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Can I rephrase your question as"Can we conduct cluster analysis using ordinal data?"? Thanks

You are trying to determine an appropriate distance measure, and clearly you are noticing how tricky this can be.

Ordinal data is not interval data. You should consider:

• Whether the distance between each category is the same (is the distance between 2 and 3 the same as the distance between 3 and 4?)
• Whether special consideration needs to be given to the neutral/null category (in your case, 1: no effect).
• Whether several of your causes variables need to be considered together. For example, you may decide to sum 2 related variables together and treat them as one (derivative) variable for purposes of clustering.
• These considerations have psychological roots. For example, people tend to give more weight to the difference between options at the ends of the scale than in the middle.
  

You may decide on an approach based on these considerations that involves: - cleaning the data - transforming the current scale into one in Euclidean space. or, you may decide this is not necessary for your purposes.

Existing research that uses the Likert scale often utilizes distance measures based on Cosine distance and Pearson Correlation.

You may find the following useful:

Under what conditions should Likert scales be used as ordinal or interval data?
https://news.ycombinator.com/item?id=2423313

The TWOSTEP cluster procedure in SPSS handles variables at different levels of measurement.  It produces a simple clustering, not a hierarchical clustering.Details of how to proceed depend on the details such as what questions you are using the data to answer, any logical sets of variables, etc.

• If you are using Likert scales (sum or mean of a set of Likert items), the results are very unlikely to discrepant from the interval level of measurement.
• If you have Likert items meant to be be part of scales, you might want to do item analysis (e.g., with RELIABILITY) and see if they do comprise a scale or scales.
• Age is usually considered a ratio level variable.  There is an intrinsic meaning to zero.