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Warren Nutter and James M. Buchanan did not revise “Universal Education” to turn against providing tuition grants to segregated schools in 1965. Their revised text contains no call to expel segregation academies from the tuition grant program and does not even express disapproval of the goals or the work of segregation academies. Recent claims to that effect by Fleury (2023) and Levy and Peart (2023) cannot be sustained by either textual or contextual evidence.

Failed deliveries (i.e. deliveries not accomplished due to the absence of customers) represent a critical issue in B2C (Business-to-consumer) e-commerce last-mile deliveries, implying high costs for e-commerce players and negatively affecting customer satisfaction. A promising option to reduce them would be scheduling deliveries based on the probability to find customers at home. This work proposes a solution based on presence data (gathered through Internet of Things [IoT] devices) to organise the delivery tours, which aims to both minimise the travelled distance and maximise the probability to find customers at home.

The adopted methodology is a multi-method approach, based on interviews with practitioners. A model is developed and applied to Milan (Italy) to compare the performance of the proposed innovative solution with traditional home deliveries (both in terms of cost and delivery success rate).

The proposed solution implies a significant reduction of missed deliveries if compared to the traditional operating mode. Accordingly, even if allocating the customers to time windows based on their availability profiles (APs) entails an increase in the total travel time, the average delivery cost per parcel decreases.

On the academic side, this work proposes and evaluates an innovative last-mile delivery (LMD) solution that exploits new AI (Artificial Intelligence)-based technological trends. On the managerial side, it proposes an efficient and effective novel option for scheduling last-mile deliveries based on the use of smart home devices, which has a significant impact in reducing costs and increasing the service level.

State-owned enterprises’ (SOEs) goals are perceived as two-sided blades, providing goods or services to the public on one side and escalating the government’s wealth on the other side. Treating the SOEs, government encounters the problem of injection strategy or privatize them. At the same time, managers have the option to formulate the SOEs strategy to boost performance. By using Miles and Snow’s typology strategy and the above factors, this paper investigates those impacts on Indonesia’s SOEs’ performance. This study aims to propose strategic typology as the main predictor with other variables such as the size, ownership structure, market competitiveness and capital subsidy on SOEs.

The study uses archived SOEs’ financial data from 2014 to 2018 to predict the financial performance using ordinal logistic regression analysis. The additional factors, such as firm size, ownership structure, market concentration and capital subsidy, are incorporated.

The result demonstrates that SOEs strategic typology, market concentration, size, ownership structure and capital subsidy significantly affect Indonesia’s SOEs’ performance.

To the best of the authors’ knowledge, this paper is the first elaborating government policies for SOEs, such as capital subsidy and state ownership, on the perspective of Miles and Snow’s strategy-performance relationship. Correspondingly, the paper contributes to examine the Indonesian characteristic SOE type with the performance. No single study has previously explored this relationship in the context of SOE in Indonesia.

This paper aims to explore the conditions in a business-to-business-to-consumer (B2B2C) context characterized by new technologies. Innovations enhance disintermediation and pursue sustainability goals that drive customers’ willingness to use eco-friendly delivery options, namely, parcel lockers – in e-commerce and their impacts in terms of communication and transparency along the supply network.

The study conducted an extensive survey in Italy and Germany, collecting 1,010 usable responses. Structural equation modelling was used to analyse the data with the aim of identifying the factors that drive customers’ willingness to use parcel lockers and the effect on customers’ behaviour as determined by the disclosure of information about the environmental performance of different delivery options.

The results highlight several factors affecting the willingness to use parcel lockers, namely, performance and effort expectancy, social influence, technology anxiety, hedonistic motivation and environmental knowledge. The results also demonstrate that the disclosure of information about the environmental performance of different delivery options influences customers’ behaviour.

This paper faces several limitations, mostly related to the focus on just two countries, the use of cross-sectional data and the survey’s explicit reference to just one type of product. Nevertheless, the findings contribute to the discussion on the relevance of information sharing along the supply chain, providing favourable evidence in this regard. It also improves the stream of research concerning technology adoption in the context of e-commerce, highlighting factors that can lead consumers to use eco-friendly self-service technologies.

The results can support companies in understanding how they can design and manage the last mile of delivery to jointly achieve customer satisfaction, process efficiency and superior environmental performance.

This pioneering contribution studies the adoption of delivery solutions for e-commerce and its implications for the supply network.

