Forecasting the next revolution: food technology’s impact on consumers' acceptance and satisfaction

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nuria Recuero-Virto ◽  
Cristina Valilla-Arróspide
Keyword(s):  
Artificial Intelligence ◽  
Circular Economy ◽  
Food Industry ◽  
Design Methodology ◽  
Social Progress ◽  
Technological Innovations ◽  
Text Data ◽  
Content Type ◽  
Innovative Solutions ◽  
Twitter Users

PurposeIn a sector that needs to satisfy a fast-increasing population, advancements like cultivated meat and bio-circular economy are basic to sustain the industry and the society. As innovations are key for economic and social progress, it is crucial to understand consumers' position on this matter.Design/methodology/approachBased on text data mining, 7,030 tweets were collected and organised into 14 different food-related topics. Of the total, 6 of these categories were positive, 5 were negative and 3 were neutral.FindingsIn total, 6 categories related to food technologies were positively perceived by Twitter users, such as innovative solutions and sustainable agriculture, while 5 like the virtual dimensions of the industry or crisis-related scenarios were negatively perceived. It is remarkable that 3 categories had a neutral sentiment, which gives ground to improvement before consumers have a negative opinion and consequently will be more complicated to change their minds.Originality/valueTechnological innovations are becoming predominant in the food industry. The SARS-CoV-2 pandemic has made the sector improve even faster. Traditional methods needed to be substituted and technologies such as robots, artificial intelligence, blockchain and genetics are here to stay.

Warehouse robot market boosted by Covid pandemic and technological innovations

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Robert Bogue
Keyword(s):  
Artificial Intelligence ◽  
Design Methodology ◽  
Technological Innovations ◽  
Future Prospects ◽  
Short Introduction ◽  
Mixed Product ◽  
Content Type ◽  
Market Growth ◽  
Technological Developments ◽  
Robotic Automation

Purpose This paper aims to provide details of recent commercial and technological developments that are driving robotic warehouse automation. Design/methodology/approach Following a short introduction, this first provides a commercial background and identifies the factors driving the market growth. It then gives examples of robotics companies, products and applications that exploit innovations in artificial intelligence (AI). It then considers future prospects, and finally, brief conclusions are drawn. Findings Amazon’s acquisition of Kiva led to a community of new robot manufacturers and the realisation by major e-commerce companies that robotic automation would be required to maintain competitiveness. The Covid pandemic caused a surge in e-commerce and a critical shortage of labour, which further highlighted the need for automation and boosted robotic deployments. Recent advances in AI have resulted in a rapidly growing community of companies producing AI-powered robots which offer advanced capabilities such as mixed product picking, sorting and kitting. These are being deployed by a growing number of e-commerce and logistics companies and are paving the way towards ever-higher levels of warehouse automation. Full automation will soon become a reality. Originality/value This paper identifies the factors driving the rapidly developing warehouse robot business by considering the companies, products, technology and applications.

The circular economy meets artificial intelligence (AI): understanding the opportunities of AI for reverse logistics

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Matthew Wilson ◽  
Jeannette Paschen ◽  
Leyland Pitt
Keyword(s):  
Artificial Intelligence ◽  
Reverse Logistics ◽  
Circular Economy ◽  
Design Methodology ◽  
Emerging Technology ◽  
Future Research ◽  
Entrepreneurial Ecosystem ◽  
Content Type ◽  
Entrepreneurial Opportunities ◽  
Logistics Process

PurposeTechnology is an important force in the entrepreneurial ecosystem as it has the potential to impact entrepreneurial opportunities and processes. This paper explores the emerging technology of artificial intelligence (AI) and its implications for reverse logistics within the circular economy (CE). It considers key reverse logistics functions and outlines how AI is known to, or has the potential to, impact these functions.Design/methodology/approachThe paper is conceptual and utilizes the literature from entrepreneurship, the CE and reverse logistics to explore the implications of AI for reverse logistics functions.FindingsAI provides significant benefits across all functions and tasks in the reverse logistics process; however, the various reverse logistics functions and tasks rely on different forms of AI (mechanical, analytical, intuitive).Research limitations/implicationsThe paper highlights the importance of technology, and in particular AI, as a key force in the digital entrepreneurial ecosystem and discusses the specific implications of AI for entrepreneurial practice. For researchers, the paper outlines avenues for future research within the entrepreneurship and/or CE domains of the study.Originality/valueThis paper is the first to present a structured discussion of AI's implications for reverse logistics functions and tasks. It addresses a call for more research on AI and its opportunities for the CE and emphasizes the importance of emerging technologies, particularly AI, as an external force within the entrepreneurial ecosystem. The paper also outlines avenues for future research on AI in reverse logistics.

