Abstract
This paper aims to enhance the understanding of the influencing factors and consequences of feedback, with a particular focus on brand outputs and co-creation, and to identify future research areas related to feedback. First, we propose to clarify definitions by introducing actionable customer feedback and drawing clear distinctions among synonymic concepts used in the literature. Then, we conduct a systematic literature review of 73 journal articles from the past two decades and synthesize their findings in the feedback, brand, and co-creation intercept. We also introduce a structure for feedback-related antecedents, moderators, mediators, and performance outputs. As a main contribution, we offer a visual representation of the findings of the systematic literature review to support scholars of customer behavior who are discovering their own directions according to their expertise. Through the use of visual tools such as tables and figures, we provide summary statistics reflecting the methodologies used in the literature, the industries involved, the geographical spread, and adjacent theories used. We also summarize the different positions of feedback within conceptual frameworks. We contribute to the literature by proposing and visually demonstrating new grouping dimensions of the antecedents, mediators, moderators and performance outcomes of the feedback literature. Finally, we recommend directions for future research on actionable feedback. We recommend studying the mediating and moderating impacts of demographics, gender, environmental characteristics, geography (especially developing economies), and B2B businesses on actionable feedback. The roles of trust and feedback in brand outputs, for example, brand value and brand equity, requires further investigation. Finally, we recommend exploring constructs in which feedback plays multiple roles in different positions.
1 Introduction
Consumer feedback is an essential building block of the customer-supplier relationship (Gremyr et al. 2022; Hanssens – Pauwels 2016; Kohtamäki et al. 2021). As a significant source of information (Mou et al. 2019), it plays an essential role in the innovation capability of firms (Nathai-Balkissoon et al. 2017), and a vast amount of input is generated daily, especially by digital tools. As a result, gathering customer feedback has become more accessible and less expensive for firms. However, the easy accessibility of information has also made transforming it into a strategic advantage more challenging. Therefore, a structured approach is needed that offers understanding of the underlying mechanisms, the prerequisites, and the effects of feedback. In addition, it is critical to understand how feedback can create value. Therefore, a structured approach should consider the relevance of feedback in co-creation and brand outputs.
There are various definitions of customer feedback in the literature, such as the product or service information that consumers feed back to sellers (Guo – Li 2022). Feedback is also described as a general communication process in which the sender provides information about the receiver's output (Dargahi – Namin 2021). Moreover, feedback contains solicited and unsolicited information for service improvement (Yi – Gong 2013). Solicited feedback is often called active feedback because the receiver actively initiates it, whereas unsolicited feedback is often referred to as passive feedback (Gremyr et al. 2022). Both parties can initiate feedback in various formats, including one- and two-way feedback (i.e., co-creation). Scholars also point out that the difference between codified and personalized feedback. Codified feedback is digitally acquired and transmitted data, often in a formal database, whereas personalized feedback is informal that is generated and transmitted between people (Gremyr et al. 2022).
In this study, we propose further clarification of the definition of feedback. In behavioral science, feedback is actionable information about the difference between the desired and actual levels of any system parameters (Ramaprasad 1983). Therefore, in the proposed definition, customer feedback should refer to the actionable information provided by customers to the vendor about the gap between an actual product parameter and the desired parameter from the consumer's point of view. Thus, in its content, feedback is a form of consciously provided customer insight.
Following the logic of actionable information related to a product parameter, we should draw a clear distinction between our definition and several concepts used synonymously with feedback in the literature. The term customer information describes any information about customers, especially their online behavior (Taylor 2004); even if such data are gathered with the individual's consent, this information cannot be regarded as a conscious actionable input about a product parameter. Customer reviews and customer opinions describe conscious information sharing from the customer's side, but the scope is broader than that of pure product parameter information. Therefore, customer reviews and customer opinions may contain actionable feedback but are not necessarily equal to that. WOM (word of mouth) is an interaction between consumers. By sharing market- and product-related information, consumers influence one another's behavior and attitudes (Huete-Alcocer 2017). Although firms analyze and use WOM as a vital source of information for product development and service improvement, WOM does not always contain actionable information on product parameters.
Feedback has already been studied extensively in the literature (Nasr et al. 2018). There are also systematic literature reviews (SLRs) on eWOM in the hospitality context (Chen – Law 2016), on customer loyalty in the insurance industry (Larsson – Broström 2020), and on mobile app data mining, with a particular focus on customer opinion (Genc-Nayebi – Abran 2017). However, we did not find a general, industry-independent review that synthesizes recent customer feedback-related studies in the literature.
After conceptually narrowing the definition of feedback, this study poses the following research question: What are the influencing factors and consequences of feedback, especially regarding brand outputs and co-creation?
Co-creation is included in our research question for two reasons. First, the literature often examines feedback as part of the co-creation process. Second, according to our definition of feedback, value is created via one or two methods of communication. For example, a dialog (i.e., two-way communication) between customers and suppliers or between multiple stakeholders (Vargo – Lusch 2008) can be regarded as a co-creation mechanism, as information is mutually shared and resources are mutually allocated behind the work stream. Our investigation should also focus on co-creation and subsets of co-creation theories (Prahalad – Ramaswamy 2004).
There is a wealth of literature on constructs with a feedback component. Therefore, there is an opportunity to integrate the knowledge attained from a feedback perspective to investigate the impact of feedback on brand outputs and its role in co-creation. As a result, this study aims to conduct a systematic literature review (Tranfield et al. 2003) using the relevant Q1–Q3 literature in the co-creation, feedback, and brand intercept.
This study has several implications. First, we narrow the definition of feedback by distinguishing it from synonymic terms; then, by reviewing the contemporary body of literature, we introduce a new general synthesis of the main antecedents, performance outputs, mediators, and moderators of feedback. Next, we identify relevant specific brand outputs. We provide figures and tables for the examined variables to support the academic community in finding future directions for research. Moreover, this study provides an extensive list of actionable directions for future studies to better understand the influence of feedback on brands. Finally, the study highlights the operational importance of our synthesis for managers.
The remainder of this study is structured as follows. First, we explain the review process and share the findings of the feedback literature, focusing on its relation to co-creation and brand value. Accordingly, we describe how feedback and embracing constructs can occupy different positions in empirical models. After that, we summarize and synthesize the variables of the literature, explaining personal-individual, relational, and product- or process-related antecedents as well as brand output- and value proposition output-type performance variables. We also provide a summary of related moderators and mediators. Finally, based on the areas already covered in the contemporary literature, we highlight research gaps and recommend future research. At the end of the study, we also discuss the managerial implications of this paper.
2 Literature review
2.1 Process
To understand the current academic viewpoints about feedback and its main antecedents and consequences, with particular attention given to brand outputs, we conducted a systematic literature review (Tranfield et al. 2003). Using the Scopus online search engine and Web of Science database, we collected articles from the past two decades, from November 2002 to November 2023. Feedback or customer feedback provided a general, broad scope. To focus on brand outputs and include co-creation, we used the following search term criteria for available journal articles: co-creation and (&) feedback and (&) brand (n = 71)/co-creation and (&) customer feedback (n = 45)/co-creation and (&) consumer feedback (n = 11)/brand value and (&) feedback (n = 95). The number of articles in the area has shown an accelerating trend in recent years. Within the studied period, 51% of all articles were published in the last three years (2021–2023) (Fig. 1). Following standard exclusion criteria (Keszey 2020), we selected articles from Q1–Q3 journals (n = 188). Of the selected articles, 21 were excluded because “feedback” had a different definition, namely, describing the subsequent effect of an action on a specific object (i.e., feedback of brand extension on the brand), and an additional 105 articles were removed based on a deeper analysis of the abstracts (Kohtamäki et al. 2018), as these articles did not elaborate on the feedback phenomenon. These exclusions reduced the number of relevant articles to 73 for further analysis. In the literature review, we used a coding scheme to collect information about the industry, geography, analytical method used, sample size of the empirical study, theoretical research framework, and variables examined in the empirical studies.
Number of journal articles by year of publishing co creation & feedback & brand/co creation & customer feedback/co creation & consumer feedback/brand value & feedback
Source: authors.
