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This research focuses on suggesting an optimized model for selecting best employees using advanced multi-criteria decision making method to a supply chain firm, who is planning to start a new cold chain business vertical.

Study has been conducted in a supply chain firm in North India, who wants to expand its business with the help of efficient team members. In total 38 applicants were considered for the study, as selected by the firm after initial screening from pool of talent. AHP-LP and TOPSIS-LP integrated approach were applied separately for evaluation and implementation of personnel selection model. Further, both the approaches were compared to find the best fit and optimized model.

As per the findings, both AHP and TOPSIS can be used to select the best candidate among the alternatives available. TOPSIS was found easier to implement as it involves ranking of applicants with respect to each skills required for respective job profile only once, whereas AHP involves pair-wise comparison among candidates with respect to each skills required for respective job profile and normalization of each comparison, resulting in the formation of number of comparison matrices. However, AHP is more reliable as it considers consistency check for each level of pair-wise comparison. Hence, there is a chance to avoid or revise the human judgment error. Integrated ranking and optimization approach minimizes the cost by suggesting the relevant positions to be filed to make an efficient team.

Group of interviewers are involved in the decision-making process, hence there are chances of biasness in ranking method which can influence the group decision. Research is limited to a particular geography of North India therefore needs to be tested for other regions also in order to generalize. The research will help the third party logistics (3PL) and other related firms in efficient team selection.

The researcher focuses on formalizing a method for potential candidate selection by considering the constraints of the organization. It has been observed that limited researches have been done on the application of AHP-LP or TOPSIS-LP integrated approach for selection process. Hence, this research proposes two integrated ranking-optimization method and suggests the best fit by comparing both the approaches.

Information technology service management (ITSM) has become a major IT department management system in organizations. Successful implementation of ITSM depends on select adequate ITSM software. Evaluation and selection of the ITSM solution or software packages is complicated and time-consuming decision-making problem. This paper aims to present an approach for dealing with such a problem.

This approach introduces functional, non-functional requirements and novel fuzzy out-ranking evaluation method for ITSM software selection. The presented approach breaks down ITSM software selection criteria into two broad categories, namely, functional (service strategy, service design, service transition, service operation, continual service improvement according to Information Technology Infrastructure Library V3) and non-functional requirements (quality, technical, vendor, implementation) including totally 46 selection criteria. A novel fuzzy superiority and inferiority ranking (FSIR) was developed and made applicable for ITSM software selection based on identified criteria.

The proposed approach is applied to IT services company to select and acquire ITSM software, and the provided numerical example illustrates the applicability of the approach for this choice. The approach can facilitate firms to achieve suitable ITSM software and have a precise acquisition decision; however, the limitation of dependency on experts’ competence and proficiency in the both ITSM field and IT technical issues exists.

The approach can facilitate firms to achieve suitable ITSM software and have a precise acquisition decision; however, the limitation of dependency on experts’ competence and proficiency in the both ITSM field and IT technical issues exists.

Facilitating of ITSM implementation through its handy software selection is the major impact of current research.

A facile FSIR-based approach for software selection has been customized to contribute to the current literature in the ITSM field. Facilitating of ITSM implementation through its handy software selection is the major impact of current research.

This paper follows a systematic literature review (SLR) method covering the published studies until March 2021. The authors have extracted the related studies from different online databases utilizing quality-assessment-criteria. In order to review high-quality studies, 32 papers have been chosen through the paper selection process. The selected papers have been categorized into three main groups, decision-making methods (17 papers), meta-heuristic methods (8 papers) and fuzzy-based methods (7 papers). The existing methods in each group have been examined based on important qualitative parameters, namely, time, cost, scalability, efficiency, availability and reliability.

Cloud computing is known as one of the superior technologies to perform large-scale and complex computing. With the growing tendency of network service users to utilize cloud computing, web service providers are encouraged to provide services with various functional and non-functional features and supply them in a service pool. In this regard, choosing the most appropriate services to fulfill users' requirements becomes a challenging problem. Since the problem of service selection in a cloud environment is known as a nondeterministic polynomial time (NP)-hard problem, many efforts have been made in recent years. Therefore, this paper aims to study and assess the existing service selection approaches in cloud computing.

