Abstract
Beneficiaries of e-commerce growth are both companies and customers. E-commerce creates new opportunities for development for already existing entities and gives prospects for rapid growth to emerging ones. Customers can simply and quickly find products, compare them and choose the best one. Thanks to e-commerce, an additional value is created for the customers which is associated with a lower price of the product, convenience in the form of twenty-four hour access to e-shops, various methods of deliveries and possibility of product return. Logistics, then, plays a very important role in e-commerce. The logistics value is created not only by the online sellers but also by many other entities, such manufacturers, distributors, marketplaces, and logistics and couriers companies. They can be grouped into the following stakeholders: e-tailers, suppliers, complementors, as well as the final customers. All together are a part of the e-commerce value network. The aim of these studies is to determine the relationship between perceived logistics value, customer satisfaction and loyalty in e-commerce. For the needs of this paper, we scrutinized a random sample of 800 individuals representing retailers, customers, suppliers and complementors of e-commerce in Poland. To test this relationship, a discriminant analysis was performed to establish whether differences in perceptions exist between the e-commerce stakeholder groups.
Keywords: Repayment behaviourconscientiousnesspunishment avoidancesense of collectivismlocus of controldecision making style
Introduction
Thanks to the Internet, trade has become as easy and convenient as never before. Its beneficiaries
are both companies and customers. Almost each firm has the potential to become a successful trader
(WTO, 2016). E-commerce creates new opportunities for development for already existing entities and
gives prospects for rapid growth to emerging ones. It is possible thanks to low entry barriers that
encourage more and more companies to sell their products on the Internet. They can offer a wider range
of products without having to physically present them. Companies are able to save on both fixed and
variable costs, such as rent, labour and other overheads associated with physical presence in shopping
centers and bricks-and-mortar stores. In turn, customers can simply and quickly find products and
compare them. Moreover, they may buy new products, which they did not previously use due to their
unavailability in terms of location in distant places (e.g. goods from abroad), lack of time or a different
lifestyle. Moreover, online shopping allows customers to save money.
Today, one of the most important contemporary challenges facing e-commerce seems to be
logistics and meeting the high expectations of e-commerce customers, ensuring their satisfaction and,
consequently, loyalty to the place of purchase. The unique role of logistics in e-commerce (Bask,
Lipponen, & Tinnilä, 2012; Masmoudi, Benaissa, & Chabchoub, 2014; Ramanathan, George, &
Ramanathan, 2014; Yu, Wang, Zhong, & Huang, 2017) and in the creation of value for the customer was
indicated by many authors (Willersdorf, 1990; Francis, Fisher, Thomas, & Rowlands, 2014). One of the
most frequently indicated imperatives of the need for changes in the e-commerce industry is technology.
However, the dynamics of changes in the e-commerce industry is related not only to technological
innovations (Bakker, Zheng, Knight, & Harland, 2008), but also to changes in customer behavior and
their expectations, as well as the need to adapt other stakeholders of value in e-commerce. The issue of e-customers’ expectations and preferences has been the subject of research for many years (Bhattacherjee,
2001), as well as the problem of logistics challenges in e-commerce, consisting in ensuring an adequate
level of services. Finding an optimal balance between pricing, customer expectations and logistics service
levels has been an increasing challenge. This aspect points to the need for continuous monitoring of
customer preferences and provision of appropriate and profitable (in a cost-effective manner) logistics
value. The problem of the actual proper understanding of the final e-commerce customers' expectations
by the remaining participants co-creating the logistics value in the network seems to be weakly
recognized. The confrontation of e-commerce customers’ preferences and the knowledge of co-creators of
values on this subject may be an extremely important decision-making premise in the area of shaping an
appropriate level of logistics in e-commerce. The ultimate goal of the created logistics value
corresponding to the customers' preferences is satisfaction and, in accordance with the relationship
marketing approach, the loyalty of final customers. This aspect, i.e. achieved satisfaction and loyalty of
final customers, can be understood differently by individual participants in the value network. Satisfaction
and loyalty have been the subject of research for some time. However, it is rare to confront customer
satisfaction and loyalty with knowledge on this topic from other participants in the value network.
Conclusions from such research can significantly affect the undertaking of actions eliminating any gaps in
the customer satisfaction and loyalty.
