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Writing for Impact in Service Research

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For service researchers, contributing to academic advancement through academic publications is a raison d’être. Moreover, demand is increasing for service researchers to make a difference beyond academia. Thus, service researchers face the formidable challenge of writing in a manner that resonates with not just service academics but also practitioners, policy makers, and other stakeholders. In this article, the authors examine how service research articles’ lexical variations might influence their academic citations and public media coverage. Drawing on the complete corpus of Journal of Service Research ( JSR) articles published between 1998 and 2020, they use text analytics and thereby determine that variations in language intensity, immediacy, and diversity relate to article impact. The appropriate use of these lexical variants and other stylistic conventions depends on the audience (academic or the public), the subsection of this article in which they appear (e.g., introduction, implications), and article innovativeness. This article concludes with an actionable “how-to” guide for ways to increase article impacts in relation to different JSR audiences.
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Scholarly Article
Writing for Impact in Service Research
Chahna Gonsalves
1
, Stephan Ludwig
2
, Ko de Ruyter
1
,
and Ashlee Humphreys
3
Abstract
For service researchers, contributing to academic advancement through academic publications is a raison d’ˆ
etre. Moreover,
demand is increasing for service researchers to make a difference beyond academia. Thus, service researchers face the formidable
challenge of writing in a manner that resonates with not just service academics but also practitioners, policy makers, and other
stakeholders. In this article, the authors examine how service research articles’ lexical variations might influence their academic
citations and public media coverage. Drawing on the complete corpus of Journal of Service Research (JSR) articles published between
1998 and 2020, they use text analytics and thereby determine that variations in language intensity, immediacy, and diversity relate
to article impact. The appropriate use of these lexical variants and other stylistic conventions depends on the audience (academic
or the public), the subsection of this article in which they appear (e.g., introduction, implications), and article innovativeness. This
article concludes with an actionable “how-to” guide for ways to increase article impacts in relation to different JSR audiences.
Keywords
article impact, service research, lexical variation, text mining, writing style
The impact of service research articles defines their contribution
to science, economy, society, the environment, and culture.
Research article impact, typically proxied through citations and
media coverage, matters for service researchers’ field recogni-
tion, career prospects, and funding. It also defines the prestige
of institutions, journal editors, and entire scientific disciplines.
But how can service researchers increase the impact of their
articles?
Many service research articles achieve modest impact both
in academia and with the general public. Within the service
discipline, Journal of Service Research (JSR) articles are
among the most well-cited, high-impact publications (see Web
Appendix 1 for an overview of service journals’ journal impact
factor and Hindexes; Bitner 2014). Yet approximately 28%of
its articles have 10 cites or fewer (measured July 2020). In
addition, approximately 36%have yet to receive a single media
mention (Altmetric 2020). The research topics could be a rea-
son, but rigorous and conscientious review processes are in
place to ensure the quality of content. The articles’ impact,
or lack thereof, instead might depend on how they are written
and who is reading them (Crosier 2004). Even academics fre-
quently suggest that articles are written in an overly compli-
cated manner, and journal review teams commonly ask authors
to improve their writing style. Chief marketing officers simi-
larly attribute their relative lack of interest in academic articles
to the dense, impersonal, and emotionless writing style (Ben-
nett 2007), noting that the knowledge is “lost in translation”
(Shapiro, Kirkman, and Courtney 2007, p. 249). Other than an
unfounded suggestion to mimic stylistic conventions of current
or award-winning academic articles (Baron 2018), little gui-
dance is available for service researchers on how to write for
impact.
Prior research offers valuable insights on the influence of
university reputation, author affiliation, and journal rankings
on article impact (Stremersch, Verniers, and Verhoef 2007).
Extant studies also relate the general readability of marketing
articles to citations and best-paper awards (Sawyer, Laran, and
Xu 2008). However, these factors are largely beyond the con-
trol of individual scholars, especially junior researchers, or are
straightforwardly solved with the help of a copy editor. Several
stylistic conventions (e.g., framework illustrations, explicit
statement of contributions) might improve impact (Ortinau
2011), though we lack any empirical proof of such effects.
Accordingly, new, actionable insights on how to write for
impact may derive from conceptualizations about lexical var-
iations (Bradac, Bowers, and Courtright 1980), which posit that
intensity, immediacy, and diversity might influence the impact
of written texts. Critically, however, the appropriate uses of
lexical variants may depend on the articles’ target readership
1
King’s College Business School, King’s College, London, United Kingdom
2
The University of Melbourne, Victoria, Australia
3
Medill School of Journalism, Northwestern University, Evanston, IL, USA
Corresponding Author:
Chahna Gonsalves, King’s College London, Bush House, 30 Aldwych, London
WC2B 4BG, United Kingdom.
Email: chahna.gonsalves@kcl.ac.uk
Journal of Service Research
1-20
ªThe Author(s) 2021
Article reuse guidelines:
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DOI: 10.1177/10946705211024732
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(academia or the public), the subsections in which the variants
appear (Baron 2018), and the relative innovativeness of the
topics discussed (Chandy 2003).
With this study, we aim to offer three primary insights for
service researchers that might help them increase the academic
and public impact (i.e., citations and media coverage) of their
articles. First, we systematically derive and empirically assess
the influence of lexical variations (intensity, immediacy, and
diversity) and stylistic conventions on article impact, across all
JSR articles published before 2020. We thereby extend previ-
ous research on nontextual (e.g., author, institution) and gen-
eral readability impact factors. Second, we show that the
appropriate use of the lexical variants depends on the article
subsection in which they are used and the article’s relative
innovativeness. Third, we offer an expansive set of actionable
propositions, pitfalls, and challenges related to how to write
articles to achieve greater academic and public impact.
Conceptual Background
Research article impact relates to the extent to which an arti-
cle’s ideas or findings influence subsequent academic research,
as well as public and managerial stakeholders (Franke, Edlund,
and Oster 1990). An article’s academic impact is typically
proxied using citation counts (Thelwall 2012). The general
public’s uptake of scholarly works can be assessed by tracing
an article’s influence on organizations and actors that transcend
the university sector (Wilsdon et al. 2015). Impact measures
pertaining to public uptake, such as Alternative metrics (Alt-
metrics), often take the sum of article-related press releases,
case studies, public policy documents, and patents, as well as
public, social, and alternative media (Altmetric 2017; Born-
mann, Haunschild, and Adams 2019; Costas, Zahedi, and Wou-
ters 2015; Gumpenberger, Gla¨nzel, and Gorraiz 2016;
Mukherjee, Subotic´, and Chaubey 2018; Ozanne et al. 2017;
Thelwall et al. 2013). Prior research into what influences
research articles’ academic impact shows that university repu-
tation, affiliation, and journal ranking matter (Li, Sivadas, and
Johnson 2015; Stremersch, Verniers, and Verhoef 2007). The
impact of service research articles also is fundamentally driven
by their content and style. These influences are inextricably
related; great ideas resonate if they are communicated in a style
that makes them accessible (Rynes, Bartunek, and Daft 2001).
With regard to content, for example, articles’ academic
impact depends on the degree to which they build on existing
knowledge bases (Stewart and Zinkhan 2006). Impact may
further depend on generalizability, and many editors seek stud-
ies with insights across sectors (De Ruyter, Wetzels, and Van
Birgelen 1999). Although impact does not seem to depend on
whether researchers use a qualitative or quantitative approach
(Mingers and Xu 2010), the use of mixed methods is often
suggested to boost resonance with academic readers (Creswell
and Clark 2017).
Stylistically, common suggestions to increase impact
include using (1) explicit outlines or enumeration of contribu-
tions for the reader (Reinartz 2016), (2) a diagram to illustrate
the conceptual framework, (3) short titles (Baron and Russell-
Bennett 2016), (4) more key words (Stremersch, Verniers, and
Verhoef 2007), and (5) quantifications to illustrate relevance
(e.g., “few studies,” “little research”; Swales 1990). Such style
features are common to academic convention and may have
positive potential for citation impact, yet may not necessarily
influence the media coverage the article receives. In addition,
writing style serves as a quality proxy of content that can influ-
ence impact (Judge et al. 2007). According to communication
and linguistics research, the manner of reasoning, rather than
the strength of the reasons given, predicts impact (Seibold,
Lemus, and Kang 2010). Therefore, writing style can influence
readers’ article evaluations both directly and indirectly (Born-
mann and Daniel 2009), which should be critical to article
impact (Baron and Russell-Bennett 2016). Advising research-
ers to practice lexical entrainment and adapt their own writing
style to those of existing publications may be too generic or
abstract though. Which elements should be mimicked?
To address specific lexical variants that might improve audi-
ence resonance and impact, we turn to the theory of lexical
variation (Bradac, Bowers, and Courtright 1979, 1980), which
proposes that lexical variations in intensity, immediacy, and
diversity are pivotal in producing audiences’ inferences. These
lexical variations encapsulate the semantic, syntactic, and prag-
matic levels of writing, respectively (Mick 1986). Their rela-
tive use naturally varies across people, groups, and
communication contexts. By purposefully varying their use,
speakers can guide impression formation (Bradac, Bowers, and
Courtright 1979). Studies emphasize the importance of lexical
variation to direct audiences’ attention (Hamilton and Hunter
1998), trigger attitude change (Hamilton, Hunter, and Burgoon
1990), and elicit relational perceptions (e.g., similarity; O’Sul-
livan, Hunt, and Lippert 2004). For example, variation in lan-
guage intensity influences attitude change indirectly by
enhancing message clarity (Hamilton, Hunter, and Burgoon
1990) and perceived message strength (Hamilton and Stewart
1993). O’Sullivan, Hunt, and Lippert (2004) find that more
immediate language (e.g., first- and third-person pronouns)
increases the perceived psychological closeness, competence,
and credibility of the speaker. Tausczik and Pennebaker (2010)
further suggest that lexical diversity may affect the perceived
credibility of message content. Therefore, varying intensity,
immediacy, and diversity in service research articles may influ-
ence their impact. We present our expectations about the asso-
ciation between lexical variations, lexical variation in different
subsections of an article, the innovativeness of the topic, which
moderates this effect, and article impact (summarized in
Tables 1 and 2).
