ORIGINAL_ARTICLE
A model of explaining the factors influencing on intention of internet news websites users (Case study: Student of Semnan University)
Usage of information technology to provide services titled as electronic services is one the most important ways of competitive advantage achievement for recent organizations. Service delivery, service quality and characteristics of electronic services are firstly related to customer intention to use the services; And secondly, they have an influence on customer satisfaction and behavioral intentions. This study aims to investigate the effect of perceived risks, website content, service convenience, and individual pc skills on website service quality, satisfaction, and behavioral intention of internet news websites users. This study is applied in terms of objective and is descriptive-survey in terms of data collection and a correlation one. Statistical population is students of Semnan University who have visited website news at least one time. A sample of 384 respondents was selected by a simple random sampling approach. Data was collected by a self administrated questionnaire and analyzed by structural equation modeling using LISREL software. Results indicated that: 1) service convenience and website content have a positive and significant impact on website service quality; 2) perceived risk has a negative and significant impact on website service quality and behavioral intention; 3) website service quality has a positive and significant impact on satisfaction and behavioral intention; 4) satisfaction has a positive and significant impact on behavioral intentions; and 5) individual PC skills has a positive and significant impact on service convenience.
https://jitm.ut.ac.ir/article_54419_04756442d6923ba15c590e84514c8c0f.pdf
2015-09-01
473
492
10.22059/jitm.2015.54419
behavioral intentions
internet news websites
Satisfaction
website service quality
Abolghasem
Ebrahimi
aebrahimi@shirazu.ac.ir
1
Assistant Prof., Faculty of Management, Shiraz University, Shiraz, Iran
LEAD_AUTHOR
Niloufar
Imankhan
n.imankhan@iaufb.ac.ir
2
Assistant Prof., Department of Management, Firoozkooh Branch, Islamic Azad university , Firoozkooh, Iran
AUTHOR
Abdolreza
Esmaeli
aesmaeli@aeoi.org.ir
3
Assistant Prof., Plasma and Nuclear Fusion Research School, Nuclear Science and Technology Research Institute, Tehran, Iran
AUTHOR
Ajzen, I. (1985). From intentions to actions: A theory of planned behavior (pp. 11–39). Berlin, Germany: Springer-Verlag. DOI: 10.1007/978-3-642-69746-3_2.
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37
Shih, H. P. (2004). An empirical study on predicting user acceptance of e-shopping on the Web. Information & Management, 41(3): 351-368.
38
Sweeney, J. C., Soutar, G. N. & Johnson, L. W. (1999). The role of perceived risk in the quality–value relationship: A study in a retail environment. Journal of Retailing, 75(1): 77-105.
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45
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46
ORIGINAL_ARTICLE
Investigation the effect of Information technology competency on knowledge processes in ARAK’s justice
Study of information technology within organizations has flourished over the past decade. Although some studies have found a significant relationship between information technology competency and knowledge processes, others studies have not found such a relationship. The purpose of this study is to examine the effect merit IT on knowledge processes in ARAK’s justice. The descriptive- survey research is management type. The sample included 102 employees of Arak Justice who answered a questionnaire. Its validity and reliability were checked. The research hypothesis was tested using SEM. According to the results, IT knowledge and IT operations has a direct significant, positive effect on acquisition and transfer of knowledge. Also, IT infrastructure has a direct significant, positive effect on the acquisition of knowledge. In the end, the proposals are discussed for future researchs.
https://jitm.ut.ac.ir/article_54269_81ed948e4bb83a6234da6225dcaf4803.pdf
2015-09-01
493
510
10.22059/jitm.2015.54269
Information Technology
Knowledge
knowledge processes
SEM
Rahele
Esfandani
sfandani.rahele12@yahoo.com
1
MSc. Financial Management, Management University of Arak, Iran
LEAD_AUTHOR
Mostafa
Ali Miri
malimiri@ent.ut.ac.ir
2
Assistant Prof., of governmental management group,Azad University, Arak, Iran
AUTHOR
Al-Hawamdeh, S. (2002). Knowledge management: re-thinking informationmanagement and facing the challenge of managing tacit knowledge. Information Research, 8(1): 143-144.
1
Bhatt, G.D. & Grover, V.) 2005). Types of information technology capabilities and their role in competitive advantage: an empirical study. Journal of Management Information Systems, 22 ( 2): 253-261.
2
Chen, C. J. & Huang, J. W. (2007). How organizational climate and structure affect knowledge management- social interaction perspective. international journal of information management, 27 (2): 104-118.
3
Choi, S.Y. & Lee, H. & Yoo, Y. (2010). The impact of information technology and transactive memory systems on knowledge sharing, application and team performance: a field study. MIS Quarterly, 34 (4): 870-855.
4
Crawford, J. & Leonard, L.N.K. & Jones, K. (2011). The human resource’s influence in shaping IT competence. Industrial Management & Data Systems, 111 (2): 164-183.
5
Goudarzi, M. & Abutorabi, M. & Dasti Gardi, M. & Dasti Gardi, k. (2009).The relationship between organizational culture and knowledge management managers of project manager in Physical Education Organization. Journal of Sport Management, (2): 201-214. (in Persian)
6
Hawajreh, K.M. & Sharabati, A. (2012). The Impact of Information Technology on Knowledge Management Practices. International Journal of Business, Humanities and Technology, 2 (7): 32-46.
7
Ho, C.T. (2009). The relationship between knowledge management enablers performance. Industrial Management & Data Systems, 109(1): 98-117.
8
Hsiao, Y.C., Chen, C.J. & Chang, S.C. (2011).Knowledge management capacity and organizational performance:the social interaction view. International Journal of Manpower, 32 ( 5/6): 645-660.
9
Janz, B. D. & Prasarnphanich, P. (2003). Understanding the antecedents of effective knowledge management: the importance of a knowledge-centered culture. Decision Sciences, 34(2): 351-384.
10
King, W.R. (2005). Communication and information processing as a critical success factor in the effective knowledge organization. International Journal of Business Information Systems, 1 (1/2): 31-52.
11
Koenig, M.E. & Srikantaiah, T. (2007). KM: lesson learned, American Society for Information Science and Technology. Second printing. USA: information today inc.
12
Merat, A. & Bo. D. (2012). Strategic analysis of knowledge firms: the links between knowledge management and leadership. Journal of Knowlrdge Management, 17 (1): 3-15.
13
Migdadi, M. (2008. (Knowledge management enablers and outcomes in the smalland-medium sized enterprises. ndustrial Management & Data Systems, 109(6): 58-840.
14
Mostafapour, M., Kashef, S.M. & Mohammadi, S. (2012). The Relationship between Knowledge Management and Applying Information Technology in the Departments of Sports and Youth in West Azerbaijan. Iran, International Journal of Sport Studies, 2 (9): 465- 471. (in Persian)
15
Patrakosol, B. & Lee, S.M. )2009). IT capabilities, inter firm performance, and the state of economic development. Industrial Management & Data Systems,109 (9): 1231-1247.
16
Pérez López, S., Peón, J.M. & Ordás, C.J. (2009). Information Technology as an Enabler of Knowledge Management: An Empirical Analysis, Knowledge Management and Organizational Learning. Annals of Information Systems, 4:111-129.
17
Pérez-López, S. & Alegre, J. (2012). Information technology competency, knowledge processes and firm performance. Industrial Management & Data Systems, 112 (4): 644 – 662.
18
Rastogi, P. (2000). Knowledge management and intellectual capital the new virtuous reality. Human System Management, 19(1): 39-49.
19
Sobhani, Y., Honari, H., Shahlayi, J. & Ahmadi, A. (2013). The relationship between information technology and knowledge management in sport federations, sport management, Journal of Sport Management, 17: 73-55.
20
(in Persian)
21
Tian, J., Nakamon, Y. R. & Wierzbicky, A. (2009). Knowledge management and knowledge creation in academia: A study based on surveys in a japanes research university. journal of knowledge management, 13(2): 76-92.
