Optimizing the interaction of technical,social and organizational factors in work groups—an application of the multidimensional classification method

This paper suggests a new multidimensional classification method for finding design rules for work groups from the viewpoint of optimizing the interaction of technical, social and organizational factors in work groups. It is called the contingent multidimensional classification method (CMDC)

For classifying tasks, the CMDC evaluates three kinds of similarities.

(1)Similarity in the attributes of tasks.

(2)Similarity in the effects of tasks.

(3)Similarity in the attributes of worker and supervisors being assigned the tasks.

The effects are measured by such effectiveness indexes as job satisfaction or work performance.

Several design rules are needed to adapt to various situations, because there is no single best rule for designing effective work groups. The diverse design rules for determining interrelationships among constituent units of the work group—task, worker and supervisor—can be found by examining the properties of ‘similar task types’ resulting from classifying tasks by CMDC     

A multidimensional classification method for finding the design rules of work groups

This paper suggests a new multidimensional classification method (CMDC-II), which is a method for finding the design rules of effective work groups by determining rational combinations of workers, tasks and supervisors. The CMDC-II is a new method for providing design rules from the viewpoint of design goal attainment. The features of our methodology are summarized as follows.

Technical, social and organizational factors are introduced as attributes of task, worker and supervisor.

Goals, criteria, standards and goal sets are integrated into a multidimensional space.

The design rules are found by the use of the CMDC-II.

The design is performed by determining an effective combination of task, worker and supervisor.     

Determination of similar task types by the use of the multidimensional classification method: towards improving quality of working life and job satisfaction

In this paper the entity is defined as the constituent unit of the work group. Actually the entity means the individual worker, supervisor, or task. These entities have respectively their attributes and also contribute to the effectiveness of the design of the work group. Similar types of entities are constructed by considering the interrelations between attributes and effectiveness.

The suggested MDC (multidimensional classification method) is a new method of classifying the entities in relation to the defined attribute space and effectiveness space and of better constructing similar types. From the viewpoint of the operationality of design and redesign of the work group, the MDC is useful to determine rationally the similar types of entities. In fact, in relation to job satisfaction, the similar task types could be successfully constructed by the use of the MDC. As a result, higher job satisfaction could be realized by manipulating the similar task types so determined.

The similar types which are determined by the MDC are useful to create the design rules for manipulating the entities in the process of designing an effective work group. By determining the similar types of workers and supervisors and also adopting work performance and productivity as effectiveness indexes, the methodology can be established for designing an effective work group.     

On the evaluation of group effectiveness for designing work groups

This study suggests a method evaluating the effectiveness of the individual work group, i.e. group effectiveness. In the design process it is very important to know what effectiveness we can expect from a proposed work group, and also when redesigning or reappraising a work group we must be able to evaluate the existing State of effectiveness. In either case the evaluation of group effectiveness is carried out through a procedure for ascertaining the goals for which the work group is designed.

A special characteristic of our suggested method is that the group effectiveness is evaluated on the basis of configural patterns in multidimensional space. That is. each group member's response to effects is discriminated as an ‘effect-point’ in the multidimensional ‘effectiveness space’, which is formed by the use of a multidimensional scaling method, and then the relative effectiveness is assessed from the patterns of the effect-points in the effectiveness space.

In order to appraise the existing state and estimate the design goals, the effectiveness must be related to the attributes of the work group. These relationships can he found from analyses employing ‘multidimensional classification methods’, i.e. M DC, CMDC-I, and CMDC-II. Thus the designer is able to predict effectiveness from the attributes of the proposed work group. In this paper we examine these relationships by the analysis of two indices of effectiveness (job satisfaction and work performance) and the attributes of the worker and task which are the critical elements for the design of an effective work group. We suggest a procedure to evaluate group effectiveness and identify the design goals. Our procedure will be applied to the design of more effective and better work groups.     

Cross-training policies and team performance

Labour flexibility is an important issue in the design and development of teams. By means of an analytical study this paper investigates the impact of cross-training on team performance. Four cross-training policies are distinguished and compared according to their effects on important performance measures, such as the load of the bottleneck worker and the number of newly used qualifications seen in various situations. These measures indicate a team's effectiveness and efficiency. Furthermore, they are related to psychological, social and organizational aspects of team functioning. A task assignment heuristic serves as a tool for comparing the cross-training policies. This is applied in an experimental study in which the team situation varies with respect to the cross-training policy, the level of absenteeism, and the variation in the mix of orders. It is shown that a worker-oriented cross-training policy, which attempts to spread multi-functionality evenly among employees, performs well. This policy offers the opportunity to shift work among employees to keep the load of the bottleneck worker low. The required coordination effort for allocating workers to tasks is also relatively low. In line with previous research, this study shows a diminishing positive effect of expanding the level of labour flexibility. The coordination effort required to apply additional flexibility appears to increase linearly with the amount of additional cross-training. The diminishing positive effect and the linearly increasing coordination effort suggest that managers should critically consider the level of labour flexibility in worker teams.     

