Essays on neighborhood effects and spatial diffusion: Evidence from online grocery retailing

For a traditional retailer, the size of the customer pool can evolve over time but is largely bounded in space. In contrast, an Internet retailer with the appropriate shipping infrastructure can draw customers from a wide-ranging geographical area (e.g., the entire United States). Insight into the process of customer base evolution is therefore of considerable importance for managers and researchers alike. In this dissertation, we examine the space-time sequencing of customer orders and the individual trial decision for customers shopping at an Internet grocery retailer (Netgrocer.com). Drawing on literature in economics, marketing and sociology, we conjecture that the trial decision may be subject to neighborhood effects. That is, exposure to the actions of proximate others—either through direct social interaction or passive observation—influences the trial decision of individuals who have yet to experience the service. We focus on obtaining answers to the following general research questions: (1) Is there evidence that neighborhood effects are helping to generate the observed pattern of customer evolution in space and time? (2) If so, what is the economic impact of neighborhood effects on space-time diffusion? (3) Are the neighborhood effects absent for repeat purchase decisions? These questions are examined in two separate essays. In the first essay, we develop a discrete-time hazard model in which consumer trial decisions arise from utility-maximizing behavior. In the second essay, a spatial mixture modeling framework is developed. Each essay addresses substantive implications for customer base evolution in an Internet retailing context. All models are calibrated on a unique dataset that combines: (1) a complete transaction history from Netgrocer.com, (2) US Census information, and (3) region-level retail structure data. Geographic Information System (GIS) analysis is employed to create an alternative representation of spatial interactions

The MNE as a portfolio: Interdependencies in MNE growth trajectory

We conceptualize the MNE as a portfolio of interdependent sub-units, and examine its growth trajectory in relation to its existing portfolio. The empirical testing is based on a unique dataset that details all the location moves of US legal services MNEs during 1949–2006. These MNEs evolve in directions that follow from their past. Their portfolios affect their subsequent moves, speaking for the impact of interdependencies among sub-units on the evolution of MNEs. The portfolio exercises stronger impact on entry than on exit, suggesting that different forces affect MNEs’ expansion and contraction. We outline strategic and organizational implications of the conceptualization of the MNE as a portfolio.

A SPATIAL MIXTURE MODEL OF INNOVATION DIFFUSION

The diffusion of new product or technical innovation over space is here modeled as an event-based process in which the likelihood of the next adopter being in region r is influenced by two factors: (i) the potential interactions of individuals in r with current adopters in neighboring regions, and (ii) all other attributes of individuals in r that may influence their adoption propensity. The first factor is characterized by a logit model reflecting the likelihood of adoption due to spatial contacts with previous adopters, and the second by a logit model reflecting the likelihood of adoption due to other intrinsic effects. The resulting spatial diffusion process is then assumed to be driven by a probabilistic mixture of the two. A number of formal properties of this model are analyzed, including its asymptotic behavior. But the main analytical focus is on statistical estimation of parameters. Here it is shown that standard maximum-likelihood estimates require large sample sizes to achieve reasonable results. Two estimation approaches are developed which yield more sensible results for small sample sizes. These results are applied to a small data set involving the adoption of a new Internet grocery-shopping service by consumers in the Philadelphia metropolitan are

Annual and seasonal patterns in etiologies of pediatric community-acquired pneumonia due to respiratory viruses and Mycoplasma pneumoniae requiring hospitalization in South Korea

BACKGROUND: Community–acquired pneumonia (CAP) is one of the leading worldwide causes of childhood morbidity and mortality. Its disease burden varies by age and etiology and is time dependent. We aimed to investigate the annual and seasonal patterns in etiologies of pediatric CAP requiring hospitalization. METHODS: We conducted a retrospective study in 30,994 children (aged 0–18 years) with CAP between 2010 and 2015 at 23 nationwide hospitals in South Korea. Mycoplasma pneumoniae (MP) pneumonia was clinically classified as macrolide-sensitive MP, macrolide-less effective MP (MLEP), and macrolide-refractory MP (MRMP) based on fever duration after initiation of macrolide treatment, regardless of the results of in vitro macrolide sensitivity tests. RESULTS: MP and respiratory syncytial virus (RSV) were the two most commonly identified pathogens of CAP. With the two epidemics of MP pneumonia (2011 and 2015), the rates of clinical MLEP and MRMP pneumonia showed increasing trends of 36.4% of the total MP pneumonia. In children < 2 years of age, RSV (34.0%) was the most common cause of CAP, followed by MP (9.4%); however, MP was the most common cause of CAP in children aged 2–18 years of age (45.3%). Systemic corticosteroid was most commonly administered for MP pneumonia. The rate of hospitalization in intensive care units was the highest for RSV pneumonia, and ventilator care was most commonly needed in cases of adenovirus pneumonia. CONCLUSIONS: The present study provides fundamental data to establish public health policies to decrease the disease burden due to CAP and improve pediatric health

Neighborhood effects and trial on the internet: Evidence from online grocery retailing

Discrete time hazard, Neighborhood effect, Random utility, Retailing, C25, M30,