Job satisfaction

CHAPTER I
Introduction
Job satisfaction is one of the important factors that has drawn research interest among scholars and practitioners interested in enhancing employee productivity. Past literature is in consensus on the possible correlation between job satisfaction and employee resilience (Abualrub et al., 2016; Bojadjiev et al., 2015). Devi and Rani (2016) defined job satisfaction as a positive emotional response employees experience when doing their jobs and a personal feeling of satisfaction on the job, which in turn motivates an employee to become more productive. Resilience defined by King et al. (2015) as workers' ability to adapt to changing circumstances even when such circumstances are disruptive or discouraging.
Within the knowledge industry, job satisfaction is key to organizational success, because
satisfied employees are more likely to remain committed to their jobs and work towards executing set goals. Sarrasin et al. (2017) shared that motivation is key to long-term employee resilience and productivity within the knowledge industries such as the Canadian airline sector. Suifan (2019) added that motivated employees within the hotel, restaurant, and tourism sector tend to be more productive and innovative compared to demotivated employees. In the travel, teaching, and healthcare industries within the United States of America, a study by Utami et al. (2016) showed that less motivated employees were highly associated with voluntary attrition, resignations, and absenteeism.
Addae and Boso (2020) reported that low job satisfaction among Ghanaian employees was largely associated with perceived absence from work and high turnover intentions. Wang et al. (2019) reported similar observations on job satisfaction with a study on 278 hospital employees in Australia. Researchers found that employees who did not receive training, career advancement, skill development, or positive feedback from their managers were most likely to show high attrition due to low motivation (Wang et al., 2019). These insights also reveal that job motivation is correlated with workplace resilience because demotivated workers tend to be less committed to remaining in their current jobs. Similar observations were reported by Sarrasin et al. (2017), where demotivated Canadian airline workers were more likely to seek alternative employment or voluntary resignations.
Lu et al. (2020) noted that about 35% of new employees within the knowledge sector in China and South Korea are more likely to leave their jobs within the first year of employment. In addition, about 61% of the workers surveyed shared that they are less likely to retire in their current jobs or organizations, indicating a high possibility of seeking alternative employments or organizations. Naifeh and Kearney shared that between 2010 and 2015, 27% of the American employees within the hospitality industry reported being dissatisfied in their current jobs and expressed willingness to seek recruitment in other companies. In the last five years, 31% of current employees within the tourism, travel, and hospitality industry have been actively seeking alternative jobs, which was an increase of 4% from the year 2015 (Naifeh & Kearney, 2020). Supporting these considerations, insights by Lu et al. (2020) and Naifeh and Kearney (2020) showed that demotivated workers were less likely to persist in their jobs, hence the high instances of job resignations and attrition rates.
A similar correlation between job satisfaction and workplace resilience has been reported within the American knowledge industry. Côté et al. (2020) conducted quantitative research on teaching, customer support, and library employees to examine how job satisfaction influences their workplace resilience. The researchers also explored the possible mediating role of perceived organizational support and work engagement on the relationship between job satisfaction and resilience. Results revealed that work engagement and top management support influenced employee job satisfaction and further informed their organization's resilience. Highly motivated employees were less likely to leave their jobs, thereby indicating a potential relationship between job motivation and workplace resilience (Côté et al., 2020).
Contrary to the above considerations, the literature findings reveal that the association between job satisfaction and workplace resilience is complex and may not be a linear relationship. Gagné et al. (2015) shares that one of the main variables that influence the relationship between job satisfaction and workplace resilience is the existing employee incentives in an organization. In elaboration, employees who receive feedback, praise, and job promotion tend to be highly motivated and more likely to remain in their jobs than workers who do not receive support from top management (Gagné et al., 2015). Jayaweera (2015) reports that workplace environmental factors such as management support, training, and skills development motivate workers to become committed to their organization. Additional insights by Resnick (2011) revealed that motivated individuals are more likely to show high resilience and creativity in their work, with low attrition rates.
As applies to this study, motivation refers to the level of commitment, energy level, amount of creativity, and enthusiasm employees show to their organization when executing tasks (Antonaki et al., 2014; McGuire et al., 2015). Past researchers have attempted to examine the possible role motivation plays in facilitating employee performance and workplace loyalty. Jawaad et al. (2019) reported that motivation mediates the relationship between employee job satisfaction, organizational commitment, and human resource practices. Fernet et al. (2015) explored the potential mediating role of motivation and job characteristics of transformational leadership and optimal employee productivity. Results revealed motivation influenced the relationship between leadership style and employee performance.
Manalo et al. (2019) investigated how job satisfaction mediated the relationship between motivation, workplace commitment, and work engagement among secondary school teachers in Metro-Manila, the Philippines. Results revealed that job satisfaction affected employee motivation and subsequently informs the teachers’ intention to remain or resign from their jobs. Oh et al. (2017) further examined the mediating role of organizational value on employee commitment, motivation, and productivity. Insights from the survey participants indicated that a positive workplace environment and existing organizational culture influence employee motivation. Motivated workers, in terms of being valued and appreciated, tended to be more creative, productive, and committed to their organizations and were less likely to express the intention to leave their current organizations or workplaces (Oh et al., 2017).
Existing Gaps in The Literature
Despite the growing research interest on job satisfaction and workplace resilience, the relationship between the two variables is inclusive. Linn et al. (2020) reported that past research has attempted to explore different factors that mediate the relationship between job satisfaction and employee resilience in their work. Results from the extant literature show inclusive evidence that job satisfaction directly influences employee resilience because job satisfaction depends on many variables (Linn et al., 2020). For instance, Topchyan and Woehler (2020) noted that employees might show resilience towards their work because of personal issues such as lack of alternative employment, but their resilience may not necessarily indicate that they are satisfied with their jobs. By contrast, Ahluwalia and Preet (2017) shared that an employee may continue working in their low paying jobs and poor working conditions solely due to their love towards their work despite low job satisfaction.
Further research in the past literature on job satisfaction and workplace resilience revealed a lack of consensus on the specific relationship that exists between the two variables. Moreover, the examination of different literature on the topic indicates that researchers have often used different variables when exploring workplace resilience (such as pay, career development, and personal growth opportunities) and job satisfaction (such as leadership types, internal politics, trust, and organizational citizenship) (Al-dalahmeh et al., 2018; Haar & Staniland, 2016; Srivastava & Madan, 2020; Varshney & Varshney, 2017; Zheng et al., 2017). As such, there are limited studies that have presented a single conceptual framework on the main job satisfaction and workplace resilience variables that may be used to understand employee dynamics within the knowledge industry.
Lastly, thorough extensive research, it was apparent that all job satisfaction scales were outdated and very time consuming. Gagne et al. (2007) conducted a thorough literature review on seven different job satisfaction scales which included the Overall Job Satisfaction (Brayfield & Rothe, 195), Michigan Organizational Assessment Questionnaire (Cammann, Fichman, Jenkins, & Klesh 1979), Hoppock’s satisfaction scale (Hoppock, 1935), The Job in General Scale (Ironson, Smith, Brannick, Gibson, & Paul, 1989), Job Descriptive Index (Smith, Kendall, & Hulin, 1969), the Minnesota Satisfaction Questionnaire (Weiss, Dawis, England, & Lofquist, 1967), and Job Satisfaction Survey (Spector, 1985) to create a new job satisfaction scale that is relatable to today’s workplace (Gagne et al., 2007). This instrument measures job satisfaction, but with another construct, work satisfaction. In this measure, work satisfaction is defined as the current change and developments in the way the job is performed versus the “non-traditional work arrangements” (Arthur, Khapova, & Wilderom, 2005; Hall & Moss, 1998). Furthermore, work satisfaction measures and individuals satisfaction with specific “job or career” (Gagne et al., 2007). Therefore, using a relatable and valid instrument to measure work satisfaction will add value to understanding the relationship between work satisfaction and workplace resilience along with examining the mediating role of self-determined motivation.
The Problem Statement
Evidence extracted from past studies also indicates that the common variables that have been used to explore employee workplace resilience and performance include job satisfaction, job involvement, organizational commitment, perceived job characteristics, and work satisfaction (Al-dalahmeh et al., 2018; Ćulibrk et al., 2018; Fernet et al., 2015; Paul et al., 2016; Vallerand, 1997). However, initial literature failed to identify studies within the knowledge industry that have investigated the relationship between job satisfaction and workplace resilience and whether motivation mediates the relationship between the two variables. Thus, there is a need to undertake the current study and examine the extent to which motivation mediates the relationship between job satisfaction and workplace resilience within the knowledge industry (Ćulibrk et al., 2018; Fernet et al., 2015). In the light of the identified knowledge gap from the past literature, the next section presents a description of how the current study will add and substantiate the existing body of knowledge on the relationship between job satisfaction and workplace resilience.
Contribution of the Study
Past research conveyed that the relationship between job satisfaction and workplace resilience remains inconclusive. Proponents denoted that there is a positive linear correlation between job satisfaction and workplace resilience (Haar & Staniland, 2016; Srivastava & Madan, 2020; Varshney & Varshney, 2017; Zheng et al., 2017). Furthermore, employees who show high levels of job satisfaction are more likely to be resilient in their workplace by remaining loyal and showing less intention to leave or resign (Al-dalahmeh et al., 2018). However, critics note that job satisfaction does not necessarily result in workplace resilience because of the different factors that determine individual satisfaction levels (Oh et al., 2017). According to Manalo et al. (2019), factors that may contribute to one employee's job satisfaction may not necessarily result in the satisfaction of another employee. Therefore, employee diversity in job preferences may affect their satisfaction levels and subsequent workplace resilience (Sarrasin et al., 2017; Utami et al., 2016).
