LUẬN văn THẠC sĩ the effects of packaging attributes on vietnamese consumers purchase intention

INTRODUCTION

Research Motivation

Frazao (1995) claim that an improvement in dietary habit has high probability to avoid 20% of diseases caused by cancer, cardio-vascularity and diabetes Thus, Vietnamese consumers concern more about healthy and nutritional issues, especially, food products consuming According to Nielsen’s 2016 survey on “Health and Sensitivity to Ingredients”, almost 70% of Vietnamese buyers consider the ingredients content of the food and beverage they consumed In this sense, as one of the healthiest grains on earth, oats meal became a popular choice of Vietnamese consumers who have high health consciousness but most of oats meal sold in Vietnam market are from foreign brands with higher price than traditional grains Catching this opportunity, many Vietnamese firms started joining this potential and sustainable market with more reasonable price range for oats meal products However, according to Vietnamese buyers who consume oats meal for many years, Vietnamese oats meal product package have less detailed nutritional content than foreign products whilst that information are one of important conditions they consider when purchase oats meal As a result, not only package elements design (i.e color, graphic, font, shape, size), the informational elements (i.e product information, nutritional information) also place a significant role in attracting buyers in the store (Mutsikiwa, 2013), especially, in case of healthy food likes oats meal Additionally, due to the transformation from direct trade to self-service trade, packaging become an effective tool assist a certain product stand out among various alternative brand (Butkeviciene,

2008) Traditionally, package has 3 main role including product protection, usage supporting and message transition (Silayoi and Speece, 2004) Similarly, Rundh

(2013) indicated that products package is used as marketing communication tool to provide product information, product usage instruction to buyers

Due to package is the first thing customer see at store, thus, package design is used as an effective tool attracting buyer’s attention and can boost consumer actual purchasing at the point-of-sale (Muhammad 2014) Accordingly, marketers should determine what visual and functional package to develop a suitable marketing strategy and enhance the relationship with targeted customers based on their needs and interest consideration (Kotler and Keller, 2008) In order to transfer products message, there has more than 2 package elements are required (Chou, 2012) In low involvement products, visual attributes place an important role in attracting buyer’s intention (Silayoi and Speece, 2007) In this sense, based on product value perception and consuming volume, Hingley et al (2007) claimed that food and beverage products are considered as low-involvement products because it has low value and high volume consuming Hence, in food and beverage products consuming, buyers tend to rely on package design to evaluate its quality while making a purchase decision (Steenkamp, 1990) In addition, among many factors that influence consumer purchase intention, product packaging has become an effective tool to be different and attracting consumer attention and stimulating them to purchase a particular product (Olga & Natalia, 2006; Vidales, 1995), especially in the current self-service economy However, domestic food products cannot compete with imported one due to local enterprises have not realized that packaging is a company’s branding function and possible potential of packaging design as a brand communication tool (Vietnam Financial Magazine, 2018) Thus, from perspective of

Mr Yoon Byung Soo - Director of Lotte Mart Vietnam's product strategy department, Vietnamese products food packaging is less attractive than Thailand, China or America (Vietnam Financial Magazine, 2018) Specifically, “While the international packaging tends to simplify with courteous color, Vietnamese package is too fancy” observed Yoon Byung Soo (Vietnam Financial Magazine, 2018) Obviously, the underdeveloped use of packaging design in Vietnamese food products is a one of the main reasons that made Vietnam food products are less competitive than imported products Vietnamese Marketers need to understand that package is a crucial element to enhance point of purchase communication For above reasons, author decided to consider “The effects of packaging attributes on Vietnamese consumers Instant Oats purchase intention” as personal thesis topic.

Research Objectives

There exist very limited comprehensive practical studies have precisely analyzed packaging as a customer’s purchase communication tool in Vietnam from customer perspectives Hence, this paper aims to quantitatively analyze the impact of packaging design on consumer purchase intention then provide Vietnamese managers a better understanding about the importance of packaging in differentiating among competitors on the shelves Particularly, the study has the following sub-objectives:

• To measure precisely the influences of packaging elements (i.e visual and verbal elements) on buying intention under the moderation of involvement level

• To identify which attributes should be concentrated while designing packaging.

Research Scope

Due to the purpose of this research is focusing on the package influences only on purchase intention, to control the price influences and promotion impacts, author chose Vietnamese instant oat brands which have the same price range is 100.000 VND for a 400 grams package without any promotion at the moment There have three Vietnamese instant oats brands including Xuan An, Vinamit and Union were used to packaging assessment In addition, to determine the suitable targeted group, author chose participants who have already consumed Vietnamese instant oats before collecting their feedback about a certain product.

Research Structure

This study formulates a conceptual framework, of the interaction between packaging design and consumer buying intention, considering involvement level as mediator This research is divided into 5 fundamental chapters including literature review, research methodology, analysis results and conclusion

This chapter provides an introduction about study motivation, research objectives, research scope and research structure.

LITERATURE REVIEW

Consumer Behavior

According to AMA (American Marketing Association), customer behavior is defined as “The dynamic interaction of affect and cognition, behavior, and environmental events by which human beings conduct the exchange aspects of their lives" In the other words In other words, customer behavior is consideration, emotion and reaction of customer in the consumer process (Satish K Batra and S H

H Kazmi, 2004) The behavior of customer is affected by many factors such as the opinions from family or friends, social media, advertising, product information, prices, packaging, product appearance can all affect the feelings, thoughts and behavior of customers

Research on consumer behavior is an important task that has a great influence in the decision-making process of marketing strategies (Philip Kotler, 2001, p 197-

198) Previously, marketers could understand consumers through their exposure, transaction and daily sales experiences However, due to the growth of market size, marketing managers no longer have direct contact with their customers and the information from sales department is becoming subjective As a result, many managers started using consumer behavioral research to have an appropriate and accurate information in order to attract more customers According to Peter Drucker, who is considered the "father" of modern business management said: "The ultimate goal of all business activities is to create customers And only two business tools can do this is marketing and creativity ”(Vneconomy)

Practically, to build and develop an effective marketing strategy as well as launching a new product to market, managers need to study consumer behavior to construct an effective strategy which stimulate customer’s needs to purchase their products

Purchase decision making process is defined as the stage where the consumer actually purchase the product (Amstrong, 2012) The first purchase decision making processes, were introduced by Engel, Blackwell & Kollat, includes 5 stages:

“Problem recognition, Information search, Evaluation of alternatives, Purchase intention and Post-purchase behavior” These five stages are a good framework for assessing customer buying behavior However, customers do not always go through these five stages, they may skip or reverse one For example, if a customer feels they need to buy chocolate to eat, they can go to a store immediately to buy a chocolate bar without searching any information or considering alternatives in advance

Meanwhile, in case of car’s purchase decision making, customer will thoroughly research product information as well as comparing to others similar car brands before making final buying decision In conclusion, the purchase decision making processes is different among the amount of effort a consumer puts into a product while purchasing it

The buying process starts with buyers being aware of demand The buyer feels there is a difference between the actual status and the desired status The buying demand is created from internal or external stimuli or both of them In the case of internal stimuli, the physiological needs such as hunger, thirst, sexuality gradually increases to a certain degree and becomes an urgent need Based on previous experience, people understand how to deal with the urgent need and its motives will lead to the actions can satisfy that need On the other hand, the needs are made from an external stimulus, such as from newspapers, advertisements, friends, society, etc

For example, a person passes a noodle shop and feels the smell of pho that has stimulated the person to feel hungry or a woman sees a beautiful dress of her neighborhood or watches a new perfume commercial, In short, all of these stimuli suggest a problem or need

At this stage, marketers need to identify what situations that often make consumers quickly recognize their problem They should study consumers behavior to find out what kinds of feelings have generated problems or needs, explain what makes them, and how they impact consumers to choose to buy a certain product

After recognizing needs stage, a consumer starts looking for information If the desire of buyers is strong enough and the products are available at that time, they tend to buy them immediately In contrast, if the desired products are not within the reach, the

If consumers' impulse is strong, and desired products are within reach, consumers will most likely buy immediately Otherwise, consumers will keep their needs in their subconscious Consumers may refuse to search for information, or find out basically products information, or actively seek information related to their needs

In case they want to search for information, there are usually the following sources of information

• Family, friends, neighbors and acquaintances

• Commercial information collected through advertising, salesman, merchants, packaging or product displays

• Public information obtained from mass media and organizations

• Personal experience obtained through the interaction in daily life, survey or product usage

