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Table 1. Facility and amenity factor loading and reliability. Items of facility and amenity Factor loading Cronbah alpha ATM machine 0.717 Photostat and printing services 0.714 Water machine 0.690 Storage rooms for unused staffs 0.625 Small library 0.616 24 h study room 0.611 Vending machine 0.552 Lift 0.539 Free internet access 0.539 Laundry with washer and dryer at each floor 0.538 Mirror in the room Hot water in the bathroom 0.516 0.516 0.92 Lockable storage space inside the room 0.515 Visual tour in website 0.503 Laundry monitoring system 0.499 Fitness room 0.498 Small mart 0.495 24 h Taxi for emergency use 0.483 Pin board in the room 0.429 Variety of food in food stall (Chinese Malay Indian) 0.427 Kitchen 0.358 Indoor pool (specially for female) 0.340 preferred facility. The next three important facilities were mentioned as mirror in the room (Mean 3.50, SD 0.69), water machine (Mean 3.43, SD .77) and variety of food in food stall (Mean 3.40, SD .80). In addition the students showed a great desire for facilities of pin board in the room (Mean 3.35 SD .74), Laundry with washer and dryer at each floor (Mean 3.33 SD .82), ATM machine (Mean 3.31 SD .92), big storage space inside the wall of the room (Mean 3.24 SD .77) , photostat and printing services (Mean 3.20 SD .92), 24 h study room (Mean 3.17 SD .93), small mart ( Mean 3.12 SD .90), lift (Mean 3.08 SD 1.05) fitness room (Mean 3.07 SD .91) laundry monitoring system ( Mean 3.05 SD .91) as well as storage room for unused stuffs (Mean 3.00 SD .91) as indicated by mean score of higher than 3. Besides, the facilities that might be generally found in the majority of university residence halls, this study also examined the students’ preferences for facilities such as kitchen, laundry monitoring system, 24 h taxi for emergency uses and indoor pool for female students. Among these facilities, students had the highest preference for laundry monitoring system (Mean 3.05, SD .91). This system is used by some universities from developed countries. With this system, students are able to check the availability of washing machines and dryers online through the internet. This system can easily help students to manage and save their time and instead of Khozaei et al. 7337 queuing for using washing machines and dryers, they can use the machines in less crowded hours. The students’ desire for having the kitchen in residence hall (M 2.95 SD 0.99) and 24 h available taxi (M 2.95 SD 0.94) were also respectively high. Further it was of interest to understand whether male and female students differ significantly on their preferences. Accordingly an independent sample t test was conducted. Significant differences were found between male and female students on facility and amenity preferences. These facilities and amenities were more important for female students than their male counterparts. Table 4 presents the result of the independent-samples t test. A series of 1 way ANOVA were performed to examine students’ preferences in base of nationality, race, and study level. No significant differences were found between mean score of students from different nationalities. However a significant difference was found between race and facility and amenity preferences. Post hoc comparisons using the Tamhanes’T2 test indicated that the mean score for Chinese students (M=71.49, SD=8.76) was significantly higher than the Malay students (M=68.68, SD=12.64). Table 5 The result of study also indicated a significant difference between study level (undergraduate, master by research, master by course work, PhD students) and facility and amenity preferences. Post hoc comparisons
7338 Afr. J. Bus. Manage. Table 2. Demographic characteristics of participants. Variable Valid percent Gender Male Female 32.2 67.8 Age Nationality Race Study level using the Tukey HSD test indicated that the mean score for undergraduate students (M=70.19, SD=11.50) was significantly higher than the PhD students (M=62.54, SD=11.94). DISCUSSION This study examined the degree of students’ preferences for some facilities and amenities in residence halls. This study which is a part of a vast study on student housing preferences conducted at the Universiti Sains Malaysia residence halls. The data collected for development of Student accommodation preferences index (SAPI) (Khozaei et al., 2011) was used for the means of study. SAPI is an instrument for study of students’ housing stated preferences. In fact studies on housing preferences can be categorized into two main categories; stated preferences and revealed preferences. Revealed preferences studies concentrate on residences’ current housing choice. It is supposed that the residences’ desire can be understood by their purchase or selected residence. In the other hand stated preference studies “are based on intended choices or hypothetical choices” (Coolen and Hoekstra, 2001). It is obvious that the stated preferences studies are more applicable in the context of on campus housing 18-20 41.0 21-23 44.0 24-26 6.3 27-29 3.6 above 30 5.2 Malaysian 88.3 Indonesian 0.8 Iranian 4.4 Iraqis 1.1 other 5.5 Malay 49.1 Indian 4.8 Chinese 36.3 other 9.8 Undergraduate 83.0 Master by research 2.5 Master course work 7.4 PhD 7.0 while the revealed preferences studies might lead to a better understanding of the off campus housing preferences” The result of this study revealed that among all facilities and amenities, free internet access, lockable storage space and mirror in students’ room, water machine and variety of food in food stall were the most 5 highest preferred facilities and amenities in the residence hall. Access to the internet was reported the highest preferred facility in the residence halls. The result of this study supports the studied that emphasizes on the importance of access to internet for today’s life. In fact in recent years several studies have examined the impor-tance of access to internet among different people of society such as students, travellers and firm staffs. In the for example context of university residence halls, khozaei et al. (2010) found that better access to internet was one of the reasons that students preferred a specific resi-dence hall to others. the other study showed that “overall Internet use for academic purposes has increased” and students have positive opinions about the Internet's utility for academic work (Jones et al., 2008). Ogan et al. (2008) with study of undergraduate students found that “respon-dents to the survey went to the Internet daily, on average for 4.4 h. Overall, students saw the Internet as having a positive impact on their lives”. In a evaluated the importance of some amenities in hotel rooms among male and
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African Journal of Business Managem
