Efficiency Measurement and Improvement Projection of container terminals

Data Envelopment Analysis (DEA) is a multifactor productivity measurement tool and is used in assessing the relative efficiency of homogenous units. DEA assumes that the decision making unit (DMU) are homogenous in their environment and avoids any error or noise in measurements. Container terminals, which act as an interface between the sea and the shore, for loading and unloading of containers from ship to shore and vice-versa, may operate with its own attributes and goals. Every container terminal is characterized by some physical values that represent different relevant properties of the terminal. DEA, if employed alone, to measure the efficiency and set the bench mark for inefficient terminals gives biased result because all the container terminals may not be inherently similar. In order to overcome this shortcoming, in this paper, two important fields of information technology: data mining and data envelopment analysis is integrated to provide a new tool to appropriately set bench mark for inefficient terminals and prioritize the technical inputs that have the greatest impact needed to improve the inefficient terminals which otherwise is not possible with DEA alone.Abstract = i Contents = ii List of Tables = iii List of Figures = iv 1. Introduction = 1 1.1 Research Background = 1 1.2 Research Objectives = 2 1.3 Organization of the Chapters = 3 2. Literature Review = 4 2.1 Data Envelopment Analysis: The Concept = 4 2.2 Review of Efficiency Measures in Port Sector = 10 3. Efficiency Measurement of Container Ports = 13 3.1 Research Design = 13 3.2 Research Methodology = 14 4. Data Analysis = 30 4.1 Evaluating the Efficiency of Container Terminals using DEA = 30 4.2 Determining the Improvement Path of Inefficient Terminals = 40 5. Conclusion = 44 6. References = 4

Decision support systems (DSS) for wastewater treatment plants: a review of the state of the art

The use of decision support systems (DSS) allows integrating all the issues related with sustainable developmentin view of providing a useful support to solve multi-scenario problems. In this work an extensive review on theDSSs applied to wastewater treatment plants (WWTPs) is presented. The main aim of the work is to provide anupdated compendium on DSSs in view of supporting researchers and engineers on the selection of the mostsuitable method to address their management/operation/design problems. Results showed that DSSs weremostly used as a comprehensive tool that is capable of integrating several data and a multi-criteria perspective inorder to provide more reliable results. Only one energy-focused DSS was found in literature, while DSSs based onquality and operational issues are very often applied to site-specific conditions. Finally, it would be important toencourage the development of more user-friendly DSSs to increase general interest and usability.This work is part of a research project supported by grant of the Italian Ministry of Education, University and Research (MIUR) through the Research project of national interest PRIN2012 (D.M. 28 December 2012 n. 957/Ric – Prot. 2012PTZAMC) entitled “Energy consumption and Greenhouse Gas (GHG) emissions in the wastewater treatment plants: a decision support system for planning and management – http://ghgfromwwtp.unipa.it” in which the first author is the Principal Investigator. In addition, some coauthors acknowledge the partial support of the Industrial Doctorate Programme (2017-DI-006) and the Research Consolidated Groups/Centres Grant (2017 SGR 574) from the Catalan Agency of University and Research Grants Management (AGAUR), from Catalan Government.Peer ReviewedPostprint (author's final draft

Risk management and risk control for state-owned firms of China

As global economic integration deepens and enterprises scale up their business, the enterprise groups have become the mainstream of the company's development form. Subsidiaries of the Company have grown in size and increasingly diversified. Thus how does the parent Company control its subsidiaries effectively has become an urgent challenge, especially for the state-owned enterprises in China. This thesis studies the management and control of state-owned enterprises in China, carrying certain theoretical and practical significance. The research examined the theory and mechanism of management of SOEs, and evaluation on employee performance. It also analyzed performance evaluation, coordination and risk control strategies of SOEs' subsidiaries. The same studies were repeated on state-owned enterprise groups and extended to the strategies of risk management and risk control. The thesis first examined the conundrum of effective cooperation between subsidiaries of different departments and the parent company for efficient allocation of resources. To tackle this headache, the IAHP and DEA model were adopted to help group decision makers better measure the performance of employees and organizations. The thesis used the Balanced Scorecard (BSC) tool as the main principle and the combination of fuzzy mathematics and Delphi and entropy weight methods as the main methodology to assess the performance. In addition, a novel method of using multi-reasoning, multi-dimensional and dynamic factors was developed to assess the performance of SOE employees, and this method was proven to be effective. Moreover, the super-efficiency DEA model which takes into account work performance, work ability, work attitude, job potential and other factors in the evaluation on employee performance was developed and tested. Finally, risk map for SOEs was proposed and evaluated

Application of DEA in benchmarking: a systematic literature review from 2003–2020

Benchmarking is an effective method for organizations to increase their productivity, quality of products, reliability of processes or services. The organization may make a comparison between its performance and that of the peers from benchmarking, and recognize their advantages as well as disadvantages. The main objective of the present systematic literature review has been the study of DEA benchmarking process. Therefore, it examined and gave a summary of various DEA models applied worldwide to improve benchmarking. Accordingly, a list of published academic papers that appeared in high-ranking journals between 2003 and February 2020 was collected for a systematic review of the DEA benchmarking application. Consequently, the papers selected have been classified according to year of publication, purpose of research, outcomes and results. This study has identified eight major applications including: transportation, service sector, product planning, maintenance, hotel industry, education, distribution and environmental factors. They take up a total of 82% of all application-embedded papers. Among all the applications, the highest recent development has been in both the transportation and service sectors. Results showed higher potential of DEA as a suitable evaluation method for the further benchmarking researches, wherein the production feature between outputs and inputs has been practically lacked or very hard to obtain. First published online 4 January 202

