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Using hybrid SEM –artificial
intelligence
Approach to examine the nexus between
boreout, generation, career, life and
job satisfaction
A. Mohammed Abubakar
College of Business and Social Sciences,
Antalya Bilim Universitesi, Antalya, Turkey
Abstract
Purpose –Boreout is a psychological state of intense boredom and apathy. Characterized by the absence of
mental stimuli (i.e. menial tasks) required to keep employees conscious about their environment, and this
incessant decline in mental stimuli may turn employees into “professional zombies.”The diversity in work
needs and preferences across generations has become a key organizational factor, generational differences
have been studied in Western countries, not much information is available about generational cohorts and
satisfaction (i.e. career, life and job satisfaction) in developing countries. The purpose of this paper is to
provide more insights on these phenomena.
Design/methodology/approach –Drawing upon conservation of resources theory, this paper examines
the potential effects of boreout on important job outcomes (i.e. career, life and job satisfaction) conditioned by
generation (Gen-Xers and Gen-Yers) in the service industry. Data analyses with Artificial Intelligence
technique (i.e. artificial neural network) and structural equation modeling were conducted with data collated
from Nigerian service employees.
Findings –Results revealed that boreout has a negative impact on career, life and job satisfaction. The
hypothesized relationships were significantly moderated by generation cohorts as Gen-Xers and Gen-Yers
were found to be distinct cohorts.
Originality/value –This paper advocates that non-western organizations should avoid utmost service
standardization and rigid stylization of work processes and procedures.
Keywords Job satisfaction, Quantitative, Nigeria, Service industry, Life satisfaction, Advanced statistical,
Career satisfaction, Boreout
Paper type Research paper
Overview
Organizations are investing heavily in programs meant to improve service employees’
behaviors during service encounters (Batt and Moynihan, 2002). These behaviors are
nothing else, other than scripted interaction and behavioral schemas. Service
standardization is harmful especially when it becomes extreme, employees are required
to act like robots e.g. recitation of scripts. Research has shown that the standardization of
service often reduces on-the-job challenge, which impedes creativity and encourages
habituation ( Janssen, 2000). This lack of service arousal and excitement might help
explain recent findings, which estimated that about 20 percent of service employees
are demotivated, and that demotivation causes about 15 percent of the total turnover
(Stock, 2015). Service standardization and formal procedures designed for customer
interaction in service delivery seems to demotivate employees (Wilk and Moynihan, 2005),
demotivation results in increased service failure (Abubakar and Arasli, 2016; Harris and
Ogbonna, 2002, 2006).
Personnel Review
© Emerald Publishing Limited
0048-3486
DOI 10.1108/PR-06-2017-0180
Received 14 June 2017
Revised 26 May 2018
13 December 2018
Accepted 22 February 2019
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0048-3486.htm
An abridged version of this research was presented at the ICEB’18, Fourth International Congress on
Economics and Business, Budapest/Hungary. The authors also thank colleagues within those sessions
for their comments.
Using hybrid
SEM
Quarto trim size: 174mm x 240mm
Research concerning lack of challenging work indicates that it can result to undesirable
outcomes ranging from job dissatisfaction, withdrawal, reduced job performance to turnover
(Bruursema et al., 2011; Gursoy et al., 2011; Van der Heijden et al., 2012). This paper is relevant
to the contemporary satisfaction approach and the service industry as a plethora of
management literatures and empirical studies related to (i.e. job satisfaction, career satisfaction
and life satisfaction) are limited to one or at most two forms of satisfaction (Chuang and Lei,
2011; Karatepe, 2010; Lee and Way, 2010; Zhao et al., 2011); with the exception of (Karatepe and
Karadas, 2015; Yavas et al., 2013). Accordingly, this study introduces a new satisfaction
understanding that combines the aforementioned variables. The point here is that, individuals
improve their overall well-being by consciously investing in the three domains of satisfaction,
so as to have a meaningful work-life and non-work-life experiences.
Research (e.g. Near, 1984; Russo et al., 2016; Sirgy and Lee, 2018) shows that the influence of
work-life (job and career related satisfactions) on non-work-life (life related satisfaction) is
pervasive and mutually reinforcing (i.e. job and career satisfactions lead to life satisfaction and
vice versa). Thus, career, job and life satisfaction are related to each other –career and job is a
priority in people’s lives and as a priority it is likely to be associated with other areas of life and
generational cohorts. While these concepts are widely used in mainstream Western contexts,
little is currently known about generational cohorts’perceptions in regard to career, life and job
satisfaction in other geo-cultural regions such Nigeria, and West Africa at large. This study
sought to redress this research gap by investigating the nature of interplay between the
variables. Moreover, literature related to work attitudes and behaviors such boreout in relation to
generation seems scarce in the West African context, this calls for a complete frame of reference.
Fajana (2009) argued that generational cohort is a function of employees’orientation,
attitudes and behaviors at work in Nigeria. Contrary, Owoyemi et al. (2011) found that
irrespective of the differences in age(s), the employees’attitudes to work and behaviors are the
same owing to unionized and participatory management style in Nigeria. Even with this,
boreout can still reign, because union membership in developing countries barely insulate
employees (Ineme and Ineme, 2016). Nigerian service industry workers (e.g. telecommunication
and financial services) in the same age group are more likely to share similar work attitudes
and orientation than those in the manufacturing and hospitality industry (Owoyemi et al.,
2011). Similar observations were made in South Africa (Mncwango, 2016).
