African Journal of Agricultural Marketing Vol. 2 (1), pp. 064-070, March, 2014. Available online at www.internationalscholarsjournals.org © International Scholars Journals Full Length Research Paper Why is comprehending client mind-set toward 4Ps marketing mix essential? The case of the livestock input industry in Indonesia Edward Kokose and Cornelius Addos 1 Department of Business Administration, National Central University, Taiwan. 2 Faculty of Agriculture, Sebelas Maret University, Indonesia. Accepted 25 February, 2014 One of the main issues of agricultural development in Indonesia was marketing of agricultural products. It was not only due to the weakness of agricultural marketing policy, but also lack of research, particularly research related to the costumer’s attitude of marketing mix. Understanding of costumer’s attitude of marketing mix was really important. Many literatures indicated that one of the advantages of this was to design the marketing mix strategy. The main purposes of this study were, first, to evaluate the customer’s attitude toward marketing mix among distinct market segments of livestock input industry, and second, to examine the influence of demographic variables on customer attitude toward marketing mix. The methodology used in this study was survey method through distribute of questionnaire to respondents. Respondent of this study was poultry livestock farmer who have used company feed product and kept livestock in Java Island, Indonesia. The findings of this study revealed that, first, the three market segments were perceived differently and second, there was no significance difference among various demographic variables. This finding showed the importance of market segmentation to determine the appropriate strategy. Eventually, this research provided guidance for agribusiness managers to investigate deeply the customers understanding, preferences and perception. Key words: Customer’s attitude, marketing mix, livestock input industry. INTRODUCTION Many authors argue that understanding the customer attitude toward 4Ps (product, price, place and promotion) marketing mix is important. In case of Indonesia as a big developing country in Asia, the issues of customer attitude toward 4Ps of agribusiness particularly in livestock input industry is crucial. The question is why un- derstanding the customer attitude toward 4Ps marketing mix is important in livestock input industry? Constantinides (2006) emphasizes that marketing mix is a framework of the dominant marketing management *Corresponding author. E-mail: edward_kokose@gmail.com . Tel: +886-3-876-9654 paradigm to identify market development, environmental changes and trends. Several studies confirm that the 4Ps is indeed the trusted conceptual platform of practitioners dealing with operational marketing issues (Romano and Ratnatunga, 1995; Coviello et al., 2000). The wide acceptance of the 4Ps among field marketers is the result of their profound exposure to this concept during college years, since identifying the 4Ps as the controllable parameters is likely to influence the consumer buying process and decisions (Brassington and Pettitt, 2003; Soekartawi, 2005a). The marketing practitioners in livestock industries, particularly on the input suppliers to farmer producers consider the 4Ps as the powerful toolkit of marketing strategy. The input suppliers play an important role in the Kokose & Addos 064 agribusiness system which provides farmers and ranchers with the feed, seed, credit, equipment, etc. (Bierlien and Woolverton, 1991). In reality, the farmer producers are not homogeneous. They differ on dimensions such as sizes, management styles, location, production practices, and so forth. In efforts to segment the farm market, farms are often grouped by criteria such as crops grown, type of technology employed, and region of production (Rosenberg and Turvey, 2001). Segmentation is an important element of market planning. It is, in fact, at the very crucial of developing a thorough, well-reasoned, competitive advantage achieving strategic plan for a product and a business unit (Sudharsan and Winter, 1998; Soekartawi, 2005a). Successful serving targeted customers involves first, segmenting the market into smaller more homogeneous customer groups, profiling these groups, then deciding which customer’s segments to pursue, and then developing the 4Ps marketing mix to best serve the chosen target customers (Alexander et al., 2005). This study is to evaluate different segments of customers’ attitude toward 4Ps. Using sales classes as a measurement of farm size, this study classifies customers into three segments: small, middle and large. In fact, the study related to customer attitude in the farmer producer has not been sufficiently conducted. Therefore, two research questions guide this study: (1) Do customer’s attitude toward marketing mix among market segments