Ananth V. Iyer

Problem definition: Stockists are the entity in the supply chain who deliver to the millions of small shops that account for over 90% of retail sales in India. The stockist purchases product from the manufacturer, develops retailer interest in carrying the product, solves the logistics problem of delivery to retailers, and manages retail credit and money collection. In return, the stockist is provided assistance by the manufacturer and paid an associated margin that is a percent of the product’s retail price. We observed relatively low distribution margins offered to the stockists in India that was a surprise given infrastructure and financing challenges. We noted that the low margins are enabled by the efficiency in product delivery and demand stimulation induced by the stockist. In this paper, we focus on the analysis of screening contracts offered by manufacturers to stockists. Methodology: We use a principal–agent model structure and model the routing cost, inventory cost, and demand impact of the stockist’s capability. We then use a substitutes or complements relationship between manufacturer assistance and stockist impact to understand the optimal contract structure—i.e., level of assistance and associated retail margin. We describe the economics associated with the stockist, provide data regarding the margins and assistance provided by the manufacturer, and use the model to understand their use in developing an effective supply chain. Results: Our model uses three parameters to show that a manufacture can adjust the level of spatial retailer intensity and thus the impact of the stockist in generating demand, the fraction of high-performing stockists associated with the manufacturer and the nature of the relationship between assistance provided and its impact on the stockist’s performance (i.e., complements or substitutes relationship), to attain superior performance. Academic/practical relevance: We parameterize data from Indian firms in the consumer goods industry to understand the observed assistance provided by the manufacturer to the stockist, and associated margins. We then use our model to understand actions taken by a manufacturer in the Indian market. Managerial implications: Our analysis provides a framework for manufacturers to design screening contracts for stockists who play a vital role in managing the fragmented retail markets in developing countries. The online supplement is available at https://doi.org/10.1287/msom.2018.0722 . This paper has been accepted for the Manufacturing & Service Operations Management Special Issue on Value Chain Innovations in Developing Economies.

This special issue presents production and operations management research papers from emerging markets worldwide, focusing on their unique contexts, institutions and markets. Collectively, they offer insights into the unique operations management strategies and practices that firms face in emerging markets. The magnitude and pace of change is staggering. As a result, execution and managing growth in these emerging markets represents both huge operational and supply chain risks, and simultaneously vast opportunities. We are confident that these papers stimulate new operations management research while highlighting the effective use of different research methodologies. We welcome you to enjoy this special issue of POMS. We express our deep gratitude to editorial team for their support. We especially wish to thank the authors for their contributions to this special issue.

We study the linkages between firm‐level quality initiatives such as quality management systems (QMS) and total quality management (TQM) and output productivity in the Indian auto component industry. We use externally validated quality certification and quality awards as proxies for QMS and TQM, respectively, as it is difficult to directly measure the QMS and TQM efforts of firms. We use an unbalanced panel of 220 firms and a balanced panel of 73 firms from the Indian auto component industry over the period 1993–2006 to study these links. Both parametric as well as non‐parametric approaches are used, as appropriate, to measure the rate of change in productivity and the impact of quality initiatives on productivity change during this period. We determine the proportion of productivity resulting from technical change and relative efficiency change, thus providing insights into the structure of productivity improvements. We find that TQM efforts resulted in a high rate of productivity change (11%) in the award‐winning firms after the award. On the other hand, pre‐certification productivity change due to QMS was 5% and post‐certification change was 3.6%. In the periods prior to certification, productivity change was driven mainly by technical change; whereas the source of productivity change after certification is mixed. However, prior to awards, productivity change was driven mainly by relative efficiency change, whereas post‐award productivity change was due to technical change. The results suggest that management focus on attaining certification did generate conceptual learning (linked to technical change) during the period leading to certification, but these effects were not significant after certification. The results also suggest that the TQM programs generated significant productivity gains in the long run, although setting the associated systems in place did not result in significant productivity change prior to winning awards. Thus, the study provides direct but nuanced evidence linking quality certification as well as the adoption of TQM programs to the associated conceptual and operational learning processes and their impact on the change in productivity.

We model the impact of information visibility in a two-level supply chain consisting of independent retailers who share upstream supply. The manufacturer supplies similar products to the two retailers and each retailer serves its independent end market. Retailers face one period of demand and satisfy the demand by ordering in the first period or back-ordering some of the demand and satisfying it in the second period. The wholesale price in the second period is decreasing in the total order size across the two retailers in the first period. This decrease in wholesale price captures the market learning effect of aggregate orders that has been extensively documented in empirical literature. We use a game-theoretic framework to investigate the ex-ante incentives for retailers to share their private demand information. We show that: (1) retailers have no incentives to share information about their private values when equilibrium order quantities are interior, i.e., the order size is between zero and the demand; (2) partial information sharing may be the equilibrium strategy for retailers when equilibrium order quantities are binding on the demand. Finally, numerical examples are provided for illustration. This paper thus identifies conditions under which different levels of information sharing may be the equilibrium outcomes in a supply chain.