The effects of smart manufacturing on the work
design of blue- and white-collar employees
Author
Bik, Jasper (S4175611) j.l.w.bik@student.rug.nl 06-36128040
Kleine Leliestraat 13, 9712 TD Groningen University of Groningen
Faculty of Economics and Business Pre-Master Supply Chain Management Date
21-06-2020
Abstract
This paper aims to explore what the changes are in work design because of the implementation of smart manufacturing technologies. Smart manufacturing technologies’ characteristics and their effect on task characteristics are investigated. An empirical case study was conducted consisting of three companies in the manufacturing industry. Key findings show that characteristics regarding information availability and transparency cause the main changes in work design. Blue-collar employees experience more changes in the characteristics task variety and task identity. White-collar employees experience more changes in the characteristics feedback and autonomy. This paper contributes to the literature by investigating the underlying relationship between smart manufacturing technology characteristics and work design.
Keywords Smart manufacturing technologies, work design, blue-collar employees, white-collar employees
Supervisor S. Waschull
Theme Smart manufacturing and the future of work - Project 1A Smart manufacturing and work design
1. Introduction
Companies are constantly looking for opportunities to work more efficient and effective to gain a competitive advantage. The developments within the fourth industrial revolution (i.e. industry 4.0) make a lot of new innovative technologies available for manufacturing companies to gain this competitive advantage. Industry 4.0 has smart manufacturing (SM) as its centre and key aspect (Frank, et al., 2019). SM is defined as the application of networked, information-based technologies in manufacturing (Davis, et al., 2012). Nowadays, people, machines, and products are linked together because of smart manufacturing technologies (SMTs), which enables faster and more precise exchange of information (Gorecky, et al., 2014). Rauch et al. (2020) mentioned that this is developing into a future where robots, machines, and other devices collaborate with people and support them in their work activities, but they also mentioned that different technologies might even replace employees. Considering this, SMTs create many opportunities, but this also poses many risks for human work.
Implementing new SMTs ensures many changes in an organization. One of these changes is the changing work design for not only blue-, but also white-collar employees due to unprecedented application scenarios (Hartmut, 2016). Cagliano et al. (2019) and Parker & Grote (2020), have shown in their research that these new technologies can have both positive and negative effects on work design. For example, the cognitive demands that blue- and white-collar employees experience increases due to the increased technical complexity of systems being used (Cagliano, et al., 2019). Besides, in the presence of higher-level technical complexity, blue-collar employees will experience a higher level of autonomy (Cagliano, et al., 2019). Possible negative effects for blue- and white-collar employees could be extra workload and variation in tasks (Parker & Grote, 2020). Furthermore, developments within SMTs lead to new situations for employees and it requires a different work design, these are common problems and difficulties companies must deal with. It is important for companies to design work properly because a bad work design can lead to bad firm performance, unmotivated employees, and various other negative effects (Parker, et al., 2017).
System (MES). ERP is an information system that integrates information-based processes within and across departments in an organization (Zhang, et al., 2005). MES is an information system for manufacturing control (Ugarte, et al., 2009). Understanding the dimensions and characteristics of ERP and MES will contribute towards understanding the underlying relationship with designing work. This leads to the following research question: What are different characteristics of ERP- and MES-systems within a manufacturing workplace and how do these affect the task characteristics of both blue- and white-collar employees?
To provide an answer to the question, a multiple case study has been conducted, exploring the underlying relationship between the characteristics of SMTs and their effect on work design. Besides, investigated is how these characteristics relate to the work design on both blue- and white-collar employees and possible differences in work design between these two types of employees. This study contributes in a societal way by investigating an actual problem for manufacturing companies. Uncertainty and the unknown consequences of implementing SMTs on work design are actual problems manufacturing companies currently face (Frank, et al., 2019). By conducting this study, manufacturing companies become more aware of the consequences of work design after implementing new SMTs. This is important because both SMTs and good work design could lead to better firm performance (Morgeson & Humphrey, 2006).
The structure of this paper is as follows: first, a description and analysis of the theory about SMTs, important work design characteristics, and the relationship between SMTs and work design are given. Second, the research methodology of this study is provided before the results are presented and discussed. Finally, the results will be interpreted and discussed.
2. Literature review
In this chapter the most important theoretical concepts will be discussed and analysed. First SMTs, explicit ERP and MES, and their characteristics are reviewed. Thereafter, work design and important task characteristics are presented considering blue- and white-collar employees. In the end, a link is made between the technologies and work design and its characteristics. After this, the insights are combined in a theoretical framework.
