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Software Startups -- A Research Agenda
Michael Unterkalmsteiner, Pekka Abrahamsson, Xiaofeng Wang, Anh Nguyen-Duc, Syed M. Ali Shah, Sohaib Shahid Bajwa, Guido H. Baltes, Kieran Conboy, Eoin Cullina, Denis Dennehy, Henry Edison, Carlos Fernández-Sánchez, Juan Garbajosa, Tony Gorschek, Eriks Klotins, Laura Hokkanen, Fabio Kon, Ilaria Lunesu, Michele Marchesi, Lorraine Morgan, Markku Oivo, Christoph Selig, Pertti Seppänen, Roger Sweetman, Pasi Tyrväinen, Christina Ungerer, Agustín Yagüe
TL;DR
Software startups operate under uncertainty, scarce resources, and pressure to develop scalable products, but software engineering research lacks a sufficiently specific evidence base for their practices and success factors. This paper develops a network-based research agenda spanning six clusters and more than seventy research questions, connecting prior studies with future research and interdisciplinary collaboration. It frames the agenda as an early effort to support understanding of software startups while acknowledging definitional and scope limitations.
Problem
Software startups differ from mature companies and small businesses, yet research lacks comprehensive evidence on startup-specific engineering practices, technical debt management, and success factors.
Method
The paper develops a bottom-up research agenda from a network of software startup researchers, organizing eighteen tracks into six thematic clusters and grounding topics in prior and proposed research.
Results
The agenda identifies more than seventy research questions across startup engineering, evolution, ecosystems, human aspects, non-startup applications, and research methodologies and theories.
Takeaways & Limitations
The agenda is intended to support collaboration among researchers and startup environments and to generate knowledge, tools, and methods relevant to software startup practice.
Takeaways & Limitations
The agenda’s bottom-up development may be biased toward participating researchers’ preferences, and its scope excludes some potentially relevant areas until more evidence exists.
Abstract
from arXiv · showhide
Software startup companies develop innovative, software-intensive products within limited time frames and with few resources, searching for sustainable and scalable business models. Software startups are quite distinct from traditional mature software companies, but also from micro-, small-, and medium-sized enterprises, introducing new challenges relevant for software engineering research. This paper's research agenda focuses on software engineering in startups, identifying, in particular, 70+ research questions in the areas of supporting startup engineering activities, startup evolution models and patterns, ecosystems and innovation hubs, human aspects in software startups, applying startup concepts in non-startup environments, and methodologies and theories for startup research. We connect and motivate this research agenda with past studies in software startup research, while pointing out possible future directions. While all authors of this research agenda have their main background in Software Engineering or Computer Science, their interest in software startups broadens the perspective to the challenges, but also to the opportunities that emerge from multi-disciplinary research. Our audience is therefore primarily software engineering researchers, even though we aim at stimulating collaborations and research that crosses disciplinary boundaries. We believe that with this research agenda we cover a wide spectrum of the software startup industry current needs.
1. Introduction
Software startups develop innovative software-intensive products under time and resource constraints while seeking sustainable, scalable business models. Their survival challenges and broad economic relevance motivate a research agenda connecting software engineering research with startup practice and collaboration.
- Software startups develop innovative software-intensive products under time constraints and with limited resources while searching for sustainable and scalable business models.
- Startups contribute to wealth, progress, jobs, innovation, and a wide variety of digital services and products.
- Software startups face survival challenges involving product development, customer acquisition, and entrepreneurial team building.
- The agenda is driven by past and current software startup research and previews future research while supporting collaboration across research and startup environments.
- The paper organizes its research topics into six main tracks after clarifying software startup definitions and prior knowledge.
2. Background
Software startups are temporary, growth-oriented organizations developing innovative products amid uncertainty, technological change, resource scarcity, and turbulent markets. Existing research identifies major challenges and incomplete engineering knowledge, while definitions and success factors remain insufficiently established.
- A startup is a temporary organization creating innovative products under extreme uncertainty and seeking a scalable, repeatable, profitable business model.
- Software startups additionally face rapid technological change, resource scarcity, immature operations, multiple influences, and turbulent markets.
- There is no consensus on defining software startups, so researchers should explicitly characterize the startups included in their studies.
- Software startups face resource shortages, reactivity, inexperienced small teams, reliance on a single product, innovation demands, and uncertainty.
- Research has not yet established software startup success factors or whether general new-business factors apply specifically to software startups.
- Existing studies offer only snapshots of startup engineering practices, leaving an insufficient empirical knowledge base for understanding how those practices support startups.
3. Research Agenda
The research agenda was developed by a network of startup researchers with varied perspectives and organizes eighteen tracks into six thematic clusters. Its scope includes software engineering while recognizing relevant areas outside the current agenda.
- The agenda was developed by a researcher network whose interests span different angles and perspectives on the software startup phenomenon.
- Each research topic follows a pattern covering background, motivation, research questions, potential impact, methodologies, and related work.
