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\title{The Adoption of E-CRM System in Service Firms: Creation of a Measurement Scale}
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             \author[1]{Sameh  Tebourbi}

             \author[2]{Romdhane  Khemakhem}

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\date{\small \em Received: 12 February 2021 Accepted: 1 March 2021 Published: 15 March 2021}

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\begin{abstract}
        


This paper aimed to develop scales to measure the adoption of the e-CRM systems in service firms. A qualitative study consists of 10 semi-structured interviews to explore the intention of marketers to adopt the e-CRM system; we opted for an inductive approach for the generation of items, since the scales in the literature are not adapted to the context of this study.We chose six experts to take part in the survey; data collection was carried out through interviews; these experts judged the relevance of each of the 27 items generated.During the 6 interviews, we noted several relevant impressions and remarks from the experts.

\end{abstract}


\keywords{measurement scale, testability of e-CRM system, observability of e-CRM system and service firms.}

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\let\tabcellsep& 	 	 		 
\section[{Introduction}]{Introduction}\par
dopting information technology by individuals and organizations is part of the information systems (IS) implementation process, an area of research that has received considerable attention in recent years \hyperref[b17]{(Zabadi, 2016)}. However, understanding the successful implementation of information technology remains one of the major challenges facing the IS field (Princewill \hyperref[b15]{Lekara, 2019)}, and research efforts have been mixed and inconclusive.\par
It should be noted that the poor development of the theory and the inadequate measurement of constructs have turned research on IS into a wide variety A of subjects (George M, Florida I Richard D, Paul Clay Fort Lewis Coll, 2017) (It is also clear that well-defined constructs are based on theory, and the operationalization of these constructs by measurements with high degrees of validity and reliability is a necessary condition. Recently, many researchers have started using theories of diffusion of innovation \hyperref[b16]{(Rogers, 2003)} to study implementation problems. One of the most cited theories on perceived characteristics in literature which, in a survey of several innovation studies, identified five characteristics of an innovation that affect the rate of diffusion of an innovation. They are the relative advantage, compatibility, complexity, observability and, testability.\par
We proposed to test two characteristics namely: testability and, observability of e-CRM system by managers in service companies. Despite the importance of the perceived characteristics in dissemination research, documentary research indicated that most of the existing instruments designed to exploit these characteristics lacked reliability and validity.\par
The main objective of this research was to develop scales to measure the observability and testability of the e-CRM system in service firms. However, we notice that all of the scales developed are generally applicable to various innovations, in particular to other types of information technology. Therefore, items apply only to the use of the e-CRM system have been excluded. It should also be noted that, although some researchers study innovations at the organizational level and responses at the individual level. 
\section[{II. Theoretical Research Framework}]{II. Theoretical Research Framework}\par
The theory used to deal with this problem is diffusion of innovations \hyperref[b16]{(Rogers, 2003)}.\par
Although, this theory will be applied to Innovation Technology IT products like Java language (used in network or hypertext environments) or technologies, like software engineering tools. The Theory of Diffusion of Innovation of \hyperref[b16]{Rogers (2003)} is proposed to help the integration of technologies in companies.\par
The integration goals are at the same time the adoption of the technology with the users, the implementation and, the institutionalization of the use. perceptions by individuals of five attributes of innovation that influence the individual adoption process, namely the relative advantage, compatibility, complexity, divisibility and visibility of the innovation \hyperref[b16]{(Rogers, 2003)}. The adoption rate of an innovation is positively linked to the relative advantage perceived, compatibility, test possibility and observability, and negatively related to the perceived complexity of the innovation.\par
We proposed to test two characteristics, namely: testability and observability of e-CRM system by managers in service companies.\par
CRM is a business management tool focused initially on the automation of the sales force  {\ref (Buttle, 2004}) and which has evolved towards a global concept of customer relationship management whose ultimate goal is customer loyalty and thus the improvement of the company's results (Gil-Gomez et al., 2020).\par
Testability " is the degree to which an innovation can be tested on a limited field before it is used" (Rogers2003). "A new idea that you can try before you adopt it is generally quicker to adopt than others. This possibility would allow the individual or any other adoption unit to better understand how innovation works. Thus, an innovation that can be tested beforehand poses less risk for the individual or the organization that intends to adopt it" \hyperref[b16]{(Rogers, 2003)}.\par
The first research relating to the diffusion of innovation considers innovation to be unchangeable over time. However, testing an innovation can allow an individual to "customize" or personalize it to give birth to an innovation more suited to his situation. This is what \hyperref[b16]{Rogers (2003)} calls "reinvention." Here, we admit that an innovation can be modified or changed following its adoption and implementation process.\par
Observability "is the degree to which the results of innovation are visible. \hyperref[b16]{(Rogers, 2003)}, The more visible the results, the more rapid its adoption. At this level, the example given by \hyperref[b16]{Rogers (2003)} concerns PC technology with its two components, namely hardware and software.\par
The hardware part includes the electronic elements (visible); on the other hand, the software part includes the program for the PC system. The software part of technological innovation is not observable. 
\section[{III.}]{III.} 
\section[{Qualitative Research}]{Qualitative Research}\par
To clarify and complete the identification of the adoption characteristics of innovations in information technology, specifically the testability and observability of the e-CRM system, we conducted 10 semi-structured interviews with managers of service firms.\par
The interview guide, which includes a total of ten questions, was designed in two main parts. The first part is regrouping general questions. The second part of the questions related to the perceived characteristics of adoption of the "e-CRM system" innovation, namely testability and observability concerning the diffusion theory of innovation of \hyperref[b16]{(Rogers, 2003)} Appendix1.\par
We stopped the interviews when we found that the last interview did not provide any additional information (Gavard-Perret et al., 2012). The interview lasted on average 20 minutes, is administered, face to face.  
\section[{Content Analysis}]{Content Analysis}\par
We chose NVivo software, a tool used to analyze all kinds of qualitative data.\par
The content analysis process is inherent in respecting a certain approach described by \hyperref[b10]{Giannelloni and Vernette (2001)}.\par
10 semi-structured interviews were recorded and transcribed, thus constituting the verbatims. The data were processed according to the thematic content analysis method. It is a question of dividing the speech of the interviewees into units of meaning to bring out the underlying themes \hyperref[b3]{(Evrard et al 2009)}. Thus, two themes appeared through the various interviews:\par
