Purpose
The purpose of this paper is to update existing Kauffmann’s NK model to evaluate the manufacturing fitness of strategic business capabilities. The updated model is tested in a digital ...manufacturing (DM) setting to investigate the sequence for developing cumulative capabilities that can yield the maximum payoff.
Design/methodology/approach
The authors develop a grey–DEMATEL–NK fitness model and show its application, through a case study, to a DM firm in India.
Findings
The grey–DEMATEL–NK model helps evaluate multiple manufacturing capabilities and indicates that quality–flexibility–cost–delivery is the sequence that yields the maximum manufacturing fitness (competitive payoff) for a DM firm. This sequence helps the firm reorganise its internal business processes and is different from that used to develop cumulative capabilities in a traditional manufacturing setting (quality–delivery–flexibility–cost).
Originality/value
This study presents a pilot model for computing the cumulative capabilities payoff and prescribes a sequence for developing cumulative capabilities within a DM context.
High‐tech organizations maintain a portfolio of R&D projects that address problems with different levels of complexity. These projects use different strategies to search for technological solutions. ...Projects refining existing products, processes, and technologies, for instance, employ a local search strategy to improve performance, while projects developing new products, processes, and technologies employ a distant search strategy. However, projects can shift in their levels of complexity due to exogenous technological changes, and failure to change search strategy in turn can negatively impact project performance. This study first develops grounded theory via case studies to understand how high‐tech organizations manage R&D projects when complexity shifts. The case data come from 142 informants in 12 R&D projects at three high‐tech business units. A cross‐case comparison shows that three interconnected mechanisms positioned at multiple levels within the organization enable high‐tech organizations to identify such shifts and adjust the project's search. We refer to this strategy as responsive search. We then conduct agent‐based simulation experiments to examine the conditions under which the responsive search outperforms other canonical search strategies. Overall, this study sheds light on the underexplored question of how to make mid‐project corrections by effectively identifying and managing shifts in project complexity.
Using a simulation of organizational adaptation in turbulent and complex landscapes, I examine how the optimal balance between exploration and exploitation is influenced by the organization's task ...environment. I find that, contrary to conventional wisdom, increasing exploration relative to exploitation is not always the optimal response to increased environmental turbulence or complexity. Turbulence is found to have a curvilinear effect on the optimal share of exploratory versus exploitative adaptation, with the relative importance of exploitation greatest at moderate degrees of turbulence. While environmental complexity is found to have a generally positive effect on the optimal share of exploration, the effects of complexity and turbulence are found to interact and, jointly, to increase the relative importance of exploitative adaptation over exploratory adaptation. These findings suggest that the proper exploration–exploitation balance depends, in complex ways, on the pressures for global versus local adaptability posed by the interaction of turbulence and complexity.
Companies innovating in dynamic environments face the combined challenge of unforeseeable uncertainty (the inability to recognize the relevant influence variables and their functional relationships; ...thus, events and actions cannot be planned ahead of time) and high complexity (large number of variables and interactions; this leads to difficulty in assessing optimal actions beforehand).
There are two fundamental strategies to manage innovation with unforeseeable uncertainty and complexity: trial and error learning and selectionism. Trial and error learning involves a flexible (unplanned) adjustment of the considered actions and targets to new information about the relevant environment as it emerges. Selectionism involves pursuing several approaches independently of one another and picking the best one ex post.
Neither strategy nor project management literatures have compared the relative advantages of the two approaches in the presence of unforeseeable uncertainty and complexity. We build a model of a complex project with unforeseeable uncertainty, simulating problem solving as a local search on a rugged landscape. We compare the project payoff performance under trial and error learning and selectionism, based on a priori identifiable project characteristics: whether unforeseeable uncertainty is present, how high the complexity is, and how much trial and error learning and parallel trials cost. We find that if unforeseeable uncertainty is present and the team cannot run trials in a realistic user environment (indicating the project's true market performance), trial and error learning is preferred over selectionism. Moreover, the presence of unforeseeable uncertainty can reverse an established result from computational optimization: Without unforeseeable uncertainty, the optimal number of parallel trials increases in complexity. But with unforeseeable uncertainty, the optimal number of trials might decrease because the unforeseeable factors make the trials less and less informative as complexity grows.
We address the contested state of theory and the mixed empirical evidence on the relationship between turbulence and vertical scope by studying how turbulence affects the benefits of commitment from ...integrated development of components and the benefits of flexibility from sourcing components externally. We show that increasing turbulence first increases but then decreases the relative value of vertical integration. Moderate turbulence reduces the value of flexibility by making supplier selection more difficult and increases the value of commitment by mitigating the status quo bias of integrated structures. Both effects improve the value of integration. Higher levels of turbulence undermine the adaptive benefits of commitment, but have a less adverse effect on flexibility, making nonintegration more attractive. We also show how complexity and uneven rates of turbulence moderate the nonmonotonic relationship between turbulence and integration.
This paper was accepted by Jesper Sørensen, organizations
.
