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Publication Index: ScopusSubject: sustainability

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    Citation - Scopus: 1
    Sustainable Business Model Innovation: a Quantitative Analysis of Relevant Factors
    (Institute of Electrical and Electronics Engineers Inc., 2023) Salimnezhad,A.; Dastgoshade,S.
    To integrate sustainability targets into a company's business model, one potential mechanism is sustainable business model innovation (SBMI). It defines how new business models are developed to change organizations' existing business model targets for sustainable development. Despite SBMI's great potential to address industries' long-standing sustainability challenges, it is not fully adopted in practice. This study through a DEMATEL technique strives to outline the possible actions that need to be taken before implementing SBMI to enhance the success rate. The current study investigates the most significant and necessary actions through strategic, institutional, and operational segments. Results suggest that action programs at organizations' strategic- and institutional levels are more critical to have a successful SBMI implementation. Moreover, our results indicate that innovation or more clearly how innovation is practiced within an organization is key to fully unlocking the SBMI's potential. © 2023 IEEE.
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    Article
    Citation - WoS: 4
    Citation - Scopus: 5
    Experimental Investigation of Communication Performance of Drones Used for Autonomous Car Track Tests
    (Mdpi, 2021) Yildiz, Melih; Bilgic, Burcu; Kale, Utku; Rohacs, Daniel
    Autonomous Vehicles (AVs) represent an emerging and disruptive technology that provides a great opportunity for future transport not only to have a positive social and environmental impact but also traffic safety. AV use in daily life has been extensively studied in the literature in various dimensions, however; it is time for AVs to go further which is another technological aspect of communication. Vehicle-to-Vehicle (V2V) technology is an emerging issue that is expected to be a mutual part of AVs and transportation safety in the near future. V2V is widely discussed by its deployment possibilities not only by means of communication, even to be used as an energy transfer medium. ZalaZONE Proving Ground is a 265-hectare high-tech test track for conventional, electric as well as connected, assisted, and automated vehicles. This paper investigates the use of drones for tracking the cars on the test track. The drones are planned to work as an uplink for the data collected by the onboard sensors of the car. The car is expected to communicate with the drone which is flying in coordination. For the communication 868 MHz is selected to be used between the car and the drone. The test is performed to simulate different flight altitudes of drones. The signal strength of the communication is analyzed, and a model is developed which can be used for the future planning of the test track applications.
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    Article
    Citation - WoS: 3
    Citation - Scopus: 4
    Predictive Rental Values Model for Low-Income Earners in Slums: the Case of Ijora, Nigeria
    (Taylor & Francis Ltd, 2023) Iroham, Chukwuemeka O.; Misra, Sanjay; Emebo, Onyeka C.; Okagbue, Hilary, I
    It is well known most often that values of properties tend to hike at the effluxion of time. This has necessitated the adoption of predictive models in interpreting outcomes in the property market in the future. Earlier studies have been oblivious of such models' outcomes as it affects any focal group, particularly the vulnerable. This present study focuses on the low-income earners found in the slum. The Ijora community in Lagos was the highlight of this study, particularly Ijora Badia and Ijora Oloye, regarded as slums according to the UNDP report. The entire fifty-two (52) local agents in the Ijora community were surveyed in cross-sectional survey research that entailed the questionnaire's issuance. The nexus of data collection, pre-processing, data analysis, algorithm application, and model evaluation resulted in retrieving rental values within the years 2010 and 2019 on two predominant residential property types of self-contain and one-bedroom flats found within the community. Three selected algorithms, Artificial Neural Network (ANN), Support Vector Machine, and Logistic Regression, were essentially used as classifiers but trained to predict the continuous values. These algorithms were implemented through the use of Python's SciKit-learn Library and RapidMiner. The findings revealed that though all three models gave accurate predictions, Logistic Regression was the highest with low error values. It was recommended that Logistic Regression be applied but with much data set of property values of low-income earners over much more period. This study will contribute to the Sustainable development goals(SDG) 11(Sustainable cities and communities) of the United Nations to benefit developing countries, especially in sub-Saharan Africa.