- Eighteen research tracks were grouped into six major clusters according to thematic similarities and differences to facilitate presentation and discussion.
- Marketing and business and economic development are relevant directions outside the paper’s current scope that may be added when more evidence exists about their interaction with startup engineering.
3.1. Supporting Startup Engineering Activities
This research track examines how software engineering practices can support startups operating with scarce resources, rapid change, and uncertainty. It proposes research on engineering context, practices, technical debt, and trade-offs between delivery speed and future product viability.
- Supporting Startup Engineering Activities: Software startups often fail amid market, team, resource, or product problems, while the role of engineering practices in product success remains insufficiently explored.
- Supporting Startup Engineering Activities: Ad-hoc or borrowed agile practices may neglect startup-specific challenges because quality improvements can increase cost and time, while strict backlogs may hinder innovation.
- Context and practices: The agenda asks whether engineering is a startup success factor, how startup contexts should be defined, and which practices work in those contexts.
- Technical debt management: Rapidly changing software markets make new-product speed and time-to-market increasingly important considerations for startup engineering decisions.
- Technical debt management: Technical debt management can help startups identify maintenance costs and decide when investing in software improvement is profitable.
- Technical debt management: The agenda investigates startup evolution problems, improvement priorities, trade-off factors, roadmap timing, and agile technical debt management under uncertainty.
- Technical debt management: Answering these questions could support implementation choices involving deadlines, change complexity, cost, and future potential for practitioners and researchers.
- Technical debt management: Technical debt decisions differ across contexts, and specific studies of technical debt management in software startups remain scarce.
3.3. Cooperative and Human Aspects in Software Startups
Software startup research examines how distinctive resource constraints, rapid development, growth, and collaboration shape competencies and teamwork. Key questions concern team characteristics, stakeholder communication, internal relationships, and competence growth, while evidence remains limited on managing competencies as startups grow.
- Competencies: Software startups require different competencies from mature companies, especially during resource-constrained early development and rapid organizational growth.These phases affect software development and competency needs.
- Competencies: Research on startup competencies can extend knowledge of software engineering under challenging conditions, particularly during early and growth stages.The agenda identifies these periods as especially valuable for academia and practitioners.
- Teamwork: Startup success depends on team execution and close collaboration among founders, team members, mentors, and investors.Entrepreneurship research cited in the agenda reports that over 80 percent of startups surviving beyond two years were founded by at least two people.
- Teamwork: Startup-team research asks whether successful startups share cultural, organizational, or team characteristics and how teams manage internal and external relationships.External stakeholders include mentors and investors.
- Research gaps: Existing software-engineering research has identified team factors in startup failure, but the generalizability of trust-related findings across geographies remains uncertain.The cited geographic limitation concerns influencing variables on relational capital in Chinese IT startups.
3.4. Applying Startup Concepts in Non-Startup Contexts
This section investigates applying Lean Startup and internal-startup concepts within established organizations, including portfolio management and open innovation. It highlights potential benefits alongside cultural, strategic, intellectual-property, and evidence gaps requiring research.
- Internal software startups: Internal software startups let large companies pursue an idea from business formation through product development and market introduction.They are intended to support both improvement of existing businesses and exploration of future businesses.
- Internal software startups: Internal-startup implementation faces cultural conflicts and cannibalization concerns, while established companies provide shared resources and network access.The cited benefits include capital, human resources, and corporate networks.
- Lean Startup: Lean Startup application differs between mature firms and startups: mature firms begin with existing-user data, whereas startups generate ideas and validate them with new users.The difference concerns how the build-measure-learn cycle begins.
- Research directions: The agenda proposes applying Lean Startup to project portfolio management and open innovation, including coordination across initiatives and organizations.It identifies portfolio coordination and multi-organization participation as specific contexts.
- Project portfolio management: Portfolio management practices centered on individual project completion and episodic reviews do not adequately handle dynamic projects or overly large portfolios.The section links this problem to the need for more dynamic portfolio approaches.
- Open innovation: Open innovation offers expertise, possible R&D savings, shorter time-to-market, and collaborative networks but introduces commitment, alignment, intellectual-property, and contributor-management challenges.These challenges motivate research on how Lean Startup can be implemented and aligned with strategy.
- Research gaps: Research on Lean Startup in portfolio management is limited, while applications in open innovation have mainly been practice-driven rather than empirically established.The agenda calls for theory and empirical evidence to support or refute effectiveness claims.
3.5. Software Startup Ecosystems and Innovation Hubs
Software startup ecosystems comprise interacting entrepreneurs, developers, investors, experts, and support programs that influence startup formation and development. Research seeks to characterize, measure, compare, and model how these ecosystems evolve.
- Ecosystem components: Software startups operate within ecosystems involving entrepreneurs, developers, investors, scientists, consultants, and programs providing funding, incubation, acceleration, training, networking, and consulting.These elements collectively form the environment surrounding startup development.
