* Corresponding author.
E-mail address: firstname.lastname@example.org (W. Vicente-Ramos)
© 2020 by the authors; licensee Growing Science, Canada.
International Journal of Data and Network Science 4 (2020) 337-346
Contents lists available at GrowingScience
International Journal of Data and Network Science
Impact of digital transformation on the individual job performance of insurance companies in Peru
Carla Victoria Guzmán-Ortiza, Nohelia Gabriela Navarro-Acostaa, Wilmer Florez-Garciaa and
aUniversidad Continental, Peru
C H R O N I C L E A B S T R A C T
Received: July 20, 2020
Received in revised format: Au-
gust 29, 2020
Accepted: September 21, 2020
Available online: September 21,
The objective of this study was to analyze and determine the impact of digital transformation on
the individual job performance of insurance companies in Peru. The deductive inferential scien-
tific method of explanatory level was used, with a non-experimental design, to four insurance
companies that operate in the regions of Arequipa, Cusco, Iquitos, Lima, Tacna and Trujillo. The
results generated by structural equations show that customer service experience (CSE), based on
digital transformation, had a positive impact on task performance (p <0.05) and contextual per-
formance (p <0.05); in contrast, the customer service experience (CSE), based on digital transfor-
mation, was found to have no impact on counterproductive behavior (p> 0.05). In relation to the
collaborator's capabilities (CC) based on digital transformation, the results reveal that it had a
significant influence on task performance (p <0.05) and contextual performance (p <0.05), while
it did not have any impact on counterproductive behavior (p> 0.05). Likewise, processes based on
digital transformation (P) significantly influence task performance (p <0.05) and contextual per-
formance (p <0.05), unlike counterproductive behavior that did not present a causal link with the
processes (p> 0.05). Finally, the business model based on digital transformation (BM) had no
implications for task performance (p> 0.05), contextual performance (p> 0.05) and counterpro-
ductive behaviors (p> 0.05). The conclusion of the study indicates that the customer service ex-
perience, the collaborator's capabilities and processes based on digital transformation contribute
to the performance and contextual performance of the workers of the insurance companies in Peru.
© 2020 by the authors; licensee Growing Science, Canada.
Individual job performance
Customer service experience
Currently, we are living a fairly advanced phase of the digital age, so that constant innovations in communication technologies
have changed the way in which organizations communicate with their customers, thus replacing traditional business models,
in which obtaining data required investment in sophisticated computer systems and innovation studies had a very high cost,
due to this, most decisions were based on the analysis and intuition of managers (Rogers, 2016). Today, there are cloud-based
systems that are increasingly cheap and easy to use, these new technologies are based on analytical applications, artificial
intelligence, big data, internet of things, robotics, among others (Stark, 2020). However, technology alone does nothing, it
requires knowing the environment surrounding digital transformation. Digital transformation has become very popular in
recent years, organizations have mostly focused on improving only the area of information technology. According to Stark
(2020) it is not only a technological change, but also a change in the organization, culture and business, “digital transformation
is a complex and demanding process that requires the commitment of all the company's resources: human, technological,
physical, organizational and financial.” (Kutnjak et al., 2019, p. 1293); it is about reworking strategies, products and processes
taking advantage of digital technologies, seeking to give added value to the customer. According Katz (2018) affirms that
digital transformation has generated a positive impact on production processes; Due to the fact that it allows the automation
of processes and the decentralization of functions, optimizing the activities carried out by human capital, which leads to
improving the use of material and financial resources. Rogers (2016) mentions that, there are five domains that describe the
digital transformation landscape: (1) Customers, (2) competition, (3) data, (4) innovation and (5) value; which allows organ-
izations to develop a different approach to innovation, because by using agility methodologies and design thinking, it is pos-
sible to maximize organizational learning and minimize costs. Almost all industries have been immersed in the digitization
of their processes, the financial sector has not been the exception. Butler (2020) shows that, since banks and insurance com-
panies are heavily regulated, they invest more than others in information technology, seeking to improve their operational
processes, through the creation of new products with added value, pointing to new models of business with the purpose of
improving the profitability of the company, in addition to building and maintaining a close relationship with the client.