To understand how lack of on-the-job challenge affects the aforementioned job outcomes,
this paper investigates a new conceptual phenomenon, known as Boreout. Job boreout refers to
“a negative psychological state of low work-related arousal manifested by job boredom, a crisis
of meaning, and a crisis of growth at work”(Stock, 2015, p. 574). Boreout as a low strain but
disturbing phenomenon needs managerial attention and represents a hidden threat to
employees at individual level and the organization at organizational level. Service employees
who suffer from boreout are less innovative as they engage in habitualized behaviors (Van Dyne
et al., 2002). Against this backdrop, using conservation of resources (COR) theory as a theoretical
framework this study develops and tests a new research model that investigates the
relationship between boreout and (i.e. career, life and job satisfaction) in the service industry.
According to Park and Gursoy (2012, p. 1195), “generational differences in work values (e.g.
work centrality, attitudes and leisure values) may further qualify the meaning of one work-
related variable to another.”This is primarily due to shared historical experiences (e.g.
birthdates, education, events, and lifestyle) among a group of people (Schuman and Scott, 1989).
Logically, one could speculate that boreout may have differential impacts on employees in
different generational cohorts. The use of the two-stage predictive-analytic, structural equation
modeling (SEM) and artificial neural network (ANN) analysis may provide a more holistic
understanding, thus, providing significant methodological contribution from the statistical point
of view. This is because the non-compensatory neural network analysis is able to complement
the weaknesses of the compensatory and linear SEM analysis (Abubakar et al., 2017).
PR
Boreout and research framework
The term boreout was coined by Rothlin and Werder (2008) in their work labeled “Boreout!
Overcoming workplace Demotivation.”Boreout entails the absence of meaningful tasks, rather
than the presence of stress. The conception here is that, a demotivated employee is not lazy
rather an individual who has lost interest in his/her work. Boreout consists of three dimensions:
boredom, loss of meaning, and lack of possibilities to grow (Stock, 2015). Job boredom is “a state
of relatively low arousal and dissatisfaction which is attributed to an inadequately stimulating
environment”(Mikulas and Vodanovich, 1993, p. 3). This may cause negative affectivity and
frustration due to the absence of or restricted social interaction, a form of resource loss
(Fisher, 1998). The absence of challenge at work can cause a crisis of meaning (Stock, 2015).
When employees lack this sense of importance, they are less likely to pursue organizational
goals (Kass et al., 2003). Lack of personal growth can cause a crisis of growth at work.
According to COR theory, resources are “conditions, objects, energies, relationships and
personal characteristics that are valued by the individuals or that serve as a means for
attainment of these objects”personal characteristics, energies, and conditions’(Hobfoll, 1989,
p. 516). From boreout lens, low work arousal, loss of meaning and lack of developmental
opportunities depicts resource loss. These resource losses may harm service employees, as it
leaves them with fewer resources (e.g. motivation and energy) to invest in their work
(Halbesleben et al., 2013, p. 493). Technically, these resources evolve in caravans; that is the
existence of resources may bring additional resources in the long run and vice versa. Based on
this proposition, resource investment is necessary for resource gain or resource recovery,
individuals who suffer from boreout will enter a loss spiral because of their inability or
unwillingness to invest remaining resources. Thus, their inability to invest their existing
resources to gain resources or recover from loss may decrease their satisfactions, in this view
boreout and satisfactions relate reciprocally.
Boreout and career satisfaction
Career satisfaction reflects how service employees feel about their career-related roles,
organizational experiences, accomplishments and success (Greenhaus et al., 1990). Measures
of objective career success include status, salary, promotion, family structure and position
(Kong et al., 2012). Measures of subjective career success include individuals’feelings of
accomplishment and satisfaction (Ng et al., 2005). Research has shown that challenging and
meaningful jobs can enhance career satisfaction (Burke, 2001; Kong et al., 2012). Challenge
stressors motivate employees because they install positive emotions, promote personal
growth and give a sense of personal accomplishment (LePine et al., 2005). While, boreout
seems to take off these challenge, by demotivating employees, and installing negative
emotions through job boredom. Furthermore, a crisis of meaning and a crisis of growth at
work tend to diminish personal accomplishment. It is important to note that those suffering
from boreout are dissatisfied with their professional situation (Rothlin and Werder, 2008).
There remains a dearth of empirical investigation concerning this relationship. Thus:
H1. Boreout is negatively related to career satisfaction.
Boreout and life satisfaction
Life satisfaction refers to “one’s evaluation of life, rather than the feelings and emotions that
are experienced in the moment”(Diener et al., 1985). Karatepe and Karadas (2015) added that
accumulation of individual resources determines life satisfaction. From boreout lens,
depletion of individual resources may affect important job outcomes like life satisfaction. In
order words, employees without sufficient resources because boreout are prone to negativity
(Rothlin and Werder, 2008). Job boredom, a crisis of meaning and a crisis of growth at work
have high tendency to reduce employees’work engagement (Stock, 2015). Consistent with
Using hybrid
SEM
COR theory, less engaged employees are likely to report lower life satisfaction, primarily due
to resource loss. The paradox of boreout is that despite the resource loss, employees are
unable to ask for more challenging tasks, or discuss the situation with superiors (Rothlin
and Werder, 2008). It could be speculated that as boreout perpetuates, life satisfaction may
decrease. Thus:
H2. Boreout is negatively related to life satisfaction.
