Post Covid 19 Transformative Strategies on Sustainability of Women Owned Beauty and Cosmetics Smes in Upper Mount Kenya Counties, Kenya

Post Covid 19 Transformative Strategies on Sustainability of Women Owned Beauty and Cosmetics SMEs in Upper Mount Kenya Counties, Kenya

Dr. Peter Gituma Kimathi¹, Dr Lucy Karimi Njagi²

¹Lecturers Faculty of Business Studies, Chuka University

²Department of Business Administration P.O Box 109-60400. Chuka, Kenya

DOI: https://dx.doi.org/10.47772/IJRISS.2025.914MG0098

Received: 05 May 2025; Accepted: 11 May 2025; Published: 17 June 2025

ABSTRACT

The year 2020 marks the silver jubilee of the Beijing Platform for Action, and was expected to be a moment to celebrate the milestones made in enhancing gender parity and opportunities. However, the effects of COVID-19 pandemic threaten   to erode the minimal gains achieved this far. Amidst COVID-19, Women-led enterprises across Africa have significantly been impacted. UN Women, conducted a survey on women SME owners across 30 African countries which revealed that most women-led SMEs are at risk of permanent business shutdown as a result of the pandemic. The pandemic, initially was health hazard, fast mutated to a twin-menace that would threaten both lives and livelihoods. Global stock markets plunged in value by about US$6 trillion in less than a week (24th to 28th February 2020), according to S & P Dow Jones Indices with many yet to recover. The pandemic decelerated Kenyas projected GDP growth which resulted to Central Bank of Kenya revising its estimate for 2020 from the initial 6.2% to 3.4%. Most affected were Small and Medium Enterprises; due to limited resources that disabled them to withstand prolonged uncertainty and multi-faceted restrictions, as a result of the pandemic. Key among the ventures threatened with extinction are women owned small and Medium Enterprises that faced numerous post-pandemic challenges. The inevitable priority shift to women entrepreneurs, diversion of business funds, sharp decline in demand and supply of commodities, together with costly production. The research reviewed the impact of post COVID-19 on women owned Beauty and cosmetics enterprises in upper Mount Kenya counties on the basis of affordable credit facilities, networking and Market innovativeness, different sectors had their ways in which women enterprises had been affected by the pandemic. Theories supporting this magnitude of impact are limited too; with the closest being resource dependency theory, structural inertia theory and real options theory. The study applied both primary and secondary data collection method on a sample of 35 respondents. Findings based on the study objectives revealed that women owned enterprises are disproportionately affected by the pandemic. The study   recommends advancement on networking, creating environment and culture for innovation and resource interventions to help women owned SMEs upscale them from post -Covid effect and necessary preparations for re-occurrence of similar pandemics in future.

Keywords: Covid 19 pandemic, Transformative strategies, women owned businesses, small and medium enterprises

Background of the study

The COVID-19 pandemic has taken a profound toll on businesses across the globe. The dual shock of the coronavirus pandemic and government mandated economic shutdowns to contain the spread of the virus plunged the world economy into a deep recession in 2020 (Long and Ascent, 2020). COVID-19 has completely changed and disrupted many jobs, markets, and industries. In particular, the cosmetic industry has been hit hard since consumers are now staying home more frequently and also wearing masks in public. Many consistent cosmetic consumers may not see the value in using, let alone buying, cosmetics when their job or school may only require virtual meetings. Additionally, mask requirements may affect any type of lip and, partially, face cosmetic usage (Altman, 2020). So how exactly has COVID-19 impacted the cosmetic industry’s markets, jobs, and overall direction? Consumers may or may not notice a significant change since the cosmetic industry was at its height in 2018 (Statista, 2020). However, due to the pandemic, the cosmetic industry in the United States is expected to decline 17.6% in 2020 as well as expected to lose revenue and experience noteworthy setbacks (Fernandez, 2020; Global Cosmetic Industry, 2020; Hiner, 2020). Due to these significant changes, it is imperative that past success is compared to the industry’s current state. Understanding the past and present will give insight into forecasting the future. For example, understanding the industry’s past and present status will illustrate both revenue and job losses that have occurred. To examine the issue further, a survey has been created specifically for this Honors thesis that may showAll around the world, firms had to cope with a broad range of concurrent challenges, including suspensions of their in-person operations, mobility restrictions, a remote workforce, supply chain disruptions, and falling consumer demand. The beauty and cosmetics industry has become Kenya’s new hub of investment that is pulling in big money to establish new lines of business and to snap up successful enterprises through multi-million-shilling acquisition deals. Cosmetics play an important role in enhancing one’s inherent beauty and physical features. Men have also joined this industry with a number of products designed for them lately, which was not the case before.

