Leveraging Market Research Techniques in IS: A Review and Framework of Conjoint Analysis Studies in the IS Discipline

Abstract

With cloud and mobile computing, information systems (IS) evolve towards mass-market services. While user involvement is critical for IS success, the IS discipline lacks methods that allow integrating the "voice of the customer" in the case of mass-market services with individual and dispersed users. Conjoint analysis (CA), from marketing research, allows for understanding user preferences and measures user trade-offs for multiple product features simultaneously. While CA has gained popularity in the IS domain, the existing studies have mostly been one-time efforts and no cumulative research patterns have been observed. We argue that CA could have a significant impact on IS research (and practice) if it were fully developed and adopted as a method in IS. From reviewing 70 CA studies published between 1999 and 2019 in the IS field, we find that CA can be leveraged in the initial conceptualization, iterative design and evaluation of IS and their business models. We critically assess the methodological choices along the CA procedure to provide recommendations and guidance on "how" to leverage CA techniques in future IS research. We then synthesize our findings into a "Framework for Conjoint Analysis Studies in IS" that outlines "where" CA can be applied along the IS lifecycle.

Uncovering the digitalization impact on consumer decision-making for checking accounts in banking

“…We used partial least squares structural equation modeling (PLS-SEM) and finite mixture modeling (Flexmix) to estimate the effects. The analysis of discrete choice data in PLS-SEM is based on linear probability models (Hair et al, 2019; Naous & Legner, 2020). We chose this novel analysis approach to conduct multigroup analysis for moderation effects.…”

“…Accordingly, eight choice sets were built systematically using an established choice experiment design software. We included our five service attributes for checking accounts with two levels each to preserve the orthogonality of the experimental design (Kuhfeld et al, 1994;Naous & Legner, 2020; Fig. 1 Research model 2007).…”

Predictive Maintenance on the Energy Distribution Grid–Design and Evaluation of a Digital Industrial Platform in the Context of a Smart Service System

“…Therefore, we make use of a willingness-to-pay (WTP) analysis to evaluate our designed ensemble artifact. A WTP analysis generally aims to quantify the utility function of a customer in monetary units-i.e., the willingness to pay for a service or prodct [62]- [64]. Thus, it is able to determine the value-in-use, i.e., "individual judgment of the sum total of all the functional and emotional experience outcomes" [65, p. 120].…”

Uso del análisis conjunto para estimar preferencias de consumo de leche de cabra en polvo en la Región de Coquimbo Chile

“…La investigación para su recopilación de datos se desarrollo en 3 etapas: 1º revisión bibliográfica para identificar los principales atributos que se consideran importantes al momento de preferir un producto tradicional a partir de leche de cabra y sus derivados; 2º realización de entrevistas a expertos (8 profesionales, especialistas en desarrollo de productos agroalimentarios) y un focus group (10 participantes del segmento objetivo) de manera de delimitar las características en la decisión de compra a un total de cuatro atributos y ocho niveles propuestos (Tabla 1); 3º se aplicó un cuestionario, compuesto de tres secciones: (i) preguntas de caracterización del encuestado sobre su género, edad, ingreso familiar, lugar de residencia, nivel educación entre otras; (ii) preguntas sobre el comportamiento de compra de productos tradicionales a partir de leche de cabra, y en especial la leche de cabra en polvo; (iii) se propuso 8 alternativas de producto (experimento) que los encuestados debieron jerarquizar en función de sus preferencias de consumo (escala ordinal de 1 a 8), mediante el método perfiles completos (Naous & Legner 2017). La apreciación se realizó, asignando el valor 1 al perfil más deseado y 8 al menos deseado, información necesaria para desarrollar el análisis conjunto, tarjeta que se observa en la Figura 1.…”

“…Atributos y niveles propuestos para el experimento de la decisión de compra de leche de cabra en polvo de la Región de Coquimbo Chile. Para el análisis de las preferencias, se utilizó la fórmula de valoración del producto la que proporciona una estimación de los pesos de importancia relativa de los atributos, que se basa en la premisa de que los diferentes niveles de atributos hacen una contribución parcial a la utilidad total (Naous & Legner 2017).…”