Network Companies Research Articles

Design and analysis of ride-sourcing services with auxiliary autonomous vehicles for transportation hubs in multi-modal transportation systems

Autonomous vehicles (AVs), which can be fully controlled by remote/online operators, could be an extension of ride-sourcing services provided by transportation network companies (TNCs). Meanwhile, substitutive and complementary relationships between ride-sourcing and public transit could also help TNCs increase their profit under certain strategies. Unlike previous studies that generally ignored either AVs or interactions between public transit and ride-sourcing, we introduce AV-involved operational strategies into a multi-modal system. In this paper, we focus on transportation hubs in an urban area and let the TNC assign AVs to these hubs for serving only within that particular hub at a differentiated fare; meanwhile, passengers could choose among AVs, human-driven vehicles (HVs), combined modes with public transit and AVs or HVs, or other travel modes to fulfill their travel needs. We develop a mathematical model to investigate the impacts of such an operational strategy, and formulate an optimisation problem to maximise the TNC's profit and minimise total waiting time simultaneously by adjusting AV fare and fleet size. We further propose a comprehensive modeling framework with the analytical model, optimisation problem, calibration method, and heuristic algorithm, making it a general approach for different real-world scenarios. Following the framework, we conduct a case study based on real-world datasets of public transit and ride-sourcing services in Hangzhou, China. Different market schemes are analyzed and compared with the currently existing situation. The results demonstrate that by adopting this auxiliary-AV-oriented operational strategy, the TNC's profit and public transit ridership can both be increased, and passengers could enjoy a shorter waiting time for HV ride-sourcing trips. Moreover, the TNC is more inclined to allocate more AVs to hubs with large commute needs and uncongested traffic, leading to a high profit for the TNC and a short waiting time for passengers. Societal preferences towards AV trips are also analyzed. The results provide in-depth references for real-world AV-related ride-sourcing operational problems.

Using Online Videos to Improve Attitudes toward Shared Autonomous Vehicles: Age and Video Type Differences

Future adoption of shared automated vehicles (SAVs) should lead to several societal benefits, but both automated vehicles (AVs) and ridesharing must overcome their barriers to acceptance. Previous research has investigated age differences in ridesharing usage and factors influencing the acceptability and acceptance of AVs. Further complicating our understanding of SAV acceptance, much of the public lack accurate knowledge and/or actual experience regarding AVs. In this study, we employed a 3 (age group) × 4 (video condition) longitudinal mixed experimental design to investigate age differences in anticipated SAV acceptance after viewing different types of introductory videos related to AVs (educational, experiential, or both) or currently available ridesharing provided by transportation network companies (control). Younger, middle-aged, and older adults were randomly assigned to watch (1) an educational video about SAV technologies and potential benefits, (2) an experiential video showing an SAV navigating traffic, (3) both the experiential and educational videos or (4) a control video explaining how current ridesharing services work. Attitudes toward SAVs (intent to use, trust/reliability, perceived usefulness, perceived ease of use, safety, desire for control, cost, authority, media, and social influence) were measured before and after viewing the video(s). Significant differences in how SAV attitudes changed were found between the educational and experiential video conditions relative to the control video and between different age groups. Findings suggest that educational and/or experiential videos delivered in an online format can have modest but significant improvements to their viewers’ attitudes toward SAVs—particularly those of older adults.

Model for Identification of Electrical Appliance and Determination of Patterns Using High-Resolution Wireless Sensor NETWORK for the Efficient Home Energy Consumption Based on Deep Learning

The growing demand for electricity and the constant increase in electricity rates have intensified the interest of residential and non-residential energy consumers to reduce their energy consumption. The introduction of non-conventional renewable energies (photovoltaic and wind, in the residential case) demands new proposals to obtain a home energy management system (HEMS), which allows reducing the use of electrical energy. This article incorporates artificial intelligence techniques to demand response, allowing control, switching, turning on and off of appliances, modifying and reducing consumption, and achieving improvements in the quality of life in the home. In addition, an architecture based on a smart socket and an artificial intelligence model that recognizes the consumption of electrical appliances in high resolution (sampling every 10 s) is proposed. The system uses the Wi-Fi communication protocol, ensuring that the smart sockets wirelessly provide the data obtained to the public cloud. The use of Deep Learning allows us to obtain a central control model of the home, which, when interconnected to the smart electrical distribution networks of companies, could generate a positive impact on the environmental effects and CO2 reduction.

