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International Journal of Productivity and Performance ManagementEmerald Article: Antecedents And Outcomes Of Human Resource Information System (HRIS) UseNormalini Md. Kassim, Ramayah T., Sherah Kurnia
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This is an EarlyCite pre-publication article: Normalini Md. Kassim, Ramayah T., Sherah Kurnia, (2012),"Antecedents And Outcomes Of Human Resource Information System (HRIS) Use", International Journal of Productivity and Performance Management, Vol. 61 Iss: 6 (Date online 20/6/2012)
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Erik Beulen, (2009),"The contribution of a global service provider's Human Resources Information System (HRIS) to staff retention in emerging markets: Comparing issues and implications in six developing countries", Information Technology & People, Vol. 22 Iss: 3 pp. 270 - 288http://dx.doi.org/10.1108/09593840910981446
Indrit Troshani, Cate Jerram, Sally Rao Hill, (2011),"Exploring the public sector adoption of HRIS", Industrial Management & Data Systems, Vol. 111 Iss: 3 pp. 470 - 488http://dx.doi.org/10.1108/02635571111118314
E.W.T. Ngai, F.K.T. Wat, (2006),"Human resource information systems: a review and empirical analysis", Personnel Review, Vol. 35 Iss: 3 pp. 297 - 314http://dx.doi.org/10.1108/00483480610656702
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Antecedents And Outcomes Of Human Resource Information System (HRIS) Use Author Details Author 1 Name: Normalini Md. Kassim Department: School of Management University/Institution: Universiti Sains Malaysia Town/City: Penang Country: Malaysia Author 2 Name: T. Ramayah Department: School of Management University/Institution: Universiti Sains Malaysia Town/City: Penang Country: Malaysia Department: Department of Information Systems University/Institution 2: The University of Melbourne Town/City: Carlton Country: Melbourne Author 3 Name: Sherah Kurnia Department: Department of Information Systems University/Institution: The University of Melbourne Town/City: Carlton Country: Melbourne Corresponding author: T. Ramayah Corresponding Author’s Email: [email protected] Acknowledgments (if applicable): n/a Biographical Details (if applicable): n/a Structured Abstract: Purpose - The purpose of this paper is to test some antecedents and outcomes of Human Resource Information System (HRIS) Use in Malaysia. Design/methodology/approach - A research model based on questionnaire gleaned from the literature was used to collect data through a purposive sampling technique whereby only those companies who are using HRIS were targeted in Penang, Malaysia. The data collected was analyzed using structural equation modelling technique with the use of partial least squares (PLS) approach. Findings - Results show that 4 out of the 5 antecedents are significant predictors of extent of use and that extent of use is significantly related to all 5 outcome variables. This study provides further evidence on the appropriateness of using Roger’s innovation attributes to measure different dimensions of attitude towards extent of HRIS use and Remenyi’s and Zuboff’s IT framework to measure the outcomes from the extent of HRIS use. Research limitations/implications - Firstly, this study cannot be generalized to all other individuals as the respondents are confined to HR professional employees in local services companies and multinational companies. Therefore, the results cannot be generalized to individuals working in other industries. Secondly, the study’s is carried out using a particular type of technological innovation which is HRIS system in this case. As such, the research needs to be replicated to examine the robustness of the findings across a wider range of technologies solution and samples. Practical implications - The findings also suggest that IT appears to serve as an empowering function for HR professionals, providing a medium in which HR professionals can provide increased value in their work. The study will also help organizations in the implementation or deployment of new information technology products, systems or processes. Organization can now ensure a smoother implementation plan by addressing the attributes of the innovation that its employees will most likely to have concern with. Originality/value - This paper adds to the existing literature of HRIS antecedents and outcomes in a developing country setting. Although there has been some research on the same issue but the number is very small in comparison to the literature appearing from the developed countries. Keywords: Human resource management, Implementation, Information systems, Innovation, Performance Article Classification: Research paper
Antecedents And Outcomes Of Human Resource Information System (HRIS) Use
INTRODUCTION
A human resource information system (HRIS) is a system used to acquire, store, manipulate, analyze, retrieve, and distribute pertinent information about an organization’s human resource (Tannenbaum, 1990). Initially, such a system was used in human resource management to support transaction processing and maintain management control. A good human resource decision is more likely to follow from a good human resource information system (HRIS). Such a system should therefore be provided to both human resource and line managers to facilitate decision making. Systems of this type are discussed in the literature under the heading of decision-support-systems (DSS). For example, optimization techniques can provide a powerful foundation for the development of spreadsheet decision support systems to assist supply chain members to negotiate and make decisions that are the best for their supply chain (Beheshti, 2010). A HRIS is made up of various elements and if one element does not function properly, it could well cause the function of the entire system to fail. When all elements work correctly and the system works properly it should benefit the organization. Similarly the HRIS is usually a part of the organization’s larger management information system (MIS), which would include accounting, production, and marketing functions, to name just a few. The special function of HRIS is to gather, collect, and help analyze the data necessary for the human resource department to do its job properly (Anthony, Kacmar, & Perrewe, 2002). The HRIS can improve administrative efficiency through faster information processing, improved employee communications, greater information accuracy, lower HR costs and overall HR productivity improvements (Dery, Grant, & Wiblen, 2009; Wiblen, Grant, & Dery, 2010). HRIS can facilititate strategic value generation by helping design and implement internally consistent policies and practices that ensure that human assets contribute to achieving business objectives (Boateng, 2007). The most salient factor impacting organizations and employees today is technological change. This can be seen in areas such as computer-supported work-at-home, overall changes in labour force skills, and changes in organizational structure and organization of work. Information technology (IT) has grown substantially in recent years and driven much of this change. (Roach, 1991) found that in 1991 American service sector companies spent more than $100 billion on hardware and in 1996 American banks spent almost $18 billion on IT (The Economist, 1996). One implication is that the nature of work is likely to shift as IT has the potential to change the roles of employees within the organization. However, Gardner, Lepak, and Bartol (2003), found that almost 75% of all IS projects are never completed, while between one-third and one-half of all IS projects never reach the implementation stage. In a survey conducted by Price Waterhouse, 25 per cent of senior executives responsible for IS project implementation in the financial services sector reported that over 50 per cent of IS projects end in failure (Carr & Lee, 1994). With such bleak percentages, it is clearly important for management to continually examine their processes and not become complacent or satisfied. Unfortunately, the operational processes of online companies are difficult to formulate, as evidenced by their high failure rates (Sameer, Brett, & Josie, 2010).
