Mapping Anthropomorphism through Bibliometrics and TCCM Approach

The emergence of anthropomorphic thinking can be argued to have started about 40,000 years ago.^[1] The term’ anthropomorphism’ was mentioned in research on comparative psychology concerning the discussion on animal mentality.^[2] Anthropomorphism enables a “default schema” to help the sense-making process even if it is altered in case of inconsistent information.^[3] People often refer to restaurants as “cool,” the stock market as it is “climbing” or “falling,” and oceans as “angry” or “calm.” In human interactions, we frequently witness non-human objects getting attributed by human adjectives. This psychology of calling, perceiving, and imagining non-human objects as if they are humans is called anthropomorphism. Thus, anthropomorphism is “attributing human qualities or behaviors to non-human entities, objects, and events”.^[4]

In business and management, the anthropomorphism of non-human agents is also found in consumers, who name their cars or treat their computers as their friends.^[5] Thus, the manufacturers and firms are highly focused on providing consumers with products and services that exhibit anthropomorphism characteristics in consumer and organizational behavior. It led to the development of innovative products such as AI-enabled Amazon’s Alexa, Apple’s Siri, or Roomba’s vacuum cleaner that can process human voice commands and perform tasks accordingly.^[6] Human characteristics in the context of anthropomorphism might contain “emotional states”,^[7] “physical appearance”,^[8] and “inner mental motivations and states”.^[9] The non-human agents in this context can be imaginary or real, such as natural forces, non-human animals, religious deities, nations, electrical and mechanical devices, or electronic gadgets.^[10] These non-human agents can act or be imagined to be acting from an anthropomorphic vision. This anthropomorphic vision is responsible for determining how humans behave towards non-human agents.

This study uses the TCCM framework, which Paul and Rosado-Serrano developed, as a literature review tool to extend the insights of anthropomorphism studies.^[11] Thus, the complex nature of anthropomorphism stimulates new-age researchers to conduct a structured review of the available relevant information on this topic through bibliometric analysis.^[12] The bibliometric analysis facilitates tracking down the evolution and characteristics of a topic within a given field of study using a quantitative assessment of data on publication records.^[13] The research patterns of authors, journals, institutes, and countries were evaluated using bibliometric tools to identify and assess patterns of collaboration between them.^[14] Significant theoretical revelations, contexts, characteristics, and methods have also been offered to suggest future research avenues in anthropomorphism. Thus, the primary goal of this study is to conduct a systematic review to clarify the state of the art in anthropomorphism.

In this study, authors have attempted to draw inferences from the publication data in many ways by answering the following research questions:

• How has anthropomorphism literature evolved considering its Theories, Context, Characteristics, and Methodologies (TCCM)?
• What are anthropomorphism studies’ geographical area, subject area, keyword, author, journal, and affiliation trends?
• How is anthropomorphism research work being recognized by the research fraternity?
• How do the authors, publications, sources, keywords, and their affiliations network with one another?

This research paper is organized as follows. A systematic literature review of significant articles using the TCCM methodology has been deliberated in the following section. Thereafter, the materials and methods adopted in this study have been declared. In the next section, bibliometric analysis, citation analysis, and network analysis are conducted and showcased using the quantitative data points until data retrieval. Finally, the paper has been concluded with research conclusion and future research directions.

This research work integrates TCCM methodology to deepen the understanding of anthropomorphism studies’ theories, contexts, characteristics, and methods.

Fundamentally, anthropomorphism is a human response that is naturally mindless but consciously denied by individuals who actively exercise it, especially in the case of computers, robots, and chatbots. Based on the theory of mindfulness and mindlessness,^[15] humans mindlessly apply social cues and make sense when interacting with non-human entities but deny this when they are mindful. Based on three key psychological determinants of anthropomorphism, “the accessibility and applicability of egocentric or homocentric knowledge” (elicited agent knowledge), “the motivation to be effective social agents” (effectance motivation) and “the motivation for social connection” (Sociality motivation), people anthropomorphize and when they do not.^[4] According to the Schema Congruity theory, anthropomorphism was evaluated by congruity affected by schemas-based processing.^[16] The paradoxical research of anthropomorphism can be solved by the cognitive theory of cultural representations, wherein if the representations have both “inferential potential” and salience, then such representations become steady and extensive.^[17] The theory of mind from developmental psychology underpins humans’ capacity to observe human intentions in non-human inducements.^[18] Social theories include social identity theory,^[19] social learning theory,^[20] social agency theory,^[21] social exchange theory,^[22] and social response theory.^[23]

