Developing Eco-Fishing Ports in East Java: A Structural Equation Modeling Analysis

The importance of environmental conservation and sustainable utilization of marine resources has increased global attention in recent decades [1, 2]. Issues such as climate change, declining fish populations, and the degradation of marine ecosystems have mobilized the international community to seek sustainable solutions Robotham [3]. The imperative to preserve marine ecosystems and fish populations has necessitated the development of eco-fishing ports [4]. Therefore, an eco-fishing port is a key infrastructure in preserving marine resources and supporting fishing communities' economic sustainability. According to Nur et al. [5], fishing ports are crucial in the fisheries supply chain.

The fishing ports serve as gateways for the processing and distribution of marine resources, thus making the management of fishing ports significantly important in sustaining the fisheries sector [6]. Eco-fishing port is a key to achieving sustainability in the fisheries sector. It is designed and managed considering minimal environmental impact and promoting sustainable fishing practices in economic activities [7, 8]. One of the significant aspects of an eco-fishing port is sustainable management strategies of marine resources. This includes implementing friendly fishing practices, such as non-destructive fishing, monitoring fish stocks and catch restrictions, and enforcing strict regulations against environmentally harmful fishing practices [9]. Eco-fishing ports can also provide facilities for scientific research to support a better understanding of marine ecosystems and the fish species. The eco-fishing port approach would not only protect fish populations but also ensure that fishermen can continue accessing abundant marine resources in the future [5, 10].

The fishing port supports efforts to preserve marine ecosystems and sustain fish populations, provides tangible benefits to local fishermen, and ensures the sustainable use of marine resources for future generations [11]. In pursuit of sustainable development goals, in-depth research on the impact of various aspects of the fishing port model is highly relevant [12]. This research expected to provide valuable insights for policymakers, researchers, and practitioners in efforts to maintain the sustainability of the fisheries sector through eco-fishing port in East Java [13].

This research examines previous similar research and successful sustainable fishing port initiatives from across the world [14]. This research examined how factors like future growth, current environmental regulations, and expanding beyond just fishing can influence sustainability of port of Vigo. Similarly, Mansour [15] conducted a study on a sustainable green port policy in Egypt, focusing on resource management, minimizes environmental impact from port operations, prevents pollution, and improves public and environmental health, striving to balance environmental, social, and economic well-being.

The analysis of previous studies and actual conditions of fishing ports in East Java, Indonesia summarizes six aspects affecting the sustainability of fishing ports, including market demand, community welfare, infrastructure, environment, community empowerment, and regulation aspects [16, 17]. Furthermore, the aspects that influence the eco-fishing port as a sustainable port model need to be further analyzed. This research uses exploratory factor analysis and confirmatory factor analysis to establish SEM for empirical analysis. The research will elucidate the Partial Least Square based Structural Equation Modelling (PLS-SEM) used to analyze the factors affecting the development of eco-fishing port, making it a significant contribution towards guiding steps to preserve marine environments and promote sustainability in the fisheries industry.

This explanatory research design employed the survey method. Questionnaires and google forms were utilized in this research. The analysis employed variable indicators presented as statements and respondents assigned scores on a scale for strongly disagree to strongly agree, using a numerical range of 1 to 5. This study employed PLS-SEM, which is particularly suited for complex models and theory development with multiple constructs and indicators. It is often encountered in sustainability studies involving various interrelated factors. Additionally, PLS-SEM does not require normal distribution assumptions, making it advantageous for this research as real-world data that may exhibit non-normality, and offering robust insights that can inform sustainable practices and policies. PLS-SEM utilizing exogenous, endogenous latent, and indicator variables as outlined [27]. A measurement model was appropriately employed to depict the associations between latent/construct variables and their respective indicators, referred to as outer relations.

The measurement model elucidated the connection between the latent variable and its indicator variable (manifest), commonly called the outer relation or measurement model. This model comprised both the formative indicator model and the reflective indicator model. The reflective model manifests when the latent variable influences the manifest variable. In contrast, the formative model clarifies that the manifest variable impacts the latent variable, with the causality direction flowing from the manifest variable to the latent variable. Eqs. (1) and (2) illustrate the reflective model as presented by [28]:

Measuring model equations are

$X=\Lambda X \xi+\delta$           (1)

$Y=\Lambda Y_\eta+\varepsilon$             (2)

Structural model equation is

$X=\Gamma \xi+\zeta$                 (3)

ΛX and ΛY are the factor loadings of the index X (md, cw, if, env, ce) and two endogenous Y (rg and ef), δ and ε are the measurement errors of the explicit variables, ξ and η are the exogenous latent variables and endogenous latent variables respectively. ξ is the residual, Γ is the matrix of structural coefficient between the latent variables and the external dependent latent variables [29].