Recent studies have examined determinants of HRIS adoption in Singapore (Teo, Lim, & Fedric, 2007) and the degree to which HRIS can enable strategic focus of HR (Dery et al., 2009; Wiblen et al., 2010). According to Indrit et al. (2011), the adoption of HRIS in the public sector depends on environmental, organizational, and technology context factors. In the last decade (1995-2005), concerted efforts have been made by the Malaysian government to provide a stronger platform for the country‘s transition to a knowledge-based society (Eight Malaysian Plan, 2000-2005; Ninth Malaysian Plan., 2006-2010). E-government is variously defined but the common focus is on the application of ICT to improve the internal management of the government, to offer more flexible and convenient services to the public and to a limited extent, enhance public participation and democracy. HRIS has been a part of the improvements suggested and carried out under the e-government initiatives of the Malaysian government under the ambitious Multimedia Super Corridor (MSC). Another initiative introduced is e-procurement which is called e-Perolehan, which was to streamline the process of government procurement and was tied closely to the computerization of the adminstration. Kaliannan, Awang and Raman (2007) studied the electronic procurement system and highlighted issues inherent within Malaysia’s e-Perolehan initiative that prevent the government and the service provider from maximizing the value potential of the e-Perolehan system are cost, infrastructure and skills, business focus or change management, system constraints and government policy. The need for efficient and effective performance management systems (PMS) has increased over the last decade. The use of PMS has improved the performance and overall quality of an organization (Burgess, Ong & Shaw, 2007; Cuthbertson & Piotrowicz, 2011; Waal & Counet, 2009). According to Temple (2000), many smaller companies already use service providers for HR-related systems such as payroll, and training departments are rapidly utilising online classes as well as video technology. With this growth in IT utilization, practitioners and researchers alike recognize that IT may have a tremendous impact on the different functions, including HR, and individuals in the organization (Gardner et al., 2003). Ulrich (1997), for instance, has argued that, “technology will change how work is done in general and how HR (human resources) is practiced in particular”. As the human resource management function increases its use of IT, there are likely to be implications for HR professionals as well (Sparrow & Daniels, 1999). As more HR professionals are able to be more responsive, answer queries more quickly, and provide more accurate information, HRIS may enable HR professionals to increase their responsiveness to their constituencies. Although companies have spent millions of dollars on implementing various information systems, usage among end users remains low (Schaupp, Carter, & McBride, 2010) especially in developing countries. This has been higlighted in E-government (Lean, Zailani, Ramayah & Fernando, 2009), online stock trading (Ramayah, Rouibah, Muniandy & Rangel, 2009), e-learning (Ramayah, 2010) and E-HRM (Yusoff, Ramayah & Ibrahim, 2011). This is not good as the investment is already a sunk cost and if the system is not used then it is deemed to have failed. Despite the importance of HRIS for organizations, there is still a limited understanding of what deternines the successful use of HRIS in a developing country like Malaysia. The next section of this paper discusses the theoretical foundation. This is followed by an explanation of the research model and the hypotheses. Next, the method used is described before the findings are covered. This includes an assessment of goodness of measures, namely, construct validity, convergent validity, discriminant validity and reliability of the
constructs. Subsequent sections deal with discussion, implications, limitations and conclusion.
THEORETICAL FOUNDATION
The adoption and diffusion of innovation is a subject that has been widely studied across a broad spectrum of disciplines, including social science, marketing, engineering and management. Diffusion of innovation literature has been developed across a number of disciplines to explain the flow of information, ideas, practices, products, and services within and across cultures and subcultures, or market segments. For example, Rogers (1983) in his diffusion of innovation theory identified compatibility, relative advantage, complexity, trialability and observability as characteristics of an innovation that influence its adoption. Subsequent research provided empirical support for compatibility, relative advantage and complexity (Tornatzky & Klein, 1982). On the other hand, in the IT literature, one of the most prominent frameworks of IT (technological innovation) impact includes three stages of use: automation, information, and transformation (Remenyi, Money & Twite, 1991; Zuboff, 1988). This framework of IT impact is developmental in that each stage but must be developed for the technology to be accessed or exploited. For the purpose of this study, we have combined both theoretical perspectives to better understand the influence of various perceived attributes of innovations on the extent of use of HRIS system and the impacts of this HRIS system usage. There have been numerous studies on innovation, spanning many disciplines and focusing on both organizational and individual levels. In his innovation diffusion theory, Rogers (1983) proposes that innovation adoption is a process of uncertainty reduction and information gathering. Information about the existence of the innovation as well as about its characteristics and features flows through the social system within which adopters are situated. Potential adopters engage in information-seeking behaviors to learn about the expected consequences of using the innovation: and an assessment and evaluation of this information determines adoption behavior. Thus, communication channels and information processing by potential adopters play a central role in Roger’s theory. In his innovation diffusion theory, an individual’s decision to adopt or not adopt a particular innovation is influenced by five key perceptions about the characteristics of the innovation: relative advantage, compatibility, complexity, trialability, and observability. A short description of each of the constructs is presented below.
