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Journal articles on the topic 'Information systems Quality'

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Published: 4 June 2021
Last updated: 3 February 2022

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1

Menkus, Belden. "Information Systems Quality Assurance Enhances Information Systems Security." EDPACS 17, no. 12 (June 1990): 6–10. http://dx.doi.org/10.1080/07366989009450603.

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2

Nelson, Klara G. "Global Information Systems Quality." Journal of Global Information Management 4, no. 4 (October 1996): 4–15. http://dx.doi.org/10.4018/jgim.1996100101.

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3

Andersson, Thorbjorn, and Liisa A. von Hellens. "Information systems work quality." Information and Software Technology 39, no. 12 (January 1997): 837–44. http://dx.doi.org/10.1016/s0950-5849(97)00042-6.

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4

Andersson, Thorbjorn, and Liisa A. von Hellens. "Information systems work quality." Computer Standards & Interfaces 21, no. 2 (June 1999): 166. http://dx.doi.org/10.1016/s0920-5489(99)92179-7.

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5

Wilson, Cathleen Krueger. "Quality-driven information systems." Journal of Nursing Care Quality 7, no. 1 (October 1992): 7–15. http://dx.doi.org/10.1097/00001786-199210000-00004.

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6

Prior, Derek. "Quality control information systems." Quality and Reliability Engineering International 1, no. 4 (October 1985): 227–34. http://dx.doi.org/10.1002/qre.4680010404.

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7

Forza, C. "Quality information systems and quality management." Industrial Management & Data Systems 95, no. 2 (March 1995): 6–14. http://dx.doi.org/10.1108/02635579510082502.

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8

Havelka, Douglas, Steve G. Sutton, and Vicky Arnold. "Information Systems Quality Assurance: Users Perceptions Of Information Systems And Systems Design Quality Factors." Review of Business Information Systems (RBIS) 5, no. 2 (April 1, 2001): 49–62. http://dx.doi.org/10.19030/rbis.v5i2.5350.

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With the emergence of information systems reliability and quality assurance and its perceived revenue generation in the billions of dollars, the accounting profession has developed a keen interest in improving the understanding of the underlying factors affecting information quality. This paper expands the Havelka et al. (1999) study, which explored the key quality factors impacting the information requirements definition stage of the systems development process. The extensions explored within the current paper focus on the relationship between users perceptions toward information systems and key quality factors for systems design. In particular, user involvement and user satisfaction are examined for their potential impact on the weightings of quality factors. The results indicate that users perceptions toward information systems do influence their perceptions of the importance of the key quality factors for systems design. This result may allow practitioners to tailor a project management strategy for IS development based on targeted users current perceptions of information systems.
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9

Flores, Javier, and Jun Sun. "Information Quality Awareness and Information Quality Practice." Journal of Data and Information Quality 10, no. 1 (May 30, 2018): 1–18. http://dx.doi.org/10.1145/3182182.

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10

Zoto, Erjon. "Data quality and accounting information systems: Actual performance in Albania." Perspectives of Innovations, Economics and Business 14, no. 1 (February 6, 2014): 34–41. http://dx.doi.org/10.15208/pieb.2014.04.

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11

Niland, J. C., L. Rouse, and D. C. Stahl. "An Informatics Blueprint for Healthcare Quality Information Systems." Journal of the American Medical Informatics Association 13, no. 4 (July 1, 2006): 402–17. http://dx.doi.org/10.1197/jamia.m2050.

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12

Paper, David, and James A. Rogder. "Quality information systems through people." Journal of High Technology Management Research 7, no. 2 (September 1996): 269–82. http://dx.doi.org/10.1016/s1047-8310(96)90008-5.

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13

Touq, Ahmed Bin, and Anthony Ijeh. "Information Quality in Participatory Systems." International Journal of Knowledge-Based Organizations 7, no. 4 (October 2017): 19–31. http://dx.doi.org/10.4018/ijkbo.2017100102.

