Master Thesis The Impact of Country-of-Origin and Cultural Values on the Purchase Intention and Willingness-to-Pay a premium for organic products

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Master Thesis

The Impact of Country-of-Origin and Cultural Values on the

Purchase Intention and Willingness-to-Pay a premium for

organic products

Eugenia Chirica

University of Groningen

Faculty of Economics and Business

MSc Marketing Management

e.chirica@student.rug.nl

s3463818

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_{supervisor: Prof. Dr. L. M. Sloot}

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Abstract

The research paper attempts to explore the impact that relationships between the country of origin of product (e.g. local, imported), the product’s organic nature and the consumer’s individual cultural values have on the purchase intention and willingness-to-pay for a hedonic or utilitarian product. A survey with 8 experimental conditions was distributed via a digital environment and completed by 284 respondents that live either in the Netherlands or in Romania. Afterwards, multiple-way ANOVAs and regression were employed in testing the conceptualized model. It was revealed the consumers have a very strong preference for local products and the highest purchase intention for locally made products regardless of the organic or hedonic nature the product might have. In the case of willingness-to-pay a premium, the organic product exceeded the local one, yet the results for this dependent construct cannot be generalized on population level. Additionally, it was revealed that cultural dimensions did not have a moderating effect.

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1. Introduction

We live in an interconnected world. Global sourcing practices are increasingly incorporated into the food supply (Ganesan, George, Jap, Palmatier, & Weitz, 2009). Scandals that involve food incidents grow easily from local to cross-boundaries international impact on consumers (Barbarossa, De Pelsmacker, Moons, & Marcati, 2016). This leads to changes in what and how food is consumed across the world. The saying “You are what you eat” can be hypothesized, tested, and afterwards, have a transformative effect on the offer of a retailer or, proliferation of a restaurant chain. In this context, retailers take upon themselves the role of “gatekeepers between consumers and eco-friendly products” (Guyader, Ottosson, & Witell, 2017).

Managers of retail chains are faced with the challenge of delivering transparent information about the level of safety and the origin of their food assortments to the “people” without sacrificing the “profits” (Wognum, Bremmers, Trienekens, Van Der Vorst, & Bloemhof, 2011). Throughout this process they need to adjust their strategies in accordance with the leading trends in food retailing. Healthiness is one of the four trends identified by the EFMI Food Trend Model as a trigger of innovation that may lead to either value growth from improved quality or to strengthened competitive position. The popularity of the healthiness trend is illustrated by the growing demand for organic products in food and cosmetics industries (Ghazali, Soon, Mutum, & Nguyen, 2017). The term organic food implies compliance with the legal regulations that limit the usage pesticides and fertilizers in production process (McFadden & Huffman, 2017).

Organic food production and consumption has become a trending research and practice topic as well. From the practice standpoint, according to Statista (2018), the sales of organic products in Europe have almost tripled from 10.2 billion euros in 2004 to 29.8 billion euros in 2015. Moreover, the overall surface used for organic agriculture in Europe in 2015 has reached 12.7 million hectares, which is more than twelve times the area of land used in 1994. Whereas from the research perspective, several studies tackled the underlying psychological reasons behind the consumer’s intention to purchase organic products (Rana & Paul, 2017), whilst others included the product specific attributes in the study of demand for organic food (e.g. Asif, Xuhui, Nasiri, & Ayyub, 2018).

A drawback of many organic food studies is that they focus on the reason behind the behaviour of the already existing pool of organic food consumers at the expense of the potential customers sample and the new insights they could give. Several researchers explored how organic product attributes influence the hedonic or utilitarian perception of the consumer at individual level and the subsequent behavioural intention (e.g. Lee & Yun, 2015; Apaolaza, Hartmann, López, Barrutia, & Echebarria, 2014). Moreover, although there are studies that tackle the product type and organic nature simultaneously (e.g. Hidalgo-Baz, Martos-Partal, & González-Benito, 2017; Mantovani, Tarola, & Vergari, 2016), they build on the premise that organic products are hedonic products. Hence, in this study, one of the objectives is to provide the bigger picture by including both hedonic and utilitarian types of food products that can be grown both, organically and conventionally.

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comparative research. What is more, despite the fact that there are several studies on the Country-of-Origin (COO) effects in the case of food retailing, there is solely a limited number of studies that tackle COO and organic food consumption simultaneously (Thøgersen, Pedersen, Paternoga, Schwendel, & Aschemann-Witzel, 2017a). (Thøgersen, Pedersen, Paternoga, Schwendel, & Aschemann-Witzel, 2017b) Therefore, a retailer lacks the necessary academic support when put in the position of deciding between launching an organic private-label (PL) product-line using ingredients from the country it operates in “made in home-country (HC)” or importing the ingredients “made in foreign home-country” for more countries in which the chain operates.

Consequently, the aim of this study is to fill that gap by putting together the mentioned 3 pieces of the food retailing puzzle: organic nature of the product, COO, and utilitarian or hedonic product nature; and analysing the impact they have on the willingness-to-buy (WTB)1

and willingness-to-pay a premium (WPP) when accounting for the moderating effect of the cultural norm influence. Accordingly, the main research question and the sub questions of this study are as follows:

RQ1: What is the effect of COO on the purchase intention for organic products when

considering the utilitarian or hedonic nature of product and the cultural influence?

