The Causal Relationship Between Job Characteristics, Organizational Support, Stress and Performance
Bibliographic record
Abstract
Job stress is a common occurrence and of the utmost concern for management (Avey, Luthans, & Jensen, 2009). Canadian employees report workplace stress as a primary cause of mental health concerns which can subsequently impact workplace productivity and job performance (Mental Health Commission of Canada, 2019). In addition, the novel Coronavirus has had several negative consequences on people including for example the forced closure of work which has resulted in financial, social and health-related problems in part due to the consequences of stress (Brooks et al., 2020; Hossain, Sultana, & Purohit, 2020; Probst, Humer, Stippl, & Pieh, 2020; Sharma et al., 2020). Sports organizations are their employees are certainly not immune to the deleterious effects of stress (c.f., MacIntosh & Burton, 2019). Consequently, one of the management considerations to attenuate for stress is known as job characteristics (c.f., Hackman & Oldham, 1976). Hackman and Oldham (1976) developed the job characteristics theory, which can be used to understand the relationship between job characteristics, job design with various outcomes of interests such as performance. They suggested five characteristics of the job (i.e., skill variety, task identity, task significance, autonomy, and feedback) that influenced personal and work-related outcomes (Hackman & Oldham, 1976). Research has shown that when employees are faced with stressful conditions and high job demands, moral and economic support from the organization is needed (Krishnan & Mary, 2012). Organizational support theory (OST) proposes that employees form a general perception and belief concerning how the organizational management values their contributions and cares about their well-being (Eisenberger et al., 1986; Rhoades & Eisenberger, 2002). According to OST, such perceptions could have considerable effects on work outcomes (Eisenberger & Stinglhamber, 2011; Rhoades & Eisenberger, 2002), employees’ work attitudes and behaviors including feelings of stress (Kurtessis et al., 2015). The purpose of this study was to investigate the causal relationship between job characteristics, perceived organizational support, job stress, and job performance. This research was conducted on the employees within the sports sectors in Canada (N = 146) during the Covid-19 pandemic. Using a structural equation model (SEM), this study describes the relationships which exist based upon validated existing measures, specifically: Job Characteristics questionnaires (Morgeson & Humphrey, 2006), Perceived Organizational Support (SPOS) short version questionnaire (Eisenberger, Cummings, Armeli, & Lynch, 1997), Job Stress Scale (Parker & DeCotiis, 1983) and Williams and Anderson’s job performance questionnaire (Williams & Anderson, 1991). The results of the study confirm that job characteristics components can decrease overall job stress and improve job performance amongst sports employees even during a pandemic. Moreover, there is a significant impact between the level of organizational support and job stress. Specifically, when organizational support increases, job stress will be reduced. This study contributes to the extant sport management literature within organizational behavior and provides an account of the importance for management to take a person-centered approach, particularly during high-stress times such as the Covid-19 Pandemic.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".