SlideShare a Scribd company logo
A Pesquisa em SI sobre
       GSS é Relevante?

 Information Resources Management Journal
                Winter 1998
      Munir Mandviwalla and Paul Gray

         Sistema de Apoio à Decisão
             Prof. Jairo Dornelas

Equipe – João Gratuliano e Maria da Conceição
           16 de novembro de 2005
NEPSI
Starting Reflection


   “What information consumes is rather
  obvious: It consumes the attention of its
    recipients . . . Human attention is the
             scarcest resource.”

             Herbert A. Simon,
        economist, Nobel Prize winner


NEPSI
The Authors
Munir Mandviwalla,                   Paul Gray
founding chair of                    is Professor
the MIS                              Emeritus and
department,                          Founding
and Executive                        Chair of
Director, Irwin                      Information
L. Gross                             Science at
eBusiness                            Claremont
Institute, Fox                       Graduate
School of Business and               University. He specializes in
Management, Temple University        information systems, particularly
holds a a Ph.D. in MIS also from     decision support systems,
Claremont Graduate University. His   knowledge management, data
research interests include           warehousing and electronic
collaborative systems, electronic    commerce.
commerce strategy, and the use of
prototyping for theory development



NEPSI
GSS – Group Support Systems

  • System to provide computer and communication
    support for decision making in organizations.
  • “...facilitate formulation and solution of unstructured
    problems by a group of people” (DeSanctis and
    Gallupe)




NEPSI
Research Methodology

  • “Introspective” approach
        – Looking at the profession
        – Actual research: recent publications (1990-1995)
  • Analyze relevance in terms of:




NEPSI
Research Methodology




                                              7 (groups)

                                             13 (gss)


                                             13 (gss)

                                              4 (+2 vt)



    Actual Search (2001-2005)          Scirius – Total: 48
      (for this presentation)        Proquest – Total: 244
                                Science Direct – Total: 25
NEPSI
Research Methodology

  The journal have different rates of publications, but
  the average is relatively constant from 1990 to 1995.




NEPSI
GSS Focus and Methodology
                                Theoretical
                                                    Conceptual
        S Develop                  5%
                        S Issues         Archival     14%
           14%             3%               3%

                                                           Case Study
  S Design                                                    11%
  Frameork
     6%
             Survey
              3%                                         Field
                                                          9%

                      Lab Experiment
                           32%




NEPSI
Analysis of GSS Research




NEPSI
Action Items




NEPSI
Action Items

  GSS Research should:
  (a) Estabilish linkages to referent disciplines
  (b) Emphasize complex tasks and realistic subjects
  (c) Emphasize experiments that use similar design and that
      focus on a related topic so that results may be pooled for
      meta-analytic studies
  (d) Encourage the continued development and use of qualitative
      methodologies
  (e) Encourage theory-based and testable systems development
      research projects and methodologies
  (f) Embrace new commercially available technologies
  (g) Research systems based on different perspectives
  (h) Expand beyond face-to-face meetings



NEPSI
Prioritized List of Action Items

  (f) Embrace new commercially available
      technologies

  (h) Expand beyond face-to-face meetings

  (b) Emphasize complex tasks and realistic
      subjects

  (g) Research systems based on different
      perspectives




NEPSI
(f) Embarce new commercially
        available technologies
  • Lotus notes and others have became well know in
    industry.
  • These (researched papers) compete for niche
    markets.

  Alerts                   Created more than 10 years ago
                           (before 1988)
  The problem is that
  only few organizations
  actually use these
  systems or systems
  like that.




NEPSI
GroupSystems




NEPSI
GroupSystems meeting rooms




NEPSI
GroupSystems meeting rooms
           in Finland




NEPSI
Supporting Lightweight Customization for
             Meeting Environments




NEPSI
(h) Expand beyond face-to-face
             meetings
  • GSS resaerch has almost exclusively focused on
    text as a medium for interacton, even though,
    drawing, graphic, audio, and video technology
    have become commonplace in the industry.
  • As a result... Ignore tasks taht include illustrations,
    gestures,pattern recognition, body langue,
    emotion, and so on.
  • On 82 papers, 64 (78%) focused on face-to-face
    meeting.
  • Suggestion for NEPSI – A different interface to
    GSS using some “game” interaction (RPG, Chess,
    etc.)

