Title: An Empirical Study of Measures of Success in Micro Businesses. Author: Elizabeth Walker, Edith Cowan University. ABSTRACT Small business plays a vital role in the economy of most nations. This is in terms of both employment creation and revenue generated. When segmented into size category, micro businesses, which are defined in Australia as either non employing or employing 5 or less people, make up over 80% of all businesses. Yet there has been little dedicated research into this category. Past research has often incorporated micro business with small businesses in general, therefore their opinions on issues such as growth and measures of success have not been investigated separately. The traditionally accepted criteria of business success have been by financial measures, such as increases in turnover, revenue or profit or by increases in number of employees. Conversely, decreases in any of these financial measures is often deemed as failure. By definition increases in these financial measures must be continual, there is therefore, an implicit assumption that these businesses want to grow. However there is a body of literature that state small businesses and micro businesses, do not necessarily want to grow continually. Further these non-growth businesses are using alternative criteria to measure their business success. These are affective measures, linked to lifestyle issues and are outside the conventional economic paradigms. This paper will report the findings of an empirical study carried out on a sample of approximately 300 small and micro businesses in the business service sector in Western Australia. The results take into account demographic factors and issues such as the age of the business and how the business owner actually measured their success. Whereas achieving a level of financial security was a goal for the majority of the respondents, the aspect of lifestyle was equally important. INTRODUCTION Small business is an essential component to the economic well being of most nations. This is because of the contribution it makes to GDP, the numbers of people that small business employs and in the total number of actual businesses. In Australia for the period 1995-1996, small business generated $75 billion and employed 60% of the workforce (Australian Bureau of Statistics, 1998a). Small business comprises of almost 94% of all Australian businesses with the remaining 6% being classified as medium and less than 1% as large business (Australian Bureau of Statistics, 1998b). The Australian definitions of business size are as follows. A large business employs over 500 people, a medium business employs between 100 and 500 and a small business is one which employs 20 or fewer staff in a service industry and 100 or less in a manufacturing industry. A micro business is defined as being a business which is either nonemploying or employs less than five people (Australian Bureau of Statistics, 1998a). On this basis, in Australia 84% of all small businesses can be classified as micro enterprises (Australian Bureau of Statistics, 1998c). Given that micro businesses make up such a large proportion of all businesses it is interesting that there has been very little dedicated research into this group. Exceptions include Baines & ICSB 2000
Wheelock (1998); Baines, Wheelock, & Abrams (1997)and Chell & Baines (1998) in the UK and Deschamps & Dart (1998) in Canada. Most previous research into small business has treated the businesses as homogenous and has often not segmented findings by size. Size in this instance is being defined by number of employees, not turnover. What this has done is treat all businesses as equal with regard to size and has used other variables, such as gender, education, entrepreneurial ability to assess differences. This paper reports on empirical research in one industry category, ‘Property and Business Services’, and uses size as the key defining variable. The size categories are micro business (either non employing or employing 5 or less people and generic or larger small business (employing more than 5 people). One aspect was looked at specifically, that being how micro and larger small businesses measured their success. LITERATURE REVIEW Interest into small business is not a new phenomenon. However past research has not always differentiated between the size of the business and has often assumed that small business is just a scaled down version of big business. This is perhaps not the case. If small business in general is not a scaled down version of larger business (Burns, 1996a; Keats & Bracker, 1988; Penrose, 1980), then perhaps the same can be said in relation to micro business and larger small business. Accepting that the majority of past literature has not differentiated with regard to size, the research can however be segmented into two broad areas, pre-business formation and post formation.
