Realizing business value of agile IT applications: antecedents in the supply chain networks

This research develops a framework for organizational value creation from agile IT applications. Based on the four themes in the business value research—business process perspective, complementarities, application level of analysis, and extent of use—three antecedents (organizational fit, process assimilation, and network adoption) are identified as pre-requisites for realizing the value of agile supply chain applications. Advanced planning and scheduling (APS) systems are used as examples, and two case studies for their implementation in the electronics and consumer goods industry are reported to support the propositions. The theories of diffusion of innovation, complementarities, network externalities, and technology structuration are applied to develop the propositions for fit, assimilation, and network effects. Information sharing and industry clockspeed are identified as the moderating factors in the proposed model. The framework has both managerial and research relevance. The research guides managers regarding ways to more fully realize the value of agile applications and forms a basis for future research on the business value of IT applications.

Business process integration as a solution to the implementation of supply chain management systems

In the domain of supply chain management (SCM), various software packages have been developed for planning business strategies. To solve the problem of system productivity in applying planning packages, we propose a solution concept, business process integration (BPI), which fuses workflow and enterprise application integration (EAI) technology. Two characteristic policies are included in BPI. The first is to design the minimum set of business processes for real-time information sharing with planning packages without changing other processes. The second is to integrate several systems with EAI technology and to manage their execution with a workflow tool. Based on these policies, we propose various design templates and integration adapters. Our evaluation shows that using BPI, a target system can be developed with less manpower, in less time, and with higher quality than previous methods.     

Supply chain positioning strategy integration, evaluation, simulation, and optimization

When a company faces the global market, they would have to reengineer their processes and reorient their operation strategies, such as supply chain positioning strategy (SCPS) to benefit the most from a given situation. SCPS refers to actions taken by firms to respond to and satisfy customers' demand. The traditional concepts of production positioning strategy has been extended in this paper to develop various supply chain positioning strategies with a view that, for different production strategies, supply chain strategies should also be different. Obviously, each typical strategy has its advantages and limitations, and only fits for some certain scenarios. In this study, typical SCPSs have been defined, analyzed and classified. Supply chain dynamics and their impact on various strategies are also discussed. Subsequently, general integration approaches of the proposed strategies have been explored. Then, an approach for implementing SCPS in electronics industry is elaborated. It is shown that with integrated strategies, companies can get their desired optimal business values, even under great supply chain dynamics. It is expected that this method would be suitable for global organizations that has a need to cater to varying demands in different regions.     

On-demand e-supply chain integration: A multi-agent constraint-based approach

With e-business emerging as a key enabler to drive supply chains, the focus of supply chain management has been shifted from production efficiency to customer-driven and partnership synchronization approaches. This strategic shift depends on the match between the demands and offerings that deliver the services. To achieve this, we need to coordinate the flow of information among the services, and link their business processes under various constraints. Existing approaches to this problem have relied on complete information of services and resources, and have failed to adequately address the dynamics and uncertainties of the operating environments. The real-world situation is complicated as a result of undetermined requirements of services involved in the chain, unpredictable solutions contributed by service providers, and dynamic selection and aggregation of solutions to services. This paper examines an agent-mediated approach to on-demand e-business supply chain integration. Each agent works as a service broker, exploring individual service decisions as well as interacting with each other for achieving compatibility and coherence among the decisions of all services. Based on the framework, a prototype has been implemented with simulated experiments highlighting the effectiveness of the approach.     

SCOlog: A logic-based approach to analysing supply chain operation dynamics

In a complex business world, characterised by globalisation and rapid rhythms of change, understanding supply chain (SC) operation dynamics is crucial. This paper describes a logic-based approach to analysing SC operation dynamics, named SCOlog. SC operation is modelled in a declarative fashion and it is simulated following rule-based execution semantics. This approach facilitates the automated explanation of simulated SC operational behaviours and performance. The automated explanation support provided by SCOlog is found to improve the understanding of the domain for non-SCM experts. Furthermore, SCOlog allows for maintainability and reusability.     

