Abstract
Knowledge-intensive crowdsourcing (KIC) is becoming one of the most promising domains of crowdsourcing by leveraging human intelligence and building a large labor-intensive service network. In this network, the service providers (SPs) constitute the backbone of the KIC platform and play an important role in connecting the platform and service requesters. The SPs are a group of distributed crowds with a complex composition and high level of uncertainty, resulting in great challenges in service quality and platform management. Understanding the SPs’ competency is an effective way for the platform to manage them. Therefore, we attempt to connect the competency analysis to the environment of KIC to investigate and identify the criteria of SPs’ competency (i.e., the competency factors and dimensions required for being competent for the SPs’ business). To this end, we leverage the Latent Dirichlet Allocation (LDA) model to explore and extract hidden competency dimensions from online interview records. We then introduce the competency theory to identify and label the competency factors and dimensions and construct the three-level KSAT competency model, which presents a comprehensive vision of the SPs’ performance standards in the context of KIC. Given the competency criteria in the KSAT competency model, we use the Best-Worst Method (BWM) to determine their weights, which reflect their importance when evaluating the SPs’ competency from the platforms’ perspective. The results show that skill and knowledge are the two most important competency factors, and customer relationship management and communication ability are the two most valuable competency dimensions when evaluating the SPs’ competency. Furthermore, the KSAT competency model can be applied to analyze the competency of individuals or organizations in many other industries as well.
Highlights
As facilitated by highly developed information technologies, knowledge-intensive crowdsourcing (KIC) taps into the creative and innovation fields, changing the traditional way of how business is conducted [1]
Parameters α and β are the hyperparameters for prior distributions of θd and φk, respectively. e plate notations at the bottom of each rectangle denote their usage to illustrate the replications; i.e., the K plate represents the number of topics, the N plate represents the total number of unique words within documents, and the M plate represents the number of documents. e arrows represent conditional dependencies among components in the following way: per-word topic distribution zd,n is dependent on the topic distribution per document θd, and the observed word in each document wd,n is dependent on zd,n and all the topics φk. e conditional dependencies enable the definition of the joint distribution of observed and unobserved variables
The main outputs yielded by the Latent Dirichlet Allocation (LDA) are, namely, topics φk and their weights in each document θd, and per-word weight within each topic zd,n. at is to say, the outputs of LDA consist of K topics, wherein each topic is denoted as a combination of words with different probability of occurrence
Summary
As facilitated by highly developed information technologies, knowledge-intensive crowdsourcing (KIC) taps into the creative and innovation fields (e.g., designers), changing the traditional way of how business is conducted [1]. The KIC platform experiences tremendous growth in the user base and becomes a large complex network. In this network, a large number of open and crowdsourcing service providers (SPs) constitute the backbone of the KIC platform. As a vital connection between the platform and service requesters, they assist the KIC platform in running a wide range of business and services catering to numerous end customers of different types and attain business success in their areas of professionals. In this process, they can meet the service requesters’ demand.
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