Small and Medium Enterprises play a significant and indispensable role in the economic development of a country. They generate varied sources of income, create employment, enhance innovation and competition, provide opportunity for upskilling, and ultimately help improve living standards. These in turn promote entrepreneurship, build an industrial base at diverse levels and build resilience of economies (Anyanga & Nyamita, 2016; KNBS, 2016; Miles, Lehman & Fillis, 2017). Success of any economy depends on the success of businesses within it; MSMEs thus form the backbone of most economies (Ndiaye, Razak, Nagayev & Ng, 2018).  Networking helps enterprises to build their reputation, create a competitive advantage, and engage stakeholders. Moreover, by actively talking to or involving stakeholders which supports sustainable development.

Statement Of Problem

Health crisis stifled the global economy in two major ways namely social distancing in a bid to curb the spread of this virus which led to shutdown of financial markets, businesses and all social gathering, and the intensified uncertainty around the hasty rate of spread of the virus, which led to hibernation among consumers and investors. Both demand and supply were thus adversely affected. The cosmetic industry is a multi-billion-dollar industry that has taken a financial hit in 2020 due to COVID-19. The drop in cosmetic usage leaves the industry in question for future consumer intention and behavior. By the summer of 2020, revenue had dropped by 7.4%, and employment dropped by 3.91%. With dwindling numbers in revenue and jobs, marketers must grasp the changes in consumer behavior and attitudes so that new strategies can be implemented. With updated strategy and priorities, marketers can pull the cosmetic industry back to pre-COVID-19 numbers. Kenya ranks among the top ten most vulnerable economies to COVID-19, largely due to her close interrelations with China, and given that Kenya, like most other developing nations, is not well prepared to handle the impact of a health pandemic of such magnitude. Impact in the rural areas is more and direct; largely resulting from the disruption of the supply chain and fluctuating operations due to undeveloped infrastructures among other factors Continued challenges in obtaining capital for growth among women owned businesses will further be compounded by the effects of the pandemic, as most women owned ventures will not have favorable business performance record to qualify for these loans. For an economy like Kenya where women owned ventures are mostly small and informal, the number of women entrepreneurs accessing funding over the years has been negligible. Level of networking and collaboration still remains low. The levels of technology adoption through innovativeness needs to be harnessed within women owned SMEs. These necessities a need to carry a research to uncover post Covid 19 transformative strategies on sustainability of women owned SMEs in upper Mount Kenya Counties.

General Objective of the Study

The general objective of the study was to investigate post Covid 19 transformative strategies on sustainability of women owned beauty and cosmetics SMEs in upper Mount Kenya Counties

Specific Objectives

The study will be guided by the following specific objectives:

• To assess the effect of access to affordable credit on sustainability of women owned beauty and cosmetics SMEs in upper Mount Kenya Counties
• To establish the influence of networking on sustainability of women owned beauty and cosmetics SMEs in upper Mount Kenya Counties
• To assess the impact Market innovativeness on sustainability of women owned beauty and cosmetics SMEs in upper Mount Kenya Counties
• To assess the joint effect of post Covid 19 transformative strategies on sustainability of women owned beauty and cosmetics SMEs in upper Mount Kenya Counties

Study Hypotheses

• Ho: There is no statistical significance influence between access to affordable credit and sustainability of women owned beauty and cosmetics SMEs in upper Mount Kenya Counties
• Ho: There is no statistical significance Influence between networking and sustainability of women owned beauty and cosmetics SMEs in upper Mount Kenya Counties
• Ho: There is no statistical significance influence between Market innovativeness and sustainability of women owned beauty and cosmetics SMEs in upper Mount Kenya Counties
• Ho: There is no joint statistical significance Influence between post Covid 19 transformative strategies and sustainability of women owned beauty and cosmetics SMEs in upper Mount Kenya Counties

Study Location

Mount Kenya is located in the former Eastern and Central provinces of Kenya, now Meru, Embu, Laikipia, Kirinyaga, Nyeri and Tharaka Nithi counties, about 90 kilometres north of the equator, around 150 km north-northeast of the capital Nairobi. The main economic activities includes: crop production (industrial & food crops), horticulture, livestock, fisheries, forestry, catering and accommodation and other service industries

