Mechanism of incentives and accountability in rural institutions: Regional context in global dimensions of SDGS

Abstract

This study aims to analyze the extent to which government incentives and village accountability contribute to village development in Indonesia. The achievement of the Village Development Index (VDI) consists of three dimensions: social resilience, economic resilience, and environmental resilience. These indicators align with the goals of achieving Sustainable Development Goals (SDGs). The research was conducted using village data from Central Sulawesi Province, Indonesia. The data were obtained from 303 villages and sourced from the Central Sulawesi Statistics Agency. The results of the study show that village accountability and government incentives through the village fund have a positive effect on VDI. This finding is consistent with the differences in VDI measurements using both VDI scores and status. After exploring the dimensions based on VDI, this study also found that accountability had an impact on social resilience and economic resilience, while government incentives contributed to social resilience and environmental resilience. However, village assistance does not appear to have made a significant contribution to village development, and it has also been found that village development in Indonesia has not been evenly distributed in terms of topography. This research provides new insights about the relationship between government incentives, village accountability, and the achievement of SDGs in the rural context. It proposes the formation of accountable villages as one of the strategies and indicators for achieving SDGs in the rural areas of Indonesia.

Keywords:

• government incentives
• financial accountability
• rural studies
• SDGs
• Indonesia

PUBLIC INTEREST STATEMENT

This study examines the role of government incentives and village accountability in village development in Indonesia, using the Village Development Index (VDI) as a measure of progress in social, economic, and environmental resilience aligned with Sustainable Development Goals (SDGs). Data from 303 villages in Central Sulawesi Province were analyzed, and the results indicate that both village accountability and government incentives, particularly through the village fund, positively impact VDI. The research also highlights the influence of accountability on social and economic resilience, while government incentives contribute to social and environmental resilience. However, village assistance has not significantly contributed to village development, and disparities in development were observed based on topography. The study suggests promoting accountable villages as a strategy for achieving SDGs in Indonesia’s rural areas, providing valuable insights into rural development dynamics.

1. Introduction

Rural development is a multidimensional aspect with political dimensions, resources, accountability, priorities, and choices (Douglas, 2005). Meanwhile, the achievement of the SDGs and the implementation of good governance still face several challenges. These problems include the low interaction of stakeholders in various sectors and scales to ensure equality, fairness, and accountability mechanisms in decision-making (Bowen et al., 2017). Additionally, there are still many challenges in the development and achievement of SDGs in the village context, such as structural problems, governance issues, capacity constraints, financial literacy, complicated budgeting and financial reporting systems, and corruption (Antlöv et al., 2016; Bebbington et al., 2006; Beekman et al., 2014; Derks & Romijn, 2019; Douglas, 2005; Gupta et al., 2021; Harun et al., 2021; Mulyana et al., 2022; Surachman & Astuti, 2020; Vasstrøm & Normann, 2019). Biglari et al. (2022) emphasize the differences in capacity and challenges faced by each country in implementing and achieving SDGs. To fill the gap in research, this study aims to analyze the extent to which accountability and government incentives influence village development. Specifically, it analyzes the role of government incentives (referred to as “Dana Desa”) and village accountability in the framework of achieving SDGs indicators in the rural context in Indonesia.

National government commitment, policies, strategies, governance, and accountability have become crucial factors in achieving SDGs (Abhayawansa et al., 2021; Bowen et al., 2017; Breuer & Leininger, 2021; Hickmann et al., 2022; Lauwo et al., 2022). According to Lauwo et al. (2022), intended government policies and strategies include planning financial resources, empowering and engaging collaborative stakeholders, and strengthening integrative governance systems that support achieving accountability at the local level. Hickmann et al. (2022) emphasize the importance of stakeholder involvement, institutional and governance structures, and the availability of financial resources in supporting the achievement of the SDGs. Indonesia has placed significant emphasis on efforts to achieve SDGs indicators by exploring the role of the annual budget for each village as a government incentive to advance rural development. Additionally, Indonesia has used VDI as an indicator of village development. In this regard, government incentives and village accountability are critical determinants of achieving SDGs in the rural context in Indonesia.