Boreout and job satisfaction
Job satisfaction was conceptualized as an affective and cognitive construct by Netemeyer
et al. (1997); which include “positive emotional state resulting from the appraisal of one’sjobor
job experiences to all characteristics of the job itself and the work environment which
employees find rewarding, fulfilling, and satisfying, or frustrating and unsatisfying”(p. 86).
In short job satisfaction is associated with an evaluation of job characteristics Bakker and
Demerouti (2008) added that service employees who find interest and meaning in their jobs
often display elevated levels of affective commitment and performance. Challenge stressors
offers opportunities for personal development, growth and accomplishment, which enhances
job satisfaction and impedes job search behaviors (Cavanaugh et al., 2000; Stock, 2015).
Job boredom depletes valuable job resources, service employees with a crisis of meaning at
work perceive their work as futile (Douglas et al., 2004), and are less likely to deliver superior
service due to loss of work spirit (Purohit, 2010; Walker, 2009). Individuals with a crisis of
growth suffers from knowledge decline, which also affects performance (Bakker et al., 2010).
There is a dearth of empirical investigation concerning this relationship, intuitively speaking
job satisfaction for employees who suffer from boreout may decline. Thus:
H3. Boreout is negatively related to job satisfaction.
Moderating role of generation
Generation is “an identifiable group that shares birth years, age, location, and significant life
events at critical developmental stages”(Kupperschmidt, 2000, p. 66). Baby Boomers cohorts are
born between 1946 and 1964; Gen-Xers cohorts (1965–1980) and Gen-Yers cohorts (1981–2000)
as noted by Fry (2016). Attitudes of people in various generation with preferences of flexibility
and fulfillments ( Joyner, 2000), work attitudes (Costanza et al., 2012), work values (Smola and
Sutton, 2002), job satisfaction (Westerman and Yamamura, 2007) and commitment (D’Amato
and Herzfeldt, 2008) varies. Variation occurs because of the shared memorable life experiences
and events (Park and Gursoy, 2012), which shape attitudes and values of social life of
individuals in the same cohorts (Schuman and Scott, 1989).
According toSchwartz and Ros (1995), work value typology, and insecurity would result in
a generational emphasis on conservation and self-enhancement values. Socioeconomic
development was found to be negatively related to conservation and self-enhancement values
(Schwartz and Sagie, 2000). Inglehart’s (1997) theory of inter-generational values proposes that
individual’s basic values reflect the socioeconomic conditions of their birth dates. A possible
link between COR theory and generational cohorts surface because of environmental factors.
For instance, Gen-Xers experienced periods of economic prosperity, recession, distress
and family disruption (high divorce rate for parents) during their formative years
(Kupperschmidt, 2000). As a result, they are more individualistic, less loyal, and less
committed to employers (de Meuse et al., 2001, Tulgan, 1995), place less importance on job
security and status, but value personal freedom and challenging work, which allows for a
balanced work-personal life style (Kupperschmidt, 2000). Gen-Yers value working for
personal enjoyment and career success, working in a supportive culture and having training
and development (Broadbridge et al., 2007).
PR
Gen-Xers are not work-centric, value work–life balance and moderate leisure (Smola and
Sutton, 2002; Twenge et al., 2010). Gen-Xers prefers challenging jobs and better opportunities
to develop their own careers rather than seeking job security (Kupperschmidt, 2000). Like their
predecessors, Gen-Yers are not work-centric, have high leisure work values and they prefer
jobs that provide more leisure time than the older generations (Cennamo and Gardner, 2008;
Twenge et al., 2010). Research shows that they prefer meaningful and fulfilling work and are
not tolerant of less challenging work (Lancaster and Stillman, 2002; Park and Gursoy, 2012).
According to socioemotional selectivity theory (SST), older individuals harbor positive
feelings than negative ones as compare to younger individuals. Aging can cause a shift in
allocation of cognitive resources (Carstensen, 2006), in other words, future time perspective
(FTP) among older individuals diminishes, because they have got more of their life behind
them. According to Modderman (2017), “age was correlated with a decline in FTP, just as
predicted by SST,”in the context of this study age and satisfactions. Nevertheless, certain
work characteristics, like job complexity and job control moderated this relation in a way that
the relation became weaker with higher levels of satisfaction and control (Zacher and Frese,
2009). Retirement age lies around 65, it is worthwhile to examine if middle-aged people have
more positive or negative emotions (Modderman, 2017). Boreout (i.e. a crisis of meaning at
work, a crisis of growth at work and job boredom) might diminish older individual’s positivity.
In addition, older individuals have lower FTP (a feeling about life and a feeling about future),
because they have limited time left and can achieve little compare to their younger
counterparts. In this view, the negative impact of boreout on (i.e. life, job and career
satisfaction) will felt more among Gen-Xers than Gen-Yers. Thus:
H4a. Gen-Xers will strengthen the relationship between boreout and career satisfaction
as compare to Gen-Yers.
H4b. Gen-Xers will strengthen the relationship between boreout and life satisfaction as
compare to Gen-Yers.
H4c. Gen-Xers will strengthen the relationship between boreout and job satisfaction as
compare to Gen-Yers.
