Socio Economic Profile of Househohold Consumers in Mizoram: India

The Socio economic Characteristics of Household Customers in Mizoram 2. 1 Introduction Consumer Behaviour, being the psychological dimension of marketing management, is based on various factors. Since all of us are consumers, what we buy, how we buy, where and when we buy, in how much quantity we buy depends on our perception, self concept, social and cultural background and our age and family cycle, our attitudes, beliefs, values, motivation, personality, social class and many other factors that are both internal and external to us (Mark ES and Armen T, 1985).
This is very evident in India, the second most populous nation in the world and the number one contributor to the world’s population growth of potential customers (Population Reference Bureau, 2000). Traditionally, marketers have often relied on intuition and demographic information such as age, sex, income level and occupation for identifying potential areas (Dash PK and Sarangi M, 2008). According to Sproles and Kendall (1986, p. 67), identification of these characteristics among the consumers helps to profile (individual) consumer style, educate consumers about their specific decision-making characteristics, and counsel families on financial management. Again, many research studies show that consumer profiles are crucial as it deals with the mental orientation of consumers in making decisions (Wells, 1975; Lastovicka, 1982; Westbrook and Black, 1985; Sproles and Sproles, 1990; Stone, 1954; Darden and Moschis, 1976).
The important effects of demographic, socioeconomic and regional factor have been demonstrated by various studies in consumers’ choice of foreign and domestic products, or rather ethnocentrism too (Sharma, 1995; Klien, 1998 and Elliot 2003). In the present chapter, it is intended to highlight who the Mizoram household consumers are on the basis of their demographic and socioeconomic profile. 2. 2 Profile of the household customers Taking household customers as sample units, the households are sampled from urban and rural areas. All the eight (8) functioning districts are taken into consideration for the study.

For the research, all the district headquarters, namely, Aizawl, Champhai, Kolasib, Lawngtlai, Lunglei, Mamit, Saiha and Serchhip are taken as urban samples. The rural samples are taken from the following villages/towns – Saitual and Aibawk from Aizawl district, Khawbung and Khawzawl from Champhai district, Bilkhawthlir and Vairengte from Kolasib district, Chawngte and Diltlang from Lawngtlai district, Hnahthial and Zobawk from Lunglei district, Rawpuichhip and Kawrthah from Mamit district, Tuipang and Sangau from Saiha district and N. Vanlaiphai and Thenzawl from Serchhip District. 0 households are sampled from the district headquarters for the urban sample and 20 households from each of the villages/towns mentioned for the rural population sample, making it 40 rural households for every district. In all, 640 households i. e. 80 households from each districts, 40 from urban areas and 40 from rural areas are sampled to cover the whole State. The profiling of households is done, with suitable modifications and necessary adjustments in accordance to Splores and Kendall’s Consumer Styles Inventory model (Splores and Kendall, 1986).
Following Leon GS and Leslie LK’s demographic segmentation, the sample is studied on the basis of the education level, main occupation, family size, composition of the households in terms of number of adults, children, male and female members, range of income, number of earning members in a household and lastly, the type of durable products owned by household customers. Analysis is done using F-Test and Pearson Correlation to find out the relationship between rural and urban population for each of the demographic variables. F-Test analysis tests to see whether two population variances equal each other.
Essentially, the analysis compares the ratio of two variances. The assumption is that if the variance is equal, the ratio of the variances should be equal to 1. Variance may be defined as the square of standard deviation, standard deviation being the dispersion about the data set’s mean (Stephen L. Nelson, 2007). Standard deviation is calculated using the formula: ? = v? fd2x/N – [? fdx/N]2 and variance will be ? 2 (Mohan Singhal, 1999) Pearson Correlation is used to determine the relationship between the two set of data ‘x’ and ‘y’ viz. rban and rural population. The formula for finding out the correlation ‘r’ can be noted using the formula: rxy = N? fxy-? fx.? fy/v[N? fx2-(? fx)2][N? fy2-(? fy)2] The output will be between -1 to +1. Positive value signifies positive correlation i. e. both the data sets move in same direction while negative value signifies negative correlation i. e. the two data sets move in different direction (Lokesh Koul, 2009). The purpose of using F Test is to determine the homogeneity of the two sets i. e. rural and urban household customers. Correlation Analysis is sed to find out the nature and degree of relationship between the rural and urban household customers for each of the socio economic variables. 2. 2. 1Education According to Harold H. Kassarjian (1971), education, like other personal qualities including sex, income, family cycle and so on, play an important role in influencing the buying behaviour. The respondents who represented their households were broadly classified into illiterates, literates, Below Class 10, Class 10, college drop-outs, graduates and post graduates on the basis of their education level and are represented in Exhibit 1.