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The study explores the impact of participatory systems on information quality using Abu Dhabi as a case study. Participatory systems are used for deciding social change to affect residents and citizens positively. The case study research method was used to examine information quality in a participatory system. Content of the participatory system was assessed for information quality and it was found to support theoretical claims that Abu Dhabi residents and citizens participate in building sustainable competition using participatory systems. The limitations of the study are found in its focus on a single application, the app CityGuard. Through examining the use of CityGuard, specific issues were recognized which allowed the definition of steps on how its use could impact social change more positively. This paper presents findings from the use of CityGuard as a public participatory tool.
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14

Duraivelu, K. "Quality metrics for information systems." OPSEARCH 41, no. 3 (September 2004): 200–207. http://dx.doi.org/10.1007/bf03398845.

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15

Eilon, Samuel. "Measuring quality of information systems." Omega 21, no. 2 (March 1993): 135–38. http://dx.doi.org/10.1016/0305-0483(93)90046-n.

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16

E. M. Khalil, Omar, Diane M. Strong, Beverly K. Kahn, and Leo L. Pipino. "Teaching Information Quality in Information Systems Undergraduate Education." Informing Science: The International Journal of an Emerging Transdiscipline 2 (1999): 053–59. http://dx.doi.org/10.28945/601.

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17

Salmela, H. "From information systems quality to sustainable business quality." Information and Software Technology 39, no. 12 (January 1997): 819–25. http://dx.doi.org/10.1016/s0950-5849(97)00040-2.

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18

English, Larry P. "Information Quality." Journal of Database Management 16, no. 1 (January 2005): 18–32. http://dx.doi.org/10.4018/jdm.2005010102.

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19

Kučera, M., A. Látečková, and P. Szovics. "Improving quality of economic information systems to ensure competitive advantage for companies." Agricultural Economics (Zemědělská ekonomika) 50, No. 8 (February 24, 2012): 365–68. http://dx.doi.org/10.17221/5218-agricecon.

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A prosperous company with a goal to maintain competitiveness in a strong international environment should eliminate obsolete management methods and innovate the information system used in the company with the application of effective economic software. This paper deals with the current situation of economic software or Enterprise Resource Planning (ERP) in companies and opportunities and advantages of using software in the area of cost management. Economic gains in practice are also discussed in this contribution. 
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20

Elfa Kiswara Rahmantya, Yanneri, Ubud Salim, Djumahir, and Atim Djazuli. "Hospital’s competitive advantage through service quality, information systems and Islamic work ethics." Problems and Perspectives in Management 17, no. 2 (May 17, 2019): 193–204. http://dx.doi.org/10.21511/ppm.17(2).2019.14.

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The aim of this study is to analyze and measure the factors that influence competitive advantage seen from the quality of services, Islamic work ethics and information systems. The population of this study was all patients of BPJS participants in hospitals in Kuningan, West Java. This study uses a proportional random sampling technique to determine the sample. The respondents of this study were 115 respondents. Analysis was carried out using Partial Least Square (PLS). Results of the study prove that Islamic work ethics are positive and significant to competitive advantage. Competitive advantage can also be influenced by the hospital information system. Service quality also has a positive and significant influence on competitive advantage. Islamic work ethics, information system and service quality is a factor that can build competitive advantage in hospitals in Kuningan.
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21

Selbmann, H. K., and B. Pietsch-Breitfeld. "HOSPITAL INFORMATION SYSTEMS AND QUALITY ASSURANCE." International Journal for Quality in Health Care 2, no. 3-4 (September 1, 1990): 335–44. http://dx.doi.org/10.1093/intqhc/2.3-4.335.

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22

Zahedi, Fatemeh (Mariam). "Quality information systems: a unifying framework." International Journal of Technology Management 16, no. 4/5/6 (1998): 446. http://dx.doi.org/10.1504/ijtm.1998.002683.

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23

Anonymous. "Design of water quality information systems." Eos, Transactions American Geophysical Union 70, no. 29 (1989): 714. http://dx.doi.org/10.1029/89eo00226.

