Satisfaction on Small Retailer-Supplier Relationships: a Case of a Telecommunication Company in Portugal

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MASTER

SERVICES MANAGEMENT

Satisfaction on Small Retailer–Supplier

Relationships: a Case of a

Telecommunication Company in

Portugal

Cátia Filipa Pereira da Silva

M

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SATISFACTION ON SMALL RETAILER–SUPPLIER RELATIONSHIPS:

A CASE OF A TELECOMMUNICATION COMPANY IN PORTUGAL

Cátia Filipa Pereira da Silva

Dissertation

Master in Services Management

Supervised by

Rui Alberto Ferreira dos Santos Alves

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Abstract

Purpose: The purpose of this study is to determine the antecedents of Satisfaction, both Economic and Non-Economic, in small retailer–supplier relationship, to find how the Economic and Non-Economic Satisfaction of small retailers relates with their Repurchase Intent, to understand if the antecedents of Satisfaction of small retailers have interrelationships, and to find if the two dimensions of Satisfaction of small retailers are related in the Portuguese B2B telecommunication environment.

Design/methodology/approach: A quantitative approach was carried out and targeted small retailers in the Portuguese telecommunication sector. The sample comprised 77 business owners who are usually the purchasing deciders in these companies. Data was collected through a survey and then analysed by Linear Regressions to test the hypotheses. Findings: The results indicate that the Trust small retailers have on their supplier positively influence their Non-economic Satisfaction. However, only the Economic Satisfaction of small retailers has a positive influence on their Repurchase Intention. Additionally, the results show that the degree of Communication small retailers have with their supplier is positively correlated with their Trust, and that Trust is positively correlated with their Commitment towards the relationship. Moreover, the findings show that the Economic Satisfaction of small retailers has a positive link with their Non-economic Satisfaction and their Repurchase Intent.

Originality/value: The results of this study contribute to the literature by filling out three gaps: the lack of research on Satisfaction in B2B relationships, Satisfaction as a multidimensional construct, and channel research on small retailers.

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Resumo

Objetivo: O objetivo deste estudo é (1) determinar os antecedentes da Satisfação, tanto a Económica quanto a Não Económica, na relação pequeno retalhista-fornecedor, (2) perceber como a Satisfação Económica e Não Económica dos pequenos retalhistas se relaciona com sua Intenção de Recompra, (3) entender se os antecedentes de Satisfação dos pequenos retalhistas têm relações entre si e (4) averiguar se as duas dimensões da Satisfação dos pequenos retalhistas se relacionam no ambiente português de telecomunicações B2B. Design/Metodologia/Abordagem: Foi usada uma abordagem quantitativa e foi dirigida a pequenos retalhistas do sector das telecomunicações em Portugal. A amostra é constituída por 77 donos de negócio que são habitualmente quem, nestas empresas, toma a decisão de comprar. Os dados foram recolhidos através de um questionário e, em seguida, analisados através de diversas Regressões Lineares para testar as hipóteses do estudo. Resultados: Os resultados indicam que a Confiança que os pequenos retalhistas têm nos seus fornecedores influencia positivamente sua Satisfação Não Económica. No entanto, apenas a Satisfação Económica do pequeno retalhista influencia positivamente a sua Intenção de Recompra. Além disso, os resultados mostram que o grau de Comunicação dos pequenos retalhistas com o seu fornecedor está positivamente relacionado com sua Confiança e que a Confiança está positivamente relacionada com o seu Compromisso com o relacionamento. Além disso, os resultados mostram que a Satisfação Económica dos pequenos retalhistas tem um vínculo positivo com sua Satisfação Não Económica e sua Intenção de Recompra.

Originalidade/valor: Os resultados deste estudo contribuem para a literatura ao preencherem três lacunas: a escassez de estudos sobre a Satisfação nas relações B2B, sobre

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iii a Satisfação como constructo multidimensional e sobre pequenos retalhistas como canais de distribuição.

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4.2.1. What are the antecedents of Satisfaction, both Economic and Non-Economic, of small retailers with their suppliers in the telecommunication sector in Portugal? 28 4.2.2. Does small retailers’ Economic Satisfaction and Non-Economic Satisfaction with their suppliers influence their Repurchase Intent? ... 30

4.2.3. Are there interrelations between the antecedents of Satisfaction? ... 31

4.2.4. Are the two dimensions of Satisfaction, Economic and Non-economic, related? 33 5. Final considerations ... 34

5.1. Discussion ... 34

5.2. Limitations and future research ... 37

5.3. Theoretical implications ... 38

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vi

6. References ... 41

Annexes ... 50

Annex I - Measures ... 50

Annex II – Measures validation ... 52

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List of tables

Table 1. Research papers on B2B relationships ... 10

Table 2. Variables measures ... 20

Table 3. Reliability of scales ... 23

Table 4. Economic Satisfaction Multiple Linear Regression results ... 28

Table 5. Non-economic Satisfaction Multiple Linear Regression results ... 29

Table 6. Repurchase Intent Multiple Linear Regression results ... 30

Table 7. Trust Simple Linear Regression results ... 31

Table 8. Commitment Simple Linear Regression results ... 32

Table 9. Economic Satisfaction Simple Linear Regression results ... 33

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List of figures

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1. Introduction

In the telecommunication sector in Portugal, there are three major players that retailers can choose as suppliers. In this context of intense competition, the creation of barriers can be achieved by establishing and nurturing long-term business relationships in suppliers’ distribution channel (Venetis & Ghauri, 2004; Viio & Grönroos, 2014).

By focusing their strategies in order to elevate their partners’ relationship Satisfaction, suppliers can build long-term relationships (Ruiz-Martínez, Frasquet, & Gil-Saura, 2019). In the literature, there is consensus that building long‐term relationships with customers is the essence of business‐to‐business marketing (Hutt & Speh, 2004) and, for that reason, companies are increasingly moving from transactional exchanges to relational exchanges (Nguyen et al., 2007).

This dissertation has the objective of (1) determining the antecedents of Satisfaction, both Economic and Non-Economic, in supplier-small retailer relationship, (2) finding how the Economic and Non-Economic Satisfaction of small retailers relates with their Repurchase Intent, (3) understanding if the antecedents of Satisfaction of small retailers have interrelationships and (4) finding if the two dimensions of Satisfaction of small retailers are related in the Portuguese B2B telecommunication environment.

While there is an extensive research on the factors that affect Satisfaction in the business-to-consumer (B2C) market, less is known about the factors influencing the Satisfaction in the business-to-business (B2B) market (Cassia et al., 2017), such as supplier-retailer, manufacturer-distributor or supplier-distributor relationships. Furthermore, the existing literature doesn’t pay too much attention to small retailers, which typically have business

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2 particularities that could reflect in different results regarding the factors influencing the Satisfaction with their supplier. There is a gap in channel research when it comes to the small retailing area and, particularly, in the buyer behaviour in the retailer–supplier relationship (up-stream behaviour) (Runyan & Droge, 2008; Ferro, Padin, Svensson, & Payan, 2016).

