This document discusses using HR analytics to improve employee performance through performance appraisals. It proposes that subjectivity bias in performance appraisals decreases perceived accuracy and fairness, reducing willingness to improve. The use of HR analytics can reduce subjectivity bias by providing more objective performance data, increasing perceived accuracy and fairness and thus improving willingness to perform. A conceptual framework is developed linking these factors to explain how HR analytics can address issues in performance appraisals to boost employee motivation and performance.

1. HR analytics and performance
appraisal system
A conceptual framework for employee
performance improvement
Anshu Sharma
Department of Human Resource Management, School of
Management,
BML Munjal University, Gurgaon, India, and
Tanuja Sharma
Department of Human Resource Management,
Management Development Institute, Gurgaon, India
Abstract
Purpose – This paper aims to explore the role of human resource
(HR) analytics on employees’ willingness
to improve performance. In doing so, the paper examines issues
related to the performance appraisal (PA)
system which affect employees’ willingness to improve
performance and how HR analytics can be a potential
solution to deal with such issues.
Design/methodology/approach – The paper develops a
conceptual framework along with propositions
by integrating both academic and practitioner literatures, in the
field of HR analytics and performance
management.

2. Findings – The paper proposes that the use of HR analytics will
be negatively related to subjectivity bias in
the PA system, thereby positively affecting employees’
perceived accuracy and fairness. This further
positively affects employees’ satisfaction with the PA system,
which subsequently increases employees’
willingness to improve performance.
Research limitations/implications – The paper provides
implications for both researchers and
practitioners in the performance management area for improving
employees’ performance by applying HR
analytics as a strategic tool in the PA system. It also provides
implications for future researchers to
empirically test the conceptual framework in different
organizational settings.
Originality/value – The paper offers insights into how the use of
HR analytics can deal with issues of
subjectivity bias in the PA system and positively affects
employees’ willingness to improve performance.
Keywords Performance appraisal, Employee performance,
Performance improvement,
HR analytics, Perceived accuracy
Paper type Conceptual paper
1. Introduction
Employees are a significant investment for organizations
(Schraeder and Jordan, 2011), as they
have the power to affect organizational effectiveness (Sundaray,
2011). To meet increasing
competition, they are expected to perform higher and better
(Biswas and Varma, 2011). With
rising importance of employee performance for organizational

3. effectiveness and competitive
advantage, organizations are increasingly investing in various
development activities such as
coaching, developmental centers and career planning for
performance improvement (Hameed
and Waheed, 2011). It is seen that employees’ performance
improvement and effectiveness
are strongly affected by their performance evaluations during
performance appraisals
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684
Received 14 April 2016
Revised 20 November 2016
11 February 2017
Accepted 17 March 2017
Management Research Review
Vol. 40 No. 6, 2017
pp. 684-697
© EmeraldPublishingLimited
2040-8269
DOI 10.1108/MRR-04-2016-0084
The current issue and full text archive of this journal is
available on Emerald Insight at:
www.emeraldinsight.com/2040-8269.htm
http://dx.doi.org/10.1108/MRR-04-2016-0084
(Latham et al., 1993; Gibbons and Kleiner, 1994; Mir and
Ahmed, 2014). Out of all human

4. resource (HR) practices, the performance appraisal (PA) system
is seen as most critical, but it
also accounts for a large portion of employees’ dissatisfaction
in terms of perceived fairness and
effectiveness (Shrivastava and Purang, 2011), as biased
performance evaluations create
challenges for ethical decision-making in organizations (Maas
and Torres-González, 2011), and
usually result in employee dissatisfaction with the appraisal
process (Ahmad et al., 2012).
Dissatisfaction with the performance process can further be
linked to negative employee
outcomes such as higher turnover intention and lower
commitment levels (Dusterhoff et al.,
2014), which subsequently negatively affects employee
performance (Fu and Deshpande, 2014;
Wong et al., 2015).
However, there is limited research on how the PA system can
help improve employee
performance (DeNisi and Pritchard, 2006). This may be a
probable reason why most
companies only report overall effectiveness and efficiency of
their PA system and shy away
from reporting its effect on employee performance (Fink, 2010).
Establishing an effective PA
system is one of the key challenges faced by HR professionals
for performance improvement
(Harrington and Lee, 2015). Hence, there is a strong need for
research to look into how PA
systems can be made more acceptable to employees and to
further examine their impact on
employee performance. Reviewing literature on PA systems,
Murphy and DeNisi (2008)
suggested that research needs to examine the effects of new
technologies on PA systems, as

