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During 2020, governments around the world introduced contact-tracing apps to fight the COVID-19 pandemic. In order for contact-tracing apps to be efficient tools in combatting pandemics, a significant proportion of the population has to install it. However, in many countries, the success of apps introduced during the COVID-19 pandemic has been limited due to lack of public support. This paper aims to better understand why consumers seem unwilling to install and use a contact-tracing app.

In this study, the authors test a number of determinants hypothesized to influence acceptance of contact-tracing apps based on the theory of privacy calculus (Dinev and Hart, 2006). Both perceived privacy concerns, as well as perceived hedonic, utilitarian and pro-social benefits are included. The hypotheses are tested through SEM analysis on a representative sample of 1,007 Swedish citizens.

The results indicate significant privacy concerns with using contact-tracing apps. However, this is to some extent offset by perceived hedonic and pro-social positive consequences of using the app. This study further shows that a general positive attitude towards innovation increases acceptance of the app.

The study contributes to research on consumer privacy, both in general in its application of the calculus model but also specifically in the context of contact-tracing apps. Moreover, as the results highlight which aspects that are important for consumers to accept and install an app of this kind, they also represent an important contribution to policymakers in countries around the world.

The purpose of this paper is to explore the antecedents of self-disclosure intention on mobile social applications. This study integrates privacy calculus model and elaboration likelihood theory to reconcile the rational and heuristic views of privacy decision making.

Using a “random dialing” sampling method, an empirical survey with 913 respondents was conducted. A series of regression models were employed to test the proposed relationships. Robust checks with sub-group analysis were conducted.

Self-disclosure intention develops along a dual route including the central route and the peripheral route. When the central route predominates, social media users form their attitudes toward self-disclosure based on a rational calculus of the privacy concern and perceived rewards. When the peripheral route predominates, users perform a more heuristic evaluation of relevant informational cues (information about privacy harms, the extent of information asymmetry between users and operators) and contextual cues (flow experience, privacy disclosure of friends). Peripheral cues moderate the relationships between central cues and self-disclosure intention.

This paper extends the Elaboration Likelihood Model by investigating the interaction between the central route and peripheral route. The results provide alternative explanations on the renowned “privacy paradox” phenomenon.

The purpose of this paper is to allocate marketing budgets in complex environments, where data are scarce and management judgment is available. In this research, marketing budgets are allocated, to maximize customer equity as a long-term profitability measure.

The researchers provide a model for allocation of marketing budgets based on both decision calculus and econometric models and combine it with the concept of Markov chain model to cope with data scarcity. Dynamic programming is used to find the optimal solution.

The authors examine the model in telecommunication industry. Applicability of the model is supported by an illustrative example. To allocate marketing budgets, researchers consider three strategies for each period: do nothing, retention-focused strategy and acquisition-focused strategy. The results show the applicability and effectiveness of the model to find the best strategy.

As the suggested approach is based on management judgment, it is useful in situations, as the authors have experts or experienced managers to achieve reliable data. In situations which the authors do not have access to experienced managers, the results may be unreliable.

The suggested approach is useful in situations of data scarcity, where experienced managers are accessible. The researchers have focused on telecommunication industry cases; however, the model is useful in other industries like the insurance industry.

The main contribution of the research lies in the suggestion of a new approach to allocate marketing budgets in data scarcity situations in multi-period planning horizons. The researchers use both decision calculus and econometric tools to find the transition matrices of marketing plans.

This paper aims to analyze soil electrical properties based on fractional calculus theory due to the fact that the frequency dependence of soil electrical parameters at high frequencies exhibits a fractional effect. In addition, for the fractional-order formulation, this paper aims to provide a more accurate numerical algorithm for solving the fractional differential equations.

This paper analyzes the frequency-dependence of soil electrical properties based on fractional calculus theory. A collocation method based on the Puiseux series is proposed to solve fractional differential equations.

The algorithm proposed in this paper can be used to solve fractional differential equations of arbitrary order, especially for 0.5th-order equations, obtaining accurate numerical solutions. Calculating the impact response of the grounding electrode based on the fractional calculus theory can obtain a more accurate result.

This paper proposes an algorithm for solving fractional differential equations of arbitrary order, especially for 0.5th-order equations. Using fractional calculus theory to analyze the frequency-dependent effect of soil electrical properties, provides a new idea for ground-related transient calculation.

Considering that users’ information privacy concerns may affect the development of e-commerce, the purpose of this paper is to explore what drives internet users’ willingness to provide personal information; further, the paper examines how extrinsic rewards moderate the relationship between users’ information privacy concerns and willingness to provide personal information.

Data collected from 345 valid internet users in the context of electronic commerce were analyzed using the partial least squares approach.

