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In Chapter 1, we critically reviewed the foundations of the free enterprise capital system (FECS), which has been successful primarily because of its wealth and asset accumulation potentiality and actuality. In this chapter, we critically argue that this capacity has been grounded upon the profit maximization (PM) theories, models, and paradigms of FECS. The intent of this chapter is not anti-PM. The PM models of FECS have worked and performed well for more than 200 years of the economic history of the United States and other developed countries, and this phenomenon is celebrated and featured as “market performativity.” However, market performativity has not truly benefitted the poor and the marginalized; on the contrary, market performativity has wittingly or unwittingly created gaping inequalities of wealth, income, opportunity, and prosperity. Critical thinking does not combat PM but challenges it with alternative models of profit sharing that promote social wealth, social welfare, social progress, and opportunity for all, which we explore here. Economic development without social progress breeds economic inequality and social injustice. Economic development alone is not enough; we should create a new paradigm in which economic development is the servant of social progress, not vice versa. Such a paradigm shift involves integrating the creativity and innovativity of market performativity and the goals and drives of social performativity together with PM, that is, from market performativity to social performativity.

Using social relations theory, we argue that entrepreneurship ecosystems must also include relationships such as market pricing, equality matching, authority ranking and communal sharing to be successful and thrive.

We theorize using Fiske’s typology that a successful entrepreneurial system must have certain characteristics to be successful.

In doing so, we suggest an alternative perspective of the role of exchange relationships in ecosystems which considers both the geographic context and social relationships as equally important ecosystem components. Our contributions include (1) exposing social processes as the explanatory mechanism for exchanges instead of solely market forces, (2) illustrating the role of regional cultural differences in exchanges and (3) emphasizing how entrepreneurs can better realize ecosystem benefits through understanding the methods of exchange in these ecosystems.

Social relationships include a wide variety of different types of resources and exchange mechanisms, so by their inclusion into the entrepreneurship ecosystem literature, a more complete view of ecosystems is possible.

This study aims to investigate the predictive role of team personality composition in facilitating shared leadership through team member exchange (TMX), while also to examine the moderating effect of organizational culture.

The authors conducted a two-stage online survey and selected the customer service teams, claims teams and financial teams of 26 Chinese insurance companies as the research samples. The authors finally obtained validated questionnaires from 107 teams with 457 members. The hypothesized relationships were tested using SPSS 25.0 and Mplus.

The results indicate that both team relationship-oriented and task-oriented personality composition have significant positive effects on shared leadership with team-member exchange serving as a full mediator for both paths. As a boundary condition, organizational culture (i.e. including internal integration values and external adaptation values) has a moderating effect on the influence of TMX on shared leadership.

The study investigates the predictive role of team personality composition on shared leadership, which complements the empirical studies of shared leadership antecedents in the literature. Drawing on social exchange perspective, the authors find out that TMX serves as a mediator between team personality composition and shared leadership. The authors also identify the moderating effect of organizational culture on the emergence of shared leadership. The research emphasizes the contextual boundary condition in this process.

The purpose of this paper is to explore a new approach to solve the problem of positive and negative offset in the calculation process of integral elements, then propose a series of new grey relational degree model for cross sequences.

The definitions of cross sequences and area elements have been proposed at first. Then the concept of difference degree between sequences has been put forward. Based on the definition of difference degree between sequences, various modified grey relational degree models for cross sequences have been proposed to solve the measurement problem of cross sequence correlation relationships.

(1) The new definition of cross sequences; (2) The area element; (3) Various modified grey relational degree models for cross sequences based on the definition of difference degree between sequences.

The grey relational analysis model of cross sequences is a difficult problem in grey relational analysis. The new model proposed in this article can effectively avoid the calculation deviation of grey relational analysis model for cross sequences, and reasonably measure the correlation between cross sequences. The new model was used to analyse the food consumer price index in Shaanxi Province, clarifying the relationship between different types of food consumer price indices, some interesting results that are not completely consistent with general economic theory were obtained.

The new definition of cross sequences, the area element and various modified grey relational degree models for cross sequences were proposed.

Aim to the limitations of grey relational analysis of interval grey number, based on the generalized greyness of interval grey number, this paper tries to construct a grey angle cosine relational degree model from the perspective of proximity and similarity.

