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This study aims to explore the potential benefits favoring the adaptation of structural optimization techniques in the additive manufacturing (AM) of medical utilities to meet the repetitive demand for functionally precise customized orthoses. Irregularities encountered during the conventional treatment of tendon injuries can be eschewed using advanced structural simulation in design and innovative splint fabrication using 3D printing.

A customized mallet finger splint designed from 3D scans was subjected to ANSYS topological simulation comprising multi-level weight reduction to retain optimal mass (100%, 90%, 80%, 70% and 60%). A batch of the four typical 3D printing materials was chosen to conduct a comparative mechanical and thermal stress analysis, facilitating the selection of the optimal one for fabricating functionally adaptive splints. Assurance of structural safety was accomplished through the experimental validation of simulation results against the testing data set of ASTM D695 and ASTM D638 Type-1 specimens over a universal testing machine (UTM). Fused deposition modeling (FDM) 3D printing processed the optimized splint fabrication to assist evaluation of weight reduction percentage, fitting aesthetics, appearance, comfort, practicality and ventilation ease at the user end.

AM efficacy can efficiently execute the design complexity involved in the topology optimization (TO) results and introduces rehabilitation practicality into the application. Topologically optimized splint provided with favorable comfort, stiffness and strengthening features, offers ventilation ease and structural stability for customized appliances, with 30.52% lighter weight and 121.37% faster heat dissipation than unoptimized one.

The state of art multidisciplinary optimization featured with structural and material optimization attributes can deliberately meet medical necessity for performance-oriented orthotic devices.

Samirah Al-Saleh <sameeraalsaleh@hotmail.com> is a lecturer in geography and tourism at King Abdul Aziz University, Jeddah, Saudi Arabia. She is also a doctoral candidate in the Faculty of Business and Law at the University of Sunderland, United Kingdom. She has participated in numerous tourism conferences in Saudi Arabia and abroad. She has contributed to the journal, Al Aqiq, in a recent special edition on the topic of domestic tourism in Saudi Arabia.

For sustainable progress of heritage tourism in Muslim regions, exaggerated and distorted notions of Islam have to be dispelled. To accomplish such an arduous task, the first step is to examine media content employed by key tourism organizations/agencies in Muslim countries. This chapter examines the heritage environments and contemporary macro environment factors in Muslim countries that are either secular or Islamic in nature. Using cultural indicators, it further analyzes the content of website marketing employed by the leading tourism authorities in the selected regions to understand if considerations and efforts are made to market Muslim heritage. The findings indicate mixed results.

Introduction: Artificial intelligence (AI), the engineering of brilliant machinery, performs intelligent human intelligence tasks, such as learning and problem-solving. Insurance is a financial protection policy either for individuals or entities to reimburse losses from the insured company. The role of AI in insurance always helps enhance customer services and understand their behaviour.

Purpose: This chapter aims to determine the role of AI in the insurance industry in India. The insurance industry is expanding very fast, and to further increase its horizons, the part of the technology of AI is essential. However, this sector has initiated using AI technology and is expanding its scope to benefit the customers.

Methodology: The authors selected research papers of the last five years to review and determine how the technology changed during the period and how an increase in AI benefits the industry and facilitates delivering the best services, and understanding the customer’s needs and behaviour.

Findings: It has been found that the industry is moving very fast and adopting the AI technology methods to enhance customer services, betterment for growing India, and serve insurance services to the nation efficiently.

Working capital efficiency (WCE) is crucial for the sustainability of both large and small firms. This study aims to use the sample of micro, small and medium-sized enterprises (MSMEs) in India and tries to understand the critical determinants of WCE.

Using a fixed effect panel data model on a sample of 578 MSMEs (59 micro, 226 medium and 296 small firms), this study explores the relationship between the predictors of WCE. Additionally, the study adopted two metrics for measuring WCE among each type of firm (micro, small and medium).

Several firm-specific variables, including leverage (lever), firm age (AGE), firm size (Fsiz), profitability (Prof), extended payment terms (EPT), human capital (HCap), asset turnover ratio (ATR), reverse factoring (RF) and firm growth (FG), have a significant effect on working capital management efficiency (WCE). In contrast, tangibility (Tangib) and salary expenses (Sal) had an insignificant effect on working capital management efficiency.

The study is based on secondary data. Future studies may incorporate some primary data, which will facilitate qualitative analysis.

The studies explore the relationship between WCE and expenses in HCap, EPT, RF and Sal as the predictors for WCE, which was not studied earlier in MSMEs scenario, especially in case of developing nation.

While founder characteristics have been studied extensively as a factor in attracting employees, organizational attributes of startups have received little attention. To fill the void, this study aims to examine organizational attributes of startups to attract employees.

This research collected 8,817 online employer reviews of 117 startups from Glassdoor.com. This research conducted two studies. In Study 1, a topic modeling approach was applied to identify startup attributes to attract employees having actual employer experience and to examine the importance and relationship of the attributes, drawing the person–organization fit theory. Study 2 used logistic regression analysis to explore the effect of identified attributes on employer attractiveness based on the signaling theory.

Study 1 found six attributes: high-quality coworkers, entrepreneurial culture, development, company outlook, physical office and stereotypical startup perks. This study also found high-quality coworkers, entrepreneurial culture and development are not only related to each other but also more critical attributes than other attributes. The core value of the three attributes can be conceptualized as “learning opportunity.” Study 2 found that employees attracted to “learning opportunity” are more likely to recommend their employers than instrumental attributes, including physical office and stereotypical startup perks.

This research elaborates on employer attributes to attract employees in the context of startup based on the real voices of employees having actual employer experience. Furthermore, this research extends the understanding of employer attributes contributing to employer attractiveness by combining qualitative review data with quantitative rating data.