Modularity and Delayed Product Differentiation in Assemble-to-order Systems: Analysis and Extensions from a Complexity Perspective

The paper assumes a product design around modular architectures and discusses the suitability of the principle of delayed product differentiation in assemble-to-order environments. We demonstrate that this principle does not enable one to make optimal decisions concerning how variety should proliferate in the assembly process. Therefore, we propose to complement this principle in that we additionally consider the variety induced complexity throughout the assembly process. The weighted Shannon entropy is proposed as a measure for the evaluation of this complexity. Our results show that the delayed product differentiation principle is reliable when the selection probabilities of module variants at each assembly stage are equal and the pace at which value is added in the whole assembly process is constant. Otherwise, the proposed measure provides different results. Furthermore, the entropy measure provides interesting clues concerning eventual reversals of assembly sequences and supports decisions regarding what modules in an assembly stage could be substituted by a common module.modularity; complexity; ATO; delayed product differentiation

Variety Management in Assemble-to-Order Supply Chains

Assemble-to-order refers to a supply chain strategy in which products are not assembled until customer order arrives. It is based on the so-called form postponement that is to hold components at a generic form and to delay the point of product differentiation. The performance of an assem-ble-to-order supply chain depends on two main dimensions, which are responsiveness and achievement level of scale economies. Responsiveness refers to the capability of fulfilling customer requirements in a fast-paced manner, whereas the achievement of scale economies reflects the degree of operations efficiency. Assemble-to-order supply chains induce high product variety, which has adverse effects on performance. We use demand volumes as a proxy for scale economies and lead times as a proxy for responsiveness. A matrix that consists of both dimensions can be defined, in which we distinguish between short/long lead times and low/high demand volumes. This matrix is called performance matrix. On the other hand, the consequence that results from product variety is a high demand variability of end products, which also affects the demand variability of components. An analysis of component demand variability enables one to identify the components with low/high demand variability. These components can further be classified into supplied and in-house made components. Thus, a second matrix (called component matrix) with two dimensions, namely variability (low/high) and supply source (in-house/supplier) can be defined. Due to the supply source dimension in the component matrix, the supply chain perspective is also taken into ac-count. The combination of both matrixes into a single one provides the performance/component matrix for assemble-to-order supply chains. To use the final matrix, it is necessary to compute lead times, demand volumes and demand variability of the supplied and in-house made components. By plotting the components in the matrix, one can determine the problems induced by variety. In order to improve the performance of the assemble-to-order supply chain, the implementation of variety management strategies is necessary. The identified strategies are: commonality, component families, modularity, and platforms. Based on the performance/component matrix, we discuss how these strategies or a combination of them can contribute to derive recommendations that aim to alleviate variety impacts on the as-semble-to-order supply chain.Assemble-to-order; Supply Chain Management; Variety Management

Open source innovation: Characteristics and applicability outside the software industry

Motivation of this paper is to discuss that the open source model of innovation does not only seem practical in the software industry, but also in various other industrial contexts. We develop the concept of Open Source Innovation (OSI) as a generalisation of the open source model of software development (OSS). Our definition centres on the collaboration of volunteers and the free revelation of knowledge between actors. Since OSI exhibits important differences to several related concepts in the literature, we conclude that it is an innovation model in its own right, deserving more attention and research. We further proceed to identify aspects affecting the application of the OSI model in industry practices, grouping them into economic, technical, legal, and social factors. Based on these results as well as expert interviews, we find that the applicability of OSI is primarily determined by the characteristics of, first, the innovation object and, second, the group of contributors, rather than the industrial sector. Finally, we advance propositions on the employment of OSI in industrial practice, relating its feasibility to the innovation object and the group of contributors. --

Enabling and sustaining collaborative innovation

This paper extends the principles of open source software development to a non-industry-specific level by introducing the Open Source Innovation (OSI) model. OSI exhibits main differences to other related models and concepts such as the private-collective model, commons-based peer production, R&D networks and is therefore an innovation model in its own right. In order for OSI projects to be successful, numerous factors need to be fulfilled. We make the distinction between four categories of factors: economic, technical, legal, and social. In each category, we differentiate between enabling and sustaining factors. The enabling factors must be met at the beginning of the project, whereas the sustaining factors must be satisfied as the project progresses. --

Enabling and Sustaining Collaborative Innovation

This paper extends the principles of open source software development to a non-industry-specific level by introducing the Open Source Innovation (OSI) model. OSI exhibits main differences to other related models and concepts such as the private-collective model, commons-based peer production, R&D networks and is therefore an innovation model in its own right. In order for OSI projects to be successful, numerous factors need to be fulfilled. We make the distinction between four categories of factors: economic, technical, legal, and social. In each category, we differentiate between enabling and sustaining factors. The enabling factors must be met at the beginning of the project, whereas the sustaining factors must be satisfied as the project progresses.OSI, open source innovation, R&D