Despite large bodies of research related to the impacts of e-commerce on last-mile logistics and sustainability, there has been limited effort to evaluate urban freight using an equity lens. Therefore, this study proposes a modeling framework that enables researchers and planners to estimate the baseline equity performance of a major e-commerce platform and evaluate equity impacts of possible urban freight management strategies. The study also analyzes the sensitivity of various operational decisions to mitigate bias in the analysis.

The model adapts empirical methodologies from activity-based modeling, transport equity evaluation, and residential freight trip generation (RFTG) to estimate person- and household-level delivery demand and cargo van traffic exposure in 41 U.S. Metropolitan Statistical Areas (MSAs).

Evaluating 12 measurements across varying population segments and spatial units, the study finds robust evidence for racial and socio-economic inequities in last-mile delivery for low-income and, especially, populations of color (POC). By the most conservative measurement, POC are exposed to roughly 35% more cargo van traffic than white populations on average, despite ordering less than half as many packages. The study explores the model’s utility by evaluating a simple scenario that finds marginal equity gains for urban freight management strategies that prioritize line-haul efficiency improvements over those improving intra-neighborhood circulations.

Presents a first effort in building a modeling framework for more equitable decision-making in last-mile delivery operations and broader city planning.

Background: The study focuses on the challenges encountered during the distribution of food and face-mask items during the first COVID-19 lock-down by various relief supply chain actors.

Methods: Data were collected from forty (40) relief actors through online (via Zoom and telephones) and face-to-face interviews, between January 2021 to March 2021. Data was coded based on per-determined themes after which it was further processed using Atlas ti. v7.57 to generate patterns.

Results: The study established challenges related to needs identification, procurement, warehousing, transportation, handling, beneficiary verification, and last-mile distribution. Additionally, the media and politics coupled with the emergence of new actors and governance issues were part of the challenges identified.

Conclusions: The identified challenges were internal and external to the relief supply chain; hence actors could have control over some while others were beyond their control. The findings could inform practitioners and policymakers on what challenges are likely to affect their operations, especially during a pandemic, and design appropriate coping mechanisms.

The COVID-19 pandemic has resulted in a brand-new phenomenon in customer consumption patterns. This resulted from heightened health awareness brought on by the COVID-19 epidemic. There is a dearth of appropriate health psychology perspectives in the existing study examining the effect of COVID-19 on consumers’ use of crowdsourced logistics (CL) platforms. In order to provide unique and thorough insights into how consumer health concerns can affect consumers’ subjective views and their decisions to use CL, this study combines the health belief model and the technology acceptance model.

Five hundred valid responses from an online survey that was created and administered in Singapore were analysed using structural equation modelling.

The findings show that all of the suggested constructs have a favourable influence on consumers’ intentions to use CL. The suggested model also demonstrates high explanatory power, with perceived usefulness serving as the primary driver, followed by perceived ease of use and self-efficacy.

The study advances previous academic research on CL and offers guidance to CL companies and lawmakers for promoting sustainable and secured last-mile delivery.

This chapter demonstrates the ways in which digital inclusion functions as a super social determinant of health, particularly within the arena of family carework and healthcare for vulnerable disabled US communities. The focus on vulnerable populations, including the elderly, chronically ill, young disabled, neurodivergent, and/or medically complex children and the families that care for them, is a useful case to present a compelling argument for the need to take seriously digital inclusion to maximize health, safety, and well-being for growing populations of Americans today. The authors argue that digital inclusion is an increasingly influential social determinant of health and a key dimension of health equity that offers important benefits and potentials, especially for vulnerable patient populations, for whom in-home and family-centered care are necessary parts of health maintenance, prevention, and well-being. The chapter ends with a discussion of ways that the US government can mitigate digital barriers and facilitate equitable access to broadband internet and e-health resources that address the intersections of digital, health, and care inequalities, with significant impacts in all three dimensions.

Much of extant literature on entrepreneurship ecosystems is geared toward mid- and large-size metropolitan areas, and small cities are considered disadvantageous without essential elements for the ecosystem. The purpose of this paper is to shed light on understanding how small cities can have vibrant entrepreneurship ecosystems.

This study conducted 42 semistructured interviews of entrepreneurs and supporters in small towns of Montana, USA. This study also supplemented with a survey of 178 firms.

Entrepreneurs in small cities enjoy dense support networks including experienced entrepreneurs, key business and civic leaders and elected officials. They also attend entrepreneurial events and establish connections with support organizations with a distance of 200 miles.

The cases in this paper demonstrate that small cities can have vibrant entrepreneurship ecosystems without urban diversity and agglomeration. That additionally means that we should not apply the theoretical framework developed with large urban areas to small cities and consider different models of development for small cities.