1. INTRODUCTION:

Packaging is regarded as a vital component of our modern lifestyle and is a significant element of the branding process. Earlier, packaging was considered as a meager protective tool but today it is considered as an important element of marketing. Nowadays packaging is often considered as the fifth ‘P’ of the marketing mix. Richardson et al. (1994) described packages as product related but with extrinsic properties. Underwood (2003) claimed packages having intrinsic or extrinsic attributes based on certain features they possess. Pilditch (1961) was the first person to propose packs as the ‘silent salesman’. Later, Lewis (1991) supported Pilditch’s views, describing good packaging as far more than a salesman but a flag of recognition and a symbol of values. Vazquez, Bruce and Studd (2003) stated that today, the pack must come lively at the point of purchase, in order to represent the salesman.

Purchase behaviour of consumers in most emerging economies such as India has considerably changed due to an increase in the per capita disposable income, global interaction ,information and communication technologies, urbanisation, education and health awareness, movement of households towards higher income groups, changes in lifestyle and family structure etc. (Ali, Kapoor and Moorthy, 2010).This changing lifestyle and increasing self service has positioned product package as a tool to stimulate impulse buying and increase sales promotion.

Doherty and Tranchell (2007) opined that the world loves chocolate. They suggested argued that nine out of ten people liked chocolates and the tenth person always lied. They even explained that chocolate could make everyone smile even bankers. Patwardhan et al. (2010) suggested that of out of the many secondary factors affecting consumer’s buying behaviour of chocolates, packaging was found to be equally important. Packaging in the chocolate industry is therefore vital especially when targeted to young consumers. Today packages are designed to go with different occasions, demand to different social segments and differentiate between different brands. Based on the results from relevant previous research studies, this paper makes an attempt to identify the influence of four major chocolate packaging cues on young consumers mind using multiple regression analysis. The study identified key product packaging cues influencing buying decisions of young consumers across high impulse FMCG’s (chocolate bars) in a semi urban area (Kannur District) of Northern Kerala.

2. LITERATURE REVIEW:

Packaging plays an important role in marketing of any item. It communicates the marketing objective of a specific product to the consumer. According to Sonsino (1990) package design variables mainly constituted the following components: colour, typography, pictures, shape, size, and material. Sauvage (1996) explained the significance of shape as an important factor in creating an image about the product and the brand. He mentioned that the material of a package affected consumer thought process. He also identified that carefully chosen typography was important for readability. Underwood et al. (2001) explained that pictures on packages increased learning and were considered more vibrant stimuli than verbal explanations. Underwood (2003) suggested that consumers linked meanings to the package colours in three different groups namely ‘the physiological’, ‘the cultural’, and ‘the associational’. He also explained the significance of size of the package when considering the visibility of a package and the information it displayed. Rigaux Bricmont (1982) concluded that the combined effects of brand names and brand packaging increased consumers' perceptions of quality.

Packaging must be attractive, informative, and correctly identify the product and communicate its real benefits (Stem 1981, Meyer and Herbert 1981). Wansink (1996) found out circumstances in which larger package sizes facilitated greater use than smaller package sizes. Schoormans and Robben (1997) suggested that the more a package redesign deviated from the existing package design in a product class, the more product attention was induced. Nancarrow, Wright and Brace (1998) explained the significance of product packaging as one of the most significant impetus for delivering the brand message directly to the prospective consumers. Mccracken and Mackln (1998) explained that the visuals linked with a brand name enhanced the memory for the brand. Rettie and Brewer (2000) explained the asymmetry of perception of elements of packaging by showing that to maximize recall, words should be on the right-hand sides of packs, and pictures should be on the left. Calclch and Blair (2001) mentioned that when disembedding skill was correlated with acquisition time, there were considerable differences among consumers in the duration of time needed to acquire package information. Kozup et al. (2003) described that when favorable nutrition information or health claims were presented on product packages, consumers had more positive attitudes towards the product, nutrition attitudes, and purchase intentions.

Silayoi and Speece (2004) in their research on time pressure and involvement level established that visual elements positively influenced purchase decisions more in the low involvement situation, while informational elements played an important role in higher involvement decision-making. Time pressure changed on how consumers evaluated products at the point of purchase, partly by reducing ability to give attention to informational elements. Ampuero and Vila (2006) discussed packaging designs and positioning perceptions in the minds of the consumers. They explained that each positioning strategy was linked with precise graphical variables on product packages. Raghubir and Greenleaf (2006) carried out tests on package size. They found out that the ratio of the sides of a rectangular product or package could positively encourage purchase intentions. Silayoi and Speece (2007) indicated that packaging technology which gave a message of convenience and ease of use played the most important role in consumer likelihood to buy. Thomas (2007) suggested that an optimal package could create positive thrust for a brand. He further explained that beginning of any high-quality package design must start at the prepackage design phase and must travel through several stages before the pack is commercialized. Silayoi and Speece (2007) said that when a consumer was in doubt, the product package becomes important in the purchase option because of its ability to communicate to consumers at the point of sales.

