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This study aims to examine the differential impact of ride-hailing services (RHS) on private and commercial vehicle ownership from five metropolitan cities in India.

Using vehicle ownership data from five metropolitan cities over period 1991 to 2020, a panel corrected standard errors model was estimated to model the association between RHS and vehicle ownership.

The results indicate that advent of RHS has led to a significant reduction in private vehicle ownership rates and a corresponding increase in addition of intermediate public transport. The net effects of RHS on road congestion and pollution levels need to be studied in detail.

The findings of this study can potentially assist policymakers and mobility planners in efforts to decarbonise and decongest urban transport.

This study sets precedence in analysing the impact of RHS on private and commercial vehicle independently. Further, to the best of the author’s knowledge, this is the first study to examine this association for the city of Delhi and Kolkata.

The proliferation of ride-hailing businesses brings significant considerations for improving the driver's operational performance. Informed by the literature on sharing economy, general deterrence theory and protection motivation theory this research investigates the behavioral factors impacting ride-hailing drivers' operational performance.

The authors empirically test the antecedents impacting a ride-hailing driver's operational performance using an online survey dataset comprising 513 ride-hailing drivers working for Uber and Lyft in the United States.

Ride-hailing drivers' intention to comply with the ride-hailing company guidelines results in better operational performance for the driver. Moreover, drivers believe that ride-hailing companies have effective penalties to deter drivers from violating company guidelines. However, drivers also believe that the chances of being caught while ignoring the company guidelines are low.

The results of this research support the decision-making processes of ride-hailing company managers and offer insights on how managers can enhance the operational performance of their drivers.

This study provides unique contributions to emerging research at the intersection of peer-to-peer asset sharing, behavioral studies and technology management. This research is one of the first to explore the role of behavioral factors such as coping mechanisms on the operational performance of sharing economy workers.

Given the increasing volatility, uncertainty, complexity, and ambiguity, egalitarian ecosystems may play an important role to establish equality among various stakeholders. With this idea, the study aimed to understand conflicts and challenges in creating an egalitarian ecosystem in the application-based cab aggregator (ABCA) market.

Narratives of various stakeholders involved in the ABCA business were collected. The study involved narrations from direct and indirect stakeholders up to saturation till common themes were found. Grounded theory methodology using constant comparison was explored to interpret the results. After the results were obtained, root cause analysis was undertaken using the why–why methodology to understand ground-level reality.

In total, 13 major issues were identified using grounded theory for narrative analysis that cab aggregator companies, driver-partners, and riders faced. The stakeholders' inability in the ecosystem to see each other's problems could be accorded to their self-interest, rational boundedness and asymmetric information. These findings collude with Banaji et al. (2004) and Chugh et al. (2005).

This study explained each stakeholder's perspectives about their counterparts that influence non-egalitarianism. The study further suggested possible areas for solving the issues and promoting cooperation.

Product-service systems (PSS) are regarded as highly sustainable solutions. However, studies identifying and comparing the sustainable potential of product-service offerings by considering the three sustainability dimensions are still scarce. This paper aims to benchmark and analyse the sustainable potential of a use-oriented PSS, showing the influence of the context of implementation on the sustainable potential of the solutions.

By adopting a competitive benchmarking approach, six bicycle-sharing systems from different countries were selected for analysis. The main sustainability-related aspects in use-oriented PSS (the systems investigated) were identified through a literature review. Multiple secondary sources were used to collect data about the analysed PSS. A qualitative analysis was conducted through triangulation of the sources to identify and compare the systems by considering the selected sustainability aspects.

The main results show that use-oriented PSS provide a range of economic, social, and environmental benefits, confirming the sustainable potential of such solutions. Several similarities between the systems have been identified, along with some differences, especially regarding their integration with other transport systems and the use of renewable energy, which can affect users' acceptance, operation efficacy, and overall sustainable potential of the solutions.

This study identifies best practices that can be considered by other bike-sharing businesses to improve their sustainability potential.

This study identifies and explores the sustainable potential of bicycle-sharing solutions using a benchmark approach. It augments existing empirical knowledge on sustainable PSS and business models by revealing best practices, including the context that may enhance the sustainability potential of the solutions regarding environmental, economic, and social benefits.

As a result of the COVID-19 pandemic, numerous businesses have migrated to an online delivery platform (ODP) to survive and reconnect with their customers. This study aims to focus on how the public perceives ODP. It examined the acceptance of digital platforms for delivering daily necessities, especially food, in Brunei Darussalam during the COVID-19 pandemic.

The online survey collected 350 valid samples, and the online questions were distributed using a snowball sampling method, with the questionnaire’s softcopy prepared in Qualtrics and sent via email and social media as hyperlinks. In 2021, we sent out the questionnaire link via email, WhatsApp and Facebook to people and organizations for about six months.

According to the findings of the study, product quality is a critical factor that consumers consider while making online purchases of different products. The COVID-19 condition positively affects customer acceptance, performance, effort and product quality. This research indicates that service quality, online habits and trust do not influence customer acceptance of an ODP.

The study contributes to the body of knowledge regarding factors influencing the acceptance of ODPs. The factors that influence people’s acceptance of ODPs, especially during the COVID-19 pandemic, are assessed as to whether the COVID-19 pandemic influences people’s acceptance and the identified factor that has the strongest influence on the acceptance of digital delivery platforms.

