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The goal of this research is to demonstrate micro‐electro‐mechanical systems (MEMS)‐based transducers for aircraft maneuvering. Research in wind tunnels have shown that micro‐actuators can be used to manipulate leading edge vortices found on aerodynamic surfaces with moderate to highly swept leading edges, such as a delta wing. This has been labeled as the MEMS vortex shift control (MEMS‐VSC). The work presented in this paper seeks to detail the evolution of real‐world flight tests of this research using remotely piloted vehicles (RPVs).

Four different RPVs were constructed and used for flight tests to demonstrate the ability of using MEMS devices to provide flight control, primarily in the rolling axis.

MEMS devices for high angle‐of‐attack (AOA) turning flights have been demonstrated and the paper finds that the success of a complex project like the MEMS‐VSC requires the marriage of basic science expertise found in academia and the technical expertise found in industry.

Owing to the need to test fly the RPVs at low altitudes for video documentation while performing high AOA maneuvers, the attrition of the RPVs becomes the dominant factor to the pace of research.

MEMS sensors and actuators can be used to augment flight control at high AOA, where conventional control surfaces typically experiences reduced effectiveness. Separately, the lessons learned from the integration efforts of this research provide a potentially near parallel case study to the development of ornithopter‐based micro aerial vehicles.

This is the only research‐to‐date involving the demonstration of the MEMS‐VSC on real‐world flight vehicles.

The purpose of this paper is to determine the effects of fatigue on fused deposition modeling rapid prototyped acrylonitrile butadiene styrene (ABS) materials.

FDM dog bones based on UNI EN ISO 527‐1 (1997) were tested at 100, 80, 60, and 40 per cent nominal values of the ultimate stress for nine different print orientations. The samples were cyclically stressed in a tensile tester at 25.4 mm/min (extension) and relaxed at 12.7 mm/min.

Although FDM ABS has a tensile strength that is relatively close to that of the bulk material, up to 80 percent, its ability to absorb energy before fracture has a tremendous amount of room for improvement. FDM ABSplus (P430) material properties are noticeably more isotropic than the predecessor, ABS (P400). The ABSplus fractures in the order of thousands of cycles at 40 percent of ultimate stress load, while the ABS exhibits the similar cycle limits at 60 percent of its ultimate stress load.

FDM ABS parts are limited in fatigue characteristics even though they exhibit similar ultimate stress limits as with bulk materials, warranting further research in improving FDM parts expected to experience cyclical loads.

This paper adds knowledge to the limited fatigue data in literature for FDM ABS. It investigated the load cyclic data of fused deposition modeled ABS through analyzing its cycle‐by‐cycle strain energy, providing another means of identifying the fatigue characteristics of materials.

The purpose of this paper is to explore how internal and external factors simultaneously drive firms to adopt green supply chain (GSC) initiatives and to construct a comprehensive research model by drawing upon institutional theory, stewardship theory, and view of performance.

The data collected from 380 manufacturers in the electrical and electronics industries in Taiwan were analyzed via structural equation modeling and bootstrapping.

First, institutional pressures affect the GSC initiatives of firms. Second, institutional pressures influence the environmental stewardship behaviors (ESBs) of managers. Third, the ESBs of managers affect the GSC initiatives of firms. Fourth, the GSC initiatives of firms influence their environmental performance, economic performance, and competitiveness. Fifth, the bootstrapping results reveal that institutional pressures indirectly affect the GSC initiatives of firms through the ESBs of managers.

Environmental sustainability has intensified the need for firms to develop a corporate culture. Future research can investigate the relationship among the institutional pressures, greening corporate culture, and GSC initiatives of firms.

Those managers facing institutional pressures must continually focus on the effects of external factors on the GSC initiatives of their firms. They must also increase their commitment and support to such initiatives to attain favorable levels of environmental performance, economic performance, and competitiveness.

This study integrates four streams of literature on institutional theory, stewardship theory, GSC initiatives, and view of performance. Apart from analyzing field- and organization-level data simultaneously, this paper is also the first to demonstrate the relationships among institutional pressures, ESBs of managers, GSC initiatives, and firm performance.

