Establishing Relationships between Innovation Characteristics and IT Innovation Adoption in Organizations: A Meta-analysis Approach
Mumtaz Abdul Hameed
Department of Information Systems and Computing, Brunel University, Uxbridge, Middlesex UB8 3PH, UK
Steve Counsell
Department of Information Systems and Computing, Brunel University, Uxbridge, Middlesex UB8 3PH, UK
Corresponding author:
Mumtaz Abdul Hameed,
Department of Information Systems and Computing,
Brunel University,
Uxbridge,
Middlesex UB8 3PH
United Kingdom
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EstablishingRelationships between Innovation Characteristics and ITInnovation Adoption in Organizations: A Meta-analysis Approach
Abstract
This article presents the findings of a meta-analysis of innovationcharacteristics that influence the adoption of Information Technology (IT) in organizations. Past studies that examine the determinants of IT innovation adoption have produced inconsistent and contradictory results and deducing a definitive set of attributes for innovation adoption has become impractical.The study aggregated findings of past research on IT adoption using meta-analysis to identify key factors in terms of innovation or technology that influences adoption of IT in organization.Six innovation characteristics most commonly examined by researchers were analysed.The results of our meta-analysis confirmed that relative advantage, compatibility, cost, observability and trialability were strong determinants of IT innovation adoption. However, the study found no association between complexity and IT innovation adoption.The effect of stage of innovation, type of innovation, type of organization and size of organization as four moderating conditions was also examined.
Keywords: adoption of information technology; innovation adoption, meta-analysis,moderating effect.
Introduction
The adoption of innovation is the introduction of ideas, products, processes, systems and technologies regarded as novel to the adopting organization (Rogers, 1995). Innovation adoption has been examined in a variety ofacademic disciplines such as marketing, economics, communication, sociology, Information Systems (IS), education and organizational research (Fichman and Carroll, 1999).Successful innovation is essential forthe economy of any organization.
In the past two decades, research has focused on the study of technological innovation and, in particular,adoption of Information Technology(IT). The adoption of IT in an organization allows businesses to improve their efficiency and effectiveness. At present, due to the importance of IT, it is generally perceived that the organization should innovate to gain competitive advantage. It is also evident from the literature that successful IT adoption and implementation processescan create a notable performance gain and economical advantages(Rogers, 1983).Understanding how and why organizations adopt and implement IT innovations and the knowledge of underlying factors that manipulate the organizational adoption of IT helps businesses to more effectively evaluate their IT implementation.
The likely improvement of a firm’s performance and profitability are the main motives for anorganization to adopt an innovation(Zhu et al., 2006).Research has identified several other factors that influence the organization’s decision to adopt an innovation(Thong and Yap, 1995; Premkumar, 2003; Damanpour and Schneider, 2006). A number of studies have examined the factors influencing adoption of IT in an organization(Chau and Tam, 1997; Looi, 2005; Teo et al., 2009). Researchers and practitioners have attempted to examine the innovation behaviour of firms, the determinants from various contexts that influence the adoption process of ITand the processes of technological change within the organization.
IS researchers have examined various factors in different contexts that influence IT innovation adoption; however, empirical work inidentifying the characteristics of IT adoption hasproduced contrasting outcomes.For example, in identifying the factors enabling and inhibiting the adoption of Integrated Service Data Network (ISDN) in United States (US) firms, Lai and Guynes (1994) found complexity of innovation as a significant determinant, Lai and Guynes (1997) found it as an insignificant determinant. Premkumar et al., (1994) found compatibility of an innovation as a significant attribute for the adoption of Electronic Data Interchange (EDI). However, Premkumar and Ramamurthy (1995) found compatibility, irrelevant for the adoption of EDI. Similarly, Seyal and Rahman (2003) found trialability and observability of an innovation as major determinants offore-commerce adoption in organizations, yet Chang (2004) found these two attributes insignificant for e-commerce adoption.Wolfe (1994) stated that one of the major issues in the organizational innovation literature is the contradiction and disagreement among study findings. Later, Rye and Kimberly (2007) argued that one of the characteristics of innovation adoption research is the inconsistency in research findings.