Citation: Society and Economy 47, 1; 10.1556/204.2024.00011
2.2 Overview of the literature
Table 1 provides summary statistics from the literature. Twenty-seven percent of studies were conducted in Asia, 25% in Europe, 15% in North America, 4% in Australia, 3% in South America, and 3% in Africa, while the rest did not specify the place of origin. Scholars have focused primarily on services or service-type activities within defined industries. In general, the importance of the hospitality industry has grown in academic studies over the past two decades (Morosan et al. 2014). In our research, hospitality and leisure was the most researched segment (n = 20, 27%), with more than twice the number of studies than the second most popular industry, technology/IT/telecom (n = 7, 9%).
Literature statistics (n = 73)
| Article distribution by geographies | Article distribution by journal ranking | ||||
| Asia | 20 | Q1 | 43 | ||
| Europe | 18 | Q2 | 18 | ||
| North America | 11 | Q3 | 12 | ||
| Australia & New Zealand | 3 | ||||
| South America | 2 | Analytical methods | |||
| Africa | 2 | Quantitative | |||
| Multiple/not defined | 17 | SEM | 36 | ||
| Experimental design | 7 | ||||
| Article distribution by industries | Regression | 4 | |||
| Hospitality and leisure | 20 | Other | 4 | ||
| Cross industries | 17 | Qualitative | |||
| Tech: It, Telecom | 7 | Netnography | 2 | ||
| Not defined | 6 | Content analysis | 1 | ||
| Small business/services | 5 | Other | 7 | ||
| Banking, Finance | 4 | n.a. | 12 | ||
| Vehicle, Transport | 4 | ||||
| Fashion | 3 | Adjacent theories appeared in multiple articles by frequency | |||
| Retail | 3 | Social exchange theory | 10 | ||
| Education | 2 | Customer citizenship theory | 5 | ||
| Consultancy | 1 | Stimulus-organism-response framework | 4 | ||
| Food | 1 | Identity/Social identity theory | 3 | ||
| Consumer culture theory | 2 | ||||
| Expectancy theory | 2 | ||||
| Flow theory | 2 | ||||
| Article distribution by sample size* | Self-determination theory | 2 | |||
| Quantitative studies | Self-presentation theory | 2 | |||
| below 100 | 2 | Stakeholder theory | 2 | ||
| 100–200 | 6 | Uses and gratification theory | 2 | ||
| 200–500 | 26 | Attribution theory | 2 | ||
| above 500 | 17 | Self-congruence theory | 2 | ||
| Empowerment theory | 2 | ||||
*Articles with multiple empirical studies included.
Note. Search words: co creation & feedback & brand/co creation & customer feedback/co creation & consumer feedback/brand value & feedback; Q1–Q3.
Source: authors.
Ninety-three percent (n = 68) of the research focused on business-to-consumer (B2C) or consumer-to-consumer (C2C) aspects, whereas only five articles discussed the business-to-business context (B2B) (Gosling et al. 2017; Gremyr et al. 2022; Rubio et al. 2021; Sandbacka et al. 2013; Sarkar – Banerjee 2021). Most empirical research (n = 51) was based on existing theories and studies of other latent variables and examined the interplay between sets of variables using structural equation modeling (SEM, n = 36). Most models drew conclusions based on 200+ respondents. The average sample size was 354.
2.3 Adjacent theories
Social exchange theory (SET) dominates the literature (Assiouras et al. 2019; Bozkurt et al. 2021; Hussain et al. 2021; Kim et al. 2022; Paulssen et al. 2019; Rubio et al. 2021; Saunders – Rod 2012; Seifert – Kwon 2019; Torres-Moraga et al. 2021; Van Tonder – Petzer 2022). This theory posits that people engage in social interactions to gain personal or social benefits (Kim et al. 2022). The extended interpretation of SET suggests that these interactions extend beyond the activities necessary to maintain a pure customer-supplier relationship (Assiouras et al. 2019). Alongside core business transactions, there is additional perceived value in the information exchange characterized by informal reciprocity (Blau 2017). Therefore, the perceived cost and expected benefit of such interactions must be balanced. Furthermore, feedback is not necessarily part of operational transactions, and a perceived value must be attached to compensate for the effort of giving and receiving the information (Alford 2002).
The second most frequently used theoretical approach is customer citizenship theory (Arica – Çorbaci 2020; Assiouras et al. 2019; Burnham et al. 2021; Dewalska-Opitek – Mitręga 2019; Van Tonder – Petzer 2022). Customer citizenship behavior involves a set of actions that are not part of prompt core service delivery but rather help both the receiver and the provider in the long term (Groth 2005). Finally, the third most frequently used theory is the stimulus‒organism‒response theory (Aljarah – Alrawashdeh 2020; Carlson et al. 2018; Guo – Li 2022; Zakiah et al. 2023), which provides a general framework for studying consumer behavior, elaborating the input/stimulus, output/response, and internal organismic factors (Jacoby 2002). The stimulus‒organism‒response theory makes no specific reference to feedback. However, feedback is part of customer interaction, primarily in the online arena or social media (Al Amin 2022); therefore, its presence is essential and cannot be excluded.
2.4 Conceptual clarification and the position of feedback in empirical studies
The selected articles with quantitative analysis (n = 51) cover a wide range of antecedents and outcomes, among which we first focus on the position of feedback. Table 2 shows the various roles assigned to feedback in the empirical models.
Summary of feedback roles and positions within conceptual frameworks
Source: authors.
The table is structured in three segments: antecedents, mediators/moderators and performance outputs. In each segment, we further separate the constructs into two groups: constructs in which feedback or its thematically identical variations are standalone variables and constructs in which feedback is present as an element of another construct. The relevance of constructs in which feedback is included must be explained. The following section introduces these embracing constructs and explains their feedback connections.
2.5 Feedback as part of another construct
Customer citizenship behavior (Aljarah – Alrawashdeh 2020; Arica – Çorbaci 2020; Assiouras et al. 2019; Dewalska-Opitek – Mitręga 2019; Oertzen et al. 2020; Torres-Moraga et al. 2021; van Tonder et al. 2020; Van Tonder – Petzer 2022; Yi – Gong 2013; Zakiah et al. 2023) as a voluntary act (Groth 2005) consists of a wide range of activities, such as assisting other customers, providing solicited responses to companies, sub-divisions, advocacy, and participating in firm activities (Balaji 2014). We regard solicited responses as feedback, which is helpful information for the firm to improve service delivery (Balaji 2014).
Another essential construct is co-creation (Akman et al. 2018; Arica – Çorbaci 2020; Assiouras et al. 2019; Chou et al. 2018; Dretsch et al. 2023; Ferm – Thaichon 2021; France et al. 2020; Kennedy 2017; Liljedal 2016; Sarkar – Banerjee 2021; Seifert – Kwon 2019; Shulga – Busser 2020; Zhang – Ma 2021). It assumes a continuous dialog between firms and customers and drives processes from one-way, firm-to-customer communication to two- or multiway customer-to-firm or customer-to-customer communication (Prahalad – Ramaswamy 2004). Multiway communication to improve service delivery must include actionable information on performance parameter improvement; therefore, feedback is an integral part of co-creation (Ramaswamy – Ozcan 2018).
Customer participation (Zhang et al. 2022) generally refers to any activities a customer needs for successful service delivery (Yi et al. 2011). Therefore, customer participation is a construct in which feedback plays a role. It has also been proven in the banking industry that customer feedback surveys can be part of successful customer retention strategies (Chahal – Bala 2017). Another feedback-embracing construct is flow (Csikszentmihalyi – Csikszentmihalyi 1992). The literature describes flow as a focused and rewarding mental state during an extensively engaging activity (Sangroya et al. 2021). The prerequisites for reaching this psychological stage are clear goals, autonomy, feedback, and concentration (Yoo et al. 2018).