22
ORIGINAL_ARTICLE
Designing fuzzy expert system for chief privacy officer in government and businesses E-transactions
The Chief Privacy Officers (CPO) are faced with many and varied responsibilities and roles. In this paper, a fuzzy expert system is designed, called "Chief Privacy Officer Fuzzy Expert System (CPOFEX)", to inform the Chief Privacy Officer about "the Status of the Privacy of Government and Businesses (G-B) E-Transactions". To develop the research model and knowledge base of the mentioned expert system, the concepts of “the Chief Privacy Officers (CPO) Capability“, “Electronic Crimes Intents“, “Type of Government and Business E-Transactions“, “Professional Ethics-Orientation in E-Transactions Parties“, “Privacy Protector Technologies in Enterprise“ were identified, as components of "the Status of the Privacy of Government and Businesses E-Transactions". To validate the mentioned expert system, the outputs of the system were compared with the experts views. This system can help to analyze "the status of the privacy of government and businesses e-transactions", and provide more accurate advices.
https://jitm.ut.ac.ir/article_54073_d0135808f5e0ab7c814068c4da23d7e7.pdf
2015-09-01
511
530
10.22059/jitm.2015.54073
chief privacy officer
Expert system
Fuzzy logic
government and businesses e-transactions
Sha’ban
Elahi
elahi@modares.ac.ir
1
Associate Prof., Information Technology Management Department, Faculty of Management and Economic, Tarbiat Modares University, Tehran, Iran
LEAD_AUTHOR
Mostafa
Rashidi
frank.wiseman1990@gmail.com
2
MSc. in Information Technology Management, Faculty of Management and Economic, Tarbiat Modares University, Tehran, Iran
AUTHOR
Mahmoud
Sadeghi
sadegh_m@modares.ac.ir
3
Associate Prof., Private Law Department, Faculty of Law, Tarbiat Modares University, Tehran, Iran
AUTHOR
Arias-Aranda, D., Castro, J.L., Navarro, M., Sánchez, J.M., Zurita, J.M. (2010). A Fuzzy expert system for business management. Expert Systems with Applications, 37 (12): 7570–7580.
1
Aslani, H.R. (2006). Information Technology Laws. Tehran: Mizan Publications.
2
(in Persian)
3
Awazu, Y. & Desouza, K. C. (2004). The Knowledge Chiefs: CKOs, CLOs and CPOs. European Management Journal, 22(3): 339–344.
4
Azar, A, Fani, A.A. & Dajkhosh, S.S. (2013). Modeling Business Ethics Using Fuzzy Analytic Network Process. Ethics in Science & Technology, ???(3): ???-???. (in Persian)
5
Bamberger, K.A. & Mulligan, D.K. (2011). New governance, chief privacy officers, and the corporate management of information privacy in the United States: An initial inquiry. Law & Policy, 33(4): 477-508.
6
Belanger, F. & Hiller, J.S. (2006). A framework for e-government: privacy implications. Business process management journal, 12 (1): 48-60.
7
Beldad, A., de Jong, M. & Steehouder, M. (2010). Reading the least read? Indicators of users' intention to consult privacy statements on municipal websites. Government Information Quarterly, 27(3): 238-244.
8
Bella, G., Giustolisi, R. & Riccobene, S. (2011). Enforcing privacy in e-commerce by balancing anonymity and trust. Computers & Security, 30 (8): 705-718.
9
Damghanian, H. & Siahsarani Kojuri, M. A. (2012). A Study on the Effect of Perceived Security on the Trust of Female Customers in the Internet Banking: (A Survey of the SADERAT BANK in Semnan). Journal of Information Technology Management, 4(13): 71-88. (in Persian)
10
Den Butter, F. A. G., Liu, J., & Tan, Y.H. (2012). Using IT to engender trust in government-to-business relationships: The Authorized Economic Operator as an example. Government Information Quarterly, 29(2): 261-274.
11
Dimick, C. (2012). The new privacy officer. Journal of AHIMA/American Health Information Management Association, 83(4): 20-25.
12
Dinev, T. & Hart, P. (2006). An extended privacy calculus model for e-commerce transactions. Information Systems Research, 17 (1): 61-80.
13
Elahi, Sh. & Hassanzadeh, A. (2009). A framework for evaluating electronic commerce adoption in Iranian companies. International Journal of Information Management, 29(1): 27–36.
14
Elahi, Sh., Khadivar, A. & Hassanzadeh, A. (2012). Designing a Decision Support Expert System for Supporting the Process of Knowledge Management Strategy Development . ???, 3(8): 43-62. (in Persian)
15
Ghodselahi, A. (2011). Designing a Fuzzy Expert system for Risk Management in Banking Industry. [Master thesis]. Supervisor: Elahi, Sha’ban. Tehran: Tarbiat Modares University, Faculty of Management and Economic.
16
(in Persian)
17
Hasangholipour, T., Amiri, M., Fahim, F.S. & Ghaderi Abed, A. (2013). Effects of Consumer Characteristics on their Acceptance of Online Shopping: A Survey in Faculty of Management, University of Tehran. Journal of Information Technology Management, 5(4): 67-84. (in Persian)
18
Hashemi, M. & Malek, M.R. (2012). Protecting location privacy in mobile geoservices using Fuzzy inference systems. Computers. Environment and Urban Systems, 36(4): 311–320.
19
Hochberg, J., Jackson, K., Stallings, C., McClary, J.F., DuBois, D. & Ford, J. (1993). NADIR: An automated system for detecting network intrusion and misuse. Computers & Security, 12(3): 235-248.
20
Hosseini Dolwlat Abadi, F. (2001). The Ethical Conscience and ways of fostering it. [Master thesis]. Supervisor: Dr Hojati. Tehran: Tarbiat Modares Uni.
21
(in Persian)
22
Jensen, C., Potts, C. & Jensen, C. (2005). Privacy practices of Internet users: Self-reports versus observed behavior. International Journal of Human-Computer Studies, 63(1–2): 203–227.
23
Jutla, D.N., Bodorik, P. & Zhang, Y. (2006). PeCAN: An architecture for users’ privacy-aware electronic commerce contexts on the semantic web. Information Systems, 31 (4): 295-320.
24
Kailay, M. P. & Peter, J. (1995). RAMeX: a prototype expert system for computer security risk analysis and management. Computers & Security, 14(5): 449–463.
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Kalloniatis, Ch., Belsis, P. & Gritzalis, S. (2011). A soft computing approach for privacy requirements engineering: The Pris framework. Applied Soft Computing, 11(7): 4341–4348.
26
Karami, A. & Guerrero-Zapatab, M. (2015). A Fuzzy anomaly detection system based on hybrid PSO-Kmeans algorithm in content-centric networks. Neurocomputing, 149: 1253–1269.
27
Karat, J., Karat, C.M., Brodie, C. & Feng, J. (2005). Privacy in information technology: Designing to enable privacy policy management in organizations. International Journal of Human-Computer Studies, 63(1): 153-174.
28
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30
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31
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Majdalawieh, M. (2010). The Integrated Privacy Model: Building a Privacy Model in the Business Processes of the Enterprise. International Journal of Information Security and Privacy archive, 4 (3): 1-21.
33
Miah, Sh., Kerr, D. & Gammack, J.G. (2009). A methodology to allow rural extension professionals to build target-specific expert systems for Australian rural business operators. Expert Systems with Applications. 36(1): 735–744.
34
Naderi, A & Ghaseminezhad, Y. (2014). Investigating the Indicators Affecting the Success of Modern Banking Services Strategies from the View Point of Managers and Experts of Ansar Bank. Journal of Iranian Technology Management, 6(3): 487-504.
35
Qin, B., Zhou, X., Yang, J. & Song, C. (2006). Grey-theory based intrusion detection model. Journal of Systems Engineering and Electronics, 17(1): 230–235.
36
Reddick, C.G. & Roy, J. (2013). Business perceptions and satisfaction with e-government: Findings from a Canadian. Government Information Quarterly, 30(1): 1-9.
37
Reza Karimi, M., Sepandarand, S. & Haghshenas, F. (2012). Study of the Effects of Customers’ Perceptions of Security and Trust on their Use of the Agriculture Bank of Iran’s e-Payment System. Journal of Iranian Technology Management, 4(11): 135-154.
38
Rezmierski, V. E. & Marshall, R. S. (2002). University systems security logging: who is doing it and how far can they go? Computers & Security, 21 (6)1: 557–564.
39
Shamsi, Z. (2014). Designing a Fuzzy expert system for selecting new IT product development projects. [Master thesis]. Supervisor: Elahi, Sha’ban. Tehran: Tarbiat Modares University, Faculty of Management and Economic.
40
(in Persian)
41
Sivanandam, S. N., Sumathi, S. & Deepa, S.N. (2007). Introduction to Fuzzy Logic using MATLAB. Springer-Verlag Berlin Heidelberg.
42
Summers, R. C. & Kurzban, S.A. (1988). Potential applications of knowledge-based methods to computer security. Computers & Security, 7(4): 373–385.
43
Taghva, M.R. & Izadi, M. (2013). Investigating Security in Developed Information Systems through Service oriented Architecture (SOA). Journal of Information Technology Management, 5(3): 25-42. (in Persian)
44
Tajfar, A. H., Mahmoudi Maymand, M., Rezasoltani, F. & Rezasoltani, P. (2015). Ranking the barriers of implementing Information Security Management System and Investigation of readiness rate of exploration management. Journal of Information Technology Management, 6(4): 551-566. (in Persian)
45
Vaishnavi, V. K. & Kuechler, Jr. W. (2008). Design Science Research Methods and Patterns, Innovating Information and Communication Technology. Auerbach Publications, Taylor & Francis Group.
46
Vosough, M., Taghavi Fard, M. T. & Alborzi, M. (2015). Bank card fraud detection using artificial neural network. Journal of Information Technology Management, 6(4): 721-746. (in Persian)
47
Xidonas, P., Ergazakis, E., Ergazakis, K., Metaxiotis, K., Askounis, D., Mavrotas, G. & Psarras, J. (2009). On the selection of equity securities: An expert systems methodology and an application on the Athens Stock Exchange. Expert Systems with Applications, 36(9): 11966–11980.
