How Does Each ESG Dimension Predict Customer Lifetime Value by Segments? Evidence from U.S. Industrial and Technological Industries
Round 1
Reviewer 1 Report
While this study is quite interesting, it also has several drawbacks.
First, in the introduction, the selling points are very weak. In particular, it is necessary to clarify what the theoretical contributions are.
Second, the core of this study is to consider customer lifetime value by segments, However, there is no comparison of hypotheses based on segments.
Third, what is the segment criteria? There is no difference test results for each segment.
Eventually, all hypotheses must be retested and then, the discussion should be updated based on new findings.
Good luck.
Author Response
Dear Reviewer,
We would firstly like to thank you for your efforts in revising our study. Both the criticisms and the suggestions have been extremely valuable to us and undoubtedly have served to make notable improvements. We are also pleased and grateful for the good scores given to our work in your report.
We attach are the responses to all the suggestions made in the report in the same order they were made and following the same structure. We hope that the arguments and changes are satisfactory and that we have made them easy to identify in this manuscript.
Yours sincerely,
Author Response File: 
Author Response.pdf
Reviewer 2 Report
Dear Authors
The study is interesting, but there is no conclusion, only discussions at the end of the paper. Thus, the ESG reader is left without knowing what conclusion the study reached. This is a flaw in the study.
Where is the conclusion of the paper?
Best Regards
Author Response
We would like to thank you for your efforts in revising our study. We are also pleased and grateful for the good scores given to our work in your report.
Below are the responses to the confusion-mistake made in the manuscript ('discussion' instead of 'conclusions'). The content of this section have also modified. We hope that the arguments and changes are satisfactory.
Yours sincerely,
- Conclusion
In this research, we studied how sustainability effects predict firms’ financial performance. We relied on the customer segments of 547 U.S. firms from the industrial and technological sectors. The proposal prediction model contained ten initiatives/indicators grouped into the three performance categories from the Refinitiv Thomson Reuter Eikon database [33], which sustainability literature also generally recognises: environmental, social and governance [42]. The three initiatives under the environmental performance category are resource use, emissions and innovation. The four initiatives under the social performance category are personnel, human rights, community and product responsibility. The three initiatives under the governance performance category are management, shareholders and CSR strategies.
The predictive quality is satisfied in entire sample and each segment (see table 5). Analysing the main indicator in the entire sample, q2_predict, we obtained a large effect (0.40). R2 indicator shows a moderate effect (0.41) in entire sample. Both indicators of the prediction quality (q2_predict and R2) also improved when we applied the PLS-POS technique in segments. With prediction-oriented modelling, our study shows that sustainability predicts the financial performance (CLV) in all three categories of sustainability initiatives, measured with ten formative indicators of a composite model due to predictive validity. However, four indicators (innovation, shareholder, product responsibility and human rights), whose loadings were low compared to the commonly accepted criteria and whose weights were not significant, can be excluded as they do not contribute to the prediction. According to [46], ‘even if an item contributes little to explained variance in a formative construct, it should be included in the measurement model’. The motive is that dropping a formative indicator implies dropping a part of the composite latent construct. In this sense, we take into account these results of the measurement of the constructs for the purpose of predictive research, to generate predictions with current data as accurately as possible.
The result of our study was proof of the hypotheses for the entire model (see table 6). Of the three antecedents of CLV, social dimension is the main precursor of CLV with a direct effect coefficient equal to 0.38, environmental dimension is the second precursor of CLV with a direct effect coefficient equal to 0.18 and finally, governance dimension is the third precursor of CLV with a direct effect coefficient equal to 0.16. According to the aim of this study, firm's sustainability assessment is also tested by each driver (ESG dimension) in each segment. Thus, we compare hypotheses among segments that predict CLV. As a result, the three customer-predicted segments also demonstrated that the values of the path coefficients were very different among them as well as with respect to the entire model, which obtained path values between 0.10 and 0.40 in three performance categories (ESG). The prediction in segment 1 was characterised by only a poor direct effect (0.15) of the environmental performance category on the CLV, which also suggests an absence of impact on the CLV by this segment. The governance performance category showed a medium and positive effect (0.36), and the social performance category showed a medium-high and positive effect (0.49), which suggests both mixed application of sustainability initiatives and their impact on the CLV of this segment. The prediction in segment 2 was characterised by nonsignificant effects of both the social performance category (-0.06) and the governance performance category (-0.09) on the CLV, which also suggests an absence of impact by this segment on the CLV. The environmental performance category showed a greater effect (0.93), which also suggests a greater full impact on the CLV of this segment. The prediction in segment 3 is characterised by a greater full direct effect (0.82) of the social performance category on the CLV and poor impact of the governance category. The significant and negative effect of the environmental category on the CLV suggests that a nonprofitable effect is mixed with the rest of the sustainability initiatives of this segment.
