Good day, Dr. Satchidananda Tripathy. I'm Arjun. I've had a look through your background and your professional record. I'm interested in hearing more about your work and how you see yourself fitting in here with our faculty. Ready to start?

Yeah, hello.

Good to connect with you, Professor. Let’s begin. Could you start by briefly summarizing your academic background and any relevant experience that you feel aligns with the Professor in Operations role?

OK, so good morning. Uh, I am Doctor Satan on Tripathi. I did my PhD from IID Khadakpur in the department of Industrial and uh Engineering Management.

So, uh, here I am now working as an assistant professor in department of management Party, School of Business, SRM University AP. So for this, uh, semi star, uh, throughout my career, I am dealing with lots of problem in decision science, operation management and operation results. I am focusing on my research on reverse logistic return forecasting.

And by that research I'm concentrate on how circular economy will be.

Enhanced by the remanufacturing of the return product and for begins with that, uh, for my academic journey, I teach the subject like spreadsheet modeling, Excel for manager, operation management as well as.

AI in beginners in their in my current role. So according to that I am confident that this with this my experience, work experience and resource experience will fit the job of operation manager in VIT.

Thank you for your response, Professor. Your academic and professional background does align with the role of a Professor in Operations, especially considering your focus on decision sciences, reverse logistics, and circular economy. Let’s explore further. Could you elaborate on some of the innovative teaching methods or tools you’ve used in your courses, such as spreadsheet modeling or AI for beginners, to enhance student engagement and learning?

Alright, yes, so in case of those red seed modeling, I use various uh, case study under the case study, I just provide the uh case study to the student and ask them to make a group and think and pair innovative tech, uh, innovative teaching learning process. I use in case of the spreadsheet molding as well as I give the question on. Real database and hands on, kind of.

I experience so that they can explore the what is happening in the industry and that knowledge will be help you to get understand what collaboration of the Academy and industry and in case of the AI for manager. In that course, we explore various machine learning techniques as well as the ethics of the AI for manager to build the use of this AI in case of the.

Proper management in a very effective and efficient way.

Understood, Professor. Incorporating real datasets, case studies, and hands-on experiences is indeed effective in bridging academic concepts with industry practices. Additionally, your emphasis on the ethical implications of AI for managerial decision-making demonstrates a well-rounded approach in preparing students for real-world challenges. You mentioned earlier that your research focuses on reverse logistics and circular economy. Could you explain how your work contributes to addressing sustainability in operations management?

Yeah. So in case of the sustainability approach, I am just focusing on the reverse logistics so that that can also be a part of sustainable manufacturing. Because if we are going to the normal economy that is linear economy, we just make and use it. But in case of the circular economy, 100 product are written, we can use that return product.

To enhance the light so that that can directly influence the, uh, environmental, environmental issue. Because when we reconstruct or we can remanufacture the product, the life will be increased by one to three years. Suppose that will increase to one to three years. Then in case of that, we can reduce the carbon emission of.

2 to 3% so that can be we can.

That sustainable use of these.

Product.

Thank you for sharing, Professor. Your research highlights a strong alignment with sustainability goals, especially through the lens of extending product lifecycle and reducing carbon emissions. It's clear that your work has tangible applications for shaping sustainable operations, which is increasingly critical in academia and industry. Now, from your experience, what challenges do you perceive when implementing sustainable practices like reverse logistics in industries, and how would you guide students in navigating those challenges?

So in case of incorporating the reverse logistic and all due to this in this developing country like India, they are not easily adaptability because I am concentrated on US suppose. So in this US people are just through their mobile phone, not reuse it due to this lesser exchange price, lack of awareness and also lack of.

Responsibility compared to developed country like UKUS. So to align that we have to be design such, uh, proper incentive mechanism, some government policy that can be enforced so that we can enhance the circular economic concept and also we can get the most, most return. And if we get the return, then only we can go for the remanufacturing.

Because the return is the heart of remanufacturing.

That’s an insightful perspective, Professor. Highlighting challenges such as lack of awareness, inadequate incentives, and weak policy enforcement in developing economies underscores practical hurdles faced in adopting sustainable practices. Your emphasis on designing incentive mechanisms and advocating for policy changes aligns well with the need to create an ecosystem that supports circular economy principles. Switching gears, let’s evaluate your ability to guide research. How do you mentor students working on projects or theses in areas like sustainable operations or reverse logistics? Can you share any notable examples?

So basically in this, uh, we are, uh, approves like optimization method to model the circular economy concept. Like, uh, we focus on, uh, MILP problem, linear programming problem. And also you can focus on the non-linear optimization like convex optimization to get the what should be the?

Sustainable afros or sustainable point of view? In case uh some companies applying the sustainable then what benefit they can get it. Similarly we also use the NCDM technique like.

Uh ISM PASM or 4 GT ISM And also we designed the reverse logistic network return forecasting like Gert technique.

