Determinants of Consumers' Perceived Experience Value in Relation to Online Organic Food Purchase

Organic food buying behavior is high involvement purchase and related to consumers’ deeper value system. The decision-making is quiet complex due to its high price and lack o f t rustworthiness. Therefore, there is a need for separate and more engaging shopping platform, which can co-create a delightful and enjoyable shopping experience for the consumers. Literature does not give a clear understanding about the factors which can influence Consumers’ Perceived Experience Value (CPEV). Hence the study aims to identify the drivers or the determinants of CPEV in relation to online organic food purchase. The objectives of this study are to identify the domain of constructs along with their respective items for CPEV and their relation through qualitative exp loration and validate the items for respective construct through Exploratory and Confirmatory Factor Analysis. The study contributes a scale which can measure the constructs like Cognitive Engagement, Emot ional Engagement, Behavioral Engagement, Telepresence, Willingness to co-create, Willingness to pay for Experience and Ease of Use in relat ion to online organic food purchase which was not available in the existing literature. This will be beneficial for the o rganic food producers to develop a digital marketing strategy and penetrate the market. The study will also help the service and experience designers to explore these opportunities and create a platform for the small-scale farmers and contribute in their livelihood development.


Introduction
The decision around organic food purchase is associated to a deeper value system of the consumers' involving logical and intellectual reasoning (Tarkiainen and Sundqvist, 2009) and co mp licated selection p rocess as the price is high and low trustworthiness (Lavin et al., 2015). Studies show that organic food purchase is considered to be a high involvement decision-making where economic considerations and trustworthyness plays a significant role (Ghosh et. al., 2019). The adoption of organic food is not so satisfactory when marketed with conventional food. Therefore, there is a need for separate and more engaging shopping platform, which can co-create a delightful and enjoyable shopping experience for the consumers. Hence the study aims to identify the drivers or the determinants of Consumers' Perceived Experience Value in relat ion to online organic food purchase.
Experience value is exp lained in the literature as a language which e xp lains "interactive relat ivistic preference experience" (Ho lbrook 1999). This lead by Ho lbrook's have been adopted in many studies where explo ration and testing of this value construct has been done in different market ing situations (Prebensen et al, 2013;Woodall 2003; Sweeney and Soutar 2001). On the other hand, Perceived value has been extensively recognised in various literature related to marketing theories in order to understand consumer behavior (Nilson 1992; Ostrom and Iacobucci 1995) and consumer perceived value (Woodruff, 1997) as "a customer's perceived preference for and evaluation of product or service attributes and their performances, and consequences arising fro m use that facilitate (or b lock) achieving the customer's goals and purposes in use situations." Perceived experience value has also been outlined and tested in various context like hospitality (Al-Sabbahy et. al 2004; Kashyap and Bojanic 2000); in heritage tourism (Chen and Chen 2010), cruise experiences (Du mand and Mattila 2005; Petrick 2004). However, there is not much work has been done in the context of Organic Food Purchase.
Literature shows that consumers' response to a website or any other platform mediated by dig ital technology which comprises of four experiential states. They are consumer engagement, perceived interactivity and ease of use, participation or co-creation and telepresence (Hollebeek, 2011b). Telepresence is a mental state of being present in an environment of a situation med iated by computers or other digital med ia (Mollen & Wilson, 2010). Easy to purchase is one of the key driver to create a better shopping experience for the consumers (Brodie et al., 2011). The concept of Consumer Engagement has a multi-d imensional approach which is based on stakeholders' specific man ifestation of relevant emotional, cognitive and behavioral dimensions which are interactive and co-created through consumer experience (Ho llebeek, 2011a, Groeger et. al., 2016). So et al. (2014) in the study mentioned that by and large consumer engagement has been a theoretical discourse, with very little empirical backing for the development of theory. Also the literature does not give a clear understanding about the factors which can influence Consumers' Perceived Experience Value (CPEV). Hence there is also a need to identify the factors and the relevant items to measure CPEV. Therefore, the study aims to focus on theory development in the area of consumer engagement and consumers perceived experience value in relation to online organic food shopping. The relevant research questions for this study are as follows.

What determines Consumers' Perceived Experience
Value (CPEV) in relation to Online Organic Food Purchase? 2. What drives the consumers to engage with an online organic food brand?

