Exploration of Age-related differences in
task dynamics
Student: Kao Yang (10827307)
Supervisor: Hannah Berkers
MSc. in Business Administration Leardership and Management Track
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Statement of originality
This document is written by Student Kao Yang who declares to take full
responsibility for the contents of this document.
I declare that the text and the work presented in this document is original
and that no sources other than those mentioned in the text and its references
have been used in creating it.
The Faculty of Economics and Business is responsible solely for the
Table of contents
Abstract ... 4
Exploration of Agerelated differences in task dynamics ... 5
Introduction ... 5
Study 1 ... 7
Conceptual background and hypotheses development ... 7
Task dynamics... 7
Agerelated theories ... 10
Method ... 18
Participants and data collection... 18
Measures and Coding ... 20
Data analysis and results ... 23
Data analysis... 23
Results... 24
Study 2 ... 29
Method ... 31
Participants and data collection... 32
Data coding and analysis ... 33
Results ... 34
Reasons of agerelated differences in task dynamics ... 34
Agerelated differences of how task dynamics happen... 37
Discussion ... 42
Theoretical implications ... 43
Practical implications ... 45
Limitations and future research ... 45
References ... 47
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Abstract
Research topic: The purpose of this study was to explore whether there are any age-related
differences in task dynamics, why and how these changes happen.
Background: The phenomenon of aging and task change are prominent in organizations. It is
necessary to discover the appropriate match between employees at different ages and tasks.
Methodology: This study utilized both quantitative and qualitative method to examine and
explore research questions. Study 1 of quantitative research was aimed at examining the relationship between employees at different ages/career stages, and study 2 aimed at exploring underlying reasons of task change and explaining how tasks dynamics happens.
Findings: According to study 1, there were significant age-related differences in proportion of
new tasks in total tasks, whereas the age-related differences in task variety and task of person specialization were not significant. Moreover, employees at different career stages showed no significant inclination towards task variety, task of person specialization and new tasks, either. The study 2 revealed the detailed reason for established and non-established relationship, and identified the pattern for task dynamics, which was that younger employees are more likely to craft new tasks which can fulfill their developmental needs as well as organizational
performance than older employees.
Exploration of Age-related differences in task
dynamics
Introduction
It is noteworthy that the nature and structure of organizations, jobs, and careers have changed dramatically (Evans, Kunda, & Barley, 1994; Hall, 1996; Rousseau, 1997). Even if working in the same organizations, employees quite possibly have to face the change of their tasks. Especially paired with ageing problems increasingly threatening organizations ( Taylor, 2006; K insella & Phillips, 2005), making sure that employees at different life stages can perform tasks in positive mood is of highly significance to job design. Moreover, with the weakening attachment between employees and organizations, the jobs and tasks provided to employees should fit and satisfy their unique capabilities, preference, motivation and value (Rousseau et al., 2006) so as to attract and retain talents to keep organizations constantly competitive. Based on these reasons, it is time to have scrutiny into the relationship between employees and jobs they perform, in particular, the relationship between employees at different ages and task dynamics.
The concept of task dynamics by far, seems not to have a unified interpretation. Literally, task dynamics refers to the change in tasks. Research in this area mainly showed interest in job design (Morgeson & Humphrey, 2006) and job crafting (Frese & Fay, 2001; Wrzesniewski & Dutton, 2001). However, although many researchers have stressed the importance of taking into account the role of individual differences such as age in job design (Morgeson & Humphrey, 2006), only a few studies focused on the effect of age on job character istics (e.g.,
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Zaniboni, Truxillo, & Fraccaroli, 2013; Zacher & Frese, 2011), not to mention the relationship between age and task dynamics. Furthermore, the research of age effect in work motivation (Inceoglu, Segers & Bartram, 2012) as well as job-related skills and competencies (Johnson, Holdsworth, Hoel, & Zapf, 2013) indicted that physical and psychological changes that come with age can have an implication for work behavior and attitudes (Truxillo & Fraccaroli, 2013), which may constitute the basis of analyzing the change in tasks. As noted above, it is highly necessary to add to the understanding of career dynamics with the possible influence of employees’ age.
The current study conducted two studies to examine whether there are any differences in task dynamics in terms of employees’ age, why and how these changes happen, which can fill the gap by examining and exploring task dynamics in the context of employees’ age and thus is important to the field of industrial psychology in dealing with workforce in the future (Rhodes, 1983). Specifically, this paper utilized lifespan theory (Baltes & Baltes, 1990), career dynamics model (Fried et al., 2007) and job demand-resource model (Demerouti, Bakker, A. B, Nachreiner, & Schaufeli, 2001) which demonstrates age-related changes in work to explain the possible relationships between age and task dynamics. Since these theories take into account both the objective capabilities (e.g. skills) and resources related with employees’ age and the subjective psychological needs due to the position in their careers, the analyzing process facilitated more detailed reasons arise. F inally exploring the way to promote task dynamics provided a new perspective of enhancing employees’ performance (Cleveland & Shore, 1992)
meanwhile, advances hypotheses meant to answer the research questions in study 1. The ensuing sections of study 1 was aimed at testing the age-related differences in task dynamics, and study 2 with the purpose of exploring the detailed reasons for age differences in task dynamics and how task dynamics happens. The following part of discussion encompasses theoretical and practical implication of the study and lastly the paper concludes by discussing limitation and future research.
Study 1
Conceptual background and hypotheses development
Task dynamics
The review of task dynamics is geared towards providing the necessary theoretical basis for understanding the change processes of tasks. Tasks are defined by a goal of the work and are regular parts of a work, and they may be assigned by supervisors or se lf-set (Stamov-Roßnagel & Biemann, 2012). Accordingly, one possible way for task change is that organizations initiate top-down organizational interventions to improve employees’ motivation and organizational performance, such as job design (or job redesign) and job enrichment (Demerouti, 2014). The other path is the bottom-up approach that is initiated by employees or jobholders themselves to improve the design of their work, also called job crafting (Demerouti, 2015).
Job design continues to be of considerable practical significance to organizations (Tims & Bakker, 2010). Since the basic premise of job design is that work of stimulating nature is
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and behavioral work results (Morgeson & Campion, 2003), motivating employees and enhancing the organizational performance therefore serves as the remarkable function of job design. Moreover, the mechanism of changing the work is to promote the conditions and contents of work, which can greatly make employees feel motivated and satisfied.
