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Mapping research in marketing: trends, influential papers and agenda for future research

Spanish Journal of Marketing - ESIC

ISSN : 2444-9695

Article publication date: 5 December 2023

Issue publication date: 7 March 2024

This study aims to map the conceptual structure and evolution of the recent scientific literature published in marketing journals to identify the areas of interest and potential future research directions.

Design/methodology/approach

The 100 most influential marketing academic papers published between 2018 and 2022 were identified and scrutinized through a bibliometric analysis.

The findings further upheld the critical role of emerging technologies such as Blockchain in marketing and identified artificial intelligence and live streaming as emerging trends, reinforcing the importance of data-driven marketing in the discipline.

Research limitations/implications

The data collection included only the 100 most cited documents between 2018 and 2022, and data were limited only to Scopus database and restrained to the Scopus-indexed marketing journals. Moreover, documents were selected based on the number of citations. Nevertheless, the data set may still provide significant insight into the marketing field.

Practical implications

Influential authors, papers and journals identified in this study will facilitate future literature searches and scientific dissemination in the field. This study makes an essential contribution to the marketing literature by identifying hot topics and suggesting future research themes. Also, the important role of emerging technologies and the shift of marketing toward a more data-driven approach will have significant practical implications for marketers.

Originality/value

To the best of the authors’ knowledge, this is the first comprehensive study offering a general overview of the leading trends and researchers in marketing state-of-the-art research.

Bibliometric analysis
Citation analysis
Research publications
Science mapping
Análisis bibliométrico
Análisis de citas
Publicaciones de investigación
Mapeo científico
市场营销; 文献计量分析; 引文分析; 研究出版物; 科学绘图。

Ramos, R. , Rita, P. and Vong, C. (2024), "Mapping research in marketing: trends, influential papers and agenda for future research", Spanish Journal of Marketing - ESIC , Vol. 28 No. 2, pp. 187-206. https://doi.org/10.1108/SJME-10-2022-0221

Emerald Publishing Limited

Published in Spanish Journal of Marketing - ESIC. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

1. Introduction

Marketing is vital to all businesses’ survival, long-term growth, development and success ( Czinkota et al. , 2021 ). Generally, the domain of marketing encompasses (1) the identification of marketing opportunities, (2) the creation of competitive advantages, (3) the effective utilization of resources, (4) the communication and delivery of products or services to customers, (5) the creation of value to customers and (6) the satisfaction of customers’ needs profitably ( Simkin, 2000 ).

The evaluation of academic marketing literature has progressively become relevant in recent years ( Das et al. , 2022 ; Hair and Sarstedt, 2021 ). The increasing number of academic publications in marketing varies in different contributions, which made it difficult for scholars to track new trends and find influential manuscripts to advance the body of knowledge. The primary objective of a research publication is to be known and influence others’ work. Nevertheless, the created knowledge is fragmented, and the emergence of new marketing topics is continuously changing the research map of marketing. Moreover, marketing is an applied discipline in that marketing research not only aims to generate scientific knowledge but also to provide insights and knowledge that can be practically used to inform marketing decisions ( Jedidi et al. , 2021 ). In addition, technological advancement has rapidly affected marketing practices and management ( Amado et al. , 2018 ). To address this challenge, this paper aims to map the conceptual structure and the evolution of knowledge to uncover the existing topics, trending areas of interest and future directions.

Despite considerable research efforts in the marketing field, little has been done to review prior research works systematically. Moreover, recent review articles have mainly focused on specific marketing domains or are limited to particular contexts, such as customer experience ( Chauhan et al. , 2022 ), marketing communication ( Domenico et al. , 2021 ), customer engagement ( Chen et al. , 2021 ), consumer behavior ( Oliveira et al. , 2022 ), advertising ( Jebarajakirthy et al. , 2021 ) and product or brand positioning ( Saqib, 2021 ), while context-specific reviews include marketing in emerging markets ( Paul et al. , 2016 ), sustainable marketing ( Lunde, 2018 ), business-to-business marketing ( Pandey et al. , 2020 ), luxury brand marketing ( Arrigo, 2018 ) and tourism marketing ( Han and Bai, 2022 ). The lack of a holistic review of marketing research created a gap in the existing research. Therefore, it is necessary to provide a big picture of the most recent marketing literature. The most recent review work in the same vein was conducted by Morgan et al. (2019) , who evaluated 257 marketing strategy articles published in the six most influential marketing journals during 1999–2017. Nevertheless, given its focus on marketing strategy and limited research sources, it does not provide a comprehensive framework that covers all aspects of the marketing field. To complement the work by Morgan et al. (2019) , this paper conducts a review with a more recent timeframe that focuses on recent trends, patterns and development in the field. The inclusiveness of journals will also enable identifying areas of interest beyond marketing strategy.

What is the knowledge structure of the state-of-the-art most influential academic research in marketing?

What are the current research trends?

What are possible pathways for future research in marketing?

The present work will facilitate the understanding and advancement of theories and knowledge in the field. Also, this paper provides valuable insights into the field’s most relevant and pressing issues and informs where future research efforts should be focused. This will, in turn, improve the practical relevance and usefulness of future research and ensure that research efforts are targeted toward topics that will yield impactful results. Moreover, it offers up-to-date information for marketing researchers.

2. Methodology

This study focuses on characterizing the most influential academic marketing articles published between 2018 and 2022 and discussing the marketing state of the art.

2.1 Search strategy

A search string was applied in the Scopus database to find the most relevant articles for this research ( Ramos et al. , 2019 ). The Scopus database was chosen for the literature review as it is generally considered one of the largest repositories with the most relevant indexed publications and one of the most universally acknowledged bibliographic databases ( Kumar et al. , 2020 ). It is recognized as the most well-organized and of the highest credibility and quality standards, with the most significant global impact and more comprehensive cover ( Muñoz-Leiva et al. , 2015 ; Rojas-Lamorena et al. , 2022 ) and is consistent with previous bibliometric reviews applied in the marketing research setting ( Kumar et al. , 2021 ; Paul and Bhukya, 2021 ). In addition, it follows Donthu et al. (2021) ’s recommendation to select only one database to minimize human errors during analysis. All marketing journals (212) indexed in Scopus were included in the current study. The journal selection takes a rather inclusive approach instead of the sole inclusion of marketing-specific journals, as marketing is a diverse and evolving field not strictly tied to a single-subject field ( Baumgartner and Pieters, 2003 ) but often intersects with other disciplines. For instance, given the rapid advancement of technology and its influence on marketing practices, topics such as information systems or big data are growing in importance and relevance to the marketing literature ( Amado et al. , 2018 ). Accordingly, journals such as the International Journal of Information Management have also contributed significantly to marketing recently ( Veloutsou and Ruiz Mafe, 2020 ). The search was conducted on June 9, 2023.

2.2 Selection process and final data set

The search was conducted in the Scopus database and limited to 2018 to 2022 to obtain state-of-the-art articles. Five years is a reasonable timeframe to capture a discipline’s essence and to conduct a bibliometric analysis ( Borgohain et al. , 2022 ). The collection of articles over five years reflects varied, robust, broad, inclusive and unrelated marketing research interests in the marketing field ( Bettenhausen, 1991 ). The focus on the most recent works permits uncovering the most recent trends without the influence of older topics. Only articles were selected as they represent the most advanced and up-to-date knowledge and are recognized for their academic value ( Rojas-Lamorena et al. , 2022 ). In total, 44,767 articles were collected. To select the most recent influential marketing articles, the top 100 most cited articles were selected. The citation metric acknowledges the impact of the articles ( Donthu et al. , 2021 ) and reflects the impact of scholarly work in subsequent research ( Purkayastha et al. , 2019 ).

In addition, it is recognized as one of the most relevant metrics of academic research ( Dowling, 2014 ). Although assessing the influence of an article based on citation analysis represents a significant limitation because articles may be cited for multiple reasons, citation analysis is considered an objective approach that exhibits less systematic biases for research impact evaluation ( Baumgartner and Pieters, 2003 ). Previous works have used citation metrics for bibliometric analysis. For instance, Law et al. (2009) analyzed the most influential articles published in Tourism journals using citation counts, whereas Brito et al. (2018) identified the areas of interest in football research and listed the articles based on citation frequency. From each article, the following variables were retrieved: authors’ names and keywords, document title, year, source title and citation count. The information was extracted in CSV file format.

2.3 Final data set

The final data set includes 100 articles from 28 journals. The authors’ names were reviewed for normalization purposes as they have different nomenclatures in different articles (e.g. Dwivedi YK vs Dwivedi Y) so that the software understands them as the same.

2.4 Data analysis

The CSV file with the final data set was input for the bibliometric analysis. Data were analyzed using the mapping analysis R-tool bibliometrix ( Aria and Cuccurullo, 2017 ). This package allows different types of analysis, offering an overview of the research field. A bibliometric analysis permits to analyzing the bibliographic material quantitatively, providing an objective and reliable analysis ( Broadus, 1987 ; Sepulcri et al. , 2020 ) and summarizing the existing literature and identifying emerging topics of research ( Hota et al. , 2020 ). The authors’ names and keywords, year of publication, source title and the number of citations were collected from each article. A performance analysis was performed to acknowledge the field’s citation structure, most relevant sources, authors and articles. Then, science mapping analysis through a co-occurrence analysis was performed. The co-occurrence analysis aims to overcome the descriptive nature of the bibliometric analysis, uncovering gaps and research trends ( Palmatier et al. , 2018 ; Quezado et al. , 2022 ). The gaps and research trends led to a future research agenda.

3. Results and discussion

3.1 total citations by year.

As indicated in Table 1 , the 100 articles were cited 41,888 times, an average of 418.88 citations per article. The most contributing years were 2019 and 2020, with 33 published articles yearly. The year with the highest number of citations was 2019, with 14,621 citations, corresponding to 34.90% of the total citations. This record is strongly linked to the work of Snyder (2019) , with 1,872 citations that characterized different types of literature reviews and suggested guidelines on conducting and evaluating business research literature reviews. Due to the increasing number of publications, it is challenging to keep current with state-of-the-art research ( Briner and Denyer, 2012 ). Reviewing the existing research is fundamental for understanding marketing research inconsistencies, gathering and synthesizing previous research and serving as guidance for researchers and practitioners. In addition, literature reviews contribute to identifying potential gaps, suggesting novel research lines and allowing a balanced growth of a research field ( Hulland and Houston, 2020 ).

The year with the highest mean total citations per article and year was 2021 (527.5 and 175.83, respectively). This result is highly associated with Donthu et al. (2021) ’s work, with 1,221 citations, that explained how to develop a bibliometric analysis.

The main difference between a literature review and bibliometric analysis is the focus and the methodological approach. A literature review aims to critically analyze and synthesize existing knowledge under a research topic ( Snyder, 2019 ). In turn, a bibliometric analysis is a specific approach within the field of scientometrics that uses quantitative and statistical methods to analyze the scientific production and articles’ characteristics published in a specific research domain ( Aria and Cuccurullo, 2017 ).

3.2 Most influential articles

Seminal articles in marketing assume an essential role in its development ( Berry and Parasuraman, 1993 ). The number of citations was used to define and measure the impact of the most influential articles. The most cited document (total citation = 1,872) was Snyder’s (2019) work on conducting an overview and suggesting guidelines for conducting a literature review ( Table 2 ). The normalized citation compares an article’s performance to the data set’s average performance ( Bornmann and Marx, 2015 ; Rita and Ramos, 2022 ). Snyder (2019) ’s work has the highest normalized citation index (4.13), revealing its outstanding performance compared with the remaining articles from the data set.

