One crucial aspect of modern supply chains is that they operate not just in dynamic environments but in rapidly changing, fluid ones. Change is relentless, and adjustments must be made instantly once a change is addressed. The continuous adjustment pressures extend beyond dynamics and best describe modern supply chains. That’s why it is essential to incorporate all the chain’s changes, and one recent approach to address this behaviour is supply chain stress testing. The primary objective is to employ simulation techniques to develop data-driven models that enhance supply chain resilience. Businesses can better adapt to changes by preparing for disruptions through simulation. Preparing for disruptions requires understanding their characteristics, like how long they last, how often they occur, and how severe they are. This study examines how higher disruption frequency impacts supply chain performance and resilience. Using discrete-event simulation, we analysed twelve different frequency scenarios. The model was tested on a transformers manufacturer serving clients throughout Africa and the Middle East. The findings show specific disruption frequencies at which service levels drop significantly, and backlogs become persistent. Additionally, service degradation at higher frequencies is non-linear, with all areas experiencing over 50% reductions that do not improve over two years. These findings highlight the frequency of disruptions as a driver of supply chain non‑viability.

1. There has been a very significant number of paper submissions to EJIS in recent years on the topic of artificial intelligence (AI), with many of these focusing in some way on responsibility. Thi...

Although the COVID-19 pandemic is behind us, the seminal challenge for agile teams has not gone away, as “Work-From-Home (WFH) is here to stay”. Despite a wealth of literature documenting the challenges of applying agile methods in remote environments, practical guidance for overcoming these challenges remains limited. Furthermore, systematic meta-guidelines to help practitioners develop tailored, context-specific solutions are largely absent. This article reports on an Action Research project conducted at S&P Global 18 months after the company’s transition to a WFH model. The project aimed to evaluate existing adaptations to remote work, identify persistent issues, and develop strategies to address them. Our investigation revealed that while ad-hoc solutions — such as virtualizing Scrum ceremonies and shifting informal in-person conversations to Slack channels — enabled work continuity during the pandemic, they proved insufficient for tackling more complex challenges. Intriguingly, only two ongoing issues stemmed from misalignments between Scrum and remote settings, while the remainder were rooted in flawed Scrum implementation. With our guidance, the participating team not only rediscovered the “Inspect and Adapt” principle but also mastered a systematic approach to method tailoring, enabling them to devise measures that effectively resolved most of their issues. Our study reinforces prior findings indicating the applicability of Scrum beyond its traditional “home ground”, while also highlighting the need for remote teams to exhibit even greater discipline in adhering to the Scrum framework to navigate the additional challenges of remote work. We also observed a heightened necessity for more comprehensive documentation in remote settings to compensate for limited immediate access to colleague assistance, which consequently restricts knowledge sharing. Finally, the structured approach we employed offers valuable guidance for software companies seeking to identify and address operational inefficiencies in both remote and hybrid work environments. • Most issues stem from flawed Scrum implementation, not its mismatch with remote work. • Remote Scrum reveals hidden dysfunctions not apparent in traditional office settings. • Remote teams need more strategic documentation to enhance knowledge sharing. • Tailored Scrum with collaboration tools excels remotely, defying collocation assumptions. • Action Research guides practitioners to systematically refine their practices.

• Synthesizes empirical studies on responsible AI and the underlying principles. • Differentiates between principles and governance of AI in a responsible way. • Analyzes through a critical lens existing studies and uncovers underlying assumptions. • Defines the notion of responsible AI governance based on the synthesis and critical reflection. • Develops a research agenda and identifies important areas for future research within the IS domain. The widespread and rapid diffusion of artificial intelligence (AI) into all types of organizational activities necessitates the ethical and responsible deployment of these technologies. Various national and international policies, regulations, and guidelines aim to address this issue, and several organizations have developed frameworks detailing the principles of responsible AI. Nevertheless, the understanding of how such principles can be operationalized in designing, executing, monitoring, and evaluating AI applications is limited. The literature is disparate and lacks cohesion, clarity, and, in some cases, depth. Subsequently, this scoping review aims to synthesize and critically reflect on the research on responsible AI. Based on this synthesis, we developed a conceptual framework for responsible AI governance (defined through structural, relational, and procedural practices), its antecedents, and its effects. The framework serves as the foundation for developing an agenda for future research and critically reflects on the notion of responsible AI governance.

