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Periodicals

A review of rapid prototyping techniques for tissue engineering purposes

Rapid prototyping (RP) is a common name for several techniques, which read in data from computer-aided design (CAD) drawings and manufacture automatically three-dimensional objects layer-by-layer according to the virtual design. The utilization of RP in tissue engineering enables the production of three-dimensional scaffolds with complex geometries and very fine structures. Adding micro- and nanometer details into the scaffolds improves the mechanical properties of the scaffold and ensures better cell adhesion to the scaffold surface. Thus, tissue engineering constructs can be customized according to the data acquired from the medical scans to match the each patient's individual needs. In addition RP enables the control of the scaffold porosity making it possible to fabricate applications with desired structural integrity. Unfortunately, every RP process has its own unique disadvantages in building tissue engineering scaffolds. Hence, the future research should be focused on the development of RP machines designed specifically for fabrication of tissue engineering scaffolds, although RP methods already can serve as a link between tissue and engineering.

Architecture & Planning• 2008• Informa
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The Role of Leadership in a Digitalized World: A Review

Digital technology has changed organizations in an irreversible way. Like the movable type printing accelerated the evolution of our history, digitalization is shaping organizations, work environment and processes, creating new challenges leaders have to face. Social science scholars have been trying to understand this multifaceted phenomenon, however, findings have accumulated in a fragmented and dispersed fashion across different disciplines, and do not seem to converge within a clear picture. To overcome this shortcoming in the literature and foster clarity and alignment in the academic debate, this paper provides a comprehensive analysis of the contribution of studies on leadership and digitalization, identifying patterns of thought and findings across various social science disciplines, such as management and psychology. It clarifies key definitions and ideas, highlighting the main theories and findings drawn by scholars. Further, it identifies categories that group papers according to the macro level of analysis (e-leadership and organization, digital tools, ethical issues, and social movements), and micro level of analysis (the role of C-level managers, leader's skills in the digital age, practices for leading virtual teams). Main findings show leaders are key actors in the development of a digital culture: they need to create relationships with multiple and scattered stakeholders, and focus on enabling collaborative processes in complex settings, while attending to pressing ethical concerns. With this research, we contribute to advance theoretically the debate about digital transformation and leadership, offering an extensive and systematic review, and identifying key future research opportunities to advance knowledge in this field.

Architecture & Planning• 2019• Frontiers Media
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Periodicals

An Automated Technique for Generating Georectified Mosaics from Ultra-High Resolution Unmanned Aerial Vehicle (UAV) Imagery, Based on Structure from Motion (SfM) Point Clouds

Unmanned Aerial Vehicles (UAVs) are an exciting new remote sensing tool capable of acquiring high resolution spatial data. Remote sensing with UAVs has the potential to provide imagery at an unprecedented spatial and temporal resolution. The small footprint of UAV imagery, however, makes it necessary to develop automated techniques to geometrically rectify and mosaic the imagery such that larger areas can be monitored. In this paper, we present a technique for geometric correction and mosaicking of UAV photography using feature matching and Structure from Motion (SfM) photogrammetric techniques. Images are processed to create three dimensional point clouds, initially in an arbitrary model space. The point clouds are transformed into a real-world coordinate system using either a direct georeferencing technique that uses estimated camera positions or via a Ground Control Point (GCP) technique that uses automatically identified GCPs within the point cloud. The point cloud is then used to generate a Digital Terrain Model (DTM) required for rectification of the images. Subsequent georeferenced images are then joined together to form a mosaic of the study area. The absolute spatial accuracy of the direct technique was found to be 65–120 cm whilst the GCP technique achieves an accuracy of approximately 10–15 cm.

Architecture & Planning• 2012• Multidisciplinary Digital Publishing Institute
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Periodicals

A Novel Transfer Learning Based Approach for Pneumonia Detection in Chest X-ray Images

Pneumonia is among the top diseases which cause most of the deaths all over the world. Virus, bacteria and fungi can all cause pneumonia. However, it is difficult to judge the pneumonia just by looking at chest X-rays. The aim of this study is to simplify the pneumonia detection process for experts as well as for novices. We suggest a novel deep learning framework for the detection of pneumonia using the concept of transfer learning. In this approach, features from images are extracted using different neural network models pretrained on ImageNet, which then are fed into a classifier for prediction. We prepared five different models and analyzed their performance. Thereafter, we proposed an ensemble model that combines outputs from all pretrained models, which outperformed individual models, reaching the state-of-the-art performance in pneumonia recognition. Our ensemble model reached an accuracy of 96.4% with a recall of 99.62% on unseen data from the Guangzhou Women and Children’s Medical Center dataset.