The relative influences of these sources of information on buyers purchase decisions are different by the type of product and buyer’s characteristics Generally, consumers receive most of the information about products from commercial sources which is controlled by marketers However, the most effective sources are from personal information sources because commercial information sources often perform notification functions while personal information sources perform the function of assessment and affirmation For example, computer programmers often know about computer software products through commercial information sources, but discuss to programming experts about software products before final buying decision

Marketers need to understand the importance of the information source which is usually referred by their target customers to strategically format information sources As a result, in order to create a marketing content which is effectively communicates to target markets, marketers should interview consumers to collect their first opinion about products, brand image and what sources they received information and the how consumers react to the differences between each source

Before making a purchase decision, buyers process the collected information and then evaluate others similar brand The evaluation process is usually done based on the following principles and sequences

Firstly, consumers consider a product with a set of attributes In particular, each attribute is assigned to a useful function that can bring satisfaction to consumers when they use it

Secondly, consumers tend to classify the attributes according to the levels of importance based on their needs to be satisfied Thirdly, consumers build themselves a set of beliefs in brands as a framework for evaluating the attributes of product

Packaging

Products package is known as a portion of the product itself as well as brand recognition Packaging has an important role in presenting products features and providing product information to customers From buyers’ perspectives, both package and products are the same on the shelves During the purchase decision making process, customer uses package as a supportive tool in evaluating products quality and its functions to make a right choice

The package design adds value not only to the package but also to the product

Visual package design elements including pictures, colors, font, materials, size, shape have a significant role in product perception Meanwhile, verbal package design elements importantly detailed product information At the point of purchase, the fundamental role of package and packaging design is to make buyers’ attention and to be highlighted among compertitors in the store

Effective packaging and package design are the outcome of the collaboration between designers, marketers and customers Thus, packaging design is one of the marketing strategy tools for products itselfs According to Prone (1993), customer’s impulse buying is made by packaging which boosts products function, connects to company’s image and helps company brand stands out among competitors (Gaber &

Jones, 2000) Hence, in the buying decision making process, packaging has an significant role in communicating with customers by providing goods-related information

Besides, packaging is also defined as product positioning which creates the company brand in the customers mind and emphasized the added value that differentiate products from alternatives Maggard (2976) claimed that product positioning induces marketing mix where the portions including pricing policy, place, products and promotion are involved” Considering positioning elements and competitors capability helps marketers to conduct an appropriate marketing strategy (Ampuero & Vila, 2006) The differences of the relevant element’s category depend on positioning strategy’s aim i.e globalization or localization As the result, packaging performs in different functions to reach the different goals, however, stimulating customer purchasing a particular products is the main role of positioning

Hence, while marketers use positioning to place products in the market, packaging and package design are used as assistant of company to attract customers’s attention

Trationally, packaging is used to protect the actual products from damage caused by external factors including “climatic, bacteriological and transit hazards”

(Stewart, 1995) Recently, package do not only have logistic and preservation function but also psychological function i.e packaging communicate to customer

Accrording to Bill Stewart (2004), there has three main functions of package is mentioned as below

To contain: Packaging acts in covering role which ensure the visual features, original functions and the quality of product during the lead time A package, which has a good containing function, enhance the trust of customer about products

To protect: Packaging acts a protection part to keep actual products against external effects including temperature, moisture, light, etc In this term, designers choose package material based on the characteristics of the goods, the transit process and the environmental risks that it will faced with Accordingly, if package performs this function well, the shelf life and the freshness of goods will be extended

To Identify: Packaging plays an important role in reminding customer about the available of goods and providing products information to buyers Customers can easily access product information e.g ingredient, country of origin, production and expiry date, etc In addition, this function can stimulate customers actual purchasing and assist product standing out among alternatives

Product design is described as an decisive tool to create marketing strategy for consumer goods (Rundh, 2009) To enhance a competitive marketing strategy, along with SWOT analyzing, the product design should involve the references from customers (Creusen et al, 2010) Packaging is an effective communication method helping marketers to show their product information and message to consumers (Silayoi & Speece, 2007)

Product design influences the success of consumer goods (Bloch, 2005)

According to Holmes (2012), product design is not only an informational tool but also used to attract buyers’ intention and stimulate their sensation A unique packaging assist product in differentiating consumer good from alternative products (Holmes et al, 2012)

Additionally, as an element of product design, packaging design has a significant communitive role and a strong impact on consumer purchase intention (Salem, 2017), thus, packaging is an important instrument in marketing strategy

Based on previous related literature (Sonsino, 1990; Hine, 1995; Vila &

Ampuero, 2007; Underwood, 2003), visual package design consists of two major attributes, such as graphic and structural elements Graphic component includes color, typographic, shape, image while the structural component consists of size and material used to cover actual products (Hine, 1995) Additionally, Silayoi and Speece

(2004, 2007) added verbal component involving factors related to information or words such as brand name, product information, language used on package (Salem,

2017) In some aspects, three of them have influences customers purchase intention

Theoretically, involvement is the level of importance a customer puts in while they are purchasing a certain products or services It is a causal variable influencing to a number of dependents variables such as buyer’s purchase decision or communication behavior (Laurent, 1985) Hence, consumer’s purchase decision making process differs individually due to the difference of their involvement level

In the other words, the level of involvement significantly affects consumer decision making processes (Quester and Smart, 1998) Additionally, Silayoi and Speece

(2004) claimed that involvement level and the situation of consumption determine which product attributes are considered by buyers In consuming low involvement products, buyers tend to pay more intention on visual attributes while they carefully research before buying high involvement products.

Research Gap and Research Questions

Author Review of article Research Gap

Underwood (2001) The theoretical framework was conducted to understand the communicative effects of package image on brand attention According to the virtual reality simulation results, package image positively influences consumer's brand attention in private label brand

These qualitative papers mainly aim to explore the initial understanding of the relationship between packaging and purchase intention with the considering involvement level as its moderator However, they did not have any precise measurement the interaction among them Additionally, most of these papers just focused on the impact of visual element only, did not mentioned much

Underwood (2003) The exploratory qualitative study confirmed the role of packaging in enhancing the relationship between consumer and brand in low involvement products

This is a qualitative approach research adopting a focus group method to understand consumer response to product packaging and packaging design influences on the consumer purchase decision The findings are that customers decision mostly affected by visual elements when they considered low involvement products under high time pressure

This paper study relationship between packaging graphic elements and positioning strategies from related previous study and found that the existing literatures mainly concentrated on the impacts of visual elements including color, shape, typography and image which is determined by corresponding positioning strategy

(2008) An empirical research found that non-verbal components enhances consumer impulsive purchasing while verbal components did not impact on repeated purchasing

Mutsikiwa (2014) This paper aims to evaluate the influences of aesthetics package design on buyer's purchase decision in daily products consuming The analysis focused on package color, material, instruction and typographic

Collected information from in-depth interviews and observation of 11 older participants (in range 58 - 85 years old)'s behavior with fast-moving consumer products packaging

The results indicated that customers aging has positive relationship with their perceived risk in packaging interaction about the role of verbal elements

A qualitative study examines the influences of package design and naming strategies on perceived quality and purchase intentions The results show that while packaging positively effects on perceived quality and purchase decision, the naming strategy did not have any significant impacts

These quantitative had objectively analyze the impacts of package attributes on purchase intention but there has no positive direct relationships among them

Muhammad (2014) This study used quantitative analysis to test the influence of verbal elements (i.e nutritional information, product information, country-of-origin) on consumer buying behavior The findings revealed that product information has negative impact

Imiru (2017) The paper used correlation and regression to analysis the relationship between packaging attributes on consumer purchase decision As the result, there has no relationship between package color and material

To fill these research gap, this study aims to investigate the positive relationship between packaging elements and purchase intention by adding involvement level as moderator of their interactions According to Quester and Smart (1998), involvement level strongly influences consumer buying decision making processes Additionally, in case of low involvement level, consumer normally affected by visual packaging design while buyers pay more intention to the product itself in case of high involvement (Grossman and Wiseblit, 1999) In general, this paper purpose to precisely measure the relationship between packaging design and purchase intention under moderated by involvement level with following research questions

1 Is there a positive relationship between packaging design and consumer purchase intention?

2 Does involvement level influence the relationship between packaging and consumer buying intention?

Theoretical framework and research hypotheses

Figure 2 2: The proposed research framework

Packaging is not only used for logistic purpose but also as critical communication tools of products (Hellstrom & Nilsson, 2011) In marketing literature, package is considered as the appearance of product (Chung e al, 2006), thus, it is the first thing consumers interact before actual goods usage in retail environments (Marchi,

