An analysis of factors affecting purchasing decisions for natural fresh fish and processed fish in the upper northeastern region of thailand

Nội dung text: An analysis of factors affecting purchasing decisions for natural fresh fish and processed fish in the upper northeastern region of thailand

1. AN ANALYSIS OF FACTORS AFFECTING PURCHASING DECISIONS FOR NATURAL FRESH FISH AND PROCESSED FISH IN THE UPPER NORTHEASTERN REGION OF THAILAND Sakkarin Nonthapot*1 ABSTRACT: This survey research aims to analyze the factors affecting purchasing decisions for fresh fish and processed fish from nature in the upper northeastern region of Thailand. A questionnaire was applied as the research tool, using a 7-point Likert scale. 420 samples were collected by employing a random sampling method. Eight variables from their answers are processed by Explanatory Factor Analysis. The eight variables are grouped as follows: 1) the factors affecting the consumption of natural fish (3 factors): physical environment factors, pricing factors, and quality factors; and 2) the factors affecting the consumption of processed fish from nature (3 factors): product factors, pricing factors, and seasonal factors. Entrepreneurs in the fresh and processed fish markets should focus on the application of the marketing mix to stimulate fish consumers and to enhance awareness about product quality and cleanliness in the distribution areas. Keywords: Fresh fish, Natural fish, Processed fish, Purchasing Decisions 1. INTRODUCTION At present, “fresh water fish in natural water resources” is regarded as an economic resource for many Thai people due to its distribution around the country. It is an ingredient in many types of food and is a source of protein that people can easily access. Freshwater fish also brings income to people in the community. For this reason, in the upper northeastern region, which is far from the sea, freshwater fish is a major resource and the rate of consumption is higher compared to the other regions in Thailand. In regard to the statistics report on Thailand’s freshwater fisheries by the Department of Fisheries (2017) overall, the quantity of fish is not certain, and during drought, the quantity of fish falls. In years in which Thailand faces abnormally hot weather, a lot of natural fish deaths occur, and this may lead to the deprivation of some fish for consumers in several areas Fig.1).( Source: Department of Fisheries (2017) 1 Indo-China Country International Trade and Economic Research S ector, Faculty of Integrated Social Sciences, Khon Kaen University, Nong Khai Campus, Thailand E-mail: sakkno@kku.ac.th
2. INTERNATIONAL CONFERENCE STARTUP AND INNOVATION NATION 579 Fig. 1. Quantity of Freshwater Fish Fishing in Thailand Freshwater fisheries might be regarded as the treasure of gross domestic product (GDP) when compared to saltwater fisheries. However, freshwater fisheries are connected to the lifestyle of people in the community by providing careers and income, especially in the northeastern region, which is the origin of Chi River, the Pong River, the Songkram River, and the Huay Luang River. The region has a population of 12 million people; therefore, freshwater fisheries are a major component in national economic development. The upper northeastern region is the source of natural fish from the Mekong River (Sompolkrang et al, 2015). Nonetheless, regarding the region’s characteristics, there are a lot of brooks, reservoirs, and dams which are the natural habitats of several types of fish. Freshwater fish are directly distributed and are also processed into products at major water resources such as Ubolratana Dam, Lam Pao Dam, and the mouth of the Songkram River. In the upper northeastern region, freshwater fish are the main product. Moreover, there are products from processed natural fish available at water resources and tourist spots; therefore, the distribution is in the form of household business. On the other hand, the variety of freshwater fish and processed fish sales in the upper northeastern region of Thailand may affect consumers’ purchasing behavior for fish but no study on the factors affecting purchasing decisions for fresh fish and processed fish from nature have been conducted in that area. However, it should be studied to assist in future government planning. 