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The purpose of this paper, applying concepts in the plant-based food sector, is a focus on the competitive rival trap for startup firms, with their initial advantage for under-served market segments, only to be overtaken by scale, speed, and brands of incumbent brand firms. As a case study of industry transformation, the food production sector illustrates how organizational innovation brings new forms of rivalry, from the farm gate to the kitchen plate. As a result, startups face a rivalry trap, if unable to scale quickly, as incumbents reframe their strategic response with startup acquisitions, corporate incubators or alliance partnerships consumer demand.

This paper outlines the features of precision agriculture, a new paradigm for agriculture and food production, requiring new competences and skillsets in the protein revolution, including issues like virus, bacteria and the molecular structure of food groups, animal breeding and veterinary medicine. Plant-based foods is used as a case study for startups and the rivalry trap.

The emergence of plant-based foods is a case study of market opportunity and creative destruction, where the potential market varies from $25bn to $72bn, and growing faster in the dairy sector. However, food incumbents bring new strategic responses and a rivalry trap, where startups must gain scale quickly in capabilities, talent and marketing prowess, often exploiting demand in market niches unimpeded by incumbent rivals.

Startups in biological sciences face massive challenges to increase scale and scope, even with unique intellectual property.

Startup firms need multidisciplinary management teams with a global outlook.

Plant-based foods form part of the protein revolution but face challenges of scale, cost competitiveness and taste, despite advantages for climate mitigation.

The impact of technological and science applications has blurred the traditional concept of industry boundary, with huge variations in the intangible knowledge component in their core activities and capabilities. Underlying variations imply that not all industries have similar supply demand conditions, with variations in input costs, capital intensity and innovation needs, with strategic implications for the rivalry trap.

The Internet of Things (IoT) is becoming increasingly popular in agribusiness to help increase food production capacity for the ever-expanding global population. This chapter provides a holistic overview of the latest trends around the applications of IoT in agriculture. We begin by giving an overview of IoT and its capabilities, followed by a deep dive into the practical and realistic aspects of leveraging IoT into the agroecosystem. IoT is already being used for many intelligent agriculture applications, such as open-field agriculture, controlled environment agriculture (greenhouse), livestock breeding, agricultural machinery, and more. This chapter examines those applications and ventures beyond the farm into several other aspects of the ecosystem, including storage, warehouse ambiance control, agri-data analytics and decision control, logistics, environmental safety, etc. The contents of the chapter would be based on extensive studies and empirical analysis of the latest research papers on this subject from around the globe, accurately interpreted and transformed by the authors in light of their academic background and professional experience in the digital transformation arena.

The purpose of this paper is to analyze the attitudes of meat consumers in Rio Grande do Sul, Brazil, concerning cultured meat. This State is characterized by its strong cultural identity and social practices, barbecue being its typical dish.

The authors applied a cross-sectional survey with meat consumers residing in Porto Alegre/RS, the sample of which, composed of 538 individuals, expressed the population heterogeneity. The data were analyzed using the Pearson chi-square, Cramer's V, and correspondence analysis.

The results demonstrate that although six of ten people were willing to try cultured meat, only four of them responded positively to the willingness to consume it over conventional meat. Young individuals demonstrated a favorable attitude towards the product, expressing a greater propensity both to try it and to include it in the diet regularly. However, the rejection of cultured meat gradually intensified after 40 years old. The previous knowledge and familiarity with the investigated subject are not predictive of the intention of experimentation so that almost two-thirds of the individuals who did not know the product were positively willing to try it.

Despite the recent intensification of studies about consumer behavior towards cultured meat, its analysis in a context in which meat historically plays a fundamental role in socioeconomic development is still little explored. The originality of our research is circumscribed by the understanding of the behavior of meat consumers, members of a culture where it plays a central role.

This paper aims to analyse how local agri-food systems (LAFS), compared to other production models, can offer innovative responses to the important environmental challenges facing food production under the twin transition. These responses are more conducive to community inclusion and local development.

The paper combines territorial development, clusters and industrial districts literature with studies on agri-food industry environmental problems and twin transition technologies to develop an agri-food systems typology. This typology is based on a territorial approach to environmental challenges of food production and serves to illustrate the ways in which LAFS can provide innovative responses to these challenges.

The study allows to visualise the differences between LAFS and other agri-food production models, showing how the operationalisation and implementation of digitisation occur at territorial level and how rural communities are involved in the process. The theoretical proposal emphasises not assuming that technology is inherently beneficial but ensuring that its implementation is inclusive and generates social value for the communities.

The paper aims to enrich future research by adopting a territorial perspective to study the twin transition challenges associated with food production systems.

Artificial Intelligence (AI) is a growing technology impacting several business fields. The agricultural sector is facing several challenges, which may be supported by the use of such a new advanced technology. The aim of the paper is to map the state-of-the-art of AI applications in agriculture, their advantages, barriers, implications and the ability to lead to new business models, depicting a future research agenda.

A structured literature review has been conducted, and 37 contributions have been analyzed and coded using a detailed research framework.

Findings underline the multiple uses and advantages of AI in agriculture and the potential impacts for farmers and entrepreneurs, even from a sustainability perspective. Several applications and algorithms are being developed and tested, but many barriers arise, starting from the lack of understanding by farmers and the need for global investments. A collaboration between scholars and practitioners is advocated to share best practices and lead to practical solutions and policies. The promising topic of new business models is still under-investigated and deserves more attention from scholars and practitioners.