2007) Obviously, most of consumer buying decisions are made in the store based on packaging elements (Salem, 2017) As a result, package place the tremendous role in interacting the relationship between buyers and certain brand (Salem, 2017) According to Kotler & Keller (2011), product package is illustrated as the performance of designing and creating products container which do not only keep actual products from external hazard factors but also become a “silent salesman” to increase sales volume

There have many different definitions about the packaging elements In the related research of Smith and Taylor (2004), they divided packaging design into six parts including “color, size, form, materials, graphic and flavor” Besides, Kotler (2003) claims that product package involves similar six elements, such as “color, size, form, material, text and brand” These elements should be considered in package design process (Vila and Ampuero, 2007) Differently, Underwood (2003) separate packaging into two main attributes i.e structural attributes (“form, size of the containers and materials”) and graphic attributes (“color, shape, typography and image”) Obviously, similar to Underwood (2003), Smith & Taylor (2004) do not mention about verbal elements of packaging which has decisive influences on actual purchase of high- educated consumer (Mutsikiwa et al, 2013) To fill this gap, Rettie and Brew (2000) mentioned about positioning function of packaging, thus, they separated packaging to main groups: visual (e.g color, image, shape, font, size) and verbal (e.g brand name, slogans) elements Additionally, according to Silayoi and Speece (2004), packaging has two major elements: visual and informational elements Visual elements, includes graphics, size and shape of packaging, influence the affective aspect of purchase decision making of consumer Meanwhile, informational elements, which impact cognitive aspects, consists of product information (e.g the name of the firm, address, country of origin, production and expiry date)

Though both Rettie & Brew (2000) and Silayoi & Speece (2004) considered the importance of informational elements, they did not mention about the environmental effects of package materials which significant influence on customer’s food purchase intention (Rundh, 2005) due to the growth of environmental concerned consumers Not only that, they also did not indicate the role of printed language which may affect on the willingness to purchase of buyers (Salem, 2017)

Therefore, to fill above gaps, author considered the environmental influence of package materials as a part of structural elements (Hine, 1995) and the language as verbal elements (Salem, 2017) As the results, based on the references of existing literature, this paper divided packaging into three main elements: graphic elements (e.g color, shape, font, picture), structural element (e.g size, material) and verbal elements (e.g brand name, product information, language)

Graphic elements: Graphics elements, are factors can be seen, comprised of color combination, shape, background image and the font style used on packaging (Hine,

Structural elements: structural elements, are factors simultaneously designed to display and protect the products effectively, consist of product size design and material should be used

Verbal elements: Verbal elements, are factors related to information or words, include brand name, the information of product and the language used on packaging In the decision-making process, the verbal attributes influence the cognitive

Product involvement, is the level of interest or effort that consumers put in purchasing a certain product, divided into two type including low and high involvement

High involvement products, are perceived as having high value with high cost and provide long term benefits and buyers tend to carefully evaluation before purchasing it Meanwhile, low involvement products have cheaper cost, thus, buyers do not need much time to deeply research or consider before chasing its

According to Sproles & Kendall (1986), purchase intention is a “mental orientation characterizing a customer’s approach to making choice” Purchase intention associates with cognitive and affective process in decision making process

Additionally, consumer purchase intention is likely influenced by three main packaging design components including graphic, structural and verbal elements

Before conducting quantitative analysis, the measurement of each variable was referred from existing researches were indicated as following table:

Table 2 2: Measurement of variables Variable No of questions Measurement sources

2.4.3 Integration of literature review and hypothesis 2.4.3.1 Graphic package elements and purchase intention

Color has significant influence on consumer emotion (Salem, 2017), thus, color selection process is very importance to design an attractive package (Cheskin, 1957)

Package color assists product differentiate from other brand and enhance consumer’s long-lasting memories about products Color is an effective design tool without cost, product attributes and function adjustments (Garber et al, 2000)

According to Steward (2004), each packaging color of a particular product has a transferred message to consumers Especially, for food products, package color has strong impact on customers perception about the food taste (Kauppinen, 2010;

Koch&Koch, 2003; Gaber et al, 2000)

Each buyer has different feeling and interest in package color (Mutsikiwa et al.,

2013) Hence, based on their psychological status, buyers may select some colors among others choices (Martindale and Moore, 1998) Additionally, consumers choose colors according to their cultural associations (Grossman and Wisenblit, 1999)

Therefore, to make the right choice of color, marketers should fully understand the meanings of each colors in different cultural context (Salem, 2017)

Interestingly, many customers confirm that they have potential to purchase a certain product without reading the label or product information (Salem, 2017)

Previous marketing literature proved that the shape of package associating with message affect consumer feeling and perceived quality (Abdelsamie et al, 2013;

Ruumpol, 2014) For instance, while male is impressed by linear angular shapes, female prefer curving line and round shape (Shimp, 1990) When considering two products with the same weight, buyers tend to choose the product which has taller shape because in buyer’s mindset, the higher has larger volume (Silayoi et al, 2007) Additionally, an innovative package helps products enhance the attractiveness and stand out among similar brands (Salem, 2017) Unique packaging is a competitive tool used for differentiating and consequently increase products sales volume (Sherwood, 1999)

According to Salem (2017), pictures and graphics affect consumer sensory the pictures, are printed on product packaging, describes the information related to the goods, such as products usage instructions and its functions where consumer can generally imagine what the product is (Pensasitorn, 2015) Hence, pictures on package places an important role in communicating to customer through transferring products information and imagined stimuli about products (Salem, 2017) In the other words, packaging image is an effective instrument to convey the functions of product and assist goods to be different from alternatives (Meyers and Lubliner, 1998)

Font design has a significant role in catching buyer’s eyes (Salem, 2017)

Possibly, due to small or unclear fonts, the information of goods is ambiguously described to buyers resulting to misunderstanding and concerning about product quality (Parmar et al, 2009) As a result, along with the development of design technology, to have an innovative font style, many companies hire experts to design a creative and attractive font style used for their logos, slogans and product package (Imiru, 2017)

Therefore, font style, is a powerful tool to draw consumers attention, has positive impact on consumers purchase decision (Imiru, 2017)

In general, the graphic elements have significant impacts because they have a capability to influence the emotion and feeling of targeted customers (Silayoi and Speece, 2004) Thus, graphic elements positively impact on buyer’s purchase intention perceived quality (Saker, 2015) Based on discussion above, the first hypothesis was established as below:

H1: Graphic packaging elements positively influence consumer’s instance oats purchase intention

2.4.3.2 Structural package elements and purchase intention

As package shape, buyers consider package sizes to make volume perception

Hence, the size design should meet consumer’s demand (Makanjuola and Enujiugha,

2015) According to Benedetti et al (2014), marketers should understand target’s customers behavior before making product sizes decision Additionally, package sizes strongly influence on consumer buying choice when buyers cannot clearly evaluate product quality, thus, they are potential to buying smaller one for trial usage (Ksenia,

2013) Meanwhile, some buyers prefer the large size of products for saving cost

Therefore, to meet different type of consumer demands, it would be better if goods are sold in various packaging size (Rundh, 2005)

According to Smith (2004), packaging material is designed according to products characteristics, functions and consumer’s needs In a research about packaging (Hollywood, 2013), buyers confirm that they will not purchase products which has low quality and cannot keep the freshness of foods Obviously, the packaging material have positive affect on consumers perceived quality of products, especially, in case of food products (Silayoi & Speece, 2004) In addition, many today consumers more concern about environmental issues (Rundh, 2005) Accordingly, buyers potentially choose products which have environment friendly, recycle and ease-reuse packaging (Rundh,

Based on previous literature review, to understand more the influences of structural elements will be thoroughly analyzed in the following section; thus, the second hypothesis was conducted as following:

H2: Structural packaging elements positively influence consumer’s instance oats purchase intention

2.4.3.3 Verbal package elements and purchase intention

METHODOLYGY AND RESEARCH DESIGN

Research approach

According to Sarantakos (2005), social science can be conducted in quantitative or qualitative approach While qualitative approach tent to explore and understand the individual or social phenomenon by observation and involvement (Bryman & Bell,

2007), the quantitative research adopts statistic and numerical analysis methods to assess objectively theories Quantitative research concentrates on the “what” of the research topic rather than the “why” (qualitative approach) of the research topic In the other words, it focuses on describing the nature of a phenomenon instead of explaining further “why, when or how” it happened Due to this study aims to understand what extent packaging elements design (i.e visual and verbal elements) influence instant oats purchase intention of Vietnamese consumers which can be addressed by quantitative approach Additionally, Cavana et al (2008) indicated that quantitative research often uses deductive logic which is the process starts with developing hypotheses based on existing theory and then conduct a conclusion after hypotheses testing processes

Deductive approach assists researchers to explain quantitatively the relationships between research concepts and variables that are corresponding with research objectives Therefore, quantitative and deductive approach are the most suitable approaches to conduct this study.