Interaction behavior is a two-way interpersonal communication between actors before, during, and after service delivery (Busagara et al. 2020). The exchange aims for optimal service; therefore, feedback is an integral part of it. Customer engagement behavior (Bozkurt et al. 2021; Carlson et al. 2018; Shen et al. 2020; Vokić et al. 2022; Zakiah et al. 2023) spans from recommendations and WOM to blogs, supporting other customers, writing reviews, and taking legal action (Van Doorn et al. 2010). Writing reviews and taking legal action meet the definition of feedback in terms of providing operational information on reducing the gap between the actual and the desired state of a parameter (Van Doorn et al. 2010). The extra role of customers, including customer citizenship behavior, describes the voluntary gestures of customers that do not involve actual purchase or consumption but can consist of product development participation, support for other customers, or the provision of constructive feedback (Hussain et al. 2021; Paulssen et al. 2019).
Introducing these concepts in our study provides an opportunity to better understand the feedback mechanism, as it is not a standalone action but part of a complex process. We observed that specific models locate feedback in multiple roles. For example, the co-creation process contains feedback, which impacts customer citizenship behavior, in which feedback is also included (Assiouras et al. 2019); as another example, customer citizenship behavior mediates the impact of value co-creation on satisfaction (Arica – Çorbaci 2020).
2.6 Antecedents and performance outcomes of feedback in empirical studies
After reviewing the various feedback positions, we summarize their antecedents and performance outcomes. We created new grouping dimensions (Kohtamäki et al. 2018) to synthesize the empirical studies. First, we listed the individual variables from the analyzed literature and grouped the identical variables and the conceptually identical synonyms into subgroups; then, subgroups were consolidated into three main categories, as shown in Fig. 2. The main categories of antecedents are personal/individual, relational, and process- or product-related, while the performance outcomes are summarized under two categories: brand outcome and value proposition outcome.
Summary of the antecedents and performance outcome variables of feedback
Citation: Society and Economy 47, 1; 10.1556/204.2024.00011
2.6.1 Antecedents of feedback
Personal/individual antecedents refer to the quality, knowledge, or attributes of the feedback provider. Accordingly, attitude refers to a set of emotions or beliefs of the feedback provider toward a particular object (Akman et al. 2018; Oertzen et al. 2020; Seifert – Kwon 2019; van Tonder et al. 2020; Van Tonder – Petzer 2022); brand attachment describes the emotional connection of the feedback provider to the brand (Hussain et al. 2021); brand experience is a subjective internal response to brand-related stimuli (Kennedy 2017; Sarkar – Banerjee 2021; Yang et al. 2021); brand knowledge refers to the individual's understanding of the brand and products (Sarkar – Banerjee 2021); demographics (Oertzen et al. 2020) are related to the characteristics of the individual; and motivation is the driving force behind the individual's actions (Burnham et al. 2021; Dewalska-Opitek – Mitręga 2019). Self-congruity refers to the difference or similarity between one's self-perception and one's perception of a brand (Shen et al. 2020).
Relational antecedents are those that refer to an aspect of a relationship between the feedback receiver (i.e., the firm) and the feedback provider (i.e., the customer), such as company relations, under which we categorize variables determining firms' activities targeting the customer-firm relationship (Dewalska-Opitek – Mitręga 2019; Fagerstrøm et al. 2020; Paulssen et al. 2019; Sarkar – Banerjee 2021), and engagement, through which we describe the strengths of the relationship between the actors (Ferm – Thaichon 2021; France et al. 2018; Piyathasanan et al. 2017; Vokić et al. 2022; Yang et al. 2021). Market orientation (Robinson – Celuch 2016) describes a company's attitude and willingness to utilize customer and market information (Hooley et al. 2000), while relatedness is vital for understanding the motivation of individuals to relate to others and achieve meaningful involvement (Sarkar – Banerjee 2021). Social interactions empower community members to provide feedback and increase individuals' interest in helping fellow members (Akman et al. 2018). Finally, trust highlights the importance of the feedback provider's confidence in the feedback receiver (Akman et al. 2018; Ferm – Thaichon 2021; Rubio et al. 2021; Yang et al. 2021).
Process and product-related antecedents refer either to a process in which both the feedback provider and the feedback receiver are engaged (and exert an influence on the feedback, i.e., co-creation) or to a product and its attributes (i.e., quality). These variables are co-creation (Arica – Çorbaci 2020; Assiouras et al. 2019; Sarkar – Banerjee 2021), “a business strategy used in the practices based on cooperation with customers” (Arica – Çorbaci 2020, p. 2), and corporate actions involving various company processes and activities (Abbas et al. 2018; Aljarah – Alrawashdeh 2020; Bozkurt et al. 2021; Kennedy 2017; Sarkar – Banerjee 2021). An image describes a general impression of a subject, such as a tourist destination (Vokić et al. 2022). Perceived values or benefits are product-related attributes (Celuch – Walz 2020; Hussain et al. 2021; Robinson – Celuch 2016; Rubio et al. 2019; Sarkar – Banerjee 2021; Van Tonder – Petzer 2022), similar to product quality (Carlson et al. 2018; Oertzen et al. 2020; Zakiah et al. 2023) and product usage (Tseng 2020).
2.6.2 Performance outcomes of feedback
Performance outcomes are grouped into brand outcomes and value proposition outcomes. Under the brand outcomes subcategory, we summarize brand-related performance outcomes, such as brand avoidance (Abro et al. 2020), which describes the phenomenon in which consumers deliberately choose a different brand (Lee et al. 2009); brand engagement, which is the attachment between the brand and consumers (Caber et al. 2023; Sangroya et al. 2021; Shen et al. 2020); and brand image (Sandbacka et al. 2013), which is a subjective perception of brand performance based on set parameters (Patterson 1999). Brand value is the financial worth of the brand (Chahal – Bala 2017; France et al. 2020). Employer branding (Tandon et al. 2023) refers to the reputation of employers among employees and job seekers. Customer retention equity describes the monetary value of a firm's ability to retain customers (Chahal – Bala 2017). Loyalty (Vokić et al. 2022) refers to employee attachment and devotion as a positive outcome of employer branding. Purchase intention refers to the customer's willingness to purchase the brand or the product (Guo – Li 2022; Liljedal 2016). Finally, we also regard trust (Liu et al. 2023) as a brand outcome.
Regarding value proposition outcomes, we consider feedback outcomes related to either customer satisfaction, which describes to what extent the product meets the customer's expectation, or abandonment likelihood, which describes the probability of a negative purchase decision (Jain et al. n.d.). The value proposition outcome can also be a set of perceived values (Arica – Çorbaci 2020; Furenes et al. 2018; Furenes et al. 2017). Perceived values include emotional value, which is a positive feeling attached to an action or goods received (France et al. 2020); epistemic value, which is a perceived value of cognitive success (Piyathasanan et al. 2017); and price, quality, and social values (France et al. 2020; Kim et al. 2022). Price value refers to the monetary exchange required to obtain a product, whereas quality values are derived from the product's perceived performance, including value for money and overall service ratings (Kim et al. 2022). In other words, these are economic values (Cabiddu et al. 2019), while social value is the product's ability to influence social identification (France et al. 2020).
Process-related outcomes refer to the set of coordinated activities as a whole on which the feedback or the feedback provider has a major influencing role. We regard flow experience (Zakiah et al. 2023) and value co-creation (Dretsch et al. 2023) as potential process-related outcomes of the feedback.
2.7 Moderators and mediators of feedback in empirical studies
The analyzed empirical studies provide a large selection of mediators and moderators, which are summarized in Fig. 3. First, we discuss the moderators and mediators influencing the antecedent impact on feedback, and then, we summarize the variables moderating and mediating the influence of feedback on performance outcomes. As in the case of the antecedents of feedback, we group the moderator and mediator variables under the three main categories: personal/individual, relational, and process or product related.
Summary of the mediators and moderators of the feedback constructs
Citation: Society and Economy 47, 1; 10.1556/204.2024.00011
2.7.1 Moderators of feedback antecedents (Fig. 3, Section I.)
Personal/individual moderators of feedback antecedents are attitude, which is a set of emotions or beliefs held by the feedback provider regarding a particular object (van Tonder et al. 2020; Van Tonder – Petzer 2022; Yang et al. 2021), and motivation, which is the driving force behind individuals' actions (Paulssen et al. 2019). Under the title of relational moderators of feedback antecedents, relationship type refers to the length of the company-customer relationship and whether the customer is a member of the loyalty program (Rubio et al. 2021). Process- or product-related feedback antecedent moderators are brand/platform usage, which considers the feedback provider's choice of brand or digital platform (Bozkurt et al. 2021; Rubio et al. 2019), and employee benevolence, which measures the perceived goodwill of the employee of the service provider toward the customer (Celuch – Walz 2020).
