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This paper aims to offer a tutorial/introduction to new statistics arising from the theory of optimal transport to empirical researchers in econometrics and machine learning.

Presenting in a tutorial/survey lecture style to help practitioners with the theoretical material.

The tutorial survey of some main statistical tools (arising from optimal transport theory) should help practitioners to understand the theoretical background in order to conduct empirical research meaningfully.

This study is an original presentation useful for new comers to the field.

This focal chapter deals with the understanding of important ethical theories used in executive moral reasoning such as teleology, deontology, distributive justice and corrective justice, virtue ethics versus ethics of trust, from the perspectives of intrinsic versus instrumental good, moral worth versus moral obligation, and moral conscience versus moral justification. Ethical and moral reasoning will power executives to identify, explore, and resolve corporate moral dilemma, especially in the wake of emerging gray market areas where good and evil, right or wrong, just or unjust, and truth and falsehood cannot be easily distinguished. We focus on developing corporate skills of awareness of ethical values and moral imperatives in current otherwise highly commoditized and turbulent human, market, and corporate situations. The challenges of morality are multifaceted and diverse. Professionals usually have self-discipline and self-regulation abilities, ego strength, and social skills. Morality in the professions is not concerned with the issues of rudimentary socialization; rather, the issues involve deciding between conflicting values, where each value represents something good in itself. There are problems in both knowing what is right, good, true, and just on the one hand, and on the other hand, in doing what is right and avoiding wrong, doing good and avoiding evil, and being fair and just while avoiding being unfair and unjust. Several contemporary cases will illustrate the challenging dimensions of ethical and moral reasoning, moral judgment and moral justification embedded in executive decision processes, and corporate growth and profitability ventures.

The purpose of this paper is to illustrate how game theoretic solution concepts inform what classes of problems will be amenable to artificial intelligence and machine learning (AI/ML), and how to evolve the interaction between human and artificial intelligence.

The approach addresses the development of operational gaming to support planning and decision making. It then provides a succinct summary of game theory for those designing and using games, with an emphasis on information conditions and solution concepts. It addresses how experimentation demonstrates where human decisions differ from game theoretic solution concepts and how games have been used to develop AI/ML. It concludes by suggesting what classes of problems will be amenable to AI/ML, and which will not. It goes on to propose a method for evolving human/artificial intelligence.

Game theoretic solution concepts inform classes of problems where AI/ML 'solutions' will be suspect. The complexity of the subject requires a campaign of learning.

Though games have been essential to the development of AI/ML, practitioners have yet to employ game theory to understand its limitations.

The alienation of megaproject environmental responsibility (MER) behavior is destructive, but its mechanism has not been clearly depicted. Based on fraud triangle theory and the fuzzy set qualitative comparative analysis (fsQCA) method, this study explored the combined effect of antecedent factors on alienation of MER behavior.

Based on the fraud triangle theory and literature review, eight influencing factors associated with the alienation of MER behavior were first identified. Subsequently, the fuzzy-set qualitative comparative analysis was used in this study to reveal configurations influencing alienation of MER behavior.

The study found nine configurations of MER behavioral alienation antecedent factors, integrated into three types of driving modes, i.e. “economic pressure + learning effect,” “institutional defect + moral rejection,” and “information asymmetry + economic pressure + expectation pressure.”

By analyzing the configuration effects of various induced conditions, this study puts forward a comprehensive analysis framework to solve the alienation of MER behavior in the megaprojects and a practical strategy to control alienation of MER behavior.

While studies about business-to-business (B2B) relationships have mainly addressed buyer–supplier long-term exchanges, focusing on social outcomes such as trust, commitment and cooperation, there is little research that explores the social outcomes which stem from short-term B2B transactions. The purpose of this paper is to explain buyers’ intention to renew a contract after discrete and time-delimited transactions by suggesting a model that complements social exchange theory with theories of fairness. In detail, this study aims to determine how evaluations of economic and social outcomes are complemented by both procedural fairness and distributive fairness.

The hypotheses are tested in the social couponing industry with a survey of a sample of 199 firms purchasing advertising services from daily deal websites. Data are analyzed using covariance-based structural equation modeling (CB-SEM).

The findings reveal direct effects of procedural fairness on social outcomes (satisfaction) and distributive fairness on the intention to renew a contract, negative moderating effect of procedural fairness on the relationship between economic outcomes (campaign effectiveness) and social outcomes (satisfaction).

In discrete, time-delimited transactions, high levels of procedural fairness may partially compensate for low levels of economic outcomes and prevent a reduction in social outcomes. Hence, when economic outcomes are influenced largely by external, uncontrollable conditions, the buyer seems to appreciate the supplier’s efforts to behave fairly.

Social outcomes matter even in discrete transactions and considerations of fairness should be integrated in the management of discrete transactions. Sharing economic outcomes fairly is not sufficient to secure the buyer’s intention to renew the contract.

This study proposes and tests a model that complements social exchange theory with theories of fairness and explains contract renewal in discrete, time-delimited transactions, encompassing both economic outcomes and social outcomes.

This study aims to investigate gamification-based training program through the lens of self-determination theory and in the context of corporate training programs. It integrates the self-determination theory, game elements and learning outcomes in gamified training programs to derive insights.

