Introduction

The effectiveness of Special Economic Zones (SEZs) in promoting economic development is a topic of considerable debate and importance. SEZs provide fiscal and non-fiscal incentives to attract investments, with the expectation of generating multiplier effects on the local economy. However, the net benefits of SEZs remain uncertain, particularly in terms of balancing public and private interests. To the best of our knowledge, SEZ proponents lack empirical evidence to support their conviction that net benefits outweigh incentives. Therefore, this study aims to address this gap by investigating both the direct and indirect impacts on the surrounding community and regional economic development of the SEZ in a particular location.

SEZs have gained prominence in developing countries because of their potential to spur economic growth and attract foreign direct investment (FDI) (Aggarwal, 2019; Narula and Zhan, 2019; Zeng, 2022). Indonesia currently hosts 19 SEZs developed through a market-driven approach. This study focuses on the Kendal SEZ, which adopts a unique approach compared to other SEZs in Indonesia. There are three reasons why we chose the Kendal District. First, we considered Kendal as the most successful SEZ among the Indonesian SEZs in terms of the number of companies operating in the designated area. Second, Kendal is on Java Island, specifically in the central part, which is the most populous region of Indonesia. Third, Kendal has a controlling factor, Pati Regency, that is similar to Kendal without SEZ designation. These three factors are important determinants of SEZ’s impact on its surrounding areas.

The question of whether a SEZ brings net economic benefits to the host economy, specifically to surrounding areas, remains unchanged. This is true in the case of balancing interests between public agencies and private entities. In the SEZ areas, companies receive special fiscal and nonfiscal measures. Common incentives that attract investors include tax holidays and custom exemptions. To compensate for taxpayer-funded monetary support, public agencies demand multiplier effects from private enterprises’ investments in the SEZ. On the other hand, companies have forgone economic benefits by giving up investments in other destinations and hope that their opportunity losses will be compensated by fiscal incentives given by the government.

Despite the odds, SEZs have emerged as a prominent economic development strategy in many developing countries, attracting significant attention due to their potential to spur economic growth and attract FDI (Aggarwal, 2019; Narula and Zhan, 2019; Zeng, 2022). These designated areas, characterized by favorable business regulations and infrastructure, create an environment conducive to attracting domestic and international investors (Farole, 2011). As developing countries have more appetite for FDI as a source of economic growth, their dependency on SEZs is higher than in the developed world (Farole, 2011). In this case, Indonesia is no exception. To date, 19 designated SEZs have been designated around the archipelago; however, the net benefits to society are being questioned.

Previous studies using several SEZ locations in Indonesia revealed a similar barrier in terms of SEZ governance that is still dominated by the nuance of the top-down approach (Hidayat and Negara, 2020; Taufiqurrahman and Khoirunurrofik, 2023). However, we interviewed the National Council for Special Economic Zone and confirmed that there was a shift in approaching other locations, such as the Kendal SEZ, which was claimed to apply a different approach than top-down (the so-called “market-driven approach”). SEZs have become pivotal instruments for fostering regional development and industrial growth worldwide, yet comprehensive evaluations of their socioeconomic and spatial impacts remain crucial for understanding their true potential. This is a crucial study in the ongoing policy debate on the benefits of having SEZs in many areas of Indonesia. This study specifically examines an SEZ in Kendal Regency, Central Java.

This study explores the observable impacts of the Kendal SEZ in terms of economic changes, structural transformations in household expenditures, and labor force absorption. The study also identifies emerging challenges faced by SEZs and provides input for future directions of SEZ development, aiming to maximize the effects on regional economies. The method employs a comprehensive mixed-methods approach, combining qualitative thematic analysis and robust quantitative methods. Additionally, quantitative analysis considered the COVID-19 pandemic to enrich the findings and discussion.

This paper is organized as follows: we first review the theoretical basis of the development of SEZ and discuss the criticism of SEZ theory. We then conduct explanatory research using qualitative data by conducting thematic analysis, coding, and triangulation on the results of focus group discussions and in-depth interviews (IDIs) with the businesses in Kendal SEZ. To reconfirm the findings from the qualitative study, we conduct a detailed analysis of SEZs’ impact on the regional economy using descriptive statistics, the location quotient (LQ) method, Propensity Score Matching-Difference in Difference (PSM-DiD), and spatial analysis. The last section presents the main conclusion and policy considerations. By addressing the novelty of current knowledge and considering the specific challenges faced by developing nations, this research aims to contribute to the existing literature and inform policymakers and stakeholders about the potential benefits and limitations of SEZs in fostering economic growth.

Theoretical framework

The development of SEZs is rooted in the agglomeration theory proposed by Alfred Marshall (1920) agglomeration theory, which suggests that industries cluster together to reduce transportation costs and enhance efficiency. Krugman (1991) expanded on this by highlighting the benefits of spatial concentration, including increased real wages and regional growth. SEZs are geographically defined areas with distinct regulatory environments that attract investment (Frick and Rodríguez-Pose, 2019). The success of SEZs depends on policy design, implementation strategies, and integration with a broader economy (Aggarwal, 2019). However, SEZs can also create challenges such as uneven development and environmental concerns (Li et al., 2021).

The development of SEZs departs from the agglomeration concept developed by Alfred Marshall in 1920. Marshall stated that companies tend to build industries close to each other because economic agglomeration reduces transportation costs, which include the movement of goods, people, and ideas (World Bank, 2017). Developing agglomerations among raw materials suppliers and product development companies will enhance technical efficiency by reducing the costs of procuring raw or semi-finished materials (The Nguyen, 2023). Developing SEZs using the agglomeration principle will attract many companies because of the efficiency and interdependence between companies.

According to Krugman (1991), companies that gather in one core zone/region incur lower transportation costs to form the goods and manufacturing market. This condition increases workers’ real wages. It encourages the migration of workers from peripheral areas to the core area, which in turn enlarges the core area market and leads to the agglomeration of all industrial activities in one area. Furthermore, it will create positive company growth, urban development, and regional growth. Even with the second-stage economic impact, Hartwell (2018) noted that zone development through SEZ will provide benefits such as reduced unemployment, increased regional growth, and higher exports.

SEZs have emerged as a significant policy tool for economic development, particularly in developing and transition economies. As highlighted by Frick and Rodríguez-Pose (2019), SEZs are geographically delimited areas within a country where business and trade laws differ from the rest of the territory. These zones are designed to attract foreign investment, boost exports, create employment, and stimulate economic growth through various incentives, including tax breaks, streamlined regulations, and improved infrastructure.

