Keywords

Entrepreneurship, Business Failure, Business Re-Entry.

Introduction

Restarting new business after failure is not an easy task. It involves entrepreneur’s ability to overcome the barriers caused by the preceding business failure. This phenomenon has received less attention from scholars (Amaral et al., 2011); Baù et al. (2017); Stam et al.(2008) and particularly the study related to the length of time that entrepreneur need to establish new business after experiencing business failure. Moreover, Guerrero & Peña-Legazkue, (2019) stated that this field of study is still in its early phase in entrepreneurship and need to be systemically investigated.

There have been many studies devoted to investigating aspects that influence entrepreneur’s re-entry process (Fu, (2018); Koçak et al.(2010); Lin & Wang (2019); Nielsen & Sarasvathy, (2011); Stam & Schutjens (2006) however most study is relying on entrepreneur’s intention to re-enter. Even though between entrepreneur intention and actual behaviour are very close (Lin & Wang, 2019) however Stam & Schutjens (2006) argued that entrepreneur’s intention to re-enter and their actual re-entry process are having fundamental differences. According to Stam & Schutjens (2006) any study of entrepreneur re-entry process should differentiate between reentry intention and re-entry effort.

Accordingly, the purpose of this study is to examine entrepreneur re-entry process. Specifically, investigating factors that influence duration of novice entrepreneur to re-enter the entrepreneurship after failure. The main objective of this study is to discover the underlying mechanism of the relationship between the amount of time that novice entrepreneurs need to build their new business, and its predictors variables, experience, age, and education background. This research attempts to answer the following questions: Do entrepreneur’s experience, age, and education influence entrepreneur’s re-entry duration, directly or indirectly? How do entrepreneur’s educational background and age affect the duration of re-entry process?

By answering the research questions, this study is expected to have contribution to the growing body of entrepreneur re-entry process research. This study is one in small amount of study that specifically investigating novice entrepreneur re-entry process based on actual reentry. Our study is among the first to investigate the underlying mechanism of education and entrepreneur’s age on failed entrepreneur’s to re-start another business.

Literature Review

The Effect of Experience toward Re-Entry

Guerrero and Peña-Legazkue (2019) point out that, entrepreneur experience together with networking skill and leadership skills will contribute to helping entrepreneurs collect and assemble the necessary resources to reopen their new business. Wakkee and Moser, (2016); Unger et al. (2011) also stated similarly, they pointed out that the re-entry process would need less time and effort if the entrepreneurs had experience in doing all the tasks to start the new business. This idea was confirmed by Amaral et al. (2011) that found more experienced entrepreneurs tend to restart another business directly after their previous failure. Entrepreneur with high experiential capital will be able to gather resources more quickly than entrepreneur with low experiential capital and will re-enter to the business venture more quickly (Guerrero & Peña-Legazkue, 2019).

Moreover, Stam et al. (2008) point out that, there are two categories of experience; entrepreneurial experience and industrial/employment experience. Entrepreneurial experience can be gained through entrepreneurial related activities such as running own business or have been involved in the process of venture creation. While employment experience is typical of experience that can be obtained from employment service or as a paid employee. According to Stam et al.(2008); entrepreneurial experience is the only type of experience that can help entrepreneur to start a business. In their study, Stam et al. (2008) found that entrepreneurial experience is significantly influence entrepreneur’s choice to open and run a new business again after experiencing business closure.

On the other hand , employment experience it adversely affects the duration of entrepreneur's re-entry process Stam et al.(2008). According to Stam et al. (2008) the effect of employment experience on re-entry process, is stronger only when the employment experience is related to the business that would be opened. This finding is also supported by Nielsen & Sarasvathy, (2011), they found that, not all experience contribute to the re-entry process, only experience which relate to the new business may have an impact on the time needed to establish new business. Similarly, Amaral et al. (2011) also found that employment experience does not influence the time needed to re-enter entrepreneurship. According to Amaral et al. (2011), a higher level of employment experiential capital will give an entrepreneur advantages to enter employment, therefore, it will decrease their intention to start another business.

