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53. Benchmarking sustainable E‐commerce enterprises based on evolving customer expectations amidst COVID‐19 pandemic.

Author

Pratap, Saurabh, Jauhar, Sunil Kumar, Daultani, Yash, and Paul, Sanjoy Kumar

Subjects
COVID-19 pandemic, CONSUMERS, ELECTRONIC commerce, CUSTOMER satisfaction, ONLINE shopping
Abstract

The 2019 coronavirus disease (COVID‐19) pandemic has seriously impacted the performance of all types of businesses. It has given a tremendous structural boost to e‐commerce enterprises by forcing customers to online shopping over visiting physical stores. Moreover, customer expectations of the digital and operational capabilities of e‐commerce firms are also increasing globally. Thus, it has become crucial for an e‐commerce enterprise to reassess and realign its business practices to meet evolving customer needs and remain sustainable. This paper presents a comprehensive performance evaluation framework for e‐commerce enterprises based on evolving customer expectations due to the COVID‐19 pandemic. The framework comprises seven primary criteria, which are further divided into 25 sub‐criteria, including two sustainability factors, namely, environmental sustainability and carbon emissions. The evaluation approach is then practically demonstrated by analyzing the case of three Indian e‐commerce firms. The results are obtained using a multi‐criteria decision‐making (MCDM) method, namely, Fuzzy VIKOR, to capture the fuzziness of the inherent decision‐making problem. Further, numerical analysis is conducted to evaluate and rank various e‐commerce enterprises based on customer expectations and satisfaction benchmarks. The findings explain the most important criteria and sub‐criteria for e‐commerce businesses to ensure customer expectations along with their economic and environmental sustainability. [ABSTRACT FROM AUTHOR]

Published
2023
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62. Time Table Scheduling for Educational Sector on an EGovernance Platform: A Solution from an Analytics Company.

Author

Kumar, Vimal, Malviya, Ankita, Verma, Pratima, Muthukumaar, Vignaesh, Jauhar, Sunil Kumar, and Sharma, Nagendra Kumar

Subjects
EDUCATIONAL innovations, CLASSROOMS, DECISION making, FACULTY-college relationship, POVERTY
Abstract

Course timetabling is a multi-dimensional assignment problem which is the assignment of courses to faculty members, and then the assignment of these courses to time slots. Class scheduling, from the perspective of a school or a department, is a difficult problem. Typically, each course must be assigned an instructor, time slot(s) during the week, and a classroom. At any given time slot, at most one course can be assigned to an instructor and a room. The requirements and preferences of the instructors, estimated enrollment of students, and characteristics of the course must also be taken into account. The timetabling problem has become much more complex. This problem is solved based on many restrictions such as the period time, the available number of classrooms, capacity of the classrooms or number of seats in each, amount of the registered student and other restrictions from faculty members. Because of the reasons mentioned, a scheduler, a human decision-maker, consumes time to solve the problem. Furthermore, the assignment of the students to classrooms requires concerning the suitable number of students for the classroom since it may increase cost and waste opportunity for another appropriate classroom. [ABSTRACT FROM AUTHOR]

Published
2018

64. DEA for measuring the academic performance of a higher educational institute of Uttarakhand, India.

Author

Ali, Imran, Pant, Millie, Rana, U. S., and Jauhar, Sunil Kumar

Subjects
DATA envelopment analysis, UNIVERSITIES & colleges, COLLEGE students, TEACHING
Abstract

This paper estimates the performance assessment of 15 academic department of government PG College, Gopeshwar, Chamoli Uttarakhand (India) for the academic year 2011-2012. In Indian context efficiency of a government PG degree college of Uttarakhand state (India) is being measured for the first time to the best of authors knowledge. Using DEA models, we estimate the overall technical, pure technical and scale efficiency and identify the reference sets for inefficient departments for teaching and research separately. We also classify the academic departments in the high, middle and low robustness in terms of overall technical efficiency (OTE) for teaching and research efficiency. [ABSTRACT FROM AUTHOR]

Published
2017

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