Firstly, the algorithms of the generalized greyness of interval grey number and interval grey number vector are given, and its properties are analyzed. Then, based on the grey relational theory, the grey angle cosine relational model is proposed based on the generalized greyness of interval grey number, and the relationship between the classical cosine similarity model and the grey angle cosine relational model is analyzed. Finally, the validity of the model in this paper is illustrated by the calculation examples and an application example of related factor analysis of maize yield.

The results show that the grey angle cosine relational degree model has strict theoretical basis, convenient calculation and is easy to program, which can not only fully utilize the information of interval grey numbers but also overcome the shortcomings of greyness relational degree model. The grey angle cosine relational degree is an extended form of cosine similarity degree of real numbers. The calculation examples and the related factor analysis of maize yield show that the model proposed in this paper is feasible and valid.

The research results not only further enrich the grey system theory and method but also provide a basis for the grey relational analysis of the sequences in which the interval grey numbers coexist with the real numbers.

The paper succeeds in realizing the algorithms of the generalized greyness of interval grey number and interval grey number vector, and the grey angle cosine relational degree, which provide a new method for grey relational analysis.

This study aims to capture how the association between a multichannel relational communication strategy (MRCS) and customer performance is contingent upon such customer performance (low- versus high-performance customers) and to reconcile past contradictory results in this marketing-related topic. To this end, the authors propose and validate the method of quantile regression as an unconventional, yet effective, means to proceed to that reconciliation.

This study collected data from 4,934 customers of a private pension fund firm and accounted for both firm- and customer-initiated relational communication channels (RCCs) and for customer lifetime value (CLV). This study estimated a generalized linear model and then a quantile regression model was used to account for customer performance heterogeneity.

This study finds that specific RCCs present different levels of association with performance for low- versus high-performance customers, where outcome customer performance is the dependent variable. For example, the relation between firm-initiated communication (FIC) and performance is stronger for low-CLV customers, whereas the relation between customer-initiated communication (CIC) and performance is increasingly stronger for high-CLV customers but not for low-CLV ones. This study also finds that combining different forms of FIC can result in a negative association with customer performance, especially for low-CLV customers.

The authors tested the conceptual model in one single firm in the specific context of financial services and with cross-sectional data, so there should be caution when extrapolating this study’s findings.

This study offers nuanced and precise managerial insights on recommended resource allocation along with relational communication efforts, showing how managers can benefit from adopting a differentiated-customer performance approach when designing their MRCS.

This study provides an overview of the state of the art of MRCS, proposes a contingency analysis of the relationship between MRCS and performance based on customer performance heterogeneity and suggests the quantile method to perform such analysis and help reconcile past contradictory findings. This study shows how the association between RCCs and CLV varies across the conditional quantiles of the distribution of customer performance. This study also addresses a recent call for a more holistic perspective on the relationships between independent and dependent variables.

Drawing upon theories of conservation of resources (COR), broaden-and-build (BnB), self-determination, and the job demands- resources (JD-R) model, this study uniquely tries to understand the mechanisms that contribute to happiness at work by proposing a model of the effects of emotional culture of joy on happiness at work, where psychological safety and relational attachments serve as intervening mechanisms among the aforesaid relationship.

A three-wave time-lagged study with 340 employees from Pakistani organizations was conducted. Data were analyzed using covariance-based structural equation modelling.

The results indicate that emotional culture of joy significantly predicts happiness at work. Furthermore, emotional culture of joy significantly and positively influences both psychological safety and relational attachment. Finally, the relationship between emotional culture of joy and happiness at work is found to be mediated by both relational attachment and psychological safety.

The results are of utmost importance as they provide insights to policy makers and organizations administrators on the value of emotional culture of joy and its contribution to employees’ wellbeing, and indeed its role in fostering important psychological and emotional resources such as psychological safety and relational attachment.

This study is unique for the following reasons. First, it addresses and bridges a gap pertaining to the drivers of happiness at work. Second, this is the first study that considers emotional culture of joy as an antecedent to happiness at work. Third, the employment of both psychological safety and relational attachment as intervening mechanisms in the relationship between emotional culture of joy and happiness at work has not been previously addressed in the management and wellbeing literature. Finally, the study shifts direction from studying organizational drivers (i.e. HR, organization support, etc.) of happiness at work to the examination of psychological and emotional resources that may influence happiness at work.