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Constructing and evaluating behavioral science models is a complex process. Decisions must be made about which variables to include, which variables are related to each other, the functional forms of the relationships, and so on. The last 10 years have seen a substantial extension of the range of statistical tools available for use in the construction process. The progress in tool development has been accompanied by the publication of handbooks that introduce the methods in general terms (Arminger et al., 1995; Tinsley & Brown, 2000a). Each chapter in these handbooks cites a wide range of books and articles on specific analysis topics.

Tourism research contains a large share of consumer behavior-orientated studies using multidimensional constructs (exogenous/endogenous). Accordingly, scholars have mainly made use of a two-step approach that can be referred to as PCA-MLR (principal component analysis and then ordinary least squares multiple linear regression analysis) to examine the relationships among exogenous and endogenous constructs in a statistical model. Although this two-step approach has contributed to the advancement of tourism research, it still suffers from a number of drawbacks which can readily be overcome by a so-called second-generation statistical tool, namely, partial least squares approach to structural equation modeling (PLS-SEM). The current chapter explains and illustrates (with an application to tourism data) the advantages (e.g., several layers of estimations, suiting small sample sizes, robustness to multicollinearity, model-based clustering, etc.) of PLS-SEM both from a statistical and practical point of view. Finally, an elucidation is also provided for suggesting PLS-SEM as an alternative to PCA-MLR instead of COV-SEM (covariance-based structural equation modeling). The chapter concludes by proposing that PLS-SEM is a reliable and flexible statistical approach that is of high value, in particular, for applied research.

In recent years, the use of structural equation modeling (SEM) has become widespread in tourism and hospitality research. Because there are two different approaches to SEM (i.e., covariance-based SEM and variance-based, partial least squares SEM), this brings challenges for researchers about which SEM to use and what to report in each SEM approach. Therefore, the purpose of this chapter is to discuss the differences between CB-SEM and PLS-SEM and to provide comprehensive guidelines for researchers on how to apply each SEM. Within this context, the authors first briefly summarize the fundamentals and advantages of using SEM. Then, the authors explain in detail the major issues that should be considered when selecting between CB-SEM and PLS-SEM. Finally, to ensure rigorous research practices, the authors provide step-by-step guidelines for the application of both CB-SEM and PLS-SEM.

Smart card-based E-payment systems are receiving increasing attention as the number of implementations is witnessed on the rise globally. Understanding of user adoption behavior of E-payment systems that employ smart card technology becomes a research area that is of particular value and interest to both IS researchers and professionals. However, research interest focuses mostly on why a smart card-based E-payment system results in a failure or how the system could have grown into a success. This signals the fact that researchers have not had much opportunity to critically review a smart card-based E-payment system that has gained wide support and overcome the hurdle of critical mass adoption. The Octopus in Hong Kong has provided a rare opportunity for investigating smart card-based E-payment system because of its unprecedented success. This research seeks to thoroughly analyze the Octopus from technology adoption behavior perspectives.

Cultural impacts on adoption behavior are one of the key areas that this research posits to investigate. Since the present research is conducted in Hong Kong where a majority of population is Chinese ethnicity and yet is westernized in a number of aspects, assuming that users in Hong Kong are characterized by eastern or western culture is less useful. Explicit cultural characteristics at individual level are tapped into here instead of applying generalization of cultural beliefs to users to more accurately reflect cultural bias. In this vein, the technology acceptance model (TAM) is adapted, extended, and tested for its applicability cross-culturally in Hong Kong on the Octopus. Four cultural dimensions developed by Hofstede are included in this study, namely uncertainty avoidance, masculinity, individualism, and Confucian Dynamism (long-term orientation), to explore their influence on usage behavior through the mediation of perceived usefulness.

TAM is also integrated with the innovation diffusion theory (IDT) to borrow two constructs in relation to innovative characteristics, namely relative advantage and compatibility, in order to enhance the explanatory power of the proposed research model. Besides, the normative accountability of the research model is strengthened by embracing two social influences, namely subjective norm and image. As the last antecedent to perceived usefulness, prior experience serves to bring in the time variation factor to allow level of prior experience to exert both direct and moderating effects on perceived usefulness.

The resulting research model is analyzed by partial least squares (PLS)-based Structural Equation Modeling (SEM) approach. The research findings reveal that all cultural dimensions demonstrate direct effect on perceived usefulness though the influence of uncertainty avoidance is found marginally significant. Other constructs on innovative characteristics and social influences are validated to be significant as hypothesized. Prior experience does indeed significantly moderate the two influences that perceived usefulness receives from relative advantage and compatibility, respectively. The research model has demonstrated convincing explanatory power and so may be employed for further studies in other contexts. In particular, cultural effects play a key role in contributing to the uniqueness of the model, enabling it to be an effective tool to help critically understand increasingly internationalized IS system development and implementation efforts. This research also suggests several practical implications in view of the findings that could better inform managerial decisions for designing, implementing, or promoting smart card-based E-payment system.

