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How Internet of Things Influences Human Behavior Building Social Web of Services via Agent-Based Approach


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The paper discovers potential human interactions with growing amount of internet of things (IoT) via proposed concept of Social Web of Services (classical social web with smart things - daily life objects connected to the internet). To investigate the impact of IoT on user behaviour patterns we modelled human-thing interactions using agent-based simulation (ABM). We have proved that under certain conditions SmartThings, connected to the IoT, are able to change patterns of Human behaviour. Results of this work predict our way of living in the era of caused by viral effects of IoT application (HCI and M2M connections), and could be used to foster business process management in the IoT era.
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Mikhail KOMAROV*1, Nikita KONOVALOV*2 and Nikolay KAZANTSEV*3
Abstract: The paper discovers potential human interactions with growing amount of
internet of things (IoT) via proposed concept of Social Web of Services (classical social web
with smart things - daily life objects connected to the internet). To investigate the impact of
IoT on user behaviour patterns we modelled human-thing interactions using agent-based
simulation (ABM). We have proved that under certain conditions SmartThings, connected to
the IoT, are able to change patterns of Human behaviour. Results of this work predict our
way of living in the era of caused by viral effects of IoT application (HCI and M2M
connections), and could be used to foster business process management in the IoT era.
Keywords: Internet of Things, Internet of Service, Web of Service, Social Web of
Service, business model, Agent-based theory, smart home, virality, digital transformation
1. Introduction
No one in 90s may even thought that in 20 years 4 billion IPv4 addresses will not be enough
to satisfy Internet connection demand. Already in 2008-2009 the number of Internet-
connected devices exceeded the number of people on the planet that we consider as a starting
point of structural changes described in this article. Cisco Internet Business Solutions Group
proclaimed it as a start of Internet of Things era [9]. Academia researchers have widely
studied these changes last years and coined more notions: Internet of Services (IoS) and Web
of Services (WoS). Even though these terms look very similar, they have noticeable
distinctions: they enhance, overlap and supplement the original IoT concept. We summarised
the main notions used in the article in the Table 1.
* Faculty of business and management, National Research University Higher School of
Vol. 41 (2016)
DOI: 10.1515/fcds-2016-0012
No. 3
ISSN 0867-6356
e-ISSN 2300-3405
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Table 1. Main definitions used in paper
1 Smart thing /
smart object
Objects that are called smart carry chunks of
application logic that let them make sense of
their local situation, intercommunicate and
interact with human users via IP protocol. Kortuem [15]
2 Internet of
Things (IoT)
he worldwide network of interconnected
objects uniquely addressable based on standard
communication protocols.
RFID group
3 Internet of
Services (IoS)
the global infrastructure that uses the Internet as
a medium for offering and selling services -
tradable goods. It r
epresents a model of IoT
(self-) organization.
[6], [13], [22]
Web of
the network of interconnected services [6,13]
5 Social Web of
The network of shared services by people and
devices via social networks [6,13]
The main goal of our research is to check how the raising number of internet connected
devices influence users. We do it providing and testing a simulation model of SWoS as a
reasoning tool for enhancing IoT business models. Firstly, we analyse an existing benchmark
of IoT business model through the prism of Osterwalder Canvas framework [18] (chapter 2),
apply Agent based modelling simulation (chapter 3) and describe practical application of
models (chapter 4).
2. The raise of things
From its foundation, the Internet is constantly improving to be more and more
personalized especially during the last two years. Online environment is already about to
M. Komarov, N. Konovalov, N. Kazantsev
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aggregate each aspect of individual’s everyday life, for example, controlled via mobile
device. Business in its turn, goes digital as well: virtual workplaces and processes, digital
customers and digital “Things”. The whole picture is seen as a digital “Ecosystem”, where
enterprises are connected with its suppliers, distributors and customers in a common digital
network. Making business in such Ecosystems is more profitable for companies due to
economies of scale, as they are no longer acting as individual corporate entities. Accenture
Technology Vision 2015 names this trend “We-Economy [1].
