It is well known that most new ventures suffer from a significant lack of resources, which increases the chances of failure (Shepherd, Douglas and Shanley, 2000) and makes it difficult to attract stakeholders and financing for the venture (Bhide & Stevenson, 1999). The Resource-Based View (RBV) (Barney, 1991; Wernerfelt, 1984) is a dominant theoretical base increasingly drawn on within Strategic Management. While theoretical contributions appling RBV in the domain of entrepreneurship can arguably be traced back to Penrose (1959), there has recently been renewed attention recently (e.g. Alvarez & Busenitz, 2001; Alvarez & Barney, 2004). This said, empirical work is in its infancy. The purpose of this study is to develop a measurement scale that can serve to assist such empirical investigations. Current empirical measures are lacking in three ways for the application of RBV to the entrepreneurship arena. First, measures for resource characteristics and configurations associated with typical competitive advantages found in entrepreneurial firms need to be developed. These include such things as alertness and industry knowledge (Kirzner, 1973), flexibility (Ebben & Johnson, 2005), strong networks (Lee et al., 2001) and within knowledge intensive contexts, unique technical expertise (Wiklund and Shepard, 2003). Second, the RBV has the important limitations of being relatively static and modelled on large, established firms. In this context, traditional RBV focuses on competitive advantages. However, newly established firms often face disadvantages, especially those associated with the liabilities of newness (Aldrich & Auster, 1986). It is therefore important in entrepreneurial contexts to expand to an investigation of responses to competitive disadvantage through an RBV lens. Conversely, recent research has suggested that resource constraints actually have a positive effect on firm growth and performance under some circumstances (eg. George, 2005; Mishina et al., 2004). Third, current empirical applications of RBV measured levels of particular resources available to a firm. They infer that these resources deliver firms competitive advantage by establishing a relationship between these resource levels and performance (e.g. via regression on profitability). However, there is the opportunity to directly measure the characteristics of resource configurations that deliver competitive advantage, such as Barney's well known VRIO (Valuable, Rare, Inimitable and Organisation) framework (Barney, 1991). This is a limitation of most empirical RBV studies, whether in the domain of entrepreneurship or not.
Methodology/Key Propositions :
The aim of our study is to develop and test a scales for measuring resource advantages (and disadvantages) and their VRIO characteristics for entrepreneurial firms. The study proceeds in three stages. The first stage developed our initial scales based on earlier literature. Where possible, we adapt scales based on previous work. The first block of the scales related to the level of resource advantages and disadvantages. Respondents were asked the degree to which each resource category represented an advantage or disadvantage relative to other businesses in their industry on a 5 point response scale: Major Disadvantage, Slight Disadvantage, No Advantage or Disadvantage, Slight Advantage and Major Advantage. Items were developed as follows. Network capabilities (3 items) were adapted from (Madsen, Alsos, Borch, Ljunggren & Brastad, 2006). Knowledge resources marketing expertise / customer service (3 items) and technical expertise (3 items) were adapted from Wiklund and Shepard (2003). flexibility (2 items), costs (4 items) were adapted from JIBS B97. New scales were developed for industry knowledge / alertness (3 items) and product / service advantages. The second block asked the respondent to nominate the most important resource advantage (and disadvantage) of the firm. For the advantage, they were then asked four questions to determine how easy it would be for other firms to imitate and/or substitute this resource on a 5 point likert scale. For the disadvantage, they were asked corresponding questions related to overcoming this disadvantage. The second stage involved two pre-tests of the instrument to refine the scales. The first was an on-line convenience sample of 38 respondents. The second pre-test was a telephone interview with a random sample of 31 Nascent firms and 47 Young firms ( 3 years in operation) generated using a PSED method of randomly calling households (Gartner et al. 2004). Several items were dropped or reworded based on the pre-tests. The third stage (currently in progress) is part of Wave 1 of CAUSEE (Nascent Firms) and FEDP (Young Firms), a PSED type study being conducted in Australia. The scale will be tested and analysed with a random sample of approximately 700 Nascent and Young firms respectively. In addition, a judgement sample of approximately 100 high potential businesses in each category will be included.
Results and Implications :
The scale has now been pre-tested using an online pre-test (N=38) and a telephone pilot of N=78. The factor structure of these items confirmed the distnctiveness of the constructs. The reliabilities are within an acceptable range: Cronback alpha for each construct were: Marketing expertise (reduced to 3 items; 0.802); Technical Expertise (3 items; 0.701); Cost (4 items; 0.726); Flexibility (2 items; 0.761); Industry Knowledge (3 items; 0.843); Network Capabilities (reduced to 3 items; 0.927); Product uniqueness (4 items, 0.778). The paper will report the results of the main study (stage 3 - currently data collection is in progress) will allow comparison of the level of resource advantage / disadvantage across various sub-groups of the population. Of particular interest will be a comparison of the high potential firms with the random sample. The study will provide an opportunity for researchers to better operationalise RBV theory in studies within the domain of entrepreneurship. Cost (4 items; 0.726); Flexibility (2 items; 0.761); Industry Knowledge (3 items; 0.843); Network Capabilities (reduced to 3 items; 0.927); Product uniqueness (4 items, 0.778). The paper will report the results of the main study (stage 3 - currently data collection is in progress) will allow comparison of the level of resource advantage / disadvantage across various sub-groups of the population. Of particular interest will be a comparison of the high potential firms with the random sample. The study will provide an opportunity for researchers to better operationalise RBV theory in studies within the domain of entrepreneurship
