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\title{Investigating the Technology Diffusion Problems in a Multi Culture Environment: A Case of Telecom Sector}
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             \author[1]{Sabahat  Mahmood}

             \author[2]{Irfan Anjum  Manarvi}

             \affil[1]{  International Islamic University Islamabad.}

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\date{\small \em Received: 8 December 2012 Accepted: 5 January 2013 Published: 15 January 2013}

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\begin{abstract}
        


Technology diffusion is an important aspect that is considered as economically important, while offering particularly large benefits to the organizations (Erik. A & Ken.G 2002). This study will explore the barriers to the diffusion of a new technology in a Telecom Sector organization. Ease of use, Job-fit, facilitating condition, training, Top management support, and project communication were found frequently used factors to investigate the usage behavior of employees of a telecom, manufacturing, engineering and government service sector industries. This study also investigates the impact of culture while diffusing a new technology in an organization.System generated real time data is administered for evaluating the employee performance after implementing the new SpeechLog software in the QAU department as well as a questionnaire based survey was administered personally on 140 employees, In response to the survey, 120 valid responses were received. The response rate was 85%. Among the respondents, 70% were male while 30% were female.

\end{abstract}


\keywords{technology diffusion, telecom industry, technology acceptance, culture.}

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\let\tabcellsep& 	 	 		 \par
Abstract -Technology diffusion is an important aspect that is considered as economically important, while offering particularly large benefits to the organizations (Erik. A \& Ken.G 2002). This study will explore the barriers to the diffusion of a new technology in a Telecom Sector organization. Ease of use, Job-fit, facilitating condition, training, Top management support, and project communication were found frequently used factors to investigate the usage behavior of employees of a telecom, manufacturing, engineering and government service sector industries. This study also investigates the impact of culture while diffusing a new technology in an organization. System generated real time data is administered for evaluating the employee performance after implementing the new SpeechLog software in the QAU department as well as a questionnaire based survey was administered personally on 140 employees, In response to the survey, 120 valid responses were received. The response rate was 85\%. Among the respondents, 70\% were male while 30\% were female.\par
The findings indicate that the emerged model over all explains 71\% variation in intention to use while ease of use job-fit training and top management support were significant factor while explaining the intention to use SpeechLog software. Mostly respondents agreed that they like the idea of using SpeechLog software and they want to adopt it. Employees say that it has improved their work performance by completing their task efficiently. This research will help the Telecom organization's Management to understand the problems faced by employees while diffusing a new technology. 
\section[{Introduction increased competitiveness, especially diffusion of new}]{Introduction increased competitiveness, especially diffusion of new}\par
The intent of this study is to report these problems in the progression of examining the role of culture during the technology diffusion in Telecom sector organization of Pakistan. The population of this study was XYZ employees of QAU department who were using new technology for call evaluation of call center department.\par
The objective of technology diffusion in any organization is to provide large benefits over time which in turn proves to be economically important. Further it involves internal reorganization of both production and management processes as well as upgrading of skills which leads to increase in economic value (Erik A \& Ken.G 2002).\par
Previous research addressed different problems in technology diffusion in a multi culture environment as well as different models has been proposed by scholars from different disciplines and studied technology diffusion and acceptance of user towards information system from different perspectives \hyperref[b0]{(Ajzen, 1991}  Technology can diffuse in multiple ways with significant variations, depending on the particular technology, across time, over space, and between different industries and enterprise types. Moreover, the effective use of diffused technologies by firms frequently requires organizational, workforce, and follow-on technical changes. It is evident from literature that there are a number of potential factors that could influence the usage of an information system. In many developing countries organizations faces problem and even failure in transferring technology into practice (Atiyyah 1989; Cuningham \& Sarayrah 1994). One common reason for its failure is the unwillingness or reluctance to change of users to accept a new technology. Developing countries come across cultural and social barriers when diffusing technology into practice.\par
task completion play's a key role in organizational performance, the users should be provided successful training to encourage the SpeechLog application usage as its training and learning are very important in successful implementation. The positive usage behavior of this software will leads to job completion on time, which improves the employee's performance. The objective of this study is to explore various problems that might be faced by the management and employees during technology diffusion. 
\section[{II.}]{II.} 
\section[{THEORETICAL FRAMEWORK}]{THEORETICAL FRAMEWORK}\par
An investigation into the past research revealed that a considerable amount of literature is there regarding technology diffusion problems while diffusing a new technology in an organization. A set of variables have been explored to study the intention to use of employees. It will provide the information as to which variable is more influential in the usage of SpeechLog application by the employees of telecom sector Pakistan. The name of the telecom organization is kept confidential in the study and don't mentioned here due to the organizational policies. This research is expected to contribute to the understanding for management the challenges in in build technology diffusion towards use of SpeechLog application; it will calculate the overall software performance through real time system generated data. The second part of the research is also important in providing information about the employee's intention to use SpeechLog application and the problem faced by the employees while using a new technology. Based on the following research a framework is emerged as shown in Figure \hyperref[fig_1]{1}. In this research model, Ease of use, Job-Fit, Facilitating condition, training, top management support, project communication and culture are the independent variables which have their effect on the intention to use SpeechLog software (dependent variable). In order to achieve the research objective, following research hypothesis are proposed.  