Autonomous vehicles: a review of the ethical, social and economic implications of the AI revolution

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shweta Banerjee
Keyword(s):  
Artificial Intelligence ◽  
Autonomous Vehicles ◽  
Design Methodology ◽  
Technological Advancement ◽  
Economic Implications ◽  
Content Type ◽  
The Public ◽  
Autonomous Cars ◽  
The Subject ◽  
Practical Implications

PurposeThere are ethical, legal, social and economic arguments surrounding the subject of autonomous vehicles. This paper aims to discuss some of the arguments to communicate one of the current issues in the rising field of artificial intelligence.Design/methodology/approachMaking use of widely available literature that the author has read and summarised showcasing her viewpoints, the author shows that technology is progressing every day. Artificial intelligence and machine learning are at the forefront of technological advancement today. The manufacture and innovation of new machines have revolutionised our lives and resulted in a world where we are becoming increasingly dependent on artificial intelligence.FindingsTechnology might appear to be getting out of hand, but it can be effectively used to transform lives and convenience.Research limitations/implicationsFrom robotics to autonomous vehicles, countless technologies have and will continue to make the lives of individuals much easier. But, with these advancements also comes something called “future shock”.Practical implicationsFuture shock is the state of being unable to keep up with rapid social or technological change. As a result, the topic of artificial intelligence, and thus autonomous cars, is highly debated.Social implicationsThe study will be of interest to researchers, academics and the public in general. It will encourage further thinking.Originality/valueThis is an original piece of writing informed by reading several current pieces. The study has not been submitted elsewhere.

How to survive in the age of artificial intelligence? Exploring the intelligent transformations of SMEs in central China

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jinqiang Wang ◽  
Yaobin Lu ◽  
Si Fan ◽  
Peng Hu ◽  
Bin Wang
Keyword(s):  
Artificial Intelligence ◽  
Small And Medium Enterprises ◽  
Policy Support ◽  
Central China ◽  
Limited Resources ◽  
Text Data ◽  
Content Type ◽  
External Pressures ◽  
Medium Enterprises

PurposeThe purpose of the research is to explore how small and medium enterprises (SMEs) in central China achieve intelligent transformation through the use of artificial intelligence (AI). Because of unequal resource allocation, constraints on the intelligent transformation of SMEs in central China are different from those in economically and technologically well-developed coastal provinces. Hence, the authors focus on SMEs in central China to identify drivers of and barriers to intelligent transformation.Design/methodology/approachThe interview data were collected from 66 SMEs across 20 industries in central China. To verify the validity of the data collection method, the authors used two methods to control for retrospective bias: multi-level informants and enterprises' AI project application materials (Wei and Clegg, 2020). The final data were validated without conflicts. Next, the authors cautiously followed a two-step approach recommended by Venkatesh et al. (2010) and used NVivo 11.0 to analyze the collected text data.FindingsSMEs in central China are enthusiastic about intelligent transformation while facing both internal and external pressures. SMEs need to pay attention to both internal (enterprise development needs, implementation cost, human resources and top management involvement) and external factors (external market pressure, convenience of AI technology and policy support) and their different impacts on intelligent transformation. However, constrained by limited resources, SMEs in central China have been forced to take a step-by-step intelligent transformation strategy based on their actual needs with the technological flexibility method in the short term.Originality/valueConsidering the large number of SMEs and their importance in promoting China's economic development and job creation (SME Bureau of MIIT, 2020), more research on SMEs with limited resources is needed. In the study, the authors confirmed that enterprises should handle “social responsibility” carefully because over-emphasizing it will hinder intelligent transformation. However, firms should pay attention to the role of executives in promoting intelligent transformation and make full use of policy support to access more resources.