Abstract The World Health Organization (WHO) highlights the significant threat that unsustainably long working hours pose to our mental and physical well-being. Aligning with this concern, an Agile principle emphasizes that “Agile processes promote sustainable development.” However, previous work in 2023 debunked this notion of inherent stability in Agile systems, such as the Scrum and Kanban frameworks. In this study, we aim to analyse the relationship between system stability and the tendency of teams to work outside reasonable office hours. We inspect 295 historic Agile projects completed in intive, a software development company. We assess the percentage of late-night, early-morning, or weekend hours where a Product Backlog Item (PBI) was created or resolved and compare this percentage of Unsustainable Hours metric to the Stability Metric and the number of Inventory Days remaining. The analysis showed that almost no correlation exists between the Unsustainable Hours worked and either the system stability or outstanding inventory. These findings indicate that, while working unconventional and potentially excessive hours is a concern, it does not appear to be linked to the stability of Agile systems. This highlights the need for a deeper understanding of individual and team motivations to foster long-term sustainable work practices.

Qualitative surveys are emerging as a popular research method in software engineering (SE), particularly as many aspects of the field are increasingly socio-technical and thus concerned with the subtle, social, and often ambiguous issues that are not amenable to a simple quantitative survey. While many argue that qualitative surveys play a vital role amongst the diverse range of methods employed in SE there are a number of shortcomings that inhibits its use and value. First there is a lack of clarity as to what defines a qualitative survey and what features differentiate it from other methods. There is an absence of a clear set of principles and guidelines for its execution, and what does exist is very inconsistent and sometimes contradictory. These issues undermine the perceived reliability and rigour of this method. Researchers are unsure about how to ensure reliability and rigour when designing qualitative surveys and reviewers are unsure how these should be evaluated. In this paper, we present a systematic mapping study to identify how qualitative surveys have been employed in SE research to date. This paper proposes a set of principles, based on a multidisciplinary review of qualitative surveys and capturing some of the commonalities of the diffuse approaches found. These principles can be used by researchers when choosing whether to do a qualitative survey or not. They can then be used to design their study. The principles can also be used by editors and reviewers to judge the quality and rigour of qualitative surveys. It is hoped that this will result in more widespread use of the method and also more effective and evidence-based reviews of studies that use these methods in the future.

Abstract Agile systems, like the Kanban and Scrum frameworks, are built on assumptions of sustainability and stability, however, there is little empirical evidence on whether such systems are stable in practice or not. Therefore, in this study we aim to inspect the stability of Agile systems by leveraging the concept of stability described in Queueing Theory. We define a novel metric, the Stability Metric, as a way of assessing queueing systems, especially Agile systems. We inspect 926 Jira projects in 14 organizations with over 1.6 million product backlog items using this metric. The analysis showed that 72.89% of these Jira projects were not stable and stable systems, on average, had product backlog sizes 10 times shorter than unstable ones. These results suggest that while the goal of Agile is to create a sustainable, stable way of working, this is not guaranteed, and a better understanding of systems and queues may be required to help design, create, coach, and maintain optimal Agile systems.

Abstract To satisfy the need for analytical data in the development of digital services, many organizations use data warehouse, and, more recently, data lake architectures. These architectures have traditionally been accompanied by centralized organizational models, where a single team or department has been responsible for gathering, transforming, and giving access to analytical data. However, such centralized models presuppose stability and are incompatible with agile software development where applications and databases are continuously updated. To achieve more agile forms of data management, some organizations have therefore begun to experiment with distributed data management models such as “data meshes”. Research on this topic is however limited. In this paper, we report findings from a case study of a public sector organization in Norway that has begun the transition from centralized to distributed data management, outlining both the benefits and challenges of a distributed approach.

