نیاز تحقیق برای ارزیابی ایجاد ارزش آنلاین در فرایند پیچیده رفتار خرید مصرف کننده

Consumers face considerable frustration when purchasing structurally and/or semantically complex high-involvement products online. Reliance on computer-mediated communications for their information needs may result in functional and emotional frustration from information overload and lack of personal trust. This paper proposes a responsive real-time information system as a proxy for a perceptive sales representative who assesses customer needs based on information exchanges and then offers appropriate responses. By tracking and analyzing a consumer's online activity, vendors can offer information relevant to the consumer's real-time needs, facilitating their purchase process. In essence, this is a real-time value co-creation process based on the consumer offering cues to vendors through their key strokes and mouse click activity. This allows for differentiated information offerings for inexperienced and more experienced consumers, creating value by dynamic information serving. Where appropriate value is created, consumers will experience less frustration and continue online, rather than possibly moving offline or to alternative vendors. In examining the bases of consumer information needs in complex purchases, this paper identifies the data required to enable a responsive dialog between vendors and consumers.

If the internet is to become a fully fledged distribution channel for complex goods and services, vendors need to deal with the reality of complex consumer behavior and rethink the use of online information exchange data. This paper proposes that vendors offer relevant information online in real time to facilitate the consumer's purchase process by co-creation of value. In the context of this paper, “value co-creation” is the value derived from engagement in the consumer's pre-sales process. Value is created when a consumer is offered useful information and gains understanding, reassurance and/or hedonic fulfilment in the process (Grant et al., 2007). The value creation relies on an analysis of online consumer behavior to determine which information sources and formats are most likely to meet their needs at a given point in time. The approach follows the view of Payne et al. (2008): that a customer becomes a co-creator of value through the development of customer–supplier relationships based on interaction and dialogue. The key problem addressed by this paper is the frustration of consumers in dealing with the massive range of information available to them online. Consumer frustrations arise from several sources, ranging from simple information overload (Lee and Lee, 2004), dysfunctional search results associated with the “law of adverse selection” (Redmond, 2002), and utility effects such as lower levels of recall associated with screen-based information (Jones et al., 2005). Where semantic complexity is an issue, online utility is further compromised, because consumers prefer objective or unambiguous information online, but turn to offline information sources for subjective or taste-based opinions (Ratchford et al., 2003). The ideal response to this problem is to use online information exchanges in the same way as a perceptive salesperson discerns consumer motives and information needs during face-to-face encounters and acts to satisfy those needs. This answers the call of other researchers (Porter, 2001; Wind and Mahajan, 2002; Urban, 2004, p. 5) for a focus on consumer needs, rather than the capabilities of technology in an online environment. To achieve this, a focus is required on achieving engagement with consumers through dialog, and by serving relevant information as they move through a complex purchase process online. The paper is structured as follows: the following section outlines the research challenges for real-time value co-creation online and a process model for doing so in the form of a flowchart. Subsequent sections define the requisite data for assessing consumer real-time information needs based on the constructs identified in the flowchart. The ability of current clickstream and factor identification research to provide such data is then reviewed, with several clear limitations arising. Finally, consumer text inputs (such as online forums) are introduced as a complementary data source that addresses current research practice limitations and enables modeling of complex online purchase behavior. The final section summarizes the paper's findings and outlines a research agenda for modeling complex consumer behavior.

This paper outlines the potential to offer relevant information in real-time online interactions to consumers engaged in a complex purchase process. A system that enables such value co-creation relies on data derived from the consumer's behavior to anticipate and serve dynamic information based on cognitive and behavioral theories. Thus, important utility limitations of computer-mediated communications are potentially improved, adding functionality to the convenience of internet information access for consumers. Organizations using such a system stand to realize substantial gains over organizations that do not in attracting and retaining customers through a process leading to eventual purchase. However, while the data needs seem relatively clear, a substantial research program is required for the development of such a system. First, a detailed classification system of web pages on a website is required to enable tracking of consumer activity in breadth and depth and to identify patterns of behavior. Second, behavioral patterns should be identified and related to contingent decision-making factors and perceived risk management need for classification into a typology of heuristic behavior types. Third, the trade-offs between different online information sources needs to be understood to resolve some of the apparent contradictions of utility reflected in current research. The resulting understanding of utility and trade-offs between information sources then needs to be related to heuristic patterns of behavior to inform protocols for information serving. Finally, the language and culture relating to groups associated with the product should be investigated to enable structural and lexicographic analysis of consumer text entries.