Loyalty in B2B relationship using emarkets

(1)

Loyalty in B2B relationship using emarkets

by

Bas van Dongen

University of Groningen

Faculty of Economics and Business

Master Thesis IB&M

(2)

2

Abstract

(3)

3

Introduction

With the rise of the internet came new possibilities for firms. One of those was the sale of products through their websites. This also gave rise to companies that focus on online sales such as Amazon. US Business to Business (B2B) alone sold over $8 trillion in goods in total in 2014 according to Wu (2015), only a part of that is in ecommerce however, she believes that the US B2B ecommerce market will grow to $1 trillion, twice the size of the US Business to Consumer (B2C) ecommerce market in 2020. This shows that a large part of sales is already done through B2B and that this market portion will only grow.

One of the most important parts for stores is customer loyalty (Rauyruen and Miller, 2007). Loyal customers may even be up to ten times as profitable as an average customer (Anderson and Srinivasan, 2003, Health, 1997, Newell, 1997). Especially on the Internet the loyalty (e-loyalty) of customers is an essential part of the strategy, because a competitor´s products are only a few clicks away (Srinivasan et al. 2002, Carter, Wright, Thatcher and Klein, 2014). Customer loyalty has been a subject that has been researched a lot even before the internet gave a new dimension to it, both in the B2C context (Dick and Basu, 1994) as well as in the B2B context (Rauyruen and Miller, 2007). Loyalty in the B2B context is researched less than in the B2C context (Russell-Bennett, McColl-Kennedy and Coote 2007), however that does not mean that it is not important. Customer loyalty in the B2B context is important because gaining new customers is costly and the retention of customers is linked to long-term profitability (Anderson and Mittal, 2000, Davis-Sramek, Droge, Mentzer and Myers, 2009, Reichheld 1996, rauyruen and Miller 2007). This difference in amount of research is even more true when it comes to the internet, loyalty has been researched a lot in the B2C context, while in the B2B context there is hardly any research on e-loyalty (Janita and Miranda, 2013, Toufaily, Ricard and Perrien, 2013). Toufaily et al. (2013) noted this gap and suggested that more research is needed.

(6)

6 company, despite situational influences and marketing efforts that lead to transfer behavior” (pp. 1439). And after their literature research they created an integrative model of online customer loyalty.

B2B ecommerce has several advantages over traditional markets. It reduces procurement costs before, during and after the transaction is complete (Lucking-Reiley and Spulber, 2001, Rao, Truong, Senecal, & Le, 2007) Rao et al. (2007) state that emarkets reduce search costs in several ways, facilitating comparisons through providing information on sellers and products along with the availability and the prices, improving the buyer’s options through expansion of the supplier base, buyers can more easily compare their selections due to real-time inventory listing and near-perfect market information. They also state that transaction costs are lower using emarkets due to low asset specificity and low coordination costs. Costs are reduced during and after the transactions because there is no need to meet in person as communication can be done over the internet (Lucking-Reiley and Spulber, 2001).

These advantages also show how ecommerce through the use of an emarket makes national borders less relevant and it even disregards physical barriers in some instances. It not only reduces the cost that come with a transaction, it also widens the range of possible suppliers and buyers that can be reached with ease. With an emarket and the use of the internet, it is just as easy to view the products for sale in China as the products that are for sale in the Netherlands. The wider range of possible suppliers and buyers is interesting for companies as these unknown companies might have better quality or lower priced goods. It also makes communication easier and faster as an email takes the same time to go from one person to another regardless of physical distance. In the B2C context Kassim and Abdullah (2010) performed a cross-cultural analysis on the effect of perceived service quality dimensions on customer satisfaction, trust, and loyalty in e-commerce settings. In their paper they compared Qatar and Malaysia. They found, while most explanations of loyalty had no greater effect in one country than the other, there were however significant differences that indicate that cultural distance has an impact on how much of an effect an explanation has on loyalty. This paper will look into whether the nationality of a company has an effect on their perceived importance of factors in explaining e-loyalty.

(7)

7 which led to many suppliers not using the emarkets (Rao et al. 2007). This ease makes the loyalty important for companies in the ecommerce context to not lose market share because of the ease with which buyers can compare their products with other products.

Considering how large the B2B market is and the capabilities of the internet, I believe that research in online B2B relationships should be expanded. Due to differences between traditional and online B2B I believe that there may be different variables that are important and that a new model should be made. There is research on online B2C loyalty and what is necessary to cultivate it in consumers. However I think that the same models that are used for B2C e-loyalty cannot be applied to the B2B context. This is because the difference between private customers and firms are too large, especially considering the consequences of buying something. For example, if a consumer were to buy screws to fix two boards together to build a birdhouse, if the screws were of low quality and were to break then the wooden house would break and the consumer would have to buy better screws. However if a construction company were to buy low quality equipment or material they risk far more than a consumer. In the case of equipment they run the risk that it can malfunction, which forms a health and safety risk, or that it takes longer than better quality equipment, which costs them time. For companies the time they take to complete a project translates into money, because the faster a project can be completed, the more projects can be completed in total. In the case of low quality materials they run the risk of lowering structural integrity or possible break downs which also increase the time it takes to complete a project, and if a problem with the materials only occurs after they completed the project this could also lead to a lowered reputation. Also Hande, Ghosh and Govil (2015) show that different factors are important for businesses and for consumers in e-commerce. On the other hand it might also be true that the two share concepts such as trust which are important in both B2C and B2B ecommerce.

Research questions

Research question 1: To what extent do managers in the B2B ecommerce judge that e-loyalty of customers is important?

(8)

8 Research question 3: Do domestic and foreign managers on the B2B emarkets differ in their opinions on importance of e-loyalty and the factors that influence e-loyalty?

Contributions

Because there is so little research on the variables that influence e-loyalty in the B2B context, my research will make a model of the important variables for B2B e-loyalty and the important variables that online B2C research uses. Using the meta-analysis from Toufaily et al. (2013), I can find the most researched and most significant variables that affect the e-loyalty in B2C. I will try to explain which factors are perceived to be important by suppliers in emarkets and how important those factors are perceived to be. At the moment due to the lack of research it is unknown whether and if so how B2B ecommerce is different from B2C ecommerce. This research tries to shed light on that subject and show what aspects of the B2B ecommerce are important to suppliers with respect to e-loyalty of customers.

