Logistic Choice Research Articles

Shipping Chain Choices in Long-Distance Supply Chains

Shipping chain configuration is one of the key logistics choices that have been ignored or treated insufficiently in the current freight transportation models. This study focuses on the shipping chain configuration and the modeling of its relevant logistics choices, including number of stops and stop types. A brief descriptive analysis of the results of an online establishment survey to explore different shipping chain configurations used by decision makers (business establishments) was done. Also, a system of hierarchical database models of shipping chain choice for freight transportation was presented. A system of decision tree models was proposed to determine the shipping chain configuration of freight transportation by identifying number of stops and type of stops per chain. The results of the survey were used for analysis and model estimation. The proposed decision tree models were developed by using 80% of the observations in the data, and the remaining 20% were used to validate the models. The results of model estimation indicated that shipments’ attributes were the most significant variables in predicting the configuration of the shipping chain. The results of the validation showed that the estimated trees could predict the shipping chain configuration for the test data with an acceptable precision, which confirmed that decision tree models were powerful tools that could be used to predict shipping chain configurations of freight flows.

Recursive Stochastic Choice

We characterize two sorts of stochastic choice rules in which the agent makes current decisions using a forward-looking value function that takes future randomizations into account. Both sorts of rules generalize logistic choice, and are equivalent to it in static problems. The rules differ in how the agent views future choice sets and how he views his future randomizations. One rule is equivalent to the discounted logit used in applied work, and exhibits a “preference for flexibility;” the other is “error-averse” and penalizes the addition of undesirable choices to a menu.

Dynamic Network Logistic Regression: A Logistic Choice Analysis of Inter- and Intra-Group Blog Citation Dynamics in the 2004 US Presidential Election

Methods for analysis of network dynamics have seen great progress in the past decade. This article shows how Dynamic Network Logistic Regression techniques (a special case of the Temporal Exponential Random Graph Models) can be used to implement decision theoretic models for network dynamics in a panel data context. We also provide practical heuristics for model building and assessment. We illustrate the power of these techniques by applying them to a dynamic blog network sampled during the 2004 US presidential election cycle. This is a particularly interesting case because it marks the debut of Internet-based media such as blogs and social networking web sites as institutionally recognized features of the American political landscape. Using a longitudinal sample of all Democratic National Convention/Republican National Convention–designated blog citation networks, we are able to test the influence of various strategic, institutional, and balance-theoretic mechanisms as well as exogenous factors such as seasonality and political events on the propensity of blogs to cite one another over time. Using a combination of deviance-based model selection criteria and simulation-based model adequacy tests, we identify the combination of processes that best characterizes the choice behavior of the contending blogs.

Finitely Precise Dynamic Programming and Portfolio Choice

Using a standard lifetime savings and portfolio choice model with a logistic choice function, we demonstrate that the predictions of the infinitely precise model are not robust to the introduction of realistic levels of household imprecision. The predicted deviations from the optimal stock/bond allocation are large and biased towards bonds, which can help explain the equity-premium puzzle.

Comparation of logistic regression methods and discrete choice model in the selection of habitats

Based on a review of most recent data analyses on resource selection by animals as well as on recent suggestions that indicate the lack of an unified statistical theory that shows how resource selection can be detected and measured, the authors suggest that the concept of resource selection function (RSF) can be the base for the development of a theory. The revision of discrete choice models (DCM) is suggested as an approximation to estimate the RSF when the choice of animal or groups of animals involves different sets of available resource units. The definition of RSF requires that the resource which is being studied consists of discrete units. The statistical method often used to estimate the RSF is the logistic regression but DCM can also be used. The theory of DCM has been well developed for the analysis of data sets involving choices of products by humans, but it can also be applicable to the choice of habitat by animals, with some modifications. The comparison of the logistic regression with the DCM for one choice is made because the coefficient estimates of the logistic regression model include an intercept, which are not presented by the DCM. The objective of this work was to compare the estimates of the RSF obtained by applying the logistic regression and the DCM to the data set on habitat selection of the spotted owl (Strix occidentalis) in the north west of the United States.