Exhibit 1: Educational profile of household respondents Table 1: Education level of rural and urban respondents Number of household customers Education LevelRuralUrban Illiterates5 (1. 56)4 (1. 25) Literates70 (21. 88)21 (6. 56) Below class 1071 (22. 19)41 (12. 81) Class 1080 (25. 00)61 (19. 06) College drop outs30 (9. 38)32 (10. 00) Graduates51 (15. 94)105 (32. 81) Post graduates13 (4. 06)56 (17. 50) Total320320 Note: Figures in parenthesis are percentages. Taking into account the responses of rural and urban respondents as shown in Table 1, the outcome F-test value tallied to 0. 840913.
This shows a high degree of similarity in the variances of the two sets, indicating homogeneity in composition between the two sets of respondents. The Pearsonian Correlation gave an output of 0. 287853, a positive relationship between rural and urban. Even though there is a high degree of homogeneity between the two sets of samples, the relationship between the same set is not very strong when introducing Correlation Analysis. According to Census India 2001, Mizoram stood as one of the leaders in the field of literacy. With 88. 48% rate of literacy, Mizoram came in second next to Kerala.
This rationale is reflected in the study as Table 1 indicated that only 1. 41% of the household respondents are illiterates. Even though there is not much difference between rural and urban respondents in respect of illiterates, the rural sample shows that majority of the rural households have passed class 10 i. e. 25% of the 320 rural households, while the majority of the urban households are graduates with 32. 81% of the 320 urban households. Although there is a rather significant gap in the level of education between rural and urban samples, it is interesting to note that rural households do have access to higher education. . 38% are college drop outs, 15. 94% are graduates and 4. 06% of the rural households hold post graduate degrees. That makes 29. 38% of the rural households have exposure to collegiate environment and thus, to urban lifestyle as all of the 22 colleges including Law Colleges are established in urban areas i. e. district headquarters (Statistical Handbook, 2008). 2. 2. 2 Occupation According to the Statistical Handbook (2008) published by the Government of Mizoram, agriculture and its allied sectors have a declining figures in terms of Gross State Domestic Product (GSDP) for the past years from 2005-06 till 2007-08.
Further decline is expected from the quick estimate made by the Department. One factor so stated in the Handbook being the mautam famine. This may also result in change of occupation from agriculture to other sectors to ensure livelihood. On the other hand, the State saw the incubation of private corporates in the form of insurance companies, banking companies and other private societies. Various private banking companies like Axis Bank, Syndicate, Central Bank of India, Bank of Baroda, Punjab National Bank, IDBI, have started their branch offices in Mizoram bringing about employment opportunities for educated youths (see Table 7. , Statistical Handbook 2008). At the same time, private insurance companies mushroomed in Mizoram from the past five years. According to the Taxation Department , companies like Birla Sunlife, Tata-AIG, Bajaj-Alliance, Reliance etc. have started their ventures in Mizoram, again opening employment for the sons-of-the-soil. With the fast advent of mobile-telecom industry in Mizoram since mid-2003, companies like Airtel, Reliance, Aircel, Tata-Indicom, Vodafone began employing mizo youths as their operational staffs. Even then, the largest employing organization is the State Government.
According to the 5th Economic Census 2005 , the State Government accounted for 85% of employment in the State with 40,603 posts under its umbrella. In fact, the up-gradation data as on 2006 showed 51,070 employees including muster-rolls and work-charges. Purchase involvement and consumer behaviour is greatly influenced by the occupation of the household consumers (Harold H. Kassarjian, 1971). Therefore, the study categorise the sample households as Agriculture, Carpentry and Skilled Workers, Daily Wage Earner, Government Employed, Private Company Employed and Business or Own Enterprise.
