基于演化博弈的企业知识型员工激励机制研究

调动知识型员工的积极性、使之在企业发展中发挥更大作用,是现代人力资源管理的重要方面,也是提升企业综合竞争力、实现企业长远发展的关键。文章运用演化博弈理论,建立了以企业以及知识型员工为基本博弈主体的演化博弈模型;通过对演化博弈系统的局部稳定性分析及各因素变量对博弈双方演化行为的影响分析,提出了可能的控制方法。     

Dynamic learning in behavioral games: A hidden Markov mixture of experts approach

Over the course of a repeated game, players often exhibit learning in selecting their best response. Research in economics and marketing has identified two key types of learning rules: belief and reinforcement. It has been shown that players use either one of these learning rules or a combination of them, as in the Experience-Weighted Attraction (EWA) model. Accounting for such learning may help in understanding and predicting the outcomes of games. In this research, we demonstrate that players not only employ learning rules to determine what actions to choose based on past choices and outcomes, but also change their learning rules over the course of the game. We investigate the degree of state dependence in learning and uncover the latent learning rules and learning paths used by the players. We build a non-homogeneous hidden Markov mixture of experts model which captures shifts between different learning rules over the course of a repeated game. The transition between the learning rule states can be affected by the players?? experiences in the previous round of the game. We empirically validate our model using data from six games that have been previously used in the literature. We demonstrate that one can obtain a richer understanding of how different learning rules impact the observed strategy choices of players by accounting for the latent dynamics in the learning rules. In addition, we show that such an approach can improve our ability to predict observed choices in games.     

Breaking the Rules: Examining the Facilitation Effects of Moral Intensity Characteristics on the Recognition of Rule Violations

This research project seeks to discover whether certain characteristics of a moral issue facilitate individuals’ abilities to detect violators of a conditional rule. In business, conditional rules are often framed in terms of a social contract between employer and employee. Of significant concern to business ethicists is the fact that these social contracts are frequently breached. Some researchers in the field of evolutionary psychology argue that there is a biological basis to social contract formation and dissolution in business. However, although it is inescapable that biological forces shaped a fixed neural structure that guides and limits humans’ abilities, we argue that characteristics of the situation in which the person finds himself or herself moderate the activation of these neural circuits in ordinary business social contract situations. Specifically, the moral intensity associated with the social contract conditional rule is likely to influence peoples’ abilities to detect violators of the rule. This study utilizes adapted versions of the Wason selection task and manipulates the issue-contingent moral intensity characteristics of magnitude of consequences, proximity, and social consensus to assess if moral intensity facilitates detection of rule violators. Results from this empirical study indicate no relationship between moral intensity characteristics and issue recognition but do provide insights into the evolutionary psychology approach. David M. Wasieleski is an Assistant Professor in the Leadership and Change Management Division of the A.J. Palumbo School of Business Administration and the John F. Donahue Graduate School of Business at Duquesne University. He received his Ph.D. from the University of Pittsburgh. David’s recent research focuses on individuals’ biological propensity for ethical behavior and its effect on workplace relationships. His other research interests include moral intensity, cognitive moral development, stakeholder agenda-building, and policy learning. Sefa Hayibor is an Assistant Professor of Management in the Sobey School of Business at Saint Mary’s University (Canada). He received his Ph.D. from the University of Pittsburgh. His research interests include business ethics and ethical decision-making, stakeholder motivation and management, charismatic leadership, and cognitive heuristics and biases.     

Identifying emergence process of group panic buying behavior under the COVID-19 pandemic

The sudden COVID-19 caused frequent incidents of large-scale material panic buying, resulting in imbalance in supply and demand of goods and threatening social stability. It is of great significance to analyze the formation of group panic buying and help alleviate such action. This paper takes the panic buying phenomenon as the research target, quantifies the internal and external factors affecting individual buying behavior, restores the selection process of individual buying behavior, and constructs the emergence model of group panic buying behavior by using the idea of cluster dynamics. Through simulations, we find that: (1) The epidemic information intensity has a significant impact on the emergence of group rush buying behavior. (2) Government intervention plays a significant role in reducing the scale of group rush buying. Besides, the effects of intervention reach the best before people who do not participate in rush buying disappear. In addition, we also discuss the impact, limitations and future research directions.     

