The relationship of consumer psychology and consumer experience to consumer satisfaction and organisational performance: literature review

Abstract

Consumer psychology, consumer experience, consumer satisfaction, and organizational performance constitute domains that exert a direct or indirect influence on a company’s operational efficacy. Despite their inherent expansiveness, these realms are typically scrutinized discretely and frequently devoid of explicit linkage to organizational performance. Nonetheless, their interrelations enable the characterization of consumer profiles and the quantification of these attributes. Should these characteristics manifest in a company’s performance, they can be leveraged through various managerial tools. This article endeavors to systematically review literature across these domains via a structured literature inquiry to foster a holistic understanding of the consumer paradigm, particularly emphasizing satisfaction dynamics and influential factors, notably rooted in psychological and experiential frameworks. Such insights are pivotal for enhancing organizational performance. The chosen methodology, a systematic literature review, specifically a structured approach, is deemed optimal for its comprehensive coverage of diverse facets of consumer behavior and their nexus with organizational outcomes. Our inquiry advocates for a mixed-methods research design targeting customers of select companies within a specific national and industrial context. The inquiry encompasses consumer satisfaction, personality (as a constituent of consumer psychology), consumer experience, consumer cognition (as a component of consumer experience), and organizational (financial) performance. Despite the absence of comprehensive research in these areas, this study promises to unearth transformative insights for enhancing organizational efficacy. It is recommended to conduct extensive research with a mixed design, within the selected country and industry, which will be focused on customers of selected companies.

Keywords:

• Consumer satisfaction
• consumer psychology
• consumer experience
• organisational performance

Reviewing Editor:

• Kaouther Kooli, Bournemouth University, United Kingdom of Great Britain and Northern Ireland

Subjects:

• Consumer Psychology
• Consumer Behaviour
• Consumer Behaviour

1. Introduction

There are several studies that examine consumer satisfaction (CS) in the context of financial (business) performance (FP) (e.g. Golovkova et al., 2019; Kerr & Marcos-Cuevas, 2023; Ting & Ahn, 2024), consumer experience (CE) (e.g. Kaigorodova et al., 2018) and consumer psychology (CP) (e.g. Tsung & Tseng, 2023; Menon et al., 2006). As a rule, however, these three problem areas are examined separately (in the context of organizational performance (OP)) or CP is examined concerning CS (e.g. Halim et al., 2011) and CE within (as part of) CS (e.g. Terpstra & Verbeeten, 2014). If CP and CE are related to CS in the context of OP separately, it can be reasonably assumed that they will also be related to this satisfaction together. However, there is not much research that would examine these three areas together in the context of OP (see below). There are mainly researches that examine these three areas in the context of OP to employees, respectively. employee experience (Ahearne et al., 2005).

Another interesting approaches in different industries came e.g. from the study about sport by Glebova and Desbordes (2021), they explained how Sports Spectators Customer Experiences (SSCX) are changing because of the rapid uptake of digital technologies, or the research about museum by Vesci et al. (2020), they analysed the quality of experience in the Italian art museum context and to understand the mediating role of satisfaction between museum experiences and visitors’ word-of-mouth behavioural intentions.

Therefore, we decided to fill this gap of scientific knowledge and use a systematic literature search to determine the potential for joint research CP (personality), CE (knowledge) and CS in the context of OP (financial, business, firm performance). The article aims to find out what research has been conducted in these areas and what is the current state of knowledge in research in these areas, including the interrelationships of these areas so that it is possible to conduct precisely targeted follow-up (quantitative) research. The article is mainly focused on the definition and method of measuring the investigated quantities, including the determination of mutual relations and methods of their measurement.

2. Theoretical framework

The researched areas are relatively large and, as mentioned in the introduction, they are usually examined separately. If we want to carry out meaningful research, it is necessary to define these areas, especially in the context of (partial) mutual relations. At the same time, CS and OP can be considered as the basic links of research, as it was clear from the introduction, and therefore these areas will be characterized first, including mutual relations. In particular, CP, but also CE will then be characterized concerning a possible relationship between CS and OP.

2.1. Consumer satisfaction (CS)

Consumer satisfaction can be defined as ‘an aggregate affective response of varying intensity with a time-specific destination and limited duration, focusing on key aspects of product acquisition and/or consumption’ (Giese & Cote, 2000). The study by Xie et al. (2022) constructs a formation model of customer well-being in customer experience with joy and customer satisfaction as mediating factors linking three critical factors-convenience, performance and the relationship of customer experience with consumer well-being.

Another research found a link between CS, CE and FP, specifically, it was found that CS is affected by CE, respectively. that CE is the basis of CS, where CS is related to the FP of the company (for more details see Terpstra & Verbeeten, 2014). Thus, it can be assumed that CE will positively affect CS, which will affect (positively or negatively) FP. Other interesting study by Luan et al. (2022) showed that service-oriented organizational citizenship behavior was an important mechanism by which employees’ overall life satisfaction positively affected customer satisfaction. Wei and Prentice (2022) added a new idea about the relationship between AI service quality and customer engagement and satisfaction.

An important issue is how to measure CS and its relationship to FP. CS can be measured as a separate (multidimensional) construct (as so-called general customer satisfaction) (Berraies & Hamouda, 2018), in which case, In this case, there is a direct effect on FP. The relations between CS and FP are generally positive, except for the retail sector Foster and Gupta (1997), specifically discount stores and shoe sales (Anderson et al., 2004), or the sector services in general (Brown & Mitchell, 1993). Conversely, when CS is measured by a specialized structural model (index), the effect of customer satisfaction on FP is indirect, through customer loyalty (Anderson et al., 2004).