Considering the contention that exists in the current study, Al-dalahmeh et al. (2018) noted that lack of consensus in the academic and practitioner literature regarding job satisfaction and workplace resilience is attributed to the use of different methodologies research variables. The current study, therefore, seeks to add new knowledge in the existing literature by exploring the mediating role of motivation on the relationship between job satisfaction and workplace resilience.
This study's findings will additionally identify if motivation is likely to influence the relationship between job satisfaction and workplace resilience, further helping identify the possible conceptual or theoretical framework discussed below to understand how motivation may influence both job satisfaction and resilience. As a result, obtained findings would be central to filling the current knowledge gap in the literature regarding the specific nature of the relationship between job satisfaction and workplace resilience and motivation likely to influence this relationship.
Significance of the Study
Undertaking this study is important because it will help examine the existing knowledge gap between job satisfaction and workplace resilience while assessing whether self-determined motivation mediates the relationship between job satisfaction and resilience. Jawaad et al. (2018) noted that different factors influence workplace resilience depending on the working environment and job characteristics. Therefore, there is no single set of universal application variables to all workplaces when determining factors that influence workplace resilience and job satisfaction (Kašpárková et al., 2018; Wang et al., 2017). Furthermore, this study hopes to provide evidence that self-determined motivation affects resilience. Gagné et al. (2015) and Jayaweera (2015) noted that the relationship between job satisfaction and workplace resilience remains complex because of the different variables that influence resilience and satisfaction. Zheng et al. (2018) noted that different individual employee preferences such as intrinsic and extrinsic variables, managerial factors, and organizational settings, mediate employee job satisfaction, and subsequent organizational commitment. There is a lack of definite factors that may help understand variables that mediate job satisfaction and workplace resilience. Researchers recommend additional research to explore potential mediating variables between job satisfaction and resilience (Gagné et al., 2015; Jayaweera, 2015; Zheng et al., 2018). Therefore, this study would be key in filling this knowledge gap where self-determined motivation likely to mediate the relationship between job satisfaction and workplace resilience among knowledge workers in the United States.
Purpose and Scope of the Study
The general purpose of this study is to investigate the impact of work satisfaction on workplace resilience mediated by self-determined motivation among knowledge workers in the United States in 2021. Therefore, the specific scope of the research is limited to the knowledge industry in the United States, including programmers, physicians, pharmacists, architects, engineers, scientists, design thinkers, public accountants, lawyers, academics, and any other white-collar workers whose job necessitates one to think for a living. The choice of knowledge workers was informed by recent trends of high employee attrition and absenteeism due to growing concerns of demotivated workers in this sector (Lu et al., 2020; Naifeh & Kearney, 2020). Also, the scope of examining the sector was informed by the scarcity of studies that have examined the mediating role that self-determined motivation has on work satisfaction and workplace resilience (Sarrasin et al., 2017; Zheng et al., 2017), especially within the knowledge sector.
Dependent, Independent, and Mediating Variables
Three key variables form the basis of this study. The variables include (a) work satisfaction, which is used as the independent variable, (b) workplace resilience, which is the dependent variable, and (c) self-determined motivation, which is the mediating variable. As a dependent variable, workplace resilience presents the variable that will be tested and measured in this study, and its change depends on the independent variable (work satisfaction). By contrast, work satisfaction presents the independent variable that is not influenced by the other variables that are being measured in this study (i.e. workplace resilience and self-determined motivation). Finally, self-determined motivation will be used as a mediating variable where it will be examined whether it links the independent and the dependent variables and whether its existence may help explain the relationship between the above two variables.
Research Questions
Four research questions were created to guide and explore the proposed study purpose. The research questions include the following:
RQ1: To what extent do greater levels of work satisfaction predict workplace resilience of knowledge workers in the United States?
RQ2: To what extent do greater levels of work satisfaction predict self-determined motivation in knowledge workers in the United States?
RQ3: To what extent do greater levels of self-determined motivation predict workplace resilience?
RQ4: To what extent do greater levels of self-determined motivation mediate the relationship between work satisfaction and workplace resilience among knowledge workers in the United States?
Figure 1
Model of Proposed Hypotheses

Note. This figure demonstrates the proposed model for the four hypotheses of this study.
Definition of Terms
Job Satisfaction
Devi and Rani (2016) defined job satisfaction as a positive emotional response employees experience when doing their jobs and a personal feeling of satisfaction on the job, which in turn motivates an employee to become more productive.
Knowledge Workers
Davenport (2005) defined knowledge workers as individuals who have to think for a living. These individuals in the workplace cultivate growth and creation, develop processes, and solve complex problems.
Motivation
Gagne et al. (2018) defined motivation as the level of engagement, performance, and well-being that employees show to their organization when executing tasks. Self-determination theory has two types of motivation: intrinsic and extrinsic. Intrinsic motivation is defined as a receiving gratification for a task that is intriguing for oneself. Whereas, extrinsic motivation is defined as receiving external gratification from a task completed (Gagne et al., 2010).
Self-determined Motivation
Self-determined motivation consists of two types of motivation, intrinsic motivation and identified regulation (Gagne et al., 2018). Intrinsic motivation refers to an individual’s satisfaction with an activity due to personal interests. Identified regulation is defined as one’s internalized “value and meaning” in an activity (Tremblay et al. 2009).
Work Satisfaction
Gagne et al. (2007) defined work satisfaction as one’s satisfaction with a specific job or career. Specifically, in this study, the scale used to measure one’s satisfaction with their work assesses an individual’s personal approval of their work tasks and encompassing happiness with their work.
Workplace Resilience
King et al. (2015) defined resilience as the ability of employees to adapt to changing circumstances even when such conditions are disruptive or discouraging. Workplace resilience will be measured using the 20-item Workplace Resilience Instrument (WRI) to identify four main factors that contribute to employees’ workplace resilience within the knowledge industry (Mallak & Yildiz, 2016). The first factor is active problem solving, which is an individual’s ability to approach a problem in a positive manner. The next factor is team efficacy, where an individual has the ability to work with all team members to achieve the overall team goal. The third factor is confident sense-making, which is an individual’s ability to make sense of chaos to create order. The ability to focus on the solution of a problem and not be distracted by uncontrollable issues. The final factor is bricolage which is defined as an individual’s ability to act quickly and swiftly in a high stress situation.  
CHAPTER II
Literature Review
Job Satisfaction
Over the decades, job satisfaction has attracted growing research interest among scholars and practitioners within organizations. Job satisfaction has been defined as the satisfying or positive emotional state resulting from the overall assessment of one’s job or job experiences (e.g., Locke, 1976; Shaffer and Harrison, 1998). Whereas, the concept of work satisfaction focuses on involvements and insights relating to one’s own work (Bussing et al., 1999). In fact, the two constructs appear to be vastly overlapping, and work satisfaction could be considered as a major component of job satisfaction (Arthur, Khapova, & Wilderom, 2005; Hall & Moss, 1998).
Various studies have attempted to determine factors that influence job satisfaction and its influence on employee productivity in organizations (Utami et al., 2016; Wang et al., 2019). For example, Wang et al. (2017) reported that job satisfaction increases employee creativity, commitment, and productivity within the healthcare industry. Utami et al. (2016) reported that job satisfaction influences employee motivation, loyalty, and desire to work towards organizational goals within the Indonesian power generation companies. Despite these findings, however, researchers indicate that there is no consensus that job satisfaction directly affects productivity.
Wang et al. (2019) noted that job satisfaction has an influence on employee productivity because individuals have the ability to be creative and innovative within the organization. Some of the important variables that may influence productivity include pay, motivation, management support, training, and skills development, feedback, and appreciation (Wang et al., 2019). Similar observations have been made by Yuen et al. (2018) in their study on determinants of employee performance and job satisfaction among seafarers. In their study, Yuen et al. (2018) surveyed 116 seafaring officers and their subordinates. Using structural equation modeling, the results revealed that job satisfaction is associated with the performance and productivity of seafaring workers. However, individual productivity was further influenced by the attractiveness of compensation and stress associated with working on board a ship.
Al-dalahmeh et al. (2018) set to explore the effect of engagement on employee performance within the information and technology (IT) sector through the mediating role of job satisfaction. A total of 429 IT employees from Jordanian banks and financial institutions participated in the study. Results revealed that organizational performance significantly impacts on IT employees (through dedication, absorption, and vigor), which in turn affected organizational performance. Moreover, results revealed that engagement positively and significantly impacted job satisfaction, with vigor having the most impact. However, job satisfaction had a partial mediation effect on the relationship between employee engagement and company performance. The findings emphasize possible need by Jordanian IT departments in the banking industry to facilitate engagement and satisfaction to improve organizational performance, a move that will yield positive outcomes for the banks. Similar observations by Putu and Rahyuda (2019) from 140 lecturers from Dhyana Pura University foundation showed that motivation through psychological empowerment had a mediating effect on job satisfaction and performance. However, the studies by Al-dalahmeh et al. (2018) and Putu and Rahyuda (2019) evaluated the possible mediation role of motivation on employee and organizational performance, thereby making it difficult to assess whether similar mediation exists between job performance and workplace resilience.