- Ecosystem development: Studying ecosystem creation, characteristics, and evolution can identify conditions and concrete actions that support successful software startups.The proposed actions include public policies and private activities.
- Research questions: The agenda asks which elements make an ecosystem fruitful, whether ecosystem types differ, how ecosystems evolve, and how their outputs and qualities can be measured.These questions address ecosystem structure, variation, development, and evaluation.
- Methods and models: Existing mapping methods have been applied to software startup ecosystems in Israel, São Paulo, and New York.Researchers are also developing a maturity model with international expert input.
- Methods and models: The proposed ecosystem maturity model requires further research and validation before practical use by practitioners and policymakers.This is the section’s explicit boundary on current applicability.
3.6. Theory and Methodologies for Software Startup Research
The agenda calls for theories and methods that explain startup dynamics, evaluate Lean Startup across contexts, and address the practical difficulty of collecting empirical data. It proposes several theoretical lenses while identifying definitional, cumulative, applicability, and access constraints.
- Theory: The proposed theoretical lenses include the hunter-gatherer model, Cynefin, Effectuation theory, and Boundary Spanning theory.These theories are presented as potentially meaningful for studying software startups.
- Theory: The hunter-gatherer model distinguishes searching for an innovative idea from implementing it, assigning change-driven and plan-oriented characteristics respectively.The model treats both activities as necessary for concrete results.
- Theory: Effectuation describes decision-making under uncertainty as reasoning from available means toward ends rather than from desired ends toward necessary means.The theory is rooted in entrepreneurship and includes principles such as affordable loss.
- Theory: Software startup research lacks sufficient understanding of startup dynamics across diverse contexts, situations, and places.The agenda presents theorizing as necessary for making sense of these varied settings.
- Lean Startup research: Lean Startup research has been largely practice-led, creating a need for clearer concepts, cumulative theory, and evidence across environments.The agenda frames academic research as a way to connect practice and empirically assess utility.
- Lean Startup research: Unclear definitions and interpretations of concepts such as MVP hinder critical appraisal, evidence-based evaluation, and comparison across Lean Startup studies.The problem concerns inconsistent definitions, uses, and evaluations.
- Lean Startup research: Adherence-based Lean Startup measures limit applicability beyond the original domain, including large and regulated organizations.The agenda therefore asks which concepts underpin Lean Startup and how they transfer across environments.
- Methodology: Empirical startup research is constrained by startups’ limited person-hours and calendar time for research participation.The agenda links this access problem to the difficulty of collecting data on core startup challenges.
4. Discussion
The discussion connects software startup engineering to lightweight requirements practices, startup evolution, human aspects, internal startup concepts, and research methodologies. It also frames the agenda as a bottom-up, collaborative effort with acknowledged coverage limits.
- Software startup engineering: Software startups’ time and resource constraints make lightweight requirements analysis important for identifying customer and business value.Prototypes, product innovation assessment, test cases as requirements, and user testing are identified as relevant approaches.
- Startup evolution models and patterns: Earlier analysis of requirements and value propositions could reduce the cost of pivoting and support heuristics for startup survival.The discussion links requirements research with startup evolution models, patterns, and survival capabilities.
- Cooperative and human aspects in software startups: Research on cognitive abilities, team composition, workload, informal communication, and expertise identification addresses cooperative and human aspects of software startups.These aspects are presented as a substantial area for understanding startup work.
- Non-startup contexts and research implementation: Some research tracks examine applying startup concepts in non-startup contexts, while others address theories and collaborations needed to implement the research agenda.The agenda includes internal startups, theoretical foundations, and efficient research collaboration with software startups.
- Methodological basis: The agenda was developed bottom-up by a sample of researchers whose prior, current, and future work guided the proposed areas.The authors invited many peers because this approach may be biased toward individual researchers’ preferences.
5. Outlook and Conclusions
The paper presents software startups as an important, rapidly emerging research area and calls for multidisciplinary collaboration to develop useful knowledge. It also emphasizes that the agenda remains provisional because concepts, theories, findings, and topic coverage require further development.
- Research area: The research agenda is an early attempt to establish software startups as a fast-growing research area and map its topics and questions.It is framed as a way to understand software startups and accumulate knowledge for future entrepreneurial initiatives.
- Multidisciplinary collaboration: Software startup practice can benefit from collaboration among Software Engineering, Economics, Entrepreneurship, Design, Finance, Sociology, and Psychology researchers.The paper argues that Software Engineering is only one relevant discipline.
- Foundations for future research: The emerging field still needs clear concept definitions, substantive theories, and validation of initial findings through future studies.The paper warns that weak foundations risk irrelevant questions and insufficiently rigorous results.
- Scope and continuation: The agenda is not exhaustive and may omit important Software Engineering topics relevant to software startups.The authors explicitly invite additions of tracks, topics, and research questions.
- Research community: Contributions from researchers with different institutions and backgrounds are invited to advance the agenda through the Software Startup Research Network.The network is presented as a vehicle for collaboration and extending the research agenda.