Smart manufacturing technologies and their characteristics
SMTs that are the central and key aspects for industry 4.0, enables companies to analyse large amount of data in real-time, improve strategic and operational decision making, and it increases quality, flexibility and productivity of companies (Davis, et al., 2012; Delagonare, et al., 2018; Frank, et al., 2019). Materials, equipment, and machine parts are connected via the internet due to installed sensors and actuators, this is seen as one of the important components of SMTs (Frank, et al., 2019; Rauch, et al., 2020).
Characteristics
Characteristics can be defined as a property that is particular to an SMT and are used to determine differences or similarities between technologies (Tao & Qi, 2019). Mittal et al. (2019) have carefully grouped ERP & MES as IT-based production management systems. These systems are tools that connect everything happening in the organization through the help of IT. The applied characteristics for this research are IT-driven, information transparency, heterogeneous knowledge, flexibility, and interoperability. These characteristics provide a comprehensive and targeted list to get an in-depth understanding of the SMTs. The five characteristics are shortly explained in Table 1.
Table 1
Smart manufacturing Characteristics CHARACTERISTICS DESCRIPTION
IT-DRIVEN Human decisions are substantiated and made using information technology. IT-driven applications and devices can be used. INFORMATION
TRANSPARENCY
Amount of information, including real-time information, that is available. Makes it possible for others to see performed actions.
HETEROGENEOUS KNOWLEDGE
Mechanisms to make the collected data more understandable for human user and to make the decision making easier for them.
FLEXIBILITY A system can be considered flexible when it can adapt to changes in the external environment. For example, the manufacturing process can respond on rapidly changing demand.
INTEROPERABILITY Systems units being able to exchange and share information with each other. Networkability, distributed systems, information appropriateness, integrability, standardized connectivity, and decentralized are included in the interoperability cluster.
Adapted from (Mittal, et al., 2019)
Both ERP and MES will be defined and explained subsequently with emphasis on the mentioned characteristics.
Enterprise resource planning
activities through independent software modules, such as inventory or supply chain management modules, while constantly updating a central database (Quiescenti, et al., 2011). According to the literature, the characteristics IT-driven, information transparency, heterogeneous knowledge, and interoperability might be applicable for ERP. A simplified overview of an ERP system is given in Figure 1.
(Powell, et al., 2013)
Manufacturing Execution System
MES is a control system for monitoring and managing manufacturing operations on a factory shop floor, it enables the optimization of production activities from start to finished goods (Ferrer & Lastra, 2018; Ugarte, et al., 2009). Besides, MES collects information on a wide number of shop floor activities and serves as a bridge between the shop floor and the top-level office-planning systems (i.e. ERP) (Zayati, et al., 2012). Hence, MES fills the gap between the management and shop floor control. An MES contains eleven core functions which are: operations scheduling, process management, document control, data collection, labour management, quality management, dispatching production units, maintenance management, product tracking & genealogy, performance analysis, and resource allocation & status (Ugarte, et al., 2009). It is important to acknowledge that some functionalities are directly linked to the process, while others are supportive. A visualization of MES’ functionalities and MES as a bridge between different company levels is given in Figure 2. The main purpose of MES is tracking, monitoring, and documenting the process of transforming raw materials into finished goods, which contributes to achieving on-time performance and adherence towards customer
Figure 1
order schedules (Sellitto & Vargas, 2020; Zayati, et al., 2012). Based on the literature, it is possible that all five aforementioned characteristics of Mittal et al. (2019) apply to MES.
In line with the aim of this paper, the following section will further elaborate on work design and important task characteristics.
Work design and important task characteristics
Work design is a term that describes the structure, organization, and content of activities, tasks, and roles performed by individuals and groups in work settings (Cordery & Parker, 2012). Early studies have shown the importance of work design regarding a range of individual, group, and organizational outcomes (Hackman & Oldham, 1976; Wall & Martin, 1987). Morgeson & Humphrey (2006) divided work design into task characteristics, knowledge characteristics, social characteristics, and contextual work characteristics. Task and knowledge characteristics are known as motivational work characteristics, in jobs where these characteristics occur employees are expected to be more satisfied and motivated. Social characteristics emphasize that jobs are involved in a wider social environment. Finally, contextual work characteristics reflect the context within work is performed (Morgeson & Humphrey, 2006). This paper focuses on task characteristics because these characteristics will undergo the greatest change as a result of the implementation of SMTs (Parker & Grote, 2020). The five task characteristics will be briefly explained.
