Internetalisation : the Internet's influence on international market growth in the firm's outward internationalisation process

It has been suggested that the Internet is the most significant driver of international trade in recent years to the extent that the term =internetalisation‘ has been coined (Bell, Deans, Ibbotson & Sinkovics, 2001; Buttriss & Wilkinson, 2003). This term is used to describe the Internet‘s affect on the internationalisation process of the firm. Consequently, researchers have argued that the internationalisation process of the firm has altered due to the Internet, hence is in need of further investigation. However, as there is limited research and understanding, ambiguity remains in how the Internet has influenced international market growth. Thus, the purpose of this study was to explore how the Internet influences firms‘ internationalisation process, specifically, international market growth. To this end, Internet marketing and international market growth theories are used to illuminate this ambiguity in the body of knowledge. Thus, the research problem =How and why does the Internet influence international market growth of the firm’ is justified for investigation. To explore the research question a two-stage approach is used. Firstly, twelve case studies were used to evaluate key concepts, generate hypotheses and to develop a model of Internetalisation for testing. The participants held key positions within their firm, so that rich data could be drawn from international market growth decision makers. Secondly, a quantitative confirmation process analysed the identified themes or constructs, using two hundred and twenty four valid responses. Constructs were evaluated through an exploratory factor analysis, confirmatory factor analysis and structural equation modelling process. Structural equation modelling was used to test the model of =internetalisation‘ to examine the interrelationships between the internationalisation process components: information availability, information usage, interaction communication, international mindset, business relationship usage, psychic distance, the Internet intensity of the firm and international market growth. This study found that the Internet intensity of the firm mediates information availability, information usage, international mindset, and business relationships when firms grow in international markets. Therefore, these results provide empirical evidence that the Internet has a positive influence on international information, knowledge, entrepreneurship and networks and these in turn influence international market growth. The theoretical contributions are three fold. Firstly, the study identifies a holistic model of the impact the Internet has had on the outward internationalisation of the firm. This contribution extends the body of knowledge pertaining to Internet international marketing by mapping and confirming interrelationships between the Internet, internationalisation and growth concepts. Secondly, the study highlights the broad scope and accelerated rate of international market growth of firms. Evidence that the Internet influences the traditional and virtual networks for the pursuit of international market growth extends the current understanding. Thirdly, this study confirms that international information, knowledge, entrepreneurship and network concepts are valid in a single model. Thus, these three contributions identify constructs, measure constructs in a multi-item capacity, map interrelationships and confirm single holistic model of ‗internetalisation‘. The main practical contribution is that the findings identified information, knowledge and entrepreneurial opportunities for firms wishing to maximise international market growth. To capitalise on these opportunities suggestions are offered to assist firms to develop greater Internet intensity and internationalisation capabilities. From a policy perspective, educational institutions and government bodies need to promote more applied programs for Internet international marketing. The study provides future researchers with a platform of identified constructs and interrelationships related to internetalisation, with which to investigate. However, a single study has limitations of generalisability; thus, future research should replicate this study. Such replication or cross validation will assist in the verification of scales used in this research and enhance the validity of causal predications. Furthermore, this study was undertaken in the Australian outward-bound context. Research in other nations, as well as research into inbound internationalisation would be fruitful.

Generating rules with predicates, terms and variables from the pruned neural networks

Artificial neural networks (ANN) have demonstrated good predictive performance in a wide range of applications. They are, however, not considered sufficient for knowledge representation because of their inability to represent the reasoning process succinctly. This paper proposes a novel methodology Gyan that represents the knowledge of a trained network in the form of restricted first-order predicate rules. The empirical results demonstrate that an equivalent symbolic interpretation in the form of rules with predicates, terms and variables can be derived describing the overall behaviour of the trained ANN with improved comprehensibility while maintaining the accuracy and fidelity of the propositional rules.