48
Xu, D.L., Liu, J., Yang, J.B., Liu, G.P., Wang, J., Jenkinson, I. & Ren, J. (2007). Inference and learning methodology of belief-rule-based expert system for pipeline leak detection. Expert Systems with Application, 32(1): 103-113.
49
ORIGINAL_ARTICLE
An investigation on the moderating role of users’ self-efficacy and mobile banking satisfaction in Iran
Mobile banking as a subset of e-banking is one of the newest communication channels between banks and customers. Via m-banking, customers receive services such as checking their bank account balance, transfer of funds, pay bills and etc. However, the rate of m-banking among Iranian users is very low. The purpose of this study is to investigate the moderating role of user’s self-efficacy on m-banking satisfaction. According to the developed research model, information quality, service quality, system quality, reputation and structural assurance are factors that influencing trust and satisfaction of m-banking and users’ self-efficacy moderates this relationship. This study is a quantitative research and a sample of 230 Iranian m-banking users has been surveyed. Research hypotheses were tested by structural equation modeling. The results showed that effect of service quality on trust, system quality on trust, system quality on satisfaction, reputation on trust, structural assurance on trust and trust on satisfaction were significant. This study also showed the role of self-efficacy as a moderator between the relationship of service quality, system quality and reputation with trust. Finally, recommendations were proposed for customer satisfaction of m-banking.
https://jitm.ut.ac.ir/article_53926_a8572ac1828d4ec9fe4df176d7cb868f.pdf
2015-09-01
531
552
10.22059/jitm.2015.53926
Customers Satisfaction
customers trust
Electronic banking
mobile banking
Self-Efficacy
Seyed Mohammadbagher
Jafari
sm.jafari@ut.ac.ir
1
Assistant Prof., Faculty of Management and Accounting, College of Farabi, University of Tehran, Iran
LEAD_AUTHOR
Ali
Hamidizadeh
hamidizadeh@ut.ac.ir
2
Assistant Prof., Faculty of Management and Accounting, College of Farabi, University of Tehran, Iran
AUTHOR
Mohaddece Sadat
Moaddab
mathkernel@yahoo.com
3
MSc. in Information Systems Management, Faculty of Management and Accounting, College of Farabi, University of Tehran, Iran
AUTHOR
Aminbidekhti, A., Rezaeei, A. & Saburinia, M. (2008). Prioritize service quality variables by using Hysteresis model: The case in Iran Melli Bank. Journal of the Faculty of Humanities, 24(9): 7- 26. (in Persian)
1
Asr-e- Iran (2010). 80% Europeans use from Mobile Banking, Azar 23. Retrieved from: Asriran.com. (in Persian)
2
Bandarian, R. (2011). Identification and determination effective factors in customer satisfaction in research and technology organizations; The case: Research institute of petroleum industry. Journal of Strategic management thought, 5(9): 201-222. (in Persian)
3
Beldad, A., De Jong, M. & Steehouder, M. (2010). How shall I trust the faceless and the intangible? A literature review on the antecedents of online trust. Computers in Human Behavior, 26(5): 857-869.
4
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5
Cruz, P., Neto, L.B.F., Muñoz-Gallego, P. & Laukkanen, T. (2010). Mobile banking rollout in emerging markets: evidence from Brazil. International Journal of Bank Marketing, 28(5): 342-371.
6
Dehghan-Dehnavi, M., Edalat, A. & Kohzadi, N. (2004). Commerceand Mobile Banking in Iran and world. The 3nd National Conference on Electronic Commerce. Tehran: Commerce ministry, Assistance planning and economic affairs. (in Persian)
7
Esfidani, M., Akbari, F. & Davari, M. (2007). Mobile Banking in Iran, challenges and barriers, offering solution based on Technology Acceptance Model (TAM). The 4nd National Conference on Electronic Commerce. Tehran: Commerce ministry, Assistance planning and economic affairs. (in Persian)
8
Fayaz-Bakhsh A. & Geravandi, S. (2015). Medical students’ perceptions regarding the impact of mobile medical applications on their clinical practice. Journal of Mobile Technology in Medicine, 4(2): 51-52.
9
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10
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11
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12
Hanafizadeh, P., Behboudi, M., Koshksaray, A.A. & Tabar, M.J.S. (2012). Mobile-Banking Adoption by Iranian Bank Clients. Telematics and Informatics, 31(1): 62-78.
13
Ho, R. (2006). Handbook of univariate and multivariate data analysis and interpretaion with SPSS, London /New York: Taylor & Francis Group, LLC.
14
Human, H. (2005). Structural equation modeling by using Lisrel software. Tehran: samt. (in Persian)
15
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16
IT Analysis. (2012). Only 5% Iranians are Mobile Banking user. Azar 23. Retrieved from: Itanalyze.com. (in Persian)
17
Kim, G., Shin, B., & Lee, H. G. (2008). Understanding dynamics between initial trust and usage intentions of mobile banking. Information Systems Journal, 19(3): 283-311.
18
Laukkanen, T. & Cruz, P. (2009). Comparing consumer resistance to mobile banking in Finland and Portugal. In e-Business and Telecommunications (pp. 89-98). Springer Berlin Heidelberg. DOI: 10.1007/978-3-642-05197-5_6.
19
Lee, K.C., & Chung, N. (2009). Understanding factors affecting trust in and satisfaction with mobile banking in Korea: A modified DeLone and McLean’s model perspective. Interacting with computers, 21(5): 385-392.
20
Lin, H.F. (2012). Determining the relative importance of mobile banking quality factors. Computer Standards & Interfaces, 35(2): 195-204.
21
Luarn, P. & Lin, H. H. (2005). Toward an understanding of the behavioral intention to use mobile banking. Computers in Human Behavior, 21(6): 873-891.
22
Luo, X., Li, H., Zhang, J. & Shim, J. P. (2010). Examining multi-dimensional trust and multi-faceted risk in initial acceptance of emerging technologies: An empirical study of mobile banking services. Decision Support Systems, 49(2): 222-234.
23
Miller, D.E. & Kunce, J.T. (1973). Prediction and statistical overkill revisited. Measurement and Evaluation in Guidance, 6(3): 157-163.
24
Sarmaye Bank (2010). Mobile Banking from the perspective of 7 banking network senior manager. Azar 23. Retrieved from: http://wwwSarmayebank.com.
25
(in Persian)
26
Sekaran, O. (2002). Research methods in management. Translators: Sa’ebi, M. & Shirazi, M., Tehran: press (Institute Education and Research Management and planning). (in Persian)
27
Shomakher, R. & Lumax, R. (2009). The introduction On structural equations modeling, Translator: Ghasemi, V., Tehran: press (Publication Sociologists). (in Persian)
28
Siau, K. & Shen, Z. (2003). Mobile communications and mobile services. International Journal of Mobile Communications, 1(1): 3-14.
29
Suoranta, M. & Mattila, M. (2004). Mobile banking and consumer behaviour: new insights into the diffusion pattern. Journal of Financial Services Marketing, 8(4): 354-366.
30
Taghavifard, M. & Torabi, M. (2010). the effective factors in useing of Mobile Banking services by customers and Their ranking (The case: Branches Tejarat Bank in Tehran). Journal of Explores Commerce Management, 3(2): 117- 139. (in Persian)
31
Wessels, L. & Drennan, J. (2010). An investigation of consumer acceptance of M-banking. International Journal of Bank Marketing, 28(7): 547-568.
32
Zhou, T. (2012). An empirical examination of initial trust in mobile banking. Internet Research, 21(5): 527-540.
33
ORIGINAL_ARTICLE
The role of internet of things (IOT) in knowledge management systems (Case study: Performance management of Yazd municipality staff)
With the development of Internet of things (IOT) technologies in recent years, the development of knowledge management systems based on them, as well as the role of these systems in different organizational areas such as staff performance management should be considered. The objective of this study is to design an application based on the IOT, and analysis of its role in staff performance improvement. The methodology of this study is action research based on the design of information systems with RAD approach and prototyping design method, and focus on one of the performance indicators of the Yazd municipality staff, namely daily working time. The proposed knowledge management based structure to control the entry and exit of staff in the case of study, and implementation of its prototype indicated that IOT can play roles in improving staff performance in six specific areas in two parts of data collection and management of entry and exit. In general, IOT could be used as a reliable basis to generate required data for knowledge management in knowledge based processes, especially knowledge discovery in physical and digital environments.
https://jitm.ut.ac.ir/article_53916_4b7903365b4af353bf9fd19a10235857.pdf
2015-09-01
553
572
10.22059/jitm.2015.53916
Internet of Things (IoT)
Knowledge Management
Municipality
RFID
staff performance management
Hamid Reza
Khedmatgozar
khedmatgozar@students.irandoc.ac.ir
1
Ph.D. Csndidate in Information Technology Management, Iranian Research Institute for Information Science and Technology (IRANDOC),Tehran, Iran
LEAD_AUTHOR
Akhondzadeh-Noughabi, E., Albadvi, A. & Aghdasi, M. (2014). Mining customer dynamics in designing customer segmentation using data mining techniques. Quarterly Journal of Information Technology Management, 6(1): 1-30. (in Persian)
1
Atzori, L., Iera, A. & Morabito, G. (2010). The internet of things: A survey. Computer networks, 54(15): 2787-2805.
