Uplift modeling and its implications for B2B customer churn prediction: A segmentation-based modeling approach

Caigny, Arno De; Coussement, Kristof; Verbeke, Wouter; Idbenjra, Khaoula; Phan, Minh Hieu

doi:10.1016/j.indmarman.2021.10.001

Cited by 31 publications

(8 citation statements)

References 51 publications

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“…Prescriptive analytics can be further enhanced through AI methods, which are now only conceptually developed (Lepenioti et al ., 2020). Only a handful of organizations are implementing it at an early stage (De Caigny et al ., 2021).…”

Section: Discussionmentioning

confidence: 99%

Bibliometric review on human resources management and big data analytics

Fauzi

Kamaruzzaman²,

Rahman³

2022

IJM

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PurposeThis study aims to provide an in-depth understanding of big data analytics (BDA) in human resource management (HRM). The emergence of digital technology and the availability of large volume, high velocity and a great variety of data has forced the HRM to adopt the BDA in managing the workforce.Design/methodology/approachThis paper evaluates the past, present and future trends of HRM through the bibliometric analysis of citation, co-citation and co-word analysis.FindingsFindings from the analysis present significant research clusters that imply the knowledge structure and mapping of research streams in HRM. Challenges in BDA application and firm performances appear in all three bibliometric analyses, indicating this subject’s past, current and future trends in HRM.Practical implicationsImplications on the HRM landscape include fostering a data-driven culture in the workplace to reap the potential benefits of BDA. Firms must strategically adapt BDA as a change management initiative to transform the traditional way of managing the workforce toward adapting BDA as analytical tool in HRM decision-making.Originality/valueThis study presents past, present and future trends in BDA knowledge structure in human resources management.

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Section: Discussionmentioning

confidence: 99%

Bibliometric review on human resources management and big data analytics

Fauzi

Kamaruzzaman²,

Rahman³

2022

IJM

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“…Customer and supplier segmentation are at the core of supply chain management (Cooper et al ., 1997; Lambert, 2014). When properly implemented, segmentation should enable managers to identify supply chain relationships that are candidates for partnership, then tailor specific strategies to leverage the profit potential for each relationship (McDonald and Dunbar, 2012; De Caigny et al ., 2021). The literature on segmentation has been focused mainly on B2C relationships, and the few papers on B2B contexts address alternative bases of categorization rather than seeking empirical evidence of the outcomes of segmentation (Day et al ., 2010).…”

Section: Introductionmentioning

confidence: 99%

Are supply chain partnerships developed and implemented according to their potential?

Enz

Lambert

2023

IJLM

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PurposeGrounded in contingency theory and strategic fit theory, the goal for this research was to determine if managers differentiate in terms of the degree of partnership when allocating resources for planning, joint operating controls, communication and other management components to relationships and if this differentiation is based on the Partnership Model (Lambert et al., 1996).Design/methodology/approachIn total, 381 managers representing 31 relationships participated in one-and-a-half-day partnership meetings, and the authors analyzed how the management components were implemented in each relationship compared to the recommendations in the Partnership Model.FindingsManagers did not differentiate types of partnerships which led to over-resourcing relationships with low potential and under-resourcing those with the highest potential for creating value. The principles of contingency theory and strategic fit were not used for managing relationships.Research limitations/implicationsContingency theory combined with the relationship view suggests that management components should not be implemented at the same level for all relationships, but in the 31 relationships studied different partnership types were not managed based on their potential.Practical implicationsThe research reinforces the need for a formal structure like the Partnership Model to establish joint goals for a relationship and guide management in implementation.Originality/valueEffective supply chain management depends on the ability of managers to differentiate among partnership types and fit relational mechanisms that are appropriate. However, researchers tend to generalize their findings to all partnerships regardless of potential. The authors found support for the Partnership Model published in IJLM in 1996 as a method to resource different types of partnerships following the contingency perspective and strategic fit theory.

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“…This would further aggravate the issue of randomized treatments on high value customers, as they are now a major part of the customer base. This entails that a profit-driven extension to the CCU B2B approach suggested by De Caigny et al (2021) would not be suitable for all B2B firms, and that a profit-driven CCP alternative should exist next to it.…”

Section: Introductionmentioning

confidence: 99%

B2Boost: instance-dependent profit-driven modelling of B2B churn

et al. 2022

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The purpose of this paper is to enhance current practices in business-to-business (B2B) customer churn prediction modelling. Following the recent trend from accuracy-based to profit-driven evaluation businessto-customer churn prediction, we present a novel expected maximum profit measure for B2B customer churn (EMPB), which is used to demonstrate how current practices are suboptimal due to large discrepancies in customer value. To directly incorporate the heterogeneity of customer values and profit concerns of the company, we propose an instance-dependent profit maximizing classifier based on gradient boosting, named B2Boost. The main innovation of B2Boost is the fact that it considers these differences and incorporates them into the model construction by maximizing the objective function in terms of the EMPB. The results indicate that the expected maximal profit gains made in our analyses are substantial.This study arguments towards both deploying models based on customer-specific profitability differences, as well as evaluating based on our instance-dependent EMPB measure.

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Uplift modeling and its implications for B2B customer churn prediction: A segmentation-based modeling approach

Cited by 31 publications

References 51 publications

Bibliometric review on human resources management and big data analytics

Bibliometric review on human resources management and big data analytics

Are supply chain partnerships developed and implemented according to their potential?

B2Boost: instance-dependent profit-driven modelling of B2B churn

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