By far the most popular approach to job design research derives from Job characteristics model (Hackman & O ldham, 1976). The five “core job characteristics” are: skill variety, which refers to different kinds of activities required in carrying out tasks; task identity, which requires doing a whole and identifiable piece of work through the process; task significance, which describes a substantial impact tasks have on the lives of people; autonomy, which describes the freedom employees has in carrying out work and feedback, which refers to direct and clear information employees are provided about their tasks (Parker et al., 2001; Oldham & Hackman, 2010 ).
According to Hackman et al. (1976), the five job characteristics were expected to increase positive behavior outcomes at work through promoting employees’ job satisfaction and internal work motivation (Hackman et al, 1976; Humphrey et al, 2007; Parker et al., 2001). So considering job characteristics as the important indicators to measure task dynamics is of remarkable meaning. However, given the unique tasks and working conditions prevalent in each job, changing tasks only by job design sometimes seems partly ineffective (Demerouti, 2015). The other way of task dynamics therefore attracts growing attention.
Job crafting emphasize the initiatives individuals take (Frese & Fay, 2001) to alter their work to better fit their personal needs and goals (Grant & Parker, 2009). Since uncertainty is a major characteristic of modern work (Scott & Davis, 2007), it is almost impossible to manage
uncertainty through control systems (Weick, Sutcliffe & Obstfeld, 2008), and hence, organizations can only rely on employees to take initiative to change how work is executed (Frese & Fay, 2001). Additionally, Wrzesniewski and Dutton (2001) summarized three basic individual needs giving rise to job crafting: the need to control over certain aspects of the work, the need to express a positive sense of self and confirmed by others, and the need to be connected to others.
Also from the job characteristics perspective, Job demand-resource model (Bakker & Demerouti, 2007; Demerouti et al., 2001) claims that employees make changes to their tasks by balancing their job demands and job resources with their personal needs and abilities (Tims & Baker, 2010). Several studies have discovered that employees with high job resources and tolerable job demands can improve employees ’ motivation and performance (Crawford, Lepine & Rich, 2010).
Based on the theories above, employees can actively cra ft their jobs because they want to manage uncertainty of their tasks (Frese & Fay, 2001), and fulfill their needs to establish connections with others (Wrzesniewski & Dutton, 2001) and keep the balance between job demands and resources (Demerouti et al., 2001). Especially the job demand-resource model (Demerouti et al., 2001) provides a new perspective to explain the age differences in job demands and resources, and therefore leads to the possible changing of tasks.
Taken together, the change of tasks tends to take the forms of job design and job crafting, which is closely related to the behavior and initiate of employers and employees in the organization. In addition, both of the two types of task change can be analyzed from the job characteristics perspective: job design theory describes five core characteristics of tasks and
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job crafting theory emphasizes the balance between demands and resources in jobs, reminding the study to take into account the job or tasks characteristics during the analysis of task dynamics. Lastly, both of the theories improve the organizational results by increasing employees’ motivation which directly boosts task dynamics.
Age-related theories
Although age is in many ways simply a statistical control variable in work (Truxillo & Fraccaroli, 2013), age as a matter of fact, can have a great implication for change of tasks. According to the extant literature, there is shift in employees’ motives as they age, and employees therefore transfer the inclination towards job characteristics (Inceoglu et al., 2012). So in order to figure out the relationship between age and task dynamics, understanding the relationship between age and task characteristics can help with the redesign of tasks for employees at different age stages (Zaniboni et al., 2013) and thus contributes to the understanding of the relationship between age and task dynamics. Lifespan development theory (Baltes, Staudinger, & Lindenberger, 1999) and career stage theory (Fried et al., 2007) provide a good framework of analyzing age-related changes in task characteristics and furthermore task dynamics.
Lifespan development theory proposes that changes continuously happen throughout one ’s lifespan and this development consists of several adaptive behaviors, such as transformation, acquisition, maintenance and attrition that occurred in the process of one’s life advancement (Baltes et al., 1999). To cope with changes happening in the environment as people age, it is of highly importance for individuals to apply strategies to adapt to the aging process and
meanwhile, to maximize gains and minimize losses when the biological, mental as well as social reserves decline across the life span (Hobfoll & Shirom, 2001; Truxillo et al., 2012). And a lifespan perspective can also be useful for explaining the interaction between age and task dynamics because people usually spend a tremendous part of their life at work where they are more inclined to applying adaptive strategies (Truxillo et al., 2012) to make sure the best fit between tasks and themselves.
There are two common adaptive strategies. Selective optimization and compensation (SOC) identifies three strategies people use throughout the aging process (Baltes & Baltes, 1990). Selection refers to making choices about what objects to pursue. Then people allocate resources and efforts to optimize their outcomes. Lastly, people use compensation strategy to offset age-related decline of their performance (Truxillo et al., 2012). So SOC theory elucidates the strategies people use to adapt to age-related changes, as well as dynamic changes in their work (Baltes & Dickson, 2001). For example, older employees may select certain types of tasks that can match their needs (e.g. application of accumulated experience and knowledge), allow them to optimize their efforts to achieve their desired results and also compensate their incline in other tasks (e.g. learning new knowledge). In contrast, younger employees may choose the opposite tasks that demand learning new knowledge rather than applying accumulated experience. So SOC theory, from the perspective of adaptive strategies, explains why employees at different ages prefer different types of tasks, which should be the possible cause of change in tasks.
Compared to SOC, socioemotional selectivity (SES) theory emphasizes that the perception of time is important in the selection of social goals (Carstensen, Isaacowitz, & Charles, 1999).
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For younger employees who perceive time more open-ended, prefer knowledge-related goals. Whereas for older employees, time is considered limited, and hence emotional goals are given a higher priority (Carstensen et al., 1999). Relevant to the tasks, SES theory can help to predict that younger employees, with the future-oriented goals (Zaniboni et al., 2013), are more likely to choose tasks that increase their work-related knowledge and benefit their career development; conversely, older employees showing less interest in accumulating new knowledge and skills, are inclined to select tasks leading to affective rewards at work (Truxillo et al., 2012). SES theory therefore explains different tasks wanted by employees at different ages through making a distinction of their work-related goals.