The testability of the e-CRM system theme and the observability of the e-CRM system theme. Then, we proceeded to the codification of the transcriptions of the different categories of the themes. Following the coding of the interviews, we established the summary grid (appendix2) which integrates the details of the speech of the participants in the qualitative survey. Concerning the thematic analysis, first, we carried out the vertical analysis and, secondly, we carried out the horizontal analysis. This analysis is qualified by these authors as\par
The diffusion theory of innovations has modeled the rate of adoption of innovation according to the The penultimate step is to determine the relative weight for each dimension.\par
Regarding the dimension relating to "testability" we note through the qualitative analysis that out of the ten interviews carried out, all the directors affirm that they had tested the e-CRM system before adopting it.\par
Ultimately and given the comments collected, we consider that the variable "testability" is one factor to be taken into account in the adoption of the e-CRM system by service companies.\par
Concerning the dimension relating to "observability" through qualitative analysis, out of the ten interviews carried out, 9 Marketers affirm that observability must be considered a factor of the e-CRM adoption.\par
To the question: "In your opinion, are the e-CRM system and its results visible and observable? Explain". The STB Customer Manager replied: "The system is not very visible in my organization".\par
And do you think this influenced your company's decision to adopt this innovation? "Yes, of course ".\par
The sales consultant, Ooreedoo "saw the results of the adoption of the e-CRM system in information traffic speed". Observability has a very strong weight as a factor of adoption of the e-CRM system in service firms. 
\section[{a) The synthesis reports}]{a) The synthesis reports}\par
This step allowed us to generate the items of the measurement scale for the adoption of the e-CRM system. It will be the subject of the following paragraph. The first, step in the process of developing a new measuring instrument is "specification of the domain construct" (in the words of Churchill 1979) Mckenzie and, al (2011). 
\section[{c) Content validity}]{c) Content validity}\par
Our choice is based on the method of Law she (1975), who proposed a content validity ratio (CVR), use to measure the degree of agreement between the experts on the relevance of the items. 
\section[{d) The expert population}]{d) The expert population}\par
In our research, we have chosen 6 teachers and computer scientists to have theoretical knowledge and skills in CRM. 
\section[{e) Collection procedure}]{e) Collection procedure}\par
For our survey of experts, data collection was carried out through interviews and was administered by "electronic mail" (appendix3).\par
The expert was first invited to assess the relevance of each item (not necessary, important but not essential, essential). The objective of this evaluation is to verify the relevance of each item by calculating the CVR \hyperref[b13]{(Lawshe 1975)}.\par
Each expert also had the option of adding items that did not appear in the proposed battery of items. He also had the opportunity to suggest a reformulation of the items he found ambiguous. The CVR of each item is obtained using the following formula from Lawshe (1975, p. 567): CVR = (ne-N / 2) / N / 2;\par
Given when we called on 6 experts (N / 2 = 3) the CVR formula will be as follows: CVR = (ne-3) / 3\par
With ne: number of experts who declared the item to be "essential" and N the total number of experts. The CVR is between -1 and + 1.\par
Furthermore, \hyperref[b13]{Lawshe (1975)} established minimum CVR values according to the size of the panel. The Table  {\ref below} provides the minimum CVR values required to retain an item.  1. I have a lot of opportunities to test various e-CRM system applications before adopting them to see their usefulness and to test the crucial components of the system. 1 1 2. I have the opportunity to use the e-CRM system as an experiment to better understand the operating mode to keep the reliability of the system. 1 2\par
3. I tried the e-CRM system before adopting it within the company. 1 3 
\section[{b) Generation of items, content analysis and purification of the "e-CRM system adoption" scale i. Generation of items}]{b) Generation of items, content analysis and purification of the "e-CRM system adoption" scale i. Generation of items}\par
The generation of items is done using literature review and qualitative interviews and intuition \hyperref[b2]{(Churchill, 1979)}. whose object is for our research the generation of items for the construct "adoption of system e-CRM". 5. I tested the e -CRM system before implementing it to be able to master its tools and functionality. 1 5\par
6. I am considering a trial period to adapt the system to our company and our working methods. 1 6\par
7. testing the e-CRM system avoids the risk of dysfunction during adoption. 0.66 8. Testing the system before setting it up encourages me to adopt it. 0.33 9. I don't make much effort to try the e-CRM system. 0.66 10. I used the system during its implementation within the company without the test before. 1 7\par
11. There are many people in my organization who can help i try out the various applications of the system. 0.66\par
Observability of e -CRM system 1. I have often seen other users of the e-CRM system. 1 1 2. In my organization, several members have the e-CRM system. 1 2\par
3. I saw the e-CRM system used outside my company. 1 3 4. The system is not very visible in my organization. 0.33 5. I saw the e-CRM system used in my business.\par
-0.66 6. I have not seen other people using the e-CRM system in my department. 0.66 7. I have observed other people in my department using the e-CRM system. 1 8. I have seen sales advisers on most computers. 0\par
9. The e-CRM system tries to create a unique vision of each customer to discover the sales opportunities, improves the competitive position. 1\par
10. The e-CRM system enables customer loyalty. 1\par
11. The e-CRM system offers better customer service. 1\par
12. The e-CRM system allows sellers to be reactive. 0.33 \hyperref[b12]{13}. The e-CRM system allows sellers to be more aware. 1\par
14. The e-CRM system meets the real needs for customers 1\par
15. The e-CRM system, allows the speed of information flow. 1 10 16. When adopting the e-CRM system there are always updates to customer data. 1 11\par
Our panel comprises 6 experts, so all items with a CVR greater than or equal to 0.99 will be kept, so they have good content validity and, the others will be rejected. The CVR analysis results led to changes in the items (which went from 27 to 18). During the 6 interviews, we noted several relevant impressions and remarks from the experts. Some reformulations have been proposed by the experts to simplify, specify or present in a more concrete and relevant way the content targeted by each indicator. 
\section[{Global Journal of Management and Business Research}]{Global Journal of Management and Business Research}\par
Volume XXI Issue II Version I Year 2021 ( ) E © 2021 Global Journals 
\section[{Items Reformulation}]{Items Reformulation}\par
Testability of du e-CRM system Testability of the e-CRM system I have many opportunities to test various applications of the e-CRM system before adopting it to see its usefulness and to test the crucial components of the system.\par
Testing the e-CRM system shows its usefulness.\par
I have the opportunity to use the e-CRM system as an experiment to better understand the Using the e-CRM system allows me to understand its operating mode.\par
Operating mode in order to keep the reliability of the system. I tested the e -CRM system before implementing it to be able to master its tools and functionalities.\par
Testing the e-CRM system allows you to master its tools and functionalities.\par
