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The purpose of this study to improve the efficiency of customer acquisition and retention through the design of salary information disclosure mechanism.

This study develops a stylized game-theoretic model of delegating customer acquisition and retention, focusing on how firms choose delegation and wage information disclosure strategy.

The results confirm the necessity for enterprises to disclose salary information. When sales agents are risk neutral, firms should choose multi-agent (MA) delegation and disclose their wages. However, when agents are risk averse, firms may disclose the wages of acquisition agents or both agents in MA delegation, depending on the uncertainty of the retention market.

This paper contributes to the literature on delegation of customer acquisition and retention and demonstrates that salary disclosure can be used as a supplement to the incentive mechanism.

We attempt to construct a grey three-way conflict analysis model with constraints to deal with correlated conflict problems with uncertain information.

In order to address these correlated conflict problems with uncertain information, considering the interactive influence and mutual restraints among agents and portraying their attitudes toward the conflict issues, we utilize grey numbers and three-way decisions to propose a grey three-way conflict analysis model with constraints. Firstly, based on the collected information, we introduced grey theory, calculated the degree of conflict between agents and then analyzed the conflict alliance based on the three-way decision theory. Finally, we designed a feedback mechanism to identify key agents and key conflict issues. A case verifies the effectiveness and practicability of the proposed model.

The results show that the proposed model can portray their attitudes toward conflict issues and effectively extract conflict-related information.

By employing this approach, we can provide the answers to Deja’s fundamental questions regarding Pawlak’s conflict analysis: “what are the underlying causes of conflict?” and “how can a viable consensus strategy be identified?”

This paper aims to study the agent learning from expert demonstration data while incorporating reinforcement learning (RL), which enables the agent to break through the limitations of expert demonstration data and reduces the dimensionality of the agent’s exploration space to speed up the training convergence rate.

Firstly, the decay weight function is set in the objective function of the agent’s training to combine both types of methods, and both RL and imitation learning (IL) are considered to guide the agent's behavior when updating the policy. Second, this study designs a coupling utilization method between the demonstration trajectory and the training experience, so that samples from both aspects can be combined during the agent’s learning process, and the utilization rate of the data and the agent’s learning speed can be improved.

The method is superior to other algorithms in terms of convergence speed and decision stability, avoiding training from scratch for reward values, and breaking through the restrictions brought by demonstration data.

The agent can adapt to dynamic scenes through exploration and trial-and-error mechanisms based on the experience of demonstrating trajectories. The demonstration data set used in IL and the experience samples obtained in the process of RL are coupled and used to improve the data utilization efficiency and the generalization ability of the agent.

This study aims to explore how managers exercise agency in strategic investment decisions (SIDs) by drawing on their knowledgeability of the strategic context. Specifically, the authors address the role of position–practice relations and irresistible causal forces in this conduct.

The authors examine SID-making (SIDM) practices in four case organisations operating in highly competitive markets, conducting interviews with managers at various levels and analysing company documents. Drawing on strong structuration theory, the authors show how managerial decision makers draw upon their knowledge of organisational context when exercising agency in SIDs.

The authors provide insights into how SIDM behaviour, specifically agents’ conduct, is shaped by a combination of position–practice relations and the agents’ comprehension of their organisation’s context.

The authors extend the SIDM literature by surfacing the issue of how actors’ conjuncturally-specific knowledge of external structures shapes the general dispositions they draw on in exercising agency in practice.

The authors extend the SIDM literature by surfacing the issue of how actors’ conjuncturally-specific knowledge of external structures shapes the general dispositions they draw on in exercising agency in practice. Particularly, the authors contribute to this literature by identifying irresistible causal forces and illuminating why actors might not resist in SIDM processes, despite having the potential to do so.

Every company or manufacturing system is vulnerable to breakdowns. This research aims to analyze the role of Multi-Agent Technology (MAT) in minimizing breakdown probabilities in Manufacturing Industries.

