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Structuring a Quantitative Paper: Page # 6. Research Topic: Impact of Artificial Intelligence on the adoption of the intention in Saudi Arabia market. Please check the attached syllabus and the subject.

Note: the first three parts of the paper [ Introduction, Literature review, Abstract]

– Total of the pages as follow in the syllabus but it will be around 20 pages or more.

– Every other two weeks after the first dart it will be daft submission from the paper.
– The questionnaire of the paper it should follow the attached example.
– The level of the paper writing it should not be advance because I am not Native speaker, from Saudi Arabia.


Step 1:


 How to start any [EVERY] Research Project                                                                                                                                                                                                            

In a page or less, using only bullet points, answer these questions [or fill out this outline].



  1. What is the problem you are seeking to address? [If there is no problem, then there is usually no research ]


  1. Why is this an important [not just interesting] contemporary or upcoming problem? [i.e., old problems don’t need to be readdressed if they are not still a problem]
  2. Who else has addressed this problem? [Very rarely is the answer to this: “nobody”. Be creative. Someone has studied something related to this problem, even if it isn’t the exact same This requires a lit review.]
  3. In what way are the prior efforts of others incomplete? [i.e., if others have already addressed the problem, what is left to study – what are the “gaps”?]
  4. How will you go about filling these gaps in prior research? [i.e., study design]


  1. Why is this an appropriate approach?


  1. [If applicable] Who is your target population for studying this problem? [Where are you going to get your data?]


  1. How are you going to get the data you want? [quantity and quality]



If you would like to use the answers to the above questions as the substance of your introduction section, just add these two points:



  1. Overall, what did your endeavors discover?


  1. How is your paper organized to effectively communicate the arguments and contributions you are trying to make?



Step 2:

 Developing Your Quantitative Model                                                                                                                                                                                                         Ten Steps for Formulating a Decent Quantitative Model

  1. Identify and define your dependent These should be the outcome[s] of the phenomenon you are interested in better understanding. They should be the effected thing[s] in your research questions.
  2. Figure out why explaining and predicting these DVs is


  1. Why should we care?


  1. For whom will it make a difference?


  1. What can we possibly contribute to knowledge that is not already known?


  1. If these are all answerable and suggest continuing the study, then go to #3, otherwise, go to #1 and try different
  1. Form one or two research questions around explaining and predicting these


  1. Scoping your research questions may also require you to identify your


  1. Is there some existing theory that would help explore these research questions?


  1. If so, then how can we adopt it for specifically exploring these research questions?


  1. Does that theory also suggest other variables we are not considering?


  1. What do you think [and what has research said] impacts the DVs we have chosen?


  1. These become


  1. What is it about these IVs that is causing the effect on the DVs?


  1. These become


  1. Do these relationships depend on other factors, such as age, gender, race, religion, industry, organization size and performance, ?
    1. These become Moderators


  1. What variables could potentially explain and predict the DVs, but are not directly related to our interests?


  1. These become control variables. These are often some of those moderators like age and gender, or variables in extant
  1. Identify your


  1. Do you have access to this population?


  1. Why is this population appropriate to sample in order to answer the research questions?


  1. Based on all of the above, but particularly #4, develop an initial conceptual model involving the IVs, DVs, Mediators, Moderators, and
    1. If tested, how will this model contribute to research [make us think differently] and practice [make us act differently]?

Please Draw the Research Model Below:






Structuring a Quantitative Paper

Step 3:


Standard outline for quantitative model building/testing paper

  • Title [something catchy and accurate]
  • Abstract [concise – 150-250 words – to explain paper]: roughly one sentence each:
    • What is the problem?
    • Why does it matter?
    • How do you address the problem?
    • What did you find?
    • How does this change practice [what people in business do], and how does it change research [existing or future]?
  • Keywords [4-10 keywords that capture the contents of the study]
  • Introduction [2-4 pages] The main purpose of the introduction is to convince the reader that this study is
    • What is the problem and why does it matter? And what have others done to try to address this problem, and why have their efforts been insufficient [i.e., what is the gap in the literature]? [1-2 paragraphs]
    • What is your DV[s] and what is the context you are studying it in? Also briefly define the DV[s]. [1-2 paragraphs]
    • One sentence about sample [e.g., “377 undergraduate university students using Excel”].
    • How does studying this DV[s] in this context adequately address the problem? [1-2 paragraphs]
    • What existing theory/theories do you leverage, if any, to pursue this study, and why are these appropriate? [1-2 paragraphs]
    • Who else has pursued this research question [or something related], and why were their efforts insufficient? [see section above about “how to start every research project”] [1-2 paragraphs]
    • Briefly discuss the primary contributions of this study in general terms without discussing exact findings [i.e., no p- values here].
    • How is the rest of the paper organized? [1 paragraph]
  • Literature review [1-3 pages] The main purpose of the literature review section is to establish who else has addressed a similar research question, and how your study will extend or clarify these. This helps both for positioning your contribution within extant literature, and for motivating why your study is needed [beyond these extant studies].
    • Fully define your dependent variable[s] and summarize how it has been studied in existing literature within your broader context [like Information systems, or, Organizations, ].
    • If you are basing your model on an existing theory/model, use this next space to explain that theory [1 page] and then explain how you have adapted that theory to your
    • If you are not basing your model on an existing theory/model, then use this next space to explain how existing literature in your field has tried to predict your DV[s] or tried to understand related research
    • [Optionally] Explain what other constructs you suspect will help predict your DV[s] and Inclusion of a construct should have good logical/theoretical and/or literature support. For example, “we are including construct xyz because