Frick and Rodríguez-Pose (2019) established a basic conceptual understanding of SEZs as geographically defined areas with distinct regulatory environments. This foundational concept underscores the importance of spatial economics in SEZ theory. The authors emphasize that SEZs are not only economic tools but also spatial policy instruments that have implications for regional development patterns. Aggarwal (2019) expanded on this foundation by highlighting the complexity of factors influencing SEZ success. This multifaceted approach suggests that SEZ performance cannot be attributed to a single factor but rather to the interplay of policy design, implementation strategies, and integration with the broader economy. This perspective adds depth to the theoretical framework by emphasizing the importance of holistic policy approaches.

The spatial dimension of SEZs is a critical aspect of their theoretical framework. Frick and Rodríguez-Pose (2022) analyzed how the geographic location of SEZs influences their performance, highlighting the importance of connectivity, agglomeration economies, and regional economic conditions. This spatial perspective is crucial for understanding why some SEZs succeed while others fail and how they contribute to regional development patterns.

The effectiveness of SEZs in promoting economic development has been the subject of extensive research. Aggarwal (2019) emphasized that the success of SEZs depends on various factors, including policy design, implementation strategies, and integration with the broader economy. Rodríguez‐Pose et al. (2022) further elaborated on this, suggesting that the impact of SEZs is contingent on the local context, institutional quality, and capacity to generate links with the domestic economy.

Frick and Rodríguez-Pose (2023) explored the evolution of SEZ policies, noting a shift from traditional export-oriented zones to more diverse and specialized zones. This evolution reflects changing global economic patterns and the need for SEZs to adapt to new challenges and opportunities. Ma et al. (2023) contribute to this discussion by examining the role of SEZs in fostering innovation and technological upgrading, particularly in the context of emerging economies. Li et al. (2021) highlights the potential challenges and unintended consequences of SEZs. These may include uneven development, the creation of economic enclaves disconnected from the local economy, and concerns about labor rights and environmental sustainability. The theoretical framework of SEZs must, therefore, consider not only their potential benefits but also their limitations and the need for careful policy design to ensure that they contribute positively to inclusive and sustainable economic development.

The way SEZs function to optimize their diverse opportunities and benefits was elucidated by Chen et al. (2022). The zone development SEZs will also create a pool of skilled workers who are attracted by higher wages, opening opportunities for companies to develop more specialized industries and fostering a climate for creating links and matches between labor providers and companies. The gathering of companies in the zone will create a technological spillover (Chen et al., 2022). Concentrating firms in zones facilitates the spillover of industry-related knowledge or ideas among workers and promotes further specialization and industry-specific innovation, leading to firm growth (Henderson et al., 2012).

SEZs or industrial parks have the potential to serve as effective tools for promoting industrialization and structural transformation (Zeng, 2021), but their success depends on their proper implementation and other factors, such as the size of the zone and country context, that significantly determine the performance of SEZs (Frick and Rodríguez-Pose, 2019). In particular, investing in SEZs can: (1) provide a bundling of public services in a geographically concentrated area; (2) improve the efficiency of limited government funds/budgets for infrastructure; (3) facilitate cluster development or agglomeration of certain industries; and (4) enhance urban development by providing facilities conducive to improved living conditions for both basic wage workers and highly skilled technical workers, taking advantage of economies of scale in the provision of environmental services, such as water treatment plants and solid waste treatment plants (Zeng, 2016). Thus, SEZs can be conducive to both job creation and income generation, potentially protecting the environment and promoting green growth and eco-friendly cities (Lin and Wang, 2014).

In China, the development of SEZs has attracted almost 50 FDI (Zeng, 2015) and has also supported local economic development (Wang, 2013). Another study in Costa Rica showed that SEZs not only attract and increase FDI but also increase investment in fields related to high technology, particularly those related to microprocessors and health equipment (Monge-González et al., 2005). The study conducted by the Asian Development Bank (ADB) shows that SEZs also have an impact on increasing exports in several countries, such as driving an increase in exports of 17% in Bangladesh, 44% in China, 11% in South Korea, 67% in the Philippines, and 67% in Sri Lanka (ADB, 2015). The existence of SEZs will stimulate higher exports if a country adopts an outward-looking and export-oriented program (Zeng, 2016).

Aggarwal (2019) identified that in successful countries with SEZ implementation like China, the Republic of Korea, and Taiwan, evolutionary strategic approaches allowed the flexibility of doing many over time without reducing the government’s role. Instead, the government plays an extended development role in terms of providing strong bureaucratic competencies and political will to strengthen the competitiveness of the economy and its capacity. Therefore, Farole (2011) posited that the Global Competitiveness Index is a critical factor indicating the country context implementation of SEZs to determine the success of SEZ programs. Zeng (2021) lists some other factors influencing the success of SEZs in terms of a favorable macro environment, including a robust legal and regulatory framework, strong government dedication, and effective alignment of the zoning initiative with the overall development strategy at the national or regional level. A successful SEZ also means that the country is “open for business” as a result of being able to upgrade infrastructure, human capital, and institutional framework across the entire economy (Narula and Zhan, 2019).

Learning the experiences of the least successful countries in sub-Saharan Africa and South Asia, this study finds that SEZs did not bring about economic transformation; rather, they could be a tool to enhance political power through patronage to increase competitiveness in tradable sectors. This finding corresponds with other studies that country-level policymaking and legislation effectively influenced the nature of zone management by public, private, or public-private-partnership (PPP) operators (Farole, 2011; Frick and Rodríguez-Pose, 2023).

Kendal SEZ: overview

Indonesia has used SEZs to promote balanced development for disadvantaged regions and stimulate economic dynamics within those areas. SEZs are expected to enhance the competitiveness of outer islands as investment destinations (National Council for SEZ Indonesia, 2022). As of 2022, Indonesia had 19 SEZs, including Kendal. The designation of the Kendal business area as a Kendal SEZ was recorded in 2019; meanwhile, the operational start was in 2021. Covering an area of 1000 hectares, Kendal SEZ is projected to employ 20,000 individuals by 2025, with a business investment of $5 billion USD and a development investment of 758 million USD, totaling 737.4 million USD (as of August—September 2022). The Kendal SEZ is expected to bolster the economic growth of Central Java Province, aiming to increase the region’s contribution to Gross Domestic Product from 8.7% to 11–12% (National Council for SEZ Indonesia, 2022).

The Kendal SEZ is an optimal SEZ category, outpacing others in terms of investment realization. In 2022, there were 77 registered business entities within the Kendal SEZ, comprising 24 operational businesses, 13 under construction, and 40 under the permitting process. Investment in the Kendal SEZ area reached 53% of the targeted amount within its 3-year implementation period (National Council for SEZ Indonesia, 2021). The total investment in the Kendal SEZ over the 3 years increased from 490 million USD to 1.9 billion USD, with employment opportunities growing from 2875 individuals to 18,320 individuals. Additionally, the estimated export realization for 2022 is ~50 million USD (National Council for SEZ Indonesia, 2021).