These concepts lead appearance of the new business models [6,13]. For instance, by
monitoring of IoT products lifecycle, companies are able to sell devices directly to the
customer at the very moment when such need occurs. By embedding the IoT into social
networks and providing mobile and ubiquitous access to its services, companies improve
their predictive analytics. Meanwhile Cloud technologies play a role of intermediate platform
to connect users, “Things” and Enterprises into a digital Ecosystem [11].
2.1. Smart home a benchmark of Smart Thing business initiatives
The problem of unified control of all smart devices exercised the minds of such market
incumbents as Microsoft, Cisco and others, but their projects had little success. However,
during CES 2014 conference Samsung4 presented their new attempt. The developed app for
smartphones or TVs (with Android OS, apparently) let people control home appliances, for
example heating system or turn the lights on and off when they are not home with three main
functions: device control, home view and smart customer interface. Home View, another part
of the service, let people check up on their home using appliance cameras. Moreover, a
customer service component alerts people when their appliances need replacing or servicing
- something manufacturers would clearly enjoy.
A dedicated Smart Home software protocol (SHP) connects the related devices
(refrigerators, washers and dryers, ranges, microwaves, dishwashers, vacuums, smartphones,
TVs, gears, audio systems, cameras, computing devices and LED lighting)) and opens access
for other vendors, if they choose to get on board. The company plans to eventually expand
the Smart Home service to cover home-energy, secure home access, health care, and “eco
home applications” through the partnerships with third-party service providers.
There is no detailed information on how exactly operates their platform, and we suppose
that all third-parties devices could be included into this app only via agreements with
Samsung. The business model of its service is shown on (Fig.1):
4 Leading Korean company is a major manufacturer of home appliances like washing machines and
refrigerators, not to mention smartphones
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Figure 1. IoT influenced Smart Home Business model
For today, the main limitation for new market players is the range of supported devices
and their availability. It is crucially important to work with the most popular and affordable
smart devices in order to sweep the market. The biggest competition today is on US market,
where there are several competitors and maximal share of iOS devices than in other countries
[6]. At the same time, in other countries, Samsung has more power, because the accessibility
of its competitors’ devices is limited while Samsung products are readily available. However,
there is still an opportunity to beat the electronic giant, because of the type of supported
devices. While Samsung operates with its own appliances, which are rather massive and
expensive, it is possible to enter the market with smaller, cheaper and simpler devices like
sensors and power outlets offered by SmartThings [24] and Revolv [20].
The market of smart devices control application is still unsaturated, which leaves an
opportunity for new players. There are also several companies, which provide means of
communicating to any service via an encrypted P2P connection (Weaved) [25] or different
services for developers (Microsoft Home OS and others). However, these three described
company are the main pretenders for the unified method of controlling smart devices.
What happens when the number of smart things connected to Smart Home and mother
IoT-influenced business models will emerge? How that will affect human behaviour
To investigate that in the next chapter we use Agent based modelling (ABM).
M. Komarov, N. Konovalov, N. Kazantsev
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3. Agent based model simulation
3.1. Agents
ABM simulation is a perfect solution for scrutinizing the aspects of complex systems,
which comprise interacting agents. Bonabeau [3] highlighted three main benefits of this
approach: it captures emerged phenomena, has a natural-language description and flexibility.
What is more, ABM models could be classified depending on their purposes and modelling
approach by Borshchev [5]. In our research we used simulation model to track the execution
through the discrete states, analyze dynamics and interactions within the algorithm suggested.
