Rulers of the world,unite! The challenges and opportunities of artificial intelligence

A decade ago, we published an article in Business Horizons about the challenges and opportunities of social media with a call to action: “Users of the world, unite!” To celebrate its anniversary, we look at artificial intelligence and the need to create the rules necessary for peaceful coexistence between humanity and AI. Hence, we now are urging: “Rulers of the world, unite!” In this article, we outline six debates surrounding AI in areas like artificial superintelligence, geographical progress, and robotics; in doing so, we shed light on what is fact and what is utopia. Then, using the PESTEL framework, we talk about the six dilemmas of AI and its potential threat and use. Finally, we provide six directions on the future of AI regarding its requirements and expectations, looking at enforcement, employment, ethics, education, entente, and evolution. Understanding AI’s potential future will enable governments, corporations, and societies at large (i.e., the rulers of this world) to prepare for its challenges and opportunities. This way, we can avoid a scenario in which we return in 10 years to write the article: “Dreamers of the world, unite!”     

Deposit AI as the “invisible hand” to make the resale easier: A moderated mediation model

While existing works pay little attention to price setters and the application of artificial intelligence (AI) agents in second-hand trading, the current research examines whether, and how, price setter (AI VS. seller)affects buyers' willingness to pay (WTP)in the case of second-hand trading on P2P platform. 25 interviews and 3 online studies have been conducted to demonstrate the results: (i) compared with goods priced by sellers, buyers are more willing to pay for goods priced by platform AI (Studies 1&2), (ii) buyers' perceived objectivity mediates the relationship between price setter and buyers' WTP (Study 2), (iii) perceived reductionistic of AI eliminates the effect of price setter on WTP (Study 3), and (iv) augmented intelligence (vs. AI)can have equal effect on buyers’ WTP (Study 4). These findings offer considerable implications for practitioners on how to build an AI pricing agent that is superior to humans on P2P second-hand trading platforms while ensuring the well-being of platform traders.     

Taking AIM at Theoretical and Pragmatic Impact: A Call for Actionable,Insightful, and Measurable Research

Ongoing debate surrounds the relative importance of theory and practice within supply chain research. Some contend that strong theory is central to knowledge advancement and its application to practice should be a secondary concern. Others argue that emphasizing theory moves the field away from its applied roots and the concerns of managers. We transcend this debate by proposing that theory and practice are separate dimensions rather than opposing concerns. Research projects can thus be strong in terms of both theory and practice, weak on both, or strong on one and weak on the other. We propose that placement within the first category requires scholars to devise research that is AIM—actionable (i.e., it provides a basis for making changes), insightful (it provides new ideas on important issues), and measurable (its effects can be quantitatively assessed). The impact of such research is magnified or dampened by the degree to which scholars achieve theoretical contextualization (i.e., adjusting the theory to reflect the setting under investigation) and theoretical calibration (i.e., alignment between theory and methods). Because “AIMing high” can deliver strong value for both scholars and managers, we encourage scholars, editors, and reviewers to embrace it in the development and evaluation of research.     

How artificial intelligence will affect the future of retailing

Artificial intelligence (AI) will substantially impact retailing. Building on past research and from interviews with senior managers, we examine how senior retailing managers should think about adopting AI, involving factors such as the extent to which an AI application is customer-facing, the amount of value creation, whether the AI application is online, and extent of ethics concerns. In addition, we highlight that the near-term impact of AI on retailing may not be as pronounced as the popular press might suggest, and also that AI is likely to be more effective if it focuses on augmenting (rather than replacing) managers’ judgments. Finally, while press coverage typically involves customer-facing AI applications, we highlight that a lot of value can be obtained by adopting non-customer-facing applications. Overall, we remain very optimistic as regards the impact of AI on retailing. Finally, we lay out a research agenda and also outline implications for practice.     

Sports Marketing

Although text messaging as a communication tool in society is rampant, research on its effects within print advertisements is lacking. To help fill this void, we employ three between-subject experiments (i.e., Study 1: text message vs. no text message; Studies 2 and 3: text message vs. traditional language). We posit that using text message copy in print ads is a unique (as grounded in distinctiveness theory) and fitting (as grounded in communication trust theory) approach to commune with targeted viewers and, therefore, should lead to favorable advertising outcomes. The experimental results confirm this notion. For example, responses concerning ad novelty, attention toward the ad, attitude toward the ad, purchase intention, and perceived brand trust are more favorable toward the text message condition ads. Implications and directions for future text message-related research are discussed.     

