Research and design methodologies and applications

¶ … customer's purchase behavior is an important part of increasing revenue for business. When this is connected to the greater use of online sources of knowledge it becomes critical to a business's survival to produce knowledge bases (KB) that improve customer satisfaction and attitudes about the product or service. Consequently Hsu (2011) focuses "attention on knowledge-base capabilities and their relationships with customers' self-service in conjunction with repeat purchase intention" (Hsu et al., 133). The study is valuable because it examines an area of customer behavior that has received limited attention through empirical research.

For this study the researcher examines four major constructs and the relationship between them. The major constructs tested in this study are Knowledge Base (KB) of a computer product (KBCP), self-service experience (SSE), purchase intention (PI) and product attributes (PA). The literature suggests that the construction of a KB requires that the existing mechanism, procedures and information relating to a product be constantly updated through the knowledge management system (KM). The knowledge about a particular product and its regular updating and management constitutes a knowledge base. The SSE is influenced by the Self-service technologies (SST) that are available to the customer. SST are considered to be passive or active based on the nature of the customer related tasks that are accommodated by the technologies. The passive technologies engage simple tasks while more complex tasks are achieved through active technologies.

The PA is a function of the information that is available to the customer about the product. The customer may acquire this knowledge prior to online access or after they have accessed the product. The PAs therefore or not inherent to the product but are constructed through customer interaction with the KB. The final construct utilized in this study is PI. This relates to the attitude the customer possesses after interaction with the KB. The PI can be either positive or negative. This signifies the likelihood that the customer will purchase the product.

The researchers construct five critical hypotheses based on the presumed theoretical interaction between the variables established from the constructs. H1 assesses the relationship between perception of the KB of computer products and self-service experience. Notice that the KB is not measured directly but rather the customer perception of the KB. H2 also assess the perception of the KB but this time with reference to the purchase intention of the customer. In H4 and H5 the researcher examines the importance of product attributes and the self-service experience and the purchase intention of the customer.

Additionally, the variables for the constructs were derived from prior research. The constructs were measured using 13 variables excised from the literature. In all of these hypotheses the independent variables do not seek to measure the construct itself but rather the customer's attitude toward the construct is used as a proxy for the construct. As the authors note the study utilizes more reflective constructs rather than formative (Hsu et al., 140). KBCP is measured through ease of navigation of the KB and other similar questions. SSE refers to the problem solving experiences of customers through independent use. PA is operationalized as "possible factors for customers to select a certain brand" (Hsu et al., 140). The other dependent variable PI is measured through would you buy this brand?

The problem of purchase intention is complex and it is not possible to capture the variability within the construct with a single question. Additionally consideration should be given to directly measure the value received from prior experience with the product or service. While there seems to be a tacit acceptance of this variable its omission from the model limits the explicative power of the model. It is reasonable to assume that self-efficacy is correlated to the prior experiences of a customer so the omission of this variable ignores a critical theoretical lynch from being tested.

The researcher may have ignored this element because of the problems that may result from multicollinearity (Kerlinger, & Lee 2000). It is very difficult to adequately measure prior experiences and not capture some of the variance represented by some of the other constructs in the model. While self-efficacy is linked to the KB and KM systems, at the core of self-efficacy is prior experience with the product or similar products.