The research question of this study is whether the Kendal SEZ impacts regional economic growth, both directly and indirectly. What is the magnitude of the impact, and how do all processes within the SEZ Kendal area and its surroundings contribute to regional economic growth? Indirectly, it also aims to determine the position of the area regarding regional economic growth, whether increasing, constant, or decreasing, as depicted in the research framework illustrated in Fig. 1.

Fig. 1: Framework for evaluating the impacts of the Kendal SEZ on the surrounding economy.
figure 1

Source. Authors’ conceptualization and visualization.

Methods

Study area

We conducted this study from September to December 2022 within the Kendal SEZ, located in Kendal Regency, Central Java, Indonesia. Kendal SEZ boasts a geo-economic advantage rooted in the geographical location of Kendal Regency, situated near Semarang City, the capital of Central Java Province, with the Ahmad Yani International Airport and the Tanjung Emas International Port, intersected by a toll road segment of the Trans Java Toll Road, as well as traversed by the Double Track Railway connecting the capital city of Indonesia in Jakarta to Central Java and East Java provinces. The strategic geographical advantage of the Kendal SEZ includes export-oriented industries, import substitution, high-tech products, special applications supporting industry development, and industry-based industries.

This study employed a novel approach to address the knowledge gap resulting from partial analysis between qualitative and quantitative methods. The novelty of this study is demonstrated by the mixed-methods approach, which establishes interconnections that mutually support or confirm the results of qualitative statistical analysis with the findings of quantitative analysis.

Qualitative method

Research design

Focus group discussions (FGDs)

This study was conducted under the auspices of the Secretariat General of the Indonesia National Council for SEZ to evaluate the economic impact of the Kendal SEZ, which was chosen as a case study due to its pivotal role in the industrial and economic landscape of Central Java. The primary stakeholders and entities involved in the Kendal SEZ include: (i) the Central Java SEZ Zone Council, responsible for implementing the general policies set by the SEZ National Council to manage and develop the SEZ in the Central Java region; (ii) the Administrator of the Kendal SEZ (government), which oversees business licensing, permits, services, and supervision within the Kendal SEZ; (iii) the Kendal Industrial Park (KIP) (private), serving as the Business Entity for the Development and Management of the Kendal SEZ; and (iv) tenants/companies operating within the Kendal SEZ.

For qualitative data collection, we conducted Focus Group Discussions (FGDs) and IDIs. Four FGDs were held. The first FGD, which involved the KIP and the Kendal SEZ Administrator, gathered information on the Kendal SEZ profile and related permits. The second FGD included additional key stakeholders beyond the KIP and the Kendal SEZ Administrator, namely, the Central Java SEZ Zone Council and other government agencies at the Kendal Regency level, such as the Statistics Office, the regional branch of the Central Bank of Indonesia, the Kendal Planning, Research, and Development Agency, and the Kendal Treasury Office. This FGD understood the SEZ’s development and the government’s support for its operations and growth. The third FGD employs purposive sampling, limiting the sample for FGDs and IDIs to the categories of tenants/ companies in operation and construction, which is in line with the research objectives. The sample criteria were determined through a preliminary FGD with the Secretariat General of the Indonesia National Council for SEZ and the KIP. The fourth FGD was conducted as a triangulation effort to validate findings from the perspective of the 15 tenants/ companies. These findings were cross-checked with representatives of the Kendal SEZ Administrator and the Central Java SEZ Zone Council. This triangulation process ensured a comprehensive analysis by integrating multiple viewpoints and verifying data consistency across key stakeholders, thereby strengthening the reliability and depth of the qualitative insights.

In-depth Interviews (IDIs)

After the third FGD, IDIs research was conducted with fifteen tenants, nine tenants in operation and six in construction, as the sampling frame was representative of the tenants’ population in the Kendal SEZ. The 15 tenants serving as informants for IDIs represent various sectors, including chemicals, food, cable/steel/electronics/industrial component manufacturing, packaging/warehousing, textiles, and toys and furniture. In addition, triangulation was conducted during the IDI process to ensure qualitative analysis’s rigor and credibility. This involved cross-verifying statements regarding the indirect impacts of the operationalization of the Kendal Special Economic Zone by comparing perspectives shared by informants from one industrial sector with those from other sectors. This approach enabled the identification of consistent themes across sectors, thereby enhancing the validity of the findings.

The FGDs and IDIs lasted for 1–2 hours each, and all the FGDs and IDIs were audio-recorded using a voice recorder, transcribed verbatim in Bahasa Indonesia, and analyzed using template analysis following (King, 2012). The number of informants and topics covered in each FGD is detailed in Table A.1 in the Appendix.

Qualitative data analysis

The template analysis is a structured variant of thematic analysis, offering a balanced approach that combines rigorous organization with the flexibility to tailor the analysis to the specific requirements of a given study. While it is predominantly employed to analyze data derived from individual interviews, its applicability extends to various other qualitative data forms (King, 2012). According to King (2012), the steps in conducting template analysis are as follows: (i) conduct preliminary coding, incorporating a priori themes where applicable; (ii) construct an initial template by organizing preliminary codes into coherent groups and establishing both hierarchical and lateral relationships among themes; (iii) systematically apply the initial template to the entire set of transcripts, iteratively refining it to ensure all significant data are captured, thereby developing the final template.

First, we defined a priori themes based on the FIAS (2008) guidelines for zone development, national targets of the Kendal SEZ, and an initial reading of the transcripts (details can be found in Table A.2 in the Appendix). Second, we developed an initial template by organizing a priori themes into coherent groups. Third, we developed the final template iteratively to capture all important data gathered from FGDs and IDI.

After data collection, we performed coding for template analysis using QSR NVivo 14, a qualitative research software (Richards, 1999). NVivo facilitates template analysis through data organization, allowing researchers to import and organize FGD/IDI transcripts, coding iteratively using first a priori theme, initial template, and finally produce the final template, and visualization. After the coding process was completed, project maps were created using NVivo to visualize the results.

Data triangulation

This involves collecting data from different sources to ensure comprehensive coverage of the research topic. In this research, data were gathered from various business actors/tenants within the Kendal SEZ, including those in different stages of operation (e.g., “in construction” and “in operation”) and in different business sectors (e.g., chemicals, food, cable/steel/electronics/industrial components manufacturing, packaging/warehousing, textiles, and toys and furniture). This approach helps cross-verify information and provides a more robust understanding of economic impacts.

In addition, different methods were used to collect data: interviews with business actors and FGDs with different stakeholders, including government agencies. By combining these methods, the research mitigates the biases and limitations inherent in any single method, leading to more reliable and valid results.

