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The increasing importance and proliferation of text data provide a unique opportunity and novel lens to study human communication across a myriad of business and marketing applications. For example, consumers compare and review products online, individuals interact with their voice assistants to search, shop, and express their needs, investors seek to extract signals from firms' press releases to improve their investment decisions, and firms analyze sales call transcripts to increase customer satisfaction and conversions. However, extracting meaningful information from unstructured text data is a nontrivial task. In this chapter, we review established natural language processing (NLP) methods for traditional tasks (e.g., LDA for topic modeling and lexicons for sentiment analysis and writing style extraction) and provide an outlook into the future of NLP in marketing, covering recent embedding-based approaches, pretrained language models, and transfer learning for novel tasks such as automated text generation and multi-modal representation learning. These emerging approaches allow the field to improve its ability to perform certain tasks that we have been using for more than a decade (e.g., text classification). But more importantly, they unlock entirely new types of tasks that bring about novel research opportunities (e.g., text summarization, and generative question answering). We conclude with a roadmap and research agenda for promising NLP applications in marketing and provide supplementary code examples to help interested scholars to explore opportunities related to NLP in marketing.

This research work has developed an integrated fuzzy Delphi and neutrosophic best–worst framework for selecting the sustailient (sustainable and resilient) supplier for an additive manufacturing (AM)-enabled industry.

An integrated fuzzy Delphi method (FDM) and neutrosophic best–worst method (N-BWM) approach is developed. 34 supplier evaluation criteria falling under 4 groups, that is, traditional, sustainable, resilient, and AM specific, are identified and validated using the FDM. Afterward, the weights of each criterion are measured by N-BWM. Later on, the performance evaluation is carried out to determine the best-suited supplier. Finally, sensitivity analysis is performed to know the stability and robustness of the proposed framework.

The outcome indicates the high performance of the suggested decision-making framework. The analysis reveals that supplier 4 (S4) is selected as the most appropriate for a given firm based on the FDM and N-BWM method.

The applicability of this framework is demonstrated through an industrial case of a 3D-printed trinket manufacturer. The proposed research helps AM decision-makers better understand resiliency, sustainability, and AM-related attributes. With this, the practitioners working in AM business can prioritize the supplier selection criteria.

This is the primitive study to undertake the most critical aspect of supplier selection for AM-enabled firms. Apart from this, an integrated FDM-N-BWM framework is a novel contribution to the literature on supplier selection.

The desire of international retail brands to implement sustainable supply chain practices in the fashion value chain and improve suppliers' sustainability efforts; this research paper elucidates the relationship between blockchain technology and sustainability to impact apparel firms' triple bottom line.

For studying the impact of sustainable supply chain practices on the triple bottom line, a survey questionnaire was chosen and sent out to 500 garment companies simultaneously, of which 371 responded. The data collected is cross-sectional. The questionnaire survey was developed keeping in mind a few demographic elements such as experience, age and qualification to generalize the findings. For analysis, SmartPLS is used to run model structuring and regression analysis.

Test runs on model structure confirm the instrument's validity and reliability. Bootstrapping on the theoretical model to test developed hypotheses suggests that supply chain sustainability practices positively affect social, environmental and economic performance in a direct relationship. Further, indirect relation testing conducted to test blockchain technology's moderation influences only the constructs' relations.

The clubbing of sustainable supply chain practices and blockchain technology is a novel idea in the apparel industry; however, there are more constructs in the context of practice-based theory and supply chain which impact firm performance. Also, the research limits itself from discussing IT infrastructure and smart contract types that impact the technology's performance.

The study provides a framework for interpreting the synergetic influence of SSCP on firm social, environmental and economic performances, which is demanded both by consumers and regulators in an industry. The results suggest that managers sustainably design the production ecosystem, thus eliminating any discrepancy or slackness in the complete chain. Usually, suppliers are ignored, which are precursors in implementing SSCP.

The paper studies sustainability problems through ecological modernization theory and practical-based theory giving a unique perspective on the issue faced by the apparel industry and combining sustainable supply chain practices and blockchain.

This paper aims to perform a comparative study between capabilities of two numerical schemes from two main branches of numerical methods for solving hyperbolic conservation equations.