Architecture & Planning• 2020• Multidisciplinary Digital Publishing Institute
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A Hierarchy of Time-Scales and the Brain

In this paper, we suggest that cortical anatomy recapitulates the temporal hierarchy that is inherent in the dynamics of environmental states. Many aspects of brain function can be understood in terms of a hierarchy of temporal scales at which representations of the environment evolve. The lowest level of this hierarchy corresponds to fast fluctuations associated with sensory processing, whereas the highest levels encode slow contextual changes in the environment, under which faster representations unfold. First, we describe a mathematical model that exploits the temporal structure of fast sensory input to track the slower trajectories of their underlying causes. This model of sensory encoding or perceptual inference establishes a proof of concept that slowly changing neuronal states can encode the paths or trajectories of faster sensory states. We then review empirical evidence that suggests that a temporal hierarchy is recapitulated in the macroscopic organization of the cortex. This anatomic-temporal hierarchy provides a comprehensive framework for understanding cortical function: the specific time-scale that engages a cortical area can be inferred by its location along a rostro-caudal gradient, which reflects the anatomical distance from primary sensory areas. This is most evident in the prefrontal cortex, where complex functions can be explained as operations on representations of the environment that change slowly. The framework provides predictions about, and principled constraints on, cortical structure-function relationships, which can be tested by manipulating the time-scales of sensory input.

Architecture & Planning• 2008• Public Library of Science
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Periodicals

Blockchain for Industry 4.0: A Comprehensive Review

Due to the proliferation of ICT during the last few decades, there is an exponential increase in the usage of various smart applications such as smart farming, smart healthcare, supply-chain & logistics, business, tourism and hospitality, energy management etc. However, for all the aforementioned applications, security and privacy are major concerns keeping in view of the usage of the open channel, i.e., Internet for data transfer. Although many security solutions and standards have been proposed over the years to enhance the security levels of aforementioned smart applications, but the existing solutions are either based upon the centralized architecture (having single point of failure) or having high computation and communication costs. Moreover, most of the existing security solutions have focussed only on few aspects and fail to address scalability, robustness, data storage, network latency, auditability, immutability, and traceability. To handle the aforementioned issues, blockchain technology can be one of the solutions. Motivated from these facts, in this paper, we present a systematic review of various blockchain-based solutions and their applicability in various Industry 4.0-based applications. Our contributions in this paper are in four fold. Firstly, we explored the current state-of-the-art solutions in the blockchain technology for the smart applications. Then, we illustrated the reference architecture used for the blockchain applicability in various Industry 4.0 applications. Then, merits and demerits of the traditional security solutions are also discussed in comparison to their countermeasures. Finally, we provided a comparison of existing blockchain-based security solutions using various parameters to provide deep insights to the readers about its applicability in various applications.

Architecture & Planning• 2020• Institute of Electrical and Electronics Engineers
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Periodicals

IoT Privacy and Security: Challenges and Solutions

Privacy and security are among the significant challenges of the Internet of Things (IoT). Improper device updates, lack of efficient and robust security protocols, user unawareness, and famous active device monitoring are among the challenges that IoT is facing. In this work, we are exploring the background of IoT systems and security measures, and identifying (a) different security and privacy issues, (b) approaches used to secure the components of IoT-based environments and systems, (c) existing security solutions, and (d) the best privacy models necessary and suitable for different layers of IoT driven applications. In this work, we proposed a new IoT layered model: generic and stretched with the privacy and security components and layers identification. The proposed cloud/edge supported IoT system is implemented and evaluated. The lower layer represented by the IoT nodes generated from the Amazon Web Service (AWS) as Virtual Machines. The middle layer (edge) implemented as a Raspberry Pi 4 hardware kit with support of the Greengrass Edge Environment in AWS. We used the cloud-enabled IoT environment in AWS to implement the top layer (the cloud). The security protocols and critical management sessions were between each of these layers to ensure the privacy of the users’ information. We implemented security certificates to allow data transfer between the layers of the proposed cloud/edge enabled IoT model. Not only is the proposed system model eliminating possible security vulnerabilities, but it also can be used along with the best security techniques to countermeasure the cybersecurity threats facing each one of the layers; cloud, edge, and IoT.