GHG emissions of supply chains from different retail systems in Europe

An approach has been developed to collect data and measure energy use and GHG emissions from logistics activities for product supply chains. This approach has been used to assess the GHG efficiency of several supply chains of the same product marketed through different types of retail systems in Europe. The retail types considered are hyper and supermarkets, corner shops, open-air markets, producer's basket direct sale, farm shops and e-commerce; Their GHG efficiencies are quantified and compared for food products, considering whole supply chains from the farm gate where they are grown to the consumer's home. This supply chain efficiency approach highlights the importance of the various operations carried out within the supply chains, such as transport, warehousing, the shop itself, and even consumer behaviour for the last mile. While supermarkets in towns, shops included in a delivery system, or open air markets in town centre appears to be very efficient, rural area and independent shops with lower turnover are less favourable. Indeed, the outcomes of an online consumer survey show large differences amongst the GHG efficiency values for all these retail systems. Therefore, potential logistics choices for improving the supply chain performance could be identified.

A micro-simulation model of shipment size and transport chain choice

Practically every international, national or regional freight transport model system in the world lacks explicit treatment of logistics choices (such as shipment size considerations or the use of distribution centres). This paper deals with the development of a new logistics model and its application within the national freight model systems of Norway and Sweden. This logistics model operates at the level of individual firm-to-firm (sender-to-receiver) relations and simulates the choice of shipment size and transport chain for all (several millions) these relations within the country, export and import. A logistics model with deterministic cost minimisation has been constructed for both Norway and Sweden. The full random utility logistics model has not yet been estimated on disaggregate data, but this is planned for both countries. For Sweden, more limited disaggregate models for the choice of mode and shipment size have been estimated.

College Students' Choice Modeling of Taking On-Line International Business Courses

To understand students' choice behavior of taking on-line international business courses, a survey study is conducted to collect information regarding students' actual choices of taking on-line courses and potential factors that may have impacts on students' choices of online learning. Potential factors such as enrollment status, demographic background, maturity level, and supportive technology are extracted from published research studies. A sample of one hundred and fifty-five observations is then used to build a logistics choice model. The choice model confirms six of the considered factors have statistically significant impacts on students' choice of taking on-line international business courses. The findings from modeling students' choice behavior are used to test hypotheses and quantify the comparative factor impacts over the choice behavior. In addition to gain understanding of our students' choices of taking on-line courses, we like to share our data analysis findings and modeling results with other colleges, especially the ones that are evaluating the potentials of this modern learning mode for their courses.

Temperament and friendship in preschool-aged children

The influence of three components of temperament (activity level, impulsivity, and soothability) on children's friendships was investigated. Children (40 girls, 35 boys) aged 43 to 69 months responded to a sociometric interview and teachers provided temperament ratings. The probability of children choosing particular classmates as friends was evaluated based on the genders and temperaments of the dyad. A logistic choice model revealed that the choice of friends is highly influenced by gender, high impulsivity, and high soothability. Furthermore, the gender of the chooser and the activity level of the friend interacted such that girls chose low activity level friends and boys chose high activity level friends. In addition, the likelihood of a child being chosen as a friend based on gender and temperament was significantly correlated with popularity for girls, but not for boys.

Temperament and friendship in preschool-aged children

The influence of three components of temperament (activity level, impulsivity, and soothability) on children's friendships was investigated. Children (40 girls, 35 boys) aged 43 to 69 months responded to a sociometric interview and teachers provided temperament ratings. The probability of children choosing particular classmates as friends was evaluated based on the genders and temperaments of the dyad. A logistic choice model revealed that the choice of friends is highly influenced by gender, high impulsivity, and high soothability. Furthermore, the gender of the chooser and the activity level of the friend interacted such that girls chose low activity level friends and boys chose high activity level friends. In addition, the likelihood of a child being chosen as a friend based on gender and temperament was significantly correlated with popularity for girls, but not for boys.

Cox-McFadden Partial and Marginal Likelihoods for the Proportional Hazard Model with Random Effects

In survival analysis, Cox's name is associated with the partial likelihood technique that allows consistent estimation of proportional hazard scale parameters without specifying a duration dependence baseline. In discrete choice analysis, McFadden's name is associated with the generalized extreme-value (GEV) class of logistic choice models that relax the independence of irrelevant alternatives assumption. This paper shows that the mixed class of proportional hazard specifications allowing consistent estimation of scale and mixing parameters using partial likelihood is isomorphic to the GEV class. Independent censoring is allowed and I discuss approximations to the partial likelihood in the presence of ties. Finally, the partial likelihood score vector can be used to construct log-rank tests that do not require the independence of observations involved.