In the new era, the key measure to accelerate the construction of smart city, so as to promote the modernization of urban governance system and governance capacity, is to establish a good urban ...innovation ecosystem, and guide its continuous evolution to the direction of the highest efficiency and the best performance. Focusing on solving the practical problem of “how the urban innovation ecosystem evolves”, this paper develops a NK algorithm using BP neural network and DEMATEL method. First, through literature research, constructing the urban innovation ecosystem including five subsystems of innovation talents, innovation subjects, innovation resources, innovation environment and innovation network. Then, taking Beijing as an example, the weights and the number of epistatic relationships of each subsystem in its innovation ecosystem are calculated by BP neural network and DEMATEL method, and the NK model is modified; on this basis, the fitness values corresponding to different states of the system are calculated using MATLAB software, and the optimal evolution path of Beijing innovation ecosystem is determined through the comparison of 100,000 simulation results. The results show that the optimal evolution path of Beijing's innovation ecosystem is to create a favorable environment and culture for innovation first; then increase the input of innovation resources; and then promote the development of innovation network assets; on this basis, cultivate, attract and retain innovative talents; and finally strengthen the construction of innovation subjects.
Franchisee has become a powerful tool for many logistics enterprises in affiliate mode to seize market share. But affiliate mode has emerged many drawbacks that can aggravate the divergence of ...interests between franchisees and headquarter and then leads to the problem of franchisee loss. In this paper, the franchisee loss problem is studied from the perspective of vulnerability. The loss of a franchisee is seen as a node that has been attacked. The performance change before and after an attack is used to reflect the strength of a network’s vulnerability. Efficacy and efficiency are proposed to measure the performance change based on NK model, which specializes in studying complex adaptive system such as logistics network. Results show that efficacy and efficiency vary according to network scale. For relatively small networks, their efficacy shows more obvious fluctuation with the variation of network scale than efficiency does. In these networks, the redundancy of network nodes is high. But the percentage of redundant nodes decreases with the increase of scale and the efficacy can be improved with the reduction of redundant nodes. The network structure of them is not stable. As for relatively large networks, efficiency fluctuates more apparently with the change of complexity than efficacy does. In these networks, most nodes are influential and the percentage of influential nodes shows obvious change with complexity. The network structure tends to be stable. In conclusion, the study on the influence of franchisee loss from vulnerability can provide us with greater visibility and insight into the organization structure of logistics networks. Corresponding cases are introduced to confirm our conclusions.
•We introduce NK model into the study of the influence of franchisee loss.•Based on NK model, two new measurements are proposed to measure the performance of express logistics network.•Three kinds of nodes are found in the logistics network. They can help us have a better understanding about the network.•We extend our discussions on nodes to the discussions on levels in the network as few scholars have done this work.•Small networks should focus on the enhancement of efficacy, while relatively large ones should focus on efficiency.
It is well recognized that many organizations operate under situations of high complexity that arises from pervasive interdependencies between their decision elements. While prior work has discussed ...the benefits of low to moderate complexity, the literature on how to cope with high complexity is relatively sparse. In this study, we seek to demonstrate that Lindblom’s decision-making principle of
muddling
through
is a very effective approach that organizations can use to cope with high complexity. Using a computational simulation (
NK
) model, we show that Lindblom’s
muddling
through
approach obtains outcomes superior to those obtained from boundedly rational decision-making approaches when complexity is high. Moreover, our results also show that
muddling
through
is an appropriate vehicle for bringing in radical organizational change or far-reaching adaptation.
This paper’s purpose is to clarify groupthink phenomena and to assess the devil’s advocacy as a groupthink prevention measure. An agent-based model is presented to formalize group closed-mindedness ...and insulation in a group decision making setting. The model was validated by showing that groupthink results in the decision with low quality and the group’s inability to explore more alternatives. Besides that, the devil’s advocacy also formulated in the model. The simulation results of different conditions of the devil’s advocacy support Janis’ suggestion to utilize the devil’s advocacy to alleviate groupthink. It is also found that the utilization of devil’s advocacy depends on the group’s condition and the desired amount of conflict to produce the best decision.
Diversity in teams has become an important societal and economic issue which is studied in various scientific domains. In organizational sciences, particularly empirical research methods prevail. ...This paper proposes to explore agent-based computational economics as a research approach for workforce diversity more intensely due to its inherent properties like capturing heterogeneous interacting agents. For highlighting this, this paper presents an agent-based computational model based on the framework of NK fitness landscapes. In the simulations, artificial organizations search for superior levels of organizational performance with search being delegated to several and potentially diverse decision-making agents. The experiments control for the level of task complexity and reflects four different attributes of workplace diversity among agents: cognitive capabilities to (i) generate and (ii) evaluate new solutions, (iii) effort efficiency and (iv) commitment to the overall organizational objective. The results suggest that the effects of workforce diversity differ across task complexity and attributes of diversity. Diversity of commitment has the strongest impact which results from interactions among local maximizers and agents seeking to globally maximize with only local means. Moreover, the results point to nonlinear effects of multi-attributive diversity on organizational performance.
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