Psychology theories have been widely used in anthropomorphism studies, followed by social theories and theories related to human-technology interfaces. The review of these theories reveals that the groundwork of anthropomorphism can be attributed to theories comprising psychological factors. These studies then progress into social needs and technology-related theories, extending into consumer and organizational behavior theories.

Context-based classification studies offer various facets of any concept under study.^[24] Anthropomorphism studies are deliberated in different contexts apart from its origin in psychology, like human-technology interaction, sociology, consumer behavior, and organizational behavior. The extant research base is so disjointed and diverse that few definitive assumptions lead to the challenge of using anthropomorphic processes in different contexts. The studies extensively covered the contexts of psychology, sociology, and technology, followed by consumer behavior domains. However, it is still nascent in the context of organizational behavior.^[25]

Extensive literature has concentrated its focus on the most significant characteristic of anthropomorphism, which is humanization. The attributes of anthropomorphism make authors think about humanizing non-humans, which is the crux of anthropomorphism. The most relevant keywords are “human”,^[26] “human factor”,^[27] “humanness”,^[28] and “human likeness”.^[29] The characteristics of anthropomorphism can also be highlighted, including its antecedents and consequences. These studies have reached distant growth, yet the consolidation of such studies remains a challenge.

A body of anthropomorphism research has been dedicated to identifying its antecedents. However, these studies deal mainly with the domains of psychology and technology. There are excellent prospects for studying the antecedents in other available domains. When the construct of anthropomorphism is examined in detail to check its antecedents, it is found that psychological motives make humans anthropomorphize. The motives of sociality motivation and effectance motivation are the predictors or antecedents of anthropomorphism.^[30] When elaborated in organizational scenarios, these motives emerge as humans’ sense-making and social connection needs.^[31] Verbal speech quality and psychological features like autonomy, sociability and personality trigger the anthropomorphic schemas.^[32] Elicited agent knowledge, effectance motivation, and sociality motivation are the three key determinants of anthropomorphism.^[33] Technological factors like identity cues and communication performance, individual factors like personality traits and competence, and environmental factors like task characteristics and social influence form the antecedents of anthropomorphism in AI-enabled technologies.^[34] Self-esteem and intrinsic religiosity decide anthropomorphism regarding superstitious belief.^[35]

The research work on outcomes of anthropomorphism focuses majorly on efficacy, social connection, and belief systems, yet very few studies consolidate the findings. The significant outcomes of the anthropomorphism process can be evoking interpersonal behaviors, social and personal identification, and psychological contract.^[31] The process of anthropomorphism positively affects self-efficacy and social connection.^[32] Human-technology relationships, perceptions, attitudes, emotional engagement and motivation in terms of overall appraisal, intentions, and active responses and usage behavior form the consequences of AI-enabled technology anthropomorphism.^[34] Anthropomorphism regarding superstitious belief results in horoscope importance and behavioral superstitious beliefs.^[35]

Studies related to anthropomorphism majorly focus on theory extension. As an abstract concept, anthropomorphism needs theory backing, and its advancement must contribute to theory building. Studies, particularly from the consumer behavior domain, were found to be contributing to model testing.^[36] Scale development was extensively carried out in consumer behavior and technology-human interaction studies. Statistical analyses majorly include regression analysis,^[37] factor analysis,^[38] structural equation modeling,^[39] correlation analysis,^[40] and variance analysis.^[41] The studies involving antecedents and consequences employed statistical analysis.

Table 1 depicts the research methods employed in the case of various anthropomorphism study areas, as observed in the literature review and bibliometrics.