Relative Advantage
Rogers (2003) defines relative advantage ais the degree to which an innovation is perceived to be better than the idea it supersedes. It can also be viewed as the degree to which an innovation is perceived to bring added benefits to the user. Hence, it is often measured in terms of economic profitability, productivity improvement and other benefits. The nature of the innovation determines which specific types of relative advantage it brings to the end user. The adoption of an innovation depends on whether the expected benefits of an innovation matches the demand of potential adopters. In the Technology Acceptance Model (TAM) by Davis (1989), this particular attribute is referred to as perceived usefulness. In general, the relative advantage of an innovation as perceived by members of a social system is positively related to its rate of adoption.
Compatibility
Rogers (2003) states that compatibility is the degree to which an innovation is perceived as consistent with the existing values, past experiences, and needs of potential adopters. An idea that is more compatible with the existing values and norms is less uncertain to the potential adopters and hence fits more closely to an innovation that can be easily accepted by potential adopters into part of their lifestyle. An innovation can be compatible or incompatible with (1) socio-cultural values and beliefs, (2) previously introduced ideas, or (3) client needs for the innovation.
Complexity
Rogers (2003) defines complexity as the degree to which an innovation is perceived as relatively difficult to understand and use. Any new idea may be classified on the complexity simplicity continuum. Some innovations are clear in their meaning to potential adopters whereas others are not. In the TAM model, this attribute is referred to as perceived ease of use.
Trialability
According to Rogers (1983), trialability is the degree to which an innovation may be experimented with on a limited basis. New ideas that can be tried on an installment plan are generally adopted more rapidly than innovations that are not divisible. Some innovations are more difficult to divide for trial than others. The personal trying out of innovation is a way to give meaning to innovation, to find out how it works under one’s own interpretation. This trial is a means to dispel uncertainty about adopting an innovation.
Observability or Visibility
Visibility or Observability is defined by Rogers (2003) as the degree to which the results of an innovation are visible to others. The results of some ideas are easily observed and communicated to others, whereas some innovations are difficult to observe or to describe to others. Rogers (1962) argues that the more visible an innovation (and its benefits), the greater the likelihood of adoption, simply because the gains from adoption will be more easily recognized.
The impact of the innovaton
Extensive use of information technology impacts the HR professional job role through influencing information demands on these employees. In terms of impact, according to Remenyi, Money and Twite (1991) and Zuboff (1988), IT includes three stages of use which are automation, information, and transformation. In the automation stage, IT is used primarily to automate manual systems and reduce the need of personnel to perform routine activities. According to Zuboff (1988), IT automation often reduces the amount of routine work that must be done, potentially providing more opportunities for individuals to think and use their full cognitive capacities. A short description of these opportunities is presented below.
Enable information responsiveness
As HR professionals are able to be more responsive, answer queries more quickly, and provide more accurate information, HRIS may enable these professionals to increase their responsiveness to their constituencies. Thus, with more extensive use of HRIS, HR professionals are able to provide increased information responsiveness.
Enable information autonomy
According to Remenyi et al. (1991) and Zuboff (1988), increased autonomy may result from HR employees using sites such as kiosk and web applications that come from increased HRIS usage. Thus, more extensive use of HRIS will enable HR professionals to be more autonomous in handling HR information.
Enable external professional links
An IT system may connect an organization to the internet, and thus allow HR professionals to access other organizations and points of reference to gather information that they need to remain current in their industry (Remenyi et al., 1991; Zuboff, 1988). By having increased information connectivity, HR professionals can demonstrate flexibility in the event of unanticipated change. Thus, more extensive use of HRIS will enable HR professionals to increase their links to external professionals.
Time required on transformation activities
With more extensive use of HRIS, there will likely be more time available for HR professionals to allot to other activities as they transform current activities and focus on business operations and practices (Remenyi, et al., 1991; Zuboff, 1988). HR professionals will be expected to spend more time attending to organization-wide issues, strategy development issues, and organizational change efforts. Thus, more extensive use of HRIS will enable HR professionals to spend more time on broader and more transformational issues.
Time required on IT support activities
IT influences the work that HR professionals perform by focusing more time on activities related to IT support, such as maintaining and developing IT-based HR applications. Thus, more extensive use of HRIS will enable HR professionals to spend more time on IT support activities.
RESEARCH MODEL
This study is to understand the influence of various perceived attributes of innovations on the extent of HRIS system usage and the outcomes of HRIS system usage. The research model in Figure 1 was developed based on the Rogers (1983) innovation diffusion model, the IT framework model of Remenyi et al. (1991) and the work of Zuboff (1988) .
[Insert Figure 1 here]
Hypotheses Development
According to Gan (2003), if a Personal Digital Assistant (PDA) allows user to perform both their personal and business tasks more effectively, it provides tremendous advantage to users. Thus, it would be expected that individuals who perceive PDA as advantageous would also be likely to adopt the device. Tornatzky and Klein (1982) found relative advantage to be an important factor in determining adoption of new innovations. Previous researches (Adams, Nelson & Todd, 1992; Lean et al., 2009; Ndubisi & Jantan, 2003; Sang, Lee & Lee, 2010; Schaupp et al., 2010; Teo, 2001; Van Slyke, Lou, Belanger & Sridhar, 2010) have indicated that perceived usefulness/relative advantage is positively related to system usage. This leads to the following hypothesis: H1: Perceived relative advantage is positively related to extent of HRIS use.
