Ability  to  Form  and  Process  Mental  Knowledge

國

立 政 治 大 學

‧

N a tio na

l C h engchi U ni ve rs it y

Figure 4.1 Conceptual Framework of this research

4.1.1 Ability to Form and Process Mental Knowledge

As we discussed before, when building up a concept map to framing the design situations, designers are actually manipulating their mental imagery trying to make sense of the data. It’s a new knowledge creating process and we will examine this process from two perspectives.

One is the ability to make association; another is the synthesis process, namely, combine what people see with what they already know.

Arrows (1): The nodes on the mind map can be seen as frame parts that construct the whole frame whereas the links between nodes are the relations of the connected frame parts. In order to examine the ability to process mental imagery, we categorize these relations in five types of association based on the law of association (Dawson and Medler, 2010), which are context association, analogy association, contiguity association, contrast association and similarity association.

‧

Table 4.1 Types of associations

Type of association Definition Examples

Context association The relations between two concepts with a causal or sequential relation.

Hot à Sweat

Wake up à Brush Teeth

Analogy association The relations between two concepts with some shared meaning.

Life à Drama Final Exam à War

Contiguity association The relations between a series of concepts in contact or in proximity.

Transportation à

Bike, Bus, Train, Ship, Plane

Contrast association The relations between two concepts with inversed properties.

Happy à Sad Hot à Cold

Similarity association The relations between two concepts that share lots of similar properties.

Bowl à Cup Hotel à B&B

Arrow (2) and (3): When framing and reframing the situations, designers iteratively combine what they observe with what they already know trying to make sense of the situation as well as gain some implications. The ability to do observation and interview is very important. The more the details are found, the more completed the system can be modeled.

Another crucial ability is the ability to recall and associate to past experience. Every found phenomenon needs to be interpreted by the designers to give meaning of it. Hence, to properly interpret the phenomenon is one of the important expertise of designers. Compared

‧

立 政 治 大 學

‧

N a tio na

l C h engchi U ni ve rs it y

to the novices, experts in a field of study not only have more concepts integrated in their cognitive frameworks but also possess broader extent of propositional linkages between subordinate and superordinate concepts (Chi, Feltovich, & Glaser, 1981; Novak, 1988). In service design field, the ability to integrate the newly found concept with the existing knowledge will influence the quality of derived insights.

4.1.2 Insight Quality

After design synthesis, the derived insights will have different qualities. Here we estimate the insight quality from both macro and micro view. From the macro view, we examine the influencing extents of the insights. On the other hand, we consider the perceived satisfaction of the designers to examine the insight quality from a micro view.

From the macro view: Insight Depth

The purpose of discovering insights is to develop new service concepts satisfying customers’

latent needs, drawing upon the capacities and influences of service providers. Here we adapt the 3-D model for value proposition by Kwan and Yuan (2010) for the measurement of insight depth. The model has three dimensions including stakeholders, value (strategy) directions, and customer empowerment stages. Each dimension has several nominal values, and a point or an area in the space is a potential value proposition. As mentioned before, our main ideas embedding S-D logic that emphasizes the value co-creation between service provider and the customer. For the purpose of co-creating with customers to maximize the value, service providers tend to let customers take control of variables that are conventionally pre-determinant by themselves. In other words, making the customers highly empowered in order to increase involvement and responsiveness. As a result, we only focus on designing the services with high customer empowerment so that the dimension of customer empowerment stage is not taken into consideration in this research. Furthermore, we order the nominal

‧

then shown in Figure 4.2, which we call insight depth map.

