Shopping behaviour in B2C Retail Online Shopping: A study on the mediation effect of E-commerce Trust and Intimacy perception in Webrooming, Showrooming and Avoidance

Master’s Degree Program in Data-Driven Marketing Shopping behaviour in B2C Retail Online Shopping: A study on the mediation effect of E-commerce Trust and Intimacy perception in Webrooming, Showrooming and Avoidance Amanda López Barreto Dissertation presented as partial requirement for obtaining the Master Degree Program in Data-Driven Marketing NOVA Information Management School Universidade Nova de Lisboa NOVA Information Management School Universidade Nova de Lisboa SHOPPING BEHAVIOUR IN B2C RETAIL ONLINE SHOPPING A study on the mediation effect of E-commerce Trust and Intimacy perception in Webrooming, Showrooming and Avoidance By Amanda López Barreto Master Thesis presented as partial requirement for obtaining the Master’s degree in Data-Driven Marketing, with a specialisation in Digital Marketing and Analytics Supervisor: Professor Diego Costa Pinto July 2023 STATEMENT OF INTEGRITY I hereby declare having conducted this academic work with integrity. I confirm that I have not used plagiarism or any form of undue use of information or falsification of results along the process leading to its elaboration. I further declare that I have fully acknowledged the Rules of Conduct and Code of Honor from the NOVA Information Management School. Amanda López Barreto [Barcelona, 15th of July] Ⅰ DEDICATION TO MY MUM,MY FUNDAMENTAL PILLAR For being my best example, for the sacrifices she made, so I can be writing this thesis, and for the time we could not spend together because of my “I have an idea”. An idea she supported without knowing the what, how, or how much and has led me to this accomplishment. I’m lucky to have the best motivational, supporting and “Yes” person I know as my mum. TO MY BOYFRIEND,MY GREATEST COINCIDENCE For being there in the good moments and in the not so good ones. From believing in me and not letting me abandon, to spending time reading this thesis up and down. But more than anything, for being a big part of my motivation to get a master’s degree, showing me new versions of myself and growing together with me in this process. If we had not met, I would not have written this. Without you, I would have gone crazy in this process, with you, I could be my crazy self during it. Ⅱ ACKNOWLEDGEMENTS TO MY TUTOR, Prof. Diego Costa Pinto, for his feedback and valuable advice and time. I enjoyed our joint work and his experience and dedication in guiding me. TO MY WORK TEAM AT APPINIO, For letting me have the space, time, and comprehension I needed to make my thesis while working full time, and supporting me with their online panel. Ⅲ ABSTRACT This study aims to analyze the mediation effects of Trust and Intimacy in B2C Online Shopping sites, also referred to as E-commerce. Also, deepen on the effect of these concepts in the selection of a purchase channel, phenomenons known as Webrooming or Showrooming; or as opposite, Avoidance. To analyze these concepts, this dissertation is based on different theories, an extensive Literature Review, and the statistical analysis of 500 online surveys made to Online Shopping usual buyers in Spain. Based on this, an empirical test is made, using PLS-SEM and a disjoint two-stage approach, to determine a correlation between the SOR-based Conceptual Framework concepts and the Hypotheses. It concludes by confirming that Trust, and also Intimacy, positively affect Online B2C E-commerce perception, and have a direct mediation effect on Webrooming, Showrooming, and Avoidance. These and other results imply new contributions – among others – to retailers, specially those that implement omnichannel strategies. KEYWORDS Online Trust; Online Intimacy;Retail Online Shopping; B2C E-commerce; Showrooming, Webrooming; Avoidance Sustainable Development Goals (SGD): Ⅳ INDEX 1. Introduction.............................................................................................................. 1 2. Literature review....................................................................................................... 4 2.2 Importance of relationships and emotions in purchasing decisions........................4 2.2 The concepts of trust and intimacy..........................................................................4 2.2.1 Trust in Online Shopping................................................................................. 5 2.2.1.1 Trust and Reliability................................................................................6 2.2.1.2 Trust and Credibility............................................................................... 7 2.2.1.3 Trust and Security...................................................................................8 2.2.2 Intimacy in Online Shopping........................................................................... 9 2.2.2.1 Intimacy and Care.................................................................................10 2.2.2.2 Intimacy and Empathy.......................................................................11 2.2.2.3 Intimacy and Communication.............................................................. 12 2.2.2.4 Intimacy and Personal Experience....................................................... 12 2.3 Online Retail Shopping - Functionality vs Emotionality..........................................13 2.4 Shopping behaviours: Webrooming, Showrooming and avoidance...................... 15 2.4.1 Webrooming............................................................................................16 2.4.2 Showrooming.......................................................................................... 17 2.4.3 Avoidance................................................................................................17 3. Conceptual model and hypotheses.......................................................................... 19 3.1 Hypotheses.................................................................................................19 4. Methodology...........................................................................................................21 4.1 Data Collection and Sampling.................................................................... 21 4.2 Measures....................................................................................................22 4.3 Data analysis...............................................................................................23 5. Results and discussion............................................................................................. 25 5.1 Demographic Analysis................................................................................ 25 5.2 Measurement Model of Reflective Constructs – Reliability and Validity... 28 5.3 Measurement Model of Higher-Order Formative Constructs.................... 31 5.4 Structural Model – Hypotheses Testing.....................................................33 5.5 Mediation Analysis.....................................................................................37 6. Conclusions and future lines of research..................................................................40 6.1 Theoretical Implications............................................................................. 42 6.2 Managerial Implications.............................................................................43 6.3 Limitations and further lines of research................................................... 45 Bibliographical References...........................................................................................47 1. Appendix A.....................................................................................................................63 Appendix B.........................................................................................................................72 Ⅴ Annexes..............................................................................................................................73 LIST OF FIGURES Figure 1.............................................................................................................................20 Conceptual Model....................................................................................................................20 Figure 2.............................................................................................................................28 Measurement Model for Reflective Constructs (Step-1)......................................................... 28 Figure 3.................................................................................................................................... 32 Step Two of Disjoint-Two Stage Approach............................................................................... 32 Figure 4.............................................................................................................................36 Mediation Analysis...................................................................................................................36 LIST OF TABLES Table 0........................................................................................................................................... 24 Scale and Measurements.......................................................................................................................24 Table 1........................................................................................................................................... 25 Demographic Analysis............................................................................................................................25 Table 2........................................................................................................................................... 29 Reliability and Validity Measures of Lower-Order Reflective Constructs...............................................29 Table 3........................................................................................................................................... 30 Discriminant Validity of Zero-Order Reflective constructs (HTMT criterion)......................................... 30 Table 4........................................................................................................................................... 32 VIF Values and Significance of outer weights of higher-order formative construct (Trust & Intimacy factors)...................................................................................................................................................32 Table 5........................................................................................................................................... 33 Hypothesis Testing.................................................................................................................................33 Table 6........................................................................................................................................... 