In progress Optimizing work environments at small companies for business performance and employee well-being: Ability, motivation, and opportunity to do so and the role of governments

Reference:
ERIM PhD 2015 RSM LIS SCM1

Abstract

Ideally, one would have a work environment that is good for employee well-being and business performance. Although one might interpret this as if it is a trade-off between employee well-being and business performance, evidence indicates that there actually can be a win-win situation. That is, a work environment that is simultaneously good for employee well-being and for business performance. However, if this is true, why are there still work environments that impose significant risks on the well-being of employees? The first aim of this PhD project is to find an answer to this question. Thus, examine why some companies organize the work environment such that it has positive effects on both employee well-being and business performance, and others do not. The second aim is to examine whether governments should regulate or deregulate for optimal employee well-being and business performance. To unravel these issues, we will relate employee well-being and business performance to the ability, motivation, and opportunity of companies. Moreover, we will investigate whether governmental affects the ability, motivation, and/or opportunity of companies. The main study of this PhD project is a 2-year monitoring of about 60 companies from the Dutch metal industry.

Keywords

Employee well-being; Business performance; Work environment; Governmental regulation

Time frame

2015 - 2019

Topic

The following subthemes are distinguished within the theme Supply Chain Management: (i) Sustainability and Supply Chain Optimization,

(ii) Terminal Optimization, (iii) Transportation, (iv) Purchasing and Supply Management, and (v) Behavioural Operations. These five subthemes are described in the following sections, together with a number of example Ph.D. projects.

 

Subtheme: Sustainability and Supply Chain Optimization

The research on Sustainability and Supply Chain Optimization focuses on developing analytic approaches to improve economic and environmental performance of supply chains. According to Cradle to Cradle principles, closing material and product loops is essential for reaching true sustainability, and this calls for radical innovations in the supply chain. This in particular requires the integration of the forward chain with the service and reverse chain. Smarter use of existing resources and processes in the forward chain and avoiding material and energy need altogether leads to important gains in terms of economic and ecological footprints. This subtheme also includes the mathematical analysis of methods for supply chain optimization. Example projects are the following:

 

  • Coordinated supply chain internalisation of external costs of transportation logistics. For various reasons, companies are progressively involved in voluntary or regulated programs that aim to reduce the negative externalities of their logistics activities. The reduction of (carbon) emissions has received particular attention. While some programs are regulated, such as the sulphur emission limits for maritime shipping in worldwide Emission Control Areas, other programs are voluntary, such as the supply chain wide emission reduction programs initiated by OEMs (e.g. Mattel, SCA) and retailers (e.g. Walmart, Tesco), and the Environmental Shipping Index proposed by the World Port Climate Initiative. In supply chains, the reduction of negative externalities needs to be coordinated, as the associated investments and returns are not distributed evenly. The proposed research will consider quantitative modelling of supply chain coordination problems between multiple organisations associated with voluntary and regulated programs with an emphasis on emissions and the role of ports in logistics networks. For further information: prof.dr. Rob Zuidwijk: rzuidwijk@rsm.nl.
  • Smart auditing of supply chain data. Companies operating in the supply chain continuously collect data about their internal operations and external environment. One of the most important functions of Business Intelligence in risk assessment is its powerful analytics for detecting business exceptions, as a detective measure in risk management. Smart environments store supply chain business data in large volume, but information overload may confound the human decision maker from realizing the true status of the system, causal relationship between exceptions, and the effect of treatment measure. To avoid this, managers aggregate the data into business reports. When analyzing the report, the manager is looking for extreme or exceptional items, tries to find out the underlying causes, and decides for further controlling actions. This is done by business analytics, i.e. reversing the process of report generation, drilling down in a managerial model, or using additional knowledge possibly from external sources. In this project we want to develop new methods for smart auditing supply chain data to support managers in checking compliance rules, identifying rare patterns and finding underlying causes. For further information: prof.dr. Hennie Daniëls: hdaniels@rsm.nl.

