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Research on strategic choices available to the firm are often modeled as a limited number of possible decision outcomes and leads to a discrete limited dependent variable. A limited dependent variable can also arise when values of a continuous dependent variable are partially or wholly unobserved. This chapter discusses the methodological issues associated with such phenomena and the appropriate statistical methods developed to allow for consistent and efficient estimation of models that involve a limited dependent variable. The chapter also provides a road map for selecting the appropriate statistical technique and it offers guidelines for consistent interpretation and reporting of the statistical results.

The purpose of this paper is to extend significantly the technology acceptance model (TAM) of Davis to design an extended TAM model to be used in the evaluation and assessment of e-information services for information research such as e-library services. The present TAM extension is based on two variables of behavioral intention: the perceived ease of use and perceived usefulness of a system. Furthermore, the user satisfaction, free access, information architecture, content richness, policies and rules, publishers’ quality, system self-efficacy and task technology fit were incorporated into the TAM to extend it with other factors theoretically motivated and would be of interest more generally.

The researcher adopted an experimental approach-based comparison between an experimental group (107 researchers) using an electronic information service (the e-library service of the university) and a control group (107 researchers) not registered in this e-information service of the university.

The researcher used the effect size values based t-test independent samples at the 0.05 level to adapt the structural model equation to the experimental sample. Principal results show that the behavioral intention was influenced significantly by user satisfaction. The perceived usefulness of the e-library services was influenced significantly by the perceived ease of use, information architecture, content richness, free access, publishers’ quality, task-technology fit and e-library service self-efficacy.

This paper is useful in advancing a framework for the evaluation and assessment of the electronic information service used for information research and exploring users’ attitudes toward using that service.

Longitudinal regression analysis is conducted to clarify causal relations and control for unwanted influences from actor heterogeneity and state dependence on theoretically important coefficient estimates. Because strategic management contains theory on how firms differ and how firm actions are influenced by their current strategic position and recent experiences, consistency of theory and methodology often requires use of longitudinal methods. We describe the theoretical motivation for longitudinal methods and outline some common methods. Based on a survey of recent articles in strategic management, we argue that longitudinal methods are now used more frequently than before, but the use is still inconsistent and insufficiently justified by theoretical or empirical considerations. In particular, strategic management researchers should use dynamic models more often, and should test for the presence of actor effects, autocorrelation, and heteroscedasticity before applying corrections.

Artificial neural network (ANN) models, part of the discipline of machine learning and artificial intelligence, are becoming more popular in the marketing literature and in marketing practice. This paper aims to provide a series of tests between ANN models and competing predictive models.

A total of 46 pairs of models were evaluated in an objective model-building environment. Either logistic regression or multiple regression models were developed and then were compared to ANN models using the same set of input variables. Three sets of B2B data were used to test the models. Emphasis also was placed on evaluating small samples.

ANN models tend to generate model predictions that are more accurate or the same as logistic regression models. However, when ANN models are compared to multiple regression models, the results are mixed. For small sample sizes, the modeling results are the same as for larger samples.

Like all marketing research, this application is limited by the methods and the data used to conduct the research. The findings strongly suggest that, because of their predictive accuracy, ANN models will have an important role in the future of B2B marketing research and model-building applications.

ANN models should be carefully considered for potential use in marketing research and model-building applications by B2B academics and practitioners alike.

The research contributes to the B2B marketing literature by providing a more rigorous test on ANN models using B2B data than has been conducted before.

This study is an updated and enhanced version of the study named “Building a methodology to assess the e‐government transformation success” presented by İskender and Özkan in the 18th Americas Conference on Information Systems (AMCIS 2012). The main purpose of this study is to explain the development of the methodology presented in the previous study in detail, but as an add‐on to the previous one, it also applies the developed methodology on the real data collected from Turkish public institutions to show the practical implementation of it and to evaluate the preliminary results.

The methodology explained in this study is designed to collect quantitative data to assess the relationship between the success level of e‐government transformation in Turkish public institutions (dependent variable) and the probable factors (independent variables) which might be effective on this success. The dependent variable is formed by using the framework of IS Success Model created by DeLone and McLean (D&M IS Success Model), while the independent variables are gathered from literature by analyzing 100 studies focusing on probable success factors.

The major output of this study is a common methodology designed to collect and analyze the data of different stakeholder groups in e‐government transformation, but the practical implementation shows that the independent variables gathered from the literature as the probable causes of the success in e‐government transformation are not really the causes of this success, although they are positively correlated to it. In addition to this, trying to evaluate the effect of each single independent variable on the dependent variable separately is not a logical way, as some of these variables are subject to reciprocal suppression with the other ones.

