1,868 research outputs found

    SERVICE-PROCESS CONFIGURATIONS IN ELECTRONIC RETAILING: A TAXONOMIC ANALYSIS OF ELECTRONIC FOOD RETAILERS

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    Service-processes of electronic retailers are founded on electronic technologies that provide flexibility to sense and respond online to the dynamic and complex needs of customers. In this paper, we develop a taxonomy of service-processes in electronic retailing and demonstrate their linkage to customer satisfaction and customer loyalty. The taxonomy is grounded in a conceptual classification scheme that differentiates service-process stages on a continuum of flexibility. Using data on electronic service-processes collected from 255 electronic food retailers, we identified eight configurations for the taxonomy. We also collected and analyzed publicly reported customer satisfaction survey data that were available for 52 electronic food retailers in the study sample. The results of this analysis indicate positive and significant correlation of the ordering of the taxonomy configurations with (i) customer satisfaction with product information, product selection, web site aesthetics, web site navigation, customer support, and ease of return, and (ii) customer loyalty. Taken together, the results of our empirical analyses demonstrate that the taxonomy captures information and variety within and across the electronic service-process configurations in ways that can be related to customer satisfaction and customer loyalty.Marketing, Research and Development/Tech Change/Emerging Technologies,

    New Knowledge for Old Regions? The Case of the Software Park Hagenberg in the Traditional Industrial Region of Upper Austria

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    This paper seeks to enhance our understanding about the opportunities and limits of new path creation in traditional regional innovation systems. Due to their inherited historical legacies, such systems are usually thought of being ill-equipped to give rise to high-tech or knowledge intensive activities. Departing from recent insights on research concerned with the transformation of innovation systems and evolutionary economic geography we identify in a conceptual way enabling and constraining factors for the rise of new development paths in traditional regions. Empirically, we focus on the case of the “Software Park Hagenberg†(SPH) located in the old industrial region of Upper Austria. We examine key events triggering the emergence and subsequent evolution of the SPH and explore the role of the RIS in shaping the development trajectory of the SPH. Moreover, applying social network analysis tools, we investigate the pattern of networking between firms, research organisations and educational bodies within the SPH and we provide some evidence on the diffusion of knowledge and innovation generated though these interactions throughout the regional economy.

    Supply chain integration model: practices and customer values

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    Dissertation to obtain PhD in Industrial EngineeringIn order to increase partnership efficiency and truly meet the customers' demands, in today's business environment companies are operating in supply chains. Integration of supply chains facilitates minimizing diferent types of wastes and satisfying needs of the end customer. The first step toward supply chain integration is to understandand the customer values, and to reconfigure supply chain to support those values. The current research addresses supply chain integration through quantifying relations between supply chain practice and customer values. It employs Bayesian network and analytic network process as tools to quantify comparative relations among entities. The proposed approach starts with identifying trade-offs along customer values using Bayesian network. In parallel supply chain practices are comparatively analyzed through interviews with experts which is technically quantified using analytic network process. Thereafter, these two parallel phases join together to form a network of customer values and supply chain practices. The network is able to quantitatively identify relations among nodes; in addition, it can be used to plan scenarios and handle senstitivity analyses. This model is expected to be used by supply chain decision makers to have a quantitative measure for monitoring the influence of practices on preferences of the end customer. A survey and two case studies are discussed which go through aforementioned phases. The survey identifies and analyzes six customer values namely quality, cost, customization, time, know-how and respect for the environment. It makes input for the two cases which develop supply chain integration model for fashion and food industry. Supply chain practices are categorized into two groups of manufacturing and logistics practices. The two case studies include five manufacturing practices as cross functional operations, decrease work in process, implement standards, mixed production planning, and use recyclable materials as well as four logistics practices namely visibility to upstream /downstream inventories, information sharing with customer, implement logistics standards, and just in time.Fundação para a Ciência e Tecnologia - (MIT Project: MIT-Pt/EDAM-IASC/0022/2008

