國立虎尾科技大學 |

Data and decision analytics for business operations = principles, problems, and practice /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Data and decision analytics for business operations/ by Michelle L. F. Cheong, Ma Nang Laik.
其他題名:	principles, problems, and practice /
作者:	Cheong, Michelle L. F.
其他作者:	Ma Nang Laik.
出版者:	Cham :Springer Nature Switzerland : : 2024.,
面頁冊數:	xviii, 323 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:	Springer Nature eBook
標題:	Business logistics. -
電子資源:	https://doi.org/10.1007/978-3-031-72255-4
ISBN:	9783031722554

Data and decision analytics for business operations = principles, problems, and practice /
Cheong, Michelle L. F.

Data and decision analytics for business operationsprinciples, problems, and practice /[electronic resource] :by Michelle L. F. Cheong, Ma Nang Laik. - Cham :Springer Nature Switzerland :2024. - xviii, 323 p. :ill. (some col.), digital ;24 cm.

1. Introduction -- 2. Demand Forecasting -- 3. Inventory Management -- 4. Distribution Management -- 5. Capacity Planning -- 6. Optimization Theory -- 7. Special Optimization Problems -- 8. Workforce Planning And Scheduling -- 9. Heuristic Algorithms -- 10. Queuing Theory -- 11. Simulation.

In this book, readers will be exposed to the Data and Decision Analytics Framework which helps a business analyst to first identify the root cause of business problems by collecting, preparing, and exploring data to gain business insights, before proposing what objectives and solutions should be developed to solve the problems. To guide the reader through the learning and application of this framework, several cases are included in the book to illustrate the typical operations management problems faced by businesses. These cases are based on experiences in business domains such as retail, healthcare, transportation and logistics operations, and banking, and they are related to demand forecasting, inventory management, distribution management, capacity planning, resource allocation, workforce scheduling, and service system management. For each case, a complete mapping of the case into the Data and Decision Analytics Framework was done to explain how the framework was applied to derive the data insights from data analytics, to define the business objectives, make the necessary assumptions, and then develop the solution to the business problem. This book aims at senior-year undergraduate or graduate students studying industrial engineering, business management with a focus on operations, or data science. They will learn how to use data analytics to first analyze problems to identify the root cause of problems, before developing the solutions supported by decision analytics.

ISBN: 9783031722554

Standard No.: 10.1007/978-3-031-72255-4doiSubjects--Topical Terms:

562973
Business logistics.

LC Class. No.: HD38.5

Dewey Class. No.: 658.5

Data and decision analytics for business operations = principles, problems, and practice /
LDR:02831nam a2200325 a 4500 001 1154196
003 DE-He213
005 20241228115244.0
006 m d
007 cr nn 008maaau
008 250619s2024 sz s 0 eng d
020 $a 9783031722554 $q (electronic bk.)
020 $a 9783031722547 $q (paper)
024 7 $a 10.1007/978-3-031-72255-4 $2 doi
035 $a 978-3-031-72255-4
040 $a GP $c GP
041 0 $a eng
050 4 $a HD38.5
072 7 $a UN $2 bicssc
072 7 $a COM021000 $2 bisacsh
072 7 $a UN $2 thema
082 0 4 $a 658.5 $2 23
090 $a HD38.5 $b .C518 2024
100 1 $a Cheong, Michelle L. F. $3 1481868
245 1 0 $a Data and decision analytics for business operations $h [electronic resource] : $b principles, problems, and practice / $c by Michelle L. F. Cheong, Ma Nang Laik.
260 $a Cham : $c 2024. $b Springer Nature Switzerland : $b Imprint: Springer,
300 $a xviii, 323 p. : $b ill. (some col.), digital ; $c 24 cm.
505 0 $a 1. Introduction -- 2. Demand Forecasting -- 3. Inventory Management -- 4. Distribution Management -- 5. Capacity Planning -- 6. Optimization Theory -- 7. Special Optimization Problems -- 8. Workforce Planning And Scheduling -- 9. Heuristic Algorithms -- 10. Queuing Theory -- 11. Simulation.
520 $a In this book, readers will be exposed to the Data and Decision Analytics Framework which helps a business analyst to first identify the root cause of business problems by collecting, preparing, and exploring data to gain business insights, before proposing what objectives and solutions should be developed to solve the problems. To guide the reader through the learning and application of this framework, several cases are included in the book to illustrate the typical operations management problems faced by businesses. These cases are based on experiences in business domains such as retail, healthcare, transportation and logistics operations, and banking, and they are related to demand forecasting, inventory management, distribution management, capacity planning, resource allocation, workforce scheduling, and service system management. For each case, a complete mapping of the case into the Data and Decision Analytics Framework was done to explain how the framework was applied to derive the data insights from data analytics, to define the business objectives, make the necessary assumptions, and then develop the solution to the business problem. This book aims at senior-year undergraduate or graduate students studying industrial engineering, business management with a focus on operations, or data science. They will learn how to use data analytics to first analyze problems to identify the root cause of problems, before developing the solutions supported by decision analytics.
650 0 $a Business logistics. $3 562973
650 0 $a Business logistics $x Decision making. $3 891976
650 0 $a Queuing theory. $3 528238
650 1 4 $a Data Science. $3 1174436
650 2 4 $a Business Analytics. $3 1387864
650 2 4 $a Operations Management. $3 1069063
650 2 4 $a Operations Research and Decision Theory. $3 1366301
650 2 4 $a Business Information Systems. $3 669204
650 2 4 $a Computer Application in Administrative Data Processing. $3 1365952
700 1 $a Ma Nang Laik. $3 1481869
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-3-031-72255-4
950 $a Professional and Applied Computing (SpringerNature-12059)