Emmanouil Stiakakis

Foreign Direct Investments, Exports, and Economic Growth in Croatia: A Time Series Analysis☆

This paper studies the relationship between foreign direct investments, exports, and economic growth in Croatia using annual time series data for the period 1994-2012. Several econometric models are applied including the bounds testing (ARDL) approach and the ECM-ARDL model. The results confirm a bidirectional long run and short run causal relationship between exports and growth. These results offer new perspectives and insight for a new policy in Croatia for a sustainable economic growth.

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.

Combining metrics for software evolution assessment by means of Data Envelopment Analysis

Research and practice in software engineering have led to an extensive set of metrics for the evaluation of almost every aspect of software development. One of the major challenges for any quality model is the combination of metrics, which are complementary to each other. In this paper, we propose the use of Data Envelopment Analysis (DEA), a non‐parametric technique employed in economics, as a means of providing a unified view of selected design metrics. The proposed application of DEA aims at assessing the overall trend of quality during the evolution of software systems, by considering releases of a project as units to be ranked. An important benefit derived from the use of DEA is the ability to “normalize” the evaluation over the size characteristics of the examined systems, which is vital when comparing projects of different scale. Results are presented for successive versions of two open‐source, one industrial and one research project, whereas validation, whereas validation is performed by comparing the findings with the results obtained by Analytic Hierarchy Process, which is an acknowledged multi‐criteria decision analysis approach. According to the results, DEA enables the perception of global trends in qualitative characteristics, which would be otherwise difficult to recognize and interpret. Copyright

Combining the priority rankings of DEA and AHP methodologies: a case study on an ICT industry

This article presents a case study on how data envelopment analysis DEA and analytic hierarchy process AHP could be combined to produce priority rankings for a set of companies. The shortcomings of each method, when exclusively used to deal with multiple criteria decision analysis MCDA problems, are also analysed. The dataset of this study, arising from the European Union EU Industrial RD following that, ranking of the efficient companies could be attained through AHP.

The impact of environmental practices on firms’ efficiency: the case of ICT-producing sectors

The aim of this paper is to shed light on the debate concerning the impact of environmental practices on firms’ efficiency. It focuses on two of the most representative sectors of information and communication technologies’ industry, i.e. computer hardware and telecommunications equipment. The Data Envelopment Analysis (DEA) method was chosen to measure firm-level efficiency, since we are interested in the relative evaluation of a firm with respect to all other firms in a given set. The methodology is based on a three-stage approach: (1) construct an appropriate efficiency ratio, (2) divide the sampled companies into two discrete categories, i.e. the companies with more restrictive environmental practices (adherence to specific standards) and those with less restrictive practices (adoption of a general framework), and (3) calculate DEA efficiency scores. According to our findings, ICT companies which implement strict environmental practices are not necessarily more efficient than their rivals. Consequently, except for the case of compulsory regulations, ICT companies should consider all the possibilities and implement the practices best suited to their needs.

Benchmarking library and application software with Data Envelopment Analysis

Library software is generally believed to be well-structured and follows certain design guidelines due to the need of continuous evolution and stability of the respective APIs. We perform an empirical study to investigate whether the design of open-source library software is actually superior to that of application software. By analyzing certain design principles and heuristics that are considered important for API design, we extract a set of software metrics that are expected to reflect the improved nature of libraries. An initial comparison by conventional statistical analysis confirms the overall belief that products of different software size scale should not be compared by simply examining metric values in isolation. In this paper, we propose the use of Data Envelopment Analysis (DEA), borrowed from production economics, as a means of measuring and benchmarking the quality of different object-oriented software designs captured by software metrics and apply this approach to the comparison of library and application software. The advantages offered by DEA and the differences between the application of DEA in an economic and a technological context are discussed. Results of the approach are presented for 44 open-source projects, equally divided between libraries and applications.

Drivers of a tourism e-business strategy: the impact of information and communication technologies

The possible interactions among tourism organizations, their customers and other organizations are considered in this article. Based on these interactions, three drivers of an integrated e-business strategy in the tourism sector are suggested: (1) customizing tourist products, personalizing services and supporting mobile services, (2) sharing tourism information and operational data, and (3) offering tailor made products and supporting user-generated content. In order to emphasize our suggestions, the most representative figures derived from recent surveys conducted by the Sectoral e-Business W@tch are selected and analyzed. These figures are: (a) the use of customer relationship management applications in tourism and the importance of mobile services for different sectors of the economy including tourism, for the first driver, (b) the use of supply chain management systems, online purchasing and finally the use of broadband Internet as a complementary indicator, for the second driver, and (c) the use of ICT-enabled product and process innovations and dynamic packaging, for the third driver. The clear positive tendencies of these figures indicate the rising importance of our suggested directions as basic drivers of a tourism e-business strategy.

Privacy-preserving recommendations in context-aware mobile environments

Purpose This paper aims to address privacy concerns that arise from the use of mobile recommender systems when processing contextual information relating to the user. Mobile recommender systems aim to solve the information overload problem by recommending products or services to users of Web services on mobile devices, such as smartphones or tablets, at any given point in time and in any possible location. They use recommendation methods, such as collaborative filtering or content-based filtering and use a considerable amount of contextual information to provide relevant recommendations. However, because of privacy concerns, users are not willing to provide the required personal information that would allow their views to be recorded and make these systems usable. Design/methodology/approach This work is focused on user privacy by providing a method for context privacy-preservation and privacy protection at user interface level. Thus, a set of algorithms that are part of the method has been designed with privacy protection in mind, which is done by using realistic dummy parameter creation. To demonstrate the applicability of the method, a relevant context-aware data set has been used to run performance and usability tests. Findings The proposed method has been experimentally evaluated using performance and usability evaluation tests and is shown that with a small decrease in terms of performance, user privacy can be protected. Originality/value This is a novel research paper that proposed a method for protecting the privacy of mobile recommender systems users when context parameters are used.

A Model to Identify the Dimensions of Mobile Service Quality

The aim of this paper is to identify the dimensions of mobile service (m-service) quality. Based on the literature review and intervening to specific theoretical frameworks according to some critical characteristics of the mobile setting (security, personalization, etc.), a new hierarchical and multidimensional model is proposed. This model is validated using confirmatory principal component analysis of the data collected through an empirical research conducted among m-service users. The eleven components, which were extracted, are consistent with the dimensions suggested in our model.

A Method for Privacy-Preserving Context-Aware Mobile Recommendations

Mobile recommender systems aim to solve the information overload problem found by recommending products or services to users of mobile smartphones or tables at any given point in time and in any possible location. Mobile recommender systems are designed for the specific goal of mobile recommendations, such as mobile commerce or tourism and are ported to a mobile device for this purpose. They utilize a specific recommendation method, like collaborative filtering or content-based filtering and use a considerable amount of contextual information in order to provide more personalized recommendations. However due to privacy concerns users are not willing to provide the required personal information to make these systems usable. In response to the privacy concerns of users we present a method of privacy preserving context-aware mobile recommendations and show that it is both practical and effective.