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Publisher: Emerald   (Total: 345 journals)

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Showing 1 - 200 of 345 Journals sorted alphabetically
A Life in the Day     Hybrid Journal   (Followers: 12)
Academia Revista Latinoamericana de Administraci√≥n     Open Access   (Followers: 2, SJR: 0.178, CiteScore: 1)
Accounting Auditing & Accountability J.     Hybrid Journal   (Followers: 32, SJR: 1.71, CiteScore: 3)
Accounting Research J.     Hybrid Journal   (Followers: 25, SJR: 0.144, CiteScore: 0)
Accounting, Auditing and Accountability J.     Hybrid Journal   (Followers: 24, SJR: 2.187, CiteScore: 4)
Advances in Accounting Education     Hybrid Journal   (Followers: 16, SJR: 0.279, CiteScore: 0)
Advances in Appreciative Inquiry     Hybrid Journal   (Followers: 1, SJR: 0.451, CiteScore: 1)
Advances in Autism     Hybrid Journal   (Followers: 31, SJR: 0.222, CiteScore: 1)
Advances in Dual Diagnosis     Hybrid Journal   (Followers: 47, SJR: 0.21, CiteScore: 1)
Advances in Gender Research     Full-text available via subscription   (Followers: 4, SJR: 0.16, CiteScore: 0)
Advances in Intl. Marketing     Full-text available via subscription   (Followers: 6)
Advances in Mental Health and Intellectual Disabilities     Hybrid Journal   (Followers: 83, SJR: 0.296, CiteScore: 0)
Advances in Mental Health and Learning Disabilities     Hybrid Journal   (Followers: 31)
African J. of Economic and Management Studies     Hybrid Journal   (Followers: 10, SJR: 0.216, CiteScore: 1)
Agricultural Finance Review     Hybrid Journal   (SJR: 0.406, CiteScore: 1)
Aircraft Engineering and Aerospace Technology     Hybrid Journal   (Followers: 208, SJR: 0.354, CiteScore: 1)
American J. of Business     Hybrid Journal   (Followers: 17)
Annals in Social Responsibility     Full-text available via subscription  
Anti-Corrosion Methods and Materials     Hybrid Journal   (Followers: 11, SJR: 0.235, CiteScore: 1)
Arts and the Market     Hybrid Journal   (Followers: 9)
Asia Pacific J. of Innovation and Entrepreneurship     Open Access  
Asia Pacific J. of Marketing and Logistics     Hybrid Journal   (Followers: 8, SJR: 0.425, CiteScore: 1)
Asia-Pacific J. of Business Administration     Hybrid Journal   (Followers: 5, SJR: 0.234, CiteScore: 1)
Asian Association of Open Universities J.     Open Access   (Followers: 1)
Asian Education and Development Studies     Hybrid Journal   (Followers: 5, SJR: 0.233, CiteScore: 1)
Asian J. on Quality     Hybrid Journal   (Followers: 3)
Asian Review of Accounting     Hybrid Journal   (Followers: 2, SJR: 0.222, CiteScore: 1)
Aslib J. of Information Management     Hybrid Journal   (Followers: 30, SJR: 0.725, CiteScore: 2)
Aslib Proceedings     Hybrid Journal   (Followers: 304)
Assembly Automation     Hybrid Journal   (Followers: 2, SJR: 0.603, CiteScore: 2)
Baltic J. of Management     Hybrid Journal   (Followers: 3, SJR: 0.309, CiteScore: 1)
Benchmarking : An Intl. J.     Hybrid Journal   (Followers: 10, SJR: 0.559, CiteScore: 2)
British Food J.     Hybrid Journal   (Followers: 16, SJR: 0.5, CiteScore: 2)
Built Environment Project and Asset Management     Hybrid Journal   (Followers: 15, SJR: 0.46, CiteScore: 1)
Business Process Re-engineering & Management J.     Hybrid Journal   (Followers: 8)
Business Strategy Series     Hybrid Journal   (Followers: 6)
Career Development Intl.     Hybrid Journal   (Followers: 17, SJR: 0.527, CiteScore: 2)
China Agricultural Economic Review     Hybrid Journal   (Followers: 2, SJR: 0.31, CiteScore: 1)
China Finance Review Intl.     Hybrid Journal   (Followers: 5, SJR: 0.245, CiteScore: 0)
Chinese Management Studies     Hybrid Journal   (Followers: 4, SJR: 0.278, CiteScore: 1)
Circuit World     Hybrid Journal   (Followers: 16, SJR: 0.246, CiteScore: 1)
Collection Building     Hybrid Journal   (Followers: 11, SJR: 0.296, CiteScore: 1)