2.2. Organizational performance (OP)

Organizational performance can be defined as the ability of an organization to achieve its goals by satisfying its customers more efficiently and effectively than its competitors (Kotler, 1984). Company performance can be monitored through business results or their quantification. In this context, Neely et al. (2005) understand efficiency as the degree to which customer requirements are met (effectiveness) or as the degree of economic use of a company’s resources that leads to given CS (efficiency).

OP can be measured as a two-dimensional construct (operational and financial performance), where operational performance represents the efficiency and effectiveness of customer service and FP represents standard aggregate financial indicators, especially profitability (Overstreet et al., 2013). This method of measurement corresponds to the definition of performance according to Neely et al. (2005). At the same time, performance (in the economic sense) is linked to CS (e.g. see the research by Gloor et al., 2022; Sultana et al., 2023). If part of our research is CS, it can be examined separately and within the framework of performance, we can focus only on FP.

2.3. Consumer experience (CE)

Consumer experience can be defined as: ‘the total outcome to the customer from the combination of environment, goods and services purchased’ (Lewis & Chambers, 2000, p. 46). CE is thus closely related to consumer psychology, as CEs have a psychological dimension (Walls et al., 2011). However, it is also related to the product. Therefore, if the CE is focused on the product, resp. product category, CK (see below) can be understood as a part of CE. Within the measurement, CE can be understood as a multidimensional (four-dimensional) construct, which is measured separately, without further specification or links to other factors, such as CS or FP (Walls et al., 2011), one of the dimensions can be CP or CK.

2.4. Consumer knowledge (CK)

Consumer knowledge is understood in our research as a product CK, resp. product category, which can be understood in three similar ways as objective knowledge, subjective knowledge and experience (Flynn & Goldsmith, 1999). At the same time, CK is closely related to CE, as the acquired experience increases the acquired knowledge, in this sense CE depends on CK (Rose et al., 2011). Concerning the focus of our research, we will understand CK as an experience (with a product) so that our concept of CK is compatible with the concept of CE. CK can be measured by a single quantity (Suchánek & Králová, 2019) or as a one-dimensional construct (Shirin & Kambiz, 2011). Park et al. (1992), however, recommend a multidimensional construct for measuring CK.

2.5. Consumer psychology (CP)

Consumer psychology can be defined as: ‘the utilization of distinctly psychological concepts and methods to understand (explain and predict) the dynamics underlying, influencing, and determining consumer behaviour’ (Jacoby, 1976). From a psychological point of view, CP has two areas of focus: consumer information processing (CIP), ‘which includes consumer cognition and affect. CIP has as its theory base social and cognitive psychology ‘a behavioural decision theory (BDT), ‘which includes topics such as choice models, economic psychology, and consumer search strategies’ (Loken, 2006). CP is conceived in our research from these two perspectives.

2.6. Personality (P)

In our research, personality is understood as personality traits, which can be defined as ‘endogenous dispositions that follow intrinsic paths of development essentially independent of environmental influences’ (McCrae et al., 2000, p. 173). The measurement usually uses a multi-dimensional construct or model, which is based on specific models, such as Big Five (McCrae & Costa, 1987), but it is also possible to meet with a one-dimensional construct (Suchánek & Králová, 2018). Because P controls the cognitive and affective system of individuals (Zabkar et al., 2017), it is very closely related to CIP (if they are not directly part of it). On the other hand, P is also closely related to influences) CS (Siddiqui, (2012). In this regard, however, it is necessary to emphasize that our research is focused only on P consumers.

3. Methods

Concerning Paul and Criado (2020), we performed a domain-based systematic literature review, specifically a structured review, and in applying this method, we followed the guidelines that the authors present in their article. The structured review seems to be the most suitable method for our research due to the focus on different areas of the customer (psychology, experience, satisfaction) and organizational performance where we look for opportunities to interconnect, as we consider it a gap in current research, which represents the potential for further research. We chose a similar procedure as Mishra et al. (2021) in our research, with the difference that we did not perform the part of the analysis devoted to the background of the publication and the focus and content of the publication manually, but with the use of specialized Atlas software.

In carrying out the systematic review, we performed four steps: selection of research questions, databases and keywords; application of practical screening criteria; application of methodological screening criteria; synthesizing our findings (Mishra et al. 2021 according to Fink, 2010). The first three steps are part of this chapter devoted to research methodology, the fourth step is part of the next chapter devoted to results.

The first step is the selection of research questions, databases and keywords. Following the above literature search, the following keywords were selected: consumer, customer, satisfaction, psychology, personality, experience, knowledge, financial, business, firm, organizational, performance. These words were further put into context to cover all three research areas (CS, CP and CE) in the context of organizational performance. This created a function that was entered into the search engines of the Web of Science (WoS) and Scopus databases. The WoS database was selected concerning the breadth of coverage, higher impact of articles and emphasis on English (Aghaei Chadegani et al., 2013). The Scopus database, in turn, due to higher journal coverage, as ‘Scopus has a wider coverage of journals as compared to the Web of Science, the Web of Science continues to be more selective in its journal coverage’ (Singh et al., 2021). The resulting search functions are as follows:

WoS:TS = (((consumer* or customer*) and satisfaction and (psychology or personality or (personal and characteristic*)) and (experience or knowledge)) and ((financial or business or firm or organisational) and (performance)))

Scopus:TITLE-ABS-KEY ((consumer* OR customer*) AND satisfaction AND (psychology OR personality OR (personal AND characteristic*)) AND (experience OR knowledge)) AND ((financial OR business OR firm OR organisational) AND (performance)) AND (LIMIT-TO (DOCTYPE, ‘ar’) OR LIMIT-TO (DOCTYPE, ‘re’)) AND (LIMIT-TO (LANGUAGE, ‘English’))

The second step is the application of practical screening criteria. Given the diverse length of research in individual areas (where, for example, the roots of CP research lie in the 1950s and CS research has been conducted since the 1970s), we have decided not to limit the search for relevant publications. The research was conducted in July 2021. At the same time, we focused only on articles in English.

