diff --git a/django_server/application_evaluator/management/commands/import_challenges_s4c.py b/django_server/application_evaluator/management/commands/import_challenges_s4c.py
new file mode 100644
index 0000000..fe1370f
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+++ b/django_server/application_evaluator/management/commands/import_challenges_s4c.py
@@ -0,0 +1,144 @@
+# Create management command to add criteria to application rounds
+
+from django.core.management.base import BaseCommand
+from django.db.models import Q
+
+from application_evaluator.models import ApplicationRound, CriterionGroup, Criterion
+
+# This is just for testing purposes
+criteria_json = [
+    {
+        "criterion_group": {"name": "Functional criteria", "weighting": "40%"},
+        "criteria": [
+            {"name": "Enabling dynamic management of public areas", "abbr": "EDMA", "max_points": 25, "threshold": 13},
+            {"name": "Use of space data", "abbr": "USDa", "max_points": 30, "threshold": 15},
+            {"name": "Interoperability", "abbr": "Inte", "max_points": 20, "threshold": 10},
+            {"name": "Data Security & Privacy", "abbr": "DSec", "max_points": 15, "threshold": 7},
+        ],
+    },
+    {
+        "criterion_group": {"name": "Non-functional criteria", "weighting": "20%"},
+        "criteria": [
+            {"name": "Innovativeness", "abbr": "Inno", "max_points": 70, "threshold": 35},
+            {"name": "Impacts on city and citizens", "abbr": "IoCC", "max_points": 30, "threshold": 15},
+        ],
+    },
+    {
+        "criterion_group": {"name": "Project management criteria", "weighting": "20%"},
+        "criteria": [
+            {"name": "Project management plan", "abbr": "PMPl", "max_points": 50, "threshold": 25},
+            {"name": "Composition of the project team", "abbr": "CPro", "max_points": 50, "threshold": 25},
+        ],
+    },
+    {
+        "criterion_group": {"name": "Commercial feasibility", "weighting": "10%"},
+        "criteria": [
+            {
+                "name": "Replication & implementation across multiple cities",
+                "abbr": "RImp",
+                "max_points": 60,
+                "threshold": 30,
+            },
+            {"name": "Business model", "abbr": "Busi", "max_points": 40, "threshold": 20},
+        ],
+    },
+    {
+        "criterion_group": {"name": "Price", "weighting": "10%"},
+        "criteria": [
+            {
+                "name": "Binding contract price for carrying out the work in Phase 1",
+                "abbr": "BCon",
+                "max_points": 30,
+                "threshold": 15,
+            },
+            {
+                "name": "indicative price for the work in all 3 PCP phases (total price)",
+                "abbr": "IPri",
+                "max_points": 70,
+                "threshold": 35,
+            },
+        ],
+    },
+]
+
+
+def setup_criterion_groups_and_criteria(application_rounds, criteria_json):
+    """
+    Sets up criterion groups and criteria for given application rounds based on JSON configuration.
+
+    Args:
+        application_rounds: List of ApplicationRound objects
+        criteria_json: List of dictionaries containing criterion group and criteria configurations
+    """
+    for application_round in application_rounds:
+        # Track order for groups and criteria
+        group_order = 0
+
+        for group_data in criteria_json:
+            group_info = group_data["criterion_group"]
+            criteria_list = group_data["criteria"]
+
+            # Convert percentage string to float (e.g., "40%" -> 0.4)
+            weighting = float(group_info["weighting"].strip("%")) / 100
+
+            # Create or get criterion group
+            criterion_group, created = CriterionGroup.objects.get_or_create(
+                application_round=application_round,
+                name=group_info["name"],
+                defaults={
+                    "order": group_order,
+                    "abbr": group_info["name"][:8],  # Use first 8 chars as abbreviation if not provided
+                },
+            )
+
+            # Update the group order even if it already existed
+            criterion_group.order = group_order
+            criterion_group.save()
+
+            # Calculate total max points for this group
+            total_max_points = sum(criterion["max_points"] for criterion in criteria_list)
+
+            # Create or update criteria
+            for criterion_order, criterion_data in enumerate(criteria_list):
+                # Calculate the weighted value for this criterion
+                criterion_weight = (criterion_data["max_points"] / total_max_points) * weighting
+
+                # Modify the name to include max points
+                criterion_name = f"{criterion_data['name']} [max {criterion_data['max_points']}]"
+
+                criterion, created = Criterion.objects.get_or_create(
+                    application_round=application_round,
+                    name=criterion_name,  # Using modified name here
+                    group=criterion_group,
+                    defaults={"order": criterion_order, "weight": criterion_weight, "public": True},
+                )
+
+                # Update values even if criterion already existed
+                criterion.order = criterion_order
+                criterion.weight = criterion_weight
+                criterion.save()
+
+            group_order += 1
+
+
+class Command(BaseCommand):
+    help = "Create criterion groups and criteria for given application rounds"
+
+    def add_arguments(self, parser):
+        parser.add_argument("--application-rounds", nargs="+", type=str)
+
+    def handle(self, *args, **options):
+        # Create Q objects for each application round name prefix
+        q_objects = Q()
+        for ar_name in options["application_rounds"]:
+            q_objects |= Q(name__startswith=ar_name)
+
+        # Search for application rounds matching any of the name prefixes
+        ars = ApplicationRound.objects.filter(q_objects)
+
+        if not ars.exists():
+            self.stdout.write(self.style.WARNING("No matching application rounds found"))
+            return
+        setup_criterion_groups_and_criteria(ars, criteria_json)
+
+        self.stdout.write(self.style.SUCCESS(f"Successfully imported criteria for {ars.count()} application round(s)"))