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\title{Information System Development and Use Practices in Khyber Pakhtoon Khwa (K.P.K) Pakistan (An Empirical Study of the Demographics Impacts)}
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             \author[1]{Dr. Ghulam Muhammad  Kundi}

             \author[2]{Dr. Ghulam Muhammad  Kundi}

             \author[3]{Dr. Ghulam Muhammad  Kundi}

             \affil[1]{  Gomal University Dera Ismail Khan, K.P.K, Pakistan.}

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\date{\small \em Received: 10 December 2011 Accepted: 4 January 2012 Published: 15 January 2012}

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\begin{abstract}
        


There is no doubt in the reality that Information Technology (IT) is revolutionizing organizations on unprecedented proportions thereby stimulating others to adopt it but despite this fact research indicates that a large number of information system development projects are failing to achieve their objectives in toto. Thus, there are partial and total failure stories of IT projects. Furthermore, information system (IS) failures are common to all types of organizations: public, private or small, medium and large irrespective of operating in a developed or developing country.The research on IS failure frequently cites non-technical issues as the most decisive factors in the success or failure of any IT project. That is, IT can do miracles but all this requires 'adequate management of the 'demographics of an IT project.' Non-technical critical success and failure factors are catching wider attention during the last decades among the IS research community.One can understand that technology can be imported but not the demographic of the organization thus, nontechnical issues are 'local in nature, structure and intensity,' which definitely need local studies of ISD and use practices so as to dig-out 'customized ISD and use process. This research is an effort in the same line of thinking.

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\keywords{information technology (IT), information system (IS), information system development (ISD), perception about IT, , proje}