Based on a feature created from keywords for the WoS search engine, 49 usable results were selected. Of these results, 44 were articles in peer-reviewed journals (articles or reviews) and 5 were conference proceedings. Concerning the procedure of Mishra et al. (2021) 5 conference proceedings were excluded from the research. The remaining 44 articles were manually examined based on the title, abstract, keywords and full text of the article, with a specific focus on the research areas (at least one of them) and their in-depth examination instead of a superficial mention of them (Mishra et al. 2021). This made a further reduction to the final 18 cells, which were subjected to content analysis.

The Scopus search engine used the same function as the WoS database to make the results comparable. Compared to the Wos database, in the case of the Scopus database, the search could have been better targeted through the occurrence of keywords in the title, abstract and keywords in the article, which we used. The search selected 194 usable results (articles in peer-reviewed journals. All 194 articles were further manually reviewed as in the case of the WoS database. This further reduced to the final 52 articles, which were subjected to content analysis. Thanks to 7 duplications of articles from both databases, 63 articles were finally included in the set of examined articles, which were subsequently subjected to content analysis. The selection criteria are summarised in Table 1.

Table 1. Summary of selection criteria.

Type of filter	Description	Results: WoS/Scopus
Substantial	All results with the keywords ‘consumer’ ‘customer’ ‘satisfaction’ ‘psychology’ ‘personality’ ‘personal’ ‘characteristic’ ‘experience’ ‘knowledge’ ‘financial’ ‘business’ ‘firm’ ‘organisational’ ‘performancë in the title, keyword or abstract and using the boolean operators AND, OR	49/194
Substantial	Exclusion of conference proceedings	44/194
Substantial and methodological	Reading of the abstracts of articles to check the substantial relevance	18/52
Duplicate	Exclusion of duplicate articles found in both databases	7
Articles analyzed		63

Source: Authors according to Bueno et al. (2019).

The third step is the application of methodological screening criteria. For the content analysis of articles selected based on the above criteria, a protocol was created, which contains basic information about the analyzed articles (Mishra et al. 2021). This information can be summarized in four basic areas, which are listed in Table 2. Information from the bibliographic data area was retrieved manually based on the search results of publications in the WoS and Scopus databases.

Table 2. Review protocol.

Bibliographic data
Author(s)	Who is/are the author(s) of the publication?
Year	In which year was the work published?
Title	What is the title of the publication?
Journal name	If it is a journal: what is the journal’s name?
Quartile by ISI-impact (2021) of the journal	If it is a journal, how was the journal ranked in 2021?
Harzings’ Publish or Perish	How often the publication is cited in WoS?
Definition of related terms
Definition of terms	What is the definition of CS, CP, P, CE, CK, OP?
Background of the publication
Methodology of the publication	How are the investigated quantities measured?
	What is the research design?
	What research method was used?
	What statistical method was used?
Sample	How many respondents were in the survey?
Country	Which country is the subject of the publication?
Sector	Which sector is the subject of the publication?
Focus and content of the publication
The focus of the publication	What is the focus of the publication?
Relations between areas	What areas have been identified for relationships?

Source: Authors according to Stechemesser and Guenther (2012).

Information from the remaining three areas was manually coded in the relevant publications using the Atlas program. Concerning the research goal, the following codes were created for a systematic literature search, which is based on the review protocol in Table 2 and are focused on the analysis of the background of the publication, definition of related terms and focus and content of the publication in the relevant software.

Concerning diversity, resp. inconsistency in the definition of research areas (terms), it is important to find out how the authors defined these areas (terms) in their research. The first code, which contains six sub-codes, is, therefore, What_definition (from the area of Definition of related terms), which is focused on the definition of CS, CP, P, CE, CK and OP (Prayag et al., 2019).

The second group of codes (specifically the second to eighth codes) focuses on the Background of the publication. The second code is focused on the method of measuring the above quantities, i.e. whether these quantities are constructs (one or multidimensional), separate quantities or indices (models), containing several constructs. The code is called How_measure_structure, again it contains six sub-codes and the result is one of four characteristics (one-dimensional construct, multidimensional construct, separate quantity, index/model).

The third, fourth and fifth codes are focused on the design and research methods used, including statistical methods. The third code is called How_design, again it contains six sub-codes and the result is one of three characteristics (quantitative, qualitative or mixed research design) (Prayag et al., 2019). The fourth code is called How_methods, again it contains six sub-codes and the result is a specific characteristic of the research method used concerning its design. The fifth code is called How_statistical_methods, again it contains six sub-codes and the result is a specific characteristic of the statistical methods used. All of the above codes focus on the methodology of the publication.

The sixth code focuses on identifying the country in which the research was conducted and is called Which_country. The seventh code focuses on the sector in which the research was conducted and is called Which_sector. The eighth code is focused on the sample size, resp. on the number of respondents in the research. The code is called How_much_sample, while the code takes numerical values and the result is the identification of the number of respondents in the relevant research.