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Editors Prof. Wilfred Isioma Ukpere
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Electronic submission of manuscript
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Fees and Charges: Authors are requi
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Table of Contents: Volume 5 Number
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7166 Afr. J. Bus. Manage. the high
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7168 Afr. J. Bus. Manage. Cargo mov
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7170 Afr. J. Bus. Manage. has produ
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7172 Afr. J. Bus. Manage. resources
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7174 Afr. J. Bus. Manage. celebrate
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7176 Afr. J. Bus. Manage. effective
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7178 Afr. J. Bus. Manage. interacti
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7180 Afr. J. Bus. Manage. firstly,
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7182 Afr. J. Bus. Manage. TQM pract
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7184 Afr. J. Bus. Manage. with lowe
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7186 Afr. J. Bus. Manage. in a diff
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7190 Afr. J. Bus. Manage. Decision
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7192 Afr. J. Bus. Manage. restructu
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7194 Afr. J. Bus. Manage. Performan
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7196 Afr. J. Bus. Manage. firm perf
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African Journal Of Business Managem
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7200 Afr. J. Bus. Manage. to establ
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7202 Afr. J. Bus. Manage. marketing
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7204 Afr. J. Bus. Manage. initial a
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7206 Afr. J. Bus. Manage. from the
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7208 Afr. J. Bus. Manage. Phillips
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7210 Afr. J. Bus. Manage. of the sa
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7212 Afr. J. Bus. Manage. ′ w k m
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7214 Afr. J. Bus. Manage. procedure
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7218 Afr. J. Bus. Manage. Figure 2.
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7220 Afr. J. Bus. Manage. stimulate
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7222 Afr. J. Bus. Manage. these com
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7228 Afr. J. Bus. Manage. Table 2.
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7234 Afr. J. Bus. Manage. CRM resea
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7238 Afr. J. Bus. Manage. The one a
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7242 Afr. J. Bus. Manage. and Norto
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7250 Afr. J. Bus. Manage. DEFINING
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7256 Afr. J. Bus. Manage. critical
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7260 Afr. J. Bus. Manage. external
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7262 Afr. J. Bus. Manage. represent
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7270 Afr. J. Bus. Manage. business
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7274 Afr. J. Bus. Manage. Satisfact
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7276 Afr. J. Bus. Manage. Score of
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7282 Afr. J. Bus. Manage. Satisfact
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Page 222 and 223: Table 2. Companies and countries co
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Page 234 and 235: Table 5. Utilities for subject 1 Li
Page 236 and 237: REFERENCES Anderson JC, Narus JA (1
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7386 Afr. J. Bus. Manage. aggregate
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7388 Afr. J. Bus. Manage. Analysis
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(Bass and Avolio, 1994). Leaders fo
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the employees. When employees are e
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Table 1. Means, standard deviation
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negativity in the organization. Tra
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of psychological ownership. Thus te
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Meyer JP, Becker TE, Vandenberghe C
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goods industry in the future. LITER
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F + 2 0. 110 * F + Table 3. Factor
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APPENDIX Data for evaluation on the
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anks. Camanho and Dyson (2005) enha
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Step A-4: Correlation analysis Star
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Table 1. Original raw data of input
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Table 5. Scenario table. Wang and W
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Delmas M, Toka Y (2005). Deregulati
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Technology managers need to attract
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λ is the parameter for risk aversi
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specified ranges of return, for eac
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Carlsson C, Fulle´r R, Majlender P
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Stock Exchange, (Rao, 2010) in Nati
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etween size and unsystematic risk i
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The research schema Figure 1 indica
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Table 3. Result of Freidman rank te
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Table 8. The result of Spearman cor
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significant differences between the
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leadership. The process of manageri
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indices of quality of life work. On
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Figure 2. The values of standardize
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Table 4. The values of coaching ind
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Table 1. Contrast between hedonic a
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in consumers’ shopping behavior.