COMPEL: The Intl. J. for Computation and Mathematics in Electrical and Electronic Engineering     Hybrid Journal   (Followers: 3, SJR: 0.22, CiteScore: 1)
Competitiveness Review : An Intl. Business J. incorporating J. of Global Competitiveness     Hybrid Journal   (Followers: 5, SJR: 0.274, CiteScore: 1)
Construction Innovation: Information, Process, Management     Hybrid Journal   (Followers: 14, SJR: 0.731, CiteScore: 2)
Corporate Communications An Intl. J.     Hybrid Journal   (Followers: 7, SJR: 0.453, CiteScore: 1)
Corporate Governance Intl. J. of Business in Society     Hybrid Journal   (Followers: 7, SJR: 0.336, CiteScore: 1)
Critical Perspectives on Intl. Business     Hybrid Journal   (SJR: 0.378, CiteScore: 1)
Cross Cultural & Strategic Management     Hybrid Journal   (Followers: 8, SJR: 0.504, CiteScore: 2)
Development and Learning in Organizations     Hybrid Journal   (Followers: 8, SJR: 0.138, CiteScore: 0)
Digital Library Perspectives     Hybrid Journal   (Followers: 28, SJR: 0.341, CiteScore: 1)
Direct Marketing An Intl. J.     Hybrid Journal   (Followers: 6)
Disaster Prevention and Management     Hybrid Journal   (Followers: 21, SJR: 0.47, CiteScore: 1)
Drugs and Alcohol Today     Hybrid Journal   (Followers: 139, SJR: 0.245, CiteScore: 1)
Education + Training     Hybrid Journal   (Followers: 23)
Education, Business and Society : Contemporary Middle Eastern Issues     Hybrid Journal   (Followers: 1, SJR: 1.707, CiteScore: 3)
Emerald Emerging Markets Case Studies     Hybrid Journal   (Followers: 1)
Employee Relations     Hybrid Journal   (Followers: 8, SJR: 0.551, CiteScore: 2)
Engineering Computations     Hybrid Journal   (Followers: 3, SJR: 0.444, CiteScore: 1)
Engineering, Construction and Architectural Management     Hybrid Journal   (Followers: 10, SJR: 0.653, CiteScore: 2)
English Teaching: Practice & Critique     Hybrid Journal   (SJR: 0.417, CiteScore: 1)
Equal Opportunities Intl.     Hybrid Journal   (Followers: 3)
Equality, Diversity and Inclusion : An Intl. J.     Hybrid Journal   (Followers: 14, SJR: 0.5, CiteScore: 1)
EuroMed J. of Business     Hybrid Journal   (Followers: 1, SJR: 0.26, CiteScore: 1)
European Business Review     Hybrid Journal   (Followers: 8, SJR: 0.585, CiteScore: 3)
European J. of Innovation Management     Hybrid Journal   (Followers: 24, SJR: 0.454, CiteScore: 2)
European J. of Management and Business Economics     Open Access   (Followers: 1, SJR: 0.239, CiteScore: 1)
European J. of Marketing     Hybrid Journal   (Followers: 21, SJR: 0.971, CiteScore: 2)
European J. of Training and Development     Hybrid Journal   (Followers: 13, SJR: 0.477, CiteScore: 1)
Evidence-based HRM     Hybrid Journal   (Followers: 5, SJR: 0.537, CiteScore: 1)
Facilities     Hybrid Journal   (Followers: 3, SJR: 0.503, CiteScore: 2)
Foresight     Hybrid Journal   (Followers: 7, SJR: 0.34, CiteScore: 1)
Gender in Management : An Intl. J.     Hybrid Journal   (Followers: 20, SJR: 0.412, CiteScore: 1)
Grey Systems : Theory and Application     Hybrid Journal   (Followers: 1)
Health Education     Hybrid Journal   (Followers: 2, SJR: 0.421, CiteScore: 1)
Higher Education, Skills and Work-based Learning     Hybrid Journal   (Followers: 46, SJR: 0.426, CiteScore: 1)
History of Education Review     Hybrid Journal   (Followers: 12, SJR: 0.26, CiteScore: 0)
Housing, Care and Support     Hybrid Journal   (Followers: 8, SJR: 0.171, CiteScore: 0)
Human Resource Management Intl. Digest     Hybrid Journal   (Followers: 18, SJR: 0.129, CiteScore: 0)
Humanomics     Hybrid Journal   (Followers: 3, SJR: 0.333, CiteScore: 1)
IMP J.     Hybrid Journal  
Indian Growth and Development Review     Hybrid Journal   (SJR: 0.174, CiteScore: 0)
Industrial and Commercial Training     Hybrid Journal   (Followers: 5, SJR: 0.301, CiteScore: 1)
Industrial Lubrication and Tribology     Hybrid Journal   (Followers: 6, SJR: 0.334, CiteScore: 1)