(Ugarte, et al., 2009)
Figure 2
Job autonomy is defined as the amount of freedom, independence & discretion to schedule work, making decisions, and choosing methods to perform the tasks (Morgeson & Humphrey, 2006). Job autonomy is seen as a necessity for success in today’s dynamic world and autonomy, therefore, improves job performance (Parker, et al., 2017). Task variety refers to the number of different tasks belonging to a job to perform the work. Jobs that require different tasks are often more challenging and thereby appealing to perform (Morgeson & Humphrey, 2006). People in jobs that have high task significance positively influence the lives or work of others, those people are likely to experience greater meaningfulness in their work (Morgeson & Humphrey, 2006). When an employee is working on the entire or whole piece of work and can clearly identify the results of their efforts is called task identity (Sims, et al., 1976). Feedback from the job is thought to enhance knowledge of the results of the job (Morgeson & Humphrey, 2006). Blue- and white-collar workers
Blue-collar workers are classified as employees who perform manual labour (Cambridge dictionary, 2020). Most of this work involves something physically built or maintained. In contrast, a white-collar worker is someone who performs professional, managerial, or administrative work (Cambridge dictionary, 2020). A white-collar worker normally performs work in an office environment, sitting in front of a computer. There are some important differences between white- and blue-collar workers. The most important difference for this research is that blue-collar workers are usually closer supervised in comparison with white-collar workers, this limits the opportunities for growth and development for blue-white-collar workers (Schreurs, et al., 2011). Furthermore, blue-collar work is seen as a more physically demanding job (Schreurs, et al., 2011). In contrast, white-collar workers are generally employed in resourceful jobs, with challenging work and more control (Schreurs, et al., 2011). Taking the research of Morgeson & Humphrey (2006) into account, it is most likely to expect that white-collar workers have a higher job autonomy and task significance than blue-white-collar workers. The following section will analyse the current research on the relationship between SMTs and work design.
Relationship between smart manufacturing and work design
effect could be that automated decision making replaces human judgement (Parker & Grote, 2020). New technological systems and devices could also lead to a reduction of low skilled manual tasks and therefore the increased need for high technical qualified personnel (Cagliano, et al., 2019). A positive effect of the required change in task variety is the replacement of routine and cognitive tasks (Parker & Grote, 2020). The variation of new tasks and therefore learning new skills could have a positive effect on the critical psychological state of the employee (Morgeson & Humphrey, 2006). At the same time, the implementation of ERP could lead to a reduction in people’s task variety (Parker & Grote, 2020). Several tasks that were previously performed by employees are replaced after the implementation of systems as ERP and MES. New tasks will emerge but are likely to be more monotonous (Delagonare, et al., 2018). With the implementation of new technologies as ERP and MES, a lot of new and useful information and data becomes available, which leads to better feedback regarding the performance (Wang, et al., 2015).
Current research neglects the insight into the characteristics of SMTs. More insight is needed to get an understanding of the underlying relationship between SMTs and work design. Furthermore, the different effects on blue- and white-collar employees have not been investigated. As both kinds of employees perform different kinds of jobs, the implementation of SMTs might have a different effect on the work design of these employees.
Theoretical framework
3. Methodology
Research designQualitative research was conducted to answer the research question. Qualitative research can be used to create a methodology for approaching, understanding, analysing, and explaining management phenomena at a social or company level (Delattre, et al., 2009). To conduct this study a multiple case study was conducted. Yin (2009) describes a case study as “an empirical inquiry that investigates a contemporary phenomenon in-depth and within its real-life context, especially when the boundaries between phenomenon and context are not clearly evident”. A case study fits this study best because there is little information about how SM affects work design. A multiple case study is chosen because it provides a more solid base for explanation and theory building. Empirical evidence can show the effects for blue- and white-collar employees. The unit of analysis is the work of blue- and white-collar employees.
Research setting
This research is conducted within the manufacturing sector. This sector is chosen because manufacturing companies are facing challenging situations due to the implementation of SMTs (Frank, et al., 2019). In selecting suitable cases for this research several requirements have been selected. The chosen companies must be manufacturing companies, active in the business to business market, and should have implemented at least two SMTs. Besides, both blue- and white-collar employees must work at the selected companies and work with the implemented SMTs. These requirements have been determined to obtain mainly useful information for this research.
Table 2
Overview selected cases
Data collection
By using a well-designed semi-structured interview important data from key areas are conducted. Moreover, it allows a lot of flexibility to bring personal perspectives to the discussion (Barrett & Twycross, 2018). During a semi-structured interview, the researcher can develop follow-up questions to get an in-depth understanding of important subjects (Barrett & Twycross, 2018). An interview script was developed that was used in all cases. By conducting interviews with different employees with each a different function, the difference between blue- and white-collar employees could be investigated.
