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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 AdoptersFull 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
LanguageLanguage
1.GenderGender
2.Age GroupAge Group
3. EducationHighest educational level
4.Job Titlecurrent job title
Job GroupJob Group
5.TenureTenure 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. EmployeesNo. of Employees
8. Age of OrganisationAge of Organisation
9. PR Department Availability of PR Department
10. SM Dedicated PositionAvailability of SM staff Position
Adoption and Implementation of SM Tools
11.SM Adoption and ImplementationLevel of SM tools adoption
12. Time Using SMDuration 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.FlickrFlickr
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 SNMost 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
16.1.1Enable PR practitioners to accomplish tasks quickly
16.1.2Improve the quality of the work of public relations practitioners.
16.1.3Make it easier for PR practitioners to do their work.
16.1.4Enhance the job effectiveness of  the PR practitioners.
16.1.5Increases my productivity.
Internal Factors Affecting SM Usage – Disadvantages of SM
16.2.1It is complex to use.
16.2.2Its practices is a complex process.
16.2.3It is hard to learn.
16.2.4It will be dificult to integrate SM into our current work
16.2.5This technology is unclear and difficult to understand
16.2.6This technology is unclear and difficult to operate
Availability of organisational resources to enhance SM Usage
16.3.1Sufficient human resources Availabile to support SM usage 
16.3.2Sufficient knowledge to support SM usage 
16.3.3Sufficient finances to support SM usage 
Availability of I.T expertise to enhance SM Usage
16.4.1I.T experts readily available for any assistance with SM technology.
16.4.2PR team understands computer better than other departments
16.4.3Presence of atleast one computer expert PR team
16.4.4All PR team members are computer literate
16.4.5All PR employees are able to computer to solve problems
16.4.6Availability of proper IT infrastructure.
16.4.7Availability  of  technology  tools.
16.4.8Availability of stable network to support Web and Internet Technologies.
Management Commitment
16.5.1Management likely to support SM adoption as strategically important
16.5.2Management enthusiastically support SM adoption
16.5.3Management allocated adequate resources to support SM adoption
156.5.4Management aware of benefits of SM adoption
16.5.5Management encourages PR practitioners to use SM while on official tasks
16.5.6Management has open attitude towards technological changes in PR and marketing
16.5.7Management is not afraid of taking risks
16.5.8Management willingness to change culture to meet SM requirements
16.5.9Management willingness to invest funds in SM
16.5.10Management encourage employees to learn new technology
16.5.11Management has positive attitudes towards SM
16.5.12Management supports employee to learn technology in SM.
External Factors Affecting SM Usage
17.1.1IT solutions availability motivates us to adopt SM applications.
17.1.2External consultant support encourages us to adopt SM applications.
17.1.3Local vendor supports in terms of quality of technical encourages us to adopt SM.
17.1.4The availability of external knowhow concerning IT applications is important to use SM  in our organisation.
17.1.5Availability and quality of IT infrastructure in local market encourages us to adopt IT applications.
17.1.6We can usually find help quickly when having questions on how to work with these applications.
17.1.7The costs of internet communications encourage us to use SM applications.
17.1.8We can use specialists hired from outside  the organisation to control our resources during SM  adoption.
17.1.9Accessibility, usefulness, and cost of external knowhow from agencies.
17.1.10The availability of qualified human resoures locally encourages our organisation to use SM.
17.1.11Technological diffusion in SM is quite large in our area of business.
17.1.12The availability of capital encourages us to extend the use of SM.
17.1.13The extents of change agents’ promotion efforts motivate us to use SM.
17.1.14The quality of industrial relations encourages our organisation to adopt SM.
17.1.15The quality of local work force encourages our organisation to use IT applications and SM.
Social Influences To Adopting SM
17.2.1People who influence our organisation’s behaviour think that we should use SM.
17.2.2People who are important to our organisation think that we should use  SM.
17.2.3The 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.
17.2.5The desire of organisation to be seen as leader in the case of SM implementation.
17.2.6Organizations in Jordan who use SM have a high profile.
Effectiveness of SM Use
18.1Using SM has helped us in fundraising activities.
18.2Using SM has attracted new supporters.
18.3Using SM allows us to be more efficient in communications.
18.4Using SM increasing trust within the community.
18.5Using 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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