Propensity to adopt technological innovations: the impact of personal characteristics and organizational context

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Abstract

This study investigated how personal characteristics and organizational context are associated with strategic decision makers' intentions to adopt technological innovations. Positive significant relationships were found between hospital top managers' intentions to adopt potential innovations and risk propensity, self-efficacy, perceived organizational strategy, perceived information processing capacity, and perceived resource availability. The impact of personal and organizational factors on intentions to adopt, implications of our results, and future research directions are discussed.

Introduction

Courses of action taken by organizations in responding to increasing environmental complexity and turbulence reflect the strategic decisions their top managers make (Hambrick and Mason, 1984). In attempts to explain how and why organizational responses to similar environmental stimuli may change, several researchers have focused on cognitive activities of top managers (e.g., Thomas and McDaniel, 1990; Gioia and Chittipeddi, 1991; Schneider and De Meyer, 1991; Lant et al., 1992). The complicated and unstructured nature of strategic issues (Mintzberg et al., 1976) makes top managers' cognitive “sensemaking” processes critically important for the outcome of the strategic decision process (Thomas et al., 1993). For organizations striving to gain and maintain a competitive advantage in today's increasingly dynamic and complex industry environment, a strategic issue that is of paramount importance is the adoption of organizational innovations from the external environment (Schewe, 1996). This paper examines the acquisition of radical organizational innovations from the external environment within a strategic decision making framework.

We adopt the definition of an innovation as “any idea, practice, or material artifact perceived to be new by the relevant unit of adoption” (Zaltman et al., 1973; p. 10). Similarly, Rogers and Shoemaker (1971)define innovation as “an idea, practice, or object perceived as new by the individual” (p. 19). The common element in both of these definitions is that what matters is whether the product (or idea, process, practice or object) is new according to the perceiving individual or adopting unit. Whether it is new objectively is not important as long as it seems new to the adopting unit. A radical innovation, besides being new to the organization, is also radically different from the current organizational practices, and thus, requires significant changes in organizational processes, behaviors, and structure (Nord and Tucker, 1987). Innovation radicalness varies with the degree of change it brings on the existing systems (Zaltman et al., 1973; Damanpour, 1988). External acquisitions of radical organizational innovations represent strategic issues since they involve major changes in organizations' structuring and resource usage patterns.

Previous studies of innovation diffusion have predominantly explored the relationship between innovation adoptions and organizational level variables (Kim, 1980; Damanpour, 1987Damanpour, 1988). For example, Damanpour (1991), in a meta-analysis of 23 empirical studies, found significant positive relationships between innovation and organizational attributes such as specialization, professionalism, and communication. Saleh and Wang (1993)investigated factors such as entrepreneurial strategy, organizational structure and climate that differentiate innovative from less-innovative organizations. On the individual characteristics side, many studies have explored the impact of the role and characteristics of key persons or champions of innovation management and implementation (Chakrabarti, 1974, Howell and Higgins, 1990b; Chakrabarti and Hauschildt, 1989; Allen, 1985; Howell and Higgins, 1990aHowell and Higgins, 1990b; Ancona and Caldwell, 1992). For example, Howell and Higgins (1990a), Howell and Higgins (1990b)found that champions of innovations take higher risks, are more innovative, and exhibit charismatic leader behaviors. Chakrabarti and Hauschildt (1989)suggested guidelines for facilitating division of labor between technical experts, sponsors, and champions of projects. Yet, there is a considerable lack of theory development, and corresponding empirical investigation, addressing the impacts of both individual variables and organizational context on innovation adoptions within strategic decision making contexts.

Given the increasing rate of change and innovation in most environments, industries, and organizations, an understanding of the effects of personal and organizational contexts on innovation adoption decisions may assist in our understanding of how strategic decision makers interpret and respond to potential innovations. Perceived effects of innovations on organizational performance lead decision makers to respond in a certain way. For example, there is evidence that perceived organizational “performance gaps” initiate a search for innovation (Zaltman et al., 1973) and that innovations are adopted with the intent of increasing organizational performance (Damanpour, 1990, Damanpour, 1991). Decision makers attribute meanings to innovations, resulting in intention to respond, and more specifically, in the acceptance or non-acceptance of new technology (Agarwal and Prasad, 1997; Tabak and Barr, 1998). The purpose of this study is to investigate the relationship between personal factors, organizational context, and decision makers' intentions to adopt radical innovations for their organizations. The study's focus is on decision makers' cognitive representations of potential innovations as the primary means of examining how individual and organizational factors might affect innovation decisions.

Section snippets

Organizational adoption of radical innovations

Organizational adoption of an innovation, like any other strategic issue, is an event perceived by decision makers to have a potential impact on the future effectiveness of the organization (Ansoff, 1980; Dutton et al., 1983). In understanding innovation decision making, one must identify why the same or similar innovations are perceived differently by top managers and how perceptions are linked to intentions. Previous research in strategic decision making has sought to address this question

Sampling and data collection procedures

We chose the hospital industry to test our hypotheses. Hospitals operate in highly competitive, and rapidly changing industry environments in which top managers are frequently involved in interpreting and responding to strategic issues such as innovation adoption decisions (Topping and Hernandez, 1991; Arndt and Bigelow, 1992; Jansen et al., 1994). The American Hospital Association's (AHA) definition of “community hospitals” was used. This definition includes all non-federally owned hospitals

Results

Table 1 presents means, standard deviations, and correlations for all dependent and independent variables included in this study. Examination of the means in Table 1 shows that, in general, the decision makers interpreted innovations as positive with a mean of 65.88% intention to adopt. Sixty-eight percent of the respondents was male. The average age was 44.

Multiple regression analyses were performed to test all hypotheses simultaneously. All independent variables were entered simultaneously

Discussion

In this study, we developed and tested a model of the determinants of top managers' intentions to adopt radical organizational innovations. Most research examining innovation diffusion have focused on structural determinants (Damanpour, 1991). Knowledge of how individual and organizational contexts jointly affect the decision making process has been lacking. The results of this research suggest that studies investigating organizational phenomena should include effects of both individual and

Implications and directions for future research

Future research should explore other industries and organization sizes to evaluate innovation adoption in organizations. Two potential research questions to address are: “Do the effects of predictors vary from one industry to another?” and “Do the effects of different predictors vary with organization size?” Again, we need to point out that since our data were cross-sectional, we could only guess the direction of influence between personality factors, organizational factors and intentions to

Acknowledgements

The authors thank Gary Dickson, Gregg Young, Editor-in-Chief, Michael K. Badawy, and the anonymous reviewers for their helpful comments and suggestions on earlier versions of this paper.

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