It was observed that anthropomorphism studies in the context of psychology and sociology employ conceptual analysis and mixed methods over statistical and mathematical analyses. Anthropomorphism in technology and management domains employs statistical and mathematical analyses and mixed methods.

Post-TCCM analysis found that there is no satisfactory and sufficient integration of interdisciplinary perspectives on anthropomorphism as a concept. There are high-stake domains like autonomous driving, environmental conservation, education, and healthcare therapy, which are underexplored with limited research on anthropomorphism’s acts and impacts having contextual specificity. Additionally, TCCM analysis reveals demographic and cultural gaps with heavy coverage of Western perspectives and neglect of non-Western focus with some exceptions.^[42] Existing literature neglects the adverse outcomes of anthropomorphism, discussing anthropomorphism’s potential risks. To the best of the researchers’ knowledge, none of the studies offer an integrative examination of this topic so far. Hence, to support these revelations of TCCM analysis, a bibliometric analysis is carried out in the following section to further extend the understanding of anthropomorphism.

In this research, authors implemented a 3-stage approach. Firstly, we retrieved relevant data from the Scopus database and refined it for further analysis. Secondly, we conducted a systematic literature review using the TCCM methodology to comprehend the many facets of anthropomorphism research studies. Thirdly, using quantitative information, bibliometric analysis was performed with the help of research data points, citations, and network analysis.

Systematic literature review process has different steps according to different researchers.^[43,44] Various review methodologies are shaped through these systematic literature review studies based on the research objectives. A systematic literature review is a recurring procedure intended to answer the pre-defined research questions that assist in concluding past results.^[45] Likewise, this article draws references from previous literature on anthropomorphism.

We retrieved relevant research data from the Scopus database until December 2024. SCOPUS was the primary choice for the database as it includes 20% more articles in the various categories than Web of Science.^[46,47] Authors executed the search query using the keyword ‘anthropomorphism’ through the ‘abstract, title, and keywords’ search in the Scopus database. Initially, the authors retrieved 3,787 research datasets. Later, the data were filtered considering the type of documents as articles, conference papers, and review papers) totalling 3,378 datasets. Thereafter, authors considered only journal papers as a source type for research, further limiting the use of 2565 publication datasets. Furthermore, the authors preferred the publication language to be ‘English,’ compressing publication datasets to 2,369. Finally, the research datasets of 2,316 research studies published until 2024 were considered for further bibliometric analysis.

The publication dataset consists of various data points such as authors, year of publications, source titles, citation counts, author’s affiliations, keywords, number of publications by authors, subject areas, document type, source type, affiliation, and country concerning each publication was stored in dot CSV files for further bibliometric and network analysis study using free opensource visualization software ‘VOSviewer’ and ‘GPS visualizer.’

The bibliometric analysis aims to analyze available literature to obtain transparent and systematic insights into a concept under study. Bibliometric analysis is a great aid when the research objective is to evaluate the considerable body of literature.^[48] It is a method to evaluate the bibliographic data quantitatively.^[49] The graphics created by bibliometric analysis led to an understanding of the advancement of the topic under study.^[50] The chronological publication patterns resulting from bibliometric analysis help to understand the sources, authors, countries, institutions, and other important parameters of an area of study.^[51]

This section of the study elucidates the analyses of the bibliometric study of anthropomorphism. The retrieved data showcase the demography of each publication in anthropomorphism research. In bibliometric analysis, quantitative data related to the publications is used to understand the direction of the research interest.

In 1900, Thorndike mentioned the term ‘anthropomorphism’ in the context of comparative psychology concerning animal mentality. Thereafter, it took almost a hundred years to accelerate the studies concerning anthropomorphism. Figure 1 exhibits the annual trends of publications indicating growth in anthropomorphism studies. Until 2000, merely five percent of publications were published in anthropomorphism studies. During 2001-2010, it saw slow growth in publishing only 194 (8.38%) publications. Anthropomorphism studies took a great leap from 2011 to 2020, publishing 766 (33.07%) of total publications. In the last five years (2020-2024), the anthropomorphism studies boosted with 1,232 (53.20%) publications until data retrieval.