According to Scardovi (2017), insurance companies face a crucial digital transformation challenge, as technological innova-
tions are posing an unprecedented number of competitive threats and require accelerating the digitization of their business
and operational processes. Traditional insurance companies depend to a great extent on sales channels, agents and physical
intermediaries, which still show limited knowledge of digital tools; They still maintain a high level of manual processes,
which leads to a risk related to reprocessing and complaints from customers, which in most traditional companies still retain
old computer systems and collaborators have a deep-rooted cultural resistance. While insurance companies with digital
knowledge have begun to innovate in their processes, creating a complete customer experience in all their channels, working
with a comprehensive vision in their business model, focused on satisfying the customer's need, while continuing to side the
digital and organizational culture of its stakeholders. Burcu and Sertaç (2018) mention that insurance companies managed to
create new strategic experiences for customers, thanks to the analysis of data obtained in digital sales channels, as it improves
the segmentation and identification of target customers; and the proper handling of Big Data has optimized risk management.
According to the School of Senior Management and Administration (EADA), in its Second Report “Executive Digital Level
in Peru 2019”, it mentions that companies began to bet on creating areas of innovation and research, seeking to find new
niches in the market, adapting to the needs of consumers who are increasingly demanding. Insurance companies took a long
time to adapt to digitization (Albrecher et al., 2019). Therefore, the digital transformation in this sector arrived in Peru between
2016 and 2017 (UTEC, 2019), where few companies bet on the creation of value and incorporation of new technologies.
Currently, the landscape has changed positively, more and more organizations are creating innovation laboratories, adopting
design thinking in their processes, however, the great challenge is to adapt their organizational culture to the digital transfor-
mation that they have been developing, since they must operate in a macroeconomic context in which young companies
pursuing technology-driven business models are expanding at a rapid pace (Braun & Schreiber, 2017).
For Eling and Lehman (2018), digitization unites the analog with the digital and aims to profoundly modify the financial and
insurance ecosystem, generating an impact on all the activities that make up the value chain of insurance companies, starting
from the product development to pricing, underwriting, sales and distribution, claims, asset and risk management. Braun &
Schreiber (2017), mention that faster the insurance business adapts and integrates to digital innovation, the more likely it is
that traditional insurers will survive, since the market context is constantly changing, and the profile of customers has varied
over time, they are now in constant search of digital experiences throughout the insurance purchase journey. Likewise, insur-
ance companies always sought to be close to their stakeholders and satisfy their needs; However, the situation caused by
Covid-19 has generated that all industries have to accelerate their digital transformation process (Kim, 2020); Social distanc-
ing has put insurers to the test, so they have chosen to carry out remote work, prioritizing the development of applications in
which the client can make inquiries and procedures without the need to go to a physical office. This scenario has generated
that new technologies have changed the way insurers and clients interact, for example: social networks, applications, chatbots,
video calls, among others (Eling & Lehman, 2018). In this line of analysis, this research aims to measure the impact of digital
transformation on the individual job performance of insurance companies in Peru.
2. Literary review
2.1. Digital transformation
According to Kutnjak et al. (2019, p. 1293), the digital transformation “is a complex and demanding process that requires the
commitment of the entire company to use resources: human, technological, physical, organizational and financial, so digital-
ization implements digital tools throughout the organization, especially focus especially on people and business processes,
based on the change of the business model”. Along these lines Boateng, et al. (2020, pp. 26-44), affirm that, innovation,
technology, creativity and digitization are the tools that are put at the service of customers, to make a transformative future a
reality, for this they differ: “three key areas where executives of the company is being digitally transformed: customer expe-
rience, operational processes and business models, which change and form the foundations of the digital transformation pro-
cess ”. The technological leap in this era is exponential, therefore, digital transformation is not only a technological change,
but also an organizational, cultural and management change that consists of reworking strategies, products and processes
taking advantage of digital technologies, it is also the deep transformation of business models and competencies, organiza-
tional models, business processes and practices; all this, to satisfy the customers you want, from anywhere, at any time by
managing information and improving the customer experience through digital technology (Stark, 2020).
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It is necessary to consider that the digital transformation generates a digital culture, with a new mentality to access knowledge
because it is “the set of behaviors and habits developed and applied by managers and employees of an organization to take
full advantage of the potential of new technologies, through better use and better dissemination throughout the organization
in order to transform the business model or organizational models to create value for customers, employees and shareholders.
” (Ochoa, 2016, p. 76). These behaviors and habits will allow to exploit benefits of technology that can improve the processes
and results of the organization.
