledge in academic libraries for strategic planning and customer orientation. Practical implications: The suggested approach can serve as a basis for the development of data-based decision support systems focusing on the tracking of the usage of library services and customer preferences over time. Originality/value: Up to now the discussion of customer intelligence as a foundation of strategic planning in academic libraries has been almost a blank space in the literature. The paper contributes to fill this gap.

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Planning and Evaluation of New Academic Library Services by Means of Web-based Conjoint Analysis

Cited by 14 publications

References 10 publications

Preservice Music Teachers’ Employment Preferences

Preservice Music Teachers’ Employment Preferences

Literature Review of Data Mining Applications in Academic Libraries

Strategic planning and customer intelligence in academic libraries

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