Eija Koskivaara

Artificial neural networks in analytical review procedures

This article gives an overview of artificial neural network (ANN) studies conducted in the auditing field. The review pays attention to application domains, data and sample sets, ANN‐architectures and learning parameters. The article argues that these auditing ANN‐applications could serve the analytical review (AR) process. The summary of the findings pays attention to whether authors state that ANNs have potential to improve analytical review (AR) procedures. Furthermore, the article evaluates which are the most influential contributions and which are open ends in the field. The article makes some practical suggestions to motivate academics and practitioners to collaborate in further exploration of the potential of ANNs.

Artificial neural network models for predicting patterns in auditing monthly balances

The aim of this study is to investigate the potential of artificial neural network (ANN) models to recognise patterns when auditing monthly balances in financial accounts. ANNs have been used in many different disciplines as a basis for building intelligent information systems. This study examines the predictive ability of an ANN by building models using the 72 monthly balances of a manufacturing firm. The monthly balances are regarded as a time-series and the target is to recognise the dynamics and the relationships between different accounts. Furthermore, a certain seeded material error with signals from the ANN model is investigated. The results achieved indicate that neural networks seem promising for recognising the dynamics and the relationships between financial accounts.

Integrating analytical procedures into the continuous audit environment

The objective of this article is to show how to embed analytical procedures (AP) into the continuous audit environment. The audit environment is discussed in terms of audit phases, where the role of APs is to obtain evidence for auditors. The article addresses different characteristics of AP techniques. Furthermore, the article compares four different AP techniques to form expectations for the monthly sales values. Two of these techniques are simple quantitative ones, such as the previous years value and the mean of the previous years values. The advanced quantitative techniques are regression analysis and an artificial neural network (ANN)-based model. In a comparison of the prediction results, the regression analysis and ANN model turn out to be equally good. The development of these kinds of tools is crucial to the continuous audit environment, especially when most data transmission between companies and their stakeholders are moved into the electronic form.

Open-Source Software Implications in the Competitive Mobile Platforms Market

The era of the PC platform left a legacy of competitive strategies for the future technologies to follow. However, this notion became more complicated, once the future grew out to be a present with huge bundle of innovative technologies, Internet capabilities, communication possibilities, and ease in life. A major step of moving from a product phone to a smart phone, eventually to a mobile device has created a new industry with humongous potential for further developments. The current mobile platform market is witnessing a platforms-war with big players such as Apple, Google, Nokia and Microsoft in a major role. An important aspect of today’s mobile platform market is the contributions made through open source initiatives which promote innovation. This paper gives an insight into the open-source software strategies of the leading players and its implications on the market. It first gives a precise overview of the past leading to the current mobile platform market share state. Then it briefs about the open-source software components used and released by Apple, Google and Nokia platforms, leading to their mobile platform strategies with regard to open source. Finally, the paper assesses the situation from the point of view of communities of software developers complementing each platform. The authors identified relevant implications of the open-source phenomenon in the mobile-industry.

Value-creating E-Government business Models for Early childhood Education in Finland

In many cases, e-government is considered a name for transforming informative public services into electronic mode, although the focus of e-government should be on creating value for citizens as well as public organizations. In this article we apply Amit and Zott’s (2001) e-business value creation methods to an egovernment environment, namely early childhood education in Finland. The objective of the collaborative action research study was to find out what kind of business models in e-government would create value for citizens. The methodological result based on the collaborative nature of the study is a method for analyzing and generating business models. Amit & Zott’s framework also seems to be applicable to the e-government environment, and we were able to draw many viable business models for early childhood education, which forms the practical contribution of the study.

ICT Supporting Daily Physical Activity - with Special Reference to Pedometers in the Step-Shape Project

ICT Supporting Daily Physical Activity - with Special Reference to Pedometers in the Step-Shape Project Physical inactivity (PA) is one of the leading risks for mortality worldwide. One of future main drivers for physical activity could be information and communication technology gadgets and services that support active way of living. This study focuses on investigating and understanding how individuals use pedometers to support their physical activity and what their end-user experience is. In addition to individual scope, this is also important both for information society and healthcare organizations. They urgently require new approaches and tools to reshape their customers inactive lifestyle. Data for this study was collected with semi-structured questionnaire from subjects who used pedometers for a three month period and reported the daily step. The participants increased their PA during the project and most of them also informed on their intention to continue the more active lifestyle. The pedometer and the developed step collection table were easy to use and useful in supporting PA. ICT will inevitably play a major role in promotion of physically active lifestyle.

Visualization of Patterns in Accounting Data with Self-organizing Maps

Neural networks are data driven methods. They provide additional information to the decision process as might be left hidden otherwise. Neural networks have already been applied in many different business areas; and they can be used for prediction, classifying, and clustering. They can learn, remember, and compare complex patterns. This chapter shows how a neural network, especially Kohonen’s self-organizing map (SOM), can be used in visualization of complex accounting data. The SOM is used for clustering ten years of monthly income statements of a manufacturing firm. The purpose is to show how the data sets of various accounts and years form their own groups. We found that the SOM can be a visual aid for classifying and clustering data sets, and that it reveals if some cluster contains data that a priori should not be in it. Hence, it can be used for signaling unexpected fluctuations in data. Furthermore, the SOM is a possible technique embedded in the continuous monitoring and controlling tool.

A New Model to Study ICT Adoption in Connection with Physical Activity – The TAMPA-Model

Physical inactivity is one of the leading risks for mortality worldwide. One of future main drivers for physical activity could be information and communication technology (ICT) gadgets and services that support active way of living. This study is the first attempt to model ICT adaption and awareness matrix to motivate and use ICT to support daily physical activity. This is important for individuals and also for information society and healthcare organizations to cope with physical inactivity challenge. They urgently require new approaches and to reshape their customers’ inactive lifestyle. End-user experience data for this research was collected with semi-structured questionnaire from subjects who used pedometers for a three-month- period. In the questionnaire there were questions related to motivation, awareness and also use of information technology connected to physical activity. Based on the results, usage habits and patterns of pedometers, this paper classifies the end-users into four distinctive groups. This classification is called TAMPA-model (Technology Adaption Matrix for Physical Activity -model).

Service quality of Early Childhood Education web portals in Finnish municipalities

Increasing number of governmental organizations have transformed material on their web sites as a way of providing users with information about their products and services. In this paper, we apply Yang et al (2005) instrument for analyzing municipal early childhood education (ECE) web sites in Finland. The objective of the study was to find out the quality of ECE web portals as well as to give hints to improve their value from users’ point of view. In general the five dimensions, usability, usefulness of content, adequacy of information, accessibility, and interaction, of the Yang et al model seems to be applicable also in the early childhood education environment.