2.2. Dimensions of Digital Transformation
According to Kutnjak et al. (2019) “organizations focus especially on people (collaborator capacity) and business processes,
driven by digital technology, which directly affects the change of their business model.” (p.1293).
2.2.1. Dimension 1: Customer service experience
The customer experience is the result of the reaction of a customer to certain stimuli of the company before, during and after
the purchase of a product or service, likewise, the customer experience is the process of strategic management of all experi-
ences of clients with a company (Bruhn & Hadwich, 2012). For a client's experience to be optimal, Abolhassan (2017) affirms
that “companies must change their strategic approach to the integral, as well as the individualized optimization of the customer
experience customer in all digital media and traditional touch points, design plays an important role in terms of graphic
presentation and user experience design, it is important to infer that simplicity, intuition and reactivity are key characteristics
that companies must take mainly considered in the digital transformation of its user interface (front-end) and integration with
the back office is not neglected; this It is because the processes of the support program (back-end) in logistics, accounting,
warehousing or product development, can have the same impact on the customer experience, as well as on the customer-
oriented areas.”(p. 13).
2.2.2. Dimension 2: Collaborator capabilities
According to Chiavenato Chiaventato (2014, p. 2), it is “the competences (qualities of someone who is capable of analyzing
a situation, proposing solutions and solving issues and problems) that constitute the greatest personal assets, to be successful,
the administrator must develop three durable competencies: knowledge, perspective and attitude”. Likewise, Angulo (2017,
the competences involve knowledge (conceptual), know-how (procedures) and knowing how to be (attitudinal) to define
employee actions in the workplace, through the design and implementation of permanent training programs for the promotion
of human talent, development of integration skills between people and teams, above technological investment, which become
facilitators of knowledge management. Therefore, it has to do with a set of characteristics of workers such as their experience,
knowledge, aspects related to their emotional state, attitudes, motivations, etc.; which must be aligned to the organization,
that is, to technical, productive, customer service conditions, among others. It also plays a preponderant role culture at work,
such as discipline, order, achievement of goals, etc. Overall, it can be said that work productivity or depends on a set of
elements that promote good work performance in increasingly changing and demanding environments; along this line, ac-
cording to Mohamad et al. (2016), it is necessary to develop competencies so that people face changes and work challenges,
generating innovative ideas for solutions to different problems in their work practice.
2.2.3. Dimension 3: Process
There are several guidelines that must be followed when a company wants to bet on the change. According Stark (2020, p.
29) A business process is an organized set of activities, with clearly defined inputs and outputs, that creates business value;
the business processes of an organization are generally divided into three main groups, these are: management processes,
which includes quality regarding products and services according to an adequate planning of the processes; support processes,
which creates value for internal customers, for people within the organization, and operational processes that create value for
external customers (p. 29). In this regard, Galvis and González (2014) mention that business process management is a way to
improve the visibility of the business and to equip organizations with skills and tools that allow them to respond quickly to
changes and optimize benefits such as: (1) better understanding and visibility of processes, (2) improvement in handling
exceptions and errors, (3) saving time and reducing costs due to increased efficiency of operations, ( 4) improvement in
employee performance, and (5) possibility of improving processes based on evidence obtained by monitoring their execution.
2.2.4. Dimension 4: Business model
Vukanovic Z. (2016, p. 78), defines that “A business model has three components: content (What is consumed?), Customer
experience (How is it packaged?) And platform (How is it delivered?) “These components work together to create a compel-
ling value proposition for the customer.” According to Abolhassan (2017), considering the stages of digital transformation, a
business model encompasses: new sales, models, as well as new products and new business models. businesses that often lead
to new digital ecosystems in the medium and long term, adding that companies will not be able to withstand the increasing
competitive pressure on their own.
2.3. Individual job performance
According to Chiavenato (2019), performance is “the set of characteristics or capabilities of behaviors or performance of a
person, team or organization.” (p. 206). While work methodologies have changed dramatically in recent years, employee
performance management methods have changed at a much slower rate (Veingerl et al., 2020). The concept of performance
entails different perspectives of analysis, in this line, Bauer et al. 2017) state that digital transformation has generated profound
changes in all work dimensions, so four dimensions are essential to increase work performance: adaptation of workspaces
(adaptive), integration of work processes (Intuitive), processes in real time (connected), and increase in digital systems (As-
According to Ramos-Villagrasa (2019), the measurement of job performance can be carried out from different perspectives,
and therefore its operationalization obeys different methodologies, in this sense, for the present study the contribution of
Koopmans (2015) was considered, who identifies three core dimensions of job performance: (1) task performance, (2) con-
textual performance, and (3) counterproductive behavior (Fig. 1).
