Forbes 30 Under 30 – Alumnus Prof. Srijan Kumar

IIT Kharagpur alumnus, Prof. Srijan Kumar has been included in Forbes 30 under 30 in Science,
Class of 2022!

Prof. Kumar is an Assistant Professor at the Georgia Institute of Technology. He is a specialist in
AI, ML, and Data Science. In his attempt to make the internet a safer place he is involved in
developing Data Science and Machine Learning solutions to combat fraudsters, trolls, and other
malicious entities. His research has influenced Twitter’s Birdwatch platform. It is also
implemented by Flipkart.

An alumnus of the 2013 batch from the Computer Science and Engineering Department of the
Institute, Prof. Kumar went on to pursue his Masters and a Ph.D. from the University of
Maryland, College Park.

He said that he is ever grateful to the teachers at the Computer Science Department. He specially
conveyed his gratitude to his mentor Prof. Partha Pratim Chakrabarti. He also thanked Prof. Niloy
Ganguly and Prof. Animesh Mukherjee for introducing him to Machine Learning and Data
Science.

Content Writer:- Arkaprabha Pal, Office of Alumni Affairs & Branding

Email: pal18arkaprabha@gmail.com

Gone in a flash?

It is that time of the year. The beginning of a string of festival months that keep both online and offline stores busy. It is also that time when customers are most likely to be wooed with online flash sales (OFS) that give them the opportunity to purchase goods at large discounts.

Big e-tailers prepare for OFS as they would prepare for war as this is also their golden chance to not only attract buyers but also ensure that disloyal customers come back to their site. They spruce up the operations, marketing and logistics components, especially beefing up the technology backbone in preparation for the onslaught.

Most of the preparation is done keeping in mind pre- and during- OFS services, given that such sale invariably carries risk of service failure. However, latest research by a joint team which comprised members from the Vinod Gupta School of Management of IIT Kharagpur, shows that there ought to be as much preparation for post-sales operations for OFS. This is because a responsive recovery protocol does wonders to the buyer’s self-esteem and level of satisfaction, thereby ensuring e-loyalty to the e-tailer.

One might recall with ease “The Big Billion Day” sale introduced by Flipkart in October, 2014 that received a massive backlash from customers due to technical glitches that the site encountered as it’s servers crumbled under the pressure of heavy traffic. A generic apology email issued to all customers post the incident was intended to restore the buyer’s self-esteem and trust in the website.

Why buyer’s self-esteem? This is because, in case of OFS, which is a ‘time-pressured failure-prone environment’, the opportunistic customer enters into play in order to secure a short-term financial gain despite knowing the potential risk of service failure. In case of service failure, the customer attributes the failure to self, which is what makes the failure recovery process more complicated. However, as this study finds, perceived justice with service recovery (PJWSR) in the mind of the customer could go a long way in leading to customer satisfaction (post-recovery satisfaction or SSR). This may even lead to e-loyalty, which is what all e-tailers target.

A few prior studies have explored customer behaviour in familiar online environments, but none have examined e-service failures or the consequences of recovery of those failures. The joint study by the research team not only looks in depth into e-commerce service failure and contributes to customer opportunism literature, but also proposes a new contextual scale for measuring OFS e-commerce service failure and the impact of recovery-induced justice on a customer’s loyalty. The research team consisted of Prof. Saini Das from VGSoM, Prof. Abhishek Mishra from IIM Indore and Prof. Dianne Cyr from the Beedie School of Business, Simon Fraser University, Vancouver, Canada.

Drawing from previous research by Tan et al., the joint study classifies service failure as functional, information and system failures. The first kind of failure may include website crashing, becoming inaccessible during purchase, or increasing customer efforts for making a purchase. Incorrect or incomplete information regarding product specifications, offers, hidden charges, firm policies, security features etc constitute information failure. System failures include poor overall system quality of an e-commerce website which inhibits effective product/service delivery to end-customers.

It is not that customers are unaware of the risks. “Yet, such failures during OFS cause customer disappointment and have a negative effect on the PJWSR,” says the study, probably more than what would be expected under normal circumstances.

The study defines PJWSR as the “customer’s cognitive and hedonic evaluations of the efficacy of the overall recovery process, including apology and subsequent compensations received after the service failure….” PJWSR is composed of all three – Distributive justice, which indicates the customer’s perception of fairness of the monetary/non-monetary compensation received as part of the post-failure recovery process; Procedural justice, which refers to the customer’s belief about the adequacy of the flexibility and efficiency of the recovery process itself; and Interactive justice, which refers to the extent of fairness, honesty, courtesy and empathy with which service providers communicate with the customers during the recovery process.

The recovery process is crucial in the case of OFS because customer opportunism has such a dominant role to play in this kind of sale. The dynamics of recovery in OFS is very different from that in a regular shopping environment since an opportunistic customer is easier to recover despite her dissatisfaction due to failure. The study says, “…an opportunistic customer, with failure self-attribution and lower expectation of acquisition from an OFS, considers a service recovery as more judicious, compared to a non-opportunistic customer, even though (s)he is equally disenchanted with the failure.”

The study goes on to say that PJWSR, by mitigating the negative experience of the customer in case of an OFS failure, makes the customer satisfied and lowers their intention to switch.

The study has the job cut out for managers of the e-tail business. They must not only ensure that their OFS avoid functional, information and system failures. They should also be extremely concerned about providing appropriate service recovery that includes a high sense of distributive, procedural and interactive justice for customers after a service failure.

In fact, the study suggests, the e-tailer can adopt targeted service recovery efforts for OFS customers. They have to avoid failures, but “if the failure does happen, they need to create justice through effective recovery” in order to “latch” on to customers who engaged with them out of opportunism in the first place.