Showing papers by "Elkafi Hassini published in 2022"

The impact of digital transformation on supply chains through e-commerce: Literature review and a conceptual framework

Abstract: One of the profound impacts of digitalization on supply chains is manifested through e-commerce. The latter has significantly grown during the last two decades, with further amplifications during the COVID-19 pandemic. This has created operational and policy making challenges for firms when deciding about how best to manage the resulting growth in e-commerce. While the impact of e-commerce on supply chains has been widely recognized in the literature, there was no effort to systematically review the literature, conceptualize some of the challenges and propose future research directions. This paper fills this gap by reviewing 153 publications from 1999 to 2019. We classify the reviewed literature based on which supply chain drivers were investigated, as well as, the employed research methodology. In addition, we conduct network and content analysis to uncover the main research themes and potential research directions namely, developing analytical centred; modelling based ecosystem for environment; leveraging data mining to enhance sustainability; balance between growth and sustainability; consumer demand and uncertainty; coordination in e-commerce logistics; last mile alternatives and cost management of innovative technique implementations. Furthermore, based on our literature review, we propose a conceptual framework where we interlink supply chain stages with a firm’s business strategy, digital transformation strategy and performance.

Interpretable data-driven model for Climate-Induced Disaster damage prediction: The first step in community resilience planning

Abstract: The frequency and magnitude of Climate-Induced Disasters (CID) have been increasing consistently over the past few decades. Alleviating the impacts of such disasters is thus critically important. Hence, a systematic data-driven framework is developed to predict CID-related damages. The framework encompasses four phases: (1) Data Collection and Fusion, where spatial interpolation methods are employed to integrate data from multiple sources, (2) Feature Selection, which aims at comparing several filter, wrapper, and embedded bbmethods to select relevant features, (3) Model Development, where machine learning techniques are employed to develop the prediction model, and (4) Result Analysis and Model Interpretation, where the black-box nature of the model is decoded using different interpretability techniques. To demonstrate the framework's utility, wind disaster property damages were linked to hazard, climate, land cover, social, housing, demographic and economic data recorded in the state of New York from 2010 to 2018. Features that are significantly important for property damage prediction were selected, and a set of machine learning models were subsequently developed. The best performing model was a random forest-based regression tree, and yielded a coefficient of determination of 0.79. Expectedly, property damages were found to depend on the complex interplay between disaster, climate, socioeconomic, housing, and demographic conditions rather than on the hazard characteristics only. The developed framework is the first step in community resilience planning, where CID recovery time and associated costs, together with the predicted damage extent and the specificities of the affected communities, can be linked to quantify community resilience under future climate-induced hazards.

A review of bricks-and-clicks dual-channels literature: trends and opportunities

Abstract: Abstract The proliferation of e-commerce has changed the retail market landscape significantly in most industries. Due to fiercer competition, many bricks-and-mortar retailers established an online channel and have become bricks-and-clicks. On the other hand, some e-tailers are adding a conventional channel to their portfolio by launching physical stores or forming a partnership with traditional retailers. Deciding on whether or not to adopt a dual-channel policy and how to operate it, in the presence of online sales, present multiple and unique research challenges. More than two decades of research have accumulated and there is a need for a comprehensive look at what has been achieved and where more research is required. Recent reviews in the field are limited in scope and depth: they focus on fulfillment and distribution issues only and cover a limited portion of the literature, less than 60 journal papers versus more than 260 papers in this survey. In this paper, we offer a structured literature review (SLR) on bricks-and-clicks dual-channels. We contribute to the literature in three main areas: (1) We present a comprehensive look at all operational aspects of bricks-and-clicks dual supply chains, (2) provide a systematic discussion of common demand modeling functions, and (3) analyze the reviewed literature, identify recent research trends and opportunities, and illustrate how existing research can be used to address up-to-date challenges in the industry.

Transportation data visualization with a focus on freight: a literature review

Abstract: ABSTRACT Road-based freight movements are a critical component of the supply chain and transportation networks. With the drive to invest in big data collection capabilities, most of the collected freight movement data remain underutilized. To improve the efficiency and resiliency of the supply chain, it is essential to enhance the visibility of goods movements on road networks. To this end, we provide in this paper a comprehensive literature review on this topic and analyze the previous research from different perspectives, such as data levels of abstraction and existing visualization techniques. In addition, we provide a taxonomy of freight transportation visualization according to the underlying analytic objective. Furthermore, we propose a decision support tool to aid freight data analysts in selecting the right visualization tools. Finally, we identify research gaps in the field of freight transportation visualization. Highlights Systematic bibliometric analysis of state of art research related to location-based telematics data visualization Applications for location-based telematics data based on different levels of abstraction A taxonomy for visualization techniques for location-based telematics data and possible application in freight transportation A proposed decision support tool for selecting possible visualization techniques based on the abstraction and availability of data Discussion of challenges and future research direction for freight transportation data visualization