Means of achieving Business Process Management success factors

Business Process Management (BPM) in recent years has become a highest priority area for most organizations. Since this concept is multidisciplinary, success in this endeavour requires considering different factors. A number of studies have been conducted to identify these factors; however, most are limited to the introduction of high-level factors or to the identification of the means of success within only a specific context. This paper presents a holistic framework of success factors as well as the associated means for achieving success. This framework introduces nine factors, namely culture, leadership, communication, Information Technology, strategic alignment, people, project management, performance measurement and methodology. Each of these factors are characterized further by defining some sub-constructs and under each sub construct the means for achieving success are also introduced. This framework including means for achieving success can be useful for BPM project stakeholders in adequately planning the initiative and checking the progress during the implementation.

Application of text mining in analysing road crashes for road asset management

Traffic safety is a major concern world-wide. It is in both the sociological and economic interests of society that attempts should be made to identify the major and multiple contributory factors to those road crashes. This paper presents a text mining based method to better understand the contextual relationships inherent in road crashes. By examining and analyzing the crash report data in Queensland from year 2004 and year 2005, this paper identifies and reports the major and multiple contributory factors to those crashes. The outcome of this study will support road asset management in reducing road crashes.

Thai word segmentation with hidden Markov Model and decision tree

The Thai written language is one of the languages that does not have word boundaries. In order to discover the meaning of the document, all texts must be separated into syllables, words, sentences, and paragraphs. This paper develops a novel method to segment the Thai text by combining a non-dictionary based technique with a dictionary-based technique. This method first applies the Thai language grammar rules to the text for identifying syllables. The hidden Markov model is then used for merging possible syllables into words. The identified words are verified with a lexical dictionary and a decision tree is employed to discover the words unidentified by the lexical dictionary. Documents used in the litigation process of Thai court proceedings have been used in experiments. The results which are segmented words, obtained by the proposed method outperform the results obtained by other existing methods.

User-designer collaboration during the early stage of the design process

As user involvement becomes a necessary part of the product development process, various ways of accessing users' latent needs have been developed and studied. Reviews of literatures in user involvement and product development have revealed that accessing users' latent needs and transferring them into design process could be facilitated by effectively implementing user-designer collaboration during the early stage of the design process. In this paper, various types of user-designer collaboration were observed and then distinct characteristics of user-designer collaboration were classified into three categories. 1) Passive objectivity, 2) workplace democratisation, and 3) shared contexts were observed as strategies for better user-designer collaboration, which have been employed in the area of user-centred design, user participatory design and design for experiencing. Based on the literature review, this paper proposed a basic collaboration mechanism between the users and the designers during the early stage of the design process and then discussed how its mechanism will help to describe the interactions between the users and the designers during the user involvement sessions.

Personalised ontology learning and mining for web information gathering

Over the last decade, the rapid growth and adoption of the World Wide Web has further exacerbated user needs for e±cient mechanisms for information and knowledge location, selection, and retrieval. How to gather useful and meaningful information from the Web becomes challenging to users. The capture of user information needs is key to delivering users' desired information, and user pro¯les can help to capture information needs. However, e®ectively acquiring user pro¯les is di±cult. It is argued that if user background knowledge can be speci¯ed by ontolo- gies, more accurate user pro¯les can be acquired and thus information needs can be captured e®ectively. Web users implicitly possess concept models that are obtained from their experience and education, and use the concept models in information gathering. Prior to this work, much research has attempted to use ontologies to specify user background knowledge and user concept models. However, these works have a drawback in that they cannot move beyond the subsumption of super - and sub-class structure to emphasising the speci¯c se- mantic relations in a single computational model. This has also been a challenge for years in the knowledge engineering community. Thus, using ontologies to represent user concept models and to acquire user pro¯les remains an unsolved problem in personalised Web information gathering and knowledge engineering. In this thesis, an ontology learning and mining model is proposed to acquire user pro¯les for personalised Web information gathering. The proposed compu- tational model emphasises the speci¯c is-a and part-of semantic relations in one computational model. The world knowledge and users' Local Instance Reposito- ries are used to attempt to discover and specify user background knowledge. From a world knowledge base, personalised ontologies are constructed by adopting au- tomatic or semi-automatic techniques to extract user interest concepts, focusing on user information needs. A multidimensional ontology mining method, Speci- ¯city and Exhaustivity, is also introduced in this thesis for analysing the user background knowledge discovered and speci¯ed in user personalised ontologies. The ontology learning and mining model is evaluated by comparing with human- based and state-of-the-art computational models in experiments, using a large, standard data set. The experimental results are promising for evaluation. The proposed ontology learning and mining model in this thesis helps to develop a better understanding of user pro¯le acquisition, thus providing better design of personalised Web information gathering systems. The contributions are increasingly signi¯cant, given both the rapid explosion of Web information in recent years and today's accessibility to the Internet and the full text world.