According to Abualrub et al. (2016), job satisfaction is associated with employee perception about their job and how well it helps them achieve or meet personal needs. In elaboration, Abualrub et al. (2016) conducted a study on the relationship between job satisfaction, work environment, and intent to stay. A total of 330 hospital nurses were invited to participate in the study. Results from the correlational analysis revealed a strong positive relationship between work environment and job satisfaction. Further, logistic regression analysis showed that receiving housing, high pay, and a supportive working environment contributed to job satisfaction, and subsequently informed the nurses’ intention to stay in their organizations. Therefore, insights by Abualrub et al. (2016), Wang et al. (2019), and Yuen et al. (2018) revealed that job satisfaction influenced employee productivity and it was influenced by different factors such as pay, work itself, working environment, management support, promotion opportunities, and interpersonal relationships.
Underwriting the above considerations, it becomes evident that although researchers have shown that job satisfaction may affect employee productivity and creativity, many constructs impact job satisfaction. Addae and Boso (2020) researched factors that influence job satisfaction, employee absence, and distributive justice among skilled workers in Ghana. A total of 298 employees working in the public and private sector were invited to participate in a survey questionnaire. Results from structural equation modeling revealed that perceived distributive justice (fairness, rewards, promotions) impacts employee job satisfaction, and subsequently affects employee absence or turnover intention (Addae & Boso, 2020). Moreover, Addae and Boso (2020) reported that turnover intention moderated the relationship between employee absence and job satisfaction.
The findings by Addae and Boso (2020) align with observations made by previous researchers in that the absence of job satisfaction contributes to reduced organizational commitment, poor performance, and lethargy among workers (Abualrub et al., 2016; Bojadjiev et al., 2015; Utami et al., 2016; Yuen et al., 2018). In elaboration, dissatisfied workers are more likely to quit their jobs, show low levels of creativity, and less likely to be productive. Even so, the literature reveals that job satisfaction varies from one employee to another even under similar workplaces and work conditions. As a result, the literature advocates a multidimensional approach to employee satisfaction focusing on addressing the challenging nature of work, work-life balance, regular appreciation, competitive pay and remuneration, and availing opportunities for individual career progression (Abualrub et al., 2016; Wang et al., 2019; Yuen et al., 2018).
Ćulibrk et al. (2018) conducted quantitative research to identify a possible relationship between job involvement, organizational commitment, work characteristics, and the mediation effect of job satisfaction. A sample size of 566 employees drawn from eight Serbian companies was invited to participate in survey questionnaires. Results showed that job involvement partially mediated job satisfaction in organizational commitment. Job satisfaction was influenced by work characteristics but not by organizational policies, which did not affect employee satisfaction (Ćulibrk et al., 2018)). However, the researchers did not examine whether the motivation of employees mediated the relationship between job satisfaction and employee commitment or resilience.
Gheitani et al. (2019) set to determine the impact of work ethics on organizational commitment and job satisfaction among employees of Bank Maskan, by assessing the possible mediating role of intrinsic motivation. In their empirical analysis, Gheitani, et al. (2019) collected survey responses from 220 employees. Results revealed a positive and significant relationship existed between work ethic, job satisfaction, and organizational commitment with intrinsic motivation mediation the relationship among variables. Also, a direct relationship was noted between work ethic in Bank Maskan and job satisfaction, although there was no direct or significant relationship between work ethic and organizational commitment. Intrinsic motivation was shown to play a partial mediatory role in the association between work ethic and job satisfaction, but a complete mediatory effect between work ethic and organizational commitment (Gheitani, et al., 2019). The findings of this study present important observations on the possible mediatory role that motivation has on organizational commitment and job satisfaction through work ethic. Additional research, however, is needed to explore the possible mediating role of motivation on the relationship between job satisfaction and resilience.
Jawaad et al. (2019) noted that job satisfaction and organizational commitment are largely influenced by multiple motivation factors. Specifically, motivation is an innate force whose different constructs serve to shape and maintain highly individualistic factors that may change from time to time, depending on the motives and needs of an employee. For instance, working environment characteristics may not have a causal connection with motivation but they impact the level of employee experience with motivation. Together, environment forces and innate forces inform employee satisfaction and resilience (Jawaad et al., 2019). Bratton and Gold (2017) shared that factors that contribute to job satisfaction also contribute to resilience and subsequently affect the motivation of workers in their organizations. The relationship between workplace resilience and job satisfaction is likely to be mediated by different motivation issues. Bratton and Gold (2017) indicated that the motivation considerations include intrinsic factors (e.g. feedback, recognition, praise, autonomy) and extrinsic factors (e.g. money, pay raises, bonuses, and benefits). Therefore, multiple motivation constructs may affect the relationship between job satisfaction and workplace resilience, although these motivation factors do not necessarily have the same mediating effect (Jawaad et al., 2019), or may not even have any mediating effect on this relationship (Bratton & Gold, 2017; Suleiman et al., 2017).
In addition, multiple theories and research support employee productivity and intent to stay when individuals are most satisfied with their line of work. An example, Locke’s Value theory states job satisfaction occurs when an individual’s requirements for a job are aligned with the job itself. In other words, when there is a disconnect between the individuals desires of the job and the actual job, this causes job dissatisfaction and lack productivity (Locke, 1976). Another theoretical model, job characteristics model (JCM) denotes that job satisfaction happens when the job environment “intrinsically motivates” employees, which aligns with the model of this study, self-determination theory (Hackman & Oldham, 1974; Gagne et al., 2007).
Gagne et al. (2007) scale, Satisfaction with Work is grounded in Gagne et al. (2017) self-determination theory (SDT). Self-determination theory is a multifaceted framework on human motivation within organizational behavior studies. Gagne et al. examined individuals are inclined to be more engaged and high performing when three “basic needs” are achieved; competent, autonomous, and related. These three needs are defined as such, when an individual is competent they feel empowered when faced with “challenges and demands.” Next when an individual has an awareness of freedom without control, they feel a sense of autonomy. The last need is the ability to have relationships that are beyond superficial and have an impact on both ends of the relationship.
Workplace Resilience
Workplace resilience is one of the core constructs associated with positive organizational behavior. Linnenluecke (2017) found that the extant literature on resilience is characterized by various uncertainties. For instance, the existing studies on resilience have different conceptualizations about resilience. As such, different studies have developed multiple theories, definitions, and understandings about resilience within organizations (Linnenluecke, 2017). Further, Linnenluecke (2017) indicated that available literature has not made a conceptual assessment of possible differences and similarities among different streams of literature on how resilience may be understood and implemented within organizations. Hartmann et al. (2019) also reported that the existing body of knowledge on resilience lacks a clear concept of how resilience develops and influences organizational or employee outcomes. Moreover, Kahn et al. (2018) emphasized the need for additional research to address the current resilience challenges resulting from conceptual inconsistencies.
Initial efforts to develop a clear conceptual framework on resilience reveal that resilience is impacted by factors such as career opportunities, motivation, autonomy, and self-efficacy (Fisher et al., 2018). Kahn et al. (2018) shared that employees who show high career resilience are more likely to engage in autonomous work, proactively embrace choices to improve their work, and positively impact on organizational changes. Hartmann et al. (2019) conducted a critical review of resilience within organizational teams and individuals. Results revealed that employees with high resilience engage in activities such as investing in career changes, collecting information about career opportunities, and identifying realistic action plans and goals to pursue (Hartmann et al., 2019). Resilient employees were less likely to leave their organization during times of risk and uncertainty. Moreover, resilient teams were more likely to identify their interests, weaknesses, and strengths in facilitating organizational performance (Kahn et al., 2018; Hartmann et al., 2019).
A study by Paul et al. (2016) set to fill this knowledge gap by assessing mediating factors that influence the relationship between organizational citizenship behavior and employee resilience. A sample of 345 employees drawn from the manufacturing sectors in Himachal Pradesh and Uttarakhand in India were invited to participate in the study. Survey questionnaires were used to collect relevant information and a model developed to test the formulated research hypotheses. Hierarchical multiple regression was used to test the hypotheses on the mediating effects of organizational commitment on organizational citizenship behavior and resilience. Results revealed there is a positive relationship between resilience and organizational citizenship behavior (Paul et al., 2016).
Findings further revealed that resilience influences organizational commitment among employees. The formulated research hypotheses were confirmed where an organizational commitment was noted to mediate the relationship between organizational citizenship behavior and resilience (Paul et al., 2016). The findings provide advancements for both resilience and employee behavior and provide direction to companies that desire to motivate and maintain positive employee performance and competitive market advantage. Employee outcomes may be enhanced through resilience training programs to facilitate long-term commitment. Findings from past studies support the notion that resilience may have a positive effect on employee behavior, attitudes, and performance thereby contributing to positive organizational citizenship behavior (Probst et al., 2017; Rosário et al., 2017; Sanei & Poursalimi, 2018). However, Paul et al. (2016) noted that few studies have attempted to examine the underlying mechanisms of employee resilience and organizational citizenship behavior and any possible mediating variables that may potentially influence this relationship.
Moreover, Weick’s sensemaking theory (1993), which was utilized to create the workplace resilience instrument, was grounded by two tragic events, The Mann Gulch fires (Weick, 1993) and the Tenerife plane crash (Weick, 1990). These events created the framework for sensemaking theory, which is defined as a thought process that invokes an individual to think and “make sense” of any given situation within a workplace. The theory aligns with the four factors within the workplace resilience instrument: active problem-solving, ability to work through issues in high stress situations; team efficacy, an individual is able to see the value in working in a team setting and drawing strengths from each team member; confident sense-making, is the ability to make quick and effective decisions in stressful situations; and bricolage, is when an individual can step back in a pressured situation to make an educated decision for any given situation in the workplace (Mallak & Yildiz, 2016). All four of the aforementioned factors encompass the theory of sensemaking, as required by a resilient individual to make quick and informed decisions in high stress situations within the workplace.
