The Performance of University Spin-Offs: The Impact of Entrepreneurial Capabilities and Social Networks of Founding Teams during Start-Ups

Objectives: University spin-offs have increasingly received attention from academia, governments, and policymakers because they not only generate new innovations, productivity, and jobs the regional economies but also significantly improve university productivity and creativity (Hayter, 2013, Urbano and Guerrero, 2013). However, a lack of understanding of the contribution made by a founding team to a spin-off’s performance still remains within current studies. Employing a resource-based view theory and social networks approach, this paper addresses this gap by exploring university spin-offs in Spain. Prior work: University spin-off studies have concentrated on analysing entrepreneurial business models (Ndonzuau et al., 2002, Vohora et al., 2004b, Bower, 2003, Mets, 2010) to understand how the commercialization of research is undertaken to create a university spin-off. University spin-offs were also been analysed from the perspective of a university’s capabilities (Powers and McDougall, 2005), or capabilities and social networks of an established spin-off instead of the founding teams (Walter et al., 2006). Moreover, Vohora et al. (2004a) and Shane (2004) have suggested founders need to build capable teams, which must have entrepreneurial capabilities and qualitative social networks, to create effective university spin-offs. Both entrepreneurial capability and social network theory have been studied in prior entrepreneurship research, but have received less attention within the context of the university spin-offs (Gonzalez-Pernia et al., 2013). Approach: Utilising an internet-based survey, this paper explores entrepreneurial capabilities and social networks of founding teams in Spanish university spin-offs using quantitative data analysis. Basing upon resource-based view theory of Barney (1991) to study entrepreneurial capabilities of the founding teams, the research employ entrepreneurial technology, strategy, human capital, organizational viability, and commercial resources (see Vohora et al., 2004a). To study social networks of a founding team, we employ the conceptual model of Hoang and Antoncic (2003) that divides networks into three components: structure, governance, and content. Results and implications: The results from an examination of the sample of 181 Spanish university spin-offs empirically demonstrate that by exploiting social networks a founding team can improve its entrepreneurial capabilities, which in turn enhance its spin-off’s performance. By employing the work of Vohora et al. (2004a) and Shane (2004), this paper constructs a model in which entrepreneurial capabilities play a mediate role between social networks and spin-off’s performance. Thus, the paper has implications for universities in training and policy development to support spin-off’s activity. Value: This study addresses some fundamental questions to contribute to the theory-based understanding of university spin-offs: How do entrepreneurial capabilities of founding teams influence the performance of university spin-offs? How do social networks of founding teams contribute to the process of the university spin-offs

Taking Stock of the Digital Revolution: A Critical Analysis and Agenda for Digital, Social Media, and Mobile Marketing Research

Marketing has been revolutionized due to the rise of digital media and new forms of electronic communication. In response, academic researchers have attempted to explain consumer- and firm-related phenomena related to digital, social media, and mobile marketing (DSMM). This paper presents a critical historical analysis of, and forward-looking agenda for, this work. First, we assess marketing’s contribution to understanding DSMM since 2000. Extant research falls under three eras, and a fourth era currently underway. Era 1 focused on digital tools and platforms as consumer and marketer decision aids. Era 2 studied online communications channels (e.g., online forums) as word of mouth marketing “laboratories,” capturing the potential of DSMM for social information transmission. Era 3 embraced the notion of “connected consumers” by considering various antecedents and consequences of socially interconnected consumers in marketplaces. Era 4, currently starting, considers mobile marketing and brings psychological and social theories to bear on emergent DSMM issues. Second, we critique the DSMM literature and advance a series of recommendations for future research. While we find much to applaud, we argue that several problems limit the relevance of this research moving forward and suggest ways to alleviate these concerns moving forward

Does Empirical Embeddedness Matter? Methodological Issues on Agent-Based Models for Analytical Social Science

The paper deals with the use of empirical data in social science agent-based models. Agent-based models are too often viewed just as highly abstract thought experiments conducted in artificial worlds, in which the purpose is to generate and not to test theoretical hypotheses in an empirical way. On the contrary, they should be viewed as models that need to be embedded into empirical data both to allow the calibration and the validation of their findings. As a consequence, the search for strategies to find and extract data from reality, and integrate agent-based models with other traditional empirical social science methods, such as qualitative, quantitative, experimental and participatory methods, becomes a fundamental step of the modelling process. The paper argues that the characteristics of the empirical target matter. According to characteristics of the target, ABMs can be differentiated into case-based models, typifications and theoretical abstractions. These differences pose different challenges for empirical data gathering, and imply the use of different validation strategies.Agent-Based Models, Empirical Calibration and Validation, Taxanomy of Models

