A proposed methodology for the prediction of mental workload, based on engineering system parameters

In the design of engineering systems, mental workload is one of the most important factors in the allocation of cognitive tasks. Current methods of task allocation have criteria that are defined in only general terms and are thus not very useful in aiding detailed decision-making in system design. Whilst there are many quantitative criteria available to determine the physical space in human-machine interaction, system designers really require an explicit model and specific criteria for the following identification of the mental workload imposed by the system; prediction of both human and system performance; evaluation of the alternatives of system design; and the design of system components. It is argued that the available methods of workload or performance are either too domain-dependent to apply to the design of other systems, or subject-dependent and thus do not reflect the objective workload imposed by the system. The presented research adopts a new approach to cognitive task analysis in dynamic decision-making systems. Based on the characteristics derived from task analysis, a general conceptual model of the prediction of mental workload in system design is proposed. In the new model, workload is represented by a set of system parameters—task arrival rate, task complexity, task uncertainty, and performance requirements—which are considered to be the main sources of workload. In this context, workload becomes an objective demand of engineering systems, independent of any subjective factors. Whether an individual or population is overloaded depends upon their workload threshold with respect to the specified task and environment. It is hoped that this new model, after both laboratory and industrial validation, could be used by system designers to predict the workload imposed on people by systems.     

A routine-based framework implementing workload control to address recurring disturbances

Abstract

This research focuses on responsiveness in high variety manufacturing environments. To achieve it, the article proposes to develop Dynamic Response Capabilities (DRCs) of the manufacturing system defined as the abilities to readjust the planned operating parameters of workload, capacity, and lead time, in the wake of disturbances. To inform their development, built on the Workload Control theory, a routine-based framework is proposed. The framework supports an integrated approach for the implementation of adaptive decision-making routines for workload, capacity, and lead time readjustments at different stages in the order fulfilment process. Findings from two empirical cases show the appropriateness of the framework to develop and utilise DRCs in different settings of disturbances. Results of a simulation study, with one of the case companies, also shows the effectiveness of the framework to drive performance improvements in presence of recurring disturbances leading to demand variability.     

A conceptual framework for the study of work and mental health

Abstract

The key features which influence mental health both in jobs and unemployment are brought together within a single perspective. Three principal axes of affective well-being are identified as warranting investigation, and it is suggested that nine environmental features are of primary importance. The impact of these features on mental health is viewed as analogous to the influence of vitamins on physical health, with an explicit non-linearity in the relationship. This ‘vitamin model’ is extended to permit examination of individual differences (for example, in terms of baseline values and specific matching characteristics), and empirical evidence is summarized. It is concluded from previous research that job features do not interact synergistically in relation to employee well-being, although this possibility may not yet have been adequately tested. The framework is suggested to be adequately comprehensive, but, as is the case with other models, it requires development in respect of the specific mechanisms operating between environmental features and mental health.     

The SAM Framework: Modeling the Effects of Management Factors on Human Behavior in Risk Analysis

Complex engineered systems, such as nuclear reactors and chemical plants, have the potential for catastrophic failure with disastrous consequences. In recent years, human and management factors have been recognized as frequent root causes of major failures in such systems. However, classical probabilistic risk analysis (PRA) techniques do not account for the underlying causes of these errors because they focus on the physical system and do not explicitly address the link between components' performance and organizational factors. This paper describes a general approach for addressing the human and management causes of system failure, called the SAM (System-Action-Management) framework. Beginning with a quantitative risk model of the physical system, SAM expands the scope of analysis to incorporate first the decisions and actions of individuals that affect the physical system. SAM then links management factors (incentives, training, policies and procedures, selection criteria, etc.) to those decisions and actions. The focus of this paper is on four quantitative models of action that describe this last relationship. These models address the formation of intentions for action and their execution as a function of the organizational environment. Intention formation is described by three alternative models: a rational model, a bounded rationality model, and a rule-based model. The execution of intentions is then modeled separately. These four models are designed to assess the probabilities of individual actions from the perspective of management, thus reflecting the uncertainties inherent to human behavior. The SAM framework is illustrated for a hypothetical case of hazardous materials transportation. This framework can be used as a tool to increase the safety and reliability of complex technical systems by modifying the organization, rather than, or in addition to, re-designing the physical system.     

