Chapter 6 EVALUATION
6.6 Measurements and Data Collection
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6.6 Measurements and Data Collection
In this chapter we will expound data gathering on BlockFarm and correlative variables mapping to our measurement proposed in Chapter 4. We estimate to monitor user’s behaviors on the system for improving our system lasting about two weeks, the result will be transformed into our measurement during the session of data collection.
For providing better user experience to our players and becoming more persuasive of our theory, system updating of BlockFarm will keep making based on the feedback data arrangement.
6.6.1 Measurement of Critical Mass
Critical mass is the kernel of this research, which contains two sides of concept:
benefits and costs (show in Formula 4.4.2, The Function of the Fulfillment of Critical Mass). Data of benefit is the anticipation and the sense of marketing from service designers, besides, data of cost includes four different perspectives of obstruction which are participants’ ability, monetary cost of participants, acquisition cost, and barriers to entry, and both of them are measured by our assistant module.
Phase 1: Data Fetched by Designer and D3 Accelerator Assistant Module.
In this application of BlockFarm, the invested funds and the anticipative revenue is evaluated and determined by our project members that we will explain in Chapter 6.7.
On the other hand, cost measured by our assistant module correspond to the variables as follows:
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1. Participants’ Ability:
It is mapping to the variables of willingness to provide and collective efficacy in Degree of Operant Empowerment. By reason of willingness to provide refers to all smart properties the participant owned and are ready to contribute to the digital ecosystem, including their real assets and capabilities.
When reaching collective efficacy means participants are willing to do more efforts than they must to for improving the environment of digital ecosystem and the sustainable conditions. These two measurements are correlate with the concept of participants’ ability proposed in our research.
2. Monetary Cost of Participants
Monetary cost is also and anticipation made by service designers in order to equilibrate the present benefit. Notwithstanding services are often free to users in the digital world, they are not always acquiring without charging anything especially for some services that are developed to make profits. Consequently, we think our service designers should consider about redressing the balance of the shortcomings of charging and the realism of ecosystem sustainability. Accordingly, we ponder over the implementation cost, the unfamiliarity of blockchain application and the destination of BlockFarm during design thinking, we determined not to charge monetary cost from our players yet. However, we will still possibly charge to our participants while BlockFarm is no longer a gamification application of blockchain.
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In our proposition, acquisition cost is resembling to the opportunity cost of not taking part in the designed ecosystem. In this circumstance, the variable of searching volume proposed in the degree of desirability of Completeness Operant Configuration can best represent the opinion of it. The degree of desirability is an evaluation which refers to the share of voice according to google trend. By virtue of google is the first searching engine in the world, we use the tendency that people all over the world pay attention to and desire for on purpose of standing for the opportunity cost of people who refuse to join the ecosystem.
4. Barriers to Entry
Barriers to entry is the opposite to acquisition cost, it means people are willing to participate in the digital ecosystem but is blocked from the enter barriers. They often take place when the manipulation is too complicated or the service design is not friendly enough to the public. Correspondingly, the variable of complexity of interaction in the Operation Flow of Linkware Design can best symbolize the measurement of the obstacles made by the unfriendly design.
Phase 2: Calculate Network Effect Level and Critical Mass by formula.
After two-weeks data gathering from designer and the D3 Accelerator Assistant Module which collecting data from system fetched and players’ feedback, we had collect 75 sample size of raw data using for calculation. The function of measuring arising level of network effect factors and critical mass are proposed in Chapter 4, Formula 4.4.1 and Formula 4.4.2, and our system will measure the arising level of
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network effect factors to see the correlation between it and the fulfillment of critical mass based on the computing result.
Formula 4.4.1
Formula 4.4.2
6.6.2 Supervisory of Interaction between D3 Accelerator Assistant Module
In accordance with the conceptual framework shown in figure 4.1, we had declared that there are interrelationships between our D3 Accelerator Assistant Module (Figure 6.6.2.1). After data fetching and the measurement of critical mass, we have to monitor the interactions between each dimension of the assistant module for the purpose of giving designers feedback about how to improve their digital ecosystem, and whether to ameliorate the mechanism design of digital ecosystem, the function development, the system delivery, the user interface, or the user experience, etc. as first priority under limited budgets. Moreover, we will also pay more attention to justify if there are surely no negative effects between those dimensions, and all of them are definitely related to reaching critical mass.
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Figure 6.6.2.1 Correlation between D3 Accelerator Assistant Module