Question

Think about two research topics related to information systems: one that is applied research, and another that is basic research. I expect to see a two part submission approximately one page single spaced consisting of: Applied research, Basic research and a summary.

Part 1 - Provide a 1-paragraph summary of an IS related applied research topic.

Argue why the topic is applied research.

Describe the data you would collect for your project - be specific, e.g., gender, sales, region, age, trust, opinions on customer service, etc.

Describe whether you would collect the data yourself or use data that is readily available.

Describe whether the data you collect would be quantitative or qualitative data.

How would you collect the data and from what data sources?

Part 2 - Include a 1-paragraph summary of an IS related basic research topic.

Argue why the topic is basic research.

Describe the data you would collect for your project - be specific, e.g., gender, sales, region, age, trust, opinions on customer service, etc.

Describe whether you would collect the data yourself or use data that is readily available.

Describe whether the data you collect would be quantitative or qualitative data.

How would you collect the data and from what data sources?

Answer 1

VS APPLIED research BASIC research New knowledge acquired has specific commercial objectives: products, procedures or services. Desire to expand knowledge Curiosity driven. Intended to answer or how questions. Increase understanding of fundamental principles. why, what Answer specific questions aimed at solving practical problems. Does not have immediate commercial objectives. It may not necessarily result in an invention or a solution to a practical problem. Answer fundamental Creates new products, technologies and processes questions: how do things work? Leads to new products, technologies & processes Leads to new fundamental questions

PART 1:

The topic that has been chosen here is from the Journal of Information Systems Applied Research, Volume 12. The research is on A Machine Learning Approach to Optimizing Diabetes Healthcare Management Using SAS Analytic Suite. If you want to access the research i am referring to go on to: https://drive.google.com/open?id=1P5bHR4O_XeFOvRSTLlANxq-pgQrXoYki

summary:

A typical healthcare business challenge was explored to demonstrate the effectiveness of data mining and machine learning techniques on large-scale medical and pharmacy claims data for about 70,000 patients newly diagnosed with type II diabetes. The business challenge was to move uncontrolled diabetic patient (H1AC > 7) to a controlled state (H1AC < 7). Two models were explored for this purpose and the regression was observed to perform slightly better than decision tree. Regression model was subsequently used to score “new” data. Analyses revealed the drivers and probabilities of a patient being diagnosed as controlled. Obtained results can provide incentives for the business decision maker to explore interventional programs that could enhance the quality of treatment for the uncontrolled diabetic. The article provides an added value to business and the analytic literature by exploring and explaining predictive analytics and associated techniques from the perspective of the business.

This could be considered an applied research since it contains a systematic procedure of artificial intelligence based classification to a practical problem, which in this case is to identify class 2 diabetes patients and to prescribe for them measures in decreasing their H1AC levels to below 7. It contains identifying factors that directly affects the condition and diagnostics of diabetes and uses these for the purpose of classification. At the end what we receive is an advanced technology with a practical application.

Data of importance for this specific research are:

Patient name - and other details like age, gender, location and nationality

Healthcare institution name-     and other details like location and specification

Patient H1AC levels-    and other glucose related values obtained via blood test

Patient body analysis-    and other results obtained from various tests

Patient diagnostic history-    previous diagnostics from consultations

Patient heredity timeline-       etc.....

The preferred mode for data collection in this specific example is to use the readily available data from various medical institutions. The database with all or partial data from above, is itself capable to build and train a classifying model. The data to be explored and aggregated from must be of genuine reliability and high in quantity and therefore accessing patient records from a healthcare database is the best option.

The type of primary data that we have to collect is Qualitative, since we need details on each patient to realize a trend of factors resulting in diabetes. The research method here is exploratory and the approach is subjective. Here although computations are necessary in evaluation of patient details, we resort to data mining since it offer objective conclusions from discrete data.

The data could be collected by contacting medical centers and requesting access to their database. In normal cases this would require a few amount of money but comparatively very low considering the importance of the research.

PART 2:

This topic has been chosen from a research on Academia made public by Jhon Loyd Gellica. The research is on System : Information Management System for Loan Processing. If you want to access the research i am referring to go on to: https://drive.google.com/open?id=1GPW5Gw_LQ5RSnQm1LqOvQdstNwevYD2T

summary:

The system is composed of mainly two features and functions and those are the loan system and profiling system. In loan system, the client will comply all the requirements to avail and acquire the loan of the said program. The staff will then input the client’s information and data in the database system.On the second part and function which is the profiling system, it is only allowed for the user to view the data and information of the client on the system except for editing. The clients’ information and data will be viewed by looking up/searching the client’s name on the database.

This could be considered a basic research since it make use of universal principles like analyzing a person's financial situation before making decisions on loan approval. The intentions are to expand the knowledge of the process in the business and management but has no immediate commercial objectives.

The data included here are:

Client data - name,gender, age, address social status, employment, salary and contact

Loan data- amount, type of loan, date, interest rate and payback time

Service- type, Employee Id

and previous records regarding clients from all other financial institutions.

In this specific case the most feasible solution is to collect the data manually since they are individual to each person and records with the same individual are less reliable for considering another case of financial transaction. The data are gathered by analyzing the clients social status and his/her salary options to draw out an optimal personal description. These are manually gathered and verified comparing to legal document. It will be from these descriptions that the decisions will be made.

Here the priority is to quantitative data since the primary objective is a conclusion based on the description that has been evaluated by certain rules. The rules maybe be arithmetic or logical but are more concerned with comparisons to how likely the approval of such a transaction will be successful. The analysis is more statistical and the outcome anticipated is a measured action.

The data could either be collected from other financial institutions just to compare any lending payments that would be a potential black mark. But when it comes to analyzing a client, most of the data are collected from the client itself and evaluated on the basis of how genuine and reliable the documents produced are, on basis of the employer decision.

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