NEPSI
Electronic meeting systems
                  domain




               From 2x2 (time and place)
             to 2x3x2 (time, place and size)
NEPSI
Beyond Meeting Rooms:
  Community Bar




NEPSI
(b) Emphasize complex tasks
         and realistic subjects
  • GSS research oversimplify group work
  • Simple tasks conducted in academic settings
    (opposed to business settings)
  • Interaction effects are ignored
  • Work is considered modular rather than overlaping
  • Concentrate on preference and brainstorming
    creativity tasks
  • Organizations are often reluctant to provide access
    to “real” subject or settings.
  • On 67 arcticles, 58% involved the use of students
    for subject and were conduct in academic settings.


NEPSI
Case study: EMS for Councils




NEPSI
COLAB




NEPSI
COLAB: Boardnoter




NEPSI
COLAB applications: Cognoter




NEPSI
COLAB applications: Cognoter




NEPSI
LiveBoard development: Tivoli




NEPSI
Tivoli Screen




NEPSI
Tivoli user interface




NEPSI
(g) Research systems based on
       different perspectives
  • Unfortunately most of the systems in tabe 4, follow
    a deterministic view.
  • Determinism by definition limits the scope of
    research.




NEPSI
CaptureLab




NEPSI
A chauffeured meeting




NEPSI
Executives in CaptureLab




NEPSI
Future: smart media spaces?




NEPSI
Is IS research on GSS relevant?

Yes, because:                 No, if we consider:
• IS invented the concept
   of decision rooms
• Developed HW and SW
   to implement these
   rooms
• The results of the
   research studies have
   illuminated imporant
   human aspects (i.e. role
   and use of brainstorm in
   face-to-face decion
   oriented meetings.)




 NEPSI
Discussion




NEPSI
Discussion




NEPSI
Conclusion




NEPSI
Conclusion
                                 Computer
        GSS involve
        3 sciences
                         Behavioral   Management




NEPSI
Links

• Grouplab University of Calgary – AB - Canada
    – http://grouplab.cpsc.ucalgary.ca/papers/
• Department of Computer Sciences – Groupware
  University of Tampere - Finland
  (most illustrations in this presentation)
    – http://www.cs.uta.fi/~ov/gw/intro/index.html
                                                     Saila Ovaska




NEPSI

More Related Content

What's hot

Management Information System (MIS)
Management Information System (MIS)Management Information System (MIS)
Management Information System (MIS)
Navneet Jingar
 
Introduction to databases
Introduction to databasesIntroduction to databases
Introduction to databases
Aashima Wadhwa
 
House Price Prediction Using Machine Learning
House Price Prediction Using Machine LearningHouse Price Prediction Using Machine Learning
House Price Prediction Using Machine Learning
IRJET Journal
 
Gdss
GdssGdss
Planning, design and implementation of information systems
Planning, design and implementation of information systemsPlanning, design and implementation of information systems
Planning, design and implementation of information systems
Online
 
Entity relationship diagram (erd)
Entity relationship diagram (erd)Entity relationship diagram (erd)
Entity relationship diagram (erd)
tameemyousaf
 
Applying eTOM (enhanced Telecom Operations Map) Framework to Non-Telecommunic...
Applying eTOM (enhanced Telecom Operations Map) Framework to Non-Telecommunic...Applying eTOM (enhanced Telecom Operations Map) Framework to Non-Telecommunic...
Applying eTOM (enhanced Telecom Operations Map) Framework to Non-Telecommunic...
Alan McSweeney
 
3 pillars of big data : structured data, semi structured data and unstructure...
3 pillars of big data : structured data, semi structured data and unstructure...3 pillars of big data : structured data, semi structured data and unstructure...
3 pillars of big data : structured data, semi structured data and unstructure...
PROWEBSCRAPER
 
Mis model
Mis modelMis model
Mis model
JananiSelvaraj10
 
Management Information System (Full Notes)
Management Information System (Full Notes)Management Information System (Full Notes)
Management Information System (Full Notes)
Harish Chand
 
Managing data resources
Managing  data resourcesManaging  data resources
Managing data resources
Prof. Othman Alsalloum
 
ITSM and Service Catalog Overview
ITSM and Service Catalog OverviewITSM and Service Catalog Overview
ITSM and Service Catalog Overview
Christopher Glennon
 
Orchestration and provisioning architecture for effective service management
Orchestration and provisioning architecture for effective service managementOrchestration and provisioning architecture for effective service management
Orchestration and provisioning architecture for effective service management
Alan McSweeney
 
Decision tree- System analysis and design
Decision tree- System analysis and designDecision tree- System analysis and design
Decision tree- System analysis and design
Prof.Nilesh Magar
 
e-Zest Remote Infrastructure Management Services (RIM) Services
e-Zest Remote Infrastructure Management Services (RIM) Servicese-Zest Remote Infrastructure Management Services (RIM) Services
e-Zest Remote Infrastructure Management Services (RIM) Services
e-Zest Solutions
 
