Introduction
Native or indigenous chicken breeds play a pivotal role in rural economies of developing and under developed countries. They are crucial for the rural underprivileged and marginalised groups of the population, not only for providing secondary income but also for supplying eggs and meat for their own sustenance.1-3 These native chickens or yard fowls are produced worldwide, mostly using backyard and free-range systems with little to no suitable housing.4 As native birds do not require additional nutritional or management support to produce eggs or meat when individuals supply their kitchen and household kitchen waste as supplementary feed, rural people prefer raising native chickens over high-yielding exotic or hybrid birds 3,5. Native birds thrive when left to scavenge the owners’ backyards without any assistance 6, ensure rural residents a means of sustaining their way of life and ensuring nutritional security.7,8
India is one of the world’s top producers of poultry meat and eggs, and the consumption across the country predominantly includes the consumption of chicken meat and eggs. In India, 37.2% of 851.8 million total chickens recorded in 2019 were of the native or indigenous type, and the remaining were improved. In addition, the native/desi poultry population in the country increased by 45.79% in 2019 over 2012, while the commercial poultry population expanded by only 4.5% during this period. Around 50 per cent of the meat produced in India is contributed by poultry (4.06 million tonnes in 2018-19). Because it is affordable and widely available, chicken meat is preferred by the majority of the population as the main meat option. The Indian poultry market is worth $22.97 billion by 2022.9 Contributions from the chicken meat and egg industries were 75.32 and 24.67%, respectively, and it is projected that the poultry industry market in India will increase at a compound annual growth rate (CAGR) of 10.18% from 2023 to 2028, bringing the total market value to $41.94 billion.10
The Indian National Bureau of Animal Genetic Resources characterised and registered 19 chicken breeds in India11, and numerous nondescript desi chicken breeds have been reported by many authors.12-16 Owing to their compatibility with regional taste preferences and cooking methods, native or indigenous chicken breeds are highly desired. Small-scale and backyard poultry farming practices have persisted and grown steadily in regions where large-scale commercially manufactured poultry products are available, which illustrates how local communities have chosen a sustainable production system that results in wholesome, culturally appropriate food.5,13,17 The demand for native chicken meat has been increasing, and it is priced at premiums over broiler chicken meat. Consumers are prepared to pay more for native chicken meat and eggs, particularly in metropolitan areas. Notably, the retail price of native chicken meat is currently almost three times that of broilers in metropolitan areas.4
Although traditionally, native chickens have been reared mostly in backyard environments, semi-intensive and intense native chicken farms have become increasingly common in recent years, which can be attributed to the growing demand for native chicken meat and the lucrative prices it fetches. Additionally, a number of government-sponsored development initiatives in India aggressively promote the raising of native chickens with the aim of improving the livelihoods of women and other marginalised groups. On the demand side, consumers prefer native chickens to broilers assuming that they are produced using a lot more organically. Given these circumstances, this study aimed to investigate the household preferences for native chicken meat that might affect the sustainability of the evolving intensive systems of native chicken production.
Materials and Methods
Consumer preferences for native chicken in India were studied using a structured and pretested online questionnaire. The questionnaire was exclusively administered to individuals residing in India who confirmed their consumption of chicken meat. This Google form survey was conducted through social media from April to May 2023. In this study, a snowball sampling technique was utilized, with researchers and stakeholders serving as social media gatekeepers to promote the survey. Participants were required to meet specific inclusion criteria: residing in India, actively consuming chicken meat, being over 18 years old, and willingly engaging in and completing the online survey. Additionally, participants, regardless of gender, should either primarily or jointly share responsibility for food consumption decisions within the household, including food shopping and preparation, while also meeting the criterion of being an earning member (for males) or primary shopper (for females, if not earning). In this research study, all survey participants provided informed consent and participated voluntarily. They were provided with clear information about the study’s objectives and procedures. Participants were assured that their participation was entirely voluntary, with the right to refrain from submitting the survey form at any time without consequences. Strict ethical guidelines were followed to protect their rights and privacy.
The final dataset included responses from 503 individuals, with 305 expressing a preference for native chicken meat and 198 opting for broiler chicken meat as their choice. Extensive data encompassing demographic and socioeconomic attributes, along with consumers’ preferences for consuming native chicken meat and the monthly quantities procured, were collected online. In addition, a set of 39 statements regarding chicken meat purchasing behaviour were presented to survey participants to elucidate their perceptions on a 5-point Likert scale (1, denoting “Strongly Disagree”, to 5, representing “Strongly Agree”). The Cronbach’s Alpha value of 0.930 for the Likert scale statements demonstrates excellent internal consistency and reliability of the responses.
