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This study presents the development of a supply chain (SC) observatory, which is a benchmarking solution to support companies within the same industry in understanding their positioning in terms of SC performance.

A case study is used to demonstrate the set-up of the observatory. Twelve experts on automatic equipment for the wrapping and packaging industry were asked to select a set of performance criteria taken from the literature and evaluate their importance for the chosen industry using multi-criteria decision-making (MCDM) techniques. To handle the high number of criteria without requiring a high amount of time-consuming effort from decision-makers (DMs), five subjective, parsimonious methods for criteria weighting are applied and compared.

A benchmarking methodology is presented and discussed, aimed at DMs in the considered industry. Ten companies were ranked with regard to SC performance. The ranking solution of the companies was on average robust since the general structure of the ranking was very similar for all five weighting methodologies, though simplified-analytic hierarchy process (AHP) was the method with the greatest ability to discriminate between the criteria of importance and was considered faster to carry out and more quickly understood by the decision-makers.

Developing an SC observatory usually requires managing a large number of alternatives and criteria. The developed methodology uses parsimonious weighting methods, providing DMs with an easy-to-use and time-saving tool. A future research step will be to complete the methodology by defining the minimum variation required for one or more criteria to reach a specific position in the ranking through the implementation of a post-fact analysis.

The purpose of this study is to investigate empirically whether the presence of dependence influences the strength and direction of the relationship between social capital and operational performance.

The authors tested two effects, moderator and mediator, of the dependence between social capital and operational performance in the buyer–supplier relationship in the supply chain. The authors use dependence as a dichotomous variable and empirically test the hypotheses using hierarchical linear regression from data collected from 117 industrial companies in Brazil.

The results show that although dependence does not have a mediating effect on social capital shares in operational performance, it moderates the strength of trust actions in relation to cost, delivery, flexibility and innovativeness of the buyer.

As for the practical implications, in a buyer–supplier relationship, managers may not be fully capable of decreasing dependence and thus increasing the effect of trust actions on operational performance.

For management practices in the textile and clothing industry, social capital actions contribute to strategic objectives, increasing collaboration between supply chain partners, and for operations, offering more options in managing social ties.

The purpose of this paper is to present a modified failure mode and effects analysis (FMEA) in order to make the assignment of the scores for the occurrence factor more robust, and to link the FMEA chart directly to the maintenance activities.

A well-known clustering algorithm (i.e. K-means), along with a normalisation approach, are applied and compared for the assignment of the occurrence scores. Subsequently, the relationship between failures and maintenance operations is made explicit by a correlation matrix. Finally, the K-means algorithm is applied to the maintenance operations again in order to sort them into priority classes.

It is found that this revised FMEA approach improves the standard one due to its more rigorous mathematical formulation and lean applicability in real operating environments.

The novel approach may be improved by a deeper statistical analysis and/or applying the fuzzy theory.

A real case study is introduced in order to show the applicability of this approach to the quality control of a blow moulding process. It is found that this approach reveals a high potentiality for dealing with real issues.

The paper provides a further step towards bridging the gap between theory and practical application of the FMEA approach.

Based on the tenets of complexity theory, the purpose of the study is to identify the causal recipes that can lead to improved customer loyalty.

A cross-country sample was drawn from Pakistan, China and Italy to explore customers’ hotel experiences. The study used asymmetrical fuzzy set qualitative comparative analysis (fsQCA) to unearth the recipes of antecedent conditions that can predict high scores in customer loyalty.

The study results complementing the major tenets of complexity theory found several recipes in each of the countries that can lead to improved customer loyalty.

Instead of focusing on individual factors, and how they impact loyalty, the study will help hotel management to understand the complexity of loyalty and it may not be improved through individual focus on antecedent conditions, instead, different pathways/recipes can help improve the loyalty. The study will help managers uncover alternative ways to attain increasing customer loyalty. The results reveal that customers in different countries have varied paths leading to loyalty, showing that hotel administration should not consider all customers as equal, with changing culture there is a change in how high loyalty may be achieved.

Customer loyalty is a complex construct, and the latest research reveals that symmetric methods have significant limitations, as they view loyalty as an outcome of isolated antecedents. Symmetric methods are less informative and have limited theoretical implications. Drawing on the tenets of complexity theory the study contributes to the loyalty literature in the hotel industry by highlighting the causal configurations leading to improved customer loyalty.