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The purpose of this research is to gain a better understanding of how a crowd-shipping platform can achieve a critical mass of senders and carrier crowd members to yield network effects that are necessary for the platform to grow and thrive. Specifically, this research studies the participation decisions of both senders and carriers over time and the impacts of the resulting feedback loop on platform growth and performance.

An agent-based model is developed and used to study dynamic behavior and network effects within a simulated crowd-shipping platform. The model allows both carriers and senders to be represented as autonomous, heterogeneous and adaptive agents, whose decisions to participate in the platform impact the participation of other agents over time. Survey data inform the logic governing agent decisions and behaviors.

The feedback loop created by individual sender and carrier agents' participation decisions generates complex and dynamic network effects that are observable at the platform level. Experimental results demonstrate the importance of having sufficient crowd carriers available when the platform is initially launched, as well as ensuring that sender and carrier participation remains balanced as the platform grows over time.

The model successfully demonstrates the power of agent-based modeling (ABM) in analyzing network effects in crowd-shipping systems. However, the model has not yet been fully validated with data from a real-world crowd-shipping platform. Furthermore, the model's geographic scope is limited to a single census tract. Platform behavior will likely differ across geographic regions, with varying demographics and sender/carrier density.

The modeling approach can be used to provide the manager of a volunteer-based crowd-shipping program for food rescue with insights on how to achieve a critical mass of participants, with an appropriate balance between the number of restaurant food donation delivery requests and the number of crowd-shippers available and willing to make those deliveries.

This research can help a crowd-shipping platform for urban food rescue to grow and become self-sustainable, thereby serving more food-insecure people.

The model represents both senders and the carrier crowd as autonomous, heterogeneous and adaptive agents, such that network effects resulting from their interactions can emerge and be observed over time. The model was designed to study a volunteer crowd-shipping platform for food rescue, with participant motivations driven by personal values and social factors, rather than monetary incentives.

This study aims to review the literature on sharing economy logistics and crowd logistics to answer the three following questions: How is the literature on sharing economy logistics structured? What are the main trends in sharing economy logistics and crowd logistics? What are the future research options?

Bibliometric analysis is used to evaluate 85 articles published over the past 12 years; it identifies the top academic journals, authors and research topics contributing to the field.

The sharing economy logistics and crowd logistics literature is structured around several disciplines and highlights that some are more scientifically advanced than others in their subject definitions, designs, modelling and innovative solutions. The main trends are organized around three clusters: Cluster 1 refers to the optimal allocation of costs, prices, distribution and supplier relationships; Cluster 2 corresponds to business related crowdsourcing and international industry practices; and Cluster 3 includes the impact of transport on last-mile delivery, crowd shipping and the environment.

The study is based on data from peer-reviewed scientific journals and conferences. A broader overview could include other data sources such as books, book chapters, working papers, etc.

Future research directions are discussed in the context of the evolution from crowd logistics to crowd intelligence, and the complexities of crowd logistics such as understanding how the social crowd can be integrated into the logistics process. Our results are part of the crowd science and engineering concept and provide some answers about crowd cyber-system questions regarding crowd intelligence in logistic sector.

This study aims to investigate the conditions for the financial feasibility of an incentive-based model for self-drop or crowdsourced drop of the product to be returned at designated drop boxes (thereby ensuring a contactless process).

Constraint-based non-linear mathematical modeling was done for cost differential with and without crowdsourcing. This was analyzed against returns on investment for the installed infrastructure. Scenarios were looked into from the linear, iso-elastic and logarithmic demand functions to identify the optimal incentive policy. The results were further evaluated using “willingness to return” for customer willingness for product returns via drop boxes.

Crowdsourcing is viable when product returns are no more than 15%–20% of the overall products, with a logistics cost differential of 15%–25%. These were only viable when the product return incentive was within the range of 15%–20% of the product cost, as well as the penalty was in the range of 25 to 40% for wrong returns.

The findings are expected to aid the organizations in successfully designing product return policies while adhering to the post-COVID-19 norms, including contactless transactions and social distancing.

The study provides a look into the viability sensitivity of effective gains/profitability against the required level of service for returns, wrong returns, penalties and incentives for crowdsourcing in a developing country like India.