Research Objective
The researcher felt a need for concept development through qualitative exp lorat ion rather than merely testing the existing concepts. Therefore, the study was conducted through a combination of qualitative and quantitative research. The following research objectives are i). Identify the domain of constructs for CPEV and their relation through qualitative exploration. ii). Identify the items for each of the construct through qualitative exploration. iii). Validate the items for respective construct through quantitative technique.

Research Method
The researcher in this study had worked on to identify the related domain of constructs pertaining to consumers' perceived experience value through qualitative exploration.

Qualitative Research Method
Depth interview was conducted through convenience and judgmental sampling. The criteria to select the samples were regular organic food consumer and regular online shopper. The consumers were selected fro m three organic stores in Bangalore who were ready to spare 20-30 minutes for the interview. 10 such interviews were conducted. The interviews were recorded and the transcripts were used for qualitative research. So me open-ended questions which were ad min istered during the depth interview with the respondents. 1. What do you think is the major barrier of organic food purchase? 2. How can we create an experience, wh ich will make online organic food more trustworthy? 3. What are the informat ion you should be looking for in a online organic store?
Grounded Theory and affin ity diagramming was used as a tool for Qualitative Research.

Grounded Theory (GT)
Grounded Theory was first proposed by Glaser and Strauss (1967) under the domain of social science research. This is also an organized and appropriate approach in generating items and cluster them to different dimensions (Parry, 2003). The researcher continued the analysis of the interview-transcripts till it was felt to reach a saturation level along the dimensions and no new items or were getting generated. Grounded Theory is executed through three phases. The first phase is open coding which is considered to be the most intensive phase. This is followed by axial coding and selective coding. Below is an excerpt fro m the transcript of the depth interview conducted to understand cognitive engagement of consumers with online organic food purchase.
"It is d ifficult to belief the organic produce and their claim. I will prefer to associate and feel more trustworthy with an organic brand, which better connects me with the farmers. An online platform where the source of fruits and vegetables can be tracked which will make their produce more trustworthy. I want to get more informat ion about the nutritional value of fruits and vegetables and also local food recipe. Most of the time we don't know how to cook it."

Open Coding
Here the respondent mentioned about those characteristics of online organic food purchase which might cause better consumer engagement and consumers' perceived experience value. Open coding on the data was conducted in this study to identify mult iple underlying concepts, which are also known as labeled phenomena or primary label (Gou lding, 2002). The primary labeling was done on the basis of researcher's understanding in relation to its significance in the data.  The researcher coded "More trustworthy with better connectivity with the farmers" because the respondents felt that this can make them mo re engaged with the organic brand and can create better experience by giving a sense of connectedness with the farmers and easy to belief the product. Similarly, "More trustworthy if source and vegetables and fruits" can be tracked was coded because the respondents felt that this cerate more cognitive engagement with the organic brand and can create better experience by more transparent process . The next two codes or labels are "More information about nutritional value of fruits and vegetables" and "More information about local recipe" because the respondents' feeling is that this can result to better cognitive engagement with the online organic brand.

Affinity Diagramming
Affin ity diagram was deviced by a Japanese anthroplpgist Kawakita Jiro in the year 1960. This is also known as affin ity chart or K-J Method (Foster, 2010). It is a tool to generate groups of data based on their natural relationship through brainstorming (Foster, 2010). A ffinity diagramming is a participatory method where concepts written on cards or sticky notes are sorted into related groups and sub-groups (Courage & Baxter, 2005). An affinity diagramming was done to determine how the users mentally organize the items into categories. So me broad categories have been identified fro m the literature and expert opinion and the new items which were generated fro m depth interview of the indiv iduals followed by open coding or primary labeling were written on sticky notes which are sorted into categories as a workshop activity. 6 masters students from different disciplines in an institute were selected who were well informed and regular consumer of organic food and frequently purchase through an online platform.
The steps for affinity diagram which was conducted in this study were as follows i). Record each of the items fro m the list of open coding on the sticky note. ii). The broad category was plotted on a large sheet. iii). All the team members were allotted 15 minutes to populate the sheet on related categories. Each member in the team was given a set of sticky notes which consists of all the items. iv). Then everyone in the team were individually allowed to move the sticky notes silently without discussion. v). The maximu m nu mber of votes for each o f the items in a particular category were selected. vi). Then draw the final affinity diagram.
The intension of this affinity diag ramming was to diagnose the items which can exp lain the concepts by organizing the qualitative data generated through open coding.

