The Integration of Unified Theory acceptance Use Technology (UTAUT) and End user Computing Satisfaction (EUCS) to Evaluate Information System (IS). PDF

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1.1 Room 1 (Jintan) – Session 1: Human Resource Management Modeling the Impact of Resistance to Change within the Context of Human Resources Information Systems Adoption Abdulrahman Al Shikhy Graduate School of Business - University Kebangsaan Malaysia, Bangi, Malaysia Zafir Mohd Makhbul Faculty of Economics and Management- University Kebangsaan Malaysia, Bangi, Malaysia Khairul Anuar Mohd Ali Graduate School of Business - University Kebangsaan Malaysia, Bangi, Malaysia Ali Al Mazari PSCJ, AL-Faisal University, Jeddah, Saudi Arabia

Abstract Resistance to change is widely known as a significant factor of failing to adopt new technologies. Despite several studies that have considered the implementation and deployment of critical success factors of Management Information Systems (MIS) in business domains, a knowledge gap regarding resistance to change and adoption remains the hot topic of interest, mainly in the area of human resources information systems (HRIS). This work presented a thorough review and suggested a direction for future development of HRIS adoption model. The work proposed a model to investigate the extent of the relationship between resistance to change (RTC) and technology acceptance model (TAM) model variables toward the actual use of HRIS. In terms of academic contributions, the proposed model is expected to give theoretical evidence and contribute to the literature of knowledge about HRIS adoption. The finding will give valuable insights of a complete model about the resistance to use HRIS. Keywords: Technology Acceptance Model (TAM), Human Resources Information System (HRIS), and Resistance to Change (RTC).

1. Introduction Information and communication technologies (ICT) plays a major role in every aspect of our life. ICT creates the potential for improving, planning, forecasting the demand of employees, training and development, salary forecast, and others, which support workers’ experiences in the human resources (HR) department by enabling them to be connected with a large number of people from inside and outside the company (Oldham & Silva, 2015). Modern human resources information systems (HRIS) make optimal use of the Internet to fulfill objectives and enable the HR department to view and assist an employee at any time and location by using different means. Due to this evolution, challenges frequently emerged between the large amount of investment made in HRIS and the real profit gained as reported by many studies (Parente & McCullough, 2009; O’Malley, Grossman, Cohen, Kemper, & Pham, 2010). Singh, Jindal, and Samim (2011) argued that to adopt HRIS implementation in any organization, re-engineering of business processes is required. However, in the literature, a number of studies have been focusing on the HRIS with different concerns (Nagendra & Deshpande, 2014), for example, they found some factors have been preventing the firms to achieve their target gains from the adopted HRIS, such as shortage support from the management and limited budget. In another study (Indrit, Cate, & Hill, 2011), they found that the adoption of HRIS depends on environmental and technology context factors. Conversely, Islam, Ali, and Wafi (2010) found that old managers with a higher level of education are more resistant to changes in multinational organizations in Malaysia. 1