The state of the art development of AHP (1979-2017): A literature review with a social network analysis

Although many papers describe the evolution of the analytic hierarchy process (AHP), most adopt a subjective approach. This paper examines the pattern of development of the AHP research field using social network analysis and scientometrics, and identifies its intellectual structure. The objectives are: (i) to trace the pattern of development of AHP research; (ii) to identify the patterns of collaboration among authors; (iii) to identify the most important papers underpinning the development of AHP; and (iv) to discover recent areas of interest. We analyse two types of networks: social networks, that is, co-authorship networks, and cognitive mapping or the network of disciplines affected by AHP. Our analyses are based on 8441 papers published between 1979 and 2017, retrieved from the ISI Web of Science database. To provide a longitudinal perspective on the pattern of evolution of AHP, we analyse these two types of networks during the three periods 1979?1990, 1991?2001 and 2002?2017. We provide some basic statistics on AHP journals and researchers, review the main topics and applications of integrated AHPs and provide direction for future research by highlighting some open questions

Creating public value in information and communication technology: a learning analytics approach

This thesis contributes to the ongoing global discourse in ICT4D on ICT and its effect on socio-economic development in both theory and practice. The thesis comprises five studies presented logically from chapters 5 to 9. The thesis employs Mixed Methods research methodology within the Critical Realist epistemological perspective in Information Systems Research. Studies 1-4 employ different quantitative research and analytical methods while study 5 employs a qualitative research and analytical method. Study 1 proposes and operationalizes a predictive analytics framework in Learning Analytics by using a case study of the Computer Science Department of the University of Jos, Nigeria. Multiple Linear Regression was used with the aid of the Statistical Package for Social Sciences (SPSS) analysis tool. Statistical Hypothesis testing was then used to validate the model with a 5% level of significance. Results show how predictive learning analytics can be successfully operationalized and used for predicting students’ academic performances. In Study 2 the relative efficiency of ICT infrastructure utilization with respect to the educational component of the Human Development Index (HDI) is investigated. A Novel conceptual model is proposed and the Data Envelopment Analysis (DEA) methodology is used to measure the relative efficiency of the components of ICT infrastructure (Inputs) and the components of education (Outputs). Ordinary Least Squares (OLS) Regression Analysis is used to determine the effect of ICT infrastructure on Educational Attainment/Adult Literacy Rates. Results show a strong positive effect of ICT infrastructure on educational attainment and adult literacy rates, a strong correlation between this infrastructure and literacy rates as well as provide a theoretical support for the argument of increasing ICT infrastructure to provide an increase in human development especially within the educational context. In Study 3 the relative efficiency and productivity of ICT Infrastructure Utilization in Education are examined. The research employs the Data Envelopment Analysis (DEA) and Malmquist Index (MI), well established non-parametric data analysis methodologies, applied to archival data on International countries divided into Arab States, Europe, Sub-Saharan Africa and World regions. Ordinary Least Squares (OLS) Regression analysis is applied to determine the effect of ICT infrastructure on Adult Literacy Rates. Findings show a relatively efficient utilization and steady increase in productivity for the regions but with only Europe and the Arab States currently operating in a state of positive growth in productivity. A strong positive effect of ICT infrastructure on Adult Literacy Rates is also observed. Study 4 investigates the efficiency and productivity of ICT utilization in public value creation with respect to Adult Literacy Rates. The research employs Data Envelopment Analysis (DEA) and Malmquist Index (MI), well established non-parametric data analysis methodologies, applied to archival data on International countries divided into Arab States, Europe, Sub-Saharan Africa and World regions. Findings show a relatively efficient utilization of ICT in public value creation but an average decline in productivity levels. Finally, in Study 5 a Critical Discourse Analysis (CDA) on the UNDP Human Development Research Reports from 2010-2016 is carried out to determine whether or not any public value is created or derived from the policy directions being put forward and their subsequent implementations. The CDA is operationalized by Habermas’ Theory of Communicative Action (TCA). Findings show that Public Value is indeed being created and at the core of the policy directions being called for in these reports.School of ComputingPh.D. (Information Systems

The state of the art development of AHP (1979-2017): a literature review with a social network analysis

Although many papers describe the evolution of the analytic hierarchy process (AHP), most adopt a subjective approach. This paper examines the pattern of development of the AHP research field using social network analysis and scientometrics, and identifies its intellectual structure. The objectives are: (i) to trace the pattern of development of AHP research; (ii) to identify the patterns of collaboration among authors; (iii) to identify the most important papers underpinning the development of AHP; and (iv) to discover recent areas of interest. We analyse two types of networks: social networks, that is, co-authorship networks, and cognitive mapping or the network of disciplines affected by AHP. Our analyses are based on 8441 papers published between 1979 and 2017, retrieved from the ISI Web of Science database. To provide a longitudinal perspective on the pattern of evolution of AHP, we analyse these two types of networks during the three periods 1979–1990, 1991–2001 and 2002–2017. We provide some basic statistics on AHP journals and researchers, review the main topics and applications of integrated AHPs and provide direction for future research by highlighting some open questions

New Fundamental Technologies in Data Mining

The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by "Data Mining" address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data mining