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Article
Publication date: 17 July 2017

Pilsik Choi

The purposes of this paper are to propose a different profitability metric (i.e. anchor category profits) at the category level based on the concept of anchor categories and to…

543

Abstract

Purpose

The purposes of this paper are to propose a different profitability metric (i.e. anchor category profits) at the category level based on the concept of anchor categories and to illustrate how such a metric can be calculated in field settings to offer a balanced view of profit structure from both the accounting and marketing perspectives.

Design/methodology/approach

First, the concept of anchor categories is developed drawing on anchor effects theory and automatic cognitive processing theory. Based on anchor categories, this paper proposes a formula for calculating anchor category profits. Using the data collected with a survey instrument, this paper calculates accounting profits and anchor category profits for two grocery stores.

Findings

The intra-store analysis of accounting profits and anchor category profits reveals that the two profit measures project different profit contribution patterns by product categories for each store. The inter-store analysis provides quite different, yet useful information about profit structures for the two grocery stores. Although the two stores are similar in terms of accounting profits, their anchor category profits show different pictures regarding profit contribution patters by product categories between the two stores, revealing that different categories attract customers to different stores.

Practical/implications

Comparing accounting profits and anchor category profits allows retail managers to identify traffic generator categories and cash generator categories, which helps retail managers develop more effective category management to increase storewide profits.

Originality value

This paper increases understanding of the relationship between product categories and store choice behavior by offering a theoretical rationale to explain why some product categories influence consumers’ store choice. This paper also proposes anchor category profits as a more implementation-friendly category-level profitability metric that combines accounting principles with consumers’ shopping trip planning behavior.

Details

Management Research Review, vol. 40 no. 7
Type: Research Article
ISSN: 2040-8269

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Article
Publication date: 14 August 2024

Jaekyeong Kim, Pil-Sik Chang, Sung-Byung Yang, Ilyoung Choi and Byunghyun Lee

Because the food service industry is more dependent on customer contact and human resources than other industries, it is crucial to understand the factors influencing employee job…

253

Abstract

Purpose

Because the food service industry is more dependent on customer contact and human resources than other industries, it is crucial to understand the factors influencing employee job satisfaction to ensure that employees provide satisfactory service to customers. However, few studies have incorporated employee reviews of job portals into their research. Many job seekers tend to trust company reviews posted by employees on job portals based on the information provided by the company itself. Thus, this study utilized company reviews and job satisfaction ratings from employees in the food service industry on a job portal site, Job Planet, to conduct mixed-method research.

Design/methodology/approach

For qualitative research, we applied the Latent Dirichlet Allocation (LDA) model to food service industry company reviews to identify 10 job satisfaction factors considered important by employees. For quantitative research, four algorithms were used to predict job satisfaction ratings: regression tree, multilayer perceptron (MLP), random forest and XGBoost. Thus, we generated predictor variables for six cases using the probability values of topics and job satisfaction ratings on a five-point scale through LDA and used them to build prediction algorithms.

Findings

The analysis showed that algorithm accuracy performed differently in each of the six cases, and overall, factors such as work-life balance and work environment have a significant impact on predicting job satisfaction ratings.

Originality/value

This study is significant because its methodology and results suggest a new approach based on data analysis in the field of human resources, which can contribute to the operation and planning of corporate human resources management in the future.

Details

Data Technologies and Applications, vol. 59 no. 1
Type: Research Article
ISSN: 2514-9288

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