Longitudinal analysis of interorganizational collaborative networks of cross-laminated timber (CLT) construction

Purpose Cross-laminated timber (CLT) is an innovative construction material that provides a balanced mix of structural stiffness, fabrication flexibility and sustainability. CLT development and innovation diffusion require close collaborations between its supply chain architectural, engineering, construction and manufacturing (AECM) stakeholders. As such, the purpose of this study is to provide a preliminary understanding of the knowledge diffusion and innovation process of CLT construction. Design/methodology/approach The study implemented a longitudinal social network analysis of the AECM companies involved in 100 CLT projects in the UK. The project data were acquired from an industry publication and decoded in the form of a multimode project-company network, which was projected into a single-mode company collaborative network. This complete network was filtered into a four-phase network to allow the longitudinal analysis of the CLT collaborations over time. A set of network and node social network analysis metrics was used to characterize the topology patters of the network and the centrality of the companies. Findings The study highlighted the scale-free structure of the CLT collaborative network that depends on the influential hubs of timber manufacturers, engineers and contractors to accelerate the innovation diffusion. However, such CLT supply collaborative network structure is more vulnerable to disruptions due to its dependence on these few prominent hubs. Also, the industry collaborative network’s decreased modularity confirms the maturity of the CLT technology and the formation of cohesive clusters of innovation partners. The macro analysis approach of the study highlighted the critical role of supply chain upstream stakeholders due to their higher centralities in the collaborative network. Stronger collaborations were found between the supply chain upstream stakeholders (timber manufacturers) and downstream stakeholders (architects and main contractors). Originality/value The study contributes to the field of industrialized and CLT construction by characterizing the collaborative networks between CLT supply chain stakeholders that are critical to propose governmental policies and industry initiatives to advance this sustainable construction material.

Enhancing Demand Prediction: A Multi-Task Learning Approach for Taxis and TNCs

Taxis and Transportation Network Companies (TNCs) are important components of the urban transportation system. An accurate short-term forecast of passenger demand can help operators better allocate taxi or TNC services to achieve supply–demand balance in real time. As a result, drivers can improve the efficiency of passenger pick-ups, thereby reducing traffic congestion and contributing to the overall sustainability of the program. Previous research has proposed sophisticated machine learning and neural-network-based models to predict the short-term demand for taxi or TNC services. However, few of them jointly consider both modes, even though the short-term demand for taxis and TNCs is closely related. By enabling information sharing between the two modes, it is possible to reduce the prediction errors for both. To improve the prediction accuracy for both modes, this study proposes a multi-task learning (MTL) model that jointly predicts the short-term demand for taxis and TNCs. The model adopts a gating mechanism that selectively shares information between the two modes to avoid negative transfer. Additionally, the model captures the second-order spatial dependency of demand by applying a graph convolutional network. To test the effectiveness of the technique, this study uses taxi and TNC demand data from Manhattan, New York, as a case study. The prediction accuracy of single-task learning and multi-task learning models are compared, and the results show that the multi-task learning approach outperforms single-task learning and benchmark models.

Критерии теплосетевых организаций: проблемы правоспособности

Amendments to the heat supply laws came into force over a year ago, providing criteria for acquiring the status of a heat network company. The purpose of these innovations was to bring order to the heat market and maintain competent professional players. It aimed at consolidating network assets in the last resort heat supplier, the unified heat distribution company, and depriving enterprises that lack the necessary material, labor, and technical resources for proper maintenance and repair of heat networks of the status of a heat network company. The intermediate results of the reform suggest now that the legislator’s expectations were not fully met. While disclosing the historical peculiarities of heat industry development in the pre-reform period, this article examines the factors that first led to the emergence of multiple heat network companies in the heat supply market and then prompted the legislator to take measures to optimize the number of regulated organizations. To simulate the potential effects of legal regulation, the author examines the electric power industry, which is related to heat supply. The legislator had already established criteria for local grid organizations in this industry several years before the reform of heat network companies. However, the legal position of the Constitutional Court of the Russian Federation prevented the legislator’s efforts from being fully implemented. To address the problem at hand, the author suggests transitioning from quantitative to qualitative criteria for evaluating an entity’s compliance with the status of a heat network company. This approach will prioritize the reliability of heat supply over using compliance as a formal basis for depriving bona fide enterprises of the status of a professional player in the heat market.