This paper aims to analyze the main challenges and critical success factors (CSFs) in managing multi-sided platforms (MSP) in Brazil, as well as to understand the differences between this management model and traditional companies.

Semi-structured interviews were conducted with experienced professionals in the field, focusing on challenges, CSFs and difficulties in managing MSP businesses. The data were analyzed using a mixed-method approach, involving content analysis for qualitative data and grey relational analysis and sensitivity analysis for quantitative data.

The experts identified eight CSFs, seven key differences between traditional businesses and MSPs, and five technology-related challenges in managing MSPs. They assessed the main difficulties reported in the literature and ranked them, with the most critical challenges being competition with companies adopting MSP models in the same sector (product/service niche) and the necessity for ongoing process adjustments to accommodate scalability.

This study enhances understanding of CSF, disparities between traditional and MSPs and technology-related challenges in this management model. The results can assist managers in emerging nations in enhancing the performance of MSP operations and can be a resource for researchers studying various contexts and creating company guidelines.

Effective information security management (ISM) contributes to building a healthy organizational digital ecology. However, few studies have built an analysis framework for critical influencing factors to discuss the combined influence mechanism of multiple factors on ISM performance (ISMP). This study aims to explore the critical success factors and understand how these factors contribute to ISMP.

This study used a mixed-method approach to achieve this study’s research goals. In Study 1, the authors conducted a qualitative analysis to take a series of International Organization for Standardization/International Electrotechnical Commission standard documents as the basis to refine the critical factors that may influence organizations’ ISMP. In Study 2, the authors built a research model based on the organizational control perspective and used the survey-based partial least squares-based structural equation modeling (PLS-SEM) approach to understand the relationships between these factors in promoting ISMP. In Study 3, the authors used the fuzzy set qualitative comparative analysis (fsQCA) method to empirically analyze the complex mechanisms of how the combinations of the factors affect ISMP.

The following three research findings are obtained. First, based on the text-based qualitative analysis, the authors refined the critical success factors that may increase ISMP, including information security policies (ISP), top management support (TMS), alignment (ALI), information security risk assessment (IRA), information security awareness (ISA) and information security culture (ISC). Second, the PLS-SEM testing results confirmed TMS is the antecedent variable motivating organization’s formation (ISP) and information control (ISC) approaches; these two types of organization control approaches increase IRA, ISA and ALI and then promote ISMP directly and indirectly. Third, the fsQCA testing results found two configurations that can achieve high ISMP and one driving path that leads to non-high ISMP.

This study extends knowledge by exploring configuration factors to improve or impede the performances of organizations’ ISM. To the best of the authors’ knowledge, this study is one of the first to explore the use of the fsQCA approach in information security studies, and the results not only revealed causal associations between single factors but also highlighted the critical role of configuration factors in developing organizational ISMP. This study calls attention to information security managers of an organization should highlight the combined effect between the factors and reasonably allocate organizational resources to achieve high ISMP.

Public participation in policy-making can play a fundamental role in improving effectiveness via two mechanisms: strengthening the alignment between public needs and proposed measures, and increasing public consensus (and compliance) about them. It is, therefore, particularly relevant to foster public participation in sustainable mobility planning at the urban scale, as strongly recommended by the European Union, not only to avoid protests and resolve conflicts but also to find the best solutions for the city. Among many different tools and methodologies for implementing public participation, Living Labs have also shown great potential in enhancing the co-creation of strategies and measures for achieving sustainable mobility for both passengers and freight.

Through the analysis of the participatory process carried out by the municipality of Rome to support the definition of the Sustainable Urban Mobility and Logistics Plans, this chapter explores different involvement levels, tools and strategies in this field, with a particular focus on the innovative Logistics Living Lab developed in this city. This also contributes to filling a gap in the literature on how and to what extent citizens could or should participate in city logistics planning. The results of the analysis highlight that, despite these efforts, citizen participation in planning urban logistics is still a challenge that deserves additional effort and resources to be properly enhanced and improved and that a Living Lab offers great potential to meet this challenge. In turn, this case study could help policy-makers to identify solutions for more effective and acceptable measures to addressing city logistics and the externalities it generates.

This paper aims to review the literature on “E-fulfillment” with respect to marketing and operations issues in the current dynamic and complex e-tailing environment and thereby generate significant insights.