The contradictory nature of innovation studies has been mostly attributed to a failure to recognize innovation antecedents and can be perceived very differently according to the specific organizational conditions involved (Wolfe, 1994). As a result, factors found to be influential in one organizational setting may not have any weight or, inversely,any impact depending on the setting.Due to the unpredictability of past findings on factors influencing the adoption of IT in organization, it has become almost impossible to define a set of attributes for innovation adoption. However, it is fundamental to identify factors that enable or inhibit its implementation processes.
IT innovation adoption has become as established research area in the IS field (Venkatesh et al., 2003). Reviewing and re-evaluating existing literature on IT innovation adoption can help researchers identify existing strengths, weaknesses and limitations of IT innovation studies and provide new opportunities for alternative research methods to explore (Venkatesh et al., 2007). Re-examining and summarizing past findings of innovation adoption research initiates novel, productive and rigorous investigations.
Motivated by these issues, this study seeks to improve our understandingof IT adoption and aims to fill the knowledge gap in the innovation adoption literature by investigating the major determinants of IT adoption in terms of innovation or technological context. It is important to address the reasons why there has been so much inconsistency in past studies on identifying the determinants of IT adoption.
The study presented aggregated the findings of past literatureexamining the relationship between innovation attributes and IT innovation adoption using meta-analysis. A meta-analysis allows (a) aggregation of the findings from large number of studies in a systematic way and the representation of samples from diverse research contexts, (b) evaluation of findings of past literature on relationships between innovation characteristics and IT innovation adoption and then (c) aggregation to obtain overall conclusions on that association. This study statistically analyzes a large collection of results from individual studies and combines them to find an average outcome.By aggregating past findings, the study aims to validate those existing findings and clarify inconsistencies that might be present in the primary studies.Furthermore, meta-analysis enabled the study to examine the effect of different research conditions (moderators) on these innovation adoption attributes.With the large amount of samples from different individual studies under different research conditions, a meta-analysis allowed the study to identify the influence of those conditions on the relationships considered.
The research question that guides this examination is ‘What are the key innovation attributes that allows a successful adoption and implementation of IT in organization”. Prior to examination of the innovation determinants, the study presents a conceptual model base on innovation literature. The modeldepicts IT adoption process and innovation factors affecting IT innovation adoption in organizations andwe identify the major innovation or technological determinants that either facilitate or hinder IT adoption. Together, the study enhances our understanding of the different research conditions that affect the relationship between the innovation characteristics and IT innovation adoption. In addition, the study enables us to understand the rationale for the inconsistency in past studies examining innovation determinants of IT adoption.
Background
ITinnovationadoption and innovation characteristics
ISliterature has identified various factors as potential determinants of IT innovation adoption in organizations (Thong and Yap, 1995)and researchers have empirically validatedvarious attributes in different contextsthat influence the adoption of IT in organizations(Iacovou, et al., 1995; Thong and Yap, 1995; Premkumar, 2003; Chan and Ngai, 2007). In general, these studiesinvestigated the influence of the characteristics of innovation, the organization, the environment in which an organization operates and of the individuals within organizations.
The foundation of the research on the adoption of new technologies emerged from Rogers (1983) innovation diffusion theory, famously known as Diffusion of Innovation (DOI). The perception of DOI is on the perceived characteristics of the innovation that either facilitates or hinders adoption. DOI has been recognized as the theoretical starting point of the research on ITinnovation adoption(Grover and Goslar, 1993). Researchers have used DOIextensively bycombining attributes from other contexts to investigate factors affecting ITadoption in organizations(Premkumar and Roberts, 1999; Seyal and Rahman, 2003; Zhu et al., 2006).
This study focuses on the association between innovation or technological characteristics and IT innovation adoption. Rogers (1995) identified relative advantage, compatibility, complexity, trialability and observability as five major innovation attributes. Table 1 shows characteristics examined in IS literature as innovation factors influencing IT innovation adoption.
