Knowledge diffusion and agricultural development

Low agricultural productivity remains the primary source of poverty in the developing regions and yet little is known about the influence on agricultural productivity of domestic and international accumulated R&D knowledge and the channels through which this knowledge is transmitted internationally. Following a large scientific literature, this article argues that R&D and R&D knowledge spillover are ecozone‐specific and, therefore, are transmitted internationally through ecozones, where ecozones are the broadest biogeographic division of the earth's land surface. Using data for a panel of 88 countries, it is shown that international knowledge spillovers are ecozone‐specific and have been an important contributing factor behind the marked widening of the income gap between developed and developing countries since 1983.     

Business models and the managerial sensemaking process

This study examines the managerial sensemaking process around business models. Drawing on fieldwork, this study introduces a model to describe how managerial sensemaking occurs around business model development and use. This study shows that managerial sensemaking around business models occurs through a mutually co‐constituted process, a separate yet shared process, or a combination of them resulting from an interplay between sensemaking and sensegiving activities. To facilitate their sensemaking around business models, managers draw on several schemas. Over time, some schemas underlying business models remain unchanged, while others change in varying degrees.     

Modeling the effects of including/excluding attributes in choice experiments on systematic and random components

This paper examines the impact of attribute presence/absence in choice experiments using covariance heterogeneity models and random coefficient models. Results show that attribute presence/absence impacts both mean utility (systematic components) and choice variability (random components). Biased mean effects can occur by not accounting for choice variability. Further, even if one accounts for choice variability, attribute effects can differ because of attribute presence/absence. Managers who use choice experiments to study product changes or new variants should be cautious about excluding potentially essential attributes. Although including more relevant attributes increases choice variability, it also reduces bias.     

An Approach to Security for Unstructured Big Data

Security of Big Data is a huge concern. In a broad sense, Big Data contains two types of data: structured and unstructured. Providing security to unstructured data is more difficult than providing security to structured data. In this paper, we have developed an approach to provide adequate security to unstructured data by considering types of data and their sensitivity levels. We have reviewed the different analytics methods of Big Data to build nodes of different types of data. Each type of data has been classified to provide adequate security and enhance the overhead of the security system. To provide security to a data node, and a security suite has been designed by incorporating different security algorithms. Those security algorithms collectively form a security suite which has been interfaced with the data node. Information on data sensitivity has been collected through a survey. We have shown through several experiments on multiple computer systems with varied configurations that data classification with respect to sensitivity levels enhances the performance of the system. The experimental results show how and in what amount the designed security suite reduces overhead and increases security simultaneously.     

Exploring the widening food gap: an international perspective

Using data for a long panel of 90 developed and developing countries, this article explores the effects of research and development (R&D) and fixed capital stock on agricultural land productivity over the period 1961–2012. Instruments are used for R&D to deal with feedback effects and measurement errors. The results show very high social returns to investment in R&D and to fixed capital stock, suggesting that increasing investment in these factors are promising ways of arresting the increasing food prices due to increasing demand for animal protein, population growth, desertification, salinization, soil erosion, climate change, and decreasing growth in land productivity.     

Construction of an open innovation network and its mechanism design for manufacturing enterprises: a resource-based perspective

Innovation is the engine of development for enterprises, and there is an increasing trend to adopt an open innovation strategy. However, how to manage external resources in an open, collaborative and complementary manner, and in a shared environment that will yield the greatest networking effects, it is a challenging task. Because there is no such a satisfactory model for an open innovation strategy that combine operational mechanisms with the management of, external resources. Thhis article tries to fill the gap by adopting a resource-based perspective to construct an overall open innovation (OOI) business model. In this model, external resources are classified as industrial and non-industrial entities, to enable the identification of the interaction methods between manufacturing enterprises and external resources. The management of external resources involved in a Technology Open Innovation (TOI) cycle is given particular attention that includes: 1) the classification of the external resources of a TOI, 2) the general mechanisms extracted to promote qualified resources in and unqualified resources out, and 3) a business model to conceptualize the collaboration between enterprises and external resources. A case study of TOI is also provided to empirically verify its feasibility. This paper contributes to the literature by providing an original operational model and mechanism design for an open innovation strategy that is capable of managing external resources effectively.     

How training and innovation link to farm performance: a structural equation analysis

The complexity of modern farm management places great demands on the skill, knowledge and capability of farm managers and their families. Keeping abreast of emerging technologies and innovations that can affect each key farm enterprise, and knowing how best to marshal the resources required for profitable farm production, are key tasks of farm management. This study draws on a longitudinal data set of 240 broadacre farmers to compare and analyse their farm performance over a decade. Using structural equation modelling, we examine relationships between the farm family's involvement in training, their human capital, their use of various innovations and ultimately the linkages of these factors to farm financial and productivity performance. Several statistically significant inter‐relationships are found, and some factors are shown to have significant positive links to farm performance. We find that training undertaken by the farm family, the farm family's human capital and their use of innovations, particularly key cropping innovations, have significant beneficial impacts on farm performance. The farmer's skills in time and organisational management, their engagement in business planning and the unique environmental characteristics of the farm also significantly and positively influence farm performance.     

The public R&D and productivity growth in Australia's broadacre agriculture: is there a link?

This paper investigates the dynamic relationships between research and development (R&D) expenditure and productivity growth in Australian broadacre agriculture using aggregate time series data for the period 1953 to 2009. The results show a cointegrating relationship between R&D and productivity growth and a unidirectional causality from R&D to TFP (total factor productivity) growth in Australian broadacre agriculture. Using the dynamic properties of the model, data from beyond the sample period are analysed by employing the variance decomposition and the impulse response function. The findings reveal that R&D can be readily linked to the variation in productivity growth beyond the sample period. Furthermore, the forecasting results indicate that a significant out‐of‐sample relationship exists between public R&D and productivity in broadacre agriculture.     

Modern Slavery Disclosure Regulation and Global Supply Chains: Insights from Stakeholder Narratives on the UK Modern Slavery Act

Journal of Business Ethics - The purpose of this article is to problematise a particular social transparency and disclosure regulation in the UK, that transcend national boundaries in order to...     

Exploring the impact of R&D and climate change on agricultural productivity growth: the case of Western Australia*

This article empirically examines the impact of R&D and climate change on the Western Australian Agricultural sector using standard time series econometrics. Based on historical data for the period of 1977–2005, the empirical results show that both R&D and climate change matter for long‐run productivity growth. The long‐run elasticity of total factor productivity (TFP) with respect to R&D expenditure is 0.497, while that of climate change is 0.506. There is a unidirectional causality running from R&D expenditure to TFP growth in both the short run and long run. Further, the variance decomposition and impulse response function confirm that a significant portion of output and productivity growth beyond the sample period is explained by R&D expenditure. These results justify the increase in R&D investment in the deteriorating climatic condition in the agricultural sector to improve the long‐run prospects of productivity growth.