Micro Macro Entrepreneurship
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Abstract: Most people know that micro and small businesses are the backbone of any economy, whether it's developing or already well-established. A wide variety of MSE expansion behaviors may be identified. Finding and studying the factors that affect the growth of MSEs is the main objective of this research. The external business's accessibility and sales environment were the metrics used to gauge the expansion of MSEs in this study. A number of players and elements impact the organization's success; some of them may be managed, while others cannot. Therefore, it is necessary to examine both the micro and macro environmental elements that significantly affect SIU's performance, bearing this in mind.
Keywords: MSEs, performance, environment and micro
INTRODUCTION
Picture a clothes business set up shop in a neighborhood market. Loyal consumers who provide immediate feedback, regional fabric and accessory suppliers, and close rivals would all make up its microenvironment. These factors have an immediate impact on the client relationships and daily operations of the boutique. Such internal elements constitute the microenvironment.
Nevertheless, the macroenvironment is as crucial. The boutique's bottom line may take a hit if, for example, inflation was to spike or if customer tastes were to shift. Businesses may benefit from taking advantage of online marketing courses by learning to adjust to these changes and create winning strategies. Changes in customer tastes and the nature of businesses might result from technological developments like the proliferation of online marketplaces. Additionally, societal variables, such as shifting ecological concerns or fashion trends, might influence consumer desires. These outside forces make up what is called the macro environment.
An organization's larger, uncontrollable external variables are referred to as the "macro environment" when discussing their impact on performance. It encompasses the following areas: law, politics, economics, society, and technology (PESTEL). Industries and marketplaces are impacted by these variables, which shape strategies and opportunities for the long term. In an ever-evolving global market, companies must adjust to these macro influences if they want to be competitive and in compliance.
Both the micro and macro environments are important to an organization, but the former is concerned with internal matters and stakeholders and the latter with external factors that are beyond its control. Customers, suppliers, rivals, and workers make up the micro environment, whilst economic, technical, social, and political forces, as well as environmental variables, make up the macro environment. While the macro environment has immediate and direct effects on the company, the micro environment has an indirect but noticeable effect.
In contrast to the immutability of the macro environment, the micro environment is under the organization's control. Enterprises need to change and react. The macro environment necessitates access to economic trends, regulatory changes, and technology improvements on a frequent basis, while the micro environment necessitates regular monitoring of rival tactics, supplier performance, and consumer preferences.
LITERATURE REVIEW
Wang, D. (2021) This paper's overarching goal is to learn more about the branding strategies used by micro-enterprises (MEs). Using a comparative method, the study looks at companies in China and the UK. The work's theoretical foundation one example is the Stereotype Content Model (SCM), which claims that things linked to people—like names and logos—are intrinsically evaluated based on their "warmth" (reliability, authenticity, and helpfulness) and "competence" (success, efficiency, and effectiveness). The SCM model incorporates the entity's status—whether distinguished or glamorous—but it does so as a precondition to competency evaluations. A more modern perspective views it as a visual aspect that consumers evaluate without thinking.
Neta, D. S., Shambare, R., & Sigauke, C. (2020) Many entrepreneurs face disappointment when their entrepreneurial dreams and the reality of running a firm don't align in the early stages, when the majority of new enterprises fail. The high incidence of emerging venture attrition in South Africa is supposedly caused, among other things, by these differences that are called an entrepreneurial gap (EG). Even when the majority of the necessary resources have been provided, the company might still fail due to a failure to adequately address this aspect of EG. More has to be understood about the entrepreneur component of early-stage company success, according to this report. In order to help aspiring business owners be better prepared, this article set out to identify and categorize the elements that contribute to entrepreneurial gaps. The results provide solid information that mentors, coaches, and other relevant support systems may utilize to raise the degree of readiness among aspiring entrepreneurs.
Li, T. (2025) The results demonstrate a favorable relationship between financial capital and the entrepreneurial models proposed by Schumpeter and Kirzner. Assigning resources from entrepreneurial endeavors to opportunities is favorably impacted by educational capital. Institutional regulatory settings may also make it easier for entrepreneurs to fund Kirznerian ventures while discouraging them from investing in Schumpeterian ones. Lastly, a larger degree of corruption limits Kirznerian entrepreneurship while encouraging new entrepreneurial activity.
Junsong Chen, Céline Viala, Francesco Schiavone, Giorgia Rivieccio, and David Kalisz (2021) The way of life of a country is one such example. Up until now, user entrepreneurship—one of the growing literature streams in the previous decade—has undervalued this corpus of knowledge. In light of this knowledge vacuum, this study sets out in order to resolve the following inquiry: To what extent are user entrepreneurs influenced by factors at the national level? How does culture play a role in this kind of relationship? The study looked at the effects of the four parts of Thai and Turkina's model of entrepreneurship examines the activities of new business units in the healthcare sector that have been developed by user innovators. The chosen approach makes use of statistical tools derived from polynomial regression models, cluster analysis, and principal component analysis (PCA). The results show that nations whose users engage in comparable entrepreneurial activities tend to cluster together. A non-linear connection among various macro-level factors of health user entrepreneurship is defined by such behavior. Specifically, when a nation's health culture is paired with user entrepreneurship, an inverted U-shaped curve appears. When we look at this nonlinear connection across countries, we see that national culture acts as a moderator.