Based on SOC and SES theory, it is clear that age plays an important role in the process of task dynamics, especially by affecting the adaptive process and goals selection. Employees at different ages can thus focus on different job characteristics, and are more motivated to nudge task dynamics.
Career dynamics theory (Fried, Grant, Levi, Hadani, & Slowik, 2007) from the career stage perspective is another important theory to explain the relationship between age-related changes in tasks. According to Super & Hall (1978), a person’s life cycle was regarded as a series of stages characterized by changing patterns of activities, career concerns, values, and needs, which emerge as the individual ages and passes through various age ranges. So career stages are actually another form of employees’ age.
According to Fried et al. (2007), any career changes or job transitions are decided by how employees expect their career to develop over time ( Hall & Chandler, 2005), and employees’ reaction to stimulating work and tasks re lies on the stage of their career. When viewing time
as an objective linear advancement from past to present to future (Slife, 1993), employees at early career stages respond favorably to a lack of job stimulation, but respond less favorably to complexity, task variety and skill variety at later career stages. W hen viewing time, from the subjective perspective, as cyclical and more relative to the surrounding context ( Jones, 1988), employees’ decision to delay job stimulation at present not only to the vale nce of future rewards, but also to whether the length of delay is appropriate for the value of future outcomes. It is therefore can be suggested that employees’ reactions to stimulating tasks and their efforts to craft more stimulating tasks may depend on their career aspirations and expectations (Fried et al., 2007).
In a nutshell, age and career dynamics emphasize the function of time from both objective and subjective perspective of employees in task dynamics: For one part, people at different ages usually adopt different adaptive strategies to guarantee the fit with tasks; career dynamics, on the other hand, stresses the individual expectations towards tasks at different career stages.
Age and task dynamics
To better understand the job design/crafting for employees at different ages/career stages, digging into job characteristics can help to learn more about the change of tasks per se (Zaniboni et al., 2013). Besides, since job characteristics are not experienced by employees in the same way (Zaniboni et al., 2014), age/career stages seem to matter a lot in the attitude or reaction of employees towards task dynamics, and different job characteristics also benefit employees at different ages (Carstensen, 1991).
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The paper utilized task variety, task of perso n specialization and new tasks to measure the change of tasks. According to job characteristics model ( Hackman & O ldham, 1976), task variety is considered to be of different value to older and younger employees (Truxillo et al., 2012). Particularly, task variety is believed to be more beneficial to younger employees because it provides opportunities of learning multiple knowledge and skills for their future career (Truxillo et al., 2012). Task of person specialization stress the level of skills needed in tasks (Carter & Keon, 1989), and specifically, it refers to tasks which demands employees with formal knowledge or training (Dewar and Hage, 1978). So it is can be expected that older employees have more advantage than younger employees over this type of tasks. And new tasks describe the totally different tasks after changing and younger employees are more advantageous that older fellows as they can better balance the job demand and resources toward new tasks (Demerout et al., 2001).
Task variety is defined as a wide range of tasks which the job requires employees to perform (Morgeson & Humphrey, 2006). According to SOC theory (Baltes & Baltes, 1990), older employees, rather than focus on a wide range of tasks, are more likely to choose certain domains of tasks to realize their strengths with the purpose of optimize their time and efforts, which consequently provides opportunities for them to compensate their disadvantage in weak tasks(Zaniboni et al., 2013). Moreover, the distinction of two types of social goals of SES theory (Carstesen et al., 1999) implies that young adults prefer to perform more tasks for gaining new knowledge and experience. By contrast, older employees are less motivated to do multiple tasks, but pursue tasks satisfying emotional needs.
less likely to be interested in demanding jobs of multiple tasks due to the limited time of their career. As employees become older with deterioration of relevant learning abilities, cognitive demands and multiple tasks are found beyond older employees’ abilities, and they, rather than try to do more tasks, prefer to attach more attention to extending their mental energy ( Baltes, Staudinger, & Lindenberger, 1999 ) and building meaningful relationships through tasks (Baltes, Staudinger, & Lindenberger, 1999). Employees in later career stages are thus expected to be less in favor of task variety.
Based on these theories, whereas task variety may be more welcome by younger employees at their early career stages, high level of task variety could be detrimental to older employees at their late career stages.
H1: a. There are different attitudes of younger employees and older employees towards task variety: young employees prefer multiple tasks, while older employees prefer fewer tasks.
b. There are different attitudes of employees at different career stages towards task variety: employees at earlier stages prefer multiple tasks, while employees at later stages prefer fewer tasks.
Task of person specialization Person specialization is considered as a result of narrowing the areas of expertise such that a variety of work performed by employees is all directed to a narrow substantive area (Spaeth, 1979, p. 748). And task of person specialization thus refers to certain types of tasks which demands employees with formal knowledge or training (Dewar and Hage, 1978).
When considered with age, SOC theory (Baltes & Baltes, 1990) suggests that older employees can gain lots of benefits from performing tasks requiring accumulated skills and
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knowledge, which compensates other tasks demanding new skills where they are weak (Zaniboni et al., 2013). In contrast, younger employees with less experience need to learn and accumulate required skills and knowledge which makes them unqualified for specialized tasks.
From the career dynamics perspective, younger employees at their early career stages decide to accept less stimulating tasks as they expect that their jobs and tasks may become more stimulating, challenging and complex over time (Fried et al., 2007). Indeed, since careers are regarded as a lifelong series of developmental stages, employees at earlier career stages may more prefer tasks with simple skills because they usually expect these simple tasks will pave the way for the challenging tasks later in their career stages (Fried et al., 2007; Fried & Slowik, 2004). O lder employees, on the contrary, have no such expectations as they have already approach the end of their career stages and thus are more inclined to realize their value through applying their accumulated skills and knowledge.
It is, therefore, can be expected that older employees at their later stages should prefer tasks of person specialization than younger employees at their earlier stages.
H2: a. There are different attitudes of younger employees and older employees towards task of person specialization: older employees more prefer task of person specialization than younger employees.
b. There are different attitudes of employees at different career stages towards task of person specialization: employees at later stages more prefer task of person specialization than employees at earlier stages.
Job demand-resource model influences the attitudes or reactions of employees at different ages towards new tasks from two aspects.
