Introduction
In today’s society, most start-ups are founded and led by a team rather than individuals (Ben-Hafaïedh, Reference Ben-Hafaïedh2017; Ben-Hafaïedh, Champenois, Cooney & Schjoedt, Reference Ben-Hafaïedh, Champenois, Cooney and Schjoedt2024; Yang, Cozzarin, Peng & Xu, Reference Yang, Cozzarin, Peng and Xu2022). An entrepreneurial team is defined as “two or more individuals who have a significant financial interest and participate actively in the development of the enterprise (Cooney, Reference Cooney2005). Existing research has demonstrated that teams have more resources, knowledge, and skills than individuals to deal with the various challenges they face at different stages of a firm’s development that require complexity and flexibility in decision-making (Chowdhury, Reference Chowdhury2005; Linder, Lechner & Villani, Reference Linder, Lechner and Villani2025; Soleimani & Stauffer, Reference Soleimani and Stauffer2024; West III, Reference West III2007). At the heart of the entrepreneurial team research, one of the most critical factors is entrepreneurial team composition, and more specifically, team diversity (Sundermeier & Mahlert, Reference Sundermeier and Mahlert2023; Zhou & Rosini, Reference Zhou and Rosini2015). Numerous studies have suggested that team diversity in terms of demographic, informational, personality, and cognitive attributes (Das, Das & Chattopadhyay, Reference Das, Das and Chattopadhyay2021; Fiorentino, Longobardi, Morrone & Scaletti, Reference Fiorentino, Longobardi, Morrone and Scaletti2024; Kaiser & Müller, Reference Kaiser and Müller2015; Zhou, Hu & Zey, Reference Zhou, Hu and Zey2015; Zhou & Rosini, Reference Zhou and Rosini2015) can act as a double-edged sword, offering both beneficial and detrimental impacts on start-up success. Team diversity is commonly associated with enhanced creativity, broader perspectives, and innovative problem-solving approaches (Martins & Sohn, Reference Martins and Sohn2022; Qi, Armstrong, Yang & Li, Reference Qi, Armstrong, Yang and Li2022). Additionally, team diversity represented a key to securing resources, attracting funding, and navigating the uncertainty of a dynamic environment (Beckman, Burton & O’Reilly, Reference Beckman, Burton and O’Reilly2007; Bessagnet & Abreu, Reference Bessagnet and Abreu2025; Hanifzadeh, Talebi & Jafari-Sadeghi, Reference Hanifzadeh, Talebi and Jafari-Sadeghi2024; Klotz, Hmieleski, Bradley & Busenitz, Reference Klotz, Hmieleski, Bradley and Busenitz2014; Knight, Greer & De Jong, Reference Knight, Greer and De Jong2020). However, team diversity is also recognized for its potential to generate friction, hinder collaboration, and disrupt decision-making processes (Linder et al., Reference Linder, Lechner and Villani2025). These internal challenges can significantly influence the start-up’s ability to survive, becoming even more critical during the different developmental stages of the venture life cycle that require high levels of coordination, adaptability, and strategic alignment (Diakanastasi, Karagiannaki & Pramatari, Reference Diakanastasi, Karagiannaki and Pramatari2018; Patzelt, Preller & Breugst, Reference Patzelt, Preller and Breugst2021).
While the potential benefits of diversity are well-documented (Eisenhardt, Reference Eisenhardt2013; Fuel, Pardo-del-val & Revuelto-Taboada, Reference Fuel, Pardo-del-val and Revuelto-Taboada2022; Hemmert et al., Reference Hemmert, Cross, Cheng, Kim, Kotosaka, Waldenberger and Zheng2022; Horvatinovic, Mikic & Dabić, Reference Horvatinovic, Mikic and Dabić2023; Horwitz & Horwitz, Reference Horwitz and Horwitz2007; Huovinen & Pasanen, Reference Huovinen and Pasanen2010; Kakarika, Reference Kakarika2013; Martins & Sohn, Reference Martins and Sohn2022; Qi et al., Reference Qi, Armstrong, Yang and Li2022; Santisteban, Mauricio & Cachay, Reference Santisteban, Mauricio and Cachay2021; Soleimani & Stauffer, Reference Soleimani and Stauffer2024), recent literature reviews (Sundermeier & Mahlert, Reference Sundermeier and Mahlert2023; Zhou & Rosini, Reference Zhou and Rosini2015) suggest that the evidence supporting these positive effects has become increasingly robust. In contrast, the negative consequences of diversity remain less consistent and often fail to achieve the same level of empirical robustness (Sundermeier & Mahlert, Reference Sundermeier and Mahlert2023; Zhou & Rosini, Reference Zhou and Rosini2015). Specifically, while previous studies have extensively examined the effect of team diversity on different venture outcomes, such as financial performance, growth rates, and innovation performance, the impact of team diversity in the context of venture survival remained underinvestigated, also because existing studies focus their empirical analysis on successful companies Moreover, existing studies consider the effects of teams’ diversity from a static point of view, while the startups go through different stages, and the effects of team diversity could be different according to the firm’s development stage. Entrepreneurial ventures move through distinct stages such as formation, growth, scaling, and maturity, each characterized by unique challenges and resource demands, and the impact of team diversity is unlikely to remain static across these stages (Diakanastasi et al., Reference Diakanastasi, Karagiannaki and Pramatari2018). In this context, it becomes evident that while team diversity offers substantial opportunities for entrepreneurial success, its inherent dynamic challenges cannot be ignored. This duality highlights the need to examine the dynamic impact of diversity across a start-up’s lifecycle and its potential to act as a destabilizing force, contributing significantly to venture failure when mismanaged. Thus, building on this dynamic perspective to address the aforementioned gap, this study aims to answer the following research question:
RQ1: Which entrepreneurial team diversity characteristics (demographic, informational, personality, and cognitive) harm start-ups’ survival, considering the different stages of development?
To tackle the research question, this study adopts a qualitative research design. Specifically, while previous studies are focused on successful companies, the present study adopts an original retrospective methodology called post-mortem analysis aimed at analyzing the dynamics related to failed start-ups. The adopted methodology consists of a three-step approach designed to systematically reconstruct the role of team diversity in start-up failure. First, interviews with failed start-ups available on the publicly accessible Failory database were collected and triangulated with additional sources of evidence to ensure data accuracy and contextual depth. Subsequently, adopting an inductive coding process following the Gioia methodology (Gioia, Corley & Hamilton, Reference Gioia, Corley and Hamilton2013), first-order codes were developed directly from the raw data, then grouped into second-order themes and aggregate dimensions, allowing for the systematic identification of diversity-related attributes. In the final step, guided by post-mortem methodology and grounded in detailed firm histories, the negative effects of diversity dimensions were contextualized within each start-up’s developmental trajectory (Dingsøyr, Reference Dingsøyr2005; Schieg, Reference Schieg2007). This process enabled a nuanced understanding of which specific diversity-related factors contributed to failure, as they unfolded over time within the venture’s lifecycle.
