*Article* **Strategic Entrepreneurship and the Performance of Women-Owned Fish Processing Units in Cibinong District, Bogor Regency**

**Aditya Ari Yudhanto \*, Emma Rochima and Rivani**

Regional Innovation Graduate School, Universitas Padjadjaran, Bandung 45363, Indonesia

**\*** Correspondence: aditya21014@mail.unpad.ac.id

**Abstract:** Strategic entrepreneurship refers to the ability of an MSME to investigate potential entrepreneurial ventures while exploiting its current competitive advantages. Academics and practitioners have offered models to deconstruct strategic entrepreneurship; however, there are few distinctive strategic entrepreneurship models appropriate for certain business circumstances. Culinary businesses in Cibinong District, Bogor Regency face several challenges, including low-quality human resources, inadequate capital and technology, and poor entrepreneurial spirit. This study aims to learn how the performance of women-owned fish processing MSMEs under COVID-19 conditions connects to several strategic entrepreneurship components, such as environmental factors, individual resources, resource orchestration, and competitive advantage. Research data taken from 30 women-owned fish processing businesses were processed using SMART-PLS 3.0, followed by a quantitative descriptive method analysis. The outcome was that the components of the environment, specific resources, and orchestration of those resources could generate performance and value for the customer, leading to competitive advantages. This research provides a current understanding of attitudes to businesswomen's activities throughout the pandemic period, particularly in relation to entrepreneurship chances and MSME performance. Strategic entrepreneurship is necessary to improve performance in dynamic environments.

**Keywords:** businesswomen; environmental factors; individual resources; organizational resources; resource orchestration; creating performance; entrepreneurship

#### **1. Introduction**

The adoption of financial and nonfinancial initiatives within businesswomen's organizations has a number of benefits for businesses. Financial indicators are typically used to assess a company's efficiency; on the other hand, some nonfinancial measurements, such as customer loyalty and employee happiness, need to be considered and cannot be disregarded (Visedsun and Terdpaopong 2021). It is important to take into account how the organizational climate, including leadership, culture, and organizational structure, might impact an organization's success (Odongo et al. 2019).

One of the dynamic environmental factors that micro, small, and medium enterprises (MSMEs) must address in 2020 is the COVID-19 outbreak. Regrettably, social distance restrictions have decreased the number of customers, especially in the food and culinary industries. Many firms can prosper in a changing environment by seeking new business opportunities, such as incorporating activity on websites, applications, social media, ecommerce, and the exploitation of other resources. Despite the COVID-19 outbreak having an influence on the MSME food or culinary processing business, it is still rated as a high performer and a possible winner (Dcode Economic and Financial Consulting 2020). Entrepreneurs need to be more creative, aggressive, and competitive to survive and perform well in a dynamic economy. Strategic entrepreneurship is the term for this style of conduct (Ireland et al. 2003).

**Citation:** Yudhanto, Aditya Ari, Emma Rochima, and Rivani. 2023. Strategic Entrepreneurship and the Performance of Women-Owned Fish Processing Units in Cibinong District, Bogor Regency. *Economies* 11: 88. https://doi.org/10.3390/ economies11030088

Academic Editors: María del Carmen Valls Martínez, José-María Montero and Pedro Antonio Martín Cervantes

Received: 30 December 2022 Revised: 4 March 2023 Accepted: 9 March 2023 Published: 13 March 2023

**Copyright:** © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

The concept of strategic entrepreneurship helps businesses, despite size and age, produce superior performance and preserve profits through opportunity- and advantageseeking activities to reach prosperity in a dynamic and globalizing environment (Tülüce and Yurtkur 2015; Zucchella and Magnani 2016). Strategic entrepreneurship may increase the variety of goods on the market, create new market niches, and stimulate novel forms of competition (Kantur 2016). To increase profitability and market share, businesses of all sizes should integrate strategic entrepreneurship into their operations (Dogan 2015). MSMEs may be capable of continuing to achieve their primary goal of promoting economic growth, value creation, competitiveness, and employment (Awang et al. 2015).

A strategic entrepreneurial approach is appropriate for small and large organizations (Papulova and Papulova 2015). Entrepreneurship can influence national economic growth, including in Indonesia. Indonesia must quicken and elevate the caliber of its economic growth as a growing country. To create competitive entrepreneurial circumstances, it is essential to construct an entrepreneurial ecosystem (Iqbal et al. 2021). According to the Ministry of Cooperatives and MSMEs of Indonesia, MSMEs accounted for 97% of employment in 2021; moreover, they made up 61.97% of the country's GDP (Mariana 2022). MSMEs in the marine and fishery sectors have great potential for Indonesian business development. There are 60,855 small, medium, and large fish processing facilities in Indonesia (Directorate General of Competitiveness of Marine and Fishery Product Development of Marine dan Fishery Ministry of Indonesia 2019). Some of these are in Bogor Regency.