Fields of contestation and contamination: Maize seeds, agroecology and the (de)coloniality of agriculture in Malawi and South Africa

Farmer-managed seed systems and the conservation of agrobiodiversity are increasingly recognized as important components of food and seed sovereignty. In contrast, hybrid, genetically modified (GM), and, increasingly, gene-edited crops continue to be promoted by Green Revolution proponents as a “climate smart” package that includes fertilizers, pesticides, purchased seeds, and links to global markets. Influencing seed laws and policies to support the uptake of modern crop varieties has been a key entry point in many countries, facilitated by networks of foreign donors, philanthropists, governments, and multinational companies. Using the case of South Africa, where GM crops have been grown for several decades, we provide insights on implications for Malawi, which passed a Seed Act in 2022, implicitly supporting GM crops. Both countries have histories of colonial agriculture with strong policy support for modern, hybrid varieties of maize, and the replacement (and displacement) of local, open-pollinated maize varieties. In South Africa, several studies have revealed the contamination of smallholder fields and seed systems. Through a political ecology lens, we explore how maize and its cotechnologies were commodified in South Africa and Malawi, and what South African experiences of GM crop adoption in smallholder farming systems can tell us about the challenges to be faced by smallholder Malawian farmers. We reveal how colonial histories and ongoing colonialities of power, knowledge, being, and nature continue to shape the character and form of agriculture in both countries, running counter to the needs of agroecological smallholder farmers and their ways of knowing and being. We conclude by envisioning what reimagined, transformed and decolonial approaches for food and agriculture might look like on the African continent, and how they might contribute toward the attainment of food and seed sovereignty and an agroecological future.

Customer Choice of Different Types of Non-Autonomous and Autonomous Transportation Network Company Services in the San Francisco Bay Area

In recent years, transportation network companies (TNCs) have grown rapidly. However, with the high intensity of competition caused by multi-homing and low switching costs, providers like Uber and Lyft have yet to achieve profitability. Following the winner-takes-all theory, providers fight for market dominance with price wars and incentives, expecting to achieve profitability once they gain market power. However, despite extensive research on why customers use TNCs instead of other modes, there is limited research on customer choice between competing TNCs. This study examines how customers choose among competing providers and service options for booking rides, considering the influence of service characteristics. The research questions are answered for the San Francisco Bay Area, various TNC and autonomous TNC (ATNC) services (Basic, Green, Premium, and Pool), and use cases based on time urgency and trip purpose. For this, we conducted a choice-based conjoint (CBC) analysis with 1,415 participants. Results indicate that an almost equal number of customers choose services based on loyalty or habit as those customers who switch services based on better waiting times or prices. The results confirm the importance of provider size on customer choice and indicate a high time- and price-sensitivity of customers. On average, Green services are most preferred, followed by Basic, Premium, and Pool. When comparing TNC and ATNC services, customers are positive toward autonomous services but require lower prices to switch. These findings contribute to the understanding of customer choice in competitive TNC and future ATNC markets, with relevance for both theory and practitioners.

