Spatial Pattern of Multi-dimensional Regional Disparities in the Level of Socio-economic Development in West Bengal: A Geographical Analysis

Micro-level spatial analysis of the different phenomenon duly associated with human development and also with the wellbeing of a nation. The study is a heart-core attempt to examine the inter-block regional disparity and development by constructing a multidimensional approach-based index. The study used thirty-four sub-dimensional variables under the five dimensions, including health, education, economy, socio-demography, and transport. The article used the data of the district statistical handbook of 2013 and census data of 2011. The empirical results of the study confirm the existence of huge inter-regional disparity on multi-dimensional developmental aspects, which drastically hampers the allround growth and socio-economic development of Jalpaiguri Administrative Dvision (JAD) of West Bengal. The blocks of Khairabari, Darjeeling-Pulbazar, Rngli-rangit, Mirik, Kurseong, Kalimpong I & II are found to be high regional imbalances in the development of education, health, employment, and economy. The study also helps to identify the most backward blocks. It confirms the huge inter-block/district disparities in West Bengal. The study argued that the low developed and high disparities blocks require special attention from policymakers in order to the improvement of overall socio-economic development of the study area.


Introduction
Regional disparities at the micro-level hamper the developmental process and minimize the scope of national growth on large (Braveman, 2014;Ohlan, 2013). Regional disparities have been closely linked with the development and influence the factors of economy and policy formation (Novkovska, 2017). The work of Novkovska (2017) found that hidden economic growth substantially influences the development and stretches the interregional gap of developmental factors. Regional disparity defines as an unequal spatial 76

Study Area
The proposed study measured the spatial pattern of micro-regional disparity and development perspective of Jalpaiguri Administrative Division (JAD), one of the least developed parts of West Bengal. It lies on the foothills of the Himalayas, and the major part of the JAD is drained by several small rivers and tributaries of river Ganga and Brahmaputra like, Tista, Mahanada, Jaldhaka, and Karala. The river Tista originated from Sikkim Himalaya, flows southwards. After entering West Bengal, it cut down the JAD into two parts.
The left bank is popularly known as Dooars, and the right bank is known as Tarai. Moreover, the major portion of JAD's economy is fed up by the tourism industry's revenue. It is a famous tourist destination (Darjeeling, Kalimpong, Mirik, Dooars and so on), mainly famous for hill stations, dense forests, and wildlife. The JAD shares international boundaries with Bhutan in the north, Bangladesh in the south, and Nepal in the West. The previous studies demonstrated that the population of the region is lived with the least socio-economic development and low capacity of livelihood diversification (Barman, 2020;Sam & Chakma, 2016;Sarkar, 2017). Moreover, the nature of deprivations is similar to that of the other region of India. However, limited research has been conducted to depict the micro-level (interblock) scenario, which is an important criterion for policy formation.
Presently, JAD is comprised of five districts, i.e., Darjeeling (9 blocks), Kalimpong (3 blocks), Jalpaiguri (7 blocks), Alipurduar (6 blocks), and Cooch Behar (12 blocks). In 2014 the Alipurduar district was separated from Jalpaiguri, and in 2017 the Kalimpong district was separated from Darjeeling district. The demographic attributes and location of 37 blocks illustrate in Table 1 and Figure. (Table 1). As per the 2011 Census, the region has a literacy rate of about 72.41 percent, which is lower than the state average literacy rate of 77.08 percent. In addition, the gender gap in literacy of JAD is recorded as 14.61, which is much higher than the state, i.e., 11.51. Around 20 percent of people of JAD are living below the poverty line. Here, 22.5 percent population from Cooch Behar, 22.1 percent from Jalpaiguri, and 14.7 percent population from Darjeeling belong to the below poverty line (Bhandari & Chakraborty, 2015). It indicates that the people of JAD are regularly countered several vulnerabilities to run their livelihood and to facing difficulties in access of the basic necessary items for quality life, namely, quality education, earning, food security, and health care facilities.

Data Source
The study is a definite attempt to identify the spatial pattern of regional imbalances, examine the aspects of micro-level regional development.