Data analysis
The interviews were analysed with the use of coding. First, a coding scheme, shown in Table 3, was created based on components of the theoretical framework. Subsequently, the interviews were read multiple times and interesting and useful text fragments were selected and put in an excel file, this was done per interview. After that, in an iterative process, all text fragments were labelled with a code or multiple codes. Through this, relationships between codes could be recognized quickly. Table 3 Coding scheme Main variables A1.1 Autonomy A1.2 Task variety A1.3 Task identity A1.4 Task significance A1.5 Feedback
A2.1 Autonomy A2.2 Task variety A2.3 Task identity A2.4 Task significance A2.5 Feedback B1.1 IT-driven B1.2 Information transparency B1.3 Heterogeneous knowledge B1.4 Flexibility B1.5 Interoperability B2.1 IT-driven B2.2 Information transparency B2.3 Heterogeneous knowledge B2.4 Flexibility B2.5 Interoperability B A A1 A2
White collar workers
Blue collar workers
4. Results
In analysing the data, specific details on how the characteristics of SMTs (ERP & MES) caused changes in the task characteristics autonomy, task variety, task identity, task significance, and feedback became insightful. Furthermore, differences and similarities between blue- and white-collar employees became clear. In appendix B a concise overview is given of which SM characteristics influence which task characteristics. Next, the characteristics will be identified for the SMTs and after that, these will be outlined in detail regarding their effect on the task characteristics.
Characteristics ERP and MES
The determination of which characteristics belong to each SMT is done using the conducted interviews and the literature of chapter 3. Characteristics of ERP are IT-driven, information transparency, heterogeneous knowledge, and interoperability. Characteristics that belong to MES are IT-driven, information transparency, heterogeneous knowledge, flexibility, and interoperability. Corresponding quotes from the interviews are included in Appendix C. ERP and MES are almost characterized by the same characteristics, except ERP is not characterized as a flexible system. During the interview with the director of company I this became clear:
“We consider ERP-systems as liquid concrete. It flows inside your organization, there it hardens, and you are completely stuck and there is no way left. You have to participate in that process, after the implementation,
changing is almost impossible for an SME.” IT-driven
The affected task characteristics of blue- and white-collar employees, due to the IT-driven characteristic of ERP and MES are summarized in Table 4.
Table 4
Changed task characteristics
BLUE-COLLAR WHITE-COLLAR
ERP Task variety None
MES Task variety
Task identity
The implementation of ERP mainly affected the employees on the shop floor. The ERP-system requires input, therefore new devices were installed which created new mandatory tasks to complete the job. The new mandatory tasks lead to a change in task variety for blue-collar employees. A blue-collar employee from company I mentioned in the interview:
“The job remains actually the same, it has not become any harder. We only need a short introduction and explanation about the new devices. However, a new task has been added with the mandatory entering of
numbers in the system.”
At companies B & F the function of an operator changed due to the implementation of MES. Different from ERP, implementation of MES changed the task identity of blue-collar employees. After the implementation of MES, employees had input in the whole production process. New applications have been used and monitoring the production process contains different tasks regarding the use of new applications. The initial operator remains responsible for the produced products but in a different way. This became clear in the interview with a manager technical services from Company B:
“Since the implementation of MES, the operator is no longer a carpenter but more a controller or quality inspector. When a machine has errors, the operator must try to solve the problem. So, they are also getting more
functions as a mechanic.” Information transparency
The task characteristics that are affected for blue- and white-collar employees, due to the information transparency characteristic of ERP and MES are summarized in Table 5.
Table 5
Changed task characteristics
The effect on the task characteristics of blue- and white-collar employees is the same for ERP and MES regarding the information transparency characteristic. Real-time information
availability created new decision options for operators. The system provides more and better information through monitors, giving the employees more responsibilities and access to information on the whole process of the product. This created a change in autonomy and task identity. Furthermore, direct feedback from the system is a new feature for blue-collar employees because permission from the system is required before the employee can continue with the task. Examples are given by operators of company F & I:
“Previously we had to explain the work transfer in person, that is no longer the case. Because we do the work and the system brings it directly to the next department. No human communication is needed anymore, the
system controls it all.” (Company F)
“We get direct feedback, for example, when I get a product and I scan the wrong location then I immediately get a notification.” (Company I)
For white-collar employees, real-time information availability created a better knowledge of the process. This knowledge was used to give better and focused feedback. Besides, it created a possibility to propose possible changes that could lead to some improvements for the company. This is an example of how information transparency changed autonomy. The company director of company B emphasized the improvement of information transparency:
“The most important mechanism for change for us was the information flow. Since the systems were implemented a vast amount of information was gathered and used for improvements.” (Company B)
Heterogenous knowledge
Heterogeneous knowledge synthesis is in line with the characteristic information transparency. The affected task characteristics for blue- and white-collar employees, due to the heterogeneous knowledge synthesis of ERP and MES are summarized in Table 6.
