The Effects of Risk Preferences on the Adoption of Post-Harvest Technology: Evidence from Rural Cambodia

Shimamoto, Daichi; Yamada, Hiroyuki; Wakano, Ayako

doi:10.1080/00220388.2017.1329527

Cited by 11 publications

(10 citation statements)

References 27 publications

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“…This is consistent with the work by Shimamoto et al. (2017) who find that increasing risk aversion is associated with increasing WTP for moisture meter use. Our work adds the literature by showing that, even for a completely unfamiliar technology, the actual function of the technology (risk‐reducing in this context) plays a significant role in shaping the relation between risk aversion and technology adoption.…”

Section: Discussionsupporting

confidence: 93%

“…Notably, Shimamoto et al. (2017) find using a sample of 142 farmers in Cambodia, that being more risk‐averse increases the probability of people using moisture meters to measure the moisture content of rice seed. We build on the existing evidence by (1) experimentally eliciting WTP to measure demand for moisture meters, instead of relying on reported previous use of the technology as in Shimamoto et al.…”

Section: Introductionmentioning

confidence: 99%

“…We build on the existing evidence by (1) experimentally eliciting WTP to measure demand for moisture meters, instead of relying on reported previous use of the technology as in Shimamoto et al. (2017), and (2) by eliciting risk preferences using real payoffs. In addition, the moisture meters used in the auctions were not available locally, so participants did not have any previous awareness and knowledge of the products.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Willingness to pay for a new farm technology given risk preferences: Evidence from an experimental auction in Kenya

Channa

Ricker‐Gilbert

Groote

et al. 2021

Agricultural Economics

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This paper describes an experimental auction conducted among maize traders and farmers in Western Kenya to measure adoption for two low-cost technologies that can measure grain moisture content. Willingness-to-pay auctions (WTP) were combined with a risk preference lottery, allowing an opportunity to study the impact of risk preferences on technology adoption. The specifics of this technology also allows us to identify the impact of risk aversion on willingness to pay for a technology when production uncertainty is not part of the equation. We also randomized two variations of the BDM method for collecting WTP data allowing for a mechanism by which to study the impact of the method on valuation data. We find some evidence that risk aversion increased willingness to pay. Another result with implications in implementation of field experiments in the developing world is that farmers were sensitive to the method in which the auction was presented but traders were not.

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Section: Discussionsupporting

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Willingness to pay for a new farm technology given risk preferences: Evidence from an experimental auction in Kenya

Channa

Ricker‐Gilbert

Groote

et al. 2021

Agricultural Economics

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“…Compared to risk-averse farmers, risk-tolerant farmers are at least 17% less likely to adopt new improved rice varieties. This finding is similar to Shimamoto et al (2018) for farmers in Cambodia. The Wald tests performed to evaluate the equality of various risk-tolerant categories against each other show statistically significant difference.…”

Section: Probit Regression Resultssupporting

confidence: 84%

Using Farmers’ Risk Tolerance to Explain Variations in Adoption of Improved Rice Varieties in Nepal

Begho

2021

Journal of South Asian Development

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Rice is the leading cereal crop in Nepal and an important source of calories and plant protein. Despite the importance of rice, there are reports of widespread cultivation of older varieties with considerably large adoption lags. This warrants further investigation into the factors that influence rice farmers’ adoption decisions. Risk attitude is reported to be an important determinant of farmers’ decisions. However, in Nepal, evidence of the effect of risk attitude on the adoption of improved crop varieties is limited because this important factor is not considered in adoption studies. This article, therefore, connects field experiment, theoretical understanding of farmers’ risk attitudes and empirical models with the aim of investigating determinants of farmers adoption of improved rice varieties in Nepal. The results show that majority of farmers currently grow old varieties. The top four varieties—Sona Mahsuri, Sarju-52, Samba Mahsuri and Radha-4—have an average varietal release age of 27 years. By estimating a binary response regression model, this article shows that risk attitude is a significant determinant of rice farmers’ adoption decision. Specifically, the results show that risk-tolerant farmers have the lowest propensity to adopt new improved rice varieties. This article, therefore, highlights the importance of promoting holistic benefits over making risk-reducing attributes salient when new crop varieties are developed and disseminated to farmers.

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“…This has been applied in the study of decision-making for technology adoption, both by business researchers (e.g., Yoo & Kim, 2018) and behavioral economists (e.g., Streletskaya et al, 2020). Consequently, the adoption decision-making process has been examined from all manner of decision science perspectives, ranging from utility theory (Shimamoto et al, 2018) and intuition (Gagnon & Toulouse, 1996), with recent accounts suggesting that managers should balance effectual and causal reasoning when adopting new technologies (Mero et al, 2020). In this article, we do not examine the decisionmaking process per se but instead attempt to capture the broad range of psychological variables which appear to be influencing decisionmakers in technical settings, including both the individual decisionmaker and organizational-level factors.…”

mentioning

confidence: 99%

What use is technology if no one uses it? The psychological factors that influence technology adoption decisions in oil and gas.

Roberts¹,

Millar²,

Corradi³

et al. 2021

Technology, Mind, and Behavior

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What use is technology if no one uses it? This question underscores the critical interaction between people and the technology, highlighting the importance of understanding the underlying psychological factors that influence technology uptake. This study focuses on the corporate decision-makers who are the "gatekeepers" to the introduction of new technologies by their organizations. The offshore oil and gas industry has been characterized as reluctant to adopt new technology. Our thematic analysis of an interview study with 37 innovation technology stakeholders from this sector identified a set of six categories encompassing 15 psychological factors that influence the organizational decision-maker. The categories were labeled personality, attitudes, motivations, cognitive factors, social factors, and organizational factors set in a Psychological Technology Adoption Framework. This is the first attempt to focus exclusively on the main psychological factors that relate to this key decision-maker in the adoption of new technology. With further development, this preliminary psychological technology adoption framework can be used to develop interventions that support the successful technology uptake in the oil and gas business and similar industries.

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The Effects of Risk Preferences on the Adoption of Post-Harvest Technology: Evidence from Rural Cambodia

Cited by 11 publications

References 27 publications

Willingness to pay for a new farm technology given risk preferences: Evidence from an experimental auction in Kenya

Willingness to pay for a new farm technology given risk preferences: Evidence from an experimental auction in Kenya

Using Farmers’ Risk Tolerance to Explain Variations in Adoption of Improved Rice Varieties in Nepal

What use is technology if no one uses it? The psychological factors that influence technology adoption decisions in oil and gas.

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