A framework for variance analysis of customer equity based on a Markov chain model

Matsuoka, Kohsuke

doi:10.1016/j.jbusres.2021.02.039

Cited by 11 publications

(5 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The popular methods for state transition include Markov chain model, finite state machine, and automata theory. The feature of Markov chain switching model enables applications to predict customer behavior in marketing area, such as predicting level of retail resilience (Rajesh et al, 2021), estimating online customer repurchase motivation (Li et al,2019), analyzing variance for customer equity (Matsuoka, 2021), and inferring stages of business-to-business buying journey (Marvasti et al, 2021). The concept of Markov chain specifies that future state depends on previous state and the chain presents a long-run steadystate level.…”

Section: Markov Chain Switching Modelmentioning

confidence: 99%

Analyzing the Omni-Channel Shopper Journey Configuration of Generations Y and Z

Chang

Chen

2022

Journal of Organizational and End User Computing

View full text Add to dashboard Cite

Omni-channel retailing has been an essential issue to enterprises nowadays. This research applies goal theory to Engel-Kollat-Blackwell model in the omni-channel context and adapt the concept of Harris, Riley & Hand (2018) to shopper journey configurations, including search, evaluation, and purchase of decision making process. This study selected iPhone as the product and collected 179 participants of Gen Y and 126 participants of Gen Z to analyze shopper’s journey. The results indicated Gen Y replied on online review after searching and made own judgement, and preferred store purchase. Gen Z either replied on online review or directly made own judgement after searching, and preferred store purchase. Both generations utilized all types of search and referred to online reviews of evaluation process, and purchased at the store. Our findings also benefit to companies’ mange profitable omni-channel strategy.

show abstract

Section: Markov Chain Switching Modelmentioning

confidence: 99%

Analyzing the Omni-Channel Shopper Journey Configuration of Generations Y and Z

Chang

Chen

2022

Journal of Organizational and End User Computing

View full text Add to dashboard Cite

show abstract

“…For a given test level α, if F A > F α , the dependent variable was considered to be remarkably impacted by factor A . The concentration, optical path length, and spectral bandwidth were taken as the variable factors, λ max and Abs max were considered as the dependent variables, and multifactor analysis of variance was performed where k is the number of levels of the i th control variable and r stands for the number of levels of the j th controlled variable.…”

Section: Methodsmentioning

confidence: 99%

“…The concentration, optical path length, and spectral bandwidth were taken as the variable factors, λ max and Abs max were considered as the dependent variables, and multifactor analysis of variance was performed. 39 i k j j j j y…”

Section: ■ Introductionmentioning

confidence: 99%

Electronic Excitation Characteristics and Spectral Behavior of Phosphate Anions

et al. 2023

View full text Add to dashboard Cite

Absorption spectra are fundamental bases for the qualitative and quantitative analysis of the target chemical, and the development of an analytical model can be improved by studying its characteristics and rules. In the present study, the electronic excitation characteristics of phosphate anions (H 2 PO 4 − , HPO 4 2− , and PO 4 3− ) were analyzed based on the charge-transfer spectrum. In addition, the absorption spectra of phosphate anions at the energy level of PBE0/6-311+G (d,p) were recorded based on the time-dependent density functional theory (TD-DFT) method. Different (HPO 4 2−) n •(H 2 O) 10−n molecular clusters were theoretically constructed, and the combined TD-DFT method and independent gradient model revealed that red shift of the maximum absorption wavelength (λ max ) with the increase of phosphate anion concentration (0−10 mM) may be caused by the decrease of hydrogen bond interaction. In addition, the prominent dispersion in the short-wave region mainly resulted in the red shift of λ max with the increase in optical path length (1−100 mm). Moreover, with the increase in spectral bandwidth (0.4−3.0 nm), λ max slightly blue-shifted because of the increase in energy through the slit, and repeatability of the corresponding absorbance measurement at λ max gradually improved. As the spectral bandwidth increased, light monochromaticity became poor, resulting in the decrease of the linearly fitted correlation coefficient of the concentration−absorbance curve. Finally, the multivariate analysis of variance results showed that the optical path length was the most significant factor that influenced the absorption spectral characteristics of phosphate anions. This study provides a basis for the qualitative and quantitative analysis of phosphate anions by using absorption spectra and also renders a theoretical reference for absorption spectroscopy of other chemicals.

show abstract

“…Companies analyze and manage customers or customer groups based on customer profitability analysis and customer acquisition funnel (Matsuoka, 2021). Customers or customer groups may vary in loyalty, profitability, risk, and other factors .…”

Section: Developing and Building Customer Lifetime Valuementioning

confidence: 99%

Management of Customer Lifetime Value in Organizations

Mandal

2023

Journal of Business Ecosystems

View full text Add to dashboard Cite

Companies should focus on customer lifetime value, its management, and on profitable customers for company growth. The objective of the study is to analyze customer lifetime value and to manage it effectively. The methodology adopted is a conceptual analysis of various aspects of customer lifetime value and its management. Companies should appreciate the importance of customer lifetime value and the connections among customer lifetime value, brand equity, and customer equity. They should develop and build customer lifetime value through various measures (viz., improvement in customer services, customer engagement, enhancing the growth potential of customers, management of unprofitable customers, rewarding profitable customers, and developing customer touch points). They should develop customer loyalty through trust and measure customer lifetime value. Academicians may suggest models that are effective in measuring customer lifetime value and identifying profitable customers. Managers may suggest effective strategies and initiatives for better management of customer lifetime value.

show abstract

A framework for variance analysis of customer equity based on a Markov chain model

Cited by 11 publications

References 37 publications

Analyzing the Omni-Channel Shopper Journey Configuration of Generations Y and Z

Analyzing the Omni-Channel Shopper Journey Configuration of Generations Y and Z

Electronic Excitation Characteristics and Spectral Behavior of Phosphate Anions

Management of Customer Lifetime Value in Organizations

Contact Info

Product

Resources

About