ORIGINAL_ARTICLE
The relationship between stock liquidity risk and financial information quality criteria in Tehran Stock Exchange
The current study aims to investigate the relationship between stock liquidity risk and financial information quality criteria (i.e. the timely dividends announcement, accruals quality and the percentage of profitability prediction error) of companies listed on the Tehran Stock Exchange. For this purpose, 148 cases of data from listed companies, collected from 2007 to 2012, were employed in order to test the hypotheses during 2007-2012. The results of the study reveal that there is a significant relationship between liquidity risk (the dependent variable) with quality of accruals, percentage of profitability prediction error and timely dividends announcement (independent variables). High levels of accruals quality and timely dividends announcement, cause reduction in stock's liquidity risk, and high percentages of profitability prediction error increase the stocks' liquidity risk.
https://ijms.ut.ac.ir/article_54999_8ecfd7144ae341c481e79e0f433e8c54.pdf
2015-10-01
503
521
10.22059/ijms.2015.54999
Accruals quality
Liquidity risk
percentage of profitability prediction
quality of information
timely dividends announcement
Mahmoud
Mousavi Shiri
mousavi1973@yahoo.com
1
Department of Economics, Management and Accounting, Payame Noor University, Iran
LEAD_AUTHOR
Masome
Roshandel
m.roshandel2011@gmail.com
2
Department of accounting, Islamic Azad University of Mashad, Mashad, Iran
AUTHOR
Acharya, V. & Pedersen, L.H. (2005). “Asset pricing with liquidity risk”. Journal of Financial Economics, 77(2), 375–410.
1
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2
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3
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7
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22
ORIGINAL_ARTICLE
Corporate diversification and efficiency of manufacturing firms listed in Bursa Malaysia
There is little consensus on the corporate diversification-efficiency relationship in the diversification literature. The study aims to contribute to the literature by looking jointly at two dimensions of corporate diversification as product diversification and international diversification and the relationship between them. The results show negative relationship between product diversification and efficiency, international diversification and efficiency and corporate diversification and efficiency in manufacturing firms listed in Bursa Malaysia. This study also has described main variables which have an impact on the diversification-efficiency relationship and has guided managers on how to pursue an optimal diversification strategy.
https://ijms.ut.ac.ir/article_55000_519f137aa22dcd0aca9bc10fbc6a6e83.pdf
2015-10-01
523
544
10.22059/ijms.2015.55000
Corporate diversification
International diversification and efficiency
Product diversification
Meysam
Doaei
mdoaeii@gmail.com
1
Research, Development and Islamic Studies Center, Securities and Exchange Organization, Tehran, Iran
LEAD_AUTHOR
Melati
Ahmad Anuar
m-melati@utm.my
2
Faculty of Management, Universiti Teknologi Malaysia, Skudai, Johor Bahro, Malaysia
AUTHOR
Zuhaimy
Ismail
zuhaimy@utm.my
3
Faculty of Science, Universiti Teknologi Malaysia, Skudai, Johor Bahro, Malaysia
AUTHOR
Ahmad, A. C.; Ishak, Z., & Manaf, N. A. A. (2003). “Corporate governance, ownership structure and corporate diversification: Evidence from the Malaysian listed companies”. Asian Academy of Management Journal, 8, 67-89.
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87
ORIGINAL_ARTICLE
Positive psychological capital: The role of Islamic work ethics in Tehran Public Organizations
Swift development in economic aspects and the call for more concentration on the ethics in new era is taking considerations in the world. The aim of this study was the investigation of the impact of the Islamic work ethics and its aspects in every point of human being characters, especially in employees’ hope, resilience, optimism and efficacy, as the dimensions of Positive Psychological Capital. The conducted research method for achieving mentioned aim was descriptive and correlation and the statistical population were employees of six public organizations in the Tehran province located in Iran (a country with the large Muslim population), participated in this study. The results of the analyzing the questionnaires and testing the hypotheses by Warp PLS indicated Islamic Work Ethics had positive effect on Positive Psychological Capital. These findings provide evidence to the importance of including Islamic Work Ethics in future research. Additionally, these findings provide significant suggestions for the utilization of Islamic work ethics in organizational practice too, that is in Staff recruitment, Compensation, Performance evaluation and HRM Strategies.