Innovation is a key factor in assessing organizational success. The purpose of this paper is to examine how the organizational culture and operations strategy impact organizational innovation. It explores the influence of various combinations of organizational cultures and operations strategies on a firm’s ability to innovate both in process and product.

A conceptual model is developed which attempts to explain how the reciprocal and dynamic interactive relationship between organizational culture and operations strategy and innovation is structured. In total, 233 valid questionnaires were collected from 17 small- and medium-sized enterprises (SMEs) in Taiwan. Structural equation modeling was used to investigate the direction and strengths of the relationships and develop a comprehensive picture to illustrate the drivers of successful innovation.

The analysis and conclusions confirm the suitability of Culture–Strategy–Innovation Model and the detailed results demonstrate that a combination of innovative organizational culture and flexibility-oriented operations strategy has the strongest influence on a firm’s innovation process thereby improving their innovative organizational outcomes.

Although based on Taiwanese manufacturing industries these results provide useful insights for manufacturing industries in general. In alternative contexts, the combination of different dimensions of culture and strategy can be expected to cause different levels of success in innovation. This study provides robust evidence to explain the organizational climate needed to guide the innovative and flexibility considerations needed for SMEs in the manufacturing industry.

This is an empirical study which specifically investigates the activities of SMEs in the metal/plastic manufacturing industry in Taiwan and in particular examines organizational culture, operations strategies and innovation. The research model proposed and confirmed offers a new multi-dimensional structure of culture and strategy linked with their various related dynamic interrelationships and the drivers that impact organizational innovation.

Little research has been conducted on the internal factors that drive green product (GP) innovation and how family influence affects firm adoption of GP innovation. This study aims to apply multiple perspectives to bridge this research gap, adopting the resource-based view (RBV) to examine what and how internal factors affect firm adoption of GP innovation, and using the behavioral theory of family firms to investigate whether family influence fosters or hinders firm adoption of GP innovation.

This study used a multichannel approach and adopted content analysis to collect and evaluate data on listed Taiwanese firms and used cross-sectional regression analysis to examine the effect of internal factors and family influence on firm adoption of GP innovation.

The results showed that the internal factors of green capabilities, R&D intensity and firm size significantly and positively affected firm adoption of GP innovation separately. Furthermore, the study found that family influence (ownership and control) significantly and negatively affects firm adoption of GP innovation separately.

This study contributes to the academic research of innovation management, green management and family firms in several aspects, but also has some limitations. This study examined only the relationship between a firm’s internal factors and GP innovation. Future research might test the relationship between a firm’s internal factors and adoption of green process innovation. In addition, such research can explore how integrated internal and external factors influence firm adoption of GP innovation.

From the RBV, the internal factors of green capabilities, R&D intensity and firm size that can exert crucial effects on firm engage in firm’s adoption of GP innovation. This study suggests that top managers in family-influenced businesses should maintain appropriate commitment and support for fostering and facilitating firm GP innovation.

From the RBV, this study examined how internal factors affect firm adoption of GP innovation. Moreover, based on the behavioral theory of family firms, this study further examined how family influence (ownership and control) affects firm adoption of GP innovation. This paper extended both perspectives to examine green issues.

From the RBV, this study examined how internal factors affect firms’ GP innovation. Moreover, based on institutional theory, this study further examines how a family firm moderates the relationship between a firm’s internal factors and GP innovation. The paper extended both perspectives to probe further the green issues.

Building upon the framework of glocalization, the purpose of this paper is to summarize the development of National Basketball Association (NBA) in Chinese market, explore its successful and unsuccessful places, and propose strategies of glocalization for the NBA as well as other overseas sport leagues.

The current case study was organized by summarizing the developmental history of NBA in China, analyzing its current promotional practices, investigating into its marketing strategies, and extrapolating practical references for other sport leagues aiming to penetrating into the Chinese marketplace.

