Entrepreneurial organizing activities and nascent venture performance

This research provides an improved understanding of how ventures successfully organize via resource allocations. Conceptually, we apply elements of action theory to account for resource trade-offs that occur as entrepreneurs make decisions about adding staff members to boundary spanning, technical core, and management functions. We then model how these allocation decisions differentially impact nascent venture performance. Empirically, we test our model with a sample of 2484 entrepreneurs captured in the Kauffman Firm Survey, a longitudinal dataset that tracks a random sample of US startups over an 8-year period. Results from dynamic panel estimation reveal evidence of both performance penalties and performance boosts as the result of entrepreneurs adding staff to specific areas, revealing optimality in specific configurations of entrepreneurial organizing elements.

Team Ventures and Acquisition Exits: Are Team-Founded Ventures More Likely to be Acquired?

We investigate whether team ventures are more likely to be acquired than single-founder ventures, and if so, attempt to determine what number of founders results in the highest acquisition likelihood. Using the Kauffman Firm Survey (KFS) of US businesses started in 2004, our results indicate that team-founded new ventures are more likely to be acquired, and that there is a positive and diminishing relationship between team size and acquisition likelihood. This study contributes to the understanding of drivers of exit for new ventures, and opens up the new venture exit literature to future contributions of a team demography approach.

Technical inefficiency of the manufacturing sector in Laos: a case study of the firm survey

PurposeThis study aims to unlock the path of growth for sustainable economic development and accomplish the government's vision 2030 by ameliorating the productivity of the manufacturing sector in Laos.Design/methodology/approachThis study applied cross-sectional data of 2,009 firms from the national firm survey, namely the Economic Census Survey (ECS), in 2012/13 in addition to employing the stochastic frontier analysis (SFA) to assess the production frontier and factors behind the technical inefficiency to arrive at policy recommendations.FindingsThe study found that the efficiency level varied across subindustries with an average of 72.51% in full potential production. Out of the five classified groups, Sub4 (chemical and plastic) was found to be the most efficient manufacturer, while the rest in order are Sub1 (food and beverage), Sub5 (furniture and others), Sub2 (garment and textile), and Sub3 (paper and printing), providing the evidence to improve the technical efficiency. This study discovered that the firm's size, accounting system and credit access are crucial to enhancing the production efficiency of all sampling firms. However, these factors might be subject to specific industries.Practical implicationsFor the implication to the business community and policymakers, the findings of this study could be a reference in terms of which areas they should concentrate on to improve the technical efficiency as a part of productivity in the manufacturing industry. For instance, it suggests that firms could improve their production efficiency by introducing the accounting system, laborers' skills (education of managers) and engaging in international trade activities. Additionally, it asks policymakers to help private firms by improving the infrastructure, credit access, training and trade facilitation.Originality/valueIt is believed that, as the major contribution in Lao literature, this study is the first research applying the largest data from the national survey – the Lao ECS – examining the technical efficiency in the manufacturing sector in the country, and overcoming the gap of the previous research which recruited few policy variables and applied a small sample size in one specific industry. Therefore, the findings of this study impart more insights into the analysis, providing more effective and credible recommendations to policymakers and firms to improve their technical efficiency and, consequently, their competitiveness.

How is Innovation Performance Under the Restriction of Industry Cluster: Evidence from a Survey on High-Tech Firms

Under-development of high-tech industry cluster hampers the strategy of innovation-driven for less developed regions. While prior studies has demonstrated innovation difference among regions, little attention has been paid to innovation heterogeneity at firm-level. An conceptual model is adopted to evaluate innovative activities of high-tech firms in under-development regions. Using unique firm survey, an investigation was thoroughly conducted on high-tech firms. Based on survey data of 142 high-tech firms, some interesting results emerge. Lack of support from industry cluster, depression effect of technological innovation is not obvious. SMEs have more inclination to innovate, asymmetry exist between occupation of innovative resources and innovation ability, and weak innovation agglomeration effect shows in two development zones. Further analysis on input-output efficiency of innovation indicate that, input-output efficiency of R&D funding is relatively good, but R&D personnel and innovation management are insufficient, which lead to low effective conversion effect.

Upgrading Italy's Industrial Capacity: Industry 4.0 across Regions and Sectors

How are Industry 4.0 investments distributed across Italian regions and sectors? Which are the main drivers of diffusion? To address these questions, in this study we exploit rich firm survey data on the adoption of the new digital technologies and examine their adoption patterns. On the one hand, we produce novel insights into the drivers of structural change in the Italian economy, and on the other, we provide evidence on the technological upgrading of Italy's production capacity that is relevant for policy. The results of econometric tests on region-sector pairs indicate that corporate governance characteristics, innovation patterns and type of industrial relations are significant predictors of the uneven regional and sectoral distribution of Industry 4.0 investments.

Factors Determining the Survival of New Companies

This article discusses the determinants of the survival of new companies, with particular emphasis on their sources of financing. We have analysed the impact of experience in the same focal industry, of having a competitive advantage and intellectual property rights (patents and trademarks) and of debt financing on the probability of a start-up's survival, using a logit model based on the Kauffman Firm Survey (KFS) database data covering 4,928 American companies which operated from 2004 to 2011. Additionally, we can demonstrate that start-ups that use debt financing have a better chance of staying in business. Factors such as intellectual capital and competitive advantage are also positively correlated with the prospects for start-up survival.

Money Matters: An Examination of the Impact of Financial Structure on Nascent Venture Performance; Evidence from the Kauffman Firm Survey

This study was carried out to empirically test the impact of financial structure on nascent enterprise performance. The study used a centralistic nomothetic longitudinal methodology to examine a panel data derived from the first four years of the Kauffman firm Survey (KFS). The result revealed that financial structure (equity financing, debt financing, and trade-financing) influenced nascent enterprise performance, but inconsistently over the first four years of business existence. The average capital structure of the sample was supported by the literature and followed the pecking order of equity, debt, and trade financing. Results suggested that capital structure has an important ramification for nascent enterprise performance, but the capital mix of successful nascent enterprises do not necessarily follow an orthodox format.