The statistical and econometric analyses of the data were performed using Stata®16.0. Socioeconomic associations with preferences for native chicken were assessed through chi-square analysis. A Factor Analysis was conducted on the 39 Likert scale statements, employing the Principal Component Analysis Extraction Method and the Varimax Rotation Method with Kaiser Normalisation, which reduced the dimensionality of the statements into nine distinct factors. The factor scores derived from these nine factors were then used as explanatory variables (from X19 to X27 in Table 1) in the two-part model to study the factors influencing consumers’ preferences for native chicken meat.
Table 1: Descriptions of variables in the two-part model (1st Part: Logit; 2nd Part: Log-Linear).
Predictors |
Descriptions |
Specification |
Label |
Gender |
Male; Female |
1 – If Male; 0 – If otherwise |
X1 |
Age Group (years) |
⋜ 26; 26–35; 36–45; 46–60; ˃ 60 |
1 – If ⋜ 26; 2 – If 26–35; 3 – If 36–45; 4 – If 46–60; 5 – If ˃ 60 |
X2
|
Monthly Income Brackets (INR) |
≤ 10000; 10,001 – 30,000; 30,001 – 60,000; 60,001 – 90,000; > 90,000 |
1 – If ≤ 10000; 2 – If 10,001 – 30,000; 3 – If 30,001 – 60,000; 4 – If 60,001 – 90,000; 5 – If > 90,000 |
X3 |
Educational levels |
Primary School; Secondary School; Collegiate |
1 – If Primary; 2 – If Secondary; 3 – If Collegiate |
X4 |
Marital status |
Married; Unmarried (single) |
1 – If Married; 0 – If otherwise |
X5 |
Habitat (living area) |
Urban; Rural |
1 – If Urban; 0 – If otherwise |
X6 |
Cohabiting with family |
Yes; No |
1 – If Yes; 0 – if otherwise |
X7 |
Senior citizens at home |
Yes; No |
1 – If Yes; 0 – If otherwise |
X8 |
Children at home |
Yes; No |
1 – If Yes; 0 – If otherwise |
X9 |
Household size |
Count |
Count |
X10 |
Religiona |
Christian; Hindu; Muslim; Others |
1 – If Hindu; 0 – If otherwise |
X11 |
1 – If Muslim; 0 – If otherwise |
X12 |
||
1 – If Others; 0 – If otherwise |
X13 |
||
Chicken consumptionb (frequency) |
Daily; Alternate Days; Twice Weekly; Weekly; Fortnightly; Occasionally |
1 – If Daily; 0 – If otherwise |
X14 |
1 – If Alternate Days; 0 – If otherwise |
X15 |
||
1 – If Twice Weekly; 0 – If otherwise |
X16 |
||
1 – If Weekly; 0 – If otherwise |
X17 |
||
1 – If Fortnightly; 0 – If otherwise |
X18 |
||
Comfort |
Factor Analysis |
Factor Score |
X19 |
Affordability |
Factor Analysis |
Factor Score |
X20 |
Knowledge |
Factor Analysis |
Factor Score |
X21 |
Nutrition |
Factor Analysis |
Factor Score |
X22 |
Palatability |
Factor Analysis |
Factor Score |
X23 |
Food Quality |
Factor Analysis |
Factor Score |
X24 |
Fitness |
Factor Analysis |
Factor Score |
X25 |
Purity (natural) |
Factor Analysis |
Factor Score |
X26 |
Sustainability |
Factor Analysis |
Factor Score |
X27 |
Reference categories: a – Christian; b – Occasionally (randomly) |
In this study, a two-part model, closely related to the ‘hurdle model’18-22 and the Heckman selection model23 was adopted as a viable alternative to analyze the factors influencing household consumption of native chicken meat with mixed discrete-continuous outcomes.24
The structural expression of the two-part model is given by
E(Y|X) = Pr(Y>0|X) ∗ E(Y|Y>0, X).
The first part Pr(Y>0|X) denotes the probability that a respondent has exhibited preference for native chicken meat given a set of variables X. The second part E(Y|Y>0, X) denotes the expected monthly quantity of native chicken consumed, Y, given that the respondent has nonzero preference Y>0 and a set of variables X. In this study, the first part employed a logit regression to predict the likelihood of a binary event, specifically whether consumers prefer to purchase native chicken (coded as 1) or not (coded as 0), while the second part utilised ordinary least squares (OLS) regression with a log-transformed dependent variable (y) to analyse the quantity associated with the amount of native chicken purchased if a consumer exhibited a preference in the first part. The same set of regressors shown in Table 1 was used in both parts of the model to maintain consistency in the analysis.