34 Structural model assessment.................................................................................................................34 Table 7........................................................................................................................................... 37 Mediation Analysis................................................................................................................................ 37 Table 8........................................................................................................................................... 69 Scales and measurements for Further Lines of Research...................................................................... 69 Ⅵ LIST OF ABBREVIATIONS AND ACRONYMS BBB Better Business Bureau.It is a private non-profit organization founded in 1912. BBB's self-described mission is to focus on advancing marketplace Trust SOR Stimulus-Organism-Response B2B Business to Business B2C Business To Consumer OPRs Online Product Recommendations CRs Customer Reviews Ⅶ As other studies have shown, the personality of each individual also affects the concept of Trust regarding brands. The study from Gefen (2000), surveying 217 individuals about their experience shopping in an e-commerce book store, showed that while familiarity indeed builds Trust, “it is primarily people's disposition to Trust that affects their conviction in the vendor”. Therefore, the Trusting Disposition of every individual will also be taken into account. 2.2.1.2 Trust and Credibility Another concept, highly related to Trust by the scholars Keller (2001) and Ohanian (1990), is Credibility. Keller defines Trust as “a judgement made by a perceiver regarding the Credibility of the caller”, which results in positive communication features that affect the recipient. The author also states that the Credibility of a brand extends to assessments of the business that created it. So, in order to measure credibility and therefore Trust, the empiricist states three dimensions of Brand Credibility: Expertise,Trustworthiness and Perceived Quality (the first two, also introduced in the research by Ohanian, 1990). Expertise is related to the level of competency, innovation, and market leadership of a brand;Brand Trustworthiness is “the capacity of a brand to be perceived as sensitive to the interest of customers”, and Brand Likeability “is what a brand needs to have in order to be seen as entertaining, fascinating, and worthwhile” (based on the three dimensions of Credibility by Keller, 2001). Notwithstanding, in order to complement the definition of Credibility in the context of Trust for online stores, the concept of Perceived Quality, introduced by both Keller (2009) and Ohanian (1990), as another of the Brand Judgments made by consumers, was chosen. It’s also worth to measure inside the parameters of credibility, and have an extensive review since the customer is not able to have visual and material proof of the quality of the product According to Keller (2009), perceived quality refers to how customers perceive a product's overall quality in relation to competing options on the market. It’s the “consumers’ feeling about a product” (Khan et al., 2019). It has been proved that the quality perception not only affects credibility (and therefore Trust) but also the purchasing decision. Perceived quality has been related to purchase intention (as a short term effect). On the other hand, other authors have related perceived quality with the concepts of Brand Trust and Loyalty (as a long term effect). Nevertheless, there has been a different range of opinions on these regards, since they had different conclusions on the relationship of these terms. Sengguruh , Esti and Rahayu (2020) based the foundations of their research on this significative differences, since authors like Alhadad (2015); Biedenbach and Marell, (2009), confirmed that perceived quality has a significant impact on Brand Loyalty and Trust; While other studies 7 (Listiana, 2015; Marakanon and Panjakajornsak, 2016) found no significant relationship between perceived quality and these Brand Dimensions. The research gap gets even more significant when we talk about research involving both the concepts of perceived quality and the online shopping or e-commerce phenomenon. 2.2.1.3 Trust and Security In order to have a more focused context of the concept of Trust around e-commerce, it is worth mentioning the concept of Security. It analyzes how customers feel about the management of their personal data's security, and has an impact on their level of confidence in online services (Palak & Akshat, 2016; Hoffman et al., 1999; Miyazaki& Fernandez, 2000). E-commerce security is one of the most noticeable security features that influence the end user through their interactions with e-businesses and has its own unique peculiarities. Actually, “major two critical problems for both e-commerce consumers and sites are privacy and security” (Palak & Akshat, 2016), to the point that some customers refused to buy online due to the lack of Trust or fear for their personal information (Niranjanamurthy & Dharmendra, 2013). In order to avoid it, E-sellers must design settings where customers feel secure and at ease while engaging in any kind of data transaction. Trust is an important issue in e-commerce stores since they integrate different payment systems in which the retailer or sales person is not present in person (and instead, is just dealing with an interface), which represent an increased perception of security risk (p.228). To determine the relationship between Trust and Security in online shopping, some elements of the E-commerce Security Framework (Labuschagne, 2000; Kim et al., 2005) will be taken into consideration, such as: Data Integrity, Data Confidentiality and Data Authenticity. Other elements of the E-commerce Security Framework also include: Access Control and Non-repudiation (more technical elements, which will not be considered in this investigation). Data Integrity ensures info has not been tampered with (Niranjanamurthy & Dharmendra, 2013) . From an IT point, it is implemented by message digest or hashing, which is a cryptographic function to protect a piece of data (Niranjanamurthy & Dharmendra, 2013). However, a usual way for consumers to measure the integrity of the e-commerce stores, is the verification of reviews, (also called OPRs - Online Product Recommendations) made by other customers (CRs - Customer Reviews) and its content. With CRs , customers are able to obtain a realistic buying experience and a resource to understand the items by reading online reviews. But not all recommendations count, since research 8 made by Benlian et al. (2012) shows that: “Customer reviews express higher trusting beliefs and perceived affective quality than provider recommendations”. Data Confidentiality is “the ability to prevent unauthorized parties from interpreting, modifying or understanding data” (Labuschagne, 2000). It is one of the main concerns of the e-commerce industry, and it’s considered a critical organisational and technological requirements for any efficient and productive online payment transaction activity (Abdul et al., 2020; Niranjanamurthy & Dharmendra, 2013). With the introduction of online payments, online scams and identity theft emerged as a consumer's fear (Hille et al., 2015). Lastly, on the concepts considered for describing the relation between Security and Trust, authenticity plays a big role. Data Authenticity, is described as ensuring that someone is who he or she claims to be, both in the case of the brand and consumer. It can be implemented for example by the usage of Digital Signatures or Trusted Third Parties, which provide an insignia or Digital Certificate that can be shown on websites as a sign of Authentication (Niranjanamurthy & Dharmendra, 2013). To summarise, there is vast research made regarding the concept of Trust, yet, it's still unclear how crucial Trust is obtained as a holistic concept towards the brand (and not as an asset that from the mere functionality or security of a website), as Egger (2000) confirmed in the context of “Online Shopping and how the perception of Trust are conquered”. Previous research also focused on the Trust built by the interface (and related it to security and privacy) (Alba et al. 1997; Loiacono, et al.,2002, Reynolds; Song & Zahedi 2005; Yun Y, et al., 2005) and User Experience design (Nielsen Norman Group, 2000). However, as Luhman (1979), Geffen (2004), Keller (2001) and Ohanian (1900) show in their research, it also relies on abstract concepts (such as Predictability, Familiarity and Trusting disposition or Expertise, Trustworthiness, Likeability, Perceived Quality and Security concepts). 2.2.2 Intimacy in Online Shopping Intimacy, as noted by Levenson (1974), “is a venerable word with a long history of changing meaning”, also, it means different things to various people, and has huge importance in the Western world (Hook et al., 2003). It has often been attributed to human relationships (Lee, 2022; Fletcher et al., 2019; Hall, 2019). However, in terms of marketing and consumer behaviour, the most common term of study is Brand Intimacy (Fournier, 1998; Natarelli, 2018; Park et al., 2006; Roberts 2004), which can be defined as “the science of how we bond with the brands we use and love” (Natarelli, 2018); along with Customer Intimacy, a proposed business model created by Treacy & Wiersema (2007), consisting in 9 delivering what specific customers want; but seen as what the brands can do for customers in order to build intimacy and loyalty in the long-term. As a consequence, one can say that the research concentrates its efforts in relation to the dimensions of the brand. It’s been proven that brands and branding are one of the factors that influence Intimacy (Park et al., 2006; Roberts 2004, Natarelli, 2018; Fournier, 1998). But it’s also a fact that there is an insufficient body of research in regard to the dimension of the existence of Intimacy in the purchasing channel (as of Offline and Online), not relating it to a specific brand. The growth of the internet – and most recently, innovations on AI and VR technologies – has made it feasible to interact personally with mass markets (Cusumano et al., 2020), making Intimacy a concept no longer attached to face-to-face interaction (Eileen, B and Rhacel, S., 2010). It is extremely important to also consider this purchasing channel dimension, in order to understand customers better and get to know if this Intimacy is something that customers are missing in an online environment. Further data analysis by Jasper (2000), using factor analysis, indicated four major characteristics in the sense of Customer Intimacy. “The four dimensions are Care, Communication, Trust and Comfort” (Jasper, F., 2000). Also mentioned by Hook et al. (2003), the categories of Love and affection (Care), trust, and self-disclosure (meaning communication). 