Twenty years of "Lipid World": a fertile partnership with David Deamer

"The Lipid World" was published in 2001, stemming from a highly effective collaboration with David Deamer during a sabbatical year 20 years ago at the Weizmann Institute of Science in Israel. The present review paper highlights the benefits of this scientific interaction and assesses the impact of the lipid world paper on the present understanding of the possible roles of amphiphiles and their assemblies in the origin of life. The lipid world is defined as a putative stage in the progression towards life's origin, during which diverse amphiphiles or other spontaneously aggregating small molecules could have concurrently played multiple key roles, including compartment formation, the appearance of mutually catalytic networks, molecular information processing, and the rise of collective self-reproduction and compositional inheritance. This review brings back into a broader perspective some key points originally made in the lipid world paper, stressing the distinction between the widely accepted role of lipids in forming compartments and their expanded capacities as delineated above. In the light of recent advancements, we discussed the topical relevance of the lipid worldview as an alternative to broadly accepted scenarios, and the need for further experimental and computer-based validation of the feasibility and implications of the individual attributes of this point of view. Finally, we point to possible avenues for exploring transition paths from small molecule-based noncovalent structures to more complex biopolymer-containing proto-cellular systems.711473 - Minerva Foundation; 80NSSC17K0295, 80NSSC17K0296, 1724150 - National Science FoundationPublished versio

UNDERSTANDING THE EVOLUTION OF INFORMATION SYSTEMS RESEARCH FROM THE PERSPECTIVE OF CO-AUTHORSHIP NETWORK: A COMPREHENSIVE DATA ANALYSIS FROM 1993 TO 2012

Based on the articles published in three top journals in the field of information systems (MISQ, ISR and JMIS) from 1993 to 2012, we conduct a research of the structure, characteristics and development trend of co-authorship network through scientometrics and social network analysis approaches. We gain a number of insights after synthetical analysis. In the last two decades the whole co-authorship network density in information systems faces a tendency of decrease. The co-authorship network presents properties of “small world”. The number of articles published by scholars and institutions in the three elite journals all display a ‘long tail’ phenomenon. The field of information systems has a stable development in the biggest component, and has not yet went into a mature and steady stage. Quite a lot of outstanding scholars and educational resources came from USA, Canada and Hong Kong, and USA has held eight institutions of the top ten. The ranking of an entire institution can be influenced by even one or two authors, indicating that outcome from one level might propagate to the next level

Integration and the hold-up problem in the design organization for engineering projects

The paper presents a perspective of the design organization in engineering projects based on the economic concept of the hold-up problem. By integrating the economic theories on the boundaries of organizations into the existing knowledge on design in engineering projects, the paper hypothesizes a theoretical framework that represents the design organization in the context of the hold-up problem. The framework is illustrated with findings from an interpretive study of a large-scale engineering project that faced design integration issues that are well explained by the hold-up problem. The findings suggest the specific nature of the hold-up problem in design organizations which calls for a managerial mindset based on the concept of the social network and relational contracting instead of the typical project management reasoning based on static hierarchies of scope and controlling mechanisms

Data Science in Supply Chain Management: Data-Related Influences on Demand Planning

Data-driven decisions have become an important aspect of supply chain management. Demand planners are tasked with analyzing volumes of data that are being collected at a torrential pace from myriad sources in order to translate them into actionable business intelligence. In particular, demand volatilities and planning are vital for effective and efficient decisions. Yet, the accuracy of these metrics is dependent on the proper specification and parameterization of models and measurements. Thus, demand planners need to step away from a black box approach to supply chain data science. Utilizing paired weekly point-of-sale (POS) and order data collected at retail distribution centers, this dissertation attempts to resolve three conflicts in supply chain data science. First, a hierarchical linear model is used to empirically investigate the conflicting observation of the magnitude and prevalence of demand distortion in supply chains. Results corroborate with the theoretical literature and find that data aggregation obscure the true underlying magnitude of demand distortion while seasonality dampens it. Second, a quasi-experiment in forecasting is performed to analyze the effect of temporal aggregation on forecast accuracy using two different sources of demand signals. Results suggest that while temporal aggregation can be used to mitigate demand distortion\u27s harmful effect on forecast accuracy in lieu of shared downstream demand signal, its overall effect is governed by the autocorrelation factor of the forecast input. Lastly, a demand forecast competition is used to investigate the complex interaction among demand distortion, signal and characteristics on seasonal forecasting model selection as well as accuracy. The third essay finds that demand distortion and demand characteristics are important drivers for both signal and model selection. In particular, contrary to conventional wisdom, the multiplicative seasonal model is often outperformed by the additive model. Altogether, this dissertation advances both theory and practice in data science in supply chain management by peeking into the black box to identify several levers that managers may control to improve demand planning. Having greater awareness over model and parameter specifications offers greater control over their influence on statistical outcomes and data-driven decision