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The purpose of this article is to develop an integrative framework of accelerator design to answer the question of what activities accelerators perform and how they function within a structured framework. Research on the functioning of accelerators as a mechanism for startup engagement produced multiple empirical results. However, the comparability of relevant research is strongly limited, currently hindering theoretical developments. Existing accelerator design models often differ and only partially overlap, which leaves extant literature with a fragmented and discordant conceptual understanding.

Based on a meta-synthesis method using qualitative analysis of 36 accelerator design articles, an integrative framework is developed. After identification of relevant literature, a renowned method for extracting, coding and synthesizing data on individual and cross-study level is applied to identify accelerator design constructs. Eventually, identified accelerator design constructs are integrated into a framework resting on the activity system lens of business model design.

The article reconciles fragmented knowledge on accelerator design and shows how accelerator design can be holistically conceptualized by 32 key activities clustered in eight design dimensions. The framework is complemented by an initial guideline for measurement. The findings further highlight formerly disregarded aspects of governance and community formation from a processual and structural perspective.

This article is the first to present a comprehensive picture of accelerator design integrating multiple empirical findings of prior research into a single coherent framework. This framework offers a shared foundation for future research exploring the delineations, functioning and impact of accelerators. From a practical perspective, the article provides managers of accelerators a guide to design, review and improve programs according to their value creation goals.

This study aims to investigate a startup accelerator’s decisions toward exerting effort in an information acquisition process and selecting an information disclosure strategy. In particular, the authors are interested in examining which factors may cause the accelerator to report more or less accurate information, which will subsequently affect the investment decision and the outcome of the ventures. This study examines the impact of the equity share taken by the accelerator on the effort level being exerted in the information acquisition process, as well as the accelerator’s decision on the information disclosure regime.

The authors use mathematical models built upon well-established theoretical and practical concepts to analyze the research problems and derive the findings.

The authors show that when the accelerator takes a sufficiently large equity share from the entrepreneur in exchange for admitting the entrepreneur’s venture into the acceleration program, the accelerator is motivated to exert a significant level of effort to observe an accurate signal for the quality of the venture, and then disclose the information about the venture’s quality consistently with the observed signal (informative disclosure regime). On the other hand, if the accelerator takes a small equity share, it is optimal for her to exert no effort in the information acquisition process and simply adopt the basic disclosure regime, where the accelerator reports the quality of the venture based solely on the ex ante expected payoff of the venture, regardless of the observed signal.

The results indicate that an equity sharing scheme, which awards a sufficient amount of equity to the accelerator, can be an effective tool to help obtain accurate information about the quality of a startup venture and make a well-informed investment decision.

This research illustrates that the ownership stake of the accelerator can potentially indicate the accuracy of the information about the venture provided by the accelerator to outside investors. That is, when the stake held by the accelerator is large, the investors can conjecture that the information about the venture reported by the accelerator may be highly accurate and reliable. In contrast, if the accelerator holds a small stake, then it is likely that the information provided by the accelerator may not add any value to the publicly available information. These insights can guide investors (e.g. angle investors, venture capitalists, etc.) in making well-informed startup investment decisions.

This paper aims to review in-memory computing (IMC) for machine learning (ML) applications from history, architectures and options aspects. In this review, the authors investigate different architectural aspects and collect and provide our comparative evaluations.

Collecting over 40 IMC papers related to hardware design and optimization techniques of recent years, then classify them into three optimization option categories: optimization through graphic processing unit (GPU), optimization through reduced precision and optimization through hardware accelerator. Then, the authors brief those techniques in aspects such as what kind of data set it applied, how it is designed and what is the contribution of this design.

ML algorithms are potent tools accommodated on IMC architecture. Although general-purpose hardware (central processing units and GPUs) can supply explicit solutions, their energy efficiencies have limitations because of their excessive flexibility support. On the other hand, hardware accelerators (field programmable gate arrays and application-specific integrated circuits) win on the energy efficiency aspect, but individual accelerator often adapts exclusively to ax single ML approach (family). From a long hardware evolution perspective, hardware/software collaboration heterogeneity design from hybrid platforms is an option for the researcher.

IMC’s optimization enables high-speed processing, increases performance and analyzes massive volumes of data in real-time. This work reviews IMC and its evolution. Then, the authors categorize three optimization paths for the IMC architecture to improve performance metrics.

Entrepreneurial support programs, like incubators and accelerators, often offer mentorship to new ventures. However, existing research on mentoring has mainly focused on the entrepreneur's perspective, leaving researchers with limited understanding of why experienced mentors provide support to new ventures. This study aimed to explore mentors' motives in mentor–venture relationships and their impact on the advisory process. It also examined different types of mentors (social and commercial) and their motivations for assisting and supporting new ventures.

