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Does the adoption of the Enterprise Risk Management (ERM) improve bank profitability? Does ERM also reduce bank risk? By analyzing a sample of banks located in European emerging markets between 2005 and 2013, the aim of this chapter is to empirically investigate the determinants of firm performance, both in terms of bank profitability and risk, with respect to the adoption of Enterprise Risk Management (ERM). In order to capture the effect of the ERM program adoption on banks’ performance, we both use market-based measures as well as accounting-based indexes. Following the seminal literature on the topic (Aebi, Sabato, & Schmid, 2012; Eckles et al., 2014; Ellul & Yerramilly, 2013; Hoyt & Liebenberg, 2003, 2011; Lin, Wen, & Yu, 2012; Pagach & Warr, 2010), we adopt a binary proxy variable, that is, the appointment of a Chief Risk Officer (CRO), to define whether the firm is currently undertaking an ERM program. Our results show that a post-ERM firm experiences an increase in the risk-adjusted profits and a reduction of the overall risk.

Building on Lambert’s (2001) work on turnover intent in law enforcement, this study examines how organizational characteristics and job attitudes along with job satisfaction, and organizational commitment affect turnover intent among Taiwanese police officers.

Data were collected from the New Taipei City Police Department (NTCPD) in the summer of 2012 via stratified random sampling (N = 1,035). Structural equation modeling was employed to examine factors affecting turnover intent.

Job satisfaction and organizational commitment reduced the risk of turnover, while job stressors and training effectiveness directly increased the risk. Worthy of note, officers with a Central Police University degree and who were married had a lower risk of turnover.

This study applies Lambert’s (2001) turnover intent model in law enforcement agencies developed in the West to a non-western policing setting. The use of SEM assures the robustness of the findings. Some noteworthy contrasts in findings from Western and non-Western settings are presented.

The aim of this article is to construct a performance evaluation framework that can be employed in companies to enhance their business operations and strengthen their financial advantage in the current environment. To validate the approach, a case example has been included to assess the practicality and validity of this approach when applied in a real environment.

This study focuses on an important part of the strategic planning process: internal scrutiny and environmental (external) scanning, in which an evaluation of company performance is divided into two stages by using network DEA and the cross-efficiency approach. In addition, this article employs Miles and Snow's typology for classifying the strategies used by companies.

The analytical results show that the proposed framework can be useful for companies seeking to evaluate which strategies may be the most appropriate, based on Miles and Snow's typology, to effectively reallocate limited resources.

The evaluation in this study only uses financial data and does not take other nonfinancial indicators into consideration.

This research provides value by classifying each company included in the study in terms of its capability and financial efficiency according to Miles and Snow's system of strategy classification. Second, an internal and external performance measuring framework is constructed. Finally, some propositions for top management are provided by analyzing the financial advantages of using a performance evaluation framework that can help top management make decisions more objectively.

Many reviews on the internet are contributed their time to evaluate which are largely transparent generally; however, How are these information valuable and useful to visitors before making a purchasing decision? As the reason, there is a need to understand the distal path of visitors concern. The purpose of this paper is to evaluate the effects of both perceived useful and valuable motivations on visitors’ willingness to buy in the distal paths.

Web questionnaire survey.

Visitors’ confirmation was the beginning to impact the intention to buy through only one distal path, perceived value (PV) and satisfaction.

Even though the author tried his best to design and implement thoughtfully for this research, there are still some limitations. First, the results could be influenced by self-selection bias. The sample of respondents surveyed in this study consisted of young adults (58.90 percent were between the ages 21 and 25 years old), the majority of whom (54.79 percent) were students. Therefore, in the context of this study, the visitors surveyed were young and able to easily access information online. The phenomenon has been, proved by Hsu (2013), found, it still needs to explore further. Second, perceived usefulness did not have a significant impact on satisfaction which consistent with Tao et al. (2009) result. The data represent the response’ feeling for now; it needs to be explored further. Third, it would also be worthwhile to investigate any obstacles, such as believable (Cheung et al., 2012) that might reduce the intentions to buy of visitors. Finally, recommendations and promotions have also been found to influence visitors’ further purchasing behavior, such as extra buy (Tsao, 2013). These phenomena are worth investigating in future research.

To inspire visitors, information of reviews can be posted by offering positive or negative suggestions (e.g. good or bad experience); managers should improve their products or services from the suggestions of reviews and need to consider the distinctive influences of various aspects of reviews when promoting products and devising e-marketing strategies. Marketers should recruit and filter reviews to write positive suggestions of their own products or service. IS practitioners should post the reviews might need to provide more detailed information (e.g. the reasons of like or dislike). The posted information from reviews should be accurate, particularly aiming at visitors who are motivated by reviews’ suggestions. All proposed measures are particularly important for visitors with sufficient reviews effects. Greater transparency of reviews might be achieved by more explicit reviews information (e.g. via like or dislike statements).

