Artificial intelligence and machine learning for maturity evaluation and model validation

In this paper, we discuss the possibility of using machine learning (ML) to specify and validate maturity models, in particular maturity models related to the assessment of digital capabilities of an organization. Over the last decade, a rather large number of maturity models have been suggested for different aspects (such as type of technology or considered processes) and in relation to different industries. Usually, these models are based on a number of assumptions such as the data used for the assessment, the mathematical formulation of the model and various parameters such as weights or importance indicators. Empirical evidence for such assumptions is usually lacking. We investigate the potential of using data from assessments over time and for similar institutions for the ML of respective models. Related concepts are worked out in some details and for some types of maturity assessment models, a possible application of the concept is discussed

Lessons to Be Learned: Political Party Research and Political Party Assistance

Generally speaking, the effects of international political party assistance are viewed nega-tively, or at least controversially. This study attributes some of the shortcomings of political party aid to the poor relationship between assistance providers and political science party research. They simply operate in different worlds. Party assistance lacks clear-cut concepts and strategies in practice, which makes it difficult to adequately evaluate it. At issue is its 'standard method,' with its 'transformative' intention to change the party organization of the assistance receivers. At the same time, the scholarship on political parties can provide only limited help to assistance providers due to its own conceptual and methodological re-strictions, such as the Western European bias underlying its major concepts, the predominance of a functionalist approach, and the scant empirical research on political parties outside of Europe and the US. Taking a cue from recent political party research, we could begin to question the overarching role of political parties in the transition and consolidation proc-ess of new democracies. Other research findings emphasize the coexistence of different types of party organizations, and the possibility of different organizational developments, which might all be consistent with consolidating democracy. All this suggests the necessity of abandoning the controversial aim of the 'transformative impact' of political party aid.Die Wirksamkeit der internationalen Parteienförderung wird als wenig effektiv beurteilt - auch wenn dieses Urteil umstritten ist. Ein Grund für die Schwierigkeiten der Parteienförderung wird hier in den kaum vorhandenen Beziehungen zwischen Parteienförderern und der Parteienforschung gesehen, die weitgehend isoliert voneinander arbeiten. Der Parteienförderung fehlen klare Konzepte und Strategien, die eine angemessene Evaluierung ihrer Aktivitäten erlauben würden. Ein Grundproblem ist ihre so genannte 'Standardmethode' mit ihrem 'Transformationsziel', dem zufolge die Organisation der Empfängerpartei verändert werden soll. Zugleich kann die Parteienforschung aufgrund ihrer eigenen Wissensgrenzen bisher nur beschränkt Hilfe anbieten. Dazu zählen der westeuropäische Bias ihrer zentralen Konzepte, die Dominanz des funktionalistischen Ansatzes und die noch immer geringen empirischen Forschungsergebnisse zu Parteien außerhalb Europas und der USA. Jüngste Forschungsergebnisse lassen vermuten, dass die Rolle der Parteien im Transitions- und Konsolidierungsprozess überschätzt wurde, andere betonen die gleichzeitige Koexistenz ganz unterschiedlicher Parteitypen und die Möglichkeit unterschiedlicher Organisationsentwicklung, was letztlich zur Konsolidierung von Demokratie führen kann. All dies legt schließlich nahe, das grundlegende Transformationsziel der Parteienförderung aufzugeben

Labor And The Politics Of Structural Adjustment In Australia And Indonesia

The labour forces of Australia and Indonesia are compared for the period from the late 1960s to the 1990s. The position of labour in a global economy is also considered. It is determined that the outlook for organised labour is bleak, however its position is also contingent upon national circumstance

Artificial intelligence and machine learning for maturity evaluation and model validation

In this paper, we discuss the possibility of using machine learning (ML) to specify and validate maturity models, in particular maturity models related to the assessment of digital capabilities of an organization. Over the last decade, a rather large number of maturity models have been suggested for different aspects (such as type of technology or considered processes) and in relation to different industries. Usually, these models are based on a number of assumptions such as the data used for the assessment, the mathematical formulation of the model and various parameters such as weights or importance indicators. Empirical evidence for such assumptions is usually lacking. We investigate the potential of using data from assessments over time and for similar institutions for the ML of respective models. Related concepts are worked out in some details and for some types of maturity assessment models, a possible application of the concept is discussed