Industrial Machine to Machine Technologies

Introduction

Shaping the Future of Industrial Marketing, Special issue of Industrial Marketing Management; Deadline 1 Sep 2018

Industrial Marketing Management

Call for Papers

Industrial Machine to Machine Technologies – Shaping the Future of Industrial Marketing

Deadline for submission: 1 September 2018

Overview and Purpose

The aim of this special issue is to assess the current state and possible future avenues of both theory development and industrial marketing practices for companies using the industrial machine to machine (M2M) internet technologies to advance their business.

Different types of machines have been independently communicating using different standards in wired and wireless way for decades (Kaufman 1966; Mathews, Wilson and Backhaus 1977). This special issue focuses on recent developments on this area namely industrial machine to machine information technologies. Specific area is the industrial marketing impacts of the industrial M2M information technologies which can be fully automated or need some human intervention via e.g. human machine interface (HMI) e.g. panels.

M2M technology enables any device e.g. sensor attached to machine to capture an event (e.g. pressure change) and send that information via for example a fixed line or smart phone networks to an application that translates that into meaningful information (e.g. tire pressure of a mining dumper has lowered radically – alert for assistance). Devices such as sensors can communicate metered or otherwise received data e.g. inventory level, price change, humidity, temperature etc. to other devices and machines (Internet of Things / Internet of Future). Increasingly, firm are implementing artificial intelligent and machine learning to infuse M2M with long desired intelligence – smart manufacturing etc. As M2M enables direct and synchronous communication between machines it also creates opportunities for marketers.

Devices can be part of bigger machines while machines might be connected to internal and external networks of machines. As individual machines are integrated to networks of machines, the biggest power of M2M can be unleashed. Geographically dispersed devices, sensors and machines form value networks that corporates manage e.g. when the inventory level information or price change in one location is recorded and transmitted forward, the application software can act upon the information autonomously based on some decision rule. Or human intervention can also be called for e.g. to place orders to replenish inventory. Besides common industrial marketing processes that are influenced by M2M there are industry specific challenges.

In the manufacturing e.g. automotive and elsewhere industrial robots that are part of M2M network perform many types of tasks from material handling to welding and panting (Michalos et al., 2010). Critical questions to address are among others fault detection and alarm limits that will influence several business critical processes including service levels and order taking.

In the steel industry business relationships the steel hardness information has been for long time send via wireless networks which enables the steel hardening company immediately fill in the gap in the production line (Salo, 2012).

Besides the manufacturing and steel industries, transportation industry (cars, busses, trucks and rental) is one of the key focus area to observe the change brought by M2M. Both telematics and autonomous vehicles (Diss 2015; Simonite 2016) are changing the industrial logistics. In the truck industry truck producer Volvo offers Telematics Gateway to increase the up time of trucks which is similar to Scandia’s fleet management service. Additionally, precision agriculture enables real-time management of farms and wineries (Lohr, 2015) while oil and gas industries and others have myriad of internal M2M applications and outward looking M2M applications e.g. enabling the remote management.

Overall, it can be stated that M2M is changing the processes how value is created, communicated and captured in multiple industries. To deepen and widen our theoretical and practical understanding of the influences brought by M2M on industrial marketing we urge scholars and practitioners to focus upon these or other key issues. We seek manuscripts that draw on multiple methodologies including qualitative, quantitative, case study or triangulation of methods. All manuscripts should have clear relevance to the industrial/B2B or business market domain.

Possible topics include, but are not limited to:

  • How is M2M/IoT altering value creation and capture in industrial markets?
  • What markets are emerging due to M2M and how do these markets influence industrial marketing?
  • How the type of M2M platforms (open or closed) influences industrial marketers?
  • How are after sales and industrial services marketing altered due to M2M? E.g. challenges and benefits of M2M remote management e.g. health management of fleet of similar machines e.g. cars, busses, trucks and airplanes.
  • What is the role and need of buyer or seller intervention in M2M operations and management?
  • How M2M is impacting industrial sales? E.g. integrating M2M outputs to Salesforce.com and similar software as well as other API’s.
  • What are the influences of near-zero downtime imperative enabled by M2M on selling, ordering and other marketing functions?
  • How M2M alters current buyer-seller relationships and business networks (e.g. value network, supply chain/network or other hybrid organization)?
  • How pricing practices and strategies are changed due to increased price transparency enabled by M2M?
  • How is M2M influencing the patterns of communications between industrial actors?
  • What kind of industrial marketing capabilities and talent is required in different marketing areas and functions to cope with change brought by M2M?
  • How is marketing decision making changed with digital analytics and metrics data of M2M?
  • How is the nature of industrial work changing due to M2M e.g. industrial robots, sensors and telematics
  • How is marketing management and measurement altered/improved by M2M?
  • How digital analytics, artificial intelligence and/ or machine learning influence above or other topics in the industrial marketing?

Other topics are also welcome as long as they relate with Industrial Machine to Machine Technologies and how they shape industrial marketing. Papers submitted to Industrial Marketing Management should be explicit about the contribution to industrial/B2B marketing or business markets.

Manuscript Preparation and Submission

To submit a paper please visit the IMM editorial site at

https://www.evise.com/profile/#/IMM/register.

Please login, register as an author, and submit the paper as the site will instruct you. Submissions are welcome no later than 1 September 2018. When you get to the step in the process that asks you for the type of paper, select SI: Industrial Machine to Machine Technologies. All papers will be reviewed through the standard double-blind peer review process of IMM. In preparation of their manuscripts, authors are asked to follow the Author Guidelines closely. A guide for authors, sample articles and other relevant information for submitting papers are available at:

https://www.elsevier.com/journals/industrial-marketing-management/0019-8501/guide-for-authors.

All queries about the special issue should be sent to the Guest Editor (see below).

Guest Editor

Jari Salo, Professor of Marketing, Department of Economics and Management, University of Helsinki, Jari.Salo@helsinki.fi

References

Diss, K. (2015), “Driverless trucks move all iron ore at Rio Tinto’s Pilbara mines, in world first.” Accessed August 9th, http://www.abc.net.au/news/2015-10-18/rio-tinto-opens-worlds-first-automated-mine/6863814.

Kaufman, E. (1966), “Data Systems That Cross Company Boundaries,” Harvard Business Review, 41(January-February), 141-155.

Lohr, S. (2015),. Data-ism: The revolution transforming decision-making, consumer behavior, and almost everything else, New York, NY: Harper Business.

Mathews, L.E., Wilson, D.T. and Backhaus, K. (1977), “Selling to the Computer Assisted Buyer,” Industrial Marketing Management, 6 (4), 307-315.

Michalos, G., Makris, S., Papakostas, N., Mourtzis, D., & Chryssolouris, G. (2010), “Automotive assembly technologies review: challenges and outlook for a flexible and adaptive approach,”CIRP Journal of Manufacturing Science and Technology, 2 (2), 81-91.

Salo, J. (2012), “The role of mobile technology in a buyer-supplier relationship: a case study from the steel industry,” Journal of Business & Industrial Marketing, 27 (7), 554-563.

Simonite, T. (2016), “Mining 24 Hours a Day with Robots,” Accessed August 9th, https://www.technologyreview.com/s/603170/mining-24-hours-a-day-with-robots/