Architecture & Planning• 2020• Multidisciplinary Digital Publishing Institute
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Periodicals

A Novel Cloud-Based Framework for the Elderly Healthcare Services Using Digital Twin

With the development of technologies, such as big data, cloud computing, and the Internet of Things (IoT), digital twin is being applied in industry as a precision simulation technology from concept to practice. Further, simulation plays a very important role in the healthcare field, especially in research on medical pathway planning, medical resource allocation, medical activity prediction, etc. By combining digital twin and healthcare, there will be a new and efficient way to provide more accurate and fast services for elderly healthcare. However, how to achieve personal health management throughout the entire lifecycle of elderly patients, and how to converge the medical physical world and the virtual world to realize real smart healthcare, are still two key challenges in the era of precision medicine. In this paper, a framework of the cloud healthcare system is proposed based on digital twin healthcare (CloudDTH). This is a novel, generalized, and extensible framework in the cloud environment for monitoring, diagnosing and predicting aspects of the health of individuals using, for example, wearable medical devices, toward the goal of personal health management, especially for the elderly. CloudDTH aims to achieve interaction and convergence between medical physical and virtual spaces. Accordingly, a novel concept of digital twin healthcare (DTH) is proposed and discussed, and a DTH model is implemented. Next, a reference framework of CloudDTH based on DTH is constructed, and its key enabling technologies are explored. Finally, the feasibility of some application scenarios and a case study for real-time supervision are demonstrated.

Architecture & Planning• 2019• Institute of Electrical and Electronics Engineers
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Periodicals

The physical environment of Kongsfjorden–Krossfjorden, an Arctic fjord system in Svalbard

Kongsfjorden-Krossfjorden and the adjacent West Spitsbergen Shelf meet at the common mouth of the two fjord arms. This paper presents our most up-to-date information about the physical environment of this fjord system and identifies important gaps in knowledge. Particular attention is given to the steep physical gradients along the main fjord axis, as well as to seasonal environmental changes. Physical processes on different scales control the large-scale circulation and small-scale (irreversible) mixing of water and its constituents. It is shown that, in addition to the tide, run-off (glacier ablation, snowmelt, summer rainfall and ice calving) and local winds are the main driving forces acting on the upper water masses in the fjord system. The tide is dominated by the semi-diurnal component and the freshwater supply shows a marked seasonal variation pattern and also varies interannually. The wind conditions are characterized by prevailing katabatic winds, which at times are strengthened by the geostrophic wind field over Svalbard. Rotational dynamics have a considerable influence on the circulation patterns within the fjord system and give rise to a strong interaction between the fjord arms. Such dynamics are also the main reason why variations in the shelf water density field, caused by remote forces (tide and coastal winds), propagate as a Kelvin wave into the fjord system. This exchange affects mainly the intermediate and deep water, which is also affected by vertical convection processes driven by cooling of the surface and brine release during ice formation in the inner reaches of the fjord arms. Further aspects covered by this paper include the geological and geomorphological characteristics of the Kongsfjorden area, climate and meteorology, the influence of glaciers, freshwater supply, sea ice conditions, sedimentation processes as well as underwater radiation conditions. The fjord system is assumed to be vulnerable to possible climate changes, and thus is very suitable as a site for the demonstration and investigation of phenomena related to climate change.

Architecture & Planning• 2002• Wiley
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Periodicals

Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applications

The thriving of artificial intelligence (AI) applications is driving the further evolution of wireless networks. It has been envisioned that 6G will be transformative and will revolutionize the evolution of wireless from “connected things” to “connected intelligence”. However, state-of-the-art deep learning and big data analytics based AI systems require tremendous computation and communication resources, causing significant latency, energy consumption, network congestion, and privacy leakage in both of the training and inference processes. By embedding model training and inference capabilities into the network edge, edge AI stands out as a disruptive technology for 6G to seamlessly integrate sensing, communication, computation, and intelligence, thereby improving the efficiency, effectiveness, privacy, and security of 6G networks. In this paper, we shall provide our vision for scalable and trustworthy edge AI systems with integrated design of wireless communication strategies and decentralized machine learning models. New design principles of wireless networks, service-driven resource allocation optimization methods, as well as a holistic end-to-end system architecture to support edge AI will be described. Standardization, software and hardware platforms, and application scenarios are also discussed to facilitate the industrialization and commercialization of edge AI systems.