Selection of Indicators
Multi-dimensional indicator selection produces a comprehensive summary of various developmental aspects of a region. Likewise, social indicators variably represent the social growth of a region (Kumar & Rani, 2019). Drewnowski (1972) indicates to use quantifiable and measurable variables to understand the inheritance scenario of socio-economic wellbeing and needs of the people altogether. The indicators also ascertain the developmental perspective of a region (Ohlan, 2013).
In the study, selected five dimensions, i.e., Socio-demography, Health, Education, Employment and economy, transport. The five dimensions included thirty-four subdimension variables ( Table 2). The selected indicators may be positively or negatively influence the developmental process of a region. For example, increasing road length, family welfare centers, hospitals positively stimulate the regions development and helps in achieving the wellbeing targets of the population. In contrast, high population density, a pupil-teacher ratio at a different level of schooling negatively triggered the development. To comprehend the inter-block spatial pattern of multi-criteria-based disparities and developmental stages of the Jalpaiguri administrative division, selected indicators (for the latest and availability of data) summarizes in Table 2.
Note: Parentheses represent the symbol of selected dimensions and sub-dimensions; *the conjectural relation assuming in increasing trend, the adopted variables essentially modified as per the requirement of the study and availability of block level data.

Data Analysis
There is no universal methodology to examine the disparity and development of a region. The different studies used different methods and included diversified variables to measure the extent of regional disparity. Further, most used methods included weighted and unweight Aggregation methods, factor analysis, Principle Component Analysis, Ranking aggregation, Monetary index, Wroclaw taxonomic method (Kumar & Rani, 2019;Ohlan, 2013). The steps of multi-dimensional disparity index presented in the schematic diagram and flow chart of Figure 2 and Figure 3. In the first two step, it mainly involved in the identification of variables which has been recognized the multi-criteria based disparity Suranjan Majumder / Geosfera Indonesia 6 (3), 2021, 260-300 measurement. In the third stapes, employed the data standardization methods by using the Eq.
1 & 2. The data standardization is necessary because not each variable measure with the same unit. For example, population density measures per square kilometer, literacy rate measure through percentage, whereas population, pupil-teacher ratio is unitless. The data standardization procedure was first applied by UNDP in the construction of the Human Development Index (Banu & Biswas, 2011). Later, it is widely used in a different fields.
Sh is the unstandardized value of i th row of k variable for block b; Smin and Smax is the minimum and maximum value of k variable; Indexshiis the standardized value which applying in the further calculation.
Here, DIjrepresents five dimensions mentioned in the above discussion; V1ikjb…Vnikjbis the standardized value of i th row of k variable of j dimension of b block.
In the final stage, the five dimensional disparity indices (DIj) aggregated with weighted by applying Eq. 4.
Where the MDIb is the Multi-dimensional vulnerability index for the block b, and WEDU…WTRANS is the weightage of the five major dimensions. The weights are determined by the number of variables employed for each dimension calculation. It ensures that all variable equally represents to the overall index (Adu et al. 2013). Moreover, in analyzing the spatial pattern of regional disparity and development, assigning the weight of indicators Suranjan Majumder / Geosfera Indonesia 6 (3), 2021, 260-300 deliversprecise and comparable results (Pal, 1995).The blocks having the highest index value are termed as highest disparity and least developed and vice versa.

Results and Discussion
The part of results and discussions elaborately addresses regional disparity issues in approaching the multi-dimensional aspects of regional development and its inter-block spatial variability. The mapping of regional disparity helps identify the backward blocks, which concise the task of policymakers in preparing a best-fit development plan. It provides a comprehensive outline of the spatial variability of health, education, economy, socio-demography, and transport infrastructure. Also, it provides an overview of the socioeconomic development of selected parts of JAD.