Axial Coding
Axial Coding is the next phase after Open Coding as per grounded theory. Evolving hypotheses, and different relationship statements are created at conceptual abstract level and not directly fro m the raw data. These statements and hypotheses are then tested through other methods (Corb in, 1998). This process requires more conceptual clarity and abstraction at theoretical level. It also requires a sophisticated coding technique, commonly termed as 'axial coding' as per Grounded Theory (Glaser and Strauss, 1967).
The abstract concepts encompass multiple tangible instances revealed from the data (Goulding, 2002). Various stages of data gathering, interpretation and analysis emp loys complex and sophisticated methods for theoretical coding. According to grounded theory analysis need to be raised at a more abstract level. Therefore, the concept is away fro m description and leads more towards theory development (Goulding, 2002). Here in this study one such concept is consumers' Cognitive Engagement (CE) wh ich the researcher derived to be one of the driving factor for Consumers' Perceived Experiential Value (CPEV), Similarly Emot ional Engagement (EE), Behavioral Engagement (BE), Telepresence (Tele), Willingness to co-create (WTC), Willingness to Pay for Experience (WPE), Ease of Use (EOU) are other driv ing factors of CPEV.
Here in this study the respondents or the participants in affinity diagramming wo rkshop and the researcher felt that more trustworthy with better connectivity with the farmers, more t rustworthy if source and vegetables and fruits can be tracked, more in formation about nutritional value of fru its and vegetables, more information about local recipe are related to consumers' cognitive engagement and which in turn can lead to Consumers' Perceived Experiential Value. Similarly, all the categories and sub categories (Table 1) were analyzed through axial coding.

Emotional Engagement (6)
 I wish to get fresh organic vegetable/fruit through online store.  I wish to be connected with the marginalized organic farmers and understand their production challenges.  I wish to get more geographical information related to crop planning.  I would love to get customized fresh local food from our indigenous small-scale food producers, which is difficult to make at home.  I feel, the need for local grown food produce seems to be fading out from customers' mind.  I wish for a better experience and engagement with local grown food and food produce.

Be havioral Engagement (4)
 I will better avoid online organic purchase, as I tend to buy more than my requirement.  I am okay with late delivery if am sure about the quality of vegetable/fruit.  I will be patient enough with irregular delivery of organic producers if I am convinced with their supply chain challenges.  I will be convinced with their late or irregular delivery if I can track their service touch points and have a personalized connection with the producers.

Te le pre sence (3)
 I get deeply engaged with well-designed online store and tend to buy more.  I forget about my real need and spend lot of time on this attractive virtual store.  I feel my mind becomes fully engaged if the online store is well designed and attractive.

Ease of Use (4)
 I can only buy through those online stores, which is simple and easy to navigate.  I can buy through those online stores where every steps are clear and understandable.  It makes online shopping more easy if it provides necessary food information like nutritional value, place where it is grown etc.  I get more confused if too much information is provided.

Willingne ss to pay for e xpe rie nce (5)
 I will buy organic food even it is expensive.  I will engage and pay more for organic food if I get a clear understanding about their source.  I am ready to pay more if I feel I am more connected with the field and the farmers.  I will buy organic food over conventional food if there is a reliable online service.  I am ready to pay more on organic food if there is a continuous supply through an online platform.

Willingness to cocreate (5)
 Ready to engage more if I feel that I am more connected with the field and the farmers through this online platform and can chat with them.  Love to purchase through a platform where I can place my demand and help the farmers for effective crop planning.  Like to form local customer group and help the organic food producers to resolve their supply chain challenges.  Will be happy to own a kitchen garden in my apartment and grow some easy to maintain organic vegetables/fruits.  Like to be a part of a community space where I can share my feedback and ideas on regular basis and help the organic farmers.

Selective Coding
The categories and sub-categories were analy zed based on axial coding reflects that all the categories are linked to CPEV. The study from mu ltip le depth interviews conducted among the consumers and the experts revealed that CPEV has some relation with cons umers' cognitive, behavioral and emotional engagement, telepresence, willingness to co-create, ease of use and willingness to pay for experience. The categories and sub categories, which evolved through qualitative research, were partially listed in Table 1.

Quantitative Research Method
The items generated from qualitative research were used for questionnaire design and survey. An online survey was conducted across India. The questionnaire consists of 33 items and the respondents had to mark them in a 5-point scale with 1 as lowest level of agreement and 5 as highest level of agreement.