SQ1: Does the country cultural norm moderate the impact of COO of organic product on the

purchase intention?

RQ2: What is the effect of COO on the WTP a premium for organic products when

considering the utilitarian or hedonic nature of product?

SQ1: Does the country cultural norm moderate the impact of COO of organic product on the

WTP a premium?

SQ2: Are the differences between the purchase intention and WTP for local opposed to

imported organic products significant for retailers?

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2. Literature Review

This paper investigates the conjoint impact of the organic nature of the product, COO, the utilitarian or hedonic shopping value, and the cultural influence on outcomes of importance to retailers. Therefore, in this section the theoretical background for the separate elements of the study is presented.

2.1. Studies on the organic nature of the product

Organic food is the outcome of organic agriculture that is subject to a set of farming regulations. The regulating institutions impose a ban on synthetic fertilizers and pesticides usage throughout the entire production journey (McFadden & Huffman, 2017). Additional farming regulations are imposed on regional or country level for issuing a certificate that states the product is organic. For instance, whereas in USA synthetic somatotropin may be used as a growth hormone, in the European Union (EU), it is forbidden (Gomiero, 2017). Due to the differences in the farming process, organic products are often perceived as more nutritious than the conventionally grown products. Previous comparative research on the nutritional value of organic fruit opposed to the nutritional value of conventional fruit has shown that indeed organic fruit is richer in vitamins and antioxidants (Mditshwa, Magwaza, Tesfay, & Mbili, 2017).

However, according to the Mditshwa et al. (2017), the better taste perception for organic products is a “halo effect” from the “organic label” tag. This conclusion has been reached in another study by Tobin et. al (2013) of the difference between the sensorial attributes of a range of organically and conventionally produced fruits and vegetables. The study has shown that there are no significant differences between the colour, taste, smell, sweetness, flavour, and aftertaste attributes of the organic and conventional fruits and vegetables sampled (Tobin, Moane, & Larkin, 2013).

In addition to the studies that focused on the nutritive and sensorial differences between organic and conventional products, several studies focused on explaining the influence of the consumer specific attributes that affect the decision to act in particular way towards organic food consumption (Rana & Paul, 2017) using the Theory of Planned Behaviour (TPB) as a valid measure (Paul, Modi, & Patel, 2016). In the table below, a few selected studies that tackle the purchase intention for organic products using the TPB and the factors they found influential for the intentional decision to purchase organic products are presented.

Table 1. Chosen studies and the found influencing factors

Author(s) Influential factors for opting to buy organic products (Hwang, 2016) Self-presentation

(Kauppinen-Räisänen, Rindell, & Åberg, 2014)

Degree of conscientiousness as environmental awareness indicator

(Yadav, 2016) Both altruistic (e.g. concern for environment) and egoistic (e.g. concern for individual health) values

(Prentice, Chen, & Wang, 2017a)

Food safety and environmental issues related attributes (such as: labelling, logos, certifications) and their impact on individual attitude

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Furthermore, from table 1, one can see some similarities in the findings on the underlying consumer motivation for purchasing organic as follows: both external factors and internal factors play a significant role in the decision-making process. As Hill and Lynchehaun (2002) stress in their paper, cultural values as well play an important role in the consumers’ food choice decision-making. Throughout this study, the consumers’ personal cultural values will be used in the analysis of the effect that country-of-origin labelling of organic or conventional products has on consumers’ behavioural intention.

2.2. Studies on the COO

Stressing the previously mentioned importance of being informed about the origins of the available food offer among modern consumers, country-of-origin strikes as a relevant element in understanding the current food-retail mechanism. COO refers to the added positive or negative perceptions of a product derived from the nationality of the product specified on its label (Yunus & Rashid, 2016). The country-of-origin image (COI) has a halo or horn effect on the way products are evaluated (Carneiro & Faria, 2016). In this sense, a handful of studies focused on defining the country-image impact on specific product perception from a specific country, such as the “made in China” horn effect for Huawei smartphones (Yunus & Rashid, 2016), Belgian chocolate halo effect (Rousseau, 2015), and French wine perceived superior quality (Celhay & Remaud, 2018).

Additional food retail COO studies focused on specific food categories from a COO in comparison with one or more available alternative COOs for the same type of product. For example, meat from USA COO is perceived as more qualitative and is preferred to the one from Mexico (Berry, Mukherjee, Burton, & Howlett, 2015), honey from a particular Finnish region is perceived as sweeter and preferred to honey from other Finnish regions within the Finnish COO among a Finnish sample of respondents (Kortesniemi et al., 2018). Although, there are some studies that attempt to make the distinction between products with local COO label and foreign label (e.g. Beiermann, Jones Ritten, Thunström, & Ehmke, 2017; Costa, Carneiro, & Goldszmidt, 2016), in line with the research conducted by Carneiro and Faria (2016), using several different conceptualizing methods for the COO impact has led to inconsistent study outcomes and a limitation in the cross countries, cross studies comparison option.