Tonkin et al. (2018) noted that resilience contributes to positive employee adaptation during uncertainty and adversity. Considering the modern adverse and disruptive work environment, scholars and practitioners have developed a keen interest in exploring the concept of workplace resilience and how it impacts employee productivity and organizational performance (Hartmann et al., 2019). To examine the existing body of literature on workplace resilience, a number of meta-analyses and systematic reviews have been conducted. For instance, Todt et al. (2018) reported that social support and resilience are key to mitigating the negative impacts of project terminations within the construction sector.
Quantitative research by Stoverink et al. (2018) on manufacturing sector employees revealed that building resilient teams contributed to successful problem solving and management of uncertain business environments. Shoss et al. (2018) conducted a case study on employee resilience during job insecurity. A cross-sectional survey using 1,071 university employees in the United States revealed that resilience mitigated negative consequences of job insecurity on interpersonal relationships and emotional exhaustion. As such, resilience was found to have a buffering effect on employees during times of job insecurity (Shoss et al., 2018). A review by Linnenluecke (2017) on past studies on resilience in business organizations revealed that resilience impacts employee commitment and success when exposed to pressure and heavy workloads.
Relationship Between Job Satisfaction and Workplace Resilience
Researchers have explored the potential relationship between job satisfaction and workplace resilience. Srivastava and Madan (2020) investigated the relationship between career satisfaction and resilience. The study was conducted in Delhi, India, focusing on 272 middle-level managers drawn from 10 private banks. Survey results showed that employees who have high resilience are more satisfied with their careers. Such employees were found to have better control over their daily tasks and duties, even during uncertain times. Srivastava and Madan (2020) concluded that resilience has a positive and significant relationship with job satisfaction. Study results indicated resilience accounted for 41% of the variance with job satisfaction and resilience. These results further revealed a strong relation between the two constructs, job satisfaction and resilience.
Kašpárková et al. (2018) examined the relationship between resilience and job satisfaction among knowledge workers in helping professions in Czech. A quantitative research approach was used with 360 knowledge workers taking part in the study. Results of this study through structural equation modeling, showed job satisfaction was not a mediator for workplace resilience and showed partial mediation by work engagement. On the other hand, levels of resilience and perceived job performance were positively related in knowledge workers in Czech. Uzonwanne and Nwanzu (2017) investigated employee satisfaction with pay and their subsequent commitment to stay in their organizations. A total of 225 bank leaders from the southwest and northern Nigeria were invited to participate in the study. Results from multiple regression analyses indicated that employee satisfaction with pay increased their job commitment and intention to stay within their current workplaces.
Ghandi et al. (2017) explored the relationship between job satisfaction, resilience, turnover intention, and stress among counselors. Path analysis was used to examine this relationship using survey responses obtained from 207 counselors at Shahriar-based learning institutions. Results revealed that resilience had a positive, direct, and significant impact on job satisfaction. By contrast, resilience had a negative, significant effect on job stress. Furthermore, job satisfaction was reported to have a significant negative impact on employee turnover intention, while job stress was noted to have a direct and significant impact on turnover intention (Ghandi et al., 2017). Job stress and job satisfaction were noted to mediate the relationship between resiliency and turnover.
Haar and Staniland (2016) surveyed 191 Maori employees to examine how resilience influences individual career satisfaction. Further, the researchers investigated the moderating effects and direct impacts of workplace collectivism in their organizations. Results from structural equation modeling showed that there was a strong support for the measurement model where resilience is a strong predictor of job satisfaction among Maori workers. Collectivism had a significant impact on resilience where employees who report high levels of collectivism also reported high levels of career satisfaction, but low levels of resilience. The findings show that resilient employees tend to show adaptive behavior especially in areas of morale, social functioning, and somatic health (Haar & Staniland, 2016).
Varshney and Varshney (2017) investigated the effect of resilience on job satisfaction and performance among construction managers in Saudi Arabia. Researchers surveyed 126 managers in the Saudi Arabia construction sector. Results revealed that resilience mediates the relationship between performance and job satisfaction. Resilient employees were found to persist in their work even during the turbulent business environment. Also, resilient workers were noted to adapt to change and help formulate solutions to the most challenging problems in the industry. High resilience contributes to individual workplace motivation where employees are able to bounce back after disappointments and steadily move towards their objectives. Varshney and Varshney (2017) noted that resilient employees tend to be highly satisfied with their jobs, demonstrate high capacity building skills, effective team communication, and maintain their energy during stressful working circumstances.
Underwriting the above considerations, it becomes elaborate that there is a direct relationship between job satisfaction and resilience. Bedi and Bedi (2017) pointed out that workers with high resilience demonstrate high psychological health and better control over their work compared to persons with lower resilience. Ghandi et al. (2017) added that resilience contributes to high productivity and better efficiency. During difficult times, resilient workers are better prepared and highly likely to be satisfied with changing working conditions. Haar & Staniland (2016) recommended managers and organizations to be responsive to the strong relationship between career satisfaction and resilience by creating employee assistance programs focused on enhancing their resilience. Zheng et al. (2017) shared that workers have resilience potential that may be developed over time through training and, in turn, contributes to improved job satisfaction and well-being. Haar & Staniland (2016) and Ghandi et al. (2017) added that high resilient workers show better health outcomes and self-esteem when working, resulting in better productivity and higher efficiency.
Zheng et al. (2017) shared that job satisfaction is one of the main factors that contribute to high turnover rates among healthcare workers. Considering the high stressing environment in the mental health sector, job satisfaction is key to reducing attrition and absenteeism among nurses. Zheng et al. (2017) noted that resilience plays an important role in facilitating healthcare workers’ adaptation to stressful workplaces and may serve as a factor that influences job satisfaction. Therefore, Zheng et al. (2017) attempted to investigate influencing factors of job satisfaction among nurses within the psychiatric department in Singapore and the possible relationship between job satisfaction and resilience. A survey questionnaire was used to collect demographic data, resilience, and job satisfaction information from 874 nurses. Results from correlation analysis showed a positive and significant relationship between job satisfaction and workplace resilience. Zheng et al. (2017) noted that psychiatric nurses who are satisfied with their jobs are more likely to be resilient, less likely to quit, and persist in delivering knowledge even during stressing working conditions. Based on the above literature insights, it can be concluded that job satisfaction has a positive relationship with resilience. Therefore, this study will examine the relationship between work satisfaction and workplace resilience.
H1: Work Satisfaction will have a positive effect on knowledge workers’ workplace
Resilience.
Motivation
To understand motivation, studies have used different theories in examining and assessing how workers might best be supported to be motivated in their jobs (Latham et al., 2016; Swann et al., 2020). The main theories used in motivation include biological-based theory, goal-setting theory, and self-determination theory. The biological-based theory of motivation, also called the Intuition Theory postulates that motivation is regulated by neural pattern recognition events (Locke & Latham, 2019). Under motivation, the theory argues that it is not the nature of adversity that is essential, but how workers deal with potential uncertainty. The goal-setting theory states that specific and challenging goals, in addition to feedback contribute to better and higher task performance. Goals give and indicate the direction to employees to remain focused and determined. Goal setting focuses on principles of clarity, challenge, commitment, feedback, task complexity, self-efficiency, and goal commitment (Locke & Latham, 2019; Latham et al., 2016; Swann et al., 2020).
Self-determination theory postulates that individuals are motivated to grow and change by three universal and innate psychological needs (Wu et al., 2020). That is, individuals, become self-determined when their needs for autonomy, connection, and competence are fulfilled. The self-determination theory was used in this study and has been widely applied in various organizational contexts. For example, Tsai et al. (2021) applied self-determination theory to examine how athletes may be influenced to be more resilient in sporting events. Wu et al. (2020) used self-determination theory to examine the motivation for joining gang groups, offending, and continued persistence in remaining in these groups. Baluku et al. (2020) used self-determination theory to examine employee resilience and continued commitment to their workplaces, compared self-employed and salaried workers.
Furthermore, the study SDT argues Self-determination theory is grounded in two types of motivation, intrinsic and extrinsic motivation. Intrinsic motivation is defined as an individual’s satisfaction with an activity due personal interests. Extrinsic motivation is when one’s satisfaction is derived from external factors, such as negative or positive “rewards and punishments” (Gagne et al, 2010). However, extrinsic motivation can also be influenced by internal factors. Therefore, extrinsic motivation has a spectrum with four regulations, external regulations, introjected regulation, identified regulation, and integrated regulation. First external regulations, which is when an individuals does a task to receive positive accolades and avoid negative outcomes. Introjected regulation is the next on the spectrum, which is when an individual is motivated to complete a task to please others rather than one self. Subsequently, identified regulation is when one is motivated to complete a task because it is personally enticing and not influenced by others. Lastly, integrated regulation is when an individual goes above and beyond expectations for a task, because they are motivated internally. SDT covers all facets of an individual’s motivation to work within organizations. In this study, the use of self-motivation theory will be key to understand how workplace satisfaction is likely to impact workplace resilience and identify possible self-determined motivation factors likely to inform individual resilience.
