Next Article in Journal
Exploring the Role of a Colombian University to Promote Just Transitions. An Analysis from the Human Development and the Regional Transition Pathways to Sustainability
Previous Article in Journal
Analysis of Declarative and Procedural Knowledge According to Teaching Method and Experience in School Basketball
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sustainability
Volume 13
Issue 11
10.3390/su13116013
sustainability-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

“I am Delighted!”: The Effect of Perceived Customer Value on Repurchase and Advocacy Intention in B2B Express Delivery Services

by
Carlos Correa
1,
David Alarcón
1,* and
Ignacio Cepeda
2
1
Department of Social Anthropology, Psychology and Public Health, Pablo de Olavide University, 41013 Sevilla, Spain
2
Department of Business Administration and Marketing, University of Seville, 41004 Sevilla, Spain
*
Author to whom correspondence should be addressed.
Sustainability 2021, 13(11), 6013; https://doi.org/10.3390/su13116013
Submission received: 9 April 2021 / Revised: 21 May 2021 / Accepted: 25 May 2021 / Published: 26 May 2021
(This article belongs to the Section Economic and Business Aspects of Sustainability)
Browse Figures
Versions Notes

Abstract

:
Express parcel delivery has increased significantly in recent years because of changes in technology and consumer habits, as has the number of express parcel delivery companies and the competitiveness among them. For an express parcel business to be sustainable, it must succeed in increasing customer perceived value (CPV). This study aims to investigate the business-to-business (B2B) performance between companies and their main express parcel service provider. The main objective was to analyze the impact of CPV on both the intention to repurchase services and the intention to recommend such services in the business-to-business (B2B) express parcel delivery sector. This study develops a research model that is analyzed in the express parcel sector in Spain using the variance-based structural equation technique, partial least squares (PLS-SEM), for data analysis. The findings reveal that with express parcel services in the B2B sector, perceived value was positively associated with the customer’s perceived satisfaction and trust, which in turn enhances the intention to repurchase and stimulates advocacy. In a market as competitive as the express parcel market in the B2B environment, customer perceived value is a critical factor in ensuring company sustainability.

1. Introduction

The express delivery services (EDS) sector, which includes the activities of collecting, transporting, and delivering documents, packages, and other goods from door to door in a limited time frame [1], is experiencing very significant growth worldwide due to changes in traditional consumption habits in the online consumption of both end customers (B2C) and businesses (B2B). In addition, this growth has been accentuated by the recent global pandemic caused by COVID-19 (acronym for coronavirus disease 2019), which has driven and entrenched this new type of consumption [2]. These behavioral changes have been aided by information and communication technologies and the democratization of mobile devices, tablets, social networks, and B2B and B2C digital channels [3]. Due to this increased demand for express parcel delivery services, in recent years, the number of express parcel delivery companies and the competitiveness among them has increased significantly. This can lead to an increase in unsustainable consumption, both by production systems and distribution systems. For this reason, parcel delivery companies are increasingly taking into consideration the objective of enhancing efficiency and reducing their ecological footprint. However, to promote the transition to sustainable consumption, express parcel delivery companies must also meet the needs of their customers, while offering value to their consumers in such a way that the customer favors the continuity of the relationship over profits [4]. Thus, for an express parcel business to be sustainable in the long term, it must succeed in satisfying customer needs, increasing sales, and stimulating advocacy [4,5].
According to the DBK Sector Observatory [6], a leader in the provision of commercial, financial, sectoral, and marketing information in Spain and Portugal, the increase in ecommerce has a notable impact on the increase in the turnover of parcel and courier companies. This has led to significant growth in the use of express parcels, reaching a turnover of EUR 7.45 billion in 2019 (4.9% more than in the 2018 financial year) in B2B parcels. The explanation for this performance of the courier and parcel market can be partly supported by the increase in online consumption and in the outsourcing of services [7,8], as well as the improvement of supply chain management that has generated greater efficiency in the commercial distribution sector [9]. In 2018, revenues from postal shipments reached EUR 4872.2 million (+19.4% compared to 2017). Of this, 27.7% corresponded to the traditional postal segment, i.e., approximately EUR 1350.9 million, down 1.1% compared to 2017. Revenues from the express courier and parcel segment reached EUR 3521.3 million, 72.3% of the total, with a growth of 29.8% compared to 2017 [10].
Companies require express parcel services for both receiving materials from their suppliers and shipping products or services to their end customers and businesses. However, studies show that most companies tend to use a limited number of express parcel service providers, eventually establishing stable business relationships over time with their main express parcel provider [11]. Although the B2B relationship between the customer company and the express parcel service company is usually continuous over time [12], as in any competitive industry, the continuity of the business relationship depends on companies being satisfied with their express parcel providers [13,14,15,16]. In turn, customer satisfaction is directly dependent on the customer’s perceived value of the purchased service or product [13,17,18]. While, in the last decade, there has been a growing number of studies on customer perceived value in B2C, there is still not much evidence on the influence of perceived value on the business relationship in B2B in the express parcel industry. B2B relationships between express parcel companies and their customers tend to be long term and ongoing. This fact makes the study of factors influencing repurchase and recommendation to other companies a topic of particular relevance and interest. Empirical studies on these antecedent variables in B2C contexts are numerous, but in B2B contexts they are very scarce, and, specifically in the express parcel sector, they are almost nonexistent. This study aims to shed light on and fill the gap in the literature on empirical studies of express parcel companies in the B2B context by analyzing the main triggers that have an impact on the intention to repurchase from and to recommend these types of companies. The main objective of the study was to evaluate, in the context of B2B express parcel services, the antecedents of repurchase and recommendation intention of express parcel services. It examines what roles satisfaction, switching cost, and trust play in B2B express parcel services. Further, the study explores the indirect relationships between customer perceived value and repurchase and recommendation intention in B2B. To achieve these purposes, we reviewed previous studies of B2B customer perceived value (CPV) and the relationship CPV with mediating factors such as customer satisfaction, switching cost, and trust, with the final aim of examining their impact on repurchase intention and recommendation. Based on this review, the hypotheses proposed are tested on a structural model, and the results are discussed with the conclusions reached.

2. Literature Review and Hypotheses

2.1. B2B Customer Perceived Value

Companies are increasingly realizing that their customers are choosing to purchase value-added products and services capable of providing a highly satisfying experience [19]. The concept of customer value is the basis of a large number of recent studies within the relationship marketing literature, and it has been positioned as one of the main approaches for understanding customers [20,21,22]. Several authors have attempted to define customer perceived value (CPV). Customer perceived value (CPV) represents the consumer’s overall evaluation of the utility of a product based on perceptions of what was paid and what was received [18]. Day and Huang [23] propose that customer perceived value (CPV) represents the difference between the benefits and costs perceived by the customer. Customer perceived value is the customer’s subjective evaluation of the characteristics of the product or service, its performance, and the consequences of using that product or service [24].
These definitions share the subjective and multidimensional nature of customer perceived value (CPV) with regard to received products or services [25]. Although product quality is a primary requirement for achieving customer perceived value [26,27,28], CPV is a multidimensional and subjective notion that ranges from product quality to the utility that the customer receives through the services given by the supplier [25]. Some studies assert that product quality alone is not sufficient for customer perceived value to exist [29]. Several studies argue that customer experience has an increasingly closer relationship with customer perceived value [3,30,31]. Other authors point out that value resides in the experience and not exclusively in the quality of the product or service consumed [32,33,34,35,36]. Several authors use these constructs of customer experience and customer perceived value as synonyms [29,37,38,39,40].
According to Pine and Gilmore’s theory [29], product quality, service quality, and contextual experience are the three main determinants of customer perceived value, which in turn will influence customers’ preferences and purchase intentions [41]. Previous studies show that there is an association between customer perceived value (CPV) and repurchase and recommendation intention [42,43]; however, to date, few studies have been conducted on express parcel services in the B2B service environment [44,45].

2.2. Hypotheses Development

2.2.1. Customer Perceived Value and B2B Customer Satisfaction

According to the disconfirmation paradigm [18], customer satisfaction increases when perceived value exceeds expectations. Satisfaction in the financial services sector is defined from the perspective of the attitude, evaluation, and response expressed by a customer in the purchase process, and some studies find that the customer’s overall attitude towards their financial service provider is satisfactory when it exceeds their expectations [46,47]. Similarly, in the luxury sector, it has been observed that customer satisfaction with products or services depends on whether such products or services meet or exceed customer expectations [48,49]. In Internet banking services, e-satisfaction is defined as meeting expectations regarding purchased services. It has been observed that if the performance of an online service exceeds expectations, the customer will be satisfied; otherwise, the customer will not be satisfied [50].
As overall customer satisfaction is defined by the differences between the value the customer expects and the value actually received [51,52], satisfaction will depend on CPV [28,44,45,53]. In the logistics industry in general, and specifically with B2B express parcels, customer satisfaction will depend on the perceived value of the service, which will directly and indirectly impact their trust and business continuity with the express parcel provider [54,55,56,57,58,59,60]. Our hypothesis is as follows:
Hypothesis 1 (H1).
The customer perceived value (CPV) of a B2B express parcel company positively influences customer satisfaction.