1st know the features & functions of information systems
1st know the features & functions of information systems1st know the features & functions of information systems
1st know the features & functions of information systems
Bronte666
 
Management Information Technology - Chapter 1
Management Information Technology - Chapter 1Management Information Technology - Chapter 1
Management Information Technology - Chapter 1
Joel Briza
 
Kunalhasija CMDB & ITIL
Kunalhasija CMDB & ITILKunalhasija CMDB & ITIL
Kunalhasija CMDB & ITIL
Kunal Hasija
 
Big Data: Issues and Challenges
Big Data: Issues and ChallengesBig Data: Issues and Challenges
Big Data: Issues and Challenges
Harsh Kishore Mishra
 
Capturing Data Requirements
Capturing Data RequirementsCapturing Data Requirements
Capturing Data Requirements
mcomtraining
 

What's hot (20)

Management Information System (MIS)
Management Information System (MIS)Management Information System (MIS)
Management Information System (MIS)
 
Introduction to databases
Introduction to databasesIntroduction to databases
Introduction to databases
 
House Price Prediction Using Machine Learning
House Price Prediction Using Machine LearningHouse Price Prediction Using Machine Learning
House Price Prediction Using Machine Learning
 
Gdss
GdssGdss
Gdss
 
Planning, design and implementation of information systems
Planning, design and implementation of information systemsPlanning, design and implementation of information systems
Planning, design and implementation of information systems
 
Entity relationship diagram (erd)
Entity relationship diagram (erd)Entity relationship diagram (erd)
Entity relationship diagram (erd)
 
Applying eTOM (enhanced Telecom Operations Map) Framework to Non-Telecommunic...
Applying eTOM (enhanced Telecom Operations Map) Framework to Non-Telecommunic...Applying eTOM (enhanced Telecom Operations Map) Framework to Non-Telecommunic...
Applying eTOM (enhanced Telecom Operations Map) Framework to Non-Telecommunic...
 
3 pillars of big data : structured data, semi structured data and unstructure...
3 pillars of big data : structured data, semi structured data and unstructure...3 pillars of big data : structured data, semi structured data and unstructure...
3 pillars of big data : structured data, semi structured data and unstructure...
 
Mis model
Mis modelMis model
Mis model
 
Management Information System (Full Notes)
Management Information System (Full Notes)Management Information System (Full Notes)
Management Information System (Full Notes)
 
Managing data resources
Managing  data resourcesManaging  data resources
Managing data resources
 
ITSM and Service Catalog Overview
ITSM and Service Catalog OverviewITSM and Service Catalog Overview
ITSM and Service Catalog Overview
 
Orchestration and provisioning architecture for effective service management
Orchestration and provisioning architecture for effective service managementOrchestration and provisioning architecture for effective service management
Orchestration and provisioning architecture for effective service management
 
Decision tree- System analysis and design
Decision tree- System analysis and designDecision tree- System analysis and design
Decision tree- System analysis and design
 
e-Zest Remote Infrastructure Management Services (RIM) Services
e-Zest Remote Infrastructure Management Services (RIM) Servicese-Zest Remote Infrastructure Management Services (RIM) Services
e-Zest Remote Infrastructure Management Services (RIM) Services
 
1st know the features & functions of information systems
1st know the features & functions of information systems1st know the features & functions of information systems
1st know the features & functions of information systems
 
Management Information Technology - Chapter 1
Management Information Technology - Chapter 1Management Information Technology - Chapter 1
Management Information Technology - Chapter 1
 
Kunalhasija CMDB & ITIL
Kunalhasija CMDB & ITILKunalhasija CMDB & ITIL
Kunalhasija CMDB & ITIL
 
Big Data: Issues and Challenges
Big Data: Issues and ChallengesBig Data: Issues and Challenges
Big Data: Issues and Challenges
 
Capturing Data Requirements
Capturing Data RequirementsCapturing Data Requirements
Capturing Data Requirements
 

Viewers also liked

Group decision support systems (gdss)
Group decision support systems (gdss)Group decision support systems (gdss)
Group decision support systems (gdss)
Mihir joshi
 
2. information system
2. information system2. information system
2. information system
PIRAGASHMURUGAN
 
Decision Making in an Organization
Decision Making in an OrganizationDecision Making in an Organization
Decision Making in an Organization
ed gbargaye
 
I.C.T notes
I.C.T notesI.C.T notes
I.C.T notes
Abacheng Ghadafi
 
Information And Decision Support System
Information And Decision Support SystemInformation And Decision Support System
Information And Decision Support System
megat zainurul anuar
 
