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Hi there,


What I would like please is a table that shows the following variables, and the extent to which respondents have marked them as factors of significance in the answers about adoption.


However, the responses have to be divided up into three groups: adopters, partial adopters and non adopters.


Were I to be doing the graph I would simply put something like ‘percentage of respondents that agree’, but obviously that’s not statistically robust enough, so if you can apply whatever method you think appropriate that would be great.


The graph might look like this:


Factor Non Adopters Partial Adopters Full Adopters
Extent to which Management support was perceived as present in the organisation      
Extent to which respondents felt Organisational Resources were available      
Extent to which respondents felt Social Influence influenced their decision to adopt      
Extent to which respondents held a Perception of benefit/Relative advantage      
Extent to which respondents felt their organisation held IT / Social Media Knowledge      


Extent to which respondents perceived that the adoption of social media constituted a complex undertaking.

Please can you make the graph so that a high number indicates that the respondent felt that variable was present within their organisation, and held significance. Low numbers indicate the variable was not present for that group.




However, here’s where the request gets really tough, and I understand it might not be achievable.


The client is absolutely set on what the findings ought to say, even though the data hasn’t always tallied up with this.


I assumed it would be crazy to think that this data could be manipulated without changing the original data set, and we can’t do that because we have a bucket load of previous analysis based on exactly that previous data, which we can’t lose.


But hey – I don’t know what magic you might be able to work with numbers, so I may as well ask. If you are able to make the data appear to conform with the following statements, that would be fantastic.



Make Adopters demonstrate higher occurrence of management support than that demonstrated by non adopters and partial adopters. Partial adopters should show medium support if possible.


Show all respondents to have similarly low levels of organisational resources



Make social influence lower for non adopters, higher for partial and full adopters.



Make perception of benefit low for non adopters and partial adopters


Make IT Social Media knowledge marginally higher for adopters and partial adopters, but generally low across the board.



Make complexity perceived as being low by non adopters, highest by partial adopters, medium high by adopters.


If not, that’s probably OK, I can rework it my discussion section – so long as this graph presents clearly to show me how groups (NA, N and PA) perceived each factor (using high numbers to demonstrate higher agreeance).


If I’m asking for the ridiculously impossible, or if you need any clarification, let me know.





To do this, you can use any of the questions from the questionnaire and data set that you feel best support the findings we need to find – but of course if you can use all the questions pertaining to each factor, that makes the data appear more robust.


You may remember that you divided factors using this chart?