PRE-BUSINESS FORMATION The research into this aspect of business has looked at issues such as the characteristics of the person who is going into self employment, in regard to their demographic and psychographic profiles. Also researched has been their motivations and reasons for business entry, including the type of business they are going to start (Bird, 1989; Birley, 1996; Birley & Westhead, 1994; Brockhaus,1982; Cromie, 1987; Gartner, 1988; Gatewood, Shaver & Gartner, 1995; Hamilton,1987; Gray, 1997; Johnson, 1990; Mazzarol et al., 1997). What has evolved are both theories and profiles. Demographic aspects such as gender, age, education, have been extensively researched, often with comparisons being conducted (Barkham, 1994; Dolinsky et al.,1993; Ljunggren & Kolvereid, 1996; Loscocco et al., 1991; Marlow, 1997; Robinson & Sexton, 1994; Rosa et al., 1994; Welsch & Young, 1984). Given the large number of variables that make up a possible ‘profile’ it is difficult to come up with a generic picture of the typical small business owner (SBO). What can be said is that all sorts of people go into self employment. So if this is the case, are there more significant differences in motivations for business start-up? The reason for starting a business has been dichotomised into either pull or push factors (Buttner, 1993; Gray, 1994b; Hamilton, 1987; Lawrence & Hamilton, 1997). That is, some people are pulled towards starting a business by aspects such as fulfilling an ambition of being one’s own boss, seeing a potential business opportunity, or to use skills and knowledge that have been acquired in previous employment. The opposite of pull is push and these factors are associated with more negative start-up reasons such as redundancy, perceived lack of opportunity or being generally unhappy as an employee. The reasons stated are often a combination of these two factors. POST FORMATION Having established the business in some form and having survived over a certain length of time, other aspects of research have looked at the future intentions of the businesses, whether the business is successful and why it has become so. The reasons given for having been successful are primarily process or strategic reasons, such as having a business plan, having good human resources, good product or good management practices (Burns, 1996b; Cooper, 1981; Lyles et al., 1993; Moore, 1990). The other aspect of business survival/success is often attributed to the personal characteristics of the small business owner, such as high motivation, determination, perseverance, good communication skills. These characteristics are often thought to be crucial to the success of any business. MEASURES OF SMALL BUSINESS SUCCESS When looking at these post formation aspects and the reasons given for why businesses might prosper, or in some cases just survive, the measurements used for success are traditionally of a financial nature. Small business success, indeed all business success, is predominantly measured in either increases in turnover, or revenue or in increases in number of people employed (Barkham et al., 1996; Brüderl & Preisendörfer, 1998; Gray, 1997a; Gibb & Davies, 1992; Holmes & Zimmer, 1994; Ibrahim & Goodwin, 1986; Kalleberg & Leicht, 1991). ICSB 2000
Conventionally, financial measures have been used for several reasons. They are easy to understand, apply and administer. Further, economic data is often used in comparison against existing data and as benchmarks for future measures. Jennings & Beaver (1997) sum up this economic focus by stating, “Existing studies commonly define success in narrow accountancy terms using criteria based upon financial analyses and ratios such as sales growth, profitability, cash-flow and productivity” (p. 67). But are these numerical values really how the owners of small businesses measure their success? Regardless of which measures are predominantly used, it is accepted that the owners of small businesses are in business primarily to make a profit. What is perhaps more difficult to ascertain is how much or how large a profit? That question is beyond the scope of this present paper. However if it is accepted that there is a level of financial security that needs to be attained and which is personally determined by the individual business owner, then what other measures could be used? An alternative to pure financial measures are affective or subjective measures, such as lifestyle and personal freedom and balancing work and domestic responsibility (Birley & Westhead, 1994; Brush, 1992; Buttner & Moore, 1997; Green & Cohen, 1995; Kuratko, Hornsby & Naffziger, 1997; LeCornu et al., 1996; Loscocco, 1997; Parasuraman et al., 1996). As an illustration, Kuratko, Hornsby & Naffziger (1997) state that, “intrinsic rewards are those often cited by entrepreneurs which center around the satisfaction of being one's own boss, being more in control of one's own destiny, and having ultimate responsibility for the success of the venture” (p. 26). Additionally, in her in-depth study of 30 couples, Loscocco (1997) stated that most, "traded off a higher degree of economic success for personal balance" (p. 209). This theory of lifestyle issues being equally if not more important than financial criteria in regard to the measurement of small business success was tested in the study. CHOICE OF SAMPLE There are some inherent difficulties when attempting to research small businesses. The first is the problem of getting a representative sample. This is because of the heterogeneity of the total small business population. The desire for the research to be truly representative of all small businesses is virtually impossible to achieve because of the sheer diversity of industries and the myriad of subsets thereof. Even allowing for a statistical numerically viable sample, there are often too many variables to achieve a genuine stratified random sample of all small businesses. This is confirmed by Gibb cited in Read (1998) who stated that, “the search for a representative sample is rarely possible in any small firms research as the small firms sector is so diverse" (p. 72). Whereas the ideal would be to have an across industry sample, it was felt that there would be some small and micro businesses who would simply not participate. This was verified in the pilot testing of the research, when several of the participants only agreed to be interviewed because of personal appeal by the researcher. Therefore only one industry sector was chosen as the sample. It is important that this limitation is acknowledged as the results might not be applicable to small businesses in other industries. As Storey (1994) states in his comparison of past research, "the vast bulk of studies have been conducted independently of each other. Frequently they address issues of specific interest to the researcher, but do so in a way which makes comparability with other studies difficult" (p.125). ICSB 2000