Crowdfunding projects have been the subject of contrasting narratives. To many, they are the antithesis of predatory bottom-line business ventures, and to others, they are an under-regulated vehicle for immature, or unscrupulous project owners to exploit inexperienced and vulnerable investors. These differences are significant, given many use crowdfunding to build public awareness and project a positive image. We use the myth of Prometheus – the Greek god associated with “defiant progress” and technological advancement – as a sensitising lens to build a set of competing, dialectic archetypes. We then apply these archetypes through a Hegelian dialectic analysis of three high-profile crowdfunding campaigns. The overarching contribution of the study is that it provides a foundation for discussion of the positive and negative narratives surrounding crowdfunded project owners and explicates the limitations of crowdfunding as an enabler of positive systemic change. The dialectic approach provides a systematic means of identifying the essence of disagreement between narratives. While it may be too early to predict the outcomes for emerging technology-driven initiatives such as crowdfunding, the use of myth offers a sophisticated means to look for “rhyming” phenomena, where the phenomena at play are similar to the grand frailties of humankind throughout history.

Artificial Intelligence (AI) has been argued to offer a myriad of improvements in how we work and live. The notion of AI comprises a wide-ranging set of technologies that allow individuals and organizations to integrate and analyze data and use that insight to improve or automate decision-making. While most attention has been placed on the positive aspects companies realize by the adoption by the adoption and use of AI, there is a growing concern around the negative and unintended consequences of such technologies. In this special issue we have made a call for research papers that help us explore the dark side of AI use. By adopting a dark side lens, we aimed to expand our understanding of how AI should be implemented in practice, and how to minimize or avoid negative outcomes. In this editorial, we build on the notion of responsible AI, to highlight the different ways in which AI can potentially produce unintended consequences, as well as to suggest alternative paths future IS research can follow to improve our knowledge about how to mitigate such occurrences. We further expand on dark side theorizing in order to uncover hidden assumptions of current literature as well as to propose other prominent themes that can guide future IS research on AI adoption and use.

Following the highly pervasive and effective use of agile methods at the team level, many software organisations now wish to replicate this success at the organisational level, adopting large-scale agile methods such as SAFe, Scrum-at-Scale, and others. However, this has proven significantly challenging. An analysis of the extant literature reveals a disparate set of studies across each individual method, with no cross-method comparison based on empirical evidence. This systematic literature review compares the main large-scale agile methods, namely SAFe, LeSS, Scrum-at-Scale, DAD, and the Spotify model. It is the first study to analyse and compare each of the method’s principles, practices, tools, and metrics in a standardised manner. For each method, it presents not just the original method specifications but also all extensions and modifications to each method proposed by subsequent empirical research. It includes in this comparison not just commercial large-scale methods but also those that have been custom-built in organisations such as Nokia, Ericsson, and others. Based on the findings reported in this study, practitioners can make a more informed decision as to which commercial method or method component or, indeed, custom-built method is better suited to their needs. Our study reveals a number of theoretical and practical issues in the current literature, such as an emphasis on the practices of commercial frameworks at the expense of their underlying principles, or indeed any of the custom method. A set of challenges and success factors associated with the use of large-scale agile methods are identified. The study also identifies a number of research gaps to be addressed across methods.

This issue of the European Journal of Information Systems (EJIS) is a special issue on Business Process Management and Digital Innovation. Guest editors Jan Mendling, Brian Pentland, and Jan Recker...