The purpose of this article is to explore the differences between members of the e-commerce value
network in the perception of customer preferences towards logistics value as well satisfaction and loyalty
of customers. The research used a discriminatory analysis allowing identification of the assessed elements
(i.e. logistics value, satisfaction and loyalty) as the most diversifying stakeholders in terms of their role in
the value network.
Literature Review and Theoretical Framework
2.1.Logistics as a value
A value is a core concept of marketing and strategic management. It is worth to remember that its
theoretical roots lie in economics. Worth and price were explained by representatives of the classic school
of economics, such as A. Smith and D. Ricardo, who formulated the methodical approach to value. They
incorporated customer utility into the value definition and the value creation parameters, such as capital
inputs, technologies, labour costs, esteem value and relative shortages. In general meaning, a “value can
be defined as an evaluation of the utility of a product understood as a relationship between what has been
received and what has been given – value represents a compromise between what can be obtained and
what should be given” (Kawa & Światowiec-Szczepańska, 2019). Moreover, value in management is
referred to the customer and it is named a value for the customer (Kotler, 1994).
One of the key factors of value in e-commerce is logistics. It is to provide the right product, at the
expected time, cost, in the right quantity, condition, location, and to the right customer. Thanks to its
processes and tools, the promise of fulfilling the order can be realized. Logistics is undoubtedly an
important area of activity for e-commerce companies – apart from supporting the processes of managing
the flow of goods, it fulfills the function of integrating and interconnecting the separate business entities.
Logistics spans the boundaries between goods suppliers, service providers, and customers (Stank,
Goldsby, Vickery, & Savitskie, 2003). Researchers understand value for customer in terms of logistics in
quite a similar way. Very often, logistics value refers to the reduction of lead time and business costs, and
improvement of flexibility, responsiveness and reliability of shipping services (Lee & Song, 2010). The
level of service performance should be based on an accurate assessment of what the customer truly
values. Understanding the consumer perception of service quality is a critical issue that will provide valuable information for sellers to understand and retain their existing consumer base. Customers’
perceptions are formed on the basis of their experience of the services received from an organization. It is
believed that customers’ perception and expectations are strongly related concepts as to how customers
recognize service quality. The unstable e-market conditions may justify the necessity to analyze customer
preferences and evaluate future behavior (Christopher, 2000; Bakker, Zheng, Knight, & Harland, 2008).
2.2.Network value in e-commerce
The issue of the value network has been the subject of research for many years. Broadly speaking,
value network is a set of cooperating entities in order to produce specific items, sell them and
consequently create a specific benefit (Lusch, Vargo, & Tanniru 2010). Value network entities include
not only enterprises (online sellers, and their suppliers), but also customers which are be almost any
individual or business person. The sellers are mostly online retailers (e-tailers) which have Internet shops
or sell products or services on marketplaces, auction platforms , etc. The term "supplier" is broadly
understood here and includes both providers of products (goods and services) sold through the electronic
channel and other entities offering complementary services, e.g. financial and logistics services, IT
solutions, price comparison services. The latter are named as complementors (Kawa & Światowiec-
Szczepańska, 2019). Today, the biggest challenge is a creation of value network in which apart from the
particular interests of individual network participants, the customer's preferences and expectations are
taken into account, as well as his or her willingness to incur costs in return for the benefits obtained
(Kawa & Światowiec-Szczepańska 2018).
2.3.Satisfaction and loyalty
According to Olivier (1999), satisfaction is treated as a response to the customer's fulfillment
which is not simply about the extent of being pleased, but it is a process, as well (Nisar & Prabhakar,
2017). Kotler (1994) claims that satisfaction is the degree to which the experience of the product meets
the customer’s expectations.
Next, loyalty can be defined as the customer’s eagerness to buy the product of a specific brand or
to use a service once again. It obviously translates into repeatability of purchases, regardless of the
marketing efforts to promote rival brands (Olivier, 1999). In such a case, the customer will still want to
buy a given product or services even if those offered by other providers appear more competitive. The customer’s trust in that company is, then, determined by loyalty and is mainly noticeable as the
customer’s emotional attachment to a given entity and willingness to maintain this special type of ties.
Both of these constructs, i.e. satisfaction and loyalty are frequently and deeply discussed in the
literature on various industries. The dynamic growth of e-commerce has caused researchers to o study
satisfaction and loyalty in the Internet, in particular the mutual impact of both of them. In fact, most
studies show that satisfaction has a positive effect on loyalty (Cyr, 2008) or repurchase intention (Kwon
& Lennon 2008). Furthermore,, researchers have observed a positive relation between satisfaction and
customer spending when higher satisfaction leads to more spending in e-commerce (Nisar & Prabhakar,
2017).