Central Sulawesi Province, with the highest growth rate of Gross Regional Domestic Product (GRDP) compared to other provinces in Indonesia, was chosen as the sample, consisting of 303 villages. Government incentives represent the extent of the national government’s commitments and policies in supporting village development through funding support. Meanwhile, village accountability represents the extent of the role of local government capacity and credibility in supporting village development. Hickmann et al. (2022) and Lauwo et al. (2022) discovered the important role of financial resource capacity in achieving the SDGs. Therefore, to support the achievement of SDGs in the rural context in the economic, social, and environmental fields, a strategy of government incentives is needed to strengthen village human resource and financial capacity. The paper is divided into five sections. The first section provides the background of the study. The second section discusses the literature review and the basis for developing hypotheses. The third section outlines the research methods used. The fourth section presents the research results, and finally, the fifth section presents conclusions, implications, limitations, and suggestions for further research.

2. Literature review and hypothesis development

2.1. Government incentives in village development

State support plays an important role in protecting the welfare of rural communities. This support extends beyond policy development and includes implementation, governance, assistance, and incentives (Bowen et al., 2017; Gupta et al., 2021). Lauwo et al. (2022) state that the governance system should promote accountability at the local level by formulating policies and strategies for planning financial resources and empowering collaborative stakeholders. However, due to limited resources, government programs in rural areas often face challenges and may fail in the early stages of implementation due to misalignment of focus (Derks & Romijn, 2019).

Harun et al. (2021), Surachman and Astuti (2020), and Antlöv et al. (2016) found that the management of village fund incentives from the central government, given to village administrations, was not fully effective in supporting village development. This highlights the significance of financial resources in supporting the implementation of development programs at the local level (Hickmann et al., 2022; Lauwo et al., 2022). Given the limited financial resources in rural areas, substantial government incentives can play a crucial role in supporting the achievement of SDGs targets in those areas (Antlöv et al., 2016). Therefore, the first hypothesis was formulated as follows:

H1:

Government incentives have a positive effect on village development in achieving SDGs targets.

2.2. Financial accountability in village development

Accountability is interpreted as a relationship between actors and forums, where actors have an obligation to explain and justify their actions, while forums can ask questions and provide judgments, ultimately leading to consequences that must be faced by actors (Bovens, 2007). Achieving public accountability requires a publication medium that allows accurate and comprehensive information to be received by rural communities, enabling them to ask questions and/or provide assessments of the information provided. Accounting, reporting, accountability, and governance processes play a crucial role in determining the achievement of SDGs, which can lead to the creation of social and economic values in the long term (Abhayawansa et al., 2021).

The achievement of the SDGs represents the extent of the performance or quality of public services in a country or region. Public services are closely related to the implementation of accounting and auditing in terms of funding, governance, and accountability in the control and operation of public services (Broadbent & Guthrie, 2008; Furqan et al., 2021). Previous studies have analyzed the linkages between accountability, transparency, and community participation with government performance and the quality of public services (Husnah & Adam, 2022; Furqan et al., 2020; Speer, 2012). Similarly, at the village level, several previous studies have analyzed the relationship between accountability and transparency with the quality of public services and the trust of rural communities (Pratolo et al., 2022; Sofyani et al., 2022). The linkage is explained through the mechanism of actualizing accountability, emphasizing the effectiveness of implementing the government’s internal control system, disclosure, and compliance with government accounting standards. Governance and accountability can support the implementation of more effective, efficient, and higher-quality public services (Furqan et al., 2020).

In relation to SDGs, the role of accountability is mainly characterized by financial reporting and monitoring mechanisms. It is also related to the availability of adequate data and performance indicators for all stakeholders to communicate and measure performance in achieving the SDGs. These indicators underline why accountability can play an important role in achieving the SDGs in each country (Abhayawansa et al., 2021; Bowen et al., 2017; Breuer & Leininger, 2021; Lauwo et al., 2022). Furthermore, Pratolo et al. (2022) found a significant effect of accountability on service quality at the rural level. Thus, the second hypothesis was formulated as follows:

H2:

Financial accountability has a positive effect on village development in achieving SDGs targets.

3. Methodology

This research was conducted in villages in Central Sulawesi Province, Indonesia. The province is known for its abundant natural resource potential. During 2020–2021, Central Sulawesi Province ranked among the top 2 positions with the highest GRDP growth in Indonesia. It covers a total area of approximately 61,841.29 km2, making it the largest province on Sulawesi Island. The province comprises 1 city, 12 districts, 176 sub-districts, 2,020 villages, and 1,632 islands. Almost all districts have coastal and island areas, and there are remote indigenous communities that have not been adequately empowered (Central Bureau of Statistics-Central Sulawesi, 2022).

