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company. METHODOLOGY Table 1. Questions measuring main variables. Fazlzadeh et al. 7661 Latent variables Mean Delivery service quality Reliability in delivery times 3.43 Quality of the product packaging when delivered 3.42 Transfer of product to your place 3.33 Quality of the product itself when delivered 3.39 Reception of the proper invoice/delivery papers 3.27 Kindness and friendliness of the delivery personnel 3.57 Appearance of the delivery personnel (uniform, cleanness) 3.47 Installation service quality Accurate information about time of installation 3.31 Time elapsed between delivery and installation 3.36 Attentiveness of installation personnel in order to avoid damages 3.16 Flawless of the installation 3.17 Kindness and friendliness of the installation personnel 3.22 Advice and instructions given by the technicians 3.28 Overall satisfaction Level of satisfaction from their co-operation with the retailer in the context of the particular purchase 3.51 Re-purchase intention Intention to prefer the same retailer in the next purchase of a new home appliance Word of mouth Intention to recommend the retailer to friends and relatives 3.25 This study attempt to understand affect quality of after-sales services on customer overall satisfaction and on their behavioural intentions to re-purchase and to recommend (Word-of-Mouth). According to the Rigopoulou et al. (2008), we used a behavioural model in which the following latent variables are included: 1) “Delivery” service quality, that this variable is measured as a latent one using seven indicators, including the “reliability in delivery times” (D1), the “quality of the product packaging when delivered” (D2), the “transfer of product” (D3), the “quality of the product itself when delivered” (D4), the “reception of the proper invoice/delivery papers” (D5), the “kindness and friendliness of the delivery personnel” (D6) and the “appearance of the delivery personnel” (D7). 2) “Installation” service quality, that this variable is measured as a latent one using six indicators, including the “accurate information about time of installation” (I1), the “time elapsed between delivery and installation” (I2), the “attentiveness of installation personnel in order to avoid damages” (I3), the “flawless of the installation” (I4), the “kindness and friendliness of the installation personnel” (I5) and 3.49 the “advice and instructions given by the technicians” (I6). In the model, the following measurement variables are included: i. “Overall Satisfaction”, which refers to the customers’ level of satisfaction from their co-operation with the retailer in the context of the particular purchase. ii. “Repurchase Intention” which is related to the customers’ intention to prefer the same retailer in the next purchase of a new electric appliance. iii. “Word-of-Mouth” which refers to the customers’ intention to recommend the retailer to their friends and relatives. The product category under examination is home appliances in Iran that offer after-sales services to customers. The research conducted was based on questionnaire as a research tool. Overall, a total of 302 usable responses were included in the research conducted. The variables (Table 1) were measured on five-point scales anchored “completely dissatisfied” and “fully satisfied” or “definitely yes” – “definitely no”, respectively. The structural equation modelling (SEM) was performed using the “Amos 18” software. RESULTS Table 1 show that, respondents feel quite satisfied from
7662 Afr. J. Bus. Manage. Figure 1. The model. Table 2. Goodness of fit test results for the model. Variable � � GFI AGFI NFI TLI IFI CFI RMSEA Value 96.3 0.963 0.940 0.986 0.997 0.998 0.998 0.022 Installation both after-sales services offered, namely “delivery” and “installation”. The mean score of the satisfaction regarding the “delivery” is 3.45, while the respective score for “installation” is slightly lower (3.25). The vast majority of the specific quality elements of the two services, were judged by the respondents to be quite satisfactorily provided, with mean scores from 3.27 to 3.57 for delivery and 3.16 to 3.36 for installation, Mean scores for “word of mouth” (3.25) and “repurchase intention” (3.49). For the scales reliability analysis, Cronbach α, were calculated for both latent variable measurement scales. Results revealed that both “delivery” (αD = 0.972) and “installation” (αI = 0.947) scales were reliable. According to the results, as presented in Table 2, all the important indicators of the model fit, as suggested by Hoyle (1995), have accepted values. For this reason, this Overall satisfaction model is considered as an acceptable one (Figure 1). As (Figure 1) indicated: 1. “Delivery” and “installation” service quality positively affect customers’ overall satisfaction. 2. “Delivery” and “installation” service quality positively affect customer’s intention for recommendations. 3. “Delivery” and “installation” service quality positively affect customers re-purchase intentions. 4. Overall, satisfaction positively affects customers’ intentions to recommend the retailer to friends and relatives. 5. Overall, satisfaction positively affects customers’ repurchase intentions. Conclusion Customer satisfaction has been studied and recognized