The process of value co-creation for customers entails the formation of shared goals and values,
which should coincide with customer preferences and be responsive to their perceptions. Thus, a successful value network should be seen by all the members’ aligned perception of it. The key
determinants of a well-functioning value network are proper understanding of customers’ preferences and
a consistent assessment of their satisfaction and loyalty. The idea of the value network in e-commerce as
a scope of our research is presented in Figure

Research Method
3.1.Data collection and sample
The assumption behind the research was that the respondent (representing retailers, customers
suppliers, complementors and) was to look at the value from the viewpoint of the final customer, no
matter what their role in e-commerce was. This attitude was adopted because the value network is built
around its customers. The customer is the core of the e-commerce system and it is the customer who
finally assesses the value (Kawa & Światowiec-Szczepańska, 2018). Computer-assisted telephone
interview was chosen as the technique of information collection in the research, preceded by focus group
interviews. The qualitative methods were used for an initial analysis of the issue of value creation, in
order to provide information necessary for the right organization of the research by the quantitative
method, including, first and foremost, the development of a measuring instrument.The study was
conducted from November 2017 to May 2018 by an external agency. A total of 800 correctly filled
questionnaires was obtained (200 records in each group – retailers, customers, , suppliers, and
complementors) (Kawa & Światowiec-Szczepańska, 2019).
3.2.Measurements
On the basis of the theoretical considerations, 7 corresponding measures were distinguished in the
study; namely, Packaging, Delivery monitoring, Time and flexibility of delivery, Convenience of return,
Convenient place of delivery (all referring to the logistic value) as well as Satisfaction and Loyalty.
Because relationship related variables were latent, a multi-item scale approach was adopted in this
research in order to increase item reliability. All items for measuring the variables of interest found in the
literature were applied. A five-point Likert-type scale was used by the respondents to indicate the extent
to which they agreed with a given statement. For each of the constructs the scale was as follows: 1 =
strongly disagree to 5 = strongly agree. The results were then verified in terms of quality with the use of
validity and reliability measures (Cronbach’s alpha coefficients of all constructs were higher than 0.76).
3.3.Multiple discriminant analysis
Given our interest in exploring the dimensions of logistics value contributing to differences in
perception between value network participants as well as those in perceived satisfaction and loyalty, we
deemed discriminant analysis an appropriate analytical approach. Multiple Discriminant Analysis is a
multivariate technique using several variables simultaneously to classify an observation into one of
several a priori groups, in this case: four groups of e-commerce value network participants. This is done
by the statistical decision rule of maximizing the between-group variance relative to the within-group
variance, and is expressed as the ratio of the between-group to the within-group variance. Discriminant
analysis is preferred because it has an advantage over the t-test in that it compares two groups in terms of
group centroids, thereby taking into account the interactions between the individual variables.
Discriminant analysis is useful when the researcher is interested either in understanding group differences
or in classifying objects into groups. The technique is most appropriate in situations with a single
categorial dependent variable and several metrically scaled independent variables. Given the purpose of
the research, we considered discriminant analysis as a type of profile analysis, which provides an
objective assessment of the differences between groups on a set of independent variables (in this situation
discriminant analysis is similar to multivariate analysis of variance; about differences see: Hair, Black,
Babin, & Anderson, 2010, p. 446). The discriminant model is developed by applying a simultaneous
procedure in SPSS to the 800 respondents included in the sample. The independent variables are the five
logistics value scales with high inter-item reliability (Packaging, Delivery monitoring, Time and
flexibility of delivery, Convenience of return, Convenient place of delivery), as well as Loyalty and
Satisfaction. The dependent variable is the type of role in the e-commerce chain supply (e-tailer, supply,
complementor, customer). All calculations and the analysis in this study were done with IBM SPSS
Statistics version 25.
Findings
Table
> 0.5) were demonstrated by the following pairs: convenient place of delivery and packaging as well as
loyalty and satisfaction.
