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We study firms that sell multiple substitutable products and customers whose purchase behavior follows a nested logit model, of which the multinomial logit model is a special case. Customers make purchasing decisions sequentially under the nested logit model: they first select a nest of products and subsequently purchase one within the selected nest. We consider the multiproduct pricing problem under the general nested logit model with product-differentiated price sensitivities and arbitrary nest coefficients. We show that the adjusted markup , defined as price minus cost minus the reciprocal of price sensitivity, is constant for all the products within a nest at optimality. This reduces the problem's dimension to a single variable per nest. We also show that the adjusted nest-level markup is nest invariant for all the nests, which further reduces the problem to maximizing a single-variable unimodal function under mild conditions. We also use this result to simplify the oligopolistic multiproduct price competition and characterize the Nash equilibrium. We also consider more general attraction functions that include the linear utility and the multiplicative competitive interaction models as special cases, and we show that similar techniques can be used to significantly simplify the corresponding pricing problems.

We study assortment optimization problems where customer choices are governed by the nested logit model and there are constraints on the set of products offered in each nest. Under the nested logit model, the products are organized in nests. Each product in each nest has a fixed revenue associated with it. The goal is to find a feasible set of products, i.e., a feasible assortment, to maximize the expected revenue per customer. We consider cardinality and space constraints on the offered assortment, which limit the number of products and the total space consumption of the products offered in each nest, respectively. We show that the optimal assortment under cardinality constraints can be obtained efficiently by solving a linear program. The assortment optimization problem under space constraints is NP-hard. We show how to obtain an assortment with a performance guarantee of 2 under space constraints. This assortment also provides a performance guarantee of 1/(1- ) when the space requirement of each product is at most a fraction of the space availability in each nest. Building on our results for constrained assortment optimization, we show that we can efficiently solve joint assortment optimization and pricing problems under the nested logit model, where we choose the assortment of products to offer to customers, as well as the prices of the offered products. Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2014.1931 . This paper was accepted by Dimitris Bertsimas, optimization.

The currently available transport modeling tools are used to evaluate the effects of behavior change. The aim of this study is to analyze the interaction between the transport mode choice and travel behavior of an individual—more specifically, to identify which of the variables has the greatest effect on mode choice. This is realized by using a multinomial logit model (MNL) and a nested logit model (NL) based on a utility function. The utility function contains activity characteristics, trip characteristics including travel cost, travel time, the distance between activity place, and the individual characteristics to calculate the maximum utility of the mode choice. The variables in the proposed model are tested by using real observations in Budapest, Hungary as a case study. When analyzing the results, it was found that “Trip distance” variable was the most significant, followed by “Travel time” and “Activity purpose”. These parameters have to be mainly considered when elaborating urban traffic models and travel plans. The advantage of using the proposed logit models and utility function is the ability to identify the relationship among the travel behavior of an individual and the mode choice. With the results, it is possible to estimate the influence of the various variables on mode choice and identify the best mode based on the utility function.

Background The agricultural sector remains the main source of livelihoods for rural communities in Ethiopia, but faces the challenge of changing climate. This study investigated how smallholder farmers perceive climate change, what adaptation strategies they practice, and factors that influence their adaptation decisions. Both primary and secondary data were used for the study, and a multinomial logit model was employed to identify the factors that shape smallholder farmers’ adaptation strategies. Results The results show that 90% of farmers have already perceived climate variability, and 85% made attempts to adapt using practices like crop diversification, planting date adjustment, soil and water conservation and management, increasing the intensity of input use, integrating crop with livestock, and tree planting. The econometric model indicated that education, family size, gender, age, livestock ownership, farming experience, frequency of contact with extension agents, farm size, access to market, access to climate information and income were the key factors determining farmers’ choice of adaptation practice. Conclusion In the Central Rift Valley of Ethiopia, climate change is a pressing problem, which is beyond the capacity of smallholders to respond to autonomously. Farmers’ capacity to choose effective adaptation options is influenced by household demography, as well as positively by farm size, income, access to markets, access to climate information and extension, and livestock production. This implies the need to support the indigenous adaptation strategies of the smallholder farmers with a wide range of institutional, policy, and technology support; some of it targeted on smaller, poorer or female-headed households. Moreover, creating opportunities for non-farm income sources is important as this helps farmers to engage in those activities that are less sensitive to climate change. Furthermore, providing climate change information, extension services, and creating access to markets are crucial.

