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The authors investigate the manufacturer's choice of discount schemes in a supply chain with competing retailers.

Using a game-theoretic model, the authors build two discount frameworks and compare and analyze the effects of different discount schemes on the performance of supply chain members.

The authors find that the retail price (market demand) in the quantity discount scheme is always higher (lower) than that in the market share discount scheme. The authors also find that the retailers' preference for discount schemes is antithetical to the manufacturer's preference in most cases. However, under certain conditions, there will be a win-win situation where Pareto-optimization occurs between the manufacturer and retailers when they choose the same discount scheme.

On the one hand, the authors assume that the two retailers are symmetrical in market size and operation efficiency. It would be interesting to study the effect of different discount schemes on retailers when the retailers have different market sizes or operating efficiency. On the other hand, the authors study the manufacturer's choice of discount schemes in a supply chain with one common manufacturer and two competing retailers. However, in practice, there exist other supply chain structures. Future research can examine the problem of choices of discount schemes in other different supply chain structures.

This paper help retailers and manufacturers to choose the best discount schemes.

This paper suggests that a high discount scale is not always beneficial (detrimental) to retailers (the manufacture).

The authors build two discount schemes (the quantity and the market share) in a supply chain consisting of one manufacturer and two retailers, and the authors focus on the effects of different discount schemes on the competition between two retailers. By comparing the two discount schemes, the authors study which discount scheme is the better choice for the manufacturer when facing competing retailers.

This study aims to examine the relationships between the different national culture dimensions presented by Hofstede and innovation data by country to analyze which characteristics of national culture dimensions contribute to the country becoming more innovative.

The study is characterized as descriptive and quantitative, using multiple linear regression equations as data analysis technique. To carry out the analysis, this study made use of secondary data from Hofstede’s national culture database, data on innovation indicators from the Global Innovation Index and population data from the World Bank database. The analysis comprises data from 2015 to 2018.

National culture affects innovation rates positively. The most favorable situation to boost innovation is when there is a low distance from power, high individualism, femininity characteristics, low aversion to uncertainty, long-term orientation and a higher level of indulgence.

The temporal analysis comprises a wider list of countries from all continents, which had not been considered in previous studies.

This study explores the characteristics of high-speed rail (HSR) and air transportation networks in China based on the weighted complex network approach. Previous related studies have largely implemented unweighted (binary) network analysis, or have constructed a weighted network, limited by unweighted centrality measures. This study applies weighted centrality measures (mean association [MA], triangle betweenness centrality [TBC], and weighted harmonic centrality [WHC]) to represent traffic dynamics in HSR and air transportation weighted networks, where nodes represent cities and links represent passenger traffic. The spatial distribution of centrality results is visualized by using ArcGIS 10.2. Moreover, we analyze the network robustness of HSR, air transportation, and multimodal networks by measuring weighted efficiency (WE) subjected to the highest weighted centrality node attacks. In the HSR network, centrality results show that cities with a higher MA are concentrated in the Yangtze River Delta and the Pearl River Delta; cities with a higher TBC are mostly provincial capitals or regional centers; and cities with a higher WHC are grouped in eastern and central regions. Furthermore, spatial differentiation of centrality results is found between HSR and air transportation networks. There is a little bit of difference in eastern cities; cities in the central region have complementary roles in HSR and air transportation networks, but air transport is still dominant in western cities. The robustness analysis results show that the multimodal network, which includes both airports and high-speed rail stations, has the best connectivity and shows robustness.

This paper discusses a case of truck sharing as an application of the sharing economy. This case study examines a real mixed feed company with multiple factories. In this company’s operation, bulk trucks located in a factory had not previously been shared for delivery with other factories to their pre-assigned customers of stock farms. Therefore, this paper suggests a new delivery system that facilitates truck-sharing and analyzes its effects on the transport cost and trucks’ CO₂ emissions. To this end, this paper develops vehicle routing models to represent the current delivery practice and the new truck-shared delivery (TSD). In addition, models are developed for a carbon control policy of an emission trading scheme (ETS) and the effects of the ETS on truck-sharing are investigated. Numerical analysis is conducted to identify the effects of the TSD and the carbon control policy and draw practical implications.

The immigrant entrepreneurship literature indicates that immigrant entrepreneurs reap numerous benefits from their co-ethnic communities℉ social capital. These benefits, however, often come at a price because scholars note the potential for this community social capital to impose limitations on the entrepreneurs. While the literature largely focuses on the benefits of social capital, there is no research on what motivates the immigrant entrepreneurs to engage with their co-ethnic community in terms of contributing to, and utilizing, their co-ethnic communities℉ social capital, and the consequences these may have on their enterprises. Addressing this gap in the literature is important in the development of successful immigrant enterprises. Thus, based on a model posited by Portes and Sensenbrenner (1993), we suggest that immigrant entrepreneurs℉ motivations will influence their use of, and contributions to, co-ethnic community social capital, impacting, in turn, business success. We contribute to both the immigrant entrepreneurship and social capital research through exploring how entrepreneurs℉ motives, with respect to their co-ethnic communities℉ social capital, influence business success.