Industrial Management & Data Systems     Hybrid Journal   (Followers: 7, SJR: 0.904, CiteScore: 3)
Industrial Robot An Intl. J.     Hybrid Journal   (Followers: 2, SJR: 0.318, CiteScore: 1)
Info     Hybrid Journal   (Followers: 1)
Information and Computer Security     Hybrid Journal   (Followers: 22, SJR: 0.307, CiteScore: 1)
Information Technology & People     Hybrid Journal   (Followers: 45, SJR: 0.671, CiteScore: 2)
Innovation & Management Review     Open Access  
Interactive Technology and Smart Education     Hybrid Journal   (Followers: 12, SJR: 0.191, CiteScore: 1)
Interlending & Document Supply     Hybrid Journal   (Followers: 62)
Internet Research     Hybrid Journal   (Followers: 37, SJR: 1.645, CiteScore: 5)
Intl. J. for Lesson and Learning Studies     Hybrid Journal   (Followers: 4, SJR: 0.324, CiteScore: 1)
Intl. J. for Researcher Development     Hybrid Journal   (Followers: 10)
Intl. J. of Accounting and Information Management     Hybrid Journal   (Followers: 9, SJR: 0.275, CiteScore: 1)
Intl. J. of Bank Marketing     Hybrid Journal   (Followers: 10, SJR: 0.654, CiteScore: 3)
Intl. J. of Climate Change Strategies and Management     Hybrid Journal   (Followers: 17, SJR: 0.353, CiteScore: 1)
Intl. J. of Clothing Science and Technology     Hybrid Journal   (Followers: 7, SJR: 0.318, CiteScore: 1)
Intl. J. of Commerce and Management     Hybrid Journal   (Followers: 1)
Intl. J. of Conflict Management     Hybrid Journal   (Followers: 14, SJR: 0.362, CiteScore: 1)
Intl. J. of Contemporary Hospitality Management     Hybrid Journal   (Followers: 14, SJR: 1.452, CiteScore: 4)
Intl. J. of Culture Tourism and Hospitality Research     Hybrid Journal   (Followers: 20, SJR: 0.339, CiteScore: 1)
Intl. J. of Development Issues     Hybrid Journal   (Followers: 9, SJR: 0.139, CiteScore: 0)
Intl. J. of Disaster Resilience in the Built Environment     Hybrid Journal   (Followers: 6, SJR: 0.387, CiteScore: 1)
Intl. J. of Educational Management     Hybrid Journal   (Followers: 5, SJR: 0.559, CiteScore: 1)
Intl. J. of Emergency Services     Hybrid Journal   (Followers: 9, SJR: 0.201, CiteScore: 1)
Intl. J. of Emerging Markets     Hybrid Journal   (Followers: 3, SJR: 0.474, CiteScore: 2)
Intl. J. of Energy Sector Management     Hybrid Journal   (Followers: 2, SJR: 0.349, CiteScore: 1)
Intl. J. of Entrepreneurial Behaviour & Research     Hybrid Journal   (Followers: 4, SJR: 0.629, CiteScore: 2)
Intl. J. of Event and Festival Management     Hybrid Journal   (Followers: 7, SJR: 0.388, CiteScore: 1)
Intl. J. of Gender and Entrepreneurship     Hybrid Journal   (Followers: 6, SJR: 0.445, CiteScore: 1)
Intl. J. of Health Care Quality Assurance     Hybrid Journal   (Followers: 12, SJR: 0.358, CiteScore: 1)
Intl. J. of Health Governance     Hybrid Journal   (Followers: 27, SJR: 0.247, CiteScore: 1)
Intl. J. of Housing Markets and Analysis     Hybrid Journal   (Followers: 9, SJR: 0.211, CiteScore: 1)
Intl. J. of Human Rights in Healthcare     Hybrid Journal   (Followers: 7, SJR: 0.205, CiteScore: 0)
Intl. J. of Information and Learning Technology     Hybrid Journal   (Followers: 8, SJR: 0.226, CiteScore: 1)
Intl. J. of Innovation Science     Hybrid Journal   (Followers: 11, SJR: 0.197, CiteScore: 1)
Intl. J. of Intelligent Computing and Cybernetics     Hybrid Journal   (Followers: 3, SJR: 0.214, CiteScore: 1)
Intl. J. of Intelligent Unmanned Systems     Hybrid Journal   (Followers: 4)
Intl. J. of Islamic and Middle Eastern Finance and Management     Hybrid Journal   (Followers: 9, SJR: 0.375, CiteScore: 1)
Intl. J. of Law and Management     Hybrid Journal   (Followers: 2, SJR: 0.217, CiteScore: 1)
Intl. J. of Law in the Built Environment     Hybrid Journal   (Followers: 3, SJR: 0.227, CiteScore: 0)
Intl. J. of Leadership in Public Services     Hybrid Journal   (Followers: 26)
Intl. J. of Lean Six Sigma     Hybrid Journal   (Followers: 7, SJR: 0.802, CiteScore: 3)
