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Organizations across industries are increasingly using Artificial Intelligence (AI) systems to support their innovation processes, supply chains, marketing and sales and other business functions. Implementing AI, firms report efficiency gains from automation and enhanced decision-making thanks to more relevant, accurate and timely predictions. By exposing the benefits of digitizing everything, COVID-19 has only accelerated these processes. Recognizing the growing importance of AI and its pervasive impact, this chapter defines the “social value of AI” as the combined value derived from AI adoption by multiple stakeholders of an organization. To this end, we discuss the benefits and costs of AI for a business-to-business (B2B) firm and its internal, external and societal stakeholders. Being mindful of legal and ethical concerns, we expect the social value of AI to increase over time as the barriers for adoption go down, technology costs decrease, and more stakeholders capture the value from AI. We identify the contributions to the social value of AI, by highlighting the benefits of AI for different actors in the organization, business consumers, supply chain partners and society at large. This chapter also offers future research opportunities, as well as practical implications of the AI adoption by a variety of stakeholders.

The architecture, engineering and construction industry faces several challenges when performing life-cycle cost calculations. On the basis of activity theory, this study aims at improving our understanding of the current cost calculation in design practices as an activity system with a number of built-in contradictions.

Drawing on one of the authors’ practical experience from a design office, the research design comprises a paradigmatic case study of a Danish architecture firm, in which data are gathered through documents, observations, interviews and physical artefacts. Moreover, this paper applies a literature review on barriers for adopting life-cycle costing.

The paper identifies a number of primary, secondary, tertiary and quaternary contradictions between practices of design, cost calculations and data management. Thus, hypotheses are formulated on how and to what extent these different contradictions shape cost calculations in design practices to obstruct or support the application of life cycle costing principles in design.

This study is part of an ongoing research project. Thus, additional analysis is required before the authors may conclude on final results.

This paper identifies a number of factors that obstruct or support the implementation of life cycle costing in current design practices.

This paper provides new insights into the various contradictions that shape data management in architectural offices as a prerequisite for improving life cycle design practices.

This paper will examine the unsafe work practices that are plaguing the construction industry. Statistics show that four out of five of all workplace accidents are attributed to unsafe behaviour. Research studies have sought to understand worker self-protection. For example, it is difficult to make predictions of conditions that influenced worker’s behaviour to act unsafely or safely in a given work situation. It is evident there is a gap in the literature in this area of research, most notably failing to understand the underlying “why” factors. The aim of the study is to identify and examine the proximate set of contributing factors most likely to have an influence on workers’ decisions about participation in unsafe behaviour.

To perform the study, questionnaires were adopted, and 225 construction workers from 9 construction companies participated in the study.

Results showed that both underlying organisational factors and individual factors could affect the risk aversion among construction workers. The paper also highlights measures to create a safe work environment to minimise unsafe behaviour among construction workers. Results from the study are important to help organisation to systematically plan for a good working environment.

As the results were based only from the questionnaires, a deeper understanding behind the workers’ responses was not probed.

Construction companies should work at several organisational levels at the same time. It is necessary to include levels such as individual, group, workplace and management levels, thus taking a system perspective on risk behaviour and safety.

This chapter reflects on the understanding of the phenomenon known as Smart Industry, Industry 4.0, fourth industrial revolution, and many other labels. It does so by reflecting on the issue of terminology, as well as the existing diversity regarding the description of the phenomenon. The issue of meaning is addressed by assessing the results from Culot, Nassimbeni, Orzes, and Sartor (2020) and Habraken and Bondarouk (2019) which are, subsequently, used to develop a workable description. Findings from the two assessed studies raise the question of whether a workable construction of the phenomenon is to be understood as the key technologies or the distinctive developments? A question without a definitive answer, but I will present my view by taking inspiration from the manner in which the prior industrial revolutions are commonly understood. This leads to a, still multifaceted though, more focused understanding of the phenomenon. The insights, formulated proposition and developed model stemming from the reflection of terminology and meaning of the phenomenon helps move the current technology-related phenomenon forward. They assist with the establishment of well-documented papers. A critical aspect if we aim to understand how management will look like in the era of this phenomenon.

“The unexamined life is not worth living” (Socrates). That is, without critically inquiring into the knowledge of life which is well-being and valuable, life is not worth living. Critical thinking questions existing theories and their unexamined and obsessive assumptions and generalizations, constraints, and “best” practices of the prevailing system of management and tries to replace them with more valid assumptions and generalizations that uphold the dignity, uniqueness, and inalienable rights of the individual person and the community. Better outcomes result from asking the right questions than from having the right answers. In the diverse, pluralist cultural environment of today, the promise of a truly generative dialog among Occidental (Western) and Oriental (Eastern) cultures and civilizations holds great hope for the future. Critical thinking (CT) is an “inclusive” thinking system that can facilitate this dialog such that all of us have a meaningful space and place in this universe. After defining CT and arguing its importance for executives, this chapter introduces CT in two parts: Part 1: Various Approaches to Critical Thinking; Part 2: Major Theories of Critical Thinking. Several contemporary business cases will be invoked to illustrate the need, nature, and scope of corporate CT.

This paper investigates effective human-robot collaboration (HRC) and presents implications for Human Resource Management (HRM). A brief review of current literature on HRM in the smart industry context showed that there is limited research on HRC in hybrid teams and even less on effective management of these teams. This book chapter addresses this issue by investigating factors affecting intention to collaborate with a robot by conducting a vignette study. We hypothesized that six technology acceptance factors, performance expectancy, trust, effort expectancy, social support, organizational support and computer anxiety would significantly affect a users' intention to collaborate with a robot. Furthermore, we hypothesized a moderating effect of a particular HR system, either productivity-based or collaborative. Using a sample of 96 participants, this study tested the effect of the aforementioned factors on a users' intention to collaborate with the robot. Findings show that performance expectancy, organizational support and computer anxiety significantly affect the intention to collaborate with a robot. A significant moderating effect of a particular HR system was not found. Our findings expand the current technology acceptance models in the context of HRC. HRM can support effective HRC by a combination of comprehensive training and education, empowerment and incentives supported by an appropriate HR system.

