• Management & Information Systems Review
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• v.35 no.3
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• pp.57-79
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• 2016

It is required to derive various conclusions by identifying the type of power and the relationship between SCMs and presenting practical implications. Thus, we can identify the differential effects of each type of power on SCM performance. We can contribute to develop the practical implications at more sophisticated multi-dimension by comparing results of this study with various SCM theories. Through previous studies, the source of power is largely divided into binding power and non-binding power. Binding power is classified into behavior coercion, binding reward and relationship legitimacy. Non-binding power is classified into work expertise, information superiority and value compliance. Enterprises should fully understand and recognize partners within supply chains including understanding of the source of power, imbalance and results. Thus, we look into types of power and effects on trust and commitment, and identify a causal relationship leading to collaboration and SCM performance. Specific research results are as follows. First, the binding power did not give a significant effect to the trust. However, the binding power gave a positively(+) significant effect to the commitment. Second, non-binding power showed a significant effect on both trust and commitment. As a result of analysis on total effects, it was shown that non-binding power gave indirect effects to collaboration and SCM performance. Third, it was shown that both trust and commitment significantly affected collaboration. From the perspectives of social exchange theory and trading cost theory among inter-organizational relationship theory, it may lead to SCM performance of trust, commitment and collaboration. Moreover, it was found that association of each attribute of power led to the significant result. Fourth, it was shown that trust and collaboration significantly affected SCM performance. However, commitment did not directly affect SCM performance, but it indirectly significantly affected SCM performance through collaboration. Proper use of this power can firmly build partnerships between members of the supply chain and induce the improvement on supply chain performance and satisfaction of members.

• Proceedings of the Korean Society of Crop Science Conference
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• 2019.09a
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• pp.5-5
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• 2019

The objectives of this paper are (i) to analyze past trends and future directions of rice production, consumption and trade across the world and (ii) to discuss emerging challenges and future directions in the global rice industry. Rice is a staple food of over half of the world's 7.7 billion people. It is an important economic, social, political, and cultural commodity in most Asian countries. Rice is the $1^{st}$ most widely consumed, $2^{nd}$ largely produced, and $3^{rd}$ most widely grown food crop in the world. It was cultivated by 144 million farms in over 100 countries with harvested area of over 163 million ha producing about 745 million tons paddy in 2018. About 90% of the total rice is produced in Asia. China and India, the biggest rice producers, account for over half of the world's rice production. Between 1960 and 2018, world rice production increased over threefold from 221 to 745 million tons (2.1% per year) due to area expansion from 120 to 163 million ha (0.5% per year) and paddy yield increase from 1.8 to 4.6 t/ha (1.6% per year). The Green Revolution led massive increase in rice production prevented famines, provided food for millions of people, reduced poverty and hunger, and improved livelihoods of millions of Asians. The future increase in rice production must come from yield increase as the scope for area expansion is limited. Rice is the most widely consumed food crop. The world's average per capita milled rice consumption is 64 kilograms providing 19% of daily calories. Asia accounted for 84% of global consumption followed by Africa (7%), South America (3%), and the Middle East (2%). Asia's per capita rice consumption is 100 kilograms per year providing 28% of daily calories. The global and Asian per capita consumption increased from the 1960s to the 1990s but stable afterward. The per capita rice consumption is expected to decline in Asia but increase outside Asia especially in Africa in the future. The total milled rice consumption was about 490 million tons in 2018 and projected to reach 550 million tons by 2030 and 590 million tons by 2040. Rice is thinly traded in international market because it is a highly protected commodity. Only about 9% of the total production is traded in global rice market. However, the volume of global rice trade has increased over six-fold from 7.5 to 46.5 million tons between the 1960s and 2018. A relatively small number of exporting countries interact with a large number of importing countries. The top five rice exporting countries are India, Thailand, Vietnam, Pakistan, and China accounting for 74% of the global rice export. The top five rice importing countries are China, Philippines, Nigeria, European Union and Saudi Arabia accounting for 26% of the global rice import. Within rice varieties, Japonica rice accounts for the highest share of the global rice trade (about 12%) followed by Basmati rice (about 10%). The high concentration of exports to a few countries makes international rice market vulnerable to supply disruptions in exporting countries, leading to higher world prices of rice. The export price of Thai 5% broken rice increased from 198 US$/ton in 2000 to 421 US$/ton in 2018. The volumes of trade and rice prices in the global market are expected to increase in the future. The major future challenges of the rice industry are increasing demand due to population growth, rising demand in Africa, economic growth and diet diversification, competition for natural resources (land and water), labor scarcity, climate change and natural hazards, poverty and inequality, hunger and malnutrition, urbanization, low income in rice farming, yield saturation, aging of farmers, feminization of agriculture, health and environmental concerns, improving value chains, and shifting donor priorities away from agriculture. At the same time, new opportunities are available due to access to new technologies, increased investment by the private sector, and increased global partnership. More investment in rice research and development is needed to develop and disseminate innovative technologies and practices to overcome problems and ensure food and nutrition security of the future population.

