6,111 research outputs found

    What attracts vehicle consumers’ buying:A Saaty scale-based VIKOR (SSC-VIKOR) approach from after-sales textual perspective?

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    Purpose: The increasingly booming e-commerce development has stimulated vehicle consumers to express individual reviews through online forum. The purpose of this paper is to probe into the vehicle consumer consumption behavior and make recommendations for potential consumers from textual comments viewpoint. Design/methodology/approach: A big data analytic-based approach is designed to discover vehicle consumer consumption behavior from online perspective. To reduce subjectivity of expert-based approaches, a parallel Naïve Bayes approach is designed to analyze the sentiment analysis, and the Saaty scale-based (SSC) scoring rule is employed to obtain specific sentimental value of attribute class, contributing to the multi-grade sentiment classification. To achieve the intelligent recommendation for potential vehicle customers, a novel SSC-VIKOR approach is developed to prioritize vehicle brand candidates from a big data analytical viewpoint. Findings: The big data analytics argue that “cost-effectiveness” characteristic is the most important factor that vehicle consumers care, and the data mining results enable automakers to better understand consumer consumption behavior. Research limitations/implications: The case study illustrates the effectiveness of the integrated method, contributing to much more precise operations management on marketing strategy, quality improvement and intelligent recommendation. Originality/value: Researches of consumer consumption behavior are usually based on survey-based methods, and mostly previous studies about comments analysis focus on binary analysis. The hybrid SSC-VIKOR approach is developed to fill the gap from the big data perspective

    Security based partner selection in Inter-organizational workflow systems

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    The creation of inter-organizational workflow implies the coalition of partners' efforts and resources in order to achieve a set of common objectives and goals. However, this openness may cause a huge damage to the participating entities due to security breaches. The risk of unsuccessful collaboration should be well studied. Thus, the key for successful collaboration is to select the appropriate collaborators based on specific security criteria for each outsourced task. In this sense, several criteria have to be considered, among them: trust and reputation level, policy similarity level, security level and privacy compliance level. The proposed security based partner selection approach allows us to rank participating entities in the collaboration based on the main security criteria in order to assign each task to the suitable partner with the most appropriate and efficient way

    Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

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    This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

    Preferences based Customized Trust Model for Assessment of Cloud Services

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    In cloud environment, many functionally similar cloud services are available. But, the services differ in Quality of Service (QoS) levels, offered by them. There is a diversity in user requirements about the expected qualities of cloud services. Trust is a measure to understand whether a cloud service can adequately meet the user requirements. Consequently, trust assessment plays a significant role in selecting the suitable cloud service. This paper proposes preferences based customized trust model (PBCTM) for trust assessment of cloud services. PBCTM takes into account user requirements about the expected quality of services in the form of preferences. Accordingly, it performs customized trust assessment based on the evidences of various attributes of cloud service. PBCTM enables elastic trust computation, which is responsive to dynamically changing user preferences with time. The model facilitates dynamic trust based periodic selection of cloud services according to varying user preferences. Experimental results demonstrate that the proposed preferences based customized trust model outperforms the other model in respect of accuracy and degree of satisfaction

    Assessment of Cyber Risks in an IoT-based Supply Chain using a Fuzzy Decision-Making Method

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    Purpose: The Internet of Things (IoT) is a relatively new paradigm that is growing rapidly in modern wireless communication scenarios. The main idea of this concept is the pervasive presence of all kinds of objects around us. This technology is the basis of today's intelligent life and is known as one of the most important sources of big data. Meanwhile, businesses are no exception to this rule and try to use the Internet of Things to make their business smarter. Supply chain management is a goal-based goal of linking business operations to provide a common view of market opportunity. Methodology: Using IoT technology, all major parts of the supply chain, including supply, production, distribution and sales, can be affected. Because this evolutionary technology is intertwined with Internet technology, the use of network-based tools can always create risks for business owners who use these technologies. Therefore, understanding and investigating a variety of cyber risks in this area can It is very important and by understanding their hands, we can prevent many future risks. Linear analysis based on hierarchical analysis is used. Findings: The results show that privacy is very important in interaction with suppliers as well as customers, and therefore those effective measures to deal with these risks can reduce many of the problems caused by this technology. Originality/Value: This paper attend to assessment of cyber risks in an IoT-based supply chain using a fuzzy decision-making method

    Security Enhanced Applications for Information Systems

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    Every day, more users access services and electronically transmit information which is usually disseminated over insecure networks and processed by websites and databases, which lack proper security protection mechanisms and tools. This may have an impact on both the users’ trust as well as the reputation of the system’s stakeholders. Designing and implementing security enhanced systems is of vital importance. Therefore, this book aims to present a number of innovative security enhanced applications. It is titled “Security Enhanced Applications for Information Systems” and includes 11 chapters. This book is a quality guide for teaching purposes as well as for young researchers since it presents leading innovative contributions on security enhanced applications on various Information Systems. It involves cases based on the standalone, network and Cloud environments
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