Abstract: The complex and problematic relationship between software development methods and practices is well documented. Methods are difficult to adopt. There are several barriers toward successfully bringing methods to practice, and practices are, by the end of the day, quite different from method prescriptions. Methods are, however, continually developed, and organisations spend considerable resources trying to improve practices through adoption of new methods. We know relatively little about the long-term dynamics involved in such adoption efforts. This research reports from a three-year effort within an IT department of a large multinational company in which a new method was first introduced, then used to support organisation-wide projects, and subsequently extended based on emerging practices. The study applies two complementary knowledge management perspectives – networks and networking – to interpret the experiences from the case. The study reveals how method perceptions and approaches shift radically through different stages of software method adoption.

The growing interest in Structured Equation Modeling (SEM) techniques and recognition of their importance in IS research suggests the need to compare and contrast different types of SEM techniques so that research designs can be selected appropriately. After assessing the extent to which these techniques are currently being used in IS research, the article presents a running example which analyzes the same dataset via three very different statistical techniques. It then compares two classes of SEM: covariance-based SEM and partial-least-squaresbased SEM. Finally, the article discusses linear regression models and offers guidelines as to when SEM techniques and when regression techniques should be used. The article concludes with heuristics and rule of thumb thresholds to guide practice, and a discussion of the extent to which practice is in accord with these guidelines.

Search Based Software Engineering (SBSE) is an emerging paradigm in which search based optimisation algorithms are used to balance multiple software engineering objectives. The SBSE approach has been the subject of much recent interest. However, despite the fact that many optimisation algorithms are highly parallel, there has been very little work on exploiting this potential for scalability. This is an important oversight because scalability is so often a critical Software Engineering success factor. This paper shows how relatively inexpensive General Purpose computing on Graphical Processing Unit (GPGPU) can be used to run suitably adapted optimisation algorithms, opening up the possibility of cheap scalability. The paper develops a search based optimisation approach for multiple objective regression test optimisation, evaluating it on benchmark regression testing problems as well as larger real world problems. The results indicate that speed–ups of over 20x are possible using widely available standard GPUs. It is also encouraging that the results reveal a statistically strong correlation between larger problem instances and the degree of speed up achieved.

Abstract: Conceptual modeling continues to be an important means for graphically capturing the requirements of an information system. Observations of modeling practice suggest that modelers often use multiple modeling grammars in combination to articulate various aspects of real-world domains. We extend an ontological theory of representation to suggest why and how users employ multiple conceptual modeling grammars in combination. We provide an empirical test of the extended theory using survey data and structured interviews about the use of traditional and structured analysis grammars within an automated tool environment. We find that users of the analyzed tool combine grammars to overcome the ontological incompleteness that exists in each grammar. Users further selected their starting grammar from a predicted subset of grammars only. The qualitative data provides insights as to why some of the predicted deficiencies manifest in practice differently than

The attention of software vendors has moved recently to Small to Medium-sized Enterprises (SMEs) offering them a vast range of Enterprise Systems (ES) including ERP, CRM, SCM and E-Procurement systems, which were formerly adopted by large firms only. From reviewing the literature on the adoption and diffusion of Information Systems ’ (IS) innovations, the question of ‘why some SMEs choose to adopt ES while seemingly similar others facing the same market conditions do not ’ is still under-studied. This paper intends to fill this gap by developing a model that can be used to predict which SMEs are more likely to become adopters of ES. Using direct interviews, data was collected from 102 SMEs located in the Northwest of England. Logistic regression was used to analyse the data. Results reveal that factors influencing SMEs ’ adoption of ES are different from factors influencing SMEs ’ adoption of other previously studied IS innovations. SMEs were found to be more influenced by technological and organisational factors than environmental factors. Moreover, results indicate that firms with a greater perceived relative advantage, a greater ability to experiment with ES before adoption, a greater top management support, a greater organisational readiness and a larger size are predicted to become adopters of ES.

Continuous technological development has created new ways of utilising IT in the public sector. However, the use of information technology is still to a large degree in its infancy in early childhood education. The study focuses on the adoption of IT innovations within early childhood education context in Finland. IT innovations can be used for instance in communication between different actors in early childhood education, in rationalisation of day care management and in support of the child's healthy growth. The study examines the organisational factors that enhance or hinder organisational innovativeness. A qualitative multiple case study approach was selected in order to understand the adoption processes in different organisations.