Method and materials
Sample and procedure
Consonant to prior researches, this paper employed a judgmental sampling approach. A
non-probability sampling technique employed when the sample selected approximately
represents the target population. Precursory interviews with practitioners’show that the
provision of personal services by service employees is important in the banking, retailing,
and telecommunication industry in the Nigerian context. In these industries, service
employees have direct contact with customers, which makes them suitable to study boreout.
Non-managerial/non-supervisory service employees who had full-time jobs in these
industries were selected. Consistent with Karatepe and Karadas (2015), part-time and
contract employees were not included in the sample, because they do not spend time and
stay at work as long as full-time employees do.
An e-mail that incorporated a link to the electronic questionnaire was sent to potential
participants with a request to voluntarily participate in the research and financial incentives
were not given to encourage participation due to budget limitations. In total, 1,000 e-mails
were sent, 38 e-mails bounced back owing to full mail-box and erroneous e-mail address
entry, as such 962 e-mails were delivered. Two weeks later, a second e-mail was sent to all
the 962 respondents asking them to ignore the message if they had participated. Due to the
anonymous nature of the survey, the researcher could not distinguish between those who
participated and those who did not; logically social desirability bias seems to be reduced.
Using hybrid
SEM
A total of 303 valid responses were retrieved, and only 258 responses were used due to
missing information. A comparison of the first and second responses suggested that there is no
significant difference. Of these responses, 53 percent were women and the rest men, 42 percent
were married and the rest were single and 55 percent belongs to Gen-Xers cohort and the rest
Gen-Yers. In total, 42 percent have organizational tenure between three and five years,
38 percent between six and eight years, 14 percent less than three years and the rest nine years
and above. In all, 44 percent of the respondents have monthly income above 100,000Naira,
34 percent between 80,000 and 99,999Naira, 17 percent between 50,000 and 79,999Naira and the
rest less than 50,000 Naira per month[1]. Most of the participants (47 percent), have bachelor’s
degrees, 30 percent have some college degrees, and 12.4 percent have higher degrees, and the
rest are high school certificate holders. Jackson (2005) revealed that younger workers mostly
occupy entry level jobs, with the highest concentration in the service sector. According to Park
and Gursoy (2012, p. 1196), Gen-Xers ‘are currently dominant in the service workforce as
Boomers retire, and Gen-Yers cohort are replacing Baby Boomers in the workplace. As such, the
data in this study reflects the reality in the service industry.
Instruments. Boreout was measured via 12 items adopted from the work of Stock (2015).
Career satisfaction was measured via five items adopted from the work of Greenhaus et al.
(1990). Recent studies that adopted this scale includes (Erdogan et al., 2018; McKevitt et al.,
2017). Life satisfaction was measured via five items adopted from the work of Diener et al.
(1985). Recent studies that adopted this scale includes (Ruvalcaba-Romero et al., 2017; Sheldon
et al., 2018). Response choices for boreout, career and life satisfaction ranges from 1 ¼disagree
strongly to 5 ¼agree strongly. Job satisfaction was measured via three items adopted from the
work of Netemeyer et al. (1997). Response choices for two items range from 1 ¼disagree
strongly to 5 ¼agree strongly, and for the other item response choice range from 1 ¼very
dissatisfied to 5 ¼very satisfied. Recent studies that adopted this scale includes (Karatepe and
Karadas, 2015). Self-reports seem appropriate for outcomes like boreout, career, life and job
satisfaction (Chan, 2009), the rationale here is that these are private events known by the
employee alone (Conway and Lance, 2010). This notion received empirical support from Shalley
et al.’s (2009) study, who argued that respondents are the ones who are aware of the subtle
things in their jobs. Henceforth, the current study adopted a self-report approach.
Results
All the measures were subjected to a confirmatory factor analysis for scale purification
using SPSS and AMOS program. The model fit indices are as follows: ( χ
2
¼469.6, df ¼
218, GFI ¼0.87; NFI ¼0.87; CFI ¼0.93; TLI ¼0.92; RMSEA ¼0.067; RMR ¼0.014;
χ
2
/df ¼2.15). Retained items factor loadings for each variable exceeded the recommended
value 0.60 (Bagozzi and Baumgartner, 1994). The Cronbach’sαcoefficients and composite
reliability (CR) for each latent variable was above 0.60, and the average variance extracted
(AVE) by each latent variable was above 0.50, except for boreout and life satisfaction.
Fornell and Larcker (1981) suggested that if AVE is less than 0.5 and CR is higher than 0.6,
the convergent validity of the construct is still adequate. Overall, model fit statistics and
significant loadings indicated evidence of convergent validity (Anderson and Gerbing, 1988)
(see Table I). The square root of each constructs AVE were above the absolute value of the
correlations with another factor. In addition, correlation coefficients were below 0.80 which
demonstrates evidence of discriminant validity (Kline, 2011).
For common method variance (CMV), confidentiality of the participants was assured,
and the online nature of the survey ensures this. Second, proximal and psychological
approaches were used to make it appear that the measurement of the predictor variable is
not related to the measurement of the criterion variables, by placing them on separate pages
(Podsakoff et al., 2003). Third, we compare the χ
2
for the single-factor model ( χ
2
¼1,577.1;
PR
df ¼222) with that of the measurement model ( χ
2
¼469.6; df ¼218), the Δχ
2
¼1,107.5
was significant. Moreover, the single-factor model fit indices were significantly worse than
that of the measurement model. This means that, the correlations between the observed
variables cannot be explained using a single-factor, these results provided support for the
four-factor measurement model and the potential threats of CMV seems not to be a problem
(Podsakoff et al., 2003). Fourth, ANN was used to complement the weakness of SEM, and the
bias neutron was used to abate this problem.
