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Mission The Journal of Marketing Research ( JMR ) is a bimonthly journal serving the scholarly and practitioner communities in the field of marketing.

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JMR is a broad-based journal that aims to publish the highest-quality articles in the discipline of marketing. Published articles must make a significant contribution to the marketing discipline, provide a basis for stimulating additional research, and meet high standards of scholarship.

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The past, present, and future of marketing strategy

Published: 04 July 2020
Volume 31 , pages 163–174, ( 2020 )

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Sibel Sozuer ORCID: orcid.org/0000-0003-1513-4362 1 ,
Gregory S. Carpenter 2 ,
Praveen K. Kopalle 3 ,
Leigh M. McAlister 4 &
Donald R. Lehmann 1

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This article provides a high-level overview of marketing strategy research and offers a number of suggestions of areas ripe for future research. We discuss the most fundamental concepts that continue to drive current marketing strategy research and examine how these concepts have shaped marketing strategy and the role of the marketing function. In addition, we highlight the developments in marketing accountability, marketing’s influence within the firm, and alternatives to a market-driven approach in generating sustainable competitive advantage. Finally, we identify directions for future research in the light of recent developments, availability of new data, and emerging issues.

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Strategic marketing, marketing strategy and market strategy, the theoretical foundations of strategic marketing and marketing strategy: foundational premises, r-a theory, three fundamental strategies, and societal welfare, explore related subjects.

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Columbia Business School, Columbia University, New York, NY, USA

Sibel Sozuer & Donald R. Lehmann

Kellogg School of Management, Northwestern University, Evanston, IL, USA

Gregory S. Carpenter

Tuck School of Business, Dartmouth College, Hanover, NH, USA

Praveen K. Kopalle

McCombs School of Business, University of Texas at Austin, Austin, TX, USA

Leigh M. McAlister

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Sozuer, S., Carpenter, G.S., Kopalle, P.K. et al. The past, present, and future of marketing strategy. Mark Lett 31 , 163–174 (2020). https://doi.org/10.1007/s11002-020-09529-5

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Issue Date : September 2020

DOI : https://doi.org/10.1007/s11002-020-09529-5

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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

Year		TC*	Mean TC* per article	Mean TC* per year	Citable years
2018	26	9,015	346.73	57.79	6
2019	33	14,621	453.36	90.67	5
2020	33	13,692	414.91	103.73	4
2021	8	4,220	527.5	175.83	3
2022	0	0	0	0	2
Total	100	41,888	418.88	69.81

Document	Title	TC	Average TC per year	Normalized TC
	Literature review as a research methodology: an overview and guidelines	1,872	374.40	4.13
(2021)	How to conduct a bibliometric analysis: an overview and guidelines	1,221	407.00	2.31
(2020)	Assessing measurement model quality in PLS-SEM using confirmatory composite analysis	1,103	275.75	2.66
	Tourism and COVID-19: impacts and implications for advancing and resetting industry and research	977	244.25	2.35
(2019)	Predictive model assessment in PLS-SEM: guidelines for using PLSpredict	913	182.60	2.01
(2021)	Digital transformation: a multidisciplinary reflection and research agenda.	758	252.67	1.44
(2019)	How to specify, estimate, and validate higher-order constructs in PLS-SEM	728	145.60	1.61
(2019)	Artificial intelligence for decision making in the era of big data – evolution, challenges and research agenda	724	144.80	1.60
	Impact of covid-19 on consumer behavior: will the old habits return or die?	716	179.00	1.73
	The rise of motivational information systems: a review of gamification research	639	127.80	1.41

No. of articles	Scopus quartile	SJR	TC
26	Q1	4.91	10,008
22	Q1	2.90	12,265
6	Q1	2.54	1,875
4	Q1	3.43	1,376
4	Q1	2.48	1,706
4	Q1	6.02	1,220
4	Q1	6.25	1,850
3	Q1	1.63	1,769
3	Q1	2.66	984
3	Q1	10.8	1,120

Authors	Topical focus	No. of articles	Fractionalized frequency	Total citations	-Index	-Index	-Index
Dwivedi YK	Digital innovation	7	1.16	3,361	7	7	1.17
Hair JF	Multivariate analysis	5	1.18	3,615	5	5	0.83
Hughes DL	Artificial intelligence	5	0.57	2,305	5	5	1.00
Ringle CM	Data and business analytics	4	0.84	2,512	4	4	0.67
Sarstedt M	Structural equation modeling	4	0.84	2,512	4	4	0.67

