# Introduction eveloping a computer-based information system (CBIS) is not simply the purchase and installation of hardware and software (Rockart, et al., 1996;Smith, 1998;Walsham, 1993Walsham, , 2000;;Turban et al., 2004). It rather goes beyond it to the problems of people, organization and the context (Avgerou and Cornford, 1998); Segars and Grover, 1996); Dann et al., 1998). Research findings assert that an IS development (ISD) is a 'social process' (Lyytinen, 1987;Checkland, 1991;Walsham, 1993) thereby considering all the human, organizational, contextual and technological issues as in case of any organizational project. 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, Argyris, 1971;Kaasboll, 1997;Dann et al., 1998;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, Land et al., 1992;Segars and Grover, 1996). Environment or context is significant since its change altogether changes requirements for the success/failure of an IT project (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 (Argyris, 1971;Segars and Grover, 1996). 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 (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 (Kaasboll, 1997). Likewise, organizational factors are less threatening during the initial phases of ISDLC but once new system is in action 'IT-business-alignment' (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 Glass, 1998). 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, Avison and r-Harper, 1990;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. 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. 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. # Review of the relevant literature 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 (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 (Segars and Grover, 1996;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 (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 (Kaasboll, 1997). # b) Perceptions about IT Life is what one believes in so perceptions of technology have bearing upon how they are used (see for example, Brooke, 1995;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 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 (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. # c) Approaches and Methodologies Several approaches have been theorized, exercised and reduced into black-n-white for computerization efforts (Hirschheim and Klein, 1989; Wynekoop and Russo 1995; Avison and Fitzgerald, 1995;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 (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. Under hard and soft approaches, structured and unstructured ISD methodologies have been developed respectively. SSADM and STRAIDS (Weaver, 1993;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 Henshall, 1979;Mumford, 1997). New CBIS changes the power structures therefore; losers and winners are created where losers naturally resist changing (see for example, 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, Markus, 1981Markus, , 1983;;Drummond, 1995;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 (Glass, 1998). Failures are the repositories of the research questions for problemsolutions and improvement (Ewusi-Mensah and Przasnyski, , 1992McGrath, 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 Hirschheim, 1987;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 (Collins and Bicknell, 1997;Glass, 1998;Sauer, 1999) N = 4372 n = 277 Formula n a = [(nN a ? a )/((N a ? a )+(N b ? b )+(N c ? c ))] # c) Data Collection and Analysis i. Data Collection Methods 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. 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. 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: 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 3.5 provides the detail. # Multiple Regression g) Pilot Study All the above constructs and methods were used in the pilot study with the objectives of: ? Testing the research tools (particularly constructs). As a consequence several attributes were pinpointed by the respondents, which have been included in the questionnaire. ? Computing statistics to calculate 'sample-size' for the main study. # h) Reliability of Instrument 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 (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. # MS explained MS residual 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. 