Intl. J. of Logistics Management     Hybrid Journal   (Followers: 10, SJR: 0.71, CiteScore: 2)
Intl. J. of Managerial Finance     Hybrid Journal   (Followers: 5, SJR: 0.203, CiteScore: 1)
Intl. J. of Managing Projects in Business     Hybrid Journal   (Followers: 2, SJR: 0.36, CiteScore: 2)
Intl. J. of Manpower     Hybrid Journal   (Followers: 2, SJR: 0.365, CiteScore: 1)
Intl. J. of Mentoring and Coaching in Education     Hybrid Journal   (Followers: 25, SJR: 0.426, CiteScore: 1)
Intl. J. of Migration, Health and Social Care     Hybrid Journal   (Followers: 12, SJR: 0.307, CiteScore: 1)
Intl. J. of Numerical Methods for Heat & Fluid Flow     Hybrid Journal   (Followers: 11, SJR: 0.697, CiteScore: 3)
Intl. J. of Operations & Production Management     Hybrid Journal   (Followers: 19, SJR: 2.052, CiteScore: 4)
Intl. J. of Organizational Analysis     Hybrid Journal   (Followers: 3, SJR: 0.268, CiteScore: 1)
Intl. J. of Pervasive Computing and Communications     Hybrid Journal   (Followers: 3, SJR: 0.138, CiteScore: 1)
Intl. J. of Pharmaceutical and Healthcare Marketing     Hybrid Journal   (Followers: 4, SJR: 0.25, CiteScore: 1)
Intl. J. of Physical Distribution & Logistics Management     Hybrid Journal   (Followers: 11, SJR: 1.821, CiteScore: 4)
Intl. J. of Prisoner Health     Hybrid Journal   (Followers: 8, SJR: 0.303, CiteScore: 1)
Intl. J. of Productivity and Performance Management     Hybrid Journal   (Followers: 7, SJR: 0.578, CiteScore: 2)
Intl. J. of Public Sector Management     Hybrid Journal   (Followers: 30, SJR: 0.438, CiteScore: 1)
Intl. J. of Quality & Reliability Management     Hybrid Journal   (Followers: 7, SJR: 0.492, CiteScore: 2)
Intl. J. of Quality and Service Sciences     Hybrid Journal   (Followers: 2, SJR: 0.309, CiteScore: 1)
Intl. J. of Retail & Distribution Management     Hybrid Journal   (Followers: 6, SJR: 0.742, CiteScore: 3)
Intl. J. of Service Industry Management     Hybrid Journal   (Followers: 2)
Intl. J. of Social Economics     Hybrid Journal   (Followers: 5, SJR: 0.225, CiteScore: 1)
Intl. J. of Sociology and Social Policy     Hybrid Journal   (Followers: 50, SJR: 0.3, CiteScore: 1)
Intl. J. of Sports Marketing and Sponsorship     Hybrid Journal   (Followers: 1, SJR: 0.269, CiteScore: 1)
Intl. J. of Structural Integrity     Hybrid Journal   (Followers: 2, SJR: 0.228, CiteScore: 0)
Intl. J. of Sustainability in Higher Education     Hybrid Journal   (Followers: 14, SJR: 0.502, CiteScore: 2)
Intl. J. of Tourism Cities     Hybrid Journal   (Followers: 2, SJR: 0.502, CiteScore: 0)
Intl. J. of Web Information Systems     Hybrid Journal   (Followers: 4, SJR: 0.186, CiteScore: 1)
Intl. J. of Wine Business Research     Hybrid Journal   (Followers: 8, SJR: 0.562, CiteScore: 2)
Intl. J. of Workplace Health Management     Hybrid Journal   (Followers: 10, SJR: 0.303, CiteScore: 1)
Intl. Marketing Review     Hybrid Journal   (Followers: 15, SJR: 0.895, CiteScore: 3)
Irish J. of Occupational Therapy     Open Access   (Followers: 5)
ISRA Intl. J. of Islamic Finance     Open Access  
J. for Multicultural Education     Hybrid Journal   (Followers: 1, SJR: 0.237, CiteScore: 1)
J. of Accounting & Organizational Change     Hybrid Journal   (Followers: 6, SJR: 0.301, CiteScore: 1)
J. of Accounting in Emerging Economies     Hybrid Journal   (Followers: 9)
J. of Adult Protection, The     Hybrid Journal   (Followers: 15, SJR: 0.314, CiteScore: 1)
J. of Advances in Management Research     Hybrid Journal   (Followers: 2)
J. of Aggression, Conflict and Peace Research     Hybrid Journal   (Followers: 44, SJR: 0.222, CiteScore: 1)
J. of Agribusiness in Developing and Emerging Economies     Hybrid Journal   (SJR: 0.108, CiteScore: 0)
J. of Applied Accounting Research     Hybrid Journal   (Followers: 17, SJR: 0.227, CiteScore: 1)
J. of Applied Research in Higher Education     Hybrid Journal   (Followers: 49, SJR: 0.2, CiteScore: 0)
