Industrial Smart Services: Types of Smart Service Business Models in the Digitalized Agriculture

Kampker, Achim; Jussen, Philipp; Moser, Benedikt

doi:10.1109/ieem.2018.8607270

Cited by 7 publications

(6 citation statements)

References 8 publications

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“…Surprisingly, only one article (Kampker et al, 2018) in our sample specifically refers to business model types. This article (allocated to cluster 3 (navigation / robots)) differentiates between six different business model types in a digitalized agriculture reaching from less to high complexity.…”

Section: Probing Into the Implementation Of Sustainability-oriented T...mentioning

confidence: 99%

Assessing emerging sustainability-oriented technologies: the case of precision agriculture

Rennings,

Baaden,

Block

et al. 2024

Scientometrics

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The pressing need for a transition towards a more sustainable economy has given rise to sustainability-oriented innovations (SOIs). The development of SOIs involves a wide range of emerging technologies, some of which are highly uncertain and may have the potential to transform an existing industry. Thus, the identification and assessment of emerging technologies is pivotal for established companies to evaluate business opportunities as well as for researchers and policy makers to support the transition to a more sustainable economy. Therefore, we aim to contribute by offering a new approach that seeks to assess such emerging technologies that contribute to sustainability transition (i.e., sustainability-oriented technologies (SOTs)) by means of spectral cluster analysis based on the semantic similarities of scientific research articles in the field of precision agriculture (PA); a case example where multiple SOIs occur. Our analyses reveal that spectral cluster analysis is a suitable approach for assessing emerging SOTs. In addition, multi-perspective assessments based on, inter alia, related United Nations Sustainable Development Goals, Web of Science subject categories, strategic diagrams, and business models allows to render a holistic assessment of a scientific research area (in this case PA) and its emerging SOTs as well as their evolution into commercial SOIs.

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Section: Probing Into the Implementation Of Sustainability-oriented T...mentioning

confidence: 99%

Assessing emerging sustainability-oriented technologies: the case of precision agriculture

Rennings,

Baaden,

Block

et al. 2024

Scientometrics

View full text Add to dashboard Cite

show abstract

“…By formula (7), the LS problem was converted into the minimization of the objective of N independent learners. This paper iteratively solves each simple regression model g (n.) with gradient boosting algorithm.…”

Section: G Arg Min Loss C Arg Min Loss a H G Hmentioning

confidence: 99%

“…The application of the Internet of things (IoT) to agricultural production and agricultural product (AP) sales leads to intelligent agriculture, which is smarter than traditional agriculture, bringing lots of convenience to our work and life. In intelligent agriculture, the agricultural production and AP sales are controlled by sensors and data crawlers, via mobile or computer platforms [6][7][8]. With the elapse of time, both the production data collected by sensors and online sales data gathered by crawlers will grow exponentially.…”

Section: Introductionmentioning

confidence: 99%

Application of Big Data Analysis to Agricultural Production, Agricultural Product Marketing, and Influencing Factors in Intelligent Agriculture

Cheng

2022

CIT. J. comput. inf. technol

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Agricultural Internet of things (AIoT) promotes the modernization of traditional agricultural production and marketing model. However, the existing time series prediction methods for agricultural production and agricultural product (AP) marketing cannot adapt well to most real-world scenarios, failing to realize multistep forecast of production and AP marketing data. To solve the problem, this paper explores the big data analysis of agricultural production, AP marketing, and influencing factors in intelligent agriculture. To realize long-, and short-term predictions, a small-sample time series model was set up for AIoT production, and a big-sample time series model was constructed for AP marketing. The data fusion algorithm based on Kalman filter (KF) was adopted to fuse the massive multi-source AP marketing data. The proposed strategy was proved valid through experiments.

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“…So far, to the best of our knowledge, no research has yet identified SBMPs in the field of digital agriculture. The only prototypical business model patterns in digital agriculture were identified by Kampker et al [19], who explored business model patterns for industrial smart services. Given this review of the literature, we aim to identify emerging SBMPs in digital agriculture from startups using the methodology outlined in the following chapter.…”

Section: Current Literature On Solution Business Model Patterns (Sbmps)mentioning

confidence: 99%

Emerging innovation patterns in digital agriculture: A study of 198 digital solutions from 116 startups

Schirmer¹,

Eber²,

Florez³

et al. 2021

Proceedings of the Annual Hawaii International Conference on System Sciences

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To tackle humanity's food challenges, agricultural companies need to exploit technological advancements by innovating their business models. Solution business model patterns (SBMPs) play a central role in business model innovation. However, the current literature on SBMPs is outdated and has not been adapted for the field of agriculture. By analyzing 198 digital solutions from 116 agriculture startups, we identify 18 SBMPs, nine of which have not been identified in any previous research. We thus significantly expand the existing literature on SBMPs and outline the technological drivers of emerging SBMPs. Furthermore, putting the 18 identified SBMPs into the context of agriculture will help agricultural companies innovate their business models. Three SBMPs with high potential to tackle humanity's food challenges are further discussed.

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Industrial Smart Services: Types of Smart Service Business Models in the Digitalized Agriculture

Cited by 7 publications

References 8 publications

Assessing emerging sustainability-oriented technologies: the case of precision agriculture

Assessing emerging sustainability-oriented technologies: the case of precision agriculture

Application of Big Data Analysis to Agricultural Production, Agricultural Product Marketing, and Influencing Factors in Intelligent Agriculture

Emerging innovation patterns in digital agriculture: A study of 198 digital solutions from 116 startups

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