Exhibit 2 shows the profile of occupations of the respondents. Exhibit 2: Occupation profile of household respondents Table 2: Occupation of rural and urban respondents Number of household customers OccupationRuralUrban Agriculture81 (25. 31)3 (0. 94) Carpentry and Skilled Workers31 (9. 69)9 (2. 81) Daily wage earner40 (12. 50)32 (10) Government Employed99 (30. 94)223 (69. 69) Private Company employed3 (0. 94)19 (5. 94) Business66 (20. 63)34 (10. 63) Total320320 Note: Figures in parenthesis are percentages Applying F-test, the relationship of rural and urban sample variances is calculated as 0. 79742, a low degree of homogeneity in terms of their variance ratio. Table 2 shows that rural households are more evenly distributed in terms of different occupations than their urban counterparts. But then, the correlation degree gave a rather high positive correlation of 0. 69526. This may be due to the fact that the highest frequencies of both rural and urban households are government employed. Agriculture is still an important occupation for the rural households, claiming more than 1/4th of the whole rural households while agriculture is quite negligible for the urban population as an occupation.
One indication that private companies are yet to penetrate the rural areas is the negligible employment by private companies in rural areas. Rural savings and insurance can yet still be tapped by private company players. Since 2005, National Rural Employment Guarantee Act/ Scheme began enhancing the purchasing power of the rural households. Moreover, this particular wage employment scheme encourages savings and personal insurance for the rural households . Rs. 39,500 crores will be pumped into the rural areas nation-wide in the year 2009-10 under this scheme.
This can be an opportunity as the rural consumers constitute more than 75% of the Indian population and out of the 1. 61 lakhs household in Mizoram, rural areas account for almost half of the whole population of the State (The Marketing Whitebook, 2005). Own enterprise or business constitute a significant proportion of households in the rural sample, again an indication of good business opportunity for rural banking. The overall tabulation shows that 50% of the whole sample population are government employed, signifying a large business pool with secured incomes for marketers. . 2. 3 Family size As the primary consumer decision making unit, the family has been the subject of intense examination for a number of years (Lakshmi PV and Murugan MS, 2008). Family may be regarded as one of the strongest source of influence on consumer behaviour, its size being the significant determinant (Matin Khan, 2006). As the core unit of defining culture, family has a very prominent effect on attitude formation in various facets of marketing (Burke, 2002; Wood, 2002). It may be held true that the family size matters in household consumer behaviour.
The larger the family, the larger its consumption needs and wants. Product preferences also depend a lot on the household size (Srivastava KK and Sujata K, 2008). Exhibit 3 gives the overview family size of the household respondents. Exhibit 3: Family size profile of the household respondents Table 3: Family size of the rural and urban respondents Number of household customers Number of family membersRuralUrban Upto 211 (3. 44)22 (6. 88) 3 – 5152 (47. 50)154 (48. 13) 6 – 8133 (41. 56)138 (43. 13) 9 and above24 (7. 50)6 (1. 88) Total320320 Note: Figures in parenthesis are percentages
Exhibit 3 shows that about 47% of households are bigger families with 6 or more members and Table 3 indicated that the number of families with membership of 9 and above is four times more in rural areas than in urban areas. According to the 2001 Census, the average size of scheduled tribe households in the rural areas was 5. 2 members while in urban areas it was 4. 9 members. It should be noted that the two family sizes viz. 3 to 5 members and 6 to 8 members together accounted for 89. 06% of the rural respondents and 91. 26% of their urban counterparts.
Taking the family sizes 3 to 5 and 6 to 8, the median size lies between 5 and 6 member-households. This indicates the similarity of the households studied with that of the Census 2001 figures . The F-Test shows a very high degree of 0. 932141, indicating high homogeneity between the rural and urban respondents. Further application of Correlation Analysis gave the value of 0. 987285, demonstrating a very high level of relationship between the rural and urban customer households. Hence, both the tests show that there is not much difference between the rural and urban households in respect to family size.