https://ijms.ut.ac.ir/article_55001_dfeff7dbfd546c0a9feb515ed6293158.pdf
2015-10-01
545
566
10.22059/ijms.2015.55001
Ethics
Islamic work ethics
Positive psychological capital
Saied
Sehhat
sehhat@yahoo.com
1
Faculty of Management and Accounting, Allameh Tabataba'i University, Tehran, Iran
AUTHOR
Seid Mojataba
Mahmoud zadeh
sm.mahmoudzadeh@yahoo.com
2
Faculty of Management and Accounting, Allameh Tabataba'i University, Tehran, Iran
AUTHOR
Mostafa
Ashena
m_ashena10@yahoo.com
3
Faculty of Management and Accounting, Allameh Tabataba'i University, Tehran, Iran
LEAD_AUTHOR
Samira
Parsa
samira.parsa@yahoo.com
4
Alzahra University
AUTHOR
Abdul Rashid, M. Z. & Ibrahim, S. (2005). “Students’ perceptions of business ethics: does religiousness matter?”. Proceedings of the 2nd International Conference of the Asian Academy of Applied Business, Padang, Indonesia: Universitas Andalas.
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Ali, J.A. (2005). Islamic Perspectives on Management and Organization. Edward Elgar Publishing, UK.
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Ali, J.A. & Al-Owaihan, A. (2008). “Islamic work ethic: a critical review”. Cross Cultural Management an International Journal. 15(1), 5-19.
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Ali, JA & Al-Kazemi, A (2007). “Managerial problems in Kuwait”. Journal of Management Development, 21(5), 366-375. Avey, B. (2011). “Meta-Analysis of the Impact of Positive Psychological Capital on Employee Attitudes, Behaviors, and Performance”. human esource development quarterly, 22(2).
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Quarterly, 33(4), 689-708.
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34
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55
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56
ORIGINAL_ARTICLE
Activity– level as a link between customer retention and consumer lifetime value
Customer activity has received more attention due to the increase of social network applications. Moreover, customer activity could be an answer to the research debate about the significant relationship between retention rate and lifetime profitability of customers. Several researchers believe that an increase in the retention rate of customers may enhance their customer lifetime value (CLV), or their lifetime profitability. Other researchers believe that this relationship does not exist or is not significant, and retention rate alone cannot adequately explain lifetime value. This study aims to tackle this challenge and empirically examines the relationship between retention rate and CLV. Moreover, it investigates whether the activity level of customers increases the relationship between retention rate and CLV. This research has been empirically verified in the banking industry; and various techniques including analytic hierarchy process (AHP), mathematical models, and statistical techniques have been used. The empirical results reveal an exponential correlation between the combination of activity level and retention rate with CLV.
https://ijms.ut.ac.ir/article_55002_67ec1b0ef1a7349ccc57201122d90b7f.pdf
2015-10-01
567
587
10.22059/ijms.2015.55002
customer activity
Customer Lifetime Value (CLV)
customer retention
Relationship marketing
Neda
Abdolvand
n.abdolvand@alzahra.ac.ir
1
Assistant Professor, Management Department, Faculty of Social Science and Economics, Alzahra University, Iran
LEAD_AUTHOR
Vahid
Baradaran
v_baradaran@iau-tnb.ac.ir
2
Industrial Engineering Department, Islamic Azad University-Tehran North Branch
AUTHOR
Amir
Albadvi
amir.albadvi@gmail.com
3
Faculty of Engineering, Tarbiat Modares University, Iran
AUTHOR
Abdolvand, N.; Albadvi, A. & Koosha, H. (2014). “Customer Lifetime Value: Literature Scoping Map, and an Agenda for Future Research”. International Journal of Management Perspective, 1(3), 41-59.
1
Al-Hawari, M. (2006). “The effect of automated service quality on bank financial performance and the mediating role of customer retention”. Journal of Financial Services Marketing, 10(3), 226-243.
2
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3
Brodie, R. J.; Hollebeek, L. D.; Juric´, B. & Ilic, A. (2011). “Customer Engagement: Conceptual Domain, Fundamental Propositions, and Implications for Research”. Journal of Service Research, 14(3), 252-271.
4
Campbell, D. & Frei, F. (2009). “Cost Structure, Customer Profitability, and Retention Implications of Self-Service Distribution Channels: Evidence from Customer Behavior in an Online Banking Channel”. Management Science, 56(1), 4-24.