Towards a framework of critical success factors for implementing supply chain information systems

Supply chain information systems (SCISs) have emerged as the core of successful management in supply chains. However, the difficulties of SCIS implementations have been widely cited in the literature. Research on the critical success factors (CSFs) for SCIS implementation is rather scarce and fragmented. Therefore, the objective of this paper is to compile a framework of CSFs for implementing SCISs. Based on 10 key articles focusing on ERP implementations, we have built a list of critical success factors as a starting point for the SCIS literature search. Thereafter, based on 21 SCIS articles, CSFs for supply chain information system implementation have been defined. The analysis showed that some CSFs have been ignored and important supply chain characteristics have been overlooked. Moreover, it is not always easy for project managers to know how to implement and apply CSFs in practice.     

Machine learning for dynamic multi-product supply chain formation

Recent trend in eCommerce applications toward effectively reducing supply chain costs—including spatial, temporal, and monetary resources—has spurred interest among researchers as well as practitioners to efficiently utilize supply chains. One of the least studied of these views is adaptive or dynamic configuration of supply chains. This problem is relatively new since faster communications over the Internet or by any other means and the willingness to utilize it for effective management of supply chains did not exist a few decades ago. The proposed framework addresses the problem of supply chain configuration. We incorporate machine-learning techniques to develop a dynamically configurable supply chain framework, and evaluate its effectiveness with respect to comparable static supply chains. Specifically, we consider the case where several parts go into the production of a product. A single supplier or a combination of suppliers could supply these parts. The proposed framework automatically forms the supply chain dynamically as per the dictates of incoming orders and the constraints from suppliers upstream.     

动态供应链与控制问题研究进展

首先,阐述了在新的信息网络,特别是无线射频识别技术(RFID)环境下,供应链系统动态情景问题;然后,讨论了动态供应链运作特性问题,并分析了动态供应链系统中经典控制、最优控制、模型预测控制、鲁棒控制等问题;最后,指出了动态供应链系统与控制进一步研究的几个问题.     

A review of supply chain complexity drivers

Studies on supply chain complexity mainly use the static and dynamic complexity distinction. While static complexity describes the structure of the supply chain, the number and the variety of its components and strengths of interactions between these; the dynamic complexity represents the uncertainty in the supply chain and involves the aspects of time and randomness. This distinction is also valid when classifying the drivers of supply chain complexity according to the way they are generated. Supply chain complexity drivers (e.g., number/variety of suppliers, number/variety of customers, number/variety of interactions, conflicting policies, demand amplification, differing/conflicting/non-synchronized decisions and actions, incompatible IT systems) play a significant and varying role in dealing with complexity of the different types of supply chains (e.g., food, chemical, electronics, automotive).     

Risk assessment and management for supply chain networks: A case study

The aim of this study is to show how a timed Petri nets framework can be used to model and analyze a supply chain (SC) network which is subject to various risks. The method is illustrated by an industrial case study. We first investigate the disruption factors of the SC network by a failure mode, effects and criticality analysis (FMECA) technique. We then integrate the risk management procedures into design, planning, and performance evaluation process of supply chain networks through Petri net (PN) based simulation. The developed PN model provides an efficient environment for defining uncertainties in the system and evaluating the added value of the risk mitigation actions. The findings of the case study shows that the system performance can be improved using risk management actions and the overall system costs can be reduced by mitigation scenarios.     