2
Barnaghi, P., Wang, W., Henson, C. & Taylor, K. (2012). Semantics for the Internet of Things: early progress and back to the future. International Journal on Semantic Web and Information Systems, 8(1): 1-21.
3
Becerra-Fernandez, I. & Sabherwal, R. (2010). Knowledge management: Systems and processes. ME Sharpe: NewYork, NY.
4
Cooper, J. & James, A. (2009). Challenges for database management in the internet of things. IETE Technical Review, 26(5): 320.
5
Dennis, A., Wixom, B. H. & Roth, R. M. (2012). Systems analysis and design. 5rd Edition. John Wiley & Sons: NewYork, NY.
6
El Ghazali, Y., Lefebvre, É. & Lefebvre, L. A. (2012). The Potential of RFID as an Enabler of Knowledge Management and Collaboration for the Procurement Cycle in the Construction Industry. Journal of technology management & innovation, 7(4): 81-102.
7
IBM (2014). Bringing Big Data to the Enterprise, Retrieved from http://www-01.ibm.com/software/data/bigdata. (Accessed on 02.11.2014).
8
ITU Strategy and Policy Unit (SPU). (2005). ITU Internet Reports 2005: The internet of things. Geneva: International Telecommunication Union (ITU), Retrieved from http://www.itu.int/wsis/tunis/newsroom/stats/The-Internet-of-Things-2005.pdf. (Accessed on 02.11.2014).
9
Kranenburg, R. V., Anzelmo, E., Bassi, A., Caprio, D., Dodson, S. & Ratto, M. (2011). The Internet of Things. In 1st Berlin Symposium on Internet and Society: Exploring the Digital Future, Berlin: October 25-27.
10
Malhotra, Y. (2005). Integrating knowledge management technologies in organizational business processes: getting real time enterprises to deliver real business performance. Journal of knowledge management, 9(1): 7-28.
11
Mehrjerdi, Y. Z. (2008). RFID-enabled systems: a brief review. Assembly Automation, 28(3): 235-245.
12
Miorandi, D., Sicari, S., De Pellegrini, F. & Chlamtac, I. (2012). Internet of things: Vision, applications and research challenges. Ad Hoc Networks, 10(7): 1497-1516.
13
Monavarian, A., Shaabani, E. & Ahmadi, H. (2014). Acquiring core competencies in IKCO through elements of knowledge management: Investigating the mediation role of knowledge management processes. Quarterly Journal of Information Technology Management, 6(4): 701-720. (in Persian)
14
Müller, G., Richter, K., Plate, C. & Mandelartz, J. (2008). Optimizing maintenance processes with RFID and related knowledge management. In 4th World Congress on Maintenance. Haikou, Hainan, China: Nov (pp. 24-26).
15
Rahnavard, F. & Mohammadi, A. (2010). Identifying Critical Success Factors of Knowledge Management System in Academic Centers & Faculties of Tehran. Quarterly Journal of Information Technology Management, 1(3): 37-52. (in Persian)
16
Rowley, J. E. (2007). The wisdom hierarchy: representations of the DIKW hierarchy. Journal of Information Science, 33(2): 163–180.
17
Vaishnavi, V. K. & Kuechler Jr, W. (2007). Design science research methods and patterns: innovating information and communication technoloy, Auerbach Publications, Taylor & Francis Group: NewYork, NY.
18
Von Der Gracht, H. A. (2012). Consensus measurement in Delphi studies: review and implications for future quality assurance. Technological Forecasting and Social Change, 79(8): 1525-1536.
19
Zhang, L., Atkins, A. & Yu, H. (2012). Knowledge Management Application of Internet of Things in Construction Waste Logistics with RFID Technology. International Journal of Computing Science and Communication Technologies, 5(1): 760-767.
20
Zorzi, M., Gluhak, A., Lange, S., & Bassi, A. (2010). From today's intranet of things to a future internet of things: a wireless-and mobility-related view. Wireless Communications, IEEE, 17(6): 44-51.
21
ORIGINAL_ARTICLE
Provide a decision support system for locating new businesses (Ccase study: Locating toy manufacturing)
Concept of locating business units includes the most important factors in their success and one the most competitive advantage of industrial units. Entrepreneurs have been considered in this context, and different mathematical models have been developed. This paper aims to develop a decision support system based on a mathematical model in linear programming. In a comprehensive approach to this article, three general headings can be recognized. First, as background concepts related to decision support systems, expert systems and mathematics of location reviewed. On the second part, the foundations of mathematics and logic model used in this study is explained. Finally, the samples software designed to implement the model are introduced and as a case study finding a best place for a toy manufacturing is studied and based on the outputs of software the province of Qom have introduced.
https://jitm.ut.ac.ir/article_54001_7873f47687cc3fa98818d8a547e37ef4.pdf
2015-09-01
573
594
10.22059/jitm.2015.54001
decision support system
expert systems
Locating
Linear programming
Toys
Amirhossein
Rahbar
a.h.rahbar@ut.ac.ir
1
Ph.D. Candidate in futue study, Faculty of new sciences and technologies University of Tehran, Iran
AUTHOR
Ali
Lahoutian
ali.lahoutian@ut.ac.ir
2
Ph.D. Candidate in public administration, Faculty of Management University of Tehran, Iran
LEAD_AUTHOR
Mahmoud
Vahedi Moghaddam
managingdirector@bwf.ir
3
MSc in electronic business, Faculty of Management University of shiraz, Iran
AUTHOR
Arya-Nejad, M. & Sajjadi, S.J. (2002). Linear programming. Tehran, Iran University of Science and Technology press. (in Persian)
1
Captivo, M. & Climaco Joao, N. (2008). On Multicriteria Mixed Integer Linear Programming Based Tools for Location Problems- An Updated Critical Overview Illustrated with a Bicritreia DSS. Computación y Sistemas, 12(2): 216-231.
2
Church, R. & Murray A. (2009). Business Site Selection, Location Analysis and GIS. Online Library.
3
Dias, J., Captivo, M. & Clímaco, J. (2006). A Decision Support System for Location Problems. In F. Adam , P. Brézillon, S. Carlsson & P. Humphreys (Eds.), Proceedings of CIDMDS: 388-340.
4
Elahi, S., Khadivar, A. & Hasanzadeh, A. (2012). Designing a Decision Support Expert System for Supporting the Process of Knowledge Management Strategy Development. Journal of Information Technology Management, 3(8): 43-62. (in Persian)
5
Entezari Heravi, A. (2004). Plant Layout, Tehran: jahan Jamejam press.
6
Erkut, E. & Alp, O. (2007). Designing a network for hazardous materials shipments. Comput Oper Res 34(5):1389–1405.
7
European Competitiveness and Sustainable Industrial Policy Consortium (ESCIP). (2013). Study on the competitiveness of the toy industry. available on: http://ec.europa.eu/enterprise/sectors/toys/files/reports-and-studies/final-report-lead-in-toys-ecorys_en.pdf.
8
Farahani, R. Z., SteadieSeifi, M., &Asgari, N. (2010). Multiple criteria facility location problems: A survey. Applied Mathematical Modelling, 34(7): 1689-1709.
9
Faiz, S., Krichen, S. & Inoubli, W. (2014). A DSS based on GIS and Tabu search for solving the CVRP: The Tunisian case. The Egyptian Journal of Remote Sensing and Space Science, 17(1): 105–110.
10
Fernandes, S., Captivo, M. & Clímaco, J. (2014). A DSS for bicriteria location problems. Decision Support Systems, 57: 224–244.
11
Figueira, J., Greco, S. & Ehrgott, M. (2005). Multiple criteria decision analysis: State of the art surveys Springer Verlag. DOI: 10.1007/b100605.
12
Firouzi, M., Sajjadian, N. & Sajjadian, M. (2011). Spatial Decision Support Systems for natural disaster risk management in the villages with using GIS, A step in the direction of sustainable development: a case study of villages in Mazanadaran province. Village and development, 14(2): 93-115. (in Persian)
13
Freund, J. (1992). Mathematical Statistics. USA. Preintce-hall. (in Persian)
14
Hekmatpour, M., Feiznia, S., Ahmadi, H. & Khalilpour, A. (2007). Zoning suitable areas for artificial recharge at Varamin plain with GIS and Decision Support Systems (DSS). Journal of Enviromental Studies, 33(42): 1-8. (in Persian)
15
Jafarnejad, A., Rahbar, A., Moghadaspoor, S. & Vahedimoghadam, M. (2010). Designing a Decision Making Model to Measure Scientific Research Essays of Management. Journal of Information Technology Management, 1(3): 19-36. (in Persian)
16
Jia, H., Ordóñez, F. & Dessouky, M. (2005). Modeling framework for facility location of medical services for large-scale emergencies, Create report, Under FEMA Grant.
