Process fragmentation and port performance: Merging SNA and text mining

Research on express service defect evaluation based on semantic network diagram and SERVQUAL model

This paper constructs a defect evaluation model of express service, uses the text mining methods of web crawler, SVM (Support Vector Machine) emotion analysis and LDA (Linear Discriminant Analysis) topic model to capture and clean up the online negative comment data of express service, establishes a semantic network diagram, and uses LDA topic model to extract the characteristic words of defect topic. Based on SERVQUAL model, it can classify the subject characteristic words of express service defects from the dimensions of tangibility, reliability, responsiveness, assurance, empathy and economy, etc., calculate the degree value and attention value of express service defects, and establish IPA model for defect mapping and identify the improvement direction. The evaluation model constructed in this paper has reference value for evaluating the defects of service industry and improving service quality. It is found that the "responsiveness" defect is the primary improvement direction, and the reliability, assurance and economy are the secondary improvement defects. Among them, the "responsiveness" defect has five improvement detail defects. The evaluation model constructed in this paper has reference value for evaluating the defects of service industry and improving service quality.

Evolution of Knowledge Structure in an Emerging Field Based on a Triple Helix Model: the Case of Smart Factory

As an important emerging field of science and technology, smart factories have received attention from academia, industry, and the government. Currently, although some scholars have examined the research trends in the field of smart factories, we have not found any research on the analysis of the knowledge output of relevant organizations among smart factories. An urgent problem is whether cooperation between organizations with different characteristics will affect the overall development of intelligent factories. This study aimed to perform a comprehensive analysis of the knowledge content and structure of a smart factory and the characteristics of its knowledge production structure. We also evaluated whether the triple helix structure was stable, and whether the research topics of different issues were similar. The triple helix model was used to study three aspects of the knowledge structure of a smart factory: university, government, and industry. Furthermore, the research contents of different organizations were analyzed in detail using network analysis. It was found that research funding at the national level leads to a knowledge spillover effect. After 2015, a triple helix knowledge structure was formed in the field of smart factories, which maintained a certain stability until 2020. The output of triple helix cooperation research has a significant impact. University research focuses more extensively and intensively on technology, government research on macro aspects, and Industry 5.0 has become a hotspot in industry research. The government needs to provide new platforms to integrate and promote the development of smart factories.

A scholarly network of AI research with an information science focus: Global North and Global South perspectives

This paper primarily aims to provide a citation-based method for exploring the scholarly network of artificial intelligence (AI)-related research in the information science (IS) domain, especially from Global North (GN) and Global South (GS) perspectives. Three research objectives were addressed, namely (1) the publication patterns in the field, (2) the most influential articles and researched keywords in the field, and (3) the visualization of the scholarly network between GN and GS researchers between the years 2010 and 2020. On the basis of the PRISMA statement, longitudinal research data were retrieved from the Web of Science and analyzed. Thirty-two AI-related keywords were used to retrieve relevant quality articles. Finally, 149 articles accompanying the follow-up 8838 citing articles were identified as eligible sources. A co-citation network analysis was adopted to scientifically visualize the intellectual structure of AI research in GN and GS networks. The results revealed that the United States, Australia, and the United Kingdom are the most productive GN countries; by contrast, China and India are the most productive GS countries. Next, the 10 most frequently co-cited AI research articles in the IS domain were identified. Third, the scholarly networks of AI research in the GN and GS areas were visualized. Between 2010 and 2015, GN researchers in the IS domain focused on applied research involving intelligent systems (e.g., decision support systems); between 2016 and 2020, GS researchers focused on big data applications (e.g., geospatial big data research). Both GN and GS researchers focused on technology adoption research (e.g., AI-related products and services) throughout the investigated period. Overall, this paper reveals the intellectual structure of the scholarly network on AI research and several applications in the IS literature. The findings provide research-based evidence for expanding global AI research.

Digitalization in Maritime Transport and Seaports: Bibliometric, Content and Thematic Analysis

In this paper, a bibliometric, content and thematic analysis of digitalization in maritime transport and seaports was performed. The research was primarily motivated by the scarcity of similar works offering a comprehensive and recent literature analysis, the advancements of the maritime digitalization itself, and its influence on all related processes. The initial investigation phase considered 8178 publications, leading through the research steps to the final inclusion of 280 papers, the thematic and content analysis of which were performed using various bibliometric tools. The research encompassed various criteria, ranging through databases, keywords, topics, research areas and others. The resulting concept map emphasized the main concepts that digitalization in maritime transport relies on, or strives towards. The aim of the study was to address the fundamental research questions, with the tendency to define the main key points in the current maritime transport and seaport digitalization process. It can be concluded that an increasing number of authors recognize the importance of new digital technologies in maritime transport and seaports. However, with new digital technologies come specific risks such as spoofing or data manipulation that need to be further analyzed.

Estimation of the knowledge management model for performance measurement in university libraries

Purpose

The study aims to expand the literature on evaluating the performance of professionals and academic libraries, rationalizing management and providing reliable services to the academic community. The performance assessment model covers the four components (management competence, professional experience, financial add/projects and library services) in the context of the knowledge management model.

Design/methodology/approach

Based on quantitative data, the study defines a set of assumptions for testing the four components of performance evaluation within a knowledge management framework to develop appropriate and robust models for improving employee performance and library services. The structural equation model has been applied to sample data from 339 administrative librarians at 190 universities in Pakistan.

Findings

Statistical evidence confirms that the applicability of the proposed performance-based model enhances management competence, makes accurate decisions, develops professional skills and strengthens human resource organization and knowledge management techniques in developing the efficiency of academic libraries.

Practical implications

In the long term, academic leaders and policymakers value investment in the professional development of top library management as they participate in the decision-making process. Organizing training for service employees, supporting innovative research projects and providing library technology infrastructures ultimately improve academic performance and research when integrated into the knowledge management model.

Originality/value

So far, comprehensive literature on performance and knowledge management has been published separately. However, based on the key data collected by senior library administrators using the structured research questionnaire, the comprehensive performance evaluation research based on a knowledge management model is innovative to improve academic library services and close the literature gap.

An Experimental Analytics on Discovering Work Transference Networks from Workflow Enactment Event Logs

Work transference network is a type of enterprise social network centered on the interactions among performers participating in the workflow processes. It is thought that the work transference networks hidden in workflow enactment histories are able to denote not only the structure of the enterprise social network among performers but also imply the degrees of relevancy and intensity between them. The purpose of this paper is to devise a framework that can discover and analyze work transference networks from workflow enactment event logs. The framework includes a series of conceptual definitions to formally describe the overall procedure of the network discovery. To support this conceptual framework, we implement a system that provides functionalities for the discovery, analysis and visualization steps. As a sanity check for the framework, we carry out a mining experiment on a dataset of real-life event logs by using the implemented system. The experiment results show that the framework is valid in discovering transference networks correctly and providing primitive knowledge pertaining to the discovered networks. Finally, we expect that the analytics of the work transference network facilitates assessing the workflow fidelity in human resource planning and its observed performance, and eventually enhances the workflow process from the organizational aspect.