RESEARCH METHODOLOGY
Analytical and descriptive aspects coexist in this piece. The premise is tested via analytical research, while the difficulties encountered by micro entrepreneurs are studied through descriptive research.
1. First-Party Information
To get to the heart of the matter, entrepreneurs are being polled via questionnaires. Among the intended responders were company owners, many of whom are enduring challenges due to the present state of affairs. The main data for the research is collected via a standardized questionnaire that investigates the different difficulties encountered by microentrepreneurs.
2. Information Gleaned from Secondary Sources
International journals, online publications, government websites, personal accounts, and other sources are consulted for this data.
Design of the Sample The researchers in this study used a "purposive sampling method" to choose their samples.
3. Quantity of Subjects Studied
The vastness and dispersion of the cosmos necessitated sampling in order to conduct scientific investigations. The sample size was 85 answers.
4. Instruments and Methods
Data analysis included the use of percentages and ratios, among other statistical tools. Tabular presentations were among the ways used to display data.
The z-test for proportions is used. Data analysis for tests:
Here = sample proportion,
= hypothetical value = 50% = 0.50, n = sample size
DATA ANALYSIS AND INTERPRETATION
Table 1 Gender classification
Source: Primary Data
Inference: Gender was a factor for 85 respondents, with the respondents is shown in Table 1. Men made up 75% of the sample, while women made up 25%. Males make up the bulk of the responders.
Table 2 Age classification
AGE |
RESPONDENTS |
PRECENTAGE |
Below 25 |
19 |
22 |
26-40 |
25 |
30 |
41-Above 55 |
41 |
48 |
TOTAL |
85 |
100 |
Source: Primary Data
Based on the data in Table 2, we can deduce that, out of 85 total respondents, 48% were in the 41–55 age bracket, with 30% falling into the 26–40 age bracket following closely behind. Contributions from those under the age of 25 were the lowest, at 22%.
Table 3 Initial funding for business
FUNDING FOR INITIAL BUSINESS |
RESPONDENTS |
PERCENTAGE |
Own funds |
46 |
54 |
Loan from Friends and Family |
25 |
29 |
Non-banking financial institution |
4 |
5 |
Commercial Bank Loans |
10 |
12 |
TOTAL |
85 |
100 |
Source: Primary Data
Inference: Of the 85 people who took the survey, 29% wanted to use their own funds, 29% wanted to borrow from family and friends, 12% wanted to use loans from commercial banks, and 5% wanted to use non-banking financial organizations. The full breakdown is in Table 3. When they first started out, most entrepreneurs put their personal money into the venture.
Table 4 Financial obstacles faced while starting business venture
Source: Primary Data
When asked about financial difficulties, 29% of respondents said they were somewhat so, 23% said they were very low, and 14% said they were extremely high. Only 8% said they were low, and 11% said they were very high.
A2-Around 37% of respondents found moderate demand to be a hindrance, whereas just 4% found extremely high demand to be an issue.
While 41% faced considerable hurdles due to a lack of knowledge and skills, 18% faced very low obstacles, and 16% faced low obstacles (A3).
Thirdly, 32% of respondents found a lack of clients to be a moderate impediment, while 6% found it to be a very high difficulty.
A same number of respondents (25%) found competition to be very difficult, while only 10% found it to be extremely so.
Only 5% of responders faced very high difficulties, while 39% had intermediate problems, with A6-Inefficient Planning.
Just 5% of respondents experienced very high difficulties, while 29% had intermediate obstacles, when it came to A7-Fixed Expenditures.
Concerning A8-Working Capital, 29% of respondents reported moderate hurdles, while 9% reported extremely low obstacles.
In their early years of operation, the vast majority of respondents encountered the following challenges: insufficient knowledge and expertise, inadequate funding, little demand, few clients, fierce competition, high fixed expenses, and low working capital.
Table 5 Major constraint of business growth
MAJOR CONSTRAINT |
RESPONDENTS |
PERCENTAGE |
Lack of demand |
17 |
20 |
Lack of finance |
20 |
24 |
Lack of labour |
12 |
15 |
Lack of technology |
14 |
16 |
Lack of marketing |
21 |
25 |
TOTAL |
85 |
100 |
Source: Primary Data
Inference: Table 5 shows that 25% of respondents see a lack of marketing as a key limitation for the expansion of their businesses. Another 24% cite a lack of cash, and 20% cite a lack of demand. Major limitations due to a shortage of labor or technology affected 16% and 15% of respondents, respectively. Respondents mostly have issues with marking.
Table 6. The following is a frequency distribution of managers affected by microenvironmental influences. Data table for calculations
When the p-value is less than 0.05, which is considered statistically significant, the null hypothesis is rejected.
It is possible to reject the null hypothesis that all micro factors are present when the p-value is less than 0.05 in every case.
Table 7 The following is a frequency distribution of managers affected by macro environmental conditions. Data table for calculations:
A p-value below the significance level of 0.05 indicates rejection of the null hypothesis.
All p-values are less than 0.05, hence we may reject the null hypothesis about the all-macro factors.
CONCLUSION
There are two types of environments: micro and macro. Because it includes immediate and particular aspects, adapting to a microenvironment is comparatively easier. In response to the micro environment, businesses may make modifications or adjustments that are within their power. On the other hand, external variables that affect the macro environment are more extensive and sometimes difficult to foresee, making adaptation to this setting more difficult. Before making any strategic moves, businesses should keep a close eye on these factors and study them thoroughly.