The result provides a basis to generate concrete advice for owners about reviews concern to enhance visitors’ PV. It seems sensible to pursue two strategies: first, enhance the visitors’ PV to trigger motivation forward, and second, inspire the visitors to progress smoothly in the visiting stage.

The results of the expectation-confirmation theory applied to reviews recommendations how important to employ for enterprises. These reviews were either directly given by experienced users or at least validated with their help to visitors. Therefore, the value is building the distal bridge between visitors and customers through online general reviews.

The purpose of this study is to discover valuable customers for enterprises. The international market of Taiwan airlines can be enhanced; thus, this study aims at Taiwan’s airline market as a research area.

This research uses data mining technologies with a proposed model to analyse airline customer values for big data online marketing systems, such as customer relationship management (CRM) system. The research applied supervised apriori algorithm, socio-economic variables and a proposed model to discover the rules/markets.

The results show that eight markets were discovered and three association rules were established for business systems of airlines.

The valuable travellers/markets can be discovered by this research. By collecting shoppers’ transactional data, global online CRM and point of sales (POS) systems can be big data marketing systems. The research framework can be easily applied in online CRM/POS or big data marketing systems for international airlines; however, it is for other global businesses as well.

Nowadays, the agricultural business environment is expended to the whole world. Transaction records in point of sales and customer relationship management (CRM) systems can be large-scale data for long-established global chain businesses. Thus, the purpose of this paper is to using a proposed data mining approach to discover valuable markets/customers of urban coffee shop industry (retailer) in current environment of Taiwan, which can implement the industry's data-driven marketing strategy on a CRM system.

In this research approach, Ward's method, C5.0 decision tree and a proposed model are applied for discovering valuable markets and mining useful customer rules.

These found markets and discovered rules can be applied on marketing information or CRM system for identifying valuable customers and target markets.

In this study, the CRM system can be the media for the data-driven marketing strategy in environment of Taiwan. The approach of this research can be applied on other businesses for their data-driven marketing strategies as well.

Online customer relationship management (CRM) is an important issue for implementing digital marketing of electronic commerce or social commerce. The purpose of this study is to establish valuable markets for discovering customer knowledge from data-driven CRM systems for enhancing growth rates of businesses. Airline or travel agency industries are online businesses in the world. Therefore, the industries in Taiwan will be an empirical case for this study.

This research applied a procedure with an applied proposed model for establishing valuable markets from data-driven CRM systems. However, the study used a proposed customer value model (recency, frequency and monetary [RFM]; RFM model-based), the analytic hierarchy process (AHP) procedure and a proposed equation for estimating customer values.

For enhancing the data-driven CRM marketing of the industries, in this research, the market of air travelers can be partitioned into eight markets by the proposed model. As well, the markets can be ranked by the AHP procedure. Furthermore, the travelers’ customer values can be estimated by a proposed customer value equation.

Via the applied proposed procedure, online airlines, travel agencies or other online businesses can implement the research procedure as their data-driven marketing strategy on their online large-scale or Big Data customers’ databases for enhancing sales rates.

The purpose of this paper is to propose a data mining approach for mining valuable markets for online customer relationship management (CRM) marketing strategy. The industry of coffee shops in Taiwan is employed as an empirical case study in this research.

Via a proposed data mining approach, the study used fuzzy clustering algorithm and Apriori algorithm to analyze customers for obtaining more marketing and purchasing knowledge of online CRM systems.

The research found three hard markets and one fuzzy market. Furthermore, the study discovered two association rules and two fuzzy association rules.

However, industry of coffee shops has been always a fast-growing and competitive business around the world. Thus, marketing strategy is important for this industry. The results and the proposed data mining approach of this research can be used in the industry of coffee shop or other retailers for their online CRM marketing systems.

The purpose of this paper is to investigate the effects of anthropomorphism and identify factors related to adopting voice shopping on smart speakers.

Progress in partial least squares structural equation modeling (PLS-SEM) approach is used to test the proposed research framework regarding anthropomorphism and user perceptions on voice shopping via smart speakers. Individuals' responses to questions about attitude and intention to use voice shopping via smart speakers were collected and analyzed.

The results showed that anthropomorphism had a positive influence on satisfaction, which, in turn, had a positive impact on intention to adopt voice shopping, and customers had positive opinions regarding smart speakers.

This study only reflects a younger perspective on smart speaker voice shopping. This study identified the characteristics of smart speakers that increase customers' intention to purchase, which can be used to formulate sales strategies and management guidelines.

This research provided a new perspective to enable practitioners to promote smart speakers for voice shopping. Smart speaker manufacturers can utilize the findings of this research to improve the system design of smart speakers to further facilitate voice shopping.

Unlike previous studies, which focused on product attributes of smart speakers or voice shopping experiences, this study provided a clear picture of how the anthropomorphic feature of smart speakers affects customers' intention to adopt voice shopping.