Generic filters
Exact matches only
Filter by content type

Prof. Dr. Kazem Haki

Büro 52-6150
Müller-Friedberg-Strasse 6/8
9000 St. Gallen
+41 71 224 3248


  • Enterprise Architecture
  • Process (vs. Variance)-based Theories
  • Enterprise-wide Information Systems
  • Publikationen

    Platform ecosystems are complex ecologies of firms with individual competencies and collective objectives. The sustainable evolution of platform ecosystems is thereby contingent on taking advantage of the individual competencies of the ecosystem’s actors toward obtaining collective objectives. To learn more about platform ecosystem evolution and dynamics, we study Salesforce, a leading and thriving B2B platform ecosystem. We find that the ecosystem’s evolution was closely defined not only by the platform owner’s orchestrating initiatives, but also by its complementors’ and customers’ competencies and particularities. Specifically, we derive three distinct dimensions of evolution, namely the extension of the platform core technology, the extension of the platform’s functional scope, and the industry-specific specialization of the platform. We further identify three cross-dimension levers, namely proprietary developments, acquisitions, as well as partnerships and alliances, which were employed by the platform owner to drive its platform ecosystem’s evolution.

    Firms struggle to meet dynamically changing customers’ needs. One challenge is to navigate a complex search space to find resources needed for innovations that meet customers’ needs. Another challenge is to acquire the resources at lower costs than revenue opportunities to yield profitability. Digital platforms promise to address these challenges better than the market by providing search matching capabilities and modular, reusable resources. We examine whether platforms improve innovation performance and profitability of firms better than the market, as assumed. Using agent-based modeling and simulation, we find that firms perform better in the market when environmental complexity is low. As environmental complexity increases, firms start to perform better on the platform than in the market, specifically when the platform owner remarkably invests in search matching and modularity capabilities. The study advances our understanding of the environmental conditions under which platforms could be superior or inferior to the market.

    Today’s fast-growing and ever-changing business environments force software development teams to release high-quality software on a tight schedule. The notion of technical debt (TD) captures the technical compromises wherein software quality is sacrificed for short-term goals. One of the most significant challenges for technical debt management (TDM) is time as a factor of complexity. TD arises from decisions that are favorable in the short term but cause a need for complex and costly actions in the long term. Building on the applications of nudges – the use of small design modifications in choice environments to guide people’s behavior – and on their psychological effects, in this design science research we develop and evaluate design elements of a Technical Debt Management Label (as a TDM nudge) in a technology-driven organization. The TDM label aims to guide software developers’ decisions towards adopting TDM activities that are favorable in the long term.

    Digital platforms (DPs) – technical core artifacts augmented by peripheral third-party complementary resources – facilitate the interaction and collaboration of different actors through highly-efficient resource matching. As DPs differ significantly in their configurations and applications, it is important from both a descriptive and a design perspective to define classes of DPs. As an intentionally designed artifact, every classification pursues a certain purpose. In this research, the purpose is to classify DPs from a business model perspective, i.e. to identify DP clusters that each share a similar business model type. We follow Nickerson et al.’s (2013) method for taxonomy development. By validating the conceptually derived design dimensions with ten DP cases, we identify platform structure and platform participants as the major clustering constituent characteristics. Building on the proposed taxonomy, we derive four DP archetypes that follow distinct design configurations, namely business innovation platforms, consumer innovation platforms, business exchange platforms and consumer exchange platforms.

    Inspired by the city planning metaphor, enterprise architecture (EA) has gained considerable attention from academia and industry for systematically planning an IT landscape. Since EA is a relatively young discipline, a great deal of its work focuses on architecture representations (descriptive EA) that conceptualize the different architecture layers, their components, and relationships. Beside architecture representations, EA should comprise principles that guide architecture design and evolution toward predefined value and outcomes (prescriptive EA). However, research on EA principles is still very limited. Notwithstanding the increasing consensus regarding EA principles’ role and definition, the limited publications neither discuss what can be considered suitable principles, nor explain how they can be turned into effective means to achieve expected EA outcomes. This study seeks to strengthen EA’s extant theoretical core by investigating EA principles through a mixed methods research design comprising a literature review, an expert study, and three case studies. The first contribution of this study is that it sheds light on the ambiguous interpretation of EA principles in extant research by ontologically distinguishing between principles and nonprinciples, as well as deriving a set of suitable EA (meta-)principles. The second contribution connects the nascent academic discourse on EA principles to studies on EA value and outcomes. This study conceptualizes the “mechanics” of EA principles as a value-creation process, where EA principles shape the architecture design and guide its evolution and thereby realize EA outcomes. Consequently, this study brings EA’s underserved, prescriptive aspect to the fore and helps enrich its theoretical foundations.