is perceived differently? and (2) Do demographic variables influence the customer attitude toward marketing mix? It is expected that this research would provide recommendation for livestock input suppliers to develop greater understanding of how to serve existing and potential customer based on 4Ps concept for a basis to meet profitability of their business. LITERATURE REVIEW Several studies measuring customer attitude towards marketing mix have been carried out in industries and emerging nations (Gaski and Etzel, 1986; Wee and Chan, 1989; Chan et al., 1990; Bhuian and Kim, 1999; Lysonski et al., 2003; Chan and Cui, 2004). A significant study in measuring consumer sentiments towards marketing practices was carried out by Gaski and Etzel (1986, 2005). Other researchers Wee and Chan (1989) found that the pricing strategies and advertising appeals must also be adapted to suit the consumer’s needs and tastes. The influence of demographic variables on attitudes towards marketing was found that the less educated, the lower income group, and those with no jobs or less privileged jobs were most hostile towards marketing. Bhuian and Kim (1999) examined the influence of country origin toward marketing mix element and found that consumers prefer most the marketing mix element related to the product of Japan and USA. Marketing strategy for industrial market Harbor et al. (2006) pointed out that the market interaction between agricultural input industry and farmer producers is similar to that observed in a B2B environment. In this interaction, farmer producer is the buyer and agricultural input industry in this case livestock input industry is the industrial market. Thus, understanding the drivers and determinants of this transformation process is critical to a successful marketing strategy to serve the farmer producers of the future (Boehlje, 1992). The ability of agricultural input suppliers to serve farmer producers depends on the effective exchange of information between firms and consumers. Insufficient information may leave farmer producers exposed to inappropriate products and can limit firms' ability to respond to farm producers' needs (Tripp and Pal, 2000). Many marketing researchers have broadly argued marketing strategy to be a concept built on robust platform of segmentation, targeting and positioning (Ferrell et al., 2002; Walker et al., 2001). Marketing strategy requires decisions about the specific target of customers. Besides, marketing mix may be developed to target market by positioning it suitably in a superior way. In this context, the study of the effectiveness of the marketing tools is essential for an appropriate marketing strategy. Appropriateness of marketing strategies may be viewed as the congruence of market offerings of a set of products and its corresponding consumer perception among its target segment. More the target segment is able to understand and believe the cues (Richardson et al., 1994) communicated by the firms through marketing mix, more is the effectiveness of the marketing strategies. Recently, Constantinides (2006) reviewed the criticisms on the 4Ps marketing mix emanating from industrial market area. He mentioned most researchers agree that industrial market is indeed different from consumer marketing in a number of aspects like the formalized decision making procedures, the buying practices and rationality of choices and the special character of the industrial customer. Long term relationships, based on empathy, mutual benefits and co-operation (Flint et al., 1997), understanding of customer’s needs and service (Shaw, 1995) are other important success factors. Market segmentation in the agricultural industry In industrial marketing, adoption of strategic planning as central to business operations today leads to a key di- rection for segmenting industrial markets (Constantinides, 2006). The formal grouping of cus-tomers/potential customers based on similarities in their strategies 065 Afr. J. Agric. Mark. (Sudharsan and Winter, 1998). Griffith and Pol (1994) reported a successful use of firm demographic data for segmenting industrial markets. Laughlin and Taylor (1991) proposed that industries can be classified based on their respective concentration ratios and product customization requirements. They suggest that the classification be used as the basis for segment selection decisions. In the agribusiness market as an industrial market, customer segmentation is also a way for better understanding customer preferences for products, services, and information which are important to their industries. The customer segmentation is based on a two-dimensional characterization of the producer market. The characterization is defined in terms of: 1) size measured by gross sales, and 2) purchasing behavior (Boehlje, 1992). Furthermore, he argued that market segmentation frequently consists of grouping buyers into