The Impact of Channel Leadership Behavior on Intrachannel Conflict

Schul, Patrick L.; Pride, William M.; Little, Taylor L.

doi:10.2307/1251194

Cited by 77 publications

(57 citation statements)

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“…However, in the literature, the significance of the canonical correlation is believed to be insufficient in making valid conclusions, as there are contentious arguments on using the significance of canonical correlation to make conclusion as well as to determine the number of canonical variates or functions to retain for the purpose of making inference. The reason is that significance test tells us absolutely nothing about the magnitude of the relationship (i.e., it does not reveal the amount of variance shared by the two sets of variables), and its statistical significance is heavily influenced by sample size; as it is possible for the test to be statistically significant with large sample sizes (see [41,44,45]). On this note, the use of redundancy coefficient was suggested as it reveals the amount of variance shared by the two sets of variables.…”

Section: Canonical Correlation Analysismentioning

confidence: 99%

Analysis of Soil-Vegetation Interrelationships in a South-Southern Secondary Forest of Nigeria

Eni

Iwara

Offiong

2012

International Journal of Forestry Research

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Soil-vegetation interrelationships in a secondary forest of South-Southern Nigeria were studied using principal component analysis (PCA) and canonical correlation analysis (CCA). The grid system of vegetation sampling was employed to randomly collect vegetation and soil data from fifteen quadrats of 10 m × 10 m. PCA result showed that exchangeable sodium, organic matter, cation exchange capacity, exchangeable calcium, and sand content were the major soil properties sustaining the regenerative capacity and luxuriant characteristics of the secondary forest, while tree size and tree density constituted the main vegetation parameters protecting and enriching the soil for its continuous support to the vegetation after decades of anthropogenic disturbance (food crop cultivation and illegal logging activities) before its acquisition and subsequent preservation by the Cross River State government in 2003. In addition, canonical correlation analysis showed result similar to PCA, as it indicated a pattern of relationship between soil and vegetation. The only retained canonical variate revealed a positive interrelationship between organic matter and tree size as well as an inverse relationship between organic matter and tree density. These extracted soil and vegetation variables are indeed significantly important in explaining soil-vegetation interrelationships in the highly regenerative secondary forest.

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Section: Canonical Correlation Analysismentioning

confidence: 99%

Analysis of Soil-Vegetation Interrelationships in a South-Southern Secondary Forest of Nigeria

Eni

Iwara

Offiong

2012

International Journal of Forestry Research

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“…A participative leadership style, which has been defined as "joint decision-making or at least shared influence in decision-making by a superior and his or her employees" (Somech, 2003(Somech, , p. 1003, likely benefits the company and its employees in terms of better quality of decisions, increased employee motivation, satisfaction and commitment (Somech, 2003). Participative leaders discuss relevant issues with employees, ask for their opinions and take these into account when making decisions (Schul et al, 1983). In case these discussions take place 'en groupe' they may also generate trickle-round effects as employees will get to know each other's opinions.…”

Section: Trickle Effects: Some Insights From Csr and Organization Stumentioning

confidence: 99%

Trickle Effects of Cross-Sector Social Partnerships

2010

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Cross-sector social partnerships are often studied from a macro and meso perspective, also in an attempt to assess effectiveness and societal impact. This paper pays specific attention to the micro perspective, i.e. individual interactions between and within organizations related to partnerships that address the 'social good'. By focusing on the potential effects and mechanisms at the level of individuals and the organization(s) with which they interact, it aims to help fill a gap in research on partnerships, including more insight into the process of interaction. We conceptually explore microlevel interactions, and how partnership effects may 'trickle down' (e.g. from management to employees), or 'trickle up' (from employees to management), or 'trickle round' (e.g. between employees). Based on literature from various disciplines, we discuss how more generic theories on social exchange and contagion, social learning and attraction-selection-attrition can help shed light on micro-level interactions in a partnership, considering in particular transmission mechanisms via employees, top and middle management, and customers. In this way, partnerships can have wider benefits, as individuals have multiple roles and effects at the micro level can spread to the meso and macro levels as well. Implications for research and practice are outlined.

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“…However, in the literature, the significance of the canonical correlation is believed to be insignificant in making valid conclusions, as there are contentious arguments on using the significance of canonical correlation to make conclusion as well as determine the number of canonical variates or functions to retain for the purpose of making inference. The reason being that significance test tells us absolutely nothing about the magnitude of the relationship (that is, it does not reveal the amount of variance shared by the two sets of variables), and its statistical significance is heavily influenced by sample size; as it is possible for the test to be statistically significant with large sample sizes (see Sherry and Henson, 2005;Schul et al, 1983;Lambert and Durand, 1975;Green, 1978;Laessig and Duckett, 1979). On this note, the use of redundancy coefficient and cross loading was suggested as they reveal the amount of variance shared by the two sets of variables (Sherry and Henson, 2005;Schul et al, 1983;Henson and Smith, 2000;Lambert and Durand, 1975).…”

Section: Canonical Correlation Analysismentioning

confidence: 99%

Multivariate Analysis of Soil-Vegetation Interrelationships in a South-Southern Secondary Forest of Nigeria

Iwara¹,

Ogundele²,

Eli³

et al. 2011

IJB

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Multivariate statistical techniques were employed to study soil-vegetation interrelationships in a secondary forest of South-Southern Nigeria. The grid system of vegetation sampling was used to randomly collect vegetation and soil data from fifteen quadrats of 10m x 10m. The result of principal components analysis identified seven basic sets of soil-vegetation variables that enhanced the interrelationships. Canonical correlation result indicated a positive association between organic matter and tree size, while the linear association between organic matter and tree density revealed an inverse relationship. The result of redundancy coefficient indicated that 18 percent of the variance in vegetation characteristics was accounted for by the variability in soil properties whereas, 81 percent of the variance in soil properties was accounted for by the variability in vegetation characteristics. The regression analyses on the other hand indicated that exchangeable sodium positively influenced tree species composition and richness; and that tree size as well as tree density exerted substantial influence on the contents of organic matter and total nitrogen of the soil. However, drawing inference from results of canonical correlation analysis and those of multiple regression analysis, it was concluded that soil and vegetation components of the secondary forest vegetation were mutually dependent and therefore exerted joint influences on each another.

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The Impact of Channel Leadership Behavior on Intrachannel Conflict

Cited by 77 publications

References 0 publications

Analysis of Soil-Vegetation Interrelationships in a South-Southern Secondary Forest of Nigeria

Analysis of Soil-Vegetation Interrelationships in a South-Southern Secondary Forest of Nigeria

Trickle Effects of Cross-Sector Social Partnerships

Multivariate Analysis of Soil-Vegetation Interrelationships in a South-Southern Secondary Forest of Nigeria

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