The Influence of Lexical Variants on Impact
Intensity is defined as “language indicating the degree and
direction of distance from neutrality” (Burgoon and King
1974, p. 241). It manifests through the use of positive or neg-
ative affect words (Berger and Milkman 2012). As an example
of a service research article with high levels of intensity (e.g.,
2Journal of Service Research XX(X)
Table 1. Results for Lexical Variation on Citations.
Variable
Entire Article Entire Article Abstract Introduction
Conceptual Back-
ground
Theoretical Implica-
tions
Managerial Implica-
tions Future Research
Model 1a Model 2a Model 3 Model 4 Model 5 Model 6 Model 7 Model 8
bzbzbzbzbzbzbzbz
Lexical variation
Intensity 0.12** 13.75 0.20** 19.61 0.00 0.44 0.18** 15.62 0.20** 14.23 0.10** 6.44 0.08** 5.78 0.14** 10.27
Immediacy 0.28** 22.29 0.26** 18.75 0.05** 5.30 0.07** 4.63 0.46** 26.80 0.09** 7.04 0.17** 14.28 0.19** 17.22
Diversity 0.38** 15.78 0.32** 11.91 0.04** 3.44 0.01 0.72 0.23** 12.54 0.05* 2.39 0.06** 4.01 0.04* 2.35
Intensity sq. 0.09** 13.80 0.04** 6.85 0.09** 14.61 0.14** 13.47 0.03** 3.59 0.01 0.84 0.11** 13.10
Immediacy sq. 0.04** 6.92 0.07** 11.77 0.11** 11.50 0.09** 6.66 0.04** 3.70 0.08** 6.33 0.02 1.61
Diversity sq. 0.17** 7.56 0.13** 18.90 0.04** 6.41 0.14** 18.82 0.02** 3.77 0.08** 10.23 0.04** 7.93
Control features
Contribution statement 0.15** 7.15 0.15** 7.63 0.09** 4.67 0.12** 5.76 0.18** 8.86 0.14** 6.86 0.09** 4.64 0.19** 9.60
Framework 0.12** 6.69 0.09** 4.62 0.31** 16.61 0.13** 7.36 0.09** 4.65 0.12** 6.29 0.12** 6.56 0.12** 6.38
Title words 0.03** 3.16 0.03** 2.92 0.07** 7.77 0.05** 5.68 0.06** 6.92 0.04** 4.47 0.04** 4.32 0.02* 2.44
Key words 0.06** 5.24 0.04** 3.53 0.05** 4.51 0.08** 7.45 0.00 0.25 0.03* 2.38 0.05** 4.93 0.05** 4.98
Quantifiers 0.29** 22.49 0.26** 19.63 0.12** 11.20 0.00 0.24 0.04* 2.18 0.18** 12.35 0.16** 13.59 0.06** 5.02
Quantifiers sq. 0.08** 15.18 0.07** 13.91 0.02** 2.80 0.05** 6.21 0.10** 7.20 0.08** 9.18 0.02** 3.86 0.01 0.67
Readability 0.08** 6.29 0.08** 5.77 0.24** 12.55 0.46** 17.58 0.11** 3.56 0.29** 12.62 0.53** 20.93 0.07** 2.81
Word count 0.53** 29.42 0.51** 27.87 0.31** 17.27 0.18** 10.38 0.22** 11.90 0.09** 4.38 0.05** 3.06 0.24** 12.83
Number of references 0.06** 4.60 0.04** 2.69 0.20** 22.12 0.21** 21.11 0.15** 14.37 0.23** 24.48 0.17** 16.61 0.21** 22.11
Across sectors 0.12** 6.70 0.13** 7.34 0.20** 11.05 0.17** 9.64 0.13** 7.26 0.16** 9.19 0.10** 5.62 0.16** 9.21
Quantitative 0.24** 7.96 0.28** 9.04 0.84** 33.31 0.69** 28.26 0.61** 25.35 0.70** 28.89 0.76** 31.32 0.63** 26.00
Quantitative and Qualitative 0.05 1.48 0.07* 1.96 0.68** 20.69 0.53** 15.99 0.39** 11.98 0.48** 14.94 0.67** 19.92 0.34** 10.57
Innovativeness 0.21** 20.19 0.25** 23.30 0.25** 23.03 0.26** 25.71 0.28** 26.13 0.26** 25.44 0.22** 20.52 0.24** 22.27
Award winner 1.08** 37.38 1.08** 37.04 1.00** 31.53 1.19** 41.28 1.10** 37.33 1.17** 41.43 1.02** 34.93 1.23** 43.14
Number of authors 0.04** 4.23 0.05** 5.40 0.00 0.54 0.05** 5.16 0.00 0.47 0.00 0.45 0.00 0.08 0.01 1.58
U.S. affiliation 0.12** 7.50 0.15** 9.02 0.01 0.47 0.09** 5.70 0.11** 6.65 0.06** 3.44 0.12** 7.12 0.09** 5.27
Article age 0.95** 76.56 0.96** 76.12 1.00** 66.92 0.82** 67.46 0.84** 70.03 0.81** 67.69 0.83** 67.45 0.86** 70.25
Press release 0.06** 8.81 0.06** 9.20 0.05** 7.75 0.00 0.74 0.07** 10.04 0.02** 3.13 0.04** 6.06 0.05** 7.95
Log-likelihood 5,949.62 5,787.25 6,127.24 6,333.54 6,200.61 6,781.17 6,302.29 6,363.66
Pseudo R
2
.61 .62 .59 .58 .59 .55 .58 .58
Note. Subject area effects are controlled for in the model, and correlations are reported in Web Appendix 3. Citations ¼385 Journal of Service Research articles.
*p< .05 (two-tailed). **p< .01.
3
Table 2. Results for Lexical Variation on Media Coverage.
Variable
Entire article Entire article Abstract Introduction
Conceptual back-
ground
Theoretical implica-
tions
Managerial implica-
tions Future research
Model 1b Model 2b Model 9 Model 10 Model 11 Model 12 Model 13 Model 14
bzbzbzbzbzbzbzbz
Lexical variation
Intensity 0.17** 5.14 0.03 0.38 0.15* 2.10 0.11 1.78 0.03 0.36 0.27** 4.81 0.09 1.68 0.21** 4.42
Immediacy 0.26** 5.15 0.28** 5.12 0.09* 1.99 0.09 1.38 0.15* 1.98 0.22** 3.91 0.01 0.14 0.23** 4.59
Diversity 0.15 1.46 0.15 1.42 0.14** 3.55 0.17** 3.16 0.23** 3.05 0.22** 3.00 0.04 0.64 0.28** 3.83
Intensity sq. 0.08** 2.63 0.15** 3.89 0.05* 2.05 0.11** 3.05 0.20** 6.95 0.10* 2.86 0.11** 4.56
Immediacy sq. 0.15** 4.26 0.05 1.72 0.17** 3.50 0.18** 3.13 0.26** 8.27 0.00 0.04 0.04 0.75
Diversity sq. 0.15 1.78 0.06** 2.96 0.07* 2.34 0.01 0.22 0.03 0.97 0.02 0.71 0.10** 3.27
Control features
Contribution statement 0.18* 2.51 0.16* 2.26 0.22** 3.04 0.25** 3.32 0.13 1.78 0.13 1.88 0.14 1.94 0.19** 2.69
Framework 0.09 1.32 0.09 1.23 0.13 1.85 0.03 0.43 0.03 0.43 0.03 0.39 0.04 0.66 0.01 0.20
Title words 0.13** 4.22 0.13** 3.91 0.05 1.59 0.10** 3.19 0.16** 5.15 0.12** 3.65 0.10** 3.04 0.11** 3.35
Key words 0.10* 2.24 0.07 1.75 0.14** 3.10 0.16** 3.79 0.05 0.97 0.06 1.45 0.15** 3.36 0.08 1.78
Quantifiers 0.36** 5.90 0.33** 5.51 0.11** 2.68 0.19** 3.64 0.42** 5.80 0.35** 6.72 0.02 0.49 0.04 0.75
Quantifiers sq. 0.23** 5.50 0.16** 3.41 0.04* 2.05 0.04 1.31 0.00 .04 0.06* 2.44 0.01 0.79 0.12** 3.26
Readability 0.00 0.00 0.01 0.23 0.13 1.90 0.31** 2.99 0.18 1.48 0.28** 3.24 0.05 0.45 0.46** 4.84
Word count 0.18 1.92 0.17 1.76 0.44** 7.04 0.07 1.11 0.30** 3.67 0.30** 3.67 0.20* 2.54 0.22** 2.59
Number of references 0.35** 5.48 0.35** 5.45 0.17** 3.61 0.14** 2.95 0.15** 2.70 0.21** 4.59 0.17** 3.80 0.14** 3.02
Across sectors 0.27** 3.84 0.34** 4.54 0.48** 6.55 0.24** 3.32 0.23** 3.24 0.30** 4.11 0.24** 3.45 0.38** 5.46
Quantitative 0.24 1.64 0.21 1.42 0.78** 6.62 0.77** 6.29 0.65** 5.42 0.49** 3.97 0.68** 5.46 0.57** 4.52
Quantitative and Qualitative 0.20 1.13 0.20 1.17 0.41* 2.54 0.32 1.89 0.37* 2.29 0.02 0.10 0.21 1.27 0.24 1.40
Innovativeness 0.10* 2.35 0.10* 2.30 0.16** 3.61 0.19** 4.24 0.20** 4.58 0.15** 3.49 0.21** 4.88 0.12** 2.79
Award winner 0.04 0.12 0.02 0.07 0.10 0.35 0.03 0.11 0.17 0.53 0.12 0.40 0.07 0.24 0.13 0.42
Number of authors 0.20** 6.06 0.18** 5.34 0.14** 3.83 0.15** 4.13 0.14** 4.04 0.14** 4.13 0.20** 5.88 0.16** 4.80
U.S. affiliation 0.50** 7.36 0.52** 7.61 0.45** 6.91 0.60** 9.31 0.56** 8.73 0.61** 9.16 0.50** 7.55 0.49** 7.23
Article age 0.14** 3.00 0.17** 3.52 0.26** 5.32 0.11* 2.49 0.11** 2.63 0.10* 2.15 0.00 0.06 0.05 1.03
Press release 0.13** 2.94 0.08 1.72 0.20** 4.47 0.15** 3.11 0.06 1.35 0.16** 3.67 0.15** 3.55 0.06 1.27
Log-likelihood 1,046.85 1,031.50 1,005.90 1,041.69 1,026.39 1,036.20 1,087.50 1,029.07
Pseudo R
2
.38 .39 .40 .38 .39 .39 .35 .39
Note. Subject area effects are controlled for in the model, and correlations are reported in Web Appendix 3. Media coverage ¼298 Journal of Service Research articles.
