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The set of journals have been ranked according to their SJR and divided into four equal groups, four quartiles. Q1 (green) comprises the quarter of the journals with the highest values, Q2 (yellow) the second highest values, Q3 (orange) the third highest values and Q4 (red) the lowest values.

The SJR is a size-independent prestige indicator that ranks journals by their 'average prestige per article'. It is based on the idea that 'all citations are not created equal'. SJR is a measure of scientific influence of journals that accounts for both the number of citations received by a journal and the importance or prestige of the journals where such citations come from It measures the scientific influence of the average article in a journal, it expresses how central to the global scientific discussion an average article of the journal is.

Evolution of the number of published documents. All types of documents are considered, including citable and non citable documents.

This indicator counts the number of citations received by documents from a journal and divides them by the total number of documents published in that journal. The chart shows the evolution of the average number of times documents published in a journal in the past two, three and four years have been cited in the current year. The two years line is equivalent to journal impact factor ™ (Thomson Reuters) metric.

Evolution of the total number of citations and journal's self-citations received by a journal's published documents during the three previous years. Journal Self-citation is defined as the number of citation from a journal citing article to articles published by the same journal.

Evolution of the number of total citation per document and external citation per document (i.e. journal self-citations removed) received by a journal's published documents during the three previous years. External citations are calculated by subtracting the number of self-citations from the total number of citations received by the journal’s documents.

International Collaboration accounts for the articles that have been produced by researchers from several countries. The chart shows the ratio of a journal's documents signed by researchers from more than one country; that is including more than one country address.

Not every article in a journal is considered primary research and therefore "citable", this chart shows the ratio of a journal's articles including substantial research (research articles, conference papers and reviews) in three year windows vs. those documents other than research articles, reviews and conference papers.

Ratio of a journal's items, grouped in three years windows, that have been cited at least once vs. those not cited during the following year.

Evolution of the percentage of female authors.

Evolution of the number of documents cited by public policy documents according to Overton database.

Evoution of the number of documents related to Sustainable Development Goals defined by United Nations. Available from 2018 onwards.

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Journal of Marketing Research ( JMR ) delves into the latest thinking in marketing research concepts, methods, and applications from a broad range of scholars. It is included in both the  Financial Times  top 50 business journals and the University of Texas at Dallas research rankings journal list. Learn more about JMR here .

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Journal of Public Policy & Marketing ( JPP&M ) is a forum for understanding the nexus of marketing and public policy, with each issue featuring a wide-range of topics, including, but not limited to, ecology, ethics and social responsibility, nutrition and health, regulation and deregulation, security and privacy. Learn more about JPP&M here .

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Impact factor: 4.9

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Review articles: purpose, process, and structure

• Published: 02 October 2017
• Volume 46 , pages 1–5, ( 2018 )

Cite this article

• Robert W. Palmatier 1 ,
• Mark B. Houston 2 &
• John Hulland 3  

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Many research disciplines feature high-impact journals that are dedicated outlets for review papers (or review–conceptual combinations) (e.g., Academy of Management Review , Psychology Bulletin , Medicinal Research Reviews ). The rationale for such outlets is the premise that research integration and synthesis provides an important, and possibly even a required, step in the scientific process. Review papers tend to include both quantitative (i.e., meta-analytic, systematic reviews) and narrative or more qualitative components; together, they provide platforms for new conceptual frameworks, reveal inconsistencies in the extant body of research, synthesize diverse results, and generally give other scholars a “state-of-the-art” snapshot of a domain, often written by topic experts (Bem 1995 ). Many premier marketing journals publish meta-analytic review papers too, though authors often must overcome reviewers’ concerns that their contributions are limited due to the absence of “new data.” Furthermore, relatively few non-meta-analysis review papers appear in marketing journals, probably due to researchers’ perceptions that such papers have limited publication opportunities or their beliefs that the field lacks a research tradition or “respect” for such papers. In many cases, an editor must provide strong support to help such review papers navigate the review process. Yet, once published, such papers tend to be widely cited, suggesting that members of the field find them useful (see Bettencourt and Houston 2001 ).

In this editorial, we seek to address three topics relevant to review papers. First, we outline a case for their importance to the scientific process, by describing the purpose of review papers . Second, we detail the review paper editorial initiative conducted over the past two years by the Journal of the Academy of Marketing Science ( JAMS ), focused on increasing the prevalence of review papers. Third, we describe a process and structure for systematic ( i.e. , non-meta-analytic) review papers , referring to Grewal et al. ( 2018 ) insights into parallel meta-analytic (effects estimation) review papers. (For some strong recent examples of marketing-related meta-analyses, see Knoll and Matthes 2017 ; Verma et al. 2016 ).

Purpose of review papers

In their most general form, review papers “are critical evaluations of material that has already been published,” some that include quantitative effects estimation (i.e., meta-analyses) and some that do not (i.e., systematic reviews) (Bem 1995 , p. 172). They carefully identify and synthesize relevant literature to evaluate a specific research question, substantive domain, theoretical approach, or methodology and thereby provide readers with a state-of-the-art understanding of the research topic. Many of these benefits are highlighted in Hanssens’ ( 2018 ) paper titled “The Value of Empirical Generalizations in Marketing,” published in this same issue of JAMS.

The purpose of and contributions associated with review papers can vary depending on their specific type and research question, but in general, they aim to

Resolve definitional ambiguities and outline the scope of the topic.

Provide an integrated, synthesized overview of the current state of knowledge.

Identify inconsistencies in prior results and potential explanations (e.g., moderators, mediators, measures, approaches).

Evaluate existing methodological approaches and unique insights.

Develop conceptual frameworks to reconcile and extend past research.

Describe research insights, existing gaps, and future research directions.

Not every review paper can offer all of these benefits, but this list represents their key contributions. To provide a sufficient contribution, a review paper needs to achieve three key standards. First, the research domain needs to be well suited for a review paper, such that a sufficient body of past research exists to make the integration and synthesis valuable—especially if extant research reveals theoretical inconsistences or heterogeneity in its effects. Second, the review paper must be well executed, with an appropriate literature collection and analysis techniques, sufficient breadth and depth of literature coverage, and a compelling writing style. Third, the manuscript must offer significant new insights based on its systematic comparison of multiple studies, rather than simply a “book report” that describes past research. This third, most critical standard is often the most difficult, especially for authors who have not “lived” with the research domain for many years, because achieving it requires drawing some non-obvious connections and insights from multiple studies and their many different aspects (e.g., context, method, measures). Typically, after the “review” portion of the paper has been completed, the authors must spend many more months identifying the connections to uncover incremental insights, each of which takes time to detail and explicate.

The increasing methodological rigor and technical sophistication of many marketing studies also means that they often focus on smaller problems with fewer constructs. By synthesizing these piecemeal findings, reconciling conflicting evidence, and drawing a “big picture,” meta-analyses and systematic review papers become indispensable to our comprehensive understanding of a phenomenon, among both academic and practitioner communities. Thus, good review papers provide a solid platform for future research, in the reviewed domain but also in other areas, in that researchers can use a good review paper to learn about and extend key insights to new areas.

This domain extension, outside of the core area being reviewed, is one of the key benefits of review papers that often gets overlooked. Yet it also is becoming ever more important with the expanding breadth of marketing (e.g., econometric modeling, finance, strategic management, applied psychology, sociology) and the increasing velocity in the accumulation of marketing knowledge (e.g., digital marketing, social media, big data). Against this backdrop, systematic review papers and meta-analyses help academics and interested managers keep track of research findings that fall outside their main area of specialization.

JAMS’ review paper editorial initiative

With a strong belief in the importance of review papers, the editorial team of JAMS has purposely sought out leading scholars to provide substantive review papers, both meta-analysis and systematic, for publication in JAMS . Many of the scholars approached have voiced concerns about the risk of such endeavors, due to the lack of alternative outlets for these types of papers. Therefore, we have instituted a unique process, in which the authors develop a detailed outline of their paper, key tables and figures, and a description of their literature review process. On the basis of this outline, we grant assurances that the contribution hurdle will not be an issue for publication in JAMS , as long as the authors execute the proposed outline as written. Each paper still goes through the normal review process and must meet all publication quality standards, of course. In many cases, an Area Editor takes an active role to help ensure that each paper provides sufficient insights, as required for a high-quality review paper. This process gives the author team confidence to invest effort in the process. An analysis of the marketing journals in the Financial Times (FT 50) journal list for the past five years (2012–2016) shows that JAMS has become the most common outlet for these papers, publishing 31% of all review papers that appeared in the top six marketing journals.

As a next step in positioning JAMS as a receptive marketing outlet for review papers, we are conducting a Thought Leaders Conference on Generalizations in Marketing: Systematic Reviews and Meta-Analyses , with a corresponding special issue (see www.springer.com/jams ). We will continue our process of seeking out review papers as an editorial strategy in areas that could be advanced by the integration and synthesis of extant research. We expect that, ultimately, such efforts will become unnecessary, as authors initiate review papers on topics of their own choosing to submit them to JAMS . In the past two years, JAMS already has increased the number of papers it publishes annually, from just over 40 to around 60 papers per year; this growth has provided “space” for 8–10 review papers per year, reflecting our editorial target.

Consistent with JAMS ’ overall focus on managerially relevant and strategy-focused topics, all review papers should reflect this emphasis. For example, the domains, theories, and methods reviewed need to have some application to past or emerging managerial research. A good rule of thumb is that the substantive domain, theory, or method should attract the attention of readers of JAMS .

The efforts of multiple editors and Area Editors in turn have generated a body of review papers that can serve as useful examples of the different types and approaches that JAMS has published.

Domain-based review papers

Domain-based review papers review, synthetize, and extend a body of literature in the same substantive domain. For example, in “The Role of Privacy in Marketing” (Martin and Murphy 2017 ), the authors identify and define various privacy-related constructs that have appeared in recent literature. Then they examine the different theoretical perspectives brought to bear on privacy topics related to consumers and organizations, including ethical and legal perspectives. These foundations lead in to their systematic review of privacy-related articles over a clearly defined date range, from which they extract key insights from each study. This exercise of synthesizing diverse perspectives allows these authors to describe state-of-the-art knowledge regarding privacy in marketing and identify useful paths for research. Similarly, a new paper by Cleeren et al. ( 2017 ), “Marketing Research on Product-Harm Crises: A Review, Managerial Implications, and an Agenda for Future Research,” provides a rich systematic review, synthesizes extant research, and points the way forward for scholars who are interested in issues related to defective or dangerous market offerings.

Theory-based review papers

Theory-based review papers review, synthetize, and extend a body of literature that uses the same underlying theory. For example, Rindfleisch and Heide’s ( 1997 ) classic review of research in marketing using transaction cost economics has been cited more than 2200 times, with a significant impact on applications of the theory to the discipline in the past 20 years. A recent paper in JAMS with similar intent, which could serve as a helpful model, focuses on “Resource-Based Theory in Marketing” (Kozlenkova et al. 2014 ). The article dives deeply into a description of the theory and its underlying assumptions, then organizes a systematic review of relevant literature according to various perspectives through which the theory has been applied in marketing. The authors conclude by identifying topical domains in marketing that might benefit from additional applications of the theory (e.g., marketing exchange), as well as related theories that could be integrated meaningfully with insights from the resource-based theory.

Method-based review papers

Method-based review papers review, synthetize, and extend a body of literature that uses the same underlying method. For example, in “Event Study Methodology in the Marketing Literature: An Overview” (Sorescu et al. 2017 ), the authors identify published studies in marketing that use an event study methodology. After a brief review of the theoretical foundations of event studies, they describe in detail the key design considerations associated with this method. The article then provides a roadmap for conducting event studies and compares this approach with a stock market returns analysis. The authors finish with a summary of the strengths and weaknesses of the event study method, which in turn suggests three main areas for further research. Similarly, “Discriminant Validity Testing in Marketing: An Analysis, Causes for Concern, and Proposed Remedies” (Voorhies et al. 2016 ) systematically reviews existing approaches for assessing discriminant validity in marketing contexts, then uses Monte Carlo simulation to determine which tests are most effective.

Our long-term editorial strategy is to make sure JAMS becomes and remains a well-recognized outlet for both meta-analysis and systematic managerial review papers in marketing. Ideally, review papers would come to represent 10%–20% of the papers published by the journal.

Process and structure for review papers

In this section, we review the process and typical structure of a systematic review paper, which lacks any long or established tradition in marketing research. The article by Grewal et al. ( 2018 ) provides a summary of effects-focused review papers (i.e., meta-analyses), so we do not discuss them in detail here.

Systematic literature review process

Some review papers submitted to journals take a “narrative” approach. They discuss current knowledge about a research domain, yet they often are flawed, in that they lack criteria for article inclusion (or, more accurately, article exclusion), fail to discuss the methodology used to evaluate included articles, and avoid critical assessment of the field (Barczak 2017 ). Such reviews tend to be purely descriptive, with little lasting impact.

In contrast, a systematic literature review aims to “comprehensively locate and synthesize research that bears on a particular question, using organized, transparent, and replicable procedures at each step in the process” (Littell et al. 2008 , p. 1). Littell et al. describe six key steps in the systematic review process. The extent to which each step is emphasized varies by paper, but all are important components of the review.

Topic formulation . The author sets out clear objectives for the review and articulates the specific research questions or hypotheses that will be investigated.