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2.3. Studies on the hedonic or utilitarian shopping value of the product

The hedonic and utilitarian approach within research been applied in three prominent roles: as the shopping value, as the shopping motivations, and as the type of product (Bradley & LaFleur, 2016). Firstly, the hedonic and utilitarian shopping value refers to the type of value one gains through the shopping experience. Hedonic shopping value is given by the stimulation of multiple sensorial receptors and of the emotive area when shopping, whereas utilitarian shopping value is given when the shopping experience is task-oriented and stimulates mainly the cognitive perception (Jones, Reynolds, & Arnold, 2006).

Secondly, hedonic and utilitarian dimensions have been used in understanding and explaining the shopping motivations of the customers. While the ultimate utilitarian shopping motive is in the completion of the functional task, such as buying a needed product, the hedonic shopping motive is slightly more diverse as it is in the stimulation of fun, sensorial experience in order to fulfil a “hedonic task” (Arnold & Reynolds, 2003). According to Arnold et al. (2003), there are six categories of hedonic shopping motivations: adventure shopping, social shopping, gratification shopping, idea shopping, role shopping, and value shopping. The six hedonic shopping motivation categories have been employed in various research contexts. For instance, the hedonic shopping motivations were used in explaining the shopping motives across countries with different cultural values, such as collectivism and individualism (see Evanschitzky et al., 2014), or in researching the connection between hedonic motivations and compulsive buying in developed and emerging markets (Horváth & Adigüzel, 2017). If one were to use this approach for the classification of food into hedonic or utilitarian kind, any food product that is sold with a promotional discount could become the subject of hedonic value shopping motivation.

Thirdly, the utilitarian and hedonic product type classification is done in accordance with the predominance of the cognitive or affective processing route usage by the customer when exposed to a product (Voss, Spangenberg, & Grohmann, 2003). Among the existing conjoint research on organic products and the hedonic food type, many researchers opted for the vice and virtue distinction, where vice food is mainly hedonic and virtue food utilitarian. Van Doorn and Verhoef (2011) have found that the organically labelled vice food products were perceived as less qualitative by consumers, and the lower quality perceived quality subsequently affected negatively the willingness-to-pay a premium.

In the case of categorization of food products along the hedonic or utilitarian dimensions, Loebnitz and Grunert (2018) find the different end-goals that food consumption leads to as a primary criterion. Hence, if the consumption of a food product is caused by hunger, the product is utilitarian, on the other hand, if the food consumption is motivated by the consumer’s desire for pleasure, the product is hedonic. Given the fact that this study makes use of the distinction between hedonic and utilitarian food, this later definition of utilitarian and hedonic product types will be used in this paper and not the hedonic shopping value nor the hedonic shopping motivation.

2.4. Studies on the cultural influence

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consumption across countries (Minton, Spielmann, Kahle, & Kim, 2018). Moreover, cultural dimensions have been found effective in explaining the COO influence in food choice (Barbarossa et al., 2016).

Concerning the study of organic food consumption, the most relevant dimensions appear to be individualism-collectivism, uncertainty avoidance, A Long-term (LT) versus Short-term (ST) orientation, and indulgence. Collectivism and uncertainty avoidance are two of the four original cultural dimensions. Whereas LT orientation and indulgence have been added later to the list of dimensions.

Firstly, collectivism makes the distinction between the people in individualistic countries, who look after their individual benefit in decision making, and people in collectivistic countries, who live as members of a group and do what the majority does (G. H. Hofstede, 1983). Secondly, uncertainty avoidance relates to the way in which people accept the uncertainty of the future ahead of them, mainly people with weak uncertainty avoidance are expected to be more open to beliefs and attitudes that differ from their own, while people with strong uncertainty avoidance are likely to engage in behaviour and decision-making that leads to avoidance or reduction of the risks from unknown.

Thirdly, the LT versus ST orientation was the fifth dimension added to the original four dimensions model. LT oriented countries were described by the ability to deny oneself an instant gratification for bigger gain in the further future, whereas ST oriented countries have people who are closer to a present, immediate gratification mindset at the expense of potential future vulnerability, which is not an object of their worries (G. Hofstede, 1999).

Additionally, a sixth dimension was added in 2010, the indulgence versus restraint. People from highly indulgent countries are more likely to gratify immediately wishes that lead to joyful experiences, and to have a stronger perceived control over their own lives when compares to less indulgent or more restraint people (G. Hofstede, 2011).

Having defined the chosen cultural dimensions, it is worth mentioning that a study on green consumption has investigated their role of collectivism and LT versus ST orientation as independent variables (Sreen, Purbey, & Sadarangani, 2018). However, the study is limited solely to the Indian market and is different from a study on organic products as green products include a wider category of products that are mainly characterized their sustainability, which is not the same as organicity.

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3. Conceptual Model

In the general conceptual model of this study, two independent variables are considered: Country-of-origin and organic nature of the product. The cultural influence and hedonic product type variables are controlled for moderating effect each, whereas the measured dependent variables are purchase intention and WPP.

The figure below illustrates the conceptual model framework.

Figure 1. Conceptual framework of the study

Furthermore, the underlying relationships behind the construct are presented along with the hypotheses.

3.1. The effect of COO

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the researcher suspects an interaction effect between the two variables. Adding to this list of studies, the model of (Dransfield et al., 2005), according to which the first part of this study is modelled, and the results that have shown higher purchase intention and WTP for locally produced food regardless of its organic or conventional nature, the following hypotheses are developed:

Hypothesis 1a. Local COO is likely to lead to higher purchase intention than imported

products.