Another concern found in the literature is the lack of congruence on the measurement of Satisfaction (Mpinganjira, Roberts-Lombard & Svensson, 2017), because some researches measure this construct using social aspects of business relationships while others using only the Economic benefits of the relationship.

The present study addresses these three gaps, contributing to a richer understanding of retailers’ perspective and, in sum, addresses the following research questions:

1) Which factors influence the Satisfaction, both Economic and Non-Economic, of small retailers with their suppliers in the telecommunication sector in Portugal? 2) Does small retailers’ Economic Satisfaction and Non-Economic Satisfaction with

their suppliers influence their Repurchase Intent?

3) Are there interrelations between the antecedents of Satisfaction?

4) Are the two dimensions of Satisfaction, Economic and Non-economic, related? This dissertation aims to evaluate the relationship between Trust, Commitment, Communication, Economic Satisfaction, Non-Economic Satisfaction and Repurchase Intent using a sample of small retailers in telecommunication sector in Portugal through an adaptation of the conceptual model developed by del Bosque Rodríguez, Agudo & San Martín Gutiérrez (2006).

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3 To achieve the goals mentioned above, the present study used a quantitative approach and carried out a survey that targeted small retailers of the Portuguese telecommunication sector.

This study is currently structured as follows: after this introduction, Section 2 includes the relevant literature on the topic of Satisfaction and Satisfaction in the B2B relationships. Section 3 includes the conceptual model and its hypotheses supported by the review of the literature of the antecedents of Satisfaction and the Repurchase Intent as a consequence of Satisfaction. Section 3 also gives an overview of the methodology that was used. The results of the hypothesis tests are in Section 4. Finally, Section 5 includes the discussion of the results as well as the study limitations, future research, managerial contributions and theorical contributions.

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2. Literature review

This section presents a contextualization of the B2B relationships since it’s important to study the more relevant findings of previous research. It starts with the definition of small retailers, followed by the review of the construct of Satisfaction. Then, the review is focused on specifically Satisfaction on B2B context. At the end of this section the dimensions of Satisfaction are analysed, as well as its antecedents and the Repurchase Intent, as its outcome.

2.1. Defining small retailers

This research context is small retailers that are considered micro enterprises. Micro enterprises are included in the designation of SMEs by the European Union. According to their staff headcount, turnover and total balance sheet, SMEs are subdivided in three categories (micro, small and medium-sized). The European Commission define micro enterprises as the businesses which employ fewer than 10 persons and their annual turnover or annual balance sheet total is less than €2 Million (Commission Recommendation 2003/361/EC).

SMEs form 99% of companies in the European Union, what makes them really important for the European economy. Nevertheless, small retailers, due to their size, face different business challenges when comparing to firms with a bigger dimension. The European Union even created policies specifically targeting SMEs with the aim of ensuring that Europe is an attractive place to set up a company and do business and that its policies are small businesses friendly. However, research on small retailers is often ignored in larger

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5 contexts (Runyan & Droge, 2008). In the recent literature, only a study on both aspects of Economic and Non-Economic Satisfaction was found in the SME context. That study was developed by (Ferro, Padin, Svensson, & Payan, 2016). The author that also highlighted this gap in the literature.

2.2. Satisfaction

In the marketing literature, the definition of Satisfaction is focused on the degree of fulfilment of the expectations of the parties involved in an exchange relationship (Anderson and Naurus, 1984; El-Ansary & Robicheaux, 1976; Han, Kim, & Srivastava, 1998). That is, Satisfaction is considered to be a measure of the customer experience, after a purchase (Oliver, 1980). In sum, when a customer makes a purchase, he goes through a cognitive process where he compares the benefits and sacrifices he previously expected with the ones he actually got. Satisfaction is the result of this evaluation.

Satisfaction plays an important role in business-to-business (B2B) relationships (Graca et al., 2015), since it is a key factor to establish long-term relationships with customers and, consequently, strengthen their Repurchase Intentions (Lee, Jeong, Tark Lee & Jin Sung, 2008). However, the literature has way more focus on the B2C context than in the B2B context (Cassia et al., 2017).

Ruíz-Martinez et al. (2019) pointed out the need to provide better empirical evidence about the antecedents of Satisfaction and its influence on Repurchase Intent in the B2B context, as this study will do. As the author refers in his recent research, the big discrepancy between the number of studies on the B2C and B2B context reinforces the limitation in content and scope in the last one (Watson, Beck, Henderson & Palmatier, 2015). This

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6 study addresses the topic of customer Satisfaction in the B2B telecommunication environment and attempts to fill the existing gaps in the literature.

2.3. Satisfaction on business-to-business markets

Creating and nurturing long-term business relationships has benefits to both parties involved (Bolton et al., 2000). For instance, Venetis and Chauri (2004) recognize those beneficial effects such as, from the provider’s point of view, “the creation of barriers against competition, the decrease of price competition and the generation of more revenue per customer with decreasing costs due to repeat purchase” and Andaleeb (1996) added the role of this relationships on the access to markets.

When reviewing the business marketing literature, there are two types of relationships that we can identify: the transactional relationships, when customers make purchases mainly on the basis of price and switch suppliers frequently (Ghauri, 1999), and the relational exchange relationships, the more desirable ones, when a long orientation is developed between the two parties and means more than a mere sequence of transactions (Dwyer, Oh and Schurr, 1987). Several researchers such as Dwyer (1980), Robicheaux and El-Ansary (1985) and Mpinganjira, Bogaards, Svensson & Mysen (2014) identified Satisfaction as a fundamental component of exchange relationships and its longevity. Establishing and maintaining good business relationships is even more important in B2B contexts than in B2C markets due to the large orders often associated with such exchanges (Mpinganjira et al., 2017),

In the literature, Satisfaction is a fundamental variable in models of channel member behaviour (Michie & Sibley, 1985). In the B2B relationships, Satisfaction can be viewed as

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7 “an affective state resulting from the appraisal of all aspects of a firm's working relationship with another firm” (Anderson & Narus, 1984). Thus, firms that perceived that the benefits of the relationship are equal or higher than what was initially expected, are more likely to maintain and expand the relationship (Thibaut & Kelley, 1959).

Del Bosque Rodríguez et al. (2006) points out that one of the concerns found in the literature is how Satisfaction in the B2B context is measured. Mpinganjira et al. (2017) in their literature review also referred how incongruent the measurement of Satisfaction is. There are studies that measure Satisfaction by evaluating only social aspects of business relationships while others on the Economic benefits of the relationship.

The next section includes a review on the dimensions of Satisfaction.

2.3.1. Dimensions of Satisfaction

Geyskens and Steenkamp (2000), Palmatier (2008), Wood et al. (2014) defend that Satisfaction isn’t a unitary construct and two types of Satisfaction in B2B relationships can be distinguished, the Economic and the Non-Economic Satisfaction:

a) Economic Satisfaction is defined as “a channel member’s evaluation of the Economic outcomes that flow from the relationship with its partners such as sales volume, margins, and discounts” (Geyskens and Steenkamp, 2000);

b) Non-Economic Satisfaction is defined as “as a channel member’s evaluation of the psychosocial aspects of its relationship, in that interactions with the exchange partner are fulfilling, gratifying, and facile” (Geyskens and Steenkamp, 2000). In sum, the authors described the Economic Satisfaction as a construct more focused on objective and tangible benefits from the relationship, while Non-Economic Satisfaction is

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8 more oriented to intangible aspects of the relationship. Geyskens & Steenkamp (2000) attribute the importance of this distinction to the possibility of the feeling of Satisfaction not being achieved because of one of the dimensions not corresponding to the expectations of one of the channel’s member.