Study design . The author specifies relevant problems, populations, constructs, and settings of interest. The aim is to define explicit criteria that can be used to assess whether any particular study should be included in or excluded from the review. Furthermore, it is important to develop a protocol in advance that describes the procedures and methods to be used to evaluate published work.

Sampling . The aim in this third step is to identify all potentially relevant studies, including both published and unpublished research. To this end, the author must first define the sampling unit to be used in the review (e.g., individual, strategic business unit) and then develop an appropriate sampling plan.

Data collection . By retrieving the potentially relevant studies identified in the third step, the author can determine whether each study meets the eligibility requirements set out in the second step. For studies deemed acceptable, the data are extracted from each study and entered into standardized templates. These templates should be based on the protocols established in step 2.

Data analysis . The degree and nature of the analyses used to describe and examine the collected data vary widely by review. Purely descriptive analysis is useful as a starting point but rarely is sufficient on its own. The examination of trends, clusters of ideas, and multivariate relationships among constructs helps flesh out a deeper understanding of the domain. For example, both Hult ( 2015 ) and Huber et al. ( 2014 ) use bibliometric approaches (e.g., examine citation data using multidimensional scaling and cluster analysis techniques) to identify emerging versus declining themes in the broad field of marketing.

Reporting . Three key aspects of this final step are common across systematic reviews. First, the results from the fifth step need to be presented, clearly and compellingly, using narratives, tables, and figures. Second, core results that emerge from the review must be interpreted and discussed by the author. These revelatory insights should reflect a deeper understanding of the topic being investigated, not simply a regurgitation of well-established knowledge. Third, the author needs to describe the implications of these unique insights for both future research and managerial practice.

A new paper by Watson et al. ( 2017 ), “Harnessing Difference: A Capability-Based Framework for Stakeholder Engagement in Environmental Innovation,” provides a good example of a systematic review, starting with a cohesive conceptual framework that helps establish the boundaries of the review while also identifying core constructs and their relationships. The article then explicitly describes the procedures used to search for potentially relevant papers and clearly sets out criteria for study inclusion or exclusion. Next, a detailed discussion of core elements in the framework weaves published research findings into the exposition. The paper ends with a presentation of key implications and suggestions for the next steps. Similarly, “Marketing Survey Research Best Practices: Evidence and Recommendations from a Review of JAMS Articles” (Hulland et al. 2017 ) systematically reviews published marketing studies that use survey techniques, describes recent trends, and suggests best practices. In their review, Hulland et al. examine the entire population of survey papers published in JAMS over a ten-year span, relying on an extensive standardized data template to facilitate their subsequent data analysis.

Structure of systematic review papers

There is no cookie-cutter recipe for the exact structure of a useful systematic review paper; the final structure depends on the authors’ insights and intended points of emphasis. However, several key components are likely integral to a paper’s ability to contribute.

Depth and rigor

Systematic review papers must avoid falling in to two potential “ditches.” The first ditch threatens when the paper fails to demonstrate that a systematic approach was used for selecting articles for inclusion and capturing their insights. If a reader gets the impression that the author has cherry-picked only articles that fit some preset notion or failed to be thorough enough, without including articles that make significant contributions to the field, the paper will be consigned to the proverbial side of the road when it comes to the discipline’s attention.

Authors that fall into the other ditch present a thorough, complete overview that offers only a mind-numbing recitation, without evident organization, synthesis, or critical evaluation. Although comprehensive, such a paper is more of an index than a useful review. The reviewed articles must be grouped in a meaningful way to guide the reader toward a better understanding of the focal phenomenon and provide a foundation for insights about future research directions. Some scholars organize research by scholarly perspectives (e.g., the psychology of privacy, the economics of privacy; Martin and Murphy 2017 ); others classify the chosen articles by objective research aspects (e.g., empirical setting, research design, conceptual frameworks; Cleeren et al. 2017 ). The method of organization chosen must allow the author to capture the complexity of the underlying phenomenon (e.g., including temporal or evolutionary aspects, if relevant).

Replicability

Processes for the identification and inclusion of research articles should be described in sufficient detail, such that an interested reader could replicate the procedure. The procedures used to analyze chosen articles and extract their empirical findings and/or key takeaways should be described with similar specificity and detail.

We already have noted the potential usefulness of well-done review papers. Some scholars always are new to the field or domain in question, so review papers also need to help them gain foundational knowledge. Key constructs, definitions, assumptions, and theories should be laid out clearly (for which purpose summary tables are extremely helpful). An integrated conceptual model can be useful to organize cited works. Most scholars integrate the knowledge they gain from reading the review paper into their plans for future research, so it is also critical that review papers clearly lay out implications (and specific directions) for research. Ideally, readers will come away from a review article filled with enthusiasm about ways they might contribute to the ongoing development of the field.

Helpful format

Because such a large body of research is being synthesized in most review papers, simply reading through the list of included studies can be exhausting for readers. We cannot overstate the importance of tables and figures in review papers, used in conjunction with meaningful headings and subheadings. Vast literature review tables often are essential, but they must be organized in a way that makes their insights digestible to the reader; in some cases, a sequence of more focused tables may be better than a single, comprehensive table.

In summary, articles that review extant research in a domain (topic, theory, or method) can be incredibly useful to the scientific progress of our field. Whether integrating the insights from extant research through a meta-analysis or synthesizing them through a systematic assessment, the promised benefits are similar. Both formats provide readers with a useful overview of knowledge about the focal phenomenon, as well as insights on key dilemmas and conflicting findings that suggest future research directions. Thus, the editorial team at JAMS encourages scholars to continue to invest the time and effort to construct thoughtful review papers.

Barczak, G. (2017). From the editor: writing a review article. Journal of Product Innovation Management, 34 (2), 120–121.

Article   Google Scholar  

Bem, D. J. (1995). Writing a review article for psychological bulletin. Psychological Bulletin, 118 (2), 172–177.

Bettencourt, L. A., & Houston, M. B. (2001). Assessing the impact of article method type and subject area on citation frequency and reference diversity. Marketing Letters, 12 (4), 327–340.

Cleeren, K., Dekimpe, M. G., & van Heerde, H. J. (2017). Marketing research on product-harm crises: a review, managerial implications. Journal of the Academy of Marketing Science, 45 (5), 593–615.

Grewal, D., Puccinelli, N. M., & Monroe, K. B. (2018). Meta-analysis: error cancels and truth accrues. Journal of the Academy of Marketing Science, 46 (1).

Hanssens, D. M. (2018). The value of empirical generalizations in marketing. Journal of the Academy of Marketing Science, 46 (1).

Huber, J., Kamakura, W., & Mela, C. F. (2014). A topical history of JMR . Journal of Marketing Research, 51 (1), 84–91.

Hulland, J., Baumgartner, H., & Smith, K. M. (2017). Marketing survey research best practices: evidence and recommendations from a review of JAMS articles. Journal of the Academy of Marketing Science. https://doi.org/10.1007/s11747-017-0532-y .

Hult, G. T. M. (2015). JAMS 2010—2015: literature themes and intellectual structure. Journal of the Academy of Marketing Science, 43 (6), 663–669.

Knoll, J., & Matthes, J. (2017). The effectiveness of celebrity endorsements: a meta-analysis. Journal of the Academy of Marketing Science, 45 (1), 55–75.

Kozlenkova, I. V., Samaha, S. A., & Palmatier, R. W. (2014). Resource-based theory in marketing. Journal of the Academy of Marketing Science, 42 (1), 1–21.

Littell, J. H., Corcoran, J., & Pillai, V. (2008). Systematic reviews and meta-analysis . New York: Oxford University Press.

Book   Google Scholar  

Martin, K. D., & Murphy, P. E. (2017). The role of data privacy in marketing. Journal of the Academy of Marketing Science, 45 (2), 135–155.

Rindfleisch, A., & Heide, J. B. (1997). Transaction cost analysis: past, present, and future applications. Journal of Marketing, 61 (4), 30–54.

Sorescu, A., Warren, N. L., & Ertekin, L. (2017). Event study methodology in the marketing literature: an overview. Journal of the Academy of Marketing Science, 45 (2), 186–207.

Verma, V., Sharma, D., & Sheth, J. (2016). Does relationship marketing matter in online retailing? A meta-analytic approach. Journal of the Academy of Marketing Science, 44 (2), 206–217.

Voorhies, C. M., Brady, M. K., Calantone, R., & Ramirez, E. (2016). Discriminant validity testing in marketing: an analysis, causes for concern, and proposed remedies. Journal of the Academy of Marketing Science, 44 (1), 119–134.

Watson, R., Wilson, H. N., Smart, P., & Macdonald, E. K. (2017). Harnessing difference: a capability-based framework for stakeholder engagement in environmental innovation. Journal of Product Innovation Management. https://doi.org/10.1111/jpim.12394 .

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Palmatier, R.W., Houston, M.B. & Hulland, J. Review articles: purpose, process, and structure. J. of the Acad. Mark. Sci. 46 , 1–5 (2018). https://doi.org/10.1007/s11747-017-0563-4

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Brand Activism in the Service Industry: A Systematic Literature Review and Directions for Future Research and Practices

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Researchers are increasingly examining brand activism, where companies integrate strong social, environmental, or political stances into their core strategies. This study focuses on brand activism within the service industry. A systematic literature review was conducted, combining bibliometric analysis and structured review, following the SPAR-4-SLR protocol. 48 publications were analyzed without time limits to uncover themes within brand activism. The study refines understanding of brand activism in marketing strategy, suggests new research directions, and offers managerial insights. This research advances the study of brand activism by exploring its role in the service industry.

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Knowledge mapping and evolution of research on older adults’ technology acceptance: a bibliometric study from 2013 to 2023

• Xianru Shang   ORCID: orcid.org/0009-0000-8906-3216 1 ,
• Zijian Liu 1 ,
• Chen Gong 1 ,
• Zhigang Hu 1 ,
• Yuexuan Wu 1 &
• Chengliang Wang   ORCID: orcid.org/0000-0003-2208-3508 2  

Humanities and Social Sciences Communications volume  11 , Article number:  1115 ( 2024 ) Cite this article

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• Science, technology and society

The rapid expansion of information technology and the intensification of population aging are two prominent features of contemporary societal development. Investigating older adults’ acceptance and use of technology is key to facilitating their integration into an information-driven society. Given this context, the technology acceptance of older adults has emerged as a prioritized research topic, attracting widespread attention in the academic community. However, existing research remains fragmented and lacks a systematic framework. To address this gap, we employed bibliometric methods, utilizing the Web of Science Core Collection to conduct a comprehensive review of literature on older adults’ technology acceptance from 2013 to 2023. Utilizing VOSviewer and CiteSpace for data assessment and visualization, we created knowledge mappings of research on older adults’ technology acceptance. Our study employed multidimensional methods such as co-occurrence analysis, clustering, and burst analysis to: (1) reveal research dynamics, key journals, and domains in this field; (2) identify leading countries, their collaborative networks, and core research institutions and authors; (3) recognize the foundational knowledge system centered on theoretical model deepening, emerging technology applications, and research methods and evaluation, uncovering seminal literature and observing a shift from early theoretical and influential factor analyses to empirical studies focusing on individual factors and emerging technologies; (4) moreover, current research hotspots are primarily in the areas of factors influencing technology adoption, human-robot interaction experiences, mobile health management, and aging-in-place technology, highlighting the evolutionary context and quality distribution of research themes. Finally, we recommend that future research should deeply explore improvements in theoretical models, long-term usage, and user experience evaluation. Overall, this study presents a clear framework of existing research in the field of older adults’ technology acceptance, providing an important reference for future theoretical exploration and innovative applications.

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Introduction.

In contemporary society, the rapid development of information technology has been intricately intertwined with the intensifying trend of population aging. According to the latest United Nations forecast, by 2050, the global population aged 65 and above is expected to reach 1.6 billion, representing about 16% of the total global population (UN 2023 ). Given the significant challenges of global aging, there is increasing evidence that emerging technologies have significant potential to maintain health and independence for older adults in their home and healthcare environments (Barnard et al. 2013 ; Soar 2010 ; Vancea and Solé-Casals 2016 ). This includes, but is not limited to, enhancing residential safety with smart home technologies (Touqeer et al. 2021 ; Wang et al. 2022 ), improving living independence through wearable technologies (Perez et al. 2023 ), and increasing medical accessibility via telehealth services (Kruse et al. 2020 ). Technological innovations are redefining the lifestyles of older adults, encouraging a shift from passive to active participation (González et al. 2012 ; Mostaghel 2016 ). Nevertheless, the effective application and dissemination of technology still depends on user acceptance and usage intentions (Naseri et al. 2023 ; Wang et al. 2023a ; Xia et al. 2024 ; Yu et al. 2023 ). Particularly, older adults face numerous challenges in accepting and using new technologies. These challenges include not only physical and cognitive limitations but also a lack of technological experience, along with the influences of social and economic factors (Valk et al. 2018 ; Wilson et al. 2021 ).

User acceptance of technology is a significant focus within information systems (IS) research (Dai et al. 2024 ), with several models developed to explain and predict user behavior towards technology usage, including the Technology Acceptance Model (TAM) (Davis 1989 ), TAM2, TAM3, and the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al. 2003 ). Older adults, as a group with unique needs, exhibit different behavioral patterns during technology acceptance than other user groups, and these uniquenesses include changes in cognitive abilities, as well as motivations, attitudes, and perceptions of the use of new technologies (Chen and Chan 2011 ). The continual expansion of technology introduces considerable challenges for older adults, rendering the understanding of their technology acceptance a research priority. Thus, conducting in-depth research into older adults’ acceptance of technology is critically important for enhancing their integration into the information society and improving their quality of life through technological advancements.