The obtained results indicate that in decision-making methods, the assignment of proper weights to the criteria has a high impact on service ranking accuracy. Also, since service selection in cloud computing is known as an NP-hard problem, utilizing meta-heuristic algorithms to solve this problem offers interesting advantages compared to other approaches in discovering better solutions with less computational effort and moving quickly toward very good solutions. On the other hand, since fuzzy-based service selection approaches offer search results visually and cover quality of service (QoS) requirements of users, this kind of method is able to facilitate enhanced user experience.

Although the current paper aimed to provide a comprehensive study, there were some limitations. Since the authors have applied some filters to select the studies, some effective works may have been ignored. Generally, this paper has focused on journal papers and some effective works published in conferences. Moreover, the works published in non-English formats have been excluded. To discover relevant studies, the authors have chosen Google Scholar as a popular electronic database. Although Google Scholar can offer the most valid approaches, some suitable papers may not be observed during the process of article selection.

The outcome of the current paper will be useful and valuable for scholars, and it can be a roadmap to help future researchers enrich and improve their innovations. By assessing the recent efforts in service selection in cloud computing and offering an up-to-date comparison of the discussed works, this paper can be a solid foundation for understanding the different aspects of service selection.

Although service selection approaches have essential impacts on cloud computing, there is still a lack of a detailed and comprehensive study about reviewing and assessing existing mechanisms in this field. Therefore, the current paper adopts a systematic method to cover this gap. The obtained results in this paper can help the researchers interested in the field of service selection. Generally, the authors have aimed to specify existing challenges, characterize the efficient efforts and suggest some directions for upcoming studies.

Green supplier selection is one of the crucial activities in green supply chain management. However, limited studies have addressed the vagueness and complexities during the selection process, particularly in multi-criterion decision-making (MCDM) circumstances. Hence, the purpose of this paper is to develop a group decision model using a modified fuzzy MCDM approach for green supplier selection under a complex situation.

The proposed study develops a framework for sorting decisions in green supplier selection by using the hesitant fuzzy qualitative flexible multiple attributes method (QUALIFLEX). The synthetic consistent or inconsistent indexes were used to calculate all alternative suppliers by normalizing the hesitant fuzzy decision matrix.

The proposed framework has been successfully applied and illustrated in the case example of CB02 contract section in Hong Kong–Zhuhai–Macau Bridge project. The results show various complicated decision-making scenarios can be addressed through the proposed approach. The synthetic (in)consistent indexes are able to calculate all alternative suppliers by normalizing the hesitant fuzzy decision matrix.

The research contributes to improving accuracy and reliability decision-making processes for green supplier selection, especially under vagueness and complex situations in megaprojects.

Due to the increasing awareness of environmental and social issues, many practitioners and researchers have paid attention to sustainable supply chain management. As the performance of suppliers determines the success of supply chains, sustainable supplier selection becomes more and more important. Existing sustainable supplier selection models evaluated the sustainability of suppliers in three aspects (economic, environmental and social) and assumed that values on different criteria can completely compensate for each other directly. However, in reality, criteria in economic, environmental and social aspects are heterogeneous, and the decision-maker’s preferences on criteria belonging to different aspects are different. In this case, values on criteria belonging to different aspects are not allowed to completely compensate for each other directly. To solve this problem, this paper aims to propose a hybrid sustainable supplier selection approach integrating compensatory and non-compensatory decision rules.

In the proposed approach, the compensatory decision method Technique for Order of Preference by Similarity to Ideal Solution is used to evaluate performances of suppliers with respect to economic, environmental and social aspects. The non-compensatory decision method Elimination and Choice Translating Reality is used to evaluate performances of suppliers on sustainable criteria comprehensively. Through the proposed approach, only criteria belonging to the same aspects are allowed to compensate for each other directly. Finally, experimental results show that the proposed integrated approach is effective and efficient to help the decision-maker select optimal sustainable suppliers.

This is an original approach that integrates compensatory and non-compensatory decision rules, which can benefit from the two kinds of decision rules simultaneously. The integrated approach can be used as an aid for companies to select the best sustainable suppliers.

This paper presents an original integrated sustainable supplier selection approach using both compensatory and non-compensatory methods. It can benefit from the advantages of both compensatory and non-compensatory methods. The proposed approach can express preferences of the decision-maker on sustainable criteria sufficiently and maximize economic benefits while meeting environmental needs.

The purpose of this paper is to examine the information gathering methods used during enterprise system (ES) selection among Polish organizations and to have IT consulting experts evaluate these methods, which will result in identification of the preferred approach for the information‐gathering task during system selection.