On one hand, job demands can incite physical as well as psychological work strain (Liebermann, Wegge & Muller, 2013). As employees get older, they may risk losing fluid intelligence, such as a decline in memory (Hess, 2005), which inevitably leads to poor learning outcomes (Kanfer and Ackerman, 2004). So it is obvious that when faced with new tasks, the dropping of job-related abilities of older employees may hinder them from learning new skills for new tasks and can cause them suffer great work strain. But for younger employees, strong learning abilities make them more adapted to emerging new tasks.
On the other hand, job resources guarantee the basic needs satisfied during performing new tasks. Just as Maurer et al. (2003) concluded that adult age negatively influences personal variables (e.g. learning ability and attitude) as well as situational variables (e.g. resources and support from organization). As older employees may face more age-related constraints, less resources and support to learn something new at work, such as supervisory, compared to younger employees (Mirvis & Hall, 1996; Sterns & Subich, 2002), they tend to develop preferences to take on tasks they are more familiar with.
As regards career dynamics model (Fried et al., 2007), employees at their early career stages may react more positively towards new tasks, as they consider learning new skills and knowledge as a stepping stone to a highly promising prospect, while employees at later career stages hardly have such feelings. Hence, it is sensible to expect that younger employees at their early career stages are more positive about new tasks than older employees at their late career stages.
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H3: a. There are different attitudes of younger employees and older employees towards new tasks: young employees prefer more new task of than older employees.
b. There are different attitudes of employees at different stages towards new tasks: employees at earlier stages prefer more new task than employees at later stages.
Method
Study 1 used a quantitative and deductive method to test the relationship between age of employees and task dynamics. Being realistic and positivistic, quantitative research is aimed at discovering and explaining phenomenon through using mathematically based methods (Aliaga & Gunderson, 2000). So the study 1, based on lifespan development theory (Baltes et al., 1999), career dynamics model (Fried et al. (2007) and job demand-resource theory (Maurer et al., 2003), proposed a set of hypotheses which directed the whole research process, and then tested these hypotheses with data collected. Therefore, quantitative method is more suitable to explain the basic relationship between age/career stages and task dynamics.
Participants and data collection
For study 1, a quantitative research was conducted among elementary school teachers and non-teachers. Nowadays, the tasks of teachers are complex and challenging due to the complicated nature of desired professional knowledge ( Zaslavsky & Leikin, 2004), and the fact that there is no “text book” for the tasks (Peled, 2007). Especially to design effective educating tasks, technical (lessons work in a practical and understandable way), domain (teaching topic is covered fully and in an appropriate sequence) and generic (deeper insights affiliate the topic from other area as an interconnected structure) level of tasks (Cooper et al.,
2006) calls for different teachers’ skills and abilities to be applied to achieve ideal teaching goals. It is, therefore, necessary to figure out whether teachers at different ages or career stages prefer the same kinds of tasks and further, what the relationship is between age or career stage and different tasks.
The data was collected in 9 elementary schools in Netherlands during the period from February to March, 2015, with 134 employees (teachers and non-teachers) in total participating in this study. The tool for collecting data was offered by TNO, which is a leading organization dedicated to creating innovation solutions for various industries. The tool is online software which consists of 8 analysis steps and guides the users to do job analysis in detail. For example, “Task diagnosis” is a start- up step, asking respondents to input all the tasks they perform for their job. And “task chart” and “task dynamics” helps to judge the different proportions of tasks and the process of tasks changing. And the s tep of “risk/needs analysis” is aimed at analyzing the strength and drawbacks of each task.
Data collection started in February, 2015. After approaching some elementary schools with the introduction of research purpose, 9 elementary schools finally participated in this research. To collect the data, further explanation of this software and training was given in these schools, and then each respondent including teachers and non-teachers was asked to log on this software, and followed the instructions of each step to input the information of their tasks on it. The data, especially the individual information was treated confidentially and used exclusively for research purpose.
There were in total 134 teachers and non-teachers participating in the research. After ruling out the invalid cases, which had missing data in any variable, there were in total 114
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cases available for further analysis. O f 114 participants, there were 97 females and 17 males (14.9% of the sample). Age ranges from 25 to 65 years with an average of 46 years (SD = 11.1). More specifically, the age distribution was as follows: 13 participants (11.4%) were under 30 years, 40 (35.1%) were between 31 and 45 years, 61 (53.5%) were above 45 years. In addition, most of the participants (93%) possess the education degree of HBO. Employee tenure varies greatly, from less than one year (n=2, 1.8%) to more than 20 years (n=36, 31.6%), and the average tenure belongs to the group of 11-15 years (SD=1.45), in which there were 37 respondents, covering 37.5% of the sample.
Measures and Coding
The data mainly consisted of three categories of variables: task-related variables, such as task types, number of tasks, relative time spent, actual task dynamics, preferred future task dynamics/job crafting; consequence-related variables, including job satisfaction, job performance; and demographic variables, such as age, tenure, gender, educational background. Due to the fact that these variables were used for more than one research paper, they include variables that are not addressed in the current study. The following measurement thus only concentrates on variables needed.
Age:Age in the current study refers to chronological age. Since age was presented as “the year of birth” in the study, for the actual need of analysis, a recoding was conducted first to transfer the year of birth into the chronological age. In order to disclose the age-related differences in task numbers, a differentiation was then conducted between younger, middle-age and older working adults based on chronological age. Despite numerous
definitions of older and younger workers, the current study mainly adopts the definition of World Health Organization (1993) which sets the threshold of aging worker at 45. Hence, we specifically examine whether older employees (≥45 years), middle-aged employees (31-44 years) and younger employees (≤30 years) differ significantly over task numbers and task types. For the convenience of analysis, younger, middle-aged and older employees were recoded as 1, 2, and 3
Career stage: Just as Morrison (1994) proposed, employees with longer tenure are more likely to have expertise and experience with regard to some tasks. The paper thus utilized job tenure which measures the time spent on the job (Lee & Wilbur, 1985), to operationalize career stages of employees. The group of organizational tenure was set ahead of data collection, and there were 7 groups, ranging from the group 1 of less than 1 year to group 7 of more than 20 years. Consistent with the division of age groups, the division of earlier stages and later stages described the employees who worked less than 8 year and more than 20 respectively with the first years of going to work at about 22 years old. So the original 7 groups of organizational tenure were recoded: 1 to 4 groups (ranging from less than 1 year to 10 years) were recoded as 1; 5, 6 groups (ranging from 11 years to 20 years) were recoded as 2, and 7 group (more than 20 years) was recoded as 3.