Reviewing relevant literature to identify research gaps helps further solidify the theoretical foundation of the research topic. However, many existing literature reviews primarily focus on the factors influencing older adults’ acceptance or intentions to use technology. For instance, Ma et al. ( 2021 ) conducted a comprehensive analysis of the determinants of older adults’ behavioral intentions to use technology; Liu et al. ( 2022 ) categorized key variables in studies of older adults’ technology acceptance, noting a shift in focus towards social and emotional factors; Yap et al. ( 2022 ) identified seven categories of antecedents affecting older adults’ use of technology from an analysis of 26 articles, including technological, psychological, social, personal, cost, behavioral, and environmental factors; Schroeder et al. ( 2023 ) extracted 119 influencing factors from 59 articles and further categorized these into six themes covering demographics, health status, and emotional awareness. Additionally, some studies focus on the application of specific technologies, such as Ferguson et al. ( 2021 ), who explored barriers and facilitators to older adults using wearable devices for heart monitoring, and He et al. ( 2022 ) and Baer et al. ( 2022 ), who each conducted in-depth investigations into the acceptance of social assistive robots and mobile nutrition and fitness apps, respectively. In summary, current literature reviews on older adults’ technology acceptance exhibit certain limitations. Due to the interdisciplinary nature and complex knowledge structure of this field, traditional literature reviews often rely on qualitative analysis, based on literature analysis and periodic summaries, which lack sufficient objectivity and comprehensiveness. Additionally, systematic research is relatively limited, lacking a macroscopic description of the research trajectory from a holistic perspective. Over the past decade, research on older adults’ technology acceptance has experienced rapid growth, with a significant increase in literature, necessitating the adoption of new methods to review and examine the developmental trends in this field (Chen 2006 ; Van Eck and Waltman 2010 ). Bibliometric analysis, as an effective quantitative research method, analyzes published literature through visualization, offering a viable approach to extracting patterns and insights from a large volume of papers, and has been widely applied in numerous scientific research fields (Achuthan et al. 2023 ; Liu and Duffy 2023 ). Therefore, this study will employ bibliometric methods to systematically analyze research articles related to older adults’ technology acceptance published in the Web of Science Core Collection from 2013 to 2023, aiming to understand the core issues and evolutionary trends in the field, and to provide valuable references for future related research. Specifically, this study aims to explore and answer the following questions:

RQ1: What are the research dynamics in the field of older adults’ technology acceptance over the past decade? What are the main academic journals and fields that publish studies related to older adults’ technology acceptance?

RQ2: How is the productivity in older adults’ technology acceptance research distributed among countries, institutions, and authors?

RQ3: What are the knowledge base and seminal literature in older adults’ technology acceptance research? How has the research theme progressed?

RQ4: What are the current hot topics and their evolutionary trajectories in older adults’ technology acceptance research? How is the quality of research distributed?

Methodology and materials

Research method.

In recent years, bibliometrics has become one of the crucial methods for analyzing literature reviews and is widely used in disciplinary and industrial intelligence analysis (Jing et al. 2023 ; Lin and Yu 2024a ; Wang et al. 2024a ; Xu et al. 2021 ). Bibliometric software facilitates the visualization analysis of extensive literature data, intuitively displaying the network relationships and evolutionary processes between knowledge units, and revealing the underlying knowledge structure and potential information (Chen et al. 2024 ; López-Robles et al. 2018 ; Wang et al. 2024c ). This method provides new insights into the current status and trends of specific research areas, along with quantitative evidence, thereby enhancing the objectivity and scientific validity of the research conclusions (Chen et al. 2023 ; Geng et al. 2024 ). VOSviewer and CiteSpace are two widely used bibliometric software tools in academia (Pan et al. 2018 ), recognized for their robust functionalities based on the JAVA platform. Although each has its unique features, combining these two software tools effectively constructs mapping relationships between literature knowledge units and clearly displays the macrostructure of the knowledge domains. Particularly, VOSviewer, with its excellent graphical representation capabilities, serves as an ideal tool for handling large datasets and precisely identifying the focal points and hotspots of research topics. Therefore, this study utilizes VOSviewer (version 1.6.19) and CiteSpace (version 6.1.R6), combined with in-depth literature analysis, to comprehensively examine and interpret the research theme of older adults’ technology acceptance through an integrated application of quantitative and qualitative methods.

Data source

Web of Science is a comprehensively recognized database in academia, featuring literature that has undergone rigorous peer review and editorial scrutiny (Lin and Yu 2024b ; Mongeon and Paul-Hus 2016 ; Pranckutė 2021 ). This study utilizes the Web of Science Core Collection as its data source, specifically including three major citation indices: Science Citation Index Expanded (SCIE), Social Sciences Citation Index (SSCI), and Arts & Humanities Citation Index (A&HCI). These indices encompass high-quality research literature in the fields of science, social sciences, and arts and humanities, ensuring the comprehensiveness and reliability of the data. We combined “older adults” with “technology acceptance” through thematic search, with the specific search strategy being: TS = (elder OR elderly OR aging OR ageing OR senile OR senior OR old people OR “older adult*”) AND TS = (“technology acceptance” OR “user acceptance” OR “consumer acceptance”). The time span of literature search is from 2013 to 2023, with the types limited to “Article” and “Review” and the language to “English”. Additionally, the search was completed by October 27, 2023, to avoid data discrepancies caused by database updates. The initial search yielded 764 journal articles. Given that searches often retrieve articles that are superficially relevant but actually non-compliant, manual screening post-search was essential to ensure the relevance of the literature (Chen et al. 2024 ). Through manual screening, articles significantly deviating from the research theme were eliminated and rigorously reviewed. Ultimately, this study obtained 500 valid sample articles from the Web of Science Core Collection. The complete PRISMA screening process is illustrated in Fig. 1 .

Presentation of the data culling process in detail.

Data standardization

Raw data exported from databases often contain multiple expressions of the same terminology (Nguyen and Hallinger 2020 ). To ensure the accuracy and consistency of data, it is necessary to standardize the raw data (Strotmann and Zhao 2012 ). This study follows the data standardization process proposed by Taskin and Al ( 2019 ), mainly executing the following operations:

(1) Standardization of author and institution names is conducted to address different name expressions for the same author. For instance, “Chan, Alan Hoi Shou” and “Chan, Alan H. S.” are considered the same author, and distinct authors with the same name are differentiated by adding identifiers. Diverse forms of institutional names are unified to address variations caused by name changes or abbreviations, such as standardizing “FRANKFURT UNIV APPL SCI” and “Frankfurt University of Applied Sciences,” as well as “Chinese University of Hong Kong” and “University of Hong Kong” to consistent names.

(2) Different expressions of journal names are unified. For example, “International Journal of Human-Computer Interaction” and “Int J Hum Comput Interact” are standardized to a single name. This ensures consistency in journal names and prevents misclassification of literature due to differing journal names. Additionally, it involves checking if the journals have undergone name changes in the past decade to prevent any impact on the analysis due to such changes.

(3) Keywords data are cleansed by removing words that do not directly pertain to specific research content (e.g., people, review), merging synonyms (e.g., “UX” and “User Experience,” “aging-in-place” and “aging in place”), and standardizing plural forms of keywords (e.g., “assistive technologies” and “assistive technology,” “social robots” and “social robot”). This reduces redundant information in knowledge mapping.

Bibliometric results and analysis

Distribution power (rq1), literature descriptive statistical analysis.

Table 1 presents a detailed descriptive statistical overview of the literature in the field of older adults’ technology acceptance. After deduplication using the CiteSpace software, this study confirmed a valid sample size of 500 articles. Authored by 1839 researchers, the documents encompass 792 research institutions across 54 countries and are published in 217 different academic journals. As of the search cutoff date, these articles have accumulated 13,829 citations, with an annual average of 1156 citations, and an average of 27.66 citations per article. The h-index, a composite metric of quantity and quality of scientific output (Kamrani et al. 2021 ), reached 60 in this study.

Trends in publications and disciplinary distribution

The number of publications and citations are significant indicators of the research field’s development, reflecting its continuity, attention, and impact (Ale Ebrahim et al. 2014 ). The ranking of annual publications and citations in the field of older adults’ technology acceptance studies is presented chronologically in Fig. 2A . The figure shows a clear upward trend in the amount of literature in this field. Between 2013 and 2017, the number of publications increased slowly and decreased in 2018. However, in 2019, the number of publications increased rapidly to 52 and reached a peak of 108 in 2022, which is 6.75 times higher than in 2013. In 2022, the frequency of document citations reached its highest point with 3466 citations, reflecting the widespread recognition and citation of research in this field. Moreover, the curve of the annual number of publications fits a quadratic function, with a goodness-of-fit R 2 of 0.9661, indicating that the number of future publications is expected to increase even more rapidly.

A Trends in trends in annual publications and citations (2013–2023). B Overlay analysis of the distribution of discipline fields.

Figure 2B shows that research on older adults’ technology acceptance involves the integration of multidisciplinary knowledge. According to Web of Science Categories, these 500 articles are distributed across 85 different disciplines. We have tabulated the top ten disciplines by publication volume (Table 2 ), which include Medical Informatics (75 articles, 15.00%), Health Care Sciences & Services (71 articles, 14.20%), Gerontology (61 articles, 12.20%), Public Environmental & Occupational Health (57 articles, 11.40%), and Geriatrics & Gerontology (52 articles, 10.40%), among others. The high output in these disciplines reflects the concentrated global academic interest in this comprehensive research topic. Additionally, interdisciplinary research approaches provide diverse perspectives and a solid theoretical foundation for studies on older adults’ technology acceptance, also paving the way for new research directions.

Knowledge flow analysis

A dual-map overlay is a CiteSpace map superimposed on top of a base map, which shows the interrelationships between journals in different domains, representing the publication and citation activities in each domain (Chen and Leydesdorff 2014 ). The overlay map reveals the link between the citing domain (on the left side) and the cited domain (on the right side), reflecting the knowledge flow of the discipline at the journal level (Leydesdorff and Rafols 2012 ). We utilize the in-built Z-score algorithm of the software to cluster the graph, as shown in Fig. 3 .

The left side shows the citing journal, and the right side shows the cited journal.

Figure 3 shows the distribution of citing journals clusters for older adults’ technology acceptance on the left side, while the right side refers to the main cited journals clusters. Two knowledge flow citation trajectories were obtained; they are presented by the color of the cited regions, and the thickness of these trajectories is proportional to the Z-score scaled frequency of citations (Chen et al. 2014 ). Within the cited regions, the most popular fields with the most records covered are “HEALTH, NURSING, MEDICINE” and “PSYCHOLOGY, EDUCATION, SOCIAL”, and the elliptical aspect ratio of these two fields stands out. Fields have prominent elliptical aspect ratios, highlighting their significant influence on older adults’ technology acceptance research. Additionally, the major citation trajectories originate in these two areas and progress to the frontier research area of “PSYCHOLOGY, EDUCATION, HEALTH”. It is worth noting that the citation trajectory from “PSYCHOLOGY, EDUCATION, SOCIAL” has a significant Z-value (z = 6.81), emphasizing the significance and impact of this development path. In the future, “MATHEMATICS, SYSTEMS, MATHEMATICAL”, “MOLECULAR, BIOLOGY, IMMUNOLOGY”, and “NEUROLOGY, SPORTS, OPHTHALMOLOGY” may become emerging fields. The fields of “MEDICINE, MEDICAL, CLINICAL” may be emerging areas of cutting-edge research.

Main research journals analysis

Table 3 provides statistics for the top ten journals by publication volume in the field of older adults’ technology acceptance. Together, these journals have published 137 articles, accounting for 27.40% of the total publications, indicating that there is no highly concentrated core group of journals in this field, with publications being relatively dispersed. Notably, Computers in Human Behavior , Journal of Medical Internet Research , and International Journal of Human-Computer Interaction each lead with 15 publications. In terms of citation metrics, International Journal of Medical Informatics and Computers in Human Behavior stand out significantly, with the former accumulating a total of 1,904 citations, averaging 211.56 citations per article, and the latter totaling 1,449 citations, with an average of 96.60 citations per article. These figures emphasize the academic authority and widespread impact of these journals within the research field.

Research power (RQ2)

Countries and collaborations analysis.

The analysis revealed the global research pattern for country distribution and collaboration (Chen et al. 2019 ). Figure 4A shows the network of national collaborations on older adults’ technology acceptance research. The size of the bubbles represents the amount of publications in each country, while the thickness of the connecting lines expresses the closeness of the collaboration among countries. Generally, this research subject has received extensive international attention, with China and the USA publishing far more than any other countries. China has established notable research collaborations with the USA, UK and Malaysia in this field, while other countries have collaborations, but the closeness is relatively low and scattered. Figure 4B shows the annual publication volume dynamics of the top ten countries in terms of total publications. Since 2017, China has consistently increased its annual publications, while the USA has remained relatively stable. In 2019, the volume of publications in each country increased significantly, this was largely due to the global outbreak of the COVID-19 pandemic, which has led to increased reliance on information technology among the elderly for medical consultations, online socialization, and health management (Sinha et al. 2021 ). This phenomenon has led to research advances in technology acceptance among older adults in various countries. Table 4 shows that the top ten countries account for 93.20% of the total cumulative number of publications, with each country having published more than 20 papers. Among these ten countries, all of them except China are developed countries, indicating that the research field of older adults’ technology acceptance has received general attention from developed countries. Currently, China and the USA were the leading countries in terms of publications with 111 and 104 respectively, accounting for 22.20% and 20.80%. The UK, Germany, Italy, and the Netherlands also made significant contributions. The USA and China ranked first and second in terms of the number of citations, while the Netherlands had the highest average citations, indicating the high impact and quality of its research. The UK has shown outstanding performance in international cooperation, while the USA highlights its significant academic influence in this field with the highest h-index value.