Justification of the study

The researcher singled out Beauty and cosmetics women owned enterprises. In Kenya is the key drivers of the Kenyan economy include a strong population growth, a growing number of people belonging to the middle-class and an educated workforce. Increased growth of the beauty and personal care market in Kenya, combined with the fact that Kenya is recognized as the sales and distribution hub for the larger East African market, has attracted many international brands. Improvement and change in the current lifestyles of individuals have been among the key factors to the major growth of the Kenya Beauty and cosmetics industry. Consumers have now become more conscious regarding the usage of cosmetics in their daily lives in an effort to step up their style quotient and overall personality.

LITERATURE REVIEW

Theoretical Review

Due to the novelty of this pandemic and its effects, there seems to be a limited theoretical backing for businesses during such uncertainties. Craighead et. al., (2020), proposes that pandemics are qualitatively very different from typical business disruptions; hence scholars must sharpen their theoretical tools in line with the new theoretical demands made of them and the survival of MSMEs. The proposed theories, though limited in view of the pandemic‟s impact, are Resource Dependency theory, Structural Inertia theory and Real Options theory.

Resource dependence theory (RDT) argues that businesses depend on others within their environment for access to critical inputs such as materials, labor, and cash (Pfeffer & Salancik, 1978). Dependence thus generates uncertainty as the external parties may fail the firm for various reasons. Ventures react by putting in place strategies and structures that may decrease or eliminate their dependence on external parties. While the strategies may have proved workable for normal modes of operation and typical disruptions, both the structures and strategies may not handle the supersonic speed and nature of pandemics.

Structural Inertia theory, arising through evolution of population ecology thinking, portends that structural inertia (natural selection beyond the firm‟s control) explains why some businesses cannot adjust to changing conditions (Hannan & Freeman, 1984). Ordinarily, women owned MSMEs tend to fail more than men owned and larger firms due to resource limitations among other factors (Hannan & Freeman, 1984). In times of strife, the risk is amplified because the women owned MSMEs do not operate on a level ground with their counterparts, and they often lack the resources requisite for the level of „transiliency‟ (resilience during transition) needed for survival (Craighead et. al., 2020).

Real options theory (Myers, 1977), has a focal point on how managers can make better decisions when faced with uncertainty; by creating real option for themselves in which they have an opportunity rather than an obligation to take daring decisions. Undoubtedly, pandemics such as COVID-19 have created the highest level of uncertainty in modern history, thus leaving the entrepreneurs in precarious situations.

Empirical Review

COVID-19 pandemic has proven to be one of the largest disruptions in contemporary history; having spread to over 200 countries and regions around the world and subsequently triggered the worst economic depression since the Great Depression (International Monetary Fund, 2020). Governments and businesses alike initially went into panic mode, torn between choosing lives or livelihoods, which seemed mutually exclusive (McKinsey & Company, 2020). Most governments chose the former and put in place measures and restrictions intended to curb the spread of the virus. Demands were made on the businesses that required swift decisioning with little or no cushioning or fallback options; the situation was dire.

Micro, Small and Medium Enterprises have been hardest hit by the effects of this pandemic – from the curfews, social distancing, to the supply chain disruptions that saw them compelled to close much earlier, shut down (entertainment and personal service sectors), and contend with shortage of much needed supplies (World Bank, 2020). Women-owned businesses suffered a bigger blow as the stay-home campaigns became the „only‟ solution at hand; the women entrepreneurs had to revert to their first role – unpaid home care, while businesses took a distant last in the list of priorities. Business resources were diverted in a bid to stockpile for the families, self-medicate at home for fear of going to hospitals for all other ailments, and supporting the struggling extended families (United Nations, 2020).

Bartika, Bertrand, Cullenc, Glaeserd, Lucac, and Stanton, (2020), took a survey of over 5,800 MSMEs operating in the United States of America. The survey was administered in collaboration with Alignable, a network-based platform that focuses on the MSME ecosystem. The findings were that small businesses were financially very fragile, with most having less than one month‟s worth of expenses at hand. Barely few weeks into the pandemic, 43 of small businesses had temporarily closed; risk of permanent closure was negatively related to the length of the catastrophe. If despite the administrative support of small businesses in America the impact was so severe weeks into the crisis, how much worse for developing economies like Kenya where small business operate with minimal capital, are heavily dependent on routine transactions and quite a limited number of local customers (Williams & Schaefer, 2020).