Decision Support System - Management Information System
Decision Support System - Management Information SystemDecision Support System - Management Information System
Decision Support System - Management Information System
Nijaz N
 
Chapter 1-introduction to ict
Chapter 1-introduction to ictChapter 1-introduction to ict
Chapter 1-introduction to ict
Aten Kecik
 
Ict ppt
Ict pptIct ppt
ICT in Education
ICT in EducationICT in Education
ICT in Education
Ollie Bray
 
Types Of Information Systems
Types Of Information SystemsTypes Of Information Systems
Types Of Information Systems
Manuel Ardales
 
Network Effects
Network EffectsNetwork Effects
Network Effects
a16z
 

Viewers also liked (11)

Group decision support systems (gdss)
Group decision support systems (gdss)Group decision support systems (gdss)
Group decision support systems (gdss)
 
2. information system
2. information system2. information system
2. information system
 
Decision Making in an Organization
Decision Making in an OrganizationDecision Making in an Organization
Decision Making in an Organization
 
I.C.T notes
I.C.T notesI.C.T notes
I.C.T notes
 
Information And Decision Support System
Information And Decision Support SystemInformation And Decision Support System
Information And Decision Support System
 
Decision Support System - Management Information System
Decision Support System - Management Information SystemDecision Support System - Management Information System
Decision Support System - Management Information System
 
Chapter 1-introduction to ict
Chapter 1-introduction to ictChapter 1-introduction to ict
Chapter 1-introduction to ict
 
Ict ppt
Ict pptIct ppt
Ict ppt
 
ICT in Education
ICT in EducationICT in Education
ICT in Education
 
Types Of Information Systems
Types Of Information SystemsTypes Of Information Systems
Types Of Information Systems
 
Network Effects
Network EffectsNetwork Effects
Network Effects
 

Similar to Group Support Systems - GSS

Scientific Information Management at the U.S. Geological Survey
Scientific Information Management at the U.S. Geological SurveyScientific Information Management at the U.S. Geological Survey
Scientific Information Management at the U.S. Geological Survey
Dave Govoni
 
Requirements Engineering Research: How good are we at solving practical prob...
Requirements Engineering Research:  How good are we at solving practical prob...Requirements Engineering Research:  How good are we at solving practical prob...
Requirements Engineering Research: How good are we at solving practical prob...
Daniel Mendez
 
Progressive focusing and trustworthiness in qualitative research: The enablin...
Progressive focusing and trustworthiness in qualitative research: The enablin...Progressive focusing and trustworthiness in qualitative research: The enablin...
Progressive focusing and trustworthiness in qualitative research: The enablin...
University of Glasgow
 
Sustainable Group Housing Projects: Setting Up a Methodological and Substant...
Sustainable Group Housing Projects:  Setting Up a Methodological and Substant...Sustainable Group Housing Projects:  Setting Up a Methodological and Substant...
Sustainable Group Housing Projects: Setting Up a Methodological and Substant...
DS2BE
 
Data Science for Every Student at RPI
Data Science for Every Student at RPIData Science for Every Student at RPI
Data Science for Every Student at RPI
Steven Miller
 
Ml pluss ejan2013
Ml pluss ejan2013Ml pluss ejan2013
Ml pluss ejan2013
CS, NcState
 
DBR (Design-Based Research) in mobile learning-Mlearn2013 Doha A_Palalas C_G...
DBR (Design-Based Research) in mobile learning-Mlearn2013 Doha  A_Palalas C_G...DBR (Design-Based Research) in mobile learning-Mlearn2013 Doha  A_Palalas C_G...
DBR (Design-Based Research) in mobile learning-Mlearn2013 Doha A_Palalas C_G...
Agnieszka (Aga) Palalas, Ed.D.
 
Action research for_librarians_carl2012
Action research for_librarians_carl2012Action research for_librarians_carl2012
Action research for_librarians_carl2012
srosenblatt
 
OAI7 Research Objects
OAI7 Research ObjectsOAI7 Research Objects
OAI7 Research Objects
seanb
 
Action research for_librarians_carl2012
Action research for_librarians_carl2012Action research for_librarians_carl2012
Action research for_librarians_carl2012
srosenblatt
 
Research methods
Research methodsResearch methods
Research methods
agribusinessclass
 
Bannan aect2012
Bannan aect2012Bannan aect2012
Bannan aect2012
Brenda Bannan, Ph.D.
 
