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This study aims to examine the enablers of productivity of enterprise-level Agile development process using modified total interpretative structural modeling (TISM). The two main objectives of the current study are to determine the variables influencing enterprise-level agile development productivity and to develop modified TISM for the corresponding components.

To identify enablers of the productivity of enterprise-level agile software development process a literature review and opinions of domain experts were collected. A hierarchical relationship among variables that show direct and indirect influence is created using the modified TISM (M-TISM) technique with Cross Impact Matrix-Multiplication Applied to Classification analysis. This study examined and analyzed the relationships between the determinants within the enterprise using a M-TISM technique.

With the literature review, the study could identify ten enabling factors of the productivity of Agile development process at the enterprise level. Results depict that program increment (PI) planning and scalable backlog management, continuous integration and continuous delivery (CI/CD), agile release trains (ART), agile work culture, delivery excellence, lean and DevOps practices, value stream mapping (VMS), team skills and expertise, collaborative culture, agile coaching, customer engagement have an impact on the productivity of enterprise-level Agile development process. The results show that team collaboration, agile ways of working and customer engagement have a greater impact on productivity improvement for enterprise-level Agile development process.

The developed model is useful for organizations employing scaled Agile development processes in software development. This study provides a recommended listing of key enablers, that may enable productivity improvements in the Agile development process at the enterprise level. Strategists should focus on team collaboration and Agile project management. This study offers a modified TISM model to academicians to help them understand the effects of numerous variables on maintaining the productivity of an enterprise-level Agile. The identified characteristics and their hierarchical structure can help project managers during the execution of Agile projects at the enterprise level, more effectively, increasing their success and productivity.

The study addresses the gap in the literature by interpretative relationships between the identified enabling factors. The model validation is carried out by a panel of nine experts from several information technology organizations deploying Agile software development at the enterprise level. This unique method broadens the knowledge base in Agile software development at scale and provides project managers and practitioners with a practical foundation.

The central task is to define the ties, existing between economic dimensions, which can be expressed in specific relations that require special attention during projecting to ensure they are not disrupted. The development of a computer‐based mathematical and economic model makes it possible to constantly monitor the condition of the entire economy of a given region, both from a global aspect, as well as by its individual sectors of activities.

Economics employs a number of scientific disciplines and their methods, making this approach both multidisciplinary and interdisciplinary. Unlike the variables defined in the model–variables such as domestic product, the volume of fixed funds, the volume of new investment and employment, which change from year to year – the model parameters are considered constants for the entire period to which the model is applied. The parameter estimation indicates the extent to which the defined model is acceptable as a model of future regional economic and tourism growth.

Providing the trends of past are unacceptable in the future period, the author proposes the use of structured policies, above all in the field of investments, to guide development in the desired direction. The author has addressed this particular issue through the example of a specific tourist region, and has tested and designed a development model not only for the regional economic system, but also for its tourism subsystem.

Although they are suited to certain types of decisions, these methods have shown to be inadequate for other types, long‐term strategic decisions in particular, which require so‐called intuitive methods.

Optimal decision‐making in systems' operations is not possible without predictions pertaining to future economic development. The answers to numerous questions in estimating development factors are being provided by new methods, which seek to incorporate and assert an interdisciplinary approach, that is, a systematic approach in preparing decisions.

This methodology can be used in combination with “classical” methods of research, that will can help to recommend optimum development strategies for regional economic development.

This study aims to understand how practitioners use their insights in software development models to share experiences within and between organizations.

This is a qualitative study of practitioners in software development projects, in large-, medium- or small-size businesses. It analyzes interview material in three-step iterations to understand reflexive practice when using software development models.

The study shows how work processes are based on team members’ experiences and common views. This study highlights the challenges of organizational learning in system development projects. Current practice is unreflective, habitual and lacks systematic ways to address recurring problems and share information within and between organizations. Learning is episodic and sporadic. Knowledge from previous experience is individual not organizational.

Software development teams and organizations tend to learn about, and adopt, software development models episodically. This research expands understanding of how organizational learning takes place within and between organizations with practitioners who participate in teams. Learnings show the potential for further research to determine how new curriculums might be formed for teaching software development model improvements.

In a variety of domains, teams represent the main mechanism for dealing with change, complexity, and uncertainty in organizations. Consequently, teams need to be able to adapt and effectively use shared and complementary cognitive processing while collaborating to deal with these challenges.

A conceptual review is provided that addresses this type of complex collaborative cognition via discussion of macrocognition and the processes contributing to effective team problem-solving.

Despite extensive research on problem-solving, research and theories regarding how problem-solving changes over time as teams develop is missing. With this review, we extend research on team problem-solving and team development through integration of existing theory and concepts from the team literature.

This review provides a theoretical foundation for understanding and studying the developmental dynamic of team problem-solving.

A team problem-solving development model is described which outlines the degree to which the primary elements of team development are likely to affect macrocognitive processes within problem-solving phases. A set of propositions is offered in order to guide research on team development in collaborative problem-solving.

The purpose of this study is to estimate an empirical model for new office space development starts, based on the theoretical treatment of urban growth. The study introduces a new parameter, namely, office space-usage pattern, to the office space development equation and tests whether developers respond to non-price measures in deciding to commence new developments.

The study first introduces a co-integration approach based on an error correction model to test for long-run relations and short-run dynamics of new office space development. A multivariate regression model is then introduced to identify significant determinants that influence office development starts. The study uses annual data over a time span of 30 years.

Estimated results provide strong evidence that the newly introduced parameter exerts a positive impact on new office space development. It suggests that if the average floor space per employee changes by one percentage point, new office development starts would change by 1.5 percentage point, indicating even a marginal change in floor-space usage per employee (SPE) would have a significant impact on new office space development. Empirical estimates also suggest a strong response of office development starts to the lagged land supply and office space stock.