The sampling method used was the Slovin formula. An initial sample of 329 villages was determined using secondary data collected from the Bureau of Statistics (BPS) of Central Sulawesi Province. Additional data on VDI and village fund budgets were obtained from the Ministry of Villages, Development of Outer Regions, and Transmigration of the Republic of Indonesia. The research was conducted from July to August 2022. There were 26 villages whose data could not be confirmed, resulting in a final sample of 303 villages that proportionally represented all districts in Central Sulawesi Province. To address the research problem, the empirical model used to test the research hypothesis is as follows:

(1) $\mathrm{V}\mathrm{D}{\mathrm{I}}_{\mathrm{t}}={\beta }_0+{\beta }_1\mathrm{F}\mathrm{U}\mathrm{N}\mathrm{D}\mathrm{I}\mathrm{N}{\mathrm{G}}_{\mathrm{t}}+{\beta }_2\mathrm{A}\mathrm{C}\mathrm{C}\mathrm{O}\mathrm{U}\mathrm{N}{\mathrm{T}}_{\mathrm{t}}+{\beta }_3\mathrm{A}\mathrm{S}\mathrm{S}\mathrm{I}\mathrm{S}\mathrm{T}\mathrm{A}\mathrm{N}\mathrm{C}{\mathrm{E}}_{\mathrm{t}}+{\beta }_4\mathrm{T}\mathrm{O}\mathrm{P}\mathrm{O}\mathrm{G}\mathrm{R}\mathrm{A}\mathrm{P}\mathrm{H}{\mathrm{Y}}_{\mathrm{t}}+{\epsilon }_{\mathrm{t}}$(1)

VDI is a village development variable measured by the score and status of the developing village index. This study used VDI data as a basis for measuring village development, which is expected to be used as a foundation for assessing the achievement of SDGs indicators in the rural context in Indonesia. However, the availability of SDGs indicators in the rural context was not available. FUNDING is a government funding incentive variable measured by the natural logarithm of the amount of village funds distributed by the government to the village government. ACCOUNT is a village accountability variable, measured by the village accountability index obtained from the results of the Principal Component Analysis (PCA), as also carried out by Dougherty et al. (2000) and Setyaningrum et al. (2013). The main goal of PCA is to reduce dimensions or reduce variables that initially have a large number to smaller ones while retaining as much variation as possible in the original variables to be easily interpreted (Jolliffe, 2002).

The PCA technique initiates by defining the variables or their dimensions based on relevant concepts and theories. Accountability in the public sector was conceptualized using Bovens (2007, 2010) and Mulgan (2020) as the basis. The items encompass regulations pertaining to reporting and accountability for village governance, which includes the management of village finances and assets. Village accountability was derived from a composite value of 6 dimensions, namely regulations, media, data documentation media, human resource capacity, system, and information.

The first dimension is regulations which represents the dimension of the availability of village regulations, measured through (a) regulations on reporting mechanisms, (b) regulations on publication mechanisms, (c) regulations on mechanisms for community participation, and (d) regulations on public complaint mechanisms. The second dimension is media which represents the dimension of the availability of media publications, measured by (a) websites, (b) social media, (c) billboards, and (d) announcement boards. The third dimension is documentation which represents the dimension of the availability of data documentation media, measured by (a) computer/laptop, (b) storage cabinet, (c) external hard drive, and (d) Google Drive. The fourth dimension is human resource which represents the dimension of human resource capacity, measured by (a) village officials with an economic/accounting background, (b) village officials who attended training on drafting village budgets, (c) village officials who attended training, and (d) village officials who took part in village financial report preparation training. The fifth dimension is system which represents the dimension of the information system, measured by (a) village information system, (b) updates to the village information system, (c) village financial systems, and (d) updates to the village financial system. Lastly, the sixth dimension is information which represents the dimension of the type of information provided by the village community, measured by (a) information on village planning, (b) information on the realization of village revenues and expenditures, (c) information on program implementation/village performance, and (d) information on village-owned enterprises.

