Alberto Cavazza, Francesca Dal Mas, Paola Paoloni and Martina Manzo
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…
Abstract
Purpose
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.
Design/methodology/approach
A structured literature review has been conducted, and 37 contributions have been analyzed and coded using a detailed research framework.
Findings
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.
Originality/value
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.
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Keywords
Cristina Ledro, Anna Nosella and Andrea Vinelli
Due to the recent development of Big Data and artificial intelligence (AI) technology solutions in customer relationship management (CRM), this paper provides a systematic…
Abstract
Purpose
Due to the recent development of Big Data and artificial intelligence (AI) technology solutions in customer relationship management (CRM), this paper provides a systematic overview of the field, thus unveiling gaps and providing promising paths for future research.
Design/methodology/approach
A total of 212 peer-reviewed articles published between 1989 and 2020 were extracted from the Scopus database, and 2 bibliometric techniques were used: bibliographic coupling and keywords’ co-occurrence.
Findings
Outcomes of the bibliometric analysis enabled the authors to identify three main subfields of the AI literature within the CRM domain (Big Data and CRM as a database, AI and machine learning techniques applied to CRM activities and strategic management of AI–CRM integrations) and capture promising paths for future development for each of these subfields. This study also develops a three-step conceptual model for AI implementation in CRM, which can support, on one hand, scholars in further deepening the knowledge in this field and, on the other hand, managers in planning an appropriate and coherent strategy.
Originality/value
To the best of the authors’ knowledge, this study is the first to systematise and discuss the literature regarding the relationship between AI and CRM based on bibliometric analysis. Thus, both academics and practitioners can benefit from the study, as it unveils recent important directions in CRM management research and practices.
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Anette Rantanen, Joni Salminen, Filip Ginter and Bernard J. Jansen
User-generated social media comments can be a useful source of information for understanding online corporate reputation. However, the manual classification of these comments is…
Abstract
Purpose
User-generated social media comments can be a useful source of information for understanding online corporate reputation. However, the manual classification of these comments is challenging due to their high volume and unstructured nature. The purpose of this paper is to develop a classification framework and machine learning model to overcome these limitations.
Design/methodology/approach
The authors create a multi-dimensional classification framework for the online corporate reputation that includes six main dimensions synthesized from prior literature: quality, reliability, responsibility, successfulness, pleasantness and innovativeness. To evaluate the classification framework’s performance on real data, the authors retrieve 19,991 social media comments about two Finnish banks and use a convolutional neural network (CNN) to classify automatically the comments based on manually annotated training data.
Findings
After parameter optimization, the neural network achieves an accuracy between 52.7 and 65.2 percent on real-world data, which is reasonable given the high number of classes. The findings also indicate that prior work has not captured all the facets of online corporate reputation.
Practical implications
For practical purposes, the authors provide a comprehensive classification framework for online corporate reputation, which companies and organizations operating in various domains can use. Moreover, the authors demonstrate that using a limited amount of training data can yield a satisfactory multiclass classifier when using CNN.
Originality/value
This is the first attempt at automatically classifying online corporate reputation using an online-specific classification framework.
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Alexander P. Henkel, Martina Čaić, Marah Blaurock and Mehmet Okan
Besides the direct physical health consequences, through social isolation COVID-19 affects a considerably larger share of consumers with deleterious effects for their…
Abstract
Purpose
Besides the direct physical health consequences, through social isolation COVID-19 affects a considerably larger share of consumers with deleterious effects for their psychological well-being. Two vulnerable consumer groups are particularly affected: older adults and children. The purpose of the underlying paper is to take a transformative research perspective on how social robots can be deployed for advancing the well-being of these vulnerable consumers and to spur robotic transformative service research (RTSR).
Design/methodology/approach
This paper follows a conceptual approach that integrates findings from various domains: service research, social robotics, social psychology and medicine.
Findings
Two key findings advanced in this paper are (1) a typology of robotic transformative service (i.e. entertainer, social enabler, mentor and friend) as a function of consumers' state of social isolation, well-being focus and robot capabilities and (2) a future research agenda for RTSR.
Practical implications
This paper guides service consumers and providers and robot developers in identifying and developing the most appropriate social robot type for advancing the well-being of vulnerable consumers in social isolation.
Originality/value
This study is the first to integrate social robotics and transformative service research by developing a typology of social robots as a guiding framework for assessing the status quo of transformative robotic service on the basis of which it advances a future research agenda for RTSR. It further complements the underdeveloped body of service research with a focus on eudaimonic consumer well-being.
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Sara Alonso-Muñoz, Fernando E. García-Muiña, María-Sonia Medina-Salgado and Rocío González-Sánchez
This study aims to offer a research overview of circular food waste management, covering key themes and trends. It analyses state-of-the-art research in this field and proposes an…
Abstract
Purpose
This study aims to offer a research overview of circular food waste management, covering key themes and trends. It analyses state-of-the-art research in this field and proposes an agenda to guide future research.
Design/methodology/approach
This study outlines bibliometric analysis from a sample of 349 articles with VOSviewer and SciMat software to identify research trend topics.
Findings
The findings reveal a substantial amount of interest in this field. The main research topics relate to the recovery processes and valorisation of food waste and its conversion into renewable and cleaner materials or energy sources, towards circularity. However, these processes require consideration of social aspects that facilitate their implementation, which are currently under-researched.
Practical implications
Companies can target their circular food waste management by considering three key aspects. Firstly, the establishment of closer and more sustainable relationships with various stakeholders; Secondly, a regulatory framework and the support of institutions are both required for the correct implementation of circularity. Finally, what is not measured does not exist. It is therefore necessary to establish indicators to measure both the level of development of circularity in waste management and the fulfilment of the established objective.
Originality/value
This bibliometric analysis looks at the application of circularity principles in food waste management from a holistic perspective, considering different areas of knowledge.
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Akhilesh S Thyagaturu, Giang Nguyen, Bhaskar Prasad Rimal and Martin Reisslein
Cloud computing originated in central data centers that are connected to the backbone of the Internet. The network transport to and from a distant data center incurs long…
Abstract
Purpose
Cloud computing originated in central data centers that are connected to the backbone of the Internet. The network transport to and from a distant data center incurs long latencies that hinder modern low-latency applications. In order to flexibly support the computing demands of users, cloud computing is evolving toward a continuum of cloud computing resources that are distributed between the end users and a distant data center. The purpose of this review paper is to concisely summarize the state-of-the-art in the evolving cloud computing field and to outline research imperatives.
Design/methodology/approach
The authors identify two main dimensions (or axes) of development of cloud computing: the trend toward flexibility of scaling computing resources, which the authors denote as Flex-Cloud, and the trend toward ubiquitous cloud computing, which the authors denote as Ubi-Cloud. Along these two axes of Flex-Cloud and Ubi-Cloud, the authors review the existing research and development and identify pressing open problems.
Findings
The authors find that extensive research and development efforts have addressed some Ubi-Cloud and Flex-Cloud challenges resulting in exciting advances to date. However, a wide array of research challenges remains open, thus providing a fertile field for future research and development.
Originality/value
This review paper is the first to define the concept of the Ubi-Flex-Cloud as the two-dimensional research and design space for cloud computing research and development. The Ubi-Flex-Cloud concept can serve as a foundation and reference framework for planning and positioning future cloud computing research and development efforts.