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Purpose: Technological innovations and frameworks that provide a framework for unification have evolved to improve information exchange across organisational units and information security. These integration technologies share and communicate information using defined protocols and different data. Service-oriented architecture (SOA) is a significant emerging approach that enables modular design solution construction.

Methodology: These designs are beneficial when many apps operating on different architectures and networks need to connect. A well-defined strategy and company-specific guidelines are essential for ensuring the firm’s systematic adoption of such an architecture. The critical components of MASSOASCM ‘(Multi-Agent System Service Oriented Architecture Supply Chain Management’ are a multi-agent system (MAS), a service-oriented structure, and supplier management. The MASSOASCM model has been made, and a production unit has been made to show how it works.

Findings: It has been stated that it saves development costs, and inventory management, all of which are critical concerns in any company. Our goal is to create an inventory control approach that relies on MAS and SOA but also a simulation that demonstrates how it works and may enhance Supply Chain Management (SCM) productivity in a production plant.

Practical Implications: The SCM implementation comprises three different services: SCM, SOA, and MAS. These facilities are constructed, maintained, planned, and implemented individually before being brought together collectively using MAS and SOA techniques.

Decision support systems are becoming an indispensable tool for managing complex supply chains. The purpose of this paper is to develop a multi-agent-based supply chain management system that incorporates big data analytics that can exert autonomous corrective control actions. The effects of the system on supply chain agility are explored.

For the development of the architecture of the system, a sequential approach is adopted. First three fundamental dimensions of supply chain agility are identified – responsiveness, flexibility and speed. Then the organisational design of the system is developed. The roles for each of the agents within the framework are defined and the interactions among these agents are modelled.

Applications of the model are discussed, to show how the proposed model can potentially provide enhanced levels in each of the dimensions of supply chain agility.

The study shows how the multi-agent systems can assist to overcome the trade-off between supply chain agility and complexity of global supply chains. It also opens up a new research agenda for incorporation of big data and semantic web applications for the design of supply chain information systems.

The proposed information system provides integrated capabilities for production, supply chain event and disruption risk management under a collaborative basis.

A novel aspect in the design of multi-agent systems is introduced for inter-organisational processes, which incorporates semantic web information and a big data ontology in the agent society.

A traditional supply chain, all too often, is a sequence of weakly connected activities both within and outside the organization and leads to many misalignments. Tackling this inherent lack of coordination is a major value creation opportunity for supply chain managers. This paper aims to present a coordination framework, called ASCEND, to align the inventory decisions in decentralized supply chains.

The framework rests on three pillars – multi‐agent technology, coordination theory, and optimization technology. Inventory alignment is transformed into a decentralized constraint satisfaction optimization problem, which is then solved using a genetic algorithm‐based coordination process. The guiding principle of this framework is the establishment of a proper incentive alignment mechanism through cost‐sharing and service level contracts, taking into account the associated dependencies.

The results of the pilot study indicate that the coordination framework reduces the supply chain inventory‐holding cost, compared with the “as‐is” scenario. Interestingly, the results also indicate that not all the supply chain partners will experience lower inventory costs in the absence of a proper incentive alignment mechanism. Only through cost sharing and service level contracts can the value of coordination be realized by each partner in a supply chain network!

The coordination approach is applied to a pilot supply chain. The results of the case study lead to 10.4 percent (average) reduction in supply chain inventory‐holding costs, validating the efficacy of the coordination framework.

This research has resulted in the development of a supply chain coordination framework, which requires the establishment of a proper incentive alignment mechanism, based on cost‐sharing and service level contracts, and taking into account the associated dependencies.

The objective of this paper is to present a model that uses multi‐agent system (MAS) technology to assist doctors based at rural areas to receive timely expert opinions from specialist doctors working in medical institutions like the Postgraduate Institute of Medical Research, Chandigarh or the All India Institute of Medical Sciences, New Delhi.

A MAS is a software entity wherein agent metaphor is used to represent human‐like intelligence and behavior. These agents are distributed over geographical areas and are part of software running at these sites. The foundation for this model lies in the fact that medical intelligence is distributed in nature and, if it is possible to bring this knowledge together, it could prove to be advantageous in providing improved health care to those people in rural areas. A few existing research works are included to demonstrate the usage of MAS in health care.

It has been observed that the health scenario in India is ranked poor world‐wide by international organizations and, with the increasing population, this will worsen.

Initially, the aim is to concentrate on a few medical departments only. It can be extended into more detailed framework.

Physical computing and networking infrastructure are required for practical implementation along with training for the doctors.

The primary beneficiaries of this system are likely to be those patients in the rural sector requiring expert medical opinion. The government health organizations will be able to provide quality medical facilities comparable with the medical facilities available in the developed nations. Currently this would seem to be a distant dream.

Cities evolved into quite complex urban systems. The rigid management process must reflect the complexity of the current political, social, and economic environment. With the vast city growth, citizens experience new difficulties – traffic congestion, pollution, immigration, overcrowding, and inadequate services.

In our research, we analyze problems and benefits that occur with the growing complexity and offer a new concept considering every city as a live and constantly developing complex adaptive system of many participants and actors that operate in an uncertain environment. These actors (residents, businesses, transport, energy, water supply providers, entertainment, and others) are the main elements of city life.

The new concept of “Smart City 5.0” is based on a previously developed model of Smart City 4.0 (compared with Industry 4.0) and implements the Urban Digital Ecosystem, where every element can be represented by a smart agent operating on its behalf. It is shown that smart services can interact vertically and horizontally in the proposed ecosystem, supporting competition and cooperation behavior based on specialized network protocols for balancing the conflicting interests of different city actors.