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\let\tabcellsep& 	 	 		 
\section[{Introduction}]{Introduction}\par
eveloping a computer-based information system (CBIS) is not simply the purchase and installation of hardware and software  {\ref (Rockart, et al., 1996;} {\ref Smith, 1998;} {\ref Walsham, 1993} {\ref Walsham, , 2000;;} {\ref Turban et al., 2004)}. It rather goes beyond it to the problems of people, organization and the context \hyperref[b1]{(Avgerou and Cornford, 1998)}; Segars and Grover, 1996); \hyperref[b13]{Dann et al., 1998)}. Research findings assert that an IS development (ISD) is a 'social process'  {\ref (Lyytinen, 1987;} {\ref Checkland, 1991;} {\ref Walsham, 1993)} thereby considering all the human, organizational, contextual and technological issues as in case of any organizational project.\par
Human challenges include difference of perceptions about IT among the developers and users due to several gaps of education, communication, culture, motivation and satisfaction (see for example, \hyperref[b0]{Argyris, 1971;}\hyperref[b33]{Kaasboll, 1997;}\hyperref[b13]{Dann et al., 1998;}\hyperref[b31]{Glass, 1998)}. The Nature (public or private), policies and procedures, the IT maturity, power structures etc., make up some of the issues emanating from the organization itself (see for example, \hyperref[b35]{Land et al., 1992;} {\ref Segars and Grover, 1996)}. Environment or context is significant since its change altogether changes requirements for the success/failure of an IT project \hyperref[b29]{(Flowers, 1997}). Herzberg's two factors theory suggests that job-satisfiers relate to the job-contents while jobdissatisfiers emerge from the job-context (Luthans, 1995:149). Technology is not widely quoted as big deal but IT professionals are frequently cited as the toughest challenge in an IT project due To their intellectual distance from the nature and requirements of an organization \hyperref[b0]{(Argyris, 1971;} {\ref Segars and Grover, 1996)}.\par
All of these challenges crop-up during different stages of an ISD life cycle (ISDLC). A global format for this cycle is: IS planning, requirements capture and analysis, design, implementation, use and maintenance and up-gradation \hyperref[b2]{(Avison and Wood-Harper, 1990}). The intensity of issues vary from one stage to another for example, communication gap between developers and users at planning level is minor issue as compared to the same at requirements capture, training and use levels \hyperref[b33]{(Kaasboll, 1997)}. Likewise, organizational factors are less threatening during the initial phases of ISDLC but once new system is in action 'IT-business-alignment' \hyperref[b10]{(Burn, 1996}; Poulymenko and Holemes, 1997) emerges as a big issue, which is widely reported as the major cause of many IS failure (ISF) cases around the world (see for example, Ewusi-Mensah and \hyperref[b31]{Glass, 1998)}.\par
In nutshell, IS community is unanimous on admitting that it is not technology-related issues rather human, organizational and contextual variables which make or break the future of an IT project (see for example,  {\ref Avison and r-Harper, 1990;} {\ref Poulymenakou and Holmes, 1996)}. Furthermore, all of these factors are purely local in nature requiring customized-research projects to unearth indigenous footage of the impacts from these variables on the development trajectory of an IT projects.\par
The objectives of this study were to o unearth the ISD and use practices in KPK, Pakistan and local versions of challenges to the ISDLC from human, organizational, contextual and technology factors besides management concerns in the domestic ITprojects and to build-up a customized set of guidelines for handling an IT-project's development-trajectory successfully in education and health sectors of the economy. This is the first project of its kind in KPK, Pakistan that unearthed purely 'localized and customized' problems and solution models for ITprojects. Likewise, the study will be contributive both in improving ISD and use practices as well as help in minimizing the chances of IS failure.\par
Since IT is indispensable to organizations but research warns that inadequate management of ITprojects result either into partial failure or total termination of the efforts. The question of this research therefore, was 'How far local management is succeeding in identifying and handling challenges to the ISD and use process in the indigenous context of KPK Pakistan? II. 
\section[{Review of the relevant literature}]{Review of the relevant literature}\par
The literature on IS development and use process is scattered across the organization, management, information-systems and computer studies. Researchers have identified critical success and failure factors (variables) about different aspects and stages in IT projects (see for example, Ennals, 1995; Beynon-Davies, 1995; Beynon-Davies and Lloyd-Williams, 1999). There is substantial evidence on the role of organizational, human and contextual factors in the whole process of infusing IT into organizational structure and culture  {\ref (Walsham, 1993:25)}. a) Demographics of ISD process ISD is a social process therefore, it is certainty affected by all the surrounding factors. Organizational size and structure, policies, management style, methods and procedures, rules and regulations have to be taken into account at every step in the ISD and use process  {\ref (Segars and Grover, 1996;} {\ref Smith, 1998)}. Likewise, a fear-based organizational culture (Poulymenakou and Holmes, 1996) hinders a transparent IT project since people hesitate to admit mistakes and failures (Beynon-Davies, 1995; Warne, 1997; Beynon-Davies and Lloyd-Williams, 1999). An information system is designed, created, operated and used by humans thus, humans reflect in every move and dimension of the ISD and use trajectory  {\ref (Sauer, 1993)}. Although technology (hardware, software and professionals) is neither an end nor all in the story of computerizing an organization, however, their availability and usability may trigger many questions. It is however, widely documented that IS developers (professionals) can create problems if developer-user gaps are not addressed early \hyperref[b33]{(Kaasboll, 1997)}. 
\section[{b) Perceptions about IT}]{b) Perceptions about IT}\par
Life is what one believes in so perceptions of technology have bearing upon how they are used (see for example, \hyperref[b9]{Brooke, 1995;}\hyperref[b12]{Collins and Bicknell, 1997)}. The perceptions of rich and poor nations have shifted away from economic milestones to knowledge yardsticks. Now information-rich and information-poor are the criteria to determine power of the nations. So where does a nation perceives itself on the continuum of digital-divide, reflects the use-level of IT in that country. In the organizational context, there are some kinds of 'silver-bullet' and 'leading-edge' syndromes \hyperref[b31]{Glass, 1998)}' about IT expressing the belief that IT is a panacea for all management ills, while others disbelieve in any miraculous contributions of this technology \hyperref[b6]{(Baskerville and Smithson, 1995)}. Technocrats like accountants, engineers and scientists view IT as a commodity but mangers vision it, as a differentiator for the business. 
\section[{c) Approaches and Methodologies}]{c) Approaches and Methodologies}\par
Several approaches have been theorized, exercised and reduced into black-n-white for computerization efforts \hyperref[b32]{(Hirschheim and Klein, 1989}; Wynekoop and Russo 1995; \hyperref[b3]{Avison and Fitzgerald, 1995;}\hyperref[b4]{Avison and Shah, 1997)}. They are grossly categorized into hard and soft approaches. Some researchers, particularly those hailing from computer science, suggest highly structured and scientifically managed approaches assuming that an IT project is a technical venture . Business managers however, perceive it as a business-project therefore prefer soft approaches so that the social nature of the development trajectory could be entertained  {\ref (Walsham, 2000)}. These extremes have been compromised by the advocates of 'socio-technical' approaches, which assert that both technical and social management skills are required to handle IT-related efforts successfully.\par
Under hard and soft approaches, structured and unstructured ISD methodologies have been developed respectively. SSADM and STRAIDS  {\ref (Weaver, 1993;}\hyperref[b14]{DeMarco, 1979;}  Several models are given in the literature to postulate a standard set of stages for an IT project. There are linear, waterfall and spiral models of an ISDLC. Userparticipation have widely been researched and identified as the critical factor to IT-project development and ultimately system's use (see for example, Mumford, and  {\ref Henshall, 1979;} {\ref Mumford, 1997)}. New CBIS changes the power structures therefore; losers and winners are created where losers naturally resist changing (see for example, \hyperref[b2]{Avison and Wood-Harper, 1990}). An ISD has to be protected from the 'political maneuvering' or power struggle during the whole cycle of ISD otherwise, there is ample evidence on many IS failures, which were politically devastated (see for example, \hyperref[b37]{Markus, 1981}\hyperref[b39]{Markus, , 1983;;} {\ref Drummond, 1995;}\hyperref[b40]{McGrath, 1997)}. f) Success or Failure (Good and Bad Experiences) Literature is filled with stories of IT projects but unfortunately most episodes are about the failure because successes have little for research therefore reported occasionally \hyperref[b31]{(Glass, 1998)}. Failures are the repositories of the research questions for problemsolutions and improvement (Ewusi-Mensah and  {\ref Przasnyski, , 1992}\hyperref[b40]{McGrath, 1997)}. It has been found that the risk of IS failure is equal to all the small, medium and large enterprises in the developed and developing worlds and operating either in public or private sectors. IS failure have been extensively researched with the findings that there can be correspondence, process, system and expectation failures or project abandonment and terminations (Nawaz et al, 2007; Lyytinen and  {\ref Hirschheim, 1987;} {\ref Sauer, 1993;}. Whatever the name and nature of failure, there is broader agreement on two things: a. the same mistakes are committed in every IS failure case \hyperref[b12]{(Collins and Bicknell, 1997;}\hyperref[b31]{Glass, 1998;} {\ref Sauer, 1999)}   N = 4372 n = 277 Formula n a = [(nN a ? a )/((N a ? a )+(N b ? b )+(N c ? c ))] 
\section[{c) Data Collection and Analysis i. Data Collection Methods}]{c) Data Collection and Analysis i. Data Collection Methods}\par
Given the social-cum technical and global-cumlocal nature of the topic, data was collected from all the possible sources to squarely cover all the related dimensions so that a comprehensive view of both the problem and solution could be envisaged. Self-administered Questionnaire: It was the main inflow of primary data through a sophisticated and standardized set of questions arranged in a wellstructured format. The instrument was successfully used in the pilot study. The same was applied in the main study.\par
3. Follow-up Interviews: Questionnaire covered the main variables; however, follow-up interviews were conducted for: a. collecting data that was missing in the questionnaire and b. gather data, which could not be captured through the questionnaire.\par
ii. Data Analysis Tools Specific data analysis tools were used to carveout meaning from the collected data. Tabulation was the top tool for 'data-reduction' as well as presentation of the findings. The tools used for analysis of the data in the study are given below:\par
1. Descriptive Tools: Besides textual analysis of secondary data, statistical descriptive-tools were used to explore and present: a. Respondents' profile (demographies) and b. Description of all the research-variables.  e) Theoretical Framework A set of hypothesis was developed on the basis of relationships postulated in the theoretical framework. Table \hyperref[tab_1]{3}.5 provides the detail.  
\section[{Multiple Regression g) Pilot Study}]{Multiple Regression g) Pilot Study}\par
All the above constructs and methods were used in the pilot study with the objectives of:\par
? Testing the research tools (particularly constructs).\par
As a consequence several attributes were pinpointed by the respondents, which have been included in the questionnaire.\par
? Computing statistics to calculate 'sample-size' for the main study. 
\section[{h) Reliability of Instrument}]{h) Reliability of Instrument}\par
The overall reliability of Cronbach's alpha was estimated at 0.9288, with 277 cases and 42 survey items. This value obviously exceeds the required minimum threshold for the overall Reliability-test, i.e. 0.7 \hyperref[b34]{(Koo, 2008)}.  The results of the 5 th hypothesis are given in the below table. Since there are more than two groups and IT is measured on an interval scale, ANOVA is appropriate to test this hypothesis. If we look into the table, we find df in the 3 rd column refers to the degrees of freedom, and each source of variation has associated degrees of freedom. For the between-groups variance, df = (K-1), where K is the total number of groups or levels. Because there were three groups, we have (3-1) = 2 df. The df for the within groups sum of squares equals (N-K), where N is the total number of respondents and K is the total number of groups. As there were no missing responses, the associated df is (277-3) = 276. 
\section[{MS explained MS residual}]{MS explained MS residual}\par