According to Macal and North [17], an agent should possess the following patterns:
Rules to define agent behavior and decision-making
Protocols to communicate with other agents within the system
Have autonomous and self-directing functionality
Be goal-oriented
Taking to consideration these patterns, we have highlighted two types of agents in the
Type 1: a Human
Type 2: a Smart Thing (ST) - any electronic gadget with acting scripts, connected to the
As we proceeded with individual agent behavioural rules, the model could be classified
as a micro level simulation [4]. Both types of agents have their own attributes in order to
trigger behavioural patterns within current simulation process algorithm. Epstein [7] found
out that the understanding of social interactions lies in a deep process analytics from which
these interactions arise. In order to scrutinize the simulation’s results we found out 3 potential
1. Smart Things interaction is able to shape a fully viral behavioral trend under the
suggested default algorithm conditions.
2. Smart Things interaction is able to shape a partly viral behavioral trend under the
suggested default algorithm conditions.
3. Smart Things interaction, supported with human social effects is not able to shape a
behavioral trend under the suggested default algorithm conditions.
We have modelled the interaction between Human and ST according to the subjective
and average resource requirement. Resource Requirement (RR) is random and specific to
each Human agent numeric value, which shows optimal outcome of the Resource usage for
concrete Human agent. Either it could be subjective for the concrete Human with individual
machine settings or Human agent can accept a requirement trade off, offered by the ST, and
receive Average RR with default machine settings (Fig.2).
According to the model (Fig.1), it takes more time for Human to use Resource and get
subjective RR (i.e. making choice, machine tune-up, etc.), than to use default setting with
How Internet of Things influences human behavior ...
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average RR suggested by Smart Thing. This motivates Human for insignificant N% RR
tradeoff. In case the current average RR differs by less than N% from the subjective RR,
Human will use default average value instead of subjective one.
Figure 2. UML visualization of Smart Thing simulation
3.2. ABM description
We have pre-defined a list of conditions before simulation:
1. We assume that one Human has one Smart Thing
2. Humans interact with each other according to the simple random social graph
3. Smart Things are all connected into a one single net, so they can calculate the average
4. Social nature of Human agents influences on their decisions (Once three of four
socially connected agents start using the average RR mode, the fourth Human will switch to
this mode as well, no matter what the trade-off percentage is.)
Out of respect to the visual aspects, we did a simulation using random social network of
20 Human agents, using their 20 Smart Things (ST). Relations quantities between Humans
were randomly generated from 6 to 8 for each agent, representing a social graph (Fig.3, 4).
ST were interconnected into a single network.
M. Komarov, N. Konovalov, N. Kazantsev
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Figure 3. Social graph for Human agents
This model requires several stages of simulation:
1. On the first stage, all the humans have subjective RR (SRR) mode and randomly get
their value from 1 to 100. Smart Things, interconnected in the net, calculate the average value
of RR. We assume that the number of agents during the simulation is constant.
2. After that, STs choose Humans with N% difference between subjective and average
RR to make an trade off offer (Due to the sample size, trade-off percentage was set as 20%).
These Humans choose the average RR and will use it on further stages.
3. At the beginning of the second stage, each Human agent checks if any three of his
social friends switched to the average RR. In this case, this agent switches as well. Then,
Humans use their Resources according to the chosen RR mode. After that, SmartThings
calculate the new average RR and start looking for the new humans with possibility of 20%
4.On the further stages, the cycle repeats.
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Figure 4. Social graph for ST agents
3.3. Simulation result
In our simulation, different factors were evaluated coherently one by one to define the
extent of trend virality. These factors are trade off percentage level, number of social nets per
agent, value corridor for randomly generated subjective RR.
Each factor was divided into three value corridors, meanwhile other factors’ values were
fixed. The most effective way to create a fully viral trend appeared to be agent trade off
percentage level. It signifies that the more flexible decisions are made by an agent, the more
viral the trend is. Moreover, the number of social nets per agent plays a vital role as well.
According to the Appendix 1, fewer nets quantity could decrease trend virality drastically. It
took 27 attempts to reach a fully viral trend with 1 to 4 nets amongst 20 agents. Finally, value
corridor for subjective RR describes dispersion of agents’ preferences. It is easier to reach a
fully viral trend when Humans have similar preferences for resource requirement.