This paper is based on a systematic literature review on e-fulfillment focusing on marketing and operations issues therein. This systematic literature review consists of a critical review on e-fulfillment under planning (review question initialisation), searching (literature search), screening (literature evaluation), extraction and synthesis and reporting phases to conceptualise e-fulfillment. A total of 122 research articles have been reviewed to explore e-fulfillment and to develop key constructs and propositions.

This review provides the following three outcomes. First, the varied-fulfillment definitions have been critically reviewed, leading to synthesis, and thereby, an e-fulfillment definition is provided. Further, the variations for e-fulfillment across product types, which have been identified as a key variable for e-fulfillment, have been explored. Second, authors find five e-fulfillment components at the marketing and operations interface: website quality, customisation strategy, distribution strategy, last mile delivery and return management. Continuing with the e-fulfillment interface with marketing, the linkages between e-fulfillment and select post-purchase consumer behaviours measures across different product types have been reviewed. The paper thus with a focus on synthesising e-fulfillment literature from a process perspective emphasises the consumer behaviour metric for measuring e-fulfillment performance.

This study would help academicians, researchers, e-tailers and practitioners to understand e-fulfillment from a process perspective. For the researcher, it presents areas for future research by giving possible research directions in this emerging area. This study also brings out the impact of e-fulfillment according to product type on the post-purchase consumer behaviour measures, which will help e-tailers to link e-fulfillment to consumer behaviour metrics.

The paper classifies the fragmented literature to develop constructs and propositions for e-fulfillment. This is the first kind of study on e-fulfillment process and its impact on select post-purchase consumer behaviour measures across product types.

There is limited literature linking e-fulfillment and product type with postpurchase consumer behavior measures like loyalty, even though there has been a rapid increase in e-tailing. E-fulfillment is defined in literature as a sequence of processes. Each process in this sequence is expected to have a different impact on consumer loyalty across product type. Thus relative importance of e-fulfillment processes leading to consumer loyalty. The purpose of this study is to investigate the impact of e-fulfillment on consumer loyalty across two product types: “standard, regular” and “physical product” (e.g. book, clothing, etc.) and “standard, nonregular” and “physical product” (e.g. computer, refrigerator, etc.) using the peak-end rule theory for an e-tailer.

To know the consumer loyalty for e-fulfillment across the two product types, the partial least square-structural equation modeling approach aided by the SmartPLS 3 tool was used for data analysis as it avoids biases in the parameter estimation in regression analysis. A total of 603 consumer responses through an online and physically administered questionnaire were obtained and were used for the empirical analysis.

Results indicate that for standard, nonregular and physical products, all the e-fulfillment components (customization strategy, website quality, distribution strategy, last mile delivery and return management) positively impact consumer loyalty. Except for the customization strategy, for standard regular and physical product types, all other e-fulfillment components positively impact consumer loyalty.

This study will be helpful to e-tail managers to configure the e-fulfillment components according to product types, thereby increasing consumer loyalty.

While some e-fulfillment components have been linked to consumer loyalty in literature, there is no study establishing linkages between e-fulfillment as a construct and consumer loyalty across product types. This has implications for decision makers in e-tail as the study provides e-fulfillment strategy customization across product types for achieving consumer loyalty in e-tail, a key marketing metric.

This research investigates the effects that blockchain exerts on omnichannel solutions and logistics strategies with the aim of solving the last mile issues and improving performance.

Research hypotheses are developed according to the literature review and the related gaps. Then, the hypotheses are tested using structural equation modelling and adopting a partial least squares – path modelling technique on a dataset composed of 157 firms.

Blockchain technology alone is not an effective driver in solving last mile issues and improving performance. Rather, it exerts a positive contribution to both omnichannel and logistics. However, omnichannel is not effective in managing last mile problems and increasing performance without the support of other practices. Firms need to implement a strong logistics system to manage the last mile and get high performance, which can be then reinforced through blockchain and omnichannel solutions.

This research investigates the novel wave of research on blockchain and its impact on logistics management and omnichannel. It combines these ingredients to address the issues of last mile and improve the economic performance. The research provides an empirical verification of a new research stream that currently lacks empirical support.