Context Inner source software development (ISSD) has been viewed as an alternative approach in which organisations adopt open source software development (OSSD) practices and exploit its benefits internally. Objective In this paper, we aim to provide an extensive review of current research on ISSD and to establish a research agenda on this domain. Method The review is primarily performed using a systematic literature review protocol. Results We identified, critically evaluated and integrated the findings of 37 primary studies, describing 25 empirical research papers, 10 frameworks/methods, models and tools to support the implementation of inner source, as well as a set of benefits and challenges associated with ISSD. Conclusion This study presents four main contributions. First, the study provides an in-depth review of ISSD to date, i.e. the evolution of research across inner source, contributions of existing research developments, and theories, models and frameworks used to study inner source. Second, our review applies the OSSD approach framework as the lens to analyse ISSD. Third, the review updates the key challenges associated with ISSD from a management perspective. The final contribution is the establishment of a research agenda to advance knowledge on ISSD.

Open Source Software (OSS) mailing lists have become popular targets for mining sentiment and emotions, as they provide a centralized communication hub between the distributed OSS community. Sentiment and emotions within communities can provide insights into how a community responds to certain events, who are the key members and how their behaviours impact the rest of the community. Such insights can inform initiatives aimed at fostering positive interactions between OSS community members, strengthening social ties, and helping the community accomplish its tasks. This poster presents our initial results from sentiment analysis of an OSS mailing list, and answers two key questions: (1) Given that the mailing list is used for peer-review of code, is the community sentiment negative overall? (2) Is community sentiment related to the month of the release cycle?

“Prometheus, teacher in every art, brought the fire that hath proved to mortals a means to mighty ends.”(Aeschylus, 6C B.C.)Technological progress is often measured by increased speed and efficienc...

Open Source software (OSS) has been highly prevalent in both practice and research. Given the value and effectiveness of OSS development to date, practitioners are keen to replicate these practices inside their respective corporations. This application of OSS practices inside the confines of a corporate entity has been coined Inner Source Software (ISS). While ISS presents many benefits, little is known about the opposing tensions that arise as a result of transitioning from a closed to an open software development environment. Such environments are increasingly under pressure to embrace more open and collaborative principles internally, while simultaneously managing operations in a tight and controlled manner. As part of this study, we conducted 20 interviews with international ISS expects across 15 global organisations. We uncover 13 core tensions that arise from the adoption of open principles in closed software practices. Based on these emerging results, we present new insights on the implementation of strategies to overcome competing tensions from openness in software development. We present some recommendations, which also call for fundamentally new research directions.

Given the value and effectiveness of open source software development to date, practitioners are keen to replicate these practices inside their respective corporations. This application of open source practices inside the confines of a corporate entity has been coined inner source software development. However, while organisations have found ways to directly benefit from revenue streams as a result of leveraging open source practices internally, the current research on inner source is scattered among different areas. Thus gaining clarity on the state-of-the-art in inner source research is challenging. In particular, there is no systematic literature review of known research to date on inner source. We address this challenge by presenting a systematic literature review that identifies, critically evaluates and integrates the findings of 29 primary studies on inner source. Case study approach is the common research approach undertaken in the area. We also identified 8 frameworks/methods, models and tools proposed in the literature to support inner source, as well as a set of benefits and challenges associated with inner source. We envision future work to perform deeper analysis and synthesis on the empirical research on inner source software development.

Anecdotal evidence suggests that use and effectiveness of flow tools and analytics is rapidly increasing across the software community. The differentiating feature of flow methods is their speed, epitomised by terms such as lead-time, cycle time, and cost of delay. Yet, existing research tends to largely focuses on the textbook version of flow, rather than any rigorous examination of its use in the turbulent and constantly changing 'real world' environment within which it is applied. This is a significant limitation given that software development is a highly metric oriented, complex and socially embedded activity. This study draws on a single case with four software development teams to identify the benefits realized when flow practices and analytics are integrated with a contemporary business intelligence and analytical software. It also provides an immediate practical contribution by identifying a set of lessons drawn from the case studied that may be applicable in future implementations of flow tools and analytics and the lessons learned can then be tailored and applied to other software development contexts.

