Recommendation Technologies for Configurable Products

Falkner, Andreas A.; Felfernig, Alexander; Haag, Albert

doi:10.1609/aimag.v32i3.2369

Cited by 59 publications

(29 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…OSCs are knowledge-based software applications that support potential customers or sales people who are interacting with customers online to completely and correctly specify a product solution from within the company's offerings [1][2][3]. Sales configurators are designed with the purpose of guiding users toward configuration solutions that best fulfill their specific needs [53][54][55][56]. In many cases OSCs are implemented with recommendation systems to further facilitate customers in their search for suitable solutions [51,53,55].…”

Section: Online Sales Configuratorsmentioning

confidence: 99%

Users’ Social-interaction Needs While Shopping via Online Sales Configurators

Grosso¹,

Forza²

2019

Int J Ind Eng Manag

View full text Add to dashboard Cite

The growing adoption of social web technologies such as social software (SSW) in online configuration environments has enabled the possibility of supporting configurator users in interacting digitally with real people while they are shopping for customized products. Previous research has identified that online sales configurators (OSCs) are currently connected to SSW with different modalities to provide configurator users with a variety of options to digitally interact with real people. Enriching the configuration environment with social-interaction tools has engendered the phenomenon of socialproduct customization. Recent studies considered the social product-customization by investigating the impact that community feedback and social comparisons has on configurator user. However, the OSCs users' need to interact with different referents during their configuration process, and whether the SSW-OSCs connections respond to this need are still unsearched. To address this gap, the present study explores (a) whether users experience the need to interact with different referents while shopping via OSCs and (b) which interaction modalities users are looking for. By considering 943 configuration experiences from 189 users of 378 OSCs for various consumer goods, the present study finds that the need for social interaction by OSC users is highly relevant. Moreover, OSC users perceive the need to interact with different referents during different stages of the configuration process, and, depending on the referent with whom they wish to interact, they are interested in different interaction modalities in terms of how and where those interactions take place. These findings imply that mass customizers may leverage their customers' need to interact with real people while shopping online via OSCs in order to better engage their actual and potential customers.

show abstract

Section: Online Sales Configuratorsmentioning

confidence: 99%

Users’ Social-interaction Needs While Shopping via Online Sales Configurators

Grosso¹,

Forza²

2019

Int J Ind Eng Manag

View full text Add to dashboard Cite

show abstract

“…In this subsection, first we explain the relationship between configuration technologies and constraint satisfaction problems, then show how CONFREQ can be applied on a constraint satisfaction problem from the smart home domain. The configuration of a new gateway infrastructure requires configuration technologies with integrated recommendation functionalities (Falkner et al 2011). When starting a new configuration, the configuration environment should be able to exploit information about already existing gateway installations in order to reuse some parts of the installation for the new gateway.…”

Section: Confreq: Recommendations For Configuratorsmentioning

confidence: 99%

An overview of recommender systems in the internet of things

Felfernig¹,

Erdeniz²,

Uran³

et al. 2018

J Intell Inf Syst

Self Cite

View full text Add to dashboard Cite

The Internet Of Things (IoT) is an emerging paradigm that envisions a networked infrastructure enabling different types of devices to be interconnected. It creates different kinds of artifacts (e.g., services and applications) in various application domains such as health monitoring, sports monitoring, animal monitoring, enhanced retail services, and smart homes. Recommendation technologies can help to more easily identify relevant artifacts and thus will become one of the key technologies in future IoT solutions. In this article, we provide an overview of existing applications of recommendation technologies in the IoT context and present new recommendation techniques on the basis of real-world IoT scenarios.

show abstract

“…For example, a user interacting with a configurator is in the need of explanations (Junker, 2004;Sinz et al, 2007) in terms of why a solution has been identified or why no solution could be found (Falkner et al, 2011;Junker, 2004). For example, a user interacting with a configurator is in the need of explanations (Junker, 2004;Sinz et al, 2007) in terms of why a solution has been identified or why no solution could be found (Falkner et al, 2011;Junker, 2004).…”

Section: Solution Search In Advanced Cspsmentioning

confidence: 99%