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In this empirical study, export strategies of 131 California exporting manufacturers were examined. A factor analysis of fifty variables yielded five factors which were analysed subsequently through multiple discriminant analysis. Two of the five factors, strategic planning and export strategies, were found to be meaningful in discriminating between small and large exporters. Implications for managers are offered.

When Burroughs acquired Sperry a few years ago, market analysts were highly skeptical about the success of the merger. Two organizations with distinctly different cultures, organizational practices, and incompatible product lines had to be merged into a cohesive unit.

Many recent books on management have focused on the importance of leadership in the success of an organization. One hears more and more about the key role a CEO can play in the implementation of certain strategies.

The last several years have seen a rash of takeovers—hostile and friendly—affecting the basic structure of U.S. corporations. Many of these takeovers have been spearheaded by a small group of raiders who, with the help of ingenious financing techniques and willing sources of funds, have threatened the long‐term existence of even the largest corporations in this country.

To design, control and evaluate photovoltaic (PV) systems, an accurate model is required. Accuracy of PV models depends on model parameters. This study aims to use a new algorithm called improved social spider algorithm (ISSA) to detect model parameters.

To improve performance of social spider algorithm (SSA), an elimination period is added. In addition, at the beginning of each period, a certain number of the worst solutions are replaced by new solutions in the search space. This allows the particles to find new paths to get the best solution.

In this paper, ISSA is used to estimate parameters of single-diode and double-diode models. In addition, effect of irradiation and temperature on I–V curves of PV modules is studied. For this purpose, two different modules called multi-crystalline (KC200GT) module and polycrystalline (SW255) are used. It should be noted that to challenge the performance of the proposed algorithm, it has been used to identify the parameters of a type of widely used module of fuel cell called proton exchange membrane fuel cell. Finally, comparing and analyzing of ISSA results with other similar methods shows the superiority of the presented method.

Changes in the spider’s movement process in the SSA toward the desired response have improved the algorithm’s performance. Higher accuracy and convergence rate, skipping local minimums, global search ability and search in a limited space can be mentioned as some advantages of this modified method compared to classic SSA.

Institutional changes, in a historical context, through simultaneous evolutionary and metamorphic processes either deform or reform long-enduring institutions. The chapter delves into the Persian history from the early days of the reign of Nāṣer al-Dīn Shāh-e Qājār in 1848 to the recent years and traces Persian institutions' historical transformations, which culminated to the Persian women entrepreneurship. Thus, the chapter first sets the historical context in each period and then sheds light on the pivotal issues of each period's women. The undergirding base of the discussions is the assumption of the change in institutions as natural metamorphosis in the animate. Finally, the discussions contribute to the conceptualization of the Institutional Triangulation and in the case of Persia, a cultural-driven triangulation, which has paved the way to the formation of a stupendously hegemonic patriarchal and masculine sociopolitical economy in Persia, that has historically affected women's institutionalization, subjugation, subordination, marginalization, socialization, emancipation, and most recently Islamization phases.

The study aims to predict a low-velocity impact on a plate reinforced with carbon nanotubes (CNTs) using machine learning models.

The first-order shear deformation plate theory (FSDT) is used to express the plate displacements filed. The Hertz nonlinear contact law is used to predict the contact between impactor and plate. Using the energy method and Hamilton’s principle, the motion equations are extracted. The six main parameters considered as inputs to machine learning models are CNTs percentage, impactor radius, plate thickness, plate length and width, CNTs distribution profile and impactor initial velocity. These input parameters are used to predict two impact targets including contact force and contact time.

As the values of the targets are continuous, the machine learning task is considered a regression problem. Therefore, this study uses different regression models to predict the targets. These regression models include linear regression, stochastic gradient descent regressor, Bayesian regression, partial least squares regression, Gaussian process regression, multilayer perceptron regressor, support vector regression and decision tree regression. To validate the effectiveness of the regression models, experiments are designed based on different evaluation metrics. The results of the experiments demonstrate that the machine learning models achieve promising performance in predicting the contact force and contact time based on the input parameters.

Due to the volume of high numerical calculations of impact mechanics to reach the response, the targets of the impact problem are predicted using a variety of machine learning methods.

The purpose of this paper is to explore the reasons for and consequences of leaders moving from other sectors to the public arena and provide guidelines for successful transitions to the public sector.

The paper relies on a conceptual analysis of leadership theory, critical reasoning and several examples to explore the phenomenon the authors call Leadership Leap (LL).

