Purpose The purpose of this paper is to introduce a novel approach to studying disaster management operations: the emergence of coordination-clusters in long-term rehabilitation projects and innovation dynamics in coordination-clusters. Design/methodology/approach The problem addressed is examining the coordination dynamics in long-term rehabilitation operations. A mixed methods research approach was adopted where a combination of qualitative and quantitative techniques was used for data collection and analysis to study the phenomenon of the coordination evolution in long-term rehabilitation projects. Findings The results indicate resilience in the behavior of involved actors from different organizations as they re-organize into coordination-clusters and collectively work to overcome the unfolding challenges of long-term rehabilitation projects in areas affected by major disaster. Research limitations/implications The results provide some answers to the question of how to map and analyze the phenomenon of coordination-clusters and their consequent coordination dynamics, and thereby steps to redesign the approach to execute long-term rehabilitation projects in places affected by major disasters. Practical implications The combination of Actor-network theory and critical incident technique with social network analysis and community detection provides an integrated network-based view of coordination dynamics in long-term recovery operations. Such perspective would broaden the empirical basis for the planning and management of complex disaster management operations. Originality/value The results of the research offer a new approach to study coordination dynamics in disaster management operations. The proposed method provides a tool to examine the evolution of processes involved with the recovery phase of a disaster management cycle.

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In this paper we introduce a novel approach to study emerging organizational relations and coordination structures in crisis response operations. We use dynamic modeling methods to analyze operations in conjunction with network analysis to study relationships among coordinating teams. The goal of the research is to produce a model describing evolution of crisis response operation as network based dynamic system. Ultimately, the model should help create different scenarios of cross-organizational collaboration in crisis events to gage effectiveness of crisis response systems. The envisioned research outcome will impact the future design of response plans in crisis management and hopefully contribute to the shift towards decentralized network based response plans.

ABSTRACT:Today, multi-image 3D reconstruction is an active research field and generating three dimensional model of the objects is one the most discussed issues in Photogrammetry and Computer Vision that can be accomplished using range-based or image-based methods. Very accurate and dense point clouds generated by range-based methods such as structured light systems and laser scanners has introduced them as reliable tools in the industry. Image-based 3D digitization methodologies offer the option of reconstructing an object by a set of unordered images that depict it from different viewpoints. As their hardware requirements are narrowed down to a digital camera and a computer system, they compose an attractive 3D digitization approach, consequently, although range-based methods are generally very accurate, image-based methods are low-cost and can be easily used by non-professional users. One of the factors affecting the accuracy of the obtained model in image-based methods is the software and algorithm used to generate three dimensional model. These algorithms are provided in the form of commercial software, open source and web-based services. Another important factor in the accuracy of the obtained model is the type of sensor used. Due to availability of mobile sensors to the public, popularity of professional sensors and the advent of stereo sensors, a comparison of these three sensors plays an effective role in evaluating and finding the optimized method to generate three-dimensional models. Lots of research has been accomplished to identify a suitable software and algorithm to achieve an accurate and complete model, however little attention is paid to the type of sensors used and its effects on the quality of the final model. The purpose of this paper is deliberation and the introduction of an appropriate combination of a sensor and software to provide a complete model with the highest accuracy. To do this, different software, used in previous studies, were compared and the most popular ones in each category were selected (Arc 3D, Visual SfM, Sure, Agisoft). Also four small objects with distinct geometric properties and especial complexities were chosen and their accurate models as reliable true data was created using ATOS Compact Scan 2M 3D scanner. Images were taken using Fujifilm Real 3D stereo camera, Apple iPhone 5 and Nikon D3200 professional camera and three dimensional models of the objects were obtained using each of the software. Finally, a comprehensive comparison between the detailed reviews of the results on the data set showed that the best combination of software and sensors for generating three-dimensional models is directly related to the object shape as well as the expected accuracy of the final model. Generally better quantitative and qualitative results were obtained by using the Nikon D3200 professional camera, while Fujifilm Real 3D stereo camera and Apple iPhone 5 were the second and third respectively in this comparison. On the other hand, three software of Visual SfM, Sure and Agisof...