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The methodologies of the marketing literature: mechanics, uses and craft

• Theory/Conceptual
• Published: 08 November 2021
• Volume 11 , pages 416–431, ( 2021 )

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• Terry Clark 1 &
• Thomas Martin Key   ORCID: orcid.org/0000-0002-7338-627X 2  

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Of the three scholastic modes with which to develop ideas and create knowledge in research: logic, empirics, and the literature , the latter is perhaps one of the least understood and studied. This paper is a first-of-its-kind delve into what the literature is, how it is used, and its impact as a foundation for theory and conceptual work in the discipline of marketing. We create a novel approach that provides a framework to understand the way literature functions in the research process and expose the hidden mechanics of how it creates and ties together various forms of meaning through what we call, citation-based reasoning. It is through this lens that we conclude with insights for how a deeper understanding of the literature can stoke continued impact in the marketing discipline, especially for theory building and conceptual development.

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Clark, T., Key, T.M. The methodologies of the marketing literature: mechanics, uses and craft. AMS Rev 11 , 416–431 (2021). https://doi.org/10.1007/s13162-021-00210-2

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How to Read the Literary Market: An Introduction

Understood as a modern institution, literature is historically bound to the extension of market rationality. The commodification of literature since the late eighteenth century has changed the ways in which we handle literary works: rather than just perused by individual readers, books are promoted, traded, consumed, and legally protected. Over the past three decades, scholars have focused increased attention on how to conceptualize this encroachment of market principles into the sphere of culture ( Agnew 1986; Bourdieu 1996; Woodmansee 1994 ). They have shown that concepts like ‘the fine arts’, ‘high literature’, and ‘aesthetic autonomy’ have evolved not in opposition but rather as historical responses to and functions of the commercialization and professionalization of culture. In so doing they have reflected upon an array of intersecting cultural developments such as the specialization of the poet as professional writer and distributor of a marketable commodity and the diversification of literary practice across artistic and commercial spaces. What conjoins these projects is the broad question of how to read the literary market.

Many approaches toward literary market economies have pursued the aim of identifying the absent causes that determine literary production and consumption. This objective informed the works of marketplace critics of the 1980s (e.g., Gilmore 1985; Michaels 1987 ) but has also inspired the bulk of the more recent “New Economic Criticism” (e.g., McClanahan 2016; Poovey 2008 ). These branches of revisionist scholarship revolve around the social and economic, the material and ideological implications and constraints conditioning the production, reception, and distribution of literature. They emphasize literature’s crucial function as a site of political resistance and complicity, albeit by positing a rather static causality between the social and the cultural, politics and literature.

A number of competing contemporary approaches stemming from the resurgence of the sociology of literature have provided alternatives to the premises established by economic literary criticism. This development deserves a word of explanation. For what literary scholars think is sociology differs notably from how sociologists would identify their own discipline. Moreover, “‘sociology of literature’ has always named a polyglot and rather incoherent set of enterprises. It is scattered across so many separate domains and subdomains of scholarly research, each with its own distinct agendas of theory and method, that it scarcely even rates the designation of a ‘field’” ( English 2010 , v). For example: Birmingham School cultural materialism does champion a broad sociological interest in the life worlds of readers and writers. But that type of work is only peripherally relatable to some of the projects that sailed under New Historicist flags in the 1980s, although scholars in the wake of Stephen Greenblatt had a similarly committed interest in the social. Likewise, the reception of Michel Foucault’s bio-political writings of the 1970s and early 1980s encouraged a good deal of critics to inquire into the social and discursive foundations of power regimes. But that interest remained insular, almost disconnected from projects designed in pursuit of site-specific, empirical analyses of social power.

This sense of diversity notwithstanding, there is a set of vaguely identifiable thematic concerns and methodological premises at the center of sociological literary scholarship. When literary scholars turn into sociologists they typically focus on different actors in the literary market: publishing houses, agencies, and retailers; they look at matters of literacy and reading techniques, the interrelations of publishers, authors, and readers, and the history of production technology, treating the book and the literary text as objects of commerce and trade, and as cornerstones in the diverse constructions of socio-historical and cultural identities. These issues, to be sure, have troubled literary scholars since the beginnings of academic English studies in the early twentieth century, but they have never been clustered exclusively within a subfield called ‘sociology of literature’ or ‘marketplace criticism.’ In part this has to do with the evolution of literary theory during the post-45 period on both sides of the Atlantic, wherein Marxism was long considered to be the go-to paradigm for all things social. And while the continued interest in Pierre Bourdieu’s cultural sociology has helped to reintegrate sociological study into the domains of the English department since the 1990s, this interest has turned the field of literary production into a somewhat predictable metaphor customarily used to describe various forms of capital exchange (and barely anything else).

Focusing on these putative limitations, a number of recent studies have pointed out that the bulk of Bourdieu-derived scholarship still rests on the opposition between aesthetic and economic value, arguing that modern literature is marked by the tension of withdrawing from the mechanisms of the market and, at the same time, being shaped by it ( English 2005; Griem 2017; Leypoldt 2014; Theisohn and Weder 2013 ). In seeking to circumnavigate such binary models of the literary field, these critics have brought back to the forefront of scholarship questions of aesthetic experience, affect, or singularity, and thus re-conceptualized the market as a social institution – and a Latourian actor-network ( Felski 2015 ) – irreducible to its function of monetary allocation (e.g., Sklansky 2017 ). Following these interventions, aesthetic and economic value are neither irreconcilable nor indistinguishable, and questions about the form, appearance, and experience are put in fruitful dialogue with questions about the commodification and marketability of literary works.

Moreover, there has been a strong comeback of studies in the history of the book that in many ways complements the symbolic readings of the literary market both in terms of its transatlantic dimension and in its historical evolution. While there were incipient forms of what we now understand to be a literary market in eighteenth-century Britain ( Siskin 1998 ), the idea of a professionalized literary field did not become plausible on US soil before the 1840s. And even then, there remained a tremendous influence of British and continental European publishing on American authors, publishers, and retailers as the American market was constrained by rigid copyright laws ( McGill 2010 ). As Joseph Rezek has argued, conceiving of literary history in national terms denies the material and economic realities of early nineteenth-century literature: “British and American publishing were not separate affairs in the early nineteenth century” ( Rezek 2015 , 25). Literary practitioners at the time were aware that the literary marketplace of the early nineteenth century spanned the Atlantic. And they also knew how incoherently and unpredictably this market evolved across nation-states and institutions. For example: Boston, New York, and Philadelphia developed relatively early into powerful publishing centers in the US, not least because of their favorable geographical locations in the Northeast. But the Midwest and the Southern colonies, lacking stable trade routes to Europe, remained isolated as literary regions for the better part of the nineteenth century. Similar discontinuities can be observed in the case of London’s ascent into “world literary space” ( Casanova 2004 ), to borrow Pascale Casanova’s term, and the consequent emergence of an Anglo-European literary periphery in the eighteenth century. Given these contexts, any inquiry into the relationship between economy and literature must take account of this complex history, rather than simply assume that a literary market and its variously entangled hierarchies of value have always been there.

This special issue creates a critical forum on theories, methods, and techniques currently used for scholarly work at the intersection of culture and the economy. Reflecting the issue’s concerns with literature and the market, the articles cover a wide historical scope, ranging from the nineteenth century to the present. And by conjoining theoretical and historical concerns, they highlight the aesthetic, cultural-sociological, and narrative dimensions of literature and the market. Among other issues, the contributors focus on particular theoretical trajectories to refine our understanding of the relation between literature and the market, and they discuss the methods of analysis that are most promising for the study of modern literature and its integral role within market society. At the same time, most of the contributors relate their arguments to concrete sites of literary practice so as to maintain that any theoretical argument about the literary market can only make sense on the grounds of the market’s empirical foundations. Understood as social practices, reading and writing are never context-free.

This special issue’s methodological intervention grows out of a literal understanding of its title, “How to Read the Literary Market.” We move beyond an understanding of the literary market as a context or institutional setting that must be analyzed with extra-literary means, as if the market remained external to the literary text. Rather, works of literature themselves can be instructive for how to read (i.e., to form, comprehend, and reform) dynamics of the literary market. A number of our contributions therefore explore literary texts that highlight and draw on market dynamics and their effects on literary aesthetics and narrative structures. Accordingly, the essays assembled here seek to show that a sociology of literature must not only reflect upon the social and economic forces emerging from and around literature, but that it needs to tackle the very questions literary texts pose vis-à-vis the social; questions, that is, which target issues of race, class, gender, and the issue of creative production itself.

Considering the meaning and the status of the ‘literary’ within the framework of the literary market, Tim Lanzendörfer’s essay is both a critical reflection of the historically established and culturally inherent conflicts between ‘high’ and ‘low,’ avant-gardist and commercial, autonomous and complicit, and thereby an inquiry into this issue’s larger methodological interest. Philipp Löffler, in turn, offers a more specific account of central developments in the antebellum book market, focusing on two case studies: Nathaniel Hawthorne’s ascent into the literary establishment of the 1840s – based mainly on the promotion of his short fiction – and the attempts to advertise Harriet Beecher-Stowe’s Uncle Tom’s Cabin across socially and politically diverse readerships in the South and the North.

Nicola Glaubitz’s essay explicitly asks “How Useful is Bourdieu’s Notion of Capital for Describing Literary Markets?” Her answer – “Yes, Bourdieu’s notion of capital is useful” – is grounded in a careful analysis of three major critical works indebted to Bourdieu’s work: John Guillory’s Cultural Capital (1993); James English’s The Economy of Prestige (2005); and Clayton Childress’s Under the Cover (2017). Julika Griem integrates conceptions of literary markets, marketing, and marketability into the study of literature. By combining textual and sociological analysis, Griem turns to spatial and spatializing strategies on various levels of literary communication, relating Bourdieu’s sociology of literature to more recent studies on literary ecologies and consumer culture by David Alworth and Jim Collins.

The essays by Florian Sedlmeier and Stefanie Mueller explore the relationship between African American writing and the sociocultural implications of the literary market. Sedlmeier’s essay confronts Pierre Bourdieu’s notions of literary capital with William Dean Howells’s criticism of African American writers. The lens of Bourdieu, Sedlmeier argues, allows us to see the tension between the possibility of converting cultural difference into literary capital and the necessity to maintain a universal notion of literary capital, with which Howells endowed writers such as Paul Dunbar and Charles Chesnutt. In her essay “‘No more little boxes’ – Poetic Positionings in the Literary Field,” Stefanie Mueller analyzes Thomas Sayers Ellis’s poem “Skin, Inc.” (2010). In her close reading, Mueller shows that Ellis uses the metaphor of incorporation in terms of its economic and its formal affordances. Also drawing on Bourdieu’s work, Mueller thinks of the poem as a form of poetic position-taking in the early twenty-first-century United States. While she explores the literary marketplace as presented in Ellis’s poem, Mueller draws particular attention to the role of race in the US literary field, in particular with regard to what has been labeled a ‘post-soul aesthetic.’

The editors would like to thank Eleni Patrika and Aiden John for diligently formatting the issue.

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A qualitative analysis of the marketing analytics literature: where would ethical issues and legality rank?

Imran bashir dar.

1 Department of Technology Management, Faculty of Management Sciences, International Islamic University, Islamabad, Pakistan

Muhammad Bashir Khan

Abdul zahid khan, bahaudin g. mujtaba.

2 Management and Human Resources, Huizenga College of Business and Entrepreneurship, Nova Southeastern University, 3301 College Avenue, Fort Lauderdale, FL 33314-7796 USA

In response to the concerns of global data-driven disruption in marketing, this qualitative study explores the issues and challenges, which could unlock the potential of marketing analytics. This might pave the way, not only for academia–practitioner gap mitigation but also for a better human-centric understanding of utilising the technologically disruptive marketing trends, rather making them a foe. The plethora of marketing issues and challenges were distilled into 45 segments, and a detailed tabulation of the significant ones has been depicted for analysis and discussion. Furthermore, the conceptually thick five literary containers were developed, by coupling the constructs as per similarity in their categorical nature and connections. The ‘ethical issues and legality’ was identified as on the top, which provided literary comprehension and managerial implication for marketing analytics conceptualisation in the fourth industrial revolution era.