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24

Sylla, Cheickna. "Quality assurance systems information requirements planning." Computers & Industrial Engineering 15, no. 1-4 (January 1988): 302–6. http://dx.doi.org/10.1016/0360-8352(88)90103-9.

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25

Sargent, P. "Data quality in materials information systems." Computer-Aided Design 24, no. 9 (September 1992): 477–90. http://dx.doi.org/10.1016/0010-4485(92)90028-9.

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26

Stawowy, Marek, Stanisław Duer, Jacek Paś, and Wojciech Wawrzyński. "Determining Information Quality in ICT Systems." Energies 14, no. 17 (September 5, 2021): 5549. http://dx.doi.org/10.3390/en14175549.

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The article deals with the estimation of information quality (IQ) in information and communication technologies (ICT) systems. A number of recent publications were analyzed, as well as ISO standards concerning quality and information quality. Due to the limitations of the known methods of estimating IQ, the authors present their own proprietary concept based on multidimensional and multi-layer modeling using methods of estimating uncertainty. The modeling proposed in this publication uses sixteen dimensions of quality known from the literature. The features of dimensions are taken into account as another layer and information states as successive steps in the IQ model. An example of calculations is also presented in which the mathematical evidence method used in estimating the uncertainty is extended to the modeling of dependent elements. The article also presents a simulation based on the presented example. This simulation shows the assumed dependencies between the output and input values.
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27

Kesharwani, Ankit, Venkatesh Mani, Jighyasu Gaur, Jighyasu Gaur, Samuel Fosso Wamba, and Sachin S. Kamble. "Service Quality Measurement in Information Systems." Journal of Global Information Management 29, no. 6 (November 2021): 1–19. http://dx.doi.org/10.4018/jgim.20211101.oa30.

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Traditionally measurements of service quality have followed the expectation-disconfirmation approach. Further, previous studies have shown that negative disconfirmation is more influential than positive disconfirmation. In this research, we hypothesized information systems(IS) service quality scales based on the dimensionality of the expectation-disconfirmation (ED) and desire-disconfirmation (DD) approach. Using the SERVQUAL+ instrument and data collected from 321 IS users, we developed ED and DD based IS service quality scales using contemporary methods, such as LISREL-based CFA. We have proposed and empirically validated the following two new IS service quality constructs: Service Adequacy (difference of expected service and perceived service) and Service Superiority (difference of desired service and perceived service). Our results indicate that both measures have shown better predictive power than earlier scales like SERVQUAL+ and the IS ZOT scales. We have outlined several implications of ED and DD scales to practice and research.
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28

Wang, Shouhong, and Hai Wang. "Information quality chain analysis for total information quality management." International Journal of Information Quality 2, no. 1 (2008): 4. http://dx.doi.org/10.1504/ijiq.2008.019560.

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29

Talburt, John, Therese L. Williams, Thomas C. Redman, and David Becker. "Information quality research challenge." Journal of Data and Information Quality 5, no. 1-2 (September 4, 2014): 1–3. http://dx.doi.org/10.1145/2629603.

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30

Lukyanenko, Roman. "Information Quality Research Challenge." Journal of Data and Information Quality 7, no. 1-2 (June 6, 2016): 1–3. http://dx.doi.org/10.1145/2856038.

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31

Davies, Mark A. P. "Perceived Information Quality." Journal of International Consumer Marketing 13, no. 4 (June 2001): 29–50. http://dx.doi.org/10.1300/j046v13n04_03.

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32

Lukyanenko, Roman, and Jeffrey Parsons. "Information Quality Research Challenge: Adapting Information Quality Principles to User-Generated Content." Journal of Data and Information Quality 6, no. 1 (March 4, 2015): 1–3. http://dx.doi.org/10.1145/2723166.