Clement (2007) highlighted the significance of human behaviour model to describe the in-store purchase behaviour and demonstrated through an eye-track experiment on how visual impact from packaging design influenced buying behaviour .His experiment also showed an extended decision making process where visual attention at the point of sale was the central factor for the post-purchase phase .Lo¨ fgren (2008) suggested a metaphor ‘the first moment of truth’ where in the product package functioned as a ‘silent salesman’. Wakefield et al. (2008) examined on how an increase in plainer structure of cigarette packaging influenced adult smokers' perceptions about brand image. Results indicated that plain packaging policies that removed most brand design elements were likely to be most successful in removing cigarette brand image associations. Wang and Chen (2009) noticed that having illustrations in the package design was one of the important factors which influenced buying emotion. Results indicated that food packaging illustrations using high sharp expression was the most popular, and rendering graphic was the most common. Becker et al. (2011) examined the influence of packaging design on taste impressions. Results indicated that visual design parameters such as packaging colour and packaging shape inspired potency perceptions. It was also found that angular product shapes inspired intense taste sensations.

Estiri et al. (2010) analyzed the effects of packaging elements on consumer behaviour in three stages: pre-purchase, purchase and post purchase. Results indicated that the informational element of food packaging were considered as the most important product selection criteria while visual element of packaging attracted least attention in all the three stages of purchase decisions. Wang and Chou (2010) found out that consumers comprehended the messages of packaging via more than two visual elements. Typography along with illustration was the best mode for consumers to comprehend products. Design elements such as brand name, product name, product image, package shape, and colour association all contributed to the comprehension of products; while attached product information design, structure design, and volume design did not make such contribution. Venter et al. (2011) mentioned that participants mainly perceived food packaging based on its functional and physical attributes through unprompted awareness. In this context, information attributes of packaging were considered as crucial, as participants considered certain information as being important either for their health or for deciding whether to choose the product.

An eye-catching packaging for the chocolates forces consumers to buy the chocolates. Even though a few may not approve it expressively, such good packages unquestionably improve the cerebral image of the product. Packaging tends to augment the value and worth of the chocolate and can even mirror the quality of the contents inside the package (Giyahi, 2012). Suraj and Raveendran (2012) illustrated a situation confronting child and the parent when making a purchase decision at the checkouts for high impulse purchase categories namely chocolates using an Elaboration Likelihood Model approach. They explained the significance of packaging cues, pester power and the time pressure in bifurcation of the persuasive process into central and peripheral routes. The ‘central route’ was used to process information due to high package relevance, high personal motivation and high cognitive communication of the child resulting in the purchase of the chocolate. In the ‘peripheral route’, the child or the parent had low personal interests and low product involvement. The end result was ‘purchase’ or ‘no purchase’. The present study explored the influence of four key chocolate packaging cues that could possibly influence the purchase decision of young consumers (students) using multiple regression analysis. Chocolate bars were only included in the study. Assorted chocolates, candies and gums were excluded.

3. RESEARCH METHODOLOGY:

The students were asked to imagine that a new chocolate bar has been launched in the market and were yet to sight it or taste it or a chocolate bar which was already positioned in the market and were yet to sight it or taste it .The present study identified the influence of four key chocolate packaging cues that could possibly influence the purchase decision of students in such a scenario. A multiple cross sectional descriptive type of research (Malhotra, 2006) was designed for the study. The study identified the perception of three different groups of chocolate consumers’ namely i) secondary/higher secondary students, ii) graduates and iii) postgraduates towards chocolate packaging. Respondents fell in age group between 11-27 years. Convenient sampling was used as the sampling technique and a total of 240 responses were collected. Primary data was used in the study and a survey method of data collection technique was undertaken. Data collection was carried out in two schools and four colleges in Kannur district (semi urban area) of Kerala State. A pre-tested questionnaire was used as the data collection instrument. Pretesting of the questionnaire was done among a small group of students from a college to modify/eliminate inconsistency and lack of clarity in certain questions. Pretesting helped to screen out certain chocolate packaging cues such as ‘typography’, ‘size’, ‘material’ and ‘technology’ which were of less significance as far as students community under study were considered and retained four packaging cues such as ‘shape’, ‘information’, ‘colour’ and ‘picture’ for further analysis using multiple regression. All verbal components on chocolate package constituted the packaging cue named ‘information’. This mainly took the form of ‘nutritional information’, ‘price’, ‘brand name’, ‘manufacturing unit’s address’, ‘expiry dates’, ‘nutritional claims’, ‘ingredients’, ‘storage information’, ‘feedback information’ etc. Data obtained through the questionnaires were analyzed using SPSS software package (Version 12) in 95 percent confidence interval.

