Faktor Keputusan Belanja Online Produk Pertanian Dan Non-Pertanian

Pemasaran produk menggunakan media online telah mendisrupsi sistem pemasaran produk konvensional. Studi ini untuk mengetahui faktor determinan pengunaan media online dalam pembelian produk pertanian dan non-pertanian. Data penelitian menggunakan data primer dengan pengukuran menggunakan skala likert untuk menemukan faktor determinan yaitu umur, pendidikan, metode pembayaran, kenyaman belanja, varian produk, harga, kepercayaan dan kemudahan belanja. Data dianalisis dengan pendekatan regresi logistik biner yaitu Logit Model. Hasil studi menemukan bahwa faktor pembelian online adalah umur dan pendidikan sedangkan enam variabel lainnya tidak signifikan. Hal ini menguatkan dugaan bahwa karaktersitik para penggunaan media online di daerah penelitian adalah masyarakat memiliki pengetahuan dan keterampilan dalam memahami teknologi digital. Sebanyak 72 persen yang melakukan belanja online adalah para generasi muda, usia remaja dan dewasa awal. Para remaja dan dewasa awal cepat menyesuaikan dengan tren perubahan terknologi digital dan rasa ingin mencoba hal-hal baru. Pemasaran online melalui berbagai situs-aplikasi digital, belum banyak dikenal responden di daerah penelitian, sehingga keenam variabel tidak menjadi penentu dalam belanja online. Salah satu kendala utama di daerah penelitian adalah kesulitan jaringan internet sehingga perlu perluasan jaringan internet dan memberikan literasi dalam menggunakan aplikasi belanja online. 

Exploiting vehicular social networks and dynamic clustering to enhance urban mobility management

Transport authorities are employing advanced traffic management system (ATMS) to improve vehicular traffic management efficiency. ATMS currently uses intelligent traffic lights and sensors distributed along the roads to achieve its goals. Furthermore, there are other promising technologies that can be applied more efficiently in place of the abovementioned ones, such as vehicular networks and 5G. In ATMS, the centralized approach to detect congestion and calculate alternative routes is one of the most adopted because of the difficulty of selecting the most appropriate vehicles in highly dynamic networks. The advantage of this approach is that it takes into consideration the scenario to its full extent at every execution. On the other hand, the distributed solution needs to previously segment the entire scenario to select the vehicles. Additionally, such solutions suggest alternative routes in a selfish fashion, which can lead to secondary congestions. These open issues have inspired the proposal of a distributed system of urban mobility management based on a collaborative approach in vehicular social networks (VSNs), named SOPHIA. The VSN paradigm has emerged from the integration of mobile communication devices and their social relationships in the vehicular environment. Therefore, social network analysis (SNA) and social network concepts (SNC) are two approaches that can be explored in VSNs. Our proposed solution adopts both SNA and SNC approaches for alternative route-planning in a collaborative way. Additionally, we used dynamic clustering to select the most appropriate vehicles in a distributed manner. Simulation results confirmed that the combined use of SNA, SNC, and dynamic clustering, in the vehicular environment, have great potential in increasing system scalability as well as improving urban mobility management efficiency1916CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP401802/2016-7; 2015/25588-6; 2016/24454-9; 2018/02204-6; 465446/2014-088887.136422/2017-002014/50937-

Future cities and autonomous vehicles: analysis of the barriers to full adoption

The inevitable upcoming technology of autonomous vehicles (AVs) will affect our cities and several aspects of our lives. The widespread adoption of AVs repose at crossing distinct barriers that prevent their full adoption. This paper presents a critical review of recent debates about AVs and analyse the key barriers to their full adoption. This study has employed a mixed research methodology on a selected database of recently published research works. Thus, the outcomes of this review integrate the barriers into two main categories; (1) User/Government perspectives that include (i) Users' acceptance and behaviour, (ii) Safety, and (iii) Legislation. (2) Information and Communication Technologies (ICT) which include (i) Computer software and hardware, (ii) Communication systems V2X, and (iii) accurate positioning and mapping. Furthermore, a framework of barriers and their relations to AVs system architecture has been suggested to support future research and technology development

Autonomous vehicles and smart cities- future directions of ownership vs shared mobility