The paper explores the context, antecedents, causes and consequences of LL. The leaders’ self-confidence, ego and hubris are often considered to be the reason for leaping to an unfamiliar sector; however, the causes are much more complex. The authors suggest that in addition to the leaders’ personal characteristics, LL is encouraged by a culture of celebrity, excessive focus on the leaders and a longing for heroes. Ignoring or disregarding the context and overestimating the need for revolutionary change further exacerbate LL. The authors consider conditions for success and suggest areas for future research.

We are increasingly witnessing leaders who are successful and considered experts in one sector transition into the public sector. Although some are successful, others face obstacles and fail to live up to expectations. The unique characteristics of public leadership, specifically the collective nature of the sector and the crucial role of context and systems, provide a particular challenge for LL in the sector.

In this research, the free vibration sensitivity analysis of cracked fiber metal laminated (FML) beams is investigated numerically and experimentally. The effects of single and double cracks on the frequency of the cantilever beams are simulated using the finite element method (FEM) and compared to the experimental results.

In FEM analysis, the crack defect is simulated by the contour integral technique without considering the crack growth. The specimens are fabricated with an aluminum sheet, woven carbon fiber and epoxy resin. The FML specimens are constructed by bonding five layers as [carbon fiber-epoxy/Al/carbon fiber-epoxy/Al/carbon fiber-epoxy]. First, the location and length of cracks are considered input factors for the frequency sensitivity analysis. Then, the design of the experiment is produced in the cases of single and double cracks to compute the frequency of the beams in the first and second modes using the FEM. The mechanical shaker is used to determine the natural frequency of the specimens. In addition, the predicted response values of the frequency for the beam are used to compare with the experimental results.

Consequently, the results of the sensitivity analysis demonstrate that the location and length of the crack have significant effects on the modes.

Effective interaction diagrams are introduced to investigate crack detection for input factors, including the location and length of cracks in the cases of single and double cracks.

Even the smartest organizations believe that “good enough is never good enough.” Highly intelligent people may be able to do important things individually; still, it is their accumulated brainpower that allows them to do great things. Collective intelligence means when a group of people do things that seem intelligent. On the other hand, when intelligent people are gathered or hired in an organization, they tend toward collective stupidity and slow-wittedness. Therefore, the purpose of the present study is to develop a model of the factors affecting and affected by collective stupidity.

This study was conducted using a mixed-method approach and in two phases: qualitative and quantitative. First, in the qualitative phase and in order to achieve new findings, semi-structured interviews with experts from 12 knowledge-based companies were used to design a conceptual model and formulate the hypotheses. At the end of the qualitative phase, the conceptual model and relationships between variables were drawn. Then, in the quantitative phase, by running structural equation modeling, the antecedents and consequences of collective stupidity derived from the qualitative phase findings were analyzed and the research hypotheses were tested in 110 industrial knowledge-based companies.

The results of the qualitative phase revealed that individual, group and organizational factors were the antecedents of collective stupidity, with individual factors having three dimensions, collective ones including two dimensions and organizational ones focusing on the characteristics of managers/companies. It was also found that collective stupidity had individual consequences in three dimensions and organizational consequences in five dimensions; and one-sidedness, non-strategic thinking, organizational injustice and weakness in the management of key personnel were extracted as mediators. The results of the quantitative phase confirmed the research model and showed that individual factors and organizational consequences had the lowest (0.037) and highest (1.084) effect sizes on collective stupidity, respectively.

The study of the phenomenon in a particular context and the difficulty of generalizing the findings to other situations, the small size of the study population due to the disproportionate number of experts to the total staff in the qualitative phase, and the limited participation of experts due to the negative nature of the issue in the quantitative phase. Taking advantage of the diversity of experts' mental abilities through equipping the organization with tools for recognizing collective stupidity, improving collective decision-making, enhancing the efficiency of think tanks and organizational prosperity in the age of knowledge economy, preventing damage to the body of knowledge of the company and reducing social loafing can be the main operational implications of this study.

Using a mixed-method approach for analyzing the antecedents and consequences of collective stupidity in this study and examining such a phenomenon in a knowledge-based organizational context and its implementation in a developing country can be among the innovations of the present research. By following a few studies conducted in this field in addition to the organizational pathology of the phenomenon using a fundamental method, this study obtained deep results on how to make the maximum use of experts’ capacities. This was to the extent that in all of the three sections, i.e. the antecedents and consequences of collective stupidity, a new factor emerged.