Structural Equation Modeling (SEM) offers researchers additional flexibility and enhanced research conclusions, yet it is still underutilized in accounting. This may be in part because many researchers are not sufficiently familiar with SEM. SEM can be difficult to apply, especially if the research study was not appropriately planned to accommodate the necessary assumptions and data requirements. This article helps researchers overcome some barriers to using SEM by providing a simple guide to effectively planning a study suitable for an SEM analysis while also suggesting references and additional reading on the topic. To further encourage the use of SEM, the practical benefits of using SEM over the traditional regression approach for some research situations are also explained. Finally, a comparison of a regression and an SEM analysis of the same data testing the same theoretical model is included in the Appendices A and B in order to compare the differences in the research conclusions obtained by the two methods of analysis.

Purpose — Study the causal effect of psychological factors on mode choice, using an instrument which gathered attitudinal, affective and habitual behaviour factors, with an application to a Canadian and Chilean sample.

Approach — Ad hoc questionnaire used to collect information related to psychological factors, studying the role of these factors upon mode choice using structural equation modelling, combining a measurement model and the latent variables.

Findings — Emotional (affective) factors have a strong influence on mode choice, as well as attitudinal and habitual factors. Car users have a strong positive emotion to the transport mode they use when compared with public transport users and transit utilization.

Research limitations — The inclusion of social factors, such as norm, role and self-concept, is desirable for a better understanding of people's behaviour regarding transport mode usage. The structural equation modelling was used to analyse the causal effects among factors, but it is not intended to model mode choice. An advanced approach would be to estimate a hybrid discrete choice model.

Practical implications — Realizing the real importance of personal psychological factors on mode choice is a key issue when intending to implement mobility and travel demand management strategies. The success of these strategies strongly relies on people's change of behaviour, which does not depend only on instrumental and socio-demographic factors, such as cost, time and income, but also on these very inner personal aspects.

Originality/value — Capture psychological factors through a comprehensive survey, which rests on a psychological framework and considers simultaneously attitudinal, affective and habitual personal factors, as well as instrumental and socio-demographic information. Make a comparison among cities belonging to different countries regarding the role of these factors, cities with a different cultural and social background.

The strategic management literature emphasizes the concept of business intelligence (BI) as an essential competitive tool. Yet the sustainability of the firms’ competitive advantage provided by BI capability is not well researched. To fill this gap, this study attempts to develop a model for successful BI deployment and empirically examines the association between BI deployment and sustainable competitive advantage. Taking the telecommunications industry in Malaysia as a case example, the research particularly focuses on the influencing perceptions held by telecommunications decision makers and executives on factors that impact successful BI deployment. The research further investigates the relationship between successful BI deployment and sustainable competitive advantage of the telecommunications organizations. Another important aim of this study is to determine the effect of moderating factors such as organization culture, business strategy, and use of BI tools on BI deployment and the sustainability of firm’s competitive advantage.

This research uses combination of resource-based theory and diffusion of innovation (DOI) theory to examine BI success and its relationship with firm’s sustainability. The research adopts the positivist paradigm and a two-phase sequential mixed method consisting of qualitative and quantitative approaches are employed. A tentative research model is developed first based on extensive literature review. The chapter presents a qualitative field study to fine tune the initial research model. Findings from the qualitative method are also used to develop measures and instruments for the next phase of quantitative method. The study includes a survey study with sample of business analysts and decision makers in telecommunications firms and is analyzed by partial least square-based structural equation modeling.

The findings reveal that some internal resources of the organizations such as BI governance and the perceptions of BI’s characteristics influence the successful deployment of BI. Organizations that practice good BI governance with strong moral and financial support from upper management have an opportunity to realize the dream of having successful BI initiatives in place. The scope of BI governance includes providing sufficient support and commitment in BI funding and implementation, laying out proper BI infrastructure and staffing and establishing a corporate-wide policy and procedures regarding BI. The perceptions about the characteristics of BI such as its relative advantage, complexity, compatibility, and observability are also significant in ensuring BI success. The most important results of this study indicated that with BI successfully deployed, executives would use the knowledge provided for their necessary actions in sustaining the organizations’ competitive advantage in terms of economics, social, and environmental issues.

This study contributes significantly to the existing literature that will assist future BI researchers especially in achieving sustainable competitive advantage. In particular, the model will help practitioners to consider the resources that they are likely to consider when deploying BI. Finally, the applications of this study can be extended through further adaptation in other industries and various geographic contexts.