Current research trends	Future research questions
Brown cluster – AI (e.g. , 2019; , 2020; , 2021)
Blue cluster – Covid-19 (e.g. ; ; , 2021)
Red cluster – bibliometric analysis (e.g. , 2018; ; , 2021)
Purple cluster – social media (e.g. ; , 2018; )
Orange cluster – live streaming (e.g. , 2019; )
Green cluster – Blockchain (e.g. , 2018; ; )

Potential research gaps	Future research questions
Data-driven marketing: to explore the potential of data-driven marketing by leveraging deep learning, AI and IoT technologies to enhance marketing practices, optimize customer targeting and improve overall business performance in the digital era
Environmental sustainability: to investigate the potential of using neuromarketing techniques, gamification and mixed reality to promote sustainable consumption practices
Mass personalization: to investigate how personalization of customers’ experiences can be enhanced and implemented responsibly and ethically
Wearable technology: to investigate how wearable technologies can foster deeper connections between consumers and brands

Category	Year	Quartile
Business and International Management	1999	Q1
Business and International Management	2000	Q1
Business and International Management	2001	Q1
Business and International Management	2002	Q1
Business and International Management	2003	Q1
Business and International Management	2004	Q1
Business and International Management	2005	Q1
Business and International Management	2006	Q1
Business and International Management	2007	Q1
Business and International Management	2008	Q1
Business and International Management	2009	Q1
Business and International Management	2010	Q1
Business and International Management	2011	Q1
Business and International Management	2012	Q1
Business and International Management	2013	Q1
Business and International Management	2014	Q1
Business and International Management	2015	Q1
Business and International Management	2016	Q1
Business and International Management	2017	Q1
Business and International Management	2018	Q1
Business and International Management	2019	Q1
Business and International Management	2020	Q1
Business and International Management	2021	Q1
Business and International Management	2022	Q1
Business and International Management	2023	Q1
Economics and Econometrics	1999	Q1
Economics and Econometrics	2000	Q1
Economics and Econometrics	2001	Q1
Economics and Econometrics	2002	Q1
Economics and Econometrics	2003	Q1
Economics and Econometrics	2004	Q1
Economics and Econometrics	2005	Q1
Economics and Econometrics	2006	Q1
Economics and Econometrics	2007	Q1
Economics and Econometrics	2008	Q1
Economics and Econometrics	2009	Q1
Economics and Econometrics	2010	Q1
Economics and Econometrics	2011	Q1
Economics and Econometrics	2012	Q1
Economics and Econometrics	2013	Q1
Economics and Econometrics	2014	Q1
Economics and Econometrics	2015	Q1
Economics and Econometrics	2016	Q1
Economics and Econometrics	2017	Q1
Economics and Econometrics	2018	Q1
Economics and Econometrics	2019	Q1
Economics and Econometrics	2020	Q1
Economics and Econometrics	2021	Q1
Economics and Econometrics	2022	Q1
Economics and Econometrics	2023	Q1
Marketing	1999	Q1
Marketing	2000	Q1
Marketing	2001	Q1
Marketing	2002	Q1
Marketing	2003	Q1
Marketing	2004	Q1
Marketing	2005	Q1
Marketing	2006	Q1
Marketing	2007	Q1
Marketing	2008	Q1
Marketing	2009	Q1
Marketing	2010	Q1
Marketing	2011	Q1
Marketing	2012	Q1
Marketing	2013	Q1
Marketing	2014	Q1
Marketing	2015	Q1
Marketing	2016	Q1
Marketing	2017	Q1
Marketing	2018	Q1
Marketing	2019	Q1
Marketing	2020	Q1
Marketing	2021	Q1
Marketing	2022	Q1
Marketing	2023	Q1

Year	SJR
1999	3.380
2000	3.132
2001	3.565
2002	5.712
2003	5.399
2004	5.405
2005	4.599
2006	3.517
2007	3.767
2008	5.054
2009	4.467
2010	4.456
2011	5.211
2012	4.949
2013	6.449
2014	5.450
2015	5.911
2016	6.486
2017	7.819
2018	6.895
2019	7.325
2020	6.321
2021	5.372
2022	7.415
2023	5.984

Year	Documents
1999	78
2000	39
2001	41
2002	37
2003	35
2004	42
2005	56
2006	61
2007	58
2008	59
2009	79
2010	91
2011	92
2012	71
2013	52
2014	66
2015	58
2016	67
2017	64
2018	60
2019	60
2020	60
2021	60
2022	71
2023	77