Recent research on channel relationships addresses Satisfaction as a multidimensional construct. However, there is still a gap in the literature when it comes to this subject. The only studies found, at this day, considering directly Economic and Non-Economic Satisfaction, were the ones developed by el Bosque Rodriguez et al. (2006), Nyaga, Whipple, & Lynch (2010), Rutherford (2012), Wood, Johnson, Boles, & Barksdale, 2014), Ferro et al. (2016), Mpinganjira et al. (2017) and Høgevold et al. (2020).

2.3.2. Antecedents of Satisfaction

Satisfaction has been considered as a result derived from relationships between buyers and sellers (Anderson & Narus, 1984; Smith & Barclay, 1997), that is intensified if the firm perceives its impact (for instances in profits) (Ruekert & Churchill, 1984).

Relationship Satisfaction is considered one of the central constructs of relationship marketing due to its importance in understanding the development and preservation of business-to-business relationships and the studies involving this concept analyse its antecedents as well as its consequences.

Marketing research on the B2C context is more consistent when it comes to antecedents of Satisfaction, mostly when comparing to the B2B setting (Janita & Miranda, 2013). The literature studying business-to-business relationships has demonstrated interest in identifying the factors that influence positively long-term successful relationships (Ruiz-Martínez, 2019). As part of the study of relationship Satisfaction, the most relevant factors

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9 on predicting Satisfaction found in empirical papers on business-to-business relationships are summarized in Table 1. In other words, the papers in Table 1 have Satisfaction as final dependent variable.

2.3.3. Outcomes of Satisfaction

When it comes to the consequences of relationship Satisfaction, the literature highlights Repurchase Intent as a positive outcome (Lee et al., 2008; Russo, Confente, Gligor, & Cobelli, 2017). This is because a loyal customer develops behaviours that reflect the motivation to maintain the relationship (Cassia et al., 2017), which means they are willing to purchase again.

Based on the literature review mentioned in this chapter, a theoretical model adaptation (Figure 1) from a model developed by del Bosque Rodríguez et. al (2006) is proposed in the next chapter for testing three of the antecedents of Satisfaction, both Economic and Non-Economic, found in literature (Trust, Commitment and Communication) and an outcome of Satisfaction (Repurchase Intent) applied in the retailer-supplier relationship in the telecommunication sector in Portugal.

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Antecedent Context Authors

Trust

Agency-client Venetis & Ghauri (2004)

Supplier-distributor Payan & McFarland (2005)

Supplier-retailer Terawatanavong, Whitwell & Widing (2007)

Manufacturer-retailer Del Bosque Rodríguez, Agudo & San Martín Gutiérrez (2006)

Manufacturer-supplier Ferro, Padin, Svensson & Payan (2016)

Supplier-buyer Roberts-Lombard, Mpinganjira & Svensson

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Buyer-supplier Mpinganjira, Roberts-Lombard & Svensson

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Manufacturer-distributor

Vázquez-Casielles, Iglesias & Varela-Neira (2017)

Manufacturer–supplier Mungra & Yadav (2019)

Seller-buyer Høgevold, Svensson & Otero-Neira (2020)

Manufacturer-supplier Sales-Vivó, Gil-Saura & Gallarza (2020)

Commitment

Manufacturer-retailer del Bosque Rodriguéz et al. (2006)

Supplier-retailer Terawatanavong et al. (2007)

Supplier-buyer Roberts-Lombard et al. (2017)

Manufacturer-supplier Ferro, Padin, Svensson & Payan (2016)

Buyer-supplier Mpinganjira et al. (2017)

Manufacturer–supplier Mungra & Yadav (2019)

Seller-buyer Høgevold, Svensson & Otero-Neira (2020)

Manufacturer-supplier Sales-Vivó, Gil-Saura & Gallarza (2020)

Communication

Supplier-dealer Jonsson & Zineldin (2003)

Manufacturer-distributor del Bosque Rodriguéz et al. (2006)

Buyer–supplier Graca, Barry & Doney (2015)

Buyer-supplier Glas (2018)

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3. Methodology

The key construct in this study is relationship Satisfaction.

3.1. Conceptual model and hypothesis

Figure 1. Conceptual model and hypothesis

The diagram above shows the theoretical model of this study and summarizes the research hypotheses. The model is an adaptation of the conceptual model developed by del Bosque Rodríguez et. al (2006). The adaption was based on the literature review included on the previous chapter, as well as, the literature review, that is included on this chapter, of the relationship between each independent factor (Communication, Trust and Commitment) with Satisfaction, between Satisfaction and Repurchase Intent, between the intercorrelations of Communication, Trust and Commitment and between Economic and Non-Economic Satisfaction, which allowed the hypothesis to be formulated.

H1: The greater the supplier’s Communication, the greater the Economic Satisfaction of the small retailer.

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12 H2: The greater the supplier’s Communication, the greater the Non-Economic Satisfaction of the small retailer.

H3: The greater the small retailer’s Trust in in the supplier, the greater his Non-Economic Satisfaction.

H4: The greater the supplier’s Commitment, the greater the Economic Satisfaction of the small retailer.

H5: The greater the small retailer’s Commitment in in the supplier, the greater his Non-Economic Satisfaction.

H6: The greater the small retailer’s Economic Satisfaction, the greater his Repurchase Intent. H7: The greater the small retailer’s Non-Economic Satisfaction, the greater his Repurchase Intent. H8: The greater the supplier’s Communication, the greater the small retailer’s Trust in in the supplier.

H9: The greater the small retailer’s Trust in in the supplier, the greater the small retailer’s Commitment to the supplier.

H10: The greater the small retailer’s Economic Satisfaction, the greater his Non-Economic Satisfaction.

3.1.1. Communication and Satisfaction in B2B relationships

Communication is a key factor of all business relationships (Hänninen & Karjaluoto, 2017). Anderson & Narus (1990) define Communication as “the formal as well as informal sharing of meaningful and timely information between firms”. Previous research has recognized that Communication is one of the key factors in the development of long-term relationships (Gilaninia et al., 2011) because it allows firms to keep in touch with valued customers, to provide timely and Trustworthy information on service and service changes and to communicate proactively if, for instances, a delivery problem occurs. As such, exchange of information can generate an improvement in the development of functions within the relationship (Guetzkow, 1965).

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13 The positive link between Satisfaction and Communication is referred in the literature (Cannon & Perreault, 1999; Mohr & Sohi, 1995).The research of del Bosque Rodríguez et al. (2006) concluded that Communication is an important factor in the distributor’s Economic Satisfaction process, but it doesn’t have a direct effect on Non-Economic Satisfaction.

