In managerial decision-making support, computer assistance has historically been least effective in which stage of the decision process (identifying alternatives, evaluating them, or choosing one)?

Introduction / Context:
Decision support systems (DSS) and analytics tools help managers structure problems, generate options, and evaluate consequences. Yet, the ultimate choice among alternatives often requires human judgment, values, and risk appetite. This item tests where computers typically contribute the least in the classic decision cycle.

Given Data / Assumptions:

• Decision stages: problem identification, alternative identification, alternative evaluation, and alternative selection.
• Computers excel at calculation, search, and simulation.
• Human judgment dominates when preferences, ethics, and strategy are involved.

Concept / Approach:

Computers can surface patterns to identify problems (alerts, outliers), propose alternatives (optimization heuristics, search), and evaluate alternatives (what-if analysis, simulations). However, selecting one course of action typically integrates soft factors like culture, politics, stakeholder trade-offs, and managerial experience—areas where automated tools are least decisive.

Step-by-Step Solution:

Verification / Alternative check:

Management science literature consistently distinguishes model-based evaluation from the managerial act of choosing, which remains human-centric even with decision aids.

Why Other Options Are Wrong:

Problem identification: Alerts and anomaly detection are routine for systems.

Alternative identification: Search/optimization can enumerate feasible options.

Alternative evaluation: Simulation and scoring models thrive here.

None: Incorrect because one stage—selection—is clearly least supported.

Common Pitfalls:

Assuming automation can replace judgment. DSS augments, but does not dictate, managerial choices.

Final Answer:

alternative selection