A National collaboration network. B Annual volume of publications in the top 10 countries.

Institutions and authors analysis

Analyzing the number of publications and citations can reveal an institution’s or author’s research strength and influence in a particular research area (Kwiek 2021 ). Tables 5 and 6 show the statistics of the institutions and authors whose publication counts are in the top ten, respectively. As shown in Table 5 , higher education institutions hold the main position in this research field. Among the top ten institutions, City University of Hong Kong and The University of Hong Kong from China lead with 14 and 9 publications, respectively. City University of Hong Kong has the highest h-index, highlighting its significant influence in the field. It is worth noting that Tilburg University in the Netherlands is not among the top five in terms of publications, but the high average citation count (130.14) of its literature demonstrates the high quality of its research.

After analyzing the authors’ output using Price’s Law (Redner 1998 ), the highest number of publications among the authors counted ( n  = 10) defines a publication threshold of 3 for core authors in this research area. As a result of quantitative screening, a total of 63 core authors were identified. Table 6 shows that Chen from Zhejiang University, China, Ziefle from RWTH Aachen University, Germany, and Rogers from Macquarie University, Australia, were the top three authors in terms of the number of publications, with 10, 9, and 8 articles, respectively. In terms of average citation rate, Peek and Wouters, both scholars from the Netherlands, have significantly higher rates than other scholars, with 183.2 and 152.67 respectively. This suggests that their research is of high quality and widely recognized. Additionally, Chen and Rogers have high h-indices in this field.

Knowledge base and theme progress (RQ3)

Research knowledge base.

Co-citation relationships occur when two documents are cited together (Zhang and Zhu 2022 ). Co-citation mapping uses references as nodes to represent the knowledge base of a subject area (Min et al. 2021). Figure 5A illustrates co-occurrence mapping in older adults’ technology acceptance research, where larger nodes signify higher co-citation frequencies. Co-citation cluster analysis can be used to explore knowledge structure and research boundaries (Hota et al. 2020 ; Shiau et al. 2023 ). The co-citation clustering mapping of older adults’ technology acceptance research literature (Fig. 5B ) shows that the Q value of the clustering result is 0.8129 (>0.3), and the average value of the weight S is 0.9391 (>0.7), indicating that the clusters are uniformly distributed with a significant and credible structure. This further proves that the boundaries of the research field are clear and there is significant differentiation in the field. The figure features 18 cluster labels, each associated with thematic color blocks corresponding to different time slices. Highlighted emerging research themes include #2 Smart Home Technology, #7 Social Live, and #10 Customer Service. Furthermore, the clustering labels extracted are primarily classified into three categories: theoretical model deepening, emerging technology applications, research methods and evaluation, as detailed in Table 7 .

A Co-citation analysis of references. B Clustering network analysis of references.

Seminal literature analysis

The top ten nodes in terms of co-citation frequency were selected for further analysis. Table 8 displays the corresponding node information. Studies were categorized into four main groups based on content analysis. (1) Research focusing on specific technology usage by older adults includes studies by Peek et al. ( 2014 ), Ma et al. ( 2016 ), Hoque and Sorwar ( 2017 ), and Li et al. ( 2019 ), who investigated the factors influencing the use of e-technology, smartphones, mHealth, and smart wearables, respectively. (2) Concerning the development of theoretical models of technology acceptance, Chen and Chan ( 2014 ) introduced the Senior Technology Acceptance Model (STAM), and Macedo ( 2017 ) analyzed the predictive power of UTAUT2 in explaining older adults’ intentional behaviors and information technology usage. (3) In exploring older adults’ information technology adoption and behavior, Lee and Coughlin ( 2015 ) emphasized that the adoption of technology by older adults is a multifactorial process that includes performance, price, value, usability, affordability, accessibility, technical support, social support, emotion, independence, experience, and confidence. Yusif et al. ( 2016 ) conducted a literature review examining the key barriers affecting older adults’ adoption of assistive technology, including factors such as privacy, trust, functionality/added value, cost, and stigma. (4) From the perspective of research into older adults’ technology acceptance, Mitzner et al. ( 2019 ) assessed the long-term usage of computer systems designed for the elderly, whereas Guner and Acarturk ( 2020 ) compared information technology usage and acceptance between older and younger adults. The breadth and prevalence of this literature make it a vital reference for researchers in the field, also providing new perspectives and inspiration for future research directions.

Research thematic progress

Burst citation is a node of literature that guides the sudden change in dosage, which usually represents a prominent development or major change in a particular field, with innovative and forward-looking qualities. By analyzing the emergent literature, it is often easy to understand the dynamics of the subject area, mapping the emerging thematic change (Chen et al. 2022 ). Figure 6 shows the burst citation mapping in the field of older adults’ technology acceptance research, with burst citations represented by red nodes (Fig. 6A ). For the ten papers with the highest burst intensity (Fig. 6B ), this study will conduct further analysis in conjunction with literature review.

A Burst detection of co-citation. B The top 10 references with the strongest citation bursts.

As shown in Fig. 6 , Mitzner et al. ( 2010 ) broke the stereotype that older adults are fearful of technology, found that they actually have positive attitudes toward technology, and emphasized the centrality of ease of use and usefulness in the process of technology acceptance. This finding provides an important foundation for subsequent research. During the same period, Wagner et al. ( 2010 ) conducted theory-deepening and applied research on technology acceptance among older adults. The research focused on older adults’ interactions with computers from the perspective of Social Cognitive Theory (SCT). This expanded the understanding of technology acceptance, particularly regarding the relationship between behavior, environment, and other SCT elements. In addition, Pan and Jordan-Marsh ( 2010 ) extended the TAM to examine the interactions among predictors of perceived usefulness, perceived ease of use, subjective norm, and convenience conditions when older adults use the Internet, taking into account the moderating roles of gender and age. Heerink et al. ( 2010 ) adapted and extended the UTAUT, constructed a technology acceptance model specifically designed for older users’ acceptance of assistive social agents, and validated it using controlled experiments and longitudinal data, explaining intention to use by combining functional assessment and social interaction variables.

Then the research theme shifted to an in-depth analysis of the factors influencing technology acceptance among older adults. Two papers with high burst strengths emerged during this period: Peek et al. ( 2014 ) (Strength = 12.04), Chen and Chan ( 2014 ) (Strength = 9.81). Through a systematic literature review and empirical study, Peek STM and Chen K, among others, identified multidimensional factors that influence older adults’ technology acceptance. Peek et al. ( 2014 ) analyzed literature on the acceptance of in-home care technology among older adults and identified six factors that influence their acceptance: concerns about technology, expected benefits, technology needs, technology alternatives, social influences, and older adult characteristics, with a focus on differences between pre- and post-implementation factors. Chen and Chan ( 2014 ) constructed the STAM by administering a questionnaire to 1012 older adults and adding eight important factors, including technology anxiety, self-efficacy, cognitive ability, and physical function, based on the TAM. This enriches the theoretical foundation of the field. In addition, Braun ( 2013 ) highlighted the role of perceived usefulness, trust in social networks, and frequency of Internet use in older adults’ use of social networks, while ease of use and social pressure were not significant influences. These findings contribute to the study of older adults’ technology acceptance within specific technology application domains.

Recent research has focused on empirical studies of personal factors and emerging technologies. Ma et al. ( 2016 ) identified key personal factors affecting smartphone acceptance among older adults through structured questionnaires and face-to-face interviews with 120 participants. The study found that cost, self-satisfaction, and convenience were important factors influencing perceived usefulness and ease of use. This study offers empirical evidence to comprehend the main factors that drive smartphone acceptance among Chinese older adults. Additionally, Yusif et al. ( 2016 ) presented an overview of the obstacles that hinder older adults’ acceptance of assistive technologies, focusing on privacy, trust, and functionality.

In summary, research on older adults’ technology acceptance has shifted from early theoretical deepening and analysis of influencing factors to empirical studies in the areas of personal factors and emerging technologies, which have greatly enriched the theoretical basis of older adults’ technology acceptance and provided practical guidance for the design of emerging technology products.

Research hotspots, evolutionary trends, and quality distribution (RQ4)

Core keywords analysis.

Keywords concise the main idea and core of the literature, and are a refined summary of the research content (Huang et al. 2021 ). In CiteSpace, nodes with a centrality value greater than 0.1 are considered to be critical nodes. Analyzing keywords with high frequency and centrality helps to visualize the hot topics in the research field (Park et al. 2018 ). The merged keywords were imported into CiteSpace, and the top 10 keywords were counted and sorted by frequency and centrality respectively, as shown in Table 9 . The results show that the keyword “TAM” has the highest frequency (92), followed by “UTAUT” (24), which reflects that the in-depth study of the existing technology acceptance model and its theoretical expansion occupy a central position in research related to older adults’ technology acceptance. Furthermore, the terms ‘assistive technology’ and ‘virtual reality’ are both high-frequency and high-centrality terms (frequency = 17, centrality = 0.10), indicating that the research on assistive technology and virtual reality for older adults is the focus of current academic attention.

Research hotspots analysis

Using VOSviewer for keyword co-occurrence analysis organizes keywords into groups or clusters based on their intrinsic connections and frequencies, clearly highlighting the research field’s hot topics. The connectivity among keywords reveals correlations between different topics. To ensure accuracy, the analysis only considered the authors’ keywords. Subsequently, the keywords were filtered by setting the keyword frequency to 5 to obtain the keyword clustering map of the research on older adults’ technology acceptance research keyword clustering mapping (Fig. 7 ), combined with the keyword co-occurrence clustering network (Fig. 7A ) and the corresponding density situation (Fig. 7B ) to make a detailed analysis of the following four groups of clustered themes.

A Co-occurrence clustering network. B Keyword density.

Cluster #1—Research on the factors influencing technology adoption among older adults is a prominent topic, covering age, gender, self-efficacy, attitude, and and intention to use (Berkowsky et al. 2017 ; Wang et al. 2017 ). It also examined older adults’ attitudes towards and acceptance of digital health technologies (Ahmad and Mozelius, 2022 ). Moreover, the COVID-19 pandemic, significantly impacting older adults’ technology attitudes and usage, has underscored the study’s importance and urgency. Therefore, it is crucial to conduct in-depth studies on how older adults accept, adopt, and effectively use new technologies, to address their needs and help them overcome the digital divide within digital inclusion. This will improve their quality of life and healthcare experiences.

Cluster #2—Research focuses on how older adults interact with assistive technologies, especially assistive robots and health monitoring devices, emphasizing trust, usability, and user experience as crucial factors (Halim et al. 2022 ). Moreover, health monitoring technologies effectively track and manage health issues common in older adults, like dementia and mild cognitive impairment (Lussier et al. 2018 ; Piau et al. 2019 ). Interactive exercise games and virtual reality have been deployed to encourage more physical and cognitive engagement among older adults (Campo-Prieto et al. 2021 ). Personalized and innovative technology significantly enhances older adults’ participation, improving their health and well-being.

Cluster #3—Optimizing health management for older adults using mobile technology. With the development of mobile health (mHealth) and health information technology, mobile applications, smartphones, and smart wearable devices have become effective tools to help older users better manage chronic conditions, conduct real-time health monitoring, and even receive telehealth services (Dupuis and Tsotsos 2018 ; Olmedo-Aguirre et al. 2022 ; Kim et al. 2014 ). Additionally, these technologies can mitigate the problem of healthcare resource inequality, especially in developing countries. Older adults’ acceptance and use of these technologies are significantly influenced by their behavioral intentions, motivational factors, and self-management skills. These internal motivational factors, along with external factors, jointly affect older adults’ performance in health management and quality of life.

Cluster #4—Research on technology-assisted home care for older adults is gaining popularity. Environmentally assisted living enhances older adults’ independence and comfort at home, offering essential support and security. This has a crucial impact on promoting healthy aging (Friesen et al. 2016 ; Wahlroos et al. 2023 ). The smart home is a core application in this field, providing a range of solutions that facilitate independent living for the elderly in a highly integrated and user-friendly manner. This fulfills different dimensions of living and health needs (Majumder et al. 2017 ). Moreover, eHealth offers accurate and personalized health management and healthcare services for older adults (Delmastro et al. 2018 ), ensuring their needs are met at home. Research in this field often employs qualitative methods and structural equation modeling to fully understand older adults’ needs and experiences at home and analyze factors influencing technology adoption.

Evolutionary trends analysis

To gain a deeper understanding of the evolutionary trends in research hotspots within the field of older adults’ technology acceptance, we conducted a statistical analysis of the average appearance times of keywords, using CiteSpace to generate the time-zone evolution mapping (Fig. 8 ) and burst keywords. The time-zone mapping visually displays the evolution of keywords over time, intuitively reflecting the frequency and initial appearance of keywords in research, commonly used to identify trends in research topics (Jing et al. 2024a ; Kumar et al. 2021 ). Table 10 lists the top 15 keywords by burst strength, with the red sections indicating high-frequency citations and their burst strength in specific years. These burst keywords reveal the focus and trends of research themes over different periods (Kleinberg 2002 ). Combining insights from the time-zone mapping and burst keywords provides more objective and accurate research insights (Wang et al. 2023b ).

