Artificial intelligence-based systems applied in industrial marketing: An historical overview, current and future insights

Martínez–López, Francisco J.; Casillas, Jorge

doi:10.1016/j.indmarman.2013.03.001

Cited by 139 publications

(77 citation statements)

References 14 publications

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“…AI, as a major shift in the global economy, is influencing all aspects of human and business activities nowadays. It holds the promise to create efficiency and effectiveness by using data generated from an explosion of digital touchpoints [5], [6]. At the same time, it comes with its own concerns relating to privacy concerns, user distrust, data leakages, information transparency, and ethical concerns.…”

Section: Introductionmentioning

confidence: 99%

“…However, according to the Cognizant's report, only about 50% of surveyed 975 executives across industries in U.S. and Europe had policies and procedures in place to address ethical concerns while designing AI applications [12]. Although potential benefits emerged from AI technologies have been widely discussed in many current literatures, the sustainable outcomes from business to the society that AI presents is remained unexplored [6]. Specifically, there is an urgently need to understand how AI solutions can be designed to operate responsibly and act in a manner meeting stakeholder expectations and applicable regulations [7], [13], [14].…”

Section: Introductionmentioning

confidence: 99%

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Toward an Understanding of Responsible Artificial Intelligence Practices

Wang¹,

Xiong²

2020

Proceedings of the Annual Hawaii International Conference on System Sciences

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Artificial Intelligence (AI) is influencing all aspects of human and business activities nowadays. Although potential benefits emerged from AI technologies have been widely discussed in many current literature, there is an urgently need to understand how AI can be designed to operate responsibly and act in a manner meeting stakeholders' expectations and applicable regulations. We seek to fill the gap by exploring the practices of responsible AI and identifying the potential benefits when implementing responsible AI practices. In this study, 10 responsible AI cases were selected from different industries to better understand the use of responsible AI in practices. Four responsible AI practices are identified, including governance, ethically design solutions, risk control and training and education and five strategies for firms who are considering to adopt responsible AI practices are recommended.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Toward an Understanding of Responsible Artificial Intelligence Practices

Wang¹,

Xiong²

2020

Proceedings of the Annual Hawaii International Conference on System Sciences

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“…However, these algorithms are far from using common sense reasoning in a way that is comparable to the human. There is a surprisingly long history of this type of research (see, e.g., [51][52][53]). However, the use of new approaches in artificial intelligence there is the likelihood of success in using verbal descriptions in marketing problems.…”

Section: Discussionmentioning

confidence: 99%

Fuzzy Similarity Used by Micro-Enterprises in Marketing Communication for Sustainable Development

Schüller

Doubravský

2019

Sustainability

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The purpose of this paper is to present fuzzy reasoning as a formal tool for determining the differences in perception of individual communication channels by customers. These differences in customer perception are important for micro-enterprises to develop an effective green advertising campaign. These kinds of enterprises are not able to conduct their own extensive marketing research or use the service of marketing agencies. Micro-enterprises are the cornerstone for sustainable local economic growth where the community plays an irreplaceable role for sustainable development. Marketing communication is unique and complex because it focuses on feelings, moods, and personal preferences. The main problem is the uncertainty of this input data which makes it difficult to develop effective green advertising campaigns. Fuzzy sets and fuzzy reasoning are used to make verbal descriptions suitable for computer applications. A fuzzy pairwise similarity is used in this paper. The case study has eight relevant variables/marketing communication media, e.g., e-mailing, social networks, web pages, text messaging, newspapers, phone calls, posters and radio, and five segments of respondents selected by age. Each segment is presented as a fuzzy conditional statement. A set of fuzzy pairwise similarities is generated.

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“…Moreover, the data-based collaboration can cost-effectively develop the intelligence of industrial production/service [ 48 ]. For example, in the chemical industry, different equipment is used in different production stages, and different data are collected.…”

Section: Collaborative Sensing Intelligencementioning

confidence: 99%

Industrial Internet of Things-Based Collaborative Sensing Intelligence: Framework and Research Challenges

Chen

Lee

Shu

et al. 2016

Sensors

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The development of an efficient and cost-effective solution to solve a complex problem (e.g., dynamic detection of toxic gases) is an important research issue in the industrial applications of the Internet of Things (IoT). An industrial intelligent ecosystem enables the collection of massive data from the various devices (e.g., sensor-embedded wireless devices) dynamically collaborating with humans. Effectively collaborative analytics based on the collected massive data from humans and devices is quite essential to improve the efficiency of industrial production/service. In this study, we propose a collaborative sensing intelligence (CSI) framework, combining collaborative intelligence and industrial sensing intelligence. The proposed CSI facilitates the cooperativity of analytics with integrating massive spatio-temporal data from different sources and time points. To deploy the CSI for achieving intelligent and efficient industrial production/service, the key challenges and open issues are discussed, as well.

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Artificial intelligence-based systems applied in industrial marketing: An historical overview, current and future insights

Cited by 139 publications

References 14 publications

Toward an Understanding of Responsible Artificial Intelligence Practices

Toward an Understanding of Responsible Artificial Intelligence Practices

Fuzzy Similarity Used by Micro-Enterprises in Marketing Communication for Sustainable Development

Industrial Internet of Things-Based Collaborative Sensing Intelligence: Framework and Research Challenges

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