17
Keen P.G.W. & Scott Morton M. S. (1987). Decision Support Systems: An Organizational Perspective. Addison-Wesley.
18
Little & King Co, (2010). The Transformational Toy Manufacturing Industry. US. Little & King Co.
19
Lombardi, P. & Ferretti, V. (2015). New spatial decision support systems for sustainable urban and regional development. Smart and Sustainable Built Environment, 4 (1): 45 – 66.
20
Mahmoudi, S.M. (2007). Information systems in management. Tehran: University of Tehran press (UTP). (in Persian)
21
Papathanasiou, J. & Paparrizou, A. (2007). A Decision Support System for the Facility Location Problem under Time Constraints. Advanced Modeling and Optimization, 9(1): 117-134.
22
Paya, A. (2010). Scrutinizing the comprehensive scientific map of the country. Quarterly Journal of Industrial Technology Development, 8(14): 5-22.
23
(in Persian)
24
Salimifard, K. & Babaeezadeh, S. (2011). A Decision Support System for University Course Timetabling: Persian Gulf University Case Study. Journal of Information Technology Management. 3(7): 77-92. (in Persian)
25
Seifi, F., Pazira, E., Zahedipour, H. & Massihabadi, M. (2010). Ability of spatial decision support systems (SDSS) in locating industrial waste landfill in Saveh city. Second National Conference of Water Resource Management. (in Persian)
26
Shahrezaee, M., Seifbarghy, M. & Ehtesham, Rasi, R. (2012). Designing a Decision Support System (DSS) for Supplier Selection in Multiple Discount Environment. Journal of Information Technology Management. 4(112): 89-112. (in Persian)
27
Tompkins, J. White, J., Bozer, Y., Frazelle, E., Tanchoco, J. & Trevino, J. (2003). Facilities Planning. USA. John Wiley & Sons Inc.
28
Turban, E. and Aronson, J.E. (2005). Decision Support Systems and Intelligent Systems. Prentice Hall.
29
Yano Research Institute, (2004) Toy’s Market in Japan. Yano Research Institute.
30
Zografos, K.G., Vasilakis, G.M. & Giannouli, I.M. (2000). Methodological framework for developing decision support system (DSS) for hazardous materials emergency response operations. Journal of Hazardous Materials. 71: 503–521.
31
ORIGINAL_ARTICLE
Explaination of personnel selection model in private IT companies
Maintain and enhance the quality of human resources and achieve maximum value from IT industry employees is the most important concern of managers. Most of researches in this area focus on companies’ endeavour to recruiting qualified experts in the IT industry in the next decade. The selection of qualified personnel for organizations which focus on human resouces as a strength, will be a major issue. Therefore, in this study, companies active in the field of information technology as one of the technology companies, have been examined for optimal absorption of manpower. In the present study, multi-criteria decision-making is used. IT active companies are studied in the current research. In order to design the proper employment model of this companies and due to a variety of quantitative and qualitative parameters, TOPSIS multi attribute decision making (MADM) model is used for prioritization of employment alternatives. Moreover Meta synthesis method is employed to extract the effective indices in the scientific literature. Among authentic researches, finally 7 indices are selected for TOPSIS weighted measure. According to the model, 33 alternatives are investigated at a sample active company. The model is used for three types of professions: IT project manager, information systems analyst and computer programmer. Our model is compared with the traditional methods of personnel selection. The results, shows the consistency between the model and traditional methods. At the end, cause of some contradictions is discussed.
https://jitm.ut.ac.ir/article_54756_03d2a6ba8e2cea01f5a7b5237cfab452.pdf
2015-09-01
595
614
10.22059/jitm.2015.54756
Human Resource
Information Technology
personnel selection
TOPSIS
Amir
Roodi
mhroodi@gmail.com
1
MSc, Information Technology Management, University Of Tehran, Tehran, Iran
LEAD_AUTHOR
Ahmad
Khalili Jafarabad
ahmad.khalili@ut.ac.ir
2
PhD Student, Information Technology Management, University Of Tehran, Tehran, Iran
AUTHOR
Aggarwal, R. (2014). Identifying and Prioritizing Human Capital Measurement Indicators for Personnel Selection Using Fuzzy MADM. Third International Conference on Soft Computing for Problem Solving Advances in Intelligent Systems and Computing (pp. 427-439). Springer India.
1
Askounis, D. & Kelemenis, A. (2009). A New TOPSIS-based Multi-Criteria Approach to Personnel Selection. Expert Systems with Applications, 37 (7): 4999-5008.
2
Azam Vaziri, S., Mansouri, H. & Adiban, A. (2009). Identify and Prioritize The Factors Affecting Labor Productivity Using MADM Techniques Case Study of Hormozgan Ministry of Education. Talim Tarbiat, (100): 135-159.
3
(in Persian)
4
Azar, A. & Rajabzadeh, A. (2002). Applied Decision Making. Tehran: Negah Danesh. (in Persian)
5
Baschab, J., Carr, N. & Piot, J. (2007). The Executive's Guide to Information Technology, 2nd ed. John Wiley & Sons.
6
Bazrpash, M. & Ansari, G. (2007). Application of Multi Attribute Decision Making Models of Meritocracy Brokers Islamic Republic of Iran. Modiriate Farda, (18): 41-54. (in Persian)
7
Bench, S. & Day, T. (2010). The User Experience of Critical Care Discharges: a Meta-Synthesis of Qualitative Research. International Journal of Nursing Studies, 47(4): 487-499.
8
Canós, L. & Liern, V. (2008). Soft Computing-Based Aggregation Methods for Human Resource Management. European Journal of Operational Research, 189(3): 669-681.
9
Chen, C. (2000). Extensions of the TOPSIS for Group Decision-Making Under Fuzzy Environment. Fuzzy Sets and Systems, 114(1): 1-9.
10
Chen, L. & Cheng, C. (2005). Selecting IS Personnel Use Fuzzy GDSS Based on Metric Distance Method. European Journal of Operational Research, 160(3): 803-820.
11
Chien, C., & Chen, L. (2008). Data Mining to Improve Personnel Selection and Enhance Human Capital: A Case Study in High-Technology Industry. Expert Systems with Applications, 34(1): 280-290.
12
Childs, K. (2003). The IT Industry Learning Cycle. Certification Magazine, 5(5):16.
13
CIO.GOV. (2011). Information Technology Workforce Capability Assessment. Chief Inforation Officers Council, https://cio.gov/wp-content/uploads/downloads /2012/09/2011_ITWCA_Results_Report_Final_5.31.11.pdf.
14
Eckle, J. (2005). Most-Sought IT Skills. Computerworld, 39(11): 49.
15
Eskandari, A. (2008). Topsis MADM Techniques Used in Capital Budgeting Method. Qazvin: Qazvin Azad University. (in Persian)
16
Ghodsipoor, S. (2002). Discussions on Multi-Criteria Decision. Tehran: Amir Kabir University. (in Persian)
17
Grossman, R. (2006). HR’s Rising Star in India. HR Magazine, 51(9): 46.
18
Güngör, Z., Serhadlıog˘lub, G. & Kesen, S. (2009). A Fuzzy AHP Approach to Personnel Selection Problem. Applied Soft Computing, 9(2): 641-646.
19
Harvey, M., Novicevic, M. & Garrison, G. (2004). Challenges to Staffing Global Virtual Teams. Human Resource Management Review, 14 (3): 275-294.
20
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21
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24
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26
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28
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29
Kelemenis, A., Ergazakis, K. & Askounis, D. (2010). Support Managers’ Selection Using an Extension of Fuzzy TOPSIS. Expert Systems with Applications, 38(3): 2774-2782.
30
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(in Persian)
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Saremi, Mousavi, & Sanai. (2009). TQM Consultant Selection in SMEs With TOPSIS Under Fuzzy Environment. Expert Systems with Applications, (36): 2742-2749.
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Shih, H., Shyur, H. & Lee, E. (2007). An Extension of TOPSIS For Group Decision Making. Mathematical and Computer Modelling, 45(7): 801-813.
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Zimmer, L. (2006). Qualitative Meta-Synthesis: a Question of Dialoguing With Texts. Journal of Advanced Nursing, 53(3): 311-318.
49
Zolfani, S. & Banihashemi, S. (2014). Personel Selection Based on a Novel Model of Game Theory and MCDM Approaches. 8th International Scientific Conference Business and Management. Vilnius Gediminas Technical University,Lithuania.