Thus, it is argued that Communication can be perceived as an antecedent of Satisfaction (Schuler, 1979) and the ensuing hypothesis is formulated:

H1: The greater the supplier’s Communication, the greater the Economic Satisfaction of the small retailer.

H2: The greater the supplier’s Communication, the greater the Non-Economic Satisfaction of the small retailer.

3.1.2. Trust and Satisfaction in B2B relationships

Ganesan (1994) defends that long‐term orientation is influenced by the extent to which customers and vendors Trust their “channel partners”. Trust in manufacturer‐distributor is defined as the belief of a firm that another company will perform actions that will result in positive outcomes and the other company will not take unexpected actions that will consequent in negative outcomes for the firm (Anderson & Narus, 1990). Therefore, suppliers who are perceived as being concerned with positive customer outcomes will be more Trusted than suppliers who are perceived as being interested only in their own welfare (Chumpitaz Caceres & Paparoidamis, 2007).

When it comes to the positive link between Trust and Satisfaction, there is consensus in the marketing literature. However, some authors defend that Trust is an antecedent of Satisfaction (Andaleeb, 1996; Siguaw et al. 1998; Farrelly & Quester, 2005) while others argue that Satisfaction is an antecedent of Trust (Ganesan, 1994; Selnes,1998; Ha, Lee, &

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14 Janda, 2016). In this study, it will be considered that the retailer's Trust in the supplier is an antecedent of Satisfaction in relationships between the partners.

The literature on the B2B context addresses the relations among Trust and Non-Economic Satisfaction (del Bosque Rodríguez et al., 2006; Ferro et al., 2016). When the retailer Trusts his supplier, he will feel secure due to the belief in the supplier’s intentions to generate positive outcomes and this evaluation will make him more satisfied with the relationship (Andaleeb, 1996). For that reason, the ensuing hypothesis is formulated:

H3: The greater the small retailer’s Trust in in the supplier, the greater his Non-Economic Satisfaction.

3.1.3. Commitment and Satisfaction in B2B relationships

Commitment has long been a key construct in the relationship marketing literature (Parasuraman, Berry & Zeithaml, 1991; Wu, Zhou & Wu, 2012). Commitment has a special role in the enhancement of exchange relationships, because “when trading partners are committed to each other they are more willing to cooperate and comply with the others’ requests, share information and engage in joint problem solving” (Vasudevan, Gaur & Shinde, 2006). Sung & Choi (2010) describe Commitment as a partner’s willingness to establish a long-term relationship with another partner and to remain with that link, inclusive of an emotion of psychological attachment. Also, Tellefsen (2002) defends that that willingness means that the buyer will perceive that it is worth investing a special effort to maintain the relationship indefinitely. On the other hand, Human & Naudé (2014) argue that the level of Commitment of a customer will depend on his perception of the amount of effort that the seller also puts into the relationship.

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15 The literature supports the positive link between Commitment and Satisfaction. But some authors defend that Commitment is a direct outcome of Satisfaction to the relationship (Geyskens et al., 1999; Moliner, Sánchez, Rodrìguez & Callerisa, 2007; Wood et al., 2014; Espejel, Fandos & Flavián (2011); Mohr & Spekman (1994) while others argue that Commitment is an antecedent of Satisfaction (Anderson & Narus, 1990; Wong & Zhou, 2006; Ruekert & Churchill (1984), Svensson Mysen & Payan, 2010). The literature on the B2B context, as well as Trust, addresses the relations among Commitment and Economic and Non-Economic Satisfaction (Geyskens et al., 1999; Farrelly & Quester, 2005; del Bosque Rodríguez et al., 2006; Ferro et al., 2016). However, some studies, such as the one developed by del Bosque Rodríguez et al. (2006), show that Commitment only leads to Economic Satisfaction.

In this research, it is considered that if the retailer perceives that the supplier is committed, he will strive to work in the relationship. Therefore, Commitment can be perceived as an antecedent of Satisfaction in a retailer–supplier relationship and the following hypothesis can be formulated:

H4: The greater the supplier’s Commitment, the greater the Economic Satisfaction of the small retailer.

H5: The greater the small retailer’s Commitment in in the supplier, the greater his Non-Economic Satisfaction.

3.1.4. Repurchase Intent as a result of Satisfaction in B2B relationships Customer loyalty is a key factor in the success of a B2B relationship (Kumar, Pozza, I.D. & Ganesh, 2013) and can be defined as a “deeply held Commitment to rebuy or repatronize a preferred product/service consistently in the future, thereby causing repetitive same-brand or same brand-set purchasing, despite situational influences and marketing efforts having

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16 the potential to cause switching behaviour” (Oliver, 1999). That is, customer loyalty is related with relationship Commitment. That’s why the literature suggests that loyalty is a multidimensional construct that combines attitudinal and behavioural loyalty (Day, 1969). In the B2B context, the attitudinal loyalty refers to affective Commitment and the behavioural loyalty refers to the intention of repurchase (Blocker, Flint, Myers & Slater, 2011).

Companies work for the achievement of customer Satisfaction due to its outcomes, such as Repurchase Intent (Anderson & Mittal, 2000). In the literature, there are numerous studies linking positively Repurchase Intent and customer Satisfaction (Woodruff, 1997; Lam, Shankar, Erramilli & Murthy, 2004; Vos et al., 2016). Glavee-Geo (2019) also stated that the propensity to continue the relationship is affected by the congruence between the levels of Economic and Non-Economic Satisfaction.

In this study, Satisfaction will be tested as an antecedent of the behavioural loyalty (Repurchase Intent) and, based on the above, the ensuing hypothesis is formulated:

H6: The greater the small retailer’s Economic Satisfaction, the greater his intention to repurchase. H7: The greater the small retailer’s Non-Economic Satisfaction, the greater his intention to repurchase.

3.1.5. Communication and Trust in B2B relationships

As mentioned above, Communication and Trust are key factors in the success of business relationships and, in the literature, both constructs are seen as antecedents of satisfaction. However, there is also a relationship between these two constructs. Many authors argue that Communication is a predictor of Trust (Anderson & Narus, 1990; Morgan & Hunt, 1994; Selnes, 1998; del Bosque Rodríguez et al., 2006). This link is explained by the fact

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17 that, when the supplier strives to give useful information to the retailer, the retailer will view his suppliers as competent.

Based on the above, the ensuing hypothesis is formulated:

H8: The greater the supplier’s Communication, the greater the small retailer’s Trust in in the supplier.

3.1.6. Trust and Commitment in B2B relationships

There is strong evidence in the literature that Trust is an antecedent of Commitment (Morgan & Hunt, 1994; del Bosque Rodríguez et al., 2006; Human & Naudé, 2014; Hashim & Tan, 2015; Mpinganjira et al., 2017). While Trust is associated with the social interactions between the parties involved, Commitment is more related with the plan of continuing the relationship (Ferro et al., 2016) and that’s the reason why the literature points Trust as the predictor construct. Buyers will believe that their supplier will not have opportunistic behaviours towards them if they trust them and “where this trust exists, it helps to reduce levels of perceived vulnerability to risks and creates an environment where firms can invest in building long-term relationships” (Mpinganjira et al., 2017).