This will be exploratory research that contributes to the existing literature by explaining how important loyalty in the online B2B context is in the perception of suppliers, which factors are important for developing e-loyalty in the perception of suppliers and whether nationality plays a role in the perceived importance of those factors. At the moment there is close to no research, even though the B2B market is very large and the ecommerce in B2B is expected to grow. It will also compare this to the existing research on traditional B2B loyalty and relationship seeking behavior. This research finds that there are varying degrees of perceived importance in both the factors taken from traditional B2B and online B2C commerce. Several groups of related factors in the eyes of the suppliers can be found and there was no significant difference found between the perceptions of suppliers from different countries. In the end this research will formulate implications for managers.

The rest of the paper is structured as follows.

(9)

(10)

10

Literature review

As I stated earlier loyalty has been researched a lot in the past with regards to both B2B, offline and online B2C context. It is hardly researched in the online B2B context. This while the B2B ecommerce has a rather large portion of the total B2B trade and is still growing. According to predictions by Wu (2015) in the US alone the online B2B commerce will reach twice the size of the US B2C ecommerce market, $1 trillion, in 2020.

Because it is such a rapidly growing form of commerce it is important to know how to operate in this different environment and to find the differences between the traditional B2B environment and the online ecommerce environment. One such difference is the importance of loyalty. Researchers agree that loyalty is one of the most important aspects for companies (Rauyruen and Miller, 2007). Anderson and Srinivasan, (2003) Health, (1997) and Newell (1997) even agree that customers who are loyal to a store can be up to ten times more profitable than customers without loyalty.

Attitudinal and Behavioral loyalty

Loyalty is not a single concept, it consists of two parts (Rauyruen and Miller, 2007): attitudinal loyalty and behavioral loyalty. Attitudinal loyalty is the loyalty that consists of the amount of repeat purchases made by a customer. Behavioral loyalty is when the customer is willing to recommend your company to other people. A customer who repeatedly purchases at the same store may not have a high attitudinal loyalty. Repeat purchases alone are not enough to be loyal, there might be a different reason for this, such as that the store is the only feasible option for the customer to purchase a particular good. The repeat purchases have to come with an intent to buy there even if there are other companies with comparable product for comparable or lower prices (Rauyruen and Miller, 2007).

Transactional versus Relationship marketing

(11)

11 called transactional intention. A customer with transactional intent shows an opportunistic and short-term attitude toward the firm. They buy products because it is forced on them, by switching costs, convenience, low prices etc., or without any involvement. These customers hold no affection or affinity towards the brand, the intermediary or the firm. Due to this a firm cannot rely on them for loyalty as they can switch anytime it becomes favorable for them to do so. On the other extreme of the continuum are the customers who act in the opposite way towards the firm. They are more long-term oriented and they do not act opportunistically. They might even be willing to pay a premium to keep the relationship going. These customers are the ones who in the long run add a significant amount of value to the company. Short-term factors such as price and convenience affect these customers little to not at all and they will make a large effort to buy from that particular firm. This relationship intention also applies to suppliers and there are two different marketing approaches for the two extremes of the continuum. Transaction marketing (TM) is the approach for the short-term, where the immediate transaction holds the focus. It is more tactical and involves, aside from short-term thinking also acting. The amount of sales holds the most important focus in this approach and any service or support after the sale is concluded is considered an extra cost. As the name implies the deal itself is both the start and the end of the relationship. This approach is best suited to mass market and commodity markets, because the number of transactions is the most important in those industries and the firms cannot survive without these transactions (Baker, Buttery, and Richter-Buttery., 1998). This approach searches for the opportunistic customers who have transactional intent.

(12)

12 below both variables that influence loyalty in the traditional B2B commerce and variables that were proven to have a significant influence on e-loyalty in B2C ecommerce.

Explanation of customer loyalty in the B2B sector

Aside from the emarket which is used by the companies and the loyalty that they may want to obtain as part of their relationship seeking behavior there are also of course the variables that influence the attitudinal and behavioral loyalty as there is little research on the variables that influence the loyalty in B2B ecommerce. In the following pages I will outline the main explanations for customer loyalty discussed in the literature on traditional offline B2B context.

Satisfaction

According to Horppu et al. (2008) one of the prerequisites for trust in a website is the satisfaction with that website. They define satisfaction as “an affective consumer condition towards the web site that results from an evaluation of all the aspects that make up the consumer relationship” (horppu et al. 2008 pp. 404). This study researched online B2C loyalty in which the website was the website of the firm that sold the product. This view is also shared by Kassim and Abdullah (2008). Molinari, Abratt and Dion (2008) researched the effects of satisfaction in B2B on loyalty. They defined it as the buyer’s satisfaction with the delivered good or service and found a positive link between the two. Lam et al. (2004) made a distinction between two different kinds of satisfaction, service encounter or transaction-specific satisfaction and overall or cumulative satisfaction. The first of these focuses on the satisfaction with the product or service, and the latter focuses on the satisfaction that accumulates over a series of encounters with a firm. While cumulative satisfaction may give a broader idea on satisfaction it is also similar to a combination of different variables, namely satisfaction with a product, support service quality and commitment. Therefore I will focus on the first definition of satisfaction with the product sold and expect this to also have a positive influence on loyalty in the online B2B setting, satisfaction directly influences e-loyalty (Molinari, Abratt and Dion, 2008, Kassim and Abdullah, 2008, Lam et al. 2004 Liang et al. 2008).

Trust

(13)

13 relationships it is important to understand the nature of trust and how improtant it is for loyalty, as that has a large impact on the relationship. Some authors even go as far as saying that trust is the most important part of developing a succesful relationship and loyalty in B2B. “relationship marketing is built on the foundation of trust” (Berry, 1995, pp. 242). Schefter and Reichheld (2000, pp. 107) also note the importance of trust in “to gain loyalty of customers, you must first gain trust”. And Rauyruen and Miller (2007, pp. 24) also state that “trust is an important feature or aspect in the building and development of quality relationships through a process of making and keeping promises”. This shows that trust is important in traditional B2B loyalty. Because I believe that the involvement of an emarket only allows for easier finding of suppliers I believe that trust will also influence loyalty in online commerce (Berry, 1995, Horppu et al. 2008, Kassim and Abdullah, 2008, Liang et al. 2008 Rauyruen and Miller, 2007, Schefter and Reichheld, 2000).

Commitment

(14)

14 a lesser effect on loyalty than it did on traditional B2B loyalty, but still a positive effect on e-loyalty.