5
Chandler, J. D. & Vargo, S. L. (2011). “Contextualization and value-in-context: How context frames exchange”. Journal of Marketing Theory, 11(1), 35-49.
6
Cohen, D.; Gan, C.; Yong, H. H. A. & Chong, E. (2007). “David Cohen; Christopher Gan; Hua Hwa Au Yong; Esther Chong”. David Cohen; Christopher Gan; Hua Hwa Au Yong; Esther Chong, 2(1), 40-79.
7
Dubihlela, J. & Khosa, P. M. (2014). “Impact of e-CRM Implementation on Customer Loyalty, Customer Retention and Customer Profitability for Hoteliers along the Vaal Meander of South Africa”. Mediterranean Journal of Social Sciences, 5(16), 175-183.
8
Farquhar, J. D. (2004). “Customer retention in retail financial services: an employee perspective”. The International Journal of Bank Marketing, 22(2/3), 86-99.
9
Gessner, G. H. & Volonino, L. (2005). “Quick Response Improves Return on Business Intelligence Investment”. Information System Management, 23(3), 66-74.
10
Gupta, S.; Hanssens, D.; Hardie, B.; Kahn, W.; Kumar, V.; Lin, N. (2006). “Modeling Customer Life-Time Value”. Journal of Service Research, 9(2), 139-155.
11
Gupta, S. & Lehman, D. R. (2003). “Customers as assets”. Journal of Interactive Marketing, 17(1), 9-24.
12
Gupta, S.; Lehmann, D. R. & Stuart, J. A. (2004). “Valuing Customers”. Journal of Marketing Research, XLI, 7-18.
13
Haenlien, M.; Kaplan, A. M. & Beeser, A. J. (2007). “A Model to Determine Customer Lifetime Value in a Retail Banking Context”. European Management Journal, 25(3), 221-234.
14
Harrison, T. & Ansell, J. (2002). “Customer retention in the insurance industry: Using survival analysis to predict cross-selling opportunities”. Journal of Financial Services Marketing, 6(3), 229-239.
15
Heinonen, K. (2009). “Health Care Customer Value Cocreation Practice Styles”. Int. J. Electronic Business, 7(2), 1-24.
16
Heinonen, K.; Strandvik, T. & Voima, P. (2013). “Customer dominant value formation in service”. European Business Review, 25(2), 104-123.
17
Helkkula, A.; Kelleher, C. & Pihlström, M. (2012). “Characterizing Value as an Experience : Implications for Service Researchers and Managers”. Journal of Service Research, 15(1), 59-75.
18
Hidalgo, P.; Manzur, E.; Olavarrieta, S. & Farías, P. (2007). “Customer retention and price matching: The AFPs case. Journal of Business Research, 61(6), 691-696.
19
Hoppe, D. & UdoWagner. (2014). “The role of lifetime activity cues in customer base analysis”. Journal of Business Research, 67(5), 963-989.
20
Hwang, Y. & Kim, D. J. (2007). “Customer self-service systems: The effects of perceived Web quality with service contents on enjoyment, anxiety, and e-trust”. Decision Support Systems, 43(3), 746-760.
21
Jain, D. & Singh, S. S. (2002). “Customer Lifetime Value Research in Marketing: A Review and Future Directions”. Journal of Interactive Marketing, 16(2), 34-46.
22
Kumar, V.; Ramani, G. & Bohling, T. (2004). “Customer Lifetime Value Approaches and Best Practice Applications”. Journal of Interactive Marketing, 18(3), 60-72.
23
Kumar, V.; Aksoy, L.; Donkers, B.; Venkatesan, R.; Wiesel, T. & Tillmanns, S. (2010). “Undervalued or Overvalued Customers: Capturing Total Customer Engagement Value”. Journal of Service Research, 13(3), 297-310.
24
Kwon, K. & Kim, C. (2012). “How to design personalization in a context of customer retention: Who personalizes what and to what extent?”. Electronic Commerce Research and Applications, 11, 101-116.
25
Mickelsson, J. (2013). “Customer Activity in Service”. Journal of Service Management, 24(5), 534-552.
26
Mickelsson, J. (2014). Customer Activity: A Perspective on Service Use. Hanken School of Economics, Helsinki, Finland.
27
Onyeaso, G. & Adalikwu, C. (2008). “An Empirical Test 0f Customer Retention-Perceived Quality Link: Strategic Management Implications”. Journal of Business Strategies, 25(1), 53-71.