2.2.2.1 Intimacy and Care Intimacy is sometimes defined narrowly to mean the familiarity resulting from close association. (Jamieson, 2007) achieved as a result of an action that repeats. In this close association, it’s critical for creating intimacy, understood as an expression of affection and care (Waring et al., 2003). Therefore, not every action that repeats will create intimacy (Hook et al., 2003). Also, Kunce & Shaver (1994) as cited by Jasper (2000), takes the concept from defining care as noticing and responding to another's needs. Therefore, we refer to the situation created by Online Shops and their customers, when, interacting overtime, they develop a sense of relationship, and create intimacy through showing affection and care. This “Sense of Caring”, was described by Cook (2010) as one of the intangible reasons for initial purchase decisions. Some elements that would increase this “Sense of caring” are: Courtesy, Willingness to help and Ability to Problem-Solve (Cook, 2010). These elements can be perceived, (through different ways or touchpoints), in both offline and online environments. Customer care in the field of marketing encompasses a strategic approach aimed at transforming an organization into a customer-centric entity, thereby setting it apart from competitors. The primary objective of this approach is to enrich the overall customer experience. This strategy can be viewed as a contrasting alternative to the product-centric marketing approach (Cook, 2010). 10 Within offline retail settings, the prevailing perspective regarding customer care often characterizes it as an action performed by the company, rather than a perceptible experience or emotion felt by the customers themselves (Lewis,1988; Sturdy, 1998; Majava & Isoherranen, 2019; Serravalle & Pantano, 2023). It’s frequently associated with the concepts of Support Hotlines, Customization and Personalization, for example, offering customizing corners in-store (Cook, 2010; Serravalle & Pantano, 2023). In online settings, care is understood as “the attention paid to preand post-purchase” (Souitaris, V., & Balabanis, G., 2007, p.247). These concepts possess a substantial operational nature, exhibiting practical relevance and applicability in various contexts, but they do not fully encompass the emotional dimension associated with the profound sense of caring and intimacy. 2.2.2.2 Intimacy and Empathy Empathy is the capacity to feel other people's emotions and make guesses about what they could be feeling or thinking (Berkeley University, 2005). “It can be conceived of as an interaction between any two individuals, with one experiencing and sharing the feeling of the other” (Decety & Lamm, 2006). It is a healing energy, according to therapists, and it is crucial to the development of relationships (Suler, 2016) Empathy, unlike other concepts associated with Intimacy, has not conventionally been regarded as a marketing concept within the realm of academic research. However, scholarly discourse has characterized empathy within the domains of leadership and interpersonal relationships as “a genuine desire to help individuals, demonstrated through practices such as active listening, adept questioning, and maintaining a non-judgmental stance” (Cook, 2010). When applied to the context of Online Shopping and Intimacy, this empathetic approach holds promise for cultivating meaningful connections and enriching customer experiences. As noted by Suler (2016), empathy has been found to be one of the most appreciated human traits in technology. Researchers confirm that “service encounters” are crucial for consumers (Bitner, 1990; Cook, 2010; Shostack, 1985). Defined firstly by Shostack (1985), those are “the periods of time in which customers directly interact with a service”. It is known that empathy is a human feeling, and human feelings are better expressed and understood more deeply in a one-to-one interaction and in in-person (offline) environments (Burgoon et al., 2021; Lieberman & Schroeder 2020). This is due to non-verbal communication, “from exchanging a smile, to touching, to modulating the sound of one’s voice to convey emotions (e.g., humour or sarcasm)”, “making the issuer of the message seem less capable of having emotions” (Lieberman & Schroeder, 2020 p.17). One of the streams of research posits that face-to-face service encounters tend to exhibit higher levels of empathy (Burgon et al., 2021). 11 Conversely, another line of research provides reassurance that senior managers' reaffirmation of their commitment to empathetically engaging consumers can potentially yield benefits even within technology-driven and online environments (Gorry, G., & Westbrook, R., 2011). Empathy plays an important role during these “service encounters” and helps in having a better sense of satisfaction, intimacy, and decision-making. Therefore, it should be considered and studied, to confirm or deny if this subtle and profound human feeling can be recreated or perceived digitally. 2.2.2.3 Intimacy and Communication In a study made by Waring et al. (2003), the investigators discovered communication, understood as the ability to resolve conflict, to be one of the key indicators for intimacy. Also, vast literature suggests (Hatfield, E., & Rapson, R. L., 1993; Hook et al.,2003; Cook, 2010) that Self-disclosure, (or the capacity of communicating to express one’s feelings) is one of the four components to assess intimacy in a relationship. Additionally, the yearly-conducted study of Gallop (2023), shows, year by year, that there is a high correlation between employee engagement and customer engagement. Empathizing, the importance of communication for the creation of intimate feelings in relationships. 2.2.2.4 Intimacy and Personal Experience Shopping experiences offline and online can vary in the different and individual touchpoints (interactions) (Bitner et al., 2008). However, “this siloed focus on individual touchpoints misses the bigger – and more important – picture: the customer’s end-to-end experience” Maechler et al. (2019). Moore and Doherty (2007), go even one step further in providing the term “experience economy”, in which “the process of purchasing a product is as significant as the product”. Therefore, considering the findings of Maechler et al. (2019) “Personal Experience is widely regarded as the accumulation of touchpoints that a consumer had (p.2)”. In this case, with a specific purchase channel (online), and their feelings during those experiences. Campo and Breugelmans (2015) argue that those who have a certain expertise, will have confidence in the seller and the delivery method, thus developing a feeling of Intimacy. Thus, we propose that expertise plays a vital role in developing Intimacy in a purchasing channel. Memories are the cognitive processes through which individuals encode, store, and retrieve information from past experiences (Srull et al., 1985). Previous behavioural studies suggest that memories are playing a big role in our daily life decision-making processes such as purchasing channels (Zeitamova et al., 2012). Empirical studies provide evidence that consumers respond 12 positively when they have a history or a series of positive memories (Brown et al., 2003; Orth and Gal, 2012). Memories can also be associated with a personal shopping experience, for example shopping in a marketplace (Bernard, 2011) differs from shopping in a mall (Li et al., 2021), and therefore, creates different memories. Since, in both types of channels, the customer is the foundation of the business and keeps it in existence, therefore, it is worthwhile to fulfil the existing research gap in terms of intimacy and online customer care. We provide a novel approach for measuring the degree of Intimacy established with a customer in Online Shopping stores. The current section of the literature review examines complex emotions of Intimacy and Trust in the context of online buying, since they are important factors in relationships. Consumers' desire to do online transactions is influenced by their level of Trust, which is essential for efficient commerce. Therefore, customer impressions of E-commerce are influenced by a number of trust-related factors, including Reliability, Credibility, and Security (adapted from Gefen,2004; Gupta & Dubei 2016;; Keller,2001; Luhmann, 1979; Lin 2013; Ohanian, 1990). One of the most important factors in developing relationships with businesses and consumers is Intimacy, since it is a basic human desire (Lee, 2022; Fletcher et al., 2019; Hall, 2019) and it can be defined with factors like Care, Communication, Empathy and Personal Experience (adapted from (Cook, 2010;Hook et al., 2003; Jasper 2000, and Maechler et al. 2019). The notion of the constructs forming Trust and Intimacy, and these emotions in the purchase channel, whether it is Online or Offline, are, nevertheless, not well-established in study, in comparison to the same notions in regard to brand. This research attempts to offer insights into improving consumer experiences in the e-commerce space by examining aspects including care, communication, empathy, and personal experience. To summarize, Trust and Intimacy are deeply related to Online Shopping and are essential for efficient commerce, influencing consumers willingness to engage in online transactions. As e-commerce continues to thrive, recognizing and balancing both functional and emotionality aspects, such as the above referenced. 2.3 ONLINE RETAIL SHOPPING - FUNCTIONALITY VS EMOTIONALITY “With the development of the Internet, e-commerce has changed the people’s how-to buy and customers have become accustomed to using the Internet instead of the store to make purchases. Compared with the traditional business model, online shopping has a wide range of selectivity and 13 “one-stop” shopping; moreover, there aren’t the obstacles of time, space, and circulation”(Yuping, 2016). However, there are other types of obstacles in e-commerce stores, which refer to functionality, and for which vast research can be found. For instance, one of the commonly accepted studies conveys two factors about retail online shopping: The model considers perceived ease of use and perceived usefulness are the major influencing factors on the acceptance behaviour (Pavlou, 2003). On the other side, Usability is one of the topics which is considered to be related within customer satisfaction. But, as said by Roland Hubscher (2004), usability has frequently been promoted as the magic fix for underperforming internet enterprises. Although better usability will generally improve these sites and their potential for success, usability alone will not result in a highly thriving online presence. After all, regardless of how aesthetically pleasing and functional the website may be, no sane individual will spend money at an unreliable online retailer. “E-commerce websites should emphatically consider the hedonic value of customers, whether they can offer interest and joy in online shopping is the most important factor” Yuping, 2016. On the other side, recent research shows that emotions are also a key consideration in the design of e-commerce websites. An e-commerce website should satiate the emotional demands of its visitors, not only its functional ones. (Guo et al., 2015). Emotions are able to drive engagement, (which entails a two-way dialogue between a brand and its customers, since today’s companies have the ability to listen and present more intelligent and individualized marketing messages and encourage users to make a purchase while simultaneously sharing it (Henderson on Digiday, 2012) which is an invaluable asset for any brand. Actually, studies like the one from the global consultancy Gensler (2013), show that “high-emotion” customers are more satisfied, purchase their favourite brands more often (see Annex 2), and are more likely to recommend the brand to their friends. Also, they were two times more likely than “low-emotion” consumers to say that their favourite brand is part of their daily routine. Therefore, the study concludes by affirming that “brands need to recognize the investments, both financial and emotional, that customers are willing to make, and repay the favour” (Gensler, 2013). While the most recent research is beginning to name emotions in e-commerce and purchase intent as a determining factor, no results are found on how precise emotions like Trust and Intimacy affect it. 14 These can be perceived and positively or negatively alter the perception of online retail and affect the final decision for a purchase channel as the final outcome. 