Reflecting the frequency and time of first appearance of keywords in the study.

An integrated analysis of Fig. 8 and Table 10 shows that early research on older adults’ technology acceptance primarily focused on factors such as perceived usefulness, ease of use, and attitudes towards information technology, including their use of computers and the internet (Pan and Jordan-Marsh 2010 ), as well as differences in technology use between older adults and other age groups (Guner and Acarturk 2020 ). Subsequently, the research focus expanded to improving the quality of life for older adults, exploring how technology can optimize health management and enhance the possibility of independent living, emphasizing the significant role of technology in improving the quality of life for the elderly. With ongoing technological advancements, recent research has shifted towards areas such as “virtual reality,” “telehealth,” and “human-robot interaction,” with a focus on the user experience of older adults (Halim et al. 2022 ). The appearance of keywords such as “physical activity” and “exercise” highlights the value of technology in promoting physical activity and health among older adults. This phase of research tends to make cutting-edge technology genuinely serve the practical needs of older adults, achieving its widespread application in daily life. Additionally, research has focused on expanding and quantifying theoretical models of older adults’ technology acceptance, involving keywords such as “perceived risk”, “validation” and “UTAUT”.

In summary, from 2013 to 2023, the field of older adults’ technology acceptance has evolved from initial explorations of influencing factors, to comprehensive enhancements in quality of life and health management, and further to the application and deepening of theoretical models and cutting-edge technologies. This research not only reflects the diversity and complexity of the field but also demonstrates a comprehensive and in-depth understanding of older adults’ interactions with technology across various life scenarios and needs.

Research quality distribution

To reveal the distribution of research quality in the field of older adults’ technology acceptance, a strategic diagram analysis is employed to calculate and illustrate the internal development and interrelationships among various research themes (Xie et al. 2020 ). The strategic diagram uses Centrality as the X-axis and Density as the Y-axis to divide into four quadrants, where the X-axis represents the strength of the connection between thematic clusters and other themes, with higher values indicating a central position in the research field; the Y-axis indicates the level of development within the thematic clusters, with higher values denoting a more mature and widely recognized field (Li and Zhou 2020 ).

Through cluster analysis and manual verification, this study categorized 61 core keywords (Frequency ≥5) into 11 thematic clusters. Subsequently, based on the keywords covered by each thematic cluster, the research themes and their directions for each cluster were summarized (Table 11 ), and the centrality and density coordinates for each cluster were precisely calculated (Table 12 ). Finally, a strategic diagram of the older adults’ technology acceptance research field was constructed (Fig. 9 ). Based on the distribution of thematic clusters across the quadrants in the strategic diagram, the structure and developmental trends of the field were interpreted.

Classification and visualization of theme clusters based on density and centrality.

As illustrated in Fig. 9 , (1) the theme clusters of #3 Usage Experience and #4 Assisted Living Technology are in the first quadrant, characterized by high centrality and density. Their internal cohesion and close links with other themes indicate their mature development, systematic research content or directions have been formed, and they have a significant influence on other themes. These themes play a central role in the field of older adults’ technology acceptance and have promising prospects. (2) The theme clusters of #6 Smart Devices, #9 Theoretical Models, and #10 Mobile Health Applications are in the second quadrant, with higher density but lower centrality. These themes have strong internal connections but weaker external links, indicating that these three themes have received widespread attention from researchers and have been the subject of related research, but more as self-contained systems and exhibit independence. Therefore, future research should further explore in-depth cooperation and cross-application with other themes. (3) The theme clusters of #7 Human-Robot Interaction, #8 Characteristics of the Elderly, and #11 Research Methods are in the third quadrant, with lower centrality and density. These themes are loosely connected internally and have weak links with others, indicating their developmental immaturity. Compared to other topics, they belong to the lower attention edge and niche themes, and there is a need for further investigation. (4) The theme clusters of #1 Digital Healthcare Technology, #2 Psychological Factors, and #5 Socio-Cultural Factors are located in the fourth quadrant, with high centrality but low density. Although closely associated with other research themes, the internal cohesion within these clusters is relatively weak. This suggests that while these themes are closely linked to other research areas, their own development remains underdeveloped, indicating a core immaturity. Nevertheless, these themes are crucial within the research domain of elderly technology acceptance and possess significant potential for future exploration.

Discussion on distribution power (RQ1)

Over the past decade, academic interest and influence in the area of older adults’ technology acceptance have significantly increased. This trend is evidenced by a quantitative analysis of publication and citation volumes, particularly noticeable in 2019 and 2022, where there was a substantial rise in both metrics. The rise is closely linked to the widespread adoption of emerging technologies such as smart homes, wearable devices, and telemedicine among older adults. While these technologies have enhanced their quality of life, they also pose numerous challenges, sparking extensive research into their acceptance, usage behaviors, and influencing factors among the older adults (Pirzada et al. 2022 ; Garcia Reyes et al. 2023 ). Furthermore, the COVID-19 pandemic led to a surge in technology demand among older adults, especially in areas like medical consultation, online socialization, and health management, further highlighting the importance and challenges of technology. Health risks and social isolation have compelled older adults to rely on technology for daily activities, accelerating its adoption and application within this demographic. This phenomenon has made technology acceptance a critical issue, driving societal and academic focus on the study of technology acceptance among older adults.

The flow of knowledge at the level of high-output disciplines and journals, along with the primary publishing outlets, indicates the highly interdisciplinary nature of research into older adults’ technology acceptance. This reflects the complexity and breadth of issues related to older adults’ technology acceptance, necessitating the integration of multidisciplinary knowledge and approaches. Currently, research is primarily focused on medical health and human-computer interaction, demonstrating academic interest in improving health and quality of life for older adults and addressing the urgent needs related to their interactions with technology. In the field of medical health, research aims to provide advanced and innovative healthcare technologies and services to meet the challenges of an aging population while improving the quality of life for older adults (Abdi et al. 2020 ; Wilson et al. 2021 ). In the field of human-computer interaction, research is focused on developing smarter and more user-friendly interaction models to meet the needs of older adults in the digital age, enabling them to actively participate in social activities and enjoy a higher quality of life (Sayago, 2019 ). These studies are crucial for addressing the challenges faced by aging societies, providing increased support and opportunities for the health, welfare, and social participation of older adults.

Discussion on research power (RQ2)

This study analyzes leading countries and collaboration networks, core institutions and authors, revealing the global research landscape and distribution of research strength in the field of older adults’ technology acceptance, and presents quantitative data on global research trends. From the analysis of country distribution and collaborations, China and the USA hold dominant positions in this field, with developed countries like the UK, Germany, Italy, and the Netherlands also excelling in international cooperation and research influence. The significant investment in technological research and the focus on the technological needs of older adults by many developed countries reflect their rapidly aging societies, policy support, and resource allocation.

China is the only developing country that has become a major contributor in this field, indicating its growing research capabilities and high priority given to aging societies and technological innovation. Additionally, China has close collaborations with countries such as USA, the UK, and Malaysia, driven not only by technological research needs but also by shared challenges and complementarities in aging issues among these nations. For instance, the UK has extensive experience in social welfare and aging research, providing valuable theoretical guidance and practical experience. International collaborations, aimed at addressing the challenges of aging, integrate the strengths of various countries, advancing in-depth and widespread development in the research of technology acceptance among older adults.

At the institutional and author level, City University of Hong Kong leads in publication volume, with research teams led by Chan and Chen demonstrating significant academic activity and contributions. Their research primarily focuses on older adults’ acceptance and usage behaviors of various technologies, including smartphones, smart wearables, and social robots (Chen et al. 2015 ; Li et al. 2019 ; Ma et al. 2016 ). These studies, targeting specific needs and product characteristics of older adults, have developed new models of technology acceptance based on existing frameworks, enhancing the integration of these technologies into their daily lives and laying a foundation for further advancements in the field. Although Tilburg University has a smaller publication output, it holds significant influence in the field of older adults’ technology acceptance. Particularly, the high citation rate of Peek’s studies highlights their excellence in research. Peek extensively explored older adults’ acceptance and usage of home care technologies, revealing the complexity and dynamics of their technology use behaviors. His research spans from identifying systemic influencing factors (Peek et al. 2014 ; Peek et al. 2016 ), emphasizing familial impacts (Luijkx et al. 2015 ), to constructing comprehensive models (Peek et al. 2017 ), and examining the dynamics of long-term usage (Peek et al. 2019 ), fully reflecting the evolving technology landscape and the changing needs of older adults. Additionally, the ongoing contributions of researchers like Ziefle, Rogers, and Wouters in the field of older adults’ technology acceptance demonstrate their research influence and leadership. These researchers have significantly enriched the knowledge base in this area with their diverse perspectives. For instance, Ziefle has uncovered the complex attitudes of older adults towards technology usage, especially the trade-offs between privacy and security, and how different types of activities affect their privacy needs (Maidhof et al. 2023 ; Mujirishvili et al. 2023 ; Schomakers and Ziefle 2023 ; Wilkowska et al. 2022 ), reflecting a deep exploration and ongoing innovation in the field of older adults’ technology acceptance.

Discussion on knowledge base and thematic progress (RQ3)

Through co-citation analysis and systematic review of seminal literature, this study reveals the knowledge foundation and thematic progress in the field of older adults’ technology acceptance. Co-citation networks and cluster analyses illustrate the structural themes of the research, delineating the differentiation and boundaries within this field. Additionally, burst detection analysis offers a valuable perspective for understanding the thematic evolution in the field of technology acceptance among older adults. The development and innovation of theoretical models are foundational to this research. Researchers enhance the explanatory power of constructed models by deepening and expanding existing technology acceptance theories to address theoretical limitations. For instance, Heerink et al. ( 2010 ) modified and expanded the UTAUT model by integrating functional assessment and social interaction variables to create the almere model. This model significantly enhances the ability to explain the intentions of older users in utilizing assistive social agents and improves the explanation of actual usage behaviors. Additionally, Chen and Chan ( 2014 ) extended the TAM to include age-related health and capability features of older adults, creating the STAM, which substantially improves predictions of older adults’ technology usage behaviors. Personal attributes, health and capability features, and facilitating conditions have a direct impact on technology acceptance. These factors more effectively predict older adults’ technology usage behaviors than traditional attitudinal factors.

With the advancement of technology and the application of emerging technologies, new research topics have emerged, increasingly focusing on older adults’ acceptance and use of these technologies. Prior to this, the study by Mitzner et al. ( 2010 ) challenged the stereotype of older adults’ conservative attitudes towards technology, highlighting the central roles of usability and usefulness in the technology acceptance process. This discovery laid an important foundation for subsequent research. Research fields such as “smart home technology,” “social life,” and “customer service” are emerging, indicating a shift in focus towards the practical and social applications of technology in older adults’ lives. Research not only focuses on the technology itself but also on how these technologies integrate into older adults’ daily lives and how they can improve the quality of life through technology. For instance, studies such as those by Ma et al. ( 2016 ), Hoque and Sorwar ( 2017 ), and Li et al. ( 2019 ) have explored factors influencing older adults’ use of smartphones, mHealth, and smart wearable devices.

Furthermore, the diversification of research methodologies and innovation in evaluation techniques, such as the use of mixed methods, structural equation modeling (SEM), and neural network (NN) approaches, have enhanced the rigor and reliability of the findings, enabling more precise identification of the factors and mechanisms influencing technology acceptance. Talukder et al. ( 2020 ) employed an effective multimethodological strategy by integrating SEM and NN to leverage the complementary strengths of both approaches, thus overcoming their individual limitations and more accurately analyzing and predicting older adults’ acceptance of wearable health technologies (WHT). SEM is utilized to assess the determinants’ impact on the adoption of WHT, while neural network models validate SEM outcomes and predict the significance of key determinants. This combined approach not only boosts the models’ reliability and explanatory power but also provides a nuanced understanding of the motivations and barriers behind older adults’ acceptance of WHT, offering deep research insights.

Overall, co-citation analysis of the literature in the field of older adults’ technology acceptance has uncovered deeper theoretical modeling and empirical studies on emerging technologies, while emphasizing the importance of research methodological and evaluation innovations in understanding complex social science issues. These findings are crucial for guiding the design and marketing strategies of future technology products, especially in the rapidly growing market of older adults.

Discussion on research hotspots and evolutionary trends (RQ4)

By analyzing core keywords, we can gain deep insights into the hot topics, evolutionary trends, and quality distribution of research in the field of older adults’ technology acceptance. The frequent occurrence of the keywords “TAM” and “UTAUT” indicates that the applicability and theoretical extension of existing technology acceptance models among older adults remain a focal point in academia. This phenomenon underscores the enduring influence of the studies by Davis ( 1989 ) and Venkatesh et al. ( 2003 ), whose models provide a robust theoretical framework for explaining and predicting older adults’ acceptance and usage of emerging technologies. With the widespread application of artificial intelligence (AI) and big data technologies, these theoretical models have incorporated new variables such as perceived risk, trust, and privacy issues (Amin et al. 2024 ; Chen et al. 2024 ; Jing et al. 2024b ; Seibert et al. 2021 ; Wang et al. 2024b ), advancing the theoretical depth and empirical research in this field.

