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Review of Farm management Information Systems (FMIS)



There have been considerable advancements in the field of MIS over the years, and it continues to grow and develop in response to the changing needs of the business and marketing environment. Professionals and academicians are contributing and serving the field of MIS through the dissemination of their knowledge and ideas in professional journals. Thus, changes and trends that likely have an impact on MIS concepts, processes, and implementation can be determined by reviewing the articles published in journals. Content of the articles published in journals can also give us an idea about the types of research and themes that are popular during a given period. To see the evolutionary change in the field of MIS, the present study examined the content of articles published in business and marketing journals.
New York Science Journal, 2010;3(5): Salami et al., Review of FMIS
Review of Farm Management Information Systems (FMIS)
Payman Salami *1, and Hojat Ahmadi1
1. Department of Agricultural Machinery Engineering, Faculty of Biosystems Engineering, University of Tehran,
P.O. Box 4111, Karaj 31587-77871, Iran
Abstract: There have been considerable advancements in the field of MIS over the years, and it continues to grow
and develop in response to the changing needs of the business and marketing environment. Professionals and
academicians are contributing and serving the field of MIS through the dissemination of their knowledge and ideas
in professional journals. Thus, changes and trends that likely have an impact on MIS concepts, processes, and
implementation can be determined by reviewing the articles published in journals. Content of the articles published
in journals can also give us an idea about the types of research and themes that are popular during a given period. To
see the evolutionary change in the field of MIS, the present study examined the content of articles published in
business and marketing journals. [New York Science Journal 2010;3(5):87-95]. (ISSN 1554 – 0200).
Key words: Farm Management Information Systems; FMIS; GIS; IT; MIS
1. Introduction
In today’s dynamic world everything is changing
very radically; and as the 21st century dawns,
revolutionary changes are also beginning to challenge
the business and marketing world. To cope with the
increasing competition and uncertainty, companies need
to take advantage of the information technology (IT)
and information systems (IS). IS offer firms new ways
of improving efficiency. Thus, the need for management
of information is becoming the heart of marketing for
the firms in order to survive in highly competitive
markets. As the significance of management
information systems (MIS) has been increasing,
marketing and business environments have been
revolutionizing through the applications of IT. Hence,
the role of MIS in business and marketing has been also
changing continuously due to rapid advancements in
technology (Nasir, 2005).
Productivity gains in the agricultural industries
have historically been driven by the adoption of new
technical products and processes. It has been the realm
of extension to make sure that farmers hear about these
processes and technologies, and usually it has been
State governments who have funded the extension effort.
With the rapid increase in the complexity of the
technology of farming, there is now a recognized need
to improve the skills and education of our farmers - the
human capital of agriculture. The Internet is changing
the way society accesses and processes information.
Farmers now have access to a wide range of information
about many aspects of their farming systems, but it is
often thought by scientists and extension specialists that
many lack the skills necessary to use that information to
improve their farm profitability and sustainability
through technical innovation. (Bell, 2002).
We live in what is being called the "information
age", an era in which it is the knowledge and skills of
the workforce that will determine our fate in a globally
competitive marketplace. Knowledge and skills go
hand-in-hand with informed management, and it is in
better management that increased productivity will be
The managerial tasks for arable farming are
currently transforming into a new paradigm, requiring
more attention on the interaction with the surroundings
(Sigrimis et al., 1999; Dalgaard et al., 2006). Among
other things, this managerial change is caused by
external entities (government, public) applying
increasing pressure on the agricultural sector to change
production from a focus on quantity to an alternate
focus on quality and sustainability (Halberg, 1999).
This change has been enforced by provisions and
restrictions in the use of production input (e.g. fertilizers,
agrochemicals, etc.) and with subsidies as an incentive
for the farmer to engage in a sustainable production. In
general, this change of conditions for the managerial
tasks on the farm has necessitated the introduction of
more advanced activities monitoring systems and
information systems to secure compliance with the
restrictions and standards in terms of specific
production guidelines, provisions for environmental
compliance, management standards as prerequisites for
New York Science Journal, 2010;3(5): Salami et al., Review of FMIS
subsidies, etc. Until now, the farmers most often have
dealt with this increased managerial load by trying to
handle a bulk of information in order to make precise
decisions. The increasing use of computers and the
dramatic increase in the use of the internet have to some
degree improved and eased the task of handling and
processing of acquired external information but still, the
acquisition and analysis of available information have
proven a demanding task, since information can be
scattered over many sites and not necessarily
interrelated and collaborative. Specific attempts to
improve this situation has included the launch of
“web-based collaborative information system”
developments, combining different information
components (models, data, text, graphics) from different
but collaborating sources (Jensen et al., 2001). However,
such systems still has to be enhanced in terms of
collaboration with automated acquisition of operational
farm data and integration with the overall Farm
Management Information Systems (FMIS).
Information management plays an important role
in how well farms are able to deal with increasing
demands. In plant production tasks in the field,
agricultural machinery now plays a key role in process
acquisition and documentation of data. It is important
that field tasks are carried out according to plan, and if
sudden changes in plan are needed that these follow
standards and regulations and help to improve the
outcome (Pesonen et al., 2008).