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. # ANOVA Hypothesis No.7: Higher the perceptions about IT, greater are the chances/perceptions of success in IT projects. 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. 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. 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. 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. 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. # Summary of Model 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. 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. # Major findings and discussion 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 (Argyris, 1971;Kaasboll, 1997;Dann et al., 1998;Glass, 1998) while, Land et al., 1992;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 (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 (Luthans, 1995:149). 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: 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 Drummond (1994Drummond ( , 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) 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. 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. 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 (1993,1999) 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. # VI. # Conclusions 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: 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. 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. 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. 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. 1![Literature Survey: After preliminary literature survey for pilot study, the same was continued in the main research for two purposes: a. optimizing the selected variables and b. data on the topic.](image-2.png "1 .") demographies like organization, humans and context.For example, ETHICS stands for effective technical andhuman implementation of computer systems. MultiViewdemands multi-view perception and treatment ofcomputerization projects.d) Project ManagementAn ISD and use process needs to be managedadequately otherwise leading-edge technology andhuge budgets may gather dust. It is said that thisadequacy is possible if it is recognized that "project isless a matter of understanding constraints and more afunction of personal skills (Elton and Justin, 1998).Researchers have unearthed several IT-projectmanagement strategies. It is now squarely admitted thatan IT project is like any other business project (Smith,1998) therefore, all technical, organizational, human andcontextual dimensions have to be brought on the tablefor visualizing a holistic view of the project.e) ISD Life CycleAn ISD process never ends since it demandsconstant upgrading thus, a cycle continues forever inthe form of recursive stages (Avison and Fitzgerald,1995; Avison and Shah, 1997; Turban et al, 2004:235). 3and b. the 32 : Stratified Samples (Area-by-Sector Samples)PopulationStandardSampleArea-Wise Sectors(Strata)DeviationsSizesPublic Sector Health DIK3600.825Public Sector Health Peshawar6170.737Private Sector Health DIK2100.8916Private Sector Health Peshawar4580.6626Public Sector Education DIK6250.6635Public Sector Education Peshawar7200.8752Private Sector Education DIK2750.6916Private Sector Education Peshawar4800.833Consultants DIK2470.613Consultants Peshawar3800.7824TOTAL4372277Table 3.3 : Sample Selection ProceduresSample (FINITE population)Stratified SamplesPilot Study StatisticsPilot Study StatisticsStandard Deviation (?) Standard Error (E) Z value at 95% Confidence Sample Population N Target Population0.72 0.082 1.96 4372 INFINITEHealth (public) DIK Health (public) Peshawar Health (private) DIK Health (private) Peshawar Education (public) DIKN 360 617 210 458 625SD 0.8 0.7 0.89 0.66 0.66NSample Size277Education (public) Peshawar7200.87Formulan = [? 2 /((z 2 /E 2 )+(? 