Purpose: Previous research identified a measurement gap in the individual assessment of social misconduct in the workplace related to gender. This gap implies that women respond to comparable self-reported acts of bullying or sexual discrimination slightly more often than men with the self-labeling as “bullied” or “sexually discriminated and/or harassed.” This study tests this hypothesis for women and men in the scientific workplace and explores patterns of gender-related differences in self-reporting behavior.

Basic design: The hypotheses on the connection between gender and the threshold for self-labeling as having been bullied or sexually discriminated against were tested based on a sample from a large German research organization. The sample includes 5,831 responses on bullying and 6,987 on sexual discrimination (coverage of 24.5 resp. 29.4 percentage of all employees). Due to a large number of cases and the associated high statistical power, this sample for the first time allows a detailed analysis of the “gender-related measurement gap.” The research questions formulated in this study were addressed using two hierarchical regression models to predict the mean values of persons who self-labeled as having been bullied or sexually discriminated against. The status of the respondents as scientific or non-scientific employees was included as a control variable.

Results: According to a self-labeling approach, women reported both bullying and sexual discrimination more frequently. This difference between women and men disappeared for sexual discrimination when, in addition to the gender of a person, self-reported behavioral items were considered in the prediction of self-labeling. For bullying, the difference between the two genders remained even in this extended prediction. No statistically significant relationship was found between the frequency of self-reported items and the effect size of their interaction with gender for either bullying or sexual discrimination. When comparing bullying and sexual discrimination, it should be emphasized that, on average, women report experiencing a larger number of different behavioral items than men.

Interpretation and relevance: The results of the study support the current state of research. However, they also show how volatile the measurement instruments for bullying and sexual discrimination are. For example, the gender-related measurement gap is considerably influenced by single items in the Negative Acts Questionnaire and Sexual Experience Questionnaire. The results suggest that women are generally more likely than men to report having experienced bullying and sexual discrimination. While an unexplained “gender gap” in the understanding of bullying was found for bullying, this was not the case for sexual discrimination.

Rights and duties are involved in every area of business and markets, and society and governments. Most often, rights and duties involve serious ethical and moral issues of conflict. A good theory of the ethics of rights and duties, obligations, and responsibilities will empower us to understand the impact of our actions on various stakeholders. Additionally, a deep understanding of rights and duties could help us to analyze better the impact of our executive actions on various stakeholders and, in particular, to fathom the damaging effects of rights and duties violated by the man-made current financial crisis when seen from an ethical and moral point of view. Our coverage on the ethics of corporate rights and duties will comprise of two parts: Part 1: The Nature of Corporate Business Rights and Duties, and Part 2: Respecting Corporate Rights and Duties. The chapter will feature Newcomb Wellesley Hohfeld’s framework of legal interests such as claims, privileges, power, and immunity and its various applications to contemporary market and corporate executive situations. We illustrate the theory of rights and duties using several cases from the current turbulent markets.

Advances in Big Data, artificial Intelligence and data-driven innovation bring enormous benefits for the overall society and for different sectors. By contrast, their misuse can lead to data workflows bypassing the intent of privacy and data protection law, as well as of ethical mandates. It may be referred to as the ‘creep factor’ of Big Data, and needs to be tackled right away, especially considering that we are moving towards the ‘datafication’ of society, where devices to capture, collect, store and process data are becoming ever-cheaper and faster, whilst the computational power is continuously increasing. If using Big Data in truly anonymisable ways, within an ethically sound and societally focussed framework, is capable of acting as an enabler of sustainable development, using Big Data outside such a framework poses a number of threats, potential hurdles and multiple ethical challenges. Some examples are the impact on privacy caused by new surveillance tools and data gathering techniques, including also group privacy, high-tech profiling, automated decision making and discriminatory practices. In our society, everything can be given a score and critical life changing opportunities are increasingly determined by such scoring systems, often obtained through secret predictive algorithms applied to data to determine who has value. It is therefore essential to guarantee the fairness and accurateness of such scoring systems and that the decisions relying upon them are realised in a legal and ethical manner, avoiding the risk of stigmatisation capable of affecting individuals’ opportunities. Likewise, it is necessary to prevent the so-called ‘social cooling’. This represents the long-term negative side effects of the data-driven innovation, in particular of such scoring systems and of the reputation economy. It is reflected in terms, for instance, of self-censorship, risk-aversion and lack of exercise of free speech generated by increasingly intrusive Big Data practices lacking an ethical foundation. Another key ethics dimension pertains to human-data interaction in Internet of Things (IoT) environments, which is increasing the volume of data collected, the speed of the process and the variety of data sources. It is urgent to further investigate aspects like the ‘ownership’ of data and other hurdles, especially considering that the regulatory landscape is developing at a much slower pace than IoT and the evolution of Big Data technologies. These are only some examples of the issues and consequences that Big Data raise, which require adequate measures in response to the ‘data trust deficit’, moving not towards the prohibition of the collection of data but rather towards the identification and prohibition of their misuse and unfair behaviours and treatments, once government and companies have such data. At the same time, the debate should further investigate ‘data altruism’, deepening how the increasing amounts of data in our society can be concretely used for public good and the best implementation modalities.