Best seller!? Unintended negative consequences of popularity signs on consumer choice behavior

Popularity signs (e.g., “best seller”, “top rated”) are frequently employed by marketers to help consumers in their purchase decisions. Whereas extant research focused mostly on the positive aspects of such a strategy, we demonstrate that it can also have adverse effects on consumer post-choice behavior. Depending on consumer regulatory orientation, such popularity signs can make the decision task more complex and increase feelings of uncertainty. The results of seven studies, including real choice decisions and field data, show that the provision of popularity signs can have negative consequences on consumers with a prevention (vs. promotion) focus by increasing the heterogeneity of their consideration set, which in turn is associated with an increase in choice uncertainty and a decrease in choice commitment. Beyond their theoretical significance, our findings shed novel light on the ways to implement popularity signs for a more efficiently targeted marketing effort.     

Augmenting discrete-choice data to identify common preference scales for inter-subject analyses

Discrete-choice experiments are commonly used to measure subjects?? preference structures and are often preferred to other measurement methods because they better align with actual choice behavior and avoid some of the well-documented biases inherent in alternative elicitation methods. A limitation of discrete-choice methods is the loss of inter-subject comparability because preference estimates are invariant to linear transformations necessitating indentifying constraints that remove a common, between-subjects utility scale. This constraint limits the application of discrete-choice results to situations where within-subject comparisons are meaningful. They enable one to sort options for each subject but not to sort subjects according to the relative intensity of their preferences. This paper uses auxiliary data to recover a common preference scale for between-subject comparisons. The model combines discrete-choice data with ratings data while adjusting for response biases due to method effects. The joint model moves the identification constraints from the sub-model for the discrete-choice data to the sub-model for the ratings data. The proposed methodology is complementary to willingness-to-pay computations when studies lack price or its economic foundation is untenable.     

Evolutionary game-theoretic model for dynamic congestion pricing in multi-class traffic networks

This paper describes an evolutionary game-theoretic learning model for dynamic congestion pricing in urban road networks, taking into account route choice stochasticity and reliability considerations, and the heterogeneity of users, in terms of their value of travel time and real-time information acquisition. The learning model represents the dynamic adjustments of users to travel cost changes which may take place in the day-to-day as well as the within-day timescales. The implementation into a simplified and a real urban road network signifies the important implications of modeling the dynamic and stochastic learning components of users’ behavior for accommodating the efficient deployment of congestion pricing schemes.     

三方博弈情景下品牌真实性的提升策略研究

为了研究品牌真实性的提升,通过构建政府、企业、消费者的三方博弈模型,分析提升品牌真实性的过程中博弈主体各方的变量影响关系、策略选择,并用Matlab模拟仿真三方博弈行为的相互演化过程。研究发现,在监督、惩罚、品牌价值提升等因素的作用下,当公众参与水平较高且达到一定水平时,会推动政府及企业积极实施品牌真实性策略,博弈主体三方的策略选择在演化过程中彼此相互影响。     

Evolution of retail formats: Past,present, and future

In this paper, the authors review current literature on retail formats and propose a new customer-centric framework for retailers to focus on as they continue to innovate and evolve. Specifically, they review the literature on how formats compare in their attributes and compete with each other; the role of customer behavior in format choice; and developments in multichannel and omnichannel retailing. They propose a framework for retail formats suggesting two paths – either reduce friction in the customer journey or enhance customer experience. They discuss the challenges faced by offline (physical store-first) and online (digital-first) retailers and elaborate on strategies each type of retailer is pursuing to address these challenges. Finally, they offer directions for future research in this domain. They conclude by calling for newer digital-first and physical-first players to continue coming up with different customer-centric formats, which they predict will slowly morph into integrated retailers, leaving space for newer players to enter the market and hence keep the wheel of retailing spinning.     