Measuring agri-food supply chain performance and risk through a new analytical framework: a case study of New Zealand dairy

Abstract

Many researchers and practitioners have long recognized the significance of measuring performance. Although general guidelines for measuring business performance are widely available, no appropriate measurement frameworks have been developed for measuring agri-food supply chain performance. Particularly, food quality and risk-related indicators have not been well integrated into existing performance measurement systems. Our research, therefore, addresses this knowledge gap by first providing an in-depth review of extant performance measurement systems and frameworks. It then develops an analytical framework by extending the Supply Chain Operations Reference (SCOR) model which has been extensively implemented across non-food industries. The analytical framework is further validated by utilizing a case study of 50 farmers and 10 dairy companies, operating in the New Zealand dairy industry.

Our pilot testing and subsequent findings show that the individual metrics interlocked with the analytical framework are in-line with the key industrial practices adapted by the New Zealand dairy industry. In addition, the framework is flexible and scalable to evaluate and benchmark other agri-food supply chains – ranging from fresh products such as fruits and vegetables to processed foods such as canned fruits. The findings further show that the detailed information required for measuring the level-3 SCOR metrics is not easily available in the industry, as researchers need to access specific company records that may be confidential. Consequently, this study provides how agri-food supply chain managers can employ our new analytical framework in-conjunction with the SCOR model for a deeper understanding of the complicated performance measurement indicators applied in their agri-food production systems and relevant supply chains.     

A Framework for Estimating the Adverse Health Effects of Contamination Events in Water Distribution Systems and its Application

Intentional or accidental releases of contaminants into a water distribution system (WDS) have the potential to cause significant adverse health effects among individuals consuming water from the system. A flexible analysis framework is presented here for estimating the magnitude of such potential effects and is applied using network models for 12 actual WDSs of varying sizes. Upper bounds are developed for the magnitude of adverse effects of contamination events in WDSs and evaluated using results from the 12 systems. These bounds can be applied in cases in which little system‐specific information is available. The combination of a detailed, network‐specific approach and a bounding approach allows consequence assessments to be performed for systems for which varying amounts of information are available and addresses important needs of individual utilities as well as regional or national assessments. The approach used in the analysis framework allows contaminant injections at any or all network nodes and uses models that (1) account for contaminant transport in the systems, including contaminant decay, and (2) provide estimates of ingested contaminant doses for the exposed population. The approach can be easily modified as better transport or exposure models become available. The methods presented here provide the ability to quantify or bound potential adverse effects of contamination events for a wide variety of possible contaminants and WDSs, including systems without a network model.     

Integrated approach for optimizing quality control in international manufacturing networks

Abstract

This article aims at providing an integrated approach for optimizing quality control in International Manufacturing Networks (IMN) which can be characterized by consisting of numerous plants acting autonomously according to an individual target system. A key challenge is to ensure the overall process quality despite distributed value creation processes and differing target systems in dynamic environments. Hence, the developed approach allows for identifying potentials in the quality control strategy using a value stream-based method to visualize quality characteristics and procedures in the production process chain. Furthermore, the approach contains a framework for identifying possible improvement measures and a simulation-based evaluation concept to evaluate the effects of different measures with respect to individual target systems. The simulation combines elements of a discrete-event simulation in order to depict the value stream with agent-based modelling for realizing different target systems by considering distinctive plant roles. The article concludes with a case study of a globally operating automotive supplier to apply the approach. A forward research agenda is proposed that evaluates the approach in multiple cases, deriving patters across companies or industries.     