Moreover, the control variables consist of village assistants and regional topography. Village assistance represents the presence of village assistants and is measured categorically (1 = not available; 2 = inactive; 3 = active). Meanwhile, topography is measured on a categorical scale (1 = mostly peaks/cliffs; 2 = mostly slopes; 3 = mostly plains; 4 = mostly valleys).

4. Research results

Descriptive statistical descriptions for each dimension forming the Village Accountability Index (VDI) are presented in Table 1.

Table 1. Descriptive Statistics of village accountability dimensions

Information	N	Means	Standard Deviations	Min	Max
REGULATIONS	303	0.92	0.78	0	2
MEDIA	303	1.65	1.17	0	4
DOC	303	2.16	0.63	1	4
HR	303	0.60	1.13	0	4
SYSTEM	303	3.15	1.15	0	4
INFORMATION	303	1.19	1.10	0	4

Information:

REGULATIONS, is a dimension of the availability of village regulations, as measured by (a) regulations on reporting mechanisms, (b) regulations on publication mechanisms, (c) regulations on mechanisms for community participation, (d) regulations on public complaint mechanisms; MEDIA, is a dimension of the availability of media publications as measured by (a) websites, (b) social media, (c) billboards, (d) announcement Boards; DOC, is a dimension of availability of data documentation media, as measured by: (a) computer/laptop, (b) storage cabinet, (c) external hard drive, (d) google drive; HR, is a dimension of human resource capacity, as measured by: (a) village officials who have an economic/accounting background, (b) village officials who attended training on drafting village budget, (c) village officials who attended training; (d) village officials who took part in village financial report preparation training; SYSTEM, is a dimension of an information system, which is measured by: (a) village information system (b) village information system updates, (c) village financial systems, (d) village financial system updates; INFORMATION, is a dimension of the type of information provided by the village community, as measured by: (a) information on village planning, (b) information on the realization of village revenues and expenditures, (c) information on program implementation/village performance, (d) information on village-owned enterprises.

Table 1 indicates that the average sampled village has sufficient documentation of media and information systems, regulations, and media publications. However, there is a lack of adequate support from human resources in accelerating village accountability. These findings align with Fitriani et al. (2020) and Sofyani et al. (2022), who have shown that the competence of village government officials is low, leading to limited information and discussion spaces in the rural context. Additionally, Surachman and Astuti (2020) and Harun et al. (2021) found that the substantial influence of the central government in managing village funds and VFI in Indonesia hampers the initiative of village stakeholders in formulating their own regulations to achieve village accountability.

Regarding the availability of village government human resources, the average village lacks sufficient personnel to support reporting and publications. The findings indicate limited participation of village officials in training on village budget and financial reports. These results align with Harun et al. (2021) and Antlöv et al. (2016), who emphasize that the realization of village accountability in Indonesia is still very limited due to significant institutional challenges, with village administrators heavily relying on central governments. As a result, there is low initiative from village governments to establish regulations and provide necessary facilities for the implementation of reporting, accountability, and information publication for the rural community. Additionally, the implementation of the PCA analysis procedure involved presenting correlation analysis between the variables using the Spearman correlation measurement (Table 2).

Table 2. Correlation analysis

Variable	Regulations	Media	Doc	HR	System	Information
Regulations	1.000
Media	0.247*** (0.000)	1.000
Doc	0.105* (0.0 66)	0.153*** (0.007)	1.000
HR	0.238*** (0.000)	0.196*** (0.000)	0.212*** (0.000)	1.000
System	0.140** (0.014)	− 0.022 (0.646)	−0.115** (0.044)	− 0.072 (0, 206)	1.000
Information	0.0 89* (0.121)	0.422*** (0.000)	0.159*** (0.00 5)	0.2 17*** (0.000)	0, 162*** (0.004)	1.000

***,**,* = Significant P-value 1%, 5%, 10%.

Source: Secondary data and field data, (Processed, 2022).