基于证据源和组合规则双修正的证据合成

针对冲突证据合成时传统证据合成和单一修正改进方法存在的问题，提出了新的证据源预处理和组合规则双修正的证据合成方法。利用夹角余弦理论，计算证据向量距离后转化得到权重系数，依据权重系数对证据进行重新概率分配，完成证据源修正；之后用修正的动态合成规则，进行修正证据的合成;同时提出了算法分析模型。实例结果验证了算法在证据合成时具有最优结果、较强通用性和稳定性，可应用于信息融合、不确定信息决策等领域。     

A new perspective on “the new rule”of the current account

In an influential series of contributions, Kraay and Ventura (2000, 2003) offer a “new rule” for the current account: in response to a temporary income shock, the change in the current account is equal to the change in saving times the ratio of net foreign assets to wealth. We analyze the impact of a temporary income shock on the current account in the context of a two-country dynamic general equilibrium model of portfolio choice and show that the new rule does not hold. We also show that the cross-section evidence reported by Kraay and Ventura in favor of the new rule is a feature implied by the steady state of the model that is conceptually distinct from the new rule. We argue that the new rule could only hold in a model with one-way capital flows (only inflows or outflows, but not both), a feature that is strongly counterfactual.     

Market entry into new export markets: When are firms more likely to imitate their competitors’ market presence?

We investigate the extent to which competitors’ presence in a given export market has an impact on a firm's decision to enter such a market and, more precisely, under what conditions imitation is more likely to take place. We show that firms with greater export knowledge are more likely to enter those countries where their competitors are already present. Furthermore, experiential knowledge seems necessary to absorb valuable information provided by the presence of competitors in those markets. Thus, imitation should not be regarded as the option best suited for firms with reduced expertize that follow blindly their competitors into new markets. Through a panel analysis of Brazilian exporters during the 2001–11 period, our study contributes to research on market entry decisions, especially stressing the critical role of prior relevant knowledge in facilitating imitation among players.     

劳动者与厂商互动区位选择均衡分析——基于技术扩散的微观基础

技术扩散模型一直是区域经济研究的一个重要方面,但是已有模型均缺乏微观经济基础。通过对劳动者和厂商最大化行为的研究,建立了互动区位选择模型,结果表明劳动者为选择最优居住区位而流动进入企业引起的技术扩散将影响厂商的区位选择。     

Pride in my past: Influencing sustainable choices through behavioral recall

Emotional appraisal research has demonstrated that recalling a past behavior and its associated emotions can influence future behavior. However, how such recalled emotions shape sustainable consumer choice has not been examined. This study examines the role of recalled pride and guilt in shaping sustainable purchase intentions and the mediating role of anticipated pride and guilt. A conceptual model is proposed for motivating sustainable purchase intentions through the emotions associated with the behavioral recall. The model is applied in two experiments with online consumers examining purchase intentions of low carbon cars. Recalling feelings of pride associated with a past sustainability‐related behavior increases sustainable purchase intention, as compared with a neutral recall. This effect occurs through the mediation of both anticipated pride at the prospect of a sustainable behavior choice and anticipated guilt if the future choice is not sustainable. Similar hypotheses relating to recalled guilt at past unsustainable behavior were not supported. The study contributes to research on sustainable consumption, revealing an emotional route by which past behavior can influence future behavior. It also adds to emotional appraisal research by showing the role of specific self‐conscious emotions in forming this route, as prior research has focused more broadly on emotional valence.     

Empathic cultural consumers: Pay what you want in the theater

Pay what you want (PWYW) is an increasingly popular sales strategy in which consumers voluntarily decide how much to pay for a product or service. PWYW has often been described as an exercise in the “empathy economy,” where consumers' payment choices might be seen as empowered expressions of their tastes and preferences, and sellers have a stronger incentive for empathizing with them. Beyond their economic interest, PWYW experiences also deserve significant attention in the social sciences given that they challenge several key assumptions of rational choice and neoclassical economic theory, as well as conventional consumer behavior and pricing theories. This paper analyzes three plays performed at the Beckett Theater in Barcelona using PWYW with very profitable outcomes. Our analysis shows that socio-psychological factors, such as payments attributed to others and satisfaction with the play, are the best predictors of customer payments.     

