The Service-Dominant Logic Based Approach for Technology Spillover

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立 政 治 大 學

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This study tries to extend the use of the input-output table to build a S-D logic based approach for unfolding and measuring the technology spillover within services.

8.2 The Service-Dominant Logic Based Approach for Technology Spillover

As mentioned earlier, although the traditional input-output analysis approach can‟t be directly used to explore and measure the expected effects of technology spillover within services, this study attempts to extend this approach in terms of incorporating S-D logic into its existing analytical procedure and explicit principles while retaining its ease of usability. The extended approach not only defines the core S-D logic concept (i.e. value co-creation by providers and customers) but also sets up customer involvement as essential indicators to measure the effects of technology spillover. The approach can be described in detail by following subsections.

8.2.1 The Phases of the Service-Dominant Logic Based Approach

This study is to build a S-D logic based approach by mapping the concept and extending steps of the input-output analysis approach to those in services, resulting in the modified steps of the new approach as shown in Figure 8-2. The S-D logic based approach will then be described in detail as follows.

 Analyzable alternative definition

In the beginning, the initial step is to define what analyzable alternatives, which are the vertical items (i.e. inputs) of the input-output analysis table, will be considered.

These alternatives are to be examined on their relations with the topics of a specific domain under analysis. This step can take industries or products as the analyzable alternatives. For example, in order to realize effects of technology spillover of service industries in a nation, the analyzable alternatives can include the banking service, the education services, or leisure service, etc. However, the alternatives are taken mainly

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Compared to the demand items definition step (which takes the same items as the input items definition step within the traditional input-output analysis), the target values are defined as what merit the aforementioned alternatives want to create for customers. This study defines target values to not only represent the value-in-use feature but also emphasize value co-creation as addressed in S-D logic (rather than just the value added as addressed in G-D logic). That is, these values can also be generated by customers. For example, “trust” is one of vital values that eBay wants to deliver to their customers by building a secure transaction platform. In addition, eBay also proposes a ranking service to its customers who can score each other on the transaction platform. This service would indirectly increase the perception of the trust value of eBay by customer involvement.

Figure 8 - 2 Steps of S-D logic based approach

 Operant-based data inputting

Since the concept of S-D logic includes G-D logic, this step of our study is to input operant-based and operand-based data by either the quantitative or qualitative methods. Hence, the data is not restricted to a specific type depending on the research topic and research resource considerations. The data can be generated not only from the providers‟ aspect but also from the customers‟ aspect. Hence, this step can also identify the indicators of customer involvement for operant-based data collecting. For example, recommendation posts of customers at a website can be considered as

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立 政 治 大 學

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N a tio na

l C h engchi U ni ve rs it y

~ 167 ~

operant-based data for a service sector. The main difference between this step and the goods-based data inputting step is that the analytical data mainly rests on the forms of operant resources involving customer involvement.

 Operant-based data processing

After inputting data, we need to do further calculations and categorizations based on the data types in order to realize the meanings of operant-based data. For example, the data can be processed to represent a bar chart which shows the distribution results in detail (such as Figure 8-3) in order to enable service providers to realize the circumstance of each industry. Service Providers can plan the feasible and innovative strategies to their customers based on the implications of the chart. The data can be computed to attain certain relations such as input coefficients or inter-industry coefficients of the S-D logic based input-output analysis approach. However, the concept of this step is different from the operand-based data processing in terms of a gap function defined for the evaluation of the present operation performance of service industries rather than just the inter-dependency between the input investment and the output products.

 Service-based spillover analysis

According to the results of service-based spillover analysis, we can not only realize the strength and weakness within the industry (such as goods-based spillover analysis) but also define the core values that can be co-created by providers and customers. Consequently, that will help service providers come up with innovative services to increase their competency and capability and involve customers to participate in. Finally, service providers can also explore the possible fields for adopting a new technology in services by analyzing technology spillover effects.

Although the original input-output analysis approach has been useful and

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立 政 治 大 學

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N a tio na

l C h engchi U ni ve rs it y

~ 168 ~

straightforward for enterprises to utilize, the approach only has been solving the problems of G-D logic. Consequently, this study extends the approach to incorporate S-D logic. This thesis will also follow the above steps of S-D logic based approach to measure the effect of technology spillover.

Figure 8 - 3 The gaps among service industries 8.2.2 Measuring the Effect of Technology Spillover

Besides the presentation of the S-D logic based approach, this study will also propose how to measure the effects of a technology spillover. To better understand the measurement, this paper uses a case study to demonstrate the measuring process. This case study is to evaluate the effects of the spillover of the Exquisite Technology that will be briefly described in Chapter 3. In other words, we will explore the potential spillover opportunities to adopt the Exquisite Technology through the application of the S-D logic based approach. Besides, we consider the different categories of service sectors which are defined by the directorate general of budget, accounting and statistics (http://eng.dgbas.gov.tw), which is a government authority of Taiwan, during the analysis process for the accuracy and reliability in the data. In addition, we also use performance characteristics of service sectors from the council for economic

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立 政 治 大 學

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N a tio na

l C h engchi U ni ve rs it y

~ 169 ~

planning and development to represent the target values because of the representative and sufficiency.

Furthermore, this study will proceed to conduct two investigations by using qualitative methods including focus group interview and secondary data analysis. In the first investigation we invited five experts with the service technology background to share their experiences and knowledge in order to calculate the spillover effects.

Moreover, secondary data analysis can help us clearly identify the relations and influences in a specific service sector by reviewing and analyzing the previous research, literature, and official documentation.