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The purpose of the chapter is to study the possibility of applying modern intellectual methods and technologies of decision-making for managing complex poorly structured systems.

The methodology of the chapter includes fuzzy cognitive approach, analysis of causal connections, dynamic modeling with application of the impulse processes tools, sustainability analysis of the studied system, and scenarios analysis.

The authors offer fuzzy cognitive approach to modeling the risk management system of commercial Bank POS-loaning processes. The simulated system is represented as a fuzzy-oriented weighted multigraph with a pulse action transmitted through it. The modeling process is implemented in the form of successive execution of the following stages: determining the goal, formation of fuzzy cognitive map, dynamic modeling with application of impulse processes tools, and scenarios analysis of development situation and selection the best.

The developed model of management system is a basis for analyzing the tendencies of various situations development that appear during work of banks in the express loaning segment. It allows forecasting and modeling the strategies of behavior as a reaction to external influences and to determine trajectories of management that allow reducing the internal risks of commercial Bank POS-loaning processes. Fuzzy cognitive approach is an effective tool for decision support during risk management in activities of a commercial bank and could be used for modeling and analysis of functioning and other poorly structured socioeconomic systems.

The overall goal of this chapter is twofold. First, the authors aim to identify indigenous phenomena that influence employee turnover and retention in the Chinese context. Second, the authors link these phenomena to the contextualization of job embeddedness theory. To achieve the goal, the authors begin by introducing three macro-level forces (i.e., political, economic, and cultural forces) in China that help scholars analyze contextual issues in turnover studies. The authors then provide findings in the literature research on employee retention studies published in Chinese academic journals. Next, the authors discuss six indigenous phenomena (i.e., hukou, community in China, migrant workers, state-owned companies, family benefit prioritization, and guanxi) under the three macro-level forces and offer exploratory propositions illustrating how these phenomena contribute to understanding employee retention in China. Finally, the authors offer suggestions on how contextualized turnover studies shall be conducted in China.

This paper examines the relationship between transportation quality, customer satisfaction and profitability. Specifically, this study examines the simultaneous and asynchronous effect of quality of transportation services on customer satisfaction and financial performance and then performs the same examination in relation to the effect of customer satisfaction on financial performance. The partial least squares approach to structural equation modelling is used to examine longitudinal data from 1995 to 2018 from the US airline industry. The findings suggest that low service quality in transportation has adverse effects on customer satisfaction and financial performance, while the impact of customer satisfaction on financial performance in the US Airline transportation industry is mixed. The authors found that the impact of customer satisfaction on financial performance is significant in full-service airlines but not in low-cost airlines. Surprisingly, the authors found no significant direct relationship between transportation quality and financial performance in the US airline industry.

International tourism is a major source of export receipts for many countries worldwide. Although it is not yet one of the most important industries in Taiwan (or the Republic of China), an island in East Asia off the coast of mainland China (or the People's Republic of China), the leading tourism source countries for Taiwan are Japan, followed by USA, Republic of Korea, Malaysia, Singapore, UK, Germany and Australia. These countries reflect short, medium and long haul tourist destinations. Although the People's Republic of China and Hong Kong are large sources of tourism to Taiwan, the political situation is such that tourists from these two sources to Taiwan are reported as domestic tourists. Daily data from 1 January 1990 to 30 June 2007 are obtained from the National Immigration Agency of Taiwan. The heterogeneous autoregressive (HAR) model is used to capture long memory properties in the data. In comparison with the HAR(1) model, the estimated asymmetry coefficients for GJR(1,1) are not statistically significant for the HAR(1,7) and HAR(1,7,28) models, so that their respective GARCH(1,1) counterparts are to be preferred. These empirical results show that the conditional volatility estimates are sensitive to the long memory nature of the conditional mean specifications. Although asymmetry is observed for the HAR(1) model, there is no evidence of leverage. The quasi-maximum likelihood estimators (QMLE) for the GARCH(1,1), GJR(1,1) and EGARCH(1,1) models for international tourist arrivals to Taiwan are statistically adequate and have sensible interpretations. However, asymmetry (though not leverage) was found only for the HAR(1) model and not for the HAR(1,7) and HAR(1,7,28) models.