Among the top 10 most cited articles, three are related to PLS-SEM. The partial least squares – structural equation modeling (PLS-SEM) is relevant for marketing as it allows to examine of complex relationships between latent variables and manifest variables, permitting a flexible and less restrictive analysis in terms of statistical assumptions than other modeling techniques, such as confirmatory factor analysis and principal component analysis ( Hair et al. , 2020 ). By using PLS-SEM, marketing researchers can explore complex relationships among variables, test research hypotheses, identify the relative importance of different influencers and assess the validity and reliability of the measured variables ( Sarstedt et al. , 2019 ). It is frequently used in research involving the modeling of theoretical constructs, such as customer satisfaction ( Ramos et al. , 2022 ), brand image ( Kunkel et al. , 2020 ) or perceived quality ( Ariffin et al. , 2021 ) research.

Surprisingly, there are no articles from 2018 in the top 10 most cited articles. However, there are two articles published in 2021. One of the papers published in 2021 is the work of Verhoef et al. (2021) , which explores digital transformation and innovation in business models and suggests a research agenda for future studies. Digital transformation and innovation are highly relevant for marketing as it provokes consumer behavior change ( Lemos et al. , 2022 ). In addition, it allows companies to adapt to consumer behavior changes, seize the opportunities for segmentation and personalization, improve communication and engagement and increase operational efficiency ( Muneeb et al. , 2023 ; Zhang et al. , 2022 ).

3.3 Source impact

Table 3 depicts the top 10 most impactful sources of the 100 most influential marketing articles. The intellectual convergence is exhibited based on common sources and referencing patterns ( Donthu et al. , 2021 ), and identifying journals may facilitate future literature search and scientific dissemination.

Among the 28 journals, the International Journal of Information Management (IJIM) contributed the most papers (26 papers), followed by the Journal of Business Research (JBR) (22 papers) and the Journal of Retailing and Consumer Services (JRCS) (6 papers). These journals are all First Quartile journals based on SCImago Journal Rank (SJR) indicator, with an impact factor of 4.906, 2.895 and 2.543, respectively. The IJIM focuses on contemporary issues in information management ( Elsevier, 2023a ). Information management field of research plays a fundamental role in marketing, providing data and insights that guide marketing strategies, improve segmentation and customization, leverage automation marketing, data-driven decision-making and the performance evaluation of marketing initiatives ( Dwivedi et al. , 2020 ). The JBR aims to publish recent business research dealing with the spectrum of actual business practical settings among different business activities ( Elsevier, 2023b ), while the JRCS focuses on consumer behavior and policy and managerial decisions ( Elsevier, 2023c ). The findings indicate the contribution and importance of IJIM to the marketing field, recognizing the relevance of information management. Surprisingly, leading marketing journals listed in the Financial Times 50 ( Ormans, 2016 ), such as the Journal of Consumer Research , Journal of the Academy of Marketing Science and Journal of Marketing , only produced a small number of relevant articles in our data set. This result suggests that their papers may not be as impactful or influential as those published in other outlets. Nevertheless, the quality of the articles published in these outlets reflects the most original and well-executed research, as they have high submission rates. However, their rate of acceptance is very low.

Among the top 10 most productive journals, JBR is the one with the highest number of citations. This result confirms Table 2 ’s results as it lists six articles that were published in this journal ( Donthu et al. , 2021 ; Hair et al. , 2020 ; Sheth, 2020 ; Sigala, 2020 ; Snyder, 2019 ; Verhoef et al. , 2021 ).

3.4 Contributing authors

Key authors are essential to the field’s structure and growth ( Berry and Parasuraman, 1993 ) and positively influence the most impactful articles ( Rojas-Lamorena et al. , 2022 ). Thus, it is imperative to identify them and acknowledge their impact. Between 2018 and 2022, 100 documents were written by 312 different authors.

Table 4 characterizes the top 10 most productive authors among the most influential marketing research articles over the past five years. The authors’ indices were calculated, including h -index, g -index and m -index. The Hirsh index ( h -index) is the proposal to quantify productivity and the journal’s impact considering the number of papers and citations per publication ( Hirsch, 2005 ). The g -index aims to measure the performance of the journals ( Egghe, 2006 ), considering the citation evolution of the most cited papers over time. Furthermore, the m -index, also called the m -quotient, considers the h -index and the time since the first publication ( n ); hence, m -index = h -index/ n ( Halbach, 2011 ).

Professor Dwivedi YK is the most prolific, with seven published articles indicating more than one paper yearly. Although he is placed second as the most cited author (3,361), he has the highest h - (7), g - (7) and m -index (1.17). Professor Dwivedi’s research focuses on digital innovation and technology consumer adoption and the use of information systems and information technology for operation management and supply chain, focusing on emergent markets. Digital innovation and understanding technology consumer adoption allow companies to engage with consumers efficiently and personally ( Alalwan et al. , 2023 ). In addition, information systems and information technology applied in operation management and supply chain permit a higher efficiency and visibility in commercial activities, aiding companies to optimize processes, reduce costs and improve customer care ( Tasnim et al. , 2023 ). Professor Dwivedi is a Professor at the School of Management, Swansea University, UK ( Swansea, 2023 ). The second most productive author is Hair JF, and Hughes DL, with five articles each. Professor Hair JF is the most cited author in the list of the most productive authors. This record is highly associated with the work “Assessing measurement model quality in PLS-SEM using confirmatory composite analysis” ( Hair et al. , 2020 ), with 1,103 citations. Multiple papers gather authors from the list. For instance, the article “Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy” ( Dwivedi et al. , 2021 ) was co-authored by Professors Dwivedi YK and Hughes DL. This paper has 637 citations and addresses the transformative power that artificial intelligence (AI) may have for the automation and replacement of human tasks, highlighting opportunities, challenges and impacts. AI plays a fundamental role in marketing, permitting advanced personalization, task automation, advanced data analysis, campaign optimization and improved customer experience, leading to personalized experiences and better marketing results ( Duan et al. , 2019 ; Dwivedi et al. , 2021 ).

Fractionalized frequency displays the multiauthored articles. This analysis is relevant to understand how researchers interact with each other ( Rojas-Lamorena et al. , 2022 ). A credit is attributed to each author, depending on the number of co-authors. If a paper has two authors, each receives a half-point. If a paper has three authors, each receives a third of a point, and so on ( Cuccurullo et al. , 2016 ). Professor Hughes DL has the lowest score (0.57) on the five most productive authors list, suggesting a strong relationship with colleagues through co-authorship based on shared interests.

3.5 Co-occurrence analysis

Figure 1 presents the authors’ keywords co-occurrence analysis and reflects the relationship between the keywords and the data set ( Wang et al. , 2012 ). Co-occurrence analysis aims to establish relationships and map the conceptual structure of the most influential marketing academic articles and reveal current research trends ( Eduardsen and Marinova, 2020 ). The thicker the lies among each cluster, the stronger the connection between the keywords. The size of each edge indicates the occurrence frequency. Thematic map displays the top 50 keywords and a minimum of 5 clusters. The thematic map shows six clusters, of which two are with the largest nodes, including AI (brown) and Covid-19 (blue). However, clusters with smaller nodes are bibliometric analysis (red), social media (purple), blockchain (green) and customer engagement (orange).

The brown cluster suggests a topic under AI technology. The cluster’s keywords highlight an interconnection and application of AI, machine learning and cognitive computing in the marketing research field. Deep learning, natural language processing and machine learning make part of a broader spectrum of AI ( Verma et al. , 2021 ). Cognitive computing refers to the capacity of computer systems to mimic human capacity to process information, learn and make decisions ( Duan et al. , 2019 ). These technologies handle big data efficiently, predict consumer behavior and support decision-making in actionable insights, transforming marketing strategies ( Blanco-Moreno et al. , 2023 ; Dwivedi et al. , 2021 ).

The blue cluster reflects the pandemic that affected the globe between 2020 and 2023 ( United Nations, 2023 ). This cluster reveals a close relationship between the Covid-19 pandemic and consumer behavior ( Sheth, 2020 ). The interest in understanding the attitudes and consumers’ decision-making is highly relevant for future pandemics ( Pereira et al. , 2023 ). In addition, the pandemic brought social and industry challenges that deserve academic attention ( Dwivedi et al. , 2020 ; Muneeb et al. , 2023 ). This cluster also addresses overconsumption driven by impulsive behavior promoted by the pandemic ( Islam et al. , 2021 ; Marikyan et al. , 2023 ). This cluster suggests insights on how companies can adequately develop marketing strategies to face the pandemic challenges and effectively respond to health crises.

The red cluster reveals a direct connection between bibliometric analysis and scientific assessment. The bibliometric analysis is applied to reveal research patterns and knowledge structure and access the scientific production impact ( Ramos and Rita, 2023 ). The use of bibliographic coupling, co-occurrence analysis and the Scopus database supplies the data set for the identification of relationships and patterns within the literature ( Donthu et al. , 2021 ), summarizing the existing literature and identifying emerging topics of research ( Hota et al. , 2020 ).

The purple cluster highlights the terms social media and marketing. The keyword social media highlights the role of platforms, such as Instagram or TikTok, for advertising ( Alalwan, 2018 ), understanding the role of influencers ( Lou and Yuan, 2019 ), and for co-creation in brand communities ( Kamboj et al. , 2018 ), influencer marketing. Social media platforms are fundamental for any communication strategy as they connect with the audience, create engagement and awareness and promote products and services ( Lou and Yuan, 2019 ). The strategic use of social media in marketing is fundamental for companies to establish an effective presence and build long-lasting relationships.

The orange cluster suggests a relationship between live streaming and customer engagement ( Wongkitrungrueng and Assarut, 2020 ). This interconnection suggests that live streaming can be an effective channel for developing social commerce, influencing purchase intentions ( Sun et al. , 2019 ). Real-time and direct interaction with customers promote greater involvement and improve customer experience.

The green cluster suggests a focus on applying blockchain technology in information systems. Blockchain is a decentralized and immutable technology for transaction registers studied in the supply chain context ( Min, 2019 ). It has a significant potential to transform data management ( Lemos et al. , 2022 ).

4. Conclusions and future research agenda

This study represents a map of the conceptual structure and evolution of the state-of-the-art scientific literature published in marketing journals to identify the areas of interest and potential future research directions. This review aimed to (1) acknowledge the structure of the state-of-the-art most influential academic marketing research, (2) identify current research trends and (3) suggest future research prospects.

4.1 RQ1: knowledge structure

Regarding RQ1, the most cited article among the top 100 between 2018 and 2022 was the work of Snyder (2019) , with 1,872 citations, followed by the work of Donthu et al. (2021) , with 1,221. The years 2019 and 2020 were those that most contributed to the top 100 most cited, with 33 articles each. Accordingly, these years had the most citations, 14,621 and 13,692, respectively. The IJIM was the source with the highest number of articles published from our data set ( n = 26). However, the JBR, with 22 published articles, was the journal with the highest citations ( n = 12,265). Every journal from the top 10 prolific sources is ranked in Scopus (SJR) as Q1. Professor Dwivedi YK was the most prolific author, with seven articles published, followed by Professors Hair JF and Hughes DL, with five articles each. Although placed second on the most productive authors list, the most cited author was Professor Hair JF, with 3,615 articles.