Autonomous task decision-making and its implications for job design

This paper describes a model for task related decision-making. A distinction is made between three types of task decisions: boundary control decisions, which related the task system to its environment; intrasystem control decisions, which determine the means of performing the assigned tasks; and regulation decisions, which counteract disturbances that may affect task performance. Propositions for autonomous decision-making by the task performer under various conditions, derived from the model, were confirmed through extensive investigations of actual workstations.

Implications of research findings on job design are also discussed.     

How does digital office affect overtime through job autonomy in China? A nonlinear mediating model for the autonomy paradox

Digital offices that rely on Internet technology have become a typical working mode in the information era, and the coexistence of extended and flexible working hours generally occurs worldwide. However, knowledge of the non-linear relationship between job autonomy and overtime in a digital-working environment is relatively scarce. Based on the autonomy paradox and the too-much-of-a-good-thing theory, this study adopts the China General Social Survey of 2017 data to establish and examine the relationship between digital office, job autonomy, and overtime hours, as well as their potential mechanisms. The results show an inverted U-shaped relationship between digital office level and job autonomy and a positive U-shaped relationship between job autonomy and overtime hours. Moreover, job autonomy plays a non-linear mediating role in the relationship between digital office level and overtime hours. Specifically, with the improvement in the digital office, the marginal effect of the digital office level on overtime hours through its effect on job autonomy decreases. Additionally, this effect may vary due to age, sex, and skill levels. Therefore, as the trend of digitalization and flexibility of the labor process becomes increasingly prominent, the difficulty of statistics and control of working hours also increases. Accurate control over digitalization and autonomy levels has become key to realizing the sustainable and healthy development of digital offices.     

LABORATORY STUDIES OF REPETITIVE WORK. II : PROGRESS REPORT ON RESULTS FROM TWO SUBJECTS

This experiment is the first or a series undertaken to test proposals put forward earlier by the first author that in repetitive work (i) output would be higher and variability less if breaks were given at the end of an actite period (period of optimum performance) rather than at the point when output decreased; (ii) the end of an actile period would be indicated by the onset of irregularity in performance which could be determined by the incidence longcycle times in unpaced work and an increase in the number of missed cycles in paced work; and (iii) the length of an actile period will depend on the demand made by the job and upon the capacity of the worker to meet the demand (her actility)

Results from two subjects tested for a period of 3 1/ 2 months suggest that proposal (i) is correct. A condition in which two breaks were given at limes indicated by an increase in long times in unpaced performance gave a significantly better output and lower variance than a condition in which one break was given at a time indicated by a fall in output. Both subjects had relatively fewer misses in the paced condition when three breaks were given than when working continuously

The technique for obtaining long times in unpaced work which formed part of (ii) was found to be practical and a simpler method was devised. The results obtained seem to confirm that the method has validity. No definite conclusions can be drawn on paced work

There is some tentative confirmation of (iii); in the paced condition the actile period seems to have been 1 hour compared with 1 1/4hours in the unpaced condition. Further, the better worker gave her best unpaced performance when rest was given after 1 1/4 hours whereas the less good worker did best when rest was given after 1 hour.     

Characteristics of a Work Organization from a Lean Perspective

Abstract:

Implementation of lean practices results in significant changes in an organization. Current research in lean production primarily focuses on examining relationships between the implementation of lean production (LP) and the performance of the organization; however, there is a need to assess the implications of large-scale changes such as lean production on work design characteristics and employee outcomes. The purpose of this article is to study the impact of lean production on work design characteristics, such as autonomy, task identity and skill variety, and employee outcomes. This article proposes a conceptual framework that indicates key LP practices and their influences on work characteristics and employee outcomes.

Current research in LP identifies transformations in lean models inspired by sociotechnical principles. This article presents a comprehensive literature review of an evaluation of LP based on sociotechnical design principles. This evaluation contributes toward developing an insight for the proposed framework of the work design characteristics in a lean environment. Finally, a causal loop diagram is used to derive theoretical implications of the conceptual framework proposed.     