5. it is seen that adoption and implementation of new information
technologies improve
performance in organizations (Edmondson et al., 2003; Wang,
2010; Schraeder and Jordan,
2011). Recently, Farr et al. (2013) highlighted that
incorporating technology into the PA
system has several benefits over traditional PA systems and can
benefit both organizations
and employees. New age technology, such as analytics, also
referred to as HR analytics,
when used for HR purposes (Bassi, 2011; Davenport et al.,
2010; Fink, 2010; Levenson, 2005),
can have a significant impact on individual and organizational
performance (CIPD, 2015). It
is also seen that top-performing organizations tend to apply
analytics rather than intuition
to their decision-making activities, which differentiates them
from their low-performing
counterparts (LaValle et al., 2011). However, it is observed that
HR analytics still play a little
role in HR strategy formulation and decision-making (Falletta,
2014). Hence, in this paper,
we aim to explore the role of HR analytics in the PA system and
subsequently on employees’
willingness to improve performance.
2. Research question
The purpose of the present paper is to explore two research
questions:
RQ1. How does the PA system affect employee’s willingness to
improve performance?
RQ2. How does the use of HR analytics in the PA system affect
employee’s willingness
to improve performance?

6. To explore the above-stated research questions, the paper begins
by examining the issues
related to the PA system that affect employees’ willingness to
improve performance. The
paper then examines how the use of HR analytics in the PA
system can be used to deal with
such issues.
3. Theoretical development
3.1 Performance appraisal system and issues of subjectivity bias
Performance measurement is a key element of performance
management (Brudan, 2010).
One of the issues in measuring performance is that it is not a
static entity but a fluid process,
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685
hence there are a number of levels at which performance can be
measured, such as input,
output and processes (Stannack, 1996). To improve
performance, it is important to quantify
the multi-dimensional aspects of performance which play a
dominant role in performance
measurement systems for better measurement and management
of performance
(Dervitsiotis, 2004). PA systems designed by organizati ons may
vary in their levels of
subjectivity and objectivity in their evaluation criterion, where
subjectivity is defined as the
extent to which rater has a direct personal influence on the
ratee’s performance rating (Maas

7. and Torres-González, 2011). Although, subjectivity in
performance measurement was
introduced to decrease distortion by taking into account those
aspects of the employees’ job
that cannot be captured through quantitative measures or in
those cases where the employer
is not able to measure what he requires from employees
(Kauhanen and Napari, 2012).
Subjective performance measures can be defined as the
superior’s subjective judgments
about the qualitative aspects of the job performance and
increased discretion of managers in
performance ratings (Moers, 2005), which also resulted in
performance evaluation bias.
PA systems suffer from subjectivity bias for various reasons
(Laird and Clampitt, 1985);
one such reason is the human element related to raters’
attributions and expectations
(Moser, 1992; Gibbons and Kleiner, 1993), assessment being a
cognitive process. Managers’
cognitive ability to recall employees’ performance behavior
over a period adds to PA biases
in which performance information is selected, observed and
organized by them, which leads
to observational inaccuracy affecting accuracy and effectiveness
of the PA system (Lee,
1985). Tsui and Bruce (1986) suggested that affect is a source
of bias in appraisal, as it
reduced rater accuracy in performance ratings. Personal factors
such as employees’ gender,
mood and interpersonal affect (Robbins and DeNisi, 1993,
1998) were also found to bias PA
ratings. Interpersonal affect was found to affect performance
appraisal ratings and showed
how managers inflate performance ratings of low-performing

8. subordinates due to
interpersonal affect (Varma et al., 1996; Varma et al., 2005).
Ittner et al. (2003) revealed that
inherent subjectivity in the balanced score card plan led to the
problems of favoritism and
uncertainty in the reward system. Earlier multi-source
assessments, also known as 360-
degree feedbacks, were used to increase objectivity; however
they also faced certain issues,
such as the non-equivalence in ratings (Van der Heijden and
Nijhof, 2004). Subjectivity in
performance measurement was found to be a strong reason for
inconsistent application of
objective performance measures and a potential gaming strategy
(Watts et al., 2009).
Highlighting the presence of subjective biases in the PA
process, Bento, White and Zacur
(2012) revealed how obesity stigma influenced employees’ PA,
once again questioning the
“the ethos of objectivity” in PA. Also, centrality bias, a type of
manager’s performance
evaluation bias where the manager tends to compress
performance ratings, emerges when
managers subjectively evaluate performance, and this bias
negatively affects performance
improvement (Bol, 2011). Few researchers have shown that
cultural variation of the rater in
the form of interdependent self-construal also leads to
subjective biases such as evaluation
leniency and creates preferences during performance
evaluations (Mishra and Roch, 2013;
Saffie-Robertson and Brutus, 2014). The implementation of
pay-for-performance raised
issues related to perceived inequity due to subjective biases in
performance measurement
(Park, 2014). Most of the performance evaluations are