Based on the above, the ensuing hypothesis is formulated:

H9: The greater the small retailer’s Trust in in the supplier, the greater the small retailer’s Commitment to the supplier.

3.1.7. Economic Satisfaction and Non-Economic Satisfaction in B2B relationships

The marketing literature didn’t pay too much attention to the relationship between the two dimensions of satisfaction (del Bosque Rodriguez et al., 2006) and the existing one is not

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18 coherent. Some authors argue that Non-economic Satisfaction is an antecedent of Economic Satisfaction (Farrelly and Quester, 2005). Contrarily, some authors state that Economic Satisfaction is the predictor construct (del Bosque Rodriguez et al., 2006; Rutherford, 2012; Mpinganjira et al., 2017), because “when there is a high level of economic satisfaction, the members will be willing to respond to a particular problematic situation positively and constructively, thereby increasing their social satisfaction with the relationship” (del Bosque Rodriguez et al., 2006). Based on that, in this study, Economic Satisfaction will be tested as an antecedent of Non-Economic Satisfaction and the ensuing hypothesis is formulated:

H10: The greater the small retailer’s Economic Satisfaction, the greater his Non-Economic Satisfaction.

3.2. Methodological approach and procedures of data collection

To reach the research objectives, the present study used a quantitative method (Cooper & Schindler, 2008). Data was collected through a survey targeting the owners of small retail businesses in the Portuguese telecommunication sector. In similar studies in the literature, a survey methodology was chosen. This choice is due to the nature of relationship Satisfaction and other interpersonal variables – they “develop over long periods of time and are very difficult to manipulate and/ or observe in experimental test situations” (Abdul-Muhmin, A. G. 2005).

Stores of the businesses were visited the survey was personally handed out to its owners, and later pick-up. The data collection started out on the 21st_{of January of 2020 and ended}

on the 15th_{March of 2020, earlier than expected due to a coronavirus outbreak. This}

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19 of 2020 and the Portuguese government declared the state of emergency on the 22th of March of 2020. From that day on, all stores except groceries and pharmacies were forced to close, as one of the measures of the state of emergency (Decree-Law no 2-A/2020 of 20th_{of March of 2020 by the President of the Republic, 2020). For that reason, the data}

collection had to be ended sooner than expected.

3.3. Instruments development and measures

To elaborate the survey and analyse the antecedents of Satisfaction an adaptation of the model developed by del Bosque Rodríguez et al. (2006) was used. The literature review resulted in the addition of Repurchase Intent to the model, as a consequence of Satisfaction.

The survey was divided into two sections. In the first section the participants had to answer questions about their business characteristics (e.g. type of business and business age). The second section comprised scales developed to evaluate the antecedents and consequences of Economic and Non-economic Satisfaction.

All measures used in this research were adopted from existing scales. Table 2 represents the factor’s number of items, scales and authors. The items for each factor are shown in Annex I.

Besides Trust and Repurchase Intent, all the measures used in this study were the same as the ones used in the original model developed by del Bosque Rodríguez et al. (2006). del Bosque Rodríguez et al. (2006) measured Trust in two different factors: benevolence and credibility. However, in this study the factor Trust is measured as an unidimensional construct due to the statement of Doney & Cannon (1997): “although credibility and

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20 benevolence could be conceptually distinct, in business relationships such as those studied here (buyer-seller), they may be so intertwined that in practice they are operationally inseparable”. The factor Repurchase Intent was not used in the original model, so this measure was found in the literature review too.

Factor Items Scale Authors

Communication 5-item

Seven-point Likert-scale (1=strongly disagree and

7=strongly agree)

Adapted from Cannon & Perreault (1999) and Morgan & Hunt (1994)

Commitment 4-item

7=strongly agree)

Adapted from Anderson & Weitz (1989)

Trust 4-item

7=strongly agree)

Adapted from Doney & Cannon (1997)

Non-Economic

Satisfaction 5-item

7=strongly agree)

Adapted from Anderson and Narus (1984), Gassenheimer & Ramsey

(1994) and Ruekert & Churchill (1984)

Economic

Satisfaction 5-item

7=strongly agree)

Adapted from Gassenheimer & Ramsey (1994)

Repurchase

Intent 3-item

Five-point category response format (1=extremely unlikely and

7=extremely likely)

Adapted from Blocker et al. (2011)

Table 2. Variables measures

3.4. Sample

The Portuguese telecommunication sector was the setting of this research and the unit of analysis was the relationship between a supplier of telecommunication products and small retail businesses.

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21 The population that was analysed was the small retail businesses in the distribution channel of one of the three biggest players in the telecommunication sector in Portugal who buy products for resale. In other words, the respondents were asked about the same telecommunication supplier, referred as company XYZ throughout this paper for privacy reasons, exclusively when responding to the questions. The total population comprised 397 small retail businesses.

The small retailers of the telecommunication sector were chosen because this sector has a growing economic importance and several particularities that need to be studied. The survey targeted the owner of these businesses as respondents because of the fact that, due to the size of this type of businesses, they are usually the purchasing decider. However, in case that the mentioned don’t apply, that is, the addressed person is not qualified to answer the questionnaire, it was asked to the owner to forward it to another individual who has the purchasing decision.

As mentioned, to collect data, the small retail businesses were visited and the survey was personally handed out to its owners and, at a later time, the filled-out ones were picked up. The 77 responses mentioned were a result of a total of 108 visits, resulting in a response rate of about 71%.

The overall sample is composed of 77 small retail businesses that had the telecommunication company XYZ as supplier, being 45% telecommunication focused retail businesses and 55% retail businesses with other business focuses besides telecommunication.

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22

3.5. Data analysis

To analyse the data, this study started to check the validity of the measures of its model through the evaluation of the Cronbach’s alpha for each factor and through several Factor Analysis. After that and to test the hypothesis of the model, two Multiple Linear Regressions were used in order to derive the importance of the factors influencing retailers’ Satisfaction, both Economic and Non-Economic, with the supplier analysed in the study, company XYZ. To reach the second research objective and finding if Satisfaction, both Economic and Non-Economic, is related with the Repurchase Intent of small retailers’, it was also performed a Multiple Linear Regression Analysis. Finally, to reach the third objective of this study, which is understanding if the antecedents of Satisfaction of small retailers’ interrelationships and the fourth objective have of finding if the two dimensions of Satisfaction of small retailers are related, three Simple Linear Regressions were run. The statistics were performed using the Statistical Package for the Social Sciences (SPSS) to carry out the statistical analysis: the calculation of the Cronbach’s alpha, the factor analysis and the multiple regression analysis.

3.5.1. Measures validation

To validate the measures of this study (Communication, Commitment, Trust, Non-Economic Satisfaction, Satisfaction and Repurchase Intent), a reliability analysis and a dimensionality analysis were performed. The reliability of the measures was checked using the Cronbach’s alpha and the dimensionality using a Factor Analysis via the method of Principal Components analysis.