The typical measures of significance for the differences across groups is Wilks’ lambda and
Table 02 provides the group means and the test of equality for each independent variable. Despite the
relatively high value of the Wilks’ lambda measures (the smaller the Wilks’ lambda, the more important
The visualization of the four-group model: customers, e-tailers, suppliers and complementors is
shown in Figure
coordinates representing the first and second functions. The observations concerning the corresponding
groups concentrate around the most typical points for a given group. The graph indicates a significant
range of the area common to all groups. Nevertheless, there are significant differences between the group
centroids and the distribution of the observations behind them. According to the classification results
(Table 05), the most homogeneous group is e-tailers, while the least homogenous one embraces clients.

The final measure of the classification accuracy is Press’s Q. It tests the statistical significance in
such a way that the classification accuracy is better than chance.
𝑃𝑟𝑒𝑠𝑠′𝑠 𝑄 = [𝑁 − (𝑛𝐾)]2
(𝐾 − 1) = [800 − (426 × 4)]2
800(4 − 1) = 340.5
The critical value at a significance level of 0.01 is 6.63. Thus, the predictions are significantly
better than chance.
Discussion and Conclusions
The aim of these studies was to determine the relationship between perceived preferred logistic
value, customer satisfaction and loyalty and the role of the stakeholder in e-commerce supply
management. To test this relationship, a discriminant analysis was performed to establish whether
differences in perceptions exist between e-commerce value network stakeholder groups.
The analysis produced several major findings. First, there are three dimensions of discrimination
between stakeholders in e-commerce value network. The first dimension is typified by very high
perceptions of customer satisfaction and loyalty. The second dimension is characterized by relatively high
loyalty and score of convenient place of delivery along with time and flexibility of delivery. The last
dimension is distinguished by extremely high assessment of convenience of return, convenient place of
delivery, along with other dimensions of logistics value (i.e. packaging and delivery monitoring).
Profiling the four groups on these dimensions and variables associated with each dimension enables to
understand the perceptual differences among them. In terms of logistics value, customers averagely have
the highest requirements for delivery monitoring and convenience of return. They show the lowest
preferences towards packaging. Interestingly, monitoring of delivery is rated by customers at the highest
level compared to the rest of the groups. This may suggest that it is the element of logistics value
underestimated by other members of the e-commerce value network.
Customers generally show relatively high satisfaction with their on-line shopping. Only according
to the complementors, customer satisfaction is higher. Customers admit relatively moderate loyalty to
places of purchase on the Internet. This can be confirmed by the low customer loyalty rate assessed by e-tailers. In turn, suppliers and complementors assess customers’ loyalty at a higher and comparable level.
E-tailers indicate the highest customer preferences for delivery monitoring along with time and flexibilty
of delivery. Still, their monitoring assessment is lower than that made by the customers. In addition, e-
tailers assess customers' preferences for returns and packaging at a lower level than customers.
Both in the case of customer satisfaction and loyalty, e-tailers' feelings are the lowest in the entire
e-commerce value network. This result may indicate high competitiveness of the marketplace and great
difficulties in tying customers to on-line stores. Other value network stakeholders: suppliers and
complementors assess customer satisfaction and loyalty at a relatively high level. E-customers' loyalty
perceived by them is, however, much higher than the customers themselves indicate. In addition, the
suppliers and the complementors underestimate the need for monitoring the delivery; the same is true for
the complementors and such aspects of the logistics services as convenience of returns or convenience of
the place of delivery.
The research conducted indicates that there is no perfect understanding of clients' preferences
towards the level of logistics value, nor customer satisfaction and loyalty in the entire value network of e-
commerce. The research allowed to confirm significant differences between particular groups of value
network members in the analyzed industry. The statistical analysis carried out confirmed differences in
the perception of customer preferences in all variables that create logistics value, but with varying
intensity. The greatest determinant of the differences was Convenient place of delivery and Convenience
of return. Such elements of logistics value as: Time and flexibility of delivery and Delivery monitoring
have much lower discriminating power. The problem of packaging is almost identical to the chain's
participants. However, it should be noted that the differences between the groups are not equal.
An equally interesting observation seems to be significant differences in perception - exceeding
those related to the logistics services - of customer satisfaction and loyalty. In the case of satisfaction, the
greatest distance is observed between the retailers and the complementors. The first group assesses
satisfaction lower than the group of clients, while the second group evaluates it significantly higher
Acknowledgements
This paper has been written with financial support of the National Center of Science [Narodowe
Centrum Nauki] – grant number DEC-2015/19/B/HS4/02287.