Linking Knowledge with Action for Sustainable Development - William C. Clark
Linking Knowledge with Action for Sustainable Development - William C. ClarkLinking Knowledge with Action for Sustainable Development - William C. Clark
Linking Knowledge with Action for Sustainable Development - William C. Clark
CCAFS | CGIAR Research Program on Climate Change, Agriculture and Food Security
 
NUS PhD e-open day 2020
NUS PhD e-open day 2020NUS PhD e-open day 2020
NUS PhD e-open day 2020
Abhik Roychoudhury
 
Research trends qualitative analysis in cscl
Research trends  qualitative analysis in csclResearch trends  qualitative analysis in cscl
Research trends qualitative analysis in cscl
Merlien Institute
 
Holmes "Institutional Infrastructure for Data Sharing"
Holmes "Institutional Infrastructure for Data Sharing"Holmes "Institutional Infrastructure for Data Sharing"
Holmes "Institutional Infrastructure for Data Sharing"
National Information Standards Organization (NISO)
 
Paul Henning Krogh A New Dawn For E Collaboration In Science
Paul Henning Krogh   A New Dawn For E Collaboration In SciencePaul Henning Krogh   A New Dawn For E Collaboration In Science
Paul Henning Krogh A New Dawn For E Collaboration In Science
Vincenzo Barone
 
Defense questions, Prof. Venter
Defense questions, Prof. VenterDefense questions, Prof. Venter
Defense questions, Prof. Venter
University of Eastern Finland, IMPDET-LE
 
A Pragmatic Perspective on Software Visualization
A Pragmatic Perspective on Software VisualizationA Pragmatic Perspective on Software Visualization
A Pragmatic Perspective on Software Visualization
Arie van Deursen
 
Linked Open Data: Combining Data for the Social Sciences and Humanities (and ...
Linked Open Data: Combining Data for the Social Sciences and Humanities (and ...Linked Open Data: Combining Data for the Social Sciences and Humanities (and ...
Linked Open Data: Combining Data for the Social Sciences and Humanities (and ...
Richard Zijdeman
 

Similar to Group Support Systems - GSS (20)

Scientific Information Management at the U.S. Geological Survey
Scientific Information Management at the U.S. Geological SurveyScientific Information Management at the U.S. Geological Survey
Scientific Information Management at the U.S. Geological Survey
 
Requirements Engineering Research: How good are we at solving practical prob...
Requirements Engineering Research:  How good are we at solving practical prob...Requirements Engineering Research:  How good are we at solving practical prob...
Requirements Engineering Research: How good are we at solving practical prob...
 
Progressive focusing and trustworthiness in qualitative research: The enablin...
Progressive focusing and trustworthiness in qualitative research: The enablin...Progressive focusing and trustworthiness in qualitative research: The enablin...
Progressive focusing and trustworthiness in qualitative research: The enablin...
 
Sustainable Group Housing Projects: Setting Up a Methodological and Substant...
Sustainable Group Housing Projects:  Setting Up a Methodological and Substant...Sustainable Group Housing Projects:  Setting Up a Methodological and Substant...
Sustainable Group Housing Projects: Setting Up a Methodological and Substant...
 
Data Science for Every Student at RPI
Data Science for Every Student at RPIData Science for Every Student at RPI
Data Science for Every Student at RPI
 
Ml pluss ejan2013
Ml pluss ejan2013Ml pluss ejan2013
Ml pluss ejan2013
 
DBR (Design-Based Research) in mobile learning-Mlearn2013 Doha A_Palalas C_G...
DBR (Design-Based Research) in mobile learning-Mlearn2013 Doha  A_Palalas C_G...DBR (Design-Based Research) in mobile learning-Mlearn2013 Doha  A_Palalas C_G...
DBR (Design-Based Research) in mobile learning-Mlearn2013 Doha A_Palalas C_G...
 
Action research for_librarians_carl2012
Action research for_librarians_carl2012Action research for_librarians_carl2012
Action research for_librarians_carl2012
 
OAI7 Research Objects
OAI7 Research ObjectsOAI7 Research Objects
OAI7 Research Objects
 
Action research for_librarians_carl2012
Action research for_librarians_carl2012Action research for_librarians_carl2012
Action research for_librarians_carl2012
 
Research methods
Research methodsResearch methods
Research methods
 
Bannan aect2012
Bannan aect2012Bannan aect2012
Bannan aect2012
 
Linking Knowledge with Action for Sustainable Development - William C. Clark
Linking Knowledge with Action for Sustainable Development - William C. ClarkLinking Knowledge with Action for Sustainable Development - William C. Clark
Linking Knowledge with Action for Sustainable Development - William C. Clark
 
