A review of consumer-to-consumer digital information and knowledge sharing Open Access

The rapid advancement and confluence of technologies favoring digitalization and cultural changes has shifted consumer behavior to the digital world. This digital behavior is observed in scenarios such as social networks, platforms, e-commerce sites, and a multitude of digital communities formed for various purposes.

Current digital scenarios expand the possibilities of consumer behavior benefiting both companies and society. For example, in addition to making purchases in digital settings, consumers generate referrals, influence others, and share information through social media (Kumar and Pansari, 2016). Information sharing formats depend on the recipients of the information and knowledge generated by consumers. In a consumer-to-business (C2B) (co-production) format, consumers interact with artificial intelligence (AI) or company employees, and the information they provide is used for the co-production of products/services (Ebrahimi et al., 2021). In the consumer-to-consumer (C2C) (co-consumption) format, information and knowledge are directed toward other consumers, helping them increase their knowledge and improve their decisions.

There are two prominent trends in C2C information sharing studies. The first is word of mouth (WOM), or its digital variant, electronic word of mouth (eWOM), that focuses on persuasive communication among consumers with a clear positive or negative valence. Although eWOM does not cement knowledge, it has a strong chance of becoming viral. Therefore, eWOM is of significant short-term interest to marketing management. (Cheung and Thadani, 2012; Hennig-Thurau et al., 2004). The second is information and knowledge sharing (I&KS) that focuses more on the construction and accumulation of knowledge than on virality. I&KS is an emerging research topic in the discipline of consumer behavior (Camillieri et al., 2024).

I&KS has crucial social and economic implications. From a social perspective, I&KS promotes consumer empowerment, constructs digital communities (Boyd et al., 2014), and lays the foundation of the sharing economy (Aoki, 2021). It generates a better balance of power between organizations and consumers by allowing them to act in more informed ways. Additionally, ideas for more responsible behavior are disseminated within the framework of the C2C flow of information and knowledge. Therefore, I&KS represents a space with great capacity to contribute to the United Nations (2015) Sustainable Development Goal 12: Responsible Consumption and Production. From an economic perspective related to business, I&KS digital spaces are valuable repositories of knowledge that allow companies to calibrate their marketing strategies and identify ideas for product development or improvement. Additionally, from similar economic perspective, I&KS behavior is highly desirable for companies, as it is closely linked to brand loyalty and future purchase intentions (Li et al., 2022; Sukhu and Bilgihan, 2014).

From a quantitative perspective, I&KS remains a less developed field than eWOM (Donthu et al., 2021). However, the implications of I&KS are more significant. As I&KS has economic and social importance and is a developing field in consumer studies, this study contributes to this area by evaluating and presenting I&KS knowledge through a systematic literature review. To the best of our knowledge, as no previous study has undertaken this effort,. It is necessary to stimulate growth in this area and avoid fragmentation or repetition (Cruz-Cárdenas et al., 2021; Snyder, 2019). Accordingly, we propose the goals of our study in terms of specific objectives (O1–O3), referring to the existing literature on C2C I&KS in the digital world:

• O1.

  To describe the main characteristics of the published body of documents.

• O2.

  To systematize the results of the selected articles.

• O3.

  To establish knowledge gaps and generate guidelines for future research.

This remaining study is organized as follows: Section 2 presents the fundamental concepts of I&KS and compares them with similar concepts. Section 3 describes the stages of the study based on the PRISMA method and input–process–output model used to organize the existing knowledge for the selected 51 articles. Section 4 provides the main characteristics of 51 articles. Section 5 presents the most relevant results of the content analysis according to the input–process–output model and main themes or topics in 51 articles using Leximancer, a text mining tool. Section 6 discusses the results and implications. Finally, Section 7 concludes the study and provides guidelines for professional practice and future research.

Information sharing in the business world can take various paths: business to business (B2B), business to consumer (B2C), C2B, and C2C.

Consumers are fundamental actors in information sharing. In the C2B format, consumers become co-creators of value by sharing information and knowledge about products and services with companies. In the C2C format, consumers share information with other consumers, leading to citizenship behavior such as helping other consumers or clients by performing functions similar to those of company employees (Ebrahimi et al., 2021).

Consumers store information and knowledge called tacit knowledge in their minds owing to their experience, studies, or own research. Tacit knowledge becomes explicit when externalized through communication (Panahi et al., 2012). Therefore, technology and digital social spaces are fundamental to I&KS. Digital platforms and their tools, such as posts, likes, ratings, questions and answers (Q&As), multimedia resources, and emojis, facilitate and accelerate information transmission.

Information sharing behavior among consumers in the C2B format often transforms into C2C knowledge sharing; for example, when consumers share information and knowledge with companies by making inquiries, submitting complaints and suggestions, and extending congratulations (Mogaji et al., 2021). When these actions are conducted through social media and other digital spaces, they become available to other consumers, generating useful information and knowledge. As the main interest of consumers in these cases is to initiate a dialogue with companies, the interactions are partly hidden from other consumers by continuing it through internal channels. Similarly, information and knowledge shared through C2C are also available to companies and are useful in improving their products or services.

Regarding C2C I&KS behavior underscored in this study (i.e. to build knowledge and communities), some points must be highlighted. A dynamic way to conceive I&KS behavior is based on the online purchasing process. Consumers play multiple roles in e-commerce; they are mainly information seekers in decision-making processes and share information after a purchase (Lin and Wang, 2023). On some e-commerce platforms, only qualified buyers can provide product ratings and reviews.

Another way to conceive I&KS is based on consumer involvement. On the one hand, knowledge sharing can adopt an exclusively informative format, only endorsing information (e.g. liking or forwarding) or generating simple information, such as providing simple recommendations (Brodie et al., 2016). Here, consumers focus on evaluating and popularizing their knowledge. On the other hand, consumers innovate and share their own designs or modifications to existing products/services, such as health treatments, art, software, home improvement, and cooking recipes (De Jong and Lindsen, 2022). The significant time and effort invested by consumers engender paid knowledge sharing, in which consumer innovation is transformed into adapted or innovative products marketed in sharing economy environments (Aoki, 2021).

Another useful way to understand I&KS is to contextualize it within the types of exchanges among consumers. While I&KS is related to information and knowledge support, people in some communities seek broader support. For example, in online health communities, the concept of social support encompasses both I&KS and emotional support (empathy and solidarity) (Hajli, 2014; Zhou et al., 2020). Social support (i.e. knowledge and emotional support) is essential for consumers to feel attracted to online communities (Hajli, 2014).