The paper reports the state-of-the-art of AI in agriculture and its impact on the development of new business models. Several new research avenues have been identified.

This study aims to investigate the use of Artificial Intelligence (AI) applied to vertical farms to evaluate whether disrupting technology supports sustainability and increases strategic business model choices in the agricultural sector. The study responds through empirical analysis to the gap on the subject of AI-driven business models present in the growing sector literature.

The paper analyzes the case of “ZERO”, a company linked to the strategy innovation ecosystem of the Ca’ Foscari University of Venice, Italy. The empirical data were collected through a semi-structured questionnaire, interviews and the analysis of public news on the business model available in the analyzed case study. The research is empirical and uses exploratory, descriptive analysis to interpret the findings. The article focuses on the evaluation of AI impact on the agricultural sector and its potential to create new business models.

The study identified how AI can support the decision-making process leading to an increase in productivity, efficiency, product quality and cost reduction. AI helps increase these parameters through a continuous learning process and local production, and the possible decrease in prices directed toward the goal of zero km food with fresh products. AI is a winning technology to support the key elements of the vertical farm business model. However, it must be coupled with other devices, such as robots, sensors and drones, to collect enough data to enable continuous learning and improvement.

The research supports new research trends in AI applied to agriculture. The major implication is the construction of ecosystems between farms, technology providers, policymakers, universities, research centers and local consumer communities.

The ZERO case study underlines the potential of AI as a destructive technology that, especially in vertical farms, eliminates external conditions by increasing productivity, reducing costs and responding to production needs with adequate consumption of raw materials, boosting both environmental and social sustainability.

The study is original, as the current literature presents few empirical case studies on AI-supporting business models in agriculture. The study also favors valuable strategic implications for the policies to be adopted in favor of new business models in agriculture.

Food-related innovations might contribute to a qualitative leap in the transition to sustainable food systems. In this article, the authors map the existing literature on food and innovation in order to identify and systematise major research streams and relate them to current discussions on sustainability. The authors rely on a broad definition of innovation covering specific technological innovations as well as social, environmental and system innovations.

The authors analysed the relationship between innovation and food through bibliometric and content analysis, augmented with visualisation based on data (N = 7,987) extracted from the Web of Science. The published volume, research areas and influential journals were investigated using descriptive analyses.

This review categorises the literature on innovation and food into six main clusters, showing that most of the studies are carried out at the macro-level related to the global sustainable food systems. Network visualisation allowed them to distribute recent keywords associated with innovation across the agri-food value chain. Moreover, the authors identified environmental, social and economic pillars of innovation, which not only relate to sustainability but also are associated with open innovation as well as social innovation and eco-innovation.

This bibliometric analysis is amongst the first to examine the holistic knowledge structure surrounding a triple concept of innovation, food and sustainability. In addition, the study identifies research gaps and indicates new research directions, which add further value.

Amidst compounding crises and increasing global population’s nutritional needs, food supply chains are called to address the “diet–environment–health” trilemma in a sustainable and resilient manner. However, food system stakeholders are reluctant to act upon established protein sources such as meat to avoid potential public and industry-driven repercussions. To this effect, this study aims to understand the meat supply chain (SC) through systems thinking and propose innovative interventions to break this “cycle of inertia”.

This research uses an interdisciplinary approach to investigate the meat supply network system. Data was gathered through a critical literature synthesis, domain-expert interviews and a focus group engagement to understand the system’s underlying structure and inspire innovative interventions for sustainability.

The analysis revealed that six main sub-systems dictate the “cycle of inertia” in the meat food SC system, namely: (i) cultural, (ii) social, (iii) institutional, (iv) economic, (v) value chain and (vi) environmental. The Internet of Things and innovative strategies help promote sustainability and resilience across all the sub-systems.

The study findings demystify the structure of the meat food SC system and unveil the root causes of the “cycle of inertia” to suggest pertinent, innovative intervention strategies.

This research contributes to the SC management field by capitalising on interdisciplinary scientific evidence to address a food system challenge with significant socioeconomic and environmental implications.

The present study addresses acceptance of in vitro meat (IVM) among a predominantly student sample in Germany. It is investigated to which extent food technology neophobia, the currently followed diet and information treatments impact acceptance of IVM measured via the construct willingness to buy (WTB).

A quantitative online-survey was conducted in August 2020 using a between-subject design with three different information treatments and one control group. Moreover, the Food Technology Neophobia (FTN) scale was employed, For the statistical analysis, the χ² and Kruskal–Wallis test were used. Additionally, a binary logit model was specified and estimated in order to investigate the determinants of willingness to buy IVM accounting for the effects of gender, age, vegetarianism/veganism, FTN, prior knowledge, information treatments and potential interaction effects.

Participants following a vegan or vegetarian diet exhibit a lower likelihood of IVM acceptance in comparison to participants following an omnivore diet. However, a considerable share of vegan and vegetarian participants expressed a positive WTB. Moreover, an increasing FTN score (i.e. an increase in food technology neophobia) goes along with a reduced likelihood of acceptance, while all three information treatments increase acceptance in comparison to the control group. The largest effect on acceptance could be found for the environmental benefit treatment.

The findings show that especially among a young and highly educated sample the stressing of environmental benefits of IVM has a substantial impact on acceptance. This might be taken up in information and marketing campaigns once the product becomes available on the European market.

So far the empirical evidence on German consumers' acceptance of IVM is scarce. The present study addressed this research gap by focusing on a young sample with a high percentage of vegetarians and vegans and analyzing the role of food technology neophobia and different information treatments in a between-subject design.