東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Analysing trends and patterns in emp...

Majumder, Soumi.

FindBook

Google Book

Amazon

博客來

Analysing trends and patterns in employee engagement through AI

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Analysing trends and patterns in employee engagement through AI/ by Soumi Majumder, Bitan Misra.
作者:	Majumder, Soumi.
其他作者:	Misra, Bitan.
出版者:	Singapore :Springer Nature Singapore : : 2025.,
面頁冊數:	xv, 75 p. :ill., digital ;24 cm.
內容註:	Introduction -- Importance of measuring employee engagement trends in organisations -- Employee engagement challenges -- Significance of Employee Engagement Levels in the Workplace -- Employee Engagement Models -- Artificial intelligence in employee engagement and retention -- Leveraging AI for Employee Engagement -- AI-powered analytics uncover hidden patterns in employee engagement data -- Predictive analytics: Anticipating future engagement trends with AI -- Ethical Considerations and Future Directions of AI in Employee Engagement.
Contained By:	Springer Nature eBook
標題:	Personnel management - Data processing. -
電子資源:	https://doi.org/10.1007/978-981-96-4496-4
ISBN:	9789819644964

Analysing trends and patterns in employee engagement through AI
Majumder, Soumi.

Analysing trends and patterns in employee engagement through AI[electronic resource] /by Soumi Majumder, Bitan Misra. - Singapore :Springer Nature Singapore :2025. - xv, 75 p. :ill., digital ;24 cm. - SpringerBriefs in applied sciences and technology. Computational intelligence,2625-3712. - SpringerBriefs in applied sciences and technology.Computational intelligence..

Introduction -- Importance of measuring employee engagement trends in organisations -- Employee engagement challenges -- Significance of Employee Engagement Levels in the Workplace -- Employee Engagement Models -- Artificial intelligence in employee engagement and retention -- Leveraging AI for Employee Engagement -- AI-powered analytics uncover hidden patterns in employee engagement data -- Predictive analytics: Anticipating future engagement trends with AI -- Ethical Considerations and Future Directions of AI in Employee Engagement.

This book explores the concept of employee engagement, which is crucial for a company's success, as it is closely linked to job satisfaction and employee morale. Engaged workers tend to be more productive, efficient, and committed to the values and objectives of the company. Artificial intelligence plays a significant role in HR analytics, particularly in automating tedious tasks like data collection and organization from multiple sources. AI-driven employee engagement software can analyze employee feedback, surveys, and social media posts to capture the overall sentiment of the workforce. This allows HR teams to gain insights into employee experiences and perceptions, uncover areas for improvement, and address any issues that require attention. By leveraging past data and employing machine learning algorithms, AI enables HR professionals to predict turnover rates, forecast employee engagement levels, and identify potential flight risks.

ISBN: 9789819644964

Standard No.: 10.1007/978-981-96-4496-4doiSubjects--Topical Terms:

648630
Personnel management
--Data processing.

LC Class. No.: HF5549.5.D37

Dewey Class. No.: 658.30028563

Analysing trends and patterns in employee engagement through AI
LDR:02606nmm a2200337 a 4500 001 2412365
003 DE-He213
005 20250725174737.0
006 m d
007 cr nn 008maaau
008 260204s2025 si s 0 eng d
020 $a 9789819644964 $q (electronic bk.)
020 $a 9789819644957 $q (paper)
024 7 $a 10.1007/978-981-96-4496-4 $2 doi
035 $a 978-981-96-4496-4
040 $a GP $c GP
041 0 $a eng
050 4 $a HF5549.5.D37
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 658.30028563 $2 23
090 $a HF5549.5.D37 $b M234 2025
100 1 $a Majumder, Soumi. $3 3595990
245 1 0 $a Analysing trends and patterns in employee engagement through AI $h [electronic resource] / $c by Soumi Majumder, Bitan Misra.
260 $a Singapore : $b Springer Nature Singapore : $b Imprint: Springer, $c 2025.
300 $a xv, 75 p. : $b ill., digital ; $c 24 cm.
490 1 $a SpringerBriefs in applied sciences and technology. Computational intelligence, $x 2625-3712
505 0 $a Introduction -- Importance of measuring employee engagement trends in organisations -- Employee engagement challenges -- Significance of Employee Engagement Levels in the Workplace -- Employee Engagement Models -- Artificial intelligence in employee engagement and retention -- Leveraging AI for Employee Engagement -- AI-powered analytics uncover hidden patterns in employee engagement data -- Predictive analytics: Anticipating future engagement trends with AI -- Ethical Considerations and Future Directions of AI in Employee Engagement.
520 $a This book explores the concept of employee engagement, which is crucial for a company's success, as it is closely linked to job satisfaction and employee morale. Engaged workers tend to be more productive, efficient, and committed to the values and objectives of the company. Artificial intelligence plays a significant role in HR analytics, particularly in automating tedious tasks like data collection and organization from multiple sources. AI-driven employee engagement software can analyze employee feedback, surveys, and social media posts to capture the overall sentiment of the workforce. This allows HR teams to gain insights into employee experiences and perceptions, uncover areas for improvement, and address any issues that require attention. By leveraging past data and employing machine learning algorithms, AI enables HR professionals to predict turnover rates, forecast employee engagement levels, and identify potential flight risks.
650 0 $a Personnel management $x Data processing. $3 648630
650 0 $a Artificial intelligence $x Business applications. $3 3785910
650 1 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Artificial Intelligence. $3 769149
650 2 4 $a Machine Learning. $3 3382522
650 2 4 $a Employee Health and Wellbeing. $3 3235926
700 1 $a Misra, Bitan. $3 3753027
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a SpringerBriefs in applied sciences and technology. $p Computational intelligence. $3 2054423
856 4 0 $u https://doi.org/10.1007/978-981-96-4496-4
950 $a Business and Management (SpringerNature-41169)