Understanding Vendor Preference in the Crowdsourcing Marketplace: The Influence of Vendor-Task Fit and Swift Trust

1.IntroductionThe vendor selection problem in outsourcing has been an abiding issue in IS research and practice [Cao et al. 2007a; Cao et al. 2007b; Cullen et al. 2006]. Vendor selection is one of the most critical steps, so much so that the success of outsourcing process is largely dependent on successful choice of vendors [Lee 2008; Wadhwa et al. 2007]. There are a number of reasons [Dickson 1966; Weber et al. 1991] that make vendor selection difficult for clients, especially in terms of IT projects. One pitfall leading to outsourcing failure is that clients have minimal knowledge about outsourcing methodologies, especially in the vendor selection process [Power et al. 2004]. Crowdsourcing, the latest incarnation of outsourcing, also suffers from the vendor selection problem, since the crowdsourcing marketplace (CM) has undergone rapid development worldwide, especially in the United States. Samplings of the 5 leading companies that publish statistics on their marketplace are listed below in Table 1. As we can see, almost 19 million registered vendors are competing for jobs in various CMs. Given the complexity of the matter, online vendor selection is certainly worthy of investigation.Bearing the risks and difficulties in mind, some scholars have asserted that incentives and mechanisms could be set up by the CM to help alleviate problems through sundry website features. How will the website features influence a client's choice of certain vendors? At the moment, there are gaps in our understanding of the client decision making processes in the crowdsourcing marketplace.In order to pursue the logic of our study, it is first important to define the scope of the study. Among sundry crowdsourcing applications, in particular, a CM, there are two prevailing models, the contract and contest models. The contest model allows clients to specify the reward and choose the best solution (no bids are solicited) while the contract model allows the client to choose the vendor based on qualifications and proposals for work. In the latter mode, the vendor undertakes the task with an agreed reward and specific time limit to finish the work. In fact, there is a contest element in the contract model but it occurs before the work is actually done.For further clarification, we can state the key roles in the CM context in Table 2. A CM is a trusted online intermediary ensuring that online vendors successfully complete the task requests and online clients pay for the charges. The crowdsourcing client is an entity that initiates the crowdsourcing process by submitting a task request and specifying the acceptance criteria. Task characteristics of interest refer to the attributes of the task including work effort specified, duration, requirements, etc. Crowdsourcing vendors are members of the crowd who bid for the job, undertake the tasks, and gain monetary reward from the clients for their work.Our belief is that in the contract model, selection is a competitive process among the vendors and client's choice of the vendor is based on his or her evaluation of the vendor-task fit and swift trust, which are the two main foci of this study. In this study, we provide a nuanced angle for examining the issue of vendor selection, by defining our dependent variable vendor preference as the degree of client's willingness to choose the vendor to perform his or her task posted on a CM. Vendor-task fit as perceived by the client is proposed to be an important factor influencing vendor preference. Swift trust is developed prior to repeated interactions and is a second factor affecting client decisions. Therefore, this paper aims to answer the following research questions:RQ1: What are the factors influencing client's vendor preference in the crowdsourcing marketplace? And how important are these factors? RQ2: Is swift trust a significant antecedent of vendor preference in the crowdsourcing marketplace? The objective of the study is to derive and empirically test a theoretically grounded model of factors leading to vendor preference. …