In Tornatzky and Klein’s (1982) meta-analysis of innovation adoption, they find that an innovation is more likely to be adopted when it is compatible with an individual’s job responsibilities and value system. Previous empirical studies found positive relationship between compatibility and intention to use (Gan, 2003; Karahana, Straub & Chervany, 1999; Ojha, Sahu & Gupta, 2009; Tan & Teo, 2000; Tornatzky & Klein, 1982; Van Slyke et al., 2010). Thus, the next hypothesis is stated as: H2: Perceived compatibility is positively related to extent of HRIS use.
Past research has indicated that innovation with substantial complexity requires more technical skills and needs greater implementation and operational effort to increase its chances of adoption (Cooper & Zmud, 1990). As with any other new computing system introduced to the market, HRIS is expected to be easy to use. It is therefore expected that the less complex to use HRIS is perceived to be, the more likely it is for an individual to adopt it. There is extensive empirical evidence that perceived ease of use, which is the opposite of perceived complexity, is significant and positively related to usage intentions (Davis, Bagozzi & Warshaw, 1989; Ojha et al., 2009; Ramayah & Aafaqi, 2003; Ramayah & Ignatius, 2005; Van Slyke et al., 2010; Venkatesh, 1999) . This leads to the next hypothesis: H3: Perceived complexity is negatively related to extent of HRIS use.
Rogers (1995) argues that potential adopters who are allowed to experiment with an innovation will feel more comfortable with the innovation and are more likely to adopt it. Agarwal and Prasad (1997) stated that the more adopters experiment with a new technology and explore its ramifications, the greater the likelihood that the innovation will be used during early stages of adoption. Any uncertainties about the innovation will also be reduced when trials are allowed. Thus, this becomes the basis of hypothesis four in this study which is stated as: H4: Perceived trialability is positively related to extent of HRIS use.
Visibility measures the degree to which an innovation is visible to individuals in a social system. Gan (2003) argue that when an innovation is perceived to be more visible to members of a social system, it is more likely to be adopted. This is because visibility creates a visual impact similar to what advertising media does. The visual impact in turn creates awareness of the product and hence increases its likelihood to be further evaluated. It is therefore expected that if HRIS is more visible to individuals, the more likely it is to be
adopted. Visibility/observability of an innovation has been found to be positively related to intention to use (Gan, 2003; Karahana et al., 1999; Venkatesh & Brown, 2001). If a positive result of an innovation can be observed and is likely to be communicated by others, the intention to use will be greater (Karahana et al., 1999; Kolodinsky, Hogarth & Hilgert, 2004; Xia & Lee, 2000). Thus, it is hypothesized that: H5: Perceived visibility is positively related to extent of HRIS use.
The automation of HR activities may impact the role of HR professionals by absorbing information-intensive tasks (Snell, Pedigo & Krawiec, 1995; Zuboff, 1988). As IT is used more extensively, it might enable HR professionals to access more information, allow them to answer queries from employees and managers in a timely fashion, and enable them to be more efficient at handling complex information as repetitive job tasks are automated. As more HR professionals are able to be more responsive, answer queries more quickly, and provide more accurate information, IT may enable HR professionals to increase their responsiveness to their constituencies (Gardner, et al., 2003). Thus, it is hypothesized that: H6: More extensive use of HRIS enables increased information responsiveness by HR
professionals.
Managers perceived IT as improving their confidence in decision making, removing uncertainty from decisions, and overall increasing their role in the organization (Buchanan & McCalman, 1988). Snell et al. (1995) suggest that increased HR autonomy may result from employees using sites such as kiosks and web applications that are a result of increased IT usage. Thus, it is hypothesized that: H7: More extensive use of HRIS enables greater information autonomy for HR
professionals.
As the extent of HRIS use increases, HR professionals are more likely to have increased opportunity to make connections to information from external sources. An IT system may connect an organization to the internet, and thus allow HR professionals to access other organizations and points of reference to gather information that they need to remain current in their industry (Gardner et al., 2003). Thus, it is hypothesized that: H8: More extensive use of HRIS enables HR professionals to make greater use of external
professional links.
IT absorbs the information intensive, but low value-added tasks and this provide the user more time to focus on strategic issues and customized activities (Lepak & Snell, 1998). With more extensive use of HRIS, there will likely be more time available for HR professionals to allot to other activities as they transform current activities and focus on business operations and practices. HR professionals will be expected to spend more time attending to organization wide issues, strategy development issues, and organizational change efforts. Thus, it is hypothesized that: H9: More extensive use of HRIS requires HR professionals to spend more time on
transformational activities.
Extensive use of HRIS that requires more time spent on implementation of new information technologies may also require HR professionals to spend more time on IT-related support activities to guide the users of the systems (Bhattacherjee & Hirschheim, 1997; Halachmi, 1992). IT influences the focus of work that HR professionals perform by focusing more time on activities related to IT support, such as maintaining and developing IT-based HR applications. Thus, it is hypothesized that:
H10: More extensive use of HRIS requires HR professionals to spend more time on IT
support activities.