Borrowing networks for innovation: The role of attention allocation in secondhand brokerage

AbstractResearch SummaryThis study investigates how people connecting with brokers who span structural holes in a firm's communication networks can enhance their innovative performance. Through sociometric data from a large software company, we observe that individuals who pay attention to information from brokers achieve higher innovative performance compared with those who ignore such information. The advantage of paying attention to brokers' information is more pronounced when people operate in highly constrained networks. Yet, our post hoc analysis reveals that people typically allocate less attention to information from brokers than from local colleagues—they systematically do the opposite of what they should do for innovative performance. Our findings regarding the role of attention for secondhand brokerage make significant contributions to studies of networks and innovation for behavioral strategy.Managerial SummaryThis study investigates how innovation is influenced by paying attention to brokers within a company. Brokers are individuals who bridge different groups, providing access to varied information. Analysis of internal data from a large software company reveals that employees who heed the ideas of brokers tend to be more innovative, especially in close‐knit networks. However, there is a notable tendency for people to ignore brokers, favoring information from familiar colleagues instead. This indicates a significant attention bias, where the potentially most valuable sources for innovation are often unattended. Our research highlights the critical need for a strategic approach to distributing attention within company networks, which can significantly boost innovative performance.

Hospital–Provider Company Network for Home Non-Invasive Ventilation: A Feasibility Pilot Study

This study assessed the feasibility of implementing a hybrid hospital–provider company (PC) clinical pathway for patients with chronic respiratory failure (CRF) through the adaptation and follow-up of non-invasive ventilation (NIV). Over a 3-month period, a PC physiotherapist case manager oversaw the adaptation process, making adjustments as necessary, using remote monitoring and home visits. Outcome measures, including the number of patients enrolled, serious adverse events, hospitalizations, survival rates, professional time allocation, NIV adherence, nocturnal apnea–hypopnea, and oxygen saturation, Δ arterial carbon dioxide pressure (PaCO2), dyspnea, Short Physical Performance Battery (SPPB), exercise tolerance, quality of life, physical activity, and patient satisfaction, were collected. The recruitment rate was 74% (nineteen patients). Commonly reported adverse events included leakage, discomfort and sleep disturbance. Predominant interventions were four home visits (3; 4) and two NIV adjustments (1; 5). The overall program time commitment averaged 43.97 h per patient (being hospital 40 ± 11% and PC 60 ± 11%). Improvements in PaCO2, dyspnea, SPPB and exercise tolerance were observed by the third month. Adherence to NIV was high, with good or very good satisfaction with its use. This study demonstrates that a hybrid hospital–PC service for NIV adaptation and follow-up is not only feasible but also shows validity, reliability, and acceptability.

Digital transformation in the tourism sector: the key role of social networks

The research seeks to establish the use of social networks in companies in the tourism sector, especially to identify the most popular networks, their type and the role they play in these companies. The problem was approached through a systematic literature review, focused on the use of social networks in tourism companies. The Scopus database was consulted, initially finding 179 articles, using the keywords: social media, tourism and hotels. After applying the exclusion criteria, 15 articles were identified. The findings indicate that the Tripadvisor network, specialized in the tourism sector, is the most used, followed by Facebook and Twitter, which are generalist networks. It is concluded that social networks have transformed the way in which users in the hotel sector interact, research and make decisions about their accommodations, consulting the opinions and previous experiences of other users.

Capturing planning: Politics of land based accumulation in Tehran

This paper contributes to the literature on the relationships between the state and other actors around the politics of the extraction of value from urban developments by focusing on one planning institution in the Tehran metropolitan area, the Tehran Point 5 Committee (TPC). Drawing from studies on state capture, the paper shows how this planning institution, initially established to make spatial plans flexible and implementable through deliberating on zoning relief requests, has been captured by strong political actors and their networks of front companies. By collecting and analyzing quantitative and qualitative data on the decisions of this institution from 2009 to 2019 and the corresponding spatial pattern of the projects with granted zoning relief, I examine how these actors cluster around the TPC to shape, expand, and exploit opportunities from urban development to their benefit while harming the public good. I argue that the explanatory frameworks of neoliberalism, elite informality, and corruption fail to adequately account for the political drivers that undergird the operation of this institution. The paper draws attention to the susceptibility of the planning systems, in particular those components with discretionary powers, to be a target of state capture under circumstances of political distortions, due to the role they can play in extracting and distributing significant economic returns from urban development.

