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Power 4 Distribution Transformers are complex assemblies of metallic and insulating materials which generate equally complex electrostatic and electromagnetic fields.

Certain elements of Hayek’s work are prominent precursors to the modern field of complex adaptive systems, including his ideas on spontaneous order, his focus on market processes, his contrast between designing and gardening, and his own framing of complex systems. Conceptually, he was well ahead of his time, prescient in his formulation of novel ways to think about economies and societies. Technically, the fact that he did not mathematically formalize most of the notions he developed makes his insights hard to incorporate unambiguously into models. However, because so much of his work is divorced from the simplistic models proffered by early mathematical economics, it stands as fertile ground for complex systems researchers today. I suggest that Austrian economists can create a progressive research program by building models of these Hayekian ideas, and thereby gain traction within the economics profession. Instead of mathematical models the suite of techniques and tools known as agent-based computing seems particularly well-suited to addressing traditional Austrian topics like money, business cycles, coordination, market processes, and so on, while staying faithful to the methodological individualism and bottom-up perspective that underpin the entire school of thought.

This paper aims to contribute to the tactical and operational decision making of manufacturing and logistics operations by providing novel insights into modelling and simulation, based on complex adaptive systems (CAS).

The research approach is theoretically based on CAS with agent‐based modelling (ABM) as the implementation method. A case study is presented where an agent‐based model has contributed to increased understanding and precision in decision making at a packaging company in the UK.

The results suggest that ABM provides decision‐makers with robust and accurate “what‐if” scenarios of the dynamic interplay among several business functions. These scenarios can guide managers in the process of moving from policy space to performance space, i.e. concerning priorities of improvement efforts and choices of production/manufacturing policies, warehouse policies, customer service policies and logistics policies. Furthermore, it is found that ABM can include and pay attention to several aspects of CAS and thus provide understanding of, and explanation for, the patterns and effects which emerge in manufacturing and logistics settings.

Aided by agent‐based models and simulations, practitioners' levels of intuition can be enhanced since patterns on the macro level emerge from agents' interactive behaviour. Together with insights from CAS these emergent patterns can be explained and understood, and are thus beneficial for the improvement of decision making in companies.

The case presented distinguishes this paper from what has been written in previous articles on the application of ABM, since such articles have not produced any empirically verified results after implementation of ABM.

The purpose of this paper is to investigate the benefits and the barriers of agent based decision support (ABDS) systems in the supply chain context.

Two ABDS systems have been developed and evaluated. The first system concerns a manufacturing supply chain while the second concerns a service supply chain. The systems are based on actual case companies.

This research shows that the benefits of ABDS systems in the supply chain context include the possibility to increase versatility of system architecture, to improve supply chain visibility, to conduct experiments and what‐if analyses, to improve the understanding of the real system, and the possibility to improve communication within and between organizations in the supply chain. The barriers of ABDS systems in the supply chain context include the difficulty to access data from partners in the supply chain, the difficulty to access data on a higher level of granularity, and the difficulty to retrieve data from other information systems.

The research is explorative in nature therefore empirical data from similar and other research settings should be gathered to reinforce the validity of the findings.

This research provides knowledge and insights on how ABDS systems may be developed and used in the supply chain context and demonstrates its main benefits and barriers.

This research expands the current research of benefits of ABDS systems to the supply chain domain and also addresses the barriers of ABDS systems to a larger extent than previous research. Comparisons to other simulation based decision support systems are also given.

The purpose of this is to add both to the development of complex systems thinking in the subject area of operations and production management and to the limited number of applications of computational models and simulations from the science of complex systems. The latter potentially offer helpful decision‐support tools for operations and production managers.

A mechanical engineering firm was used as a case study where a combined qualitative and quantitative methodological approach was employed to extract the required data from four senior managers. Company performance measures as well as firm technologies, practices and policies, and their relation and interaction with one another, were elicited. The data were subjected to an evolutionary complex systems (ECS) model resulting in a series of simulations.

The findings highlighted the effects of the diversity in management decision making on the firm's evolutionary trajectory. The CEO appeared to have the most balanced view of the firm, closely followed by the marketing and research and development managers. The manufacturing manager's responses led to the most extreme evolutionary trajectory where the integrity of the entire firm came into question particularly when considering how employees were utilised.

