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Article
Publication date: 30 June 2020

Yin-Ju Chen and Jian-Ming Lo

Decision-making is always an issue that managers have to deal with. Keenly observing to different preferences of the targets provides useful information for decision-makers who do…

210

Abstract

Purpose

Decision-making is always an issue that managers have to deal with. Keenly observing to different preferences of the targets provides useful information for decision-makers who do not require too much information to make decisions. The main purpose is to avoid decision-makers in a dilemma because of too much or opaque information. Based on problem-oriented, this research aims to help decision-makers to develop a macro-vision strategy that fits the needs of different clusters of customers in terms of their favorite restaurants. This research also focuses on providing the rules to rank data sets for decision-makers to make choices for their favorite restaurant.

Design/methodology/approach

When the decision-makers need to rethink a new strategic planning, they have to think about whether they want to retain or rebuild their relationship with the old consumers or continue to care for new customers. Furthermore, many of the lecturers show that the relative concept will be more effective than the absolute one. Therefore, based on rough set theory, this research proposes an algorithm of related concepts and sends questionnaires to verify the efficiency of the algorithm.

Findings

By feeding the relative order of calculating the ranking rules, we find that it will be more efficient to deal with the faced problems.

Originality/value

The algorithm proposed in this research is applied to the ranking data of food. This research proves that the algorithm is practical and has the potential to reveal important patterns in the data set.

Details

Data Technologies and Applications, vol. 55 no. 2
Type: Research Article
ISSN: 2514-9288

Keywords

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Article
Publication date: 9 May 2023

Dan Wang

This research conducts bibliometric analyses and network mapping on smart libraries worldwide. It examines publication profiles, identifies the most cited publications and…

840

Abstract

Purpose

This research conducts bibliometric analyses and network mapping on smart libraries worldwide. It examines publication profiles, identifies the most cited publications and preferred sources and considers the cooperation of the authors, organizations and countries worldwide. The research also highlights keyword trends and clusters and finds new developments and emerging trends from the co-cited references network.

Design/methodology/approach

A total of 264 records with 1,200 citations were extracted from the Web of Science database from 2003 to 2021. The trends in the smart library were analyzed and visualized using BibExcel, VOSviewer, Biblioshiny and CiteSpace.

Findings

The People’s Republic of China had the most publications (119), the most citations (374), the highest H-index (12) and the highest total link strength (TLS = 25). Wuhan University had the highest H-index (6). Chiu, Dickson K. W. (H-index = 4, TLS = 22) and Lo, Patrick (H-index = 4, TLS = 21) from the University of Hong Kong had the highest H-indices and were the most cooperative authors. Library Hi Tech was the most preferred journal. “Mobile library” was the most frequently used keyword. “Mobile context” was the largest cluster on the research front.

Research limitations/implications

This study helps librarians, scientists and funders understand smart library trends.

Originality/value

There are several studies and solid background research on smart libraries. However, to the best of the author’s knowledge, this study is the first to conduct bibliometric analyses and network mapping on smart libraries around the globe.

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Article
Publication date: 25 August 2023

Dickson K.W. Chiu and Kevin K.W. Ho

847

Abstract

Details

Library Hi Tech, vol. 41 no. 4
Type: Research Article
ISSN: 0737-8831

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Article
Publication date: 14 August 2020

Yun-Fang Tu and Gwo-Jen Hwang

This study aims to explore the transformation of the roles of libraries, application trends and potential research issues of library-supported mobile learning.

810

Abstract

Purpose

This study aims to explore the transformation of the roles of libraries, application trends and potential research issues of library-supported mobile learning.

Design/methodology/approach

The publications in the Scopus database from 2009 to 2018 are reviewed and analyzed from various aspects, such as the roles of libraries in mobile learning, types of libraries, research foci and sensing or location-based technologies.