2.2.2. Customer Perceived Value and B2B Customer Trust

Trust is defined as the belief that consumers must have that everything will go correctly in a customer–supplier relationship [61,62]. Additionally, trust is defined as the illusion that a particular firm will carry out actions that will yield positive results [63]. Moorman et al. [64] describe trust between two parties as the conviction that both parties are involved in a beneficial relationship. This type of conviction prolongs the duration of the relationship [65] by enhancing commitment to the relationship [66]. To that end, trust can be considered a valuable component of any successful relationship [66], fostering the development of long-term relationships and increasing commitment to the relationships [65,67].
Especially in various B2B industries, trust in suppliers is a critical variable in business [68]. Trust increases customers’ predisposition for long-term business relationships [69]. In B2B service companies, trust has an important weight in the retention of suppliers with good reputations [70]. Trust in a supplier in the B2B environment is linked to emotions that may imply calmness, security, and hope. In contrast, distrust is associated with fear, uncertainty, stress, and worry. Thus, an untrusted supplier is perceived as a threat that requires a higher level of control to ensure that it delivers as expected [71].
Trust depends on satisfaction and customer perceived value (CPV); when a customer perceives value, they tend to experience satisfaction and trust the supplier more [28]. In the B2B services sector, trust plays a key role in personal relationships between the sellers and buyers of services; the more customer perceived value a service has, the more trust the customer will have in the supplier [72]. Our hypotheses are as follows:
Hypothesis 2 (H2).
The customer perceived value (CPV) of a B2B express parcel company positively influences customer trust.
Hypothesis 3 (H3).
The degree of customer satisfaction with a B2B express parcel company is positively related to customer trust.

2.2.3. Customer Perceived Value and B2B Switching Costs

Switching costs refer to the perceived cost that customers discover once they change their service provider [73]. Switching costs significantly influence the intention to continue with the provider [74], explaining even more variance than customer satisfaction [75]. Burnham et al. [74] identified three types of switching costs: procedural, which involves the loss of time and effort invested; financial, which results from quantifiable economic loss; and relational, which is due to the rupture of ties and identity. Furthermore, the loss of a commercial relationship is the factor that most increases switching costs, and a good customer–supplier relationship makes it less likely that the buyer will consider the possibility of changing suppliers [73].
From the perspective of the customer–supplier relationship in B2B, higher customer perceived value and customer satisfaction will imply higher switching costs, improving the relationship and minimizing the possibility of supplier switching [76,77]. Our hypotheses are as follows:
Hypothesis 4 (H4).
The customer perceived value (CPV) of a B2B express parcel company positively influences switching costs.
Hypothesis 5 (H5).
Customer satisfaction with a B2B express parcel company positively influences the cost of switching suppliers.

2.2.4. Customer Perceived Value and B2B Repurchase Intent

In a competitive business environment, maintaining customer repurchase intention and avoiding switching behavior are very important [78]. The cost of attracting new customers is higher than that of keeping current customers [79]; thus, much of the efforts in B2B marketing should be directed at increasing repurchase intention. Repurchase intention is defined as an individual’s judgment about buying a designated service from the same company again, taking into account the individual’s current situation and likely future circumstances [80]. From a behavioral point of view, repurchase intention refers to the likelihood that an individual will continue to purchase products from the seller in the future [81,82]. Repurchase intention can be the result of customer satisfaction with and trust in a particular company’s product or service [83]. Repurchase intention is strongly dependent on service quality [84,85]. According to the customer value paradigm [86], service quality is an additional component of customer perceived value, and overall CPV is positively associated with repurchase intention [44,87,88,89].
In the B2B service sector, interpersonal aspects, such as switching costs, trust, and the customer’s perceived value of the supplier, have been shown to have a high impact on the repurchase intention of service buyers [90,91]. Specifically, in express parcel services, it has been found that situational factors, such as company location and delivery times, are less important in ensuring customers’ repurchase intention than individual and social service factors, such as innovativeness, optimism, and human interaction [92]. Particularly in the transportation services industry, for companies such as express parcel services, trust has been found to be a key factor in choosing suppliers as they transport customer goods that can be very valuable [93]. In the B2B relationship, customer perceived value (CPV) increases trust in the customer’s express parcel provider and, in turn, increases repurchase and recommendation intention [28,75]. Our hypotheses are as follows:
Hypothesis 6 (H6).
B2B express parcel company customer switching costs are positively associated with repurchase intention.
Hypothesis 7 (H7).
B2B express parcel company customer trust positively influences repurchase intention.
Hypothesis 8 (H8).
B2B express parcel company customer trust mediates the relationship between customer perceived value (CPV) and repurchase intention.

2.2.5. Customer Perceived Value and B2B Recommendation Intention

In this study, the intention to promote or recommend is defined as the probability that a customer will recommend a service provider to others in the future [94]. A concept that is widely used in previous studies and related to recommendation intention is so-called WOM (word of mouth), which is understood as a form of informal recommendation in relation to a certain product or service [95,96,97,98]. Specifically, WOM could be defined as the comments made by customers about a given service or product [99]. Recently, other studies have used a new concept that has evolved in different digital environments: electronic word of mouth (e-WOM), which analyzes purchase decisions based on customer recommendations on the web [100]. In this study, which is focused on B2B, we employ the concept of customer recommendation intention broadly referring to both formal and informal modes of communicating the benefits of using a supplier to others [101].
In general, recommendation intention can be considered to be an expressive response of trust motivated by emotional factors of satisfaction or perceived benefits versus costs [102]. VPC exerts influence through relationship satisfaction, trust in repurchase, and recommendation intention [25]. Chai et al. [101] found that customer repurchase intention is positively associated with advocacy intention, and, in turn, customer perceived value directly and indirectly influences advocacy intention. Customers who perceive value in the purchase of a product or service tend to repeat the purchase and recommend their supplier to new customers [101]. In the context of B2B services, it has been found that customer perceived value has a positive impact on loyalty and subsequent advocacy intention for such services [103]. Customer perceived value (CPV) influences both trust and customer recommendation intention [28]. Our hypotheses are as follows:
Hypothesis 9 (H9).
Repurchase intention positively influences express parcel provider recommendation intention.
Hypothesis 10 (H10).
B2B express parcel company customer trust and repurchase intention mediate the relationship between customer perceived value (CPV) and recommendation intention.

2.3. Conceptual Model

Customer perceived value (CPV) is a critical factor in ensuring company sustainability in the B2B environment. This study aims to investigate the business-to-business (B2B) performance between companies and their main express parcel service provider. The main objective was to analyze the impact of CPV on both the intention to repurchase services and the intention to recommend such services in the business-to-business (B2B) express parcel delivery sector. This study develops a research model (see Figure 1) that analyzes the effect of customer perceived value on the satisfaction, trust, and switching costs of express parcel services and how these variables predict repurchase intention and recommendation intention in the B2B sector.

3. Materials and Methods

3.1. Sample

A total of 186 multisector companies participated in this study. The inclusion criterion was that all of these companies had express parcel providers as strategic partners for their business activity. Online surveys were sent to the participants by email requesting participation and explaining the objectives of the research along with a link to the online survey. The survey was sent to 325 companies, of which 185 (57%) responded fully. The survey was conducted online using the Typeform platform. The surveys were collected between 3 March 3 and 8 April 2020. The sample was drawn from mailing lists of the national chambers of commerce and entrepreneurs’ associations, using corporate Facebook and LinkedIn contacts, and submitted to the managers of B2B ecommerce companies who use express parcel providers.
The participants were asked questions through online surveys using the Typeform digital platform for sample management. The survey was sent by email to companies that use express delivery services for their business. The email was distributed to the membership lists of business associations, national chambers of commerce, and the Spanish business trade confederation. Participation in the questionnaire was encouraged through professional contacts on social networks such as LinkedIn and Facebook. Contact with the companies was accomplished by email. The questionnaire was completed by 329 companies, of which 185 were completed, i.e., 56.20%, with an average response time of 14 min and 36 s.
At the beginning of the survey, the participants were informed of the objectives of the present investigation. The text informed the participants of the purely experimental purposes of the study and that the information would not be stored longer than necessary to obtain the conclusions of the investigation. Permission to participate was requested, with exclusive use of the data for conferences or future scientific publications. The participants were informed that they could withdraw from the study at any time if they so wished. Similarly, the participants were informed that their identity would be kept anonymous.

3.2. Measurement Scales

A 7-point Likert-type scale was used to measure each of the statements on each item. Specifically, the response options ranged from 1 (strongly disagree) to 7 (strongly agree) (see Table 1).
To measure the value perceived by the customer, we used a scale adapted from Gounaris [26]. The scale is composed of 4 items that assess the value that the customer gives to the expectations fulfilled by the product or service [25,26]. Adapted versions of the scale have been employed to measure customer perceived value of the banking, food, and motor sector services associated with customer satisfaction, trust, and loyalty [28,104,105].
Customer satisfaction was measured using a scale adapted from Ruiz et al. [44] and based on Taylor and Baker’s [106] and Oliver’s [107] work. The scale is composed of 6 items. This scale has been used in previous studies to compare customer satisfaction of service providers in the U.S. and Spain [44].
To measure the cost of change in the service sector, the Fandos et al. scale [75], adapted from Burnham et al. [74], was used. The scale is composed of 5 items. The switching cost scale has been used to analyze the relationship between switching costs and loyalty in customers of financial institutions [75] and to measure the switching costs of telephone company customers [108].
The Morgan and Hunt scale [66] was used to measure the level of trust in the express delivery provider. The scale is composed of 3 items. The scale has been employed in previous studies to analyze the relationship of customer trust to purchase intention in the automotive, retail, and ecommerce sectors [66,109,110,111].
The Ruiz et al. [44] scale, adapted from Zenithal et al. [85], was used to measure the intention to repurchase express parcel logistics services. The scale is composed of 3 items. This scale has been used to analyze the relationship of service quality, customer perceived value, satisfaction, and repurchase intention in sectors such as the restaurant and online shopping industries [42,112].
The Chai et al. scale [101] was used to measure the intention to recommend. The scale is composed of 3 items. The scale has been used to study the relationship between customer perceived value and recommendation intention in the insurance, online shopping, and private education sectors [113,114,115].

