代写BSAN2201 Principles of Business Analytics Article Review – Briefing Notes调试数据库编程

BSAN2201 Principles of Business Analytics

Article Review - Briefing Notes

Background

The course BSAN2201 Principles of Business Analytics has three assessment items: an article review (a written piece of assessment in Word form), a case study and presentation (a second written piece but in PowerPoint form plus recorded presentation), and a reflection (a short video recording).

These notes outline my expectations for the article review. The article review is intended as a precursor to the case study – perhaps exciting your interest in a topic and building your knowledge of the topic, as well as and demonstrating your ability to critique what is currently written on the topic. Before discussing the review further, outlining the nature and scope of business analytics and  the broad requirements of the case study has some value (more details on the case study later in the Semester).

One way to think about business analytics is to think of a matrix in two dimensions – with the domains of business analytics in one dimension and methods of business analytics in another. Think of the domains as potential application areas of analytics to the established business disciplines:

financial analytics, marketing analytics, supply chain analytics, talent analytics, etc. Methods include predictive and prescriptive analytics, machine learning and deep learning, etc. Hence, the concept of the “business analytics matrix.” In this course – Principles of Business Analytics – a key focus is on how the analytics revolution is changing the practice of business, including how analytics is changing the practice of the established business disciplines. Methods of business analytics are the principal focus of the companion course BSAN2204 Methods of Business Analytics.

In a little more detail, the domains of business analytics include accounting/financial analytics, people/talent analytics, operations analytics, marketing analytics, social media analytics, and supply chain analytics, etc.  Broadly speaking, the domains relate to the application of analytics to substantive business questions (the application areas). The methods of business analytics include data visualisation, predictive analytics/forecasting, data mining/machine learning, text/web analysis, and optimisation/simulation techniques, and machine learning techniques supporting artificial intelligence, etc. The methods are the engine room of analytics.

Towards the Case Study

Try to write the article review with the case study in mind. The purpose of the case study (the second assignment) is to show your understanding of how a business is applying analytics to create a competitive advantage – or could use analytics to do so.  The case study might address the following  broad questions. (1) What is the impact of business analytics on business practice, and how is this impact demonstrated?  (2) What is the future of business analytics, in what ways are the applications of business analytics changing?  (3) How is a particular domain of business analytics evolving – what are the business questions that are asked, how is analytics helping to address these questions?

Scoping your case study is probably the most fundamental choice you have to make – doing so may help to set the direction for your article review. For example, (1) you could focus on a particular business and the practice and impact of analytics and on that business. Or (2) you could write a more general case study identifying a particular aspect of business analytics and its implications for an industry sector, or (3) you might address your case study to public policy makers or consumers – linking analytics to issues of potential concern to policy makers. You may be able to think of other approaches than these three. You decide the scope, but you may find writing a more focused case study more rewarding than writing one with a broader focus.

The papers listed in the appendix may help you to get started with your reading program for the article review and case study.  You will probably need to look outside this list if you write on a specific domain of business analytics (e.g., accounting/financial analytics, marketing analytics, etc.). I strongly encourage you to draw your articles from the established business magazines including Business Horizons, California Management Review, Harvard Business Review, MIT Sloan Management Review, etc.  Iam not asking you to and nordo I expect you to review papers from academic journals (e.g., Journal of Finance, Journal of Marketing).  Keep the focus on business magazines – you might even adopt the style of these articles in writing your review and case study.

With this background, what form. should the articular review take and what steps are necessary to complete it?  Recall, the article review is intended as a precursor to the case study.  Hence, it would probably make sense for you to approach and write the article review with your anticipated approach to the case study in mind.  Of course, you can change your mind later about the direction of the case study and pursue a different line of attack.  Perhaps the feedback on the review you receive will be useful in making this decision.

Key Sections in the Article Review

The review will probably have sections like the following ones.

1.    Background

2.    Review/synthesis

3.    Critical discussion

4.    Implications for practice

5.    Conclusion

The background section should introduce the approach and outline the scope of the review. The review itself might take one of several different approaches.  Perhaps the easiest way to write the review is to review one paper after another in chronological order.  Of course, this may not be the best way to present the review. You might be able to see a pattern in the papers – contrasting earlier versus later papers, identifying shifts in thinking across the papers, establishing points of agreement and/or disagreement, etc. You decide the approach and keep in mind your review should “add value.”  A chronological approach is often a natural place to start, but may not offer much of a value-add.  (You may find yourself writing and rewriting the review.)

The review/synthesis should not simply be a review of one paper after another – try to synthesise the papers in some way.  Can you present the papers by chronological order, or by theme, or by some other ways that shows understanding and insight?  In summarising each article, it may be useful to ask yourself the following questions.  (1) What is the article trying to achieve, what are its broad objectives?  (2) What are the key ideas put forward in the article, what is the core claim(s) the author(s) makes?  (3) What evidence does the author(s) advance to support the key concepts/ideas? (4) How practical are the recommendations, what barriers might organisations have to overcome to  achieve them? Of course, you might think of additional points to address.

Perhaps the key section to the article review is the critical discussion. Writing the review/synthesis should build your domain knowledge.  In the critical discussion section, you should offer your opinions and your critique – of the papers, the field, the applications you have read about, etc. Offer a balanced perspective – what is “good/bad” about the papers, “important/unimportant,” even what is “feasible/infeasible” (from an organisational perspective).  How has reading the papers broadened your perspective and what, if anything is missing from the papers you read for the review?

