Principles of Kabir Wealth Curve

The authors developed a wealth curve (bell curve) that can predict a group of individual’s wealth based on the crossover interaction effect of the average intelligence quotient (one's ability to perform, comprehend and learn) and emotional awareness (emotional ability to recognize and make sense of emotions). To move towards the right on the X-axis of the Kabir wealth curve (e.g. accumulate more wealth), individuals have to improve emotional awareness and choose a professional career path that lands higher income. Similarly, those facing social injustice can accumulate more wealth by improving emotional awareness, which will help them navigate challenging environments.

Principles of Kabir Wealth Curve

The authors developed a wealth curve that can predict a group of individual’s wealth based on the crossover interaction effect of the average intelligence quotient (one's ability to perform, comprehend and learn) and emotional intelligence (emotional awareness and emotional ability to express and handle interpersonal relationships judiciously and empathically).

Pengaruh Strategi Diversifikasi terhadap Kinerja Perusahaan dengan Moderasi Efisiensi

Studi ini menguji pengaruh moderasi efisiensi atas hubungan diversifikasi dan kinerja perusahaan-perusahaan non keuangan yang tercatat dalam Bursa Efek Indonesia dari tahun 2013 hingga 2017 di Indonesia. Tujuan dari penelitian ini adalah untuk memperoleh bukti empiris atas efek moderasi efisiensi dalam hubungan strategi diversifikasi dan kinerja perusahaan terutama dengan banyaknya hasil penelitian yang berbeda terkait pengaruh strategi diversifikasi, juga belum pernah digunakannya efisiensi sebagai variabel moderasi di Indonesia. Metode penelitian menggunakan regresi linear berganda dengan diversifikasi terdiri atas diversifikasi related dan diversifikasi unrelated, serta pengukuran efisiensi menggunakan Data Envelopment Analysis.Hasil penelitian menunjukkan bahwa strategi diversifikasi related maupun unrelated tidak mempengaruhi kinerja perusahaan secara signifikan. Di sisi lain, efisiensi tidak memoderasi hubungan antara strategi diversifikasi terhadap kinerja perusahaan. Namun, temuan dalam penelitian ini mengindikasikan adanya crossover interaction (Baron dan Kenny, 1986) antara variabel efisiensi dan diversifikasi. Hal ini dibuktikan dengan hubungan yang tidak signifikan antara diversifikasi dan kinerja tetapi, adanya hubungan signifikan antara efisiensi dan kinerja, disertai variabel interaksi yang berhubungan signifikan terhadap kinerja. Berdasarkan temuan tersebut, penelitian selanjutnya sebaiknya meneliti pengaruh moderasi diversifikasi terhadap hubungan antara efisiensi dan kinerja. Hasil penelitian juga diharapkan dapat berkontribusi bagi teori terkait strategi diversifikasi serta digunakan dalam pengambilan keputusan perusahaan dan investor. Limitasi penelitian ini terdiri dari kurangnya literatur yang membahas strategi diversifikasi sebagai variabel moderasi serta pengukuran diversifikasi menggunakan variabel biner.

Revisiting the remember–know task: Replications of Gardiner and Java (1990)

One of the most evidential behavioral results for two memory processes comes from Gardiner and Java (Memory & Cognition, 18, 23–30 1990). Participants provided more “remember” than “know” responses for old words but more know than remember responses for old nonwords. Moreover, there was no effect of word/nonword status for new items. The combination of a crossover interaction for old items with an invariance for new items provides strong evidence for two distinct processes while ruling out criteria or bias explanations. Here, we report a modern replication of this study. In three experiments, (Experiments 1, 2, and 4) with larger numbers of items and participants, we were unable to replicate the crossover. Instead, our data are more consistent with a single-process account. In a fourth experiment (Experiment 3), we were able to replicate Gardiner and Java’s baseline results with a sure–unsure paradigm supporting a single-process explanation. It seems that Gardiner and Java’s remarkable crossover result is not replicable.

Quantification of G × E interaction for feed barley genotypes by parametric and non-parametric measures

Genotype × environment (G × E) interaction of 28 feed barley genotypes in 12 environments was quantified by the parametric and non-parametric measures. Significant differences among G × E, environments and genotypes were observed as 42.3% of the total variance accounted for interaction effect. Interaction Principal Component Axes (IPCA1, IPCA2, IPCA3 and IPCA4) contributed 32.2, 20.3, 15.6 and 10.5% of the interaction sum of squares. Crossover interaction among genotypes and environments was confirmed by positive and negative values IPCAs. RD2786 followed by RD2876 had large negative IPCA1 score along with positive IPCA3 and IPCA4 values. Desirable genotypes were arranged in ascending order by D values as G23 (1.32) < G2 (1.42) < G20 (1.47) < G21 (1.63). The least AMMI Stability Value (ASV) score was observed for KB1367 followed by JB290 for yield performance. Smallest Pi was satisfied by BH 946, HUB 113 and RD2552. Environmental variance and CV identified non-stable performance of RD2874 and NDB1578 along with RD2876. Wricke’s ecovalence showed UPB1040 and UPB1042 as promising genotypes. Nonparametric measures (Si1, Si2 , Si3, Si4) pointed towards UPB1040 and PL881 for stable and unstable genotypes, however, Si5, Si6 selected UPB1040 and UPB1042 as of stable yield. More or less similar results were observed by parametric as well as non-parametric measures.

Revisiting the Remember-Know Task: Replications of Gardiner and Java (1990)

One of the most evidential behavioral results for two memory processes comes from Gardiner and Java (1990). Participants provided more remember than know responses for old words but more know than remember responses for old nonwords. Moreover, there was no effect of word/nonword status for new items. The combination of a crossover interaction for old items with an invariance for new items provides strong evidence for two distinct processes while ruling out criteria or bias explanations. Here, we report a modern replication of this study. In three experiments (Experiments 1, 2, and 4) with larger numbers of items and participants, we were unable to replicate the crossover. Instead, our data are more consistent with a single-process account. In a fourth experiment (Experiment 3), we were able to replicate Gardiner and Java’s baseline results with a sure-unsure paradigm supporting a single-process explanation. It seems that Gardiner and Java’s remarkable crossover result is not replicable.