Cites per document	Year	Value
Cites / Doc. (4 years)	1999	1.614
Cites / Doc. (4 years)	2000	1.543
Cites / Doc. (4 years)	2001	1.906
Cites / Doc. (4 years)	2002	2.462
Cites / Doc. (4 years)	2003	3.138
Cites / Doc. (4 years)	2004	4.099
Cites / Doc. (4 years)	2005	4.568
Cites / Doc. (4 years)	2006	3.629
Cites / Doc. (4 years)	2007	3.567
Cites / Doc. (4 years)	2008	4.300
Cites / Doc. (4 years)	2009	5.120
Cites / Doc. (4 years)	2010	4.899
Cites / Doc. (4 years)	2011	4.390
Cites / Doc. (4 years)	2012	4.495
Cites / Doc. (4 years)	2013	4.691
Cites / Doc. (4 years)	2014	5.379
Cites / Doc. (4 years)	2015	5.762
Cites / Doc. (4 years)	2016	5.895
Cites / Doc. (4 years)	2017	6.313
Cites / Doc. (4 years)	2018	6.122
Cites / Doc. (4 years)	2019	7.048
Cites / Doc. (4 years)	2020	7.610
Cites / Doc. (4 years)	2021	7.398
Cites / Doc. (4 years)	2022	8.167
Cites / Doc. (4 years)	2023	9.610
Cites / Doc. (3 years)	1999	1.614
Cites / Doc. (3 years)	2000	1.510
Cites / Doc. (3 years)	2001	1.685
Cites / Doc. (3 years)	2002	2.728
Cites / Doc. (3 years)	2003	3.179
Cites / Doc. (3 years)	2004	3.796
Cites / Doc. (3 years)	2005	3.553
Cites / Doc. (3 years)	2006	3.391
Cites / Doc. (3 years)	2007	2.969
Cites / Doc. (3 years)	2008	3.789
Cites / Doc. (3 years)	2009	4.876
Cites / Doc. (3 years)	2010	4.189
Cites / Doc. (3 years)	2011	3.803
Cites / Doc. (3 years)	2012	3.927
Cites / Doc. (3 years)	2013	4.638
Cites / Doc. (3 years)	2014	4.684
Cites / Doc. (3 years)	2015	4.799
Cites / Doc. (3 years)	2016	4.960
Cites / Doc. (3 years)	2017	5.723
Cites / Doc. (3 years)	2018	5.646
Cites / Doc. (3 years)	2019	6.764
Cites / Doc. (3 years)	2020	6.772
Cites / Doc. (3 years)	2021	5.994
Cites / Doc. (3 years)	2022	8.083
Cites / Doc. (3 years)	2023	7.503
Cites / Doc. (2 years)	1999	1.640
Cites / Doc. (2 years)	2000	1.057
Cites / Doc. (2 years)	2001	1.675
Cites / Doc. (2 years)	2002	2.525
Cites / Doc. (2 years)	2003	2.962
Cites / Doc. (2 years)	2004	2.819
Cites / Doc. (2 years)	2005	3.026
Cites / Doc. (2 years)	2006	2.837
Cites / Doc. (2 years)	2007	2.444
Cites / Doc. (2 years)	2008	3.336
Cites / Doc. (2 years)	2009	4.162
Cites / Doc. (2 years)	2010	3.275
Cites / Doc. (2 years)	2011	3.071
Cites / Doc. (2 years)	2012	3.475
Cites / Doc. (2 years)	2013	3.798
Cites / Doc. (2 years)	2014	3.488
Cites / Doc. (2 years)	2015	3.619
Cites / Doc. (2 years)	2016	4.355
Cites / Doc. (2 years)	2017	4.800
Cites / Doc. (2 years)	2018	5.031
Cites / Doc. (2 years)	2019	5.742
Cites / Doc. (2 years)	2020	4.433
Cites / Doc. (2 years)	2021	5.650
Cites / Doc. (2 years)	2022	5.800
Cites / Doc. (2 years)	2023	6.115