Keyword co-occurrence cluster analysis has revealed multiple research hotspots in the field, including factors influencing technology adoption, interactive experiences between older adults and assistive technologies, the application of mobile health technology in health management, and technology-assisted home care. These studies primarily focus on enhancing the quality of life and health management of older adults through emerging technologies, particularly in the areas of ambient assisted living, smart health monitoring, and intelligent medical care. In these domains, the role of AI technology is increasingly significant (Qian et al. 2021 ; Ho 2020 ). With the evolution of next-generation information technologies, AI is increasingly integrated into elder care systems, offering intelligent, efficient, and personalized service solutions by analyzing the lifestyles and health conditions of older adults. This integration aims to enhance older adults’ quality of life in aspects such as health monitoring and alerts, rehabilitation assistance, daily health management, and emotional support (Lee et al. 2023 ). A survey indicates that 83% of older adults prefer AI-driven solutions when selecting smart products, demonstrating the increasing acceptance of AI in elder care (Zhao and Li 2024 ). Integrating AI into elder care presents both opportunities and challenges, particularly in terms of user acceptance, trust, and long-term usage effects, which warrant further exploration (Mhlanga 2023 ). These studies will help better understand the profound impact of AI technology on the lifestyles of older adults and provide critical references for optimizing AI-driven elder care services.

The Time-zone evolution mapping and burst keyword analysis further reveal the evolutionary trends of research hotspots. Early studies focused on basic technology acceptance models and user perceptions, later expanding to include quality of life and health management. In recent years, research has increasingly focused on cutting-edge technologies such as virtual reality, telehealth, and human-robot interaction, with a concurrent emphasis on the user experience of older adults. This evolutionary process demonstrates a deepening shift from theoretical models to practical applications, underscoring the significant role of technology in enhancing the quality of life for older adults. Furthermore, the strategic coordinate mapping analysis clearly demonstrates the development and mutual influence of different research themes. High centrality and density in the themes of Usage Experience and Assisted Living Technology indicate their mature research status and significant impact on other themes. The themes of Smart Devices, Theoretical Models, and Mobile Health Applications demonstrate self-contained research trends. The themes of Human-Robot Interaction, Characteristics of the Elderly, and Research Methods are not yet mature, but they hold potential for development. Themes of Digital Healthcare Technology, Psychological Factors, and Socio-Cultural Factors are closely related to other themes, displaying core immaturity but significant potential.

In summary, the research hotspots in the field of older adults’ technology acceptance are diverse and dynamic, demonstrating the academic community’s profound understanding of how older adults interact with technology across various life contexts and needs. Under the influence of AI and big data, research should continue to focus on the application of emerging technologies among older adults, exploring in depth how they adapt to and effectively use these technologies. This not only enhances the quality of life and healthcare experiences for older adults but also drives ongoing innovation and development in this field.

Research agenda

Based on the above research findings, to further understand and promote technology acceptance and usage among older adults, we recommend future studies focus on refining theoretical models, exploring long-term usage, and assessing user experience in the following detailed aspects:

Refinement and validation of specific technology acceptance models for older adults: Future research should focus on developing and validating technology acceptance models based on individual characteristics, particularly considering variations in technology acceptance among older adults across different educational levels and cultural backgrounds. This includes factors such as age, gender, educational background, and cultural differences. Additionally, research should examine how well specific technologies, such as wearable devices and mobile health applications, meet the needs of older adults. Building on existing theoretical models, this research should integrate insights from multiple disciplines such as psychology, sociology, design, and engineering through interdisciplinary collaboration to create more accurate and comprehensive models, which should then be validated in relevant contexts.

Deepening the exploration of the relationship between long-term technology use and quality of life among older adults: The acceptance and use of technology by users is a complex and dynamic process (Seuwou et al. 2016 ). Existing research predominantly focuses on older adults’ initial acceptance or short-term use of new technologies; however, the impact of long-term use on their quality of life and health is more significant. Future research should focus on the evolution of older adults’ experiences and needs during long-term technology usage, and the enduring effects of technology on their social interactions, mental health, and life satisfaction. Through longitudinal studies and qualitative analysis, this research reveals the specific needs and challenges of older adults in long-term technology use, providing a basis for developing technologies and strategies that better meet their requirements. This understanding aids in comprehensively assessing the impact of technology on older adults’ quality of life and guiding the optimization and improvement of technological products.

Evaluating the Importance of User Experience in Research on Older Adults’ Technology Acceptance: Understanding the mechanisms of information technology acceptance and use is central to human-computer interaction research. Although technology acceptance models and user experience models differ in objectives, they share many potential intersections. Technology acceptance research focuses on structured prediction and assessment, while user experience research concentrates on interpreting design impacts and new frameworks. Integrating user experience to assess older adults’ acceptance of technology products and systems is crucial (Codfrey et al. 2022 ; Wang et al. 2019 ), particularly for older users, where specific product designs should emphasize practicality and usability (Fisk et al. 2020 ). Researchers need to explore innovative age-appropriate design methods to enhance older adults’ usage experience. This includes studying older users’ actual usage preferences and behaviors, optimizing user interfaces, and interaction designs. Integrating feedback from older adults to tailor products to their needs can further promote their acceptance and continued use of technology products.

Conclusions

This study conducted a systematic review of the literature on older adults’ technology acceptance over the past decade through bibliometric analysis, focusing on the distribution power, research power, knowledge base and theme progress, research hotspots, evolutionary trends, and quality distribution. Using a combination of quantitative and qualitative methods, this study has reached the following conclusions:

Technology acceptance among older adults has become a hot topic in the international academic community, involving the integration of knowledge across multiple disciplines, including Medical Informatics, Health Care Sciences Services, and Ergonomics. In terms of journals, “PSYCHOLOGY, EDUCATION, HEALTH” represents a leading field, with key publications including Computers in Human Behavior , Journal of Medical Internet Research , and International Journal of Human-Computer Interaction . These journals possess significant academic authority and extensive influence in the field.

Research on technology acceptance among older adults is particularly active in developed countries, with China and USA publishing significantly more than other nations. The Netherlands leads in high average citation rates, indicating the depth and impact of its research. Meanwhile, the UK stands out in terms of international collaboration. At the institutional level, City University of Hong Kong and The University of Hong Kong in China are in leading positions. Tilburg University in the Netherlands demonstrates exceptional research quality through its high average citation count. At the author level, Chen from China has the highest number of publications, while Peek from the Netherlands has the highest average citation count.

Co-citation analysis of references indicates that the knowledge base in this field is divided into three main categories: theoretical model deepening, emerging technology applications, and research methods and evaluation. Seminal literature focuses on four areas: specific technology use by older adults, expansion of theoretical models of technology acceptance, information technology adoption behavior, and research perspectives. Research themes have evolved from initial theoretical deepening and analysis of influencing factors to empirical studies on individual factors and emerging technologies.

Keyword analysis indicates that TAM and UTAUT are the most frequently occurring terms, while “assistive technology” and “virtual reality” are focal points with high frequency and centrality. Keyword clustering analysis reveals that research hotspots are concentrated on the influencing factors of technology adoption, human-robot interaction experiences, mobile health management, and technology for aging in place. Time-zone evolution mapping and burst keyword analysis have revealed the research evolution from preliminary exploration of influencing factors, to enhancements in quality of life and health management, and onto advanced technology applications and deepening of theoretical models. Furthermore, analysis of research quality distribution indicates that Usage Experience and Assisted Living Technology have become core topics, while Smart Devices, Theoretical Models, and Mobile Health Applications point towards future research directions.

Through this study, we have systematically reviewed the dynamics, core issues, and evolutionary trends in the field of older adults’ technology acceptance, constructing a comprehensive Knowledge Mapping of the domain and presenting a clear framework of existing research. This not only lays the foundation for subsequent theoretical discussions and innovative applications in the field but also provides an important reference for relevant scholars.

Limitations

To our knowledge, this is the first bibliometric analysis concerning technology acceptance among older adults, and we adhered strictly to bibliometric standards throughout our research. However, this study relies on the Web of Science Core Collection, and while its authority and breadth are widely recognized, this choice may have missed relevant literature published in other significant databases such as PubMed, Scopus, and Google Scholar, potentially overlooking some critical academic contributions. Moreover, given that our analysis was confined to literature in English, it may not reflect studies published in other languages, somewhat limiting the global representativeness of our data sample.

It is noteworthy that with the rapid development of AI technology, its increasingly widespread application in elderly care services is significantly transforming traditional care models. AI is profoundly altering the lifestyles of the elderly, from health monitoring and smart diagnostics to intelligent home systems and personalized care, significantly enhancing their quality of life and health care standards. The potential for AI technology within the elderly population is immense, and research in this area is rapidly expanding. However, due to the restrictive nature of the search terms used in this study, it did not fully cover research in this critical area, particularly in addressing key issues such as trust, privacy, and ethics.

Consequently, future research should not only expand data sources, incorporating multilingual and multidatabase literature, but also particularly focus on exploring older adults’ acceptance of AI technology and its applications, in order to construct a more comprehensive academic landscape of older adults’ technology acceptance, thereby enriching and extending the knowledge system and academic trends in this field.

Data availability

The datasets analyzed during the current study are available in the Dataverse repository: https://doi.org/10.7910/DVN/6K0GJH .

Abdi S, de Witte L, Hawley M (2020) Emerging technologies with potential care and support applications for older people: review of gray literature. JMIR Aging 3(2):e17286. https://doi.org/10.2196/17286

Article   PubMed   PubMed Central   Google Scholar  

Achuthan K, Nair VK, Kowalski R, Ramanathan S, Raman R (2023) Cyberbullying research—Alignment to sustainable development and impact of COVID-19: Bibliometrics and science mapping analysis. Comput Human Behav 140:107566. https://doi.org/10.1016/j.chb.2022.107566

Article   Google Scholar  

Ahmad A, Mozelius P (2022) Human-Computer Interaction for Older Adults: a Literature Review on Technology Acceptance of eHealth Systems. J Eng Res Sci 1(4):119–126. https://doi.org/10.55708/js0104014

Ale Ebrahim N, Salehi H, Embi MA, Habibi F, Gholizadeh H, Motahar SM (2014) Visibility and citation impact. Int Educ Stud 7(4):120–125. https://doi.org/10.5539/ies.v7n4p120

Amin MS, Johnson VL, Prybutok V, Koh CE (2024) An investigation into factors affecting the willingness to disclose personal health information when using AI-enabled caregiver robots. Ind Manag Data Syst 124(4):1677–1699. https://doi.org/10.1108/IMDS-09-2023-0608

Baer NR, Vietzke J, Schenk L (2022) Middle-aged and older adults’ acceptance of mobile nutrition and fitness apps: a systematic mixed studies review. PLoS One 17(12):e0278879. https://doi.org/10.1371/journal.pone.0278879

Barnard Y, Bradley MD, Hodgson F, Lloyd AD (2013) Learning to use new technologies by older adults: Perceived difficulties, experimentation behaviour and usability. Comput Human Behav 29(4):1715–1724. https://doi.org/10.1016/j.chb.2013.02.006

Berkowsky RW, Sharit J, Czaja SJ (2017) Factors predicting decisions about technology adoption among older adults. Innov Aging 3(1):igy002. https://doi.org/10.1093/geroni/igy002

Braun MT (2013) Obstacles to social networking website use among older adults. Comput Human Behav 29(3):673–680. https://doi.org/10.1016/j.chb.2012.12.004

Article   MathSciNet   Google Scholar  

Campo-Prieto P, Rodríguez-Fuentes G, Cancela-Carral JM (2021) Immersive virtual reality exergame promotes the practice of physical activity in older people: An opportunity during COVID-19. Multimodal Technol Interact 5(9):52. https://doi.org/10.3390/mti5090052

Chen C (2006) CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. J Am Soc Inf Sci Technol 57(3):359–377. https://doi.org/10.1002/asi.20317

Chen C, Dubin R, Kim MC (2014) Emerging trends and new developments in regenerative medicine: a scientometric update (2000–2014). Expert Opin Biol Ther 14(9):1295–1317. https://doi.org/10.1517/14712598.2014.920813

Article   PubMed   Google Scholar  

Chen C, Leydesdorff L (2014) Patterns of connections and movements in dual‐map overlays: A new method of publication portfolio analysis. J Assoc Inf Sci Technol 65(2):334–351. https://doi.org/10.1002/asi.22968

Chen J, Wang C, Tang Y (2022) Knowledge mapping of volunteer motivation: A bibliometric analysis and cross-cultural comparative study. Front Psychol 13:883150. https://doi.org/10.3389/fpsyg.2022.883150

Chen JY, Liu YD, Dai J, Wang CL (2023) Development and status of moral education research: Visual analysis based on knowledge graph. Front Psychol 13:1079955. https://doi.org/10.3389/fpsyg.2022.1079955

Chen K, Chan AH (2011) A review of technology acceptance by older adults. Gerontechnology 10(1):1–12. https://doi.org/10.4017/gt.2011.10.01.006.00

Chen K, Chan AH (2014) Gerontechnology acceptance by elderly Hong Kong Chinese: a senior technology acceptance model (STAM). Ergonomics 57(5):635–652. https://doi.org/10.1080/00140139.2014.895855

Chen K, Zhang Y, Fu X (2019) International research collaboration: An emerging domain of innovation studies? Res Policy 48(1):149–168. https://doi.org/10.1016/j.respol.2018.08.005