The mean square for each of variation (column 5 of the results) is derived by dividing the sum of squares by its associated df. Finally, the F value itself equals the explained mean square divided by the residual mean square. In this case, F = .240 (.014/.053). The F value is significant at the .676. As calculated F value .240 in table No. 4.14 is less than the tabulated F value 3.00, so H 0 hypothesis of this study is not substantiated. That is, there is no significant difference in the means implies that professors and doctors view IT differently from that of IT consultants.   \hyperref[tab_5]{4}.15 points correlations between the research variables, average correlations can be seen from last column. In the order of magnitude, the biggest weight of correlation is between the 'Satisfaction' and rest of the variables (r=0.7) and smallest correlationscore on Problems (r=0.512) and Development (r=0.535) with all the variables. However, 8 out of 10 variables are significantly correlated with r from 0.5, to 0.7. 
\section[{ANOVA}]{ANOVA}\par
Hypothesis No.7: Higher the perceptions about IT, greater are the chances/perceptions of success in IT projects.\par
On 5 point scale the relationship between higher perceptions about IT for greater chances/perception of success in IT projects was significant as tested by simple regression analysis. The first table lists the independent variable which is centered into the regression model and R (.104a) is the correlation of the independent variable with the dependent variable.\par
In the Model Summery table, The R Square (.011), which is the explained variance, is actually the square of the multiple R (.104a) 2 . The ANOVA table shows that the F value of 4.217 is significant at the .038a. In the df (degree of freedom) in the same table, the first number represents the independent variable (1); the second number (277) is the total number of complete responses for all the variables in the equation (N), minus the number of independent variables (K) minus 1. (N-K-1) [(277-1-1) = 275]. The F statistic produced (F = 4.217) is significant at the .038a level.\par
To be statistically significant calculated correlation must be at least .304 on 5 point scale, it is inferred that the influence of perception about IT is significant as beta score is .513, thus H 0 hypothesis is not substantiated.\par
The next table titled Coefficients helps us to see that the independent variable influences most the variance in success of IT projects (i.e., is the most important). If we look at the column Beta under Standardized Coefficients, we see that the highest number in the beta for perception about IT .511 is significant at the .038a level. The results illustrate that the independent variable is significant.\par
This implies that perception about IT significantly influence the chances/perceptions of success in IT projects, thus the H 0 hypothesis is rejected. The multiple regressions analysis was applied according to standardized coefficient on 5 point scale for the dependence of success/failure of an IT-project on organizational, human, contextual and technology. The first table lists the four independent variables that are centered into the regression model and R (.561a) is the correlation of the four independent variables with the dependent variable, after all the intercorrelations among the four independent variables are taken into account. 
\section[{Summary of Model}]{Summary of Model}\par
In the Model Summery table, The R Square (.315), which is the explained variance, is actually the square of the multiple R (.561a) 2 . The ANOVA table shows that the F value of 61.553 is significant at the .000a. In the df (degree of freedom) in the same table, the first number represents the number of independent variables (4); the second number (277) is the total number of complete responses for all the variables in the equation (N), minus the number of independent variables (K) minus 1. (N-K-1) [(277-4-1) = 272]. The F statistic produced (F = 61.553) is significant at the .000a level.\par
To be statistically significant calculated correlation must be at least 0.304 on 5 point scale, it is inferred that the influence of organization, human, context and technology on success of IT projects was found highly significant thus, the H 0 hypothesis is not substantiated.  
\section[{Major findings and discussion}]{Major findings and discussion}\par
Several studies have focused on the human challenges i.e. difference of perceptions about IT among the developers and users due to several gaps of education, communication, culture, motivation and satisfaction \hyperref[b0]{(Argyris, 1971;}\hyperref[b33]{Kaasboll, 1997;}\hyperref[b13]{Dann et al., 1998;}\hyperref[b31]{Glass, 1998)} while, \hyperref[b35]{Land et al., 1992;} {\ref Segars and Grover, 1996)} studied the issues emanating from the organization and technology i.e. the nature, policies and procedures, the IT maturity, power structures etc. Likewise environment or context is significant because it influence and change altogether requirements for the success/failure of an IT project \hyperref[b29]{(Flowers, 1997)}. Similarly, Herzberg's two factors theory suggests that job-satisfiers relate to the job-contents while job-dissatisfiers emerge from the job-context  {\ref (Luthans, 1995:149)}.\par
With this context, theoretical framework developed after literature review was used to get readings from the real-world situation (ISD and Use practices in KPK Pakistan). Primary data collected through questionnaire provided sufficient material about the problem-situation in the background of ideal theoretical framework extracted from the documented knowledge. The analysis and logical reasoning of the primary and secondary data provides good base for findings, following are the major findings along with discussion of this study:\par
The empirical results of this study points that public sector organizations in KPK Pakistan are less optimistic about the role of IT than private sector as indicated by the t value 15.097, which means that in KPK Pakistan, private sector is more optimistic about the role of IT in organizations for maximum efficiency and effective utilization of both the human and material resources of the organization that is why they are heavily investing in computerization of their organizational operations. This study further finds that public sector organizations are under-using IT potentials in comparison to private sector; the results of t statistics 14.234 support the literature. As for as Escalation in IT projects is concerned which are widely studied by researchers like  {\ref Drummond (1994}\hyperref[b15]{Drummond ( , 1996))}, again results of the study identified that escalation is severe issue of the public sector organizations than in private enterprises of KPK Pakistan according to t statistics 16.573. This implies that the ratio of time-delays, costoverruns, compromise on lesser objectives is very high in public sector IT projects of KPK, which may leads to failure or total termination of projects, eating budget and resources of the organizations. Experts believe in application of soft methodologies and user participation in ISD (giving parallel importance to socio-technical factors) along with effective training and education of all the stakeholders involved also documented by Walsham (2000) \hyperref[b32]{Hirschheim and Klein (1989)} Wynekoop and Russo (1995) Mumford and Weir (1979), however, this study have points that in comparison to private sector, public sector is ignoring these international signals and play down the human, social and psychological aspect in ISD, use and maintenance. The application of hard and fast rules with bureaucratic mind set (cumbersome procedures from project proposal to development, implementation and use are very common in public sector organizations. This may also result into miscommunication between the developer and user; make management of resistance to change more difficult.\par
The calculated F value .240 of this study explains the differences among professors and doctors and IT consultants who view ISD differently due their background diversities. Moreover the experience of non-IT workforce is negatively correlated with perceptions about IT that significantly affect the ISD and use process. Perceived ease of use, usefulness and experience with IT also play pivotal role in perception of users about IT projects. This study has found that ITpeople overestimate while non-IT workers underestimate the role of IT in the organizations. This is verified by the t value .891 which pin point that there are gaps between IT people and Non IT workers with reference to role of IT in an organization which necessitates the education, close and intimate relations, corporation and coordination among these two groups to development more understanding of the organization and management, technical competency and skills in their respective fields and to effectively use IT as competitive weapon for the accomplishment of organizational goals and objectives through innovation, growth, cost effectiveness, alliance and mergers as higher the perceptions about IT, greater will be the chances/perceptions of success in IT projects. This is further supported by the Beta .511, which verified the arguments of Elton and Justin (1998) that higher perception about IT leads to greater success of IT projects development, use and implementation.\par
The nature (public/private), size, structure, objectives, and culture of the organization determine the organizational IT maturity i.e. the experience with ISD and use. The mechanism for developer-user interaction political/power struggles may help decrease the control the political maneuvering and powers struggle in IT projects development which according Sauer  {\ref (1993,} {\ref 1999)}  C list for the policy makers to devise strategies and policy when they are deciding about the IT projects development and use process. The beta .704 further highlight the value of that human element which play more important role than other factors i.e. organization, context and technology however, technology effects are greater than organizational and contextual factors. The common misperceptions about IT and perceptual gaps between developers and users as researcher's postulates with reference to ISD and use could be minimized through organizational motivation techniques for IT. 
\section[{VI.}]{VI.} 
\section[{Conclusions}]{Conclusions}\par
The national IT policy is a very important document that set guidelines for the computerization in any country; Pakistan introduced its 1 st IT policy in 1990 while Electronic Transaction Ordinance and Electronic Crimes Act were promulgated in 2002 and 2003 respectively, however according to Kundi (2009) there are several deficiencies and it is not comprehensive. Following are some suggestion for policy makers in the background of ISD and use practices in KPK Pakistan:\par
Promotion of IT-culture in all corners of the country among all segments of the society besides ITeducation may be made compatible to the market needs, this demands revision of the old curricula and project management and evaluation techniques in IT education.\par
The feudal mind set of administrative machinery is also is the cause of failure of ISD and Use in KPK, so change in mind set of the administrative machinery and decision makers and effective training along with continuous updating of the information systems (eGovernment in particular) is required for effective ISD and use in KPK Pakistan. Moreover, human element play key role in success or failure of IT projects in comparison to technical factors, so developers are required not to ignore the human element rather give equal importance to socio-technical factors. Last but not the least is that administrative, socio-technical, political and cultural support is the backbone for successful development and implementation of IT project which must be ensured.\par
During the study it was observed that most of the IT projects were not completed within stipulated times which overburden the finances, inorder to remain economical and effective the project must completed within time and budget. The main reason of timely non completion is the political maneuvering and kickback involved in the projects besides imposing attitude and IT-organizational maturity which widens the gap between developers and users. In this connection Orgware, people-ware, hardware and software training may be continuously provided to both developers and users, so that the common misperceptions about IT and perceptual gaps between developers and users may be minimized/ or bridged during the ISD and use for successful development and implementation.\par
Succinctly, one can understand that technology can be imported but not the demographic of the organization thus, non-technical issues are 'local in nature, structure and intensity,' which definitely need local studies of ISD and use practices so as to dig-out 'customized ISD and use process. \begin{figure}[htbp]
\noindent\textbf{1}\includegraphics[]{image-2.png}
\caption{\label{fig_0}1 .}\end{figure}
    \begin{figure}[htbp]
\noindent\textbf{} \par 
\begin{longtable}{P{0.85\textwidth}}
demographies like organization, humans and context.\\
For example, ETHICS stands for effective technical and\\
human implementation of computer systems. MultiView\\
demands multi-view perception and treatment of\\
computerization projects.\\
d) Project Management\\
An ISD and use process needs to be managed\\
adequately otherwise leading-edge technology and\\
huge budgets may gather dust. It is said that this\\
adequacy is possible if it is recognized that "project is\\
less a matter of understanding constraints and more a\\
function of personal skills (Elton and Justin, 1998).\\
Researchers have unearthed several IT-project\\
management strategies. It is now squarely admitted that\\
an IT project is like any other business project (Smith,\\
1998) therefore, all technical, organizational, human and\\
contextual dimensions have to be brought on the table\\
for visualizing a holistic view of the project.\\
e) ISD Life Cycle\\
An ISD process never ends since it demands\\
constant upgrading thus, a cycle continues forever in\\
the form of recursive stages (Avison and Fitzgerald,\\
1995; Avison and Shah, 1997; Turban et al, 2004:235).\end{longtable} \par
 