28
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29
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30
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33
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34
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35
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36
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37
TAN, A. R. (2007) When Product Life Cylcle Meets Customer Activity Cycle. Paper presented at the 3rd Research Conference on Relationship Marketing and CRM, Brussels, Belgium.
38
Tsai, C.-F.; Hu, Y.-H.; Hung, C.-S. & Hsu, Y.-F. (2013). “A comparative study of hybrid machine learning techniques for customer lifetime value prediction”. Kybernetes, 42(3), 357-370.
39
Vargo, J. R. M.-K. S. L.; Dagger, T. S.; Sweeney, J. C. & Kasteren, Y. v. (2015). “Health Care Customer Value Cocreation Practice Styles”. Journal of Service Research, doi: 10.1177/1094670512442806.
40
Villanueva, J. & Hanssens, D. M. (2007). “Customer Equity: Measurement, Management and Research Opportunities”. Foundations and Trends in Marketing Intelligence & Planning, 1(1), 1-95.
41
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42
ORIGINAL_ARTICLE
Evaluation of recommender systems: A multi-criteria decision making approach
The evaluation and selection of recommender systems is a difficult decision making process. This difficulty is partially due to the large diversity of published evaluation criteria in addition to lack of standardized methods of evaluation. As such, a systematic methodology is needed that explicitly considers multiple, possibly conflicting metrics and assists decision makers to evaluate and find the best recommender system among a given set of alternatives. This paper introduces Multi-Criteria Decision Making (MCDM) approach for evaluation of recommender systems. In particular, this paper proposes the use of Data Envelopment Analysis (DEA) approach, as a sub-category of MCDM, in order to solve this problem. Various DEA models are introduced and their applicability are illustrated. A real case of evaluation of recommender systems is used to demonstrate the approach.
https://ijms.ut.ac.ir/article_55003_e0672151440415f08eafc2f15152f8af.pdf
2015-10-01
589
605
10.22059/ijms.2015.55003
Data Envelopment Analysis
Evaluation
metrics
Multi-Criteria Decision Making
Recommender systems
Babak
Sohrabi
bsohrabi@ut.ac.ir
1
Faculty of Management, University of Tehran
AUTHOR
Mehdi
Toloo
mehdi.toloo@vsb.cz
2
Department of Business Administration, Technical University of Ostrava
AUTHOR
Ali
Moeini
moeini@ut.ac.ir
3
School of Engineering, University of Tehran
AUTHOR
Soroosh
Nalchigar
soroosh.n@gmail.com
4
University of Tehran
LEAD_AUTHOR
Adomavicius, G. & Tuzhilin, A. (2005). “Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions”. Knowledge and Data Engineering, IEEE Transactions on, 17(6), 734-749.
1
Amin, G. R. (2009). “Comments on finding the most efficient DMUs in DEA: An improved integrated model”. Computers & Industrial Engineering, 56(4), 1701-1702.
2
Amin, G. R. & Toloo, M. (2007). “Finding the most efficient DMUs in DEA: An improved integrated model”. Computers & Industrial Engineering, 52(1), 71-77.
3
Balabanović, M. & Shoham, Y. (1997). “Fab: content-based, collaborative recommendation”. Communications of the ACM, 40(3), 66-72.
4
Banker, R. D.; Charnes, A. & Cooper, W. W. (1984). “Some models for estimating technical and scale inefficiencies in data envelopment analysis”. Management science, 30(9), 1078-1092.
5
Bobadilla, J.; Ortega, F.; Hernando, A. & Gutiérrez, A. (2013). “Recommender systems survey”. Knowledge-Based Systems, 46, 109-132.
6
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7
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8
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9
Cook, W. D. & Seiford, L. M. (2009). “Data envelopment analysis (DEA)–Thirty years on”. European Journal of Operational Research, 192(1), 1-17.
10
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11
Ertay, T.; Ruan, D. & Tuzkaya, U. R. (2006). “Integrating data envelopment analysis and analytic hierarchy for the facility layout design in manufacturing systems”. Information Sciences, 176(3), 237-262.
12
Fouss, F. & Saerens, M. (2008). “Evaluating performance of recommender systems: An experimental comparison”. In Web Intelligence and
13
Intelligent Agent Technology, 2008. WI-IAT'08. IEEE/WIC/ACM International Conference on (Vol. 1, pp. 735-738). IEEE.