The third group of codes is focused on the Focus and content of the publication (specifically the ninth to twelfth codes). The ninth code focuses on the quantity (or quantities) that the publication examines. The code is called What_focus and can contain one to six areas (CS, CP, P, CE, CK, OP). The tenth code focuses on the relationships between the six areas examined (terms). The code is called How_relationships_area, where the code can contain one to six areas (CS, CP, P, CE, CK, OP) and the result is to find out between which areas certain relationships were found if the research was focused on more areas.

4. Results

The results obtained were synthesized in this chapter. The basic bibliographic results are listed separately for both databases, as these results could not be assessed together. The results for the other parts of the Review Protocol have already been considered together.

4.1. Bibliographic data

Although the search for relevant articles was not limited in time, the articles found from the WoS database fell within the time interval 2002–2020, with most articles (4) being published in 2017 (3 in 2020). It turns out that the interconnection of thematic areas examined by us is relatively new, thus confirming the assumption of the existence of a gap in scientific research. As part of the analysis of the found articles, the results of basic bibliographic data from the Review protocol are first presented.

Complete results from the WoS database are given in Appendix 1a (supplementary material). Most articles (2 each) were published in the European Journal of Marketing, Tourism Management, Journal of service research and Managing service quality.

Complete results from the Scopus database are given in Appendix 1b (supplementary material). Also, in this case, the search for relevant articles was not limited in time, while the found articles from the Scopus database fell within the time interval 1997–2021. Most articles (11) were published in 2019 (5 in 2017). The results from the Scopus database thus correspond to the results of the WoS database and reaffirm the assumption about the novelty of the researched topic and the existence of a gap in the scientific study of this issue.

Most articles were published in the journals Sustainability (5) and Tourism Management (3), followed by the journals Applied ergonomics, Asia Pacific Journal of Marketing and Logistics, Journal of Services Marketing, Psychology & Marketing (both with 2 articles). Among the best journals in their field (according to the CiteScore rank 2020 quartile) are e.g. Current Issues in Tourism (among the top ten journals in Business, Management and Accounting (BMA)), Tourism Management (the first journal in BMA), Management Science (in the first decile in BMA), Computers in Human Behavior (among the top ten journals in their respective fields).

From the bibliographic data of both databases, it is clear that the topic is relatively new. At the same time, it is clear that most of the results (articles) have been published in quality journals in the relevant fields (including BMA). The researched topic thus hides a considerable potential for research, including the possibility of publishing in prestigious journals. On the other hand, this places considerable demands on researchers and the research itself, as the research will have to be carried out very well. It is therefore clear that the researched topic is relatively demanding for research.

4.2. Definition of related terms

Another part of the Review Protocol examined was the Definition of related terms. The summary results of this part are given in Appendix No. 2 (supplementary material). It is clear from the results that from the examined areas all areas were defined in the performed research, except for CP and OP. In the field of CP, the absence of a definition is quite logical, as it is a relatively broad area of own scientific research, within which several independent types of research are carried out. It is therefore not necessary to define a certain area in the articles, but rather the subject of the research itself, including specific factors and links. For the OP, the situation is somewhat more complicated, as this area is disproportionately narrower than the CP. However, in this case (such focused research) OP again forms only a certain framework of research, i.e. is not the main subject of research, so the authors did not need to define this area separately and were satisfied only with the definition of indicators by which the OP will measure, i.e. defining the context in which they will place their research. In addition, the OP area is focused on the company, while the other areas are on the customer. The analyzed articles were primarily focused on the customer, so OP from this point of view was only a marginal topic.

The results show that the authors devoted most of their space to the definition of CS and P (e.g. Bogicevic & Bujisic, 2021; Faullant et al., 2011, Gountas & Gountas, 2007; Ha & Jang, 2013; Ihtiyar, 2019). From the results, it can be concluded that CS is one of the key areas that need to be carefully defined for research into this area to be well conducted. The definition of P is in turn essential due to the concretization of a wide range of possibilities of examining CP. It can be concluded that P represents a partial part of CP. Another reason for focusing on P is the importance of this area, especially for CE.

The results show that CS is defined primarily in the context of CP, resp. P and CE (e.g. Moliner-Velázquez et al., 2019; del Bosque & San Martín, 2008, Aurier & Guintcheva, 2014). It is therefore possible to assume the links of these three quantities. P is defined primarily concerning the emphasis on personal traits, so expect links primarily to CS and CE. CE is defined to customer expectations, where a link to CS can be expected. The definition of CK is focused on the general evaluation of the product or service performed by the customer, so again we can expect a link primarily to CS.

From the review of definitions, it can be concluded that CP (e.g. Zhao et al., 2020; Aurier & Guintcheva, 2014) represents rather a certain general framework in which research focused on CS and CE takes place, with some concretization and integration of this area into their own. The research of the OP also represents a certain framework in which the research is embedded. However, the CP is focused on the customer (natural person), while the OP is focused on the company. It can be assumed that the CP relates primarily to the customer (CS and CE), while the OP relates to the company. If the CP lies at the beginning of the customer-company relationship, then the OP lies at its end. The results show that the key areas of research are CS and P in the context of CP and OP, which are supplemented by CE and CK, which will probably be most related to CS. Thus, CS seems to be in the middle of a customer-business relationship and is thus a key area that connects everyone else.

4.3. Background of the publication

This part of the review can be divided into four sub-areas focused on methodology (summary results are given in Tables 3 to 5 and Appendix 3, supplementary material), sample (Table 6), country (Table 7) and sector (Table 8).

Table 3. Research design.

