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Supplier selection in the supply chain network (SCN) has strategic importance and involves multiple factors. The multi-criteria nature of the problem coupled with environmental uncertainty requires several procedures and considerations. The issue of decision-making in selecting the best among various qualified suppliers remains the major challenge in the pharmaceutical industry. This study investigated the multi-criteria multi-supplier decision-making process and proposed a model for supplier selection problems based on mixed-integer linear programming.

The concept of principal component analysis (PCA) was used to reduce data dimensionality, and the four best criteria have been considered and selected. The result is subjected to decision-makers’ (DMs’) reliability test using the concept of a triangular fuzzy number (TFN). The importance of each supplier to each measure is established using fuzzy technique for order preference by similarity to an ideal solution approach, and the suppliers have ranked accordingly.

This study proposes a mixed integer linear programming model for supplier selection in a pharmaceutical company. The effectiveness of the proposed model has been demonstrated using a numerical example. The solution shows the model's applicability in making a sound decision in pharmaceutical companies in the space of reality. The model proposed is simple. Readily commercial packages such as LINDO/LINGO and GAMS can solve the model.

This research contributed to the systematic manner of supplier selection considering DMs’ value judgement under a fuzzy environment and is limited to the case study area. However, interested researchers can apply the study in other related manufacturing industries. However, the criteria have to be revisited to suit that system and might require varying ratings based on the experts' opinions in that field.

This work suggests more insights practically by considering a realistic and precise investigation based on a real-life case study of pharmaceutical companies with six primary criteria and twenty-four sub-criteria. The study outcome will assist organizations and managers in conducting the best decision objectively by selecting the best suppliers with their various standards and terms among many available contenders in the manufacturing industry.

In this paper, the authors attempted to identify the most critical attributes to be preserved by the top managers (DMs) while selecting suppliers in pharmaceutical companies. The study proposed an MILP model for supplier selection in the pharmaceutical company using fuzzy TOPSIS.

Estimators for derivatives associated with a density function can be useful in identifying its modes and inflection points. In addition, these estimators play an important role in plug-in methods associated with bandwidth selection in nonparametric kernel density estimation. In this paper, we extend the nonparametric class of density estimators proposed by Mynbaev and Martins-Filho (2010) to the estimation of m-order density derivatives. Contrary to some existing derivative estimators, the estimators in our proposed class have a full asymptotic characterization, including uniform consistency and asymptotic normality. An expression for the bandwidth that minimizes an asymptotic approximation for the estimators’ integrated squared error is provided. A Monte Carlo study sheds light on the finite sample performance of our estimators and contrasts it with that of density derivative estimators based on the classical Rosenblatt–Parzen approach.

The purpose of the paper is to evaluate print and electronic resources of TERI’s Library and Information Centre (LIC) with an aim to maximize the net marginal benefits and minimize net marginal costs, without compromising the quality of the library resources.

The parameters considered for analyzing the value of the library resources for this exercise were resource access costs, strategic value of the resource based on subject area coverage, frequency of use, citations, direct and indirect benefits to users. The data regarding these parameters were provided from wide range of sources (both tangible and intangible), to come out with the qualitative and quantitative assessment through an optimization and simulation based model.

Out of the total holdings in TERI LIC that were analyzed, 85 percent of book collections and 63.5 percent of journals were found to be useful for the researchers. The least-used books and journals were identified for weeding to optimize the value of library for users and make space for new and topical library collections.

A sample of data sources out of the total library collections was defined for the evaluation.

The paper demonstrates the value of library resources that is of critical importance to libraries for an effective and efficient delivery of services for generating future knowledge. Evaluating the value of libraries resources has implications both for librarians as well as library users.

The evaluation exercise established the efficacy of the TERI library holdings for research and academic purposes in the domain of sustainable development. The library collection was found to be cost effective and beneficial to meet the future demand from the user community.

The domain of study on mediated suffering is ensconced within an Orientalist paradigm which ideologically structures our visuality and gaze. The consignment of suffering through bodies of alterity and the geo-politics of the Global South encodes the coloniality of power as a dominant reading. It then naturalizes the West as the voyeur in its consumption of the abject bodies of the Global South. Creating a binary through this East-West polarization in the oeuvre of suffering as a realm of study, it creates the hegemony of the West as the moral guardian of suffering, imbuing it with the right to accord pity and compassion to the lesser Other. Beyond elongating the Orientalist trajectory which lodged the body politic of the Global South as a sustained ideological site of suffering, it hermeneutically seals the East as irredeemable, ordaining it through the gaze over the Other as a mode of coloniality. In countering this Eurocentric proposition, this chapter contends that this coloniality of gaze needs further rumination and new sensibilities in the study of mediated suffering, particularly following 9/11 and the shifting of the geo-politics of suffering in which the West is dispossessed through its own manufactured ideologies of the ‘War on Terror’ such that it is under constant threat of terrorist attacks and through the movement of the displaced Other into the Global North. Besieged and entrapped through its own pathologies of risks and threats, the West is projected through its own victimhood and the politics of the Anthropocene within which risks are seemingly democratized by environmental degradation as an overarching threat for all of humanity. Despite these shifts in the global politics, the scholarship of suffering is locked into this polarity. The chapter interrogates this innate crisis within this field of scholarship.

Although the previous generations of the Industrial Revolution have brought many advantages to human life, scientists have been looking for a substantial breakthrough in creating technologies that can improve the quality of human life. Nowadays, we can make our factories smarter using new concepts and tools like real-time self-optimization. This study aims to take a step towards implementing key features of smart manufacturing including  preventive self-maintenance, self-scheduling and real-time decision-making.

