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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.

While it is known that digital transformation facilitates data flow in supply chains, its importance on green supply chain management (GSCM) has not been investigated concisely. This paper aims to expand the theory of digital transformation in GSCM by investigating the interconnections between these concepts and providing an integrative view of a smart green supply chain management (Smart GSCM).

This adopts a configurational perspective on digital transformation and supply chain management (SCM) to investigate the different dimensions of Smart GSCM and their contribution to green performance. Therefore, this paper analyzes data from 473 manufacturing companies using regression techniques.

The results show how smart supply chain contributes to green performance through managing green relationships (external GSCM activities) and establishing green operations (internal GSCM activities). Furthermore, this paper finds partial mediating effects for external and internal GSCM activities on green performance. These findings show that smart supply chain (i.e. digital transformation strategy and front-end technologies, supported by several back-end technologies) is directly associated with higher levels of GSCM. It is specifically associated with one of the internal dimensions of green operations, namely, green purchasing activities. Hence, the findings suggest that digital transformation alone is insufficient to achieve green performance, needing a GSCM configuration to mediate this effect.

This study calls attention to how managers should integrate these at least three different perspectives of SCM: digital transformation, external relationships and internal operations to increase green performance.

As the main contribution, this study provides a configurational and holistic understanding of the different dimensions and mechanisms in Smart GSCM.

Studies suggest deep brain stimulation (DBS) as a treatment modality for the refractory obsessive-compulsive disorder (OCD). It is unclear where to place the DBS. Various sites are proposed for placement with the ventral capsule/ventral striatum (VC/VS) among the most studied. Herein, we aim to summarize both quantitative Yale-Brown Obsessive-Compulsive Scale (YBOCS) data and qualitative descriptions of the participants' symptoms when given. A literature search conducted via PubMed yielded 32 articles. We sought to apply a standard based on the utilization of YBOCS. This yielded 153 distinct patients. The outcome measure we focused on in this review is the latest YBOCS score reported for each patient/cohort in comparison to the location of the DBS. A total of 32 articles were found in the search results. In total, 153 distinct patients' results were reported in these studies. Across this collection of papers, a total of 9 anatomic structures were targeted. The majority of studies showed a better response at the last time point as compared to the first time point. Most patients had DBS at nucleus accumbens followed by VC/VS and the least patients had DBS at the bilateral superolateral branch of the median forebrain bundle and the bilateral basolateral amygdala. The average YBOCS improvement did not seem to directly correlate with the percentile of patients responding to the intervention.

Well-controlled, randomized studies with larger sample sizes with close follow up are needed to provide a more accurate determination for placement of DBS for OCD.

In 2007, the authors conducted a case study of 13 teachers across seven elementary schools. We learned that, due to pressures of the No Child Left Behind Act (NCLB, 2002) and state mandated testing, these schools were akin to reading academies—focused chiefly on the teaching of reading skills. They promised to share their results with local administrators and teachers, initiating the reconsideration of elementary social studies. To this end, they revisited school sites, revealed their findings, and offered to “fit into” ongoing discussions of curricular change. They attempted to engage teachers in courageous conversations, or honest, frank appraisal of current conditions. Eventually, they talked with approximately 100 K-6 teachers, principals, and district administrators. Framing their inquiry in Giddens (1984) theory of structuration, they present their efforts to build collaborative relationships in three cases of narrative inquiry. They follow it with dilemmas and insights for the field organized into five considerations: courageous conversation, curricular control, integration, social studies advocacy, and courting schools.

One of the central requirements of research is that the knowledge acquired should not only be academically rigorous, but also socially useful. If an article fails to address practical relevance, the audience will question its value and respond with “so what?”. Due to recent criticism regarding the practical relevance of innovation research, the purpose of this paper is to examine whether a similar “ivory divide” prevails in research on innovation in family businesses. More specifically, this paper investigates to what extent and at what depth researchers generate practical implications for innovation in family businesses. Furthermore, different strategies to bridge the “ivory divide” are discussed.

This literature review systematically analyses the findings of 50 journal articles focusing on innovation in family businesses published between 2004 and 2015. Based on this, the articles are classified according to their degree of practical relevance.

Although the findings unanimously show the relevance of innovation for strengthening business’s performance, only a minority of articles offer in-depth implications for practitioners in terms of practical guidance for action and application-oriented recommendations. A number of reasons for the development of this “ivory divide” are discussed and suggestions for how the connection between research and practice could be strengthened are provided.

This paper attempts to provide an impulse toward more practically oriented family business research in order to increase its interestingness to academics and its value to practitioners.

To decrease wear and friction, zinc dialkyldithiophosphate (ZDDP) has been used in engine oil for several decades, but the mechanism of the tribofilm formation is still unclear. The purpose of this study is to characterize the chemical details of the tribofilm by using high-resolution approaching.

An ISO VG 100 mineral oil mixed with ZDDP was used in sliding tests on cylindrical roller bearings. Tribofilm formation was observed after 2 h of the sliding test. X-ray photoelectron spectroscopy (XPS) and atom probe tomography (APT) were used for chemical analysis of the tribofilm.

