Search results

This teaching case aims to encourage reflection on the formulation of the strategic repositioning of an automotive dealership.

Built on the teaching case method, it portrays the situation of the Premium Motors automotive dealership in the face of a strategic repositioning. Management and the board discuss ways to minimize the impact of the coronavirus disease 2019 (COVID-19) pandemic on sales figures. The situation presents the possibility of entering a new product segment.

How to make consumers correctly understand the new positioning? The case is structured to enable reflection and teaching of marketing strategies, with each student having the possibility of putting themselves in the role of company managers. The environment and trajectory are also portrayed, broadening the perception of the studied company and providing devices for solving the emerging problems of the case.

The case becomes a tool to promote knowledge, from the implementation to the management of strategic repositioning. Thus, the teaching notes offer directions on how professors can use the teaching case with their undergraduate and graduate students in disciplines related to strategy and marketing.

The purpose is to investigate whether Brazilian e-commerce nonusers all have the same reasons not to purchase online or whether different behavior patterns might lead them to cluster in different groups.

This study carried out cluster analyses on a large sample (N = 9,065) from a nationwide survey on the use of information and communication technology in Brazil.

Three clusters of e-commerce nonusers were identified: the first cluster is quite reluctant; the second is characterized by disbelief in e-commerce; and the last cluster includes members who must see a product to believe it. Overall, nonusers have different reasons not to shop online, but they also share some similarities in this regard. Furthermore, socioeconomic factors do not seem to affect their behavior. The findings suggest that merchants’ failure to attract customers’ attention and tangibility are the major barriers to e-commerce use.

Even though nonusers have different reasons not to shop online, the key pattern that emerges is the value of tangibility for these individuals, which is a barrier present in all three clusters. This suggests that current marketing strategies and advertisements are ineffective to reach these consumers. Vendors should therefore try different approaches.

The findings contribute to the information systems (IS) literature by bringing a new perspective to the understanding of e-commerce rejection in addition to having managerial implications that involve strategies to attract potential users based on their specificities.

This research aims to identify the optimal configuration of investment which leads firms to their best competitive positions, considering the degree of concentration in the market.

The methodology was quantitative and based on secondary data with samples of 124, 106 and 90 firms from competitive environment classified as perfect competition, monopolistic competition and oligopoly, respectively. Proposed models' parameters were estimated by means of genetic algorithms.

Adjustments on firm's investment are contingent on the degree of competition they face. Results are in line with existing academic research affirmation that the purpose of investments is to create and exploit opportunities for positive economic rents and that investments allow firms to protect from rivals' competitive actions and reinforce the need for investment decision makers to consider the environment in which the firm is competing, when defining the amount of investment that must be done to achieve and maintain a favorable competitive advantage position.

This research brings two main original contributions. The first one is the identification of the optimal amount of capital and R&D investments which leads firms to their best competitive positions, contingent to the degree of concentration of the competitive environment in which they operate, and the size of the firm. The second one is related to the use of genetic algorithms to estimate optimization models that considers the three competitive environments studied (perfect competition, monopolistic competition and oligopoly) and the investment variables in the linear and quadratic forms.