Research design

According to Souna (2007), research design is defined as “the framework or guide used for the planning, implementation, and analysis of a study” The different of research questions or hypotheses lead to the different of research design, thus, understanding and distinguishing exactly the types of research design is an important mission while conducting a study Based on the researcher’s variables controlling level, quantitative research design is divided into 4 main types: descriptive, correlational, causal-comparative and experimental design

Causal-comparative design is adopted to create the cause-effect relationship among variables In this research design, independent variables are considered as causal factors while dependent variables are affected factors Causal-comparative design is a popular design used in social science to analyze human behavior through assessing the cause-effect relationship among groups

To research objectives, this study purpose to precisely check the impact of packaging design elements on consumer purchase intention Therefore, the usage of causal-comparative design is the most suitable solution Causal-comparative design is considered to widely used to examine in marketing research (Lynn, 2003) Based on above discussion, this research process is designed as figure 3.1, the process includes 5 main stages: literature review, research design, data collection, data analysis and conclusion

Figure 3 1: The research process flow chart

L ite ra tur e R ev ie w

Data collection Selection of basic research methods: Questionnaires/ survey

Interpretation of results and findings

Conclusion and recommendation Preliminary literature

R es ea rc h D es ign D at a C ol le ct ion Da ta A na lys is C onc lus ion

Data selection

Research data has been collected from both secondary and primary sources

According to Saunders (2009), secondary data is the information collected from existing sources including company reports, academic journals, scientific articles and media information Otherwise, primary data is gathered by researchers themselves to answers their research questions (Hox & Boeije, 2005) Saunders (2009) claimed that the reliability of data collection is very important to have a valuable result

Secondary data has been gathered mainly from academic journals and scientific articles The secondary is used as references for gathering primary data and research questions Author purpose to find the suitable secondary data related to packaging design and its impacts on consumer purchase intentions In addition, to solve research problem, author used key words such as packaging elements, purchase decision and consumer involvement level to search expected secondary data The used database is belonging to Yokohama National University, Vietnam National University and Google Scholar

According to Churchill and Lacobucci (2010), researchers should consult the secondary research first then conduct the primary data to achieve a general knowledge about research topic The primary data was collected according to specific research purpose and research question (Mark Saunder, 2009) To gather primary data, this study used online survey built by google forms

According to Malhotra (2007), the kind of data analysis determine the required sample size Additionally, Tabachnick & Fidell (2007) indicated that CFA sensitively requires the certain sample size because it is inconsistent if the sample size is too small

Unfortunately, there no any acceptable criteria for choosing a valid sample size for CFA which is used in this research (Hair et al., 2010) Hair et al (2010) also indicated that the minimum size can be 100 in case of the model containing under 5 constructs and each of them consists of more than 3 items with high item communalities (> 0.6); 150 in case of model with at most 7 constructs have modest communalities (0.5); 300 in case of models involves at most 7 constructs with low item communalities (0.45) and over 500 for models consists a large number of constructs with low item communalities and under 3 measurements items Generally, 100 is the practical and acceptable size for SEM (Hair et al., 2010)

Furthermore, for SEM in using AMOS, Pallant (2005) claimed that the sample size should be “at least five times the number of question items Accordingly, the proposal model involves 2 independent variables, 1 moderate variable, 1 dependent variable containing 30 question items Specifically, 10 for “Graphic elements” variable,

4 for “Structural elements”, 8 for “Verbal elements”, 4 for “Involvement level” and 4 for “Purchase intention” Hence, there has 30 items in total (30 x 5 = 150) which mean that 150 is the minimum acceptable sample size Therefore, this study considered 150 for minimum sample size estimation

3.3.2.2 Data Collection and participants characteristics

Due to the conveniences and objectivity, survey became a popular tool to gather information from respondents Especially, along with the spreading of internet, online survey tends to be the more cost-effective than traditional method such as paper surveys or face-to-face interviews Online survey assists researchers reduce the geographical dependence and connect to more hard-to-reach respondents in less developing time and money

Therefore, data of this study was collected by online surveys from March 29 th to April 20 th , 2019 The criteria for participating in this study was that the respondents who are considering to buy instant oats Hence, there was 250 people were sent the link of the questionnaire via social media (Facebook, Instagram) and e-mail, however, 103 indicated that they did not plan to purchase instance oats As a result, only 147 responses who have specific characteristic shown in table 3.1, are validated for further analysis

Although this result was not estimated sample size (150), this quantity is still larger than the acceptable minimum sample size for CFA (100) suggested by Hair et al (2010)

Table 3 1: Frequency of demographic information of respondents

Items Number of respondents Percentages

According to Kothari (1985), the questionnaire is “mainly accumulation of inquiries that suit the study area and its targets, and the solution to which will give the information necessary to check the assumptions made for the research” To conduct questions, analyst need to consider thoroughly the research area (Yin, 2002), thus, the questionnaires are conducted from theoretical framework made in chapter two with research items are referred from literature review and modified by the pilot study The questionnaires were distributed to participants under multiple choice questions which syncs with their perception and opinion The questions originally design in English then translated to Vietnamese After the preliminary translation, to ensure the Vietnamese survey is easily to understand, author distributes the questionnaire to sample of 30 participants Based on group’s discussion, author has deleted, modified the question items to be more suitable for Vietnamese consumer context Additionally, to measure the reliability of questionnaire, research used Cronbach’s alpha test As a result, the Cronbach’s alpha coefficients each variable was greater than 0.7 meaning that the questionnaire is significant and high reliable coefficients Therefore, the questionnaire was adjusted to avoid the probabilities of misinterpretation, distraction and partiality through ensure the design of questionnaire assists to collect the expected responses from participants The final questionnaire is shown at appendixes section

Questionnaire is the measurement, which is used to evaluate the research hypotheses, includes subjective items Each item in questionnaire was evaluated by five-point Likert scales (“1: strongly disagree, 2: disagree, 3: no opinion, 4: agree, and 5: strongly agree”) Author divided questionnaire into seven sections The first section consists of questions related to demographic information including gender, age, income and living area In the second section, before going to packaging evaluation parts with

30 relevant questions (Table 3.2), each participant was asking to select one of three packaging image of corresponding Vietnamese instant oats and then they were asked to evaluate only one brand they chose in the next sections The third section includes two photos describing the front & back side of product packaging and 10 questions to evaluate graphic design were adapted from Olawepo (2015) The fourth section also consists of two parts including front & back side image of product packaging and 4 questions conducted from Salem (2017) The fifth section includes front & back side image of product packaging and verbal packaging design (8 questions) were referred from Salem (2017) The sixth part concentrated on consumer involvement level consisting of 4 items which were conducted from Mittal (1989) Lastly, purchase intention questions were adapted from Weisstein (2017) and Pei (2014)

Table 3 2: Study variable areas and corresponding section of the questionnaire

The color combination on the packaging draws my attention

2 The color combination can easily be remembered

3 The color combination makes product stands out among another brand

4 The shape of packaging is unique compared to another brand

5 The shape of packaging is comfortable to use

6 The Font used on the product is legible and can be understood

7 The Font used in writing Ingredient composition is legible and could be interpreted

8 The Font used on the product attracts attention from distance

9 The picture quality of the product packaging draws my attention

10 The picture of the product packaging reflects the fact that it is healthy

The size of packaging meets my demand

12 Packaging material is made from recycle materials

13 Packaging material has high quality

14 Packaging material is environmentally friendly

Brand name on packaging draws my attention

16 Brand name on packaging is unique compared to another brand

17 Brand name on packaging is easy to remember

18 Product information on packaging is described clearly

19 Product information on packaging effects trust for the product

20 Storage information on packaging is easy to follow

21 I react more favorably to product packaging imprinted in Vietnamese

22 Product information on packaging (such as: the name of the firm, address, country of origin, production and expiry date) is clearly printed

In selecting from the many types and brands of Instant Oats available in the market, I will care a great deal as to which one I buy