Determination of the technological solutions for
the information management system has two
dimensions; determining user needs and determining the
technological infrastructure. Understanding of user
needs in early development state and bringing the
knowledge to designing process is important when
constructing new systems so, that they will achieve user
acceptance efficiently (Kaasinen, 2005). The needs are
taken into account when designing the new system
architecture and choosing the technology to utilize in
the system. Inventory of available technologies gives
understanding of technological resources and
possibilities that we have as building units of the new
system. As a result of the creative designing process the
specifications of the new system can be presented.
Management information systems encompass a
broad and complex topic. To make this topic more
manageable, boundaries will be defined. First, because
of the vast number of activities relating to management
information systems, a total review is not possible.
Those discussed here is only a partial sampling of
activities, reflecting the author's viewpoint of the more
common and interesting developments. Likewise where
there were multiple effects in a similar area of
development, only selected ones will be used to
illustrate concepts. This is not to imply one effort is
more important than another. Also, the main focus of
this paper will be on information systems for use at the
farm level and to some lesser extent systems used to
support researchers addressing farm level problems (e.g.,
simulation or optimization models, geographic
information systems, etc.) and those used to support
agribusiness firms that supply goods and services to
agricultural producers and the supply chain beyond the
production phase (Harsh, 2004).
The MIS manager's objective in IS development is
to identify a project's goals, environment, and alternate
development strategies, then to evaluate the alternatives
and thus select the approach that will best deliver the
system. This is a complex problem that influences the
procedures and work styles of everyone involved. Also,
various people involved have different perceptions of
needs and are naturally biased toward familiar
approaches (Berrisford et al., 1979; Brousseau, 1988;
Naumann, et al., 1982; Willis, 1988).
2. Materials and methods
There have been considerable advancements in the
field of MIS over the years, and it continues to grow
and develop in response to the changing needs of the
business and marketing environment. Professionals and
academicians are contributing and serving the field of
MIS through the dissemination of their knowledge and
ideas in professional journals. Thus, changes and trends
that likely have an impact on MIS concepts, processes,
and implementation can be determined by reviewing the
articles published in journals. Content of the articles
published in journals can also give us an idea about the
types of research and themes that are popular during a
given period. To see the evolutionary change in the field
of MIS, the present study examined the content of
articles published in business and marketing journals.
Specifically, changes and trends in the scope of research
topics over time were examined (Nasir, 2005).
A management information system includes internal
and external sources of data and allows that data to be
modified and structured in different ways as different
decisions need different sets of information (Oslon,
Management information systems (MIS) is an
integral part of the overall management system in an
Purposeful organization comprising tolls like enterprise
New York Science Journal, 2010;3(5): Salami et al., Review of FMIS
resource planning (ERP), overall information systems
(IS), etc. ERP is an industry notion for a wide set of
management activities which support all essential
business processes within the enterprise. The
management system support management activities on
all levels as well as provide for the identification of key
performance indicators (KPI’s) (Folinas, 2007).
Typically, ERP is integrated with a database system and
will often include applications for the finance and
human resources aspects of a business.
Information systems are the software and hardware
systems that support data-intensive applications.
Especially, information systems provide the possibility
to obtain more information in “real-time” enabling a
close monitoring of the operations performance and
enhance the connection between executed operations
and the strategic targets of the enterprise (Lyons, 2005;
Folinas, 2007). However, in terms of deriving the
requirements for the information system design, often
targeted information systems lack a definitive
formulation. Different stakeholders have different
perspectives on what is and what is not the most
important to be included in the design of an information
MIS differ from regular information systems
because the primary objectives of these systems are to
analyze other systems dealing with the operational
activities in the organization. In this way, MIS is a
subset of the overall planning and control activities
covering the application of humans, technologies, and
procedures of the organization. Within the field of
scientific management, MIS is most of ten tailored to
the automation or support of human decision making
(O’Brien, 1999). Figure 1 shows the conceptually
decomposing of the different management systems in an
organization (Sørensen et al., 2009).
Enterprise Resource Planning (ERP):
- Enterprise-wide and cross-functional system aimed at coordinating all the resources, information,
and activities required to complete business processes
Figure 1. Concept of management information systems.
Information Systems (IS):
- The application of people, documents, technologies and procedures
- solving business processes comprising related, structured activities or tasks that
produce a specific service or product
Management Information System (MIS):
- refer to the group of information management methods tied to
the automation or support of human decision making
• Decision support system
• Expert system
• Executive decision
• …
New York Science Journal, 2010;3(5): Salami et al., Review of FMIS
By following this conceptual framework and
notation, a FMIS is depicted as a planned system of the
collecting, processing, storing and disseminating of
data in the form of information needed to carry out the
operations functions of the farm.
