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European Journal of Developing Country Studies, Vol.2 2006 ISSN(paper)2668-3385 ISSN(online)2668-3687 www.BellPress.org

A Study on Factors Influencing the Purchase Decision of FMCG among Bangladeshi Consumers G. M. Shafayet Ullah Lecturer, School of Business Studies Department of Business Administration Southeast University House# 64, Road# 18, Block # B, Banani, Dhaka-1213, Bangladesh Panuel Rozario Prince Lecturer, Department of Business Administration Victoria University of Bangladesh 58/11/A, Panthapath, Dhaka-1205, Bangladesh Abstract Fast Moving Consumer Goods (FMCG) is one of the largest sectors in the economy of Bangladesh. In the last few years the FMCG industry in Bangladesh has experienced dramatic growth; both qualitative and quantitative improvements have occurred in the consumer durable items. Fast Moving Consumer Goods or FMCG in marketing means convenient and low involvement products like- salt, flours, pens, chocolates etc. But in recent years, the FMCG industries worldwide have experienced a difficult market condition. In some categories, formerly popular brands have either been deleted or squeezed between the category leaders and low-cost competitors. This study has identified eight primary factors that influence consumer’s purchase decision of FMCG products in Bangladesh. These factors are Sales Promotion, Unavailability of Brand, Time Constraints, In-Store TVC, Variety Seeking Behavior, Product Features, End of Aisle Display and Product Convenience. This study recommends focusing on three important factors i.e. Sales Promotion, Time Constraints and Unavailability of Brand to smoothen the progress of the FMCG industries in Bangladesh. The FMCG industries will find better development opportunities if the findings of this study are used as input in their strategic decision making. Keywords: FMCG, Consumer Preference, Actual Purchase, Sales Promotion, Unavailability of Brand, Time Constraints, In-Store TVC, Variety Seeking Behavior, End of Aisle Display, Product Convenience. 1. Statement of the Problem The Bangladeshi FMCG sector is one of the largest sectors in the country’s economy. It has strong Multi National Company (MNC) presence and is characterized by well established distribution networks, intense competition between the organized and unorganized segments and low operational costs (PPFAS, n.d.). Being a developing economy, Bangladesh is gradually becoming a large market especially for the Fast Moving Consumer Goods or FMCG. In the last few years the FMCG industry in Bangladesh has experienced dramatic growth; both qualitative and quantitative improvements have occurred in the consumer durable items (Hamid et al. 2008). While purchasing the high involvement products like- electronic goods, luxury items or lifestyle products, the prior in-home decisions of purchase are not usually altered in the store environment. On the contrary, for the convenient and low involvement products like- salt, flours, pens, chocolates etc., a significant level of distortion from the prior decision of brand choice is frequently observed (Russo, Medvec & Meloy, 1996). These convenient and low involvement products are also known as Fast Moving Consumer Goods (FMCG) in marketing. For the marketers, it is very difficult and sometimes impossible to track consumers’ brand preference. Marketers may form any consumer’s intention to buy and help him to facilitate his purchasing process by providing essential information. According to Perner (n.d.) the final decision of which brand to buy from available brands comes from an internal information processing that marketers can never fully influence from outside. Sometimes after deciding which brand to buy, consumers change their decision at the time of actual purchase from the retail outlet. The end result of any marketing activity is to persuade the prospective

