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This study is centered on the identification of the most appropriate Technology Adoption (TA) model for investigating the adoption of Industry 4.0 technologies within pharmaceutical and related enterprises. The aim is to facilitate a smooth transition to advanced technologies while concurrently achieving environmental sustainability.

Selection of a suitable TA theory is carried out using a hybrid multi-criteria decision-making (MCDM) approach incorporating PIvot Pairwise RElative Criteria Importance Assessment (PIPRECIA) and Fuzzy Measurement of alternatives and ranking according to Compromise solution (F-MARCOS) methods. A group of three experts is formulated for the ranking of criteria and alternatives based on those criteria.

The results indicate that out of all six TA models considered unified theory of acceptance and use of technology (UTAUT) model gets the highest utility function value, followed by the technical adoption model (TAM). Further, sensitivity analysis is conducted to confirm the validity of the MCDM model employed.

Challenging times like COVID-19 pointed out the importance of technology in the pharmaceutical and healthcare sectors. TA studies in this area can help in the identification of critical factors that can assist pharmaceutical firms in their efforts to embrace emerging technologies, enhance their outputs and increase their efficiency.

The novelty of this research lies in the fact that the utilization of a TA theory prior to its implementation has not been witnessed in existing scholarly literature. The utilization of a TA theory, specifically within the pharmaceutical industry, can assist enterprises in directing their attention toward pertinent factors when contemplating the implementation of emerging technologies and achieving sustainable development.

Users often struggle to select choosing among similar online services. To help them make informed decisions, it is important to establish a service reputation measurement mechanism. User-provided feedback ratings serve as a primary source of information for this mechanism, and ensuring the credibility of user feedback is crucial for a reliable reputation measurement. Most of the previous studies use passive detection to identify false feedback without creating incentives for honest reporting. Therefore, this study aims to develop a reputation measure for online services that can provide incentives for users to report honestly.

In this paper, the authors present a method that uses a peer prediction mechanism to evaluate user credibility, which evaluates users’ credibility with their reports by applying the strictly proper scoring rule. Considering the heterogeneity among users, the authors measure user similarity, identify similar users as peers to assess credibility and calculate service reputation using an improved expectation-maximization algorithm based on user credibility.

Theoretical analysis and experimental results verify that the proposed method motivates truthful reporting, effectively identifies malicious users and achieves high service rating accuracy.

The proposed method has significant practical value in evaluating the authenticity of user feedback and promoting honest reporting.

This study aims to improve the offshore wind farm (OWF) site selection evaluation index system and establishes a decision-making model for OWF site selection. It is expected to provide helpful references for the progress of offshore wind power.

Firstly, this paper establishes an evaluation criteria system for OWF site selection, considering six criteria (wind resource, environment, economic, technical, social and risk) and related subcriteria. Then, the Criteria Importance Though Intercrieria Correlation (CRITIC) method is introduced to figure out the weights of evaluation indexes. In addition, the cumulative prospect theory and technique for order preference by similarity to an ideal solution (CPT-TOPSIS) method are employed to construct the OWF site selection decision-making model. Finally, taking the OWF site selection in China as an example, the effectiveness and robustness of the framework are verified by sensitivity analysis and comparative analysis.

This study establishes the OWF site selection evaluation system and constructs a decision-making model under the spherical fuzzy environment. A case of China is employed to verify the effectiveness and feasibility of the model.

In this paper, a new decision-making model is proposed for the first time, considering the ambiguity and uncertainty of information and the risk attitudes of decision-makers (DMs) in the decision-making process.

This article aims to systematically review the literature published in recognized journals focused on cognitive heuristic-driven biases and their effect on investment management activities and market efficiency. It also includes some of the research work on the origins and foundations of behavioral finance, and how this has grown substantially to become an established and particular subject of study in its own right. The study also aims to provide future direction to the researchers working in this field.

For doing research synthesis, a systematic literature review (SLR) approach was applied considering research studies published within the time period, i.e. 1970–2021. This study attempted to accomplish a critical review of 176 studies out of 256 studies identified, which were published in reputable journals to synthesize the existing literature in the behavioral finance domain-related explicitly to cognitive heuristic-driven biases and their effect on investment management activities and market efficiency as well as on the origins and foundations of behavioral finance.