*p< .05 (two-tailed). **p < .01.
4
30%higher than the average), many citations, and extensive
media coverage, Hennig-Thurau et al. (2010) open with the
statement: “The ways consumers communicate with each other
have been changing dramatically over the last decade, and the
same is true for how consumers gather and exchange informa-
tion about products and how they obtain and consume them” (p.
311, emphasis added). Research on affect suggests a relation-
ship between the increased use of affective language and
impression formation, attitudes, and behavior (Hamilton and
Hunter 1998). Intensity enhances the dynamism of a message,
which increases attention to it (Hamilton and Stewart 1993;
Hong and Li 2017). The mere presence of affective words in
written text increases cognitive involvement, which enhances
the likelihood of behavioral response (Peters, Kashima, and
Clark 2009). Higher intensity communication styles also make
factual information more accessible to readers (Zajonc 1980).
Therefore, articles that appear interesting and stimulate desire,
through some emotional connection, are more likely to be read
and downloaded by the public (Baron and Russell-Bennett
2016). Research in marketing further shows that intensity
increases intentions to forward emails (Eckler and Bolls
2011) and share news articles (Berger and Milkman 2012), the
likelihood of rating a message as helpful (Li and Zhan 2011),
and customer reviews’ impact on purchase decisions (Ludwig
et al. 2013). Milkman and Berger (2014) similarly find that
emotionally intense language enhances social media sharing
of scientific synopses among members of the public. Therefore,
articles with greater intensity likely attain more academic cita-
tions and more media coverage than less intensely written arti-
cles, and we posit:
P1: Generally, a greater degree of intensity is associated
with more citations.
P2: Generally, a greater degree of intensity is associated
with more media coverage.
Immediacy pertains to the degree to which language creates a
psychological sense of closeness or distance. Greater immediacy
is linked to the increased use of the present tense, first-person
singular pronouns (e.g., “I,” “me,” “my”), and discrepancies
(e.g., “should,” “would,” “could”), as well as the reduced use
of articles and long words (Pennebaker and King 1999). Such
language marks engaging social interactions and implies aware-
ness of the message recipient (Borelli et al. 2011; Mehrabian
1967). Immediacy has been associated with positive communi-
cative outcomes of academic and public discourses (e.g., Ma¨rz,
Schubach, and Schumann 2017), including enhanced affective
and cognitive learning from educational messages (Allen, Witt,
and Wheeless 2006) and perceptions of websites’ source com-
petence, trustworthiness, and credibility (O’Sullivan, Hunt, and
Lippert 2004). By using immediate language such as “we find
that,” rather than “it was found that,” authors can strengthen
their implied ownership of the arguments and findings (Gilbert,
Gilbert, and Mulkay 1984). Societal and managerial audiences
thenmaytendtolinksuchverbalownership(e.g.,“my
findings”) to greater content credibility. However, in academic
articles, impersonality and stylistic anonymity are considered
desirable features, seemingly because less immediate language
signals more objective, convincing reporting of academic find-
ings (Hyland 2002) and less psychological or personal involve-
ment by the researcher (Borelli et al. 2011). In service research,
as an example of low levels of immediacy (e.g., 28%lower than
the average), we note Brady and Cronin (2001), which has been
cited extensively but has attracted no media coverage; the arti-
cle’s opening statement reads: “It is widely acknowledged that
successful organizations need to have a customer-oriented busi-
ness culture” (p. 241). We expect that greater immediacy in
service research articles reduces subsequent academic citations.
However, articles written with greater immediacy should reso-
nate better with the general public and garner more media cov-
erage. Accordingly:
P3: Generally, a greater degree of immediacy is associated
with fewer citations.
P4: Generally, a greater degree of immediacy is associated
with more media coverage.
Diversity, which refers to the range or “richness” of the voca-
bulary used, also may have a decisive influence on a service
research article’s impact. In service research, for example, Coll-
ier and Bienstock (2006) use moderate diversity, with an illus-
trative opening statement that reads: “Delivering quality in
services has been shown to be an important strategy for market-
ers who are trying to differentiate their service offerings by
establishing customer value and satisfying customer needs” (p.
260). None of these words is unique within the article; each of
them is repeated (some several times). When it comes to diver-
sity though, academic researchers and societal or managerial
audiences have widely divergent preferences. As determined
by the number of unique words, relative to the total number of
words in a text, diversity affects the perceived credibility of
message content (Tausczik and Pennebaker 2010). Some studies
argue that academic readers and peer reviewers prefer complex-
ity and evaluate less readable articles more favorably (Bauerly,
Johnson, and Singh 2006; Stremersch, Verniers, and Verhoef
2007). Diversity also appears positively associated with aca-
demic readers’ judgments of the authors’ intellectual compe-
tence (Armstrong 1980). Such factors might partially explain
why Collier and Bienstock’s (2006) paper is cited so heavily.
In contrast, among societal and managerial audiences, a general
consensus is that the diverse language is challenging to read and
unnecessarily hinders understanding (Crosier 2004). Compre-
hension of a text might depend on the extent to which readers
know the words used (Pressley and Wharton-McDonald 1997),
and a more lexically diverse text imposes greater demands on
readers’ vocabulary knowledge. To the extent that reading lexi-
cally diverse texts requires more cognitive effort, it may deplete
cognitive resources and push readers to seek familiar, easily
processed texts, which they find more enjoyable to read (Alter
and Oppenheimer 2009). Considering the link between enjoy-
ment and engagement with texts (Berger and Milkman 2012),
we anticipate that complex articles, which are processed less
Gonsalves et al. 5
fluently and enjoyed less, may be less likely to have societal and
managerial impacts. That is, lexically diverse language might
improve academic audiences’ quality judgments but reduce gen-
eral readership. Formally:
P5: Generally, a greater degree of diversity is associated
with more citations.
P6: Generally, a greater degree of diversity is associated
with less media coverage.
The Asymmetric (Nonlinear) Influence of Lexical Variants
on Impact
When examining the theoretical and analytical importance of the
link between the use of lexical variants and overall article impact,
we also recognize that the relationship could be asymmetric or
nonlinear. Rather than straightforward predictors, lexical variants
might function better at moderate levels of use. For example,
emotionless framing may reduce engagement with academic arti-
cles, even among academic readers (Holbrook 1986; Ladik and
Stewart 2008), but extremely intense articles also might violate
academic communication norms and conventions and prompt
questions about reliability and scientific neutrality (Giles et al.
1987). Similarly, the broader public likely interprets excessive
intensity as a persuasion attempt (Rocklage, Rucker, and Nordg-
ren 2018), which could invoke their resistance (Friestad and
Wright 1994) or negative attitudes (Campbell and Kirmani
2000). An overt use of immediacy could lead academic readers
to worry about objectivity of the author and reduce credibility for
societal and managerial audiences (Burgoon and Le Poire 1993),
likely reducing the article’s impact. Diverse language also may
be necessary to express research ideas rigorously, evoking greater
credibility, though past some level, even academics might find
the writing too complicated (Clayton 2015). Relatedly, journal
review teams frequently request reducing complexity (Bagchi
et al. 2017). Extreme diversity also can exclude general readers
(Badley 2019). So, excessive diversity likely reduces article
impact among academic, societal, and managerial readers (Schar-
rer et al. 2012). Therefore, we predict that the effects of intensity,
immediacy, and diversity on article citations diminish (or
reverse) with excessive use. At high levels, increasing the use
of each lexical variant should not affect article impact as drama-
tically as it does at lower levels.
P7: Intensity, immediacy, and diversity have an inverted U-
shaped effect on citations.
For general readers, the effects of the lexical variants also
should diminish (or reverse) with relatively excessive use:
P8: Intensity, immediacy, and diversity have an inverted U-
shaped effect on media coverage.
The Moderating Effect of Subsections on Impact
Academic papers tend to adhere to a well-established sche-
matic structure, as reflected in the main sections of each
manuscript. The structures may vary with the nature of the
research, but common sections include the abstract, introduc-
tion, conceptual background, theoretical implications, manage-
rial implications, and further research. Each section serves a
unique purpose, which may alter the influence of the lexical
variants on article impact (Biber, Connor, and Upton 2007).