Prior studies argue that social capital is vital for firm growth. Adding to this line of research, this paper provides more evidence regarding the contribution of bonding and bridging social ties to various aspects of small-l and medium-sized enterprise (SME) development. Building on the original data from Russia, this paper investigates the effects of firm-internal and firm-external relational ties on SME performance and geographic expansion. The findings indicate that horizontal bridging ties facilitate specific strategies of SME growth. Thus, this paper supports prior research conducted in the Asian context, and allows for extending the outcomes of bonding and bridging social capital into broader institutional settings. In addition, this study raises the question of relationship between the composition of social capital and distinct organizational characteristics of SMEs. Finally, the paper discusses the implications for future research, and outlines some practical recommendations for SMEs operating in emerging markets.

Esta investigación utiliza la Teoría Basada en Recursos como base para un modelo que permite integrar las acciones organizacionales con las variables que pueden moderar, directa o indirectamente, su impacto en el alto desempeño de los clubes de fútbol.

Se desarrolla una contrastación empírica en tres fases. La primera fue la técnica de regresión lineal. En segundo lugar, un análisis multivariado de covarianza (MANCOVA) y el tercer procedimiento, una regresión por mínimos cuadrados en dos fases. El objetivo de usar estos dos últimos procedimientos fue evaluar el efecto conjunto de las variables independientes sobre las variables dependientes, así como los efectos de interacción entre las mismas.

Se validan las relaciones, directas e indirectas, entre las variables organizacionales y decisionales previstas en el modelo. También se valida la importancia de las acciones promocionales del club, para lograr competitividad basada en su desempeño o resultados.

Investigaciones futuras se podrían replicar en otros países, usando muestras más grandes con técnicas estadísticas más complejas. También, se podría contrastar si las relaciones encontradas pueden variar según las culturas, o pueden usarse otras variables no contempladas en este estudio.

El cuestionario usado es una fuente de información fiable para los directivos de marketing de los clubes de fútbol, puesto que las escalas pueden ser usadas como guías para evaluar y diagnosticar su potencial de competitividad basada en el desempeño.

Los clubes de fútbol tienen un desarrollo e impacto directo en la sociedad. Por ello, las implicancias en el club recaerán en el entorno cercano (aficionados y sociedad) a este.

Esta investigación aporta varias contribuciones fundamentales a la literatura sobre la competitividad organizacional en el sector deportivo, con aplicación específica a los clubes de fútbol. Este es uno de los escasos estudios que muestran que la competitividad es el resultado de una dinámica motivacional y organizativa, y que el éxito de los clubes se basa en un fenómeno más complejo que solo la asistencia a los eventos. También, es una investigación en un país emergente, lo cual extiende la aplicabilidad teórica y práctica del fenómeno estudiado.

This paper analyzes two external costs often associated with port development, cost to fisheries from marine dredge disposal and damages from air pollution, using estimates of development and operation for a proposed (but since cancelled) container port as a case study. For dredge disposal, a bio-economic model was used to assess short- and long-term and indirect (joodweb) damages to fisheries from marine disposal of clean sediments. In the case of air pollution, estimates of annual activity levels and emission coefficients are used to estimate incremental annual emissions of three key pollutants (NOx, HC and CO) for trucks, trains, yard vehicles, and vessels. These estimates allow for phasing in of strict new air pollution regulations. For both external costs, sensitivity analyses are used to reflect uncertainty. Estimates of shadow values in year 2002 dollars amount from $0.094 per cubic yard to $0.169 per cubic yard of clean dredged material for the selected disposal site and from $0.0584 per mile (jor current control standards) to $ 0. 0023 per mile (after phasing in of new regulations) for air pollution from heavy trucks.

The measurement capabilities of the data envelopment analysis (DEA) models are used to train the artificial neural network (ANN) models for the best performance modeling of the sawmills in Ontario. The bootstrap DEA models measure robust technical efficiency scores and have benchmarking abilities, whereas the ANN models use abstract learning from a limited set of information and provide the predictive power.

The complementary modeling approaches of the DEA and the ANN provide an adaptive decision support tool for each sawmill.

The trained ANN models demonstrate promising results in predicting the relative efficiency scores and the optimal combination of the inputs and the outputs for three categories (large, medium and small) of sawmills in Ontario. The average absolute error in predicting the relative efficiency scores varies from 0.01 to 0.04, and the predicted optimal combination of the inputs (roundwood and employees) and the output (lumber) demonstrate that a large percentage of the sawmills shows less than 10% error in the prediction results.

The purpose of this study is to develop an integrated DEA-ANN model that can help in the continuous improvement and performance evaluations of the forest industry working under uncertain business environment.

This study aims to evaluate the network robustness of major Asian airlines and to explore which airport types have the greatest impact on robustness. We also analyze airports’ specific brokerage roles and their impacts on the robustness of the entire air route network. We select 10 major Asian full-service airlines that operate the main passenger terminals at the top-ranked hub airports in Asia. Data is collected from the Official Airline Guide passenger route dataset for 2017. The results of the network robustness analysis show that Air China and China Eastern Airlines have relatively high network robustness. In contrast, airlines with broader international coverage, such as Japan Airlines, Korean Air, and Singapore Airlines have higher network vulnerability. The measure of betweenness centrality has a greater impact on the robustness of air route networks than other centrality measures have. Furthermore, the brokerage role analysis shows that Chinese airports are more influential within China and Asia but are less influential globally when compared to other major hub airports in Asia. Incheon International Airport, Singapore Changi Airport, Hong Kong International Airport, and Narita International Airport play strong “liaison” roles. Among the brokerage roles, the liaison role has a greater impact on the robustness of air route networks.