Results and Discussion
Preferences for Native Chicken Meat
This study received completed responses from 503 individuals who were chicken meat eaters and tried native chicken meat at least once. Only nine (1.79%) of 503 respondents had never tried broiler chicken meat more than once and restricted the eating of native chicken alone. It should be noted that although 305 of the 503 respondents expressed a preference for native chicken meat, they (except nine strict native chicken meat eaters) ate and purchased broiler chicken meat, which is often larger than native chicken, due to economic and cuisine considerations. They (305) preferred native chicken meat over broiler meat for its taste, nutritional quality, health, organic nature, and elegance when served to guests. In Table 2, the preferences for and consumption of native chicken meat in the study population are described in terms of demographics.
Among the 376 male respondents, 211 (56.12%) indicated that they preferred native chicken meat to broilers, whereas 165 (43.88%) did not. In contrast, among the 127 female respondents, 94 (74.02%) reported an inclination toward native chicken meat, with 33 (25.98%) indicating otherwise. There was also a highly significant (χ2=12.74; p=0.000) relationship between gender and preference for native chicken meat, where women showed a considerably higher predisposition for native chicken meat than men.25 Age segment-based analysis of the tendency to consume native chicken meat revealed a significant association (χ2=13.52; p=0.009) between the two groups. In contrast to the younger age groups, older age groups showed a reduced preference for native chicken meat. These results imply that the preferences of the population for native chicken meat are influenced by age.26 Similarly, a significant association (χ2=13.91; p=0.008) was observed between income levels and preferences for native chicken meat.27 Accordingly, there was also a significant relationship (χ2=6.26; p=0.044) between the propensity to consume native chicken meat and the “educational levels” of respondents, with native chicken meat consumption rates of 61.54% for primary educated respondents, 88.89% for secondary-level qualified respondents, and 59.53% for graduates. This shows that consumer consumption patterns and preferences for chicken meat are influenced by educational background.28
Table 2: Demography-wise Desi-Chicken Meat Preferences and Consumption.
Characteristics |
Category |
Total (N) |
Response Frequency |
Quantity (Mean kg.) |
χ2 [p value] |
|
Yes |
No |
|||||
Gender
|
Male |
376 |
211 (56.12) |
165 (43.88) |
1.495 |
12.74 [0.000] |
Female |
127 |
94 (74.02) |
33 (25.98) |
1.574 |
||
Age Groups (years) |
⋜ 26 |
61 |
42 (68.85) |
19 (31.15) |
1.714 |
13.52 [0.009] |
26–35 |
103 |
66 (64.08) |
37 (35.92) |
1.492 |
||
36–45 |
116 |
78 (67.24) |
38 (32.76) |
1.538 |
||
46–60 |
178 |
101 (56.74) |
77 (43.26) |
1.446 |
||
˃ 60 |
45 |
18 (40.00) |
27 (60.00) |
1.500 |
||
Income Brackets (INR) |
≤ 10000 |
44 |
28 (63.64) |
16 (36.36) |
1.786 |
13.91 [0.008] |
10,001 – 30,000 |
75 |
43 (57.33) |
32 (42.67) |
1.698 |
||
30,001 – 60,000 |
96 |
56 (58.33) |
40 (41.67) |
1.536 |
||
60,001 – 90,000 |
103 |
78 (75.73) |
25 (24.27) |
1.378 |
||
> 90,000 |
185 |
100 (54.05) |
85 (45.95) |
1.470 |
||
Education |
Primary |
13 |
8 (61.54) |
5 (38.46) |
1.750 |
6.26 [0.044] |
Secondary |
18 |
16 (88.89) |
2 (11.11) |
1.563 |
||
Collegiate |
472 |
281 (59.53) |
191 (40.47) |
1.511 |
||
Marital status |
Married |
412 |
249 (60.44) |
163 (39.56) |
1.532 |
0.04 [0.846] |
Unmarried |
91 |
56 (61.54) |
35 (38.46) |
1.464 |
||
Habitat (living area) |
Urban |
421 |
260 (61.76) |
161 (38.24) |
1.481 |
1.36 [0.243] |
Rural |
82 |
45 (54.88) |
37 (45.12) |
1.744 |
||
Cohabiting with family? |
Yes |
437 |
260 (59.50) |
177 (40.50) |
1.521 |
1.81 [0.178] |
No |
66 |
45 (68.18) |
21 (31.82) |
1.511 |
||
Senior citizens at home? |
Yes |
251 |
168 (66.93) |
83 (33.07) |
1.595 |
8.32 [0.004] |
No |
252 |
137 (54.37) |
115 (45.63) |
1.427 |
||
Children at home? |
Yes |
251 |
163 (64.94) |
88 (35.06) |
1.543 |
3.89 [0.049] |
No |
252 |
142 (56.35) |
110 (43.65) |
1.493 |
||
Household size (count) |
≤ 2 |
29 |
11 (37.93) |
18 (62.07) |
1.500 |
9.91 [0.042] |
3 |
117 |
65 (55.56) |
52 (44.44) |
1.515 |
||
4 |
220 |
139 (63.18) |
81 (36.82) |
1.435 |
||
5 |
77 |
49 (63.64) |
28 (36.36) |
1.663 |
||
≥5 |
60 |
41 (68.33) |
19 (31.67) |
1.646 |
||
Religion |
Christian |
35 |
21 (60.00) |
14 (40.00) |
1.357 |
5.56 [0.135] |
Hindu |
420 |
261 (62.14) |
159 (37.86) |
1.506 |
||
Muslim |
41 |
18 (43.90) |
23 (56.10) |
1.694 |
||
Others |
7 |
5 (71.43) |