The present study utilizes a qualitative research approach to investigate the motivations and mechanisms through which new venture mentors assist founders in their growth and success. In-depth interviews were conducted with 18 mentors supporting both social and commercial ventures. These mentors were selected from ten accelerator and incubator programs situated in Belgium. The interviews aimed to gain insights into the mentors' motivations and their experiences in the role of mentors.

Based on the social exchange theory and the norm of reciprocity, this study identified two main motives of mentors: “gaining back” reflecting mentors’ self-interest in deriving benefits from the relationship and “paying back” representing their altruistic reasons for supporting new ventures. Additionally, the study identified mentor functions that primarily involved providing career-related support to new ventures. Moreover, the research revealed intriguing similarities and differences in the motivations and mentoring functions between mentors of social and commercial ventures.

Future research should explore the evaluation process and criteria used by mentors and new ventures when selecting each other for a productive mentoring relationship. Additionally, further investigation is needed to examine the firm-level impact of various mentoring services on the performance of social and commercial new ventures at different stages of development. Comparing mentor motives and functions across diverse geographical settings would address the limitation of the study and provide a more comprehensive understanding of the topic.

The findings of the study can inform policymakers, accelerator and incubator program managers and new ventures seeking mentors and support initiatives. They can use the insights to design effective mentoring programs that align with the specific needs and motivations of mentors and new ventures. Understanding the different motives and functions of mentors can help in the selection of appropriate mentors who can provide the necessary support and expertise to new ventures.

The study highlights the importance of mentorship in the development of entrepreneurial ecosystems. Accelerator and incubator programs play a crucial role in connecting new ventures with mentors who have the right motivation and expertise, contributing to the growth and success of new ventures and the overall entrepreneurial ecosystem. By identifying both altruistic and self-interest motivations in mentoring relationships, the study emphasizes the dual dimensions that characterize the mentor–venture relationship. This understanding can foster stronger collaborations and reciprocal exchanges between mentors and new ventures, ultimately benefiting both parties.

This research contributes to the entrepreneurship literature by exploring the mentor–new venture relationship from mentors' perspective. It expands the existing research on mentor–protégé relationships, broadening the understanding of mentoring dynamics in different organizational settings. The findings offer insights grounded in social exchange theory and provide directions for future research on mentor–venture relationships, resource exchange and relationship development. The study also holds practical implications for policymakers and program managers involved in fostering mentoring initiatives for new ventures.

This research aims at the theory of planned behavior (TPB) and the global entrepreneurship monitor (GEM) framework – How can cognitive traits for entrepreneurship be used by incubators and accelerators?

In this research the authors analyze the factors that catalyze the founding of new technology-based firms. From a practitioner stand-point, the GEM posits that these factors can be classified as contextual, social and individual factors. The present study focuses on the latter, looking into how demographic characteristics, possession of human capital and cognitive traits interrelate. The authors rely on a sample of 141 technological new ventures being incubated in Madrid, Spain, which is analyzed with the multilayer perceptron technique.

The results show that cognitive traits, as defined in the TPB, act as the “last mile” in the entrepreneurial decision process, while demographic and human capital factors appear to antecede them. These results are relevant for incubators and accelerators, which now gain a better, more complete understanding of success factors of their incubatees.

This research deals both with practitioners' view of entrepreneurship and with scientific literature, intertwining both with the purpose of providing valuable information for incubators and accelerators.

The purpose of this paper is to solve the issue of via filling and pattern plating simultaneously by concentration optimization of accelerator and leveler in the electroplating bath.

This paper designs a series of experiments to verify the performance of pattern plating with the via filling plating formula. Then the compositions of electroplating solution are optimized to achieve via filling and pattern plating simultaneously. Finally, the mechanism of co-plating for via and line is discussed in brief.

To achieve excellent performance for via filling and pattern plating simultaneously, proportion of additives are comprehensively considered in optimization of electroplating process. Effects of additives on the via filling and pattern plating should be taken into consideration, especially in achieving flat lines.

This paper discusses the different effects of accelerator and leveler on the via filling and the pattern plating, respectively. The process of co-plating for the via and the line is presented. The superfilling of via and the flat line are simultaneously obtained with the optimized via filling formula.

The purpose of this paper is to provide a systematic review of literature on corporate engagement with start-ups (CEWS) by identifying the modes, contexts, antecedents, barriers and outcomes. As an emerging field, CEWS presently has no such review available which will help in building consensus within the field and shape future research directions.

The study followed a two-phased systematic review of literature. Three research databases (i.e. Web of Science, ScienceDirect and SCOPUS) were accessed to gather and conduct the review. Of the total 379 papers retrieved, 63 total relevant papers were studied and analysed. The exhaustive review of literature helped to uncover the contexts, perspectives, antecedents, outcomes and barriers reported across the different modes of CEWS.

