scholarly journals Integrated Decision Support Systems (IDSS) for Dairy Farming: A Discussion on How to Improve Their Sustained Adoption

Animals ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 2025
Author(s):  
Michel Baldin ◽  
Tom Breunig ◽  
Roger Cue ◽  
Albert De Vries ◽  
Mark Doornink ◽  
...  
Keyword(s):  
Decision Support ◽  
Data Collection ◽  
Decision Support Systems ◽  
Support Systems ◽  
Dairy Farm ◽  
Ease Of Use ◽  
Barriers To Adoption ◽  
Production And Distribution ◽  
Collection Data ◽  
Decision Making Processes

Dairy farm decision support systems (DSS) are tools which help dairy farmers to solve complex problems by improving the decision-making processes. In this paper, we are interested in newer generation, integrated DSS (IDSS), which additionally and concurrently: (1) receive continuous data feed from on-farm and off-farm data collection systems and (2) integrate more than one data stream to produce insightful outcomes. The scientific community and the allied dairy community have not been successful in developing, disseminating, and promoting a sustained adoption of IDSS. Thus, this paper identifies barriers to adoption as well as factors that would promote the sustained adoption of IDSS. The main barriers to adoption discussed include perceived lack of a good value proposition, complexities of practical application, and ease of use; and IDSS challenges related to data collection, data standards, data integration, and data shareability. Success in the sustainable adoption of IDSS depends on solving these problems and also addressing intrinsic issues related to the development, maintenance, and functioning of IDSS. There is a need for coordinated action by all the main stakeholders in the dairy sector to realize the potential benefits of IDSS, including all important players in the dairy industry production and distribution chain.

The Role of Decision Support Systems (DSS) in Planning For Improved Water Quality in Coastal Lakes

2011 ◽  
pp. 47-73 ◽  
Author(s):  
R. A. Kelly ◽  
W. S. Merritt
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Juvenile Fish ◽  
Ease Of Use ◽  
Coastal Lakes ◽  
Management Actions ◽  
Trade Offs ◽  
Decision Making Processes

Coastal lakes are ecosystems which provide significant environmental, social and economic values. They are a key habitat for many aquatic species, particularly for juvenile fish and aquatic invertebrates. They are a focus for human activity, including recreation, tourism, and many forms of industry and production such as oyster and commercial fisheries. More and more the foreshore areas of lakes are seen as a desirable place to live, with urban development a key pressure on lake systems. However current development, use and management of these systems mean that these values are already under threat. Environmental managers, urban planners and other decision makers need to make complex decisions about patterns of current and future use of these systems which allow for the trade-offs associated with various activities to be effectively taken into account. Decision support systems (DSS) are seen to have a role to play in supporting these activities.When developed properly, DSS can support decision making processes by providing users with a tool that shows the relationships between drivers of a system and outcomes. Environmental outcomes (e.g. estuary health) are controlled by often complex biophysical, ecological, economic and/or social drivers and processes. In this context a DSS should address uncertainty in data, knowledge and predictions, and allow users to explore the sensitivity of outcomes to controllable drivers (e.g. management actions), uncontrollable drivers (e.g. climate variability) and uncertainty. The DSS development and adoption process also needs to be flexible to a changing decision making environment. Ultimately the success of any DSS will depend not only on its technical capacity, including the robustness of any science underlying it, or the ease of use of any interface but also on the circumstances into which it arrives: the time and money allowed for training, capacity building, incorporation of stakeholder comments and development of trust between DSS developers, scientists and the community; the way in which the DSS is embedded in the decision making process; and the ‘politics’ and constantly changing face of the decision making environment.This chapter will discuss issues regarding the development of a DSS under typical planning timeframes where there are limited resources (time and budgetary) and where current and future management issues may not be certain and/or may change over the planning timeframe. The chapter largely draws on experiences gained during the development and application of the CAPER DSS in the Great Lakes, NSW Australia.

Decision Support Systems and Decision-Making Processes

2010 ◽  
pp. 135-143 ◽  
Author(s):  
Udo Richard Averweg
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Management Problem ◽  
Upper Management ◽  
Structured Problems ◽  
Decision Making Processes ◽  
Complex Decision Making ◽  
Computer Based

Decision support systems (DSS) deal with semi-structured problems. Such problems arise when managers in organisations are faced with decisions where some but not all aspects of a task or procedure are known. To solve these problems and use the results for decision-making requires judgement of the manager using the system. Typically such systems include models, data manipulation tools, and the ability to handle uncertainty and risk. These systems involve information and decision technology (Forgionne, 2003). Many organisations are turning to DSS to improve decision-making (Turban, McLean, & Wetherbe, 2004). This is a result of the conventional information systems (IS) not being sufficient to support an organisation’s critical response activities—especially those requiring fast and/or complex decision-making. In general, DSS are a broad category of IS (Power, 2003). A DSS is defined as “an interactive, flexible, and adaptable computer-based information system, specially developed for supporting the solution of a non-structured management problem for improved decision-making. It utilises data, it provides easy user interface, and it allows for the decision maker’s own insights” (Turban, 1995). There is a growing trend to provide managers with IS that can assist them in their most important task—making decisions. All levels of management can benefit from the use of DSS capabilities. The highest level of support is usually for middle and upper management (Sprague & Watson, 1996). The question of how a DSS supports decision-making processes will be described in this article. This article is organised as follows: The background to decisionmaking is introduced. The main focus (of this article) describes the development of the DSS field. Some future trends for the DSS field are then suggested. Thereafter a conclusion is given.