Figure 2 shows a sample system architecture as it
should be understood by the user of the system. The
essential structure that should be understood is the
centrality of the FMIS as the system to which all other
parties are connected. The arrows, representing
communication, are purposely left vague in the sense
that they do not specify the protocol or content of the
communication. This is because the end user need not
know or even care how the communication between
the various systems is handled, only that it occurs and
that it is possible. The entire system appears to the
farmer through a browser interface or the interface
provided by the ISO-11783 TC. The TC interface is a
special case to the other available interfaces as it acts
as the gateway between the FMIS and the ISOBUS
enabled tractor-implement combination (Pesonen et al.,
Figure 3 shows the technical view of the FMIS
with the connected systems grouped to four categories.
The architecture will be discussed bottom-to-top,
starting with the data storage and then moving on to
the application logic. The application logic is further
divided to class library, data transformation and
communication layers. Finally the data transfer and
formats to the different systems are considered
(Pesonen et al., 2007).
All data within the FMIS are stored to several
RDBMS (relational database management system)
using the SQL (structured query language) query
language for interaction. The three databases of figure
5.2 are:
Authentication database contains the
identification and authentication information for all
users of the system. Also contained within the
authentication database are the access permissions to
data that are used when dealing with for example
authorities and contractors. The authentication
database additionally contains the authentication
information to other services; if a mutual trust and
agreement exists between the maintainers of the FMIS
and some external service, the FMIS can
automatically authenticate users for the external
Figure 2. FMIS architecture from the viewpoint of the user.
New York Science Journal, 2010;3(5): Salami et al., Review of FMIS
General FMIS database contains the same
heterogeneous collection of information about the
farm that is stored by any commercial FMIS. One
difference is that the general FMIS database must also
contain information on farm equipment required for
precision agriculture. The schema of the general FMIS
database is complicated by the amount and diversity
of the stored information. However, this complexity
requires no novel techniques as the design and
implementation of similar databases can be considered
routine work in software development.
GIS database contains exclusively data related to
precision agriculture. The data need not be stored in a
native GIS format though several relational databases
have GIS extensions available to provide efficient
queries for the stored GIS data. The GIS database is
also the first database expected to exhibit performance
problems under an increasing load.
3. Results and discussion
In terms of information handling, the farmer
needs to manage a lot of information in order to make
economical and environmental sound decisions.
Currently, this process is very labor intensive and for
most parts, executed manually. The important
concerns and problems voiced by the farm manager
include the time consuming tasks of monitoring field
operations, manage the finances and application for
subsidies which is further complicated by the lack of
integrated soft and hardware to manage this work and
the lack of coordination when such programs do exists.
Also, the farmer voice a need for additional
information and advanced technologies to manage
monitoring and data acquisition on-line in the field.
When looking at the external concerns, it is seen that
this mostly concerns the need for sustainable
production of farm products, which is further pursued
by regulations and the possibility to receive subsidies
when more sustainable management practices are
abided by. Table 1 lists some of the voiced concerns
(Sørensen et al., 2009).
In a study of the use of Farm Management
Information Systems (FMIS), Lewis looked at the
information sources used by farm decision-makers. He
Figure 3. FMIS architecture from the viewpoint of the developer
New York Science Journal, 2010;3(5): Salami et al., Review of FMIS
found that, for the majority of farmers, the most
important source of management information was
other farmers. The most innovative group also rated
their own records highly, then came outside advice
from accountants and field days. Local and
agricultural newspapers also scored highly, well above
national newspapers, commercial newsletters or
government publications (Lewis, 1997).
Hayes et al. demonstrated a positive association
between the on-farm use of a MIS and herd
performance. Significant resources are required to
implement and use these aids, but improvements in
the overall productivity of dairy farms that calve
seasonally might be achieved if these technologies
were to be more generally adopted (Hayes et al.,
In terms of the "importance" of this information
(perhaps synonymous with trustworthiness), family
came highest except for the most innovative group,
who rated their own records just above family. Other
farmers and other professionals such as agricultural
consultants, accountants and bookkeepers came next,
although the most innovative farmers rated discussion
groups higher than these. Agricultural newspapers
were next most important, and for the most innovative
farmers, farming magazines. Universities, product
pamphlets, national newspapers, bankers, solicitors,
insurance agents, government publications and
television broadcasts were all seen as of low
importance. Agricultural and technical colleges were
seen of high importance, but only by those farmers
who had no FMIS (Bell, 2002).
Another study of a quite different group - grape
growers in the Yarra Valley (Almonte, 1998), came to
similar conclusions, despite the fact that the target
group was very different (e.g. over 70% had tertiary
qualifications). The main sources of information were
grower groups, other growers, accountants, their own
records, field days, and then family. Next came
scientific journals, something not seen in other
categories of farmers. Lowest came television, radio,
local newspapers and salespersons. There was a
significant positive correlation between age and using
information from families and negative correlations
between both level of education and size of farm and
the use of information from consultants and grower
groups respectively. It seems that the larger the
operation, the less the need for outside information.
In a study in Rafsanjan, Iran (Abdollahi
Ezzatabadi et al., 2002), the farmer participation in
establishing a simple Farm Management Information
System investigated. The results showed that the
farmers were willing enough to accept the system.
Nevertheless, having an accounting system in the first
step toward the establishment of an information
system, this is used by only 42% of the sampled
farmers. The main reason for this is the lack of
knowledge about the benefits of such systems.