This review reveals that investors often use cognitive heuristics to reduce the risk of losses in uncertain situations, but that leads to errors in judgment; as a result, investors make irrational decisions, which may cause the market to overreact or underreact – in both situations, the market becomes inefficient. Overall, the literature demonstrates that there is currently no consensus on the usefulness of cognitive heuristics in the context of investment management activities and market efficiency. Therefore, a lack of consensus about this topic suggests that further studies may bring relevant contributions to the literature. Based on the gaps analysis, three major categories of gaps, namely theoretical and methodological gaps, and contextual gaps, are found, where research is needed.

The skillful understanding and knowledge of the cognitive heuristic-driven biases will help the investors, financial institutions and policymakers to overcome the adverse effect of these behavioral biases in the stock market. This article provides a detailed explanation of cognitive heuristic-driven biases and their influence on investment management activities and market efficiency, which could be very useful for finance practitioners, such as an investor who plays at the stock exchange, a portfolio manager, a financial strategist/advisor in an investment firm, a financial planner, an investment banker, a trader/broker at the stock exchange or a financial analyst. But most importantly, the term also includes all those persons who manage corporate entities and are responsible for making their financial management strategies.

Currently, no recent study exists, which reviews and evaluates the empirical research on cognitive heuristic-driven biases displayed by investors. The current study is original in discussing the role of cognitive heuristic-driven biases in investment management activities and market efficiency as well as the history and foundations of behavioral finance by means of research synthesis. This paper is useful to researchers, academicians, policymakers and those working in the area of behavioral finance in understanding the role that cognitive heuristic plays in investment management activities and market efficiency.

The purpose of this study is to investigate the role of consumers’ moral preferences between moral and economic benefits and consumers’ moral and rational behaviour intentions based on moral decision-making models of previous studies.

Respondents were asked to answer a questionnaire measuring moral and economic benefits, consumers’ moral preferences and moral and rational behaviour intention after reading a stimulus describing imaginary fashion brand A’s unethical activities.

Moral and economic benefits directly and significantly affect moral and rational behaviour intention. Homo economicus evoked by an economic benefit had a negative effect on moral behaviour intention.

This study focused only on a moral benefit and an economic benefit as factors evoking consumers’ moral preferences. This study was also conducted only in a Korean context and considered a specific industry. In future research, the results of this study should be extended to design the “possibility of punishment” to encourage moral behaviour by discouraging the effect of homo economicus. The results have implications for companies such as social enterprises and charities that want to promote consumers’ moral behaviour.

This study provides evidence on why ethical consumers do not always make ethical decisions by confirming that homo economicus has a significant influence on not only rational behaviour intention but also moral behaviour intention.

The collection and use of personal medical information for mobile health (mHealth) service raise significant privacy concerns. In this context, this study aims to explore the privacy paradox and its impact from the perspective of paradox resolution.

Based on social support theory and privacy calculus theory, this study first studies the effect of social support on perceived benefits, and explores the moderating effect of perceived health status on the privacy trade-off process. Secondly, the study examines the path of “privacy concerns – disclosure intention – disclosure behavior” to verify the existence of the privacy paradox. Following this, based on rational choice theory, the rationality degree is introduced as a moderating variable to investigate both its impact on the central route and the strength of this impact on the privacy paradox.

Empirical results show that informational support and emotional support influence perceived benefits significantly. Perceived benefits significantly influence privacy concerns, and perceived health status has a significant positive moderating effect. The authors further find that there is a privacy paradox within the mHealth context, and the privacy paradox is moderated negatively by rationality degree. The findings indicate that the impact strength of the privacy paradox will decrease with increases in rationality degree.

The findings indicate that it is crucial to evaluate the privacy paradox and its impact from the perspective of paradox resolution.

This study offers a complete comprehension of the privacy paradox in mHealth and provides several valuable recommendations for enhancing both mHealth services and privacy controls.

The study focuses on drug safety regulation capture, reveals the inner mechanism and evolutionary characteristics of drug safety regulation capture and provides suggestions for effective regulation by pharmacovigilance.

The article introduces prospect theory into the game strategy analysis of drug safety events, constructs a benefit perception matrix based on psychological perception and analyzes the risk selection strategies and constraints on stable outcomes for both drug companies and drug regulatory authorities. Moreover, simulation was used to analyze the choice of results of different parameters on the game strategy.

The results found that the system does not have a stable equilibrium strategy under the role of cognitive psychology. The risk transfer coefficient, penalty cost, risk loss, regulatory benefit, regulatory success probability and risk discount coefficient directly acted in the direction of system evolution toward the system stable strategy. There is a critical effect on the behavioral strategies of drug manufacturers and drug supervisors, which exceeds a certain intensity before the behavioral strategies in repeated games tend to stabilize.

