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The purpose of this paper is to explore how circular start-ups design and implement innovation into their business models to increase their positive impact.

This qualitative study is based on an exploratory multiple-case study involving six circular start-ups with positive impact in Poland. Data gathering took place via in-depth interviews with start-up founders.

The analysis demonstrates that three factors, which are strongly interconnected, can significantly influence the development of a circular start-up. The first is the purpose-led motivation for circularity as a solution, mostly concentrated on the environmental education of different market actors. The second factor is built on the aim to increase the positive impact by addressing the most pressing social and environmental problems. It determines the impact on society as well as on the environment and the extent to which its model can be scaled up. The third factor is driven by the understanding of the purpose of the innovation, concentrated on the business model innovation regarding circularity.

This paper demonstrates the benefits for diverse stakeholders and the importance of using circular business models in start-up development. Circularity can be perceived as a main part of the new approach to improve sustainability.

Circular start-ups represent a new phenomenon in the entrepreneurial market. While the structure and logic of the circular business model in start-ups are significantly unexplored in the management literature, this model is viewed as a crucial step in the direction of increasing the positive impact of start-ups. From a theoretical and practical perspective, it is important to understand the differences and similarities in this area within different markets.

Existing business model frameworks show weak conceptual unification, a paucity of measurement focus and limitations when applied in emerging economies. The study proposes a new business model framework – “Start-up Evaluation Calculus Using Research Evidence” (SECURE). The purpose of this study is to allow the measurement of the impact of business model design on start-up performance in emerging economies.

Data collected from 713 entrepreneurs in select cities of India, Oman and the United Arab Emirates is analyzed through structural equation modeling. The study uses measurement and structural models to examine the validity of measures and additionally tests the five hypothesized relationships proposed in the study.

The SECURE’s components comprising desirability, marketability, feasibility, scalability and viability showed validity and reliability. They synergistically demonstrated a statistically significant effect on a mix of financial and non-financial start-up performance outcomes. An alternative structural relationship that examined the impact of SECURE on only financial performance outcomes showed a weaker model fit. The findings indicate that a business model framework is useful when its ex ante measures show a positive causal effect on the desired performance outcomes.

The scores obtained by the SECURE framework serve as an evaluative tool that informs entrepreneurs and start-ups on the readiness of their proposed, incubated or existing start-ups.

Replacing subjective judgments with objective assessment criteria, SECURE is one of the first quantitative and performance-driven business model frameworks that contain measures from all functional domains of a start-up business. Start-ups can evaluate their business models against the SECURE model’s research-driven quantitative criteria and assess their impact on start-up performance.

Value creation based on artificial intelligence (AI) can significantly change global healthcare. Diagnostics, therapy and drug discovery start-ups are some key forces behind this change. This article aims to study the process of start-ups' value creation within healthcare.

A multiple case study method and a business model design approach were used to study nine European start-ups developing AI healthcare solutions. Obtained information was performed using within and cross-case analysis.

Three unique design elements were established, with 16 unique frames and three unifying design themes based on business models for AI healthcare start-ups.

Our in-depth framework focuses on the features of AI start-up business models in the healthcare industry. We contribute to the business model and business model innovation by systematically analyzing value creation, how it is delivered to customers, and communication with market participants, as well as design themes that combine start-ups and categorize them by specialization.

This paper aims to investigate the effect of business incubation metrics based on an adaptation of the lean start-up (LS) framework on start-up survival after incubation. This study also analyzes the obstacles in implementing the LS framework as incubation metrics.

This study uses mixed methods. Quantitative research using multiple linear regression was applied to the data of 30 start-ups incubated at Bandung Techno Park for the 2014–2017 period and survival tracking data after the incubation. A qualitative approach to complete the explanatory work was conducted through in-depth interviews with 12 respondents, including start-up graduates from the incubation program, program managers and mentors.

This study confirms that several LS incubation metrics significantly affect start-up sustainability after incubation. In addition, this study also explains several problems in applying the LS discipline that needs attention to increase incubation success.

Research was conducted only at one technology business incubator (TBI) model that focuses on digital start-ups in the emerging ecosystem. Research results can be biased in different situations and ecosystems.

The explanation of the relationship of LS-based incubation metrics to the survival of start-ups, as well as the challenges of their implementation, can be a reference for TBI management to consider and prioritize intervention strategies, thereby improving TBI’s business processes and increasing the success rate of incubated start-ups.

