Here is the regular update on my key research outputs from the last 12 months. I continued to write mostly about AI and Big Data as managerial and social phenomena and as mechanisms for studying markets. There is also a paper about food waste recycling behaviours, which is a bit of a departure for me… though, sustainability issues are an old interest of mine: my very first publication, back in 1994, was, exactly, on that topic.
The purpose of this yearly catch up posts is to make it easy for you to see what I have been working on, and to encourage you to reach out if you want discuss how my research can help your organisation or how we can work together.
Journal articles
- Keegan, B. J., Canhoto, A. I. & Yen, D. (2022). Power negotiation on the tango dancefloor: The adoption of AI in B2B marketing. Industrial Marketing Management, 100, 36-48. https://doi.org/10.1016/j.indmarman.2021.11.001
Abstract:
Acknowledging the lack of empirical research on the adoption of AI in B2B marketing and the research gap in studying power from a network perspective, this paper explores how the drivers of AI adoption as marketing solutions affect network actors’ power dynamics. Using data collected through 20 semi-structured interviews with business managers and engineers involved in AI adoption for B2B marketing activities, as well as academic experts in the field of AI, this paper discusses how AI adoption priorities and motives shape the power dynamics amongst the various network actors, including focal firms, AI suppliers and tech giant companies. The findings show that, in the context of AI adoption in B2B, both technology and expertise are key sources of power, and that data creates and perpetuates power negotiations and renegotiations in the network. We envisage this process as the movements on a busy dancefloor where groups of actors are engaged in what we refer to as the Power Tango. This paper contributes to the power dependence theory by showing that, through the adoption process, network actors’ power is exchanged, exercised, counter-balanced and perpetuated, creating fluid network dynamics.
Highlights
- AI adoption process creates fluid power dynamics amongst AI service network actors.
- B2B AI service network actors include focal firms, AI suppliers and tech giants.
- AI technology, expertise and data are actors’ power sources.
- Actors’ power exchanges and negotiations resemble the moves in Tango dance.
- The network resembles the Tango dancefloor, where multiple actors jostle for space.
Keywords: Artificial intelligence, Third-party suppliers, Power, Service network, Power dependence, Network dynamics
You can find a blog post, here.
- Canhoto, A. I. & Brough, A. R. (2022). The ca Explosion. Social Marketing Quarterly. doi:10.1177/15245004221076858
Abstract:
Background
Government and private responses to the COVID-19 pandemic resulted in the generation and dissemination of personal data not previously available in the public sphere.
Focus of the Article
This “Notes from the Field” paper reflects on the implications of this surge of new data for the study and practice of social marketing. The paper examines how this phenomenon impacts on the following aspects of social marketing: (1) Setting of explicit social goals; (2) citizen orientation and focus; (3) value proposition delivery via the social marketing intervention mix; (4) theory-, insight-, data-, and evidence-informed audience segmentation; (5) competition/barrier and asset analysis; and (6) critical thinking, reflexivity, and being ethical.
Research Question
How are the government and private responses to the pandemic shaping the generation and use of personal data, and what are the implications of this eruption of data for the social marketing scholarly community?
Approach
The paper highlights how the pandemic resulted in significant changes in behaviour of government and citizens alike, and how these changes, in turn, spurred the generation and dissemination of new personal data. Subsequently, we draw on the Core Social Marketing Concepts framework to explore how the aforementioned data explosion impacts on the six dimensions of this central framework.
Importance to the Social Marketing Field
The COVID-19 pandemic is more than a temporary public health event. Therefore, it is important to consider the lasting consequences that may stem from the pandemic-induced personal data explosion, for both consumers and social marketing scholars and practitioners.
Methods
This paper comments on a topical matter, and discusses its implications for the social marketing community.
Results
We find that the data explosion creates conflicting social marketing goals, and that inequalities in access to digital technology are increasingly impacting what voices are heard, and which concerns are prioritized. Moreover, new innovations may be enabled or needed, leading to the improvement of firms’ ability to create value for individual citizens; the creation of new datasets—particularly among demographics that previously had a limited digital footprint—enhances the ability to segment markets and target social marketing activities. Furthermore, the pandemic-induced data explosion may lead to the identification of additional barriers to positive social behaviours that have emerged, diminished, or even disappeared during the pandemic; but researchers need to critically examine the consequences of the government and private behaviours at the macro, meso, and micro levels.
Recommendations for Research or Practice
We propose a research agenda for the social marketing community, consisting of 21 research questions.