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European Journal of Developing Country Studies, Vol.2 2006 ISSN(paper)2668-3385 ISSN(online)2668-3687 www.BellPress.org group of consumers to acquire what the marketers are offering in the marketplace in exchange of consumers’ money. To accomplish this goal, marketers are constantly applying diversified marketing tools to influence the consumers to buy their offerings. Companies are striving to attain the higher portion of their consumer’s wallet through fierce marketing strategies. Every marketer dreams to have his products stocked exclusively in the shelves of his consumer’s homes. However, in marketing, it is always said that, “In the end, the consumer is king!” (Richard P. Gee, n.d.). This study focuses around identifying the factors significantly influencing the consumers’ preferences for the FMCG products during actual purchase from the retail outlets. 2. Literature Review Fast Moving Consumer Goods (FMCG) are the products that are sold quickly at relatively low prices. Though the profit made on FMCG products are relatively small in terms of retail sales, they are generally sold in large quantities in wholesale. So, the cumulative profit on such products can be large. Brand Careers Glossary (n.d.) states that FMCG is an expression used to describe frequently purchased, low cost, low involvement, convenient consumer items, i.e., snack foods, cleaning products, stationeries, and toiletries etc. The main characteristics of FMCG’s from the consumers' perspective are- frequent purchase, low involvement (little or no effort to choose the item - products with strong brand loyalty are exceptions to this rule) and low price. Additionally, from the marketers' angle, the main characteristics of FMCGs are- high volumes, low contribution margins, extensive distribution networks and high stock turnover (Majumdar, 2004). There are other definitions regarding FMCG from various viewpoints. Fast Moving Consumer Goods are usually low priced and low risk products that require very little thought when purchasing on a daily basis (Food & Safety Promotion Board, 2005). Examples of FMCG generally include a wide range of frequently purchased consumer products such as toiletries, cosmetics, oral hygiene products, shaving products and detergents, as well as other non-durables such as glassware, light bulbs, batteries, stationary products and plastic goods. FMCG may also include pharmaceuticals, consumer electronics, packaged food products and soft drinks, although these are often categorized separately. Some of the best known examples of multinational FMCG companies in Bangladesh include Colgate-Palmolive, Reckitt Benckiser, Nestlé, Unilever, Procter & Gamble, Coca-Cola, Kraft, PepsiCo etc. Some national FMCG companies are Square, PRAN and ACI etc. One of the thrust areas of interest could be FMCG segments given Bangladesh's large population with progressive increase in purchasing capacity (Rashid, 2010). Bangladesh saw a growth of over 8% for the year 2003-04. These findings on growth trends around the fast emerging south Asian sub-regional consumer market were released by research firm AC Nielsen. Bangladesh has discovered the catalytic effect of lower unit packs as an evolutionary path. In Bangladesh, changes in consumers’ buying behavior and aggressive distribution by marketers have helped the branded packaged goods to hold the sector’s growth. Categories such as hair oil, detergents, milk powder and toothpaste recorded double digit growth rates (Business Standard, 2004). US giants like Proctor & Gamble and Johnson & Johnson have already recorded encouraging surge in sales of their products in Bangladesh. The FMCG market watchers say good performance of Unilever, having around $500 million dollar annual turnover in Bangladesh, might have opened the eyes of $80 billion plus P&G and $60 billion plus Johnson & Johnson on Bangladesh’s fast growing market of middleclass consumers (Positive Bangladesh, 2011). This is consistent with previous industry studies and with research conducted by marketing academics which found that approximately 50% of grocery purchases can be classified as ‘unplanned’ (POPAI Special Report 1978; Kollat and Willet 1967; Park et al. 1989). Consumer promotions constitute a significant part of the marketing effort of consumer nondurable (Neslin et al. 1985). For products sold in supermarkets, point-ofpurchase promotion is particularly attractive, because the large proportion of grocery purchase decisions are made after entering the store. A recent study by the Point-of-Purchase Advertising Institute (POPAI) found that two-thirds of supermarket purchases are the result of an in-store decision (Agnew 1987). Brand choice probabilities is an opportunistic state as a function of prevailing marketing activity (e.g., feature, display, and price) and the consumer's established preferences for the brands in the category. It is well known that the mechanism governing the purchase decisions of consumers is influenced by marketing mix variables (‘non-stationary’) and that it varies over the population (‘heterogeneous’) (Wagner & Taudes 1986). Findings from the study of Morrison in 1966 argued that consumers can be characterized based on their brand purchasing patterns within a product class (cited in Kahn & Raju 1991). For example, some consumers' purchase behavior can be characterized as reinforcing, i.e., a tendency to repurchase the last brand bought (Morrison 1966; Jeuland 1979, cited in Kahn & Raju 1991), while other consumers' purchase behavior can be characterized as