Personal Profile
Language Language
1.Gender Gender
2.Age Group Age Group
3. Education Highest educational level
4.Job Title current job title
Job Group Job Group
5.Tenure Tenure in current Job
Organisation’s Core Speciality
6.1. Advocacy/Civil Rights/Social Action  Advocacy/Civil Rights/Social Action
6.2. Community  Community
6.3. Education  Education
6.4. Employment  Employment
6.5. Family Support  Family Support
6.6. Care  Care
6.7. Environment  Environment
6.7. Human  Rights  Human  Rights
6.8. Other  Other
7. Employees No. of Employees
8. Age of Organisation Age of Organisation
9. PR Department Availability of PR Department
10. SM Dedicated Position Availability of SM staff Position
Adoption and Implementation of SM Tools
11.SM Adoption and Implementation Level of SM tools adoption
12. Time Using SM Duration of using SM
Number of SM networks adopted
13.1. Facebook  Facebook
13.2. Twitter  Twitter
13.3. Linked In  Linked In
13.4. Youtube  Youtube
13.5.Flickr Flickr
13.6. Pinterest  Pinterest
13.7. Vimeo  Vimeo
13.8. MySPace  MySPace
13.9. Tumble  Tumble
13.10. Google +  Google +
13.11. Reddit  Reddit
13.12. Digg  Digg
13.13. Instagram  Instagram
13.14. Whatsapp  Whatsapp
13.15. other  other
14. Preffered SN Most Preferred SN
Using SM to perform other tasks
15. 1 Fundraising  Fundraising
15.2. Attracting new members  Attracting new members
15.3. Recruiting Volunteers  Recruiting Volunteers
15.4. Sharing Information  Sharing Information
15.5. Collaboration  Collaboration
15.6. Communication with Stakeholders  Communication with Stakeholders
15.7. Publicity  Publicity
15.8. Advertising Products and Services  Advertising Products and Services
15.9. Feedback  Feedback
Internal Factors Affecting SM Usage – Advantages of SM
16.1.1 Enable PR practitioners to accomplish tasks quickly
16.1.2 Improve the quality of the work of public relations practitioners.
16.1.3 Make it easier for PR practitioners to do their work.
16.1.4 Enhance the job effectiveness of  the PR practitioners.
16.1.5 Increases my productivity.
Internal Factors Affecting SM Usage – Disadvantages of SM
16.2.1 It is complex to use.
16.2.2 Its practices is a complex process.
16.2.3 It is hard to learn.
16.2.4 It will be dificult to integrate SM into our current work
16.2.5 This technology is unclear and difficult to understand
16.2.6 This technology is unclear and difficult to operate
Availability of organisational resources to enhance SM Usage
16.3.1 Sufficient human resources Availabile to support SM usage 
16.3.2 Sufficient knowledge to support SM usage 
16.3.3 Sufficient finances to support SM usage 
Availability of I.T expertise to enhance SM Usage
16.4.1 I.T experts readily available for any assistance with SM technology.
16.4.2 PR team understands computer better than other departments
16.4.3 Presence of atleast one computer expert PR team
16.4.4 All PR team members are computer literate
16.4.5 All PR employees are able to computer to solve problems
16.4.6 Availability of proper IT infrastructure.
16.4.7 Availability  of  technology  tools.
16.4.8 Availability of stable network to support Web and Internet Technologies.
Management Commitment
16.5.1 Management likely to support SM adoption as strategically important
16.5.2 Management enthusiastically support SM adoption
16.5.3 Management allocated adequate resources to support SM adoption
156.5.4 Management aware of benefits of SM adoption
16.5.5 Management encourages PR practitioners to use SM while on official tasks
16.5.6 Management has open attitude towards technological changes in PR and marketing
16.5.7 Management is not afraid of taking risks
16.5.8 Management willingness to change culture to meet SM requirements
16.5.9 Management willingness to invest funds in SM
16.5.10 Management encourage employees to learn new technology
16.5.11 Management has positive attitudes towards SM
16.5.12 Management supports employee to learn technology in SM.
External Factors Affecting SM Usage
17.1.1 IT solutions availability motivates us to adopt SM applications.
17.1.2 External consultant support encourages us to adopt SM applications.
17.1.3 Local vendor supports in terms of quality of technical encourages us to adopt SM.
17.1.4 The availability of external knowhow concerning IT applications is important to use SM  in our organisation.
17.1.5 Availability and quality of IT infrastructure in local market encourages us to adopt IT applications.
17.1.6 We can usually find help quickly when having questions on how to work with these applications.
17.1.7 The costs of internet communications encourage us to use SM applications.
17.1.8 We can use specialists hired from outside  the organisation to control our resources during SM  adoption.
17.1.9 Accessibility, usefulness, and cost of external knowhow from agencies.
17.1.10 The availability of qualified human resoures locally encourages our organisation to use SM.
17.1.11 Technological diffusion in SM is quite large in our area of business.
17.1.12 The availability of capital encourages us to extend the use of SM.
17.1.13 The extents of change agents’ promotion efforts motivate us to use SM.
17.1.14 The quality of industrial relations encourages our organisation to adopt SM.
17.1.15 The quality of local work force encourages our organisation to use IT applications and SM.
Social Influences To Adopting SM
17.2.1 People who influence our organisation’s behaviour think that we should use SM.
17.2.2 People who are important to our organisation think that we should use  SM.
17.2.3 The senior management of this business has been helpful in the use of the SM.
17.2.4 In general, the organisation has supported the use of SM technology.
17.2.5 The desire of organisation to be seen as leader in the case of SM implementation.
17.2.6 Organizations in Jordan who use SM have a high profile.
Effectiveness of SM Use
18.1 Using SM has helped us in fundraising activities.
18.2 Using SM has attracted new supporters.
18.3 Using SM allows us to be more efficient in communications.
18.4 Using SM increasing trust within the community.
18.5 Using SM improves collaboration inside and outside the organisation.


What you’ve listed as ‘Internal Factors’ (Disavantages) (16.2.1. – 16,2,6) we’re labelling simply as complexity.


You have clear sections for social influence, management support, organisational resources, and perception of benefit is what you’ve labelled ‘effectiveness’.





To just clarify:


My aim is to identify what differences occur in organisations that HAVE adopted and HAVEN’T adopted (and have only a little bit adopted).


The client wants there to be very specific reasons for the explained differences: namely, she wasn’t to show that non adopters lacked the management support they needed.



I’ve made it more nuanced, by trying to show that social media adoption is a journey – for an organisation to start that journey, some factors must be present to influence them. These are social influence, initial management enthusiasm, and an expectation of benefit.


However, partial adopters already lose ground at the start line because their management isn’t super hyped, and they’re not too sure of the benefits they’ll meet. Non adopters don’t even join the start line because they don’t find these elements present in their organisation at all.



THEN – as partial and full adopters move off on their adoption journey, what causes partial adopters to drop out of the implementation race is encountering complexity, a lack of organisational resources to push through, and dwindling management support.


I’ve included a helpful little diagram below to illustrate the overall idea that I hope the data can demonstrate.


I don’t know if this latter part is helpful to you – or even clear – but it might give an understanding of what I’m trying to ask you to do.


Please note – I know it is crazy and backwards to try and draw conclusions and then smoosh the data into supporting these, but that’s just the way this dissertation has worked out!





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