The Determinants of Convention Site Selection: A Logistic Choice Model from Experimental Data

One of the most attractive segments of the travel and tourism market is the meetings and conventions sector. Convention and visitor bureaus (CVBs) covet this important visitor group to compete for a share of the spoils this segment now represents. But very little is known about the factors that determine how the site for a convention is chosen from among the many different alternative host destinations available. Consequently, CVBs and other destination management organizations (DMOs) lack adequate knowledge for competitive action. This study reports the results from a stated choice experiment on the Australian domestic conventions industry. It provides statistical evidence of the determinant site attributes that influence the choice of convention site and finds that although convention facility and accommodation factors are critical, a destination must offer additional features to compete effectively. The study also demonstrates the application of stated choice modeling for assessing the utility of each choice attribute.

How have college decisions changed over time? An application of the conditional logistic choice model

This paper examines how individuals from 1972, 1982, and 1992 chose whether and where to attend college by estimating the importance of postsecondary costs and quality. Using the conditional logistic choice model to exploit extensive match-specific information between individuals and colleges and include the thousands of alternatives available to prospective students, the paper is able to approximate an individual's college outlook as never before. The results suggest that although tuition price was an important determinant of attendance for the class of 1972, college costs do not explain differences in enrollment for the class of 1992. However, price is still found to be an important factor when individuals choose between colleges, particularly among low-income students. Additionally, college quality has become a more important factor in college decisions.

Does the Format of a Financial Aid Program Matter? The Effect of State In-Kind Tuition Subsidies

This paper examines the importance of format in aid programs, focusing on state appropriations to public postsecondary institutions. These funds subsidize costs for in-state students, but they may also influence choices between institutions due to their in-kind format. Using the conditional logistic choice model and extensive match-specific information, the paper approximates the choice between nearly 2700 college options to examine the effect of several dissimilar state systems. The results suggest that the level and distribution pattern of subsidies strongly affect decisions. If the aid could instead be applied to any in-state college, up to 29% more students would prefer to attend private four-year colleges.

Perfect value and outlier detection in logistic binary choice models

Tins paper discussed some diagnostic tools for logistics binary choice models using techniques based on perfect values. The concept of perfect value fit is defined for logistic models in an analogous approach used when dealing with non ignorable non-iespouse in contingency tables. Performance ol outlier diagnostics based on perfect values is illustrated on a set of data on incidents in pre-Challenger launches.

Third Party Logistics Choice

Logistics managers were surveyed regarding decisions (1) to use third party logistics services and (2) practices regarding the selection of third party providers. Responses suggest that decisions to use third party logistics services are not driven by strong preconceptions, pro or con, regarding the attractiveness of the third party option. Further, attitudes toward the use of third party logistics services are not greatly affected by the firm's competitive responsiveness strategy or its perceived external environment. When a decision has been made to use third party providers, a wide range of performance oriented selection criteria are important. But, price considerations are important only after performance criteria have been met, and both the firm's competitive responsiveness strategy and external environment affect the selection criteria. It was concluded that selection criteria were much more affected by performance issues rather than cost issues. Implications for logistics service providers, users, teachers, and researchers are presented.

Cost-Effective Transport Choices for Wholesaler-Distributors Using Transport Probability Analysis

Logistics choices will have an increasingly larger impact on wholesaler-distributors. Transportation costs must be balanced against inventory and stock-out costs within service contraints to achieve optimum mode choice. Transport Probability Analysis (TPA), a method which can be used effectively by wholesaler-distributors to acheive and to monitor this balanace, is brifly described. A summary and results of a study conducted at Alfred University which compares the cost effectiveness of two competing modes of transportation: truck and piggyback are presented. The study used TPA and computer simulation to compare costs associated with buffer stock, stock-outs, and holding costs. Results contradict preconceived notions that trucks are always superior to rail in terms of cost-effectiveness and flexibility, showing increasing cost savings for piggyback service for longer distances.

An Empirical Comparison of Conditional and Marginal Likelihood Methods in a Longitudinal Study

A derivation of a logistic choice model suggests the importance of omitted variables, which may be tackled using either conditional or marginal likelihood methods. The two approaches seem to give different results when applied to data from the Michigan Panel Study of Income Dynamics. Reasons for these discrepant results are explored by examining the correlation of included and omitted effects, the distributionlal form of those omitted effects, and the consequences of endogenous variables among the covariates.

Implications of Cost-Service Trade-offs on Industry Logistics Structures

The characteristics of the technology and markets within an industry will affect the range of logistics systems observed in that industry. In some industries the range is wide, while in others all firms make the same logistics choices. This paper explores these differences. We propose the concept of an efficient frontier of cost-service choices and show how firms align themselves along the frontier.