This study provides critical insights into the intricate interplay between demographic, informational, personality, and cognitive diversity and venture survival, exposing stage-specific diversity attributes previously overlooked in empirical studies. Specifically, findings reveal that personality and cognitive diversity are most problematic in idea development, personality and informational diversity during product development, and personality and demographic diversity during the launch stage.
From a theoretical point of view, this study contributes to entrepreneurial team research, explicitly emphasizing the dark side of team diversity by focusing on failed start-ups adopting a dynamic approach considering the stages of development in the investigation. More specifically, this study challenges the predominantly positive view of team diversity, providing a dynamic perspective on the impact of team diversity on venture outcomes. This nuanced perspective provides new insights into how team diversity influences venture outcomes at different stages and advances the broader understanding of team dynamics and venture survival in the entrepreneurial context.
This work also offers recommendations that empower startup managers to leverage team diversity as a strategic asset while navigating the dynamic challenges of different stages of development.
The paper is structured as follows: The next section presents a review of the relevant literature that frames the context and rationale for this study; in section 3, the adopted methodological approach is explained and described. The final sections highlight findings and discuss them based on the existing literature. Theoretical, practical, and policy implications are also provided, as well as the study’s limitations, which open avenues for future research.
Literature review
Entrepreneurial team composition represents a foundational and increasingly prominent focus within entrepreneurship research, with team diversity emerging as a critical factor in shaping venture dynamics, strategic decision making, and overall outcomes (Das et al., Reference Das, Das and Chattopadhyay2021; Linder et al., Reference Linder, Lechner and Villani2025; Sundermeier & Mahlert, Reference Sundermeier and Mahlert2023). Entrepreneurial team diversity, commonly defined as ‘the distribution of differences among the members of a unit concerning a common attribute’ (Harrison & Klein, Reference Harrison and Klein2007) is increasingly recognized as a key determinant of how ventures navigate complexity, innovate, and adapt in dynamic environments (Das et al., Reference Das, Das and Chattopadhyay2021). Research on entrepreneurial teams has traditionally categorized diversity into two broad categories: surface-level and deep-level diversity. Surface-level diversity refers to observable traits such as age, gender, nationality, education, and professional background (Linder et al., Reference Linder, Lechner and Villani2025; Ma, Xiao, Guo, Tang & Singh, Reference Ma, Xiao, Guo, Tang and Singh2022; Troise, Giovando, Jabeen & Bresciani, Reference Troise, Giovando, Jabeen and Bresciani2024; Wei, Mo, Zhang & Yang, Reference Wei, Mo, Zhang and Yang2024). In contrast, deep-level diversity encompasses less immediately apparent attributes, which become more evident through interactions and communication over time, including individuals’ values, beliefs, attitudes, and opinions (Chen & Liu, Reference Chen and Liu2024; Kollmann, Stöckmann, Meves & Kensbock, Reference Kollmann, Stöckmann, Meves and Kensbock2017; Schoss, Urbig, Brettel & Mauer, Reference Schoss, Urbig, Brettel and Mauer2020; Su, Luo, Lau & de Jong, Reference Su, Luo, Lau and de Jong2024). The study conducted by Zhou and Rosini (Reference Zhou and Rosini2015) further refines this distinction, classifying diversity characteristics into three broad categories: demographic diversity, which includes factors such as age, gender, race, and ethnicity; informational diversity, which encompasses differences in education, professional experience, and expertise; and personality and cognitive diversity, which covers individual personality traits and behavioral patterns.
A growing body of literature has recognized the importance of entrepreneurial teams’ diversity in shaping start-ups’ success (Jin et al., Reference Jin, Madison, Kraiczy, Kellermanns, Crook and Xi2017; Sundermeier & Mahlert, Reference Sundermeier and Mahlert2023). The Upper Echelons Theory offers a powerful lens through which to understand how the characteristics of founding teams shape organizational outcomes (Hambrick & Mason, Reference Hambrick and Mason1984). According to this perspective, strategic choices, innovation trajectories, and overall firm performance are not merely rational processes but are deeply influenced by the psychological, cognitive, and demographic attributes of team members. They interpret information and navigate uncertainty based on their individual experiences, values, and cognitive styles, which inevitably shape collective decisions and venture direction (Finkelstein, Hambrick & Cannella, Reference Finkelstein, Hambrick and Cannella2009; Li, Reference Li2017; Rössig & Schmidt, Reference Rössig and Schmidt2025). Within entrepreneurial teams where decisions are often made collaboratively under high uncertainty, these dynamics are even more pronounced. The Upper Echelons perspective thus provides a strong theoretical foundation for analyzing how diversity across demographic (e.g., age, gender, education), informational (e.g., functional and industry experience), and cognitive (e.g., personality traits, thinking styles, motivation) dimensions can impact team cohesion, communication, and ultimately, start-up success or failure (Berman, Shoham & Teltch, Reference Berman, Shoham and Teltch2024; Boling & Vecchiarini, Reference Boling and Vecchiarini2024; Qian, Zhang & Kuai, Reference Qian, Zhang and Kuai2024; Zhou & Rosini, Reference Zhou and Rosini2015). It has been suggested that diverse teams, with their proposed benefits of increased creativity and innovativeness (Sethi, Smith & Park, Reference Sethi, Smith and Park2002; Sundermeier & Mahlert, Reference Sundermeier and Mahlert2023), are considered particularly well-suited to address the complex, non-routine challenges typical of entrepreneurial ventures. Heterogeneous groups bring a broader range of perceptions, skills, and knowledge, which enhances their ability to process information, adapt to change, and generate innovative solutions (Kakarika, Reference Kakarika2013; Zhou & Rosini, Reference Zhou and Rosini2015). Empirical evidence confirms that team diversity improves cognitive task performance, including creative problem-solving, strategic decision-making, and overall performance (Martins & Sohn, Reference Martins and Sohn2022; Qi et al., Reference Qi, Armstrong, Yang and Li2022). Linder et al. (Reference Linder, Lechner and Villani2025) demonstrate that informational diversity expands the cognitive resources required for exploring and developing creative solutions. Additionally, diverse entrepreneurial teams engage in faster learning and iterative experimentation, key capabilities for early-stage ventures. In the same vein, Wei et al. (Reference Wei, Mo, Zhang and Yang2024) suggested that so-called informational diversity (e.g., differences in educational and professional backgrounds) can act as an initial resource, generating positive stress (challenge stress) that stimulates team involvement and improves overall performance. Ma et al. (Reference Ma, Xiao, Guo, Tang and Singh2022) reinforced this perspective by showing that informational diversity can promote knowledge sharing and strengthen team stability, especially in culturally collectivist-oriented contexts. Su et al. (Reference Su, Luo, Lau and de Jong2024) found that variation in entrepreneurial passion within teams promotes resilience and sustained effort under uncertainty. Also, Kier and McMullen (Reference Kier and McMullen2020) demonstrated a positive relationship between imaginativeness diversity and the quality of new ideas that are generated.