Architecture & Planning• 2021• Institute of Electrical and Electronics Engineers
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Internet of Things (IoT) and the Energy Sector

Integration of renewable energy and optimization of energy use are key enablers of sustainable energy transitions and mitigating climate change. Modern technologies such the Internet of Things (IoT) offer a wide number of applications in the energy sector, i.e, in energy supply, transmission and distribution, and demand. IoT can be employed for improving energy efficiency, increasing the share of renewable energy, and reducing environmental impacts of the energy use. This paper reviews the existing literature on the application of IoT in in energy systems, in general, and in the context of smart grids particularly. Furthermore, we discuss enabling technologies of IoT, including cloud computing and different platforms for data analysis. Furthermore, we review challenges of deploying IoT in the energy sector, including privacy and security, with some solutions to these challenges such as blockchain technology. This survey provides energy policy-makers, energy economists, and managers with an overview of the role of IoT in optimization of energy systems.

Architecture & Planning• 2020• Multidisciplinary Digital Publishing Institute
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Routines and Other Recurring Action Patterns of Organizations: Contemporary Research Issues

This paper reports and extends discussions carried out during a workshop held at the Santa Fe Institute in August 1995 by the authors. It treats eight major topics: (i) the importance of carefully examining research on routine, (ii) the concept of ‘action patterns’ in general and in terms of routine, (iii) the useful categorization of routines and other recurring patterns, (iv) the research implications of recent cognitive results, (v) the relation of evolution to action patterns, (vi) the contributions of simulation modeling for theory in this area, (vii) examples of various approaches to empirical research that reveal key problems, and (viii) a possible definition of ‘routine’. An extended appendix by Massimo Egidi provides a lexicon of synonyms and opposites covering use of the word ‘routine’ in such areas as economics, organization theory and artificial intelligence.

Architecture & Planning• 1996• Oxford University Press
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Periodicals

Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation

This paper surveys the current state of the art in Natural Language Generation (NLG), defined as the task of generating text or speech from non-linguistic input. A survey of NLG is timely in view of the changes that the field has undergone over the past two decades, especially in relation to new (usually data-driven) methods, as well as new applications of NLG technology. This survey therefore aims to (a) give an up-to-date synthesis of research on the core tasks in NLG and the architectures adopted in which such tasks are organised; (b) highlight a number of recent research topics that have arisen partly as a result of growing synergies between NLG and other areas of artificial intelligence; (c) draw attention to the challenges in NLG evaluation, relating them to similar challenges faced in other areas of NLP, with an emphasis on different evaluation methods and the relationships between them.

Architecture & Planning• 2018• AI Access Foundation
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The Geomechanics of CO2 Storage in Deep Sedimentary Formations

This paper provides a review of the geomechanics and modeling of geomechanics associated with geologic carbon storage (GCS), focusing on storage in deep sedimentary formations, in particular saline aquifers. The paper first introduces the concept of storage in deep sedimentary formations, the geomechanical processes and issues related with such an operation, and the relevant geomechanical modeling tools. This is followed by a more detailed review of geomechanical aspects, including reservoir stress-strain and microseismicity, well integrity, caprock sealing performance, and the potential for fault reactivation and notable (felt) seismic events. Geomechanical observations at current GCS field deployments, mainly at the In Salah CO2 storage project in Algeria, are also integrated into the review. The In Salah project, with its injection into a relatively thin, low-permeability sandstone is an excellent analogue to the saline aquifers that might be used for large scale GCS in parts of Northwest Europe, the U.S. Midwest, and China. Some of the lessons learned at In Salah related to geomechanics are discussed, including how monitoring of geomechanical responses is used for detecting subsurface geomechanical changes and tracking fluid movements, and how such monitoring and geomechanical analyses have led to preventative changes in the injection parameters. Recently, the importance of geomechanics has become more widely recognized among GCS stakeholders, especially with respect to the potential for triggering notable (felt) seismic events and how such events could impact the long-term integrity of a CO2 repository (as well as how it could impact the public perception of GCS). As described in the paper, to date, no notable seismic event has been reported from any of the current CO2 storage projects, although some unfelt microseismic activities have been detected by geophones. However, potential future commercial GCS operations from large power plants will require injection at a much larger scale. For such large-scale injections, a staged, learn-as-you-go approach is recommended, involving a gradual increase of injection rates combined with continuous monitoring of geomechanical changes, as well as siting beneath a multiple layered overburden for multiple flow barrier protection, should an unexpected deep fault reactivation occur.

