scholarly journals Data-Driven Decision-Making

2021 ◽  
pp. 47-59
Author(s):  
Sophie J. Barbu ◽  
Karen McDonald ◽  
Lisceth Brazil-Cruz ◽  
Lisa Sullivan ◽  
Linda F. Bisson

AbstractAddressing barriers to inclusion requires understanding the nature of the problem at the institutional level. Data collection and assessment are both crucial for this aim. In this chapter, we describe two important classes of data: (1) data on diversity that define the potential nature of the issues at stake and the need for change, and (2) data on assessing the usefulness of new programs, processes, and policies in creating a more diverse institution. Both sets of data are important for effective decision-making. At the same time, data analyses can be challenging because issues of equity and inclusion are complex and determining the basis of comparison or the “ideal” diversity target can be difficult. Nevertheless, data gathering and analysis are critical to assess progress and to provide a basis for both accountability and efficacy. Moreover, the ability to document that a problem indeed exists will help justify the need for change and, ideally, spur corrective action.

Author(s):  
András Sajó ◽  
Renáta Uitz

This chapter examines the relationship between parliamentarism and the legislative branch. It explores the evolution of the legislative branch, leading to disillusionment with the rationalized law-making factory, a venture run by political parties beyond the reach of constitutional rules. The rise of democratically bred party rule is positioned between the forces favouring free debate versus effective decision-making in the legislature. The chapter analyses the institutional make-up and internal operations of the legislature, the role of the opposition in the legislative assembly, and explores the benefits of bicameralism for boosting the powers of the legislative branch. Finally, it looks at the law-making process and its outsourcing via delegating legislative powers to the executive.


2013 ◽  
Vol 28 (3) ◽  
pp. 577-587 ◽  
Author(s):  
Donghyun Kim ◽  
Deying Li ◽  
Omid Asgari ◽  
Yingshu Li ◽  
Alade O. Tokuta ◽  
...  

2005 ◽  
Vol 11 (1) ◽  
pp. 133-166
Author(s):  
M. Iqbal

ABSTRACTIn the recent past life companies have made many decisions which they have had cause to deeply regret. This paper looks at the range of decision making theories available. It then examines recent examples of decisions that had unfavourable consequences and explores why they were taken, and goes on to describe a systematic approach to decision making which can help management assess more objectively the difficult choices confronting them today. The approach does not require espousal of any specific decision theory or method of value measurement. The focus is on the decision making process and the organisation's capacity to handle change. The paper identifies the three requirements for effective decision making.


2011 ◽  
Vol 225-226 ◽  
pp. 407-410 ◽  
Author(s):  
Wan Qing Li ◽  
Mu Jie Chen ◽  
Wen Qing Meng

An unascertained measure-entropy evaluation model for the program selection of shaft construction under complex conditions is established so that a scientific and effective decision making method is provided in this paper, the evaluation model of shaft construction is established based on unascertained measure and entropy weight theory, then, the model proposed in this paper is applied to evaluate three shaft construction program comprehensively, and the evaluation results show validity and applicability of the model.


Author(s):  
Raj Veeramani ◽  
Narayanan Viswanathan ◽  
Shailesh M. Joshi

Abstract New approaches for decision making are emerging to support the use of the Internet for supply-web interactions in the manufacturing industry. In this paper, we discuss one such paradigm, namely similarity-based decision support. It recognizes that knowledge of similar experiences can support rapid and effective decision making in various forms of supply-web interactions. We illustrate this approach using two prototype systems, WebScout (an agent-based system for customer–supplier matchmaking in the job-shop machining industry context) and TOME (Treasury of Manufacturing Experiences — an Intranet application to aid manufacturability assessment in foundries).


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