Task variety: Since task variety refers to the wide range of tasks (Morgeson & Humphrey, 2006), the study thus utilized “number of tasks” during data collection to represent task variety. The data of tasks collected was the name of actual tasks, such as teaching, preparing, mentoring and so on, so the number of tasks was calculated by counting the number of total tasks each respondent typed.
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Task of person specialization: The relevant data collected was in the form of different task types. Task type was measured by asking the respondents to give a simple descript ion of what kinds of tasks they are performing within their current job status. There were 13 tasks mostly mentioned by respondents. They were teaching, preparation, correcting, need pupil, feedback, parent meeting, development of teachers, administration, having meetings, making reports, learning techniques, MR and committee.
According to Corwin (1969), specialization of teachers’ tasks is defined as the proportion of teachers teaching subjects in which they either majored or minored in college. Beck and Betz (1974) considered specialization as the degree to which the teachers’ classroom activities are limited to a narrow set of subjects taught. So from these definitions above, teachers’ tasks of person specialization should be centered on teaching activities. Moreover, teaching is not an isolated activity, which consists of a series of auxiliary tasks such as preparation, giving feedback, to realize its value, so one of the criteria of teachers’ task specialization is tasks designed or helpful for teaching.
Also according to the Dewar and Hage (1978), task of person specialization refers to certain types of tasks which demands employees with formal knowledge or training, which means that specialized tasks in this study can only be assumed by teachers because they have accepted formal teaching knowledge and training. So the second criterion of teachers’ task specialization is tasks exclusively performed by teachers.
Based on the two criteria, teaching, preparation, correcting, giving feedback, parent meeting and needed pupil belonged to specialized tasks for teachers, because they firstly, were tasks closely around teaching. For example, preparation means getting ready for teaching and
correcting means working on the assignments set by teaching. Secondly, they were the tasks that can only be performed by teachers. Without the formal training for teachers, one cannot assume the responsibility of teaching. Finally, count the number of specialized task s as classified for each participant as the coded task specialization.
New tasks: To represent new tasks, this paper utilized “proportion of ne w tasks” which measured the weight of new tasks in one’s total tasks. Instead of using the number of new tasks, the proportion of new tasks emphasized the relative value of new tasks because there was no comparability in the case that numbers of total tasks were not equal. And it was coded by counting the number of new tasks and total tasks respectively first, and t hen calculated the ratio of new tasks to total tasks.
Data analysis and results
Data analysis
Data obtained through the aforementioned method was analyzed with IBM’s Statistical Package for Social Sciences version 21. Additionally, no counter- indicative statements were used, so recoding is not necessary. Moreover, 20 cases were eliminated because they lacked the key variables in the study. Since the study was not based on questionnaire, there was also no need to review scale reliabilities. And scale means was done by computing the average value of each variable in the study.
Hypothesis testing was done with the use of one-way ANOVA, which allows to test hypotheses related to the differences of means between two or more groups. In this study, one-way ANOVA was to test if there exist differences of task number/specialized
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tasks/proportion of new tasks at different ages. The test consisted of two steps: the first step was to test homogeneity of variance to make sure that there are no significant differences of variance of observational variables, which is also a prerequisite for ANOVA analysis; the second step is to do one-way ANOVA for the hypotheses.
Results
Scale meansBy means of the analysis of Bivariate Correlations, the table 1 describes the means,
deviations and correlations of pivotal variables in the hypotheses. It clearly shows that, among the 3 dependent variables, only the proportion of new tasks is significantly related to age, with a Pearson correlation coefficient of .222 and the significant value less than .05. Moreover, the correlation between age and proportion of new tasks is quite weak, for the coefficient is less than 0.3. But none of these 3 variables are related to organizational tenure. The results hence indicate that there exists relationship between age of employees and the proportion of new tasks in their total tasks.
Table 1: Means, Standard Deviations, Correlations
Variables M SD 1 2 3 4 5 6 1 gender .150 .360 2 age 46 11.10 .087 3 tenure 5.36 1.450 .100 .67** 4 task number 10.96 1.560 .009 .094 .084 5 specialized tasks 4.690 1.400 -.190 .018 -.028 .50**
6 proportion_new .330 0.190 -.016 .222* .064 -.049 -.074 ** Correlation is significant at the 0.01 level (2-tailed)
* Correlation is significant at the 0.05 level (2-tailed)
Hypotheses test
One more step that had to be taken before the hypotheses was looking into the homogeneity of variance assumption for all three dependent variables. The table 2 below shows the result of homogeneity of variance test.
Table 2 Test of homogeneity of variance
Levene df1 df2 sig.
Task number .319 2 111 .727
Task specialization .323 2 111 .724
Percentage_new .548 2 111 .580
Statistical significance: * p <.05
It is clear from the table 2 that the significance value of all of three variables are bigger than 0.05 (.727, .724 and .580 respectively), so there is no reason to refuse the original hypothesis, which is that the variance of variables is equal. After testing the variance of variables, the result of one-way ANOVA was presented in table 3 below.
Table 3 Results of one-way ANOVA_AGE
SS DF MS F Sig.
Task number 1.463 2 .730 .296 .744
Specialized tasks .201 2 .101 .050 .951
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The table 3 demonstrates the age differences in 3 dependent variables: task number, specialized
tasks and proportion of new tasks. There was a statistically significant effect of age on
proportion of new tasks employees perform, with F value of 2.749 and p=068 (p <0.1), which means there are significant differences in different age groups with respect to the proportion of new tasks in total tasks. While for task number and specialized tasks, the p values are both bigger than 0.1, 0.744 and 0.951 respectively. And therefor there are not significant differences in different age groups with respect to task number and specialized tasks.
Table 4 Results of one-way ANOVA_TENURE
SS DF MS F Sig.