NUS PhD e-open day 2020
NUS PhD e-open day 2020NUS PhD e-open day 2020
NUS PhD e-open day 2020
 
Research trends qualitative analysis in cscl
Research trends  qualitative analysis in csclResearch trends  qualitative analysis in cscl
Research trends qualitative analysis in cscl
 
Holmes "Institutional Infrastructure for Data Sharing"
Holmes "Institutional Infrastructure for Data Sharing"Holmes "Institutional Infrastructure for Data Sharing"
Holmes "Institutional Infrastructure for Data Sharing"
 
Paul Henning Krogh A New Dawn For E Collaboration In Science
Paul Henning Krogh   A New Dawn For E Collaboration In SciencePaul Henning Krogh   A New Dawn For E Collaboration In Science
Paul Henning Krogh A New Dawn For E Collaboration In Science
 
Defense questions, Prof. Venter
Defense questions, Prof. VenterDefense questions, Prof. Venter
Defense questions, Prof. Venter
 
A Pragmatic Perspective on Software Visualization
A Pragmatic Perspective on Software VisualizationA Pragmatic Perspective on Software Visualization
A Pragmatic Perspective on Software Visualization
 
Linked Open Data: Combining Data for the Social Sciences and Humanities (and ...
Linked Open Data: Combining Data for the Social Sciences and Humanities (and ...Linked Open Data: Combining Data for the Social Sciences and Humanities (and ...
Linked Open Data: Combining Data for the Social Sciences and Humanities (and ...
 

Recently uploaded

20240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 202420240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 2024
Matthew Sinclair
 
How to use Firebase Data Connect For Flutter
How to use Firebase Data Connect For FlutterHow to use Firebase Data Connect For Flutter
How to use Firebase Data Connect For Flutter
Daiki Mogmet Ito
 
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Albert Hoitingh
 
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
Neo4j
 
UiPath Test Automation using UiPath Test Suite series, part 5
UiPath Test Automation using UiPath Test Suite series, part 5UiPath Test Automation using UiPath Test Suite series, part 5
UiPath Test Automation using UiPath Test Suite series, part 5
DianaGray10
 
20 Comprehensive Checklist of Designing and Developing a Website
20 Comprehensive Checklist of Designing and Developing a Website20 Comprehensive Checklist of Designing and Developing a Website
20 Comprehensive Checklist of Designing and Developing a Website
Pixlogix Infotech
 
Introduction to CHERI technology - Cybersecurity
Introduction to CHERI technology - CybersecurityIntroduction to CHERI technology - Cybersecurity
Introduction to CHERI technology - Cybersecurity
mikeeftimakis1
 
Full-RAG: A modern architecture for hyper-personalization
Full-RAG: A modern architecture for hyper-personalizationFull-RAG: A modern architecture for hyper-personalization
Full-RAG: A modern architecture for hyper-personalization
Zilliz
 
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AI
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIEnchancing adoption of Open Source Libraries. A case study on Albumentations.AI
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AI
Vladimir Iglovikov, Ph.D.
 
Artificial Intelligence for XMLDevelopment
Artificial Intelligence for XMLDevelopmentArtificial Intelligence for XMLDevelopment
Artificial Intelligence for XMLDevelopment
Octavian Nadolu
 
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfObservability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Paige Cruz
 
Microsoft - Power Platform_G.Aspiotis.pdf
Microsoft - Power Platform_G.Aspiotis.pdfMicrosoft - Power Platform_G.Aspiotis.pdf
Microsoft - Power Platform_G.Aspiotis.pdf
Uni Systems S.M.S.A.
 
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with SlackLet's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
shyamraj55
 
Building RAG with self-deployed Milvus vector database and Snowpark Container...
Building RAG with self-deployed Milvus vector database and Snowpark Container...Building RAG with self-deployed Milvus vector database and Snowpark Container...
Building RAG with self-deployed Milvus vector database and Snowpark Container...
Zilliz
 
Presentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of GermanyPresentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of Germany
innovationoecd
 
TrustArc Webinar - 2024 Global Privacy Survey
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc Webinar - 2024 Global Privacy Survey
TrustArc Webinar - 2024 Global Privacy Survey
TrustArc
 
Large Language Model (LLM) and it’s Geospatial Applications
Large Language Model (LLM) and it’s Geospatial ApplicationsLarge Language Model (LLM) and it’s Geospatial Applications
Large Language Model (LLM) and it’s Geospatial Applications
Rohit Gautam
 
Climate Impact of Software Testing at Nordic Testing Days
Climate Impact of Software Testing at Nordic Testing DaysClimate Impact of Software Testing at Nordic Testing Days
Climate Impact of Software Testing at Nordic Testing Days
Kari Kakkonen
 
