Timothy J. Richards and Mark R. Manfredo
During the 1990s, the rate of consolidation among agricultural cooperatives, including mergers, acquisitions, strategic alliances, and joint ventures, increased significantly…
Abstract
During the 1990s, the rate of consolidation among agricultural cooperatives, including mergers, acquisitions, strategic alliances, and joint ventures, increased significantly. While post‐merger performance has been examined extensively for investor‐owned firms, this has not been the case for agricultural cooperatives, primarily because these firms do not have an explicit profit motive or publicly traded stock. Results from a two‐stage econometric model reveal that a major motivation for cooperatives to engage in these activities is to circumvent capital constraints. Furthermore, the decision to merge and financial performance are jointly endogenous, with profitability positively influenced and sales growth negatively influenced by the likelihood of merger.
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Mark R. Manfredo and Timothy J. Richards
Numerical simulation of several typical risk management strategies using pro forma financial statements from representative U.S. dairy cooperatives shows that combinations of…
Abstract
Numerical simulation of several typical risk management strategies using pro forma financial statements from representative U.S. dairy cooperatives shows that combinations of forwards, swaps, and cash marketing strategies for output (cheese), along with various forward contracts offered to cooperative members to manage the variability of milk revenues, have the potential to improve cooperative‐, and ultimately member‐level risk‐return performance. Because most cooperatives have limited access to equity capital, effective use of available risk management tools can increase cooperative value by increasing debt capacity, avoiding bankruptcy costs, and preventing the distortion of capital budgeting decisions. Moreover, the offering of risk management tools to individual members as a service may prove valuable in the retention of these members in the cooperative.
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Phillip T. Manno, Jesus Bravo, Mark Manfredo and Rafael C. Leon
Water availability and usage in agriculture suggests increasing scarcity. To ensure the long-term sustainability of water resources, efficient pricing and distribution methods…
Abstract
Purpose
Water availability and usage in agriculture suggests increasing scarcity. To ensure the long-term sustainability of water resources, efficient pricing and distribution methods must be considered. The role that market-based systems of water distribution can play in enhancing the management and sustainability of water resources has garnered attention. An important element that cannot be ignored when contemplating changes to established agricultural water delivery systems must be users’ readiness for change. Thus the purpose of this paper is to examine factors that impact the readiness for organizational change to a system where users can buy and sell water in an open market.
Design/methodology/approach
Using data collected from a survey of greenhouse growers in Almería, Spain, a model of binary choice was developed to predict the probability of growers’ readiness to buy and sell water in an open market.
Findings
The level of education of the grower, and the use of a euro per hour water metering system positively impacted the probability of the willingness to participate in formal water markets. Also, the degree of satisfaction in the administration of the growers’ irrigation community, as well as their overall confidence in anticipated water supplies, had a negative impact on readiness to change.
Research limitations/implications
This research offers an interesting and unique scholarly contribution as it fuses the extant management literature on the topic of organizational change with issues related to natural resource management, thus contributing to the growing literature(s) related to resource sustainability and management.
Originality/value
This research provides insight into some important factors which may predict the readiness to change of agricultural water users toward more market-driven distribution systems.
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While the extant literature is replete with theoretical and empirical studies of value at risk (VaR) methods, only a few papers have applied the concept of VaR to quantify market…
Abstract
Purpose
While the extant literature is replete with theoretical and empirical studies of value at risk (VaR) methods, only a few papers have applied the concept of VaR to quantify market risk in the context of agricultural finance. Furthermore, papers that have done so have largely relied on parametric methods to recover estimates of the VaR. The purpose of this paper is to assess extreme market risk on investment in three actively traded agricultural commodity futures.
Design/methodology/approach
A nonparametric Kernel method was implemented which accommodates fat tails and asymmetry of the portfolio return density as well as serial correlation of the data, to estimate market risk for investments in three actively traded agricultural futures contracts: corn, soybeans, and wheat. As a futures contract is a zero‐sum game, the VaR for both short and long sides of the market was computed.
Findings
It was found that wheat futures are riskier than either corn or soybeans futures over both periods considered in the study (2000‐2008 and 2006‐2008) and that all three commodities have experienced a sharp increase in market risk over the 2006‐2008 period, with VaR estimates 10‐43 percent higher than the long‐run estimates.
Research limitations/implications
Research is based on cross‐sectional data and does not allow for dynamic assessment of expenditure elasticities.
Originality/value
This paper differs methodologically from previous applications of VaR in agricultural finance in that a nonparametric Kernel estimator was implemented which is exempt of misspecification risk, in the context of risk management of investment in agricultural futures contracts. The application is particularly relevant to grain elevator businesses which purchase grain from farmers on a forward contract basis and then turn to the futures markets to insure against falling prices.
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David D. Van Fleet, Abagail McWilliams and Michael Freeman
To develop an understanding of communication among agribusiness journals and to examine patterns of citations that allow the measurement and description of the structure of…
Abstract
Purpose
To develop an understanding of communication among agribusiness journals and to examine patterns of citations that allow the measurement and description of the structure of communication flows among those journals in a network.
Design/methodology/approach
The data for this study were gathered from the Journal Citation Reports (JCR) published by Thomson Scientific (Philadelphia). The authors conducted a bibliometric analysis, based on an international trade analogy to explain the network of agribusiness journals and how these journals communicate with business and economics journals.
Findings
Business and economics journals and, particularly the traditionally major ones, surprisingly were scarcely every used. However, the British Food Journal stood out with 50 citations to marketing and strategic management journals.
Research limitations/implications
There are predominantly four such limitations: only 33 journals were studied, only one 5-year time period was involved, that time period is a few years old and the journal characteristics were derived using data from the “Scopes” and “Information for Authors” text on the website of each journal.