Fig. 1. Performance evaluation as a system.
Note. Prepared by the authors based on Koopmans (2015).
2.3.1. Dimension 1: Task performance
They are behaviors that contribute to the production of a good or the provision of a service (Rotundo & Sackett, 2002). This
dimension is the one that has traditionally received the most attention when evaluating worker performance, and according to
Koopmans et al. (2016) represent the competencies that individuals demonstrate in their workplace.
2.3.2. Dimension 2: Contextual Performance
This dimension is known as organizational citizenship behavior, in that sense, it can be defined as behavior that contributes
to the objectives of the organization by contributing to its social and psychological environment (Rotundo & Sackett, 2002).
The contextual dimension refers to all those behaviors that support the organization's environment, as well as the social and
psychological aspects that workers show when developing their functions (Koopmans et al. 2016).
2.3.3. Dimension 3: Counterproductive behavior
It is voluntary behavior that harms the well-being of the organization (Rotundo & Sackett, 2002). Along these lines, Bragg &
Bowling (2018), found a strong relationship between four personality traits (trait aggression, trait industriousness, trait decep-
tion, and trait self-control) and counterproductive work behavior (CWB for its acronym in English).
3. Research Model and Hypotheses
For the independent variable Digital Transformation, the following conceptual constructs and their respective items were
a) Customer service experience (CSE): Digital customer service technologies provide a personalized experience
(CSE1), digital channels offer a quick response in customer service (CSE2), customer satisfaction is measured in a
permanent (CSE3) and digital processes protect customer data privacy (CSE4)
b) Collaborator capacity (CC): The training provided by the company on digital tools is adequate (CC1), I adequately
adapt to the digitization process required by the company (CC2) and I feel committed to the work that I develop in
the process digitization of the company (CC3).
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International Journal of Data and Network Science 4 (2020) 341
c) Processes (P): The digitization of senior management processes contributes to the smooth running of the entire
organization (P1), the digitization of processes of their team supervisors contributes to the achievement of their ob-
jectives (P2) and digitization of processes in his office has improved the efficiency in customer service (P3).
d) Business Model (BM): The company's value proposition consolidates customer loyalty (BM1), the company's
digital business model contributes to the quality of customer service (BM2) and the digital platform covers the ex-
pectations of security and customer trust (BM3).
For the dependent variable Individual Labor Performance, the following conceptual constructs and their respective items were
a) Task performance (TP): I plan my work to achieve the objectives established by the company (TP1), I establish
priorities for the activities to be developed (TP2) and I meet my work goal in the expected time (TP3).
b) Contextual performance (CP): I take on challenging tasks when I complete my previous tasks (CP1), update my
knowledge related to the work I perform (CP2), frequently develop my work skills (CP3), continually present creative
solutions to new problems (CP4) and actively participate in meetings and / or consultations (CP5).
c) Counterproductive behavior (CB): I complain about the negative aspects of my job (CB1), problems at work, they
often demotivate me (CB2), I focus on the negative aspects of situations of organizational change (CB3) and I talk
to people outside the organization about the negative aspects of my work (CB4).
From which the following conceptual model and hypothesis are established.
Conceptual model and hypotheses
H1: The customer service experience (CSE) based on digital transformation generates a positive impact on task performance
H2: The customer service experience (CSE) based on digital transformation generates a positive impact on contextual perfor-
H3: The customer service experience (CSE) based on digital transformation generates a positive impact on counterproductive
H4: The capacity of the collaborator (CC) based on digital transformation, generates a positive impact on task performance
H5: The capacity of the collaborator (CC) based on digital transformation, generates a positive impact on contextual perfor-
H6: The capacity of the collaborator (CC) based on digital transformation, generates a positive impact on counterproductive
H7: Processes (P) based on digital transformation generate a positive impact on task performance (TP).
H8: Processes (P) based on digital transformation generate positive impact on contextual performance (CP).
H9: Processes (P) based on digital transformation generate a positive impact on counterproductive behavior (CB).
H10: The business model (BM) based on digital transformation generates a positive impact on task performance (TP).
