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This paper aims to develop a bi-objective mixed integer non-linear programing model to optimize the supply chain networks consisting of raw material providers, final product manufacturers and distribution centers. Raw material substitution caused by varying raw material supply amounts, prices and carbon emissions and final product substitution due to different product prices and carbon emissions are considered.

The proposed model aims to achieve total profit maximization and total carbon emission minimization. The objective function of carbon emissions is converted into a maximization problem by changing minimum to maximum. The composite objective function is the weighted sum of the bias value of each objective function. The model is then solved using software Lingo12.

Numerical analysis results show that an increase in the number of alternate raw materials for original raw material helps improve supply chain network performance, and variation in that number causes detectable but not significant changes in downstream final product substitution results.

The major differences between this work and existing research are as follows: first, although previous research considered carbon emissions in supply chain network optimization, it has not considered the substitution effects of products or raw materials. This paper considers the substitution of both raw material and productions. Second, the item substitution considered by previous research is derived from inventory shortage or price difference of original items. However, the substitution considered in the present paper is a response to differences in purchase price, production cost and carbon emissions for items.

This study aims to explore the role of cultural distance, economic integration, price competitiveness and substitution prices for tourism arrivals between 10 Southeast Asian (ASEAN) countries and 22 other origin countries from 2007 to 2019.

A panel-data gravity model is applied to estimate tourism demand in the ASEAN region. An index of cultural distance (time-variant) is introduced to examine the role of cultural differences across bilateral partners. Moreover, relative prices and substitution prices are introduced to the gravity equation to estimate price elasticities. Finally, this study tested whether the ASEAN free trade agreements (FTAs) encourage intraregional tourism arrivals. Two-panel regression approaches are used to test the model.

Cultural distance positively affects tourism inflows, boosting foreign arrivals. Income and price elasticities are important determinants in the demand model for ASEAN. A gain in price competitiveness versus alternative destinations can lead to substitution in destination choice. Meanwhile, geographic distance has a negative impact on arrivals, suggesting that connectivity and transportation are key in boosting tourism inflows in ASEAN. A decline in the disposable incomes of tourists caused by the COVID-19 pandemic may reduce tourism arrivals in the region. However, when currencies in ASEAN weaken, and consumer prices are lower than in other destinations, arrivals in ASEAN will be stimulated. FTAs have facilitated travel intra-ASEAN, which is an advantage over the extra-ASEAN sector.

Cultural heritage could be used in tourism promotion as ASEAN can attract tourists seeking novelty and new excitements. ASEAN countries could create complementary destinations and jointly promote cultural heritage to accelerate the region’s recovery. The depreciation of currencies in ASEAN and the gain in relative price competitiveness could attract more tourist visits, helping the region reestablish tourism activities in a postpandemic economy.

The model accounts for three key variables in the gravity approach: cultural distance in ASEAN tourism inflows, the effects of the ASEAN economic community on intraregional tourism, and relative and alternative price competitiveness. This study enriches the literature about tourism-demand approaches in modeling tourism arrivals.

Carbon emission is a significant issue for the current business market and global warming. Nowadays, most countries have focused to reduce the environmental impact of business with durable financial benefits. The purpose of this study is to optimize the entire cost functions with carbon emission and to find the sustainable optimal ordering quantity for retailers.

This paper illustrates a sustainable inventory model having a set of two non-instantaneous substitutable deteriorating items under joint replenishment with carbon emission. In this model demand and deterioration rate are considered as deterministic, constant and triangular fuzzy numbers. The objective is to find the optimal ordering quantity for retailers and to minimize the total cost function per unit time with carbon emission. The model is then solved with the help of Maple software.

This paper presents a solution method and also develop an algorithm to determine the order quantities which optimize the total cost function. A numerical experiment illustrates the improvement in optimal total cost of the inventory model with substitution over without substitution. The graphical results show the convexity of the cost function. Finally, sensitivity analysis is given to get the impact of parameters and validity of the model.

This study considers a set of two non-instantaneous substitutable deteriorating items under joint replenishment with carbon emission. From the literature review, in the authors’ knowledge no researcher has undergone this kind of study.

Over the past decade, biofuels production in the European Union and the United States has boomed – much of this due to government mandates and subsidies. The United States has now surpassed Brazil as the world's leading producer of ethanol. The economic and environmental impact of these biofuel programs has become an important question of public policy. Due to the complex intersectoral linkages between biofuels and crops, livestock as well as energy activities, CGE modeling has become an important tool for their analysis. This chapter reviews recent developments in this area of economic analysis and suggests directions for future research.

By “social economy” I understand a revised approach to economic science which underpins its work by incorporating values from social philosophy to re‐interpret and re‐direct an important part of its positive enquiries. It is, if you prefer, an extended version of what some call “political economy”; but I do have in mind a re‐fashioning of economic science and not merely a meeting ground with political and social values. The foundations of economics need to be revised, if political and social economy are to consist of something other than informal encounters with values. Of course, many prefer to speak instead of “social economics” as an extension of economic science to deal with the more obviously social areas of economic enquiry while incorporating humanistic values. I respect this approach and accept entirely the importance of these enquiries, but have always felt that a more radical correction of the weak posture of economic science before our present social problems is essential to tackle them properly.