Bogor Regency is a second-level administrative region of West Java Province, Indonesia, and is very important as one of the buffer zones for the capital city. According to the Statistical Agency of West Java Province, 6,088,233 people lived in Bogor Regency in 2020, representing 12.19% of the entire population of West Java Province (Statistics of West Java Province 2021). Undoubtedly, there are significant opportunities and challenges for the economic growth of this population. One of the Bogor Regency's economic drivers is the expansion of micro, small, and medium-sized enterprises (Dewi 2020). Micro, small, and medium-sized businesses are essential for boosting the economy and creating jobs in many developing countries (Iqbal et al. 2021). Thus, the development of MSMEs in Bogor Regency could create job opportunities and enhance its economic growth.

The growth of micro, small, and medium-sized businesses, particularly seafood processing, is one of the factors driving the Bogor Regency economy (Dewi 2020). Micro and small firms in Bogor Regency face several challenges to their development, including low-quality human resources, inadequate capital and technology, and poor entrepreneurial spirit. Due to a number of factors, MSMEs typically have low levels of competitiveness, which can lead to business failure (Rainanto 2019). Fortunately, the existence of these businesses could be supported by enough resources. Bogor Regency produced over 115 thousand tons of 10 different varieties of consumable fish in 2020 (Statistics of Bogor Regency 2021). These fish have great potential to be turned into competitive, high-quality fishery products. According to the requirements of the Minister of Maritime Affairs and Fisheries Regulation Number 59 of 2021 concerning "The Increasing the Added Value of Fishery Products", the increase in added value is obtained by processing fresh fish into processed fishery products.

In contrast to other sub-districts, Cibinong District serves as the administrative hub of the Bogor Regency Government and is distinguished by the absence of a village government system throughout its whole administrative region. Cibinong District can be referred to as Cibinong City or can be considered an urban region. The majority of the people in this district have access to higher-quality infrastructure facilities, infrastructure of acceptable quality, and a strong network of banking literacy (Utami 2014). Business actors exist and grow in Cibinong District because of these benefits, particularly in the processing of fishery products. Of the 135 value-added fishery business players in the Bogor Regency, 30 were in Cibinong District. Additionally, it is interesting to note that all of them are run by women.

In addition to the benefits listed above, Cibinong District has excellent potential as a market for culinary goods made from processed fish, given its position as the administrative hub of Bogor Regency. Among the 39 districts in Bogor Regency, Cibinong District has the most commercial and service facility establishments (Machmud et al. 2021). Cibinong District also has the highest scalogram in the Bogor Regency's score for economic growth facilities, and is the hub of the economic boom in Bogor Regency. Cibinong District's labor structure has evolved, shifting from a predominance in the agricultural sector to the manufacturing and service industries (Utami 2014).

In a press release in 2021, the Ministry of Women's Empowerment and Child Protection of Indonesia mandated a message for women. They stated that in the COVID-19 pandemic era, the role of women in the family was directed to further increase their active participation in various development activities (Legal Bureau of the Ministry of Women's Empowerment and Child Protection of Indonesia 2021). This demonstrates that women can actively participate in socioeconomic activities, while at the same time playing a role as housewives or teachers to instill values in their children. One measure for empowering and improving the community's economy following the COVID-19 pandemic is to increase the role of women-owned fish processing MSMEs in Bogor Regency by utilizing various local potentials, referring to targets of the Sustainable Development Goals (SDGs) agenda, number five (Gender Equality) and number eight (Decent Work and Economic Growth).

Hence, despite encountering a variety of obstacles, MSMEs may continue to fulfill their primary responsibility of fostering economic growth, value creation, competitiveness, and employment. According to the definition above, a strategic plan needs to be developed for the sustainability of women-owned fish processing MSMEs. Strategic entrepreneurship is a planning and forecasting technique used to take full advantage of possibilities when competing and outperforming rivals.

Strategic entrepreneurship is one way to gain competitive advantage supported by creativity and innovation (Ireland et al. 2003). The ability of business actors to manage their resources with the help of leadership, culture, and an entrepreneurial attitude is an example of this type of innovation. These three things are the core of entrepreneurship. Strategic entrepreneurship research is still conceptual and not based on empirical findings (Ireland et al. 2003).