2 (28.57) |
2.300 |
||
Chicken meat consumption frequency |
Daily |
34 |
9 (26.47) |
25 (73.53) |
1.667 |
37.01 [0.000] |
Alternate Days |
63 |
34 (53.97) |
29 (46.03) |
1.471 |
||
Twice Weekly |
171 |
95 (55.56) |
76 (44.44) |
1.521 |
||
Weekly |
134 |
94 (70.15) |
40 (29.85) |
1.441 |
||
Fortnightly |
24 |
12 (50.00) |
12 (50.00) |
1.708 |
||
Occasionally (randomly) |
77 |
61 (79.22) |
16 (20.78) |
1.607 |
In contrast, there was no statistically significant association (χ2=0.04; p=0.846) between respondents’ propensity to consume native chicken meat and their marital status. This suggests that native chicken meat consumption patterns were not greatly influenced by marital status.29 Similarly, the analysis indicated no statistically significant association (χ2=1.36; p=0.243) between consumer consumption of native chicken meat and habitat (rural or urban). This indicates that habitat (urban or rural) does not play a significant role in determining the predilection for consuming native chicken meat.30 Likewise, the preference for eating native chicken meat did not have any statistically significant association (χ2=1.81; p=0.178) with cohabitation (with family) status. This suggests that living arrangements do not significantly affect chicken meat consumption habits in the population.
The preference for eating native chicken meat was significantly associated (χ2=8.32; p=0.004) with the “living with senior citizens’ status of respondents, where 66.93% of those living with the elderly preferred native chicken, while only 54.37% of those who did not live with elderly people preferred. The results showed that the consumption of native chicken meat was higher in households with senior citizens.26 Similarly, having “children at home” had a significant (χ2=3.89; p=0.049) association with the preference to eat native chicken meat, with 64.94% of those who had children preferring it and only 56.35% of those who did not. These findings imply that families with children are more likely to prefer buying chicken meat.31 Likewise, the preference for native chicken meat also had a statistically significant relationship (χ2=9.91; p=0.042) with respondents’ “household size categories”. Household size impacts the consumption patterns of chicken meat, with smaller households being less likely to prefer native chicken meat than other categories. In contrast, although Muslims were less likely (43.9%) to prefer native chicken meat, there was no statistically significant relationship (χ2=5.56; p=0.135) between religion and preference for native chicken meat, with 60.00% of Christians, 62.14% of Hindus, and 71.43% of those who practiced other religions preferring native chicken meat.
Notably, a highly significant association (χ2=37.01; p=0.000) was found between the frequency of chicken meat consumption and the desire for native chicken meat. Consumers who ate chicken “daily” had a lower preference (26.47%) for native chicken meat, compared to 53.97% of “alternate day” consumers, 55.56% of “twice weekly” consumers, 70.15% of “weekly” consumers, 50.00% of “fort nightly” consumers, and 79.22% of “occasional” consumers. The findings indicated that the preference for native chicken meat is significantly influenced by consumption frequency.32
Interrelationships in Customer Attitudes Toward Chicken Meat – Factor Analysis
The results of the factor analysis that illustrate the interrelationships among the attributes of customers’ attitudes towards the purchase and consumption of chicken meat are shown in Table 3. The null hypothesis that the population correlation matrix is an identity matrix is rejected by Barlett’s test of sphericity, as the chi-square statistic was 14569.540 (p=0.000). The value of the KMO statistic (0.872) was also large (> 0.50), indicating the suitability of the collected data for factor analysis.33 Furthermore, all the extracted cummunalities were acceptable, and all variables were fit for the factor solution, as their extraction values were large enough. All the first nine components in the initial solution had over one, which accounted for 71.09 per cent of the observed variations. Factor loadings were used to measure the correlation between the variables and the factors. A strong correlation between a variable and the factor is indicated by a loading close to one, and the factors were rotated with the use of varimax with the Keyser normalisation rotation method.34 Principal component analysis was used for factor extraction, and factors with values greater than 0.300 were considered for interpretation purposes.35
Table 3: Results of Factor Analysis (Rotated Factor Loadings).