Quantitative method

Quantitative data

The findings from qualitative studies were confirmed or further tested by conducting quantitative statistical analysis of both Propensity Score Matching (PSM)—Difference in Differences (DiD) and spatial quantitative analysis, which in addition provided visual changes before and after the development of the Kendal SEZ. We examine them at aggregate, sectoral, and household levels using production and consumption measurements. Data at the aggregate level relates to production measures, whereas data at the household level relates to consumption measures. Each quantitative data analysis utilized secondary data from the same source, namely Statistics Indonesia, at the national and district levels (National Socioeconomic Survey SUSENAS (2018); National Socioeconomic Survey SUSENAS (2021); Statistics Indonesia of Kendal Regency, 2024).

These data levels were reflected in the quantitative statistical analyses of LQ, PSM, DiD, and spatial quantitative analysis to reflect visual changes before and after the development of the Kendal SEZ. Herrendorf et al. (2014) divided structural transformation into production and consumption measures. Employment and value-added share are the two most common measures of structural transformation from the production side, while final household consumption expenditure share relates to the consumption side. Many previous studies have assessed structural transformation using production rather than consumption measures. Conversely, some studies primarily consider consumption rather than production measures when examining poverty or inequality.

Quantitative data analysis

Quantitative analysis included LQ calculations to assess structural economic changes, PSM-DiD to evaluate household expenditures, and spatial analysis using Night-Time Light (NTL) data to measure economic activity.

Location quotient

The LQ is a calculation method used to determine a region’s structural transformation. This measure is measured by comparing the role of a specific economic sector in a region to that of the same economic sector in a larger administratively defined area (Tarigan, 2004).

$${\rm{LQ}}=({{\rm{X}}}_{{\rm{ir}}}/{{\rm{X}}}_{{\rm{r}}})/\left({{\rm{X}}}_{{\rm{in}}}/{{\rm{X}}}_{{\rm{n}}}\right)$$

where Xir = sector i at the regional level Xr = the total of all sectors at the regional level. Xin = sector i at the larger administrative level. Xn = total of all sectors at a larger administrative level. LQ > 1 indicates that a product in that sector has an advantage in a given region. LQ < 1 indicates that the product lacks an advantage; LQ = 1 indicates balanced productivity within a sector.

Using secondary data on Gross Regional Domestic Product (GRDP) by Industrial Origin in 2018 and 2021 from both the district and province levels. The GRDP data has been classified by Indonesia Statistics into 17 industrial sectors: agriculture, forestry, and fishing; mining and quarrying; manufacturing; electricity and gas; water supply, sewerage, waste management, and remediation activities; construction; wholesale and retail trade; repair of motor vehicles and motorcycles; transportation and storage; accommodation and food service activities; information and communication; financial and insurance activities; real estate activities; business activities; public administration and defense; compulsory social security; education; human health and social work activities; and other service activities. The analysis using LQ will show the structural economic change from Kendal Regency as a research location as well as a treatment district for econometrics exercise using PSM-DiD.

Propensity Score Matching (PSM): Difference in Differences (DiD)

Technically, this method requires determining the 1st year of treatment that was implemented. Next, we need to generate a time binary variable to determine the pre- and post-treatment periods. The interaction variables of time and treatment were determined at the beginning of the analysis. Afterward, to ensure the model works, parallel trend plotting is required; otherwise, it is not valid. The PSM-DiD analysis can be initiated by running the PSM methods. The PSM methods are Caliper, Kernel, and Mahalinobis matching. These methodologies are implemented to generate balanced samples for causal inference studies. Furthermore, a balanced test was performed to ensure that the treatment and control samples were balanced. The PSM methods run on covariates, so they are included in the model. The final stage of the analysis is to run DiD analysis on previously processed matched data.

The econometric formula for DiD as follows:

$$Y=\alpha +\delta t+\beta D+\gamma D* t+\varepsilon$$

Here, Y is the dependent variable, α is a constant, t is a time series (dummy variable), and D is a dummy variable explaining the treatment and control groups. D*t is the interaction variable between the program dummy and the research time series. This study employed PSM-DiD, where the use of matching determines which samples have relatively similar indicators, thus allowing the assessment of the program’s impact through the PSM-DiD calculation scheme.

Regression analysis using the PSM-DiD econometric model used data from the National Socioeconomic Survey (SUSENAS) from 2018 to 2020 (National Socioeconomic Survey SUSENAS (2018); National Socioeconomic Survey SUSENAS (2021)). This study used March SUSENAS data for two districts. First, Kendal Regency was a treatment district with an economic program involving the establishment and development of the Kendal SEZ. Second, Pati Regency served as the comparison (control) district without SEZ intervention. Based on this dataset, 2018 was considered t0 when both districts had not yet implemented SEZ policy. Meanwhile, 2019 and 2020 represented t1 when Kendal Regency was designated as having an SEZ.

The selection of treatment and control districts was conducted by the research team using two approaches: macro-level trend data (Statistics Indonesia of Kendal Regency, 2024; Statistics Indonesia of Pati Regency, 2024) and micro-level data (National Socioeconomic Survey SUSENAS (2018); National Socioeconomic Survey SUSENAS (2021)). The macro-level approach involves analyzing trends in GRDP by industry, the average contribution of the top five sectors to GRDP, and ranking contributions from the top five sectors. Based on the results shown in Fig. 2, it is evident that the real GRDP trends of the Kendal and Pati Regencies have been aligned from 2011 to 2020. This condition served as the foundational justification for selecting these two regencies as treatment and control because it demonstrates that both regencies have relatively similar levels of development.

Fig. 2: The trend of Kendal and Pati Real Gross Domestic Product (GRDP) by industry to justify treatment and control in the calculation.
figure 2

Source: Authors’ adaptation from Statistics Indonesia of Kendal Regency, 2024; Statistics Indonesia of Pati Regency, 2024.

Table 1 lists the number of samples available in both the treatment and control regencies. A total of 16,603 individual samples were recorded during the three time periods, with the control group consisting of 8429 samples and the treatment group consisting of 8174 samples. Each dataset included 5462 samples in 2018, 5438 samples in 2019, and 5703 samples in 2020. In each data set, both the treatment and control regencies were represented. Based on plotting results using aggregate or macro-level data from BPS for the period 2011–2020, it is evident that both Kendal and Pati have relatively similar levels of economic development. The macro-level data from both regencies confirm that they can be compared, with Kendal Regency serving as the treatment group (with SEZ) and Pati Regency as the control group (without SEZ).

Table 1 The number of samples available in both treatment and control regencies indicates comparable economic development.

In line with the trend of GRDP movement shown in Fig. 2, the trend of household expenditures using SUSENAS data also exhibits similarities. Both regencies share a trend, as depicted in Fig. 3. This figure shows a parallel trend between treatment and control during the t0 and t1 periods regarding total household expenditures. These observations serve as the rationale for selecting Pati as the control group against Kendal as the treatment group. This provides evidence that the use of PSM-DiD meets the requirement that both regions are at the same point during t0. In this analysis using PSM-DiD, the model also controls household characteristics, including marital status, employment status, health insurance, household size, recipient of social welfare cards, analysis period, and gender. These control variables show the characteristics of households that may influence the household’s expenditure level.