Health Aspect
Equivalent health infrastructure and healthcare accessibility is the crucial element for the regional development. Healthcare accessibility defines access to health centers and provides better service outcomes (Lakshmi & Sahoo, 2013). Human wellbeing depends on institutional health infrastructure, the availability of doctors and health workers, governance, and logistic support (Banu & Biswas, 2021). In their study, Banu & Biswas (2021) 1986), which hamper the process of regional growth and improvement of human resource.
The disparity existed both in rural and urban areas. However, rural areas are more likely to expouse in front of deprivation incidence than urban areas (Akthar& Izhar, 1986). Health has critically delineated socio-economic stability and human development (Miao & Wu, 2016).
Accessibility of health facilities also spatially varied, which hampered the regional development goal. In the present study, the author attempts to measure the regional disparity in health aspects, including hospitals, availability of doctors, beds availability, family welfare centers, and mortality rate (under five years of age). The index score was categorized into five levels (very low to very high) to examine the regional disparity better. The health index score ranges from 0.048 to 0.580 (Table 3). Table 3 indicates that the block Rangli-rangit has ranked last (0.580)), and the block Coochbehar-I (0.048) has been ranked first in the health disparity index. It has been further observed that the relative variation in health facilities has much higher among the 37 Community Development Blocks of the five districts under the Jalpaiguri Administrative Division ( Figure. 4). Figure 4 indicates that only two blocks, Coochbehar-I and Coochbehar-II, have a very low disparity in selected health variables.
Suranjan Majumder / Geosfera Indonesia 6 (3), 2021, 260-300  (Table 9). The study revealed that most of the blocks from Jalpaiguri and Alipurduar district moderately developed in health infrastructure. The result highlights an imbalanced pattern of development of necessary health infrastructure across the selected study area. For example, the hilly part (Darjeeling district and Kalimpong district) has a very high disparity in the availability of government hospitals, beds, and availability of doctors; whereas, the plain land of Coochbehar, part of Alipurduar, and part of Jalpaiguri district score low to the moderate disparity in health facility development. The primary reason behind this is an unequal and inadequate distribution of hospitals, doctors, primary health care facilities, and necessary logistic support. The cause to maximize the health expenditure of the population, and also they suffer from less accessibility of good health facilities.
It is evident of the developmental profile from the information presented in Table 8.
Seven blocks is low developed, six blocks are low middle developed, twenty blocks is high middle developed, and four blocks is highly developed in terms of health infrastructure as depicted in Table 8. It implies that only a few blocks like Coochbehar-I, Coochbehar-II, Suranjan Majumder / Geosfera Indonesia 6 (3), 2021, 260-300 Dinhata-I, and Rajganj achieved the desired development in the health aspect. However, 35.13 percent of blocks experienced low and low middle development, where the majority of blocks belong to Darjeeling and Kalimpong district. It is a concerning issue for both districts, also hamper the future policy implication. Generally, the lack of hospitals, beds, and doctors in the proportion of the population is alarming for these blocks.

Educational Aspect
Education is a fundamental component of human development (Das, 2018). It also helps a region for the transformation process from underdeveloped to developing. So, the regional disparity in the educational aspect directly influences the variability of regional development at the macro-level. Brandt (1980) stated that educational development is a crucial factor that helps achieve the overall development goal and enhance the capability to transform human resources into human capital.

Figure 5. Inter-block spatial pattern of Educational Disparity Index
Human capital is an essential asset under the assets pentagon of sustainable livelihood (ALC India, 2018). It helps improve the capacity and skills of people, able to diversify the occupational opportunities which reduced the chance of exposure from livelihood vulnerability. Here, vulnerability means joblessness, poverty, a low wage. Education also a significant part of human development (Das, 2018). Therefore, educational infrastructure needs to be equally distributed for inclusive regional development and implementation of smooth governance. The regional gap in the access and opportunities of educational facilities, evident to less developed region as well (Biriescu & Babaita, 2014). The Special school (preprimary, Anganwari) and primary school are the base of educational development in India.
Unequal distribution of school reduces the chance of enrollment of the student. Further, the distance of the school from the house also hampers the growth of a region's human resource, even forcing students to drop their education at an early stage, especially the scenario is worst for female students (Biswas, 2016;Rao & Gupta, 2006).
The persistence inequality of educational facilities across the region coupled with inter-block disparity in education index. The education index ranges from 0.373 to 0.799 (Table 4) Table 9 reveals that in the educational sector, fourteen blocks are found to be very low disparity, covered area of about 40.08 percent and population of 41.17 percent. Twelve blocks with an area of 32.06 percent and a population of 37.92 percent are the low disparity category. The results indicate that spatial variation in the disparity of educational aspects has existed in the study area. Although, the disparity is high in the part of the mountainous blocks due to the physiographic inaccessibility and hindrances.
The educational development is also variably experienced by the selected blocks. The blocks of Darjeeling-Pulbazar, Kalimpong-I, Kalimpong-II, Kurseong, Mirik, Rangli-rangit, and Sukhiapokhri-Jorebunglow experienced low development in the educational dimension (Table 8).