Although the developed methodology is a generic one, the practical implementation of it in this study only uses the data of Turkish public institutions.

Since the methodology is a generic one, it might be used by the other interested researchers to do similar or alternative analyses with the same or different sample groups.

Understanding the relationship between the e‐government transformation success and the probable success factors better might be helpful to develop better policies focusing on the social, legal, technical and economic dimensions of the subject more properly.

Apart from the similar studies in the literature, the methodology developed in this study provides a way for the researchers who want to collect comparable quantitative data not only from external stakeholders (citizens who use e‐government services) but also from internal stakeholders (government officials who provide these services and benefit from them in the internal processes of the public institutions).

Based on the American antidumping cases against China, the purpose of this paper is to construct an early warning model for Chinese exports.

In order to overcome the drawbacks of the existing early warning models for antidumping, first, the authors screen out six most relevant indices that play a key role in US textile corporations' decision of antidumping petition against China from 2002 to 2006, then design a early warning system for antidumping petition based on panel data logit model.

The regression result indicates that unemployment ratio and import‐penetration ratio significantly influence the antidumping filing decisions; when the other invariables keep the same, with the market share of China textile goods increasing by 1 per cent point, the odds ratio of antidumping petitions against China textiles increases by about 3.7 per cent.

As far as the authors are aware there is no definite research yet about early warning system of antidumping events, and this paper aims to specifically address this issue.

This paper examines the relationship between environmental uncertainty and tax avoidance at the firm level. We posit that managers faced with more uncertain environments are likely to engage in more tax avoidance activities. We find a significant and negative relationship between environmental uncertainty and effective tax rates, and our results persist through a battery of robust checks. We further find that managerial ability mitigates the above relationship. Moreover, we find that small, highly leveraged, and innovative firms operating in uncertain environments engage in more tax avoidance.

As a field, we should put more emphasis on interpreting the magnitude of coefficient estimates rather than only assessing statistical significance. To support this claim, I demonstrate how focusing only on statistical significance can lead to incorrect and incomplete conclusions in many common applications of the linear regression model. Moreover, I demonstrate why interpreting coefficient estimates in common non-linear estimators (e.g., probit, logit, Poisson, and negative binomial estimators) requires additional care compared to the linear regression model.

This paper is the main section on quantitative data analysis. It explains the concepts at a greater detail to help non-Math/Stat scholars to understand the basics easily. Proper data analysis is critical to any research. If data are not properly analyzed, then it may give results which either cannot be properly interpreted or wrongly interpreted. This section covers univariate, multivariate analysis and then, factor analysis, cluster analysis, conjoint analysis, and multidimensional scaling (MDS) techniques.

This paper aims to examine the factors affecting the implementation of corporate social responsibility (CSR) sustainably in mobile operators in the kingdom of Bahrain.

The research relies on the existing literature as a secondary data source. The primary data was collected through questionnaires distributed to three leading mobile operators in the Kingdom of Bahrain. The research's population numbered 1,689, and the sample size was 313; the simple random sampling method was used for data collection with a response rate of 87.2% out of a total sample size of 273 respondents. In addition, the responses were analyzed using statistical package for the social sciences (SPSS) software version 24.0; specifically, Spearman's rank correlation was used to test the hypotheses. The research design was quantitative, so a nonparametric procedure was applied to test the hypotheses.

The research produced positive relationships between the independent variables (economic, legal, ethical, philanthropic and environmental responsibilities) and the dependent variable: CSR implementation by Bahrain mobile operators; therefore, the five proposed hypotheses were accepted; furthermore, the highest positive correlation coefficient was 0.735 for environmental responsibility, and the lowest correlation coefficient was 0.533 for economic responsibility.

The research produced positive relationships between the independent variables (economic responsibility, legal responsibility, ethical responsibility, philanthropic responsibility and environmental responsibility) and the dependent variable: CSR implementation by Bahrain mobile operators; therefore, the five proposed hypotheses were accepted; furthermore, the highest positive correlation coefficient was 0.735 for environmental responsibility, and the lowest correlation coefficient was 0.533 for economic responsibility.

The outcomes of the research mainly suggest that mobile operators assign employees who have been working with the company for more than 7 years to implement CSR; due to their engagement to implement CSR as a sustainable practice more than others with less than 3 years or 3-6 years in Bahrain mobile operators. Besides, the research provides a starting point by which other researchers could investigate CSR in other sectors in the Kingdom of Bahrain.

The research provided a framework for Bahrain mobile operators to assist them in enhancing the implementation of CSR in a sustainable manner, which are economic, legal, ethical, philanthropic and environmental responsibilities.