Table 1: Innovation characteristics considered in literature and some references
Researchers have investigated various other innovation factors that influence the adoption of IT in organizations.Zhu et al.,(2006), in their study of e-business diffusion in European organizations tested relative advantage, compatibility, costs and security. Tan et al., (2009) examined the relationship of relative advantage, compatibility, complexity, trialability, observability, security, cost; and internet adoption barriers in Malaysian small and medium enterprises (SMEs). Mirchandani and Motwani (2001) studied the relationship between relative advantage, compatibility and cost among others in the adoption of e-commerce in US firms. Tornstzky and Klein (1982) in their meta-analysis of innovation characteristics of IT adoption considered relative advantage, complexity, communicability, divisibility, cost, profitability, compatibility, trialability, observability and social approval.
Despite contradictory findings for some innovation characteristics, research studies consider those attributes more frequently than others. To identify the key innovation determinants influencing the adoption and implementation of IT, a study needs to examine the magnitude and strength of relevant factors. Among these attributes, relative advantage, complexity, compatibility, cost, trialability and observability were most consistently found in the IS literature. Jeyaraj et al. (2006) in a literature review study found that most frequently used predictors of IT adoption in organizations among others were relative advantage, compatibility and complexity. Table 2 provides a description of each of these innovation characteristics and expected association with IT adoption.
Table 2: Key innovation characteristics and expected relationship
In the subsequent sections we describe each of these characteristics in detail.
Relative advantage
Relative advantage of an innovation is the degree to which an innovation is perceived as being better than a competing or preceding idea (Rogers, 1995). Relative advantage has been identified as one of the most significant factors driving the adoption and use of IT innovations in organizations (Iacovou et al., 1995). Relative advantage of the innovation is a key variable in all studies associated with IT innovation adoption and are frequently described in terms of direct and indirect benefits. Direct benefits are operational cost savings, improved cash flow, increased productivity and improved operational efficiency, while indirect benefits are competitive advantage, improvement in customer service, better relations with business partners and other opportunities that arise with the introduction of the innovation (Chwelos et al., 2001). Many research studies used relative advantage or perceived benefits in examining the factors affecting the adoption of IT and found to be one of the top determinants of innovation adoption. Relative advantage is expected to be positively related to the adoption of IT (Rogers, 1995).
Complexity
Complexity is the degree to which an innovation is perceived as difficult to understand and use (Rogers, 1995). Innovations that are more difficult are less likely to be adopted by organizations. Furthermore, complex innovations are unlikely to propagate a successful adoption process and hence to bring about the efficiency required. For the adoption of IT in organizations, complexity of an innovation is expected to influence negatively (Tornatzky and Klein, 1982; Seyal and Rahman, 2003).
Compatibility
Compatibility is defined as the degree to which an innovation is perceived as consistent with the needs, existing values, past experiences and technological infrastructure of the adopter (Rogers, 1995). The more incompatible the new innovation is with the existing processes and systems, the more resistance the organization will experience (Premkumar et al., 1994). Resistance to the adoption of an innovation within the organization will hinder its usage. If the innovation is compatible with the organizational needs and existing work practices, the firm is more likely to adopt it. Compatibility of an innovation is positively related to adoption and implementation of the innovation (Tornatzky and Klein, 1982).
Cost
The cost incurred in possessing an innovation is an important factor in considering the adoption and implementation of an innovation. The less expensive the innovation, the more likely it will be adopted and used by organizations (Rogers, 1995). The cost of an innovation is expected to negatively affect the adoption and implementation of the innovation. The costs incurred in adoption of new technology include administrative, implementation, training and maintenance costs. Innovation cost has been widely examined by researchers in their study of factors influencing innovation adoption (Jeon et al., 2006; Damanpour and Schneider, 2009). Cost is a critical factor in an adoption decision and a relatively easy characteristic to measure (Tornatzky and Klein, 1982; Zhu et al., 2006).
