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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.

Drawing on goal-setting theory and team effectiveness theory, the study aims to examine the impact of agile taskwork and agile teamwork on team performance. In addition, it investigates the mediating effect of project commitment on the impact of agile taskwork and agile teamwork on team performance. Furthermore, the study also tests the moderating role of career level on the impact of agile taskwork and agile teamwork on team performance.

Survey data were collected from 563 employees working in 290 information technology (IT) companies in India using a self-reporting structured questionnaire. Partial least squares path modeling was used to test the hypothesized model, and the Process macro was used to test the moderating effect.

The results show that agile taskwork and agile teamwork positively affect team performance and project commitment, and project commitment positively impacts team performance. Furthermore, project commitment fully mediates the relationship between agile taskwork and team performance and partially mediates the relationship between agile teamwork and team performance. Furthermore, the career level negatively moderates the impact of agile taskwork and agile teamwork on team performance.

The study shows the importance of agile work practices and project commitment to enhance team performance. Thus, the study provides managers with two strategies to improve their team performance.

There is a scarcity of research examining the distinct effects of agile taskwork and agile teamwork on team performance and the mediating role of project commitment in these relationships. Furthermore, as per the empirical evidence, no previous research has empirically examined the moderating role of career level in the agile taskwork-team performance and agile teamwork-team performance relationships.

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 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.

This chapter of the book aims to achieve sustainability and productivity in light of the interaction between managers and engineers in a lean and agile supply chain management system in today’s organizations. The main innovation of this chapter is the use of the balanced scorecard (BSC) model and fuzzy analysis network process (FANP) to create a suitable platform for the realization of this interaction between managers and engineers and to identify exactly which expert system is ideal for the main purpose. Indeed, this chapter introduces its readers to the application of strategic management tools such as the BSC accompanied by FANP in the elements of supply chain management where data analysis of lean and agile networks in supply chain management can create a competitive advantage in the organization.

The aim of this paper is to explore the possibility of using the Define-Measure-Analyze-Improve-Control (DMAIC) cycle, process mining (PM) and multi-criteria decision methods in an integrated way so that these three elements combined result in a methodology called the Agile DMAIC cycle, which brings more agility and reliability in the execution of the Six Sigma process.

The approach taken by the authors in this study was to analyze the studies arising from this union of concepts and to focus on using PM tools where appropriate to accelerate the DMAIC cycle by improving the first two steps, and to test using the AHP as a decision-making process, to bring more excellent reliability in the definition of indicators.

It was indicated that there was a gain with acquiring indicators and process maps generated by PM. And through the AHP, there was a greater accuracy in determining the importance of the indicators.

Through the results and findings of this study, more organizations can understand the potential of integrating Six Sigma and PM. It was just developed for the first two steps of the DMAIC cycle, and it is also a replicable method for any Six Sigma project where data acquisition through mining is possible.

The authors develop a fully applicable and understandable methodology which can be replicated in other settings and expanded in future research.

The purpose of this study is to examine the critical failure factors (CFFs) linked to various types of process improvement (PI) projects such as Kaizen, Lean, Six Sigma, Lean Six Sigma and Agile. Proposing a mitigation framework accordingly is also an aim of this study.

This research undertakes a systematic literature review of 49 papers that were relevant to the scope of the study and that were published in four prominent databases, including Google Scholar, Scopus, Web of Science and EBSCO.

Further analysis identifies 39 factors that contribute to the failure of PI projects. Among these factors, significant emphasis is placed on issues such as “resistance to cultural change,” “insufficient support from top management,” “inadequate training and education,” “poor communication” and “lack of resources,” as primary causes of PI project failures. To address and overcome the PI project failures, the authors propose a framework for failure mitigation based on change management models. The authors present future research directions that aim to enhance both the theoretical understanding and practical aspects of PI project failures.

Through this study, researchers and project managers can benefit from well-structured guidelines and invaluable insights that will help them identify and address potential failures, leading to successful implementation and sustainable improvements within organizations.

To the best of the author’s knowledge, this paper is the first study of its kind to examine the CFFs of five PI methodologies and introduces a novel approach derived from change management theory as a solution to minimize the risk associated with PI failure.

This study delves into the dynamics between Agile Response to Change (AR), Adaptive Scoping (AS), Stakeholder Engagement (SE) and Project Performance (PP), with a special focus on the moderating influence of Project Complexity (PC). The research, grounded in a thorough literature review, identifies critical gaps in these areas and examines the extent to which PC moderates the effects of AR, AS and SE on PP, offering new perspectives for managing complex projects.

