Person-Job Cognitive Style Fit for Software Developers: The Effect on Strain and Performance
01 Nov 2005-Journal of Management Information Systems (M. E. Sharpe, Inc.)-Vol. 22, Iss: 2, pp 193-226
TL;DR: This paper examines the fit between the preferred cognitive style of a software developer and his or her perception of the cognitive style required by the job environment, and the effect of that fit on stress/strain and performance.
Abstract: Software developers face a constant barrage of innovations designed to improve the development environment. Yet stress/strain among software developers has been steadily increasing and is at an all-time high, while their productivity is often questioned. Why, if these innovations are meant to improve the environment, are developers more stressed and less productive than they should be? Using a combination of cognitive style and person-environment fit theories as the theoretical lens, this study examines one potential source of stress/strain and productivity impediment among software developers. Specifically, this paper examines the fit between the preferred cognitive style of a software developer and his or her perception of the cognitive style required by the job environment, and the effect of that fit on stress/strain and performance. Data collected from a field study of 123 (object-oriented) software developers suggest that performance decreases and stress increases as this gap between cognitive styles becomes wider. Using surface response methodology, the precise fit relationship is modeled. The interaction of the developer and the environment provides explanatory power above and beyond either of the factors separately, suggesting that studies examining strain and performance of developers should explicitly consider and measure the cognitive style fit between the software developer and the software development environment. In practice, managers can use the results to help recognize misfit, its consequences, and the appropriate interventions (such as training or person/task matching).
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TL;DR: The research model proposes that certain technology characteristics--like usability, usefulness, complexity, and reliability, intrusiveness, and dynamism--are related to stressors (work overload, role ambiguity, invasion of privacy, work-home conflict, and job insecurity), whereas intrusive technology characteristics are found to be the dominant predictors of stressors.
Abstract: With the proliferation and ubiquity of information and communication technologies (ICTs), it is becoming imperative for individuals to constantly engage with these technologies in order to get work accomplished. Academic literature, popular press, and anecdotal evidence suggest that ICTs are responsible for increased stress levels in individuals (known as technostress). However, despite the influence of stress on health costs and productivity, it is not very clear which characteristics of ICTs create stress. We draw from IS and stress research to build and test a model of technostress. The person-environment fit model is used as a theoretical lens. The research model proposes that certain technology characteristics--like usability (usefulness, complexity, and reliability), intrusiveness (presenteeism, anonymity), and dynamism (pace of change)--are related to stressors (work overload, role ambiguity, invasion of privacy, work-home conflict, and job insecurity). Field data from 661 working professionals was obtained and analyzed. The results clearly suggest the prevalence of technostress and the hypotheses from the model are generally supported. Work overload and role ambiguity are found to be the two most dominant stressors, whereas intrusive technology characteristics are found to be the dominant predictors of stressors. The results open up new avenues for research by highlighting the incidence of technostress in organizations and possible interventions to alleviate it.
1,167 citations
TL;DR: In this paper, the effects of stress created by information and computer technology (ICT)-that is, "technostress"-on role stress and on individual productivity were explored based on empirical survey data.
Abstract: Based on empirical survey data, this paper uses concepts from sociotechnical theory and role theory to explore the effects of stress created by information and computer technology (ICT)-that is, "technostress"-on role stress and on individual productivity. We first explain different ways in which ICTs can create stress in users and identify factors that create technostress. We next propose three hypotheses: (1) technostress is inversely related to individual productivity, (2) role stress is inversely related to individual productivity, and (3) technostress is directly related to role stress. We then use structural equation modeling on survey data from ICT users in 223 organizations to test the hypotheses. The results show support for them. Theoretically, the paper contributes in three ways. First, the different dimensions of technostress identified here add to existing concepts on stress experienced by individuals in organizations. Second, by showing that technostress inversely affects productivity, the paper reinforces that failure to manage the effects of ICT-induced stress can offset expected increases in productivity. Third, validation of the positive relationship between technostress and role stress adds a new conceptual thread to literature analyzing the relationship between technology and organizational roles and structure. In the practical domain, the paper proposes a diagnostic tool to evaluate the extent to which technostress is present in an organization and suggests that the adverse effects of technostress can be partly countered by strategies that reduce role conflict and role overload.
855 citations
TL;DR: There are knowledge gaps in the research area of behavioral software engineering and that earlier research has been focused on a few concepts, which have been applied to a limited number of software engineering areas, according to the result.
230 citations
TL;DR: A review of cognitive styles research in business and management can be found in this paper, where the authors identify valid and reliable methods of assessment of cognitive style for use in business settings and draw a number of conclusions regarding the current state of Cognitive styles research and promising directions for future research.