Employment and Economic Aspect
The regional (inter-block) disparities in the employment and economic aspect are examined based on eight indicators (Table 2 and 5).  (Table 9). The results indicate that majority of blocks score high, moderate, and low disparity in EMECO. The moderate and low economic development of the blocks of Darjeeling, Jalpaiguri, and part of Alipurduar and Coochbehar districts is lack of manufacturing industry and more dependence on tea industry and agriculture.
Suranjan Majumder / Geosfera Indonesia 6 (3), 2021, 260-301 As per  (Table 8). This means that majority of the blocks are facing an alarming situation in terms of the development of eight indicators selected in the EMECO dimension. Figure 6. Inter-block spatial pattern of Employment and Economic Disparity Index

Socio-demographic Aspect
The socio-demographic aspect is a combination of social wealth and demographic characteristics. The social wealth included electricity, drinking water, and the proportion of subsidized food availability. The social and demographic phenomenon act as a vital edge for  In the study, the socio-demographic disparity index was prepared based on five subcomponents (Table 2), including population, population density, electricity, drinking water facilities, and fair price shops. The calculated index value ranges from 0.373 to 0.799 (Table   6). The Mirik block has the highest disparity, and Sitai block has the lowest disparity in the socio-demographic disparity index. Tables 6 and 9 indicates most of the blocks have a low disparity in socio-demographic aspect, which covered an area of 48.90 percent and a population of 50.75 percent (Table 9 and Figure 7). Seven and ten blocks fall under the very low and moderate disparity category, respectively. Only the block Darjeeling-phulbazar is a high disparity covered 3.30 percent of the area and 1.72 percent of the population (Table 6 and 9). The Phansidewa block of Darjeeling district observed a very high disparity in the socio-demographic aspect, covered 2.48 percent of the area and 2.77 percent of the population.

Transport Aspect
Transport has to play a critical role in the developmental process within a region. It is obvious that disparities exist between inter-regional levels in terms of the betterment of Suranjan Majumder / Geosfera Indonesia 6 (3), 2021, 260-300 transport and communication facilities. The dimension determines the level of transmission of goods and services (Das, 1999), accelerating the region's growth in a more sophisticated manner. In their studies, Li et al. (2020) found that regional development correlated with the diversifying transport network.

Figure 8. Inter-block spatial pattern of Transport Disparity Index
Here, three sub-dimensional variables have been considered to analyze the inter-block disparities and stages of development in the transport dimension (Table 2). These findings are demonstrated in Table 7 and Figure 8. Table 7 shows that the highest disparity value of transport aspects, i.e., 0.947, is attained by Coochbehar-I, followed by the block Tufanganj-II (0.722), Coochbehar-II (0.718). In contrast, the lowest disparity value is attained by Kalimpong-II, i.e., 0.090. As seen in Figure 8, one block out of Thirty-seven blocks is found to be in the very high disparity category, and twelve blocks are found to be the high disparity category. The very high disparity category covers 2.86 percent of the area and 4.43 percent of the population ( Alipurduar district) are the major tourist destination in West Bengal, share a significant proportion of revenue in the state economy. Further, Shiliguri is a significant business hub and significant transport node connecting entire India with northeast India. The following factors influence the equitable growth of the transport network across the district. However, only the development of transport networks does not provide an overall impact on the overall sustainable and inclusive regional development. 3.6 Spatial pattern of Multi-Dimensional Regional Disparity The Multi-dimensional disparity index (MDI) rank of different CD blocks and overall stage of socio-economic development of 37 blocks of 5 districts under Jalpaiguri division in West Bengal. The MDI includes education, health, socio-demography, employment, and economy and transport, presented in Table 8, and spatial variability illustrated in Figure 9.
The value of MDI varies from 0.384 to 0.571. Moreover, a total of six-block indicate a high distributional disparity of selected dimensions, where five blocks from Darjeeling district and one block from Kalimpong district. The blocks of Darjeeling-phulbazar, Sukihapokhri-jorebunglow, Rangli-rangit, Mirik, Kurseong, and Kalimpong-II are found to be very high disparity (Figure 9). These six blocks covering about 13.04 percent of the area and 7.02 percent of the population (Table 9).  (Table 9). The result indicates that Darjeeling and the newly formed Kalimpong district experienced a very high disparity in the five dimensions. Noteworthy that physiographic unsuitability, political instability, and the absence of major manufacturing industries are the major reason for the limited socio-economic development (Das, 2018). The study also found that the district of Darjeeling and Kalimpong performed better in transport development but experienced high inter and intra-regional disparity in other developmental factors. The results are also backed by the study of Das (2018); Som & Mishra (2016) . The findings of Som & Mishra (2016) illustrate that the northern part of West Bengal facing intense regional disparity caused the extortionate backwardness.

