Christos K. Georgiadis

A multi-level collaborative filtering method that improves recommendations

We propose a recommendation method that improves collaborative filtering.We divide the Pearson Correlation Similarity (PCC) in multiple levels.The proposed method has been tested on five real datasets.A comparison to alternative methods is provided in order to show its effectiveness. Collaborative filtering is one of the most used approaches for providing recommendations in various online environments. Even though collaborative recommendation methods have been widely utilized due to their simplicity and ease of use, accuracy is still an issue. In this paper we propose a multi-level recommendation method with its main purpose being to assist users in decision making by providing recommendations of better quality. The proposed method can be applied in different online domains that use collaborative recommender systems, thus improving the overall user experience. The efficiency of the proposed method is shown by providing an extensive experimental evaluation using five real datasets and with comparisons to alternatives.

Insider threats in corporate environments: a case study for data leakage prevention

Regardless of the established security controls that organizations have put in place to protect their digital assets, a rise in insider threats has been observed and particularly in incidents of data leakage. The importance of data as corporate assets is leading to a growing need for detection, prevention and mitigation of such violations by the organisations. In this paper we are investigating the different types of insider threats and their implications to the corporate environment, with specific emphasis to the special case of data leakage. Organisations should evaluate the risk they are facing due to insider threats and establish proactive measures towards this direction. In response to the challenging problem of identifying insider threats, we design a forensic readiness model, which is able to identify, prevent and log email messages, which attempt to leak information from an organisation with the aid of steganography.

Extending an e-Government Service Measurement Framework to m-Governement Services

This paper provides a measurement framework for mobile government (m-government) services adapted from the electronic government (e-government) environment. The measurement framework comprises the identification / categorization of m-government services, the sophistication stages of a service and the indicators used to evaluate the progress of these services. Three distinct categories of m-government services are identified, allowing for public agencies to prioritize their m-government initiatives. Α modification in the sophistication stages’ structure is also proposed, in order to achieve a more functional and flexible evaluation of m-government services. In addition, the appropriateness of selected indicators from the field of e-government is evaluated.

Analysing m-commerce research: technology, applications and research themes

Mobile and wireless communication technologies have enabled the provision of innovative services for individuals, organisations and society, while at the same time they have spawned a plethora of research opportunities. This special issue encapsulates four of the best papers that were presented during the 9th International Conference on Mobile Business/9th Global Mobility Roundtable. The papers discuss four seminal m-commerce topics. In our course to introduce the special issue, we perform a short outline of the trajectory of m-commerce research under three perspectives: technology, applications and core research themes.

Investigating customer satisfaction dimensions with service quality of online auctions: an empirical investigation of e-Bay

Over the recent years, C2C (consumer-to-consumer) electronic market has increased rapidly, and has become the most active segment of e-markets today. Despite the growth and popularity of online auctions and especially of e-Bay, which has been considered to be one of the most profitable e-commerce companies, the online auction environment is risky and transactions are complex due to the fact that buyer and seller do not know each other and they are not familiar. Although many studies have examined the impact of e-service quality on customer satisfaction in B2C (business-to-consumer) or B2B (business-to-business) commerce, the literature is insufficient in the case of C2C commerce. However, a number of authors have conducted research in C2C and particularly in e-Bay but in all of the cases, data source from e-Bay’s feedback system was employed in order to investigate service quality issues. Nevertheless, in this study a field research was conducted in order to collect the necessary data and thus reducing possible bias. The purpose of this paper is to examine some determinants of satisfaction with service quality dimensions in the online auction environment. More specifically, this paper is examining the case of e-Bay, in order to have a better understanding of buyers’ satisfaction in this risky environment. The paper’s aim is accomplished through an empirical investigation of a sample of 2,099 buyers of e-Bay, examining buyers’ expectation and perception levels towards service quality of e-Bay. Gap analysis was first employed in order to identify users’ disconfirmation dimensions in the online auction market place. Some research hypotheses are formulated to find out whether these dimensions have a positive disconfirmation. In most of the cases a positive disconfirmation is tracked down. Secondly, factor analysis was utilized to identify broad determinants of e-Bay service quality. The pool of the initial items deduced to four factors. These factors are, to a degree, differentiated in the Greek environment from factors found in other studies. A second round of research hypotheses are formulated again to find out whether those factors are related to the users’ disconfirmation dimensions. Finally, a new theoretical model is proposed based on the above mentioned hypotheses.