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23 3.5.1.1 Measures’ reliability

To test how closely related the items of each factor are as a group, the Cronbach’s alpha was calculated. In other words, Cronbach’s alpha is considered to be a measure of scale reliability. The internal consistency of all scales (Cronbach’s alpha) included on Table 3 are higher than 0,9 which is considered excellent (Nunnally, 1978). However, a high value for alpha does not indicate that the measure is unidimensional. So, in addition to measuring internal consistency, this study used a Factor Analysis via the method of Principal Components analysis to check the dimensionality of the scales on the next section.

Factor Cronbach’s alpha

Communication 0,943 Commitment 0,910 Trust 0,943 Non-Economic Satisfaction 0,920 Economic Satisfaction 0,952 Repurchase Intent 0,985

Table 3. Reliability of scales

3.5.1.2 Measures’ dimensionality

The scales used in this study have been adapted from previous research, so the method chosen to check the scales’ dimensionality was a Factor Analysis via the method of Principal Components analysis for each scale (Annex II).

The first step of each Factor Analysis is to determine the suitability of the data for structure detection with the Kaiser-Meyer-Olkin (KMO) test and the Bartlett's test of sphericity. In other words, it is necessary to evaluate the quality of the correlations to use a Factor Analysis. The KMO’s coefficient should be higher than 0.5 and close to 1.0 to indicate that a factor analysis would be useful for the data in analysis and the Bartlett's test of sphericity

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24 should be less than 0.05 (Pestana & Gageiro, 2003). These two conditions were met for each factor, which means that it is possible to proceed with the Factor Analysis (Annex II). The next step for the Factor Analysis was to determine the number of factors to retain using the values of Communalities for each item, the value of Factor Loading for each item and the value of the Total Variance Explained for each scale.

The communalities represent the total variance quantity that a factor shares with all the other values included in the analysis. A communality value below 0.50 indicates that the item isn’t significative and should be excluded of the factor which it belonged to initially, because small values indicate items that do not fit well with the factor solution (Hair et al., 1998). The results showed that none of the items initially proposed should be excluded (Annex II).

The Factor Loading corresponds to the relationship of each item to the underlying factor. When an item has a Factor Loading below 0,4, it should be excluded from its factor (Hair et al., 1998). The smallest Factor Loading of this analysis was 0,803 and, thus, no factor was excluded.

The Total Variance Explained indicates the degree of explanation reached by all the items that were calculated for each scale in the Factor Analysis. The values for each set of items of this study vary between 78,95% and 97,01% (Annex II), which indicates that every factor analysed is explained significantly by its correspondent items.

In conclusion, the measure validation was done after the measures’ reliability and dimensionality tests, with no excluded items. In that way, it was valid to create a composite measure of the items that measure the factors of this study - Communication, Commitment, Trust, Non-Economic Satisfaction, Economic Satisfaction and Repurchase Intent. The average of points of the items of each factor generated the factor’s measure.

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25

4. Hypothesis analysis

To test the hypothesis of the model and reach the objectives of this study, which are (1) determining the antecedents of Satisfaction, both Economic and Non-Economic, in supplier-small retailer relationship, (2) finding how the Economic and Non-Economic Satisfaction of small retailers relates with their Repurchase Intent, (3) understanding if the antecedents of Satisfaction of small retailers have interrelationships and (4) finding if the two dimensions of Satisfaction of small retailers are related in the Portuguese B2B telecommunication environment, four Multiple Linear Regressions were used as well as three Simple Linear Regressions.

4.1. Linear Regression assumptions

In order to run Linear Regressions, Simple and Multiple, it was necessary to validate if the data of this study could actually be analysed by this method. To do that, it was necessary to check if the data used meet the following four assumptions or, otherwise, the results of the regression wouldn’t be valid:

a) Assumption of the independence of the residuals

Linear Regression assumes that residuals are independent from each other or, in other words, uncorrelated. This assumption is checked through the Durbin-Watson test (Annex III). The residuals are independent if the value of this test is d ≈ 2 (Marôco, 2011);

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26 b) Assumption of multicollinearity

Linear Regression assumes that the independent variables are not highly correlated with each other. This assumption is checked through the analysis of the Variance Inflation Factor (VIF) values in the coefficients table (Annex III). The existence of multicollinearity is low if the VIF value is below 10 (Hair, Black, Babin & Anderson, 2014);

c) Assumption of the normal distribution of the residuals

Linear Regression states that the residuals should have a normal distribution. This assumption can be checked through the analysis of a normal probability plot (Annex III). The residuals have a normal distribution if the values represented in that graph are distributed near the main diagonal (Marôco, 2011);

d) Assumption of the homoscedasticity of residuals

Linear Regression assumes that the variance of the residuals is similar across the values of the independent variables. This assumption is checked through the analysis of a scatterplot (Annex III). A distribution is assumed to be homoscedastic when the pattern of distribution of points against the line does not show a clear pattern (Hair et al., 2014). All the previous assumptions were analysed and checked (Annex III) for each Linear Regression that was performed in this study:

a) A Multiple Linear Regression with Communication and Commitment as independent variables and Economic Satisfaction as dependent variable (Hypothesis 1 and 4);

b) A Multiple Linear Regression with Communication, Trust and Commitment as independent variables and Non-Economic Satisfaction as dependent variable (Hypothesis 2, 3 and 5);

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27 c) A Multiple Linear Regression with Economic Satisfaction and Non-Economic Satisfaction as independent variable and Repurchase Intent as dependent variable (Hypothesis 6 and 7);

d) A Simple Linear Regression with Communication as independent variable and Trust as dependent variable (Hypothesis 8);

e) A Simple Linear Regression with Trust as independent variable and Communication as dependent variable (Hypothesis 9);

f) A Simple Linear Regression with Economic Satisfaction as independent variable and Non-Economic Satisfaction as dependent variable (Hypothesis 10).

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28

4.2. Results

4.2.1. What are the antecedents of Satisfaction, both Economic and Non-Economic, of small retailers with their suppliers in the telecommunication sector in Portugal?

Model Summaryb R R Square Adjusted R Square Durbin-Watson .048a _0,002 _-0,025 _1,948 ANOVAa Sum of

Squares df Mean Square F Sig.

Regression 0,632 2 0,316 0,086 .918b

Residual 271,990 74 3,676

Total 272,622 76

Coefficientsa

B Std. Error Beta t Sig.

(Constant) 3,839 0,912 4,209 0,000

Communication 0,089 0,250 0,075 0,357 0,722

Commitment -0,053 0,294 -0,038 -0,182 0,856

a. Predictors: (Constant), Communication, Commitment b. Dependent Variable: Economic Satisfaction

Table 4. Economic Satisfaction Multiple Linear Regression results

Hypothesis 1 and 4 stated that the supplier’s Communication and Commitment are positively correlated with the Economic Satisfaction of the small retailer. To test these two hypotheses, a Multiple Linear Regression was run. The results (Table 4) rejected both hypothesis due to their low level of significance. The regression output shows that

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29 Communication and Commitment predictor variables aren’t statistically significant because their p-values (0.722 and 0.933) respectively) are above the significance level of 0.05.