Intra-class correlations analysis (ICC) with the aid of two-way mixed and absolute
agreement definitions were used to assess the level of agreement between employees. The aim
was to check whether employees in different industries can be differentiated on the variables
under investigation. Single and average measures were reported for the variables, boreout
(ICC ¼0.49 and 0.91); career satisfaction (ICC ¼0.71 and 0.91); life satisfaction (ICC¼0.46
and 0.81); job satisfaction (ICC ¼0.55 and 0.79). Overall the F-value for ANOVA tests were all
significant ( po0.001). It appears that the scores in the variables are attributed to perceptions
of employees, and not necessarily the nature of the industry or branch office.
Instruments
Loadings
(t-statistics)
Boreout (α¼91, CR ¼0.90, AVE ¼0.49)
In my job I feel bored 0.72 –
In my job I am not fascinated by my tasks 0.70 10.66
In my job I am not able to concentrate 0.72 11.03
In my job I am frustrated _
a
_
a
My work seems meaningless 0.73 11.21
I do not see any sense in my work 0.72 11.15
I suffer from the fact that I do not see any point in my work 0.71 10.98
When I think about the meaning of my work I find only emptiness 0.68 10.38
My job offers me opportunities for personal growth and development (r) 0.73 11.29
My work gives me the feeling that I can achieve something (r) 0.70 10.81
My work offers me the possibility of independent thought and action (r) 0.61 9.40
I learn new things in my work (r) 0.68 10.45
Career satisfaction (α¼91, CR ¼0.89, AVE ¼0.68)
I am satisfied with the success I have achieved in my career 0.62 12.07
I am satisfied with the progress I have made toward meeting my overall career goals 0.69 14.48
I am satisfied with the progress I have made toward meeting my goals for income 0.95 30.99
I am satisfied with the progress I have made toward meeting my goals for advancement 0.98 –
I am satisfied with the progress I have made toward meeting my goals for the
development of new skills
_
a
_
a
Life satisfaction (α¼81, CR ¼0.82, AVE ¼0.47)
In most ways my life is close to my ideal 0.71 –
The conditions of my life are excellent 0.71 9.97
I am satisfied with my life 0.63 8.97
So far, I have gotten the important things I want in my life 0.69 9.73
If I could live my life over, I would change almost nothing 0.68 9.66
Job satisfaction (α¼79, CR ¼0.79, AVE ¼0.56)
I feel fairly well satisfied with my present line of work 0.78 10.74
I feel a great sense of satisfaction from my line of work 0.75 10.42
All things considered (i.e. pay, promotion, supervisors, co-workers etc.), how satisfied are
you with your present line of work?
0.72 –
Notes: CR, construct reliability; AVE, average variance extracted; α, Cronbach’sα.–denotes not available.
_
a
Dropped items during confirmatory factor analysis
Table I.
Psychometrics
properties of
the measures
Using hybrid
SEM
Means, standard deviations, and correlations for the study variables are presented in
Table II. Prior to testing the proposed hypotheses, the effects of control variables were
observed. There were few notable associations between the research and the control variables.
The data set revealed that boreout negatively influenced career satisfaction (β¼−0.426,
po0.001), life satisfaction (β¼−0.474, po0.001), and job satisfaction (β¼−0.614,
po0.001) of service employees. Hence, H1–H3 received empirical support. Refer to Table III.
For the moderating effect of generational cohorts on the measurement model, a moderation
analysis was conducted (Aiken and West, 1991). The standardized boreout value was
multiplied by generation to produce the interaction term. Finally, the “main”effects were
included in the model to prevent a biased estimate of the interaction. Refer to Table III.
The results in Table III show an insignificant interaction between boreout and generation on
career satisfaction (β¼−0.006, pW0.10), this means that the effect of boreout on career
satisfaction is not different across generational cohort. Thus, H4a was rejected. A significant
interaction between boreout and generation on life satisfaction was uncover (β¼−0.226,
po0.01). The negative effect of boreout on life satisfaction was higher for Gen-Xers. A
significant interaction between boreout and generation on job satisfaction was uncover (β¼
−0.155, po0.05). The negative effect of boreout on job satisfaction was higher for Gen-Xers than
for Gen-Yers. Thus, H4b and H4c received empirical support. To further explore the nature and
form of the interaction, a significant interaction was plotted graphically (see Figures 1 and 2).
Variable 1 2 3 4 5 6 7 8 9 10
1. Gender –
2. Tenure 0.001 –
3. Marital Status −0.069 0.065 –
4. Income −0.041 0.134* 0.107 –
5. Education 0.109 −0.022 −0.175** 0.119 –
6. Generation 0.002 0.079 0.476** 0.029 −0.119 –
7. Boreout −0.027 0.016 0.073 −0.060 −0.064 0.061 –
8. Career
satisfaction 0.095 −0.108 −0.108 −0.014 0.157** −0.065 −0.428** –
9. Life satisfaction 0.009 0.045 −0.053 −0.002 0.059 0.012 −0.473** 0.444** –
10. Job satisfaction 0.047 0.035 −0.010 0.091 0.035 −0.010 −0.613** 0.274** 0.502** –
Mean 1.53 3.41 1.41 3.17 2.60 1.55 4.57 1.36 1.28 1.40
SD 0.50 0.85 0.49 0.90 0.84 0.50 0.39 0.52 0.36 0.42
Notes: *po0.05; **po0.01 (two-tailed)
Table II.