2.7.2 Mediators of the feedback antecedents (Fig. 3, Section II.)
Like feedback antecedent moderators, attitude is positioned as a personal/individual mediator (Ferm – Thaichon 2021; van Tonder et al. 2020); similarly, we list brand experience as an individual mediator of feedback impact (Hongsuchon et al. 2023). Relational mediators of feedback antecedents include customer identification, which entails measuring the feedback provider's emotional association with the feedback receiver (Celuch – Walz 2020), and engagement, which refers to customer engagement (Zakiah et al. 2023) as a “state of mind that motivates customers to adopt company-supporting behaviors” (Abbas et al. 2018: 4). Under process- or product-related feedback antecedent mediators, we list perceived values and benefits. This term refers either to guest satisfaction (Assiouras et al. 2019) or to perceived service quality (Aljarah – Alrawashdeh 2020).
2.7.3 Moderators of the performance outcomes of feedback (Fig. 3, Section III.)
Personal/individual moderators of the performance outcomes of feedback are brand knowledge, which is also positioned as an antecedent of feedback (Liljedal 2016); gender (Sangroya et al. 2021); and global connectedness, which refers to individuals' relationships with the globalized world (Roy Bhattacharjee et al. 2023). Relational moderators of the performance outcomes of feedback are information credibility, or the perceived quality of the information (Abro et al. 2020). Credible information is “information which has several supports” (Abro et al. 2020: 5). Process- or product-related moderators of the feedback outcomes are feedback type, which refers either to the source of the feedback, i.e., peer feedback (Zhang – Ma 2021), or to positive feedback (Furenes et al. 2018). Innovativeness refers to a user's skills and attitude toward participating in product development (Windasari – Visita 2019). Process enjoyment describes participants' psychological state during the activity (Furenes et al. 2018). Finally, product complexity examines the level of perceived consumer competence to co-create (Liljedal 2016).
2.7.4 Mediators of the performance outcomes of feedback (Fig. 3, Section IV.)
Personal/individual mediators of the performance outcomes of feedback include the following. First, the disconfirmation of expectations occurs when an individual's initial expectations about a specific performance differ from his or her perceived performance (Piyathasanan et al. 2017). Positive disconfirmation drives satisfaction. The need for recognition is an individual characteristic of the co-creator (Piyathasanan et al. 2017) involving the “need to have one's self, one's works, and other things associated with one's self, known and approved by others” (Schaffer 1953: 4). Finally, psychological ownership describes a feeling of possessiveness regarding the target product (Roy Bhattacharjee et al. 2023). Relational mediators of the performance outcomes of feedback are brand engagement (Furenes et al. 2017; Sangroya et al. 2021), which is defined as “the level of an individual customer's motivational, brand-related & context-dependent state of mind characterized by specific levels of cognitive, emotional & behavioral activity in brand interactions” (Hollebeek 2011: 7), and psychological distance, which “refers to the subjective experience of something or someone being close to or far from the self” (Zhang – Ma 2021: 3).
Process or product-related mediators of the performance outcomes of feedback include communication quality, which refers to the perceived quality of the information exchange for the consumers (Kim et al. 2022), as well as corporate actions such as networking, corporate communications, and the service process (Sandbacka et al. 2013). Customer citizenship behavior involves a set of actions that are not part of prompt core service delivery (Arica – Çorbaci 2020) but that help both the receiver and the provider in the long term (Groth 2005). The organizational response is the reaction of the firm to a service failure or negative customer feedback (Abro et al. 2020). Perceived values or benefits are utilitarian values, which provide substantial gains (relevant information about product experiences, promotions, or value for money (Kim et al. 2022)) to the individual, and hedonic values, which relate to the psychological satisfaction derived from community interactions (Guo – Li 2022).
3 Agenda for future research
In this paper, we performed a systematic literature review of the influencing factors and consequences of feedback, with a particular focus on brand outputs and co-creation. First, we formalized the definition of actionable feedback. Then, based on the systematic analysis of 73 journal articles from the past two decades involving the intersections of feedback, branding, and co-creation, we provided comprehensive statistics on geographical and industry distributions, adjacent theories, journal rankings, sample sizes, and methods used. We found that most of studies were B2C related (mainly leisure and hospitality) and empirical based on social exchange and customer citizenship theory. We also identified that the antecedents, mediators and moderators used by scholars can be divided into three groups: personal/individual, relational and process/product related. Similarly, we classified performance outcomes into brand-related, value proposition-related, and process-related outcomes. Our findings are visually presented in two tables and two figures to support scholars in finding their own path for future research; nevertheless, in this section, we provide our own recommendations.
We recommend including additional demographic data in future studies. It is important to note that gender exerts a significant influence on engagement in customer citizenship behavior (Balaji 2014). The moderating role of gender has been studied extensively in the literature (Harymawan et al. 2023; Mensah – Boachie 2023; Setyowati et al. 2023). Gender moderates the feedback effect, but whether it moderates or mediates the impact of antecedents on feedback should be further explored. Current studies also need more information about the mediating or moderating impact of age groups and education. Thus, future research should explore this topic further. We also recommend studying how environmental characteristics influence the feedback process: examples could include the service sector versus production (manufacturing), the lucrative commercial situation versus struggling businesses, the profitability level of the category, or even the overall business ecosystem.
Adding different industries and other geographic regions would also contribute to the generalization of emerging theories. For example, although Western Europe is well covered in feedback-related research, Eastern Europe needs more representation in the literature. Although market orientation is applicable in transitioning economies, similar to Western Europe (Hooley et al. 2000), there are sociopolitical (Kornai 2016) and economic developmental differences (Karo – Kattel 2015) compared to Western economies. Therefore, we recommend exploring feedback-related processes in African, Eastern European, and South American companies.
Based on the literature, we identified trust as a relational antecedent of feedback. We recommend further studies on feedback-trust relations. One direction is to investigate how trust can mediate or moderate the influence of feedback on a brand outcome (i.e., brand equity). The second is to investigate how feedback can influence trust, similar to studies of the impact of credible online reviews (Tran et al. 2022). Among the 73 analyzed articles, we found only one recent study in which the impact of feedback on trust was explored in an online trading platform context (Liu et al. 2023). The rationale for this recommendation is that negotiation theories often link cooperation and trust (Ross – LaCroix 1996). Customers are willing to promote service innovation if perceived support or trust is present (Rubio et al. 2021), and brand trust exerts an impact on purchase intentions (Husain et al. 2022).
We also recommend exploring the importance of feedback on brand preference and brand equity and deepening the understanding of the impact of feedback on brand value. Several brand-related antecedents and brand outcomes have been analyzed in the literature; among those, brand avoidance has been studied in the telecom context (Abro et al. 2020), but we did not find empirical data for brand preference concerning feedback. The influence of feedback on brand value has been shown in the banking (Chahal – Bala 2017) and IT sectors (France et al. 2020). Nevertheless, we need to gain knowledge of this phenomenon in other industries. Moreover, examining the specific impact of feedback exchange, we could not find evidence of a strong influence on brand value, as it was not proven that the feedback element of the co-creation process exerts any positive impact on the perceived quality, emotional, price, or social values related to the brand in a B2C environment (France et al. 2020). Furthermore, we did not find brand equity among the variables in the studied literature. In addition to discussing brand value, brand equity, and feedback, we need more information about the potential negative impact of ignoring or not reacting appropriately to consumer feedback. Therefore, future studies should define and validate models in which feedback and the reaction to the feedback influence brand-related measures.