Motivation plays an important role in facilitating employee performance and positive engagement within the organization. Ullah et al. (2020) shared that proactive personality and organizational support positively impact one’s motivation and commitment to their workplace. Motivated employees feel more involved and actively engaged within their organizations than demotivated workers. According to Mahmoud et al. (2020), motivation is of two types: extrinsic and intrinsic. On the one hand, intrinsic motivation means that an employee is driven from within through feedback, praise, promotion, and recognition. On the other hand, extrinsic motivation means that stimulation occurs from external factors such as awards, pay, bonuses, and other tangible feedback (Budnicket al., 2020; Mahmoud et al., 2020; Ullah et al., 2020).
Survey findings by Gautam and Basnet (2020) from 150 faculties based on hierarchical regression showed that trust and training affect work motivation and employee commitment to organizational performance. Moreover, Gautam and Basnet (2020) reported that motivation mediates the relationship between organizational culture (social cohesion, communication, and job challenge) and skills training. As a result, employee motivation is central to workplace performance and productivity. Budnick et al., (2020) pointed out the different reasons why employee motivation is crucial. For instance, motivation allows top management to work towards the objectives and goals of their companies. Failure to have in place a motivated workplace would result in reduced performance and competitiveness and reduced productivity. Motivated employees become creative and formulate solutions to achieve higher output for their organizations (Budnick et al., 2020).
Chien et al. (2020) elaborated that perceived lack of motivation at the workplace may subject companies to risky positions. Having a motivated workforce is highly beneficial to companies in terms of increased employee commitment, continued employee development, improved efficiency, and overall worker satisfaction that impacts on positive growth. In general, the primary focus of human resources is to ensure motivated employees considering the positive association between motivation and building employee morale and productivity (Gupta, 2020; Nawaz et al., 2018). Reizer et al. (2019) further stressed that a successful organization prioritizes employee motivation to ensure organizational and job satisfaction. The concept is in line with Fredrick Herzberg's two-factor theory, which states that there are a set of factors within an organization that contributes to job satisfaction and others that cause dissatisfaction (Herzberg, 1987; Nawaz et al., 2018).
Lorincová et al. (2019) reported that in line with Herzberg's two-factor theory, motivation creates a quality of work-life and improves internal condition among workers. In addition, hygiene or external motivation increases employee satisfaction with their work. If employees are adequately motivated, they are more likely to be satisfied with their work and this will contribute positively to their productivity. As such, these factors may be considered intrinsic motivation as they are associated with employees' desire to learn or act to achieve set obligations. Motivation triggers the willingness and interest of workers who see the value of activities executed within the organization such as financial growth, market competition, and reduced costs of operations.
Islam et al. (2020) investigated the relationship between job satisfaction, motivation factors, and employee commitment within a low-cost airline organization. Researchers used quantitative research and collected data using survey questionnaires from 400 employees from a low-cost company. Stepwise multiple regression analysis was conducted to explore the relationship between different variables and the association between motivation, job satisfaction, and organizational commitment. Results showed that intrinsic motivation is positively associated with job satisfaction where most influencing factors of this relationship included responsibility, advancement, nature of work, and recognition (Islam et al., 2020). Moreover, researchers found that extrinsic motivation through job security, administration, company policy, working conditions, supervision, and salary impacts on motivation and subsequent employee satisfaction (Islam et al., 2020). These findings emphasize the need for organizations to adopt strategies to enhance employee motivation to improve performance and long-term positive working relationships while reducing attrition and costs related to hiring and training new employees.
Suifan (2019) explored how work motivation mediates job satisfaction and work environmental factors. Researchers used survey questionnaires to collect data from 295 Jordanian commercial bank workers. Results showed that work motivation had a significant positive mediation effect on work environmental factors and job satisfaction. However, the findings of this study do not help in understanding the possible mediation effect of motivation on job satisfaction and workplace resilience.
Sanei and Poursalimi (2018) assessed the mediating effect of job satisfaction on the relationship between motivation, support, training, and perceived organizational commitment. Survey data from 159 participants from a city municipality at Sabzevar city were used in structural equation modeling. Results showed that motivation had a positive and significant effect on employee commitment through training and perceived support. Moreover, job satisfaction had a positive and significant effect on normative commitment and employee continuance in an organization. Motivation had a positive effect on perceived commitment with a mediating impact on job satisfaction. That is, more motivation through training and perceived support contributes to higher job satisfaction, which in turn results in normative commitment and employee commitment. These findings reveal that intrinsic motivation factors such as organizational support and career advancement opportunities may have a mediating role on job satisfaction and workplace resilience.
Fernet et al. (2015) explored possible mediating effects by transformational leadership and job characteristics on the relationship between motivation and employee functioning. Results showed job demand mediates between transformational leadership and both commitment and burnout. Manalo et al. (2019) examined the mediating role of job satisfaction on the relationship between work engagement and organizational commitment among private secondary school teachers. The motivation was noted to have a direct positive effect on work engagement and organizational commitment, without the mediating effect of job satisfaction. The presence of job satisfaction as a mediating variable reduced the effect of motivation on work engagement and organizational commitment. The findings showed job satisfaction significantly mediates the motivation of employee work engagement and organizational commitment. Oh et al. (2017) also shared that job satisfaction mediates the relationship between selection and recruitment, work environment, and training. Similar mediation effect of job satisfaction on employee resilience and productivity in the Turkish banking and telecommunication sectors have also been reported by Seckin-Celik and Çoban (2016), while Wang et al. (2017) found similar results among health-care staff in township health centers in rural China.
In summation, findings from the surveyed literature show that researchers have attempted to examine the potential impact of job satisfaction and motivation on employees in different knowledge sectors. However, insights from past literature show there is a potential knowledge gap when establishing possible relationships among these variables. Although various studies have attempted to examine how motivation impacts job satisfaction, there is no consensus on specific factors that are likely to explain the relationship between job satisfaction and workplace resilience. Available studies often explore individual intrinsic motivation or extrinsic motivation factors and assess their impact on organizational commitment or employee productivity (Ali et al., 2017; Wilson, 2015). In terms of the mediating variable, most studies have largely examined job satisfaction and its mediation effect on work commitment, organization performance, resilience, and employee behavior. Thus, there is a need to further understand whether work satisfaction effects self-determined motivation.
H2: Work Satisfaction will have a positive effect on knowledge workers’ self-determined motivation
Motivation and Workplace Resilience
A growing body of literature has also indicated that employee motivation informs their resilience and persistency in their organizations. Cantante-Rodrigues et al. (2021) investigated possible associations between employee motivation, performance, and resilience. The primary objective was to assess the possible association between the three constructs. Quantitative research was used where data was collected using survey questionnaires from 249 professional employees. Correlation analysis showed a positive relationship between work engagement and resilience, but a negative relationship between demotivation (e.g., due to burnout and poor work engagement) and resilience. Cantante-Rodrigues et al. (2021) also noted that while work engagement was positively and significantly (p < 0.05) related to performance, burnout negatively affected performance resulting in job dissatisfaction and subsequent job turnover (i.e., low workplace resilience).
A quantitative study by Aziz et al. (2018) examined the association between motivation and resilience. The researchers focused on the constructs of the emotional labor motivation and job resilience due to burnout (i.e., personal accomplishment, depersonalization, and emotional exhaustion). Survey questionnaires were used to collect data from 416 working professionals. Results showed that low emotional wellbeing was positively correlated to depersonalization and emotional exhaustion, thereby resulting in low workplace resilience. However, high emotional well-being contributed positively to personal accomplishment, thereby enhancing workplace resilience among professional employees (Aziz et al., 2018).
Lopes and Chambel (2017) used self-determination theory to examine the impact of autonomous motivations on employee resilience at the workplace in terms of interest and enthusiasm during task execution. A total of 196 temporary agency workers participated in the survey. Results showed that autonomous motivations influenced increased work engagement among workers. However, autonomous motivation did not contribute to increased enthusiasm towards task execution. Instead, external motivation from manager feedback and support influences work commitment and task completion (Lopes & Chambel, 2017). These findings further echo observations by Aziz et al. (2018) and Cantante-Rodrigues et al. (2021) on the potential relationship that might exist between motivation and workplace resilience.
Further, a recent study by Zhang et al. (2020) also conducted a cross-sectional study on job satisfaction, work engagement, and resilience. A quantitative study was undertaken where data from 2693 doctors were collected. Results showed that doctors who are poorly motivated or were dissatisfied in their jobs were more likely to show high voluntary turnover, implying low workplace resilience. Thus, lack of job satisfaction has a direct negative effect on turnover and work engagement. In turn, work engagement has an indirect effect on job attrition through work resilience (Zhang et al., 2020). These findings further support past studies such as Aziz et al. (2018) and Lopes and Chambel (2017) regarding the direct positive relationship between motivation and workplace resilience. Therefore, self-determined motivation among employees is likely to have a direct influence on individual resilience within their organization. In the light of these findings, it may be postulated that:
H3: Self-determined motivation will have a positive effect on workplace resilience.
The Effect of Motivation on Work Satisfaction and Resilience
Past studies have attempted to investigate the potential relationship between motivation and employee productivity or organizational performance. However, a review of past literature focuses on different motivation constructs such as pay, feedback, career growth opportunities, and remuneration on job satisfaction and employee resilience (Ahluwalia & Preet, 2017; Budnick et al., 2020). According to Chien et al. (2020), different motivational factors (intrinsic and extrinsic) affect job satisfaction and subsequently contribute to workplace commitment. As such, motivation may direct some behavior towards job satisfaction and workplace resilience. Gagné et al. (2015) reported that motivated employees who are offered career advancements, skills development, and competitive pay, are satisfied with their jobs, have long-term loyalty, or continued to stay with the organization.