\caption{\label{tab_0}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{3} \par 
\begin{longtable}{P{0.85\textwidth}}
and b. the\end{longtable} \par
 
\caption{\label{tab_1}Table 3 .}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{3} \par 
\begin{longtable}{P{0.11612021857923498\textwidth}P{0.2895264116575592\textwidth}P{0.06502732240437159\textwidth}P{0.19353369763205827\textwidth}P{0.05418943533697632\textwidth}P{0.04180327868852459\textwidth}P{0.05496357012750455\textwidth}P{0.03406193078324225\textwidth}P{0.0007741347905282332\textwidth}}
\tabcellsep \tabcellsep \multicolumn{4}{l}{2 : Stratified Samples (Area-by-Sector Samples)}\\
\tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{Population}\tabcellsep Standard\tabcellsep Sample\\
\tabcellsep \multicolumn{2}{l}{Area-Wise Sectors}\tabcellsep \multicolumn{2}{l}{(Strata)}\tabcellsep Deviations\tabcellsep Sizes\\
\tabcellsep \multicolumn{2}{l}{Public Sector Health DIK}\tabcellsep \tabcellsep 360\tabcellsep 0.8\tabcellsep 25\\
\tabcellsep \multicolumn{2}{l}{Public Sector Health Peshawar}\tabcellsep \tabcellsep 617\tabcellsep 0.7\tabcellsep 37\\
\tabcellsep \multicolumn{2}{l}{Private Sector Health DIK}\tabcellsep \tabcellsep 210\tabcellsep 0.89\tabcellsep 16\\
\tabcellsep \multicolumn{2}{l}{Private Sector Health Peshawar}\tabcellsep \tabcellsep 458\tabcellsep 0.66\tabcellsep 26\\
\tabcellsep \multicolumn{2}{l}{Public Sector Education DIK}\tabcellsep \tabcellsep 625\tabcellsep 0.66\tabcellsep 35\\
\tabcellsep \multicolumn{3}{l}{Public Sector Education Peshawar}\tabcellsep 720\tabcellsep 0.87\tabcellsep 52\\
\tabcellsep \multicolumn{2}{l}{Private Sector Education DIK}\tabcellsep \tabcellsep 275\tabcellsep 0.69\tabcellsep 16\\
\tabcellsep \multicolumn{3}{l}{Private Sector Education Peshawar}\tabcellsep 480\tabcellsep 0.8\tabcellsep 33\\
\tabcellsep Consultants DIK\tabcellsep \tabcellsep \tabcellsep 247\tabcellsep 0.6\tabcellsep 13\\
\tabcellsep \multicolumn{2}{l}{Consultants Peshawar}\tabcellsep \tabcellsep 380\tabcellsep 0.78\tabcellsep 24\\
\tabcellsep \tabcellsep TOTAL\tabcellsep \multicolumn{2}{l}{4372}\tabcellsep \tabcellsep 277\\
\tabcellsep \multicolumn{5}{l}{Table 3.3 : Sample Selection Procedures}\\
\multicolumn{3}{l}{Sample (FINITE population)}\tabcellsep \tabcellsep \multicolumn{3}{l}{Stratified Samples}\\
\tabcellsep Pilot Study Statistics\tabcellsep \tabcellsep \tabcellsep \multicolumn{3}{l}{Pilot Study Statistics}\\
\multicolumn{2}{l}{Standard Deviation (?) Standard Error (E) Z value at 95\% Confidence Sample Population N Target Population}\tabcellsep 0.72 0.082 1.96 4372 INFINITE\tabcellsep \multicolumn{2}{l}{Health (public) DIK Health (public) Peshawar Health (private) DIK Health (private) Peshawar Education (public) DIK}\tabcellsep \tabcellsep N 360 617 210 458 625\tabcellsep SD 0.8 0.7 0.89 0.66 0.66\tabcellsep N\\
\multicolumn{2}{l}{Sample Size}\tabcellsep 277\tabcellsep \multicolumn{3}{l}{Education (public) Peshawar}\tabcellsep 720\tabcellsep 0.87\\
Formula\tabcellsep n = [? 2 /((z 2 /E 2 )+(? 2 /N))]\tabcellsep \tabcellsep \multicolumn{3}{l}{Education (private) DIK Education (private) Peshawar}\tabcellsep 275 480\tabcellsep 0.69 0.8\\
\tabcellsep \tabcellsep \tabcellsep Consultants DIK\tabcellsep \tabcellsep \tabcellsep 247\tabcellsep 0.6\\
\tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{Consultants Peshawar}\tabcellsep \tabcellsep 380\tabcellsep 0.78\end{longtable} \par
 
\caption{\label{tab_2}Table 3 .}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{3} \par 
\begin{longtable}{P{0.06427469135802469\textwidth}P{0.11084104938271604\textwidth}P{0.6427469135802469\textwidth}P{0.01902006172839506\textwidth}P{0.013117283950617283\textwidth}}
\multicolumn{4}{l}{Information System Development and Use Practices in Khyber Pakhtoon Khwa (K.P.K) Pakistan}\\
\tabcellsep \tabcellsep (An Empirical Study of the Demographics Impacts)\tabcellsep \\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep 2012\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep Year\\
\tabcellsep \tabcellsep 4 : Operationalized Variables\tabcellsep \\
\tabcellsep Variables\tabcellsep Attributes\tabcellsep Code\\
\tabcellsep \tabcellsep \tabcellsep OF\\
\tabcellsep Technological\tabcellsep Hardware, Software and IT professionals. Availability, expenses, usability\tabcellsep TF\\
3\tabcellsep Factors\tabcellsep and possibility to upgrade the above items. Developers' organizational\tabcellsep \\
\tabcellsep \tabcellsep knowledge\tabcellsep \\
\tabcellsep ISD\tabcellsep Government and Institutional IT Policies; User Needs Analysis; User\tabcellsep ISD\tabcellsep D D D D ) C\\
\tabcellsep \tabcellsep Participation, Training; Implementation; Maintenance; and Evaluation in\tabcellsep \tabcellsep (\\
4\tabcellsep \tabcellsep ISD, ISD approaches, Methodologies, Project management, User\tabcellsep \\
\tabcellsep \tabcellsep participation, developer-user communication, user training, Management\tabcellsep \\
\tabcellsep \tabcellsep of the resistance to change.\tabcellsep \\
5\tabcellsep IS Use\tabcellsep Experience with IT; User-developer-communication Perceived Ease of Use (PEU); Perceived Usefulness (PU); Volume of Use;\tabcellsep USE\\
6\tabcellsep Perceptions\tabcellsep IT: the Problem-Solver; Digital Divide; and Socio-economic Impacts of IT.\tabcellsep PRC\\
7\tabcellsep Problems\tabcellsep Problems of IT Projects Development, Use and User-Satisfaction\tabcellsep PRB\\
8\tabcellsep Satisfaction\tabcellsep User-Satisfaction IT Projects Development and Use Practices.\tabcellsep STF\\
9\tabcellsep Opportunities\tabcellsep Opportunities for IT Project Success in K.P.K.\tabcellsep OPR\\
\tabcellsep \multicolumn{2}{l}{Success/ Failure Definition of success/failure, Degree of success and failure, Ratio of}\tabcellsep SFF\\
10\tabcellsep \tabcellsep success and failure, Critical success and failure factors, Escalation in IT\tabcellsep \\
\tabcellsep \tabcellsep projects.\tabcellsep \end{longtable} \par
  {\small\itshape [Note: 1 Human Factors Perceptions about digital divide, silver-bullet syndrome, usability, commodity vs. differentiator, leading-edge syndrome, Organizational motivation techniques for IT, Perceptual gaps between developers and users. HF 2 Organization Factors Nature (public/private), Size, Structure, Objectives, and culture of the organization. IT maturity (experience with ISD and use) The mechanism for developer-user interaction Political/power struggles.]} 
\caption{\label{tab_3}Table 3 .}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{3} \par 
\begin{longtable}{P{0.6794377067254685\textwidth}P{0.02342888643880926\textwidth}P{0.04966923925027563\textwidth}P{0.014057331863285557\textwidth}P{0.08340683572216097\textwidth}}
\tabcellsep \tabcellsep \multicolumn{3}{l}{5 : List of Working Hypothesis}\\
\tabcellsep \multicolumn{2}{l}{Hypothesis}\tabcellsep \tabcellsep Statistical Tools Applied\\
\multicolumn{4}{l}{1 The Public organizations are under-}\tabcellsep t-test\\
\multicolumn{4}{l}{using IT potentials in comparison to}\\
\multicolumn{2}{l}{private sector.}\tabcellsep \tabcellsep \\
\multicolumn{2}{l}{2 Escalation}\tabcellsep (time-delays,\tabcellsep cost-\tabcellsep t-test\\
\multicolumn{4}{l}{overruns, compromise on lesser}\\
\multicolumn{4}{l}{objectives) of IT projects is more}\\
\multicolumn{4}{l}{common in public organizations than}\\
\multicolumn{3}{l}{in private enterprises.}\tabcellsep \\
\multicolumn{4}{l}{3 IT-people overestimate while non-IT}\tabcellsep t-test\\
\multicolumn{4}{l}{workers underestimate the role of IT}\\
\multicolumn{3}{l}{in the organizations.}\tabcellsep \\
\multicolumn{4}{l}{4 Public sector is less optimistic about}\tabcellsep t-test\\
\multicolumn{4}{l}{the role of IT than private sector.}\\
\multicolumn{4}{l}{5 Professors, doctors and consultants}\tabcellsep ANOVA\\
\multicolumn{3}{l}{view IT differently.}\tabcellsep \\
\multicolumn{4}{l}{6 Experience of non-IT workforce is}\tabcellsep Correlation\\
\multicolumn{2}{l}{negatively}\tabcellsep correlated\tabcellsep with\tabcellsep analysis\\
\multicolumn{3}{l}{perceptions about IT.}\tabcellsep \\
\multicolumn{4}{l}{7 Higher the perceptions about IT,}\tabcellsep Simple\\
\multicolumn{4}{l}{greater are the chances/perceptions}\tabcellsep Regression\\
\multicolumn{3}{l}{of success in IT projects}\tabcellsep \\
8 The\tabcellsep \multicolumn{2}{l}{organizational,}\tabcellsep human,\\
\multicolumn{4}{l}{contextual and technological factors}\\
\multicolumn{4}{l}{collectively determine the variation in}\\
\multicolumn{4}{l}{the success/failure of an IT-project.}\end{longtable} \par
 