Table 6
Changed task characteristics
After the implementation of ERP or MES, tasks of blue-collar employees changed because their function is more about checking and controlling regarding the available data. An operator can make their own decisions based on the available data, they are not depending on their team leader anymore. This decision-making freedom caused by available data changed the autonomy and tasks of a blue-collar employee. Operators from Company I and B described these changes as follow:
“Because of the ERP-system it is more transparent for us what we have to do in a day and how much machine capacity or time is still available for us, which allows us to determine with which product we start.” (Company
I)
“The amount of information available helped us to get a better view on what products needed to be made and where made, where the raw materials are and who has to overview which production lane.” (Company B)
For white-collar employees the feedback has improved because the availability of understandable data created a more fundamental basis for good feedback. Also, better and more insightful data broadened the autonomy for white-collar employees, as more decisions could be made by employees based on the available data. The company director of company I described how he used data for determining purchasing terms at the supplier. Besides, the operational manager of company F stated how he improved his feedback using data that had become available as the effect of implementing MES.
“What can be of great value is the feedback you can give to your suppliers. That upfront is determined that all products are here within a week. Then after 1 year you have insight that of the 1000 orders, they did not deliver
100 orders. Then you can use that feedback during a purchasing conversation.” (Company I)
Every week we have a “weekstart”. In there we keep track of progress, show the performances of last week, and so on. There I can now easily show, based on data what we are currently performing and how the upcoming
period looks like.” (Company F) Flexibility
Flexibility is qualified as a characteristic for only MES, the effect of this characteristic on the task characteristics of blue- and white-collar employees are shown in Table 7.
Table 7
Changed task characteristics
BLUE-COLLAR WHITE-COLLAR
MES None Task identity
In the findings no evidence is found for changed task characteristics of blue-collar employees. Flexibility created changes, especially for white-collar employees. MES created the opportunity for a white-collar employee to make decisions in various situations because of the flexibility of the system. Due to the flexibility characteristic of MES it is possible to monitor and manage the production process from various locations, this affects the task identity and autonomy for a white-collar employee. This situation occurs for Company F as the operational manager mentioned the following in the interview:
“We can keep track of the process from a distance. From the office we can manage the production. In fact, during the construction of the current factory, the factory and the office were 30kilometers separated. First the
production process was made operational and after that the new office was being build.” (Company F)
Interoperability
Interoperability is a basis for the characteristics information transparency and heterogeneous knowledge. The task characteristics that changed because of the interoperability of ERP and MES are shown in Table 8.
Table 8
Changed task characteristics
The findings showed that the interoperability of ERP and MES created the same changes in task characteristics. ERP and MES created integration between departments and different information became available for operators. Before the implementation of SMTs information was logged by the employees. The information is already available in the system due to integration. In the current situation, the content had to be checked which shows a change in tasks. The new information that became available requires operators to perform various new tasks. These subjects were mentioned during the interview:
“The operator used to be a carpenter without big or automated machines. Due to MES, the operator has become more a mechanic that deals with machine failures and they got a quality control function” (Company B)
BLUE-COLLAR WHITE-COLLAR
ERP Task identity
Task variety
Autonomy Feedback
MES Task identity
Task variety
The roles are by name still the same. Only in many places they have different tasks to do. Largely the same actions and therefore we need less team management” (Company F)
“I actually still do the same job. Only I have more information available from the system and different tasks have been added, like putting information into the system.” (Company Y)
Integration and the exchange of information between various departments happened. Having the right information at the right time improved the ability to give substantiated feedback for white-collar employees. White-collar employees can show the new available information to strengthen their feedback. Besides insight into the right information created a wider autonomy for these white-collar employees. It makes the negotiating position for a person stronger while having facts available from the system. The following was said during the interviews:
“While we are on the phone with a customer, all information that is needed, is available. That information is delivery time, prices, availability.” (Company I)
“The progress of various frames in the factory is more clearly on the dashboards. You can better monitor what is going on. When a machine breaks down, you immediately have insight, in the needed repair time.” (Company
F)
5. Discussion and conclusion
The following chapter will provide a concise summary of the results, discussion of the interpretation of the results, implications for theory & practice, and a critical reflection of this research.
Interpretation of results
This paper aimed to answer the following research question: What are different characteristics of ERP- and MES-systems within a manufacturing workplace and how do these affect the task characteristics of both blue- and white-collar employees?
There is no big difference between ERP and MES and their effect on task characteristics of blue- and white-collar employees. The main differences occur between the type of employees. As blue-collar employees experience more changes in the characteristics task variety and task identity, white-collar employees experience more changes in feedback and autonomy. An interpretation of these results will be given below.