Based on this, researchers have the chance to conduct empirical research by identifying the traits of women who process fishery products, and by examining the relationships between variables in the strategic entrepreneurship model that are related to the success of MSME women who process fishery products in Bogor Regency. Women who process fishery products will be identified based on their age, level of education, business ownership status, business history, time of business establishment, sources of business capital, total assets, total turnover, and number of employees.

It is obvious that strategic planning must be devised to secure the long-term viability of MSMEs. An approach to making the most of the prospects in Cibinong District, in terms of addressing retail rivalry and boosting the sector's competitiveness, is through strategic entrepreneurship. This study investigates the characteristics of women-owned fish processing units in Bogor Regency, strategic entrepreneurial considerations, and the influence of input-process-output segmentation to maximize opportunities by fostering competition in MSME business processes.

The subject of this study is fish processing MSMEs in Cibinong District owned by women. The purpose of this study is to comprehend the relationship between the performance of women-owned fish processing MSMEs under the conditions of COVID-19 and the components of strategic entrepreneurship. The findings of this study will be useful for the development of governmental intervention strategies that suit the needs of businesswomen involved in the processing of fish. This study also applies structural equation modeling using partial least squares (PLS-SEM) to a new field.

#### **2. Materials and Methods**

This study used a survey method using a questionnaire, with women-owned fish processing units serving as the direct respondents, to provide a thorough account of the circumstances surrounding a case. Data collection, surveys, and the direct distribution of questionnaires to respondents were all part of the search methodology, which focused on women-owned fish processing facilities in Cibinong District, Bogor Regency.

According to the Statistics of West Java Province in 2020, the population of Bogor Regency was 6,088,233, or 12.19% of the total population of the province (Statistics of West Java Province 2021). Bogor Regency consists of 40 districts (Saraswati 2014), and is the most populated resident regency in Indonesia (Directorate General of Population Affairs and Civil Registration of the Ministry of Home Affairs of Indonesia 2021; Kusnandar 2021). Cibinong District is one of the most densely populated districts in Bogor Regency.

In contrast to other sub-districts, Cibinong District, which serves as the administrative hub of the Bogor Regency Government, is distinctive in that the entirety of its administrative region lacks a village government structure. The bulk of the population in this district benefits from better access to education, high-quality infrastructure, and a strong network of banking literacy (Aprilia et al. 2021; Utami 2014). Figure 1 provides a map of the area studied in Cibinong District, Bogor Regency.

**Figure 1.** Cibinong District Map of Bogor Regency.

#### *2.1. Census Data Collection Method*

For this analysis, we combined primary and secondary data. Primary data were collected directly via a questionnaire to determine how effectively management understood strategic entrepreneurship. This study was carried out between August 2022 and October 2022 in Cibinong District, Bogor Regency with a census of 30 respondents of commercial businesswomen fish processing units. Secondary data on strategic entrepreneurship were gathered from a variety of relevant literary works, including journals, books, earlier study findings, and statistical data reports (Hair et al. 2017).

The goal of the questionnaire was to assess the six aspects of strategic entrepreneurship (environmental factors, organizational resources, individual resources, resource orchestration, creating value and advantage, and creating performance). The environmental factors were measured using items developed by Revilla et al. (2011) and Tang (2008), while the organizational resource items proposed by Hitt et al. (2011) were used. Resource orchestration was measured by adapting items from Carnes et al. (2017), creating value and advantage by adapting items from Porter (2007)**,** and creating performance by adapting the items from Shepherd and Wiklund (2009). All items were evaluated using a Likert scale of one to five, with five expressing strong agreement. The Likert scale is used to convey how strongly respondents agree or disagree with specific statements about actions, things, people, or events. The suggested scale typically consists of five points. A Likert scale was chosen with five class scores as the measurement. There are a total of five groups, made up of the average value of each informant. The following formula can be utilized to determine class intervals:

$$\text{SR} = (\mathbf{a} - \mathbf{b})/\mathbf{c}$$

Explanation:k

SR = Range.

a = Maximum scores.

b = Minimum scores. c = Number of class intervals.

> SR = (5 − 1)/5 = 0.8

These calculations enable us to establish that the calculated scale range is 0.8. According to the statement on the research questionnaire, the average range of 1.00–1.80 falls into the Poor category, >1.80–2.60 falls into the Fair category, >2.60–3.40 falls into the Good category, >3.40–4.20 falls into the Very Good category, and >4.20–5.00 falls into the Excellent category. The items used to measure each variable are listed in Table A1 in Appendix A.