H11: The business model (BM) based on digital transformation generates a positive impact on contextual performance (CP).
H12: The business model (BM) based on digital transformation generates a positive impact on counterproductive behavior
The present study applied the deductive inferential scientific method, for which the type and level of applied and explanatory
research were used respectively, since it was intended to measure the causal link that exists between the study variables.
Likewise, the research design used is the non-experimental cross-sectional design.
4.1 Population and sample
The population is made up of workers from companies in the Peruvian insurance sector, made up of men (39.5%) and women
(60.5%), with an age range between 25 years and over, who were the object of study. A sample of 305 workers from insurance
companies was obtained, which are distributed in the north, center and south of Peru, located in the regions of Arequipa,
Cusco, Iquitos, Lima, Tacna and Trujillo.
4.2 Data collection instruments
Questionnaires were designed and applied to the collaborators of the different insurance companies in Peru. The structure of
the instrument presents 13 items for the digital transformation variable (four from customer service experience, three from
collaborator capabilities, three from processes and three from business models) and 12 items for the individual job perfor-
mance variable (three from performance work, five of contextual performance and four of counterproductive behaviors). For
the validation of the instrument, the Delphi methodology was followed, likewise, the reliability was determined through the
Cronbach's Alpha coefficient.
5.1. Assessment of the Measurement Model
Table 1 shows the measurement analysis of the model, based on the reliability and validity of the measurement scales. Re-
garding reliability, the internal consistency of the scales is evidenced through the Cronbach Alpha value (between 0.785 to
0.880) and the composite reliability (between 0.860 to 0.916). With respect to convergent validity, all factor loadings are
above 0.700 (Cordova et al., 2020). Likewise, all the scales have percentages of average variance extracted (AVE) greater
than 50%. The discriminant validity of the construct was tested by the Fornell Larcker criteria, which verifies the independence
of each of the scales, considering that the square root of the AVE is greater than the correlations with the rest of the scales. In
all cases, the assumption was met.
Results of the model measurement analysis
CSE 0.785 0.860 0.753
0.808 0.606 0.779
CC 0.834 0.900 0.840
0.906 0.751 0.867
P 0.838 0.903 0.831
0.902 0.756 0.869
BM 0.846 0.906 0.861
0.889 0.764 0.874
TP 0.828 0.897 0.835
0.901 0.744 0.863
CP 0.861 0.900 0.695
0.858 0.644 0.803
CB 0.880 0.916 0.811
0.883 0.732 0.856
As shown in Fig. 3, in all cases an R2 greater than 0.100 was obtained, which is very significant, showing that the model
significantly explains the variance of the conceptual constructs of the dependent variable.
C. V. Guzmán-Ortiz et al. /
International Journal of Data and Network Science 4 (2020) 343
Results for the hypothesized model with structural equations
5.2. Assessment of the Structural Model
After verifying the validity and reliability of the measurement model, the relationships of the constructs were tested. The
hypotheses were tested by examining the path of the coefficients and their levels of significance. Bootstrapping was performed
with 5500 subsamples to verify the statistical significance of each path of coefficients. Figure 3 shows the estimated trajectory
of the PLS analysis.
Modeling digital transformation and individual job performance
Considering that six specific relations have p <0.05, the proposed hypotheses H1, H2, H4, H5, H7 and H8 are accepted as
shown in Table 2:
Results of the model structure analysis
Hypotheses Mean sample Standard deviation Beta p value Decision
CSE → TP -0.185 0.070 2.704 0.007 Accept H1
CSE → CP -0.242 0.073 3.359 0.001 Accept H2
CSE → CB -0.059 0.075 0.730 0.465 Denies H3
CC → TP 0.488 0.067 7.351 0.000 Accept H4
CC → CP 0.514 0.062 8.252 0.000 Accept H5
CC → CB -0.151 0.079 1.926 0.054 Denies H6
P → TP 0.180 0.080 2.229 0.026 Accept H7
P → CP 0.184 0.084 2.149 0.032 Accept H8
P → CB -0.180 0.102 1.765 0.078 Denies H9
BM → TP 0.098 0.086 1.158 0.247 Denies H10
BM → CP 0.136 0.087 1.591 0.112 Denies H11
BM → CB 0.025 0.083 0.295 0.768 Denies H12
6. Discussion and conclusion
Based on the results obtained, this document provides a description of the impact of digital transformation (from the dimen-
sions: customer service experience, collaborator capabilities, processes and business model) on the individual job performance
of companies in insurance in Peru.