2.4 SHOPPING BEHAVIOURS: WEBROOMING, SHOWROOMING AND AVOIDANCE According to Schiffman and Kanuk (2000), consumer behaviour refers to how consumers choose their personal or home items by using the resources they have available, such as money, time, and effort. As said before, this behaviour can be influenced by emotional components and motivations (Barr & Cuthbertson, 1991; Maslow, 1943; Roberts, 2005), even acquiring the status of hedonic5approach to shopping, in opposition to utilitarianism (Rajan, 2020). There are many factors influencing consumer shopping behaviour and channel preference, some of them subjective to each person’s personality, and others, commonly accepted. Such as, Positive emotions influence, (always increase consumers’ purchasing intentions, while negative emotions reduce consumers’ purchasing intentions (Pappas et al., 2016); Past purchase behaviour (Van den Poel & Buckin, 2005), which can cause behavioural biases; Perceived benefits and value for money (subjective to the monetary level, category of the article etc.) (Chang & Wang, 2011) and Social Influence, as conceptualized by Turner (1991), which refers to the impact created by society on individuals, shaping their thoughts, values, and actions and contributing to the formation of their social identity. It encompasses the influence of societal beliefs, norms, and values, which play a significant role in shaping individuals' attitudes and behaviours. We can therefore conclude that was research is found on general shopping behaviours, motivations and biases. Several factors, as previously discussed along the literature review, exert influence on the consumer's choice of browsing channel to make an optimal selection, as well as the channel through which they ultimately decide to make the purchase. Either for pure online retailers or omnichannel ones, knowing about the customer journey is essential (Lemon et al., 2016). As Lemon et al. (2016) agree, solely through a comprehensive understanding of consumers' channel choice behaviour can retailers effectively shape and influence it using appropriate strategic interventions. Lepkowska-White, (2004) studied in an early-stage of e-commerce and omnichannel strategies, the type of customers in regard to the channel choice for different parts of the journey. She identified 5Hedonic shopping refers to the act of engaging in shopping activities primarily for the sake of pleasure, enjoyment, and emotional gratification, rather than solely for the purpose of fulfilling functional or practical needs. 15 three types of customer. This classification pertains to distinct consumer groups based on their shopping behaviours and preferences, and is explained below. Verhoef et al., (2007), after taking these three groups into consideration, grouped all these customers by the name of research-shoppers, studying the phenomenon in a more general way. These shoppers are the ones with a tendency to use one channel for browsing and another for purchasing. 2.4.1 Webrooming Firstly, we have online browsers, who primarily utilise the internet to educate themselves about products and services, but opt to make their final purchases in traditional brick-and-mortar stores (Lepkowska-White, 2004). This leads to Webrooming, a phenomenon in which Online Browsers create within their shopping behaviour. From search Online, to Buying On-Site (Aw, E.C.X., 2019;2020). A substantial body of research indicates that E-commerce will only gain power, even dethroning traditional commerce, in the upcoming years (Einav et al., 2017). On the other hand, an alternative perspective bases on Webrooming as a key factor to indicate the that E-commerce will be just one more touchpoint in a new and more integrated customer journey, based on the fact that, as Webrooming suggest, a lot of people browses but not everyone converts, resulting in low conversion rates. Contradicting, therefore, the “gloom and doom hearsay on how online commerce is dominating, and may one day eliminate the existence of physical stores” (Aw, E.C.-X., et al. 2021). In any case, “a retailer should not be concerned if a consumer decides to browse its website but does not buy online, since the consumer may then decide to buy the product in-store’ (Soopramanien & Robertson, 2007) . Retailers should then integrate it in their omnichannel strategy when possible. The motivations behind this concept, are the previous mentioned on the chapter of Intimacy (such as communication, empathy with the Sales Staff, Sense of Caring and Personal experience (Villani, 2018) – since historically, there used to be a large tradition of Offline Shopping). Also, consumer traits and channel factors play a big role. Such as the motivation to touch the product (of course, not applicable to service type of products) (Flavián et al., 2019), the need for interaction; Or the Perceived convenience, usefulness (Wang et al., 2021), and perceived risk of buying Online (Niranjanamurthy & Dharmendra, 2013), are mentioned in the Webrooming literature. In their research, Arora and Sahney (2018) found that consumers' perceptions of the aforementioned motivations—such as advantages provided by online channels (low search effort and access to online reviews) and purchase advantages found only in online stores (such as motivation to touch, interactions with sales staff, assistance, or other benefits like immediate possession) — have a significant impact on attitude and Webrooming propensity. 16 ●The first big block of questions included questions about Trust, Intimacy and Way of Shopping (Showrooming, Webrooming or Avoidance): the various constructs defined in the literature review (e.g., Reliability, Familiarity, Trusting disposition, Intimacy ; Care, Empathy, Communication, Personal Experience; Webrooming, Showrooming, Avoidance). Questions for the constructs of Trust (Gefen, 2004; Gupta & Dubei, 2016; Keller, 2001; Lin , 2013; Luhmann, 1979; Ohanian,1990), were adapted from (Cook,2010; Jasper, 2000; Maechler et al. 2019; Treacy & Wiersema, 2009). Questions for Purchasing Channel Preference (only considering Webrooming, Showrooming and Avoidance) were adapted from (Aw,2019;2020;2021; Lepkowska-White, 2004; Mutum & Ghazali; 2006). Table 0. defines the questions, measurements, and scales made to define and measure the relationship between the co-constructs that were found to define Trust, Intimacy and Purchasing Channel Preference. 4.3 Data analysis The study adopted a reflective-formative type of hierarchical research model. PLS-SEM 4.0 was used to test the model, because it involved second-order formative constructs. The disjoint two-stage approach was adopted in this study due to the presence of second-order formative constructs and an unequal number of lower-order reflective constructs. Hair, et al. (2019) directed that the conceptual model did not show the second-order constructs. In this approach, firstly the measurement model was estimated without the presence of second-order construct, from which the scores of latent variables were estimated and stored separately in the original data file. In the second step, the estimated scores of lower-order constructs were used as the indicators of the second-order constructs, thus making them lower-order constructs. After that, the reliability and validity were assessed for all the constructs and later the structural model was tested using PLS-SEM for hypotheses testing. The sample size was adequate to evaluate the model using PLS-SEM. Previous studies provide evidence that PLS-SEM is appropriate to assess models using small to medium sample sizes (Ringle et al., 2012). In addition, we comply with the Crochan’s equation for determining the sample size. 23 Table 0 Scale and Measurements 24 5. RESULTS AND DISCUSSION Below, a specific analysis within different statistical methods using PLS-SEM 4.0 was made. Results can also be found in the following online dashboard link for a data visualization: https://admin.appinio.com/#/analyzer/648734370dd3204984115a0a 5.1 Demographic Analysis Frequency distribution was used to describe the frequency and percentage of the respondents falling under each category, hence explaining the demographic distribution of the sampling population (Table 2). Results indicated that almost half of the respondents were female (50.5%), and half were male (49.50%). Furthermore, around two-third of the respondents were employed (employed or self-employed) (64.13%), while a few were not employed (15.43%). More than half of the respondents had at least one child (< 18 years old) in the household (54.91%). Nearly forty-four percent of the respondents were in a solid partnership (43.89%), while the remaining were either married/ in registered partnership (29.06%) or available/ single (27.05%). Also, two-third of the respondents were equally distributed in the household size categories of three persons (33.67%) or four persons (31.06%). Most of the respondents fell into the second income category (23.85%), followed by the third income category (18.04%) and first income category (17.03%). Most of the respondents had been educated till lower secondary school (24.85%), followed by primary education (23.25%) and higher secondary school (14.43%). All respondents had lived in an urban area (100%) and had shopped on the Internet (100%). Lastly, the respondents either shopped on the internet on a monthly basis (49.50%) or weekly basis (44.89%), while some respondents were also found to have shopped on the internet on a daily basis (5.61%). 