The research has a qualitative exploratory design with grounded theory being the main research method. A mixed quantitative‐qualitative approach to data collection was used: an e‐mail‐based survey was used as an introductory stage to gather data on information‐gathering methods. The results of the survey were evaluated by ES experts during unstructured interviews. The interviews were then transcribed and coded according to the grounded theory coding techniques.

The evaluation of selection approaches revealed that the approach to information gathering should depend on the level of configurability of the systems subject to selection. Two generic approaches were identified: requirements driven – for highly configurable systems, and system functionality driven – for the systems offering limited configurability. Interaction between the customer and the bidder was also identified as the main condition for preparing the unbiased offer by the bidders.

Regarding the survey study, as the survey sample was small and the sample selection process was not random, the results should not be generalised to the whole population of Polish enterprises. It would be also beneficial to test the validity of the findings from the grounded theory study on the big population of ES bidders with the use of statistical methods.

For highly configurable systems, a model that includes a business process analysis, detailed requirements' specification and dedicated system functionality presentation is the preferred approach. A workshop is preferred to obtaining a ready requirements list. For systems offering limited configurability, an approach centred on system presentation is more suitable. In this case the requirements should be gathered during the presentation on a “gap‐fit” basis.

There is a significant lack of research that explores the selection process, with the stress on organizational needs and system functionality information gathering and makes indications for improvement of this process from the consulting enterprise (bidder) point of view. The paper fills this gap by presenting the results of a survey among Polish enterprises regarding selection routines and the evaluation of these routines by expert ES professionals, resulting in the development of the preferred set of information‐gathering methods.

Service supplier selection is a multi-criteria decision-making (MCDM) problem assuming a strategic role for the competitiveness of high-tech manufacturing companies. Nevertheless, especially for service quality evaluation, there is little empirical evidence of the practical usefulness of MCDM methodologies. Aiming to cover this gap between theoretical approaches and empirical applications, the purpose of this paper is to propose a fuzzy extended analytic hierarchy process (FEAHP) approach for service supplier evaluation.

A hybrid approach which combines some of the strengths of the analytic hierarchy process (AHP) and of the fuzzy set theory is presented, as organized into five steps. A case study is used to evaluate the applicability in a real company context.

The usability of the approach is demonstrated in an aerospace company for solving the supplier selection problem of a business software whose applications are still in infancy: a Test Data Management System (TDMS). The illustrative application contains both “general” criteria to be used for other service supplier selection contexts as well as service-specific criteria related to software selection.

Even if the application regards the selection of a software supplier, the methodology can be generically extended to other services’ selection in complex manufacturing industries through the personalization of some criteria.

Implications can be derived both for business managers involved into the decision-making process and for suppliers identifying the most promising features of software quality.

The originality consists in the combination into a hybrid approach of the strong points of the AHP with the fuzzy set; the inclusion of multiple perspectives of decision criteria for service supplier selection, basically the “software product” and “supplier” ones; a real empirical application to test and demonstrate the efficacy and the practical utility of the proposed approach.

Web services play vital role in the development of emerging technologies such as Cloud computing and Internet of Things. Although, there is a close relationship among the discovery, selection and composition tasks of Web services, research community has treated these challenges at individual level rather to focus on them collectively for developing efficient solution, which is the purpose of this work. This paper aims to propose an approach to integrate the service discovery, selection and composition of Semantic Web services on runtime basis.

The proposed approach defined as a quality of service (QoS)-aware approach is based on QoS model to perform discovery, selection and composition tasks at runtime to enhance the user satisfaction and quality guarantee by incorporating non-functional parameters such as response time and throughput with the Web services and user request. In this paper, the proposed approach is based on ontology for semantic description of Web services, which provides interoperability and automation in the Web services tasks.

This work proposed an integrated framework of Web service discovery, selection and composition which supports end user to search, select and compose the Web services at runtime using semantic description and non-functional requirements. The proposed approach is evaluated by various data sets from the Web Service Challenge 2009 (WSC-2009) to show the efficiency of this work. A use case scenario of Healthcare Information System is implemented using proposed work to demonstrate the usability and requirement the proposed approach.

The main contribution of this paper is to develop an integrated approach of Semantic Web services discovery, selection and composition by using the non-functional requirements.