Correlation analyses
with aggregate
descriptive statistics
Independent variable Dependent variable B(β)
Boreout Career satisfaction −0.569(−0.426) ***
Boreout Life satisfaction −0.436(−0.474) ***
Boreout Job satisfaction −0.663 (−0.614)***
Generation Career satisfaction −0.041 (−0.040)
Generation Life satisfaction 0.029 (0.040)
Generation Job satisfaction 0.023 (0.027)
Interaction effect
Boreout Career satisfaction −0.561 (−0.422)***
Boreout ×Generation Career satisfaction −0.002 (−0.006)
Boreout Life satisfaction −0.250 (−0.288)***
Boreout ×Generation Life satisfaction −0.047 (−0.226)***
Boreout Job satisfaction −0.515 (−0.511)***
Boreout ×Generation Job satisfaction −0.037 (−0.155)**
Notes: B, unstandardized coefficients; β, standardized coefficients; **po0.05; *** po0.01 (two-tailed)
Table III.
SEM results
utilizing maximum
likelihood estimates
PR
The management literature is devoid of combined methods e.g., SEM and ANN. ANN is
“a massively parallel distributed processor made up of simple processing units, which has a
natural propensity for storing experiential knowledge and making it available for use”(Haykin,
2001), ANN are known to operate via neurons divided into three components (i.e. input, hidden
and output layer). The input nodes in the input layers is the predictor variable, the hidden nodes
in the hidden layers process the data beforetheyaretransformedintoanoutputvalue
(dependent variable) using activation functions. The synaptic weights of the neural connections
will be adjusted via an iterative training process and the outcome is passed to the output node.
According to Leong et al. (2015) and Abubakar et al. (2018), “ANN is an artificial
intelligence tool that has outperformed these models as it can detect both linear and
nonlinear relationships with high predictive accuracy in comparison to traditional linear
models (i.e. logistic regression, MRA and SEM). Leong et al. (2015) added that ANN requires
no multivariate assumptions such as normality, linearity or homoscedasticity to be fulfilled.
Despite these advantages, ANN is not so ideal for testing causal relationships due to its
“black-box”operating nature and since linear models (e.g. SEM) have the possibilities of
over-simplifying the complexities in decision-making processes (Abubakar, 2018), the use of
the SEM–ANN approach in this study would complement each other.
1
1.5
2
2.5
3
3.5
4
4.5
5
Low Boreout High Boreout
Life Satisfaction
Moderator
Low Generation
High Generation
Notes: low generation: Gen-Yers; high generation: Gen-Xers
Figure 1.
Interaction effects on
life satisfaction
1
1.5
2
2.5
3
3.5
4
4.5
5
Low Boreout High Boreout
Job Satisfaction
Moderator
Low Generation
High Generation
Notes: low generation: Gen-Yers; high generation: Gen-Xers
Figure 2.
Interaction effects on
job satisfaction
Using hybrid
SEM
For this study, ANN multi-layer perceptron utilizing Resilient Backpropagation with
Weight Backtracking algorithm provided in R(neural net package) was used. Logistic
function is used as the activation function for both hidden and output layer of the ANN model
and sum squared errors was used as differentiable error function. The number of hidden nodes
generated was (3, 3). As a first step, I tested the model with generalized linear model (GLM)
function. Using prediction function in neuralnet GLM predictedan mean square oferror (MSE)
that is equals to 26.56, while neural network prediction produced an MSE that is equals to 0.24,
suggesting that the model is best predicted via neural nodes. The synaptic weights of the input
nodes on the hidden and output nodes are presented diagrammatically in Figure 3.
The training process needed 21,510 steps until all absolute partial derivatives of the error
function were smaller than 0.01. The estimated weights show that boreout and generation
exerts significant effects on the outcome variables. The distribution of the generalized weights
in Figures 4, 6 and 8 suggests that boreout has a nonlinear effect on the response variables as
the variance of the generalized weights are less than zero, suggesting a negative effect.
Furthermore, the interaction between boreout and generation has a nonsignificant effect on
career satisfaction, most of the generalized weights are less nearly zero (see Figure 5). However,
the interaction between boreout and generation have a non-linear effect on life and job
satisfaction, as the variance of the generalized weights are less than zero (see Figures 7 and 9).
Overall, this corroborate the hypotheses and the findings in SEM (Figures 4–9).
BOREOUT
BOREOUT GEN
Error: 12.342093 Steps: 21,510
CAREER SATISFACTION
LIFE SATISFACTION
JOB SATISFACTION
15.48215
–53.56991
–0.61421
–11.9548
–14.05218
–0.38385
–0.46469
0.67847
4.8013
2.7224
–4.76263
–1.46649
–907.1645
–4.59274
0.63861
3.701
–0.3924
12.55343 0.72754
–1.83529
–1.54864
0.06547
0.9605
1.34407
–0.32472
–1.7961
0.09132
–1.93106
0.86044
0.71796
–1.74824
1.24361
–0.00155
111
Figure 3.
