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Quantum Computing for Social Business Optimization: A practitioner’s perspective

TLDR
In this article , the authors conducted a literature review and empirical study to explore the core process areas that need to be considered for the consideration of quantum computing in social business and found that limited scalability, regulatory challenges, high initial cost, limited availability of quantum resources, education and training and security are the most important process areas for industry practitioners.
Abstract
Abstract Currently, E-commerce is widely adopted as it is important for business management and economic growth in the new global economy, and to reach the rapid increasing population. To better manage the e-commerce, it is important to collect and evaluate the Consumer Behaviour data for decision making and optimization. The conventional computing technologies need high amount of power and time for large data analysis. Quantum computing has the potential to analyze the large amount of data more efficiently than classical computing. This paper aims to explore the core process areas that need to be consider by the practitioners for adopting quantum computing in social business. To address the objective of this study, we conducted a literature review and empirical study to explore the core process areas that need to be considered for the consideration of quantum computing in social business. The results show that limited scalability, regulatory challenges, high initial cost, limited availability of quantum resources, education and training and security are the most important process areas that need to be focused by the industry practitioners. The result of this study gives a knowledge base for research and practitioners community to develop the tools and strategies for the adoption of quantum computing in social business.

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Book ChapterDOI

Selecting Empirical Methods for Software Engineering Research

TL;DR: This chapter describes a number of empirical methods available and analyzes the types of questions each best addresses, providing a suitable basis for both understand- ing and selecting from the variety of methods applicable to empirical software engineering.
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Analysis of interactions among the barriers of reverse logistics

TL;DR: In this article, the authors analyze the interaction among the major barriers, which hinder or prevent the application of reverse logistics in automobile industries, using Interpretive Structural Modeling (ISM) to understand the mutual influences among the barriers.
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Developing Interconnection Matrices in Structural Modeling

TL;DR: It is shown that the possibilities of interconnection can be completely prescribed in a characteristic logic equation that can be used as the complete basis for development of an interconnection matrix.
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A comparison between Fuzzy AHP and Fuzzy TOPSIS methods to supplier selection

TL;DR: The comparative analysis has shown that the Fuzzy TOPSIS method is better suited to the problem of supplier selection in regard to changes of alternatives and criteria, agility and number of criteria and alternative suppliers.
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Selecting green suppliers based on GSCM practices: Using Fuzzy TOPSIS applied to a Brazilian electronics company

TL;DR: This paper proposes a framework using Fuzzy TOPSIS to select green suppliers for a Brazilian electronics company; this framework is built on the criteria of green supply chain management (GSCM) practices.
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How does the principles of quantum computing impact the current digital marketing practices?

The provided paper does not discuss the impact of quantum computing on current digital marketing practices.