Model Summaryb R R Square Adjusted R Square Durbin-Watson .249a _0,062 _0,023 _1,836 ANOVAa Sum of

Regression 16,288 3 5,429 1,609 .195b

Residual 246,345 73 3,375

Total 262,633 76

Coefficientsa

(Constant) 3,219 0,880 3,660 0,000

Communication 0,021 0,251 0,018 0,084 0,933

Trust 0,533 0,262 0,427 2,036 0,045

Commitment -0,438 0,326 -0,320 -1,345 0,183

a. Predictors: (Constant), Communication, Trust, Commitment b. Dependent Variable: Non-Economic Satisfaction

Table 5. Non-economic Satisfaction Multiple Linear Regression results

Hypothesis 2, 3 and 5 stated that the supplier’s Communication, Trust and Commitment are positively correlated with the Non-economic Satisfaction of the small retailer. To test these three hypotheses, another Multiple Linear Regression was run. The results (Table 5) confirmed that Trust predictor variable is positive and statistically significant (β=0.427, p-value=0.045). However, Communication and Commitment variables aren’t statistically significant because their p-values (0,933 and 0.183, respectively) are above the significance level of 0.05. The R2_{of this model is 0.062, which means that only 6.2% of the variance in}

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30 4.2.2. Does small retailers’ Economic Satisfaction and Non-Economic

Satisfaction with their suppliers influence their Repurchase Intent?

Model Summaryb R R Square Adjusted R Square Durbin-Watson .584a _0,341 _0,323 _2,008 ANOVAa Sum of Squares

df Mean Square F Sig.

Regression 88,818 2 44,409 19,157 .000b

Residual 171,540 74 2,318

Total 260,358 76

Coefficients

(Constant) 3,308 0,424 7,809 0,000 Economic Satisfaction 0,634 0,135 0,649 4,705 0,000 Non-economic Satisfaction -0,093 0,137 -0,094 -0,681 0,498

a. Predictors: (Constant), Economic Satisfaction, Non-economic Satisfaction b. Dependent Variable: Repurchase Intent

Table 6. Repurchase Intent Multiple Linear Regression results

Hypothesis 6 and 7 stated that the retailer’s Economic Satisfaction and Non-economic Satisfaction are positively correlated with the Repurchase Intent of the small retailer. To test these two hypotheses, a Multiple Linear Regression was run. The results (Table 6) confirmed that Economic Satisfaction predictor variable is positive and statistically significant (β=0.649, p-value=0.000). However, Non-economic Satisfaction variable isn’t statistically significant because its p-value (0.498) is above the significance level of 0.05. The R2_{of this model is 0.341, which means that 34.1% of the variance in Repurchase Intent of}

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31 4.2.3. Are there interrelations between the antecedents of Satisfaction?

Model Summaryb R R Square Adjusted R Square Durbin-Watson .780a _0,609 _0,603 _1,827 ANOVAa Sum of

Regression 102,340 1 102,340 116,602 .000b

Residual 65,827 75 0,878

Total 168,167 76

Coefficientsa

(Constant) 1,568 0,353 4,446 0,000

Communication 0,726 0,067 0,780 10,798 0,000

a. Predictors: (Constant), Communication b. Dependent Variable: Trust

Table 7. Trust Simple Linear Regression results

Hypothesis 8 stated that the supplier’s Communication is positively correlated with the Trust of the small retailer. To test this hypothesis, a Simple Linear Regression was run. The results (Table 7) confirm this hypothesis since the coefficient is positive and statistically significant (β=0.78, p-value= 0.000). The R2_{of this model is 0.609, which means that}

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32 Model Summaryb R R Square Adjusted R Square Durbin-Watson .824a _0,680 _0,675 _2,114 ANOVAa Sum of

Regression 95,389 1 95,389 159,197 .000b

Residual 44,939 75 0,599

Total 140,328 76

Coefficientsa

(Constant) 1,530 0,323 4,743 0,000

Trust 0,753 0,060 0,824 12,617 0,000

a. Predictors: (Constant), Trust b. Dependent Variable: Commitment

Table 8. Commitment Simple Linear Regression results

Hypothesis 9 stated that the supplier’s Trust is positively correlated with the Commitment of the small retailer. To test this hypothesis, a Simple Linear Regression was run. The results (Table 8) confirm this hypothesis since the coefficient is positive and statistically significant (β=0,824, p-value=0.000). The R2_{of this model is 0.680, which means that 68% of the}

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33 4.2.4. Are the two dimensions of Satisfaction, Economic and

Non-economic, related? Model Summaryb R R Square Adjusted R Square Durbin-Watson .729a _0,532 _0,526 _1,926 ANOVAa Sum of

Regression 139,719 1 139,719 85,255 .000b

Residual 122,914 75 1,639

Total 262,633 76

Coefficientsa

(Constant) 0,852 0,342 2,490 0,015

Economic

Satisfaction 0,716 0,078 0,729 9,233 0,000

a. Predictors: (Constant), Economic Satisfaction b. Dependent Variable: Non-economic Satisfaction

Table 9. Economic Satisfaction Simple Linear Regression results

Hypothesis 10 stated that the supplier’s Economic Satisfaction is positively correlated with the Non-economic Satisfaction of the small retailer. To test this hypothesis, a Simple Linear Regression was run. The results (Table 9) confirm this hypothesis since the coefficient is positive and statistically significant (β=0.729, p-value=0.000). The R2_{of this}

model is 0.532, which means that 53.2% of the variance in Non-Economic Satisfaction of small retailers is explained by their Economic Satisfaction.

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34

5. Final considerations

5.1. Discussion

This study has the following objectives: (1) determining the antecedents of Satisfaction, both Economic and Non-Economic, in supplier-small retailer relationship, (2) finding how the Economic and Non-Economic Satisfaction of small retailers relates with their Repurchase Intent, (3) understanding if the antecedents of Satisfaction of small retailers have interrelationships and (4) finding if the two dimensions of Satisfaction of small retailers are related in the Portuguese B2B telecommunication environment.

When it comes to the antecedents of Satisfaction, the results only concluded that Trust is an antecedent of Non-economic Satisfaction (H3). This finding verifies the one reported in the original study by del Bosque Rodríguez et al. (2006), as well as similar studies like the ones developed by Ferro et al. (2016) and Mpinganjira et al. (2017). However, no significant direct relationship was found between the other antecedents, Communication and Commitment, and the two dimensions of Satisfaction, comparatively with the original study. One possible explanation for these results can be the size of the businesses analysed in this research. Small retailers, due to their characteristics and business environment, can value more other aspects of the relationship, such as the instrumental ones (product, price and logistics) that weren’t a part of the model. Small businesses usually struggle for their survival (Runyan and Droge, 2008). For instance, due to their business fragility, small retailers can be more price sensitive. Nevertheless, the results of this research show that in Portugal’s small retailer–supplier relationship Trust is based on the belief that the business

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35 partner will behave considering the interests of the other partner (Doney & Cannon, 1997) and it impacts significantly the non-economic dimension of Satisfaction.