Despite existing research emphasizing the positive effects of team diversity, numerous negative effects can also arise (Yoo, Lee & Lee, Reference Yoo, Lee and Lee2024). Amason, Shrader and Tompson (Reference Amason, Shrader and Tompson2006) found that diversity in age, education, and experience negatively affects the sales of startups operating in highly dynamic environments. Bjørnåli and Aspelund (Reference Bjørnåli and Aspelund2012) and Pinelli, Cappa, Franco, Peruffo and Oriani (Reference Pinelli, Cappa, Franco, Peruffo and Oriani2020) showed that age and educational diversity hinder international growth and funding. Blank and Carmeli (Reference Blank and Carmeli2021) noted that experience diversity reduces investment opportunities. Zhang and Wang (Reference Zhang and Wang2017) linked educational and experience diversity to lower profitability. Differences in personality, passion, and motivation (Boone & Hendriks, Reference Boone and Hendriks2009; De Mol, Cardon, de Jong, Khapova & Elfring, Reference De Mol, Cardon, de Jong, Khapova and Elfring2020; Heckhausen, Reference Heckhausen2013) increase conflict and weaken team cohesion.
Despite these insights, the extant literature fails to identify the impact of entrepreneurial team diversity in the context of venture survival. Existing research focuses disproportionately on short-term performance indicators rather than the existential risk of start-up failure. In addition, much of the existing literature fails to contextualize the effects of team diversity within the dynamic processes of the start-up journey. Focusing primarily on contextual factors such as team cohesion and conflict and environmental conditions, studies overlooked the evolving nature of diversity’s impact at different stages of development. The extant literature assumes that the composition of entrepreneurial teams remains the same as start-up growth. However, this is not a plausible assumption because entrepreneurial teams are defined as ‘open, dynamic systems’ (Sundriyal, Lévesque, Wennberg & Norgren, Reference Sundriyal, Lévesque, Wennberg and Norgren2024). As suggested by several studies, entrepreneurial teams are not fixed entities, but they adapt and evolve alongside the growth and development of their ventures (Patzelt et al., Reference Patzelt, Preller and Breugst2021; Yusubova, Andries & Clarysse, Reference Yusubova, Andries and Clarysse2020). Failing to consider how the impact of diversity evolves as start-ups progress through different stages, such analyses miss critical insights into the changing needs and challenges of entrepreneurial teams. To support this dynamic perspective, research on technology start-ups has shown that teams with strong technical expertise are most effective during the initial stages of idea generation and product development. In contrast, as start-ups transition to commercialization and growth, combining technical and commercial expertise becomes essential for success (Yusubova et al., Reference Yusubova, Andries and Clarysse2020). Similarly, Tzabbar and Margolis (Reference Tzabbar and Margolis2017) demonstrated that the positive effects of founding team human capital, such as educational heterogeneity and diverse experience, are more pronounced in the growth stage compared to the early stage. In the early stages, alignment among team members regarding goals, beliefs, and abilities is particularly critical for creating a cohesive vision (Chen & Kanfer, Reference Chen and Kanfer2006). Additionally, Muñoz-Bullon, Sanchez-Bueno and Vos-Saz (Reference Muñoz-Bullon, Sanchez-Bueno and Vos-Saz2015) found that diversity in industry and start-up experience is vital for moving a venture from the conception to the creation phase. In sum, these studies highlight the importance of tailoring team diversity to the specific requirements of each development stage.
To address this critical gap, the present study adopts a dynamic lens to investigate the underexplored dark side of entrepreneurial team diversity. Unlike prior research that focuses predominantly on successful ventures, this study uniquely examines failed start-ups across distinct developmental stages, aiming to identify which diversity characteristics may undermine team effectiveness and compromise venture survival. In doing so, it offers a nuanced, stage-contingent understanding of entrepreneurial team diversity, contributing to a more realistic and actionable framework for team design and management in entrepreneurship.
Methodology
Since the present study aims to understand which entrepreneurial team diversity characteristics were decisive in the start-up failure, a post-mortem analysis was performed (Dobusch, Köster, Schäfer & Seckler, Reference Dobusch, Köster, Schäfer and Seckler2022).
Post-mortem analysis involves examining outcomes retrospectively, often called ‘research in the past.’ According to Dingsøyr (Reference Dingsøyr2005), retrospective analysis can be a ‘collective learning activity that can be organized for projects when they complete a phase or are terminated. The main motivation is to reflect on what happened in a project to improve future practices for the individuals involved in the project and the organization as a whole.’ This methodological approach is multifaceted and highly adaptable, with applications across various fields. For instance, it can be used to evaluate a project’s final product, as reported by Zhang and Iyer (Reference Zhang and Iyer2007), or to enhance software design estimation through process simulation, as demonstrated by Aguilar-Ruiz, Ramos, Riquelme and Toro (Reference Aguilar-Ruiz, Ramos, Riquelme and Toro2001). Typically, post-mortem analysis represents a knowledge management tool in small and medium-sized software projects (Schieg, Reference Schieg2007). As start-ups can be considered small projects, this work employs a post-mortem analysis to understand the reasons for their failure.
