Classification Essay of SCRM Research

This article investigates the current developments in research and practices in the domain of Supply Chain Risk Management (SCRM) through a systematic and typological approach in order to improve the understanding of SCRM field. This field has created a strong scientific and professional polemic, resulting in an exponential growth of published research work, reports and article. However, it has been discussed that SCRM lacks typological approach by several authors underlining this fact through their frameworks. In response, this review examines various perceptions, notions, definitions, drivers and sources of Supply Chain Risk (SCR), in order to identify major SCRM frameworks. This analysis is required in order to identify the main issues that needed to be addressed in the field of SCRM. Thus, the objective of this paper is to classify these frameworks so as to identify news issues, opportunities and directions for further study and researches.

Building an Effective Customer Loyalty Program

Customer loyalty schemes is a practice, employed by retailers, to reward their loyal customers. It entails giving incentives such as loyalty cards, reward points, etc. These also serve as a repository of information about a customer which helps in targeted marketing. This chapter analyses some of the successful customer loyalty programs by companies, discusses some of the reasons of failures of such program and looks at what industry experts have to say in this regard. We then collate all this information to suggests a process to identify and choose the right customer loyalty programs for a company.

Omni-Channel Retailing

Technological developments, changes in consumer behavior and intense competition are the most important threats of today, affecting many sectors as well as the retail industry. Innovative retailers, in the face of with these threats, have embraced and implemented the omni-channel retailing approach, which is the next step in multi-channel. However, other players in the retail industry lag behind this change. The aim of this chapter is to establish the experiences of innovative retailers that have adopted omni-channel retailing in the context of risks, challenges and opportunities. The research data were obtained using questionnaire method from the retailers in Turkey, one of the developing countries. As a result of the study, it was found that retailers who would adopt the omni-channel retailing would have the opportunities to be able to dominate all channels, provide better services to the customers, increase customer satisfaction and loyalty, keep in constant contact with the customers, get better customer recognition and increase sales volume.

Improving Forecasting for Customer Service Supply Chain Using Big Data Analytics

In this book chapter, the authors highlight the potential of big data analytics for improving the forecasting capabilities to support the after-sales customer service supply chain for a global manufacturing organization. The forecasting function in customer service drives the downstream resource planning processes to provide the best customer experience at optimal costs. For a mature, global organization, its existing systems and processes have evolved over time and become complex. These complexities result in informational silos that result in sub-optimal use of data thereby creating inaccurate forecasts that adversely affect the planning process in supporting the customer service function. For addressing this problem, the authors argue for the use of frameworks that are best suited for a big data ecosystem. Drawing from existing literature, the concept of data lakes and data value chain have been used as theoretical approaches to devise a road map to implement a better data architecture to improve the forecasting capabilities in the given organizational scenario.

Building High Quality Big Data-Based Applications in Supply Chains

Global retail business has become diverse and latest Information Technology (IT) advancements have created new possibilities for the management of the deluge of data generated by world-wide business operations of its supply chain. In this business, external data from social media and supplier networks provide a huge influx to augment existing data. This is combined with data from sensors and intelligent machines, commonly known as Internet of Things (IoT) data. This data, originating from the global retail supply chain, is simply known as Big Data - because of its enormous volume, the velocity with which it arrives in the global retail business environment, its veracity to quality related issues, and values it generates for the global supply chain. Many retail products manufacturing companies are trying to find ways to enhance their quality of operational performance while reducing business support costs. They do this primarily by improving defect tracking and better forecasting. These manufacturing and operational improvements along with a favorable customer experience remain crucil to thriving in global competition. In recent years, Big Data and its associated technologies are attracting huge research interest with academics, industry practitioners, and government agencies. Big Data-based software applications are widely used within retail supply chain management - in recommendation, prediction, and decision support systems. The spectacular growth of these software systems has enormous potential for improving the daily performance of retail product and service companies. However, there are increasingly data quality problems resulting in erroneous tesing costs in retail Supply Chain Management (SCM). The heavy investment made in Big Data-based software applications puts increasing pressure on management to justify the quality assurance in these software systems. This chapter discusses about data quality and the dimensions of data quality for Big Data applications. It also examines some of the challenges presented by managing the quality and governance of Big Data, and how those can be balanced with the need of delivery usable Big Data-based software systems. Finally, the chapter highlights the importance of data governance; and it also includes some of the Big Data managerial practice related issues and their justifications for achieving application software quality assurance.

