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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.

Purpose: In reality, financial decisions are made under conditions of asymmetric information that results in either favorable or adverse selection. As far as financial decisions affect growth of the firm, the latter must also be affected by either favorable or adverse selection. Therefore, the core objective of this chapter is to examine the determinants of each financial decision and the effects on growth of the firm under conditions of information asymmetry.

Design/Methodology/Approach: This chapter uses data for the non-financial firms listed in S&P 500. The data cover quarterly periods from 1989 to 2014. The statistical tests include linearity, fixed, and random effects and normality. The generalized method of moments estimation method is employed in order to examine the relative significance and contribution of each financial decision on growth of the firm, respectively. Standard and proposed proxies of information asymmetry are discussed.

Findings: The results conclude that there is a variation in the impact of financial variables on growth of the firm at high and low levels of information asymmetry especially regarding investment and financing decisions. A similar picture emerges in the cases of firm size and industry effects. In addition, corporate dividen d policy has a similar effect on firm growth across all asymmetric levels. These findings prove that information asymmetry plays a vital role in the relationship between corporate financial decisions and growth of the firm. Finally, the results contribute to the vast literature on the estimation of information asymmetry by demonstrating that the classical and standard proxies for information asymmetry are not consistent in terms of the ability to differentiate between favorable or adverse selection (which corresponds to low and high level of information asymmetry).

Originality/Value: This chapter contributes to the related literature in two ways. First, this chapter offers updated empirical evidence on the way that financing, investment, and dividends decisions are made under conditions of favorable and adverse selection. Other related studies deal with each decision separately. Second, the study offers new proxies for measuring information asymmetry in order to reach robust estimates of the effects of financial decisions on growth of the firm under conditions of agency problems.

This study examines whether US effective tax rates on foreign income of US multinationals (MNCs) vary according to the favorability of US macroeconomic conditions relative to those of non-US countries. We use the pre-Tax Cuts and Jobs Act of 2017 regime as our setting and present evidence that US effective tax rates on foreign earnings are higher (lower) in periods when macroeconomic conditions in the US are favorable (unfavorable) relative to those elsewhere in the world. These results imply that firms seek to maximize after-tax returns when making asset allocation decisions, even when faced with US repatriation tax costs. We provide further evidence indicating that our primary results vary predictably according to certain firm characteristics, namely the ability to acquire funds for investment through less expensive means than repatriation of foreign profits, high intangible asset intensity, and tax aggressiveness. Finally, we show that economic uncertainty in the US counters the positive effects of favorable US macroeconomic conditions on US effective tax rates on foreign earnings. Our findings have implications for the policy debate around the US taxation of foreign earnings and provide a (partial) explanation for the observed lower-than-expected levels of repatriation activity following the implementation of the Tax Cuts and Jobs Act of 2017.

This paper addresses social interatcion and the formation of value beliefs in markets. It empirically examines value construction by analyzing rebidding behavior in online auctions, wherein individuals reassess the maximum price they would pay for a given product. Statistical analyses of more than 10,000 auctions containing more than 55,000 individual bids on the auction website eBay suggest that rebidding is positively associated with a lack of auction-internal price information and bidder inexperience. Analyses also suggest that engaging in rebidding is positively associated with an individual winning an auction. This work, therefore, helps to provide a deeper understanding about valuation, price formation, and the organization of markets. This work contributes to domains of research related to the construction of value and the emergence, evaluation, and legitimization of new products, services, and ideas.