25 Table 1 Demographic Analysis Variables Category Frequency Percentage Gender Male 247 49.50% Female 252 50.50% Working Status Employed (Employed/ Self-Employed) 320 64.13% Not employed/ Not working 77 15.43% Pupil/ student/ in-training 52 10.42% In Interest 26 5.21% Others 24 4.81% Children in household (<18) At least one child (<18) in the household 274 54.91% No children (<18) in the household 225 45.09% Marital Status Available/ Single 135 27.05% Married/ In Registered Partnership 145 29.06% In a solid partnership 219 43.89% Household Size 1 Person 26 5.21% 2 Persons 107 21.44% 3 Persons 168 33.67% 4 Persons 155 31.06% More than 4 Persons 43 8.62% Income category Income category 1 (Lowest) 85 17.03% Income category 2 119 23.85% Income category 3 90 18.04% Income category 4 71 14.23% Income category 5 57 11.42% Income category 6 30 6.01% Income category 7 18 3.61% Income category 8 (Highest) 29 5.81% Education Level Less than Primary Education 9 1.80% Primary Education 116 23.25% Lower Secondary School 124 24.85% 26 Higher Secondary School 72 14.43% Post-Secondary Tertiary Education 28 5.61% Short Tertiary Education 30 6.01% Bachelor or Similar Degree 47 9.42% Masters or Similar Degree 68 13.63% Ph.D. or Similar Degree 5 1.00% Urban (> 100k Einw.) No 499 100% Yes 0 0% Shop on Internet No 0 0% Yes 499 100% Frequency of Shop on Internet Every Day 58 5.61% Weekly 224 44.89% Monthly 247 49.50% 27 5.2 Measurement Model of Reflective Constructs – Reliability and Validity Figure 2 Measurement Model for Reflective Constructs (Step-1) In the first stage of the disjoint two-stage approach, the reliability and validity of the lower-order constructs were tested. Firstly, Cronbach’s alpha and composite reliability (CR) was tested to test reliability (Table 2). Both Cronbach’s alpha and composite reliability should be higher than the threshold level of 0.70 (Hair, et al., 2017). All variables had a Cronbach’s alpha and composite reliability higher than 0.70, indicating that all variables were reliable. 28 Secondly, convergent validity was tested using the factor loadings and average variances extracted (AVE) (Hair, et al., 2014) (Table 2). To achieve acceptable convergent validity, the factor loadings of all items should be higher than the threshold level of 0.70 (Landau & Everitt, 2017). Two items i.e., one question from empathy ‘I would like to feel support from sales assistants while I buy online’ and one question from security ‘When buying online, I'm afraid of being robbed giving my credit card information’ had a factor loadings of 0.060 and 0.049 respectively. Thus, these items having low factor loadings were deleted from the model. All remaining items had achieved acceptable factor loadings of 0.70, thus considered as acceptable convergent validity. Also, the average variance extracted for all constructs was higher than the threshold level of 0.50 as suggested, thus achieving acceptable convergent validity. Thirdly, the discriminant validity was tested using the Heterotrait-Monotrait ratio (HTMT) matrix (Table 3). All values of Heterotrait-Monotrait ratio (HTMT) were less than the threshold values of 0.85 as suggested by Hair et al. (2017). Hence, the discriminant validity has been achieved. Hence, the PLS-SEM analysis proceeded. 29 Table 2 Reliability and Validity Measures of Lower-Order Reflective Constructs Constructs Items Factor Loadings Cronbach’s alpha Composit e reliability Average variance extracted (AVE) Reliability R1 0.861 0.839 0.902 0.755 R2 0.857 R3 0.889 Credibility C1 0.771 0.747 0.840 0.568 C2 0.793 C3 0.737 C4 0.711 Security S1 0.882 0.701 0.870 0.770 S3 0.872 Care CA1 0.946 0.878 0.942 0.891 CA2 0.942 Communication CO1 0.911 0.818 0.916 0.846 CO2 0.928 Empathy E2 1.000 1.000 1.000 1.000 Personal Experience PE1 0.958 0.754 0.879 0.785 PE2 0.808 Online B2C Perception OP1 0.885 0.721 0.878 0.782 OP2 0.883 Showrooming S1 1.000 1.000 1.000 1.000 Webrooming W1 1.000 1.000 1.000 1.000 Avoidance A1 0.792 0.704 0.862 0.758 A2 0.943 30 Table 3 Discriminant Validity of Zero-Order Reflective constructs (HTMT criterion) 1 2 3 4 5 6 7 8 9 10 1 Avoidance 2 Care 0.41 1 3 Communicatio n 0.12 6 0.47 5 4 Credibility 0.27 2 0.67 7 0.66 8 5 Empathy 0.27 6 0.70 3 0.59 2 0.64 1 6 Online B2C Perception 0.40 8 0.79 0.78 3 0.81 6 0.73 3 7 Personal Experience 0.66 7 0.44 4 0.08 3 0.22 1 0.25 4 0.31 8 8 Reliability 0.11 5 0.47 0.74 4 0.68 3 0.52 3 0.69 6 0.09 9 Security 0.15 4 0.38 7 0.57 3 0.61 4 0.45 2 0.55 4 0.16 9 0.56 7 10 Showrooming 0.57 2 0.35 9 0.04 1 0.23 1 0.21 5 0.33 3 0.56 1 0.09 1 0.14 7 -1 1 Webrooming 0.48 7 0.14 1 0.14 4 0.09 5 0.04 7 0.09 3 0.56 3 0.11 0.07 6 0.51 2 5.3 Measurement Model of Higher-Order Formative Constructs In the disjoint Two-stage approach, it is recommended that after checking for reliability and validity, the second-order constructs are calculated using the latent variables’ scores of lower-order reflective constructs as computed by SMART-PLS (Becker, et al., 2012). These latent variables’ scores will then be treated as lower-order constructs of higher-order formative constructs (Becker, et al., 2012). These lower-order constructs were further assessed for multicollinearity and significance of outer weights in higher-order formative constructs. 31 Table 4 VIF Values and Significance of outer weights of higher-order formative construct (Trust & Intimacy factors) VIF Original Sample (O) T statistics (\O/STDEV|) p-value Trust Reliability 1.538 0.410*** 14.658*** 0.000 Credibility 1.568 0.500*** 16.320*** 0.000 Security 1.343 0.315*** 10.087*** 0.000 Intimacy Care 1.964 0.409*** 22.517*** 0.000 Communication 1.433 0.219*** 6.825*** 0.000 Empathy 2.092 0.347*** 20.668*** 0.000 Personal Experience 1.171 0.376*** 10.628*** 0.000 * p < 0.05, ** p < 0.01, *** p < 0.001 Variance Inflation Factor (VIF) was used to assess the multi-collinearity among lower-order constructs of higher-order formative constructs. All VIF values ranged between 1.171 and 2.092, which was less than the threshold value of 5 as suggested by Hair, et al. (2017). Thus, there was no issue of multicollinearity in the model. Furthermore, the outer weights were computed by conducting PLS-SEM with 5,000 bootstrapping subsamples. Results indicated that all outer weights were significant at 5% (p< 0.05), proposing that each lower-order construct significantly measure their reflective higher-order constructs including Trust and Intimacy and hence can be used as lower-order constructs for higher-order formative constructs in the structural model. 32 Table 7 Mediation Analysis Original samples (O) T statistics (|O/STDEV|) p-value Direct Effect Trust →Showrooming −0.137* 2.392* 0.017 Trust →Webrooming −0.238*** 3.964*** 0.000 Trust →Avoidance −0.165*** 2.873*** 0.004 Intimacy →Showrooming 0.491*** 8.193*** 0.000 Intimacy →Webrooming 0.374*** 5.481*** 0.000 Intimacy →Avoidance 0.498*** 8.154*** 0.000 Specific Indirect effect Trust →Online B2C Perception →Showrooming 0.029 1.234 0.217 Trust →Online B2C Perception →Webrooming −0.033 1.420 0.156 Trust →Online B2C Perception →Avoidance 0.048* 2.056* 0.039 Intimacy →Online B2C Perception →Showrooming 0.042 1.246 0.213 Intimacy →Online B2C Perception →Webrooming −0.048 1.246 0.213 Intimacy →Online B2C Perception →Avoidance 0.070* 2.216* 0.027 * p < 0.05, ** p < 0.01, *** p < 0.001 39 6.CONCLUSIONS AND FUTURE LINES OF RESEARCH The present research extends the literature on the topics of Trust and Intimacy related to Online Shopping B2C, and its mediation effect on the phenomenons of Webrooming and Showrooming. Researchers in Trust (Geffen,2004; Gupta & Dubei, 2016; Keller, 2001;Lin, 2013; Luhman,1979 ad Ohanian, 1900) and Intimacy (Cook, 2010;Hook et al., 2003; Jasper 2000, and Maechler et al. 2019) suggests that these complex human emotions, are formed within a range of sub-constructs or sub-emotions. The first finding of the study, essential for the further development of it, was to confirm that the variables established as lower-order constructs, measure their respective higher-order construct (using the Disjoint Two-Stage Approach). Therefore, it confirms, as the Literature Review suggested, that Reliability, Security, and Credibility mediate Trust; and Care, Communication, Empathy and Personal Experience, mediate Intimacy. This resulted in the analysis of the Higher Constructs of Trust and Intimacy as a whole, in a model with high predictive accuracy. Past research on Trust, related to Online Shopping, focused on User Experience on the website, taking into account issues related to security (Hoffman et al., 1999; Miyazaki & Fernandez, 2000; Palak & Akshat, 2016) and functional or design web features. (Guo et al., 2015; Pavlou, 2003) This line of research demonstrates and gives evidence of the importance of these features for a better Customer experience. However, with the increasing growth of E-commerce (Cramer-Flood, 2022;Global Ecommerce Sales Growth Report for 2021-2026, 2022; U.S. Census Bureau, 2023), factors not related to the design or safety, demonstrate to be key for customers and need to be analyzed. This present research contributes to the confirmation of Trust and Intimacy as key factors, each one affecting positively the Online B2C Retail Perception (confirming H1, H1a and H1b). Also, it extends the literature on Trust and Intimacy related to Online Shopping and the dimension of Channel Preference (with Webrooming, Showrooming and Avoidance as a result) , confirming the direct effect of both Trust and Intimacy on channel preference (H3b confirmed, and direct mediation effect confirmed for Trust and Webrooming on all three dimensions of channel preference). In doing so, this paper contributes to extending the literature on Trust, which, although extensive, has not been previously related to the topics of Showrooming and Webrooming - and allows light on new possibilities on Intimacy related to the rest of the topics. Moreover, the hypothesis of Trust having a direct effect on Avoidance was confirmed (H3a). This perception is confirmed to be also partially mediated when introducing the Online B2C perception, and the same with the relationship between Intimacy, Online B2C Perception and Avoidance 40 (remarking as well that both can also be found to have a direct effect without the middle Organism). It also confirms that Online B2C perception by itself has a positive impact on avoidance (H2c) – When the perception of Trust and Intimacy in Online B2C is negative or low, it will directly affect by increasing digital channel-avoidant behaviours (this brings new insights into the Avoidant description of Lepkowska-White, 2004). Therefore, we can conclude that the only relation in which Online B2C Perception shows to have a mediating effect (on both Trust and Intimacy), is avoidance. By doing so, we extend previous research on Avoidance motivations (Mutum, 2006; Niranjanamurthy & Dharmendra, 2013) and perceived risks (Hoffman et al., 1999; Miyazaki & Fernandez, 2000; Palak & Akshat, 2016) by confirming the Lack of Trust as a motivation factor for avoidance, and adding the Lack of Intimacy as a mediator. This research further demonstrates the strong effect of Intimacy in Online Shopping Perception and its mediation effect on Webrooming and Showrooming, and puts it in the spotlight as a crucial element. It suggests that Intimacy has greater impact on Online B2C Perception and a stronger effect size on Webrooming and Showrooming (as seen in change in dependent variable due to each independent variable (O) in the Mediation Analysis – Table 7) compared to the concept of Trust. Therefore, we can say that this study contributes to the extension of the topic of “Intimacy” (Cook, 2010; Hook et al., 2003; Jasper, 2000) (which does not have a literature as extensive as trust) by confirming it as one of the main topics to study in relationship marketing and customer care by evidencing the importance of Intimacy for Customers. It also collaborates in the extension of the findings (Gorry, G., & Westbrook, R., 2011), on the importance of empathy practices in Online environments – finding a direct relation, not only to these environments, but to Webrooming and Showrooming. In general, this dissertation started from such abstract topics as the aforementioned lower-order constructs and relates them to the Online Shopping environment, and such actual and concrete phenomena as Webrooming and Showrooming. Consequently, this thesis is providing an analytical layer that can help various stakeholders involved, such as researchers, students, and retailers. In addition, as we have wanted from the beginning, starting from a social point of view and motivation, understanding this data from society and what it demands, can serve – beyond making consumers spend more money – to increasing the comfortable and human feelings during the shopping experience and make the user connect. 