Fig. 3: Parallel trend of Kendal and Pati Regency from the PSM-DiD analysis to justify treatment and control in the calculation.
figure 3

Source: Authors’ adaptation from National Socioeconomic Survey (SUSENAS) 2018, 2019, and 2020.

Spatial analysis

We conducted spatial analysis using a Geographic Information System, primarily focusing on spatial statistical calculations. We obtained the measurement variables from various secondary sources and combined them with composite nighttime light (NTL) satellite image data. NTL data capture aggregate light emissions and energy during nighttime in a specific period, providing insights into economic activity (Henderson et al., 2012; Keola et al., 2015; Mellander et al., 2015). We integrated the satellite images with secondary data, including surveys, censuses, administrative records, and field observations. These data sources provided predictor variables, such as NTL levels, and explanatory variables such as population growth and land-building tax values. The data usage details in this analysis are described in Table 2. The analysis of NTL composite images involved the following steps: preparation of nighttime VIIRS DNB (Visible Infrared Imaging Radiometer Suite Day/Night Band) images as the primary dataset, creation of a 1-km buffer around target areas to define the analysis regions, calculation of mean radiance and total light emissions for each buffered region, and application of a Geographic Weighted Regression (GWR) model to analyze spatial patterns and relationships. This process was conducted over 5 years to assess trends and spatial variations in NTL emissions.

Table 2 The organization of data and variables in the analysis.

To understand the spatial growth dynamics, we employed the Geographically Weighted Regression (GWR) model, which is a statistical technique designed to explore the relationships between spatial variables (Brunsdon et al., 1996). This model differs from traditional regression because it considers the spatial dimensions of each measured variable in the calculations (Getis and Ord, 1992). The spatial regression model can be expressed using the following formula.

$$\begin{array}{l}{{\rm{Y}}}_{{\rm{i}}}\left({\rm{NTL}}\right)={{\rm{\beta }}}_{0}\left({{\rm{X}}}_{{\rm{i}}},{{\rm{Y}}}_{{\rm{i}}}\right)+{{\rm{\beta }}}_{1}\left({{\rm{X}}}_{{\rm{i}}},{{\rm{Y}}}_{{\rm{i}}}\right){\rm{A}}+{{\rm{\beta }}}_{2}\left({{\rm{X}}}_{{\rm{i}}},{{\rm{Y}}}_{{\rm{i}}}\right){\rm{B}}\\\qquad\qquad\quad+\,{{\rm{\beta }}}_{3}\left({{\rm{X}}}_{{\rm{i}}},{{\rm{Y}}}_{{\rm{i}}}\right){\rm{C}}+{{\rm{\beta }}}_{4}\left({{\rm{X}}}_{{\rm{i}}},{{\rm{Y}}}_{{\rm{i}}}\right){\rm{D}}+{{\rm{\varepsilon }}}_{{\rm{i}}}\end{array}$$

Where, β0: intercept coefficient β1… β4: explanatory coefficients at each location A…D: explanatory variables, in this case, socioeconomic factors Xi, Yi: matrix of coordinates at each location. εi: residue or error value generated by the model.

Results

Qualitative analysis identifying the impacts

The conceptualization and visualization of the coding results, facilitated by NVivo, is depicted in Fig. 4. The qualities of a Kendal SEZ that mainly attract private companies to operate in a Kendal SEZ are the key strengths that differentiate and give an advantage to Kendal SEZs over other SEZs or industrial zones. These qualities include fiscal and non-financial incentives, relatively cheap labor wages, cheap sea freight due to its proximity to Tanjung Emas Port Semarang, safety, availability of raw materials, and similar regulations to China.

Fig. 4: The key strengths of the Kendal SEZ.
figure 4

Source: Authors’ conceptualization and visualization assisted by NVivo.

Our triangulation data demonstrates that the data is robust and reliable. First, it showed multiple informants and broad representation. The findings were supported by responses from several companies in the Kendal SEZ. For instance, six of the fifteen companies indicated plans to increase job creation, and three companies in the “in construction” phase detailed their investment plans. This diversity of sources strengthens the validity of the data. The inclusion of companies at different operational stages (“in construction” and “in operation”) and from various sectors within the SEZ also ensures a broad representation of perspectives. This diversity helps to capture a more complete picture of the economic impact, further validating the findings.

Second, the data presented consistency in responses from different informants, highlighting the reliability of the findings. For example, most companies (ten out of fifteen) expressed intention to expand their factories, and five companies planned to expand their export markets. Such patterns emerging from multiple informants provide a solid basis for the conclusions. Third, the information was cross-verified using different methods and informants. For example, qualitative interviews provided insights into the perceived economic impact, supported by concrete data on employment and investment figures, and were cross verified with FGD with the Kendal SEZ Administrator and the Central Java SEZ Zone Council. This ensures that the findings are not based on isolated opinions but are supported by a comprehensive data set. By showing that the arguments and information are supported by several informants and different stakeholders (government and business), the research demonstrates the rigorous application of triangulation, enhancing the credibility and reliability of the conclusions. This thorough approach ensures that the findings are well-founded and reflect the broader economic trends within the Kendal SEZ.

Impact on manufacturing industry growth

In line with the quantitative findings indicating an increase in manufacturing industries in the Kendal SEZ, business actors within the SEZ area are optimistic about their business development. We asked questions about the firm’s profit target, level of output/production, export and domestic sales, investment, employment, and perceived increase in social welfare and economic activities within the SEZ area and surrounding areas to understand the informant’s perception of the direct economic impact of the Kendal SEZ.

The respondents believed that they had an increasing level of employment and would employ more in the future, with an increasing level of investment, production, and export. Six out of 15 selected companies in Kendal SEZ have plans to increase job creation from 300 to 3800 people. Three out of 15 sample companies in the “in construction” status have plans to increase investments ranging from approximately Rp 462 billion to Rp 14 trillion, representing an increase of ~27% to 62% from the current investment value. Informants also plan to increase production by raising production targets, expanding or adding factories, and adding production lines. Both companies in the “in construction” and “in operation” stages have plans for business expansion. Ten of fifteen sample companies, or 67 percent, plan to expand their factories. Five out of fifteen companies plan to expand their export markets, and only one out of the fifteen companies plan to increase the domestic content of their products.

Other prominent responses were that informants perceived significant changes in the economic structure due to job switching from local villagers’ previous jobs to work in SEZs or informal sectors (MSMEs), which had flourished to supply the various needs of SEZs (food, housing, etc.). SEZ workers are also believed to have higher purchasing power.

