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The growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured data and can inform recommendations for increasing profits and consumer utility – if only the model outputs are interpretable enough to earn the trust of consumers and buy-in from companies. To build a foundation for understanding the importance of model interpretation in image analytics, the first section of this article reviews the existing work along three dimensions: the data type (image data vs. video data), model structure (feature-level vs. pixel-level), and primary application (to increase company profits vs. to maximize consumer utility). The second section discusses how the “black box” of pixel-level models leads to legal and ethical problems, but interpretability can be improved with eXplainable Artificial Intelligence (XAI) methods. We classify and review XAI methods based on transparency, the scope of interpretability (global vs. local), and model specificity (model-specific vs. model-agnostic); in marketing research, transparent, local, and model-agnostic methods are most common. The third section proposes three promising future research directions related to model interpretability: the economic value of augmented reality in 3D product tracking and visualization, field experiments to compare human judgments with the outputs of machine vision systems, and XAI methods to test strategies for mitigating algorithmic bias.

Social media such as Facebook thrive with the arrival of Web 2.0. This chapter merges traditional social network analysis (SNA) with symbolic interactionism (SI) to create a hybrid method of SNA to allow researchers to study the sociability found in Facebook. The discussion begins with identifying a common ground of SNA and SI, found in Georg Simmel’s work, and then develops methodological procedures to locate cliques in Facebook networks. A visualization technique is also suggested to further single out the social forms found in Facebook.

Globalization, the ever-increasing worldwide flow of ideas, practices, and material objects resulting in increasing interdependency between people and nations across the globe, has numerous interrelated economic, political, cultural, ideological, environmental, and technological facets.

In an effort to make the elusive and multifaceted concept of globalization more tangible and measurable, different instruments have been developed, usually in the form of “indexes” based on quantitative data. These indexes mainly result in rankings of individual cities as well as whole countries with respect to their supposed level of globalization. Some items of the existing indexes to measure the level of globalization of nation states or cities refer to phenomena that are to some extent visually observable, but many aspects and manifestations of globalization escape these rather crude operationalizations.

Visual approaches to globalization help to enrich and complement the more abstract and mainly quantitatively supported discourses around this multifaceted phenomenon. They may provide valid and unobtrusive ways to assess and understand the impact of culture and cultural exchange in the daily lives of inhabitants of cities around the world and add a unique “localized,” cross-cultural empirical perspective to the many divergent views and discussions about the presumed beneficial or detrimental nature of these processes. An ‘in situ’ visual approach to globalization may help to uncover the “real life” impact and the specific contexts of these processes at different locations. This chapter discusses different options for researching globalization and cultural change in cities.

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.

Purpose – For decades, archivists have been appraising, preserving, and providing access to digital records by using archival theories and methods developed for paper records. However, production and consumption of digital records are informed by social and industrial trends and by computer and data methods that show little or no connection to archival methods. The purpose of this chapter is to reexamine the theories and methods that dominate records practices. The authors believe that this situation calls for a formal articulation of a new transdiscipline, which they call computational archival science (CAS).

Design/Methodology/Approach – After making a case for CAS, the authors present motivating case studies: (1) evolutionary prototyping and computational linguistics; (2) graph analytics, digital humanities, and archival representation; (3) computational finding aids; (4) digital curation; (5) public engagement with (archival) content; (6) authenticity; (7) confluences between archival theory and computational methods: cyberinfrastructure and the records continuum; and (8) spatial and temporal analytics.

Findings – Each case study includes suggestions for incorporating CAS into Master of Library Science (MLS) education in order to better address the needs of today’s MLS graduates looking to employ “traditional” archival principles in conjunction with computational methods. A CAS agenda will require transdisciplinary iSchools and extensive hands-on experience working with cyberinfrastructure to implement archival functions.

Originality/Value – We expect that archival practice will benefit from the development of new tools and techniques that support records and archives professionals in managing and preserving records at scale and that, conversely, computational science will benefit from the consideration and application of archival principles.

Organizational fields are shaped by both the relations that organizations forge and the language they express. The structure and discourse of organizational fields have been studied before, but seldom in combination. We offer a methodological approach that integrates relations and expressions into a comprehensive visualization.