For example, the introductory section delineates the appropri-
ate frame of reference, argues for research relevance, identifies
potential gaps, and outlines the contributions. Intensity in this
section thus might serve to capture readers’ attention (Day
2017). Even if the effectiveness of intensity may taper off for
the research audience, general readers find very intense lan-
guage engaging in introductions (Crosier 2004). The concep-
tual background section provides a matter-of-fact discussion of
existing evidence pertaining to each key construct and the rela-
tionships among them (Ortinau 2011). Authorial suppression
and impersonality conveyed through phrases such as “the
authors argue ... and “previous studies conclude that ...”is
advised in the conceptual background to communicate appro-
priate integrity to the academic and general reader and enable
them to focus on the conceptual underpinnings (Hyland 2002).
In the implications sections, authors elaborate on inferences
and the relevance of their findings for academic and societal
and managerial readers (Thelwall 2019). Due to their diverse
target readers, it is suggested that the theory and managerial
implications sections should feature intense, lively language
that engages readers and underscore the relevance of the
research (Ortinau 2010), with moderate complexity to resonate
across audiences (Tapp 2004). Finally, most articles contain a
limitations and further research section (Ortinau 2010). Sum-
mers (2001) suggests intensity in these sections is counterpro-
ductive; rather, limitations and suggestions for research should
be presented objectively (nonimmediate verbiage) and ration-
ally (emotionless language). Therefore, we propose that the
effects of intensity, immediacy, and diversity on academic cita-
tions are not only curvilinear but are also differentially mod-
erated by the subsection of the article.
P9: The relation of the (a) inverted U-shaped use of inten-
sity, (b) U-shaped use of immediacy, and (c) inverted U-
shaped use of diversity with citations varies differentially
by article subsection.
1
However, we expect the direction of the curvilinear effects
of intensity, immediacy, and diversity on media coverage may
be reversed. Therefore, we propose:
P10: The relation of the (a) U-shaped use of intensity, (b)
inverted U-shaped use of immediacy, and (c) U-shaped used
of diversity with media coverage varies differentially by
subsection.
The Moderating Effect of Article Innovativeness
The innovativeness of an article’s ideas likely influences sub-
sequent citations and media coverage (Johnson 2003). Articles
6Journal of Service Research XX(X)
that are diverse in their references and draw from a “variety of
disciplinary perspectives” (Tellis, Chandy, and Ackerman
1999, p. 121) might confer an impact advantage by providing
new perspectives on a topic that are conceptually distant from
the article’s discipline (Bettencourt and Houston 2001). How-
ever, innovative content is relatively unfamiliar and more com-
plicated to process, so the appropriate use of lexical variants
may be even more important for relatively radical articles
(Chandy 2003). The inherent inseparability of content and style
dictates an investigation of their joint effect. Intensity, for
example, tends to boost engagement more with relatively com-
plex information (Duhan et al. 1997) because affective infor-
mation is easier to represent and access from memory (Ortony,
Clore, and Foss 1987). Immediacy allows researchers to
emphasize and seek support for their innovative contributions
but may dissuade academic and general readers by sending a
clear indication of the perspective from which the content
should be interpreted (Hyland 2002). With limited prior knowl-
edge though, simple message framing enhances the likelihood
that a message is understood (Wagner, Baccarella, and Voigt
2017). Lexical diversity may not affect academic readership as
considerably (Bauerly, Johnson, and Singh 2006), but innova-
tive perspectives might best be presented straightforwardly, to
facilitate wider understanding and exert greater societal and
managerial impact (Gray, Grundva
˚gOttesen,andMatear
2005). In summary, the influence of the lexical variants on
academic citations and media coverage should vary with the
relative innovativeness of the article.
P11: Relative innovativeness of the article’s topic moder-
ates the impact of the lexical variants, such that (a) the use
of intensity increases citations even more, (b) the use of
immediacy reduces citations even more, and (c) the use of
diversity increases citations even more.
P12: Relative innovativeness of the article’s topic moder-
ates the impact of the lexical variants, such that (a) the use
of intensity increases media coverage even more, (b) the use
of immediacy reduces media coverage even more, and (c)
the use of diversity reduces media coverage even more.
Empirical Study
Setting and Sample
We collected all JSR articles published prior to July 2020,
along with information about citations from Web of Science
and Google Scholar. We also account for information about the
publishing authors and publication dates from the Institute for
Scientific Information’s Social Sciences Citation Index (ISI-
SSCI). All articles and article information were collected
through downloading and parsing. Three coders, independent
of the study, separated each article into conventional subsec-
tions (i.e., abstract, introduction, conceptual background, the-
oretical implications, managerial implications, and future
research suggestions); because other sections (e.g., data,
results) are not consistently included in every article (e.g., con-
ceptual articles, qualitative research), we excluded them from
our analysis, to ensure comparability. The initial sample con-
tained 467 articles. Similar to Stremersch, Verniers, and Ver-
hoef (2007), we excluded editorials, conceptual reviews, and
published calls for research (82 in total).
Measurement Development
Academic citations and media coverage. The number of Web of
Science citations offers a common measure of academic impact
(Gruber 2014). To measure media coverage, we retrieved the
Altmetric impact score, available at Altmetric.com (Davis and
Ozanne 2019; Repiso, Castillo-Esparcia, and Torres-Salinas
2019; Thelwall and Nevill 2018). The Altmetric attention score
(AAS; Ortega 2020) also tracks academic articles listed in
ISI-SSCI using a digital object identifier, which enables
researchers to monitor online attention to their research outputs
(Holmberg and Vainio 2018). A proprietary, composite score,
the AAS is calculated by adding multiple, weighted metrics,
which assign value to various events and sources (Altmetric
2019). Some authors raise concerns about the arbitrariness of
AAS weightings, its validity, and the shortcomings associated
with combining different metrics in the same count (Gumpen-
berger, Gla¨nzel, and Gorraiz 2016; Mukherjee, Subotic´, and
Chaubey 2018). However, Altmetric.com also offers wider
coverage of alternative metrics than providers such as PlumX
or Impact Story (Ortega 2018), and the AAS correlates strongly
with media-related indicators of impact (Ortega 2020). There-
fore, we believe the AAS, calculated using count data, provides
valuable insights into article impact when used as a comple-
ment (cf. alternative) to traditional citation metrics (Gruber
2014; Haustein, Costas, and Larivi`ere 2015). Bornmann,
Haunschild, and Adams (2019) also affirm the convergent and
discriminant validity of the AAS for mentions of research in
news media, Facebook, blogs, Wikipedia, and policy docu-
ments. Furthermore, we assert that studies that indicate a weak
correlation of the AAS with citation-based impact indicators
(Costas, Zahedi, and Wouters 2015; Thelwall et al. 2013) actu-
ally indicate the AAS captures attention to research articles, as
a dimension of societal impact (Bornmann, Haunschild, and
Adams 2019). Accordingly, various studies use the AAS to
measure awareness and engagement with research articles
beyond academia (Davis and Ozanne 2019). We had access
to scores for 298 of the JSR articles in our data set.
Lexical variation measures. Following Hamilton and Stewart
(1993), we operationalized language intensity as a composite
score of the proportion of positive and negative affect words
(e.g., “good,” “surprising,” “struggle”). In line with previous
research in marketing (e.g., Berger and Milkman 2012), we use
the Linguistic Inquiry and Word Count (LIWC) dictionary to
calculate the proportion of affect words in each article and
subsection. For immediacy, we follow Ma¨rz, Schubach, and
Schumann (2017) and obtain a composite measure of the pro-
portion of first-person singular pronouns (e.g., “I,” “we”) and
present-tense verbs (e.g., “get,” “use”), as well as inverse pro-
portions of discrepancies (e.g., “should,” “would”), words with
Gonsalves et al. 7
more than six letters and articles (e.g., “a,” “an,” “the”). A
higher score indicates a more personal, immediate communi-
cation style. We calculate lexical diversity using a type-token
ratio (Chamblee et al. 1993) or the ratio of the number of
unique (i.e., distinct) words in the document (types) to its total
number of words (tokens). The resulting proportion of vocabu-
lary size for each article indicates its degree of diversity.
Article innovativeness is defined as the reliance on knowl-
edge sources that are less traditional and more conceptually
distant from current service research and marketing thought
(Bettencourt and Houston 2001; Johnson 2003). To measure
article innovativeness, we count the total number of refer-
ences in a given article and measure the percentage of these
references that derive from outside service and marketing
research. Articles that are less diverse in their sources of
knowledge, and presumably less innovative, would have a
large number of references to other marketing research stud-
ies which are the proximal disciplines for service research
(Johnson 2003).
Control measures. We account for several stylistic features that
may influence impact, according to previous research.
Coders, independent of the study, dummy coded each article
as 1 if it includes an explicit contribution statement (e.g.,
“thereby we contribute,” “against this backdrop we study”)
and 0 otherwise. Similarly, they coded articles as 1 if a con-
ceptual framework was included and 0 otherwise (Ortinau
2011). We note the number of words in articles’ titles (title
words; Baron and Russell-Bennett 2016), the number of key
words used, and the number of references (excluding self-
citations), all gathered from Web of Science (Stremersch,
Verniers, and Verhoef 2007). To account for the length of
each article and subsection, we use the total word count.A
composite measure reflects the proportion of numbers and
quantifier words (derived using LIWC), indicating articles’
degree of quantification (Swales 1990). As a measure of read-
ability, we use the Dale-Chall Readability Score (Sawyer,
Laran, and Xu 2008). Coders noted whether each article (1)
presented findings across service sectors (De Ruyter, Wet-
zels, and Van Birgelen 1999), (2) was based exclusively on
quantitative results, or (3) included both quantitative and qua-
litative results (coded 1) or not (coded 0; Creswell and Clark
2017; Mingers and Xu 2010). Some subjects of study may be
more cited than others. To control for the general subject areas
covered in an article, we mined the articles for any mention of
any of the 1,150 topic identifier key words derived by Stre-
mersch, Verniers, and Verhoef (2007). We then classified for
each article whether it discussed any of the nine subject areas
(coded 1; i.e., product management and branding, business-
to-business, relationship marketing, marketing communica-
tions and sales, strategy and international marketing, pricing,
methods, consumer behavior, and retailing and e-commerce)
or not (coded zero). We include these dummy variables across
all our models.