Understanding the Adoption of Mobile Data Services: Differences among Mobile Portal and Mobile Internet Users

This study attempts to investigate the potential differences among individual adoption patterns between m-portal and m-internet services usage. A theoretical model that reflects a set of unique predominant factors of IS usage was developed. The model was empirically tested using data collected on mobile data services adoption. The results indicate that there are differences among the adoption behavior of mobile portal users and mobile internet users. Specifically, mobile internet use is likely to be driven by utilitarian expectations and overall usefulness of accessing the web through this alternative medium. On the contrary, mobile portals use is likely to be dependent on the users’ current state of innovativeness and not being affected by the actual utility of the mobile data service. The paper concludes with theoretical and practical implications of our findings.

A dynamic multi-level collaborative filtering method for improved recommendations

One of the most used approaches for providing recommendations in various online environments such as e-commerce is collaborative filtering. Although, this is a simple method for recommending items or services, accuracy and quality problems still exist. Thus, we propose a dynamic multi-level collaborative filtering method that improves the quality of the recommendations. The proposed method is based on positive and negative adjustments and can be used in different domains that utilize collaborative filtering to increase the quality of the user experience. Furthermore, the effectiveness of the proposed method is shown by providing an extensive experimental evaluation based on three real datasets and by comparisons to alternative methods. We propose a method that improves collaborative filtering recommendations.It may use either a static or a dynamic multi-level approach.It is based on positive and negative adjustments of the users similarity values.Both approaches have been experimentally evaluated using three real datasets.Our approaches produce results of better quality when compared to alternatives.

Web of things: understanding the growing opportunities for business transactions

Building on the Internet of Things (IoT), the Web of Things (WoT) refers to a realistic and easily applicable idea of connecting an abundance of daily used devices and objects, such as embedded devices (smartphones, tablets etc.), through already well-established Web standards. Modern devices (which are usually equipped with sensors), have the ability to observe and monitor their environments. Consequently, there are unique opportunities and benefits to be reaped, by creating virtual counterparts, which allow access to their functionality through well-known protocols and standards (such as REST and HTTP). In this way, a corresponding digital world of vast resources is actually generated. Such opportunities can be of immense importance for business-centric scenarios where data provided and exchanged can complement and add to existing business models, thus playing an important part in the future planning of businesses. In this paper we firstly attempt to highlight the current research approaches specifically from the view of business centric scenarios. We discuss current research directions as well as existing problems and challenges based on the WoT paradigm and its implementations. We also highlight the methods, techniques and architectures involved, especially from the perspective of Web Services interactions. We attempt to stress the importance and possible benefits of implementing WoT methods, in a number of different enterprises operations. We focus on a domain specific application, implementing the notions of the Web of Things on medium sized enterprises, such as a network of retail stores. Finally, we study the information provided by applying the WoT approach and we analyze the influence that this information has for the future planning of business procedures.

Introduction to the special issue on User Experience in e-Business Environments

In the emerging global economy, e-commerce and e-business have increasingly become a necessary component of business strategy and a strong catalyst for economic development. Various applications of e-commerce are continually affecting trends and prospects for business over the Internet, including e-tailing, online publishing and online bidding. Eventually, with the rising proliferation of Internet, the customers’ expectations and demands have been changed. Customers seek to buy products and services in more competitive prices, without compromising the offered quality. A lot of research has been conducted worldwide on e-commerce, as it is undoubtedly a growing market and its applications represent a particularly highgrowth area in business sector. However, there has been little consideration on examining and evaluating user experience (expectations, perceptions, satisfaction) in the e-business context. The customer’s experience is a very important factor for the success of any e-commerce practice because it influences the customer’s perceptions of value and product/service quality, and therefore is affecting customer loyalty and retention. Customers’ perceptions are formed subsequent to their experience of the services received from an organization. Customers’ expectations revolve around their conviction about the products and services that they receive from the organization. Customers evaluate the service perceive performance, grounding on their expectation that they already have about the service of the company. Customers assigned

Explaining the Adoption of Mobile Internet Applications

This study aims at investigating the adoption behavior of mobile Internet users in Greece. An integrated model comprising of seven factors was developed and tested through the execution of a national telephone survey (N=139). The results of the survey suggest that the emotional state of individuals while using mobile Internet, social influence from their peers, and their personal innovativeness comprise the predictive factors of adoption behavior. Moreover, the study reveals that performance expectancy is a strong predictor of mobile Internet adoption mediated through individuals’ emotional state. The paper concludes with a critical discussion of the results comparing the study findings with past mobile data services studies.