Novice entrepreneurs mostly do not have previous entrepreneurial experience (Ucbasaran, Alsos, Westhead, & Wright, 2008). For novice entrepreneurs, practical experience mostly gained by doing daily tasks in their previous employment (Guerrero & Peña-Legazkue, 2019). They might also gain relevant experience from running their own business, however the amount of experience may not significant since their business not last longer. Therefore, for novice entrepreneur we expect that employment experience would play more role in the entry process. Accordingly, in this study we argue that entrepreneur’s experience (employment experience) increases the time that they need to set up their new business. It also means when the entrepreneur’s working experience is getting higher, the time that they need to restart business after failure is getting longer. To test this notion, we propose hypothesis below.

H₁: Experience (EXPR) has a positive direct effect toward duration to re-enter new business (DUR)

The effect of Age toward re-entry

The effect of age has been found not the same for different entrepreneur’s life stages (Kautonen et al., 2014). Baù et al. (2017) found out that, age has a double role in influencing the process of re-starting a new business after a failure. According to Baù et al. (2017) the age of an entrepreneur can either speed up or slow down the process. Baù et al., (2017), revealed an inverted S shape pattern. This finding is supported by Kautonen et al., (2014), who found that, age might have positive and negative effect on re-entry, and it is depend on the stage of life of the entrepreneurs. However Kautonen et al., (2014), discovered that the likelihood of an entrepreneur to reopen their business is believed following an inversed ‘U’ shape pattern.

The actual re-entry situation can be very different, since entrepreneur must deal with real consequences. Particularly for novice entrepreneur who starting up another business after failure. Younger novice entrepreneurs may not want to move quickly to entrepreneurship after their business have been closed. They have more career opportunities than the older entrepreneurs (Amaral et al., 2011). They may also have less financial responsibility, since most of younger entrepreneur still single. While for the older entrepreneurs, no business also means no job and no income. Therefore, it is crucial for the older entrepreneur to set up the business more quickly.

To conclude we argued that for novice entrepreneur who failed their previous business, age has a liner negative effect toward time to re-start new business. It means younger entrepreneur will take longer time to re-start another business. We also propose hypotheses:

H₂: Age (AGE) have negative direct effect toward duration to re-enter new business (DUR)

According to Guerrero & Peña-Legazkue, (2019); when the entrepreneurs are getting older, their experience also will expand. While according to Amaral et al. (2011) when entreprenur posess more experince, they tend to delay the re-entry process. Therefore, we propose a hypothesis as written:

H_2a: Age (AGE) have a positive indirect effect toward duration to re-enter new business (DUR) through experience (EXPR)

The effect of Education toward re-entry

Formal education is believed to have an important role in a new venture creation (Parker & Praag, 2012). According to Baù et al. (2017), the number of years in education is an important factor that determines entrepreneurs decision to re-start their business after failure. Entrepreneurs who invest their time and money in formal education and acquired knowledge from it, can collect information more effectively than entrepreneurs who do not. With greater knowledge, it can help entrepreneurs to overcome re-entry barrier, thus, this process can be speed up.

According to Riddell, (2008) in entrepreneurship, knowledge acts as a scaffold to create a new business. Wagner (2005) also found that education level has a positive influence on an entrepreneur’s intention to re-enter business. While Hessels et al. (2011) found that the there is a positive effect of formal education toward intention to re-enter, however the effect on entrepreneur might different regarding to the country where the entrepreneur live.

Contradict to the all those studies, Stam et al. (2008) found out that, education has a negative effect toward re-entry intention. Stam et al. (2008) explained that entrepreneurs who had a higher level of education found easier to get other jobs. This idea is also supported by Amaral et al. (2011) and Guerrero & Peña-Legazkue, (2019).

They argued that entrepreneurs with higher degree of education has a smaller likelihood of restarting their business. It is because they have greater opportunities to start/resume their career as a paid employee and they tended to postpone the re-entry process.

It is obvious that the previous studies have found different effect of education toward reentry intention. There is no consensus among scholars related to the role of education toward intention. This may be caused the re-entry process is a very complex process. There are many aspects determine this process. Therefore, the effect of education toward re-entry process must depend on other aspects and circumstances. The influence of education on serial entrepreneur could be different from novice entrepreneur. And the influence of education on business re-entry might also different between successful exit and failure exit. Additionally, apparently there was no previous study have found a relationship of education toward time to re-enter another business, since most of the previous studies were investigating the effect of education toward entrepreneur’s intention to open new business, not the actual action of the entrepreneurs itself.