How design	References
Quantitative	Jin et al., 2012
Qualitative	Franke et al., 2017, Aurier & Guintcheva, 2014
Mixed method	Ashworth & Bourassa, 2020, Beatty et al., 2016, Bigné et al., 2005, Chu et al., 2012, Faullant et al., 2011, Garry, 2008, Gountas & Gountas, 2007, Hackett & Foxall, 1997, Löfgren et al., 2008, Orth et al., 2016, Roy et al., 2017, Tuu & Olsen, 2009, Yeh et al., 2019, Zhao et al., 2020, Yeh & Jeng, 2015, Rhee & Lee, 2021, Kocabulut & Albayrak, 2019, Ihtiyar, 2018, Ihtiyar, 2019, Faerber et al., 2021, Choi et al., 2019, Ban et al., 2019, Wang et al., 2010, Uzir et al., 2020, Tung et al., 2017, del Bosque & San Martín, 2008, Cohen et al., 2014, Campos et al., 2017, Brown et al., 2008, Moliner-Velázquez et al., 2019, Faerber et al., 2021, Bogicevic & Bujisic, 2021

Source: Authors.

Table 4. Method of measuring the examined variables.

How to measure the structure	References
one-dimensional construct	–
multidimensional construct	Wang et al., 2017, Moliner-Velázquez et al., 2019, Quach et al., 2019, Ashworth & Bourassa, 2020, Bogicevic & Bujisic, 2021, Choi et al., 2019, Zhao et al., 2020, Roy et al., 2017
independent variable	–
index/model	Sperkova, 2020, Noe & Uysal, 2004, Hsieh & Yeh, 2018, del Bosque & San Martín, 2008, Brown et al., 2008

Source: Authors.

Table 5. Research method.

Research area	How methods	References
CS	Questionnaires	Ashworth & Bourassa, 2020, Bigné et al., 2005, Chu et al., 2012, Faullant et al., 2011, Garry, 2008, Gountas & Gountas, 2007, Hackett & Foxall, 1997, Jin et al., 2012, Löfgren et al., 2008, Orth et al., 2016, Roy et al., 2017, Tuu & Olsen, 2009, Yeh et al., 2019, Zhao et al., 2020, Yeh & Jeng, 2015, Rhee & Lee, 2021, Kocabulut & Albayrak, 2019, Ihtiyar, 2018, Ihtiyar, 2019, Faerber et al., 2021, Choi et al., 2019, Ban et al., 2019, Wang et al., 2010, Uzir et al., 2020, Tung et al., 2017
	Interviews	Garry, 2008, Aurier & Guintcheva, 2014, Molliner-Velázquez et al., 2019, Johnson et al., 2009
	Focus groups	Aurier & Guintcheva, 2014
	Experiment	Erskine et al., 2019
CE	Questionnaires	Ban et al., 2019, Kim et al., 2019, Löfgren et al., 2008, Orth et al., 2016, Roy et al., 2017
CK	Interviews	Beatty et al., 2016
CP	Questionnaires	Beatty et al., 2016, Wei et al., 2017
	Interviews	Beatty et al., 2016, Aurier & Guintcheva, 2014
	Focus groups	Aurier & Guintcheva, 2014
P	Questionnaires	Quach et al., 2019, Ihtiyar, 2018, 2019, Kocabulut & Albayrak, 2019, Faullant et al., 2011, Gountas & Gountas, 2007, Ha & Jang, 2013, Jin et al., 2012
	Interviews	Molliner-Velázquez et al., 2019
OP	–	–

Source: authors.

Table 6. Size of the examined sample.

Sample – respondents	References
Units (1–9)	–
Tens (10–99)	Franke et al., 2017
Hundreds (100–999)	Aurier & Guintcheva, 2014, Ban et al., 2019, Bigné et al., 2005, Bogicevic & Bujisic, 2021, Brown et al., 2008, Cohen et al., 2014, del Bosque & San Martín, 2008, Farias, 2019, Faullant et al., 2011, Garry, 2008, Ha & Jang, 2013, Hackett & Foxall, 1997, Choi et al., 2019, Chu et al., 2012, Ihtiyar, 2018, Ihtiyar, 2019, Jin et al., 2012, Johnson et al., 2009, Kocabulut & Albayrak, 2019, Löfgren et al., 2008, Moliner-Velázquez et al., 2019, Orth et al., 2016, Quach et al., 2019, Rhee & Lee, 2021, Roy et al., 2017, Tan et al., 2017, Tung et al., 2017, Tuu & Olsen, 2009, Uzir et al., 2020, Wang et al., 2010, Wei et al., 2017, Yeh et al., 2019, Zhao et al., 2020
Thousands (1000 and more)	Ashworth & Bourassa, 2020, Campos et al., 2017, Faerber et al., 2021, Gountas & Gountas, 2007, Tarasi et al., 2013

Source: Authors.

Table 7. Countries where the research was conducted.

Country	References
Australia	Ashworth & Bourassa, 2020, Quach et al., 2019, Roy et al., 2017, Wanget al., 2017
Canada	Ashworth & Bourassa, 2020
New Zealand	Ashworth & Bourassa, 2020
United Kingdom	Ashworth & Bourassa, 2020
United States of America	Beatty et al., 2016, Bogicevic & Bujisic, 2021, Yeh et al., 2019, Wang & Beise-Zee, 2013
Germany	Faerber et al., 2021, Franke et al., 2017
Norway	Johnson et al., 2009
Malaysia	Tan et al., 2017, Ihtiyar, 2018, Ihtiyar, 2019
Taiwan	Wang et al., 2017, Yeh et al., 2019, Chu et al., 2012
Bangladesh	Uzir et al., 2020
China	Choi et al., 2019, Zhao et al., 2020, Yeh et al., 2019, Wang & Beise-Zee, 2013
Chile	Farias, 2019
India	Khanna & Seth, 2018
Turkey	Kocabulut & Albayrak, 2019
Spain	Moliner-Velázquez et al., 2019, Bigné et al., 2005, del Bosque & San Martín, 2008
South Korea	Rhee & Lee, 2021
France	Aurier & Guintcheva, 2014
Brazil	Campos et al., 2017
Vietnam	Tuu & Olsen, 2009

Source: authors.