The current case study concluded that when facing the current challenges, the NBA needs to bring authentic American cultural commodities while adding Chinese characteristics to accommodate local fans. Meanwhile, the NBA management needs to continue seeking ways to work out and through the differences in government models and cultural contexts between China and USA. In addition, this study suggested that the research framework of glocalization would be an ever intriguing inquiry needed for other sport organizations or leagues seeking expansion to overseas markets.

A thorough case study with the NBA that has achieved huge successes in Chinese markets will provide valuable implications for sport leagues to broaden their overseas markets.

The concept and practice of e-services has become essential in business transactions. Yet there are still many organizations that have not developed e-services optimally. This is especially relevant in the context of Indonesian Airline companies. Therefore, many airline customers in Indonesia are still in doubt about it, or even do not use it. To fill this gap, this study attempts to develop a model for e-services adoption and empirically examines the factors influencing the airlines customers in Indonesia in using e-services offered by the Indonesian airline companies. Taking six Indonesian airline companies as a case example, the study investigated the antecedents of e-services usage of Indonesian airlines. This study further examined the impacts of motivation on customers in using e-services in the Indonesian context. Another important aim of this study was to investigate how ages, experiences and geographical areas moderate effects of e-services usage.

The study adopts a positivist research paradigm with a two-phase sequential mixed method design involving qualitative and quantitative approaches. An initial research model was first developed based on an extensive literature review, by combining acceptance and use of information technology theories, expectancy theory and the inter-organizational system motivation models. A qualitative field study via semi-structured interviews was then conducted to explore the present state among 15 respondents. The results of the interviews were analysed using content analysis yielding the final model of e-services usage. Eighteen antecedent factors hypotheses and three moderating factors hypotheses and 52-item questionnaire were developed. A focus group discussion of five respondents and a pilot study of 59 respondents resulted in final version of the questionnaire.

In the second phase, the main survey was conducted nationally to collect the research data among Indonesian airline customers who had already used Indonesian airline e-services. A total of 819 valid questionnaires were obtained. The data was then analysed using a partial least square (PLS) based structural equation modelling (SEM) technique to produce the contributions of links in the e-services model (22% of all the variances in e-services usage, 37.8% in intention to use, 46.6% in motivation, 39.2% in outcome expectancy, and 37.7% in effort expectancy). Meanwhile, path coefficients and t-values demonstrated various different influences of antecedent factors towards e-services usage. Additionally, a multi-group analysis based on PLS is employed with mixed results. In the final findings, 14 hypotheses were supported and 7 hypotheses were not supported.

The major findings of this study have confirmed that motivation has the strongest contribution in e-services usage. In addition, motivation affects e-services usage both directly and indirectly through intention-to-use. This study provides contributions to the existing knowledge of e-services models, and practical applications of IT usage. Most importantly, an understanding of antecedents of e-services adoption will provide guidelines for stakeholders in developing better e-services and strategies in order to promote and encourage more customers to use e-services. Finally, the accomplishment of this study can be expanded through possible adaptations in other industries and other geographical contexts.

This study aims to explore the relationships among institutional pressures, commitment of resources and returns management. Returns management is regarded as a part of supply chain management. However, the research in returns management has received much less attention. To bridge the gap, this study concerns key concepts from two important schools of thought, i.e. institutional theory and the resource-based view, to build up the research model.

Retailers and maintenance providers in the 3C industry (computers, communication and consumer electronics) in Taiwan were surveyed, and the statistical methods of hierarchical and moderated regression were used to examine the relationships among institutional pressures, commitment of resources and returns management.

Institutional pressures, comprising non-market and market pressures, affect the implementation of returns management (product return practices and product recovery practices). Commitments of resources positively and significantly moderate the relationship between the pressures imposed by non-market and market actors and product return practices and product recovery practices.

This study investigates only the factors that drive returns management. Future research can examine the relationship between the antecedents and consequences of returns management. Furthermore, returns management may become increasingly critical for firms to develop and perform corporate social responsibility (CSR). Therefore, future research can investigate the relationship between CSR practices and returns management.