Table 1 Descriptive Statistics

	Mean	Std. Deviation	N
Packaging and first purchase	59.7660	23.93310	240
Shape	93.4043	7.49100	240
Information	89.0213	21.36480	240
Picture	95.5745	17.78340	240
Colour	107.0851	14.98820	240

Source: Survey data

Table 2 Correlations

		Packaging and first purchase	Shape	Information	Picture	Colour
Pearson Correlation	Packaging and first purchase	1.000	-.074	.623	.778	.847
	Shape	-.074	1.000	.124	-.344	-.416
	Information	.623	.124	1.000	.683	.570
	Picture	.778	-.344	.683	1.000	.793
	Colour	.847	-.416	.570	.793	1.000
Sig. (1-tailed)	Packaging and first purchase	.	.311	.000	.000	.000
	Shape	.311	.	.203	.009	.002
	Information	.000	.203	.	.000	.000
	Picture	.000	.009	.000	.	.000
	Colour	.000	.002	.000	.000	.

Source: Survey data

The following hypotheses were framed for the study.

H1: Visual elements of chocolate package influence purchase decision less as compared to informational elements.

H2: There is no significant difference of the influence of visual element ‘shape’ of chocolate package as far as sex of the respondents were considered.

H3: There is no significant difference of the influence of visual element ‘colour’ of chocolate package as far as sex of the respondents were considered.

H4: There is no significant difference of the influence of visual element ‘picture’ of chocolate package as far as sex of the respondents was considered.

The conceptual framework of the study is shown as below

Multiple regressions are statistical techniques that allow predicting someone’s score on one variable on the basis of their scores on several other variables. It includes many techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables. Multiple regression analysis was carried out on four critical packaging cues/variables (criterion variables) namely ‘shape’, ‘information’, ‘colour’ and ‘picture’ to test H1. Interval variable named ‘Packaging and first purchase’ was designated as the predictor variable. Correlations, ANOVA, t tests were also used to predict the results. Hypotheses H2 to H4 were tested using chi square tests.

4. RESULT AND DISCUSSION:

Multiple regression analyses on 240 cases were performed using enter method. The descriptive statistics are as shown in Table 1.

Correlations between the variables from Table 2 indicated that there is no strong correlation between the criterion and the predictor variables. The values here were found to be acceptable and hence the entire criterion variables were retained for further analysis.

The model summary indicated the following result as shown in Table 3.

Table 3 Model Summary

Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.923(a)	.852	.838	9.63770

a Predictors: (Constant), Shape, Information, Picture, Colour

Source: Survey data

The Adjusted R Square value (.838) from Table 3 indicated that the model accounted for 83.8% of variance.

Standardized beta coefficients which give a measure of contribution of each variable to the model (Table 5), indicated that the variable named ‘colour’ had the highest beta coefficient. This clearly dictated that a unit change in this predictor variable had a large effect on the criterion variable.

Table 4 ANOVA (b)

Model		Sum of Squares	Mean Square	F	Sig.
1	Regression	22447.277	5611.819	60.417	0.000(a)
	Residual	3901.149	92.884
	Total	26348.426

a. Predictors: (Constant), Shape, Information, Picture, Colour; b. Dependent Variable: Packaging and first purchase

Source: Survey data

ANOVA result from Table 4 indicated an overall significance (p < 0.05) for the model.

Table 5 Coefficients (a)

Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
		B	Std. Error	Beta
1	(Constant)	-232.079	30.500		-7.609	0.000
	Shape	1.298	0.252	0.406	5.159	0.000
	Information	-0.162	0.110	-0.144	-1.469	0.149
	Picture	0.530	0.156	0.394	3.393	0.002
	Colour	1.254	0.165	0.786	7.584	0.000

a Dependent Variable: Packaging and first purchase; Source: Survey data

Table 6 Sex * Shape and purchase decision Cross tabulation

		Shape and purchase decision					Total
		Strongly agree	Agree	Neither agree/disagree	Disagree	Strongly disagree
Sex	Male	11	42	17	19	16	105
	Female	22	59	17	26	11	135
Total		33	101	34	45	27	240

Source: Survey data

Table 7 Chi-Square Tests

	Value	df	Asymp. Sig. (2-sided)
Pearson Chi-Square	4.869(a)	4	0.301
Likelihood Ratio	4.878	4	0.300
Linear-by-Linear Association	3.096	1	0.078
N of Valid Cases	240

a 0 cells (.0%) have expected count less than 5. The minimum expected count is 11.81.