Practical implications
Exchanges of agribusiness knowledge and information among diverse stakeholders (consumers, suppliers and public agencies) in a complex environment require a better understanding of the network of agribusiness journals and their relation to traditional business and economics journals.
Social implications
Networks of journals facilitate cooperation and interactions to improve developments in the field.
Originality/value
Examining citations from and to the field of agribusiness is interesting and important because knowledge is transferred through networks comprise those who contribute to journals, read them and learn from them, i.e. by “talking” to each other as well as by practitioners who also read and learn from those journals.
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This paper aims to examine from commodity portfolio managers’ perspective the performance of liquidity adjusted risk modeling in assessing the market risk parameters of a large…
Abstract
Purpose
This paper aims to examine from commodity portfolio managers’ perspective the performance of liquidity adjusted risk modeling in assessing the market risk parameters of a large commodity portfolio and in obtaining efficient and coherent portfolios under different market circumstances.
Design/methodology/approach
The implemented market risk modeling algorithm and investment portfolio analytics using reinforcement machine learning techniques can simultaneously handle risk-return characteristics of commodity investments under regular and crisis market settings besides considering the particular effects of the time-varying liquidity constraints of the multiple-asset commodity portfolios.
Findings
In particular, the paper implements a robust machine learning method to commodity optimal portfolio selection and within a liquidity-adjusted value-at-risk (LVaR) framework. In addition, the paper explains how the adapted LVaR modeling algorithms can be used by a commodity trading unit in a dynamic asset allocation framework for estimating risk exposure, assessing risk reduction alternates and creating efficient and coherent market portfolios.
Originality/value
The optimization parameters subject to meaningful operational and financial constraints, investment portfolio analytics and empirical results can have important practical uses and applications for commodity portfolio managers particularly in the wake of the 2007–2009 global financial crisis. In addition, the recommended reinforcement machine learning optimization algorithms can aid in solving some real-world dilemmas under stressed and adverse market conditions (e.g. illiquidity, switching in correlations factors signs, nonlinear and non-normal distribution of assets’ returns) and can have key applications in machine learning, expert systems, smart financial functions, internet of things (IoT) and financial technology (FinTech) in big data ecosystems.
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Martin Odening and Jan Hinrichs
This study examines problems that may occur when conventional Value‐at‐Risk (VaR) estimators are used to quantify market risks in an agricultural context. For example, standard…
Abstract
This study examines problems that may occur when conventional Value‐at‐Risk (VaR) estimators are used to quantify market risks in an agricultural context. For example, standard VaR methods, such as the variance‐covariance method or historical simulation, can fail when the return distribution is fat tailed. This problem is aggravated when long‐term VaR forecasts are desired. Extreme Value Theory (EVT) is proposed to overcome these problems. The application of EVT is illustrated by an example from the German hog market. Multi‐period VaR forecasts derived by EVT are found to deviate considerably from standard forecasts. We conclude that EVT is a useful complement to traditional VaR methods.
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Citizens are substantial stakeholders in every e-government system, thus their willingness to use and ability to access the system are critical. Unequal access and information and…
Abstract
Citizens are substantial stakeholders in every e-government system, thus their willingness to use and ability to access the system are critical. Unequal access and information and communication technology usage, which is known as digital divide, however has been identified as one of the major obstacles to the implementation of e-government system. As digital divide inhibits citizen’s acceptance to e-government, it should be overcome despite the lack of deep theoretical understanding on this issue. This research aimed to investigate the digital divide and its direct impact on e-government system success of local governments in Indonesia as well as indirect impact through the mediation role of trust. In order to get a comprehensive understanding of digital divide, this study introduced a new type of digital divide, the innovativeness divide.
The research problems were approached by applying two-stage sequential mixed method research approach comprising of both qualitative and quantitative studies. In the first phase, an initial research model was proposed based on a literature review. Semi-structured interview with 12 users of e-government systems was then conducted to explore and enhance this initial research model. Data collected in this phase were analyzed with a two-stage content analysis approach and the initial model was then amended based on the findings. As a result, a comprehensive research model with 16 hypotheses was proposed for examination in the second phase.
In the second phase, quantitative method was applied. A questionnaire was developed based on findings in the first phase. A pilot study was conducted to refine the questionnaire, which was then distributed in a national survey resulting in 237 useable responses. Data collected in this phase were analyzed using Partial Least Square based Structural Equation Modeling.
The results of quantitative analysis confirmed 13 hypotheses. All direct influences of the variables of digital divide on e-government system success were supported. The mediating effects of trust in e-government in the relationship between capability divide and e-government system success as well as in the relationship between innovativeness divide and e-government system success were supported, but was rejected in the relationship between access divide and e-government system success. Furthermore, the results supported the moderating effects of demographic variables of age, residential place, and education.
This research has both theoretical and practical contributions. The study contributes to the developments of literature on digital divide and e-government by providing a more comprehensive framework, and also to the implementation of e-government by local governments and the improvement of e-government Readiness Index of Indonesia.
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Daniel Fesenmaier and Kelly MacKay
Tourism is leisure commodified. As a commodity, the actuality of tourism has been suggested as less important than its expressive representations. What is depicted or not depicted…
Abstract
Tourism is leisure commodified. As a commodity, the actuality of tourism has been suggested as less important than its expressive representations. What is depicted or not depicted in destination image advertising, and on whose authority it is selected, involves a more complex question of what comprises the destination and who has the power to define its identity. Recently, there has been a shift in the promotional role of destination marketing organizations where it has broadened to include product (attraction) development and industry relations. This role extension enables a matching of authoritative voice and reconstructed reality in order to verify official imaging. The symbolism and meaning of destination image can be interpreted through a deconstructionist analysis of tourist destination advertising. This paper explores significance of tourism promotion on tourist culture as it packages touristic representations.