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1 – 3 of 3Md. Nurul Islam, Guangwei Hu, Murtaza Ashiq and Shakil Ahmad
This bibliometric study aims to analyze the latest trends and patterns of big data applications in librarianship from 2000 to 2022. By conducting a comprehensive examination of…
Abstract
Purpose
This bibliometric study aims to analyze the latest trends and patterns of big data applications in librarianship from 2000 to 2022. By conducting a comprehensive examination of the existing literature, this study aims to provide valuable insights into the emerging field of big data in librarianship and its potential impact on the future of libraries.
Design/methodology/approach
This study employed a rigorous four-stage process of identification, screening, eligibility and inclusion to filter and select the most relevant documents for analysis. The Scopus database was utilized to retrieve pertinent data related to big data applications in librarianship. The dataset comprised 430 documents, including journal articles, conference papers, book chapters, reviews and books. Through bibliometric analysis, the study examined the effectiveness of different publication types and identified the main topics and themes within the field.
Findings
The study found that the field of big data in librarianship is growing rapidly, with a significant increase in publications and citations over the past few years. China is the leading country in terms of publication output, followed by the United States of America. The most influential journals in the field are Library Hi Tech and the ACM International Conference Proceeding Series. The top authors in the field are Minami T, Wu J, Fox EA and Giles CL. The most common keywords in the literature are big data, librarianship, data mining, information retrieval, machine learning and webometrics.
Originality/value
This bibliometric study contributes to the existing body of literature by comprehensively analyzing the latest trends and patterns in big data applications within librarianship. It offers a systematic approach to understanding the state of the field and highlights the unique contributions made by various types of publications. The study’s findings and insights contribute to the originality of this research, providing a foundation for further exploration and advancement in the field of big data in librarianship.
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Keywords
The purpose of this study is to provide an optimal joint strategy of multi-period pricing and sales effort for a retailer with a logit choice demand in an integrated channel.
Abstract
Purpose
The purpose of this study is to provide an optimal joint strategy of multi-period pricing and sales effort for a retailer with a logit choice demand in an integrated channel.
Design/methodology/approach
Customer demand is characterized by a logit choice model, it varies over time and is influenced by price and sales effort. The multi-period decision model for the retailer is constructed using a discrete-time dynamic programming method to determine the optimal price and sales effort in each period.
Findings
When the inventory level does not exceed a certain threshold, decreasing price and increasing sales effort over time or as inventory level increases are the optimal strategies. However, once the inventory level exceeds the threshold, the optimal strategy is to maintain both price and sales effort constant as the inventory level changes or to increase price and decrease sales effort over time. Additionally, the greater the influence of sales effort on demand or the higher the arrival rate of customers, the higher the optimal price and the greater the optimal sales effort level.
Originality/value
This study contributes to the existing research on dynamic pricing and sales effort in integrated channels by incorporating a logit choice model. Furthermore, it provides valuable management insights for retailers operating in an integrated channel to make pricing and sales effort decisions based on inventory level and time period.
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Keywords
Guangwei Liang, Zhiming Gao, Cheng-Man Deng and Wenbin Hu
The purpose of this study is to reveal the effect of nano-Al2O3 particle addition on the nucleation/growth kinetics, microhardness, wear resistance and corrosion resistance of…
Abstract
Purpose
The purpose of this study is to reveal the effect of nano-Al2O3 particle addition on the nucleation/growth kinetics, microhardness, wear resistance and corrosion resistance of Co–P–xAl2O3 nanocomposite plating.
Design/methodology/approach
The kinetics and properties of Co–P–xAl2O3 nanocomposite plating prepared by electroplating were investigated by electrochemical measurements, scanning electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy, Vickers microhardness measurement, SRV5 friction and wear tester and atomic force microscopy.
Findings
A 12 g/L nano-Al2O3 addition in the plating solution can transform the nucleation/growth kinetics of the plating from the 3D progressive model to the 3D instantaneous model. The microhardness of the plating increased with the increase of nano-Al2O3 content in plating. The wear resistance of the plating did not adhere strictly to Archard’s law. An even and denser corrosion product film was generated due to the finer grains, with a high corrosion resistance.
Originality/value
The effect of different nano-Al2O3 addition on the nucleation/growth kinetics and properties of Co–P–xAl2O3 nanocomposite plating was investigated, and an anticorrosion mechanism of Co–P–xAl2O3 nanocomposite plating was proposed.
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