This research suggests that managers under institutional pressures should continually pay attention to the effects of external factors on returns management. Additionally, the results reveal that a commitment of resources can reinforce the relationship between the pressures imposed by non-market and market actors and the implementation of returns management. Under significant institutional pressures and resource constraints, managers may increase the effectiveness of returns management while attending to the concerns of non-market and market actors.

This study presents a model that considers three major explicative variables: institutional pressures, resources commitment and returns management. It is the first investigation to integrate three streams of literature on institutional theory, the resource-based view and returns management.

This chapter explored how people and technology are managed in the workplace. It examines how data and data analytics in AI, human resource information system (HRIS), learning content management systems, learning management systems, and talent management software have become major components of human resource and workforce development. Middle-skill, low-skill, and disadvantaged employees are being asked to use their knowledge, skills, and abilities (KSAs) to evaluate and understand technology systems, technology resources, and equipment in the workplace. HRD and HRM professionals must understand the competencies and resources needed to achieve harmony and balance between people and technology use in the workplace.

The purpose of this paper is three-fold: to review the categories explaining mainly optimization algorithms (techniques) in that needed to improve the generalization performance and learning speed of the Feedforward Neural Network (FNN); to discover the change in research trends by analyzing all six categories (i.e. gradient learning algorithms for network training, gradient free learning algorithms, optimization algorithms for learning rate, bias and variance (underfitting and overfitting) minimization algorithms, constructive topology neural networks, metaheuristic search algorithms) collectively; and recommend new research directions for researchers and facilitate users to understand algorithms real-world applications in solving complex management, engineering and health sciences problems.

The FNN has gained much attention from researchers to make a more informed decision in the last few decades. The literature survey is focused on the learning algorithms and the optimization techniques proposed in the last three decades. This paper (Part II) is an extension of Part I. For the sake of simplicity, the paper entitled “Machine learning facilitated business intelligence (Part I): Neural networks learning algorithms and applications” is referred to as Part I. To make the study consistent with Part I, the approach and survey methodology in this paper are kept similar to those in Part I.

Combining the work performed in Part I, the authors studied a total of 80 articles through popular keywords searching. The FNN learning algorithms and optimization techniques identified in the selected literature are classified into six categories based on their problem identification, mathematical model, technical reasoning and proposed solution. Previously, in Part I, the two categories focusing on the learning algorithms (i.e. gradient learning algorithms for network training, gradient free learning algorithms) are reviewed with their real-world applications in management, engineering, and health sciences. Therefore, in the current paper, Part II, the remaining four categories, exploring optimization techniques (i.e. optimization algorithms for learning rate, bias and variance (underfitting and overfitting) minimization algorithms, constructive topology neural networks, metaheuristic search algorithms) are studied in detail. The algorithm explanation is made enriched by discussing their technical merits, limitations, and applications in their respective categories. Finally, the authors recommend future new research directions which can contribute to strengthening the literature.

The FNN contributions are rapidly increasing because of its ability to make reliably informed decisions. Like learning algorithms, reviewed in Part I, the focus is to enrich the comprehensive study by reviewing remaining categories focusing on the optimization techniques. However, future efforts may be needed to incorporate other algorithms into identified six categories or suggest new category to continuously monitor the shift in the research trends.

The authors studied the shift in research trend for three decades by collectively analyzing the learning algorithms and optimization techniques with their applications. This may help researchers to identify future research gaps to improve the generalization performance and learning speed, and user to understand the applications areas of the FNN. For instance, research contribution in FNN in the last three decades has changed from complex gradient-based algorithms to gradient free algorithms, trial and error hidden units fixed topology approach to cascade topology, hyperparameters initial guess to analytically calculation and converging algorithms at a global minimum rather than the local minimum.

The existing literature surveys include comparative study of the algorithms, identifying algorithms application areas and focusing on specific techniques in that it may not be able to identify algorithms categories, a shift in research trends over time, application area frequently analyzed, common research gaps and collective future directions. Part I and II attempts to overcome the existing literature surveys limitations by classifying articles into six categories covering a wide range of algorithm proposed to improve the FNN generalization performance and convergence rate. The classification of algorithms into six categories helps to analyze the shift in research trend which makes the classification scheme significant and innovative.