Conceptual Framework

Independent variable                                        Dependent variable

Transformative Strategies

Figure 1. Conceptual Framework

RESEARCH METHODOLOGY

Research Design

The study adopted a descriptive survey research design, to describe the state of affairs as they existed in the study. This design helped in establishing the influence of post Covid 19 transformative strategies on sustainability of women owned SMEs in upper Mount Kenya Counties, Kenya .A research design, is important in studying the inter-relations between the study variables. (Mugenda & Mugenda, 2003).

Target Population

The study conducted a survey on 35 registered Beauty and cosmetics women owned SMEs in upper Mount Kenya Counties, Kenya dully registered by Ministry of trade and industries. According to Ministry of Trade,Co-operative and Tourism (2023), there are 150 registered large beauty and cosmetics women owned SMEs in upper Mount Kenya Counties, The respondents were 35owners  of these enterprises. For reliability the study focused on Meru and Embu County since the population shared similar characteristics

Data Collection Procedures

The questionnaire were administered on drop and pick to the owners of these enterprises with the help of two research assistant.

Data Analysis

The data collected from the questionnaires was first arranged and coded and later analyzed using both descriptive and inferential statistics through Statistical Packages for Social Sciences (SPSS), version 24. A statistical test of internal consistency of the test items was carried out. The computation of Cronbach’s alpha facilitated this test. According to Allen and Yen (2002), Cronbach’s alpha splits all the questions on the instrument every possible way and computes correlation values for them all. In the end, output is one number for Cronbach’s alpha and just like a correlation coefficient, the closer it is to one, the higher the reliability estimate of the instrument. Cronbach’s alpha is a less conservative estimate of reliability than test/retest. Items with low correlation coefficients were considered inappropriate as they may not be measuring what they are supposed to measure. As a rule of the thumb, items with coefficients of 0.7 and above are acceptable while those falling below are suspect and thus are excluded. In this study, all the items used for both exit strategy and survival had Cronbach’s alpha of more than 0.7, hence all were included for analysis.

Data Presentation

Data was presented in form of tables showing, percentages, mean and standard deviation. Correlation was done to determine, the strength of the relationship between dependent and independent variables. Multiple regression analysis was also done to test hypothesis and to show the relationship between dependent and independent variables.

RESULTS AND DISCUSSIONS

The study achieved a response rate of 95% (33 out of 35targeted enterprises which was considered adequate for analysis. Majority of the enterprises that participated in the study were 5 – 20 years old (66.6%), 20.5% were below 5 years old. The rest (12.9%) were more than 20 years old. The purpose of this study was to investigate the influence post covid 19 transformative strategies on sustainability of women owned smes in upper mount Kenya Counties, Kenya

Reliability Test

The study conducted a reliability test to establish if the research instrument was reliable. Cronbach’s alpha was used. A coefficient of 0.7 is recommended for a newly established questionnaire (Hassan & Marston, 2019).

Table 1: Summary of the Reliability Coefficients

 Source: Survey Data, (2024)

The findings in Table 1, indicate reliability levels of the instrument ranging from 0.885 for Information Communication Technology, 0.891 for Data Management, 0.781 for on-line marketing, 0.834 for Sustainability and the overall reliability is 0.847. These levels are above the acceptable minimum value of 0.50 and above the recommended value of 0.7. Therefore, the instrument was considered to have appropriately measured the relevant information.

Diagnostic Tests

To ascertain fitness of the model normality, multicollinearity, autocorrelation and heteroscedasticity diagnostic tests were conducted. This was to establish if the assumptions of the Ordinary Least Squares hold.

Normality Test

The researcher used Shapiro-Wilk test to determine the normality of the error term. Results of the test are depicted in Table 2.

Table 2: Normality test for the Residual

Source: Survey Data, (2024)

Results in Table 2, show the Shapiro wilk statistic for Affordable Credit, Networking and Market Innovativeness  were all greater than 0.05, hence showing a normal distribution of the residual. Test statics of greater than 0.05 indicate a normal distribution of the residual (Gissane, 2016). Therefore, it was suitable for use in further analysis since the residual was normal.