RESEARCH METHODOLOGY
The study population comprises HR executives and HR professionals who are working in the companies around Penang, Malaysia. The selected site for this study is Bayan Lepas Free Industrial Zone, Prai Industrial Zone, and services organizations in Penang. A purposive sampling technique was employed. The reason for choosing this site is the relevance of its working population to this study. Many of the companies operating are related to semiconductor or personal computer industry in general. The employees of these companies are largely familiar with information technology products due to the nature of their jobs. As HRIS is relatively new, selecting a site with respondents having access to this system is important. Primary participants were HR professionals working in companies. Data were obtained about HRIS usage from the HR executives and multiple respondents selected in each organization to diminish concerns with single informant bias. To obtain the study data, fifty individuals were selected to participate in the survey. The initial questionnaire was mailed to all the potential respondents and included was a request that the respondent ask two further HR professionals to complete questionnaires that were enclosed with the HR executive survey. To ensure meaningful data is collected, each respondent was required to acknowledge that he or she knew what HRIS was before completing the questionnaire. Althought 88 responses were received, 18 of these were rejected due to errors in completing sections of the questionnaire. Therefore, only a sample size of N=70 was used for this study giving a high response rate of 47%. Data were collected using a questionnaire which used a 5-point Likert scale response format. Survey items were developed from a review of the literature and pilot tested with HR executives from twelve organizations. Very minimal changes were made to the final version of the questionnaires. The innovation characteristics measurement was adapted from Moore and Benbasat (1991) which was previously used in the Malaysian context by Gan (2003).
FINDINGS
The demographic profile of respondents is presented in Table 1. There was an equal representation from male and female, with a majority having tertiary education. Most were in the age group of between 26 and 35 years old and income level of RM2000 to RM3999 per month (USD 1 = RM 3).
[Insert Table 1 here]
To assess the model, we used SmartPLS M3 2.0 (Ringle, Wende, & Will, 2005) to estimate the parameters in the outer and inner model. PLS tries to maximize the variance explained of the dependent variables. It offers many benefits with respect to distribution requirements, type of variables, sample size and the complexity of the model to be tested. We applied PLS path modeling with a path-weighting scheme for the inside approximation (Chin, 1998; Tenenhaus, Vinzi, Chatelin & Lauro, 2005; Wetzels, Schroder & Oppen, 2009). Then, we applied the nonparametric bootstrapping approximation (Chin, 1998; Tenenhaus, et al., 2005; Wetzels et al., 2009) with 200 resampling to obtain the standard errors of the estimates.
Assessment of the Measurement Model
First we tested convergent validity which is the degree to which multiple items measuring the same concept are in agreement. As suggested by Hair, Black, Babin, and Anderson (2010) we used the factor loadings, composite reliability and average variance extracted to assess convergence validity. The loadings for all items exceeded the recommended value of 0.5 (Hair et al., 2010). Composite reliability values (see Table 2), which depict the degree to which the construct indicators indicate the latent construct ranged from 0.801 to 0.954 which exceeded the recommended value of 0.7 (Hair et al., 2010). The average variance extracted, which reflects the overall amount of variance in the indicators accounted for by the latent construct, were in the range of 0.557 and 0.901 which exceeded the recommended value of 0.5 (Hair et al., 2010).
[Insert Table 2 here]
Discriminant validity of constructs
Next we proceeded to test the discriminant validity. Discriminant validity is the extent to which the measures is not a reflection of some other variables and is indicated by the low correlations between the measure of interest and the measures of other constructs (Cheung & Lee, 2010). Discriminant validity can be examined by comparing the squared correlations between constructs and the average variance extracted for a construct (Fornell & Larcker, 1981). As shown in Table 3, the squared correlations for each construct is less than the average variance extracted by the indicators measuring that construct indicating adequate discriminant validity. In total, the measurement model demonstrated adequate convergent validity and discriminant validity.
[Insert Table 3 here]
Assessment of the Structural Model
We then evaluated the structural model to test the hypotheses. As shown in Figure 2 and Table 4, nine out of the ten hypotheses were supported. Compatibility (β = 0.264, p< 0.01), Complexity (β = 0.203, p< 0.01), Trialability (β = 0.184, p< 0.01) and Visibility (β = 0.111, p< 0.05) were all positively related to extent of HRIS use. Thus H2, H3, H4 and H5 were supported while H1 was not supported. The extent of HRIS use was positively related to information responsiveness (β = 0.601, p< 0.01), information autonomy (β = 0.564, p< 0.01),
external professional link (β = 0.341, p< 0.01), transformational activities (β = 0.339, p< 0.01), and IT support (β = 0.393, p< 0.01). These give support for H6, H7, H8, H9 and H10 of this study. The variance explained for each model is given in Figure 2.