The study highlighted the five prominent modes of CEWS favoured by large corporations and start-ups. It found that the large corporations and start-ups associate with one another on the basis of complementarities of activities, resources and motives to pursue their strategic orientations. The engagements also face barriers on the ground, such as incompatibility of goals, power imbalances, cultural differences and weak engagement plans. Most important contexts seen were the high-technology industries in the developed economies like the USA and Europe. It also found that ecosystem creation, accessing innovation and corporate strategy have been preferred as the most productive modes of CEWS in the literature.

This review provides practitioners with a detailed list of the modes and drivers of CEWS. Subsequently, the barriers that need to be managed to successfully execute a specific mode of engagement. This shall enable the practitioners in developing and adopting the best practices while engaging with the start-ups to better facilitate the outcomes of CEWS.

To the best of the authors’ knowledge, there is no systematic literature review available in the domain of CEWS – thus, this study makes an important methodological contribution to the field. By consolidating the fragmented yet growing knowledge on CEWS, the study presents a detailed understanding of what drives and obstructs the engagement between large corporations and start-ups.

South Africa’s youth bulge provides both a potential asset and challenge for economic growth. The potential demographic dividend that this youth bulge represents can only manifest if youth are economically active. With youth unemployment above 51% and 7.6 million youth not in employment, education, or training − large numbers of youth are at-risk for long-term social and economic exclusion. This will only perpetuate structural inequality and poverty. In the context of extended lacklustre economic growth, the capacity of the formal economy to create large-scale employment is limited without active interventions to facilitate successful transition and entry into the labour market. This chapter explores the nature of youth transitions in South Africa. It examines the range of ‘failures’ that hamper successful transitions and presents a framework for conceptualising the role of labour market interventions in overcoming these. It then locates the Harambee Youth Employment Accelerator (Harambee) within the ecosystem of labour market interventions, describing its approach, evolution and the lessons that have emerged for how to support successful youth transitions.

Agrifood value chains in developing countries are transforming into higher value markets which require sustainable practices, with smallholders playing a critical role. However, smallholders are a heterogeneous group which may have discrepancies in outcomes to meet sustainability standards. This paper aims to empirically investigate smallholders' heterogeneity towards sustainable value chain practice in developing countries.

Eight key enabling factors of sustainable value chain transformation were used to explore smallholders' typology, then profiled, based on their socio-economic status and current practices. A quantitative method was applied in Indonesia's cashew sector with 159 respondents from the primary producer area on Madura Island. A combination of descriptive analysis, cluster analysis, cross-tab analysis and one-way ANOVA analysis was used in this study.

Four types of groups were identified, each with distinct characteristics and arranged in priority order as follows: accelerator, progressor, inattentive and conservative groups. Interventions can be implemented on per clusters basis or based on potential similarities among clusters, depending on priority. It is noted that the pursuit of sustainable value chain practices by smallholders is not necessarily associated with high socio-economic status, as those with low socio-economic status may have a stronger inclination towards them.

The paper enhances awareness of practitioners and policymakers regarding smallholders' heterogeneity in sustainable value chain practice. It enables more effective and focused interventions to support smallholders who require assistance in sustainable production and value-adding activities. Different smallholders' characteristics call for different assistance/intervention. Practitioners can recognise smallholders' characteristics that are more compatible with higher value markets and sustainability requirements to better integrate their practices. Policymakers must carefully develop short-term and long-term interventions based on the activities prioritised by particular traits to “hit the right button” for smallholders' practice development.

This study investigates the typology of smallholders towards sustainable value chain practices by using eight enabling factors and profiling them based on their socio-economic condition and current practices. Additionally, this study shifts the focus of typology exploration away from the traditional lens of farm sustainability to a larger perspective which encompasses sustainable value chain activities.

This paper aims to explore the challenges faced by start-ups during COVID-19 and highlight solutions for catering to the new-normal consumer behaviour. The study accounts for 15 deep-tech start-ups sailing through the pandemic and their responsiveness. This study brings forth insights and experiences from the Indian start-up founders and CEOs during COVID-19.

This study uses a qualitative approach and is exploratory and phenomenological. A purposive sample of 15 young start-ups founded between the years 2013–2020 by founders aged between 24 and 41 was selected for the study. The recorded telephonic interview was collected from the founders from April 2021 to September 2021. The thematic analysis of the study evolves from Braun and Clarke (2006) using the MAXQDA 2020.

The study emphasizes upon challenges faced by start-ups, crisis management of start-ups and the relevance of technology-based start-ups during challenging times. This research provides a qualitative framework to establish the role of the technology acceptance model (TAM) towards the adaptability, responsiveness and resilience demonstrated by the start-ups. The findings also highlight the solutions to address challenges faced by start-ups and road to recovery.

The study has great relevance and lessons for budding entrepreneurs during crisis management. The study has implications for corporations and governments in terms of setting up incubators and accelerators to support budding entrepreneurs.

The study is unique in highlighting the relevance and importance of TAM for start-ups during crisis management like COVID-19. The study thrusts upon the need of technology acceptance for better crisis management.