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School counselors are committed to serving students' social-emotional, postsecondary, and academic needs while they navigate primary and secondary school (American School Counselor Association, 2019). Much has been said about the ways in which school counselors can impact postsecondary outcomes and social emotional health. It is important that we also address the ways school counselors can impact positive academic outcomes as it is intertwined in postsecondary options and success. For Black males, academic success has traditionally been met with systemic barriers (i.e., school-to-prison pipeline, lower graduation rates, lower incomes, higher unemployment rates, and lower college going rates (National Center for Edcuation Statisitics, 2019a, 2019b, 2020a, 2020b) and low expectations. School counselors are charged to be leaders and change agents for social justice and equity in our schools by the American School Counselor Association (ASCA, 2019) and can impact systemic change. This chapter will explore ways in which school counselors can impact positive academic outcomes for Black males. School counselors as change agents and advocates are positioned to make a real impact for Black male academic success. The authors will also provide some recommendations and best practices for elementary, middle, and high school counselors as they work with students, teachers, and families from an anti-deficit model as outlined by Harper (2012).

The purpose of this study is to examine the effects of banking innovations (INNs) on customer experience (EXP), satisfaction (SAT) and loyalty (LOY).

The author evaluated the data using a structural equation method-artificial neural network (SEM-ANN) method. The author’s results show the presence of relationship between INN, EXP, SAT and LOY. In this study, the node layers of ANNs add an input layer, hidden layers and an output layer. Each “node” acts as an artificial neuron that communicates with others. The ANN model takes the variables from the SEM analysis as input neurons.

The author observed the significant effects between INN, EXP, SAT and LOY using the normalised importance generated by the multilayer perceptron used in the feed-forward back propagation of the ANN methodology. In this study, the ANN model can predict LOY through service innovation, with a forecast accuracy of 77.6%.

By applying neural network modelling, this research helps us understand how service innovation affects customer behaviour. For the first time, the author examined service innovations' direct and indirect impact on loyalty through EXP and SAT. The author made a significant conceptual contribution by using a non-compensatory model of ANNs to circumvent the limitations of linear models.