Academic Libraries Performance Evaluation Model In The Age Of Big Data

In the last decade,the culture of research in the field of library and information science focused on different areas of studies.Although the published literature related to the advancement in technology and information organization is growing globally yet in this scenario,the innovations and emerging technological trends lead to opportunities and threats.The use of emerging technologies and trends in different fields of knowledge remains challenging.These challenges are associated with organizational performance,culture,internal and external environment,infrastructure,organizational policies,technology,and human resource management.This thesis consists of three research aspects;each of the research aspects evaluates the use of big data analytics technology and analyzes the factors based on libraries performance.The research aspect emphases on the analysis of big data analytics in libraries and evaluate the culture and trends by the use of analytics across the academic institutes of Pakistan.It also based on empirical-based research to assess the perceptions of library and information science professionals towards the implementation of big data analytics and discussed the factors to enhances the academic library performance for the better utilization of library resources and services in Pakistan.The main aspect of the dissertation explores the libraries performance-based factors with the help of literature review that consisted on the culture of data-driven,organizational infrastructure,and personal responsibilities of librarians to improve the resources and services of libraries.With this,it also analyzes the capabilities and skills of LIS professionals in academic organization culture and performance.In the other aspect,the results of the study narrate the strong association among the understanding of the skills and abilities of library and information science professional’s performance in academic institutes of Pakistan.It also investigates the associations among the different challenges faced by the academic libraries’ professionals in the new era of big data.1)The purpose of the research is to postulate the implementation of big data analytics in academic libraries.The development in the technological infrastructure has improved the organizational culture,and the enhancement in the analytical competencies ascertain the successful implementation process of big data analytics in academic libraries.This research proposed a conceptual model that based on five main components(latent factors)towards the implementation of big data analytics in libraries such as;the data-driven culture,organizational infrastructure,capabilities of human resources and competencies of the professionals.For data collection,a survey research questionnaire was constructed with the help of a comprehensive literature review.The data were obtained from 211 administrative librarians to know the components and the practices of big data analytics in academic libraries.The statistical technique confirmatory factor analysis was applied to evaluate the observed values based on the five latent factors using the structural equation model software for the evaluation and the implementation process of big data analytics(BDA)in the academic libraries.The research findings revealed a significant and robust positive association between the latent factors and their impact on the observed values in the implementation process of big data analytics in libraries.The results of the hypothesized theoretical model confirm the data-driven culture in the organization,adequate infrastructure,responsibilities and the required competencies of librarians in to meet the needs and requirements of library users in the era of big data and digital environment.The research limitation reveals a country perspective for the implementation process of big data analytics in the academic libraries.2)The concept of big data has been extensively considered a technological modernization in organizations and educational institutes.The purpose of this study is to determine whether the Technology Acceptance Model(TAM)correctly measured the satisfaction of librarians in using big data analytics in academic libraries.The researchers used an empirical research method for data collection from 211 Pakistan universities librarians.Using the TAM,libraries performance was tried to comprehend through the big data process and the organizational factors of libraries.For confirmatory factors analysis model data were analyzed using the structural equation modeling(SEM)on SPSS and AMOS statistical software packages.Findings reveal the factors of academic libraries with the array of different resources of big data that leads to the components of organizational performance.In the light of TAM and confirmatory factors analysis,the variance of academic libraries performance analyzed the effectiveness on the ease of use,perceived usefulness,big data analytical skills,and the big data practices in academic libraries.For the measurement of endogenous variable TAM is a robust predictive tool in the research.It also highlights the association between the elements of performance factors faced in libraries to assemble the resources and tools of big data.It also makes a good impact on the use of big data analytics for researches and professionals in the field of library and information science.3)The purpose of the study is to analyze the views and capabilities of librarians for the implementation of big data analytics in academic libraries of Pakistan.The study also sets out to check the relationship between the required skills of librarians’ and the application of big data analytics.A survey was conducted to gather the required data from the target audience.The targeted population of the study was Head/In-charge library managers of Pakistani university libraries,which were 173 in total.All the respondents(academic librarians)were invited through an email to respond to the survey voluntarily.Out of 173 respondents from Higher Education(HEC)of Pakistan chartered university libraries,118 librarians completed the survey,68.2%that considered final,and after checking data,and recommended for analysis.To analyze the collected data,statistical technique Pearson-correlation was applied using statistical package for social science(SPSS)version 25 to know the strength of the mutual correlation of variables.The findings of the study show a strong correlation between the required competencies and skills of librarians for the implementation of big data analytics in academic libraries.In all variables of the study,the correlation was highly significant,except two of the variables,including "concept of big data" and "different forms of data." The study also reveals that most of the respondents are well aware of the concept of big data analytics".Moreover,they are using a large amount of data to carry out various library operations,including the acquisition,preservation,curation,and analysis of data.This third phase of the study is significant in the sense that it fills a substantial gap in the literature regarding the perspective of librarians on big data analytics.