We controlled for several external features of the articles
that previous research has linked to their impact: the number of
authors, whether the first author has a U.S. affiliation (i.e.,
employed by a U.S. university or institution ¼1ornot ¼0),
whether (¼1) or not (¼0), the article was a JSR Best Paper
award winner, and the age of the article as the number of years
since its publication (e.g., Li, Sivadas, and Johnson 2015; Stre-
mersch and Verhoef 2005). Third, in line with Humphreys
(2010) and Trusov, Bucklin, and Pauwels (2009), we include
apress release measure of the number of press releases con-
taining the full title and journal information within a year of the
article’s publication date, obtained from the Dow Jones Factiva
database (https://global-factiva-com). Web Appendix 3 offers
greater detail about each measure operationalization, and Web
Appendix 4 includes the means, standard deviations, and cor-
relations for 385 JSR articles.
Modeling Approach
To assess impact in terms of academic citations, we specified a
series of Poisson models that account for the negatively skewed
number of academic citations (27.6%of articles have 10 cita-
tions or fewer, skewness ¼8.922; Cameron and Trivedi 2013).
For media attention, we accounted for the number of null media
mentions (36.34%with no mentions [July 2020], skewness ¼
9.71), then conducted negative binomial and zero-inflated
Poisson regression analyses. Because the zero-inflated Poisson
regression was a better predictor of observed articles without
mentions, we only report its outcomes. The general regression
model results indicate the effects of article style, content, and
external features, which we summarize for academic citations
in Table 1 and media coverage in Table 2 (see also Figure 1),
along with specific effects for each subsection. In Table 3, we
reveal how the effects depend on the relative innovativeness of
the article. For interpretability, we standardized all predictor
variables.
Results
We organize this discussion by lexical variant, starting with the
overall results (P
1
–P
6
), then the nonlinear impact (P
7
and P
8
),
and finally the different subsections (P
9
and P
10
) and relative
topic innovativeness (P
11
and P
12
).
Intensity
Considering the overall implications for citations of articles in
JSR (Table 1, Model 1a), we find that more intensity in writing
increases citations (b
Intensity
¼0.12, p< .01) and media cover-
age (b
Intensity
¼0.17, p< .01; Table 2, Model 1b), in line with
P
1
and P
2
, respectively. As we anticipated in P
7
, the effect of
intensity on citations is nonlinear and follows an inverted U
shape, tapering off at greater values (b
Intensity
¼0.20, p< .01;
b
Intensity Sq.
¼0.09, p< .01; Table 1, Model 2a). The positive
relation between intensity and media coverage is linear, con-
trarytoP
8
(b
Intensity
¼0.03, p¼.70; b
Intensity Sq.
¼0.08,
p< .01; Table 2, Model 2b). With regard to the relation
between articles’ use of intensity and citations, we find they
8Journal of Service Research XX(X)
vary across the respective subsections (Table 1, Models 3–8;
see also Web Appendix 5, in line with P
9
. For the introduction
(b
Intensity
¼0.18, p< .01; b
Intensity Sq.
¼0.09, p< .01), con-
ceptual background (b
Intensity
¼0.20, p< .01; b
Intensity Sq.
¼
0.14, p< .01), theoretical implications (b
Intensity
¼0.10, p<
.01; b
Intensity Sq.
¼0.03, p< .01), and future research (b
Intensity
¼0.14, p< .01; b
Intensity Sq.
¼0.11, p< .01) sections, greater
intensity relates to more citations until it becomes excessive,
where the effect follows an inverted U shape. The use of inten-
sity in abstracts (b
Intensity
¼0.00, p¼.66; b
Intensity Sq.
¼0.04, p
< .01) follows a U shape, such that using either very little or a
great deal of intensity relates positively to citations. In the
managerial implications section, more intensity is always better
(b
Intensity
¼0.08, p< .01; b
Intensity Sq.
¼0.01, p¼.40). For
intensity across subsections and media coverage, we also find
differences, in line with P
10
(Table 2, Models 9–14; Web
Appendix 6). Specifically, the use of more intensity in the
introduction (b
Intensity
¼0.11, p¼.07; b
Intensity Sq.
¼0.05,
p< .05) and managerial implications sections (b
Intensity
¼
0.09, p¼.09; b
Intensity Sq.
¼0.10, p< .05) increase media
coverage. Intensity in the abstract (b
Intensity
¼0.15, p< .05;
b
Intensity Sq.
¼0.15, p< .01) relates positively to media
coverage until it becomes excessive, following an inverted
U shape. The relations of the use of intensity in the conceptual
background (b
Intensity
¼0.03, p¼.72; b
Intensity Sq.
¼0.23,
p< .01), theoretical implications (b
Intensity
¼0.27, p< .01;
b
Intensity Sq.
¼0.20, p< .01), and future research (b
Intensity
¼
0.21, p< .01; b
Intensity Sq.
¼0.11, p< .01) subsections with
media coverage all follow a U shape. Noting the actual distri-
bution of observations (Web Appendix 6), that the maximum
impact of intensity on media coverage is at the lowest level of
intensity; therefore, less intensity in these subsections relates to
more media mentions, but increased use relates increasingly
negatively to it. Contrary to P
11
, the use of more intensity in
articles providing innovative perspectives relates negatively to
citations (b
Intensity and Innovativeness
¼0.12, p< .01; Table 3,
Model 15). With regard to P
12
, we find no significant effect of
intensity on media coverage (b
Intensity and Innovativeness
¼0.04,
p¼.34) of articles that feature innovative perspectives
(Table 3, Model 16).
Immediacy
For the overall implications of citations of articles in JSR
(Table 1, Model 1a), in line with our expectations (P
3
), more
immediacy in writing decreases citations (b
Immediacy
¼0.28,
p< .01). Moreover, as predicted by P
4
, greater immediacy
relates positively to subsequent media coverage (b
Immediacy
¼
0.26, p< .01; Table 2, Model 1b). Contrary to P
7
, the effect of
immediacy on citations is linear; excessive immediacy leads to
even fewer citations (b
Immediacy
¼0.26, p< .01; b
Immediacy Sq.
¼0.04, p< .01; Table 1, Model 2a). The positive relation
between immediacy and media coverage is also nonlinear, as
predicted by P
8
. The positive effect of using more immediacy
on media coverage follows an inverted U shape, where exces-
sive use reduces media coverage even more (b
Immediacy
¼0.28,
p< .01; b
Immediacy Sq.
¼0.15, p< .01; Table 2, Model 2b). For
the relation between articles’ use of immediacy and citations
(Table 1, Models 3–8; Web Appendix 5), we find hardly any
variation across subsections (partial support for P
9
). Only in
abstracts is a moderate use of immediacy associated with the
greatest impact on citations, following an inverted U shape,
where using too little or too much reduces them (b
Immediacy
¼0.05, p< .01; b
Immediacy Sq.
¼0.07, p< .01). Although
we find a nonlinear U-shaped relation between immediacy and
citations, our observations in Web Appendix 5 clarify that the
use of more immediacy in the introduction (b
Immediacy
¼
0.07, p<.01;b
Immediacy Sq.
¼0.11, p< .01), conceptual
background (b
Immediacy
¼0.46, p< .01; b
Immediacy Sq.
¼
0.09, p< .01), theoretical implications (b
Immediacy
¼0.09, p
< .01; b
Immediacy Sq.
¼0.04, p< .01), and managerial implica-
tions (b
Immediacy
¼0.17, p< .01; b
Immediacy Sq.
¼0.08, p<
.01) sections relates negatively to citations, following a U
shape (each negative effect tapers off slightly with greater
Figure 1. Overall style implications of lexical variations for citations and media coverage.
Gonsalves et al. 9
immediacy). In the future research section, more immediacy
relates negatively to citations (b
Immediacy
¼0.19, p<.01;
b
Immediacy Sq.
¼0.02, p¼.11). We find differences in the
relation between the use of immediacy across subsections and
media coverage, as anticipated by P
10
(Table 2, Models 9–14;
Web Appendix 6). Specifically, immediacy in the introduction
(b
Immediacy
¼0.09, p¼.17; b
Immediacy Sq.
¼0.17, p< .01),
conceptual background (b
Immediacy
¼0.15, p< .05; b
Immediacy
Sq.
¼0.18, p< .01), and theoretical implications (b
Immediacy
¼
0.22, p< .01; b
Immediacy Sq.
¼0.26, p< .01) has the greatest
effect on media coverage at moderate use, following an
inverted U shape, but the positive effect tapers off at very high
uses. In the abstract (b
Immediacy
¼0.09, p< .01; b
Immediacy Sq.
¼0.05, p¼.09) and future research sections (b
Immediacy
¼
0.23, p<.01;b
Immediacy Sq.
¼0.04, p¼.45), immediacy
negatively relates to media coverage. Its use does not relate
significantly to media coverage for the managerial implication
subsection (p> .10 for both main and squared effects). In
contrast with P
11
, increased use of immediacy does not relate
significantly to citations of articles that provide innovative
perspectives (b
Immediacy and Innovativeness
¼0.00, p< .91; Table 3,
Model 15). As predicted by P
12
, increased use of immediacy
relates negatively to subsequent media coverage of articles
with greater innovativeness (b
Immediacy and Innovativeness
¼
0.26, p< .01; Table 3, Model 16).
