Relationships between Wireless Technology Investment and Organizational Performance

Relationships between Wireless Technology Investment and Organizational Performance

Laurence Mukankusi, Jared Keengwe, Yao Amewokunu, Assion Lawson-Body
DOI: 10.4018/978-1-60566-014-1.ch164
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Abstract

Information technology (IT) investments are justified based on average improvement in performance (Peacock & Tanniru, 2005). Firms rely on those investments (Demirhan, Jacob, & Raghunathan, 2002; Duh, Chow, & Chen, 2006; Tuten, 2003) because executives believe that investments in wireless technologies help boost company performance. In this regard, the benefits from wireless technology applications depend on the extent to which they are congruent with the firm’s performance (Duh et al., 2006). But, some IS researchers argue that competitors may easily duplicate investments in IT resources by purchasing the same hardware, software, and network, and hence resources necessarily do not provide sustained performance (Santhanam & Hartono, 2003). The use of wireless communications and computing is growing quickly (Kim & Steinfield, 2004; Leung & Cheung, 2004; Yang, Chatterjee, & Chan, 2004). The future of wireless technology may also bring more devices that can operate using the many different standards and it may be possible that a global standard is accepted, such as the expected plans for the 3G technology UMTS. The wireless beyond 3G (B3G) systems or the so called composite radio environments (CRE) (or even 4G systems) possess multiple features that allow employees to collaborate with each other and provide diverse access alternatives (Kouis, Domestichas, Koundourakis, & Theologou, 2007). But issues of risk and uncertainty due to technical, organizational, and environmental factors continue to hinder executive efforts to produce meaningful evaluation of investment in wireless technology (Smith, Kulatilaka, & Venkatramen, 2002). Despite the use of investment appraisal techniques, executives are often forced to rely on instinct when finalizing wireless investment decisions. A key problem with evaluation techniques that emerges is their treatment of uncertainty and their failure to account for the fact that outside of a decision to reject an investment outright, firms may have an option to defer an investment until a later period (Tallon, Kauffman, Lucas, Whinston, & Zhu, 2002). In addition, many authors believe that if firms can combine the appropriate investment strategies to create a unique wireless technology capability, superior firm performance can be the result. Utilization of wireless devices and being “connected” without wires is inevitable (Gebauer, Shaw, & Gribbins, 2004; Jarvenpaa, Lang, Reiner, Yoko, & Virpi, 2003). Market researchers predict that by the end of 2005, there will be almost 500 million users of wireless devices, generating more than $200 billion in revenues (Chang & Kannan, 2002; Xin, 2004). And by 2006, the global mobile commerce (m-commerce) market will be worth $230 billion (Chang & Kannan, 2002). Such predictions indicate the importance that is attached to wireless technologies as a way of supporting business activities. Evaluating investments in wireless technology and understanding which technology makes the “best fit” for a company or organization performance is difficult because of the numerous technologies and the costs, risks, and potential benefits associated with each technology.
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Introduction

Information technology (IT) investments are justified based on average improvement in performance (Peacock & Tanniru, 2005). Firms rely on those investments (Demirhan, Jacob, & Raghunathan, 2002; Duh, Chow, & Chen, 2006; Tuten, 2003) because executives believe that investments in wireless technologies help boost company performance. In this regard, the benefits from wireless technology applications depend on the extent to which they are congruent with the firm’s performance (Duh et al., 2006). But, some IS researchers argue that competitors may easily duplicate investments in IT resources by purchasing the same hardware, software, and network, and hence resources necessarily do not provide sustained performance (Santhanam & Hartono, 2003).

The use of wireless communications and computing is growing quickly (Kim & Steinfield, 2004; Leung & Cheung, 2004; Yang, Chatterjee, & Chan, 2004). The future of wireless technology may also bring more devices that can operate using the many different standards and it may be possible that a global standard is accepted, such as the expected plans for the 3G technology UMTS. The wireless beyond 3G (B3G) systems or the so called composite radio environments (CRE) (or even 4G systems) possess multiple features that allow employees to collaborate with each other and provide diverse access alternatives (Kouis, Domestichas, Koundourakis, & Theologou, 2007). But issues of risk and uncertainty due to technical, organizational, and environmental factors continue to hinder executive efforts to produce meaningful evaluation of investment in wireless technology (Smith, Kulatilaka, & Venkatramen, 2002). Despite the use of investment appraisal techniques, executives are often forced to rely on instinct when finalizing wireless investment decisions. A key problem with evaluation techniques that emerges is their treatment of uncertainty and their failure to account for the fact that outside of a decision to reject an investment outright, firms may have an option to defer an investment until a later period (Tallon, Kauffman, Lucas, Whinston, & Zhu, 2002). In addition, many authors believe that if firms can combine the appropriate investment strategies to create a unique wireless technology capability, superior firm performance can be the result.

Utilization of wireless devices and being “connected” without wires is inevitable (Gebauer, Shaw, & Gribbins, 2004; Jarvenpaa, Lang, Reiner, Yoko, & Virpi, 2003). Market researchers predict that by the end of 2005, there will be almost 500 million users of wireless devices, generating more than $200 billion in revenues (Chang & Kannan, 2002; Xin, 2004). And by 2006, the global mobile commerce (m-commerce) market will be worth $230 billion (Chang & Kannan, 2002). Such predictions indicate the importance that is attached to wireless technologies as a way of supporting business activities. Evaluating investments in wireless technology and understanding which technology makes the “best fit” for a company or organization performance is difficult because of the numerous technologies and the costs, risks, and potential benefits associated with each technology.

The purpose of this study is twofold: first, to identify and discuss different investment options, and second, to assist in formulating a wireless technology investment strategy for increasing organizational performance. This article is organized as follows. The next section outlines wireless technology investments and organizational performance. The third section contains major uncertainties and risks in the field of wireless technologies. In the fourth section, wireless technology and IT investment tools are examined. In the fifth section, formulating a wireless technology investment strategy is discussed. The conclusion of this article is presented in the sixth section.

Key Terms in this Chapter

Semantic Web: Provides us with common formats for the interchange of data related to real world objects. It is similar to the WWW, which enables the interchange of documents, but aims to become an environment for automated processing in addition to human browsing.

Self-Organizing Map (SOM): A simulated neural network based on a grid of artificial neurons by means of prototype vectors. In an unsupervised training the prototype vectors are adapted to match input vectors in a training set. After completing this training the SOM provides a generalized K-means clustering as well as topological order of neurons.

Environmental Scanning: The way in which managers study their relevant marketing environment; comprises both looking for and looking at information available in the business environment.

Information Structure: Partition of the information environment in meaningful topic clusters.

Competitive Intelligence (CI): CI is characterized as (1) the process of acquiring, analyzing, and evaluating any information about known and potential competitors systematically or (2) actionable information gained in this process.

Information Foraging Theory (IFT): Explains information-seeking behavior of humans similar to food foraging. Basic elements are the perceived information “scent” of media (names, key words, etc.) and costs (particularly, by means of search time) for accessing the media.

Intelligent Agents: A software entity that acts on behalf of the user to reduce both work and information load. It operates continuously and autonomously in a defined target environment.

Information Infrastructure: An element of IFT, which is made up by all knowledge already gained on the topic under consideration.

CI-Spider: Starting from a URL provided by a user, the CI Spider automatically retrieves, summarizes, and categorizes the content in linked pages using noun phrases and graphical concept maps.

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