3.3. Data Analysis

To analyze the data derived from the questionnaires, the partial least squares (PLS-SEM) technique was used. This SEM technique is based on variance, and it is part of the multivariate analysis family used to analyze the relationships between indicated variables. In our model, all measures are operationalized as composites [116,117]; thus, we decided to use PLS-SEM to test our model and hypotheses. This decision was made because we use composites estimated in Mode A [118,119], and we adopt an explanatory approach following Henseler [120].
Composites are estimated in Mode A when the indicators that compose the latent variable are correlated. Similarly, Mode A composites are a good choice with small or medium sample sizes [121]. A two-step process has been indicated to consistently evaluate models using PLS-SEM [119] as follows: (1) evaluation of the measurement model and (2) evaluation of the structural model.
We use a bootstrap procedure [122] to find the significance of the indices. With bootstrapping, which is a resampling procedure, we can determine the significance of the path coefficients, weights, and indicator loadings for each composite (i.e., latent variable).
For data analysis, we used the SmartPLS 3.2.6. software package (Bönningstedt, Germany) [123]. To test for mediation effects, we followed the procedure described by Nitzl et al. [124] and Cepeda-Carrion et al. [125].

4. Results

Using the indicated PLS-SEM technique, the following results were obtained by analyzing the measurement model and the structural model [119]. This section presents the results obtained based on the study’s general objective. The factor loadings of all items in the measurement model are above 0.70, which is an appropriate level at which 50% of the variance of the indicators can be explained [126].

4.1. Analysis of the Measurement Model

A good measurement model should demonstrate sufficient reliability and validity. The results show that the measurement model meets all of the commonly stipulated requirements.
The most appropriate measures of internal consistency reliability are composite reliability, Dijkstran and Henseler’s rhoA, and Cronbach’s alpha [127]. The model satisfies the prerequisite of construct reliability, and all measurements are greater than 0.8 (see Table 2).
The average variance extracted (AVE) serves as a measure of unidimensionality [128]. The average variance extracted value (AVE) for all constructs is greater than 0.5 (Table 2), showing appropriate convergence and convergent validity of the measures. The square root of AVE for each individual construct exceeds the correlation value between itself and the other constructs, fulfilling the discriminant validity requirement and showing that the variance captured by the latent variable exceeds 50% [128,129,130]. Finally, the heterotrait-monotrait ratio (HTMT) provides evidence of discriminant validity [131]. Some authors suggest a threshold of 0.9 [119], others propose a strictest value of 0.85 [126]. Most of the variables attain discriminant validity, as indicated by values below 0.85 in the HTMT (Table 3). However, discriminant validity between switching cost and customer perceived value is reached below a threshold of 0.9.

4.2. Analysis of the Structural Model

After checking that the measurement items have appropriate properties, we examine the individual hypotheses (Table 4). H1 shows that the customer perceived value of the B2B express parcel company’s service is positively associated with customer satisfaction (β = 0.662, p < 0.001). Hypotheses H2 and H4 are also supported by the data, and customer perceived value is positively associated with trust level (β = 0.418, p < 0.001) and with express parcel provider switching costs (β = 0.355, p < 0.001).
Satisfaction with the B2B express parcel company is positively associated with switching costs, H5 (β = 0.516, p < 0.001), and the degree of satisfaction has a positive influence on customer trust in the express parcel provider, H3 (β = 0.496, p < 0.001).
Customer repurchase intention is predicted by B2B express parcel company switching costs, H6 (β = 0.450, p < 0.001), and by trust in the B2B express parcel company, H7 (β = 0.272, p < 0.01). In turn, H9 is tested; the B2B express parcel customer’s repurchase intention positively influences the intention to recommend the B2B express parcel company (β = 0.714, p < 0.001).
Table 5 shows the indirect effects of customer perceived value (CPV) on repurchase and recommendation intention mediated by customer trust. Customer trust in the B2B express parcel company fully mediates the relationship between customer perceived value (CPV) and repurchase intention, H8 (β = 0.173, p < 0.01). Customer trust and repurchase intention regarding the B2B express parcel company partially mediate the relationship between customer perceived value (CPV) and recommendation intention, H10 (β = 0.123, p < 0.01). According to prior studies, in the case of H8, the type of mediation is full, because the indirect effects of customer perceived value on repurchase intention mediated by customer trust is significant, and the direct effect of customer perceived value on repurchase intention is not significant [124,125]. However, in H10, we have partial mediation, as both the direct effect of customer perceived value on advocacy intention and the indirect effect through mediation are significant [119,125]. This indicates that a portion of the effect of customer perceived value on advocacy intention is mediated through customer trust and repurchase, while customer perceived value still explains a portion of advocacy that is independent of trust and repurchase intention.
The results (see Figure 2) show that VPC broadly explains satisfaction (R2 = 0.438), trust (R2 = 0.695), and switching costs (R2 = 0.635) with regard to express parcel providers. Overall, the model largely explains repurchase intention (R2 = 0.456) and recommendation intention (R2 = 0.510).

5. Discussion

5.1. Theoretical Contribution

According to Zeithaml [18], VPC is a customer’s overall judgment about the usefulness of a product or service based on perceptions of what they give and what they receive. In the B2B relationship, the customer’s perceived value of express parcel services has a positive impact on satisfaction with and trust in the supplier. Our study claims that customer perceived value VPC is a key success factor for express parcel companies in the B2B environment. The customer’s perception of satisfaction and trust in their service provider depends on customer perceived value (CPV); in turn, CPV indirectly influences repurchase and recommendation intention through its relationship with satisfaction, trust, and switching costs.
These results are consistent with other studies that have found that customer satisfaction is strongly associated with customer perceived value [28,44,45,53]. Specifically, in the B2B service sector, it has previously been found that customer perceived value influences trust between the sellers and buyers of services: the more value the customer attaches to a service, the more trust they will have in their regular supplier [111]. In addition, higher perceived value is directly associated with switching costs, increasing switching costs when the customer perceives high value in the service obtained [76,77].
Similarly, the customer’s perception of the value of the service indirectly influences their future relationship with the supplier, and its indirect effect explains a large part of the variance in repurchase intention. Particularly, in the B2B industry, with regard to services such as transportation, previous studies have found that the intention to continue with the same service provider depends on trust and switching costs, and the customer’s perceived value positively influences the trust in the service provider and switching costs [75,93].
Previous service sector studies show that there is a positive association between customer perceived value (CPV) and recommendation intention [42,43,45,113,114,115]. With the present research, we sought to understand how the construct of customer perceived value (CPV) is related to the intention to repurchase express parcel services and the intention to recommend such logistics services to third parties in the business-to-business (B2B) environment. To test this objective, we analyzed the effect of VPC on satisfaction, trust, and switching costs, as well as how such VPC influences repurchase and recommendation behavioral intentions. The results show that customer perceived value (CPV) has an indirect effect on future repurchases of express parcel services from business customers. At the same time, future and continued repurchases have a direct effect on the recommendation of such services to other customers who regularly use express parcel services for the sale and distribution of their companies’ products. Furthermore, we find that the effect of customer perceived value (CPV) on repurchase intention and recommendation intention is mediated by the variables of satisfaction, trust, and switching costs within this B2B environment. Overall, CPV positively influences repurchase and recommendation behavioral intention.
We can conclude that B2B express parcel companies should focus their efforts on increasing the value perceived by the customer to increase customer satisfaction and transmit more trust. In this way, both the relationship between the customer and supplier will be strengthened, decreasing the risk of switching and increasing the intention to repurchase, and the supplier can increase its sales due to the effect of the recommendation among customers of express parcel companies [28,53]. Yang and Peterson [132] point out that customer perceived value (CPV) substantially influences satisfaction with the contracted service. In addition, customer perceived value has a great influence on the customer’s decision and evaluation of the different switching costs that the customer would suffer if that customer decided to change suppliers [133,134,135]. Other studies claim that satisfaction is a mediating variable in the effect of customer perceived value on trust and switching costs [24,136]. Sharma and Patterson [137] undertook research indicating that, in a personal financial planning service context, switching costs positively mediate the effect of satisfaction and trust on a future relationship commitment.
From a behavioral point of view, satisfied customers who express a high level of trust in their supplier tend to have a higher level of use of a service than those who are not satisfied [138,139]. Moreover, it has been shown that satisfied customers of B2B services and with a higher degree of trust in their supplier have a greater tendency to recommend the services offered by their usual supplier to other companies that require such services [84,85]. As the results show, customers with a high level of satisfaction and trust in their supplier have a higher tendency to continue to repurchase that supplier’s services, which positively impacts the intention to recommend the supplier to their professional colleagues within an industry (B2B) and to those within their personal network [101]. Thus, the intention to repurchase and recommend services depends on the quality of the service and, with it, the perceived value per customer [85]. In line with previous studies in other sectors, our results show that a sustainable long-term parcel delivery company must generate perceived value to the customer, which will not only result in increased turnover but more importantly in enhanced trust and recommendation among the customer’s network [5,42,140,141,142].

