Research question and methodology selection

Generally, research is based on qualitative, quantitative or a combination o f these techniques. As discussed in the previous section, the research philosophy position will influence the methodology chosen for the research. In addition, the research questions and research objectives also contribute as factors to the methodology decision (Frankel et al., 2005; and Ellram, 1996). Thus, this section provides an overview o f the selection o f the methodology to address the research question described in Section 1.4.

i) How is the supply chain process carried out in the healthcare industry in the context of developing countries’ private healthcare, especially in Malaysia? Can the Inventory Routing Problem approach be used to improve supply chain operations?

Ellram (1996) states that the case study methodology is suitable for answering the

‘how’ and ‘why’ questions in both exploratory and explanatory research. On the other hand, quantitative methods like the survey or secondary data analysis need to be used

in order to answer the ‘how much’, ‘how many’, ‘w ho’, ‘w hat’ and ‘w here’ questions in explorative, descriptive and predictive research.

Therefore, the case study approach is chosen as the method to explore the existing supply chain process in the case organization, since the research endeavours to answer the ‘how’ question. Moreover, additional information and a better understanding o f the performance o f the current policies can be obtained via secondary organisation data analyses.

This study is also interested in investigating the potential o f implementing the IRP approach in the Malaysian healthcare industry, to manage several clinics in one organisation. Generally, previous research in the IRP area has mostly determined a solution for the gas industry, (Bell et al., 1983; and Campbell and Savelsbergh, 2002).

The benefit o f the centralised decision making that integrates two important elements in the supply chain has motivated other researchers to expand the application o f the IRP to other industries. According to Meredith (1998), the case study strategy can be used as an early exploratory investigation where the variables are still unknown and the phenomenon not yet fully understood. The case study is therefore considered to be the best strategy to investigate existing supply chain processes, evaluate the problems that occur as well as identify the improvement strategies needed to overcome the problems.

Furthermore, the information on the general healthcare supply chains in Malaysia and improvement supply chain strategies that exists in the healthcare supply chain is reviewed from the literature. The sources o f the literature and the design o f case study that appropriate for this research are discusses in detail in Section 3.5.1. and 3.5.2 respectively.

ii) How should the parameters in the Inventory Routing Problem be set?

How should the supplier decide on which retailers should be replenished during each replenishment period?

The various replenishment approaches to solve the Inventory Routing Problem that used by previous researchers are examined from the literature. Nevertheless, the

review o f the appropriate replenishment procedures to be implemented has also considered the joint replenishment approach as this could be used to solve the multi­

item problem for a single location. Furthermore, the appropriateness o f the inventory control policy to be adopted in this thesis also taking into account the suitability o f the case study organisation based on their supply chain environment.

It has been found that the periodic “can-order” policy is the best approach to solve the multi-items problem. This concept seems appropriate as a new replenishment policy for IRP gives flexibility for the supplier to consolidate the replenishment among retailers. Therefore, the characteristic o f the new IRP model including the parameters and the condition that triggered the replenishment are evaluated based on the “can- deliver” policy concept in the literature and the analysis in the organisation.

iii) How does the proposed policy perform in the single item multi­

retailer case? How do the variables influence the result?

Analysis o f the new IRP policy is carried out using quantitative methods. Quantitative modelling in operations management is appropriate for understanding the causal relationship between control variables and the performance variable o f the model.

Further, these approaches are able to examine the behaviour o f the suggested policies under different scenarios and quantify the best solution that optimises the performance measurement in either the physical or economic aspects o f the model.

Bertrand and Fransoo (2002) categorise model-based quantitative research as axiomatic and empirical research, since both can be classified as descriptive and normative/prescriptive research. Axiomatic normative (AN) research is a typical type o f model-based quantitative research in the Operational Research field. The AN research is primarily concerned with finding the best solutions for improving previous research or solving a newly defined problem as a scientific contribution to the existing knowledge (ibid).

Similarly, Ragsdale (2004) categorised mathematical models into prescriptive, predictive and descriptive categories based on the characteristics o f the mathematical function and independent variables o f the problem. Table 3.3 shows the difference

between the three model categories and suitable management science techniques for

In contrast, Beamon (1998) eliminated the optimisation model and categorised the analytical model into two different categories, namely, deterministic analytical models and stochastic analytical models and introduced economic models as a new category in multi-stage models for supply chain design and analysis. The supply chain’s taxonomies discussed in Min and Zhou (2002) also included hybrid models which contain both deterministic and stochastic elements and IT-driven models as a result o f growing IT software usage in modelling the supply chain.

With regard to the modelling process, Law and Kelton (2000) indicate that the relationship between variables for a simple problem may be modelled to obtain an exact solution using analytical mathematical methods such as calculus and probability theory. However, a simulation method is more appropriate to model and solve a complex system numerically using a computer. According to Harrell et al. (2003), the complexity o f the system is related to the interdependencies and the variability factors. Duncan (1972) refers to the environmental complexity based on the number

and interdependencies o f the environment variables. Figure 3.2 shows the relationship between the analytical difficulty and the level o f complexity as illustrated by Harrell et al. (2003). It can be seen from the figure that an increasing number o f interdependencies and uncertainty levels in the system raises the level o f analytical difficulty exponentially.

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Number o f interdependencies and random variables

Figure 3.2: The relationship between analytical difficulty and the number of interdependencies and random variables (Source: Harrell et al., 2003)

It has been suggested by Ragsdale (2004) that the simulation approach is more useful for studying stochastic inventory control since the solution to determine an optimal ordering level, time, and quantity is not possible to express just using a simple formula. Banks et al. (1999) also state that simulation is an appropriate tool for studying an internal interaction in a complex systems or subsystems. Banks et al.

(1999) also contend that simulation is suitable for identifying an improvement in the system under study. It is also able to determine the consequence o f implementing a new design or approach to the system as well as provide valuable insight into the systems regarding the effect o f each variable and highlight those variables most likely to have a large impact in the systems (Ibid). Chang and Makatsoris (2001) also report that supply chain simulation is beneficial for the organisation to carry out what-if analyses by testing different alternative improvement strategies and identify the impact o f the changes without interrupting the current process. Moreover, Terzi and Cavalieri (2004) state that simulation is a powerful method among other quantitative methods for supply chain decision making. Similarly, Law and Kelton (2000) indicate that simulation is among the most common techniques used in operations research and

management besides mathematical programming and statistical techniques. The growing trend o f simulation usage by various industries to redesign and improve their existing system proves that the simulation is a practical tool for studying the supply chain (Chu, 2003).

Accordingly, the simulation model is adopted in this thesis to address this research question. Simulation is capable o f evaluating the behaviour o f the proposed IRP model to various input factors. The comparison of a new improvement strategy with other inventory policies can also be simply obtained via simulation by updating the model configuration. The detail on simulation model is discusses in Section 3.6.

iv) How should the routing strategy be incorporated into the IRP model to reduce cost, improve vehicle effectiveness, and reduce energy consumption?

The simulation model is expanded to evaluate the impact o f different vehicle effectiveness strategies on the IRP model. The appropriate vehicle effectiveness strategies to include in the analysis are reviewed from the literature. Similarly, the literature is the primary source to develop new transportation cost function in the IRP model that considers minimizing a route based cost to yield a minimum energy consumption and high vehicle effectiveness.