By drawing directly from the opinions and views of managers, rather than from logical “if‐then” rules and averaged mathematical representations of agents that characterise agent‐based and other self‐organisational models, this work builds on previous applications by capturing a micro‐level description of diversity that has been problematical both in theory and application.

This approach can be used as a decision‐support tool for operations and other managers providing a forum with which to explore: the strengths, weaknesses and consequences of different decision‐making capacities within the firm; the introduction of new manufacturing technologies, practices and policies; and the different evolutionary trajectories that a firm can take.

With the inclusion of “micro‐diversity”, ECS modelling moves beyond the self‐organisational models that populate the literature but has not as yet produced a great many practical simulation results. This work is a step in that direction.

This paper aims to explore how omni-channel data flows should be integrated by specifying what data, omni-channel agents and information and digital technologies (IDTs) should be considered and connected.

A multiple case study method is used with 17 British companies. The studies are supported by 68 interviews with the case companies and their consumers, 5 site visits, 4 focus group meetings and the companies’ archival data and documentations.

This paper provides novel frameworks for omni-channel data flow integration from consumer and business perspectives. The frameworks consist of omni-channel agents, their data transactions and their supporting IDTs. Relatedly, this paper formalizes the omni-channel data flow integration in the forms of horizontal, vertical and total integrations and explores their contributions to the adaptability of omni-channel, as a complex adaptive system (CAS). It also discusses that how inter-organizational governance mechanisms can support data flow integration and their relevant IDT implementations.

The breadth and depth of the required IDTs for omni-channel integration prove the necessity for omni-channel systems to move toward total integration. Therefore, supported by CAS and inter-organizational governance theories, this research indicates how data flow integration and IDT can transform the omni-channel through self-organization and autonomy capability enhancement.

This research’s recommended frameworks provide a robust platform to formalize data flow integration as the omni-channel's core driver. Accordingly, it moves the literature from a basic description of “what omni-channel is” and provides a novel and significant debate on what specific data should be shared at what levels between which agents of the omni-channel, and with what type of relationship governance mechanism, to assure omni-channel horizontal, vertical and total integrations.

Perishable inventory management for the grocery sector has become more challenging with extended omnichannel activities and emerging consumer expectations. This paper aims to identify and formalize key performance measures of omnichannel perishable inventory management (OCPI) and explore the influence of operational and market-related factors on these measures.

The inductive approach of this research synthesizes three performance measures (product waste, lost sales and freshness) and four influencing factors (channel effect, demand variability, product perishability and shelf life visibility) for OCPI, through industry investigation, expert interviews and a systematic literature review. Treating OCPI as a complex adaptive system and considering its transaction costs, this paper formalizes the OCPI performance measures and their influencing factors in two statements and four propositions, which are then tested through numerical analysis with simulation.

Product waste, lost sales and freshness are identified as distinctive OCPI performance measures, which are influenced by product perishability, shelf life visibility, demand variability and channel effects. The OCPI sensitivity to those influencing factors is diverse, whereas those factors are found to moderate each other's effects.

To manage perishables more effectively, with less waste and lost sales for the business and fresher products for the consumer, omnichannel firms need to consider store and online channel requirements and strive to reduce demand variability, extend product shelf life and facilitate item-level shelf life visibility. While flexible logistics capacity and dynamic pricing can mitigate demand variability, the product shelf life extension needs modifications in product design, production, or storage conditions. OCPI executives can also increase the product shelf life visibility through advanced stock monitoring/tracking technologies (e.g. smart tags or more comprehensive barcodes), particularly for the online channel which demands fresher products.

This paper provides a novel theoretical view on perishables in omnichannel systems. It specifies the OCPI performance, beyond typical inventory policies for cost minimization, while discussing its sensitivity to operations and market factors.

A variety of equity-linked insurance contracts such as variable annuities (VA) and equity-indexed annuities (EIA) have gained their attractiveness in the past decade because of the bullish equity market and low interest rates. Due to the complexity of their inherent nature, pricing and risk management of these products are quantitatively challenging and therefore have become sources of concern to many insurance companies. From a financial engineer's perspective, the options in VA and those embedded in EIA can be modeled as puts and calls, respectively, and enable the use of numerical option pricing techniques. Additionally, values of VA and EIA move in opposite directions in response to changes in the underlying equity value. Therefore, for insurers who offer both businesses, there are natural offsets or diversification benefits in terms of economic capital (EC) usage. In this chapter, we consider two specific products: the guaranteed minimal account benefit (GMAB) and the point-to-point (PTP) EIA contract, which belong to the VA and EIA classes respectively. Taking into account mortality risk and suboptimal dynamic lapse behavior, we build a framework that quantifies the value of each product and the natural hedging benefits based on risk-neutral option pricing theory. With Monte Carlo simulation and finite difference methods being implemented, an optimum product mixture of those two contracts is achieved that deploys capital the most efficiently.

