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Nowadays, companies have required new alternatives and strategies to handle environmental sustainability difficulties, primarily as ecological and social awareness has grown. In this context, the aim is to determine the green transportation indicators in companies with corporate identity and logistics activities at the international level in Giresun, Ordu, Gümüshane, Artvin, Rize, and Trabzon in the Eastern Black Sea Region in Turkey. At the same time, the study contributes to providing an effective and applicable solution to decision-making problems involving the assessment of green transportation indicators and smart network strategies in the logistics sector, which is a critical sector for countries. The purpose of this paper is to address these issues.

This study aims to propose a model for the selection of smart network strategy and to determine the criteria weights used in green transportation indicators, and establish an ideal smart network strategy. In achieving the outlined goals of the study, the authors believe that the model proposed in the study will draw the focus to green logistics which will aid the environmental, economic and social efforts of businesses and governments through the provision of efficient use of scarce resources, which will, in turn, ensure that we leave a sustainable environment for future generations and businesses enjoy a competitive advantage. At the same time, different smart network strategies and green transportation indicators in companies show the success rate of social, economic and environmental indicators in green logistics practices. In addition to providing innovative, reliable and sustainable transportation systems, smart network strategies are critical for businesses to create cost advantages. Through the green transportation indicators and smart network strategies selection model outlined in this study, it is clear that the contribution will not only be limited to businesses, as the society and governments will also benefit from the important indicators on sustainability, as well as the protection of the environment and nature.

According to the findings, “economic indicators” is the essential green transportation indicator in logistics companies with a corporate identity and worldwide transportation operations. Besides, the “mixed access model strategy” is the most appropriate smart network strategy in logistics firms with corporate identity and worldwide transportation activities. Currently, it is possible to assume that logistics organizations prefer to profit from all smart network strategies in terms of cost optimization and competitiveness rather than from just one. The study, on the other hand, which is a road map that will help sustainability practices in the logistics sector due to green transportation, also examines the similarities and differences of green transportation practices in companies in the relevant sector and to what extent they can be reflected. As a result, the study provides a practical road map for selecting green transport indicators and a smart network strategy process for the logistics industry.

This study examined logistics companies with a corporate identity and international transportation activities in provinces in the Eastern Black Sea Region such as Ordu, Giresun, Trabzon, Rize, Artvin and Gümüshane. Novel picture fuzzy level based weight assessment (PF-LBWA) and picture fuzzy combined compromise solution (PF-CoCoSo) methods are developed to solve the decision-making problem.

The Internet of Things (IoT), as one of the new digital technologies, has created wide applications in various industries, and one of the most influential industries of this technology is the transportation industry. By integrating the IoT with the transportation industry, there will be dramatic changes in the industry, and it will provide many entrepreneurial opportunities for entrepreneurs to develop new businesses. Opportunity identification is at the heart of the entrepreneurial process, and entrepreneurs identify innovative goods or services to enter a new market by identifying, evaluating, and exploiting opportunities. Despite the desire of transportation managers to invest in the IoT and the increase in research in this area, limited research has focused on IoT-based entrepreneurial opportunities in the transportation industry. Therefore, the present study aims to identify IoT-based entrepreneurial opportunities in the transportation industry and examine their importance.

To achieve the research objective, the authors applied a mixed approach. First, adapting the lens of the industry value chain theory, a comprehensive literature review, besides a qualitative approach including semi-structured interviews with experts and thematic analysis, was conducted to identify the entrepreneurial opportunities. The identified opportunities were confirmed in the second stage using a quantitative survey method, including the Student t-test and factor analysis. Finally, the identified opportunities were weighted and ranked using the best worst method (BWM).

Entrepreneurial opportunities are classified into five main categories, including “smart vehicles”, “business partners/smart transportation supply side”, “supporting services”, “infrastructures”, and “smart transport management and control”. The infrastructures group of opportunities ranked the highest amongst the identified groups.

This study adds to the digital entrepreneurship opportunity recognition literature by addressing opportunities in a smart industry propelled by digital technologies, including developing new products or new applications of the available technologies. Additionally, inspired by the industry value chain theory, this article develops a framework including various digital entrepreneurial opportunity networks which are necessary to add value to any industry and, thus, could be applied by entrepreneurs to recognize opportunities for new intermediaries to enter other digital-based industries. Finally, the present study identifies the IoT-based entrepreneurial opportunities in the smart transportation industry and prioritizes them, providing practical insights regarding the creation of entrepreneurial ecosystems in the field of smart transportation for entrepreneurs and policymakers.

The objective of this research work is to design a data-based solution for administering traffic organization in a smart city by using the machine learning algorithm.