\caption{\label{tab_4}Table 3 .}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.33159652638610554\textwidth}P{0.047695390781563124\textwidth}P{0.17261189044756178\textwidth}P{0.23223112892451567\textwidth}P{0.01646626586506346\textwidth}P{0.049398797595190384\textwidth}}
\tabcellsep \multicolumn{5}{l}{1 : Description of the Research Variables}\\
Variables\tabcellsep Min\tabcellsep Max\tabcellsep Mean\tabcellsep \multicolumn{2}{l}{Rank Std. Deviation}\\
HF\tabcellsep 3.17\tabcellsep 5.44\tabcellsep 4.5559\tabcellsep 4\tabcellsep .47526\\
OF\tabcellsep 3.11\tabcellsep 4.88\tabcellsep 3.8071\tabcellsep 5\tabcellsep .41125\\
TF\tabcellsep 3.21\tabcellsep 6.64\tabcellsep 4.6851\tabcellsep 3\tabcellsep .57352\\
ISD\tabcellsep 3.50\tabcellsep 5.45\tabcellsep 4.7106\tabcellsep 3\tabcellsep .46861\\
USE\tabcellsep 2.13\tabcellsep 6.21\tabcellsep 5.6248\tabcellsep 2\tabcellsep .78603\\
PRC\tabcellsep 3.27\tabcellsep 5.31\tabcellsep 4.5234\tabcellsep 1\tabcellsep .63711\\
PRB\tabcellsep 2.23\tabcellsep 5.11\tabcellsep 4.3321\tabcellsep 2\tabcellsep .56241\\
STF\tabcellsep 2.47\tabcellsep 5.39\tabcellsep 4.5005\tabcellsep 3\tabcellsep .77512\\
OPR\tabcellsep 3.14\tabcellsep 5.21\tabcellsep 4.3101\tabcellsep 2\tabcellsep .46327\\
SFF\tabcellsep 2.22\tabcellsep 6.11\tabcellsep 5.5137\tabcellsep 2\tabcellsep .67512\\
\multicolumn{6}{l}{Table 4.2 : List of the Demographic Variables and Attributes}\\
\multicolumn{2}{l}{Variables}\tabcellsep \multicolumn{4}{l}{Working Definitions (Attributes) Code}\\
\multicolumn{2}{l}{1 Respondent-}\tabcellsep \multicolumn{3}{l}{Professors, Doctors, Consultants}\tabcellsep RTP\\
Type\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
2 Sector\tabcellsep \tabcellsep \multicolumn{2}{l}{Public and Private}\tabcellsep \tabcellsep PPR\\
3 Nature\tabcellsep \tabcellsep \multicolumn{2}{l}{Health/Education}\tabcellsep \tabcellsep HED\\
4 Gender\tabcellsep \tabcellsep \multicolumn{2}{l}{Male/Female}\tabcellsep \tabcellsep GDR\\
5 ICT-\tabcellsep \tabcellsep \multicolumn{3}{l}{IT People/Non-IT Workers}\tabcellsep CNC\\
\multicolumn{2}{l}{Background}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
6 Age\tabcellsep \tabcellsep \multicolumn{3}{l}{Age of the Respondents}\tabcellsep AGE\\
\multicolumn{2}{l}{7 Experience}\tabcellsep \multicolumn{3}{l}{Using Computer Since}\tabcellsep EXP\\
\multicolumn{2}{l}{8 Designation}\tabcellsep \multicolumn{3}{l}{Designation of the Professors,}\tabcellsep DSG\\
\tabcellsep \tabcellsep \multicolumn{3}{l}{Doctors and IT Consultants}\tabcellsep \\
9 City\tabcellsep \tabcellsep \multicolumn{3}{l}{Peshawar/Dera Ismail Khan}\tabcellsep CTY\\
\multicolumn{3}{l}{i. Demographic Impacts The impacts of demographics on ISD and use practices are well documented by Wims \& Lawler, 2007; Mehra \& Mital, 2007. The developers of IT projects are constantly advised by the experts to address demographic differences regarding the development and use of IT projects for generating and sustaining positive user attitudes for effective uses of IT (Gay et al.,}\tabcellsep \multicolumn{3}{l}{2006), which are based on the user-characteristics of gender, age, educational level, computer skills, experience with use of IT besides users styles, personal goals and attitudes, preferences, cultural background, experience, motivation (Moolman \& Blignaut, 2008). The tables 4.3, 4.4 and 4.5 elaborate the statistics on demographic variables:}\end{longtable} \par
 
\caption{\label{tab_5}Table 4 .}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.0391304347826087\textwidth}P{0.10108695652173913\textwidth}P{0.05108695652173913\textwidth}P{0.11956521739130435\textwidth}P{0.05108695652173913\textwidth}P{0.11304347826086958\textwidth}P{0.05108695652173913\textwidth}P{0.11521739130434783\textwidth}P{0.05108695652173913\textwidth}P{0.09347826086956522\textwidth}P{0.06413043478260869\textwidth}}
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep D D D D ) C\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep (\\
\tabcellsep \multicolumn{2}{l}{Type of}\tabcellsep \multicolumn{2}{l}{IT people/Non-}\tabcellsep \multicolumn{2}{l}{Public/Private}\tabcellsep \multicolumn{2}{l}{Health//Education}\tabcellsep \multicolumn{2}{l}{Gender}\\
\tabcellsep \multicolumn{2}{l}{Respondent}\tabcellsep \multicolumn{2}{l}{IT Workers}\tabcellsep \multicolumn{2}{l}{(df 352= 1.96)}\tabcellsep \multicolumn{2}{l}{(df 352=1.96)}\tabcellsep \multicolumn{2}{l}{(df 352= 1.96)}\\
\tabcellsep \multicolumn{2}{l}{(df 2/351 =}\tabcellsep \multicolumn{2}{l}{(df 352= 1.96)}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep 3.0)\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
Variables\tabcellsep F\tabcellsep p-\tabcellsep Cal. T-\tabcellsep p-\tabcellsep Cal. T-\tabcellsep p-\tabcellsep Cal. T-\tabcellsep p-\tabcellsep Cal. T-\tabcellsep p-\\
\tabcellsep \tabcellsep Value\tabcellsep Val\tabcellsep Value\tabcellsep Val\tabcellsep Value\tabcellsep Value\tabcellsep Value\tabcellsep Val\tabcellsep Value\\
HF\tabcellsep 5.417\tabcellsep .002\tabcellsep 11.025\tabcellsep .000\tabcellsep -3.256\tabcellsep .002\tabcellsep 11.024\tabcellsep .000\tabcellsep 8.112\tabcellsep .000\\
OF\tabcellsep 6.305\tabcellsep .001\tabcellsep 10.946\tabcellsep .000\tabcellsep -3.829\tabcellsep .000\tabcellsep 11.244\tabcellsep .000\tabcellsep 4.235\tabcellsep .000\\
TF\tabcellsep 26.032\tabcellsep .000\tabcellsep 8.304\tabcellsep .000\tabcellsep -2.164\tabcellsep .018\tabcellsep 9.404\tabcellsep .020\tabcellsep 1.784\tabcellsep .050\\
ISD\tabcellsep .710\tabcellsep .331\tabcellsep 12.556\tabcellsep .000\tabcellsep -4.873\tabcellsep .000\tabcellsep 13.843\tabcellsep .000\tabcellsep 5.822\tabcellsep .000\\
USE\tabcellsep 25.374\tabcellsep .000\tabcellsep 11.877\tabcellsep .000\tabcellsep -2.610\tabcellsep .006\tabcellsep 14.565\tabcellsep .000\tabcellsep 4.621\tabcellsep .000\\
PRC\tabcellsep 10.230\tabcellsep .000\tabcellsep 8.335\tabcellsep .000\tabcellsep -1.132\tabcellsep .207\tabcellsep 10.351\tabcellsep .000\tabcellsep 5.856\tabcellsep .000\\
PRB\tabcellsep 12.111\tabcellsep .000\tabcellsep 7.214\tabcellsep .000\tabcellsep -2.153\tabcellsep .017\tabcellsep 12.240\tabcellsep .000\tabcellsep 5.745\tabcellsep .000\\
STF\tabcellsep 5.316\tabcellsep .001\tabcellsep 10.021\tabcellsep .000\tabcellsep -4.762\tabcellsep .000\tabcellsep 10.451\tabcellsep .000\tabcellsep 5.711\tabcellsep .000\\
OPR\tabcellsep 21.651\tabcellsep .000\tabcellsep 10.835\tabcellsep .000\tabcellsep -3.651\tabcellsep .000\tabcellsep 8.5313\tabcellsep .000\tabcellsep 4.332\tabcellsep .000\\
SFF\tabcellsep 22.263\tabcellsep .000\tabcellsep 7.203\tabcellsep .000\tabcellsep -2.053\tabcellsep .017\tabcellsep 8.338\tabcellsep .021\tabcellsep 1.673\tabcellsep .040\\
\tabcellsep \multicolumn{2}{l}{ANOVA}\tabcellsep \multicolumn{2}{l}{t-Test}\tabcellsep \multicolumn{2}{l}{t-Test}\tabcellsep t-Test\tabcellsep \tabcellsep t-Test\tabcellsep \end{longtable} \par
 