Nonetheless, other researchers have observed that intrinsic motivation factors such as feedback and praise largely contribute to job satisfaction and resilience than extrinsic motivation factors. According to Gautam and Basnet (2020), recognition and job promotion largely motivates healthcare workers to continue working in their companies due to individual satisfaction related to the feeling of being appreciated and having a sense of belonging to their company. Gupta (2020) added that fair job evaluation and career development opportunities affect both job satisfaction and subsequent commitment to stay among workers in the airline and hotel industries. Findings by Gautam and Basnet (2020) and Gupta (2020) cautioned that extrinsic motivation factors such as pay and wages may have a positive impact on job satisfaction, but would not necessarily contribute to workplace resilience. For instance, Gautam and Basnet (2020) reported that high pay may help employees meet most of their individual material needs, thereby contributing to job satisfaction. On the contrary, however, having competitive pay and working in a stressful environment where there is no top management support or fairness may demotivate employees and inform their decision for voluntary turnover, thereby negatively impacting on resilience or commitment to stay.
Islam et al. (2020) showed that intrinsic and extrinsic motivation may have different impacts on employee motivation and continued to stay in low-cost airline companies. Job satisfaction and continued resilience are more likely to be informed by working conditions and organizational factors than by material needs. In this case, intrinsic motivation largely informs individual job commitment then preceded by extrinsic motivation or material considerations. Pancasila et al. (2020) conducted a study on job satisfaction and employee willingness to stay in their organizations in Indonesia. The study was to examine how work motivation is influenced by leadership and its implication on employee commitment and performance. A total of 355 participants from a coal mining company in Indonesia participated in the study through survey questionnaires. Results from structural equation modeling revealed that work motivation is influenced by leadership style, and in turn influences job satisfaction, employee performance, and commitment to stay. In terms of employee commitment, Pancasila et al. (2020) noted that leadership (in terms of receiving support, feedback, praise, recognition) had a substantial influence on job satisfaction than compensation. The effect size of leadership on job satisfaction was 0.263 compared to the effect size of compensation, which was 0.171. In terms of job performance or willingness to stay, leadership had an effect size of 0.175 compared to compensation 0.166. Therefore, leadership characteristics were noted to have a dominant influence on job satisfaction and employee loyalty than material compensation alone (Pancasilaet al., 2020).
Reizer et al. (2019) reported that if employee performance is excellent, they are likely to show continued commitment in their workplace where the company growth will continue to be experienced. Performance is often high when workers have the necessary skills and receives fair compensation. Ahluwalia and Preet (2017) shared that the motivation of employees serves to encourage the individual working spirit and willingness to contribute to organizational growth through their innovativeness. According to Budnick et al. (2020), if workers feel motivated, then they are likely to show high satisfaction in their work and execute tasks enthusiastically, thereby contributing to improved organizational performance. However, Chien et al. (2020) pointed out that some empirical findings provide inconsistent results where career motivation alone may not contribute to job satisfaction and organizational commitment. Similar observations by Aksoy et al. (2018) showed that there is a strong positive correlation between intrinsic motivation and job satisfaction, but not between extrinsic motivation and job satisfaction. These conflicting observations in the literature show there may be potential confounding motivation factors (extrinsic and intrinsic) that mediate the relationship between work satisfaction and workplace resilience, thereby necessitating the need for the current study. Through the above literature, there is a need to examine the below hypothesis,
H4: Work satisfaction has a positive effect on the workplace resilience of knowledge
workers through the mediating effect of self-determined motivation.
 
Chapter III
Methodology
The purpose of this quantitative, survey research study is to investigate the relationship between job satisfaction and workplace resilience and examine whether self-determined motivation mediates this relationship. In the current methodology chapter, strategies, and methods that will be used to identify participants and collect relevant data are presented. Specifically, the chapter discusses the following issues: (a) participants, (b) research design, (c) survey instruments, (d) data collection procedures, and (e) proposed data analysis methods. These aspects are further detailed in the subsequent sections.
Participants
The population of research interest in this study will be limited to employees within the knowledge sector located in the United States. Specifically, the study sample will include, but not limited to employees working in the tourism sector, restaurants, supermarkets, customer support knowledges, hotels, banking, and financial institutions. The focus on the knowledge sector was informed by growing concerns about high attrition, voluntary turnover, and job dissatisfaction among workers in this sector (Behravesh et al., 2019; Foley, 2020; Hammond et al., 2018). Amako (2020) reported high turnover rates among employees prompting the need to investigate how job disaffection contributes to high voluntary turnover and employee absenteeism in the knowledge industry in the United States. According to the U.S. Bureau of Labor Statistics (2020), the knowledge industry employed more than 45 million people in 2019. In the United States, there are more than 9.7 million workers within the knowledge industry (U.S. Bureau of Labor Statistics, 2020). Some of the major sectors include hotels, accounting, tourism, teaching, and tourism. Therefore, the study population will be limited to the estimated 9.7 million workers within the knowledge industry in the United States.
However, since it is not possible to survey all the 9.7 million employees within the knowledge industry, a representative sample will be selected to participate in the study. A convenience sample that will be recruited into the study will include subordinate employees, managers, assistant managers, and other skilled employees drawn from different knowledge sector industries. All participants will be at least 18 years of age with a specific focus on workers who have at least 3 months of work experience in their current organization. In this case, the assumption is that employees or managers who have more than 3 months of work experience in their respective jobs have become aware about the extent to which they are satisfied or motivated at work.
Design
The current section presents the research design proposed for the current study. The specific focus of this section is to detail the type of design to be used, the data collection strategy, and the sampling strategy. The section further presents the operational definitions of the independent and dependent variables and how they will be measures.
Research Design
The quantitative research method will be used in this study where empirical data will be collected using Qualtrics Online Survey Platform, which will be retrieved through MTurk. Creswell (2017) shared that quantitative research enables researchers to collect relevant numerical data for a correlational study to establish important trends and statistics between independent and dependent variables. Quantitative data further enables researchers to test the hypothesis on the relationship between variables and determine any potential mediators in the topic being studied (Creswell, 2017; Davies, 2020). In this study, the independent variable is work satisfaction, the dependent variable is workplace resilience, while the mediator is self-determined motivation. Specifically, the decision to use quantitative research method in the current research study will be fundamental in exploring major trends on how work satisfaction impacts workplace resilience mediated by self-determined motivation.
The choice to use quantitative research design in this study is informed by its potential strengths to the research process. According to Creswell (2017), quantitative research enables the researcher to use a large sample size. As such, the obtained results are largely generalizable to other study settings, unlike qualitative research where the use of a small sample size limits the generalizability of the findings. Ghauri et al. (2020) further elaborated that quantitative research ensures the objectivity of the collected information since the researchers detach themselves during the data collection process. Thus, a researcher has little influence on how participants respond to the survey items further eliminating subjective bias in the final results (Ghauri et al., 2020). Mat et al. (2020) noted that since quantitative research uses a standard survey questionnaire, future researchers can replicate the same research and compare similar findings.
Nonetheless, despite the advantages of using quantitative research, there are potential limitations that need to be taken into consideration. For instance, Creswell (2017) cautioned that unlike qualitative data, results from surveys are limited to numerical descriptions. That is, quantitative findings lack detailed narratives and fail to provide elaborate accounts of human perceptions towards the topic in terms of feelings, personal opinions, and individual thoughts. Bryman (2016) noted that using closed-ended questionnaires limits participants in sharing additional information on the topic. In other cases, information shared through close-ended survey questions may not necessarily reflect the exact opinion of participants on the phenomenon under study, but only the closest match of their expressions (Creswell, 2014; Davies, 2020). As identified by Buchanan and Hvizdak (2009), developing standard survey questions might lead to false representation and structural bias where the results reflect the views of researchers than those of the participating subjects.
Operational Definitions of the Variables
The variables used in this include work satisfaction which is used as the independent variable, workplace resilience which is the dependent variable, and motivation which is the mediating variable. The operational definition of work satisfaction in this study refers to the positive emotional response employees experience when doing their work and a personal feeling of satisfaction with the job or career (Gagne et al., 2007). Workplace resilience is defined as the ability of employees to adapt to changing circumstances even when such situations are disruptive or discouraging (King et al., 2015). Finally, motivation refers to the two types of self-determined profiles, which are self-determined (intrinsic motivation and identified regulation) and non self-determined (introjected regulation and extrinsic motivation) (Gagne et al., 2007).
Sampling Strategy
Survey questions will be prepared using the Qualtrics Online Survey Platform. Before collecting survey data, participants will be asked for informed consent that would have been approved by the Institution Review Board (IRB). The informed consent page will include an option to either continue or exit the survey. An informed consent form will (Appendix A) detail the aim and research purpose of this study. Thereafter, participants will be asked to answer all inclusion criteria (Appendix B) to ensure only qualified participants enroll in the study. Qualified participants will access the study through MTurk using a survey code that is created by the researcher. Each survey session will last between 15-25 minutes. Upon completing the survey questionnaire, the participants will be asked to submit the completed responses by clicking on the ‘submit’ button.