24 I think that the various types and brands of Instant Oats available in the market are all very different

25 To me, making a right choice of instant oats is very important

26 In making my selection of Instant Oats, I concern about the outcome of my choice

I would be willing to buy Instant Oats of this brand

28 If I were going to buy Instant Oats, the probability of this brand is high

29 The probability that I would consider buying the instant oats of this brand is high

30 The probability that I would purchase the instant oats of this brand is high

Data Analysis

The Cronbach’s alpha value is a popular tool to purify research measurements

Nunnally and Bemstein (1994) suggested that the Cronbach’s Alpha value of each variable should be greater than 70 threshold To gain the possible highest reliability coefficient, the variables are purified by deleting items which have the lowest item- to-total correlation or items which have the value “Cronbach’s alpha if item deleted” is greater than total Cronbach’s Alpha value In this study, there has 4 variables with

30 items were measured in this section When the Cronbach’s Alpha coefficient reaches to expected value, the analysis goes to the continuous improvement cycle stage

In this study, the measurements were the result of combination from different existing related literature, thus, each measure needs to be ensured the internal consistency and construct validity for further analysis Chen & Paulraj (2004) recommended that the continuous improvement cycle is a suitable tool to improve the construct validity of a variable measure Similarly, Churchill (1979) suggested exploratory factor analysis (EFA) is a reliable instrument to assess the reliability and construct validity of a newly created data Table 3.2 indicated 3 types of used methods for continuous improvement cycle stage in this research Firstly, the EFA was adopted to organize construct validity, secondly, the confirmatory factor analysis (CFA) step which is mentioned thoroughly in the next part After analyzing, if the internal consistency and construct validity are as expected, the measurement scale is reliable and valid enough to use in next analysis

Table 3 3: Suggested procedure for improve measurement construct validity

Internal consistency Cronbach’s Alpha Construct validity

Unidimensional: Factor loadings Convergent Validity: Eigen value, Variance Extracted-VE, Reliability

Convergent Validity: t-values, squared correlations Fits and unidimensional assessment: Fits and indices Discriminant Validity: constrained model pairs; Variance Extracted versus squared correlation between factors Composite Reliability; Variance Extracted

The research data was analyzed through statistical techniques including descriptive statistics, quantitative data analysis (e.g EFA, CFA, SEM, etc) This study adopted CFA to validate construct measurements while structural equation modeling (SEM) for assess research hypotheses

Exploratory factor analysis (EFA) aim to explore the underlying structure of a certain set of variables In the other words, EFA clarified the pattern of correlations among variables by discovering underlying factors According to Gorsuch (1983), EFA is adopted to following below reasons:

• To narrow down the large quantity of items to smaller one for modelling purposes where larger group of items may interrupt modelling process of all measurements individually

• To select a subgroup of factors from larger group by identifying highest correlations with the principal component factors

• To identify uncorrelated items to avoid multicollinearity while adopting multiple regression

• To increase the validity of measurement scale through showing the constituent items load in the same factor and eliminate proposed scale which cross-load in more than a factor

EFA includes three fundamental stages: “(1) assessment of suitability of data for factor analysis, (2) factor extractions and (3) factor rotation” Hence, preliminary analysis should involve some assumptions (indicated in table 3.3) to tested data suitability before conducting EFA To check the linear relationship between variables, Hair et al (2010) recommend the usage of Plotted-Point (P-P plots) corresponding with the ideal line for linearity to exist In addition, multicollinearity occurs when among independent variable has high intercorrelation level and leads to unreliable probability values (P-value) and larger confidence intervals of independent variables

The value of variance inflating factor (VIF) is used to identify multicollinearity occurrences (VFI > 10)

Outliers No outliers accepted (Hair et al., 2010) Linearity No multicollinearity (Hair et al., 2010) Normality Should be Normally distributed (Hair et al., 2010) Sample size Minimum: 5 cases to each study items

Tabachnick&Fidell, 2007) Bartlett’s test of sphericity Be significant (p < 0.5) (Tabachnick&Fidell, 2007) Kaiser-Meyer-

Index ≥ 0.5 (Hair et al., 2010; Malhotra,

The Kaiser-Myer-Olkin (KMO) is used to measure the adequacy of sampling

The KMO, is considered as the best method for determining the acceptability of data for subsequent factor analysis Tabachnick & Fidell (2007) indicated that if the KMO values is too small or accounts in the range 0 to 1.0, the factor analysis should not be operated The KMO need to be 0.6 or higher to run factor analysis

The Bartlett’s test aim to generally check the significance of the correlation matrix According to Nunnally (1978), the best outcome of this test is “the value of the test statistics for population is large and the significant level is small” Similarly, Tabachnick and Fidell (2007) claimed that data is reliable if the Bartlett’s test of population is significant (p < 0.5)

Factor extraction is the important analysis way of EFA Researchers use factor extraction to identify what factor can summarize the interrelationship among variables Hair et al (2010) indicated that tactor extraction consists of 7 methods which are “principal components analysis (PCA), unweighted least squares, generalized least squares, maximum likelihood, principal axis factoring, alpha factoring, and image factoring” This study used principle component analysis which is the most popular used in EFA Tabachnick & Fidell (2007) claimed that PCA is the good choice for researchers who are interested in empirical summary rather than theoretical solution

Meanwhile, Hair et al (2010) indicated that the items which have factor loading greater than 0.50 are valuable for further analysis To select which factors remained in scale, Hair et al (2010) also suggests that researchers should keep factors have eigenvalue greater than 1.0 to use in further examination When the quantity of retained factors were addressed, researcher aim to determine the pattern of loading for interpretation by rotation There exist 2 direction for rotation including orthogonal (varimax) and oblique rotation This study adopted varimax rotation which purpose to “simplify factors by maximizing the variance of the loadings within factors, across variables” (Tabachnick & Fidell, 2007)

In this study introduction chapter, author mentioned that SEM was used for hypothesis testing and re-specifying the model before determining the final result

Hence, before assessing hypothesis by SEM, the items were purified by multiple iterations of CFA with the maximum likelihood estimation method (MLE) Hair et al

(2010) suggested the CFA’s cut-off points indicating in the table 3.4 and table 3.5 as following table:

Table 3 5: Model diagnostics in CFA

> 4 possible problem Path Estimate (Construct to Indicator) ≥ 5 ; ideally ≥ 0.7; and be significant Square Multiple correlations (SMC) or reliability

Chi-square Value with non- significant p-value

Normed Chi-square (CMIN/df) ≤ 3

Goodness-of-fit Index (GFI) 0 < GFI ≤ 1 Adjusted Goodness-of-fit Index (AGFI) 0 < AGFI ≤ 1

Tucker-Lewis Index (TLI) 0 < TLI ≤ 1

Comparative Fit Index (CFI) 0 < CFI ≤ 1 Root Mean Square of Error of Estimation

Author used structural equation modelling (SEM) to describe specifically the research model and analyze the relationship between independent and dependent variables as well as interaction effect of moderator addressed in this study

SEM is a technique which is embraces effectively many common multivariate analysis methods such as factor analysis, analysis of variance and regression In the other words, Byrne (1994) indicated that SEM is a statistical methodology for testing hypothesis to the multivariate analysis which is popularly used in market research

SEM includes the clarification of linear regression-type model framework with a certain number of observed variables (indicator variables) by representing the structural relationship or equations among latent variables (unobserved variables)

Testing the co-variation among observed variables assist researchers to:

• Identify the coeficient values in the linear model framework

• Test the model acceptability for representing the studied processes

• According to model acceptability testing, conclude that the reliability of variables relationship

Particularly, SEM assist researches conduct the hypothesis models of marker behavior and assess research model statistically Furthermore, SEM predicts the unknown coefficients in a group of linear structural equation system which normally involves observed variables and related latent variables (unobserved variables) In addition, during analysis process, SEM assumes there exists a causal-relation between a certain number of observed variables and latent variables and observed variables play as indicators role

Latent variable defined as unobserved or unmeasured variable, which has theoretical constructs and can be directly measurable, normally be referred as “factors” or “common factors” which are assumed than can be observed when they have the significant influence on the outcome resulted by observed variables Additionally, latent variables can directly affect other latent

Due to latent variables are unobservable, thus, we tent to measure them indirectly As a result, each latent variable was linked to a certain number of observed variables Accordingly, in SEM analysis procedure, the first step of a formal statistically valid process is the connecting of latent variables to observed variables which is presented as rectangles in below figure 3.2

