Performance expectancy and use of enterprise architecture: training as an intervention

The theoretical basis of enterprise architecture: A critical review and taxonomy of relevant theories

Enterprise architecture is a collection of artifacts describing various aspects of an organization from an integrated business and IT perspective. Practicing enterprise architecture in organizations implies using these artifacts to facilitate information systems planning and improve business and IT alignment. Despite its long history, the enterprise architecture discipline still remains largely atheoretical and lacks a solid theoretical basis. Based on our previous empirical studies of the practical usage of enterprise architecture artifacts in multiple organizations and broad literature analysis, this conceptual article identifies and discusses in detail 10 theories that can be considered key for understanding how an enterprise architecture practice works: actor-network theory, boundary objects theory, cognitive fit theory, communities of practice theory, decision-making theories, information processing theory, knowledge management theory, management fashion theory, media richness theory, and uncertainty principle. Taken together, these theories offer a comprehensive theoretical view of an enterprise architecture practice explaining the role of enterprise architecture artifacts, their usability, and participation of stakeholders and, therefore, may constitute a theoretical basis of the entire enterprise architecture discipline. Although this article does not elaborate on any of these theories, it brings these theories to light, establishes their critical importance for comprehending an enterprise architecture practice, and positions them as central to the enterprise architecture discourse. Each of these theories can be leveraged by enterprise architecture scholars in their future studies for analyzing enterprise architecture practices through respective theoretical lenses. This article intends to provide fresh theoretical insights on enterprise architecture, spark new waves of theoretical enterprise architecture research, and contribute to the development of a sound theoretical foundation for the enterprise architecture discipline.

Impacts of computerized maintenance management system and relevant supportive organizational factors on total productive maintenance

Purpose

The application of automated systems is rapidly increasing in different industries and organizations. In this regard, computerized maintenance management systems (CMMS) using information technology play an important role in the automating production systems. The purpose of this paper is to investigate the impacts of CMMSs and relevant supportive organizational factors on the effectiveness of total productive maintenance.

Design/methodology/approach

This study is classified as a quantitative survey-based research using structural equation modeling. The scope of the study includes manufacturing companies in Iran. A total of 125 questionnaires from 60 companies were collected from January to March 2014 to help validate the conceptual model and test the hypotheses.

Findings

The results support the concept CMMSs positively relates to relevant supportive organizational factors (resource allocation, decision-making structure, senior management support, employees’ involvement and effective instruction) on the effectiveness of total productive maintenance. The relevant supportive organizational factors can also be seen as the predictors of CMMSs.

Originality/value

This study integrates the CMMSs and relevant supportive organizational factors in a robust model to examine the effectiveness of total productive maintenance. This study also examines the impacts of CMMSs and relevant supportive organizational factors on total productive maintenance which seems to not be done previously.

Enterprise Architecture: What Did We Study?

Enterprise architecture (EA) is a description of an enterprise from an integrated business and IT perspective intended to improve business and IT alignment, and is used in the majority of large companies. However, despite that EA was established as an independent discipline long ago, a commonly accepted “big picture” in EA research is still missing. As a result, the scope of the EA discipline is vague, the extent of diversity in EA publications is poorly understood and the progression of the EA research stream over time is unclear. In this paper I conduct a comprehensive EA literature review covering 1075 publications aiming to structure, clarify and consolidate the whole EA research stream. I analyze the distribution of the EA research stream by time, source, research methodology and attitude, code all the issues discussed in EA publications into 42 narrow EA-related topics and 11 broader themes, establish the conceptual relationship between them and present a picture of the EA discipline “on a page”. Moreover, I classify all EA-related topics into four categories according to their lifecycles helping future EA researchers to better understand the evolution of the EA discipline and make the maximum contribution to it.

Conceptual Model of Enterprise Architecture Management

Enterprise architecture (EA) is a description of an enterprise from an integrated business and IT perspective. Enterprise architecture management (EAM) is a management practice embracing all the management processes related to EA aiming to improve business and IT alignment. EAM is typically described as a sequential four-step process: (i) document the current state, (ii) describe the desired future state, (iii) develop the transition plan and (iv) implement the plan. This traditional four-step approach to EAM essentially defines the modern understanding of EA. Based on a literature review, this paper demonstrates that this four-step approach to EAM, though practiced by some companies, is inadequate as a model explaining the EAM phenomenon in general. As a substitute, this paper synthesizes the generic conceptual model of EAM providing a more realistic conceptualization of EAM describing it as a decentralized network of independent but interacting processes, artifacts and actors.