2. LITERATURE REVIEW There are various water resources in the northeastern region supporting diverse natural fish; however, there has not been any study on the characteristics and patterns of processed fish production. Songsrirote (2010) studied only the demand and supply for seasonal fresh fish in a study of the value chain for fish in Yasothon province during the years 2009-2010 based on 12 fresh fish merchants. In reality, at every water resource, there are many fresh fish and fish product merchants, but there has been no study of the patterns of the supply chain in that area except for studies on fresh fish and fish product pricing and the fish market system. Similarly, coastal fisheries in Trang province depend on the knowledge and experience of the fisherman because a stable fishery system and product distribution over many seasons depends on the quantity and quality of labor, the market system, the season, and other related food production factors (Tarasook et al, 2014). In addition, Daothong (2010) studied consumers’ purchasing intention and behavior for freshwater fish in Chao Phrom Market in Phra Nakhon Si Ayutthaya District, Phra Nakhon Si Ayutthaya Province, focusing on Nile Tilapia. Product factors, price factors, and place factors were found to be the marketing mix factors affecting consumers’ purchasing decisions at the highest level while promotion factors and physical evidence factors were found to affect their buying intention at a high level. Lastly, price factors influenced their decisions the least. Nauman et al, (1995) studied the factors influencing purchasing intention for fresh fish by surveying consumers in the northeastern region of the USA to collect marketing data about the purchasing decision for Bass, Trout, and Salmon. According to the study, the perceiving experience and preferences for products affected the consumers’ buying decision for bass, trout, and salmon. In the study of consumer attitudes in fish selection, Conte et al, (2014) demonstrated that product quality was the factor that positively influences the consumers’ purchasing decision and it leads to a change in consumer attitudes towards fish products. Ahmed et al, (2011) surveyed households in Kuala Lumpur using a questionnaire with 700 respondents and interviews and found that personal attitudes affecting Malaysian consumers’ buying decision for seawater fish comprised perceptions of seawater fish consumption, taste, and the nutrient value of fresh fish. From the aforementioned findings about purchasing decisions for fish, it is evident that several behaviors and factors influence consumer buying intention, for example, experience and preferences for bass, trout, and salmon (Nauman et al, 1995), which are important factors in the fish market. These factors
3. 580 HỘI THẢO KHOA HỌC QUỐC TẾ KHỞI NGHIỆP ĐỔI MỚI SÁNG TẠO QUỐC GIA are applied in the study of the factors influencing purchasing decision and consumption of fresh fish and processed fish from nature in the upper northeastern region of Thailand. 3. METHODOLOGY 3.1 Research methodology 3.1.1 Population and Sample Group The population comprises buyers of fresh fish and processed fish in 6 main markets in 6 provinces which are 1. Pho-Chai Market in Nong Khai Province, 2. Thetsaban Fresh Market in Udon Thani Province 3. Thetsaban Fresh Market in Khon Khaen Province 4. Thetsaban Fresh Market in Sakon Nakhon Province 5. Thetsaban Fresh Market in Kalasin Province and 6. Thetsaban Fresh Market in Nakhon Phanom Province. 3.1.2 Sample group The representatives of customers who buy fresh fish and processed fish from nature in the main 6 markets. The sample group has reliability at 95% and acceptable error at 0.05, using W.G. Cochran’s method (1953) without realization of the total population. The setup for sampling is 0.4 which is equal to a sample size of 323. However, to enhance the credibility of the data, with variations in the study area, the sample group includes 420 customers.The representatives of customers who buy fresh fish and processed fish from nature were selected by employing the accidental sampling method. The quota areas were set up as shown in Table 1. Table 1. Number of the sample buyers who buy fresh fish and processed fish from nature Fresh Market in each Province Fresh Fish Buyers Processed Fish Buyers Pho-Chai Market in Nong Khai 70 Samples 70 Samples Thetsaban Fresh Market in Udon Thani 70 Samples 70 Samples Thetsaban Fresh Market in Khon Khaen 70 Samples 70 Samples Thetsaban Fresh Market in Sakon Nakhon 70 Samples 70 Samples Thetsaban Fresh Market in Kalasin 70 Samples 70 Samples Thetsaban Fresh Market in Nakhon Phanom 70 Samples 70 Samples Total 420 Samples 420 Samples Source: From calculation 3.2 Tools and Sampling A Likert Scale questionnaire was used as the data collection tool to elicit opinions about buying decisions for fresh fish and processed fish as shown in Table 2. Table 2. Consumer opinions about buying decisions for fresh fish and processed fish Level of consumer opinion Score Highly influence 7 Influence 6 Small Influence 5 Neutral 4 Rarely influence 3 No influence 2 Definitely no influence 1