9. deliberately distorted or biased
(Campbell et al., 1998). Most of the employee dissatisfaction
issues associated with the PA
system are related to this subjectivity in performance
measurement (Cooke, 2008). There is a
need to reduce rater bias, as it is seen as a barrier to effective
PA, such as gender and group
identification (Roberson et al., 2007; Wilson, 2010; Javidmehr
and Ebrahimpour, 2015).
Issues of subjectivity related to human cognition make it
difficult for the performance
management system to be fair and accurate (Kim and Rubianty,
2011), and subjective
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evaluations are perceived to be unfair and biased (Maas and
Torres-González, 2011). Hence,
it is proposed that subjectivity bias in the PA system would
decrease employees’ perceived
accuracy and fairness of the PA system.
P1. Subjectivity bias in the PA system will be negatively related
to the employees’
perceived accuracy and fairness of the PA system.
3.2 HR analytics and performance appraisal system
Biases result in discrimination at work, and means should be
employed to check such biases
(Hennessey and Bernardin, 2003; Kastl and Kleiner, 2003).
Scholars have highlighted the

10. need to resolve issues related to subjective biases in
performance evaluation (Laird and
Clampitt, 1985; Maas and Torres-González, 2011; Moers, 2005;
Van der Heijden and Nijhof,
2004; Watts et al., 2009). Providing objective measures is one
way to mitigate biases in
supervisory ratings (Campbell et al., 1998). Researchers
suggested structured diary-keeping
as one way to reduce inaccuracy by minimizing performance
information recall bias (DeNisi
and Peters, 1996; Varma et al., 1996). The principal–agent
model states that favoritism and
bias can be reduced by placing more emphasis on objective
rather than subjective measures
in the PA (Ittner et al., 2003) and with the use of observable,
objective evaluation criteria.
Performance measurement is never seen as a complete scientific
activity, and there is always
a need to develop frameworks that generate accurate and
trustworthy information for HR
use (Baron, 2011). Organizations have started appreciating the
need for unbiased, accurate
and timely performance information, as the time and quality of
information provided
determine the speed and quality of HR decision-making (Hill,
2013). According to Simon
(1955), human decision-making is bounded by their limited
cognitive ability and the
availability of information for making that decision, which he
conceptualized as the term
“bounded rationality”. He posited that the quality of managerial
decisions improves
substantially, that is it becomes “objectively rational” if done
with computer-assisted
reasoning, as these decisions are not accompanied with any
social and/or cognitive biases

11. (Simon, 1996). Tools such as fuzzy multi-attribute decision-
making have been found to make
fair performance evaluations by identifying and sorting
employees based on their
improvement needs (Manoharan et al., 2011). Hence, conscious
efforts should be made by
organizations to use information systems so as to facilitate
unbiased decision-making (Maas
and Torres-González, 2011).
This is where HR analytics can play a significant role. HR
function had undergone
transformation with the advent of the human resource
information system, and there are
possibilities that analytics will further transform HR into a
strategic business partner by
providing performance data (Lawler et al., 2004). The huge data
collected through various
information systems are of little use, if the data cannot be
properly analyzed to provide
meaningful implications (Pemmaraju, 2007). Although most of
the organizations till now
used analytics to make financial and operational decisions,
organizations have begun to use
analytics for HR decisions, such as to evaluate employee
performance and/or to allocate
employees’ time and effort (Kiron et al., 2012). HR metrics are
found to affect HR decisions
(Dulebohn and Johnson, 2013), but HR analytics is more than
just metrics and/or scorecards
(Mondore et al., 2011), it consists of various modeling tools
such as behavioral modeling,
predictive modeling, impact analysis, cost–benefit analysis and
ROI analysis (Levenson,
2005) required for strategic HR decision-making. Also, the use
of analytics makes it easier to