Statements (about purchase and consumption of chicken meat…) |
Component (Factors) |
||||||||
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
9 |
|
Promotes relaxation |
.804 |
|
|
|
|
|
|
|
|
Cheers me up |
.788 |
|
|
|
|
|
|
|
|
Eases stress handling |
.761 |
|
|
|
|
|
|
|
|
Facilitates coping with life’s challenges |
.756 |
|
|
|
|
|
|
|
|
Maintains alertness |
.738 |
|
|
|
|
|
|
|
|
Enhances well-being (feel good) |
.665 |
|
|
|
|
|
|
|
|
Cost-effective |
|
.890 |
|
|
|
|
|
|
|
Aware of meat prices |
|
.885 |
|
|
|
|
|
|
|
Always hunt for special deals |
|
.869 |
|
|
|
|
|
|
|
Budget-friendly |
|
.867 |
|
|
|
|
|
|
|
Excellent value for money |
|
.584 |
|
|
|
|
|
|
|
Familiar with chicken meat |
|
|
.813 |
|
|
|
|
|
|
Mindful of my chicken choices |
|
|
.810 |
|
|
|
|
|
|
Conscious of my dietary preferences |
|
|
.788 |
|
|
|
|
|
|
Distinguish chicken products |
|
|
.785 |
|
|
|
|
|
|
Have confidence in my meat choice |
|
|
.716 |
|
|
|
|
|
|
Nutrient-rich |
|
|
|
.802 |
|
|
|
|
|
Promotes good health |
|
|
|
.763 |
|
|
|
|
|
Rich in protein |
|
|
|
.723 |
|
|
|
|
|
Abundant in vitamins and minerals |
|
|
|
.673 |
|
|
|
|
|
Beneficial for skin, teeth, hair, nails, etc. |
|
|
|
.632 |
|
|
|
|
|
Has appealing appearance |
|
|
|
|
.789 |
|
|
|
|
Has pleasant aroma (smell) |
|
|
|
|
.771 |
|
|
|
|
Has delicious taste |
|
|
|
|
.743 |
|
|
|
|
Has enjoyable texture |
|
|
|
|
.733 |
|
|
|
|
Food quality is my key factor |
|
|
|
|
|
.828 |
|
|
|
Food quality guides my purchases |
|
|
|
|
|
.784 |
|
|
|
There are multiple aspects to food quality |
|
|
|
|
|
.776 |
|
|
|
Food quality serves as my motivator |
|
|
|
|
|
.657 |
|
|
|
Helps me control my weight |
|
|
|
|
|
|
.836 |
|
|
Is low in fat |
|
|
|
|
|
|
.821 |
|
|
Is low in calorie |
|
|
|
|
|
|
.813 |
|
|
Free from artificial ingredients |
|
|
|
|
|
|
|
.798 |
|
Additive-free |
|
|
|
|
|
|
|
.796 |
|
Comprises natural ingredients |
|
|
|
|
|
|
|
.763 |
|
I prefer purchasing organic chicken |
|
|
|
|
|
|
|
|
.791 |
I prefer to buy free-range chicken |
|
|
|
|
|
|
|
|
.706 |
Sustainability is important to me |
|
|
|
|
|
|
|
|
.657 |
I support the local farming community |
|
|
|
|
|
|
|
|
.533 |
Extraction Method: Principal Component Analysis; Rotation Method: Varimax with Kaiser Normalisation. |
|||||||||
Factors: 1 – Psychological Well-Being; 2 – Affordability; 3 – Knowledge; 4 – Nutrition; 5- Palatability; 6 – Food Quality; 7 – Fitness; 8 – Purity (natural); 9 – Traditional farming |
Six assertions, viz., ‘Promotes relaxation’, ‘Cheers me up’, ‘Eases stress handling’, ‘Facilitates coping with life’s challenges’, ‘Maintains alertness’, and ‘Enhances well-being (feel good)’, are grouped as one factor that is related to the “Psychological Well-Being” of consumers. The advantages of eating chicken meat on an emotional and psychological level are represented by this component as a source of comfort and relaxation.36,37 By grouping the responses to the five statements, namely, (i) cost-effective, (ii) aware of meat prices, (iii) always hunt for deals, (iv) budget-friendly, and (v) excellent value for money, the factor analysis extracted the second component that can be referred to as “Affordability”. The outcomes showed that customers thought about how affordable and cost-effective chicken meat was.38-40
The factor analysis derived the third component by clustering the consumers’ responses to “familiar with chicken meat”, “mindful of my chicken choices”, “conscious of my dietary preferences”, “distinguish chicken products” and “have confidence in my meat choice” which could be referred to as “knowledge” because it symbolises consumers’ knowledge, awareness, and consciousness regarding various aspects of chicken meat.41-44 “Nutrition,” which included the statements “nutrient-rich,” “promotes good health,” “rich in protein,” “abundant in vitamins and minerals,” and “beneficial for skin, teeth, hair, nails, etc.” was derived as the fourth factor. This factor underscores the perception of consumers that chicken meat is a source of nutrition and health benefits.37,45,46
In the factor analysis, the fifth component, “palatability,” was created by combining the statements “appealing appearance,” “pleasant aroma (smell),” “delicious taste,” and “enjoyable texture.” This variable reflects how consumers rate the sensory qualities of chicken meat.45,47-50 “Food Quality” was derived as the sixth component by the factor analysis. This factor was extracted by grouping the responses for “food quality is my key factor”, “food quality guides my purchases”, “there are multiple aspects to food quality”, and “food quality serves as my motivator”.51-53 This component highlights the importance of food quality in individuals’ decision making while buying chicken meat. By integrating consumer responses to the assertions that “helps me control my weight,” “is low in fat,” and “is low in calories,” the seventh factor, “Fitness,” was derived by factor analysis.54-56 This factor demonstrates the connection between eating chicken meat and staying physically fit.