India, for several decades, have been involved in defining family size, in fact, one of the earliest nation to be concerned with the issue . Decadal studies show that there has been a marginal decrease in family size from 5. 5 in 1980s to 5. 3 in 2001 even though there is a very significant increase in population during 1980 and 2001 from 493,757 to 888,573 . This is an indication of growing nuclearization of families in the Indian society as stated in Census India Report and an indication of mass education and media awareness of the general population demonstrated in the decrease of family size, an after-effect of family planning. . 2. 4 Age Product needs and interests vary with the age of the customers (Srivastava KK and Sujata K, 2008). Obviously then, different age groups present different marketing challenges and opportunities. Marketers thus have found age to be a particularly useful demographic variable for distinguishing segments (Elliot et al, 2003). Table 4 shows the number of adults in both rural and urban households. Table 4: Number of adults Number of household customers Number of adultsRuralUrbanTotal Upto 2102 (31. 88)104 (32. 50)206 (32. 19) 3 – 5146 (45. 63)171 (53. 44)317 (49. 53) 6 – 871 (22. 19)41 (12. 81)112 (17. 50) 9 and above1 0. 31)4 (1. 25)5 0. 78) Total320320640 Note: Figures in parenthesis are percentages The output value of F Test gave a significantly high 0. 768617 showing the similarity between the rural and urban household customers in respect of the adult population. A correlation degree of positive . 959861 also indicates that there is a very high positive relationship between the two samples. Almost 50% of the households have 3 to 5 adult members. About 22% of the households in rural Mizoram have the adult population of 6 to 8 members, whereas only 13% of the households in urban Mizoram have the same number of adult population.
It is already demonstrated in Table 3 that the median household size of the samples is between 5 to 6 members. Therefore, it can be stated that the majority of households are adult-dominated. As for the children population, the rural and urban households are studied of its child members, categorizing them in 2 subsets, below 14 years of age and between 14 to 18 years of age. Table 5: Number of children below 14 years Number of household customers Number of children below 14 yearsRuralUrbanTotal Upto 2112 (35)94 (29. 38)206 (32. 19) 3 – 566 (20. 63)78 (24. 38)144 (22. ) 6 – 820 (6. 25)16 (5)36 (5. 63) 9 and above01 (0. 31)1 (0. 16) Total198189387 Note: Figures in parenthesis are percentages Of the 320 rural households, 198 households have family members below 14 years and out of 320 urban households, 189 households have family members between 14 to 18 years of age. Table 6: Number of children between 14 to 18 years Number of household consumers Number of children between 14 to 18 yearsRuralUrbanTotal Less than 255 (10. 94)76 (23. 75)131 (20. 47) 3 – 559 (18. 44)42 (13. 13)101 (15. 78) 6 – 88 (2. 5)12 (3. 75)20 (3. 13) More than 90 (0. 31)1 (0. 16) Total122131253 Note: Figures in parenthesis are percentages Out of the 320 rural households, 122 households have family members between 14 to 18 years of age. Out of the 320 urban households, 131 households have family members between 14 to 18 years of age. The distinction of the children population into the 2 subsets is to segment the consumption needs and wants (Srivastava KK and Sujata K, 2008) Analysis of the rural and urban respondents with children below 14 years gave F-test value of 0. 884167 and a correlation coefficient of . 970224.
These results showed the close relationship between the two samples. Again, rural households and urban households with children between 14 to 18 years gave an F-test output of 0. 888851 and a correlation coefficient of . 886998, showing a positive relationship between the samples. This again shows that there is not much difference between the rural and urban household customers. A significant finding from the two subset tables is that most of the households in both rural and urban areas have the highest frequency in the least number of children in its family members i. . not more than 2 in the household, followed by 3 to 5 children in a household. While most of the households have 3 to 5 adults, most of the households have less than 2 members classified as children. This clearly demonstrated that most of the households are in the family stages known as Full Nest II and III . 2. 2. 5 Income Income is, perhaps the single factor which significantly define the consumer behaviour of households. In fact, much of the other demographic characteristics like education, family size, and culture depend largely on the income of the households.