Regarding the impact of the customer service experience, based on digital transformation, on individual job performance
In the study, it was found that the customer service experience, based on digital transformation, has a significant influence on
the dimensions of task performance (p <0.05) and contextual performance (p <0.05), as well as a negative implication on the
counterproductive behavior dimension (p> 0.05). These results are in line with those of Ying-Yu et al. (2016), who mention
that customer service services through the web portal: B2B functions and cloud computing services significantly influence
the organizational performance of the Taiwanese textile industry. According to Itani et al. (2017), the proper use of social
networks as digital tools, positively affects the performance of employees. Likewise, Stoeckli et al. (2019) affirm that the
customer service experience, through chatbots, has been focused mainly on cost reduction and computer support for decision-
making, in this way, its implementation provides added value by improving performance of internal workflows, in addition
to taking advantage of the benefits of business systems such as alignment, control, interaction, operability and greater effi-
ciency, in the context of information systems.
Regarding the impact of the collaborator's capacity, based on the digital transformation in individual job performance
The research results show that the collaborator's capacity, based on digital transformation, has a significant influence on the
dimensions of task performance (p <0.05) and contextual performance (p <0.05), and a negative relation with the dimension
of counterproductive behavior (p> 0.05).
Similar results were obtained by Mihova & Ivanova (2020), who mention that Bulgarian organizations, immersed in the
digitalization process, promote the adaptability of their collaborators to digital environments, which is related to the capacities
of innovation, creativity and skills to team work; Therefore, the human resources area must redouble its efforts to constantly
promote digital learning for its collaborators, so that they are highly effective and this provides optimal results by improving
the performance of the organization. According to Winasis et al. (2020), 80% of the employees of a private bank in Indonesia
demonstrate commitment to the digital transformation that the financial sector is going through, where their employees have
a high level of commitment, work with passion and have an emotional bond with the company, which leads to better job
performance. Likewise, Maida et al. (2017), in an investigation carried out to an Indonesian insurance company, found that
job satisfaction and leadership style are positively related to employee productivity, achieving a significant effect on company
Regarding the impact of the processes, based on digital transformation, on individual job performance
The processes, based on digital transformation, have a significant influence on the dimensions task performance (p <0.05)
and contextual performance (p <0.05), and a negative relation link with the counterproductive behavior dimension (p> 0.05).
Witherspoon (2015), affirms that adoption of information technologies in insurance companies, of the microinsurance cate-
gory in Kenya, has been crucial for the performance of the insurance sector, generating a positive relationship with customer
C. V. Guzmán-Ortiz et al. / International Journal of Data and Network Science 4 (2020) 345
satisfaction, the performance of the personnel, product development and operational activities. In this line, Rosero (2019),
argues that digital tools establish a positive influence of knowledge management with the dynamic capacity of organizational
agility, which allows detecting and responding to changes in the environment, simplifying the ways of working and speeding
up processes; reaffirming that organizational agility based on processes has a positive impact on organizational performance,
production and operations, increasing labor productivity and the offer of products and services in companies.
Regarding the impact of the business model, based on digital transformation, on individual job performance
The business model, based on digital transformation, shows a negative relationship with the dimensions of task performance
(p> 0.05), contextual performance (p> 0.05) and counterproductive behavior (p> 0.05). In this regard, Khansa et al. (2017),
mention that, the use of social networks during the working day generates counterproductive behavior, which dissipates work
resources and interferes with performance at work. Likewise, Farivar and Richardson (2020), affirm the advancement of
information technologies has diversified the forms of work, one of them being remote work; however, working from home
extends the number of working hours, which generates greater worker burnout. However, the findings of Shishi et al. (2016),
indicated that customer service orientation, training, empowerment, affective organizational commitment, work stressors, and
emotional exhaustion influenced the recovery of clients by staff. On the other hand, Pitoyo and Suharyanto (2020), mention
that, the use of technological products in companies in the city of Bandung, Indonesia, generates great benefits by improving
product quality, reducing time in manufacturing processes and services, which have a significant effect on the performance
While this document provides several contributions to the literature, there are limitations as there is little research on the
impact of digital transformation and individual job performance, so further research is recommended to explore the role of
the insurance industry digitization in intangible service companies, so that greater investment in research will contribute to
the development of the sector.
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