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European Journal of Developing Country Studies, Vol.2 2006 ISSN(paper)2668-3385 ISSN(online)2668-3687 www.BellPress.org variety-seeking, i.e., a tendency to shift away from the last brand purchased (Givon 1984; Kahn et al. 1986; Lattin & McAlister 1985; Lattin 1987, Kahn & Raju 1991). Advertising is the vehicle used by producers to inform consumers of the existence and attributes of their brands. The effect of advertising on sales or market share of a firm is probably the most researched relationship in marketing. Advertising encourages consumers to try a new brand or a brand they have not bought for a long time (Givon & Horsky 1990). One potential consequence of these promotions is their tendency to accelerate consumer purchases. That is, in response to a promotion, consumers may buy more quantity of the product category, or buy at an earlier time (Blattberg et al. 1981, Shoemaker 1979, Wilson et al. 1979). A number of marketing researchers suggested that dealing patterns might influence purchase behavior (Krishna 1991, Winer 1986). Previous research on state dependence indicates that a brand's purchase probabilities vary over time and depend on the levels of inertia and variety seeking and on the identity of the previously purchased brand (Chintagunta 1998). Study of Kahn and Raju (1991) indicates that, for a minor brand, price discounts have a relatively larger effect for the reinforcement segment than for the variety-seeking segment. Conversely, for a major brand, price discounts have a relatively larger effect for the variety-seeking consumers than for the reinforcement consumers. Lee and Labroo (2004) suggest that consumers prefer brands that are easy to recognize and brands whose information is easy to understand. Earlier research has shown that ease of processing may be perceptual or conceptual in nature. Perceptual processing is feature-based, and has more to do with ease of recognition. Perceptual processing ease benefits brand choice in situations where all the brand choices are present in the environment as in a supermarket. 2. Conceptual Framework Depending on the findings of the previous studies and exploratory research, twenty variables are primarily being considered for analysis. It is assumed that these twenty variables generally affect consumers’ brand preference for FMCG in store environment. Variables are Sales Promotion, Point of Purchase Advertising, Product Feature, Product Display, Competitive Pricing, Dealing Pattern, Ease of Recognition, End of Aisle Display, In-Store TVC, Salesperson Influence, Unavailability of Preferred Brand, Attractive Packaging, Convenience, Variety Seeking Tendency of Consumer, Influence of Other Customers, Store Environment, Time Constrain, Cash Constrain, Delightful Mind of Consumer and Level of Involvement of Consumer. The framework is clarified in figure 1. 3. Methodology 3.1 Data Collection The research is descriptive in nature, as it tends to portray what actually works as the motive for changing the predetermined brand while purchasing the FMCG products from the store. Secondary data was used to construct the basic framework of the study before proceeding with primary data. Primary data was collected from a group of respondents through structured questionnaires by personal in-home interview procedure. 3.2 Samples Primary data was collected from a group of 143 respondents from Dhaka City, Bangladesh. The respondents were selected through the convenience sampling technique, since the procedure is less time consuming and more convenient. 3.3 Analysis Techniques In the first step of the study, some variables were identified which may have effect on consumer decision making at store environment through exploratory study on previous research works and focus group discussion with small group of respondents. In the second phase, a statistical analysis was conducted on those previously identified influential variables on the basis of primary data collected through survey. The questionnaire consisted of two parts; first part elicited the basic demographic information of the respondents through some close ended questions and the second part drew out the respondent’s attitude toward twenty statements through the five point Likert scale. Each statement represented a variable that is being studied in this research. Likert scale is one of the most prominent scales to researchers that are used to find the level of agreement or disagreement of the respondent toward any statement of interest. Two statistical techniques had been used to analyze the data. These were descriptive statistical analysis

