Global Software Development: Measuring, Approximating and Reducing the Complexity of Global Software Development Using Extended Axiomatic Design Theory

This paper considers GSD projects as designed artefacts, and proposes the application of an Extended Axiomatic Design theory to reduce their complexity in order to increase the probability of project success. Using an upper bound estimation of the Kolmogorov complexity of the so-called ‘design matrix’ (as a proxy of Information Content as a complexity measure) we demonstrate on two hypothetical examples how good and bad designs of GSD planning compare in terms of complexity. We also demonstrate how to measure and calculate the ‘structural’ complexity of GSD projects and show that by satisfying all design axioms this ‘structural’ complexity could be minimised

Crossing the Communication Barrier in Global Software Development Projects via Global Software Development Brokers

As the key stakeholders in Global Software Development (GSD) projects are distributed across geographical locations, many GSD projects suffer from a communication barrier, which exists due to language-, cultural-, time zone (and possibly other) differences among key stakeholders. This barrier not only increases communication cost, it also decreases the efficiency and quality of stakeholder communication, adding extra risks to these projects, and decreasing the probability of success. So far, there is no simple solution to this problem. Using the Collaborative Networks paradigm, this paper introduces the concept of ‘Global Software Development Collaborative Network’ (GSD-CN) as a formal model to analyse communication cost and quality. The paper proposes a new entity (role) called Global Software Development Broker (GSDB). We argue and demonstrate in an example that the proposed GSDBs will (a) simplify the network structure, (b) decrease communication cost, and (c) improve communication quality – consequently increasing the probability of success of GSD projects

The moderating influence of device characteristics and usage on user acceptance of smart mobile devices

This study seeks to develop a comprehensive model of consumer acceptance in the context of Smart Mobile Device (SMDs). This paper proposes an adaptation of the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT2) model that can be employed to explain and predict the acceptance of SMDs. Also included in the model are a number of external and new moderating variables that can be used to explain user intentions and subsequent usage behaviour. The model holds that Activity-based Usage and Device Characteristics are posited to moderate the impact of the constructs empirically validated in the UTAUT2 model. Through an important cluster of antecedents the proposed model aims to enhance our understanding of consumer motivations for using SMDs and aid efforts to promote the adoption and diffusion of these devices

Co-evolution path model : how enterprises as complex systems survive on the edge of chaos

In this theoretical paper, we introduce and describe a model, and demonstrate its origins from the disciplines of Enterprise Architecture, cybernetics and systems theory. We use cybernetic thinking to develop a &lsquo;Co-evolution Path Model&rsquo; that describes how enterprises as complex systems co-evolve with their complex environments. The model re-interprets Stafford Beer&rsquo;s Viable System Model, and also uses the theorem of the &lsquo;good regulator&rsquo; of Conant and Ashby, exemplifying how various complexity management theories could be synthesised into a cybernetic theory of Enterprise Architecture, using concepts from the generalisation of EA frameworks.<br /

Modern software cybernetics: new trends

Software cybernetics research is to apply a variety of techniques from cybernetics research to software engineering research. For more than fifteen years since 2001, there has been a dramatic increase in work relating to software cybernetics. From cybernetics viewpoint, the work is mainly on the first-order level, namely, the software under observation and control. Beyond the first-order cybernetics, the software, developers/users, and running environments influence each other and thus create feedback to form more complicated systems. We classify software cybernetics as Software Cybernetics I based on the first-order cybernetics, and as Software Cybernetics II based on the higher order cybernetics. This paper provides a review of the literature on software cybernetics, particularly focusing on the transition from Software Cybernetics I to Software Cybernetics II. The results of the survey indicate that some new research areas such as Internet of Things, big data, cloud computing, cyber-physical systems, and even creative computing are related to Software Cybernetics II. The paper identifies the relationships between the techniques of Software Cybernetics II applied and the new research areas to which they have been applied, formulates research problems and challenges of software cybernetics with the application of principles of Phase II of software cybernetics; identifies and highlights new research trends of software cybernetic for further research

Modern software cybernetics: New trends

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Software cybernetics research is to apply a variety of techniques from cybernetics research to software engineering research. For more than fifteen years since 2001, there has been a dramatic increase in work relating to software cybernetics. From cybernetics viewpoint, the work is mainly on the first-order level, namely, the software under observation and control. Beyond the first-order cybernetics, the software, developers/users, and running environments influence each other and thus create feedback to form more complicated systems. We classify software cybernetics as Software Cybernetics I based on the first-order cybernetics, and as Software Cybernetics II based on the higher order cybernetics. This paper provides a review of the literature on software cybernetics, particularly focusing on the transition from Software Cybernetics I to Software Cybernetics II. The results of the survey indicate that some new research areas such as Internet of Things, big data, cloud computing, cyber-physical systems, and even creative computing are related to Software Cybernetics II. The paper identifies the relationships between the techniques of Software Cybernetics II applied and the new research areas to which they have been applied, formulates research problems and challenges of software cybernetics with the application of principles of Phase II of software cybernetics; identifies and highlights new research trends of software cybernetic for further research

Relationship Between Software Development Team Structure, Ambiguity, Volatility, and Project Failure

Complex environments like the United States Air Force\u27s advanced weapon systems are highly reliant on externally developed software, which is often delivered late, over budget, and with fewer benefits than expected. Grounded in Galbraith\u27s organizational information processing theory, the purpose of this correlational study was to examine the relationship between software development team structure, ambiguity, volatility and software project failure. Participants included 23 members of the Armed Forces Communications and Electronics Association in the southeastern United States who completed 4 project management surveys. Results of multiple regression analysis indicated the model as a whole was able to predict software project failure, F(3,19) = 10.838, p \u3c .001, R2 = 0.631. Software development team structure was the only statistically significant predictor, t = 2.762, p = .012. Implications for positive social change include the potential for software development company owners and military leaders to understand the factors that influence software project success and to develop strategies to enhance software development team structure