When considering the Farm Management
Information System (FMIS) from the perspective of
systems usability presented here, the information
management system is more than just data storage and
functionalities supporting farm management. It has an
important active role in providing on-line support and
assistance in everyday farm activities. Thus we
suggest that the newly designed information
management system concept for automated plant
production should be named Active Farm
Management Information System, AFMIS (Pesonen et
al., 2008).
In a study on the development, change, and
transformation of Management Information Systems
(Nasir, 2005) the following results Obtained: The
results of the content analysis indicate a change in the
themes and concepts of IS over the past three decades.
Between the years 1970 and 1979, most of the articles
have concentrated on the development of IS design
and they have underlined critical factors in achieving
successful and effective IS design. In the first ten
years, IS has been used predominantly to support the
managers in their decision making. Besides, it is
evident that implementation of IS into sales
management has been popular and widespread in this
era. However, IS implementations in the sales
management have been limited to make forecasting
about the sales and to take feedback from the sales
persons. However, in the second ten years, IS
implementations have disseminated into different
domains of business such as maritime industry,
industrial markets, motor carrier markets, banking
sector, etc.. The roles and responsibilities of the
managers in the MIS began to change, and the
significance of user involvement (such as involvement
of executive managers, managers, and line managers)
in the management processes of IS has increased
during 1980s. As the need of interaction among
executives, users, and IS managers has increased for
the success of MIS operations, the decentralization of
New York Science Journal, 2010;3(5): Salami et al., Review of FMIS
IS departments has become a dominant issue during
the period of 1980–1989. Similarly, the significance of
collaboration and interaction among the high-level
executives, users, and information system managers
has also continued to be mentioned during the period
1990–2002. However, in contrast to the period of
1980–1989, in the period of 1990–2002 the changing
role of chief information officers (CIO) has been
discussed. Practitioners of the period 1990–2002 have
discussed whether CIO is adding value or not. As the
firms began to outsource their IS, a discussion of
whether to outsource IS or use in-house IS also started
at that time.
Naranjo-Gil in a study showed that TMT
diversity is an important variable influencing the
relationship between MIS sophistication and strategic
performance. The issues of management
organizational performance are critical problems
confronting top managers in public organizations. The
findings of this paper provide a fruitful avenue for
improving our understanding of strategic performance
in hospitals and other organizations (Naranjo-Gil,
2009). Governmental authorities have to design the
MIS to provide a broad range of information to health
care managers. Thus, top management teams can face
the challenge of balances and coordinates patients,
financial, organizational and community needs
(Fuller-Love & Cooper, 1996; Brittain & Macdougall,
1995; Shortell et al., 1996). A FMIS is depicted as a
planned system of the collecting, processing, storing
and disseminating of data in the form of information
needed to carry out the operations functions of the
4. Conclusions
MIS differ from regular information systems
because the primary objectives of these systems are to
analyze other systems dealing with the operational
activities in the organization. In this way, MIS is a
subset of the overall planning and control activities
covering the application of humans, technologies, and
procedures of the organization. Within the field of
scientific management, MIS is most of ten tailored to
the automation or support of human decision making.
General FMIS database contains the same
heterogeneous collection of information about the
farm that is stored by any commercial FMIS. One
difference is that the general FMIS database must also
contain information on farm equipment required for
precision agriculture.
Correspondence to:
Payman Salami
Department of Agricultural Machinery Engineering,
Faculty of Biosystems Engineering, University of
Tehran, P.O. Box 4111, Karaj 31587-77871, Iran
Fax: +98-21-665-93099
Cell phone: +98-918-373-4751
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Payman Salami was born in 1979 in Kurdistan/Iran, received his B.Sc. degree in
Agricultural Machinery Engineering from the Bu-Ali Sina University, Iran, in 2003. He is
now M.Sc. student in Agricultural Mechanization Engineering in the University of Tehran
under supervision of Dr Hojat Ahmadi. His research fields include Analytics of input
output and waste energies in agriculture production, Information Systems, Application of
GIS and RS systems in agriculture, Condition Monitoring, and Mechanization Indices.
New York Science Journal, 2010;3(5): Salami et al., Review of FMIS
Hojat Ahmadi was born in Shiraz/Iran in 1969, received B.Sc. degree in Agricultural
Machinery Engineering from the University of Shiraz, Iran, in 1992, M.Sc. and Ph.D.
degrees in Mechanical Engineering of Agricultural Machinery from the University of
Tehran, Iran, in 1996 and 2001, respectively. He is currently assistant professor in
Department of Mechanical Engineering of Agricultural Machinery at University of
Tehran. His current research interests are Machinery Fault Detection, Vibration & Oil
Monitoring, Signal Processing, Precision Agriculture and System Maintenance.
... In general, FMIS are used to collect, process, store, and disseminate data in the form of information needed for operational processes Salami and Ahmadi, 2010;Sørensen et al., 2010). They can be based on digital applications and support the user in the decision-making process. ...