DATA ANALYSIS RESULTS

Measurement Scale Test

Cronbach’s Alpha coefficients are coefficients in statistical tests that are used to check the correlation between observed variables, in order to analyze the scale reliability assessment To purify measurement, this method allows analyst to remove unsuitable variables and unreliable variables in the research measurement The variables which have corrected items-total correlation values greater than 0.3 and Cronbach's Alpha coefficient greater than 0.6 are acceptable and appropriately used in the next stage (Nunnally and Burnstein, 1994) Many researchers agree that when Cronbach’s Alpha is between 0.7 and 1, the scale of measurement is good and the correlation will be higher

No Variables Number of Items

The results are shown in the table indicated that all of 5 variables had the Cronbach’s alpha above 0.7, thus the measurement achieved reliability test However, to purify the measurement of Verbal Elements, author deleted two items VB2 and VB3 which had the values of “Cronbach’s Alpha if Item deleted” greater than Cronbach’s Alpha coefficient Specifically, the removed variables are shown as below table:

VB2: “Brand name on packaging is unique compared to another brand”

VB3: “Brand name on packaging is easy to remember”

Overall, after eliminating 2 item, the satisfied 5 variables with 28 items were used for exploratory factor analysis step

In this research, factor analysis will help us consider the possibility of reducing

28 observed variables down to a smaller number to reflect particularly the impact of packaging elements on the consumer buying intention The original model has 5 latent variables with 28 observed variables which affected the intention to buy Vietnamese brand of instant oats, is used for EFA stage

As mentioned in the previous chapter, remained items were analyzed by exploratory factor analysis (EFA) with Principal components method for extraction and Varimax method for rotation The results (table 4.3) indicated that 4 factors were extracted from measurement scales with extraction sum of squared loadings being about 63.24% (greater than 50%) The KMO index was significant at 0.853 and the Bartlett’s Test of Sphericity had chi- square= 2540.660, df= 378 and sig= 000

Table 4 3: Exploratory Factor Analysis Results

• KMO = 0.801 proved that factor analysis is appropriate;

• Sig (Bartlett’s Test) = 0,000 (Sig 1 represented the variation explained by each variable and the collected variables has the best summary information;

• The Rotation Sum of Squared Loadings (Cumulative%) = 63.24> 50% proved that 63.24% of the data variation is explained by 5 new factors are shown as following table

The color combination on the packaging draws my attention 713

The color combination can easily be remembered 803

The color combination makes product stands out among another brand 828

The shape of packaging is unique compared to another brand 809

The shape of packaging is comfortable to use 682

The Font used on the product is legible and can be understood 767

The Font used in writing Ingredient composition is legible and could be interpreted 772

The Font used on the product attracts attention from distance 644

The picture quality of the product packaging draws my attention 764

The picture of the product packaging reflects the fact that it is healthy 786

Brand name on packaging draws my attention 675

Product information on packaging is described clearly 733

Product information on packaging effects trust for the product 738

Storage information on packaging is easy to follow 748

I react more favorably to product packaging imprinted in Vietnamese 747

Product information on packaging (such as: the name of the firm, address, country of origin, production and expiry date) is clearly 733

I would be willing to buy Instant Oats of this brand 854

If I were going to buy Instant Oats, the probability of this brand is high 846

The probability that I would consider buying the instant oats of this brand is high 820

The probability that I would purchase the instant oats of this brand is high 819

In selecting from the many types and brands of Instant Oats available in the market, I will care a great deal as to which one I buy

I think that the various types and brands of Instant Oats available in the market are all very different .812

To me, making a right choice of instant oats is very important 753

In making my selection of Instant Oats, I concern about the outcome of my choice 702

The size of packaging meets my demand 753

Packaging material is made from recycle materials 738

Packaging material has high quality 699

Packaging material is environmentally friendly 618

According to the table “Rotated components results”, after exploratory factors analysis, all of 28 items were sorted in to 5 groups with factor loading greater than 0.5

Accordingly, the 5 latent variables were renamed as below:

• LATENT VARIABLES 1, named as “GRAPHIC ELEMENT”, has eigenvalue equal to 7.992 > 1 There have 10 observed variables were used to measure this latent variable

• LATENT VARIABLES 2, named as “VERBAL ELEMENT”, has eigenvalue equal to 3.480 > 1 There have 6 observed variables were used to measure this latent variable

• LATENT VARIABLES 3, named as “PURCHASE INTENTION”, has eigenvalue equal to 3.054 > 1 There have 4 observed variables were used to measure this latent variable

• LATENT VARIABLES 4, named as “INVOLVEMENT LEVEL”, has eigenvalue equal to 2.432 > 1 There have 10 observed variables were used to measure this latent variable

• LATENT VARIABLES 5, named as “STRUCTURAL ELEMENT”, has eigenvalue equal to 1.146 > 1 There have 10 observed variables were used to measure this latent variable

Along with purifying observed variable discussed in chapter 3, confirmatory factor analysis is also used to measure the relevance of the model to primary data

Chi-square (CMIN); Normed Chi-square (CMIN /df); CFI - Comparative Fit Index;

TLI - Tucker & Lewis index); RMSEA index - Root Mean Square Error Approximation are the values used for test the fitness of research model

Additionally, according to Nguyen Khanh Duy (2009): The model is considered suitable for primary data if the Chi-square test has P-value > 0.05; If the model receives a probability value of Chi-square greater than 0.08 or GFI and CFI index close to 1 and RMSEA index below 0.08 (Browne and Cudek, 1992) In the research which has CMIN/df < 3 (with sample n = 0.5) and statistically significant p is equal to 0.000

The specific results are shown in the following table:

Table 4 6: Confirmatory Factor Analysis results

CMIN/df RMSEA GFI TLI CFI

Overall, the results strongly indicated that research model received acceptable fit to the primary data

The standardized regression weights of 28 measurements were used to check this criterion As a result, the loadings are greater than 0.05 – recommended values by Anderson & Gerbing (1884) with the highest and the lowest values corresponding to 0.955 and 0.528 Additionally, the composite reliability (CR) and average variance extracted (AVE) were calculated All 5 latent variables had CR values greater than 0.6 (Bagozzi & Yi, 1988) and AVE value above 0.5 (Fornell & Larcker, 1981)

Particularly, the AVE values of verbal element and structural element were less than 0.5 at 0.462 and 0.401 respectively, however, according to SheuFen et al (2012) that values were acceptable In general, all those values of 5 variables achieved the convergent validity requirements The specific results were indicated in following table

Table 4 7: Composite reliability and AVE results

Latent Variables Composite reliability AVE

Discriminant validity aim to explore whether 5 concepts were unrelated or not

The correlation coefficient and covariance of 5 concepts resulted from CFA were used At p-value < 0.05, all of the correlation of each pair of latent variables has the values less than unity (Steekamp & Van Trijp, 1991), thus, they were exactly irrelevant

Table 4 8: The new latent variables

No Observed variables Latent variables

1 The color combination on the packaging draws my attention

2 The color combination can easily be remembered

3 The color combination makes product stands out among another brand

4 The shape of packaging is unique compared to another brand

5 The shape of packaging is comfortable to use

6 The Font used on the product is legible and can be understood

7 The Font used in writing Ingredient composition is legible and could be interpreted

8 The Font used on the product attracts attention from distance

9 The picture quality of the product packaging draws my attention

10 The picture of the product packaging reflects the fact that it is healthy

1 The size of packaging meets my demand

2 Packaging material is made from recycle materials

3 Packaging material has high quality

4 Packaging material is environmentally friendly

1 Brand name on packaging draws my attention

2 Product information on packaging is described clearly

3 Product information on packaging effects trust for the product

4 Storage information on packaging is easy to follow

5 I react more favorably to product packaging imprinted in Vietnamese

6 Product information on packaging (such as: the name of the firm, address, country of origin, production and expiry date) is clearly

In selecting from the many types and brands of Instant Oats available in the market, I will care a great deal as to which one I buy

2 I think that the various types and brands of Instant Oats available in the market are all very different

3 To me, making a right choice of instant oats is very important

4 In making my selection of Instant Oats, I concern about the outcome of my choice

1 I would be willing to buy Instant Oats of this brand

2 If I were going to buy Instant Oats, the probability of this brand is high

3 The probability that I would consider buying the instant oats of this brand is high

4 The probability that I would purchase the instant oats of this brand is high

After EFA and CFA, in conclusion, the model, used for testing the relationship between packaging elements and consumer purchase intention, includes 5 latent variables and 28 observed variables which are satisfied to adopt in confirmatory factor analysis.