In regard to this circumstances this study tend to support Stam et al. (2008) and Guerrero & Peña-Legazkue, (2019). It seems more reseonable that higher education entrepreneur who experiencing business failure will not quickly restarting their business. This may becaused they more likely to change their carerr path to become paid employee. Furthermore, the negative effects of business failur are more greater for unexperience entrepreneur (Metzger, 2006), especialy novice entrepreneru wih high education backgorund, will likely to receive higher stigma.Therefore they migh take more time to return the entrpreneurhsip :

H₃: Education (EDU) has a positive direct effect toward duration to re-enter the business (DUR)

Furthermore, according to Riddell (2008) number of years in formal education would effectively leverage entrepreneur’s knowledge and skill. This would also mean, the longer years in formal education will contribute to the entrepreneur’s experience development. As has been stated above that higher experience will increase the duration to set up new business. Hence, we propose hypothesis:

H_3a: Education (EDU) has a positive indirect effect toward duration to re-enter the business (DUR) through experience (EXPR)

Methodology

The population of this study is the owner of small company who had experienced in business failures who lives in Jakarta and its surrounding cities. The data was collected through online surveys. Invitations to take part in this research were spread via email, social media and WhatsApp messages. In total, 317 entrepreneurs participated in this study; however only 226 observations can be analysed (Figure 1).

The independent variables in this study are experience (EXPR), age (AGE), and education (EDU). EXPR is referring to an entrepreneur’s previous experience (both entrepreneurial and working experience) which was measured by the number of years. To measure this variable, we have four categories of years of experience. Meanwhile the AGE variable is specifying how old the entrepreneurs were and measured by years. We calculate the age of respondent based on their year of birth. EDU which defined as number of years in formal education, have four categories that represent length of time in formal education. The dependent variable in this study is DUR. This variable refers to the time that entrepreneurs have been spent to reopen their businesses after closing the previous one. Variable DUR was calculating by subtracting the year when the new business began to operate, and the year of the previous business was closed.

Path analysis is used to predict the relationship between all independent variables and the dependent variables in a complex structural path. It also analysed the relationship among independent variables that can show any indication of mediation effect one or more variables. All variables in this study are observed variable which connected to other variables. According to Jenatabadi, (2015), this study can be considered as a specific structural equation modelling (SEM), thus, to analyse the data, we decided to use Smart PLS.

Results

From the descriptive analysis, it revealed the demographic profile of the respondents. Based on the category of business, the results revealed that 55.7 % of the entrepreneurs were in trading, 29.4% were in the service industry and 14.9 % in were in manufacture.

The average age of entrepreneurs who participated in this study was 41.7. It ranged from the youngest at 15 years old to the oldest at 65 years old. Regarding to their experience, the first category or entrepreneurs who have less than 2 years of experience found to be the smallest group (8,4%) and the highest group is the second category, 45,13 %. While there were 15.4 % of entrepreneurs who have more than 20 years of experience. The average duration to re-start new venture is 4,45 years.

The path analysis result showed that nearly all independent variables were found to have significant relationship toward dependent variable, with 95% confidence level. This result proved that H1 is supported, which also mean EXPR had a positive and significant impact on DUR with path coefficient 0.266 (p=0.000). It indicated that, more experience entrepreneurs tend to impede the business re-entry process. This result confirmed Amaral et al. (2011); Guerrero & Peña-Legazkue (2019); Stam et al. (2008) study that found entrepreneur’s with higher employment experience has bigger chance to change their career path to become paid employee after experiencing business failure.

It was found that AGE had the greatest impact on DUR (-0.437 p=0.000). This result also confirmed that H2 was supported. Therefore, it showed that younger entrepreneurs tend to take longer time in restarting their new business after failure, while the older entrepreneur prefer to re-start the business more quickly. Unlike the older entrepreneur, most of younger entrepreneurs had no family yet. Therefore, there was no obligation for them to cover family living expenses. Hence, they were not in a hurry to restart a new business to earn money. This result was contradict to Kautonen et al. (2014); Baù et al. (2017), who found out that younger entrepreneur need less time to re-enter the entrepreneurship compare to the older entrepreneur. This result also proved that in case actual re-entry, especially for novice entrepreneur, the relationship between AGE and DUR were linear.

