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This paper aims to propose a solution for dissolving the “privacy paradox” in social networks, and explore the feasibility of adopting a synergistic mechanism of “deep-learning algorithms” and “differential privacy algorithms” to dissolve this issue.

To validate our viewpoint, this study constructs a game model with two algorithms as the core strategies.

The “deep-learning algorithms” offer a “profit guarantee” to both network users and operators. On the other hand, the “differential privacy algorithms” provide a “security guarantee” to both network users and operators. By combining these two approaches, the synergistic mechanism achieves a balance between “privacy security” and “data value”.

The findings of this paper suggest that algorithm practitioners should accelerate the innovation of algorithmic mechanisms, network operators should take responsibility for users’ privacy protection, and users should develop a correct understanding of privacy. This will provide a feasible approach to achieve the balance between “privacy security” and “data value”.

These findings offer some insights into users’ privacy protection and personal data sharing.

The purpose of the study is to investigate and analyze the dynamics of the government-enterprise grain joint storage mechanism, particularly, focusing on profit-driven speculative behaviors exhibited by enterprises within this context. The study aims to understand the various factors influencing the behavior of stakeholders involved in grain storage, including government storage departments, agent storage enterprises and quality inspection agencies.

The study employs a tripartite evolutionary game model to investigate profit-driven behaviors in government-enterprise grain joint storage. It analyzes strategies of government departments, storage enterprises and quality inspection agencies, considering factors like supervision costs and speculative risks. Simulation analysis examines tripartite payoffs, initial probabilities and the impact of digital governance levels to enhance emergency grain storage effectiveness.

The study finds that leveraging digital governance tools in government-enterprise grain joint storage mechanisms can mitigate risks, enhance efficiency and ensure the security of grain storage. It highlights the significant impact of supervision costs, speculative risks and digital supervision levels on stakeholder strategies, offering guidance to improve the effectiveness of emergency grain storage systems.

The originality of this study lies in its integration of digital governance tools into the analysis of the government-enterprise grain joint storage mechanism, addressing profit-driven speculative behaviors. Through a tripartite evolutionary game model, it explores stakeholder strategies, emphasizing the impact of digital supervision levels on outcomes and offering insights crucial for enhancing emergency grain storage effectiveness.

With the advent of transformational and digital technologies, companies are striving to integrate digital transformation strategy (DTS) into their business models to stay competitive. However, in many cases, the implementation of DTS fails because managers lack knowledge about the opportunities and challenges associated with this strategy.

First, a bibliometric analysis was conducted with data related to DTS from the Scopus database for the period 2011–2023 to identify scientific trends in the field of DTS. Subsequently, 2,363 documents were collected and analyzed using Vosviewer software. Finally, the opportunities and challenges within the field of DTS were identified as one of the latest trends through a meta-synthesis method.

The findings of this research highlight the current scientific trends in the field of DTS. Also, the challenges of implementing the DTS are lack of instructions and rules, financial weakness, lack of alignment, inappropriate organizational structure, lack of digital organizational culture, challenges related to employees, lack of a digital leader and cyber threats. In addition, DTS implementation opportunities can be divided into three groups: improving customer experience, improving business processes and strategic renewal and creation of new business models.

The present research introduces two key innovations. The first is to offer a summary of prior research in the field of DTS. The second is identifying the opportunities and challenges associated with adopting this strategy, which is one of the latest trends.

Studies have shown that within-domain compensatory consumption can successfully repair the damaged self, but other research indicates that it can undermine self-control because such consumption causes self-threat rumination that impairs self-regulatory resources. This paper aims to identify a boundary condition that reconciles and explains these contradictory findings.

The authors conducted three experiments to show that within-domain compensatory consumption undermines self-control, but only in some situations. They test a boundary condition (i.e. type of connections between within-domain products and self-threat domain) for the effects of such consumption on self-threat rumination and self-control.

This paper demonstrates that within-domain (but not across-domain) compensatory consumption induces rumination and reduces subsequent self-control, but only when the product’s connection to the self-threat domain is made explicit through brand names or slogans. When the connection is merely implicit, rumination and self-control deficits are not observed.

Consumers may seek certain products to bolster threatened aspects of their self-concept. Marketing tactics that explicitly highlight connections to such self-aspects can lower a consumer’s self-control resulting in stronger purchase intent, while at the same time hindering the possibility of self-concept repair. Managers need to be wary of ethical concerns.

