scholarly journals Strategic Planning Effectiveness and Leadership for Educational Institutions

2020 ◽  
pp. 83-98
Author(s):  
Aieman Ahmad Al-Omari ◽  
Keyword(s):  
Decision Making ◽  
Strategic Planning ◽  
Literature Review ◽  
Data Driven ◽  
Educational Institutions ◽  
Data Driven Decision Making ◽  
Community Needs ◽  
Future Leaders ◽  
Conducting Research

The purpose of this chapter aimed to determine strategic planning, and strategic planning effectiveness that helped to improve leadership for educational institutions. Discusses the literature review used as a methodology for conducting research on strategic planning and leadership in educational institutions. Findings of this paper related to future leaders of educational institutions may need to use data-driven decision-making skills as work continues at their school and changes are made to meet community needs. Originality/Value: Future of educational institutions leaders, should be knowledgeable of the research and data that's out there so that we keep tuned in to what different kinds of strategies are working, understanding how we evaluate what we are doing.

The business of the library is service

2017 ◽  
Vol 118 (7/8) ◽  
pp. 447-450
Author(s):  
Bruce E. Massis
Keyword(s):  
Decision Making ◽  
Literature Review ◽  
Design Methodology ◽  
Business Practice ◽  
Data Driven ◽  
Business Practices ◽  
Data Driven Decision Making ◽  
Content Type

Purpose The purpose of this paper is to suggest that today’s libraries function using business practices in its management of the library to ensure that its service-based mission is respected. Design/methodology/approach Literature review and commentary on this topic that has been addressed by professionals, researchers and practitioners. Findings Libraries have learned from business the importance of using not only the business practice of using a vigorous level of data-driven decision-making, but data-driven reporting as well to a public that expects a higher level of scrutiny, clarity and precision. Paired with evidence from those who have benefitted from the library’s programs and services most visibly, this combination of data and human-driven anecdotes can serve as the optimum marriage of business and service-based confirmation of library success. Originality/value The value in exploring this topic is to make the distinction between libraries whose supporters expect it to be formally managed like a business as opposed to those who suggest that business practices be used in library operations to ensure its mission as a service-based entity is maintained.

scholarly journals A literature review on the affective factors that influence data-driven decision-making

2021 ◽  
Author(s):  
Edmond Sebestyén
Keyword(s):  
Decision Making ◽  
Literature Review ◽  
Educational Process ◽  
Data Driven ◽  
Data Driven Decision Making ◽  
Data Literacy ◽  
Affective Factors ◽  
Affective Components ◽  
Educational Field ◽  
Systematic Collection

AbstractData-driven decision-making (DDDM) has been playing an increasing role in contemporary teaching, since it includes systematic collection, analysis, and application of data to improve students’ educational performance. However, little is known about the affective factors that influence this data-based practice. Thus, the purpose of this study was to systematically examine previous research on the affective factors that influence DDDM based on the following criteria: (1) the level of DDDM usage; (2) the emphasis of affective factors; and (3) the nature of the interventions and their effects on teachers. According to the findings, this literature review showed how little DDDM-related affective factors have been researched, even though the knowledge of DDDM can help expand its application in the educational field. For example, although the most widely used tool is the Data-Driven Decision-Making Efficacy and Anxiety Inventory (3D-MEA), which has shown promising results in terms of measuring the efficacy and development of data literacy, other affective components have yet to be tested, due to their novelty in the field. The implication of the findings is that obtaining more information about DDDM and its affective elements can help reduce teachers’ anxiety toward this approach and ultimately enhance the overall educational process.

scholarly journals Sustainable, Smart, and Sensing Technologies for Cyber-Physical Manufacturing Systems: A Systematic Literature Review

2021 ◽  
Vol 13 (10) ◽  
pp. 5495
Author(s):  
Mihai Andronie ◽  
George Lăzăroiu ◽  
Roxana Ștefănescu ◽  
Cristian Uță ◽  
Irina Dijmărescu
Keyword(s):  
Decision Making ◽  
Internet Of Things ◽  
Literature Review ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Data Driven ◽  
Smart Manufacturing ◽  
Production Networks ◽  
Production Logistics ◽  
Time Production

With growing evidence of the operational performance of cyber-physical manufacturing systems, there is a pivotal need for comprehending sustainable, smart, and sensing technologies underpinning data-driven decision-making processes. In this research, previous findings were cumulated showing that cyber-physical production networks operate automatically and smoothly with artificial intelligence-based decision-making algorithms in a sustainable manner and contribute to the literature by indicating that sustainable Internet of Things-based manufacturing systems function in an automated, robust, and flexible manner. Throughout October 2020 and April 2021, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “Internet of Things-based real-time production logistics”, “sustainable smart manufacturing”, “cyber-physical production system”, “industrial big data”, “sustainable organizational performance”, “cyber-physical smart manufacturing system”, and “sustainable Internet of Things-based manufacturing system”. As research published between 2018 and 2021 was inspected, and only 426 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, we selected 174 mainly empirical sources. Further developments should entail how cyber-physical production networks and Internet of Things-based real-time production logistics, by use of cognitive decision-making algorithms, enable the advancement of data-driven sustainable smart manufacturing.

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