\caption{\label{tab_6}Table 4 .}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.00764126712328767\textwidth}P{0.20958904109589038\textwidth}P{0.07168236301369864\textwidth}P{0.04293664383561644\textwidth}P{0.0021832191780821915\textwidth}P{0.06877140410958904\textwidth}P{0.044028253424657535\textwidth}P{0.005821917808219178\textwidth}P{0.06913527397260275\textwidth}P{0.1309931506849315\textwidth}P{0.036023116438356165\textwidth}P{0.060038527397260275\textwidth}P{0.031292808219178084\textwidth}P{0.0542166095890411\textwidth}P{0.015646404109589042\textwidth}}
\tabcellsep \multicolumn{12}{l}{Information System Development and Use Practices in Khyber Pakhtoon Khwa (K.P.K) Pakistan}\\
\tabcellsep \tabcellsep \tabcellsep \multicolumn{10}{l}{(An Empirical Study of the Demographics Impacts)}\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{Age}\tabcellsep \tabcellsep \multicolumn{3}{l}{Exp with Computer}\tabcellsep \tabcellsep ICT-Q\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{3}{l}{(df 352= 1.96)}\tabcellsep \multicolumn{3}{l}{(df 352= 1.96)}\tabcellsep \multicolumn{2}{l}{(df 352= 1.96)}\\
\tabcellsep \tabcellsep \multicolumn{3}{l}{Variables}\tabcellsep Cal. T-\tabcellsep p-\tabcellsep \tabcellsep \multicolumn{2}{l}{Cal. T-}\tabcellsep p-Value\tabcellsep \multicolumn{2}{l}{Cal. T-}\tabcellsep p-Value\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep Val\tabcellsep \multicolumn{2}{l}{Value}\tabcellsep Val\tabcellsep \tabcellsep \tabcellsep Val\\
\tabcellsep \tabcellsep \tabcellsep HF\tabcellsep \tabcellsep -.204\tabcellsep \multicolumn{2}{l}{.838}\tabcellsep \multicolumn{2}{l}{5.146}\tabcellsep .000\tabcellsep \multicolumn{2}{l}{7.271}\tabcellsep .000\\
\tabcellsep \tabcellsep \tabcellsep OF\tabcellsep \tabcellsep -.129\tabcellsep \multicolumn{2}{l}{.897}\tabcellsep \multicolumn{2}{l}{6.779}\tabcellsep .000\tabcellsep \multicolumn{2}{l}{9.513}\tabcellsep .000\\
\tabcellsep \tabcellsep \tabcellsep TF\tabcellsep \tabcellsep 1.219\tabcellsep \multicolumn{2}{l}{.224}\tabcellsep \multicolumn{2}{l}{6.333}\tabcellsep .000\tabcellsep \multicolumn{2}{l}{5.691}\tabcellsep .000\\
\tabcellsep \tabcellsep \tabcellsep ISD\tabcellsep \tabcellsep .127\tabcellsep \multicolumn{2}{l}{.899}\tabcellsep \multicolumn{2}{l}{4.308}\tabcellsep .000\tabcellsep \multicolumn{2}{l}{12.742}\tabcellsep .000\\
\tabcellsep \tabcellsep \multicolumn{2}{l}{USE}\tabcellsep \tabcellsep -2.752\tabcellsep \multicolumn{2}{l}{.006}\tabcellsep \multicolumn{2}{l}{5.363}\tabcellsep .000\tabcellsep \multicolumn{2}{l}{9.132}\tabcellsep .000\\
2012\tabcellsep \tabcellsep \multicolumn{2}{l}{PRC PRB STF}\tabcellsep \tabcellsep .002 1.331 -.201\tabcellsep \multicolumn{2}{l}{.998 .231 .827}\tabcellsep \multicolumn{2}{l}{6.012 6.232 5.235}\tabcellsep .000 .000 .000\tabcellsep \multicolumn{2}{l}{8.533 4.580 6.161}\tabcellsep .000 .000 .000\\
Year\tabcellsep \tabcellsep \multicolumn{2}{l}{OPR SFF}\tabcellsep \tabcellsep .133 -211\tabcellsep \multicolumn{2}{l}{.888 .828}\tabcellsep \multicolumn{2}{l}{5.662 4.035}\tabcellsep .000 .000\tabcellsep \multicolumn{2}{l}{8.402 6.160}\tabcellsep .000 .000\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{t-Test}\tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{t-Test}\tabcellsep \tabcellsep t-Test\\
\tabcellsep \multicolumn{12}{l}{Table 4.5 : City, Use of IT Since, Designation (Professor, Doctors and IT Consultants) Impacts}\\
\tabcellsep \tabcellsep City\tabcellsep \tabcellsep \tabcellsep \multicolumn{3}{l}{Use of IT Since}\tabcellsep \multicolumn{3}{l}{Designation}\tabcellsep \multicolumn{2}{l}{Designation}\tabcellsep Designation (IT\\
\tabcellsep \tabcellsep \multicolumn{3}{l}{(df 352=1096)}\tabcellsep \multicolumn{3}{l}{(df 352= 1.96)}\tabcellsep \multicolumn{3}{l}{(Professors)}\tabcellsep \multicolumn{2}{l}{(Doctors)}\tabcellsep Consultants)\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{3}{l}{(df 352= 3.0)}\tabcellsep \multicolumn{2}{l}{(df 1/134=3.0)}\tabcellsep (df 352= 310)\\
\tabcellsep Variables\tabcellsep Cal T-\tabcellsep p-\tabcellsep \tabcellsep Cal. T-\tabcellsep p-\tabcellsep \tabcellsep F\tabcellsep \tabcellsep p-\tabcellsep F\tabcellsep p-\tabcellsep F\tabcellsep p-\\
\tabcellsep \tabcellsep Value\tabcellsep Value\tabcellsep \tabcellsep Val\tabcellsep \multicolumn{2}{l}{Value}\tabcellsep \tabcellsep \multicolumn{2}{l}{Value}\tabcellsep \tabcellsep Value\tabcellsep Value\\
\tabcellsep HF\tabcellsep -4.722\tabcellsep .000\tabcellsep \tabcellsep -1.887\tabcellsep \multicolumn{2}{l}{.460}\tabcellsep \multicolumn{2}{l}{-3.665}\tabcellsep .002\tabcellsep .743\tabcellsep .920\tabcellsep .812\tabcellsep .710\\
\tabcellsep OF\tabcellsep -3.446\tabcellsep .000\tabcellsep \tabcellsep -2.055\tabcellsep \multicolumn{2}{l}{.041}\tabcellsep \multicolumn{2}{l}{-.734}\tabcellsep .842\tabcellsep 2.488\tabcellsep .080\tabcellsep 3.124\tabcellsep .011\\
\tabcellsep TF\tabcellsep -.584\tabcellsep .377\tabcellsep \tabcellsep -1.271\tabcellsep \multicolumn{2}{l}{.157}\tabcellsep \multicolumn{2}{l}{1.264}\tabcellsep .770\tabcellsep 3.404\tabcellsep .000\tabcellsep 1.424\tabcellsep .051\\
\tabcellsep ISD\tabcellsep -1.610\tabcellsep .085\tabcellsep \tabcellsep -3.041\tabcellsep \multicolumn{2}{l}{.003}\tabcellsep \multicolumn{2}{l}{1.873}\tabcellsep .233\tabcellsep .0239\tabcellsep .721\tabcellsep 1.771\tabcellsep .021\\
\tabcellsep USE\tabcellsep -3.641\tabcellsep .399\tabcellsep \tabcellsep -1.666\tabcellsep \multicolumn{2}{l}{.386}\tabcellsep \multicolumn{2}{l}{1.473}\tabcellsep .366\tabcellsep .329\tabcellsep .730\tabcellsep 1.521\tabcellsep .003\\
\tabcellsep PRC\tabcellsep -4.030\tabcellsep .010\tabcellsep \tabcellsep -1.244\tabcellsep \multicolumn{2}{l}{.202}\tabcellsep \multicolumn{2}{l}{1.321}\tabcellsep .273\tabcellsep 1.351\tabcellsep .022\tabcellsep 1.745\tabcellsep .061\\
\tabcellsep PRB\tabcellsep -4.611\tabcellsep .000\tabcellsep \tabcellsep -1.776\tabcellsep \multicolumn{2}{l}{.461}\tabcellsep \multicolumn{2}{l}{-3.554}\tabcellsep .001\tabcellsep .732\tabcellsep .911\tabcellsep .811\tabcellsep .711\\
( D D D D ) C\tabcellsep STF OPR\tabcellsep -3.335 -1.434\tabcellsep .000 .000\tabcellsep \tabcellsep -2,043 -2.154\tabcellsep \multicolumn{2}{l}{.041 .040}\tabcellsep \multicolumn{2}{l}{..635 -3.556}\tabcellsep .001 .002\tabcellsep 2.377 .732\tabcellsep .070 .900\tabcellsep 3.013 .701\tabcellsep .010 .611\\
\tabcellsep SFF\tabcellsep -.475\tabcellsep .000\tabcellsep \tabcellsep -2.144\tabcellsep \multicolumn{2}{l}{.156}\tabcellsep \multicolumn{2}{l}{1.153}\tabcellsep .711\tabcellsep 3.303\tabcellsep .000\tabcellsep 1.346\tabcellsep .050\\
\tabcellsep \tabcellsep \multicolumn{2}{l}{t-test}\tabcellsep \tabcellsep \multicolumn{2}{l}{t-Test}\tabcellsep \tabcellsep \multicolumn{3}{l}{ANOVA}\tabcellsep \multicolumn{2}{l}{ANOVA}\tabcellsep ANOVA\\
\tabcellsep \multicolumn{8}{l}{b) Hypothesis Testing Hypothesis No.1: The Public organizations are under-using IT potentials in comparison to private sector. Results of independent sample t-test are shown in the below tables. As may be seen, the difference in the means of 3.65 and 2.58 with the standard deviations}\tabcellsep \multicolumn{4}{l}{of .51 and .47 for the public and private respectively on the IT-potentials as IT use is significant. Similarly, calculated t value 14.234 in table No. 4.6 is greater than the tabulated t value 1.960, thus H 0 is not substantiated, which validates that public sector is under using IT potentials in comparison to private sector.}\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{4}{l}{Group Statistics}\tabcellsep \tabcellsep \\
\tabcellsep \tabcellsep \tabcellsep \multicolumn{3}{l}{Nature}\tabcellsep N\tabcellsep \multicolumn{2}{l}{Mean}\tabcellsep \multicolumn{3}{l}{Std. Deviation}\tabcellsep Std. Error Mean\\
\tabcellsep \tabcellsep \multicolumn{2}{l}{IT Potentials}\tabcellsep \multicolumn{2}{l}{Public}\tabcellsep 149\tabcellsep \multicolumn{2}{l}{3.6577}\tabcellsep \multicolumn{2}{l}{.518702}\tabcellsep \tabcellsep .03383\\
\tabcellsep \tabcellsep \tabcellsep \multicolumn{3}{l}{Private}\tabcellsep 128\tabcellsep \multicolumn{2}{l}{2.5812}\tabcellsep \tabcellsep .47114\tabcellsep \tabcellsep .03541\\
\tabcellsep \tabcellsep \multicolumn{11}{l}{Table 4.6 : Represents Groups Statistics for Hypothesis No. 1}\\
\tabcellsep \multicolumn{5}{l}{a. Grouping Variables: Public, Private}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep \multicolumn{3}{l}{b. Testing Variable: IT-Potentials}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_7}Table 4 .}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.011510416666666667\textwidth}P{0.4303125\textwidth}P{0.016822916666666667\textwidth}P{0.006197916666666667\textwidth}P{0.028333333333333332\textwidth}P{0.33291666666666664\textwidth}P{0.02390625\textwidth}}
( D D D D ) C\tabcellsep \multicolumn{4}{l}{Hypothesis No.4: Public sector is less optimistic}\tabcellsep \multicolumn{2}{l}{organizations is significant. Where calculated t value}\\
\tabcellsep \multicolumn{2}{l}{about the role of IT than private sector.}\tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{15.097 in table No. 4.13 is greater than the tabulated t}\\
\tabcellsep \multicolumn{4}{l}{Results of independent sample t-test for the}\tabcellsep \multicolumn{2}{l}{value 1.960, Thus H 0 is not substantiated. This implies}\\
\tabcellsep \multicolumn{4}{l}{fourth hypothesis are shown in the below tables. As may}\tabcellsep \multicolumn{2}{l}{that private sector is more optimistic about the role of IT}\\
\tabcellsep \multicolumn{4}{l}{be seen, the difference in the means of 1.64 and 1.37}\tabcellsep \multicolumn{2}{l}{in organizations for maximum efficiency and effective}\\
\tabcellsep \multicolumn{4}{l}{with the standard deviations of .45 and .34 for the public}\tabcellsep \multicolumn{2}{l}{utilization of both the human and material resources of}\\
\tabcellsep \multicolumn{4}{l}{and private respectively on the Role of IT in}\tabcellsep the organization.\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{Group Statistics}\\
\tabcellsep \tabcellsep Nature\tabcellsep N\tabcellsep Mean\tabcellsep Std. Deviation\tabcellsep Std. Error Mean\\
\tabcellsep Role of IT in Org.\tabcellsep Public\tabcellsep 149\tabcellsep 1.6437\tabcellsep .45367\tabcellsep .01545\\
\tabcellsep \tabcellsep Private\tabcellsep 128\tabcellsep 1.3772\tabcellsep .37160\tabcellsep .02302\\
\tabcellsep \multicolumn{6}{l}{Table 4.12 : Show Group Statistics for Hypothesis No.4}\\
\tabcellsep \multicolumn{2}{l}{a. Grouping Variables: Public, Private}\tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep b. Testing Variable: Role of IT\tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_8}Table 4 .}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.85\textwidth}}
Hypothesis No.5: Professors, doctors and\\
consultants view IT differently.\end{longtable} \par
 