Architecture & Planning• 2012• Springer Science+Business Media
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Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence

Abstract This paper explores the important role of critical science, and in particular of post-colonial and decolonial theories, in understanding and shaping the ongoing advances in artificial intelligence. Artificial intelligence (AI) is viewed as amongst the technological advances that will reshape modern societies and their relations. While the design and deployment of systems that continually adapt holds the promise of far-reaching positive change, they simultaneously pose significant risks, especially to already vulnerable peoples. Values and power are central to this discussion. Decolonial theories use historical hindsight to explain patterns of power that shape our intellectual, political, economic, and social world. By embedding a decolonial critical approach within its technical practice, AI communities can develop foresight and tactics that can better align research and technology development with established ethical principles, centring vulnerable peoples who continue to bear the brunt of negative impacts of innovation and scientific progress. We highlight problematic applications that are instances of coloniality, and using a decolonial lens, submit three tactics that can form a decolonial field of artificial intelligence: creating a critical technical practice of AI, seeking reverse tutelage and reverse pedagogies, and the renewal of affective and political communities. The years ahead will usher in a wave of new scientific breakthroughs and technologies driven by AI research, making it incumbent upon AI communities to strengthen the social contract through ethical foresight and the multiplicity of intellectual perspectives available to us, ultimately supporting future technologies that enable greater well-being, with the goal of beneficence and justice for all.

Architecture & Planning• 2020• Springer Nature (Netherlands)
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Lithium-Ion Battery Storage for the Grid—A Review of Stationary Battery Storage System Design Tailored for Applications in Modern Power Grids

Battery energy storage systems have gained increasing interest for serving grid support in various application tasks. In particular, systems based on lithium-ion batteries have evolved rapidly with a wide range of cell technologies and system architectures available on the market. On the application side, different tasks for storage deployment demand distinct properties of the storage system. This review aims to serve as a guideline for best choice of battery technology, system design and operation for lithium-ion based storage systems to match a specific system application. Starting with an overview to lithium-ion battery technologies and their characteristics with respect to performance and aging, the storage system design is analyzed in detail based on an evaluation of real-world projects. Typical storage system applications are grouped and classified with respect to the challenges posed to the battery system. Publicly available modeling tools for technical and economic analysis are presented. A brief analysis of optimization approaches aims to point out challenges and potential solution techniques for system sizing, positioning and dispatch operation. For all areas reviewed herein, expected improvements and possible future developments are highlighted. In order to extract the full potential of stationary battery storage systems and to enable increased profitability of systems, future research should aim to a holistic system level approach combining not only performance tuning on a battery cell level and careful analysis of the application requirements, but also consider a proper selection of storage sub-components as well as an optimized system operation strategy.

Architecture & Planning• 2017• Multidisciplinary Digital Publishing Institute
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From the Quantum Approximate Optimization Algorithm to a Quantum Alternating Operator Ansatz

The next few years will be exciting as prototype universal quantum processors emerge, enabling the implementation of a wider variety of algorithms. Of particular interest are quantum heuristics, which require experimentation on quantum hardware for their evaluation and which have the potential to significantly expand the breadth of applications for which quantum computers have an established advantage. A leading candidate is Farhi et al.’s quantum approximate optimization algorithm, which alternates between applying a cost function based Hamiltonian and a mixing Hamiltonian. Here, we extend this framework to allow alternation between more general families of operators. The essence of this extension, the quantum alternating operator ansatz, is the consideration of general parameterized families of unitaries rather than only those corresponding to the time evolution under a fixed local Hamiltonian for a time specified by the parameter. This ansatz supports the representation of a larger, and potentially more useful, set of states than the original formulation, with potential long-term impact on a broad array of application areas. For cases that call for mixing only within a desired subspace, refocusing on unitaries rather than Hamiltonians enables more efficiently implementable mixers than was possible in the original framework. Such mixers are particularly useful for optimization problems with hard constraints that must always be satisfied, defining a feasible subspace, and soft constraints whose violation we wish to minimize. More efficient implementation enables earlier experimental exploration of an alternating operator approach, in the spirit of the quantum approximate optimization algorithm, to a wide variety of approximate optimization, exact optimization, and sampling problems. In addition to introducing the quantum alternating operator ansatz, we lay out design criteria for mixing operators, detail mappings for eight problems, and provide a compendium with brief descriptions of mappings for a diverse array of problems.