4.2 RQ2: current research trends

As for RQ2, this bibliometric analysis allowed us to identify current research trends through the co-occurrence analysis. Since a comprehensive future research agenda stimulates researchers to continue their research efforts ( Hulland and Houston, 2020 ), we suggest marketing future research questions to gain a deeper knowledge of current research trends ( Table 5 ).

Although AI has existed for over six decades ( Duan et al. , 2019 ), the development of supercomputers that analyze big data led to the exponential use of this technology. Its application in marketing varies and includes trend and prediction analysis, chatbots and marketing automation. However, particularly for data analysis, multiple research questions are yet to be answered ( Dwivedi et al. , 2021 ). Grounded on the AI (brown) cluster, it would be interesting to uncover different uses of AI to improve big data analysis.

The Covid-19 pandemic disrupted global habits ( Sheth, 2020 ). New habits emerged, changing the industry landscape in multiple dimensions, such as consumer, leisure and work behavior. Although multiple studies were published regarding the topic, much is yet to be uncovered. The effects of this pandemic are yet to be fully acknowledged, demanding future studies to comprehend the permanent changes in society ( Islam et al. , 2021 ). In addition, uncovering the best-implemented industry marketing strategies can be helpful, as it is inevitable that new pandemics occur in the future ( Pereira et al. , 2023 ).

Bibliometric analyses map and summarize existent research, extending the global understanding of a research topic and increasing the quality and success of scholarly work ( Donthu et al. , 2021 ). However, the analysis is mainly descriptive ( Ramos and Rita, 2023 ). Combining bibliometric analysis with other methods may enhance the results, leading to an advancement in using such an approach.

Social media is broadly used for marketing-related activities. Through social media platforms, it is possible to build brand image, generate leads for the company’s website, analyze and monitor data, or be an influencer marketer ( Alalwan, 2018 ; Lou and Yuan, 2019 ). Nevertheless, the implementation of gamification techniques ( Bhutani and Behl, 2023 ; Wanick and Stallwood, 2023 ), privacy concerns ( Saura et al. , 2023 ) and collective decision-making ( Dambanemuya et al. , 2023 ) are issues that deserve the attention of researchers.

Livestreaming captured the attention of digital retailing marketers in recent years and significantly changed social interaction. However, different types of live streaming exist, such as webinars, game streaming, corporate streaming, vlogs or personalized content, and can be used in different industries ( Zhang et al. , 2023 ). Investigating the influence of live streaming on consumer engagement may enhance understanding of its relevance for the industry and improve marketing effectiveness ( Wongkitrungrueng and Assarut, 2020 ).

Blockchain technology allows tracing and enhances transaction transparency, creating authenticity certificates to prevent fraud or loyalty programs to build customers’ loyalty and trust ( Lemos et al. , 2022 ). Despite several studies being conducted to understand the impact of this technology on marketing ( Marthews and Tucker, 2023 ; Tan and Salo, 2023 ), there is much to be learned and questions unanswered.

4.3 RQ3: future research agenda

Based on the comprehensive bibliometric analysis findings, potential directions for future research are presented ( Table 6 ). Topics surrounding data-driven marketing are particularly relevant ( Zhang et al. , 2022 ) due to the data abundance and technological advances, and they have the potential to be further developed. For instance, issues arising from adopting AI to uncover hidden patterns in big data or integrating data from different sectors or industries to understand consumer behavior are yet to be understood. In addition, environmental sustainability is highly relevant due to the increasing customers’ awareness of the topic and its influence on developing marketing strategies ( Jung et al. , 2020 ). However, multiple questions are yet to be answered. In particular, the influence of gamification techniques to promote positive, environmentally sustainable consumer behavior and how emerging technologies influence the customers’ perception of sustainable products. Mass personalization allows consumers to customize product features ( Qin and Lu, 2021 ). This topic is highly relevant to the industry and underexplored in marketing. For instance, how can mass personalization be efficiently implemented in highly productive industries? Or how can emerging technologies improve mass personalization programs? Finally, the wearable technologies market is exponentially growing and is increasingly essential to consumer behavior ( Ferreira et al. , 2021 ).

5. Conclusions and limitations

Through the bibliometric analysis of the 100 most influential marketing papers published between 2018 and 2022, this review presents potential directions for knowledge advancement and comprehensive information to facilitate future literature search ( Boell and Cecez-Kecmanovic, 2014 ) by identifying the current research focus, conceptual structure and trends in the marketing field. In addition, this review contributes to practice by identifying the most influential articles for the marketing scientific community interested in gaining scientific insights. Meanwhile, the important role of emerging technologies and the shift of marketing toward a more data-driven approach will have significant practical implications for marketers.

This work has limitations that need to be stated. First, data were limited to Scopus database and restrained to indexed marketing journals. However, it is essential to note that all scientific databases have limitations. Second, to select the most influential marketing documents, the only criterion was on a commonly used metric – the number of citations. Although citation metrics are commonly used, they may incorrectly demonstrate the quality of the work. There are multiple reasons for a work to be cited ( Vogel and Güttel, 2012 ), such as a journal’s prestige or factors related to the methods ( Hota et al. , 2020 ). The Mathew effect phenomenon also exists in science ( García-Lillo et al. , 2017 ). Third, articles take time to be cited. This means that the most recent articles from our data set may have fewer citations, but it does not mean that their quality is poorer. Fourth, to select the most influential marketing articles, every journal under the subject area “Business, Management and Accounting” and category “Marketing” were selected. However, there are journals listed in other subject areas and categories. Nevertheless, the data set may still provide significant insight into the marketing field.

Thematic map based on the authors’ keywords co-occurrence

Acknowledgements

Paulo Rita’s work was supported by national funds through FCT (Fundação para a Ciência e a Tecnologia), under the project – UIDB/04152/2020 – Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS.

Since submission of this article, the following authors have updated their affiliations: Ricardo Ramos is at Technology and Management School of Oliveira do Hospital, Polytechnic Institute of Coimbra, Oliveira do Hospital, Portugal; ISTAR, Instituto Universitário de Lisboa (ISCTE-IUL), Lisboa, Portugal; Centre Bio R&D Unit, Association BLC3 – Tecnology and Innovation Campus, Oliveira do Hospital, Portugal; Paulo Rita is at NOVA Information Management School (NOVA IMS), Universidade NOVA de Lisboa, Lisboa, Portugal; and Celeste Vong is at NOVA Information Management School (NOVA IMS), Universidade NOVA de Lisboa, Lisboa, Portugal.

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The future of social media in marketing

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Published: 12 October 2019
Volume 48 , pages 79–95, ( 2020 )

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Introduction

Social media is used by billions of people around the world and has fast become one of the defining technologies of our time. Facebook, for example, reported having 2.38 billion monthly active users and 1.56 billion daily active users as of March 31, 2019 (Facebook 2019 ). Globally, the total number of social media users is estimated to grow to 3.29 billion users in 2022, which will be 42.3% of the world’s population (eMarketer 2018 ). Given the massive potential audience available who are spending many hours a day using social media across the various platforms, it is not surprising that marketers have embraced social media as a marketing channel. Academically, social media has also been embraced, and an extensive body of research on social media marketing and related topics, such as online word of mouth (WOM) and online networks, has been developed. Despite what academics and practitioners have studied and learned over the last 15–20 years on this topic, due to the fast-paced and ever-changing nature of social media—and how consumers use it—the future of social media in marketing might not be merely a continuation of what we have already seen. Therefore, we ask a pertinent question, what is the future of social media in marketing?

Addressing this question is the goal of this article. It is important to consider the future of social media in the context of consumer behavior and marketing, since social media has become a vital marketing and communications channel for businesses, organizations and institutions alike, including those in the political sphere. Moreover, social media is culturally significant since it has become, for many, the primary domain in which they receive vast amounts of information, share content and aspects of their lives with others, and receive information about the world around them (even though that information might be of questionable accuracy). Vitally, social media is always changing. Social media as we know it today is different than even a year ago (let alone a decade ago), and social media a year from now will likely be different than now. This is due to constant innovation taking place on both the technology side (e.g., by the major platforms constantly adding new features and services) and the user/consumer side (e.g., people finding new uses for social media) of social media.

What is social media?

Definitionally, social media can be thought of in a few different ways. In a practical sense, it is a collection of software-based digital technologies—usually presented as apps and websites—that provide users with digital environments in which they can send and receive digital content or information over some type of online social network. In this sense, we can think of social media as the major platforms and their features, such as Facebook, Instagram, and Twitter. We can also in practical terms of social media as another type of digital marketing channel that marketers can use to communicate with consumers through advertising. But we can also think of social media more broadly, seeing it less as digital media and specific technology services, and more as digital places where people conduct significant parts of their lives. From this perspective, it means that social media becomes less about the specific technologies or platforms, and more about what people do in these environments. To date, this has tended to be largely about information sharing, and, in marketing, often thought of as a form of (online) word of mouth (WOM).

Building on these definitional perspectives, and thinking about the future, we consider social media to be a technology-centric—but not entirely technological—ecosystem in which a diverse and complex set of behaviors, interactions, and exchanges involving various kinds of interconnected actors (individuals and firms, organizations, and institutions) can occur. Social media is pervasive, widely used, and culturally relevant. This definitional perspective is deliberately broad because we believe that social media has essentially become almost anything—content, information, behaviors, people, organizations, institutions—that can exist in an interconnected, networked digital environment where interactivity is possible. It has evolved from being simply an online instantiation of WOM behaviors and content/information creation and sharing. It is pervasive across societies (and geographic borders) and culturally prominent at both local and global levels.

Throughout the paper we consider many of the definitional and phenomenological aspects described above and explore their implications for consumers and marketing in order to address our question about the future of marketing-related social media. By drawing on academic research, discussions with industry leaders, popular discourse, and our own expertise, we present and discuss a framework featuring nine themes that we believe will meaningfully shape the future of social media in marketing. These themes by no means represent a comprehensive list of all emerging trends in the social media domain and include aspects that are both familiar in extant social media marketing literature (e.g., online WOM, engagement, and user-generated content) and emergent (e.g., sensory considerations in human-computer interaction and new types of unstructured data, including text, audio, images, and video). The themes we present were chosen because they capture important changes in the social media space through the lenses of important stakeholders, including consumers, industry/practice, and public policy.

In addition to describing the nature and consequences of each theme, we identify research directions that academics and practitioners may wish to explore. While it is infeasible to forecast precisely what the future has in store or to project these on a specific timeline, we have organized the emergent themes into three time-progressive waves, according to imminence of impact (i.e., the immediate, near, and far future). Before presenting our framework for the future of social media in marketing and its implications for research (and practice and policy), we provide a brief overview of where social media currently stands as a major media and marketing channel.

Social media at present

The current social media landscape has two key aspects to it. First are the platforms—major and minor, established and emerging—that provide the underlying technologies and business models making up the industry and ecosystem. Second are the use cases; i.e., how various kinds of people and organizations are using these technologies and for what purposes.

