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One of the critical reasons for the nonacceptance of additive manufacturing (AM) processes is the lack of understanding and structured knowledge of design for additive manufacturing (DfAM). This paper aims to assist designers to select the appropriate AM technology for product development or redesign. Using the suggestion provided by the design assist tool, the user’s design alterations depend on their ability to interpret the suggestion into the design without affecting the design’s primary objective.

This research reports the development of a tool that evaluates the efficacy values for all seven major standard AM processes by considering design parameters, benchmark standards within the processes and their material efficacies. In this research, the tool provides analytical and visual approaches to suggestion and assistance. Seventeen design parameters and seven benchmarking standards are used to evaluate the proposed product and design quality value. The full factorial design approach has been used to evaluate the DfAM aspects, design quality and design complexity.

The outcome is evaluated by the product and design quality value, material suit and material-product-design (MPD) value proposed in this work for a comparative assessment of the AM processes for a design. The higher the MPD value, the better the process. The visual aspect of the evaluation uses spider diagrams, which are evaluated analytically to confirm the results’ appropriateness with the proposed methodology.

The data used in the database is assumed to make the study comprehensive. The output aims to help opt for the best process out of the seven AM techniques for better and optimized manufacturing. This, as per the authors’ knowledge, is not available yet.

This paper aims to disentangle the mechanism linking digital servitization and manufacturing firm performance. The contributions of the service networks and slack resources are analyzed.

Drawing on a survey of manufacturing firms that have implemented or are implementing digital service projects in China, this paper examines the mediation effect of service networks and the moderated mediation effect of slack resources to capture the role of service networks and slack resources in the relationship between digital servitization and manufacturing firm performance.

Both basic and advanced digital services can equally contribute to manufacturing firm performance. Service networks mediate the relationship between basic digital servitization and manufacturing firm performance. No moderated mediation effect of slack resources is found, but slack resources negatively moderate the effects of basic digital services on service networks and positively impact service networks.

The mediating mechanism of service networks in the relationship between digital servitization and manufacturing firm performance is theorized, and it is clarified that service networks mediate the association between basic digital services and manufacturing firm performance but not advanced digital services. Additionally, there is no significant difference in performance implications when manufacturing firms provide basic versus advanced digital services, answering the call for research on the various types of digital servitization. This paper also identifies firms’ slack resources as the boundary conditions under which basic digital services influence service networks and the positive impacts of slack resources on service networks, bridging the network literature, organizational slack literature and digitalization literature under the framework of service ecosystem research.

This paper aims to investigate the eco-friendly neodymium tartrate (NdTar) inhibitor for mild steel in sodium chloride (NaCl) solution.

The mild steel 1010 coupon was considered for the current study. Weight loss and the electrochemical methods were used to evaluate the inhibitory effects of neodymium chloride (NdCl₃) and NdTar on mild steel in NaCl solution. Scanning electron microscopy, energy-dispersive X-ray analysis and attenuated total reflectance-Fourier transform infrared spectroscopy measurements were carried out to study the morphology and composition of the film, nature of deposits and corrosion products formed in test media on the corroded steel, with the objective of further analyzing the observed behavior of the two inhibitors.

Of the two, NdTar performs better than NdCl₃ because it shields mild steel surfaces for longer. According to the results, when NdCl₃ is present in a corrosive solution, the protective film only comprises Nd/Fe oxide/hydroxide/carbonate. However, when neodymium is coupled with the tartrate group (an organic group) and then added to the NaCl solution, the inhibitor film comprises both bimetallic complexes (Fe-Tar-Nd) and metal oxide/hydroxide/carbonate, which results in a more compact film and has higher inhibition efficiency.

This study evaluated the combined effects of inorganic and organic inhibitors with those of an inorganic inhibitor used alone for mild steel in NaCl solution.