Navigating imposed innovation: A decision-making framework

Modern economies are characterized by the rising role of nonmarket actors (e.g., regulatory agencies, social activists, labor unions, media) that are gaining influence over the behavior of for-profit firms. These nonmarket stakeholders use their clout over industry players to impose innovations that require costly changes in business practices or technological trajectories while lacking firm-level economic justification. How should a company respond when it is pressured to adopt a new practice or change its products, while the economic calculations suggest that this is going to be a pure cost? Our study suggests alternative strategic responses to imposed innovation pressures and explores the factors determining the choice of an optimal strategy. Grounding the argument on the outside-in approach to pursuing imposed innovations, we propose a framework of organizational responses to external pressures to innovate, with varying degrees of firm engagement and different levels of cooperation with other industry actors. We also present a decision tree approach, allowing organizational decision makers to analyze the contextual determinants and ultimately arrive at the most appropriate, context-determined strategy.     

Coevolution of home country support and internationalization of emerging market firms

This study explores the role of diverse home country support for the internationalization of emerging market firms through a coevolutionary approach. A coevolutionary approach can improve our understanding of the complexities of comprehensive institutional transition in emerging market economies which allows firms to adapt and leverage institutional support for internationalization. Based on institutional theory and the strategic choice perspective, we present a coevolutionary model of mutualism and competition among businesses, government officials and industry players through multidirectional interactions. Our research offers an alternative and nuanced explanation of selective and relevant home country support, the role of independence of firms, support criteria and reinforcement of governance for internationalization of emerging market firms. This study contributes to the literature of home country support for internationalization through an enrichment of the institutional framework and strategic choice with a political perspective.     

When do B2B brands influence the decision making of organizational buyers? An examination of the relationship between purchase risk and brand sensitivity

The dominant perspective on organizational buying behavior suggests that buyers tend to rely on objective criteria when making product choice decisions and that the potential influence of subjective cues, such as brands, on buyer decision making decreases with increasing risk. An alternative perspective, confirmed in this study by in-depth interviews with various managers, suggests that brands serve as a risk-reduction heuristic, whereby the influence of brands on decision making increases as a function of risk. Building on risk and information processing theories, this research builds on these complementary perspectives to propose that risk and brand sensitivity relate in a U-shaped manner, where brand sensitivity is highest in relatively low- or high-risk situations. The results of scenario- and survey-based field studies—involving 206 and 180 members of buying centers, respectively—suggest that both perspectives have merit and support the proposed nonlinear relationship. Moreover, the findings reveal that the risk-brand sensitivity relationship is moderated by competitive intensity, such that the linear (negative) and quadratic (positive) effects are stronger when competitive intensity is low.     

Overcoming data limitations for store choice modelling.: Exploiting retail chain choice data by means of aggregate logit models

This paper reports on research aimed at exploiting certain data sources for store choice modelling purposes. Many databases, such as some consumer panels, only record the firm chosen by consumers and not the specific store at which they shop. Four alternative approaches are proposed in order to use this raw information for studying patronage determinants at store level: (a) an ordinary logit model in which chain utility is averaged across stores within; (b) an ordinary logit model in which the choice set is assumed to be composed of the nearest store for each chain; (c) a straightforward application of an aggregate logit model; and (d) the application of an aggregate logit model with choice sets spatially bounded by a distance threshold representing the maximum distance that consumers are willing to travel for shopping. The models are empirically tested in the context of spatial choice behaviour. Goodness of fit indicators reveal that only models (b), (c) and (d) acceptably represent competitive interaction dynamics. As performance of (b) is slightly better than that of (c), it seems that a priori the ‘nearest store assumption’ is a better approach than the modelling of aggregate choice structures. However, when the latter approach is applied with more reliable choice sets, as suggested in model (d), the best performance is achieved. The results thus lead us to think that the aggregate logit model is a promising methodology for solving the problem at issue, but subject to an appropriate definition of the consumers’ choice sets. In fact, such an approach provides a more suitable modelling solution to the extent that the saturation and the intra-firm store heterogeneity become more intense, because these situations presumably imply that consideration sets include several stores from the same chain.     

Allocating Profit Among Rational Players in a Fuzzy Coalition: A Game Theoretic Model

In this paper, the problem of allocation of the profit, obtained from a fuzzy coalition, among its players is considered. It is argued that this allocation is influenced by satisfaction of the players in regards to better performance and success within a cooperative endeavour. Our model is based on the real life situations, where possibly one or more players compromise on their payoffs in order to help forming a coalition. We have developed a dynamic approach to obtain a suitable solution to the corresponding cooperative fuzzy game. Further, the notion of a penalty among the bargaining players is introduced. This would inflict them to reasonable demands only.