The accuracy and performance of a newly developed high‐resolution central scheme vs a higher‐order Godunov‐based method are evaluated in the context of black‐oil reservoir simulations. Both methods are modified enabling study of applications that are not strictly hyperbolic and exhibit local linear degeneracies in their wave structure.

The numerical computations show that while both schemes produce results with virtually the same accuracy, the Godunov method reproduces slightly more accurate results at the expense of calculation of eigen‐structures.

The paper investigates only one dimensional problems, but the idea can be easily extended to multi‐dimensional problems.

The paper shows the strengths and weaknesses of two practical numerical methods.

Such comparative study has not been published elsewhere and in particular, the performance of numerical methods on simulating hysteresis effect in hydrocarbon reservoirs has not been investigated in detail before.

Code smells indicate deep software issues. They have been studied by researchers with different perspectives. The need to study code smells was felt from the perspective of software industry. The authors aim to evaluate the code smells on the basis of their scope of impact on widely used open-source software (OSS) projects.

The authors have proposed a methodology to identify and rank the smells in the source code of 16 versions of Apache Tomcat Software. Further, the authors have analyzed the categorized smells by calculating the weight of the smells using constant weights as well as Best Worst Method (BWM). Consequently, the authors have used Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to determine the rank of versions using constant weights as well as BWM.

Version 1 of Apache Tomcat has least smell, and version 8 is reported to contain the maximum code smells. Notable differences in both the cases during the trend analysis are reported by the study. The findings also show that increase is observed in the number of code smells with the release of newer versions. This increment is observed till version 8, followed by a subtle marked depreciation in the number of code smells in further releases.

The focus is to analyze smells and rank several versions of Apache Tomcat, one of the most widely used software for code smell study. This study will act as a significant one for the researchers as it prioritizes the versions and will help in narrowing down the options of the software used to study code smell.

In this paper, the flow of multiphase fluids in a one-dimensional homogeneous porous media involving the gravity effects is numerically studied using the dominant wave method. The paper aims to discuss these issues.

The numerical scheme used for solving the pressure equations, obtained for the black-oil model, is a backward Euler scheme while the hyperbolic mass conservation equations, derived for both black-oil and Buckley-Leverett models, are solved using the dominant wave method. Higher-order schemes are achieved using either variable derivatives along with the minmod limiter or a MUSCL type interface construction scheme using the Fromm's limiter. The mass conservation equations are solved using the first-order forward Euler method in time. Harten's entropy correction procedure is employed to avoid non-physical expansion shocks.

It was found that the dominant wave method can accurately solve multiphase flow equations involving gravity effects. Numerical experiments also show that both minmod and Fromm's limiters can be successfully used to construct higher-order schemes while the minmod limiter gives slightly more diffuse solutions.

The flow models considered here include two- and three-phase Buckley-Leverett and the black-oil models and the capillary effects are neglected.

The proposed scheme can be efficiently used for solving problems involving non-convex flux functions especially those experienced during gravity drainage process in hydrocarbon reservoirs.

To the best of authors knowledge, this is the first time that the dominant wave method has been used to tackle multiphase flow problems involving gravity effect.

Product configurators are expert systems that support product customization by defining how predefined entities and their properties may be combined. Developers of configuration systems act as designers, although they do not often recognize that they are performing as such. Moreover, exploring solution spaces is typically not integral to configuration projects, as this task is typically perceived as mapping existing knowledge to the configurator. This article argues that developing configurators may be understood by distinguishing between the problem and solution spaces using design thinking (DT).

A multiple-case-study approach with four configuration projects is adopted to study two projects involving DT and compare them to two similar projects not involving DT. Data collection depended on multiple data sources via workshops and semi-structured interviews.

First, DT methods and concept–knowledge (C-K) theory are integrated into configuration projects. Second, the application of DT during configurator development is presented through workshops and interviews, which demonstrates the benefits of DT in overcoming existing challenges.

The case studies demonstrate the successful implementation of DT in developing configurators. However, a limited number of cases in only one company limits the generalizability of the results.

The framework's individual steps create a structured approach to supporting industrial companies with a toolbox of DT techniques and methods for configuration projects.

