Anh Nguyen-Duc

Startup Metrics that Tech Entrepreneurs need to know

Time for AI (Ethics) Maturity Model Is Now

There appears to be a common agreement that ethical concerns are of high importance when it comes to systems equipped with some sort of Artificial Intelligence (AI). Demands for ethical AI are declared from all directions. As a response, in recent years, public bodies, governments, and universities have rushed in to provide a set of principles to be considered when AI based systems are designed and used. We have learned, however, that high-level principles do not turn easily into actionable advice for practitioners. Hence, also companies are publishing their own ethical guidelines to guide their AI development. This paper argues that AI software is still software and needs to be approached from the software development perspective. The software engineering paradigm has introduced maturity model thinking, which provides a roadmap for companies to improve their performance from the selected viewpoints known as the key capabilities. We want to voice out a call for action for the development of a maturity model for AI software. We wish to discuss whether the focus should be on AI ethics or, more broadly, the quality of an AI system, called a maturity model for the development of AI systems.

Software Startups - A Research Agenda

Software startup companies develop innovative, software-intensive products within limited timeframes and with few resources, searching for sustainable and scalable business models. Software startup ...

Minimum Viable Product or Multiple Facet Product? The Role of MVP in Software Startups

Minimum viable product (MVP) is the main focus of both business and product development activities in software startups. We empirically explored five early stage software startups to understand how MVP are used in early stages. Data was collected from interviews, observation and documents. We looked at the MVP usage from two angles, software prototyping and boundary spanning theory. We found that roles of MVPs in startups were not fully aware by entrepreneurs. Besides supporting validated learning, MVPs are used to facilitate product design, to bridge communication gaps and to facilitate cost-effective product development activities. Entrepreneurs should consider a systematic approach to fully explore the value of MVP, as a multiple facet product (MFP). The work also implies several research directions about prototyping practices and patterns in software startups.

“Failures” to be celebrated: an analysis of major pivots of software startups

In the context of software startups, project failure is embraced actively and considered crucial to obtain validated learning that can lead to pivots. A pivot is the strategic change of a business concept, product or the different elements of a business model. A better understanding is needed on different types of pivots and different factors that lead to failures and trigger pivots, for software entrepreneurial teams to make better decisions under chaotic and unpredictable environment. Due to the nascent nature of the topic, the existing research and knowledge on the pivots of software startups are very limited. In this study, we aimed at identifying the major types of pivots that software startups make during their startup processes, and highlighting the factors that fail software projects and trigger pivots. To achieve this, we conducted a case survey study based on the secondary data of the major pivots happened in 49 software startups. 10 pivot types and 14 triggering factors were identified. The findings show that customer need pivot is the most common among all pivot types. Together with customer segment pivot, they are common market related pivots. The major product related pivots are zoom-in and technology pivots. Several new pivot types were identified, including market zoom-in, complete and side project pivots. Our study also demonstrates that negative customer reaction and flawed business model are the most common factors that trigger pivots in software startups. Our study extends the research knowledge on software startup pivot types and pivot triggering factors. Meanwhile it provides practical knowledge to software startups, which they can utilize to guide their effective decisions on pivoting.

Exploring the outsourcing relationship in software startups: A multiple case study

Abstract -- Software startups are becoming increasingly popular in software industry as well as other sectors of economy. Startups that lack necessary competences often seek for external resources from outsourcing partners. Little is known how this outsourcing relationship works and whether it makes sense to outsource the technical competence to an external party. This is among the first investigations on the outsourcing relationships in software startups. By conducting exploratory case studies at six startups, we found a mixed experience with outsourcing. The experimental nature of an early product development makes outsourcing a feasible option, although startups often suffer from its uncertainty and managing commitments from partners. Results further propose that early contract-based activities could be transformed into a long-term partnership by adopting a startup boundary spanner's role, establishing an inter-personal relationship and maintaining a mutual commitment.1