Hypothesis 1b. Local COO is likely to lead to higher WPP than imported products.

Hypothesis 1c. Products that are both organically labelled and of local COO should yield the

highest WTB and the highest WPP.

3.2. The effect of Organicity of a Product

In the context of this study, the organic and conventional nature of a product is given according to its production means. Certified organic products (products with the organic label) are the result of organic farming practices within a frame of legal regulations at region or country level. They have been proved to have a higher nutritional value than their conventional counterparts (Mditshwa et al., 2017), however the augmented sensorial experience in taste, for instance, was proven to be a halo effect. Moreover, among the most common organic labelling biases is the healthier halo effect that was tested by Lee, Shimizu, Kniffin, and Wansink (2013). They took three pairs of two identical organic products, where one product was labelled organic and the other regular. The conducted preference and WTP test resulted in a between 16 and 23.4% higher WTP interval for organically labelled products than for regular ones. Based on these highlighted results and the theoretical background on organic products, the following hypotheses are formed:

Hypothesis 2a. Organic labelled products are expected to yield a higher purchase intention

than conventional ones.

Hypothesis 2b. Organically labelled products are expected to yield a higher WPP than

conventional ones.

3.3. The effect of hedonic or utilitarian product type

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Hypothesis 3a/b. When a product is hedonic, the positive effect of (a) organic labelling/(b)

local COO on the PI and WPP will become more positively augmented than when a product is utilitarian.

3.4. The effect of cultural values

As pointed earlier, the Hofstede’s selected cultural dimensions are used at adapted individual level.

3.4.1. Collectivism and High Uncertainty Avoidance

Collectivism regards the individual as part of the group that acts according to the norms of the group. Sreen et al. (2018) have found that collectivism directly influences the attitude, perceived behavioural control, and subjective norms, which are direct predictors of the purchase intention as part of TPB. High collectivistic score at individual level is expected to lead to higher feeling of connection with the community one belongs to.

H4a: The level of individual collectivism will positively moderate the impact of local COO

on PI and WPP

Uncertainty avoidance is about the degree of openness to the unfamiliar and unknown among people. People with high uncertainty avoidance are expected to be more resistant to beliefs and attitudes that differ from their own (Hofstede, 1983). Hence, when it comes to choosing between a product of familiar origin and one of less known origin, the high uncertainty segment shall choose the product of familiar origin.

H4b. High uncertainty avoidance will positively moderate the effect of products of local COO

on the WTB and WPP

3.4.2. LT Orientation and Indulgence

Countries that are LT oriented usually deny oneself an instant gratification for bigger gain in the future. For a LT oriented individual this could mean refraining himself from overeating for better health in the future. In the light of the more nutritional content of organic food, the following is hypothesized:

H4c: LT orientation will positively moderate the effect of organic product type on the WTB

and WPP

Indulgence edge of the indulgence-restraint cultural dimension is similar to the ST edge of the LT-ST orientation dimension (Hofstede, 2011). People with high indulgence frequently engage in instant gratification for experiential reason and due to the perceived behavioural control. Indulgent people are those who are more likely to “indulge” themselves with premium purchases. Organic products are associated with premium price amongst the minds of the consumers. Prentice et al. (2017) have tested the individual level indulgence for moderating effect on the relationship between organic certification and purchase intention and found a significant moderating effect. Hence, this leads to the following hypothesis:

H4d: Indulgence will positively moderate the effect of organically produced food on the

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4. Methodology

This chapter tackles in detail the experimental design of the study, the variables measurement, the population overview, and the data analysis plan.

4.1. Design of the study and sample selection

For this research, a 2x2x2 between-subjects design is used with the following two-levelled factors: organic nature of the product (organic/conventional), COO (local/imported), and hedonic type of the product (hedonic/utilitarian). Although the hedonic type of the product is tested for a moderating role, for the research study the variable is an experimental one.

Moreover, to allocate respondents to one of the eight conditions, web-surveys shall be designed and distributed among a sample of Dutch and Romanian respondents through the digital medium. The method of sampling is convenience sampling, considered to be a common type of sampling due to its convenience and easiness regarding accessibility for the researcher (Elliot, Fairweather, Olsen, & Pampaka, 2016). This sampling type is used due to the limited time and resources availability. Even though the convenience sampling definition points at the drawbacks of the sampling method, mainly the fact that the sample might not be representative enough for the population (hence not generalizable), convenience sampling has been found as the most common sampling method for both qualitative and quantitative data among graduate theses (Catalano, 2013).

4.2. Experimental manipulation

As previously mentioned, the study has a 2x2x2 format. The reason for which the hedonic product type is added to the experimental variables list along with the independent factors lies in the author’s assumption that by using a hedonic/utilitarian product the respondent will perceive hedonic/utilitarian added value. Subsequently, this moderates the impact of both independent variables on the dependent ones.

The chosen product category is fruits and vegetables, given the expansion of organic practice within it. Furthermore, the selected hedonic and utilitarian products are strawberries that generate sensorial experience and tomatoes that are mainly consumed as part of meal for hunger satisfaction or being healthy. The main underlying reason behind this choice is the fact that both products are produced locally and imported for Dutch and Romanian respondents, and both products are sold in an organic and a regular format simultaneously.