A machine learning framework for managing traffic infrastructure and air pollution in urban centers relies on a predictive analytics model. The model makes use of transportation data to predict traffic patterns based on the information gathered from numerous sources within the city. It can be promoted for strategic planning determination. The data features volume and calendar variables, including hours of the day, week and month. These variables are leveraged to identify time series-based seasonal patterns in the data. To achieve accurate traffic volume forecasting, the long short-term memory (LSTM) method is recommended.

The study has produced a model that is appropriate for the transportation sector in the city and other innovative urban applications. The findings indicate that the implementation of smart transportation systems enhances transportation and has a positive impact on air quality. The study's results are explored and connected to practical applications in the areas of air pollution control and smart transportation.

The present paper has created the machine learning framework for the transportation sector of smart cities that achieves a reasonable level of accuracy. Additionally, the paper examines the effects of smart transportation on both the environment and supply chain.

The aim of this study is to propose a governance model and key performance indicators on how policymakers can contribute to a more accessible, inclusive and sustainable mobility within and across smart cities to examine sustainable urban mobility grounded on the rational management of public transportation infrastructure.

This study employed desk research methodology grounded on secondary data from existing documents and previous research to develop a sustainable mobility governance model that explores key factors that influence future urban policy development. The collected secondary data was descriptively analyzed to provide initiatives and elements needed to achieve sustainable mobility services in smart cities.

Findings from this study provide evidence on how cities can benefit from the application of data from different sources to provide value-added services to promote integrated and sustainable mobility. Additionally, findings from this study discuss the role of smart mobility for sustainable services and the application for data-driven initiatives toward sustainable smart cities to enhance mobility interconnectivity, accessibility and multimodality. Findings from this study identify technical and non-technical factors that impact the sustainable mobility transition.

Practically, this study advocates for the use of smart mobility and data-driven services in smart cities to improve commuters' behavior aimed at long-term behavior change toward sustainable mobility by creating awareness on the society and supporting policymakers for informed decisions. Implications from this study provide information that supports policymakers and municipalities to implement data-driven mobility services.

This study provides implications toward behavioral change of individuals to adopt a more sustainable mode of travels, increase citizens’ quality of life, improve economic viability of business involved in providing mobility-related services and support decision-making for municipalities and policymakers during urban planning and design by incorporating the sustainability dimension into their present and future developments.

This paper explores how urban transportation can greatly reduce greenhouse gas emissions and provides implications for cities to improve accessibility and sustainability of public transportation, while simultaneously promoting the adoption of more environmentally friendly means of mobility within and across cities. Besides, this study provides a detailed discussion focusing on the potential opportunities and challenges faced in urban environment in achieving sustainable mobility. The governance model developed in this study can also be utilized by technology startups and transportation companies to assess the factors that they need to put in place or improve for the provision of sustainable mobility services.

The purpose of this paper is to use the conceptual model of the Smart Transportation Management (STM) system and analyze how the included factors change the performance of distribution activities and what management issues are at stake.

To prepare the paper, a literature study was made and case studies carried out in companies and organizations that are included in advanced transportation setups, including infrastructure providers, carriers, truck manufacturers, software providers, shippers, and more.

The main finding of the study is a model that includes three major components of smart transportation management, namely, smart goods, smart vehicles and smart infrastructure. These components embrace some factors that have effects on supply chain performance; however, to different extents.

The paper uses a framework for the smart transportation management system that is useful when studying advanced transportation management systems, the functions that need to be supported and what factors have effects on supply chain performance.

Practical implications are mainly based on the structure of the smart transportation system that is used and the identified factors that affect the performance of the supply chain, as these factors can be influenced by logistics management.

The framework used in this research is a new development that collects advanced functions of goods identification, vehicle information systems and infrastructure systems into one conceptual model for smart transportation management that include some factors that are affecting supply chain performance.

This chapter critically evaluates the opportunities and challenges in adopting information technology for enhancing transportation in developing countries. The conception framework emerging from this study highlights four key stakeholders and the country context in developing and integrating information technology for improving transportation in developing countries – Tech developers, Transporters, Transport Tech start-ups and Travellers. This study makes cogent theoretical contributions to the growing body of works around technological innovation, smart mobility and intelligent transport systems, albeit from a developing country perspective. This study has also emerged from managerial implications for stakeholders, especially the tech developers, transporters and transport tech start-ups. There is a need for innovative ideas to address the inherent transportation challenges in Africa, and the customers are counting on these stakeholders to make the technology readily available and accessible.

The purpose of this study is to explore the causal relationship between smart transportation technology innovation and green transportation efficiency.

