Social Norms, Percieved Business Opportunity And Working Women Entrepreneurial Intention In Nigeria

Theoretical and hypothesis development

Theoretical framework and measurement

In line with discussion above Figure 01 below depict the framework of the study.

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The framework above indicate that whether there is a link in connection between social norms, perceived business opportunity and working women entrepreneurial intention. Therefore, hypothesis below may likely offer in line with the objective of this research:

Hypothesis 1: Social norms significantly influences working women entrepreneurial intentions in Nigeria.

Hypothesis 2: Perceived business opportunity significantly influences working women entrepreneurial intentions in Nigeria.

Methodology

Convenience sampling was used for this study because according to Sekaran and Bougie ( 2013) this sampling lets the scholar to get uncomplicated information, facts and movements concerning the study deprived of the difficulties of using a randomised sample. Another reason for this method, is that is useful in time sensitive because very little preparation is needed to use for the collection of information. The population of this research are the working women those want to stimulate and advance positively to improved and sustain the autonomy to animate their lives as they wish. The paper used 375 usable response to analysed data Using PLS-SEM due to significant to account for measurement error and accommodate non-normality and complex model ( Hair et al., 2014). Therefore, the second generation statistical tool of Smart PLS 3.0 software application ( Ringle et al., 2005) remained considered in the study and writing the outcomes.

Common method bias

This research consider common method bias because in every cross-sectional survey research, most of the technical and numerical actions to solved some of the common method variance were; reverse expression questionnaires and preserving the secrecy of the respondents has been applied in line with Podsakoff et al. ( 2003). Subsequently, as stated by Bagozzi et al. ( 1991), the common method bias is neither be an issue in this research, as corroborated further by the results and tenability of the research instruments ( Gorondutse & Hilman, 2017).

Measurement

This paper adopted Entrepreneurial Intention Questionnaire (EIQ) and a modified version ( Kautonen et al., 2015; Şen et al., 2018) was used which is line with theory of TPB to create an entrepreneurial intention questionnaire (EIQ).

Descriptive statistic

Evaluation of PLS-SEM results

This paper adopted two step method which comprises on the first assessment on outer model and second is on the assessment of a structural model following the procedures from Hair et al. (2014), Henseler et al. ( 2009). Initial step in this section was to assess on the measurement model which emphasized on outer models to determine the goodness of measure ( Gorondutse & Hilman, 2017).

Measurement model

In this section measurement model was assessed which is intended for ensuring that the model specification is valid and reliable this is in line with Hair et al. ( 2017) it clearly pointed out the rule of thumb as, for an outer loading to be considered such a model should be 0.5 and above and for the average variance extracted (AVE), it should be larger than 0.5 also. Outer loading basically is assessing the individual’s items reliability for each construct. On top that, in this path model assessment section ( Gorondutse & Hilman, 2017).

This study achieved convergent validity in Table 02 , in line with on Structural Equation Modeling (SEM) literature ( Gorondutse & Hilman, 2017), considering instruments reliability, the average variance extracted and composite reliability. Meaning that, the element of individual variable are extremely burdened and substantial in determining their own variables by at minimum value of 0.7 and above outer loadings, next the research look at the composite reliability is at minimum 0.7 and at the same time average variance extracted (AVE) is at minimum 0.5 ( Bagozzi et al., 1991; Gorondutse & Hilman, 2017; Hair et al., 2017).

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This paper adopted the Fornell and Larcker ( 1981) principles. As stated Fornell and Larcker ( 1981) discriminant validity is method by relating the correlations in respect of the latent variables AVE square roots ( Gorondutse & Hilman, 2017). This scholar also supported that the square root of the AVE values required to be more than the latent construct’s correlations ( Gorondutse & Hilman, 2017). As Indicated in the table below the results confirms that the discriminant validity is achieved (see Table 03 ; Figure 02 ). Equally HTMT result indicate the value are lesser than the essential yardstick value of HTMT 0.85 ( Kline, 2011), other scholar suggest that HTMT 0.90 ( Gold, Malhotra & Segars, 2001), this indicate discriminant validity is achieved for the variables of this paper (see Table 04 ).

Structural model assessment

Hair et al. ( 2017) detailed that the structural model assessment starts with an investigation of the direct relationships in this paper ( Gorondutse & Hilman, 2017). In this paper 2wo hypotheses that posed the association among the variables were established out of which the entire hypotheses were supported. The direct path relationship is shown in Table 05 which labelled the direct effect of every latent construct on the dependent construct.

In addition, Hair et al. ( 2017) seen structural model as a model that examination the direct association in respect of dependent and independent variables. As stated, in PLS-SEM, structural model designates on the directional connotation between the variables and their t-statistics as well as the path factor ( Gorondutse & Hilman, 2017). Based on the path modelling result in Table 05 to the path coefficient, partial least squares are considered by Gorondutse and Hilman ( 2017), this is inline with what is applicable as the standardized beta coefficient in regression analysis.

Looking on the Table 05 shows that all the two hypotheses were significantly supported and have a t-value which is bigger than 1.96 and it’s satisfactory to backing the two direct hypotheses. For instance; Hypothesis 1 projected that social norms will impact working women entrepreneurial intention, the results indicated a significant association between social norms and working women entrepreneurial intention. (β = 0.665, t = 20.550), hence it supports Hypothesis 1. Hypothesis 2 predicted perceived business opportunity significantly influence working women entrepreneurial intention. Whereby, the results revealed a substantial connection in respect of perceived business opportunity and employed women entrepreneurial intention. (β = 0.314, t = 6.665), In addition, the confidence interval bias results indicate that there is a significant result since the values is greater than 0 (see Table 06 ; Figure 03 ). The study variables explain 51% variation in working women entrepreneurial intention (see Table 07 ).