Introduction

The three dominant approaches (institutional, functional, commodity) used in past decades for dealing with overall marketing science concepts seem to be losing their viability with speed (Shepherd 1955 ), parallel to the availability of digital business avenues and diversity in sources of data (Hauser 2007 ; Dasan 2013 ; Wedel and Kannan 2016 ). Therefore, the analytics approach, with a problem-solving thinking frame, though had been discussed in the 1950s, is being observably adapted, and outcomes in terms of causation are continuously being gauged. Thoughtfully, academia has been left behind in this case, where now curriculum innovation (Wilson et al. 2018 ) and a shift of practices to gain academic coherence is being reportedly welcomed (Davenport and Harris 2017 ).

As per the field of Marketing, the mapping and quantification of causality are becoming the core of Marketing science, which is mastered by Marketing Analytics with a focus on action ability and informed decisions that have strategic value while not overlooking hard-data evidence (Grigsby 2015 , pp. 15–16; Rackley 2015 , pp. 1–30). Informed decisions, for the survival of any organisation, must get into action to create readiness for change (reaction) as per the evolution in the outer environment. The same is true for the biologically continued existence of organisms and for simple things as driving a car without a dashboard (Rackley 2015 , pp. 1–6). Even during the coronavirus pandemic situation, the thorniest question for board rooms today is the usage of disruptive technologies to sustain marketing efforts that could bear fruit (Balis 2020 ; Shah and Shah 2020 ; Waldron and Wetherbe 2020 ).

In terms of defining the concept of marketing analytics, there are many notable research endeavours, from the start of the new millennium, each having its analytical grounds (Davenport and Harris 2017 ). The researchers confined themselves to the sense that could glue the understanding blocks of academia and practitioners. So, marketing analytics has been sensed as exposing oneself to the descriptive, diagnostic, predictive, and prescriptive stages for insightful data reservoirs, for functional intimacy of marketing science in the contemporary world to sustain the competition and get better results through smarter decisions (Davenport and Harris 2017 ; Davenport et al. 2010 ; Davenport 2006 ; Farris et al. 2010 ).

Talking about issues and challenges, marketing analytics is research heaven for academia but a trap for the practitioners, as it has emerged from the process of convergence and divergence of multifaceted business areas (Mahidhar and Davenport 2018 ; Davenport and Kim 2013 ; Davenport and Harris 2007 ). Moreover, it is a continuous struggle to know about the customers before they know about themselves, and it could be done by marketing analytics (Davenport and Harris 2017 ; Farris et al. 2010 ). This can pave the way for a culture that would be conducive for marketing analytics in the corporate world. Marketing analytics is shifting from being merely a buzzword to full-fledge research area that is termed to be multidimensionally nascent, which is apparent by various systematic literature reviews on the subject concerned in connection to data-rich environments (Wedel and Kannan 2016 ), web analytics and key performance indicators (Saura et al. 2017 ), social media metrics (Misirlis and Vlachopoulou 2018 ), defining the field and convergence status (Krishen and Petrescu 2018 ), data mining (Dam et al. 2019 ), links to other fields and methods (France and Ghose 2019 ), research and practice environments (Iacobucci et al. 2019 ), and prescriptive analytics (Lepenioti et al. 2020 ).

Presently, senior marketing professionals are worried about their ability to measure these factors (Mahidhar and Davenport 2018 ). The data reservoirs are available, but the aligned mechanism for converting the data into actionable insights is observed to be a big missing link (Farris et al. 2010 ), which could result in analytically strategical misfit from consumer and marketing perspective (Zhang et al. 2010 ). Therefore, marketing analytics could be a threat to almost all the business models for pre-data backed economy, held globally. This may be termed as sustainable disruption, which means a continuous rigorous change (Davenport and Kim 2013 , pp 105–110). Moreover, it is evident that the improvement in technology has been phenomenal in the past century; still, the remarks of Peter Drucker are relevant in terms of computer and man, so the study of the issues and challenges would be necessary to mitigate any risks of failure (Guercini 2020 ). Therefore, despite the plethora of books and articles on the problem area concerned, a lack of research is apparent in terms of exhaustively studying the marketing analytics issues and challenges.

Procedural genesis for systematic literature review (SLR)

As pointed out by connection between decades of research that the view about systematic literature review (SLR) has been evolving and enriching itself (Webster and Watson 2002 ). Therefore, confining to a step-by-step approach and sticking to a set pattern defined by past research, which have been cited by the majority of the researches, were followed by the researchers for a line of action that could result in a significant research outcome (Levy and Ellis 2006 ; Okoli and Schabram 2010 ). The steps were grouped into three levels as input planning, process execution, and outcome reporting, by following the steps as reflected in Fig.  1 .

PRISMA statement

PRISMA, “Preferred Reporting Items for Systematic reviews and Meta-Analyses”, is one of the most endorsed ways for diagrammatically reporting the quality and rigour of systematic literature reviews. Therefore, the researchers applied the guidelines by Moher et al. ( 2009 ), with 62,621 citations, known as the “PRISMA Statement”.

Apart from reporting the systematic review, AMSTAR “measurement tool for assessment of systematic reviews” was studied (Shea et al. 2009 ), cited 1506 times, to enhance the quality of this study in terms of methodological validity and reliability. Additionally, the structure of “PICOS”, “participants, interventions, comparators, outcomes, and study design” was followed to clarify the scope of this study in terms of the multiple interventions and criteria (Smith et al. 2011 ; Van den Bosch and Sang 2017 ). Therefore, the quality assessment and enhancement of reporting, methodological aspects, and scope were exhausted through applying PRISMA, learning from the AMSTAR tool and following PICOS. The researchers did their best in not compromising on any level and dimension for developing a valuable and comprehensive systematic literature review study.

SLR process step by step

The PRISMA statement has four dimensions: (i) Identification, (ii) Screening, (iii) Eligibility, and (iv) Included, as reflected in Fig.  1 . These dimensions are further bifurcated into five steps. First, research questions were developed based on the current basic understanding of the problem from the call for papers and impactful recent research reservoir available from various databases and high-quality journals. The backward search in terms of the references, authors, and keywords was done to see through the results for any missing piece of research work, based on which the present work has been carried out (Webster and Watson 2002 ). Additionally, the forward search was done to review the further contribution of authors and its relevance to the problem. Moreover, the forward reference search was exercised to check the selected being cited by other researchers. This exercise of backward and forward search equipped the researchers with a basic picture of the theoretical contributions in terms of the problem at hand (Fig.  2 ).

Explored marketing analytics issues and challenges (MAICs)

The second step to identify the related studies by applying multiple metrics (Harzing 2007 ) . Third, the search metrics were accompanied by time frame and other restrictions, along with key search terms for exploring the digitally available research reservoirs. The fourth step has been inclusion and exclusion process application on the filtered body of quality research work. At this stage, the spearhead inspection of the literary reservoir is executed in terms of problem and research questions relevancy. The fifth step is to synthesise the finalised stream of research work, having a significant contribution in the problem area.

Research questions

This research study is aimed to address the proceeding research questions:

What sort of issues and challenges related to marketing analytics implementation were identified by the past research?

What are the most critical/highly ranked issues and challenges of marketing analytics (2000 to 2020)?

Criterion based exhaustive literature exploration

The level of exhaustiveness is measured by observation of search outcomes through “Publish or Perish 7” (PoP7) software sourced from Harzing ( 2007 ), accompanied with backward and forward searches, through different keywords relating to various dimensions of the research questions being considered. Once the output gets repeatedly and notably similar to previous search exercises, then the reliable maturity level could be achieved. For this purpose, a wide variety of carefully selected keywords, based on topic/area, marketing analytics, in this case, are used in a variety of combination through applying Boolean operators like OR/NOT/AND to enhance the “search reach” and enrich “search depth” (Webster and Watson 2002 ; Hedges and Cooper 2009 ; Baker 2016 ). The relevancy of the keywords was adapted by first searching for the highly cited articles discussing “marketing analytics” and fetching keywords for issues and challenges from them. Afterwards, those keywords, such as “marketing analytics” AND “barrier” OR “challenge”, “strategy”, “issue”, “failure”, “success”, “implementation”, “performance”, “measurement”, “understanding”, “problem”, “application”, “operation”, “process”, “execution”, “acceptance”, “critical success factors”, “marketing analytics implementation challenges”, and “marketing analytics implementation issues and challenges”. Total papers (deleting all duplications, excluding other material) extracted were 854 from which only 73 highly cited articles were selected. Notably, even after searching through coupling the issues and challenges keywords with “marketing analytics”, the filters of the rigorous study were plugged in to go beyond search metrics.

Databases and digitalised reservoirs

For furthering the research process, decision making for the selection of databases has been projected by backward and forward search, which presented the journals and publishers having the most relevant and impactful number of articles. Therefore, the question of “where” and “how” has been addressed for the readiness of review (Levy and Ellis 2006 ). The databases below are the filtered reservoirs, as per citations and relevancy of the articles related to the issues and challenges, and availability at the university library or beyond it:

• Harvard Business Press
• Taylor & Francis
• Wiley Online Library
• Journals of American Marketing Association (AMA)
• INFORMS PubsOnline
• Ingenta Connect

Filtration and extraction of research articles

The amalgamation of the research articles through strict numerous restrictions has been ground into final filtration by exploring the content in them in terms of the problem area, marketing analytics issues, and challenges, as per the past research available. The articles that notably and chiefly discussed the issues and challenges were extracted after review, and the remaining studies were abandoned (Levy and Ellis 2006 ; Hedges and Cooper 2009 ). The numbers of the selected papers for review were narrowed by exerting the following metrics:

• (i) As reflected in the step three of PRISMA statement, the papers having relevant and quality research (peer-reviewed, impact factor journals and high citations) were selected
• (ii) The research papers or conference papers that are not peer reviewed, duplicates, and nonrelevant papers were discarded
• (iii) Articles written in English language, published within the time frame of 2000–2020, discussing the issues and challenges of marketing analytics in a reasonable manner were included (Levy and Ellis 2006 ; Okoli and Schabram 2010 ).

The researcher for point (i) first checked the relevancy of the research paper or conference paper and whether they are peer reviewed or not. This does not mean that the researchers filtered the relevant research papers or conference papers that were peer reviewed and were not impact factor or highly cited. Actually, the fifth stage of “PRISMA Statement” steered the researchers to finalise and extract the articles having significant contribution, which resulted in terms of impact factor journal articles mostly that were eventually highly cited as well. It can be tracked from the results reflected in “Table 6 —ScientoMetrics-Quartile Analytics” that 92% of the finalised papers are categorised within Q1 to Q3, whereas 80% are from Q1.

ScientoMetrics-quartile analytics

This extensive exercise paved the way for finalised selection of 59 papers (only a handful) from 73 highly cited, based on the original result of 997 that were selected, as detailed in Tables ​ Tables1 1 and ​ and2 2 (Table ​ (Table3 3 ).

Sum of holistic search by research databases

The bold values signify the numeric result in terms of frequency for the research papers observed as per the captioned criteria

Research articles filtered/finalised by research databases

Theoretical mapping of marketing analytics (2000–2020)

Synthesise and evaluation

The papers discussing marketing analytics issue and challenges identified in Table ​ Table2 2 pave the way for detailed synthesis as per research question 1. Table ​ Table4 4 projects the issues and challenges of marketing analytics for the previous two decades. The papers have been organised in terms of their publication year and details about the specific qualitative and quantitative method that is provided as well.

Marketing analytics issues and challenges (2000–2020)

The exhaustive search for the marketing issues and challenges from the relevant, impactful, and having significant contribution reflected, along with the overall literature synthesis, reflected the list of 45 marketing analytics issues and challenges, captioned as Marketing Analytics Issues and Challenges (MAICs 1–45), in Table ​ Table5. 5 . From these MAICs, the non-significant ones have been dropped, which can be traced from the numbering of the issues and challenges accordingly, in Table ​ Table4. 4 . The citations and journal information about the finalised 59 research papers are tabulated in Appendix. Moreover, Table ​ Table6 6 (ScientoMetrics-Quartile Analytics) shows the impact of the journals in which the papers have been published, ranging from Q1 to Q3.