ERP and MES are classified by Mittal et al. (2019) as IT-based production management information systems. Besides Frank et al. (2019) classified ERP and MES as SMTs that contribute to integration. ERP and MES are both technologies that are implemented with the same goal of integrating departments and getting a better insight into information (Ugarte, et al., 2009). Therefore, the characteristics of ERP and MES mainly overlap. This overlap and placement of ERP and MES lead to the fact that the characteristics regarding information availability and transparency cause the main changes in the work design of blue- and white-collar employees. Characteristics as information transparency, heterogeneous knowledge, and interoperability contribute to changes in four task characteristics. Research by Krivec & Guid (2020) indicates that new information availability and transparency for employees leads to different reactions and decisions by employees.
applications creates new tasks and requires learning new skills. This is typically an effect for blue-collar employees as these people have less experience working with computers and online systems.
White-collar employees experience more changes in autonomy and feedback, which is in contrast with blue-collar employees. This confirms what has been predicted in the literature because white-collar employees in manufacturing companies generally have more responsibilities and decision autonomy as blue-collar employees (Schreurs, et al., 2011). This difference remains the same after the implementation of MES and ERP because white-collar employees now have more and better insight into important information. Real-time access to, for example, stock quantity, costs, and utilization rate creates an opportunity for white-collar employees to provide more focused en substantiated feedback. The effects of information availability confirm the expectations based on the literature of Hartmut (2016).
Implications for theory & practice
This empirical research contributes to the current literature by giving insight into the underlying relationship between characteristics of SMTs and their effect on work design of blue- and white-collar employees. The characteristics regarding information availability and transparency are of great importance for the induced change in work design. For blue-collar workers this results in learning new skills, because of newly creating tasks. Besides, white-collar employees obtain a wider autonomy and obtain more possibilities to give feedback.
The insights in this underlying relationship can be of great usage for practical implications. Companies that are considering implementing MES or ERP, can use these insights to determine in which way employees could be prepared. White-collar employees can on forehand be trained in processing new and different data, how to handle wider autonomy, and the process of giving feedback. Blue-collar employees can be instructed that the way of working might change, which leads to different and new tasks. Preparation in time and emphasize that the change is important for the company, might help the adjustment of blue-collar employees.
Critical reflection and limitations
References
Auberbach, C. & Silverstein, L., 2003. Qualitative Data : An Introduction to Coding and Analysis. 1 ed. New York: New York University Press.
Barrett, D. & Twycross, A., 2018. Data collection in qualitative research. Evid Based Nurs, pp. 63-64.
Beard, J. W. & Summer, M., 2004. Seeking strategic advantage in the post-net era: viewing ERP systems from the resouce-based perspective. Journal of Strategic Information Systems, 2(13), pp. 129-150.
Cagliano, R., Canterino, F., Longoni, A. & Bartezzaghi, E., 2019. The interplay between smart manufacturing technologies and work organization International Journal of Operations and Production Management, pp. 1-29.
Cambridge dictionary, 2020. Cambridge dictionary. 4th ed. Cambridge: Cambridge.
Cordery, J. & Parker, S. K., 2012. Work Design: Creating Jobs and Roles that promote Individual Effectiveness. The Oxford Handbook of Industrial and Organizational Psychology, pp. 1-63.
Davis, J. et al., 2012. Smart manufacturing, manufacturing intelligence and demand-dynamic performance. Computers and Chemical Engineering, pp. 145-156.
Delagonare, L. S., Benitez, G. B., Ayala, N. F. & Frank, A. G., 2018. The expected contribution of Industry 4.0 technologies for industrial performance. International Journal of Production Economics, pp. 383-394.
Delattre, M., Ocler, R., Moulette, P. & Rymeyko, K., 2009. Singularity of Qualitative Research Tamara Journal, pp. 33-50.
Ferrer, B. R. & Lastra, J. L. M., 2018. Towards the encapsulation and decentralisation of OKD-MES services within embedded devices. International Journal of production research, 3(56), pp. 1286-1298.
Frank, A. G., Dalenogare, L. & Ayala, N. F., 2019. Industry 4.0 technologies: Implementation patterns in manufacturing companies. International Journal of Production Economics, pp. 1-27.
Frey, C. B. & Osborne, M. A., 2017. The future of employment: How susceptible are jobs to computerisation?. Technological Forecasting & Social Change, pp. 254 - 280.
Gorecky, D., Schmitt, M., Loskyll, M. & Zühlke, D., 2014. Human-machine-interaction in the industry 4.0 era. 2014 12th IEEE International conference on industrial informatics, pp. 289-294.
Hackman, R. J. & Oldham, G. R., 1976. Motivation through the Design of Work: Test of a Theory. Organizational Behavior and Human Performance, Issue 16, pp. 250-279.
