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Agile principles have been widely used in software development team practice since the creation of the Agile Manifesto. Studies have examined variables related to agile principles without systematically considering the relationships among key team, agile methodology, and process variables underlying the agile principles and how these variables jointly influence the achievement of software development agility. In this study, the authors tested a team/methodology–process–agility model that links team variables (team autonomy and team competence) and methodological variable (iterative development) to process variables (communication and collaborative decision-making), which are in turn linked to software development agility (ability to sense, respond and learn).

Survey data from one hundred and sixty software development professionals were analyzed using structural equation modeling methods.

The results support the team/methodology–process–agility model. Process variables (communication and collaborative decision-making) mediated the effects of team (autonomy and competence) and methodological (iterative development) variables on software development agility. In addition, team, methodology and process variables had different effects on the three dimensions of software development agility.

The results contribute to the literature on organizational IT management by establishing a team/methodology–process–agility model that can serve as a basis for developing a core theoretical foundation underlying agile principles and practices. The results also have practical implications for organizations in understanding and managing holistically the different roles that agile methodological, team and process factors play in achieving software development agility.

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.

This paper aims to close the gap between the generic concept of knowledge activities (KAs) and implementing them in the context of software engineering organisations concentrating on the non-technical aspects, such as team organisation and practices.

This qualitative research used a questionnaire with practitioners such as software developers and team leads who were asked to provide feedback on a set of team practices and measures typically used in software engineering projects and assess their relation to the activities of acquiring, codifying, storing, maintaining, transferring and creating knowledge. The obtained results were analysed using frequency analysis and further descriptive statistics yielding a matrix linking the investigated team practices and measures to KAs.

Team practices and measures commonly applied in software engineering can be facilitated to trigger particular KAs. While most of these team practices and measures originate from agile methods, they are not restricted to these. A purposeful composition can help in assembling a balanced set of KAs aimed at fostering given knowledge goals in software engineering organisations.

By bridging the communication and terminology gap between knowledge management research and software engineering practitioners, this work lays the foundation for assessing software teams’ knowledge profiles more easily and creating prerequisites for implementing knowledge management by facilitating common practices and measures often already part of their daily work. Hence, overhead can be avoided when implementing knowledge management.

To the best of the authors’ knowledge, this is the first study investigating application and relevance of KAs in the software industry by linking them to practices and measures well-accepted in software engineering, thus providing the necessary vocabulary for the implementation of knowledge management in software development teams.

Agile methods are increasingly being applied in the contexts of innovation beyond traditional information technology (IT) and physical product development projects, such as when process improvements are being implemented. Nevertheless, this phenomenon is still recent and little addressed in the literature, with few descriptions of empirical cases. This study aims to address this gap.

This multiple case study aims to present and discuss the application of Agile practices embedded in large companies’ innovation value chains, focusing on improvements of business processes. The following research question is pursued: How are large companies applying elements of Agile methods to their innovation processes when implementing incremental improvements in their operational processes? Based on the idea that the Agile-Stage-Gate model is an alternative to this challenge, this study investigates the application of this hybrid model in two large Brazilian companies by presenting their idiosyncrasies, lessons learned, adaptations, challenges and benefits.

Overall, it was observed that the experience with the application of the Agile-Stage-Gate model is positive for these companies, with better customer engagement, easier project control and increased productivity of the project team.

For those aiming to implement the Agile-Stage-Gate model, this paper identifies the main adaptations made in order to combine the purist approaches and critical success factors for its implementation.

This study aims to investigate the effects of organizational culture factors on the selection of software process development models and develops a conceptual model for selecting and adopting process development models with an organizational culture approach, using 12 criteria and their sub-criteria defined in Fey and Denison’s model (12 criteria).

The research hypotheses were investigated using statistical analysis, and then the criteria and sub-criteria were selected based on Fey and Denison’s model and the experts’ viewpoints. Afterward, the organizational culture of the selected company was measured using the data from 2016 and 2017, based on Fey and Denison’s questionnaire. Due to the correlation between the criteria, using the decision-making trial and evaluation technique, the correlation between sub-criteria were determined, and by analytical network process method and using Super-Decision software, the process development model was preferred to the 12 common models in information systems development.

Results indicated a significant and positive effect of organizational culture factors (except the core values factor) on the selection of development models. Also, by changing the value of organizational culture, the selected process development model changed either. Sensitivity analysis performed on the sub-criteria implied that by changing and improving some sub-criteria, the organization will be ready and willing to use the agile or risk-based models such as spiral and win-win models. Concerning units where the mentioned indicators were at moderate and low limits, models such as waterfall, V-shaped and incremental worked more appropriately.

While many studies were performed in comparing development models and investigating their strengths and weaknesses, and the impact of organizational culture on the success of information technology projects, literature indicated that the impact of organizational sub-culture prevailing in the selection of development process models has not been investigated. In this study, new factors and indicators were addressed affecting the selection of development models with a focus on organizational culture. Correlation among the factors and indicators was also investigated and, finally, a conceptual model was proposed for proper adoption of the models and methodologies of system development.

The objective of this chapter is to identify the key characteristics of Global Services businesses that will thrive and achieve success in the future. These factors are integrated into three main pillars, which we refer to as the Triple-Win. The first and most obvious pillar is technology as a tool. The second pillar is the design and sustainability of the business model, without which the previous factor would be merely a cost and not an investment. And last but not the least, there is the purpose which gives meaning to the proposal, focusing on the human being and their environment. The DIDPAGA business model sits at the intersection of these three elements.

This study seeks to illuminate the managerial tensions inherent in implementing scaled agile (on the organizational, top management, middle management and team levels) and to frame these challenges within the broader context of project management.

