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The purpose of this paper is to develop an effective approach to support and guide production improvement processes utilising online product reviews.

This paper combines two methods: (1) natural language processing (NLP) to support advanced text mining to increase the accuracy of information extracted from product reviews and (2) quality function deployment (QFD) to utilise the extracted information to guide the product improvement process.

The paper proposes an approach to automate the process of obtaining voice of the customer (VOC) by performing text mining on available online product reviews while considering key factors such as the time of review and review usefulness. The paper enhances quality management processes in organisations and advances the literature on customer-oriented product improvement processes.

Online product reviews are a valuable source of information for companies to capture the true VOC. VOC is then commonly used by companies as the main input for QFD to enhance quality management and product improvement. However, this process requires considerable time, during which VOC may change, which may negatively impact the output of QFD. This paper addresses this challenge by providing an improved approach.

Contact centers (CCs) are one of the main touch points of customers in an organization. They form one of the inputs to customer relationship management (CRM) to enable an organization to efficiently resolve customer queries. CCs have an important impact on customer satisfaction and are a strategic asset for CRM systems. The purpose of this paper is to review the current literature on CCs and identify their shortcomings to be addressed in the current digital age.

The current literature on CCs can be classified into the analytical and the managerial aspects of CCs. In the former, data mining, text mining, and voice recognition techniques are discussed, and in the latter, staff training, CC performance, and outsourced CCs are discussed.

With the growth of information and communication technologies, the information that CCs must handle both in terms of type and volume, has changed. To deal with such changes, CCs need to evolve in terms of their operation and public relations. The authors present a state-of-the-art review of the challenges in identifying the gaps in order to have the next generation of CCs. Lack of an interactive CC and lack of data integrity for CCs are highlighted as important issues that need to be dealt with properly by CCs.

As far as the authors know, this is the first paper that reviews CCs’ literature by providing the comprehensive survey, critical evaluation, and future research.

In data engineering, view formalisms are used to provide flexibility to users and user applications by allowing them to extract and elaborate data from the stored data sources. Conversely, since the introduction of EXtensible Markup Language (XML), it is fast emerging as the dominant standard for storing, describing, and interchanging data among various web and heterogeneous data sources. In combination with XML Schema, XML provides rich facilities for defining and constraining user‐defined data semantics and properties, a feature that is unique to XML. In this context, it is interesting to investigate traditional database features, such as view models and view design techniques for XML. However, traditional view formalisms are strongly coupled to the data language and its syntax, thus it proves to be a difficult task to support views in the case of semi‐structured data models. Therefore, in this paper we propose a Layered View Model (LVM) for XML with conceptual and schemata extensions. Here our work is three‐fold; first we propose an approach to separate the implementation and conceptual aspects of the views that provides a clear separation of concerns, thus, allowing analysis and design of views to be separated from their implementation. Secondly, we define representations to express and construct these views at the conceptual level. Thirdly, we define a view transformation methodology for XML views in the LVM, which carries out automated transformation to a view schema and a view query expression in an appropriate query language. Also, to validate and apply the LVM concepts, methods and transformations developed, we propose a viewdriven application development framework with the flexibility to develop web and database applications for XML, at varying levels of abstraction.

Today, eXtensible Markup Language (XML) is fast emerging as the dominant standard for storing, describing, representing and interchanging data among various enterprises systems and databases in the context of complex web enterprises information systems (EIS). Conversely, for web EIS (such as ecommerce and portals) to be successful, it is important to apply a high level, model driven solutions and meta‐data vocabularies to design and implementation techniques that are capable of handling heterogonous schemas and documents. For this, we need a methodology that provides a higher level of abstraction of the domain in question with rigorously defined standards that are to be more widely understood by all stakeholders of the system. To‐date, UML has proven itself as the language of choice for modeling EIS using OO techniques. With the introduction of XML Schema, which provides rich facilities for constraining and defining enterprise XML content, the combination of UML and XML technologies provide a good platform (and the flexibility) for modeling, designing and representing complex enterprise contents for building successful EIS. In this paper, we show how a layered view model coupled with a proven user interface analysis framework (WUiAM) is utilized in providing architectural construct and abstract website model (called eXtensible Web, xWeb), to model, design and implement simple, usercentred, collaborative websites at varying levels of abstraction. The uniqueness xWeb is that the model data (web user interface definitions, website data descriptions and constraints) and the web content are captured and represented at the conceptual level using views (one model) and can be deployed (multiple platform specific models) using one or more implementation models.

Information Privacy is becoming an increasingly important field of research with many new definitions and terminologies. Along similar rates of increase are the use, uptake and expansion of collaborative environments (CEs). There is a need for a better understanding and classification of information privacy concepts and terms. The purpose of this paper is to provide a taxonomy of information privacy in CEs. The knowledge provided from an information privacy taxonomy can be used to formulate better information privacy policies, practices, and privacy enhancing technologies.

Through the hierarchical classification and categorization of information privacy concepts and principles an organized representation of these components has been produced. Each area was well surveyed and researched and then classified into a number of sub‐categories according to their nature and relevance.

A taxonomy was successfully developed with the identification of three high level dimensions of information privacy. Within each dimensional view a further three sub‐classifications were proposed each with their own unique nature.

This paper provides an Information Privacy taxonomy for CEs, the first of its kind to be proposed. A number of new Information privacy terms are defined that make up the categorization and classification of information privacy concepts and components.

In this chapter, the authors consider the relationships between institutional settlements at the field level and the instantiation of logics at the organizational level. The authors present the case of Supervised Consumption Sites (also known as Safe Injection Sites) in Alberta, Canada where a settlement of logics supported by one government was disrupted with the election of a new provincial government in 2015, and then disrupted again after the election of yet another government four years later. The authors use this case to show how different institutional settlements can support or threaten particular types of organizations, and they also show how the instantiation of different settlements in organizations (organizational hybridity) can impact the ways in which organizations present themselves. By analyzing the public justifications provided by key members of Supervised Consumption Sites, they draw attention to connections between institutional settlements at the field level and organizational attempts to manage multiple logics.

This study aims to investigate the effect of healthy food advertising (HFA) in preventing obesity (measured using the healthy eating attitude and perceived self-regulatory success) through the meta-cognitive role of consumer wisdom (CW). The meta-cognitive role of CW to better promote healthy eating attitude and behavior is relevant and underexplored.

Data were collected from 310 young consumers through an online survey. Reliability and validity were established using confirmatory factor analysis, and hypotheses were analyzed through structural equation modeling using MPlus V8.3.

The results reveal that HFA has a positive influence on all dimensions of CW: responsibility, purpose, perspective, reasoning and sustainability. All dimensions but one augment a positive healthy eating attitude, but only responsibility and sustainability enhance consumers’ self-regulatory success. The findings show that HFA does not directly prevent obesity, but CW mediates the relationship between that advertising and obesity prevention. These findings show that CW establishes a mindful connection between HFA and obesity control.

This research extends the theory of CW in the context of healthful eating and contributes significantly to the advertising, hospitality and obesity literature.

This study also has implications for multiple stakeholders, including consumers, restaurant operators, hospitality managers, brand managers, the government and society in general.

To the best of the authors’ knowledge, this study marks the first attempt to investigate the role of CW in preventing obesity. It is also the first study to examine the relationships of HFA with CW and a healthful attitude toward eating.