Technical efficiency and risk of pineapple production among smallholders in Johor, Malaysia

Pineapple is one of the most important crops in Malaysia and government recognizes its potential for exploitation. To that end, increasing pineapple production through improvement in its yield seems to be a reliable approach to achieve the Malaysia Pineapple Industry Board’s agency yield target of 64 metric tonnes/ha in 2020. Efforts are being focused on Johor as the largest pineapple producing state (54%) in Malaysia which has the potential to achieve the yield target, with the government supporting smallholder production capacity. However, despite the various governmental support, pineapple production is hampered by the lower yield compared to the yield target. In 2020, average national pineapple yield was roughly 22.9 metric tonnes/ha. Since at a current technology, the yield is normally associated with the level of input use, the low pineapple yield was potentially caused by the technical inefficiency in the input use. The production inputs are essential to pineapple farming, which is likely to result in output variability (risk) and inefficiency. This indicates that the empirical models for measuring technical efficiency need to consider the element of production risk associated with inputs in pineapple production. This research aims to shed light on the possible causes of pineapple production fluctuation being experienced by pineapple smallholders in Johor state in recent years. The gap between observed output and achievable output presents an opportunity for an increment in output which offers the inspiration for this study as it is concerned with examining the technical efficiency on pineapple production. The main objective of this study is to determine technical efficiency and production risk of smallholder pineapple production in Johor as two possible sources of the production variability. The specific objectives were to estimate the technical efficiency of smallholders’ pineapple production; to analyse production risks with respect to the inputs levels of smallholders’ pineapple production; and to determine influencing factors that affect the technical efficiency of smallholders’ pineapple production. Data from a total of 290 randomly selected smallholder pineapple farms in Johor by using multistage sampling procedure. The research employed purposive sampling to select districts in Johor based on their relative importance in pineapple production and a systematic random sampling method to acquire random samples. The data for the study were collected from the pineapple smallholders in Johor from June till December 2021. The study employed stochastic frontier production function model (SFA) with flexible risk specification for parametric approach, and data envelopment analysis (DEA) for non-parametric approach without accounting for production risk in order to depict more holistic feature of pineapple farms efficiency in Johor. For the first objective, technical efficiencies results of smallholder pineapple producers were compared between SFA and DEA techniques. Specifically, the average efficiency score of SFA was 68.1%, implying that the farmers in the study area were technically inefficient. On the other hand, the result of DEA technical efficiency score was 96.0%, also, implying that the pineapple farmers were technically inefficient. For the second objective, pineapple suckers were found to be risk reducing input while fertilisers and hormones were risk increasing inputs. By implication, it shows that risk-averse farmers are expected to use more suckers in the study area. The results also revealed that the mean output was positively influenced by suckers, fertiliser, agrochemicals, labour and hormone. For the third objective, several characteristics of farm operators such as demographics variables (farming experience); and institutional variables (extension contact and seminar participation); were found to have significant effects on the technical inefficiency of pineapple production in the study area. The study concludes that the trans-log production function was the best fit for the data for estimation of farmers’ technical efficiency as the analysis recorded that technical efficiency enhances the variability of pineapple production in the study area. The model estimates showed that production risk contributes considerably to the variability of pineapple production levels. Findings of this research show that output variability is primarily explained by technical inefficiency and production risk. It is recommended that relevant government agencies should ease the accessibility to extension visits, to hold seminars and promote the sharing of knowledge by experienced farmers, which could enlighten other farmers towards improving their production volumes. Furthermore, policy strategies aiming at improving technical efficiency should emphasise effective and efficient use of existing inputs among pineapple smallholders. The outcome of technical efficiency and production risk estimation have indicated the level of utilisation of the present technology used in the production process as well as rooms for improvement that can be translated to better income and livelihood among the smallholders.

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