Task number 1.870 2 .935 .379 .686
Specialized tasks 2.088 2 1.044 .526 .592
Proportion_new .038 2 .019 .535 .587
* The mean difference is significant at the 0.1 level
The table 4 demonstrates the age differences in 3 dependent variables: task number, specialized
tasks and proportion of new tasks. According to the significance value, none of these variables are
significant in terms of tenure because p values are all bigger than 0.1, 0.6886, and 0.592 and
0.587 respectively. So it is clear that there are not significant differences in different career stages with respect to task number, specialized tasks and new tasks.
So based on the statistical results, part of the hypothesis 3a was supported: there are different attitudes of younger employees and older employees towards new tasks, while hypothesis 3b was not supported, which means there are no significant attitudes of employees
at different career stages towards new tasks. What is more, hypothesis 1 and 2 were not supported, and thus there are not different attitudes of younger employees and older employees towards task variety or task of person specialization. Since hypothesis 3a was only partly tested, and whether the older employees or young employees prefer new tasks demands further analysis.
Table 5 Results of Tukey post-hoc tests
Difference(I-J) Std.Error Sig. LB UB
young middle-age -.106 .059 .177 -.229 .017
old -.133 .057 .054 -.250 -.015
old middle-age .027 .038 .760 -.052 .105
* The mean difference is significant at the 0.1 level
A Tukey post-hoc test was used to gain more insight into how younger or older employees reacted differently towards new tasks. The table 4 of Tukey post-hoc tests revealed that the proportion of new tasks was significantly higher for the old employees compared to the young employees (p= .054), which means older employees have more new tasks in their total tasks compared to younger employees. And there was no statistically significant difference of the middle-age employees with the young employees (p= .177) and with the older employees (p
= .76), so the diction between preference towards new tasks of middle-age employees and
younger/older employees was not remarkable.
The findings were very interesting, because the hypothesis 3a proposed that younger employees prefer more new tasks than their older fellow, and the result was just opposite that older employees are more in favor of new tasks. So the hypothesis 3a was actually partly
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The overall goal of study 1 was to examine whether employees at different ages or career stages also experience different task variety, task of person specialization and proportions of new tasks in their total tasks. Results showed that firstly, there are no significant different preferences of employees at different career stages towards task variety, task of person specialization and new tasks. Secondly, employees at different ages do not show significant inclinations towards task variety and task of person specialization, but have different preferences towards different proportions of new tasks, and older employees prefer to assume more new tasks their younger employees, which only partly supported hypothesis 3a.
Study 1 applied lifespan theory, career dynamics model and job demand-resource model to the level of task analysis, but the result was somewhat against the theory or model. Firstly, according to job demand-resource model, when employees get older, the y may face the lack of personal resources such as learning ability and situational resources such as support from organizations (Maurer et al., 2013). So for older employees, considering their disadvantage in task-related resources, it is not wise for them to take on totally new tasks compared to their younger fellow. Secondly, career dynamics model indicates that employees at their early career stage can gain new knowledge and skills from performing new tasks, which is helpful for their future career (Fried et al., 2007), whereas employees at later career stage do not have too much expectations for future as younger employees. The contradiction between theories and results make it necessary to have a qualitative research about the reason of this phenomenon.
unsupported hypotheses, the study went to explore the underlying reasons of these existed or non-existed relationships between age and task dynamics, and furthermore, tried to find out how to promote task dynamics happen to better enhance the organizational adaptation.
Study 2
The study 1 verified the relationship between age and proportion of new tasks in total tasks of younger/older employees, and meanwhile, did not support age-related differences as well as career stage differences with respect to task variety and task of person specialization. Most importantly, the results were completely on the opposite side of theories ( Demerouti et al., 2001; Fried et al., 2007) which raised a series of questions, such as why do older employees have more new tasks in their total tasks than younger employees? Additionally, it was suggested that age research should go beyond providing evidence of differences between younger and older employees (e.g., N g & Feldman, 2008; Sturman, 2003) to investigating how those differences emerge in the first place (N g & Feldman, 2013), which demands more insights anchored on individual differences during the analysis of task change. So the first goal of study 2 was to reveal the reasons of age-related differences in task dynamics from a more individual perspective.
Ng and Feldman (2013) proposed five major areas that they expect individual changes may occur as they age: cognitive capacity, personality, goal orientation, socio-emotional experience, and health. In order to experience task change, employees must have the willingness to embrace changes (personality and goal orientation), the ability to take on new tasks (cognitive capacity and health), and a work context which fosters personal growth
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during change (socio-emotional experience) (Ng and Feldman, 2013). Especially from the perspectives of personalities, it can be inferred that older employees with the personality of openness to experience are more likely to take on new tasks than employees without this personality.
The second goal of study 2 was to explore how task dynamics happens with the consideration of age. The existed research of job design (Morgeson & Campion, 2003) and job crafting (Frese & Fay, 2001), rather than pay attention to the change of tasks per se, mainly focused on the effect of individual motivations and behavior during the process of change as they age. It is therefore of necessity to analyze how the tasks change from more comprehensive perspectives.
According to job design (Morgeson & Campion, 2003) and job crafting theory (Frese & Fay, 2001), tasks are changed in two ways: top-down organizational interventions and bottom- up individual initiative. In other words, tasks can be changed by their employers or themselves per se. Although both top-down and bottom-up change can work, a horizontal perspective is best (Hall & Hord, 2006). So there might also exist another situation that new tasks emerge naturally because of accumulated experience and knowledge, etc.
Apart from the way of change, type of change itself is also a key contingency variable that interacts with the implementation method to determine change success (Waldersee & Griffiths, 2004). According to the classification of Lawrence (1969), technical change makes a measurable modification in the physical routines of the job, and social change, conversely, refers to the way employees think it will alter their established relationships in the organization. Leavitt (1965) expanded these two types of change by adding a structural
change, which refers to optimizing organizational performance through careful design of the organizational structure, such as reorganizing work flows. As regards the match between change type and change path, Dunphy and Stace (1990) argued that large-scale changes including technical and structural change is better with top-down method, whereas small-scale social change can just be realized by increasing participation.
Based on the literature above, the paper accordingly inferred that the successful change of tasks should also take into account both the way of task change and task change type. But whether the type of task change follows the general change type in organizations, whether the match is still the same and whether age matters in change type and match remains further exploration in study 2.