This research qualifies the existing findings by presenting “type of product connection” as a key determinant of within-domain compensatory consumption’s impact on self-control. Researchers need to be conscious of the type of products (explicitly vs implicitly connected to the self-threat domain) they use in compensatory consumption studies, because this may influence their findings.

Driven by the evidence from the literature on the significance of mobile (m-)payment in economic growth and productivity and at the same time the relative dismal adoption of this service, the purpose of present paper is to elucidate the merchants’ m-payment adoption from the perspective of trust, drawing upon the game theory framework, in the Malaysian context.

An online survey consisting of 302 respondents was carried out to investigate the impact of trust and opportunism on merchants’ perceived trustworthiness using a two-staged structural equation modeling–neural network approach to determine the significance and relative importance of variables. This study also applies a game-theoretic approach to analyze the impact of trust on the relationship between merchants and m-payment service providers.

The results indicate a positive and statistically significant relationship between merchant trust, merchant opportunism and perceived trustworthiness, and a statistically significant negative relationship was found between m-payment provider opportunism and perceived trustworthiness. The findings from the prisoner’s dilemma two-player model indicate that the scenarios of mutual trust and mutual opportunism as paradigmatic of cooperation and defection produce the best and worse outcomes, respectively. An intriguing result was the positive impact of merchant opportunism on perceived trustworthiness, which indicates a very calculative orientation of merchants in m-payment contracting.

To the best of the authors’ knowledge, this is among the first attempts to propose a game theory approach to the interaction between merchants and m-payment providers under the framework of trust and opportunism. A game theory study in the context of m-payment adoption can contribute to the theoretical literature by providing insights into the decision-making processes of merchants. By incorporating trust and opportunism into the game theory model, we can gain a better understanding of how they affect the decision-making process and overall adoption rates. The conclusions and implications provide useful insights for managers of both m-payment platforms and merchants in this relational exchange. The results of the present research can provide insights into the factors that influence merchant decisions and guide them toward suitable partnerships for successful adoption and can guide authorities for policy interventions and supporting adoption efforts.

In order to solve the problem of inaccurate calculation of index weights, subjectivity and uncertainty of index assessment in the risk assessment process, this study aims to propose a scientific and reasonable centralized traffic control (CTC) system risk assessment method.

First, system-theoretic process analysis (STPA) is used to conduct risk analysis on the CTC system and constructs risk assessment indexes based on this analysis. Then, to enhance the accuracy of weight calculation, the fuzzy analytical hierarchy process (FAHP), fuzzy decision-making trial and evaluation laboratory (FDEMATEL) and entropy weight method are employed to calculate the subjective weight, relative weight and objective weight of each index. These three types of weights are combined using game theory to obtain the combined weight for each index. To reduce subjectivity and uncertainty in the assessment process, the backward cloud generator method is utilized to obtain the numerical character (NC) of the cloud model for each index. The NCs of the indexes are then weighted to derive the comprehensive cloud for risk assessment of the CTC system. This cloud model is used to obtain the CTC system's comprehensive risk assessment. The model's similarity measurement method gauges the likeness between the comprehensive risk assessment cloud and the risk standard cloud. Finally, this process yields the risk assessment results for the CTC system.

The cloud model can handle the subjectivity and fuzziness in the risk assessment process well. The cloud model-based risk assessment method was applied to the CTC system risk assessment of a railway group and achieved good results.

This study provides a cloud model-based method for risk assessment of CTC systems, which accurately calculates the weight of risk indexes and uses cloud models to reduce uncertainty and subjectivity in the assessment, achieving effective risk assessment of CTC systems. It can provide a reference and theoretical basis for risk management of the CTC system.

The health and survival of massively multiplayer online games (MMOGs) are of paramount concern to stakeholders. It is essential to understand the usage behaviors of exploitative and exploratory strategies. By combining the typical user experience with psychological mechanisms in MMOGs, this study is devoted to clarifying how technology affordance and digital perfectionistic intention influence reinforcement and variety-seeking orientations of MMOGs use.

This study adopted a sequential triangulation mixed-methods design to explore how diverse usage behaviors of reinforced and varied use in MMOGs are formed. After proposing the theoretical framework from MMOGs affordance, perfectionistic intentions, and diverse use, empirical evidence was initially collected from representative samples through a survey. Qualitative interviews from players in MMOGs and game industry practitioners are conducted to confirm the results, supplement understanding, and gather insights from diverse backgrounds. The quantitative and qualitative inferences are discussed to validate the research focus.

