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This study aims to determine whether consumers are willing to pay a premium for locally produced hard apple cider and examine the factors influencing this premium. This study examines the influence of hard apple cider attributes and consumer characteristics on consumer preferences for local hard apple cider.

Data from a 2019 survey of 875 Tennessee consumers regarding their preferences for a local hard apple cider were obtained. Probit estimates were used to calculate the premium consumers were willing to pay for a locally made hard apple cider and factors influencing this premium. A multivariate probit was used to ascertain factors influencing the importance of attributes (e.g. heirloom apples, sweetness/dryness, sparking/still and no preservatives added) on local hard apple cider preference.

Consumers would pay a $3.22 premium for local hard apple cider compared with a $6.99 reference product. Local foods preferences, urbanization, weekly purchases of other alcoholic beverages and shopping venues influenced premium amounts. Other important attributes were sweetness/dryness and no preservatives. Influence of consumer demographics suggests targeted marketing of local ciders could be successful.

Few studies examine consumer preferences for hard apple ciders. This study represents a cross-sectional analysis of the premium consumers would pay for local hard apple ciders and the importance of other hard apple cider attributes.

The purpose of this paper is to examine the blockchain as a trusted computing platform. Understanding the strengths and limitations of this platform is essential to execute large-scale real-world applications in blockchains.

This paper proposes several modifications to conventional blockchain networks to improve the scale and scope of applications.

Simple modifications to cryptographic protocols for constructing blockchain ledgers, and digital signatures for authentication of transactions, are sufficient to realize a scalable blockchain platform.

The original contributions of this paper are concrete steps to overcome limitations of current blockchain networks.

This study aims to assess the effect of water variation on bioethanol production from cassava peels (CP) using Saccharomyces cerevisiae yeast as the ethanologenic agent.

The milled CP was divided into three treatment groups in a small-scale flask experiment where each 20 g CP was subjected to two-stage hydrolysis. Different amount of water was added to the fermentation process of CP. The fermented samples were collected every 24 h for various analyses.

The results of the fermentation revealed that the highest ethanol productivity and fermentation efficiency was obtained at 17.38 ± 0.30% and 0.139 ± 0.003 gL⁻¹ h⁻¹. The study affirmed that ethanol production was increased for the addition of water up to 35% for the CP hydrolysate process.

The finding of this study demonstrates that S. cerevisiae is the key player in industrial ethanol production among a variety of yeasts that produce ethanol through sugar fermentation. In order to design truly sustainable processes, it should be expanded to include a thorough analysis and the gradual scaling-up of this process to an industrial level.

This paper is an original research work dealing with bioethanol production from CP using S. cerevisiae microbe.

1. Hydrolysis of cassava peels using 13.1 M H₂SO₄ at 100 ^oC for 110 min gave high Glucose productivity

2. Highest ethanol production was obtained at 72 h of fermentation using Saccharomyces cerevisiae

3. Optimal bioethanol concentration and yield were obtained at a hydration level of 35% agitation

4. Highest ethanol productivity and fermentation efficiency were 17.3%, 0.139 g.L⁻¹.h⁻¹

Hydrolysis of cassava peels using 13.1 M H₂SO₄ at 100 ^oC for 110 min gave high Glucose productivity

Highest ethanol production was obtained at 72 h of fermentation using Saccharomyces cerevisiae

Optimal bioethanol concentration and yield were obtained at a hydration level of 35% agitation

Highest ethanol productivity and fermentation efficiency were 17.3%, 0.139 g.L⁻¹.h⁻¹

China is not only the biggest importing country of the raw materials of forest products, but also the biggest exporting country of intermediate and final forest products. The paper aims to discuss these issues.

The authors use the Khandelwal (2010) method and trade data from 2000 to 2014 of bilateral forest products between China and ten main developed countries to evaluate the quality of China’s forestry imports and exports. Subsequently, the influencing factors of product quality are analyzed.

The results show that the current export quality of plywood and fiberboard is decreasing, and the export quality of particleboard and paper products is on the rise. A further study finds that several factors have the positive effects on the quality of forestry exports, including gross domestic product of the importing country, forestry export value of the importing country as well as the number of forestry higher education graduates of the exporting country. Moreover, the study also finds that the status of an Asia-Pacific Economic Cooperation member has a negative effect on the quality of forestry exports, while the distance cost has a negative influence on fiberboard, paper and paperboard.

The study suggests that China needs to strengthen the research and development investment on forest products, and improve the quality of forest products to promote the trade development of forestry exports.

