A factor-cluster analysis profile of consumers

Higuchi, Angie; Maehara, Rocío

doi:10.1016/j.jbusres.2020.09.030

Cited by 17 publications

(18 citation statements)

References 40 publications

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“…According to Higuchi and Maehara (2021), studies related to food choice reveal that non-sensory aspects have an impact over consumption decisions, which is similar to Carrillo et al (2011) and Rozin (1996) findings. The decisionmaking process, for instance, also considers the frequency of consumption of a product, or even where to buy a certain kind of food.…”

Section: Introductionsupporting

confidence: 59%

Factors related to Quinoa Consumption in Peru during the COVID-19 Pandemic

Higuchi

Maehara²,

Sánchez-Pérez³

2022

Innovar

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Quinoa is a traditional food grain that originated in the Peruvian Andean region. The United Nations declared 2013 to be the International Year of Quinoa (iyq). This official launch had a great impact around the world. On the contrary, it had minor impact on the consumption of quinoa in Peru, which remained relatively steady in the following years. However, the covid-19 pandemic raised concerns about nutrition and health among consumers. Therefore, this study seeks to analyze quinoa consumption in Peru during the covid-19 pandemic. Primary data were collected between September 2020 and August 2021 in Lima Metropolitan Area, Peru. Exploratory factor analysis with varimax rotation was performed for data analysis, and logistic binomial analysis was then conducted to consolidate the hypothesis of this study. The main outcomes identified were that (i) current quinoa consumers in Peru ate quinoa even before the iyq; (ii) consumers who are concerned about their health and nutrition needs increased quinoa consumption during the pandemic; (iii) women showed a higher probability of daily to weekly trend in quinoa consumption; and (iv) people with the highest income have more probability of purchasing food at supermarkets than those who earn less. The findings of this study can shed some light on consumers’ expectations and perceptions regarding quinoa consumption behavior during covid-19.

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Section: Introductionsupporting

confidence: 59%

Factors related to Quinoa Consumption in Peru during the COVID-19 Pandemic

Higuchi

Maehara²,

Sánchez-Pérez³

2022

Innovar

Self Cite

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“…Los hallazgos del estudio evidenciaron que la intención de evitar alimentos procesados con EAN realizada por estudiantes universitarios puede ser explicada por los constructos que componen la TCP y la formación entregada por las carreras en el área de la salud. Este hallazgo es consistente con investigaciones previas que señalan que el modelo de la TCP puede efectivamente explicar la elección alimentaria de las personas 19,21,24,29 .…”

Section: Resultsunclassified

Factores que determinan la elección de alimentos procesados por estudiantes universitarios en el contexto de las etiquetas de advertencia nutricional

et al. 2022

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“…Hwang et al [9] estimated the probability of customers' return using a machine learning approach on the received feedback comments and satisfaction ratings regarding the previous usage of the service. Higuchi and Maehara [38] used a factor-cluster analysis to cluster customers. Our investigation also resulted in appropriate investment patterns (funds and products) for potential investors.…”

Section: Discussionmentioning

confidence: 99%

“…Some authors have examined the impact of various factors that influence customer decisions [9,[28][29][30][31]. Some studies have been conducted on customer clustering and segmentation based on customer behavioral perspectives, customer behavioral factors, demographic factors, and environmental objects [32][33][34][35][36][37][38]. Goncarovs [39] described a five-step customer segmentation method consisting of gathering quantitative information, creating specific microsegments, sorting microsegments, and creating final customer segments.…”

Section: Edmondson and Mcmanusmentioning

confidence: 99%

Exploration of the investment patterns of potential retail banking customers using two-stage cluster analysis

2021

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Identifying investment patterns as part of customer segmentation is one of the most important tasks in retail banking. Clustering customers effectively is an important element of improving marketing policy and strategic planning. There are several methods for identifying similar groups of customers and describing their characteristics to offer them appropriate products. However, using machine learning methods is rare, and the application is limited for certain types of data. The aim of this study is to investigate the benefits of using a two-stage clustering method using neural-network-based Kohonen self-organizing maps followed by hierarchical clustering for identifying the investment patterns of potential retail banking customers. The unique benefit of this method is the ability to use both categorical and numerical variables at the same time. This research examined 1,542 responses received for an online investment survey, focusing on the questions that are related to the respondents’ investment preferences and their current financial assets. The research utilizes descriptive statistics and multiple correspondence analysis (MCA) to understand the variables and Kohonen self-organizing maps (SOMs), in combination with hierarchical clustering, to identify customer groups and describe the characteristics of these clusters. The analysis was able to identify clusters of potential customers with similar preferences and gained insights into their investment patterns related to their investment portfolio and investment behavior, including their savings profile, attitude to risk-taking, and preferences for investment advice. These findings were supported by additional insights through the application of multiple correspondence analysis (MCA) describing patterns of financial instruments and portfolios. The main contribution of the research is the combined application of the machine learning methods Kohonen SOM, hierarchical clustering, and MCA for investment pattern analysis in the retail banking business.

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A factor-cluster analysis profile of consumers

Cited by 17 publications

References 40 publications

Factors related to Quinoa Consumption in Peru during the COVID-19 Pandemic

Factors related to Quinoa Consumption in Peru during the COVID-19 Pandemic

Factores que determinan la elección de alimentos procesados por estudiantes universitarios en el contexto de las etiquetas de advertencia nutricional

Exploration of the investment patterns of potential retail banking customers using two-stage cluster analysis

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