This study formulated a framework of six factors and twenty-eight variables (explored in the literature). A hybrid approach of Multi-Criteria Decision-Making Technique (MCDM) was employed in the framework to prioritize, rank and establish interrelationships between factors and variables grouped under them.

The research findings reveal that the “Manufacturing Process” is the most essential factor, while “Integration Manufacturing with Maintenance” is highly impactful on the other factors to eliminate the flaws that may cause system breakdown. The findings of this study also provide a ranking order for variables to increase the performance of factors that will assist manufacturers in reducing maintenance efforts and enhancing process efficiency.

The ranking order developed in this study may assist manufacturers in reducing maintenance efforts and enhancing process efficiency. From the manufacturer’s perspective, this research presented MAT as a key aspect in dealing with the complexity of manufacturing operations in manufacturing organizations. This research may assist industrial management with insights into how they can lower the probability of breakdown, which will decrease expenditures, boost productivity and enhance overall efficiency.

This study is an original contribution to advancing MAT’s theory and empirical applications in manufacturing organizations to decrease breakdown probability.

Individuals develop and perform and process their identities in relationships with others as well as with the environment in which they find themselves, Many of these relationships with others are characterized by fundamental inequalities. In finding their identities, the subordinate in the relationship develops an identity that typically take steps – by vocal and non-vocal gestures – to perform this particularized identity. The identification of self is not only related to the others, with eachindividual in reflective communication, but also reflections characterized by inequality. In continuing to do so, he or she will experience a certain powerlessness, indeed what Marx called alienation.

The purpose of this study is to extend sales control research to inside sales. Aside from a few notable exceptions (Conde et al., 2022) much of the sales control literature has focused on a single control mechanism rather than a sales control portfolio perspective. The authors add multiple layers to Conde et al. (2022) by capturing secondary operational data and manager interviews to access sales control theory in practice.

With operational data from a Fortune 100 financial services company and sales manager interviews, the authors present evidence that managers apply a portfolio of controls to ensure sales agents’ overall performance.

Findings support that cultural controls have a greater influence on overall performance than a focus solely on process and outcome controls. Inside sales managers can generate better results when they focus on creating an employee-centric culture rather than controlling sales agents with formal sales controls.

This study extends sales control research by examining inside sales managers’ formal and informal sales controls. Historically, inside sales had sales leaders balance a myriad of sales controls grounded in strict oversight. With a few notable exceptions, the limited inside sales control research provides the opportunity to display an inside sales manager’s need to jointly focus on operational results and sales outcomes, illustrating the importance of cultural controls compared to other sales process and outcome controls. This research considerably extends sales controls research by focusing on inside sales.

This paper aims to study the role of self-concept in consumer relationships with anthropomorphised conversational artificially intelligent (AI) agents. First, the authors investigate how the self-congruence between consumer self-concept and AI and the integration of the conversational AI agent into consumer self-concept might influence such relationships. Second, the authors examine whether these links with self-concept have implications for mental well-being.

This study conducted in-depth interviews with 20 consumers who regularly use popular conversational AI agents for functional or emotional tasks. Based on a thematic analysis and an ideal-type analysis, this study derived a taxonomy of consumer–AI relationships, with self-congruence and self–AI integration as the two axes.

The findings unveil four different relationships that consumers forge with their conversational AI agents, which differ in self-congruence and self–AI integration. Both dimensions are prominent in replacement and committed relationships, where consumers rely on conversational AI agents for companionship and emotional tasks such as personal growth or as a means for overcoming past traumas. These two relationships carry well-being risks in terms of changing expectations that consumers seek to fulfil in human-to-human relationships. Conversely, in the functional relationship, the conversational AI agents are viewed as an important part of one’s professional performance; however, consumers maintain a low sense of self-congruence and distinguish themselves from the agent, also because of the fear of losing their sense of uniqueness and autonomy. Consumers in aspiring relationships rely on their agents for companionship to remedy social exclusion and loneliness, but feel this is prevented because of the agents’ technical limitations.