Evolution of the Role of Measurement Systems in Industrial Decision Support

2016 ◽  
pp. 560-580 ◽  
Author(s):  
Miroslaw Staron ◽  
Wilhelm Meding ◽  
Kent Niesel ◽  
Ola Söder
Keyword(s):  
Decision Support ◽  
Data Collection ◽  
Decision Support Systems ◽  
Information Needs ◽  
Support Systems ◽  
Measurement Data ◽  
Automated Measurement ◽  
Measurement Systems ◽  
Distributed Decision

Measurement data can be used for decision support in multiple ways – from one-time, manual data collection/presentation (reporting) through flexible business intelligence solutions to online, automated measurement systems. In centralized organizations, the measurement data is often collected through reporting, but the trends in modern organizations with empowered teams, globalized development, and needs to monitor continuously longer supply chains requires shift in the design and use of measurement systems. In this chapter, we present a study of evolving measurement systems at three companies with global businesses – Ericsson, Volvo Cars, and Axis Communications. The results of the study include the identification of the timeline of the evolution, distinct generations of measurement systems and information needs in the different phases of the evolution. The experiences show how to evolve centralized decision support systems to support global and distributed decision support.

Managerial Decision Support in the Post-COVID-19 Era

2021 ◽  
pp. 225-241
Author(s):  
Jan Kalina
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Management Practices ◽  
Support Systems ◽  
Management Decision ◽  
Managerial Decision ◽  
Massive Datasets ◽  
New Development ◽  
Decision Making Processes

The COVID-19 pandemic accelerated trends to digitalization and automation, which allow us to acquire massive datasets useful for managerial decision making. The expected increase of available data (including big data) will represent a potential for an increasing deployment of management decision support systems for more general and more complex tasks. Sophisticated decision support systems have been proposed already in the pre-pandemic times either to assist managers in specific decision-making processes or to perform the decision making fully automatically. Decision support systems are presented in this chapter as perspective artificial intelligence tools contributing to a deep transform of everyday management practices. Attention is paid here to their new development in the quickly transforming post-COVID-19 era and to their role under the post-pandemic conditions. As an original contribution, this chapter presents a vision of information-based management, which far exceed the rather limited pre-pandemic visions of evidence-based management focused primarily on critical thinking.

How Groupware Systems Can Change How an Organisation Makes Decisions

2011 ◽  
pp. 426-433
Author(s):  
Frédéric Adam ◽  
Jean-Charles Pomerol ◽  
Patrick Brézillon
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Study Protocol ◽  
Support Systems ◽  
Decision Making Processes ◽  
The Impact

In this article, a newspaper company which has implemented a computerised editorial system is studied in an attempt to understand the impact that groupware systems can have on the decision making processes of an organisation. First, the case study protocol is presented, and the findings of the case are described in detail. Conclusions are then presented which pertain both to this case and to the implementation of decision support systems that have a groupware dimension.

Decision Support Systems and Decision-Making Processes

2010 ◽  
pp. 218-224 ◽  
Author(s):  
Udo Richard Averweg
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Management Problem ◽  
Upper Management ◽  
Structured Problems ◽  
Decision Making Processes ◽  
Complex Decision Making ◽  
Computer Based

Decision support systems (DSS) deal with semi-structured problems. Such problems arise when managers in organisations are faced with decisions where some but not all aspects of a task or procedure are known. To solve these problems and use the results for decision-making requires judgement of the manager using the system. Typically such systems include models, data manipulation tools, and the ability to handle uncertainty and risk. These systems involve information and decision technology (Forgionne, 2003). Many organisations are turning to DSS to improve decision-making (Turban, McLean, & Wetherbe, 2004). This is a result of the conventional information systems (IS) not being sufficient to support an organisation’s critical response activities—especially those requiring fast and/or complex decision-making. In general, DSS are a broad category of IS (Power, 2003). A DSS is defined as “an interactive, flexible, and adaptable computer-based information system, specially developed for supporting the solution of a non-structured management problem for improved decision-making. It utilises data, it provides easy user interface, and it allows for the decision maker’s own insights” (Turban, 1995). There is a growing trend to provide managers with IS that can assist them in their most important task—making decisions. All levels of management can benefit from the use of DSS capabilities. The highest level of support is usually for middle and upper management (Sprague & Watson, 1996). The question of how a DSS supports decision-making processes will be described in this article. This article is organised as follows: The background to decisionmaking is introduced. The main focus (of this article) describes the development of the DSS field. Some future trends for the DSS field are then suggested. Thereafter a conclusion is given.