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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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7292 Afr. J. Bus. Manage. determine
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7298 Afr. J. Bus. Manage. Procedure
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7308 Afr. J. Bus. Manage. required
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7310 Afr. J. Bus. Manage. This obse
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7318 Afr. J. Bus. Manage. expectati
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7320 Afr. J. Bus. Manage. Compensat
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7324 Afr. J. Bus. Manage. Psychol.,
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7326 Afr. J. Bus. Manage. the resea
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7328 Afr. J. Bus. Manage. Z( T, whe
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7330 Afr. J. Bus. Manage. (10) and
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7332 Afr. J. Bus. Manage. during wh
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7334 Afr. J. Bus. Manage. optimal v
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7336 Afr. J. Bus. Manage. satisfact
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7340 Afr. J. Bus. Manage. female re
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7344 Afr. J. Bus. Manage. Populatio
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7352 Afr. J. Bus. Manage. ln S = ln
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7356 Afr. J. Bus. Manage. but some
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7358 Afr. J. Bus. Manage. investiga
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7360 Afr. J. Bus. Manage. when conf
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7362 Afr. J. Bus. Manage. PCs in a
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7364 Afr. J. Bus. Manage. supported
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7366 Afr. J. Bus. Manage. Psychol.,
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7368 Afr. J. Bus. Manage. social pr
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Table 2. Companies and countries co
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to CSR clearly and reliably. The st
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consumers to participate with the t
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A Liao 7379 Figure 1. Example of ev
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Table 3. Summary statistics of the
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Table 5. Utilities for subject 1 Li
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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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Page 466 and 467: Table 7. Ideal characteristics of m
Page 468 and 469: qualitative analysis of fifteen hou
Page 470 and 471: section. In Section 3, we will disc
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Page 474 and 475: of Am. Acad. of Bus., Cambridge. 4(
Page 476 and 477: directors and propose the board ind
Page 478 and 479: composition is the outcome of a neg
Page 480 and 481: Table 1. Descriptive statistics. Ti
Page 482 and 483: Table 3. The determinants of board
Page 484 and 485: Booth JR, Cornett M, Tehranian H (2
Page 486 and 487: provides a wider response and swift
Page 488 and 489: Correlation “Customary Approach
Page 490 and 491: Table 2. Correlation matrix of EAC
Page 492 and 493: Table 9. Intra-EAC imports as share
Page 494 and 495: Martin JC (1999). The European Mone
Page 496 and 497: participate in the highest degree o
Page 498 and 499: innovation. A secondary innovation
Page 500 and 501: Figure 2. The switching ecology of
Page 502 and 503: Table 1. Revenue growth rate and CA
Page 504 and 505: African Journal of Business Managem
Page 506 and 507: variables (Beattie and Jones, 1999a
Page 508 and 509: Table 3. Explanations of dependent
Page 510 and 511: Courtis JK (1997). Corporate annual
Page 512 and 513: treated in the literature, its rela
Page 516 and 517: as an important factor in the manag
Page 520 and 521: satisfaction may also reduce the ov
Page 522 and 523: Table 1. Customer expectations on s
Page 524 and 525: Table 2. Contd. Machirori and Fatok
Page 526 and 527: and travelling may lead to satisfac
Page 528 and 529: and professionally developmental pr
Page 530 and 531: Table 1. Organizational elements mo
Page 532 and 533: Table 2. Studying the demographical
Page 534 and 535: education might involve plenty of c
Page 538 and 539: (Deng et al., 2010). To date, there
Page 540 and 541: Table 2. Results of hierarchical re
Page 542 and 543: WOM. The comparison can be seen in
Page 544 and 545: UPCOMING CONFERENCES International
Page 546: African Journal of Business Managem
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