Table 2 displays the correlation between the various dimensions used to form the accountability index. The village accountability index was created using the PCA method, incorporating all these dimensions. To enhance the efficiency of the component model and maximize the degree of component loadings, matrix rotation was conducted using the orthogonal varimax method. The results reveal that a loading of 0.3 was applied. Component 1 comprises dimensions related to publication media, types of information, availability of human resources, existence of regulations, and documentation of media and reporting information systems. On the other hand, Component 2 encompasses dimensions related to the reporting information system, types of information, existence of regulations, media publications, media documentation, and availability of human resources. This indicates that the village accountability index, formed based on the PCA procedure, effectively represents most of the variables used to construct the index, making it suitable for further testing. The equation for the formation of the village accountability index variable is presented as follows:

$\mathrm{A}\mathrm{C}\mathrm{C}\mathrm{O}\mathrm{U}\mathrm{N}\mathrm{T}\mathrm{S}{ }_{\mathrm{t}}=0.3939(\mathrm{R}\mathrm{E}\mathrm{G}\mathrm{U}\mathrm{L}\mathrm{A}\mathrm{T}\mathrm{I}\mathrm{O}\mathrm{N}\mathrm{S}{ }_{\mathrm{t})}+0.5309(\mathrm{M}\mathrm{E}\mathrm{D}\mathrm{I}\mathrm{A}{ }_{\mathrm{t})}+0.3312(\mathrm{D}\mathrm{O}\mathrm{C}{ }_{\mathrm{t})}+0.4371(\mathrm{H}{\mathrm{R}}_{\mathrm{t})}+0.0816(\mathrm{S}\mathrm{Y}\mathrm{S}\mathrm{T}\mathrm{E}\mathrm{M}{ }_{\mathrm{t})}+0.5055(\mathrm{I}\mathrm{N}\mathrm{F}\mathrm{O}\mathrm{R}\mathrm{M}\mathrm{A}\mathrm{T}\mathrm{I}\mathrm{O}\mathrm{N}{ }_{\mathrm{t})}$

Table 3 presents the average VDI value as 0.657, suggesting that the average village falls under the category of developing villages, while some are categorized as underdeveloped. The mean FUNDING value of 879.03 indicates that the average village fund budget amounts to 879.03 million rupiah. As for ASSISTANCE, the mean value of 2.85 indicates that most villages have been actively assisted by village facilitators. The mean TOPOGRAPHY value of 2.32 suggests that some villages are situated on the slopes of the mountains. Further details on the correlation between variables can be found in Table 4.

Table 3. Descriptive Statistics of research variables

Information	Means	Std. Dev	Min	Max
VDI	0.65	0.06	0.42	0.85
FUNDING*	879.03	180.65	639.93	1975.01
ACCOUNTS	−6.09	1.35	−2.816	3.846
ASSISTANCE	2.85	0.51	1.00	3.00
TOPOGRAPHY	2.32	0.47	2.00	4.00

VDI, the Village Development Index, is determined by evaluating the score and status of the village, which includes a comprehensive explanation of VDI dimensions, indicators, scoring, and status found in Attachment 1. FUNDING represents a government funding incentive variable, and its measurement is based on the natural logarithm of the amount of village funds distributed by the government to the village government. ACCOUNT is a village accountability variable, which is evaluated through the village accountability index formed from various dimensions, such as Regulation, Media, Documentation, HR, Systems & Information (refer to Table 1 for a detailed explanation of these dimensions). ASSISTANCE is a variable that assesses the presence of village assistants, categorized as “1” if village assistants are not available, “2” if they are present but not active, and “3” if they are actively involved. Additionally, TOPOGRAPHY is measured categorically, with “1” representing a topographic area mostly composed of peaks/cliffs, “2” for mostly slopes, “3” for mostly plains, and “4” for mostly valleys.

* In million rupiahs.

Source: processed data (2022).

Table 4. Variable correlation analysis

Variable	VDI	FUNDING	ACCOUNTS	ASSISTANCE	TOPOGRAPHY
VDI	1.000
FUNDING	0.219*** (0.001)	1.000
ACCOUNTS	0. 215*** (0.000)	0.049 (0.393)	1.000
ASSISTANCE	0.062 (0.275)	−0.061 (0.282)	0.227*** (0.001)	1.000
TOPOGRAPHY	0.147** (0.010)	−0.035 (0.540)	0.349*** (0.000)	0.084 (0.142)	1.000

* **, **, = significant P-value 1%, 5%,

Source: Data processed, 2022.

Table 4 illustrates a noteworthy correlation between the VDI variables and the FUNDING, ACCOUNT, and TOPOGRAPHY variables. This suggests a positive relationship between village development and government incentives, accountability, and village topography. However, the ASSISTANCE variable does not show a significant correlation with the VDI variable. Moving forward, Table 5 presents the results of testing the research hypothesis.