The organic/local origin manipulations

The web-survey, following the personal information consent and privacy form, has a randomization block that is responsible for allocating the respondents evenly across the 8 conditions. The 8 images used in this phase are presented in Appendix 1.

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4.3. Measurement

Except for the manipulated block, where the respondent is given only one product type that can be a combination between hedonic or utilitarian, organic or conventional, and of local COO or imported, all the questions the respondents are exposed to are the same across the conditions. Additional information on demographic variables for control purpose was collected at the end of the study, after the purchase intention, WPP, and individual level cultural influence has been measured through validated in academic context constructs.

4.3.1. Measurement of Purchase Intention

Purchase intention is measured using a 7-point Likert scale on items adapted from Sreen et al. (2018). Items like “I will purchase the shown product in my next visit” are included. The scale has been validated and employed in several academic research papers with the TPB framework.

4.3.2. Measurement of WPP

Barber, Kuo, Bishop, and Goodman (2012) make the distinction between contingent and trasaction data-based means of measuring the willingness-to pay. The contingent method is rather easy to implementate as it asks the consumer directly for a stated amount that they are willing-to-pay, however, many respondents have the tendency to overestimate the value of this amount, which leads to erronate results. To account for this consumer tendency, the second method of WTP measurement through actual trasaction data provides more accurate results through employment of techniques such as Vickery auction, where the highest bidder has to buy the product at the price stated by the second highest bidder. Nonetheless, in this study the contingent valuation method is employed with the question: “Knowing that 250 grams of strawberries/tomatoes cost on average 1.39/0.99 euros, what do you think the value of the packaged product you saw is?” adapted from Barber et al. (2012). In order to fight off the drawbacks associated with this method, instead of an open question, the respondents are given 7 options to choose from the estimate that is the closest to theirs as follows: „1) About 50% cheaper 2) About 30% cheaper 3) About 10% cheaper 4) About the same price 5) About 10% more expensive 6) About 30% more expensive 7) About 50% more expensive”.

4.3.3. Measurement of Cultural Influence

For the cultural influence constructs, the validated individual level items of Sharma (2010) for collectivism, uncertainty avoidance, and LT orientation have been adopted. Whereas the individual level indulgence measurement items have been adopted from the study of Prentice et al. (2017). All the items are rated on a 7-point Likert scale (with values ranging from 1 = STRONGLEE AGREE to 7 = STRONGLY DISAGREE). An overview of all the selected constructs and the items can be seen in Appendix 2.

4.3.4. Measurement of hedonic perception

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4.3.5. Control variables

Two types of control variables were collected as part of the study. The first type controlled whether the manipulation was effective among the respondents by asking them three questions at the very end of the survey: what product they saw, was it organically labelled, was it produced locally. A correct answer to the first question in addition to another correct answer allows to keep the respondent. A dummy variable with the participants that answer correctly all the three questions was constructed. The newly created dummy was used for the second type of control, control whether the differences between those that passed the total manipulation control check and those who did not were significant. The second control variable of such kind is the country of residence. With a few exception all respondents currently live either in Romania either in the Netherlands, the differences between a citizen of a western country and one of a central European country became relevant. Bogdan and Novak (2017) point at the bigger financial insecurity among the youth from central Europe in contrast to the youth of western countries, consequently income is also controlled for. Another control measure for testing the successful experimental manipulation of the hedonic nature of the product was introduced through the product hedonic level variable.

4.4. Data Analysis Plan

Having all the data gathered, the first step in its analysis was to clean the dataset from outliers with missing or unrealistic answers. Secondly, the manipulation check output was analysed, thereupon a descriptive analysis of the sub-sample per condition with the end goal of familiarity with the data resulted in the table 2 below.

Table 2. Summary of the obtained data with means

Conditions, Manipulations and Means 1 2 3 4 5 6 7 8 Frequency (n) 31 35 31 35 35 35 32 36 Frequency (%) 11.5% 13.0% 11.5% 13.0% 13.0% 13.0% 11.9% 13.3% Manipulation

Organicity no no yes yes no no yes yes

COO local imported imported local imported local local imported

Hedonic yes yes yes yes no no no no

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5. Results

The aim of this chapter is to describe all the steps prior to hypotheses testing and the hypotheses testing results. Initially for this purpose a two-way MANOVA was meant to be used as described in the methodology section. The first steps in this regard included testing for the assumptions of the model, mainly if there is a linear relationship between the pair of dependent variables for each of the eight experimental condition groups. A scatterplot assessment has revealed that there is no linear relationship between WTB and WPP in the dataset (see Appendix 3).

Tabachnick and Fidell (2014), affirm that without a linear relationship between the variables, the power of the two-way MANOVA to spot differences between groups decreases. Following this first red flag, the multicollinearity assumption was tested for subsequently. Pearson’s correlation values were more than 0.6 points below the accepted threshold of │r│< .9 (see Appendix 4), hence the two dependent variables are only moderately correlated. In the light of these details, two separate two-way ANOVAs were considered more fit for testing the model.

5.1. Sample description

This study has reached a total of 285 respondents, however only 278 entirely completed the survey. Furthermore, following the manipulation check section outcome, the respondents that did not identify the product correctly (5) and the outliers (3)2_{were removed from the data,}

hence the sample size was reduced to n=270.