Hartmut, H.-K., 2016. Digitization of industrial work: Development paths and prospects. Labour Market Res, pp. 1-14.
Jacobs, R. & Bendoly, E., 2003. Enterprise Resource Planning: Developments and Directions for OMR. European journal of operational research, 2(146), pp. 233-240.
Katerattanakul, P., Lee, J. J. & Hong, S., 2014. Effect of business characteristics and ERP implementation on business outcomes. Management Research Review, 2(37), pp. 186-206. Krivec, J. & Guid, M., 2020. The influence of context on information processing. International Quarterly of Cognitive Science, Issue 21, pp. 167-184.
Kus, A. & Pyplacz, P., 2019. The Importance of Information Management in the Context of Industry 4.0. Social Sciences, pp. 11-24.
Morgeson, F. P. & Humphrey, S. E., 2006. The Work Design Questionnaire (WDQ): Developing and Validating a Comprehensive Measure Assessing Job Design and the Nature of Work. Journal of Applied Psychology, pp. 1321-1339.
Parker, S. K. & Grote, G., 2020. Automation, Algorithms, and Beyond: Why Work Design Matters More Than Ever in a Digital World. Applied Psychology, 0(0), pp. 1-45.
Parker, S. K., Morgeson, F. P. & Johns, G., 2017. One Hundred Years of Work Design Research: Looking Back and Looking Forward. Journal of Applied Psychology, 3(102), pp. 403-420.
Parker, S. K., Van den Broeck, A. & Holman, D., 2017. Work design influences: A synthesis of Multi-level Factors that Affect the Design of Work. Academy of Management Annals, pp. 267 - 308.
Quiescenti, M. et al., 2011. Business process-oriented design of Enterprise Resource Planning (ERP) systems for small and medium enterprises. International journal of production research, 18(44), pp. 1797-3811.
Rauch, E., Linder, C. & Dallasega, P., 2020. Anthropocentric perspective of production before and within Industry 4.0. Computers & Industrial Engineering , pp. 1-15.
Schreurs, B. et al., 2011. Job demands-resources and early retirement intention: Differences between blue- and whit-collar workers. Economic and Industrial Democracy, 1(32), pp. 78-68. Sellitto, M. A. & Vargas, E. J. d., 2020. A method to align functionalities of a manufacturing execution system with competitive priorities. Journal of manufacturing technology management, 31(2), pp. 353-369.
Sims, H. P., Szilagyi, A. D. & Keller, R. T., 1976. The Measurement of Job Characteristics. The Academy of Management Journal, 2(19), pp. 195-212.
Ugarte, B. S. d., Artiba, A. & Pellerin, R., 2009. Manufacturing execution system-a literature review. Production Planning and Control, 20(6), pp. 525-539.
Wall, T. D. & Martin, R., 1987. Job and Work Design. International review of industrial and organizational psychology, pp. 61-91.
Yin, R. K., 2009. Case study research: Design and methods. 4th ed. s.l.:Sage publications. Zayati, A., Biennier, F., Moalla, M. & Badr, Y., 2012. Towards lean service bus architecture for industrial integration infrastructure. J Intell Manuf, Issue 23, pp. 125-139.
Zhang, Z. et al., 2005. A framework of ERP systems implementation success in China: An empirical study. International journal of production economics , 98(1), pp. 56-80.
Appendix A: Interview script
Section 0: Some notes on conducting the interviews:
● Introduce yourself, the research, and the purpose of the research. ● Outline the structure of the interview, and its duration.
● Explain the follow-up procedure (interview will receive a copy if required) ● Refer to informed consent form outlining (see example on google drive):
o Describe the purpose of the interview o Indicate the confidentiality of the interview
o Participation is voluntary, may stop interview or not answer any question o No foreseeable risk
o Get their signature, printed name, and date🡪 send to supervisor
Section 1: Background information
1.1. What is your role in the company, and your tasks & responsibilities? 1.2. Could you briefly describe your company in terms of:
• Industry
• Products and services
• Types of market served (B2B/B2C) • Number of employees
• Type of production processes
Section 2: Information on the smart manufacturing technology(ies)
2.1.Could you describe the smart manufacturing technology X and Y, and elaborate on: - the setting/context where they were implemented (replacing or augmenting what
processes, activities)?
- To which departments and functions does this technology relate to?
2.2.Which were/are the main objectives and motivations for adopting technology X and adopting technology Y?
2.3.How do you judge a good design and/or implementation of the (smart manufacturing) technology?
2.4.What are the ultimate criteria for success (of the implementation)? How do you meet these? (you could take each criterion in turn and probe how its achieved to see if work design is mentioned)
Section 3: Assessing work design changes
Generic questions about expected changes in work design of X.