Limitations
Our analysis focuses on the behaviour of government and citizens in North America and Western Europe.
Keywords: Covid-19, Big Data, Open data, Strategy, Social marketing,
You can find a related blog post, here.
- Manika, D., Iacovidou, E., Canhoto, A., Pei, E. and Mach, K. (2022) ‘Capabilities, opportunities and motivations that drive food waste disposal practices: A case study of young adults in England’. Journal of Cleaner Production, 370.. 1 – 15. DOI: https://doi.org/10.1016/j.jclepro.2022.133449
Abstract:
Data in England suggests that food waste is still being disposed into the black bin, also known as residual waste, despite continuous efforts to promote separate food waste collection and food waste reduction practices. Furthermore, it has been anecdotally reported that 18 to 30-year-olds have the highest propensity to generate large amounts of food waste and thus need to be urgently engaged in communication that helps them change their behaviour. This study aims to explore young adults’ capabilities (C), opportunities (O), and motivations (M) that may lead to a certain behaviour (B) towards food waste disposal practices (FWDP) grounded on the Behaviour Change Wheel, also called the COM-B model, and could reveal barriers to action. In doing so, a case study approach is used via Harrow Council residents in England within the age group of 18–30 years old. The study took place amid the national lockdown due to the Covid-19 pandemic and targeted young residents within the 18–30 age group using a structured interview approach with a diagnostic questionnaire promoted through Harrow Council’s social media account, followed by in-depth interviews with eligible participants. Out of the 30 residents who completed the diagnostic questionnaire, 35% reported no FWDP, 42% partial FWDP (i.e., some incorrect items in the black bin waste), and 23% reported engaging in FWDP. The first two groups only were invited to the online interviews. The interview results are organised using the COM-B model and reveal that: 1) due to Covid-19 there was a shift to home cooking and increased food waste generation (B); 2) there is a lack of FWDP knowledge, information on benefits, and advice on alleviating pests/health concerns from councils, whereas FWDP differences between councils and reliance on ‘common sense’ often create confusion around FWDP (C); 3) the council may not always provide a caddy or a drop-off/collection service, whereas economic (caddy liners purchase) and logistic concerns (e.g., the lack of a regular collection schedule, unfavourable features of the caddy, and lack of prompts/reminders) resulted to limited uptake of FWDP as the norm (O); 4) the benefits of FWDP do not outweigh costs, while feelings of disgust and a sense of inconvenience lead to lack of or partial FWDP (M). To our knowledge, this is the first study using the COM-B model within the context of FWDP and with a specific focus on young adults in England. Novel theoretical and practical insights are discussed, along with limitations and future research directions.
Keywords: Food waste disposal practices, Domestic food waste, Residents, Young adults, England, Behaviour change wheel
You can find a related blog post, here.
Book chapter
- Canhoto, A. I. (2022). Approaches to emotion and sentiment analysis. in The SAGE Handbook of Digital and Social Media Marketing. Editors: Hanlon A, Tuten TL . 2: 127-145. Sage, London 28 Jun 2022
Abstract:
Given the importance of emotions in the outcome of marketing initiatives, and the ubiquity of digital and social media in everyday life, marketing scholars as well as marketing practitioners are interested in identifying and analysing online displays of consumers’ emotions. The analysis of sentiment displayed in online content can assist marketers in anticipating consumer behaviour and, where pertinent, take remedial action.
This chapter outlines techniques for studying sentiment online, and is organised as follows. In the first section, we review the techniques for identifying and collecting sentiment data, in the digital environment. We illustrate their application in different marketing areas, and discuss their relative advantages and disadvantages. Then, in the subsequent section, we turn our attention to techniques for analysing digital sentiment data, in order to detect the sentiment valence and arousal level. We also consider the use of technological tools to process and classify digital sentiment data. Namely, we discuss how software can assist in processing the large volumes of data available online, depending on the goal of the analysis. This chapter concludes with a discussion of the challenges of conducting sentiment analysis, both those related to the study of sentiment per se, and those related to the use of technology to automate the analysis process.
Keywords: Sentiment analysis, emotions, automation, online conversations
Others
Another key research output this year was my participation in the House of Lords’ Public Services Committee looking at “A public services workforce fit for the future”.
There is a video here; and the full report is accessible here.
If you would like to know more about the work underpinning these outputs, or if you think that we can work together, don’t hesitate to get in contact.
Ana Canhoto 