The purpose of this paper is to analyze price transmission in the Chinese pork market between 1994 and 2016 and examine any incidence and causes of asymmetric price transmission.

The approach uses threshold autoregressive models, asymmetric error correction models and autoregressive moving average models to examine the price transmission using monthly pig and pork prices from 1994 to 2016.

While a symmetric price transmission between pork and pig prices was identified for the period between June 1994 and June 2007, an asymmetric price transmission response between pork and pig prices was found for the period July 2007 to June 2016. Key factors behind the asymmetric price transmission include the chicken price and China’s provisional purchasing and stockpiling policy which is having a counter-productive impact on prices.

The paper contributes to the literature by examining price transmission in two different periods: 1994 to 2007 where prices are lower and more stable; and 2007 to 2016 where prices are higher and volatile. The paper examines the impact of production and market policies on price transmission in the Chinese pork and pig market, with several policy implications.

This study aims to measure the relationship between demand and exchange rate shocks in the tourism industry.

A panel data set is constructed covering the period between 1995 and 2017, and the data set includes the top 26 countries that host 10 million tourists and above in the world as of 2017. The standard errors of the series are used as an indicator of shocks. First, the cross-sectional dependency, stationarity and the homogeneity of the series are examined; second, a panel cointegration analysis is implemented; third, long-term panel cointegration coefficients are analyzed with Dynamic Common Correlated Effects (DCCE) approach; and, finally, Dumitrescu and Hurlin’s (2012) Granger non-causality test is used to detect the causality.

The preliminary analyses show that the variables are cross-sectional dependent and heterogeneous and are stationary in their first difference; hence, the effects of the shocks are temporary. On the other hand, as a result of the panel cointegration analysis, it is found that both series are cointegrated over the long-term. However, the long-term coefficients estimated with the DCCE approach are found not to be statistically significant. Finally, as a result of the Dumitrescu and Hurlin’s (2012) Granger non-causality test, it is concluded that there is a causality running from exchange rate shocks to demand shocks.

To the best of the authors’ knowledge, the cointegration between the tourism demand shocks and exchange rates shocks has not been investigated before, and therefore, this study is considered to be a pioneering study that will contribute to the literature.

This paper aims to compare and analyze the effect of the dual-credit policy and product substitution rate on the automakers’ operational strategies under different production modes (e.g. centralized and independent), and further illustrate which production mode is more conducive to improving new energy vehicle (NEV) development.

The decision-making models for a centralized production mode where an integrated automaker produces both NEVs and fuel vehicles (FVs) and for independent production mode where an NEV automaker faces competition from a traditional FV automaker were formulated. The equilibrium solutions of each production mode were obtained by extreme value and game theory methods. The conclusions of the theoretical analysis were further verified with numerical analyses using IBM-MATLAB R2019a. Some management insights could be obtained by comparison analysis.

Under the dual-credit policy, an increase in the NEV credit trading price will always raise production quantity of NEVs, but only in an independent production mode where a higher trading price will also bring higher total profits to NEV automakers. In addition, only when the NEV credit trading price is high enough, a rising product substitution rate will be more favorable to NEV production and restrain FV production. Furthermore, an independent production mode is more favorable for the initial production of NEVs, but as each of the two vehicle types captures a certain amount of market share, a centralized production mode will be more conducive to the full replacement of FVs by NEVs.

The main contributions of this study include the formulation of decision-making models for FVs and NEVs in not only a centralized production mode but also an independent production mode. Moreover, this paper comprehensively analyzes how the dual-credit policy and product substitution relationship affect automakers’ production and pricing decisions. Then, the specific conditions under which each production mode is more conducive to NEV production and sales are summarized. The results proposed in this study provide scientific managerial insights for automakers and policy makers.

To develop a framework for systematically defining the relevant market for intermediate goods that incorporates downstream market conditions.

We combine the well-established “Hicks-Marshall” conditions of derived demand for inputs with “critical loss/critical elasticity of demand” to yield insights into the definition of antitrust markets for intermediate goods and the competitive effects from a merger.

We show that examining “Hicks-Marshall” conditions can provide a more rigorous framework for analyzing relevant markets for intermediate goods. We also show that solely examining demand substitution possibilities for direct customers of an input can lead to an incorrect market definition.

Our framework may be difficult to apply in circumstances when several different downstream products use the input being examined and each of those downstream products has a different elasticity of demand.

We illustrate how reasonable ranges for key parameters relating to the ability of firms to substitute to other inputs and to adjust to downstream market conditions will often be sufficient to define antitrust markets for intermediate goods in practice.

Previous antitrust analysis has not systematically analyzed the impact of downstream market conditions in assessing market definition for intermediate goods. The framework we develop will be useful to future researchers attempting to define relevant markets for intermediate goods and evaluating the competitive effects of a merger.