J. of Asia Business Studies     Hybrid Journal   (Followers: 2, SJR: 0.245, CiteScore: 1)
J. of Assistive Technologies     Hybrid Journal   (Followers: 19)
J. of Business & Industrial Marketing     Hybrid Journal   (Followers: 10, SJR: 0.652, CiteScore: 2)
J. of Business Strategy     Hybrid Journal   (Followers: 11, SJR: 0.333, CiteScore: 1)
J. of Centrum Cathedra     Open Access  
J. of Children's Services     Hybrid Journal   (Followers: 5, SJR: 0.243, CiteScore: 1)
J. of Chinese Economic and Foreign Trade Studies     Hybrid Journal   (Followers: 1, SJR: 0.2, CiteScore: 0)
J. of Chinese Entrepreneurship     Hybrid Journal   (Followers: 4)
J. of Chinese Human Resource Management     Hybrid Journal   (Followers: 6, SJR: 0.173, CiteScore: 1)
J. of Communication Management     Hybrid Journal   (Followers: 6, SJR: 0.625, CiteScore: 1)
J. of Consumer Marketing     Hybrid Journal   (Followers: 19, SJR: 0.664, CiteScore: 2)
J. of Corporate Real Estate     Hybrid Journal   (Followers: 3, SJR: 0.368, CiteScore: 1)
J. of Criminal Psychology     Hybrid Journal   (Followers: 131, SJR: 0.268, CiteScore: 1)
J. of Criminological Research, Policy and Practice     Hybrid Journal   (Followers: 44, SJR: 0.254, CiteScore: 1)
J. of Cultural Heritage Management and Sustainable Development     Hybrid Journal   (Followers: 10, SJR: 0.257, CiteScore: 1)
J. of Documentation     Hybrid Journal   (Followers: 183, SJR: 0.613, CiteScore: 1)
J. of Economic and Administrative Sciences     Hybrid Journal   (Followers: 2)
J. of Economic Studies     Hybrid Journal   (Followers: 5, SJR: 0.733, CiteScore: 1)
J. of Economics, Finance and Administrative Science     Open Access   (Followers: 1, SJR: 0.217, CiteScore: 1)
J. of Educational Administration     Hybrid Journal   (Followers: 6, SJR: 1.252, CiteScore: 2)
J. of Enabling Technologies     Hybrid Journal   (Followers: 11, SJR: 0.369, CiteScore: 1)
J. of Engineering, Design and Technology     Hybrid Journal   (Followers: 16, SJR: 0.212, CiteScore: 1)
J. of Enterprise Information Management     Hybrid Journal   (Followers: 4, SJR: 0.827, CiteScore: 4)
J. of Enterprising Communities People and Places in the Global Economy     Hybrid Journal   (Followers: 1, SJR: 0.281, CiteScore: 1)
J. of Entrepreneurship and Public Policy     Hybrid Journal   (Followers: 8, SJR: 0.262, CiteScore: 1)
J. of European Industrial Training     Hybrid Journal   (Followers: 2)
J. of European Real Estate Research     Hybrid Journal   (Followers: 3, SJR: 0.268, CiteScore: 1)
J. of Facilities Management     Hybrid Journal   (Followers: 5, SJR: 0.33, CiteScore: 1)
J. of Family Business Management     Hybrid Journal   (Followers: 7)
J. of Fashion Marketing and Management     Hybrid Journal   (Followers: 12, SJR: 0.608, CiteScore: 2)
J. of Financial Crime     Hybrid Journal   (Followers: 366, SJR: 0.228, CiteScore: 0)
J. of Financial Economic Policy     Hybrid Journal   (Followers: 1, SJR: 0.186, CiteScore: 0)
J. of Financial Management of Property and Construction     Hybrid Journal   (Followers: 8, SJR: 0.309, CiteScore: 1)
J. of Financial Regulation and Compliance     Hybrid Journal   (Followers: 8, SJR: 0.159, CiteScore: 0)
J. of Financial Reporting and Accounting     Hybrid Journal   (Followers: 14)

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Journal Cover
International Journal of Intelligent Computing and Cybernetics
Journal Prestige (SJR): 0.214
Citation Impact (citeScore): 1
Number of Followers: 3  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1756-378X
Published by Emerald Homepage  [345 journals]
  • A two-phase multiobjective optimization for benchmarking and evaluating
           service quality in banks
    • Pages: 446 - 470
      Abstract: International Journal of Intelligent Computing and Cybernetics, Volume 11, Issue 4, Page 446-470, November 2018.