Moreover, a very limited systematic experiential has proved the agreements about the relationship between ICT and HRM, especially regarding the outcomes related to the actual use of HRIS and the effects on the performance of a firm (Marler & Fisher, 2013). For example, Al-Mobaideen, Allahawiah, and Basioni, (2013) found that ICT infrastructure is important to successfully implement of HRIS. Nagendra and Deshpande (2014) also found that the efficiency of HR planning depends on the alignment of HRIS between information systems (IS) strategy and HR strategy. Nevertheless, it has been reported that the most notable variables affecting firms and workers are the changes to a new technology. A significant issue has emerged because of the changes to HRIS applications, which is the employee’s resistance to change (Klaus & Blanton, 2010). HRIS, similar to any technology project, faces resistance from workers, especially when it is presented without any introduction, and causes frustration among the workers’ “end user” to accept it (Adams, Berner, & Wyatt, 2004). Consequently, firms and workers will not achieve their goals with limited levels of acceptance (Noor & Razali, 2011). As mentioned earlier, many researchers argued that the major factor of any technology projects failure is acquiring resistance by end users to use such new technologies. In earlier studies, researchers utilized the use of the technology acceptance model (TAM) to inspect the attitude toward the acceptance of new technological programs and initiatives. For example, the TAM is utilized to investigate the actual use and behavioral issues among end users towards different technologies such as e-book learns, e-digital libraries, e-learning, online shopping, and e-medical records (Babakhani, 2014; Khalid, 2013; Ngai, & Wat, 2006; Nov & Schecter, 2012; Nov & Ye, 2008). The contribution of this work is to explore the literature by filling the knowledge gap and the positivism to understand the relationship between the employee’s resistance to use HRIS and the actual use of HRIS. To accomplish this objective and to respond to a recent call for research about filling the knowledge gap of HRIS, the contribution of this work will help most organizations to understand who needs to avoid the employee’s resistance to have best HRIS performance. Moreover, this work tries to understand which element has the most impact on the actual use of HRIS, and it will help managing the process of developing appropriate systems and strategies for the future. According to Kassim, Ramayah, and Kurnia (2012), there is an incomplete understanding about the effectiveness of HRIS usage in developing countries such as Malaysia. According to The International Statistical Institute in 2014, in the context of “Gross national income (GNI) per capital per year,” developing countries are defined as the countries that have a GNI equal or less than US$ 11,905. Furthermore, this work will make an endeavor in crossing over the advanced separation in the middle of developed and developing countries regarding the utilization of HRIS. Moreover, this work will fill the gap of theoretical contributions, and this work is expected to give a theoretical evidence to HR and IS, and also gives valuable insights into the important points to avoid any resistance to use HRIS in the future.

2. Problem Statement Despite several studies that have considered the implementation and critical success factors of information system in business domains, a knowledge gap with regard to the resistance to change and adoption remain a hot topic of interest. In Malaysia, Ramayah, Nornina, Noorliza, and Normalini (2006) studied the utilization and adoption of a HRIS among professionals and HR executives which working in Penang. Their work revealed that compatibility and visibility were significant related and complexness was not significant related to extent of use of HRIS. Despite the growing interest in TAM, empirical enquiry on TAM, HRIS has been limited, and need more empirical study, from this study we can also identify obstacles and suggest ways to overcome it. Moreover, several studies and experimental research have considered the investigation of using the information communication technologies (ICT) in different disciplines (Nov & Schecter, 2012; Sargent, Hyland, & Sawang, 2012; Van Offenbeek, Boonstra, & Seo, 2013) but not in the area of HRIS acquisition mainly within the context of developing countries like Malaysia. Furthermore, there is frustration in understanding one of the most problems associated with employees’ resistance to use 2