The industry sector chosen was ‘Property and Business Services’ (ANZSIC Division L). Included in this category are real estate agents, management consultants, technical engineers, accountants and bookkeepers, secretarial and employment services, the legal profession and various other smaller professions and trades. There were several reasons for choosing this industry sector. This sector is the second largest industry sector, after construction. It is also the third fastest growing sector, in terms of employment levels, after health & community services and education (Australian Bureau of Statistics 1998c) The sector has a range of business sizes. It was anticipated that there would be both micro and larger small businesses within the sample, thus allowing for meaningful comparisons. As some of the subsets of business services were accounting, the legal profession, real estate, secretarial services and management consultants, it was felt that not only would there be a reasonable representation of women in the sample, but also that the category was almost gender neutral. This is in contrast with sectors such as retail and personal services which have a high female ownership and sectors such as construction and mining which are very much male dominated. Finally, there have been a number of previous studies which have used business services as their sample, such as Barrett, 1998; Breen, Calvert & Oliver, 1995 and Still & Guerin, 1991 from Australia, and Baines & Wheelock, 1998; Buttner & Moore, 1997; Cliff, 1998; Fasci & Valdez, 1998; Ljunggren & Kolvereid, 1996; Loscocco et al., 1991 and McKechnie, Ennew & Read, 1998, from the UK, Canada and the US. The focus of this paper are findings from a study that looked at perceived measures of success in small and micro businesses in the business service sector in Perth, Australia. METHODOLOGY The instrument used was a 4 page questionnaire, consisting of some basic demographic questions, 3 sections which were rated scales and a short open ended section, where the respondents could say what they liked most and least about being in business. A reply paid envelope was enclosed. The sample was derived from data from Australia on Disc, which is a data base of all Australian businesses. The initial sampling frame was all Western Australian businesses which had the Australian standard industry codes ranging from 7700 to 7899. The sample was further defined by postcodes, using 6000-6030 and 6100-6210. These postcodes are classified as within the Perth metropolitan area. This generated a complete data base of 13,498 businesses. From this a systematic random sample was generated, taking every 10th entry, starting at 7. This then gave a total of 1349. This list was further reduced by entries which were in some way incomplete, such as not having a complete telephone number or a complete address. Also excluded from the sample were any multi-national, national or franchised companies. The final number of entries randomly derived from the population to make up the final sampling frame was 1172.
The actual sampling was done in 2 stages. The first stage involved an initial qualifying telephone call by the researcher to approximately half of the sample. Agreement was gained either from the actual business owner or someone who agreed on their behalf. Some of the businesses declined to participate or did not meet the criteria of being a small independently owned and operated business. When agreement had been ascertained the covering letter and the envelope were addressed personally. The second stage involved sending the questionnaire to small businesses which had not been qualified in any way. The covering letter and envelope were addressed to either ‘The Proprietor’ or a personal name if it appeared in their business name. In total 724 questionnaires were sent, of which 295 businesses replied, and 11 questionnaires were returned undelivered. These were from the businesses which had not been qualified. In all there were 290 useable responses, which gives an overall response rate was 40%. As this sector of business is notoriously difficult to get to respond to postal questionnaires (Fischer, Reuber & Dyke, 1993; Hamilton, 1987), the response rate is therefore considered adequate (Roberts, 1999). RESULTS & DISCUSSION Demographic Characteristics It was anticipated that the industry sector chosen would illicit responses from a broad range of demographic variables. Of the 290 respondents, 36% were women and 64 % were men. Age was asked as categorical rather than absolute, and had a normal distribution with the largest percentage of respondents in the 41-50 age bracket. The majority, (79%) were either married or in a de facto relationship and also had children, (76%). With regard to education, again the majority had at least a diploma/certificate, an undergraduate qualification or a postgraduate qualification (85%). Nearly 37% had a post graduate qualification, which is higher than the national average. However the industry sector could have a bearing on this figure, as it included accountants, the legal profession and management consultants from a variety of professions. There were no major gender differences in most of the demographic factors with the exception of educational qualifications. The respondents were asked to indicate the highest level they achieved. The women in the study had a higher level of tertiary qualification (See Table 1).