Product quality

In a competitive environment one of the most important things to do is to gain an edge over your competitors. There are various ways to do this, one of which is to make high quality products (Reed, Lemak and Mero, 2000). Quality is something that most customers deem too important to compromise. It is also often considered as a criterion for selecting potential suppliers, seen as even more important than price (Liukko, Vuori, & Woodside, 1997). Most research agrees that the concept of product quality is very reliant on the perception of the customer. It is defined as a key attribute that customers use to evaluate products” (Shetty, 1987, pp. 46) or “the extent to which the supplier's product meets the customer's specification” (Ulaga, 2003, pp. 683). The concept of product quality encompasses three things according to Čater and Čater (2010): performance, reliability and consistency. All three of these are seen as important and positive in the customer’s perception. Stating it very simply, people prefer high quality products over low quality products (Ulaga 2003, Choi et al. 2006, Čater and Čater 2010). This leads me to believe that a higher product quality leads to both more attitudinal and behavioral e-loyalty.

Perceived information risk

(15)

15 2007). Second, “there are also uncertainties related to verification of the terms and conditions of the contract. Working with unknown suppliers limits the capability of suppliers to participate in the purchasing process and may cause the incompatibility between processes of suppliers and buyers” (Rao et al., 2007, pp. 1038). To streamline and solve these uncertainties supplier and buyer need to exchange information, however because the other party is unknown this may lead to loss of sensitive information. These uncertainties lead me to believe that when companies are afraid of these uncertainties they may be less willing to enter into a relationship. Therefore I believe that perceived risk of information loss has a negative effect on e-loyalty.

Perceived value of emarket

(16)

16

Figure 1. conceptual model B2B variables

Explanation of customer loyalty in the B2C sector

In the following pages I will outline the main explanations for customer loyalty discussed in the literature on online B2C commerce. These explanations are related to characteristics of the company, the products offered, and consumers’ perceptions of company and online shopping characteristics respectively.

Characteristics of the company

Competence

“A business's high level of competence provokes credibility in the consumer's mind and influences both customer loyalty and the propensity to formulate positive recommendations” (Toufaily et al. 2013, pp. 1443). When a company is competent they make sure that they uphold their end of a deal and make sure to meet deadlines and provide adequate or higher quality of goods or services. These are all positive things that can lead to e-loyalty, both attitudinal and behavioral (Toufaily et al. 2013)

Reliability of the supplier

(17)

17 it is one of the best indicators of the quality of the supplier. Aside from this, without reliability the promised product or service may not be delivered or performed to satisfaction. This dissatisfaction would lead the buyer to search for a different supplier. Therefore I believe that a higher reliability leads to higher e-loyalty.

Products and services that the company offers

Innovativity of the product

Torres-Moraga, Vásquez-Parraga, and Zamora-González, (2008) have researched the effect of products and brands on loyalty, and how they can be used to cultivate loyalty in consumers. They found that products may have a lesser effect on loyalty than brands, however they also researched the innovativity of the product on loyalty. They found that innovativity in products has a significant effect on loyalty when compared to products that have no innovativity. They theorized that “This may happen because innovative products require more customer participation in the process of delivering the product to the customer” (Torres-Moraga et al. 2008, pp. 308). The customer participation they mention is the market research into what exactly a consumer wants in a product as well as testing a product to see if it works as expected, as well as whether it is complete or if it is still missing something. This leads to their belief that manufacturers and providers of traditional products compared to innovative products may rely heavily on an established base of customers to stay in business, while the providers and manufacturers of innovative products have to put more effort into their work to satisfy the consumer (Torres-Moraga et al. 2008).

Purchase volume

According to Storbacka, Strandvik, and Grönroos, (1994) the relationship between supplier and buyer is different between buyers who purchase small volumes and those that buy larger volumes. This power is often used in negotiations.

(18)

18 Storbacka et al. (1994) have created a framework with which they measure the profitability of a relationship with a customer. In this framework they analyse how much of a customer’s expenses go to the supplier, for example if a construction company were to buy nails at one company and screws at another then both suppliers miss out on part of the possible patronage of the buyer. They call the amount that is bought at the supplier relationship revenue and how much the buyer buys in the entire industry, total industry volume (TIV). This does not only apply to different items bought at different suppliers, but also to the same item bought at different suppliers. They reason that for a supplier it is important to raise the relationship revenue to as large a part of the TIV as possible to raise profits. They also reason that this would improve the relationship. In summary, larger purchase volume gives buyers a form of power in the relationship, which would lead to e-loyalty because they do not have that at a different supplier, and when the purchase volume is a large part of the TIV, then this also increases loyalty.

Ability to save time

“The timesaving factor is a strong advantage that clients seek, especially those who shop and buy online, and the desire to save time significantly affects online loyalty” (Toufaily et al. 2013, pp. 1443)

Devaraj, Fan and Kohli, (2003) researched e-loyalty in the B2C context and found that several factors play a significant role. One of these was the ease of use and the amount of time it saves for the customers. They used a survey and asked questions that related these factors. They also found that taking a lot of time results in potential customers to leave the web shop and to take their business to other suppliers. This shows that saving time means that buyers go to their web shop.

With their survey they also found that there was a significant relationship between time savings and the loyalty of buyers, they said: “Due to time and cost savings from online shopping, we find that customers are inclined to continue to reward online stores with their loyalty” (Devaraj et al. 2003, pp. 190)

Support service

(19)

19 service from the supplier to help the buyer with any possible problems. While a buyer may be satisfied with a product, the price, the time saving and all the other variables mentioned, there is still another thing that a supplier can provide. The after sale support service is also appreciated by buyers. This support service includes any possible problems the buyer may have with the product, or help with installation of a product. When the support service quality is high, this allows the buyer to solve problems with the help of the supplier or to smoothly use the bought product before any problems arise. “A company positively influences customer online loyalty if able to save time for customers and offer them high quality support services” (Toufaily et al. 2013, pp. 1442). It is also noted by Balabanis et al. (2006) and Kassim and Abdullah (2010) that support service quality has a positive effect on loyalty.

IT policies of the emarket

One of the positive points about an emarket is the ease with which to find suppliers and the transparency of information. However this transparency has a downside, it is necessary to be careful not to make the emarket too transparent because this may lead to possible confidential data loss to other companies for the users of the emarket (Zhu 2002). To make sure that this is not a problem the IT policies of the emarket together with the IT employees of the emarket should create safeguards so that the users are safe. Without IT policies both buyers and suppliers may stay away, therefore IT policies most likely affect e-loyalty in a positive way (Toufaily et al. 2013)

Consumer’s view of the company

Attachment to the supplier and its products

(20)

20 Switching costs

(21)

21 what to expect on which page, which saves them time and effort (Balabanis, 2006). Financial switching costs are the loss of monetary funds that are related with switching to a different supplier, such as the loss of loyalty points with a store as used in B2C (Balabanis, 2006). In B2B this may take the form of having to make new negotiations with an unknown supplier while there are already favorable conditions with a previous supplier. As a result higher switching costs can result in e-loyalty.