 

Subtheme: Terminal Optimization

The research on Terminal Optimization focuses on developing theories, and quantitative optimization models and tools to improve the design, operations, and planning and control of terminal processes. Such terminals include warehouses, port and railway terminals, and trans-shipment centres with the related material handling systems. Our research resulted into insight into the relations between layout, storage strategies, order batching, and picker routing methods. The developed design principles (layout, system selection) are currently used by several warehouse design companies. An example project is the following:

 

  • Stochastic models for the design of automated warehousing systems. Complex automated warehousing systems require sophisticated stochastic models to adequately describe and predict the consequences of variability in processes like picking, transporting, sorting, and buffering. These models have proved their value in supporting practical operations and decision making in, for example, warehouse layout, order scheduling, and product storage. In this project we aim to make a big leap forward in the development of stochastic models, and in particular queuing models, for the design of automated warehousing systems and their interfaces with manual processes. The proposal focusses on the study of stand-alone components, such as storage and retrieval systems, as well as complete warehousing concepts, such as dynamic picking systems, or combinations of picking and sorting systems in interaction with manual processes. Ultimately we envision a hierarchical modelling approach: the results of the stochastic models will provide input to the optimization of the warehouse design. For further information: prof.dr. René de Koster: rkoster@rsm.nl.

 

Subtheme: Transportation Management

The aim of the research on Transportation Management is to improve the performance of passenger and cargo transportation systems, usually based on the application of simulation and mathematical optimization methods. Within the Smart Port program, research is carried out focusing on improving the transport connections between the Port of Rotterdam and the Hinterland via rail and barge, and on security and compliance in international transportation. Furthermore, due to our close cooperation with Netherlands Railways (NS), much research focuses on optimization of railway systems. Specific topics of this subtheme include robustness and reliability of transportation systems, fleet composition, city distribution, the effective use of information, and revenue management.

Example projects within this subtheme are the following:

 

  • Passenger oriented disruption management in public transport: This project focuses on disruption management in public transport, where the aim is to uphold as much as possible service for the passengers in disrupted situations. The project aims at understanding how passenger behaviour can be used as input and possibly be influenced in such situations, so that the remaining system capacity can be utilized most effectively. Real-time disruption management strategies are developed based on mathematical optimization models for rescheduling the timetable, and the vehicle and crew schedules. Passenger behaviour is studied based on Big Data sources like smart cards. This project is carried out in close cooperation with Netherlands Railways, and builds upon the earlier research carried out in this area. For further information: prof.dr Leo Kroon: lkroon@rsm.nl.
  • Punctuality in public transport: Public transportation in cities is subject to strict regulations regarding the punctuality of the services rendered. Depending on the concession, charges due to failing to meet punctuality agreements may be substantial. Though punctuality is equally required for regional and urban transportation, public transportation in urban contexts is typically affected by a myriad of city-related factors. Deviations from timetables may be caused by events, like congestion, road construction or car accidents. In other cases, these deviations have more subtle origins related with social events, school outings, tourism, or weather conditions. On a more structural note, punctuality of public transportation may be influenced by changes in the social configuration of neighborhoods due to, for instance, aging or wealth. The aim of this project is to develop a structural approach to monitoring punctuality, to identify causes for punctuality breaches, to forecast punctuality based on variations in urban conditions, and to develop approaches for improving punctuality. For further information: dr. Jan van Dalen: jdalen@rsm.nl.
  • Big data in traffic and transportation: Traffic and transportation processes generate massive amounts of operational data. The potential of these data often goes beyond straightforward monitoring, considering their use to actively manage capacity, influence behavior, analyze patterns, describe present states, or forecast future developments. The realization of these potential benefits is less straightforward, as it requires investments in a proper data infrastructure, advanced skills in business analytics, and a clear view of business strategy, which can be prohibitive, even for larger companies. The aim of this project is to develop big data applications in traffic and transportation. Prominent examples are the use of automatic detection devices and electronic trade documentation to infer the utilization of the traffic infrastructure or to detect improper container contents. For further information: dr. Jan van Dalen: jdalen@rsm.nl.

