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Multiple classifier systems have been used widely in computing, communications, and informatics. Combining multiple classifier systems (MCS) has been shown to outperform a single classifier system. It has been demonstrated that improvement in ensemble performance depends on either the diversity among or the performance of individual systems. A variety of diversity measures and ensemble methods have been proposed and studied. However, it remains a challenging problem to estimate the ensemble performance in terms of the performance of and the diversity among individual systems. The purpose of this paper is to study the general problem of estimating ensemble performance for various combination methods using the concept of a performance distribution pattern (PDP).

In particular, the paper establishes upper and lower bounds for majority voting ensemble performance with disagreement diversity measure Dis, weighted majority voting performance in terms of weighted average performance and weighted disagreement diversity, and plurality voting ensemble performance with entropy diversity measure D.

Bounds for these three cases are shown to be tight using the PDP for the input set.

As a consequence of the authors' previous results on diversity equivalence, the results of majority voting ensemble performance can be extended to several other diversity measures. Moreover, the paper showed in the case of majority voting ensemble performance that when the average of individual systems performance P is big enough, the ensemble performance P^m resulting from a maximum (information‐theoretic) entropy PDP is an increasing function with respect to the disagreement diversity Dis. Eight experiments using data sets from various application domains are conducted to demonstrate the complexity, richness, and diverseness of the problem in estimating the ensemble performance.

Under such circumstances, how to assign the highest priority for future products which will create the greatest value will be the key success factor for a product planning model. The purpose of this study is to construct an improved planning model for new products based on the theoretical structures of technology roadmaps and patent analysis.

This study takes the perspective of a product planning strategy, using technology roadmap developed by Institute of Manufacturing Technology of the University of Cambridge, combining with scenario planning and patent analysis. The main body of the proposed model is the technology roadmap of the product. Through patent analysis, the technology roadmap was integrated into the hierarchical execution of product planning to improve the disadvantages of the original technology roadmap and thereby clarify the content of the implemented procedure. With the planning of digital home products in a large household appliance manufacturer in China as a case study, the feasibility of the proposed model was verified.

The improved planning model for new products comprised five planning phases: market scenario planning, product feature analysis, technological development analysis, patent combination analysis, and resource allocation. A matrix corresponding to product planning was established. The case study is to find out the developing trends in next‐generation product features in six different scenarios of digital home for M, a home appliance manufacturer. There are five steps of the product planning model. The product planning model provides enterprises with integrated information from market demand, technology as well as patents. At the same time, it is easy to maintain and reproduce. The authors expect the model to make a contribution to practical product planning.

This model should become an essential prediction tool for enterprises developing new products and can assist in decision‐making and strategic implementation.

The purpose of this paper is to analyze the development of body fitness equipment in Taiwan from the viewpoint of innovation and the factor of success for innovation.

The research methods include a literature study and a case study. In addition, the innovation activity of an enterprise is based on the viewpoint of procedure (input‐process‐output). The innovation activity of an enterprise is separated into three phases: innovation motivation, innovation process, and innovation performance.

The enterprise's competitive advantage and efficiency can clearly be seen, and the reason for the enterprise's success can easily be identified through a structural analysis of the innovation process. The research results indicate four factors for the success of Johnson: mastering technology, good management, employment of diversified talents, and clear brand positioning.

The innovation research model provides a comprehensive summary of the innovation process, stressing innovation activity. The study of the factors of success does not establish quantified or non‐quantified innovation indicators.

The factor of success of innovation is not exactly the same for every company. Sorting and analyzing the individual cases can serve as a basis of reference and act as a guidepost for other companies in similar industries during their business development.

The analysis model of innovation activity can clearly explore the development process of the innovation success of an enterprise. Simultaneously, this research can serve as a role model for other companies when they innovate.

Unique product design is a highlight of sustainable branding. The purpose of this paper is to investigate whether product design affects customers’ psychological responses (i.e. cognitive and affective responses) to smartphones, and, in turn, affects their brand loyalty (i.e. attitudinal and behavioral brand loyalty), further advancing the knowledge of product design and brand management.

This work used survey data from 456 Taiwanese with experience using smartphone. Structural equation modeling was employed to test the proposed model and hypotheses.

The results indicate that the product design significantly affects both cognitive response and affective response, which, in turn, significantly affect both attitudinal brand loyalty and behavioral brand loyalty. The findings also suggest that the moderating effect of product involvement on the relationship between product design and affective response is statistically significant, although it does not positively and significantly moderate the link between product design and cognitive response.

This study has two main limitations. First, this study was conducted in the context of smartphones, thus potentially constraining the generalization of the results to other industries. Second, the data in this study were obtained from a cross-sectional design.

These findings can permit companies to generate more brand loyalty in their customers and guide their management of assets and marketing activities.

This paper presents new insights into the nature and importance of product design in brand value.

Environmental sustainability is one of the most pressing issues faced by the electric and electronics industry today. Industries are being challenged to incorporate environmental initiatives in their corporate strategies. Thus, this study aims to investigate the impact of stakeholder pressures (regulatory, internal and market) on green supply chain management and green corporate resources as well as their effects on the economic and environmental performance of Taiwan's electric and electronic industry.

