Users’ Satisfaction and Return on Investment (ROI) for Online Database Library Databases: A Malaysian Technical University Perspective

Wahab, Eta; Shamsuddin, Alina; Abdullah, Nor Hazana; Hamid, NorAziati Abdul

doi:10.1016/j.sbspro.2016.05.075

Cited by 7 publications

(6 citation statements)

References 16 publications

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“…In Malaysia, Wahab et al (2016) examined the ROI of subscribing to online databases. The findings of the study suggested that subscribing to online databases provided a positive value and that more benefits were generated when the subscription was supported by research grants.…”

Section: Related Studiesmentioning

confidence: 99%

Measuring the value of online databases: a case study to validate an ROI model

Kaba

Refae

Eletter

et al. 2023

PMM

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PurposeThe return on investment (ROI) model is a tool used to measure the financial benefits and costs of an investment, in this case, the investment in digital library resources. By applying this model to the AAU digital library resources, the study seeks to determine whether these resources are providing sufficient value for the investment made in them.Design/methodology/approachThe proposed ROI model has two distinct phases and utilizes two different sets of data to calculate the return on investment for a database subscription. In Phase I, the ROI is calculated based on the total number of downloads of full-text articles from the database during the academic year 2019–2020. This information is used to determine the financial returns of the database subscription costs. In Phase II, the ROI is calculated by examining the citations drawn from the Scopus database on a sample of 30 funded research projects for the College of Engineering during the year 2019. These data are used to determine the impact of the database subscription on research output and its contribution to the success of the College of Engineering's research projects. The two phases of the proposed ROI model aim to provide a comprehensive understanding of the value of the database subscription and its impact on both financial returns and research output.FindingsThe findings of the study indicated different results between Phase 1 and Phase 2 of the study. The positive ROI in Phase 1 suggests that the investment in online databases has a good return for the AAU, as they are gaining almost a dollar for every dollar spent. However, the negative ROI in Phase 2 is concerning. It suggests that the investment in the IEEE database is not generating a positive return for the AAU and may even be costing the institution money. Overall, these findings highlight the importance of measuring ROI in academic libraries, particularly in Arab countries where resources may be limited. By understanding the impact of library investments on institutional outcomes, libraries can make informed decisions about where to allocate their resources and how to optimize their services to best serve their communities.Research limitations/implicationsThe findings of the current study were based on data collected from a specific sample, therefore, the findings may not be generalized to other academic libraries. A similar study with larger and more diverse samples can help to validate and extend the results of this study.Originality/valueThe findings of the study provide evidence that the proposed ROI model can be effectively applied in Arab countries and academic libraries in the Arab world, this could encourage more institutions in the region to adopt this model for evaluating their investments and projects. The study may also guide how to adapt the model to the specific cultural and organizational contexts of Arab countries.

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Section: Related Studiesmentioning

confidence: 99%

Measuring the value of online databases: a case study to validate an ROI model

Kaba

Refae

Eletter

et al. 2023

PMM

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“…Scholars increasingly rely on electronic resources with a high prevalence of non-traditional materials (Nicholas and Huntington, 2006). Faculty satisfaction and desire to utilize online databases are determined by the quality of online databases (Wahab et al, 2016).…”

Section: Academic Research Databasesmentioning

confidence: 99%

Teachers’ use of academic research databases and its relationship to their research skills and performance

CAMAHALAN¹,

NAPARAN²

2022

International Journal of Social Sciences and Education Research

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This descriptive-correlational study aims to determine the relationship between teachers' use of academic research databases, research skills, and teachers' performance. Research teachers in public secondary schools under the Pagadian City division, Philippines, were selected as participants for the survey. The results showed a strong positive correlation between teachers' use of academic research databases and research skills. However, teachers' performance has no relationship with research skills and teachers' use of academic research databases. Since teachers' use of academic research databases and research skills among the teacher-participants of this study were not related to their very satisfactory performance, teachers may have been developed successfully due to the Department of Education's reinforced programs, training conferences, and workshops.

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“…ROI indicates the profitability of an investment. As mentioned in [19], ROI is the ratio of annual financial resource gained or lost to the investment. ROI is calculated using (9) where I is the investment.…”

Section: ) the Financial Analysis Modelmentioning

confidence: 99%

“…the results are shown in Table 10. The last step is, determining Alternatives' Relative Closeness Value to Ideal Solution using (19) and the results are shown in Table 11. The value is then ranked using descending order to obtain the largest value as the most appropriate alternative decision.…”

Section: The Alternative Rankingmentioning

confidence: 99%

Integrated AHP, Profile Matching, and TOPSIS for selecting type of goats based on environmental and financial criteria

Primasari

Wardoyo

Sari

2018

Int. J. Adv. Intell. Informatics

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Goat farm businessman should considered environmental and financial criteria in breeding their commodities. The environmental factors are temperature, humidity, rain intensity, and altitude. For financial criteria, used several sub criteria i.e NPV (Net Present Value), ROI (Return On Investment), BCR (Benefit Cost Ratio), PBP (Payback Period), and BEP (Break Event Point) to determine financial feasibility. This research aims to develop a decision support system for selecting type of goat to breed by combining AHP, Profile Matching, and TOPSIS. AHP method was used for calculating the weight, Profile Matching for environment suitability evaluation, and TOPSIS for producing a valid decision that represents the goat expert's decision. The result showed that three methods can be integrated, and an experimental results which was validated by expert show that Bligon goat had the highest preference value (0.8835847). This can be concluded that DSS decision was valid and it successfully represented expert’s consideration.

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