Determination and exchange of supply information for co-operation in complex production networks

Today's manufacturing industry is characterised by strong interdependencies between companies operating in globally distributed production networks. The operation of such value-added chains has been enabled by recent developments in information and communication technologies (ICT) and computer networking. To gain competitive advantages and efficiency improvements such as reduced inventory and higher delivery reliability, companies are introducing information exchange systems that communicate demand to suppliers and production progress information to customers in the network. This article proposes a system that supports co-operation in complex production networks by enabling companies to determine and exchange supply information with their customers. The requirements for such a system are analysed and it is embedded in a framework of supply chain management business processes. The system facilitates the determination and exchange of meaningful, reliable and up-to-date order status information from the supplier to the customer. Based on comparing the progress of an internal production order with a pre-defined milestone model for each product, the status of the customer order is determined and—in case of lateness—communicated to the customer together with an early warning. To demonstrate the developed supply information concepts and processes, the business process is implemented as a pilot system and evaluated by the user companies participating in the 5th Framework IST project Co-OPERATE.     

Enterprise modelling methodology for forward and reverse supply chain flows integration

The paper proposes a new enterprise modelling methodology called ERE-GIO applicable to supply chain reengineering and integration. It is based on two major phases: reverse engineering of the supply chain and then forward engineering. It takes advantages of previous enterprise modelling methodologies, especially CIMOSA. The application of the defined methodology on the logistics flow of an industrial company has allowed the integration of the reverse logistics flows in the traditional supply chain, thanks to the modelling of business processes and the flows related to it.     

An agent-based approach for e-manufacturing and supply chain integration

A major problem facing manufacturing organisations is how to provide efficient and cost-effective responses to the unpredictable changes taking place in a global market. This problem is made difficult by the complexity of supply chain networks coupled with the complexity of individual manufacturing systems within supply chains. Current systems such as manufacturing execution systems (MES), supply chain management (SCM) systems and enterprise resource planning (ERP) systems do not provide adequate facilities for addressing this problem. This paper presents an approach that would enable manufacturing organisations to dynamically and cost-effectively integrate, optimise, configure, simulate, restructure and control not only their own manufacturing systems but also their supply networks, in a co-ordinated manner to cope with the dynamic changes occurring in a global market. This is realised by a synergy of two emerging manufacturing concepts: Agent-based agile manufacturing systems and e-manufacturing. The concept is to represent a complex manufacturing system and its supply network with an agent-based modelling and simulation architecture and to dynamically generate alternative scenarios with respect to planning, scheduling, configuration and restructure of both the manufacturing system and its supply network based on the coordinated interactions amongst agents.     

Impact of the integration of tactical supply chain planning determinants on performance

In fulfilling customers’ orders, one of the goals of tactical supply chain planning is to satisfy the customers in terms of delivery efficiency, delivery quantity accuracy and on-time delivery. These performance objectives can be impacted by the way firms plan each of the three phases of the supply chain: procurement, production and distribution. Though the link between each of these phases and supply chain performance has been studied in extant literature, very few authors have considered all three phases at the same time. By adopting an integrated approach, this paper therefore aims to study the manner in which, taken together in one model, the planning determinants of the different phases impact on supply chain performance. It is important for managers to understand, from a holistic and integrated perspective, how a given combination of the planning determinants of the supply chain functions impacts positively or negatively on the performance of the supply chain. To carry out this study, this paper starts by proposing an integrated framework that is based on the SCOR model and the customer order decoupling point (CODP), followed by a five-step methodology for tactical supply chain planning. Then, using an analytical model and simulations, and based on a numerical example, it shows how the proposed methodology can be applied in a given decision-making situation. Our results enabled to identify the worst and the best combinations of planning determinants.     

Measuring supply chain resilience using a deterministic modeling approach

To achieve a competitive edge in an uncertain business environment where change is imperative, one of the significant challenges for an organization is to mitigate risk by creating resilient supply chains. This research proposes a model using graph theory which holistically considers all the major enablers of resilience and their interrelationships for analysis using an Interpretive Structural Modeling approach. The uniqueness of this model lies in its ability to quantify resilience by a single numerical index. The quantification of resilience will help organizations assess the effectiveness of various risk mitigation strategies. This will provide tools for managers to compare different supply chains while offering a deeper knowledge of how supply chain characteristics increase or decrease resilience and consequently affect supply chain risk exposure. Thus, the research supports organizations in measuring and analyzing supply chain resilience and facilitates supply chain decision-making. The proposed method could simplify the dynamic nature of environment for managing disruptions in a supply chain. This novel approach for determining the supply chain resilience index (SCRI) advocates the consideration of resilience aspects in supply chain design, thus giving a competitive advantage to achieve market share even during a disruption.     

