What influences the speed of prototyping? An empirical investigation of twenty software startups

It is essential for startups to quickly experiment business ideas by building tangible prototypes and collecting user feedback on them. As prototyping is an inevitable part of learning for early stage software startups, how fast startups can learn depends on how fast they can prototype. Despite of the importance, there is a lack of research about prototyping in software startups. In this study, we aimed at understanding what are factors influencing different types of prototyping activities. We conducted a multiple case study on twenty European software startups. The results are two folds, firstly we propose a prototype-centric learning model in early stage software startups. Secondly, we identify factors occur as barriers but also facilitators for prototyping in early stage software startups. The factors are grouped into (1) artifacts, (2) team competence, (3) collaboration, (4) customer and (5) process dimensions. To speed up a startups progress at the early stage, it is important to incorporate the learning objective into a well-defined collaborative approach of prototypingComment: This is the author's version of the work. Copyright owner's version can be accessed at doi.org/10.1007/978-3-319-57633-6_2, XP2017, Cologne, German

Video Game Development in a Rush: A Survey of the Global Game Jam Participants

Video game development is a complex endeavor, often involving complex software, large organizations, and aggressive release deadlines. Several studies have reported that periods of "crunch time" are prevalent in the video game industry, but there are few studies on the effects of time pressure. We conducted a survey with participants of the Global Game Jam (GGJ), a 48-hour hackathon. Based on 198 responses, the results suggest that: (1) iterative brainstorming is the most popular method for conceptualizing initial requirements; (2) continuous integration, minimum viable product, scope management, version control, and stand-up meetings are frequently applied development practices; (3) regular communication, internal playtesting, and dynamic and proactive planning are the most common quality assurance activities; and (4) familiarity with agile development has a weak correlation with perception of success in GGJ. We conclude that GGJ teams rely on ad hoc approaches to development and face-to-face communication, and recommend some complementary practices with limited overhead. Furthermore, as our findings are similar to recommendations for software startups, we posit that game jams and the startup scene share contextual similarities. Finally, we discuss the drawbacks of systemic "crunch time" and argue that game jam organizers are in a good position to problematize the phenomenon.Comment: Accepted for publication in IEEE Transactions on Game

Does maturity level influence the use of agile UX methods by digital startups? Evaluating design thinking, lean startup, and lean user experience

Context: Agile UX methods such as Design Thinking, Lean Startup, and Lean User Experience have been employed to deliver customer value and improve organizational performance. However, there is a lack of studies that assess how these tools are used at different stages of maturity of digital startups. Objective: The present study aims to compare the knowledge of graduated, incubated, and pre-incubated digital startups at university incubators concerning the use of Agile UX methods so that weaknesses and opportunities can be identified to provide co founders and scholars with new strategic insights. Method: Six reduced focus groups were conducted with 14 members of the six selected startups via multiple case studies. Answers were registered by researchers and then analyzed using an inductive process and codification. Results: The results indicated that digital startups had contact with consumers through market research, viability analysis, and product discontinuity. However, except for one startup, deficiencies in co-founders’ participation throughout developing products and services projects were identified. As far as the multiple case studies are concerned, Design Thinking and Lean Startup were employed by four of the startups, while two of them used the Lean User Experience method due to its higher maturity level. Conclusion: Although all Agile UX methods were employed, all six digital startups reported having made adaptations to the methods or to have used them only partially. Finally, it was concluded that the maturity level influences the Agile UX methods of each digital startup according to its nature and its stage of development in the market.Campus Lima Centr

Lean Startup as an Entrepreneurial Strategy: Limitations, Outcomes and Learnings for Practitioners

Purpose: This paper aims to address threecore questions around (1) what limitations exit with the methodology and/or its use; (2) what is the methodology's impact on performance outcomes; and (3) what learnings can practitioners and educators employ as part of the startup efforts. Methodology: A review of available peer and non-peer review literature relevant to the lean startup methodology, its limitations (pitfalls, fallacies, problems), and outcomes to address the core questions. Findings: This review identifies limitations with the methodology in several areas: business sector fit; issues associated with customer discovery; experimentation; iterating/pivoting; and the minimum viable product. Limitations may be related to the methodology, the incomplete understanding of its fundamental components, inconsistent (and non-rigorous) use of the methodology, and the inability to address risks (e.g., technological) beyond resolving market uncertainty. Also, experience related to outcomes with the lean startup reveals mixed findings due to the diverse methods, populations, and endpoints used. Such facets underly the mix of experiences seen in both the peer and non-peer review literature. This review identifies that rigorous implementation leads to statistically significant (P<0.05) outcome differences (e.g., discarding poor ideas, number of pivots, and revenue realization). Practical Implications: Practitioners and educators should consider educational, implementation, business sector, outside influences, outcomes, and investor preferences to use the methodology. Originality: This paper provides one of the first extensive literature reviews to examine what limits exist, where, and whether these are associated with the methodology or due to user, cultural, or business sector considerations. It also provides several relevant learnings for practitioners and educators to consider when using the methodology. Conclusions: Current evidence indicates that multiple issues do exist. Such limits are related to the methodology's inherent structure and user, sector, and external influence considerations. Further, outcomes vary based on study methods, variables, populations, business verticals, and implementation. Practitioners should consider some of the recommendations offered when utilizing this methodology to optimize their experience and outcomes