Psychosocial safety climate as an antecedent of work characteristics and psychological strain: A multilevel model

Abstract

Psychosocial safety climate (PSC) refers to a specific organizational climate for the psychological health of workers. It is largely determined by management and at low levels is proposed as a latent pathogen for psychosocial risk factors and psychological strain. Using an extended Job Demands-Control-Support framework, we predicted the (24 month) cross-level effects of PSC on psychological strain via work conditions. We used a novel design whereby data from two unrelated samples of nurses working in remote areas were used across time (N=202, Time 1; N=163, Time 2), matched at the work unit level (N= 48). Using hierarchical linear modelling we found that unit PSC assessed by nurses predicted work conditions (workload, control, supervisor support) and psychological strain in different nurses in the same work unit 24 months later. There was evidence that the between-group relationship between unit PSC and psychological strain was mediated via Time 2 work conditions (workload, job control) as well as Time 1 emotional demands. The results support a multilevel work stress model with PSC as a plausible primary cause, or “cause of the causes”, of work-related strain. The study adds to the literature that identifies organizational contextual factors as origins of the work stress process.     

Measuring Sharedness of Team-Related Knowledge: Design and Validation of a Shared Mental Model Instrument

Many researchers have explored how people share and construct similar mental models in teams. They have claimed that successful team performance depends on a shared mental model of team members about task, team, equipment and situation. Most of the literature has illustrated simplified relationships between a team's mental model and their performance without a valid instrument addressing the confined and relevant constructs of a shared mental model. This paper describes the instrument development steps and the conceptual framework for factors associated with shared mental models. After development and refinement, the instrument was finalized for use to measure team-related knowledge. The final instrument consists of 42 items that are linked to the five emergent factors of shared mental models including general task and team knowledge, general task and communication skills, attitude toward teammates and task, team dynamics and interactions, and team resources and working environment.     

Integration of process planning and production planning and control in cellular manufacturing

Organisations willing to succeed in global competition have to integrate their internal and external processes. This especially includes planning and production control (PPC) processes. Optimised allocation of the production resources and quick response to demand changes result in lower cost and improvement of production performance. Practitioners and researchers have been trying to achieve these goals using production planning techniques. Although the results are significant, it seems necessary to integrate production operations in order to improve the production performance. The goals, information and decisions taken in production planning and control and process planning are often very different and difficult to integrate in Cellular Manufacturing (CM) environments. Designing an efficient PPC system and integrating it with process planning in a cellular environment is of the same importance. The following paper proposes first a comprehensive framework of integrated process planning and production planning and control in CM. Then, with respect to this framework and utilising the domain knowledge in the area of CM systems, an integrated model based on Integrated Definition Modeling Language is developed. The application of the models has been considered as a case study for a production system in electronics and telecommunication sector in a plant in Iran. The validity and completeness of the proposed model is tested by a panel of experts in the areas of production planning and control in CM environments.     

Comparing reactive Kanban and reactive CONWIP

This paper compares a reactive Kanban system to a reactive CONWIP system under conditions of unstable changes in demand using simulation experiments. After an introduction, a model of the JIT ordering systems, the Kanban and the CONWIP systems, is constructed. In order to obtain the fundamental information for developing a control rule of buffer size, the performance of the two types of the JIT ordering systems is analysed under various stable-demand conditions by simulation experiments. Based on the results, the reactive JIT ordering systems are proposed, and the performance of the proposed systems is investigated. The results showed that both of the proposed systems can react to unstable changes in demand and maintain the mean waiting time of demand at less than the required level. In the reactive Kanban system, the total of the mean work-in-process inventories becomes much less than that in the traditional Kanban system without controlling buffer size. However, in the reactive CONWIP system, the total of the mean work-in-process inventories becomes much more than or nearly equal to that in the traditional CONWIP system without controlling buffer size under the strongly correlated or the weakly correlated processing times, respectively. Based on the results, it can be claimed that, in the proposed systems, the reactive Kanban system is more effective to react to unstable changes in demand than the reactive CONWIP system.     

The Mapping of Contingencies in Mental Models Found in Organizations

From a cognitive perspective, mental models held by individuals are thought to guide interactions with objects or systems, including interpersonal interactions. Frameworks that categorize types of interactions in organizations suggest that they are guided by cultures and mental models that range from the egoistic to the cosmos-centric. From a behavioral perspective, what the cognitive approach calls mental models are sets of verbal rules. Therefore, we suggest that behavior analysis could be used to reconceptualize the mental model literature, generating new research questions and more rigorous experimentation. Cognitive constructs such as more expansive mental models may simply be a function of an individual’s or group’s increased attention to interlocking contingencies. Applying behavioral interventions such as acceptance and commitment therapy could be a way to examine the utility of a behavior analytic approach.     

