Horngren's Cost Accounting: A Managerial Emphasis

Srikant M. Datar; Madhav  Rajan

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Book | 2018

Horngren's Cost Accounting: A Managerial Emphasis

by Srikant M. Datar and Madhav Rajan

Abstract

Horngren’s Cost Accounting defines the cost accounting market and continues to innovate today by consistently integrating the most current practice and theory into the text. This acclaimed, market-leading text emphasizes the basic theme of “different costs for different purposes” and reaches beyond cost accounting procedures to consider concepts, analyses, and management. The 16th edition incorporates the latest research and most up-to-date thinking into all relevant chapters so that students are prepared for the rewards and challenges they will face in the professional cost accounting world of today and tomorrow.

Keywords: Cost accounting; Cost Accounting; Management;

Format: Print

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Citation:

Datar, Srikant M., and Madhav Rajan. Horngren's Cost Accounting: A Managerial Emphasis. 16th ed. Pearson Education, 2018.

About the Author

Srikant M. Datar

Arthur Lowes Dickinson Professor of Business Administration
Senior Associate Dean for University Affairs

Accounting and Management

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Case | HBS Case Collection | October 2018

Fundraising at St. Camillus Hospital

Srikant M. Datar and Caitlin N. Bowler

St. Camillus is a fictional non-profit hospital in rural Maine facing a serious budget deficit. As Director of Marketing, Victoria Stern is building a team to modernize the hospital fundraising efforts. An interview with a promising candidate who is also a digital native forces her to confront shifting attitudes toward issues of data and privacy across generations against the backdrop of continued cybercrime and data breaches within the healthcare industry. Students grapple with the tension between data as "useful" or private within an organization. In this context they explore the ethical issues they will face around data security and data governance in their roles as managers.

Keywords: data analysis; data privacy; data governance; ethics; non-profit; health care; fundraising; data security; Data and Data Sets; Safety; Governance; Ethics; Health Care and Treatment;

Citation:
Datar, Srikant M., and Caitlin N. Bowler. "Fundraising at St. Camillus Hospital." Harvard Business School Case 119-027, October 2018. View Details

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Case | HBS Case Collection | August 2017 (Revised September 2018)

Tamarin App: Natural Language Processing

Srikant M. Datar and Caitlin N. Bowler

In this case, students explore the challenges of using sentiment analysis to monitor and understand public perception around a software application, Tamarin SEO App. Technical topics include building a filtering classifier using naive Bayes and sentiment analysis This case was written for the second-year MBA course “Managing with Data Science.” The course provides MBA students with no programming experience an introduction to the field of data science and its applications in business. Students learn to (1) carefully articulate the business ask, (2) reason carefully from the ask; through metrics and models, and outputs; and (3) evaluate outputs from models to (4) develop a plan for action.

Keywords: data science; branding; perception; Data Analytics; analysis; Data and Data Sets; Brands and Branding; Analysis; Perception; Planning;

Citation:
Datar, Srikant M., and Caitlin N. Bowler. "Tamarin App: Natural Language Processing." Harvard Business School Case 118-015, August 2017. (Revised September 2018.) View Details

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Case | HBS Case Collection | August 2018 (Revised September 2018)

LendingClub (A): Data Analytic Thinking (Abridged)

Srikant M. Datar and Caitlin N. Bowler

LendingClub was founded in 2006 as an alternative, peer-to-peer lending model to connect individual borrowers to individual investor-lenders through an online platform. Since 2014 the company has worked with institutional investors at scale. While the company assigns grades and sub-grades to each application using its own risk evaluation model, it also makes detailed data on each loan application available to both kinds of investors for their own analyses.
The case follows MBA graduate Emily Figel as she researches LendingClub as a potential investment vehicle for the small wealth management firm she will join in the fall. Using LendingClub’s historical data, she learns the fundamentals of predictive analytics to see whether she can build models to predict whether a borrower will repay or, ultimately, default on the obligation.
This first case (A) presents students with relevant, detailed data about how the LendingClub model works. This includes LendingClub’s business model, the grading of loans, the unique opportunities and risks. It also follows Figel as she dives into the data to use it to build a model. In the B and C cases, Figel explores several specific techniques for training models.
Technical topics include: understanding the data, data preparation, balanced and unbalanced data sets, constructing training-validation-holdout sets, cross-validation, predictions and target leakage.

Keywords: data science; Data Analytics; Investing; loans; Investment; Financing and Loans; Data and Data Sets; Analysis; Forecasting and Prediction; Business Model;

Citation:
Datar, Srikant M., and Caitlin N. Bowler. "LendingClub (A): Data Analytic Thinking (Abridged)." Harvard Business School Case 119-020, August 2018. (Revised September 2018.) View Details

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Horngren's Cost Accounting: A Managerial Emphasis

Abstract

Citation:

About the Author

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