Two other concepts involving consumer interaction with information and/or knowledge in virtual environments are eWOM and online brand advocacy (OBA). Section 1 discusses eWOM and how it differs from I&KS. eWOM refers to information in a simple and persuasive format that has polarity (positive or negative) and a probability of going viral (Cheung and Thadani, 2012; Hennig-Thurau et al., 2004). In contrast, OBA is always positive toward a brand. It includes both verbal and nonverbal communication (e.g. exclamations and emojis) (Wilk et al., 2020). It overlaps with I&KS to some extent. However, I&KS behavior in the consumption field extends beyond just information about the brand and includes information and knowledge in broader areas of consumption, such as products and their use, consumption habits, sustainability, places of purchase, and technologies. In general, I&KS is considered a recent development in the discipline of consumer behavior (Camilleri et al., 2024).

I&KS has consequences of varying depths for individual consumers and societies. At a more superficial level, it is viewed as an input that improves consumer decision-making (Lin and Wang, 2023). At a deeper level, I&KS is an instrument for changing consumer and societal behaviors (Kiss et al., 2024; Wang et al., 2024; Zhang et al., 2024a). These behavioral changes have been a target of interest for both for-profit companies and public and non-profit organizations. Thus, companies seek to stimulate behaviors favorable to the purchase of their products, whereas non-profit and government organizations seek to spread consumer behaviors that are more sustainable. Changing consumer behaviors becomes even more complex to achieve when a large part of these behaviors has migrated to the digital world (Olan et al., 2024; Phuthong, 2023; Zhang et al., 2024b).

The social diffusion theory is a valuable tool for understanding the adoption of alternative behaviors to those prevailing in society (Ye et al., 2021). Combining this theory with new digital tools for I&KS would generate mechanisms of social change that are highly valuable to different types of organizations. At the center of these mechanisms are consumers as behavior propagators (Kiss et al., 2024; Wang et al., 2024). Using focused analyses, previous authors have allowed us to infer that knowledge about I&KS has irregularly developed. For example, researchers have a strong preference for studying I&KS behavior as a dependent variable (Wang et al., 2024; Zhang et al., 2024a). Owing to the significant gap in theoretical knowledge and the underemployed potential of I&KS in professional practice, it becomes necessary to structure and organize the state of the art of research in I&KS. As no previous studies have undertaken this effort, the present study aimed to contribute to this area of research by reviewing the existing literature on I&KS.

Bibliometric studies and systematic literature reviews analyze existing knowledge in an area and discover its structure. Bibliometric studies are efficient in scientific fields characterized by extensive documentary research, where they establish their performance and map science (Donthu et al., 2021). Systematic literature reviews investigate a few studies, but establish, in a more profound and critical way, the knowledge accumulated in an area, detect research gaps, and draw guidelines for future studies (Page et al., 2021; Palmatier et al., 2018; Snyder, 2019). As I&KS is a recent and growing field with limited research (unlike eWOM), we selected a systematic literature review method for this study.

This study was conducted in a series of stages commonly accepted in literature review research practice (Cruz-Cárdenas et al., 2021; Palmatier et al., 2018): 1) formulation of objectives, 2) search strategies and inclusion of documents, 3) analysis of the selected documents, and 4) discussion and recommendations. Each stage was guided by the PRISMA philosophy. These guidelines, initially formulated by Moher et al. (2009), are updated several times, most recently by Page et al. (2021).

This study’s methodological process has the following stages: Stage 1 involves the formulation of objectives, where the study objectives are outlined as describing, systematizing, and generating recommendations regarding the state of knowledge about I&KS. Stage 2 covers the document search and inclusion strategies (Section 3). Stage 3 focuses on the analysis of selected documents (Sections 4 and 5). Finally, Stage 4 includes the discussion and recommendations (Section 6).

The search strategy began with the selection of the target database. The main criterion was the balance between the content quality and breadth of coverage. Accordingly, of the two academic and scientific databases with impact metrics, Web of Science (WOS) and Scopus, we selected the Scopus database because it offered greater coverage than WOS, with almost twice as many journals with impact metrics, and most WOS journals with impact metrics are included in Scopus (Pranckuté, 2021). Moreover, Scopus is recognized for maintaining appropriate content quality standards (Baas et al., 2020; Singh et al., 2021).

The second key aspect was establishing the search term chain. Therefore, we conducted an exploratory study based on the methodology suggested by Cruz-Cárdenas et al. (2021). According to them, the central content to be searched was first defined based on the research objectives. Two content areas were identified that could be synthesized in a single idea: sharing knowledge in the context of consumer behavior. Subsequently, words or phrases best representing this idea were chosen. Thus, the initial search chain was “knowledge sharing” AND consumer. This chain was entered into the Scopus database search engine, specifying that the search should be conducted in the titles, abstracts, and keywords of the documents. Once the search output was produced, the “keyword” option was selected, which displayed all the other keywords associated with the documents extracted by the initial search chain, additionally displaying their usage frequency (i.e. the number of associated documents). Based on these results, the associated keywords present in at least five documents were selected. In this process, keywords that, although frequent, were not directly associated with the objectives of the study in the authors’ opinion, were discarded (e.g. “human,” “sales,” “article,” “male,” “female,” “empirical study,” and “survey,” among others). After following this process, the search string was expanded until it became (consumer OR customer) AND (“knowledge sharing” OR “knowledge-sharing” OR “information sharing” OR “knowledge exchange” OR “information exchange” OR “experience sharing” OR “knowledge contribution” OR “information contribution”).

Then, document recovery was performed. Figure 1 shows the complete process. The search string was applied in July 2023 to titles, abstracts, and keywords and yielded 1,013 documents. Additionally, two filters were applied to search delimitations. First, we limited the search to articles published in peer-reviewed journals to guarantee quality. Therefore, conference papers, book chapters, books, editorials, and reviews were excluded. Second, we limited the search for articles published in English, which constituted most documents obtained, to enable subsequent analyses of thematic content clusters. No time limits were established. These delimitations generated 498 records. At this point, the automated search was terminated.

To guide the subsequent steps in the document selection process, several inclusion and exclusion criteria were developed based on the research objectives. Although most criteria in this step were addressed, others arose during document evaluation.