A Crowdsourcing Recommendation that Considers the Influence of Workers

In the context of the continuous development of the Internet, crowdsourcing has received continuous attention as a new cooperation model based on the relationship between enterprises, the public and society. Among them, a reasonably designed recommendation algorithm can recommend a batch of suitable workers for crowdsourcing tasks to improve the final task completion quality. Therefore, this paper proposes a crowdsourcing recommendation framework based on workers’ influence (CRBI). This crowdsourcing framework completes the entire process design from task distribution, worker recommendation, and result return through processes such as worker behavior analysis, task characteristics construction, and cost optimization. In this paper, a calculation model of workers’ influence characteristics based on the ablation method is designed to evaluate the comprehensive performance of workers. At the same time, the CRBI framework combines the traditional open-call task selection mode, builds a new task characteristics model by sensing the influence of the requesting worker and its task performance. In the end, accurate worker recommendation and task cost optimization are carried out by calculating model familiarity. In addition, for recommending workers to submit task answers, this paper also proposes an aggregation algorithm based on weighted influence to ensure the accuracy of task results. This paper conducts simulation experiments on some public datasets of AMT, and the experimental results show that the CRBI framework proposed in this paper has a high comprehensive performance. Moreover, CRBI has better usability, more in line with commercial needs, and can well reflect the wisdom of group intelligence.     

Worker allocation in lean U-shaped production lines

U-shaped lines are widely used in lean systems. In U-shaped production lines, each worker handles one or more machines on the line: the worker allocation problem is to establish which machines are handled by which worker. This differs from the widely-investigated U-line assembly line balancing problem in that the assignment of tasks to line locations is fixed. This paper address the worker allocation problem for lean U-shaped production lines where the objectives are to minimize the quantity of workers and maximize full work: such allocations provide the opportunity to eliminate the least-utilized worker by improving processes accordingly. A mathematical model is developed: the model allows for any allocation of machines to workers so long as workers do not cross paths. Walking times are considered, where workers follow circular paths and walk around other worker(s) on the line if necessary. A heuristic algorithm for tackling the problem is developed, along with a procedure representing the ‘traditional’ approach of constructing standard operations routines. Computational experiments considering three line sizes (up to 20 machines) and three takt time levels are performed. The results show that the proposed algorithm both improves upon the traditional approach and is more likely to provide optimal solutions.     

Stress assessment based on Ergonomics coupled with image-processing tools and techniques for lean product design and development

This paper presents an innovative lean ergonomic tool (LET) for mental stress through facial muscle activity assessment. An image-processing tool has been developed based on the analysis of facial angles. These angles were perceived by analyzing the stress levels of product development team members at certain conditions. A total number of 26 subjects participated in the experiments. On the basis of angular deviation levels, a stress level classification scheme was developed using neutral position of each team members for each task. Through statistical analysis, team members were divided into the groups of same degree of stress level. Each group was assigned a numerical expression value which was relative to the perceived stress level of that group for each task. Using five distinct action categories, a criterion for the evaluation of stress level was proposed which was validated through two distinct case studies. The developed LET will help the top management in taking corrective actions to reduce the stress level during product design and development.     

Lead time prediction in unbalanced production systems

Whether job due dates are set internally or externally, it is critical for the shop floor controller to be able to accurately predict job lead times. Previous research has shown that utilizing information on the congestion levels along a job's route is more valuable than overall shop congestion levels when predicting job lead times. While this information is easily attained in a simulation model, in industrial applications the task may be considerably more difficult, especially when lot splitting is used to accelerate material flow. We examine the effectiveness of three lead time estimation procedures which utilize different shop information in bottleneck-constrained production systems where lot splitting is practiced under a variety of experimental conditions. The results indicate that accurate lead time estimates can be obtained using information pertaining solely to the bottleneck work centre when the bottleneck is at an entry work centre. This offers operations managers a substantial ease in implementation over previously reported methods. The results also show that the operations managers interested in accurately estimating job lead times are well advised to take advantage of the excess capacity at non-bottleneck work centres by performing additional setups, and take measures that reduce bottleneck shiftiness.     

The ergonomic design of workstations using virtual manufacturing and response surface methodology

The increasing use of computerized tools for virtual manufacturing in workstatin design has two main advantages over traditional methods first it enables the designer to examine a large number of design solutions; and second, simulation of the work task may be performedin order to obtain the values of various performance measures. In this paper a ne~ structural. methodology for the workstation design is presented. Factorial experiments and the response surface methodology are integrated 111 order to reduce the number of examined design solutions and obtain an estimate for the best design configuration With respect to multi-objective requirements.     