Impact on job creation

Based on IDIs with industry stakeholders, we found that community members who were previously engaged in managing fishponds, particularly milkfish farms, have partially transitioned to work in Kendal SEZs (manufacturing) and other micro, small, and medium enterprises (MSMEs) or informal sectors since the establishment of the Kendal SEZ in the area. This sentiment was conveyed by the following informants:

“In the village close to the location of Kendal SEZ, people used to work in the sea and fishponds. Then, new entrepreneurs emerged, providing housing and rental accommodations for workers. Eateries sprang up in a nearby village. In the Brangsong subdistrict, where living conditions were low, now we had eateries, laundries, and lodgings.”

(Source: Informant PU 6, Warehouse service)

“The village head mentioned that the youth used to work in fishponds, and the unemployed were employed as laborers in SEZ.”

(Source: Informant PU 8, Textile manufacturer)

These statements corresponded to most the respondents’ argument that local workers from Kendal and surrounding districts had been employed. The experience from China reveals that SEZs increase employment because of the job creation of new firms and the expansion of incumbent firms (similar to KIP) (Zheng, 2021). However, informants raised issues of labor shortage from surrounding areas both for operational-level workers and for middle-level management human resources, and issues of work discipline, work ethics, and resilience, which we analyzed as weaknesses of Kendal SEZ, as shown in the coding results in Fig. 5. As evidence, out of 50 percent of new machines, only 20 percent could be operated due to a lack of worker skills (Informant PU 2).

Fig. 5: The challenges faced by the Kendal SEZ: labor shortages.
figure 5

Source: Authors’ conceptualization and visualization assisted by NVivo.

The local government has implemented a link-and-match program between the skills taught based on the educational curriculum in vocational schools and local work training agencies and skills demanded by the industries by adopting new machines at schools and job training centers. However, it has not yet been able to meet the needs of the industries (Informant PU 1, PU 10, PU 12). The inability of all relevant stakeholders in the Kendal District to overcome these weaknesses could hamper the development of the Kendal SEZ. A recent study in three locations of SEZ Indonesia found that creating broad opportunities for quality education and vocational training alongside corporate engagement can ensure that the skills acquired meet the needs of businesses (Hornok and Raeskyesa, 2024). These findings were triangulated by the fourth FGD with the Kendal SEZ Administrator and the Central Java SEZ Zone Council. The administrator and local government were aware of these issues and collaborated with the Department of Manpower and the Junior High School Education Office to align the curriculum with the skills needed by businesses in the SEZ/industry.

Impact on residential housing growth

As shown in Fig. 6, besides the growth of micro, small, and medium enterprises (MSMEs), there is a multiplier effect from the Kendal SEZ that has driven the emergence of ~22 real estate developments in its vicinity (Kendal Industrial Park, 2022). This information from Kendal Industrial Park as the Business Entity for the Development and Management of the Kendal SEZ is further reinforced by evidence from four informants confirming the emergence of housing projects around the SEZ. Informants who argued to perceive increasing purchasing power of its employees have also indicated that there are several demands from employees for employment verification letters as one of the requirements for applying for housing loans. Some companies have even partnered with banks to make auto-debit arrangements from employee accounts to facilitate housing loan repayments.

“Many employees are requesting employment verification letters for housing loans in the Kendal area. Companies have partnered with BNI Griya (state-owned enterprise bank), enabling employees to make auto-debit payments for housing loans.”

Fig. 6: Categories of Micro, Small, Medium Enterprises (MSMEs) and informal sectors thriving due to the indirect impacts of the Kendal SEZ.
figure 6

Source: Authors’ conceptualization and visualization assisted by NVivo.

(Source: Informant PU 12, textile/garment manufacturer, in operation)

“Very Basic Houses/subsidized houses (Rumah Sangat Sederhana or RSS) with a land area of 36 m2 have gained significant interest. Many employees request employment verification letters to obtain RSS in the vicinity.”

(Source: Informant PU 13, textile manufacturer, in operation)

Impact on the growth of informal jobs (Micro, Small, and Medium Enterprises/MSMEs)

Apart from the growth in the manufacturing industry, the Kendal SEZ has also had an impact on the growth of MSMEs, such as food stalls or small eateries, rental houses and rental or boarding rooms, catering, and laundry, as shown in the coding results in Fig. 6. Several respondents specifically described the types of businesses they believe have experienced growth. Other respondents stated that the increasing workforce has influenced economic growth by driving demand for clothing, food, and shelter. In addition, companies within the SEZ area have contributed to the growth of MSMEs through partnerships for the procurement of goods and services. Partnerships or outsourcing to MSMEs are a condition for claiming tax holidays/allowances from the Investment Coordinating Board.

The following statements provide further evidence of the growth of informal jobs due to the development of the Kendal SEZ:

“Small eateries or food stalls have experienced an increase in quantity, and lodgings have seen both demand and prices rise. Street vendors have also increased in number, and there has been a 200–300 percent increase in MSMEs and laundry businesses. Housing development is also occurring around the SEZ, with prices on the rise.”

(Source: Informant PU 7, chemical biopesticide manufacturer, in operation)

There’s a partnership with an MSME for “emping melinjo” (chips-English). An MoU will be signed on January 6, 2023, and the price will match the market price. However, the company will purchase the same quantity of raw materials, not more if the price goes down, and will not reduce the purchase of raw materials if the price goes up.”

(Source: Informant PU 9, frozen food manufacturer, in construction)

“Supporting the local community by purchasing office supplies, outsourcing cleaning services, security guards, and employee transportation.”

(Source: Informant PU 12, textile manufacturer, in operation)

Challenges faced by companies operating in the Kendal SEZ

Although the companies are optimistic about operational profitability within the Kendal SEZ, results of the coding process showed that companies still encounter infrastructure and other technical and procedural challenges, as shown in Fig. 7. Twenty percent of the respondents raised concerns about the need to implement the Kendal Port and a power plant to expedite processes and reduce transportation costs. In addition, several informants expressed concerns about land subsidence, which leads to additional expenses for land reclamation.

Fig. 7: Challenges encountered by companies operating in the Kendal SEZ.
figure 7

Source: Authors’ conceptualization and visualization assisted by NVivo.

Other challenges include difficulties in obtaining an investment license and claiming tax restitution/tax holiday/tax allowance, difficulties in utilizing SEZ customs documents under the national single-window system, the necessity for additional customs gates at the exit point, SEZ operators that should be more active and fast response, needs for adequate roads, public transportation, and other public facilities inside SEZs, and needs for more information dissemination. Kendal Port and fiscal and non-fiscal incentives initially attracted investors and businesses to operate in the Kendal SEZ. If SEZ management and local authorities do not cooperate to overcome these obstacles, they could threaten the future of Kendal SEZ’s development.