I am considering a trial period in order to adapt the system to our company and to our working methods.\par
A trial period is essential. I used the system during its implementation within the company without testing it before. I do not have the possibility to try different applications on the e-CRM system.\par
Observability of e-CRM system Observability of the e-CRM system I have not seen other people who use the e-CRM system in my department.\par
The e-CRM system is not yet adopted in my department.\par
The e-CRM system tries to create a unique vision for each customer to discover the sales opportunities, improves the competitive position.\par
The e-CRM system tries to create a unique vision for each client.\par
Regarding item 15, the term information is replaced by the term data.\par
Regarding the addition of items by the experts, item 10, where there is the question of loyalty, has been divided into six items (10a to 10f) so as not to be limited to loyalty, which is only one phase among others in the CRM process (there is also acquisition, re-acquisition, identification, evaluation, etc.). 10b. The e-CRM system makes it possible to assess the customer's profitability and to determine its value.\par
10c. The e-CRM system identifies customers and describes their profiles.\par
10d. The e-CRM system allows better conversion of prospects into customers. 10e. The. e-CRM system helps to win back lost customers.\par
10f. The e-CRM system makes it possible to assess the level of customer satisfaction.\par
We noted that only one expert among the 6 forming the panel suggested adding these items 10b to 10 f. However, these items are not added since they are not recommended by the majority of experts. Item 16 relating to the observability of the e-CRM system is divided into two items.\par
The majority of experts suggested adding items 16a and 16b to distinguish data collection and processing.  When adopting the e-CRM system there are always updates to customer data. 16 a. The e-CRM system allows better collection of customer data. 16 b. The e-CRM system allows better use of customer data. 
\section[{f) Purification of the "intention to adopt e-CRM system" scale}]{f) Purification of the "intention to adopt e-CRM system" scale}\par
Once the content validity for the development of the measuring instrument has been designed, a testpilot will be carried out. The objective of the pilot test is to verify the reliability of the items (Dwivedi et al., 2010).\par
For this, factorial analyzes are considered necessary in order to identify the main factors explaining the results obtained, to eliminate redundant items and thus, to reduce the number of items  {\ref (DeVellis, 2003)}.\par
The participant According to \hyperref[b2]{Churchill (1979)}, we used two independent samples to conduct the "exploratory factorial analysis" AFE and the "confirmatory factorial analysis" AFC within the framework of the development of the new measuring instrument of "adoption of the system e -CRM ".\par
The two samples come from the same survey, will be a question of dividing the initial sample into two sub-samples randomly then designating a first subsample for the AFE and a second sub-sample for the AFC. Since our questionnaire as a whole was not perceived as long, we conducted a single survey with a global sample of 340 companies and we extracted two independent subsamples: a subsample of 240 observations for the 'AFE and a subsample of 100 observations for the AFC.\par
The procedure Regarding our study, we have chosen to administer our questionnaire face to face and by e-mail to managers, directors, customer managers, sales managers or marketing managers in companies mainly in the service sector.\par
The questionnaire, on the instrument of intention to adopt electronic customer relationship management "e-CRM" (containing 19 items) and socio-demographic questions. 
\section[{g) Description of the sample}]{g) Description of the sample}\par
The questionnaire (appendix 4) was collected from a sample of 240 managers from various service companies. The characteristics of this sample are presented in the table below: ( )E © 2021 Global Journals V.\par
Exploratory Factor Analysis AFE of the measurement scale in development phase: "adoption of e-CRM system".\par
As recommended by \hyperref[b2]{Churchill (1979)}, the development of a new measuring instrument requires the completing of an AFE and an AFC. In the context of our work, it is rather a question of identifying the latent structure or the factors of "intention to adopt an e-CRM system". We will then use the AFP method.\par
During the introduction of the 19 items for the AFE, the KMO index displays a high value (0.73), the Chi 2 of the Bartlett test (of value equal to 2260.9) displays zero significance and the determinant of the matrix correlation is different from 0 thus justifying the usefulness of using factor analysis.\par
For the purification of the measurement scale, we started by eliminating the item with the lowest commonality of less than 0.4, namely the item T3 (0.068).\par
The analysis was restarted without the item and the new values of the communities re-examined. Each time, the item with the lowest community below 0.4 was eliminated until all the remaining indicators had acceptable communities.  
\section[{h) Identification of factors}]{h) Identification of factors}\par
At the 12th step in the scale cleaning phase, the 8 remaining items displayed satisfactory commonalities (greater than 0.4). The factorial contributions after oblimin rotation of 8 items were therefore analyzed. These items represent three factors with eigenvalues greater than 1. ( )E © 2021 Global Journals\par
Confirmatory factor analysis of the measurement scale "Adoption of the e-CRM system" We choose the smart PLS approach, the criteria, which led us to opt for this approach relate to the research objective which is exploratory in nature and the reduced sample size which is 100 units. The stages of the analysis through the PLS approach According to Hulland (1999), evaluating PLS model involves the careful examination of three main methodological elements, namely, determining the nature of the relationships between measures and constructs, evaluating reliability and the validity of the measurements and the evaluation of the final model. In our work, the relationships between constructs and their measures are reflexive. 
\section[{i) Estimation of the measurement model}]{i) Estimation of the measurement model}\par
The measurement model specifies the relationships between the latent variables and their observed indicators. This model is evaluated based on the reliability of the internal coherence, the convergent validity and the discriminant validity of the measures of the constructs.\par
The results of the confirmatory factor analysis. The reliability of the constructions PLS software provides us with values for composite reliability. \hyperref[b12]{Hair et al. (2014)} suggest that each of these values must be greater than 0.7. The composite reliability values for the constructs from our research are all greater than 0.7.   {\ref 2014}), this reliability is verified when the factorial contributions of the constructs (outer loading) are each greater than 0.5 and are significant. The results, relating to the indicators of our model are satisfactory about this condition. 
\section[{k) The validity of constructs}]{k) The validity of constructs}\par
To check the validity, we are basing ourselves on the one hand on the convergent validity test, which is based on the examination of the correlations (loading) of the measurements with their respective constructs and, on the other hand, on the discriminant validity test, which represents l extent to which the measures of one construct differ from the measures of another construct in the model (Fernandez, 2012).\par