... FMIS can be useful management tools for farmers in order to collect, process, store, and disseminate data in daily farm business operations Salami and Ahmadi, 2010;Sørensen et al., 2010). Based on FMIS, farmers can be supported in the process of decision making, in the reduction of production costs, or in the production of safe and quality agricultural products (Fountas et al., 2015;Munz et al., 2020). ...
Farm Management Information Systems (FMIS) have undergone tremendous development in the recent past. With the sharp increase in documentation requirements for agricultural businesses, the potential of FMIS to become widely used comprehensive management tools is high but not yet fully exploited in practice. Consequently, there is a need to improve and adjust these systems. However, there is little research about how to optimize FMIS in order to meet the needs of the users. To answer this question, a deeper understanding of how users differ from other groups regarding their intensity of use and their perceptions of FMIS is needed but has hardly been explored so far. By means of a standardized online questionnaire in the summer of 2019, the skills and attitudes of 280 German farmers regarding the use of FMIS were surveyed. By means of a cluster analysis, different user segments were analyzed to gain deeper insights into which characteristics FMIS users and non-users have. Four clusters were identified including two non-user groups and two user groups with varying potential for FMIS providers and marketers. The results show that the lack of persuasiveness of the existing systems by not (yet) offering solutions to farmers’ problems and needs is a major barrier. One main driver for the use of FMIS is to manage the increasing political and social requirements with the help of a professional documentation of farm activities. On the one hand, the results accompany the ongoing digital transformation in agribusiness and contribute on the other hand to the digitization process on farms by increasing new knowledge about farmers’ requirements regarding FMIS. The results also provide relevant insights for software development companies to adjust their products according to the farmers’ needs.
... The higher values of energy parameters exhibited by different treatments were on account of higher seed and haulm yields and lower energy inputs under these treatments. Similar findings have also been reported by many literatures (10)(11)(12)(13)(14). ...
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Field experiments were carried out at the Agronomy Main Research Farm, O.U.A.T. Bhubaneswar, Odisha, India during 2019 and 2020 to find out energetics and economics of green gram as influenced by varying land configuration and nutrient management practices. Split-plot Design was adopted with three replications. Results of the experiment showed that raised bed method with PDM-139 cultivar in combination with F6 treatment gave the highest pooled yield (522.84 kg ha-1 and 455.29 kg ha-1) respectively. Similar trend was observed in Energy productivity (0.358kg MJ/ha and 0.335 kg/MJ respectively) and efficiency (1.42 kg MJ ha-1 and 1.17 MJ ha-1respectively). Economic analysis also revealed that flat bed with PDM-139 with F6 treatment combination gave the highest pooled B: C ratio (1.75) during the years of investigation.
... Smart electronic tools with easy use and affordable prices are important factors in the real-time business decision-making for farmers under the highly competitive markets known as Farm Management Information Systems (FMIS). FMIS was integrated by various technologies and standard software packages such as information technology (IT), information systems (IS), and enterprise resource planning (ERP) in the form of information for data collection, processing, storing, and disseminating [61]. All of FMIS operations, information and multiple business functions with registration, interoperation, and communication in connection with [58,59]). ...
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The outbreaks of plant pathogenic viruses and insect pests affect agricultural product supply chain systems. Environmentally friendly innovative technologies are provided accurate, practical, and acceptable means for surveillance by farmers. The bioactive compound applications are derived from plant essential oils with antiviral activities as well as integrating insect pest control and management are useful choices. Successful comprehensive planning, including material production systems, extraction techniques, quality testing, and product creation are essential for strategic and operational decision-making under current operation management trends of Agriculture 4.0. This information can potentially be used to impel today agriculture and set the directions for supports. The role of management and data analysis will meet the challenges of increasing populations and food security with the ultimate goal to achieve efficient and sustainable effectiveness for all participants in directing the world agricultural systems.
... Seeking assistance from professionals by providing technical knowledge through various means can optimize farm productivity (Salami and Ahmadi, 2010). Other authors stated that the more knowledge about AI, the more likely to become proactive in formulating preventive measures (Rehman et al., 2022), however, the respondents did not seek out professional help. ...
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This study was conducted on backyard chicken farmers of Escalante City, Negros Occidental to assess their knowledge and awareness of the disease. Despite most of the respondents being aware of AI, a huge fraction believe that the disease is caused by bacteria. Moreover, most of them have low knowledge and awareness about the disease, which is supported that none of them obtained knowledge through seminars, professional assistance, or membership in any chicken-raising associations. Similar studies should be conducted by other LGUs and the government must be proactive in information dissemination about the disease.
... Thus, consolidating all data, especially the farm activities, becomes important to support farmers' decision making. Prior to this, farmers may utilize the internet and recently developed devices such as tablets and smartphones to consolidate the data by using Farm Management Information System (FMIS) as an application to collaborate and interrelate with other information on the internet to facilitate more precise decision-making (Salami & Ahmadi, 2010). Therefore, the researcher focused on farm management, which is essential for all farmers, including smallholder farmers, to use FMIS as an ICT solution for transforming their traditional business towards agribusiness. ...
