Small manufacturing businesses: meeting decision support needs

2000 ◽  
Vol 7 (3) ◽  
pp. 272-284 ◽  
Author(s):  
Yanqing Duan ◽  
Russell Kinman
Keyword(s):  
Decision Support ◽  
Support Needs

Information and decision support needs in patients with type 2 diabetes

2014 ◽  
Vol 22 (1) ◽  
pp. 46-59 ◽  
Author(s):  
Nina Weymann ◽  
Martin Härter ◽  
Jörg Dirmaier
Keyword(s):  
Type 2 Diabetes ◽  
Decision Support ◽  
Support Needs

Decision Support Systems in Small Businesses

2011 ◽  
pp. 974-977 ◽  
Author(s):  
Yanqing Duan ◽  
Mark Xu
Keyword(s):  
Decision Support ◽  
Small Business ◽  
Empirical Study ◽  
Decision Support Systems ◽  
Small Businesses ◽  
Support Systems ◽  
Manufacturing Sector ◽  
Large Body ◽  
Support Needs ◽  
The Uk

Decision support systems (DSSs) are widely used in many organisations (Arslan et al., 2004; Belecheanu et al., 2003; Dey, 2001; Gopalakrishnan et al., 2004; Lau et al., 2001; Puente et al., 2002). However, there is a common tendency to apply experience and techniques gained from large organisations directly to small businesses, without recognising the different decision support needs of the small business. This article aims to address the issues related to the development and the implementation of DSSs in small business firms. Our arguments are based on evidence drawn from a large body of DSS literature and an empirical study conducted by the authors in the UK manufacturing sector.

From Decision Making to Decision Support

2019 ◽  
Author(s):  
Frederic Adam ◽  
Ciara Heavin
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Operations Research ◽  
Human Cognition ◽  
Support Needs ◽  
Managerial Decision ◽  
Full Diversity ◽  
History Of ◽  
Research Questions ◽  
Considerable Depth

In such a complex and well-researched domain as decision support systems (DSS), with a long history of authors making insightful contributions since the 1960’s, it is critical for researchers, especially those less experienced, to have a broad knowledge of the seminal work that has been carried out by prior generations of researchers. This can serve to avoid proposing research questions which have been considered many times before, without having consideration for the answers which have been put forward by previous scholars, thereby reinventing the wheel or “rediscovering” findings about the life of organizations that have been presented long before. The study of human and managerial decision-making is also characterized by considerable depth and seminal research going back to the beginning of the 20th century, across a variety of fields of research including psychology, social psychology, sociology or indeed operations research. Inasmuch as decision-making and decision support are inextricably linked, it is essential for researchers in DSS to be very familiar with both stream of research in their full diversity so they are able to understand both what activity is being supported and how to analyze requirements for developing decision support artefacts. In addition, whilst the area of decision support has sometimes been characterized by technology-based hype, it is critical to recognize that only a clear focus on the thinking and actions of managers can provide decisive directions for research on their decision support needs. In this article, we consider first the characteristics of human cognition, before concentrating on the decision-making needs of managers and the lessons that can be derived for the development of DSS.

scholarly journals The Gray Zone: Adolescent and Young Adult Decision Support Needs for Ulcerative Colitis

2020 ◽  
Vol 5 (2) ◽  
pp. 238146832094070
Author(s):  
Andrea Meisman ◽  
Nancy M. Daraiseh ◽  
Phil Minar ◽  
Marlee Saxe ◽  
Ellen A. Lipstein
Keyword(s):  
Ulcerative Colitis ◽  
Decision Making ◽  
Decision Support ◽  
Focus Groups ◽  
Medical Decision Making ◽  
Medical Decision ◽  
Support Needs ◽  
Final Decision ◽  
Care Providers ◽  
Medical Decisions

Purpose. To understand the medical decision support needs specific to adolescents and young adults (AYAs) with ulcerative colitis (UC) and inform development of a decision support tool addressing AYAs’ preferences. Methods. We conducted focus groups with AYAs with UC and mentors from a pediatric inflammatory bowel disease clinic’s peer mentoring program. Focus groups were led by a single trained facilitator using a semistructured guide aimed at eliciting AYAs’ roles in medical decision making and perceived decision support needs. All focus groups were audio recorded, transcribed, and coded by the research team. Data were analyzed using content analysis and the immersion crystallization method. Results. The facilitator led six focus groups: one group with peer mentors aged 18 to 24 years, three groups with patients aged 14 to 17 years, and two groups with patients aged 18 to 24 years. Decision timing and those involved in decision making were identified as interacting components of treatment decision making. Treatment decisions by AYAs were further based on timing, location (inpatient v. outpatient), and family preference for making decisions during or outside of clinic. AYAs involved parents and health care providers in medical decisions, with older participants describing themselves as “final decision makers.” Knowledge and experience were facilitators identified to participating in medical decision making. Conclusions. AYAs with UC experience changes to their roles in medical decisions over time. The support needs identified will inform the development of strategies, such as decision support tools, to help AYAs with chronic conditions develop and use skills needed for participating in medical decision making.