[Insert Table 4 here]
[Insert Figure 2 here]
DISCUSSION, IMPLICATIONS, LIMITATIONS AND CONCLUSION
Relative advantage was hypothesized to be positively related to extent of use of HRIS. This study found that the hypothesis was not supported. It can be argued that while HRIS may seem to be useful to a certain age level of professional, the older generation might find it hard to adapt to the new technology. They may prefer the manual way of doing things. This finding contradicts (Choi, Choi, Kim & Yu, 2003; Gan, 2003; Lean et al., 2009; Sang et al., 2010; Schaupp et al., 2010; Tan & Teo, 2000; Tornatzky & Klein, 1982; Van Slyke et al., 2010) with those who have consistently found relative advantage and compatibility to be very important factors. Our inconsistent result may be attributable to the profile of the respondents where a majority of them have used HRIS for more than three years. The substantial experience, with most respondents holding managerial and executive positions, may mean they perceive that the system is useful and there is not much variation in the data. Compatibility was hypothesized to be positively related to extent of use of HRIS. This study found that the hypothesis was supported. It can be argued that the HRIS system that is compatible to an individual’s lifestyle will lead to a higher level of use. This finding supports the works of (Gan, 2003; Karahana et al., 1999; Ojha et al., 2009; Tan & Teo, 2000; Tornatzky & Klein, 1982; Van Slyke et al., 2010) who have found compatibility to be very important in adoption decisions to use technological innovations. Complexity is hypothesized to be negatively related to extent of use of HRIS. This study found that the hypothesis was supported. This may be because if the HRIS system is perceived to be very difficult to use then it will not be used extensively. This observation is similar to the results of many previous studies based on the TAM model (Davis et al., 1989; Ojha et al., 2009; Ramayah et al., 2003; Ramayah & Ignatius, 2005; Van Slyke et al., 2010; Venkatesh, 1999) which have consistently found complexity (ease of use) to be a factor influencing adoption. Trialability was also posited to be positively related to extent of use of HRIS. This study found that the hypothesis was supported. Trialability is perceived as an important attribute as Agarwal and Prasad (1997) stated that the more the adopters experiment with a new technology and explore its ramifications, the greater the likelihood that the innovation will be used during early stages of adoption. This is reasoned as any uncertainties about the innovation will also be reduced when trials are allowed to the potential users. Visibility is hypothesized to be positively related to extent of use of HRIS. This study found that the hypothesis was supported. This could be that respondents who have used the system themselves are more likely to develop a positive impression of the system compared to those that have not. In this case, respondents that have used the HRIS system in the workplace
could have developed an impression that HRIS system has certain benefits that have influenced the use of it by the people around. This is consistent with previous studies (Gan, 2003; Karahana et al., 1999; Kolodinsky et al., 2004; Venkatesh & Brown, 2001; Xia & Lee, 2000) which found visibility to be a significant predictor of technology usage. The hypothesized more extensive use of HRIS enables increased information responsiveness and information autonomy by HR professionals were supported. The results support the works of Zuboff (1988) and Remenyi et al.(1991) which theorize that with more extensive use of IT, HR tasks are further automated making HR professionals more efficient through their responsiveness and autonomy. The hypothesis that more extensive use of HRIS also enables HR professionals to make greater use of external professional link was supported. The HR professionals in this study were able to connect more to external professional links as a result of more extensive use of IT suggesting a potential for them to learn more innovative ways in which to deliver HR activities. This is consistent with the previous study of Gardner et al. (2003) which found empirical evidence to support this finding. The hypothesis that more extensive use of HRIS requires HR professionals to spend more time on transformational activities and IT support activities was also supported. HR professionals spend more time on transformational and IT support activities, suggesting that more extensive use of IT turned HR professional focuses them towards more knowledge based activities as they shift attention to developing IT-based HR applications. This is consistent with the previous study of Gardner et al. (2003) .
Implications
This study has important implications for both research and marketing of innovation. In terms of research, this study provides further evidence on the appropriateness of using Roger’s innovation attributes to measure different dimensions of attitude towards extent of use of HRIS and Remenyi’s & Zuboff’s IT frameworks to measure the outcomes from the use of HRIS. There are a number of reasons that can explain why findings of this study may differ from previous studies. One of them is that Roger’s innovation diffusion theory applies to a diverse set of research fields including rural sociology, psychology, marketing and technology adoption; and applicability of these various attributes could differ from one research field to the other. As such we can conclude that the combined theoretical perspectives can be used to better understand the influence of various perceived attributes of HRIS on the extent of system usage and the impacts on HRIS system usage. This study also found that IT appears to serve as an empowering function for HR professionals, providing a medium in which HR professionals can provide increased value in their work. IT is a tool that HR professionals can utilize to provide more value to the organization (Ulrich, 1998). The findings also hold important practical implications for the marketing strategy for innovations particularly those that are information technology solutions. A marketing strategy for an innovation solution should consider increased emphasis on bringing the best value in terms of relative advantage and compatibility of the solutions to its potential market. These attributes should be given due emphasis during system solution conceptualization, design, testing as well as manufacturing stage. In addition, when the system solution is rolled out to
the market, it should be positioned as a solution that truly delivers these attributes which are the most common attributes potential customers seek in an innovation. Lastly, the study will also help organizations in the implementation or deployment of new information technology products, systems or processes. Organization can now ensure a smoother implementation plan by addressing the attributes of the innovation that its employees will most likely to have concern with.
Contribution to theory
The process of adopting new innovations has been studied for over 30 years, and one of the most popular adoption models is described by Rogers in his book, Diffusion of Innovations. The objective of this study was to understand the influence of various perceived attributes of innovations on the extent of HRIS usage and the outcomes of HRIS use. The research framework is based on combining Rogers theory of adoption and theory related to IT impact. Rogers (1983) proposed that there are five factors that contribute to adoption such as relative advantage, compatibility, complexity, trialability and visibility. According to Remenyi et al. (1991) and Zuboff (1988), IT impact includes three stages of use that are automation, information, and transformation. The study relies on the notion that extensive use of information technology impacts the HR professional job role through influencing information demands on these employees such as demand for providing IT support. Haines and Petit (1997) found that involvement, training, support, documentation and application development are among factors contributing to user satisfaction and system usage. There are similarities between contributing factors to the rate of adoption by Rogers (1983) and contributing factors to influence user satisfaction and system usage by Haines and Petit (1997).
