Panos Louvieris

Performance Measurement Systems in Tourism, Hospitality, and Leisure Small Medium-Sized Enterprises: A Balanced Scorecard Perspective

In response to the United Kingdom’s government’s desire to improve the performance of tourism, hospitality, and leisure small medium-sized enterprises, this article analyzes the performance measurement processes within 10 best practice organizations. Related to contemporary approaches to improving business performance in the management literature, performance measurement approaches are analyzed using the balanced scorecard framework. An exploratory case study approach using the balanced scorecard as the theoretical framework was taken to explore and elicit critical success factors in performance measurement. Results revealed that four key concepts drove measurement and performance evaluation systems across the sample. These were the exercising of budgetary control with a view to increasing total revenue, the undertaking of customer relationship management as a means of improving quality of service and customer retention, the necessity for strategic management in managing internal business processes, and collaboration (both inter and intra) to drive innovation and learning. The article also proposes a balanced scorecard template for hotels.

Statistical Testing in Forecasting Model Selection

The ability of various econometric and univariate time-series models to generate accurate forecasts of international tourism demand is evaluated. Accuracy is assessed in terms of error magnitude and also directional change error. Statistical testing for both forecasting bias and directional change forecasting performance is introduced. The empirical results show that for 1-year-ahead forecasting, the time-varying parameter model performs consistently well. However, for 2- and 3-years-ahead forecasting, the best model varies according to the forecasting error criterion under consideration. This highlights the importance (for longer term forecasts) of selecting a forecasting method that is appropriate for the particular objective of the forecast user.

Effects-based feature identification for network intrusion detection

Intrusion detection systems (IDS) are an important element in a networks defences to help protect against increasingly sophisticated cyber attacks. IDS that rely solely on a database of stored known attacks are no longer sufficient for effectively detecting modern day threats. This paper presents a novel anomaly detection technique that can be used to detect previously unknown attacks on a network by identifying attack features. This effects-based feature identification method uniquely combines k-means clustering, Naive Bayes feature selection and C4.5 decision tree classification for pinpointing cyber attacks with a high degree of accuracy in order to increase the situational awareness of cyber network operators.

Robust Synchronization for 2-D Discrete-Time Coupled Dynamical Networks

In this paper, a new synchronization problem is addressed for an array of 2-D coupled dynamical networks. The class of systems under investigation is described by the 2-D nonlinear state space model which is oriented from the well-known Fornasini-Marchesini second model. For such a new 2-D complex network model, both the network dynamics and the couplings evolve in two independent directions. A new synchronization concept is put forward to account for the phenomenon that the propagations of all 2-D dynamical networks are synchronized in two directions with influence from the coupling strength. The purpose of the problem addressed is to first derive sufficient conditions ensuring the global synchronization and then extend the obtained results to more general cases where the system matrices contain either the norm-bounded or the polytopic parameter uncertainties. An energy-like quadratic function is developed, together with the intensive use of the Kronecker product, to establish the easy-to-verify conditions under which the addressed 2-D complex network model achieves global synchronization. Finally, a numerical example is given to illustrate the theoretical results and the effectiveness of the proposed synchronization scheme.

Managing customer behaviour dynamics in the multi-channel e-business environment: Enhancing customer relationship capital in the global hotel industry

Managing the dynamics of customer behaviour in the rapidly emerging multi-channel e-business environment is complex. Establishing an enduring and profitable dialogue with a customer requires that online relationship management applications can accommodate the channel variety in the customer’s e-communications portfolio, including their buyer behaviour dynamics. With reference to the global hotel industry, this paper considers the impact of Internet multi-channel access on the customer decision-making process; how differences in buyer behaviour and loyalty level influence the relationship management process; and the implications of effectively managing buyer behaviour and the provision of multi-channel customer accessibility for competitive advantage.

Human-Centered Safety Analysis of Prospective Road Designs

One of the most important issues in road safety management is the lack of reliable methods for predicting the likelihood of accidents. Road safety assessment systems have been developed; however, these systems only employ historical or retrospective analyses, and the human factor element is weak or missing. Effective safety management requires both holistic and prospective viewpoints, with human factors having an intrinsic role. The main goal of this paper is to contribute toward that need through the application of Bayesian belief networks and road traffic simulation for validating the safety requirements of prospective road designs. The theoretical platform of the method is the concepts of human performance and mental workload and how these affect accident likelihood. This paper presents a novel method and a tool that integrates these two mature technologies, for assessing the safety performance of road designs before they are developed. A case study is included that illustrates the application of the method and tool.

IT induced business transformation in higher education: an analysis of the UniCafé experience and its implications

This paper is concerned with the changes in the business processes of higher education that may result from the introduction of IT enabled, either eLocalised or eDistributed, learning methods. It provides a framework based on the issues of commercial business transformation that can be linked to changes in the teaching and learning process and learner markets. Evidence from a case study of the UniCafe project based at the University of Surrey and other surrounding projects and initiatives is considered in the light of this matrix in order to highlight some of the key organizational challenges facing future development.

New frontiers in cybersegmentation: marketing success in cyberspace depends on IP address

Focuses on the forthcoming next generation Internet’s address system (IPv6) which will potentially redefine the way marketers approach the segmentation of interactive cybermarkets. Explores the ramifications of Internet‐based purchasing systems to buyer behaviour. Differences and similarities of next generation direct marketing compared with classic and neoclassic direct marketing approaches are evaluated. Sensitivity to changes and differences in customer decision‐loyalty type are explored from the perspective of building high value customer relationships, where decision‐loyalty type is considered to be a key resegmentation variable for personalised interactive cybermarketing.

Assessing critical success factors for military decision support

This paper outlines the application of case-based reasoning and Bayesian belief networks to critical success factor (CSF) assessment for parsimonious military decision making. An important factor for successful military missions is information superiority (IS). However, IS is not solely about minimising information related needs to avoid information overload and the reduction of bandwidth but it is also concerned with creating information related capabilities that are aligned with achieving operational effects and raising operational tempo. Moreover, good military decision making, should take into account the uncertainty inherent in operational situations. Herein, we illustrate the development and evaluation of a smart decision support system (SDSS) that dynamically identifies and assesses CSFs in military scenarios and as such de-clutters the decision making process. The second contribution of this work is an automated configuration of conditional probability tables from hard data generated from simulations of military operational scenarios using a computer generated forces (CGF) synthetic environment.

Integrating the enterprise: the role of a language system for a marketing conception

A marketing‐centric view of the connected enterprise implies that qualitative information in its systems and general document structures share a marketing‐based vocabulary – we propose that this should be founded on POSIT. As any system needs to be accessed and understood by people, the basis of its construction and navigation principles should be transparent even though many component processes will be automated. Based on the use of natural language, a user‐defined glossary stems from a selection of primitives and relationships between them. Semantic mapping employing the reciprocal text‐to‐graphical capability of EXPRESS and EXPRESS G is outlined. The significance of XML and related developments is introduced in the context of qualitative information search and extraction from documents. Consensual language also aids connectivity of intranets and extranets to the Internet.