Figure 1:
Annual trends of publication in anthropomorphism studies. Source: Author compilation.

In this section, we attempted to highlight the most influential bibliometric data points in anthropomorphism studies. Table 2 presents the top ten trends in this field, considering subject areas, authors, keywords, affiliations, associated countries, and source titles in anthropomorphism-related research. The publications might fall under more than one category of the subject areas. Social science was the preferred subject area, followed by arts and humanities, computer science, business, management, accounting, and psychology. Waytz and Epley were the leading authors in anthropomorphism studies, with 12 and 10 publications each. It was obvious that anthropomorphism (with 53.93% occurrences) is the leading keyword espoused by researchers in anthropomorphism studies. The researcher’s fraternity commonly used human-oriented keywords. A few of them from the list of top ten were human/s (23.45%), male (8.17%), female (8.07%), and adult (6.82%). The most affiliated organizations in anthropomorphism studies were ‘Sungkyunkwan University’ with 24 publications in anthropomorphism, followed by ‘The University of Chicago (23)’, ‘The University of Oxford (18)’ and ‘Monash University (18)’. Among the source titles, ‘ Computers in Human Behavior’ with 60 publications, was the most sought-after journal by the researcher fraternity in anthropomorphism studies, followed by ‘International Journal of Social Robotics’ (54) and ‘Frontiers in Psychology’ (39) until data retrieval.

Using the free, open-source software ‘gpsvisuliser.com,’ the geographical dispersal of the authors/organizations in anthropomorphism studies has been exhibited in Figure 2. The red-coloured node displayed on the map depicts countries associated with the publications in anthropomorphism. The size of each node correlates with the number of publications from that particular country. The USA emerged as the leader in anthropomorphism research, boasting 715 publications (30.87%), followed by the UK (12.65%), China (11.18%), Germany (7.12%), and Australia (5.57%) until the data retrieval.

Figure 2:
Geographical distribution of research in anthropomorphism studies. Source: gpsvisuliser.com.

The researchers’ work in the research fraternity is recognized by citing their related publications as a reference. Citations indicate the impact of the researcher’s work value on other researchers’ ability to pursue their research interests. Table 3 presents the annual citation counts for studies on anthropomorphism up until the data retrieval date of this study. Of 2,316 publications examined in this research, 1,901(88.99%) had been cited at least once. It depicts a rising citation trend annually, signifying the importance of the research on anthropomorphism studies. The total citations received until data retrieval were 77,102 counts. Notably, 69,589 (90.26%) of these citations occurred in the last ten years, from 2015 to 2024. The peak annual citation count was in 2024, with 21,661 (28.09%) citations, indicating significant advancements in recent research on anthropomorphism.

Based on citations received by the total publications in the source titles considered in this study, Table 4 portrays the top ten journals in anthropomorphism studies. The topmost journal ‘Computers in Human Behavior’ was able to fetch 5,445 (7.06%) citations from 59 publications, followed by ‘The International Journal of Social Robotics’ with 3,882 (5.04%) citations, and ‘Journal of Consumer Research’ with 3,148 (4.08%) citations until data retrieval. Interestingly, ‘Trends in Cognitive Sciences’ and ‘Journal of Social Issues’ with only one and two publications received 1,266 (1.64%) and 2,441 (3.17%) citations, respectively.

Out of 2,316 publications considered in this research, 1,901 (82.08%) were cited at least once, amounting to 77,102 citations until data retrieval. There were 415 (17.92%) publications, primarily published during the last five years, that had not received any citations until data retrieval. Five publications have received more than 1,000 citations, and 166 have fetched at least 100 citations. Table 5 exhibits the top ten publications in anthropomorphism studies. Almost all top ten publications indicate rising trends of citations annually.

Network analysis is a visual graphical representation of data points using a set of relationships between entities represented by the nodes. Edges act as a linkage between the related nodes. This study used the open-source visualization software ‘VOSviewer’ to draw network diagrams.