Chen X, Hu Z, Wang C (2024) Empowering education development through AIGC: A systematic literature review. Educ Inf Technol 1–53. https://doi.org/10.1007/s10639-024-12549-7

Chen Y, Chen CM, Liu ZY, Hu ZG, Wang XW (2015) The methodology function of CiteSpace mapping knowledge domains. Stud Sci Sci 33(2):242–253. https://doi.org/10.16192/j.cnki.1003-2053.2015.02.009

Codfrey GS, Baharum A, Zain NHM, Omar M, Deris FD (2022) User Experience in Product Design and Development: Perspectives and Strategies. Math Stat Eng Appl 71(2):257–262. https://doi.org/10.17762/msea.v71i2.83

Dai J, Zhang X, Wang CL (2024) A meta-analysis of learners’ continuance intention toward online education platforms. Educ Inf Technol 1–36. https://doi.org/10.1007/s10639-024-12654-7

Davis FD (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q 13(3):319–340. https://doi.org/10.2307/249008

Delmastro F, Dolciotti C, Palumbo F, Magrini M, Di Martino F, La Rosa D, Barcaro U (2018) Long-term care: how to improve the quality of life with mobile and e-health services. In 2018 14th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), pp. 12–19. IEEE. https://doi.org/10.1109/WiMOB.2018.8589157

Dupuis K, Tsotsos LE (2018) Technology for remote health monitoring in an older population: a role for mobile devices. Multimodal Technol Interact 2(3):43. https://doi.org/10.3390/mti2030043

Ferguson C, Hickman LD, Turkmani S, Breen P, Gargiulo G, Inglis SC (2021) Wearables only work on patients that wear them”: Barriers and facilitators to the adoption of wearable cardiac monitoring technologies. Cardiovasc Digit Health J 2(2):137–147. https://doi.org/10.1016/j.cvdhj.2021.02.001

Fisk AD, Czaja SJ, Rogers WA, Charness N, Sharit J (2020) Designing for older adults: Principles and creative human factors approaches. CRC Press. https://doi.org/10.1201/9781420080681

Friesen S, Brémault-Phillips S, Rudrum L, Rogers LG (2016) Environmental design that supports healthy aging: Evaluating a new supportive living facility. J Hous Elderly 30(1):18–34. https://doi.org/10.1080/02763893.2015.1129380

Garcia Reyes EP, Kelly R, Buchanan G, Waycott J (2023) Understanding Older Adults’ Experiences With Technologies for Health Self-management: Interview Study. JMIR Aging 6:e43197. https://doi.org/10.2196/43197

Geng Z, Wang J, Liu J, Miao J (2024) Bibliometric analysis of the development, current status, and trends in adult degenerative scoliosis research: A systematic review from 1998 to 2023. J Pain Res 17:153–169. https://doi.org/10.2147/JPR.S437575

González A, Ramírez MP, Viadel V (2012) Attitudes of the elderly toward information and communications technologies. Educ Gerontol 38(9):585–594. https://doi.org/10.1080/03601277.2011.595314

Guner H, Acarturk C (2020) The use and acceptance of ICT by senior citizens: a comparison of technology acceptance model (TAM) for elderly and young adults. Univ Access Inf Soc 19(2):311–330. https://doi.org/10.1007/s10209-018-0642-4

Halim I, Saptari A, Perumal PA, Abdullah Z, Abdullah S, Muhammad MN (2022) A Review on Usability and User Experience of Assistive Social Robots for Older Persons. Int J Integr Eng 14(6):102–124. https://penerbit.uthm.edu.my/ojs/index.php/ijie/article/view/8566

He Y, He Q, Liu Q (2022) Technology acceptance in socially assistive robots: Scoping review of models, measurement, and influencing factors. J Healthc Eng 2022(1):6334732. https://doi.org/10.1155/2022/6334732

Heerink M, Kröse B, Evers V, Wielinga B (2010) Assessing acceptance of assistive social agent technology by older adults: the almere model. Int J Soc Robot 2:361–375. https://doi.org/10.1007/s12369-010-0068-5

Ho A (2020) Are we ready for artificial intelligence health monitoring in elder care? BMC Geriatr 20(1):358. https://doi.org/10.1186/s12877-020-01764-9

Hoque R, Sorwar G (2017) Understanding factors influencing the adoption of mHealth by the elderly: An extension of the UTAUT model. Int J Med Inform 101:75–84. https://doi.org/10.1016/j.ijmedinf.2017.02.002

Hota PK, Subramanian B, Narayanamurthy G (2020) Mapping the intellectual structure of social entrepreneurship research: A citation/co-citation analysis. J Bus Ethics 166(1):89–114. https://doi.org/10.1007/s10551-019-04129-4

Huang R, Yan P, Yang X (2021) Knowledge map visualization of technology hotspots and development trends in China’s textile manufacturing industry. IET Collab Intell Manuf 3(3):243–251. https://doi.org/10.1049/cim2.12024

Article   ADS   Google Scholar  

Jing Y, Wang C, Chen Y, Wang H, Yu T, Shadiev R (2023) Bibliometric mapping techniques in educational technology research: A systematic literature review. Educ Inf Technol 1–29. https://doi.org/10.1007/s10639-023-12178-6

Jing YH, Wang CL, Chen ZY, Shen SS, Shadiev R (2024a) A Bibliometric Analysis of Studies on Technology-Supported Learning Environments: Hotopics and Frontier Evolution. J Comput Assist Learn 1–16. https://doi.org/10.1111/jcal.12934

Jing YH, Wang HM, Chen XJ, Wang CL (2024b) What factors will affect the effectiveness of using ChatGPT to solve programming problems? A quasi-experimental study. Humanit Soc Sci Commun 11:319. https://doi.org/10.1057/s41599-024-02751-w

Kamrani P, Dorsch I, Stock WG (2021) Do researchers know what the h-index is? And how do they estimate its importance? Scientometrics 126(7):5489–5508. https://doi.org/10.1007/s11192-021-03968-1

Kim HS, Lee KH, Kim H, Kim JH (2014) Using mobile phones in healthcare management for the elderly. Maturitas 79(4):381–388. https://doi.org/10.1016/j.maturitas.2014.08.013

Article   MathSciNet   PubMed   Google Scholar  

Kleinberg J (2002) Bursty and hierarchical structure in streams. In Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 91–101. https://doi.org/10.1145/775047.775061

Kruse C, Fohn J, Wilson N, Patlan EN, Zipp S, Mileski M (2020) Utilization barriers and medical outcomes commensurate with the use of telehealth among older adults: systematic review. JMIR Med Inform 8(8):e20359. https://doi.org/10.2196/20359

Kumar S, Lim WM, Pandey N, Christopher Westland J (2021) 20 years of electronic commerce research. Electron Commer Res 21:1–40. https://doi.org/10.1007/s10660-021-09464-1

Kwiek M (2021) What large-scale publication and citation data tell us about international research collaboration in Europe: Changing national patterns in global contexts. Stud High Educ 46(12):2629–2649. https://doi.org/10.1080/03075079.2020.1749254

Lee C, Coughlin JF (2015) PERSPECTIVE: Older adults’ adoption of technology: an integrated approach to identifying determinants and barriers. J Prod Innov Manag 32(5):747–759. https://doi.org/10.1111/jpim.12176

Lee CH, Wang C, Fan X, Li F, Chen CH (2023) Artificial intelligence-enabled digital transformation in elderly healthcare field: scoping review. Adv Eng Inform 55:101874. https://doi.org/10.1016/j.aei.2023.101874

Leydesdorff L, Rafols I (2012) Interactive overlays: A new method for generating global journal maps from Web-of-Science data. J Informetr 6(2):318–332. https://doi.org/10.1016/j.joi.2011.11.003

Li J, Ma Q, Chan AH, Man S (2019) Health monitoring through wearable technologies for older adults: Smart wearables acceptance model. Appl Ergon 75:162–169. https://doi.org/10.1016/j.apergo.2018.10.006

Article   ADS   PubMed   Google Scholar  

Li X, Zhou D (2020) Product design requirement information visualization approach for intelligent manufacturing services. China Mech Eng 31(07):871, http://www.cmemo.org.cn/EN/Y2020/V31/I07/871

Google Scholar  

Lin Y, Yu Z (2024a) An integrated bibliometric analysis and systematic review modelling students’ technostress in higher education. Behav Inf Technol 1–25. https://doi.org/10.1080/0144929X.2024.2332458

Lin Y, Yu Z (2024b) A bibliometric analysis of artificial intelligence chatbots in educational contexts. Interact Technol Smart Educ 21(2):189–213. https://doi.org/10.1108/ITSE-12-2022-0165

Liu L, Duffy VG (2023) Exploring the future development of Artificial Intelligence (AI) applications in chatbots: a bibliometric analysis. Int J Soc Robot 15(5):703–716. https://doi.org/10.1007/s12369-022-00956-0

Liu R, Li X, Chu J (2022) Evolution of applied variables in the research on technology acceptance of the elderly. In: International Conference on Human-Computer Interaction, Cham: Springer International Publishing, pp 500–520. https://doi.org/10.1007/978-3-031-05581-23_5

Luijkx K, Peek S, Wouters E (2015) “Grandma, you should do it—It’s cool” Older Adults and the Role of Family Members in Their Acceptance of Technology. Int J Environ Res Public Health 12(12):15470–15485. https://doi.org/10.3390/ijerph121214999

Lussier M, Lavoie M, Giroux S, Consel C, Guay M, Macoir J, Bier N (2018) Early detection of mild cognitive impairment with in-home monitoring sensor technologies using functional measures: a systematic review. IEEE J Biomed Health Inform 23(2):838–847. https://doi.org/10.1109/JBHI.2018.2834317

López-Robles JR, Otegi-Olaso JR, Porto Gomez I, Gamboa-Rosales NK, Gamboa-Rosales H, Robles-Berumen H (2018) Bibliometric network analysis to identify the intellectual structure and evolution of the big data research field. In: International Conference on Intelligent Data Engineering and Automated Learning, Cham: Springer International Publishing, pp 113–120. https://doi.org/10.1007/978-3-030-03496-2_13

Ma Q, Chan AH, Chen K (2016) Personal and other factors affecting acceptance of smartphone technology by older Chinese adults. Appl Ergon 54:62–71. https://doi.org/10.1016/j.apergo.2015.11.015

Ma Q, Chan AHS, Teh PL (2021) Insights into Older Adults’ Technology Acceptance through Meta-Analysis. Int J Hum-Comput Interact 37(11):1049–1062. https://doi.org/10.1080/10447318.2020.1865005

Macedo IM (2017) Predicting the acceptance and use of information and communication technology by older adults: An empirical examination of the revised UTAUT2. Comput Human Behav 75:935–948. https://doi.org/10.1016/j.chb.2017.06.013

Maidhof C, Offermann J, Ziefle M (2023) Eyes on privacy: acceptance of video-based AAL impacted by activities being filmed. Front Public Health 11:1186944. https://doi.org/10.3389/fpubh.2023.1186944

Majumder S, Aghayi E, Noferesti M, Memarzadeh-Tehran H, Mondal T, Pang Z, Deen MJ (2017) Smart homes for elderly healthcare—Recent advances and research challenges. Sensors 17(11):2496. https://doi.org/10.3390/s17112496

Article   ADS   PubMed   PubMed Central   Google Scholar  

Mhlanga D (2023) Artificial Intelligence in elderly care: Navigating ethical and responsible AI adoption for seniors. Available at SSRN 4675564. 4675564 min) Identifying citation patterns of scientific breakthroughs: A perspective of dynamic citation process. Inf Process Manag 58(1):102428. https://doi.org/10.1016/j.ipm.2020.102428

Mitzner TL, Boron JB, Fausset CB, Adams AE, Charness N, Czaja SJ, Sharit J (2010) Older adults talk technology: Technology usage and attitudes. Comput Human Behav 26(6):1710–1721. https://doi.org/10.1016/j.chb.2010.06.020

Mitzner TL, Savla J, Boot WR, Sharit J, Charness N, Czaja SJ, Rogers WA (2019) Technology adoption by older adults: Findings from the PRISM trial. Gerontologist 59(1):34–44. https://doi.org/10.1093/geront/gny113

Mongeon P, Paul-Hus A (2016) The journal coverage of Web of Science and Scopus: a comparative analysis. Scientometrics 106:213–228. https://doi.org/10.1007/s11192-015-1765-5

Mostaghel R (2016) Innovation and technology for the elderly: Systematic literature review. J Bus Res 69(11):4896–4900. https://doi.org/10.1016/j.jbusres.2016.04.049

Mujirishvili T, Maidhof C, Florez-Revuelta F, Ziefle M, Richart-Martinez M, Cabrero-García J (2023) Acceptance and privacy perceptions toward video-based active and assisted living technologies: Scoping review. J Med Internet Res 25:e45297. https://doi.org/10.2196/45297

Naseri RNN, Azis SN, Abas N (2023) A Review of Technology Acceptance and Adoption Models in Consumer Study. FIRM J Manage Stud 8(2):188–199. https://doi.org/10.33021/firm.v8i2.4536

Nguyen UP, Hallinger P (2020) Assessing the distinctive contributions of Simulation & Gaming to the literature, 1970–2019: A bibliometric review. Simul Gaming 51(6):744–769. https://doi.org/10.1177/1046878120941569

Olmedo-Aguirre JO, Reyes-Campos J, Alor-Hernández G, Machorro-Cano I, Rodríguez-Mazahua L, Sánchez-Cervantes JL (2022) Remote healthcare for elderly people using wearables: A review. Biosensors 12(2):73. https://doi.org/10.3390/bios12020073