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.

Fluctuations in the tender price index have an adverse effect on the construction sector and the economy at large. This is largely due to the positive relationship that exists between the construction industry and economic growth. The consequences of these variations include cost overruns and schedule delays, among others. An accurate forecast of the tender price index is good for controlling the uncertainty associated with its variation. In the present study, the efficacy of using an adaptive neuro-fuzzy inference system (ANFIS) for tender price forecasting is investigated. In addition, the Box–Jenkins model, which is considered a benchmark technique, was used to evaluate the performance of the ANFIS model. The results demonstrate that the ANFIS model is superior to the Box–Jenkins model in terms of the accuracy and reliability of the forecast. The ANFIS could provide an accurate and reliable forecast of the tender price index in the medium term (i.e. over a three-year period). This chapter provides evidence of the advantages of applying nonlinear modelling techniques (such as the ANFIS) to tender price index forecasting. Although the proposed ANFIS model is applied to the tender price index in this study, it can also be applied to a wider range of problems in the field of construction engineering and management.

To analyze the emergence of cyberbullying in the news and to unveil the extent to which this new social problem is being constructed as a moral panic.

Ethnographic content analysis is conducted on a sample of 477 local and national newspaper articles published from 2004 to 2011. Goode and Ben-Yehuda’s five criteria of a moral panic – consensus, concern, hostility, disproportionality, and volatility – are used as a lens to analyze how this issue emerged in U.S. culture.

News coverage of this issue erupted within a very short time period, drawing important attention to a previously unknown social problem facing youth. Yet in the construction of cyberbullying as a new threat to social order, the news coverage sometimes inflates the magnitude and severity of the problem. In doing so, the media work to misrepresent, misinform, and oversimplify what is a more complicated and perhaps not yet fully understood issue among youth today.

Electronic aggression is something that is of growing concern to children, parents, educators, and policymakers. Evidence has begun to show that its effects may be as harmful as face-to-face bullying. Since the media play a vital role in the designation of certain issues as worthy of the public’s attention, it is pertinent that this information is presented in an accurate fashion, rather than simply promoting a moral panic around the topic.

Future research should move beyond print media to examine how TV, popular culture, and social media sites construct this problem. This should include research on the public’s understanding and interpretation of these mediated forms of communication.

The rapid growth of digitalization is being used for the betterment of the banking and financial services sector and many other industries. Digital banking (DB) is transforming traditional banking activities into a digital environment. The benefits and conveniences that DB bring to consumers and financial institutions (FIs) have led FIs to adopt various DB innovations. However, to determine whether the demand for DB is at a healthy level, it is necessary to evaluate how DB innovations are accepted among consumers. This chapter is a “viewpoint” of the author that reviews the background of DB in Sri Lanka (SL) and evaluates the success of its diffusion.

The status of the DB diffusion in SL is discussed under DB ecosystem, and DB customer adoption. The DB ecosystem is discussed through the topics of the country’s digital infrastructure (DI), technological know-how within the banks, technology adoption of the market vendors, and consumer’s digital literacy. Then, the consumer use of the DB services is evaluated using the transactions that happened through DB systems against paper-based payments. Statistics presented by Central Bank of Sri Lanka (CBSL) are used as secondary data for the study.

According to the findings of this report, consumer DB adaption is still in its infancy compared to the development of the country’s DB ecosystem. Considering the causes that drives consumer innovation decisions, this chapter highlights the need for industry practitioners to revisit their DB marketing strategies based on consumers’ culture and innovativeness. To that end, further studies are necessary on how individuals’ culture influences DB adoption.