To recruit participants into the study, convenience sampling, a non-probability sampling technique, will be used (Etikan, 2016). The use of the convenience sampling technique is informed by the need to meet the pre-established participant selection criteria. That is, all participants must be located within the United States of America, have at least 3 months of working experience in their current organizations or job positions, and are employed within the knowledge industry. Etikan (2016) noted that convenience sampling makes it easier to make generalizations about the recruited sample and recruitment of participants who have relevant qualifications, skills, and knowledge on the phenomenon under study. Therefore, using convenience sampling in this study was key to identifying pre-determined participants with specific characteristics such as currently working in the knowledge sector industry such as customer support employees, schools, tourism sector, restaurants, supermarkets, hotels, banking, and financial institutions.
Power Analysis
To determine an appropriate sample size that will be invited to participate in this study, GPower analysis was performed. Power analysis is commonly used in study design to identify the needed sample size of a population to infer findings from the sample to the population (Faul et al., 2009). The size of the sample in this study was derived using the population data of 9.7 million workers within the knowledge industry in the United States. Using this population value, sample-size tables from Verma and Verma (2020) indicated that the size of the sample should be N = 385 for any population greater than 100,000. Using the GPower sample-size calculator resulted in a sample size of N = 385, with a response distribution of 50%, at a 95% confidence level, and with a 5% margin of error.
The 95% significance level is based on the assumption that if the findings will likely indicate a statistically significant difference, then the researcher can be 95% confident in the observed results not being caused by randomness, thus rejecting the null hypothesis. G*Power indicated a sample size of N = 312 at a power level of 0.95 (α = .05) with an effect size of f2 = .05. Based on these values, the target sample size for this study will be N = 350. The additional 38 participants will account for potential outliers that may be found. The key difference, in this case, is that the effect size used in the calculation was at the larger end of the numbers reported by Faul et al. (2009).
Measuring Independent and Dependent Variables
Work satisfaction will be measured using the 5-item Satisfaction with Work Scale (SWWS) to identify the important factors that inform employee satisfaction within the knowledge industry. Motivation will be measured using the 12-item Motivation at Work Scale (MAWS) to identify self-determined motivation that mediates the relationship between job satisfaction and workplace resilience. By contrast, workplace resilience will be measured using the 20-item Workplace Resilience Instrument (WRI) to identify main factors that contribute to employees’ workplace resilience within the knowledge industry.
Instruments
The current section outlines the survey instruments that will be used in the data collection process. Three survey instruments will be used in this study to measure job satisfaction, self-determined motivation, and workplace resilience all based on the Likert Scale rating scale. The instruments include the Satisfaction with Work Scale (SWWS) developed by Gagne et al. (2007), the Motivation at Work Scale (MAWS) developed by Gagne et al. (2010), and Workplace Resilience Instrument (WRI) developed by Mallak and Yildiz (2016).
Satisfaction with Work Scale. The Satisfaction with Work Scale (SWWS) consists of 5 survey items and will be used to measure work satisfaction (Appendix C). The SWWS is grounded on the self-determination theory, which is thoroughly reviewed in a previous chapter. The SWWS measures responses from participants based on a seven-point Likert scale, strongly agree to strongly disagree. Some of the items included in the SWWS include “The conditions under which I do my work are excellent?” and “I am satisfied with the type of work I do?”. Permission to use the SWWS was granted by the author. The scale was selected for this study because of its brevity and proven internal reliability (.75) and test-retest reliability (.77, p < .001) (Gagne et al., 2007). The scale was validated using four samples, 220 employees from various organizations, 103 retirees from a non-profit, 167 dental equipment manufacturing company, and 2267 Canadian transportation employees. A confirmatory factor analysis (CFA) with maximum likelihood was conducted on the above four sample. The CFA exhibited a one-factor structure with some correlated errors (chi-square(5) = 833.37, p < .001, NNFI = .54, CFI = .77, AGFI = .65, RMSEA = .25). However, this model yielded a poor fit, therefore the researchers, ran a lagrange multiplier (LM) tests, where the results significantly improved the fit (chi-square(3) = 10.32, p < .05, NNFI = .99, CFI = .998, AGFI = .99, RMSEA = .03) (Gagne et al., 2007). The SWWS is easy to score as it involves adding the item scores to get a total score. The cut off scores are, 31-35, extremely satisfied; 26-30, satisfied; 21-25, slightly satisfied, 20, neutral, 15-19, slightly dissatisfied; 10-14, dissatisfied; 5-9, extremely dissatisfied.
The Motivation at Work Scale. The self-determined motivation will be measured using the 12-item Motivation at Work Scale (MAWS) instrument developed by Gagne et al. (2010) (Appendix D). The MAWS instrument will ask participants to indicate their level of disagreement to each of the 12 statements using Likert scale scoring ranging from 1 (not at all) to 7 (exactly). MASWS is constructed based on self-determination theory and consists of 12 items that can be divided into four subscales. The subscales correspond to the four types of motivations postulated by the self-determination theory namely intrinsic motivation (IM), identified regulation (IDEN), introjected regulation (INTRO), and extrinsic motivation (EXT). To obtain the score for the Motivation at Work Scale, the researcher had to review the Work Extrinsic and Intrinsic Motivation Scale (WEIS) developed by Tremblay et al., 2009). The MAWS score can be calculated “by multiplying the mean of each subscale by weights corresponding to the underlying level of self-determination” (Ryan & Connell, 1989). The formula for determining the MAWS is as follows: MAWS = (+3 x IM) + (+1 x IDEN) + (-1 x INTRO) + (-2 x EXT). A positive score indicates a self-determined profile and a negative score suggests a non-self-determined profile. In terms of construct validity, MAWS has internal consistency values of α = .89 (IM), α = .83 (IDEN), α = .75 (INTRO), and α= .69 (EXT) for self-determined and non-self-determined motivation, respectively. Therefore, the scale is suitable for assessing motivation in the current study.
Work Resilience Instrument. Workplace resilience will be measured using the 20-item WRI instrument developed by Mallak and Yildiz (2016) (Appendix E). The WRI measures individual resilience in the workplace and it consists of four factors. The four factors serve to identify different dimensions of workplace resilience including team efficacy, active problem solving, confident sense-making, and bricolage. Each of the four factors shows internal consistency and validity of between α = 0.77 and α = 0.83 and with omega values ranging .77-.84 (Mallak & Yildiz, 2016). Active problem-solving focuses on the intention to do something positive as opposed to remaining inactive hoping the problem will go away. Team efficacy emphasizes the ability of employees to work with teams and understand how teams need to operate to achieve organizational goals. Confident sense-making denotes the ability to extract order from chaos, while bricolage focuses on being resilient to changing tasks and risks at work (Mallak & Yildiz, 2016).
The WRI scale will be measured on a 5-point liker scale (1 = Not true at all, 5 = True nearly all the time). The WRI is scored across four factors: Active Problem-Solving, Team Efficacy, Confident Sense-Making, and Bricolage. The Active Problem-Solving is scored by summing the scores from items 1-3 and divide by 3. The Team Efficacy is scored from items 4-7 and divided by 4. The Confident Sense-Making is scored from items 8-14 and divided by 7, while the Bricolage is scored by summing scores from items 15-20 and divided by 6. Some of the key survey items on the WRI scale include “I take delight in solving difficult problems”, “I try to make sense of the situation when it becomes chaotic,” and “I exercise creativity when under extreme pressure”.
Demographic Characteristics. Demographic characteristics are collected for potential inferential and descriptive data analysis. The expected demographic characteristics of the participants will include diverse individuals in terms of gender, age, race/ethnicity, education level, occupations, and work experience (Appendix F). In terms of age, the participants will include persons at least 18 years of age while the gender will include male, female, nonbinary gender, participants although other participants may choose not to share their gender (APA, 2015). Additional characteristics will include a generalizable and inclusive group participants from different ethnic groups including Caucasians, Black or African Americans, Hispanics or Latino, and other minority groups such as Native American Indians, Asians, and Pacific Islanders or Native Hawaiian, and Alaska Natives. The education level of the participants is expected to range from high school, college, undergraduate, and postgraduate degree holders. Besides, the occupation of the participants is expected to range from teachers, customer support providers, accountants, financiers, organizational leaders, and managers in different knowledge sectors. Finally, in terms of years of work experience, the expected results will include persons with more than 3 months of work experience up to 30 or 40 years of experience. The demographic questionnaire will be administered after the instruments to reduce any potential bias that can occur from self-reporting data (Rosenman et al., 2011). Additionally, respondents can be open and honest with their survey responses without the risk of judgement based on demographics. To maintain data confidentiality and ensure participant anonymity, the researcher will avoid collecting personal details such as names, places of work, and place of residence (Creswell, 2017).
Procedures
The current procedure section details how participants will be contacted and recruited, briefed as to the purpose of the study, and protected for all human rights as research participants. The section also examines how participants will be tracked and measured and compensated for participating in this study through the Amazon Mechanical Turk. Further, the section details debriefing that participants will receive at the completion of the study.
Contacting and Recruiting Participants. The 312 participants will be recruited through Amazon Mechanical Turk (MTurk). The MTurk is a crowdsourcing marketplace that enables researchers to outsource survey questionnaires to collect relevant data on the topic under study. The motivation to use the MTURK in sample recruitment is informed by the ongoing pandemic of 2020 coronavirus disease (COVID-19) (Binder, 2020). Using MTurk ensures there is reduced physical contact and social distancing in maintained to align with the ministry of health guidelines on reducing the risk of COVID-19 transmission (Binder, 2020). Recent studies have also used MTurk to collect survey questionnaires and reported the technique to be suitable in social science research. For instance, Lee et al. (2020) used MTurk to collect survey data on anxiety and fear resulting from the COVID-19 pandemic among patients and care providers. Conway et al. (2020) also used MTurk to collect correlational data on why conservatives were less concerned about the COVID-19 than liberals.