\caption{\label{tab_9}Table 4 .}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.095525494276795\textwidth}P{0.0672216441207076\textwidth}P{0.09729448491155046\textwidth}P{0.041571279916753384\textwidth}P{0.06987513007284078\textwidth}P{0.057492195629552545\textwidth}P{0.10437044745057232\textwidth}P{0.08579604578563996\textwidth}P{0.05041623309053069\textwidth}P{0.095525494276795\textwidth}P{0.01149843912591051\textwidth}P{0.07341311134235172\textwidth}}
\tabcellsep IT\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{Sum of Squares}\tabcellsep df\tabcellsep \multicolumn{2}{l}{Mean Square}\tabcellsep F\tabcellsep Sig.\tabcellsep \\
\tabcellsep \multicolumn{3}{l}{Between Groups}\tabcellsep .026\tabcellsep \tabcellsep 2\tabcellsep \tabcellsep .014\tabcellsep .240\tabcellsep .676\tabcellsep \\
\tabcellsep \multicolumn{2}{l}{Within Groups}\tabcellsep \tabcellsep \multicolumn{2}{l}{11.146}\tabcellsep 204\tabcellsep \tabcellsep .053\tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep \tabcellsep Total\tabcellsep \tabcellsep \multicolumn{2}{l}{11.172}\tabcellsep 206\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep \tabcellsep \multicolumn{8}{l}{Table 4.14 : Represents ANOVA Results for Hypothesis No.5}\tabcellsep \tabcellsep \\
\multicolumn{6}{l}{a. Grouping Variables: Professor, Doctors \& IT}\tabcellsep \tabcellsep \multicolumn{5}{l}{Hypothesis No.6: Experience of non-IT}\\
consultants\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{6}{l}{workforce is negatively correlated with perceptions}\\
\multicolumn{2}{l}{b. Testing Variable: IT}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{about IT.}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{3}{l}{15 : Correlation}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep HF\tabcellsep OF\tabcellsep TF\tabcellsep ISD\tabcellsep USE\tabcellsep PRC\tabcellsep PRB\tabcellsep STF\tabcellsep \multicolumn{2}{l}{OPR SFF}\tabcellsep Average r\\
HF\tabcellsep 1\tabcellsep 0.651\tabcellsep 0.44\tabcellsep 0.611\tabcellsep 0.746\tabcellsep 0.486\tabcellsep 0.404\tabcellsep 0.409\tabcellsep \multicolumn{2}{l}{0.541 0.301}\tabcellsep 0.535286\\
OF\tabcellsep 0.651\tabcellsep 1\tabcellsep 0.758\tabcellsep 0.746\tabcellsep 0.834\tabcellsep 0.732\tabcellsep 0.349\tabcellsep 0.455\tabcellsep \multicolumn{2}{l}{0.632 0.647}\tabcellsep 0.646429\\
TF\tabcellsep 0.44\tabcellsep 0.758\tabcellsep 1\tabcellsep 0.577\tabcellsep 0.745\tabcellsep 0.665\tabcellsep 0.334\tabcellsep 0.334\tabcellsep \multicolumn{2}{l}{0.466 0.403}\tabcellsep 0.550429\\
ISD\tabcellsep 0.611\tabcellsep 0.746\tabcellsep 0.577\tabcellsep 1\tabcellsep 0.708\tabcellsep 0.506\tabcellsep 0.281\tabcellsep 0.372\tabcellsep \multicolumn{2}{l}{0.607 0.431}\tabcellsep 0.543\\
USE\tabcellsep 0.746\tabcellsep 0.834\tabcellsep 0.745\tabcellsep 0.708\tabcellsep 1\tabcellsep 0.718\tabcellsep 0.719\tabcellsep 0.431\tabcellsep \multicolumn{2}{l}{0.617 0.734}\tabcellsep 0.700143\\
PRC\tabcellsep 0.486\tabcellsep 0.732\tabcellsep 0.665\tabcellsep 0.506\tabcellsep 0.718\tabcellsep 1\tabcellsep 0.275\tabcellsep 0.203\tabcellsep \multicolumn{2}{l}{0.264 0.566}\tabcellsep 0.512143\\
PRB\tabcellsep 0.404\tabcellsep 0.349\tabcellsep 0.334\tabcellsep 0.281\tabcellsep 0.719\tabcellsep 0.275\tabcellsep 1\tabcellsep 0.263\tabcellsep \multicolumn{2}{l}{0.348 0.271}\tabcellsep 0.375\\
STF\tabcellsep 0.409\tabcellsep 0.455\tabcellsep 0.334\tabcellsep 0.372\tabcellsep 0.431\tabcellsep 0.203\tabcellsep 0.263\tabcellsep 1\tabcellsep \multicolumn{2}{l}{0.232 0.322}\tabcellsep 0.352429\\
OPR\tabcellsep 0.541\tabcellsep 0.632\tabcellsep 0.466\tabcellsep 0.607\tabcellsep 0.617\tabcellsep 0.264\tabcellsep 0.348\tabcellsep 0.232\tabcellsep 1\tabcellsep 0.305\tabcellsep 0.524175\\
SFF\tabcellsep 0.301\tabcellsep 0.647\tabcellsep 0.403\tabcellsep 0.331\tabcellsep 0.734\tabcellsep 0.556\tabcellsep 0.271\tabcellsep 0.322\tabcellsep \multicolumn{2}{l}{0.305 1}\tabcellsep 0.536238\end{longtable} \par
  {\small\itshape [Note: Correlation is significant at the 0.01 level (2-tailed). (n=277)]} 
\caption{\label{tab_10}Table 4 .}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.330703125\textwidth}P{0.15539062499999998\textwidth}P{0.041171875\textwidth}P{0.07171875\textwidth}P{0.08632812499999999\textwidth}P{0.003984375\textwidth}P{0.07171875\textwidth}P{0.05578125\textwidth}P{0.022578124999999998\textwidth}P{0.010625\textwidth}}
Model\tabcellsep R\tabcellsep \multicolumn{2}{l}{R. Square}\tabcellsep \multicolumn{3}{l}{R. Square (Adjusted)}\tabcellsep Estimation Std Error\\
1\tabcellsep .104(a)\tabcellsep .011\tabcellsep \tabcellsep \multicolumn{2}{l}{.008}\tabcellsep \tabcellsep .23501\\
\multicolumn{5}{l}{a. Constant Predictors, Perception about IT,}\tabcellsep \tabcellsep \\
\multicolumn{3}{l}{Success/Perception of IT Projects.}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep \multicolumn{7}{l}{Table 4.16 : Represents Model Summary for Hypothesis No.7}\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{ANOVA}\tabcellsep \\
Model\tabcellsep \tabcellsep \multicolumn{3}{l}{The sum of Squares}\tabcellsep df\tabcellsep \multicolumn{2}{l}{Square of Mean}\tabcellsep F\tabcellsep Sig.\\
1\tabcellsep Regression\tabcellsep \tabcellsep .239\tabcellsep \tabcellsep 1\tabcellsep .239\tabcellsep 4.217\tabcellsep .038(a)\\
\tabcellsep Residual\tabcellsep \tabcellsep 21.982\tabcellsep \multicolumn{2}{l}{275}\tabcellsep .055\\
\tabcellsep Total\tabcellsep \tabcellsep 22.220\tabcellsep \multicolumn{2}{l}{277}\tabcellsep \\
\multicolumn{3}{l}{a. Constant Predictors, Perception about IT}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{5}{l}{b. Dependent Variable: Success/Perception of IT}\tabcellsep \tabcellsep \\
Projects\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{Coefficients}\tabcellsep \\
\tabcellsep \tabcellsep \tabcellsep \multicolumn{3}{l}{Non Standardized}\tabcellsep \multicolumn{2}{l}{Standardized}\\
Model\tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{Coefficients}\tabcellsep \tabcellsep \multicolumn{2}{l}{Coefficients}\tabcellsep t\tabcellsep Sig.\\
\tabcellsep \tabcellsep \tabcellsep B\tabcellsep \multicolumn{2}{l}{Std. Error}\tabcellsep Beta\\
1\tabcellsep \multicolumn{2}{l}{(Constant)}\tabcellsep 3.128\tabcellsep .045\tabcellsep \tabcellsep \tabcellsep 69.497\tabcellsep .000\\
\tabcellsep \multicolumn{2}{l}{Perception about IT}\tabcellsep .057\tabcellsep .028\tabcellsep \tabcellsep .513\tabcellsep 2.078\tabcellsep .038\\
\multicolumn{5}{l}{a. Dependent Variable: Success/Perception of IT}\tabcellsep \tabcellsep \\
Projects\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_11}Table 4 .}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.85\textwidth}}
12\\
Volume XII Issue XV Version I\\
D D D D ) C\\
(\\
Global Journal of Computer Science and Technology\\
© 2012 Global Journals Inc. (US)\end{longtable} \par
 