The selection of micro and small-scale criteria refers to article 35 of Government Regulation number 7 of 2021 (Government of Indonesia 2021). This law states that micro standards have an annual revenue of fewer than 2 billion rupiahs and business capital of no more than 1 billion rupiahs, excluding land and structures. In addition, small-scale businesses are considered to be businesses that do not include land and buildings, with yearly sales of between 2 billion and 15 billion rupiahs and business capital of between 1 billion and 5 billion rupiahs.

## *2.2. Data Analysis*

The data processing and analysis for this study employed partial least square structural equation modeling, validity testing, reliability tests, descriptive analyses, and Simulation of Partial Least Square Structural Equitation (PLS-SEM). In this study, Smart PLS 3.0 was used. Descriptive analysis was performed to obtain a wide description of the characteristics of respondents, including gender, age, education, and MSME profile, as well as to describe strategic entrepreneurship implementation using the mean. For the measurement, a 5 point Likert scale was used to determine the scale range. A Likert scale is used to assess responders' attitudes, views, and perceptions of social issues (Sugiyono 2017).

The measurement model (outer model) and the structural model (inner model) are the two sub-models that make up PLS-SEM analysis (Hair et al. 2014). The constructs' convergent validity, discriminant validity, and reliability are assessed using the outer model (Hair et al. 2017). In addition, the inner model is used to assess the relevance of the path coefficients and the R-square value. Two categories of variable are used in PLS-SEM. The first is an observed variable, sometimes known as a manifest variable because it can be seen immediately. The second category is unobserved variables, sometimes known as latent variables since they cannot be observed directly (Hair et al. 2014). Together with the seven latent variables, there are 36 manifest variables (environmental influences, organizational resources, individual resources, resource orchestration, competitive advantage and value creation, and performance creation).

This research mainly employed the strategic entrepreneurship model based on Hitt et al. (2011) combined with Kiyabo and Isaga (2019) model. This study adopted Hitt et al. (2011) input-process-output model, extending the understanding of the strategic entrepreneurship construct. This used environmental factors, organizational resources, and individual resources as inputs, along with resource orchestration as the process, and creating value for customer advantages as the outputs. Another output was added: SME performance, from Kiyabo and Isaga (2019) model. Hence, from these models, this study generates the

input, process, and output of the strategic entrepreneurship model with inputs such as environmental factors (X1), organizational resources (X2), and personal resources (X3). The process segment has a variable latent resource orchestration (X4). Thus, the output section contains two variables: producing value and competitive advantage (X5), and creating performance (Y). Figure 2 displays the research model.

**Figure 2.** The Research Model.

The research hypotheses, as shown by the research model in Figure 2, are as follows:

**H1:** *Environmental factors (FL) have a positive effect on resource orchestration (OS).*

**H2:** *Organizational resources (SOs) have a positive effect on resource orchestration (OS).*

**H3:** *Individual resources (SI) have a positive effect on resource orchestration (OS).*

**H4:** *Resource orchestration (OS) has a positive effect on creating value and competitive advantage (NS).*

**H5:** *Creating value and competitive advantage (NS) has a positive effect on performance creation (KM).*

The outer model evaluation and the inner model evaluation are the two evaluation models utilized in PLS-SEM data analysis (Cheung 2013). Outer models are used to examine the effects of latent variable indicators. Multicollinearity was employed in this work to clarify the data without any discernible bias prior to analysis. The absence of a multicollinearity issue is a prerequisite for properly examining the outer model. A situation with substantial correlation or connectedness between indicators is called multicollinearity. A variance inflating factor (VIF) value of more than five indicates a multicollinearity correlation value, which is defined by a correlation value of more than nine. Multicollinearity is present if the latent variable VIF value is more than five. The actions that can be taken include lowering or eliminating indications with a high degree of association (Hair et al. 2017).

The evaluation of the outer model consists of three tests. A convergent validity test can be used to assess how well manifest variables can explain hidden variables by looking at loading factors above 0.50. When the average variance extracted (AVE) result is more than 0.50, the discriminant validity test is used to assess how many latent variables and manifest variables differ from one another. A previous study explained the connection between Cronbach's alpha above 0.60 and composite reliability used to test composite reliability (Hair et al. 2017). The inner model is utilized to determine the effect of the independent variable on the dependent variable by comparing the coefficient of determination (R square) and the path coefficient (Ghozali 2015).

#### **3. Results and Discussion**

#### *3.1. Common Method Bias*

A problem known as common method bias (CMB) occurs when the measuring technique utilized in an SEM study causes issues, rather than the network of causes and effects among latent variables in the model under investigation (Kock 2015). In this study, Smart PLS was used to identify CMB threats. The test signified that the VIF elements were lower than the 3.3 threshold. This indicates that the model is free from CMB (Hair et al. 2017; Kock 2015).