Inter-district Disparity of Multi-Dimensional Development Aspect
This section provides a valid underlying scenario on the inter-dimensional developmental disparity of five districts of the Jalpaiguri division ( Figure 10). It helps to understand the overall issue more effectively. Figure 10 indicates that the district of Cooch Behar is moderately facing inter-dimensional disparity in regional development. However, the performance is worse in economic and transport development. The transport facilities are not relatively improved and equitably distributed to accelerate the growth of the district, which affects the economic growth. It also indicates a tendency of one-sided transport network development where the majority of the blocks of Cooch Behar, Jalpaiguri, and Alipurduar district experienced a lack of railway and bus terminus facility poor condition of roads. However, Darjeeling and Kalimpong district experienced satisfactory development in Suranjan Majumder / Geosfera Indonesia 6 (3), 2021, 260-300 transport network development ( Figure 10). The reason already mentioned in the above discussion. Further, Darjeeling and Kalimpong districts performed very poor in education, economic, and health aspects. The interesting scenario is that all the districts experience relatively equal development in the socio-demographic aspect. This means, sociodemographic factors not highly influenced the overall inter-district development. Moreover, the newly formed district Alipurduar is bitterly performed in all sectors of development compared to its counterparts. found that the greater level of regional disparity has subsisted at national and state levels. The outcome of the present study affirms the previous findings. The study eventually corroborated that regional disparity is commonly found at the micro-level developmental unit in West Bengal. Yousuf et al. (2014) also studied the array of socio-economic development.
In the study, they found inter-district disparity gradually backpedal the regional growth and reduced the course of human wellbeing (Yousuf et al., 2014). The result of Chotia & Rao (2015) indicates that there is a close inter-linkage of economic development with region education, health, transport, energy, and agricultural performance.

