Guest editorial: Market transformation to an IT-enabled services-oriented economy

Publication Type

Editorial

Publication Date

10-2015

Abstract

In the past decade, we have observed the fast growth of new IT-enabled service markets. For example, entertainment companies offer online music. Mature firms and start-ups sell video and gaming services. Meanwhile, high-tech firms provide data storage, software applications, and computing power as web-based services. Physicians deliver healthcare services through electronic platforms, and financial firms promote mobile banking and electronic stock trading to clients as IT-based financial services. We have also witnessed the emergence of the new on-demand economy or the sharing economy, as business press observers have called it.

In these industries and economic contexts, firms have created transformational services with powerful, new technological approaches to support freelance workforces and create market coordination approaches that enable them to become service providers in ways we have not seen before. How firms conduct these new forms of business, their evolving cost structures and risks, and the way consumers respond to and interact with them all have changed too. This new economy is more IT-enabled and service-oriented than ever before.

This special issue on “Market Transformation to an IT-Enabled Services-Oriented Economy” was initiated in mid-2013 with support from incoming Editor-in-Chief, James Marsden, and completed in mid-2015. The primary intention of the guest editors, Robert J. Kauffman, Dan Ma, and Byungjoon Yoo, was to encourage new research that examines IT-enabled transformations in services markets — new value chains, innovative partnerships, and novel business models, as well as new products, services, competitive strategies, and market structures. We have chosen five representative articles out of a larger number of submissions to showcase empirical research using statistics and econometrics, and theoretical research using economic models — all with innovative applications. These articles have gone through an initial screening and a developmental process involving two to three rounds of rigorous review and revision to ensure topical relevance for the special issue theme, depth of insight and richness in the contribution of new knowledge, and thoughtful and readable writing. We provide a brief overview of these articles next.

The lead article, “Information transparency in prediction market” by Annie Shengyun Yang, Ting Li, and Eric van Heck, analyzes the impact of information transparency on the efficiency and accuracy of a prediction market. Prediction markets are popular new market mechanisms that are based on the aggregation of information to establish prices as proxies for the expectation and prediction of uncertain future events. The authors implemented a field experiment to show how information – the key commodity in prediction markets – is disclosed and disseminated by the IT support services of a prediction market's infrastructure. This increases the level of trader interaction by supporting the sharing of information market-wide. The theoretical contribution consists of observations about how IT-enabled information transparency affects prediction market performance, in terms of information aggregation efficiency and predictive accuracy. The authors further hypothesize that better performance occurs when trader participation activity and dynamic interactions are supported well. To test their hypotheses, the authors constructed twelve prediction markets for their field experiment. They showed that improved information transparency, via the disclosure of traders' buy and sell orders, led to more trader interaction. This, in turn, led to improved efficiency in information aggregation and prediction accuracy. A counter-intuitive result in this research is that full disclosure and information transparency may not always improve prediction market trading. This result is evocative of earlier findings in the information economics literature – for example, Ronald Hilton [1] in Management Science in 1981 suggested some general determinants of the value of information – that can be revisited in contemporary research on IT-enabled prediction markets.

The second article, “Pricing strategy for cloud computing: A damaged services perspective” by Jianhui Huang, Robert J. Kauffman and Dan Ma, looks at vendor-side value-maximizing pricing strategies in cloud computing services markets. The authors discuss Amazon's EC2 services delivery and pricing practices as starting points for their exploration. They develop an economic model of duopoly competition between cloud computing services vendors, based on prior research on information goods, revenue-managed pricing, and software product versioning. The business model they analyze includes the hybrid services offering of reserved-services contracts, as well as interruptible spot-price on-demand contracts for cloud computing. Their model incorporates self-selecting business customers and spot-price services interruption risks that can be leveraged to improve the vendors' profits, and enhance market efficacy. A key contribution to knowledge in this research is that interruptible spot-price services can be viewed as damaged services, similar to the way that software applications can be more effectively sold to different kinds of customers as products with full or limited functionality, according to Bhargava and Choudhary [2] in 2008 Management Science article. It turns out that this distinction for cloud computing is highly valuable for the vendor that implements this kind of strategy, and typically outperforms a one-service only strategy. This research is the first in the literature to identify the business value of the damaged services strategy approach.