Automated Network Incident Identification through Genetic Algorithm-Driven Feature Selection

The cybersecurity landscape presents daunting challenges, particularly in the face of Denial of Service (DoS) attacks such as DoS Http Unbearable Load King (HULK) attacks and DoS GoldenEye attacks. These malicious tactics are designed to disrupt critical services by overwhelming web servers with malicious requests. In contrast to DoS attacks, there exists nefarious Operating System (OS) scanning, which exploits vulnerabilities in target systems. To provide further context, it is essential to clarify that NMAP, a widely utilized tool for identifying host OSes and vulnerabilities, is not inherently malicious but a dual-use tool with legitimate applications, such as asset inventory services in company networks. Additionally, Domain Name System (DNS) botnets can be incredibly damaging as they harness numerous compromised devices to inundate a target with malicious DNS traffic. This can disrupt online services, leading to downtime, financial losses, and reputational damage. Furthermore, DNS botnets can be used for other malicious activities like data exfiltration, spreading malware, or launching other cyberattacks, making them a versatile tool for cybercriminals. As attackers continually adapt and modify specific attributes to evade detection, our paper introduces an automated detection method that requires no expert input. This innovative approach identifies the distinct characteristics of DNS botnet attacks, DoS HULK attacks, DoS GoldenEye attacks, and OS-Scanning, explicitly using the NMAP tool, even when attackers alter their tactics. By harnessing a representative dataset, our proposed method ensures robust detection of such attacks against varying attack parameters or behavioral shifts. This heightened resilience significantly raises the bar for attackers attempting to conceal their malicious activities. Significantly, our approach delivered outstanding outcomes, with a mid 95% accuracy in categorizing NMAP OS scanning and DNS botnet attacks, and 100% for DoS HULK attacks and DoS GoldenEye attacks, proficiently discerning between malevolent and harmless network packets. Our code and the dataset are made publicly available.

Zero Trust Security Model for Enterprise Networks

Zero Trust (ZT) is security model and follow the concept of ânever trust, always verifyâ. ZT require to strict identity verification for devise and clients trying to access recourses on private networks regardless of whether they are sitting within or outside the networks. As opposed to perimeter-based architecture, which makes the assumption that all internal network parties are trusted and all external network parties are untrusted. In enterprise network the internal network parties is automatically seen as trusted entities granting them access to network resources. The insider threat actor has been successful in exploiting their access. So that, enterprise networks become more exposed to inside and outside threads. As a result, we need to add the zero-trust principle to the enterprise network to protect it from the inside. In this paper, the ZT model, is assumed inside the militarized zone. There may be a threat to the sensitive data. Any internal company network users cannot manipulation on his computer without permission from the administrator this is done by the group policies that have been implemented in ZT. This model has been shown to be quite effective in protecting the sensitive data against unauthorized access and also the manipulation by the insider user. Following that, an attack originating from inside of the network was launched against the enterprise and zero trust network. In the enterprise network, the network was effectively attacked, and the attack’s validity was also increased to fully penetrate the enterprise. The attack did not succeed in the zero-trust network because the attacker cannot pass the User Account Control (UAC) to gain the NT authority.

Comprehensive Evaluation Model for Competitiveness of Mass Media Companies in the IoT Sensor Networks

Mass media companies can be elaborated as organizations that manipulate technological components for their various departments such as movie studios, publishing houses, radio and television station management teams that impact a large range of audience via vast communication strategies. The companies have also been referred to as media conglomerates, media groups, or media houses further illustrating their grasp over the global markets and their revenue structures. The largest media companies such as Apple, Disney, and Comcast among others, offer products and services to users that are diverse individuals as well as large organizations leading to significant revenues as well as challenges that have been further explored in a comprehensive manner in the study. IoT utilizes wireless networks that are without infrastructure to install a huge number of wireless sensors that track system, physical, and environmental conditions. If you're wanting to integrate WSN into your business, our highly driven and experienced engineers can give you an all-encompassing solution.