PCI PIN Basics Webinar from the Controlcase Team
PCI PIN Basics Webinar from the Controlcase TeamPCI PIN Basics Webinar from the Controlcase Team
PCI PIN Basics Webinar from the Controlcase Team
ControlCase
 
Data structures and Algorithms in Python.pdf
Data structures and Algorithms in Python.pdfData structures and Algorithms in Python.pdf
Data structures and Algorithms in Python.pdf
TIPNGVN2
 

Recently uploaded (20)

20240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 202420240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 2024
 
How to use Firebase Data Connect For Flutter
How to use Firebase Data Connect For FlutterHow to use Firebase Data Connect For Flutter
How to use Firebase Data Connect For Flutter
 
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
 
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
 
UiPath Test Automation using UiPath Test Suite series, part 5
UiPath Test Automation using UiPath Test Suite series, part 5UiPath Test Automation using UiPath Test Suite series, part 5
UiPath Test Automation using UiPath Test Suite series, part 5
 
20 Comprehensive Checklist of Designing and Developing a Website
20 Comprehensive Checklist of Designing and Developing a Website20 Comprehensive Checklist of Designing and Developing a Website
20 Comprehensive Checklist of Designing and Developing a Website
 
Introduction to CHERI technology - Cybersecurity
Introduction to CHERI technology - CybersecurityIntroduction to CHERI technology - Cybersecurity
Introduction to CHERI technology - Cybersecurity
 
Full-RAG: A modern architecture for hyper-personalization
Full-RAG: A modern architecture for hyper-personalizationFull-RAG: A modern architecture for hyper-personalization
Full-RAG: A modern architecture for hyper-personalization
 
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AI
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIEnchancing adoption of Open Source Libraries. A case study on Albumentations.AI
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AI
 
Artificial Intelligence for XMLDevelopment
Artificial Intelligence for XMLDevelopmentArtificial Intelligence for XMLDevelopment
Artificial Intelligence for XMLDevelopment
 
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfObservability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
 
Microsoft - Power Platform_G.Aspiotis.pdf
Microsoft - Power Platform_G.Aspiotis.pdfMicrosoft - Power Platform_G.Aspiotis.pdf
Microsoft - Power Platform_G.Aspiotis.pdf
 
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with SlackLet's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
 
Building RAG with self-deployed Milvus vector database and Snowpark Container...
Building RAG with self-deployed Milvus vector database and Snowpark Container...Building RAG with self-deployed Milvus vector database and Snowpark Container...
Building RAG with self-deployed Milvus vector database and Snowpark Container...
 
Presentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of GermanyPresentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of Germany
 
TrustArc Webinar - 2024 Global Privacy Survey
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc Webinar - 2024 Global Privacy Survey
TrustArc Webinar - 2024 Global Privacy Survey
 
Large Language Model (LLM) and it’s Geospatial Applications
Large Language Model (LLM) and it’s Geospatial ApplicationsLarge Language Model (LLM) and it’s Geospatial Applications
Large Language Model (LLM) and it’s Geospatial Applications
 
Climate Impact of Software Testing at Nordic Testing Days
Climate Impact of Software Testing at Nordic Testing DaysClimate Impact of Software Testing at Nordic Testing Days
Climate Impact of Software Testing at Nordic Testing Days
 
PCI PIN Basics Webinar from the Controlcase Team
PCI PIN Basics Webinar from the Controlcase TeamPCI PIN Basics Webinar from the Controlcase Team
PCI PIN Basics Webinar from the Controlcase Team
 
Data structures and Algorithms in Python.pdf
Data structures and Algorithms in Python.pdfData structures and Algorithms in Python.pdf
Data structures and Algorithms in Python.pdf
 