Over the last decade, there has been increasing discussions about self-driving cars and how most auto-makers are racing to launch these products. However, this discourse is not limited to transportation only, but how such vehicles will affect other industries and specific aspects of our daily lives as future users such as the concept of work while being driven and productivity, entertainment, travel speed, and deliveries. Although these technologies are beneficial, access to these potentials depends on the behaviour of their users. There is a lack of a conceptual model that elucidate the acceptance of people to Self-driving cars. Service on-demand and shared mobility are the most critical factors that will ensure the successful adoption of these cars. This paper presents an analysis of public opinions in Nottingham, UK, through a questionnaire about the future of Autonomous vehicles' ownership and the extent to which they accept the idea of vehicle sharing. Besides, this paper tests two hypotheses. Firstly, (a) people who usually use Public transportation like (taxi, bus, tram, train, carpooling) are likely to share an Autonomous Vehicle in the future. Secondly, (b) people who use Private cars are expected to own an Autonomous Vehicle in the future. To achieve this aim, a combination of statistical methods such as logistic regression has been utilised. Unexpectedly, the study findings suggested that AVs ownership will increase contrary to what is expected, that Autonomous vehicles will reduce ownership. Besides, participants have shown low interest in sharing AVs. Therefore, it is likely that ownership of AVs will increase for several reasons as expressed by the participants such as safety, privacy, personal space, suitability to children and availability. Actions must be taken to promote shared mobility to avoid AVs possession growth. The ownership diminution, in turn, will reduce traffic congestion, energy and transport efficiency, better air quality. That is why analysing the factors that influence the mindset and attitude of people will enable us to understand how to shift from private cars to transport-on-demand, which is a priority rather than promoting the technology

Dynamic management of traffic signals through social IoT

Traffic congestion is a major threat to transportation sector in every urban city around the world. This causes many adverse effects like, heavy fuel consumption, increased waiting time, pollution, etc. and pose an eminent challenge to the movement of emergency vehicles. To achieve better driving we proceed towards a trending research field called Social Internet of Vehicles (SIoV). A social network paradigm that permits the establishment of social relationships among every vehicle in the network or with any road infrastructure can be radically helpful. This holds as the aim of SIoV, to be beneficial for the drivers, in improving the road safety, avoiding mishaps, and have a friendly-driving environment. In this paper, we propose a Dynamic congestion control with Throughput Maximization scheme based on Social Aspect (D-TMSA) utilizing the social, behavioral and preference-based relationships. Our proposed

Toward a Bio-Inspired System Architecting Framework: Simulation of the Integration of Autonomous Bus Fleets & Alternative Fuel Infrastructures in Closed Sociotechnical Environments

Cities are set to become highly interconnected and coordinated environments composed of emerging technologies meant to alleviate or resolve some of the daunting issues of the 21st century such as rapid urbanization, resource scarcity, and excessive population demand in urban centers. These cybernetically-enabled built environments are expected to solve these complex problems through the use of technologies that incorporate sensors and other data collection means to fuse and understand large sums of data/information generated from other technologies and its human population. Many of these technologies will be pivotal assets in supporting and managing capabilities in various city sectors ranging from energy to healthcare. However, among these sectors, a significant amount of attention within the recent decade has been in the transportation sector due to the flood of new technological growth and cultivation, which is currently seeing extensive research, development, and even implementation of emerging technologies such as autonomous vehicles (AVs), the Internet of Things (IoT), alternative xxxvi fueling sources, clean propulsion technologies, cloud/edge computing, and many other technologies. Within the current body of knowledge, it is fairly well known how many of these emerging technologies will perform in isolation as stand-alone entities, but little is known about their performance when integrated into a transportation system with other emerging technologies and humans within the system organization. This merging of new age technologies and humans can make analyzing next generation transportation systems extremely complex to understand. Additionally, with new and alternative forms of technologies expected to come in the near-future, one can say that the quantity of technologies, especially in the smart city context, will consist of a continuously expanding array of technologies whose capabilities will increase with technological advancements, which can change the performance of a given system architecture. Therefore, the objective of this research is to understand the system architecture implications of integrating different alternative fueling infrastructures with autonomous bus (AB) fleets in the transportation system within a closed sociotechnical environment. By being able to understand the system architecture implications of alternative fueling infrastructures and AB fleets, this could provide performance-based input into a more sophisticated approach or framework which is proposed as a future work of this research

Activating Energy Communities for Systemic Change

The speed of energy transition in the Netherlands is low, in contrast to its 2050 climate change target of net-zero emissions. The transition requires 7.5 million households with natural gas connections, to move to renewable energy sources. The main challenge is not technical, many viable options are already available, but social: people will need to be supported to decide and act. In this paper, we identify interventions that could activate change within energy communities, through 19 interviews conducted in March 2021 in Austerlitz, Zeist municipality, The Netherlands. Interview questions were guided by the Capability, Opportunity, Motivation, and Behavioural (COM-B) change model. The model explains factors that affect people’s behaviour. Results indicate that renovation and energy transition are viewed as two separate processes. Austerlitz homeowners are waiting for the government to lead the energy transition process, while they continue to renovate their homes to improve comfort, aesthetics, safety, and convenience. Also, current interventions towards activating households are piecemeal and more focused on creating external opportunities (such as financial support), and barely address the psychological capabilities and motivation factors (belief, attitude, social norm, and perceived behavioural control). To boost psychological capabilities and motivation, we recommend interventions that enhance homeowners’ belief that the energy transition is part of their long-term home renovation plans, for their own benefit, to motivate them to drive the energy transition process. Interventions may include ‘show’ or ‘display’ houses where energy transition was combined with renovations and highlighting inspirational energy transition stories on the municipality website