In writing the section on implications for practice, you should try to extract the managerial implications of the papers you have read.  That is, what do the articlesimply for practice, how should business practices change to accommodate the recommendations the author(s) make?  You may even be able to identify a specific business or businesses that would benefit from the ideas and practices discussed in the articles.  In broad terms, the practical implications should specifically identify the message(s) or take away for business (that may be relevant when you construct your case study).  Think about the counterfactual – would will likely happen to businesses that do not act on the implications?

The implication section should then set-up your conclusion section. In the conclusion, you might be explicit about the likely direction of your case study. In particular, can you think of some potentially “big” and or “ provocative” ideas worth exploring further, or a business or issue you would like to write more about?  The conclusion should offer a bridge between the articles you have read and your initial ideas for your case study – its broad direction, ambitions, focus, etc.

Use of Artificial Intelligence

The use of artificial intelligence (AI) is permitted in this course and for this specific assessment item. For example, you could use ChatGPT or PaLM2 to help set the structure for your Article Review.  I would like you to disclose your use of AI – if you do decide to use AI.  I would like you to add a brief statement to your submission addressing how you used AI and what the use of AI contributed to your submission.  My expectation is that large language models will not be particularly useful in writing your article review – the articles you review will be very specific (probably beyond the specificity of a large language model).

Furthermore, the usual academic standards apply to your work – whether you use AI or not.  For example, the University has clear guidelines in relation to originality and plagiarism. You are discouraged from entering the text of articles you review into a large language model.  Doing so may conflict with the copyright of the original author or publisher, or both.

Getting Started

You might consider the following steps in getting started on the article review. Probably the most important step is establishing the scope – do so with a vision for your case study in mind.

1.    Set the scope: a broad review or a specific review focused on a theme or domain

2.    Identify the articles you wish to critique

3.    Read and summarise the papers

4.    Synthesise the papers/integrate their perspectives

5.    Develop your own views – critique the papers, develop your own opinions

6.    Come to some conclusion – what’s “good/bad,” “ insightful/uncritical,” etc.

7.    Suggest a question(s) you may address in your case study

Finally, think of these notes as a guide only.  They communicate my broad expectations – but you may think of different and better ways to approach the review.

Submission Guidelines

Your review should take the form. of a Word document (or similar) and you should submit your review using the Turnitin link on the course Blackboard page.  You should write about 2,500-3,000  words (some variation around this is OK).  Note the review is worth 30 percent of your score in the course.  Check the course profile for details of the due date.

Assessment Criteria

Please refer to the separate document on assessment criteria (marking criteria).

Appendix: Example Articles on Business Analytics

The Analytics Revolution

Kiron, David, Pamela Kirk Prentice, Renee Boucher Ferguson (2014), “The Analytics Mandate,” MIT Sloan Management Review, 55(4), 1-25.

Mcafee, Andrew and Erik Brynjolfsson (2012), “ Big Data: The Management Revolution,” Harvard Business Review, 90(10), 60-128.

Urban, Glen, Artem Timoshenko, Paramveer Dhillon, and John R. Houser (2020), “Is Deep Learning a Game Changer for Marketing Analytics?” MIT Sloan Management Review, 61(2), 71-76.

The Analytics Advantage

Acito, Frank and Vijay Khatri (2014), “ Business Analytics: Why Now and What Next?” Business Horizons, 57(5), 565-570.

Fountaine,Tim, Brian McCarthy, and Tamim Saleh (2019), “Building the AI-Powered Organization,” Harvard Business Review, 97(4), 62-73.

Ransbotham, Sam and David Kiron (2017), “Analytics as a Source of Business Innovation,” MIT Sloan Management Review, 58(3).

Sainam, Preethika, Seigyoung Auh, Richard Ettenson, and Yeon Sung Jung (2022), “How Well Does Your Company Use Analytics? A Framework to Identify Your Strengths and Weaknesses,” Havard   Business Review Digital Articles, 27 July, 1-10.

Data Literacy/Strategy

Pigni, Federico, Gabriele Piccoli, and Richard Watson (2016), “ Digital Data Streams: Creating Value from the Real-Time Flow of Big Data,” California Management Review, 58(3), 5-25.

Dallemule, Leandro and Thomas H. Davenport (2017), “What’s Your Data Strategy?  The Key is to Balance Offense and Defense,” Harvard Business Review, 95(3), 112.

Reid, Hoffman (2016), “Using Artificial Intelligence to Set Information Free,” MIT Sloan Management Review, 58(1), 20-22.

Ransbotham,Sam, David Kiron, Pamela Kirk Prentice (2015), “Minding the Analytics Gap,” MIT Sloan Management Review, 56(3), 63-68.

Analytics: Fulfilling the Promise

Adomavicius, Gediminas, Jesse Bockstedt, Shawn P. Curley, Jingjing Zhang, and Sam Ransbotham (2019), “The Hidden Side Effects of Recommendation Systems,” MIT Sloan Management Review, 60(2), 13-15.

Barton, Dominic and David Court (2012), “Making Advanced Analytics Work for You,” Harvard Business Review, 90(10), 78-83, 128.

Davenport, Thomas H. and Rajeev Ronanki (2018), “Artificial Intelligence for the Real World,” Harvard Business Review, 96(1), 108-116.

Shah, Shvetank, Andrew Horne, and Jaime Capella (2012), “Good Data Won’t Guarantee Good

Decisions: Most Companies have Too Few Analytics-Savvy Workers. Here’s How to Develop Them,” Harvard Business Review, 90(4), 23.