However, depending on the sample size, number of social relations and SRR limitations,
the trend may occur to be partially viral. In this case, not all of the Human agents will switch
to the AVG RR mode. It is proved by the number of simulation attempts, which were done
until fully trend were achieved and all agents were switched.
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Detail representation of simulation No.5 (see Appendix 1) is shown on the Figure 5.
Vertices of the graph are named according to the mask XXAVGYY, where:
XX is the number of simulation stage, on which agent switched his mode,
AVG average value for RR,
YY ID of an agent, from 1 to 20.
Figure 5. Representation of Smart Thing simulation
Depending on the number of social relations between the Humans and their quantity, the
simulation leads to strengthening the trend. In our case, all the Human agents were influenced
by the ST proposal during the fourth attempt. On the larger samples, ST proposals may not be
that influential.
Overall, the SmartThings, connected to the IoT, are able to change patterns of Human
behavior (see Fig.6).
How Internet of Things influences human behavior ...
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Figure 6. Representation of Smart Thing simulation
Overall, we can conclude that that under the given simulation conditions and agents
quantity, two different types of trend were set: fully viral trend (all the agents switched their
mode) and partly viral trend. This means that options 1 and 2 are observed within given
simulation conditions. Absolutely viral trend (achieved at the first attempt) was reached with
the following simulation conditions:
1. Either trade off percentage level for subjective RR was set at abs. 50% from the
current stage average RR level,
2. Or each Human agent was acquainted with 40%-60% of other agents within the
whole net,
3. Or scatter of random subjective RR was narrowed to 30%-70% value corridor.
Lower levels of presented conditions lead to the option 2 - partly viral trend. Option 3 -
was not detected under given simulation conditions.
3.4. Outcomes
This IoT ABM simulation is good example of slight manipulation on the trends usage
through SmartThings’ mode setting. Companies can influence these trends by controlling the
IoT networks and setting default modes for their smart products and, as a result, sell advanced
settings for SmartThings separately. This business model is very similar to nowadays concept
of InApp Purchases (IAP) and paid Download Content (DLC) embedded in numerous mobile
applications and computer games. This enhancement allows setting a selling price at the
lower level and compensate costs by offering IAP, and paid DLC.
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4. Concept development and further research
After this work was presented in Sydney DataCom iThings 2015, we received multiple
questions where it could be applied except prediction analysis. There is an obvious area
novel process management methodologies considering agents within social web of things.
Subject-oriented Business Process Management (S-BPM) is a relatively new approach
for the overall handling of work procedures in organizations from analysis to IT-based
execution including cognitive approach [10]. It focuses on the acting entities in processes
(people, software, information systems, services, etc.) and their interactions to achieve the
process goal. The explicit stakeholder and communication orientation makes it a promising
candidate to overcome major drawbacks of traditional BPM as there are deviations of lived
processes from their specification (model-reality divide), giving away opportunities for
improvement proposed by employees (lost innovation) and slow adaption of organization
and IT to changing requirements. With its easy-to-understand and easy-to-use notation based
on the SubjectPredicateObject scheme of natural language, S-BPM facilitates semantic
and organizational integration of people in the design of their work procedures. On the other
hand, a clear formal semantic behind the graphical notation allows automatic code generation
for workflow execution at runtime. Hence, stakeholders can instantly test the models they
created and iteratively improve and complete them until they are considered ready for going
live and being executed by a workflow engine. This leads to seamless roundtrip engineering
based on a common understanding of both business and IT people and can significantly
increase organizational agility. S-BPM is not just another modelling language but also a
comprehensive methodology spanning the whole business process management life cycle. It
suggests a paradigm shift from the traditional control flow-based view to a stakeholder and
communication-oriented view on business processes. Subjects represent the active entities in
a process and behave in a certain way to accomplish the goal. Their behaviour includes
exchanging messages and performing activities on business objects. Hence, a subject-
oriented specification of a process follows the standard sentence semantics of natural
language consisting of subject, predicate and object. However, S-BPM is a successfully
implemented for business process management it is strongly required to have agent based
model simulation.
