Catálogo de publicaciones - libros

The objective of this paper is to provide Supply Chain Management (SCM) researchers with an example of how to conduct empirical research using two different methodologies (case studies and surveys). The paper examines the methodology used to investigate a particular SCM topic: the SCM-performance relationship. The research design will be outlined and used to carry out the investigation as an illustration of how case studies and surveys can be used as complementary methodologies. These methodologies will be described, along with their role within the research and the contribution they were able to make to the investigation. A summary of the main advantages and disadvantages related to each one of these methodologies will be provided as well.

Supply chain relationships are impacted by the use of the Internet and the transformation through its technologies (Bak, 2004). Although an area of growing interest, little research has focused on the impact of the Internet and on understanding how different approaches for creating supply chains are suitable for different supply chain requirements (Pant et al., 2003). Similar to MacPherson et al. (1993) and Sherif & Vinze (2003), a case study research method with grounded theory approach was used. The findings of the case study (Phase A), the so-called derived theory, allowed the researcher to establish a follow up questionnaire for a second investigation (Phase B) in similar settings with a wider spectrum. In this study, blending was particularly helpful in eliciting the controversial findings and proved to be a useful source.

This paper will outline some basic issues on action research. It aims to provide an overview of the development of action research methodology. In this context, scientific theoretical discussions play an important role. Action research is less used in supply chain management research when compared to other methodologies. Against this background, it will also be discussed what approaches are used for problems and perspectives for using action research in supply chain management. Action research has a special philosophy of science background, namely that this is not the preferred science philosophy in supply chain management or operations management. The use of action research causes problems, but so does the use of other research methodologies. Therefore, there are a lot of opportunities to create knowledge by using action research.

Increasingly organizations have to identify and implement improvement initiatives in an inter-organizational context. Implementing collaborative improvement is fraught with difficulties that encompass a wide array of intra- and inter-organizational change issues and working practices. In order to overcome these difficulties, explicit attention should be paid to the accumulation and development of knowledge and to the long-term development of a capability for learning and continuous improvement between organizations. This paper describes the application of an Action Learning and Action Research approach in collaborative improvement within an Extended Manufacturing Enterprise in the Netherlands.

Companies are perceived as important actors in the drive for sustainability. Linked to this and in response to increasing demands from various stakeholder groups, companies start to look at their supply chain to enhance their overall sustainability profile. Reasons for these two major issues can be identified: (1) focal companies are held responsible for environmental and social problems caused by their suppliers, which becomes more and more important as (2) an increasing share of value is created at the supplier level. In response to such demands, companies have to find ways to incorporate environmental and social aspects into their supply (chain) management. Therefore, environmental and social standards are set up in supply management by amending the purchasing processes. This paper presents an approach to integrate social and environmental standards extensively into supply management at a focal company. Therefore, action research (AR) was used as the research methodology to identify the required changes of the sourcing structures and present possible options for the company to do so.

This paper illustrates the basic approach, structure and development path of a diagnostic instrument that integrates existing approaches of systemizing, structuring and thus elaboration of the core of supply chain management (SCM). The main purpose of this computer-aided tool is the quick indication of weak spots within supply chain enterprises. But this self diagnostic is not the focus of this paper. More interesting is the side effect of gaining feedback from diagnostics sessions. While answering diagnostic questions, users are confronted in a systematic way with concrete challenges and principles of SCM. Their industries, supply chain stages as well as the answers are documented in standardized data records. So the tool can provide useful data regarding the state of implementation and differences in key challenges for different players in different supply chains. Separate studies on potentials, obstacles and realization of SCM principles as well as existing scientific publications on design principles, interviews with industry experts, and the experiences of the concerned consulting and research institutions have been used as input in the development process of the self diagnostic instrument.

Most practical and theoretical approaches to port performance measurement are reducible to three broad categories: physical indicators, factor productivity indicators, and economic and financial indicators. However, an integrative supply chain approach is seldom adopted, although a change process towards supply chain integration is taking place in practice and new appropriate performance measurements are required. Action research enables researchers to participate in this change process, although it requires a close relationship and collaboration between practitioners and researchers. The technique used in the approach described in this paper was to present port managers and other experts with a model of port performance appropriate to the role of ports in a logistics and supply chain context.

Various papers have been published that define requirements for theory development in operations management or try to connect the knowledge generated along the different research lines. Here, we define the scope of supply chain management research and its relationship with operations management research. We show how quantitative model-driven research - especially under consideration of empirical data and simulation models - can be conducted in supply chain management research because this research type holds great potential for advancing theory. Furthermore, we illustrate our ideas via some selected research examples.

Simulation offers a middle ground between pure formal modeling, empirical observation and experiments for strategic issues in supply chain research. Although simulation models are formally specified, they are not limited to analytically solvable equation systems. Additionally, simulation approaches provide the possibility to include estimations of not easily measurable “soft” factors. The inclusio such variables increases the real world relevance of simulation studies, similar to empirical investigations. Thus, strategic simulation experiments try to combine the clarity and generality of mathematical modeling with the practical relevance and external validity of empirical research. The approach is demonstrated by a combination of system dynamics and agent-based simulation, two approaches that achieved high significance for the modeling and simulation of socio-economic systems. With the help of a simulation prototype we are able to test the stability of supply chain structures under different levels of uncertainty regarding future events, particularly changing demand.

This paper stems from a cross-fertilization research project aimed at exploring to which extent modeling methodologies and tools that are used in engineering fields could be suitable to solve management problems. A powerful object-oriented modeling language used in those contexts, Modelica, is carefully presented, and its most innovative features are discussed. Then, a very demanding management problem, namely that of understanding Supply Chain Dynamics and controlling the Bullwhip Effect, is addressed. A prototypal application of Modelica is presented in order to evaluate the capability of this language to be applied in the field of Supply Chain Dynamics analysis.