This study’s contribution to the literature is twofold. First, as the relationship between sustainability and CFP is still unclear, this study explains the impact of each ESG dimension on CFP rather than considering the sustainability initiatives as a whole. Previous research has explored sustainability as a form of management of or responsibility for the environment; however, it has failed to effectively consider the effects of each individual ESG dimension on financial results. Thus, we contribute to the literature on the relationship between sustainability and financial performance valuable information about ESG dimensions’ effects on CLV. While firms may be close in overall ESG levels, the three dimensions levels often vary considerably. As such, firms emphasise different elements to varying degrees in their ESG plans. This variance enables us to discuss each element’s individual economic productivity by considering each predictive segment. This segmentation-based methodology revealed the relationship between the three segments and the three ESG strategies. In summary, varying degrees of every ESG initiative in segment 1 achieved financial performance relying on customer marketing metrics. However, in segment 2, only environmental initiatives achieved a financial performance relying on customer marketing metrics. In segment 3, firms mainly applied social initiatives to achieve a financial performance relying on customer marketing metrics as a result of both positive governance and negative environmental initiatives having a poor effect on CLV. This study’s second contribution is its evaluation of sustainability initiatives with a customer-based corporate firm valuation (CBCV) approach. A CBCV approach suggests that customer metrics derived from customers’ responses to a firm’s marketing initiatives represent a good way to operationalise firm-market value. This study shows that the identification of different sustainability initiatives can lead to economically productive strategies in terms of producing a higher aggregated CLV level. In turn, the customer-centric perspective in the marketing literature proposes that marketing-related decision-making should occur on the basis of projected financial impact. A firm can design better strategies focused on their value proposition, achieving a different CLV as a marketing metric of the firm’s financial performance. In this way, this study goes beyond the existing research on ESG dimensions and FP that measured FP via accounting data (e.g., ROA, ROE, Tobin’s q). Notably, the current literature is unclear with regard to its outcomes, as such financial metrics can be represented as both short-term and long-term data when researchers use panel data. In fact, accounting and financial data are focused on transparency—not the transformative value of social changes. Consequently, firms can assess and predict financial performance based on the outcomes of sustainability initiatives when using the CLV aggregated level. In this context, both shifts in the firm’s marketing function towards sustainability and the evolving customer landscape reflect changes that can appear in the firm’s financial results. While sustainable consumption does not provide individual or private benefits to consumers, it contributes to the collective good. The motivation behind sustainable consumption is not its direct benefit to customers. However, this value-in-behaviour on the part of consumers benefits firms so long as it is reflected in their financial results from a communal perspective.
From a management point of view, sustainability initiatives are a good predictor of CLV. Our study defined CLV as marketing performance included both short- and long-term indicators, to predict within a single timeframe. The tests carried out on the quality of the prediction show that firms can forecast by gathering the results in two timeframes, using net sales in the short term and free cash flow in the long term. As such, policymakers can act differently regarding the fear that sustainability initiatives require a long term to have a positive effect. Previous studies with panel data underline that sustainability initiative investments add value to stakeholders in the long term but are not profitable in the short term. In contrast, our study shows that it does not extend to all stakeholders, so managers must be concerned with customers when sustainability initiatives are in an initial stage. In addition, our study identified four initiatives that have no effect on the customer-based firm’s financial performance (innovation, shareholder, product responsibility and human rights), suggesting that managers can identify more economically productive sustainability initiatives.
Regarding limitations and future lines of research, the first limitation of this study is the sample of listed firms from the Refinitiv Thomson Reuters Eikon database [33], which is specific to the United States for both industrial and technology industries. In general, studies of the relationship between sustainability and financial results are usually adjusted to a single region, due to the market rules of listed firms. However, this belief could be relaxed in studies predicting financial results based on clients. Therefore, we suggest a major study with more countries and industries. A second limitation refers to the CLV metric because we consider such profit margins as free cash flow and net sales. Parameters of CLV remain constant over time, even for retention rate, so we do not include new customers or acquisition costs in the CLV calculation. The large CLV literature shows how to parameterise CLVs, so we can apply it to customer acquisition and retention strategies from different countries and sectors, as well as other operational aspects of noncontractual models where purchase frequency is important. In contrast, the proposed basic CLV model is simple to apply and a good indicator of the value of the firm, based on customers. Finally, a third limitation is the three categories with only ten sustainability indicators as drivers of the firm's financial performance in a prediction-oriented model. Although it is relevant for sustainability marketing research, we believe that it is only a step towards the future understanding of valid sustainability models that employ new explanatory variables and forecasting by customer-based financial and nonfinancial outcomes.
Reviewer 3 Report
Dear Authors,
Congratulations to the authors for their interesting article!
This article has considerable potential to contribute to further research on the relationship between the 9 environmental, social and governance (ESG) dimensions of corporate sustainability initiatives and customer lifetime value (CLV).
This article produces an interesting study that brings to the fore important issues on the impact of each ESG dimension on companies' financial and market performance.
The area of analysis is extremely interesting and challenging in the current context of globalisation, sustainable marketing and economic and political change.
The part dedicated to the literature review framework is well done by referring to the analysis of the concepts of Customer Lifetime Value in the context of sustainable marketing, ESG dimensions of sustainable marketing, concepts that are then reflected in the authors' research.
Thus, elements such as marketing performance, sustainable marketing, competitive intelligence, market intelligence need to be considered to create contextual solutions to achieve firm performance.
In this context, rapid adaptation to new market challenges and requirements is necessary. Practically, through this study, the authors highlight the relationship between environmental, social and governance (ESG) dimensions and financial outcomes impacting on performance indicators, with the identified model having a positive and significant impact on sectoral economic performance.
The paper contains good documentation on predictive performance indicators as well as on how to exploit potential opportunities and neutralize potential threats.
The study design and data processing tools are complex and focus on quantitative analysis using SEM-PLS as well as qualitative longitudinal fuzzy set comparative analysis (fsQCA).
The sample studied is representative and the results obtained can serve as benchmarks for managerial decisions.
The authors highlight that sustainability initiatives are a good predictor of financial performance, as long as the heterogeneity of firms is taken into account.
The discussion and conclusion component is consistent and highlights the importance of the topic and research for readers.
The bibliographical references correspond to the topic addressed in the paper.
The authors have used both recent references in the literature and the results of studies relevant to the phenomenon studied. The article is correctly referenced.
Author Response
Dear Reviewer,
We would like to thank you for your efforts in revising our study. We are also pleased and grateful for the good scores given to our work in your report.
Yours sincerely,
Round 2
Reviewer 1 Report
The revision is acceptable.
Reviewer 2 Report
Dear Authors
The manuscript has improved with the changes made. Congratulations.