\section[{Methods}]{Methods}\par
The real time system generated data was collected for the 100 days for calculating the SpeechLog software performance. The call targets assigned by management and evaluated through SpeechLog software has been analyzed as well as Number of queries made through different departments and answered through SpeechLog software of QAU department has been analyzed so as to calculate the overall performance increase of the QAU department. 
\section[{a) Respondents}]{a) Respondents}\par
Questionnaire was distributed among 140 employees working in QAU department of telecom organization located in Islamabad Pakistan. In response, 120 questionnaires were returned. Data of 120 completely filled questionnaire were entered in statistical Package for Social Sciences (SPSS) for analysis. The response rate was 85\%. The response shows that the sample represented CCE's, Supervisor, Assistant Managers and manager. A pilot test was conducted to verify various dimensions of the questionnaire such as ease of completing the questionnaire, language used, and appropriateness of questions with relevance to usage behavior. Fifteen SpeechLog users working in QAU department of XYZ Company were asked to fill in the questionnaire. Feedback was obtained, in result of the pilot study minor changes in statements of the final survey tool were incorporated. 
\section[{b) Measure}]{b) Measure}\par
The questionnaire used in this research was adapted from the studies conducted on intention to use  Results and Data Analysisa) System Generated Data \& it's Analysis\par
To explain any phenomenon we seek to explain it by collecting data from the real world and then using data to draw conclusions. In this study we have taken the data of about 100 days of SpeechLog Application, it contained the details regarding queries made and the queries answered through SpeechLog as well as the assigned target done by the agents. The SpeechLog performance of first \& second week for Number of queries made and answered is shown in figure \hyperref[fig_3]{2} \& 3. It Week (For Queries) explain how SpeechLog Application will help the QAU department to answer the queries made as well as by answering some additional queries it will increase overall performance of the organization.\par
The assigned call evaluation target is also analyzed, data for the first Week is shown in figure \hyperref[fig_5]{4}, it explain how SpeechLog Application will help the agents to complete their target on time as well as by providing help through completing the additional call target will in turn increase overall efficiency of the department. Week (For Call Target)\par
The Figure  {\ref 5} shows the call evaluation target done through SpeechLog software for the second week. 
\section[{b) Reliability Statistics}]{b) Reliability Statistics}\par
To confirm the reliability of the questionnaire, cronbach's Alpha reliability statistics analysis was conducted. In statistics the cronbach's Alpha value greater than .5 is considered to be reliable scale.\par
Table  {\ref 1} shows the reliability statistics of the questionnaire. The value .947 shows that the scale used in the questionnaire is highly reliable. In order to explore the SpeechLog user responses with respect to gender. A frequency statistics was made. the respondents. Out of 120 responses, 70\% were male and 30\% were female.\par
Figure  {\ref 7} shows variation in age of the respondents. Out of 120 respondents, majority lies in 31-40 age group (N=102), while seventeen are in 20-30 age group, and 1 in 41-50 age group. Figure  {\ref 9} represent the SpeechLog usage experience possessed by the employees. Mostly respondents (N=50) had more than more than 2 years of experience, 37 having 1-2 years of experience while only 33 have less than one year experience in use of SpeechLog software.\par
Figure \hyperref[fig_1]{10} represent the respondent's distribution according to their education. Mostly respondents (N=73) had master degree qualification, 44 having bachelor degree qualification while only 3 have MS degree qualification.   Figure \hyperref[fig_1]{11} shows the respondent distribution according to ethnic origin. Mostly respondents (N=74) had Punjabi origin, 30 respondents have Muhajir origin, while 12 have Pashtun origin and only 4 have Sindhi origin.  
\section[{d) Hypotheses result and analysis}]{d) Hypotheses result and analysis}\par
In table 2 the R2 (.72) value shows that the independent variable explains the 71\% variation in the intention to use SpeechLog software. Here we can say that our model best fits and it explain significant variation in the intention to use.\par
Table \hyperref[tab_3]{3} shows the beta and significance value of each independent variable in regression model.\par
The significance value (p=.000) in table \hyperref[tab_3]{3} shows that ease of use and Job-fit is significant in measuring the intention to use. The beta value, B=.322 of Ease of use show that ease of use contribute to .322 variation the intention to use.   The value (B= .505) shows that the variable job-fit strongest predictor in measuring the behavior intention. Here we will accept H1 and H2.\par
Table \hyperref[tab_3]{3} shows the regression analysis, the p value (p>.005) shows that facilitating condition is not a significant variable in measuring the intention to use. Hence we reject H3.\par
The p value (p=.003) in table \hyperref[tab_3]{3} shows that training is a significant variable in measuring intention to use. Here we accept H4.\par
In table \hyperref[tab_3]{3}, Top management support is a significant variable in measuring intention to use. Here we accept H5.\par
The p value (p=.494) in table \hyperref[tab_3]{3} shows that the project communication is not a significant variable in measuring intention to use. Here we reject H6.\par
In Table \hyperref[tab_3]{3}, the p value (p>.005) that culture is not a significant variable in measuring the behavior intention. Here we reject H7.\par
V. 
\section[{Findings}]{Findings}\par