In this context, post-mortem analysis is a useful methodological approach for tracing and understanding the sequences of events, decisions, and factors that influenced the evolution of start-ups (Dingsøyr, Reference Dingsøyr2005; Schieg, Reference Schieg2007). The choice of post-mortem analysis is motivated by its ability to provide a systematic framework for understanding the underlying dynamics of failure, particularly for start-ups in the early stages of development. The retrospective approach allows for a detailed mapping of the milestones reached, with a focus on the diverse attributes of the entrepreneurial teams that contributed to the failure. Since the authors did not have the team’s availability but a different set of documents, a document-based post-mortem analysis method proposed by Ahonen and Savolainen (Reference Ahonen and Savolainen2010) was employed. This approach is distinguished by its adaptability and ability to analyze documentary information where the availability of primary data is limited (Ahonen & Savolainen, Reference Ahonen and Savolainen2010). This methodological approach follows three steps:
1. In the data collection, the data were collected and specified from which documents the information was derived.
2. In the second step, the cases were analyzed regarding the main issues and problems of team diversity at the different stages of the project process.
3. In the last step, the causes of failure were presented.
Data collection
The data for this study, derived from secondary sources, were collected through the Failory database, a platform dedicated to sharing detailed stories and reflections on business failures. Failory offers a rich repository dedicated to startup founders and teams, offering over 200 interviews with failed and thriving startups, over 100 blog articles on various aspects of building and managing startups, and analyses of why over 200 startups and company projects have failed. The website also features a collection of tools and resources to assist entrepreneurs in their ventures. Failory was chosen over other databases (e.g., Crunchbase or CB insights) because it provides deeper insight into businesses’ challenges rather than just financial outcomes. While platforms like Crunchbase or CB Insights focus mainly on financial information like funding rounds, valuations, and market performance, Failory captures the real reasons behind business failures through experiences and lessons learned. This makes it especially valuable for understanding what went wrong, how, and why, offering perspectives beyond metrics. Moreover, Failory database is particularly relevant because it organizes failure interviews by reconstructing them across three distinct development stages: idea development, product conception and development, and launch. This structured approach allowed us to analyze failures consistently across different phases of the startup journey, aligning with the research question and providing a clearer understanding of challenges at each stage. The data were collected following a rigorous multi-stage selection process to ensure the data collected was highly relevant and aligned with the research question. This approach followed three systematic stages, carefully extracting information from the dataset to maintain the focus on the scope of the study:
1) The Failory database includes over 200 interviews featuring start-ups at various stages. At this preliminary stage, only cases that explicitly documented experiences of failure were selected. Success stories and start-ups that were still operational were excluded, ensuring the focus remained solely on understanding the factors contributing to failure.
2) Since the study aims to examine the impact of team diversity, only start-ups with a team-based structure were included. Start-ups led by a single founder were excluded to maintain a consistent analytical focus on team dynamics rather than individual behavior. This step ensured that the dataset was directly relevant to the study’s exploration of challenges related to entrepreneurial team composition.
3) In the final stage, the authors carefully reviewed each narrative to identify cases where the failure of the start-up was linked to team characteristics and governance dynamics. This step was essential to isolate cases where team-related factors played a critical role in the outcome, ensuring that the study’s findings would be precisely targeted and meaningful.
This selection process reduced the final sample to 10 interviews, each with detailed and in-depth information, allowing for a retrospective analysis of the team’s development stages and diversity characteristics. Specifically, the final sample comprises innovative startups that failed at different developmental stages (See Table 1). This variation allows for a comprehensive assessment of how entrepreneurial team diversity influenced survival at distinct stages.
Table 1. Sample description
Subsequently, a data triangulation strategy was employed to enhance credibility and mitigate potential biases from self-reported failures. This involved cross-verifying Failory interviews with additionally publicly available secondary sources, including:
1) Websites or personal blogs (e.g., Medium, Startup Graveyard series, and Indie Hackers blog) where founders and team members shared additional perspectives on their experiences.
2) Podcasts or team member interviews published on platforms other than Failory provide alternative interviews and deeper insights into their decision-making processes and failure reflections.
3) Online articles, social media posts, and other news items related to the history of the analyzed start-ups (e.g., LinkedIn, Twitter, TechCrunch, and Business Insider), which offered external validation and broader industry perspectives on each startup’s trajectory.
By systematically cross-referencing these different sources, we could distinguish between perceived and actual causes of failure. This triangulation approach allowed for a more nuanced and credible exploration of the role of team diversity in startup survival. Rather than relying on a single retrospective account, the study constructed a multi-layered understanding of failure, ensuring that its conclusions were not just reflections of individual memory but a broader synthesis of entrepreneurial realities.
Data analysis
The study employed an inductive qualitative analysis guided by Gioia’s methodology (Gioia et al., Reference Gioia, Corley and Hamilton2013) to map crucial diversity characteristics. The analytical process was designed to be iterative, rigorous, and methodologically structured, ensuring both depth and clarity in interpretation (Ratten, Reference Ratten2024; Valenza, Zoppelletto & Fazio, Reference Valenza, Zoppelletto and Fazio2024). The coding process was supported by NVivo 12, a widely recognized Computer-Assisted Qualitative Data Analysis Software (CAQDAS), increasingly adopted in inductive and grounded theory-based studies to ensure rigor, transparency, and analytical coherence (Hess & Lebraty, Reference Hess and Lebraty2025; Maher, Hadfield, Hutchings & De Eyto, Reference Maher, Hadfield, Hutchings and De Eyto2018; Nowell, Norris, White & Moules, Reference Nowell, Norris, White and Moules2017; Woods, Paulus, Atkins & Macklin, Reference Woods, Paulus, Atkins and Macklin2016). The use of this software contributed to enhancing trustworthiness and transparency of the research process. As a recognized qualitative research tool, it facilitated systematic data organization, structured coding, and interpretative consistency (Woods et al., Reference Woods, Paulus, Atkins and Macklin2016). This software allowed for efficient management of a large volume of qualitative data, ensuring that coding remained structured, replicable, and analytically transparent. Thus, rather than serving merely as a technical tool, its use enabled the researchers to systematically conduct open coding, facilitate the emergence of first- and second-order themes, and engage in iterative comparative analysis across multiple narrative cases central to the Gioia methodology approach. In addition, NVivo supported the maintenance of a comprehensive audit trail, thereby reinforcing the trustworthiness and reproducibility of interpretive decisions (Paulus & Lester, Reference Paulus and Lester2024).
The coding process followed Gioia’s three-stage approach, ensuring a structured and methodical transition from raw data to theoretical insights (Perotti, Dhir, Ferraris & Kliestik, Reference Perotti, Dhir, Ferraris and Kliestik2024). The first stage, first-order coding, required deep engagement with the data. Researchers conducted multiple close readings of data transcripts, allowing key concepts to emerge organically without imposing preconceived theoretical assumptions. This stage focused on capturing participants’ perspectives in their own words, ensuring that first-order codes remained informant-centric and reflective of their lived experiences. The authors independently coded the data to strengthen interpretative reliability before coming together to compare results. Any discrepancies were openly discussed, refined, and reconciled, ensuring that the emerging codes maintained coherence and consistency.