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Suranjan Majumder / Geosfera Indonesia 6 (3), 2021, 260-300 They even observed that poverty also emerged as an inference due to higher Intra and inter-regional imbalances in the distribution of infrastructural components. Regions of social growth and economic sustainability are highly acquainted with the sustainable existence of necessary socio-economic indicators (Chotia & Rao, 2015;Dholakia, 2003;Novkovska, 2017;Ohlan, 2013). The study also established that there is high regional variation inhabited in the study area regarding the ordination of educational and health facilities at district and block level.
The findings supported the study of Ahmed & Hussain (2013) . Further, the results confirmed the findings of Sam & Chakma (2016) . The all-round development needs to minimize the relative disparity of all important sectors which directly interlinked with human development. For example, education and health are two critical components of accelerating the developmental process and providing a sustainable environment for human resource development. Furthermore, economy and employment highly depend on educational achievement, skills, training, and quality educational infrastructure. Moreover, the leaning on primary sectors of the economy leads to more prone towards livelihood vulnerability, namely poverty due to the low wage rate, variability of monsoonal rainfall, low productivity, crop damage, and Suranjan Majumder / Geosfera Indonesia 6 (3), 2021, 260-300 290 Suranjan Majumder / Geosfera Indonesia 6 (3), 2021, 260-300 associated lack of infrastructural facilities. It also concretizes the presence of poverty, and low human wellbeing hampers the overall developmental process. Transport build an inter-linkage to all other sector coupled with regional development. Hence, less disparity of interblock transport facilities eases the way to regional development. The table represents a correlation of selected dimensions with the overall regional disparity. The correlation shows Pearson bivariate correlation coefficient between education, health, socio-demography, economy, and employment and transport with MDI (Table 10). The person correlation coefficient indicates multi-dimensional regional disparity means development is strongly positive relation with education dimension, moderate positive relationship with health, socio-demography and economic dimension. However, transport has a very low negative relation with MDI, which indicates transport influences the overall development but in a limited appearance. The correlation coefficient of MDI with education and health is statistically significant with 99 percent (.01) confidence level, and transport is statistically significant with 95 percent (0.05) confidence level. The result further apprises that multi-dimensional regional development is largely influenced by education. The improvement in the educational and public health infrastructure positively influenced the inter-block development pattern and minimized the effect of disparity. The blocks performed better in the achievement of development where the educational infrastructure is quite satisfactory. Thereafter, it is high time to consolidate the quality educational facilities and grass root level health infrastructure, which automatically accelerate regional development.
Suranjan Majumder / Geosfera Indonesia 6 (3), 2021, 260-300  (AEDA, 2013;Das, 1999;Sultana & Aktar, 2016). Socio-economic development categorically manifested by the equitable distribution of resources (Ohlan, 2013;Wailerdsak & Siengthai, 2017) and the compatible environment with the proper influence of regional institutions and governance for its embodiment (Talmaciu, 2014). In this context, a detailed discussion of inclusive resource profile, a brief overview of sociodemographic characteristics facilitates understanding the region's socio-economic development selected for the study. Herein, I am discussing the socio-economic profile of the three major districts. These are-Darjeeling (physiographically mountainous), Jalpaiguri fact is that the Nagrakata block is fully occupied by rural settings. There is no trace of urban characteristics. The block is also concentrated by the scheduled tribe population. Literacy scenario is a concern for Jalpaiguri district. Here, 73.25 percent population are recorded as literate, means able to read and write (Census of India, 2011a). The literacy rate is much lower than the state and national average. The gender gap in literacy is 13.72 (

Conclusion
The blocks of Khairabari, Darjeeling-Pulbazar, Rngli-rangit, Mirik, Kurseong, Kalimpong I & II are found to be high regional imbalances in the development of education, health, employment, and economy. Likewise, the block Coochbehar, it was found to be highly skewed differences in transport development compare to the other counterparts. The engrossing findings is that the blocks situated in high elevation facing low development in all dimension except transport. Because transport is a major way to carried out tourism activities, the people of these blocks predominantly engaged in the tourism related activities to subsist their daily livelihood. In addition to this, the blocks of Darjeeling and Kalimpong district mainly underdeveloped, caused by the physiographic unevenness, landlessness, lack of irrigation facilities, absence of manufacturing industries, closure of tea gardens, the low opportunity of livelihood diversification, and political instability. The Gorkhaland movement, Kamtapuri movement, and Greater Cooch Behar movement are significant cause-effect association with the stagnant regional development in north Bengal. In addition to these, in JAD, the five districts have only one Higher Education University and medical college, which creates huge uncertainty in the access to better healthcare facilities and acquiring quality education. Moreover, it observed that the high disparity district all not facing high disparity in all variables of the selected dimensions. Categorically some variables of a particular dimension are resultant high and/or moderately high levels of disparity. In addition to these, to speed up the development process, the government formed new districts like Kalimpong and Alipurduar, which concisely focused on regional development, enhancing governance, and implementing government schemes and policies. However, for an inclusive regional development purpose, the government should focus on priority-based development with a targeted agenda. Also, the government must ensure the equitable distribution of infrastructural facilities, where the development is slow down.

Conflicts of Interest
The author declares that there is no conflict of interest with any financial, personal, other people or organizations related to the material in this study.