An Alternative Approach to Analyze Ipsative Data. Revisiting Experiential Learning Theory

Abstract

The ritualistic use of statistical models regardless of the type of data actually available is a common practice across disciplines which we dare to call type zero error. Statistical models involve a series of assumptions whose existence is often neglected altogether, this is specially the case with ipsative data. This paper illustrates the consequences of this ritualistic practice within Kolb's Experiential Learning Theory (ELT) operationalized through its Learning Style Inventory (KLSI). We show how using a well-known methodology in other disciplines—compositional data analysis (CODA) and log ratio transformations—KLSI data can be properly analyzed. In addition, the method has theoretical implications: a third dimension of the KLSI is unveiled providing room for future research. This third dimension describes an individual's relative preference for learning by prehension rather than by transformation. Using a sample of international MBA students, we relate this dimension with another self-assessment instrument, the Philosophical Orientation Questionnaire (POQ), and with an observer-assessed instrument, the Emotional and Social Competency Inventory (ESCI-U). Both show plausible statistical relationships. An intellectual operating philosophy (IOP) is linked to a preference for prehension, whereas a pragmatic operating philosophy (POP) is linked to transformation. Self-management and social awareness competencies are linked to a learning preference for transforming knowledge, whereas relationship management and cognitive competencies are more related to approaching learning by prehension.

Principal component analysis of financial statements. A compositional approach

“…Nowadays, CoDa spans almost all of the hard sciences and has started to be used in several management fields. Besides Linares et al 2018, examples include crowdfunding (Davis et al, 2017), financial markets (Ortells et al, 2016;Wang et al, 2019), investment portfolios (Belles-Sampera et al, 2016;Boonen et al, 2019;Glassman & Riddick, 1996), municipality budgets (Voltes-Dorta et al, 2014), product portfolios (Joueid & Coenders, 2018), market segmentation (Ferrer-Rosell & Coenders, 2018;Ferrer-Rosell et al, 2016a), market share (Morais et al, 2018), advertisement (Mariné-Roig & Ferrer-Rosell, 2018), consumer research (Ferrer-Rosell et al, 2015;Ferrer-Rosell et al, 2016b;Vives-Mestres et al, 2016a), quality management (Vives-Mestres et al, 2014; 2016b), organizational culture (Van Eijnatten, et al, 2015), and management education (Batista-Foguet et al, 2015;Mateu-Figueras et al, 2016).…”

Compositional visualization of intermedia agenda setting by the main media groups and political parties in the Spanish 2015 General Elections

“…The CoDa tradition started with Aitchison's seminal work (1982Aitchison's seminal work ( , 1986 on chemical and geological compositions where only the proportion of each part or component is of interest, since absolute amounts are irrelevant and only tell about the size of the chemical or soil sample (e.g., Buccianti et al, 2006). Nowadays, CoDa spans almost all the hard sciences and has started to be used in several fields of the social sciences, such as education (Batista-Foguet et al, 2015), economics (Fry, 2011), marketing (Vives-mestres et al, 2016), accounting (Linares-Mustarós et al, 2018), tourism Coenders, 2016), values (van Eijnatten et al, 2015), social networks (Kogovšek et al, 2013), time use (Martín-Fernández et al, 2015a) and election studies (Egozcue and Pawlowsky-Glahn, 2011;Liscano Fierro and Ortiz Rico, 2017). Content analysis in the study of the media and media groups and the analysis of AS, which resides in the communication of these media, pose similar problems in all respects as those encountered in chemical and geological analyses.…”

Survey Data on Perceptions of Contraceptive Methods as Compositional Tables

“…Calderón Carvajal & Ximénez Gómez, 2014). One of these contributions refers to the use of compositional biplots (Cortés-Rodríguez & Sánchez-Barba, 2013); a second deals with both biplots and coordinate representation of compositions (Batista-Foguet, Ferrer-Rosell, Serlavós, Coenders, & Boyatzis, 2015); and a third contribution is a preliminary study of the data we use in this paper (Pawlowsky-Glahn, Egozcue, & Planes-Pedra, 2017). Compositional tables have been further developed and applied in social sciences (Hron, Templ, & Filzmoser, 2013;Fâcevicová, Hron, Todorov, & Templ, 2016;Ortego & Egozcue, 2016).…”