51,8% of the sample population has the residence in Romania, while 47.1% reside in the Netherlands, and the remaining 1.1% resides in other countries. The ration of female to male respondents was close to two to one, with 64.4% females and 35.6% males. Although the study is equally interested in main shoppers as well as secondary shoppers, the main shopper role was measured among the sample and revealed that 64.1% of the respondents kept in the study are primary shoppers in their household. The average age of the respondent across all the 8 conditions is 24. In table 3 (below), the demographics summary per condition is shown.

Table 3. Demographics overview

Conditions 1 2 3 4 5 6 7 8 Age 23.7 23.9 24.2 22.9 25.5 24.3 23.6 24.8 Gender male 35.5% 42.9% 25.8% 34.3% 40.0% 37.1% 31.3% 36.1% female 64.5% 57.1% 74.2% 65.7% 60.0% 62.9% 68.8% 63.9% Education (%) Middle school 2.9 High school 29 25.7 16.1 31.4 17.1 20 25 13.9 College 12.9 8.6 9.7 11.4 2.9 11.4 6.3 5.6 Bachelor’s degree 48.4 51.4 67.7 37.1 40 42.9 53.1 55.6 Master’s degree 9.7 14.3 6.5 14.3 34.3 22.9 15.6 25 PhD 2.9 Other 5.7 2.9 Household size 3.58 3.21 2.43 3.20 1.94 2.51 2.84 3.14

Main grocery shopper

Yes (%) 54.8 60 71 51.4 80 65.7 68.8 61.1 No (%) 45.2 40 29 48.6 20 34.3 31.3 38.9

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5.2. Data checks

Furthermore, the employment of boxplots as part of the exploratory analysis has highlighted 7 more outliers for WTB scores and 10 more outliers for WPP scores. The outliers are more than 3 box-lengths farther from the edge of the box. Out of the 10 outliers for WPP, 3 were extreme ones. However, given the realistic values offered by the respondents and the fact that data was not incorrectly measured or missing, ANOVA tests were performed with and without outliers for each dependent variable. In the case of WTB, the tests showed no significant difference in the models with the removal of the outliers, however in the case of WPP, the model was better, with higher adjusted R squared value (+ .013). Consequently, weighting all the facts, the researcher decided to keep the outliers in the sample and be more conscious in the statistical interpretation of ANOVA for WPP.

5.3. Validity and Reliability measurement

The constructs used in this research for data collection have been used in prior studies, nonetheless, a factor analysis with the principal component extraction analysis was conducted to test the validity and reliability of the gathered output. The factor analysis has revealed the simultaneous presence of 6 factors from all the 20 introduced items. The factors were named: purchase intention, collectivism, high uncertainty avoidance, long-term orientation, indulgence, and hedonic degree. Subsequently, each factor was tested for validity using the KMO value and Bartlett’s test significance post an exploratory factor analysis. All the factors had very significant scores on Bartlett’s test of sphericity (p=.000 for each construct) and had met the KMO threshold value (>.500).

Furthermore, each factor’ reliability degree was measured using Cronbach’s alpha. According to the output of the test, all the constructs are reliable and have exceeded the .600 threshold point (Malhotra,2010). A summary of the presented data for the validity and reliability tests is presented in table 4 below.

Table 4. Validity and Reliability coefficients for the constructs

Factor KMO Bartlett’s test Cronbach’s

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Having proven the validity and reliability of the constructs, the researcher performed tests with factors and with the average values per construct. As there were no difference in the results, the researcher used the mean value per construct throughout the rest of the study.

5.4. Assumptions for parametric test

For assessing if the data is fit to be the subject of a parametric test like two-way ANOVA, several assumptions must be met. Mainly, the presence of two or more categorical independent variables and the presence of a continuous dependent variable. In this case, the study encompasses two dichotomous variables as independent variables and one as experimental variable, whilst both the dependent variables are continuous.

5.4.1. Normal distribution

The normal distribution assumption of data is required for the performance of a parametric test. The researcher has chosen to check if the assumption holds true by looking at the skewness and kurtosis values for each condition group and each dependent variable. For each measured dependent variable, half of the eight sub-samples meet the -2/+2 values for skewness and kurtosis for normal distribution, while almost half of them slightly violate the normality assumption (see Appendix 5). Adding this outcome to the fairly large sample size and the relatively equal sub-samples per conditions leads to accepting a parametric test as appropriate. Additionally, according to Maxwell and Delaney (2004), ANOVAs are considerably “robust” to slight deviations from normality.

5.4.2. Homogeneity of slopes

Another assumption of three-way ANOVA is the homogeneity of slopes, mainly the equality of the variances in WTB and WPP scores across the eight conditions. Using Levene’s test for equality of variances, it was established that there is a homogeneity of variances for WPP (p=.411), whereas for WTB the assumption is violated (p=.041). Given the relatively large size of the sample (270) and its equal distribution across conditions, one can still perform a parametric analysis with three-way ANOVA when homogeneity of slopes is violated provided the ratio of the condition with the biggest variance over the condition with the smallest variance yields a figure smaller than three (Jaccard, 1998). The biggest variance (2.53) was divided by the smallest one (1.04) and a ratio of 2.4 (< 3) was obtained.