Incorporating stakeholder decision support needs into an integrated regional Earth system model

2012 ◽  
Vol 17 (7) ◽  
pp. 805-819 ◽  
Author(s):  
J. S. Rice ◽  
R. H. Moss ◽  
P. J. Runci ◽  
K. L. Anderson ◽  
E. L. Malone
Keyword(s):  
Decision Support ◽  
Earth System Model ◽  
System Model ◽  
Support Needs ◽  
Earth System

scholarly journals Choosing a Model of Maternity Care: Decision Support Needs of Australian Women

Birth ◽  
2015 ◽  
Vol 43 (2) ◽  
pp. 167-175 ◽  
Author(s):  
Gabrielle Stevens ◽  
Yvette D. Miller ◽  
Bernadette Watson ◽  
Rachel Thompson
Keyword(s):  
Decision Support ◽  
Maternity Care ◽  
Support Needs ◽  
Care Decision

IT and Business Can Succeed in BI by Embracing Agile Methodologies

2011 ◽  
Vol 2 (3) ◽  
pp. 36-51
Author(s):  
Alex Gann
Keyword(s):  
Information Technology ◽  
Decision Support ◽  
Systems Development ◽  
Agile Development ◽  
Support Needs ◽  
Advantages And Disadvantages ◽  
Agile Methodologies ◽  
History Of ◽  
Potential Benefits

While the potential benefits from BI are vast, organizations have struggled to successfully deploy it. BI applies myriad advanced techniques, performed by the firm’s Information Technology (IT) group, to fulfill the reporting, analysis, and decision-support needs of the Lines of Business. Two of the greatest challenges in BI are accurately and continuously communicating requirements from the business to IT and quickly yet affordably delivering the requested functionality from IT to the business. Companies can overcome these challenges by embracing a prescribed set of Agile development methodologies for BI. This paper examines the history of selected systems development approaches, weighs the advantages and disadvantages of prevailing practices, and ultimately recommends a path forward to succeeding in BI through the application of Agile methodologies.

CATEGORIZATION OF DISASTER DECISION SUPPORT NEEDS FOR THE DEVELOPMENT OF AN INTEGRATED MODEL FOR DMDSS

2008 ◽  
Vol 07 (01) ◽  
pp. 115-145 ◽  
Author(s):  
SOHAIL ASGHAR ◽  
DAMMINDA ALAHAKOON ◽  
LEONID CHURILOV
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Disaster Management ◽  
Integrated Model ◽  
Model Management ◽  
Model Integration ◽  
Management Decision ◽  
Support Needs ◽  
Management Area ◽  
Disaster Scenario

The wide variety of disasters and the large number of activities involved have resulted in the demand for separate Decision Support System (DSS) models to manage different requirements. The modular approach to model management is to provide a framework in which to focus multidisciplinary research and model integration. A broader view of our approach is to provide the flexibility to organize and adapt a tailored DSS model (or existing modular subroutines) according to the dynamic needs of a disaster. For this purpose, the existing modular subroutines of DSS models are selected and integrated to produce a dynamic integrated model focussed on a given disaster scenario. In order to facilitate the effective integration of these subroutines, it is necessary to select the appropriate modular subroutine beforehand. Therefore, subroutine selection is an important preliminary step towards model integration in developing Disaster Management Decision Support Systems (DMDSS). The ability to identify a modular subroutine for a problem is an important feature before performing model integration. Generally, decision support needs are combined, and encapsulate different requirements of decision-making in the disaster management area. Categorization of decision support needs can provide the basis for such model selection to facilitate effective and efficient decision-making in disaster management. Therefore, our focus in this paper is on developing a methodology to help identify subroutines from existing DSS models developed for disaster management on the basis of needs categorization. The problem of the formulation and execution of such modular subroutines are not addressed here. Since the focus is on the selection of the modular subroutines from the existing DMDSS models on basis of a proposed needs classification scheme.

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