Table 5. Hypothesis testing results

Variable	Sign Expectations	Model-1A (Score)	Model-1B (Status)
Cons.		−0.9739 (0.0 28)	−9.2666 (0. 038)
FUNDING	H1	0.077*** (0. 000)	0.576*** (0. 007)
ACCOUNTS	H2	0.007*** (0. 004)	0.075*** (0.004)
ASSISTANCE	+	0.003 (0. 723)	0. 001 (0. 989)
TOPOGRAPHY	?	0. 013* (0. 072)	0.181*** (0. 008)
Obs.		303	303
Prob > F		0.0000	0.0000
R-squared		0.0987	0.0905
VIF means		1.10	1.10

Dependent Variable: Village Development Index; Model 1A: measured by VDI score; Model 1B: measured by VDI status.

***,**,* = significant P-value 1%, 5%, 10%.

Source: Data processed, 2022.

Table 5 displays the outcomes of testing the research hypothesis. The robustness testing indicated an R-squared value of 0.0987 for Model 1A and 0.0905 for Model 1B. This indicates that the models explain 9.87 percent and 9.05 percent of the variability, respectively, in explaining village development with a significant level (statistical value F) of 1 percent. The mean value of VIF in both models is 1.10, indicating the absence of multicollinearity issues. The results of testing the hypothesis on the two models remain consistent, despite differences in the measurement of village development variables.

The outcomes of H1 testing (Model 1A) demonstrate that the FUNDING variable positively affects VDI, with a coefficient of 0.077, significant at the 1 percent level. This implies that villages receiving higher government incentives are more likely to implement development programs more effectively compared to villages with lower government incentives. On the other hand, Model 1B reveals that the amount of funds provided by the government influences village development. In other words, villages with greater financial resources tend to have a better development status compared to those with limited financial resources. These results align with Lauwo et al. (2022) and Hickmann et al. (2022), emphasizing the significance of financial resource availability and the role of the national government in supporting the achievement of SDGs at the local level.

The findings from H2 testing reveal that the ACCOUNT variable has a positive effect on VDI, with a coefficient of 0.007, significant at the 1 percent level. This signifies that higher levels of village accountability lead to more effective village development. Villages that demonstrate greater accountability in governance and the implementation of development programs in rural areas tend to achieve a better development status compared to those with lower levels of accountability. These results align with Pratolo et al. (2022), who also highlight the role of accountability in determining service quality in rural Indonesia. Moreover, these findings support the assertions of Lauwo et al. (2022), Abhayawansa et al. (2021), Breuer and Leininger (2021), and Bowen et al. (2017), who emphasize the significance of accountability in achieving SDGs at the local level.

Concerning the outcomes of testing the control variables, Table 5 indicates that the ASSISTANCE variable does not have a significant effect on VDI in both Models 1A and IB. This suggests that the role of village assistants is not fully effective in supporting rural development in Indonesia. On the other hand, the TOPOGRAPHY variable has a positive impact on the VDI variable in both models. This indicates that differences in village topography have an influence on variations in the level and status of village development. This finding aligns with Furqan et al. (2021), who explain that differences in the quality of public services can be attributed to variations in the geographical location of local governments. Furthermore, the VDI serves as a variable measurement of village development, representing a composite index formed from the economic, social, and environmental resilience components. An additional test was conducted to determine the effect of the independent variables on each of the VDI components (Table 6).

Table 6. Additional test results for village development variable components

Variable	Model 2A (economic resilience)	Model 2B (Social resilience)	Model 2C (Environmental Resilience)
Cons.	0.181 (0. 692)	−1,303 (0. 118)	−1,801 (0. 014)
FUNDING	0.023 (0. 273)	0.084** (0. 038)	0.124*** (0. 001)
ACCOUNTS	0.012*** (0.000)	0. 010** (0. 038)	0.000 (0. 838)
ASSISTANCE	0.016 (0. 132)	0.019 (0. 212)	− 0.025* (0. 070)
TOPOGRAPHY	0.014** (0. 031)	0.022* (0. 091)	0.002 (0. 829)
Obs.	303	303	303
Prob > F	0.0000	0.0002	0.00 33
R-squared	0.1266	0.0730	0.0599

***,**,* = significant P-value 1%, 5%, 10%.

Source: Data processed, 2022.