Machines augmenting entrepreneurs: Opportunities (and threats) at the Nexus of artificial intelligence and entrepreneurship

Artificial intelligence (AI) refers to machines that are trained to perform tasks associated with human intelligence, interpret external data, learn from that external data, and use that learning to flexibly adapt to tasks to achieve specific outcomes. This paper briefly explains AI and looks into the future to highlight some of AI's broader and longer-term societal implications. We propose that AI can be combined with entrepreneurship to represent a super tool. Scholars can research the nexus of AI and entrepreneurship to explore the possibilities of this potential AI-entrepreneurship super tool and hopefully direct its use to productive processes and outcomes. We focus on specific entrepreneurship topics that benefit from AI's augmentation potential and acknowledge implications for entrepreneurship's dark side. We hope this paper stimulates future research at the AI-entrepreneurship nexus.Executive summaryArtificial intelligence (AI) refers to machines that are trained to perform tasks associated with human intelligence, interpret external data, learn from that external data, and use that learning to flexibly adapt to tasks to achieve specific outcomes. Machine learning is the most common form of AI and largely relies on supervised learning—when the machine (i.e., AI) is trained with labels applied by humans. Deep learning and adversarial learning involve training on unlabeled data, or when the machine (via its algorithms) clusters data to reveal underlying patterns.AI is simply a tool. Entrepreneurship is also simply a tool. How they are combined and used will determine their impact on humanity. While researchers have independently developed a greater understanding of entrepreneurship and AI, these two streams of research have primarily run in parallel. To indicate the scope of current and future AI, we provide examples of AI (at different levels of development) for four sectors—customer service, financial, healthcare, and tertiary education. Indeed, experts from industry research and consulting firms suggest many AI-related business opportunities for entrepreneurs to pursue.Further, we elaborate on several of these opportunities, including opportunities to (1) capitalize on the “feeling economy,” (2) redistribute occupational skills in the economy, (3) develop and use new governance mechanisms, (4) keep humans in the loop (i.e., humans as part of the decision making process), (5) expand the role of humans in developing AI systems, and (6) expand the purposes of AI as a tool. After discussing the range of business opportunities that experts suggest will prevail in the economy with AI, we discuss how entrepreneurs can use AI as a tool to help them increase their chances of entrepreneurial success. We focus on four up-and-coming areas for entrepreneurship research: a more interaction-based perspective of (potential) entrepreneurial opportunities, a more activities-based micro-foundation approach to entrepreneurial action, a more cognitively hot perspective of entrepreneurial decision making and action, and a more compassionate and prosocial role of entrepreneurial action. As we discuss each topic, we also suggest opportunities to design an AI system (i.e., entrepreneurs as potential AI designers) to help entrepreneurs (i.e., entrepreneurs as AI users).AI is an exciting development in the technology world. How it transforms markets and societies depends in large part on entrepreneurs. Entrepreneurs can use AI to augment their decisions and actions in pursuing potential opportunities for productive gains. Thus, we discuss entrepreneurs' most critical tasks in developing and managing AI and explore some of the dark-side aspects of AI. Scholars also have a role to play in how entrepreneurs use AI, but this role requires the hard work of theory building, theory elaboration, theory testing, and empirical theorizing. We offer some AI topics that we hope future entrepreneurship research will explore. We hope this paper encourages scholars to consider research at the nexus of AI and entrepreneurship.     

A Code of Ethics for CorporateCode of Ethics

Are corporate codes of ethics necessarily ethical? To challenge this notion, an initial set of universal moral standards is proposed by which all corporate codes of ethics can be ethically evaluated. The set of universal moral standards includes: (1) trustworthiness; (2) respect; (3) responsibility; (4) fairness; (5) caring; and (6) citizenship. By applying the six moral standards to four different stages of code development (i.e., content, creation, implementation, administration), a code of ethics for corporate codes of ethics is constructed by which companies can be ethically audited for compliance. The newly proposed code of ethics for corporate codes of ethics was then applied to four large Canadian companies representing a variety of industries: telecommunications; banking, manufacturing, and high technology. The ethical audit of the four companies' ethics programs based on the proposed code indicates that all four companies have room to improve the ethical nature of their codes of ethics (i.e., content, creation, implementation, administration).     