In this regard, it is necessary first to arrange simulation in order to understand how our
smart things will act as agents, become independent subjects in one process, and object in
another process. Furthermore, it is required to create an integration platform between IoT
vendors and data consumers.
5. Conclusion
The developed business model of Social Web of Services combines the idea of common
social web and usual service selling, increase the quantity of revenue streams and enhance
usual suggested ways of controlling smart devices. It may be the transition way to full Web
of Services and it can increase people's way of living by creating “smarter world”.
Provided ABM simulation showed that companies might manipulate human behavioural
patterns through ST cooperation and social effects. As a result, there are required usage
How Internet of Things influences human behavior ...
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setting trend could be created. This leads to the main enhancement of the developed business
model of Social Web of Services. A number of revenue streams is increased: enterprise is
able to sell additional settings as paid In-Machine Purchase or Download content (DLC)
where customer relationships are individualized due to subjective preferences.
Information security, information privacy and legitimacy are obstacles that we need to
avoid on the way of concept realization. We are sure, that the question of systematic resilience
should be the first thing solved before launching the platform. Moreover, we recommend the
ownership to be shared not only with private companies, but also with government officials,
and perhaps, while the service is international, its localizations in different countries should
be separated in order to protect users from different restrictions of the local government.
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The paper is an extended version of the paper presented at the International
Conference on Big Data Intelligence and Computing (DataCom 2015),
Chengdu, China, December 19-21, 2015
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Table 2. Aggregated examples of ABM simulation result.
till fully
on stages
Trade off
Social Nets
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... The IoS suggests that every connected system has its own API, and a large amount of data produced by things can be shared with the data consumers, i.e., apps, people, or other items. Komarov et al. [36] (P8) bring an IoT influenced smart home business model in which a protocol connects the related devices (refrigerators, washers, microwaves, smartphones, TVs, etc.) and opens access for other vendors to get on board. Such a model can be expanded to cover home-energy, or "eco-home applications" through the partnerships with third-party service providers. ...
... Their interactions inside these online communities follow several interesting patterns. Komarov et al. [36] (P8) provided an agent-based model simulation showing that companies might manipulate human behavioral patterns through smart things cooperation and social effects. As a result, a required usage setting trend could be created, leading to a business model of a social web of services, which would be the network of shared services by people and devices via social networks. ...
... However, social networks present challenges to the applicability of traditional sentiment analysis techniques, due to their sparse, multilingual, and noisy content [41]. In addition, information security, information privacy and legitimacy are obstacles that must also be considered [36] (P8). ...
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... In this aspect, a promising concept is to integrate as much as possible each part of the IoT-based system with one another. As smart devices can mimic human behaviour and interact with each other [202,203], in the near future IoT networks are expected to have a certain degree of consciousness [204], and this concept is called Social Internet of Things. By integrating all the possible aspects of people in technologies like IoT, future advances are expected to focus on the insertion of the human dimension. ...
The human dimension plays an essential role in the energy performance of buildings and is considered as significant as technological advances. Several studies highlighted the negative influence of occupant behaviour in underperforming buildings, while some support that technological innovations may reduce human-related uncertainties. Thus, one may consider that fully automated smart buildings are essential to achieve energy efficiency. However, if technology excludes people from decision-making processes, low acceptance and comfort/welfare levels may be reported from users. Therefore, the right combination of humans and technologies are expected to solve these problems. Buildings are emerging as complex Cyber-Physical Systems, including the Social dimension, and this provides an excellent opportunity to achieve high-performance outcomes, considering both technical and social aspects. Thus, the right choice among available up-to-date behavioural sensing – comprising active and passive sensors, as well as Kinect technology – are important in the Internet-of-Things (IoT) era. IoT-driven buildings can use real-time monitoring data to inform users and drive behavioural-based consumption change, which is an important aspect to achieve high-performance buildings and deliver user-centred services. An essential feature in this regard is to allow for human-in-the-loop approaches enabled by human-centric computing and smart devices, which has grown fast in the last few years. This literature review summarises applications and main challenges related to the combination of the human dimension and technological innovations in the building sector. This combination is expected to increase user welfare and reduce the energy consumption in buildings, as human and machine components of intelligence may complement each other regarding building performance.