14
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15
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17
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18
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19
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20
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23
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25
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28
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30
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31
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32
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33
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34
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35
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36
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37
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38
ORIGINAL_ARTICLE
Providing a multidimensional measurement model for assessing quality of sport tourism services: Empirical evidence from sport conference as sport event tourism
This study aimed to empirically develop a reliable and valid model specifically for measuring service quality of sport conferences as sport event tourism. To assess the model which has been established based on the survey, data gathered from 136 of attendees in sport conference. Finding of this study showed that participants form their service quality perceptions based on their evaluations of 4 primary dimensions including: venue quality, conference quality, access quality and trip quality. Total variance of these dimensions explained %53.82 variance of services quality. Confirmatory factor analysis showed that each of the four factors influence on the services quality, and the fit indices confirmed the conceptual model that presented in this study (Chi-Square=85.456, df=23, P=0.001, RMSEA=0.142). As a result, it is recommended to conference organizer and tourism managers, to considering these factors next to each other in order to increase and improve the service quality.
https://ijms.ut.ac.ir/article_55004_4674c662462171084e51cbd64485c6eb.pdf
2015-10-01
607
629
10.22059/ijms.2015.55004
Conference
Multidimensional scale
Service quality
Sport event
sport tourism
Reza
Andam
amir.montazeri1@yahoo.com
1
University of Shahrood
AUTHOR
Amir
Montazeri
amir.montazeri@stu.um.ac.ir
2
Ph.D. Student in Sport Management Ferdowsi University of Mashhad
LEAD_AUTHOR
Samira
Feizi
ariasport20@yahoo.com
3
Shomal University
AUTHOR
Rahimeh
Mehdizadeh
samira.feizi@gmail.com
4
University of Shahrood
AUTHOR
Alexandris, K.; Douka, S. & Balaska, P. (2012). “Involvement with active leisure participation: does service quality have a role?”. Managine Leisure, 17(1), 54 - 66.
1
Alexandris, K.; Zahariadis, P.; Tsorbatzoudis, C. & Grouios, G. (2004). “An empirical investigation of the relationship among service quality, customer satisfaction and psychological commitment in a health club context”. European Sport Management Quarterly, 4(1), 36 - 52.
2
Babakus, E. & Boller, G. W. (1992). “An empirical assessment of the SERVQUAL scale”. Journal of Business Research, 24, 235-268.
3
Baker, D. A. & Crompton, J. L. (2000). “Quality, satisfaction and behavioral intentions”. Annals of Tourism Research, 27(3), 785 - 804.
4
Bandalos, D. & Finney, S. (2009). “Item Parceling Issues in Structural Equation Modeling”. In G. A. Marcoulides, & R. Schumacker, New Developments and Techniques in Structural Equation Modeling (pp. 269-296). Taylor & Francis.
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53
ORIGINAL_ARTICLE
A model for illustrating the effective factors of strategic behavior (Case study: Social insurance company of Tehran)
Achieving the organizational objectives needs employees’ behavior and their collaboration with management. Strategic behavior-driven is depend on different factors. The aim of this article is to determine the impact of factors on strategic behavior-driven. A conceptual model was developed and tested on a survey in Social Insurance Company of Tehran which employees’ participated. Data collected by questionnaire from managers and stuffs and structure equation model (SEM) was used for data analysis by LISREL software. The findings show that employees’ engagement impact on strategic behavior-driven and perceptions of job autonomy, and organizational status were significantly impact on greater employees’ engagement.
https://ijms.ut.ac.ir/article_55005_0dd102c1c31b5ab2bad28eed3be0a2f1.pdf
2015-10-01
631
651
10.22059/ijms.2015.55005
Autonomy
Employee Engagement
Role benefit
Strategic behavior
Habibollah
Javanmard
h-javanmard@iau-arak.ac.ir
1
Associate Professor, Islamic Azad University, Arak Branch, Iran
LEAD_AUTHOR
Baumruk, R. (2004). “The missing link: the role of employee engagement in business success”. Workspan, 47, 48-52.
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17
Saks, A.M. (2006). “Antecedents and consequences of employee engagement”. Journal of Managerial Psychology, 21(7), 600-619.