5.2. Practical Applications

Inexpensive fast food delivery systems and parcel services allow people to perform their daily functions without much interruption while staying at home or in the office. The recent global situation due to the COVID-19 pandemic has exponentially increased the use of such services [143,144]. This study reveals important insights that express parcel companies in the B2B environment should consider to become more competitive and relevant to their business customers. Currently, changes are occurring in the buying habits of both end customers (B2Cs) and business customers (B2B). There is a large increase in non-face-to-face purchases supported by express parcels [6]. However, express parcel companies in the B2B environment are struggling in a very competitive scenario and are looking for factors that can increase their market share and sales. In this regard, it is shown that customer perceived value significantly influences the competitiveness of express parcel companies in B2B [3]. Customer perceived value (CPV) or customer experience management is a very powerful competitive tool used by a significant number of companies globally. Variables such as price, quality, and omnichannel are no longer differentiated [3,28,60]. New marketing trends focus on differentiating companies through emotional rather than rational aspects because the latter, in most competitors, are cosmetic.
To build a memorable and differentiating customer experience in companies in this sector, it is not enough to comply with what has been agreed upon, i.e., the delivery of goods in an agreed time slot. In addition, the entire organization must be aligned to work strategically and focused on the variables that lead to achieving a customer experience that consumers can count on. According to our study, some of these variables are satisfaction, trust, and switching costs. The objective is to improve the business customer’s intention to repurchase and to recommend services to other businesses that are express parcel users. This could result in an increase in market share, improve brand positioning, and consolidate a substantial competitive advantage over time, which in turn would enhance a company’s competitiveness and sustainability.
In addition, managers of B2B express parcel companies should bear in mind that by improving the customer’s experience and trust in the company, they are more likely to repurchase and recommend the company. This will help them to achieve better results and a sustainable competitive advantage. In this sense, and given the current environmental awareness of the population and countries in general, companies must be sensitive to these concerns and interests of society [22,140]. Express parcel delivery companies must develop strategies and actions that are environmentally sustainable, through the use of electric vehicles, the promotion of all things digital by eliminating physical documents, the commitment to environmentally friendly products and services, etc. However, strategies aimed at promoting sustainable consumption must be compatible with or even increase the value perceived by customers so that they ultimately result in profits for the company [60,142]. Thus, the challenge for managers would be to try to incorporate technological innovations that, on the one hand, make the company’s internal processes and operations more efficient and, on the other hand, improve customer experience, satisfaction, and trust, while contributing to a healthier and more sustainable environment.

6. Conclusions and Future Work

According to the customer value paradigm [86], customer perceived value is a more holistic approach than simply focusing on service quality or customer satisfaction [24,145,146,147]. In a market as competitive as the express parcel market in the B2B environment, competitors want to increase the value for their customers such that the experience of using their services is increasingly attractive [148]. Customer perceived value can be a critical factor in ensuring that users return to repurchase services on a regular basis from the same provider and to recommend them in different professional forums [17,42]. This study focuses on the various effects of customer perceived value or customer experience on express parcel services in the B2B sector.
In conclusion, our results show that for the customer experience to be memorable and for the customer to want to repurchase express parcel services from the same provider, the customer’s perceived value should be increased. At the same time, this increase in perceived value positively influences the customer’s perceived satisfaction and trust during their service experience [149]. Similarly, this lowers the likelihood of a customer switching providers, positively favoring the customer’s intention to repurchase and even recommend a service to third parties [112]. Companies wishing to increase the value perceived by the customer should have a system of indicators that measure customer experiences and their impact on the purchase of services or products [3]. Only by taking a proactive business management approach to customer perceived value when measuring customer experiences and acting on the relationships of these metrics to purchase will it be possible to deliver a superior customer experience. However, the failure to evaluate customer perceived value can facilitate market entry for competitors, and customers may seek new suppliers that offer a better customer experience.
Our research analyzes the effects of customer experience or CPV in the B2B express parcel sector. However, the sample of companies evaluated is limited and multisectoral. In future research, it would be interesting to compare whether the effect of VPC on the intention to repurchase and recommend express delivery services varies according to the business sector of the client companies. Similarly, it would be necessary to compare whether there are differences between companies that have an ecommerce model and those that have a traditional business model. In addition, there are other variables that influence repurchase and recommendation intention in the B2B express parcel sector, such as the the company’s business volume, its geographical scope, or whether it is a service or product provider, that should be explored in future research.

Author Contributions

All authors conceived the study, designed the questionnaire, and wrote the initial manuscript. C.C. collected the data. D.A. analyzed the data, wrote the results, and provided critical revisions on the successive drafts. I.C. provided critical revisions, reorganized the linking and definitions of the variables, analyses, and findings. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation, to any qualified researcher.