Table 8. Sector in which the research was conducted.

Sector	References
Hospitality, tourism	Jouhnson et al., 2009, Wang et al., 2017, Ban et al., 2019, Bogicevic & Bujisic, 2021, Faerber et al., 2021, Kocabulut & Albayrak, 2019, Moliner-Velázquez et al., 2019, Yeh et al., 2019, Aurier & Guintcheva, 2014, Bigné et al., 2005, Cohen et al., 2014, del Bosque & San Martín, 2008, Faullant et al., 2011, Jin et al., 2012, Noe & Uysal, 2004
Education	Ashworth & Bourassa, 2020, Tan et al., 2017,
Financing	Tarasi et al., 2013, Farias, 2019, Brown et al., 2008, Chu et al., 2012,
Telecommunication	Tarasi et al., 2013
Electronics	Uzir et al., 2020, Rhee & Lee, 2021
Logistics, transport	Choi et al., 2019, Franke et al., 2017, Ban et al., 2019, Zhao et al., 2020, Garry, 2008, Hackett & Foxall, 1997, Wang et al., 2017
Retail	Ihtiyar, 2018, Ihtiyar, 2019, Khanna & Seth, 2018, Roy et al., 2017, Tuu & Olsen, 2009, Wang & Beise-Zee, 2013
Health	Campos et al., 2017, Tuu & Olsen, 2009
Oil change, petrol control	Beatty et al., 2016

Source: Authors.

The first part of the methodology was focused on research design. The results shown in Table 3 show that the research design was most often mixed, i.e. that the authors used both quantitative and qualitative methods in their research.

Only minimally did the authors use only qualitative methods (2) or quantitative methods (1). Given the scope, complexity, complexity and still the relative novelty of exploring these areas together, mixed methods can be recommended for further research, where qualitative research should first be carried out (so that the areas concerned are defined and underlined in the relevant contexts) followed by quantitative research (research which will be specified about the country, sector, possible product, possibly other factors – customer, company, etc.).

Another part of the methodology was focused on the method of measuring the investigated quantities (see Table 4). The results show that when the investigated areas were examined using quantities or factors, multidimensional constructs (10) or indexes – models (5) were most often used. Neither one-dimensional constructs nor individual quantities were used in the research. Concerning the already mentioned complexity and complexity of the researched issue, it is offered to use for further research rather than constructs (multidimensional), while the identified links between the created constructs may be the basis of a complex model or index.

The third part of the methodology focused on the research methods that were used in the research. The results show that the questionnaire was most often used across the examined areas (especially in the area of CS, but also predominated or completely dominated in the areas of CE, CP and P), the authors also used interviews (partly in the areas of CS, CP and P, and this method dominated in the CK area). To a lesser extent, the authors also used a focus group (CS, CP) and once also an experiment (CS). Interestingly, the authors did not state the method of OP research. This is probably related to the fact that the OP was assessed from a financial point of view (from accounting data) and the authors, therefore, did not need to specifically state the method of collecting this data, which they obtained by looking at the financial results of companies.

The results show that in the case of qualitative research, the most appropriate method of data collection is probably an interview, while in the case of quantitative research, a questionnaire (in both cases focused on customers). If the data obtained in this way are to be placed in the context of the OP, it is proposed to use accounting data from the financial statements of companies and focus in this context on the financial performance of companies. The investigated customers and the investigated companies will have to be reconciled to be the investigated customers of the investigated companies.

The last part of the methodology focused on statistical methods used in research of relevant areas, which are summarized in Appendix 3 (supplementary material). The results show that the most frequently used research (across research areas) were structural equation modelling (SEM), some of the variants of factor analysis, or some of the variants of regression analysis. The results also show that the authors usually used more than one method (see Table 5). Looking at the analyzed articles, it is also clear that the authors used several tests, which are used when using the appropriate statistical methods. Because statistical methods can be used only in quantitative research, these results cover only the relevant part of the analyzed articles, resp. their parts. This is also probably the reason why no statistical method was used within the areas of CK and OP. For further research of the researched areas (at least in the case of quantitative research), it is possible to use the SEM method, one of the variants of factor analysis or a similar more advanced statistical method, of course with the appropriate statistical tests.

The second sub-area was focused on the size of the examined sample. The summary results are shown in Table 6. The results show that the most frequently researched samples were several hundred respondents. Only to a lesser extent was the sample the size of over a thousand respondents or, conversely, only tens of respondents.

These results again relate to quantitative research, as in the case of qualitative research, the sample size is often not explicitly stated (especially in the case of case studies, which are performed in the units of respondents).

The third sub-area focused on the country in which the research took place. The summary results are shown in Table 7. The results show that the research was not conducted in Africa. On the contrary, the most frequent surveys were conducted in the USA, Australia and China (both 4) or Germany, Malaysia, Taiwan and Spain (3). Thus, the developed countries of Western Europe and Asia predominate in the research. Given that previous research has so far taken place in only 19 countries, the potential for further research in this direction is considerable. However, given the differences between the countries of different continents and the applicability of the results, it would probably be appropriate to focus further research on a country or countries of developed Western Europe or Asia, or a comparison of results from these countries.

The last sub-area was focused on the sector in which the research was carried out. The summary results are shown in Table 8.