Feedback is a relevant element of the firm-to-firm relationship, as it plays a similar role in firm-to-customer or individual-to-individual relations (Rubio et al. 2021). However, the literature has focused primarily on business-to-consumer (B2C) examinations. Therefore, we recommend exploring feedback constructs in the B2B environment. The exploratory nature of the recommended path suggests the use of inductive qualitative methods (Edmondson – McManus 2007). Within that approach, a multiple case study would enable the researcher to examine phenomena in context (Eisenhardt et al. 2016).
Additionally, we recommend conducting further quantitative studies on B2B feedback processes. According to the resource-based view (Wernerfelt 1984), firm characteristics influence how information is used. Therefore, future research should also consider different firm characteristics, such as company size by the number of employees, ownership type, chief marketing officers' presence, business performance relative to competitors, goods versus service business, and B2B versus B2C business relations.
The main theory used in B2C studies related to feedback and co-creation is social exchange theory (Table 1), which assumes that such interactions occur even without financial benefits (Assiouras et al. 2019). However, in the B2B context, it is challenging to assume a lack of monetary motivation. The existence of monetary motivations highlights a new potential research aspect of the B2B feedback process, and future studies need to examine the validity of social exchange theory or citizenship behavior versus the resource-based view and negotiation theories. As certain variables are positioned in different roles in the feedback processes (i.e., attitude, engagement, perceived values, brand outcomes), we propose an experimental design approach to test the usage of the same variables in multiple positions in one model and to test the impact of the multiple occurrences of feedback, i.e., feedback on the feedback.
4 Managerial contributions
Employing data-driven decision-making contributes to higher productivity and profitability compared to competitors (McAfee et al. 2012). However, data utilization requires technological, organizational, and cultural adoption from the firm (McAfee et al. 2012). According to our definition, feedback is also essential actionable data for companies. The value of such data depends on the absorption capacity of the firm (Keszey 2011) and what can be triggered if feedback-related processes are present (Gremyr et al. 2022). Therefore, it is imperative to approach feedback-related processes systematically. While established processes often handle product-related codified feedback, service-related, personalized feedback processes are often missing (Gremyr et al. 2022). Leaders should thoroughly understand how feedback works and the potential technological, organizational, and cultural aspects of the feedback process.
To support that understanding, we provide a structure of the potential antecedents of feedback. Depending on the context, managers can acknowledge or select from the individual/personal or relational antecedents or even influence or decide upon the product- or process-related antecedents. For example, a firm can select from whom to accept feedback but can also improve the feedback process by offering a mechanism that encourages feedback providers. By selecting the antecedents used for feedback, managers can better control the cost of the feedback process.
Although the primary benefit of feedback derives from leveraging data, feedback influences several brand outputs and value proposition outputs as well. Therefore, to understand the total benefit of the feedback process, managers should supplement the value of the feedback data with the value of those outputs. For managers, it is also essential to be aware of feedback performance outcomes, as they not only represent benefits but can also produce risk if ignored or mishandled. For example, feedback can change purchase intention and influence perceived quality value (Liljedal 2016). To be able to read and interpret the outcomes from feedback processes, managers must be aware of the moderators and mediators as well, and we provide a structure for attaining such knowledge in this study.
5 Limitations
Despite its merit, we acknowledge that our work has some limitations. The data collection was limited to Q1–Q3 articles in the World of Science and Scopus databases. Other sources (e.g., industry reports, textbooks, Google Scholar database) were excluded from our search, as were conference contributions and articles from Q4 journals. Another limitation is the keywords used. We examined articles by the search term criteria of feedback, co-creation, and brand. Synonyms of those search words and other search words were not included. Further search criteria could be added in future studies to expand the results.
The analysis focused on providing a conceptual overview of the topic and discovering how the influencing factors and consequences of feedback have been addressed in the literature. We must acknowledge that the rich literature provides a vast range of findings from different angles, but it was not our objective to provide an extensive description of those findings. Similarly, we cannot report all the different variables used in the studies. Rather, we had to follow a specific grouping and synthesizing logic, which the authors arbitrarily designed. We hope to provide helpful directions for future research, although the related section contains only the most relevant concepts and ideas from the authors' point of view. We recommend that researchers explore and identify further opportunities based on the figures included, especially by adding further mediators and moderators to the research agenda.
Disclosure
The authors report that there are no competing interests to declare.
References
Abbas, M. – Gao, Y. – Shah, S. S. H. (2018): CSR and Customer Outcomes: The Mediating Role of Customer Engagement. Sustainability 10(11): 4243. https://doi.org/10.3390/su10114243.
Abro, M. A. – Baharun, R. – Zubair, A. (2020): Information Credibility and Organizational Feedback; a Solution to Plethora of Consumer Advocacy, Brand Avoidance and Community Usefulness. The Bottom Line 33(2): 165–181. https://doi.org/10.1108/BL-12-2019-0133.
Akman, H. – Plewa, C. – Conduit, J. (2018): Co-creating Value in Online Innovation Communities. European Journal of Marketing 53(6): 1205–1233. https://doi.org/10.1108/EJM-12-2016-0780.
Al Amin, M. (2022): The Influence of Psychological, Situational and the Interactive Technological Feedback-Related Variables on Customers’ Technology Adoption to Use Online Shopping Applications. Journal of Global Marketing 35(5): 384–407. https://doi.org/10.1080/08911762.2022.2051157.
Alford, J. (2002): Defining the Client in the Public Sector: A Social‐exchange Perspective. Public Administration Review 62(3): 337–346. https://doi.org/10.1111/1540-6210.00183.
Aljarah, A. – Alrawashdeh, M. (2020): Boosting Customer Citizenship Behavior through Corporate Social Responsibility: Does Perceived Service Quality Matter? Social Responsibility Journal 17(5): 631–347. https://doi.org/10.1108/SRJ-03-2019-0098.
Arica, R. – Çorbaci, A. (2020): The Mediating Role of the Tourists’ Citizenship Behavior between the Value Co-creation and Satisfaction. Advances in Hospitality and Tourism Research 8(1): 125–150. https://doi.org/10.30519/ahtr.649639.
Assiouras, I. – Skourtis, G. – Giannopoulos, A. – Buhalis, D. – Koniordos, M. (2019): Value Co-creation and Customer Citizenship Behavior. Annals of Tourism Research 78: 102742. https://doi.org/10.1016/j.annals.2019.102742.
Balaji, M. S. (2014): Managing Customer Citizenship Behavior: a Relationship Perspective. Journal of Strategic Marketing 22(3): 222–239. https://doi.org/10.1080/0965254X.2013.876076.
Blau, P. M. (2017): Exchange and Power in Social Life. New York: Routledge. https://doi.org/10.4324/9780203792643.
Bozkurt, S. – Gligor, D. M. – Babin, B. J. (2021): The Role of Perceived Firm Social Media Interactivity in Facilitating Customer Engagement Behaviors. European Journal of Marketing 55(4): 995–1022. https://doi.org/10.1108/EJM-07-2019-0613.
Burnham, T. A. – Ridinger, G. – Carpenter, A. – Choi, L. (2021): Consumer Suggestion Sharing: Helpful, Pragmatic and Conditional. European Journal of Marketing 55(3): 726–762. https://doi.org/10.1108/EJM-10-2019-0806.
Busagara, T. – Mori, N. – Mossberg, L. – Jani, D. – Andersson, T. (2020): Customer Information Sharing and New Service Development: Is There a Link? The Bottom Line 33(2): 133–147. https://doi.org/10.1108/BL-09-2019-0112.
Caber, M. – Albayrak, T. – Karasakal, S. – González-Rodríguez, M. R. (2023): Building Customer Citizenship Behaviour through Mobile Application Quality: the Mediating Role of Flow Experience and Customer Engagement. Current Issues in Tourism: 1–16. https://doi.org/10.1080/13683500.2023.2241606.
Cabiddu, F. – Moreno, F. – Sebastiano, L. (2019): Toxic Collaborations: Co-destroying Value in the B2B Context. Journal of Service Research 22(3): 241–255. https://doi.org/10.1177/1094670519835311.
Carlson, J. – Rahman, M. – Voola, R. – De Vries, N. (2018): Customer Engagement Behaviours in Social Media: Capturing Innovation Opportunities. Journal of Services Marketing 32(1): 83–94. https://doi.org/10.1108/JSM-02-2017-0059.
