Suppose a research study is conducted in a region known for its beautiful lakes, and the local government is considering a policy to improve the management of these lakes. The government wants to understand how the local community values different aspects of the lakes’ ecosystem services, specifically focusing on water quality and recreational activities.

In this DCE, the researchers would create hypothetical scenarios describing different alternatives that represent various combinations of attributes related to water quality and recreational activities. The attributes could include factors such as clarity of the water, presence of fish and other aquatic species, availability of boating facilities, and access to picnic areas. Each scenario would present a specific combination of attribute levels. Below is an example of the key components used in this approach.

    1. Attributes: Attributes are the characteristics or features that describe the different aspects of the lakes’ ecosystem services. In this example, the attributes include:
      1. Water clarity: This attribute represents the visual quality of the water, ranging from clear to murky.
      2. Fish and aquatic species: This attribute indicates the abundance or presence of fish and other aquatic species, ranging from abundant to limited.
      3. Boating facilities: This attribute reflects the availability or absence of facilities for boating activities, such as boat docks or rentals.
      4. Picnic areas: This attribute represents the accessibility or non-accessibility of designated areas for picnics.
    2. Levels: Levels are the specific values or states that each attribute can take. In the example, the levels for each attribute are:
      1. Water clarity:
        1. Clear.
        2. Murky.
      2. Fish and aquatic species:
        1. Abundant.
        2. Limited.
      3. Boating facilities:
        1. Available.
        2. Not available.
      4. Picnic areas:
        1. Accessible.
        2. Not accessible.
    3. Choice Sets: Choice sets are the hypothetical scenarios presented to the respondents. Each choice set comprises a specific combination of attribute levels. In the example, a choice set could be:
      1. Choice Set 1:
        • Option A: Clear water, abundant fish and aquatic species, boating facilities available, picnic areas accessible.
        • Option B: Murky water, limited fish and aquatic species, no boating facilities, no picnic areas.
      2. Choice Set 2:
        • Option A: Clear water, limited fish and aquatic species, boating facilities available, picnic areas accessible.
        • Option B: Murky water, abundant fish and aquatic species, no boating facilities, picnic areas accessible.
      3. Choice Set 3:
        • Option A: Clear water, abundant fish and aquatic species, no boating facilities, picnic areas accessible.
        • Option B: Murky water, limited fish and aquatic species, boating facilities available, picnic areas accessible.
      4. Choice Set 4:
        • Option A: Murky water, abundant fish and aquatic species, boating facilities available, no picnic areas.
        • Option B: Clear water, limited fish and aquatic species, no boating facilities, picnic areas accessible.

The respondents would be asked to choose their preferred option (A or B) or rank the options according to their preferences.

    1. Experimental Design: The experimental design refers to the plan for creating and presenting the choice sets to the respondents. It includes considerations such as the number of choice sets, the order in which they are presented, and potential variations in attribute levels. The design aims to ensure the efficient and accurate estimation of respondents’ preferences. The specific details of the experimental design would depend on the research objectives, sample size, and other factors.
    2. Analysis: The analysis of the DCE data involves examining the choices made by the respondents and estimating the relative importance of the different attributes. Various statistical models can be used to quantify the preferences and estimate the economic value associated with each attribute level. The analysis aims to derive insights into the trade-offs individuals make and the economic significance of different ecosystem service attributes.

Overall, the DCE example provided incorporates attributes representing water quality and recreational activities, with corresponding levels for each attribute. Hypothetical choice sets are created, and respondents’ choices or rankings are collected. The experimental design ensures an organized presentation of choice sets, while the subsequent analysis employs statistical models to estimate preferences and attribute values.

It’s important to note that the specific details of the attributes, levels, choice sets, experimental design, and analysis can vary depending on the research context and objectives. The example provided serves as a simplified illustration of the key components involved in a DCE within the TEEB framework.

By collecting responses from a representative sample of the local community, the researchers can analyze the choices made and derive insights about the relative importance of different attributes. For instance, they can determine how much value people place on water clarity, the presence of fish and aquatic species, availability of boating facilities, and access to picnic areas. This information helps to understand the trade-offs people are willing to make when it comes to lake management and conservation, and provides policymakers with valuable data for decision-making.

By: Nazrul Efendy Bin Noordin