    Understanding how information systems (IS) architecture evolves and what outcomes can be expected from the evolution of IS architecture presents a considerable challenge for both research and practice. The evolution of IS architecture is marked by management’s efforts to keep local and short-term IS investments in line with enterprise-wide and long-term objectives, so they often employ coercive mechanisms to enforce enterprise-wide considerations on local actors. However, an organization is shaped by a multitude of heterogeneous local actors’ actions that pursue their own, sometimes conflicting, goals, norms, and values. This study offers a theory-informed simulation model that explores how IS architecture evolves and with what outcomes in various types of organizations. The simulation model is informed by institutional theory to capture various types of organizations that are characterized by different combinations of coercive, normative, and mimetic pressures, and by complex adaptive systems theory to capture the emergent character of IS architecture’s evolution. First, we outline the insights from simulation experiments. Then, building on the simulation model and theoretical insights, we discuss implications for both research and practice.

    Enterprise architecture management (EAM) in organizations often requires coping with conflicts between long-term enterprise-wide goals and short-term goals of local decision-makers. We argue that these goal conflicts are similar to the goal conflicts that occur in public goods dilemmas: people are faced with a choice between an option (a) with a high collective benefit for a group of people and a low individual benefit, and another option (b) with a low collective benefit and a high individual benefit. Building on institutional theory, we hypothesize how different combinations of institutional pressures (coercive, normative, and mimetic) affect decision makers’ behavior in such conflictive situations. We conduct a set of experiments for testing our hypotheses on cooperative behavior in a delayed-reward public goods dilemma. As preliminary results, we find that normative and mimetic pressures enhance cooperative behavior. Coercive pressure, however, may have detrimental effects in settings that normative and mimetic pressures are disregarded. In future work, we plan to transfer the abstract experimental design of an onlinelab experiment into a field experiment setting and thus into the real-world context of EAM.

    To unlock additional business value, most enterprises are intensifying their enterprise-wide data management. In the case of the globally operating bank, we base this article on, a Chief Data Officer (CDO) organization is established for providing data governance and, in a second step, pushing data driven innovation forward. As many employees of the bank were not yet familiar with (or did not acknowledge) the need for enterprise-wide data management, this evolution exhibits characteristics of an organizational learning process. CDOs may want to actively steer this learning process by purposefully designing and adjusting their data management approach over time. Based on the major controversies the CDO has been confronted with, we propose four design dimensions for enterprise-wide data management and discuss the considerations for their configuration: (I) objective, (II) governance, (III) organization of data analytics, and (IV) expertise.

    In the context of digital platforms, platform owners strive to maximize both their platform’s stability and generativity. This is complicated by the paradoxical relationship of generativity and stability, as well as associated tensions. To aid B2B platform owners in their design decisions, we aim to derive specific design principles that address the inherent tensions such that generativity and stability are maximized simultaneously. This requires a better understanding of when and to which extent a platform’s generativity and stability are paradoxical, and under which circumstances they can be maximized simultaneously. Thus, we first develop an agent-based simulation model to analyze the effects of an exemplary design decision regarding a tension (i.e. control vs. openness) on a platform’s generativity and stability. The developed simulation model enables predictive analyses of varying degrees of control and openness and their effect on generativity and stability. The simulation model must be further refined and applied to other tensions to thoroughly understand the impact of design decisions on a platform’s generativity and stability, and ultimately derive design principles.

    Information systems (IS) increasingly expand actor-to-actor networks beyond their temporal, organizational, and spatial boundaries. In such networks and through digital technology, IS enable distributed economic and social actors to not only exchange but also integrate their resources in materializing value co-creation processes. To account for such IS-enabled value co-creation processes in multi-actor settings, this research gives rise to the phenomenon of digital value co-creation networks (DVNs). In designing DVNs, it is not only necessary to consider underpinning value co-creation processes, but also the characteristics of the business environments in which DVNs evolve. To this end, our study guides the design of DVNs through employing service dominant logic, a theoretical lens that conceptualizes value co-creation as well as business environments. Through an iterative research process, this study derives design requirements and design principles for DVNs, and eventually discusses how these design principles can be illustrated by expository design features for DVNs.



    PhD in Information Systems from the University of Lausanne, Faculty of Business and Economics (HEC), Switzerland

    M. Sc. in Information Technology Management from the University of Tehran, Faculty of Management, Iran 


    ICT Consultancy Department Deputy Manager, MAGFA IT Development Center, Iran (2 years)

    Manager of “Data Warehousing and Business Intelligence” Department, MAGFA IT Development Center, Iran (7 months)

    Enterprise Architecture Project Manager (ten projects), MAGFA IT Development Center, Iran (3 years)

    Customer Relationship Manager, MAGFA IT Development Center, Iran (1 year) 


    Nominated for the best paper award at the European Conference on Information Systems (ECIS), 2016“IMD

    Business School” scholarship foundation prize   


    Association for Information Systems (AIS)

    Swiss Chapter of the AIS (CHAIS)