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of the phenomenon through the underpinned theory available in information systems theories such as technology-organisation-environment (TOE), technology acceptance model (TAM), diffusion of innovation (DOI), and task-technology fit (TTF). The method chosen in this research was ABSTRACT This paper introduces a framework using ICT to transform smallholder farmers' traditional business towards agribusiness in Malaysia by extending the existing theoretical framework. The introduction of agribusiness to the farmers is not well understood and difficult to implement due to their limitations as smallholder farmers. The framework outlining ICT usage which was improved through identifying major factors affecting agribusiness transformation by using ICT such as environment (ENV), technology (TECH), farm work design (FWD), and information system elements (ISE). This paper focuses on testing relationships between ENV and TECH which acting as independent variables (IVs) towards agribusiness transformation using ICT as dependent variable (DV). The moderation effect of ISE and FWD acting as moderation variables (ModVs) which interacted with TECH towards agribusiness transformation using ICT were also being investigated in this paper by using slope analysis. This research used a quantitative approach to explore the nature Current Affiliation
Innerhalb des ersten Themenbereichs (I. Status quo und Entwicklung der Digitalisierung in der deutschen Landwirtschaft) der in dieser Dissertation vorliegenden Veröffentlichung wird das Modell von Porter und Heppelmann (2014) aufgegriffen und weiterentwickelt, um den Status quo der Digitalisierung in der deutschen Landwirtschaft empirisch zu erfassen. Damit konnte festgestellt werden, dass die deutschen landwirtschaftlichen Betriebe noch nicht das Niveau des "Smart Farming" und auch nicht das Niveau der "Produktsysteme" erreicht haben. Die Art der Nutzung der FMIS hinsichtlich einer verbreiteten Nutzung webbasierter Anwendungen, einer automatisch digitalen Dateneingabe und vor allem der Nutzung von universalen Datenstandards wurden innerhalb der Studie als die größten Hemmnisse auf dem Weg zum Erreichen des „Smart Farming“ identifiziert. Die Digitalisierung wird weiterhin als eine Voraussetzung für die zukünftige wirtschaftliche Leistungs- und Überlebensfähigkeit für Genossenschaften dargestellt, wobei vor allem ländliche Genossenschaften einem zunehmenden Wettbewerbsdruck, bedingt durch strukturelle Veränderungsprozesse, anhaltende Transformationsprozesse durch die Digitalisierung und durch das Aufkommen neuer Wettbewerber, ausgesetzt sind. Nach derzeitigem Wissensstand wurde das Themenfeld der Digitalisierung bei ländlichen Genossenschaften bisher nicht beleuchtet und steht nun erstmalig innerhalb des zweiten Themenbereichs dieser Dissertation im Fokus wissenschaftlicher Studien (II. Akzeptanz, Status quo und Entwicklung ländlicher Genossenschaften im Kontext der Digitalisierung). Bereits durchgeführte Studien bezeichneten Genossenschaften in Bezug auf die Adoption neuer Technologien als „late adopter" und empfehlen, dies branchenspezifisch zu untersuchen und empirisch nachzuvollziehen. Vor dem Hintergrund der erläuterten Problematik beleuchten zwei Publikationen zunächst die Determinanten von Akzeptanzfaktoren für die Nutzung digitaler Technologien bei ländlichen Genossenschaften. Die erste vorliegende Studie beruht dabei auf der Identifikation und Analyse von Akzeptanzfaktoren bezüglich der Nutzung internetbasierter Informationssysteme (IS) entlang der genossenschaftlich geprägten WSK der Rotfleischwirtschaft aus Sichtweise von Landwirten bzw. Mitglieder/KundInnen einer Viehvermarktungsgenossenschaft. Drei nutzenstiftende Faktoren bezüglich der erwarteten Nutzung von internetbasierten IS konnten dabei als valide Akzeptanzfaktoren identifiziert werden: die Unterstützung bei der Dokumentation und einem verpflichtenden Austausch von Daten Richtung Verwaltungsorganen (B2A); der überbetriebliche Datenaustausch zwischen LandwirtIn und Viehvermarktungsunternehmen/Schlachthof (B2B); die Funktion der Integration externer Daten in das IS. Eine weitere vorliegende Studie fokussiert dabei auf die intermediäre Ebene des gesamtdeutschen genossenschaftlichen Agrarhandels aus Sichtweise der GeschäftsführerInnen, wobei die drei Akzeptanzfaktoren bezüglich der erwarteten Nutzung digitaler Technologien in den Geschäftsfeldern Beschaffung und Logistik; KundInnen-/Mitgliedermanagement und Vermarktung als nutzenstiftend identifiziert werden konnten. Als größte Herausforderung auf dem Weg zur Implementierung digitaler Technologien konnten personelle und finanzielle sowie strategische und operationelle Faktoren identifiziert werden. Chancen, die sich durch eine Mitgliedschaft im genossenschaftlichen Verbund ergeben, müssen daher gezielt genutzt werden, um Herausforderungen zu begegnen und Risiken gemeinsam abzufedern. Insgesamt konnte nachgewiesen werden, dass auf Ebene der Primärproduktion und der intermediären Stufe des genossenschaftlichen Agrarhandels eine „Einstellungsakzeptanz“ gegenüber der Einführung digitaler Technologien besteht. Im Zuge der Analysen konnte die Determinante der Größe der Genossenschaft bzw. des landwirtschaftlichen Betriebs als einen positiven Einfluss auf die Akzeptanz digitaler Technologien zurückgeführt werden. Die letzte im Rahmen dieser Dissertation vorgelegte Veröffentlichung leistet einen Beitrag hinsichtlich der Identifizierung des Status quo der Adoption digitaler Technologien im genossenschaftlichen Agrarhandel und leitet daraus Möglichkeiten einer digitalen Differenzierung von Warengenossenschaften ab. Anhand einer Clusteranalyse konnten die Genossenschaften dem Cluster der „Basic Adopters“ (n=48) und der „Advanced service-orientated Adopters“ (n=18) zugeordnet werden. Vor dem Hintergrund des anhaltenden Verdrängungswettbewerbs und den in den vorliegenden Studien erlangten Erkenntnissen wird den Warengenossenschaften empfohlen, eine individuell angepasste Differenzierungsstrategie in Betracht zu ziehen und dazu konkrete digitale Kompetenzen mit einer verstärken Serviceorientierung aufzubauen, um ihr Geschäftsmodell bzw. die Geschäftsprozesse an die aktuellen Branchenentwicklungen anzupassen.