Finally, we included the following articles:

1. Articles with theoretical and empirical orientations

2. Empirical articles based on quantitative, qualitative, or mixed methods

The following articles were excluded

1. Articles dealing with information sharing and/or knowledge between organizations (B2B), from organizations to consumers (B2C), or from consumers to businesses (C2B).

2. Articles about information sharing and/or knowledge between employees of an organization or in professional practice environments

3. Articles related to information sharing and/or knowledge in nonpublic settings (e.g. using mobile instant messaging)

4. Articles focused on consumer information/knowledge seeking

5. Articles focused on WOM and eWOM

6. Articles on the construction of general knowledge in collaborative scenarios distant from consumption (e.g. the construction of Wikipedia)

7. Articles on paid knowledge sharing in the framework of C2C commercialized innovations in sharing economy scenarios

With these inclusion and exclusion criteria, 498 records were manually filtered. This study was guided by recommendations provided by other systematic literature reviews (Li et al., 2023; Nadkarni and Prügl, 2021). Accordingly, two authors independently reviewed the titles, abstracts, and keywords of 498 records to determine their inclusion or exclusion. In case of doubt, the full text of the corresponding record was analyzed. Subsequently, in a meeting, the two authors compared the results and resolved any discrepancies. Consequently, 397 records were excluded and 101 were retained to continue the process.

The next step was based on an independent review by two authors with subsequent resolution of discrepancies. However, this time, the subject of the review was the full text of the documents corresponding to the 101 selected records. For this purpose, 97 full-text documents were recovered (4 could not be located). After this final screening, 46 documents were excluded, leaving 51 documents for the systematic literature review, which were adequate for our systematic literature review (Donthu et al., 2021). Figure 1 illustrates the complete process.  Appendix Table A1 presents the list of 51 articles.

To review and synthesize existing knowledge on I&KS, we selected a stimulus–organism–response model of consumer behavior, also called an input–process–output model (Figure 2). This model was originally proposed by Schiffman and Wisenblit (2015) and was successfully applied (with certain modifications) to literature reviews on consumer behavior (Cruz-Cárdenas et al., 2021).

In the input–process–output model, the consumer is the central entity. External influences to consumers are inputs that can be macroenvironmental, microenvironmental, and marketing influences. These external influences are processed by consumers according to their personal and psychological characteristics; the resulting behaviors (outputs) are produced after a decision-making process (Schiffman and Wisenblit, 2015). The microenvironment comprises the forces closest to the object of analysis, whereas the macroenvironment comprises broad forces (e.g. culture, economy, and natural environment) that influence the entire microenvironment (Kotler and Keller, 2016).

The first descriptive analysis focused on the article’s year of publication. Research on I&KS began in 2010, except for one article that was published in 2007. Furthermore, approximately half of the articles reviewed (n = 25) were published during or after 2019, indicating a growing interest in this research topic. Four articles were published in 2019, five in 2020, five in 2021, and six in 2022. At the cut-off point (July 2023), four articles were published in 2023 and one in 2024.

Another topic of interest in descriptive analysis was the research method. This information is summarized in Table 1.

Table 1 shows that a quantitative empirical approach was adopted in 39 studies (76.5%). Additionally, three studies used a quantitative approach combined with a qualitative approach (mixed methods/multimethods). In these 42 studies, 35 studies used the survey, the prevalent quantitative data collection method. Among few studies that included a qualitative approach, netnography was the preferred method for data collection.

Moreover, among studies that adopted a quantitative empirical approach, the main method of data analysis was structural equation modeling (SEM), both in its mainstream and partial least squares (PLS) versions. Of the 42 studies that adopted a full or partial quantitative approach, 27 (64.3%) followed this analysis strategy. The prevalence of quantitative studies based on SEM/PLS-SEM is explained by the existence of solid theories from psychology, sociology, economics, and consumer behavior regarding the behavior of people in technological–digital scenarios.

Based on previously acquired data from quantitative empirical studies and the preference for SEM/PLS-SEM as the main analysis method, the next analysis determined the most commonly used basic theories to establish hypotheses or guide work. From this analysis, the technology acceptance model, social capital theory, and social exchange theory emerged as the most reliant theories.

Another descriptive aspect was the subject area to which the selected articles corresponded. The basis of this analysis was the subject area with which Scopus associated each article. This information is presented in Table 2 for the areas associated with more than five articles.

Three areas dominated the I&KS literature, business management and accounting, computer science, and social science (Table 2), allowing I&KS to be characterized as multidisciplinary. In Table 2, the percentages equal to more than 100%, as the same article is associated with different areas.

Regarding the location of the empirical work (for articles that followed this approach), two countries emerged: the United States and China, each with eight studies. The lack of cross-cultural studies on this topic was striking.

The final aspect addressed in the descriptive analysis was how quantitative studies or studies with a quantitative component (n = 42) measured I&KS behavior. In Table 3, the highest percentage (38.1%) corresponded to articles that used a 5- or 7-point Likert scale to measure current behavior (e.g. “I often share my knowledge” or “I actively share my knowledge”). Next was the intention for future behavior, also reported on 5- or 7-point Likert scales (19.0%) (e.g. “I plan to share” or “I will share”). Objective measures (14.3%) (e.g. new uploads or the number of interactions in a given period) were closely related in frequency to this form of measurement. Subsequently, the measurements of attitudes toward the behavior were placed on 5- or 7-point Likert scales (e.g. “I would consider sharing” or “I would like to post”). Few studies used nominal (yes or no) or frequency (very infrequent to very frequent) scales.

Finally, some studies did not clearly report the measurement method. In other cases, this analysis was not applied because their measurement units were different (e.g. studies that applied simulation or machine learning/natural language analysis).

Another focus of the document corpus analysis was to identify the countries that contributed the most to I&KS research and research networks formed between them. Five countries stood out for their significant presence across four or more documents: the United States (10), China (9), the United Kingdom (9), Taiwan (5), and Australia (4). Additionally, we analyzed the research networks among countries using VOSViewer software, version 1.6.20 (Van Eck and Waltman, 2023). Figure 3 illustrates these clusters.

In Figure 3, country clusters are represented in different colors and the size of the nodes is proportional to the scientific production of each country. A series of smaller clusters of one or a few countries is observed, and the clusters formed by the United States, China, and Great Britain (red) are dominant. Leadership in I&KS scientific research is attributed to the latter cluster.