The results of correlation analysis shows that Ease of use, Job-fit, Facilitating condition and training are strongly correlated with the intention to use SpeechLog software while top management support, project communication and culture have medium level correlation with intention to use SpeechLog software. The R square value (.72) shows.\par
That the overall independent variable explains 71\% variation in the intention to use SpeechLog software.\par
Here we can say that the model best fits and it explain significant variation in the intention.\par
The p value of culture (p=.925) shows insignificant variable in measuring the intention to use.\par
The p value (p=.360) in the regression analysis of the facilitating condition shows that this is not a significant variable in measuring the intention to use.\par
While exploring all variables individually, the variable ease of use is significant in measuring the intention to use. The beat value, ?=.322, show that ease of use is stronger predictor of intention to use. Job-fit is significant while explaining intention to Use SpeechLog software. The negative beta and t value indicate that this variable is not positively associated with the intention to use.\par
The regression analysis shows that the Job-fit is a significant variable while project communication is not a significant variable. Top management support and training were also found the significant contributor toward measuring intention to use toward use of SpeechLog software.\par
The overall findings analyzed from the questionnaire 'comments part' regarding problem faced while using this SpeechLog software by the employees are resistance to change, proper resources are not available, processing speed is low due to the unavailability of proper resources, Frequent training programs are required, and employee's believe that SpeechLog software is a valuable purchase and company should adopt it. The findings indicate that the culture don't have any impact on intention to use of SpeechLog software.\par
The findings from the analysis of the system generated real time data indicate that the SpeechLog software efficiently complete the task on time. 
\section[{VI.}]{VI.} 
\section[{Conclusions}]{Conclusions}\par
This study was centered on SpeechLog software intention to use and the problem faced while diffusing it. The aim of this study was to investigate factors affecting the employee intention towards use of SpeechLog software and its impact on the overall performance of the organization as well as to explore various problems that might be faced by the management and employees during technology diffusion among different cultures.\par
The first part of the study explores the literature related to technology diffusion problems faced while diffusing technology among different cultures. Use of different models and theories of intension to use of technology in different sectors especially in the telecom sector.\par
During the exploration of literature, many factors were identified for measuring the intention to use towards use of a new technology. Based on the findings a theoretical model is emerged. The population of this study was telecom organizations employees who were using SpeechLog software in QAU department of the company. The sample size of 140 was selected, however, 120 out of 140 selected participants responded. A questionnaire based survey was administered personally on 140 employees who were using SpeechLog software. In response to the survey, 120 valid responses were received. The response rate was 85\%. Among the respondents 70\% were male while 30 \% were female, the findings of this study indicate that majority of the respondents agreed that they like to use SpeechLog software. They want to become professional in SpeechLog software use and intend to use it in future. Most of the respondents think that it is a valuable purchase and company should adopt it. This research will help the management to understand the factors responsible for the intention to use SpeechLog software as well as to find out the problems faced by the employees while using new software.\par
VII. 
\section[{Recommendations}]{Recommendations}\par
Based on the findings of this research, the following recommendations are given to increase intention to use SpeechLog software as well as overcoming the problem faced by the employees while using SpeechLog software.\par
i. There is need to ensure the employees that by using SpeechLog software they will become a valuable assets to the organization by completing their tasks efficiently. ii. The employees should be provided with additional bonuses if they are performing well with the use of this new technology. iii. Frequent meetings should be planned to find out the problems faced by the employees. iv. The technical support should be provided to employees. v. The senior management should also frequently use the SpeechLog software to evaluate its effectiveness. vi. Frequent training programs should be planned to improve the understanding of the software features. vii. Top management should be supporting and should communicate well in time about the implementation of the new software. viii. The senior management should encourage SpeechLog usage. ix. Organization should provide necessary resources to use SpeechLog software.\par
VIII. 
\section[{Future Research Direction}]{Future Research Direction}\par
Current research explains the 72\% variation in the intention of use of the employees. The 29\% portion is unmeasured. There is a need of future research which explores the further variables to measure the leftover portion which was not measured in this research. This research could be helpful for other Telecom sector organization to study the problems faced while diffusing a new technology, it should be carried out in other telecom sector organizations as well as it could also be applied to other departments of the same company. \begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-2.png}
\caption{\label{fig_0}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{1}\includegraphics[]{image-3.png}
\caption{\label{fig_1}Figure 1 :}\end{figure}
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\noindent\textbf{}\includegraphics[]{image-4.png}
\caption{\label{fig_2}C}\end{figure}
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\noindent\textbf{2}\includegraphics[]{image-5.png}
\caption{\label{fig_3}Figure 2 :}\end{figure}
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\noindent\textbf{3}\includegraphics[]{image-6.png}
\caption{\label{fig_4}Figure 3 :}\end{figure}
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\noindent\textbf{4}\includegraphics[]{image-7.png}
\caption{\label{fig_5}Figure 4 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{15}\includegraphics[]{image-8.png}
\caption{\label{fig_6}1 Figure 5 :}\end{figure}
      \begin{figure}[htbp]
\noindent\textbf{} \par 
\begin{longtable}{}
\end{longtable} \par
 