Although this study provides insights into the dynamics of consumer relationships with conversational AI agents, it comes with limitations. The sample of this study included users of conversational AI agents such as Siri, Google Assistant and Replika. However, future studies should also investigate other agents, such as ChatGPT. Moreover, the self-related processes studied here could be compared across public and private contexts. There is also a need to examine such complex relationships with longitudinal studies. Moreover, future research should explore how consumers’ self-concept could be negatively affected if the support provided by AI is withdrawn. Finally, this study reveals that in some cases, consumers are changing their expectations related to human-to-human relationships based on their interactions with conversational AI agents.

This study enables practitioners to identify specific anthropomorphic cues that can support the development of different types of consumer–AI relationships and to consider their consequences across a range of well-being aspects.

This research equips marketing scholars with a novel understanding of the role of self-concept in the relationships that consumers forge with popular conversational AI agents and the associated well-being implications.

It is widely evident that trust and commitment are important pillars for strengthening the relationship between financial service firms and their customers. However, it has not been explored how the service quality, perceived cost and role of agents are important for financial service firms. To overcome this gap, this study aims to investigate the role of service quality, perceived cost and the role of agents as the commitment–trust factors in the financial insurance service (Takaful) in Malaysia, enhancing customer satisfaction.

The study follows a quantitative design in which primary data was collected using a survey instrument. The measurement instrument was adapted from the previous research, and data were collected from 264 customers of the Takaful financial service organizations in Malaysia. The data were analyzed using variance-based structural equational modeling in Smart-PLS software.

This research has revealed several useful insights that demonstrate a significant impact on service quality, perceived cost and the agents’ role in forging close relationships with their customers. Corporate image has a moderating role in relationships and has significantly impacted takaful insurance companies. The results imply that regardless of the corporate image of the financial service organizations, customers are concerned about the prices and the quality of the agents’ services.

In this study, only the predictors such as service quality, perceived costs and agents’ roles as trust–commitment factors were examined to determine customer satisfaction. Other investigations are highly recommended, such as value co-creation in takaful, takaful customer experience and takaful trust. This study offers insights to takaful insurance companies on how to keep up a positive corporate image, which will boost their trust–commitment factors and ultimately increase customer satisfaction.

By presenting commitment–trust factors and company image in an identifiable framework, the current study has expanded the discussion on takaful financial insurance services. The methodology is developed and rigorously tested to gauge customer satisfaction in takaful financial service organizations’ context.

This paper identifies the effects of different dimensions of the cuteness (i.e. baby schema cuteness and whimsical cuteness) of artificial intelligence (AI) agents on attachment to them. In addition, the current paper examines the consequences of the attachment to AI agents.

A pretest to validate the measurement scale for the attachment to AI agents and a survey study were conducted with AI agent users. The authors used structural equation modeling to analyze the data for hypothesis testing.

The baby schema and whimsical cuteness of AI agents drive consumers to develop stronger attachments to their AI agents. This is because consumers perceive cute AI agents as being more trustworthy. As a result, consumers who feel attached to their AI agents are more inclined to report higher satisfaction and commitment levels. They are also more likely to purchase products or services recommended by their AI agents and use them more frequently.

Despite the growing popularity of AI agents, there is a lack of understanding regarding which characteristics of AI agents affect consumer behavior. Therefore, this research examines how the attribute of cuteness influences consumers' attachment to AI agents and subsequently affects their satisfaction and purchase intention toward products recommended by AI agents. Our study demonstrates that the element of cuteness in AI agents plays a crucial role in shaping perceptions of benevolence trustworthiness, as well as fostering users' attachment to AI agents. Furthermore, we observe positive consumer behaviors as a result of their attachment to AI agents. The findings from this study provide valuable insights for practitioners on how to effectively utilize cuteness in AI agents.