Understanding how high-tech entrepreneurs successfully pivot as part of the entrepreneurial journey

Purpose: In their entrepreneurial journey, high-tech entrepreneurs continuously face a need to devise a competitive value proposition for the startup company and leverage emerging technology to strengthen the proposition. Entrepreneurial pivoting addresses this challenge by allowing startups to validate and refine both their strategy and business model. Therefore, the research study has investigated two theories: the Lean Startup Approach and Technology Entrepreneurship. Consequently, the study has provided an empirical investigation of the pivoting concept examined in the context of the Lean Startup approach (LSA) and Technology Entrepreneurship to improve the understanding of the entrepreneurial journey for high-tech entrepreneurs. The research also focused on understanding how the life cycle stage of an emerging technology impacts the high-tech entrepreneurs’ entrepreneurial journey. The Lean Startup Approach, the technology S-curve, and the technology readiness level (TRL) framework were investigated to address the above question. The study has provided an empirical investigation of the pivoting concept, which has been explained in the context of the lean startup approach (LSA), the technology S-curve and the technology readiness level to improve the understanding of the entrepreneurial journey for high-tech entrepreneurs leading tech startups. Apart from investigating how high-tech entrepreneurs develop competitive value propositions and how emerging technologies impact their entrepreneurial journey, the research study also investigated leadership styles and their influence on tech entrepreneurs. For this, the study has empirically investigated pivoting from the Lean Startup Approach and six different leadership styles. Due to studying pivoting from the Lean Startup Approach and investigating technology entrepreneurship, technology S-curve and technology readiness levels, this research study is titled ‘Understanding how high-tech entrepreneurs successfully pivot their startups as part of the entrepreneurial journey’. Methodological Approach: A qualitative research method was adopted by interviewing hightech entrepreneurs across the United Kingdom to validate the theories associated with the LSA and identify new insights on entrepreneurial pivoting. The interviews are divided into two stages. Firstly, thirty primary interviews were conducted to understand pivoting and the factors that trigger pivoting; the influence of the phases of technology entrepreneurship on pivoting; and the impact of stages of technology maturity in the technology S-curve on pivoting. Secondly, longitudinal interviews were conducted in three phases with nine high-tech entrepreneurs who were also involved in the thirty primary interviews. The purpose of the longitudinal interviews was to collect further data on the above-mentioned topics and understand in more detail and build up a richer picture on how high-tech startups successfully pivot as part of the entrepreneurial journey. Findings: The research study has validated the existing types of pivots and identified two new pivots (giving 16 in total). The study has validated 11 factors that trigger a tech startup to change direction and identified three new factors (giving 14 in total). The research study also determined that there can be a domino effect in pivoting, and the value proposition can be created and sustained through pivoting. The study has established the influence of the phases of technology entrepreneurship on pivoting and the impact of the stages of technology maturity in the technology S-curve on pivoting. Originality: The study provides empirical evidence on pivots and the factors associated with pivots. Moreover, the study significantly helps to improve the understanding of the influence of the phases of technology entrepreneurship on pivoting. The study has developed a new conceptual framework for TE. Furthermore, the study helped in understanding the impact of the stage of technology in the technology S-curve and technology readiness level on pivoting. The study also discusses the challenges faced by tech startups while pursuing pivots; the domino effect in pivoting; and has found evidence that pivoting leads to achieving the desired results

Software Startups -- A Research Agenda

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

Software Engineering Knowledge Areas in Startup Companies: A Mapping Study

Background - Startup companies are becoming important suppliers of innovative and software intensive products. The failure rate among startups is high due to lack of resources, immaturity, multiple influences and dynamic technologies. However, software product engineering is the core activity in startups, therefore inadequacies in applied engineering practices might be a significant contributing factor for high failure rates. Aim - This study identifies and categorizes software engineering knowledge areas utilized in startups to map out the state-of-art, identifying gaps for further research. Method - We perform a systematic literature mapping study, applying snowball sampling to identify relevant primary studies. Results - We have identified 54 practices from 14 studies. Although 11 of 15 main knowledge areas from SWEBOK are covered, a large part of categories is not. Conclusions - Existing research does not provide reliable support for software engineering in any phase of a startup life cycle. Transfer of results to other startups is difficult due to low rigor in current studies.Comment: Proceedings 6th International Conference on Software Business (ICSOB 2015), Braga, Portugal, 245-25

On the Characteristics of Internal Software Startups

In recent years, more attention has been given to internal software startups in practice and in research alike, yet the concept is not fully understood. Nor is it clear whether or not it significantly differs from stand-alone software startup, and if yes, then how. In this position paper, we propose to conceptualize internal software startups as a hybrid of two related concepts: stand-alone software startup and internal corporate venture (ICV). We derive characteristics of the both concepts from the earlier literature and use our previous research on internal software startups to uncover the differences and the similarities across the three concepts.publishedVersio