CONCLUSION

Discussion of findings

Based on the analysis results from gathered data, this chapter indicated the findings discussion and some recommendation for future related study Researcher has considered two main elements of packaging design (i.e visual and verbal attributes) to advance the argument in this study The visual elements consist of can be seen attributes such as color, shape, size, picture, material, whilst verbal elements associated with words including brand name, product information and language

The analysis results proved that graphic attributes have a positive impact on consumer’s buying intention for following reasons: the graphic package design has attractive and easily memorable color These findings are similar to previous researches (e.g Salem, 2017; Pensasitorn, 2015; Krimi et al., 2013; etc) which claimed that package color and image evoke consumer attention and easy to remember Thus, understanding buyer’s response to package color assist marketers and designers enhance their product’s competitiveness on the shelves Besides, package shape can make product more attractive and additionally enhance the convenience in usage, thus, convenience package shape can boost buyers purchase a certain product Besides, for the font style used on package, it can make product more reliable and highlighted among alternative, thus, the font needs to be legible and have the appropriate size to attract buyers from distance The findings also proved that the picture on the package has ability to evoke buyer’s feeling and play a main role in transferring product’s usage instruction as well as its function

Also, structural package design has a positive impact on consumer purchase intention due to package size meet their products quantity needs and package material plays a significant role in products as well as environmental protection In the other words, the suitable size of package stimuli consumer to purchase a certain product, therefore, it should match to consumer demands Marketer should consider the differences of target customers in the different market to design effectively a product package Today, consumers concern more about environmental issues, thus, they prefer environment friendly packaging along with requiring a package material is good enough to protect products itself from external attacks

The findings also indicated that verbal elements have positive influences on consumer purchase intention due to following reasons: the brand name draw buyer’s attention; the products information is clearly described; the printed information storage is easily to follow and consumers prefer package is printed in local language, thus, selecting a suitable language for product label plays an important role in transferring effectively message to consumers These findings align to existing studies (e.g Salem, 2017; Adam & Ali, 2014; Mutsikiwa, 2013; etc) indicated that informational element is a decisive factor while making a buying decision Buyers often make purchase intention based on printed package information Reading information on package makes buyers evaluate product quality even though visual elements draw their attention at the beginning

Interestingly, involvement level has moderated influence on the relationship between structural elements and purchase intention While the structural elements have positive effect on purchase intention, the value of its combination with involvement level is positive In this case, the high involvement level enhances the interaction between structural element and purchase intention In the other words, consumers pay attention in structural element when they have intention to buy a certain product with high involvement level Therefore, in case of high involvement products, buyers highly require not only about the quality of the product itself but also its package material which has ability to protect and maintain the quality and function of the actual products during transportation process In the other words, for high involvement products, the package material also reflects the product quality, thus, it is necessary to design a qualified package material which is consistent with the value of actual products

Differently, involvement level is found that have no influence on the interaction between graphic element and purchase intention and the relationship of verbal element and purchase intention This result, is in contrast with existing study (Silayoi and Speece, 2004, 2007; Imiru, 2017), which caused by the different in products brand collection methods Specifically, related previous study quantitatively did research in total food industry with various kinds of product, differently, this study focused on a certain product type – instant oats with a certain number of selected brands Besides, participants were asked to evaluate only one brand they selected leading to the inconsistency of data which distorted the research accuracy which caused the contrary results to previous research Additionally, the different of respondent demographic characteristics might be another reason For instance, in Vietnamese’s mindset, package is the products image which reflect quality and the thoroughness manufacturers put into products, thus, there is no difference to the degree of graphic package design requirement for low or high involvement products

In the other words, Vietnamese consumers always pay attention to graphic package design no matter how much involvement level is; thus, their purchase intention is easily affected by them (graphic design) Similarly, in Vietnam, most of buyers, purchase instant oats, have high health consciousness and safe consciousness, obviously, reading product information becomes their positive habits during shopping Their purchase intention is likelihood to be influenced by verbal element in case of consuming both low and high involvement products.

Managerial implication

This study provides some managerial implication Firstly, it improves the limitations of existing researches evaluating the role of packaging as a strategic marketing tool that have positive influences on buyer ‘s purchase intention As a result, this study highlights the literature gap in the relationship of verbal elements and purchase intention Additionally, it confirmed a different view about the moderator role of involvement level affecting the interaction of structural elements and purchase intention Furthermore, managers and marketers can use managerial implication resulted from this study to communicate with their target customers and help their products stand out in highly competitive market Last but not least, in term of marketing implication, this study provides the understanding of instant oats consumer’s response to graphic, structural and verbal packaging design Thus, it may help the relevant companies to increase their knowledge about consumer behavior to design an effective communication tool – package.

Practical implication

The findings of this study can be used by managers and marketers to design an effective packaging to ensure their products stand out among competitions Today consumers are becoming more careful when purchasing food products, thus, graphic, structural and verbal elements should be designed accurately and informatively provide ingredient contents Specifically, based on findings, this study provides some practical implication to marketers and designers in designing an effective package:

• The package design (color, shape, font, picture, brand name) should be different and memorable For example, we easily recognize the red can of Coke or the blue can of Pepsi on the shelf without reading its brand name

• The package design should truly reflect the product information with clear font style and easy-to-follow storage information

• Product should be sold in varied package size to meet different quantity demand of buyers

• Package material should be appropriate with product shelf life and transportation condition Due to the increased number of environmental consciousness consumers, designers should consider the environmentally friendly condition of package material.

Limitation and further research

Limitations of the method of sampling research: Due to the limited time and research scope, the number of samples in this research topic is only a representative part of the target group Besides, convenient random sampling method will also reduce the accuracy of research results

Limitations on research subjects: This paper only analyzes the impact of packaging design of three Vietnamese brands of instant oats, so it does not reflect results objectively

Limitation on research brand selection: due to the participants were asked to choose then evaluate different brands, thus, there exist the inconsistency of collected data which might affect research accuracy

Limitations on the scope of the study: The study is only conducted based on cultural, economic and social factors in some city in Vietnam with very small quantity, thus, the objectivity of the topic is also limited due to each area has different buying intentions

In addition to the above limitations, this study excluded other important factors affecting consumers' buying intention (such as price, promotion, taste, experiences etc.,) which may affect more or less the accuracy of the research topic

Future studies need to have a more general view of the market and understand the related research demand to provide more detailed and accurate factors that are likelihood to influence intention buying, avoiding the omission of the influencing factor that reduces the accuracy of the study

It is necessary to have larger-scale research papers nationwide, because the accuracy of this research topic will help domestic enterprises to improve their competitiveness, in this sustainable market

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ONLINE SURVEY

Link: https://forms.gle/riQj19YgVC176n9RA

Descriptive analysis

Frequency Percent Valid Percent Cumulative

Frequency Percent Valid Percent Cumulative

Frequency Percent Valid Percent Cumulative

Cronbach’s Alpha

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

EFA

Kaiser-Meyer-Olkin Measure of Sampling Adequacy .853 Bartlett's Test of Sphericity

Component Initial Eigenvalues Extraction Sums of

Extraction Method: Principal Component Analysis

ST1 Extraction Method: Principal Component Analysis a 5 components extracted.

CFA

Computation of degrees of freedom (Default model)

Number of distinct sample moments: 406 Number of distinct parameters to be estimated: 67

Minimum was achieved Chi-square = 478.959 Degrees of freedom = 339 Probability level = 000

Model NPAR CMIN DF P CMIN/DF

Model RMR GFI AGFI PGFI Default model 057 826 791 689 Saturated model 000 1.000

Delta2 TLI rho2 CFI Default model 825 804 941 934 941 Saturated model 1.000 1.000 1.000 Independence model 000 000 000 000 000

Default model 897 740 843 Saturated model 000 000 000 Independence model 1.000 000 000

Default model 139.959 86.069 201.877 Saturated model 000 000 000 Independence model 2352.820 2190.616 2522.433

Default model 3.281 959 590 1.383 Saturated model 000 000 000 000 Independence model 18.704 16.115 15.004 17.277

Model RMSEA LO 90 HI 90 PCLOSE

Model AIC BCC BIC CAIC Default model 612.959 646.172 813.318 880.318 Saturated model 812.000 1013.265 2026.116 2432.116 Independence model 2786.820 2800.700 2870.552 2898.552

Model ECVI LO 90 HI 90 MECVI

Default model 4.198 3.829 4.622 4.426 Saturated model 5.562 5.562 5.562 6.940 Independence model 19.088 17.977 20.250 19.183

