Unleashing process orientation
Bibliographic record
Abstract
Purpose In the past few years, process orientation (PO) as an integral part of enterprise system (ES) implementation has been the center of attention among practitioners and academics. The purpose of this paper is to shed light on the role of PO in ES implementation through an empirical study of Canadian and US firms. Design/methodology/approach A comparative analysis of ES implementation was performed based on the data collected from a sample of large Canadian and US firms. Exploratory factor analyses were conducted to identify the factors associated with constructs of the research model. Moreover, path analysis approach was employed to conduct comparative analysis across the two samples. Findings The findings indicate that PO significantly reduces the challenges of ES implementation. Moreover, PO has been shown to have a positive effect on the successful implementation and utilization of ES under certain conditions. However, the level of PO at different phases is observed to have diverse effects on different aspects of ES implementation as a result of opposite forces of change. In addition, the path analysis confirms the validity of measurement of PO at three phases of ES implementation. Research limitations/implications No database of managers who have been involved in all three phases of ES implementation exists; hence, the respondents are asked to answer the questionnaire only if they are involved in all three phases of ES implementation. This places a limitation on the respond rate. Originality/value This paper is the first paper that measures PO at three phases of ES implementation and explores the effect of PO on different dimensions of ES implementation. This approach provides a novel insight into understanding of the role of PO in ES implementation. This paper offers two major contributions toward a further understanding of the business processes in organizations. The first contribution of this paper is the development of measurement systems for assessing the level of PO and various dimensions of ES implementation. The second major contribution of this paper is unveiling the role of PO in ES implementation through the comparative analysis across Canadian and US firms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".