Diversity
More diversity increases citations (b
Diversity
¼0.38, p< .01), in
line with P
5
(Table 1, Model 1a), but it has no significant effect
on media coverage (b
Diversity
¼0.15, p< .15), contrary to P
6
(Table 2, Model 1b). In line with P
7
, the effect of diversity on
citations is nonlinear. The positive relation to citations is great-
est at a moderate to high use of diversity, following an inverted
U shape and tapers off at excessive use (b
Diversity
¼0.32,
p< .01; b
Diversity Sq.
¼0.17, p< .01; Table 1, Model 2a).
With regard to P
8
, diversity has no significant nonlinear impact
on media coverage (Table 2, Model 2b; b
Diversity
¼0.15,
p¼.16; b
Diversity Sq.
¼0.15, p¼.08). Considering the dis-
tribution of diversity uses across JSR articles (Figure 1), the
impact of diversity on media coverage is highest at moderate
use. For diversity and citations (see Table 1, Models 3–8; Web
Appendix 5), we find variation across subsections, in support of
P
9
. In the introduction (b
Diversity
¼0.01, p¼.47; b
Diversity Sq.
¼
0.04, p< .01), conceptual background (b
Diversity
¼0.23,
p< .01; b
Diversity Sq.
¼0.14, p< .01), and future research
(b
Diversity
¼0.04, p< .05; b
Diversity Sq.
¼0.04, p< .01) sub-
sections, the relationship follows an inverted U shape; that is,
moderate uses of diversity in these sections relate to the great-
est number of citations, whereas the use of a little or a great
deal of diversity reduces them. In the abstract (b
Diversity
¼
0.04, p< .01; b
Diversity Sq.
¼0.13, p< .01), theoretical
implications (b
Diversity
¼0.05, p<.01;b
Diversity Sq.
¼
0.02, p< .01), and managerial implications (b
Diversity
¼
0.06, p< .01; b
Diversity Sq.
¼0.08, p< .01) subsections,
greater use of diversity relates negatively to citations. Consid-
ering the relation between the use of diversity across the sub-
sections and media coverage, we find differences that are in
line with P
10
(Table 2, Models 9–14; Web Appendix 6). In
abstracts, diversity’s relation to media coverage is exponen-
tially positive (b
Diversity
¼0.14, p< .01; b
Diversity Sq.
¼0.06,
p< .01), such that coverage increases especially with exceed-
ingly diverse word use. But greater diversity in the conceptual
background (b
Diversity
¼0.23, p< .01; b
Diversity Sq.
¼0.01,
p¼.83), theoretical implications (b
Diversity
¼0.22, p< .01;
b
Diversity Sq.
¼0.03, p¼.33), and future research (b
Diversity
¼
0.28, p< .01; b
Diversity Sq.
¼0.10, p< .01) subsections
relates negatively to subsequent media coverage. Diversity in
the introduction (b
Diversity
¼0.17, p<.01;b
Diversity Sq.
¼
0.07, p< .05) relates negatively to media coverage (Web
Appendix 6), following a U shape. We find no significant
Table 3. Results for Lexical Variation and Innovativeness on Citations
and Media Coverage.
Variable
Citations Media Coverage
Model 15 Model 16
bzbz
Lexical variation
Intensity 0.19** 17.63 0.03 0.39
Immediacy 0.23** 16.35 0.22** 3.71
Diversity 0.35** 13.13 0.30* 2.53
Intensity sq. 0.12** 16.35 0.08** 2.63
Immediacy sq. 0.05** 7.36 0.14** 3.96
Diversity sq. 0.15** 6.22 0.11 1.32
Control features
Contribution statement 0.16** 7.85 0.13 1.81
Framework 0.08** 4.43 0.07 1.03
Title words 0.01 1.35 0.10** 3.21
Key words 0.04** 3.30 0.07 1.59
Quantifiers 0.24** 18.65 0.35** 5.74
Quantifiers sq. 0.06** 11.46 0.18** 4.02
Readability 0.09** 6.49 0.01 0.27
Word count 0.53** 28.64 0.20 1.94
Number of references 0.06** 4.53 0.37** 5.70
Across sectors 0.13** 7.33 0.35** 4.56
Quantitative 0.28** 9.14 0.17 1.17
Quantitative and qualitative 0.08* 2.19 0.20 1.10
Innovativeness 0.25** 21.38 0.11 1.29
Award winner 1.10** 37.24 0.07 0.22
Number of authors 0.05** 5.83 0.20** 5.96
U.S. affiliation 0.18** 10.69 0.54** 7.86
Article age 0.96** 75.89 0.20** 3.79
Press release 0.07** 10.48 0.09 1.94
Content and style features
Innovativeness Intensity 0.12** 12.52 0.04 0.96
Innovativeness Immediacy 0.00 0.11 0.26** 3.01
Innovativeness Diversity 0.02 0.94 0.57** 3.31
Log-likelihood 5,706.28 1,026.14
Pseudo R
2
.62 .39
Note. Subject area effects are controlled for in the model, and correlations are
reported in Web Appendix 3. Citations ¼385 JSR articles; media coverage ¼
298 JSR articles; JSR ¼Journal of Service Research.
*p< .05 (two-tailed). **p < .01.
10 Journal of Service Research XX(X)
relation between the use of diversity in the managerial impli-
cations section and media coverage (b
Diversity
¼0.04, p¼
.52; b
Diversity Sq.
¼0.02, p¼.47). In contrast with P
11
,we
find no significant effect of diversity on citations for innovative
articles (b
Diversity and Innovativeness
¼0.02, p¼.35). However, in
line with P
12
, the use of diversity relates positively to media
coverage (b
Diversity and Innovativeness
¼0.57, p< .01) of articles
that discuss rely on innovative and conceptually distant per-
spectives (Table 3, Models 15 and 16).
Control Features
The use of contribution statements increases academic citation
rates (b
Contribution Statement
¼0.15, p< .01), as do conceptual
frameworks (b
Frameworks
¼0.12, p< .01) and the number of key
words (b
Key words
¼0.06, p< .01; see Table 1, Model 1a).
Longer titles (b
Title words
¼0.03, p< .01) reduce citations.
Quantifying tactics follow a U-shaped curve (b
Quantifiers
¼
0.29, p< .01; b
Quantifiers Sq.
¼0.08, p< .01). As expected,
articles that are written in a more readable manner (b
Readability
¼
0.08, p< .01) and longer articles (b
Word Count
¼0.53, p<.01)
receive more citations. Similar to their effect on citations, longer
titles decrease subsequent media coverage (b
Title words
¼0.13,
p< .01). Contrary to expectation, the use of contribution state-
ments (b
Contribution Statement
¼0.18, p< .05) and more key
words (b
Key words
¼0.10, p< .05) decreases subsequent media
coverage (Table 2, Model 1b). We find no significant effect of
the inclusion of conceptual frameworks (b
Frameworks
¼0.09,
p¼.19), readability (b
Readability
¼0.00, p¼.10), or article
length (b
Word Count
¼0.18, p¼.06) on media coverage. Quan-
tifiers, which follow an inverted U shape, should be employed
moderately for optimal impact on media coverage (b
Quantifiers
¼
0.36, p<.01;b
Quantifiers Sq.
¼0.23, p< .01) as their effect
tapers off with excessive use.
To boost citations, researchers should aim to limit citation
of prior work (b
Number of References
¼0.06, p< .01). Incor-
porating insights across more than one service sector
increases citations (b
Across Sectors
¼0.12, p< .01). In general,
purely quantitative articles (b
Quantitative
¼0.24, p< .01)
receive fewer citations than purely qualitative ones. We find
no significant effect of using mixed methods on citations
(b
Quantitative and Qualitative
¼0.05, p¼.14). Incorporating
more outside marketing references, hence being more inno-
vative is negatively associated with citations (b
Innovativeness
¼
0.21, p< .01). In line with prior research, we find that
articles that win awards garner more citations (b
Award Winner
¼1.08, p< .01). Increasing the number of authors negatively
influences citations (b
Number of Authors
¼0.04, p<.01),and
U.S.-affiliated authors get cited less (b
U.S. Affiliation
¼0.12,
p< .01). Older articles have more time and thus accumulate
more citations (b
Article Age
¼0.95, p< .01), and press releases
increase citations (b
Press Release
¼0.06, p<.01)
To boost media coverage, researchers should embed their
work in prior research (b
Number of References
¼0.35, p< .01) and
advance relatively innovative perspectives (b
Innovativeness
¼
0.10, p< .05). Articles that examine multiple sectors also
achieve greater media coverage (b
Across Sectors
¼0.27, p<
.01). Whether the study uses quantitative (b
Quantitative
¼0.24,
p¼.10), mixed (b
Quantitative and Qualitative
¼0.20, p¼.26) or
qualitative approaches makes no difference. Larger author
teams (b
Number of Authors
¼0.20, p< .01) and U.S.-affiliated
authors (b
U.S. Affiliation
¼0.50, p< .01) receive greater media
coverage. Interestingly, winning a Best Paper Award (b
Award
Winner
¼0.04 p¼.91) has no effect on media coverage. We
find that older articles (b
Article Age
¼0.14, p<.01)and
articles with associated press releases (b
Press Release
¼0.13,
p< .01) are covered less in public media. We acknowledge that
the online-based scraping mechanism of Altmetric might miss
earlier (nondigital) media coverage.
Robustness Checks
In line with prior research (e.g., Costas, Zahedi, and Wouters
2015; Mingers and Xu 2010), we used the Web of Science
citation count measure as an indicator of academic impact.
As a robustness check, we confirm that the Google Scholar
citation count correlates with the Web of Science citation count
at r¼.983 (Web Appendix 4).
