TLDR: This research paper addresses the challenges of training IT professionals for information system integration during post-merger integration (PMI). Existing methods (AMILI and AMILP) suffer from a high learning curve and low motivation. The paper proposes a game-based learning design framework to transform static training into an engaging experience. It outlines requirements for this framework, drawing on learning theories, cognitive load models, and motivational theories, while specifically accounting for the unique complexities and constraints of PMI. The goal is to create an effective and motivating training solution for a critical, yet underserved, area of corporate integration.
Mergers and Acquisitions (M&A) are a common strategy for organizational growth, aiming to create synergies and achieve outcomes that individual organizations couldn’t. A critical phase in this process is post-merger integration (PMI), which involves physically reconstructing the merging organizations, including their structures, functions, and resources. Information systems (IS) play a vital role in supporting all organizational processes, making their integration a crucial, yet often overlooked, aspect of PMI.
While extensive guidance exists for PMI at the business level, there’s a significant gap in training specifically for information system integration in this complex context. Often, IT professionals tasked with IS integration in PMI lack prior experience, assuming it’s similar to standard system integration. However, IS integration in PMI is fundamentally different: systems need to be identified, and integration options range from leaving systems as they are, to replacing one, or even implementing entirely new systems, rather than just establishing data exchange between existing ones.
To address this, previous research introduced methods called AMILI (Support method for informed decision identification) and AMILP (Support method for informed decision-making) to assist with IS integration decisions in PMI. While these methods proved effective in helping inexperienced professionals achieve results comparable to experienced ones, feedback revealed a high learning curve and low learner motivation. The instructions were difficult to follow, and the detailed descriptions required significant time and effort to comprehend, especially under the high-pressure, time-constrained, and often low-incentive environment of real-world PMI activities.
Transforming Learning Through Games
This paper proposes a compelling solution: transforming the training for these complex methods into an engaging, game-based learning experience. The core hypothesis is that interactive game-based learning can compensate for the challenge of learning serious material and a lack of motivation. The research explores existing approaches to convert method training into serious games, which are games designed with a primary purpose beyond pure entertainment, such as education or corporate training.
The study adopts a design science methodology, focusing on problem identification and defining requirements for this game-based learning design framework. It draws upon foundational learning theories to ensure the design of effective learning experiences. These include Constructivist Learning Theory (learners actively construct understanding), Experiential Learning Theory (learning through experience and reflection), Situated Learning Theory (learning in real-world contexts), and Transformative Learning Theory (reflection and integration of new insights).
Collectively, these theories suggest that effective learning should be proactive (active learner involvement), applied (practical and goal-oriented), contextual (mapped to real-world scenarios), reflective (processing and evaluating results), and progressive (gradually increasing complexity).
Addressing Cognitive Load and Motivation
A key challenge in learning complex material is the limited human working memory, studied under Cognitive Load Theory. This theory identifies three types of cognitive load: intrinsic (inherent complexity of material), extraneous (unnecessary load from poor instructional design), and germane (useful load for practical application). The framework aims to reduce extraneous load through clear design and intuitive interfaces, while managing intrinsic load with strategies like segmentation and pre-training, and fostering germane load through varied practice and feedback.
To tackle learner motivation, the research incorporates models like BJ Fogg’s Behavior Model and motivational theories such as Expectancy-Value Theory (learners weigh task value against difficulty and success chances) and Self-Determination Theory. The Self-Determination Theory highlights three components for intrinsic motivation: autonomy (control over experience), competence (feeling capable), and relatedness (connection to context and others). Game-based learning is particularly effective here, as game mechanics like clear goals, immediate feedback, and voluntary engagement can enhance learners’ perception of autonomy and competence, shifting motivation from extrinsic to intrinsic.
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A Tailored Framework for PMI
The paper identifies essential requirements for a game-based learning design framework specifically tailored for IS integration in PMI. These requirements are structured into two main components: the transformation process (how the learning experience is designed) and the resulting learning experience (how training is delivered and perceived by learners). Functional, quality, and constraint requirements are defined for both components, drawing from instructional design methodologies, game-based learning approaches, and specific challenges of PMI.
What makes this proposed framework unique is its explicit separation of the design process from the learning experience, providing clear guidance for designers while ensuring the final product meets learning goals. Crucially, it is designed to teach the unique characteristics of post-merger information system integration, addressing specialized decision-making not covered by general-purpose frameworks. Furthermore, it considers constraints specific to post-merger environments, such as data confidentiality, limited timeframes, and complex stakeholder management.
This research lays the groundwork for future work, which will involve developing the framework itself, including transformation guidelines and example learning experiences. These will be iteratively tested and evaluated using real-world case studies to assess their effectiveness in terms of learner performance, engagement, and long-term knowledge retention. Ultimately, this framework could extend its application beyond PMI to broader digital transformation and complex system change initiatives across organizations. You can read the full paper here: Requirements for Game-Based Learning Design Framework for Information System Integration in the Context of Post-Merger Integration.