... Also, S-BPM is considered as a suitable approach for handling a network of individual intelligent agents in the IoT ecosystem. In this context a serious focus has to be put on the explicit understanding of such active elements acting as a subject in one process and also as an object in a different process [43]. ...
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In order to improve the effect of remote ideological and political education, this paper builds a Web ideological and political education system based on Agent technology, and adopts a three-layer abstract system architecture including Web service layer, Agent processing layer and service process layer. Moreover, based on this architecture foundation, this paper proposes an Agent-based Web service integration structure, and illustrates the overall execution process of the system through the execution process of the system integration structure. Then, this paper proposes the organization structure of multi-agent in the Agent processing layer and the organization structure of service process in the service process layer of the system. In addition, this paper uses multi-agent system design to ensure the efficient operation of the entire system, and combines algorithms to implement system resource recommendation modules and practical teaching functions. Finally, this paper designs a control experiment to test the performance of the distance ideological and political education system constructed in this paper. The research results show that the system constructed in this paper has certain practical effects.
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Both business process management and digital transformation are areas which have been a topic of interest for both academia and practice. Since digital transformation is the creation of new, innovative business models and/or change and improvement of the existing business model with the help of digital technologies, one could raise a question regarding the role which business process management plays in digital transformation. With the purpose of shedding some light on that, this paper presents a theoretical framework for observing the link between business process management and digital transformation. Moreover, the results of an extensive literature review and analysis with the regards to the presented framework have been given. The results confirm the important role of business process management in digital transformation. However, the results also indicate the need for further research and greater understanding of practice.
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This book should be understood as an invitation to capture, reflect, and stimulate discussion around many different aspects of the design of organizations. All interested persons should be encouraged to simply try this pragmatic approach to Business Process Management. There are already many companies and institutions that have been trying it successfully, and they have been surprised that their processes have become intelligible to stakeholders.
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In this study we analyze co-adoption of several modern concepts of enterprise architecture creation and describe real-time business processes generation on global cloud-based self-generated business service basis to increase the agility of enterprise. We simulated the process of generating the business model started by particular business request with the support of subject-oriented business process management approach that results in particular business process architecture, which is approved or rejected/corrected by board of directors and architectural committee of the enterprise. During that generation all necessary requirements for supporting resources, such as information, know-how, intellectual and professional skills, inputs and outputs, quality and operational risk limitations, moderation, control and monitoring, are formed. On a next twist of the development all formed requirements are to be satisfied by appropriate selections from the cloud facilities and again approved. Finally after several iterations business model will be created in reality and could be executed with predicted results. Briefly that means that certain sets of valued and weighted business process replicas are located in Clouds. In addition to that, in this article we have provided the advanced view on the topic with attempt to install a virtual SOA torrent that catches services from the Internet and makes them available to customers and represents a business service basis for real-time business processes.
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This volume contains a selection of papers from the First Workshop on Subject- Oriented Business Process Management (S-BPM ONE). Establishing a multi- and cross-disciplinary interchange of underyling and applied concepts, successful appli- tion studies, and innovative development ideas, the workshop emphasized the pro- tive realization of role- or actor-oriented modeling on the basis of exchanging m- sages when accomplishing tasks. The workshop was organized as a forum for the discussion of foundations, achievements, reflections, and further developments. In this way, its contributions not only addressed the current state of the art, but also the various lines of research and development, either running or planned. The state of the art is reflected in terms of concepts, modeling language, and tool features on the one hand. On the other hand, it is reflected through the discussion of industrial case studies. These indicate the current practice when implementing the subject-oriented BPM paradigm in industrial settings. By challenging conceptual foundations they also allow us to define a common ground for future developments in research and practice. The S-BPM ONE contributions focus on challenges arising from the evolution of service-oriented architectures and the need for more flexible business organizations. The latter require coherent and adaptive representation and processing techniques for business process modeling and execution. Corresponding technologies have to be grounded in theories of computer science, in order to provide an adequate infrastr- ture for thorough BPM including technology-enhanced change management.