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Effect size (f 2)

Chin ( 1998) stated that effect size explains the relative effect of proposed latent variables continuously has an effect endogenous latent construct that take place due to the changes in ${\text{R}}^2$. The effect size ${\text{f}}^2$ is calculated using the formula designed by Cohen ( 1988) as below:

Cohen ( 1988) suggested f2 values are 0.02 as a small effect, 0.15 represent medium effect and 0.35 having large effect. Thus, brief explanation whereby R2 included and R2 excluded represent the R squares on the predicting variable, when the independent variable is present (R2 included) or when it is withheld (R2 excluded). This eventually translates the effect of the variance of every variable. Table 08 shown below represents effect sizes of the latent variables of structural model ( Gorondutse & Hilman, 2017).

Based on Table 08 above, the effect sizes of the supported relationships with their respective t-values, effect size and their rating are based on Cohen ( 1988) criterion. Thus, the results show that out of direct hypotheses possess a medium and large ration respectively. Subsequent section explains about predictive relevance of the mode.

Predictive relevance of the study

Geisser ( 1974) stated that predictive relevance of the study model is planned to measure the predictive competence of a model. This method to evaluate predictive significance is by implementing blindfolding procedures. This blindfolding method was proposed by Gorondutse and Hilman, (2017) and Geisser ( 1974). In this paper the cross validated redundancy is adopted to evaluates the competence of the model to predict the independent variables and thus, proves the value of the model. Thus, Table 09 shows the construct cross validated redundancy output.

As shown in Table 09 above, this study’s research model has capable importance. Thus, this result is in line with Hair et al. (2014) that suggested that if Q ²> 0, the model has a predictive capability whilst if Q ²< 0, the study model do not pose any predictive ability. Hence, the predictors possess values that are greater than Zero indicating sound predictive model relevance present.

Assessment of importance and performance matrix (IPMA)

This is another PLS-SEM assessment indices Hair et al. ( 2017) stated that Importance and performance matrix analysis is valuable in spreading the results of the basic PLS-SEM consequences using the latent variable scores ( Hair et al., 2017). further, IPMA is beneficial to support scholars to further enlighten and deliberate the results for decision making suggestions. E.g the plotting result shows high reputation and low performance, it assist the organisation to recognise main part of enhancement Hair et al. ( 2017).

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Based on the Figure 04 above, the IPMA of social norms indicate very important for working women to shape their entrepreneurial intention. Thus, the working women entrepreneurs should focus much on social norms in decision making to enables them improved their intention to start new business.

Discussion

Statistically, the association in respect of social norms and working women entrepreneurial intention is positive and significant. The findings also concurred with prior studies that reported positive results between social norms and working women entrepreneurial intention ( Al Mutairi & Fayez, 2015; Almaimouni et al., 2014). Similarly, the relationship between perceived business opportunity and working women entrepreneurial intention revealed significant relation the finding concur with Faisal et al. (2017), Ravi and Nor Aishah ( 2016). The finding indicates that the intention and behaviour has become an important aspects for many person to get involved in entrepreneurship in order to attain a better lifestyle and overwhelmed their monetary issue ( Ravi & Nor Aishah, 2016). Apart from that, a positive behaviour of a person in entrepreneurship is a main key for their intention to choose or not this field as their career in the future and to be thrived in future days. So, it can be determined that the working women in Kano state, Nigeria area have intention to choose entrepreneurship career in the future which has been revealed evidently through this paper.

Implications for theory

The study, in general, has made contributions. First and foremost, contribution of this study to the literature is, it offers deep insight of compound relationships of various variables. Thus, current study fills the theoretical gap that highlighted in the problem statement by extending the current literature through empirical analysis and findings of several study variables. The current study has provided empirical evidence about the relationship of all study variables pertaining to the research framework drawn based on sound literature reviews. The results of this research validate the underpinning theory adopted for the current study on the association between social norms, perceived business opportunity and working women entrepreneurial intention ( Ajzen & Fischbein, 1980; Gorondutse, 2018).

Implications for practice

The result of this paper has suggestions for leaders off SMEs, and policy developers. The reserach increases the reputation of working women entrepreneurial intention in Nigeria. In addition, impact social norms, & perceived business opportunity as predictors has demonstrated significant role. social norms, perceived business opportunity found the significant positive impact on working women entrepreneurial intention.

Limitations of study

Like any other study, this paper has some boundaries that ought to be addressed by future researchers. Initially, the research integrates solitary social norms and perceived business opportunity that impact the working women entrepreneurial intention in Nigeria. in order to solve the limitation, this paper suggested that longitudinal studies. The longitudinal research approach could explain the composite association over a long period of time and could describe well the changes that may advance over time among the constructs.

Suggestions for future study

This paper provides some future research chances. further to the above suggestions on how to address the limitations of the present study, future research may also consider other possibilities. This paper can be protracted by doing multi-segment investigation as well as a contrast of several businesses. Secondly, future studies may consider examining the research model in other contexts. Lastly, in a future study, other variables can be analysed as a moderating or mediating variable to explain the relationship of working women entrepreneurial intention and other predictors of this study.