The purpose is twofold. First, this study aims to establish that black box tree-based machine learning (ML) models have better predictive performance than a standard linear regression (LR) hedonic model for rent prediction. Second, it shows the added value of analyzing tree-based ML models with interpretable machine learning (IML) techniques.

Data on Belgian residential rental properties were collected. Tree-based ML models, random forest regression and eXtreme gradient boosting regression were applied to derive rent prediction models to compare predictive performance with a LR model. Interpretations of the tree-based models regarding important factors in predicting rent were made using SHapley Additive exPlanations (SHAP) feature importance (FI) plots and SHAP summary plots.

Results indicate that tree-based models perform better than a LR model for Belgian residential rent prediction. The SHAP FI plots agree that asking price, cadastral income, surface livable, number of bedrooms, number of bathrooms and variables measuring the proximity to points of interest are dominant predictors. The direction of relationships between rent and its factors is determined with SHAP summary plots. In addition to linear relationships, it emerges that nonlinear relationships exist.

Rent prediction using ML is relatively less studied than house price prediction. In addition, studying prediction models using IML techniques is relatively new in real estate economics. Moreover, to the best of the authors’ knowledge, this study is the first to derive insights of driving determinants of predicted rents from SHAP FI and SHAP summary plots.

The purpose of the research is to identify the major constraints to the growth of micro, small and medium enterprises (MSMEs) in a less-developed region of an emerging economy and how these constraints are affected by owner/manager's attributes and firm-specific characteristics.

To fulfill the objectives, a structured questionnaire is used to gather data from 200 randomly selected MSMEs located in Cachar district of Assam, India. The study applies factor analysis to categorize various perceived constraints into resolute sets of problem variables or factors. Then, the summated scales are regressed on the predictors related to owner-manager's attributes and firm characteristics to validate the hypotheses.

The results demonstrate that the broad factors constraining the development of MSMEs in Cachar district are as follows: (1) financial issues, (2) infrastructure problems, (3) labor and management issues, (4) market problems and (5) input problems. Furthermore, the findings confirm that firm growth, size, age, sector, location, innovation activity, owner-manager's gender, age and level of education significantly affect the identified constraints.

Although the research is limited to the Cachar district of India, the findings are relevant for other similar districts of India and less-developed regions of emerging economies. However, the study needs to be replicated in other regions of India as well as in other emerging economies for cross-validation and to determine the generalizability of the results.

To the authors' knowledge, no studies linking the constraints faced by MSMEs to owner/manager's attributes and firm-specific characteristics are carried out in the north-eastern region of India. The study also extends the limited researches on the influence of owner-manager's attributes and firm characteristics on the constraints to the growth of MSMEs by incorporating additional predictors.

This study aimed to examine the role of big data analytics capabilities (BDAC) in fostering organizational innovation capabilities and, consequently, in achieving economic, social and environmental sustainability.

Through the lens of dynamic capability theory, this study surveyed 115 hotels using purposive sampling to gain in-depth insights regarding the factors affecting organizational sustainability in the hospitality industry. The data analysis was conducted using partial least squares-structural equation modeling (PLS-SEM).

The findings reported a substantial impact of seven core dimensions (i.e. technology, data, basic resources, technological skills, managerial skills, organizational learning and data-driven culture) in building BDAC among hotels. Moreover, BDAC was also revealed to significantly influence innovation capabilities, positively impacting all three sorts of sustainability performance. Innovation capability also mediated the relationship between BDAC and all sustainability factors.

The findings will assist policymakers and practitioners in developing effective initiatives to enhance the adoption and implementation of data science and technologies, substantially contributing to the “National IR 4.0 Policy” and “Malaysia Digital Economy Blueprint” and achieving sustainable development goals (SDGs).

The originality of this study is established by investigating the interplay between BDAC, innovation capability and sustainability performance, particularly in the context of the hotel industry, whereas the existing studies focus on exploring the advantages of BDA.