The paper raises the concern about the importance of non-price measures of the supply-side of the office market. There is scope to address the research questions using better data sets. It is also possible to model the supply adjustment process more dynamically in an error correction framework.

The findings would suggest that non-price measures, such as space-usage pattern, need to be taken into account when planning and estimating future office space needs. This finding provides valuable insight for our current knowledge on factors affecting new office supply.

This is the first study to introduce office floor space usage as a determinant of office development starts in an urban growth conceptual framework for the Hong Kong office market.

The purpose of this paper is to find good values of onsite-offshore team strength; number of hours of communication between business users and onsite team and between onsite and offshore team so as to reduce project cost and improve schedule in a global software development (GSD) environment for software development project.

This study employs system dynamics simulation approach to study software project characteristics in both co-located and distributed development environments. The authors consulted 14 experts from Indian software outsourcing industry during our model construction and validation.

The study results show that there is a drop in overall team productivity in outsourcing environment by considering the offshore options. But the project cost can be reduced by employing the offshore team for coding and testing work only with minimal training for imparting business knowledge. The research results show that there is a potential to save project cost by being flexible in project schedule.

The implication of the study is that the project management team should be careful not to keep high percentage of manpower at offshore location in distributed software environment. A large offshore team can increase project cost and schedule due to higher training overhead, lower productivity and higher error proneness. In GSD, the management effort should be to keep requirement analysis and design work at onsite location and involves the offshore team in coding and testing work.

The software project manager can use the model results to divide the software team between onsite and offshore location during various phases of software development in distributed environment.

The study is novel as there is little attempt at finding the team distribution between onsite and offshore location in GSD environment.

Motivated with the ever growing number of bibliometric trend extrapolation studies, the purpose of this paper is to demonstrate through two technologies how the selection of an upper limit of growth affects the correlation and causality of technology development measured with bibliometric data.

The paper uses Gompertz and Fisher-Pry curves to model the technological development of white light emitting diodes and flash memory, and show with extrapolation results from several bibliometric sources how a typical bias is caused in trend extrapolations.

The paper shows how drastic an effect the decision to set an upper bound has on trend extrapolations, to be used as a reference for applications. The paper recommends carefully examining the interconnection of actual development and bibliometric activity.

Despite increasing interest in modelling technological data using this method, reports rarely discuss basic assumptions and their effects on outcomes. Since trend extrapolations are applied more widely in different disciplines, the basic limitations of methods should be explicitly expressed.

The purpose of this research is to investigate sustainable strategies for skills development that is specific to the youth of South Africa. International and South African data are statistically analysed and quantified to provide inputs for the systems dynamics (SD)-based predictive skills model. The skills model simulates the impact of barriers and drivers on youth skills development towards identification of focus areas for improvement.

The research adopts a mixed-methods approach. The study begins with an explorative literature study on skills development, with the findings applied in developing (1) South African specific research instruments for small, medium and micro enterprises (SMMEs) and skills programme grant recipients and (2) a conceptual framework of the SD predictive skills model. The responses to the South African specific instruments are analysed via confirmatory factor analysis (CFA), which quantifies the input coefficients to the system dynamics model. To quantify the global inputs for the SD model, an in-depth literature review of the global skills development initiatives is conducted. The SD model output on skills, for the South African inputs, is comparatively evaluated against global inputs.

The paper details the results of the literature analysis, instrument analyses, CFA and SD model. The instrument results rank experience, skills and interactions with experts and work-based learning as most important. South African and global learners identify networking as the primary medium for identifying training and employment opportunities. South African and global learners also identify qualifications and work-based experience as key to finding employment. The quantified results of the SA and global analysis are used as inputs in the SD model to deliver a forecasting tool. The SD model finds that the global data provide for better development of the skills base than the South African inputs. The key focus areas identified for improvement in South Africa include networking, work-based experience and a reduction in administrative requirements.

The research's originality resides in the ability to predict the impact of drivers and barriers on skills development. This research sought to transform qualitative global and South African inputs into a consolidated, predictive systems-based model. The SD model can be adopted as an indicator of drivers and barriers focused towards the optimisation of skills development.

System dynamics is a whole-system modelling and learning approach, useful for tackling non-linear problems, such as sustainable urban development. The purpose of this paper is to review system dynamics applications in the simulation of sustainable urban development over a period from 2005 to 2017.

The analysis reveals that the number of applications of system dynamics modelling in the area of urban sustainable development increased in the analysed period. Research has changed its focus from the modelling of environmental problems to more complex models, portraying the multidimensional socio-economic processes that have an impact on the sustainability of urban development. Analysed case studies most often use the behaviour reproduction test for model validation, but without a unified approach. In most cases, modelling has been done in China, Germany and the USA, while urban development in the Eastern European countries, Africa and Latin America has not often been investigated. This paper indicates the knowledge gaps and suggests future research directions.

Papers that report the use of system dynamics modelling reveal a wide range of applications in urban sustainability. The analysis shows significant emphasis on environmental problems, while the interest for modelling social problems has been increasing during the last several years. Most of the modelled problems examine the sustainability of resources (land, water) and waste management, which are used for insights into the reasons for the system behaviour, forecasting future behaviour and policy testing.

The presented models were developed in most cases for the purpose of understanding the phenomena examined, as well as the future use of the models in policy planning. This brings us back to the need for greater stakeholder involvement, not only in the initial phase, but also during the whole modelling process, which could increase understanding, use and ownership of the models in the future, and thus increase their practical application.