List of the marketing analytics issues & challenges (MAICs)

Analysis and discussion

The exhaustive study of the finalised articles in terms of the issues and challenges reflected that the ethical issues and legality dimension are at the top in terms of frequency-based ranking. The ethical issues and legality involve the legal implementation of consumer rights protection in terms of privacy and usage of customer personal data. Moreover, the impact of organisational operations on consumers has to be made transparent enough so that user consent would be sought. Other issues and concerns related to implementation are concerned with the marketing analytics ecosystem.

By following the mapping and classification style of previous studies (Adams et al. 2016 ; Bembom and Schwens 2018 ; Bocconcelli et al. 2018 ; Ceipek et al. 2019 ; Klang et al. 2014 ; Nguyen et al. 2018 ; Popay et al. 2006 ; Tranfield et al. 2003 ; Zahoor et al. 2020 ), the theoretical categorisation depicts that the five literary grounds titled as RBT/RBV, Upper Echelons Theory, Organisational Learning theory, Dynamic Capability Theory/DCV, and Institutional Theory are the most influential ones in terms of constructs projected and notable research studies. This projects that the marketing analytics can be better explained by utilisation of the theoretical paradigm provided by the above, which could pave the way for further deeper studies.

Apart from the above-tabulated theories, many other theories have been employed, which include Complexity Theory (Xu et al. 2016 ; Vargo and Lusch 2017 ), Knowledge-Based View (Côrte-Real et al. 2017 ), SERVQUAL Model (Lemon and Verhoef 2016 ), Relationship Marketing Theory (Lemon and Verhoef 2016 ), Motivation-Hygiene Theory (Rutter et al. 2016 ), Supply Chain Management Theory (Schoenherr and Speier‐Pero 2015 ), Marketing Performance Measurement Theory (Järvinen and Karjaluoto 2015 ), Marketing Capability Theory (Mu 2015 ), Knowledge Management Theory (Holsapple et al. 2014 ), and Reciprocal Action Theory as well as Social Identity Theory (Chan et al. 2014 ).

Table ​ Table6 6 depicts that 92% of the total articles (54 articles) are part of Q1–Q3 journals, where 47 studies are from Q1 journals, which means that 80% of the detail in Table ​ Table4 4 is composed of the best available past studies based on the latest scientometrics.

For RQ2, the researchers classified the issues and challenges into the five themes depicting the core learning from this study that would pave the way for further studies:

Customer-centric strategic structures & customer engagement

The element of co-creation is apparent where organisations have to behave proactively to know what the customers want before they do, and to make them partners in seeking a competitive advantage. Consumer-based structures are being observed as the way forward for structural capitalisation that could support the information value chain (Mikalef et al. 2018 ; Sheng et al. 2017 ).

Integrated marketing communication (IMC) channels are the gateway for developing an ecosystem of customer relationship management so that targeted consumer engagement could be done for mental programming for description, diagnosis, prediction, and personalised prescription of customer lifetime experience management (Lemon and Verhoef 2016 ; Mikalef et al. 2018 ). Furthermore, for the sake of quant, the process of metrics alignment for not falling into the vicious trap of GIGO (garbage in, garbage out) marketing performance measures could be done when academia joins hands with practitioners and the foggy gap between two is cleared (Sheng et al. 2017 ). Furthermore, customer engagement in this age of personalisation is to go beyond purchase and build a platform through value exchange from and to marketer versus consumer, while assessing the psychological state of the customer in terms of participating in different initiatives of the marketer (Lemon and Verhoef 2016 ). Therefore, paving the way forward for the co-production of values through engagement platforms that are a mix of brick-n-mortar. This cycle of knowledge creation needs a mechanism of data insight extraction for actionable decision making (Xu et al. 2016 ).

For this purpose, the pre-analytics age conventional marketing strategies may not be that relevant for online brand communities, social networking sites, and consumer-based business structuring, where beyond text communication tools could be used and customers could be rewarded on their category of user (Chan et al. 2014 ). For the same reason, the concept of sharing economy and alignment of co-creation metrics to it have been considered as the key to unlocking future research and field opportunities (Kannan 2017 ).

Marketing analytics sticky culture & management practices

The system propelled culture accompanied by resource-based view (RBV) has been depicted to possess the operational grip for conversion into organisational capability. The management practices revolving around RBV categorise each factor into the classification of resources that involve data reservoirs, infrastructural foundation, and information systems installations. Process-oriented benchmarking is rehearsed, and metrics are prioritised accordingly (Mikalef et al. 2018 ). The marketing analytics sticky culture is sourced from the data-driven organisational culture where people, irrespective of their authority and hierarchical managerial positions, do indulge in decision-making practices that are backed by the informational projections extracted from data. Moreover, the data-driven management practices do mitigate silos decisions and propagate interdependency of actions (Wang and Hajli 2017 ).

In this jigsaw of data-driven marketing analytics, sticky analytics culture, and management practices, the issue of ethical consideration for usage of customer data and mix of customer consent versus reward is a nascent one that calls for further research (Martin and Murphy 2017 ).

Shifting the paradigm from RBV to knowledge-based view (KBV), Côrte-Real et al. ( 2017 ) are of the view that data analytics reservoirs are a network of knowledge-steered value chains that are not restricted to organisational boundaries and customer–marketer exchange mediums. These external value chains of knowledge that could promise operational agility and widening the business canvas are the next big thing to explore for competitive sustainability.

The ecosystem of marketing analytics is a whirl of RBV and KBV paradigms of industrialisation 4.0 where each function of marketing has its own set of analytical measurements for performance management. Therefore, further spearhead mapping of marketing-mix investment portfolios in high-tech or IT conducive environments is imperative (Lemon and Verhoef 2016 ; Wedel and Kannan 2016 ; Sheng et al. 2017 ).

As a crux, the aggressive proactive management practices for crafting system-oriented analytics sticky culture are necessary, which could integrate relevant management practices with overall business objectives (Mikalef et al. 2018 ; Chen et al. 2012 ). This would make insightful data utilisation that a management strategic priority would reflect the organisational agility phase. Moreover, an inclusively developed reservoir of management learning behaviours to re-adjust, re-align, and re-do practices could develop an indigenous culture. This could help the organisation to have capabilities that are hard to copy (Kannan 2017 ; Sheng et al. 2017 ).

Geo-location-based sense, data mining, and content management

The geo-location-based sense through social media management while taking care of the ethical issues and legality issues is vital to utilise the value from social mediums. Data-backed sense of social issues is a plus in this arena. The market strategies are to be ground in marketing core objectives, where knowledge sharing and change readiness are top of the line for the fifth revolution, marked by personalisation. The IT resource management for this shift is a major barrier that creates big data issues. This connects to the dearth of need analysis in terms of skill requirement and training/curriculum correspondents to analytics techniques and technological issues that disturb the customer experience management agenda (Wang and Hajli 2017 ; Bradlow et al. 2017 ; Martin and Murphy 2017 ; Sheng et al. 2017 ).

Surprisingly, Mobile analytics, as being the portable platform, has raised the bar for platform-free content management, where user-generated content is much valued for better acceptability. The disruption is caused in terms of customer privacy and security issues, where the race for EWOM & ROI has eroded societal sense. Therefore, counter disruptive technologies are imperative for governance, to develop dynamic capabilities for future marketing analytics (Mikalef et al. 2018 ; Sheng et al. 2017 ; Wedel and Kannan 2016 ; Chen et al. 2012 ).

Insightful data utilisation & performance measures

The need analysis of the business competition in terms of dynamic market capabilities and disruptive technological change sets the stage for alignment of the data management and valuation strategies (Mikalef et al. 2018 ). These strategies reflect the operations for data utilisation for the actionable insights as per the impact metrics defined for the communication channels where consumers exercise their consumer power. The digital orientation of marketing mix is exercised for mapping of the gaps in talent requirement, organisational agility, actionable metrics, and sharing the profits from marketing analytics with customers (Leeflang et al. 2014 ; Bradlow et al. 2017 ).

For this purpose, rigorous extraction and utilisation of data insights have been done through a deeper study of marketing data analytics for tracking the business process transformations that may indicate the untapped value reservoirs of “blue ocean” customer profits (Wang and Hajli 2017 ). Martin and Murphy ( 2017 ) stressed forwarding of profitability share to the customer through reward mechanism in this situation for a long-term relationship and value creation in marketing analytics age (Sheng et al. 2017 ). Wedel and Kannan ( 2016 ) presented the novel research methods for marketing analytics and depicted the connection between privacy and data security, marketing mix, and personalisation. Moreover, the future buying patterns of customers and exploration of developing service instruments in accordance calls for the usage of smart data snatching tools that could seamlessly apply metrics for customer tracking (Bradlow et al. 2017 ). The performance measures attached to this exercise may involve the issues of customer privacy and data security that needs to be vigilantly handled. The area of customer data security and privacy embedded with legal issues is a nascent marketing analytics arena that calls for further empirical research.

Besides, the marketing analytics heterogeneity enrichment is being in limelight through work on content marketing, web analytics, automation of marketing processes, and development of marketing analytics curriculum based on empiricism, as per pressing demand for unfathomable insight of related performance measures (Järvinen and Taiminen 2016 ; Schoenherr and Speier‐Pero 2015 ).

Ethical issues & legality

The most unique challenge for marketing analytics is composed of dimensions of business ethics and legality. The ethical issues involve intentional or unintentional customer privacy invasion through digitalised seamless data extraction and scanning mechanisms that could lead the company into a troublesome situation in terms of customer data privacy and security (Mikalef et al. 2018 ; Sheng et al. 2017 ).

With a balance between the customer privacy dynamics and organisational need, a reward system is a key to refrain from any conflicting situation. For this purpose, metrics must be aligned with the ethical consideration and legality issues. Moreover, the area of ethical issues and legality is complex as well as nascent in terms of research work. Therefore, demand for further research in terms of legal applications ranging from operations of web analytics to mobile analytics as privacy and protection of data is empirically evident (Sheng et al. 2017 ).

There are a variety of opinions and views floated by researchers in this regard. The performance benchmarks should be aligned with organisational dynamic capabilities (Mikalef et al. 2018 ) and the ecosystem for modulation of the customer-centric sharing economy (Kannan 2017 ) may be devised for customer profitability enhancement (Wang and Hajli 2017 ). Bradlow et al ( 2017 ) talked about customer tracking and ethical considerations. Martin and Murphy ( 2017 ) portrayed the ethical and legal dimensions of analytics in terms of data privacy, level of usage and sharing, and access nature. Côrte-Real et al. ( 2017 ) depicted the KBV perspective of analytics and data dynamics that broaden the scope of legal operations as the external channels of knowledge require legal scrutiny. Sheng et al. ( 2017 ) discussed convergence and divergence of various fields in connection in this regard. Lemon and Verhoef ( 2016 ) along with Wedel and Kannan ( 2016 ) talked about customer purchase behaviour tracking, personalisation, and ethical issues and legality mix in terms of marketing analytics. Schoenherr and Speier‐Pero ( 2015 ) depicted the curriculum development, empiricism, and legality depth. Mu ( 2015 ) researched marketing capability, product innovation, and novel legal complexities. Leeflang et al. ( 2014 ) studied the ethically and legality-wise proactive practices of professional marketers in the digitalised era. Furthermore, Chen et al. ( 2012 ) mobile analytics and technical areas connected with ethics and legality for preparing for the back-end processes.

The literacy thick encapsulation of 45 marketing analytics issues and challenges has been done based on theoretical significance and empirical sense into five construct-bonded layers that are customer-centric strategic structures and customer engagement, marketing analytics sticky culture, and management practices geo-location-based sense and data mining as well as content management, insightful data utilisation and performance measures, and ethical issues and legality. Together, they reflect the patterns in the high-quality literature spanning around two decades.

Moreover, all the marketing issues and challenges have been further classified into the process, people, outcome, and strategy as per the nature of the constructs explored from the literature. This further comprehends that the plethora of issues and challenges are triggered by these channels. Therefore, further research in terms of process-driven, people perspective, outcome-oriented, strategy-specified avenues of marketing analytics may support enrichment to this field brought by the fourth industrial revolution.