HRIS. However, there is a lack of research regarding the adoption of HRIS in Malaysia. Hence, a theoretical investigation has been conducted to explore the effects of resistance to change toward using HRIS. Marler and Fisher (2013) have reviewed 40 studies cited in high ranking journals and found that the adoption and resistance issues are still at the early stage to be fully understood. The failure rate remains high, and it has been reported that more than half of the information system projects are not complete (Gardner, Lepak & Bartol, 2003), while approximately one-third of every information system projects never reach the usage stage. Organizations have spent huge investments on the development of HR systems adoption but its acceptance among end users is still low (Schaupp, Carter, & McBride, 2010). Most of those studies have focused mainly on developing countries. Some studies have been conducted to investigate (Mat & Vrontis, 2010) the main factors that force the employees to accept or reject the new HRIS adoption in the Malaysian Airlines System (MAS). Moreover, Ahmed, Zbib, Arokiasamy, Ramayah, and Chiun (2006) found that human factor is a very important factor in any technology implementation. Note that rejection is an inbuilt human response to any new technology in daily routine (Sharma, 2013). Therefore, employees tend to use new technology but with less potential. Consequently, we will see indirect resistance from the employees in using the new technology by different ways, e.g., delaying or entering wrong data in the database (Ahmer, 2013), which leads to system failure. Based on the literature review, we found the theoretical logic underlying the mechanisms that link the resistance to change with the use of HRIS remains fragmented. (Babita, & Paramjit, 2012; Behrenbru et al., 2013; Jeswani, & Dave, 2012; Parks-Leduc, Feldman, & Bardi, 2015; Singh et al., 2011; Shroff, Deneen, & Ng, 2011; Shropshire, Warkentin, & Sharma, 2015; Wahyudi & Park, 2014; Zaied, 2012). Only a few number of studies have emphasized the relationship between resistance to change and the actual use of HRIS but excluding the variable of intention behavioral. However, some researchers have been focusing on one perspective to understand how dispositional resistance to change affects the actual use of HRIS (e.g., Laumer, Maier, & Eckhardt, 2010; Nov, & Schecter 2012; Nov & Ye, 2009; Sargent et al., 2012; Wahyudi, & Park, 2014). Despite the vitality of HRIS in many firms, there is still a knowledge gap in this field and it needs to be filled to understand which factors might prevent the firms from achieving their goals. To our understanding from the literature review, most studies have been focusing on the users’ acceptance to use HRIS rather than the real reasons for users’ resistance (reject) to use HRIS. Furthermore, from the literature review for filling the knowledge gab, until recently, no study at the researchers level of understanding has focused to include these particular variables in one single model, such as dispositional resistance to change, PEOU, PU, behavioral intention, and actual use of HRIS (Shropshire et al., 2015). Thus, further research needs to be conducted. Consequently, this lack of scholarly research points out the needs to examine these specific variables to determine the real reasons that let the end user accept or reject the HRIS application. On the basis of the issues presented previously, this work integrates dispositional resistance to change, PEOU, PU, behavioral intention, and actual usage of HRIS. In general, it attempts to address the question: How does the TAM model explain the relationship of dispositional resistance to change, perceived ease of use, perceived usefulness, behavioral intentions, and actual use of HRIS?. This work aims to integrate a theoretical framework to examine the effects of disposition resistance toward actual use of HRIS based on the technology acceptance model (TAM). The specific objective of the work is to investigate the relationship among dispositional resistance to change, TAM, behavioral intention to use HRIS, and actual usage of HRIS. 3. Literature Review Human Resources Information Systems Nowadays, information technology has enhanced many HR functions (Keim & Weitzel, 2009). Hendrickson (2003) has defined HRIS as the integrated system used to save, assemble, and anatomize data of a firm’s HR. HRIS consists of databases, computer applications, people, policy, and software 3

and hardware to amass, list, keep, convey, manage, and provide current data for the HR mission. According to Tarafdar, Tu, and Ragu-Nathan, (2010), information systems contain revolutionizing reports, design and manufacture products, contact customers and prospective customers, and management of daily operations. HRIS can be beneficial to managers (Parry, 2009) in many ways such as providing sufficient information about qualifications demand, development of training programs, salary expectations, and budgets payment for contracts negotiation (Shibley, 2011). To successfully complete the acceptance HRIS adoption in any organization, the organization has to develop a positive environment within itself. Other than that, rejection is an inbuilt human response to any type of change, especially to any type of innovation or suggestion. The acceptance of a new process occurs slowly with a lot of positive interventions after the inputs are carefully understood. Safety and risk management is another important feature that can be drawn from private HRIS and highly individual data and several aspects of safety (Karakanian, 2000). Technology Acceptance Model A determinant of technological utilization has been studied to forecast and clarify the end-client appropriation and acceptance of IT. One of the well-known theories related to technology acceptance is the theory of reasoned action (TRA), which is provided by Fishbein and Ajzen's (1975). Davis (1986) has adapted the TAM model established in the TRA and confirmed that TAM is appropriate as a theoretical model to explain and forecast the employee behavior intention to use IT (Legris, Ingham, & Collerette, 2003). Davis defined the important items as follows: i) perceived usefulness (PU): the stage where an employee is considering to use the system particularly and would promote their job performance, ii) perceived ease of use (PEOU): the stage where an employee is considering to utilize the system. Moreover, the TAM has proposed that when a servant has a new technology, there are some factors that will affect their decision about how and when they use it (Davis, Bagozzi & Warshaw, 1989). The development of a new variable that is expected to be used can be clarified by a person’s plan to utilize a particular information system determined by the apparent usability and the value of the framework. Nevertheless, their core finding was PU, and PEOU had a direct influence on behavioral intention. Consequently, they eliminated the attitude element from the later model that was developed by Venkatesh and Davis (1996). Furthermore, Venkatesh and Davis (1996) developed this model when they found that their respondents were getting confused on mixing the items of PU and PEOU together, and other variables gathered in the previous model after the respondents mixed them; thus, they came up with the extended model (see Figure 1):