50
ORIGINAL_ARTICLE
The relationship between corporate governance and IT governance in public organizations
Corporate governance is the system by which corporations are directed and controlled. Corporate governance also provides the structure through which company objectives are established, the means to achieve these objectives, and how to monitor their performance. ICTs have the potential to make organization and its services more transparent by providing easy access to information. This research aims to evaluate the relationship between information technology governance and corporate governance. The survey sample population consisted of 178 randomly taken managers and employees who work in public organizations. To examine the hypothesis, we use canonical correlation analysis. An important part of results from canonical correlation analysis indicated that there is a proper linear mixture between the variables of canonical effective factors on corporate governance and its components.
https://jitm.ut.ac.ir/article_54329_98870b6ad01666c29050637ecc16179d.pdf
2015-09-01
615
634
10.22059/jitm.2015.54329
COBIT
Corporate governance
IT governance
Mohammad Hossein
Ronaghi
mh_ronaghi@shirazu.ac.ir
1
Ph.D. Candidate in Information Technology Management, Faculty of Management University of Tehran, Iran
LEAD_AUTHOR
Jafar
Mahmoudi
jmahmudii@yahoo.com
2
Assistant Professor, Imam Hussein University, Tehran, Iran
AUTHOR
Babajani, J. & Abdi, M. (2010). The Relationship between Corporate Governance and Enterprises Taxable Profit. Financial Accounting Researches journal, 2(3): 65-86. (in Persian)
1
Chong, G. & Isimoya, E. (2007). Disclosure of Governance Information by Small and Medium-Sized Companies. Corporate governance, 7(5): 635-684.
2
Erkens, D., Hung, M. & Matos, P. (2012). Corporate governance in the 2007–2008 financial crisis: Evidence from financial institutions worldwide Original Research Article. Journal of Corporate Finance, 18(2): 389-411.
3
Gardner, S., Gowerb, C. & Rouxa, N. J. (2006). A synthesis of canonical variate analysis, generalized canonical correlation and procrustes analysis. Computational Statistics & Data Analysis, 50(1): 107–134.
4
Ghazanfari, M., Fathian, M. & Safari, M. (2011). Measuring of information technology governance maturity in Iranian financial services industry Comparison between state & private bank sectors using the COBIT4.1 framework. Journal of information technology management, 3(6): 63-88. (in Persian)
5
Hasasyeganeh, Y. & Kheirolahi F. (2009). Corporate Governance and Transparency. Accountant journal, 47: 41-49. (in Persian)
6
Hasasyeganeh Y. & Salimi, M. (2011). a model for Corporate Governance ranking in Iran. financial accounting reviews journal, 9(30): 2-36.
7
(in Persian)
8
Hasasyeganeh, Y. (2007). Corporate Governance in Iran, Auditor journal, 32: 32-39. (in Persian)
9
Hosseininasab, S. (2013). Generalization of Canonical Correlation Analysis from Multivariate to Functional Cases and its related problems. Andishe. 17 (2): 81-91. (in Persian)
10
Kerr, S. & Murthy, U. (2013). the importance of the CobiT framework IT processes for effective internal control over financial reporting in organizations: An international survey. Information & Management, 50(7): 590-597.
11
Kim, H. & Lu, Y. (2013). corporate governance reforms around the world and cross-border acquisitions. Journal of Corporate Finance, 22: 236-253.
12
Knappa, K.J., Franklin, R., Marshallc, E. & Anthony T. (2009). Information security policy: An organizational-level process model. computers & security, 28(7): 493–508.
13
Korac, N. & Kakabadse, A. (2010). IS/IT governance: Need for an integrated model, Corporate Governance, 11(4): 9-11.
14
Manian, A., Mosakhani, M. & Jami, M. (2010). Survey Relationship between IT-business Alignment and Business Performance: Using Structural Equation Model. journal of information technology management, 1(3): 89-106. (in Persian)
15
Moghimi, S.M. & Ardakani, M. (2011). Indicators to measure good governance and its role promoting e-government. journal of information technology management, 3(8): 171-188. (in Persian)
16
Munisi, G. & Randoy, T. (2013). corporate governance and company performance across Sub-Saharan African countries. Journal of Economics and Business, 70: 92-110.
17
Nikoskelainen, E. & Wright M., (2007). the impact of corporate governance mechanisms on value increase in leveraged buyouts. Journal of Corporate Finance, 13(4): 511-537.
18
Ojo, A., Janowski, T. & Awotwi, J., (2013). Enabling development through governance and mobile technology. Government Information Quarterly, 30(1): 32-45.
19
Sherry, A. & Henson, R.K. (2005). Conducting and Interpreting Canonical Correlation Analysis in Personality Research. International Journal of Service Industry Management, 84(1): 37-48.
20
Simonsson, M. & Johnson, P. (2008). The IT organization modeling and assessment tool: Correlating IT governance maturity with the effect of IT. Proceedings of the 41st Hawaii International Conference on System Sciences. Available in: https://www.computer.org/csdl/proceedings/ hicss/2008/3075/00/30750431.pdf.
21
Tian, Y. & Twite, G. (2011). corporate governance, external market discipline and firm productivity. Journal of Corporate Finance, 17(3): 403–417.
22
Valipour, H., Moradi, J. & Parvizpour, L. (2013). the Effect of Information Asymmetry on the Choice of the Mechanisms of Corporate Governance. JERA. 3 (1): 241-255. (in Persian)
23
ORIGINAL_ARTICLE
Comparative study of PhD programs of information technology management at the world top rank universities
The purpose of this paper is a comparative study of information technology management PhD programmes at the world top universities. So, the top five rankings of universities were identified. Then the top universities in the world generally and information systems/information technology field were identified too. 19 related fields were investigated. The titles of the courses of them were documented and examined. Subsequently, courses were classified according to their most frequently that include the methodology of research in information systems, data management, technical foundations of information systems, information systems development, seminar on information systems, information systems economics, information systems strategy and governance, social aspects of information systems and organization and management. Next, the proposed courses compared with courses of the programme in Iranian universities.
https://jitm.ut.ac.ir/article_54749_28fabbc8c380a78b501b9b364a622f70.pdf
2015-09-01
635
654
10.22059/jitm.2015.54749
Comparative Study
information systems
information technology management field of stud
PhD program
Mehdi
Shamizanjani
mshami@ut.ac.ir
1
Assistant Prof., Faculty of Management, University of Tehran, Tehran, Iran
AUTHOR
Narges
Farzaneh Kondori
nsfarzaneh81im@gmail.com
2
Ph.D. Student in Information Technology Management, Faculty of Management University of Tehran, Iran
LEAD_AUTHOR
Bell, C. C. (2012). Undergraduate Information Systems (IS) Curriculum and Career Track Development in United States Colleges and Universities: Assessment of Adherence to IS 2010 Curriculum Guidelines. All Graduate Theses and Dissertations. Paper 1121. available in: http://digitalcommons.usu.edu/etd /1121.
1
Berkeley University Program. (2014). Retrieved from http://www.ischool.berkeley. edu/programs/phd.
2
Boston University Program. (2014). Retrieved from http://management.bu. edu/faculty-research/departments/information systems.
3
Business School Rnking. (2013). Retrieved from http://www.businessweek. com/bschools/rankings.
4
Carnegie Mellon University Program, Heinz College Program. (2014). Retrieved from http://www.heinz.cmu.edu/school-of-information-systems-and-management /doctoral-program/phd-ism/index.aspx.
5
Carnegie Mellon University, the Tepper School of Business Program. (2014). Retrieved from http://tepper.cmu.edu/prospective-students/phd/program/ business-technologies.
6
Cornell University Program. (2014). Retrieved from http://www.gradschool. cornell.edu/academics/fields-of-study/subject/information-cience/information -science-phd-ithaca.
7
Curriculum for Ph.D of information technology management. (2009). Ministry of Science, Research & Technology, 12-48. (in Persian)
8
Georgia Institute of Technology Program. (2014). Retrieved from http://scheller. gatech.edu/degree-programs/phd/phd-concentrations/phd-itm.html.
9
Georgia State University Program. (2014).Retrieved from http://cis.robinson. gsu.edu/academic-programs/phd.
10
Hidding, G. J. (2012). Information Systems as a Professional Discipline: Focus on the Management of Information Technology. Journal of Organizational Computing and Electronic Commerce, 22 (4): 347-360.
11
Hong Kong University Program. (2014). Retrieved from http://www.fbe.hku. hk/academic-programmes/postgraduate/phd-and-mphil/ field-of-study.
12
Longenecker, H.E., Feinstein, D. & Clark, J.D. (2012). Information Systems Curricula: A Fifty Year Journey. Proceedings of the Information Systems Educators Conference, New Orleans Louisiana, USA.
13
Manual of Ph.D. test. (2014). Sanjesh organization, Retrieved from http://unr.ir/ download/download%20file/phd/Doctora93_2.pdf. (in Persian)
14
National Taiwan University program. (2014). Retrieved from http://exp. management.ntu.edu.tw/en/IM/%E8%AA%B2%E7%A8%8B%E7%89%B9% E8%89%B2/%E5%8D%9A%E5%A3%AB%E7%8F%AD#1.