During this phase, diversity-related attributes were identified based on how team members described internal challenges in their narratives. For example, statement such as ‘My business co-founder and I were extremely opposite characters’ or ‘The CTO focused on tech, the CEO favored commercial simplicity’or ‘Seniors valued stability; juniors pushed innovation’ were initially coded under informant-centric categories respectively: ‘divergent characters between co-founders’; ‘divergent priorities from different background’; ‘Young member prefer to innovate while senior resit to change.’ Moving to the second stage, second-order coding, researchers transitioned from descriptive first-order concepts to a more abstract level of interpretation. At this stage, the researchers moved beyond the informants’ language and began identifying patterns and relationships between first-order codes, clustering them into higher-level themes that revealed deeper conceptual structures. Rather than relying solely on frequency, these second-order themes were developed based on their relevance to the research question and their potential to contribute to theoretical understanding. To ensure analytical precision, the research team applied Patton’s (Reference Patton1990) dual judgment criteria, rigorously evaluating each theme’s internal coherence, ensuring logical consistency within categories and its external distinctiveness, and ensuring themes remained conceptually distinct. This process was highly iterative, involving continuous dialogue and refinement within the research team to strengthen conceptual clarity and theoretical contribution. For example, the first order codes ‘different idea about what was a priority,’ ‘favouring complex solutions vs simplicity,’ and ‘disagreement on which features prioritize,’ each derived from informant quotes, together were clustered into a second order theme called ‘difference in ideas.’ In the final stage, second-order themes were synthesized into aggregate dimensions, forming a structured framework that facilitated theoretical development (Magnani & Gioia, Reference Magnani and Gioia2023). This process ensured that emergent insights were integrated into a coherent conceptual model. For example, the second order codes ‘difference in passion,’ ‘difference in personality,’ ‘difference in ideas’ and ‘difference in vision’ that together were grouped under a second-order theme, where finally synthesized into an aggregate dimension “personality and cognitive diversity.
The final data structure, presented in Figure 1, follows Gioia et al. (Reference Gioia, Corley and Hamilton2013) systematic approach, illustrating how raw qualitative data was transformed into a higher-level theoretical insight.
Figure 1. Data structure.
Once the key entrepreneurial team diversity characteristics had been coded using Gioia’s methodology, the authors employed a post-mortem analysis approach (Ahonen & Savolainen, Reference Ahonen and Savolainen2010) to contextualize the negative effects of these dimensions within each start-up’s developmental trajectory (Dingsøyr, Reference Dingsøyr2005; Schieg, Reference Schieg2007). This approach allowed for a nuanced understanding of how specific diversity factors contributed to failure by embedding them within the temporal evolution of each firm. Specifically, to ensure analytical consistency and transparency, the authors analyzed in depth each case by considering two key elements: (1) the specific diversity characteristics that emerged from the coding process, (2) the specific stage of the start-up’s development where these characteristics produced concrete effects, contributing to the start-up’s failure.
To do so, the authors relied on detailed firm histories to construct comprehensive timelines, systematically tracing which entrepreneurial team diversity attributes were crucial across the ideation, product development, and launch phases. The authors ensured a structured and longitudinal approach to understanding how diversity factors influenced firm trajectories by meticulously documenting key events, decisions, and team dynamics (Dingsøyr, Reference Dingsøyr2005; Dobusch et al., Reference Dobusch, Köster, Schäfer and Seckler2022; Schieg, Reference Schieg2007).
To ensure methodological rigor, the analysis followed a structured and iterative process. The research team meticulously documented key events, strategic decisions, and team interactions for each case, facilitating a consistent phase-by-phase comparison. Through repeated readings and case-level synthesis, diversity dimensions identified during coding were aligned with failure events, allowing for pattern recognition and causal inference (Langley, Reference Langley1999). Throughout this process, the authors engaged in iterative and reflexive discussions to critically examine their interpretations, ensuring consistency, theoretical depth, and methodological rigor. Discrepancies in coding, case interpretation, and narrative reconstruction were addressed through a structured, multi-step validation protocol. This involved independent analysis of each firm’s history, followed by collaborative review sessions to reconcile divergent perspectives and achieve analytical alignment (Ralph, Birks & Chapman, Reference Ralph, Birks and Chapman2015). To further enhance reliability and reduce interpretive bias, the authors triangulated internal interpretations with external secondary sources, subjecting firm interviews to multiple rounds of cross-case comparison and validation (Nowell et al., Reference Nowell, Norris, White and Moules2017). The refinement process included systematically re-reading firm histories and failure accounts to uncover overlooked temporal patterns, reassess causal linkages, and contextualize entrepreneurial team diversity dynamics within broader organizational trajectories. This multi-layered and iterative approach facilitated a deeper understanding of the mechanisms by which specific diversity characteristics contributed to team dysfunctions and consequently to start-up failure. In doing so, the applied processes reinforced the internal validity of the study and supported a robust and transparent synthesis of results (Gioia et al., Reference Gioia, Corley and Hamilton2013; Patton, McKegg & Wehipeihana, Reference Patton, McKegg and Wehipeihana2015).
For example, statements such as ‘we had completely different ideas about what we were building’ and ‘we spent more time arguing than executing’ were linked to cognitive and personality diversity, and were mapped to the ideation stage, where the absence of a shared mental model and persistent interpersonal tension led to strategic misalignment and decision paralysis. In this early phase, where clarity of vision and rapid convergence on goals are essential, such divergences significantly undermined team cohesion and slowed the development of a unified business concept.
A quote like ‘our engineering team pushed for complexity while the business side needed speed’ reflected deep informational diversity, especially in terms of functional experience and priorities. This was associated with the product development stage, where the misalignment between technical and commercial logics compromised the team’s ability to make timely trade-offs between product features and market readiness. Finally, quotes such as ‘I chose partners who were unfit to help run the business and were not passionate about the vision of the company’ and ‘The older team members prioritized stability and risk avoidance, while the younger ones wanted to push boundaries and innovate’ that respectively reflect personality and demographic diversity, they were linked to the launch stage, where the differen level of passion and divergent generational perspectives gave rise to emotional disengagement, delayed decision-making, and affective conflict. These internal misalignments ultimately undermined the team’s ability to execute under pressure, sustain momentum, and respond effectively to external demands during market entry.
