Does peer monitoring influence choices between cash and food? Findings from a field experiment

To explore whether choices for transfers are influenced by peer monitoring, we examine private versus public choices among monetarily equivalent values of cash and food in northern Kenya. Many northern Kenyan communities face high-levels of chronic food insecurity and are tightly-knit, often sharing food aid transfers. Yet, humanitarian cash transfers are relatively new to the area. Whether cash will be subject to the same sharing norms is not well understood. Utilizing a randomized block experiment, we find that assigning a respondent to choose in front of peers decreases the likelihood of choosing a cash transfer relative to at least some food. We argue that peer monitoring decreases the value of cash relative to food in two inter-related ways. Choosing food in public, first, provides an opportunity for respondents to publicly demonstrate a commitment to local food aid sharing norms. Second, choosing cash in public may be riskier since cash does not yet have established sharing norms. A critical implication is that transfer choices and retargeting of resources within the community can be influenced by use of public or private discussions when eliciting community views, especially in communities where sharing is a salient social norm.     

基于微分博弈的乳制品供应链质量管理研究

考虑到合理的成本分担及公平的利润分配是影响乳制品供应链系统稳定及乳制品质量保证的重要环节,本文以一个乳制品加工企业、一个奶农(牧场)和一个零售商所构成的三级供应链为研究对象,引入微分博弈的方法,研究在4种不同的乳制品质量管理博弈情形下,乳制品供应链上各成员企业愿意为质量管理工作付出的努力及其收益.研究结果表明,乳制品加工企业的质量控制和质量改进两种工作的努力程度在3种非合作质量管理博弈情形下具有相同的表现,而在合作质量管理博弈情形下,为了供应链整体利益考虑,核心企业即乳制品加工企业的质量管理工作努力程度发生了变化.而对于乳制品供应链上游的奶农和下游的零售商而言,二者对于质量管理工作的努力程度随着乳制品供应链合作的深化而不断提高,在理想的合作博弈情形下达到了最高.     

Identifying cycling-inducing neighborhoods: A latent class approach

Understanding how spatial attributes of cities and neighborhoods induce cycling is relevant for urban planning and policy making. In this work, ordered logit and latent class models are specified and estimated to analyze how the built environment affects bicycle-commuting frequency. Data come from a survey to 1,487 people in the city of Santiago, Chile, including sociodemographic information, travel behavior patterns and place of residence and work. Using geographic information systems tools, the built environment was characterized with variables calculated for a 500-m-radius buffer around the residential and work locations of each individual. Two models are estimated, first an ordered logit model confirms that built environment variables effect on cycling is similar to what has been reported in the literature, with some new findings such as an increase in cycling when public transport accessibility is low and the role of built environment attributes at the destination. Second, a latent class ordered logit is used to identify two classes of neighborhood in term of their cycling patterns, as a function of their density, presence of cycling infrastructure and distance to the main activity center of the city. This result allows to map the class membership probabilities, potentially helping to identify neighborhoods that encourage cycling and providing relevant information for policy making and infrastructure decisions.     

Exploring the motivations to use online meal delivery platforms: Before and during quarantine

Online meal delivery platforms (OMDPs), like UberEats, have received more attention since quarantine was established to prevent the spread of COVID-19. The research into antecedents of satisfaction and continuous usage intention for OMDPs, in general, is under researched. The current study compared the antecedents of satisfaction before quarantine to the antecedents during quarantine through the lens of Expectation-Confirmation Theory. Through multiple regression analyses, the researchers found that before quarantine, sharing economy ethos, price-value, food quality, ease of use and confirmation of beliefs had a significant impact on satisfaction while during quarantine, food quality, service speed, ease of use, and confirmation of beliefs were significant. Practical and theoretical implications are discussed.     