Celuch, K. – Walz, A. M. (2020): The Role of Active Identification in Driving Retail Customer Feedback. Services Marketing Quarterly 41(2): 163–181. https://doi.org/10.1080/15332969.2020.1742980.
Chahal, H. – Bala, R. (2017): Role of Customer Retention Equity in Creating and Developing Brand Value. Journal of Relationship Marketing 16(2): 119–142. https://doi.org/10.1080/15332667.2016.1242397.
Chen, Y.-F. – Law, R. (2016): A Review of Research on Electronic Word-Of-Mouth in Hospitality and Tourism Management. International Journal of Hospitality and Tourism Administration 17(4): 347–372. https://doi.org/10.1080/15256480.2016.1226150.
Chou, C. Y. – Huang, C. H. – Lin, T.-A. (2018): Organizational Intellectual Capital and its Relation to Frontline Service Employee Innovative Behavior: Consumer Value Co-creation Behavior as a Moderator. Service Business 12(4): 663–684. https://doi.org/10.1007/s11628-018-0387-4.
Csikszentmihalyi, M. – Csikszentmihalyi, I. S. (1992): Optimal Experience: Psychological Studies of Flow in Consciousness. Cambridge, MA: Cambridge University Press.
Dargahi, R. – Namin, A. (2021): Making More in Crowdsourcing Contests: a Choice Model of Idea Generation and Feedback Type. Journal of Marketing Communications 27(6): 607–630. https://doi.org/10.1080/13527266.2020.1748094.
Dewalska-Opitek, A. – Mitręga, M. (2019): “Appreciate Me and I Will Be Your Good Soldier”. The Exploration of Antecedents to Consumer Citizenship. Engineering Management in Production and Services 11(3): 48–59. https://doi.org/10.2478/emj-2019-0020.
Dretsch, H. J. – Kirmani, A. – Lundberg, J. (2023): Designing Brand Cocreation Activities to Increase Digital Consumer Engagement. Journal of Interactive Marketing 52(2): 151–166. https://doi.org/10.1177/10949968231191097.
Edmondson, A. C. – McManus, S. E. (2007): Methodological Fit in Management Field Research. Academy of Management Review 32(4): 1246–1264. https://doi.org/10.5465/amr.2007.26586086.
Eisenhardt, K. M. – Graebner, M. E. – Sonenshein, S. (2016): Grand Challenges and Inductive Methods: Rigor without Rigor Mortis. Academy of Management Journal 59(4): 1113–1123. https://doi.org/10.5465/amj.2016.4004.
Fagerstrøm, A. – Bendheim, L. M. – Sigurdsson, V. – Pawar, S. – Foxall, G. R. (2020): The Marketing Firm and Co‐creation: An Empirical Study of Marketer and Customer's Co‐creation Process. Managerial and Decision Economics 41(2): 216–225. https://doi.org/10.1002/mde.3076.
Ferm, L.-E. C. – Thaichon, P. (2021): Value Co-creation and Social Media: Investigating Antecedents and Influencing Factors in the US Retail Banking Industry. Journal of Retailing and Consumer Services 61: 102548. https://doi.org/10.1016/j.jretconser.2021.102548.
France, C. – Grace, D. – Lo Iacono, J. – Carlini, J. (2020): Exploring the Interplay between Customer Perceived Brand Value and Customer Brand Co-creation Behaviour Dimensions. Journal of Brand Management 27(4): 466–480. https://doi.org/10.1057/s41262-020-00194-7.
France, C. – Grace, D. – Merrilees, B. – Miller, D. (2018): Customer Brand Co-creation Behavior: Conceptualization and Empirical Validation. Marketing Intelligence & Planning 36(3): 334–348. https://doi.org/10.1108/MIP-10-2017-0266.
Furenes, M. I. – Gjerald, O. – Øgaard, T. (2018): Say It’s Fantastic or Say Nothing at All: Effects of Feedback on Consumers’ Satisfaction with the Outcome of Co-production. Cogent Business & Management 5(1): 1516109. https://doi.org/10.1080/23311975.2018.1516109.
Furenes, M. I. – Øgaard, T. – Gjerald, O. (2017): How Face-To-Face Feedback Influences Guest Outcome Evaluation of Co-production: Changing or Shaping Guest Experiences? Tourism Management Perspectives 21: 59–65. https://doi.org/10.1016/j.tmp.2016.11.004.
Genc-Nayebi, N. – Abran, A. (2017): A Systematic Literature Review: Opinion Mining Studies from Mobile App Store User Reviews. Journal of Systems and Software 125: 207–219. https://doi.org/10.1016/j.jss.2016.11.027.
Gosling, J. – Hewlett, B. – Naim, M. M. (2017): Extending Customer Order Penetration Concepts to Engineering Designs. International Journal of Operations & Production Management 37(4): 402–422. https://doi.org/10.1108/IJOPM-07-2015-0453.
Gremyr, I. – Birch-Jensen, A. – Kumar, M. – Löfberg, N. (2022): Quality Functions' Use of Customer Feedback as Activation Triggers for Absorptive Capacity and Value Co-creation. International Journal of Operations & Production Management 42(13): 218–242. https://doi.org/10.1108/IJOPM-11-2021-0692.
Groth, M. (2005): Customers as Good Soldiers: Examining Citizenship Behaviors in Internet Service Deliveries. Journal of Management 31(1): 7–27. https://doi.org/10.1177/0149206304271375.
Guo, J. – Li, L. (2022): Exploring the Relationship between Social Commerce Features and Consumers’ Repurchase Intentions: The Mediating Role of Perceived Value. Frontiers in Psychology 12. https://doi.org/10.3389/fpsyg.2021.775056.
Hanssens, D. M. – Pauwels, K. H. (2016): Demonstrating the Value of Marketing. Journal of Marketing 80(6): 173–190. https://doi.org/10.1509/jm.15.0417.
Harymawan, I. – Anridho, N. – Minanurohman, A. – Ningsih, S. – Kamarudin, K. A. – Raharjo, Y. (2023): Do More Masculine-Faced CEOs Reflect More Tax Avoidance? Evidence from Indonesia. Cogent Business & Management 10(1): 2171644. https://doi.org/10.1080/23311975.2023.2171644.
Hollebeek, L. (2011): Exploring Customer Brand Engagement: Definition and Themes. Journal of Strategic Marketing 19(7): 555–573. https://doi.org/10.1080/0965254X.2011.599493.
Hongsuchon, T. – Rahardja, U. – Khan, A. – Wu, T.-H. – Hung, C.-W. – Chang, R.-H., Chen, S.-C. (2023): Brand Experience on Brand Attachment: The Role of Interpersonal Interaction, Feedback, and Advocacy. Emerging Science Journal 7(4): 1232–1246. http://dx.doi.org/10.28991/ESJ-2023-07-04-014.
Hooley, G. – Cox, T. – Fahy, J. – Shipley, D. – Beracs, J. – Fonfara, K. – Snoj, B. (2000): Market Orientation in the Transition Economies of Central Europe: Tests of the Narver and Slater Market Orientation Scales. Journal of Business Research 50(3): 273–285. https://doi.org/10.1016/S0148-2963(99)00105-8.
Huete-Alcocer, N. (2017): A Literature Review of Word of Mouth and Electronic Word of Mouth: Implications for Consumer Behavior. Frontiers in Psychology 8: 1256. https://doi.org/10.3389/fpsyg.2017.01256.
Husain, R. – Ahmad, A. – Khan, B. M. (2022): The Impact of Brand Equity, Status Consumption, and Brand Trust on Purchase Intention of Luxury Brands. Cogent Business & Management 9(1): 2034234. https://doi.org/10.1080/23311975.2022.2034234.
Hussain, K. – Jing, F. – Junaid, M. – Zaman, Q. U. – Shi, H. (2021): The Role of Co-creation Experience in Engaging Customers with Service Brands. Journal of Product & Brand Management 30(1): 12–27. https://doi.org/10.1108/JPBM-08-2019-2537.