scholarly journals Perbadingan Metode Weight Product dan Vikor Dalam Menentukan Siswa Berprestasi

2020 ◽  
Vol 6 (2) ◽  
pp. 270-279
Author(s):  
Nurhadi Nurhadi ◽  
Kejus Ronatal Sinaga ◽  
Maulana Yusuf ◽  
Rachmat Hidayat ◽  
Yusnia Budiarti
Keyword(s):  
Student Achievement ◽  
Decision Support ◽  
Data Collection ◽  
Decision Support Systems ◽  
Support Systems ◽  
Research Data ◽  
Calculation Error ◽  
Vikor Method ◽  
A Value ◽  
Criterion Method

Abstract: At Maadrasah Ibtidaiyah Jamiatul Gulami Tangerang, he often selects outstanding students as a form of spurring the potential to be competitively healthy. But often the process carried out by the Madrasah experiences a calculation error. For this reason, the authors provide a solution, namely the SPK process to determine outstanding students at madrasah ibtidaiyah jamiatul gulami Tangerang. In decision support systems, there are several methods, including those used in this study, namely WP and VIKOR. The Weight Product (WP) method is a method that uses the multiplication of values, attributes to connect ratings, by first ranking each attribute. Meanwhile, the Vise Criterion method, Jumske Optimizakija I Kompromineso Resenje (VIKOR) ranks alternatives and determines solutions that are close to ideal. In the research, data collection techniques were carried out by observing the location of the research and conducting interviews with a teacher named Muhamad Syakir S.Ag at the Madrasah. The results obtained from the research that has been done, namely the WP method are shown to A1 on behalf of Amelia Putri with a value of 0.104, while in the VIKOR method it is shown to A5 on behalf of Eka Yulia with a value of 1.00. Keywords: SPK Student Achievement WP,VikorAbstrak: Pada Maadrasah Ibtidaiyah Jamiatul Gulami Tangerang seingkali mengadakan pemilihan siswa berprestasi sebagai bentuk memacu potensi untuk berkompetitif secara sehat. Tetapi seringkali proses dilakukan oleh Madrasah tersebut mengalami kekeliruan perhitungan. Untuk itu penulis memberikan solusi yaitu dengan proses SPK untuk menentukan siswa berprestasi pada madrasah ibtidaiyah jamiatul gulami Tangerang. Pada sistem penunjang keputusan terdapat beberapa metode diantaranya yang digunakan pada penelitian ini yaitu WP dan VIKOR. Metode Weight Product (WP) adalah metode yang menggunakan cara perkalian nilai, atribut untuk menghubungkan rating, dengan dilakukan dipangkatkan terlebih dahulu rating pada setiap atribut. Sedangkan Metode Vise Kriteriajumske Optimizakija I Kompromineso Resenje (VIKOR) melakukan perangkingan terhadap alternatif dan menentukan solusi yang mendekati ideal. Pada penelitian dilakukan teknik pengumpulan data dengan cara observasi ketempat lokasi yang menjadi penelitian dan melakukan wawancara kepada seorang guru bernama Muhamad Syakir S.Ag di Madrasah Tersebut. Pada hasil yang diperoleh dari penelitian yang telah dilakukan yaitu dengan Metode WP ditunjukan kepada A1 atas Nama Amelia Putri dengan nilai 0.104.Sedangkan pada metode VIKOR ditunjukan kepada A5 atas nama Eka Yulia dengan nilai 1.00.Kata kunci: SPK Siswa Berprestasi WP, Vikor

Towards human consistent data driven decision support systems using verbalization of data mining results via linguistic data summaries

2010 ◽  
Vol 58 (3) ◽  
pp. 359-370 ◽  
Author(s):  
J. Kacprzyk ◽  
S. Zadrożny
Keyword(s):  
Data Mining ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Ease Of Use ◽  
Data Driven ◽  
Linguistic Data ◽  
Developing Area ◽  
Tools And Techniques ◽  
Data Summaries

Towards human consistent data driven decision support systems using verbalization of data mining results via linguistic data summariesWe present how the conceptually and numerically simple concept of a fuzzy linguistic database summary can be a very powerful tool for gaining much insight into the essence of data that may be relevant for a business activity. The use of linguistic summaries provides tools for the verbalization of data analysis (mining) results which, in addition to the more commonly used visualization e.g. via a GUI, graphical user interface, can contribute to an increased human consistency and ease of use. The results (knowledge) derived are in a simple, easily comprehensible linguistic form which can be effectively and efficiently employed for supporting decision makers via the data driven decision support system paradigm. Two new relevant aspects of the analysis are also outlined which was first initiated by the authors. First, following Kacprzyk and Zadrożny [1] comments are given on an extremely relevant aspect of scalability of linguistic summarization of data, using their new concept of a conceptual scalability that is crucial for large applications. Second, following Kacprzyk and Zadrożny [2] it is further considered how linguistic data summarization is closely related to some types of solutions used in natural language generation (NLG), which can make it possible to use more and more effective and efficient tools and techniques developed in this another rapidly developing area. An application of a computer retailer is outlined.

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