Table 6 presents the results of VDI components as the dependent variable. In all tests (models 2A, 2B, and 2C), the findings indicate that FUNDING has a significant positive effect on social resilience and environmental resilience. This suggests that government incentives play a role in enhancing the effectiveness of implementing village development, particularly in the economic and environmental resiliences. These results are consistent with the findings of Harun et al. (2021), which highlight that government incentives have not been fully effective in supporting rural development in Indonesia, particularly in the social sector.

Regarding village accountability, Table 6 demonstrates that the ACCOUNT variable has a significant positive effect on social and economic resilience. These findings underscore the crucial role of accountability in promoting community welfare and enhancing social and economic aspects in rural areas (Abhayawansa et al., 2021). It further emphasizes the necessity to consider policies that govern environmental performance accountability mechanisms in rural areas (Burritt & Welch, 1997). Rural stakeholders should understand the actions taken by village governments and the resulting consequences on the ecological system and environmental issues in rural communities. As for the control variable, significant differences in social and economic developments are attributed to variations in village topography. This indicates an imbalance in economic and social development across villages in Indonesia, particularly between villages situated on mountain slopes and those located on flat land or in valleys.

The VDI (Village Accountability Index) analysis was constructed by combining various dimensions that represent village accountability, including: (i) presence of regulations, (ii) media publications, (iii) media data documentation, (iv) information systems, (v) human resources, and (vi) types of information disseminated by the village government to its community. This supplementary test aims to offer insights into the factors influencing each of these dimensions. The results are presented in Table 7.

Table 7. Additional testing results of the effect of variable of village accountability dimensions on village development

Variable	Model-3A (REGULATIONS)	Model-3B (MEDIA)	Model-3C (DOC)	Model-3D (HR)	Model-3E (SYSTEM)	Model-3F (INFORMATION)
Cons.	− 1.035 (0.019)	− 1.000 (0.0 25)	− 1.075 (0.018)	−0.889 (0.001)	−0.903 (0.000)	−0.896 (0.001)
FUNDING	0.078*** (0.000)	0.077*** (0. 000)	0.070*** (0.000)	0.072*** (0.000)	0.072*** (0.000)	0.072*** (0.000)
ACCOUNTS	0.012*** (0.005)	0.007** (0.018)	0.008 (0.161)	0.003 (0.215)	0.002 (0.510)	−0.000 (0.970)
ASSISTANCE	0.004 (0.699)	0.005 (0.593)	0.006 (0.509)	0.007 (0.490)	0.007 (0.468)	0.008 (0.463)
TOPOGRAPHY	0.024*** (0.001)	0.015** (0.028)	0.020*** (0.005)	0.020*** (0.005)	0.022*** (0.002)	0.021*** (0.008)
Obs.	303	303	303	303	303	303
Prob > F	0.0000	0.0000	0.000 1	0.0000	0.0000	0.0000
R-squared	0.0963	0.0904	0. 0884	0.1418	0.1397	0.1383

***,**,* = Significant P-value 1%, 5%, 10%.

Source: Data processed, 2022.

Table 7 presents the results of assessing the influence of each dimension of the village accountability variable. The findings indicate that both the accountability mechanisms’ regulations and the media publications provided by the village government have an impact on village development. This aligns with the confirmation by Lauwo et al. (2022) regarding the necessity of policies governing accountability mechanisms at the local level, regulated by each village government. Such accountability mechanisms need to be aligned with the potential and expected socio-economic outcomes in rural environments (Vasstrøm & Normann, 2019), ensuring that stakeholders can realize accountability in the implementation of development programs in rural areas. Moreover, the findings suggest that the presence of village-owned websites, social media, bulletin boards, and billboards is crucial in supporting rural development. This emphasizes the importance of publication media to enable rural communities and other stakeholders to access comprehensive information about the implementation of development programs in villages. Encouraging village community participation in implementing plans, social activities, and economic investments in villages can lead to the achievement of dimensions of village sustainable development, as emphasized by Sabet and Khaksar (2020). On the other hand, the findings indicate that the documentation of media, human resources, information systems, and types of information, concerning village accountability mechanisms, does not significantly influence village development. This concurs with Antlöv et al. (2016), who also demonstrated the ineffectiveness in the capacity of human resources in producing village financial reports and utilizing the resulting information.