Validation of scientific topic models using graph analysis and corpus metadata

Probabilistic topic modeling algorithms like Latent Dirichlet Allocation (LDA) have become powerful tools for the analysis of large collections of documents (such as papers, projects, or funding applications) in science, technology an innovation (STI) policy design and monitoring. However, selecting an appropriate and stable topic model for a specific application (by adjusting the hyperparameters of the algorithm) is not a trivial problem. Common validation metrics like coherence or perplexity, which are focused on the quality of topics, are not a good fit in applications where the quality of the document similarity relations inferred from the topic model is especially relevant. Relying on graph analysis techniques, the aim of our work is to state a new methodology for the selection of hyperparameters which is specifically oriented to optimize the similarity metrics emanating from the topic model. In order to do this, we propose two graph metrics: the first measures the variability of the similarity graphs that result from different runs of the algorithm for a fixed value of the hyperparameters, while the second metric measures the alignment between the graph derived from the LDA model and another obtained using metadata available for the corresponding corpus. Through experiments on various corpora related to STI, it is shown that the proposed metrics provide relevant indicators to select the number of topics and build persistent topic models that are consistent with the metadata. Their use, which can be extended to other topic models beyond LDA, could facilitate the systematic adoption of this kind of techniques in STI policy analysis and design.

     

Minimising utility work and utility worker transfers for a mixed-model assembly line

Mixed-model assembly lines (MMALs) are types of production lines that are able to respond to diversified costumers’ demand for a variety of models without holding large inventories. The effective utilisation of a mixed-model assembly line requires the determination of the assembly sequence for different models. In this paper, two objectives are considered in a sequential manner, namely minimising: (i) total utility work, which means work from an additional worker to assist an operator for completion of an assembly task; and (ii) utility worker transfer which states the move of a utility worker to a different segment of the assembly line. First, due to the NP-hard nature of the problem, three heuristic methods are proposed with the aim of minimising total utility work. Then, the solutions which are obtained from the heuristics are improved in terms of the total number of utility worker transfers via a local search based method. Furthermore, the solution approach was applied in a real life mixed model tractor assembly line. Results validated the effectiveness of sequencing approach in terms of solution quality.     

Distributed task scheduling and human resource distribution in industrial service solution production: a simulation application

This paper provides a simulation model for scheduling service task operations and distributing related human resources in dispersed work centres. The managerial concern for the minimisation of temporal overhead costs of task operations in the face of fluctuating, short-term service demands is examined under restrictions imposed by resource availability, work hour flexibility and task-backlog fulfilment. Scheduling strategies are developed directly from the constrained reduction of temporal overheads of appointment and release operations in distributed, non-interlinked work centres. To ensure the model’s structural validity, simulated task backlogs are adjusted to the actual backlog-reducing procedures in real applications. The model provides means for setting up balanced work schedules that can greatly lower temporal overheads of appointment and release operations if workers are selected in accordance with compatible time availability and task qualifications. Direct comparisons of worker productivities in the different centres can also be made, allowing managers to locate bottleneck points of service operations when productivity falls short of desired expectations. The robustness of the model is ensured by finding significant parameter domains through Monte Carlo simulations, centred on data points collected from real-time demand functions in actual service operations.     

The impact of automation and artificial intelligence on worker well-being

Discourse surrounding the future of work often treats technological substitution of workers as a cause for concern, but complementarity as a good. However, while automation and artificial intelligence may improve productivity or wages for those who remain employed, they may also have mixed or negative impacts on worker well-being. This study considers five hypothetical channels through which automation may impact worker well-being: influencing worker freedom, sense of meaning, cognitive load, external monitoring, and insecurity. We apply a measure of automation risk to a set of 402 occupations to assess whether automation predicts impacts on worker well-being along the dimensions of job satisfaction, stress, health, and insecurity. Findings based on a 2002–2018 dataset from the General Social Survey reveal that workers facing automation risk appear to experience less stress, but also worse health, and minimal or negative impacts on job satisfaction. These impacts are more concentrated on workers facing the highest levels of automation risk. This article encourages new research directions by revealing important heterogeneous effects of technological complementarity. We recommend that firms, policymakers, and researchers not conceive of technological complementarity as a uniform good, and instead direct more attention to mixed well-being impacts of automation and artificial intelligence on workers.     

Workload control in unbalanced job shops

Workload control (WLC) has been developed as a production planning and control approach for job shop manufacturing. By balancing loads across work centres, WLC anticipates the fact that multiple work centres may become potential bottlenecks in the short term. This approach is generally tested in job shop models that assume equal utilisation levels for all work centres, which will create maximum bottleneck shiftiness. However, job shop practice clearly shows differences in utilisation levels, which means that some work centres can be seen as non-bottlenecks, having protective capacity. This study investigates the effect of different levels of protective capacity on the performance of state-of-the-art WLC release methods. More in detail, it shows how the level of protective capacity interacts with the influence of workload norms at work centres. Despite the fact that WLC has been developed for highly balanced utilisations, results indicate that WLC could also be effective in unbalanced situations. However, norm setting requires careful attention. Disregarding the norms of non-bottleneck work centres, a common sense approach, might strongly deteriorate performance when the level of protective capacity is not sufficiently high. Contrarily, tighter norms for non-bottleneck work centres are shown to perform better in this situation.