Findings

The role of libraries as learning material providers is examined the most in library-supported mobile learning studies, followed by the role as inquiry context providers and as knowledge-sharing platforms. In terms of the role as learning material providers, academic libraries were investigated the most and radio frequency identification (RFID) was mainly adopted. In terms of the role as inquiry context providers, special libraries were explored the most; adopted sensing technologies were more diverse (e.g. QR code, augmented reality, RFID and Global Positioning System). Only special libraries played a role as knowledge-sharing platforms, adopting augmented reality. Most research on library-supported mobile learning mainly focused on investigating the affective domain during mobile learning.

Practical implications

Five potential applications of educational roles in library-supported mobile learning are suggested based on the findings of the present study.

Originality/value

The current study provides insights relevant to the educational roles of library-supported mobile learning. The findings and suggestions can serve as references for researchers and school teachers conducting library-supported mobile learning.

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Article
Publication date: 17 December 2018

Muhammad Rafi, Zheng JianMing and Khurshid Ahmad

Digital library database resources have a significant impact on stimulating the research culture in higher education. The use of digital databases makes it possible to understand…

2825

Abstract

Purpose

Digital library database resources have a significant impact on stimulating the research culture in higher education. The use of digital databases makes it possible to understand intellectual growth, research productivity, planning and identification of user information needs. Evaluating the effectiveness of user database resource utilization and research, the purpose of this study is to assist management in developing an excellent academic policy.

Design/methodology/approach

This study establishes a quantitative method to analyze the productivity of academic research using digital databases. The secondary data extracted from the databases of 52 universities provided by Higher Education Commission (HEC) and the literature published on the Institute of Scientific Information (ISI) Web of Science. The statistical technique simple linear regression was used to analyze the data for understanding the impact of independent variables the “digital databases” on the dependent variable “research productivity”.

Findings

The result of the coefficient of multiple determination, R-squared, R2 0.679, indicated 67 per cent impact of the predictor on the outcome variable. However, the standardized coefficient Beta 0.824 revealed 82 per cent impact of the individual predictor on the outcome variable. Overall, the result of linear regression showed a significant effect of independent variables on the dependent variable. Besides, the result of correlation and the strength of association between the database resources and the academic publication was significant (p < 0.005).

Practical implications

This research work is a supportive tool for managing gaps and promoting the development of necessary measures to develop strategies and solutions to create a better academic environment. The ultimate use of standard database resources can foster higher academic research to develop innovative ideas and improve researchers’ cognitive abilities.

Originality/value

From Pakistan’s point of view, this study is the first one that gives insight into the intellectual growth of young researchers in higher education. The study provides first-hand information on the use of database resources and their significant impact on the productivity of academic research.

Details

Information Discovery and Delivery, vol. 47 no. 1
Type: Research Article
ISSN: 2398-6247

Keywords

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Article
Publication date: 6 May 2021

Yun-Fang Tu, Gwo-Jen Hwang, Joyce Chao-Chen Chen and Chiulin Lai

This study aims to investigate the influences of task-technology fit on university students’ attitudes towards ubiquitous library-supported learning when they use a mobile library…

559

Abstract

Purpose

This study aims to investigate the influences of task-technology fit on university students’ attitudes towards ubiquitous library-supported learning when they use a mobile library app, Line@Library.

Design/methodology/approach

In this study, structural equation modelling to examine 158 valid questionnaires are used. The study aims to examine the effects of task-technology fit (TTF) on university students’ attitudes towards mobile learning (AML) when using Line@Library.

Findings

The results show that task-technology fit is an important role that influences the students’ attitudes towards mobile learning. The factor “technology characteristics” is considered when the students attempted to use the mobile app to solve problems or complete tasks. This study also found that the students responded with positive perceptions of the task-technology fit and had positive perceptions of its ease of use. Furthermore, usefulness, ease of use and affection of AML were found to be the most influential predictors of mobile library adoption intention.

Originality/value

From the perspective of learners, this study investigates the relationships of the combination of social media and a mobile library between TTF and AML. This study further found that not only ease of use, usefulness and affection but also task-technology fit can be a predictor that influences students’ attitudes towards mobile learning.

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