\caption{\label{tab_12}Table 4 .}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.2570263488080301\textwidth}P{0.19730238393977415\textwidth}P{0.03306148055207026\textwidth}P{0.07145545796737766\textwidth}P{0.09171894604767879\textwidth}P{0.03519447929736512\textwidth}P{0.041593475533249685\textwidth}P{0.06292346298619825\textwidth}P{0.043726474278544536\textwidth}P{0.015997490589711415\textwidth}}
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{3}{l}{Summary of Model}\\
Model\tabcellsep R\tabcellsep \multicolumn{2}{l}{R. Square}\tabcellsep \multicolumn{3}{l}{R. Square (Adjusted)}\tabcellsep Estimation of Std Error\\
1\tabcellsep .561(a)\tabcellsep .315\tabcellsep \tabcellsep .310\tabcellsep \tabcellsep \tabcellsep .19607\\
\multicolumn{5}{l}{a. Constant Predictors, Organization, human, context}\tabcellsep \tabcellsep \\
and Technology.\tabcellsep \multicolumn{7}{l}{Table 4.19 : Represents Model Summary for Hypothesis No.8}\tabcellsep ( D D D D ) C\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{ANOVA}\tabcellsep \\
Model\tabcellsep \tabcellsep \multicolumn{3}{l}{The Sum of Squares}\tabcellsep df\tabcellsep \multicolumn{2}{l}{Square of Mean}\tabcellsep F\tabcellsep Sig.\\
1\tabcellsep Regression\tabcellsep \tabcellsep \multicolumn{2}{l}{6.996}\tabcellsep 3\tabcellsep \multicolumn{2}{l}{2.332}\tabcellsep 61.553\tabcellsep .000(a)\\
\tabcellsep Residual\tabcellsep \tabcellsep \multicolumn{2}{l}{15.224}\tabcellsep 396\tabcellsep \tabcellsep .038\\
\tabcellsep Total\tabcellsep \tabcellsep \multicolumn{2}{l}{22.220}\tabcellsep 399\tabcellsep \\
\multicolumn{5}{l}{a. Constant Predictors, Organization, human, context}\tabcellsep \tabcellsep \\
\& Technology.\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{4}{l}{b. Dependent Variable: Success of IT Projects}\tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{Coefficients}\tabcellsep \\
\tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{Non standardized}\tabcellsep \multicolumn{3}{l}{Standardized}\\
Model\tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{Coefficients}\tabcellsep \multicolumn{3}{l}{Coefficients}\tabcellsep t\tabcellsep Sig.\\
\tabcellsep \tabcellsep \tabcellsep B\tabcellsep Std Error\tabcellsep \tabcellsep Beta\\
1\tabcellsep \multicolumn{2}{l}{(Constant)}\tabcellsep 1.405\tabcellsep .137\tabcellsep \tabcellsep \tabcellsep 10.243\tabcellsep .000\\
\tabcellsep \multicolumn{2}{l}{Organization}\tabcellsep .269\tabcellsep .043\tabcellsep \tabcellsep .365\tabcellsep 9.653\tabcellsep .000\\
\tabcellsep Human\tabcellsep \tabcellsep .253\tabcellsep .029\tabcellsep \tabcellsep .704\tabcellsep 8.764\tabcellsep .000\\
\tabcellsep Context\tabcellsep \tabcellsep .412\tabcellsep .054\tabcellsep \tabcellsep .372\tabcellsep 9.651\tabcellsep .000\\
\tabcellsep \multicolumn{2}{l}{Technology}\tabcellsep .468\tabcellsep .048\tabcellsep \tabcellsep .533\tabcellsep 9.782\tabcellsep .000\\
\multicolumn{4}{l}{a. Dependent Variable: Success of IT Projects}\tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep \multicolumn{7}{l}{Table 4.21 : Portray Coefficients for Hypothesis No.8}\end{longtable} \par
 
\caption{\label{tab_13}Table 4 .}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{} \par 
\begin{longtable}{}
\end{longtable} \par
 
\caption{\label{tab_14}}\end{figure}
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\end{document}
