Journal of Systems and Information Technology

Miklós Herdon; László Várallyai; Ádám Péntek

2012 Journal of Systems and Information Technology

doi: 10.1108/13287261211279026

Purpose – The purpose of this paper is to survey, systemize and analyse the e‐readiness of small and medium‐sized enterprises (SMEs) and determine which new technologies can be applied to build a digital business ecosystem (DBE) for SMEs. Based on the results of a survey, the authors' objectives are to propose an adequate solution system that uses open source solutions for the SME through the development of a prototype based on a DBE concept. Design/methodology/approach – On the resulting principal components, the authors applied the variance analysis and built two LISREL (a linear structural equation system involving multiple indicators of unmeasured variables) models. LISREL can handle a wide array of problems and models. Based on a survey, an open source prototype solution was developed based on DBE philosophy. Findings – The authors defined different clusters. An SME can then find within the clusters further methods that could be important for their business. The authors developed two LISREL models, aiming to examine the factors that impact the use of the community applications and how they impact them, as well as the factors that impact the increase of the on‐line sales. Based on the survey, a prototype system was designed and created that can be used for the set‐up of digital business networks. Practical implications – The paper proposes an adequate solution system that uses open source solutions for the SMEs through the development of a prototype based on a DBE concept. Originality/value – Building DBEs helps to create and operate value chains that help enterprises to extend their markets. Through their help, the inquirers and buyers get to know the elements of the value chain, and can therefore make decisions much easier. The paper shows how to define e‐attributes of SMEs and clusters to build and use a DBE system for them.

Michail Salampasis; Dimitrios Tektonidis; Eleni P. Kalogianni

2012 Journal of Systems and Information Technology

doi: 10.1108/13287261211279053

Purpose – The purpose of this paper is to describe TraceALL which is a Semantic Web (SW), ontology‐based, service‐oriented framework which aims to provide the necessary infrastructure enabling food industry (particularly SMEs) to implement traceability applications using an innovative generic framework. Design/methodology/approach – The framework builds upon the idea of the Semantic Web and provides an open and extensible underlying platform that allows different traceability interconnected applications to be designed and developed. More specifically, the framework provides a formal, ontology‐based, general‐purpose methodology to support knowledge representation and information modelling in traceability systems. Additionally, it suggests an open application framework based on widely used Semantic Web standards. Finally it provides a set of core services for storing, processing and retrieving traceability information in a scalable way. These components, taken together, facilitate the efficient development of next generation traceability applications. Findings – Based on a case study which the authors executed as a proof of concept and studying the relevant literature it was found that TraceALL facilitates the development of next generation traceability applications because, from a food safety perspective, it enables all stakeholders in the food supply chain to have an information trail that follows the product's physical trail, but at the same time is cost effective, easy to manage and applicable within a globalised, networked, interoperable economic environment. Originality/value – To the best of the authors' knowledge, this is the first food traceability system based completely on solid existing standards of the Semantic Web initiative. The authors consider that the inspiring analogy between resources such as those described in the Semantic Web initiative and the core traceability concept of a Traceable Resource Unit (TRU) is an extremely useful concept for developing cost‐effective traceability applications that possess many key requirements, which are described in the paper.

Theodosios Theodosiou; Stavros Valsamidis; Georgios Hatziliadis; Michael Nikolaidis

2012 Journal of Systems and Information Technology

doi: 10.1108/13287261211279062

Purpose – A huge amount of data are produced in the agriculture sector. Due to the huge number of these datasets it is necessary to use data analysis techniques in order to comprehend the data and extract useful information. The purpose of this paper is to measure, archetype and mine olea europaea production data. Design/methodology/approach – This work applies three different data mining techniques to data about Olea europaea var. media oblonga from the island of Thassos, at the northern part of Greece. The data were from 1,063 farmers from three different municipalities of Thassos, namely Kallirachi, Limenaria and Prinos and concerned the year 2010. They were analysed using the classification algorithm OneR, the clustering algorithm k‐means and the association rule mining algorithm, Apriori from the WEKA data mining package. Also, new measures which quantify the performance of the productions of olives and oil are applied. Finally, archetypal analysis is applied in order to distinguish the most typical/stereotype farms for each region and describe their specific characteristics. Findings – The results indicate that organic cultivation could improve the production of olives and olive oil. Furthermore, the climate differences among the three municipalities seems to be a factor involved in production efficacy. Originality/value – It is the first time that data from the island of Thassos have been analysed systematically using a variety of data mining methods. Also, the measures proposed in the paper in order to analyse the data are new. Furthermore, archetypal analysis is proposed as a method to extract sterotypes/representative farms from the dataset.

Faruq A. Al‐Omari; Osama D. Al‐Khaleel; Ghassan A. Rayyashi; Sameh H. Ghwanmeh

2012 Journal of Systems and Information Technology

doi: 10.1108/13287261211279071

Purpose – The purpose of this paper is to develop an innovative information hiding algorithm. Design/methodology/approach – The proposed algorithm is based on image histogram statistics. Cumulative‐peak histogram regions are utilized to hide multiple bits of the secret message by performing histogram bin substitution. The embedding capacity, otherwise known as payload, and peak signal to noise ratio (PSNR), as well as security, are the main metrics used to evaluate the performance of the proposed algorithm. Findings – According to the obtained results, the proposed algorithm shows high embedding capacity and security at comparable PSNR compared with existing hiding information techniques. Originality/value – The simplicity, security, random distribution of embedding pixels, and on‐demand high capacity are the key advantages of the proposed approach.

Adel Alaraifi; Alemayehu Molla; Hepu Deng

2012 Journal of Systems and Information Technology

doi: 10.1108/13287261211279080

Purpose – The purpose of this paper is to explore what information systems are used within the data center industry and to develop a data center information systems classification framework for facilitating the investigation of the dimensions, operational characteristics, and value attributes of the data center information systems. Design/methodology/approach – A preliminary data center information systems classification framework is proposed based on a comprehensive review of existing information systems research. A case study of five data centers in Australia and a review of the practitioner literature in data centers are conducted. An open coding method is adopted for facilitating the analysis of the data using existing content analysis techniques. Findings – In total, 19 different types of data center information systems are identified in data centers. These information systems are being used for managing the information technology and the facility infrastructure in the data center and for improving the agility, the operational and cost performance, as well as the environmental footprint of individual data centers. Research limitations/implications – The paper builds a data center information systems classification framework to examine the role, portfolio, managerial function, and utilization of data center information systems. Such a classification would provide a foundation for further investigating the adoption of various information systems in data centers towards the continuous pursuit of sustainability development from different perspectives. Practical implications – The paper provides data center managers with recent trends and issues regarding the adoption of information systems in data centers to manage their operations. It offers data center management a valuable means for exploring innovative ways of effectively adopting various technologies to improve their performance. Originality/value – Given that there is limited research on what and how information systems are used in data centers, the paper can be viewed as one of the few data center information systems investigations that provide a good comprehension of what information systems are used and what the value drivers are with respect to the use of information systems in data centers.