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One of the key success factors for an organization is the promotion of qualified personnel for vacant positions. Especially, the promotion of middle and senior managers play an important role in terms of organization’s success. In personnel promotion problem in which the candidates are nominated within the organization and they have been working for a specific period of time and are known in their organization, the candidates should be evaluated based on their recent as well as past performances to make right selection for the vacant position. For this reason, the purpose of this paper is to propose an integrated dynamic multi-attribute decision-making (MADM) model based on intuitionistic fuzzy set for solving personnel promotion problem.

The proposed model integrates analytic hierarchy process (AHP) technique and the dynamic evaluation by intuitionistic fuzzy operator for personnel promotion. AHP is employed to determine the weight of attributes based on decision maker’s opinions, and the dynamic operator is utilized to aggregate evaluations of candidates for different years. Atanassov’s intuitionistic fuzzy set theory is utilized to represent uncertainty and vagueness in MADM process.

A numerical example is presented to show the applicability of the proposed method for personnel promotion problem and a sensitivity analysis is conducted to demonstrate efficiency of dynamic evaluation. The findings indicate that the varying weights of years employed determined the best candidate for promotion.

The novelty of this study is defining personnel promotion as a MADM problem in the literature for the first time and proposing an integrated dynamic intuitionistic fuzzy MADM approach for the solution, in which the candidates are evaluated at different years.

In the literature, many multi attributes decision making (MADM) models allow evaluation of the alternatives considering their current or last performance. However, in some MADM problems, not only current performance of alternatives but also their past performance should be taken into account in order to select the most appropriate alternative. For this reason, the purpose of this paper is to develop four procedures to evaluate the alternatives in MADM problems with multi terms.

This study uses dynamic operators to aggregate the evaluation in different terms and then, grey relational analysis (GRA) and technique for order preference by similarity to ideal solution (TOPSIS) methods are utilized to determine the most appropriate alternative. Thus, four procedures which consist of these operators and methods are developed to evaluate the alternatives in multi terms.

Some numerical examples are presented for the proposed procedures in multi-terms. Moreover, these four procedures are compared with other four procedures. The analyses of the results show that dynamic aggregation operators based on intuitionistic fuzzy set (IFS) and interval valued intuitionistic fuzzy sets (IVIFS) with GRA and TOPSIS can be used jointly for MADM problems in which alternatives are evaluated for different terms.

One of the significant mistakes faced in some MADM problems is to take into account the current performance of alternatives or is to ignore their past performance. The right selection depends on past and current performance of the alternatives. The novelty of this study is to propose four procedures for solving MADM problems in multi terms based on IFS and IVIFS using dynamic aggregation operators and GRA and TOPSIS methods.

Green supply chain management (GSCM) has become an important issue with increasing awareness of environmental protection. A firm's environmental approach is not only relevant to its inner efforts, but its suppliers' environmental performance is also important. The aim of this study is to propose an integrated multi‐criteria decision‐making (MCDM) approach based on intuitionistic fuzzy set (IFS) and grey relational analysis (GRA) for green supplier selection.

Green supplier selection is a MCDM process that contains different kinds of uncertainties. Because of the vagueness and imprecision of decision makers' evaluations and subjectivity of the criteria, IFS and GRA are exploited to handle these uncertainties.

A numerical example is presented for the proposed approach. The analyses of the results show that fuzzy set theory and grey theory can be used jointly for green supplier selection problems in uncertain environments.

There are different kinds of uncertainties in the supplier selection process. The novelty of this study is to use proper uncertainty methods in different steps instead of denoting the whole selection process by the same uncertainty theory. Supplier selection problems occupy wide space in operations research literature. Different criteria are used in different papers. In this study, detailed literature review has been carried out and some criteria among frequently confronted ones proposed for green supplier selection.

Supplier selection is a complex multiple criteria decision (MCDM) problem which directly depends on decision makers’ choice. Some decisions are getting involved with linguistic variables and they are not mathematically operable. To solve a typical decision problem through MCDM techniques, a number or a numerical interval should be defined. The purpose of this paper is to focus on that numerical interval and in a case of supplier selection, the aim is to close the decisions to the real number that the decision maker mentions and this number is in a numerical interval.

The proposed method deals with grey relational analysis (GRA) and develops it by applying triangular fuzzy numbers. The grey numbers have two defined bounds; the proposed method defines two fuzzy bounds for each grey attribute. In the proposed method, the fuzzy membership function has been employed for each bounds of grey attribute to make them to fuzzy bounds with two undefined bounds. Also to make comparison, with employing of TOPSIS technique, both of the grey fuzzy combination decision matrix and the original grey decision matrix are obtained.

The results indicate that, except to the ideal solutions, the grey relation coefficient for each alternative is too close to each other. Indeed, they are too close to zero. Applying the proposed method in problem of supplier selection shows the difference between two selected supplier in proposed method and the original grey method.

As mentioned heretofore this paper aims to make decision makers’s decision more accurate and actually there is no other researches which used this combination method.

The internal fixation plate of bone fractures by using polylactic acid (PLA) has attracted the attention of many researchers, as it is biodegradable and biocompatible to the human body. However, its brittleness has led to implant fracture. On the contrary, polypropylene carbonate (PPC), which is also biodegradable and biocompatible, has an excellent elongation at break. The purpose of this paper is to compare the PLA fixation plate with the new fixation plate made up of PLA/PPC blends by using finite element analysis (FEA).