A Multi-Agent based Configuration Process for Mass Customization

Large product variety in mass customization involves a high internal complexity level inside a companyís operations, as well as a high external complexity level from a customerís perspective. In order to reach a competitive advantage through mass customization, it is necessary to cope with both problems. This is done within the scope of variety formation and variety steering tasks: Variety formation supports customers during the configuration task according to their preferences and knowledge, variety steering tasks internally deal with finding the customizerís optimal offer. Driven by this economic background, we present a comprehensive multi-agent based design for a configuration process in this paper. It is identified as a suitable solution approach integrating both perspectives. The mass customized products are assumed to be based on a modular architecture and each module variant is associated with an autonomous rational agent. Agents must compete with each other in order to join product variants which suit real customersí requirements. The negotiation process is based on a market mechanism supported by the target costing concept and a Dutch auction.Multi-agent systems; Configuration process; Market mechanism; Mass Customization

Irrigation water use efficiency in collective irrigated schemes of Tunisia: determinants and potential irrigation cost reduction

This study aims first to measure the farm specific irrigation water use efficiency (IWUE), through non parametric DEA model; and second to evaluate the potential irrigation cost reductions and identify the main factors causing variations in IWUE among the sample farms. Cross sectional data collected from a sample of 75 farms participating in the WaDImena project in Nadhour region (northern Tunisia) was used for this aim. The results showed that the average level of IWUE across the farm sample was around 61.2% under variable returns to scale (VRS) assumption. However, the estimated mean irrigation water technical cost efficiency (ITCE) is much higher than IWUE. Farmers would be able to reduce their actual cost by 5% under VRS by adjusting irrigation water to its efficient level. This low level of cost reductions is consistent with the existing literature about IWUE in Tunisia. Moreover, education level of farmers, access to credit and agricultural extension service showed a positive relationship with the IWUE in our case study.Resource /Energy Economics and Policy,

Preparing for out of hospital cardiac arrests (OHCA) in Riyadh, Saudi Arabia: A GIS scenario-modeling approach

This study employed location-allocation modeling and a geographic information system (GIS) to study the current placement of automated external defibrillators (AEDs) in relationship to neighborhoods in Riyadh City, Saudi Arabia, and to determine the optimal locations for additional AEDs in the city. Using GIS to mathematically locate additional healthcare facilities for the placement of AEDs is more reliable than to select them using informed guesses. The objective of this research was to elaborate a mathematical and GIS model for placing AED devices so that people who need to use these devices in the City of Riyadh, Saudi Arabia, can access them within a time frame of three minutes or less, which is the international standard for such accessibility. The research employed street blocks as demand points; existing healthcare facilities, mosques, and schools as supply points; and the maximum coverage algorithm to model optimal locations for AED devices. Models were run for both vehicle and pedestrian travel times. Model results of current conditions indicated that 75% of household blocks were covered when vehicles were used to access AED sites, as compared to 9% of people when pedestrian travel to an AED is considered. Introduction of 1,371 mosques and 34 community colleges and universities as additional supply points for AEDs improved coverage to 94% for vehicular access, but only 34% for pedestrian traffic. Although mosques are considered to be focus points for Muslim communities, other facilities including, but not limited to, police stations, malls, primary and secondary schools, and playgrounds should be used to gain wider coverage. In addition, cluster analysis should be employed to avoid selecting AED supply points that are too close to each other and which are unlikely to improve accessibility. The study succeeded in elaborating a framework for conceptualizing the relationship between vehicular and pedestrian access to AEDs. It also demonstrates how GIS-based location-allocation modeling can be used for efficient placement of AEDs. The broad conceptual framework for AED placement used in this study has applicability to other countries in the Middle East

Mass Customization vs. Complexity: A Gordian Knot?

Mass customization is a business strategy that aims at satisfying individual customer needs, nearly with mass production efficiency. It induces a high complexity level because of various customer requirements and a steadily changing environment. However, mass customization has some potential to reduce complexity. These interdependencies between mass customization and complexity form a Gordian knot that should be cut in order to point out that mass customization is not just an oxymoron linking two opposite production concepts, but a business strategy that contributes towards reaching a competitive advantage. On the one hand, mass customization increases the production program, manufacturing and configuration complexities. On the other hand, mass customization can contribute to reduce complexity at the levels of order taking process, product and inventories. The main results attained through the analysis are integrated in a comprehensive framework that shows the complexity increasing and complexity decreasing aspects due to mass customization.complexity; mass customization