Crowdsourcing initiatives benefit from tapping into diversity. A vast plethora of disparate individuals, organizations, frameworks and skillsets can all play a role in sourcing solutions to a challenge. Nevertheless, while crowdsourcing has become a pervasive phenomenon, there is a paucity of research that addresses how the crowdsourcing process is measured. Whereas research has advanced various taxonomies of crowdsourcing none to date have specifically addressed the issue of measuring either specific stages of the crowdsourcing process or the process as a whole. As a first step towards achieving this goal, this research-in-progress paper examines crowdsourcing at the operational level with a view towards (i) identifying the parts of the process (ii) identifying what can be measured and (iii) categorising operational metrics to facilitate deployment in practice. The taxonomy advanced is overarching in nature and can be deployed across disciplines. Furthermore, the preliminary taxonomy presented will offer practitioners a comprehensive list of metrics that will enable them to facilitate comparison across various crowdsourcing initiatives.

In the course of conducting studies in information systems (IS), researchers must oftentimes investigate, design, and develop sound methods or approaches to best conduct their research. While new t...

This paper investigates the tightness of budgetary control over projects in a large systems development multinational. This represents a case of extreme information systems development (ISD) failure en masse, where all but two of the 22 projects in a business unit went over budget, causing senior executives to refocus their strategic priorities and cancel all current and potential projects that followed. This study focuses specifically on the two best performing (12 and 4% under budget) and worst performing (223 and 320% over budget) of these projects. Using a framework drawn from control systems theory, this study examines the ‘tightness’ of budgetary control exerted over each project, and what was done or could have been done to avert such failure. The study then identifies a set of emerging factors affecting tight budgetary control in ISD.

It has long been acknowledged that software methods should be tailored if they are to achieve optimum effect. However comparatively little research has been carried out to date on this topic in general, and more notably, on agile methods in particular. This dearth of evidence in the case of agile methods is especially significant in that it is reasonable to expect that such methods would particularly lend themselves to tailoring. In this research, we present a framework based on interviews with 20 senior software development researchers and a review of the extant literature. The framework is comprised of two sets of factors—characteristics of the method, and developer practices—that can improve method tailoring effectiveness. Drawing on the framework, we then interviewed 16 expert XP practitioners to examine the current state and effectiveness of XP tailoring efforts, and to shed light on issues the framework identified as being important. The article concludes with a set of recommendations for research and practice that would advance our understanding of the method tailoring area.

Agile systems development methods emerged as a response to the inability of previous plan-driven approaches to handle rapidly changing environments (Highsmith, 2002). Originating from the so-called...

Tailoring of methods is commonplace in the vast majority of software development projects and organisations. However, there is not much known about the tailoring and engineering of agile methods, or about how these methods can be used to complement each other. This study investigated tailoring of the agile methods, eXtreme programming (XP) and Scrum, at Intel Shannon, and involved experienced software engineers who continuously monitored and reflected on these methods over a 3-year period. The study shows that agile methods may individually be incomplete in supporting the overall development process, but XP and Scrum complement each other well, with XP providing support for technical aspects and Scrum providing support for project planning and tracking. The principles of XP and Scrum were carefully selected (only six of the 12 XP key practices were implemented, for example) and tailored to suit the needs of the development environment at Intel Shannon. Thus, the study refutes the suggestion that agile methods are not divisible or individually selectable but achieve their benefits through the synergistic combination of individual agile practices; rather, this study shows that an a la carte selection and tailoring of practices can work very well. In the case of Scrum, some local tailoring has led to a very committed usage by developers, in contrast to many development methods whose usage is limited despite being decreed mandatory by management. The agile practices that were applied did lead to significant benefits, including reductions in code defect density by a factor of 7. Projects of 6-month and 1-year duration have been delivered ahead of schedule, which bodes well for future ability to accurately plan development projects.