41 6.1 Theoretical Implications This research serves to contribute, augment, and advance the existing body of knowledge pertaining to consumer behaviour in the context of online shopping. By confirming direct relationships between specific emotions and resultant behaviours, it expands the theoretical understanding in this domain and fills a research gap on specific constructs. As mentioned in the introduction, there’s an exponential growth in the study of Online shopping behaviours of consumers, being one of the most significant research agendas (Chen, 2009). This study contributes to the knowledge of it, adds value on the Topics of Trust and Intimacy in Online Shopping, proving its direct effect and confirms the increasing tendency of Webrooming (78% of the participants declare to commit this practice) and Showrooming (half of the respondents, 52%, declared to commit it). The method used in this study, can be recommended to other researchers who want to analyze the relationship between specific emotions (Stimuli) affecting Online Shopping into a specific response (Response) in order to give an accurate answer on the upcoming challenges on consumer behaviour due to the use of technology. Firstly, it can serve as a base for those who want to study Trust and Intimacy, since the constructs used in this research to define them, were confirmed as reliable and accurate lower-order constructs (multi-collinearity was checked with a 5,000 bootstrapping). Also, since the reliability, validity and model fit demonstrated, these constraints can be applied to other type of studies, in different fields rather than consumer behaviour. It enables researchers to base their work in the constructs of Reliability, Credibility, and Security in order to study Trust as a whole, and the same with the concepts of Care, Empathy, Communication, and Personal Experience to deepen on Intimacy. This allows researchers to have strong evidence in their research adding value to other knowledge fields. For the best of our knowledge – after an exhaustive investigation work on different Journals, databases, University work repositories and Professional or Corporative Websites and reports – this dissertation presents a twofold approach on Online Shopping literature. Firstly, although it implicates many concepts in which research existed before, it brings a new layer of information studying their correlations. For the best of our knowledge, this is the first study that crosses Trust and Intimacy with Online commerce B2C Perception and the perception of Webrooming and Showrooming as a response using the SOR framework. 42 Secondly, it contributes to a new line of research based on the emotions that a channel relationship creates, rather than a brand relationship. Therefore, it differentiates from the existent Literature review focused on the brand dimension (Brand Trust and Brand Love (as in Keller, 2001; Nilowardono et al., 2020 and Roberts, 2005); Brand Intimacy (as in Fournier, 1998; Natarelli, 2018; Park et al., 2006; Roberts 2004)), and functional dimension (design and security in E-commerce as in Hoffman et al., 1999; Miyazaki & Fernandez, 2000; Palak & Akshat, 2016) and presents channel-based results. We demonstrated that both elements play a role in Online Shopping perception, and directly affect the way in which consumers decide to buy and make the final purchase decision. Furthermore, it expands the literature on Trust (confirming its direct mediation in Showrooming, Webrooming but above all, on Avoidance, where it has a direct effect (confirming H3a), and an Indirect effect mediated by Online Shopping Perception. Moreover, as said before, it fills the research gap on the concept of Intimacy related to the channel dimension. Thirdly, it was found that there was a direct effect when removing the Organism, therefore the Stimuli (Intimacy and Trust), doesn’t only affect the Online B2C Ecommerce perception positively (H, H1a, H1b), but also has a direct mediation effect on the channel preference. The testing of a model without an Organism, brought to light that the Stimuli (Trust and Intimacy) directly caused response (Showrooming, Webrooming, and Avoidance) in the absence of organism (online B2C preferences) - as stated in the mediation analysis. To finalize, one of the most novel insights that our research result reveal, is that: While both Trust and Intimacy have a positive effect on Online B2C E-commerce perception (confirming hypotheses H1, H1a and H1b), Intimacy shows to have a stronger effect compared to trust. Suggesting that customers value Intimacy even more than trust, and declare to find it less while Shopping Online. 6.2 Managerial Implications The different results, conclusions and findings, mentioned in this study, have important implications that should be considered for online retailers. Since we considered “Online Shopping” as a whole, both Only Online Retailers and Multi-channel retailers (also available offline) can find insightful conclusions. There’s valuable insights for all retailers who want to stay relevant in a constantly evolving environment by listening to what the customers demand. Several companies claim to use omnichannel strategies and expand to the online environment (Kent, 2016), for example traditional Offline retailers such as El Corte Inglés or Carrefour, integrate their Offline and Online selling strategies. However, in a fast-paced and constantly growing environment - is common to follow the 43 trends of the industry or what other competitors are doing in terms of expansion and use of technologies instead of creating new value (Kim, & Mauborgne, 2014). On the other side, as mentioned in the introduction, the fast growth comes with global challenges such as the economic and mental recuperation from a pandemic and the consequences of an on-going war against Ukraine. This dissertation confirms that moments of uncertainty, and in such a competitive and growing environment, it’s important that retailers take into account the opinions and emotions of their customers (Mandal, 2020) integrating into their strategies concepts as Trust and Intimacy, which shows to have a positive effect on Online Channel perception (H1, H1a, H1b) and a mediation effect on the purchase channel. The confirmation of Trust and Intimacy affecting online B2C Perception (H1, H1a, H1b), Online B2C Perception affecting avoidance (H3c), Trust affecting avoidance (H3a) and Intimacy affecting Webrooming (H3b) should be considered by retailers in order to create a differential value and remain close to their consumers in an over saturated market (due to low entry barriers and easy access to information and tools e.g. Shopify). All B2C retailers should be aware of the effect of Trust and Intimacy in Online B2C perception (H1). Firstly, the purely Online Retailers, but also the Offline retailers thinking about joining the Online selling environment as one of their distribution channels and the retailers who follow an Omnichannel strategy. As the literature confirms, customer journey is key (Lemon & Verhoef, 2016), but also the capacity to be perceived as Trustable and develop an Intimate relationship. Also, even if some of the relation were not considered as an initial hypothesis, the results of the present dissertation in the mediation analysis (Mediation Analysis - Table 7) bring insightful key concepts for retailers. The results confirm a stronger effect on Intimacy on Online B2C E-Commerce perception (H1b, presented on Table 6 - Hypotheses analysis). The supported hypotheses of the effect of Intimacy on Webrooming was confirmed (H3b), (confirming a positive effect), therefore a person who feels intimacy in online shopping, is likely to buy offline. However, this does not measure tendency to buy online; Tendency to buy online is measured by Showrooming. In our research, Intimacy proved to have a significant impact on Webrooming, but it also proved to have a significant impact on Showrooming. Therefore, it’s essential to have a better understand of these concepts an integrate them in omnichannel strategies (Kent et al., 2016; Verhoef et al.,2007), since the Use of numerous channels improve perceived service quality, resulting in satisfaction (Flavián et al., 2019). This expands the customer journey literature, by detecting that users can buy both online or offline when they perceive intimacy in online shopping. The same happens with Trust, users can buy both online or offline when they perceive Trust in online shopping. 