Brand loyalty

Horppu et al. (2008) have a list of different levels of commitment towards a brand by consumers. In the highest level the customer is devoted to the brand, they call this brand loyalty. Horppu et al. (2008) state that in the online environment brand loyalty is more important than in the offline environment. They find that the anonymity that the internet provides makes it even more crucial to have a recognizable brand. When a firm already enjoys brand recognizability and loyalty, this may be transferable to the online environment and create a effect when they try to expand towards online sale of their product. This halo-effect comes from the consumers who are receptive to the familiarity of the brands they trust. Horppu et al. (2008) researched whether the parent brand had an effect on website loyalty and found significant support for this hypothesis. I believe that brand loyalty may also have a positive effect on e-loyalty in the B2B online context.

Initial contact

(22)

22 Site knowledge

Knowledge about a website can give a company a positive edge over the competition, Srinivasan et al. (2002) already noted how site knowledge can lead to habitual purchase. However, site knowledge also means that a customer has put time and effort into getting to know the site. According to Balabanis et al. (2006) this knowledge of the site allows a consumer to know what to expect and makes it easier for them to find what they are searching for and they might be reluctant to put time and effort into finding and getting to know another site. Therefore I believe that site knowledge has a positive effect on e-loyalty (Toufaily et al. 2013)

Consumer’s view on online shopping

Habitual purchase and convenience

Srinivasan et al. (2002) have researched a couple of different variables which together increase the convenience of using that companies’ website. They researched whether these convenience-inducing variables had a significant effect on e-loyalty and whether e-loyalty reduced the chance that consumers would search for different suppliers. This last hypothesis is linked to habitual purchase, as they believe that previous purchase leads to more purchases and word-of-mouth recommendations. Of the 8 variables they found that “customization, contact interactivity, cultivation, care, community, choice, and character are positively related to e-loyalty is supported” (Srinivasan et al. 2002, pp. 47). These variables show that consumers are brought and linked to the website by taking care of the consumer first and supporting them. And after the customer is used to one or more of the customized sites, the contact with the supplier, the given relevant information, the care to pre- and postpurchase convenience, the community, choice of products, and the character of the website, they are used to the website and no longer feel the need to go to another website and stay with the supplier out of a habit created by the supplier. The next time they need a product they go to the same website because they have created a habit of going to that online supplier instead of looking for other suppliers who may have a better quality or similar quality good for a lower price. Attitude of purchaser toward online purchasing

(23)

23 has towards shopping can work as a kind of filter. If they believe beforehand that online shopping is not beneficial to them and have a low opinion of it, than there is a lower chance that that they will gain loyalty towards the supplier, and the inverse is also found to be true, in which a good attitude towards online shopping increases the chances of e-loyalty.

Figure 2. Conceptual model online B2C variables.

Importance of distance in ecommerce

(24)

(25)

25

Methodology

Exploratory study

In the existing literature loyalty has been researched in both the B2B sector and the B2C sector. With the rise of the internet came a new platform to conduct trade on, in the form of emarkets, and new possibilities. This platform and the possibilities that came with it have been researched in the B2C context. This research found that there are different explanations for what drives loyalty in the online B2C sector from what drives loyalty in the traditional B2C sector. Research has not been conducted on online B2B loyalty.

B2B with the use of emarkets has some differences from traditional B2B, such as reduced transaction costs (Rao et al. 2007), due to available information on sellers and products that an emarket provides. Because there are differences between traditional and online B2B commerce, there may be different explanations for loyalty. Research has shown that in the B2C sector this was also the case. The different explanations have not been researched yet. To remedy this, this study performed exploratory research to find out what possible explanations there are. In this research the suppliers of an emarket have been asked for their perception on customer loyalty in online B2B commerce.

Sample selection

B2B ecommerce takes place through the use of an emarket. This is an online marketplace in which products and services are offered and monitored by a neutral 3rd_{party. These products}

and services are offered by at least more than one supplier. Janita and Miranda (2013, pp. 815) defined them as “a form of doing business that uses Internet technology to bring together multiple vendor and customer firms at a single website or platform, that provides a variety of mechanisms enabling the parties to straightforwardly conduct their business transactions, that is led by a third party who is either neutral and unconnected to the exchange that is to take place, or one of the two parties involved (buyers or sellers)”. Janita and Miranda (2013) used that definition to find an emarket for their research. I will use the same definition for emarkets for this research.

(26)

26 The emarkets on which I focus in this paper are diverse. There are emarkets for nearly every industry, it ranges from fast moving consumer goods to an emarket on which companies look for joint ventures (directory of emarket services, 2015). As my research is focused on relationship seeking behavior and loyalty in the online B2B context through the use of an emarket, it was necessary to find an emarket in an industry that adheres to several criteria. First the industry has to deal with firms that are not opposed to relationship forming. Secondly it has to deal with firms that are not entirely focused on relationship forming. This means that the firms need to be somewhere in the middle of relationship seeking, they need to be able to gain a profit from a relationship but not have relationships as necessary for their continued existence.

To answer my research question I needed to have a sample that did not fall in either of the two extremes, completely relationship seeking and completely devoid of relationship seeking behavior. The Transactional intent suppliers would most likely consider all variables to be unimportant, while the relationship intent suppliers would most likely consider all variables extremely important. I needed an industry that falls in the middle of the continuum. An industry that would put effort in a relationship, but it is not the only way for them to stay alive as a firm. The industry I used was the construction industry, where products include everything necessary to construct buildings and infrastructure. These products are both customizable but not to the extent that it needs a deep relationship between buyer and supplier to be bought and used.

To gain a sample in this industry I found 6 emarkets that focus on this industry in The Netherlands (emarket services, 2015). From these I chose one to take my sample. Relationship intent is part of both buyers and suppliers, so I could choose a sample from either. An emarket lists the suppliers, so buyers can easily find a supplier that provides the service or good they are looking for. This means that on an emarket I can find all the suppliers that are a part of the emarket, while I cannot find the buyers that use the emarket. Because of this my sample existed of suppliers.