18
Salanova, M.; Agut, S. & Peirό, J. M. (2005). “Linking the organizational resources and work engagement to employee performance and customer loyalty: The mediation of service climate”. Journal of Applied Psychology, 90(6), 1217-1227.
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Sanchez-Cardona, Israel.; Rodriguez-Montalban, R.; Alfonso-Soto, E.; NievesLugo, K.; Torres-Qquendo, F. & Toro-Alfonso, J. (2012). “Self-efficacy and openness to experience as antecedent of study engagement of study engagement: an exploratory analysis .University of Puerto Rico, Department of Psychology”. Procedia, Social and behavioral Sciences, 46, 2163-2167.
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21
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31
ORIGINAL_ARTICLE
A multi-objective resource-constrained optimization of time-cost trade-off problems in scheduling project
This paper presents a multi-objective resource-constrained project scheduling problem with positive and negative cash flows. The net present value (NPV) maximization and making span minimization are this study objectives. And since this problem is considered as complex optimization in NP-Hard context, we present a mathematical model for the given problem and solve three evolutionary algorithms; NSGA-II, MOSA and MOPSO are applied to find the set of Pareto solutions for this multi-objective scheduling problem. In order to show performance of the algorithms, different metrics are applied and comparisons between the two algorithms are also considered. The computational results for a set of test problems taken from the project scheduling problem Bandar Abbas Gas condensate Refinery project and library are presented and discussed. Finally, the computational results illustrate the superior performance of the NSGA-II, MOSA and MOPSO algorithm with regard to the proposed metrics. In order to solve proposed method from NSGA-II algorithm, the results are compared with GAMS software in some problems. The proposed method is a Converge to the optimum and efficient solution algorithm.
https://ijms.ut.ac.ir/article_55006_b200649e4b0d12785f22cd25a75628fb.pdf
2015-10-01
653
685
10.22059/ijms.2015.55006
Comparative indicators of evolutionary algorithms
MOSA and MOPSO algorithm
NSGA-II
payment patterns
Project scheduling
resource constraints
Mostafa
Zareei
mozare66@yahoo.com
1
Faculty of Industrial Engineering, Imam Hossein (AS) University, Tehran, Iran
LEAD_AUTHOR
Hossein Ali
Hassan-Pour
hahassan@ihu.ac.ir
2
Faculty of Industrial Engineering, Imam Hossein (AS) University, Tehran, Iran
AUTHOR
Aboutalebi, R.S.; Najafi, A.A. & Ghorashi, B. (2012). “Solving multi-mode resource-constrained project scheduling problem using two multi objective evolutionary algorithms”. African Journal of Business Management, 6, 4057-4065.
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2
Azimi, F.; Aboutalebi, R. S. & Najafi, A. A. (2011). “Using Multi-Objective Particle Swarm Optimization for Bi-objective Multi-Mode Resource Constrained Project Scheduling Problem”. World Academy of Science, Engineering and Technology, 54, 285-289.
3
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4
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5
Chen, W.N.; Zhang, J. & Liu, H. (2010). A Monte-Carlo Ant Colony System for Scheduling Multi-mode Project with Uncertainties to Optimize Cash flows. proceeding of IEEE Congress on Evolutionary Computation (CEC), 1-8.
6
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7
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8
“Nature-inspired meta-heuristics for multi objective activity crashing”. Omega, 36, 1019–1037.
9
Dayanand, N. & Padman, R. (1998). Project contracts and payment schedules: The client's problem. Working Paper, The Heinz School, Carnegie Mellon University, Pittsburgh, Pennsylvania.
10
El-Rayes, K. & Kandil, A. (2005). “Time-Cost-Quality Trade-Off Analysis for Highway Construction”. Journal of Construction Engineering and Management, 131, 477-486.
11
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12
Feng, C.; Liu, L. & Burns, S.A. (1997). “Using Genetic Algorithms to Solve
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Construction Time-Cost Trade-Off Problems”. Journal of Computing in Civil Engineering, 11, 184-189.
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Marek, M.; Grzegorz, W. O. & Wezglarz, J. (2005). “Simulated annealing and tabu search for multi-mode resource-constrained project scheduling with positive discounted cash flows and different payment models”. European Journal of Operational Research, 164, 639–668.
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Algorithm-Based Multi-objective Approach for Time-Cost Trade-Off”. Journal of Construction Engineering and Management, 134, 153-156.
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41
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