What prevents consumers that are aware of Airbnb from using the platform? A mixed methods approach

The hospitality sector is now characterised by the co-existence of traditional providers and sharing economy enterprises. It is important to better understand what prevents the use of peer-to-peer accommodation rentals in the tourism marketplace. Adopting a mixed-methods approach, this study first examines travellers’ Airbnb use constraints, and then profiles 252 Airbnb non-users based on their constraints and characteristics. The findings suggest that travellers do not use Airbnb because of distrust in the providers, in the platform and in other users, as well as perceived risk and unfamiliarity. Loss of service quality, lack of local experience, legal and regulatory issues, and disinterest also prevented consumers to book Airbnb accommodations. A cluster analysis divided non-users into three segments: Traditional travellers, Sharing economy misbelievers and Airbnb prospective users. Significant differences based on age confirmed that young travellers are more confident in using peer-to-peer accommodation platforms and more interested in the philosophy.     

Modeling Airbnb demand to New York City while employing spatial panel data at the listing level

Using spatial panel data comprising a cross section of 1,461 continuously active Airbnb listings obtained from AirDNA, as well as time series data from NYC and Company and the OECD covering the time period September 2014 to June 2016, the present study quantifies own price, cross price, and income elasticities of Airbnb demand to New York City within an empirical tourism demand framework. The particular goal of the study is to establish whether the relationship between Airbnb and the traditional accommodation industry is of a substitutional or of a complementary nature. Employing a one-way fixed-effects spatial Durbin model, it can be concluded that demand is price-inelastic for Airbnb accommodation in New York City, which is a luxury good, and that the city's traditional accommodation industry as well as neighboring Airbnb listings are substitutes for the investigated Airbnb listings. The estimation results are robust against several alternative specifications of the regression equation.     

Entrepreneurs in the making: Six decisions for fostering entrepreneurship through maker spaces

Maker spaces—shared production facilities offering access to basic and advanced manufacturing technologies—have quickly become the latest must-have for universities, large corporations, and communities looking to foster entrepreneurship and innovation. While the entrepreneurial and educational prospects of maker spaces are certainly intriguing, questions remain concerning their design and effectiveness. Drawing primarily on case evidence and conversations with five maker spaces located across the U.S., we identify and present six key decisions for maker space leaders looking to foster entrepreneurship in their organizations. We conclude with a decision framework for maker space leaders and a series of questions for entrepreneurs as both groups work to pursue entrepreneurship through and in maker spaces.     

知识视角下跨界创业团队交互记忆系统作用机理研究

在当前激烈的市场竞争下，很多企业选择跨界创业，而现有相关研究相对较少。从知识视角入手，通过分析跨界创业团队交互记忆系统在促进团队内知识共享、整合方面的作用，分析其对团队知识转化的作用机理，并构建基于知识视角的跨界创业团队交互记忆系统作用模型。通过对跨界创业团队交互记忆系统的作用机理进行探究，了解跨界创业在促进企业发展方面的作用，以期丰富跨界创业相关理论，并对现实中企业跨界创业行为起到一定的促进和帮助。     

Does Airbnb have a homogenous impact? Examining Airbnb’s effect on hotels with different organizational structures

Although a number of studies have examined Airbnb’s impact on hotels, previous studies have yielded mixed results and are limited in their geographical scope. Additionally, the impact of Airbnb on hotels with different organizational structures has not been previously analyzed. Accordingly, the purpose of this study is threefold: 1) to add to our understanding of the impact of an increase of Airbnb inventory by clarifying previously inconclusive results; 2) to examine the extent to which Airbnb listings affect hotel performance measures in the overall U.S. hotel market; and 3) to investigate the influence of Airbnb on key hotel metrics by elaborating the effect of Airbnb on hotels operated under different organizational forms- chain-managed, franchised, and independent. Our results show an adverse impact of Airbnb on hotel RevPAR and ADR metrics across different organizational structures. However, interestingly, Airbnb listings did not negatively affect occupancy numbers. Theoretical and practical implications are discussed.