The creation of university start-ups and spin-offs has become a key performance indicator mandatory for technology universities in Indonesia. The existence of TBI institutions in universities as channels of technology commercialization is essential. The incubator’s success in creating a new technology-based company will have a significant social impact on the surrounding environment.

Although the LS method is popular in start-up communities and among practitioners, it is rarely used in the incubation process at universities. These results can be considered for university TBIs to explore LS as an incubation management tool to increase the success rate of incubated start-ups.

The purpose of this paper is to investigate the practices that start-ups in emerging economies can implement to design circular economy business models and how they can create and capture value from a circular economy business model.

The paper adopts a qualitative case method approach with semi-structured interviews with start-up founder promoters, its employees, its beneficiaries and its customers, conducted in two local Indian start-ups engaged in the manufacture of products and providing services that promote adoption of circular economy principles.

Analysis of the two business models reveals common patterns in building value proposition. The findings suggest that start-up ventures adopt an iterative approach to produce reusable and interlinked products and co-create with customers, vendors and local communities. They adopt mechanisms that can create, deliver and capture value while maintaining economic viability, and thus contribute towards micro- and macro-level benefits.

This study maximizes the depth of the phenomenon under investigation by leveraging case study methodology. Future research opportunities could be found in quantitative studies to increase the generalizability of the findings of this paper.

The paper presents a theoretical model linking the circular business model design and deployment mechanisms that can be used by start-up entrepreneurs desirous of embracing circular economy principles and thus contribute towards environmental, economic and developmental goals in emerging economies.

To accelerate the transition of adoption of circularity principles in emerging markets, start-up ventures could adopt circular business models that contribute towards achieving positive behavioural change. This can be achieved by integrating with different stakeholders in the value network such that they play a vital role in the process of value creation and delivery and benefit from the value captured.

An interdisciplinary approach that integrates the research streams of circular economy, and business model design has been pursued to identify the design and deployment mechanisms adopted in the circular business models of start-ups in real-world emerging economies’ context.

The purpose of this paper is to derive a taxonomy of business models used by start-up firms that rely on data as a key resource for business, namely data-driven business models (DDBMs). By providing a framework to systematically analyse DDBMs, the study provides an introduction to DDBM as a field of study.

To develop the taxonomy of DDBMs, business model descriptions of 100 randomly chosen start-up firms were coded using a DDBM framework derived from literature, comprising six dimensions with 35 features. Subsequent application of clustering algorithms produced six different types of DDBM, validated by case studies from the study’s sample.

The taxonomy derived from the research consists of six different types of DDBM among start-ups. These types are characterised by a subset of six of nine clustering variables from the DDBM framework.

A major contribution of the paper is the designed framework, which stimulates thinking about the nature and future of DDBMs. The proposed taxonomy will help organisations to position their activities in the current DDBM landscape. Moreover, framework and taxonomy may lead to a DDBM design toolbox.

This paper develops a basis for understanding how start-ups build business models capture value from data as a key resource, adding a business perspective to the discussion of big data. By offering the scientific community a specific framework of business model features and a subsequent taxonomy, the paper provides reference points and serves as a foundation for future studies of DDBMs.

Starting from corporate entrepreneurship, spin-off entrepreneurship and business model theory, this paper aims to examine the key influential factors and inherent mechanism in the process of business model transfer from parent enterprise to spin-off start-ups.

Grounded theory method is fit for constructing theoretical models, which can discover and interpret phenomenon and activities. According to the guidance of theoretical sampling and other core principles in grounded theory, this study extracts two parent enterprises named Haier and Phnix and lots of spin-offs derived from them.

This paper presents the theoretical framework that business models transfer from parents to spin-offs and probes into the embedding logic and connection relationship between factors and categories in this process, such as preconditions, incubation veins, business model elements, stripping mechanism and independent operations.

Although this study is focused on the manufacturing industry, the main characteristics, comparative advantages, governance rules summarized from transfer activities of business model in spin-off entrepreneurship can also bring inspirations to both parent enterprises and spin-off start-ups.

Excavates process and mechanism of business model transfer from internal to external, extends the theoretical perspectives about existing related theories such as corporate entrepreneurship, spin-off entrepreneurship and business model theory and reveals new approaches and methods on business model design, which is different from the past way.

