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The purpose of this research is to apply principles from the field of industrial and organizational psychology on organizational analysis and job analysis to better identify successful candidates for employment in an Information Commons.

Review of professional research, research from both library literature and industrial and organizational psychology, review of professional association surveys.

Library administration must invest time to articulate mission, value, and goals for the Information Commons before undertaking the organizational analysis. From the organizational analysis will flow the job analysis, job descriptions and hiring protocols.

Core concepts of organizational analysis and job analysis from the field of industrial and organizational psychology are pertinent and useful to library leaders in planning, implementing and staffing new service models, such as Information Commons.

The purpose of this empirical study is to identify the job tasks where decisions regarding social responsibility are likely to occur and assess the potential connections between social responsibility and professionalism.

A job study conducted by the Universal Public Procurement Certification Council (UPPCC) of 2,593 practitioners is used for data collection. Factor analysis is applied to a set of 75 procurement job tasks to determine the relationship between practitioners’ performance and management of job tasks and social responsibility variables.

The results suggest that there are specific job tasks performed and managed in both public and private sector procurement that share a unique relationship with social responsibility variables.

The manuscript advances the research on professionalism in procurement and administration through empirically testing job tasks performed and managed by practitioners and identifying relationships between job tasks according to a professional orientation toward social responsibility.

The study shows that specific job tasks are performed and managed in procurement and administration with a social responsibility consideration.

The technical nature of job tasks found to be related to social responsibility suggests a paradoxical view of the politics-administration dichotomy, and the notion that neutral tasks of both the public and private sectors are not void of a social function.

One attribute of professionalism in the literature, social responsibility, is operationalized through actual performance and management of job tasks by practitioners.

This paper aims to investigate emerging trends in data analytics and knowledge management (KM) job market by using the knowledge, skills and abilities (KSA) framework. The findings from the study provide insights into curriculum development and academic program design.

This study traced and retrieved job ads on LinkedIn to understand how data analytics and KM interplay in terms of job functions, knowledge, skills and abilities required for jobs, as well as career progression. Conducting content analysis using text analytics and multiple correspondence analysis, this paper extends the framework of KSA proposed by Cegielski and Jones‐Farmer to the field of data analytics and KM.

Using content analysis, the study analyzes the requisite KSA that connect analytics to KM from the job demand perspective. While Kruskal–Wallis tests assist in examining the relationships between different types of KSA and company’s characteristics, multiple correspondence analysis (MCA) aids in reducing dimensions and representing the KSA data points in two-dimensional space to identify potential associations between levels of categorical variables. The results from the Kruskal–Wallis tests indicate a significant relationship between job experience levels and KSA. The MCA diagrams illustrate key distinctions between hard and soft skills in data across different experience levels.

The practical implications of the study are two-fold. First, the extended KSA framework can guide KM professionals with their career planning toward data analytics. Second, the findings can inform academic institutions with regard to broadening and refining their data analytics or KM curricula.

This paper is one of the first studies to investigate the connection between data analytics and KM from the job demand perspective. It contributes to the ongoing discussion and provides insights into curriculum development and academic program design.

Reports on a case study on the design and development of two training courses for employees of gas and energy distribution companies in The Netherlands who were faced with internal and external changes. Discusses the conceptual framework of job analysis, developing a specific set of data collection techniques, particularly structured questionnaires and interviews. Concludes that each individual company should research and develop its own training course. The course should be designed to meet the company′s own peculiar requirements, there should be more professional co‐operation between industry and academe in research and training; and finally that training courses should be more widely based on the concept of job profiles, extending even to entire sectors of the economy.

The purpose of this paper is to estimate the strength of the relationship between job performance and intentions to quit (ITQ), identify moderators to this relationship, and calculate the direct and indirect effects that job performance has on ITQ and turnover.

Data from 65 studies (n=17,918) were meta‐analyzed to estimate the performance‐ITQ relationship. This overall sample was separated into subgroups for moderator analyses. Meta‐analytic path analysis was used to test the hypothesized model of turnover.

Supervisor ratings of performance had the strongest relationship with ITQ (ρ=−0.16), followed by self‐ratings (ρ=−0.14), and objective measures (ρ=−0.02). Employee nationality and job type also acted as moderators. Poor performers are more likely to quit even after controlling for job satisfaction and turnover intentions, indicating that they are more apt to engage in unplanned quitting. Good performers were slightly more likely to intend to quit after controlling for job satisfaction.

Limitations on the number and type of studies available prevented a test of how performance level acts as a moderator to the job performance‐turnover relationship and may cause some of the moderator analyses to be unstable.

The findings provide for a better understanding of how employees' job performance affects their turnover decisions and how organizations can control turnover.