Exploration of Factors That Influence Willingness to Consider Pooled Rideshare

Ridesharing has become an increasingly prevalent form of transportation. Although transportation network companies such as Uber and Lyft initially started as a personal rideshare service where individuals ride alone or with people they know, rideshare services have been expanded to pooled rideshare—a dynamic rideshare system where an individual rides with passengers they do not know. Despite the growth in rideshare services worldwide, the use of pooled rideshare in the U.S.A. is relatively low compared to other forms of transportation. A national U.S. survey ( N = 5385) was conducted to investigate reasons why individuals are willing or unwilling to consider pooled rideshare. Exploratory and confirmatory factor analyses were performed, where the exploratory factor analysis suggests five factors, specifically, service experience, time/cost, traffic/environment, privacy, and safety. Model fit indices of the confirmatory factor analysis verified that these five factors can represent the factors behind riders’ willingness to consider pooled rideshare. Furthermore, a binomial logistic regression was conducted to explore how the five factors influence riders’ willingness to consider pooled rideshare. The three factors that influence riders’ willingness to consider pooled rideshare were service experience ( B = 1.05), traffic/environment ( B = .38), and time/cost ( B = .26), while a lack of privacy ( B = −1.46) can be a deterrent for pooled rideshare. Safety is important for those who are both willing and unwilling to consider the use of pooled rideshare. Understanding these factors is important for the future of pooled rideshare services in the U.S.A.

Просування бренду підприємства в соціальних мережах (SMM)

The domestic economy is going through the most difficult period in its history. Martial law has significantly reduced the productivity and overall efficiency of Ukrainian enterprises, which are already in a difficult position after the COVID-19 pandemic. Domestic companies are forced to adapt to modern conditions and look for ways to survive. Effective business management is impossible without constant adaptation to changes in the market. Even before the start of the pandemic, most companies actively used social networks to spread information about the brand and attract new customers; the beginning of the introduction of quarantine measures, the self-isolation regime, forced companies that previously did not use social networks as a tool to promote their business, to review their approach and rethink their strategy. This became necessary in order to adapt to the realities of the time, where access to customers and the market proved to be difficult due to the limitation of physical contact. Some companies that previously ignored social media have been forced to re-establish or create a presence in these networks, as it has become a strategic necessity to stay in touch with their customers and provide appropriate promotional support for their products or services. Thus, the lockdown became a catalyst for the activation of the presence of companies in social networks, which helped them adapt to new conditions and increase their online activity in order to support business. The experience that the companies acquired during the pandemic became one of the foundations of the successful functioning of domestic enterprises during the period of active hostilities. The purpose of the present study is to out-line the theoretical and practical foundations of promoting the company’s brand in social networks (SMM) using modern information marketing tools. An analysis of scientific research by foreign and domestic economists has been carried out. The current position of SMM as a tool for enterprise promotion in the information space is analyzed. The expediency of promoting a business brand in social net-works using the example of an express delivery company is revealed. It is found that the use of social networks as a tool for brand promotion is one of the most attractive and promising ways of developing the marketing activities of enterprises. Promotion of the company’s brand in social networks will con-tribute to increasing the company’s competitiveness, as well as help to develop new sales markets. Al-so, promoting the brand in social networks provides the company with advantages in the form of: minimization of possible negative variables during the pricing process; consolidation of social opinion regarding the individuality and uniqueness of the service provided or the product produced. The article examines the essence of the brand as a grouped reflection of entrepreneurship in the social and informational environment. The need to actively maintain official pages in social networks in order to in-crease the efficiency of the company’s activities is argued. The need to analyze the external conditions of the company’s activity in the process of developing marketing measures has been determined and substantiated. It has been proven that in today’s world, the developed and active presence of an enterprise in the social networks becomes a guarantee of the client-oriented direction of the enterprise. It is substantiated that the activation of the enterprise in social networks allows to raise the general image of the company, and therefore to increase the efficiency of advertising measures for the promotion of a product or service.