To test convergent validity, we refer to the approach of Forner and Larcker (1981) and that of \hyperref[b12]{Hair et al. (2014)}. According to Forner and Larcker (1981), the convergent validity is verified when the value of the "extracted average variance or VME" of the construct is greater than 0.5. Concerning our work, the values of the VMEs provided by the PLS software are illustrated in the following table: The convergent validity is verified. Furthermore, and concerning the discriminant validity test, we refer to the approach of Forner and Larcker  {\ref (1980)}, that of \hyperref[b1]{Chin (1998)} and that used by \hyperref[b6]{Garson (2016)}. The verification of this validity is illustrated in table 15. The average variance extracted from the construct is greater than the square of the correlations of this construct with the other constructs.  
\section[{Conclusion}]{Conclusion}\par
The objective of this research is to develop a valid and reliable scale to measure the observability and testability of the e-CRM system, in service companies. A qualitative study by 10 semi-structured interviews to explore the intention of managers to adopt in the face of the testability and observability of the e-CRM system. The measurement scale was created following the paradigm of \hyperref[b2]{Churchill (1979)}   {\ref McKenzie et al. 2011}, for this, factor analyzes are considered necessary in order to identify the main factors explaining the results obtained.\par
Our research brings many contributions, creating an instrument to measure various perceptions of the use of the e-CRM system by marketers in service firms. The scale development method offers a high degree of confidence in their content and their construct validity. The result is a sparse instrument of 8 items, comprising 3 dimensions, all with acceptable levels of reliability. This instrument can now be used to study how perceptions affect the actual use of information technology by individuals. The development process also made it possible to clarify and refine certain definitions of the different concepts. The development stages showed that observability as originally defined by Rogers seemed to exploit two distinct constructions. Result Demonstration and visibility.\par
Another contribution is the use of TDI models as the basis for this study. Indeed, the literature shows that the TDI model of \hyperref[b16]{Rogers (2003)} is more complete than the other models that have tried to explain the adoption of technologies. However, no study has been examined on the TDI about the e-CRM. Rogers pointed out the need to test this model in other contexts to improve and generalize the validity of this model in various contexts and for different technologies. Therefore, the results of this study lead to enriching the conclusions of studies based on this model. Our work allowed us to test two perceived characteristics of innovation inspired by the TDI innovation diffusion theory \hyperref[b16]{(Rogers, 2003)}, namely the testability and observability of the e -CRM system in a new context to confirm its validity. As a future research path, we plan to test the set of perceived characteristics of a technological innovation. 
\section[{Interview Guide}]{Interview Guide}\par
Introductory phase: To get started, can you tell us: ? For how many years has your business existed? ? What position do you currently hold in the company? 
\section[{Centering phase}]{Centering phase}\par
Competition is the main factor propelling the principle of loyalty and the development of lasting relationships with customers. Indeed, it becomes imperative for a company to know how to anticipate customer needs as well as to develop personalized offers.\par
This through increasingly sophisticated data collection and processing programs, including customer relationship management. I would like you to talk about your relationship with your customers and the various problems encountered? ? What can we expect from a relationship with the client? ? Today we are talking more and more about electronic customer relationship management systems. Does the exploitation of electronic CRM applications create expectations by the manager? ? Can you tell us about the advantages of this system?\par
Deepening phase a) The testability of the electronic customer relationship management system 1. Do you have the opportunity to test the e-CRM system before adopting it? 2. If yes? How? 'Or' What? 3. Do you think this influenced your company's decision to adopt this innovation?\par
b) Observability of the e-CRM system 1. In your opinion, is the e-CRM system and its results visible and observable in the organization? 2. Explain. 3. Are the adoption results of this system observable in the company?\par
Before ending this interview, do you have anything to add?Category Interview1 Interview2 Interview3\textbf{Interview4}\par
Topics: The t the e-CRM system\par
Testing the e-CRM system I have the opportunity to use the e-CRM system as an experiment to better understand the mode of operation in order to keep the reliability of the system.\par
I tried the e-CRM system before adopting it in the company.\par
Testing the e-CRM system allows me to use it correctly.\par
I tested the e -CRM system before implementing it so that I could master its tools and functionalities. 
\section[{Interview5}]{Interview5}\par
Interview6 Interview7 Interview8 
\section[{Conclusion}]{Conclusion}\par
Appendix2: Summary Grid  
\section[{Interview9 Interview10}]{Interview9 Interview10}\par
Testing the e-CRM system I have used the system during its implementation within the company There are a lot of people in my organization who can help me try out the various applications on the system. without testing it before. 
\section[{Interview1 Interview2 Interview3 Interview4}]{Interview1 Interview2 Interview3 Interview4}\par
The observability of the e-CRM system Interview5 Interview6 Interview7 Interview8\par
The e-CRM system allows sellers to be responsive. 
\section[{Interview9 Interview10}]{Interview9 Interview10}\par
Appendix 3: Directory Guide\par
The adoption of the e-CRM system is defined as the process of acceptance of the e -CRM system by a decision-making unit (an individual or a firm) evolving in a particular social system.\par
Adoption is the use of new technology on an ongoing basis. The theory of diffusion of innovations has modeled the rate of adoption of an innovation according to the perceptions by individuals of five attributes of the innovation which influence the process of individual adoption namely the relative advantage, compatibility, complexity, divisibility and visibility of innovation \hyperref[b16]{(Rogers, 2003)}.\par
We will test two dimensions namely the testability and the observability of the e-CRM system. Items related to each of the two dimensions were generated which must be examined in depth by experts in the field. This is where your opinion is essential.\par
? Please assess the relevance of each item and specify whether it is "irrelevant", "importantbut not essential" or "essential"\par
? Suggest a rewording for the item if you think it is imprecise.\par
? Suggest other items that you think are capable of emphasizing the measurement tool. Your responses remain highly confidential and anonymous.\par
I have often seen other users of the e-CRM system.\par
I have observed other people in my department who use the e-CRM system.\par
The e-CRM system tries to create a unique view of each customer to discover sales opportunities, improves the competitive position.\par
The e-CRM system helps to build customer loyalty.\par
The e-CRM system helps meet the real needs of customers.\par
The e-CRM system allows salespeople to be more aware. 
\section[{When}]{When}\par
adopting the e-CRM system there are always updates of customer data.  
\section[{Irrelevant}]{Irrelevant} 
\section[{Important but not essential Essential}]{Important but not essential Essential}\par
Testability of e-CRM system \begin{figure}[htbp]
\noindent\textbf{1} \par 
\begin{longtable}{P{0.5751063829787234\textwidth}P{0.2748936170212766\textwidth}}
Three Business Consultants\tabcellsep Attijari Bank\\
one Customer Officer\tabcellsep Housing Bank\\
One branch manager\tabcellsep Housing Bank\\
Un Second agent\tabcellsep STB bank\\
TPE Back Office Bank Manager\tabcellsep All baraka bank\\
One Customer Manager\tabcellsep STB bank\\
wo Ooreedoo Sales Consultants\tabcellsep Ooreedoo\\
IV.\tabcellsep \end{longtable} \par
 