To sum up, the study 2, utilizing a semi-structured interview, first explains the reasons underlying the relationship between age and task dynamics, and then further explores how task dynamics happens with the effect of age from the aspects of the way of change and change type.
Method
When little information is known about the research question, qualitative strategy preva ils in that it facilitates discovering the underlying nature of the question (Strauss & Corbin, 1990). Study 2 therefore utilized a semi-structured interview to further explore the underlying reasons and how task dynamics happens. Interviews were semi- structured. The structured part facilitated meaningful and standardized comparisons across interviews (kreiner et al., 2006). And in unstructured part, the researcher was able to go on with interesting answers and
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comments from interviewees, which pro vided possibility for greater depth and individual insight into required questions.
Participants and data collection
Interviewees were identified by purposive sampling method (Stone, 1978). Purposive sampling was used for sample selection in that it can ma ximize the obtainment of relevant information and help the penetration of research setting ( Esterberg, 2002). Considering the language and research question of the interview, potential interviewees were chosen for certain criteria. Firstly, the interview language was in English, so it was necessary to make sure the interviewees can express their meaning clearly in English. Having a job was another criterion because only people with jobs have the possibility to experience task dynamics. In addition, age was an equally important criterion in order to guarantee the age of interviewees was distributed reasonably in different age groups as mentioned in study 1.
Interviews consisted of 4 major open-ended questions to probe the task dynamics. Because of the criteria of purposive sampling, the researcher chose interviewees by inquiring them whether they can speak English, by asking them if they have a job and by judging their age approximately by their appearance. The interviews began with a brief introduction of the purpose and research questions to the interviewees. And then the research guaranteed no interviewees’ information would be revealed and asked for permission of recording.
The interview consisted of two parts. In the first part, interviewees were asked about their demographic information, such as age, position, tenure, etc. During the second part, following the techniques proposed by Leech (2002), the researcher asked interviewees to ans wer the
required questions and pursued interesting comments and themes arising within an interview in more details (Kreiner, Hollensbe, & Sheep, 2006). The researcher first asked interviewees to describe their daily tasks and then their feels about task change. To get information about how task change happens, interviewees were lastly asked to describe some situation of task change and characteristics of new tasks. The average length of the interview was between 20 to 30 minutes. The recorded information was then transcribed in to more useful data by the researcher immediately following the interviews.
The resulting sample was composed of 8 individuals, half of which were male. There were 3 individuals falling into the younger group (≤30), 3 individuals belonging to middle-age employees (31-44), and 2 individuals were the members of older employee group (≥45 years). They represented different kinds of professions, such as consultants, sales and HR manager. And the education background covered bachelor, master and PhD.
Data coding and analysis
After the original data including recording was transcribed into the readable information, the paper coded and analyzed interviews to identify emerging patterns or common characteristics (Strauss & Corbin, 1990) about task dynamics. The researcher first labeled each research question as the conceptual categories, such as attitudes (refers to underlying reasons) and changes (refers to new tasks emerging). Then the paper began a process of selective coding in which the researcher flagged each instance where interviewees mentioned information relevant to each category. After identifying all the instances, the researcher clustered all the relevant information into conceptual categories.
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Results
Based on the coding and analysis of interview data, three findings are as follows. First, reasons of new emerging tasks are summarized into three major ways. Second, characteristics of task dynamics are discussed in which learning new knowledge is the most significant characteristic. Third, interviewees’ attitudes towards task dynamics are analyzed based on three age groups.
Reasons of age-related differences in task dynamics
Inquiring the attitudes of interviewees towards task dynamics was to discover the underlying reasons of age-related differences in task dynamics, especially new tasks. Support for task dynamics occupied most of the answers with 7 interviewees, to various degrees, indicated that they felt it was meaningful and hence liked to actively engage in new tasks. Moreover, all the younger interviewees were in favor of new tasks. Only one older interviewee felt it was difficult to perform new tasks. Table 5 presented the detailed reasons of all interviewees.
Table 5 Attitudes towards task dynamics
age group position attitudes comments
younger
ERP implement engineer
support "It is a good thing to learn more, but better in the direction you are struggling for."
tax associate support
"New tasks, such as business consultancy, which needs more knowledge, always made me very tired and exhausted, but stimulated me to learn more; old tasks, such as tax filing, are relatively easy, but I also learned less from doing it. There should be a balance between new tasks and old tasks."
ERP finance
consultant support
"I'd like to try new tasks."
middle BIW process
manager support
"It is interesting and exciting to address new challenges and knowledge and I must learn more continuously."
HR manager support “Doing challenging tasks is the biggest motivation for me to do the job.”
sales manager support "New tasks are full of challenges, opportunities as well as room for development. Age only affects the old and uninteresting tasks, such as boring forms."
older University
professor support
"The fact of becoming older, at least for me, gave me the consciousness of the limited time in the future and convinced me, rather than relax, try to use the time to the maximum and the best. Although I must admit that over the years I have less strength to fight against the bureaucracy and the rigidity of the new system, I try constantly to expand my repertoire and my
knowledge. I try to use my experience to help students who are not even singers."
administrative
director object "I was too tired to do new things. I don't like it."
For interviewees supporting task dynamics, the positivity varies in different details. For younger interviewees who were also at their earlier career stage, t he ERP implement engineer believed that new tasks should better fit the direction you are struggling for, which reflected her certain criteria for new tasks. The tax associate maintained that “there should be a balance between new tasks and old tasks”, showing that reasonable distribution of new tasks and old tasks is more beneficial for employees. As to the administrative director who was averse to new tasks, the major problem consisted in that age made her unqualified for new tasks.
Whereas most interviewees showed positive attitudes towards task dynamics, when it comes to the relationship between age and attitudes towards new tasks, interviewees in
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different age groups reflected divergent opinions. For younger interviewees, although they all like to try new things, many considerations actually define the boundary of new tasks. For example, one interviewee stressed the direction of new tasks, and the other one emphasized the balance between new and old tasks, which, to some extent, reflected more uncertainty and worry towards new trying different tasks.
The middle-aged interviewee of sales manager thought “age only affects the old and uninteresting tasks, such as boring forms”, which implied he expects changing tasks when he gets older. As to the older interviewees, the university professor who is already 53 years old admitted that he felt less strength to fight, but when he realized the limited working time left for him, he was more willing to try to use the time to the best. Conversely, the interviewee, the administrative director, who is of the same age as the professor, thought she was unable to do new things because so many limited conditions of her body and ability.