The eighth factor, “Purity (Natural)”, was extracted through factor analysis by combining the consumers’ responses for the statements “free from artificial ingredients”, “additive-free”, and “comprises natural ingredients”.37 This component exhibits the link between chicken meat choices and the purity or naturalness of chicken meat. With the statements “prefer purchasing organic chicken,” “prefer to buy free-range chicken,” “sustainability is important to me,” and “support the local farming community,” the factor analysis extracted the last component, “Sustainability,” which reflects consumers’ commitment to ethical and sustainable choices in chicken meat purchases.57-59 Those who liked organic and free-range chickens and supported local farming communities scored higher on this factor.
Factors Influencing Native Chicken Meat Preferences and Purchases: Two-Part Modelling
A two-part econometric model involving logit regression in part-1 and log-normal OLS in part-2 was used to analyse the factors affecting customers’ preferences for native chicken meat and the quantity of their monthly purchases. The robustness of the logit model in describing preference dynamics was proven by the LR chi2 statistic (332.52). The model’s good fit was highlighted by the log likelihood (-170.924), and its efficiency in capturing a sizable portion of variation was shown by the pseudo R2 (0.493). The significant F-statistic of 5.40 in Part-2 exhibited model fitness. These results indicated that the models used in part-1 and part-2 are valid and adequate.
The results from Table 4 for the two-part model showed the significance of gender in the first part (Logit), which indicated that males were 59.4% less likely to prefer native chicken meat than females. However, it did not significantly influence the quantity purchased in the second part. Therefore, while there may be gender-based preferences due to tastes and dietary preferences, they do not significantly affect consumption quantity.60
Table 4: Results of the Two-Part Model (First Part: Logit; Second Part: Log-linear).
Explanatory Variables |
Part 1: LOGIT |
Part 2: LOG-LINEAR REG. |
|||||
Coefficient |
Exp(B) |
z |
P > z |
Coefficient |
z |
P > z |
|
X1 |
-0.901 (0.380) |
0.406 |
2.37 |
0.018 |
0.026 (0.057) |
0.45 |
0.650 |
X2 |
-0.714 (0.193) |
0.490 |
3.70 |
0.000 |
-0.066 (0.032) |
2.04 |
0.041 |
X3 |
0.490 (0.138) |
1.632 |
3.54 |
0.000 |
0.010 (0.024) |
0.44 |
0.657 |
X4 |
-1.701 (0.450) |
0.183 |
3.78 |
0.000 |
-0.137 (0.069) |
2.00 |
0.046 |
X5 |
2.505 (0.665) |
12.247 |
3.77 |
0.000 |
0.325 (0.094) |
3.47 |
0.001 |
X6 |
0.377 (0.385) |
1.458 |
0.98 |
0.327 |
-0.214 (0.071) |
3.02 |
0.002 |
X7 |
-2.145 (0.581) |
0.117 |
3.69 |
0.000 |
-0.033 (0.074) |
0.44 |
0.660 |
X8 |
0.751 (0.317) |
2.119 |
2.37 |
0.018 |
0.094 (0.053) |
1.78 |
0.075 |
X9 |
0.329 (0.331) |
1.389 |
0.99 |
0.321 |
0.014 (0.056) |
0.25 |
0.803 |
X10 |
0.351 (0.144) |
1.421 |
2.45 |
0.014 |
0.045 (0.024) |
1.93 |
0.054 |
X11 |
-0.350 (0.555) |
0.704 |
0.63 |
0.528 |
0.107 (0.101) |
1.06 |
0.288 |
X12 |
-2.383 (0.774) |
0.092 |
3.08 |
0.002 |
0.008 (0.146) |
0.06 |
0.954 |
X13 |
0.524 (1.177) |
1.688 |
0.44 |
0.656 |
0.750 (0.213) |
3.53 |
0.000 |
X14 |
-3.427 (0.770) |
0.032 |
4.45 |
0.000 |
0.165 (0.155) |
1.07 |
0.286 |
X15 |
-1.759 (0.638) |
0.172 |
2.76 |
0.006 |
0.035 (0.098) |
0.36 |
0.717 |
X16 |
-2.266 (0.555) |
0.104 |
4.08 |
0.000 |
-0.036 (0.073) |
0.50 |
0.617 |
X17 |
-1.369 (0.567) |
0.254 |
2.41 |
0.016 |
-0.089 (0.071) |
1.25 |
0.211 |
X18 |
-2.414 (0.759) |
0.089 |
3.18 |
0.001 |
0.052 (0.131) |
0.40 |
0.693 |
X19 |
-0.672 (0.153) |
0.511 |
4.38 |
0.000 |
-0.095 (0.023) |
4.19 |
0.000 |
X20 |
0.785 (0.161) |
0.456 |
4.88 |
0.000 |
-0.092 (0.022) |
4.14 |