2 /N))]Education (private) DIK Education (private) Peshawar275 4800.69 0.8Consultants DIK2470.6Consultants Peshawar3800.78 3Information System Development and Use Practices in Khyber Pakhtoon Khwa (K.P.K) Pakistan(An Empirical Study of the Demographics Impacts)2012Year4 : Operationalized VariablesVariablesAttributesCodeOFTechnologicalHardware, Software and IT professionals. Availability, expenses, usabilityTF3Factorsand possibility to upgrade the above items. Developers' organizationalknowledgeISDGovernment and Institutional IT Policies; User Needs Analysis; UserISDD D D D ) CParticipation, Training; Implementation; Maintenance; and Evaluation in(4ISD, ISD approaches, Methodologies, Project management, Userparticipation, developer-user communication, user training, Managementof the resistance to change.5IS UseExperience with IT; User-developer-communication Perceived Ease of Use (PEU); Perceived Usefulness (PU); Volume of Use;USE6PerceptionsIT: the Problem-Solver; Digital Divide; and Socio-economic Impacts of IT.PRC7ProblemsProblems of IT Projects Development, Use and User-SatisfactionPRB8SatisfactionUser-Satisfaction IT Projects Development and Use Practices.STF9OpportunitiesOpportunities for IT Project Success in K.P.K.OPRSuccess/ Failure Definition of success/failure, Degree of success and failure, Ratio ofSFF10success and failure, Critical success and failure factors, Escalation in ITprojects.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. 35 : List of Working HypothesisHypothesisStatistical Tools Applied1 The Public organizations are under-t-testusing IT potentials in comparison toprivate sector.2 Escalation(time-delays,cost-t-testoverruns, compromise on lesserobjectives) of IT projects is morecommon in public organizations thanin private enterprises.3 IT-people overestimate while non-ITt-testworkers underestimate the role of ITin the organizations.4 Public sector is less optimistic aboutt-testthe role of IT than private sector.5 Professors, doctors and consultantsANOVAview IT differently.6 Experience of non-IT workforce isCorrelationnegativelycorrelatedwithanalysisperceptions about IT.7 Higher the perceptions about IT,Simplegreater are the chances/perceptionsRegressionof success in IT projects8 Theorganizational,human,contextual and technological factorscollectively determine the variation inthe success/failure of an IT-project. 41 : Description of the Research VariablesVariablesMinMaxMeanRank Std. DeviationHF3.175.444.55594.47526OF3.114.883.80715.41125TF3.216.644.68513.57352ISD3.505.454.71063.46861USE2.136.215.62482.78603PRC3.275.314.52341.63711PRB2.235.114.33212.56241STF2.475.394.50053.77512OPR3.145.214.31012.46327SFF2.226.115.51372.67512Table 4.2 : List of the Demographic Variables and AttributesVariablesWorking Definitions (Attributes) Code1 Respondent-Professors, Doctors, ConsultantsRTPType2 SectorPublic and PrivatePPR3 NatureHealth/EducationHED4 GenderMale/FemaleGDR5 ICT-IT People/Non-IT WorkersCNCBackground6 AgeAge of the RespondentsAGE7 ExperienceUsing Computer SinceEXP8 DesignationDesignation of the Professors,DSGDoctors and IT Consultants9 CityPeshawar/Dera Ismail KhanCTYi. 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.,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: 4D D D D ) C(Type ofIT people/Non-Public/PrivateHealth//EducationGenderRespondentIT Workers(df 352= 1.96)(df 352=1.96)(df 352= 1.96)(df 2/351 =(df 352= 1.96)3.0)VariablesFp-Cal. T-p-Cal. T-p-Cal. T-p-Cal. T-p-ValueValValueValValueValueValueValValueHF5.417.00211.025.000-3.256.00211.024.0008.112.000OF6.305.00110.946.000-3.829.00011.244.0004.235.000TF26.032.0008.304.000-2.164.0189.404.0201.784.050ISD.710.33112.556.000-4.873.00013.843.0005.822.000USE25.374.00011.877.000-2.610.00614.565.0004.621.000PRC10.230.0008.335.000-1.132.20710.351.0005.856.000PRB12.111.0007.214.000-2.153.01712.240.0005.745.000STF5.316.00110.021.000-4.762.00010.451.0005.711.000OPR21.651.00010.835.000-3.651.0008.5313.0004.332.000SFF22.263.0007.203.000-2.053.0178.338.0211.673.040ANOVAt-Testt-Testt-Testt-Test 4Information System Development and Use Practices in Khyber Pakhtoon Khwa (K.P.K) Pakistan(An Empirical Study of the Demographics Impacts)AgeExp with ComputerICT-Q(df 352= 1.96)(df 352= 1.96)(df 352= 1.96)VariablesCal. T-p-Cal. T-p-ValueCal. T-p-ValueValValueValValHF-.204.8385.146.0007.271.000OF-.129.8976.779.0009.513.000TF1.219.2246.333.0005.691.000ISD.127.8994.308.00012.742.000USE-2.752.0065.363.0009.132.0002012PRC PRB STF.002 1.331 -.201.998 .231 .8276.012 6.232 5.235.000 .000 .0008.533 4.580 6.161.000 .000 .000YearOPR SFF.133 -211.888 .8285.662 4.035.000 .0008.402 6.160.000 .000t-Testt-Testt-TestTable 4.5 : City, Use of IT Since, Designation (Professor, Doctors and IT Consultants) ImpactsCityUse of IT SinceDesignationDesignationDesignation (IT(df 352=1096)(df 352= 1.96)(Professors)(Doctors)Consultants)(df 352= 3.0)(df 1/134=3.0)(df 352= 310)VariablesCal T-p-Cal. T-p-Fp-Fp-Fp-ValueValueValValueValueValueValueHF-4.722.000-1.887.460-3.665.002.743.920.812.710OF-3.446.000-2.055.041-.734.8422.488.0803.124.011TF-.584.377-1.271.1571.264.7703.404.0001.424.051ISD-1.610.085-3.041.0031.873.233.0239.7211.771.021USE-3.641.399-1.666.3861.473.366.329.7301.521.003PRC-4.030.010-1.244.2021.321.2731.351.0221.745.061PRB-4.611.000-1.776.461-3.554.001.732.911.811.711( D D D D ) CSTF OPR-3.335 -1.434.000 .000-2,043 -2.154.041 .040..635 -3.556.001 .0022.377 .732.070 .9003.013 .701.010 .611SFF-.475.000-2.144.1561.153.7113.303.0001.346.050t-testt-TestANOVAANOVAANOVAb) 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 deviationsof .