      Purpose Service quality is an evaluation of how well a delivered service meets customers’ expectations. The purpose of this paper is to provide a reliable scale of measurement for service quality in banks. Design/methodology/approach The SERVQUAL model was adopted based on a Banking Service Quality (BSQ) model and a two-phase multiobjective optimization model was designed. A structured questionnaire with five-point Likert scale was administered with a 93 percent response rate of 270 sample size. A total of 22 variables were considered based on the BSQ model and the significance of these variables to customers’ satisfaction were investigated. Factor analysis was used to extract the most influential factors on the measure of service quality and four factors were selected namely: they deliver when promised, precision on account statements, queues that move rapidly and sufficient number of ATMs per branch. In order to determine the reliability of the multiple Likert questions in the survey, Cronbach’s α was used indicating a scale reliability of 0.743. Moreover, multiple regression analysis was carried out on the selected factors to design an objective function for the design and evaluation of service quality model. The model design used for benchmarking was done using multiobjective genetic algorithm in MATLAB. Similarly, the model evaluation was done in a java interface using multiobjective particle swamp optimization. Findings The evaluation results validated the designed model and showed that the factors they deliver when promised and queues that move rapidly are a more reliable scale of measurement for customer’s satisfaction than the factors precision on account statements and sufficient number of ATMs per branch. Research limitations/implications The implication of the results is that effectiveness and assurance combined with access is a more significant factor for measuring customers’ satisfaction than tangibles based on the BSQ model. Originality/value The introduction of a two-phase optimization model for model benchmarking and evaluation as compared to ordinary factor analysis of the dimension constructs.
      Citation: International Journal of Intelligent Computing and Cybernetics
      PubDate: 2018-09-10T08:46:43Z
      DOI: 10.1108/IJICC-12-2017-0155
       
  • Autonomous navigation algorithm based on AUKF filter about fusion of
           geomagnetic and sunlight directions
    • Pages: 471 - 485
      Abstract: International Journal of Intelligent Computing and Cybernetics, Volume 11, Issue 4, Page 471-485, November 2018.
      Purpose The geomagnetic field vector is a function of the satellite’s position. The position and speed of the satellite can be determined by comparing the geomagnetic field vector measured by on board three-axis magnetometer with the standard value of the international geomagnetic field. The geomagnetic model has the disadvantages of uncertainty, low precision and long-term variability. Therefore, accuracy of autonomous navigation using the magnetometer is low. The purpose of this paper is to use the geomagnetic and sunlight information fusion algorithm to improve the orbit accuracy. Design/methodology/approach In this paper, an autonomous navigation method for low earth orbit satellite is studied by fusing geomagnetic and solar energy information. The algorithm selects the cosine value of the angle between the solar light vector and the geomagnetic vector, and the geomagnetic field intensity as observation. The Adaptive Unscented Kalman Filter (AUKF) filter is used to estimate the speed and position of the satellite, and the simulation research is carried out. This paper also made the same study using the UKF filter for comparison with the AUKF filter. Findings The algorithm of adding the sun direction vector information improves the positioning accuracy compared with the simple geomagnetic navigation, and the convergence and stability of the filter are better. The navigation error does not accumulate with time and has engineering application value. It also can be seen that AUKF filtering accuracy is better than UKF filtering accuracy. Research limitations/implications Geomagnetic navigation is greatly affected by the accuracy of magnetometer. This paper does not consider the spacecraft’s environmental interference with magnetic sensors. Practical implications Magnetometers and solar sensors are common sensors for micro-satellites. Near-Earth satellite orbit has abundant geomagnetic field resources. Therefore, the algorithm will have higher engineering significance in the practical application of low orbit micro-satellites orbit determination. Originality/value This paper introduces a satellite autonomous navigation algorithm. The AUKF geomagnetic filter algorithm using sunlight information can obviously improve the navigation accuracy and meet the basic requirements of low orbit small satellite orbit determination.
      Citation: International Journal of Intelligent Computing and Cybernetics
      PubDate: 2018-07-18T02:40:32Z
      DOI: 10.1108/IJICC-07-2017-0087
       
  • An improved morphological weighted dynamic similarity measurement
           algorithm for time series data
    • Pages: 486 - 495
      Abstract: International Journal of Intelligent Computing and Cybernetics, Volume 11, Issue 4, Page 486-495, November 2018.
      Purpose The similarity measurement of time series is an important research in time series detection, which is a basic work of time series clustering, anomaly discovery, prediction and many other data mining problems. The purpose of this paper is to design a new similarity measurement algorithm to improve the performance of the original similarity measurement algorithm. The subsequence morphological information is taken into account by the proposed algorithm, and time series is represented by a pattern, so the similarity measurement algorithm is more accurate. Design/methodology/approach Following some previous researches on similarity measurement, an improved method is presented. This new method combines morphological representation and dynamic time warping (DTW) technique to measure the similarities of time series. After the segmentation of time series data into segments, three parameter values of median, point number and slope are introduced into the improved distance measurement formula. The effectiveness of the morphological weighted DTW algorithm (MW-DTW) is demonstrated by the example of momentum wheel data of an aircraft attitude control system. Findings The improved method is insensitive to the distortion and expansion of time axis and can be used to detect the morphological changes of time series data. Simulation results confirm that this method proposed in this paper has a high accuracy of similarity measurement. Practical implications This improved method has been used to solve the problem of similarity measurement in time series, which is widely emerged in different fields of science and engineering, such as the field of control, measurement, monitoring, process signal processing and economic analysis. Originality/value In the similarity measurement of time series, the distance between sequences is often used as the only detection index. The results of similarity measurement should not be affected by the longitudinal or transverse stretching and translation changes of the sequence, so it is necessary to incorporate the morphological changes of the sequence into similarity measurement. The MW-DTW is more suitable for the actual situation. At the same time, the MW-DTW algorithm reduces the computational complexity by transforming the computational object to subsequences.