A new bi-objective mathematical model based on Industry 4.0 to schedule received customer orders, which minimizes both the total earliness and tardiness of orders and the probability of machine failure in smart manufacturing, was presented. Moreover, four meta-heuristics, namely, the multi-objective Archimedes optimization algorithm (MOAOA), NSGA-III, multi-objective simulated annealing (MOSA) and hybrid multi-objective Archimedes optimization algorithm and non-dominated sorting genetic algorithm-III (HMOAOANSGA-III) were implemented to solve the problem. To compare the performance of meta-heuristics, some examples and metrics were presumed and solved by using the algorithms, and the performance and validation of meta-heuristics were analyzed.

The results of the procedure and a mathematical model based on Industry 4.0 policies showed that a machine performed the self-optimizing process of production scheduling and followed a preventive self-maintenance policy in real-time situations. The results of TOPSIS showed that the performances of the HMOAOANSGA-III were better in most problems. Moreover, the performance of the MOSA outweighed the performance of the MOAOA, NSGA-III and HMOAOANSGA-III if we only considered the computational times of algorithms. However, the convergence of solutions associated with the MOAOA and HMOAOANSGA-III was better than those of the NSGA-III and MOSA.

In this study, a scheduling model considering a kind of Industry 4.0 policy was defined, and a novel approach was presented, thereby performing the preventive self-maintenance and self-scheduling by every single machine. This new approach was introduced to integrate the order scheduling system using a real-time decision-making method. A new multi-objective meta-heuristic algorithm, namely, HMOAOANSGA-III, was proposed. Moreover, the crowding-distance-quality-based approach was presented to identify the best solution from the frontier, and in addition to improving the crowding-distance approach, the quality of the solutions was also considered.

We provide straightforward new nonparametric methods for testing conditional independence using local polynomial quantile regression, allowing weakly dependent data. Inspired by Hausman's (1978) specification testing ideas, our methods essentially compare two collections of estimators that converge to the same limits under correct specification (conditional independence) and that diverge under the alternative. To establish the properties of our estimators, we generalize the existing nonparametric quantile literature not only by allowing for dependent heterogeneous data but also by establishing a weak consistency rate for the local Bahadur representation that is uniform in both the conditioning variables and the quantile index. We also show that, despite our nonparametric approach, our tests can detect local alternatives to conditional independence that decay to zero at the parametric rate. Our approach gives the first nonparametric tests for time-series conditional independence that can detect local alternatives at the parametric rate. Monte Carlo simulations suggest that our tests perform well in finite samples. We apply our test to test for a key identifying assumption in the literature on nonparametric, nonseparable models by studying the returns to schooling.

The management accounting aspects of quality are focused on. The traditional approaches of production and marketing are summarised with questions, such as how these can be combined, what relationship is there between price and quality, how can the various departments concerned in the strategic management of quality be drawn together, how one can decide on a quality strategy and what would be a suitable control system, being asked. A solution to these is proffered by looking at the management of quality from a strategic viewpoint, relating the appropriateness of seven pure quality strategies to the product/market life cycle.

This study aims to investigate how contract design influences supplier performance. This study synthesises three theoretical views (efficiency, relational, contingency) and provides empirical support on how effective contract design improves supplier performance.

This study reviewed contract design literature and uncovered 18 factors that may impact supplier performance. Multi-criteria, decision-making analysis examined the impact of contract factors on three supplier groups: average-, over- and under-performers. Procurement experts working with a large multinational company dealing with hundreds of procuring contracts, yearly, provided their judgement on the impact of these factors on supplier performance. Semi-structured interviews with experts and other evidence were used for data and method triangulation.

Results show that contracting with under- and over- performers presents significant differences: in the case of over-performers, contracts have a dual, yet discrete, efficiency and relational role: at transaction level, they emphasise formality, protect from opportunism and include both liquidated damages and legal action clauses. At relational level, they focus on relational learning and incentivising suppliers. However, in the case of under-performers, contracts appear to focus on contingency factors, which can be a source of ambiguity, particularly in complex environments, and trust, which has a negative impact on supplier performance.

Improving contract design can help reduce partner opportunism, reduce inter-firm conflicts and avoid disputes that can bear a social cost. This study demonstrates that companies can use advanced analytical tools to reflect upon their own decision-making process of contact design in making transparent supplier performance assessments.

To the author’s knowledge, this is the first study using decision-making techniques to enhance supplier performance by improving the contract design process.

Due to increasing socio-ecological concerns, manufacturers are paying ample attention to the strategic decision-making for enhancing customer satisfaction considering Industry 4.0 requirements. Customers' preferences are being considered vital into the decisions related to sustainable supplier selection for building competitive gain. Thus, the objective of this study is to develop a real-case-based empirical approach for evaluating performance of suppliers based on customers' feedback, an area not explored much in literature. The novelty of current study lies in the development of an integrated supplier evaluation and selection model involving three phases: (1) identifying sustainable criteria according to Industry 4.0 requirement through customers' feedback, (2) calculating relative scores of criteria using Z-numbers and (3) determining evaluation weights of suppliers using fuzzy-TOPSIS. The contribution of the study lies in effective validation of the model by considering the case of a manufacturing firm, which aids the firm in evaluating performance of suppliers based on customers' socio-ecological expectations while considering reliable information provided by decision-makers (DMs).