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Richard L. Griffith, Tom Chmielowski and Yukiko Yoshita
The purpose of this article is to empirically test whether applicants fake their responses to personality based employment inventories.
Abstract
Purpose
The purpose of this article is to empirically test whether applicants fake their responses to personality based employment inventories.
Design/methodology/approach
This study utilized a within subjects design to asses whether applicants elevated their scores in an applicant conditions. Subjects who applied for a job were later contacted and asked to complete the same personality measure under an honest instructional set. The within subjects design allowed the researcher to examine faking behavior at the individual level of analysis rather than draw inferences between applicant and incumbent groups.
Findings
Results suggest that a significant number of applicants do fake personality based selection measures. Depending on the confidence interval used between 30 and 50 percent of applicants elevated their scores when applying for a job. The results also show that applicant faking behavior resulted in significant rank ordering changes that impacted hiring decisions.
Research limitations/implications
One limitation of the study is the exclusion of a job performance criterion measure. Without this measure definitive statements regarding the decay in the criterion validity of the measure cannot be made. While the study demonstrated rank ordering changes, decrements in criterion validity cannot be demonstrated without measuring job performance.
Practical implications
The practical implications of the paper are that personality measures should not be used alone. Rather they should be included in a test battery of measures that are less susceptible to faking behavior. In addition, applied researchers must continue research efforts to address the faking issue.
Originality/value
Empirical research has supported the notion that respondents can fake when instructed, however, other research has suggested that applicants do not fake in applied settings. This study is the first to provide substantial evidence that faking does occur in applicant settings and that is disrupts rank ordering of applicants.
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Koorosh Gharehbaghi, Kerry McManus, Kathryn Robson, Chris Eves and Matt Myers
The purpose of this paper is to review the Fuzzy Markov development for assessing the structural integrity of buried transportation bridges. In doing so, the appropriateness of…
Abstract
Purpose
The purpose of this paper is to review the Fuzzy Markov development for assessing the structural integrity of buried transportation bridges. In doing so, the appropriateness of Fuzzy Markov will be assessed, leading to the subsequent model.
Design/methodology/approach
This research will utilize the Fuzzy Markov techniques as the conceptual framework. Such methodology is further supported via the utilization and evaluation of 30 buried transportation bridges using the developed Fuzzy Markov model.
Findings
Subsequently, through a developed Fuzzy Markov model, this research found that as the basis of structural resilience, specific matrices for age-dependent transition probability can be compiled using conditional survival probabilities in the various structural states; as the basis of structural integrity, specific environmental and economic schemes can also be established based on inspection intervals, intervention systems and failure phases; exact inspection and maintenance intervals can be scheduled to further prolong an asset’s life; and clear and early warning signs can also be formulated for immediate intervention when the structural integrity of the asset are indeed compromised.
Originality/value
The gap within the literature currently surrounds the limitation of computational analysis for some buried structures such as bridges. Specifically, to streamline such evaluation and regimes, a Fuzzy Markov is developed and reviewed.
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Monika Saini, Drishty Goyal, Ashish Kumar and Rajkumar Bhimgonda Patil
The demand of sewage treatment plants is increasing day by day, especially in the countries like India. Biological and chemical unit of such sewage treatment plants are critical…
Abstract
Purpose
The demand of sewage treatment plants is increasing day by day, especially in the countries like India. Biological and chemical unit of such sewage treatment plants are critical and needs to be designed and developed to achieve desired level of reliability, maintainability and availability.
Design/methodology/approach
This paper investigates and optimizes the availability of biological and chemical unit of a sewage treatment plant. A novel mathematical model for this unit is developed using the Markovian birth-death process. A set of Chapman–Kolmogorov differential equations are derived for the model and a generalized solution is discovered using soft computing techniques namely genetic algorithm (GA) and particle swarm optimization (PSO).
Findings
Nature-inspired optimization techniques results of availability function depicted that PSO outperforms GA. The optimum value of the availability of biological and chemical processing unit is 0.9324 corresponding to population size 100, the number of evolutions 300, mutation 0.6 and crossover 0.85 achieved using GA while PSO results reflect that optimum achieved availability is 0.936240 after 45 iterations. Finally, it is revealed that PSO outperforms than GA.
Research limitations/implications
This paper investigates and optimizes the availability of biological and chemical units of a sewage treatment plant. A novel mathematical model for this unit is developed using the Markovian birth-death process.
Originality/value
Availability model of biological and chemical units of a sewage treatment is developed using field failure data and judgments collected from the experts. Furthermore, availability of the system has been optimized to achieve desired level of reliability and maintainability.
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Godson A. Tetteh, Kwasi Amoako-Gyampah and Amoako Kwarteng
Several research studies on Lean Six Sigma (LSS) have been done using the survey methodology. However, the use of surveys often relies on the measurement of variables, which…
Abstract
Purpose
Several research studies on Lean Six Sigma (LSS) have been done using the survey methodology. However, the use of surveys often relies on the measurement of variables, which cannot be directly observed, with attendant measurement errors. The purpose of this study is to develop a methodological framework consisting of a combination of four tools for identifying and assessing measurement error during survey research.
Design/methodology/approach
This paper evaluated the viability of the framework through an experimental study on the assessment of project management success in a developing country environment. The research design combined a control group, pretest and post-test measurements with structural equation modeling that enabled the assessment of differences between honest and fake survey responses. This paper tested for common method variance (CMV) using the chi-square test for the difference between unconstrained and fully constrained models.