the theory we are basing our model on includes xyz.” Or, “we are including construct xyz because the following logic



[abc] constrains us to include this variable lest we be careless”. Try to do this without repeating everything you are just going to say in the theory section anyway.

  • [Optionally] Briefly discuss control variables and why they are being
  • Theory & Hypotheses [take what space you need, but try to be parsimonious] The main purpose of this section is to justify your theory [provide rational rationale for the relationships you are suggesting].
    • Briefly summarize your conceptual model and show it with the Hypotheses labeled [if possible].
    • Begin supporting H1 then state H1 Support should include strong causal logic and literature.
    • H2, H3, If you have sub-hypotheses, list them as H1a, H1b, H2a, H2b, etc.
  • Methods [keep it brief; many approaches; this is just a common template] The main purpose of this section is to convince the reader that you chose the right method and that you did it
    • Construct operationalization [where did you get your measures?]
    • Instrument development [if you created your own measures]
    • Explanation of study design [e.g., pretest, pilot, and online survey]
    • Sampling [some descriptive statistics, like demographics [education, experience, etc.], sample size; don`t forget to discuss response rate [number of responses as a percentage of number of people invited to do the study]].
    • Mention that IRB exempt status was granted and protocols were followed if
    • Method for testing hypotheses [e.g., structural equation modeling in AMOS]. If you conducted multi-group comparisons, mediation, and/or interaction, explain how you kept them all straight and how you went about analyzing For example, if you did mediation, what approach did you take [hopefully bootstrapping]? Were

there multiple models tested, or did you keep all the variables in for all analyses? If you did interaction, did you add that in afterward, or was it in from the beginning?

  • Analysis [1-3 pages; sometimes combined with methods section] The main purpose of this section is to convince the

reader that you’re analysis was done correctly and your hypotheses were tested appropriately.

  • Data Screening
  • EFA [report pattern matrix and Cronbach`s alphas in appendix] – mention if items were
  • CFA [just mention that you did it and bring up any issues you found] – mention any items dropped during CFA. Report model fit for the final measurement Supporting material can be placed in the Appendices if necessary.
  • Mention CMB approach and results and actions taken if any [e.g., if you found CMB and had to keep the CLF].
  • Report the correlation matrix, CR and AVE [you can include MSV and ASV if you want], and briefly discuss any issues with validity and reliability – if any.
  • Report whether you used the full latent SEM, or if you imputed factor scores for a path
  • Report the final structural model[s] [include R-squares and betas] and the model fit for the model[s].
  • Findings [1-2 pages] The main purpose of this section is to report the results of your hypothesis
    • Report the results for each hypothesis [supported or not, with evidence].
    • Point out any unsupported or counter-evidence [significant in opposite direction]
    • Provide a table that concisely summarizes your
  • Discussion [2-5 pages] The main purpose of this section is to convince the reader of your contributions, and to expand their understanding of you
    • Summarize briefly the study and its intent and findings, focusing mainly on the research question[s] [one paragraph].
    • What insights did we gain from the study that we could not have gained without doing the study?
    • How do these insights change the way practitioners do their work?
    • How do these insights shed light on existing literature and shape future research in this area?
    • What limitations is our study subject to [e.g., surveying students, just survey rather than experiment, statistical limitations like CMB etc.]?
    • What are some opportunities for future research based on the insights of this study?
  • Conclusion [1-2 paragraphs] The main purpose of this section is to motivate the reader to use your work in their own
    • Summarize the insights gained from this study and how they address existing gaps or
    • Explain the primary contribution of the
    • Express your vision for moving forward or how you hope this work will affect the
  • References [Please use a reference manager like EndNote]
  • Appendices [Any additional information, like the instrument and measurement model stuff that is necessary for validating or understanding or clarifying content in the main body text.]
    • DO NOT pad the appendices with unnecessary statistics tables and illegible statistical models. Everything in the appendix should add value to the If it doesn’t add value, remove it.

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