Building an entrepreneurship data warehouse

The main principle of the Lean Startup movement is that static business planning should be replaced by a dynamic development, where products, services, business model elements, business objectives and activities are frequently changed based on constant customer feedback. Our ambition is to empirically measure if such changes of the business idea, the business model elements, the project management and close interaction with customers really increases the success rate of entrepreneurs, and in what way. Our first paper; “Does Lean Startup really work? Foundation for an empirical study” presented the first attempt to model the relations we want to measure. This paper will focus on how to build and set up a test harness (from now on called the Entrepreneurship Platform or EP) to gather empirical data from Companies and how to store these data together with demographical and financial data from the PROFF-portal in the Entrepreneurial Data Warehouse (from now called the EDW). We will end the paper by discussing the potential methodological problems with our method, before we document a test run of our set-up to verify that we are actually able to populate the Data Warehouse with time series data.

Female Leadership in Software Projects: A Preliminary Result on Leadership Style and Project Context Factors

Women have been shown to be effective leaders in many team-based situations. However, it is also well-recognized that women are underrepresented in engineering and technology areas, which leads to wasted efforts and a lack of diversity in professional organizations. Although studies about gender and leadership are rich, research focusing on engineering-specific activities, are scarce. To react on this gap, we explored the experience of female leaders of software development projects and possible context factors that influence leadership effectiveness. The study was conducted as a longitudinal multiple case study. Data was collected from survey, interviews, observation and project reports. In this work, we reported some preliminary findings related to leadership style, team perception on leadership and team-task context factors. We found a strong correlation between perceived team leadership and task management. We also observed a potential association between human-oriented leading approach in low customer involvement scenarios and task-oriented leading approach in high customer involvement situations.

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 startup’s progress at the early stage, it is important to incorporate the learning objective into a well-defined collaborative approach of prototyping.

Coopetition of Software Firms in Open Source Software Ecosystems

Software firms participate in an ecosystem as a part of their innovation strategy to extend value creation beyond the firm’s boundary. Participation in an open and independent environment also implies the competition among firms with similar business models and targeted markets. Hence, firms need to consider potential opportunities and challenges upfront. This study explores how software firms interact with others in OSS ecosystems from a coopetition perspective. We performed a quantitative and qualitative analysis of three OSS projects. Finding shows that software firms emphasize the co-creation of common value and partly react to the potential competitiveness on OSS ecosystems. Six themes about coopetition were identified, including spanning gatekeepers, securing communication, open-core sourcing and filtering shared code. Our work contributes to software engineering research with a rich description of coopetition in OSS ecosystems. Moreover, we also come up with several implications for software firms in pursing a harmony participation in OSS ecosystems.

How do Startups Develop Internet-of-Things Systems - A Multiple Exploratory Case Study

Internet-of-Things applications are not only the new opportunity for digital businesses but also a major driving force for the modification and creation of software systems in all industries and businesses. Compared to other types of software-intensive products, the development of Internet-of-Things applications lacks a systematic approach and guidelines. This paper aims at understanding the methodological commonalities among startups who are developing Internet-of-Things products. Using the SEMAT Essence framework, we captured common team compositions, common types of Minimum Viable Products and common way of working in early stage Internet-of-Things startups. We found that startups include various engineering and business competence, but do not cover all of what is needed. The development of Internet-of-Things applications adopts certain speed-favor approaches, i.e. rapid prototyping, iterative development and outsourcing. The finding implies some recommendations for both researchers and practitioners in the area of Internet-of-Things development.

An Empirical Study on Female Participation in Software Project Courses

Gender issues in software engineering education are gaining research attention due to the desire to promote female participation in the field. The objective of this work is to enhance the understanding of female students' participation in software engineering projects to support gender-aware course optimization. Since 2015, we have investigated the participation of female students in terms of software engineering activities and team dynamics in a software project course that involves a real customer. We found that female students are more active with project management and requirement engineering, while they remain under-represented in highly complex or specific tasks, i.e. architecture work, and user experience design. We found no statistically significant difference in perceived team dynamics between male and female students. Insights on female project activities would facilitate the arrangement of project teams so that learning can be distributed equally across genders