Are religious consumers more ethical and less Machiavellian? A segmentation study of Millennials

Millennial consumers are increasingly becoming important actors in business that account for sufficient purchasing power. However, Millennials are infamously narcissistic and their views of ethics are more relaxed than previous generations (i.e., Baby Boomers, Generation X). Millennials remain poorly understood in general, especially in the context of developing countries. Hence, the purpose of this study was to profile this generation by segmenting Millennials in Indonesia and investigating differences between these segments on their ethical beliefs and Machiavellianism, an important personality characteristic. This study used a convenience sample from a university in Indonesia (N = 540). The TwoStep cluster analysis produced three segments, namely, “The Religious Millennials”, “The Lukewarm Religious Millennials” and “The Least Religious Millennials”. Consumers who are highly religious are less likely to engage in various unethical behaviours. Interestingly, no significant differences were found between The Lukewarm Millennials and The Least Religious Millennials on their ethical beliefs. This research makes several research contributions. First, this study extended the Hunt–Vitell theory of ethics, where an individual (i.e., Millennials) confronts a problem perceived as having ethical content. Second, the study examined consumer ethics in the context of developing countries where religion plays a significant role in people’s daily life. Third, through understanding different segments, the results assist educators, social marketers and public policy makers in creating an effective campaign to reduce unethical behaviour among Millennials.     

Black,white or grey magic? Our future with artificial intelligence

ABSTRACT

Are new technologies driving us towards dystopia or utopia – or something in between? Marketers not only have a stake in finding out the answer to this question but also a direct (and indirect) influence on determining the answer. This commentary discusses recent developments in artificial intelligence (AI) and robotics, and how these are influencing marketers, consumers and society by either leading to a dystopian (black magic), utopian (white magic) or ‘dualopian’ future (grey magic). We argue that the net effect is squarely in the grey and that marketers have a unique power to leverage AI and robotics developments for good. The commentary concludes with 24 research questions forming an agenda for future research under three streams: marketing power, understanding the bias and ethics revisited.     

Four Design Criteria for any Future Contractarian Theory of Business Ethics

This article assesses the quality of Integrative Social Contracts Theory (ISCT) as a social contract argument. For this purpose, it embarks on a comparative analysis of the use of the social contract model as a theory of political authority and as a theory of social justice. Building on this comparison, it then develops four criteria for any future contractarian theory of business ethics (CBE). To apply the social contract model properly to the domain of business ethics, it should be: (1) self-disciplined, i.e., not aspire results beyond what the contract model can realistically establish; (2) argumentative, i.e., it should seek to provide principles that are demonstrative results of the contractarian method; (3) task-directed, i.e., it should be clear what the social contract thought-experiment is intended to model; and (4) domain-specific, i.e., the contractarian choice situation should be tailored to the defining problems of business ethics.     

Corporate Governance, Ethics, and the Backdating of Stock Options

Backdating of stock options is an example of an agency problem. It has emerged despite all the measures (i.e., new regulations and additional corporate governance mechanisms) aimed at addressing such problems? Beyond such negative controlling measures, a more positive empowering approach based on ethics may also be necessary. What ethical measures need to be taken to address the agency problem? What values and norms should guide the board of directors in protecting the shareholders’ interests? To examine these issues, we first discuss the role values and norms can play with respect to underlying corporate governance and the proper role of directors, such as transparency, accountability, integrity (which is reflected in proper mechanisms of checks and balances), and public responsibility. Second, we discuss various stakeholder approaches (e.g., government, directors, managers, and shareholders) by which conflicts of interest (i.e., the agency problem) can be addressed. Third, we assess the practice of backdating stock options, as an illustration of the agency problem, in terms of whether the practice is legally acceptable or ethically justifiable. Fourth, we proceed to an analysis of good corporate governance practice involving backdating options based on a series of ethical standards including: (1) trustworthiness; (2) utilitarianism; (3) justice; and (4) Kantianism. We conclude that while executive compensation schemes (e.g., stock options) were originally intended to help remedy the agency problem by tying together the interests of the executives and shareholders, these schemes may have actually become “part of the problem,” and that the solution ultimately depends upon whether directors and executives accept that all of their actions must be based on a set of core ethical values.     