Group Support Systems - GSS

  • 1. A Pesquisa em SI sobre GSS é Relevante? Information Resources Management Journal Winter 1998 Munir Mandviwalla and Paul Gray Sistema de Apoio à Decisão Prof. Jairo Dornelas Equipe – João Gratuliano e Maria da Conceição 16 de novembro de 2005 NEPSI
  • 2. Starting Reflection “What information consumes is rather obvious: It consumes the attention of its recipients . . . Human attention is the scarcest resource.” Herbert A. Simon, economist, Nobel Prize winner NEPSI
  • 3. The Authors Munir Mandviwalla, Paul Gray founding chair of is Professor the MIS Emeritus and department, Founding and Executive Chair of Director, Irwin Information L. Gross Science at eBusiness Claremont Institute, Fox Graduate School of Business and University. He specializes in Management, Temple University information systems, particularly holds a a Ph.D. in MIS also from decision support systems, Claremont Graduate University. His knowledge management, data research interests include warehousing and electronic collaborative systems, electronic commerce. commerce strategy, and the use of prototyping for theory development NEPSI
  • 4. GSS – Group Support Systems • System to provide computer and communication support for decision making in organizations. • “...facilitate formulation and solution of unstructured problems by a group of people” (DeSanctis and Gallupe) NEPSI
  • 5. Research Methodology • “Introspective” approach – Looking at the profession – Actual research: recent publications (1990-1995) • Analyze relevance in terms of: NEPSI
  • 6. Research Methodology 7 (groups) 13 (gss) 13 (gss) 4 (+2 vt) Actual Search (2001-2005) Scirius – Total: 48 (for this presentation) Proquest – Total: 244 Science Direct – Total: 25 NEPSI
  • 7. Research Methodology The journal have different rates of publications, but the average is relatively constant from 1990 to 1995. NEPSI
  • 8. GSS Focus and Methodology Theoretical Conceptual S Develop 5% S Issues Archival 14% 14% 3% 3% Case Study S Design 11% Frameork 6% Survey 3% Field 9% Lab Experiment 32% NEPSI
  • 9. Analysis of GSS Research NEPSI
  • 11. Action Items GSS Research should: (a) Estabilish linkages to referent disciplines (b) Emphasize complex tasks and realistic subjects (c) Emphasize experiments that use similar design and that focus on a related topic so that results may be pooled for meta-analytic studies (d) Encourage the continued development and use of qualitative methodologies (e) Encourage theory-based and testable systems development research projects and methodologies (f) Embrace new commercially available technologies (g) Research systems based on different perspectives (h) Expand beyond face-to-face meetings NEPSI
  • 12. Prioritized List of Action Items (f) Embrace new commercially available technologies (h) Expand beyond face-to-face meetings (b) Emphasize complex tasks and realistic subjects (g) Research systems based on different perspectives NEPSI
  • 13. (f) Embarce new commercially available technologies • Lotus notes and others have became well know in industry. • These (researched papers) compete for niche markets. Alerts Created more than 10 years ago (before 1988) The problem is that only few organizations actually use these systems or systems like that. NEPSI
  • 16. GroupSystems meeting rooms in Finland NEPSI
  • 17. Supporting Lightweight Customization for Meeting Environments NEPSI
  • 18. (h) Expand beyond face-to-face meetings • GSS resaerch has almost exclusively focused on text as a medium for interacton, even though, drawing, graphic, audio, and video technology have become commonplace in the industry. • As a result... Ignore tasks taht include illustrations, gestures,pattern recognition, body langue, emotion, and so on. • On 82 papers, 64 (78%) focused on face-to-face meeting. • Suggestion for NEPSI – A different interface to GSS using some “game” interaction (RPG, Chess, etc.) NEPSI
  • 19. Electronic meeting systems domain From 2x2 (time and place) to 2x3x2 (time, place and size) NEPSI
  • 20. Beyond Meeting Rooms: Community Bar NEPSI
  • 21. (b) Emphasize complex tasks and realistic subjects • GSS research oversimplify group work • Simple tasks conducted in academic settings (opposed to business settings) • Interaction effects are ignored • Work is considered modular rather than overlaping • Concentrate on preference and brainstorming creativity tasks • Organizations are often reluctant to provide access to “real” subject or settings. • On 67 arcticles, 58% involved the use of students for subject and were conduct in academic settings. NEPSI
  • 22. Case study: EMS for Councils NEPSI
  • 30. (g) Research systems based on different perspectives • Unfortunately most of the systems in tabe 4, follow a deterministic view. • Determinism by definition limits the scope of research. NEPSI
  • 34. Future: smart media spaces? NEPSI
  • 35. Is IS research on GSS relevant? Yes, because: No, if we consider: • IS invented the concept of decision rooms • Developed HW and SW to implement these rooms • The results of the research studies have illuminated imporant human aspects (i.e. role and use of brainstorm in face-to-face decion oriented meetings.) NEPSI
  • 39. Conclusion Computer GSS involve 3 sciences Behavioral Management NEPSI
  • 40. Links • Grouplab University of Calgary – AB - Canada – http://grouplab.cpsc.ucalgary.ca/papers/ • Department of Computer Sciences – Groupware University of Tampere - Finland (most illustrations in this presentation) – http://www.cs.uta.fi/~ov/gw/intro/index.html Saila Ovaska NEPSI