Kostas Moulinos, John Iliadis and Vassilis Tsoumas
In order to provide customers with a sense of security regarding the protection of their personal data, companies sign on to a “seal” programme, where rules designed by the seal…
Abstract
In order to provide customers with a sense of security regarding the protection of their personal data, companies sign on to a “seal” programme, where rules designed by the seal issuer in accordance to underlying laws must be adhered to. A user can verify online that a specific organisation adheres to a published privacy policy. This paper argues that the verifications means these programmes use are vulnerable to DNS spoofing attacks and present a privacy policy verification (“seal”) scheme, which is not vulnerable to attack. It is also argued that there are disadvantages in operating seal schemes that attempt to publicly certify compliance levels with a self‐regulatory privacy protection model. On the contrary, these disadvantages are softened when used in a regulatory model that has adopted comprehensive laws to ensure privacy protection.
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Stefanos Gritzalis, John Iliadis and Spyros Oikonomopoulos
A secure electronic marketplace involves a significant number of real‐time transactions between remote systems, either for commercial or for authentication purposes. The…
Abstract
A secure electronic marketplace involves a significant number of real‐time transactions between remote systems, either for commercial or for authentication purposes. The underlying infrastructure of choice to support these transactions seems to be a distributed component architecture. Distributed component software (DCS) is the natural convergence of client/server network computing and object oriented technology in a mix providing reusability, scaleability and maintainability for software constructs. In DCS a client acquires references to objects provided by components located to remote machines and invokes methods of them as if they were located in its native environment. One implementation also provides the ability to pass objects by value, an approach recently examined also by others. The three major models in the distributed component software industry are OMG’s CORBA, Sun’s Enterprise Java Beans, and Microsoft’s DCOM. Besides these, we will discuss the progress for interoperable DCS systems performed in TINA, an open architecture for telecommunications services based on CORBA distributed components. In this paper the security models of each architecture are described and their efficiency and flexibility are evaluated in a comparative manner. Finally, upcoming extensions are discussed.
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Gözde Öztürk and Abdullah Tanrisevdi
The purpose of this chapter is to shed light on researchers and practitioners about sentiment analysis in hospitality and tourism. The technical details described throughout the…
Abstract
The purpose of this chapter is to shed light on researchers and practitioners about sentiment analysis in hospitality and tourism. The technical details described throughout the chapter with a case study to provide clarifying insights. The proposed chapter adds significantly to the body of text mining knowledge by combining a technical explanation with a relevant case study. The case study used supervised machine learning to predict overall star ratings based on 20,247 comments related to Royal Caribbean International services for determining the impact of cruise travel experiences on the evaluation company process. The results indicate that travelers evaluate their travel experiences according to the most intense negative or positive feelings they have about the company.
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Stamatis Aggelopoulos, G. Menexes and I. Kamenidou
The aim of the study is to present the implications for the financing and sustainability of enterprises based on a ranking methodology for categorical financial data.
Abstract
Purpose
The aim of the study is to present the implications for the financing and sustainability of enterprises based on a ranking methodology for categorical financial data.
Design/methodology/approach
Taking advantage of the optimal scaling properties of correspondence analysis (CA), a ranking‐clustering procedure is proposed. The proposed method was applied to categorical financial variables (i.e family farm income, gross profit, gross income, labour income and profitability) collected from a stratified random sampling of 80 Greek pig farms using a structured questionnaire.
Findings
The cluster analysis revealed three distinct groups of pig farms. Several recommendations for managerial practices and financial development resulted from this study. For the farms belonging to cluster C1, that present low rankings on both criteria, a development planning process must be applied that will focus on organizational and management issues. For the farms belonging to cluster C2, that present low rankings on the “composite income” criterion, policy measures have to be undertaken, aiming at exploiting their own production coefficients, reducing fixed costs and increasing productivity. Finally, for the farms in cluster C3, that present high scores on both ranking criteria, it is recommended to take actions that will improve their competitiveness.
Research limitations/implications
The findings are limited to five selected financial variables. Therefore, future studies in the same or other business fields would benefit from incorporating a greater number of variables.
Originality/value
The proposed methodological scheme could be useful to practitioners and academics, due to the fact that limited studies have dealt with this ranking problem, particularly in relation to the Greek agricultural business environment.
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Reis da Silva Tiago and Aby Mitchell
Digital transformation in nursing education is crucial for enhancing pedagogical practices and preparing future healthcare professionals for the rapidly evolving healthcare…
Abstract
Digital transformation in nursing education is crucial for enhancing pedagogical practices and preparing future healthcare professionals for the rapidly evolving healthcare landscape. This chapter explores how the integration of digital technologies in higher education has revolutionising teaching methodologies and offered new opportunities to enhance learning experiences. It identifies gaps in digital learning modalities for undergraduate and postgraduate nursing students and discusses strategies to strengthen online literacy preparation and transition into the healthcare sector's digital transformation landscape and the 4th industrial era economy. The chapter examines best practices and challenges in digital transformation in nursing education such as blended learning environments, simulation and virtual reality, mobile learning applications and gamification strategies. Additionally, it addresses challenges in curriculum development including insufficient technological infrastructure, faculty training and development, assessment strategies and resistance to change among faculty and students. This chapter aims to provide insights and recommendations for educators, curriculum developers and policymakers in implementing successful digital transformation in nursing education.
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George Menexes and Stamatis Angelopoulos
The aim of the study is to propose certain agricultural policy measures for the financing and development of Greek farms, established by young farmers, based on the results of a…
Abstract
Purpose
The aim of the study is to propose certain agricultural policy measures for the financing and development of Greek farms, established by young farmers, based on the results of a clustering method suitable for handling socio‐economic categorical data.
Design/methodology/approach
The clustering method was applied to categorical data collected from 110 randomly selected investment plans of Greek agricultural farms. The investment plans were submitted to the “Region of Central Macedonia” administrative office, in the framework of the Operational Programme “Agricultural Development – Reform of the Countryside 2000‐2006” and refer to agricultural investments by “Young Farmers”, according to the terms and conditions of Priority Axis III: “Improvement of the Age Composition of the Agricultural Population”. The input variables for the analyses were the farmers' gender, age class, education level and permanent place of residence, the farms' agricultural activity, Human Labour Units (HLU) and farms' viability level. All these variables were measured on nominal or ordinal scales. The available data were analyzed by means of a hierarchical cluster analysis method applied on the rows of an appropriate matrix of a complete disjunctive form with a dummy coding 0 or 1. The similarities were measured through the Benzécri'sχ2distance (metric), while the Ward's method was used as a criterion for cluster formation.
Findings
Five clusters of farms emerged, with statistically significant diverse socio‐economic profiles. The most important impact on the formation of the groups of farms was found to be related to the number of HLU, the farmers' level of education and gender. This derived typology allows for the determination of a flexible development and funding policy for the agricultural farms, based on the socio‐economic profile of the formulated clusters.
Research limitations/implications
One of the limitations of the current study derives from the fact that the clustering method used is suitable only for categorical, non‐metric data. Another limitation comes from the fact that a relative small number of investment plans were used in the analysis. A larger sample covering and other geographical regions is needed in order to confirm the current results and make nation‐wide comparisons and “tailor‐made” proposals for financing and development. Finally, it is interesting to contact longitudinal surveys in order to evaluate the effectiveness of the funding policy of the corresponding programme.
Originality/value
The study's results could be useful to practitioners and academics because certain agricultural policy measures for the financing and development of Greek farms established by young farmers are proposed. Additionally, the data analysis method used in this study offers an alternative way for clustering categorical data.