Limitations

The search metrics and selection process of the quality papers between the periods 2000 and 2020 have limitations as the canvas is not so wide to cater for the concept of marketing analytics issues and challenges from inception to conception, as in the case of meta-analysis. The trend of papers does reflect that the research problem is new and much of the research has been done in between the two decades, yet the systematic literature review has its limited grounds in terms of other research methodologies. So, widening the canvas of research in terms of the research period, research design, and other factors would provide deeper insight for the academic and practitioner community.

Core implications

Ethical and legal issues have been the most prominent ones, which depict that the legal acumen capability is the steering point for any company to save itself from any business-related challenges. The intangibles are the “new tangibles” for dealing with marketing analytics issues and challenges as companies have to work on their dynamic as well as inclusive capabilities of breeding co-creation culture through customer-centric strategic structures and customer engagement. This is marked by the alignment of performance measures with rigorous utilisation of actionable data insights.

Further research considerations

Marketing analytics demands a shift in the operational capabilities of the companies in terms of people, process, strategy, and outcomes. These dimensions call for further research in terms of each of the significant issues and challenges in heterogeneous industries, while setting the research canvas to regional alliances and international ones as well. This will provide a fruitful mapping reservoir for regional and international comparative analysis across various industries. Moreover, the SLRs in the area projected that areas and the learning from this study project that

• The convergence of stages of analytics (Descriptive, Diagnostic, Predictive, Prescriptive) and marketing science is a high call to check the issues and challenges at each stage.
• The reasons for significant issues and challenges, along with their remedies and territorial best practices, are composed of the broad range of research work yet to be done
• Mix methodology research has to be adapted for looking at the phenomena and defining its constructs; afterwards, those constructs should be converted into variables by scale development. Furthermore, the development of indigenous scales for each of the issues and challenges in terms of countries will provide better inclusive measurement yardsticks, which is the need of the fourth industrial revolution.

Domain classification of issues and challenges

• A systematic literature review for issues and challenges in terms of marketing metrics has been depicted by the present study.
• The common issues and challenges of marketing intelligence and marketing analytics are a vital area that would pave the way for 4.0 readiness by the developing economies.

Biographies

is a PhD Scholar at Faculty of Management Sciences, International Islamic University, Islamabad, Pakistan. He is a permanent Faculty member at Foundation University, Islamabad, Pakistan. He has taught in various public and private universities. His research interests are marketing intelligence and analytics. He has field experience in Marketing and Educational Logistics & Supply Chain Management.

is an Ex Dean at Faculty of Management Sciences, International Islamic University, Islamabad, Pakistan. He is an Ex Vice President Academics in the same university. He has more than 30 years of university teaching experience. He is research expertise in organisational behaviour and marketing science.

Abdul Zahid Zahid

is a Chairman for Department of Technology Management, International Islamic University, Islamabad, Pakistan. His research publications in reputable journals are Knowledge Management, Technology Management, Information Science, Computer and Society, and Information Systems. He has more than 20 years of university teaching experience.

is a Professor of Human Resources Management at Nova Southeastern University in Ft. Lauderdale, Florida. He is the author and co-author of several professional and academic books dealing with diversity, ethics, and management, as well as numerous academic journal articles. During the past twenty-five years, he has had the pleasure of working with human resource professionals in the United States, Canada, Brazil, Bahamas, Afghanistan, Pakistan, St. Lucia, Grenada, Malaysia, Japan, Vietnam, China, India, Thailand, and Jamaica. This diverse exposure has provided him many insights in ethics, culture, and management from the perspectives of different firms, people groups, and countries. Bahaudin can be reached at: [email protected]

Declarations

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Imran Bashir Dar, Email: [email protected] .

Muhammad Bashir Khan, Email: moc.evil@rihsabdhomrd , Email: [email protected] .

Abdul Zahid Khan, Email: [email protected] .

Bahaudin G. Mujtaba, Email: ude.avon@abatjum , Email: ude.avon@abaatjum , https://www.nova.edu .

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• Teesside University Student & Library Services
• Subject LibGuides

Business Research Methods

• Literature Review
• Studying for your Project
• Project Outline
• Project Management
• Report Writing
• How to Reference
• Reading Lists Online

What is a literature review

“A literature review is a description of the literature relevant to a particular field or topic. It gives an overview of what has been said, who the key writers are, what are the prevailing theories and hypotheses, what questions are being asked, and what methods and methodologies are appropriate and useful" (Emerald Insight).

A literature review  is not  just a summary of everything you have read on the topic.  It is a critical analysis of the existing research relevant to your topic, and you should show how the literature relates to your topic and identify any gaps in the area of research. Our Learning Hub has lots of useful guidance for carrying out a  Literature Review .

How is it different?

It's on a much larger scale from your research for previous modules.

You may need to devise new ways of searching and managing your results.

Think about:

• Using RefWorks to manage your references
• Setting up alerts to retrieve new results for your searches

How to carry out a review

• Devise a search strategy
• Search systematically
• Read critically – i.e. deconstruct the material
• Put it all back together – reconstruct

1. Devise a search strategy

Think about the sort of research that would help your project.

1. What subject areas does you topic fall into?

2. What possible sources could you use? Think broadly, for example:

• Company reports
• Industry profiles
• Market research
• Financial reports
• Newspaper articles
• Journal articles

3. What don't you want?  What are the limits? For example, geographical restrictions or time periods.

2. Search systematically

• Plan your search first, thinking about your keywords
• Use the pages on this LibGuide to identify quality resources
• Use the tutorials and advice on those pages to improve your searches
• Use the  Inter Library Loans service  to borrow books or to obtain copies of papers which aren't in the library
• Speak to the Business Librarians for help with your searches, or to recommend new items for library stock
• Look at the programme of  Succeed @ Tees workshops , and attend any which are relevant.

3. Read critically - i.e. deconstruct your results

Read critically, argument: .

• What is the main argument?
• Is the main argument clear and logical?
• What is the evidence?
• Is the evidence valid?
• Does the evidence support the conclusions?

4. Put it all back together – reconstruct

• Group your topic areas – develop themes
• Briefly summarise key findings

- See Phrasebank for suggestions of how to phrase your sentences.

• Use the academic papers as examples of the style of academic writing as well as for their content
• Check your referencing

Succeed@Tees Workshops: Writing a Literature Review

The following workshop will help you to develop your skills in writing a literature review :

Writing a literature review

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• Last Updated: Apr 23, 2024 11:08 AM
• URL: https://libguides.tees.ac.uk/business_research

Review of Marketing Research

• Recent Chapters

All books in this series (20 titles)

Recent chapters in this series (17 titles)

• AI and Personalization
• Anthropomorphism in Artificial Intelligence: A Review of Empirical Work Across Domains and Insights for Future Research
• Artificial Intelligence and Pricing
• Artificial Intelligence and User-Generated Data Are Transforming How Firms Come to Understand Customer Needs
• Artificial Intelligence Applications to Customer Feedback Research: A Review
• Deep Learning in Marketing: A Review and Research Agenda
• Leveraging AI for Content Generation: A Customer Equity Perspective
• Marketing Through the Machine's Eyes: Image Analytics and Interpretability
• Natural Language Processing in Marketing
• The Economics of Artificial Intelligence: A Marketing Perspective
• The State of AI Research in Marketing: Active, Fertile, and Ready for Explosive Growth
• Accounting for Uncertainty in the Measurement of Unobservable Marketing Phenomena
• An Application of M-MORE: A Multivariate Multiple Objective Random Effects Approach to Marketing Scale Dimensionality and Item Selection
• How to Identify Careless Responders in Surveys
• Measurement Error and Research Design: Some Practical Issues in Conducting Research
• Measurement in Marketing: Introduction by the Volume Editors
• On the Selection and Use of Implicit Measures in Marketing Research: A Utilitarian Taxonomy
• Naresh K. Malhotra

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What is Secondary Research? Types, Methods, Examples

Appinio Research · 20.09.2023 · 13min read

Have you ever wondered how researchers gather valuable insights without conducting new experiments or surveys? That's where secondary research steps in—a powerful approach that allows us to explore existing data and information others collect.

Whether you're a student, a professional, or someone seeking to make informed decisions, understanding the art of secondary research opens doors to a wealth of knowledge.

What is Secondary Research?

Secondary Research refers to the process of gathering and analyzing existing data, information, and knowledge that has been previously collected and compiled by others. This approach allows researchers to leverage available sources, such as articles, reports, and databases, to gain insights, validate hypotheses, and make informed decisions without collecting new data.

Benefits of Secondary Research

Secondary research offers a range of advantages that can significantly enhance your research process and the quality of your findings.

• Time and Cost Efficiency: Secondary research saves time and resources by utilizing existing data sources, eliminating the need for data collection from scratch.
• Wide Range of Data: Secondary research provides access to vast information from various sources, allowing for comprehensive analysis.
• Historical Perspective: Examining past research helps identify trends, changes, and long-term patterns that might not be immediately apparent.
• Reduced Bias: As data is collected by others, there's often less inherent bias than in conducting primary research, where biases might affect data collection.
• Support for Primary Research: Secondary research can lay the foundation for primary research by providing context and insights into gaps in existing knowledge.
• Comparative Analysis : By integrating data from multiple sources, you can conduct robust comparative analyses for more accurate conclusions.
• Benchmarking and Validation: Secondary research aids in benchmarking performance against industry standards and validating hypotheses.

Primary Research vs. Secondary Research

When it comes to research methodologies, primary and secondary research each have their distinct characteristics and advantages. Here's a brief comparison to help you understand the differences.

Primary Research

• Data Source: Involves collecting new data directly from original sources.
• Data Collection: Researchers design and conduct surveys, interviews, experiments, or observations.
• Time and Resources: Typically requires more time, effort, and resources due to data collection.
• Fresh Insights: Provides firsthand, up-to-date information tailored to specific research questions.
• Control: Researchers control the data collection process and can shape methodologies.

Secondary Research

• Data Source: Involves utilizing existing data and information collected by others.
• Data Collection: Researchers search, select, and analyze data from published sources, reports, and databases.
• Time and Resources: Generally more time-efficient and cost-effective as data is already available.
• Existing Knowledge: Utilizes data that has been previously compiled, often providing broader context.
• Less Control: Researchers have limited control over how data was collected originally, if any.

Choosing between primary and secondary research depends on your research objectives, available resources, and the depth of insights you require.

Types of Secondary Research

Secondary research encompasses various types of existing data sources that can provide valuable insights for your research endeavors. Understanding these types can help you choose the most relevant sources for your objectives.

Here are the primary types of secondary research:

Internal Sources

Internal sources consist of data generated within your organization or entity. These sources provide valuable insights into your own operations and performance.

• Company Records and Data: Internal reports, documents, and databases that house information about sales, operations, and customer interactions.
• Sales Reports and Customer Data: Analysis of past sales trends, customer demographics, and purchasing behavior.
• Financial Statements and Annual Reports: Financial data, such as balance sheets and income statements, offer insights into the organization's financial health.

External Sources

External sources encompass data collected and published by entities outside your organization.

These sources offer a broader perspective on various subjects.

• Published Literature and Journals: Scholarly articles, research papers, and academic studies available in journals or online databases.
• Market Research Reports: Reports from market research firms that provide insights into industry trends, consumer behavior, and market forecasts.
• Government and NGO Databases: Data collected and maintained by government agencies and non-governmental organizations, offering demographic, economic, and social information.
• Online Media and News Articles: News outlets and online publications that cover current events, trends, and societal developments.

Each type of secondary research source holds its value and relevance, depending on the nature of your research objectives. Combining these sources lets you understand the subject matter and make informed decisions.

How to Conduct Secondary Research?

Effective secondary research involves a thoughtful and systematic approach that enables you to extract valuable insights from existing data sources. Here's a step-by-step guide on how to navigate the process:

1. Define Your Research Objectives

Before delving into secondary research, clearly define what you aim to achieve. Identify the specific questions you want to answer, the insights you're seeking, and the scope of your research.

2. Identify Relevant Sources

Begin by identifying the most appropriate sources for your research. Consider the nature of your research objectives and the data type you require. Seek out sources such as academic journals, market research reports, official government databases, and reputable news outlets.