Multicollinearity Test

The study undertook multi-collinearity test by means of variance inflation factor (VIF) consequent to examining tolerance values. A tolerance value of more than 0.1 for all the independent and dependent variables signifies no multi-collinearity while a VIF of more than 10, signifies a problem of multi-collinearity (Field, 2009).

Table 3: Multi-Collinearity Coefficients

Results in Table 3, shows all the variables had variance inflation factor of less than 10 and tolerance values greater than 0.1, hence ruling out the chance of multi-collinearity. Therefore, the findings of this study can be relied upon.

Autocorrelation Test

The study employed Durbin-Watson (DW) test to detect presence of autocorrelation. A Durbin Watson of zero implies presence of positive autocorrelation, while a Durbin Watson of 4 implies high negative correlation level. A Durbin Watson of between 2 and 2.5 implies that, there is no existence of autocorrelation (Nassiuma, 2010). The results are presented in Table 4

Table 4: Autocorrelation Test

 The results in Table 4 shows that the study statistic obtained was 2.067 implying that there was no evidence of autocorrelation.

Heteroscedasticity Test

Heteroscedasticity arises when the error term does not have a constant variance. Heteroscedasticity was tested using residual plots method.

Figure 2: Heteroscedasticity Test

Source: Survey Data, (2024)

Heteroscedasticity is present, when the widths of the residuals increase or decrease as the predicted variables increase. From the graph above, the width of the plots does not evenly increase or decrease as the predicted variable increase and also no specific pattern formed hence no evidence of the existence of heteroscedasticity.

Descriptive Analysis of Study Variables

This contains the descriptive statistics of the study variables; Access to affordable credit, Networking, Market Innovativeness and Sustainability. A five -point Likert scale was used, where 1 = not at all; 2 = less extent; 3 = moderate extent; 4 = great extent and 5 = very great extent. The descriptive statistics that summarize the responses are percentages, mean and standard deviation as depicted in Tables 5, 6, 7, 8, 9 and 10.

Access to Affordable Credit

The results of the descriptive statistics for are summarized as shown in Table .5

Table 5: Descriptive Statistics for Affordable Credit

Results in Table 5 shows that majority (56.7%) agreed that they had not accessed women enterprise funds followed by 20.6% to less extent, on the aspect of youth enterprise funds within majority 60.6% had not accessed, on the aspect of Affirmative action funds majority (58.6%) agreed they had not accessed

Networking

The responses from the statements relating to Networking are summarized in Table 6.

Table 6: Descriptive Statistics for Networking

The results from table 6 above shows that majority (62.2%) of respondents indicated they had not attended any training (52.6%) of respondents indicated they had not attended any training workshop (59.7%) stated there engage in any exchange programs and benchmarking.

Market Innovativeness

The responses from the statements relating to Market Innovativeness, are summarized in Table 7.

Table 7: Descriptive Statistics for Market Innovativeness

The results from table 7 above shows that majority (54.2%) of the respondents does not market their products and services on-line, Majority (56.6%) indicated that enterprise is not connected to online procurement while majority (58.7%) indicated that they do not interact with their customers on social media for marketing

Enterprise Sustainability

The results of descriptive statistics relating to Enterprise Sustainability measures are as depicted in Table 8.

Table 8: Descriptive Statistics for Enterprise Sustainability

The results from table 8 above shows that majority (66.5%) of the respondents indicated that sales were not growing steadily at the same time majority (71.1%) indicated that the demand for their products was not increasing, majority (68.4%) indicated that incomes have not grown over time, majority (63.6%) indicated that there were no reduction of expenses and costs in the enterprises, majority (68.4%) also indicate that enterprises did not record increase of profits over the time.

Table 9: Descriptive Statistics for Transformative Strategies

Regression and Correlation Analysis of the Study Variables

The researcher used correlation and regression to analyze the relationship between the study variables. Pearson correlation, was used to establish the strength of the relationship between Transformative Strategies and Enterprise Sustainability while regression analysis was conducted to show the relationship between Transformative Strategies and Enterprise Sustainability of Beauty and Cosmetics Women enterprises. The results are depicted in below Tables

Influence of Access to Affordable Credit on Enterprise Sustainability of Beauty and Cosmetics Women Enterprises

The first objective was to establish the influence of access to affordable credit on the enterprise sustainability of beauty and cosmetics women enterprises. The following null hypothesis was tested:

Ho₁. Access to affordable credit has no statistically significant influence on the Enterprise Sustainability of beauty and cosmetics Women SMEs in upper Mount Kenya Counties

Table 10a: Summary of Regression Model for access to Affordable Credit

 Results in Table 10, shows an R square of 0.138. This implies that, access to affordable credit contributes 13.8% of the changes in enterprise sustainability while the 87.5% is attributed to other factors excluded in the model.