Intention to use analytical artificial intelligence (AI) in services – the effect of technology readiness and awareness

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Carlos Flavián ◽  
Alfredo Pérez-Rueda ◽  
Daniel Belanche ◽  
Luis V. Casaló
Keyword(s):  
Artificial Intelligence ◽  
Technology Adoption ◽  
Design Methodology ◽  
Technology Readiness ◽  
Intention To Use ◽  
Content Type ◽  
Financial Investment ◽  
Managerial Implications ◽  
Barriers To Technology

PurposeThe automation of services is rapidly growing, led by sectors such as banking and financial investment. The growing number of investments managed by artificial intelligence (AI) suggests that this technology-based service will become increasingly popular. This study examines how customers' technology readiness and service awareness affect their intention to use analytical AI investment services.Design/methodology/approachThe automation of services is rapidly growing, led by sectors such as banking and financial investment. The growing number of investments managed by AI suggests that this technology-based service will become increasingly popular. This study examines how customers' technology readiness and service awareness affect their intention to use analytical AI investment services.FindingsThe results indicated that customers' technological optimism increases, and insecurity decreases, their intention to use robo-advisors. Surprisingly, feelings of technological discomfort positively influenced robo-advisor adoption. This interesting finding challenges previous insights into technology adoption and value co-creation as analytical AI puts customers into a very passive role and reduces barriers to technology adoption. The research also analyzes how consumers become aware of robo-advisors, and how this influences their acceptance.Originality/valueThis is the first study to analyze the role of customers' technology readiness in the adoption of analytical AI. The authors link the findings to previous technology adoption and automated services' literature and provide specific managerial implications and avenues for further research.

How can open innovation contribute to circular economy adoption? Insights from a literature review

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Gessica Mina Kim Jesus ◽  
Daniel Jugend
Keyword(s):  
Circular Economy ◽  
Open Innovation ◽  
Design Methodology ◽  
Web Of Science ◽  
Joint Effort ◽  
Content Type ◽  
Environmentally Sustainable ◽  
Scientific Databases ◽  
Sustainable Products ◽  
Practical Implications

PurposeDespite the potential of open innovation (OI) to reduce barriers to the adoption of the circular economy (CE), little is known about the integration of the two themes and how OI could contribute to a more sustainable economy. The objective of this study is to investigate how OI can contribute to the adoption of the CE.Design/methodology/approachThis study adopts a systematic review of the literature sampled from the Scopus and Web of Science scientific databases.FindingsThe main findings of the study are (1) the utilization of OI within CE is still a recent phenomenon, one which emphasizes the collaboration between stakeholders and the co-creation approach; (2) the collaboration of stakeholders can be applied to align the objectives of interested parties, in a joint effort to resolve the environmental problems of the three levels of CE and (3) an action-creation approach can be adopted as a strategy to encourage the participation of consumers in the development of environmentally sustainable products, which may favor the transition to the CE.Originality/valueThe article presents the state of the art on the CE guided by OI, highlighting the opportunities and challenges of the correlation between the two themes. The article also shows the theoretical and practical implications for an OI-driven circular economy.

scholarly journals High tech meets high touch in upscale hotels

2016 ◽  
Vol 7 (4) ◽  
pp. 347-365 ◽  
Author(s):  
Ana Brochado ◽  
Paulo Rita ◽  
Ana Margarido
Keyword(s):  
Design Methodology ◽  
New Technologies ◽  
High Tech ◽  
Technological Innovations ◽  
Content Type ◽  
Hotel Websites ◽  
Hotel Managers ◽  
The Impact ◽  
Qualitative Phase ◽  
Business Travellers

Purpose This paper presents an analysis of the impact of current technologies on customer experiences in upscale hotels and assesses the potential of the latest technologies for enhancing customers’ stay. Design/methodology/approach A two-step approach was applied in this study. The qualitative phase included an examination of upscale hotel websites, interviews with hotel managers and an internet search regarding the latest technological innovations in hotels. In the quantitative stage, a questionnaire was developed for hotel guests, generating a sample of 310 valid completed questionnaires. Findings The results reveal that hotel guests value digital involvement in their hotel experience. Moreover, business travellers and younger generations give greater importance to latest technologies. Originality/value This study analyses the most innovative technologies, providing guidance for hoteliers wishing to upgrade or implement new technologies. Based on the findings, hoteliers can achieve greater differentiation by offering the most important and latest technology to guests, enhancing their experience and attracting new customers, which can potentially lead to increased revenues. The study’s results are also important because they include the perceptions of both managers and customers.

