Fostering adoption, acceptance and assimilation in ... - KnowMiner

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Characteristics, Technological Infrastructure and Resources combine factors that are related to particular organizational properties in the context of its communication processes and practices, the technology already in place with which the KMS needs to be connected and monetary and human resources related to the adoption of the KMS. The groups are graphically presented within the final model in figure 1. Table 1: List of Factors for Organizational Adoption Factor name Model/Theory Adopter type DOI Availability TOE Characteristics TOE Commercial Advantage DOI Communication Process TOE Community Norms DOI Compatibility DOI Complexity DOI Cultural Values DOI Formal and Informal Linking Structures TOE Funding DOI Government Regulations TOE Industry Characteristics and Market Structure TOE Informal Communication DOI Information Quality ISSM Management Hierarchy DOI Observability DOI Opinion Leaders and Change Agents DOI Organizational Impact ISSM Organizational Viability FVM Price DOI Problem Solver DOI Relative Advantage DOI Risk DOI Size TOE Service Quality ISSM Slack Resources TOE Standard DOI System Quality ISSM Task-Technology Fit FVM Technological Edge DOI Technological Experience DOI Technological Infrastructure DOI Technology Support Infrastructure TOE Trialability DOI User Need Recognition DOI User Resistance DOI The factors within the groups Environment, Organizational Characteristics, Technological Infrastructure and Resources cannot be directly influenced by KMS design, as they are organization specific path-dependent idiosyncrasies or externally determined. In contrast, the factors categorized in Innovation Characteristics, Communication Characteristics and Expected Results are affected by decisions related to the KMS design, as many of them correspond to qualities and features of the KMS product. Fit is a mapping between KMS and the selected tasks and environment it should support and thus supposedly can also be influenced by KMS design. 3.2 Acceptance Factors We identified 22 factors explaining the acceptance of KMS by users as listed in table 2. The factors influencing the acceptance have been categorized into four groups. Two groups combine all expectancy-related factors: Effort Expectancy collects factors related to users’ perceptions of what they need to contribute to work with the KMS (input) and Performance Expectancy collects factors related to users’ perceptions of what the impact of working with the KMS will be (output). The factors in the third group are moderating factors from the social environment of a user (Social Influences) and the factors in the last group are personal factors impacting the acceptance decision (Attitude towards Technology- Use). Consequently, factors within the groups Attitude towards Using Technology and Social Influence are depending on culture, organizational peculiarities and personal preferences and thus cannot be directly influenced by design. The factor groups Performance Expectancy and Effort Expectancy are also underlying subjective influences, however, these factor can be influenced by KMS design, e.g., by ensuring high quality standards and providing useful product features. Table 2: List of Factors for User Acceptance Factor name Model/Theory Affect Towards Use SCT; MPCU Anxiety SCT Attitude Toward Behavior TRA; TPB Compatibility DOI Complexity MPCU Ease of Use DOI; TAM; TAM2 Extrinsic Motivation MM Facilitating Conditions MPCU Image DOI Intrinsic Motivation MM Job-Fit MPCU Long-term Consequences MPCU Outcome Expectations - Performance SCT Outcome Expectations - Personal SCT Perceived Behavioral Control TPB Usefulness TAM; TAM2 Relative Advantage DOI Results Demonstrability DOI Self-efficacy SCT Social Factors MPCU Subjective Norm TRA; TAM2; TPB Visibility DOI 3.3 Assimilation Factors Lastly, table 3 presents 22 factors that influence the assimilation of a KMS. The collected factors were categorized into four groups: Institutional Characteristics, combining factors related to certain characteristics of the organization adopting the KMS, Social System Characteristics combining factors describing social structures, as well as communication and collaboration peculiarities of the organization, Process Characteristics, combining factors describing processes in terms of a set of standard process goals; and lastly Management Characteristics, which include factors related to management quality, support and selected practices deemed important for the success of KMS assimilation into the organization.