15
National University of Singapore Program. (2014). Retrieved from http://www. comp.nus.edu.sg/is/ug-bcomp-is.html#pagetop.
16
NYU Stern University Program. (2014). Retrieved from http://www.stern.nyu. Edu /experience-stern/about/departments-centers-initiatives/academic-departments/ ioms-dept/academic-programs-courses/phd-programs/phd-information-systems #IS-Overview.
17
O’Donovan, B. & Roode, D. (2002). A framework for understanding the emerging discipline of information systems. Information Technology & People, 15 (1): 26 – 41.
18
Purdue University Program. (2014). Retrieved from http://krannert.purdue.edu /academics/MIS/phd/home.asp.
19
QS Stars Ranking. (2013). Retrieved from http://www.topuniversities.com/ university-rankings.
20
Shanghai Ranking. (2013). Retrieved from http://www.shanghairanking.com /ARWU2013.html.
21
Sidorova, A., Evangelopoulos, N., Valacich, J. S. & Ramakrishnan, T. (2008). UncoveringThe Intellectual Core of the Information Systems Discipline. MIS Quarterly, 32 (3): 467-482.
22
The Hong Kong University of Science and Technology Program. (2014).Retrieved from http://www.bm.ust.hk/isom/programs/phd_is/index.htm.
23
Times Higher Education Ranking. (2013). Retrieved from http://www.usnews. com/education/best-global-universities/rankings.
24
Topi, H., Valacich, J. S., Wright, R. T., Kaiser, K. M., Nunamaker, Jr. J.F., Sipior, J.C., de Vreede, G.J. (2010). IS 2010: Curriculum Guidelines for Undergraduate Degree Programs in Information Systems. Association for Computing Machinery and Association for Information Systems.
25
University of Arizona Program. (2014). Retrieved from http://mis.eller.arizona. edu/doctoral/courses.asp.
26
University of Georgia Program. (2104). Retrieved from http://www.terry. uga.edu/phd/concentrations/management-information-systems.
27
University of Illinois at Urbana-Champaign Program (2014). Retrieved from https://business.illinois.edu/ba/programs/phd/areas/infosys/.
28
University of Maryland Program. (2014). Retrieved from http://www.rhsmith. umd. edu/programs/phd-program/academics/fields-study/information-systems.
29
University of Minnesota Program. (2014). Retrieved from http://carlsonschool. umn.edu/degrees/phd/areas-concentration/information-and-decision-sciences.
30
University of Texas at Austin Program. (2014). Retrieved from http://www. mccombs.utexas.edu/Departments/IROM/Degree-Programs/PhD/IS.
31
University of Toronto Program. (2014).Retrieved fromhttp://www.ischool. utoronto.ca/phd.
32
ORIGINAL_ARTICLE
Introducing a model of influencing factors of customer's trust and satisfaction in E-commerce area (Case study: Group discount sites in Iran)
Studying the influencing factors on customer's trust and satisfaction in E-Commerce and adopting appropriate strategies about these factors are among the effective methods in achieving success in E-Commerce area. This article focuses on the study of effective factors on customer's trust and satisfaction in group discount websites. In this research, firstly the factor influencing on customer's satisfaction in E-commerce has been extracted through the conceptual study and the review of literature and the structural equation modeling has been presented. Then, E-questionnaire was given to the customers of group discount websites in Iran in order to evaluate the model and the relationships among the variables of the model. The analysis of the obtained results conducted through Partial least Square method proved the hypotheses of this model. The results of this research have provided with useful insight for those people who work in E-commerce; hence, they can design successful group discount websites based on group purchase income model.
https://jitm.ut.ac.ir/article_54289_cd1e1d65e58633aaa78391d2b2e77afc.pdf
2015-09-01
655
674
10.22059/jitm.2015.54289
E-commerce
group purchase
customer's satisfaction
customer`s trust
Naser
Asgari
nasgari@alumni.ut.ac.ir
1
Assistant Prof., Faculty of Management, Sattari University, Tehran, Iran
LEAD_AUTHOR
Hamed
Heidari
hamed.16633@yahoo.com
2
PhD Student, Faculty of Management, Islamid Azad University of Qazvin, Qazvin, Iran
AUTHOR
Afroozi, A. A., Parhizgar, M.M. & Rabie, A. (2011). Advance Research Method in management. Tehran: Payam Noor University. (in Persian)
1
Ahn, T., Ryu, S. & Han, I. (2007). The impact of Web quality and playfulness on user acceptance of online retailing. Information & Management, 44(3): 263-275.
2
Bagozzi, R.P. & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the academy of marketing science, 16(1): 74-94.
3
Biswamohan, D. & Bidhubhusan, M. (2012). E-CRM Practices and Customer Satisfaction in Insurance Sector. Research Journal of Management Sciences, 1(1): 2-6.
4
Bu, G.M., Zhang, B.W. & Rui, C. (2010). The Application of Unascertained Measurement Model in Customer Satisfaction of Electronic Business. Paper presented at the Management and Service Science (MASS). 2010 International Conference on. 24-26 Aug. DOI: 10.1109/ICMSS.2010. 5576814.
5
Chang, H.H. & Chen, S.W. (2009). Consumer perception of interface quality, security, and loyalty in electronic commerce. Information & Management, 46(7): 411-417.
6
Chen, Sh. C. (2012). The customer satisfaction–loyalty relation in an interactive e-service setting: The mediators. Journal of Retailing and Consumer Services, 19(2): 202-210.
7
Cronbach, L.J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3): 297-334.
8
Delone, W. H. (2003). The DeLone and McLean model of information systems success: a ten-year update. Journal of management information systems, 19(4): 9-30.
9
Delone, W. H. & Mclean, E. R. (2004). Measuring e-commerce success: applying the DeLone & McLean information systems success model. International Journal of Electronic Commerce, 9(1): 31-47.
10
Dong, X.M. (2012). Index system and evaluation model of e-commerce customer satisfaction. Paper presented at the Robotics and Applications (ISRA), IEEE Symposium on.
11
Fornell, C. & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18 (1): 39-50.
12
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13
Hong, K.K. & Kim, Y.G. (2002). The critical success factors for ERP implementation: an organizational fit perspective. Information & Management, 40(1): 25-40.
14
Hung, S.W., Cheng, M.J. & Hsieh, Sh.C. (2015). Consumers’ satisfaction with online group buying–an incentive strategy. International Journal of Retail & Distribution Management, 43(2): 167-182.
15
Jiao, Y., Yang, Jian, & Zhu, Zhanfeng. (2012). An Empirical Study of Customer Loyalty to Internet Banking in China. Paper presented at the e-Business Engineering (ICEBE), 2012 IEEE Ninth International Conference on. 9-11 Sept. DOI:10.1109/ICEBE.2012.16.
16
Karimi, M.R., Sepandarand, S. & HaghShenas, F. (2012). Study of the Effects of Customers’ Perceptions of Security and Trust on their Use of the Agriculture Bank of Iran’s e-Payment System. journal of Information Technology Management, 4(11): 135-154. (in Persian)
17
Karimi, M.R. & Ahmadi, SH. (2014). The Effect of News Websites’ Design Quality on E- loyalty and Electronic Word of Mouth (e-wom) (Case Study: Allameh Tabatabaee University, Tehran). journal of Information Technology Management, 6(2): 285-306. (in Persian)
18
Khalifa, M. & Liu, V. (2007). Online consumer retention: contingent effects of online shopping habit and online shopping experience. European Journal of Information Systems, 16(6): 780-792.
19
La, Kh.V. & Kandampully, J. (2002). Electronic retailing and distribution of services: cyber intermediaries that serve customers and service providers. Managing service quality, 12(2): 100-116.
20
Lari, S. A. & Hosseini, M. (2013). Web 2.0 Business Models Taxonomy and its Relation with Web 2.0 Features. journal of Information Technology Management, 5(3): 169-190. (in Persian)
21
Lin, H.F. (2007). The impact of website quality dimensions on customer satisfaction in the B2C e-commerce context. Total Quality Management and Business Excellence, 18(4): 363-378.
22
Liu, Y., Zhou, Ch.F. & Chen, Y.W. (2006). Determinants of E-CRM in influencing customer satisfaction PRICAI 2006: Trends in Artificial Intelligence, 4099: 767-776.
23
Lohse, G.L. & Spiller, P. (1998). Electronic shopping. Communications of the ACM, 41(7): 81-87.
24
Lu, J. (2003). A model for evaluating e-commerce based on cost/benefit and customer satisfaction. Information Systems Frontiers, 5(3): 265-277.
25
Markus, M. L. & Tanis, C. (2000). The enterprise systems experience–from adoption to success. Framing the domains of IT research: Glimpsing the future through the past, 173: 207-173.
26
McKnight, D.H. & Chervany, N.L. (2002). What trust means in e-commerce customer relationships: an interdisciplinary conceptual typology. International journal of electronic commerce, 6(2): 35-59.