Understanding the influence factors and related causation of hazardous materials can improve hazardous materials drivers’ safety awareness and help traffic professionals to develop effective countermeasures. This study investigates the statistical distribution characteristics, such as types of hazardous materials transportation accidents, driver properties, vehicle properties, environmental properties, road properties. In total, 343 data regarding hazardous materials accidents were collected from the chemical accident information network of China. An ordered logit regression (OLR) model is proposed to account for the unobserved heterogeneity across observations. Four independent variables, such as hazardous materials drivers’ properties, vehicle properties, environmental properties, and road properties are employed based on the OLR model, an ordered multinomial logistic regression (MLR) is estimated the OLR model parameters. Both parameter estimates and odds ratio (OR) are employed to interpret the impact of influence factors on the severity of hazardous materials accidents. The model estimation results show that 10 factors such as violations, unsafe driving behaviors, vehicle faults, and so on are closely related to accidents severity of hazardous materials transportation. Furthermore, three enforcement countermeasures are proposed to prevent accidents when transporting hazardous materials.

Background Livelihood diversification plays a decisive role for the reduction of poverty, food insecurity and to improve the welfare of rural communities. However, inadequate research attention has been given to explore the determinants of livelihood diversification strategies in resettlement areas of Ethiopia. This study attempts to investigate determinants of livelihood diversification strategies among the resettler households in Chewaka district of Ethiopia. Methods The study utilized both primary and secondary data which are qualitative and quantitative in their nature. Through multistage sampling procedure, a total of 384 households were selected from seven sample kebeles of Chewaka district. Data were collected using interview schedule, focus group discussions and field observations. The collected data were analyzed quantitatively and qualitatively. Descriptive and inferential statistics along with multinomial logit model have been employed to analyze the data. Results The results showed that agriculture (43.2%), agriculture plus non-farm (25.5%), agriculture plus off-farm (19.3%) and a combination of agriculture plus non-farm plus off-farm (12%) activities are the most pertinent livelihood strategies in the study area. It was found that agriculture has a leading contribution to the total households’ income (72.5%) followed by non-farm (20%) and off-farm activities (7.5%). Multinomial logit model result revealed that land holding size, educational status, livestock holding, sex, age, market distance, credit access, annual income, access to training and household sizes were the major determinants of livelihood diversification strategies. Moreover, poor infrastructural development, lack of working capital, absence of technical support, inadequate skill training and lack of awareness are constraints to livelihood diversification in the area. Conclusions The study concludes that agricultural sector alone cannot be relied upon as the core activity for rural households and as a means of reducing poverty, achieving food security and improving livelihoods in the study area. Thus, a comprehensive development plan that enhances successful livelihood diversification is found to be imperative and most urgent. Policies and actions directed towards improving livelihood of the resettlers’ communities should focus on expanding rural infrastructures, enhancing awareness creation activities and cooperation of stakeholders to bring sustainable livelihood outcome in the area.

We investigate the relevance of dynamic variables that reflect the purchase history of a household as independent variables in multicategory choice models. To this end, we estimate both homogeneous and finite mixture variants of the multivariate logit model. We consider two types of dynamic variables. Variables of the first type, which previous publications on multicategory choice models have ignored, are exponentially smoothed category purchases, which we simply call category loyalties. Variables of the second type are log-transformed times since the last purchase of any category. Our results clearly show that adding dynamic variables improves statistical model performance with category loyalties being more important than log-transformed times. The majority of coefficients of marketing variables (features, displays, and price reductions), pairwise category interactions, and cross-category relations differ between models either including or excluding dynamic variables. We also measure the effect of marketing variables on purchase probabilities of the same category (own effects) and on purchase probabilities of other categories (cross effects). This exercise demonstrates that the model without dynamic variables tends to overestimate own effects of marketing variables in many product categories. This positive omitted variable bias provides another explanation for the well-known problem of “overpromotion” in retailing.