Discussion
These analyses offer insights into how service researchers can
increase the impact (citations and media coverage) of their
articles in JSR. Beyond corroborating previous findings about
nontextual aspects (e.g., author institution), we demonstrate
that both stylistic and content considerations influence aca-
demic impact and media coverage. Our findings contrast with
prevalent literature on the drivers of article impact, which tends
to emphasize the role of content in shaping article outcomes
(Stremersch, Verniers, and Verhoef 2007). We must emphasize
that it is not our intention to be prescriptive with regard to
writing style; there must always be room for service researchers
to develop their own approaches to writing for impact and for
these styles to evolve dynamically as the journal matures. What
we have tried to do in this article, however, is to make some of
these writing practices more transparent and some of the lexical
variations more explicit. In exploring Bradac, Bowers, and
Courtright (1979), we have shown how lexical variation can
play a major role in enhancing the citations and media coverage
of a JSR article. The results suggest guidelines for using pri-
mary lexical variants (intensity, immediacy, and diversity),
which authors can follow to boost their articles’ impact. The
effectiveness of these lexical variants varies across audiences
and article subsections. There is no “one-size-fits-all” approach
to academic citations and media coverage. That said, we iden-
tify several drivers specific to each type of impact, for the
benefit of researchers, journal editors, and publishers.
Drivers of Academic Citations
Intensity enhances the dynamism of verbatim content, and this
dynamism then increases attention and readers’ responsiveness
Gonsalves et al. 11
(Berger and Milkman 2012; Ludwig et al. 2013). Building on
this finding, our results suggest that a moderate to high use of
intensity inspires interest among academic readers. Consider
the following writing style example:
Consumers generally expect good service, and when service pro-
viders fail to deliver on their promises, consumers may express
their disappointment in many different ways, ranging from simply
“swallowing it” to switching to a different service provider ...to
retaliating verbally and physically (Komarova Loureiro, Haws, and
Bearden 2018, p. 184, emphasis added).
The range of affect words signals the authors’ departure from
neutrality, making this text excerpt quite intense. Previous
research has shown that readers interpret intensity as an indica-
tion of value, relevance, and intrinsic “interestingness” (Ladik
and Stewart 2008). We add that increasing intensity, relative to
an unengaging, emotionless style, by including affective words
(e.g., “better,” “careful,” “surprising,” “critical”) has a positive
impact on the number of academic citations. Our findings sug-
gest that researchers should reduce intensity when introducing
relatively innovative perspectives. Specifically, we find that sur-
passing an intensity threshold (ideally, approximately 4%of
total words) can reduce subsequent citations.
Although immediacy enhances the communicability and
actionability of texts, service researchers aiming for academic
impact are advised to limit it. Our analysis of JSR articles
shows that less immediacy is better, except in abstracts where
articles with a moderate degree of immediacy receive more
citations (e.g., Collier and Bienstock 2006). This result aligns
with a convention that defines impersonality as a desirable
feature for academic writing (Hyland 2002). Authors should
use an impersonal style and increase the use of discrepancies
(e.g., “should,” “would,” “could”) to make their writing and
presentation of viewpoints more probabilistic.
Finally, service researchers should use a moderate degree of
diversity in their vocabulary (approximately 16%of all words
in an article should be unique). Readers tend to regard a diverse
vocabulary as an indicator of competence (O’Sullivan, Hunt,
and Lippert 2004). In line with Stremersch, Verniers, and Ver-
hoef’s (2007) suggestions, we find that lexical diversity
increases citations, except for the abstract, theoretical, and
managerial implications subsections. In these sections, toward
the end of their articles, service researchers should strive to
reduce diversity and instead relay their implications using
familiar, nonunique wording.
Citations also relate to stylistic conventions and article con-
tent. In contrast with prior research, we find that JSR articles
receive more citations when they are written in a readable
manner (according to the Dale Chall readability index; Stre-
mersch, Verniers, and Verhoef 2007). Citing more references is
negatively related to article citations which suggests that ser-
vice research relies on prior work in a different way to other
fields. In addition, JSR articles that expand their focus across
multiple service sectors are cited more, perhaps due to their
broader relevance and generalizability; we also find more
citations for JSR papers that are based on qualitative (cf. quan-
titative) methods.
Contrary to expectations, we do not find that innovative JSR
articles that extensively draw on sources external to marketing
and service research receive more citations. Peter and Olson
(1983) suggest that researchers may be more inclined to per-
spectives and theories drawn from familiar domains. However,
service research is a relatively young, interdisciplinary domain
and the integration of innovative (outside) perspectives con-
tribute to valuable advancement (Gustafsson et al. 2016). To
increase citations, authors of more innovative articles should
consider reducing the intensity of their writing. Table 4 sum-
marizes our specific findings and implications, including some
exemplary articles for service researchers.
Drivers of Media Coverage
As a general observation, a greater degree of intensity drives
more attention to JSR articles among popular media. Ideally,
about 4.9%of all words in an article should be affect words.
Yet intensity decreases the probability of extended media
coverage when used in the conceptual background, theoretical
implications, and future research subsections. In composing
these parts of their articles, service researchers should refrain
from using intensity and instead might adopt a more matter-
of-fact style. A moderate to high use of immediacy in all
article subsections except the abstract and future research
relates positively to media coverage (e.g., Sok et al. 2018).
For example, using “we find that” rather than “it was found
that” enables authors to strengthen their ownership of the
arguments and findings they present (Gilbert, Gilbert, and
Mulkay 1984). However, excessive uses of immediacy can
diminish media coverage. This finding is in line with prior
research that suggests affinity-seeking cues increase commu-
nicationeffectivenessonlyuptoapoint,beyondwhichimme-
diate language negatively influences perceptions of
objectivity (Burgoon and Le Poire 1993). It appears that the
use of relatively more diverse vocabulary in the conceptual
background, theoretical implications, and future research sec-
tion of the article reduces media coverage. This finding aligns
with previous research that argues for an accessible writing
style to engage nonacademic audiences (Crosier 2004; Stre-
mersch, Verniers, and Verhoef 2007). Contrary to expecta-
tions, we find that diversely written abstracts gain attention
in popular press. Therefore, researchers should leverage
diverse wording in their article abstracts as a mechanism to
encourage public stakeholders to read further.
Across subsections, a moderate use of quantifiers to support
claims and arguments relates positively to media coverage.
General readability and article length, in contrast, have no
significant effect. If JSR articles contain more references, they
get mentioned more in the popular press, as do articles that
address multiple service sectors and those presenting innova-
tive perspectives. Editors and reviewers might consider that
innovative articles that create buzz and have a higher premium
for sharing serve core functions of science: discovery,
12 Journal of Service Research XX(X)
dissemination, and discussion. Therefore, crowd-sourcing
attention fosters the journal’s primary goal of sharing science.
We do not find significant effects for the type of methodology
used. Detailed suggestions for using lexical variants to drive
media coverage, as well as exemplar JSR articles, are given in
Table 5.
Table 4. Drivers of Academic Citations
Category Proposition Result
Implications to Increase Cita-
tions Exemplar References
Lexical variation P1: Generally, a greater degree
of intensity is associated with
more citations
Supported Try to intensify writing and
offer more affect (e.g.,
“struggle,” “surprising,”
“good”) to avoid neutrality
Jaakkola and Alexander
(2014)
P3: Generally, a greater degree
of immediacy is associated
with fewer citations
Supported Try to maintain an impersonal
style in writing (e.g., “one,”
“should”)
Brady and Cronin (2001)
P5: Generally, a greater degree
of diversity is associated with
more citations
Supported Try to increase diversity in
writing (e.g., using a wide
range of unique vocabulary)
Collier and Bienstock
(2006)
Extreme use of lexical
variants
P7: Intensity, immediacy, and
diversity have an inverted U-
shaped effect on citations
Supported Try to (a) use a moderate to
high degree of intensity
(while avoiding excessive
use; approximately 4.3%
affect words), (b) use a more
impersonal writing style (no
more than an immediacy
score of approximately .7),
and (c) use a moderate to
high degree of diversity
(approximately 16% unique
words)
Intensity: Jones et al.
(2007)
Immediacy: Dallimore,
Sparks, and Butcher
(2007)
Diversity: Collier and
Bienstock (2006)
Moderating role of article
subsection
P9: The relation of the (a)
inverted U-shaped use of
intensity, (b) U-shaped use of
immediacy, and (c) inverted
U-shaped use of diversity
with citations varies
differentially by article
subsection
Partially supported Consider alternative writing
approaches across different
article subsections and
thereby try (a) to use
moderate to high intensity
for all subsections except
their abstract and managerial
implications, where greater
intensity is better, (b) to use
an impersonal writing style
across all subsections except
for the abstract, where a
moderate use of immediacy
is better, and (c) use a
moderate to high degree of
diversity across all
subsections except the
abstract, theoretical, and
managerial implication
subsections where lower
intensity is better
See Web Appendix 7
Moderating role of topic
innovativeness
P11: Relative innovativeness of
the article’s topic moderates
the impact of the lexical
variants, such that (a) the use
of intensity increases
citations even more, (b) the
use of immediacy reduces
citations even more, and (c)
the use of diversity increases
citations even more
Not supported When presenting relatively
more innovative and
conceptually distant
perspectives, try to use less
intensity. The use of
immediacy and diversity does
not relate to the media
coverage of innovative
articles
Intensity: Van Doorn et al.
(2010)
Immediacy: Patr´
ıcio et al.
(2011)
Diversity: Gebauer et al.
(2010)
Gonsalves et al. 13
Implications for Journals and Editors
Our results suggest considerable divergence in the impacts of
writing styles on citations and media coverage. A clear impli-
cation, which requires continued research consideration, is
that trying to appeal to different audiences may yield conflict-
ing stylistic choices and ultimately a lower overall impact
across all audiences. Many journals proactively offer advice
to authors about how to promote their research, including
Table 5. Drivers of Media Coverage.