(Im)Balanced customer-oriented behaviors and AI chatbots' Efficiency–Flexibility performance: The moderating role of customers’ rational choices

Artificial intelligence (AI) based chatbots are increasingly deployed in frontline encounters, because they combine frontline service efficiency and flexibility. Using a large-scale data set with more than 130,000 man–machine dialogues from an e-bike sharing platform, Study 1 reveals a complex relationship between chatbots' customer-oriented behaviors and their efficiency–flexibility ambidexterity. Chatbots' level of efficiency–flexibility ambidexterity is higher when their functional and relational customer-oriented behaviors are balanced rather than imbalanced (i.e., a negative imbalance effect) and when they are balanced at a higher rather than a lower level (i.e., a positive balance effect). A follow-up experiment, Study 2, and online survey, Study 3, consistently show that the negative imbalance effect is stronger as customers' perceptions of non-personalization costs decrease and privacy concerns increase, while opportunity cost has no significant influence on the negative imbalance effect. However, consistent with rational choice theory, the positive balance effect is stronger as non-personalization costs increase, privacy concerns decrease, and opportunity cost decreases. In addition, Study 1 and 3 consistently show that in alignment with the stimulus–organism–response framework, efficiency–flexibility ambidexterity partially mediates the relationship between chatbots’ (im)balanced customer-oriented behaviors and customer patronage. This study contributes to the literature on frontline ambidexterity by introducing an AI application context and a more nuanced nonlinear view of the antecedents and consequences of frontline ambidexterity.     

Trust me,I'm an influencer! - Causal recipes for customer trust in artificial intelligence influencers in the retail industry

Prior examinations of relationship development and the leverage of trust among artificial intelligence (AI) influencers and followers have been few. This study employed complexity theory to understand the main causal recipes that can lead to high trust in AI influencers. Asymmetrical fuzzy set qualitative comparative analysis (fsQCA) was used to explore the recipes that can drive high customer trust. Data were collected from 683 consumers who are familiar with AI influencers in Saudi Arabia. Our findings indicated that no single factor is sufficient to drive trust in influencers, but five causal recipes were explored for their power to secure high levels of trust in AI influencers. The findings revealed that a configuration of source attractiveness (i.e., physical attractiveness, homophily), source credibility (i.e., authenticity, expertise) and congruences (i.e., influencer, product, consumer) act as driver of consumers' trust in an AI influencer. These results are useful for practitioners since they provide new methods for boosting trust in AI influencers.     

Examining artificial intelligence (AI) technologies in marketing via a global lens: Current trends and future research opportunities

Artificial intelligence (AI) has captured substantial interest from a wide array of marketing scholars in recent years. Our research contributes to this emerging domain by examining AI technologies in marketing via a global lens. Specifically, our lens focuses on three levels of analysis: country, company, and consumer. Our country-level analysis emphasizes the heterogeneity in economic inequality across countries due to the considerable economic resources necessary for AI adoption. Our company-level analysis focuses on glocalization because while the hardware that underlies these technologies may be global in nature, their application necessitates adaptation to local cultures. Our consumer-level analysis examines consumer ethics and privacy concerns, as AI technologies often collect, store and process a cornucopia of personal data across our globe. Through the prism of these three lenses, we focus on two important dimensions of AI technologies in marketing: (1) human–machine interaction and (2) automated analysis of text, audio, images, and video. We then explore the interaction between these two key dimensions of AI across our three-part global lens to develop a set of research questions for future marketing scholarship in this increasingly important domain.     

Corporate Governance,Ethics, and the Backdating of Stock Options

Backdating of stock options is an example of an agency problem. It has emerged despite all the measures (i.e., new regulations and additional corporate governance mechanisms) aimed at addressing such problems? Beyond such negative controlling measures, a more positive empowering approach based on ethics may also be necessary. What ethical measures need to be taken to address the agency problem? What values and norms should guide the board of directors in protecting the shareholders’ interests? To examine these issues, we first discuss the role values and norms can play with respect to underlying corporate governance and the proper role of directors, such as transparency, accountability, integrity (which is reflected in proper mechanisms of checks and balances), and public responsibility. Second, we discuss various stakeholder approaches (e.g., government, directors, managers, and shareholders) by which conflicts of interest (i.e., the agency problem) can be addressed. Third, we assess the practice of backdating stock options, as an illustration of the agency problem, in terms of whether the practice is legally acceptable or ethically justifiable. Fourth, we proceed to an analysis of good corporate governance practice involving backdating options based on a series of ethical standards including: (1) trustworthiness; (2) utilitarianism; (3) justice; and (4) Kantianism. We conclude that while executive compensation schemes (e.g., stock options) were originally intended to help remedy the agency problem by tying together the interests of the executives and shareholders, these schemes may have actually become “part of the problem,” and that the solution ultimately depends upon whether directors and executives accept that all of their actions must be based on a set of core ethical values.     