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et al., 2006; Carpenter, 2008). For
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Table 2. contd Shopping satisfactio
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value in the construct of clothing
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independence, assertiveness, innova
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over those of competitors in order
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Table 2. Demographic profile and ce
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Table 4. Service satisfaction level
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There is a strong significant corre
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Dean AM (2004). Rethinking customer
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as a margin rate of 10% and rest to
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(7) Table 1. Descriptive statistics
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APPENDIX A Table 1. Failure rate te
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Table 1. Results of the multivarian
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Figure 3. Entrepreneurship as a fun
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Furkukawa K, Shafer WE, Lee GM (200
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happen to firms of any and all size
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participants attributed their failu
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Table 1. Descriptive statistics of
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Table 4 Contd. Inconsideration of l
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Table 5 Contd. Manufacturing 2.17 1
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The CLRP is an NP-hard problem, so
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No START Form a new cluster. Select
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Table 1. Computational results of G
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Table 1. Correlation of facets of C
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Figure 1. Theoretical approach adop
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quadrant (III), including product v
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consistently showed negative (posit
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signal. This hypothesis predicts a
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Variables are defined as in the ful
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Table 3. The results of model (2).
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around the world. Q. Rev. Econ. Fin
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tourism industry development. In th
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Table 2. Canonical correlation. 2 C
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Table 5. Bilateral analysis and ran
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strategies (Hart, 1995; Tello and Y
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Table 1. Reliability and construct
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Table 3. Latent variables test. She
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Haines R, Street M, Haines D (2008)
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owned insurance firm to enter the m
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affective commitment; organizationa
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Figure 1. Structural relationships
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Prior to analysis, variables were e
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Table 1. Effect decomposition for M
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Figure 5. Unstandardized estimates
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prospects. In other words, less wor
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goal of a SCM process is to create
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Sale Lean Supply Chain (LSC) Growth
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Upper Saddle River: Pearson Prentic
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the green awareness movement by ado
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usiness practices than smaller firm
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Table 3. Descriptive statistics and
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China. Green leadership could be em
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APPENDIX Appendix 1: Measures of ob
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Emotional intelligence Self monitor
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ship between a people’s perceived
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Table 1. Analysis of the reliabilit
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Table 4. Results from hypothesis te
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Ajzen I, Driver BL (1992). Applicat
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mono production economy, and rural
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Table 2. Pearson correlation betwee
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Table 1. Behavioral Phenomenon that
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Table 3. Test period data. Table 4.
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Prospect value Figure 3. Expected v
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Tversky A, Gilovich T (1989). The H
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Table 1. Components of a mentoring
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Table 3. Perceptions on the success
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Table 5. Characteristics of a mento
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terms of sustained development, are
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Table 7. Ideal characteristics of m
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qualitative analysis of fifteen hou
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section. In Section 3, we will disc
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Table 1. Participants’ demographi
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of Am. Acad. of Bus., Cambridge. 4(
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directors and propose the board ind
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composition is the outcome of a neg
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Table 1. Descriptive statistics. Ti
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Table 3. The determinants of board
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Booth JR, Cornett M, Tehranian H (2
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provides a wider response and swift
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Correlation “Customary Approach
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Table 2. Correlation matrix of EAC
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Table 9. Intra-EAC imports as share
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Martin JC (1999). The European Mone
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participate in the highest degree o
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innovation. A secondary innovation
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Figure 2. The switching ecology of
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Table 1. Revenue growth rate and CA
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variables (Beattie and Jones, 1999a
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Table 3. Explanations of dependent
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Courtis JK (1997). Corporate annual
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treated in the literature, its rela
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company. METHODOLOGY Table 1. Quest
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as an important factor in the manag
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satisfaction may also reduce the ov
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Table 1. Customer expectations on s
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Table 2. Contd. Machirori and Fatok
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and travelling may lead to satisfac
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and professionally developmental pr
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Table 1. Organizational elements mo
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Table 2. Studying the demographical
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education might involve plenty of c
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(Deng et al., 2010). To date, there
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Table 2. Results of hierarchical re
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WOM. The comparison can be seen in
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UPCOMING CONFERENCES International
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