Personality and organizational health: the role of conscientiousness

Organizational health research identifies processes through which the work environment and individual differences combine to influence both individual and organizational outcomes. This study investigated the contribution of conscientiousness to organizational health. Research in the areas of occupational stress, work performance, and organizational climate was used to develop a framework for integrating different elements of organizational health. Within this framework, the work environment was assessed by perceptions of workload and role clarity ; individual well-being was assessed by psychological distress and job satisfaction ; and behaviour important for organizational success was assessed by contextual performance. Conscientiousness was investigated within the framework using self-reports from a sample of 104 Australian employees. Conscientiousness directly influenced contextual performance but did not influence well-being or perceptions of the work environment. Conscientiousness also reduced the impact of role clarity on both psychological distress and job satisfaction. The role of conscientiousness in a comprehensive model of organizational health is discussed.     

Decentralized WIP-oriented manufacturing control (DEWIP)

DEWIP is a manufacturing control system for job shop environments aiming at achieving short and reliable lead times by establishing WIP control loops between the manufacturing work centres. The paper describes the mode of function, the setting of parameters and simulation results of the new manufacturing control system. The setting of parameters is done with the aid of the funnel model and the theory of logistic operating curves, both developed at the Institute of Production Systems at the University of Hanover. The simulation is conducted using industrial data and makes it possible to assess DEWIP with regard to lead times, WIP level, performance and schedule reliability. DEWIP is compared both with an uncontrolled process and with the manufacturing control systems Load oriented order release (LOOR), Conwip and Polca. The results suggest that DEWIP and the models employed for the setting of parameters are suitable for job shop production and therefore offer a valuable alternative to prevailing centralized manufacturing control systems.     

Return to work among employees with mental health problems: Development and validation of a self-efficacy questionnaire

Abstract

Because of the costs to both the organization and the individual, it is important that employees who are sick-listed with mental health problems are facilitated in their return to work (RTW). In order to provide adequate interventions, it is necessary to obtain a better understanding of the RTW process of people with mental health problems. Work-related self-efficacy (SE) might play a key role within this process. This paper describes the development and validation of the return-to-work self-efficacy’ scale (RTW-SE) for employees with mental health problems. Three Dutch samples of sick-listed employees were used to validate the 11-item instrument (N=2214). Based on the factor structure and reliability results, RTW-SE was conceptualized as a unitary construct. The associations with general SE, locus of control, coping, physical workload and mental health problems support the construct validity of this scale. Most importantly, RTW-SE proved to be a robust predictor of actual return to work within three months. The encouraging preliminary psychometric properties of the scale make it a potentially valuable tool in research and in clinical practice and occupational health care settings, both before and after employees have returned to work.     

An Examination of Procedural and Object-oriented Systems Analysis Methods: Does Prior Experience Help or Hinder Performance?*

Interest in object-oriented analysis (OOA) and object-oriented design (OOD) has expanded rapidly over the last several years. Proponents of OOA and OOD have called the shift to these methods “revolutionary” and have cited a number of impressive claims with respect to their use. However, empirical research investigating these claims remains in its infancy. Moreover, an examination of the literature reveals inconclusive and often conflicting results for OOA and OOD methods relative to traditional data and/or procedural techniques. This paper presents the results of an empirical study that examined both experienced and novice systems analysts using both procedural and object-oriented techniques. This research examined whether experience in using procedural methods helped or hindered performance using OOA and compared procedural and OOA methods on the subjective mental workload induced. A human problem-solving model adopted from Newell and Simon (1972) provided the theoretical framework for this study. Dependent variables include subjective mental workload, solution quality, time to perform task, and attitudinal measures. Although some of these dependent variables have been used in past research, we believe this is the first time that subjective mental workload (SMW) has been examined in an IS context. Our results indicate that both novice and experienced subjects demonstrate higher SMW when using OOA. In addition, as a group, novices prefer object-oriented techniques and find these techniques easier as compared to experienced subjects.     

