Knowledge sharing is a daily social activity involving two or more people giving and receiving knowledge (Nonaka, 1994). The way in which knowledge is shared is part of a larger culture phenomenon (Filius, de Jong, and Roelofs, 2000), in an organization or among community. The quality of the shared knowledge depends on the normative expectations a community holds about what and how much information is needed in each role or task (Bushe, 1988). Communication, which is a pre-requisite of knowledge sharing, is strongly connected to cultural conditions (Gudykunst and Ting-Toomey, 1988). Climate information including seasonal rainfall forecast information is a form of knowledge and the communication of the same may as well be considered alongside other types of knowledge.
Various sophisticated information systems exist among organizations but the most basic and most important media of knowledge sharing are the existing networks that people use in their daily work (McDermott and O’Dell, 2001). Studies in knowledge sharing have identified several features for efficient and effective knowledge sharing among people. Filius et al. (2000) found that individuals are sometimes rewarded more for keeping their knowledge to themselves than for sharing it. This can lead to a situation where a more experienced employee hides vital pieces of information from a newcomer to ensure his/her own position. This study explorers the potential influence of cultural values to instigate such behavior as deduced by Filius et al among intermediaries of climate information.
Numerous authors have identified values as an important and influential element within social-ecological systems (SES), and have linked the notion of values, with human natural resource based livelihoods. Jones et al., (2016), reviewed several studies on the role of human values in understanding and managing social-ecological systems. In their review, Jones et al., provided key insights into the social dimensions of coupled social-ecological systems and identified values as a fundamental aspect of cognition, which represent deeply held, emotional aspects of people’s cognition with potential to complement the use of other cognitive constructs, such as knowledge and mental models.
Several studies have been done on the socio-economic value of climate information. These studies have followed the decision analysis theory as applied for organizations and/or individuals. These studies include; Aura et al, 2012; Mjelde el al. 1988;, Hilton, 1981). Aura et al (2012), noted that research on the quantitative nature of the weather forecasting processes is necessary for effective uptake of climate information. Hilton, (1981) identified four general determinants of value of information including : 1) characteristics of the information system itself, 2) the structure of the decision set, 3) the structure of the decision environment, or equivalently the decision maker’s current technology, environment, and relative preferences for outcomes, and 4) the decision maker’s initial knowledge about the distribution of the stochastic variable(s) in the decision environment. Mjelde el al. (1988), defined and derived the value of climate information. They inferred that value-driven approaches orient around best outcomes for best cost, while not neglecting the margins which form essential metric for business performance. In their study, Mjelde el al. assumed that there are possible synergistic effects of knowing the climate forecast for adjacent time periods within a dynamic production process which when integrated develop the object of value. Thus in the decision analysis approach, the authors seek to answer the question: how much answering a question allows a decision-maker to improve on perceived decision. In this concept, value of climate information is the amount of money a decision maker would be willing to pay for climate information (seasonal rainfall forecast, climate data among others), prior to making a climate dependent livelihood decision.
Elwyn et al (2001), deduced that this approach of decision analysis is based on the normative expected utility theory where decision analysis is used prescriptively as a way of assisting decision makers with their choices. Thus underpinning the process is the assumption that humans are rational and logical decision makers(Tavakoli et al 2000, Thornton 1996). A rational decision, in the context of decision analysis, is one that results in the outcome with the greatest usefulness to the individual (Elwyn et al 2001).
Decision-making however occurs in a situation that demands for a managerial decision process for an organization or a household to avoid organizational damages, to improve organizational performance, or to keep the organizational state. In the case of a household, the organizational state is mainly characterized by basic values which may include at least one of the 57 value items that represent ten motivationally distinct values described by Schwartz (1992). Mjelde & Hill (1989), studied the complex nature of the process of economically valuing climate/weather forecasts. Mjelde & Hill, discussed both micro and sector economic issues faulting the idea that improvements in skill and lead time of forecast may be enough to provide economic value to decision makers in regions of the world. Mjelde & Hill, thereby deduced that integration of socio-cultural issues is necessary to obtain the overall value of current or improved climate/weather forecasts. Jones et al., (2016) suggested that researchers from the many disciplines contributing to the study of social ecological systems need to make distinctions in their usage of the term values and in the breadth of scope they apply in studying values.
Fulton er al., (1996), developed a conceptual framework for studying human values. The framework was developed as a measurement instrument for assessing basic beliefs and value orientations concerning issues of enduring relevance to management and planning.