The rise of social media, and the manner in which it has impacted both consumer behavior and marketing practice, has largely been driven by the platforms themselves. Some readers might recall the “early days” of social media where social networking sites such as MySpace and Friendster were popular. These sites were precursors to Facebook and everything else that has developed over the last decade. Alongside these platforms, we continue to have other forms of social media such as messaging (which started with basic Internet Relay Chat services in the 1990s and the SMS text messaging built into early digital mobile telephone standards in the 2000s), and asynchronous online conversations arranged around specific topics of interest (e.g., threaded discussion forums, subreddits on Reddit). More recently, we have seen the rise of social media platforms where images and videos replace text, such as Instagram and Snapchat.

Across platforms, historically and to the present day, the dominant business model has involved monetization of users (audiences) by offering advertising services to anyone wishing to reach those audiences with digital content and marketing communications. Prior research has examined the usefulness of social media (in its various forms) for marketing purposes. For example, work by Trusov et al. ( 2009 ) and Stephen and Galak ( 2012 ) demonstrated that certain kinds of social interactions that now happen on social media (e.g., “refer a friend” features and discussions in online communities) can positively affect important marketing outcomes such as new customer acquisition and sales. More recently, the value of advertising on social media continues to be explored (e.g., Gordon et al. 2019 ), as well as how it interacts with other forms of media such as television (e.g., Fossen and Schweidel 2016 , 2019 ) and affects new product adoption through diffusion of information mechanisms (e.g., Hennig-Thurau et al. 2015 ).

Although the rise (and fall) of various kinds of social media platforms has been important for understanding the social media landscape, our contention is that understanding the current situation of social media, at least from a marketing perspective, lies more in what the users do on these platforms than the technologies or services offered by these platforms. Presently, people around the world use social media in its various forms (e.g., news feeds on Facebook and Twitter, private messaging on WhatsApp and WeChat, and discussion forums on Reddit) for a number of purposes. These can generally be categorized as (1) digitally communicating and socializing with known others, such as family and friends, (2) doing the same but with unknown others but who share common interests, and (3) accessing and contributing to digital content such as news, gossip, and user-generated product reviews.

All of these use cases are essentially WOM in one form or another. This, at least, is how marketing scholars have mainly characterized social media, as discussed by Lamberton and Stephen ( 2016 ). Indeed, online WOM has been—and, we contend, will continue to be—important in marketing (e.g., in the meta-analysis by Babić Rosario et al. 2016 the authors found, on average, a positive correlation between online WOM and sales). The present perspective on social media is that people use it for creating, accessing, and spreading information via WOM to various types of others, be it known “strong ties” or “weak ties” in their networks or unknown “strangers.” Some extant research has looked at social media from the WOM perspective of the consequences of the transmission of WOM (e.g., creating a Facebook post or tweeting) on others (e.g., Herhausen et al. 2019 ; Stephen and Lehmann 2016 ), the impact of the type of WOM content shared on others’ behavior (e.g., Villarroel Ordenes et al. 2017 ; Villarroel Ordenes et al. 2018 ), and on the motivations that drive consumer posting on social media, including considerations of status and self-presentation (e.g., Grewal et al. 2019 ; Hennig-Thurau et al. 2004 ; Hollenbeck and Kaikati 2012 ; Toubia and Stephen 2013 ; Wallace et al. 2014 ).

While this current characterization of WOM appears reasonable, it considers social media only from a communications perspective (and as a type of media channel). However, as social media matures, broader social implications emerge. To appropriately consider the future, we must expand our perspective beyond the narrow communicative aspects of social media and consider instead how consumers might use it. Hence, in our vision for the future of social media in marketing in the following sections, we attempt to present a more expansive perspective of what social media is (and will become) and explain why this perspective is relevant to marketing research and practice.

Overview of framework for the future of social media in marketing

In the following sections we present a framework for the immediate, near, and far future of social media in marketing when considering various relevant stakeholders. Themes in the immediate future represent those which already exist in the current marketplace, and that we believe will continue shaping the social media landscape. The near future section examines trends that have shown early signs of manifesting, and that we believe will meaningfully alter the social media landscape in the imminent future. Finally, themes designated as being in the far future represent more speculative projections that we deem capable of long-term influence on the future of social media. The next sections delve into each of the themes in Table 1 , organized around the predicted imminence of these theme’s importance to marketing (i.e., the immediate, near, and far futures).

The immediate future

To begin our discussion on the direction of social media, in this section, we highlight three themes that have surfaced in the current environment that we believe will continue to shape the social media landscape in the immediate future. These themes—omni-social presence, the rise of influencers, and trust and privacy concerns—reflect the ever-changing digital and social media landscape that we presently face. We believe that these different areas will influence a number of stakeholders such as individual social media users, firms and brands that utilize social media, and public policymakers (e.g., governments, regulators).

Omni-social presence

In its early days, social media activity was mostly confined to designated social media platforms such as Facebook and Twitter (or their now-defunct precursors). However, a proliferation of websites and applications that primarily serve separate purposes have capitalized on the opportunity to embed social media functionality into their interfaces. Similarly, all major mobile and desktop operating systems have in-built social media integration (e.g., sharing functions built into Apple’s iOS). This has made social media pervasive and ubiquitous—and perhaps even omnipotent—and has extended the ecosystem beyond dedicated platforms.

Accordingly, consumers live in a world in which social media intersects with most aspects of their lives through digitally enabled social interactivity in such domains as travel (e.g., TripAdvisor), work (e.g., LinkedIn), food (e.g., Yelp), music (e.g., Spotify), and more. At the same time, traditional social media companies have augmented their platforms to provide a broader array of functionalities and services (e.g., Facebook’s marketplace, Chowdry 2018 ; WeChat’s payment system, Cheng 2017 ). These bidirectional trends suggest that the modern-day consumer is living in an increasingly “omni-social” world.

From a marketing perspective, the “omni-social” nature of the present environment suggests that virtually every part of a consumer’s decision-making process is prone to social media influence. Need recognition might be activated when a consumer watches their favorite beauty influencer trying a new product on YouTube. A consumer shopping for a car might search for information by asking their Facebook friends what models they recommend. A hungry employee might sift through Yelp reviews to evaluate different lunch options. A traveler might use Airbnb to book future accommodation. Finally, a highly dissatisfied (or delighted) airline passenger might rant (rave) about their experience on Twitter. While the decision-making funnel is arguably growing flatter than the aforementioned examples would imply (Cortizo-Burgess 2014 ), these independent scenarios illustrate that social media has the propensity to influence the entire consumer-decision making process, from beginning to end.

Finally, perhaps the greatest indication of an “omni-social” phenomenon is the manner in which social media appears to be shaping culture itself. YouTube influencers are now cultural icons, with their own TV shows (Comm 2016 ) and product lines (McClure 2015 ). Creative content in television and movies is often deliberately designed to be “gifable” and meme-friendly (Bereznak 2018 ). “Made-for-Instagram museums” are encouraging artistic content and experiences that are optimized for selfie-taking and posting (Pardes 2017 ). These examples suggest that social media’s influence is hardly restricted to the “online” world (we discuss the potential obsolescence of this term later in this paper), but is rather consistently shaping cultural artifacts (television, film, the arts) that transcend its traditional boundaries. We believe this trend will continue to manifest, perhaps making the term “social media” itself out-of-date, as it’s omni-presence will be the default assumption for consumers, businesses, and artists in various domains.

This omni-social trend generates many questions to probe in future research. For example, how will social interactivity influence consumer behavior in areas that had traditionally been non-social? From a practitioner lens, it might also be interesting to explore how marketers can strategically address the flatter decision-making funnel that social media has enabled, and to examine how service providers can best alter experiential consumption when anticipating social media sharing behavior.

The rise of new forms of social influence (and influencers)

The idea of using celebrities (in consumer markets) or well-known opinion leaders (in business markets), who have a high social value, to influence others is a well-known marketing strategy (Knoll and Matthes 2017 ). However, the omnipresence of social media has tremendously increased the accessibility and appeal of this approach. For example, Selena Gomez has over 144 million followers on Instagram that she engages with each of her posts. In 2018, the exposure of a single photo shared by her was valued at $3.4 million (Maxim 2018 ). However, she comes at a high price: one post that Selena sponsors for a brand can cost upwards of $800,000 (Mejia 2018 ). However, putting high valuations on mere online exposures or collecting “likes” for specific posts can be somewhat speculative, as academic research shows that acquiring “likes” on social media might have no effect on consumers’ attitudes or behaviors (John et al. 2017 ; Mochon et al. 2017 ). Moreover, Hennig-Thurau et al. ( 2015 ), show that while garnering positive WOM has little to no effect on consumer preferences, negative WOM can have a negative effect on consumer preferences.

While celebrities like Selena Gomez are possible influencers for major brands, these traditional celebrities are so expensive that smaller brands have begun, and will continue to, capitalize on the popularity and success of what are referred to as “micro-influencers,” representing a new form of influencers. Micro-influencers are influencers who are not as well-known as celebrities, but who have strong and enthusiastic followings that are usually more targeted, amounting anywhere between a few thousand to hundreds of thousands of followers (Main 2017 ). In general, these types of influencers are considered to be more trustworthy and authentic than traditional celebrities, which is a major reason influencer marketing has grown increasingly appealing to brands (Enberg 2018 ). These individuals are often seen as credible “experts” in what they post about, encouraging others to want to view the content they create and engage with them. Furthermore, using these influencers allows the brand via first person narration (compared to ads), which is considered warmer and more personal, and was shown to be more effective in engaging consumers (Chang et al. 2019 ).

Considering the possible reach and engagement influencers command on social media, companies have either begun embracing influencers on social media, or plan to expand their efforts in this domain even more. For example, in recent conversations we had with social media executives, several of them stated the growing importance of influencers and mentioned how brands generally are looking to incorporate influencer marketing into their marketing strategies. Further, recent conversations with executives at some globally leading brands suggest that influencer marketing spending by big brands continues to rise.

While influencer marketing on social media is not new, we believe it has a lot of potential to develop further as an industry. In a recent working paper, Duani et al. ( 2018 ) show that consumers enjoy watching a live experience much more and for longer time periods than watching a prerecorded one. Hence, we think live streaming by influencers will continue to grow, in broad domains as well as niche ones. For example, streaming of video game playing on Twitch, a platform owned by Amazon, may still be niche but shows no signs of slowing down. However, live platforms are limited by the fact that the influencers, being human, need to sleep and do other activities offline. Virtual influencers (i.e., “CGI” influencers that look human but are not), on the other hand, have no such limitations. They never get tired or sick, they do not even eat (unless it is needed for a campaign). Some brands have started exploring the use of virtual influencers (Nolan 2018 ), and we believe that in coming years, along with stronger computing power and artificial intelligence algorithms, virtual influencers will become much more prominent on social media, being able to invariably represent and act on brand values and engage with followers anytime.

There are many interesting future research avenues to consider when thinking about the role of influencers on social media. First, determining what traits and qualities (e.g., authenticity, trust, credibility, and likability) make sponsored posts by a traditional celebrity influencer, versus a micro-influencer, or even compared to a CGI influencer, more or less successful is important to determine for marketers. Understanding whether success has to do with the actual influencer’s characteristics, the type of content being posted, whether content is sponsored or not, and so on, are all relevant concerns for companies and social media platforms when determining partnerships and where to invest effort in influencers. In addition, research can focus on understanding the appeal of live influencer content, and how to successfully blend influencer content with more traditional marketing mix approaches.

