The competitive productivity (CP) of tourism destinations: an integrative conceptual framework and a reflection on big data and analytics

Purpose: The purpose of this study is twofold. First, this study elaborates an integrative conceptual framework of tourism destination competitive productivity (TDCP) by blending established destination competitiveness frameworks, the competitive productivity (CP) framework and studies pertaining to big data and big data analytics (BDA) within destination management information systems and smart tourism destinations. Second, this study examines the drivers of TDCP in the context of the ongoing 4th industrial revolution by conceptualizing the destination business intelligence unit (DBIU) as a platform able to create sustained destination business intelligence under the guise of BDA, useful to support destination managers to achieve the tourism destination’s economic objectives. Design/methodology/approach: In this work, the authors leverage both extant literature (under the guise of research on CP, tourism destination competitiveness [TDC] and destination management information systems) and empirical work (in the form of interviews and field work involving destination managers and chief executive officers of destination management organizations and convention bureaus, as well as secondary data) to elaborate, develop and present an integrative conceptual framework of TDCP. Findings: The integrative conceptual framework of TDCP elaborated has been found helpful by a number of destination managers trying to understand how to effectively and efficiently manage and market a tourism destination in today’s fast-paced, digital and hypercompetitive environment. While DBIUs are at different stages of implementation, often as part of broader smart destination initiatives, it appears that they are increasingly fulfilling the purpose of creating sustained destination business intelligence by means of BDA to help tourism destinations achieve their economic goals. Research limitations/implications: This work bears several practical implications for tourism policymakers, destination managers and marketers, technology developers, as well as tourism and hospitality firms and practitioners. Tourism policymakers could embed TDCP into tourism and economic policies, and destination managers and marketers might build and make use of platforms such as the proposed DBIU. Technology developers need to understand that designing destination management information systems in general and more specifically DBIUs requires an in-depth analysis of the stakeholders that are going to contribute, share, control and use BDA. Originality/value: To the best of the authors’ knowledge, this study constitutes the first attempt to integrate the CP, TDC and destination management information systems research streams to elaborate an integrative conceptual framework of TDCP. Second, the authors contribute to the Industry 4.0 research stream by examining the drivers of tourism destination CP in the context of the ongoing 4th industrial revolution. Third, the authors contribute to the destination management information systems research stream by introducing and conceptualizing the DBIU and the related sustained destination business intelligence

Understanding Common Perceptions from Online Social Media

Modern society habitually uses online social media services to publicly share observations, thoughts, opinions, and beliefs at any time and from any location. These geotagged social media posts may provide aggregate insights into people\u27s perceptions on a bad range of topics across a given geographical area beyond what is currently possible through services such as Yelp and Foursquare. This paper develops probabilistic language models to investigate whether collective, topic-based perceptions within a geographical area can be extracted from the content of geotagged Twitter posts. The capability of the methodology is illustrated using tweets from three areas of different sizes. An application of the approach to support power grid restoration following a storm is presented

FORCE-TORQUE MEASUREMENT SYSTEM FOR FRACTURE SURGERY

One of the more difficult tasks in surgery is to apply the optimal instrument forces and torques necessary to conduct an operation without damaging the tissue of the patient. This is especially problematic in surgical robotics, where force-feedback is totally eliminated. Thus, force sensing instruments emerge as a critical need for improving safety and surgical outcome. We propose a new measurement system that can be used in real fracture surgeries to generate quantitative knowledge of forces/torques applied by surgeon on tissues.We instrumented a periosteal elevator with a 6-DOF load-cell in order to measure forces/torques applied by the surgeons on live tissues during fracture surgeries. Acquisition software was developed in LabView to acquire force/torque data together with synchronised visual information (USB camera) of the tip interacting with the tissue, and surgeon voice recording (microphone) describing the actual procedure. Measurement system and surgical protocol were designed according to patient safety and sterilisation standards.The developed technology was tested in a pilot study during real orthopaedic surgery (consisting of removing a metal plate from the femur shaft of a patient) resulting reliable and usable. As demonstrated by subsequent data analysis, coupling force/torque data with video and audio information produced quantitative knowledge of forces/torques applied by the surgeon during the surgery. The outlined approach will be used to perform intensive force measurements during orthopaedic surgeries. The generated quantitative knowledge will be used to design a force controller and optimised actuators for a robot-assisted fracture surgery system under development at the Bristol Robotics Laboratory

Towards Robot-Assisted Fracture Surgery For Intra-Articular Joint Fractures

Background Treating fractures is expensive and includes a long post-operative care. Intra-articular fractures are often treated with open surgery that require massive soft tissue incisions, long healing time and are often accompanied by deep wound infections. Minimally invasive surgery (MIS) is an alternative to this but when performed by surgeons and supported by X-rays does not achieve the required accuracy of surgical treatment. Methods Functional and non-functional requirements of the system were established by conducting interviews with orthopaedic surgeons and attending fracture surgeries at Bristol Royal Infirmary to gain first-hand experience of the complexities involved. A robot-assisted fracture system (RAFS) has been designed and built for a distal femur fracture but can generally serve as a platform for other fracture types. Results The RAFS system has been tested in BRL and the individual robots can achieve the required level of reduction positional accuracy (less than 1mm translational and 5 degrees of rotational accuracy). The system can simultaneously move two fragments. The positioning tests have been made on Sawbones. Conclusions The proposed approach is providing an optimal solution by merging the fracture reduction knowledge of the orthopaedic surgeon and the robotic system's precision in 3D

Robot-Bone Attachment Device for Robot-Assisted Percutaneous Bone Fragment Manipulation

The treatment of joint-fractures is a common task in orthopaedic surgery causing considerable health costs and patient disabilities. Percutaneous techniques have been developed to mitigate the problems related to open surgery (e.g. soft tissue damage), although their application to joint-fractures is limited by the sub-optimal intra-operative imaging (2D-fluoroscopy) and by the high forces involved. Our earlier research toward improving percutaneous reduction of intra-articular fractures has resulted in the creation of a robotic system prototype, i.e. RAFS (Robot-Assisted Fracture Surgery) system. We propose a robot-bone attachment device for percutaneous bone manipulation, which can be anchored to the bone fragment through one small incision, ensuring the required stability and reducing the “biological cost” of the procedure. The device has been evaluated through the reduction of 9 distal femur fractures on human cadavers using the RAFS system

Image-Based Robotic System for Enhanced Minimally Invasive Intra-Articular Fracture Surgeries

Abstract: Robotic assistance can bring significant improvements to orthopedic fracture surgery: facilitate more accurate fracture fragment repositioning without open access and obviate problems related to the current minimally invasive fracture surgery techniques by providing a better clinical outcome, reduced recovery time, and health-related costs. This paper presents a new design of the robot-assisted fracture surgery (RAFS) system developed at Bristol Robotics Laboratory, featuring a new robotic architecture, and real-time 3D imaging of the fractured anatomy. The technology presented in this paper focuses on distal femur fractures, but can be adapted to the larger domain of fracture surgeries, improving the state-of-the-art in robot assistance in orthopedics. To demonstrate the enhanced performance of the RAFS system, 10 reductions of a distal femur fracture are performed using the system on a bone model. The experimental results clearly demonstrate the accuracy, effectiveness, and safety of the new RAFS system. The system allows the surgeon to precisely reduce the fractures with a reduction accuracy of 1.15 mm and 1.3°, meeting the clinical requirements for this procedure