Agent-based modeling and simulation (ABMS) is a relatively new approach to modeling systems composed of autonomous, interacting agents. Agent-based modeling is a way to model the dynamics of complex systems and complex adaptive systems. Such systems often self-organize themselves and create emergent order. Agent-based models also include models of behaviour (human or otherwise) and are used to observe the collective effects of agent behaviours and interactions. The development of agent modeling tools, the availability of micro-data, and advances in computation have made possible a growing number of agent-based applications across a variety of domains and disciplines. This article provides a brief introduction to ABMS, illustrates the main concepts and foundations, discusses some recent applications across a variety of disciplines, and identifies methods and toolkits for developing agent models.
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Middleware platforms have become an essential part of the modern Internet of Things (IoT) and more recently Web of Things (WoT). These platforms provide the necessary tools for data storage, processing and visualization as well as for discovery, management, and interconnection of devices, which are used by manufacturers, system integrators and end users. In this paper we first present our view on the evolution of the Web and propose a new definition of Web 3.0 based on the number of content originators, which to the best of our knowledge hasn’t been formalized in the same way before. We then give an overview of the existing IoT platforms, including our own solution, outlining technological trends on the one side and important concerns on the other. In the end, we discuss the possible direction towards the Web of Services as a potential way to solve one of the problems.
Superior utilization of technology is the most important ingredient of economic success. The concepts and issues encompass both macro-economic policy and individual firm-level strategy and operations. The necessary response to improving performance in managing technology must involve business, academia, and government. To manage technology effectively requires a better understanding not only of technology itself, but of the evolution, maturation, and diffusion of technologies throughout the global economy. The task of managing technology is integral to, and essentially synonymous with, strategic management.
Short-time information and communication technology has conversion one of the main components of modern society and Shadow on political, economic, social environment and... and is formed the base of successful new company. Similarly, ICT has increased the value of learning process, organization and management of educational institutions. Internet a driving force for many advances and innovations in developed and developing countries. Countries should be able to received progress ICT benefit. To achieve this, a group of experts with strong background of information and communication technology, independent from computer platforms or software environments must be taught to advances in technology led to development work, and changing on work organization. Therefore, the strategic policies in information technology should be considered for implementing competence of individuals in critical thinking, general competence, competence in the field of ICT expertise and ability to work, decision making, dealing dynamic success, work as members of group and effective communication occurrence.
Agent-based computational modeling is changing the face of social science. In Generative Social Science, Joshua Epstein argues that this powerful, novel technique permits the social sciences to meet a fundamentally new standard of explanation, in which one "grows" the phenomenon of interest in an artificial society of interacting agents: heterogeneous, boundedly rational actors, represented as mathematical or software objects. After elaborating this notion of generative explanation in a pair of overarching foundational chapters, Epstein illustrates it with examples chosen from such far-flung fields as archaeology, civil conflict, the evolution of norms, epidemiology, retirement economics, spatial games, and organizational adaptation. In elegant chapter preludes, he explains how these widely diverse modeling studies support his sweeping case for generative explanation. This book represents a powerful consolidation of Epstein's interdisciplinary research activities in the decade since the publication of his and Robert Axtell's landmark volume, Growing Artificial Societies. Beautifully illustrated, Generative Social Science includes a CD that contains animated movies of core model runs, and programs allowing users to easily change assumptions and explore models, making it an invaluable text for courses in modeling at all levels.