This is the first meta‐analysis to estimate the relationship between performance and ITQ and to test a meta‐analytic path model of the job performance‐job satisfaction‐ITQ‐turnover relationships.

Proposes a new empirical approach to the classification of job families. This approach reflects an attempt to incorporate data on both the performance‐related human attributes and the nature of work or performance itself in developing a job‐classification system. Employees′ technical or functional skills and career histories form the basis of this rational taxonomy system. Demonstrates step‐by‐step, with the human resource data in a large, complex organization, how a useful taxonomy of job families may be derived from these two types of qualification‐related data.

Generation A individuals with Asperger's (high-functioning autism) might increase their chance that their skills fit with job requirements (person-job fit) by considering various nonacademic and popular lists of Asperger's-friendly jobs. Asperger's “celebrity” and professor Temple Grandin's list of 51 jobs was investigated using Asperger's-related job characteristics from the US Department of Labor's O*NET job description database. Using a factor analysis resulting in six Asperger's-related job characteristics, social orientation was the only factor that significantly predicted Grandin's judgment of what is an Asperger's-related job based on a binomial logistic regression analysis. Another analysis using O*NET data showed a wide variety of jobs that were most and least associated with each of the six factors. Study limitations and future research follow the analyses.

Requirements for business improvement professionals depend on different job characteristics. By focussing on lean management, the purpose of this paper is twofold: first, to provide a comprehensive conceptualisation of competencies relevant for lean professionals by comparing them to an existing project management competency framework; and second, to identify their similarities and differences in three different analysed countries.

This paper investigates 2,701 online published job advertisements in the USA, UK and Germany by means of a content analysis to compare and contrast the respective job profiles.

Main findings are similarities and differences in the specification and perception of lean professional’s roles among the three countries. Strikingly, four out of eight considered competency categories comprise 74 per cent of the profiles’ most relevant keywords. Additionally, with the help of a latent semantic analysis, 16 specific competencies can be summarised in a lean professional’s competency taxonomy.

The collected data only represent a snapshot of lean professionals’ advertisements. Also, text mining results from job profiles could largely differ from other techniques like recruiter interviews or company surveys. Further research could use different methods or combine them to construct a more complete model.

Lean education and training as well as the respective candidate selection processes can benefit from these studies’ results.

Requirements and job contents for lean professionals have not been empirically researched on a comparable in-depth level before, even though their expertise is in high demand in any kind of business sector.

So far, in this Vulcan series, I have described how the analytical movement brought about a clearer appreciation of the nature of physical skills. There are several distinct concepts. First comes the separation of job knowledge from the skills. Job knowledge consists mainly of comprehension — an understanding of certain basic principles, theories, properties of the materials being processed, knowledge of how to calculate cutting speeds and rates of feed and so on. Skill is the mastery of the performance which operates on the actual workpiece or process. Job knowledge, being a form of comprehension, implies that the mental activity is conscious. Skill, while at the early developmental stage consciously‐controlled, is not truly a skill until most of the activity is adapted to take place within the subconscious level. The early stages of skill training communicate performance consciously but the function of repetitive exercises is to turn this conscious activity into a subconscious activity. The second principle is that skill performance is a sensori‐motor activity: that the performer is processing sensory information coming in from the task and that he uses the sensory input to control the motor or doing activity in continuous feed‐back. The contribution of the skills analyst has been to explore more fully the nature of the sensory feed‐back and to place this new knowledge at the disposal of the trainer, who previously had tended to concentrate almost exclusively on the actual doing part of performance. The third principle has to do with that sixth sense known as the kinaesthetic sense or the feel of the job when it is being properly performed. A fourth principle concerns the over‐riding importance of job analysis: the concept that training cannot be correctly designed without the task itself being analysed first. A fundamental point of job analysis is that it can be carried out at different levels of penetration and that one skill the trainer himself has to acquire is the ability to make the correct choice of that form of analysis which will optimise his results but minimise his use of effort and other resources.

The purpose of this paper is to identify different job types in the Belgian electricity sector and their relations with employee outcomes such as work engagement and innovative work behaviour (IWB).

This paper uses a combination of latent profile analysis and relative operating characteristics (ROC) analysis.

Depending on the job resources and demands, five different job types are identified corresponding largely to the Karasek and Theorell (1990) job types. Their relation with the outcomes is not parallel with low-strain jobs performing best for work engagement, and active jobs for IWB.

The combination of methods used in this study increases significantly the ease of communication of the findings, yet an external benchmark for the ROC analysis would be preferable.

To foster engagement and IWB with employees one should focus on the job content and only increase demands if they are combined with sufficient resources.

This research is the first in its kind that relates latent job types with different employee outcomes using a combination of latent profile and ROC analysis.