Editorial

Citation

Ramage, M. and Bissell, D.C.a.C. (2014), "Editorial", Kybernetes, Vol. 43 No. 5. https://doi.org/10.1108/K-04-2014-0080

Editorial

Article Type: Editorial From: Kybernetes, Volume 43, Issue 5.

We would like to begin this issue by reminding those considering submitting articles to Kybernetes of two important matters.

First, plagiarism. We have had some unfortunate cases recently, at various stages of the publication process, where the editors have learnt that substantial portions of an article had been previously published by another author, without attribution. This is simply unacceptable academic practice. We will reject out of hand articles that we receive with such material, and if we find out about plagiarism after publication, we will retract such articles (issue a formal statement that the paper should never have been published). We also have little tolerance for authors re-using large parts of previous articles of their own without proper attribution. All work published in Kybernetes (or any other academic journal) should be original. Our publisher, Emerald, have a clear statement on originality which can be found at: www.emeraldgrouppublishing.com/authors/writing/originality.htm

Second, the importance of following the author guidelines. We receive a number of submissions where authors have clearly not read the guidelines, sending us articles where references are in the wrong format (they should be Harvard-style), articles are over-long (maximum length is 7,000 words with a reduction for each figure or table used), the title is much too long (the guidelines say no more than eight words but there is some flexibility, and up to 12 words would be acceptable), etc. The author guidelines are on the inside back cover of the printed journal, and online at: www.emeraldgrouppublishing.com/products/journals/author_guidelines.htm?id=k

We are delighted to receive a wide variety of articles submitted to the journal, and we continue to value its diversity, but basic academic standards are important. As we receive so many submissions, we are increasingly rejecting out of hand articles which fail to meet these standards. Due to the large and increasing number of received manuscripts, we will also be focusing the scope of the journal and will reject manuscripts that do not make a clear and significant contribution to the core areas of cybernetics, systems or management sciences.

There are 10 papers in this issue of the journal:

Wang introduces an economic model for Chinese high-tech industries, drawing on grey systems theory. The author creates a model based on three key economic variables across five different industries, using several years of real data from these industries. The model enables the author to predict the likely growth in these industries within China, and to draw conclusions for policy making.

Chen et al. discuss a method for risk analysis in information security. Using techniques from fuzzy sets and the concept of discriminatory weight, they seek to quantify the potential information security risks in a given system and create a computational model to evaluate those risks. They illustrate their approach with an example drawn from e-government.

Duh looks at succession patterns within family businesses, and the extent to which this helps or hinders organisational knowledge creation. Drawing on key knowledge management literature and the theory of requisite holism, the author develops and discusses a set of propositions around effective knowledge transfer in family businesses.

Peng and Wang look at multi-period decision making: a series of ongoing decisions that are required to be made over different periods of time. They apply techniques from fuzzy logic to this problem, defining a set of operators on such sets. They use these techniques on a practical case concerned with the performance of subcontractors.

Lin et al. examine a key in customer relationship management – churn prediction, i.e. how to determine the numbers and rate by which customers will leave and join an organisation. They consider churn prediction in telecoms firms, and look at the usefulness of data-mining techniques for this task. They compare the accuracy of eight different models for dimensionality and data reduction, using a large data set from a telecoms firm, concluding which techniques work best.

Zou et al. examine road networks, and study how to improve traffic flows, avoiding the problem of cascading failures, through the insertion of modular topologies. They carefully model these networks and topologies through the technique of Barabási-Albert scale-free networks, and run simulations to determine the most effective strategy for road network design.

Tong et al. look at grid technologies (i.e. large scale distributed processing using the internet as a form of supercomputer) to enable effective resource management for manufacturing. They present the architecture of a grid system for manufacturing services, and explore its use for decision making in the context of uncertain information. They illustrate their answer with a case study on the rapid development of a telescope across multiple organisations.

Petkovic et al. look at tactile sensing: how robots can determine the physical properties of objects in the world. They discuss a neural networks technique called an adaptive neuro fuzzy inference strategy to discover positions of objects. Their article discusses both the neural networks involved and the physical environment used to study and refine the strategy, as well as the results of their experimental data.

Ulker and Sezen develop an algorithm for fuzzy multi-criteria decision making, specifically focused on a manufacturing problem: effective design of printed circuit boards using computer-aided design tools. Their algorithm consists of modified versions of two sets of standard fuzzy logic techniques. They evaluate their algorithm through application to a real manufacturer.

Shayegan and Aghabozorgi present a method for reducing data sets used in pattern matching, specifically in Arabic and Farsi numerals. Their technique, a version of the modified frequency diagram approach, is discussed in detail and then analysed for its effectiveness. They conclude that their technique can reduce data set volume by a significant amount without reducing its effectiveness.

We hope you enjoy this issue.

Magnus Ramage, David Chapman and Chris Bissell