Managing product value uncertainty: The role of ex ante product value delivery

Abstract

This study investigates how online retailers should solve the problem of product value uncertainty through an ex ante product value delivery policy. We construct an endogenous matching probability model depending on the ex ante strategic choice among various product value delivery measures, such as displaying product information online, opening product reviews, building a virtual showroom, and building a physical showroom. This model is different from the exogenous matching probability assumption in the literature. When the matching probability is exogenously given, the retail price reduction policy is commonly used to mitigate product value uncertainty. In contrast, when retailers can determine the matching probability through the ex ante strategic choice for the product value delivery measures, increasing the retail price to rely more on ex ante value delivery may be optimal in the mitigation of a more serious product value uncertainty. In addition, we examine the interaction between the ex ante product value delivery and the ex post return policy. The results show that the adoption of the ex post mitigation policy may encourage or discourage the adoption of the ex ante mitigation policy depending on the cost input for product value delivery and the customers’ surplus loss caused by a mismatch.

Keywords:

• Marketing
• e-commerce
• pricing
• product value uncertainty
• product value delivery
• endogenous matching probability

Acknowledgements

The authors sincerely thank the Editor-in-Chief, the associate editor, and the anonymous reviewers for their constructive comments and suggestions that have greatly improved the paper.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 In the basic model of this section, we assume that consumers do not bear any costs for product return. Our model could be easily extended to contain the return cost. Let $r$ be the return cost for each returned product that the consumers should pay. Through the similar analysis method in this section, we can obtain the online retailer’s profit maximization problem. It is optimal for the online retailer to choose among the following decisions.

(i) $r<p\le r{+\theta }^L:$

(1) If $0<r\le {\theta }^H,$ $r<p\le \min \left\{r{+\theta }^L,{\theta }^H\right\}$ and $\max \left\{\frac{p-{\theta }^L}{{\theta }^H-{\theta }^L},0\right\}<m\le \min \left\{\frac{{\theta }^{L}r}{\left({\theta }^H-{\theta }^L\right)\left(p-r\right)},1\right\},$ the profit function is as follows

$$\underset{r<p\le \mathit{min}\left\{r{+\theta }^L,{\theta }^H\right\}}{\mathit{max}}\pi \left(m,p\right)=p\left[1-\frac{p}{\mu \left(m\right)}\right]-\frac{1}{2}K{m}^2;$$

(2) If $0<r\le {\theta }^H-{\theta }^L,$ $\frac{{\theta }^{H}r}{{\theta }^H-{\theta }^L}<p\le r{+\theta }^L$ and $\frac{{\theta }^{L}r}{\left({\theta }^H-{\theta }^L\right)\left(p-r\right)}<m\le 1,$ the profit function is as follows

$$\underset{\frac{{\theta }^{H}r}{{\theta }^H-{\theta }^L}<p\le r{+\theta }^L}{\mathit{max}}\pi \left(m,p\right)=p\left[1-\frac{mp+\left(1-m\right)r}{m{\theta }^H}\right]+\left(1-m\right)\left[\frac{p-r}{{\theta }^L}-\frac{mp+\left(1-m\right)r}{m{\theta }^H}\right]\left(-p\right)-\frac{1}{2}K{m}^2=p-\frac{\left(1-m\right)p^2-\left(1-m\right)pr}{{\theta }^L}-\frac{m{p}^2+\left(1-m\right)pr}{{\theta }^H}-\frac{1}{2}K{m}^2.$$

(ii) ${r+\theta }^L\le p\le r{+\theta }^H:$

If $0<r\le {\theta }^H-{\theta }^L,$ $r+{\theta }^L<p\le {\theta }^H$ and $\frac{r}{{\theta }^H-\left(p-r\right)}<m\le 1,$ the profit function is as follows

$$\underset{r+{\theta }^L<p\le {\theta }^H}{\mathit{max}}\pi \left(m,p\right)=p\left[1-\frac{mp+\left(1-m\right)r}{m{\theta }^H}\right]+\left(1-m\right)\left[1-\frac{mp+\left(1-m\right)r}{m{\theta }^H}\right]\left(-p\right)-\frac{1}{2}K{m}^2=mp\left[1-\frac{mp+\left(1-m\right)r}{m{\theta }^H}\right]-\frac{1}{2}K{m}^2.$$

The optimal decisions could be analyzed by using the similar method in this section. The main results will still hold when the return cost $r$ is considered.

Additional information

Funding

This paper is supported by National Natural Science Foundation of China (NSFC) under Contract Nos. 71602108 and 11871327.