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European Journal of Developing Country Studies, Vol.2 2006 ISSN(paper)2668-3385 ISSN(online)2668-3687 www.BellPress.org techniques (i.e. mean, standard deviation, frequency etc.) and multivariate statistical analysis technique (i.e. Factor Analysis). Factor Analysis is a class of procedure primarily used for data reduction and summarization. In marketing research, there may be a large number of variables, most of which are correlated and which must be reduced to a manageable level. Relationships among sets of many interrelated variables are examined and represented in terms of few underlying factors. It is an Interdependence Technique, in which an entire set of interdependent relationship is examined (Malhotra 2008). The marketing and social science literature is abundant with applications of factor analysis (Churchill 1987; Timm 1975; Urban and Hauser 1980). This widely used statistical technique is frequently employed by researchers who wish to identify a relatively small number of factors or underlying dimensions that can be used to represent relationships within a large variable set (Stewart 1981). 4. Findings and Discussions The demographic profile of the sample respondents are presented in Table 1 & 2. From Table 3 it is evident that 44% people still buy the FMCG products from the small local stores. Another 37% people like to buy those products from the groceries in the local markets. Only 17.5% of the people prefer the super/mega shops as their choice for purchasing FMCG products. Table 4 also shows that, 58% of the people go for purchasing FMCG products more than twice in a month. On the other hand, 22.4% of the people go for shopping those products twice in a month. Another 19.6% people keep only one day in a month for shopping FMCG products. Cronbach's α is a coefficient of consistency and measures how well a set of variables or items measures a single, one-dimensional latent construct. Some professionals, as a rule of thumb, require a reliability of 0.70 or higher (obtained on a substantial sample) before they will use a scale (Maccallum et al., 1996). Obviously, this rule should be applied with caution when α has been computed from items that systematically violate its assumptions. In our study the Cronbach's α value is found 0.761 (see Table 5) which is more than the standard value of 0.70. Therefore, it is assumed that the variables are very reliable for the study. Result in Table 6 shows that the KMO value is more than .60 (actual is .684) which authenticates the adequacy level of sample as tested by the KMO and Bartlett's Test. So obviously the data support the use of factor analysis and suggest that the data may be grouped into a smaller set of underlying factors. Moreover the significance value of Bartlett's Test of Sphericity is less than .05 (actual 0.00). Clearly the Bartlett value has to be significant as for expecting relationships between the variables and if a factor analysis is going to be appropriate. 5. Analysis From the study, it was found that eight factors are responsible for altering consumers’ preference from the predetermined FMCG brands while they perform the actual shopping at the retail store. Those factors are Sales Promotion, Unavailability of Brand, Time Constrain, In-Store TVC, Variety Seeking Behavior, Product Features, End of Aisle Display and Product Convenience (see Table 7). Those eight factors explain almost 64.065% variance in the data. Among them the leading factor, Sales Promotion influence mostly in altering consumer brand choice with an Eigenvalue of 3.885 and able to explain 19.426% variance. Other leading factors are Unavailability of Brand (Eigenvalue 1.773), Time Constraints (Eigenvalue 1.455) and In-Store TVC (Eigenvalue 1.298). Unavailability of Brand means the out of stock situation of any particular brand. Time Constraints implies the allocation of limited time by consumer for shopping particular product. These three factors can explain 8.867%, 7.277% and 6.490% variance in data respectively. Rest four factors are presented in a descending order in Table 7 based on respective Eigenvalues. The study has selected the factors which are being extracted for having Eigenvalues over 1. Several more accurate methods for retaining factors are often grouped under the rubric of ‘rules of thumb’ (Gorsuch 1983; Zwick & Velicer 1986), among which the scree test is readily available, frequently used, and usually provides satisfactory results. The Cattell-Nelson-Gorsuch (CNG) scree test (Gorsuch, 1983) gives a statistical test for this point and contended that with principal components analysis the scree test usually produces cutoffs near Eigenvalue = 1.00. Here, the cumulative variance of the study is 64.065%. The rotated factor loadings matrix summarizes the structure by indicating which variables associate primarily with which factors. Based on the notion of ‘simple structure’ (Thurstone, 1947), here the word ‘structure’ is to denote the identification for each variable of the factor with which it is primarily associated, these variables have been classified with specific factor loadings into 8 specific factors. The cumulative variance confirms that the study result is quite acceptable