12. collect, document and retrieve a variety of performance data
from various sources (both
external and internal), which provides manager with better
information to observe employee
performance in terms of both outcome and behavior. Analytics
has greater ability to capture
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687
and aggregate data; hence, the insights derived through data
analytics help to take fact-
based decisions (Kiron et al., 2012) and help managers to focus
on hard facts rather than
intuition, which also changes the power dynamics in the
company (Falletta, 2014). As the
use of HR analytics provides integrated, consistent and
trustworthy data (LaValle et al.,
2011), it can significantly reduce biases related to human
cognition. Reducing such
subjectivity biases makes the PA process more accurate and
reliable (Murphy and DeNisi,
2008). Hence, it is proposed from the above discussion that HR
analytics can help increase
perceived accuracy of the PA system by giving more objective,
accurate and unbiased data
related to employees’ performance behavior.
P2a. Use of HR analytics in the PA system will be negatively
related to the subjectivity
bias in the PA system.
P2b. Use of HR analytics in the PA system will be positively

13. related to employees’
perceived accuracy and fairness of the PA system.
3.3 Employees’ satisfaction with the performance appraisal
system
Researchers need to study factors that predict positive employee
reactions to appraisals,
such as their perceived accuracy, fairness and satisfaction with
the PA system (Pichler,
2012). Employees’ perception of PA system effectiveness is
measured through their
perceived accuracy and fairness of the PA system (Sharma et
al., 2016). Perceived fairness of
the PA system is found to be affected by fulfillment of
employees’ psychological contract
(Harrington and Lee, 2015). In a multi-level study, Farndale and
Kelliher (2013) found that
organizational commitment was affected by employees’
perceived fairness of the PA
system. Employees lose trust in the PA system and subsequently
in the performance ratings
when they do not see this system to be fair (Murphy and DeNisi,
2008). In a meta-analytical
review of justice literature, Colquitt et al. (2001) revealed that
fairness perceptions at work
were largely affected by justice perceptions. Organizational
justice theory (Skarlicki and
Latham, 1996) has often been used to understand acts of
perceived discrimination in an
organization (Harris et al., 2004; Bibby, 2008; Wood et al.,
2013). Using organizational justice
as a theoretical support, Greenberg (1990, 2004) posits that the
construct of perceived
fairness of the PA system is multidimensional in nature with
three sub-constructs, namely,
distributive, procedural, interactional – interpersonal and

14. relational justice. These justice
dimensions can be linked to perceived fairness of an actual
appraisal rating, of procedures
used to determine the appraisal rating and of the rater’s
interpersonal treatment of the ratee
during the appraisal process, respectively (Narcisse and
Harcourt, 2008). Also, justice
dimensions are found to affect reciprocatory behaviors by
employees (Frenkel and Bednall,
2016). Fairness perceptions influenced by these justice
perceptions lead to satisfaction with
the PA system and performance feedback (Jawahar, 2007).
Justice is also seen as a predictor
to acceptability of the PA system (Briscoe and Claus, 2008).
Justice perceptions have found
to mediate relationships between administrative PA activities
(namely, salary adjustments,
promotion decisions and performance standards) and
organizational commitment (Zhang
and Agarwal, 2009), and satisfaction with the PA system
(Thurston and McNall, 2010).
Effectiveness of the PA system depends on justice perceptions
of employees (Clarke et al.,
2013). Also, perceptions of organization justice have been
found to affect ethical and
unethical behavior at work (Jacobs et al., 2014). However,
perceived accuracy, the extent to
which the performance evaluation accurately captures
employees’ actual job performance
(Kim and Rubianty, 2011), is seen as an important antecedent to
employees’ justice
perceptions, particularly their perceptions of distributive justice
(Narcisse and Harcourt,
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2008). Increased accuracy of the decisions positively affects
justice perceptions in the PA
system (Briscoe and Claus, 2008). On the contrary,
acceptability of the PA system increases
trust in the management (Mayer and Davis, 1999). Perceived
accuracy has been identified as
an important predictor of employees’ satisfaction with the PA
system (Keeping and Levy,
2000). Also, from the perspective of moral judgment,
employees’ satisfaction with the PA
system is partly determined by the perceived moral justifiability
of the PA process
(Dusterhoff et al., 2014). Hence, perceived accuracy and
fairness become important
antecedents which can affect employees’ satisfaction with the
PA process.
P3. Employees’ perceived accuracy and fairness of the PA
system will be positively
related to employees’ satisfaction with the PA system.
3.4 Employees’ willingness to improve performance
Research claims that employees’ performance improvement
after receiving performance
feedback largely depends on their attitude toward the PA system
(Maurer and Tarulli, 1996).
Literature on performance feedback suggests that most of the
time feedback interventions
had a negative impact on performance (Kluger and DeNisi,
1996; Cannon and Witherspoon,
2005), as performance improvement is most likely to occur