Abstract: In line with increased attention on the application of cognitive approaches to industrial, work and organizational psychology, the last 40 years have witnessed a growing interest in application of the cognitive style construct to the field of business and management. The purpose of this paper is threefold. First, we wish to advance understanding of cognitive styles research by elucidating trends and perspectives related to business and management. Second, we identify gaps in the literature and promising areas of research that can be further developed. This is accomplished by means of a review of papers published between 1969 and 2009. Eight themes emerged from our analysis: (a) vocational and occupational issues; (b) national culture; (c) teamwork and interpersonal relationships; (d) learning; (e) decision making; (f) creativity, innovation and entrepreneurship; (g) sales and marketing; and (h) management information systems, information management and use. Third, we identify valid and reliable methods of assessment of cognitive style for use in business and management settings. Finally we draw a number of conclusions regarding the current state of cognitive styles research and promising directions for future research.
220 citations
Cites background from "Person-Job Cognitive Style Fit for ..."
...Gaps between an individual’s style and workgroup cognitive climate were associated with communication problems (Kirton and McCarthy 1985), conflict and stress (Kettelhut and Schkade 1991), decreased performance levels (Chilton et al. 2005) and lower levels of job satisfaction (Brigham et al. 2007)....
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References
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"Person-Job Cognitive Style Fit for ..." refers background in this paper
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Abstract: Chapter 1: Overview General Perspectives on Measurement Historical Origins of Measurement in Social Science Later Developments in Measurement The Role of Measurement in the Social Sciences Summary and Preview Chapter 2: Understanding the "Latent Variable" Constructs Versus Measures Latent Variable as the Presumed Cause of Item Values Path Diagrams Further Elaboration of the Measurement Model Parallel "Tests" Alternative Models Exercises Chapter 3: Reliability Continuous Versus Dichotomous Items Internal Consistency Relability Based on Correlations Between Scale Scores Generalizability Theory Summary and Exercises Chapter 4: Validity Content Validity Criterion-related Validity Construct Validity What About Face Validity? Exercises Chapter 5: Guidelines in Scale Development Step 1: Determine Clearly What it Is You Want to Measure Step 2: Generate an Item Pool Step 3: Determine the Format for Measurement Step 4: Have Initial Item Pool Reviewed by Experts Step 5: Consider Inclusion of Validation Items Step 6: Administer Items to a Development Sample Step 7: Evaluate the Items Step 8: Optimize Scale Length Exercises Chapter 6: Factor Analysis Overview of Factor Analysis Conceptual Description of Factor Analysis Interpreting Factors Principal Components vs Common Factors Confirmatory Factor Analysis Using Factor Analysis in Scale Development Sample Size Conclusion Chapter 7: An Overview of Item Response Theory Item Difficulty Item Discrimination False Positives Item Characteristic Curves Complexities of IRT When to Use IRT Conclusions Chapter 8: Measurement in the Broader Research Context Before the Scale Development After the Scale Administration Final Thoughts References Index About the Author
11,710 citations
Book•
05 Jun 1991
TL;DR: Measurement in the Broader Research Context Before the Scale Development After the Scale Administration Final Thoughts References Index about the Author.
Abstract: Chapter 1: Overview General Perspectives on Measurement Historical Origins of Measurement in Social Science Later Developments in Measurement The Role of Measurement in the Social Sciences Summary and Preview Chapter 2: Understanding the "Latent Variable" Constructs Versus Measures Latent Variable as the Presumed Cause of Item Values Path Diagrams Further Elaboration of the Measurement Model Parallel "Tests" Alternative Models Exercises Chapter 3: Reliability Continuous Versus Dichotomous Items Internal Consistency Relability Based on Correlations Between Scale Scores Generalizability Theory Summary and Exercises Chapter 4: Validity Content Validity Criterion-related Validity Construct Validity What About Face Validity? Exercises Chapter 5: Guidelines in Scale Development Step 1: Determine Clearly What it Is You Want to Measure Step 2: Generate an Item Pool Step 3: Determine the Format for Measurement Step 4: Have Initial Item Pool Reviewed by Experts Step 5: Consider Inclusion of Validation Items Step 6: Administer Items to a Development Sample Step 7: Evaluate the Items Step 8: Optimize Scale Length Exercises Chapter 6: Factor Analysis Overview of Factor Analysis Conceptual Description of Factor Analysis Interpreting Factors Principal Components vs Common Factors Confirmatory Factor Analysis Using Factor Analysis in Scale Development Sample Size Conclusion Chapter 7: An Overview of Item Response Theory Item Difficulty Item Discrimination False Positives Item Characteristic Curves Complexities of IRT When to Use IRT Conclusions Chapter 8: Measurement in the Broader Research Context Before the Scale Development After the Scale Administration Final Thoughts References Index About the Author
10,722 citations
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...8 are considered acceptable, all scales demonstrate high reliability [31, 104, 105, 108]....
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10,664 citations