To establish the state of knowledge about I&KS, two authors trained in qualitative and quantitative research techniques reviewed the full papers and performed content analysis (Cruz-Cárdenas et al., 2021; Kaur et al., 2023) guided by the input–process–output model.

Macroenvironmental factors are broad forces (e.g. culture, technology, and economy) that affect the entire microenvironment (i.e. forces close to the object of analysis) and object of analysis, which in this case is the consumer (Kotler and Keller, 2016). Among these macroenvironmental forces, the reviewed studies emphasize culture and technology.

Regarding culture, collectivism, one of Hofstede’s (2001) cultural dimensions, and the norm of reciprocity supported I&KS in the studies. Collectivism (individuals’ prioritization of group goals) is positively associated with information sharing (Xiao et al., 2021). Additionally, collectivism plays a moderating role in intensifying the effect of attitude toward sharing information on the intention to share information about brands (Gvili and Levy, 2021). The cultural force of collectivism only applies to individuals when they feel connected to a community or group (Hofstede, 2001). Highly collectivistic individuals do not make significant efforts to support the goals or satisfy the needs of those they do not consider part of their group.

The norm of reciprocity is another cultural force that explains I&KS. It is universally manifested and drives individuals/consumers to offer something in exchange for what they receive. In the reviewed studies, the norm of reciprocity positively impacts information sharing behavior (Pai and Tsai, 2016). The reciprocity norm is activated when the consumer receives some benefit from a social network or virtual community. Furthermore, consumers strategically activate this norm in their digital communities by providing information or knowledge before receiving benefits. The norm of reciprocity exerts a positive effect on information sharing behaviors in online consumption communities, and this relationship is reinforced (moderated) by perceived receptivity in these communities (Pai and Tsai, 2016).

Technology is another important macroenvironmental force in I&KS behavior. Technological advances, such as platforms and AI, improve consumer experience in digital environments and social networks and facilitate knowledge sharing (Olan et al., 2024). Furthermore, AI technologies applied to consumers (e.g. bots, posts, and advertising deployment algorithms) evolve based on interactions with them (Olan et al., 2024). Various specific applications of technology and their effects on I&KS are discussed in Subsection 5.2, as technology no longer represents a broad force but specific ones in their actions on the consumer.

The dynamics of macroenvironmental changes are fundamental to knowledge sharing. In situations of revolutionary change that offer significant opportunities or cause great harm, consumers feel encouraged to share information with other consumers (Rockenbach and Sadrieh, 2012). However, in such situations, the performance of knowledge sharing in a community declines, as the demand for information and knowledge grows faster than the supply (Han et al., 2019). Although evidence exists regarding the influence of macroenvironmental forces on I&KS, this review reveals that studies in this area remain scarce.

Unlike the relatively scarce research on the macroenvironmental influences on I&KS, research on microenvironmental aspects is abundant. The microenvironment comprises all forces and organizations that are in direct contact with the object of analysis (Kotler and Keller, 2016)—in this case, the consumer. Three stakeholders are prominent in the knowledge sharing process (Yang et al., 2022): knowledge consumers, knowledge providers, and digital platforms (intermediaries between providers and consumers of information and knowledge).

Digital social spaces facilitating I&KS vary. First, social networks, such as Facebook, Instagram, and TikTok, connect billions of people and an enormous amount of shared information and knowledge. Second, e-commerce sites for many brands and products are I&KS spaces. Finally, social commerce is an I&KS space in which e-commerce platforms are incorporated into social networks (Bugshan and Attar, 2020). All these digital social spaces allow consumers to share experiences, review products, answer questions, and make recommendations. In e-commerce, information or knowledge sharing activity is enabled when a consumer does a purchase transaction (Lin and Wang, 2023).

Within I&KS, digital social spaces include Q&A communities, discussion forums and blogs (Chai and Kim, 2010). Additionally, owing to the value of knowledge, knowledge payment platforms have emerged (Yang et al., 2022). One example is Quora. Depending on the orientation of the digital social space in knowledge sharing, these spaces are free, freemium, paid, or reward-based.

Fellow consumers are a fundamental force in understanding I&KS. Consumers empathize with other consumers in similar situations, such as using the same brand or product category (Mogaji et al., 2021) or facing similar problems or doubts, impelling consumers to share advice on product use and improving purchasing options and help with technical problems. This increases the digital community’s knowledge regarding options, uses, and alternatives (Mogaji et al., 2021; Olan et al., 2024).

The culture/subculture existing in the digital community holds it together. The existence of a shared culture, particularly goals, ideals of fairness, and openness, directly influences people’s and consumers’ attitudes toward knowledge sharing and their intention to continue knowledge sharing (Liao et al., 2013). Additionally, knowledge sharing fosters interactions and mutual familiarization, strengthening online communities (Sloan et al., 2015).

In a virtual community, explicit social (published by the community) or implicit norms (observed in others’ behavior) are important behavioral guides for I&KS (Zhou et al., 2020). These social norms determine the type of content to share, tone, length, format, and interactions.

Another key concept explaining people’s and consumers’ tendency toward I&KS is the subjective norm (perception of social pressure to perform a behavior). The subjective norm directly influences the intention to share knowledge in Q&A scenarios (Li et al., 2022), publication of posts and replies (Wen et al., 2022), and intention to share brand information (Gvili and Levy, 2021).

The concept of social capital is fundamental for understanding I&KS. Social capital (resources that can be mobilized/obtained from a network of relationships) positively influences knowledge sharing (Ghahtarani et al., 2020). The interactions and links developed by consumers in social network or virtual communities (structural dimension of social capital) positively influence the intention to share knowledge on social media (Okazaki et al., 2017). Additionally, the feeling that one shares a vision and objectives with others (cognitive dimension of social capital) on social media positively influences the intention to use social media for knowledge sharing (Okazaki et al., 2017).

The type of knowledge sharing content is related to the lifespan of a virtual community. Initially, content focuses on subjective topics (e.g. feelings, tastes, and beliefs) and later shifts to more objective and precise information (e.g. product characteristics, store locations, likes/dislikes, and purchase recommendations) (Cervellon and Wernerfelt, 2012). In addition, the stage of a digital community’s life cycle and speed at which it passes through various stages are important for I&KS. While most digital communities seek rapid growth, excessive rapid growth hurts I&KS activities, causing knowledge sharing performance to decline because newcomers are more motivated or trained to ask questions than to answer them (Han et al., 2019).