4. INTERNATIONAL CONFERENCE STARTUP AND INNOVATION NATION 581 3.3 Statistics and Data Analysis The statistics used in the research are 1) Mean and Percentage 2) one way ANOVA testing that there is no difference in means in each fresh market and 3) Exploratory Factor Analysis or EFA. Exploratory Factor Analysis is employed to group the factors affecting opinions. This requires cluster analysis and latent variable of the factors in the testing have to be constructed to search for the mean. The criteria are as follows: Mean 1.00 – 2.00 = Definitely no influence Mean 2.01 – 3.00 = No influence Mean 3.01 – 4.00 = Rarely influence Mean 4.01 – 5.00 = Small influence Mean 5.01 – 6.00 = Influence Mean 6.01 – 7.00 = Highly influence The processes of the Exploratory Factor Analysis are as follows: 1. Consider the primary relationships of the 8 variables 2. Factor extraction is to set the number of the latent variables from Principle Component Analysis by considering the number of factors from the Eigen Values which is over 1.00 3. Orthogonal by Varimax Rotation for better cluster analysis 4. Loading selection is the consideration of a variable’s loading which includes the highest value so that the latent variables can be grouped. Loading over 0.5 requires at least 150 samples (Stevens, 2002). If any factor is not relevant to the component, it would be excluded as a latent variable and the loading must be recalculated. 5. Give a title to the component in order to communicate the meaning of the factors. 4. RESULTS AND DISCUSSION For data analysis, the author performed a reliability test with Cronbach’s Alpha and found that the opinion level towards the factors influencing the buying decisions for natural fish has reliability atan acceptable level over 0.07 for every question. For the opinion level towards the factors influencing the buying decisions for natural fish, freshness/cleanliness has the highest influence with a mean of 6.769. Next is the cleanliness of the fish tray with a mean of 6.640, natural fish quality with a mean of 6.540, seller’s human relations with a mean of 6.392, the price of natural fish with a mean of 5.550, season with a mean of 5.342, rare natural fish with a mean of 4.795, and the least influence is distance with a mean of 4.109 Furthermore, the opinion level towards the factors influencing the buying decisions for processed fish has reliability at an acceptable level of over 0.08 for every question. For the opinion level towards the factors influencing the buying decisions for processed fish products, cleanliness has the highest influence with a mean of 6.735. Next is cleanliness of the production shop with a mean of 6.721, product quality with a mean of 6.526, seller’s human relations with a mean of 6.390, price with a mean of 4.990, rare fish with a mean of 4.828, season with a mean of 4.642, and the least influence is distance with a mean of 3.819 as shown in Table 3. Table 3. Opinion level towards the factors influencing the buying decisions for natural fish and processed fish products Aspect Mean SD Levels of Opinion Natural fresh fish Natural Fish Quality 6.540 0.857 Highly Influence Rare Natural Fish 4.795 2.018 Small Influence Freshness/Cleanliness 6.769 0.566 Highly Influence Price 5.550 1.918 Influence
5. 582 HỘI THẢO KHOA HỌC QUỐC TẾ KHỞI NGHIỆP ĐỔI MỚI SÁNG TẠO QUỐC GIA Distance 4.109 2.203 Small Influence Human Relations 6.392 0.804 Highly Influence Cleanliness of tray 6.640 0.698 Highly Influence Season 5.342 2.009 Influence Total Mean 5.767 1.384 Influence Processed fish Product quality 6.526 0.794 Highly Influence Rare Natural Fish 4.828 2.162 Small Influence Cleanliness 6.735 0.502 Highly Influence Price 4.990 2.162 Small Influence Distance 3.819 2.242 Rarely Influence Human Relations 6.369 1.026 Highly Influence Shop’s cleanliness 6.721 0.536 Highly Influence Season 4.642 2.318 Small Influence Total Mean 5.579 1.468 Influence Source: From calculation Furthermore, the opinion level towards the factors influencing the buying decisions for processed fish has reliability at an acceptable level of over 0.08 for every question. For the opinion level towards the factors influencing the buying decisions for processed fish products, cleanliness has the highest influence witha mean of 6.735. Next is cleanliness of the production shop with a mean of 6.721, product quality with a mean of 6.526, seller’s human relations with a mean of 6.390, price with a mean of 4.990, rare fish with a mean of 4.828, season with a mean of 4.642, and the least influence is distance with a mean of 3.819 (Table 3.) After the consideration of the loading for each variable towards the factors to demonstrate the priority levels of each factor. The