5.5. Control variables

Previously in methodology three variables that are suspected to correlate with the dependent variables in the model were mentioned, mainly the complete manipulation success, country of residence, and income. ANOVAs were performed to tests if the correlation posit holds and the control variables need to be included in the model. Furthermore, a control test of the successful manipulation of products as hedonic or utilitarian was conducted.

To begin with country of residence, ANOVA revealed there is no significant difference between groups for both PI (p = .240) and WPP (p = .142). The correlation between complete manipulation effect was performed twice, once on the entire dataset, and once for each experimental condition. The ANOVAs were not significant (p > .05) in both cases. Hence, regardless of whether the manipulation effect on the respondent was partial or complete, the difference between the partially manipulated data and completely manipulated one is not significant for each condition and for the sample overall.

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reason, the variables were not controlled for further in the analysis. Regarding the successful hedonic manipulation, an ANOVA with the perceived hedonic level as dependent variable revealed significant differences between the hedonic perception means of the utilitarian and of the hedonic product. This implies the manipulation was successful. The complete ANOVA outputs can be found in the appendixes 6 to 9.

5.6. Testing the model

In this subchapter, all the hypothesized relationships are tested, and the fitness of the models used for this purpose is assessed. The direct effects of the categorical variables and their interactions were measured through between-subjects ANOVAs for each dependent variable, whereas the moderating effect was tested through a linear regression.

5.6.1. Three-way ANOVAs

A three-way ANOVA, instead of a two-way ANOVA, is employed to respect the independence of observations assumption. Hedonic nature of the product is an experimental variable; thus, it must be included in the model. The results of the ANOVAs are presented in parallel throughout the chapter.

Fit of the model

Initially the fit of the models was assessed by looking at the significance of each corrected model for the factorial ANOVAs and at the R squared value for each. The three-way ANOVA for purchase intention explains 6.5% of the variance in consumers’ willingness-to-buy. On the other hand, the three-way ANOVA for WPP model explains 4.6% change in the variance of willingness-to-pay a premium. The three-way ANOVAs model pointed out that the corrected model was significant when analysing the variance in PI (p =.013) and not significant for the WPP (p = .087), consequently one cannot affirm with 95% confidence that the true mean for WPP of population is included. Consult Appendixes 10 and 11 for the ANOVAs outputs.

5.6.2. Results related to the hypotheses

ANOVA PI

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Furthermore, there was a significant main effect of COO for PI score, F(1, 262) = 6.361, p = .012, partial η2_{= .024. The mean purchase intention for locally made products was 5.193}

(SE = .109) and 4.806 (SE = .108) for imported products, a statistically significance difference of .387, 95% CI [-.690, -.085], p = .012. This result sustains H1a, local COO is likely to lead to higher purchase intention than imported products.

ANOVA WPP

Similar to the ANOVA PI output, there was no statistically significant three-way interaction between organic nature, COO and hedonic nature, F(1, 262) = .487, p = .486. All the effects except for the main effect of the organic nature are not significant for WPP score. In this case,

H1c sustaining that products that are both organically labelled and of local COO should yield

the highest WTB and the highest WPP, is not accepted - due to the lack of an interaction effect on the WTB score and lack of interaction effect on WPP. Moreover, hypothesis H1b is not accepted since COO does not have a significant effect on WPP and the model is not significant on a 95% confidence interval.

The organic nature of the product, however, has a significant main effect on the score of WPP, F(1, 262) = 22.861, p = .001, partial η2 = .039. The statistically significant difference between the mean of the groups with organic products and those with regular ones was of -.133 (SE = .178). This result partially sustains H2b, “organically labelled products are expected to yield a higher WPP than conventional ones”. The partial acceptance of the hypothesis is caused by the inability to generalize relationships to population size from a sample with a model that is not significant.

5.6.3. Moderation analysis

To the researcher’s surprise, the ANOVAs did not include significant main effect from both, COO and organic nature, on both, the PI and WPP. Hence, the moderating analyses were performed partially when applicable. The constructs used in the moderation were mean-centred. There were no multicollinearity issues with all the VIF scores smaller than 10 (Malhotra, 2010), and all the obtained regression models were highly significant (p < .05). An overview of the unstandardized coefficients for the interaction effects and their significance can be seen in table 5.

Table 5. Overview of the moderating results

Hypothesis Dependent

variable

Interaction name Expected

sign

Unstandardized coefficient

Significance level

H4a PI Collectivism x COO

local + -.143 .234 H4b PI Uncertainty avoidance x COO local + .143 .204 H4c WPP LT x Organic + -.010 .959 H4d WPP Indulgence x Organic + -.171 .158

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the COO and organic nature in this study and the hypotheses: H4a, H4b, H4c, and H4d are rejected.

In the previously discussed ANOVAs, the interaction between organic nature and hedonic nature was significant solely for the utilitarian level and solely for PI. Hence, there is no positive moderation between organic nature and hedonic level of the product and H3a is rejected.

To summarize, only the following hypotheses were completely or partially accepted: H1a,

H2a, and H2b. All the other hypotheses were rejected.

