On the quest for supply chain transparency through Blockchain: Lessons learned from two serialized data projects

The ability to look into the supply chain has long enticed SCM scholars and practitioners. The possibilities created by such visibility are endless—from risk reduction and continuity planning to inventory management and cost reduction, nothing is off the table when end‐to‐end visibility is a possibility. Because of such enticements, there is usually much buzz in the industry every time a new technology that promises visibility and transparency is brought forward. Yet, years later, stories sometimes emerge that said technologies either failed to deliver or were not everything they were made out to be. Blockchain is yet another emerging technology in this space. Some consultants promise that it will be the final answer to the transparency and visibility woes that companies currently face. Yet, there is little empirical investigation regarding how the technology may benefit adopters, what the bottlenecks may be, and to what extent it may be able to deliver on these promises, without massive system‐wide upgrades of extant hardware and computing prowess. The current study takes a step in this direction by investigating a blockchain‐driven proof of concept across an industry consortium to identify promises, possibilities, and challenges of blockchain.     

Linking Order Fulfillment Performance to Referrals in Online Retailing: An Empirical Analysis

Referral management for online retailers is a strategically important activity, as referrals offer a highly cost‐effective method of customer acquisition. In fact, online customers mention referrals as the second‐most common reason for choosing to shop at a particular retailer, second only to search engine suggestions. However, while online retailers are able to improve their visibility on search engines through focused keyword insertions, they are often unable to pinpoint the drivers of referral behavior among their customers. The current research examines the relationship between two key dimensions of online retailing: order fulfillment cycle times and referral behavior. Employing a theory of customer appraisal and empirically testing the ensuing model using structural equation modeling, we find that excellent order fulfillment is instrumental in generating referrals for the online retailer, even after factoring in product quality.     

The customer consequences of returns in online retailing: An empirical analysis

Pressure continues to build on the operations management function to facilitate system and firm level benefits. In the online marketplace, one area of growing interest is that of product returns. Though commonly viewed as a cost center from an operations perspective, operations’ actions have the potential to strongly influence future customer buying behavior in several ways. Using an archival database of actual purchase and returns history provided by a moderately sized online retailer, this study examines the relationship between a customer's experience of product returns, and subsequent shopping behavior. Employing transaction cost, consumer risk, and procedural justice theories, we demonstrate that the returns management process, rather than being regarded as an afterthought to the production and deployment of goods, can significantly and positively influence repurchase behavior. Additionally, we provide evidence that certain customers should be considered for prioritization in the returns process. We suggest ways through which operations managers can take care in discharging their responsibilities in this area – to make returns processing more than simply a “necessary cost of doing business” rather, using it to their advantage in engendering repeat and increased purchase behavior.     

On the “Invisible Inventory Conundrum” in RFID‐Equipped Supply Chains: A Data Science Approach to Assessing Tag Performance

Recent trade reports suggest that RFID implementation continues to lag lofty projections. A primary concern is that, despite the high cost of implementing RFID systems, realized read‐rates fall short of expectations. This results in the invisible inventory conundrum whereby tagged merchandise may still not be accurately represented in inventory records. Drawing from data science to address this issue, we ask: How can directed data mining models be used to identify laboratory test performance criteria for RFID tags that operate reliably across the idiosyncratic facilities (i.e., unique DCs, warehouses, and stores) that comprise apparel retailers’ supply chains? We investigate this question by advancing a methodology that integrates laboratory test performance data, field tests of RFID tags fixed to apparel items and scanned under normal operating conditions, and the application of five directed data mining models to the integrated data set of laboratory and field test results. Our analyses of 45,416 observations show that two directed data mining models may identify—with near‐100% accuracy—laboratory test criteria that discriminate tags having 99% or greater read‐rates in the field. Accordingly, our study validates a generalizable methodology for identifying technical performance standards for tags that operate reliably within apparel retailers’ supply chains.     

Can Robust Optimization Offer Improved Portfolio Performance? An Empirical Study of Indian market

Journal of Quantitative Economics - The emergence of robust optimization has been driven primarily by the necessity to address the demerits of the Markowitz model. There has been a noteworthy...     