Limitations
As with all research, this study also has certain limitations. First, this study cannot be generalized to all other individuals as the respondents are confined to HR professional employees in the IT sector in local services companies and multinational companies. Therefore, the results cannot be generalized to individuals working in other industries. As such, there is still room for further investigation into the adoption of innovation by a more general population. Extending the study to include individuals working in other industries or sectors or divisions may add further support to the findings. Second, the study was carried out using a particular type of technological innovation which is HRIS system in this case. As such, the research needs to be replicated to examine the robustness of the findings across a wider range of technological solutions and samples. Finally, there are some possibilities of measurement errors. The study focused on perception of the respondents and the instrument relied on self-reports and perceptions of the respondents alone. This could have resulted in some degree of perceptual inflation of self-assessment scores. Those who enjoyed great satisfaction with the innovation may have inflated their response with respect to their intention to continue to use the innovation. Additionally, the instrument was also self-administered and there could be situations where respondents may need further clarification, which was not available.
Conclusion
This study has shown the attitude-system usage relationship in the context of HRIS technology adoption. It has shown that perceived innovation characteristics influence extent of use of the HRIS systems and also determine the outcomes from the use of HRIS systems by HR professionals. Gardner et al. (2003) found that HR professionals were able to provide increased information responsiveness to the clients that they served as well as to act autonomously when handling information. The results support the theorized impact suggesting that with more extensive use of IT, HR tasks are further automated making HR professionals more efficient through their responsiveness and autonomy. According to Gardner, et al. (2003), although there were significant results that indicate that higher levels of extent of use of IT do lead to changes in the HR professional’s job, they suggest that there is also considerably more variance to be explained. Thus it is likely that additional factors may influence the relationship between IT use and the jobs of HR professionals. Finally, this study has provided some additional insights into the relationship between individual’s attitude and extent use of HRIS in the Malaysian context. It does suggest that individual’s attitude as measured by perceived innovation characteristics in this study are relevant and valid, and they influence extent use of HRIS. In short, it does suggest that IT can lead to profound changes in the nature of professional work through such mechanisms as reducing routine work while also allowing greater information responsiveness to clients and affording greater autonomy with respect to information handling. For instance, the HR professionals in the study were already connecting to more external professional links as a result of greater use of IT, enabling greater exposure to innovative ideas. The fact that they were also spending more time on IT support activities suggests that they are acquiring an increased capacity to develop additional IT-based HR applications, thereby potentially furthering the transformational impact predicted by Zuboff’s theory. Thus, the findings have important implications not only for theory, but for practice as well.
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Appendix A. Questionnaire items
Constructs Items Source
Relative Advantage RA1. Using HRIS has improved the quality of the work I do RA2. Using a HRIS makes it easier to do my work RA3. Using a HRIS has enhanced the effectiveness of my work
RA4. Overall, I find using a HRIS to be advantageous in my work
(Moore & Benbasat, 1991); Han et al. (2006)
Compatibility CP1. Using a HRIS fits my work style CP2. Using the HRIS is compatible with all aspects of my work CP3.I think that using a HRIS fits well with the way I like to work
(Moore & Benbasat, 1991); Han et al. (2006)
Visibility
Complexity
Trialability
VIS1. I have seen what others do using the HRIS VIS2. It is easy for me to observe others using the HRIS
VIS3. I can see many individuals using the HRIS CX1. Overall, I believe that a HRIS is difficult to use CX2. Learning to operate the HRIS was difficult for me CX3. Using the HRIS requires a lot of mental effort
CX4. It was difficult to get the HRIS to do what I want TR1. I want to be able to use a HRIS on a trial basis long enough to see what it can do TR2. Was able to satisfactorily try out various uses of HRIS
TR3. I have had opportunities to try out various HRIS applications TR4. Before deciding whether to use any HRIS applications, I would want to be able to properly try them out.
(Moore & Benbasat, 1991); Han et al.
(2006) (Moore & Benbasat, 1991); Han et al. (2006)
(Moore & Benbasat, 1991); Han et al. (2006)
Extent of Use
Enable Information
Responsiveness
Enable Information Autonomy
Enable External Professional Link Time Required on Transformational Activities
Time Required on IT Support Activites
USE1. Frequency of Use (Week)
USE2. Hours Used (Week) IR1. Enables you to provide more timely information to line
managers IR2. Enables you to be more efficient at handling complex information as repetitive job tasks are automated IR3. Enables you to be more responsive and provide more accurate
information IA1. Enables you to make fewer request to line managers for routine information IA2. Enables you to access information and evaluate what was not
previously accessible IA3. Enables you to be more independent from clients IA4. Enables you to make decision and removing uncertainty from decisions
EPL1. Enables you to be more connected to professional associations EPL2. Enables you to connect to the internet and allow to access other organizations TA1. Requires you to spend more time planning organizational change efforts TA2. Requires you to spend more time attending to organization wide issues
TA3. Requires you to spend more time attending to strategy development issues TA4. Requires you to spend more time toward efforts to improve the organization
SA1. Requires you to spend more time dealing with glitches in IT-based HR systems SA2. Requires you to spend more time deskills professional and managerial work as it displaces humans and their know-how
SA3. Requires you to spend more time alter the required skill set by requiring new knowledge and skills in order for workers to utilize the new systems.
(Tan & Teo, 2000)
(Gardner, et al., 2003)
(Gardner, et al., 2003)
(Gardner, et al., 2003)
(Gardner, et al., 2003)
(Gardner, et al., 2003)
Figure 1: Research Framework
Extent of Use
(USE)
Relative Advantage (RA)
Compatibility (CP)
Complexity (CX)
Visibility (VIS)
Trialability (TR)
Information Responsiveness (IR)
Information Autonomy (IA)
External Professional Link (EPL)
Transformational Activities (TA)
IT Support Activities (SA)
Fig
ure
2.