Findings
Idea development stage
The ideation phase is a crucial foundation-setting stage where founders define their strategic vision and align on core business objectives. However, this phase often exposes critical challenges related to diversity in thought processes, working styles, and decision-making approaches. One of the most significant barriers to progress at this stage is the emergence of substantial personality and cognitive diversity issues, where profound ideological differences lead to conflicts that directly impact the venture’s survival.
A key theme from the analysis is the differences in thought processes and ideas that generate deep conflicts that slow down the start-up’s progress. This misalignment not only reduces decision-making efficiency but also leads to the fragmentation of resources and significant delays:
‘We were building too many ideas at once without focusing on a single direction. This spread our resources thin and made it impossible to move forward effectively.’
Beyond strategic misalignment, personality differences among co-founders further exacerbate tensions. While cognitive diversity can foster creativity, it frequently results in friction when co-founders lack prior experience working together. Without a shared history or an understanding of each other’s values and working styles, conflicts become more pronounced:
“My business co-founder and I were extremely opposite characters, and at times, there was a great synergy, but more and more often, this led to a lot of friction. Also, co-founders should probably have known each other for more than a year before, but we just met for the venture.
Product conception and development
The transition from ideation to product development marks a critical juncture where the vision must be transformed into tangible outputs. This phase demands intense collaboration among entrepreneurial team members, leading to frequent interactions that can both strengthen and challenge team cohesion. Personality diversity and informational diversity are key factors significantly influencing start-up survival.
One of the primary barriers at this stage is the differences in vision among founders, which can slow down progress and introduce tensions that threaten start-up stability:
‘We were not aligned on a shared vision for what to build, how to build it, and our core motivations for starting our own company. I realized we would fail after it became apparent that we spent more time debating, negotiating, and arguing each day than simply acting and doing.’
At the same time, differences in background can also create significant obstacles when team members come from different functional areas with contrasting priorities and approaches.
One of the key challenges described was the divergence between the CTO and CEO, whose different professional backgrounds led to friction in decision-making:
‘The CTO had a very technical approach, while the CEO pushed for more commercially straightforward solutions.’
Similarly, the tension between the engineering and marketing teams illustrated how diverse backgrounds could impact collaboration:
‘The engineering team insisted on building complex features unnecessary for the initial product, while the marketing team kept pushing for simplicity and speed.’
Launch stage
As a start-up reaches the launch phase, personality diversity and demographic diversity are crucial. The analysis highlights that differences in passion emerge as a critical factor influencing survival. Passion fuels the resilience needed to navigate the unpredictable nature of start-up launches, but unevenly distributed can lead to burnout and discord. The passion and diversity between team members created a serious obstacle, as the energy and commitment needed to drive the business forward. Passion was a fundamental force in navigating the chaos of the launch.
‘The reason things did not work out is that I chose partners that were unfit to help run the business and were not passionate about the vision of the company.’
The intensity of passion, especially when unevenly distributed among team members – can lead to burnout. When the rest of the team does not match one person’s drive, it can result in exhaustion, frustration, and, ultimately, disillusionment
‘Things did not work out because partners were unfit to help run the business and were not passionate about the company’s vision […] Running a team on passion and love brings real dangers. My favorite definition of burnout is ‘unrequited love’
Another critical aspect is that differences in age prove to be a crucial factor, amplified considerably in the launch phase of a start-up. While senior members bring with them established experience, they often find themselves at odds with the new generation pushing for rapid and innovative changes:
‘The older team members prioritized stability and risk avoidance, while the younger ones wanted to push boundaries and innovate. These clashes delayed critical decisions’
Discussions
The study highlights the importance of contextualizing the effects of entrepreneurial team diversity within the different developmental stages of start-ups (Muñoz-Bullon et al., Reference Muñoz-Bullon, Sanchez-Bueno and Vos-Saz2015; Patzelt et al., Reference Patzelt, Preller and Breugst2021; Tzabbar & Margolis, Reference Tzabbar and Margolis2017). The results reveal that the impact of diversity is highly dynamic, varying in nature across different phases of start-up development, thereby challenging the conventional static perspective found in much of the existing literature (Amason et al., Reference Amason, Shrader and Tompson2006; Bjørnåli & Aspelund, Reference Bjørnåli and Aspelund2012; De Mol et al., Reference De Mol, Cardon, de Jong, Khapova and Elfring2020; Pinelli et al., Reference Pinelli, Cappa, Franco, Peruffo and Oriani2020).
Unlike previous studies, which predominantly highlight the benefits of diversity in team composition (Sundermeier & Mahlert, Reference Sundermeier and Mahlert2023; Zhou & Rosini, Reference Zhou and Rosini2015), this study introduces a nuanced, stage-specific perspective that critically examines its potentially negative effects on start-up survival.
This study advances the existing literature by proposing a conceptual framework (see Fig. 2) that integrates two crucial dimensions: team diversity attributes and the distinct phases of a start-up’s lifecycle, enhancing the understanding of how team diversity characteristics (demographic, informational, and personality) influence start-up survival.
Figure 2. Proposed conceptual framework for the negative effects of entrepreneurial team diversity on venture survival in the different stages of development.
The findings shed light on the ‘dark side’ of team diversity, demonstrating that while heterogeneous teams may bring valuable knowledge and expertise, the misalignment of perspectives, skills, and motivations can pose significant risks, particularly at a critical juncture of the venture life cycle.
The study contributes to entrepreneurial team literature by extending prior research (Tzabbar & Margolis, Reference Tzabbar and Margolis2017; Yusubova et al., Reference Yusubova, Andries and Clarysse2020), emphasizing the pre-launch phase, which has been largely overlooked. The early stages – idea conception, product development, and initial launch – are particularly susceptible to the disruptive effects of team diversity.
The findings reveal that personality diversity is particularly disruptive in the idea development stage, where foundational strategic decisions are relevant. While cognitive diversity can foster creative solutions (Kakarika, Reference Kakarika2013), it also introduces friction, misalignment, and decision paralysis (Harrison & Klein, Reference Harrison and Klein2007). In this vein, the analysis suggests that deep ideological and cognitive misalignments among co-founders hinder consensus, leading to stagnation and delaying or even derailing venture progress. Moreover, the present study extends the study of Boone and Hendriks (Reference Boone and Hendriks2009) by providing empirical evidence that personality-based separation exacerbates emotional conflicts, particularly in the earliest phases of a venture’s lifecycle, where strategic cohesion is fundamental. Personality differences influence not only decision-making but also the ability of the team to sustain a shared vision, resulting in fragmentation and inefficiency. These findings highlight the critical challenge of personality diversity in early-stage entrepreneurial teams, emphasizing the need for strategies to mitigate its negative impact while preserving the benefits of diverse perspectives.