Interactions of agents in performance based supply chain management

To acquire a competitive advantage in the expanding market, manufacturing companies should be able to manage their supply chain as much effective as possible. Measuring the supply chain performance is one of the main indicators of business success. Supply chain management (SCM) involves managing the flow of materials from suppliers to manufacturing units. This paper proposes a SCM model with performance measurement capabilities. The model is designed in such a way that it well suits to multi agent systems and related implementations. This paper highlights the components of the model especially pointing out the key parameters of performance indicators.     

Challenges in business systems integration

Four main frameworks for intercompany relationships (SCOR, CPFR, ISA95 and OAG) are discussed and compared. The link between the frameworks and different supply chain integration applications such as ERP, CRM and VMI are pictured. Finally the state-of-the-art, future state and challenges of the supply chain integration applications are discussed. It is concluded that the main challenge with respect to frameworks supporting business systems integration is to extend them with implementation functionality to better support business system application development. An example of this is customer requirement fulfillment processes such as product development and order fulfillment. Not only do they cross the borders of the company's departments (sales, logistics, purchasing, etc) but also various companies in the supply chain. In spite of this development, business integration across systems and borders are still not matured and to a large extend based on human interaction.     

A genetic algorithm approach for multi-objective optimization of supply chain networks

Supply chain network (SCN) design is to provide an optimal platform for efficient and effective supply chain management. It is an important and strategic operations management problem in supply chain management, and usually involves multiple and conflicting objectives such as cost, service level, resource utilization, etc. This paper proposes a new solution procedure based on genetic algorithms to find the set of Pareto-optimal solutions for multi-objective SCN design problem. To deal with multi-objective and enable the decision maker for evaluating a greater number of alternative solutions, two different weight approaches are implemented in the proposed solution procedure. An experimental study using actual data from a company, which is a producer of plastic products in Turkey, is carried out into two stages. While the effects of weight approaches on the performance of proposed solution procedure are investigated in the first stage, the proposed solution procedure and simulated annealing are compared according to quality of Pareto-optimal solutions in the second stage.     

A multi-criterion interaction-oriented model with proportional rule for designing supply chain networks

Supply chain management has offered a way to improve the industrial environment becomes more competitive. While, the commonly seen methodologies may be effective in solving the production–distribution problem only from supplier- or customer-oriented consideration, those cannot present the interactive relationship between upstream and downstream enterprises. In the competitive semiconductor industry environment, considering the viewpoints of the supplier and consumer simultaneously is particularly required, because multiple manufacturing and demanding steps are performed at separate situations, concurrently. In this paper, we propose an interaction-oriented approach, which bases on the analytic hierarchy process (AHP) methodology and proportional rule, to solve the semiconductor distribution problem with multiple quantitative and qualitative criteria. The developed approach gives an expected satisfaction for the all participators of the whole chain while the cooperative information is shared perfectly and effectively. Analysis results demonstrate the proposed methodology is efficient and effective through a real world case study.     

Integrating multi-agent negotiation to resolve constraints in fulfilling supply chain orders

As the order fulfillment process (OFP) in supply chains shifts to outsourcing paradigm, the OFP performance relies on the coordination among supply chain partners to reach executable and effective plans. The coordination of OFP among supply chain partners can be viewed as a distributed constraint satisfaction problem (DCSP). This study adds the multi-agent negotiation mechanism to enhance the existing methods to solve the DCSP, and then evaluates the integrated system’s performance through experimentation on the OFP in the context of the metal industry. The experimental results show that the integrated system outperforms the existing distributed constraint satisfaction algorithms in various demand patterns.