The reason given by interviewees, to some extent, can answer the unresolved questions in study 1. For younger employees at their earlier stages are concerned with clarifying their career capabilities and directions in order to make choices about their future career (Hess & Jepsen, 2009), and they are therefore likely to respond favorably to a lack of job stimulation (Fried et al., 2007), including trying multiple tasks and new tasks. For older employees at their later stages, the university professor provided a new perspective for explaining the possible preference towards new tasks. As he approached the end of his career, he wanted to use his knowledge and experience to help more students. It is in line with Fried’s (2007) proposition that employees are more likely to favorably respond to task significance at later stage, because they can make lasting contributions and benefit future generations
(Wade-Benzoni, 2006). Consequently, significant and meaningful new tasks are actually supported by older employees at their later career stages.
As to task of person specialization, the other older interviewee failed to do her original, specialized tasks. Despite of the fact that she owned rich experience and knowledge, considering her deteriorating cognitive capability and energy (N g and Feldman, 2013), her boss gave her easier new tasks. So it is suggested that if the specialized tasks demand working memory, abstract reasoning, attention and processing of novel information (Kanfer & Ackerman, 2004) which decline seriously for older employees, they may be not qualified to do these kinds of tasks.
Based on the analysis above, task dynamics is an inevitable trend and most employees seem to actively engage in these changes. But whether employees at different ages or career stages prefer different kinds of task dynamics is influe nced by so many factors, including task types and individual capabilities. More details during the changing process still need to be taken into account carefully.
Age-related differences of how task dynamics happen
Interviewees described that tasks change mainly in three ways. The first way is task changing by oneself (bottom- up), which means employees themselves participate in the changing process or initiate changing tasks (Waldersee & Griffiths, 2004). The second possible way is that changes of tasks just happen naturally (horizontal) because of increased experience, knowledge and capability. Changing driven by supervisors or external factors (top-down) is the last way that tends to be procedural, focused on resource allocatio n and
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follow formal authority lines (Waldersee & Griffiths, 2004). The most widely mentioned way of task change in the interviews was changing by supervisors or external factors, with 7 interviewees attributing all or part of their new tasks to supervisors or external factor. The details of these changes are presented in Table 6.
Table 6 Details of task dynamics
w a y s p o s i t i o n e x a m p l e s
bottom-up tax associate
"Compared to the first-year associate, I can have more choices in tasks and my mentor will assign more complicated tasks to me. Like I'd like to choose tasks which need some techniques, such as calculating the tax, rather than doing some legwork."
horizontal sales manager
"I need to solve problem arising naturally, such as answering the technical questions, which actually belongs to technical sales."
ERP finance consultant
"I can do some communicating with customers after observing senior consultants' communication."
top-down BIW process manager
"Basically, my tasks were changed from only doing some technical design to design review, project management, budgeting and coordinating relevant departments, which was together with the change of positions and systems of the firm. Also my supervisor assigned me new tasks because he thought I was capable of doing these tasks."
ERP implement engineer
"Different projects, such as finance system and contract system, mean different tasks and business I need to handle."
HR manager
"Every year, my boss assigned my new tasks. At first year, I built up HR department and basic framework of HR, compiled relevant contents of training; at second year, I deepened the influence of HR department in the whole firm, and in charge of company moving; at third year: I did delegation and trained subordinates."
University professor
"The only change is the increasing difficulty to work
simultaneously with more students, due to the changes to the new system of bachelor and master. With the new system, students are forced to attend courses for the only reason to earn credit points, even if the course is not important for their future profession. The study became shorter and stiffer. For my work it is important to organize rehearsals with more singers at the same time, and this has become difficult, even impossible. "
administrative
director
"I was in this position for only 3 years, and before this position I was a supervising engineer. 3 years ago, my boss wanted me to do some office work, because I am a little bit old, and there were new engineers coming."
For the way of task changing by supervisors or external factors, just like the BIW process
manager said, “my supervisor assigned me new tasks because he thought I was capable of
doing these tasks”, it is thus easy to understand that with the growing up of employees in the
organization, knowledge, capabilities and experience change accordingly (Ng & Feldman, 2013; Zaniboni et al., 2013), and supervisors would be more likely to assign the new tasks which also match the capability of employees. And the other common situation is that organizations demands employees to continuously learn new knowledge and techniques through doing new tasks, because organizations also need to cultivate employees from within rather than always hire new employees outside to fit in the new tasks. For example, the HR manager mentioned that she did new tasks ranging from “building up basic framework of HR department” at first year to “delegating and training subordinates” at third year. She had to keep on learning new knowledge required by new tasks every year.
For the way of task changing from bottom, employees having initiatives actively engage in crafting new tasks to make his or her own tasks more meaningful and satisfying (Demerouti, 2014). However, the condition for realizing this change is that the employee has the choice
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“compared to the first-year associate, I can have more choices in tasks…and I'd like to choose tasks which need some techniques”.
As to the way of task changing naturally, it is closely related to the employee ’s experience and capability. And most of time, the new tasks just arise as the employees should do them. For the sales manager, he sometimes needed to “answer the technical questions, which actually belongs to technical sales”, just because he also has a good mastery of techniques and there was need to bother technical sales especially the situation was urgent.
Taken all together, the information above shows that there are mainly three ways accounting for the task dynamics, and every way has its underlying reasonableness and suitable situation. Also, the ways for change can co-exist at the same time.
Change type of tasks
The distinction of change types of organization (Lawrence, 1954; Leavitt, 1965) guided the researcher to look through the new tasks of interviewees to identify the change type of tasks.
Also based on table 6, the researcher found that the changes not only appeared as tasks, but also happened in the interior of the task although the task itself didn’t change. For example, sales manager mentioned, “I needed to change my sales method because of changing customers and products.” Methods to do the tasks are usually not regarded as independent tasks because they are hardly measured by performance. According to Lawrence (1954), technical change refers to the modification to the physical routines of job. When the definition is applied to the level of task, it can be regarded as the modification to the physical routines of tasks, including the method used to do the tasks. So the technical change of tasks mainly stressed the interior of tasks.