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European Journal of Developing Country Studies, Vol.2 2006 ISSN(paper)2668-3385 ISSN(online)2668-3687 www.BellPress.org as the extracted factors should account for at least 60 percent of the variances. DeVellis (2003) claimed that a value of .70 as the lowest acceptable bound for Cronbach's alpha, although some claim it may decrease to .60 in exploratory research (Hair et al., 1998). Therefore, considering the evidence, the revised model of factors influencing the purchase decision of FMCG products in Bangladesh is presented in figure 2. 6. Recommendations Some recommendations are prescribed below based on the findings of this study. These recommendations will be worthy if aligned with FMCG Company’s marketing decision making. FMCG companies should focus more on the small local stores and groceries for their promotional activity, combining both the push and pull strategies. Consumers of Bangladesh still prefer those shops over super/mega shops for FMCG product purchasing as it is evident from this research finding (see Table 3). Since most of the consumers purchase FMCG products more than twice in a month, FMCG companies can generate a stream of sale throughout the year. But to do so, those companies need to establish a strong market position by creating positive image among the prospective customer groups through various innovative and strategic marketing tools like promotional events, sponsorship, viral marketing etc. Sales Promotions are found to be the most effective tools for generating sale of FMCG’s. Companies may develop well defined, objective based, short term sales promotion strategies to gain market advantage over their competitors. Focus has to be given both on sales promotion and trade promotion. Sales person should be well chosen and trained, since they play a vital role in facilitating consumer choice decision at the time of actual purchase of FMCG products from the shop. An effective distribution system is the most significant issue in product marketing. Since it was proved through the factor Unavailability of Brand that the consumer generally switches to another brand if their preferred brand is not available at the time of purchase, the FMCG companies have to ensure the distribution of their products along with other promotional activities to the door step of the consumer. A perfect synchronization between promotional activities and distribution is very crucial in this regard. Another important factor that influences the FMCG consumers is Time Constrain. FMCG products are low involvement in nature, so consumers want to spend the least amount of time possible for purchasing them. Consumers want to spend the majority of their time and effort to high involvement products. Point of purchase advertisements like buntings, cutups, posters, stickers is very much applicable in these cases for gathering consumer attention at the last moment. And in case of low involvement products, grabbing the attention may sometime increase the chance of sales. Some innovations have to be come out from the FMCG companies to make this marketing tool more attractive to the consumer. Besides these factors, there are other factors i.e. In-Store TVC, Variety Seeking Behavior of the Consumers, Product Features, End of Aisle Display and Product Convenience which merit the FMCG companies’ attention. For last few years, markets of FMCG products are experiencing different reformations. The increasing threat posed by generic products, pricing pressure through initiatives such as Everyday Low Pricing, and the evergrowing options for consumers have made the marketers’ task tough. In some categories, formerly popular brands have been deleted, squeezed between the category leader and lower cost competitors. Therefore, the FMCG industry will find a better development opportunity if it uses the findings of this study as the input of their decision making strategies. 7. Limitations and Directions for Further Research Like all research, there were some constraints that were faced during this study. Respondents do not actually know what they really feel about the area of the study. It was difficult to extract the answer required without actually experiencing it. Respondents were busy enough with their own lives and jobs. They do not have a lot of time for analyzing the real experience of that specific situation of this study. This study can provide an insight into the future either by asking people what they plan to do or extrapolating from past or present trends. There are problems with this approach however. People often do not know what they will do in the future and what they think they will do is often very different from what they actually do. Also, in a fast-changing environment, extrapolation from the past is highly unreliable (Makridakis, 1996).

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European Journal of Developing Country Studies, Vol.2 2006 ISSN(paper)2668-3385 ISSN(online)2668-3687 www.BellPress.org The majority of the samples in this study were students. Many arguments exist, both in favor and against the convenience samples containing students. Several authors, including Beltramini (1983), Oakes (1972) have specified the dangers of using student samples in research. They have commonly mentioned threats to external validity as their prime concern, arguing that students are atypical of the general population; therefore any findings based on student samples may not be generalizable to other populations (Cunningham, Anderson Jr. and Murphy 1974). Still, some scholars diverge on this concern. Oakes (1972) argue that such arguments are unfounded because regardless of what population is sampled; generalization can be made only with caution to other populations. As generalization of the finding with student subjects is limited; this research, having majority of the samples as students, may experience the same consequences. Thus, future research should consider better samples, combining more people with occupations other than students in an attempt to replicate the model developed in this study that would allow for greater external validity. Only generic FMCG product class was considered for evaluation in this study. Bur there are many types of FMCG products within this class, each with their own different characteristics. For example, there are highly perishable FMCG products i.e. meat, fruits and vegetables, dairy products, baked goods etc. There are also FMCG products having high turnover rates i.e. alcohol, toiletries, pre-packaged foods, soft drinks, cleaning products etc. Future studies must explore how the proposed model in the present research works for a wider range of FMCG product types, situations, settings, and populations. A finding’s failure to replicate its results is evidence of its limit to the generalizability of the relation. However, when a finding does replicate its results, the scope of the relation is extended. According to a recent study by the Nielsen Company, ‘aspirational’ products i.e. breakfast cereals, cold cream, fragrances and chocolates will drive the future of the consumer products industry in the neighboring country India. As the present research took place in Bangladesh, this future trend will certainly be of an impact in here. To capture the business opportunities and lead in these markets, marketers must make decisions based on an indepth understanding of the competitive environment and consumer demands in their own sector (Moodi, 2005). Moreover, key impulse products such as biscuits, chocolates, salty snacks and confectionery, which are essentially unplanned purchases for instant gratification, are clocking high double-digit growth rates and rapid increase in retail presence (Mukherjee, 2011). Further research should offer enough variety in terms of FMCG product types in addition to the generic FMCG product class used here. Especially, certain FMCG product types i.e. aspirational FMCG products, key impulse FMCG products, highly perishable FMCG products, high turnover FMCG products etc. deserve more focused, extensive empirical future studies on Bangladeshi context. References Agnew, J. (1987), "POP Displays are Becoming a Matter of Consumer Convenience," Marketing News, 9: 14. Beltramini, R. F. (1983), “Student Surrogates in Consumer Research,” Journal of the Academy of Marketing Science, 11 (Fall): 438-443 Blattberg, R. C., Eppen, G. D. et al. (1981), "A Theoretical and Empirical Evaluation of Price Deals For Consumer Nondurables," The Journal of Marketing, 45(1): 116-129. Chintagunta, P. K. (1998), "Inertia and Variety Seeking in a Model of Brand-Purchase Timing," Marketing Science, 17: 253-270. Churchill, Gilbert A., Jr. (1987), Marketing Research: Methodological Foundations, Chicago, Illinois: The Dryden Press, 756-777. Cunningham, W. H., Anderson, T. Jr. and Murphy, J. H. (1974), “Are Students Real People?” Journal of Business, 47 (July): 399-409 DeVellis, R. F. (2003), Scale Development: Theory and Applications, Sage Publications, Inc. Gorsuch, R. L. (1983). Factor analysis, 2/E Hillsdale, NJ: Erlbaum. Givon, M. (1984), "Variety Seeking Through Brand Switching," Marketing Science, 3(1): 1-22. Givon, M. and Horsky, D. (1990), "Untangling the Effects of Purchase Reinforcement and Advertising Carryover," Marketing Science, 9(2): 171-187. Hair, J. F., Anderson, R. E. et al. (1998), "Multivariate Data Analysis Upper Saddle River." Multivariate Data Analysis, 5/E, Upper Saddle River. Jeuland, A. P. (1979), "Brand Choice Inertia as One Aspect of the Notion of Brand Loyalty," Management