44 6.3 Limitations and further lines of research This thesis has been conducted while considering a set of constraints and limitations. Firstly, in order to focus the results on the Hypotheses, the demographics of the respondents were not analysed as a mediating factor. Further lines of research could go deeper on the different sub-segments of sub-targets and identify groups in which Online Perception exists as a mediation effect. Also, another specific thing component of the Online Shopping behaviour that was not mentioned in the study, is the product category. Therefore, to deepen in the knowledge and spot specific bias and category-specific challenges, those who study individual differences in online shopping Trust and Intimacy, should include the effect on different categories (such as a product vs an experience or Retail vs Automotive). Thirdly, it is worth noting that the study primarily examined the influencing relationship of specific higher-order constructs, rather than delving into the intricate mechanisms that explain how lower-order constructs impact Trust and Intimacy in the context of Online Shopping (Hook et al., 2003; Jasper, 2000). This is a possible subject for further exploration and future research into the intricate dynamics underpinning the creation and manifestation of Trust and Intimacy in the online shopping environment. Additionally, as the study primarily aims to identify direct effects among the constructs presented in the Conceptual Framework, it did not extensively investigate the negative responses concerning the perception of Trust and Intimacy that were expressed by some participants. Future research could represent an object of study, in order to fulfill them and turn them into a more positive experience. By examining these negative responses and their underlying factors, researchers, and practitioners can work towards enhancing the overall online shopping experience and fostering stronger Trust and Intimacy between consumers and e-commerce platforms. This dissertation was only limited to confirming the importance of Trust and Intimacy, and the fact that they affect Online B2C E-commerce perception and the election of the purchasing channel. Additional examination could verify how the latest developments of technologies like AR, VR and its applications like Chatbots, Metaverse, Virtual Assistants and Virtual Try-Ons try (Shaji & George, 2012) impact these higher-order constructs (see Annex Table 8 for an example). This type of research is needed in order to maintain an iteration in omnichannel retail strategies and keep improving the overall 45 consumer experience. Furthermore, if it is determined that technology can potentially contribute to addressing these issues, follow-up investigation should be conducted to examine the various sociodemographic characteristics that may be associated with Trust and Intimacy perceptions in Online Shopping platforms among customers. Moreover, these possible follow-up studies could implement a series of guidelines of proved insights that could help retailers and stakeholders involved in Online Shopping commerce or Omnichannel strategies. For example, once sociodemographic and behavioural features have been identified, retailers could then employ techniques such as database filtering questions and Cluster Analysis to identify and categorize customers and know which group of people is more inclined to declare negative perceptions of Trust and Intimacy while shopping online. This would give shoppers more control over the experience, and allowing them to tailor the process (Burke, 2002): - Subsequently, retailers could personalize the User Interface to cater to the specific needs of customers based on these identified features. This can be achieved by utilizing, if found, technology that enhances the sense of Intimacy and Trust during the online shopping experience - In addition, during the registration process for new users, particularly those belonging to clusters that are sensitive to perceive Lack of Trust and intimacy when making online purchases, it may be beneficial to inquire about the preferred types of technology that users would like to utilize to enhance their overall shopping experience. These options may include features such as virtual reality trials, chatbots, real-time support assistants, stylists, or other professionals. By adopting these strategies, retailers can strive to create a more tailored and personalized online shopping experience that addresses customers' needs and fosters a better sense of relationship. This, is incredibly important, since, as shown in this dissertation, there is still emotional needs to cover in regard to the Online Shopping experience, and only with continuous research and iteration of the shopping experience – keeping the customer and their emotional needs at the center of their strategic decisions – retailers be able to remain leaders. 46 BIBLIOGRAPHICAL REFERENCES Abdul W,K., Kamran R & Hamza, C. (2020). E-commerce partial report. Alba, J., Lynch, J., Weitz, B., Janiszewski, C., Lutz, R., Sawyer, A. and Wood, S. (1997), “Interactive home shopping: consumer, retailer, and manufacturer incentives to participate in electronic marketplaces”. Journal of Marketing,61, (3), 38-53. https://doi.org/10.1177/002224299706100303 Alexander Benlian, Ryad Titah & Thomas Hess (2012) Differential Effects of Provider Recommendations and Consumer Reviews in E-Commerce Transactions: An Experimental Study. Journal of Management Information Systems, 29(1), 237-272, DOI: 10.2753/MIS0742-1222290107 Arantola, H. (2002). Consumer Bonding – A Conceptual Exploration. Journal of Relationship Marketing. 1. https://doi.org/10.1300/J366v01n02_06 Arora, S., & Sahney, S. (2018). Consumer’s webrooming conduct: an explanation using the theory of planned behavior. Asia Pacific Journal of Marketing and Logistics, 30(4), 1040-1063. Aw, E.C.-X. (2019). Understanding the webrooming phenomenon: Shopping motivation, channel-related benefits and costs. International Journal of Retail & Distribution Management, 47(10), 1074-1092. https://doi.org/10.1108/IJRDM-01-2019-0026 Aw, E. C. X. (2020). Understanding consumers’ paths to webrooming: A complexity approach. Journal of Retailing and Consumer Services, 53, 101991. https://doi.org/10.1016/j.jretconser.2019.101991 Aw, E.C.-X., Kamal, N., Ng, S. I., & Ho, J. A. (2021). Searching online and buying offline: Understanding the role of channel-, consumer-, and product-related factors in determining webrooming 47 intention. Journal of Retailing & Consumer Services, 58, 102-328. https://doi.org/10.1016/j.jretconser.2020.102328. Barr,D. G., & Cuthbertson, K. (1991). Neoclassical Consumer Demand Theory and the Demand for Money, The Economic Journal, Volume 101, Issue 407. Pages 855–876, https://doi.org/10.2307/2233859 Becker, J.-M., Klein, K., & Wetzels, M. (2012). Hierarchical latent variable models in PLS-SEM: guidelines for using reflective-formative type models. Long range planning, 45(5-6), 359-394. Bernard, E.K., & Makienko, I. (2011). The Effects of Information Privacy and Online Shopping Experience in E-Commerce. Academy of Marketing Studies Journal, 15, 97. Berry, L. L. (1995). Relationship marketing of services—Growing interest, emerging perspectives. Journal of the Academy of Marketing Science,23(4), 236–245. https://doi.org/10.1177/009207039502300402 Bitner, M. J., Ostrom, A. L., & Morgan, F. N. (2008). Service Blueprinting: A Practical Technique for Service Innovation. California Management Review, 50(3), 66–94. https://doi.org/10.2307/41166446 Bitner, M. J. (1990). Evaluating Service Encounters: The Effects of Physical Surroundings and Employee Responses. Journal of Marketing, 54(2), 69–82. https://doi.org/10.1177/002224299005400206 Boj, J . Liana, M. (2014) The Underlying Dimensions of Relationship Marketing in the Malaysian Mobile Journal of Relationship Marketing, 13(3), 169-190. doi.org/10.1080/15332667.2014.939017 Bojei, Jamil & Julian, Craig & Che Wel, Che Aniza & Ahmed, Zafar. (2013). The empirical link between relationship marketing tools and consumer retention in retail marketing. Journal of Consumer Behaviour, 12 (3).https://doi.org/10.1002/cb.1408 48 Levin, A. M., Levin, I. P., & Weller, J. A. (2005). A multi-attribute analysis of preferences for online and offline shopping: Differences across products, consumers, and shopping stages. Journal of Electronic Commerce Research, 6(4), 281 Lewis, B. R. (1988). Customer care in service organisations. International Journal of Operations & Production Management, 8(3), 67-75. Li, L. H., Cheung, K. S., & Tse, W. S. (2021). Understanding the shoppers’ perception in retail shopping malls: a self-determination theory perspective. Journal of Strategic Marketing, 1-16. Li, Y.P. (2016) Empirical Study of Influential Factors of Online Customers’ Repurchase Intention. iBusiness, 8, 48-60. http://dx.doi.org/10.4236/ib.2016.83006 Liao, Y. (2015). The Role of Trust on Brand Loyalty and Brand Equity. Lieberman, A., & Schroeder, J. (2020). Two social lives: How differences between online and offline interaction influence social outcomes. Current opinion in psychology, 31, 16-21. https://doi.org/10.1016/j.copsyc.2019.06.022 Liu, Y., & Yang, R. (2009). Competing Loyalty Programs: Impact of Market Saturation, Market Share, and Category Expandability. Journal of Marketing, 73(1), 93–108. https://doi.org/10.1509/jmkg.73.1.093 Lin, P. H. (2013). Shopping Motivations on The Internet: An Empirical Study of Trust, Satisfaction and Loyalty. International Journal of Electronic Business Management, 11(4). Loiacono, E.T., Watson, R.T. & Goodhue, D.L. (2002). WebQual: A Measure of Website Quality. Marketing Theory and Applications. 13, 432-438. Lone, S., & Weltevreden, J.W.J. (2022). European E-commerce Report. Amsterdam/Brussels: Amsterdam University of Applied Sciences & Ecommerce Europe. 55 Luhmann, N. (1979). Trust and Power. New York: Wiley. Khan, M. M., Memon, Z., & Kumar, S., (2019). Celebrity Endorsement and Purchase Intention: The Role of Perceived Quality and Brand Loyalty. Market Forces, 14(2), 99-120. Malär, L., Krohmer, H., Hoyer, W. D., & Nyffenegger, B. (2011). Emotional Brand Attachment and Brand Personality: The Relative Importance of the Actual and the Ideal Self. Journal of Marketing, 75(4), 35–52. https://doi.org/10.1509/jmkg.75.4.35 Mandal, P. C. (2020). Marketing in an economic downturn – Challenges and opportunities. International Journal of Business Strategy and Automation, 1(1), 46–56. https://doi.org/10.4018/ijbsa.2020010104 Maslow, A. H. (1943). A theory of human motivation. Psychological Review, 50(4), 370–396. https://doi.org/10.1037/h0054346 Mayer R.C., Davis, JH., Schoorman, F.D. (1995). An integration model of organizational Trust. AMR, 20(3), 709–34. Miyazaki, A. D., & Fernandez, A. (2000). Internet Privacy and Security: An Examination of Online Retailer Disclosures. Journal of Public Policy & Marketing, 19(1), 54–61. https://doi.org/10.1509/jppm.19.1.54.16942 Moore, C. M., Doherty, A. M., & Doyle, S. A. (2010). Flagship stores as a market entry method: the perspective of luxury fashion retailing. European Journal of Marketing, 44(1), 139-161. Mutum, D. and Ghazali, E. (2006). Online Shoppers Vs Non-Shoppers: A Lifestyle Study of MalaysianInternet Users. Eds. Welsh, D.H.B. et al. Proceedings of AGBA 3rd World Congress, Advances in Global Business Research, 3 (1), 4 – 6 January 2006, Kuala Lumpur, Malaysia, 43-54. 56 Natarelli, M., & Plapler, R. (2017). Brand Intimacy: A New Paradigm in Marketing. Hatherleigh Press. https://books.google.de/books?id=Z-DGDAAAQBAJ Natarelli, M. (2018, March 6). “Brand Intimacy” – An Interview with Mario Natarelli [Interview]. Marketing Journal. Niranjanamurthy M, & DR. Dharmendra Chahar. (2013). The study of E-Commerce Security Issues andSolutions. International Journal of Advanced Research in Computer and Communication Engineering, 2(7). Nilowardono, S., Susanti, C.E., & Rahayu, M. (2020). Effects of Perceived Quality and Social Media Marketing on Brand Loyalty through Brand Trust and Brand Love. IOSR Journal of Business and Management, 22(8), 20-29. Maechler, N., Neher, K., & Park, R. (2016). From touchpoints to journeys: Seeing the world as customers do. McKinsey & Company, 1-10. http://bitly.ws/In7P Majava, J., & Isoherranen, V. (2019). Business model evolution of customer care services. Journal of Industrial Engineering and Management (JIEM), 12(1), 1-12. https://doi.org/10.3926/jiem.2725 Mittal, B. (2006). I, Me and Mine: How Products Become Consumers’ Extended Selves. Journal of Consumer Behavior, 5 (6), 550–62. Monsuwé, T.P., Dellaert, B.G., & Ruyter, K.D. (2004). What drives consumers to shop online? A literature review. International Journal of Service Industry Management, 15, 102-121. Oatley, K., & Johnson-Laird, P. N. (1987). Towards a cognitive theory of emotions. Cognition and emotion, 1(1), 29-50. 