A Model of Business Ethics

It appears that in the 30 years that business ethics has been a discipline in its own right a model of business ethics has not been proffered. No one appears to have tried to explain the phenomenon known as ?business ethics’ and the ways that we as a society interact with the concept, therefore, the authors have addressed this gap in the literature by proposing a model of business ethics that the authors hope will stimulate debate. The business ethics model consists of three principal components (i.e. expectations, perceptions and evaluations) that are interconnected by five sub-components (i.e. society expects; organizational values, norms and beliefs; outcomes; society evaluates; and reconnection). The introduced model makes a contribution to the creation of a conceptual framework for business ethics. A few tentative conclusions may be drawn from the introduced model of business ethics. The model aspires to be highly dynamic. The ultimate outcome is dependent upon the evolution of time and contexts. It is also dependent upon and provides reference to the behaviours and perceptions of people. The model proposes business ethics to be a continuous and an iterative process. There is no actual end of the process, but a constant reconnection to the initiation of successive process iterations of the business ethics model. The principals and sub-components of the model construct the dynamics of this continuous process. They provide guidance on what and how to explore our common efforts to understand the phenomenon known as business ethics. The model provides opportunities for further research in the field of business ethics.     

The Influence of Business Ethics Education on Moral Efficacy,Moral Meaningfulness,and Moral Courage: A Quasi-experimental Study

The research described here contributes to the extant empirical research on business ethics education by examining outcomes drawn from the literature on positive organizational scholarship (POS). The general research question explored is whether a course on ethical decision-making in business could positively influence students’ confidence in their abilities to handle ethical problems at work (i.e., moral efficacy), boost the relative importance of ethics in their work lives (i.e., moral meaningfulness), and encourage them to be more courageous in raising ethical problems at work even if it is unpopular (i.e., moral courage). Specifically, the study used a rigorous quasi-experimental pretest–posttest research design with a treatment (N = 30) and control group (N = 30) to investigate whether a graduate-level course in business ethics could influence students’ levels of moral efficacy, meaningfulness, and courage. Findings revealed that participants in the business ethics treatment course experienced significant positive increases in each of the three outcome variables as compared to the control group. The largest increase was in moral efficacy, followed by moral courage, and finally, moral meaningfulness. These findings are discussed in the context of the current research on business ethics education and POS. Implications for future research are discussed.     

Qur’anic Ethics for Environmental Responsibility: Implications for Business Practice

Despite the growing interest in examining the role of religious beliefs as a guide towards environmental conscious actions, there is still a lack of research informed by an analysis of divine messages. This deficiency includes the extent to which ethics for environmental responsibility are promoted within textual divine messages; types of environmental themes promoted within the text of divine messages; and implications of such religious environmental ethics for business practice. The present study attempts to fill this gap by conducting a thorough content analysis of environmental themes within the divine message of Muslims (the Qur’an) focusing on their related ethical aspects and business implications. The analysis has revealed 675 verses in 84 chapters throughout all 30 parts of the Qur’an, with environmental content relating to the core components of the natural world, i.e. human beings, water, air, land, plants, animals, and other natural resources. This environmental content and its related ethics are grounded on the belief that humans are vicegerents of God on the earth and their behaviours and actions are motivated by earthly and heavenly rewards. Implications of these findings for different sectors/businesses are also highlighted.     

“Don't try to teach me,I got nothing to learn”: Management students' perceptions of business ethics teaching

Interest is growing towards including business ethics in university curricula, aiming at improving ethical behaviour of future managers. Extant literature has investigated the impact of ethics education on different ethics‐related students' cognitive and/or behavioural outcomes, considering variables related to training programmes and students' demographic aspects. Accordingly, we aim at assessing students' understanding of business ethics issues, by focusing on the differences in students' perceptions depending on gender, age, work experience, and ethics courses taken. Testing our hypotheses on a sample of 307 management students at a Polish university, and controlling for social desirability bias, we obtained mixed and partially surprising results. We found significant differences in students' understanding of business ethics depending on their gender and age (female and older students showed more ethical inclinations), but not depending on having taken ethics courses—actually perceptions of such courses worsened after taking them. Besides, work experience was not a significant variable. Moreover, course exposure intensiveness (i.e., number of ethics courses completed), and time passed since completion of the latest course, did not confirm hypothesized effects on most of the dependent (sub)variables. These findings stimulate further questions and challenges for future research (e.g., around course design and methodology, and social/cultural/contextual issues).