References
- Bakker, E.Zheng, J.Knight, L.Harland, C. (2008). Putting e‐commerce adoption in a value network
- (), context. International Journal of Operations & Production Management, 28(4), 313-330.
- Bask, A.Lipponen, M.Tinnilä, M. (2012). E-commerce logistics: a literature research review and topics for future research.. International Journal of E-Services and Mobile Applications, 4(3), 1-22
- Bhattacherjee, A. (2001). An empirical analysis of the antecedents of electronic commerce service continuance.. Decision support systems, 32(2), 201-214
- Christopher, M. (2000). The agile value network, competing in volatile markets.. Industrial Marketing Management, (29), 37-44
- Cyr, D. (2008). Modeling Web Site Design Across Cultures: Relationships to Trust, Satisfaction, and E-Loyalty.. Journal of Management Information Systems, 24(4), 47-72
- Francis, M.Fisher, R.Thomas, A.Rowlands, H. (2014). The meaning of ‘value’ in purchasing, logistics and operations management.. International Journal of Production Research, 52(22), 6576-6589
- Hair, J. F.Black, W. C.Babin, B. J.Anderson, R. E. (2010). Multivariate Data Analys(A global perspective, 7th Edition. New Jersey: Pearson)
- Kawa, A.Światowiec-Szczepańska, J. (2019). IT Value for Customer: Its Influence on Satisfaction and Loyalty in E-commerce.. In Asian Conference on Intelligent Information and Database Systems, Springer
- Kawa, A.Światowiec-Szczepańska, J. (2018). Value Network Creation and Value Appropriation in E-commerce.. Przedsiębiorczość i Zarządzanie, 19(6), 9-21
- Kotler, P. (1994). Marketing management: analysis planning implementation and control. Prentice Hall. Kwon W.-S., & Lennon S. J. (2008). What induces online loyalty? Online versus offline brand images.. Journal of Business Research, 62, 557-564
- Lee, E. S.Song, D. W. (2010). Knowledge management for maritime logistics value: discussing conceptual issues.. Maritime Policy and Management, 37(6), 563-583
- Lusch , R.Vargo , S.Tanniru, M. (2010). Service, value networks and learning.. Journal of the Academy of Marketing Science,38(1), 19-31
- Masmoudi, M.Benaissa, M.Chabchoub, H. (2014). Optimisation of e-commerce logistics distribution system: problem modelling and exact resolution.. International Journal of Business Performance and Value network Modelling, 6(3-4), 358-375
- Nisar, T. M.Prabhakar, G. (2017). What factors determine e-satisfaction and consumer spending in e-commerce retailing? Journal of Retailing and Consumer Services, 39, 135-144
- Olivier, R. I. (1999). Whence consumer loyalty.. Journal of Marketing, 63, 33-44
- Ramanathan, R.George, J.Ramanathan, U. (2014). The role of logistics in e-commerce transactions: an exploratory study of customer feedback and risk, Value network Strategies, Issues and Models, Springer
- Stank, T. P.Goldsby, T. J.Vickery, S. K.Savitskie, K. (2003). Logistics service performance: estimating its influence on market share.. Journal of Business Logistics, 24(1), 27-55
- Willersdorf, R. G. (1990). Adding Value through Logistics Management.. Logistics Information Management, 3(4), 6-8
- WT, O.World Trade , Report. (2016). Levelling the trading field for SMEs, World Trade Organization. Yu, Y., Wang, X., Zhong, R. Y. & Huang, G. Q. (2017). E-commerce logistics in value network management: Implementations and future perspective in furniture industry.. Industrial Management & Data Systems, 117(10), 2263-2286
Copyright information
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
About this article
Publication Date
30 October 2019
Article Doi
eBook ISBN
978-1-80296-070-9
Publisher
Future Academy
Volume
71
Print ISBN (optional)
-
Edition Number
1st Edition
Pages
1-460
Subjects
Business, innovation, Strategic management, Leadership, Technology, Sustainability
Cite this article as:
Kawa, A., & Swiatowiec-Szczepańska*, J. (2019). Logistics, Satisfaction And Loyalty In E-Commerce Value Network: Discriminant Approach. In M. Özşahin (Ed.), Strategic Management in an International Environment: The New Challenges for International Business and Logistics in the Age of Industry 4.0, vol 71. European Proceedings of Social and Behavioural Sciences (pp. 123-133). Future Academy. https://doi.org/10.15405/epsbs.2019.10.02.12