Jom Methods

---
name: jom-methods
description: Use when choosing and defending the research design for a Journal of Operations Management (JOM) empirical study — matching survey, archival/secondary, field, case, experimental, or intervention-based research to the operations question, anticipating the Empirical Research Methods Department's method check, and keeping the design observation-grounded rather than analytical.
---

# Research Design for Empirical OM (jom-methods)

## When to trigger

- You must pick a design that can actually test your operations hypotheses
- A reviewer questions whether the method fits the operations phenomenon or the level of analysis
- You are weighing a behavioral lab experiment vs. archival panel vs. survey vs. field/intervention
- You anticipate the **Empirical Research Methods Department** method check on incoming submissions

## JOM's empirical-only design space

JOM publishes empirical OM research and **does not** publish purely analytical models or optimization techniques. Every design must rest on **observation**. The native JOM design families are:

| Operations question / claim                                  | Design                                                        |
|--------------------------------------------------------------|---------------------------------------------------------------|
| Perceptions, practices, constructs across firms/plants       | **Survey** (validated multi-item scales; multi-respondent)    |
| Cause–effect on operational outcomes from secondary data     | **Archival/secondary** panel (recalls, inventory, supply ties)|
| Human operational decisions, biases, incentives              | **Behavioral-OM experiment** (lab/online, manipulation checks)|
| How operations work unfolds in context                       | **Field study / case study** (process, embedded, comparative) |
| Effect of an actively introduced change in a real setting    | **Intervention Based Research** (engaged scholarship)         |
| Pooling effects across studies                               | **Meta-analysis** of empirical OM findings                    |

## Match design to claim and level

State the **unit and level** (transaction, shift, line, plant, project, dyad, supply network) and ensure the design observes at that level. A plant-level claim tested with firm-level archival data is a level mismatch reviewers catch quickly. For multi-respondent supply-chain dyads, plan both-side data collection.

## Intervention Based Research (a JOM-distinctive genre)

JOM formally houses **Intervention Based Research**, where researchers actively intervene in a real operational problem (engaged scholarship). If you use it: pre-state the theorized effect, document the intervention protocol and timeline, separate researcher actions from observed effects, and address how engagement threatens (and how you protect) inference. Most flagship management journals do not formally house this genre — use it deliberately.

## Pre-empt the Empirical Research Methods check

JOM's Empirical Research Methods Department performs method checks on incoming empirical submissions. Defend, up front: sampling frame and response/coverage, construct operationalization, identification strategy (for causal claims), common-method separations (for survey), and reproducibility of secondary-data construction. Weak identification or unvalidated measures stall here.

## Anti-patterns

- An optimization or pure simulation model presented as the empirical contribution.
- Design that cannot observe at the claimed level.
- Single-respondent survey for a relational/dyadic operations claim.
- Intervention work that conflates the researcher's actions with the measured effect.

## Output format

```
【Design family】survey / archival / experiment / field-case / IBR / meta-analysis
【Unit & level】...
【Identification / validity strategy】...
【Methods-check readiness】sampling, measures, identification, reproducibility ...
【Next step】jom-data-analysis
```