Findings from various perspectives suggest that perfectionistic intentions are critical antecedents of different usage behaviors influenced by affordances provided in MMOGs. Goal-driven affordance with reward and competition, interaction affordance, and identity affordance are key MMOGs affordances and could affect perfectionistic intentions differently. People with different perfectionistic intentions, which are the psychological outcome of MMOGs affordances, possess diverse usage behaviors.

This study is the first to consider diverse usage behaviors in virtual worlds such as MMOGs by combining lenses of perfectionistic intentions and technology affordance. Findings from mixed-methods analysis significantly enrich the research on online game usage behavior, offering valuable theoretical and practical implications for studying usage behaviors within the virtual world.

The elderly service industry is emerging in China. The Chinese government introduced a series of policies to guide elderly service enterprises to improve their service quality. This study explores novel differentiated subsidy strategies that not only promote the improvement of service quality in elderly service enterprises but also alleviate the financial burden on the government.

Evolutionary game and Hotelling models are employed to investigate this issue. First, a Hotelling model that considers consumer word-of-mouth preferences is established. Subsequently, an evolutionary game model between local governments and enterprises is constructed, and the evolutionary stable strategies of both parties are analyzed. Finally, simulation experiments are conducted.

The findings indicate that local government decisions have a significant influence on the behavior of elderly service enterprises. Increasing the proportion of local governments opting for subsidy strategies helps incentivize elderly service enterprises to improve their service quality. Furthermore, providing differentiated subsidies based on the preferences of the customer base of elderly service enterprises can encourage service quality improvement while reducing government expenditure. The findings offer valuable insights into the design of government subsidy policies.

Compared with previous research, this study examines the role of consumer preferences in a differentiated subsidy policy. This enriches the authors’ understanding of the field by incorporating neglected aspects of consumer preferences in the context of the emerging elderly service industry.

This paper aims to offer a new history of management by tracing a religious dimension of scientific management. The thesis is that the good was foundational for bringing scientific management to success in Taylor’s native Quaker Philadelphia in the 1880s. The paper’s main contribution is to contrast the philosophical origins of Taylor’s ideas in scientific management to his native Quaker roots, and how Taylor, over time, into the 1910s, wrestled with this issue.

The paper is situated in historical interpretivism and subjectivism, leaning on contextual and narrative research on religious morality.

Quaker morality prevented managerial opportunism at Taylor’s Midvale Steel in the 1880s. Conversely, by the 1900s and 1910s, interest conflicts between workers and managers escalated when scientific management moved out of its traditional cultural contexts of Quaker Philadelphia and spread across the USA. The historical implication is, already for Taylor’s time, that scientific management never was the “one-best way” of management.

Future research needs to deepen and broaden research on scientific management when tracing the significance of religion and culture in management thought.

The paper has implications for modern studies of business morality by uncovering the practical relevance of religious business ethics at the outset of management studies.

The historic emergence of scientific management points to a theory of institutional evolution and economic growth, when religiously grounded governance of the firm deinstitutionalized, and institutional economic governance, with different but superior economic advantages, progressed by the 1900s.

The paper suggests an alternative version of the intellectual heritage of management studies by tracing the legacy of Taylor’s Quakerism and how religious and cultural ideas contributed to the formation of science in management.

The purpose of this paper is to study the effects of sports sponsorship on brand equity using two managerially related outcomes: price premium and market share.

This study uses a best–worst discrete choice experiment (BWDCE) and compares the outcome with that of the purchase intention scale, an established probabilistic measure of purchase intention. The total sample consists of 409 fans of three soccer teams sponsored by three different competing brands: Nike, Adidas and Puma.

With sports sponsorship, fans were willing to pay more for the sponsor’s product, with the sponsoring brand obtaining the highest market share. Prominent brands generally performed better than less prominent brands. The best–worst scaling method was also 35% more accurate in predicting brand choice than a purchase intention scale.

Future research could use the same method to study other types of sponsors, such as title sponsors or other product categories.

Sponsorship managers can use this methodology to assess the return on investment in sponsorship engagement.

Prior sponsorship studies on brand equity tend to ignore market share or fans’ willingness to pay a price premium for a sponsor’s goods and services. However, these two measures are crucial in assessing the effectiveness of sponsorship. This study demonstrates how to conduct such an assessment using the BWDCE method. It provides a clearer picture of sponsorship in terms of its economic value, which is more managerially useful.