A comprehensive framework is used in this paper to assess the level of green transportation efficiency in China based on the instrumental variable – generalized method of moments model, followed by an examination of the impact of innovation in smart transportation technology on green transportation efficiency. Additionally, their non-linear relationship is explored, as are their important moderating and mediating effects.

The findings indicate that, first, the efficiency of green transportation is significantly enhanced by innovation in smart transportation technology, which means that investing in such technologies contributes to improving green transportation efficiency. Second, in areas where green transportation efficiency is initially low, smart transportation technology innovation exerts a particularly potent influence in driving green transportation efficiency, which underscores the pivotal role of such innovation in bolstering efficiency when it is lacking. Third, the relationship between smart transportation technology innovation and green transportation efficiency is moderated by information and communication technology, and the influence of smart transportation technology innovation on green transportation efficiency is realized through an increase in energy efficiency and carbon emissions efficiency.

Advancing green transportation is essential in establishing a low-carbon trajectory within the transportation sector.

Nowadays, sustainable, clean, inclusive, innovative, and smart mobility in addition to urban transformation is required to achieve sustainable development as a path to preserve the world for future concerns and improve quality of life at the present, even to be kept up with growing citizens' needs. Mobility as an infrastructure component plays fundamental roles in urban transformation, and economic development. In this chapter, and based on the 5^th wave theory, related theories, models, and concepts, modern, clean, and inclusive mobility founded on high future of 4th technologies (which is called 5th technologies), digitalization, smartness, sustainability, and CSR 2.0 strategies is declared as proper clean mobility technologies to create sustainable and smart cities. Such smart cities are able to deal with challenges made by rapid, unplanned urbanization and globalization to achieve sustainable development. In this research, roles of inclusive and smart mobility systems as path to create modern and sustainable urban areas to make the world more sustainable and livable for living are declared. Literature reviews, case studies, interviews, and questionaries are applied as main methods to recognize inclusive and modern mobility and its roles in urban transformation to achieve sustainable development. This chapter is based on know-how and do-how of the author Prof. Hamid Doost on sustainability such as cooperating with Danish Sustainable Platforms Company, working with Erasmus Plus as an academic leader in Germany since 2017, cooperating with Copenhagen's former mayor and researching on sustainability. In this chapter, impact of sustainable mobility, sustainable buildings, and smart cities on CSR 2.0 and social responsibility, how these parameters improve sustainable development and sustainability in social responsibility, corporate social responsibility (CSR), and how social responsibility could influence humanities are explored.

As the world continues to urbanise, cities face increasing pressure to become more sustainable, efficient and livable. Sustainable smart cities are emerging as a promising solution to this challenge, leveraging technology and data to improve urban systems and services while reducing environmental impact. This chapter provides an overview of the concept of sustainable smart cities and its implications for urban development. It explores the key features of sustainable smart cities, including their focus on technology, data and citizen engagement and the challenges they are facing in terms of infrastructure, data management, social equity, environmental sustainability, governance and regulations. The chapter also highlights the implications of sustainable smart cities for urban planners, policymakers and other stakeholders, emphasising the need for collaborative approaches that engage citizens and stakeholders in the design and implementation of smart city initiatives.

For decades, the fast population growth worldwide was interrelated with the adopted rapid lifestyle behavior that relies on the extensive use of fossil fuels. This primary energy source has caused various urban and environmental impacts, such as global warming, air pollution, and so forth. Consequently, the identified circumstance issues have caused many health, social, and economic hindering effects for global citizens. It poses an existential threat to humanity and the global earth's ecosystem. The alarming levels of urban pollution emissions are putting enormous challenges to the related stakeholders (governments, businesses, investors, automakers, and citizens) to admit the need to decarbonize the global economy and reach sustainable development goals (SDGs) for cleaner and smarter cities across borders. As such, a vital part of a smart city is the transport sector. The road transport sector, precisely, is one of the primary consumers of fossil fuels that contribute to high carbon dioxide emissions. Accordingly, it is essential to adopt novel and sustainable urban transport solutions and promote the achievement of the SDG's eleventh goal for sustainable cities and communities. This chapter provides insight into the present global energy situation with particular attention to the road transport sector. Indeed, it highlights different emerging technologies for a sustainable and smart urban mobility future that will mitigate the environmental situation thanks to the development of drive and internet telecommunication technologies. Furthermore, we aim in this chapter to study the international progress of the transition project using the Political, Economic, Social, Technological, Environmental, and Legal (PESTEL) analysis methodology. This study is to pinpoint opportunities for project development and the challenges that set back its evolution.