The study adopts a grounded theory approach and delves into a qualitative dataset sourced from 34 interviews with subject matter experts actively engaged in scaling agile initiatives within large organizations spanning various industries. Additionally, the data have been enriched through a comprehensive literature review of the existing body of knowledge on scaling agile.

As a result of our investigation, we propose a framework of managerial tensions in scaling agile in large corporate settings and a series of research propositions and questions that may contribute significantly to the body of knowledge surrounding the phenomenon of “deprojectification” and propose agenda for the future studies in the field of project management.

The study also carries significant managerial implications. Firstly, based on the insights from the practice of scaling agile in large corporate setting, management can build awareness of the challenges inherent of transitioning to agile practices. This may help to anticipate the possible problems and proactively develop strategies how to address them. Secondly, management can be instructed about contingencies inherent in scaling agile, along with the potential disfunctions and side effects (unintended outcomes) that may emerge during the transition process. Thirdly, project management practitioners can gain insights on how scaling agile may cause shifts in the approach to managing projects, project team management and competencies that need to be developed to cope with environments where various approaches to managing projects coexist.

These insights can aid in the agile transition process, beginning with directing managerial attention toward contextual factors and progressing through potential challenges at the organizational, top management, middle management and team levels. Furthermore, the study highlights possible dysfunctionalities and side effects of scaling agile, shedding light on the “dark side” of agile.

The study contributes to the expansion of the empirical database on the implementation of agile practices in large organizational settings. It plays a role in defining and delineating the phenomenon of scaling agile within the context of project management and outlines a research agenda for future project management studies. Additionally, our study adds to the ongoing discourse surrounding the “deprojectification” effect that can occur during the scaling of agile. Lastly, it establishes connections between project management and software development literature regarding the implementation of agile at scale.

This article explores how the social media usage affect team creative performance via transactive memory system, knowledge interaction and expertise coordination.

The study is based on the perspective of transaction memory system and expertise coordination theory. A research model was constructed and tested, involving 289 individuals from 67 distributed agile software development teams.

The results indicate that social media usage is positively correlated with transactive memory system, and social media usage and transactive memory system have positive relations to knowledge interaction and expertise coordination. Moreover, this analysis shows that knowledge interaction has a positive relationship with expertise coordination, and expertise coordination positively affects team creative performance. However, knowledge interaction has no direct relationship on team creative performance, and its indirect impact on team creative performance was fully mediated by expertise coordination. This research shows that social media usage by distributed agile software development teams can support the development of transactive memory system and promote expertise coordination. In addition, knowledge interaction alone is not enough, and expertise coordination must be achieved to increase team creative performance.

First, this paper explores the mechanism of transactive memory system in distributed Agile Software Development teams from the perspective of social media, which is different from the previous information processing theory framework that confined transactive memory system to the cognitive aspects of knowledge coding, storage and retrieval. Second, this research focuses on the knowledge interaction and expertise coordination formed by team members in the process of communication in the context of social media usage, which confirms the crucial roles of social media usage and transactive memory system in team knowledge management and team creative performance. Then, this research also shows that the development of transactive memory system in the team is indeed an important factor to promote knowledge interaction and professional expertise coordination.

Digital transformations of business processes are on the rise and the result is a need for a better understanding of how the elements of intellectual capital (IC) play a role in achieving successful digital project outcomes. New structural capital in the form of digital technologies must be identified and understood. Evolving skills of human capital in assimilating digital elements must also be considered, while collaboration within the development process involving relational capital provides a critical integration among these IC elements. This study illustrates the importance of identifying and managing the integration of IC components within an agile project management framework that are essential to achieving success for a digital initiative. More specifically, this study describes the process by which a multinational technology-based products company successfully developed a dynamic decision support platform utilizing an agile approach to guide a project management team to better manage the company's operations.

This study focuses on a case analysis approach of a multinational commercial and consumer products company. The paper presents existing research on the evolving state of project management for digital initiatives and focuses on agile methods. This study then delves into the case analysis that illustrates how IC played an integral role in the company successfully developing effective decision support involving an interactive dashboard using agile Project Management (PM), which enabled the project management team to better manage resources.

An examination at the case level illustrates that effective management and integration of IC has positive effects on project outcomes. While a balanced approach is evident as a requirement, the unique characteristics of the agile project management approach entails greater emphasis on select elements to adapt to a more dynamic development process.

This work depicts the complexities in providing analytic-based decision support in an agile/flexible project management scenario. This work adds to existing research by illustrating elements within IC categories and the elements' interdependencies that play an essential role in achieving success in this more flexible project environment.

Artificial intelligence (AI) is the most progressive commodity among current information system applications. In-house development and sales of beneficial products are difficult for many software development and service companies (SDSCs). SDSCs have some implicit concerns about implementing AI software development due to the complexity of AI technology; they require an evaluation framework to avoid development failure. To fill the void, this study identified the factors influencing SDSCs when developing AI software development.

Based on complex adaptive systems theory, three aspects were developed as the main factors of hierarchy, namely, employees' capabilities, environmental resources and team capabilities. Fuzzy analytic hierarchy process (FAHP) was used to assess the SDSCs' attitude. Based on SDSCs, attitudes toward implementing AI software projects were collected to calculate the hierarchy of factors.

The outcome of FAHP is used as understanding the key factors of SDSCs for selecting an AI software project, toward the improvement of overall project planning. Employees' stress resistance was considered as a priority for the project, although professional AI skills and resources were also important.

This study suggested three variables developed using complex adaptive systems. This study contributes to a better understanding of the critical aspects of developing AI software projects in SDSCs. The study's findings have practical and academic implications for SDSCs and subsequent academic development, broadening the scope of AI software development research.