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The purpose of this paper is to develop a decision‐making procedural hierarchy for evaluation as well as selection of third‐party reverse logistics provider (3PL) under fuzzy environment.

Due to uncertainty, vagueness arising from decision makers (DM) subjective judgment towards intangible (qualitative) selection criteria, fuzzy logic has been utilized to facilitate such a decision‐making process for 3PL evaluation and selection.

Evaluating and selecting 3PL providers can be regarded as a multi‐criteria decision making (MCDM) process in which a decision maker chooses, under several selection criteria, the best suited alternative. The present study highlights a case study on evaluation and selection of 3PL service providers for a reputed Indian automobile part manufacturing company. The fuzzy based decision‐making tool applied here has been proved fruitful for its effectiveness.

There are many research issues remaining in the development of this approach. First, the definition of appropriate fuzzy linguistic variables, corresponding membership functions (MFs) and their numbers, and their universe of discourse for a general use in the algorithm. Second, a methodology for accumulating raw data and analyzing the appropriate MFs for the base linguistic variables. Third, the relative importance of every decision maker, the decision‐making environment and structure may affect the decision‐making process. These have been assumed negligible in this study.

The main contributions of this research are: first, an integrated criteria list (followed by sets of sub‐criteria) has been modeled for service quality evaluation and appraisement of 3PL providers. Each sub criteria set has been structured to be preceded by a main criteria. Second, priority weights of various main criteria as well as sub‐criteria; extent of successful performance (rating) of different sub‐criteria have been expressed in fuzzy numbers. It facilitates in accumulating DMs subjective judgments into a unique numerical evaluation score. Third, decision makers risk‐bearing attitude has been estimated and utilized in computing overall evaluation index for alternative candidates. The decision‐making framework presented here can be extended to solve any decision‐making problem designed under a complex and interconnected set of primary criteria followed by sub‐criteria or more extended elaborate criteria hierarchy.

Success of software projects depends on identification of project risks and managing the risks in a proactive manner. Risk management requires thorough insights into interrelationship of various risk factors for proposing strategies to minimize failure rate. The purpose of this paper is to develop a comprehensive structural model to interrelate important risk factors affecting the success of software projects.

Specifically, this study reveals how interpretive structural modelling helps the risk managers in identifying and understanding the interrelationship among various risk factors. A total of 23 risk factors (or risk sources) have been identified through an extensive literature review.

Necessary modelling information has been gathered from expert through a structured questionnaire survey. Matrice d’Impacts croises-multipication appliqué an classment analysis has been employed to classify the risk factors into four clusters such as autonomous, dependent, linkage and independent based on their driving and dependence power. Risk factors with strong dependence and weak driving power need urgent attention from managerial perspective.

The proposed model is useful for software managers/practitioners to address risk factors associated with complicated projects.