Table 10b: Analysis of Variance for Access to Affordable Credit

Results on Table 10b, shows (F=12.761, p=0.000). The p-value was less than 0.05, hence indicating, the model testing the influence of access to affordable credit on Enterprise sustainability was statistically significant. This means information communication technology is a good predictor of Enterprise sustainability.

Table 10c: Regression Coefficients for Access to affordable Credit

Results in Table 10c, indicates positive and significant relationship between Affordable credit and Enterprise sustainability (β = 0.274, p value < 0.05). This implies that, a unit change in affordable credit, increases Enterprise sustainability by 0.374 units. The study found a constant of 3.289 with a slope of 0.645. The t-statistic was 4.832 at a P-value of 0.00 which is less than the acceptable level of 0.05. The simple regression model for affordable credit is presented by the equation below.

Table 10d: Correlation between affordable credit and Enterprise Sustainability

As indicated in Table 10d, the coefficient was 0.264 with p –value of 0.000. This implies that, there exists a positive relationship between affordable credit and enterprise sustainability. If affordable credit was improved by a unit, the level of enterprise sustainability would also improve by 0.364 units. Therefore, the null hypothesis was rejected.

Influence of Networking on Enterprise Sustainability of Beauty and Cosmetics of Women SMEs in upper Mount Kenya Counties

The second objective was to establish the influence of networking on the enterprise Sustainability of beauty and cosmetics of Women SMEs in upper Mount Kenya Counties

 The following null hypothesis was tested:

Ho₁. Networking has no statistically significant influence on the Enterprise Sustainability of beauty and cosmetics of Women SMEs in upper Mount Kenya Counties

Table 11a: Summary of Regression model for Networking

Results in Table 11a, shows an R square of 0.175. This implies that, networking contributes 17.5% of the changes in enterprise sustainability while the 83.5% is attributed to other factors excluded in the model.

Table 11b: Analysis of Variance for Networking

Results on Table 11b, shows (F=12.871, p=0.000). The p-value was less than 0.05, hence indicating, the model testing the influence of Networking on enterprise sustainability was statistically significant. This means Networking is a good predictor of enterprise sustainability.

Table 11c: Regression Coefficients for Networking

Results in Table 11c, indicates positive and significant relationship between Networking and Enterprise sustainability (β = 0.385, p value < 0.05). This implies that, a unit change in Networking, increases enterprise sustainability by 0.374 units. The study found a constant of 2.529 with a slope of 0.485. The t-statistic was 4.542 at a P-value of 0.00 which is less than the acceptable level of 0.05. The simple regression model for networking is presented by the equation below.

Table 11d: Correlation between Networking and Enterprise Sustainability

As indicated in Table 11d, the coefficient was 0.384 with p –value of 0.000. This implies that, there exists a positive relationship between networking and enterprise sustainability. If networking was improved by a unit, the level of enterprise sustainability would also improve by 0.374 units. Therefore, the null hypothesis was rejected.

Influence of Market Innovativeness on Sustainability of Beauty and Cosmetics of Women SMEs in upper Mount Kenya Counties

The Third objective was to establish the influence of market Innovativeness on the market Sustainability of Beauty and Cosmetics of Women SMEs in upper Mount Kenya Counties

The following null hypothesis was tested:

Ho₁.  Market innovativeness has no statistically significant influence on the Sustainability of Beauty and Cosmetics of Women SMEs in upper Mount Kenya Counties

Table 12a: Summary of Regression Model for Market Innovativeness

Results in Table 12a, shows an r² of 0.19. This indicates that 19% of the changes in sustainability, can be explained Market Innovativeness, whereas, the remaining 81% is due to other factors not in the model.

Table 12b: Analysis of variance for Market Innovativeness

Results on Table 12b, shows (F=14.780, p=0.000). The p-value is less than the acceptable level of 0.05, hence indicating that the model testing the influence market Innovativeness on Enterprise sustainability was statistically significant. This means, market Innovativeness is a good predictor of Enterprise sustainability.