16. when the receiver has a positive
feedback orientation and reacts positively to change (Smither et
al., 2005). Also if employees
accept the PA system, the supervisor/rater is likely to give true
feedback and would not
resort to other means of performance improvement because
he/she understands that
employees are more likely to accept their feedback (Briscoe and
Claus, 2008). Also, the
relationship between performance ratings and feedback
acceptance is mediated by the
employee reactions to feedback (Bell and Arthur, 2008).
One of the reasons for non-acceptance of the performance
feedback is the lack of
agreement with the PA system (Campbell et al., 1998).
Employees often disagree with
their performance evaluations, as they perceive them to be
inaccurate (Campbell and
Lee, 1988). Such performance evaluations, in the form of
performance ratings, do not
provide sufficient information for employees to improve
performance, as these rating
scales do not completely eliminate the subjectivity bias (Van
der Heijden and Nijhof,
2004). The perceived fairness and accuracy of performance
feedback is one of the
determinants for employees’ willingness to improve
performance (Lee and Akhtar,
1996). The acceptance of performance feedback increases self-
efficacy among
employees with regard to that feedback (Nease et al., 1999).
Even negative feedback can
result in performance improvement (Fedor et al., 2001), if that
feedback is accepted by
employee. Only if employees accept and trust the system to be

17. legitimate, they have
positive reactions to their performance feedback (both positive
and negative) and will
try to improve their performance (Briscoe and Claus, 2008).
After the initial reaction to
feedback, the employee sets the goal and start taking action
which can lead to
performance improvement (Smither et al., 2005). Satisfaction
with PA feedback has also
been linked to satisfaction with the rater, job satisfaction and
organizational
commitment (Jawahar, 2006). Fairness and justice perceptions
(Colquitt et al., 2001) and
satisfaction with the PA system are seen as important predictors
of employee
performance (DeNisi and Pritchard, 2006). Hence, satisfaction
with the PA system can
affect work performance (Kuvaas, 2006). Employees’
perceptions of fairness and
accuracy is affected by the quality of PA feedback, which
affects employees’
performance (David, 2013; Selvarajan and Cloninger, 2012).
Employee performance can
be improved by increasing their willingness to improve
performance after receiving the
performance feedback. This can happen only when they accept
the feedback received
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689
and work on it, which largely depends on how satisfied they are
with the PA system.

18. Hence, it is proposed that employees’ satisfaction with the PA
system would result in
an increase in employees’ willingness to improve performance.
P4. Employees’ satisfaction with the PA system will be
positively related to employees’
willingness to improve performance.
4. Conceptual framework
The conceptual model emerging from the above discussion is
shown in Figure 1. The
propositions are denoted as P1, P2a, P2b, P3 and P4. The
propositions explaining negative
relationships are denoted by dotted lines (P1 and P2a).
Likewise, solid lines denote positive
relationships (P2b, P3 and P4). Here, P1 explains a negative
relationship as to how
subjectivity bias in the PA system reduces employees’ perceived
accuracy and fairness of
the PA system. Similarly, P2a explains how the use of HR
analytics in the PA system
negatively affects the subjectivity bias in the PA system. The
other three propositions (P2b,
P3 and P4) explain positive relationships such as how
perception of accuracy and fairness of
the PA system increases employees’ satisfaction with the PA
system, subsequently
increasing their willingness to improve performance.
5. Discussion and conclusion
This paper contributes in several ways. First, it integrates and
extends the literature on
two independent fields of study: analytics and PA, former being
predominantly an
information technology domain (Pemmaraju, 2007) and latter
being an HR

19. management domain. Thus, the present study is inter-
disciplinary in nature. Second, it
is one of the few studies to examine the role of HR analytics on
the PA system and
employees’ performance improvement. Third, it attempts to
address the call of
researchers to deal with issues of subjectivity in the PA system
by identifying HR
analytics as a potential solution (Laird and Clampitt, 1985;
Maas and Torres-González,
2011; Moers, 2005; Van der Heijden and Nijhof, 2004; Watts,
Augustine and Lawrence,
2009) with organizational justice theory (Skarlicki and Latham,
1996) and bounded
rationality (Simon, 1955) as the theoretical underpinning.
Future researchers may empirically test this conceptual
framework and propositions in
different organizational settings to study how HR analytics
affect PA systems and employee
Figure 1.
Conceptual model
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performance improvement. The study can be extended further by
linking HR analytics to
other important employee and organizational outcomes, such as
PA, which is found to affect
employees’ participation in informal learning activities at work

