Technological innovations in agriculture have transformed the farming systems of smallholder farmers, leading to the realization of economic incentives of higher outputs, profits, and sustainability. However, attempts to model their adoption behaviors have failed to consider the possible interdependencies and simultaneities in the adoption decision process. This may cause invalid inferences and incorrect conclusions to be made regarding smallholder farmers' adoption decisions. This study, therefore, models smallholder farmers' adoption decisions while taking into account the possibility of interdependencies and simultaneities of adopting rice productivityenhancing agricultural technologies in Ghana. Cross-sectional survey data on 1016 smallholder rice farmers sampled using a three-stage sampling method from four municipalities in two regions in Ghana were used for the study. We fit a multinomial probit model to analyze the decisions to adopt or not to adopt varied combinations of improved rice variety, fertilizer, and herbicide. Our study finds that when faced with improved rice varietyfertilizer-herbicide technological options, smallholder rice farmers' adoption decisions fell into any one of four possibilities: (a) reject all technological options, (b) adopt a particular technology only, (c) adopt two of the technologies, and (d) adopt all technological choices. We show that such adoption decisions were consistently and most significantly predicted by farm size, extension contacts, education, participation in field demonstrations, complementary input availability, and extent of commercialization. Modeling smallholder farmers' adoption decisions to capture interdependencies and simultaneities provides useful information for integrating diverse perspectives into the design and promotion of technological innovations based on their nature of adoption, the specific technological innovations, and influencing factors. We recommend that to achieve the maximum benefits, future technology promotion activities should concurrently reduce farmers' subjective uncertainties and risks, promote credit access and subsidies, as well as ensure effective input delivery systems while targeting specific technological innovations.

Advancement in agricultural technologies is seen to result in the shift in production functions. The study was conducted to establish the impact of the improved rice variety on productivity in the Ejura-Sekyedumase and Atebubu-Amantin Municipalities of Ghana. The study was based on the survey of 208 rice farmers using a three-stage stratified sampling method. The study used a structured questionnaire to collect input-output data from the rice farmers. Data were analysed using the Cobb-Douglas production function. The study found that the technical change associated with the introduction of the improved rice variety was of the non-neutral type. Further, the adoption of the improved rice variety has increased rice productivity by about 46% for the adopters. The main determinants of productivity for the adopters were seed, land, fertiliser, herbicide, and education. Productivity among the non-adopters was positively influenced by seed, land, herbicide, and fertiliser. The study concluded that the improved rice variety has superior yield advantage. The study recommends for the simultaneous promotion of improved rice varieties and their recommended inputs to increase rice productivity.

The study was conducted in Ejura-Sekyedumase Municipality of the Ashanti Region and the Atebubu-Amantin Municipality in the Brong-Ahafo Region of Ghana, in May 2013, to investigate the technological change in rice production in the two municipalities in Ghana using the output decomposition analysis approach. The study adopted a descriptive research design, based on a cross-sectional survey strategy. The study involved 216 sampled smallholder rice farmers (107 adopters of the improved variety and 109 non-adopters) using a three-stage stratified random sampling method involving operational areas, communities, and farmers. Data were collected by trained agricultural extension agents and monitored by the researchers. The Cobb-Douglas production and a modified decomposition analyses techniques were used to decompose the sources of productivity differences between the improved rice variety and the unimproved rice variety. Out of 216 rice farmers sampled, 208 completed their questionnaires. The study found that