**4. The proposed affective technology acceptance (ATA) model**

(i.e., when the new information technology (IT) had been deployed and was being used). In this period, emotions are generated based on individuals' perceptions on the features of the new technology and on their usage of the new technology resources. Individuals will assess whether the technology constitutes a threat or an opportunity and how it can adapt into their daily tasks by changing their working behaviors [33]. Some specific emotion terms such as pleasure, arousal, and enjoyment are used to relate users' attitude toward actual use of a technology [6]. Feelings are sensations perceived by the sense of touch; an affective state of consciousness that resulted from emotions, sentiments, or desires. On the other hand, cognition arises on the human beings' perception toward using technologies [16, 34]. Behavioral aspect would be from the individual's reactions toward using the information technologies [11]. Emotional Intelligence is a variable with a multifactor individual difference [35] that meets the traditional standards of intelligence. Being emotionally intelligent involves being actively able to identify, understand, process, and influence one's own emotions and those of other to guide feeling, thinking, and action. Sentiments are valence appraisals of an object that involves evaluation of whether something is liked or disliked. These evaluations were evoked by phenomena. It can come from previous experience with the object or situation or through social learning [29]. Satisfaction has been the most widely studied sentiment. Most of the work conducted has focused on satisfaction at the individual level either because of workplace events or as a predictor of workplace

Zhang and Li [36] examined the affects of emotional assessments of IT on IT utilized choices. Refer to Zhang and Li [36], two protest based full of feeling assessment builds: recognition on IT's ability to incite positive affect and impression of the IT's capacity to prompt negative affect able to influence. Their investigation demonstrated that positive affect and negative affect are particular ideas that affect perceived usefulness (PU), perceived ease of use (PEOU), and attitude toward utilizing IT tools. These impacts remain constant amid individuals in using and utilizing IT tools (ATT). Positive affect impacts PU, PEOU, and ATT, yet it turns out to be less critical to PU after some time, and positive affect just impacts PEOU; however, it turns out to be more vital to PEOU over the long run. Therefore, Zhang and Li [37] presumed

Loiacono and Djamasbi [15] also found that positive mood played a significant role in the adoption of a new technology. Their study looked at the effects of positive mood, and to understand how individual's characteristics affect an individual's cognition and behavior on the acceptance of a Decision Support System. The objective of their research is to investigate how affect can be a vital component for technology acceptance to make rational decision making. Based on Isen et al. [38], qualities of task characteristics impact one's certain state of mind particularly on tolerating another innovation, for example, Decision Support Systems (DSS) which requires subjective capacities to deal with troublesome/complex task. Association can control one's state of mind by encouraging positive temperament inside the association, and it can enhance association's results [16]. From their findings, Loiacono and Djamasbi [15] reported that positive mood could bring improvements in new technology

that affect influence a key part in individuals' connections in using IT tools.

outcomes [19].

152 Knowledge Management Strategies and Applications

acceptance.

Based on the literature findings, affective technology acceptance model involves PA and NA that were used to induce positive and negative affect states on the individuals who uses the technology were proposed. Zhang and Li [36] adapted these constructs and defined them as the perception of IT's capability to induce these feelings. It was said that the technology functions and features are capable of inducing these feelings in the individuals. Therefore, this research proposed an extension on the technology acceptance model by including this two affect states on the use of KS tools by the knowledge workers in the MSC-status organizations in Malaysia. Indication of the respondent's feelings was recorded at eight different points in times on the instrument to gather the different affective states of the knowledge workers on using the knowledge sharing tools. The measurement scale was adapted from Perlusz [39]. Two groups of undergraduate students were used to validate the scale, and it was found that the technology affect scale were consistent and valid in Perlusz studies.

In this research, PA and NA are defined as the perception on KS tools' characteristics in terms of features and functions to induce positive or negative affective states [36, 37, 40]. PA and NA were adapted from Zhang and Li [36], where they defined PA and NA as the perception of an IT's capability to induce positive or negative affect. It is an individual's perception or evaluation that an IT has the features and functions to induce positive or negative affect in him or her. In this study, the external stimulus is KS tools used by the knowledge workers in the MSC-status organizations in Malaysia. The respondents were asked to indicate the extent of how he/she feels on the usefulness, ease of use, and intention to use the KS tools in eight different points in times in the instrument. The different affective states of the knowledge workers were self-reported on the survey form. The measurement scale for PA and NA is adopted from Technology Affect Scale [39] where Perlusz [39] adapted the 10-item scale from Watson and Tellegen [41]. The scale was validated using two groups of undergraduate students who were exposed to several types of affects before interacting with mobile technologies. The Technology Affect Scale is found to be consistent and valid in his experiments.

### **4.1. PU, PEOU, ATT, and BI in technology acceptance model**

The relationships among PU, PEOU, ATT, and BI are consistent with the literature. TAM originally included attitude as a mediator between the personal beliefs constructs, and behavioral intention [4]. Individual's actual usage of the technology is dictated by behavioral goal, which is determined by perceived usefulness and perceived ease of use. The value of perceived usefulness is the degree to which an individual trusts that utilizing the innovation will upgrade his or her employment performance, and perceived ease of use is the degree to which individual trusts that utilizing the technology will be free of effort [4].

H7: There is a significant relationship between PEOU and PU.

H8: There is a significant relationship between PU and ATT.

H9: There is a significant relationship between PEOU and ATT.

H10: There is a significant relationship between ATT and BI.

### **4.2. PA and NA on the perceived usefulness, perceived ease of use, and behavioral intention to accept KS tools**

This research considers PA and NA based on evidences obtained by Zhang and Li [36]. They found that PA strongly influences PEOU, PU, and ATT, while NA only influences PEOU at the initial stage of usage. In their work, BI is mediated by ATT, but the direct influence of PA and NA on BI was not being investigated (**Figure 4**). Isen [42] presented his findings by stating that positive affect state such as joy and elation will lead a person to be creative, playful, and explore innovative ideas and think broadly. Another piece of work conducted by Isen et al. [38] using four experiments on positive and negative affects induced by a series of activities such as watching comedy films for few minutes, receiving a small bag of candy, or showing film of unpleasant feelings. They found that positive affect induced by a comedy film or a small gift of candy facilitates creativity on tasks given. At the same time, activities that designed to induce negative affect using primitive arousal devoid of any affective tone (exercise) had no effect on these measures. In their findings, negative affect neither facilitates nor impairs creativity. However, they pointed out that one of their experiments showed that negative affect was only induced by showing subjects film that induces unpleasant feelings. The proposed work in this research hypothesized the extent of how a person feels in his perception on the KS tools' features and functions (or characteristics) in their day-to-day tasks that induce positive or negative affect. This research fills the gap by examining the relationship of PA and NA and the behavioral intention to accept KS tools in the organizations. The affect induced by the perception toward how knowledge workers evaluate KS tools' affective quality is believed to be able to influence an individual's behavior and intention to accept a

**Figure 4.** ATA model.

tool. Affect construct included in the proposed Affective Technology Acceptance Model, the hypothesis is as follow:

H1: There is a significant relationship between PA and BI.

H2: There is a significant relationship between PA and PU.

H3: There is a significant relationship between PA and PEOU.

H4: There is a significant relationship between NA and PU.

H5: There is a significant relationship between NA and PEOU.

H6: There is a significant relationship between NA and BI.
