The Capability Maturity Model Integrated as a Market Engineering Maturity Model

Abstract

This article examined a variant of the capability maturity model integrated (CMMi) through the lens of market engineering process improvement. The population and sample represented a national array of U.S. marketing organizations. Using ANOVA, a 0.05 significance level, and a stratification of urban marketing organizations versus rural marketing organizations, the study showed three statistically significant differences representing the second (p = 0.00; M = 2.90), fourth (p = 0.01; M = 3.22), and sixth hypotheses (p = 0.04; M = 3.15). The second hypothesis corresponded to the first maturity level (ad hoc, random processes), the fourth hypothesis corresponded to the third maturity level (characterized and expressed processes), and the sixth hypothesis corresponded to the fifth maturity level (optimized processes).

Building a Digital Transformation Maturity Evaluation Model for Construction Enterprises Based on the Analytic Hierarchy Process and Decision-Making Trial and Evaluation Laboratory Method

“…The model, abbreviated as SW-CMM or CMM, was successfully developed by the Software Engineering Institute of Carnegie Mellon University in 1987 [24]. It is the world's most popular and practical software production process standard and software enterprise maturity level certification standard, describing each development stage in the practice of software organizations in defining, implementing, measuring, controlling, and improving their software processes [25]. The core of the CMM is to treat software development as a process and, according to this principle, conduct process monitoring and research into software development and maintenance to make it more scientific and standardized and enable enterprises to achieve business goals better [26].…”

Pre-Crime Prediction

“…At the time of this writing, an insufficient amount of time existed for data to accumulate regarding the impacts of predictive policing from a long-term, strategic view. Frei and Ruloff (1989) and Doss, et al, (2021Doss, et al, ( , 2020 indicated that an average of 20 years of data should be collected and analyzed before effective policy assessment or evaluation may occur. Given that upwards of two decades of data may be necessary for such analysis, future researchers may examine predictive tools as strategic organizational resources when sufficient time has passed to accumulate data.…”

Analyzing Critical Influencing Factors of the Maturity of Smart Construction Site Applications

“…Since then, the concept has been extended to various domains, including information technology, smart cities, smart grids, safety, health, and environmental management [12,13]. Maturity models use a series of pre-defined maturity levels to represent the evolution of the subject from nonexistent, initial, unstructured stages to highly mature optimized processes [14]. Each maturity level represents a specific phase in the subject's capability, efficiency, and complexity within the relevant domain [15].…”

“…Each maturity level represents a specific phase in the subject's capability, efficiency, and complexity within the relevant domain [15]. The model is designed to help institutions identify their current level of capability, identify opportunities for improvement, and, by implementing appropriate actions, increase their overall maturity to improve their effectiveness and competitive advantage [14]. Therefore, conducting maturity research on the application of smart construction sites is of significant importance in identifying the key factors limiting current development and facilitating the transformation and upgrading of the construction industry.…”