0.000 |
X21 |
-0.417 (0.151) |
0.659 |
2.75 |
0.006 |
-0.044 (0.023) |
1.94 |
0.052 |
X22 |
-0.841 (0.170) |
0.431 |
4.96 |
0.000 |
-0.072 (0.023) |
3.20 |
0.001 |
X23 |
-0.241 (0.164) |
0.786 |
1.47 |
0.143 |
-0.013 (0.024) |
0.54 |
0.591 |
X24 |
-0.552 (0.138) |
0.576 |
4.00 |
0.000 |
-0.064 (0.022) |
2.89 |
0.004 |
X25 |
-1.563 (0.188) |
0.209 |
8.31 |
0.000 |
-0.169 (0.025) |
6.69 |
0.000 |
X26 |
-0.673 (0.149) |
0.510 |
4.51 |
0.000 |
-0.098 (0.023) |
4.18 |
0.000 |
X27 |
1.166 (0.166) |
3.209 |
7.01 |
0.000 |
0.136 (0.027) |
5.13 |
0.000 |
Constant |
6.693 (1.819) |
806.385 |
3.68 |
0.000 |
0.322 (0.240) |
1.34 |
0.180 |
|
N = 503 LR chi2(27) = 332.52 Prob > chi2 = 0.000 Log likelihood = -170.924 Pseudo R2 = 0.493 |
N = 305 F (27, 277) = 5.40 Prob > F = 0.000 R2 = 0.345 Adj. R2 = 0.281 Log likelihood = -140.313 Root MSE = 0.4022 |
|||||
|
Log pseudolikelihood = -311.23659 |
As people aged a stage, both their preferences for and purchases of local chicken significantly reduced, by 51.0% in the first part and by 6.39% in the second part. This trend may be due to growing health concerns’ impact on dietary preferences.61 While income was not found to have a significant effect on the amount of native chicken meat purchased in Part-2, the results in Part-1 indicated that when income is raised by a category, consumers are 1.632 times (or 63.2%) more likely to choose native chicken. The findings support economic theories of consumer behaviour 62 by showing that higher-income individuals had a larger range of food choices, including for specialty foods such as native chicken. As the levels of education rise, preferences for native chicken decline significantly by 81.70% in the first part and quantity purchases by 12.80% in the second. These results are consistent with studies showing that higher education is associated with more exposure to a broad range of foods and dietary alternatives.63
Marital status had a significant impact on both consumers’ preferences for native chicken (first-part) and the quantity purchased (second-part). Married consumers preferred native chicken meat 12.247 times more than unmarried consumers and purchased 38.40% more, possibly influenced by larger family sizes or shared dietary preferences. Consumer preferences for native chicken meat (first-part) were not significantly influenced by their habitat (urban or urban) of living. However, in the second part, it was found that urban consumers purchased in a quantity that was 19.27% lower than that of their counterparts, which might be because rural consumers had more convenient access to native chicken meat at all times.
The consumers having senior citizens at home had a significant odd of preferring native chicken by 2.119 times (part-1), whereas their presence did not significantly impact the quantity of native chicken purchased (pat-2). The results implied that older people could prefer traditional native chicken meat over quantity because they would consume it in relatively smaller quantities.64 However, neither the customers’ preference for (part-1) nor the quantity of (part-2) native chicken meat they purchased were significantly influenced by having kids at home. This insignificance may be related to the children’s choice for meals made primarily using broiler meat either at home or away. In part-1, a significant coefficient for household size indicates that there is a 42.10% greater likelihood of preferring native chicken for every additional unit in household size. In part 2, the household size coefficient is 0.045 (p=0.054), which is barely significant. These findings suggest that larger households may have more varied eating habits and a propensity for traditional foods such as native chicken.
