PurposeThe purpose of this paper is to explore pre-purchase apparel evaluation cues and examine the effect of demographic variables empirically in the context of a developing country. The initiation for the study was driven by the absence of such prior research and supplemented by the big market opportunity for clothing products in the country under investigation.Design/methodology/approachA self-administered online survey was used for data collection. Demographic questions, 23 apparel measurement items composed of 17 product-based and 6 sustainability-based items, and an open-ended question were included in the questionnaire. Factor analysis was used for dimension reduction and one-way multivariate analysis of variance (MANOVA) for hypotheses testing.FindingsGarment fit, design features, colour, fabric type and seasonality are the five important characteristics most Ethiopian consumers consider while buying apparel products. Factor analysis resulted in five important factors used for pre-purchase apparel evaluation amongst which the design and extrinsic cue is found to be the most important. Environmental factors in the apparel industry got higher emphasis than social factors. While age and educational background made differences in apparel evaluation, gender did not show a significant difference.Originality/valueThe paper provides a founding insight in exploring apparel evaluation cues by considering product- and sustainability-based cues in a developing country context. It also examines the effect of three demographic variables which are rarely studied in such combination.

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In this paper, we propose 3 new sampling plans, including resubmitted single sampling plan (RSSP), repetitive group sampling (RGS) plan, and multiple dependent state (MDS) sampling plan to study the zero‐inflated negative binomial distribution in microbiological food safety and quality assurance practices. The unity value approach is used to find optimal plan parameters. The proposed plans are compared with the single sampling plan (SSP). We found that degree of clustering and excess of zeros counts affect the performance of all sampling plans. The MDS plan outperforms the SSP, RSSP, and RGS plans with respect to minimum average sample number in most cases. Both RGS and MDS plans show a comparable performance. The average run length is calculated to evaluate the rejection capability of the plans and signal the deterioration of the quality of lots. An example from 9 Irish abattoirs is used to illustrate the application of the proposed methods.