Architecture & Planning• 2019• Multidisciplinary Digital Publishing Institute
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A Critical Review of the Use of Virtual Reality in Construction Engineering Education and Training

Virtual Reality (VR) has been rapidly recognized and implemented in construction engineering education and training (CEET) in recent years due to its benefits of providing an engaging and immersive environment. The objective of this review is to critically collect and analyze the VR applications in CEET, aiming at all VR-related journal papers published from 1997 to 2017. The review follows a three-stage analysis on VR technologies, applications and future directions through a systematic analysis. It is found that the VR technologies adopted for CEET evolve over time, from desktop-based VR, immersive VR, 3D game-based VR, to Building Information Modelling (BIM)-enabled VR. A sibling technology, Augmented Reality (AR), for CEET adoptions has also emerged in recent years. These technologies have been applied in architecture and design visualization, construction health and safety training, equipment and operational task training, as well as structural analysis. Future research directions, including the integration of VR with emerging education paradigms and visualization technologies, have also been provided. The findings are useful for both researchers and educators to usefully integrate VR in their education and training programs to improve the training performance.

Architecture & Planning• 2018• Multidisciplinary Digital Publishing Institute
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Precision Agriculture Techniques and Practices: From Considerations to Applications

Internet of Things (IoT)-based automation of agricultural events can change the agriculture sector from being static and manual to dynamic and smart, leading to enhanced production with reduced human efforts. Precision Agriculture (PA) along with Wireless Sensor Network (WSN) are the main drivers of automation in the agriculture domain. PA uses specific sensors and software to ensure that the crops receive exactly what they need to optimize productivity and sustainability. PA includes retrieving real data about the conditions of soil, crops and weather from the sensors deployed in the fields. High-resolution images of crops are obtained from satellite or air-borne platforms (manned or unmanned), which are further processed to extract information used to provide future decisions. In this paper, a review of near and remote sensor networks in the agriculture domain is presented along with several considerations and challenges. This survey includes wireless communication technologies, sensors, and wireless nodes used to assess the environmental behaviour, the platforms used to obtain spectral images of crops, the common vegetation indices used to analyse spectral images and applications of WSN in agriculture. As a proof of concept, we present a case study showing how WSN-based PA system can be implemented. We propose an IoT-based smart solution for crop health monitoring, which is comprised of two modules. The first module is a wireless sensor network-based system to monitor real-time crop health status. The second module uses a low altitude remote sensing platform to obtain multi-spectral imagery, which is further processed to classify healthy and unhealthy crops. We also highlight the results obtained using a case study and list the challenges and future directions based on our work.

Architecture & Planning• 2019• Multidisciplinary Digital Publishing Institute
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Strategy making in novel and complex worlds: the power of analogy

Abstract We examine how firms discover effective competitive positions in worlds that are both novel and complex. In such settings, neither rational deduction nor local search is likely to lead a firm to a successful array of choices. Analogical reasoning, however, may be helpful, allowing managers to transfer useful wisdom from similar settings they have experienced in the past. From a long list of observable industry characteristics, analogizing managers choose a subset they believe distinguishes similar industries from different ones. Faced with a novel industry, they seek a familiar industry which matches the novel one along that subset of characteristics. They transfer from the matching industry high‐level policies that guide search in the novel industry. We embody this conceptualization of analogy in an agent‐based simulation model. The model allows us to examine the impact of managerial and structural characteristics on the effectiveness of analogical reasoning. With respect to managerial characteristics, we find, not surprisingly, that analogical reasoning is especially powerful when managers pay attention to characteristics that truly distinguish similar industries from different ones. More surprisingly, we find that the marginal returns to depth of experience diminish rapidly while greater breadth of experience steadily improves performance. Both depth and breadth of experience are useful only when one accurately understands what distinguishes similar industries from different ones. We also discover that following an analogy in too orthodox a manner—strictly constraining search efforts to what the analogy suggests—can be dysfunctional. With regard to structural characteristics, we find that a well‐informed analogy is particularly powerful when interactions among decisions cross policy boundaries so that the underlying decision problem is not easily decomposed. Overall, the results shed light on a form of managerial reasoning that we believe is prevalent among practicing strategists yet is largely absent from scholarly analysis of strategy. Copyright © 2005 John Wiley & Sons, Ltd.

Architecture & Planning• 2005• Wiley
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