Category Proposition Result Implications
Exemplar Refer-
ences
Lexical variation P2: Generally, a greater degree of
intensity is associated with more
media coverage
Supported Try to intensify writing with more
passion, using emotion words (e.g.,
“struggle,” “surprising,” “good”) to
reduce neutrality
Sok et al. (2018)
P4: Generally, a greater degree of
immediacy is associated with greater
media coverage
Supported Use more immediacy in writing (e.g., “we
find that” and “is”), and avoid an
impersonal style (e.g., “one,”
“should”)
Crosno et al.
(2009)
P6: Generally, a greater degree of
diversity is associated with less media
coverage
Not supported Although negatively correlated, media
coverage of articles is not significantly
related to researchers’ use of diversity
in their writing
Mullins, Agnihotri,
and Hall (2020)
Extreme use of
lexical variants
P8: Intensity, immediacy, and diversity
have an inverted U-shaped effect on
media coverage
Supported Try to (a) use a high degree of intensity
(while avoiding excessive use;
approximately 4.9% of affect words),
(b) use a moderate degree of
immediacy (an immediacy score of
approximately 1), and (c) limit
diversity (no more than approximately
12% unique words)
Intensity: Dawes
(2009)
Immediacy: Meyer,
Gremler, and
Hogreve (2014)
Diversity: Uhrich,
Schumann, and
von
Wangenheim
(2013)
Moderating role
of article
subsection and
topic
innovativeness
P10: The relation of the (a) U-shaped use
of intensity, (b) inverted U-shaped use
of immediacy, and (c) U-shaped used
of diversity with media coverage varies
differentially by subsection
Supported Consider alternative writing approaches
across different article subsections
and thereby (a) try to intensify writing
in the introduction and managerial
implications and aim to use a low
degree of intensity for all subsections
except the abstract, where moderate
intensity is favorable (e.g., use more
neutral formulations); (b) use a
moderate to high degree of immediacy
across all subsections but avoid using
immediacy in the future research
subsection, though in the abstract and
managerial implications subsections,
the use of immediacy does not relate
to media coverage; and (c) use a high
degree of diversity in the abstract but
limit diversity in all other subsections,
though in the managerial implications
subsection, the use of diversity does
not relate to media coverage
See Web Appendix 7
P12: Relative innovativeness of the
article’s topic moderates the impact of
the lexical variants, such that (a) the
use of intensity increases media
coverage even more, (b) the use of
immediacy reduces media coverage
even more, and (c) the use of diversity
reduces media coverage even more
Supported When discussing relatively more
innovative and conceptually distant
perspectives, try to use less
immediacy, and less diversity. The use
of intensity does not relate to the
media coverage of innovative articles
Intensity: Crosno
et al. (2009)
Immediacy: Martin
and Hill (2015)
Diversity: Warren,
Hanson, and
Yuan (2020)
14 Journal of Service Research XX(X)
guidelines for search engines, podcasts, teaching slides,
research identifiers (e.g., ORCID), abstract databases (e.g.,
Scopus), and social media hashtags and feeds (e.g., Facebook,
Twitter). Another emerging trend seeks to broaden the reach
of research by publishing chapters in handbook series (e.g.,
Edward Elgar Publishing), executive summaries, or informed
commentaries in web-based outlets (e.g., the Conversation
and LinkedIn). Our findings related to the impact of writing
style on nonacademic outlets can help guide service research-
ers in expanding the impact of their work. Such efforts are
meaningful because institutions increasingly adopt more
diverse performance indicators of impact, and because evi-
dence also suggests a positive association between traditional
academic citation metrics and (social) media metrics (Lamb,
Gilbert, and Ford 2018). Jordan (2019) shows that research
coverage on social media has a positive impact on impact
factors, citation counts, and a wider set of research rankings,
forexample.Bytuningresearcharticlesandadaptedversions
to contain appropriate levels of intensity, immediacy, and
diversity through collaborative efforts, journals, editors, and
researchers reach wider audiences and inspire greater interest
in service research.
Limitations and Future Research
Although our results offer a range of how-to-write sugges-
tions and extends an emerging body of scholarship on the
impact of academic research, our study also is subject to
several limitations that offer opportunities for continued
research. First, we examine the effect of three primary, con-
ceptually supported lexical variations on two types of article
impact. Their relative use naturally varies across people,
groups, and communication contexts. JSR, its articles, reader
preferences, and impact indices are evolving “participants.”
Any substantial changes to any of these entities will inevitably
alter some findings of our study and will certainly influence
findings across the subsections. Therefore, future research
may well find different nuances as audiences and impact mea-
sures evolve. These, as well as other style and content factors
could provide further predictive insights, moderate or mediate
the effects of these lexical variants. Scholarship on message
processing (Meyers-Levy and Malaviya 1999) and persua-
siveness (Shu and Carlson 2014) offers a treasure trove of
lexical and rhetorical ideas, which might deepen understand-
ing of how to write for impact. Second, we based our approach
on what Berger et al. (2020) refer to as “entity extraction.”
Various other methods on impact analysis exist though; for
example, future research might apply topic modeling (e.g.,
latent Dirichlet allocation [LDA]) or relation extraction
(e.g., supervised machine learning). Relatedly, whereas we
rely on topic identifier words derived by Stremersch, Ver-
niers, and Verhoef (2007), additional research could use LDA
to identify, classify, and model specific and upcoming service
topic categories and their impacts. Such studies also might
address content or stylistic cooccurrences among different
articles to investigate ongoing relationships between
subtopics or subgroups within and across service research
journals. Only two algorithms for media coverage of aca-
demic articles have been applied in prior research: the Dow
Jones Factiva database and Altmetric.com. Both indicators
continue to undergo refinement and development to increase
their robustness. As interest in impact measures of academic
research across nonacademic domains increases, we need to
continue to assess and compare alternative impact indicators.
Third, we study key academic article conventions. We find
that longer articles, explicit contribution statements, a frame-
work (conceptual or otherwise), shorter titles and more key
words increase citations. As for media impact, we find that
shorter titles, less key words, and no contribution statements
increase media coverage. The length of the article and the
inclusion of a framework are not significantly related to
media coverage. While our focus is the use of lexical variants,
the differential and partially unexpected effects of these sty-
listic conventions should be further investigated in future
research across journals and disciplines. Fourth, our analysis
exclusively includes published papers. It does not account for
the developmental stages of publishing research, such as dur-
ing the journal review process or for methods of writing for
social media. Future research should investigate differences
in writing style preferences across these different situations
and contexts.
Acknowledgment
The authors thank Professor Stefan Stremersch for his helpful
comments.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to
the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, author-
ship, and/or publication of this article.
ORCID iD
Chahna Gonsalves https://orcid.org/0000-0002-3516-4297
Ko de Ruyter https://orcid.org/0000-0002-1391-697X
Supplemental Material
The supplemental material for this article is available online.
Note
1. To test these broad propositions, we divide P9 and P10 into 36
subpropositions which are summarized in Web Appendix 2.
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Author Biographies
Chahna Gonsalves is a lecturer (assistant professor) in marketing at
King’s College London. Her research explores the role of language,
message design, and mediating technologies on consumers’ informa-
tion processing behavior and their effects on likely message impact.
She is interested in the broader process of message propagation and
consumers’ decisions to propagate informative and persuasive mar-
keting messages. Her work covers topics related to digital marketing
communication, services, and retailing.
Stephan Ludwig is an associate professor of marketing at the Uni-
versity of Melbourne, with expertise in digital marketing communi-
cations and marketing analytics. His research explores communication
design—the way we communicate—which reflects who we are, our
intentions, our relationships, and our likely impact on respective audi-
ences. He regularly collaborates with Fortune 500 companies and
exciting start-ups. His work is published in world-leading marketing
and information systems journals andfeaturedinpopular outlets
including the Conversation,HBR,the Telegraph,andder Spiegel.
He serves on the Editorial Review Board for the Journal of Marketing
and the Journal of Retailing and as an invited reviewer across flagship
marketing, information systems, and strategy journals.
Ko de Ruyter is a professor of marketing and vice dean of research at
King’s Business School. His research focuses on customer loyalty, mar-
keting strategy, and technology on the organizational frontline and social
Gonsalves et al. 19
media. He has published widely in flagship academic business journals
such as the Journal of Marketing,theJournal of Consumer Research,and
Management Science. For his leadership in the academic research com-
munity, he has been awarded a lifetime achievement by the American
Marketing Association. He is passionate about the practical relevance of
his research and its value for businesses and their customers.
Ashlee Humphreys is an associate professor of integrated marketing
communications at Medill School of Journalism and Kellogg School of
Management. She is a sociologist who examines topics in consumer beha-
vior and marketing strategy. She studies the role of institutions in markets
and the influence of language on consumer judgments of legitimacy and the
broader process of legitimation. She is the author of Social Media: Endur-
ing Principles (Oxford UP 2016), and her work is published in the Journal
of Marketing,theJournal of Consumer Research,andtheJournal of Mar-
keting Research. She serves as an associate editor for the Journal of Mar-
keting and the Journal of Consumer Research.
20 Journal of Service Research XX(X)
... Simple and powerful ideas, straightforward methods, and clear writing can heighten the subject matter's appeal for relevant stakeholders such as academics in other fields, business practitioners, the media, policy makers, and the general public (MacInnis et al., 2020). The language used is also likely to affect uptake of the topic among popular writers (Gonsalves et al., 2021). Journalists, consultants, and other professional service providers typically play a brokering role between academia and practice, offering a valuable conduit for disseminating research findings (Roberts et al., 2014). ...
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