20. (Bednall et al., 2014), and
organizational performance (Ayers, 2015). As employee
performance is seen as a function of
both individual and organizational factors (Douglas, 2014),
future studies may relate how
HR analytics can improve employee performance by linking to
other organizational factors
such as organizations’ service climate (Sharma, 2008) and
organizational psychological
climate (Biswas and Varma, 2011), which have been found to
affect employee performance.
Also, it is important to note that the role of HR analytics in
reducing biases in the PA system
is limited to the quality of data. HR needs to measure what is
important rather than
measuring what is easy to (Bassi, 2011; Ingham, 2011).
Recently, analytical tools such as Synergita and IBM Kenexa
HR analytics powered by
IBM Watson help HR professionals to get insights into
performance data for performance
improvement and talent management (IBM, 2017; Synergita,
2017). In one of Gartner’s
research notes, Hostmann et al. (2009) developed a performance
management framework
linking analytics and business intelligence. Our paper resonates
with the work of Kasemsap
(2015) on how business analytics can be used for organizational
transformation such as
performance management.
However, the use of HR analytics for strategic decision-making
largely depends on the
organizational culture because to promote fact-based decision-
making to reduce the
cognitive biases in PA, organizations should have data-oriented

21. leadership (LaValle et al.,
2011). Such a data-driven culture may be defined as:
[. . .] a pattern of behaviors and practices by a group of people
who share a belief that having,
understanding and using certain kinds of data and information
plays a critical role in the success
of their organization (Kiron et al., 2013, p. 18).
Based on this culture, organizations may be categorized on their
level of analytical
capability from analytically impaired to analytical competitors
(Davenport and Harris,
2007). DELTA (Data, Enterprise, Leadership, Target and
Analysts) provides a basic
framework for implementing analytics in organizations
(Davenport et al., 2010). Willing
firms which are analytical innovators build a data-oriented
culture by recruiting and
promoting analytical talent (Ransbotham et al., 2015).
To conclude, this paper made an attempt to explore the role of
HR analytics on PA system
and its subsequent impact on employees’ willingness to improve
performance by proposing a
conceptual model with testable propositions. The paper
highlights subjectivity bias in the PA
system as one of the issues that needs to be addressed to
increase its perceived accuracy and
fairness, which in turn affect employees’ satisfaction with the
appraisal system. To do so, HR
analytics was found to be a potential solution by increasing
accuracy and objectivity in the
appraisal process with the use of sophisticated data analysis
tools. Along with implications for
both practitioners and researchers in the field of performance

22. management, the paper also
suggested directions for future research to further enrich the
field.
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Corresponding author
Anshu Sharma can be contacted at: [email protected]

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HR analytics
697
mailto:[email protected]HR analytics and performance appraisal
system1. Introduction2. Research question3. Theoretical
development3.1 Performance appraisal system and issues of
subjectivity bias3.2 HR analytics and performance appraisal
system3.3 Employees’ satisfaction with the performance
appraisal system3.4 Employees’ willingness to improve
performance4. Conceptual framework5. Discussion and
conclusionReferences
Research and Report Writing
In the previous class assessment, I chose language and culture
as the research area I would like to do. Language and culture
are an area of interest. As I had discussed earlier, language and
culture are two different things. Language is a method/
principal that human beings use during communication. Culture
is basically the norms and customs of a particular group of
people or a society. Language is one of the elements in a
culture. The connection language and culture are intertwined.
Language is a key thing in distinguishing a particular group of
people. Language is also the key point of accessing any other
culture. If you start learning another language, it means that you
are getting attached to that particular culture.
The main objective of this paper is to find out the relationship
between culture and language. There are different types of
relationships between the both. According to (Kim, 2018) There
are different types of communication within a culture or rather