The results show that the vast majority of research was focused on services; only two research was focused on products. Of the services, he was most often the subject of research on hospitality and tourism (16), logistics and transport (7) and retail (6). It is obvious that product-oriented research offers greater potential, on the other hand, research in the field of services is already more sophisticated, i.e. that it is possible to build better on previous research. Due to the diversity of services and products, the question is therefore to what extent the results from the field of services will be applicable for possible research in the field of products.

4.4. Focus and content of the publication

The last part of the Review protocol concerned the focus and content of the analyzed articles. The focus of the articles is given in the Network Map of the code What_focus and is given in Appendix 4 (supplementary material). The results showed that the most attention is paid to Customer satisfaction, which is confirmed by Figure 1. Figure 1 shows that the most common keywords (words used) are customer satisfaction. Personality, experience and service were also strongly represented. From the results, it can be deduced that the articles are focused mainly on the areas of customer satisfaction, personality and (customer) experience, while the focus on performance (OP), CP or CK is minimal. It seems, therefore, that the central research area should be CS, to which links will be sought for other areas, especially CE and P. The area of CP can be reduced to P. It also turns out that the articles are focused primarily on services, so further research is offered to focus in the same way (if the authors want to use already performed research).

Figure 1. Word map.

In the analysis of the examined areas, it was found that in most cases the authors focused on only one of the selected areas (CS, CP, CK, CE, OP or P). The exceptions were the following studies (17 out of a total of 52, ie 33%), in which more areas appeared: e.g. Ban et al. (2019) – CE and CS, Bogicevic and Bujisic (2021) – CS, P, Ihtiyar (2018, 2019) – CS and P, Moliner-Velázquez et al. (2019) – CS, P and CE, Gountas and Gountas (2007) – CS and P.

The results show that the most researched are CS, P, CE and CP. For further research, it is proposed to use the results of such focused research and expand them to the remaining areas, i.e. CK and OP. If the central topic is CS, the results of research focused on CS can be used in the context of CK and OP.

5. Synthesis of findings

The analysis of bibliographic data shows that the researched topic, resp. areas are currently (last about five years) a current research topic. Articles that focus on these areas have been generally placed in top journals in the relevant scientific disciplines. It is obvious that from the economic point of view of research it is appropriate to focus on journals in the field of business management, or marketing or management. If the intended research in these areas is well done and the researched areas are interconnected, it is realistic to place such a research result in one of the prestigious journals.

The results show that the authors devoted the most space to the definition of CS and P (e.g. Bogicevic & Bujisic, 2021; Ihtiyar, 2019; Ha & Jang, 2013). This opens up space for further research to define other research areas, with the proviso that if CS is the dominant area, other areas should be defined in this context. At the same time, the CS and P areas are proving difficult to grasp, as there are several different definitions of these areas. It is, therefore, necessary in future research to focus also on the careful definition of CS, or P concerning the subject and goal of the research, or other research areas. It also turns out that a wide area of CP can be narrowed to P, resp. focus in the field of CP on area P.

Thanks to the fact that CS is defined primarily in the context of CP, resp. P and CE (e.g. Moliner-Velázquez et al., 2019; Zhao et al., 2020; del Bosque & San Martín, 2008), the links of these three quantities can be assumed (CS, P and CE). The relationships of these three areas (and the factors that characterize them) can then form the core of the intended conceptual model and the core of future research. When defining P, it is appropriate to focus on personal traits, with a link to CS and CE. When defining CE, it is appropriate to focus on customer expectations, where a link to CS can be expected. When defining the CK, it is appropriate to focus on the general evaluation of the product or service, which is performed by the customer, with a link primarily to the CE and further to the CS and possibly also P.

The definitions of these areas (e.g. Yeh & Jeng, 2015; Tuu & Olsen, 2009; Uzir et al., 2020) indicate that they are customer-focused. On the contrary, the OP area is focused on the company. This brings a certain complication to future research because when examining the links between all areas, it will not be enough to examine not only the customer but also the company for which the relevant person (respondent) is the customer. The research will have to take place on two levels, at the customer level and the company level. Otherwise, it will probably not be possible to connect the OP with other areas. This is probably also the reason why only minimal emphasis was placed on the OP (including its proper definition) during the search. The OP will thus represent the second framework in which the research will be embedded. Concerning the performed research, the area of the company (OP) will probably be connected with the areas of the customer (CP, resp. P, CE, CK) through CS. Within the research, CP, resp. P together with CE and CK lie at the beginning of the customer-company relationship, CS in the middle of this relationship and OP at the end. The CS area will probably connect all other areas.

In the research of the studied areas, mainly (statistical) SEM methods were used (e.g. Yeh et al., 2019; Tuu & Olsen, 2009) or some of the variants of factor analysis (including relevant statistical tests, e.g. Bogicevic & Bujisic, 2021, Farias, 2019). However, the research design was mixed and, in addition to the questionnaire, interviews and other methods (focus group, experiment, etc.) were also used in several cases. Given the relative novelty of the issue, where several separate areas will be examined, which have never been studied together in this way, a mixed research design can be recommended.

First, it would be appropriate to conduct qualitative research, both at the level of the selected company in the form of a case study, and the level of customers (researched company) in the form of interviews. Subsequently, it would be appropriate to conduct quantitative research, while at the customer level it would be appropriate to construct a questionnaire and at the company level either a questionnaire combined with a preview of the company’s financial data or it would be enough (in case of reduction of OP to financial performance) to focus on the company’s financial data preview. At the same time, it is clear that the surveyed customers (as respondents) and the surveyed companies (as respondents) will have to be reconciled to examine the customers of the surveyed companies. Subsequent evaluation of quantitative research should take place together (for both groups of respondents) ideally through the SEM method (including relevant statistical tests).

