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Examining Benchmarking Applications in the government and public sector organization:

Examining Benchmarking Applications in the government and public sector organization: An empirical study in Egypt and proposed model. Prof. Dr. Tarek Taha Ahmed Dean of Faculty of Business Administration, Professor of Business Administration Pharos University at Alexandria, Egypt

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Examining Benchmarking Applications in the government and public sector organization:

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  1. Examining Benchmarking Applications in the government and public sector organization: An empirical study in Egypt and proposed model Prof. Dr. TarekTaha Ahmed Dean of Faculty of Business Administration, Professor of Business Administration Pharos University at Alexandria, Egypt Website: www.pua.edu.eg, e-mail: dr.tarek.ahmed@pua.edu.eg Prof. Dr. Tarek Taha

  2. Research Outlines • Research Problem and Objectives • Literature review • Model Development and Research Hypotheses • Research Methodology • Data analysis and model testing • Conclusion and managerial Implications • Limitations and Further research Prof. Dr. Tarek Taha

  3. Research Problem and Objectives Despite the growing body of literature dealing with benchmarking, previous research has focused on western countries regarding private corporations rather than upon public organizations operating in the developing countries such as Egypt. Moreover, contrast to the manufacturing sector, service industry, particularly governmental services, has been long criticized for a rather limited use of benchmarking. In addition, the in-depth interviews of our preliminary study, show that benchmarking concepts are still likely unclear. Consequently the effective implementation processes of such benchmarking remain doubtful. Thus, the research carried out by this study attempted to achieve the following objectives: (a)provide a better understanding about benchmarking applications in the local context(b)determine the construct factors influencing the managerial intention of Egyptian government public organizations to apply benchmarking, (c) develop a mathematical model that can quantitatively predict the probability of applying this methodology (d) offer hypotheses that can be used to guide research on related areas, (e) provide findings that further support, confirm or contradict previous studies regarding other industries or countries. The basic assumption is that organizations could not effectively improve their performance unless they understand what level of gap exists between current performance and best practices. And the use of any specific application is determined by intention to use it. Prof. Dr. Tarek Taha

  4. Literature review Literature and past researches were reviewed and integrated sequentially, including a wide range of recently published works, in order to develop more effectively the study’s hypotheses and the research model. Based on literature review and to meet the study purposes we defined benchmarking as a continuous improvement process comparing organization’s practices against the best in the industry (business leaders) which help to take action to improve performance. Also, the current paper used the term public organizations to refer to all organizations that provide the basic services or goods consumed by the public (such as electricity, natural gas, water, Telephone services) and are either not, or cannot be, provided by the private sector (see Farneti and Guthrie, 2009) Model Development and Research Hypotheses The proposed model in the following figure contains 12structural paths. The paths from P1 to P7 represent the hypothesized relationships between the driving factors and the application of benchmarking. The paths from P9 to P12 reflect the precondition determinants of implementing such benchmarking effectively. The remaining path P8refers to the degree of continuity of applying benchmarking for improving performance in the Egyptian government institutions. Prof. Dr. Tarek Taha

  5. Yapp: Benchmarking Application Precondition Factors (to implement benchmarking effectively) Driving Forces (to apply Benchmarking) P1 (+) P Yeff: Effective implementation P2 (+) P9 (+) O T P3 (+) C P10 (+) E P4 (+) Z P8 P5 (+) S P11 (+) A Where: Where: P6 (+) M Yapp= Benchmarking Application P= Presence of quality program O= Openness toward changes C= Client complains Z= Client Orientation S= Cost pressures M= Competitive Pressures B= Budget constraint Yeff= Effective implementation T=Top management support E= Employee participation A= Awareness about benchmarking D=Availability of comparative data P7(-) P1 2(+) B D Accordingly, the following multiple regression equations (EQ1 and EQ2) can be used: EG1 : Y app = a+bP P + bO O + bC C + bZ Z + bS S + bM M -bB B +e EG2 Yeff= a+bT T + bE E + bA A + bD D + e Prof. Dr. Tarek Taha

  6. Research Methodology The research process involved the following stages: Preliminary qualitative study: A series of in-depth interviews were carried out with some key practitioners. The issues arising from this stage, combined with the literature findings, were used as a basis for the next quantitative study. Quantitative study: The quantitative stage in the form of questionnaires followed sequentially . All elements that make up the study population have been investigated. The reliability of all instruments used in the study was assessed by Cronbach alpha reliability coefficient. The coefficients ranged from 0.77 to 0.90, which exhibited an acceptable level of reliability. Data analysis and model testing The data were processed using statistical software packages (SPSS). Multiple regression analysis(Total Model) was conducted and the associated statistical inference tests with regression techniques were performed for testing the overall regression equations (F test) as well as specific partial regression coefficients (t test on b). The analysis was repeated using stepwise multiple regression analysis (using the forward inclusion approach) to select a small subset of predictor variables that explained the highest amount of variation in the criterion variable. The total correlation matrix of the research model was reviewed in-depth. No significant multicollinearity was detected. The results of testing each of the three hypotheses are given below. Prof. Dr. Tarek Taha