Furthermore, the demand for and supply of knowledge sharing in digital communities is dynamic. Many topics cease to exist and give rise to other topics. An important change in the supply and demand of I&KS occurs when a topic becomes mainstream in the discourse and practices of an industry (Shen et al., 2014). Consequently, the companies in question start providing large quantities of information and knowledge about themselves.

In conclusion, abundant knowledge exists on social actors (knowledge providers and demanders) and their interactions in digital spaces, supported by a robust foundation of psychological, economic, and sociological theories.

The digital platform design is important for user interactions. This determines the available communication tools, reward and punishment systems, trust development, and management and moderation activities.

The most studied characteristic or attribute of a platform or social digital space, and the one with the greatest impact on I&KS, is trust in the platform or digital space (for its honesty and sincerity) and in other members. Trust positively and directly influences (continuous) knowledge sharing intentions in space (Chai and Kim, 2010; Hashim and Tan, 2015; Hsu et al., 2007; Jami Pour and Taheri, 2019; Lin et al., 2022).

Social commerce platforms provide interesting additional body of evidence. Trust in a social commerce website positively influences the generation of positive comments (sharing information on positive valence) about the website (Hajli, 2020). Additionally, the relationship between trust and intention to share knowledge is bidirectional. Thus, sharing knowledge on a social commerce platform increases trust in the platform (Bugshan and Attar, 2020).

Previous studies identify tools and strategies that digital platforms implement to encourage I&KS. In this regard, the visualization of previous comments, especially their length, is crucial (Fang et al., 2018). Publications by expert participants or those with many followers are also important (Fang et al., 2018). Additionally, the platforms’ generation of a system of rewards and penalties (e.g. likes and scores) has a significant influence (Li et al., 2022; Yang et al., 2022).

Moreover, the communication tools provided by digital platforms to consumers stimulate I&KS. Offering various tools renders tacit knowledge (knowledge in people’s minds) explicit and transmits it (Panahi et al., 2012). Tools enabling the creation of vivid posts with photos and videos encourage knowledge creation behaviors (Fang et al., 2018). Additionally, the platform’s ease of use is crucial, as it positively influences the intention to share knowledge (Bilgihan et al., 2016; Yuan et al., 2016).

Finally, there are two other means of stimulating I&KS in the digital space. First, companies or organizations can freely share their own knowledge (Boon et al., 2015). Second, incorporating an administrator (often an expert), who leads and encourages interactions and sets limits within a digital community (Sloan et al., 2015).

This subsection reveals the existence of solid research on the necessary characteristics of platforms or digital spaces to stimulate I&KS. However, the value of the incessant development of technology engendering new digital spaces and interactive tools must be considered.

The marketing tools used by companies and organizations stimulate I&KS. Traditionally, these tools are divided into product, price, distribution, promotion, and communication (Kotler and Keller, 2016).

An important measure of whether companies stimulate I&KS is their ability to achieve consumer satisfaction with their products and services. For example, research reveals that consumers’ general satisfaction with an e-commerce or e-services website is positively related to their intention to share information and knowledge, both on social networks and on the website (Lin and Wang, 2023; Yuan et al., 2016).

Another powerful marketing tool that companies must use to encourage I&KS is the formation of brand communities, either official or created and controlled by consumers. The former has a significant number of members and, therefore, more possibilities for creating I&KS than the latter (Sloan et al., 2015). Companies encourage members to express doubts or questions in their official brand communities, generating knowledge sharing via responses from other consumer members (Sloan et al., 2015). To stimulate these responses, companies activate reciprocity norms by rewarding members who help others with their scores and discounts (Boon et al., 2015; Li et al., 2022).

The communication role of companies in brand communities and social networks is another valuable tool. Its application depends on the scenario in question. Moments of crisis, change, or disruption decrease the performance of I&KS in a digital space by decreasing the ratio of contributors to noncontributors of knowledge (Han et al., 2019). Specifically, during change or disruption caused by, for example, legal or economic changes or profound product innovations, more consumers seek information and knowledge than providing them. In these moments of change or disruption, when old knowledge becomes obsolete, companies must be particularly active in digital spaces to generate new information (Han et al., 2019).

The type of product/service offered by a company is critical. In the case of credence goods such as health services or education, it is difficult for consumers to evaluate the quality and efficiency of the service even after consumption. In such cases, for effective I&KS, experiences shared by many consumers are required (d’Andria, 2013). Companies offering these types of services should set these objectives.

Advertising is another tool that triggers I&KS. The attractiveness (likeability) of advertising content (e.g. its cognitive–informational and affective aspects and the characters used) directly influences consumers’ intentions to chat about or share that content (Kaur et al., 2023). Companies can make three types of appeals for sharing knowledge to consumers: altruism (helping others), ideology (knowledge must be open and shared), and learning (action effectuates improvements in one’s own personal skills and competencies) (De Jong and Lindsen, 2022). In summary, the literature search revealed a good knowledge base for marketing tools and knowledge sharing; however, it must be tested more extensively with methods other than surveys (e.g. case studies or experiments).

Personal and psychological factors are part of the input–process–output model of consumer behavior used in this review. These factors determine how consumers process endogenous inputs and initiate the decision-making process (Schiffman and Wisenblit, 2015). Among the personal and psychological factors addressed by I&KS studies are the roles played by the individual, motivation, personality traits, self-efficacy and perceived behavioral control, consumer innovativeness, influence and leadership, and awareness and identity.

Consumers adopt various roles in I&KS. They play one of the three roles in virtual social spaces (Silver and Behlendorf, 2023): searching for information (information consumers), searching for and sharing information (conduits), and primarily sharing information (amplifiers). Those who share information and knowledge also play a role in educating newcomers, especially when social or environmental causes are involved (e.g. green fashion) (Cervellon and Wernerfelt, 2012). These roles are dynamic and interconnected. For example, using social media to search for information on topics such as travel or dining in restaurants positively influences the intention to use social media for knowledge sharing (Bilgihan et al., 2014; Okazaki et al., 2017).