Rural development, as well as public accountability, is a multi-faceted concept (Douglas, 2005), with various dimensions to be considered (Bovens, 2007; Mulgan, 2000). To successfully achieve the SDGs at the grassroots level, it is crucial to identify numerous factors that play significant roles. Key considerations include the commitment of the national government, collaboration among stakeholders, financial resource support, institutional and governance structures, and accountability mechanisms (Abhayawansa et al., 2021; Bowen et al., 2017; Hickmann et al., 2022; Lauwo et al., 2022). Therefore, it is essential to gain a deeper understanding of the connections between village accountability and village development, as well as the determinants of achieving SDGs, to develop more effective strategies for supporting development implementation and the attainment of SDGs in rural areas.

5. Conclusion

The study’s results provide empirical evidence of the relationship between government incentives and village accountability in the context of village development and the achievement of SDGs in rural Indonesia. The findings demonstrate that the funding incentives provided by the Indonesian government through village funds have positively influenced village development, particularly in the economic and environmental aspects. Although their impact on social development in rural areas is not yet fully effective, this finding underscores the importance of developing a strategy to enhance the financial capacity of village governments. The study suggests mechanisms to accelerate rural development, which involves increasing the capacity of village financial resources by fostering innovation and creativity among government and village communities. Moreover, enhancing supporting infrastructure is crucial to promote mobility and economic activity in rural regions. Lastly, the findings highlight the need for governance to improve the financing capability of villages to support their development programs.

The findings also reveal that the average villages in the sample are classified as developing villages and are predominantly situated on mountain slopes. The study revealed that village topography significantly influences variations in village development, indicating an uneven distribution of development across Indonesia. The results indicated that the ineffectiveness of village assistants in supporting and promoting development initiatives in rural areas contributes to this disparity. Consequently, the findings underscore the importance of developing a strategy to achieve SDGs indicators in rural contexts. This strategy should involve encouraging, facilitating, and regulating the participation and collaboration of external stakeholders, such as universities, non-governmental organizations, and the private sector, in rural development, particularly in villages located on mountain tops or slopes.

The primary limitation of this study lies in the measurement of village development, which does not encompass all SDGs indicators in the rural context comprehensively. Nonetheless, the findings have important implications for village development strategies and the achievement of SDGs indicators in rural Indonesia. To align with the Indonesian government’s efforts to promote equitable village development and achieve SDGs indicators in rural areas, both the National Government and Regional Governments in Indonesia must prioritize strengthening the financial capacity of villages. Additionally, they should actively encourage and facilitate the implementation of accountability mechanisms at the local level.

Acknowledgments

The authors would like to express their gratitude to the Ministry of Education, Culture, Research and Technology of the Republic of Indonesia for funding this research through the 2022 National Competitive Basic Research Grant (PDKN). Additionally, the authors extend their thanks to the Center for Sustainable Governance Studies, Faculty of Economics and Business, Tadulako University.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Andi Chairil Furqan

Andi Chairil Furqan - is a lecturer in accounting at the Faculty of Economics and Business, Universitas Tadulako, Palu, Central Sulawesi, Indonesia. His research interests are on accounting studies, public sector accounting, and local government.

Abdul Kahar

Abdul Kahar - is a Senior lecturer in accounting at the Faculty of Economics and Business, Universitas Tadulako, Palu, Central Sulawesi, Indonesia. His research interests are on auditing; corporate social responsibility (CSR), and public sector accounting.

Rahma Masdar

Rahma Masdar - is a lecturer in accounting at the Faculty of Economics and Business, Universitas Tadulako, Palu, Central Sulawesi, Indonesia. Her research interest is on public sector accounting.

Cinda Andriana

Cinda Andriana - is a student at the Faculty of Economics and Business, Universitas Tadulako, Palu, Central Sulawesi, Indonesia.

Fatiah Rahmaniyah

Fatiah Rahmaniyah - is a student at the Faculty of Economics and Business, Universitas Tadulako, Palu, Central Sulawesi, Indonesia.

Risma Risma

Risma Risma - is a student at the Faculty of Economics and Business, Universitas Tadulako, Palu, Central Sulawesi, Indonesia