\caption{\label{tab_0}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2} \par 
\begin{longtable}{P{0.068\textwidth}P{0.056666666666666664\textwidth}P{0.136\textwidth}P{0.23800000000000002\textwidth}P{0.35133333333333333\textwidth}}
Model\tabcellsep R\tabcellsep R Square\tabcellsep Adjusted R square\tabcellsep Std Error of the Estimate\\
1\tabcellsep .833\tabcellsep .712\tabcellsep .703\tabcellsep .38816\end{longtable} \par
 
\caption{\label{tab_2}Table 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{3} \par 
\begin{longtable}{}
\end{longtable} \par
 
\caption{\label{tab_3}Table 3 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{} \par 
\begin{longtable}{P{0.1819298245614035\textwidth}P{0.014912280701754385\textwidth}P{0.3549122807017544\textwidth}P{0.09543859649122807\textwidth}P{0.09842105263157895\textwidth}P{0.1043859649122807\textwidth}}
Dependent Variables\tabcellsep R2\tabcellsep Independent variables\tabcellsep Beta\tabcellsep T\tabcellsep Sig\\
Intention to Use\tabcellsep .82\tabcellsep Ease of use\tabcellsep .322\tabcellsep 4.602\tabcellsep .000 *\\
\tabcellsep \tabcellsep Job-fit\tabcellsep .505\tabcellsep 6.873\tabcellsep .000 *\\
\tabcellsep \tabcellsep Facilitating Condition\tabcellsep .063\tabcellsep .917\tabcellsep .360\\
\tabcellsep \tabcellsep Training\tabcellsep .172\tabcellsep 2.967\tabcellsep .003\\
\tabcellsep \tabcellsep Top management support\tabcellsep .189\tabcellsep 2.967\tabcellsep .003\\
\tabcellsep \tabcellsep Project Communication\tabcellsep .036\tabcellsep .686\tabcellsep .494\\
013\tabcellsep \tabcellsep Culture\tabcellsep .007\tabcellsep .094\tabcellsep .925\\
2\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
Year\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
D D D D D D D D )\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
(\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_4}C}\end{figure}
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