SmartPLS: What should I do if discriminant validity HTMT>0.90?

In SmartPLS 4's Construct reliability and validity output have Composite reliability (rho_a) and Composite reliability (rho_c).

What is the difference between Composite reliability (rho_a) and (rho_c)?

Which one should use for my study?

Does anyone have a better ideas how to explain the used of Heterotrait-Monotrait Ratio of Correlations (HTMT) in assessing the discriminant validity in PLS-SEM model?

In one of my measurement CFA models (using AMOS) the factor loading of two items are smaller than 0.3. I found some scholars that mentioned only the ones which are smaller than 0.2 should be considered for deletion. However, there are various ideas in this regard. Some said that the items which their factor loading are below 0.3 or even below 0.4 are not valuable and should be deleted.

The measurement I used is a standard one and I do not want to remove any item. What should I do? 

Thank you for your valuable time.

Regards,

SmartPLS: What should I do if discriminant validity HTMT>0.90? Is any alternative available for SMART PLS?

Though AVE value must be greater than 0.5, yet the question is can i go ahead with further calculations if AVE is close to 0.5. (Little less than 0.5)...All other values, like factor loading, SCR, data adequacy etc is coming under the acceptance zone?

Cronbach alpha acceptability values

Using smartPLS 3.0

Would you please send me the license key for SmartPLS software? I will be very thankful for this act of kindness..

Reviewers comments are as follows:

Reject this manuscript as there was 4 items had factor loadings below recommended value of 0.70. Hair et al. (2010) require that each item is considered a satisfactory item when item loadings are greater than 0.70. With this flaw, it really affects the whole data analysis, discussion, conclusion and future direction presented in the entire article.

My answer to this comments was: 

There are many studies that reported that factor loadings should be greater than 0.5 for better results (Truong & McColl, 2011; Hulland, 1999), whereas in tourism context Chen & Tsai (2007) were also considered 0.5 as a cut-off for acceptable loadings. Additionally, while exploring pro-environmental consumer behavior, Ertz, Karakas & Sarigollu (2016) have considered the factor loadings of 0.4 and above for their Confirmatory factor analysis.  So, on the above ground, we have not solely chosen this criterion but also as 0.6 is better than these studies cut-offs for factor loadings.  Along in line, the standardized factor loading of all the items ranges was above the threshold limit of .6 and above also suggested by Chin, Gopal & Salisbury (1997) and Hair et al. (2006).