next step, we employ the One-way ANOVA test to confirm the homogeneous data as whole 7 markets. From the F-statistics result, it found that there is no difference in means in each fresh market for natural fish and processed fish products. In addition, the research considered the variables with the highest loadings and factor extraction. Considering the number of factors from Eigen Values with Varimax Orthogonal Rotation, it was found that there are 3 eigenvalues over 1.00 as shown in table 3, which demonstrates the clusters of 3 factors (Table 4). Comparison of all factors with loadings over 0.500 to present the factor categories of variables are shown in Table 5 Table 4. Results of Initial Eigenvalues Natural Fish Processed Fish % of Cumulative % of Cumulative Component Total Component Total Variance % Variance % 1 1.95 24.45 24.45 1 2.03 25.40 24.45 2 1.68 21.05 45.51 2 1.64 20.59 45.51 3 1.13 14.13 59.64 3 1.04 12.99 59.64 4 .83 10.43 70.08 4 .87 10.97 70.08 5 .74 9.25 79.34 5 .70 8.86 79.34 6 .68 8.56 87.91 6 .65 8.16 87.91 7 .53 6.67 94.58 7 .59 7.38 94.58 8 .43 5.41 100.00 8 .44 5.60 100.00 Source: From calculation
6. INTERNATIONAL CONFERENCE STARTUP AND INNOVATION NATION 583 Table 5. Results of Factor Analysis Natural Fish Processed Fish Products Factor 1 2 3 Factor 1 2 3 C3Freshness/cleanliness .678 - - C1 Product quality .623 - C6 Human relations .748 - - C3 Product’s cleanliness .718 - - C7 Tray’s cleanliness .827 - - C6 Human relations of seller .549 - - C4 Price - .719 - C7 Shop’s cleanliness .735 - - C5 Distance - .573 - C2 Rare natural fish - .815 - C8 Season - .680 C4 Price - .573 - C1 Fish quality - - .771 C5 Distance - .763 - C2 Rare natural fish - - .756 C8 Season - .857 Source: From calculation Generally, the using of the EFA allows defining the constructs and their groupings. From Table 5 is shown the adjustment of the groupings. Regarding the factors influencing the buying decision for natural fish, it was found that factor 1 is composed of variables C3, C6, and C7; factor 2 is composed of variables C4, C5, and C6; and factor 3 is composed of variables C1 and C2. Considering each loading, every variable value is over 0.500 which demonstrates that all variables can be grouped in any factor and this leads to cluster analysis. The title of the factor reflects the entire meaning of the variables in the same group and also reflects the consumer attitudes through the levels of their opinion in their buying decision for natural fish. As consequence, the new titles for the factors are as follows: Factor 1 is composed of 3 variables which are Freshness/Cleanliness (C3), Human Relations (C6), and Tray’s Cleanliness (C7). This indicates that the product must be clean and staff must be able to attract customers. Therefore, Factor 1 is called the Physical Evidence Factor. Factor 2 is composed of 3 variables which are Cleanliness of Natural Fish (C4), Distance (C5), and Season (C5). The variables represent the product cost setting for the producer and the consumer. Therefore, Factor 2 is called the Pricing Factor Factor 3 is composed of 2 variables which are Natural Fish Quality (C1) and Rare Natural Fish (C2). Therefore, Factor 3 is called the Product Quality Factor. For the factors influencing the buying decision for processed fish products, it was found that factor 1 is composed of variables C1, C3, C6, and C7; factor 2 is composed of variables C2, C4, and C5; and factor 3 is composed of variable C8. Considering each loading, every variable value is over 0.400 which demonstrates that all variables can be grouped in any factor and entitled as follows. Factor 1 is composed of 4 variables which are Product Quality (C1), Product Cleanliness (C3), Human Relations (C6), and Shop’s cleanliness (C7). The variables indicate why the customers buy a product. Therefore, Factor 1 is called the Product Factor. Factor 2 is composed of 3 variables which are Rare Natural Fish (C3), Product’s Price (C6), and Distance (C7). The variables represent the product cost setting for the producer and the consumer. Therefore, Factor 2 is called the Pricing Factor whereas factor 3 is composed of 1 variable which is Season (C8). Therefore, Factor 3 is called the Season Factor. From the results are similar to the results of Maciel et al., (2013) who studied the application of EFA to evaluate fish consumption at a college. It is found that in the grouping for fish quality evaluation from the Rotation Matrix result with a Quality Control Stamp (SIF) and Physical Evidence. In the same direction, due to the Product Factor is the main factor influencing the consumers’ purchasing decision in the study of natural fish and processed fish products that is similar to Conte et al, (2014).