A total of 194 valid questionnaires were collected out of the 1,000 questionnaires distributed to Taiwan's electric and electronic product manufacturers. A structural equation modeling, using Amos 22.0, was used to test the hypotheses.

The results of the analyses show that stakeholder pressure has a significant positive impact on corporate green resources and green supply chain management practices while green supply chain management practices have a significant and positive impact on organizational performance. Moreover, corporate green resources provide a mediation between organizational stakeholder pressure and green supply chain management.

The results may be of value and interest to supply chain managers and policymakers on the push factors for implementing green supply chain management practices and their consequences.

This paper shows the complementarity of stakeholder and resource-based theories in influencing organizational performance in the electric and electronic industry in the context of sustainable development. This also enhances the understanding of the antecedents and consequences of green supply chain management and provides robust findings on the relationship between environmental and economic performance.

The purpose of this paper is to find the key innovative principles for evaluating the long-term care (LTC) cloud system by exploring contradictory and complex points in its development.

The theory of inventive problem solving (TRIZ) and the decision-making trial and evaluation laboratory (DEMATEL) approaches are integrated to resolve complex contradictions in the system. The heuristic reasoning of TRIZ is applied to obtain innovation principles for an LTC cloud mining system. However, the importance and feasibility of these innovative principles require further assessment. In this study, DEMATEL is employed to clarify the complex relationships among the principles and evaluate their key influences.

This paper identifies six primary contradictions and derives 25 innovative principles for the resolution of these conflicts. Further analysis confirms three key innovative principles. First, the government should consider the overall planning of the cloud system platform, followed by the participation of other medical and LTC institutions. Second, the information capability of LTC institutions should be unified by recording the pathology data of care recipients to create an information exchange system. Third, LTC institutions should act in cooperation with medical institutions to provide professional medical capabilities.

The contributions of this paper are two-fold. First, this study provides an integrated methodology integrating the TRIZ and DEMATEL approaches to resolve LTC problems. Second, this research identifies the key innovative principles for developing an LTC cloud system in Taiwan.

Green sustainability has become a critical challenge for businesses to execute green supply chain management (GSCM). Most of the literature on GSCM emphasizes regulations as drivers and few pieces of research are conducted from an internal organizational culture view. This study aims to use the cultural perspective of market orientation (MO) and draws on both the natural resource-based view (NRBV) and dynamic capability view (DCV) to explore the relationships among green market orientation (GMO), GSCM capability and organizational performance.

A total of 1,000 survey questionnaires were distributed to the Taiwanese electronics industry and 207 valid questionnaires were collected. Data was analyzed using structural equation modeling.

The results show that GMOs have a significant positive impact on GSCM capability, environmental performance and economic performance. Moreover, GSCM capability is positively related to environmental and economic performance. The results also show that GMOs have a significant indirect influence on environmental performance and economic performance through GSCM capability.

The findings of this study suggest how Taiwan’s electrical and electronic manufacturers, while faced with pressure from competitors, customers and regulations (i.e. waste electrical and electronic equipment directive, Restriction of Hazardous Substances Directive and energy-using products directives), should efficiently and effectively implement GMO and enhance GSCM capability to improve organizational performance.

This study fills up the gap between MO and performance indistinct relationships. It has also integrated two perspectives, namely, NRBV and DCV, to explain GSCM capability as a mediator between GMO and organizational performance relationship and to examine the relationships among GMO, GSCM capability and organizational performance.

The reliability of chip‐on‐film (COF) packages is fundamentally dependent upon the quality of the eutectic Au‐Sn joint formed between the Au bumps on the integrated circuit (IC) device and the Sn‐plated Cu inner leads. Therefore, it is essential that an appropriate bonding temperature is achieved during the inner lead bonding (ILB) process. The purpose of this paper is to identify the optimal processing conditions which maximize the reliability of the Au‐Sn joints.

The paper commences by performing an experimental investigation to establish the temperature at three specific locations within the COF/ILB system in a typical gang‐bonding process. The relationship between the setting temperature of the bonding tool and the temperature of the tool surface is then calibrated using an off‐line experimental system. An ANSYS finite element (FE) model is then constructed to simulate the temperature distribution within the COF/ILB system under representative temperature conditions. The validity of the numerical model is confirmed by comparing the simulation results with the experimental temperature measurements. The FE model is then used in a 2³ factorial design process to evaluate the effect of the principal COF/ILB processing parameters, namely the contact area, the tool temperature and the stage temperature, on the temperature induced at the interface between the Au bumps on the IC chip and the Sn‐coated Cu leads on the polyimide film.

The results reveal that the interfacial bonding temperature is determined primarily by the stage temperature.

A regression analysis model is applied to the factorial design results to construct a COF/ILB design chart which enables the rapid identification of the stage and tool temperatures required to achieve the minimum feasible eutectic bonding temperature.