57 Ohanian, R. (1990). Construction and Validation of a Scale to Measure Celebrity Endorsers’ Perceived Expertise, Trustworthiness, and Attractiveness. Journal of Advertising, 19(3), 39–52. https://doi.org/10.1080/00913367.1990.10673191 Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International journal of electronic commerce,7(3), 101-134. Perea y Monsuwe, T., Dellaert, B. G. C., & de Ruyter, J. C. (2004). What Drives Consumers to Shop Online? A Literature Review. International Journal of Service Industry Management, 15(1), 102-121. https://doi.org/10.1108/09564230410523358 Perlstein, J. (2022). How Brands Can Win “Brand Attachment” Through Meaningful CRM. Forbes. Tan, Y.H., & Thoen, W. (2000). Formal Aspects of a Generic Model of Trust for Electronic Commerce. In Proceedings of the 33rd Hawaii International Conference on System Sciences. Park, C. W., Macinnis, D. J., Priester, J., Eisingerich, A. B., & Lacobucci, D. (2010). Brand Attachment and Brand Attitude Strength : Conceptual and Empirical Differentiation of Two Critical Brand Equity Drivers. Marshall Research Paper Series Working Paper. Journal of Marketing. Park, C. W., Macinnis, D. J., & Priester, J. R. (2006). Beyond Attitudes: Attachment and Consumer Behavior. Seoul National Journal, 12(2), 3–36 Patzer, G.L., 1985. The Physical Attractiveness Phenomena. Plenum Press. PayPal. PayPal E-Commerce Index. (2022, November). Plutchik, R. (1980). A GENERAL PSYCHOEVOLUTIONARY THEORY OF EMOTION. Elsevier eBooks (pp. 3–33). https://doi.org/10.1016/b978-0-12-558701-3.50007-7 58 Ramaseshan, B., & A. Stein. 2014. Connecting the dots between brand experience and brand loyalty: The mediating role of brand personality and brand relationships. Journal of Brand Management, 21(7–8): 664–683. Rashid, R. M., Rashid, Q. ul A., & Pitafi, A. H. (2020). Examining the Role of Social Factors and Mooring Effects as Moderators on Consumers’ Shopping Intentions in Social Commerce Environments. SAGE Open, 10(3). https://doi.org/10.1177/2158244020952073. Risselada, Hans, Peter C. Verhoef, and Tammo H.A. Bijmolt (2014). Dynamic Effects of Social Influence and Direct Marketing on the Adoption of High-Technology Products. Journal of Marketing, 78, 52–68. https://doi.org/10.1509/jm.11.0592 Roberts, K. (2005). Lovemarks: the future beyond brands. powerHouse Books. Schaefer, M. T., & Olson, D. H. (1981). Assessing intimacy: The PAIR Inventory. Journal of Marital and Family Therapy, 7(1), 47–60.https://doi.org/10.1111/j.1752-0606.1981.tb01351.x Schiffman, G., & Kanuk, L. (2000). Consumer Behavior. Prentice Hall, Inc. Serravalle, F., & Pantano, E. (2023). Mastering care management strategies to improve retailing: Mechanisms, capabilities, impacts and emerging opportunities. Journal of Retailing and Consumer Services, 73, 103298. https://doi.org/10.1016/j.jretconser.2023.103298 Shostack, L. (1985) Planning the Service Encounter. The Service Encounter, 234-254. Sohaib, M., Mlynarski, J., & Wu, R. (2022). Building Brand Equity: The Impact of Brand Experience, Brand Love, and Brand Engagement: A Case Study of Customers’ Perception of the Apple Brand in China. Journal of Sustainability, 15(1), 746. https://doi.org/10.3390/su15010746 Song, J., & Zahedi, F. (2005). A Theoretical Approach to Web Design in E-Commerce: A Belief Reinforcement Model. Management Science, 51(8), 1219–1235. https://doi.org/10.1287/mnsc.1050.0427 59 Soopramanien, D. G., & Robertson, A. (2007). Adoption and usage of online shopping: An empirical analysis of the characteristics of “buyers”“browsers” and “non-internet shoppers”. Journal of Retailing and consumer services, 14(1), 73-82. Souitaris, V., & Balabanis, G. (2007). Tailoring Online Retail Strategies to Increase Customer Satisfaction and Loyalty. Long Range Planning, 40, 244-261. https://doi.org/10.1016/j.lrp.2006.11.006 Srull, T. K., Lichtenstein, M., & Rothbart, M. (1985). Associative storage and retrieval processes in person memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 11(2), 316. Sturdy, A. (1998). Customer care in a consumer society: smiling and sometimes meaning it?. Organization, 5(1), 27-53. Suler, J. R. (2016). Psychology of the digital age: Humans become electric. Cambridge University Press. Straker, K., Wrigley, C., & Rosemann, M. (2015). Typologies and touchpoints: designing multi-channel digital strategies. Journal of Research in Interactive Marketing, 9, 110-128. https://doi.org/10.1108/JRIM-06-2014-0039 Treacy, M., & Wiersema, F. (2007). The discipline of market leaders: Choose your customers, narrow your focus, dominate your market. Hachette UK. Turner, J. C. (1991). Social influence. Thomson Brooks/Cole Publishing Co. Turner, J. H. (2007). Human Emotions: A Sociological Theory. Routledge. U. S. Census Bureau (2023). Quarterly retail e-commerce sales: 1st quarter 2023. https://www.census.gov/retail/mrts/www/data/pdf/ec_current.pdf 60 Van Lange, Paul A. M., Carly E., Stephen M., Drigotas, Ximena B., Arriaga, B.S., Witcher Chante, L.C., (1997). Willingness to Sacrifice in Close Relationships. Journal of Personality and Social Psychology, 72, 1373-1396. Van den Poel, D., & Buckinx, W. (2005). Predicting online-purchasing behaviour. European journal of operational research, 166(2), 557-575. Verhoef, P. C., Neslin, S. A., & Vroomen, B. (2007). Multichannel customer management: Understanding the research-shopper phenomenon. International journal of research in marketing, 24(2), 129-148. Villani, I. (2018). Transform customer experience: How to achieve customer success and create exceptional CX. John Wiley & Sons. Wang, M., Sun, L., & Hou, JD. (2021). How Emotional Interaction Affects Purchase Intention in Social Commerce: The Role of Perceived Usefulness and Product Type. Psychology Research and Behavior Management, 14, 467-481. https://doi.org/10.2147/PRBM.S301286. Wang, X., & Yang, Z. (2010). The Effect of Brand Credibility on Consumers’ Brand Purchase Intention in Emerging Economies: The Moderating Role of Brand Awareness and Brand Image. Journal of Global Marketing, 23(3), 177–188. https://doi.org/10.1080/08911762.2010.487419 Waring, E. Tillman, M.P., Frelick, L., Rusell,L., & Weisz, G. 1980. Concepts of Intimacy in the General Population. The Journal of Nervous and Mental Disease. 168(8), 471-474. Willmott, B. Retail showrooms, mobile sales. Journal of Direct Data Digital Marketing Practices 15, 229–232 (2014). https://doi.org/10.1057/dddmp.2014.4 Xi, H., Hong, Z., Jianshan, S., Li, X., Jiuchang, W., & Davison, R. (2016). Impulsive purchase behaviour in social commerce: The role of social influence. Pacific Asia Conference on Information Systems. 61 Yang, Y., Hu, Y., & Chen, J. (2005b). A web trust-inducing model for e-commerce and empirical research. https://doi.org/10.1145/1089551.1089589 Zeithamova, D., Schlichting, M. L., & Preston, A. R. (2012). The hippocampus and inferential reasoning: building memories to navigate future decisions. Frontiers in human neuroscience, 6, 70. Zhou, S., Li, T., Yang, S., & Chen, Y. (2022). What drives consumers’ purchase intention of online paid knowledge? A stimulus-organism-response perspective. Electronic Commerce Research and Applications,52, 101-126. https://doi.org/10.1016/j.elerap.2022.101126 Zhu, L., Li, H., Wang, F. K., He, W., & Tian, Z. (2020). How online reviews affect purchase intention: a new model based on the stimulus-organism-response (S-O-R) framework. Aslib Journal of Information Management,72(4), 463-488. 62 1. APPENDIX A Questionnaire 1st Draft Dear participant, This is a survey (14 questions, around 10/15 min) to evaluate the perceptions of consumers buying online in different categories. There is no risk involved in answering any of the following questions. Remember that your participation in this survey is voluntary, which means that you are free to participate or not, as well as give it up at any time. However, your responses are very important, completely anonymous, and will be used only for academic purposes. *The panel of Appinio, automatically classifies (since it already knows it) the gender and age of the respondent – which already gave their consent and declared they are over 18 years old. Question Answer Please rate your degree of agreement with the following statements about on a scale of 1 (strongly disagree) to 7 (strongly agree). I am quite certain about what I will get after buying online I know how to get what I need from with e-commerce stores I generally trust e-commerce stores I find personalized recommendations when buying online When buying online, I find more brands that are sensitive to my interests I tend to check the Social Media quality of the e-commerce stores I buy at before buying I would tend to buy a product based more on the opinion of a friend than on online reviews. I don't trust online reviews, I think they tend to be 63 false. I'm afraid of being robbed giving my card online I only buy from online stores that also exist offline. Please rate your degree of agreement with the following statements about on a scale of 1 (strongly disagree) to 7 (strongly agree). I feel like I'm part of a community when I buy offline I tend to feel closer to a brand when I spend 1 hour in an online shop vs an on-site shop I feel a sentimental or affectionate relationship with brands I've known offline Please rate how strong you feel this emotions when shopping online vs offline: Closeness, Warmth, Care, Calm, Affection I'd rather spend an hour shopping online than in a shopping mall If you are considering the purchase of a specific product that with a special emotional charge for you (e.g. a dress to assist to a wedding), where do you usually search for information (e.g. price, features etc.)? All the time Often Sometimes Rarely Never I search online for information I go to a store and ask a sales person I use the chat function on online retail stores I ask friends and family I look for a service phone number on the store website and call them I go on the brand’s social media account I check reviews on forums and blogs Study 1 Measurement Item 64 71 APPENDIX B Appendix B.NOVA IMS Ethics Committee Approval 72 ANNEXES 1.Plutchik's (1980) psychoevolutionary theory of basic emotions - Wheel of emotions 2.Representation of preferences and satisfaction of High-Emotion vs Low-Emotion Customers 73 3.Homepage of Appinio Website 4. MoTEC by Egger (2001) 5.Possible Study for Further Lines of Research 74 6. Table 8 Scales and measurements for Further Lines of Research 75 76