6. Discussion

Building on the “organic” trend of EFMI Food Trends Model and literature gaps as signalled by Thøgersen et al. (2017), Rana and Paul (2017), this model aimed to investigate comparatively and simultaneously the impacts of COO and organic nature of a product in a cross-cultural context. Out of the eleven tested hypotheses of this study, seven were rejected due to lack of interaction effect. But the lack of statistically significant interaction effects in an analysis does not necessarily mean the interaction effect does not exist in the population (Aiken, West, & Reno, 1991). Nonetheless, a statistical validity perspective is used in delivering the main insights gathered throughout this study.

Firstly, local country-of-origin was proven to have a very significant effect on the consumers purchase intention regardless of the organic or conventional nature of the product and regardless of the hedonic level of the product. Despite the consumers’ immense preference for local FMCGs, the consumer do not share the same passion for local products when it comes to willingness-to-pay a premium. For this reason, retailers that operate in more than one country are advised to allow more shelf space to locally produced utilitarian products.

Secondly, the fact that organic nature did not influence the purchase intension significantly in this sample was unexpected, but could be explained by the fact that for some consumers the products belonging to the fruit and vegetables category are associated with organic, bio traits even without the label. However, organic nature did influence the willingness-to-pay a premium of the respondents in the sample. The respondents were willing to pay significantly more for the product with the organic label compared to the regular product. Although, as part of this study, the relationship between organic nature and WTP is not generalizable for the population, the difference between the price of organic products and conventional ones is known by every shopper.

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7. Limitations and improvement

The main limitation of this study is the fact that the model attempted to explain multiple relationships at once, and when one main relationship did not hold true, the rest of the relationships based on it could not be further analysed. Future researchers of COO, organic nature and cultural influence could overcome this hurdle by organizing the study in two or three smaller studies that shall be completed and adjusted each according to a timeline. Another limitation of this is study lies in the amount of variance explained by it. A bigger sample size in future research might solve this along with a pool of a more demographically diversified sample.

This led to the convenience sampling in a digital environment limitation of the study, through the fact that most of the respondents are young adults, students with a rather small income. Hence, a recommendation for future research papers would be to conduct a follow up study on a more demographically diversified and bigger sample of people.

One final limitation of this study is the fact that it tackles solely the fruit and vegetable product category. This could be improved simply by conducting a test on more products from more food retail categories (i.e. meat products).

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Appendix list

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Appendix 2. Overview of the constructs, items and adaptation sources

Construct and Items Measure Source of adaptation

Purchase Intention

I intent to buy the shown product I plan to buy the shown product

I will purchase the product I saw in my next visit

5- points Likert scale (with values ranging from 1=Strongly Disagree, 5=Strongly Agree)

(Sreen et al., 2018)

WPP

Knowing that 250 grams of strawberries/tomatoes cost on average 1.39/0.99 euros, what do you think the value of the packaged product you saw is?

7-point scale with the following options to choose from: 1) About 50% cheaper 2) About 30% cheaper 3) About 10% cheaper 4) About the same price 5) About 10% more expensive 6) About 30% more expensive 7) About 50% more expensive

(Barber, Kuo, Bishop, & Goodman, 2012)

Cultural Influence Collectivism

The well-being of my group members is important for me

I feel good when I cooperate with my group members

It is my duty to take care of my family members, whatever it takes

Family members should stick together, even if they do not agree

7-point Likert scale (with values ranging from 1 = strongly disagree to 7 = strongly agree)

(Sharma, 2010)

High Uncertainty Avoidance

I tend to avoid talking to strangers

I prefer a routine way of life to an unpredictable one full of change

I would not describe myself as a risk-taker I do not like taking too many chances to avoid making a mistake

(Sharma, 2010)

LT orientation

I believe in planning for the long term I work hard for success in the future

I am willing to give up today’s fun for success in

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the future

I do not give up easily even if I do not succeed on my first attempt

Indulgence

When I like something, I will buy it without too much deliberation

I always do whatever I feel like and whenever I feel like it

(Prentice, Chen, & Wang, 2017b)

Hedonic level of the product

You will be presented a set of product descriptions below. Please select the description that fits best the product you have previously seen. The product I saw is:

Exciting Delightful Thrilling Fun

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Appendix 4. Pearson’s correlation between the PI and WPP Condition Pearson’s Correlation TIR -.116 SIR -.066 TIO .055 SIO -.131 TLR -.111 SLR -.208 TOL .293 SOL .250

Appendix 5. Skewness and Kurtosis values for normal distribution assumption

Condition Skewness error True Skewness Kurtosis error True Kurtosis

TRI -0,672 0,398 -1,688 -0,715 0,778 -0,919 TRL -1,062 0,398 -2,668 0,745 0,778 0,958 SRI -0,523 0,398 -1,314 -0,302 0,778 -0,388 SRL -1,863 0,421 -4,425 4,273 0,821 5,205 TOI -0,741 0,393 -1,885 0,259 0,768 0,337 TOL -0,975 0,414 -2,355 1,166 0,809 1,441 SOI -0,788 0,421 -1,872 -0,195 0,821 -0,238 SOL -1,156 0,398 -2,905 1,287 0,778 1,654

Appendix 6. ANOVA model of correlation between residence country and the WTB and

WPP

ANOVA

Sum of Squares df Mean Square F Sig. Mean Purchase Intention Between Groups 2,308 1 2,308 1,388 ,240