The latent variables consisted of five exogenous variables (md, cw, if, env, ce), an endogenous exogenous variable (rg), and an endogenous variable (ef). Table 1 outlines the specific indicators used to measure each latent variable components involved in the analysis.

Table 1. Latent/Construct variables

Table 2. Criteria model test

Primary and secondary data were both used in this investigation [55]. A systematic survey was used to evaluate the infrastructure and operations of the port, and in-depth interviews with key stakeholders and frequent port users yielded primary data [56].

The outer model (indicator test) was assessed according to the literatures as criteria outlined in Table 2. This assessment encompassed factors such as convergent validity (individual reliability), discriminant validity (internal consistency), average variance extracted (AVE), and composite reliability (discriminant validity).

This study was conducted in six fishing ports of East Java Province: The Prigi fishing port in Trenggalek Regency, the Brondong fishing port in Lamongan Regency, the Pondok Dadap fishing port in Malang Regency, the Mayangan fishing port in Probolinggo Regency, the Puger fishing port in Jember Regency, and the Tamperan fishing port in Pacitan Regency (Figure 1).

1.png

Figure 1. Site Study

The period of data collection was May to September 2023. Purposive sampling was used to choose 215 respondents from the administrative offices of the Ministry of Maritime Affairs and Fisheries., fishing companies, and fisherman communities from six fishing ports in the province of East Java participated and completed the guided questionnaire, fulfilling the minimum sample requirement criteria according to the guidelines for PLS SEM analysis [57]. Knowledge and experience are the key factors in choosing the respondents, as outlined by Hadi [44]. Reports and interview from related fishing port organizations, businesses, and establishments inside those fishing ports provided further secondary data. These sources offered valuable insights into operational practices, environmental impacts, economic impacts, social impacts, and regulatory compliance. Examining these insights enables an understanding of efficient operations, recognition of broader environmental, economic and social impacts, and an appreciation for the importance of regulatory compliance.

The collected data is first cleaned to address missing values, outliers, and inconsistencies. This step ensures the reliability and accuracy of the data before analysis. Initial descriptive statistics are generated to summarize the data and provide a basic understanding of the sample characteristics. The PLS-SEM involves model specification, measurement model assessment, structural model assessment, bootstrapping, and model fit. The parameter settings of PLS-SEM in this research used 215 data points and 5000 bootstrap samples to ensure robust estimates of standard errors and confidence intervals. A significance level of 0.05 is employed for hypothesis testing, and indicator loadings above 0.7 are retained to ensure a strong representation of the latent constructs [27]. The conceptual framework is illustrated in Figure 2.

2.png

Figure 2. Conceptual framework

The findings of this research are related to numerous references and best practice of sustainable fishing port worldwide. For instance, a methodology for transforming Egyptian ports into sustainable green ports by balancing environmental, social, and economic aspects [14]. The study highlights primary objectives such as managing resources responsibly, reducing environmental impacts, preventing pollution, and enhancing personal, community, and environmental health in fishing port. Another similar research is the port of Vigo in Spain, which is committed to enhancing its sustainability strategies by focusing on anticipating growth, staying abreast of sustainability legislation and contemporary trends, and exploring diversification opportunities. This approach acknowledges that the port has feasible options to broaden its business scope beyond conventional fishing activities [14]. The port of Valencia is another Spanish port that has made a strong commitment to transforming into a green port. It focused on reduce and monitor noise and air pollution generated by port activities by digitalizing and integrating information systems to enhance the management of road traffic at the port's entrances and exits.

Integrated with the previous studies and best practices, the strategy to develop eco-fishing ports in East Java involves a comprehensive analysis of several key variables. These include Market Demand (md), which ensures that the ports meet the economic needs of the fishing industry, Community Welfare (cw), which focuses on improving the quality of life for local community, Infrastructure (if), which ensures the ports have the necessary facilities and services to operate efficiently. Additionally, the strategy considers Environmental Carrying Capacity (env) to ensure that port activities do not exceed the ecological limits of the environment, and Community Empowerment (ce) to involve local communities in decision-making processes and boost their capacity to benefit from port activities. The Regulation (rg) is crucial for ensuring that the development and operation of the ports comply with relevant laws and policies, promoting long-term sustainability and resilience [14].