Data is sourced from software development companies operating in the city of Bangalore in India. It applies the partial least square structural equation modeling to investigate the relationship between the self-determination learning theory and game elements and the impact it has on learning outcomes.

As a precursor to the development of a game-like learning ecosystem, the authors study the perception of trainers and human resource managers toward game-based training programs in the organization. The authors find that game-based learning makes training more engaging, immersive and contextual for the learners.

The study is based on a specific sector, i.e. software development companies, and so the results may lack in generalizability. Future research, therefore, may consider other industrial sectors such as manufacturing, banking and telecom to understand the relationship between the constructs.

This study provides insights for the trainers, human resource managers and academicians on the effectiveness of gamification-based training programs. It also provides information on how the learning theory can be leveraged to understand gamification-based training programs.

This work fulfills an identified need of the training industry to understand new methods of training with an aim to improve the learning outcomes among the learners.

This study provides a deep understanding on the effectiveness of training tools such as gamified training programs in enhancing and improving the learning outcomes among the learners.

This paper examines the direct relationship between perceived corporate citizenship (CC) and purchase intention. This study also tests the mediating role of brand trust (BT), consumer–brand identification (CBI) and the moderating effect of personal norms and fear to coronavirus disease 2019 (COVID-19) by contributing social exchange theory (SET), brand relationship theory, social cognitive theory (SCT) and fear appeal theory.

Quantitative research was carried out by means of a survey with a sample of 411 regular consumers who work for national retail brands, where the unit of analysis was an individual. The study analysed the data to test the research hypotheses using SPSS and SMART partial least squares (PLS).

This study found a significant positive impact of perceived CC on purchase intention (direct path), and furthermore, a partial mediation was shown for the indirect approach. In addition, personal norms and fear to COVID-19 have a significant impact on the relationships between perceived CC on purchase intention, BT on purchase intention and CBI on purchase intention.

This study provides useful insights for managers to implement CC strategies to enhance consumer purchase intention and brand relationship in the retail sector within the COVID-19 pandemic.

The current study is perhaps the first to investigate the impact of perceived CC on purchase intention across BT, CBI, personal norms and fear to COVID-19 in the retail industry, period of COVID-19 pandemic. The study also makes some significant theoretical contributions and previously did not shed light on customer behaviour in this context.

This paper considers supply chain management organizations with the aid of 'chaotic systems theory' developed originally in physics and mathematics. Since innovations in supply chain management are vital for organizational survival 'complex systems theory' may assist in fine-tuning managerial philosophies that provide stability in supply chain management because it is on the boundary of chaos that the greatest innovational creativity occurs. Neither 'management by rigid objectives' (MBO) nor 'management by instruction' (MBI) will be suitable for the information society of the twenty-first century because chaotic social systems will no longer be effectively managed. However, the capacity for self-organization will be derived essentially from how supply chain management members accept a shared set of values or principles for action-'management by values' (MBV). Complex systems theory deals with systems that show complex structures in time or space, often hiding simple deterministic rules. This theory holds that once these rules are found, it is possible to make effective predictions and even to control the apparent complexity. The state of chaos that self-organizes is attributable to the appearance of the 'strange attractor' and provides the ideal basis for creativity and innovation in the twenty-first century. In the self-organized state of chaos, social members are not confined to narrow roles and gradually develop their capacity for differentiation and relationships, growing progressively towards their maximum potential contribution to the efficiency of the organization. In this meaning, values act as organizers of 'attractors' of disorder, which, in the theory of chaos, are systems represented by usually regular geometric configurations that predict the long-term behavior of complex systems. In supply chain management organizations (as in all kinds of social systems) the initial principles end up as the final principles in the long term. An attractor is a model representation of the behavioral results of the system. The attractor is not a force of attraction or a goal-oriented presence in the system; it simply depicts where the system is heading based on its rules of motion. In supply chain management organizations that cultivate or shares values of autonomy, responsibility, independence, innovation, creativity, and proactivity, the risk of short-term chaos is mitigated by external complexities that organizations are currently confronting. The strategy is to alter the supply chain management's surroundings so that they can benefit from management by values (MBV).

Combining the goal-setting and job demands-resources (JD-R) theories, we examine how two project resources, collaborative project leadership and financial project resources, enhance high project performance in community-academic health partnerships.

With a sequential explanatory mixed-method research design, data were collected through a survey (N = 318) and semi-structured interviews (N = 21). A hypothesised three-path mediation model was tested using structural equation modelling with bootstrapping. Qualitative data were examined using thematic analysis.

Project workers’ hope, goal-commitment and -stress: (1) fully mediate the hypothesised relationship between highly collaborative project leadership and high project performance; and (2) partially mediate the relationship between financial project resources and high project performance. The qualitative data corroborate and deepen these findings, revealing the crucial role of hope as a cognitive-motivational facilitator in project workers’ ability to cope with challenges.

Project leaders should promote project workers’ goal commitment, reduce their goal stress and boost project performance by securing financial project resources or reinforcing workers’ hope, e.g. by fostering collaborative project leadership.

The findings contribute to the project management and JD-R literature by considering the joint effects of project workers’ hope and two commonly studied project resources (collaborative project leadership and financial project resources) on high project performance. Moreover, we demonstrate the importance of the goal-setting and JD-R theories for understanding complex health-promotion projects connecting academic to community work.