Inventory Analytics

Reviewed by Sangphil Kim, Associate Professor, Winona State University on 2/16/23

Comprehensiveness rating: 5 see less

It covers all the basic concepts in inventory control theory. It is amazing that the book covers almost everything in less than 200 pages without losing the depth.

Content Accuracy rating: 5

I don’t see any incorrect content.

Relevance/Longevity rating: 5

The concepts the book covers are the fundamentals. And by providing python codes, the book keeps up with the current trend.

Clarity rating: 5

In some part, the style of writing is very concise. Personally, I prefer this style but other may not like it. However, it doesn’t skip any important information.

Consistency rating: 5

The text is consistent in terms of terminology and framework. Pretty well.

Modularity rating: 5

Definitely, the book is divisible into smaller section. Depends on the instructor’s need, he or she can take only a couple of chapters, and the text still will serve its purpose.

Organization/Structure/Flow rating: 5

Organization is clear. It cannot be better.

Interface rating: 5

Everything is clear and free of interface issues.

Grammatical Errors rating: 5

No grammatical error.

Cultural Relevance rating: 5

This is book handles scientific contents. It cannot be culturally offensive or insensitive.

When I check the number of pages, I didn’t expect a comprehensive textbook for inventory theory. However, it didn’t take too long to find I was wrong. The text is very concise and covers almost every building blocks in inventory theory. I don’t recommend this book to general business undergraduate course due to the mathematical depth it covers. It would be good textbook for advanced undergraduate or graduate level course either in business or in industrial engineering.

Reviewed by Shouhong Wang, Commonwealth Professor, University of Massachusetts Dartmouth on 11/2/22

Comprehensiveness rating: 5 see less

This OER book is a comprehensive introduction to the theories and practices of inventory control. Inventory management is a research area central to supply chain management. The book provides an effective index and glossary.

Content Accuracy rating: 5

The book provides the foundations of inventory systems and analytics models of inventory control. The content has solid research base and is accurate.

Relevance/Longevity rating: 5

The content is up-to-date and will be sustainable in the foreseeable future. Many inventory control models discussed in the book are classical. The book is easy to arrange so that necessary updates (e.g., new inventory control models) can be easily added.

Clarity rating: 5

The textbook is easy to read, and is accessible for researchers and practitioners in inventory management.

Consistency rating: 5

The book has a uniform structure. The terminology and symbols are consistent.

Modularity rating: 5

Each module (chapter or section) of the book addresses a specific inventory control theory or inventory control model. The book is easy to resign to meet specific teaching/learning needs.

Organization/Structure/Flow rating: 5

The presentation of the inventory theories or models is progressive. The presentation flow is logical and easy to follow.

Interface rating: 5

The figures in the book are clear and well-explained. They are informative.

Grammatical Errors rating: 5

The book contains no grammatical errors.

Cultural Relevance rating: 5

The book is a genuine scientific book.

This OER book is a comprehensive introduction to the theories and practices of inventory control. Inventory management is a research area central to supply chain management. The book provides the foundations of inventory systems and analytics models of inventory control. The book includes Python programs to illustrating inventory control theories and models via computational examples. This book is an excellent textbook for graduate as well as undergraduate courses which dedicate to inventory management. It is also an outstanding reference book for researchers and practitioners in the areas of supply chain management, industrial engineering, data sciences and analytics, and applications of Python programming.