As ventures transition from ideation to product development, the combined influence of personality and informational diversity becomes critical in determining failure. While diverse expertise enhances problem-solving (Kakarika, Reference Kakarika2013; Zhang & Wang, Reference Zhang and Wang2017), it also introduces coordination challenges that can lead to strategic misalignment and inefficiencies (Bjørnåli & Aspelund, Reference Bjørnåli and Aspelund2012). The findings reveal that the interaction between personality diversity (conflicting strategic visions) and informational diversity (differing technical or commercial expertise) creates tensions that can slow or derail product development. One of the primary challenges in this phase is the misalignment between technical and commercial priorities. Although prior research suggests that heterogeneous expertise enhances adaptability and innovation (Sundermeier & Mahlert, Reference Sundermeier and Mahlert2023), the study highlights its downside concerning communication barriers and decision-making inefficiencies (Pinelli et al., Reference Pinelli, Cappa, Franco, Peruffo and Oriani2020). Diversity in educational background and professional expertise presents a significant challenge during this phase concerning tensions between technical and commercial team members, which were particularly disruptive, reflecting broader coordination challenges in high-novelty firms (Blank & Carmeli, Reference Blank and Carmeli2021). Conflicts between the engineering and marketing teams over product complexity versus market readiness underscore the difficulties of aligning functional priorities. The findings emphasize that informational diversity, combined with personality diversity, exacerbates the risk of fragmentation and slowed decision-making. While diverse problem-solving approaches can drive innovation, they also heighten the likelihood of strategic misalignment and execution delays. This reinforces the idea that the benefits of informational diversity are contingent on effective communication mechanisms and shared vision alignment.
Furthermore, the results suggest that personality diversity becomes even more critical in the launch phase, where differences in passion and commitment among team members are critical for venture survival. While passion is a key driver of entrepreneurial resilience (De Mol et al., Reference De Mol, Cardon, de Jong, Khapova and Elfring2020), its uneven distribution within a team leads to internal conflicts. This supports the argument that misaligned motivation and achievement orientation among entrepreneurs reduce team cohesion (Heckhausen, Reference Heckhausen2013). Passion diversity is a key destabilizing factor, intensifying team tensions at critical transition points. Moreover, in the launch phase, personality diversity interacts with demographic diversity, particularly age diversity, to create additional challenges. Older team members prioritized stability and risk aversion, while younger entrepreneurs sought innovation and speed, creating tensions that delayed key strategic decisions. This finding resonates with previous research suggesting that age similarity facilitates smoother collaboration in international partnerships (Bjørnåli & Aspelund, Reference Bjørnåli and Aspelund2012) and enhances decision-making efficiency (Amason et al., Reference Amason, Shrader and Tompson2006). The study extends these insights by demonstrating how age diversity hinders team consensus in high-pressure environments like start-up launches.
Conclusions
The present study aims to shed light on the negative effects of entrepreneurial team diversity, which is typically viewed as a strategic asset for achieving start-up success (Horvatinovic et al., Reference Horvatinovic, Mikic and Dabić2023; Santisteban et al., Reference Santisteban, Mauricio and Cachay2021; Soleimani & Stauffer, Reference Soleimani and Stauffer2024). Specifically, this study challenges the predominantly positive view of entrepreneurial team diversity, highlighting its critical role in entrepreneurial ventures and underscoring the importance of considering its dynamic effects across different developmental stages. Drawing on a retrospective approach (Ahonen & Savolainen, Reference Ahonen and Savolainen2010), rooted in a document-based post-mortem analysis of failed ventures, this study offers a critical reassessment of entrepreneurial team diversity by demonstrating that its effects on start-up outcomes are far more complex than traditionally assumed. Team diversity emerges as a dynamic and, at times, destabilizing force whose consequences are deeply contingent on the stage of venture development. The findings of this study call for a fundamental rethinking of how team diversity is understood and managed within entrepreneurial settings. Rather than viewing it as inherently beneficial or harmful (Zhou and Rosini; Sundermeier & Mahlert, Reference Sundermeier and Mahlert2023), diversity should be recognized as a dynamic force that evolves within the venture stage of development. This suggests that the true challenge lies not in assembling a diverse team but in learning how to navigate and adapt to the tensions that diversity inevitably brings as the venture evolves.
Theoretical implications
This study offers several theoretical contributions by challenging dominant narratives in the entrepreneurial team literature. First, it sheds light on the often-overlooked dark side of team diversity, offering a counterbalanced view to a vast body of research that predominantly emphasizes its positive implications, such as enhanced creativity, access to broader knowledge bases, and improved problem-solving. While these advantages are well established, our findings reveal that diversity can also hinder a start-up’s ability to survive, increasing the risk of internal friction, misalignment, and ultimately, failure. These negative effects are particularly relevant in early-stage start-ups characterized by uncertainty, limited resources, and time-sensitive decision-making. Thus, the study makes a significant contribution by shifting focus from successful ventures to failed start-ups, a perspective that remains underexplored in current empirical literature on entrepreneurial team diversity.
Secondly, the study challenges the conventional tendency to treat team diversity as a static, uniformly beneficial trait by introducing a dynamic, lifecycle-based perspective. Specifically, the study recognizes that the risks associated with team diversity vary across different stages of a venture’s development, challenging the way team composition is traditionally understood. In this context, this study extends the entrepreneurial team literature by explicitly addressing the negative consequences of diversity across different developmental stages. Following a combined approach, the present study matches the concept derived from the literature regarding entrepreneurial team diversity and the different stages of development of start-ups. This aspect has always been considered separately in existing studies when considering the potential adverse effects of team diversity. By incorporating the lifecycle perspective into team diversity research, the study provides a more nuanced understanding of how diversity shapes start-up outcomes over time.