Estimates (Group number 1 - Default model) Scalar Estimates (Group number 1 - Default model) Maximum Likelihood Estimates

Regression Weights: (Group number 1 - Default model)

Standardized Regression Weights: (Group number 1 - Default model)

Estimate GR3 < - GRAPHIC 843 GR4 < - GRAPHIC 814 GR2 < - GRAPHIC 765 GR10 < - GRAPHIC 762 GR7 < - GRAPHIC 786 GR6 < - GRAPHIC 738 GR9 < - GRAPHIC 711 GR1 < - GRAPHIC 721 GR5 < - GRAPHIC 686 GR8 < - GRAPHIC 579 VB6 < - VERBAL 701 VB7 < - VERBAL 668 VB8 < - VERBAL 711 VB4 < - VERBAL 697 VB5 < - VERBAL 680 VB1 < - VERBAL 618 PI2 < - INTENTION 955 PI1 < - INTENTION 940 PI4 < - INTENTION 907 PI3 < - INTENTION 935 IL3 < - INVOLVEMENT 859 IL2 < - INVOLVEMENT 755

Estimate IL1 < - INVOLVEMENT 648 IL4 < - INVOLVEMENT 673 ST4 < - SRUCTURE 712 ST1 < - SRUCTURE 528 ST3 < - SRUCTURE 635 ST2 < - SRUCTURE 644

Covariances: (Group number 1 - Default model)

Estimate S.E C.R P Label GRAPHIC < > VERBAL 120 043 2.756 006 GRAPHIC < > INTENTION 647 133 4.876 ***

GRAPHIC < > INVOLVEMENT -.003 078 -.040 968 GRAPHIC < > SRUCTURE 045 056 801 423 VERBAL < > INTENTION 220 069 3.206 001 VERBAL < > INVOLVEMENT -.023 043 -.544 587 VERBAL < > SRUCTURE 029 031 948 343 INTENTION < > INVOLVEMENT 230 124 1.864 062 INTENTION < > SRUCTURE 532 107 4.967 ***

Correlations: (Group number 1 - Default model)

Estimate GRAPHIC < > VERBAL 277 GRAPHIC < > INTENTION 486 GRAPHIC < > INVOLVEMENT -.004 GRAPHIC < > SRUCTURE 081 VERBAL < > INTENTION 320 VERBAL < > INVOLVEMENT -.053 VERBAL < > SRUCTURE 101 INTENTION < > INVOLVEMENT 173 INTENTION < > SRUCTURE 603 INVOLVEMENT < > SRUCTURE 165 e7 < > e10 410

Variances: (Group number 1 - Default model)

Squared Multiple Correlations: (Group number 1 - Default model)

Estimate ST2 415 ST3 403 ST1 279 ST4 507

Estimate IL4 452 IL1 419 IL2 570 IL3 738 PI3 875 PI4 823 PI1 884 PI2 912 VB1 382 VB5 463 VB4 485 VB8 505 VB7 446 VB6 492 GR8 335 GR5 471 GR1 520 GR9 506 GR6 545 GR7 617 GR10 580 GR2 585 GR4 663 GR3 710

SEM

Number of distinct sample moments: 300 Number of distinct parameters to be estimated: 55

Minimum was achieved Chi-square = 388.004 Degrees of freedom = 245 Probability level = 000

Model NPAR CMIN DF P CMIN/DF

Model RMR GFI AGFI PGFI

Delta2 TLI rho2 CFI Default model 842 822 935 926 934 Saturated model 1.000 1.000 1.000 Independence model 000 000 000 000 000

Model PRATIO PNFI PCFI Saturated model 000 000 000 Independence model 1.000 000 000

Default model 143.004 93.328 200.611 Saturated model 000 000 000 Independence model 2181.623 2026.825 2343.813

Default model 2.658 979 639 1.374 Saturated model 000 000 000 000 Independence model 16.833 14.943 13.882 16.054

Model RMSEA LO 90 HI 90 PCLOSE

Model AIC BCC BIC CAIC

Default model 498.004 520.732 662.478 717.478 Saturated model 600.000 723.967 1497.130 1797.130 Independence model 2505.623 2515.540 2577.393 2601.393

Model ECVI LO 90 HI 90 MECVI

Default model 3.411 3.071 3.806 3.567 Saturated model 4.110 4.110 4.110 4.959 Independence model 17.162 16.102 18.273 17.230

Scalar Estimates (Group number 1 - Default model) Maximum Likelihood Estimates

Regression Weights: (Group number 1 - Default model)

Standardized Regression Weights: (Group number 1 - Default model)

Estimate INTENTION < - GRAPHIC 399 INTENTION < - VERBAL 153 INTENTION < - STRUCTURE 555 GR3 < - GRAPHIC 842 GR4 < - GRAPHIC 814 GR2 < - GRAPHIC 765 GR10 < - GRAPHIC 762 GR7 < - GRAPHIC 785 GR6 < - GRAPHIC 738 GR9 < - GRAPHIC 712 GR1 < - GRAPHIC 721 GR5 < - GRAPHIC 686 GR8 < - GRAPHIC 580

PI2 < - INTENTION 955 PI1 < - INTENTION 941 PI4 < - INTENTION 908 PI3 < - INTENTION 935 ST4 < - STRUCTURE 710 ST1 < - STRUCTURE 530 ST3 < - STRUCTURE 634 ST2 < - STRUCTURE 645

Covariances: (Group number 1 - Default model)

Estimate S.E C.R P Label GRAPHIC < > VERBAL 120 044 2.758 006 GRAPHIC < > STRUCTURE 045 056 802 423 VERBAL < > STRUCTURE 029 031 940 347 e7 < > e10 277 065 4.263 ***

Correlations: (Group number 1 - Default model)

Estimate GRAPHIC < > VERBAL 277 GRAPHIC < > STRUCTURE 081 VERBAL < > STRUCTURE 100 e7 < > e10 410

Variances: (Group number 1 - Default model)

Squared Multiple Correlations: (Group number 1 - Default model)

MODERATOR

Computation of degrees of freedom (Default model)

Number of distinct sample moments: 36 Number of distinct parameters to be estimated: 22

Minimum was achieved Chi-square = 25.536 Degrees of freedom = 14 Probability level = 030

Model NPAR CMIN DF P CMIN/DF

Model RMR GFI AGFI PGFI

TLI rho2 CFI Default model 816 631 907 791 896 Saturated model 1.000 1.000 1.000 Independence model 000 000 000 000 000

Model PRATIO PNFI PCFI Default model 500 408 448 Saturated model 000 000 000 Independence model 1.000 000 000

Default model 11.536 1.114 29.755 Saturated model 000 000 000 Independence model 110.533 77.518 151.081

Default model 175 079 008 204 Saturated model 000 000 000 000 Independence model 949 757 531 1.035

Model RMSEA LO 90 HI 90 PCLOSE

Model AIC BCC BIC CAIC

Default model 69.536 72.426 135.325 157.325 Saturated model 72.000 76.730 179.656 215.656 Independence model 154.533 155.584 178.457 186.457

Model ECVI LO 90 HI 90 MECVI

Default model 476 405 601 496 Saturated model 493 493 493 526 Independence model 1.058 832 1.336 1.066

Scalar Estimates (Group number 1 - Default model) Maximum Likelihood Estimates

Regression Weights: (Group number 1 - Default model)

ZMPI < - ZMVB 186 060 3.106 002 ZMPI < - ZMIL 109 058 1.871 061 ZMPI < - ZMSTxZIL 115 057 2.007 045

Standardized Regression Weights: (Group number 1 - Default model)

Estimate ZMPI < - ZMGR 419 ZMPI < - ZMST 449 ZMPI < - ZMVB 191 ZMPI < - ZMIL 112 ZMPI < - ZMSTxZIL 120

Covariances: (Group number 1 - Default model)

Estimate S.E C.R P Label ZMGR < > ZMIL 014 082 166 868 ZMIL < > ZMGRxZIL -.132 088 -1.507 132 ZMGR < > ZMGRxZIL -.045 086 -.524 600 ZMIL < > ZMSTxZIL -.047 083 -.573 567 ZMST < > ZMSTxZIL 039 084 462 644 ZMIL < > ZMVBxZIL 123 078 1.572 116 ZMVB < > ZMIL -.057 082 -.696 486 ZMVB < > ZMVBxZIL -.014 076 -.187 852 ZMGR < > ZMVB 215 084 2.554 011