The role of physical distribution services as determinants of product returns in Internet retailing

Pressure continues to build on Internet retailers to squeeze out inefficiencies from their day-to-day operations. One major source of such inefficiencies is product returns. Indeed, product returns in Internet retailing have been shown to be, on average, as high as 22% of sales. Yet, most retailers accept them as a necessary cost of doing business. This is not surprising since many retailers do not have a clear understanding of the causes of product returns. While it is known that return policies of retailers, along with product attributes, are two important factors related to product return incidents, little is known about which aspects of the online retail transaction make such a purchase more return-prone. In the current study, we seek to address this issue. We use a large data set of customer purchases and returns to identify how process attributes in physical distribution service (PDS) influence product returns. The first attribute involves perceptions of scarcity conditions in inventory availability among consumers when retailers reveal to consumers information on inventory levels for the products that they intend to buy. Our results show that orders in which items are sold when these conditions are revealed to shoppers have a higher likelihood of being returned than orders in which these conditions are not revealed. While prior research has argued that inventory scarcity perceptions have an effect on purchases, our findings suggest that they are also related to the likelihood of these purchases being returned. The second attribute involves the reliability in the delivery of orders to consumers. We find that the likelihood of orders being returned depends on the consistency between retailer promises of timeliness in the delivery of orders and the actual delivery performance of the orders. Moreover, we find that the effect that consistency in the delivery has in the likelihood of returns, is stronger for orders that involve promises for expedited delivery than for orders with less expeditious promises. That is, although the occurrence of returns depends on the delays in the delivery of orders to consumers relative to the initial promises made by the retailers, this effect is more notable for orders that involve promises of fast delivery.     

Covid-19 and heuristic biases: evidence from India

Stock markets worldwide have witnessed high volatility during the year 2020 owing to the eruption of Covid-19. Due to the world’s unprecedented economic challenges, this study could potentially guide financial advisors and individual investors in dealing with pandemics. An association between investors’ perception toward the intensity of Covid-19 and heuristic biases is analyzed using the responses of 290 stock investors of National Capital Region (NCR), India. The data are validated through Cronbach’s alpha, and the model fit is analyzed using EFA. Confirmatory factor analysis (CFA) is employed to investigate the relationship between Covid-19 and heuristic biases. Covid-19 does not have any influence on the overconfidence of investors. A significant positive relationship is found between Covid-19 and the remaining three heuristics, i.e., availability, anchoring, and representativeness. The present study analyzes the association between Covid-19 and specific investors’ bias only and should not be interpreted for causality. The study has the potential to guide investors in understanding the errors they are making while investing during the pandemic and the ways to deal with them. The study could provide insights to the financial advisors in understanding their customers. The implications of the study may include inputs of the errors committed by them during the pandemic. Despite the fact that an enormous amount of literature exists in the field of investors’ sentiment, a scarcity of literature is available that measures the relationship between heuristic biases and the perceived impact of the pandemic. The current study attempts to fill this gap in the literature.

     

On Ethical Violations in Microfinance Backed Small Businesses: Family and Household Welfare

Journal of Business Ethics - The microfinance business model focuses largely on lending to the woman in the household, rather than the man. The belief is that women are more trustworthy borrowers...     

On the Viability of Fixing Leaky Supply Chains for the Poor Through Benefit Transfers: A Call for Joint Distribution

Supply chain managers have yet to solve the conundrum of profitably distributing and selling to the poorest consumers. Most prevailing methods of addressing this problem take one of two contrasting approaches—that is, (1) price subsidization or (2) benefits/cash transfers. The former has been heavily studied in the literature with the consensus being that it is highly inefficient and prone to leaks. We investigate the viability of the latter by focusing on how branching out to reach the poorest customers impacts the performance of banks. Results indicate that the impacts of this approach are deleterious, thereby questioning its commercial scalability. Therefore, we argue that this approach may also have only limited potential in terms of being an effective, large‐scale solution to the problem of access for the poor. Instead, a third approach to achieve scalable Bottom of the Pyramid growth and development needs to be considered—cultivating partnerships through joint distribution.     

Electronic Logistics Service Quality (e‐LSQ): Its Impact on the Customer’s Purchase Satisfaction and Retention

The Internet retailing industry continues to grow rapidly. Several Internet retailers are, however, struggling to retain customers due to the high level of competition among incumbents. We propose that customer satisfaction with the order fulfillment process is an important determinant of overall customer satisfaction with the retailer, as well as with the extent of customer retention enjoyed by the retailer. This paper offers a new concept for electronic logistics service quality and investigates the relationship between the quality of online fulfillment and the ensuing retention of customers, using archival data on 260 online retailers. The structural equation model results indicate that satisfaction with the physical distribution quality and cost are positively related with customer’s purchase satisfaction and customer retention. Additionally, the results indicate that while purchase satisfaction is a strong indicator of customer retention, underlying drivers of purchase satisfaction do not have nearly the same impact on customer retention directly as they have on purchase satisfaction.