Neural network model
4
2
0
–2
–4
0.0 0.2 0.4 0.6 0.8 1.0
BOREOUT
Response: CAREER_SATISFACTION
GW
Figure 4.
Plot for boreout and
career satisfaction
generalized weights
PR
Cross validation is another important step of building predictive models. In order to avoid
over-fitting, a tenfold cross-validation approach with a ratio of 75:25 data for training and testing
of predictions. MSE from ten networks was used to examine the accuracy of the model. Table IV
shows that the mean MSE ranges from 0.48 to 0.64 for training and from 0.25 to 0.61 for testing.
Hence, the author concluded that the model is reliable in predicting the study outputs variables.
Discussion
Boreout is a hidden and low strain, which represent an omnipresent threat for managers in
the service industry. Much has been researched and published concerning the effects of high
strain in the service industry (Gursoy et al., 2011; Karatepe et al., 2014). Accordingly, this
4
2
0
–2
–4
0.0 0.2 0.4 0.6 0.8 1.0
BOREOUT_GEN
Response: CAREER_SATISFACTION
GW
Figure 5.
Plot for boreout and
generation interaction
generalized weights
for career satisfaction
Response: LIFE_SATISFACTION
2
0
–2
–4
0.0 0.2 0.4 0.6 0.8 1.0
4
BOREOUT
GW
Figure 6.
Plot for boreout and
life satisfaction
generalized weights
2
0
–2
–4
0.0 0.2 0.4 0.6 0.8 1.0
4
BOREOUT_GEN
GW
Response: LIFE_SATISFACTION
Figure 7.
Plot for boreout and
generation interaction
generalized weights
for life satisfaction
Using hybrid
SEM
study contributes to theory and research regarding the effect of boreout on several
employee outcomes. This paper also sheds new light on boreout as pervasive construct with
a great impact on satisfaction using the doctrines of COR theory. Specifically, the impact of
boreout on (i.e. career, life and job satisfaction) modulated by generation.
The results from both methods show that boreout negatively influence service employees’
satisfaction (i.e. career, life and job), as service employees suffering from boreout may lack the
stimuli required to complete their tasks. Second, the absence of challenge reduces the sense of
meaning at work, especially when service employees are charged with menial tasks. Third, the
perception of not learning something new would diminish the perception of personal
accomplishments. All of the aforementioned absorbs employees valued resources, this is
2
0
–2
–4
0.0 0.2 0.4 0.6 0.8 1.0
4
BOREOUT_GEN
GW
Response: JOB_SATISFACTION
Figure 9.
Plot for boreout and
generation interaction
generalized weights
for job satisfaction
Neural network Training Testing
1 0.57 0.42
2 0.54 0.39
3 0.54 0.25
4 0.52 0.43
5 0.48 0.56
6 0.49 0.54
7 0.48 0.61
8 0.60 0.37
9 0.45 0.60
10 0.64 0.15
Mean MSE 0.53 0.43
Notes: Input nodes –boreout and generation; Output nodes –career, life and job satisfaction
Table IV.
Neural network –
MSEs
2
0
–2
–4
0.0 0.2 0.4 0.6 0.8 1.0
4
BOREOUT
GW
Response: JOB_SATISFACTION
Figure 8.
Plot for boreout and
life satisfaction
generalized weights
PR
consonant with COR theory, as loss of resources often makes an individual less productive and
less satisfied (Hobfoll, 2011). Moreover, Stock (2015) found that boreout sucks employee’s energy,
which makes it hard for them to behave in a customer-oriented manner during service encounter,
this due to fewer resources e.g., motivation and energy (Stock, 2016). Halbesleben et al. (2013)
highlighted that individuals with fewer resources, such as energy finds it difficult to invest it and
that it hampers productivity. In sum, the findings in this paper shows that boreout affects service
employee’s satisfaction in a negative way.
Drawing upon literature on generational differences in the workplace, this study found that
the effect of boreout is not different across generational cohorts. More specifically, the effects of
boreout on career satisfaction is not moderated by generation. Implying that Gen-Xers and
Gen-Yers have similar level of career satisfaction when they suffer from boreout. A plausible
reason is that insufficient resources (i.e. a crisis of meaning, crisis of growth and boredom) within
a particular role domain can result in dissatisfaction (Hobfoll, 2011). Furthermore, matching
between individuals and work environments have been the focus of producing career satisfaction
(Hackman and Oldham, 1980). The current outcome shows that career satisfaction for all
generations prioritizes upward advancement, occupational identity and career progression.
Gen-Xers experience lesser life satisfactionwhenboreoutishighandalowerscoreon
boreout indicates a higher life satisfaction for Gen-Xers than for Gen-Yers. A plausible
explanation for this finding can be related to person–environment fit (Macey and Schneider,
2008); Gen-Xers value work–life balance more than Gen-Yers who value work-life and leisure
(Smola and Sutton, 2002). On the other hand, Gen-Yers have higher expectations about
promotions and pay raises in the workplace (Ng et al., 2010), so it is possible that they consider
these factors alongside boreout. Gen-Yers are leisure-oriented and are attached to high internet
and social networking usage (Park and Gursoy, 2012). In line with COR theory, it possible that
online activities (i.e. social networking and games) both at work and at home helped in
protecting further resource loss, thus, buffering the negative effect of boreout on life satisfaction.