3. Evaluate Source Credibility

Ensuring the credibility of your sources is crucial. Evaluate the reliability of each source by assessing factors such as the author's expertise, the publication's reputation, and the objectivity of the information provided. Choose sources that align with your research goals and are free from bias.

4. Extract and Analyze Information

Once you've gathered your sources, carefully extract the relevant information. Take thorough notes, capturing key data points, insights, and any supporting evidence. As you accumulate information, start identifying patterns, trends, and connections across different sources.

5. Synthesize Findings

As you analyze the data, synthesize your findings to draw meaningful conclusions. Compare and contrast information from various sources to identify common themes and discrepancies. This synthesis process allows you to construct a coherent narrative that addresses your research objectives.

6. Address Limitations and Gaps

Acknowledge the limitations and potential gaps in your secondary research. Recognize that secondary data might have inherent biases or be outdated. Where necessary, address these limitations by cross-referencing information or finding additional sources to fill in gaps.

7. Contextualize Your Findings

Contextualization is crucial in deriving actionable insights from your secondary research. Consider the broader context within which the data was collected. How does the information relate to current trends, societal changes, or industry shifts? This contextual understanding enhances the relevance and applicability of your findings.

8. Cite Your Sources

Maintain academic integrity by properly citing the sources you've used for your secondary research. Accurate citations not only give credit to the original authors but also provide a clear trail for readers to access the information themselves.

9. Integrate Secondary and Primary Research (If Applicable)

In some cases, combining secondary and primary research can yield more robust insights. If you've also conducted primary research, consider integrating your secondary findings with your primary data to provide a well-rounded perspective on your research topic.

You can use a market research platform like Appinio to conduct primary research with real-time insights in minutes!

10. Communicate Your Findings

Finally, communicate your findings effectively. Whether it's in an academic paper, a business report, or any other format, present your insights clearly and concisely. Provide context for your conclusions and use visual aids like charts and graphs to enhance understanding.

Remember that conducting secondary research is not just about gathering information—it's about critically analyzing, interpreting, and deriving valuable insights from existing data. By following these steps, you'll navigate the process successfully and contribute to the body of knowledge in your field.

Secondary Research Examples

To better understand how secondary research is applied in various contexts, let's explore a few real-world examples that showcase its versatility and value.

Market Analysis and Trend Forecasting

Imagine you're a marketing strategist tasked with launching a new product in the smartphone industry. By conducting secondary research, you can:

• Access Market Reports: Utilize market research reports to understand consumer preferences, competitive landscape, and growth projections.
• Analyze Trends: Examine past sales data and industry reports to identify trends in smartphone features, design, and user preferences.
• Benchmark Competitors: Compare market share, customer satisfaction, and pricing strategies of key competitors to develop a strategic advantage.
• Forecast Demand: Use historical sales data and market growth predictions to estimate demand for your new product.

Academic Research and Literature Reviews

Suppose you're a student researching climate change's effects on marine ecosystems. Secondary research aids your academic endeavors by:

• Reviewing Existing Studies: Analyze peer-reviewed articles and scientific papers to understand the current state of knowledge on the topic.
• Identifying Knowledge Gaps: Identify areas where further research is needed based on what existing studies still need to cover.
• Comparing Methodologies: Compare research methodologies used by different studies to assess the strengths and limitations of their approaches.
• Synthesizing Insights: Synthesize findings from various studies to form a comprehensive overview of the topic's implications on marine life.

Competitive Landscape Assessment for Business Strategy

Consider you're a business owner looking to expand your restaurant chain to a new location. Secondary research aids your strategic decision-making by:

• Analyzing Demographics: Utilize demographic data from government databases to understand the local population's age, income, and preferences.
• Studying Local Trends: Examine restaurant industry reports to identify the types of cuisines and dining experiences currently popular in the area.
• Understanding Consumer Behavior: Analyze online reviews and social media discussions to gauge customer sentiment towards existing restaurants in the vicinity.
• Assessing Economic Conditions: Access economic reports to evaluate the local economy's stability and potential purchasing power.

These examples illustrate the practical applications of secondary research across various fields to provide a foundation for informed decision-making, deeper understanding, and innovation.

Secondary Research Limitations

While secondary research offers many benefits, it's essential to be aware of its limitations to ensure the validity and reliability of your findings.

• Data Quality and Validity: The accuracy and reliability of secondary data can vary, affecting the credibility of your research.
• Limited Contextual Information: Secondary sources might lack detailed contextual information, making it important to interpret findings within the appropriate context.
• Data Suitability: Existing data might not align perfectly with your research objectives, leading to compromises or incomplete insights.
• Outdated Information: Some sources might provide obsolete information that doesn't accurately reflect current trends or situations.
• Potential Bias: While secondary data is often less biased, biases might still exist in the original data sources, influencing your findings.
• Incompatibility of Data: Combining data from different sources might pose challenges due to variations in definitions, methodologies, or units of measurement.
• Lack of Control: Unlike primary research, you have no control over how data was collected or its quality, potentially affecting your analysis. Understanding these limitations will help you navigate secondary research effectively and make informed decisions based on a well-rounded understanding of its strengths and weaknesses.

Secondary research is a valuable tool that businesses can use to their advantage. By tapping into existing data and insights, companies can save time, resources, and effort that would otherwise be spent on primary research. This approach equips decision-makers with a broader understanding of market trends, consumer behaviors, and competitive landscapes. Additionally, benchmarking against industry standards and validating hypotheses empowers businesses to make informed choices that lead to growth and success.

As you navigate the world of secondary research, remember that it's not just about data retrieval—it's about strategic utilization. With a clear grasp of how to access, analyze, and interpret existing information, businesses can stay ahead of the curve, adapt to changing landscapes, and make decisions that are grounded in reliable knowledge.

How to Conduct Secondary Research in Minutes?

In the world of decision-making, having access to real-time consumer insights is no longer a luxury—it's a necessity. That's where Appinio comes in, revolutionizing how businesses gather valuable data for better decision-making. As a real-time market research platform, Appinio empowers companies to tap into the pulse of consumer opinions swiftly and seamlessly.

• Fast Insights: Say goodbye to lengthy research processes. With Appinio, you can transform questions into actionable insights in minutes.
• Data-Driven Decisions: Harness the power of real-time consumer insights to drive your business strategies, allowing you to make informed choices on the fly.
• Seamless Integration: Appinio handles the research and technical complexities, freeing you to focus on what truly matters: making rapid data-driven decisions that propel your business forward.

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Market research - Edexcel Methods of market research – secondary research

When businesses are deciding how to develop their products and services, they undertake market research. Market research can either be done by the company itself or taken from elsewhere.

Part of Business Spotting a business opportunity

Methods of market research – secondary research

There are two main types of market research close market research Market research is the process of collecting information about the market or what customers want that might help a business to be more successful and spot gaps in the market. – primary and secondary. Secondary market research , also known as desk research, involves gathering existing data close data Facts and statistics collected together for reference or analysis. that has already been produced. Secondary research can be collected from both inside (internal) and outside (external) a business. Internal research could include financial or marketing information, such as how many people previously responded to an advert sent out by the business. External research could include information from internet research , market reports and government reports .

Internet research

Internet research includes data taken from competitors’ websites, newspaper articles and social media close social media Social media is an interactive computer based technology that allows the user to create and to share information and ideas through virtual communities and networks. . This provides a business with an overview of information relating to its industry and the types of products and services other businesses offer.

Market reports

Market reports are industry specific. They may give specific information about an industry as a whole. An example of information that could be found in a market report would be ‘46 per cent of adults aged 35–50 visit a coffee shop at least once a month’. This could help a business decide which customers to target.

Government reports

Government reports may consist of general information that is not usually industry specific but can still be useful for a business. Examples include ‘60 per cent of people aged 16–25 would consider working for £6.50 per hour’ or ‘25 per cent of the population is now aged 60 or above’. A business may use this information to decide what level of pay to offer potential employees, who its target market close target market A group of customers which a business aims its product or services at. will be or what kinds of products to develop.

More guides on this topic

• Market segmentation - Edexcel
• Competitive environment - Edexcel
• Customer needs - Edexcel

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• Open access
• Published: 08 November 2023

Policies to prevent zoonotic spillover: a systematic scoping review of evaluative evidence

• Chloe Clifford Astbury 1 , 2 , 3 ,
• Kirsten M. Lee 1 , 2 ,
• Ryan Mcleod 1 ,
• Raphael Aguiar 2 ,
• Asma Atique 1 ,
• Marilen Balolong 4 ,
• Janielle Clarke 1 ,
• Anastassia Demeshko 1 ,
• Ronald Labonté 5 ,
• Arne Ruckert 5 ,
• Priyanka Sibal 6 ,
• Kathleen Chelsea Togño 4 ,
• A. M. Viens 1 , 3 ,
• Mary Wiktorowicz 1 , 2 ,
• Marc K. Yambayamba 7 ,
• Amy Yau 8 &
• Tarra L. Penney 1 , 2 , 3  

Globalization and Health volume  19 , Article number:  82 ( 2023 ) Cite this article

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Emerging infectious diseases of zoonotic origin present a critical threat to global population health. As accelerating globalisation makes epidemics and pandemics more difficult to contain, there is a need for effective preventive interventions that reduce the risk of zoonotic spillover events. Public policies can play a key role in preventing spillover events. The aim of this review is to identify and describe evaluations of public policies that target the determinants of zoonotic spillover. Our approach is informed by a One Health perspective, acknowledging the inter-connectedness of human, animal and environmental health.

In this systematic scoping review, we searched Medline, SCOPUS, Web of Science and Global Health in May 2021 using search terms combining animal health and the animal-human interface, public policy, prevention and zoonoses. We screened titles and abstracts, extracted data and reported our process in line with PRISMA-ScR guidelines. We also searched relevant organisations’ websites for evaluations published in the grey literature. All evaluations of public policies aiming to prevent zoonotic spillover events were eligible for inclusion. We summarised key data from each study, mapping policies along the spillover pathway.

Our review found 95 publications evaluating 111 policies. We identified 27 unique policy options including habitat protection; trade regulations; border control and quarantine procedures; farm and market biosecurity measures; public information campaigns; and vaccination programmes, as well as multi-component programmes. These were implemented by many sectors, highlighting the cross-sectoral nature of zoonotic spillover prevention. Reports emphasised the importance of surveillance data in both guiding prevention efforts and enabling policy evaluation, as well as the importance of industry and private sector actors in implementing many of these policies. Thoughtful engagement with stakeholders ranging from subsistence hunters and farmers to industrial animal agriculture operations is key for policy success in this area.

This review outlines the state of the evaluative evidence around policies to prevent zoonotic spillover in order to guide policy decision-making and focus research efforts. Since we found that most of the existing policy evaluations target ‘downstream’ determinants, additional research could focus on evaluating policies targeting ‘upstream’ determinants of zoonotic spillover, such as land use change, and policies impacting infection intensity and pathogen shedding in animal populations, such as those targeting animal welfare.

The increasing incidence of zoonotic emerging infectious diseases (EIDs) has been attributed to behavioural practices and ecological and socioeconomic change, and is predicted to continue in the coming years [ 1 ]. Higher levels of anthropogenic activity, including agricultural intensification, urbanisation and other forms of land use change, have led to increased interactions between wildlife, humans and livestock, increasing the risk of cross-species transmission [ 2 , 3 , 4 ]. Meanwhile, accelerating rates of globalisation and urbanisation, leading to increased global movement of people and goods and more dense human settlements, have made outbreaks of disease in human populations more difficult to contain [ 5 ]. In response, a call has been issued by leading organisations and experts, including the United Nations Environment Programme, the International Livestock Research Institute and the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services, to complement reactive policy responses with policies that prevent zoonotic EIDs [ 1 , 6 , 7 , 8 , 9 , 10 ]. This approach, sometimes called deep prevention, would need to target upstream drivers to reduce the risk of outbreaks occuring [ 11 ].