The triangulation process conducted during the fourth FGD, involving the Kendal SEZ Administrator and the Central Java SEZ Zone Council, reinforced the validity of qualitative data by corroborating the key challenges highlighted by tenants during the IDIs, particularly regarding the realization of Kendal Port. The government, through the Kendal Administrator, acknowledged several technical issues that hindered the progress of Kendal Port’s development. Efforts to expedite its completion have been actively pursued through coordinated initiatives with a state-owned enterprise (SOE) that is responsible for managing public ports in Central Java. This triangulated approach strengthens the reliability of the findings by incorporating diverse stakeholder perspectives.

Quantitative analysis identifying the impacts

Impact on the industrial level

The economic structure of Kendal Regency is predominantly characterized by the manufacturing industry, which contributes an average of 40% (Fig. 8). Following manufacturing, the agricultural sector makes a contribution of around 19%. The contribution of the processing industry in Kendal Regency has steadily increased, particularly after the establishment of the Kendal SEZ. Although the increase from 40.2% in 2018 to 40.3% in 2021 may seem marginal, this growth can be understood considering the COVID-19 pandemic. Furthermore, Kendal SEZ officially began operations in 2019. What is noteworthy here is that within just 3 years, Kendal SEZ has already begun to play a significant role as a driving force behind the processing industry in Kendal Regency. In other words, without major disruptions like the COVID-19 pandemic, the role of the Kendal SEZ would likely have continued to grow steadily from year to year.

Fig. 8: Distribution of Kendal Regency’s real GRDP in 2018 and 2021.
figure 8

Source: Authors’ calculation from Kendal Statistics 2022.

Impact on regional development

A similar trend is evident in the LQ calculations, which show that the processing industry’s LQ score increased from 1.18 in 2018 to 1.21 in 2021. The agricultural sector although still maintaining an LQ score above 1, experienced a decline between the two periods. On the other hand, the wholesale and retail trade, motor vehicle and motorcycle repair, construction, and information and communication sectors had LQ scores below 1, indicating that these sectors are not advantageous for Kendal Regency compared to Central Java Province in both periods. Moreover, the LQ scores for these three sectors declined from 2018 to 2021. The results of the LQ analysis are presented in Table 3.

Table 3 Sectoral LQ results to GRDP’s Kendal Regency.

Impact of household expenditures

To create a balanced sample, the matching process for the PSM method must match the treated and control groups based on covariates. This analysis involves some covariates among the samples, namely, marital status, job status, health insurance, social welfare card, sex, and year of education. Based on the analysis, all covariate variables were significant to treatment variables using the logit model with Mahalinobis matching. Matching is a distance-based matching method that refers to the Mahalanobis distance metric, which considers the correlation between covariates to improve matching quality compared to others, such as Caliper and Kernel matching. The results show that all covariates are statistically significant for the treatment variable, which also examines the average treatment effect on the treated (ATT) between the treatment and control groups (Table 4).

Table 4 Propensity score matching based on covariates.

After the matching process, the next step in the analysis was to check the balance of covariates between the treatment and control groups. The result is expected to show that the treatment and control groups are matched, with an insignificant discrepancy in value. That means that the groups have similar characteristics. Then, the next analysis step using the difference in differences is performed. Table 5 shows that marital status, job status, health insurance, social welfare card, sex, and year of education were insignificant between the treatment and control groups. As a result, process matching with all covariates is satisfied.

Table 5 Propensity score matching balance check of covariates.

Figure 9 shows a low value for the percentage of standardized. The results show that the discrepancy between treatment and control groups was close to zero. The result is also consistent with the balance check across covariates, which indicates that the distance value between the two groups is insignificant.

Fig. 9
figure 9

Graph of propensity score matching balance check of covariates. Source: Authors’ calculation.

According to the PSM-DiD analysis, the presence of a Kendal SEZ has a positive impact on increasing total household and food expenditures. However, it is statistically insignificant compared with non-food expenditure. Table 6 presents the positive impact on total household expenditure, which increases by 7.6% and 6.6% with covariates. The Kendal SEZ has a greater effect on food expenditures in the treatment area, exceeding the control area by 8.87% and 9.03%. The PSM-DiD analysis results confirm that the presence of the Kendal SEZ, a flagship development program of both central and regional governments, positively impacts household expenditures in total and on food.

Table 6 PSM-DiD analysis of total and non-food expenditures of households.

Impacts based on spatial analysis

Frick et al. (2018) used nightlight emissions as a proxy for SEZ performance measured by economic activities in the area, even when economic data either do not exist or are not reliable. Using nightlights, this study categorized 346 zones in 22 developing countries based on SEZ performance into three parts, i.e., shrinking (33 countries), stable (150 countries), and growing (163 countries). This implies that half of the zones showed positive growth from SEZ implementation. Regression analysis revealed a significant correlation between the quality and performance of SEZs (Zeng, 2022).

The analysis of NTL data from 2017 to 2021 reveals the substantial impact of the Kendal SEZ on local area development. Significant changes were observed before and after the establishment of the Kendal SEZ, with urban activity reflected in the NTL image values during this period. The core SEZ locations, such as Kaliwungu District, and their surroundings exhibit peak emission fluctuations from 2019 to 2021, ranging from 1.5 to 4.0. The NTL values highlight a significant escalation in development linked to regional activities emitting light, as depicted in Fig. 10.

Fig. 10: Fluctuations in the NTL values of the Kendal SEZ area during the observation period.
figure 10

The blue line represents the monthly mean values, while the orange line shows the yearly moving average calculated on the monthly data. Source: Authors’ calculations.

Regarding spatial agglomeration, Kendal SEZ not only accelerates local economic growth and encourages added value by efficiently using technology and human resources at the regional level. Its presence strategically responds to spatial agglomeration. Detailed analysis underscores the clear manifestation of spatial agglomeration within the Kendal Regency, fostered by the dynamic interactions driven by the Kendal SEZ among closely situated areas. NTL analysis supports this observation, especially in the Kaliwungu District and its environs, which show significant fluctuations and are indicative of increased economic activity and urban development due to the Kendal SEZ. The spatial spillover effect of the SEZ, especially in interdistrict areas, is depicted in Fig. 11a. Kendal SEZ’s strategic location fosters interactions at various levels, becoming the emerging core of the regional economy and positively impacting neighboring districts. The Weleri District, an exception, had already experienced significant economic activity before the SEZ was established, as indicated in Fig. 11.

Fig. 11: Spatial spillover effect of Kendal SEZ in interdistrict areas.
figure 11

a Significant relationship between NTL and regional economic activity: the higher the coefficient value, the stronger the significance of the relationship; b Spatial agglomeration pattern in the study area, with a concentration of agglomeration predominantly occurring around the SEZ area. Source: Authors’ analysis and visualization using QGIS 3.14.