› When the technology X/Y is finally in place, how might the work of [function X/your work] change?
Per expected change, inquire about the underlying mechanisms for the change: how exactly do you think will the technology X/Y induce the change?
› What are the new activities that [you / function X] will have to perform due to the adoption of technology X/Y
› Will [you/function X] perform more or less manual activities or cognitive activities such as monitoring/controlling, problem solving due to the adoption of technology X, Y? › Will [your job/function X job] be more cognitively demanding or simpler, why?
› Would you say that [your job/function X job] will be simplified or enriched as a result of technology X/Y, if so why?
› Will [you/function X] need to develop new skills as a result of technology X, Y? Which type of skills?
› Will people work in the same teams, and in the same roles or different ones? › Will there be new employees hired due to a change in required skills? What type of
employees? If yes, can you elaborate on this?
Zooming in the changes of the key dimensions of work
Autonomy (Timing, method and decision-making autonomy)
› To what extent will [your/function X] level of autonomy change?
› What control will [you/function X] have relative to the new technology X/Y?
› Will the technology X/Y change the discretion [you/function X] have in deciding on how you plan/schedule your work? How?
› Will [you/ function X] still be in control and take many decisions? Which type?
› How will the new technology X/Y change the freedom [you/function X] have in deciding how you/he do your job (e.g. what method you apply)?
Skill variety
› Will the variety in skills [you/function X] need to do his/ her job change? Why? Task variety:
› How will [your/function X] variety of tasks change due to the implementation of technology X/Y? Why? What type of tasks are replaced/created/augmented? Interaction with others
› What about social interaction, how will technology X and Y change the way [you/function X] interact with other team-members and team-leaders? Why?
Dependency
› How will technology X/Y change the way [you are/function X] is dependent on the work of others for the completion of your work? Why>
Feedback from the job
› [Will you/function X] receive more and better feedback from the machine/system about your performance? Why?
Feedback from others
› Does the new technology X/Y change the amount of feedback [you/function X] receive from your peers/supervisors? Why?
Job demands
› To what extent did [your/function X] job demands change due to technology X, Y? Why? Problem solving demands
› To what extent did the technology change the way that [you/ function X] needs to be creative, and solve problems that have not occurred before? Why?
Task significance
› To what extent did the task significance change (i.e. the results of your work affects the life of others? Why?
Appendix B Concise overview findings
Characteristics Technologies Blue-collar White-collar Blue-collar White-collar Blue-collar White-collar Blue-collar White-collar Blue-collar White-collar
Autonomy Feedback Different tasks because of new devices and applications Different tasks because of new devices and applications Work Design Flexible system creates a possibility to do tasks at different locations Possibility to get acces to system from different locations increases autonomy More decision possibilities because of new information Usage of new data, requires different skills
Tasks are added, more checking and controlling data Because of more information, more autonomy More information, wider autonomy Decision making possible, regarding the understandble data Wider autonomy, as more and understandable data is available
Task variety Task identity Task significance
ERP & MES
ERP & MES
ERP & MES
MES
ERP & MES Interoperability Flexibility Heterogeneous knowledge Information transparency IT-driven Integration between departments, more information, wider autonomy Substantiated feedback, because of more information from departments Direct feedback
from the system
More information insight, better focused feedback possible Better insight in data, more focused feedback Integration requires different tasks and therefore new skills Integration between departments, gives more acces to information, and creates different tasks
Appendix C: Quotes characteristics smart technologies
ERPIT driven “The goal is to use monitors on the shop floor that shows the needed
information for that production process. These new devices might be a big change for the employees there.”(Company I, company director)
Information transparency
“It is one of the main goals of the whole system. That you have better and faster insight in useful information” (Company I, owner & director)
Heterogeneous knowledge
“ The insight and good information about stocks is important. This information can be used for decision making regarding stock levels. This system can provide all data in a useful dashboard.” (Company I,
company director)
Interoperability “It is a very crucial system, the backbone of the company. It is so
important these systems, you need to have knowledge about them, and how these system integrate the departments.” (Company I, owner & director)
MES
IT driven “Systems are more connected with each other, with the new technologies
this became possible and we want to use it as much as possible.” (Company F, operational manager)
Information transparency
“The amount of information available helped us to get a better view on what products needed to be made and where made, where are the raw materials and which operators has to overview which production lane” (Company B, manager technical services)
Heterogeneous knowledge
“The most important mechanism for change for us was the information flow. Since the systems were implemented a vast amount of information was gathered and used to improve production speed and quality.” (company B, manager technical services)
Flexibility “We can track the production process from a distance, this gives us the
flexibility to manage the system from our office” (Company F, operational manager)
Interoperability “MES is the link between the information from M2M information that