Zoonotic spillover, defined as the transmission of a pathogen from an animal to a human, depends on the alignment of ecological, epidemiological and behavioural factors [ 12 ]. Zoonotic pathogens must be transmitted across a spillover pathway (Fig.  1 ) in order to induce infections in humans [ 12 , 13 ]. This involves meeting a series of conditions including appropriate density and distribution of reservoir hosts, pathogen prevalence, infection intensity and human exposure [ 12 ]. Across this pathway, a number of drivers of zoonotic spillover have been identified, including changes in wildlife and livestock populations [ 14 ]; deforestation, urbanisation and other forms of land use change [ 15 , 16 ]; bushmeat consumption [ 17 , 18 , 19 ]; and a variety of human practices including hunting, farming, animal husbandry, mining, keeping of exotic pets and trade [ 8 , 9 , 20 , 21 , 22 ]. These large-scale changes have repeatedly given rise to spillover events [ 2 , 15 , 23 ], sometimes involving pathogens with epidemic or pandemic potential [ 24 ].

Spillover pathway adapted from Plowright et al. [ 12 , 13 ]

The responsibility for addressing zoonotic disease frequently spans multiple sectors of governance due to its relevance for both animals and humans. A One Health perspective, which recognises the health of humans, animals and the environment as being closely linked and inter-dependent [ 25 ], can be useful in understanding the spillover pathway and drivers of spillover events, as well as informing policy and governance approaches to address this cross-sectoral problem. At the international level, the World Health Organization, the Food and Agriculture Organization, the World Organisation for Animal Health and the United Nations Environment Programme have endorsed a One Health approach to policymaking to respond to zoonotic infectious diseases, emphasising collaboration between agencies [ 26 ].

Operationalising a One Health approach to policy

While One Health is a promising approach to preventing zoonotic EIDs, operationalising this concept remains a challenge. Evaluative evidence exists around the effectiveness of interventions to prevent spillover events [ 13 , 27 , 28 , 29 ], however these have often been implemented as short- to medium-term programmes or academic investigations [ 8 ]. In some cases, zoonoses have re-emerged after successful programmes have ended [ 29 ]. As a result, experts have argued for the incorporation of successful interventions into policy frameworks, providing interventions with the sustainability required for long-term disease control [ 8 , 10 ].

Operationalising a One Health approach to policy involves understanding the policy options, identifying the stakeholders involved and developing insights into how to successfully implement and evaluate these policies. Although the longevity and scope of government actions may make policy an effective vehicle for prevention of emerging diseases, implementing policy is a complex process involving numerous actors with competing views and interests [ 30 ]. This context presents challenges for policy development and implementation. Where relevant policies are designed and implemented in isolation, opportunities for co-benefits may be missed and interventions may produce unintended consequences [ 31 ]. Finally, while evaluative evidence is key to informing future policy decisions, the complex systems in which policies are often implemented make evaluation challenging [ 32 ].

Aims and scope

To provide insights around how to use policy to successfully prevent zoonotic spillover events, it is necessary to synthesise the available evaluative evidence. A One Health perspective allows this evidence synthesis to incorporate a wide range of policy instruments and actors and to identify approaches to successfully implementing and evaluating policies in this complex, multi-sectoral context.

Approaches to managing epidemic and pandemic infectious pathogens when they have entered human populations have been systematically catalogued in the medical literature [ 33 , 34 , 35 , 36 , 37 , 38 , 39 ]. These measures include hand washing, face masks, school closures, contact tracing, vaccination and case isolation. Further upstream, systematic reviews of interventions targeting the spillover pathway have predominantly focused on programmes rather than policies, and have been restricted by various characteristics such as geographic region [ 28 ] or pathogen type [ 29 ], or focused on programmes with an explicit endorsement of a One Health approach [ 27 ]. In consequence, a comprehensive understanding of what policies to prevent zoonotic spillover have been evaluated, what actors are involved, and how to successfully implement and evaluate them, is lacking. To address these research gaps, our objective was to synthesise the existing evaluative evidence around policies that target the determinants of zoonotic spillover.

Our approach to identifying and analysing this literature was informed by a One Health perspective, acknowledging the inter-connectedness of human, animal and environmental health.

We conducted a systematic scoping review of evaluations of policies aimed at preventing zoonotic spillover events, based on a previously published protocol [ 40 ]. Results are reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews [ 41 ]. The scoping review was conducted in line with guidelines published by Arksey and O’Malley and refined by Levac and colleagues [ 42 , 43 , 44 ], which emphasise an iterative approach suited to an exploratory research question.

The One Health perspective guided the development of the review methodology. This included the search strategy and inclusion criteria, which allow for the inclusion of policies focused on human, animal or environmental health (or any combination of these areas) and with leadership from one or more of these sectors, and the research questions, which seek to outline the policies and the range of sectors involved in implementation. While our focus on the spillover pathway meant we only included policies that had been evaluated in terms of their impacts on animal and human population distributions, health and interactions, we explicitly searched for environment-focused policies (e.g., protection of wetlands and other wildlife habitats) that might have been evaluated from this perspective. We also aimed to interrogate the One Health approach to governance, by assessing to what extent cross-sectoral collaboration – a key tenet of One Health practice [ 25 ] – emerged as a reason for policy success.

Stage 1: identifying the research question

Informed by our research objective, our research questions were:

What policies aimed at preventing zoonotic spillover (i.e., policies that target the determinants of zoonotic spillover included in the spillover pathway [ 12 ]: population distribution, health and interactions) have been evaluated?

What are the types of policies?

Which policy actors (single department, multi-sectoral, whole of government) are involved?

What are the reasons for policy success and failure, and the unintended consequences of implementing these policies?

How has evaluation of these policies been approached in the literature?

What are the methods or study designs used?

What are the outcomes?

What are the opportunities and challenges for evaluation?

Stage 2: identifying relevant studies

We systematically searched four electronic databases (Medline, Scopus, Web of Science, Global Health) in May 2021. The search strategy was organized by the main concepts in our research question: the spillover pathway; public policy; prevention; and zoonotic pathogens. The search strategy was developed iteratively, informed by existing systematic reviews focused on related concepts [ 28 , 45 , 46 , 47 , 48 , 49 ] and known indicator papers meeting inclusion criteria. We also searched the websites of 18 organisations involved in the prevention of zoonotic spillover to identify relevant grey literature. The choice of organisations was informed by an actor mapping exercise in which we identified key international organisations working on the prevention of emerging zoonoses using network sampling [ 50 ]. We searched the websites of a subset of these organisations, focusing on inter-governmental organisations and organisations whose main focus was zoonotic disease. See Supplementary File 1 for details of academic database and grey literature search strategies.

Stage 3: study selection

Studies were included if they met the following criteria:

Primary empirical study with an English-language abstract from any country or region (reviews were excluded);

Study reporting empirical findings from an evaluation of any sort; and.

Study focused on a policy implemented by government that targets the determinants of zoonotic spillover.

Academic records identified through the searches were collated and double screened using the online platform Covidence [ 51 ]. Two researchers (CCA and KML) initially screened titles and abstracts. Title and abstract screening of an initial set of 100 papers was undertaken by both researchers independently. Results were compared to ensure consistency in decisions around study eligibility, and discrepancies were resolved through consensus. This process was repeated until an acceptable level of agreement (> 90%) was reached. The remaining papers were then screened by one of the two reviewers. Full-text screening was undertaken by two independent researchers and discrepancies were resolved by consensus. Studies with full-texts in any language were eligible for inclusion if they include an English-language abstract. Full-text studies published in French, Spanish or Chinese were single-screened by a member of the research team fluent in that language (CCA or AY). Studies published in other languages were translated as necessary.

Grey literature was screened by one researcher (CCA) to determine whether it met the inclusion criteria. Publications were initially screened by looking at titles, tables of contents and executive summaries. Where these indicated that the publication might be eligible, documents were read in full to determine if inclusion criteria were met.

In line with published guidelines, the approach to study selection was refined iteratively when reviewing articles for inclusion [ 42 , 43 , 44 ].

Stage 4: charting the data

Data charting was conducted using a form designed to identify the information required to answer the research question and sub-research questions (see Supplementary File 2). Data charting focused on characteristics of the study, the policy, and the evaluation. For each policy, this included identifying which determinant of zoonotic spillover situated along the spillover pathway was being targeted. For the purpose of this study, we used a model of the spillover pathway adapted from Plowright et al.’s work [ 12 , 13 ], in which we differentiated between wildlife and domesticated animals (Fig.  1 ). This differentiation is important in the policy context, as the wildlife-domesticated animal interface is an important site for intervention, as well as the human-animal interface.

The data charting form was piloted with ten records to ensure that it was consistent with the research question, and revised iteratively [ 42 , 43 , 44 ]. Data charting was conducted by one researcher (CCA, RM, JC, AD or PS) and checked by a second researcher (CCA or KML). Discrepancies were resolved by consensus.

Stage 5: collating, summarising and reporting the results

Our protocol stated that we would use the Quality Assessment Tool for Quantitative Studies developed by the Effective Public Health Practice Project [ 52 ] to assess study quality [ 40 ]. However, on reviewing the included studies we selected two tools that were more appropriate to their characteristics: (1) ROBINS-I [ 53 ] for quantitative outcome evaluations and (2) a tool developed by the authors of a previous review [ 54 ] – based on Dixon-Woods et al.’s approach to assessing study credibility and contribution [ 55 ] – for all other study types. Two researchers (CCA and KML) assessed study quality independently for an initial set of 10 studies, before comparing assessments and reaching agreement where discrepancies occurred. This process was repeated until an adequate level of agreement was reached (> 90%). The remaining studies were assessed by a single researcher (CCA or KML). Records were not excluded based on quality assessment. Instead, assessments were primarily used to help synthesize the literature on how policies were evaluated. Quality assessment was not performed on grey literature due to the wide variability in the format and comprehensiveness of included publications.

We analysed the charted data, presenting a numerical summary of the included studies in table form, allowing us to describe the range of policy interventions that have been evaluated, aspects of policy implementation and approaches to evaluation. Based on the charted data, we inductively grouped evaluated policies with similar characteristics into policy types and assigned a policy instrument to each policy type: communication/marketing, guidelines, fiscal, regulation, legislation, environmental/social planning or service provision. We mapped policy types onto the spillover pathway shown in Fig.  1 to outline the policies that have been used to target each of these determinants. Thematic analysis was conducted using the approach described by Braun and Clarke where the focus is guided by the researcher’s analytic interests [ 56 ], with five overarching themes chosen as an a priori coding framework: (1) reasons for policy success; (2) reasons for policy failure; (3) unintended consequences of policy implementation; (4) opportunities for policy evaluation; and (5) challenges for policy evaluation. We selected these themes based on our research questions and previous familiarisation with the included articles during the process of article selection, data extraction and quality assessment. Sub-themes were subsequently identified through close reading and coding of the included articles. Thematic analysis was conducted by one researcher (RM) using the qualitative data analysis software Dedoose [ 57 ] and reviewed by the lead author (CCA).

Study characteristics

After removing duplicates, our searches identified a total of 5064 academic records. After screening titles and abstracts, we considered 330 records for full-text review. We also identified 11 relevant publications through our grey literature search. Grey literature reports were published by five organisations: four organisations focused on health and disease, including an intergovernmental organisation (the World Organisation for Animal Health) and three non-governmental organisations (the One Health Commission, the Global Alliance for Rabies Control and EcoHealth Alliance); and one non-governmental organisation focused on wildlife trade (TRAFFIC). In total, we included 95 publications in this review (PRISMA diagram in Fig.  2 ) [ 58 ].

We excluded studies which assessed the unintended consequences of policies to prevent zoonotic spillover without evaluating their effectiveness. This included studies that looked exclusively at the mental health impacts of mandatory livestock culls on farm workers [ 59 ]; studies which focused on potentially relevant factors, such as the wildlife trade, but with no consideration of outcomes situated on the spillover pathway [ 60 ]; and studies which assessed the detection power of surveillance systems without assessing the impact of associated policy interventions [ 61 , 62 , 63 ].

Policy characteristics

The characteristics of the policies evaluated in the included studies are presented in Supplementary File 3 and summarised in Table  1 . Some studies evaluated more than one policy, particularly modelling studies which compared the impacts of several policy options and process evaluations focused on a range of activities undertaken by a single government. Therefore, the number of evaluated policies (n = 111) is greater than the number of included studies (n = 95).