41. the society. One of the languages is the paralanguage.
Paralanguage is a “non-lexical component of communication by
speech. Examples are intonation, pitch and speed of speaking,
hesitation noises, gestures and facial expressions. In each
culture/ community, they have the basic gestures they make. All
these gestures have a meaning”. This is according to Oxford
dictionary.
You may find cases where different cultures have the same
gesture but the meaning is different. We learn all these gestures,
expressions and intonations from the people we grow up
together. The language is a one unifying tool in all the cultures.
As I said earlier, the paralangua ge varies in different cultures.
You may find gesture that in a particular community it
welcomes people while in another community the same gesture
language causes misunderstandings. This may even cause to rise
of ethnic groups.
According to (Sharifan,2014) paralanguage includes the speed
of speaking, intonations and so many other factors as I had
discussed, if a person is bilingual, that is speaks more than one
language, the person must have noticed the difference between
the two languages. You will notice changes in the speed at
which you are talking. Some language uses a high speed while
others are just neutral. According to (Swiderski, 2013) There
are those languages that even if you don’t understand, you feel
the speed at which the people talk. Such language is not easier
to learn if you are from a different culture. There is then the
language whose speed is just neutral. These languages are easier
to learn and understand Sharifan Explains.
There is a homologous connection between the language and
culture. This has led to the phrase; “language is culture and
culture is language”. This is according to Swiderski, Language
and culture developed a very long time ago. They were
developed even before people could learn how to write. The
connection between language and culture is so strong in that if
you don’t know one you can’t know the other. In a wide sense,

42. to learn the customs of the other culture one must learn and
understand the language of that particular culture. Without
knowing the language, one cannot understand culture. The
relationship is vice versa. Knowing the customs of a culture
without learning their language is senseless. Both language and
culture have a very strong bond between them.
According to (Jiang, 2020) Language and culture have different
effects on how think. Taking a look at a person who was born in
Germany and grew up there, this particular person has different
perceptions of other languages. German person will not think
the same as a Chinese person. The thinking process of these two
persons is affected by the culture.
Contrary to what Jiang had said (Battiste,2020) believes that the
views of a person towards other culture are not impacted by
how we think. Most of the times, the differences are brought
about by the various practices within the culture. Both are from
different culture and view things differently. According to Jiang
Just as the language affects the thinking process, the same way
culture affects the way you perceive your surroundings.
Nowadays the intercultural religions are affected by the
language of different people. This is according to (Hojjier,
2016). Unlike the olden days when transport was not so much
developed, nowadays, people can leave their homes and travel
to different cultures for vacation or even short term stay. People
who go to visit other countries find people who are using
different language from them. The concept behind language and
culture reveals itself in this case.
This case shows how a foreigner may have difficulties trying to
communicate with the people around them. According to
(Kramsch, 2014) the two people will experience
miscommunication as no one understands the other. Though
they may use gestures, remember as I had said earlier, gestures
have different meaning in different culture.
The transmission mode of both language and culture is the
same. According to (Elmes, 2017) language is transmitted to a

43. person on their birth. Although these kids are not able to talk,
they can learn the gestures from the people near them. As they
grow up, they learn their first language from their guardians and
the people near them. They are then taken to classes where they
are taught the deep language of their society.
Just the same way, culture is not taught to the people and also
the people learn the basic customs from the people near them.
In short, we would say, both culture and language are inherited.
Born ids need not be taught the basic customs and practices of a
society because they can see what the people are doing and
copy.
Language sometimes may differ from people in the same area.
This is impacted by social, geographical and functional factors.
This is according to (Shanahan, 2017) Geographical differences
may arise in the area. For example, people form the east may
not have the same language from the people in the western who
are in the same geographical area. Some of the social
differences that impact languages are age, gender, and
occupation. It is so common that youths have their language
which differ from the aged people in the same areas.
The male gender may also have their language which the female
gender will not understand. These are just but a few factors that
affect language. Despite the differences that arise from the
language used by the people, culture unifies all these people.
The people are in the same area and therefore they share the
same cultural practices and believes. Culture is a unifying
subject amongst all the people of the same cultural area.
In conclusion, in a research conducted on Iran and USA,
Hoffman said that Culture and language are the basic and
common part of our living. There may be so many differences
that exist amongst people due to their personalities and
identities but culture unites us all. The Language we share
amongst ourselves also unites us.