A central concept in consumer behavior is motivation or the activation and direction of behavior. Various motivations for I&KS are addressed in the reviewed studies. Intrinsic motivation (i.e. oriented by personal values) is positively related to the intention to share information and knowledge on e-commerce sites (Li et al., 2022; Lin and Wang, 2023). Extrinsic motivation aims at obtaining rewards (e.g, ranking, reputation, and image) and is positively related to the intention to share information and knowledge about e-commerce sites on social networks (Liao et al., 2013; Lin and Wang, 2023; Silver and Behlendorf, 2023; Sloan et al., 2015). Hedonic/enjoyment- and entertainment-oriented motivations guide I&KS behavior, for example, in Q&A environments (Li et al., 2022; Liao et al., 2013; Sloan et al., 2015). Social motivation is highly significant. Consumers motivated to interact with others share information in online communities (Sloan et al., 2015). Additionally, achievement motivation (to be competent) is positively associated with knowledge sharing behaviors (Wu and Sukoco, 2010).

Another crucial finding revolves around personality traits that favor I&KS. Several studies identify the association between the Big Five personality traits (extraversion, openness, neuroticism, agreeableness, and conscientiousness) and I&KS. On the one hand, Phuthong (2023) attributes these traits to an indirect effect, mediated by trust and subjective well-being, on consumers’ tendencies to share knowledge in social network communities. On the other hand, Jami Pour and Taheri (2019) find a direct effect of four personality traits on knowledge sharing tendencies, with extraversion, openness, and agreeableness influencing it positively and neuroticism negatively. Additionally, materialism, another personality trait, (importance given to material possessions), has a positive relationship with consumers’ tendency to share information (Xiao et al., 2021).

In addition, consumer perceptions of the control and effectiveness of knowledge sharing tasks were addressed by the reviewed studies. Perceived behavioral control (degree of perceived control in performing a behavior) directly influences browsing, liking, publishing posts, and sharing brand information (Gvili and Levy, 2021; Wen et al., 2022).

Subjective knowledge (consumers’ belief regarding their level of knowledge about a product) positively influences knowledge sharing intention (Yuan et al., 2016; Zubair et al., 2019). Self-efficacy (perception of one’s ability to tackle a task), a concept close to subjective knowledge, directly influences attitudes toward knowledge sharing and the intent to continue sharing knowledge in virtual communities (Liao et al., 2013). Furthermore, self-efficacy reinforces the positive impact of the norm of reciprocity on information sharing behaviors in digital social spaces (Pai and Tsai, 2016).

Innovation at the personal level, which some authors treat as an attitude and others as a personality trait, demonstrates a positive impact on I&KS behavior. Studies find an association between consumer innovativeness and the tendency to share information on travel and airline e-services on social media (Sukhu and Bilgihan, 2014; Yuan et al., 2016).

Previous studies address various aspects of consumer influence and leadership. A positive relationship exists between being a market maven (an influencer with general knowledge of purchasing and the market) and the frequency and quality of participation in sharing information in online communities (Kim et al., 2011). Furthermore, people with high consumer opinion leadership (consumers with a high level of influence on others) have a greater propensity to seek and share gastronomic information (Bilgihan et al., 2014).

Another interesting finding relates to the relationship between consumers’ attitudes and perceptions toward online communities and their information sharing propensity. Social identity (identification with a community) directly influences knowledge sharing in a virtual community (Shen et al., 2010). Affective commitment (belonging and attachment) to an online community directly and positively influences continuous knowledge sharing intentions (Hashim and Tan, 2015). Additionally, psychological ownership positively affects the quantity and quality of consumers’ knowledge sharing (Zhang et al., 2022).

Another important area in the process zone of the theoretical model used in this study is consumer decision-making, in this case referring to I&KS. To a large extent, previous studies rely on social exchange theory to elucidate this, considering consumers as weighing the benefits and costs associated with I&KS activities as decision-making inputs. The cost side includes the effort required by the task, possible loss of power when putting one’s own knowledge in others’ hands, and perceived risks (such as legal and social) (Bugshan and Attar, 2020; Yu et al., 2015). Benefits include community recognition, gaining friends, reciprocity from other members, and the receipt of resources (material and money) (Hsu et al., 2007; Yu et al., 2015).

This subsection reveals substantial research on personal and psychological factors in I&KS. This area of the model yielded the highest research results. This is explained by the extensive range of psychological, economic, sociological, and consumer behavior theories and the availability of well-developed instruments (e.g. measurement scales). In a complementary manner, the abundance of knowledge is attributed to the relative ease of conducting such studies, which generally use conventional methods (e.g. interviews and surveys).

The behavior or conduct of I&KS is among the outputs of the input–process–output model. One approach to various consumer behaviors in I&KS is based on the involvement or effort required. The simplest and least demanding behaviors are browsing, giving likes, and generating ratings (Bugshan and Attar, 2020; Wen et al., 2022). Although they may seem to have little relation to I&KS, likes and ratings endorse or do not endorse information and knowledge shared by others. At a higher level of involvement is the publication of posts containing information and knowledge (Wen et al., 2022). This is an I&KS behavior and takes the forms such as generating comments, making recommendations, and reporting experiences (Bugshan and Attar, 2020). Finally, generating personalized information and knowledge represents the highest level of involvement, which includes responding to posts, questions, requirements, or cross-questions (Wen et al., 2022; Zhou et al., 2020). Most I&KS that consumers engage in with others involves recommending or warning about companies and brands and helping other consumers solve problems during the purchasing process (search, purchase, and use) (Mogaji et al., 2021).

Another important issue pertaining to I&KS consumer behavior is the resources and tools used. The resources used by consumers include textual content, graphic and audiovisual presentations (sharing images, videos, and emojis), mentioning companies (e.g. using the @ sign), continuing conversations internally, and sharing direct links to content or company and product websites (Mogaji et al., 2021).

The last aspect of the output of the input–process–output model to be analyzed is behavior after engaging in I&KS. Two effects of I&KS are identified in the literature: the effects on loyalty and purchases.

Various studies find a positive relationship between I&KS behavior and loyalty to a brand and its digital community. This relationship is observed in a sample of young people in social media spaces (Sukhu and Bilgihan, 2014), online communities (Wu and Sukoco, 2010), and Q&A platforms (Li et al., 2022).

These findings confirm the relationship between I&KS and future purchases. Ebrahimi et al. (2021) identify this relationship in social networks, while Ghahtarani et al. (2020) and Hajli (2020) discover it in social commerce and e-commerce sites. Finally, Kaur et al. (2023) find a positive relationship between the intention to discuss or share attractive advertising content and the intention to purchase an advertised product.

The studies contained more results regarding post-I&KS behavior than on the I&KS behavior itself. The limited availability of qualitative research and recentness of machine-learning-based research explain this gap in the existing literature.

