34,937 research outputs found

    Operational Capabilities: The Secret Ingredient

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    We develop a theoretical definition of operational capabilities, based on the strategic management and operations management literature, and differentiate this construct from the related constructs of resources and operational practices, drawing upon the resourcebased view of the firm as our foundation. We illustrate the key features of operational capabilities using the illustration of a restaurant kitchen. Because the traits of operational capabilities are distinct, they create a barrier to imitation, making them a potential source of competitive advantage. However, operational capabilities are particularly challenging to measure, because they emerge gradually and are tacit, embedded, and manifested differently across firms. In solving this measurement conundrum, we draw upon similar situations experienced by Schein (2004) and Eisenhardt and Martin (2000) in operationalizing organizational culture and dynamic capabilities. A taxonomy of six emergent operational capabilities is developed: operational improvement, operational innovation, operational customization, operational cooperation, operational responsiveness, and operational reconfiguration. A set of measurement scales is developed, in order to measure each of the operational capabilities, and validated using two different datasets. This allows replication of the psychometric properties of the multi-item scales and helps to ensure the validity of the resulting measures

    Developing a dominant logic of strategic innovation

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    Purpose: This paper aims to lay the foundations to develop a dominant logic and a common thematic framework of strategic innovation (SI) and to encourage consensus over the field’s core foundation of main themes. Design/methodology/approach: The paper explores the intersection between the constituent fields of strategic management and innovation management through a concept mapping process. The paper categorizes the main themes and search for common ground in order to develop the core thematic framework of SI. The paper looks at the sub-themes of SI in published research and develops a more detailed framework. The conceptual categories derived from the process are then placed in a logical sequence according to how they occur in practice or in the order of how the concepts develop from one other. Findings: The results yield seven main themes that form the main taxonomy of SI: types of SI, environmental analysis of SI, SI planning, enabling SI, collaborative networks, managing knowledge, and strategic outcomes. Research limitations/implications: The new thematic framework the paper is proposing for SI remains preliminary in nature and would need to be tried and tested by researchers and practitioners in order to gain acceptability. Academic rigor and methodological structure are not sufficient to determine whether our conceptual framework will become widely diffused in academia and industry. It would have to pass through an emergent, evolutionary process of selection, adoption and an inevitable degree of change and adaptation, just like any other innovation. Practical implications: The practical implications concern the production of instructive material and the application of strategic management initiatives in industry. The proposed themes and sub-themes can serve as a logical framework to develop and update publications, which have been instrumental in their own right to shape the field. The paper also provides a checklist of potential research projects in SI, which will improve and strengthen the field. The new framework provides a comprehensive checklist of strategic management initiatives that will help industry to initiate, plan and execute effective innovation strategies. Originality/value: The concept mapping of the themes of SI yields a new dominant logic, which will influence the evolution of the field and its relevance to both academia and industry

    Ground Systems Development Environment (GSDE) interface requirements analysis

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    A set of procedural and functional requirements are presented for the interface between software development environments and software integration and test systems used for space station ground systems software. The requirements focus on the need for centralized configuration management of software as it is transitioned from development to formal, target based testing. This concludes the GSDE Interface Requirements study. A summary is presented of findings concerning the interface itself, possible interface and prototyping directions for further study, and results of the investigation of the Cronus distributed applications environment

    Socio-technical transition processes: A real option based reasoning.

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    Using a real option reasoning perspective we study the uncertainties and irreversibilities that impact the investment decisions of firms during the different phases of technological transitions. The analysis of transition dynamics via real options reasoning allows the provision of an alternative and more qualified explanation of investment decisions according to the sequentiality of pathways considered. In our framework, flexibility management through option investments concerns both the incumbent and the future technological regime. In the first case it refers to ex-post flexibility management and in the second case to ex-ante flexibility management.

    An Overview on Application of Machine Learning Techniques in Optical Networks

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    Today's telecommunication networks have become sources of enormous amounts of widely heterogeneous data. This information can be retrieved from network traffic traces, network alarms, signal quality indicators, users' behavioral data, etc. Advanced mathematical tools are required to extract meaningful information from these data and take decisions pertaining to the proper functioning of the networks from the network-generated data. Among these mathematical tools, Machine Learning (ML) is regarded as one of the most promising methodological approaches to perform network-data analysis and enable automated network self-configuration and fault management. The adoption of ML techniques in the field of optical communication networks is motivated by the unprecedented growth of network complexity faced by optical networks in the last few years. Such complexity increase is due to the introduction of a huge number of adjustable and interdependent system parameters (e.g., routing configurations, modulation format, symbol rate, coding schemes, etc.) that are enabled by the usage of coherent transmission/reception technologies, advanced digital signal processing and compensation of nonlinear effects in optical fiber propagation. In this paper we provide an overview of the application of ML to optical communications and networking. We classify and survey relevant literature dealing with the topic, and we also provide an introductory tutorial on ML for researchers and practitioners interested in this field. Although a good number of research papers have recently appeared, the application of ML to optical networks is still in its infancy: to stimulate further work in this area, we conclude the paper proposing new possible research directions