\caption{\label{tab_0}Table 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2} \par 
\begin{longtable}{P{0.29050632911392404\textwidth}P{0.3227848101265823\textwidth}P{0.021518987341772152\textwidth}P{0.021518987341772152\textwidth}P{0.021518987341772152\textwidth}P{0.021518987341772152\textwidth}P{0.021518987341772152\textwidth}P{0.06455696202531645\textwidth}P{0.06455696202531645\textwidth}}
Panel size\tabcellsep 5\tabcellsep 10\tabcellsep 15\tabcellsep 20\tabcellsep 25\tabcellsep 30\tabcellsep 35\tabcellsep 40\\
Minimum CVR value\tabcellsep \multicolumn{6}{l}{0.99 0.62 0.49 0.42 0.37 0.33}\tabcellsep 0.31\tabcellsep 0.29\end{longtable} \par
 
\caption{\label{tab_1}Table 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{3} \par 
\begin{longtable}{P{0.2193548387096774\textwidth}P{0.13709677419354838\textwidth}P{0.08225806451612903\textwidth}P{0.4112903225806452\textwidth}}
Concepts\tabcellsep Items\tabcellsep CVR\tabcellsep Items restraint\end{longtable} \par
 
\caption{\label{tab_2}Table 3 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.2809322033898305\textwidth}P{0.1944915254237288\textwidth}P{0.37457627118644066\textwidth}}
Constructs\tabcellsep Total number of items\tabcellsep Number of items retained (significant CVR> 0.6)\\
Testability\tabcellsep 11\tabcellsep 7\\
Observability\tabcellsep 16\tabcellsep 11\\
TOTAL\tabcellsep 27\tabcellsep 18\end{longtable} \par
 