The data revealed 6,018 author keywords associated with the anthropomorphism research. The leading keyword, ‘anthropomorphism,’ has been considered by 1,249 research studies and has a total link strength of 5,839 in the network. It was followed by ‘human or humans’ and ‘artificial intelligence.’ However, the keyword ‘human or humans’ had been considered with many other keywords. Notably, “human” has been linked with many other related keywords, such as animal-human, dog-human, human brand, human-agent interaction, human-automation interaction, human-robot interaction, and human-computer interaction. From the font size in the network diagram exhibited in Figure 3, it was obvious that the keyword ‘anthropomorphism’ was the most prominent among the authors in anthropomorphism studies.

Figure 3:
Network of author keywords. Source: Author compilation.

This network has considered 5,246 authors associated with the research area. It was evident from the node size that Waytz (5,754 citations), Epley (5,743 citations), and Cacioppo (4853 citations) were the leading authors in anthropomorphism research, as exhibited in Figure 4. However, we noticed from the top 10 cited authors that ‘Moon and Nass and ‘Croft, Kulić, and Zoghbi,’ with a single publication, received 2,299 and 2,036 citations, respectively, to position themselves in the top category.

Figure 4:
Network of authors linked by co-publication (Screenshot). Source: Author compilation.

The network of countries can be detected considering the interconnectedness of co-authorship among authors from various affiliated organizations worldwide. Currently, 105 countries are associated with research on anthropomorphism. As exhibited in Figure 5 in this research, authors and organizations from the USA had been far ahead of all other countries with the help of the highest number of publications (715), citations (40,381), and total link strength (291). Following the USA were authors and organizations affiliated with the UK, China, and Germany.

Figure 5:
Network of authors and source titles (Screenshot). Source: Author compilation.

The interconnectedness among thirty primary authors, thirty leading journals, and thirty main keywords was observed, as illustrated in Figure 6. The length of the vertical bar for each author, journal, and key words indicates the strength of their association. The number of edges indicates an association among the authors, keywords, and journals. It was clear from the length of the vertical bars that authors Waytz, A.,’ ‘Epley N.’ and ‘Cacioppo J.T,’ keyword ‘anthropomorphism’ and journals Computers in Human Behavior,’ ‘International Journal of Social Robotics’ and ‘Frontiers in Psychology’ were the leading authors, keywords and journals respectively in anthropomorphism studies.

Figure 6:
Network of 30 main authors, keywords, and journals. Source: Author compilation.

The research questions posited at the beginning of the study are answered by conducting a review of the burgeoning literature on anthropomorphism. As a result of TCCM analysis, it is observed that the theoretical grounds of anthropomorphism have progressed over the subsequent years. Besides all the theoretical development, there is a need for new the theoretical insights to unearth the unexplained segments of anthropomorphism. Such unexplained segments can be the human motives like “sense making” and “social connection”, in the management and corporate studies. On “context” front, anthropomorphism in terms of psychological motives of organizational behavior is yet to be explored. There is significant scope for filling this gap in the context of organizational behavior. Moreover, geographically, anthropomorphism studies are conducted in advanced Western countries like the USA and European Union nations but less in developing Asia, especially in the South Asian context. The characteristics of anthropomorphism reveal that “humanizing the non-humans” is the crux of the review in terms of its subsequent antecedents and outcomes. Lastly, the methods’ review observes that the psychology and sociology studies employ conceptual analysis and mixed methods and technology and management studies employ statistical and mathematical analyses along with mixed methods.

Moreover, anthropomorphism’s emergence in organizational behavior can focus on developing relationships between organizations and employees, strategy, organizational image, or reputation building. Employees identify their organization through anthropomorphic cues regarding “who” over “what.” When employees anthropomorphize the organizations, the relationship between them becomes more visceral. Leaders in an organizational context share a strategic mindset, which partially consists of organizational metaphors. This metaphor drives a leader’s feelings, thoughts, and actions toward effective organizational strategy. In organizational image or reputation, anthropomorphism helps the external stakeholders view the organization as a human entity, thereby facilitating its image and reputation building. The present study can be helpful in the organizational behavior domain to strategize HRM policies.