 

Subtheme: Purchasing and Supply Management

Our research on Purchasing and Supply Management focuses mainly on relational and contractual governance in buyer-supplier relations, and on purchasing strategy. The domains where we study these processes have been extended from manufacturing sectors to the public and service sectors, where for instance research is currently conducted on the use of performance-based contracts in healthcare and public infrastructure, and its impact on product and process innovation. Example projects in this theme are the following:

 

  • Performance-based contracting in service triads. Recently there has been an increasing interest in outcome-based or ‘performance-based’ contracts both in practice and in the academic literature. Traditional contracting literature, however, has focused on the context of a dyadic buyer-supplier relationship. Little or no research has been done on performance-based contracting in triadic relations, where a buyer contracts a supplier to deliver services to the buyer’s customers. This project uses and extends prior literature, in particular classical transaction cost, agency and management control theories, and the emerging literature on inter-organisational triads, to study the antecedents and effects of contractual and relational governance, in the specific context of performance-based contracts in buyer-supplier-customer triads. For further information: prof.dr. Finn Wynstra: fwynstra@rsm.nl.
  • Performance-based healthcare procurement. In many countries, healthcare spending is on the rise and projections of spend seem to indicate that current healthcare systems are unsustainable in the long run. Policymakers in various countries are looking for ways to make high quality and accessible health care services available to their citizens against affordable public and private costs. Some countries, like the Netherlands and the United States, have chosen to implement a system of regulated competition, in which healthcare purchasing is separated from healthcare provision. The idea is that healthcare providers compete to deliver healthcare services to the people that are represented by the healthcare purchasers (e.g., insurance companies or employers). Healthcare providers compete on a combination of quality and price, and are incentivized to provide high quality care at a competitive price. This project investigates how incentives for cost containment, quality and accessibility can be designed in the pre-contractual and post-contractual phases of the healthcare procurement process. For further information: dr. Erik van Raaij: eraaij@rsm.nl.

 

Subtheme: Behavioural Operations

Our research in Behavioural Operations Management focuses on the impact of human factors on company performance, next to planning and control systems. We study the role of humans (managers, workers) in operational processes, in particular the effects of systems design, organizational climate and leadership on worker behaviour, well-being and performance, including innovation. We study leader behaviour, decision making, and implied worker behaviour in interaction with systems, in contexts relevant to society. Example projects in this subtheme are the following:

 

  • The impact of behaviour on operational performance. Recent research suggests that behavioural aspects play a major role in achieving company performance, e.g. in the areas of worker productivity, safety, and job satisfaction. In this research we want to study the impact of incentives, personality, motivational factors, and management style on worker behaviour and company performance, in particular in warehouses and in transport. The research will be carried out in close cooperation with a number of companies. We aim to conduct experiments and carry out in-company research. In a first experiment we want to find out the impact of incentives and forklift driver personality on driver behaviour and warehouse operational performance. For further information: prof.dr. René de Koster: rkoster@rsm.nl.
  • Team decision making and performance: A behavioural study of the Sales & Operations Planning process. The Operations Management (OM) field witnesses a rapidly growing interest in behavioral research, but virtually all studies focus on individual decision-making. How teams make decisions is largely ignored – which is remarkable because operations and supply chain management decisions (sales & operations planning processes) are typically made in teams. Our research focuses on identification and analysis of cognitive and motivational biases that play out in sales & operations planning, including regulatory focus (a yet uncharted area in behavioral OM) and investigates the power of team reflexivity – the extent to which teams reflect on and modify their functioning – to mitigate such biases. For further information: dr. M. Schippers: mschippers@rsm.nl.
  • Online goal-setting intervention enhances student retention and academic performance. The current project will use an online intervention that has shown to be been extremely successful in raising academic performance and retention rate of students. Especially clearly defined and articulated goals give students purpose and meaning. In the current project, we aim to advance our understanding of these effects by investigating (a) specific changes in student behavior as a result of participating in this program and (b) the extent to which the program enhances academic performance of students in a problem-based learning context, and (c) the testing and implementation of an advanced goal-setting app developed for high-school students. For further information: dr. M. Schippers: mschippers@rsm.nl.

Supervisory Team

Alex Burdorf
Alex Burdorf
  • Promotor
Jan Dul
Professor of Technology and Human Factors
  • Promotor