27
Nazari, M. & Baghdadi, M. (2013). Investigating the Factors that Influence Online Impulsive Buying in Iran - Survey on Group Discount Websites. journal of Information Technology Management, 5(3): 223-239. (in Persian)
28
Nicolaou, A. I. & McKnight, D. H. (2006). Perceived information quality in data exchanges: Effects on risk, trust, and intention to use. Information Systems Research, 17(4), 332-351.
29
Norizan, K. & Nor Asiah, A. (2010). The effect of perceived service quality dimensions on customer satisfaction, trust, and loyalty in e-commerce settings: a cross cultural analysis. Asia Pacific Journal of Marketing and Logistics, 22(3): 351-371.
30
Ranganathan, C. & Ganapathy, Sh. (2002). Key dimensions of business-to-consumer web sites. Information & Management, 39(6): 457-465.
31
Roh, T. H., Ahn, Ch. K. & Han, I. (2005). The priority factor model for customer relationship management system success. Expert systems with applications, 28(4): 641-654.
32
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33
Sajedifar, A.A., Esfidani, M. R., Vahdatzad, M.H. & Mahmoodi Azar, M. (2012). The Effect of Electronic Services Quality on Trust-Building in Online Customers of Tehran’s Brokerage Firms. journal of Information Technology Management, 4(11): 47-68. (in Persian)
34
Santouridis, I., Trivellas, P. & Reklitis, P. (2009). Internet service quality and customer satisfaction: Examining internet banking in Greece. Total Quality Management, 20(2): 223-239.
35
Schaupp, L.CH., Belanger, F. & Fan, W. (2009). Examining the success of websites beyond e-commerce: An extension of the IS success model. Journal of Computer Information Systems, 49(4): 42-52.
36
Sun, Q., Wang, CH. & Cao, H. (2009). Applying E-S-QUAL Scale to Analysis the Factors Affecting Consumers to Use Internet Banking Services. Paper presented at the International Conference on Services Science, Management and Engineering. 11-12 July, Zhangjiajie. DOI: 10.1109/SSME.2009.41.
37
Sun, Q. (2010). Assessing the effects of e-service quality and esatisfaction on internet banking loyalty in China. Paper presented at the International Conference on E-Business and E-Government. 7-9 May. Guangzhou. DOI: 10.1109/ICEE.2010.31.
38
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39
Van Riel, A.C.R., Liljander, V. & Jurriens, P. (2001). Exploring consumer evaluations of e-services: a portal site. International Journal of Service Industry Management, 12(4): 359-377.
40
Wang, J.L., Liu, S.F., Wang, Y.Q. & Xie, N.M. (2008). Evaluation of customer satisfaction in automobile after-sales service based on grey incidence analysis. Paper presented at the Systems, Man and Cybernetics, 2008. SMC 2008. IEEE International Conference on. Singapore, 12-15 Oct. DOI: 10.1109/ICSMC.2008.4811651.
41
Wang, Y., Zhao, X. & Qiao, M. (2011). Customer Satisfaction Evaluation in Retail Businesses. Paper presented at the Information Management, Innovation Management and Industrial Engineering (ICIII), 2011 International Conference on. 26-27 Nov. Shenzhen, China DOI: 10.1109/ICIII.2011.322.
42
Wah Yap, B., Ramayah, T, & Wan Shahidan, W. N. (2012). Satisfaction and trust on customer loyalty: a PLS approach. Business Strategy Series, 13(4): 154-167.
43
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44
Yang, ZH., Cai, SH., Zhou, Z. & Zhou, N. (2005). Development and validation of an instrument to measure user perceived service quality of information presenting web portals. Information & Management, 42(4): 575-589.
45
Zeithaml, V. A., Parasuraman, A. & Malhotra, A. (2002). Service quality delivery through web sites: a critical review of extant knowledge. Journal of the academy of marketing science, 30(4): 362-375.
46
Zhang, P. & Von Dran, G. (2002). User expectations and rankings of quality factors in different web site domains. International Journal of Electronic Commerce, 6 (2): 9-34.
47
ORIGINAL_ARTICLE
Inter-organizational information systems integration: Representing a model for understanding integration problem domain
The goal of this article is to proposing a conceptual model explaining the Information Systems Integration. In this paper, passing the concept of Intra-Organizational Information Systems Integration, we emphasis on the concept of Inter-Organizational Integration.The problem is what the Information Systems Integration is, and which problems the organizations face.The method using in this research is a four step method proposed according to the system thinking and related theories in this domain. Due to the fact that, emphasizing on the Inter-Organizational Information Systems, at the first step we draw an expanded conceptual model of the Organizational Informatics Doman between the two organizations. After that, this model expands within the network of organizations. This model has a lot of applications. For example, using this model, we can provide a list of the important and required managerial and technical issues for the successful implementation of integration projects, which these expensive projects and programs will fail without this notification. Moreover, aggregating cognitive propositions extracting from this model, we are able to achieve an initial theory regarding Information Systems Integration.
https://jitm.ut.ac.ir/article_54709_f92bddddd3e209e9f21d7f7b78492c0b.pdf
2015-09-01
675
696
10.22059/jitm.2015.54709
Conceptual model
complex systems
expanded organizational informatics domain
Integration
inter-organizational information systems
Hassanali
Nemati Shamsabad
nemati@ut.ac.ir
1
Ph.D. in Information Technology Management, Faculty of Management, University of Tehran, Iran
LEAD_AUTHOR
Ali
Moeini
moeini@ut.ac.ir
2
Associate Prof., Faculty of Economic and Political Sciences, University of Tehran, Iran
AUTHOR
Aghajani, H., Samadi, H., Khanzadeg, M. & Samadi, H. (2014). Feasibility Study of Enterprise Resources Planning (ERP) Systems’ Implementation (Empirical Evidence: National Iranian Oil Petroleum Diffusion Cooperation (NIOPDC) – Sari Zone). Journal of Information Technology Management, 6(2): 161-186.
1
Bashokouh, M. & Alipoor, V. (2012). Communication Role in Coordinating Multiple Distribution Channels in the Electronics Industry. Journal of Information Technology Management, 4(10): 1-24.
2
Beer, S. (1984). The Viable System Model: Its Provenance, Development, Methodology and Pathology. The Journal of the Operational Research Society, 35 (1): 7-25.
3
Beynon-Davies, P. (2009). Business Information Systems. New York: PalGrave Macmilian.
4
Hasselbring, W. (2000). Information Systems Integration. ACM - Communications of the ACM , 43 (6): 33-38.
5
Hearn, G. & Pace, C. (2006). Value‐creating ecologies: understanding next generation business systems. foresight,8 (1): 55 - 65.
6
Hester, P.T. & Adams, K.M. (2013). Thinking Systemically About Complex Systems. Complex Adabtive Systems, Publication 3 (pp. 312-317). Missouri: Procedia Computer Scinece (ScienceDirect).
7
Holland, J. H. (2006). Studying Complex Adaptive Systems. Journal of Systems Science and Complexity, 19 (2): 1-8.
8
Kanz, M. & Krantz, M. (2003). The Design of an IT-System That Supports TQMain. Sweden: School of Mathematics and Systems Engineering MSI Vaxjo University.
9
Khalil, T. (2002). Management of Technology: Key Success Factors for Innovation and Sustainable Development. by Bagheri, Tehran: Matn. (in Persian)
10
Linthicum, D.S. (1999). Enterprise Application Integration. Addison Wesley.
11
Linthicum, D.S. (2004). Next Generation Application Integration: From Simple Information to Web Services. Addison-Wesley Professional.
12
Manian, A., Sarami, M. & Arabsorkhi, A. (2009). A Conceptual Model for Evaluating the Organizational Readiness for Establishing IT-Business Alignment (a Case study in ITRC). Journal of Information Technology Management, 1(1): 83-104.
13
Marashi, S., Baligh, V. & Ghiasabadi, A. (2006). Systems Thinking and evaluate its efficacy in the management of Society and organization. Tehran: Industrial Management Organization. (in Persian)
14
Mayerson, J. M. (2000). Enterprise Sysytems Integration. Best Practices Series.
15
McMillan, E. (2004). Complexity, Organizations and Change. Routledge.
16
Mirzaei Ahranjani, H., (2006). Methodological aspects of organization theory. Tehran; Samt. (in Persian)
17
Nemati Shamsabad, H. & Tabaei Aghdaei, Z. (2015). Intellihence and Knowledge in Organizationl Informatics Domain. 7th Knowledge Management Confrence, Shahid Beheshti Univesity, Tehran, Iran. (in Persian)
18
Nemati Shamsabad, H. (2006). An Appropriate Pattern for the Coordination and Integration of Information Systems in an Educational & Academic Enterprise. Master Thesis: Faculty of Management, University of Tehran.
19
(in Persian)
20
Puschman, T. & Alt, R. (2004). Enterprise Application Integration Systems and Architecture- the Case of the Robert Bosch Group. The Journal of Enterprise Information Management, 17 (2): 105-1160.
21
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