Exploratory Factor Analysis (EFA)
The initial phase of survey was conducted among 132 respondents. Out of which 129 responses were comp lete and used for analysis. EFA was conducted for dimension reduction and final item identificat ion under each factor prior to Confirmatory Factor Analysis. The items wh ich loaded equal to or mo re than 0.6 were used for further analysis. A new set of questionnaire was developed with 31 items and two items were dropped due to low factor loading. Total 618 data points were collected for second phase of data collection. Out of which 584 were comp lete and can be used for Confirmatory Factor Analysis.

Confirmatory Factor Analysis (CFA)
Structural Equations Modeling (SEM) was used to perform Confirmatory Factor Analysis. The tests were conducted for validity and reliability of the items generated for each constructs to measure CPEV (Hair et al., 2006). The fit indices for the measurement model related to Consumers' Perceived Experience Value are satisfactory (Table 2). Therefore, it can be inferred that the data fits the Model.
The advantage of CFA/SEM is its ability to assess the construct validity of a proposed measurement theory (Hair et al., 2006

Factor Loadings
The standardized loading estimates as per the literature should be around 0.5 or higher and ideally 0.7 or h igher (Hair et al., 2006). A ll the items have Standardized Loading Estimate above 0.5. And some of them are above 0.8 and 0.9 as shown in the Table 3   The AVE of all the constructs are given in Table 4 are higher than 0.5 except EE wh ich is close to 0.5. This suggests adequate convergence (Hair et. al 2006).

Construct Reliability (CR)
CR is also an indicator of CV. An estimate o f 0.7 or higher is suggestive of good reliab ility. If the construct reliability is high, then it signifies that there is an internal consistency existing with in the constructs. Therefore, this signifies that all the measures were consistent and representing the similar h idden construct (Hair et al., 2006). In Table 4 we see that the Construct Reliability of the factors are equal or above 0.7. Th is validates internal consistency and adequate convergence. The extent to wh ich the distinction between the construct exists is identified through Discriminant Validity indicator. For Discriminant valid ity, the square root of the Average Variance Ext racted of each construct should be significantly greater than the correlation of the specific construct with any of the other constructs (Fornell and Larcker,1981). Also, the value for Average Variance Extracted related to each construct should be at least 0.5 (Fornell and Larcker, 1981). As square root AVEs satisfy the above condition shown in Table 5, the constructs possess DV. The only exception here is Emotional Engagement (EE) where the value of A VE is 0.46 wh ich is close to 0.5 and can be even rounded up to 0.5. And also the value of CR fo r that construct is 0.766 which is again above 0.7. Therefore, Emotional Engagement has been considered as a valid construct in this study.

Conclusions
The determinants or constructs that can drive Consumers' Perceived Experience Value were identified through Grounded Theory. The study also generated a set of items related to each of those constructs. For examp le, the items like "More t rustworthy with better connectivity with the farmers", More trustworthy if the source of vegetables and fruits can be tracked, "Information about nutritional value of fru its and vegetables", "More information about local recipe" were mapped under a construct called Cognitive Engagement. Similarly, six items were mapped under Emot ional Engagement, four items under Behavioral Engagement, three items under Telep resence, five items under Willingness to co-create, five items under Willingness to Pay for Experience and Four items under Ease of Use. A ll the items were explored in relation to online organic food purchase.
The ite ms were generated through well-structured qualitative research methods like grounded theory and affinity diagramming. The items were validated through quantitative research like confirmatory factor analysis through structural equation modeling. The items can be used by the digital marketing team to measure the efficiency of an experience design for an online organic food store. The items will also facilitate them to measure consumers' engagement with the online platform through multiple dimensions.

Contribution of the Study
The study contributes a scale which can measure the constructs like Cognitive Engagement, Emotional Engagement, Behavioral Engagement, Telepresence, Willingness to co-create, Willingness to pay for Experience and Ease of Use in relation to online o rganic food purchase which was not available in the existing literature. A working definit ion for "Consumer Perceived Experience Value" in relat ion to online organic food purchase can be evolved around the determinants mentioned above. This will be beneficial for the organic food producers to develop a digital marketing strategy to penetrate the market. This study will also help the service and experience designers to explore this opportunity and create a platform for the small-scale farmers and contribute in their livelihood development.