Jacoby, J. (2002): Stimulus‐organism‐response Reconsidered: an Evolutionary Step in Modeling (Consumer) Behavior. Journal of Consumer Psychology 12(1): 51–57. https://doi.org/10.1207/S15327663JCP1201_05.
Jain, S. – Sharma, K. – Devi, S. (n.d.): The Dynamics of Value Co‐creation Behavior: A Systematic Review and Future Research Agenda. International Journal of Consumer Studies 48(1). https://doi.org/10.1111/ijcs.12993.
Karo, E. – Kattel, R. (2015): Economic Development and Evolving State Capacities in Central and Eastern Europe: Can “Smart Specialization” Make a Difference? Journal of Economic Policy Reform 18(2): 172–187. https://doi.org/10.1080/17487870.2015.1009068.
Kennedy, E. (2017): I Create, You Create, We All Create – for Whom? Journal of Product & Brand Management 26(1): 68–79. https://doi.org/10.1108/JPBM-01-2016-1078.
Keszey, T. (2011): How Market Information Is Transformed into Marketing Knowledge? Acta Oeconomica 61(3): 313–336. https://doi.org/10.1556/aoecon.61.2011.3.4.
Keszey, T. (2020): Behavioural Intention to Use Autonomous Vehicles: Systematic Review and Empirical Extension. Transportation Research Part C: Emerging Technologies 119: 102732. https://doi.org/10.1016/j.trc.2020.102732.
Kim, H. – Shin, H. H. – So, K. K. F. (2022): Actor Value Formation in Airbnb: Insight from Multi-Source Data. International Journal of Contemporary Hospitality Management 34(7): 2773–2797. https://doi.org/10.1108/IJCHM-10-2021-1208.
Kohtamäki, M. – Rabetino, R. – Einola, S. – Parida, V. – Patel, P. (2021): Unfolding the Digital Servitization Path from Products to Product-Service-Software Systems: Practicing Change through Intentional Narratives. Journal of Business Research 137: 379–392. https://doi.org/10.1016/j.jbusres.2021.08.027.
Kohtamäki, M. – Rabetino, R. – Möller, K. (2018): Alliance Capabilities: A Systematic Review and Future Research Directions. Industrial Marketing Management 68: 188–201. https://doi.org/10.1016/j.indmarman.2017.10.014.
Kornai, J. (2016): The System Paradigm Revisited: Clarification and Additions in the Light of Experiences in the Post-socialist Region. Acta Oeconomica 66(4): 547–596. https://doi.org/10.1556/032.2016.66.4.1.
Larsson, A. – Broström, E. (2020): Ensuring Customer Retention: Insurers’ Perception of Customer Loyalty. Marketing Intelligence & Planning 38(2): 151–166. https://doi.org/10.1108/MIP-02-2019-0106.
Lee, M. S. – Motion, J. – Conroy, D. (2009): Anti-consumption and Brand Avoidance. Journal of Business Research 62(2): 169–180. https://doi.org/10.1016/j.jbusres.2008.01.024.
Liljedal, K. T. (2016): The Effects of Advertising Consumer Co-created New Products: A Brand-Alliance Framework Model Can Predict Perceptions about Co-created Brands and Their Creators. Journal of Advertising Research 56(1): 53–63. https://doi.org/10.2501/JAR-2016-011.
Liu, Y. – Wan, Y. – Kang, J. (2023): Impact of Community-Based Governance Mechanisms on Transaction Intention on a Second-Hand Trading Platform. Journal of Theoretical and Applied Electronic Commerce Research 18(1): 689–705. https://doi.org/10.3390/jtaer18010035.
McAfee, A. – Brynjolfsson, E. – Davenport, T. H. – Patil, D. – Barton, D. (2012): Big Data: the Management Revolution. Harvard business Review 90(10): 60–68.
Mensah, E. – Boachie, C. (2023): Corporate Governance Mechanisms and Earnings Management: The Moderating Role of Female Directors. Cogent Business & Management 10(1): 2167290. https://doi.org/10.1080/23311975.2023.2167290.
Morosan, C. – T. Bowen, J. – Atwood, M. (2014): The Evolution of Marketing Research. International Journal of Contemporary Hospitality Management 26(5): 706–726. https://doi.org/10.1108/IJCHM-11-2013-0515.
Mou, J. – Ren, G. – Qin, C. – Kurcz, K. (2019): Understanding the Topics of Export Cross-Border E-Commerce Consumers Feedback: an LDA Approach. Electronic Commerce Research 19(4): 749–777. https://doi.org/10.1007/s10660-019-09338-7.
Nasr, L. – Burton, J. – Gruber, T. (2018): Developing a Deeper Understanding of Positive Customer Feedback. Journal of Services Marketing 32(2): 142–160. https://doi.org/10.1108/JSM-07-2016-0263.
Nathai-Balkissoon, M. – Maharaj, C. – Guerrero, R. – Mahabir, R. – Dialsingh, I. (2017): Pilot Development of Innovation Scales for Beverage Manufacturing Companies in a Developing Country. Cogent Business & Management 4(1): 1379214. https://doi.org/10.1080/23311975.2017.1379214.
Oertzen, A.-S. – Odekerken-Schröder, G. – Mager, B. (2020): Driving Users’ Behaviours and Engagement in Co-creating Services. Journal of Services Marketing 34(4): 549–573. https://doi.org/10.1108/JSM-06-2019-0244.
Patterson, M. (1999): Re-appraising the Concept of Brand Image. Journal of Brand Management 6: 409–426. https://doi.org/10.1057/bm.1999.32.
Paulssen, M. – Brunneder, J. – Sommerfeld, A. (2019): Customer In-Role and Extra-role Behaviours in a Retail Setting: The Differential Roles of Customer-Company Identification and Overall Satisfaction. European Journal of Marketing 53(12): 2501–2529. https://doi.org/10.1108/EJM-06-2017-0417.
Piyathasanan, B. – Mathies, C. – Patterson, P. G. – de Ruyter, K. (2017): Continued Value Creation in Crowdsourcing from Creative Process Engagement. Journal of Services Marketing 32(1): 19–33. https://doi.org/10.1108/JSM-02-2017-0044.
Prahalad, C. K. – Ramaswamy, V. (2004): Co-creation Experiences: The Next Practice in Value Creation. Journal of Interactive Marketing 18(3): 5–14. https://doi.org/10.1002/dir.20015.
Ramaprasad, A. (1983): On the Definition of Feedback. Behavioral Science 28(1): 4–13. https://doi.org/10.1002/bs.3830280103.
Ramaswamy, V. – Ozcan, K. (2018): What Is Co-creation? an Interactional Creation Framework and its Implications for Value Creation. Journal of Business Research 84: 196–205. https://doi.org/10.1016/j.jbusres.2017.11.027.
Robinson, N. M. – Celuch, K. G. (2016): Strategic and Bonding Effects of Enhancing the Student Feedback Process. Journal of Marketing for Higher Education 26(1): 20–40. https://doi.org/10.1080/08841241.2016.1146386.
Ross, W. – LaCroix, J. (1996): Multiple Meanings of Trust in Negotiation Theory and Research: A Literature Review and Integrative Model. International Journal of Conflict Management 7(4): 314–360. https://doi.org/10.1108/eb022786.
Roy Bhattacharjee, D. – Kuanr, A. – Malhotra, N. – Pradhan, D. – Moharana, T. R. (2023): How Does Self-Congruity Foster Customer Engagement with Global Brands? Examining the Roles of Psychological Ownership and Global Connectedness. International Marketing Review 40(6): 1480–1508. https://doi.org/10.1108/IMR-09-2022-0206.
Rubio, N. – Villaseñor, N. – Yague, M. J. (2019): Does Use of Different Platforms Influence the Relationship between Cocreation Value-In-Use and Participants’ Cocreation Behaviors? An Application in Third-Party Managed Virtual Communities. Complexity 2019(1): 7562903. https://doi.org/10.1155/2019/7562903.
Rubio, N. – Villaseñor, N. – Yagüe, M. J. (2021): Value Co-creation between Consumers and Distributors: the Moderating Effect of Relationship Characteristics. International Journal of Retail & Distribution Management 49(7): 1067–1088. https://doi.org/10.1108/IJRDM-10-2020-0390.