Conflicts of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

  1. Setiyawati, S.; Haryanto, B. Why Customers Intend to Use Express Delivery Services? Case Stud. Bus. Manag. Macrothink Inst. 2016, 3, 56–81. [Google Scholar] [CrossRef] [Green Version]
  2. Donthu, N.; Gustafsson, A. Effects of COVID-19 on business and research. J. Bus. Res. 2020, 117, 284–289. [Google Scholar] [CrossRef] [PubMed]
  3. Lemon, K.N.; Verhoef, P.C. Understanding customer experience throughout the customer journey. J. Mark. 2016, 80, 69–96. [Google Scholar] [CrossRef]
  4. Kemper, J.A.; Ballantine, P.W. What do we mean by sustainability marketing? J. Mark. Manag. 2019, 35, 277–309. [Google Scholar] [CrossRef]
  5. Nguyen, H.T.; Nguyen, H.; Nguyen, N.D.; Phan, A.C. Determinants of customer satisfaction and loyalty in Vietnamese life-insurance setting. Sustainability 2018, 10, 1151. [Google Scholar] [CrossRef] [Green Version]
  6. DBK INFORMA Observatorio Sectorial. Available online: https://www.dbk.es/es/estudios/15533/summary (accessed on 1 July 2020).
  7. Pettersson, A.I.; Segerstedt, A. Measuring supply chain cost. Int. J. Prod. Econ. 2013, 143, 357–363. [Google Scholar] [CrossRef]
  8. Schniederjans, A.; Schniederjans, D.; Schniederjans, M. Outsourcing Management Information System; IGI Global: Hershey, PA, USA, 2006. [Google Scholar]
  9. König, A.; Spinler, S. The effect of logistics outsourcing on the supply chain vulnerability of shippers. Int. J. Logist. Manag. 2016, 27, 122–141. [Google Scholar] [CrossRef]
  10. Ortiz, S.M. Entre regulación y competencia: Revisión institucional de la Comisión Nacional de los Mercados y la Competencia CNMC. Ph.D. Thesis, Complutense University of Madrid, Madrid, Spain, 2014. [Google Scholar]
  11. Lashley, C.; Chibili, M.N. Pocket Guide for Hospitality Managers, 1st ed.; Noordhoff Uitgevers: Groningen, The Netherlands, 2019. [Google Scholar]
  12. Rauyruen, P.; Miller, K.E. Relationship quality as a predictor of B2B customer loyalty. J. Bus. Res. 2007, 60, 21–31. [Google Scholar] [CrossRef]
  13. Čater, B.; Čater, T. Relationship-value-based antecedents of customer satisfaction and loyalty in manufacturing. JBIM 2009, 24, 585–597. [Google Scholar] [CrossRef]
  14. McGahan, A.M.; Porter, M.E. How much does industry matter, really? SMJ 1997, 18, 15–30. [Google Scholar] [CrossRef]
  15. McGahan, A.M. Competition, Strategy, and Business Performance. CMR 1999, 41, 74–101. [Google Scholar] [CrossRef]
  16. Saad, A.T. Factors affecting online food delivery service in Bangladesh: An empirical study. Br. Food J. 2020, 123, 535–550. [Google Scholar] [CrossRef]
  17. Boon-itt, S. Managing self-service technology service quality to enhance e-satisfaction. Int. J. Qual. Serv. Sci. 2015, 7, 373–391. [Google Scholar] [CrossRef]
  18. Parasuraman, A.; Zeithaml, V.A.; Berry, L.L. Servqual: A multiple-item scale for measuring consumer perceptions of service quality. J. Retail. 1988, 64, 12–40. [Google Scholar]
  19. Stolze, H.J.; Mollenkopf, D.A.; Flint, D.J. What is the right supply chain for your shopper? Exploring the shopper service ecosystem. J. Bus. Logist. 2016, 37, 185–197. [Google Scholar] [CrossRef]
  20. Christopher, M.; Payne, A.; Ballantyne, D. Relationship Marketing; Taylor & Francis: Oxford, UK, 2013. [Google Scholar]
  21. Huber, F.; Herrmann, A.; Morgan, R.E. Gaining competitive advantage through customer value oriented management. JCM 2001, 18, 41–53. [Google Scholar] [CrossRef]
  22. Polas, R.H.; Imtiaz, M.; Saboor, A.; Hossain, N.; Javed, M.A.; Nianyu, L. Assessing the Perceived Value of Customers for being Satisfied towards the Sustainability of Hypermarket in Malaysia. Int. J. Bus. Econ. Manag. 2019, 6, 248–263. [Google Scholar] [CrossRef]
  23. Day, R.H.; Huang, W. Bulls, bears and market sheep. J. Econ. Behav. Organ. 1990, 14, 299–329. [Google Scholar] [CrossRef]
  24. Woodruff, R.B. Customer value: The next source for competitive advantage. J. Acad. Mark. Sci. 1997, 25, 139–153. [Google Scholar] [CrossRef]
  25. Gounaris, S.P.; Tzempelikos, N.A.; Chatzipanagiotou, K. The relationships of customer-perceived value, satisfaction, loyalty and behavioral intentions. J. Relatsh. Mark. 2007, 6, 63–87. [Google Scholar] [CrossRef]
  26. Gounaris, S. Measuring service quality in B2B services: An evaluation of the SERVQUAL scale vis-à-vis the INDSERV scale. J. Relatsh. Mark. 2005, 19, 421–435. [Google Scholar] [CrossRef] [Green Version]
  27. Han, H.; Hyun, S.S. Customer retention in the medical tourism industry: Impact of quality, satisfaction, trust and price reasonableness. Tour. Manag. 2015, 46, 20–29. [Google Scholar] [CrossRef]
  28. Mbango, P. The role of perceived value in promoting customer satisfaction: Antecedents and consequences. Cogent Soc. Sci. 2019, 5, 1684229. [Google Scholar] [CrossRef]
  29. Pine, B.J.; Gilmore, J.H. The Experience Economy; Harvard University Press: Cambridge, MA, USA, 1999. [Google Scholar]
  30. Helkkula, A.; Kelleher, C. Circularity of customer service experience and customer perceived value. J. Cust. Behav. 2010, 9, 37–53. [Google Scholar] [CrossRef]
  31. Itani, O.S.; Kassar, A.N.; Loureiro, S.M.C. Value get, value give: The relationships among perceived value, relationship quality, customer engagement, and value consciousness. Int. J. Hosp. Manag. 2019, 80, 78–90. [Google Scholar] [CrossRef]
  32. Arnould, E.J.; Thompson, C.J. Consumer culture theory (CCT): Twenty years of research. J. Consum. Res. 2005, 31, 868–882. [Google Scholar] [CrossRef] [Green Version]
  33. Jin, N.; Line, N.D.; Goh, B. Experiential value, relationship quality, and customer loyalty in full-service restaurants: The moderating role of gender. J. Hosp. Mark. Manag. 2013, 22, 679–700. [Google Scholar] [CrossRef]
  34. Chen, C.F.; Chen, F.S. Experience quality, perceived value, satisfaction and behavioral intentions for heritage tourists. Tour. Manag. 2010, 31, 29–35. [Google Scholar] [CrossRef]
  35. Hussein, A.S.; Hapsari, R.D.V.; Yulianti, I. Experience quality and hotel boutique customer loyalty: Mediating role of hotel image and perceived value. J. Qual. Assur. Hosp. Tour. 2018, 19, 442–459. [Google Scholar] [CrossRef]
  36. Wu, C.H.J.; Liang, R.D. Effect of experiential value on customer satisfaction with service encounters in luxury-hotel restaurants. Int. J. Hosp. Manag. 2009, 28, 586–593. [Google Scholar] [CrossRef]
  37. Kozinets, R.V.; Sherry, J.F.; DeBerry-Spence, B.; Duhachek, A.; Nuttavuthisit, K.; Storm, D. Themed flagship brand stores in the new millennium: Theory, practice, prospects. J. Retail. 2002, 78, 17–29. [Google Scholar] [CrossRef]
  38. Mathwick, C.; Malhotra, N.; Rigdon, E. Experiential value: Conceptualization, measurement and application in the catalog and Internet shopping environment. J. Retail. 2001, 77, 39–56. [Google Scholar] [CrossRef]
  39. Mitchell, A. Rethink brand experience. Brand Strategy 2003, 174, 40. [Google Scholar]
  40. Poulsson, S.H.; Kale, S.H. The experience economy and commercial experiences. TMR 2004, 4, 267–277. [Google Scholar] [CrossRef]
  41. Sam, T.; Dhanya, A. Impact of product quality, service quality and contextual experience on customer perceived value and future buying intentions. EJBMR 2012, 3, 307–315. [Google Scholar]
  42. Pham, Q.T.; Tran, X.P.; Misra, S.; Maskeliūnas, R.; Damaševičius, R. Relationship between convenience, perceived value, and repurchase intention in online shopping in Vietnam. Sustainability 2018, 10, 156. [Google Scholar] [CrossRef] [Green Version]
  43. Wu, L.Y.; Chen, K.Y.; Chen, P.Y.; Cheng, S.L. Perceived value, transaction cost, and repurchase-intention in online shopping: A relational exchange perspective. J. Bus. Res. 2014, 67, 2768–2776. [Google Scholar] [CrossRef]
  44. Ruiz, D.M.; Gremler, D.D.; Washburn, J.H.; Carrión, G.C. Service value revisited: Specifying a higher-order, formative measure. J. Bus. Res. 2008, 61, 1278–1291. [Google Scholar] [CrossRef]
  45. Wang, Y.; Po Lo, H.; Chi, R.; Yang, Y. An integrated framework for customer value and customer-relationshipmanagement performance: A customer-based perspective from China. Manag. Serv. Qual. Int. J. 2004, 14, 169–182. [Google Scholar] [CrossRef]
  46. Minarti, S.N.; Segoro, W. The influence of customer satisfaction, switching cost and trusts in a brand on customer loyalty—The survey on student as IM3 users in Depok, Indonesia. Procedia Soc. Behav. Sci. 2014, 143, 1015–1019. [Google Scholar] [CrossRef] [Green Version]
  47. Leninkumar, V. The relationship between customer satisfaction and customer trust on customer loyalty. IJARBSS 2017, 7, 450–465. [Google Scholar] [CrossRef]
  48. Chiou, J.; Droge, C. Service quality, trust, specific asset investment, and expertise: Direct andindirect effects in a satisfaction-loyalty framework. J. Acad. Mark. Sci. 2006, 34, 613–627. [Google Scholar] [CrossRef]
  49. Santini, F.D.O.; Ladeira, W.J.; Sampaio, C.H. The role of satisfaction in fashion marketing: A meta-analysis. J. Glob. Fash. Mark. 2018, 9, 305–321. [Google Scholar] [CrossRef]