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.Group StatisticsNatureNMeanStd. DeviationStd. Error MeanIT PotentialsPublic1493.6577.518702.03383Private1282.5812.47114.03541Table 4.6 : Represents Groups Statistics for Hypothesis No. 1a. Grouping Variables: Public, Privateb. Testing Variable: IT-Potentials 4( D D D D ) CHypothesis No.4: Public sector is less optimisticorganizations is significant. Where calculated t valueabout the role of IT than private sector.15.097 in table No. 4.13 is greater than the tabulated tResults of independent sample t-test for thevalue 1.960, Thus H 0 is not substantiated. This impliesfourth hypothesis are shown in the below tables. As maythat private sector is more optimistic about the role of ITbe seen, the difference in the means of 1.64 and 1.37in organizations for maximum efficiency and effectivewith the standard deviations of .45 and .34 for the publicutilization of both the human and material resources ofand private respectively on the Role of IT inthe organization.Group StatisticsNatureNMeanStd. DeviationStd. Error MeanRole of IT in Org.Public1491.6437.45367.01545Private1281.3772.37160.02302Table 4.12 : Show Group Statistics for Hypothesis No.4a. Grouping Variables: Public, Privateb. Testing Variable: Role of IT 4Hypothesis No.5: Professors, doctors andconsultants view IT differently. 4ITSum of SquaresdfMean SquareFSig.Between Groups.0262.014.240.676Within Groups11.146204.053Total11.172206Table 4.14 : Represents ANOVA Results for Hypothesis No.5a. Grouping Variables: Professor, Doctors & ITHypothesis No.6: Experience of non-ITconsultantsworkforce is negatively correlated with perceptionsb. Testing Variable: ITabout IT.15 : CorrelationHFOFTFISDUSEPRCPRBSTFOPR SFFAverage rHF10.6510.440.6110.7460.4860.4040.4090.541 0.3010.535286OF0.65110.7580.7460.8340.7320.3490.4550.632 0.6470.646429TF0.440.75810.5770.7450.6650.3340.3340.466 0.4030.550429ISD0.6110.7460.57710.7080.5060.2810.3720.607 0.4310.543USE0.7460.8340.7450.70810.7180.7190.4310.617 0.7340.700143PRC0.4860.7320.6650.5060.71810.2750.2030.264 0.5660.512143PRB0.4040.3490.3340.2810.7190.27510.2630.348 0.2710.375STF0.4090.4550.3340.3720.4310.2030.26310.232 0.3220.352429OPR0.5410.6320.4660.6070.6170.2640.3480.23210.3050.524175SFF0.3010.6470.4030.3310.7340.5560.2710.3220.305 10.536238Correlation is significant at the 0.01 level (2-tailed). (n=277) 4ModelRR. SquareR. Square (Adjusted)Estimation Std Error1.104(a).011.008.23501a. Constant Predictors, Perception about IT,Success/Perception of IT Projects.Table 4.16 : Represents Model Summary for Hypothesis No.7ANOVAModelThe sum of SquaresdfSquare of MeanFSig.1Regression.2391.2394.217.038(a)Residual21.982275.055Total22.220277a. Constant Predictors, Perception about ITb. Dependent Variable: Success/Perception of ITProjectsCoefficientsNon StandardizedStandardizedModelCoefficientsCoefficientstSig.BStd. ErrorBeta1(Constant)3.128.04569.497.000Perception about IT.057.028.5132.078.038a. Dependent Variable: Success/Perception of ITProjects 412Volume XII Issue XV Version ID D D D ) C(Global Journal of Computer Science and Technology© 2012 Global Journals Inc. (US) 4Summary of ModelModelRR. SquareR. Square (Adjusted)Estimation of Std Error1.561(a).315.310.19607a. Constant Predictors, Organization, human, contextand Technology.Table 4.19 : Represents Model Summary for Hypothesis No.8( D D D D ) CANOVAModelThe Sum of SquaresdfSquare of MeanFSig.1Regression6.99632.33261.553.000(a)Residual15.224396.038Total22.220399a. Constant Predictors, Organization, human, context& Technology.b. Dependent Variable: Success of IT ProjectsCoefficientsNon standardizedStandardizedModelCoefficientsCoefficientstSig.BStd ErrorBeta1(Constant)1.405.13710.243.000Organization.269.043.3659.653.000Human.253.029.7048.764.000Context.412.054.3729.651.000Technology.468.048.5339.782.000a. 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