The mandible bone from CT data set and fixation plate was designed by using the MIMICS, Amira and Solidworks softwares. Abaqus software was used for FEA of PLA/PPC fixation plate applied on the fractured mandible bone. A model of mandibular bone with a fracture in the body was subjected to incisor load. The analysis was run to determine the von Mises stress, elongation of the fixation plate and the displacement of the fractured gap of PLA/PPC blends fixation plate.

The von Mises stress predicted that all the blend compositions were safe to be used as a fixation plate since the stress values were less than the yield strength. In addition, the stress value of the fixation plate was gradually decreased up to 20 percent when the amount of PPC increased to 30 percent. This indicates that the stress shielding effect was successfully reduced. The elongation of the fixation plate was gradually increased from 11.54 to 12.55 µm as the amount of PPC in the blends increased from 0 to 30 percent, thereby illustrating that the flexibility of the fixation plate was improved by the addition of PPC. Finally, the measured displacement of the fractured gap for all compositions of PLA/PPC blends fixation plate is less than 150 µm, which proves the likely success of fracture fixation by using the PLA/PPC blends.

An optimum solution of PLA/PPC blends and another new material such as compatibilizer need to be introduced in the blends in order to improve the performance of PLA/PPC blends as a new material for a fixation plate. Besides, by using the same method of producing PLA/PPC blends, longer durations for in vitro degradation of PLA/PPC blends are essential to further understand the degradation behavior of the blends applied in the human body. Finally, it is also important to further test the mechanical strength of PLA/PPC blends during the degradation period to know the current strength of the implant in the healing process of the bone.

PLA fixation plate and screw can commercially be used in CMF surgery since they reduce cost because of the elimination of secondary surgery to remove the fixation plate and screw after the healing process.

It is hoped that the advantages of this research will ensure the market of PLA product to continue expanding in medical application.

This study is one of the alternative ways for the biomedical researchers to improve the elongation break of PLA. Currently, many researchers focus on polymeric materials such as PLA, poly(glycolic) acid and polydioxanone blends, which were extensively being used in CMF surgery. However, the work on PLA/PPC blends to be used as one of the materials for the CMF fixation plate is very limited, if any. PPC, the proposed material for this research, will improve the mechanical performance of PLA fixation plate and screw to become more sustainable and flexible when applied on human mandible bone.

This study uses relationship marketing theory to explore affective and calculative commitment as mediators in the delight–loyalty link. Furthermore, it investigates the role of perceived employee service delivery skills, perceived value and trust in the relationships between delight, affective commitment, calculative commitment and loyalty.

A descriptive research approach was applied, and the data were collected from 332 retail banking customers in an emergent market who are overall satisfied with their bank. A self-administered questionnaire collected data from 332 respondents who adhered to the stipulated requirements to participate in the study. These respondents were selected through purposive and convenience sampling. The constructs’ interrelationships were analysed via structural equation modelling. The measurement and structural models were also assessed.

Affective and calculative commitment and delight impact loyalty. Both affective commitment and calculative commitment were found to mediate the relationship between delight and customer loyalty.

The study enhances an understanding of the role of affective and calculative commitment in strengthening the delight–loyalty link from a relationship marketing theory perspective.

The study provides guidance to the retail banking industry in emerging markets on the importance of affective and calculative commitment in strengthening the delight–loyalty link. It further informs retail banks of the need to provide banking customers with products and service value that exceed their expectations to strengthen their future commitment and loyalty to their bank.

Guided by relationship marketing theory, the role of affective and calculative commitment in mediating the delight–loyalty link in an emerging market context is uncovered.

This study seeks to understand the nexus between intellectual capital and profitability of healthcare firms in India with interaction effects.

Relevant data were extracted from the Centre for Monitoring Indian Economy (CMIE)'s Prowess database for a period of ten years 2009–2018 for a sample of 84 selected firms from the healthcare industry. This study uses value added intellectual coefficient (VAIC) and modified value added intellectual coefficient (MVAIC) as a measure of intellectual capital. Further, the study employs panel regression techniques to explore the relationship between intellectual capital and profitability.

The empirical findings reveal that the intellectual capital coefficient of healthcare firms in India averages 2.7757. It is also observed that a majority of the healthcare firms' intellectual capital coefficient is below the industry average. From the regression analysis, it is evident that the intellectual capital coefficient is positively related to the profitability of healthcare firms in India. As far as the components of intellectual capital coefficient are concerned, the capital employed coefficient (CEC) is the only component driving the profitability of healthcare firms in India. A further introduction of interaction terms improves model explainability and moderates the impact of the predictor variable on the response variable. Furthermore, it is observed that the intellectual capital coefficient of the healthcare industry is immune to changes in political regimes in India.

The findings reveal that intellectual capital is an important driver of corporate performance, thus healthcare firms in developing economies like India need to enhance their intellectual potential. Therefore, corporates and governments in developing economies should stimulate investments in developing intellectual capital for enhanced corporate performance and economic growth. Thus, this study might be used as a reference by policymakers while drafting the future policy for the development of intellectual capital in general and healthcare sector specifically.

This is among the first few studies to explore such an empirical relationship for healthcare firms in India and among the few studies of this kind across the globe. It also makes novel contributions in considering interaction variables and seeking the consistency of results across different political regimes. However, the study examines one nation and one industry; thus, the generalisation of findings requires caution.