Do Twitter phenomena check-in popular venues on Foursquare too?

2018 ◽  
Vol 46 (3) ◽  
pp. 137-146
Author(s):  
Aysun Bozanta ◽  
Birgul Kutlu
Keyword(s):  
Clustering Analysis ◽  
Design Methodology ◽  
Business Owners ◽  
Marketing Strategies ◽  
The Other ◽  
Shopping Mall ◽  
Content Type ◽  
History Of ◽  
Twitter Users ◽  
Different Characteristics

Purpose The purpose of this study is to figure out the visiting behaviors of the users who have different characteristics on Twitter. Design/methodology/approach The visit history of users who share their Foursquare check-ins on Twitter and the characteristics of visited venues (category, check-in count, tip count, like count, rating, and price tier) was collected with Foursquare API. In addition, the number of followers, friends, tweets and favorite-count were collected via Twitter API. First, users were clustered according to their Twitter related attributes. After that, profiling was applied on clusters according to the characteristics of the venues that were visited by the users. Findings Clustering analysis generated three clusters, namely, ordinary, talkative and popular. For each cluster, the visited venues were investigated according to the price classification, check-in, like, tip counts and the categories. The users in ordinary class prefer cheaper venues rather than talkative and popular users. On the other hand, popular users prefer the venues with the highest average number of check-ins, likes and tip counts. The top two categories for all clusters are cafe and shopping mall. Originality/value This study differentiates from the other studies in the literature by examining the data from Twitter with clustering and profiling these clusters with Foursquare data to understand venue preferences of Twitter users having various characteristics. The findings of this study will provide new insights for business owners to understand the customers more comprehensively and design better marketing strategies.

Risk culture and banking supervision

2017 ◽  
Vol 25 (2) ◽  
pp. 209-226 ◽  
Author(s):  
Alessandro Carretta ◽  
Vincenzo Farina ◽  
Paola Schwizer
Keyword(s):  
Cultural Differences ◽  
European Central Bank ◽  
Design Methodology ◽  
Central Banks ◽  
Banking Union ◽  
Banking Supervision ◽  
Text Data ◽  
Content Type ◽  
European Central ◽  
Risk Culture

Purpose This paper aims to analyzing the main risk culture traits of a sample of Central Banks and Supervisory Authorities in Europe as well as of the European Central Bank (ECB). Design/methodology/approach Risk culture is measured through text data processing of the official discourses made by the head Supervisory Authorities, during the years from 1999 to 2012. Findings Results highlight heterogeneous but converging risk cultures for European Union (EU) supervisors and the presence of a “distance” between these cultures and the risk culture of the ECB. Originality/value The paper points out that cultural differences, especially in presence of credit markets still characterized by poor integration, could create unwanted distortion effects during the initial stages of the Banking Union.

Software documentation is not enough! Requirements for the documentation of AI

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Florian Königstorfer ◽  
Stefan Thalmann
Keyword(s):  
Artificial Intelligence ◽  
Business Process ◽  
Design Methodology ◽  
Governance Mechanism ◽  
It Industry ◽  
Specific Nature ◽  
Content Type ◽  
Software Documentation ◽  
Disruptive Technologies ◽  
Present Information

Purpose Artificial intelligence (AI) is currently one of the most disruptive technologies and can be applied in many different use cases. However, applying AI in regulated environments is challenging, as it is currently not clear how to achieve and assess the fairness, accountability and transparency (FAT) of AI. Documentation is one promising governance mechanism to ensure that AI is FAT when it is applied in practice. However, due to the nature of AI, documentation standards from software engineering are not suitable to collect the required evidence. Even though FAT AI is called for by lawmakers, academics and practitioners, suitable guidelines on how to document AI are not available. This interview study aims to investigate the requirements for AI documentations. Design/methodology/approach A total of 16 interviews were conducted with senior employees from companies in the banking and IT industry as well as with consultants. The interviews were then analyzed using an informed-inductive coding approach. Findings The authors found five requirements for AI documentation, taking the specific nature of AI into account. The interviews show that documenting AI is not a purely technical task, but also requires engineers to present information on how the AI is understandably integrated into the business process. Originality/value This paper benefits from the unique insights of senior employees into the documentation of AI.

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