Finally, Figure 4 graphically presents the main elements of consumer behavior in I&KS. This behavior is organized according to the input–process–output model outlined in Section 3 (Figure 2).

The main analysis in this literature review, namely, content analysis, was based on a manual approach and a previously selected input–process–output model (Figure 2) widely used in the discipline of consumer behavior. To compare the results obtained (Figure 4) using a different approach, a second content analysis of the documents was conducted using AI tools. The Leximancer package was used for this purpose. Leximancer is a text mining tool that uses machine learning algorithms for analysis. It is widely used in the organizational world and in scientific research (Sullivan et al., 2018). The full texts of 51 selected articles in PDF format were used as data to determine their thematic structures. In this second analysis, the themes or areas were not imposed but emerged from the data and were labeled using Leximancer’s AI algorithm.

Figure 5 presents the results of this analysis. Five thematic clusters are identified. Each cluster encompasses a set of concepts based on their relationships or proximities. The main or central cluster, visually determined as the one with the greatest overlap with the other clusters, is “consumers.” This cluster includes concepts related to stimuli directed at consumers and their characteristics of said consumers. The second cluster, the most populated with concepts, is “sharing,” in which behaviors related to I&KS are concentrated. The third cluster, “users,” includes users and social networks. The fourth cluster, “fashion,” includes concepts related to fashion, marketing strategies, and sustainability. Finally, the fifth cluster, “value,” integrates concepts related to the benefits perceived by the consumer in I&KS.

By analyzing the results of the AI-guided analysis (Figure 5) and manually developed content analysis (Figure 4), we established several alignments and parallels. The AI-identified central “consumers” cluster largely coincided with the central “process” part of the input–process–output model and specifically with consumers and their characteristics. Moreover, the AI-developed “value” cluster coincided with the central part of the input–process–output model and decision-making process, which, in the case of I&KS, was based primarily on the estimation of benefits and costs. The AI-identified “fashion” and “users” clusters coincided with the input part of the input–process–output model. Specifically, the greatest alignment of “fashion” was with microenvironmental (e.g. marketing efforts) and macroenvironmental forces (e.g. fashion and sustainability). The “users” cluster coincided with microenvironmental forces (e.g. social networks and platforms). Finally, the “sharing” cluster largely coincided with the output part of the input–process–output model, where the resulting I&KS behavior of the consumer was observed.

This alignment of the thematic areas of the manual analysis conducted using a pre-imposed input–process–output model with the thematic areas identified via the use of AI indicates that using the input–process–output model is appropriate to organize the existing literature.

In this study, a systematic review of the I&KS literature was conducted on 51 relevant articles. This field of knowledge is expanding. I&KS differs from eWOM, which focuses on persuasive C2C digital communications with clear positive or negative valence. It is oriented toward the construction and sharing of information and knowledge, construction of digital communities, and consumer empowerment. Thus, I&KS is fundamental in promoting the sustainable development goals of the United Nations, such as Goal 12: Responsible Production and Consumption.

Quantitative studies dominate the I&KS landscape, and the main data analysis methods are different variants of SEM. Numerous psychological, sociological, economic, technology diffusion, and consumer behavior theories provide rationales for the deployment of SEM models. The I&KS field is characterized as a multidisciplinary field encompassing disciplines such as business management, computer science, and social science. Additionally, this multidisciplinary characteristic is observed in the results of other studies investigating consumer behavior in technological and digital environments (Cruz-Cárdenas et al., 2021).

An analysis of productivity by country reveals the leading role of research teams from developed (the United States and United Kingdom) and emerging countries (China). In contrast, developing countries, in which further research can better understand the behavior of I&KS, are poorly represented.

We manually organized and systematized the content of 51 selected documents based on a widely used input–process–output consumer behavior model (Schiffman and Wisenblit, 2015). Another approach used in this study—using AI to generate thematic clusters—enabled this type of organization in the literature review. A highlight of these two analyses is the identification of a transversal role of I&KS throughout the consumer behavior process.

Although macroenvironmental factors play a role in the state of knowledge in I&KS, few studies examine these factors. However, their importance must be recognized in a world characterized by frequent economic, political, and technological disruptions (Cruz-Cárdenas et al., 2021; Wan and Chih, 2024). Two possible lines of work appear promising. First, to study the indirect macroenvironmental effects on I&KS mediated by personal and psychological variables (Cruz-Cárdenas et al., 2019). Second, placing more emphasis on cross-cultural studies to understand how different macroenvironmental scenarios cause different consumer responses regarding I&KS.

Regarding microenvironmental factors, solid research exists on the characteristics of digital communities and digital platforms that explain and favor I&KS. However, we must consider the dizzying technological advances generating new products and spaces for digital social interaction. Therefore, despite the accumulated knowledge in this area, future research must continue. For example, an emerging area enabled by technology is the development of innovations by consumers marketed via C2C within the framework of the sharing economy (Aoki, 2021).

An additional research topic regarding the microenvironmental aspects of I&KS is the life cycle of the digital communities in which this practice exists. For example, rapid growth in the digital community effectuates a decline in the efficiency of I&KS because more members seek information and knowledge than providing it (Han et al., 2019). Therefore, how I&KS performs throughout the life-cycle stages of a digital community (birth, growth, stabilization, and decline) must be observed.

An additional aspect of microenvironmental forces that has not been examined in the I&KS context is personal data confidentiality and its use. Given the rapid evolution of technology and creation of new and innovative digital spaces based on consumer information exchange, further research on this topic is required.

This study’s assessment of the state of knowledge regarding the influence of marketing strategies on I&KS indicates the accumulation of a solid knowledge base. However, more studies, particularly case studies and experimental methods, must be conducted in organizational settings. As previously indicated, surveys are the prevailing method used in I&KS studies. As the fundamental objective regarding the effectiveness of marketing tools is to test their effects, the orientation of studies in this regard should be fundamentally causal (Schiffman and Wisenblit, 2015).

Most knowledge about I&KS is accumulated, as personal and psychological factors are the most studied areas. The broad basis provided by psychological, sociological, economic, and consumer behavior theories and diffusion of technologies and tools such as SEM enable rapid advancement in this area. This assessment is confirmed by other studies on consumer behavior in technological environments (Cruz-Cárdenas et al., 2021). However, most studies were conducted in a single country; therefore, cross-cultural studies that allow testing of similar theoretical models in different cultural and economic scenarios are recommended.