  50. Amin, M. Internet banking service quality and its implication on e-customer satisfaction and e-customer loyalty. Int. J. Bank Mark. 2016, 34, 280–306. [Google Scholar] [CrossRef]
  51. Oliver, R.L. Measurement and evaluation of satisfaction processes in retail settings. J. Retail. 1981, 57, 25–48. [Google Scholar]
  52. Anderson, E.W.; Fornell, C.; Lehmann, D.R. Customer satisfaction, market share, and profitability: Findings from Sweden. J. Mark. 1994, 58, 53–66. [Google Scholar] [CrossRef]
  53. Sweeney, J.C.; Soutar, G.N. Consumer perceived value: The development of a multiple item scale. J. Retail. 2001, 77, 203–220. [Google Scholar] [CrossRef]
  54. Otsetova, A.; Enimanev, K. A Study on Customer Satisfaction of Courier Services in Bulgaria. Int. J. Entrep. Innov. 2014, 6, 70–82. [Google Scholar]
  55. Otsetova, A. Relationship between logistics service quality, customer satisfaction and loyalty in courier services industry. Manag. Educ. 2017, 13, 51–64. [Google Scholar]
  56. Kesari, B.; Atulkar, S. Satisfaction of mall shoppers: A study on perceived utilitarian and hedonic shopping values. J. Retail. Consum. Serv. 2016, 31, 22–31. [Google Scholar] [CrossRef]
  57. El-Adly, M.I. Modelling the relationship between hotel perceived value, customer satisfaction, and customer loyalty. J. Retail. Consum. Serv. 2019, 50, 322–332. [Google Scholar] [CrossRef]
  58. Chand, M. The impact of HRM practices on service quality, customer satisfaction and performance in the Indian hotel industry. Int. J. Hum. Resour. Manag. 2010, 21, 551–566. [Google Scholar] [CrossRef]
  59. Dhar, R.L. Service quality and the training of employees: The mediating role of organizational commitment. Tour. Manag. 2015, 46, 419–430. [Google Scholar] [CrossRef]
  60. Wikhamn, W. Innovation, sustainable HRM and customer satisfaction. Int. J. Hosp. Manag. 2019, 76, 102–110. [Google Scholar] [CrossRef]
  61. Lu, B.; Fan, W.; Zhou, M. Social presence, trust, and social commerce purchase intention: An empirical research. Comput. Hum. Behav. 2016, 56, 225–237. [Google Scholar] [CrossRef] [Green Version]
  62. Wang, Y.; Min, Q.; Han, S. Understanding the effects of trust and risk on individual behavior toward social media platforms: A meta-analysis of the empirical evidence. Comput. Hum. Behav. 2016, 56, 34–44. [Google Scholar] [CrossRef]
  63. Anderson, J.C.; Narus, J.A. A model of distributor firm and manufacturer firm working partnerships. J. Mark. 1990, 54, 42–58. [Google Scholar] [CrossRef]
  64. Moorman, C.; Deshpande, R.; Zaltman, G. Factors affecting trust in market research relationships. J. Mark. 1993, 57, 81–101. [Google Scholar] [CrossRef] [Green Version]
  65. Ganesan, S. Determinants of long-term orientation in buyer-seller relationships. J. Mark. 1994, 58, 1–19. [Google Scholar] [CrossRef]
  66. Morgan, R.; Hunt, S. The commitment-trust theory of relationships marketing. J. Mark. 1994, 58, 20–38. [Google Scholar] [CrossRef]
  67. Anderson, E.; Weitz, B. The use of pledges to build and sustain commitment in distribution channels. J. Mark. Res. 1992, 29, 18–34. [Google Scholar] [CrossRef]
  68. Askariazad, M.H.; Babakhani, N. An application of European Customer Satisfaction Index (ECSI) in Business to Business (B2B) Context. J. Bus. Ind. Mark. 2015, 30, 17–31. [Google Scholar] [CrossRef]
  69. Chai, L.; Li, J.; Tangpong, C.; Clauss, T. The interplays of coopetition, conflicts, trust, and efficiency process innovation in vertical B2B relationships. Ind. Mark. Manag. 2020, 85, 269–280. [Google Scholar] [CrossRef]
  70. Milan, G.S.; Eberle, L.; Bebber, S. Perceived value, reputation, trust, and switching costs as determinants of customer retention. J. Relatsh. Mark. 2015, 14, 109–123. [Google Scholar] [CrossRef]
  71. McKnight, D.H.; Lankton, N.K.; Nicolaou, A.; Price, J. Distinguishing the effects of B2B information quality, system quality, and service outcome quality on trust and distrust. J. Strat. Inf. Syst. 2017, 26, 118–141. [Google Scholar] [CrossRef]
  72. Haghkhah, A.; Rasoolimanesh, S.M.; Asgari, A.A. Effects of Customer Value And Service Quality on Customer Loyalty: Mediation Role of Trust and Commitment in Business-To-Business Context. Manag. Res. Pr. 2020, 12, 27–47. [Google Scholar]
  73. Blut, M.; Evanschitzky, H.; Backhaus, C.; Rudd, J.; Marck, M. Securing business-to-business relationships: The impact of switching costs. Ind. Mark. Manag. 2016, 52, 82–90. [Google Scholar] [CrossRef] [Green Version]
  74. Burnham, T.A.; Frels, J.K.; Mahajan, V. Consumer switching costs: A typology, antecedents, and consequences. J. Acad. Mark. Sci. 2003, 31, 109–126. [Google Scholar] [CrossRef]
  75. Fandos Herrera, C.; Puyuelo Arilla, J.M. La generación de lealtad a un destino de turismo gastronómico como factor clave en el desarrollo rural. Cuad. Aragon. Econ. 2013, 23, 47–73. [Google Scholar]
  76. Lesmono, S.U.; Santoso, T.; Wijaya, S.; Jie, F. The Effect of Switching Cost and Product Return Management on Repurchase Intent: A Case Study in the B2B Distribution Channel Context in Indonesia. Int. J. Supply Chain Manag. 2020, 9, 44–53. [Google Scholar]
  77. Padgett, D.; Hopkins, C.D.; Williams, Z. Buyer dependence in B2B relationships: The role of supplier investments, commitment form, and trust. J. Bus. Res. 2020, 119, 13–24. [Google Scholar] [CrossRef]
  78. Kuo, Y.; Hu, T.; Yang, S. Effects of inertia and satisfaction in female online shoppers on repeat-purchase intention: The moderating roles of word-of-mouth and alternative attraction. Manag. Serv. Qual. Int. J. 2013, 23, 168–187. [Google Scholar] [CrossRef]
  79. Emami, J.; Lajevardi, M.; Fakharmanesh, S. An Integrated Model in Customer Loyalty Context: Relationship Quality and Relationship Marketing View. Aust. J. Basic Appl. Sci. 2013, 7, 399–407. [Google Scholar]
  80. Hellier, P.K.; Geursen, G.M.; Carr, R.A.; Rickard, J.A. Customer repurchase intention: A general structural equation model. Eur. J. Mark. 2003, 37, 1762–1800. [Google Scholar] [CrossRef] [Green Version]
  81. Chiu, C.M.; Lin, H.Y.; Sun, S.Y.; Hsu, M.H. Understanding customers’ loyalty intentions towards online shopping: An integration of technology acceptance model and fairness theory. Behav. Inf. Technol. 2009, 28, 347–360. [Google Scholar] [CrossRef]
  82. Seiders, K.; Voss, G.B.; Grewal, D.; Godfrey, A.L. Do satisfied customers buy more? Examining moderating influences in a retailing context. J. Mark. 2005, 69, 26–43. [Google Scholar] [CrossRef]
  83. Samad, A. Examining the impact of perceived service quality dimensions on repurchase intentions and word of mouth: A case from software industry of Pakistan. IOSR J. Bus. Manag. 2014, 16, 37–41. [Google Scholar] [CrossRef]
  84. Zeithaml, V.A.; Berry, L.L.; Parasuraman, A. The nature and determinants of customer expectations of service. J. Acad. Mark. Sci. 1993, 21, 1–12. [Google Scholar] [CrossRef] [Green Version]
  85. Zeithaml, V.A.; Berry, L.L.; Parasuraman, A. The behavioral consequences of service quality. J. Mark. 1996, 60, 31–46. [Google Scholar] [CrossRef]
  86. Gale, B.; Gale, B.T.; Wood, R.C. Managing Customer Value: Creating Quality and Service that Customers can See; Simon and Schuster: New York, NY, USA, 1994. [Google Scholar]
  87. Lin, L.; Chen, Y. A study on the influence of purchase intentions on repurchase decisions: The moderating effects of reference groups and perceived risks. Tour. Rev. 2009, 64, 28–48. [Google Scholar] [CrossRef]
  88. Irshad, S. Mediating role of customer value between Innovative Self-Service Technology (ISST) factors and online repurchase intention. J. Internet Bank. Commer. 2016, 21, 1–18. [Google Scholar]
  89. Suryadi, N.; Suryana, Y.; Komaladewi, R.; Sari, D. Consumer, customer and perceived value: Past and present. Acad. Strat. Manag. J. 2018, 17, 1–9. [Google Scholar]
  90. Chou, S.; Chen, C.W. The influences of relational benefits on repurchase intention in service contexts: The roles of gratitude, trust and commitment. J. Bus. Ind. Mark. 2018, 33, 680–692. [Google Scholar] [CrossRef]
  91. Doan, M.T.M. The factors affect organization customer perceived value and repurchase intention-A empirical study of professional B2B general insurance service in Vietnam. Ph.D. Thesis, International University-HCMC, Ho Chi Minh City, Vietnam, 2017. [Google Scholar]
  92. Chen, Y.; Yu, J.; Yang, S.; Wei, J. Consumer’s intention to use self-service parcel delivery service in online retailing: An empirical study. Internet Res. 2018, 28, 500–519. [Google Scholar] [CrossRef]
  93. Garver, M.S.; Williams, Z.; Goffnett, S.P.; Gibson, B.J. Parcel shipping: Understanding the needs of business shippers. J. Transp. Manag. 2016, 26, 29–46. [Google Scholar] [CrossRef]
  94. Wang, C.Y. Investigating antecedents of consumers’ recommend intentions and the moderating effect of switching barriers. Serv. Ind. J. 2009, 29, 1231–1241. [Google Scholar] [CrossRef]
  95. Brown, S.W.; Cowles, D.L.; Tuten, T.L. Service recovery: Its value and limitations as a retail strategy. Int. J. Serv. Ind. Manag. 1996, 32–46. [Google Scholar] [CrossRef]