The chapter describes the design principles and the general architecture of the Urban Digital Ecosystem, including the basic agent of smart service, protocols of the agent’s negotiation, the architecture, and basic principles Smart City knowledge base.

The developed evolutionary methodology of implementation will ensure a minimum of disruptions to city services during its transformation into an urban ecosystem to harmoniously balance all spheres of life and the contradictory interests of different city actors.

The development of communication and artificial intelligence technologies has raised interest in connectivity and increased autonomy of automated earthmoving equipment for earthwork. These changes are motivating work to reduce uncertainties, in terms of improving equipment object detection capability and reducing strikes and accidents on site. The purpose of this study is to illustrate industrial drivers for automated earthwork systems; identify the specific capabilities which make the transformation happen; and finally determine use cases that create value for the system. These three objectives act as components of a technology roadmap for automated and connected earthwork and can guide development of new products and services.

This paper used a text mining approach in which the required data was captured through a structured literature review, and then expert knowledge was used for verification of the results.

Automated and connected earthwork can enhance construction site and its embraced infrastructure, resilience by avoiding human faults during operations. Automating the monitoring process can lead to reliable anticipation of problems and facilitate real-time responses to unexpected situation via connectedness capabilities. Research findings are presented in three sections: industrial perspectives, trends and drivers for automated and connected earthwork; capabilities which are met by technologies; and use cases to demonstrate different capabilities.

This study combines the results of disintegrated and fragmented research in the area of automated and connected earthwork and categorises them under new capability levels. The identified capabilities are classified in three main categories including reliable environmental perception, single equipment decision-making toward safe outcomes and fleet-level safety enhancement. Finally, four different levels of automation are proposed for earthwork technology roadmap.

Today's volatile condition of the market is forcing the manufacturing organizations to adapt the flexible manufacturing systems (FMS) to meet the challenges imposed by international competition, ever‐changing customer demands, rapid delivery to market, and advancement in technology. There are certain enablers, which help in the implementation of FMS or in the transition process from traditional manufacturing system to FMS. The utmost need is to analyze the behavior of these enablers for their effective utilization in the implementation of FMS. This paper aims to address these issues.

This paper presents a methodology based on graph theoretical approach for finding the feasibility of transition to FMS for any industry. A universal feasibility index of transition (FIT) is proposed that evaluates and ranks different organizations according to their capability to be converted into FMS. This FIT value is obtained from a permanent feasibility function obtained from an enablers' digraph of FMS.

The major finding of this paper is that one can judge whether a particular industry is fit for FMS or not by calculating its FIT value. This FIT value can also be utilized in ranking different industries for their possible transition to FMS.

The FIT obtained from a permanent function indicates the strength of enablers and their inter‐relations. More is the value of this index; more will be suitability of that organization for FMS adoption. In this way, managers can judge that a particular organization is suitable or fit for FMS implementation or not, without making the huge investments for such a complex production system and thus, minimize their risks.

Identification, classification of enablers into some important categories, and their analysis is a unique and innovative effort in the area of FMS.

There is still little support for the consumer decision‐making process on the web, especially when prices are not the primary property of a product. Reasons for that are complex product specifications as well as often volitional weak interoperability between e‐commerce sites. This paper aims to address this issue.

The semantic web is supposed to make product information more interoperable between different sites. Additionally, some products with limited time frames of availability, like real estates or second‐hand cars, require periodical searches over several days, weeks, or even months. For those kinds of products existing systems cannot be applied. Instant information about new offers on the market is therefore crucial. Wireless access to the web enables services to become instantaneous and to provide up‐to‐date information to users.

This paper presents a framework which is based on multivariate product comparison allowing users to delegate search requests to an agent. The success of the agent depends heavily on the matching algorithm. Fuzzy utility functions and the analytical hierarchy process are a very feasible combination for the scoring of offers.

The proposed system supports users finding products on the web matching specific user preferences and instantly informs them when new items become available on the virtual market. As a specific use case the framework is being applied to the real estate sector, because especially for this sector several shortcomings of the current support have been identified.

The paper aims to address regulator-management interactions in environmental policy with reference to direct regulations, social regulations and market-based regulation.

Revision of literature to identify the European Union regulations for companies producing polymers. Expert groups consultation to enrich the information and testing of the expert system (software).

Interactions between actors dealing with environmental policy from government and business sectors cause high and growing transaction costs; in The Netherlands during 1990-2007, they represented an increase from 17 to 21 percent of all environment protection costs. Rapid, 14 percent average annual growth followed the shift from the direct to social regulations in the 1990s. Instead of the shift, better interactions management could have saved nearly four billion euro a year in the EU. In support of this, a web-based expert system is developed in a consortium of small and medium size enterprises and expert centers from seven European countries.

The system, Environmentor, contains checklists with exemplary inputs, outputs, environmental standards and technologies for permits, process for implementation of environmental management systems, as well as an administrative model and auction for the EU emission trading.

Supply chain management represents a critical competency in today’s global business environment and has been the focus of considerable, but mixed, information systems research. The research described in this paper builds on work in multi‐agent systems to argue that intelligent agents offer excellent potential and capability for supply chain management, and contributes to discussion and theory pertaining to electronic markets and supply chain disintermediation. Argues that the knowledge associated with intermediation work represents a key mediating variable between disintermediating technology and supply chain efficacy and discusses how intelligent agent technology can be employed to both intermediate and disintermediate the supply chain, attaining the cost and cycle‐time benefits of disintermediation without the attendant loss of human knowledge and expertise. The paper outlines a number of implications for theory and practice in information systems, and it formalizes some important research questions through a contingency framework to help stimulate and guide future work along these lines.