7. 584 HỘI THẢO KHOA HỌC QUỐC TẾ KHỞI NGHIỆP ĐỔI MỚI SÁNG TẠO QUỐC GIA 5. CONCLUSIONS The opinion levels for the factors influencing the buying decisions for natural fish with EFA represents three factors which are 1) the Physical Evidence Factor, 2) the Pricing Factor; and 3) the Quality Factor, including 8 variables: Natural Fish Quality (C1), Rare Natural Fish (C2), Freshness/Cleanliness (C3), Price (C4), Distance (C5), Human Relations (C6), Tray’s Cleanliness (C7), and Season (C8). In addition, the opinion levels for the factors influencing the buying decisions for processed fish with EFA represents three factors which are 1) the Product Factor, 2) the Pricing Factor; and 3) the Season Factor, including 8 variables: Product Quality (C1), Rare Natural Fish (C2), Product Cleanliness (C3), Price (C4), Distance (C5), Human Relations (C6), Shop’s Cleanliness (C7), and Season (C8). Regarding the topic of this study, entrepreneurs in the natural fish and processed fish markets address that consumers have different views based on the marketing mix (McCarthy, 1960) in four dimensions: Product, Price, Place, and Promotion. Whatever the producers or distributors’ views are, the consumers see it differently. When buying natural fish, customers regard product cleanliness, human relations, price, distance, and season, respectively. They are mainly interested in fish quality. Regarding the factors affecting consumer purchasing decisions for processed fish, the first priority is the product and cleanliness. Pricing is next, and the season is last. As a consequence, processed fish market entrepreneurs should use the marketing mix to stimulate fish consumers who are mainly interested in the product and the cleanliness of the place. These are different from the 4Ps marketing mix as previously mentioned ACKNOWLEDGMENTS This work was financially supported by the Knowledge Network Institute of Thailand andthe Thailand Research Fund. I am especially grateful to Dr.Malliga Sompholkrang, Ms. Preedaporn Suwantha, Ms.Supachaya Wongsarikan and Mr. Porowes Srichaiyo in supporting the data management. REFERENCES Ahmed, A.F., Mohamed, Z., & Mansor Ismail, M.M. (2011) Determinants of Fresh Fish Purchasing Behavior Among Malaysian Consumers. Journal of Social Sciences 3(2): 126 - 131. Cochran, W.G. (1953). Sampling Techiques. New York: John Wiley & Sons. Inc. Conte, F., Passantino A., Longo S., & Voslářová, E. (2014). Consumers’ attitude towards fish meat.Italian Journal of Food Safety 2014. 3(3):1983 DOI: 10.4081/ijfs.2014.198 Daothong, S. (2010). Behavior and Purchasing Decision on Fresh-water Fishes of Customers at Chaophrom Market in Phranakhon Si Ayutthaya District, Phranakhon Si Ayutthaya Province. Independent Study of MBA (Business Administration) Phranakhon Si Ayutthaya: Phranakhon Si Ayutthaya Rajabhat University. [In Thai]. Department of Fisheries. (2017). Fishing statistics Information and Communication Technology Center. Retrieved from stat/yearbook/data_2556/Yearbook/yearbook2013-1.5.pdf Maciel, E., Savay-Da-Silva, L.K., Vasconcelos, J.S. & Oetterer, M. (2013).Application of exploratory factor analysis to assess fish consumption in a university community.Food Science and Technology, Campinas, 33(1): 99-106. DOI: 10.1590/S0101-20612013005000016 McCarthy, J. E. (1960). Basic Marketing. A Managerial Approach. Homewood, IL: Richard D. Irwin. Nauman, F.A., Conrado, G.M., Bacon, J.R. & Manalo, A.B. (1995). Consumer Choice for Fresh Fish: Factors Affecting Purchase Decisions. Marine Resource Economics 10(2): 117-142. DOI: 10.1086/mre.10.2.42629106 Sompolkrang, M., Guayjarempanishk, P., Ueasin, N. & Nonthapot, S. (2014). Full Research Report on the Mekong River Fish Marketing System. Khon Kaen: Khon Kaen University. Songsrirote, N. (2010). Seasonal Demand and Supply for Fresh Fish in the Municipality Area of Yasothon Province. Journal of Accountancy and Management, 2 (30), 127-143. Stevens, J (2002). Applied Multivariate Statistics for the Social Sciences. Mahwah, N.J: Lawrence Erlbaum Associates. Tarasook, P., Thungwa S. & Ratanacthai, A. (2014). Factor affecting to Food Security among Coastal Artisanal Fishing Households in Trang Province. Hatyai Academic Journal. 12(1), 59-70. [In Thai].