This paper explores spatial substitution patterns using a choice experiment to estimate the non-market benefits of environmental quality improvements at different sites presented as labelled alternatives. We develop a novel modelling approach to estimate possible disproportional substitution patterns among these alternatives by including cross-effects in site-specific utility functions, combining mixed and universal logit models. The latter model allows for more flexibility in substitution patterns than random parameters and error-components in mixed logit models. The model is relevant to any discrete choice study that compares multiple sites that vary in their comparability and that may be perceived as (imperfect) substitutes. Applying the model in an empirical case study shows that accounting for cross-effects results in a better model fit. We discuss the validity of welfare estimates based on the inclusion of cross-effects. The results demonstrate the importance of accounting for substitution effects in spatial choice models with the aim to inform policy and decision-making.

Nowadays, concurrent attention to economic development and ecological issues is becoming an important trend. In this paper, we measure the eco-efficiency of 285 Chinese cities from 2003 to 2019 using a non-radial directional distance function and the data envelopment analysis method, based on which we analyze the club convergence of cities’ eco-efficiency using the logt test; we estimate the impact of open public data platforms on eco-efficiency and its convergence using a multi-period difference in difference model and panel-ordered logit model, respectively. We find that, first, open public data platforms improve cities’ eco-efficiency by about 6.5%, and the impact mechanisms include scale efficiency, technical efficiency, and total factor productivity, or, at the micro level, increasing the economic agglomeration degree, boosting the amount of foreign investment used, and increasing green innovation level. Second, there are three convergence clubs of eco-efficiency in China’s cities, whose average eco-efficiency trends are above, close to, and below average, respectively. Third, public data platforms significantly increase the probability of cities belonging to the convergence clubs of high and medium eco-efficiency (Clubs 1 and 2) and decrease the probability of belonging to the low one (Club 3). However, the mechanisms only include technical efficiency and total factor productivity, or the amount of foreign investment used and the green innovation level at the micro level.

Background There is a dearth of studies focused on the impact of self-rated health on life satisfaction among large-bodied adolescents, as well as the moderating role of physical activity in this relationship. Large-bodied adolescents refers to young people (usually aged 10–19 years) whose body size falls within the overweight or obese range as defined by the World Health Organisation’s Growth Reference, based on age- and sex-specific body mass index (BMI) percentiles. This study aimed to address the gap in research by examining the association between self-rated health and life satisfaction in a diverse sample of large-bodied adolescents from 39 countries and regions in Europe and North America. The moderating role of physical activity in the association was also examined. Methods The study analysed data from the Health Behaviour in School-aged Children (HBSC) survey, involving a sample of 24,839 large-bodied adolescents. Three sequential binary mixed effects logit models were fitted: the first assessing self-rated health alone, the second adjusting for multiple covariates, and the third incorporating an interaction term between physical activity and self-rated health. The analysis was performed using R Software (v4.1.2), with significance determined at a level of 0.05. Results The results show that adolescents who rated their health as “poor” were a little more than six times (AOR = 6.32, 95%CI: 5.30–7.54, p  < 0.001) as likely to report lower life satisfaction compared to those who rated their health as “excellent”. Those who rated their health as “good” had 1.71 times higher odds (AOR = 1.71, 95%CI: 1.44–2.04, p  < 0.001) of reporting lower life satisfaction compared to those who rated their health as “excellent”. The analysis further indicated that physical activity plays a partial moderating role in the relationship between self-rated health and life satisfaction. Participants who considered themselves “somewhat active” reported higher life satisfaction compared to their “inactive” peers (AOR = 0.58, p  = 0.031, 95% CI: 0.36–0.95). Conclusions The study supports the hypothesis that poorer self-rated health is associated with lower life satisfaction among large-bodied adolescents. It further suggests that increased physical activity can ‘partly’ buffer the negative effects of poor self-rated health on life satisfaction. These findings emphasise the importance of interventions promoting physical activity and positive self-care to improve general well-being in large-bodied adolescents.