In regard to the Repurchase Intent, which was analysed as a consequence of Satisfaction (both dimensions), only Economic Satisfaction was proved to influence it positively (H6). In other words, the response of Satisfaction, specifically the Economic dimension, impacts the small retailers’ behaviour, increasing their willingness to repurchase. The addition of this construct to the model had the objective of analysing how small retailers’ Satisfaction would impact their intent of continue the relationship with the supplier. Retailers can feel satisfied with the relationship but have no interest in continuing or nurturing the relationship with a specific supplier, especially when there are other suppliers available with similar products and prices, which is the case in the telecommunication sector. This sensitivity to the product offered and prices of this type of retailers can also be an explanation for the connection of the economic dimension of Satisfaction and the Repurchase Intent.

Besides finding the antecedents of Satisfaction and its influence on Repurchase Intent, this study also analysed the interactions between the constructs (H8, H9). The results showed strong evidence in the positive link between Communication and Trust and between Trust and Commitment, as reported in the original study by del Bosque Rodríguez et al. (2006) as well as the studies by Segarra-Moliner et al., (2013), Cater and Cater, (2010), Ferro et al. (2016) and Mpinganjira et al. (2017).

Communication in Portugal’s small retailer–supplier relationship is based on the frequency of contact with their supplier as wells as the utility of information switched in a timely manner (Cannon & Perreault, 1999; Morgan & Hunt, 1994). The reason behind the link between Communication and Trust is the fact that, when the supplier strives to

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36 give useful information to the retailer, the retailer will view his supplier as competent. Because Trust has an impact on the Non-economic Satisfaction (H3), Communication can be a form of strengthening indirectly the Satisfaction of the small retailer.

In Portugal’s small retailer–supplier relationship Commitment is based on the effort that the retailers put into the relationship, their flexibility and patience when the suppliers make mistakes and the similarity of points of view, ideas, values and executive style (Anderson & Weitz, 1989). So, as stated by del Bosque Rodríguez et al. (2006), the link between Trust and Commitment is: “the more the distributor trusts the manufacturer’s competence and good faith, the higher the commitment to the relationship”.

Finally, this study also concluded that the Economic Satisfaction of the small retailers correlates positively with their Non-economic Satisfaction. In the original study, del Bosque Rodríguez et al. (2006) this finding was also proven but with a low significance level. However, in our results the significance level was high.

Table 10 includes a summary of the results of the hypothesis tests.

Hyp. Path Beta Sig. Results

H1 Communication ® Economic Satisfaction 0,075 0,722 Rejected

H2 Communication ® Non-Economic Satisfaction 0,018 0,933 Rejected

H3 Trust ® Non-Economic Satisfaction 0,427 0,045 Supported

H4 Commitment ® Economic Satisfaction -0,038 0,856 Rejected

H5 Commitment ® Non-Economic Satisfaction -0,320 0,183 Rejected

H6 Economic Satisfaction ® Repurchase Intent 0,649 0,000 Supported

H7 Non-economic Satisfaction ® Repurchase Intent -0,094 0,498 Rejected

H8 Communication ® Trust 0,780 0,000 Supported

H9 Trust ® Commitment 0,824 0,000 Supported

H10 Economic Satisfaction ® Non-economic

Satisfaction 0,729 0,000 Supported

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37

5.2. Limitations and future research

This research analysed the interrelationship of different constructs in the relationship between small retailers and suppliers in the Portuguese telecommunication sector. Nevertheless, it’s important to take the limitations of this work into account.

First, the sample used, as mentioned, only included small businesses in the Portuguese telecommunication sector, which limits the generalization of the results to larger businesses, other sectors or other countries. This study presented different results from its original model, which can be a proof that the constructs analysed behave in different ways in different contexts. Thus, in future research, it would be interesting to test this model in other environments.

Another limitation lies in the methodology used in this research to test the hypothesis. Similar studies, such as the ones developed by del Bosque Rodriguez et al. (2006), Ferro et al. (2016) and Mpinganjira (2017), used Structural Equation Modelling (SEM) to analyse the data. However, due to the size of our sample (77 respondents), the methodology used was Regression Analysis. Regression Analysis specifies a default model, contrary to SEM that has less limitations with regard to what types of relations. If the sample of this study were bigger and, therefore, SEM was possible to use to analyse the data, there were probably more conclusions to take.

Finally, another limitation of this study is the fact that only interpersonal constructs were included as antecedents of Satisfaction. Instrumental constructs and interpersonal constructs have been studied as determinants of satisfaction in the B2B context. However, these constructs were, in almost all studies, analysed separately. Therefore, there is a lack of research when it comes to their joined effects on satisfaction. It would be interesting for

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38 future research to integrate instrumental factors on the model used, such as product, price and logistics.

5.3. Theoretical implications

This study contributes to the literature on Satisfaction in B2B markets, Satisfaction as a multidimensional construct and on channel research of small retailers by an adaptation of the model proposed by del Bosque Rodríguez et al. (2006) to the telecommunication industry that can be used in future research developed in other contexts. The model adopted in this study considers not only the antecedents of Satisfaction, as the original model, but also Repurchase Intent as a consequence of Satisfaction. Satisfaction significantly predicts Repurchase Intent, previously unexplored by del Bosque Rodríguez et al. (2006) model, but particularly relevant because the latter reflects the motivation to maintain the relationship by the act of purchasing again.

Firstly, this research supports that Trust is a key construct in B2B small retailer-supplier relationships, because it was proven that it influences the Non-economic dimension of Satisfaction, it influences the Commitment and it is influenced by Communication. Secondly, this study provides support for believing that Satisfaction in this type of relationship is a multidimensional construct formed by an economic and a non-economic dimension. The Economic Satisfaction can be described as a construct more focused on objective and tangible benefits from the relationship, while Non-Economic Satisfaction is more oriented to intangible aspects of the relationship, more specifically the psychosocial aspects. Thirdly, and contrary to predictions, only the Economic Satisfaction seems to influence the intention to buy again from the supplier.

Satisfaction on Small Retailer-Supplier Relationships: a Case of a Telecommunication Company in Portugal

Satisfaction on Small Retailer–Supplier

Relationships: a Case of a

Telecommunication Company in

Portugal

Cátia Filipa Pereira da Silva

M

SATISFACTION ON SMALL RETAILER–SUPPLIER RELATIONSHIPS:

A CASE OF A TELECOMMUNICATION COMPANY IN PORTUGAL

Abstract

Resumo

Table of Contents

List of tables

List of figures

1. Introduction

2. Literature review

2.1. Defining small retailers

2.2. Satisfaction

2.3. Satisfaction on business-to-business markets

3. Methodology

3.1. Conceptual model and hypothesis

3.2. Methodological approach and procedures of data collection

3.3. Instruments development and measures

3.4. Sample

3.5. Data analysis

4. Hypothesis analysis

4.1. Linear Regression assumptions

4.2. Results

5. Final considerations

5.1. Discussion

5.2. Limitations and future research

5.3. Theoretical implications