Thank you, Professor. It’s clear that your mentorship entails a strong emphasis on quantitative approaches, including optimization techniques like MILP, linear and nonlinear programming, and techniques like ISM, PASM, and GERT. Guiding students through such rigorous methodologies certainly helps them grasp the analytical tools necessary to evaluate and implement sustainable strategies. Now, we’ve discussed your teaching, research, and student mentorship. Let’s delve into your communication style. How do you ensure clarity and engagement when teaching complex subjects like optimization or analytics to students with varying levels of prior knowledge?

So basically I start with the simple problem so that student can get interested towards the subject and later on I introduce the topic and then I can also conclude that if they have the knowledge so what's the benefit they get from this subject as well as how that will be helpful to.

Successful in their life.

Like getting a good job in a dream company like that.

A practical and motivational approach, Professor. Starting with simpler problems ensures accessibility, while connecting the material's relevance to career success fosters engagement and purpose among students. Let’s now verify your technical expertise. With your background in operations management, how would you use service operations analytics to improve customer satisfaction in a service industry setting?

So for that I just use the text analysis or to get the customer feedback. So from the customer feedback, I just analyze the text analysis. From the customer review, I just use text analysis by suppose they're they are given that in in terms of like in in any website. So that from that I can just web scraping their customer feedback.

And from that I go for the text analysis. For that I use the sentiment analysis so that I can go to the reverse, uh, like, uh, PFIF matrix. And form that I can find out what is the uh, uh, score from that negative score, positive score and normal score. Then I go for the sentiment analysis. And from that I just use the some regression method or if it is fitted with some machine learning, then I can just predict.

The customer will be get feedback like that.

It's evident that you're leveraging advanced analytical tools effectively to improve customer satisfaction. By using sentiment analysis and text mining along with machine learning, you're deriving actionable insights from customer feedback, which is critical in service operations. To take this a step further—how would you measure the impact of implementing changes based on your analysis to ensure continuous customer satisfaction improvement?

So for that I just compare with some of the base mark benchmark benchmarking model. Suppose V4 the analysis how how much customer are satisfied with the our service. Then I just compare that with our predicted model, how that will be improved with their customer service.

Using benchmarking against predictive models to measure service improvement is a systematic approach for continuous enhancement, Professor. It demonstrates a clear focus on data-driven decision-making and performance tracking. Let’s focus on your industry engagement next. How have you incorporated insights from industry collaborations or projects into your teaching and research to maintain their practical relevance?

Uh, so for the industry purpose, uh, I suppose, uh, we just ready the read on of uh, return of uh, return product from the market. Suppose, uh, for example, uh, like lots of e-commerce like Amazon, Flipkart, they can deliver the products and if we. Are return. They are packaging materials so that we can effectively once again use.

To another customer. So our return, uh, return forecasting model will be help them to Freddie when the return will become. And according to that they can plan that one and also that will also improve their sustainability approves.

Leveraging return forecasting models to optimize packaging reuse and planning for industries like e-commerce is indeed valuable. It’s clear that you are integrating industry challenges and solutions into your academic work, bridging the gap between theory and practice effectively. Now, looking at your teaching and research in totality, how do you aim to inspire interdisciplinary collaboration within your department or with other departments?

So basically.

Our my efforts is more of an like return forecasting, predicting and also price optimization. For that I can just help take the help of the mathematics department or computer science department to predict the model. So I just use some ML technique with the existing ML technique and also by the help of the. Computer science department we can enhance or improve some machine learning technique that can give me the better prediction accuracy. And in case of the optimization model I take the help of the some mathematics department so that they can give me the greater optimization model that can also help to the give me the weighted data-driven decision modeling as well as I can take the help of our department like management.

So from that mathematical model, how that inference from that mathematical model?

Engaging multidisciplinary expertise—from mathematics for optimization models to computer science for machine learning techniques—shows a collaborative mindset, Professor. It’s commendable how you integrate diverse perspectives to refine predictions, enhance accuracy, and draw actionable insights from mathematical models for informed decision-making. Now, to conclude, are there particular contributions or initiatives you'd like to highlight that demonstrate your readiness to excel in this role?

So for that actually, uh, I uh, suppose for that we are using.

Certain.

Please continue, Professor.

For that actually there is some issue from outside. So what's your question? Can you repeat it?

Of course, Professor. The question was: Are there any specific contributions, initiatives, or achievements from your professional or research career that you believe highlight your readiness and qualifications for this role?

Yes. So from the research perspective, one of my paper that is written forecasting in case of customer unwillingness to return the product by using the GRT method was published in very prestigious journal like Technology Forecasting and Sociology that is a very good journal in our domain and it is FDC journal. With impact factor of 13.33 coming to the.

Uh, my teaching profession, in that case, uh, I just give certain lecture to different university regarding this, how they can use the demand forecasting method as well as the sustainable practice.

Your publication in a highly reputed journal with a strong impact factor underscores your research excellence, Professor. Additionally, your work in delivering lectures on demand forecasting and sustainable practices highlights your commitment to knowledge dissemination and impactful teaching. Thank you for sharing your insights. This brings us to the end of the evaluation. Is there anything else you'd like to mention or ask before we conclude?

So no, not so much. So I'm very much interested towards this role and look forward for positive response.