Source: Survey data

Table 8 Sex * Colour and purchase decision Cross tabulation

		Colour and purchase decision					Total
		Strongly agree	Agree	Neither agree/disagree	Disagree	Strongly disagree
Sex	Male	16	47	12	22	8	105
	Female	25	64	15	27	4	135
Total		41	111	27	49	12	240

Source: Survey data

Table 9 Chi-Square Tests

	Value	df	Asymp. Sig. (2-sided)
Pearson Chi-Square	3.054(a)	4	0.549
Likelihood Ratio	3.050	4	0.549
Linear-by-Linear Association	1.715	1	0.190
N of Valid Cases	240

a 0 cells (.0%) have expected count less than 5. The minimum expected count is 5.25.

Source: Survey data

Test result from Table 9 showed that Pearson Chi-Square (3.054) was no significant (p=.549; >.05) at 4 degrees of freedom at 5% confidence interval. Hence there was no significant difference of the influence of visual element ‘Colour’ of chocolate package as far as sex of the respondents were considered accepting H3.

Table 10 Sex * Picture and purchase decision Cross tabulation

		Picture and purchase decision					Total
		Strongly agree	Agree	Neither agree/disagree	Disagree	Strongly disagree
Sex	Male	18	46	18	15	8	105
	Female	31	59	24		2	135
Total		49	105	42	34	10	240

Source: Survey data

Table 11 Chi-Square Tests

	Value	df	Asymp. Sig. (2-sided)
Pearson Chi-Square	6.335(a)	4	0.175
Likelihood Ratio	6.531	4	0.163
Linear-by-Linear Association	2.883	1	0.090
N of Valid Cases	240

a 1 cells (10.0%) have expected count less than 5. The minimum expected count is 4.38.

Source: Survey data

Test result from Table 11 showed that Pearson Chi-Square (6.335) was no significant (p=.175; >.05) at 4 degrees of freedom at 5% confidence interval. Hence there was no significant difference of the influence of visual element ‘picture’ of chocolate package as far as sex of the respondents were considered accepting H4.

5. CONCLUSION:

Inferential statistics showed that chocolate packaging cues had significant influence in purchase pattern of semi urban consumers with the exception of cue named ‘information’. Using the enter method, a significant model emerged (F=60.417, p <0.05) with adjusted R square value of 0 .838.Significant predictor variables which emerged were ‘shape’ (β=0.406, p < 0.05), ‘picture’ (β=0.394, p <0.05) and ‘colour’ (β=0.786, p <0.05).The predictor variable ‘information’ was found out to be insignificant (β= -0.144, p >0.05).It was found out that the shape of package had profound influence on purchase behaviour of students falling in the age group between 11-15 years, which largely constituted secondary and higher secondary students. Colour of the package was largely influenced by female categories largely comprising graduate and post graduate students. Picture on chocolate packages were influenced on a balanced scale (evenly balanced) across all the three groups. The informational elements on chocolate packages were found to be non -appealing to the student community. Even informational elements such as ‘price’, ‘ingredients’ and ‘brand name’ were found to be insignificant upon performing bifurcation statistics on the predictor variable named ‘information’ into its component elements. This result was in contradiction to the findings of Vreeland (2000) which indicated that chocolate prices influenced consumer behaviour, Demetris and Claudio (2001) which revealed that ‘chocolate ingredients’ influenced purchase decision and that of Rigaux Bricmont (1982) who concluded that the combined effects of brand names and brand packaging increased consumers' perceptions of quality. Inferential statistics also showed that there were no significant differences of the influence of visual elements ‘picture’ , ‘colour’ and ‘shape’ of chocolate package as far as sex of the respondents were considered .

However the result supported the findings of Silayoi and Speece (2004) which stated that visual elements on packages positively influenced purchase decisions more than informational elements as far as low involvement purchase situation was considered. However the results were in contradiction to the findings of Estiri et al. (2010) pointing that the informational element of food packaging were considered as the most important product selection criteria while visual element of packaging attracted least attention.

6. LIMITATIONS AND SCOPE FOR FUTURE RESEARCH:

The study was confined in a district of Kerala and the sample size drawn was small. Future studies may be extended to a wider area with a bigger sample size. As chocolate is a type of product which is loved by consumers irrespective of age groups, the study could even be extended to all age groups from toddlers to old aged people. Such an extended study would give more information in understanding the significant differences across several demographic variables. The study can also be extended to understand the difference in purchase pattern if any across young consumers of urban and rural areas. The study could even be raveled to diverse products/brands and even on unbranded chocolates and the consumer behavior patterns can be interpreted with different methods of analysis such as discriminant analysis, conjoint analysis, factor analysis, cluster analysis etc.

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Received on 12.11.2013 Modified on 07.12.2013

Asian J. Management 5(1): January–March, 2014 page 55-61