Trialability
Rogers (1995) defines ‘trialibility’ as the degree to which the innovation may be experimented with. Being able to try innovations before adoption reduces uncertainty of potential adopters; innovations that can be tried are more likely to be adopted (Tornatzky and Klein, 1982). Trialability is important in the initiation stages of adoption.However, its implication will affect the usage of the innovation. Literature suggests a positive relationship between trialability and innovation adoption (Rogers, 1995).
Observability
Observability is the degree to which the results and the advantages of an innovation are visible to others (Rogers, 1995). Observability is sometimes referred to as ‘visibility’. The more visible or observable the usage and the outcome of the innovation, the more likely the innovation will be adopted and implemented in organizations (Tornatzky and Klein, 1982). Observability is expected to have a positive relationship with innovation adoption (Rogers, 1995).
Effects of research conditions on the association between innovation attributes and IT innovation adoption
Studies examining the relationship between innovation characteristics and IT adoption showed inconsistency in their findings. Damanpour (1991) asserts that IT innovation adoption research conducted in different research conditions often produces varying results.Also, Abdul Hameed et al. (2012) emphasizes that the boundary conditions with which the research was performed may affect the results obtained for association between innovation characteristics and IT innovation adoption. Hence, the effect of different research conditions or moderator conditions needs to be explored to verify whether these different research boundaries influence the relationship between innovation characteristics and IT adoption and are expected to affects the strength and direction of the relationship between innovation characteristics and IT adoption. Four most common contextsunder which relationship between innovation factors and IT adoption examined were stage of innovation, type of innovation, type of organization and size of organization.The next four sub-sections describe each of the four moderator conditions.
Stage of innovation
The process of innovation adoption has been divided into multiple stages in the IS literature. Rogers (1983) described innovation adoption as a three stage processes as initiation, adoption-decision and implementation. Hage and Aiken (1970) define four stages as evaluation, initiation, implementation and routinization. Kwon and Zmud (1987) divided innovation adoption into: initiation, adoption, adaptation, acceptance, routinization and infusion. Zaltman et al., (1973) explain five stages as: knowledge awareness, attitude formation, decision, initial implementation and sustained implementation. More recently, Angle and Van de Ven (2000) group innovation adoption into initiation, development, implementation and termination. The study by Darmawan (2001) describes a four stage innovation model presented as initiation, adoption, implementation and evaluation.
Although researchers split the adoption process into various stages, all these phases fit into three groups of pre-adoption, adoption-decision and post-adoption stages consistent with Rogers’ (1983) model of initiation, adoption-decision and implementation. Initiation (pre-adoption) stage consisting of activities related to recognizing a need, acquiring knowledge or awareness, forming an attitude towards the innovation and proposing innovation for adoption (Rogers, 1995; Gopalakrishnan and Damanpour, 1997). The adoption-decision stage described by Meyers and Goes (1988)reflects the decision to accept the idea through negotiations to obtain the organizational backing at various level of the organizational hierarchy and evaluate the proposed ideas from a technical, financial and strategic perspective, together with the allocation of resources for its acquisition and implementation. Implementation stage (post-adoption) involves preparing the organization for use of the innovation, performing a trial for confirmation of innovation, acceptance of the innovation by the users and continued actual use of the innovation. This ensures that the innovation becomes ingrained and developed into a routine feature of the organization with expected benefits being realized (Rogers, 1995).
Type of innovation
Innovation is the implementation and acceptance of procedures, practices, processes, systems, products, technologies or services that are new to the adopting organization (Rogers, 1995). There are many different classifications of innovation typesin the IT adoption literature; however, there is a little consistency in their definitions.Among the different types of innovation identified by the researchers is product versus process, technical versus administrative and radical versus incremental (Damanpour, 1991).
Product innovation can be defined as the introduction of a product or service which significantly improves operations. Process innovation, on the other hand, is the implementation of new system or process which changes a method of working and associated procedures. Some variation in adoption activities and distinctive organizational skills required in the adoption of product and process innovation has been identified (Utterback and Abernathy, 1975; Damanpour and Gopalakrishnan, 2001).