The behavior resulting from the I&KS model is an under-researched area. The prevailing methods in the studies analyzed, such as surveys, explain this situation. Research methods that allow for an approach to the natural behavior of consumers are needed. In this regard, qualitative methods such as netnography, although incapable of broad generalizations, can help obtain insights into the behavior of I&KS. In addition, methods based on AI, such as machine learning and natural language processing (Galiano-Coronil et al., 2024; Mastroeni et al., 2023; Mogaji et al., 2021), are highly promising in this era of big data. Future research can also connect different consumer behaviors of sharing information and knowledge; for example, analyzing the relationship between C2C and C2B I&KS.

As a final reflection in this subsection and in relation to the way of operationalizing I&KS, much more needs to be done than just considering I&KS as a dependent variable (final outcome of behavior) (Wang et al., 2024; Zhang et al., 2024a). Thus, using an input-process-output model and AI-guided analysis, the present study clarified the multiple and transversal role of I&KS in the consumer behavior process (Figure 4). Thus, future studies should treat I&KS in several ways: first, as an input that influences information-seeking consumers, that is, as an independent variable; second, as part of the consumer decision-making process, that is, as a mediating or moderating variable; and finally, as the outcome of the process, that is, as a dependent variable.

As I&KS is a space for building knowledge, both companies and nonprofit organizations act in this space. A key finding of the reviewed studies is the relationship between consumer leadership and their propensity for I&KS (Bilgihan et al., 2014; Kim et al., 2011). Consequently, consumer opinion leaders are key elements in the rapid transmission of information and knowledge, which is necessary during disruptions (Han et al., 2019) or for the rapid spread of sustainable consumption ideas and practices. Additionally, given that I&KS behavior is guided by the calculation of benefits and costs (Bugshan and Attar, 2020; Yu et al., 2015), I&KS task should not overwhelm active consumers. Therefore, AI tools for classifying and displaying content provide significant support.

Other significant topics in I&KS in professional practice include privacy, confidentiality, and data protection for consumers. Concerns about privacy and using personal data, in addition to ethical issues, are the biggest barriers to encouraging online behavior among consumers (Martin and Murphy, 2017). Consumers are more predisposed to developing online behaviors if they feel some degree of control over their information and privacy (Bandara et al., 2020). As previously indicated, the topics of privacy and data protection have rarely been studied in the I&KS context; however, experience from other digital consumer behavior scenarios allows us to derive recommendations for professional and marketing practices regarding I&KS.

Four confidentiality and information protection strategies demonstrate commitment for companies, nonprofit organizations, social networks, and other digital platforms to build the necessary trust in consumers to participate in I&KS: 1) the presence of a third party (which does not represent any company) to generate the digital space within which consumers can act (Bandara et al., 2020); 2) possibility of consumer anonymity, which can be combined with reputation measures or ratings from other consumers to ensure responsible behavior (Liao et al., 2013; Lin and Wang, 2023); 3) transparency of the digital website, which is achieved by specifying what information is collected and consumer’s option to choose the information they share (Gotsch and Schögel, 2023); and 4) ability of the website or web space to prevent external infiltrations and security breaches (Okazaki et al., 2020).

Another important topic is the relationship between the disruptive force of AI and I&KS, a form of consumer behavior, along with its implications. This relationship is best understood as reciprocity, in which both AI and consumer behavior affect each other (Jain et al., 2024). Additionally, for-profit and nonprofit organizations can obtain benefits as third actors, making this set of relationships complex. We discuss several characteristics and possibilities of this network of relationships below.

AI and its advancement have many implications for both I&KS and its exploitation by companies and organizations. It creates new digital spaces for interaction between consumers for I&KS that reinforce the positive experiences of users. More significantly, in combination with other emerging tools in the digital world, such as metaverse and extended reality, it creates more satisfying and immersive experiences (Kumar et al., 2024). Furthermore, it organizes information and knowledge that accumulates in digital spaces and helps consumers find specific content with search options. With the advent of generative AI, the possibility of producing recommendations and personalized content has increased (Mogaji and Jain, 2024). Moreover, the power of AI underpins consumers’ decision-making processes (Jain et al., 2024). AI also provides tools for companies and organizations to analyze consumer-generated content (I&KS) and leverage it to detect patterns (Mills et al., 2023). These tools include sentiment analysis, story unlocking, and thematic cluster analysis (Chen and Prentice, 2024; Kumar et al., 2024). They allow AI to refine consumer feedback effectively so that organizations can make informed decisions. Additionally, AI development benefits from I&KS, as it allows AI training and learning (Olan et al., 2024).

An additional recommendation for the advancement of professional practice involves understanding that I&KS manifests itself transversally in the consumer behavior process (Figure 4), starting the process (recognizing the need and searching for information and knowledge by the consumer), being part of the process (providing input for the comparison of alternatives), and displaying the resulting behavior (I&KS by the consumer after the purchase and use of the product). Therefore, companies and organizations must play an active role throughout the consumer behavior process. At the beginning and during the decision-making process, they must generate information and knowledge based on the state of I&KS about their products. This strategy is essential for changing consumer behaviors. At the end of the consumer behavior process, companies and organizations must encourage consumers to generate I&KS. This strategy is essential to reinforce consumers’ role as agents of change (Kiss et al., 2024; Wang et al., 2024) and to encourage other behaviors that are desirable for companies, such as brand loyalty and new purchase intentions (Ebrahimi et al., 2021; Li et al., 2022; Sukhu and Bilgihan, 2014).

I&KS is an expanding academic field. It corresponds to consumer behavior oriented toward consumer empowerment, knowledge construction, strengthening of digital communities and social change. Based on a systematic literature review, we systematized the contents of 51 selected articles using traditional content analysis and AI. I&KS is a multidisciplinary field of study dominated by quantitative methodological approaches and research teams from the United States, China, and the United Kingdom, which maintain research links. Among the avenues for future research presented by this study are macroenvironmental forces, particularly those of a disruptive nature, digital platforms and spaces that are constantly evolving, and I&KS behavior itself. Understanding I&KS is highly useful for both companies and nonprofit organizations, as it can spread sustainable consumer behavior and is closely linked to brand and digital community loyalty and future purchase intentions.

Funding: This study was funded by the Universidad Tecnologica Indoamerica, Ecuador.