Temporary staffing services: a data mining perspective

Research on the temporary staffing industry discusses different topics ranging from workplace safety to the internationalization of temporary labor. However, there is a lack of data mining studies concerning this topic. This paper meets this void and uses a financial dataset as input for the estimated models. Bagged decision trees were utilized to cope with the high dimensionality. Two bagged decision trees were estimated: one using the whole dataset and one using the top 12 predictors. Both had the same predictive performance. This means we can highly reduce the computational complexity, without losing accuracy

Temporary staffing services: a data mining perspective

Research on the temporary staffing industry discusses different topics ranging from workplace safety to the internationalization of temporary labor. However, there is a lack of data mining studies concerning this topic. This paper meets this void and uses a financial dataset as input for the estimated models. Bagged decision trees were utilized to cope with the high dimensionality. Two bagged decision trees were estimated: one using the whole dataset and one using the top 12 predictors. Both had the same predictive performance. This means we can highly reduce the computational complexity, without losing accuracy

Using webcrawling of publicly available websites to assess E-commerce relationships

We investigate e-commerce success factors concerning their impact on the success of commerce transactions between businesses companies. In scientific literature, many e-commerce success factors are introduced. Most of them are focused on companies' website quality. They are evaluated concerning companies' success in the business-to- consumer (B2C) environment where consumers choose their preferred e-commerce websites based on these success factors e.g. website content quality, website interaction, and website customization. In contrast to previous work, this research focuses on the usage of existing e-commerce success factors for predicting successfulness of business-to-business (B2B) ecommerce. The introduced methodology is based on the identification of semantic textual patterns representing success factors from the websites of B2B companies. The successfulness of the identified success factors in B2B ecommerce is evaluated by regression modeling. As a result, it is shown that some B2C e-commerce success factors also enable the predicting of B2B e-commerce success while others do not. This contributes to the existing literature concerning ecommerce success factors. Further, these findings are valuable for B2B e-commerce websites creation

Unleashing the Potential of External Data: A DSR-based Approach to Data Sourcing

External data has become an indispensable pillar in state-of-the-art decision-making and value creation in an enterprise context. Despite the increasing motivation to use external data, information systems (IS) research still lacks an adequate data sourcing perspective. This study aims to address this gap by investigating the practical challenges in this emerging field and developing a reference process for sourcing and managing external data. To this end, we adopt a design science research approach leveraging collaboration with practitioners from nine high-profile companies. Our findings contribute to the scarce body of knowledge on data sourcing in IS by proposing explicit prescriptions in the form of a reference process for sourcing and managing external data

Sharing is Caring: Using Open Data To Improve Targeting Policies

When it comes to predictive power, companies in a variety of sectors depend on having sufficient data to develop and deploy business analytics applications, for example, to acquire new customers. While there is a vast literature on enriching internal data sets with external data sources, it is still largely unclear whether and how open data can be used to enrich internal data sets to improve business analytics. We choose a particular business analytics problem – designing targeting policies to acquire new customers – to investigate how an internal data set of a German grocery supplier can be enriched with open data to improve targeting policies. Using the enriched data set, we can improve the response rate of several well-established targeting policies by more than 30% in back-testing. Based on these results, we encourage firms and researchers to use, leverage, and share open data to enhance business analytics

Data augmentation by predicting spending pleasure using commercially available external data

Type-ins are interactive online ads in which the user must enter some information, such as a brand message, into a text box in order to access additional content or submit information via a form on a website. We compared type-in ads to more traditional static ads in two places on a website: as an interstitial, in which users must view the ad to get to the next page of content, and as a form ad, in which users must view an ad to submit an online form. There was a significant increase in brand and message recall for type-ins compared to static ads for both interstitials and form ads. Furthermore, type-ins did not impact user experience positively or negatively in either case. Both interstitial and form ads, whether type-in or static, had better brand and message recall when the ad and site content were consistent (i.e., an entertainment ad on an entertainment site) than when the ad was inconsistent (i.e., a travel ad on an entertainment site). The increased recall for brand and message produced with type-in ads indicates that type-ins can play an important role in the broader goals of brand building within IMC. [ABSTRACT FROM AUTHOR] Copyright of International Journal of Integrated Marketing Communications is the property of Racom Communications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.