The result showed that agreeableness, risk-taking propensity and experience of privacy invasion were three main antecedents of information privacy concerns among the seven individual factors. Additionally, information privacy concerns did not significantly affect users’ willingness to provide personal information in the privacy calculation mechanism; however, extrinsic rewards directly affected users’ disclosure intention. The authors found that extrinsic rewards had not moderated the relationship between users’ information privacy concerns and their willingness to provide personal information.

This study is an exploratory effort to develop and validate a model for explaining why internet users were willing to provide personal information. The results of this study are helpful to researchers in developing theories of information privacy concerns and to practitioners in promoting internet users’ willingness to provide personal information in an e-commerce context.

The COVID-19 pandemic represents a unique challenge for public health worldwide. In this context, smartphone-based tracking apps play an important role in controlling transmission. However, privacy concerns may compromise the population’s willingness to adopt this mobile health (mHealth) technology. Based on the privacy calculus theory, this study aims to examine what factors drive or hinder adoption and disclosure, considering the moderating role of age and health status.

A cross-sectional survey was conducted in a European country hit by the pandemic that has recently launched a COVID-19 contact-tracing app. Data from 504 potential users was analyzed through partial least squares structural equation modeling.

Results indicate that perceived benefits and privacy concerns impact adoption and disclosure and confirm the existence of a privacy paradox. However, for young and healthy users, only benefits have a significant effect. Moreover, older people value more personal than societal benefits while for respondents with a chronical disease privacy concerns outweigh personal benefits.

The study contributes to consumer privacy research and to the mHealth literature, where privacy issues have been rarely explored, particularly regarding COVID-19 contact-tracing apps. The study re-examines the privacy calculus by incorporating societal benefits and moving from a traditional “self-focus” approach to an “other-focus” perspective. This study further adds to prior research by examining the moderating role of age and health condition, two COVID-19 risk factors. This study thus offers critical insights for governments and health organizations aiming to use these tools to reduce COVID-19 transmission rates.

The purpose of this article is to show that, within a process perspective, calculus is not only compliant with trust but also that trust forms are integral to its dynamics. Having demonstrated the theoretical bases of compatibility between reputation, economic interest and trust, and the necessary inclusion of a social context in business-to-business (B2B) exchange, this paper proposes a conceptual framework that will enable us to understand a multi-form concept of trust.

The approach to the topic is one of theoretical analysis and conceptual development.

This proposal indicates that the presence of calculus in the earliest stages of exchange relationships gives way to other forms of trust that are more cognitive and affective in nature. The elucidation of the evolutionary nature of trust shows that calculus and trust theory are complementary and provide, respectively, insight for the whole process.

The presented research by incorporating forms and time dimension adds theoretical insights and produces an incremental step toward better understanding of trust dynamics in industrial and business markets. The main challenge to the proposed model will be the empirical test.

This conceptualization should help managers understand trust creation better, and provide them with valuable information for understanding the evolution of relationships with suppliers. Segmentation based on relational phases requires tailoring each form of trust strategy, and, hence, accurate identification of a relationship phase could help categorize and subcategorize customers regarding calculative, cognitive or emotional dominant forms of trust.

The paper contributes to the discussion on how integrative approaches (calculative and non-calculative) improve our understanding of buyer–supplier relationships and promotes the emergence of a coherent vision of trust evolution.

Academic and industrial researches on nanoscale flows and heat transfers are an area of increasing global interest, where fascinating phenomena are always observed, e.g. admirable water or air permeation and remarkable thermal conductivity. The purpose of this paper is to reveal the phenomena by the fractional calculus.

This paper begins with the continuum assumption in conventional theories, and then the fractional Gauss’ divergence theorems are used to derive fractional differential equations in fractal media. Fractional derivatives are introduced heuristically by the variational iteration method, and fractal derivatives are explained geometrically. Some effective analytical approaches to fractional differential equations, e.g. the variational iteration method, the homotopy perturbation method and the fractional complex transform, are outlined and the main solution processes are given.

Heat conduction in silk cocoon and ground water flow are modeled by the local fractional calculus, the solutions can explain well experimental observations.

Particular attention is paid throughout the paper to giving an intuitive grasp for fractional calculus. Most cited references are within last five years, catching the most frontier of the research. Some ideas on this review paper are first appeared.

Does the classical liberal emphasis on freedom of association provide an intellectual cover for bigotry? We formulate this question in economic terms using James Buchanan’s economic approach to ethics, according to which moral values can be understood as preferences about other people’s behaviors. We discuss two possible market failures associated with freedom of association: inter-group externalities and Schelling-type emergent segregation. We show that the classical liberal position about freedom of association, as elaborated in Buchanan and Tullock’s Calculus of Consent, is fully equipped to deal with the first one, but not with the second. The progressive view that some preferences are so offensive that they should be dismissed rather than engaged or negotiated with can be reframed as an attempt to solve the emergent segregation problem, but it is vulnerable to political economy problems of its own, in particular to an inherent tendency to over-expand the meaning of “bigotry.”