Most policies were evaluated for their impact on human exposure (21%), pathogen prevalence in domesticated animals (18%), barriers within domesticated animals (15%), and pathogen survival and spread in domesticated animals (9%). There were also a number of multi-component policies studies across multiple stages of the spillover pathway (18%). Fewer studies focused on wildlife health and populations, and none of the included studies evaluated policies for their impact on infection intensity and pathogen release in either domesticated animals or wildlife.

Where the government department responsible for implementing a policy was identified in the paper, most policies were implemented by a single department (35%), although there were a number of multi-sectoral efforts (24%). The range of government sectors responsible for implementing policies to prevent zoonotic spillover included human health, animal health, food safety, agriculture, conservation, national parks, forestry, fisheries, environmental protection, border control and foreign affairs. Policies were predominantly intended to be implemented by private sector actors, including individuals and organisations working in trade, retail, hunting and animal agriculture. However, some policies were also implemented by public sector actors working in public health, veterinary public health and environmental conservation.

Most policies were situated in high-income (49%) and upper middle-income (28%) countries, with studies from East Asia and the Pacific (43%) and Europe and Central Asia (19%) dominating. Publications focused on policies targeting various zoonotic diseases, with the most common being avian influenza (50%), rabies (19%), brucellosis (11%) and Hendra virus (4%).

Most policies were evaluated using process (38%) or outcome (31%) evaluation. The most frequently used policy instrument was legislation (59%), particularly for managing pathogen spread in domesticated animals through measures such as mandatory vaccination, culls or disinfection protocols. Meanwhile, communication and marketing or service provision was more typically used to reduce risk in wildlife and human populations, for example by providing guidance around recommended hygiene protocol, by distributing oral vaccination in wildlife habitat or by offering vaccination to human populations.

PRISMA 2020 diagram [ 58 ]

What policies aimed at preventing zoonotic spillover have been evaluated?

Policy types targeted different determinants across the pathway to zoonotic spillover and used various approaches with different evidence of success (Table  2 ). We identified policy options including culling – both general and targeted – of wild and domesticated animals; habitat protection (limiting activities such as agriculture and animal husbandry in wildlife habitats); supplemental feeding to control wildlife movements; vaccination of both wildlife, domesticated animals and human populations with occupational exposure to animals; policies to improve biosecurity in sites where animals are kept, slaughtered and sold, including mandates and information campaigns; live animal market closures; and bans on hunting and selling wildlife. Where outcomes or impacts were evaluated, most policies saw some level of success (i.e., outcome measures were found to vary in a direction that indicated policy success), though relative effectiveness was not assessed due to variation in study design and outcome measure. Policies with consistent evidence of effectiveness – where outcome measures varied in a direction that indicated policy success in all studies included in the review – included culling and sterilisation of wildlife populations, habitat protection, vaccination in wildlife and domesticated animal populations and mandated disinfection protocols. Policies with equivocal evidence of success (i.e., outcome measures varied in different directions or studies had different findings, some indicating success and some indicating failure) included supplemental feeding of wildlife, pre-emptive livestock culls, live animal market closures and bans on wildlife hunting, trade and consumption. For many policies, there were no impact or outcome evaluations identified in this review.

What are the reasons for policy success?

The evidence from the identified impact and outcome evaluations suggests that most of the policies succeeded to some extent. A range of factors contributed to policy success. First, studies emphasized the importance of effective collaboration and coordination between various agencies, disciplines, and levels of government in the execution of policy directives [ 114 , 115 ], in line with a One Health approach to policy and governance. Policy success was attributed, in part, to strong working relationships that encouraged effective communication between various government agencies, and facilitated timely and appropriate policy responses [ 115 ]. Synergy between agencies responsible for surveillance and the execution of control strategies was also reported to be beneficial. For example, prompt communication and effective collaboration between laboratories testing samples and agencies implementing culls in the field was seen as important in the control of highly pathogenic avian influenza in Nigeria [ 116 ]. Similarly, authors also identified the importance of private-public relations and private sector contributions to implementing policies to prevent zoonotic spillover [ 112 ]. This included stronger government engagement with private veterinarians as a factor for success in reducing the spillover of Hendra virus in Queensland [ 109 ], and with farmers, poultry companies and national farming and poultry processing associations in Ghana as part of a successful campaign to reduce risk from highly pathogenic avian influenza [ 112 ]. Studies suggest that the inclusion of private sector stakeholders in the policy process has the potential to improve compliance through transparent dialogue around disease ecology, risk and risk mitigation [ 90 , 91 , 103 , 117 ]; and highlight the utility of participatory approaches in prompting behaviour changes [ 91 ].

Second, authors emphasised the significance of economic incentives, suggesting that policy impact is dependent on private actors’ appraisal of costs and benefits. Studies illustrated how incentives, including compensation, subsidies, rebates, and fines, have had varying degrees of success [ 91 , 97 , 112 , 115 ]. Compensation levels [ 104 , 114 ] and enforcement practices [ 92 ] were identified as salient factors for compliance and adherence. For example, fear of sanctions for bushmeat hunting while a ban was in place in some parts of West Africa were identified as a stronger incentive to avoid bushmeat hunting than the fear of contracting Ebola virus [ 97 ]. Culls were seen as particularly challenging in this regard: while the long-term benefits for farmers may outweigh the financial loss [ 104 ], authorities need to be conscientious of the substantial economic impacts when considering policies that mandate culling or safe disposal [ 95 ]. The direct losses related to compliance (time, labour and expenses) and indirect losses due to price fluctuations and decreases in trade volume, as well as losses to associated industries, are substantial [ 88 , 96 , 113 , 118 ].

Third, trust in government and public support for implemented policy were specified as critical factors influencing the effectiveness of disease control strategies, and research suggests that strategic engagement to facilitate compliance is a necessary step in the policy process [ 97 ]. Participatory approaches that attempt to identify and understand factors influencing compliance have been consistently used to overcome resistance to policy, as insights from engagement and consultation can lead to solutions that facilitate behaviour change at the population level [ 91 , 103 ]. For example, a World Health Organization initiative to reduce avian influenza transmission in poultry markets in Indonesia worked alongside market vendors to achieve its aims, carrying out repeated consultations with the vendors and implementing market infrastructure (such as energy and running water in the market) in collaboration with local authorities to support vendor behaviour change [ 91 ].

Fourth, studies also demonstrated the importance of public communication. The quality of information, as well as the volume, complexity and delivery of public health messages, were key factors [ 75 , 114 ]. Authors contend that communication strategies must understand the target audience and how they interpret and engage with messages [ 97 ], for example by building on relationships where there is exiting trust, such as between veterinarians advising animal vaccination and animal owners [ 117 ]. Homogenously delivered communication strategies were ineffectual: they limited opportunities for open discourse; discounted contradictory lived experiences and expressions of uncertainty; and ultimately contributed to scepticism surrounding implemented policies [ 97 , 117 ].

Finally, studies underscored the importance of surveillance infrastructure to inform intervention strategies. Surveillance programs with the ability to collect and operationalize relevant data were essential to the development of appropriate interventions that are responsive to each unique context [ 115 , 119 ]. Implementing effective surveillance programmes requires the appropriate evaluation tools [ 120 ] and trained personnel [ 81 ].

What are the reasons for policy failure?

Studies showed that perceptions of acceptability and appropriateness were crucial to the effectiveness of implemented policies [ 101 , 104 ]. Several factors were identified that negatively affected acceptability and appropriateness, including: additional expenses for private sector actors without sufficient support [ 75 , 100 , 104 , 112 , 114 ], particularly were culls were demanded but reimbursement for farmers was slow and inadequate, as in a brucellosis eradication campaign in Macedonia [ 81 ]; lack of affordable alternatives [ 97 ]; impracticality of implemented strategies [ 75 , 101 ]; lack of cultural understanding in designing policy interventions [ 97 , 100 ], for example the distribution of footwear to pig farmers in a Polynesian context where footwear was not traditionally worn [ 100 ]; lack of understanding of viral ecology [ 100 ]; as well as public scepticism and distrust [ 97 , 114 ].

Additionally, policy ineffectiveness was associated with poor planning and execution of intervention strategies, including lack of clear direction [ 114 ]; incomplete or inconsistent implementation of control measures (17); limited scope of intervention [ 114 ]; and poor enforcement [ 92 ]. A lack of adequate resources to implement strategies also contributed to policy failure [ 81 ]. Adequate financial resources were necessary to hire and train staff to run surveillance and control operations [ 81 ]. Financial resources were also necessary to fund compensation mechanisms that facilitate compliance. Willingness to adopt policy-prescribed disposal practices was found to be associated with compensation levels (incentives) as a proportion of production price, dependency on income from activities driving zoonotic risk, and contact with prevention staff [ 92 ].

What are the unintended consequences of implementing policies to prevent zoonotic spillover?

A small number of the included studies collected data on the unintended consequences of policies to prevent zoonotic spillover (n = 18). In some instances, unintended consequences were due to disease ecology or human behaviour as a result of policy failure. For example, a study assessing the impacts of the closure of a live poultry market found that, following the closure, vendors travelled to neighbouring markets to sell their animals [ 94 ]. As a result, while cases of avian influenza decreased in the area surrounding the closed market, cases increased in these neighbouring markets, leading to the wider geographic spread of the disease. In another study, elk were provided with supplementary feeding grounds to discourage them from coming into contact with the livestock who shared their range [ 65 ]. While this intervention had the intended consequence of reducing the transmission of brucellosis between elk and livestock, the spread of brucellosis between the elk using the supplementary feeding grounds – who were gathering in larger, tighter groups for longer periods, resulting in higher within-herd transmission – and other elk populations in the area increased. This resulted in an increasing prevalence of brucellosis among the elk, potentially increasing the risk of spillover to livestock. These examples illustrate the complexity of the social and ecological systems in which these policies are implemented, further suggesting the need for a One Health approach to policies to prevent zoonotic spillover.

A key unintended consequence can be attributed to the loss of profits and livelihoods sometimes associated with policies to prevent zoonotic spillover, as described above. The losses incurred by complying with regulations made farmers, hunters and other private sector actors reluctant to report potential infections, contributing to increased unauthorized or illegal activity, and unrestrained spread of disease [ 90 , 92 , 94 , 98 , 112 , 114 ]. Studies investigated the creative ways policy enforcement was circumvented, including hiding hunting equipment on the outskirts of towns or developing informal trade markets and networks [ 97 , 98 ]. Unintended consequences identified in the included evaluations emphasize an opportunity for policymakers to improve sector compliance through public education, levying the influence of consumer attitudes on industry standards [ 104 , 113 ].

A range of study designs were used to evaluate policies. Outcome evaluations (n = 33) used time series or repeat cross-sectional data to conduct evaluations of natural experiments, though most studies did not include a control group for comparison. Outcome evaluations also used case-control and modelling approaches to assess policy impact on an outcome of interest. Process evaluations (n = 30) used cross-sectional and qualitative approaches, as well as study designs combining multiple sources of data, to understand aspects of policy implementation such as the extent to which the policy was being implemented as designed, and the responses and attitudes of stakeholders involved in policy implementation. Economic evaluations (n = 11) included cost-benefit analyses, risk-benefit analyses and modelling studies. Formative evaluations (n = 17) used modelling approaches to estimate what the impacts of a proposed policy option would be in a specific context.

Outcome variables interpreted as indicators of policy success were also numerous and represented determinants along the spillover pathway. As expected, many studies assessed impact on disease transmission, including disease prevalence and incidence, disease eradication, case numbers, and basic reproduction number in human and animal populations, as well as evidence of disease in environmental samples, such as in live animal markets or at carcass disposal sites. Studies also assessed impacts on intermediate factors indicative of successful implementation of specific policies, such as the availability of wild species in markets where a trade ban had been implemented, or knowledge and practices of stakeholders in response to an educational or information campaign.