The strategy to meet the needs of the international market involves high-quality processes and the production of products that meet international standards, as well as obtaining product certification according to applicable standards [31]. The latent variable Market Demands (md) is significantly related to biosecurity (md_1), traceability (md_2), conservation of fish resources (md_4) and assurance of fish availability (md_5). Biosecurity, traceability, conservation of fish resources and assurance of fish availability is essential for ensuring the sustainability, safety, and quality of fish production to fulfill the international market demand [30].

Biosecurity measures in fisheries ensure the safety of fish products for human consumption by preventing the spread of pathogens and contaminants. Biosecurity contributes to producing safe and high-quality seafood, meeting the standards and expectations of consumers. The traceability serves the purpose of tracking and documenting the production and distribution of seafood throughout the supply chain. Its responsible ensuring environmentally friendly fishing practice, safeguarding food safety, supporting conservation of fish resources and sustainable and transparent seafood supply chains. The sustainability of fish stock in the fisheries system assures fish availability, thereby creating a stable supply in the fish market [10, 30, 31].

A fish market offering consistent assurance of fish availability tends to be more attractive to businesses and stakeholders in the supply chain, as they can plan production and distribution more effectively [5]. Hence, it is important to assess the potential sustainable yield of this commercially significant species to guarantee the long-term viability of the stock [10].

The social system variable is based on fishermen's welfare. The latent variable of Community Welfare (cw) has strong correlation to indicator of price protection (cw_3) and quality of life (cw_5). Price protection contributes to the stability of income in fishing communities by safeguarding fish prices [35]. The stability of fish prices can protect community income from price fluctuations, providing a sense of security for fishing communities in terms of both food and economic stability. Quality of life (cw_5) reflects an indicator or variable measuring the quality of life influenced by income, economic security, access to adequate education, access to infrastructure and public facilities, and the availability of sustainable fisheries resources. Therefore, the fisheries are able to provide for a household's basic need. Therefore, an improvement in quality of life is a key indicator of the increasing the Community Welfare [34].

The latent variable of Infrastructure (if) is significantly related to the indicator of port performance(if_1), fish handling infrastructure (if_2), transportation infrastructure (if_4), and communication infrastructure (if_5). The port performance reflects the overall efficiency, effectiveness, and general performance of a fisheries port, encompassing operational productivity, the speed of loading and unloading of catches, handling facilities, security, and logistical efficiency [5]. The adequate fish handling infrastructure (if_2) lead to efficient fish handling from capture to distribution, helping maintain product quality throughout the handling and storage processes [35].

The system and the effects of transportation on fishing communities are measured using sustainable transportation indicators [39]. The availability of transportation infrastructure (if_4) increased connectivity and enabled more efficient movement of fish production from fishing port to market or industry. Communication facilities (if_5) include information technology and communication networks. The communication facilities (if_5) involve tracking systems, communication between fishermen and processing centers, and information platforms supporting the exchange of crucial data. Good communication infrastructure can enhance the coordination and management of fisheries resources [40].

Environmental protection concern to a desire to protect and preserve the environment The fishing product qualities is influenced by the environment or support for environmental protection [8]. The analysis research found that the availability of water resources (env_3) and the potential for cultural and local wisdom (env_5) are closely related to Environmental Carrying Capacity [34]. A high level of environmental sustainability can create conditions that support the availability of good water resources (env_3). Meanwhile, local communities with a deep understanding of water ecosystems and the practice of local wisdom (env_5) in their management contribute to higher levels of environmental sustainability [60].

Empowering Communities related to education and training (ce_2), institution (ce_3), and business collaboration (ce_5). These three elements have positive impact to the economic and social sustainability of fishing communities [34].

The regulation for the protection of fishery resources (rg_3) aims to safe the fishery resources from overexploitation and ensure long-term sustainability. Therefore, regulation monitoring (rg_5) and enforcement of regulation (rg_6) requires a firm handling of violations in fishing port. Integrating regulations and effective enforcement against violations is crucial to ensure the sustainability of fishery resources and support the livelihoods of fishing communities. Therefore, a successful Eco-fishing port (ef) is the outcome of the effective integration of implementation of regulations (ef_2), long-term strategic plan (ef_4), protection of the local community (ef_5) and a commitment to sustainability principles throughout its operations [9].

One significant limitation of sustainable fishing port in East Java is the limited progress of implementation. Developing a diagnostic and planning tool to propose future scenarios could be beneficial. Government, private sectors, and local community through non governments organization should recognize the importance of this commitment, and fully collaborated on developing the sustainable fishing port in East Java.