Cites	Year	Value
Self Cites	1999	85
Self Cites	2000	29
Self Cites	2001	23
Self Cites	2002	28
Self Cites	2003	36
Self Cites	2004	44
Self Cites	2005	51
Self Cites	2006	43
Self Cites	2007	28
Self Cites	2008	47
Self Cites	2009	42
Self Cites	2010	76
Self Cites	2011	75
Self Cites	2012	72
Self Cites	2013	74
Self Cites	2014	50
Self Cites	2015	36
Self Cites	2016	43
Self Cites	2017	53
Self Cites	2018	38
Self Cites	2019	50
Self Cites	2020	51
Self Cites	2021	50
Self Cites	2022	73
Self Cites	2023	62
Total Cites	1999	376
Total Cites	2000	361
Total Cites	2001	332
Total Cites	2002	431
Total Cites	2003	372
Total Cites	2004	429
Total Cites	2005	405
Total Cites	2006	451
Total Cites	2007	472
Total Cites	2008	663
Total Cites	2009	868
Total Cites	2010	821
Total Cites	2011	871
Total Cites	2012	1029
Total Cites	2013	1178
Total Cites	2014	1007
Total Cites	2015	907
Total Cites	2016	873
Total Cites	2017	1093
Total Cites	2018	1067
Total Cites	2019	1292
Total Cites	2020	1246
Total Cites	2021	1079
Total Cites	2022	1455
Total Cites	2023	1433

Cites	Year	Value
External Cites per document	1999	1.249
External Cites per document	2000	1.389
External Cites per document	2001	1.569
External Cites per document	2002	2.551
External Cites per document	2003	2.872
External Cites per document	2004	3.407
External Cites per document	2005	3.105
External Cites per document	2006	3.068
External Cites per document	2007	2.792
External Cites per document	2008	3.520
External Cites per document	2009	4.640
External Cites per document	2010	3.801
External Cites per document	2011	3.476
External Cites per document	2012	3.653
External Cites per document	2013	4.346
External Cites per document	2014	4.451
External Cites per document	2015	4.608
External Cites per document	2016	4.716
External Cites per document	2017	5.445
External Cites per document	2018	5.444
External Cites per document	2019	6.503
External Cites per document	2020	6.495
External Cites per document	2021	5.717
External Cites per document	2022	7.678
External Cites per document	2023	7.178
Cites per document	1999	1.614
Cites per document	2000	1.510
Cites per document	2001	1.685
Cites per document	2002	2.728
Cites per document	2003	3.179
Cites per document	2004	3.796
Cites per document	2005	3.553
Cites per document	2006	3.391
Cites per document	2007	2.969
Cites per document	2008	3.789
Cites per document	2009	4.876
Cites per document	2010	4.189
Cites per document	2011	3.803
Cites per document	2012	3.927
Cites per document	2013	4.638
Cites per document	2014	4.684
Cites per document	2015	4.799
Cites per document	2016	4.960
Cites per document	2017	5.723
Cites per document	2018	5.646
Cites per document	2019	6.764
Cites per document	2020	6.772
Cites per document	2021	5.994
Cites per document	2022	8.083
Cites per document	2023	7.503

Year	International Collaboration
1999	8.97
2000	2.56
2001	2.44
2002	0.00
2003	17.14
2004	23.81
2005	32.14
2006	24.59
2007	37.93
2008	38.98
2009	30.38
2010	40.66
2011	38.04
2012	36.62
2013	34.62
2014	22.73
2015	41.38
2016	40.30
2017	45.31
2018	35.00
2019	5.00
2020	5.00
2021	3.33
2022	15.49
2023	6.49

Documents	Year	Value
Non-citable documents	1999	5
Non-citable documents	2000	6
Non-citable documents	2001	4
Non-citable documents	2002	1
Non-citable documents	2003	0
Non-citable documents	2004	0
Non-citable documents	2005	1
Non-citable documents	2006	2
Non-citable documents	2007	3
Non-citable documents	2008	3
Non-citable documents	2009	5
Non-citable documents	2010	19
Non-citable documents	2011	19
Non-citable documents	2012	16
Non-citable documents	2013	2
Non-citable documents	2014	2
Non-citable documents	2015	3
Non-citable documents	2016	3
Non-citable documents	2017	2
Non-citable documents	2018	2
Non-citable documents	2019	1
Non-citable documents	2020	1
Non-citable documents	2021	2
Non-citable documents	2022	3
Non-citable documents	2023	4
Citable documents	1999	228
Citable documents	2000	233
Citable documents	2001	193
Citable documents	2002	157
Citable documents	2003	117
Citable documents	2004	113
Citable documents	2005	113
Citable documents	2006	131
Citable documents	2007	156
Citable documents	2008	172
Citable documents	2009	173
Citable documents	2010	177
Citable documents	2011	210
Citable documents	2012	246
Citable documents	2013	252
Citable documents	2014	213
Citable documents	2015	186
Citable documents	2016	173
Citable documents	2017	189
Citable documents	2018	187
Citable documents	2019	190
Citable documents	2020	183
Citable documents	2021	178
Citable documents	2022	177
Citable documents	2023	187