The existing literature has not shown much research regarding the quality of China’s forestry exports through econometric analysis. Therefore, the research results provide new perspective about the influencing factors on China’s forestry trade activities.

This article summarizes the international scientific research output of global forest product models, infers future research trends and provides reference for quantitative analysis and mathematical modeling of Chinese forest product problems, with the aim of contributing to promoting domestic production of Chinese forest products and strengthening international trade competitiveness of forest products.

In 1999, Joseph Buongiorno, a scholar at the University of Wisconsin in the United States of America, proposed the global forest products model (GFPM), which was first applied to research in the global forestry sector. GFPM is a recursive dynamic model based on five assumptions: macroeconomics, local equilibrium, dynamic equilibrium, forest product conversion flow and trade inertia. Using a certain year from 1992 to present as the base period, it simulates and predicts changes in prices, production and import and export trade indicators of 14 forest products in 180 countries (regions) through computer programs. Its advantages lie in covering a wide range of countries and a wide variety of forest products. The data mainly include forest resource data, forest product trade data, and other economic data required by the model, sourced from the Food and Agriculture Organization (FAO) of the United Nations and the World Bank, respectively.

Compared to international quantitative and modeling research in the field of forest product production and trade, China's related research is not comprehensive and in-depth, and there is not much quantitative and mathematical modeling research, resulting in a significant gap. This article summarizes the international scientific research output of global forest product models, infers future research trends, and provides reference for quantitative analysis and mathematical modeling of Chinese forest product problems, with the aim of contributing to promoting domestic production of Chinese forest products and strengthening international trade competitiveness of forest products.

On the basis of summarizing and analyzing the international scientific research output of GFPM, sorting out the current research status and progress at home and abroad, this article discusses potential research expansion directions in 10 aspects, including the types, yield and quality of domestic forest product production, international trade of forest products, and external impacts on the forestry system, in order to provide new ideas for global forest product model research in China.

The purpose of this study is to analyze the influence of social capital on human capital; the effect of social capital on transaction costs; the influence of social capital, human capital and transaction costs on empowerment; the indirect effect of social capital on empowerment through human capital; and the indirect effect of social capital on empowerment through transaction costs in Bangli Regency.

The population in this research is all wood carving business in Bangli Regency, in all districts some 366 business units. The number of respondents surveyed were 191 business units in all sub-districts. The sampling technique used is stratified random sampling, with strata of business area. Inferential analysis is preceded by using factor analysis techniques to obtain factor scores on each latent variable, followed by path analysis to answer the research objectives.

Based on the analysis, the following conclusions are drawn: social capital has a positive and significant impact on human resources; positive social capital and significant positive to transaction costs; social capital and human resources have a positive and significant effect while transaction costs and no significant positive effect on empowerment; human resources partially mediate the influence of social capital on empowerment; and transaction costs do not act as a variable, mediating the influence of social capital on empowering small woodcraft industry in Bangli Regency.

This study is one of the few to investigate the role of social capital, human capital and transaction cost on empowerment of small industries, especially wood carving in Bangli District. This small woodcraft industry is famous for its uniqueness that characterizes Balinese carving ornaments. But lately, the productivity of handicrafts wood carving, especially in Bangli District, fluctuates tend to decline. Social capital, in addition to human capital and technology, also plays an important role in the production process. Social capital equals other physical capital and can increase productivity and economic efficiency. Higher social capital owned by individuals or groups can reduce transaction costs; thus economic activity can run efficiently. Social capital is the information, trust and norms of reciprocity inherent in social networks.

Timber export is an important economic development pillar in Ghana, which has a direct effect on Ghana’s domestic forestry industry development, local communities’ income and sustainable forest management and deforestation. China, as the Ghana’s largest timber export destination, brought significant impacts on Ghana’s timber export. However, there is a lack of quantitative analyses on impact factors of timber trade between the two countries in the past, which this paper sought to do.

The authors first collected Ghana’s timber exports to China from 1997 to 2017, and then based on the literature review and trade theories, the authors set up a least squares estimate (LSE)-based multiple linear regression (MLR) model to analyse the specific impact factors. In addition, multi-collinearity, autocorrelation and heteroscedasticity issues of the impact factors were checked to guarantee the accuracy of the results.