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European Journal of Developing Country Studies, Vol.2 2006 ISSN(paper)2668-3385 ISSN(online)2668-3687 www.BellPress.org Science, 25(7): 671-682. Kahn, B. E., Kalwani, M. U. et al. (1986), "Measuring Variety-Seeking and Reinforcement Behaviors Using Panel Data," Journal of Marketing Research, 23(2): 89-100. Kahn, B. E. and Raju, J. S. (1991), "Effects of Price Promotions on Variety-Seeking and Reinforcement Behavior," Marketing Science, 10(4): 316-337. Hamid, M.A., Akter, M.B. and Mazumder, M.H., (2008), ‘Characteristic features of the corporate advertisements in Bangladeshi print media”, Journal of Business and Technology (Dhaka), 03(05), 63-73. Kollat, D. T. and Willett, R. P. (1967), "Customer Impulse Purchasing Behavior," Journal of Marketing Research, 4(1): 21-31. Krishna, A. (1991), "Effect of Dealing Patterns on Consumer Perceptions of Deal Frequency and Willingness to Pay," Journal of Marketing Research, 28(4): 441-451. Lattin, J. M. (1987), "A Model of Balanced Choice Behavior," Marketing Science, 6(1): 48-65. Lattin, J. M. and McAlister, L. (1985), "Using A Variety-seeking Model to Identify Substitute and Complementary Relationships Among Competing Products," Journal of Marketing Research, 22(3): 330-339. Lee, A. Y. and Labroo, A. (2004), “Effects of Conceptual and Perceptual Fluency on Affective Judgment”, Journal of Marketing Research, 41(2), 151-165. Lindquist, J. D. and Sirgy, J. S. (2008), “Shopper, Buyer, and Consumer Behavior,” 2/E, Biztranza, New Delhi. MacCallum, R. C., Browne, M. W. et al. (1996), "Power Analysis and Determination of Sample Size for Covariance Structure Modeling," Psychological Methods, 1(2): 130. Majumdar, R. (2004), Product Management in India, 2/E, PHI Learning. pp. 26–28. ISBN 9788120312524. http://books.google.com/?id=ESJzaCJE3fQC&pg=PA26&dq=what+is+fmcg&q=what%20is%20fmcg Makridakis, S. (1996), "Factors Affecting Success in Business: Management Theories/Tools Versus Predicting Changes," European Management Journal, 14(1): 1-20. Malhotra, N. K. (2008), "Marketing Research: An Applied Orientation", 5/E, Pearson Education India. Morrison, D. G. (1966), "Testing Brand-Switching Models," Journal of Marketing Research, 3(4): 401-409. Neslin, S. A., Henderson, C. et al. (1985), "Consumer Promotions and the Acceleration of Product Purchases," Marketing Science, 4(2): 147-165. Oakes, W. (1972), “External Validity and the Use of Real People as Subjects,” American Psychologist, 27: 959962 Park, C. W., Iyer, E. S. et al. (1989), "The Effects of Situational Factors on In-Store Grocery Shopping Behavior: the Role of Store Environment and Time Available for Shopping," The Journal of Consumer Research, 15(4): 422-433. Point-of-Purchase Advertising Institute (1978), POPAI/DuPont Consumer Buying Habits Study: Special Report, New York: POPAI. Russo, J. E., Medvec, V. H. et al. (1996), "The Distortion of Information During Decisions." Organizational Behavior and Human Decision Processes, 66(1): 102-110. Shoemaker, R. (1979), "An Analysis of Consumer Reactions to Product Promotions" in Educators’ Conference Proceedings, Chicago: American Marketing Association, 244-248. Stewart, D. W. (1981), "The Application and Misapplication of Factor Analysis in Marketing Research," Journal of Marketing Research, 18(1): 51-62. Thurstone, L. L. (1947), "Multiple Factor Analysis," University of Chicago Press: Chicago. Timm, N. H. (1975), “Multivariate Analysis, With Applications in Education and Psychology,” Brooks/Cole. Urban, G. L. and Hauser, J. R. (1980), “Design and Marketing of New Products”, Prentice-Hall. Wagner, U. and Taudes, A. (1986), "A Multivariate Polya Model of Brand Choice and Purchase Incidence," Marketing Science, 5(3): 219-244. Wilson, R. D., Newman, L. M. et al. (1979), "On the Validity of Research Methods in Consumer Dealing Activity: An Analysis of Timing Issues," College of Business Administration, Pennsylvania State University. Winer, R. S. (1986), "A Reference Price Model of Brand Choice for Frequently Purchased Products," The