Even the economic environment depends on the household’s income and as Philip Kotler (2006) stated, “In the economic arena, marketers need to focus on income distribution”. Income is one of the important determinants which have a strong positive influence on the ownership of durables (Bijaya KP and Siba PP, 2008) and even preference pattern of consumable products largely depend upon the income distribution of the households (Prashanta KD and Minaketan S, 2008).
Several studies show that income, as a demographic factor, has a significant effect on purchasing styles even on the internet (Marakas GM, Yi MY and Johnson RD, 2002; Ratchford et al, 2001; Wood, 2002). The income range of the household respondents is illustrated in Exhibit 4. Exhibit 4: Income profile of household respondents Table 7: Income range of the rural and urban respondents Number of household customers Income RangeRuralUrban 2000019 (5. 94)87 (27. 19) Total320320 Note: Figures in parenthesis are percentages Taking the values given in Table 7, F-Test Analysis for the rural and urban households gave an output 0. 5093 while the Correlation Analysis gave a low positive relation degree of 0. 06. This shows that the income range distribution between rural and urban are rather loosely related, compared to other socio-economic factors already studied. In the rural sample, households with monthly income of Rs. 10,001 to 15,000 has the largest percentage, while the urban sample showed that households with more than 20,000 has the highest percentage. This may be due to the fact that the main occupation of the urban households is government jobs.
Even though the largest percentage of the rural households is government employed, a very significant portion of the rural households are engaging in agriculture (see Table 2). Another factor may be the fact that higher paying government jobs are mostly within the urban areas. According to Lalit Kumar Jha (1997), the overall average household income of Mizoram State is Rs. 10,026 per month. This income range is reflected in the total household samples with 21. 09% as the highest percentage, showing the whole household sample is the sub-set of the State population. 2. 2. 6 Earning Members
The phenomenon of ‘double income’ has been identified as a sociologically relevant variable which may affect lifestyles of households (Srivastava KK and Sujata K, 2008). Michman R (1980) identified the multiplicity of income sources of households as an important market sub-segmentation as the purchasing capacity and involvement is much more dynamic. Recently, new segment has been identified and targeted as DINK or Double Income No Kids. An interesting survey by the Associated Chamber of Commerce & Industry of India (2008) on “Changing Consumption Patterns of Delhi” shows that DINKs are high spenders .
The survey states that households DINKS spend more of their resources on luxurious lifestyles while their counterparts, double income-with kids’ households spend most of their incomes on child education, healthcare, insurance and home making, making the study of income source pattern a crucial issue for marketers. The number of earning members per households is presented in Exhibit 5 Exhibit 5: Earning members profile of household respondents Table 8: Number of earning members in rural and urban households Number of household consumers No. of Earning Member(s)RuralUrban 1248 (77. 5)141 (44. 06) 263 (19. 69)137 (42. 81) 39 2. 81)42 (13. 13) Total320320 Note: Figures in parenthesis are percentages Table 9 depicts a rather unrelated distribution of number of households for rural and urban areas. Even though F-test Analysis gave a rather low homogeneity between rural and urban households with a degree of 0. 33318, Correlation Analysis gave a significant positive relationship of 0. 700723. This shows that even though there is a rather large disparity between the means of rural and urban households, their relationship cannot be ignored. The study shows that most of the rural households have only one earning member in its households, claiming 77. 0% of the whole sample while the urban households have a very prominent proportion of two earning member households claiming 42. 81% of the urban sample, a close second to households with only one earning member. The number of earning members of rural and urban households can be co-related with the income ranges of rural and urban households. Table 7 showed that the average income range of urban households is relatively higher than rural households and Table 8 indicated that households with two earning members are quite higher in urban samples. . 2. 7 Durable products owned ORG-Gfk Year-End Reviews (2004) states that the Indian consumer durable industry is estimated at around Rs. 200 billion and growing. The healthy growth of durables market can be an offset of various factors like fragmentation of households into double-income nuclear families to the presence of easier finance options; expansion of dealer networks and after-sales services (Marketer Whitebook, 2005). In fact, durable products account for 6. 6% of yearly purchases of Indian households (Arvind Singhal, 2001).