Table 12c: Regression Coefficients for Market Innovativeness

Results in Table 12c, indicate a positive and significant relationship between market Innovativeness and enterprise sustainability of Beauty and Cosmetics enterprises. (β = 0.378, p value < 0.05). This implies, a unit change in marketing innovativeness increases enterprise sustainability of Beauty and Cosmetics enterprises by 0.378 units. The constant of regression was 2.560 with a slope of 0.309. The t-statistic obtained was 6.213 at a P-value of 0.00 which was within the acceptable level of 0.05. This implies market innovativeness has statistically significant influence on enterprise sustainability. The simple regression model for Market Innovativeness is presented by the equation below.

Table 12d: Correlation between Market Innovativeness and Enterprise Sustainability

As indicated in table12d relating Market Innovativeness and Enterprise Sustainability, the coefficient was 0.368 with a significance value less than 5%. This implies that there exists a positive relationship between market innovativeness and Enterprise Sustainability. This means that, if market innovativeness is improved by a unit, the level of Enterprise Sustainability would improve by 0.368 units. Therefore, rejecting the null hypothesis which stated that market sustainability has no statistically significant influence on Enterprise Sustainability of Beauty and Cosmetics of Women SMEs in upper Mount Kenya Counties

Joint influence of Networking, Affordable Credit and Market Innovativeness and Enterprise Sustainability

The fourth objective was to determine whether Networking, Affordable Credit and Market Innovativeness have a joint influence on the Enterprise sustainability of Beauty and Cosmetics of Women SMEs in upper Mount Kenya Counties

The null hypothesis was: Ho₄: Networking, Affordable Credit and Market Innovativeness have no statistically significant joint influence on sustainability of Beauty and Cosmetics of Women SMEs in upper Mount Kenya Counties

Table 13a: Summary of regression model for Networking, Affordable Credit and Market Innovativeness

The model summary for the joint influence showed an r square of 0.233 which implied that 23.3% of changes in sustainability of Beauty and Cosmetics of Women SMEs was associated with Networking, Affordable Credit and Market Innovativeness while the remaining 76.7% can be attributed to other reasons not factored in the model. This means that overall Transformative Strategies had more impact on Enterprise sustainability as opposed to impact of individual dimensions. Networking explained 17.5.%, Affordable Credit 13.8 % and Market Innovativeness 19.0% of the changes in Enterprise sustainability these results were similar to those of Jones (2020) who viewed digital technology adoption as a uni-dimensional construct.

Table 13b: Analysis of Variance for Networking, Affordable Credit and Market Innovativeness

The results in Table 13b shows that the combination of Networking, Affordable Credit and Market Innovativeness significantly have jointly influence on Enterprise sustainability of Beauty and Cosmetics of Women SMEs since the significance value was within the acceptable level of 0.05.

Table 13c: Regression Coefficients for Networking, Affordable Credit and Market Innovativeness

The unstandardized coefficients for Networking (r = 0.336, p = 0. 006) and Affordable credit (r = 0.266, p = 0.019) and market Innovativeness (r = 0.248, p = 0.045) shows that they are positively and significantly related to Enterprise Sustainability.

The model equation is presented as follows;

This implies that, a unit increase in Networking will increase sustainability by 0.336 units, a unit increase in Affordable credit will increase sustainability by 0.266 units while a unit increase in  market Innovativeness will increase the Enterprise Sustainability by 0.248 units. Finally, the positive constant (2.412) represents all other factors not included in the model, but can influence Enterprise Sustainability.

Table 13d: Correlation between Networking, Affordable Credit and Market Innovativeness

Enterprise Sustainability

Networking, Affordable Credit and Market Innovativeness had positive impact on Enterprise Sustainability as shown in table 13d. This means as Networking, Affordable Credit and Market Innovativeness increase, so does Enterprise Sustainability. These results reveal that Transformative Strategies jointly influence Enterprise sustainability of Beauty and Cosmetics of Women SMEs These results are similar to previous studies which concluded that Transformative Strategies significantly influence sustainability of Agri-Enterprises (Kollmann and Stöckmann, 2019; Lin et al., 2018; Wang, 2018; Lumpkin and Dess, 1996).