Documents	Year	Value
Uncited documents	1999	108
Uncited documents	2000	140
Uncited documents	2001	97
Uncited documents	2002	57
Uncited documents	2003	23
Uncited documents	2004	15
Uncited documents	2005	18
Uncited documents	2006	29
Uncited documents	2007	42
Uncited documents	2008	33
Uncited documents	2009	28
Uncited documents	2010	45
Uncited documents	2011	50
Uncited documents	2012	39
Uncited documents	2013	27
Uncited documents	2014	28
Uncited documents	2015	30
Uncited documents	2016	40
Uncited documents	2017	23
Uncited documents	2018	19
Uncited documents	2019	15
Uncited documents	2020	15
Uncited documents	2021	18
Uncited documents	2022	8
Uncited documents	2023	15
Cited documents	1999	125
Cited documents	2000	99
Cited documents	2001	100
Cited documents	2002	101
Cited documents	2003	94
Cited documents	2004	98
Cited documents	2005	96
Cited documents	2006	104
Cited documents	2007	117
Cited documents	2008	142
Cited documents	2009	150
Cited documents	2010	151
Cited documents	2011	179
Cited documents	2012	223
Cited documents	2013	227
Cited documents	2014	187
Cited documents	2015	159
Cited documents	2016	136
Cited documents	2017	168
Cited documents	2018	170
Cited documents	2019	176
Cited documents	2020	169
Cited documents	2021	162
Cited documents	2022	172
Cited documents	2023	176

Year	Female Percent
1999	31.71
2000	6.74
2001	18.52
2002	27.63
2003	21.92
2004	20.25
2005	23.96
2006	30.23
2007	23.97
2008	27.07
2009	29.11
2010	29.13
2011	25.12
2012	35.84
2013	29.69
2014	29.79
2015	29.80
2016	33.94
2017	37.13
2018	34.18
2019	24.22
2020	33.33
2021	33.77
2022	36.79
2023	38.33

Documents	Year	Value
Overton	1999	22
Overton	2000	17
Overton	2001	15
Overton	2002	19
Overton	2003	15
Overton	2004	9
Overton	2005	18
Overton	2006	21
Overton	2007	16
Overton	2008	13
Overton	2009	24
Overton	2010	33
Overton	2011	26
Overton	2012	30
Overton	2013	14
Overton	2014	22
Overton	2015	14
Overton	2016	21
Overton	2017	14
Overton	2018	12
Overton	2019	7
Overton	2020	12
Overton	2021	6
Overton	2022	8
Overton	2023	2

Documents	Year	Value
SDG	2018	3
SDG	2019	4
SDG	2020	2
SDG	2021	9
SDG	2022	9
SDG	2023	10

Principles & Clusters		Most influential contributions
RESPONSIBLE PRINCIPLE
44 articles		White et al. (2019)	How to SHIFT consumer behaviors to be more sustainable: A literature review and guiding framework
Haws et al. (2014)	Seeing the world through green-tinted glasses: Green consumption values and responses to environmentally-friendly products
Brough et al. (2016)	The green-feminine stereotype and its effect on sustainable consumption
34 articles		Brown and Dacin (1997)	The company and the product: Corporate associations and consumer product responses
Korschun et al. (2014)	Corporate social responsibility, customer orientation, and the job performance of frontline employees
Sen and Bhattacharya (2001)	Does doing good always lead to doing better? Consumer reactions to corporate social responsibility
23 articles		Luchs et al. (2010)	The sustainability liability: Potential negative effects of ethicality on product preference
Wagner et al. (2009)	Corporate hypocrisy: Overcoming the threat of inconsistent corporate social responsibility perceptions
Vlachos et al. (2009)	Corporate social responsibility: Attributions, loyalty, and the mediating role of trust
RESILIENT PRINCIPLE
22 articles		Varadarajan (2017)	Innovating for sustainability: A framework for sustainable innovations and a model of sustainable innovations orientation
Sheth et al. (2011)	Mindful consumption: A customer-centric approach to sustainability
Banerjee et al. (2003)	Corporate environmentalism: Antecedents and influence of industry type
19 articles		Swaminathan et al. (2020)	Branding in a hyperconnected world: Refocusing theories and rethinking boundaries
Kang et al. (2016)	Washing away your sins? Corporate social responsibility, corporate social irresponsibility, and firm performance
Luo and Bhattacharya (2006)	Corporate social responsibility, customer satisfaction, and market value
RESPECTFUL PRINCIPLE
31 articles		Goldstein et al. (2008)	A room with a viewpoint: Using social norms to motivate environmental conservation in hotels
Barone et al. (2000)	The influence of cause-related marketing on consumer choice: Does one good turn deserve another?
Habel et al. (2016)	Warm glow or extra charge? The ambivalent effect of corporate social responsibility activities on customers' perceived price fairness
23 articles		Martin and Murphy (2017)	The role of data privacy in marketing
Mayo and Marks (1990)	An empirical investigation of a general theory of marketing ethics
Vitell et al. (1993)	Marketing norms: The influence of personal moral philosophies and organizational ethical culture