Pan S, Jordan-Marsh M (2010) Internet use intention and adoption among Chinese older adults: From the expanded technology acceptance model perspective. Comput Human Behav 26(5):1111–1119. https://doi.org/10.1016/j.chb.2010.03.015

Pan X, Yan E, Cui M, Hua W (2018) Examining the usage, citation, and diffusion patterns of bibliometric map software: A comparative study of three tools. J Informetr 12(2):481–493. https://doi.org/10.1016/j.joi.2018.03.005

Park JS, Kim NR, Han EJ (2018) Analysis of trends in science and technology using keyword network analysis. J Korea Ind Inf Syst Res 23(2):63–73. https://doi.org/10.9723/jksiis.2018.23.2.063

Peek ST, Luijkx KG, Rijnaard MD, Nieboer ME, Van Der Voort CS, Aarts S, Wouters EJ (2016) Older adults’ reasons for using technology while aging in place. Gerontology 62(2):226–237. https://doi.org/10.1159/000430949

Peek ST, Luijkx KG, Vrijhoef HJ, Nieboer ME, Aarts S, van der Voort CS, Wouters EJ (2017) Origins and consequences of technology acquirement by independent-living seniors: Towards an integrative model. BMC Geriatr 17:1–18. https://doi.org/10.1186/s12877-017-0582-5

Peek ST, Wouters EJ, Van Hoof J, Luijkx KG, Boeije HR, Vrijhoef HJ (2014) Factors influencing acceptance of technology for aging in place: a systematic review. Int J Med Inform 83(4):235–248. https://doi.org/10.1016/j.ijmedinf.2014.01.004

Peek STM, Luijkx KG, Vrijhoef HJM, Nieboer ME, Aarts S, Van Der Voort CS, Wouters EJM (2019) Understanding changes and stability in the long-term use of technologies by seniors who are aging in place: a dynamical framework. BMC Geriatr 19:1–13. https://doi.org/10.1186/s12877-019-1241-9

Perez AJ, Siddiqui F, Zeadally S, Lane D (2023) A review of IoT systems to enable independence for the elderly and disabled individuals. Internet Things 21:100653. https://doi.org/10.1016/j.iot.2022.100653

Piau A, Wild K, Mattek N, Kaye J (2019) Current state of digital biomarker technologies for real-life, home-based monitoring of cognitive function for mild cognitive impairment to mild Alzheimer disease and implications for clinical care: systematic review. J Med Internet Res 21(8):e12785. https://doi.org/10.2196/12785

Pirzada P, Wilde A, Doherty GH, Harris-Birtill D (2022) Ethics and acceptance of smart homes for older adults. Inform Health Soc Care 47(1):10–37. https://doi.org/10.1080/17538157.2021.1923500

Pranckutė R (2021) Web of Science (WoS) and Scopus: The titans of bibliographic information in today’s academic world. Publications 9(1):12. https://doi.org/10.3390/publications9010012

Qian K, Zhang Z, Yamamoto Y, Schuller BW (2021) Artificial intelligence internet of things for the elderly: From assisted living to health-care monitoring. IEEE Signal Process Mag 38(4):78–88. https://doi.org/10.1109/MSP.2021.3057298

Redner S (1998) How popular is your paper? An empirical study of the citation distribution. Eur Phys J B-Condens Matter Complex Syst 4(2):131–134. https://doi.org/10.1007/s100510050359

Sayago S (ed.) (2019) Perspectives on human-computer interaction research with older people. Switzerland: Springer International Publishing. https://doi.org/10.1007/978-3-030-06076-3

Schomakers EM, Ziefle M (2023) Privacy vs. security: trade-offs in the acceptance of smart technologies for aging-in-place. Int J Hum Comput Interact 39(5):1043–1058. https://doi.org/10.1080/10447318.2022.2078463

Schroeder T, Dodds L, Georgiou A, Gewald H, Siette J (2023) Older adults and new technology: Mapping review of the factors associated with older adults’ intention to adopt digital technologies. JMIR Aging 6(1):e44564. https://doi.org/10.2196/44564

Seibert K, Domhoff D, Bruch D, Schulte-Althoff M, Fürstenau D, Biessmann F, Wolf-Ostermann K (2021) Application scenarios for artificial intelligence in nursing care: rapid review. J Med Internet Res 23(11):e26522. https://doi.org/10.2196/26522

Seuwou P, Banissi E, Ubakanma G (2016) User acceptance of information technology: A critical review of technology acceptance models and the decision to invest in Information Security. In: Global Security, Safety and Sustainability-The Security Challenges of the Connected World: 11th International Conference, ICGS3 2017, London, UK, January 18-20, 2017, Proceedings 11:230-251. Springer International Publishing. https://doi.org/10.1007/978-3-319-51064-4_19

Shiau WL, Wang X, Zheng F (2023) What are the trend and core knowledge of information security? A citation and co-citation analysis. Inf Manag 60(3):103774. https://doi.org/10.1016/j.im.2023.103774

Sinha S, Verma A, Tiwari P (2021) Technology: Saving and enriching life during COVID-19. Front Psychol 12:647681. https://doi.org/10.3389/fpsyg.2021.647681

Soar J (2010) The potential of information and communication technologies to support ageing and independent living. Ann Telecommun 65:479–483. https://doi.org/10.1007/s12243-010-0167-1

Strotmann A, Zhao D (2012) Author name disambiguation: What difference does it make in author‐based citation analysis? J Am Soc Inf Sci Technol 63(9):1820–1833. https://doi.org/10.1002/asi.22695

Talukder MS, Sorwar G, Bao Y, Ahmed JU, Palash MAS (2020) Predicting antecedents of wearable healthcare technology acceptance by elderly: A combined SEM-Neural Network approach. Technol Forecast Soc Change 150:119793. https://doi.org/10.1016/j.techfore.2019.119793

Taskin Z, Al U (2019) Natural language processing applications in library and information science. Online Inf Rev 43(4):676–690. https://doi.org/10.1108/oir-07-2018-0217

Touqeer H, Zaman S, Amin R, Hussain M, Al-Turjman F, Bilal M (2021) Smart home security: challenges, issues and solutions at different IoT layers. J Supercomput 77(12):14053–14089. https://doi.org/10.1007/s11227-021-03825-1

United Nations Department of Economic and Social Affairs (2023) World population ageing 2023: Highlights. https://www.un.org/zh/193220

Valk CAL, Lu Y, Randriambelonoro M, Jessen J (2018) Designing for technology acceptance of wearable and mobile technologies for senior citizen users. In: 21st DMI: Academic Design Management Conference (ADMC 2018), Design Management Institute, pp 1361–1373. https://www.dmi.org/page/ADMC2018

Van Eck N, Waltman L (2010) Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 84(2):523–538. https://doi.org/10.1007/s11192-009-0146-3

Vancea M, Solé-Casals J (2016) Population aging in the European Information Societies: towards a comprehensive research agenda in eHealth innovations for elderly. Aging Dis 7(4):526. https://doi.org/10.14336/AD.2015.1214

Venkatesh V, Morris MG, Davis GB, Davis FD (2003) User acceptance of information technology: Toward a unified view. MIS Q 27(3):425–478. https://doi.org/10.2307/30036540

Wagner N, Hassanein K, Head M (2010) Computer use by older adults: A multi-disciplinary review. Comput Human Behav 26(5):870–882. https://doi.org/10.1016/j.chb.2010.03.029

Wahlroos N, Narsakka N, Stolt M, Suhonen R (2023) Physical environment maintaining independence and self-management of older people in long-term care settings—An integrative literature review. J Aging Environ 37(3):295–313. https://doi.org/10.1080/26892618.2022.2092927

Wang CL, Chen XJ, Yu T, Liu YD, Jing YH (2024a) Education reform and change driven by digital technology: a bibliometric study from a global perspective. Humanit Soc Sci Commun 11(1):1–17. https://doi.org/10.1057/s41599-024-02717-y

Wang CL, Dai J, Zhu KK, Yu T, Gu XQ (2023a) Understanding the Continuance Intention of College Students Toward New E-learning Spaces Based on an Integrated Model of the TAM and TTF. Int J Hum-comput Int 1–14. https://doi.org/10.1080/10447318.2023.2291609

Wang CL, Wang HM, Li YY, Dai J, Gu XQ, Yu T (2024b) Factors Influencing University Students’ Behavioral Intention to Use Generative Artificial Intelligence: Integrating the Theory of Planned Behavior and AI Literacy. Int J Hum-comput Int 1–23. https://doi.org/10.1080/10447318.2024.2383033

Wang J, Zhao W, Zhang Z, Liu X, Xie T, Wang L, Zhang Y (2024c) A journey of challenges and victories: a bibliometric worldview of nanomedicine since the 21st century. Adv Mater 36(15):2308915. https://doi.org/10.1002/adma.202308915

Wang J, Chen Y, Huo S, Mai L, Jia F (2023b) Research hotspots and trends of social robot interaction design: A bibliometric analysis. Sensors 23(23):9369. https://doi.org/10.3390/s23239369

Wang KH, Chen G, Chen HG (2017) A model of technology adoption by older adults. Soc Behav Personal 45(4):563–572. https://doi.org/10.2224/sbp.5778

Wang S, Bolling K, Mao W, Reichstadt J, Jeste D, Kim HC, Nebeker C (2019) Technology to Support Aging in Place: Older Adults’ Perspectives. Healthcare 7(2):60. https://doi.org/10.3390/healthcare7020060

Wang Z, Liu D, Sun Y, Pang X, Sun P, Lin F, Ren K (2022) A survey on IoT-enabled home automation systems: Attacks and defenses. IEEE Commun Surv Tutor 24(4):2292–2328. https://doi.org/10.1109/COMST.2022.3201557

Wilkowska W, Offermann J, Spinsante S, Poli A, Ziefle M (2022) Analyzing technology acceptance and perception of privacy in ambient assisted living for using sensor-based technologies. PloS One 17(7):e0269642. https://doi.org/10.1371/journal.pone.0269642

Wilson J, Heinsch M, Betts D, Booth D, Kay-Lambkin F (2021) Barriers and facilitators to the use of e-health by older adults: a scoping review. BMC Public Health 21:1–12. https://doi.org/10.1186/s12889-021-11623-w

Xia YQ, Deng YL, Tao XY, Zhang SN, Wang CL (2024) Digital art exhibitions and psychological well-being in Chinese Generation Z: An analysis based on the S-O-R framework. Humanit Soc Sci Commun 11:266. https://doi.org/10.1057/s41599-024-02718-x

Xie H, Zhang Y, Duan K (2020) Evolutionary overview of urban expansion based on bibliometric analysis in Web of Science from 1990 to 2019. Habitat Int 95:102100. https://doi.org/10.1016/j.habitatint.2019.10210

Xu Z, Ge Z, Wang X, Skare M (2021) Bibliometric analysis of technology adoption literature published from 1997 to 2020. Technol Forecast Soc Change 170:120896. https://doi.org/10.1016/j.techfore.2021.120896

Yap YY, Tan SH, Choon SW (2022) Elderly’s intention to use technologies: a systematic literature review. Heliyon 8(1). https://doi.org/10.1016/j.heliyon.2022.e08765

Yu T, Dai J, Wang CL (2023) Adoption of blended learning: Chinese university students’ perspectives. Humanit Soc Sci Commun 10:390. https://doi.org/10.1057/s41599-023-01904-7

Yusif S, Soar J, Hafeez-Baig A (2016) Older people, assistive technologies, and the barriers to adoption: A systematic review. Int J Med Inform 94:112–116. https://doi.org/10.1016/j.ijmedinf.2016.07.004

Zhang J, Zhu L (2022) Citation recommendation using semantic representation of cited papers’ relations and content. Expert Syst Appl 187:115826. https://doi.org/10.1016/j.eswa.2021.115826

Zhao Y, Li J (2024) Opportunities and challenges of integrating artificial intelligence in China’s elderly care services. Sci Rep 14(1):9254. https://doi.org/10.1038/s41598-024-60067-w

Article   ADS   MathSciNet   PubMed   PubMed Central   Google Scholar  

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This research was supported by the Social Science Foundation of Shaanxi Province in China (Grant No. 2023J014).

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School of Art and Design, Shaanxi University of Science and Technology, Xi’an, China

Xianru Shang, Zijian Liu, Chen Gong, Zhigang Hu & Yuexuan Wu

Department of Education Information Technology, Faculty of Education, East China Normal University, Shanghai, China

Chengliang Wang

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Conceptualization, XS, YW, CW; methodology, XS, ZL, CG, CW; software, XS, CG, YW; writing-original draft preparation, XS, CW; writing-review and editing, XS, CG, ZH, CW; supervision, ZL, ZH, CW; project administration, ZL, ZH, CW; funding acquisition, XS, CG. All authors read and approved the final manuscript. All authors have read and approved the re-submission of the manuscript.

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Correspondence to Chengliang Wang .

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Shang, X., Liu, Z., Gong, C. et al. Knowledge mapping and evolution of research on older adults’ technology acceptance: a bibliometric study from 2013 to 2023. Humanit Soc Sci Commun 11 , 1115 (2024). https://doi.org/10.1057/s41599-024-03658-2

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Received : 20 June 2024

Accepted : 21 August 2024

Published : 31 August 2024

DOI : https://doi.org/10.1057/s41599-024-03658-2

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