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The limitation of the commonly used back-emf sensorless detection technique is that it is not possible to control the speed of the BLDC motor over a wide speed range as required in electric vehicles. In particular, it is not possible to control at low speeds due to the presence of noise signals near pulse width modulated (PWM) back-emf zero-crossing points at low speeds. Therefore, the duty-cycle of direct sensorless back-emf technique is limited to less than 100% since a minimum turn-off time is required to get the sample of back-emf and apply control action. In this paper, a microcontroller-based enhanced PWM back-emf zero-crossing detection method is proposed to control the speed of the BLDC motor over a wide speed range. The experimental results are presented in this paper for validation.
Digitisation in Agriculture is currently one of the most important ongoing developments to meet the growing economic, ecological and social demands in the agri-food sector in Germany. Consequently, the use of information and communication technologies (ICT) to collect, exchange and evaluate data from and between different stakeholders and systems has already established itself in the agricultural sector. However, the extent to which information systems are used and the kind of features they have at the farm enterprise level are not clear. To obtain further insight into this topic, a quantitative empirical approach was adopted. It was based on interview data from a web-based survey conducted throughout Germany at the beginning of 2018. In this survey, 329 questionnaires (representing an 8.4% response rate) were completed and evaluated using bivariate and multivariate methods. This paper aims to assign the surveyed farmers to two of the “five steps of digital evolution” model - from the “single product” to the “system of systems” - according to the stated characteristics and functions used in the Farm Management Information Systems (FMIS). According to that model, a single product (e.g. a tractor or a feed trough) develops at level 1 and becomes a “smart product” at level 2. The agricultural machine can now, for example, maintain precise tracking via integrated real-time kinematic (RTK) correction that enhances precise satellite navigation. At the third development stage, a “smart, connected product” is created, where the agricultural machine is networked with other systems. Level 4 represents an “intelligent product system”. The focus is no longer only on optimising a single process, but also on optimising process chains. At the last stage, “systems of systems” (i.e. “smart farming”), the networking of different data from diverse sources reaches the maximum level. 43 variables were used to conduct a two-step cluster analysis, in which two clusters could be identified within the sample. The farmers assigned to cluster 2 could be determined as “users of smart products” (58%) which represents level 2 of the model. These farmers are characterised by the fact that they use FMIS for the overall purpose of supporting the documentation, monitoring and planning of farm management processes. The highest level of digitisation in German agriculture was found to match level 3, what is known as “users of smart, connected products”. On this level, farmers that were assigned to the cluster 1 (42%) use their information systems to improve individual farm processes by connecting hardware, sensors, data storage and software in different ways.
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In 1998, CIGR created a new Working Group (No 18) to review recent development in information systems and to make recommendations for future action. WG 18 is chaired by Professor Richard Hegg with assistance from Professor Nick Sigrimis and others. After numerous meetings and e-mail discussions, WG 18 recommended the formation of a new CIGR Section dealing with Information Technology that is dedicated to advancing the theory, practice and application of computers, information processing and communications technology in agriculture. The Executive Board of CIGR endorsed this recommendation at its meeting in Toronto in July 22, 1999.
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The purpose of this research is to grasp the development, change, and transformation of MIS in the marketing and business world over the time. To this end, changes and trends that likely have an impact on MIS concepts, processes, and implementation were determined by reviewing the articles published in business and marketing journals. Specifically, a content analysis was conducted to (1) identify the possible trends and changes in MIS concepts and themes over the past three decades, (2) detect prevalently used research types, and (3) compare the publishing productivity of business and marketing journals about the subject of IS.