Principle Guided Questions	Corresponding UN SDG
Responsible Principle
• How can industries enhance the transparency of their production and marketing processes to provide tangible evidence of their sustainability or CSR commitments? In the wake of corporate scandals and malpractices, how can genuine CSR strategies be crafted to rebuild or repair brand reputations and have measurable impact on affected stakeholders?	Responsible consumption and production (12)
• How can industries that are directly linked to quality of life (e.g., financial services, healthcare) be improved in terms of broader access to services, enhanced service quality, and delivery that preserves consumer dignity?	Good health and wellbeing (3) Reduced inequalities (10)
• What are the crucial changes organizations need to make to their business practices to have substantial and sustained impact on environmental protection? How can such change be effectively measured and communicated to consumers and other stakeholders?	Industry, innovation, and infrastructure (9) Climate action (13) Life below water (14) Life on land (15)
Resilient Principle
• How can systematic bias be removed from technological applications in the marketplace? What biases exist in customer-facing technology that could reduce customer satisfaction and wellbeing? What benefits accrue to the firm for the elimination of bias?	Sustainable cities and communities (11) Responsible production and consumption (12) Peace, justice, and strong institutions (16)
• How does a focus on collective welfare impact firm performance and related marketing metrics (e.g., relationship quality, brand equity, customer loyalty)? How can this be measured? What is the effect of key moderating factors (e.g., industry, product type, product lifecycle, customer journey stage)?	Decent work and economic growth (8) Responsible consumption and production (12)
• As markets adapt to changing customer demands (e.g., peer-to-peer home delivery services), and customers and employees have more direct interaction outside of the workplace, how will customers perceive the firm’s relationship with their employees? What role and responsibility does the organization have in ensuring a livable wage for workers, and what are the tensions that impact the firm’s bottom line?	No poverty (1) Decent work and economic growth (8)
Respectful Principle
• How can firms better reflect the diversity of their employees and customers in a manner that retains the dignity and distinctiveness of their community and culture (beyond generalizations and stereotypes)? How does this impact the brand and the bottom line of the organization?	Gender equality (5) Reduced inequalities (10)
• How can marketing strategy help inform other business disciplines about respectful treatment of stakeholders (e.g., privacy or customer surveillance, unconscious biases, belief systems)? How might this expand the relevance of marketing in organizations and in business schools?	Gender equality (5) Reduced inequalities (10) Peace, justice, and strong institutions (16)
• What considerations are key for organizations as they expand their customer base to be inclusive of new or overlooked consumer segments? How can marketers determine the distinct needs such segments possess to create a win–win of inclusivity with dignity and profitability for the organization? How can underserved communities be incorporated in the customer base, as well as the employee base?	Decent work and economic growth (8) Reduced inequalities (10) Sustainable cities and communities (11)

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The past, present, and future of marketing strategy

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

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Practical implications

Originality/value

1. Introduction

2. Methodology

2.1 Search strategy

2.2 Selection process and final data set

2.3 Final data set

2.4 Data analysis

3. Results and discussion

3.2 Most influential articles

3.3 Source impact

3.4 Contributing authors

3.5 Co-occurrence analysis

4. Conclusions and future research agenda

4.1 RQ1: knowledge structure

4.2 RQ2: current research trends

4.3 RQ3: future research agenda

5. Conclusions and limitations

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