Search results

Effectively managing an intermodal logistics network has become a significant strategic consideration in international logistics. This study aims to empirically examine the way in which intermodal logistics network coordination can be successfully developed and sustained, and to analyze whether the highly coordinated intermodal logistics network may facilitate the greater logistics performance of network players as well as of the entire intermodal logistic network system. This study adopts social network embeddedness perspective to examine the determinants facilitating the higher level of coordination of the intermodal logistics network. An explorative interview method is being employed for the empirical analysis, and the results show that strong, dense and bridging ties within the network mechanisms facilitate a greater intermodal logistics network coordination. As a result, this helps to enhance the logistics performance of the intermodal logistics network system and its players by facilitating the enhancement of logistics services effectiveness and operational efficiency.

The primary purpose of this paper is to examine how generative Artificial Intelligence (AI) such as ChatGPT may serve as a new context for management theories and concepts.

The paper presents the analyses of selected management theories on decision-making, knowledge management, customer service, human resource management and administrative tasks and explains what may change after generative AI adoption.

The paper indicates that some management theories and concepts need to be studied in the generative AI environment that may influence managerial work at the strategic, functional and administrative levels.

This paper is an opinion piece article and does not refer to empirical data. It formulates some conclusions to further empirical research studies.

The paper analyzes selected management theories in a new technological setting. The paper also provides information about the functions of generative AI that are useful in understanding and overcoming how new technology may change organizations and management.

This paper aims to contribute to the management control systems (MCS) changes in public-private partnerships (PPSs) by developing a conceptual archetype explaining the relationship between trust and MCSs in PPPs, and highlighting how this relationship may evolve over time.

The paper adopts a longitudinal case study methodology focusing on a hospital built and operated under a project finance deal. The methods adopted include semistructured interviews, direct observation and internal documentation analysis. We conducted 15 semistructured interviews from 2019 to 2021. In analyzing different documents and interviews, we triangulated data to ensure solid interpretation.

The case shows how trust can take different configurations depending on the type of MCS used. The results highlight how different patterns of MCSs, about trust, can be combined to govern PPPs. The case also shows the temporal dynamics of how MCS and trust evolve at different organizational levels and how bureaucratic control matched with contractual trust and trust-based control matched with competence trust can coexist at different times and organizational levels.

Managers involved in PPPs will be aware of the role of different types of trust in shaping and managing the relationship between partners at different organizational levels. Furthermore, the findings could help policymakers to adopt more informed decisions and to promote practice-based trust at various organizational levels of PPPs.

The paper proposes a management control archetype based on bureaucracy- and trust-based patterns concerning the level of programmability of tasks, as well as defined risks.