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European Journal of Developing Country Studies, Vol.2 2006 ISSN(paper)2668-3385 ISSN(online)2668-3687 www.BellPress.org Journal of Consumer Research, 13(2): 250-256. Zwick, W. R., & Velicer, W. F. (1986). “A Comparison of Five Rules for Determining the Number of Components to Retain”. Psychological Bulletin, 99:432-442. Web Resources Brand career glossary (n.d.), Brand channel, viewed on 12 December 2010, http://www.brandchannel.com/education_glossary.asp Business Standard (2004), Pakistan, Bangladesh pip India in FMCG race: AC Nielsen survey, viewed on 15 May 2011, http://www.business-standard.com/india/news/pakistan-bangladesh-pip-india-in-fmcg-race-ac-nielsensurvey/199287/ Food and safety promotion board (2005), Business 2000, viewed on 12 December 2010 http://www.business2000.ie/pdf/pdf_8/fspb_8th_ed.pdf Mukherjee, W (2011), ‘Aspirational goods to drive FMCG growth: Study’, The Economics Time, 25 February 2011, Viewed on 20 May 2011, http://articles.economictimes.indiatimes.com/2011-0225/news/28634134_1_consumer-products-indian-fmcg-aspirational-products Moodie, M (2005), ‘FMCG business continuing to boom in China says new ACNielsen report’, The Moodie Report, Viewed on 19 May 2011, http://www.moodiereport.com/document.php?c_id=1178&doc_id=8001 Perner, L. n.d., Introduction to marketing, viewed 28 January 2011, http://www.consumerpsychologist.com/marketing_introduction.html Positive Bangladesh (2011), US MNCs May Expand Business in Bangladesh Market, viewed on 18 May 2011, http://positivebangladesh.wordpress.com/category/business-development-at-bangladesh/ Rashid, M 2010, ‘Investing in Bangladesh’, The Daily Star, 30 May 2010, viewed on 28 April 2011, http://www.thedailystar.net/newDesign/news-details.php?nid=140571 Richard P. Gee (n.d.), Customer is King, Viewed on 10 February 2011, http://www.geewiz.co.nz/downloads/Customer_is_King.pdf Parag Parikh Financial Advisory Services Limited (n.d.), FMCG Sector: Indian Companies Going Conglomerate, Viewed on 14 April 2011, http://www.moneycontrol.com/news_html_files/news_attachment/2008/IC_FMCG_Sector_PPFAS_Sep08.pdf Table 1: Respondents’ Demographic Profile (I)