The results show that the application of DT to configuration projects can improve user motivation, stakeholder satisfaction and knowledge acquisition.

This paper presents a finite element model for analysis of damaged RC beams strengthened or repaired by externally bonding glass fibre reinforced plastics (GFRP) on the tension side of the beams. The salient features include: (i) the introduction of a thin, six—noded element to simulate behaviour of the concrete/epoxy glue/GFRP interface and )ii( a scheme of loading a virgin RC beam to a prescribed displacement to simulate damage, unloading and then reloading the damaged RC beam fortified by an externally bonded GFRP plate. Results are presented for RC beams repaired by plates of varying thickness and a transmutation of failure mode is noted from classical flexure for the case of external reinforcement in the form of thin GFRP plates to a unique concrete cover rip off failure for thicker GFRP plates and not predicted by the ACI shear strength formula for diagonal tension failure of unplated RC beams of similar geometry.

The purpose of this paper is to investigate the performance of a specific class of high‐resolution central schemes in conjunction with the black oil models for hydrocarbon reservoir simulation.

A generalized black oil model is adopted, in which the solubility of gas in both oil and water and evaporation of oil are considered, leading to a system of equations prone to degeneracy. A computer code is generated and three test cases are solved to evaluate the performance of various schemes in terms of accuracy and discontinuity handling.

It is shown that, although some of the central schemes are highly sensitive to the choice of Courant‐Friedrich‐Levy (CFL) number and produce overly diffusive results, a certain type of this class is insensitive to the CFL number and can conveniently handle degenerate equations appearing in the reservoir simulation. The obtained results are compared with those available in the literature, showing merits of this class of schemes in complex reservoir simulation models.

This paper gives the one‐dimensional implementation of the above‐mentioned schemes. Extension to higher dimensional black oil model is currently under development by the authors.

The specific class of high‐resolution central schemes investigated here presents the same level of accuracy as more complicated numerical methods, yet keeping it much more simple, by avoiding Riemann solvers.

The high‐resolution central scheme used in this work has been newly developed and applied to simple scalar hyperbolic equations. It has been adopted for the black oil for the first time.

The purpose of this paper is to address various works on mixed convection and proposes 10 unified models (Models 1–10) based on various thermal and kinematic conditions of the boundary walls, thermal conditions and/ or kinematics of objects embedded in the cavities and kinematics of external flow field through the ventilation ports. Experimental works on mixed convection have also been addressed.

This review is based on 10 unified models on mixed convection within cavities. Models 1–5 involve mixed convection based on the movement of single or double walls subjected to various temperature boundary conditions. Model 6 elucidates mixed convection due to the movement of single or double walls of cavities containing discrete heaters at the stationary wall(s). Model 7A focuses mixed convection based on the movement of wall(s) for cavities containing stationary solid obstacles (hot or cold or adiabatic) whereas Model 7B elucidates mixed convection based on the rotation of solid cylinders (hot or conductive or adiabatic) within the cavities enclosed by stationary or moving wall(s). Model 8 is based on mixed convection due to the flow of air through ventilation ports of cavities (with or without adiabatic baffles) subjected to hot and adiabatic walls. Models 9 and 10 elucidate mixed convection due to flow of air through ventilation ports of cavities involving discrete heaters and/or solid obstacles (conductive or hot) at various locations within cavities.

Mixed convection plays an important role for various processes based on convection pattern and heat transfer rate. An important dimensionless number, Richardson number (Ri) identifies various convection regimes (forced, mixed and natural convection). Generalized models also depict the role of “aiding” and “opposing” flow and combination of both on mixed convection processes. Aiding flow (interaction of buoyancy and inertial forces in the same direction) may result in the augmentation of the heat transfer rate whereas opposing flow (interaction of buoyancy and inertial forces in the opposite directions) may result in decrease of the heat transfer rate. Works involving fluid media, porous media and nanofluids (with magnetohydrodynamics) have been highlighted. Various numerical and experimental works on mixed convection have been elucidated. Flow and thermal maps associated with the heat transfer rate for a few representative cases of unified models [Models 1–10] have been elucidated involving specific dimensionless numbers.

This review paper will provide guidelines for optimal design/operation involving mixed convection processing applications.