  96. Lang, B. How word of mouth communication varies across service encounters. Manag. Serv. Qual. 2011, 21, 583–598. [Google Scholar] [CrossRef]
  97. Chawdhary, R.; Dall’Olmo Riley, F. Investigating the consequences of word of mouth from a WOM sender’s perspective in the services context. J. Mark. Manag. 2015, 31, 1018–1039. [Google Scholar] [CrossRef] [Green Version]
  98. Simpson, P.M.; Siguaw, J.A. Destination Word of Mouth: The Role of Traveler Type, Residents, and Identity Salience. J. Travel Res. 2008, 47, 167–182. [Google Scholar] [CrossRef]
  99. Belvisi, M.; Pianeti, R.; Urga, G. Modelling Financial Markets Comovements during Crises: A Dynamic Multi-Factor Approach. Adv. Econ. 2016, 35, 317–360. [Google Scholar] [CrossRef] [Green Version]
  100. Reyes-Menendez, A.; Saura, J.R.; Martinez-Navalon, J.G. The impact of e-WOM on hotels management reputation: Exploring tripadvisor review credibility with the ELM model. IEEE Access 2019, 7, 68868–68877. [Google Scholar] [CrossRef]
  101. Chai, J.C.Y.; Malhotra, N.K.; Alpert, F. A two-dimensional model of trust-value-loyalty in service relationships. J. Retail. Consum. Serv. 2015, 26, 23–31. [Google Scholar] [CrossRef]
  102. Jones, K.; Leonard, L.N. Factors Influencing Buyer’s Trust in Consumer-to-Consumer E Commmerce. J. Comput. Inf. Syst. 2014, 54, 71–79. [Google Scholar] [CrossRef]
  103. Roy, S.K. Consequences of customer advocacy. J. Strat. Mark. 2013, 21, 260–276. [Google Scholar] [CrossRef]
  104. Javed, F.; Cheema, S. Customer satisfaction and customer perceived value and its impact on customer loyalty: The mediational role of customer relationship management. J. Internet Bank. Commer. 2017, 22, 1–14. [Google Scholar]
  105. Nyadzayo, M.W.; Khajehzadeh, S. The antecedents of customer loyalty: A moderated mediation model of customer relationship management quality and brand image. J. Retail. Consum. Serv. 2016, 30, 262–270. [Google Scholar] [CrossRef]
  106. Taylor, S.A.; Baker, T.L. An assessment of the relationship between service quality and customer satisfaction in the formation of consumers’ purchase intentions. J. Retail. 1994, 70, 163–178. [Google Scholar] [CrossRef]
  107. Oliver, R.L. A cognitive model of the antecedents and consequences of satisfaction decision. J. Mark. Res. 1980, 17, 460–469. [Google Scholar] [CrossRef]
  108. Awan, S.; Cheng, Y. Improve Communication Quality by Understanding Customer Switching Behavior in China’s Telecom Sector. Ibusiness 2016, 8, 70–83. [Google Scholar] [CrossRef] [Green Version]
  109. Inman, J.J.; Nikolova, H. Shopper-facing retail technology: A retailer adoption decision framework incorporating shopper attitudes and privacy concerns. J. Retail. 2017, 93, 7–28. [Google Scholar] [CrossRef]
  110. Sullivan, Y.W.; Kim, D.J. Assessing the effects of consumers’ product evaluations and trust on repurchase intention in e-commerce environments. Int. J. Inf. Manag. 2018, 39, 199–219. [Google Scholar] [CrossRef]
  111. Song, H.; Wang, J.; Han, H. Effect of image, satisfaction, trust, love, and respect on loyalty formation for name-brand coffee shops. Int. J. Hosp. Manag. 2019, 79, 50–59. [Google Scholar] [CrossRef]
  112. Mensah, I.; Mensah, R.D. Effects of Service Quality and Customer Satisfaction on Repurchase Intention in Restaurants on University of Cape Coast Campus. JTHSM 2018, 4, 27–36. [Google Scholar] [CrossRef]
  113. Nghia, H.T.; Olsen, S.O.; Trang, N.T.M. Shopping value, trust, and online shopping well-being: A duality approach. Mark. Intell. Plan. 2020, 38, 545–558. [Google Scholar] [CrossRef]
  114. Moradi, B.; Maroofi, F.; Ahmadizad, A. The investigating of cognitive and affective two-dimensional pattern between consumer trust, perceived value and behavioral loyalty in Iran governmental and non-governmental insurance areas. Bankacılık Ve Sigortacılık Araştırmaları Derg. 2017, 2, 21–35. [Google Scholar]
  115. Bustamam, N.M. Does Re-Enroll Intention Mediate Relationship Between Perceived Value, Student Satisfaction and Advocacy Behavior? A Perspective of Private Higher Education. IJARES 2020, 2, 130–141. [Google Scholar]
  116. Rigdon, E.E. Choosing PLS path modeling as analytical method in European management research: A realist perspective. Eur. Manag. J. 2016, 34, 598–605. [Google Scholar] [CrossRef]
  117. Henseler, J. Bridging design and behavioral research with variance-based structural equation modeling. J. Advert. 2017, 46, 178–192. [Google Scholar] [CrossRef]
  118. Rigdon, E.E.; Sarstedt, M.; Ringle, C.M. On comparing results from CB-SEM and PLS-SEM: Five perspectives and five recommendations. Mark. ZFP 2017, 39, 4–16. [Google Scholar] [CrossRef]
  119. Hair, J.F.; Risher, J.J.; Sarstedt, M.; Ringle, C.M. When to use and how to report the results of PLS-SEM. Eur. Bus. Rev. 2019, 31, 2–24. [Google Scholar] [CrossRef]
  120. Henseler, J. Partial least squares path modeling: Quo vadis? Qual. Quant. 2018, 52, 1–8. [Google Scholar] [CrossRef] [Green Version]
  121. Becker, A.; Deckers, T.; Dohmen, T.; Falk, A.; Kosse, F. The relationship between economic preferences and psychological personality measures. Annu. Rev. Econ. 2012, 4, 453–478. [Google Scholar] [CrossRef] [Green Version]
  122. Chin, W.W. Bootstrap cross-validation indices for PLS path model assessment. In Handbook of Partial Least Squares; Springer: Berlin/Heidelberg, Germany, 2010; pp. 83–97. [Google Scholar]
  123. Ringle, C.M.; Wende, S.; Becker, J.M. SmartPLS 3 [Software]; SmartPLS: Bönningstedt, Germany, 2015. [Google Scholar]
  124. Nitzl, C.; Roldán, J.L.; Cepeda, G. Mediation analyses in partial least squares structural equation modeling: Helping researchers discuss more sophisticated models. Ind. Manag. Data Syst. 2016, 116, 1849–1864. [Google Scholar] [CrossRef]
  125. Cepeda-Carrión, G.; Nitzl, C.; Roldán, J.L. Mediation analyses in partial least squares structural equation modeling: Guidelines and empirical examples. In Partial Least Squares Path Modeling; Springer: Cham, Switzerland, 2017; pp. 173–195. [Google Scholar]
  126. Hair, J.F., Jr.; Hult, G.T.M.; Ringle, C.; Sarstedt, M. A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM); Sage Publications: Thousand Oaks, CA, USA, 2016. [Google Scholar]
  127. Henseler, J.; Hubona, G.; Ray, P.A. Using PLS path modeling in new technology research: Updated guidelines. Ind. Manag. Data Syst. 2016, 116, 2–20. [Google Scholar] [CrossRef]
  128. Fornell, C.; Larcker, D.F. Structural equation models with unobservable variables and measurement error: Algebra and statistics. J. Mark. Res. 1981, 18, 382–388. [Google Scholar] [CrossRef]
  129. Barclay, D.; Thompson, R.; Higgins, C. The Partial Least Squares (PLS) approach to causal modeling: Personal computer adoption and use as an illustration. Technol. Stud. 1995, 2, 285–309. [Google Scholar]
  130. Hair, J.F.; Ringle, C.M.; Sarstedt, M. PLS-SEM: Indeed a silver bullet. J. Mark. Pract. 2011, 19, 139–151. [Google Scholar] [CrossRef]
  131. Hair, J.F., Jr.; Sarstedt, M.; Hopkins, L.; Kuppelwieser, G.V. Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. Eur. Bus. Rev. 2014, 26, 106–121. [Google Scholar] [CrossRef]
  132. Yang, Z.; Peterson, R.T. Customer perceived value, satisfaction, and loyalty: The role of switching costs. Psychol. Mark. 2004, 21, 799–822. [Google Scholar] [CrossRef] [Green Version]
  133. Fornell, C. A national customer satisfaction barometer: The Swedish experience. J. Mark. 1992, 56, 6–21. [Google Scholar] [CrossRef]
  134. Lee, J.; Lee, J.; Feick, L. The impact of switching costs on the customer satisfaction-loyalty link: Mobile phone service in France. J. Serv. Mark. 2001, 15, 35–48. [Google Scholar] [CrossRef]
  135. Oliver, R.L. Whence Consumer Loyalty? J. Mark. 1999, 63, 33–44. [Google Scholar] [CrossRef]
  136. Neal, W.D. Satisfaction is nice, but value drives loyalty. Mark. Res. 1999, 11, 21–23. [Google Scholar]
  137. Sharma, N.; Patterson, P.G. Switching costs, alternative attractiveness and experience as moderators of relationship commitment in professional, consumer services. Int. J. Serv. Ind. Manag. 2000, 11, 470–490. [Google Scholar] [CrossRef]
  138. Bolton, R.N.; Lemon, K.N. A dynamic model of customers’ usage of services: Usage as an antecedent and consequence of satisfaction. J. Mark. Res. 1999, 36, 171–186. [Google Scholar] [CrossRef] [Green Version]
  139. Ram, S.; Jung, H.S. How product usage influences consumer satisfaction. Mark. Lett. 1991, 2, 403–411. [Google Scholar] [CrossRef]
  140. Hadi, N.U.; Aslam, N.; Gulzar, A. Sustainable service quality and customer loyalty: The role of customer satisfaction and switching costs in the Pakistan cellphone industry. Sustainability 2019, 11, 2408. [Google Scholar] [CrossRef] [Green Version]
  141. Nenadál, J.; Vykydal, D.; Tylečková, E. Complex Customer Loyalty Measurement at Closed-Loop Quality Management in B2B Area—Czech Example. Sustainability 2021, 13, 2957. [Google Scholar] [CrossRef]
  142. Strenitzerová, M.; Gaňa, J. Customer satisfaction and loyalty as a part of customer-based corporate sustainability in the sector of mobile communications services. Sustainability 2018, 10, 1657. [Google Scholar] [CrossRef] [Green Version]