(27)

27 a random sample from the firms from the Netherlands. The random sample of firms from the Netherlands had a small problem, the emarket was not entirely up to date. A couple of hundred suppliers on the site either no longer existed or did not have a means for me to contact them. For every firm I could not contact, I randomly selected another. This led to a total of 327 firms from outside of the Netherlands and 673 firms from the Netherlands. Of the 1000 firms that were part of my sample I had a response of 25 companies. I also received around a 100 automated responses that told me the email address was not in use and that the email could therefore not be delivered, I received a few other responses to inform me that the sender company had a policy to not participate in such questionnaires, one response in which the sender told me he does not speak English and a few responses where the sender told me his company did not use emarkets and that they would therefore not be able to accurately answer the questionnaire. The average size was 127 employees and the average age was 49 years old. Of the 25 responses 20 were from the Netherlands while the other 5 were from Belgium, Denmark and the Czech republic.

Data collection

Because this is an exploratory research that aims to find out how loyalty is explained in the online B2B sector and because it is not yet known which factors explain loyalty and whether or not these factors are related to each other, the data collection method was focused on reaching a large sample rather than gaining in depth knowledge of the explanations and their relationship with each other from a smaller sample. To reach a large sample and gain information on the factors that possibly explain loyalty in the online B2B sector this research used a questionnaire.

An initial design of the questionnaire was created with the help of my supervisor to find problems with the questions and be able to create an adequate questionnaire to gain complete and appropriate data for the research. The final questionnaire was sent directly to the companies by email with a link to the questionnaire on Qualtrics. Qualtrics was used to ensure the anonymity of the respondent as even the researcher himself does not know which answers belong to which company.

Questions asked in questionnaire

(28)

28 asking suppliers how important repeat purchases (attitudinal loyalty) are for their company and how important word-of-mouth recommendations (behavioral loyalty) are for their company.

To answer research question 2, the suppliers were given a list of possible explanations for repeat purchases and for word-of-mouth recommendations and asked to rate the importance of those possible explanations.

Research question 3 was not asked in the questionnaire but researched in the analysis of the responses.

All the questions except for firm size and firm age were asked on a Likert scale from 1 to 7, where 1 means extremely unimportant and 7 means extremely important for either repeat purchases or word-of-mouth recommendations. Firm size and firm age were asked in absolute number to gain data as complete as possible on those two variables.

This also means that only firm size and age are absolute values that do not originate from the perception of the supplier. There are several reasons why the questions didn’t ask for absolute values of the variables. First, the dependent variables, attitudinal and behavioral loyalty are very difficult to gain actual numbers for. The attitudinal loyalty is asked in number of repeat purchases. A supplier can look up how often a company has made purchases from their company, however to answer how often repeat purchases are made, they would have to choose one buyer to provide information about. Because attitudinal loyalty is a dependent variable they would have to answer all questions about the relationship between the independent variables and repeat purchases while keeping one company in mind. This might contain sensitive information they would not want to give out as well as severely increasing the time to answer the questionnaire. Behavioral loyalty pertains to information that is not completely available to suppliers themselves, as they do not know how often, if at all, buyers recommend their company to other buyers.

(29)

29

Analysis

I categorized the variables before testing them. They were categorized into variables taken from the research on traditional B2B loyalty and variables taken from the research on online B2C loyalty, as can be seen in the conceptual model. These two categories are tested separately from each other.

To answer research question 1, I look at the means of the answer to the question on how important repeat purchases and word-of-mouth recommendations are according to the suppliers. I perform a paired sample t-test to see if one is perceived to be different from the other and if so, which one is perceived to be more important. Following this I perform a correlation test to see if they are related to each other and finally I perform a factor analysis to see how many components there are and what variables are responsible for the variation in the components.

To answer research question 2, I will perform a paired sample t-test to see if the variables differ significantly from each other, which variables significantly differ from each other, which do not significantly differ from each other, and to find out which variables are perceived by suppliers to be more important for e-loyalty. I will perform a correlation test to see if the variables correlate with each other, which would indicate that they have a relationship with each other. And finally I will perform a factor analysis to see how many meaningful components with an eigenvalue over 1 there are and what variables are responsible for the variation in the components.

(30)

30

Results

In the following section I will show the results of the data analysis. First the results of the analysis for research question 1 are shown, followed by the results for research question 2 and finally the results for research question 3.

Research question 1: To what extent do managers in the B2B ecommerce

judge that e-loyalty of customers is important?

Comparison between attitudinal and behavioral loyalty

Table 1. Attitudinal loyalty compared to Behavioral loyalty

correlation

variables mean Std. Attitudinal Behavioral

Attitudinal 5.20 1.82574 1

Behavioral 4.84 1.65025 .523* 1

*marks significant correlation

Table 2. Factor analysis Attitudinal and Behavioral loyalty Component

variables 1

Attitudinal loyalty .873 Behavioral loyalty .873

(31)

31

Research question 2: Which factors do they evaluate to be important for

developing e-loyalty of customers?

Variables based in traditional B2B literature

Table 3. Variables based on B2B literature pertaining to Attitudinal loyalty correlation

variables Mean Std. Satisfaction Trust Emarket Quality Commitment Information

Satisfaction 5.96 1.05987 1 Trust 5.76 1.45144 .806* 1 Emarket 3.40 1.52753 -.041 -.068 1 Quality 6.12 0.92736 .641* .425* .171 1 Commitment 5.64 1.15036 .705* .670* -.009 .511* 1 Information 4.6944 1.36733 .288 .339 -.018 .074 -.002 1

*marks significant correlation

Table 4. Factor analysis results on Table 5. Importance of the variables variables based on B2B literature based on B2B literature pertaining to pertaining to Attitudinal loyalty Attitudinal loyalty

Component variables 1 2 Satisfaction .940 -.052 Trust .879 -.201 Quality .724 .383 Commitment .826 .153 Emarket .006 .756 Information .316 -.579

Tables 3 and 4 show the means and the results of the correlation test and factor analysis performed on the B2B variables as the supplier perceives them to influence attitudinal e-loyalty. Table 5 shows the importance of the variables based on B2B literature for attitudinal e-loyalty compared to each other in the eyes of the suppliers based on the results of the paired sample t-test (appendix A, table 17). The column furthest left shows the groupings of the variables compared to each other in the eyes of the supplier. Satisfaction, trust, commitment

(32)

32 and quality do not significantly differ from each other and have the highest mean importance in the perception of the supplier; they are followed by information as second highest importance and emarket with the lowest importance in the perception of the supplier. The variables in the same group relate to attitudinal e-loyalty in the same way.