The results show that the ZDDP tribofilm consists of the common ZDDP elements along with iron oxides. A considerable amount of zinc and a small amount of sulfur were observed. In particular, an oxide interlayer with sulfur enrichment was revealed by APT between the tribofilm and the steel substrate. The depth profile of the chemical composition was obtained, and a tribofilm of approximately 40 nm thickness was identified by XPS.

A sulfur enrichment at the interface is observed by APT, which is beneath an oxygen enrichment. The clear evidence of the S interlayer confirms the hard and soft acids and bases principle.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-01-2020-0035/

This paper examines the innovation behavior of family-owned firms versus non-family-owned firms. The role of internal family governance and the influence of external stimuli (competition) on innovation are also considered.

The data of 20,995 family and non-family firms across 38 countries are derived from the World Bank Enterprise Survey during the period 2019–2020. Probit models are used to examine the impact of family ownership, family governance, and competition on innovation outcomes.

Family firms are more likely to make R&D investments, acquire external knowledge, engage in product innovation (including innovations that are new to the market) and process innovation, relative to non-family firms. However, a high propensity of family member involvement in top management positions can reduce innovation. Competition has a negative impact on innovation outcomes for both family and non-family firms, but it has a positive moderating effect on the innovation activities of family firms where a higher level of family member involvement in management is present.

This paper provides novel insights into family firm innovation dynamics by identifying family firms as more innovative than non-family firms for all types of indicators, debunking the idea that family firms are conservative, reluctant to change, and averse to the risks in innovation activities. However, too much family involvement in decision making may stifle some innovation activities in family firms, except in cases where the operating environment is highly competitive; this provides new insights into the ownership-management dynamic of family firms.

Family firms (FF) reveal a considerable heterogeneity in their innovation behavior. Due to the successful long-term preservation of their innovation capacity via special resources and routines, multi-generational FF are of special interest in terms of learning from good practices. Against this background, the purpose of this paper is to ascertain principles for successful innovation behavior in long-term successful FF and to contribute to bridging the theory-practice gap.

Results are generated by analyzing innovation and innovation processes in five cases of long-term successful FF. On the basis of these good practice cases, the “rules of the game” of innovating are re-constructed using fine and system analyses based on narrative interviews with the FF CEOs.

Intense reflection on the innovation characteristics of the five good practice cases along with a critical examination of the literature on innovation in FF were used to derive practical suggestions for FF in the form of 11 principles for FF taking a proactive interest in innovation.

The 11 generated principles of successfully innovative FF were validated by FF CEOs who confirmed the practical relevance of these principles as valuable guidelines for successful innovation. Owners and managers may reflect on these principles against the background of the innovation behavior of their firms and adapt them to their contextual conditions.

These principles serve as tangible suggestions for developing adequate innovation management strategies for individual FF. Furthermore, two FF CEOs were invited to comment on the viability of principles based on their comprehensive practical experience.

This paper aims to present a model that maps the relationship between factors and process stages of the knowledge transfer (KT) between new product development (NPD) teams.

The model was constructed through a quantitative evaluation with scholars and practitioners of the NPD field. To evaluate the model and its usefulness, a practical application was carried out in two large Brazilian companies.

A relationship model between 16 main influence factors and 11 stages of the KT process was obtained. It could be seen through the practical applications that the model helps companies to identify and prioritize improvement opportunities in the KT between NPD teams.

Prior studies had been concerned with the analysis of KT factors, but considering KT as an isolated act. So, this work has advanced in the deployment of the KT stages and the relationship of those with different influence factors.

This paper brings an important practical contribution, once several academic works have been concerned with to demonstrate relationships among factors, but few have shown how these results could help to solve practical issues observed in companies.

Results presented in this paper enable the extension of comprehension about the KT phenomena in the NPD process. Furthermore, this paper shows how the proposed model can be used as a decision tool to guide a diagnosis and detect improvement opportunities in KT between NPD teams.

This study aims to investigate the motivations for the adoption of Industry 4.0 technologies among manufacturing firms in developing economies. Specifically, the effects of relative advantage of the technologies, competitive pressure, and government support on the adoption are explored. Moreover, the mediating role of top management support between environmental factors (government support and competitive pressure) and the adoption of Industry 4.0 technologies is examined.

A research model is developed based on the technology-organization-environment (TOE) framework strengthened by institutional theory. Structural equation modeling (SEM) approach is employed to evaluate the model using data obtained from 215 manufacturing firms through a cross-industry survey. Additionally, a post-hoc analysis is conducted using cluster analysis and ANOVA.

The results show that competitive pressure and government support significantly promote top management support, which in turn contributes to the adoption of Industry 4.0 technologies. Relative advantage of the technologies is not significantly related to the adoption.

This study does not explore the relationship between technology type and the specific needs of manufacturing firms. Future researchers can conduct a more comprehensive analysis by examining how different technology types align with the unique needs of individual companies.

The findings of this study have implications for both policymakers and managers. Policymakers can leverage these insights to understand the underlying motivations behind manufacturing firms' adoption of Industry 4.0 technologies and develop promoting policies. In turn, managers should keep an eye on government policies and utilize government support to facilitate technology adoption.

This study uncovers the underlying motivations—government support and competitive pressure—for the adoption of Industry 4.0 technologies among manufacturing firms in developing economies. Meanwhile, it complements previous research by showing the mediating role of top management support between environmental factors (government support and competitive pressure) and the adoption of Industry 4.0 technologies.