Table 1 EDUCATION LEVEL Primary Secondary Diploma/certificate Undergraduate Post graduate
WOMEN % 0% 14% 21% 22% 43%
MEN % 1% 14% 31% 20% 34%
Business Characteristics The businesses were classified into 7 different categories as shown in Table 2. Table 2 TYPE OF BUSINESS Real estate agents Architect, surveyors, consultant engineers Computer services Legal and accounting Marketing & management consults Employment, secretarial & cleaning Not a service Missing TOTAL
FREQUENCY 14 62
PERCENTAGE 4.8% 21.4%
25 60 79
8.6% 20.7% 27.2%
22 1 290
7.6% .3% 100%
The participants were asked how long they had owned the current business and also how long they had been self employed in total. These two sets of data did not vary greatly. A further question asked how many people did they employ. This information allowed the sample to be classified as either micro or larger small businesses. The frequencies for this data are shown in tables 3 and 4a & 4b.
Table 3 LENGTH OF OWNERSHIP 1-2 Years 3-5 Years 6-10 Years 11-15 Years 16-20 Years > Years TOTAL
Table 4a SIZE OF BUSINESS < 5 employees (micro) > 6 employees Missing TOTAL Table 4b FREQUENCIES – No. OF EMPLOYEES Mean Median Mode
53 78 77 39 26 17 290
18.3% 26.9% 26.6% 13.4% 9% 5% 100%
FREQUENCY 223 56 11 290
PERCENTAGE 76.9% 19.3% 3.8% 100%
4.2 2 1
Five different measures of success had been previously identified in the literature (Birley & Westhead, 1994; Shane, Kolvereid & Westhead, 1991). The five measures were, ‘in financial terms’; ‘by my lifestyle’; ‘by increases in my customer base’; ‘by my personal freedom’ and ‘by industry/peer recognition’. Respondents were asked to indicate their agreement with the statements on a 6 point Likert scale with the anchors of 1 = strongly disagree and 6 = strongly agree. Independent t-tests were conducted for all 5 options, with the size of the business as defined into the 2 groups (<5 employees and >6 employees). The results are shown in Table 5.
Table 5 Size of business Financial terms <5 >6 Lifestyle <5 >6 Customer base <5 >6 Personal freedom <5 >6 Peer recognition <5 >6
N 233 56 223 56 223 56 223 56 223 56
Mean 4.3722 4.7679 4.4529 4.5000 4.4619 4.8393 4.2432 4.3036 4.0045 4.4464
Std deviation 1.1933 1.0953 1.2756 1.1755 1.3039 .9101 1.4220 1.2493 1.4627 1.0604
The results of the t-test showed that at a 95% C.I. there was a statistically significant difference, .025 on the factor ‘success measured in financial terms’ between the 2 groups. Additionally there were differences between the groups with regard to the measures concerning customer base (.013) and industry/peer recognition (.012). there was no difference on the factors lifestyle (.802) and personal freedom (.772). What the analysis shows is that there were some differences when the size of the business, as determined by number of employees was used as the criteria for how the businesses measure their success. That is, that larger small businesses use financial measures of success to a greater extent than micro businesses. Even though there was no significant differences with regard to ‘lifestyle’ and ‘personal freedom’, they both had a high mean score on the 6 point Likert scale. This would appear to indicate that even though the respondents do measure their success financially, they also place a high value on these two affective measures. Having established that there are some attitudinal differences, as determined by the size of the business, gender was then tested as a variable were also tested. There was not a significant difference between the size of the business and gender, with regard to how they measure their success. The mean scores on this factor (women = 4.4476 compared to men = 4.4108) were almost identical. This is perhaps contrary to previous studies which have stated that women do not use financial measures as much as men (Brush, 1992; Marlow & Strange, 1994). There was also no significant difference between women and men when it came to measuring their business success by lifestyle. Women had a slightly higher mean score (4.600) as compared to men (4.383). However women also had slightly higher mean scores on the other three factors. CONCLUSION Whilst the survey was a preliminary study and was not attempting to ascertain why size of business was a good indication of how SBO’s felt about their business, some interesting results appeared. The fact that there were only slight gender differences could mean that the past emphasis on differences has focused on gender to the exclusion of the variable ‘size of the business’. As the demographic data shows, there were more similarities than differences between women and men in the majority of areas. The past emphasis on demographic issues certainly laid the foundation of much significant research. However it would appear that the differences are diminishing. ICSB 2000
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