• Journal of Global Scholars of Marketing Science
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• v.17 no.2
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• pp.31-54
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• 2007

The exchange between buyers and sellers in the industrial market is changing from short-term to long-term relationships. Long-term relationships are governed mainly by formal contracts or informal agreements, but many scholars are now asserting that controlling relationship by using formal contracts under environmental dynamism is inappropriate. In this case, partners will depend on each other's flexibility or interdependence. The former, flexibility, provides a general frame of reference, order, and standards against which to guide and assess appropriate behavior in dynamic and ambiguous situations, thus motivating the value-oriented performance goals shared between partners. It is based on social sacrifices, which can potentially minimize any opportunistic behaviors. The later, interdependence, means that each firm possesses a high level of dependence in an dynamic channel relationship. When interdependence is high in magnitude and symmetric, each firm enjoys a high level of power and the bonds between the firms should be reasonably strong. Strong shared power is likely to promote commitment because of the common interests, attention, and support found in such channel relationships. This study deals with environmental dynamism in high-tech industry. Firms in the high-tech industry regard it as a key success factor to successfully cope with environmental changes. However, due to the lack of studies dealing with environmental dynamism and supply chain commitment in the high-tech industry, it is very difficult to find effective strategies to cope with them. This paper presents the results of an empirical study on the relationship between environmental dynamism and supply chain commitment in the high-tech industry. We examined the effects of consumer, competitor, and technological dynamism on supply chain commitment. Additionally, we examined the moderating effects of flexibility and dependence of supply chains. This study was confined to the type of high-tech industry which has the characteristics of rapid technology change and short product lifecycle. Flexibility among the firms of this industry, having the characteristic of hard and fast growth, is more important here than among any other industry. Thus, a variety of environmental dynamism can affect a supply chain relationship. The industries targeted industries were electronic parts, metal product, computer, electric machine, automobile, and medical precision manufacturing industries. Data was collected as follows. During the survey, the researchers managed to obtain the list of parts suppliers of 2 companies, N and L, with an international competitiveness in the mobile phone manufacturing industry; and of the suppliers in a business relationship with S company, a semiconductor manufacturing company. They were asked to respond to the survey via telephone and e-mail. During the two month period of February-April 2006, we were able to collect data from 44 companies. The respondents were restricted to direct dealing authorities and subcontractor company (the supplier) staff with at least three months of dealing experience with a manufacture (an industrial material buyer). The measurement validation procedures included scale reliability; discriminant and convergent validity were used to validate measures. Also, the reliability measurements traditionally employed, such as the Cronbach's alpha, were used. All the reliabilities were greater than.70. A series of exploratory factor analyses was conducted. We conducted confirmatory factor analyses to assess the validity of our measurements. A series of chi-square difference tests were conducted so that the discriminant validity could be ensured. For each pair, we estimated two models-an unconstrained model and a constrained model-and compared the two model fits. All these tests supported discriminant validity. Also, all items loaded significantly on their respective constructs, providing support for convergent validity. We then examined composite reliability and average variance extracted (AVE). The composite reliability of each construct was greater than.70. The AVE of each construct was greater than.50. According to the multiple regression analysis, customer dynamism had a negative effect and competitor dynamism had a positive effect on a supplier's commitment. In addition, flexibility and dependence had significant moderating effects on customer and competitor dynamism. On the other hand, all hypotheses about technological dynamism had no significant effects on commitment. In other words, technological dynamism had no direct effect on supplier's commitment and was not moderated by the flexibility and dependence of the supply chain. This study makes its contribution in the point of view that this is a rare study on environmental dynamism and supply chain commitment in the field of high-tech industry. Especially, this study verified the effects of three sectors of environmental dynamism on supplier's commitment. Also, it empirically tested how the effects were moderated by flexibility and dependence. The results showed that flexibility and interdependence had a role to strengthen supplier's commitment under environmental dynamism in high-tech industry. Thus relationship managers in high-tech industry should make supply chain relationship flexible and interdependent. The limitations of the study are as follows; First, about the research setting, the study was conducted with high-tech industry, in which the direction of the change in the power balance of supply chain dyads is usually determined by manufacturers. So we have a difficulty with generalization. We need to control the power structure between partners in a future study. Secondly, about flexibility, we treated it throughout the paper as positive, but it can also be negative, i.e. violating an agreement or moving, but in the wrong direction, etc. Therefore we need to investigate the multi-dimensionality of flexibility in future research.