While most studies found a reduced risk of zoonotic spillover following policy implementation, comparing the magnitude of these impacts was challenging due to the variety of study designs and outcome measures used in the included studies. However, we identified several studies which used modelling to directly compare the impacts of policy options. These studies evaluated various policy scenarios: different combinations within multi-component policy interventions [ 121 ]; culling versus vaccinating wildlife [ 122 ] and livestock [ 84 , 85 ] populations; targeting strategies to humans exclusively versus targeting humans and livestock [ 108 ]; and altering the parameters for culling and vaccination strategies, for example by modelling different ranges for culling and vaccination near infected farms [ 85 ]. These studies often highlighted trade-offs between the effectiveness of policy measures and their cost. For example, estimates of the number of infected flocks were lower when incorporating a ring cull (cull of animals on farms surrounding an outbreak) into a multi-component control strategy for highly pathogenic avian influenza [ 121 ]. However, livestock vaccination was estimated to be a highly effective strategy, with one study findings livestock vaccination to be as or more effective than a pre-emptive cull for outbreak control purposes (depending on the extent of vaccination coverage), while minimising the number of animals culled [ 85 ]. One study jointly modelled costs and benefits of strategies, and found that livestock vaccination had a higher cost-benefit ratio than a wildlife cull [ 122 ]. A final study highlighted the potential of holistic approaches, with drug administration in humans and livestock having a lower cost per disability-adjusted life year averted than intervention in humans alone [ 108 ].

Study authors noted a number of challenges encountered while evaluating policies to prevent zoonotic spillover. One study noted the difficulty of determining the impact of policies aiming to reduce spillover events between wildlife, livestock and humans, as the number of spillover events is often relatively small [ 65 ]. This highlights the importance of considering upstream determinants and risk factors as outcome measures in attempting to evaluate these policies, particularly where spillover events may happen infrequently or not at all during the period of observation. Studying changes in risk factors for spillover can provide insight on the effectiveness of different policies in tackling spillover risk.

Lack of suitable data was a frequently cited barrier to policy evaluation. As policies to prevent zoonotic spillover are often reactive, being implemented in response to an outbreak in animal populations, accessing data from before a policy was implemented was challenging. Studies highlighted the value of routinely collected data, which was often the only data available and was frequently used for policy evaluation [ 65 , 66 , 94 , 115 , 119 , 123 ]. However, in many contexts routine data on animal health is not collected [ 80 ]. Routine testing data from livestock can sometimes be used for evaluation where it exists, but it does not always provide sufficient detail for examining the potential for a policy to prevent zoonotic spillover. For example, some tests do not differentiate between current and past infection, making it difficult to identify where and when spillover occurred [ 65 ], and animal health data may not be granular enough for policy evaluation, particularly in terms of evaluating local policies [ 94 ]. Studies also highlighted instances where the private sector may own data sets reporting disease prevalence and transmission, but may be reluctant to share the data for evaluation purposes [ 121 ]. In such instances, open communication and good relationships with the private sector may be facilitators to evaluation.

Beyond the lack of baseline data, studies highlighted the difficulty in collecting information about policy compliance. As failing to comply often puts farmers and hunters at risk of fines or imprisonment, they were reluctant to disclose information about non-compliance or participation in illegal trade and sale of animals [ 86 , 92 , 97 , 112 ]. This made it difficult to determine policy effectiveness.

Quality assessment

Of the 44 quantitative evaluations, 37 were evaluated as being at moderate or higher risk of bias (see Supplementary File 4), given the possibility of bias in the assessment of intervention impact due to the presence of confounding effects. A small number of studies were determined to be at serious (n = 6) or critical (n = 1) risk of bias, for two main reasons: only having data from after the intervention was implemented; or using a case-control study model without measuring and adjusting for important potential confounders, such as the prevalence of a targeted disease prior to policy implementation. These limitations may reflect the nature of zoonotic spillover events and policy responses, which can happen quickly and leave little time for baseline data collection. Many of the included studies relied on surveillance data, but where such data sets are not available, post-test and case-control study designs may be the only options.

The quality of studies assessed with the tool developed based on Dixon-Woods’ approach [ 55 ] was high overall (n = 41, see Supplementary file 5). Most studies were rated as high in terms of clearly and comprehensively presenting their results (n = 37), analysis (n = 34), research design (n = 33), aims (n = 32) and research process (n = 28). Most studies also had a high relevance to the research question (n = 31), indicating that the research was embedded in policy, being commissioned, co-designed or conducted in partnership with government stakeholders.

We identified a range of policies targeting different parts of the spillover pathway implemented by various policy and governance sectors, including some multi-sectoral initiatives. Policies tended to rely heavily on private sector actors (including actors ranging from small-scale farmers and hunters to larger commercial operations) for implementation, suggesting that open communication and collaboration with these actors was essential for successful policy implementation. Policy success was undermined by lack of collaboration between government agencies; lack of communication between surveillance and control operations; poor understanding of the context in which policies were implemented; and inadequate financial compensation for private sector actors who lost profits and incurred additional costs by complying with policies. Where policies were ineffective, this tended to be due to unintended consequences relating to complex dynamics within the social and ecological systems where policies were implemented. Lack of appropriate data was a key obstacle to policy evaluation, and studies emphasised the importance of robust surveillance infrastructure in evaluating policies that tended to be implemented reactively, in response to an outbreak of zoonotic disease in animal or human populations.

Implications for policy and practice

The key role that the private sector and industry actors play in implementing policies to prevent zoonotic spillover is an important consideration for policymakers. Our findings suggest that many of these policies must be complied with by farmers – from subsistence and smallholder farmers to large corporations – as well as by other actors, such as hunters. Lack of awareness as well as financial costs of compliance among these groups present key barriers to policy success in this area. This set of stakeholders is complex as some may make very marginal profits, if any, and may struggle to afford the additional costs of implementing preventive policies. However, powerful actors and profitable industries are also involved, including large-scale farms and primary resource extraction enterprises [ 22 ]. Acknowledging the differences across these stakeholder groups, and in particular assessing their capacity to bear some of the costs related to prevention, emerges as crucial in successful policy implementation.

Finally, our findings highlight the importance of disease surveillance in efforts to reduce the risk of spillover events. As well as acting as an early warning system, surveillance provides a source of data to evaluate the impact of preventive policies. We found the availability of surveillance data to be a key enabling factor in evaluating policies. In addition, close collaboration between agencies responsible for disease surveillance and control efforts was key to policy success. National surveillance efforts, as well as cross-country collaboration to support global efforts, such as the United States Agency for International Development’s PREDICT program supporting surveillance in areas at high risk for zoonotic disease outbreaks [ 124 ], must be sustained and expanded. In complex areas such as the prevention of zoonotic spillover, approaches to surveillance which encompass risk factors and transmission pathways [ 125 ], as well as One Health surveillance systems which harmonise and integrate data collection and analysis from across human, animal and environmental sectors [ 126 ], are promising approaches to developing surveillance systems that support risk. This context also involves a need to strengthen surveillance capacity in remote and rural locations, as communities living in these contexts may have exposure to numerous pathogens of wildlife origin. This will require strengthening clinical and diagnostic capacity in these settings, as well as engaging with stakeholders such as community human and animal health workers and wildlife or national park rangers [ 127 ].

Comparison with existing literature

This review sought to map the range of policies implemented to reduce the risk of zoonotic spillover, and the various approaches taken to evaluation, and identify factors behind the success and failure of policy implementation and evaluation. Due to this broad scope, comparing relative effectiveness of policy interventions was challenging. Existing systematic reviews with a more specific focus could apply meta-analysis to determine which interventions were most effective. For example, a review of market-level biosecurity measures aiming to reduce the transmission of avian influenza found that reducing market size, separating poultry species, cleaning and disinfecting premises, closing markets and banning overnight storage were highly effective interventions [ 45 ]. However, our findings suggest that studies focused on the control of avian influenza dominate the literature in this space (55 out of 111 evaluated policies), and many of these are focused on market-level measures. Systematic reviews focused on other approaches to reduce spillover risk, such as on-farm biosecurity [ 47 ]; biosecurity for backyard poultry rearing [ 46 ]; and community-based interventions [ 28 ] comment on the paucity of high-quality evidence around the impacts of such approaches. By taking a broad perspective, we hope our findings will provide policy options for consideration in a number of contexts, and guide researchers in focusing their efforts on areas where evidence is lacking.

Strengths and weaknesses of the study

To our knowledge, this is the first attempt to systematically identify and document evaluations of policies aiming to prevent the spillover of zoonotic pathogens into human populations. However, because of the complex drivers of spillover events, some potentially relevant policy evaluations may be excluded where their outcome measures are too far removed from zoonotic spillover. While relevant, such evaluations will be difficult to systematically identify as they make no reference to zoonotic disease.

In addition, this review focused on policy evaluations that have been reported in the peer-reviewed literature and the grey literature published by international agencies and organisations working on these topics. Policies that have been implemented but not evaluated, or evaluated but not published in these literatures, will therefore be excluded from this review. As a result, potentially effective and important policies in the prevention of zoonotic spillover events may not have been identified. However, we hope that the findings from this review will highlight these gaps in the evaluative evidence. We also hope that this review, by extracting practical dimensions, such as study design, outcome measures and the challenges encountered in the evaluation process, will support policymakers and researchers in carrying out further policy evaluations in this space.

Unanswered questions and future research

Our findings highlight several important gaps in the evidence. First, while observational evidence emphasises the importance of upstream determinants such as environmental and ecosystem health in the increasing rate of zoonotic spillover [ 1 , 15 ], we only identified a single evaluation of a policy attempting to target one of these upstream determinants: an evaluation carried out in China to assess the impact of the Ramstar wetland protection program on avian influenza in migratory waterfowl [ 66 ]. This study found that proximity to protected wetlands reduced outbreak risk. Authors hypothesised that this effect was due to the separation of wild waterfowl and poultry populations and the diversion of wild waterfowl away from human-dominated landscapes and toward protected natural habitats. Our findings support existing calls for more quantitative and mechanistic studies of the impact of interventions supporting environmental and ecosystem health on zoonotic spillover risk [ 128 ], as well as calls for greater integration of the environment into One Health research, policy and practice [ 31 ]. Further evaluations of environment and habitat protection policies would strengthen our understanding of this area. In addition, the impact of policies to reduce deforestation or expand forest coverage, such as China’s Grain-to-Green program [ 129 ], on the spillover pathway could be evaluated. Such evaluations might consider potential unintended consequences, as these policies could promote healthier wildlife populations with better disease resistance, but may also facilitate wildlife population growth and higher rates of wildlife-human encounters [ 130 ].

There is also a lack of evaluation of policies targeting infection intensity and pathogen release in either wildlife or domesticated animals. These could include approaches such as improving animal health and welfare to make these populations more resistant to disease [ 13 ]. While arguments have been made for strengthening legal structures supporting animal welfare in order to reduce the risk of zoonotic pathogen transmission [ 131 ], there is a need to evaluate policies that take this approach.

Our review found publications evaluating a wide range of policy interventions spanning the spillover pathway, including habitat protection; trade regulations; border control and quarantine procedures; farm and market biosecurity measures; public information campaigns; and vaccination programmes for wildlife and domesticated animals, as well as human populations with occupational exposure to animals. A wide range of governance sectors implemented these policies, highlighting the prevention of zoonotic spillover as a cross-sectoral issue, though most policies were implemented by a single sector. Our findings highlight the importance of industry and private actors in implementing policies to prevent zoonotic spillover, and the need for thoughtful and effective engagement with this wide range of actors, from subsistence hunters and farmers through to industrial animal agriculture operations to address their concerns through a range of incentives. We also identified the centrality of surveillance data in evaluating policies that are often implemented reactively, and effective collaboration between surveillance and control operations as a central factor in successful policy implementation.

Data Availability

All data generated or analysed during this study are included in this published article and its supplementary information files. Analysis code for descriptive characteristics of included policies is available on GitHub.

Abbreviations

Emerging infectious disease

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CCA, JC and TLP acknowledge internal research support from York University. MW and CCA acknowledge internal research support from the Dahdaleh Institute for Global Health Research. KML acknowledges funding from the Canadian Institutes of Health Research through a Health System Impact Fellowship. AY is funded by the BBSRC through the Mandala project (grant number BB/V004832/1). AMV acknowledges support from York University through a York Research Chair in Population Health Ethics & Law. This review was undertaken as part of a project funded by the Canadian Institutes of Health Research, Grant Reference Number VR5-172686. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Clifford Astbury, C., Lee, K.M., Mcleod, R. et al. Policies to prevent zoonotic spillover: a systematic scoping review of evaluative evidence. Global Health 19 , 82 (2023). https://doi.org/10.1186/s12992-023-00986-x

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