\caption{\label{tab_3}Table 4 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{5} \par 
\begin{longtable}{}
\end{longtable} \par
 
\caption{\label{tab_4}Table 5 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{6} \par 
\begin{longtable}{}
\end{longtable} \par
 
\caption{\label{tab_5}Table 6 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{7} \par 
\begin{longtable}{}
\end{longtable} \par
 
\caption{\label{tab_6}Table 7 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{8} \par 
\begin{longtable}{P{0.6206024096385542\textwidth}P{0.08807228915662652\textwidth}P{0.14132530120481926\textwidth}}
Sectors\tabcellsep Frequency\tabcellsep Percentage\\
Financial services sector\tabcellsep 112\tabcellsep 46,7\\
Telecommunication sector\tabcellsep 78\tabcellsep 32,5\\
NICT sector\tabcellsep 48\tabcellsep 20,0\\
Total\tabcellsep 240\tabcellsep 100,0\\
Post occupated\tabcellsep \tabcellsep \\
Member of the management Team\tabcellsep 12\tabcellsep 5,0\\
Marketing manager\tabcellsep 110\tabcellsep 45,8\\
Customer manager\tabcellsep 95\tabcellsep 39,6\\
Sales manager\tabcellsep 22\tabcellsep 9,2\\
Other 1\tabcellsep 1\tabcellsep ,4\\
Total\tabcellsep 240\tabcellsep 100,0\\
Using e-CRM system CRM\tabcellsep \tabcellsep \\
No\tabcellsep 85\tabcellsep 35,4\\
For a period of fewer than 1 years\tabcellsep 49\tabcellsep 20,4\\
For a period between 1 and 5\tabcellsep \tabcellsep \\
Years\tabcellsep 31\tabcellsep 12,9\\
For a period between 5 and 10\tabcellsep \tabcellsep \\
Years\tabcellsep 75\tabcellsep 31,3\\
Total\tabcellsep 240\tabcellsep 100,0\end{longtable} \par
 
\caption{\label{tab_7}Table 8 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{9} \par 
\begin{longtable}{P{0.04853587115666179\textwidth}P{0.024890190336749635\textwidth}P{0.08960468521229868\textwidth}P{0.20658857979502196\textwidth}P{0.01493411420204978\textwidth}P{0.21032210834553441\textwidth}P{0.07218155197657394\textwidth}P{0.07715959004392386\textwidth}P{0.10578330893118594\textwidth}}
\multicolumn{2}{l}{Steps n°N umber of items}\tabcellsep \multicolumn{2}{l}{Determinant KMO}\tabcellsep Sig Bartlett\tabcellsep Attempted extraction\tabcellsep Item with the lowest commonality\tabcellsep Com\tabcellsep Item\\
1\tabcellsep 19\tabcellsep 0.001\tabcellsep \multicolumn{2}{l}{0.738 2260.97}\tabcellsep Possible (6 F)\tabcellsep T3\tabcellsep 0.068\tabcellsep deleted\\
2\tabcellsep 18\tabcellsep 0.001\tabcellsep \multicolumn{2}{l}{0.738 2170.383}\tabcellsep Possible (6F)\tabcellsep O12\tabcellsep 0.144\tabcellsep deleted\\
3\tabcellsep 17\tabcellsep 0.002\tabcellsep \multicolumn{2}{l}{0.743 2110.177}\tabcellsep Possible (5F)\tabcellsep T5\tabcellsep 0.204\tabcellsep deleted\\
4\tabcellsep 16\tabcellsep 0.002\tabcellsep \multicolumn{2}{l}{0.743 2053.114}\tabcellsep Possible (4F)\tabcellsep O4\tabcellsep 0.23\tabcellsep deleted\\
5\tabcellsep 15\tabcellsep 0.003\tabcellsep \multicolumn{2}{l}{0.744 1965.476}\tabcellsep Possible(4F)\tabcellsep T6\tabcellsep 0.267\tabcellsep deleted\\
6\tabcellsep \tabcellsep 0.004\tabcellsep \multicolumn{2}{l}{0.748 1874.238}\tabcellsep Possible(4F)\tabcellsep T4\tabcellsep 0.136\tabcellsep deleted\\
7\tabcellsep 13\tabcellsep 0.004\tabcellsep \multicolumn{2}{l}{0.748 1811.878}\tabcellsep Possible(4F)\tabcellsep O8\tabcellsep 0.185\tabcellsep deleted\\
8\tabcellsep 12\tabcellsep 0.005\tabcellsep \multicolumn{2}{l}{0.749 1742.835}\tabcellsep Possible(4F)\tabcellsep O3\tabcellsep 0.282\tabcellsep deleted\\
9\tabcellsep 11\tabcellsep 0.007\tabcellsep \multicolumn{2}{l}{0.745 1647.377}\tabcellsep Possible(4F)\tabcellsep O11\tabcellsep 0.305\tabcellsep deleted\\
10\tabcellsep 10\tabcellsep 0.01\tabcellsep \multicolumn{2}{l}{0.733 1544.17}\tabcellsep Possible(3F)\tabcellsep O2\tabcellsep 0.255\tabcellsep deleted\\
11\tabcellsep 9\tabcellsep 0.13\tabcellsep \multicolumn{2}{l}{0.735 1446.983}\tabcellsep Possible(3F)\tabcellsep O1\tabcellsep 0.182\tabcellsep deleted\\
12\tabcellsep 8\tabcellsep 0.15\tabcellsep \multicolumn{2}{l}{0.726 1398.936}\tabcellsep Possible(3F)\tabcellsep O9\tabcellsep 0.465\tabcellsep keep\end{longtable} \par
 