The research develops a conceptual model based on a critical analysis of existing literature. A comprehensive questionnaire was designed, incorporating 28 items to measure AR, AS, SE, PP and PC. Data was collected from 136 project managers across various industries, and the responses were analysed using structural equation modelling (SEM) to explore the complex interplay between these variables.

The analysis revealed that internal AR (ARint) significantly enhances both quantitative (PPqt) and qualitative aspects of PP (PPql). AS and SE were found to positively influence PPql, but their impact on PPqt was not significant. Interestingly, PC was observed to negatively moderate the relationship between ARint and PPql, while its moderating effect on the relationship between ARint and PPql was not significant. The study also notes that PC does not significantly alter the positive correlations between AS, SE and PPql.

This research contributes to the existing body of knowledge by elucidating the relationships between ARint, AS, SE and different dimensions of PP. It uniquely explores the role of PC as a moderating variable in these relationships, offering valuable insights for practitioners and researchers in the field of complex project management.

Supply chain management (SCM)-embedded valuable resources, such as capital, raw-materials, products, partners, customers and finished inventories, where the evaluation of environmental texture and flexibilities are needed to perceive sustainability. The present study aims to identify and evaluate the directory of green and agile (G-A) attributes based on decision support framework (DSF) for identifying dominating measures in SCM.

DSF is developed by exploiting generalized interval valued trapezoidal fuzzy numbers (GIVTFNs). Two technical approaches, i.e. degree of similarity approach (DSA) and distance approach (DA) under the extent boundaries of GIVTFNs, are implicated for data analytics and for recognizing constructive G-A measures based on comparative study for robust decision. A fuzzy-based performance indicator, i.e. fuzzy performance important index (FPII), is presented to enumerate the weak and strong G-A characteristics to manage knowledge risks in allied business environment.

The modeling is illustrated from the insights of decision-makers for augmenting business value based on cognitive identification of measures, where the best performance score is identified by the “sustainable packaging” under the traits of green supply chain management (GSCM). “The use of Web-based applications” under the traits of agile supply chain management (ASCM) and “Outsourcing flexibility” under traits of ASCM is found as the second and third most significant performance characteristics for business sustainability. Additionally, the “Reutilization (recycling) and reprocessing” under GSCM in manufacturing and “Responsiveness and speed toward customers needs” under ASCM are found difficult in attainment.

The G-A evaluation will assist in attaining performance excellence in day-to-day operations and overall functioning. The outcomes will help executives to plan strategic objectives and attaining success.

To reinforce the capabilities of SCM, wide extent of G-A dimensions are presented, concept of FPII is reported to manage knowledge risks based on identification of strong attributes and two technical approaches, i.e. DSA and DA under GIVTFNs are presented for attaining robust decision and directing managerial decision-making process.

This study aims to emphasize the integration of lean start-up and design thinking approaches and investigate how they may be used together.

The report uses a systematic literature review methodology to analyze and summarize previous research on combining lean start-up and design thinking. Inferences were discovered and analyzed after relevant publications were chosen based on predetermined inclusion criteria.

The research shows that combining lean start-up and design thinking significantly impacts entrepreneurship. Start-ups can efficiently uncover consumer needs, reduce risks and improve their product or service offerings by combining the client-centricity of design thinking with the iterative and data-driven concepts of lean start-up. This integration promotes an innovative culture, gives teams the freedom to try new things and learn from mistakes and raises the possibility of start-up success.

The dependence on pre-existing literature, which might cover only some potential uses and circumstances, is a weakness of this research. It is advised that more empirical research be conducted to determine the precise circumstances in which the integrated strategy performs best. Future studies should also explore the difficulties and drawbacks of using these approaches to offer suggestions for overcoming them and maximizing their advantages.

The findings have significant ramifications for business owners and other professionals working in the start-up environment. The combination of lean start-up and design thinking emphasizes the relevance of early customer interaction and empathy-driven design. To foster creativity and hasten the expansion of start-ups, practitioners are urged to create a comprehensive strategy that integrates the advantages of both techniques. Through this integration, business owners may develop solutions that appeal to their target market, increasing adoption rates and market competitiveness.

This study is interesting in comparing lean start-up and design thinking, emphasizing the overlaps and benefits of their application to entrepreneurship. This study discusses successful start-up methods by offering suggestions for future research and practice. It also provides a basis for further developing and adopting the integrated approach.