Str
uct
ura
l M
odel
Ex
tent
of
Use
(US
E)
R2 =
0.5
04
Rel
ativ
e
Ad
van
tage
(RA
)
Co
mpat
ibil
ity
(CP
)
Com
ple
xit
y
(CX
)
Vis
ibil
ity
(VIS
)
Tri
alab
ilit
y
(TR
)
Info
rmat
ion
Res
ponsi
ven
ess
(IR
)
R2
= 0
.362
Info
rmat
ion
Auto
nom
y (
IA)
R2 =
0.3
18
Ex
tern
al P
rofe
ssio
nal
Lin
k (
EP
L)
R2 =
0.1
16
Tra
nsf
orm
atio
nal
Act
ivit
ies
(TA
)
R2 =
0.1
15
IT S
upport
Act
ivit
ies
(SA
)
R2 =
0.1
55
β =
0.0
27
β =
0.1
11*
β =
0.1
84**
β =
-0.2
03**
β =
0.2
64**
β =
0.6
01**
β =
0.3
93**
β =
0.3
39**
β =
0.3
41**
β =
0.5
64**
Table 1
Demographic Profile of Respondents
Variables Category Frequency Percentage
Gender Male
Female
35
35
50
50
Education Certificate/Diploma
Bachelor Degree
Master Degree
Ph.D
5
42
19
4
7.1
60
27.1
5.7
Age (in Years) Under 20
20-25
26-30
31-35
36-40
40 and above
0
1
22
24
11
12
0
1.4
31.4
34.3
15.7
17.1
Job Manager
Executive
Others
23
46
7
24.3
65.7
10.0
Income Less than RM2000
RM2000-RM2999
RM3000-RM3999
RM4000-RM4999
RM5000-RM5999
RM6000 or more
7
19
26
6
7
1
10.6
28.8
39.4
9.1
10.6
1.5
HRIS utilization Less than a year
Between one to three years
More than three years
Others
2
14
50
4
2.9
20
71.4
5.7
Table 2
Result of the measurement model
Construct Code Loadings α CR AVE
Compatibility CP1 0.885 0.834 0.901 0.751
CP2 0.833
CP3 0.881
Complexity CX1 0.885 0.753 0.859 0.671
CX2 0.782
CX4 0.786
Enable External Professional Link EPL1 0.944 0.797 0.905 0.826
EPL2 0.872
Enable Information Autonomy IA1 0.847 0.932 0.952 0.831
IA2 0.919
IA3 0.954
IA4 0.924
Enable Information Responsiveness IR1 0.876 0.889 0.931 0.818
IR2 0.925
IR3 0.911
Relative Advantage RA1 0.786 0.867 0.909 0.714
RA2 0.820
RA3 0.896
RA4 0.873
Time Required on SA1 0.711 0.831 0.897 0.747
IT Support Activities SA2 0.941
SA3 0.921
Time Required on Transformational TA1 0.850 0.936 0.954 0.839
Activities TA2 0.949
TA3 0.949
TA4 0.913
Triability TR2 0.883 0.629 0.801 0.577
TR3 0.747
TR4 0.627
Extent of Use USE1 0.949 0.890 0.948 0.901
USE2 0.950
Visibility VS1 0.817 0.775 0.868 0.687
VS2 0.800
VS3 0.868
Note: CX3 and TR1 were deleted due to low loadings
CR = Composite reliability; α = Cronbach Alpha; AVE = Average Variance Extracted
Tab
le 3
Dis
crim
ina
nt
vali
dit
y o
f co
nst
ruct
s
1
2
3
4
5
6
7
8
9
10
11
1. C
om
pat
ibil
ity
0.7
51
2. C
om
ple
xit
y
0.6
05
0.6
71
3. E
PL
0.1
79
0.1
08
0.8
26
4.. E
xte
nt
0.4
33
0.4
26
0.1
16
0.9
01
5.
IA
0.4
49
0.3
32
0.4
20
0.3
18
0.8
31
6.
IR
0.5
08
0.4
40
0.4
55
0.3
62
0.5
93
0.8
18
7. R
A
0.6
83
0.5
57
0.0
60
0.3
77
0.3
20
0.3
85
0.7
14
8. S
A
0.1
44
0.1
85
0.3
11
0.1
55
0.3
12
0.4
06
0.1
24
0.7
47
9. T
A
0.1
18
0.0
71
0.6
63
0.1
15
0.4
45
0.4
26
0.0
45
0.3
78
0.8
39
10.
Tri
alab
ilit
y
0.6
23
0.5
84
0.0
74
0.4
13
0.2
83
0.3
27
0.5
65
0.1
14
0.0
39
0.7
60
11.
Vis
ibil
ity
0.3
84
0.5
75
0.0
10
0.3
28
0.1
87
0.2
31
0.5
17
0.0
76
0.0
13
0.4
62
0.6
87
No
te:
Dia
go
nal
s ar
e th
e A
VE
wh
ile
the
off
-dia
go
nals
are
the
squar
ed c
orr
elat
ions
Table 4
Path coefficients and hypothesis testing
Path Std Beta
T-
Statistics
Decision
H1 RA � Extent 0.027 0.452 Not Supported
H2 Compatibility � Extent 0.264 3.658** Supported
H3 Complexity � Extent -0.203 3.295** Supported
H4 Trialability � Extent 0.184 2.876** Supported
H5 Visibility � Extent 0.111 2.028* Supported
H6 Extent � IR 0.601 16.27** Supported
H7 Extent � IA 0.564 16.174** Supported
H8 Extent � EPL 0.341 7.849** Supported
H9 Extent � TA 0.339 6.79** Supported
H10 Extent � SA 0.393 10.785** Supported