Privacy concerns on social media

Consumer concerns regarding data privacy, and their ability to trust brands and platforms are not new (for a review on data privacy see Martin and Murphy 2017 ). Research in marketing and related disciplines has examined privacy and trust concerns from multiple angles and using different definitions of privacy. For example, research has focused on the connections between personalization and privacy (e.g., Aguirre et al. 2015 ; White et al. 2008 ), the relationship of privacy as it relates to consumer trust and firm performance (e.g., Martin 2018 ; Martin et al. 2017 ), and the legal and ethical aspects of data and digital privacy (e.g., Culnan and Williams 2009 ; Nill and Aalberts 2014 ). Despite this topic not seeming novel, the way consumers, brands, policy makers, and social media platforms are all adjusting and adapting to these concerns are still in flux and without clear resolution.

Making our understanding of privacy concerns even less straightforward is the fact that, across extant literature, a clear definition of privacy is hard to come by. In one commentary on privacy, Stewart ( 2017 ), defined privacy as “being left alone,” as this allows an individual to determine invasions of privacy. We build from this definition of privacy to speculate on a major issue in privacy and trust moving forward. Specifically, how consumers are adapting and responding to the digital world, where “being left alone” isn’t possible. For example, while research has shown benefits to personalization tactics (e.g., Chung et al. 2016 ), with eroding trust in social platforms and brands that advertise through them, many consumers would rather not share data and privacy for a more personalized experiences, are uncomfortable with their purchases being tracked and think it should be illegal for brands to be able to buy their data (Edelman 2018 ). These recent findings seem to be in conflict with previously established work on consumer privacy expectations. Therefore, understanding if previously studied factors that mitigated the negative effects of personalization (e.g., perceived utility; White et al. 2008 ) are still valued by consumers in an ever-changing digital landscape is essential for future work.

In line with rising privacy concerns, the way consumers view brands and social media is becoming increasingly negative. Consumers are deleting their social media presence, where research has shown that nearly 40% of digitally connected individuals admitted to deleting at least one social media account due to fears of their personal data being mishandled (Edelman 2018 ). This is a negative trend not only for social media platforms, but for the brands and advertisers who have grown dependent on these avenues for reaching consumers. Edelman found that nearly half of the surveyed consumers believed brands to be complicit in negative aspects of content on social media such as hate speech, inappropriate content, or fake news (Edelman 2018 ). Considering that social media has become one of the best places for brands to engage with consumers, build relationships, and provide customer service, it’s not only in the best interest of social media platforms to “do better” in terms of policing content, but the onus of responsibility has been placed on brands to advocate for privacy, trust, and the removal of fake or hateful content.

Therefore, to combat these negative consumer beliefs, changes will need to be made by everyone who benefits from consumer engagement on social media. Social media platforms and brands need to consider three major concerns that are eroding consumer trust: personal information, intellectual property and information security (Information Technology Faculty 2018 ). Considering each of these concerns, specific actions and initiatives need to be taken for greater transparency and subsequent trust. We believe that brands and agencies need to hold social media accountable for their actions regarding consumer data (e.g., GDPR in the European Union) for consumers to feel “safe” and “in control,” two factors shown necessary in cases of privacy concerns (e.g., Tucker 2014 ; Xu et al. 2012 ). As well, brands need to establish transparent policies regarding consumer data in a way that recognizes the laws, advertising restrictions, and a consumer’s right to privacy (a view shared by others; e.g., Martin et al. 2017 ). All of this is managerially essential for brands to engender feelings of trust in the increasingly murky domain of social media.

Future research can be conducted to determine consumer reactions to different types of changes and policies regarding data and privacy. As well, another related and important direction for future research, will be to ascertain the spillover effects of distrust on social media. Specifically, is all content shared on social media seen as less trustworthy if the platform itself is distrusted? Does this extend to brand messages displayed online? Is there a negative spillover effect to other user-generated content shared through these platforms?

The near future

In the previous section, we discussed three areas where we believe social media is immediately in flux. In this section, we identify three trends that have shown early signs of manifesting, and which we believe will meaningfully alter the social media landscape in the near, or not-too-distant, future. Each of these topics impact the stakeholders we mentioned when discussing the immediate social media landscape.

Combatting loneliness and isolation

Social media has made it easier to reach people. When Facebook was founded in 2004, their mission was “to give people the power to build community and bring the world closer together... use Facebook to stay connected with friends and family, to discover what’s going on in the world, and to share and express what matters to them” (Facebook 2019 ). Despite this mission, and the reality that users are more “connected” to other people than ever before, loneliness and isolation are on the rise. Over the last fifty years in the U.S., loneliness and isolation rates have doubled, with Generation Z considered to be the loneliest generation (Cigna 2018 ). Considering these findings with the rise of social media, is the fear that Facebook is interfering with real friendships and ironically spreading the isolation it was designed to conquer something to be considered about (Marche 2012 )?

The role of social media in this “loneliness epidemic” is being hotly debated. Some research has shown that social media negatively impacts consumer well-being. Specifically, heavy social media use has been associated with higher perceived social isolation, loneliness, and depression (Kross et al. 2013 ; Primack et al. 2017 ; Steers et al. 2014 ). Additionally, Facebook use has been shown to be negatively correlated with consumer well-being (Shakya and Christakis 2017 ) and correlational research has shown that limiting social media use to 10 min can decrease feelings of loneliness and depression due to less FOMO (e.g., “fear of missing out;” Hunt et al. 2018 ).

On the other hand, research has shown that social media use alone is not a predictor of loneliness as other factors have to be considered (Cigna 2018 ; Kim et al. 2009 ). In fact, while some research has shown no effect of social media on well-being (Orben et al. 2019 ), other research has shown that social media can benefit individuals through a number of different avenues such as teaching and developing socialization skills, allowing greater communication and access to a greater wealth of resources, and helping with connection and belonging (American Psychological Association 2011 ; Baker and Algorta 2016 ; Marker et al. 2018 ). As well, a working paper by Crolic et al. ( 2019 ) argues that much of the evidence of social media use on consumer well-being is of questionable quality (e.g., small and non-representative samples, reliance on self-reported social media use), and show that some types of social media use are positively associated with psychological well-being over time.

Managerially speaking, companies are beginning to respond as a repercussion of studies highlighting a negative relationship between social media and negative wellbeing. For example, Facebook has created “time limit” tools (mobile operating systems, such as iOS, now also have these time-limiting features). Specifically, users can now check their daily times, set up reminder alerts that pop up when a self-imposed amount of time on the apps is hit, and there is the option to mute notifications for a set period of time (Priday 2018 ). These different features seem well-intentioned and are designed to try and give people a more positive social media experience. Whether these features will be used is unknown.

Future research can address whether or not consumers will use available “timing” tools on one of many devices in which their social media exists (i.e., fake self-policing) or on all of their devices to actually curb behavior. It could also be the case that users will actually spend less time on Facebook and Instagram, but possibly spend that extra time on other competing social media platforms, or attached to devices, which theoretically will not help combat loneliness. Understanding how (and which) consumers use these self-control tools and how impactful they are is a potentially valuable avenue for future research.

One aspect of social media that has yet to be considered in the loneliness discussion through empirical measures, is the quality of use (versus quantity). Facebook ads have begun saying, “The best part of Facebook isn’t on Facebook. It’s when it helps us get together” (Facebook 2019 ). There have been discussions around the authenticity of this type of message, but at its core, in addition to promoting quantity differences, it’s speaking to how consumers use the platform. Possibly, to facilitate this message, social media platforms will find new ways to create friend suggestions between individuals who not only share similar interests and mutual friends to facilitate in-person friendships (e.g., locational data from the mobile app service). Currently there are apps that allow people to search for friends that are physically close (e.g., Bumble Friends), and perhaps social media will go in this same direction to address the loneliness epidemic and stay current.

Future research can examine whether the quantity of use, types of social media platforms, or the way social media is used causally impacts perceived loneliness. Specifically, understanding if the negative correlations found between social media use and well-being are due to the demographics of individuals who use a lot of social media, the way social media works, or the way users choose to engage with the platform will be important for understanding social media’s role (or lack of role) in the loneliness epidemic.

Integrated customer care

Customer care via digital channels as we know it is going to change substantially in the near future. To date, many brands have used social media platforms as a place for providing customer care, addressing customers’ specific questions, and fixing problems. In the future, social media-based customer care is expected to become even more customized, personalized, and ubiquitous. Customers will be able to engage with firms anywhere and anytime, and solutions to customers’ problems will be more accessible and immediate, perhaps even pre-emptive using predictive approaches (i.e., before a customer even notices an issue or has a question pop into their mind).

Even today, we observe the benefits that companies gain from connecting with customers on social media for service- or care-related purposes. Customer care is implemented in dedicated smartphone apps and via direct messaging on social media platforms. However, it appears that firms want to make it even easier for customers to connect with them whenever and wherever they might need. Requiring a customer to download a brand specific app or to search through various social media platforms to connect with firms through the right branded account on a platform can be a cumbersome process. In those cases, customers might instead churn or engage in negative WOM, instead of connecting with the firm to bring up any troubles they might have.

The near future of customer care on social media appears to be more efficient and far-reaching. In a recent review on the future of customer relationship management, Haenlein ( 2017 ) describes “invisible CRM” as future systems that will make customer engagement simple and accessible for customers. New platforms have emerged to make the connection between customer and firm effortless. Much of this is via instant messaging applications for businesses, which several leading technology companies have recently launched as business-related features in existing platforms (e.g., contact business features in Facebook Messenger and WhatsApp or Apple’s Business Chat).

These technologies allow businesses to directly communicate via social media messaging services with their customers. Amazon, Apple, Facebook, and Google are in the process, or have already released early versions of such platforms (Dequier 2018 ). Customers can message a company, ask them questions, or even order products and services through the messaging system, which is often built around chatbots and virtual assistants. This practice is expected to become more widespread, especially because it puts brands and companies into the social media messaging platforms their customers already use to communicate with others, it provides quicker—even instantaneous—responses, is economically scalable through the use of AI-driven chatbots, and, despite the use of chatbots, can provide a more personalized level of customer service.

Another area that companies will greatly improve upon is data collection and analysis. While it is true that data collection on social media is already pervasive today, it is also heavily scrutinized. However, we believe that companies will adapt to the latest regulation changes (e.g., GDPR in Europe, CCPA in California) and improve on collecting and analyzing anonymized data (Kakatkar and Spann 2018 ). Furthermore, even under these new regulations, personalized data collection is still allowed, but severely limits firm’s abilities to exploit consumers’ data, and requires their consent for data collection.

We believe that in the future, companies will be able recognize early indications of problems within customer chatter, behavior, or even physiological data (e.g., monitoring the sensors in our smart watches) before customers themselves even realize they are experiencing a problem. For example, WeWork, the shared workspace company, collects data on how workers move and act in a workspace, building highly personalized workspaces based on trends in the data. Taking this type of approach to customer care will enable “seamless service,” where companies would be able to identify and address consumer problems when they are still small and scattered, and while only a small number of customers are experiencing problems. Customer healthcare is a pioneer in this area, where using twitter and review sites were shown to predict poor healthcare quality (Greaves et al. 2013 ), listen to patients to analyze trending terms (Baktha et al. 2017 ; Padrez et al. 2016 ), or even predict disease outbreaks (Schmidt 2012 ).