Gender Male Female

Frequency 74 69

Total

143

Education Level Below SSC SSC HSC Graduate Masters Above Masters 100 Total 143 100 Total Table 2: Respondents’ Demographic Profile (II) (%) 51.7 48.3

Age < 15 Years 16 - 25 Years 26 - 35 Years 36 - 45 Years > 45 Years

Profession Govt. Service Service to Local Private Company Service to MNC Professionals Teacher Business Student Others Total

Frequency 3 82 33 15 10

Frequency 4 26 5 4 6 4 83 11 143

(%) 2.8 18.2 3.5 2.8 4.2 2.8 58.0 7.7 100

8

(%) 2.1 57.3 23.1 10.5 7.0

Frequency 6 6 52 58 16 5 143

Income Range < 5,000 TK 5,001 - 10,000 TK 10,001 - 15,000 TK 15,001 - 20,000 TK 20,001 - 25,000 TK 25,001 - 30,000 TK Above 30,000 TK

Frequency 81 22 5 15 6 8 6

(%) 56.6 15.4 3.5 10.5 4.2 5.6 4.2

Total

143

100

(%) 4.2 4.2 36.4 40.6 11.2 3.5 100


European Journal of Developing Country Studies, Vol.2 2006 ISSN(paper)2668-3385 ISSN(online)2668-3687 www.BellPress.org Table 3: Respondent's Store Preference Store Choice Small Local Store

Frequency 64

Percent (%) 44.8

Grocery in Local Market

54

37.8

Super Store

25

17.5

Total

143

100.0

Table 4: Respondent's Purchase Frequency Occurrence Frequency Once in a Month 28 Twice in a Month 32 More than Twice in a Month 83 Total 143 Table 5: Reliability Statistics

Percent (%) 19.6 22.4 58.0 100.0

Cronbach's Alpha N of Items 0.761 20 Table 6: KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Approx. Chi-Square Bartlett's Test of Sphericity Df

0.684 522.265 190

Sig.

0.000

Table 7: Factors Affecting the Consumers to Switch from the Predetermined Brands While Actually Shopping FMCG in the Retail Outlet Factor Number 1 2 3 4 5 6 7 8

Factorâ&#x20AC;&#x2122;s Name

Eigenvalues

Sales Promotion Unavailability of Brand Time Constrain In-store TVC Variety Seeking Behavior Product Features End of Aisle Display Product Convenience

3.885 1.773 1.455 1.298 1.185 1.109 1.089 1.017

9

Variance (%) 19.426 8.867 7.277 6.490 5.926 5.545 5.447 5.086

Cumulative Variance (%) 19.426 28.293 35.570 42.060 47.986 53.532 58.978 64.065


European Journal of Developing Country Studies, Vol.2 2006 ISSN(paper)2668-3385 ISSN(online)2668-3687 www.BellPress.org

1. 2. 3. 4. 5. 6. 7. 8. 9. 10.

Influential Variables Sales Promotion Point of Purchase Advertising Product Feature Product Display Competitive Pricing Dealing Pattern Ease of Recognition End of Aisle Display In-Store TVC Salesperson Influence

11. 12. 13. 14. 15. 16. 17. 18. 19. 20.

Influential Variables Unavailability of Preferred Brand Attractive Packaging Convenience Variety Seeking Tendency of Consumer Influence of Other Customers Store Environment Time Constrain Cash Constrain Delightful Mind of Consumer Level of Involvement of Consumer

Purchase Intention (for FMCG)

Purchase Decision

Figure-1: Conceptual Framework of Factors Influencing the Purchase Decision of FMCG Products

10


European Journal of Developing Country Studies, Vol.2 2006 ISSN(paper)2668-3385 ISSN(online)2668-3687 www.BellPress.org

Factor-1: Sales Promotion Variance Explained 19.426%

Factor-2: Unavailability of Brand Variance Explained: 8.867%

Factor-3: Time Constrain Variance Explained: 7.277%

Factor-4: In-store TVC Variance Explained: 6.490%

Purchase Intention (for FMCG) (Total Variance Explained: 64.065%)

Purchase Decision

Factor-5: Variety Seeking Behavior Variance Explained: 5.926%

Factor-6: Product Features Variance Explained: 5.545%

Factor-7: End of Aisle Display Variance Explained: 5.447%

Factor-8: Product Convenience Variance Explained: 5.086%

Figure-2: Revised Framework of Factors Influencing the Purchase Decision of FMCG Products

11

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