Concerning the already mentioned complexity and complexity of the researched issue, it is offered to use for further research rather than multidimensional constructs for individual areas. Based on qualitative research, a conceptual model should be created, where the links between individual constructs will be proposed in the form of hypotheses, which will then be statistically tested (e.g. by the SEM method) within quantitative research.

The results show that in the case of quantitative research, hundreds of respondents were examined (e.g. Ban et al., 2019; Roy et al., 2017). The number of respondents affects the statistical significance and generalizability of the results, with a higher number of respondents increasing the chance that the results will be statistically significant (Bowling & Ebrahim, 2005). ‘In surveys, the sample should be sufficiently large so that any major subgroups contain at least 100 cases and minor subgroups contain between 20 and 50’ (Lewin, 2005). For further research, it would be suggested to recommend a sample size of hundreds. Given the wide scope of research, the expected number of multidimensional factors and especially the need to connect a larger number of customers with one researched company, it would be appropriate to recommend for quantitative research a researched sample in the thousands (in the case of customers). Structural equation modeling requires that sample sizes be greater than 200 and the general rule for SEM is that 5 to 10 observations are required for each model parameter estimated (Hussey & Eagan, 2007). In this case we have 6 main factors with many subfactors (at least in the case of customer satisfaction) and with many items (3–5) of each (sub)factors. In the case of quantitative research of companies, a sample in the order of lower hundreds of respondents would probably suffice (see above). It is clear from the proposal that the research will be relatively demanding on the volume of data and it is necessary to prepare in this regard, for example, to work with about a hundred thousand lines in Excel. It would therefore be worthwhile to limit business research to one selected sector. For qualitative research, units of companies (probably even only one) and higher units or lower tens of customers of the respective company would probably be sufficient (see above).

Because previous research has so far taken place in only 19 countries, the potential for further research in this direction is considerable. However, given the diversity between countries on different continents and the applicability of the results, it would probably be appropriate to focus further research on a country or countries in developed Western Europe or Asia.

It is obvious that product-oriented research offers greater potential, on the other hand, research in the field of services is already more sophisticated, i.e. that it is possible to build better on previous research. In the case of mixed research, it is certainly not a problem to focus on products; in the case of stand-alone quantitative research, it would be better to focus on services. Due to the diversity of services and products, the question is to what extent the results from the field of services will apply to possible research in the field of products.

6. Conclusion

As stated in the Introduction and presented in the Theoretical framework, there are partial links between the examined areas, as these areas have already been examined, either individually or within the mutual relations of several selected areas (usually two). In this respect, it is interesting that in conducting a systematic literature search, where articles and research were searched for all these research areas together, not too many results were found and the results found did not cover all research areas. On the one hand, this confirms the novelty of the chosen view and the opportunity to carry out ground-breaking research, which will be applicable in a renowned journal. On the other hand, it poses significant obstacles for researchers, whether due to the absence of comprehensive literature, the complexity of research due to mixed design or focus on two levels (company and its customer) and last but not least the large amount of data that will need to be obtained and subsequently processed. (in the framework of quantitative research).

The conducted systematic search in this direction (at least partially) filled the gap of scientific knowledge, which undoubtedly exists in the study of mutual relations of selected areas. The research found considerable potential for joint research on consumer psychology (personality), consumer experience, customer knowledge, consumer satisfaction and organizational (financial) performance. The research also found a growing interest in these areas in recent years, not only among researchers but also among renowned scientific journals.

It is clear from the research that comprehensive research focused on all researched areas does not exist together yet, only partial researches of one or several researched areas were performed. The state of knowledge is high in the sub-areas, but within the comprehensive concept of all areas together, on the contrary, very low.

Based on the research, it is recommended (for future research) to conduct extensive research (within the quantitative part) with a mixed design, within the selected country and industry (whether focused on products or services), which will be focused on customers of selected companies. The first should be qualitative research (with using of grounded theory) the result of which should be a theoretical model, which will then be verified by subsequent quantitative research. From the customer’s point of view, satisfaction (with the product), experience (with the product), knowledge (product) and personality (the customer) should be examined, and from the company’s point of view, organizational (financial) performance. We recommend conducting this research using either SEM-PLS (due to the relationships between the factors under study, consisting of a number of items) or hierarchical modelling (due to the different levels of modelling – customer, company, or sector or country).

The limitation of our research is mainly the fact that these factors constitute separate research topics, which have not been investigated in this form, in terms of complexity and breadth. Therefore, it will be necessary to find interconnections (relationships). The considerable breadth and complexity is also a major obstacle to future research, as quantitative research will be very data intensive. Another limitation of the research is the impossibility of verifying the results obtained, precisely because of the lack of specialized research on the chosen topic.

Author contributions

Conception and design S.Č., analysis and interpretation of the data S.Č. and P.S.; the drafting of the paper S.Č., revising it critically for intellectual content P.S.; the final approval of the version to be published; S.Č. and P.S. All authors agree to be accountable for all aspects of the work.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The authors confirm that the data supporting the findings of this study are available within the article.

Additional information

Notes on contributors

Petr Suchánek

Petr Suchánek, Ph.D. is a lecturer and a researcher, he is interested in customer loyalty, customer satisfaction and business performance. His disciplines are Business Economics and Business Administration.

Simona Činčalová

Simona Činčalová, Ph.D. is a lecturer and a researcher, she is interested in corporate social responsilbity (CSR), customer satisfaction and loyalty, gender gap and managerial ethics.