Hindu and other religious consumers did not show a significant preference for native chicken in the first part, which used Christianity as the reference group. Only Muslims, nevertheless, demonstrated a significantly lower preference, with a likelihood that was reduced by 90.80%, perhaps as a result of dietary limitations on certain meats. However, in part 2, only the consumers of other religions purchased significantly more (68.80%) than Christians, while Hindus and Muslims exhibited no significant difference in their quantities purchased. These results support the hypothesis that various religious and cultural groups may have unique dietary preferences and consumption patterns.63
Notably, part-1 of the analysis revealed that respondents who consumed chicken daily, every other day, twice weekly, once weekly, or every two weeks had significantly lower preferences for native chicken meat than occasional or random chicken meat consumers (used as a reference); however, part-2 of the analysis revealed that these consumption frequencies had no significant impact on the quantity of native chicken purchased. As a result of increased native chicken meat prices, regular chicken consumers may have to spend more to satisfy their desire for native chicken; however, they might eat more broiler meat with the same budget.
With the exception of “Palatability,” eight of the nine factor scores from factor analysis that were included as predictors in the two-part model had a significant negative impact on both part-1 (preference) and part-2 (quantity purchased). These eight significant factors, namely, (i) psychological well-being, (ii) affordability, (iii) knowledge, (iv) nutrition, (v) food quality, (vi) fitness, (vii) purity (natural), and (viii) sustainability, demonstrated a consistent and statistically significant negative impact on both preference for and quantity purchase of native chicken meat. Palatability may not have had a significant impact on native chicken meat preference and quantity purchase in the context of the analysis because it is universally desired, but the other eight factors may have had a different impact due to their unique characteristics and personal preferences.
The excessively high pricing (68%), the challenge in finding the precise quantities desired (23%), and just 9% dislike of the taste were the main justifications given by respondents who did not purchase native chicken meat. Even among those who preferred and purchased native chicken meat, their purchasing power was still significantly constrained by its greater price and difficulty in being found in the precise quantities they needed. On average, Native chicken meat typically costs approximately 75% more than broiler meat. People had to purchase complete chicken because native chicken meat, unlike broiler meat, was not available in portions. This means that for a family of two to three, the quantity from one bird will be greater, whereas for larger homes, it will either be insufficient and require the purchase of multiple birds.
With their economies of scale, the expanding semi-intensive and intensive systems of native chicken production have the potential to significantly increase market supply and thus address the issues of rising market pricing and limited availability of desired quantities, eventually contributing to the sustainability of the evolving native chicken production systems.
Conclusion
Preference for and consumption of native chicken meat in India were investigated using a two-part model and factor analysis. Consumer preferences have been found to be significantly influenced by demographic parameters, such as gender, age, income, education, marital status, cohabitation, household size, presence of senior citizens or children within households, and consumption frequency. Additionally, factors such as psychological well-being, affordability, knowledge, nutrition, food quality, fitness, purity (natural), and sustainability have a negative influence on both preferences and quantity of native chicken meat purchased.
An important problem in the market for native chicken meat is the price difference, which is approximately 75% higher for native chicken meat than for broiler meat. Additionally, consumers had to purchase the entire chicken because native chicken meat was not readily available in the required quantities. This brought on challenges for smaller households and may have resulted in under- or overconsumption for larger families. The results of this study indicated a significant preference for native chicken meat, which is driven by the sustainability advantages of this food, such as ethical and sustainable production. However, improving the sustainability of semi-intensive and intensive native chicken farming depends on eliminating pricing disparities and ensuring the availability of native chicken meat in desired quantities. The long-term sustainability of native chicken farming relies on integrating consumer demand with ethical and environmentally sustainable farming methods.
Funding Sources
The authors did not receive financial support from any organization for the submitted work.
Conflict of Interest
The authors declare no conflict of interests associated with the research, including financial, personal, or professional affiliations that could influence or be perceived to influence the work presented in this manuscript.
Data Availability Statement
The datasets generated and analysed during the current study are available from the corresponding author on reasonable request.
Informed Consent Statement
In this research study, all survey participants provided informed consent and participated voluntarily. They were provided with clear information about the study’s objectives and procedures. Participants were assured that their participation was entirely voluntary, with the right to refrain from submitting the survey form at any time without consequences. Strict ethical guidelines were followed to protect their rights and privacy.
Authors’ Contributions
G.K. and K.C. conceived of the presented idea. G.K. developed the theory and performed the computations. K.C. verified the analytical methods. Both G.K. and K.C. discussed the results and contributed to the final manuscript. All authors read and approved the final manuscript.
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