Companies, wanting to better understand and mimic human interactions, will invest a lot of R&D efforts into developing better Natural Language Processing, voice and image recognition, emotional analysis, and speech synthesis tools (Sheth 2017 ). For example, Duplex, Google’s latest AI assistant, can already call services on its own and seamlessly book reservations for their users (Welch 2018 ). In the future, AI systems will act as human ability augmenters, allowing us to accomplish more, in less time, and better results (Guszcza 2018 ).

For marketers, this will reduce the need for call centers and agents, reducing points of friction in service and increasing the convenience for customers (Kaplan and Haenlein 2019 ). However, some raise the question that the increased dependence on automation may result in a loss of compassion and empathy. In a recent study, Force (2018) shows that interacting with brands on social media lowered people’s empathy. In response to such concerns, and to educate and incentivize people to interact with machines in a similar way they do with people, Google programmed their AI assistant to respond in a nicer way if you use a polite, rather than a commanding approach (Kumparak 2018 ). While this might help, more research is needed to understand the effect of an AI rich world on human behavior. As well, future research can examine how consumer generated data can help companies preemptively predict consumer distress. Another interesting path for research would be to better understand the difference in consumer engagement between the various platforms, and the long-term effects of service communications with non-human AI and IoT.

Social media as a political tool

Social media is a platform to share thoughts and opinions. This is especially true in the case of disseminating political sentiments. Famously, President Barack Obama’s victory in the 2008 election was partially attributed to his ability to drive and engage voters on social media (Carr 2008 ). Indeed, Bond et al. ( 2012 ) have shown that with simple interventions, social media platforms can increase targeted audiences’ likelihood of voting. Social media is considered one of the major drivers of the 2010 wave of revolutions in Arab countries, also known as the Arab Spring (Brown et al. 2012 ).

While social media is not new to politics, we believe that social media is transitioning to take a much larger role as a political tool in the intermediate future. First evidence for this could be seen in the 2016 U.S. presidential election, as social media took on a different shape, with many purported attempts to influence voter’s opinions, thoughts, and actions. This is especially true for then-candidate and now-President Donald Trump. His use of Twitter attracted a lot of attention during the campaign and has continued to do so during his term in office. Yet, he is not alone, and many politicians changed the way they work and interact with constituents, with a recent example of Congresswoman Alexandria Ocasio-Cortez that even ran a workshop for fellow congress members on social media (Dwyer 2019 ).

While such platforms allow for a rapid dissemination of ideas and concepts (Bonilla and Rosa 2015 ; Bode 2016 ), there are some, both in academia and industry that have raised ethical concerns about using social media for political purposes. Given that people choose who to follow, this selective behavior is said to potentially create echo chambers, wherein, users are exposed only to ideas by like-minded people, exhibiting increased political homophily (Bakshy et al. 2015 ). People’s preference to group with like-minded people is not new. Social in-groups have been shown to promote social identification and promote in-group members to conform to similar ideas (Castano et al. 2002 ; Harton and Bourgeois 2004 ). Furthermore, it was also shown that group members strongly disassociate and distance themselves from outgroup members (Berger and Heath 2008 ; White and Dahl 2007 ). Thus, it is not surprising to find that customized newsfeeds within social media exacerbate this problem by generating news coverage that is unique to specific users, locking them in their purported echo chambers (Oremus 2016 ).

While social media platforms admit that echo chambers could pose a problem, a solution is not clear (Fiegerman 2018 ). One reason that echo chambers present such a problem, is their proneness to fake news. Fake news are fabricated stories that try to disguise themselves as authentic content, in order to affect other social media users. Fake news was widely used in the 2016 U.S. elections, with accusations that foreign governments, such as Iran and Russia, were using bots (i.e., online automatic algorithms), to spread falsified content attacking Hillary Clinton and supporting President Trump (Kelly et al. 2018 ). Recent research has furthermore shown how the Chinese government strategically uses millions of online comments to distract the Chinese public from discussing sensitive issues and promote nationalism (King et al. 2017 ). In their latest incarnation, fake news uses an advanced AI technique called “Deep Fake” to generate ultra-realistic forged images and videos of political leaders while manipulating what those leaders say (Schwartz 2018 ). Such methods can easily fool even the sharpest viewer. In response, research has begun to explore ways that social media platforms can combat fake news through algorithms that determine the quality of shared content (e.g., Pennycook and Rand 2019 ).

One factor that has helped the rise of fake news is echo chambers. This occurs as the repeated sharing of fake news by group members enhance familiarity and support (Schwarz and Newman 2017 ). Repetition of such articles by bots can only increase that effect. Recent research has shown that in a perceived social setting, such as social media, participants were less likely to fact-check information (Jun et al. 2017 ), and avoided information that didn’t fit well with their intuition (Woolley and Risen 2018 ). Schwarz and Newman ( 2017 ) state that misinformation might be difficult to correct, especially if the correction is not issued immediately and the fake news has already settled into the minds of users. It was also shown that even a single exposure to fake news can create long term effect on users, making their effect larger than previously thought (Pennycook et al. 2019 ).

Notably, some research has found that exposure to opposing views (i.e., removing online echo chambers) may in fact increase (versus decrease) polarization (Bail et al. 2018 ). Accordingly, more work from policy makers, businesses, and academics is needed to understand and potentially combat political extremism. For example, policy makers and social media platforms will continually be challenged to fight “fake news” without censoring free speech. Accordingly, research that weighs the risk of limited freedom of expression versus the harms of spreading fake news would yield both theoretical and practically meaningful insights.

The far future

In this section, we highlight three emerging trends we believe will have a have long-term influence on the future of social media. Note that although we label these trends as being in the “far” future, many of the issues described here are already present or emerging. However, they represent more complex issues that we believe will take longer to address and be of mainstream importance for marketing than the six issues discussed previously under the immediate and near futures.

Increased sensory richness

In its early days, the majority of social media posts (e.g., on Facebook, Twitter) were text. Soon, these platforms allowed for the posting of pictures and then videos, and separate platforms dedicated themselves to focus on these specific forms of media (e.g., Instagram and Pinterest for pictures, Instagram and SnapChat for short videos). These shifts have had demonstrable consequences on social media usage and its consequences as some scholars suggest that image-based posts convey greater social presence than text alone (e.g., Pittman and Reich 2016 ). Importantly however, a plethora of new technologies in the market suggest that the future of social media will be more sensory-rich.

One notable technology that has already started infiltrating social media is augmented reality (AR). Perhaps the most recognizable examples of this are Snapchat’s filters, which use a device’s camera to superimpose real-time visual and/or video overlays on people’s faces (including features such as makeup, dog ears, etc.). The company has even launched filters to specifically be used on users’ cats (Ritschel 2018 ). Other social media players quickly joined the AR bandwagon, including Instagram’s recent adoption of AR filters (Rao 2017 ) and Apple’s Memoji messaging (Tillman 2018 ). This likely represents only the tip of the iceberg, particularly given that Facebook, one of the industry’s largest investors in AR technology, has confirmed it is working on AR glasses (Constine 2018 ). Notably, the company plans to launch a developer platform, so that people can build augmented-reality features that live inside Facebook, Instagram, Messenger and Whatsapp (Wagner 2017 ). These developments are supported by academic research suggesting that AR often provides more authentic (and hence positive) situated experiences (Hilken et al. 2017 ). Accordingly, whether viewed through glasses or through traditional mobile and tablet devices, the future of social media is likely to look much more visually augmented.

While AR allows users to interact within their current environments, virtual reality (VR) immerses the user in other places, and this technology is also likely to increasingly permeate social media interactions. While the Facebook-owned company Oculus VR has mostly been focusing on the areas of immersive gaming and film, the company recently announced the launch of Oculus Rooms where users can spend time with other users in a virtual world (playing games together, watching media together, or just chatting; Wagner 2018 ). Concurrently, Facebook Spaces allows friends to meet online in virtual reality and similarly engage with one another, with the added ability to share content (e.g., photos) from their Facebook profiles (Whigham 2018 ). In both cases, avatars are customized to represent users within the VR-created space. As VR technology is becoming more affordable and mainstream (Colville 2018 ) we believe social media will inevitably play a role in the technology’s increasing usage.

While AR and VR technologies bring visual richness, other developments suggest that the future of social media might also be more audible. A new player to the social media space, HearMeOut, recently introduced a platform that enables users to share and listen to 42-s audio posts (Perry 2018 ). Allowing users to use social media in a hands-free and eyes-free manner not only allows them to safely interact with social media when multitasking (particularly when driving), but voice is also said to add a certain richness and authenticity that is often missing from mere text-based posts (Katai 2018 ). Given that podcasts are more popular than ever before (Bhaskar 2018 ) and voice-based search queries are the fastest-growing mobile search type (Robbio 2018 ), it seems likely that this communication modality will accordingly show up more on social media use going forward.

Finally, there are early indications that social media might literally feel different in the future. As mobile phones are held in one’s hands and wearable technology is strapped onto one’s skin, companies and brands are exploring opportunities to communicate to users through touch. Indeed, haptic feedback (technology that recreates the sense of touch by applying forces, vibrations, or motions to the user; Brave et al. 2001 ) is increasingly being integrated into interfaces and applications, with purposes that go beyond mere call or message notifications. For example, some companies are experimenting with integrating haptics into media content (e.g., in mobile ads for Stoli vodka, users feel their phone shake as a woman shakes a cocktail; Johnson 2015 ), mobile games, and interpersonal chat (e.g., an app called Mumble! translates text messages into haptic outputs; Ozcivelek 2015 ). Given the high levels of investment into haptic technology (it is predicted to be a $20 billion industry by 2022; Magnarelli 2018 ) and the communicative benefits that stem from haptic engagement (Haans and IJsselsteijn 2006 ), we believe it is only a matter of time before this modality is integrated into social media platforms.

Future research might explore how any of the new sensory formats mentioned above might alter the nature of content creation and consumption. Substantively-focused researchers might also investigate how practitioners can use these tools to enhance their offerings and augment their interactions with customers. It is also interesting to consider how such sensory-rich formats can be used to bridge the gap between the online and offline spaces, which is the next theme we explore.

Online/offline integration and complete convergence

A discussion occurring across industry and academia is on how marketers can appropriately integrate online and offline efforts (i.e., an omnichannel approach). Reports from industry sources have shown that consumers respond better to integrated marketing campaigns (e.g., a 73% boost over standard email campaigns; Safko 2010 ). In academia meanwhile, the majority of research considering online promotions and advertisements has typically focused on how consumers respond to these strategies through online only measures (e.g., Manchanda et al. 2006 ), though this has begun to change in recent years with more research examining offline consequences to omnichannel strategies (Lobschat et al. 2017 ; Kumar et al. 2017 ).

Considering the interest in integrated marketing strategies over the last few years, numerous strategies have been utilized to follow online and offline promotions and their impacts on behavior such as the usage of hashtags to bring conversations online, call-to-actions, utilizing matching strategies on “traditional” avenues like television with social media. While there is currently online/offline integration strategies in marketing, we believe the future will go even further in blurring the lines between what is offline and online to not just increase the effectiveness of marketing promotions, but to completely change the way customers and companies interact with one another, and the way social media influences consumer behavior not only online, but offline.