In consideration of the fact that assimilation as a third step refers to the diffusion of a solution into organizational processes and work practices, nearly all of the factors correspond to organization-specific peculiarities. However, when looking at the factors that are highly affected by a new KMS, we expect Process Characteristics and Social System Characteristics to change depending on the design of the introduced KMS. Consequently, the factors within these two groups can be indirectly influenced by design decisions. In contrast, the introduction of a KMS will probably have less impact on Management Characteristics or Institutional Characteristics. Table 3: List of Factors for Process Assimilation Factor name Model/Theory Communication Channels Use DOI Decision-making Patterns DOI Extent of Coordination INST Functional Integration DOI Knowledge Barrier DOI Knowledge Embeddedness DOI Management Championship INST Methodology Influence INST Organizational Size KBT IT Function Size DOI; INST Process Cost BPM Process Quality BPM Process Time BPM Process Satisfaction BPM Promotion of Collaboration DOI Quality of Senior Leadership KBT Sophistication of IT Infrastructures KBT Strategic Investment Rationale INST Structures of Significance ST; INST (cognitive) Structures of Domination ST; INST (regulatory) Structures of Legitimation ST; INST (normative) Top Management Championship ST 3.4 Resulting Model Figure 1 presents the comprehensive model that combines factors impacting on the process of adoption, acceptance and assimilation of KMS. Moreover, the factors have been categorized so that guidance can be offered on two levels of granularity, namely the level of groups of factors and the level of individual factors. Furthermore, the model visually separates the groups that can be influenced within the design phase from groups that cannot be influenced as argued above. This differentiation seems useful because designers of KMS can distinguish between factors that can be influenced and thus are important when eliciting functional and non-functional requirements while others can be considered as environmental limitations which need to be taken into account particularly when packaging a KMS and offering it to various target groups. The set of groups that cannot be influenced by design partially consists of environmental characteristics which cannot be directly manipulated, neither by providers of KMS nor by organizations using them. Other factors that cannot be influenced correspond to characteristics of an organization and individuals willing to adopt a new technology that are comparably stable over time. However, some factors in this set of groups can be changed when using a KMS. Examples are Social Systems Characteristics which are influenced by IT and also influence how IT is used. According to AST, designers should particularly be aware of these characteristics and should explicitly state the intended use of the KMS which, however, needs to be distinguished from the KMS’s actual use in a particular organization. 4. RELATED WORK & APPLICATION Thus far, we have presented a comprehensive model of factors relevant for KMS design impacting the adoption, acceptance, and assimilation of IT. The model intends to provide guidance for analyzing and reflecting decisions related to KMS design, development and implementation in organizations based on the collected factor groups and their factors for each phase in the context of an ongoing software project. This manner of informing software design, comprising for example phases such as requirements elicitation, configuration, packaging, and offering, is not yet widely observable in the domain of KM. However, some comparable work in the general domain of IS research can be named. In ongoing research, an evaluation model for Question Answering Systems has been developed that focuses on user-centered evaluation rather than on system-centered evaluation. The proposed model comprises constructs taken from behavioral science models, such as TAM, UTAUT, TRA, and TPB, to increase user acceptance when designing Question Answering Systems [39,40]. Another study focuses on Employee Relationship Management systems and investigates the impact of usefulness on systems quality perceptions. Specific user needs should be considered in the analysis phase of system design and therefore need to be assessed properly. The model draws upon TAM among others to explain perceived usefulness [41]. It is rather common to use research results amalgamated into a single model for predicting behavior to inform system design. For example, a study used TAM to measure perceived usefulness when analyzing the connection between website design and impulse buying in the domain of e-commerce. Subsequently, research results were used to give concrete recommendations for e-commerce website designers [42]. In the application of our model we followed a similar approach. In context of a large-scale research and development project, we applied the proposed model for informing and extending requirements elicitation (especially for non-functional requirements), as well as supporting decisions with respect to packaging and offering of the KMS implemented in this project. The project aims at designing an ICT solution supporting and enhancing employees in their daily activities related to Human Resource Management, Business Process Management, KM and Innovation Management. In our efforts to increase adoption, acceptance, and assimilation of this KMS, 77 recommendations were developed for the design of the platform and addressed to platform architects, designers and developers of related business plans. These recommendations were developed by evaluating so far defined requirements, technological trends, and the ICT landscapes of pilot organizations in respect to our model. The remainder of this section will exemplify the use of the presented model to describe a collection of additional requirements and recommendations in two application areas. Here, application areas describe project-specific work groups that work on requirements elicitation, packaging and offering solutions for the KMS.
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