Gen-Xers experience lesser job satisfaction when they suffer from boreout and a lower
score on boreout indicates a higher job satisfaction for Gen-Xers than for Gen-Yers. Majority
of respondents in Gen-Xers cohorts were married as oppose to Gen-Yers who were single in
the sample. Thus, family enrichment might have buffer the negative effect of boreout on job
satisfaction for Gen-Xers. Contextual characteristics (e.g. marital status) generally have
weak relationships with enrichment (Lapierre et al., 2018), especially when there is a stressor
e.g., burnout, incivility and work-family conflict. In the context of this study, boreout is the
opposite of burnout, which means that those who experience boreout might have more
leisure time with their family, find more meaning in their family relationships which
consequently may relieve them from the negative effect of boreout. Gen-Yers are career and
leisure oriented rather than the job per se, and are characterized by economic prosperity and
advancement, as well as high internet and social networking usage (Park and Gursoy, 2012).
It is possible that they engaged in some sort of online activities while at work, which
ultimately buffers the effect of boreout on job satisfaction.
Boreout is the opposite of burnout but exerts similar effects, our findings also suggest that
older people are less likely to hold positive emotions than younger individuals. This is because
FTP is mostly lower among older individuals and with the presence of boreout, the tendency
for further positivity is evitable. The present sample is made up of individuals from Gen-Xers
and Gen-Yers, who emphasizes on employability rather than job security, they may be
considered too young to be experiencing substantial losses (Kooij et al., 2010). The take home
lesson here is that, as individuals get older workplace crisis seems to hinder further positivity.
Implications
Boreout is at large hunting down employees primarily due to overly standardized
processes, which will impede and diminish the satisfaction that every employee is entitle to.
Using hybrid
SEM
Work values and preferences across generational cohorts play a critical role in determining
the state of employee’s satisfaction and individual performance. This paper recommends
that firms should start reorganizing and restructuring their work environment and resources
to fit the unique psychological characteristics of Gen-Xers and Gen-Yers. Organizations that
place emphasis on training and development, opportunities for career progression, work
variety and a dynamic business model are more likely to attract younger generations
(Parry and Urwin, 2010; Terjesen et al., 2007) as they value autonomy and work–life balance
(Cennamo and Gardner, 2008). HRM practices should not just focus on increasing job
and career satisfaction, or balancing work-life domain, but enrich and design jobs to have
meaning and challenge, and also offer greater job autonomy by considering generation
as a contextual factor.
More specifically, integrating generational values and preferences (i.e. meaningful and
fulfilling jobs) into HRM practices can help retain younger workforce (Park and Gursoy,
2012). For instance, Gen-Yers are leisure rather than work-oriented, while Gen-Xers work–
life balance oriented. Thus, leisure activities like happy hours, video games, office mini golf,
waste basketball, ping pong and snooker can be incorporated into workplace design to
motivate Gen-Yers. Workloads and hours should be designed to balance work-family and
work-life to motivate Gen-Xers, these activities should not be limited to one generational
cohort but should be incorporated for both generations. Overall, this can stimulate,
motivate, and engage employees in their work. It is imperative for managers to learn and
have “generational intelligence”(Biggs and Lowenstein, 2011). Thus, generational
intelligence training is a valuable tool for managers to recognize and build supportive
organizational climate, which will help employees in (Gen-Xers and Gen-Yers) find intrinsic
meaning to keep balance in their work-lives.
Limitations and further research course
The strength and robustness of the current findings is that the study utilized two different
methods (neural network and SEMs) to test the data set. Nevertheless, the findings in this
paper should be interpreted considering the study’s inherent limitations. For instance, the
self-reported measures may raise concerns for CMV, although procedural efforts were madeto
lessen the impacts of CMV (i.e. ensuring confidentiality) and statistically (i.e. one factor and
ANN). The absence of a cross-lagged study design limits the causal conclusions that can be
drawn from the results. A longitudinal research design can provide confirmatory evidence for
the current findings. Moreover, these outcomes are applicable to Sub-Saharan work settings,
as such culture and/or ethnicity may have important roles in the relationships, as such future
studies should gauge for cultural and ethnic difference.
Although, the service sector is going through revolutionary change, which
dramatically affects the way in which we live and work. New services are continually
being launched to satisfy and meet consumer needs (e.g. online banking, e-Tailing, and
mobile advancement). It is important to note that the findings may not be applicable to
advanced nations with more effective resources (i.e. job design, greater autonomy, etc.).
This paper charged scholars to join the quest in finding positional moderators that
could buffer the negative effects of boreout such as waypower, and willpower. Other
fruitful avenues include the examination of potential antecedents of boreout such as
greater job autonomy, job design and work flexibility. Finally, future social science
scholars are encouraged to reap the benefits of ANN, as artificial intelligence could detect
both linear and non-linear relationships with high predictive validity. ANN outsmart
existing methods like CB-based SEM and PLS-SEM in several domains due to its
capacity to learn and predict outcomes accurately, additionally, ANN is largely
insulated from statistical flaws such as normality assumptions, sample size, linearity
and homoscedasticity.
PR
Note
1. US$1 ¼360.00 Naira€1¼427.72 Naira
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Corresponding author
A. Mohammed Abubakar can be contacted at: mohammed.abubakar@antalya.edu.tr
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