By mapping networks and discourse as co-constitutive, the method illuminates the mechanisms active in organizational fields. We utilize social impact evaluation as an issue field shaped by the presence of an interstitial community, and compare this structure with simulated alternative field configurations.

The simulations reveal that variation in organizations’ openness to adopting concepts from adjacent meaning systems alters field configurations: differentiation manifests under conditions of low overall openness, whereas moderate receptivity produces hybridizations of discourses and sometimes the emergence of an interstitial community that bridges domains. If certain organizations are open while others remain focused on their original discourse, then we observe integration in the discursive domain of the invariant organizations.

The observations from the simulations are represented by visualizing organizational fields as topographies of meaning, onto which interorganizational relations are layered. This representation localizes organizations and their interactions in a cultural space while emphasizing how meanings of relationships and organizational expressions vary with different field configurations. By adding meaning to network data, the resulting maps open new perspectives for institutional research on the adaptation, translation, and diffusion of concepts.

This chapter discussed the role of business intelligence (BI) in healthcare twofold strategic decision making of the organization and the stakeholders. The visualization techniques of data mining are applied for the early and correct diagnosis of the disease, patient’s satisfaction quotient and also helpful for the hospital to know their best commanders.

In this chapter, the usefulness of BI is shown at two levels: at doctor level and at hospital level. As a case study, a hospital is taken which deals with three different kinds of diseases: Breast Cancer, Diabetes, and Liver disorder. BI can be applied for taking better strategic decisions in the context of hospital and its department’s growth. At the doctor level, on the basis of various symptoms of the disease, the doctor can advise the suitable treatment to the patients. At the hospital level, the best department among all can be identified. Also, a patient’s type of admission, continued their treatments with the hospital, patient’s satisfaction quotient, etc., can be calculated. The authors have used different methods like Correlation matrix, decision tree, mosaic plots, etc., to conduct this analysis.

Education for sustainability has become the mechanism for creating a pool of graduates who can understand, appreciate, practice and support the achievement of Sustainable Development Goals (SDGs). In a world with diverse cultures, demographics, political ideologies, etc. faster progress towards sustainable development needs increased use of digital technologies. Integration of digital technologies like artificial intelligence (AI), metaverse, visualisation techniques, cloud computing, Internet of Things (IoT), open data repositories, geographic information system (GIS), etc. with classroom teaching can build awareness, skills, attitudes and values among students in the journey towards sustainable development and scale up the efforts towards the goals.

In this chapter, the authors have tried to bring out a list of digital technologies and the way in which they can be used in classroom teaching to ensure education for sustainability. It may be noticed that there are watertight compartments between those who know the SDGs and those with proficiency in technology. What is also needed is integration between both silos for mapping the digital technologies with the appropriate SDGs. The teachers in the higher education system need more exposure to understand and implement this integration.

This paper proposes and tests a model to explain the outcomes of three different information presentation formats. Based on cognitive fit theory, information visualization formats that best fit task characteristics are expected to lead to improved decision-making outcomes. We apply the Judgment and Decision-Making framework (Bonner, 2008) to investigate how certain factors can impact decision quality.

This study tests whether certain production variance presentation formats (percentages, dollar amounts, and schematic faces), task complexity, understanding of the presentation format, motivation, and effort increase the accuracy of a supervisor’s bonus calculation. A total of 281 students and professionals participated in this experiment. Their responses were examined using regression analysis.

Our results indicate that individuals mostly prefer the percentages presentation format and that the use of the percentages presentation format, a lower level of task complexity, and a better understanding of the variance presentation format lead to more accurate calculations in the experimental task.

Our study provides a call for further research on factors that influence the choice of presentation format as a potentially fruitful area for management accounting researchers.

We exhort practicing management accountants to exert direct influence on employees’ decision making through the use of variance presentation formats that fit their tasks and promote understanding.

Our experiment introduced two major innovations: it uses an interactive data visualization approach allowing subjects to select their preferred presentation format; and it focuses on production variances, a topic that has received less attention in the academic managerial accounting literature, but is still very relevant to practitioners.