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Most enterprises have spent an enormous amount of money and time, managing information about their business elements. Such information is often scattered in disparate legacy, operational and enterprise information systems, appointing the aggregation of valuable information and decision-making support quite difficult. Business Intelligence (BI) and their associated processes and tools are helping enterprises to solve this problem. This paper presents the principles and challenges of BI domain and evaluates its current approaches. The limitations of the above approaches will provide the basis for the design and development of a framework that pursues real time insight to business information, as well as, instantaneous awareness and appropriate response to critical business events across the entire enterprise. The proposed framework is based on Business Activity Monitoring (BAM) systems paradigm and attempts to create a unified enterprise-reporting environment. It was applied in a large Northern Greek manufacturing company in the last six months.. His research interests include: e-logistics, business-to-business integration, supply chain integration, virtual organisation/enterprise and e-commerce models and technologies.
Farmers lack well documented sets of farm level indicators to allow their own evaluation of environmental impact and to stimulate the development of more environment friendly farming practices. A set of farm level indicators of resource use and environmental impact on livestock farms was developed as part of a decision aid for farmers. The indicators were meant to be part of an extended farm account and included the surpluses and efficiencies of N, P and Cu, the energy use per kg grain and per kg milk or meat, pesticide treatment index (TFI), % unsprayed area, % small biotopes on the farm, and % weeds in grain crops. The indicators were tested on 20 Danish dairy and pig farms over a period of 3 years in order to see if they were suitable for use in the farmer’s management. The third year, farm gate surpluses varied between 89 and 265kg Nha−1, 2 and 31kg Pha−1 and 0.1 and 0.8kg Cuha−1. Energy use varied between 2.1 and 4.1MJkg−1 milk and between 14 and 20MJkg−1 live weight pig sold. For all indicators, except energy use per kg grain, the variation in indicator levels between farms was more important than the variation between years within each farm. There was significant variation between farms after correction for stocking rates and soil-and farm types, which suggests that the indicators reflect differences in management practise on comparable farms. It was demonstrated that these differences between similar farms and between the years on the individual farms might be explained by the detailed knowledge of management of the farms’ different subsystems (herd and crops). The information given by the indicators is discussed from environmental and management points of view and problems of defining and interpreting the indicators are identified. Given further development of indicators for soil quality and nature values, the farm level indicators seem a promising way of enabling farmers to include environmental topics in their management.
IT or ICT systems have been widely adopted by companies and are now part of the basic infrastructure of most organisations. ICT systems are evolving in response to both commercial and technical changes. This paper outlines some of the drivers for this continuing change, and discusses how these drivers may influence future evolution. The paper first discusses current trends and drivers, and then identifies a number of assumptions underlying current approaches to ICT system design. Criticism of these assumptions opens up new ways of thinking about the way ICT systems are designed and used, with implications for their future development.
This article proposes a major modification to the traditional systems development process. Traditional systems development approaches delay the delivery of tangible information system capabilities to users (i.e., query capabilities and decision support models, etc.) until the last stages of systems development. Consequently, it is not until after systems are developed that shortcomings in systems design surface. The authors advocate providing or at least simulating user capabilities early in the systems development process. Such an approach is made possible by the use of an online relational-type Database Management System. Introduction of such user capabilities allows users to interact with the system and heuristically determine information requirements. The authors present behavioral, technical, and operational arguments for a heuristic approach. Also, several case studies of heuristic development are discussed. The heuristic approach to information systems development is a useful concept for MIS managers, systems analysts, and users of computer-based information systems.
Selecting from the many currently available systems development methodologies (SDMs) and development techniques is a difficult problem with economic, technical, and behavioral implications. A quantitative approach to the selection problem is represented. The selection model begins with a definition of a superset of functions expected of a systems development tool. Functions are then weighted, using a Delphi approach to achieve acceptable valuations among system managers. Next, each approach under consideration is evaluated with respect to each function desired. After scores are computed for each methodology, economic and qualitative aspects such as training availability and cost can be used to differentiate the highest ranked alternatives. The four-person MBA project team from the Graduate School of Management at the University of Minnesota, with the guidance from authors, applied the model to a methodology selection problem. In addition to producing a quantitative ranking of competing methodologies, the approach described furthered understanding of the functions to be performed by the methodologies being considered. It also gained acceptance, admittedly reluctant, of the recommended methodology from managers who strongly advocated their own favorites.
Pl@nteInfo® ( is a decision support system, which uses the World Wide Web to supply farmers and agricultural advisers with just-in-time information and decision support for crop management. A subscription system enables personalised information. Background data are collected from different sources, processed by decision support models, and the results are integrated into personalised web pages with embedded graphics, expert interpretations and links to additional information. This article presents the system with its decision support facilities and subscription system, the architectural design of the system using collaborating web servers and the technical solutions for creating personalised information in real time. Through the example of Pl@nteInfo®, the article shows that it is possible to build web-based decision support systems, where personalised advice is given in real time, based on user profiles together with distributed data and decision models. The article also analyses the user acceptance of the system. This analysis showed that the farmer and adviser subscribers are very dedicated users. Both the activity patterns and the preferences of subjects in the system are significantly different between these subscriber types, with farmers generally searching specific advice and advisors using the system to keep their knowledge up-to-date.