For brands, there are a number of possible trends in omnichannel marketing that are pertinent. As mentioned earlier, a notable technology that has begun infiltrating social media is augmented reality (AR). In addition to what already exists (e.g., Snapchat’s filters, Pokémon Go), the future holds even more possibilities. For example, Ikea has been working to create an AR app that allows users to take photos of a space at home to exactly , down to the millimeter size and lighting in the room, showcase what a piece of furniture would look like in a consumer’s home (Lovejoy 2017 ). Another set of examples of AR comes from beauty company L’Oréal. In 2014 for the flagship L’Oréal Paris brand they released a mobile app called Makeup Genius that allowed consumers to virtually try on makeup on their phones (Stephen and Brooks 2018 ). Since then, they have developed AR apps for hair color and nail polish, as well as integrating AR into mobile ecommerce webpages for their luxury beauty brand Lancôme. AR-based digital services such as these are likely to be at the heart of the next stage of offline/online integration.

AR, and similar technology, will likely move above and beyond being a tool to help consumers make better decisions about their purchases. Conceivably, similar to promotions that currently exist to excitse consumers and create communities, AR will be incorporated into promotions that integrate offline and online actions. For example, contests on social media will advance to the stage where users get to vote on the best use of AR technology in conjunction with a brand’s products (e.g., instead of users submitting pictures of their apartments to show why they should win free furniture, they could use AR to show how they would lay out the furniture if they were to win it from IKEA).

Another way that the future of online/offline integration on social media needs to be discussed is in the sense of a digital self. Drawing on the extended self in the digital age (Belk 2013 ), the way consumers consider online actions as relevant to their offline selves may be changing. For example, Belk ( 2013 ) spoke of how consumers may be re-embodied through avatars they create to represent themselves online, influencing their offline selves and creating a multiplicity of selves (i.e., consumers have more choice when it comes to their self-representation). As research has shown how digital and social media can be used for self-presentation, affiliation, and expression (Back et al. 2010 ; Gosling et al. 2007 ; Toubia and Stephen 2013 ; Wilcox and Stephen 2012 ), what does it mean for the future if consumers can create who they want to be?

In addition, when considering digital selves, what does this mean for how consumers engage with brands and products? Currently, social media practice is one where brands encourage consumer engagement online (Chae et al. 2017 ; Godes and Mayzlin 2009 ), yet the implications for how these types of actions on the part of the brand to integrate online social media actions and real-life behavior play out are unclear. Research has begun to delve into the individual-level consequences of a consumer’s social media actions on marketing relevant outcomes (Grewal et al. 2019 ; John et al. 2017 ; Mochon et al. 2017 ; Zhang et al. 2017 ), however much is still unknown. As well, while there is recent work examining how the device used to create and view content online impacts consumer perceptions and behaviors (e.g., Grewal and Stephen 2019 ), to date research has not examined these questions in the context of social media. Therefore, future research could address how digital selves (both those held offline and those that only exist online), social media actions, and if the way consumers reach and use various platforms (i.e., device type, app vs. webpage, etc.) impact consumer behavior, interpersonal relationships, and brand-related measures (e.g., well-being, loyalty, purchase behaviors).

Social media by non-humans

The buzz surrounding AI has not escaped social media. Indeed, social bots (computer algorithms that automatically produce content and interact with social media users; Ferrara et al. 2016 ) have inhabited social media platforms for the last decade (Lee et al. 2011 ), and have become increasingly pervasive. For example, experts estimate that up to 15% of active Twitter accounts are bots (Varol et al. 2017 ), and that percentage appears to be on the rise (Romano 2018 ). While academics and practitioners are highly concerned with bot detection (Knight 2018 ), in the vast majority of current cases, users do not appear to recognize when they are interacting with bots (as opposed to other human users) on social media (Stocking and Sumida 2018 ). While some of these bots are said to be benign, and even useful (e.g., acting as information aggregators), they have also been shown to disrupt political discourse (as mentioned earlier), steal personal information, and spread misinformation (Ferrara et al. 2016 ).

Of course, social bots are not only a problem for social media users but are also a nagging concern plaguing marketers. Given that companies often assess marketing success on social media through metrics like Likes, Shares, and Clicks, the existence of bots poses a growing threat to accurate marketing metrics and methods for ROI estimation, such as attribution modelling (Bilton 2014 ). Similarly, when these bots act as “fake followers,” it can inflate the worth of influencers’ audiences (Bogost 2018 ). This can also be used nefariously by individuals and firms, as shown in a New York Times Magazine expose that documented the market used by some influencers to purchase such “fake” followers to inflate their social media reach (Confessore et al. 2018 ). As discussed above in relation to influencer marketing, where it has been commonplace for influencers to be paid for posts at rates proportionate to their follower counts, there have been perverse incentives to game the system by having non-human “fake” bot followers. This, however, erodes consumer trust in the social media ecosystem, which is a growing issue and a near-term problem for many firms using social media channels for marketing purposes.

However, there are instances when consumers do know they are interacting with bots, and do not seem to mind. For example, a number of virtual influencers (created with CGI, as mentioned earlier) seem to be garnering sizeable audiences, despite the fact they are clearly non-human (Walker 2018 ). One of the most popular of these virtual influencers, Lil Miquela, has over 1.5 million followers on Instagram despite openly confessing, “I am not a human being... I’m a robot” (Yurieff 2018 ). Future research might try to understand the underlying appeal of these virtual influencers, and the potential boundary conditions of their success.

Another category of social bots gaining increasing attention are therapy bots. These applications (e.g., “Woebot;” Molteni 2017 ) aim to support the mental health of users by proactively checking in on them, “listening” and chatting to users at any time and recommending activities to improve users’ wellbeing (de Jesus 2018 ). Similar bots are being used to “coach” users, and help them quit maladaptive behaviors, like smoking (e.g., QuitGenius; Crook 2018 ). Interestingly, by being explicitly non-human, these agents are perceived to be less judgmental, and might accordingly be easier for users to confide in.

Finally, the Internet of Things revolution has ushered in with it the opportunity for a number of tangible products and interfaces to “communicate” via social media. For example, in what started as a design experiment, “Brad,” a connected toaster, was given the ability to “communicate” with other connected toasters, and to tweet his “feelings” when neglected or under-used (Vanhemert 2014 ). While this experiment was deliberately designed to raise questions about the future of consumer-product relationships (and product-product “relationships”), the proliferation of autonomous tangible devices does suggest a future in which they have a “voice,” even in the absence of humans (Hoffman and Novak 2018 ).

Going forward, we believe the presence of bots on social media will be more normalized, but also more regulated (e.g., a recent law passed in California prevents bots from masquerading as humans; Smith 2018 ). Further, consumers and companies alike will be become increasingly interested in how bots communicate and interact with each other outside of human involvement. This brings up interesting potential research questions for academics and practitioners alike. How will the presence of non-humans change the nature of content creation and conversation in social media? And how should companies best account for the presence of non-humans in their attribution models?

Future research directions and conclusion

This article has presented nine themes pertinent to the future of social media as it relates to (and is perhaps influenced by) marketing. The themes have implications for individuals/consumers, businesses and organizations, and also public policymakers and governments. These themes, which represent our own thinking and a synthesis of views from extant research, industry experts, and popular public discourse, are of course not the full story of what the future of social media will entail. They are, however, a set of important issues that we believe will be worth considering in both academic research and marketing practice.

To stimulate future research on these themes and related topics, we present a summary of suggested research directions in Table 2 . These are organized around our nine themes and capture many of the suggested research directions mentioned earlier. As a sub-field within the field of marketing, social media is already substantial and the potential for future research—based on identified needs for new knowledge and answers to perplexing questions—suggests that this sub-field will become even more important over time. We encourage researchers to consider the kinds of research directions in Table 2 as examples of issues they could explore further. We also encourage researchers in marketing to treat social media as a place where interesting (and often very new) consumer behaviors exist and can be studied. As we discussed earlier in the paper, social media as a set of platform businesses and technologies is interesting, but it is how people use social media and the associated technologies that is ultimately of interest to marketing academics and practitioners. Thus, we urge scholars to not be overly enticed by the technological “shiny new toys” at the expense of considering the behaviors associated with those technologies and platforms.

Finally, while we relied heavily (though not exclusively) on North American examples to illustrate the emergent themes, there are likely interesting insights to be drawn by explicitly exploring cross-cultural differences in social media usage. For example, variations in regulatory policies (e.g., GDPR in the European Union) may lead to meaningful differences in how trust and privacy concerns manifest. Further, social media as a political tool might be more influential in regions where the mainstream media is notoriously government controlled and censored (e.g., as was the case in many of the Arab Spring countries). While such cross-cultural variation is outside the scope of this particular paper, we believe it represents an area of future research with great theoretical and practical value.

In reviewing the social media ecosystem and considering where it is heading in the context of consumers and marketing practice, we have concluded that this is an area that is very much still in a state of flux. The future of social media in marketing is exciting, but also uncertain. If nothing else, it is vitally important that we better understand social media since it has become highly culturally relevant, a dominant form of communication and expression, a major media type used by companies for advertising and other forms of communication, and even has geopolitical ramifications. We hope that the ideas discussed here stimulate many new ideas and research, which we ultimately hope to see being mentioned and shared across every type of social media platform.

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Acknowledgements

The authors thank the special issue editors and reviewers for their comments, and the Oxford Future of Marketing Initiative for supporting this research. The authors contributed equally and are listed in alphabetical order or, if preferred, order of Marvel superhero fandom from highest to lowest and order of Bon Jovi fandom from lowest to highest.

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Appel, G., Grewal, L., Hadi, R. et al. The future of social media in marketing. J. of the Acad. Mark. Sci. 48 , 79–95 (2020). https://doi.org/10.1007/s11747-019-00695-1

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Journal of Marketing Call for Papers: Marketing Impact with Research-Driven Apps

Special Issue: Journal of Marketing

Special Issue Editors: Pradeep Chintagunta (University of Chicago), Rajdeep Grewal (University of North Carolina–Chapel Hill), Detelina Marinova (University of Missouri), Rik Pieters (Tilburg University), and Shrihari Sridhar (Texas A&M University)

Marketing scholarship has the potential to benefit society, advance managerial practice, improve consumers’ lives, and contribute to fundamental scientific knowledge.

However, given the typical form and function of academic publications in the discipline, the target audience of marketing academic research (consumers, investors, firms, frontline/middle/senior management, policy makers, as well as other marketing scholars and students) face barriers to understand and adopt research findings. These barriers limit the impact of marketing academic research.

The Journal of Marketing ’s vision is to encourage a wide range of approaches that can reduce impact barriers of academic articles and consequently catalyze the message among the target audience to whom marketing scholarship should matter.

This special issue of Journal of Marketing , titled “Marketing Impact with Research-Driven Apps,” emphasizes the integration of research-driven apps into academic articles to enhance understanding, consumption, adoption, and ongoing usage of research findings.

Pradeep Chintagunta, Rajdeep Grewal, Detelina Marinova, Rik Pieters, and Shrihari Sridhar will co-edit the special issue. The editors will not submit manuscripts to the special issue.

Research-Driven Apps

A research-driven app is an online interactive tool that provides a deeper understanding of the usability of the research contribution . It serves as a dynamic computational supplement to a research manuscript, thereby adding form and function to the otherwise static nature of a research publication.

