Castillo, V. E., Bell, J. E., Rose, W. J., & Rodrigues, A. M. (2018). Crowdsourcing last mile delivery: Strategic implications and future research directions. Journal of Business Logistics , 39 (1), 7-25
The article’s primary aim was to assess the role of crowdsourced logistics (CSL) on logistics strategy. The authors applied a contingency theory lens research approach to assess the effectiveness of CSL in enhancing same-day delivery services from distribution centers to 1000 customers across New York City. The authors were also moved to understand the performance of CSL under dynamic market conditions and compare the results from the study with the traditional dedicated fleet of delivery drivers. The authors analyzed the results and gave recommendations on how firms can benefit from adopting CSL. The paper also provides a definite plan for future research by highlighting the exploration of strategic implications to deepen knowledge about the relatively new CSL phenomenon. The article will increase the knowledge in the effectiveness of crowdsourcing in last mile delivery.
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Ermagun, A., Punel, A., & Stathopoulos, A. (2020). Shipment status prediction in online crowdsourced shipping platforms. Sustainable Cities and Society , 53 , 101950
This research paper aimed to develop a model to increase the understanding and prediction of the crowd-shipping delivery performance. This understanding would help in the formulation of incentives for improving system performance and the user experience. The authors applied Random Forest algorithm for machine learning to predict 14,858 crowd-shipping requests between January 2015 and December 2016 in the US. The acceptance, bidding, and delivery were the three phases that the model was required to predict. The shipping request, social-economic features, and the built environment were used as the explanatory variables. The study results indicated that crowd-shipping gave an excellent predictive performance, even when the results of the package information are in obscurity. The results also showed that crowd-shipping could enhance the prediction of the status of shipment in real-time.
Ermagun, A., & Stathopoulos, A. (2018). To bid or not to bid: An empirical study of the supply determinants of crowd-shipping. Transportation Research Part A: Policy and Practice , 116 , 468-483
The authors present an in-depth analysis of crowdsourcing in logistics through the document-based analysis method. The authors opine that the inclusion of sensor-supported functionalities, such as the use of crowdsourcing applications, promotes user interactions at the right time and place. The authors analyzed LBCS for both “information” and “classic” logistics. The study also discussed the potential pros and cons of crowd logistics. The researcher aimed to provide the necessary basis for promoting a novel interdisciplinary approach in the field.
Frehe, V., Mehmann, J., & Teuteberg, F. (2017). Understanding and assessing crowd logistics business models–using everyday people for last mile delivery. Journal of Business & Industrial Marketing, 32 (1), 75-97.
This paper aimed to assess the characteristics and the nature of the crowd logistics (CL) business models. The authors used evaluation, a relatively new concept, to implement a sustainable crowd logistics approach. The study used a Design Science process to develop the proposed “crowd-logistics business-model concept.” The data for the study was obtained from document-based data analysis of thirteen expert interviews. The study results showed that companies could follow distinct steps in the implementation of sustainable crowd logistic services. The authors also established that open research tasks could have a greater significance in understanding the emerging fields. One limitation of the research was that the holistic approach view used lacked detailed descriptions.
Gatta, V., Marcucci, E., Nigro, M., & Serafini, S. (2019). Sustainable urban freight transport adopting public transport-based crowd shipping for B2C deliveries. European Transport Research Review , 11 (1), 1-14
The authors were motivated to assess and understand crowd shipping platforms’ economic and environmental effects in urban areas. The research was based on the city of Rome, and the study focused on how the city’s mass transit network exemplifies an environmentally-friendly crowd-shipping strategy. The study’s success depended on passengers’ willingness to buy crowd-shipping services in the form of mass transit networks, on which the study was based. After quantifying the potential demand for the crowd-shipping services, the authors created an extensive stated preference survey with a 2025 projection to estimate how externalities, such as pollution and revenues, affect the crowd-shipping strategy and its impacts on last-mile deliveries. This research’s benefits included giving freight companies and local policy-makers a good knowledge-base for the future implementation of public transport-based crowd-shipping.
Huang, L., Xie, G., Blenkinsopp, J., Huang, R., & Bin, H. (2020). Crowdsourcing for sustainable urban logistics: Exploring the factors influencing crowd Workers’ participative behavior. Sustainability , 12 (8), 3091
The authors opine that crowd logistics has become one of the most lucrative and most promising parts of several cities’ last-mile delivery challenges. Moreover, the authors note that the continued participation of workers is a critical issue that affects the growth of the crowd-logistics platform. The motive behind this paper is to comprehend how people are motivated by their continued participation in crowd-logistics and how this can provide clarity on the measures and policies that can be undertaken to support its growth. The authors used the Push-Pull–Mooring (PPM) theory to develop the research model that explains the factors that impact the participative behavior of crowd workers. Data were acquired from 455 crowd workers, and the SmartPLS3.0 software was used for data analysis. The study results showed that trust and monetary rewards strongly influenced the crowd workers to continue participating in the crowd – logistics.
