Special issue of the Journal of Business Research
Artificial Intelligence and the Shaping of Business Contexts
Guest Editors: Daniela Corsaro, Charles Hofacker, Francesco Massara
Submission deadline February 1, 2019.
Artificial Intelligence (AI) is leading to automated and interconnected business processes that have implications for actors (e.g., customers, firms, and other stakeholders), relationships and experiences. The fast pace of AI and digitization, coupled with cloud-based resources, connectivity, and customizable platform-based business models, is enabling new forms of interaction that are causing business strategists and entrepreneurs to rethink their relationships with customers and other actors they serve in context.
Similarly, the workplace is also experiencing an AI-motivated paradigm shift, as “human skills” (e.g. mechanical, analytical, and intuitive) are being enhanced, if not often replaced. Huang and Rust (2018) predict that empathetic machines will become a part of the “new” labor force.
Sales and marketing automation are thus moving towards building intelligent systems that can collaborate effectively with people (Stanford University Report, 2016). According to Salesforce (2016), predictive intelligence, “lead-to-cash” process automation, and artificial intelligence are expected to experience dramatic growth in the next three years. McKinsey has forecast that by 2020 machines will manage 85% of all transactions (Baumgartner et al., 2016). More generally, advances in autonomous technologies provide challenging prospects for integrating human-based interaction with machine-to-machine interaction or more customized and contextual forms of human-to-machine interactions.
The application of AI is already on the agenda for most companies; however, many of the issues related to the impact that AI will have on various actors and their interactions remain underexplored. For example, how will AI change the logic of business models (Wieland et al., 2017) and the (re)shaping of markets (Nenonen and Storbacka, 2018). How will the service context be affected (Hartmann et al., 2018)?
Furthermore, the use of AI raises questions about the characterization of resources and attributions of agency (see Vargo and Lusch, 2017). That is, can AI be seen as an operant resource (Akaka and Vargo, 2014)? Does AI have agency?
Arguably, all of these issues come together in the consideration of market context, especially when viewed in terms of dynamic systems, such as service ecosystems (Vargo and Lusch 2016). AI can be seen as adding new dimensions of ‘resourceness’ as it increases the complexity and thus the emergent nature of markets.
Following is a non-exhaustive and non-exclusive list of issues and questions that might be addressed in response to this CFP. Other appropriately related topics are equally welcome:
What are the effects of AI on the customer experience? What constructs moderate or mediate this relationship? How will AI shape the context for value co-creation? How will it affect resource integration and service for service exchange? What is the role of technology as an operant resource? How does AI reconcile with the Actor to Actor (A2A) orientation of S-D logic? How will value be realized and appropriated when AI is involved? To what extent will automation change pricing strategies?
How will machine-human interaction nudge decision-making processes with respect to individual and collective well-being? How is AI influencing the organization of business networks? How will sales, marketing, supply chain management, operations, and (or) communication activities benefit from AI systems? What functions will be difficult to automate? How will AI influence the integration among organizational functions? How will automation and AI affect marketing and sales employees and their interaction with other actors? Is there a “dark side” to AI? What will be the impact on employment? What ethical aspects arise from AI?
We seek conceptual as well as empirical papers, both quantitative and qualitative. We especially value multi-disciplinary approaches.
Submission deadline February 1, 2019.
Guest Editors
Daniela Corsaro (corresponding editor)
Associate Professor of Marketing
IULM University
Department of Business, Law, Economics and Consumer Behavior
Via Carlo Bò, 1 – 20143 Milano, Italy
Phone: (039) 2-89141- Email: daniela.corsaro@iulm.it
Charles Hofacker
Carl DeSantis Professor of Business Administration and Professor of Marketing Florida State University – College of Business
21 Academic Way Tallahassee, FL 32306-1110
Phone: (001) 850-644-7864 – Email: chofack@business.fsu.edu
Francesco Massara
Associate Professor of Marketing
IULM University
Department of Business, Law, Economics and Consumer Behavior
Via Carlo Bò, 1 – 20143 Milano, Italy
Phone: (039) 2-89141- Email: francesco.massara@iulm.it
Stephen L. Vargo
Shidler Distinguished Professor and Professor of Marketing
University of Hawai‘i at Manoa
2404 Maile Way Honolulu HI 96822 USA
Phone (808) 956-8167- Email: svargo@hawaii.edu
The most up-to-date version of the call for papers is available on the JBR Web site.
