Shinta Rahma Diana and Farida Farida
Technology acceptance is a measure of that technology’s usefulness. Oil palm is one of the biggest contributors to Indonesia’s revenues, thus fueling its economy. Using remote…
Abstract
Purpose
Technology acceptance is a measure of that technology’s usefulness. Oil palm is one of the biggest contributors to Indonesia’s revenues, thus fueling its economy. Using remote sensing would allow a plantation to monitor and forecast its production and the amount of fertilizer used. This review aims to provide a policy recommendation in the form of a strategy to improve the added value of Indonesia’s oil palm and support the government in increasing oil palm production. This recommendation needs to be formulated by determining the users’ acceptance of remote sensing technology (state-owned plantations, private plantation companies and smallholder plantations).
Design/methodology/approach
This review’s methodology used sentiment analysis through text mining (bag of words model). The study’s primary data were from focus group discussions (FGDs), questionnaires, observations on participants, audio-visual documentation and focused discussions based on group category. The results of interviews and FGDs were transcribed into text and analyzed to 1) find words that can represent the content of the document; 2) classify and determine the frequency (word cloud); and finally 3) analyze the sentiment.
Findings
The result showed that private plantation companies and state-owned plantations had extremely high positive sentiments toward using remote sensing in their oil palm plantations, whereas smallholders had a 60% resistance. However, there is still a possibility for this technology’s adoption by smallholders, provided it is free and easily applied.
Research limitations/implications
Basically, technology is applied to make work easier. However, not everyone is tech-savvy, especially the older generations. One dimension of technology acceptance is user/customer retention. New technology would not be immediately accepted, but there would be user perceptions about its uses and ease. At first, people might be reluctant to accept a new technology due to the perception that it is useless and difficult. Technology acceptance is the gauge of how useful technology is in making work easier compared to conventional ways.
Practical implications
Therefore, technology acceptance needs to be improved among smallholders by intensively socializing the policies, and through dissemination and dedication by academics and the government.
Social implications
The social implications of using technology are reducing the workforce, but the company will be more profitable and efficient.
Originality/value
Remote sensing is one of the topics that people have not taken up in a large way, especially sentiment analysis. Acceptance of technology that utilizes remote sensing for plantations is very useful and efficient. In the end, company profits can be allocated more toward empowering the community and the environment.
Details
Keywords
Meriam Trabelsi, Elena Casprini, Niccolò Fiorini and Lorenzo Zanni
This study analyses the literature on artificial intelligence (AI) and its implications for the agri-food sector. This research aims to identify the current research streams, main…
Abstract
Purpose
This study analyses the literature on artificial intelligence (AI) and its implications for the agri-food sector. This research aims to identify the current research streams, main methodologies used, findings and results delivered, gaps and future research directions.
Design/methodology/approach
This study relies on 69 published contributions in the field of AI in the agri-food sector. It begins with a bibliographic coupling to map and identify the current research streams and proceeds with a systematic literature review to examine the main topics and examine the main contributions.
Findings
Six clusters were identified: (1) AI adoption and benefits, (2) AI for efficiency and productivity, (3) AI for logistics and supply chain management, (4) AI for supporting decision making process for firms and consumers, (5) AI for risk mitigation and (6) AI marketing aspects. Then, the authors propose an interpretive framework composed of three main dimensions: (1) the two sides of AI: the “hard” side concerns the technology development and application while the “soft” side regards stakeholders' acceptance of the latter; (2) level of analysis: firm and inter-firm; (3) the impact of AI on value chain activities in the agri-food sector.
Originality/value
This study provides interpretive insights into the extant literature on AI in the agri-food sector, paving the way for future research and inspiring practitioners of different AI approaches in a traditionally low-tech sector.