The paper aims to describe ideas and implementation of the computer tool for computer‐aided and recycling‐oriented design. Currently, there is a strong tendency to take into account the impact of a product on the natural environment. The authors concentrated on the issue of the recycling process of the product, taking into account the phase of its design. The purpose, structure, technology and example results are presented in this paper.

It was assumed that analysis will be performed based on a set of measures of a product. These measures (developed by the authors), describing the product from the recycling point of view, are calculated automatically, according to the changes (variants) in the product's model. The presented tool is based on agent technology. The structure of the system – the agents, its roles and communication between them – has been described.

The main achievement of the work presented in this paper is the method supporting eco‐design based on agent technology. Based on the analysis of the process of recycling‐oriented eco‐design, the authors designed and then implemented the tool that aids designers' activities in the area of eco‐design. The drawn‐up method supports decision making concerning designing environmental‐friendly products. Thanks to agent technology, the design process can be conducted in the distributed design environment.

The usage of the presented computer‐aided and recycling‐oriented system during the design process requires the duplication of some of the engineer's work. The analysis is performed within the presented tool, outside the typical contemporary design environment, such as CAD 3D systems. As a consequence, there is a need to enter the product structure into the described system, which can be inconvenient. The further work of the authors assumes implementation of this concept into a CAD 3D system.

There has been a limited amount of research work regarding application agent technology in the field of end‐of‐life oriented design. The structure of the system, the measurements and idea of extension of product structure are the original results of the work. The results could be implemented into commercial computer‐aided design systems, especially into its PLM (product lifecycle management) group, due to the weak representation of end‐of‐life phases in these tools.

As the modern manufacturing twining seamlessly with logistics operations for value adding services, logistics service is becoming more and more significant. Under this research background, the purpose of this paper is to introduce an innovative evaluation model for customer satisfaction using fuzzy analytic hierarchy process (FAHP).

This model uses triangular fuzzy concept to determine the weight of each index so that subjective or objective weighting is addressed. A case study from two large express companies in China is used to demonstrate the feasibility and practicality of the proposed model for examining customer satisfaction.

One of the key findings is that Company B has higher customer satisfaction than Company A due to its quick response and flexible logistics strategy. This paper has several contributions. First, A FAHP-based customer satisfaction evaluation model is proposed for the logistics service. Second, the triangular fuzzy concept is introduced to determine the weight of each index so as to addresses the limitation of subjective or objective weighting method. Third, a case study demonstrates the implementation of the model.

First, this paper considers the fuzzy AHP for the customer satisfaction evaluation. Comparing with other multi-criteria decision-making methods like data envelopment analysis, evidential reasoning approach, and multi-attribute value theory will be carried out in the near future. Second, the manufacturing modes like make-to-order, make-to-stock, and mass-customized production may have different logistics support so that the final products may reach the final targets quickly. How to evaluate various mode-based logistics and their customer satisfactions have great significance. Finally, Big Data-enabled customer satisfaction evaluation approaches may be a possible solution.

Based on the data from questionnaire, it is found that, in practical applications, manufacturing enterprises should amend the index system according to the specific business scope and the production characteristics. Manufacturing enterprises need to collect large amounts of data through market research and conduct the measurement on the related coefficient between the measurement indicators and customer satisfaction degree. After that, they can make sorting and filtering on the measurement index according to the measurement results.

Customer satisfaction is very important to manufacturing and logistics enterprises due to its time constraints. The physical products with services like logistics are paid close attention to by the final customers.

The contribution of this paper is as follows: a FAHP-based customer satisfaction evaluation model is proposed for the logistics service; triangular fuzzy concept is introduced to determine the weight of each index so as to addresses the limitation of subjective or objective weighting method; a case study was used to demonstrate the implementation of the model. One of the key findings is that Company B has higher customer satisfaction than Company B due to its quick response and flexible logistics strategy.