    Adapter module for self-learning production systems

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    Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica, Sistemas e ComputadoresThe dissertation presents the work done under the scope of the NP7 Self-Learning project regarding the design and development of the Adapter component as a foundation for the Self-Learning Production Systems (SLPS). This component is responsible to confer additional proprieties to production systems such as lifecycle learning, optimization of process parameters and, above all, adaptation to different production contexts. Therefore, the SLPS will be an evolvable system capable to self-adapt and learn in response to dynamic contextual changes in manufacturing production process in which it operates. The key assumption is that a deeper use of data mining and machine learning techniques to process the huge amount of data generated during the production activities will allow adaptation and enhancement of control and other manufacturing production activities such as energy use optimization and maintenance. In this scenario, the SLPS Adapter acts as a doer and is responsible for dynamically adapting the manufacturing production system parameters according to changing manufacturing production contexts and, most important, according to the history of the manufacturing production process acquired during SLPS run time.To do this, a Learning Module has been also developed and embedded into the SLPS Adapter. The SLPS Learning Module represents the processing unit of the SLPS Adapter and is responsible to deliver Self-learning capabilities relying on data mining and operator’s feedback to up-date the execution of adaptation and context extraction at run time. The designed and implemented SLPS Adapter architecture is assessed and validated into several application scenario provided by three industrial partners to assure industrial relevant self-learning production systems. Experimental results derived by the application of the SLPS prototype into real industrial environment are also presented

    Dynamic Multi-Agent Based Variety Formation and Steering in Mass Customization

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    Large product variety in mass customization involves a high internal complexity level inside a company’s operations, as well as a high external complexity level from a customer’s perspective. To cope with both complexity problems, an information system based on agent technology is able to be identified as a suitable solution approach. 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 have to compete with each other in order to join coalitions representing salable product variants which suit real customers’ requirements. The negotiation process is based on a market mechanism supported by the target costing concept and a Dutch auction. Furthermore, in order to integrate the multi-agent system in the existing information system landscape of the mass customizer, a technical architecture is proposed and a scenario depicting the main communication steps is specified.Product Configuration, Mass Customization, Variety Formation and Steering, Multi Agent System

    Lean manual assembly 4.0: A systematic review

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    In a demand context of mass customization, shifting towards the mass personalization of products, assembly operations face the trade-off between highly productive automated systems and flexible manual operators. Novel digital technologies—conceptualized as Industry 4.0—suggest the possibility of simultaneously achieving superior productivity and flexibility. This article aims to address how Industry 4.0 technologies could improve the productivity, flexibility and quality of assembly operations. A systematic literature review was carried out, including 234 peer-reviewed articles from 2010–2020. As a result, the analysis was structured addressing four sets of research questions regarding (1) assembly for mass customization; (2) Industry 4.0 and performance evaluation; (3) Lean production as a starting point for smart factories, and (4) the implications of Industry 4.0 for people in assembly operations. It was found that mass customization brings great complexity that needs to be addressed at different levels from a holistic point of view; that Industry 4.0 offers powerful tools to achieve superior productivity and flexibility in assembly; that Lean is a great starting point for implementing such changes; and that people need to be considered central to Assembly 4.0. Developing methodologies for implementing Industry 4.0 to achieve specific business goals remains an open research topic

    Modeling the Portfolio of Capabilities for Product Variant Creation and Assessment

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    Choice navigation, solution space development and robust process design are the three mass customization key competences. The first and second are often mapped into product configuration or design automation systems and aim at specifying or co-designing a suitable product variant. Robust process design targets at managing a well-known but flexible supply network. As part of this, the portfolio of capabilities describes limitations to the solution space and is a valuable source of knowledge containing general design guidelines and specific manufacturing restrictions, like NC travelling distances, as well as availabilities of whole production processes. This article contributes a modeling approach that bridges solutions space development and modeling the portfolio of capabilities. Therefore, a knowledge-based engineering system is extended by a capability model of according production machines that allows to automatically check new product variants against the portfolio of capabilities and to estimate setup efforts and expenses of process changes
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