Figure 1: The last developed of TAM model by (Venkatesh & Davis, 1996, p.453)

Perceived Ease of Use External Variables

Behavioral Intention

Actual System Use

Perceived Usefulness

TAM states that the impact of outer variables on client behavior depends on client beliefs and the state of mind. The reason for choosing TAM for this examination is that TAM has been experimentally tried and underpinned over acceptances, applications, and replications (Schaupp et al., 2010; Yusoff et al., 2010; Lee, 2010). Moreover, the most outstanding tool among the effective tools is TAM model for expecting client acceptance, particularly in an information system (Bueno & Salmeron, 2008). In other words, considerable studies have examined TAM as the model to clarify employee behavioral towards the adoption and use of HRIS (Shropshire, 2015; Wahyudi & Park, 2014; Cheung & Vogel, 2013). Consequently, the most famous model used extensively in a variety of study is the TAM. The reason for choosing TAM for this body of work because it has been examine empirically and supported through validation, application, and replication (Venkatesh, 2000; Schaup et al., 2010; Lee, 4

2010; Yusoff, et. al., 2010). TAM consider as one of the most robust, powerful, and parsimonious model for forecasting user acceptance particularly in IS context (Bueno & Salmeron, 2008). Resistance to Change On the basis of previous studies, Hultman (2003) has explained the resistance as a perspective that reflects the unwelcome quality to change the ways of an individual thought or act. In 2007, Klaus, Wingreen, and Blanton pointed that resistance to change (RTC) has been recognized as the possible factor that affects the utilization of information technology. For instance, an individual RTC is frequently considered as the main cause of unsuccessful IT projects (Venkatesh & Davis, 2000; Klaus et al., 2007). In 2003, Oreg found the existence of a multidimensional variable in one factor, which is dispositional resistance to change (DRTC). The idea taps employees’ natural habit in opposing changes. When some individuals widely adapt to changes, some others demonstrate a slant to evade and contradict them. DRTC contains four sideways dimensions: routine seeking, emotional reaction, short-term focus, and cognitive rigidity. These dimensions have been defined by Oreg (2003): i) routine seekingincludes the degree to which people lean toward traditional and exceptional unsurprising undertakings, methodology, and situations; ii) emotional reactionis centered on the degree of whom people experiment the convenience, absence of eagerness, and nervousness with when changes are forced upon them; iii) short-term focus is based on the level of people who stressed on the weaknesses and inconvenience that change the reality, in contrast to concentrating the potential advantages and solace that could accumulate long haul; and iv) cognitiverigidity includes people’s resoluteness of intuition and trouble in tolerating other thoughts, points of view, and styles. In addition, the resistance to IT is the attitude proposed in keeping the execution and/or utilization of IT. Many studies have been focusing on the frameworks of TAM model by Davis (1989). This exploration flow has prompted 345 articles concentrating on the acceptance and are cited in high ranking journal of the IS field in the past 20 years (Williams, Dwivedi, Lal & Schwarz, 2009). Therefore, this work has reliably discovered the connections between attitudes, beliefs, usage behavior, and behavioral intentions as well as ordinarily concentrated on the starting decision whether to utilize IS or not. Moreover, TAM models do not take this into account, and they ignore the reasons for innovation failure or in other words, (RTC). Thus, this work proposes to go beyond the TAM models and examine the factors that influence employees’ resistance to change. 4. Research conceptual framework This work will comprehend the influence of different elements on the acceptance to use the HRIS application. The research conceptual framework (see Figure 2) is adapted based on TAM model (Venkatesh &Davis, 1996) and disposition resistance to change by Oreg (2003).

Figure 2: The conceptual framework Dispositional Resistance to change

   

Routine Seeking Emotional Reaction Short-term Focus Cognitive Rigidity

Perceived Ease of Use HRIS

Perceived Usefulness HRIS

5

Behavioral intention to use HRIS

Actual Usage of HRIS

5. Research Hypotheses Dispositional Resistance to Change, Perceived Ease of Use and Perceived Usefulness DRTC consists of four variables: emotional reaction, routine seeking, cognitive, and short-term. Furthermore, there are 17 items in this sector. These items are adopted by Oreg who had measured these variables using the five-point Likert scale. Previous ...