The correlation test showed significant correlation between the same variables that the t-test showed had no significant difference.

The factor analysis shows that there are two components with an eigenvalue over 1. The first component is explained by satisfaction, trust, quality and commitment. The second component is explained by emarket. Information explains some variance in the second component.

The three tests have the same groupings in the results. This shows that quality, satisfaction, trust and commitment are related to each other while emarket and information do not relate to the other variables in the perception of the suppliers.

Table 6. Variables based on B2B literature pertaining to behavioral loyalty correlation

variables Mean Std. Satisfaction Trust Emarket Quality Commitment Information

Satisfaction 6.20 .81650 1 Trust 6.24 .83066 .602* 1 Emarket 3.68 1.54704 .317 -.035 1 Quality 5.76 1.36260 .045 .274 .120 1 Commitment 5.76 1.23423 .504* .465* .198 .237 1 Information 4.84 1.65025 .172 -.042 .182 .284 .482* 1

(33)

33 Table 7. Factor analysis results on variables Table 8. importance of the variable based on B2B literature pertaining to based on B2B literature pertaining to

behavioral loyalty behavioral loyalty

Tables 6 and 7 show the means and the results of the correlation test and the factor analysis of the B2B variables in their perceived importance for behavioral e-loyalty.

Table 8 shows the importance of the variables based on B2B literature for behavioral e-loyalty compared to each other in the eyes of the suppliers based on the results of the paired sample t-test (appendix A, table 18). The results are similar to the results of the t-test for attitudinal e-loyalty. Satisfaction, trust quality and commitment form the group with the highest importance in the perception of the suppliers. Information has the second highest and emarket has the lowest importance for behavioral e-loyalty in the perception of the suppliers. The variables that are grouped together based on the paired sample t-test are related to each other.

Table 6 shows that satisfaction, trust and commitment are correlated and that aside from that commitment and information are correlated. Emarket and quality show no correlation with other variables.

Table 7 shows that the variables explain behavioral e-loyalty in three components. The variation in the first component is explained mainly by satisfaction, commitment and trust. The second component is explained by trust and potential information loss while the last one is explained by quality and emarket.

(34)

34

variables based in online B2C literature

Table 9. Variables based on B2C literature pertaining to Attitudinal loyalty

(35)

35 Table 10. Factor analysis results on variables Table 11. importance of the variables based on B2C literature pertaining to based on B2C literature pertaining to Attitudinal loyalty

attitudinal loyalty

Tables 9 and 10 show, in the perception of the supplier, the means of the variables that influence attitudinal e-loyalty, they also show correlation between those variables and a factor analysis of those variables. Table 11 shows the importance of the variables based on B2C literature for attitudinal e-loyalty compared to each other in the eyes of the suppliers based on the results of the paired sample t-test (appendix A, table 19). The group with the highest perceived importance for attitudinal e-loyalty is formed by support and reliability. The second highest perceived importance is given to innovativity, volume, save time, switching costs, attachment, brand loyalty, convenience, attitude, initial contact, site and competence. The lowest perceived importance for attitudinal e-loyalty is IT.

In the following part the correlations will be mentioned, if a correlation has been mentioned between two variables that will not be mentioned again. Support correlates with innovativity,

(36)

36 brand loyalty, convenience and attitude. Switching costs correlate with innovativity, volume, save time, brand loyalty, competence and IT. Innovativity correlates with brand loyalty, attitude and IT. Volume correlates with save time, attachment site and competence. Save time correlates with brand loyalty, convenience, competence and IT. Reliability correlates with initial contact. Attachment correlates with brand loyalty, site, competence and IT. Brand loyalty correlates with attitude, competence and IT. Convenience correlates with attitude. Attitude correlates with IT. Initial contact correlates with site and competence. Site correlates with competence. Lastly competence correlates with IT.

In table 10 the first component is explained by eight of the variables. In the second component the variance is explained by three variables and the last component has no variables that significantly explain the variance.

(37)

(38)

38 *marks significant correlation

Table 13. Factor analysis results Table 14. importance of the variables on variables based on B2C literature based on B2C literature pertaining to pertaining to behavioral loyalty behavioral loyalty

(39)

39 Similar to the B2C variables that influence attitudinal e-loyalty, there is little coherence among the results of the paired sample t-test (appendix A, table 20), the correlation among the variables and the variables that explain the variance in the components. The factor analysis (appendix A, table 24) showed four components with an eigenvalue above 1, however the last two components were far lower than the first two, so close to 1 and had no significant variables in them that they are not shown in the component matrix.

Research question 3:

Do domestic and foreign managers on the B2B emarkets

differ in their opinions on importance of e-loyalty and the factors that influence

e-loyalty?

Comparison of international companies outside the Netherlands and companies from inside the Netherlands

Table 15. Outside the Netherlands compared to inside the Netherlands B2B

Attitudinal Behavioral

Variables Abroad NL t-test Abroad NL t-test

(40)

40 Table 16. Outside the Netherlands compared to inside the Netherlands B2C

Tables 15 and 16 show the means and the results of an independent sample t-test of the variables when they are split by whether or not the company is from the Netherlands. The results show no significant difference between the two. This means that on average the suppliers outside of the Netherlands perceive the variables to have the same importance for e-loyalty as the suppliers from the Netherlands perceive those variables to be.

Attitudinal Behavioral

Variables Abroad NL t-test Abroad NL t-test

(41)

41

Discussion and implications

In this paper many variables were explored for their influence on online B2B loyalty, both attitudinal in the form of repeat purchases and behavioral in the form of word of mouth recommendations. These variables were divided in two segments, the ones taken from traditional B2B supplemented with the connecting medium on the internet, and the variables that were shown to have a significant influence on online B2C loyalty.

All the variables were taken from the 25 responses to a questionnaire that I sent out to the suppliers using an emarket. The answers were all in the perception of the suppliers. The possible answers ranged from 1 to 7 on a Likert scale, where 1 meant that they believed that the variable was completely unimportant with regards to influence on either attitudinal or behavioral loyalty. The suppliers were also asked how important they perceived attitudinal and behavioral e-loyalty to be for their company.

Importance

of attitudinal and behavioral loyalty

If you look at the averages of the perceived importance of attitudinal and behavioral e-loyalty you can see that they are both close to 5 out of a possible 7. As such the suppliers believed that both forms of e-loyalty are important for their companies. Also when these perceptions were tested there was no significant difference between the two. This shows that both repeat purchases and word of mouth recommendations were considered to be equally important for suppliers in the perception of the suppliers.