Sandbacka, J. – Nätti, S. – Tähtinen, J. (2013): Branding Activities of a Micro Industrial Services Company. Journal of Services Marketing 27(2): 166–177. https://doi.org/10.1108/08876041311309270.
Sangroya, D. – Yadav, R. – Joshi, Y. (2021): Does Gamified Interaction Build a Strong Consumer-Brand Connection? A Study of Mobile Applications. Australasian Journal of Information Systems 25. https://doi.org/10.3127/ajis.v25i0.3105.
Sarkar, S. – Banerjee, S. (2021): Brand Co-creation through Participation of Organization, Consumers, and Suppliers: an Empirical Validation. Journal of Product & Brand Management 30(8): 1094–1114. https://doi.org/10.1108/JPBM-01-2020-2732.
Saunders, S. – Rod, M. (2012): Brand Network Maps: A Multidimensional Approach to Brand‐consumer Relationships in the New Zealand Pharmacy Industry. International Journal of Pharmaceutical and Healthcare Marketing 6(1): 55–70. https://doi.org/10.1108/17506121211216905.
Schaffer, R. H. (1953): Job Satisfaction as Related to Need Satisfaction in Work. Psychological Monographs: General and Applied 67(14): 1. https://psycnet.apa.org/doi/10.1037/h0093658.
Seifert, C. – Kwon, W.-S. (2019): SNS eWOM Sentiment: Impacts on Brand Value Co-creation and Trust. Marketing Intelligence & Planning 38(1): 89–102. https://doi.org/10.1108/MIP-11-2018-0533.
Setyowati, A. – Bany-Ariffin, A. N. – Kamarudin, F. – Matemilola, B. T. (2023): Role of Women Board Members in the Relationship between Internal CSR and Firm Efficiency: Evidence from Multiple Countries. Cogent Business & Management 10(1): 2173048. https://doi.org/10.1080/23311975.2023.2173048.
Shen, B. – Xu, X. – Yuan, Q. (2020): Demand Learning through Social Media Exposure in the Luxury Fashion Industry: See Now Buy Now versus See Now Buy Later. IEEE Transactions on Engineering Management 70(4): 1295–1311. https://doi.org/10.1109/TEM.2020.3009742.
Shulga, L. V. – Busser, J. A. (2020): Customer Self-Determination in Value Co-creation. Journal of Service Theory and Practice 31(1): 83–111. https://doi.org/10.1108/JSTP-05-2020-0093.
Tandon, A. – Aggarwal, A. G. – Aggarwal, S. (2023): Understanding the Determinants of Reviewer Credibility: an Interpretive Structural Modeling and Artificial Neural Network Approach. Annals of Operations Research: 1–21. https://doi.org/10.1007/s10479-023-05640-8.
Taylor, C. R. (2004): Consumer Privacy and the Market for Customer Information. RAND Journal of Economics 35(4): 631–650. https://doi.org/10.2307/1593765.
Torres-Moraga, E. – Rodriguez-Sanchez, C. – Sancho-Esper, F. (2021): Understanding Tourist Citizenship Behavior at the Destination Level. Journal of Hospitality and Tourism Management 49: 592–600. https://doi.org/10.1016/j.jhtm.2021.11.009.
Tran, V. D. – Nguyen, M. D. – Lương, L. A. (2022): The Effects of Online Credible Review on Brand Trust Dimensions and Willingness to Buy: Evidence from Vietnam Consumers. Cogent Business & Management 9(1): 2038840. https://doi.org/10.1080/23311975.2022.2038840.
Tranfield, D. – Denyer, D. – Smart, P. (2003): Towards a Methodology for Developing Evidence-Informed Management Knowledge by Means of Systematic Review. British Journal of Management 14(3): 207–222. https://doi.org/10.1111/1467-8551.00375.
Tseng, T. H. (2020): Facilitation of “Strong” Branded Application Outcomes–The Self-Concept Perspective. Journal of Product & Brand Management 30(7): 976–989. https://doi.org/10.1108/JPBM-03-2020-2783.
Van Doorn, J. – Lemon, K. N. – Mittal, V. – Nass, S. – Pick, D. – Pirner, P. – Verhoef, P. C. (2010): Customer Engagement Behavior: Theoretical Foundations and Research Directions. Journal of Service Research 13(3): 253–266. https://doi.org/10.1177/1094670510375599.
Van Tonder, E. – Fullerton, S. – de Beer, L. T. (2020): Cognitive and Emotional Factors Contributing to Green Customer Citizenship Behaviours: a Moderated Mediation Model. Journal of Consumer Marketing 37(6). https://doi.org/10.1108/JCM-06-2019-3268.
Van Tonder, E. – Petzer, D. J. (2022): Factors Promoting Customer Citizenship Behaviours and the Moderating Role of Self-Monitoring: a Study of Ride-Hailing Services. European Business Review 34(6): 876–896. https://doi.org/10.1108/EBR-09-2021-0197.
Vargo, S. L. – Lusch, R. F. (2008): Service-dominant Logic: Continuing the Evolution. Journal of the Academy of Marketing Science 36: 1–10. https://doi.org/10.1007/s11747-007-0069-6.
Vokić, N. P. – Verčič, A. T. – Ćorić, D. S. (2022): Strategic Internal Communication for Effective Internal Employer Branding. Baltic Journal of Management 18(1): 19–33. https://doi.org/10.1108/BJM-02-2022-0070.
Wardley, L. J. – Bélanger, C. H. – Nadeau, J. (2017): A Co-creation Shift in Learning Management: Work Design for Institutional Commitment and Personal Growth. Higher Education 74(6): 997–1013. https://doi.org/10.1007/s10734-016-0090-0.
Wernerfelt, B. (1984): A Resource‐based View of the Firm. Strategic Management Journal 5(2): 171–180. https://doi.org/10.1002/smj.4250050207.
Windasari, N. A. – Visita, L. (2019): User Engagement Mechanisms of Online Co-design Service: Does User Innovativeness Matter? Asian Academy of Management Journal 24(1): 59–82. https://doi.org/10.21315/aamj2019.24.1.3.
Yang, B. – Yu, H. – Yu, Y. – Liu, M. (2021): Community Experience Promotes Customer Voice: Co-creation Value Perspective. Marketing Intelligence & Planning 39(6): 825–841. https://doi.org/10.1108/MIP-01-2021-0030.
Yi, Y. – Gong, T. (2013): Customer Value Co-creation Behavior: Scale Development and Validation. Journal of Business Research 66(9): 1279–1284. https://doi.org/10.1016/j.jbusres.2012.02.026.
Yi, Y. – Nataraajan, R. – Gong, T. (2011): Customer Participation and Citizenship Behavioral Influences on Employee Performance, Satisfaction, Commitment, and Turnover Intention. Journal of Business Research 64(1): 87–95. https://doi.org/10.1016/j.jbusres.2009.12.007.
Yoo, C. W. – Sanders, G. L. – Cerveny, R. P. (2018): Exploring the Influence of Flow and Psychological Ownership on Security Education, Training and Awareness Effectiveness and Security Compliance. Decision Support Systems 108: 107–118. https://doi.org/10.1016/j.dss.2018.02.009.
Zakiah, S. – Winarno, A. – Hermana, D. (2023): Examination of Consumer Engagement for Loyalty in Sustainable Destination Image. Cogent Social Sciences 9(2): 2269680. https://doi.org/10.1080/23311886.2023.2269680.
Zhang, H. – Ma, Z. (2021): Is My Design Better? A Co-creation Perspective for Online Fashion Design. Journal of Research in Interactive Marketing 16(3): 308–402. https://doi.org/10.1108/JRIM-05-2021-0132.
Zhang, Y. – Su, J. – Guo, H. – Lee, J. Y. – Xiao, Y. – Fu, M. (2022): Transformative Value Co-creation with Older Customers in E-Services: Exploring the Influence of Customer Participation on Appreciation of Digital Affordances and Well-Being. Journal of Retailing and Consumer Services 67: 103022. https://doi.org/10.1016/j.jretconser.2022.103022.