  143. Heinonen, K.; Strandvik, T. Reframing service innovation: COVID-19 as a catalyst for imposed service innovation. J. Serv. Manag. 2020, 32, 101–112. [Google Scholar] [CrossRef]
  144. Shin, Y.J.; Lee, J.Y. South Korea’s proactive approach to the COVID-19 global crisis. Psychol. Trauma. 2020, 12, 475–477. [Google Scholar] [CrossRef] [PubMed]
  145. Vargo, S.L.; Lusch, R.F. Evolving to a new dominant logic for marketing. J. Mark. 2004, 68, 1–17. [Google Scholar] [CrossRef] [Green Version]
  146. Eggert, A.; Ulaga, W. Customer perceived value: A substitute for satisfaction in business markets? J. Bus. Ind. Mark. 2002, 17, 107–118. [Google Scholar] [CrossRef]
  147. Agnihotri, R.; Dingus, R.; Hu, M.Y.; Krush, M.T. Social media: Influencing customer satisfaction in B2B sales. Ind. Mark. Manag. 2016, 53, 172–180. [Google Scholar] [CrossRef]
  148. Roy, S.; Sreejesh, S.; Bhatia, S. Service quality versus service experience: An empirical examination of the consequential effects in B2B services. Ind. Mark. Manag. 2019, 82, 52–69. [Google Scholar] [CrossRef]
  149. Chung, M.; Ko, E.; Joung, H.; Kim, S.J. Chatbot e-service and customer satisfaction regarding luxury brands. J. Bus. Res. 2020, 117, 587–595. [Google Scholar] [CrossRef]
Sustainability 13 06013 g001 550
Figure 1. Research proposed model of customer perceived value, satisfaction, trust, switching costs, repurchase intention, and advocacy intention.
Figure 1. Research proposed model of customer perceived value, satisfaction, trust, switching costs, repurchase intention, and advocacy intention.
Sustainability 13 06013 g001
Sustainability 13 06013 g002 550
Figure 2. Research proposed model. H1: Direct effect: CPV → Satisfaction (β = 0.662, p < 0.001); H2: Direct effect: CPV → Trust (β = 0.418, p < 0.001); H3: Direct effect: Satisfaction → Trust (β = 0.496, p < 0.001); H4: Direct effect: CPV → Switching Costs (β = 0.355, p < 0.001); H5: Direct effect: Satisfaction → Switching Costs (β = 0.516, p < 0.001); H6: Direct effect: Switching Costs → Repurchase Intention (β = 0.450, p < 0.001); H7: Direct effect: Trust → Repurchase Intention (β = 0.272, p < 0.01); H8: Indirect effect: CPV → Trust → Repurchase Intention (β = 0.173, p < 0.01); H9: Direct effect: Repurchase Intention → Advocacy Intention (β = 0.714, p < 0.001); H10: Indirect effect: CPV → Trust → Repurchase Intention → Advocacy Intention (β = 0.123, p < 0.01).
Figure 2. Research proposed model. H1: Direct effect: CPV → Satisfaction (β = 0.662, p < 0.001); H2: Direct effect: CPV → Trust (β = 0.418, p < 0.001); H3: Direct effect: Satisfaction → Trust (β = 0.496, p < 0.001); H4: Direct effect: CPV → Switching Costs (β = 0.355, p < 0.001); H5: Direct effect: Satisfaction → Switching Costs (β = 0.516, p < 0.001); H6: Direct effect: Switching Costs → Repurchase Intention (β = 0.450, p < 0.001); H7: Direct effect: Trust → Repurchase Intention (β = 0.272, p < 0.01); H8: Indirect effect: CPV → Trust → Repurchase Intention (β = 0.173, p < 0.01); H9: Direct effect: Repurchase Intention → Advocacy Intention (β = 0.714, p < 0.001); H10: Indirect effect: CPV → Trust → Repurchase Intention → Advocacy Intention (β = 0.123, p < 0.01).
Sustainability 13 06013 g002
Table
Table 1. Indicator loadings and items of used scales.
Table 1. Indicator loadings and items of used scales.
Item Scales 1REPADVSATSCCPVTRU
I will probably use my express delivery provider again.0.899
I have the intention to purchase the services of my express delivery provider in the future.0.912
I may use my express delivery provider’s services very frequently in the future.0.912
I will say positive things about my express delivery provider to other people. 0.939
I will recommend my express delivery provider to other people who ask me. 0.933
I will encourage friends and family to do business with my express delivery supplier. 0.874
I am satisfied with the services of my express delivery provider. 0.873
Overall, I am satisfied when using the services of my express delivery provider. 0.921
Using the services of this express delivery provider is a satisfying experience. 0.910
My choice to use my express delivery provider was the right one. 0.942
Overall, I am satisfied with my express delivery supplier. 0.917
I believe I made the right decision in choosing to rely on my express delivery provider for my service needs. 0.896
Certainly if I switch to another express delivery provider it probably would not be as good as the current one. 0.770
I am not sure if switching to another express delivery provider would be good for me. 0.706
I already know the staff; changing express delivery providers would be like starting from scratch. 0.720
My express delivery supplier has a strong social reputation. 0.712
My express delivery provider’s employees are available to help my company achieve my objectives. 0.874
My express delivery supplier’s employees are available to add value to my business. 0.898
My express delivery supplier’s employees are available to help improve my company’s sales and image. 0.915
I am satisfied with my express delivery supplier’s level of innovation and leadership position in their field. 0.789
In our relationship, I can always rely on my express delivery supplier. 0.905
In our relationship, my express delivery supplier always gets it right. 0.911
In our relationship, my express delivery supplier has high reliability and integrity. 0.911
1 Notes: REP: repurchase; ADV: advocacy; SAT: customer satisfaction; SC: switching cost; CPV: customer perceived value; TRU: trust.
Table
Table 2. Descriptive statistics, reliability, and AVEs of the constructs.
Table 2. Descriptive statistics, reliability, and AVEs of the constructs.
Scales 1MeanSDCARho ACRAVE
REP5.1451.3110.8930.8930.9340.824
ADV5.0361.3120.9050.9360.9400.838
SAT5.1981.1060.9580.9600.9670.828
SC4.6961.4140.7070.7120.8180.529
CPV4.6261.3930.8920.8920.9260.758
TRU4.7351.2510.8950.8960.9340.826
1 Notes: Mean = the average score for all the items included in this measure; SD = standard deviation; CA = Cronbach’s alpha; CR = composite reliability; AVE = average variance extracted; REP: repurchase; ADV: advocacy; SAT: customer satisfaction; SC: switching cost; CPV: customer perceived value; TRU: trust.
Table
Table 3. Discriminant validity. Heterotrait-monotrait ratio (HTMT).
Table 3. Discriminant validity. Heterotrait-monotrait ratio (HTMT).
Scales 1REPADVSATSCCPV
REP−
ADV0.778−
SAT0.8250.790−
SC0.6830.7220.722−
CPV0.5340.6240.7080.853−
TRU0.6740.6750.8330.7750.830
1 Notes: REP: repurchase; ADV: advocacy; SAT: customer satisfaction; SC: switching cost; CPV: customer perceived value; TRU: trust.
Table
Table 4. Construct effects on endogenous variables (including lower and upper limits of 97.5% confidence interval).
Table 4. Construct effects on endogenous variables (including lower and upper limits of 97.5% confidence interval).
Effects on Endogenous Variables 1Path Coeff.Confidence Intervals (97.5%)Significance of Effect
(p-Value)
2.5%CIlo97.5%CIhi
CPV → SAT (H1)0.6610.5620.759Yes (0.000)
CPV → TRU (H2)0.4170.2920.542Yes (0.000)
SAT → TRU (H3)0.4990.3430.655Yes (0.000)
CPV → SC (H4)0.2870.1200.454Yes (0.001)
SAT → SC (H5)0.4970.3560.639Yes (0.000)
SC → REP (H6)0.2960.1190.474Yes (0.001)
TRU → REP (H7)0.4140.2360.593Yes (0.000)
REP → ADV (H9)0.7140.6190.810Yes (0.000)
1 Notes: REP: repurchase; ADV: advocacy; SAT: customer satisfaction; SC: switching cost; CPV: customer perceived value; TRU: trust.
Table
Table 5. Construct effects on endogenous variables (including lower and upper limits of 97.5% confidence interval).
Table 5. Construct effects on endogenous variables (including lower and upper limits of 97.5% confidence interval).
Effects on Endogenous Variables 1Path Coeff.Confidence Intervals (97.5%)Significance of Effect (p-Value)
2.5%CIlo97.5%CIhi
CPV → TRU → REP (H8, Full mediation)0.1730.0950.250Yes (0.000)
CPV → TRU → REP → ADV (H10, Partial mediation)0.1230.0640.182Yes (0.000)
1 Notes: REP: repurchase; ADV: advocacy; SAT: customer satisfaction; SC: switching cost; CPV: customer perceived value; TRU: trust.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Correa, C.; Alarcón, D.; Cepeda, I. “I am Delighted!”: The Effect of Perceived Customer Value on Repurchase and Advocacy Intention in B2B Express Delivery Services. Sustainability 2021, 13, 6013. https://doi.org/10.3390/su13116013

AMA Style

Correa C, Alarcón D, Cepeda I. “I am Delighted!”: The Effect of Perceived Customer Value on Repurchase and Advocacy Intention in B2B Express Delivery Services. Sustainability. 2021; 13(11):6013. https://doi.org/10.3390/su13116013

Chicago/Turabian Style

Correa, Carlos, David Alarcón, and Ignacio Cepeda. 2021. "“I am Delighted!”: The Effect of Perceived Customer Value on Repurchase and Advocacy Intention in B2B Express Delivery Services" Sustainability 13, no. 11: 6013. https://doi.org/10.3390/su13116013

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop