Department of Management

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Challenges in Adoption of Business Analytics by Small Retailers: An Empirical Study in the Indian Context
(ACM Digital Library, 2023-01) Nagpal, Gaurav; Nagpal, Ankita; Jasti, Naga Vamsi Krishna
Business analytics are transforming every industry in modern times, and the retail sector is not an exception to this. However, the adoption of analytics among small and medium enterprises is quite limited. There is a decent amount of research that has been done in the recent past on identifying the barriers of digitalization for small and medium enterprises. But any such work is missing in the case of analytics. Also, the small retailer, in particular, has been left untouched by the existing research studies when it comes to identifying what prohibits him from the use of analytics for making business decisions. Using a scientific way of data collection from small and mid-sized retailers and from retail industry experts, this study explores why the local retailers are reluctant to use analytics in their work and what can be done to make them more comfortable with the use of analytics. The study also proposes a novel framework for adoption of data analytics and titles it “SPEFSERT Framework.”
Conjoint Analysis based Predictive Analytics to study the employee attitude towards virtual and digital work practices in IoT work environments
(IEEE, 2023-02) Nagpal, Gaurav; Nagpal, Ankita; Jasti, Naga Vamsi Krishna
Covid-19 has been one of the most disruptive pandemics to date. Among the other aspects of disruption, it also disrupted the way people work in organizations. Many of the organizations surrendered their offices for good. However, there are many ill effects of these unconventional work practices also. This research study aims to explore the perception of the employees towards the adoption of Virtual and flexible work practices. The study uses a conjoint analysis approach on different possible Work Practice Profiles, that specify the nature of work (Virtual, offline, or hybrid), nature of work schedule (flexible, or fixed), nature of ownership (individual, or team), and length of working hours (8.5 hours, or 9.5 hours or 10.5 hours). The study finds that the number of working hours is the most important criterion for the employees followed by mode of work, responsibility, and work schedule.
Multi-Period EOQ Model for Multi-Generation Technology Products With Short Product Life Cycles
(ACM Digital Library, 2022-07) Chanda, Udayan; Nagpal, Gaurav; Jasti, Naga Vamsi Krishna
In this paper, the multi-period EOQ model is developed for the technology products that have multiple generations co-existing in the market, with each of them having a very short product life cycle. The paper first develops the framework for computation of inventory-related costs and then minimizes the total replenishment costs using random search technique and approximating the non-linear expressions while using Simpson’s Rule for integration. The paper also provides numerical illustrations and establishes a few important theorems that relate the EOQ to the innovation of diffusions. It is found that the total replenishment cost curve, drawn on the EOQ axis in the case of technology generations is convex to the origin. Since the objective function is highly non-linear, the genetic algorithm has been used to find the solution to the problem. The study also suggests that the faster diffusion of the next generations has a conflicting effect on the EOQ of the first generation in the case of pooled and non-pooled logistics.