Discussion

The establishment of the Kendal SEZ has positively impacted regional economic development, particularly in the manufacturing sector. This finding is supported by qualitative and quantitative data, indicating increased household expenditures and urban development. However, challenges remain, including infrastructure needs and workforce skill gaps. Effective management and policy interventions are essential to maximize positive impacts and address challenges.

Findings from mixed methods reveal an increase in the manufacturing industry in Kendal Regency after the establishment of the Kendal SEZ in 2019. Data from the Kendal Department of Industry confirm a 32% increase in the number of manufacturing industries, from 56 in 2020 before the SEZ’s operation to 74 in 2022 (Kendal Industrial Park, 2022). The shift in the regional economic structure is closely linked to improvements in the local economy as a result of increased income from the manufacturing sector.

Our quantitative findings supported this finding due to the distribution of Kendal Regency’s real GRDP between 2018 and 2021, which emphasizes the contribution of the manufacturing industry, even though it was slightly different during the COVID-19 pandemic when Kendal SEZs just started their operational business. Likewise, the LQ calculation corresponds to the increase in the manufacturing sector, which is in line with the decline in the agriculture sector. The change in the economic structure manifested in the shift of the percentage composition of GRDP from the agricultural sector in a broader sense (including aquaculture) to the manufacturing sector, as perceived by industry stakeholders. We assume that without major disruptions like the COVID-19 pandemic, the role of SEZ Kendal would likely have continued to grow steadily from year to year.

The increase in the manufacturing industry is also portrayed by the NTL values around the Kendal SEZ, which align with the regional growth patterns, especially in urban development. This finding is evident through the strong spatial correlation between NTL fluctuations and regional income represented by land and building taxes in the urban sector. Since Kendal SEZ’s inception, there has been a noticeable increase in land and building tax revenue in the urban sector, particularly over the past 3 years (2020–2022, when Kendal SEZ started their business in 2021). This presence has stimulated urban activities, even during the pandemic, demonstrating a positive trend compared to sub-districts farther from the SEZ. The spatial agglomeration observed can be attributed to several factors, primarily the concentration of industrial and business activities, and the dense population in specific areas. This can positively impact regional growth by enhancing production efficiency, reducing costs, and increasing regional competitiveness. However, the positive effects of spatial agglomeration must be managed to avoid worsening inequality, environmental issues, and population concentration. Effective management and control are essential for maximizing the positive impact on regional growth and community well-being.

Our qualitative analysis findings regarding job creation, residential growth, and informal entity growth align with what Narula and Zhan (2019) mentioned about the role of SEZs in addressing spatial inequalities and linking with the informal sector. The housing indicator manifested in increasing residential areas is argued to be one of the most significant variables impacting economic growth in a positive array (Batrancea et al., 2023). However, we also identified emerging challenges in employment related to the Kendal SEZ establishment. Based on qualitative findings, we elaborate on the challenges and summarize them into three main points: (1) lack of resources for middle-level management; (2) unskilled operational-level workers; and (3) low levels of work discipline, work ethics, and resilience.

Nevertheless, based on the companies’ development plans, we found that the companies are optimistic about enhancing their operations over the next 5 years. This optimism arises not only from the Kendal SEZ being operational for just 4 years, but also due to factors like relatively low labor wages, cost-efficient transportation due to the proximity to Tanjung Emas port, the anticipated construction of the Kendal port, and the security factors within the SEZ. The Kendal SEZ is a SEZ that offers generic location advantages as key comparative advantages from its zone, such as a large supply of unskilled labor, natural resources (extractive or agricultural), and government-induced location advantages through incentives and subsidies (Narula and Zhan, 2019). Another opportunity to support Kendal SEZ development is the existence of entrepreneurship policies in Indonesia that aim to increase new ventures to boost job creation, economic development, and poverty reduction (Mirzanti et al., 2015).

The Kendal SEZ is in the initial development stage and comprises various industries. These two conditions encourage the development process to remain in the increasing return to scale stage. In line with Potter and Watts (2011), in new agglomeration areas with various types of industry and initial development, such as in the Kendal SEZ, the gathering of workers in this area will initially trigger an increase in productivity simultaneously with the accumulation of materials, raw materials, or suppliers will reduce transportation costs, and the availability of ideas and technology will reduce production costs. These three factors will push this region into a position of increasing returns to scale. In the medium term, efforts are needed to maintain this position by increasing workforce capacity, improving input distribution and stock systems, and continuing efforts to develop and implement innovation.

By addressing the novelty of current knowledge and the existing body of literature, a developing country like Indonesia lists some factors influencing the success of the SEZ program, not only related to a favorable macro environment but also depend on the readiness of human capital and institutional framework between local and national levels. Kendal SEZ, which was claimed to apply a market-driven approach, still focuses on the problem of institutional coordination between the central and local governments. In the previous study on several SEZs in Indonesia, the main barrier is related to the dominant central government on the top-down approach (Hidayat and Negara, 2020).

From a theoretical perspective, SEZ development by providing facilities conducive to improved living conditions for both basic wage workers and highly skilled technical workers. Thus, SEZs can be conducive to easy access to inputs. In relation to the Kendal SEZ, the development of a SEZ is not ensured by improved living conditions for all labor; rather, it is ensured by skilled personnel and strong ethical workers.

Conclusion

The development of the Kendal SEZ in Central Java Province has positively impacted household expenditures and the regional economic structure. This implies that the Kendal SEZ has managed to enhance the community’s well-being, as evidenced by the increase in household expenditures. The Kendal SEZ has a positive impact on the increase in household expenditures, both for food and non-food expenditures. Kendal Regency has undergone an economic structural transformation with a shift in dominance from the agricultural sector to the manufacturing sector. Additionally, a workforce shift occurred, as individuals from the vicinity of the SEZ who were previously engaged in inland fisheries or fishponds transitioned to employment within the SEZ and entrepreneurship in MSMEs (Micro, Small, and Medium Enterprises).

Based on the results of studies on Kendal SEZs, the theoretical lists some factors influencing the success of the SEZ program, not only related to a favorable macro environment but also depending on the readiness of human capital and institutional framework between local and national levels. The success of a SEZ is not ensured by the availability of inexpensive labor and easy access to inputs; rather, the availability of skilled personnel and a strong work ethic are essential.

Future policy considerations should address infrastructure and workforce challenges to sustain and enhance the benefits of SEZs. The availability of human resources from the area around the Kendal SEZ location is the main factor that needs attention to maximize the impact of the Kendal SEZ’s existence on regional economic growth, especially in Central Java. Another factor related to ease of access to the SEZ location, primarily through the construction of a seaport around the SEZ location, is worth considering.

The advancement of technology, particularly that which might boost worker capacity, must be sustained in order to preserve the growing return to scale position in several industries in one place, like Kendal. The government must offer incentives to businesses that continue to develop technology that enhances human resource capabilities.