Figure 4.2 Insight depth map

There are four degrees of the influencing scope of strategies. Take tablet computers as an example. For the economic strategy, kindle fire offered by Amazon is relatively cheap for customers. On the other hand, Samsung launched new Galaxy Tab with 4G LTE technology, which offers a functional value for customers. Game applications on the tablet can accomplish users’ need of pleasure; they provide intrinsic value to customers. According to a report from Electric Power Research Institute (2012), Apple’s new iPad only consume averagely 11.86 kilowatt-hours of electricity over a year, which only cost $1.36 USD. It’s a good example of providing environmental values. There are also four degrees of the extent of stakeholders. If revenue is the only consideration, the service provider itself is the only stakeholder. In another case, if the service provider cares about the whole supply chain, the scope of stakeholder is extended to their partners. The user-centric design focuses on the

‧

立 政 治 大 學

‧

N a tio na

l C h engchi U ni ve rs it y

customers, so the customers and community are included. Furthermore, if the design is significant enough, the stakeholders may be the whole society. Each point or area on the map represents an insight. The distance between the insight and the origin is the insight depth, which indicates the influencing scopes of the insights.

Insight  depth = 𝑆^!  +  𝑉^! (1)

(S: influencing scope of stakeholders / V: influencing scope of values)

From the micro view: Perceived Satisfaction of insight quality

If a design challenge is aimed to solve a personal problem or a business problem, we can’t judge it from the societal point of view. As a result, we also examine the insight quality by the perceptions of the designers in a micro view. As we mentioned before, a successful service should be one with desirability, feasibility, and viability (IDEO, 2010). For the purpose of being desirable, a service must provide a solution that can solve users’ problem and did not appear in the market before. Furthermore, as for feasibility, designers should care about many aspects of developing and delivering the service. For instance, the marketing strategies, the partnership with others, and the training of the first-line employees should be all taken into consideration. This is also the notion of system thinking which allows people to see the big picture instead of only part of the problem (Barile et al., 2010; Aronson, 1993).

Besides, in order to be viable in the market, designers should consider the delivered service not only as a service but also as a business. Only if a service is operated as a business, it could be evolved continuously. To engage in a business operation, besides concerning the cost of developing the services, designers should be very passionate. Hence, we also examine the designers’ agreement with their discovered insights. To sum up, we conclude three dimensions to evaluate the insight in the micro view, including the degree of innovativeness, the degree of integrity, and the degree of agreement. The definitions and some questions to

‧

立 政 治 大 學

‧

N a tio na

l C h engchi U ni ve rs it y

Table 4.2 The dimensions of perceived satisfaction of insights

Dimension Definition Questions

Innovativeness The degree of originality. Did the insights discover by others before?

Integrity The degree of having all constituents.

Did you consider all the possible influencing factors of the insights?

Agreement The degree of self-approval. Do you approve the insights?

Arrow (4): Insight discovery process is to iteratively combine what you see and what you already know. It’s also called framing and reframing in service design field. As mentioned before, the ability to link newly found phenomenon with existing knowledge is very important when discovering insights. We use both macro and micro view to measure the qualities derived insights. It not only provides a more quantitative way to measure insight qualities but also help us to examine whether the IT artifact can really facilitate the insight discovery process and further increase the qualities of derived insights.

4.1.3 Artifact facilitation

Arrow (5): The above paragraphs reflect how designers process their cognition to derive insights. In this research, the main purpose is to design an IT artifact to facilitate the insight discovery process. We hope this artifact can help service designers to process their mental knowledge by providing systematic and inspirational recommendations. We propose a system architecture with some algorithms in the following chapter to examine the feasibility.

‧

Our information system is called Discover+ as an artifact to facilitate the insight discovery.

There are three parts in the system (Figure 4.3), interactive interface, Discover+ engine, and external knowledge bases like Google and ConceptNet as depicted in Figure 4.3. Designers manipulate the system through the interactive interface. The original input is the data obtained through interview and observation. After processing, a few insights will be generated. Not only the data retrieved from the stakeholders, we also fetch some data from the external using Google search to ensure the data is sufficient. The sensing knowledge mainly comes from the ConceptNet which has been used to do commonsense reasoning for years (Liu and Singh, 2004; Shen et al., 2007). There are several semantic tools available.

ConceptNet is is more suitable for making practical context-based inferences while WordNet is for lexical categorization and Cyc is for formalized logical reasoning (Liu and Singh, 2004).

We choose ConceptNet as the knowledge base of the Discover+ because its structure of concepts connected with relations can be utilized to perform contextual reasoning which is the core of theme and frame recommendation of our system.

Figure 4.3 System Architecture