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33

Thakuriah, Piyushimita (Vonu), and Ashish Sen. "Quality of information given by advanced traveler information systems." Transportation Research Part C: Emerging Technologies 4, no. 5 (October 1996): 249–66. http://dx.doi.org/10.1016/s0968-090x(97)82900-2.

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34

Wongsim, Manirath. "EXPLORING INNOVATIVE INFORMATION QUALITY IN ACCOUNTING INFORMATION SYSTEMS ADOPTION." Journal of Academy of Business and Economics 14, no. 2 (June 1, 2014): 137–46. http://dx.doi.org/10.18374/jabe-14-2.8.

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35

Ballou, Donald, Richard Wang, Harold Pazer, and Giri Kumar Tayi. "Modeling Information Manufacturing Systems to Determine Information Product Quality." Management Science 44, no. 4 (April 1998): 462–84. http://dx.doi.org/10.1287/mnsc.44.4.462.

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36

Arinze, Bay, and Cheickna Sylla. "Information derivability analysis for quality assurance information management systems." Computers & Industrial Engineering 19, no. 1-4 (January 1990): 249–53. http://dx.doi.org/10.1016/0360-8352(90)90115-3.

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37

Rajendrakumar, Barot Mukti. "Evaluation of Critical Success Factors for Accounting Information Systems Data Quality in Gujarat." International Journal of Scientific Research 3, no. 2 (June 1, 2012): 151–53. http://dx.doi.org/10.15373/22778179/feb2014/49.

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38

Salaün, Yvette, and Karine Flores. "Information quality:." International Journal of Information Management 21, no. 1 (February 2001): 21–37. http://dx.doi.org/10.1016/s0268-4012(00)00048-7.

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39

Biran, Dov, Michael H. Zack, and Richard J. Briotta. "Competitive intelligence and information quality." Journal of Data and Information Quality 4, no. 3 (May 2013): 1–20. http://dx.doi.org/10.1145/2458517.2458520.

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40

Suryn, Witold, and Paul-Olivier Trudeau. "Information Systems Typology According to Quality Attributes." International Journal of Human Capital and Information Technology Professionals 3, no. 2 (April 2012): 16–24. http://dx.doi.org/10.4018/jhcitp.2012040102.

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Information systems support the way organizations drive their businesses and people conduct their lives. To execute this important task efficiently the quality of these systems must equal their importance. This article presents a topology of Information Systems classification according to their purpose. Each type is further divided into sub-categories representing features that enable users to drive their business and reach their goals. This paper summarizes the quality attributes that may be considered as most important and relevant to each type of information system of the classification.
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41

Chryssanthou, Anargyros, Iraklis Varlamis, John Constantine Sarivougioukas, and Ioannis Apostolakis. "Hospital Information Systems Replacement and Healthcare Quality." International Journal of Reliable and Quality E-Healthcare 1, no. 3 (July 2012): 1–12. http://dx.doi.org/10.4018/ijrqeh.2012070101.

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The aim of this paper is to develop a methodology for deciding when a Hospital Information System (HIS) must be replaced and in addition to discuss how the decision for system replacement affects the quality of healthcare services. In the hypothesis, the Hospital IS has been in operation for a period of time and the Hospital managers have to choose between the replacement with a new Information System (IS) and the continuation of its use. Leaving aside the economic factors concerning the return of a possible investment, the decision is still difficult and will be based on scientific and technological factors. The proposed methodology employs confidential information from the Hospital, which relates to the system operation and usability, the satisfaction of doctors and patients, etc. It also examines the entire working environment and common factors that affect the choice of Hospital managers (e.g., financial constraints).
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42

Chao, Li, Zhou Hui, and Zhou Xiaofeng. "Data quality assessment in hydrological information systems." Journal of Hydroinformatics 17, no. 4 (March 27, 2015): 640–61. http://dx.doi.org/10.2166/hydro.2015.042.