In this article, the authors constructed the perceived benefit matrix through the prospect value function to analyze the behavioral evolution game strategies of drug companies and FDA in the regulatory process, and to evaluate the evolution law of each factor.

The purpose of this paper is to evaluate the relationship between bankers’ perspectives and their pro-green banking behaviors (i.e. intentions). Specifically, how do bankers’ perspectives on environmental concerns, environmental normative structure and green technology affect their intentions toward G-banking activities?

A theoretical framework of the theory of bounded rational planned behavior (TBRPB) as its foundation was established. Using measurement scales to measure different aspects of environmental concern, environmental normative structure, green technology, attitudes, perceived behavioral control and subjective norms, a survey instrument was developed to examine the various associations implied by the model of TBRPB. Data were collected from the bankers of selected commercial banks in Bangladesh following the random sampling procedure. The data were analyzed using the partial least square structural equation modeling technique.

Findings indicate that all of the predictors appear to be robust in predicting the G-banking intention of the sampled bankers in Bangladesh. The results also show that attitudes, subjective norms and perceived behavioral control have significant mediating effects toward bankers’ bounded rational G-banking intention.

There are a few limitations in the study. First, the study considers environmental concerns as an antecedent of the attitude of bankers toward G-banking activities. Future studies can explore other variables related to environmental problems to study G-banking adoption and practices. Second, this study only considers the private conventional bankers as respondents to the survey to assess G-baking intention. In the future, other types of bankers, such as Islamic bankers and public banks’ bankers could be included in the survey to explore G-banking practices. Finally, this research has been done in a developing country-context.

In this study, environmental concerns of bankers appeared to be highly significant predictors to influence their attitudes toward bounded rational G-banking intention. Similarly, the social normative structure also appears to be a robust antecedent of subjective norms to influence bounded rational G-banking intention of respondent bankers. Finally, green technology or bakers’ personal and skill-related ability to control bounded rational G-banking intention also appeared to be a strongly significant predictor of green banking activities. All this evidence implies that respondent bankers in the sample responded positively to provide their positive intention toward G-banking activities based on their environmental concern.

Important social implication of the current study is G-banking practices can help reduce carbon emissions and other pollutants which would enrich overall environmental sustainability and ecological conditions.

Few studies are directed on G-banking perspective in Bangladesh. This research is one of the empirical studies which will certainly add values for the clients, institutions and policymakers in banking paradigm.

Explore what popular food influencers among Flemish emerging adults portray in their Instagram recipe posts in terms of (1) references to food literacy, (2) nutritional value, (3) rational and emotional appeals and (4) the relation between the nutritional value and rational/emotional appeals.

A content and nutritional analysis of Instagram recipe posts from seven food influencers (N = 166).

Findings reveal that food influencers rarely embed references to food literacy in their recipe posts, especially regarding meal planning, food selection, meal consumption and evaluating food-related information. Only in 28.9% of the posts information was given on how to prepare a recipe. Second, 220 recipes were included in the 166 recipe posts, of which the majority (65%) were main course meals that met at least six of the 11 nutrient criteria for a healthy main meal (67.2%). Finally, food influencers promote their recipe posts as positive narratives, focusing on the tastiness (66%) and convenience (40.9%) of meals.

This is the first study to evaluate what food influencers post nutritionally in their Instagram recipes, as well as how they promote these recipes. Health promotors should note the influential role of food influencers and seek ways to collaborate to provide information on how food literacy cues can be embedded in influencers' communications and provide insights into how influencers' recipes can be optimised.

The purpose of this study is to solve two unique but difficult partial differential equations: the foam drainage equation and the nonlinear time-fractional fisher’s equation. Through our methods, we aim to provide accurate solutions and gain a deeper understanding of the intricate behaviors exhibited by these systems.

In this study, we use a dual technique that combines the Aboodh residual power series method and the Aboodh transform iteration method, both of which are combined with the Caputo operator.

We develop exact and efficient solutions by merging these unique methodologies. Our results, presented through illustrative figures and data, demonstrate the efficacy and versatility of the Aboodh methods in tackling such complex mathematical models.

Owing to their fractional derivatives and nonlinear behavior, these equations are crucial in modeling complex processes and confront analytical complications in various scientific and engineering contexts.