The purpose of this paper is to investigate the nascent market settings from a business model innovation perspective with the research questions: How do incumbents and start-ups make sense of an emerging technology through business model design in a nascent market setting, and how does business model choice influence firm performance?

The authors have tracked the development of four case companies in the nascent electric vehicle market from 2009 to 2018 and have conducted interviews and analyzed the archival data.

The authors propose a typology of business model choices and performance where the four types of business models distinguish themselves by how the companies innovate or imitate the value proposition of the current industry as well as how they innovate or imitate the business model archetype. In accordance with these different business model choices, the actors express different logics behind their new to the product market space business model choice. These logics represent different understandings of technology potential, customer needs as well as potential for value capture and contribute to and limit the translation of emerging technologies into dominant designs in diverse ways.

The business model is conceived as a focusing device that can be used to identify market applications for emerging technologies. As new disruptive technologies often require a new to the product market space business model, literature has in recent years put a premium on business model innovation. However, the linkages between emergent technologies and the choice of a novel business model are under investigated especially in relation to how business model choice affects business performance in nascent market settings. This paper aims at filling this gap.

Digital freight forwarder (DFF) start-ups and their associated business models have gained increasing attention within both academia and industry. However, there is a lack of empirical research investigating the differences between DFFs and traditional freight forwarders (TFF) and the impact of digital start-ups on incumbents' companies. In response, this study aims to examine the key business model characteristics that determine DFFs and TFFs and propose a framework illustrating the extent to which digital logistics start-ups influence incumbent logistics companies.

Based on the primary data gathered from eight interviews with experts from start-ups' and incumbents' logistics companies, as well as secondary data, the authors identify the main factors of DFFs start-ups that have an impact on TFFs and analyze the similarities and differences in regard to the business model components' value proposition, value creation, value delivery and value capture.

The results show that differences between DFFs and TFFs appear in all four business models' components: value proposition, value creation, value delivery and value capture. In particular, the authors identify three main factors that need to be considered when assessing the impact of DFFs on TFFs: (1) the company size, (2) the market cultivation strategy and (3) the transport mode.

This is one of the first studies to specifically examine the key business model differences between DFFs and TFFs and to propose a conceptual framework for understanding the impact of digital logistics start-ups on incumbent companies.

Although it is acknowledged that entrepreneurial networks play a crucial role in fostering business model innovation (BMI) for start-ups, it is unclear how and when these networks affect BMI. This research developed a moderated mediation model to explore the impact of entrepreneurial networks on BMI in start-ups and examined the dual mediating effects of causation and effectuation, as well as the moderation of environmental dynamism.

The proposed framework was tested by hierarchical regression analyses and bootstrapping using samples of 248 start-ups in China.

The results showed that entrepreneurial networks significantly positively impacted start-up BMI. Causation and effectuation played dual mediating roles between entrepreneurial networks and BMI. Furthermore, the entrepreneurial networks-effectuation-BMI association was more substantial in highly dynamic environments, whereas the entrepreneurial networks-causation-BMI relationship was unaffected.

There are several theoretical contributions resulting from this research. The findings offer new insights for understanding the antecedents of start-up BMI from the network perspective. This research adds to the growing literature on resource orchestration (RO) by exploring the dual mediating influences of causation and effectuation in resource management. This investigation revealed the boundary condition between entrepreneurial networks and BMI by testing the moderating influence of environmental dynamism.

Start-ups must effectively use external resources embedded within networks to advance BMI. Start-up entrepreneurs should apply causation and effectuation to transform entrepreneurial network resources into BMI. Start-up entrepreneurs must dynamically manage resources in response to ever-changing environmental conditions. Resource acquisition and management of entrepreneurial networks can vary significantly in their influence on start-up BMI under different environmental contexts.

Unlike previous BMI research focused on internal organizational factors, this study highlighted the critical importance of entrepreneurial networks as a prerequisite for achieving start-up BMI, contributing to the literature on open innovation and resource-based view. Examining the dual mediating roles of causation and effectuation illustrated the bridging role of strategic decision-making logic in connecting resources to value creation, contributing to the developing RO literature. The moderating influence of environmental dynamism was explored, clarifying how start-up BMI benefits from entrepreneurial networks in differing situations. A framework for reconciling contradictory findings concerning the association between entrepreneurial networks and innovation is provided.