ЕКОЛОГІЧНИЙ МАРКЕТИНГ ТОРГОВОЇ МАРКИ «ДОБРЕ ДОБРИВО» У ЦИФРОВОМУ ПРОСТОРІ: SOCIAL MEDIA MARKETING В КОНТЕКСТІ ЕКО-БРЕНДУ

The article analyzes the competitive aspects of the Dobre Dobrivo trademark in the following areas: page design on social networks, active advertising, predominant gender of the audience (male, female), subscriber growth, quality of the audience. The aim of the article is to analyze competitors who position their products as organic (eco), and based on their experience to develop their own marketing, environmental strategy for the "Dobre Dobrivo" brand on the Instagram social network. During the development of the new TM, the goal was to get a fairly simple, sonorous, creative name. The company's logo took the form of an earth layer, in the center of which a plant is depicted, in the form of a "smiley". The mission of the Dobre Dobrivo brand is to support ecological agriculture and create a healthy future for our planet. The company offers farmers and gardeners natural, effective and environmentally friendly products that promote soil fertility and healthy plant growth. The main idea of the brand is a balanced coexistence of agricultural activity and nature. "Dobre Dobrivo" strives to provide farmers not only with a quality product, but also to expand their understanding of the importance of organic farming for environmental sustainability. The "Dobre Dobryvo" communication strategy aims to educate a wide audience about the benefits of organic fertilizers, highlighting their positive impact on the environment and sustainable development of the agricultural sector. We aim not only to sell products, but also to raise awareness of the need for an ecological approach in agriculture. Proposed goals in social networks for sellers of eco-products (in our case – fertilizers), and proposed division of the target audience into segments. Proposed communication strategy based on competitor analysis. Having studied the features of promotion in social networks of such companies as "Yaros" and "Zhyva Zemlya", both of which position themselves as manufacturers of ecological products, as well as analyzing the features of branding and audience, we formed recommendations for the company "Dobre Dobrivo" (or similar).

Exclusion for Public Safety or Inclusion for Gig Employment: Managing the Tension with a Trilogy of Guardians

Gig platforms seek to create income opportunities, particularly for socially and economically marginalized people who find it challenging to engage in regular employment. Alongside this empowerment, safety concerns over unregulated drivers for Transportation Network Companies (TNC) platforms such as Uber and Lyft have led to discourse among policymakers on the necessity of background check laws (BCLs) with different stringency to exclude individuals from TNC jobs. Drawing on theories of labeling, routine activity, and rational choice theory, we conceptualize a trilogy of guardians—the government, TNC platforms and community, to safeguard ridesharing while mitigating social costs from excluding marginalized citizens from TNC jobs. Empirically, we document the shifting of crimes into the property domain as an unintended consequence of the exclusion solution (i.e., BCLs by the government). We find digital safety technologies deployed by TNC platforms to deter crimes (i.e., in-app safety features) can serve as an alternative to BCLs. Moreover, we show that resources provided by the community can inhibit the negative impacts of exclusion by stringent BCL (i.e., through alternative income sources) and enable the effectiveness of deterrence by in-app safety features (i.e., through policing). Our study surfaces a holistic social justice assessment that involves examining the risks of excluding marginalized individuals from gig work and showing that digital technologies expand the solution space to achieve public safety of citizens and inclusivity in gig employment through enabling the role of each guardian as well as their interdependence.

An exact second order cone programming approach for traffic assignment problems

Demographic changes, urbanization and increasing vehicle ownership at unprecedented rates put a lot of strain on cities particularly on urban mobility and transportation and overwhelm transportation network infrastructures and current transportation systems, which are not built to cope with such a fast increasing demand. Traffic congestion is considered as the most difficult challenge to tackle for sustainable urban mobility and is aggravated by the increased freight activity due to e-commerce and on-demand delivery and the explosive growth in transportation network companies and ride-hailing services. There is a need to implement a combination of policies to ensure that increased urban traffic congestion does not lower the quality of life and threaten global climate and human health and to prevent further economic losses. This study aims to contribute to the United Nations (UN) climate action and sustainable development goals in tackling recurring traffic congestion problem in urban areas to achieve a sustainable urban mobility in that it offers a solution methodology for traffic assignment problem. We introduce an exact generalized solution methodology based on reformulation of existing traffic assignment problems as a second order cone programming (SOCP) problem and propose column generation (CG) and cutting plane (CP) algorithms to solve the problem effectively for large scale road network instances. We conduct numerical experiments to test the performance of the proposed algorithms on realistic road networks.