segments according to sales classes and then developing marketing strategies to serve the different segments. Each of the segments is different; for instance in terms of size, type of technology, farm management and so on (Gloy and Akridge, 1999). The process of segmentation is different from targeting (choosing which segments to address) and positioning (designing an appropriate marketing mix for each segment). The overall intent is to identify groups of similar customers and potential customers; to prioritize the groups to address; to understand their behavior, and to respond with appropriate marketing strategies that satisfy the different preferences of each chosen segment (Sengupta and Chattopadhyay, 2006). Characteristic of farmer producers This study used customer segmentation based on sales classes range divided into three classes: small, medium and large. These three classes have different character- istics in terms of buying behavior, farm management, type of technology and so forth. Harbor et al. (2006) observed that in many instances, smaller farms behave like retail consumers. Relatively speaking, they wield little individual market power. On the other hand, larger farms have the ability to interact with input and output markets in a more business-like manner, taking advantage of powers of negotiation, economies of scale, and increased market access. As a result, the relationship between agribusinesses and their commercial farm customers is much different from that between agricultural firms and those operations that fit the historical farm profile. Most investigations of small farm characteristics combine two or more of these classifications to arrive at a more limited and conclusive definition. However, small farms have been generally described as farms with limited resources, farms with a small volume of farm product sales, family farms, retirement farms, and part- time farms (Lewis, 1978). RESEARCH METHODOLOGY The data of this study was collected from customer of PT Charoen Pokphand Indonesia (CPI). CPI is one of Multinational Companies (MNCs) in agribusiness whose core business is feed mill manufacturing. The headquarter of CPI is in Thailand, and its subsidiaries are located in several countries, such as Indonesia, Malaysia, China, Korea, Singapore, Taiwan, Hong Kong, Myanmar, Turkey and Portugal. The sample of this study was the farmers who have used CPI’s products and kept livestock in Java Island, Indonesia. Sample The sampling frame was provided by CPI’s customer database of livestock in Java Island, Indonesia. Using random sampling method this research selected 600 customers. There were three sizes of customers: small (less than 500 ton per year sales), medium (500 up to 1000 ton per year sales) and large (more than 1000 ton per year sales). Classified into this category, there were 227 respondents of large size, 182 respondents of medium size and 191 respondents of small size. Totally, 600 questionnaires were distributed to respondents. The response rates were 50% for small size, 47% for medium size, and 53% for large size. Total usable questionnaires were 297, consisting of 95 small size customers, 85 medium size customers, and 120 large size customers. The samples were selected using the following formula (Djarwanto and Pangestu, 1996): P (1 − P ) 1 , 96 2 E  1 , 96 → N  P (1 − P ) N E Where: N = Total sample p = Percentage of sample proportion (in between 0 - 1) P = Total population E = Error (<10 %). Measurement The questionnaire was developed through two steps. In the first step, the questionnaire was adopted from two studies which included a measurement of consumer attitudes toward marketing mix. The first study was developed by Gaski and Etzel (1986), about the measurement of customer sentiment toward marketing mix variables. The second study was by Bhuian and Kim (1999) about measuring customer attitude toward marketing mix element pertaining to foreign products in an emerging international market. This study adopted 17 item questions from Gaski and Etzel (1986) and 5 items from Bhuian and Kim (1999). We made the other 10 questions to reflect the characteristics of agriculture product. Thus, totally 32 items were used in this questionnaire for the study. In the second step, several in depth interviews were conducted with General Managers and the Marketing Managers of CPI to explore the research area and clarify terminology. After the in depth review, several items were revised to reflect the thinking characterist ic of product and local people. The questionnaire was divided into two parts. The first part contained demographic characteristics of the respondents such as province, gender, age and education. The second part contained attitude of customer toward marketing mix. A total of 32-items were used on a five-point Likert-point scaled with the end points rating from very disagree (1) to very agree (5). Table 