According to the information given in The Marketer Whitebook (2005) 42% of all households owned radios, 20. 4% owned television, 14. 1% owned telephone, 3. 1% owned bicycle, 6. 2% owned motorized 2-wheelers, 3. 4% owned cars and 50. 9% owned unspecified durables in Mizoram. The profile of durable products owned by the households determine various dimensions of consumer behaviour, namely, purchase preference, product penetration, support purchase for already owned durables, marketing opportunities and so on. Exhibit 6 gives an overview to the ownership of durable products by the household respondents.
Exhibit 6: Durable products profile of the household respondents Number of households Table 10: Durable products owned by rural and respondents Number of household customers RuralUrban Radio205 (64. 06)182 (56. 87) LPG209 (65. 31)315 (98. 43) Music system107 (33. 43)179 (55. 93) Television218 (68. 13)308 (96. 25) Fridge189 (59. 06)306 (95. 63) Oven15 (4. 68)65 (20. 31) Washing machine125 (39. 06)210 (65. 62) Telephone135 (42. 18)289 (90. 31) Mobile233 (72. 81)300 (93. 75) Computer48 (15)187 (58. 43) Scooter42 (13. 12)18 (5. 62) Bike31 (9. 68)112 (35) Car19 (5. 93)119 (37. 18)
Note: Figures in parenthesis are percentages From Table 9, the most owned durables by rural and urban household respondents can be ranked and represented in Table 10. Table 10: Ranking of most owned durable products Ranks 12345 RuralMobileTelevisionLPGRadioFridge UrbanLPGTelevisionFridgeMobileTelephone OverallLPGMobileTelevisionFridgeTelephone Durable products are independent to factors like access to electricity, availability of LPG suppliers and petrol pumps. According to the Statistical Handbook (2008), there are 24 LPG authorised dealers, each district having at least one dealer.
There are 18 petrol pumps all over the State and every district except Mamit district has at least one recognised petrol pump. As for electrification, 570 villages have already been electrified, accounting for around 70% of the State accessing to electricity, 44. 1% of the rural households and 94. 4% of the urban households reported as electrified. According to the Taxation Department Report, mobile phone came in use only from 2003 that too started only with BSNL giving out 500 subscriptions. Till October 2008, there is a total of 2,85,287 subscribers with BSNL, Airtel, Reliance and Aircel.
This information does not take into consideration the entry of Tata-Indicom and Vodaphone service providers. Out of the 320 respondents from rural households, 233 households (i. e. 72. 81%) own mobile phones. Various factors can come into play here, the competitive and aggressive participation of mobile service providers in the rapid and widespread penetration of both rural and urban areas being one of the major factors, competing and overtaking at some places in the once monopoly of the state-owned BSNL. About 29 recognised cable TV operators operating in urban and semi-urban areas gave monthly subscription to consumers since 1991 .
Apart from these operators, private dish antennas are made available by Zee Group (Dish Tv) at affordable prices below Rs. 2,000 . This may be one of the main reasons that television is very popular in both the rural and urban areas, claiming 68. 13% of rural households and 96. 25% of urban households owned television set. It is interesting to see that even some unelectrified villages have solar powered television with dish antennas besides the thatched huts . LPG is considered household necessity for the urban households with 98. 43% of urban samples having access to LPG.
Yet, it came as the third most owned durable product in the rural areas. A prominent factor may be the easy accessibility to the LPG dealers. Aizawl has 11 LPG agents within its district, Lunglei with 4 agencies, Kolasib with 3 agencies, Champhai with 2 agencies and Lawngtlai, Mamit, Serchhip and Saiha with 1 agency each. Other factors may be the price of LPG cylinders and uncertainty of supply even at the agencies. Even though radio continues to be the most extensive network covering the entire State , its popularity is confined mostly to the rural areas, accounting for 64. 06% of rural households and 56. 7% of urban households of the sample. Advance of other electronic media, like cable television network and Doordarshan, maybe one of the main reasons. Fridge ownership accounted for 59. 06% of rural households and 95. 63% of urban households. As large number of rural households are agrarian based, they can be assumed to have easy access to fresh vegetables as compared to the urban households. The main utility of fridge being storing of food, thus is more popular in the urban areas. As for telephone, 90. 31% of the urban households have telephone connection while 42. 18% of rural households accounted for telephone connection.

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