An adaptive urban planning framework to support autonomous car technologies

In the last few decades, there has been increased discussion around smart mobility and the development of autonomous vehicles (AVs). The upcoming technology of self-driving vehicles has the potential to improve the quality of urban living and enhance sustainability, but our cities are not yet ready to adopt AVs. The physical infrastructure and legislative frameworks required are not yet in place, and public attitudes towards AVs are unclear. Although a great deal of current discussion revolves around the technical aspects of self-driving vehicles and technological maturity, there is a lack of research examining the full range of barriers to AV adoption and the potential impacts on urban planning. In order to begin to fill this gap, this study explores the barriers to full AV adoption in detail and develops an adaptive urban framework to assist urban planners, citizens, politicians, and stakeholders in their planning decision-making around AVs. To achieve this aim, the study adopts a mixed-methods research methodology following the multilevel model triangulation research design, with four distinct implementation phases. In Phase One, document analysis and content analysis is carried out to identify and analyse the barriers to the adoption of AVs in today’s cities and to analyse AV vehicle specifications and assess their potential impact on the urban transportation infrastructure. The analysis identifies key barriers in the following areas: 1) Safety; 2) User acceptance; 3) Regulations and ethics; 4) Accurate positioning & mapping; 5) Computer software & hardware; and 6) Communication Systems (Networks). The outcomes of this phase contribute to the development of a framework of barriers to the full adoption of AVs combined with the AV system architecture, tracing their interrelations, and an initial list of recommendations. In Phase Two, a semi-structured survey targeting experts in a range of disciplines associated with AVs is used to validate the framework developed in Phase One and to determine the possible impacts on city planning and transportation infrastructure of a hypothetical journey through the city of Nottingham made by a fully autonomous vehicle (Level 4). This phase reveals that the majority of experts believe that both existing design principles and design guidance will be affected, with street elements such as roundabouts/intersections, zebra crossings, charging points, on-street parking, road signs, and drop points most severely affected. For instance, 61% of experts agree that AVs’ hubs should be in each neighborhood. 19% of experts argue that manual driving should be banned. In Phase Three, a structured survey targeting members of the public in Nottingham is used to analyse current public attitudes and behaviours in respect of AVs and to begin to identify factors which might drive AV adoption in future. 57% of people are expected to share AVs and 64% are expected to own them in the city. In terms of data privacy, 46% of people disagree with sharing their data. The final phase of the research involves combining the outcomes of the previous phases to create the final adaptive urban planning framework to support future planning decision-making around AVs. A detailed list of recommendations to address the technical, social and legislative barriers identified is also proposed. The study concludes by suggesting avenues for subsequent research to build on these outcomes and further support the adoption of AVs as part of moves to promote smart mobility and enhance the quality of life in our cities

Towards the implementation of the Social Internet of Vehicles

The Internet of Vehicles (IoV) represents the emerging paradigm where vehicles are (almost) always connected to the Internet to deliver and receive information to/from other services so as to augment the knowledge and services the users can benefit from when moving in urban and rural areas by their vehicles, but not only. Furthermore, the exploitation of social networking notions into the IoV has brought to the definition of the Social IoV (SIoV) paradigm, i.e., a social network where every vehicle is capable of establishing social relationships in an autonomous way with other vehicles or road infrastructure equipment. In this paper, we propose an implementation of the SIoV leveraging on an existing cloud-based IoT platform to manage the social activity of the vehicles as defined by the SIoV paradigm. The contribution of the paper is multifold: (i) we define some static and dynamic relationships that can be established between vehicles and road infrastructures taking part to the SIoV; (ii) we show how the proposed system can be integrated into the standard Intelligent Transportation System Station Architecture (ITS SA); (iii) we illustrate an effective low-cost and flexible solution for the On-Board Unit (OBU) to enable every vehicles to participate in the SIoV and create their own relationships; (iv) we show the results of the conducted experimental tests for the creation of social relationships aimed at comparing the performance of Bluetooth, 802.11p and Wi-Fi technologies when used to manage vehicles’ radio visibility. Finally, we present two use cases: the Vehicle Diagnostic and the Smart Parking applications