\caption{\label{tab_8}Table 9 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{10} \par 
\begin{longtable}{P{0.17723404255319147\textwidth}P{0.061489361702127654\textwidth}P{0.14829787234042552\textwidth}P{0.20978723404255317\textwidth}P{0.184468085106383\textwidth}P{0.06872340425531916\textwidth}}
\multicolumn{3}{l}{Factors Items Communality}\tabcellsep Factorial contribution\tabcellsep \% of the explained variance\tabcellsep Alpha\\
Factor 1\tabcellsep T1\tabcellsep 0.986\tabcellsep 0.99\tabcellsep 36.224\%\tabcellsep 0.93\\
\tabcellsep T2\tabcellsep 0.708\tabcellsep 0.840\tabcellsep \tabcellsep \\
\tabcellsep T7\tabcellsep 0.772\tabcellsep 0.877\tabcellsep \tabcellsep \\
\tabcellsep O5\tabcellsep 0.514\tabcellsep 0.665\tabcellsep \tabcellsep \\
Factor 2\tabcellsep O6\tabcellsep 0,705\tabcellsep 0.842\tabcellsep 56.866\%\tabcellsep 0.797\\
\tabcellsep O7\tabcellsep 0,536\tabcellsep ,747\tabcellsep \tabcellsep \\
Factor 3\tabcellsep O9\tabcellsep ,0.465\tabcellsep ,704\tabcellsep 66.15\%\tabcellsep 0.638\\
\tabcellsep O10\tabcellsep 0,606\tabcellsep ,651\tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_9}Table 10 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{11} \par 
\begin{longtable}{P{0.85\textwidth}}
Composite Reliability\end{longtable} \par
  {\small\itshape [Note: j) Reliability of indicatorsFor Hair et al. (]} 
\caption{\label{tab_10}Table 11 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{12} \par 
\begin{longtable}{P{0.85\textwidth}}
VME\end{longtable} \par
 
\caption{\label{tab_11}Table 12 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{13} \par 
\begin{longtable}{P{0.3069444444444444\textwidth}P{0.22824074074074074\textwidth}P{0.18888888888888888\textwidth}P{0.1259259259259259\textwidth}}
\tabcellsep Observability1\tabcellsep Observability2\tabcellsep Testability\\
Observability1\tabcellsep 0.902\tabcellsep \tabcellsep \\
Observability2\tabcellsep 0.579\tabcellsep 0.856\tabcellsep \\
Testability\tabcellsep 0.228\tabcellsep 0.121\tabcellsep 0.901\end{longtable} \par
 