The last variable in the main relationship was EDU. Unfortunately, the direct relationship between EDU and ‘DUR was found out not significant with p-value 0.391. Therefore, we could not conclude that H3 was supported. However, from the path coefficient of EDU (0.058), it can be seen that entrepreneur with higher degree of education background was less likely to restart their business more quickly. They had more career opportunities; thus, they may try different career path before making decision to re-enter the entrepreneurship.

The path analysis result showed that AGE did not only have a direct effect toward DUR, however it also had an indirect effect on DUR through EXPR. From the relationship path of AGE and EXPR was seen that AGE had a strong effect on EXPR with path coefficient 0.302 (p=0.000). It showed that most younger entrepreneurs had less experience than the older one. While from EXPR toward DUR relationship path, it revealed that higher level of experience entrepreneur which also an older entrepreneur, tends to make a slower re-entry process than the younger entrepreneur. Even the path coefficient not as strong as AGE and EXPR, however, we can see that this relationship was statically significant (p=0.000).

The total indirect effect of AGE toward DUR was positive and significant (0.08; p=0.009). This result also confirmed that H2a was supported. However, this indirect effect was less strong than direct effect. It showed the nature effect of age toward business re-entry. Since the direct effect of AGE toward DUR greater than indirect effect, we can conclude that in the case of novice entrepreneur, AGE had A negative relationship toward DUR as predicted.

Correspondingly, from the indirect relationship analysis of EDU toward DUR, it revealed that EDU had a significant effect toward DUR through EXPR with path coefficient 0.054 (p=0.008). This result confirmed that H3a was supported. However, the effect was small. Regardless the small effect of EDU, this finding was very interesting, since the direct effect of EDU on DUR was not significant. Therefore, the indirect relationship between EDU toward DUR via EXPR, explained that most entrepreneur with high degree of education having more experience than entrepreneur with low degree. While more experience entrepreneur chose not to immediately starting a new business after failure, since they had another career option to pursue. The same finding also can be found from the direct relationship of EDU toward DUR. Even though not significant, it indicated that high education background entrepreneur likely to delay the re-entry.

This finding confirmed Stam et al. (2008); Amaral et al. (2011) study, which found out that high degree education entrepreneur had more alternative career path, therefore they less likely to re-enter the entrepreneurship after failure. In the case of actual re-entry process, it was also found out that entrepreneur with high degree of education, took more time to re-start their business. There was a possibility that they decided to find a job and became employee rather than starting another business right after the failure. High degree entrepreneur had capability to do that. Another possible reason was, that they wanted to gain more experience form the employment before continuing their entrepreneurial venture.

Conclusion

The result showed that AGE was the variable which had the largest impact on entrepreneur’ time to reopen a new business after failure. This study was also successful to provide evidence that, the effect of AGE was linear toward DUR, which contradict to Baù et al. (2017); Kautonen et al. (2014) that found a nonlinear relationship. The direct impact of AGE toward DUR was negative; however, the indirect impact of AGE toward DUR through EXPR was positive. This result indicates that older inexperience entrepreneur would open another business more quickly than the younger inexperience entrepreneur. However, the effect of experience would overturn the situation. Older experience entrepreneur tends to delay re-entering the entrepreneurship venture after failure, since they might want to pursue other career path considering they have capability to do that.

This study found that experience entrepreneur with high degree of education background tend to restrain the re-entry process. This was also confirmed (Stam et al., 2008) , Amaral et al. (2011); Guerrero & Peña-Legazkue (2019) that found high degree of education entrepreneur may choose to postpone the entrepreneurial venture after experiencing business failure.

For the future study, it is suggested to considered two different categories of entrepreneur experience, entrepreneurial experience and employment experience as Stam et al. (2008) and Amaral et al. (2011). To get more detail information regarding to the relationship of age and experience toward duration, it suggested for further study to investigate the moderator effect of education background. This study also did not consider gender as part of the model. Therefore, it would be expected to be included in future studies. However, the results of this study contribute to the existing literature by providing empirical evidence on the effects of age and experience toward entrepreneur re-entry duration after failure which is still scarce to find. This study also provides a guidance for novice entrepreneurs who have had a failure and have an intention to restart their businesses.

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