      Citation: International Journal of Intelligent Computing and Cybernetics
      PubDate: 2018-07-25T07:31:53Z
      DOI: 10.1108/IJICC-12-2016-0059
       
  • Adaptive trajectory tracking controller design for a quadrotor UAV with
           payload variation
    • Pages: 496 - 510
      Abstract: International Journal of Intelligent Computing and Cybernetics, Volume 11, Issue 4, Page 496-510, November 2018.
      Purpose The purpose of this paper is to enhance the quadrotor’s capability of short-distance delivery to satisfy the large demand for quadrotor, which is used for goods distribution in huge warehouses, under time-varying payload and external wind disturbance. Design/methodology/approach A trajectory tracking controller design based on the combination of an adaptive sliding mode control (ASMC) method and the active disturbance rejection control (ADRC) technique is proposed. Besides, an inner–outer loop control system structure is adopted. Findings Simulation results of different trajectory tracking verify the effectiveness and robustness of the proposed tracking control method under various conditions, including parameter uncertainty and external wind disturbance. The proposed control strategy ensures that quadrotor UAV is capable of tracking linear and spiral trajectory well whether it loads or unloads goods in the presence of the external wind disturbance. Originality/value The proposed method of designing a trajectory tracking controller is based on an integral ADRC and ASMC scheme so as to deal with the trajectory tracking problem for a quadrotor with payload variation.
      Citation: International Journal of Intelligent Computing and Cybernetics
      PubDate: 2018-07-25T07:37:35Z
      DOI: 10.1108/IJICC-04-2017-0029
       
  • A new method for the prediction of network security situations based on
           recurrent neural network with gated recurrent unit
    • Pages: 511 - 525
      Abstract: International Journal of Intelligent Computing and Cybernetics, Volume 11, Issue 4, Page 511-525, November 2018.
      Purpose The purpose of this paper is to solve the shortage of the existing methods for the prediction of network security situations (NSS). Because the conventional methods for the prediction of NSS, such as support vector machine, particle swarm optimization, etc., lack accuracy, robustness and efficiency, in this study, the authors propose a new method for the prediction of NSS based on recurrent neural network (RNN) with gated recurrent unit. Design/methodology/approach This method extracts internal and external information features from the original time-series network data for the first time. Then, the extracted features are applied to the deep RNN model for training and validation. After iteration and optimization, the accuracy of predictions of NSS will be obtained by the well-trained model, and the model is robust for the unstable network data. Findings Experiments on bench marked data set show that the proposed method obtains more accurate and robust prediction results than conventional models. Although the deep RNN models need more time consumption for training, they guarantee the accuracy and robustness of prediction in return for validation. Originality/value In the prediction of NSS time-series data, the proposed internal and external information features are well described the original data, and the employment of deep RNN model will outperform the state-of-the-arts models.
      Citation: International Journal of Intelligent Computing and Cybernetics
      PubDate: 2018-08-02T01:59:03Z
      DOI: 10.1108/IJICC-06-2017-0066
       
  • A two-stage skilled manpower planning model with demand uncertainty
    • Pages: 526 - 551
      Abstract: International Journal of Intelligent Computing and Cybernetics, Volume 11, Issue 4, Page 526-551, November 2018.
      Purpose Human resources are one of the most important and effective elements for companies. In other words, employees are a competitive advantage. This issue is more vital in the supply chains and production systems, because of high need for manpower in the different specification. Therefore, manpower planning is an important, essential and complex task. The purpose of this paper is to present a manpower planning model for production departments. The authors consider workforce with individual and hierarchical skills with skill substitution in the planning. Assuming workforce demand as a factor of uncertainty, a two-stage stochastic model is proposed. Design/methodology/approach To solve the proposed mixed-integer model in the real-world cases and large-scale problems, a Benders’ decomposition algorithm is introduced. Some test instances are solved, with scenarios generated by Monte Carlo method. For some test instances, to find the number of suitable scenarios, the authors use the sample average approximation method and to generate scenarios, the authors use Latin hypercube sampling method. Findings The results show a reasonable performance in terms of both quality and solution time. Finally, the paper concludes with some analysis of the results and suggestions for further research. Originality/value Researchers have attracted to other uncertainty factors such as costs and products demand in the literature, and have little attention to workforce demand as an uncertainty factor. Furthermore, most of the time, researchers assume that there is no difference between the education level and skill, while they are not necessarily equivalent. Hence, this paper enters these elements into decision making.