Esthetic trend changes with the development of society and cultural differences. A minimizer bra designed to make breasts appear smaller is now popular with large-breasted women in China. To conform to the requirements of modern aesthetics in China, this paper aims to investigate vital features of breast appearance that influence people’s subjective evaluation of breast size and analyze how bra design parameters affect breast shape and make breasts appear smaller.

This study used 3D scanning technology and reverse engineering software to obtain objective breast measurements in detail. A subjective evaluation experiment was conducted to evaluate the overall performance of seven minimizer bras compared to a basic comparison bra. Around 20 design parameters of 8 sample bras were identified to make a further study about the correlation between bra design features and breast shaping effect. To gain a deeper understanding of how bras interact with breast tissue, this study presented heat maps of the breast surface to visualize the deformation of breast shape.

Nine breasts' characteristics, such as the distance between bust points, breast depth, outer breast curvature and slope, etc. have been determined to be highly correlated with the visual reduction effect of breasts. In addition, for the bras in this experiment, the high-performance bra for women with large breasts tends to have a wider side panel, a wider under band, higher gore and a stronger transverse rigidity of the bra cup. According to the observation of heat maps of the breast surface, soft full-figure bras provide a wider range of compression to the breasts and effectively flatten the breasts.

This paper first aimed at the need to shape the ideal breast appearance for large-breasted women and make a further study of several hot-selling minimizer bras in China. The suggestions given in this paper help lingerie manufacturers better understand how design features of bras can affect their shaping effect and improve the wearing effect of minimizer bras for large-breasted women.

To understand the seismic behavior of reinforced concrete (RC) beams confined by corroded stirrups, low-reversed cyclic loading tests were carried out on seven RC beam specimens with different stirrup corrosion levels and stirrup ratios to investigate their mechanical characteristics.

The failure mode, hysteresis behavior, skeleton curves, ductility, stiffness degradation and energy dissipation behavior of RC specimens are compared and discussed. The experimental results showed that the restraint of concrete provided by corroded stirrups is reduced, which leads to a decline in seismic performance.

For the specimens with the same ratios of stirrup, as the corrosion level increased, the load-carrying capacity, stiffness, plastic deformation capacity and energy-dissipation capacity dropped significantly. Compared with the uncorroded specimen, the failure modes of specimens with high corrosion level changed from ductile bending failure to brittle failure. For the specimens with the same levels of corrosion, the higher the stirrup ratio was, the stronger the restraint effect of the stirrups on the concrete, and the seismic behavior of the specimens was obviously improved.

In this paper, a total of seven full-size RC beam specimens at joints with different stirrup corrosion levels and stirrup ratios were designed and constructed to explore the influences of corrosion levels and stirrup ratios of stirrups on the seismic performances. The failure modes, strain of reinforcement, hysteretic curves, skeleton curves, stiffness degradation and ductility factor of RC specimens are compared and discussed.

This study investigates Rokkan's research programme in the light of the differences between case- and variables-based methodologies. Three phases of the research process are distinguished. Studying the way Rokkan actually proceeded in the research within his Europe project, we find that he follows the protocols of case-methodologies such as grounded theory. In the second phase of the research process, however, he constructs variables-based models as tools for his macro-historical comparisons. To get to variables from the sensitizing concepts coded in the first phase, Rokkan defines his variables as close to cases as possible: variables as nominal level typologies, types as variable values. He thus faces two interrelated dilemmas. First, a philosophy of science dissonance: he legitimates his research only with reference to a variable-methodology, while his research is thoroughly case based. Second, a paradox of double coding: using variable-based models in the second phase, the status of the knowledge available in the first phase memos is degraded. Rokkan cannot decide between the two main solutions to these dilemmas: The first solution is to discard his heterogeneous data, instead working only with homogeneous data that opens up to more consistently variables-oriented research. The second solution is to replace the notion of variables/variable values with typology/types, thereby returning to cases, pursuing comparative case reconstructions in the third phase of research. The study concludes in favour of the second solution.