Predicting Online Returns

The E-commerce industry is growing year on year in double digits. But customers today are not only buying more through their computers, they are also returning more. The volume of these returns is such that it just can't be ignored. E-tailers today are following many practices to handle these returns but the ‘predictability' factor is still missing from their approaches. This paper tries to fulfill that void. The framework suggested in this paper will help the E-tailers to predict the probability of a particular item being returned by a particular shopper. The idea is that if the E-tailer will know the probability of return during any transaction he/she would certainly be better equipped to handle the situation.

Retail Management and Electronic Retailing

This chapter presents the overview of retail management; retail management and technology; the aspects of Electronic Retailing (e-tailing); e-tailing and Electronic Commerce (e-commerce); the perspectives on online consumer behavior; and the advanced issues of e-tailing in retail environments. Retail management focuses on the processes that go into ensuring consumers can obtain the products they want from their chosen retail store. Effective retail management helps company distributes the finished products created by the business to consumers in order to determine and satisfy what buyers want and require. E-tailing is a powerful marketing technique for the right product with the right message to the right person. The chapter argues that effective retail management and e-tailing applications generate business revenue, build brand awareness, and pave the way for broader distribution in retail environments.

Designing Distribution Centres for Omni-Channel Fulfilment

The E-Commerce market is thriving and poised for robust growth in Asia. The success of eCommerce players depends on their understanding of the market and offering various types of features. This paper gives an overview of the future of E-Commerce in India and discusses the future growth segments in India's E-Commerce. Also find out various factors that would essential for future growth of Indian E-commerce. And represent the various opportunities for retailers, wholesalers, producers and for people. In this paper, we found that the Overall E-Commerce will increase exponentially in coming years in the emerging market of India. A review of the literature revealed that, to date, no research has been conducted on the supply chain that is needed to support the growth of eCommerce business in a developing country such as India. This study aim at studying - why will e-commerce have an impact on supply chain” and “where will e-commerce affect the supply chain in future.

Technologies Enabling Omni-Channel

The retail industry has been scaling up by better co-ordination among channel partners, improving shipment delivery time at a lower possible cost over last few years. Looking at the Indian scenario, large logistics companies such as Bluedart, FedEx, Gati, etc. have launched dedicated services for online retailers. However, entrance and elevation of e-commerce focused logistic companies such as Chhotu, Mudita, Unicommerce and Delhivery seem to be promising and can be the real game changer. These companies offer solutions that address the various pain-points pertaining to the supply chain of e-commerce companies, which traditional and big supply chain & logistic providers so far failed to do. This is a global phenomenon. Despite considerable improvement in recent past, many logistics providers still struggle to cope up with inadequate infrastructure leading to operational inefficiencies to support their services. Some of such operational concerns, but not limited to, are wrong delivery, unaccepted shipment pick-ups, product unavailability leading to promise to deliver.

Applications of Intelligent Video Analytics in the Field of Retail Management

Recent technologies in the market trends have demanded the significant need for the possible solutions to intelligent video cameras that are nothing but intelligent video analytics. Today in the retail industry, intelligent video analytics has gone beyond the tradition of the domain of security and loss prevention by providing retailers insightful business intelligence such as store traffic statistics and queue data. This provides accurate and reliable information by monitoring continuously through a large number of video cameras events that human operators or employees can overlook. This paper gives an overview study of applications of intelligent video analytics in retail management as well as the state-of-the-art computer vision techniques behind them to analyze the data. It clearly demonstrates that the importance of the role that intelligent video systems and analytics play can be found in a variety of applications of intelligent video Analytics in the field of Retail Management.