      Citation: International Journal of Intelligent Computing and Cybernetics
      PubDate: 2018-09-21T11:37:47Z
      DOI: 10.1108/IJICC-04-2018-0048
       
  • A new pose estimation method for non-cooperative spacecraft based on point
           cloud
    • Abstract: International Journal of Intelligent Computing and Cybernetics, Ahead of Print.
      Purpose On-orbit service technology is one of the key technologies of space manipulation activities such as spacecraft life extension, fault spacecraft capture, on-orbit debris removal and so on. It is known that the failure satellites, space debris and enemy spacecrafts in space are almost all non-cooperative targets. Relatively accurate pose estimation is critical to spatial operations, but also a recognized technical difficulty because of the undefined prior information of non-cooperative targets. With the rapid development of laser radar, the application of laser scanning equipment is increasing in the measurement of non-cooperative targets. It is necessary to research a new pose estimation method for non-cooperative targets based on 3D point cloud. The paper aims to discuss these issues. Design/methodology/approach In this paper, a method based on the inherent characteristics of a spacecraft is proposed for estimating the pose (position and attitude) of the spatial non-cooperative target. First, we need to preprocess the obtained point cloud to reduce noise and improve the quality of data. Second, according to the features of the satellite, a recognition system used for non-cooperative measurement is designed. The components which are common in the configuration of satellite are chosen as the recognized object. Finally, based on the identified object, the ICP algorithm is used to calculate the pose between two frames of point cloud in different times to finish pose estimation. Findings The new method enhances the matching speed and improves the accuracy of pose estimation compared with traditional methods by reducing the number of matching points. The recognition of components on non-cooperative spacecraft directly contributes to the space docking, on-orbit capture and relative navigation. Research limitations/implications Limited to the measurement distance of the laser radar, this paper considers the pose estimation for non-cooperative spacecraft in the close range. Practical implications The pose estimation method for non-cooperative spacecraft in this paper is mainly applied to close proximity space operations such as final rendezvous phase of spacecraft or ultra-close approaching phase of target capture. The system can recognize components needed to be capture and provide the relative pose of non-cooperative spacecraft. The method in this paper is more robust compared with the traditional single component recognition method and overall matching method when scanning of laser radar is not complete or the components are blocked. Originality/value This paper introduces a new pose estimation method for non-cooperative spacecraft based on point cloud. The experimental results show that the proposed method can effectively identify the features of non-cooperative targets and track their position and attitude. The method is robust to the noise and greatly improves the speed of pose estimation while guarantee the accuracy.
      Citation: International Journal of Intelligent Computing and Cybernetics
      PubDate: 2018-10-04T06:38:23Z
      DOI: 10.1108/IJICC-03-2018-0036
       
  • Critical links detection in stochastic networks: application to the
           transport networks
    • Abstract: International Journal of Intelligent Computing and Cybernetics, Ahead of Print.
      Purpose The purpose of this paper is to study a multiple-origin-multiple-destination variant of dynamic critical nodes detection problem (DCNDP) and dynamic critical links detection problem (DCLDP) in stochastic networks. DCNDP and DCLDP consist of identifying the subset of nodes and links, respectively, whose deletion maximizes the stochastic shortest paths between all origins–destinations pairs, in the graph modeling the transport network. The identification of such nodes (or links) helps to better control the road traffic and predict the necessary measures to avoid congestion. Design/methodology/approach A Markovian decision process is used to model the shortest path problem under dynamic traffic conditions. Effective algorithms to determine the critical nodes (links) while considering the dynamicity of the traffic network are provided. Also, sensitivity analysis toward capacity reduction for critical links is studied. Moreover, the complexity of the underlying algorithms is analyzed and the computational efficiency resulting from the decomposition operation of the network into communities is highlighted. Findings The numerical results demonstrate that the use of dynamic shortest path (time dependency) as a metric has a significant impact on the identification of critical nodes/links and the experiments conducted on real world networks highlight the importance of sensitive links to dynamically detect critical links and elaborate smart transport plans. Research limitations/implications The research in this paper also revealed several challenges, which call for future investigations. First, the authors have restricted our experimentation to a small network where the only focus is on the model behavior, in the absence of historical data. The authors intend to extend this study to very large network using real data. Second, the authors have considered only congestion to assess network’s criticality; future research on this topic may include other factors, mainly vulnerability. Practical implications Taking into consideration the dynamic and stochastic nature in problem modeling enables to be effective tools for real-time control of transportation networks. This leads to design optimized smart transport plans particularly in disaster management, to improve the emergency evacuation effeciency. Originality/value The paper provides a novel approach to solve critical nodes/links detection problems. In contrast to the majority of research works in the literature, the proposed model considers dynamicity and betweenness while taking into account the stochastic aspect of transport networks. This enables the approach to guide the traffic and analyze transport networks mainly under disaster conditions in which networks become highly dynamic.
      Citation: International Journal of Intelligent Computing and Cybernetics
      PubDate: 2018-10-03T08:02:14Z
      DOI: 10.1108/IJICC-04-2018-0055
       
 
 
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