    Contextual impacts on industrial processes brought by the digital transformation of manufacturing: a systematic review

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    The digital transformation of manufacturing (a phenomenon also known as "Industry 4.0" or "Smart Manufacturing") is finding a growing interest both at practitioner and academic levels, but is still in its infancy and needs deeper investigation. Even though current and potential advantages of digital manufacturing are remarkable, in terms of improved efficiency, sustainability, customization, and flexibility, only a limited number of companies has already developed ad hoc strategies necessary to achieve a superior performance. Through a systematic review, this study aims at assessing the current state of the art of the academic literature regarding the paradigm shift occurring in the manufacturing settings, in order to provide definitions as well as point out recurring patterns and gaps to be addressed by future research. For the literature search, the most representative keywords, strict criteria, and classification schemes based on authoritative reference studies were used. The final sample of 156 primary publications was analyzed through a systematic coding process to identify theoretical and methodological approaches, together with other significant elements. This analysis allowed a mapping of the literature based on clusters of critical themes to synthesize the developments of different research streams and provide the most representative picture of its current state. Research areas, insights, and gaps resulting from this analysis contributed to create a schematic research agenda, which clearly indicates the space for future evolutions of the state of knowledge in this field

    Developing Real-Time Emergency Management Applications: Methodology for a Novel Programming Model Approach

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    The last years have been characterized by the arising of highly distributed computing platforms composed of a heterogeneity of computing and communication resources including centralized high-performance computing architectures (e.g. clusters or large shared-memory machines), as well as multi-/many-core components also integrated into mobile nodes and network facilities. The emerging of computational paradigms such as Grid and Cloud Computing, provides potential solutions to integrate such platforms with data systems, natural phenomena simulations, knowledge discovery and decision support systems responding to a dynamic demand of remote computing and communication resources and services. In this context time-critical applications, notably emergency management systems, are composed of complex sets of application components specialized for executing specific computations, which are able to cooperate in such a way as to perform a global goal in a distributed manner. Since the last years the scientific community has been involved in facing with the programming issues of distributed systems, aimed at the definition of applications featuring an increasing complexity in the number of distributed components, in the spatial distribution and cooperation between interested parties and in their degree of heterogeneity. Over the last decade the research trend in distributed computing has been focused on a crucial objective. The wide-ranging composition of distributed platforms in terms of different classes of computing nodes and network technologies, the strong diffusion of applications that require real-time elaborations and online compute-intensive processing as in the case of emergency management systems, lead to a pronounced tendency of systems towards properties like self-managing, self-organization, self-controlling and strictly speaking adaptivity. Adaptivity implies the development, deployment, execution and management of applications that, in general, are dynamic in nature. Dynamicity concerns the number and the specific identification of cooperating components, the deployment and composition of the most suitable versions of software components on processing and networking resources and services, i.e., both the quantity and the quality of the application components to achieve the needed Quality of Service (QoS). In time-critical applications the QoS specification can dynamically vary during the execution, according to the user intentions and the Developing Real-Time Emergency Management Applications: Methodology for a Novel Programming Model Approach Gabriele Mencagli and Marco Vanneschi Department of Computer Science, University of Pisa, L. Bruno Pontecorvo, Pisa Italy 2 2 Will-be-set-by-IN-TECH information produced by sensors and services, as well as according to the monitored state and performance of networks and nodes. The general reference point for this kind of systems is the Grid paradigm which, by definition, aims to enable the access, selection and aggregation of a variety of distributed and heterogeneous resources and services. However, though notable advancements have been achieved in recent years, current Grid technology is not yet able to supply the needed software tools with the features of high adaptivity, ubiquity, proactivity, self-organization, scalability and performance, interoperability, as well as fault tolerance and security, of the emerging applications. For this reason in this chapter we will study a methodology for designing high-performance computations able to exploit the heterogeneity and dynamicity of distributed environments by expressing adaptivity and QoS-awareness directly at the application level. An effective approach needs to address issues like QoS predictability of different application configurations as well as the predictability of reconfiguration costs. Moreover adaptation strategies need to be developed assuring properties like the stability degree of a reconfiguration decision and the execution optimality (i.e. select reconfigurations accounting proper trade-offs among different QoS objectives). In this chapter we will present the basic points of a novel approach that lays the foundations for future programming model environments for time-critical applications such as emergency management systems. The organization of this chapter is the following. In Section 2 we will compare the existing research works for developing adaptive systems in critical environments, highlighting their drawbacks and inefficiencies. In Section 3, in order to clarify the application scenarios that we are considering, we will present an emergency management system in which the run-time selection of proper application configuration parameters is of great importance for meeting the desired QoS constraints. In Section 4we will describe the basic points of our approach in terms of how compute-intensive operations can be programmed, how they can be dynamically modified and how adaptation strategies can be expressed. In Section 5 our approach will be contextualize to the definition of an adaptive parallel module, which is a building block for composing complex and distributed adaptive computations. Finally in Section 6 we will describe a set of experimental results that show the viability of our approach and in Section 7 we will give the concluding remarks of this chapter
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