1. Respondent’s profiles. Customer sizes Number of respondents by province Total West Central East Small (sales: less than 500 ton/year) 19 38 38 95 Medium (sales between 500 - 1000 ton/year) 15 32 35 82 Large (sales more than 1000 ton/year) 54 24 42 120 Total 88 94 115 297 Note: Exchange rate 1 ton = 400 USD. Table 2. Reliability for component after purification. Attribute Items after purification Chronbach α Product 1,2,3,4,5,6,7,8,9,10 0.779 Price 1,2,3,4,5 0.726 Place 1,3,4,6,7 0.707 Promotion 1,2,5,6,7,9,10 0.651 Data analyses Respondent’s demographic profile To provide a better insight into the participants, respondent’s demographic profile including province, gender, age, and education were analyzed. The province area was found West Java 29.6%, Central Java 31.6% and East Java 38.7%. The gender composition was male respondents (75.8%) and female respondents (24.2%). The age composition of respondent was 20.5% for age range less than 35 years old; 63.6% for age range 35 - 50 years old and 15.8% for age range more than 50 year old. As for the level of education, the highest level was senior high school (64.3%), the second was bachelor degree (16.2%), then followed by junior high school (11.8%) and last was master’s degree (7.7%). In addition, the respondent’s profile about customer size shows us the information dispersion of customer on each province and size. The data shows that West Java has highest number in the large farmer (54) more than small (19) and medium (15). Central Java has highest number in the small farmer (38). Meanwhile, East Java has a number customer with no striking differences among customer size (Table 1). Data accuracy analysis Reliability and validity were tested for data accuracy analysis purpose. Reliability test criteria included item-to-total correlation value of 0.3, Cronbach α value of 0.6. As can be seen in Table 2, all the values were above the required threshold values. Thus, the results provided evidence of reliability. The detailed results of the items retained for further analysis after purification using Cronbach’s α value (items retained after purification are shown in the Appendix). After purification of the items, acceptable reliability was demonstrated for each of the marketing mix variables: 0.779 for product, 0.726 for price, 0.707 for place/distribution, and 0.651 for promotion. For details, it is presented in Table 2. Besides reliability, discriminant validity was also tested for the scales.. Discriminability refers to the ability empirically to differentiate one construct from other constructs that may be similar, and to point out what is unrelated to the construct. This study did not use different methods of measurement, only discriminant validity could be tested. Discriminant validity can be indicated by predictably low correlations between the measure of interest and other measures that are supposedly not measuring the same variable or concept. To verify discriminant validity, correlations among the four scales were obtained for the combined sample. According to Gaski and Etzel (1986), if α coefficient considerably higher than its correlations with other scales, discriminant validity is upheld. Table 3 shows the correlation between the scale categories. The values, which range from 0.092 - 0.459, clearly indicate that each scale has α coefficient adequately higher than its correlations with other scales. This shows that discriminant validity of the scale is upheld. RESULT AND DISCUSSION One-way Analysis of Variance (ANOVA) was conducted to compare mean consumer attitude towards marketing mix variables across various demographic variables. The result revealed that there is not significant difference among various demographic variables such as provincial area, gender, age as well as educational level. These results indicated that demographic profile does not influence the customer attitude toward 4Ps. Meanwhile, One-way ANOVA was conducted to examine differences in attitude among groups customer size. Mean score of attitude was used to examine the differences. As shown in the Table 4, customer attitude toward overall attributes marketing mix was perceived differently among customer sizes (F = 61.279, p < 0.01). Furthermore, customer attitude toward each attribute marketing mix was varied among customer sizes, in the product attribute (F = 28.545, p < 0.01); Price (F = 23.109, p < 0.01); place (F = 21.144, p < 0.01) and promotion (F = 19.131, p < 0.01). Those findings revealed that there were differences in customer attitude among three distinct segments. The Kokose & Addos 066 Table 3. Correlation between scale categories. Scale categories Product Price Place Promotion Product 1 0.171 0.269 0.459 Price 1 0.092 0.247 Place 1 0.355 Promotion 1 Table 4. One-way ANOVA of customer attitude. Attributes Customer size Mean SD F value a Post Hoc test b Product Small 3.50 0.386 28.545** S