In response to the urgent need to bridge this critical gap in literature, the study introduces a document-based post-mortem analysis as an original methodological approach that enables a retrospective reconstruction of failure trajectories, unveiling which specific diversity-related characteristics contribute to venture failure across different stages of development. By employing this approach, the study provides a deeper understanding of how personality, cognitive, informational, and demographic diversity affect entrepreneurial outcomes over time, offering a dynamic perspective on the impact of team diversity on venture survival. Through post-mortem analysis, the study provides empirical evidence that unresolved diversity-related tensions contribute directly to venture failure by disrupting decision-making efficiency, weakening strategic alignment, and fostering interpersonal conflict. These divisions lead to fragmentation, reduced cooperation, and an inability to reach consensus on critical business decisions, particularly damaging dynamics in resource-constrained start-ups where agility and cohesion are paramount. Moreover, the findings highlight that these negative effects are not uniform across all phases of venture development but become more pronounced as start-ups progress through different stages. In the early ideation phase, cognitive diversity can create a misalignment in strategic vision, delaying crucial go-to-market decisions. In the product development phase, conflicting informational backgrounds exacerbate functional silos, limiting collaboration between technical and business-oriented team members. Finally, in the launch phase, demographic diversity, particularly age diversity, amplifies tensions regarding risk preferences and operational execution.
Practical implications
From a practical point of view, this study offers suggestions to managers and founders involved in a start-up creation process, demonstrating that what is important is not only the entrepreneurial propensity but also the intrinsic characteristics of the people involved in the project as co-founders.
Differences in personalities, values, or ways of working, especially in the early stages, can hamper team cohesion and consequently the startup’s progress. Founders must ensure that team members bring complementary expertise and align on core business goals and decision-making processes to maintain cohesion and efficiency. Founders should not only consider the skills and knowledge of their team members but also their ability to work together effectively. During product development, founders must ensure that team members effectively communicate and collaborate. Diversity in backgrounds can bring new ideas, but it can also create confusion if people are not aligned on priorities or ways of working. Regular discussions and shared decision-making processes can help align different perspectives and reduce conflict, especially between technical and business roles. In the launch phase, differences in passion and age can become critical. Founders should openly discuss roles, responsibilities, and commitment levels to ensure balanced work by respecting different points of view, staying focused on shared goals. In this context, by adopting a structured, stage-sensitive approach to diversity management, startup leaders can capitalize on their advantages while minimizing potential pitfalls, ultimately fostering team cohesion, decision-making effectiveness, and long-term entrepreneurial success. In sum, managers should facilitate structured discussions to establish shared expectations, ensuring that early-stage conflicts do not stall progress. In addition, implementing cross-functional collaboration strategies, such as regular integration meetings and clear project ownership, can prevent functional silos and delays in execution. Also, founders must proactively monitor team motivation, ensuring an equitable distribution of responsibilities and fostering a culture of shared accountability to sustain momentum and resilience.
The findings of this study are also relevant for business accelerators and incubators that should go beyond technical and financial training by integrating diversity management modules into their startup development curricula. Providing training programs to equip founders with the skills necessary could help navigate the complexities of heterogeneous teams and better manage team dynamics, making a real impact.
Policy implications
From a policy-maker’s perspective, government-backed startup grants and funding programs should include diversity management training as a prerequisite for financial support. By integrating structured governance frameworks like advisory boards and team coaching incentives, policymakers can help startups develop the internal structures needed to manage team diversity effectively. Governments and startup hubs should provide financial incentives for ventures that invest in team-building programs and leadership development initiatives. Regulatory bodies might also introduce optional diversity audits, offering startups valuable feedback on how their team composition impacts their growth trajectory. Additionally, tax benefits could be extended to startups that actively engage in inclusive hiring and leadership training programs, reinforcing positive team management practices. By implementing these policies, the startup ecosystem can become more resilient, innovative, and inclusive, ultimately reducing failure rates and fostering long-term success.
Limitations of the study and future research
Despite its theoretical and practical relevance, this study has limitations that future research can address. Firstly, the analysis is confined to the launch phase, limiting insights into post-launch dynamics. Future studies should investigate what happens beyond the launch phase, comparing pre- and post-launch challenges and examining the impact of diverse entrepreneurial team compositions over time. Additionally, this study explores the effects of team diversity in failed start-ups. Future research should incorporate a control group of successful start-ups to determine whether factors contributing to failure may, in contrast, drive success. Such a comparative approach would enhance the understanding of the nuanced role of team diversity in entrepreneurial outcomes.
The sample analyzed is composed of 10 failed start-ups, which may limit the statistical generalizability of the findings to the broader population of entrepreneurial ventures. Despite the relatively small sample size, which is consistent with the study’s qualitative, exploratory purpose and post-mortem design, which prioritizes depth over breadth, the patterns observed in this study warrant further examination through larger-scale quantitative or mixed-method studies, which could test the robustness and generalizability of the proposed stage-specific diversity-failure mechanisms.
Data Availability Statement
This study is based on secondary data from publicly available narratives published on the Failory platform (https://www.failory.com/interviews). The data were accessed and analyzed in anonymized form. No new dataset was generated.
Author contributions
Conceptualization: [Adele Parmentola and Michele Costagliola di Fiore], Methodology: [Michele Costagliola di Fiore], Formal analysis and investigation: [Michele Costagliola di Fiore], Writing - original draft preparation: [Adele Parmentola and Michele Costagliola di Fior]; Writing - review and editing: [Adele Parmentola and Michele Costagliola di Fiore], Supervision: [Adele Parmentola]
Funding statement
The authors did not receive support from any organization for the submitted work.
Conflict(s) of Interest
The authors have no relevant financial or non-financial interests to disclose. The authors have no competing interests to declare that are relevant to the content of this article.
Ethical Standards
The paper has not been published elsewhere, and it has not been submitted simultaneously for publication elsewhere.
Adele Parmentola is full professor of Business Management at the Department of Management and Quantitative Studies (DISAQ), University of Naples Parthenope, where she teaches Business Management, International Innovation Network and Entrepreneurship. She is responsible for DISAQ’s Knowtrack accelerator of ideas and businesses and she is coordinator of various research projects on entrepreneurship and innovation. She was Data Manager of the Regional Entrepreneurship Aceleration Program carried out in collaboration with the Sloan School of Management at MIT (USA). She is the coordinator of the three-year course in Business Administration at the University of Naples Parthenope. She is the author of more than 100 publications in prestigious international journals on the topics of innovation ecosystems, business digitization, and new I4.0 technologies, entrepreneurship, and green innovation.
Michele Costagliola Di Fiore is a postdoctoral research fellow in Business Management at the Department of Management and Quantitative Studies (DISAQ) at the University of Naples Parthenope. His main research interests are entrepreneurship and new venture creation, specifically focusing on entrepreneurial teams and start-up performance. He is also interested in innovation management and digitalization, focusing on the dynamics concerning environmental sustainability. He has authored several contributions on topics such as team diversity in start-ups, Industry 4.0 technologies, digital transformation, and their impact on environmental sustainability and the circular economy.
Open access