Le, T. V., & Ukkusuri, S. V. (2019). Modeling the willingness to work as crowd-shippers and travel time tolerance in emerging logistics services. Travel Behaviour and Society , 15 , 123-132
The article’s main aim was to understand the considerations of different behaviors and how they affect people’s choice in engaging in the crowd-shipping market. The authors developed an ordinary least-square and a regression model to help in carrying out the research. The authors used selective-bias terms to integrate the models. The study results suggested that the socio-demographic characteristics, social media usage, and freight transportation experience significantly affected respondents’ decisions, especially on their choice to participate in the crowd-shipping market. The study results also showed that the crowd-shipper expectation of the “expect-to-be-paid.” rate was consistent with the value-of-time literature. The study’s findings are valuable for companies considering recruiting employees to enhance their business strategies.
Rześny-Cieplińska, J. (2019). Crowd logistics–concept and application possibilities in Polish cities. Studia Ekonomiczne , 383 , 20-30.
The researcher aimed to understand how crowd logistics organizational concepts help streamline and optimize passenger processes and cargo flow in urban areas. The authors approached the study by focusing on the possibilities of implementing crowd logistics solutions, the solution types, and the advantages that can be accrued from implementing the solutions for authorities, tourists, residents, and entrepreneurs. The authors reviewed the experiences and solutions of crowd logistics as used in metropolises worldwide. They used this basis to determine the kind of crowd logistics that were likely to be adopted in Polish cities. By analyzing the possibilities of adapting the crowd logistic concept in Polish conditions, the author sought to find solutions to in improving the state of cities around the world and the challenges that hinder the implementation of such solutions.
Rześny-Cieplińska, J., & Szmelter-Jarosz, A. (2019). Assessment of the crowd logistics solutions—The stakeholders’ analysis approach. Sustainability , 11 (19), 5361
The article’s main aim was to understand the solutions for the field of crowd logistics to help in the adjustment of market offers and business models for other providers to meet the stakeholders’ needs. The article, therefore, presents the crowd logistic results from the perspective of the needs of various stakeholders in the transport and logistics field. The authors applied the AHP - analytic hierarchy process- method to develop an appropriate tool to support crowd logistics. The model’s data was derived from the service providers’ information, and the document-based analysis of data provided the evaluation criteria. From the study, recommendations for the managers were drawn. The recommendations are meant to guide managers on how to appropriately adjust the solutions to the needs of the stakeholders.
Yildiz, B., & Savelsbergh, M. (2019). Service and capacity planning in crowdsourced delivery. Transportation Research Part C: Emerging Technologies , 100 , 177-199
The article’s primary aim was to investigate the relationship between delivery offer acceptance probability and profit and outline the advantages of integrating the several restaurant delivery services. The research was also significant for highlighting insights, such as the relationship between service area and profit. The study also clarifies the pros and cons of introducing crowdsourced delivery, transport solutions and samples how some on-demand service platforms rely on crowdsourced transportation capacity in their business models. The authors established a few models supporting the service area analysis, delivery capacity planning, service quality, and interactions in such environments. Thus, the authors introduced a model that can solve most problems that arise in such settings. Therefore, the study presents results related to courier compensation and profit to the service area.
References
Castillo, V. E., Bell, J. E., Rose, W. J., & Rodrigues, A. M. (2018). Crowdsourcing last mile delivery: Strategic implications and future research directions. Journal of Business Logistics , 39 (1), 7-25.
Ermagun, A., & Stathopoulos, A. (2018). To bid or not to bid: An empirical study of the supply determinants of crowd-shipping. Transportation Research Part A: Policy and Practice , 116 , 468-483.
Ermagun, A., Punel, A., & Stathopoulos, A. (2020). Shipment status prediction in online crowdsourced shipping platforms. Sustainable Cities and Society , 53 , 101950.
Frehe, V., Mehmann, J., & Teuteberg, F. (2017). Understanding and assessing crowd logistics business models–using everyday people for last mile delivery. Journal of Business & Industrial Marketing, 32 (1), 75-97.
Gatta, V., Marcucci, E., Nigro, M., & Serafini, S. (2019). Sustainable urban freight transport adopting public transport-based crowdshipping for B2C deliveries. European Transport Research Review , 11 (1), 1-14.
Huang, L., Xie, G., Blenkinsopp, J., Huang, R., & Bin, H. (2020). Crowdsourcing for sustainable urban logistics: Exploring the factors influencing crowd Workers’ participative behavior. Sustainability , 12 (8), 3091.
Le, T. V., & Ukkusuri, S. V. (2019). Modeling the willingness to work as crowd-shippers and travel time tolerance in emerging logistics services. Travel Behaviour and Society , 15 , 123-132.
Rześny-Cieplińska, J. (2019). Crowd logistics–concept and application possibilities in Polish cities. Studia Ekonomiczne , 383 , 20-30.
Rześny-Cieplińska, J., & Szmelter-Jarosz, A. (2019). Assessment of the crowd logistics solutions—The stakeholders’ analysis approach. Sustainability , 11 (19), 5361.
Yildiz, B., & Savelsbergh, M. (2019). Service and capacity planning in crowdsourced delivery. Transportation Research Part C: Emerging Technologies , 100 , 177-199.