Importance of

factors

to e-loyalty

(42)

42 Unlike in traditional B2B research this paper has also researched variables that were shown to have a significant influence on e-loyalty in the B2C sector. This has provided 14 variables that were either not researched or proven to have an insignificant influence on loyalty in traditional B2B research. Those variables however are perceived by the suppliers to have an impact on e-loyalty. While most of those variables appear to be lower than the variables from traditional B2B research, some have a similar average perceived influence. This shows that these variables are perceived to have an impact on attitudinal e-loyalty, however unlike with the B2B variables the high amount of B2C variables combined with a low response rate made the correlation combined with the factor analysis non interpretable. Because of this I do not know whether the B2C variables are related to each other. This also means that the groupings made in the literature review cannot be found in the results. This would indicate that when it comes to attitudinal e-loyalty there is more research needed on what variables influence it, if those variables are related to each other and if so how.

The results for behavioral e-loyalty were similar to the results for attitudinal research with a few differences. This time satisfaction was related to commitment and trust, but not to quality. The correlation test and the factor analysis did not agree completely on which variables are related to each other. They did show that satisfaction trust and commitment were related. However aside from that only commitment and information correlated, while the factor analysis indicated that trust and information were related and that emarket and quality were related. This needs more research along with how those variables are related. The results on B2C variables perceived influence on the word of mouth recommendations is similar to the results gained on their perceived influence on repeat purchases. They appear to have an influence that should not be neglected by studies. When it comes to the relation between these perceived influences the same problem arose that was present for the attitudinal e-loyalty. The low response rate along with the high amount of variables made the factor analysis non interpretable for any possible related variables. This also needs more research.

(43)

43 B2B variables satisfaction, trust, commitment and quality have the highest effect. Potential information loss has the next highest effect and emarket has the lowest effect.

For behavioral loyalty, among the B2B variables satisfaction, trust, quality and commitment have the highest effect. Potential information loss has the next highest effect and emarket has the lowest effect.

For attitudinal loyalty, among the B2C variables reliability and support service have the highest effect. IT has the lowest effect, the rest of the variables have the second highest effect. For behavioral loyalty, among the B2C variables support service, reliability, attachment and initial contact have the highest effect. Competence and save time have the second highest effect and IT has the weakest effect, while the remaining variables have the third highest effect.

More research is needed to find out why some variables have a higher effect than others.

Importance of e-loyalty based on home country of the company

(44)

44 their partner while they make use of an emarket to buy or sell goods, the same influences are important regardless of the country that the company calls home.

Implications for managers

(45)

45

Limitations and suggestions

If the B2B ecommerce were researched more, then that might have made it easier to find which variables may be overlapping and I could give more of a definitive answer to which variables influence the B2B e-loyalty. At the moment with the little research done I could perform exploratory research to find out how important the suppliers perceived the variables to be for e-loyalty.

Because the information for both attitudinal and behavioral loyalty as well as most independent variables is not available I have only been able to do exploratory research that creates propositions on which variables effect loyalty in online B2B created from the perceptions of the suppliers.

In further research I suggest approaching the buyers and doing a more in-depth study to gain data on how many purchases they made with suppliers they found with the use of an emarket, and to gain data on how many times they recommended this company to others. I think that using interviews can provide data that is not only more complete but would also allow for searching for how certain variables are related to each other.

While I aimed to get a large sample, the fact remains that I only research a single industry: construction. The results may be different in other industries. I also use an emarket that originates in the Netherlands, and while the emarket allows companies from different countries to use the emarket, most of the companies in the sample are still from the Netherlands. The response rate was also very low at a small 2.5% which gave me very little data to work with. The responses included very little companies from outside the Netherlands. Because of my low response rate I have to conclude that this study has a low representativeness for both the industry and the world at large. Further research should aim to get a higher response rate.

(46)

(47)

47

References

Anderson, E. W., & Mittal, V. (2000). Strengthening the satisfaction-profit chain. Journal of

Service research, 3(2), 107-120.

Anderson, R. E., & Srinivasan, S. S. (2003). E‐satisfaction and e‐loyalty: a contingency framework. Psychology & marketing,20(2), 123-138.

Baker, M. J., Buttery, E. A., & Richter-Buttery, E. M. (1998). Relationship marketing in three dimensions.Journal of Interactive Marketing,12(4), 47-62.

Bakos, J. Y. (1997). Reducing buyer search costs: Implications for electronic marketplaces.Management science,43(12), 1676-1692.

Balabanis, G., Reynolds, N., & Simintiras, A. (2006). Bases of e-store loyalty: Perceived switching barriers and satisfaction.Journal of Business Research,59(2), 214-224.

Bansal, H. S., Irving, P. G., & Taylor, S. F. (2004). A three-component model of customer to service providers. Journal of the Academy of marketing Science,32(3), 234-250.

Berry, L. L. (1995). Relationship marketing of services—growing interest, emerging perspectives. Journal of the Academy of marketing science, 23(4), 236-245.

Carter, M., Wright, R., Thatcher, J. B., & Klein, R. (2014). Understanding online customers’ ties to merchants: the moderating influence of trust on the relationship between switching costs and e-loyalty. European Journal of Information Systems,23(2), 185-204.

Čater, T., & Čater, B. (2010). Product and relationship quality influence on customer commitment and loyalty in B2B manufacturing relationships. Industrial Marketing

Management,39(8), 1321-1333.

Cater, B., & Zabkar, V. (2009). Antecedents and consequences of commitment in marketing research services: The client's perspective. Industrial Marketing Management,38(7), 785-797.

(48)

48 Choi, D. H., Kim, C. M., Kim, S., & Kim, S. H. (2006). Customer loyalty and disloyalty in internet retail stores: its antecedents and its effect on customer price sensitivity. International Journal of Management,23(4), 925.

Davis-Sramek, B., Droge, C., Mentzer, J. T., & Myers, M. B. (2009). Creating commitment and loyalty behavior among retailers: what are the roles of service quality and satisfaction?.

Journal of the Academy of Marketing Science, 37(4), 440-454.

De Ruyter, K., Moorman, L., & Lemmink, J. (2001). Antecedents of commitment and trust in customer–supplier relationships in high technology markets. Industrial Marketing

Management,30(3), 271-286.

Devaraj, S., Fan, M., & Kohli, R. (2003). E-loyalty: elusive ideal or competitive edge?.Communications of the ACM,46(9), 184-191.