\caption{\label{tab_12}Table 13 :}\end{figure}
 		 		\backmatter  			 
\subsection[{Appendix}]{Appendix}\par
Appendix1: Qualitative study To try to understand the adoption of electronic customer relationship management "e-CRM" in service companies, a qualitative approach is therefore perfectly justified.\par
A qualitative study was planned to enrich our understanding of the meaning of the concept of adoption of the e-CRM system and to have a clear definition of this concept. Indeed, the adoption of e-CRM system is a complex concept and qualitative methods are appropriate tools to reveal how leaders perceive them from the testability and observability of the e-CRM system. Our qualitative study constitutes a semistructured interview in order to explore the intention of adoption of marketers.			 			  				\begin{bibitemlist}{1}
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\bibitem[Gil-Gomez et al. ()]{b11}\label{b11} 	 		‘Customer relationship management: Digital transformation and sustainable business model innovation’.  		 			H Gil-Gomez 		,  		 			V Guerola-Navarro 		,  		 			R Oltra-Badenes 		,  		 			Lozano-Quilis 		.  	 	 		\textit{Economic Research-Ekonomska Istra?ivanja}  		2020. 12  (1)  p. .  	 	 (J.) 
\bibitem[Rogers ()]{b16}\label{b16} 	 		\textit{Diffusion of innovation},  		 			E M Rogers 		.  		2003.  	 	 (5th Edition, Kindle edition) 
\bibitem[Fornell and Et Larcker ()]{b5}\label{b5} 	 		‘Evaluating structural equation models with unobservable variables and measurement error’.  		 			C Fornell 		,  		 			D F Et Larcker 		.  	 	 		\textit{Journal of Marketing Research}  		1981. 18 p. .  	 
\bibitem[Garson ()]{b6}\label{b6} 	 		 			G D Garson 		.  		\textit{Partial Least Squares: Regression \& Structural Equation Models},  				2016. 2016.  	 
\bibitem[I have observed other people in my department using the e -CRM system]{b21}\label{b21} 	 		\textit{I have observed other people in my department using the e -CRM system},  				 	 
\bibitem[I have often seen other users of the e-CRM system. 2. In my organization, several members have the e-CRM system 3. I saw the e-CRM system used outside my company]{b18}\label{b18} 	 		\textit{I have often seen other users of the e-CRM system. 2. In my organization, several members have the e-CRM system 3. I saw the e-CRM system used outside my company},  				 	 
\bibitem[I have seen sales advisers on most computers]{b22}\label{b22} 	 		\textit{I have seen sales advisers on most computers},  		 	 
\bibitem[Mackenzie et al. ()]{b14}\label{b14} 	 		 			Scott B Mackenzie 		,  		 			Podsakoff 		,  		 			M Philip 		,  		 			Podsakoff 		,  		 			P Nathan 		.  	 	 		\textit{Construct measurement and validation procedures in MIS and behavioral research: Integrating new and existing techniques},  				2011. 35 p. .  	 
\bibitem[Evrard et al. ()]{b3}\label{b3} 	 		\textit{Market -Etudes et recherches en marketing, 4ième édition},  		 			Y Evrard 		,  		 			B Pras 		,  		 			E Et Roux 		.  		2009. Paris: Dunod.  	 
\bibitem[Gavard-Perret ()]{b8}\label{b8} 	 		\textit{Méthodologie de la recherche en sciences de gestion: réussir son mémoire ou sa thèse},  		 			M.-Lpy Gavard-Perret 		.  		2012.  	 
\bibitem[O4: I have observed other people in my department using the e-CRM system. O5: The e-CRM system attempts to create a unique vision for each customer O6: The e-CRM system enables customer loyalty. O7: The e-CRM system offers better customer service. O8: The e-CRM system allows sellers to be more aware. O9: The e-CRM system meets the real needs of customers. O10: The e-CRM system allows the speed of data circulation. O11: The e-CRM system allows better collection of customer data. O12: The e-CRM system allows better use of customer data]{b27}\label{b27} 	 		‘O4: I have observed other people in my department using the e-CRM system. O5: The e-CRM system attempts to create a unique vision for each customer’.  	 	 		\textit{O6: The e-CRM system enables customer loyalty. O7: The e-CRM system offers better customer service. O8: The e-CRM system allows sellers to be more aware. O9: The e-CRM system meets the real needs of customers. O10: The e-CRM system allows the speed of data circulation. O11: The e-CRM system allows better collection of customer data. O12: The e-CRM system allows better use of customer data},  				 	 	 (O2: In my organization, several members have the e-CRM system. O3: I saw the e-CRM system used outside my company) 
\bibitem[Fernandez-Martinez ()]{b4}\label{b4} 	 		‘Structurefunction mapping of a heptameric module in the nuclear pore complex’.  		 			J Fernandez-Martinez 		.  	 	 		\textit{J Cell Biol}  		2012. 196  (4)  p. .  	 
\bibitem[T2: Using the e-CRM system allows you to understand how it works. T3: I tried the e-CRM system before adopting within the company. Q4: Testing the e-CRM system allows me to use it properly. T5: Testing the e -CRM system allows you to master your tools and functionalities]{b25}\label{b25} 	 		\textit{T2: Using the e-CRM system allows you to understand how it works. T3: I tried the e-CRM system before adopting within the company. Q4: Testing the e-CRM system allows me to use it properly. T5: Testing the e -CRM system allows you to master your tools and functionalities},  				 	 
\bibitem[T6: A trial period is essential. T7: I don't have the opportunity to try different applications on the]{b26}\label{b26} 	 		\textit{T6: A trial period is essential. T7: I don't have the opportunity to try different applications on the},  				 	 
\bibitem[Lekara ()]{b15}\label{b15} 	 		‘Technological Challenges in Management of Organizations’.  		 			Princewill Lekara 		.  	 	 		\textit{International Journal of Business \& Law Research}  		2019. 7  (2)  p. .  	 
\bibitem[The e-CRM system offers better customer service. 12. The e-CRM system allows sellers to be more reactive. 13. The e-CRM system allows sellers to be more aware. 14. The e-CRM system meets the real needs of customers. 1. Yes 2. No If yes CRM system attempts to create a unique vision for each client. 10. The e-CRM system enables customer loyalty. 11]{b23}\label{b23} 	 		‘The e-CRM system offers better customer service. 12. The e-CRM system allows sellers to be more reactive. 13. The e-CRM system allows sellers to be more aware. 14. The e-CRM system meets the real needs of customers. 1. Yes 2. No If yes’.  	 	 		\textit{CRM system attempts to create a unique vision for each client. 10. The e-CRM system enables customer loyalty. 11},  				 	 	 (which application is it? (Specify name) 
\bibitem[George et al. ()]{b9}\label{b9} 	 		‘The Evolving Nature of the Computer Self-Efficacy Construct: An Empirical Investigation of Measurement Construction, Validity, Reliability and Stability Over Time’.  		 			M George 		,  		 			Florida I Richard 		,  		 			D 		,  		 			Paul Clay Fort Lewis Coll 		.  	 	 		\textit{Journal of the Association for Information Systems}  		2017. 8  (1)  p. .  	 
\bibitem[Chin ()]{b1}\label{b1} 	 		‘the partial Least Squares approach for structural equation modeling’.  		 			W Chin 		.  	 	 		\textit{Marcoulides G. A, Modern Methods for Business Research},  				1998. p. .  	 
\bibitem[The system is not very visible in my Organization 5. I saw the e-CRM system used in my business]{b19}\label{b19} 	 		\textit{The system is not very visible in my Organization 5. I saw the e-CRM system used in my business},  		 	 
\bibitem[You are: 1. Member of the management team 2. Marketing Manager 3. Customer manager 4. Sales manager 5. Other, please specify ?????????????? For the following proposals]{b24}\label{b24} 	 		\textit{You are: 1. Member of the management team 2. Marketing Manager 3. Customer manager 4. Sales manager 5. Other, please specify ?????????????? For the following proposals},  		 	 	 (please indicate) 
\end{bibitemlist}
 			 		 	 
\end{document}