The study contributes to the growing body of knowledge about how customer behaviors triggered by the COVID-19 condition influence customer acceptance of ODP and how behavior influences customer acceptance of ODP.

This paper is useful to academics, practitioners and policymakers in public administration and policy management. The research provides some insights into massive adoption of ODPs that affects the disruption of conventional business practices.

Drawing on the social identity theory, this paper explores the impact of rider–driver ethnicity match on the driver’s expected ride satisfaction and willingness to perform, and rider’s trust on the driver.

The study relies on scenario-based online experiments with 291 ride-hailing drivers and 282 riders in the USA.

The findings indicate that ethnicity match between ride-hailing drivers and riders positively impact driver’s ride satisfaction and willingness to perform, and rider’s trust in the driver. The study also revealed a significant positive moderation effect of ethnic identity on the relationship of ethnicity match and those constructs.

While it may be challenging to influence an individual’s level of ethnic identity, managers can take steps to educate and train their employees regarding the impact of ethnic identity and discrimination, with a particular focus on those individuals who possess a strong sense of ethnic identity.

The findings of this research provide theoretical contributions to the existing literature on ride-hailing services and adds to the limited stream of logistics research that examines the impact of ethnicity on ride-hailing operations.

The supply chain (SC) of the fast-moving consumer goods (FMCG) sector in India witnessed a significant change soon after introducing the Goods and Services Tax (GST). With the initiation of this tax, companies started moving from individual state-wise warehouses to consolidation warehouses model to save costs. This paper proposes a model that frames a mathematical formulation to optimize the distribution network in the downstream SC by considering the complexities of multi-product lines, multi-transport modes and consolidated warehouses.

The model is designed as mixed-integer linear programming (MILP), and an algorithm is developed that works on the feedback loop mechanism. It optimizes the transportation and warehouses rental costs simultaneously with impact analysis.

Total cost is primarily influenced by the critical factor transportation price rather than the warehouse rent. The choice of warehouses at prime locations was a trade-off between a lower distribution cost and higher rent tariffs.

The study enables FMCG firms to plan their downstream SC efficiently and to be in line with the recent trend of consolidation of warehouses. The study will help SC managers solve complexities such as multi-product categories, truck selection and consolidation warehouse selection problems and find the optimum value for each.

The issues addressed in the proposed work are transporting products with different sizes and weights, selecting consolidated warehouses, selecting suitable vehicles for transportation and optimizing distance in the distribution network by considering consolidated warehouses.

This study aims to explore the impact of carbon neutral announcements on “stock market value” of publicly listed companies in China.

The event study approach is adopted. Market, market-adjusted, Carhart four-factor model and a cross-sectional regression model are employed to examine the impacts of carbon neutral announcements on “stock market value” of Chinese companies based on data from 188 carbon neutral announcements.

Carbon neutral announcements positively impact Chinese shareholder value. Carbon neutral announcements at the strategic level have a more positive and significant impact on Chinese stock market value. Innovative carbon neutral announcements do not significantly cause Chinese stock market reactions. Companies have more positive and significant stock market reactions when the companies make carbon neutral announcements that reflect high supply chain network resilience and heterogeneity and strong supply chain network relationships.

The findings uncover the business value of carbon neutral activities and provide operations managers in developing countries insights into how to improve enterprises' market value by actively implementing carbon neutral activities.

This paper is the first trial to apply an event study to examine the relationship between carbon neutral announcements and Chinese stock market value from the perspective of announcement level and type and supply chain networks. This paper introduces corporate reputation theory and enriches the application of corporate reputation theory in the field of low-carbon environmental protections and supply chains.

Collaborative Logistics (CL) and merging operations are crucial strategies for reducing costs and improving service in transportation companies. This study proposes a model for optimizing efficiency in supply chain networks through inbound and outbound Collaborative Logistics implementation among the carriers in centralized, coordinated networks with cross-docking.

A mixed-integer non-linear programming model is developed to determine the optimal truck-goods assignment while gaining economies of scale through mixing multiple less-than-truckload (LTL) products with different weight-to-volume ratios. Unlike the previous studies that have considered Collaborative Logistics from the cost and profit-sharing perspective, the proposed model seeks to determine an appropriate form of Collaborative Logistics in the VRP.

This article shows that in a three-echelon supply chain consisting of a set of suppliers, a set of customers and a cross-docking terminal, partial collaboration among the inbound carriers and outbound carriers outperforms no/complete collaboration. This approach enhances the supply chain efficiency by minimizing the total transportation costs, the total transportation miles and the total number of trucks and maximizing fleet utilization. While addressing the four points, the role of collaborative logistics among the carriers was discussed. In a three-echelon SC consisting of a set of suppliers, a set of customers and a cross-docking terminal, partial collaboration among the inbound carriers and outbound carriers outperforms no/complete collaboration. Using a combination of experimental analysis and optimization process, it was recommended that managers be cautious that too much (full or complete) or no collaboration can result in SC performance deterioration.

The suggested approach enhances the supply chain efficiency by minimizing the total transportation costs, the total transportation miles and the total number of trucks and maximizing fleet utilization. While addressing the four points, the role of Collaborative Logistics among the carriers was discussed.

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.