In mobile crowd computing (MCC), smart mobile devices (SMDs) are utilized as computing resources. To achieve satisfactory performance and quality of service, selecting the most suitable resources (SMDs) is crucial. The selection is generally made based on the computing capability of an SMD, which is defined by its various fixed and variable resource parameters. As the selection is made on different criteria of varying significance, the resource selection problem can be duly represented as an MCDM problem. However, for the real-time implementation of MCC and considering its dynamicity, the resource selection algorithm should be time-efficient. In this paper, we aim to find out a suitable MCDM method for resource selection in such a dynamic and time-constraint environment. For this, we present a comparative analysis of various MCDM methods under asymmetric conditions with varying selection criteria and alternative sets. Various datasets of different sizes are used for evaluation. We execute each program on a Windows-based laptop and also on an Android-based smartphone to assess average runtimes. Besides time complexity analysis, we perform sensitivity analysis and ranking order comparison to check the correctness, stability, and reliability of the rankings generated by each method.

In recent times, the Indian Stock Market (ISM) has been witnessing a surge in the number of IPOs listed on stock exchanges. However, on many occasions, it has been noticed that the post-listing performance of several IPOs is below par compared to the expectations of the investors. IPO performance has been one of the major concerns. In this context, the present paper endeavors to carry out a comparative performance assessment of a list of IPOs. We consider a period of three years after listing. Our sample consists of a list of IPOs with heterogeneous nature of business operations and introduced in 2018. We consider two aspects of performance, such as market-based indicators and fundamental efficiency in terms of profitability, liquidity, and risk. For comparison, LOgarithmic Percentage Change-driven Objective Weighting (LOPCOW) is used. The study period is considered as FY 2020-21. The results reflect that, for IPOs, market performance is not necessarily due to fundamental efficiency. Further, we notice that the nature of equity ownership does not influence market performance significantly. We surmise that, during the initial years, the performance of IPOs in the marketplace is more driven by speculation and short-term goals of investors. The result of the validation test indicates that the ranking using the LOPCOW method is comparable and consistent with a widely used model like Entropy.

Smartphones have become an inevitable part of every facet of modern society. The selection of a particular smartphone brand from multiple options that are available is a complex and dynamic decision-making problem, involving multiple conflicting criteria that are associated with imprecise asymmetric information imposed by the uncertainty of the consumers. In this paper, we propose a novel hybrid full consistency method (FUCOM) and a combinative distance based assessment (CODAS) based on the multi-criteria group decision-making (MAGDM) framework in the Fermatean fuzzy (FF) domain for smartphone brand selection. We derive the criteria using the UTAUT2 (unified theory of acceptance and ese of technology) model. A group of 15 decision makers (DMs) participated in our study. We compare 14 leading smartphone brands in India and find that the brands having superior features of a good quality and selling a brand image at a affordable price outperform other smartphones. To check the validity of our framework, we compare the results using extant multi-criteria decision-making (MCDM) models. We observe our model provides a consistent solution. Furthermore, we carry out a sensitivity analysis for ascertaining the robustness and stability of the results generated by our model. The results of the sensitivity analysis show that our proposed framework delivers a stable and robust solution.

The present paper introduces a new multi-criteria decision making (MCDM) model such as Evaluation based on Relative Utility and Nonlinear Standardization (ERUNS). The proposed method provides a number of unique features such as use of non-linear standardization combined with a new definition for calculating utility values of the alternatives and design flexibility. The new method is applied to compare the firm performances using Economic, Environment, Social and Governance (EESG) framework. Over the last few decades alongside economic gain, the firms have been equally emphasizing on environmental protection, social values and good governance. This paper aims to bring in the economic aspect in terms of market capitalization and enterprise value while uses rating scores for environment, social and governance to put forth an extended performance measurement framework. A set of eight leading firms belonging to the energy sector listed to NSE, India has been considered for the period FY 2022-23 as a case study. The criteria weights are calculated using the Logarithmic Percentage Change-driven Objective Weighting (LOPCOW) method. It is observed that ERUNS provides a stable and reliable ranking result free from the rank reversal issue. This paper shall be of interest to both analysts and practitioners in terms of its robust method and practical performance assessment framework.

Facility location is one of the critical strategic decisions for any organization. It not only carries the organization’s identity but also connects the point of origin and point of consumption. In the case of higher educational institutions, specifically B-Schools, location is one of the primary concerns for potential students and their parents while selecting an institution for pursuing higher education. There has been a plethora of research conducted to investigate the factors influencing the B-School selection decision-making. However, location as a standalone factor has not been widely studied. This paper aims to explore various location selection criteria from the viewpoint of the candidates who aspire to enroll in B-Schools. We apply an integrated group decision-making framework of pivot pairwise relative criteria importance assessment (PIPRECIA), and level-based weight assessment LBWA is used wherein a group of student counselors, admission executives, and educators from India has participated. The factors which influence the location decision are identified through qualitative opinion analysis. The results show that connectivity and commutation are the dominant issues.