A multilevel approach to building and leading learning organizations

A multilevel model is offered proposing that organizational learning is an interdependent system where effective leaders enact intervention strategies at the individual (micro), network (meso), and systems (macro) levels. We suggest that leaders approach organizational learning by setting the conditions and structure for learning to occur, while limiting direct interference in the actual creative processes. First, leaders may increase the level of developmental readiness of individual followers, thereby increasing their motivation and ability to approach learning experiences and adapt their mental models. These individuals then serve as catalysts of learning within and between social networks. Second, leaders may promote the diffusion of knowledge between these knowledge catalysts within and across social networks through influencing both the structure and functioning of knowledge networks. Finally, leaders may target actions at the systems level to improve the diffusion to, and institutionalization of, knowledge to the larger organization.     

Path to “Stardom” in Globally Distributed Hybrid Teams: An Examination of a Knowledge‐Centered Perspective using Social Network Analysis

Although distributed teams have been researched extensively in information systems and decision science disciplines, a review of the literature suggests that the dominant focus has been on understanding the factors affecting performance at the team level. There has however been an increasing recognition that specific individuals within such teams are often critical to the team's performance. Consequently, existing knowledge about such teams may be enhanced by examining the factors that affect the performance of individual team members. This study attempts to address this need by identifying individuals who emerge as “stars” in globally distributed teams involved in knowledge work such as information systems development (ISD). Specifically, the study takes a knowledge‐centered view in explaining which factors lead to “stardom” in such teams. Further, it adopts a social network approach consistent with the core principles of structural/relational analysis in developing and empirically validating the research model. Data from U.S.–Scandinavia self‐managed “hybrid” teams engaged in systems development were used to deductively test the proposed model. The overall study has several implications for group decision making: (i) the study focuses on stars within distributed teams, who play an important role in shaping group decision making, and emerge as a result of a negotiated/consensual decision making within egalitarian teams; (ii) an examination of emergent stars from the team members’ point of view reflects the collective acceptance and support dimension decision‐making contexts identified in prior literature; (iii) finally, the study suggests that the social network analysis technique using relational data can be a tool for a democratic decision‐making technique within groups.     

Job characteristics as predictors of ill-health and sickness absenteeism in different occupational types--a multigroup structural equation modelling approach

The objective of the present study was to test for multigroup invariance in measurement models and structural models between job characteristics, psychosocial intervening variables, health outcomes and sickness absenteeism. Four types of occupation were represented in the study: blue-collar workers ( n = 241), white-collar workers ( n = 209), elderly-care workers ( n = 338) and child-care workers ( n = 336). A first-order, six-factor multigroup confirmatory factor analysis model (i.e. measurement model) composed of two perceived job characteristics ( job autonomy and skill discretion), appraised workload, job satisfaction, stress-related ill-health and sickness absenteeism provided a good model fit. Invariance tests showed that the six-factor model fits well for all occupations. A partially recursive mediated multigroup structural model showed both similarities and differences across occupations as regards the relationships between independent latent variables ( job autonomy, skill discretion), intervening latent variables (appraised workload, job satisfaction) and dependent latent variables (stressrelated ill-health, sickness absenteeism). By comparing a generic model with occupation-specific models across occupations, this study showed that occupation-specific models were more plausible. The results indicate that it is important to examine different occupational contexts in detail to better understand how certain psychosocial factors at work influence strain in different occupations. Since job characteristics can potentially be amended, the findings have important implications for the differentiation of prevention and intervention in different occupations.     

The case for complexity: A look at the relationship between individual and structure from the inside out

Abstract

This paper develops a model of the individual – structure relationship using a predominantly sociological explanation. Adopting the perspective of the individual and grounding the approach in a structurationist framework, a system of person-based and role-based relationships is proposed. The model's implications for the individual are developed from an examination of markets, hierarchies and networks. Main conclusions cross-cut individual, functional and organizational levels: (1) work- and non-work roles need to be intentionally maintained and leveraged as a way to develop individual and organizational complexity; (2) individual discretion is essential to achieving the proper balance between the two kinds of roles; (3) networks provide the greatest potential for role satisfaction; and (4) HRD assumes an instrumental role in establishing and maintaining a culture of trust and in designing and supporting jobs that foster complexity and discretion.