Rather than simply adding an app to the end of an otherwise traditional research manuscript (problem, idea, intended contribution, theory, data, findings, conclusions, discussion, recommendations, and future research), submissions should think of their online interactive tool’s intended usability and implementation as the focal point of research. In this way, developing apps for marketing academic research may stimulate a solution-based mindset among marketing scholars that is reflected in their research output.

An app’s goal depends intricately on the scope and goals of the original research manuscript. The special issue encourages apps with a substantive focus covering a wide variety of approaches, paradigms, questions, and topics. While not exhaustive, the following list presents some types of apps well-suited to marketing academic research:

Disaggregating the strength of the behavioral effects under various conditions (e.g., three-way interactions) and depicting their underlying process;
Simulating game theory–based results (e.g., equilibrium outcomes) assuming various hypothetical primitives; and
Offering what-if predictions to various types of marketing interventions (e.g., targeted advertising) under well-defined market scenarios.
Recommending a range of marketing mix decision criteria that maximize or minimize firms’ marketing outcomes;
Offering customized plans, schedules, or interventions that help customers mitigate or enhance their life outcomes; and
Simulating marketing interventions that maximize or minimize societal outcomes.
Providing empirical results to a substantive problem across a range of subsamples and estimation methodologies;
Automating critical synthesis of extant literature across several subtopics; and
Providing interactive access to a large set of variables that accompany (but are not focal to) the specific research question studied in the manuscript.
Scoring unstructured data (e.g., text, video) to uncover novel marketing insights (e.g., authenticity, complexity); and
Modifying sample unstructured marketing input (e.g., sales pitches) into more effective unstructured material based on uncovering underlying characteristics.

Special Issue Submission Requirements

We encourage submissions similar to traditional marketing academic manuscripts submitted to Journal of Marketing that focus on novel, important, and substantive marketing topics. In addition, submissions to the special issue should include a new section titled “App Implementation.” In this section, the author(s) should:

Describe the problem solved by the app and how it supplements the research contribution of the manuscript.
Define the audience or the end users targeted by the app and the usefulness of the app to this audience over and above the current situation or available (software or other) solutions. The audience can be broad and include managers, executives, researchers, consumers, policy makers, government, media, general public, other marketing academics, and students.
Provide a secure, anonymous relatively permanent link to the app, with appropriate instructions on how to use the app and interpret the results.
Share open-source access to the app to allow accelerated dissemination upon publication. [1]

Ideally, the app implementation informs the problem statement and intended contribution of the research and manuscript.

The evaluation of manuscripts submitted for the special issue will be guided by the following:

The quality and veracity of the manuscript’s original contribution, like all manuscripts submitted to the Journal of Marketing . Thus, the app cannot substitute for the incremental contribution and validity of the original contribution.
The contribution of the app relative to alternative apps or commercial software solutions. For example, an existing implementation in software such as R, Python, or Matlab, would reduce the contribution of the app.
The usefulness and depth of insight enabled by the app itself. Authors are welcome to provide evidence for and/or demonstration of the application and effectiveness of the app in the field.

[1] AMA is working on obtaining official clearance that papers published in the special issue will (1) maintain status quo regarding copyright with the journal article, (2) allow the authors to retain ownership over their individual app’s intellectual property, and (3) ensure AMA has clear rights to house/distribute the app at no cost on behalf of the authors.

Special Issue Timeline

The timeline of the special issue is as follows:

Frequently Asked Questions

A research-driven app is an online interactive tool that provides a deeper understanding of the usability of the research contribution. It serves as a dynamic computational supplement to a research manuscript, thereby adding form and function to the otherwise static nature of a research publication.

Warren Nooshin L., Matthew Farmer, Tianyu Gu, and Caleb Warren (2021), “ Marketing Ideas: How to Write Research Articles that Readers Understand and Cite ,” Journal of Marketing , 85(5), 42–57. The goal of the article is to supplement the manuscript’s overarching goal to recognize and repair unclear writing to authors write more impactful articles.

Accordingly, the research-driven app accompanying the paper ( http://writingclaritycalculator.com/ ) uses the underlying method proposed in the paper to analyze input text and output scores pertaining to the concreteness of writing, number of examples, the percentage of sentences that use active voice etc.

Thus, the writing clarity calculator serves as a dynamic computational supplement to a research manuscript, thereby adding form and function to the otherwise static nature of the research publication.

We believe there could be different types of apps based on their purpose as well the research question.

Predictors offer model-based predictions and thereby depict the interplay among various factors affecting a marketing input, process, or outcome.
Optimizers offer normative solutions to improve currently suboptimal marketing decisions made by agents, and recommenders offer superior solutions to current problems marketing stakeholders face.
Explorers investigate sensitivity of research results to various research design assumptions.
Converters provide accessible marketing insights through the conversion of unstructured input (e.g., text, audio, videos) to structured data, and models developed in the research framework.

In the call for papers, we provide a non-exhaustive list of types of apps well-suited to marketing academic research.

That’s right. The special issue emphasizes the integration of research-driven apps into academic articles to enhance understanding, consumption, adoption, and ongoing usage of research findings. In other words, you could pursue research on any substantive marketing problem .

Papers submitted to the Special Issue will be identical in form to regular issues but for one additional requirement. Submissions to the special issue should include a new section titled “App Implementation.” In this section, the author(s) should:

Share open-source access to the app to allow accelerated dissemination upon publication.
Confirm during the submission process that any hyperlinks in the paper (especially to sites such as OSF, AsPredicted) lead to anonymized material that does not reveal the identity of the authors.

The short answer is no. We are only interested in a working app that serves as a companion to the paper. Our goal is to encourage submissions where the online interactive tool’s intended usability and implementation is intricately intertwined with the focal research goal. In this way, developing apps for marketing academic research may stimulate a solution-based mindset among marketing scholars that is reflected in their research output.

The American Marketing Association is working on obtaining official clearance that papers published in the special issue will (1) maintain status quo regarding copyright with the journal article but (2) allow the authors to retain ownership over their individual app’s intellectual property.

No, JM does not require you to provide your source code to the app. However, (1) all articles published in JM will require compliance to the JM Policy for Research Transparency to ensure correctness, and (2) if you would like to do so, JM will facilitate the distribution through the Special Issue website.

During the review process, the authors are asked to provide a secure, anonymous, relatively permanent link to the app, with appropriate instructions on how to use it and interpret the results. Upon acceptance, AMA will house/distribute the app for three years at no cost on behalf of the authors.

We are currently working with the AMA on this issue and hope to at least secure an extended window of open access so that researchers and practitioners from around the world can access the article for free.

We encourage users of the app (e.g., practitioners) to engage with/consult the authors before implementing the app for commercial purposes. This will not only help companies engage directly with the inventors of the app but also help users clarify the necessary assumptions, bounds, and contingencies associated with the deployment of the app in their setting.

No. The evaluation of manuscripts submitted for the special issue will firstly be guided by the quality and veracity of the manuscript’s original contribution, like all manuscripts submitted to the Journal of Marketing . Thus, the app cannot substitute for the incremental contribution and validity of the original contribution.

It is probably not sufficient if the app is mostly an accessible database-and-mini-analysis tool. It then replaces standard SPSS, Stata, or similar statistical packages without adding sufficient novelty.

Probably not. The app needs to be associated with an incremental contribution and hence have sufficient novelty over and above existing knowledge in marketing.

Absolutely. Journal of Marketing will host an online workshop in November 2022 that will feature demonstrations by experts to help participants get started on their journey to build apps for their own research. Since we are entering a new era of research driven by apps, we believe we are all part of this continuous, exciting, and vibrant new learning opportunity!

The manuscript submission window opens on 4/1/2023. During the manuscript submission process, authors will be required to submit the following: (1) a brief description of how the paper enhances the app (200 words) and (2) a brief description of how the app enhances the paper (200 words). The manuscript submission window closes on 9/30/2023. We expect the special issue in print and published manuscripts and promotion of apps to occur in Spring 2025.

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To facilitate the creation of research-driven apps, JM is pleased to offer two app tutorial videos recorded by ERB members :

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Published: 27 March 2024

A global timekeeping problem postponed by global warming

Duncan Carr Agnew ORCID: orcid.org/0000-0002-2360-7783 1

Nature ( 2024 ) Cite this article

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The historical association of time with the rotation of Earth has meant that Coordinated Universal Time (UTC) closely follows this rotation 1 . Because the rotation rate is not constant, UTC contains discontinuities (leap seconds), which complicates its use in computer networks 2 . Since 1972, all UTC discontinuities have required that a leap second be added 3 . Here we show that increased melting of ice in Greenland and Antarctica, measured by satellite gravity 4 , 5 , has decreased the angular velocity of Earth more rapidly than before. Removing this effect from the observed angular velocity shows that since 1972, the angular velocity of the liquid core of Earth has been decreasing at a constant rate that has steadily increased the angular velocity of the rest of the Earth. Extrapolating the trends for the core and other relevant phenomena to predict future Earth orientation shows that UTC as now defined will require a negative discontinuity by 2029. This will pose an unprecedented problem for computer network timing and may require changes in UTC to be made earlier than is planned. If polar ice melting had not recently accelerated, this problem would occur 3 years earlier: global warming is already affecting global timekeeping.

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The global historical climate database HCLIM

Elin Lundstad, Yuri Brugnara, … Stefan Brönnimann

Smooth velocity fields for tracking climate change

Iaroslav Gaponenko, Guillaume Rohat, … Jérôme Kasparian

ClimateEU, scale-free climate normals, historical time series, and future projections for Europe

Maurizio Marchi, Dante Castellanos-Acuña, … Annette Menzel

Data availability

The J 2 data are C20LongTerm.txt, downloaded from https://filedrop.csr.utexas.edu/pub/slr/degree_2/ on 25 October 2023. The Earth rotation data are eopc0420.1962-now, downloaded from https://datacenter.iers.org/products/eop/long-term/c04_20/ on 24 October 2023. The atmospheric angular momentum data are from https://datacenter.iers.org/products/geofluids/atmosphere/aam/GGFC2010/AER/ , downloaded on 1 February 2023. Other parameters are taken from the papers referenced. Source data are provided with this paper.

Code availability

The code for analysing the residual series, est.noise v.1.2, was downloaded from https://github.com/langbein-usgs on 25 June 2023. The seasonal-adjustment code stl was slightly modified from a version downloaded from https://netlib.org/a/ in June 2008.

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I thank R. Ray, L. Morrison, A. Borsa, J. Mitrovica and M. King for their comments.

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Title: realm: reference resolution as language modeling.

Abstract: Reference resolution is an important problem, one that is essential to understand and successfully handle context of different kinds. This context includes both previous turns and context that pertains to non-conversational entities, such as entities on the user's screen or those running in the background. While LLMs have been shown to be extremely powerful for a variety of tasks, their use in reference resolution, particularly for non-conversational entities, remains underutilized. This paper demonstrates how LLMs can be used to create an extremely effective system to resolve references of various types, by showing how reference resolution can be converted into a language modeling problem, despite involving forms of entities like those on screen that are not traditionally conducive to being reduced to a text-only modality. We demonstrate large improvements over an existing system with similar functionality across different types of references, with our smallest model obtaining absolute gains of over 5% for on-screen references. We also benchmark against GPT-3.5 and GPT-4, with our smallest model achieving performance comparable to that of GPT-4, and our larger models substantially outperforming it.

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Special Issue: Journal of Marketing