The next article, by Xiao Zou and Ke-Wei Huang, is entitled “A model on location-based service as infomediary and couponing channel.” The authors offer a new perspective on infomediation with location-based services (LBS), and compare its use to the services offered by traditional Internet infomediaries. LBS applications are location-focused smartphone-based means of sensing information about different customer groups. The authors view LBS apps as a new mobile commerce-related channel for product and service delivery. They support understanding consumer behavior and faster consumer decision-making, acquiring new customer information, refining a firm's market segmentation analytics, enhancing seller profitability, and promoting higher social welfare. The authors focus on LBS apps for digital couponing, using an economic model of competition with price dispersion with horizontal differentiation. They note that LBS's capacity to identify consumers' locations allows the sellers to price higher early on, and then shift later to lower prices so as to not hold back revenue production in the market. This research emphasizes an aspect of IT-enabled services market transformation that is pushing toward location-aware and time-sensitive selling and customer acquisition.

The penultimate article is by Sanghee Lim and Byungtae Lee. They examined “Loyalty programs and dynamic consumer preference in online markets.” Their research with an economic model of firm competition suggests that loyalty program promotion strategies, which have proven to be effective in traditional markets over the years, deserve closer investigation in online retail markets. Consumer preferences in the 2010s are more dynamic due to the high level of informedness that has become common, based on Internet search, mobile phones, and business websites. This dynamic aspect makes the information from the loyalty program more valuable and important for customer retention. Meanwhile, the cost for a consumer to visit a digital store is much lower in the online environment. Not only have we seen dramatic improvements in consumer informedness, we also have seen online service providers that are now able to leverage their much higher level of firm informedness. Through this, they can now develop deep insights on the impact and power of online services, such as loyalty programs and other means of promotion, when the conditions in the marketplace are different. The authors show the importance of analyzing transaction-level data to obtain business, consumer and social insights, especially for an online retailer. They emphasize the value of investments in data mining technologies and the new management and data analytics capabilities that can be developed around them. This also was discussed by Chang, Kauffman and Kwon [3] in a 2014 Decision Support Systems article on the ongoing shift in the knowledge discovery research paradigm shift in the presence of big data.

The final contribution, “Exploring the influence of the online physician service delivery process on patient satisfaction” by Hualong Yang, Xitong Guo and Tianshi Wu, concludes this special issue. Their research studies the impact of information systems on IT-enabled online healthcare services. The authors show what service factors affect the patient's satisfaction in an online healthcare services platform. They find that, during the provision of the new online services, the response speed and frequency of interactions with their physicians generally increase the satisfaction level of patients. An especially interesting insight from their empirical research is that the perceived risk of a patient's health problem has a moderating effect on the interaction between the physician's response speed in the service delivery process and the patient's level of satisfaction. The authors' results for these hypotheses were established based on survey methods in behavioral research that focused on an online health community. These are among the first results that we know of in the IS research literature that shows IT-enabled healthcare support services need to be designed with in-depth knowledge of how they affect the quality of care that patients experience from their services providers.

The Guest Editors would like to thank the reviewers, who provided timely and constructive reviews for the special issue articles, and the authors who were responsive to all the comments and made an effort to continuously improve the quality of their research work. Without their dedication and expertise, this special issue would not have been possible. We also want to thank DSS's Editor in Chief, James Marsden, for his kind guidance, as well as its Journal Managers, V Mahalakshmi and Greg Zacharewicz, for their strong support in the process of developing this special issue. We hope that the articles in this special issue will help motivate and energize other authors to do research at the forefront of new knowledge on IT-enabled transformations in various kinds of services markets.

Discipline

Computer Sciences | Management Information Systems

Research Areas

Information Systems and Management

Publication

Decision Support Systems

Volume

78

First Page

65

Last Page

66

ISSN

0167-9236

Identifier

10.1016/j.dss.2015.05.012

Publisher

Elsevier

Additional URL

https://doi.org/10.1016/j.dss.2015.05.012

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