Granule-based knowledge representation for intra and inter transaction association mining

Abstract With the phenomenal growth of electronic data and information, there are many demands for the development of efficient and effective systems (tools) to perform the issue of data mining tasks on multidimensional databases. Association rules describe associations between items in the same transactions (intra) or in different transactions (inter). Association mining attempts to find interesting or useful association rules in databases: this is the crucial issue for the application of data mining in the real world. Association mining can be used in many application areas, such as the discovery of associations between customers’ locations and shopping behaviours in market basket analysis. Association mining includes two phases. The first phase, called pattern mining, is the discovery of frequent patterns. The second phase, called rule generation, is the discovery of interesting and useful association rules in the discovered patterns. The first phase, however, often takes a long time to find all frequent patterns; these also include much noise. The second phase is also a time consuming activity that can generate many redundant rules. To improve the quality of association mining in databases, this thesis provides an alternative technique, granule-based association mining, for knowledge discovery in databases, where a granule refers to a predicate that describes common features of a group of transactions. The new technique first transfers transaction databases into basic decision tables, then uses multi-tier structures to integrate pattern mining and rule generation in one phase for both intra and inter transaction association rule mining. To evaluate the proposed new technique, this research defines the concept of meaningless rules by considering the co-relations between data-dimensions for intratransaction-association rule mining. It also uses precision to evaluate the effectiveness of intertransaction association rules. The experimental results show that the proposed technique is promising.

Quality-aware business process management

Business Process Management (BPM) has emerged as a popular management approach in both Information Technology (IT) and management practice. While there has been much research on business process modelling and the BPM life cycle, there has been little attention given to managing the quality of a business process during its life cycle. This study addresses this gap by providing a framework for organisations to manage the quality of business processes during different phases of the BPM life cycle. This study employs a multi-method research design which is based on the design science approach and the action research methodology. During the design science phase, the artifacts to model a quality-aware business process were developed. These artifacts were then evaluated through three cycles of action research which were conducted within three large Australian-based organisations. This study contributes to the body of BPM knowledge in a number of ways. Firstly, it presents a quality-aware BPM life cycle that provides a framework on how quality can be incorporated into a business process and subsequently managed during the BPM life cycle. Secondly, it provides a framework to capture and model quality requirements of a business process as a set of measurable elements that can be incorporated into the business process model. Finally, it proposes a novel root cause analysis technique for determining the causes of quality issues within business processes.

Effective pattern taxonomy mining in text documents

Many data mining techniques have been proposed for mining useful patterns in databases. However, how to effectively utilize discovered patterns is still an open research issue, especially in the domain of text mining. Most existing methods adopt term-based approaches. However, they all suffer from the problems of polysemy and synonymy. This paper presents an innovative technique, pattern taxonomy mining, to improve the effectiveness of using discovered patterns for finding useful information. Substantial experiments on RCV1 demonstrate that the proposed solution achieves encouraging performance.

Introducing a Business Process and Software Centric Approach for Enterprise System Teaching

To meet new challenges of Enterprise Systems that essentially go beyond the initial implementation, contemporary organizations seek employees with business process experts with software skills. Despite a healthy demand from the industry for such expertise, recent studies reveal that most Information Systems (IS) graduates are ill-equipped to meet the challenges of modern organizations. This paper shares insights and experiences from a course that is designed to provide a business process centric view of a market leading Enterprise System. The course, designed for both undergraduate and graduate students, uses two common business processes in a case study that employs both sequential and explorative exercises. Student feedback gained through two longitudinal surveys across two phases of the course demonstrates promising signs of the teaching approach.