Although the proliferation of research in emotional intelligence (EI) in the last 25 years has largely focused on the individual level, some researchers have proposed theories and measurement models for EI at the organizational level. Drawing from earlier work which conceptualizes organizational emotional intelligence (OEI) as a climate-level construct involving shared norms and practices this chapter sets out to investigate the relationship between perceptions of organizational emotional intelligence (OEI) and turnover intentions amongst employees. Since turnover intentions are a reliable indicator of actual turnover they are deemed to be a critical indicator for organizational performance. This chapter also builds on previous research which found that the relationship between OEI as a climate-level construct and intention to leave was mediated by organizational emotional appeal (i.e., overall reputation) and trust in senior management to explore the mediating role of other employee attitudes which have been traditionally linked to climate and individual-level outcomes in organizations, namely job satisfaction and affective commitment. By surveying employees in a UK-based charity organization (n = 173), the study finds that both job satisfaction and affective commitment mediate the impact of OEI on intention to leave and explain a moderate amount of variance in the focal construct. However, the majority of the mediation occurs through job satisfaction with a reduced mediation effect for affective commitment. Potential reasons for these results in the charity context are discussed. The chapter contributes to a wider understanding of the way in which perceptions of OEI impact on employee attitudes toward the organization and the job; and, in turn, how these attitudes impact on turnover intentions.

Citizens are substantial stakeholders in every e-government system, thus their willingness to use and ability to access the system are critical. Unequal access and information and communication technology usage, which is known as digital divide, however has been identified as one of the major obstacles to the implementation of e-government system. As digital divide inhibits citizen’s acceptance to e-government, it should be overcome despite the lack of deep theoretical understanding on this issue. This research aimed to investigate the digital divide and its direct impact on e-government system success of local governments in Indonesia as well as indirect impact through the mediation role of trust. In order to get a comprehensive understanding of digital divide, this study introduced a new type of digital divide, the innovativeness divide.

The research problems were approached by applying two-stage sequential mixed method research approach comprising of both qualitative and quantitative studies. In the first phase, an initial research model was proposed based on a literature review. Semi-structured interview with 12 users of e-government systems was then conducted to explore and enhance this initial research model. Data collected in this phase were analyzed with a two-stage content analysis approach and the initial model was then amended based on the findings. As a result, a comprehensive research model with 16 hypotheses was proposed for examination in the second phase.

In the second phase, quantitative method was applied. A questionnaire was developed based on findings in the first phase. A pilot study was conducted to refine the questionnaire, which was then distributed in a national survey resulting in 237 useable responses. Data collected in this phase were analyzed using Partial Least Square based Structural Equation Modeling.

The results of quantitative analysis confirmed 13 hypotheses. All direct influences of the variables of digital divide on e-government system success were supported. The mediating effects of trust in e-government in the relationship between capability divide and e-government system success as well as in the relationship between innovativeness divide and e-government system success were supported, but was rejected in the relationship between access divide and e-government system success. Furthermore, the results supported the moderating effects of demographic variables of age, residential place, and education.

This research has both theoretical and practical contributions. The study contributes to the developments of literature on digital divide and e-government by providing a more comprehensive framework, and also to the implementation of e-government by local governments and the improvement of e-government Readiness Index of Indonesia.

Introduction: In this era, financial literacy is conceptualised diversely in the literature. However, as a general term, ‘Financial Literacy’ can be said to mean acting in line with one’s material realities whilst using or managing money. Increasing the financial literacy rate amongst students in Kosovo is paramount since it will prepare and support them in making informed investment decisions and in managing their financial situations.

Aim: The study aims to determine the financial literacy levels of students in Kosovo and to determine the relationship between investment decisions and the Covid-19 pandemic.

Method: The dataset examines four factors (i.e. financial literacy, self-control, peer influence and COVID-19) that influence investment behaviour amongst young students in Kosovo. A total of 228 students from Kosovo participated in the study, and the survey measured their financial literacy, investment knowledge, and the COVID-19 impact on their investment decisions using the random sampling technique. The reflective measurement was made using the Partial Least Squares Structural Equation Model (PLS-SEM) on the data scanned from the survey (N = 228). The measurement includes the evaluation of external loading, internal reliability, and convergent reliability. The final equation model was evaluated and estimated using the Smart-PLS v.3.3.3 program.

Findings: The research findings are useful for companies seeking potential investors from generation Y. In addition to that, the results of the research show that students from Kosovo who are more financially literate are more skilled and make more well-informed decisions when investing. In this study, it was determined that the COVID-19 pandemic did not have a negative effect on the investment decisions of students from Kosovo.