The results showed China timber import volume, Ghana cedi (GHC)/US$ exchange rate, Ghana’s gross domestic product (GDP) and China timber consumption volume in construction sector had positive impacts; Ghana timber production volume and Ghana average timber export price had negative impacts. The results confirmed that China’s timber consumption had a positive linkage with Ghana’s timber export. The article also reviewed possible impacts caused by change in timber trade policies, which proved important but was hardly directly quantified. The authors pointed out the importance of optimizing these impact factors to make sure Ghana’s timber export to China went on the sustainable track.

There is no literature about timber trade and its impact factors between Ghana and China, which used econometric models. This paper provided new perspectives on the impact factors in timber trade between the two countries.

The goal of the paper is to examine the dynamics between innovation, market structure and trade performance. Firstly, the author first investigates the effects of innovation on trade performance. Secondly, the author then examines how market structure affect trade by classifying industries based on their innovation intensity.

The author uses a detailed level data set of eight OECD countries in a panel of 17 industries from the STAN and ANBERD Database. The author employs both a pooled regression and a two-stage quantile regression analysis. The author first investigates the effects of innovation at the aggregate level, and then the author assesses the effects at the disaggregated or firm level.

The author finds that at the aggregate level, innovation and market size have a positive and significant effect on competitivity in most of the specifications. However, innovation is negatively associated with trade performance in the case of bilateral trade between Spain and the Netherlands. Also, the sectoral analysis provides evidence that the innovation-trade nexus depends on technological classification. The author shows that: (1) the effect of innovation activity on trade performance economic performance is lower for the high technology and high concentration (HTHC) market compared to the low technology (LT) market; (2) the impact of innovation on economic performance is ambiguous for firms in the high technology and low concentration (HTLC) market.

Although the database provides a rich data set on industrial data, it fails to provide innovation output such as patent data which may underestimate the innovation activities of firms that do not have a separate R&D records. In the current context of subdue economic growth these research results have important policy implications. Firstly, the positive impact of innovation on trade performance strengthens its role for sustainable development. The negative coefficient on innovation is an indication that research intensity in some cases has not been able to create a new demand capable to boost economic performance.

The market classification analysis provides new evidence that innovation in the LT market has the potential to enhance competition. Secondly, market size supports industries that are competing in the international market. Policy makers must therefore put in place incentives to encourage firms to grow in size if they want to remain globally competitive.

Sustainable development can be supported through investment in research and development in the low technology sector.

The study is the first as far as the author knows, to examine the impact of innovation on bilateral trade performance using industry level data from OECD countries. Secondly, the author complements the existing literature by examining how innovation activities (classified as high technological intensive or low technological intensive) affect trade performance.

本研究擬探討創新觀念、市場結構和貿易表現之間的相互變革動力關係。我們首先研究創新觀念對貿易表現的影響,繼而探討市場結構對貿易表現的影響。根據各個行業的創新觀念強度,我們把行業分為不同類別。我們採用八個經濟合作暨發展組織國家的詳細級數據庫,而這八個國家、乃是STAN and ANBERD 數據庫內一個包括17個行業組別內的國家。我們採用混合估計和兩階段分位數回歸分析; 我們首先探討創新觀念所帶來的整體影響,繼而評估細分層面 (即公司層面) 上的影響。我們發現、在整體的層面上,創新觀念和市場規模、在我們大部份的規格上,均對競爭力帶來積極和重要的影響。唯在西班牙與荷蘭兩國之間的雙邊貿易上,創新觀念與貿易表現卻出現負相關的情況。而且,行業分析證實創新與貿易的關係是取決於技術分類的。我們的研究顯示:(1) 與低技術市場相比,於高技術、高集中程度的市場,創新觀念的活動對貿易表現和經濟表現的影響會較低; (2) 對處於高技術、低集中程度市場的公司而言、創新觀念對經濟表現的影響是不明確的。雖然該數據庫在工業數據方面提供一個豐富的數據集,卻未能提供如專利數據等的創新產出,這可能會導致沒有單獨研發記錄公司的創新觀念活動會被低估的情況。在現時經濟成長受到壓制的環境下,這些研究結果提供重要的政策啟示; 首先,創新觀念對貿易表現的積極影響增強了它在可持續發展方面所扮演的角色。創新觀念上的負系數顯示、在某些情況下,研究強度未能創造一個可提高經濟表現的新需求。市場分類分析提供新的證據、證明在低技術市場,創新觀念有提高競爭力的潛力; 其次,市場規模為於國際市場競爭的行業提供支援; 因此,政策制定者必須提供誘因、以鼓勵希望繼續具有全球競爭力的公司擴大其規模。