  7. The results of testing hypotheses H1 and H2: • Hypotheses H1 and H2 were accepted based on the data analysis.There was a strong, highly significant association between benchmarking application and the driving factors (Multiple R= 0.87194288 and F= 20.388919247). These factors explain the major proportion (76.02%) of the variability observed in this application among public organizations in Egypt (R2= 0.76028438). Thus, the explanatory power of the research model considered highly satisfactory (Adjusted R2= 0.72299528). However, the results. The predictive equation (EG3) can be estimated as below to evaluate the impact of each factor on the criterion variable (Yapp): • EG3: Yapp = 0.08 +0.35 P + 0.17 O + 0.19 C + 0.08 Z + 0.23 S + 0.44 M – 0.11 B • The multiple regression analyses were repeated again using the stepwise regression approach by forward inclusion to assess the relative importance of predictor variables mentioned earlier and. Only the four predictor factors (P, C, M and O) succeeded in entering into the model equation and explained 71.6 percent of the total variation in criterion variable Y (R2 =0. 716). P alone explained 58 percent of such total variation (R2 for step 1= 0.580). The high significant F- test ratio (F=30.183) of the stepwise model indicates that the results of the research model could hardly have occurred by chance. A new predictive equation (EG4) can now be estimated, as below: • EG4: Yapp = 0.40 +0.43 P + 0.19 C + 0.38 M + 0.27 O Prof. Dr. Tarek Taha

  8. The results of testing hypothesis H3: The results in the following table do not support the acceptance of hypothesis H3(X~ = 1.566037, S~= 0.106089, and Skewness = 0.941928).Despite all Egyptian public organizations reported that they implement benchmarking (all of them are bench-markers), the findings show that they are most likely practice benchmarking rarely to improve their performance (60.38%), while the remaining percent either irregularly (22.64%), or continuously (16.98%). The values of the spider diagram strong tend toward right side, reflecting the low rate of benchmarking practices among Egyptian public organizations. Prof. Dr. Tarek Taha

  9. The results of testing hypothesis H4: • Finally, hypothesis H4 was accepted based on the multiple regression analysis.The result reveals that effective implementation of benchmarking (Yeff) has significant relationship with the four precondition factors (T, E, A and D), included in the research model, (Multiple R= 0.852072008and F= 31.7998896738). The coefficient of multiple determinations (R2)of the model is 0.726026707, which indicates that 72.60% of the variation in effectiveness was explained by these factors. It is possible to assess the impact of each factor on the criterion variable (Yeff), using the predictive equation (EG5): • Yeff= 1.25 +0.97 T + 0.05 E +0.14 A + 0.07 D Conclusion and managerial Implications The growing importance of applying benchmarking in government and public-sector organizations has been highlighted throughout this study, after reviewing up-to-date relevant literature and examining many previous works. This study presents an empirical assessment of the factors affecting applying benchmarking and the precondition factor for effective implementation process. Given the dearth of works dealing with this area of study, the results of the present paper might be seen as useful potential theoreticalcontributions to the specialized literature concerning this issue. Our research attempted to integrate and encompass the most frequently cited factors in the literature, and applied them in the local context in order to best examine the phenomenon under investigation. Thus, the proposed model contained variables that have not been tested simultaneously in previous works. Prof. Dr. Tarek Taha

  10. Similarly, some practical managerial implications can be drawn from the results for practitioners such as organization managers. They can gain a better understanding of whether their current practices can be improved. In other words, government and public-sector organizations can use the results of this study to evaluate the efforts needed to enhance their applications. Also, they can benefit most from this study regarding the reasons why they show very low rate of applying benchmarking. Conclusion and managerial Implications(Continued) Limitations and future research The current research has some limitations. The study was conducted in Egypt and therefore the findings may be specific to the culture in this developing country. Also, it should be noted that the research scope was limited to the government and public services industry. Finally, since the study is cross-sectional in design, future research could undertake a more in-depth longitudinal study. However, the majority of the proposal relationships were validated, and significant, the level of R2 obtained shows that there are other variables that may influence our finding. Consequently, it is necessary to develop more complex models which may introduce alternative variables. Thank you for your attention Prof. Dr. Tarek Taha

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