Underwriting the above considerations, the use of MTurk in participant recruitment is deemed suitable and will aid in the collection of relevant quantitative data for this study. Creswell (2017) shared that data collection through online platforms has advantages over face-to-face or paper-and-pencil interviews. For instance, online data collection is cost and time effective because fewer resources are needed in the data collection process. Besides, online surveys enable research to collect a large amount of information from multiple participants within a short duration compared to the face-to-face data collection process (Creswell, 2017). However, online surveys have some limitations in that they may exclude potential participants who do not have internet access or are located in remote areas.
Briefed as to the Purpose of the Study. Before participating in the study, participants will be asked to review the informed consent form (Bryman, 2016). The informed consent form attached to the survey will brief the participants about the aim and purpose of the study. Participants will also be assured about their rights and privacy throughout the research process. Specifically, participants will be informed that taking part in this study is voluntary and that anyone is free to drop from this study at any time without any negative repercussions (Creswell, 2017). Moreover, no element of coercion or deception will be used to recruit or extract data from the participants. Upon consenting to participate in the study, participants will then be allowed to proceed with the rest of the survey questionnaire. Participants who complete the screening questionnaire, are deemed eligible for the study, and complete the survey without skipping items will receive two dollars. This compensation coverts to seven dollars and twenty-five cents for an hourly pay rate, which is higher than the average earnings of MTurk workers through the platform (Hara et al., 2017). Participants will be paid through MTurk, however, the researcher has seven days to review the participants responses and deem them as valid responses for the study. The researcher has attention check questions in each survey, to ensure participants are thoroughly reading each question and answers.
Protection of Human Rights. Some important ethical issues that emerge from this study include IRB approval, informed consent, participant privacy, and data confidentiality. The use of human subjects in this study necessitates the need to obtain IRB approval before conducting the data collection process. Suitable IRB approval will be obtained from the institution conducting this study to ensure participants are protected against emotional, psychological, and physical harm (Creswell, 2014). Moreover, informed consent will be sought from the study subjects where they will be made aware of their rights in participating in this study. Participants will be informed that taking part in the current research is voluntary and that anyone can leave at any time without negative consequences (Ghauri et al., 2020). No deception or coercion will be used in tricking participants to share data (Creswell, 2014).
Proposed Data Analysis
Descriptive statistics will be used to examine participant demographic characteristics, frequency, percentage, means, and standard deviation. The demographic characteristics will include age, gender, education level, race/ethnicity, occupation, socio-economic status, and years of work experience. Boxplot and the scatterplot will be used to detect outliers and identify missing data. Outliers will also be identified using run charts, lag plots (a type of scatter plot), and line charts. Potential outliers will be removed during post-test analysis or the collected data will be trimmed to exclude as many outliers as possible. To make valid inferences from regression analysis, the residuals of the regression will be assumed to follow a normal distribution.
Psychometric Analysis
Over the years, researchers have reviewed the effects of common method variance (CMV) and how to control the effects of the variance. Tehseen et al. (2017) investigated how to control and test for common method variance in organizational research. The study shared that if the instruments for the independent and dependent measures are from different studies, ensure participant anonymity, have an item to measure participants attention (an example, question 4 is an attention check question. It is not a part of the original measurement.), and the order of how measurements are administered (independent variable, mediator, and dependent variable), then researchers can control for CMV. Past studies that accounted for the steps above have been able to control CMV in their organizational research (Rodriguez-Ardura & Meseguer-Artola, 2020; Conway& Lance, 2010). Those steps have also been taken for this study to ensure common method variance is controlled for when measuring job satisfaction, workplace resilience, and self-determined motivation.
A confirmatory factor analysis (CFA) is a multivariate statistical procedure that will be conducted on each scale (SWWS,WRI, and MAWS) to obtain valuable information regarding the fit of the data to the theory derived model (Brown, 2006). This analysis will also Moreover, the researcher will measure the internal consistency of the study through Cronbach’s Alpha. This study will be collecting data through multiple Likert question surveys, therefore there is a need to conducted this reliability test.
Tests of Statistical Assumptions
All analyses used to test the study’s hypotheses will be based on a regression analysis model, which is associated with five main assumptions. These include, linearity, multicollinearity, independence, homoscedasticity, and normality. These assumptions are discussed further in the following section.
Linearity. The first assumption of Multiple Regression is that the relationship between the independent (IV) and the dependent (DV) variables can be characterized by a straight line. Researchers assess this relationship by producing scatterplots of the relationship between the IV and the DV. Looking at the scatterplot produced by SPSS, once can see that the relationship between the IV and the DV could be modelled by a straight line, which could suggest that the relationship between these variables is linear.
Multicollinearity. Multicollinearity will be checked in two ways: by checking the variance inflation factor (VIF) and correlation coefficient values. To check multicollinearity, correlation coefficients will be used to check a correlation matrix and look for coefficients with magnitudes of .80 or higher. If the predictors are multicollinear, they will be strongly correlated.
Independence. This test observes whether the individual data points are independent from one another (or uncorrelated). We can test this assumption using the Durbin-Watson statistic. The Durbin-Watson will always have a value in the range of zero and 4.0. If the value is from zero to 2.0, that that indicates a positive autocorrelation. If the value is 2.0, than there is no autocorrelation, and if the value is from 2.0 to 4.0, that that indicates a negative autocorrelation (Kenton, 2019).
Homoscedasticity. The next assumption will be checking for homoscedasticity using the scatterplot of the residuals on the normal P-P plot in the output data. If the data is not homoscedastic, there will be a very tight distribution to the left of the scatterplot and a very wide distribution to the right of the plot. Drawing a line around the data would look like a cone. Confounding will be determined by comparing the estimated measure of the association before and after adjusting for confounding. That is, the measure of association both before and after adjusting for a potential confounding factor will be computed.
Normality. The values of the residuals are normally distributed. This assumption can be tested by looking at the distribution of residuals. Researchers assess this by checking the Normal probability plot option.
Hypothesis Testing
To examine the four hypotheses in this study, the researcher will use multiple regression analysis and SPSS PROCESS to analyze the mediating role of motivation on work satisfaction and workplace resilience. (Baron & Kenny, 1968; Hayes, 2018). Inferential statistics will be used in testing the formulated hypotheses and also in assessing whether there is any correlation between independent and dependent variables. First, Pearson’s correlation will be used to determine whether there is any relationship between work satisfaction and workplace resilience. Pearson’s correlation will be used because it is the most applied measure of correlation when assessing the degree of linear relationships between independent variables and dependent variables (Creswell, 2017). Second, multiple regression analysis will be used to examine the constructs that influence the relationship between self-determined motivation and workplace resilience. Before undertaking the regression analysis, the appropriateness of the regression will be analyzed to ensure there is no violation of assumptions of multicollinearity, outliers, and normality. The multi-regression analysis will be used to test predictive significance between independent and dependent variables. Moreover, hypotheses testing will be performed using a test statistic vial one-sample t-test, where p-values less than 0.05 (p ≤ 0.05) will be considered significant.
Finally, Hayes (2018) PROCESS will be used to analyze the mediating role of motivation on work satisfaction and workplace resilience. The analysis will be conducted in SPSS by selecting PROCESS, with the dataset open. Thereafter, the PROCESS dialog box will open, where the researcher will select and move the IV (work satisfaction), the DV (workplace resilience), and the mediator (self-determined motivation) into the corresponding boxes in SPSS. In order to ensure the mediation effect is tested, model number 4 has to be selected. A bootstrapping procedure will be performed to calculate the standard errors and confidence intervals (OLS/ML confidence intervals). Additionally, to further examine the effect of a mediating variable, four options will have to be selected (, Effect size, Sobel test, Total effect model, and Compare indirect effects) (Hayes, 2018). The results of these tests will determine the significance or lack of significance for each hypothesis.

Potential Study Implications

Explain the potential theoretical implication of your study. Also identify potential implication for organizations and managers.
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Preliminary Suppositions and Implications
Just because you don't have to actually conduct the study and analyze the results, doesn't mean you can skip talking about the analytical process and potential implications. The purpose of this section is to argue how and in what ways you believe your research will refine, revise, or extend existing knowledge in the subject area under investigation. Depending on the aims and objectives of your study, describe how the anticipated results will impact future scholarly research, theory, practice, forms of interventions, or policymaking. Note that such discussions may have either substantive [a potential new policy], theoretical [a potential new understanding], or methodological [a potential new way of analyzing] significance.

When thinking about the potential implications of your study, ask the following questions:
• What might the results mean in regards to challenging the theoretical framework and underlying assumptions that support the study?
• What suggestions for subsequent research could arise from the potential outcomes of the study?
• What will the results mean to practitioners in the natural settings of their workplace?
• Will the results influence programs, methods, and/or forms of intervention?
• How might the results contribute to the solution of social, economic, or other types of problems?
• Will the results influence policy decisions?
• In what way do individuals or groups benefit should your study be pursued?
• What will be improved or changed as a result of the proposed research?
• How will the results of the study be implemented and what innovations or transformative insights could emerge from the process of implementation?
NOTE: This section should not delve into idle speculation, opinion, or be formulated on the basis of unclear evidence. The purpose is to reflect upon gaps or understudied areas of the current literature and describe how your proposed research contributes to a new understanding of the research problem should the study be implemented as designed.

Sample Solution