Dick, A. S., & Basu, K. (1994). Customer loyalty: toward an integrated conceptual framework.

Journal of the academy of marketing science, 22(2), 99-113.

Direcortory of emarket services, accessed on 11-06-2015

http://www.emarketservices.com/start/eMarket-Directory/index.html#FromBanner

Hande, P. V., Ghosh, D., & Govil, A. (2015). A Comparative Study on Factors Shaping Buying Behaviour on B2B and B2C E-Commerce Platforms in India. Journal of Marketing and

Consumer Research, 8, 53-58.

Health, R. P. (1997) Loyalty for sale: Everybody’s doing frequency marketing-But only a few companies are doing it well. Marketing Tools. Cowles Business Media Inc., 4, 6, 40.

Horppu, M., Kuivalainen, O., Tarkiainen, A., & Ellonen, H. K. (2008). Online satisfaction, trust and loyalty, and the impact of the offline parent brand. Journal of Product & Brand

Management,17(6), 403-413.

(49)

49 Janita, M. S., & Miranda, F. J. (2013). The antecedents of client loyalty in business-to-business (B2B) electronic marketplaces. Industrial marketing management,42(5), 814-823.

Jones, M. A., Mothersbaugh, D. L., & Beatty, S. E. (2000). Switching barriers and repurchase intentions in services.Journal of retailing,76(2), 259-274

Jones, M. A., Mothersbaugh, D. L., & Beatty, S. E. (2002). Why customers stay: measuring the underlying dimensions of services switching costs and managing their differential strategic outcomes.Journal of business research,55(6), 441-450.

Kassim, N. M., & Abdullah, N. A. (2008). Customer loyalty in e‐commerce settings: an empirical study. Electronic Markets,18(3), 275-290.

Kassim, N., & Abdullah, N. A. (2010). The effect of perceived service quality dimensions on customer satisfaction, trust, and loyalty in e-commerce settings: a cross cultural analysis.Asia

Pacific Journal of Marketing and Logistics,22(3), 351-371.

Kheng, L. L., Mahamad, O., Ramayah, T., & Mosahab, R. (2010). The impact of service quality on customer loyalty: A study of banks in Penang, Malaysia. International Journal of Marketing

Studies,2(2), p57.

Kumar, V., Bohling, T. R., & Ladda, R. N. (2003). Antecedents and consequences of relationship intention: Implications for transaction and relationship marketing. Industrial Marketing

Management,32(8), 667-676

Lam, S. Y., Shankar, V., Erramilli, M. K., & Murthy, B. (2004). Customer value, satisfaction, loyalty, and switching costs: an illustration from a business-to-business service context.

Journal of the academy of marketing science, 32(3), 293-311.

Liang, C. J., Chen, H. J., & Wang, W. H. (2008). Does online relationship marketing enhance customer retention and cross-buying?. The service industries journal,28(6), 769-787.

Lim, K. H., Leung, K., Sia, C. L., & Lee, M. K. (2004). Is eCommerce boundary-less? Effects of individualism–collectivism and uncertainty avoidance on Internet shopping. Journal of

(50)

50 Lindgaard, G., Fernandes, G., Dudek, C., & Brown, J. (2006). Attention web designers: You have 50 milliseconds to make a good first impression!.Behaviour & information technology, 25(2),

115-126.

Lucking-Reiley, D., & Spulber, D. F. (2001). Business-to-business electronic commerce. Journal of Economic Perspectives, 55-68.

Molinari, L. K., Abratt, R., & Dion, P. (2008). Satisfaction, quality and value and effects on repurchase and positive word-of-mouth behavioral intentions in a B2B services context.

Journal of Services Marketing, 22(5), 363-373.

Morgan, R. M., & Hunt, S. D. (1994). The commitment-trust theory of relationship marketing.the journal of marketing, 20-38.

Newell, F. (1997). The new rules of marketing: How to use one-to-one relationship marketing to be the leader in your industry. McGraw-Hills Companies Inc., New York.

Rao, S. S., Truong, D., Senecal, S., & Le, T. T. (2007). How buyers' expected benefits, perceived risks, and e-business readiness influence their e-marketplace usage. Industrial Marketing Management,36(8), 1035-1045.

Rauyruen, P., & Miller, K. E. (2007). Relationship quality as a predictor of B2B customer loyalty. Journal of business research, 60(1), 21-31.

Russell-Bennett, R., McColl-Kennedy, J. R., & Coote, L. V. (2007). Involvement, satisfaction, and brand loyalty in a small business services setting. Journal of Business Research, 60(12), 1253-1260.

Schefter, P., & Reichheld, F. (2000). E-loyalty: your secret weapon on the Web. Harvard Business Review, 78(4), 105-113.

Soltani, I., & Gharbi, J. E. (2008). Determinants and Consequences of the Website Perceived Value. Journal of Internet Banking and Commerce, 13(1).

(51)

51 Storbacka, K., Strandvik, T., & Grönroos, C. (1994). Managing customer relationships for profit: the dynamics of relationship quality. International journal of service industry

management,5(5), 21-38.

Toufaily, E., Ricard, L., & Perrien, J. (2013). Customer loyalty to a commercial website: Descriptive meta-analysis of the empirical literature and proposal of an integrative model. Journal of Business Research, 66(9), 1436-1447.

Ulaga, W. (2003). Capturing value creation in business relationships: A customer perspective. Industrial Marketing Management, 32(8), 677−693.

Wang, H. C., Pallister, J. G., & Foxall, G. R. (2006). Innovativeness and involvement as determinants of website loyalty: II. Determinants of consumer loyalty in B2C e-commerce.Technovation,26(12), 1366-1373.

Wu, S. (2015) US B2B eCommerce Will Be Twice The Size Of B2C eCommerce By 2020 https://www.forrester.com/US+B2B+eCommerce+Will+Be+Twice+The+Size+Of+B2C+eCom merce+By+2020/fulltext/-/E-RES122366 accessed on 19-05-2015

Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence. The Journal of marketing, 2-22.

(52)

52

Appendix A figures and tables

Table 17. Paired sample t-test B2B variables on attitudinal loyalty

(53)

53

(54)

54

(55)

55

Table 21. Factor analysis B2B variables on attitudinal loyalty

(56)

56

(57)

57

Table 24. Factor analysis B2C variables on behavioral loyalty

(58)

58

(59)

(60)

(61)

Loyalty in B2B relationship using emarkets