Selected references:
Baumgartner, T., Hatami, H., VanderArk, J. (2012), Sales Growth: Five Proven Sales Strategies from the World’s Sales Leaders, John Wiley Sons, Inc.
Cantù, C., Corsaro, D., & Snehota, I. (2012). Roles of actors in combining resources into complex solutions. Journal of Business Research, 65(2), 139-150.
Dabholkar, P. A., & Bagozzi, R. P. (2002). An attitudinal model of technology-based self-service: moderating effects of consumer traits and situational factors. Journal of the academy of marketing science, 30(3), 184-201
Gensler, Volckner, Liu-Thompkins & Weirtz (2013). Managing brands in the social media environment. Journal of Interactive Marketing, 27.4: 242-256.
Hartmann, N. N., Wieland, H., & Vargo, S. L. (2018). Converging on a New Theoretical Foundation for Selling. Journal of Marketing (March).
Homburg, C., Jozic, D., & Kuehnl, C. (2017). Customer experience management: toward implementing an evolving marketing concept. Journal of the Academy of Marketing Science, 45(3), 377-401
Hofacker, Charles F., Ko de Ruyter, Nicholas Lurie, Puneet Manchanda, & Jeff Donaldson (2016), Gamification and Mobile Marketing Effectiveness, Journal of Interactive Marketing, 34, 25-36
Huang, M. H., & Rust, R. T. (2018). Artificial intelligence in service. Journal of Service Research, 1094670517752459.
Labrecque, L. I., vor dem Esche, J., Mathwick, C., Novak, T. P., & Hofacker, C. F. (2013). Consumer power: Evolution in the digital age. Journal of Interactive Marketing, 27(4), 257-269.
Lemon, K. N., & Verhoef, P. C. (2016). Understanding customer experience throughout the customer journey. Journal of Marketing, 80(6), pp. 69-96
Massara, F., Liu, S. S., & Melara, R. D. (2010). Adapting to a retail environment: Modeling consumer–environment interactions. Journal of Business Research, 63(7), 673-681.
McKinsey Global Institute (2017). “Artificial intelligence: the next digital frontier?” Discussion paper by Bughing J., Hazan E., Ramaswamy S., Chui M., Allas T., Dahlström P., Henke N., Trench M.
Moon, Y. (2000). Intimate exchanges: Using computers to elicit self-disclosure from consumers. Journal of Consumer Research, 26(4), 323-339.
Nenonen, S., & Storbacka, K. (2018). Smash: Using Market Shaping to Design New Strategies for Innovation, Value Creation, and Growth.
Salesforce.com (2016), “State of the art on Digital Marketing”, research report.
Standford University (2016), “One Hundred Year Study on Artificial Intelligence (AI100)”, research report.
Vargo, S. L., & Lusch, R. F. (2004). Evolving to a new dominant logic for marketing. Journal of Marketing, 68(1), 1-17.
Vargo, S. L., & Lusch, R. F. (2017). Service-dominant logic 2025. International Journal of Research in Marketing, 34(1), 46-67.
Wieland, H., Hartmann, N. N., & Vargo, S. L. (2017). Business models as service strategy. Journal of the Academy of Marketing Science, 45(6), 925-943.
Yadav, M. S., & Pavlou, P. A. (2014). Marketing in computer-mediated environments: Research synthesis and new directions. Journal of Marketing, 78(1), 20-40.