Findings
The CMV results confirmed that there was significant shared variance among the different measures allowing us to distinguish between trait and faking responses and ascertain how much of the observed process measurement is because of measurement system variation as opposed to variation arising from the study’s constructs.
Research limitations/implications
The study was conducted in one country, and hence, the results may not be generalizable.
Originality/value
Measurement error during survey research, if not properly addressed, can lead to incorrect conclusions that can harm theory development. It can also lead to inappropriate recommendations for practicing managers. This study provides findings from a framework developed and assessed in a LSS project environment for identifying faking responses. This paper provides a robust framework consisting of four tools that provide guidelines on distinguishing between fake and trait responses. This tool should be of great value to researchers.
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The purpose of this paper is to critically evaluate university leadership performance using the Lean Six Sigma (LSS) framework. University leadership performance management (PM…
Abstract
Purpose
The purpose of this paper is to critically evaluate university leadership performance using the Lean Six Sigma (LSS) framework. University leadership performance management (PM) framework incorporates strategy formulation, lecturers, administrative services and the learning outcomes to achieve service quality excellence.
Design/methodology/approach
A theoretical investigation in literature was accomplished comparing PM and LSS frameworks. Through extant literature review, the authors identified five constructs (lecturers, administration staff, projects, programs and facilities) being offered by a university to evaluate the service quality excellence. Using these constructs, a student exit survey was conducted yielding a response rate of 56%. Five hypotheses were tested. The survey results evaluated reliability, convergent validity and discriminant validity of the constructs and were found to be satisfactory. To test the model fit and hypotheses between the constructs, the authors used structural equation modelling (SEM).
Findings
The LSS framework was found to be effective when compared with the PM framework, and for aligning university processes to achieve service quality excellence. The SEM result shows that there is a strong evidence to support the hypothesized model where facilities, projects and program had significant relationship with service quality excellence. The empirical evidence strongly supports that there is a relationship between the PM and the LSS frameworks.
Research limitations/implications
This research is based on a cross-sectional exit survey; future research could explore a longitudinal survey with treatment conditions to consider different genre of university leadership.
Practical implications
To achieve service quality excellence, university leadership will need to embrace LSS framework to satisfy their stakeholders. This could bring multifold organizational and social benefits.
Originality/value
Not too many studies have used the PM and the LSS framework to evaluate university leadership performance in terms of service quality excellence. This study identified constructs associated with LSS and empirically validated the scales to build on theory.
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Pawel Korzynski, Caroline Rook, Elizabeth Florent Treacy and Manfred Kets de Vries
The authors investigated how personality traits are associated with workplace technostress (perception of stressors related to the use of information and communication…
Abstract
Purpose
The authors investigated how personality traits are associated with workplace technostress (perception of stressors related to the use of information and communication technologies (ICTs).
Design/methodology/approach
The authors collected 95 self-rated and 336 observer-rated questionnaires using the personality audit and a shortened version of the technostress scale. To analyze relationships between personality dimensions and technostress, the authors applied partial least squares structural equation modeling (PLS-SEM).
Findings
This study shows that in line with previous studies, self-esteem is negatively related to levels of technostress. Contrary to our expectations, conscientiousness is positively related to technostress. Finally, the gap between a person's self-ratings and observer ratings in all personality dimensions is positively associated with technostress.
Practical implications
The authors showed that the experience of technostress varies significantly amongst individuals. By taking personality differences into account when allocating responsibilities and creating guidelines for ICT use at work, technostress could be addressed. Instead of setting organization-wide norms for availability and use, the authors suggest it would be more effective to acknowledge individual needs and preferences.
Originality/value
This study contributes to current technostress research by further examining antecedents and by focusing on the role of personality. In addition, the authors examined how differences in “self” and “observer” ratings of personality characteristics may point to variations in the way individuals experience technostress. The authors outlined concrete best practice guidelines for ICTs in organizations that take interindividual differences into account.
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Koorosh Gharehbaghi, Kerry McManus, Maged Georgy, Ken Farnes, Francesca Pagliara and Matt Myers
Through the significance matrix, this paper aims to investigate and explore the main sustainability factors of mega transportation infrastructure projects. Sydney’s Metro mega…
Abstract
Purpose
Through the significance matrix, this paper aims to investigate and explore the main sustainability factors of mega transportation infrastructure projects. Sydney’s Metro mega transportation infrastructure is used as a case study. Sydney’s Metro was selected because of its sustainability challenges faced because of the areas’ diverse ecological zones. Sydney’s Metro is thus examined as the basis of best practice for the determination of the sustainability factors of transportation infrastructures.
Design/methodology/approach
Using the significance matrix as a methodology, this research evaluates the environmental impact assessment and environmental assessment processes, to alleviate the problems of the mega transportation infrastructure.
Findings
This research found that a more comprehensive determination is needed to further analyse the sustainability factors of mega transportation infrastructures, use of a significance matrix would further assess the environmental complexities of mega transportation infrastructures and the sustainability factors of mega transportation infrastructures should include a nonlinear and asymmetrical scheme highlighting its components and carefully outlining its integration and consolidation.
Originality/value
Although there is concurrent research into sustainability factors of mega transportation, this paper undertakes a new methodology for such infrastructure. While the significance matrix is not a new concept, it has never been used specifically for mega transportation infrastructure. Subsequently, using the significance matrix as a methodology, this research undertakes such environmental analysis and assessment and thus produces a qualitative risk analysis matrix. The findings from this research will ultimately assist the key stakeholders of mega transportation infrastructures to better plan, monitor and support similar projects.