SUMMARY, CONCLUSIONS AND RECOMMENDATIONS

Summary of the Findings

The study sought to investigate post Covid 19 transformative strategies on sustainability of women owned beauty and cosmetics SMEs in upper Mount Kenya Counties where Enterprise Sustainability was measured in terms of Sales Volume, New product lines and Market size. The first objective was to assess the effect of access to affordable credit on sustainability of women owned beauty and cosmetics SMEs in upper Mount Kenya Counties .Descriptive statistics revealed that most of the enterprises did not access the affordable credit in terms of Youth Enterprise Funds, Women enterprise funds and Affirmative Action funds

The second objective was to establish the influence of networking on sustainability of women owned beauty and cosmetics SMEs in upper Mount Kenya Counties Descriptive statistics revealed that most of these enterprises we not open to networks, partnerships and collaborations on the basis of organizing or organized trainings, workshops and benchmarking.

The third objective was to determine the impact Market innovativeness on sustainability of women owned beauty and cosmetics SMEs in upper Mount Kenya Counties. Descriptive statistics revealed that most of these firms were unable to promote their products and services through On-line Advertisement, On-line Procurement and Social Media Marketing to be able to respond to market changes and secure bigger share of market. Correlation and regression results indicated that online advertisement had highest positive and significant impact on enterprise sustainability of beauty and cosmetics SMEs in upper Mount Kenya Counties.

The fourth objective was to determine assess the joint effect of post Covid 19 transformative strategies on sustainability of women owned beauty and cosmetics SMEs in upper Mount Kenya Counties. The results of the hypothesis testing found out that transformative strategies has a strong, positive and statistically significant relationship on enterprise sustainability. Additionally, access to affordable credit had the highest mean followed by market innovativeness and then networking. The null hypothesis which stated that transformative strategies have no statistically significant joint influence on the enterprise sustainability of beauty and cosmetics SMEs in upper Mount Kenya Counties. Was rejected.

Conclusions

Based on the summary of the findings, the study revealed there was a positive relationship between access to affordable credits and enterprise sustainability. Therefore, there is a need to orientate the owners of these enterprises about the available source of these credit namely: Youth enterprise funds, Women enterprise funds, Affirmative Action funds.

The study also concluded that beauty and cosmetics SMEs, should be invest in modern technology including social media email, and web-based advertising, text and multimedia messages to improve sustainability. Investing in ICT supports sustainable economic development by improving connectivity digital public services, which can accelerate the implementation of the enterprise goals and objectives by providing tools and technologies to address various dimensions of sustainable development, such as economic, social, and environmental aspects.

Market Innovativeness was noted to contribute positively to sustainability of beauty and cosmetics there is a need for Enterprises embark on On-line Advertisement On-line Procurement Social Media Marketing to launch stern competitive promotions and interact with consumers. Against the backdrop of the stern competition, online marketing needs to be key as a way to drive sustainable strategies for enterprises Access to affordable credit also had a strong, positive and statistically significant relationship on sustainability of beauty and cosmetic Enterprises. These results were in agreement with innovation Theory which proposes that, firms innovates enjoys competitive advantage and able to increase market size and share which is a crude source for sustainability.

Recommendations

The study recommends the following based on the conclusions from the study;

• Beauty and cosmetic Enterprises need to source for government affordable credit ie Youth enterprise funds, Women enterprise funds, Affirmative Action funds among others to enable them absolve the shocks of post COVID 19 challenges
• Beauty and cosmetic Enterprises need to think about economic supportive strategies that supports collaboration, innovation, and continuous learning. By fostering a culture of collaboration and continuous improvement of the enterprises to create a competitive advantage and drive long-term success in the digital age.
• Market Innovativeness requires ongoing learning and adaptation since technologies and market dynamics evolve rapidly. By investing in employee training and digital transformation efforts, businesses can ensure that their workforce is equipped with the necessary skills and knowledge to navigate the digital landscape.
• Beauty and cosmetic Enterprises should invest in researching new opportunities to enable them stay a step ahead of their competitors. For a business to survive, it must grow and acquire new opportunities. The Internet allows a business to virtually travel into new markets at a reduced cost
• There is a need by the both Central and County Governments to take initiative by informing theses enterprises on availability of affordable credit to enhance their sustainable resulting from post COVID 19 effects.

Suggestions for Further Research

The researcher suggested the following for future research;

• Other scholars can conceptualize transformative strategies using other dimensions and their impact on performance, to assess if the results will differ.
• Further research can be carried out with moderators to check effect on the relationship between transformative strategies and sustainability in other industries other than beauty and cosmetics Enterprises
• Future researchers may use longitudinal data rather than cross sectional data to limit biasness of respondents. This would enable them to study patterns and past trends.

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