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The hydrological data fed to hydrological decision support systems might be untimely, incomplete, inconsistent or illogical due to network congestion, low performance of servers, instrument failures, human errors, etc. It is imperative to assess, monitor and even control the quality of hydrological data residing in or acquired from each link of a hydrological data supply chain. However, the traditional quality management of hydrological data has focused mainly on intrinsic quality problems, such as outlier detection, nullity interpolation, consistency, completeness, etc., and could not be used to assess the quality of application – that is, consumed data in the form of data supply chain and with a granularity of tasks. To achieve these objectives, we first present a methodology to derive quality dimensions from hydrological information system by questionnaire and show the cognitive differences in quality dimension importance, then analyze the correlations between the tasks, classify them into five categories and construct the quality assessment model with time limits in the data supply chain. Exploratory experiments suggest the assessment system can provide data quality (DQ) indicators to DQ assessors, and enable authorized consumers to monitor and even control the quality of data used in an application with a granularity of tasks.
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43

Isayev, Georgiy N., and Andrey A. Roganov. "MANAGEMENT OF INFORMATION SYSTEMS QUALITY. PARADIGM IDENTIFICATION." RSUH/RGGU Bulletin. Series Records Management and Archival Studies. Computer Science. Data Protection and Information Security, no. 2 (2017): 61–75. http://dx.doi.org/10.28995/2073-6371-2017-2-61-75.

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44

Hernes, Marcin, and Andrzej Bytniewski. "DATA QUALITY IN INTEGRATED MANAGEMENT INFORMATION SYSTEMS." Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu, no. 471 (2017): 167–75. http://dx.doi.org/10.15611/pn.2017.471.15.

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45

Kibbe, David C. "Designing Quality into Health Care Information Systems." Joint Commission Journal on Quality Improvement 20, no. 11 (November 1994): 591–94. http://dx.doi.org/10.1016/s1070-3241(16)30106-7.

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46

Jelušić, Niko, Mario Anžek, and Božidar Ivanković. "Information Source Quality in Intelligent Transport Systems." PROMET - Traffic&Transportation 22, no. 2 (January 27, 2012): 125–31. http://dx.doi.org/10.7307/ptt.v22i2.171.

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Advanced automatic traffic control systems and various other ITS (Intelligent Transport Systems) applications and services rely on real-time information from the traffic system. This paper presents the overview and general functions of different information sources which provide real-time information that are used or could be used in ITS. The objective is to formally define the quality of information sources suitable for ITS based on formal models of the traffic system and information sources. The definition of quality encompasses these essential factors: traffic system information that exists or may be requested, user requirements and attributes that describe the information sources. This provides the framework and guidelines for the evaluation of information sources that accounts for relevant factors that influence their selection for specific ITS applications. KEY WORDS: information source, information source quality, Intelligent Transport Systems (ITS), automatic traffic control
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47

Toussaint, Pieter J., Albert R. Bakker, and Luuk P. J. Groenewegen. "Integration of information systems: assessing its quality." Computer Methods and Programs in Biomedicine 64, no. 1 (January 2001): 9–35. http://dx.doi.org/10.1016/s0169-2607(00)00086-9.

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48

Malik, Kamna. "BUSINESS AND INFORMATION SYSTEMS THE QUALITY LINKS." Paradigm 1, no. 1 (July 1997): 73–78. http://dx.doi.org/10.1177/0971890719970113.

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The paper explores the technology and their use that lend themselves to most effective use of Information Technology (IT) in helping organisations improve continuously. TQM tools by themselves are not enough, nor is process re-engineering. Adding a third dimension of IS makes all the three very powerful.
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49

Barenfanger, Joan. "Utilizing laboratory information systems to improve quality." Clinical Microbiology Newsletter 25, no. 6 (March 2003): 44–48. http://dx.doi.org/10.1016/s0196-4399(03)80020-x.

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50

Sarkis, Joseph, and Michael Reimann. "Quality Information Systems in Advanced Manufacturing Environments." Quality Engineering 8, no. 3 (March 1996): 419–31. http://dx.doi.org/10.1080/08982119608904644.

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