44. References
Battiste, M. (2020). Language and culture in modern society.
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1
Running Head: ENGLISH RESEARCH TOPICS
5
ENGLISH RESEARCH TOPICS
:

45. English Research Topics
English Research Topics.
The first topic of interest to be researched in this case is
language and advertising. This language and advertising issue
are the most common in the recent world because of increased
business adverts. This means that language is being used mostly
when it comes to adverts. This brings in the main motive of
what is being researched in this case when it comes to language
and advert. So the main thing that is being in this paper is the
issue of how the language is being used in advertising. Since
most people usually do use bad languages when it comes to
research.
The reasons this research topic has been selected are so many.
The first reason has been mentioned above about the issue of
advertising. Over the past recent years, social media has
increased when advertising has increased. This is alarming
because children are also engaged in social media. When
adverts that are using offensive languages are being advertised
on social media, it will be misleading to them. (Website Design
Warwick | Digital Marketing Warwick | Formation Media,
2021). Another issue is that when the language that is not
grammatically correct is being used in adverts, it will also mean
that most people will be affected and start using grammatically
wrong languages.
The people or rather the participants involved in this topic are a
few people from the media, or rather the media personnel. This

46. is because these are the people that come up with the adverts.
Another group of participants will be the people who are
watching the adverts. These are the people who are being by
everything in the adverts, including the languages used in the
adverts, which means that they should be able to give their view
on how languages and adverts affect them. After the research,
the thing that should be done is to try and change the languages
being used in adverts.
The second topic of interest to be discussed is language and
community as a topic. Language is an essential factor when it
comes to our daily leaving. Without language, then it won't be
easy to pass communication between each other. Language is
the main thing that brings or rather builds a community together
in everything that they do. The same language can also be used
to create trouble between communities. (The Importance of
Language for Your Communi ty - Higher Logic, 2021).
Language can also be defined as the main principle method of
human communication, or rather the communication is the only
thing that makes communication between each other possible.
The language can either be conveyed through writing or even
speaking or rather talking inform of speech.
The main motive for the research on language and community,
in this case, was first to explain or rather find the evidence on
how the language helps people in the community in a very big
way. Though it is already evident that language helps every
community is really of great help, it is also still very important
to bring out all the importance. In this way, people will be able
to understand and respect language. Another main motive for
the research on language and community is that people should
start using respectful language within the community. Doing
this will promote respect between people in a community in
terms of language. This will be possible since the research will
be able to identify the respectful language that will be sued by
everyone in the community.
The main participants for this topic will generally be everyone
willing to participate in the community. These people will be

47. able to be administered questionnaires containing everything
about language and community. Once this is done, the research
will be able to develop the best language to be used within a
specific community.
The third topic of interest that should be researched is the topic
of language and cultural identity. Yes, different cultures have
indeed got their own to be easily identified with. These cultures
with different languages are so many, and each culture should
be able to identify their members, mostly using the language
they speak in that particular culture. This can sometimes bring
problems and even fights between cultures because of the same
words in a language between different cultures. Still, they all
carry different meanings, which brings out the misunderstanding
between all these different cultures.
The main motive or rather the first reason why this topic of
language and culture is of priority in this research is that there
is a very big need to find if language can identify one culture
most effectively truly. Another main motive of the research was
to find out all the similar words between different communities.
Once that was done, each culture will define the words and see
if they mean something offensive among different cultures. (The
Relationship between Language and Culture Defined, 2021).
This way, the issue of misunderstandings within cultures will be
avoided. The main participants of this research will first be
individuals from different cultures. This person will give the
required information regarding their cultures once needed. The
other group of participants will be random people from the
streets who are willing to participate. This person will speak
any language that they know. After they are identified in their
cultures according to the language, they will see if it’s accurate.
Finally, after this topic, the main topic that I will continue with
for the rest of the term is dealing with language and culture.
This particular topic has been selected because the topic has got
several contents to be researched on, and it is quite interesting.
There is also a big need in the community to be researched.

48. Reference
Formation Media. 2021. Website Design Warwick | Digital
Marketing Warwick | Formation Media. [online] Available at:
<https://formationmedia.co.uk/blog/language-in-advertising-
understanding-its-use/> [Accessed 17 January 2021].
Higher Logic. 2021. The Importance Of Language For Your
Community - Higher Logic. [online] Available at:
<https://www.higherlogic.com/blog/the-importance-of-
language-for-your-
community/#:~:text=Developing%20a%20shared%20language%
20builds,community%20behavior%20with%20positive%20langu
age.> [Accessed 17 January 2021].
Day Translations Blog. 2021. The Relationship Between
Language And Culture Defined. [online] Available at:
<https://www.daytranslations.com/blog/language-and-
culture/#:~:text=Language%20and%20culture%20are%20intertw
ined,without%20accessing%20its%20language%20directly.>
[Accessed 17 January 2021].